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| -rw-r--r-- | scraper/reports/doi_domains.html | 2 | ||||
| -rw-r--r-- | scraper/reports/doi_institutions.html | 2 | ||||
| -rw-r--r-- | scraper/reports/doi_institutions_geocoded.csv | 15 | ||||
| -rw-r--r-- | scraper/reports/doi_institutions_unknown.csv | 15 | ||||
| -rw-r--r-- | scraper/reports/doi_institutions_unknown.html | 2 | ||||
| -rw-r--r-- | scraper/reports/pdf_unknown_bigrams.html | 2 | ||||
| -rw-r--r-- | scraper/reports/pdf_unknown_terms.html | 2 | ||||
| -rw-r--r-- | scraper/reports/pdf_unknown_trigram.html | 2 | ||||
| -rw-r--r-- | scraper/reports/report_coverage.html | 2 | ||||
| -rw-r--r-- | scraper/reports/report_index.html | 2 | ||||
| -rw-r--r-- | scraper/reports/stats/empty_papers.csv | 1435 | ||||
| -rw-r--r-- | scraper/reports/stats/geocoded_papers.csv | 8218 | ||||
| -rw-r--r-- | scraper/reports/stats/no_separator_papers.csv | 930 | ||||
| -rw-r--r-- | scraper/reports/stats/unknown_papers.csv | 43498 |
14 files changed, 54049 insertions, 78 deletions
diff --git a/scraper/reports/doi_domains.html b/scraper/reports/doi_domains.html index 48cd31ea..957060d7 100644 --- a/scraper/reports/doi_domains.html +++ b/scraper/reports/doi_domains.html @@ -1 +1 @@ -<!doctype html><html><head><meta charset='utf-8'><title>DOI Domains</title><link rel='stylesheet' href='reports.css'></head><body><h2>DOI Domains</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>ieeexplore.ieee.org</td><td>1846</td></tr><tr><td>link.springer.com</td><td>388</td></tr><tr><td>dl.acm.org</td><td>259</td></tr><tr><td>www.sciencedirect.com</td><td>193</td></tr><tr><td>www.computer.org</td><td>193</td></tr><tr><td>www.worldscientific.com</td><td>18</td></tr><tr><td>arxiv.org</td><td>15</td></tr><tr><td>www.ncbi.nlm.nih.gov</td><td>14</td></tr><tr><td>www.crossref.org</td><td>11</td></tr><tr><td>www.spiedigitallibrary.org</td><td>9</td></tr><tr><td>onlinelibrary.wiley.com</td><td>7</td></tr><tr><td>www.nature.com</td><td>6</td></tr><tr><td>www.mitpressjournals.org</td><td>5</td></tr><tr><td>mr.crossref.org</td><td>5</td></tr><tr><td>jivp-eurasipjournals.springeropen.com</td><td>4</td></tr><tr><td>www.tandfonline.com</td><td>3</td></tr><tr><td>www.inderscience.com</td><td>2</td></tr><tr><td>www.hindawi.com</td><td>2</td></tr><tr><td>www.scitepress.org</td><td>2</td></tr><tr><td>epubs.siam.org</td><td>1</td></tr><tr><td>www.jstage.jst.go.jp</td><td>1</td></tr><tr><td>annals-csis.org</td><td>1</td></tr><tr><td>ora.ox.ac.uk</td><td>1</td></tr><tr><td>www.emeraldinsight.com</td><td>1</td></tr><tr><td>spiral.imperial.ac.uk:8443</td><td>1</td></tr><tr><td>autosoftjournal.net</td><td>1</td></tr><tr><td>www.liebertpub.com</td><td>1</td></tr></table></body></html>
\ No newline at end of file +<!doctype html><html><head><meta charset='utf-8'><title>DOI Domains</title><link rel='stylesheet' href='reports.css'></head><body><h2>DOI Domains</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>ieeexplore.ieee.org</td><td>1846</td></tr><tr><td>link.springer.com</td><td>388</td></tr><tr><td>dl.acm.org</td><td>259</td></tr><tr><td>www.computer.org</td><td>193</td></tr><tr><td>www.sciencedirect.com</td><td>139</td></tr><tr><td>linkinghub.elsevier.com</td><td>54</td></tr><tr><td>www.worldscientific.com</td><td>18</td></tr><tr><td>arxiv.org</td><td>15</td></tr><tr><td>www.ncbi.nlm.nih.gov</td><td>14</td></tr><tr><td>www.crossref.org</td><td>11</td></tr><tr><td>www.spiedigitallibrary.org</td><td>9</td></tr><tr><td>onlinelibrary.wiley.com</td><td>7</td></tr><tr><td>www.nature.com</td><td>6</td></tr><tr><td>www.mitpressjournals.org</td><td>5</td></tr><tr><td>mr.crossref.org</td><td>5</td></tr><tr><td>jivp-eurasipjournals.springeropen.com</td><td>4</td></tr><tr><td>www.tandfonline.com</td><td>3</td></tr><tr><td>www.inderscience.com</td><td>2</td></tr><tr><td>www.hindawi.com</td><td>2</td></tr><tr><td>www.scitepress.org</td><td>2</td></tr><tr><td>epubs.siam.org</td><td>1</td></tr><tr><td>www.jstage.jst.go.jp</td><td>1</td></tr><tr><td>annals-csis.org</td><td>1</td></tr><tr><td>ora.ox.ac.uk</td><td>1</td></tr><tr><td>www.emeraldinsight.com</td><td>1</td></tr><tr><td>spiral.imperial.ac.uk:8443</td><td>1</td></tr><tr><td>autosoftjournal.net</td><td>1</td></tr><tr><td>www.liebertpub.com</td><td>1</td></tr></table></body></html>
\ No newline at end of file diff --git a/scraper/reports/doi_institutions.html b/scraper/reports/doi_institutions.html index 25ebfea6..8846cd56 100644 --- a/scraper/reports/doi_institutions.html +++ b/scraper/reports/doi_institutions.html @@ -1 +1 @@ -<!doctype html><html><head><meta charset='utf-8'><title>Institutions from IEEE</title><link rel='stylesheet' href='reports.css'></head><body><h2>Institutions from IEEE</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore</b></td><td>37</td></tr><tr><td><b>Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece</b></td><td>29</td></tr><tr><td><b>National Taiwan University, Taipei, Taiwan Roc</b></td><td>26</td></tr><tr><td><b>Department of Electrical and Computer Engineering, National University of Singapore, Singapore</b></td><td>21</td></tr><tr><td><b>Fudan University, Shanghai, China</b></td><td>21</td></tr><tr><td><b>National University of Singapore, Singapore, Singapore</b></td><td>20</td></tr><tr><td><b>Universität Hamburg, Hamburg, Germany</b></td><td>19</td></tr><tr><td><b>School of Computer Engineering, Nanyang Technological University, Singapore</b></td><td>19</td></tr><tr><td><b>School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China</b></td><td>18</td></tr><tr><td><b>South China University of Technology, Guangzhou, China</b></td><td>16</td></tr><tr><td><b>Department of Automation, Tsinghua University, Beijing, China</b></td><td>16</td></tr><tr><td><b>School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>15</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b></td><td>14</td></tr><tr><td><b>College of Computer Science and Technology, Zhejiang University, Hangzhou, China</b></td><td>14</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>14</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, China</b></td><td>13</td></tr><tr><td><b>School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China</b></td><td>12</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>12</td></tr><tr><td><b>Université de Lyon, CNRS, INSA-Lyon, LIRIS, UMR5205, F-69621, France</b></td><td>12</td></tr><tr><td><b>Zhejiang University, Hangzhou, China</b></td><td>12</td></tr><tr><td><b>School of Computer Science and Technology, Tianjin University, Tianjin, China</b></td><td>12</td></tr><tr><td><b>College of Computer Science, Sichuan University, Chengdu, China</b></td><td>12</td></tr><tr><td><b>College of Computer Science, Zhejiang University, Hangzhou, China</b></td><td>12</td></tr><tr><td><b>Department of Information Engineering and Computer Science, University of Trento, Trento, Italy</b></td><td>11</td></tr><tr><td><b>National University of Singapore, Singapore</b></td><td>11</td></tr><tr><td><b>Harbin Institute of Technology, Harbin, China</b></td><td>11</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea</b></td><td>11</td></tr><tr><td><b>State Key Laboratory of Management and Control of Complex Systems, CASIA, Beijing, China</b></td><td>10</td></tr><tr><td><b>Shanghai Jiao Tong University</b></td><td>10</td></tr><tr><td><b>Stanford University</b></td><td>10</td></tr><tr><td><b>School of Computing, National University of Singapore, Singapore</b></td><td>10</td></tr><tr><td><b>Northeastern University, Boston, MA, USA</b></td><td>10</td></tr><tr><td><b>University of Maryland, College Park</b></td><td>10</td></tr><tr><td><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore</b></td><td>10</td></tr><tr><td><b>Peking University, Beijing, China</b></td><td>10</td></tr><tr><td><b>Department of Computer Engineering, Kyung Hee University, South Korea</b></td><td>9</td></tr><tr><td><b>Dept. of Computer Science and Information Engineering, National Central University, Jhongli, Taiwan</b></td><td>9</td></tr><tr><td><b>Noblis, Falls Church, VA, U.S.A.</b></td><td>9</td></tr><tr><td><b>School of Electronic Information Engineering, Tianjin University, Tianjin, China</b></td><td>9</td></tr><tr><td><b>Shanghai Jiao Tong University, Shanghai, China</b></td><td>9</td></tr><tr><td><b>Beihang University, Beijing, China</b></td><td>9</td></tr><tr><td><b>National University of Ireland Galway, Galway, Ireland</b></td><td>9</td></tr><tr><td><b>Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China</b></td><td>9</td></tr><tr><td><b>School of Electrical and Electronic Engineering, College of Engineering, Yonsei University, Seoul, South Korea</b></td><td>9</td></tr><tr><td><b>Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan</b></td><td>9</td></tr><tr><td><b>Singapore Management University, Singapore, Singapore</b></td><td>8</td></tr><tr><td><b>P.G. Demidov Yaroslavl State University, Yaroslavl, Russia</b></td><td>8</td></tr><tr><td><b>Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Bratislava, Bratislava, Slovakia</b></td><td>8</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Center for Research on Intelligent Perception and Computing, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>8</td></tr><tr><td><b>Department of Electronic and Information Engineering, The Hong Kong Polytechnic University</b></td><td>8</td></tr><tr><td><b>CAS Center for Excellence in Brain Science and Intelligence Technology; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China</b></td><td>8</td></tr><tr><td><b>Institute of Computer Science and Technology, Peking University, Beijing, P.R. China, 100871</b></td><td>8</td></tr><tr><td><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>8</td></tr><tr><td><b>Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China</b></td><td>8</td></tr><tr><td><b>Tsinghua University, Beijing, China</b></td><td>8</td></tr><tr><td><b>State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China</b></td><td>8</td></tr><tr><td><b>University of Chinese Academy of Sciences, Beijing, China</b></td><td>8</td></tr><tr><td><b>Arizona State University, Tempe, AZ, USA</b></td><td>8</td></tr><tr><td><b>Department of Computing, Imperial College London, London, U.K.</b></td><td>8</td></tr><tr><td><b>Samsung R&D Institute, China</b></td><td>8</td></tr><tr><td><b>University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>8</td></tr><tr><td><b>Department of Computer Science and Engineering, Shanghai Jiao Tong University, China</b></td><td>8</td></tr><tr><td><b>IIIT-Delhi, India</b></td><td>7</td></tr><tr><td><b>University of Texas at Arlington, Arlington, TX, USA</b></td><td>7</td></tr><tr><td><b>National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, China</b></td><td>7</td></tr><tr><td><b>Huazhong University of Science and Technology, Wuhan, China</b></td><td>7</td></tr><tr><td><b>Bio-Computing Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China</b></td><td>7</td></tr><tr><td><b>Stony Brook University, Stony Brook University, NY 11794, USA</b></td><td>7</td></tr><tr><td><b>CyLab Biometrics Center and the Department of Electrical and Computer Engineering (ECE), Carnegie Mellon University, Pittsburgh, USA</b></td><td>7</td></tr><tr><td><b>School of Electronic and Information Engineering, Beihang University, Beijing, China</b></td><td>7</td></tr><tr><td><b>Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia</b></td><td>7</td></tr><tr><td><b>State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China</b></td><td>7</td></tr><tr><td><b>School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>7</td></tr><tr><td><b>Department of Computer Science, Jiangnan University, No. 1800 LiHu Avenue, WuXi, China</b></td><td>7</td></tr><tr><td><b>College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China</b></td><td>7</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences, China</b></td><td>7</td></tr><tr><td><b>School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China</b></td><td>7</td></tr><tr><td><b>Ulm University, Ulm, Germany</b></td><td>7</td></tr><tr><td><b>Center for Automation Research, UMIACS, University of Maryland, College Park, 20740, United States of America</b></td><td>7</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, Beijing, 100876, China</b></td><td>7</td></tr><tr><td><b>Department of Electronic Engineering, Tsinghua University, Beijing, China</b></td><td>7</td></tr><tr><td><b>Visual Computing Group, Microsoft Research, Beijing, China</b></td><td>7</td></tr><tr><td><b>School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea</b></td><td>7</td></tr><tr><td><b>Samsung Advanced Institute of Technology, Korea</b></td><td>7</td></tr><tr><td><b>Indraprastha Institute of Information Technology Delhi, Delhi, India</b></td><td>7</td></tr><tr><td><b>Southeast University, China</b></td><td>6</td></tr><tr><td><b>Department of Electrical Engineering, KAIST, Daejeon, Korea</b></td><td>6</td></tr><tr><td><b>Colorado State University, Fort Collins</b></td><td>6</td></tr><tr><td><b>Indian Institute of Technology (BHU) Varanasi, India</b></td><td>6</td></tr><tr><td><b>Department of Information Engineering and Computer Science, University of Trento, Italy</b></td><td>6</td></tr><tr><td><b>College of Information Technical Science, NanKai University, CITS, TianJin, China</b></td><td>6</td></tr><tr><td><b>SAIT India, Samsung India Software Operations Pvt. Ltd (SISO), Bangalore, India, 560093</b></td><td>6</td></tr><tr><td><b>Fudan University, Shang Hai, China</b></td><td>6</td></tr><tr><td><b>State University of New York at Binghamton, USA</b></td><td>6</td></tr><tr><td><b>Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore</b></td><td>6</td></tr><tr><td><b>Computer Science, U.Illinois at Urbana Champaign, Urbana, United States</b></td><td>6</td></tr><tr><td><b>Indian Statistical Institute, Kolkata</b></td><td>6</td></tr><tr><td>NC A&T State University, Greensboro, NC, USA</td><td>6</td></tr><tr><td><b>Department of Computer Science, Università degli Studi di Milano, Italy</b></td><td>6</td></tr><tr><td><b>College of Information Science and Engineering, Northeastern University, Shenyang, 110819, PR China</b></td><td>6</td></tr><tr><td><b>Wuyi University, Jiangmen, China</b></td><td>6</td></tr><tr><td><b>Advanced Digital Sciences Center, Singapore</b></td><td>6</td></tr><tr><td><b>School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA</b></td><td>6</td></tr><tr><td><b>Dept. of Computer Science, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</b></td><td>6</td></tr><tr><td><b>Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China</b></td><td>6</td></tr><tr><td><b>School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>6</td></tr><tr><td><b>Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China</b></td><td>6</td></tr><tr><td><b>School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China</b></td><td>6</td></tr><tr><td><b>University of Ljubljana, Ljubljana, Slovenia</b></td><td>6</td></tr><tr><td><b>University of Notre Dame, Notre Dame, IN, USA</b></td><td>6</td></tr><tr><td><b>DIA, University of Trieste, Italy</b></td><td>6</td></tr><tr><td><b>Beijing Normal University, China</b></td><td>6</td></tr><tr><td><b>The University of Queensland, Brisbane, Australia</b></td><td>6</td></tr><tr><td><b>University of Houston</b></td><td>6</td></tr><tr><td><b>Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China</b></td><td>6</td></tr><tr><td><b>School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China</b></td><td>6</td></tr><tr><td><b>Center for Machine Vision and Signal Analysis, University of Oulu, Finland</b></td><td>6</td></tr><tr><td>School of Information and Software Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, 610054, China P.R.C</td><td>6</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>6</td></tr><tr><td><b>Department of Automation, University of Science and Technology of China, Hefei, China</b></td><td>6</td></tr><tr><td><b>Department of Mechanical Engineering, Faculty of Engineering, National University of Singapore, 117576, Singapore</b></td><td>6</td></tr><tr><td><b>Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China</b></td><td>6</td></tr><tr><td><b>IIT Guwahati, Guwahati, India</b></td><td>6</td></tr><tr><td><b>School of Software, Dalian University of Technology, Dalian, China</b></td><td>6</td></tr><tr><td><b>Department of Computer Science and Engineering, Varendra University, Rajshahi, Bangladesh</b></td><td>6</td></tr><tr><td><b>Indraprastha Institute of Information Technology Delhi, New Delhi, India</b></td><td>6</td></tr><tr><td><b>School of Computer and Information, Hefei University of Technology, Hefei, China</b></td><td>6</td></tr><tr><td><b>Key Lab of Computing and Communication Software of Anhui Province, School of Computer Science and Technology, University of Science and Technology of China, Hefei, China, 230027</b></td><td>6</td></tr><tr><td><b>Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China</b></td><td>6</td></tr><tr><td><b>Queen Mary University of London, UK</b></td><td>6</td></tr><tr><td><b>Department of Computing, The Hong Kong Polytechnic University, Hong Kong</b></td><td>6</td></tr><tr><td><b>Facultad de Ingeniería, Universidad de la República, Montevideo, Uruguay</b></td><td>6</td></tr><tr><td><b>School of Software, Dalian University of Technology, China 116620</b></td><td>6</td></tr><tr><td><b>School of Computer Science & Technology, Harbin Institute of Technology</b></td><td>6</td></tr><tr><td><b>School of Computer Science and Engineering, South China University of Technology, Guangzhou, China</b></td><td>6</td></tr><tr><td><b>Microsoft Res. Asia, Beijing, China</b></td><td>5</td></tr><tr><td><b>LUNAM Université, LIUM, Le Mans, France</b></td><td>5</td></tr><tr><td><b>Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA</b></td><td>5</td></tr><tr><td><b>School of Electronics and Information, Northwestern Polytechnical University</b></td><td>5</td></tr><tr><td>Electronics and Telecommunications Research Institute, Korea</td><td>5</td></tr><tr><td><b>Institute for Microsensors, Actuators and Systems, University of Bremen, Bremen, Germany</b></td><td>5</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China, 100190</b></td><td>5</td></tr><tr><td><b>Nokia Research Center, Beijing</b></td><td>5</td></tr><tr><td><b>College of Computer Science, Zhejiang University of Technology, Hangzhou, China</b></td><td>5</td></tr><tr><td><b>Frontier Research Group, Samsung India Software Operations, India</b></td><td>5</td></tr><tr><td><b>Faculty of Information Technology, Beijing University of Technology, Beijing, China</b></td><td>5</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Bahçeşehir Üniversitesi, İstanbul, Türkiye</b></td><td>5</td></tr><tr><td><b>School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>5</td></tr><tr><td><b>IIIT-Delhi</b></td><td>5</td></tr><tr><td><b>Georgia Institute of Technology</b></td><td>5</td></tr><tr><td><b>School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea</b></td><td>5</td></tr><tr><td><b>Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China</b></td><td>5</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Science, Beijing, 100190, China</b></td><td>5</td></tr><tr><td><b>Human Language Technology Center of Excellence, The Johns Hopkins University, Baltimore, MD, 21218, USA</b></td><td>5</td></tr><tr><td><b>Department of Electronic Engineering/Graduate School at Shenzhen, Tsinghua University, China</b></td><td>5</td></tr><tr><td><b>Dalian University of Technology, China</b></td><td>5</td></tr><tr><td><b>Chinese Academy of Sciences</b></td><td>5</td></tr><tr><td><b>Nanyang Technological University, Singapore</b></td><td>5</td></tr><tr><td><b>College of Information Science and Technology, Beijing Normal University, Beijing, P.R. China</b></td><td>5</td></tr><tr><td><b>Visea İnovatif Bilgi Teknolojileri, ETGB Teknoparkı, Eskişehir, Türkiye</b></td><td>5</td></tr><tr><td><b>Ocean University of China, Department of Educational Technology, Qingdao, China</b></td><td>5</td></tr><tr><td><b>Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, China</b></td><td>5</td></tr><tr><td><b>Disney Research, UK</b></td><td>5</td></tr><tr><td>Asian Institute of Technology (AIT), Pathum Thani 12120, Thailand</td><td>5</td></tr><tr><td>Chonnam National University, Gwangju, Korea</td><td>5</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, East Lansing, MI</b></td><td>5</td></tr><tr><td><b>Microsoft Research Asia, Beijing, China</b></td><td>5</td></tr><tr><td><b>Carnegie Mellon University, ForbesAvenue, Pittsburgh PA</b></td><td>5</td></tr><tr><td><b>Telecommun. & Ind. Phys., CSIRO, Epping, NSW, Australia</b></td><td>5</td></tr><tr><td><b>Centre for Health Technologies, Faculty of Engineering and Information Technology, University of Technology, Sydney, New South Wales, Australia</b></td><td>5</td></tr><tr><td><b>Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences</b></td><td>5</td></tr><tr><td><b>Pattern Recognition and Intelligent System Laboratory, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>5</td></tr><tr><td><b>Artificial Vision Laboratory, National Taiwan University of Science and Technology, Taipei, Taiwan</b></td><td>5</td></tr><tr><td><b>Hangzhou Dianzi University, Hangzhou, China</b></td><td>5</td></tr><tr><td><b>Department of Automation, Shanghai Jiao Tong University, Shanghai, China</b></td><td>5</td></tr><tr><td><b>Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece</b></td><td>5</td></tr><tr><td><b>University of Trento, Italy, Via Sommarive, Trento (Italy)</b></td><td>5</td></tr><tr><td><b>Biometric Recognition Group - ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 - Campus de Cantoblanco - 28049, Spain</b></td><td>5</td></tr><tr><td><b>Institute of Microelectronics, Tsinghua University, Beijing, China</b></td><td>5</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Durgapur, India</td><td>5</td></tr><tr><td><b>DUT-RU International School of Information & Software Engineering, Dalian University of Technology</b></td><td>5</td></tr><tr><td><b>East China Normal University, Shanghai, China</b></td><td>5</td></tr><tr><td><b>Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>5</td></tr><tr><td><b>Department of Information Science and Engineering, Ritsumeikan University, Shiga, Japan</b></td><td>5</td></tr><tr><td><b>Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>5</td></tr><tr><td><b>Department of Automation, State Key Lab of Intelligent Technologies and Systems and Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing, China</b></td><td>5</td></tr><tr><td>Chongqing Institute of Green and Intelligent Technology, CAS, Chongqing, 400714</td><td>5</td></tr><tr><td><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China</b></td><td>5</td></tr><tr><td><b>School of Data and Computer Science, Sun Yat-Sen University, China</b></td><td>5</td></tr><tr><td><b>Centre of Development of Advanced Computing (CDAC) Mumbai, 400049, India</b></td><td>5</td></tr><tr><td><b>National Institute of Informatics, Tokyo, Japan</b></td><td>5</td></tr><tr><td><b>University of Southern California</b></td><td>5</td></tr><tr><td><b>Chongqing Institute of Technology, China</b></td><td>5</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>5</td></tr><tr><td><b>Northwestern Polytechnical University, Xi'an Shaanxi, China</b></td><td>5</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Haidian District, Beijing, China</b></td><td>5</td></tr><tr><td><b>Chinese Academy of Sciences, Beijing, China</b></td><td>5</td></tr><tr><td>SIAT at Chinese Academy of Sciences, China</td><td>5</td></tr><tr><td><b>IBM China Research Laboratory, Beijing, China</b></td><td>5</td></tr><tr><td><b>Stanford University, Stanford, CA, USA</b></td><td>5</td></tr><tr><td><b>University of California, Merced</b></td><td>5</td></tr><tr><td><b>Tsinghua National Laboratory for Information Science and Technology Institute of Microelectronics, Tsinghua University, Beijing, China</b></td><td>5</td></tr><tr><td>Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy</td><td>5</td></tr><tr><td><b>Hefei University of Technology, Hefei, China</b></td><td>5</td></tr><tr><td><b>Department of Computer Science, Xiamen University, Xiamen, P. R. China</b></td><td>5</td></tr><tr><td>University of Southern California Institute for Creative Technologies, Los Angeles, CA</td><td>5</td></tr><tr><td><b>University of Maryland, College Park, MD, USA</b></td><td>5</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798</b></td><td>5</td></tr><tr><td><b>The Institute of Optics and Electronics Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Chengdu, China</b></td><td>5</td></tr><tr><td><b>Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA</b></td><td>5</td></tr><tr><td><b>Idiap Research Institute, Martigny, Switzerland</b></td><td>5</td></tr><tr><td><b>NICTA, PO Box 6020, St Lucia, QLD 4067, Australia</b></td><td>5</td></tr><tr><td><b>College of Information and Control Engineering, China University of Petroleum, Qingdao, 266580, China</b></td><td>5</td></tr><tr><td>Department of Electronics and Telecommunication Engineering, Don Bosco Institute of Technology, Kurla (W), Mumbai, India</td><td>5</td></tr><tr><td><b>Dept. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, USA</b></td><td>5</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia</b></td><td>5</td></tr><tr><td><b>School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China</b></td><td>5</td></tr><tr><td><b>School of Electronic Engineering, Xidian University, Xi'an, China</b></td><td>5</td></tr><tr><td><b>University of Science and Technology of China, Hefei, Anhui, China</b></td><td>5</td></tr><tr><td>R V College of Engineering, Department of Computer Science and Engineering, Bangalore, India</td><td>5</td></tr><tr><td><b>Centre for Machine Vision Research, University of Oulu, Finland</b></td><td>5</td></tr><tr><td><b>Knowledge Technology Institute, Department of Informatics, University of Hamburg, Hamburg, Germany</b></td><td>5</td></tr><tr><td><b>School of Electrical Engineering Department, Korea University, Rep. of Korea</b></td><td>5</td></tr><tr><td>Inst. Nat. des Telecommun., Evry, France</td><td>5</td></tr><tr><td><b>University of Trento, Trento, Italy</b></td><td>5</td></tr><tr><td><b>National Science and Technology Development Agency, National Electronics and Computer Technology Center, Pathum Thani, 12120, Thailand</b></td><td>4</td></tr><tr><td><b>Dalian University of Technology, Dalian, Liaoning, 116024, China</b></td><td>4</td></tr><tr><td><b>School of Engineering & Applied Science, Ahmedabad University, Gujarat, India 380009</b></td><td>4</td></tr><tr><td>Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering</td><td>4</td></tr><tr><td><b>University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia</b></td><td>4</td></tr><tr><td><b>The Australian Centre for Visual Technologies, The university of Adelaide</b></td><td>4</td></tr><tr><td><b>University of the Western Cape, Bellville, Western Cape</b></td><td>4</td></tr><tr><td><b>School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, 6140, New Zealand</b></td><td>4</td></tr><tr><td><b>Tsinghua University</b></td><td>4</td></tr><tr><td><b>National Taiwan University, Taipei, Taiwan</b></td><td>4</td></tr><tr><td><b>School of Computer Science & Technology, Nanjing University of Science and Technology, China</b></td><td>4</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Rowan University, Glassboro, NJ- 08028</b></td><td>4</td></tr><tr><td><b>School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China, 710049</b></td><td>4</td></tr><tr><td><b>Media Integration and Communication Center - MICC, University of Florence, Italy</b></td><td>4</td></tr><tr><td><b>School of Computer Science, University of the Witwatersrand, Johannesburg, South Africa</b></td><td>4</td></tr><tr><td>Department of Microelectornics and Computer Science, Lodz University of Technology, ul. Wolczanska 221/223, 90-924, Poland</td><td>4</td></tr><tr><td><b>School of Computer Science and Telecommunication Engineering, Jiangsu University, ZhenJiang, Jiangsu, 212013, P. R. China</b></td><td>4</td></tr><tr><td><b>Seoul Nat'l Univ.</b></td><td>4</td></tr><tr><td><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China 100876</b></td><td>4</td></tr><tr><td><b>Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, China</b></td><td>4</td></tr><tr><td><b>Institute of Computer Science and Technology, Peking University, Beijing, China, 100871</b></td><td>4</td></tr><tr><td><b>Department of Electronic Engineering, Tsinghua University, Beijing 100084, China</b></td><td>4</td></tr><tr><td><b>School of Computer Science and Engineering, Nanjing University of Science and Technology, China</b></td><td>4</td></tr><tr><td><b>Faculty of electrical engineering, University of Ljubljana, Slovenia</b></td><td>4</td></tr><tr><td><b>Department of Information Management and Security, Korea University</b></td><td>4</td></tr><tr><td><b>Pattern Recognition and Intelligent System Lab (PRIS) Beijing University of Posts and Telecommunications, Beijing 100876, P. R. China</b></td><td>4</td></tr><tr><td><b>Institute of Intelligence Information Processing, Xidian University, Xi¿an, China, 710071</b></td><td>4</td></tr><tr><td><b>Research Center for Information Technology Innovation (CITI), Academia Sinica, Taipei, 115 Taiwan</b></td><td>4</td></tr><tr><td><b>University of Miami, Coral Gables, FL</b></td><td>4</td></tr><tr><td><b>Univ. Orléans, INSA CVL, PRISME EA 4229, Bourges, France</b></td><td>4</td></tr><tr><td><b>Institute of Systems and Robotics (ISR), University of Coimbra, Portugal</b></td><td>4</td></tr><tr><td><b>Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong</b></td><td>4</td></tr><tr><td><b>School of Electrical and Electronics Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, SEOUL, Republic of Korea</b></td><td>4</td></tr><tr><td><b>School of Information Science and Engineering, Southeast University, Nanjing, 210096, P.R. China</b></td><td>4</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea</b></td><td>4</td></tr><tr><td><b>Hong Kong University of Science and Technology, Hong Kong</b></td><td>4</td></tr><tr><td><b>INRIA Grenoble Rhone-Alpes, FRANCE</b></td><td>4</td></tr><tr><td>North China Electric Power University Department of Electronic and Communication Engineering Baoding, Hebei, China</td><td>4</td></tr><tr><td><b>Seoul National University</b></td><td>4</td></tr><tr><td>School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand</td><td>4</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China</b></td><td>4</td></tr><tr><td><b>School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology Guangxi Guilin, China</b></td><td>4</td></tr><tr><td><b>University of Portsmouth, United Kingdom</b></td><td>4</td></tr><tr><td><b>Carnegie Mellon University</b></td><td>4</td></tr><tr><td><b>Bilgisayar Mühendisliği, Başkent Üniversitesi, Ankara, Türkiye</b></td><td>4</td></tr><tr><td><b>Universidad Autonoma de Madrid</b></td><td>4</td></tr><tr><td><b>University of Oulu, Machine Vision Group, PO Box 4500, 90014, Finland</b></td><td>4</td></tr><tr><td><b>Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea</b></td><td>4</td></tr><tr><td><b>Center for Computer Vision and Department of Mathematics, Sun Yat-Sen University, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland</b></td><td>4</td></tr><tr><td>KU Leuven, Leuven, Belgium</td><td>4</td></tr><tr><td>Academia Sinica, Taipei, Taiwan</td><td>4</td></tr><tr><td><b>Institute of Computer, Hangzhou Dianzi University, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, No.95 East Road of Zhongguancun, Beijing, China</b></td><td>4</td></tr><tr><td>LIARA Laboratory, University of Quebec at Chicoutimi (UQAC), Boulevard de l'Université, Chicoutimi (Quebec), Canada</td><td>4</td></tr><tr><td>Dept. of Computing, Curtin University GPO Box U1987, Perth, WA 6845</td><td>4</td></tr><tr><td><b>Department of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, China</b></td><td>4</td></tr><tr><td>NTT Software Innovation Center, Tokyo, Japan</td><td>4</td></tr><tr><td><b>Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China</b></td><td>4</td></tr><tr><td><b>University of Electronic Science and Technology of China, Chengdu, China</b></td><td>4</td></tr><tr><td><b>Dalle Molle Instituite for Artificial Intelligence (IDSIA), Lugano, Switzerland</b></td><td>4</td></tr><tr><td><b>Dept of Electrical and Computer Engineering, University of Calgary, Calgary, CANADA</b></td><td>4</td></tr><tr><td><b>Department of Computer Science, University of Colorado at Colorado Springs</b></td><td>4</td></tr><tr><td>EECS Department, University of Kansas, Lawrence, KS</td><td>4</td></tr><tr><td><b>Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, Hunan, P.R. China</b></td><td>4</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 100190</b></td><td>4</td></tr><tr><td><b>The Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia</b></td><td>4</td></tr><tr><td><b>School of Information and Communication, Guilin University of Electronic Technology Guangxi Guilin, China</b></td><td>4</td></tr><tr><td><b>College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, P.R. China</b></td><td>4</td></tr><tr><td>Department of Mathematics and Computer Science University of Basel</td><td>4</td></tr><tr><td><b>Xi'an Jiaotong University, Xi'an, China</b></td><td>4</td></tr><tr><td><b>Department of Information Engineering, University of Brescia, Via Branze, 38 - 25123, Italy</b></td><td>4</td></tr><tr><td><b>Department of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China</b></td><td>4</td></tr><tr><td>Goa University, India</td><td>4</td></tr><tr><td><b>University of Texas at Arlington, Arlington, TX</b></td><td>4</td></tr><tr><td><b>Norwegian Biometrics Laboratory, NTNU - Gj⊘vik, Norway</b></td><td>4</td></tr><tr><td><b>Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, U.K.</b></td><td>4</td></tr><tr><td><b>University of Nottingham, UK</b></td><td>4</td></tr><tr><td>Beijing Key Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081, China</td><td>4</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education, International Research Center for Intelligent Perception and Computation, Joint International Research Laboratory of Intelligent Perception and Computation of China, Xidian University, Xi’an, China</b></td><td>4</td></tr><tr><td>VUB-NPU Joint AVSP Research Lab, Vrije Universiteit Brussel (VUB), Deptartment of Electronics & Informatics (ETRO), Pleinlaan 2, 1050 Brussel, Belgium</td><td>4</td></tr><tr><td><b>National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, Chengdu, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, China</b></td><td>4</td></tr><tr><td><b>Department of Electronic and Electrical Engineering, Pohang University of Science and Technology (POSTECH), South Korea</b></td><td>4</td></tr><tr><td><b>University of Canberra, Canberra, Australia</b></td><td>4</td></tr><tr><td>Graduate School of Information Science, Nara Institute of Science and Technology, Takayama-cho 8916-5, Ikoma-shi, Nara, Japan</td><td>4</td></tr><tr><td><b>Department of Computer Science, University of North Carolina, Charlotte, NC, USA</b></td><td>4</td></tr><tr><td><b>Institute of Machine Learning and Systems Biology, College of Electronics and Information Engineering, Tongji University, Caoan Road 4800, Shanghai 201804, China</b></td><td>4</td></tr><tr><td><b>Intel Labs, Hillsboro, Oregon, USA</b></td><td>4</td></tr><tr><td>Smart Surveillance Interest Group, Department of Computer Science, Universidade Federal de Minas Gerais, Minas Gerais, Brazil</td><td>4</td></tr><tr><td><b>Department of Automation, State Key Lab of Intelligent Technologies and Systems, and Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing, China</b></td><td>4</td></tr><tr><td><b>Université de Lyon, CNRS, UMR5205, F-69622, France</b></td><td>4</td></tr><tr><td>Shanghai University School of Communication and Information Engineering Shanghai, China</td><td>4</td></tr><tr><td>Microsoft, Redmond, WA, USA</td><td>4</td></tr><tr><td>Computer Science and Engineering, Pennsylvania State University, PA, USA SiliconScapes, LLC, PA, USA</td><td>4</td></tr><tr><td><b>Key Laboratory of Intelligent Information Processing, Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, China</b></td><td>4</td></tr><tr><td><b>Queen Mary University of London, London</b></td><td>4</td></tr><tr><td>Dept. of Computer Engineering, Keimyung University, Daegu, Korea</td><td>4</td></tr><tr><td><b>Department of Cognitive Science, Xiamen University, Xiamen, Fujian, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China</b></td><td>4</td></tr><tr><td><b>Université de Lyon, CNRS, UMR5205, F-69622, France</b></td><td>4</td></tr><tr><td><b>School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, 116024, China</b></td><td>4</td></tr><tr><td><b>DII, University of Brescia, Brescia, Italy</b></td><td>4</td></tr><tr><td><b>School of Software, Tsinghua University, Beijing, China</b></td><td>4</td></tr><tr><td>National ICT Australia and UNSW, Sydney, Australia</td><td>4</td></tr><tr><td><b>Institute for Creative Technologies, University of Southern California</b></td><td>4</td></tr><tr><td><b>School of Information Science and Technology, Xiamen University, Xiamen, China</b></td><td>4</td></tr><tr><td><b>University of California, San Diego, USA</b></td><td>4</td></tr><tr><td><b>The University of Queensland, School of ITEE, QLD 4072, Australia</b></td><td>4</td></tr><tr><td><b>Department of Computer Science, University of York, UK</b></td><td>4</td></tr><tr><td><b>Department of Automation, State Key Lab of Intelligent Technologies and Systems, Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing, China</b></td><td>4</td></tr><tr><td><b>Dept. of Computer Science, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>4</td></tr><tr><td><b>SRI International, Menlo Park, USA</b></td><td>4</td></tr><tr><td><b>Université de Lyon, CNRS, France</b></td><td>4</td></tr><tr><td><b>School of Computer Science and Technology & Joint International Research Laboratory of Machine Learning and Neuromorphic Computing, Soochow University, Suzhou, China</b></td><td>4</td></tr><tr><td><b>Department of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China</b></td><td>4</td></tr><tr><td><b>Computer Science and Engineering Department, University of South Florida, Tampa, FL, USA</b></td><td>4</td></tr><tr><td><b>Advanced Technologies Application Center 7a #21406 b/ 214 and 216, P.C. 12200, Siboney, Playa, Havana, Cuba</b></td><td>4</td></tr><tr><td><b>Çoğulortam İşaret İşleme ve Örüntü Tanıma Grubu, İstanbul Teknik Üniversitesi, İstanbul, Türkiye</b></td><td>4</td></tr><tr><td>Department of Electrical and Computer Engineering, Beckman Institute Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, IL, USA</td><td>4</td></tr><tr><td><b>National Laboratory of Pattern Recognition, CASIA, Center for Research on Intelligent Perception and Computing, CASIA, Center for Excellence in Brain Science and Intelligence Technology, CAS, University of Chinese Academy of Sciences, Beijing, 100049, China</b></td><td>4</td></tr><tr><td><b>Machine Learning and Cybernetics Research Center, School of Computer Science and Engineering, South China University of Technology, 510006, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>IC Design Group, CSIR-Central Electronics Engineering Research Institute, Pilani, Rajasthan, India</b></td><td>4</td></tr><tr><td><b>College of Information Engineering, Yangzhou University, Yangzhou, China</b></td><td>4</td></tr><tr><td><b>Department of Mathematics, Intelligent Data Center, Sun Yat-sen University, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Electronic Engineering, Tsinghua University, Beijing 100084, China</b></td><td>4</td></tr><tr><td>Universiti Kuala Lumpur, Kuala Lumpur</td><td>4</td></tr><tr><td><b>Max Planck Institute for Informatics, Saarland Informatics Campus, Germany</b></td><td>4</td></tr><tr><td><b>National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China</b></td><td>4</td></tr><tr><td><b>Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>4</td></tr><tr><td>Beijing Normal Univeristy, Beijing, China</td><td>4</td></tr><tr><td><b>Information Sciences Institute, University of Southern California, 4676 Admiralty Way, Marina Del Rey, 90292, USA</b></td><td>4</td></tr><tr><td><b>National University of Defense Technology, China</b></td><td>4</td></tr><tr><td><b>National Digital Switching System Engineering and Technological Research Center, Zhengzhou, China</b></td><td>4</td></tr><tr><td><b>Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong</b></td><td>4</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA</b></td><td>4</td></tr><tr><td><b>University of Tsukuba</b></td><td>4</td></tr><tr><td><b>University of Electronic Science and Technology of China</b></td><td>4</td></tr><tr><td><b>National Taiwan University of Science and Technology</b></td><td>4</td></tr><tr><td><b>Samsung R&D Institute, Bangalore, India</b></td><td>4</td></tr><tr><td><b>Yaroslavl State University, Yaroslavl, Russia</b></td><td>4</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Seoul National University</b></td><td>4</td></tr><tr><td><b>College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China</b></td><td>4</td></tr><tr><td><b>School of Electronics and Information Technology, Sun Yat-sen University, China</b></td><td>4</td></tr><tr><td>University of Tunis, The National Higher school of engineers of Tunis (ENSIT), Laboratory of Signal Image and Energy Mastery, LR13ES03 (SIME), Tunis, Tunisia</td><td>4</td></tr><tr><td><b>College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China</b></td><td>4</td></tr><tr><td><b>Department of Computer Science and Engineering, Sejong University, 98 Gunja, Gwangjin, Seoul 143-747, Korea</b></td><td>4</td></tr><tr><td><b>University of Maryland, College Park, Maryland 20740 United States</b></td><td>4</td></tr><tr><td><b>Face Aging Group, University of North Carolina, Wilmington, NC, USA</b></td><td>4</td></tr><tr><td><b>Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China</b></td><td>4</td></tr><tr><td><b>North Carolina State University, Department of Electrical and Computer Engineering, Raleigh, United States of America</b></td><td>4</td></tr><tr><td><b>Institute of Computer Science and Technology, Peking University, Beijing, China</b></td><td>4</td></tr><tr><td><b>College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>4</td></tr><tr><td>Media Technology Lab, Huawei Technologies Co., Ltd</td><td>4</td></tr><tr><td><b>Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, 28 Xianning West Road, Xi'an, Shaanxi, China</b></td><td>4</td></tr><tr><td><b>Keio University, Japan</b></td><td>4</td></tr><tr><td><b>National University of Defense Technology, Changsha, China</b></td><td>4</td></tr><tr><td><b>Hewlett-Packard Laboratories, Hewlett-Packard Company, Palo Alto, CA, USA</b></td><td>4</td></tr><tr><td><b>School of Computer Science and Engineering, Center for Robotics, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>4</td></tr><tr><td><b>Image Processing Center, Beihang University, Beijing, China</b></td><td>4</td></tr><tr><td><b>School of Electronic and Computer Engineering, Peking University</b></td><td>4</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing University of Surrey, Guildford, UK</b></td><td>4</td></tr><tr><td><b>Shenzhen Key Laboratory of Information Science and Technology, Shenzhen Engineering Laboratory of IS&DCP and the Department of Electronic Engineering, Graduate School at Shenzhen, Tsinghua University, Beijing, China</b></td><td>4</td></tr><tr><td>Department of Computer Graphics and Multimedia, University of Brno, Brno, Czech Republic</td><td>4</td></tr><tr><td><b>Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain</b></td><td>4</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China</b></td><td>4</td></tr><tr><td><b>Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, People's Republic of China</b></td><td>4</td></tr><tr><td><b>Video/Image Modeling and Synthesis Laboratory, Department of Computer and Information Sciences, University of Delaware, Newark, DE</b></td><td>4</td></tr><tr><td><b>Multimedia Processing Lab., Samsung Advanced Institute of Technology (SAIT), Suwon-si, Korea</b></td><td>4</td></tr><tr><td>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA</td><td>4</td></tr><tr><td><b>Osaka university, Japan</b></td><td>4</td></tr><tr><td><b>IBJ, Inc., Tokyo, Japan</b></td><td>4</td></tr><tr><td><b>The University of Tokyo, Japan</b></td><td>4</td></tr><tr><td>Faculty of Engineering, Ain Shams University, Computer and Systems Engineering Department, Cairo, Egypt</td><td>4</td></tr><tr><td>School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, China</td><td>4</td></tr><tr><td><b>College of electronic and information engineer Changchun University of Science and Technology Changchun China</b></td><td>4</td></tr><tr><td><b>School of Electrical, Computer and Telecommunication Engineering, University of Wollongong, NSW 2522, Australia</b></td><td>4</td></tr><tr><td><b>The University of Texas at Austin Austin, Texas, USA</b></td><td>4</td></tr><tr><td><b>Amity University Uttar Pradesh, Noida</b></td><td>4</td></tr><tr><td><b>Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea</b></td><td>4</td></tr><tr><td>Computer Science and Engineering Dept., University of Nevada Reno, USA</td><td>4</td></tr><tr><td><b>Dept of Computer Engineering, Kyung Hee University, Yongin-si, South Korea</b></td><td>4</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, TX, USA</b></td><td>4</td></tr><tr><td><b>University of Surrey, Guildford</b></td><td>4</td></tr><tr><td>Department of Information and Control, B-DAT Laboratory, Nanjing University of Information and Technology, Nanjing, China</td><td>4</td></tr><tr><td><b>State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Robotics, Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, 110016, China</b></td><td>4</td></tr><tr><td>Inha University, South Korea</td><td>4</td></tr><tr><td><b>Sharp Laboratories of America, Camas, WA</b></td><td>4</td></tr><tr><td><b>Department of Informatics, Aristotle University of Thessaloniki, Greece</b></td><td>4</td></tr><tr><td><b>Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Netherlands</b></td><td>4</td></tr><tr><td><b>Center for Biometrics and Security Research and the National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>4</td></tr><tr><td><b>Geintra Research Group, University of Alcala</b></td><td>4</td></tr><tr><td><b>National Engineering Research Center for Multimedia Software, Computer School, Wuhan University, Wuhan, China</b></td><td>4</td></tr><tr><td><b>Electrical and Computer Systems Engineering, School of Engineering, Monash University Malaysia, 46150 Selangor, Malaysia</b></td><td>4</td></tr><tr><td><b>Beijing Laboratory of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing, China</b></td><td>4</td></tr><tr><td><b>Department of Computer Science, Hong Kong Baptist University, Hong Kong</b></td><td>4</td></tr><tr><td><b>University of Science and Technology of China, Hefei, China</b></td><td>4</td></tr><tr><td><b>Beijing, Haidian, China</b></td><td>4</td></tr><tr><td>Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China</td><td>4</td></tr><tr><td><b>School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, U.S.A.</b></td><td>4</td></tr><tr><td>Institute for Human-Machine Communication, Technische Universität München, Germany</td><td>4</td></tr><tr><td><b>Peking University, Shenzhen, China</b></td><td>4</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada</b></td><td>4</td></tr><tr><td>Faculty of Engineering Science, Department of Systems Innovation, Arai Laboratory at Osaka University, Japan</td><td>4</td></tr><tr><td><b>Biometric Recognition Group - ATVS, EPS, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 - Campus de Cantoblanco - 28049 Madrid, Spain</b></td><td>4</td></tr><tr><td><b>Department of MathematicsIntelligent Data Center, Sun Yat-sen University, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>University of Trento, Italy</b></td><td>4</td></tr><tr><td><b>Centre for Imaging Sciences, The University of Manchester, Manchester, United Kingdom</b></td><td>4</td></tr><tr><td><b>National Laboratory of Pattern Recognition, CASIA, University of Chinese Academy of Sciences, Beijing, 100049, China</b></td><td>4</td></tr><tr><td><b>School of Electronic and Electrical Engineering, Shanghai Jiao Tong University, National Engineering Lab on Information Content Analysis Techniques, GT036001 Shanghai, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences</b></td><td>4</td></tr><tr><td><b>Department of Informatics, University of Oslo, Oslo, Norway</b></td><td>4</td></tr><tr><td><b>Speech, Audio, Image and Video Technology (SAIVT) Laboratory, Queensland University of Technology, Australia</b></td><td>4</td></tr><tr><td><b>Technicolor, France</b></td><td>4</td></tr><tr><td><b>Korea Advanced Institute of Science and Technology, Daejeon, South Korea</b></td><td>4</td></tr><tr><td><b>School of Mathematics and Computational Science, Sun Yat-sen University, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China</b></td><td>3</td></tr><tr><td><b>CyLab Biometrics Center and the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>3</td></tr><tr><td>NTT Corporation, Atsugi, Japan</td><td>3</td></tr><tr><td>Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beersheba, Israel</td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China</b></td><td>3</td></tr><tr><td><b>Vision Lab at Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA 23529, USA</b></td><td>3</td></tr><tr><td>Intel Labs China, Beijing, China</td><td>3</td></tr><tr><td><b>IBM T. J. Watson Research, Yorktown Heights, NY, USA</b></td><td>3</td></tr><tr><td><b>Computer Science and Technology, University of Science and Technology of China</b></td><td>3</td></tr><tr><td><b>School of Information Technologies, University of Sydney, Australia</b></td><td>3</td></tr><tr><td><b>Department of Electronic Engineering, The Chinese University of Hong Kong, China</b></td><td>3</td></tr><tr><td><b>Key Laboratory of Machine Perception (Ministry of Education) Engineering Lab on Intelligent Perception for Internet of Things (ELIP), Shenzhen Graduate School, Peking University, China</b></td><td>3</td></tr><tr><td>School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun, CO 130012 China</td><td>3</td></tr><tr><td><b>Center for Cognitive Ubiquitous Computing, Arizona State University, USA</b></td><td>3</td></tr><tr><td><b>School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Institute of Computing, State University of Campinas, Campinas, Brazil</b></td><td>3</td></tr><tr><td><b>Guangdong Key Laboratory of Data Security and Privacy Preserving, Guangdong Engineering Research Center of Data Security and Privacy Preserving, College of Information Science and Technology, Jinan University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>State Key Laboratory of Intelligent Technology and Systems, Department of Electronic Engineering, Tsinghua University, Beijing 100084, P.R. China</b></td><td>3</td></tr><tr><td><b>CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei 230027, China</b></td><td>3</td></tr><tr><td><b>Tokyo Institute of Technology, Tokyo, Japan</b></td><td>3</td></tr><tr><td>Radboud University, Nijmegen, Netherlands</td><td>3</td></tr><tr><td>Algılayıcılar, Görüntü ve Sinyal İşleme Grubu, HAVELSAN A.Ş. Ankara, Türkiye</td><td>3</td></tr><tr><td><b>C & C Innovation Research Labs, NEC Corporation, Nara, Japan</b></td><td>3</td></tr><tr><td>Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany</td><td>3</td></tr><tr><td><b>Imperial College London, UK</b></td><td>3</td></tr><tr><td>School of Electrical and Computer Engineering, Royal Melbourne Institute of Technology University , Melbourne, Australia</td><td>3</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, The University of Queensland, Australia</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Kyung Hee University, Seoul, South Korea</b></td><td>3</td></tr><tr><td><b>Institute for Infocomm Research, 1 Fusionpolis Way, #21-01, Connexis Singapore 138632, Singapore</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Engineering, South China University of Technology, China</b></td><td>3</td></tr><tr><td><b>Department of Radiology and the Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA</b></td><td>3</td></tr><tr><td><b>Dept. of Electrical Engineering and Comp. Sc., Northwestern University, Evanston, IL 60208, USA</b></td><td>3</td></tr><tr><td><b>School of Electronics and Computer Science, University of Southampton, Southampton, U.K.</b></td><td>3</td></tr><tr><td><b>School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China</b></td><td>3</td></tr><tr><td><b>Program of Electrical Engineering, COPPE/UFRJ, Universidade Federal do Rio de Janeiro, Rio de Janeiro-RJ CEP, Brazil</b></td><td>3</td></tr><tr><td><b>Bilgisayar Mühendisliği, İstanbul Teknik Üniversitesi, İstanbul, Turkey</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering and the Center for Automation Research, UMIACS, University of Maryland, College Park, USA</b></td><td>3</td></tr><tr><td><b>Department of Computer Engineering, Kyung Hee University, Seoul, South Korea</b></td><td>3</td></tr><tr><td><b>Michigan State University, United States of America</b></td><td>3</td></tr><tr><td>School of Engineering, University of Baja California, Tijuana, México</td><td>3</td></tr><tr><td><b>Center for Machine Vision Research, University of Oulu</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, University of South Florida, Tampa, Florida 33620</b></td><td>3</td></tr><tr><td><b>KTH Royal Institute of Technology, 100 44 Stockholm, Sweden</b></td><td>3</td></tr><tr><td><b>School of Software, Huazhong University of Science and Technology, Wuhan, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA</b></td><td>3</td></tr><tr><td>School of Computer Science, Center for Optical Imagery Analysis and Learning (OPTIMAL)</td><td>3</td></tr><tr><td><b>Department of Computing, Curtin University, Perth WA 6102, Australia</b></td><td>3</td></tr><tr><td>Department of Systems and Computing, Federal University of Campina Grande, Av. Apríigio Veloso, 882, 58429-900 Campina Grande, PB, Brazil</td><td>3</td></tr><tr><td><b>Institute of Imaging and Computer Vision, RWTH Aachen University, Templergraben 55, 52056, Aachen, Germany</b></td><td>3</td></tr><tr><td><b>Universidade Federal do Rio de Janeiro, Cx.P. 68504, Rio de Janeiro, RJ, CEP 21945-970, Brazil</b></td><td>3</td></tr><tr><td>R&D Centre Algoritmi, School of Engineering, University of Minho, Portugal</td><td>3</td></tr><tr><td><b>National Laboratory for Parallel and Distributed Processing, School of Computer, College of Computer, National University of Defense Technology, Changsha, China</b></td><td>3</td></tr><tr><td><b>Department of Computer and Information Science, Temple University, Philadelphia, PA, 19122, USA</b></td><td>3</td></tr><tr><td>Department of Control and Computer Engineering, Politecnico di Torino, Italy</td><td>3</td></tr><tr><td><b>Key Laboratory of System Control and Information Processing MOE, Department of Automation, Shanghai Jiao Tong University</b></td><td>3</td></tr><tr><td><b>College of Computer Science, Zhejiang University, China</b></td><td>3</td></tr><tr><td><b>Institute of Industrial Information Technology (IIIT), Karlsruhe Institute of Technology (KIT), 76187 Karlsruhe, Germany</b></td><td>3</td></tr><tr><td><b>School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>Institute for Electronics, Signal Processing and Communications (IESK), Otto-von-Guericke-University Magdeburg, D-39106, P.O. Box 4210 Germany</b></td><td>3</td></tr><tr><td><b>Institute for Human-Machine Communication, TU München, Theresienstrae 90, 80333 München, Germany</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Technology, Harbin Institute of Technology, China</b></td><td>3</td></tr><tr><td><b>Oak Ridge National Laboratory, USA</b></td><td>3</td></tr><tr><td>Center for Research in Intelligent Systems, University of California, Riverside Riverside, CA 92521-0425, USA</td><td>3</td></tr><tr><td><b>Department of CS&E, Indian Institute of Technology, Madras, India</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Windsor, 401 Sunset Avenue, Windsor, N9B 3P4, Canada</b></td><td>3</td></tr><tr><td>Shanghai Advanced Research Institute, CAS, Shanghai, China</td><td>3</td></tr><tr><td><b>Elektrik ve Elektronik Mühendisliği Bölümü, Eskişehir Osmangazi Üniversitesi, Türkiye</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Zhejiang University, Hangzhou, China</b></td><td>3</td></tr><tr><td><b>Software Solution Laboratory, Samsung Advanced Institute of Technology, Suwon-si, South Korea</b></td><td>3</td></tr><tr><td><b>Florida International University, Miami, FL</b></td><td>3</td></tr><tr><td><b>Rice University</b></td><td>3</td></tr><tr><td>Department of electronic engineering, Key Lab of Intelligent Perception and Image Understanding of Ministry of Education, Xi'an, China</td><td>3</td></tr><tr><td><b>Centre of Informatics, Federal University of Pernambuco, Recife-PE, Brazil. Bruno J. T. Fernandes is also with the Polytechnic School, University of Pernambuco, Brazil</b></td><td>3</td></tr><tr><td>Computer Vision Laboratory, ETH Zurich, Sternwartstrasse 7, 8092, Switzerland</td><td>3</td></tr><tr><td><b>VNU HCMC, University of Science, Ho Chi Minh City, Vietnam</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Peking University, Beijing, China</b></td><td>3</td></tr><tr><td><b>Instrumentation, IT and Systems Lab IRSEEM Rouen, FR</b></td><td>3</td></tr><tr><td><b>Aristotle University of Thessaloniki, Greece</b></td><td>3</td></tr><tr><td><b>School of Automation, Northwestern Polytechnical University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Arizona State University, Tempe, AZ, USA</b></td><td>3</td></tr><tr><td>BITS Pilani, Pilani , India</td><td>3</td></tr><tr><td>Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, Howrah-711 103, India</td><td>3</td></tr><tr><td><b>College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, Shandong, 266580, China</b></td><td>3</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences</b></td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition CAS Center for Excellence in Brain Science and Intelligence Technology Institute of Automation, Chinese Academy of Sciences, 100190, China</b></td><td>3</td></tr><tr><td><b>Univ. Bordeaux, LaBRI, PICTURA, UMR 5800, F-33400 Talence, France</b></td><td>3</td></tr><tr><td><b>Tianjin University, China</b></td><td>3</td></tr><tr><td><b>The Univ of Hong Kong, China</b></td><td>3</td></tr><tr><td><b>Advanced Technologies Application Center (CENATAV), 7A ♯21406 Siboney, Playa, P.C.12200, Havana, Cuba</b></td><td>3</td></tr><tr><td><b>GIPSA-Lab, Grenoble, France</b></td><td>3</td></tr><tr><td><b>University of Maryland, Baltimore County, Baltimore, MD, USA</b></td><td>3</td></tr><tr><td>Dept. of CS&E, IIT Madras, India</td><td>3</td></tr><tr><td><b>Samsung Research and Development Institute Bangalore Pvt Ltd., Bangalore, India</b></td><td>3</td></tr><tr><td><b>Inst. of Autom., Shanghai Jiao Tong Univ., China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, New Jersey Institute of Technology, Newark, USA</b></td><td>3</td></tr><tr><td><b>State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Imperial College London, London, U.K.</b></td><td>3</td></tr><tr><td><b>Center for Cognitive Ubiquitous Computing (CUbiC), Arizona State University, Tempe, AZ, USA</b></td><td>3</td></tr><tr><td><b>Department of Computing, Curtin University, Perth WA, Australia</b></td><td>3</td></tr><tr><td><b>SUNY Buffalo</b></td><td>3</td></tr><tr><td>Graduate School of System Design Tokyo Metropolitan University Tokyo, Japan</td><td>3</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, TOBB Ekonomi ve Teknoloji Üniversitesi, Ankara, Türkiye</b></td><td>3</td></tr><tr><td><b>Intelligent Data Center, School of Mathematics and Computational Science, Sun Yat-sen University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>Indian Institute of Information Technology at Allahabad, Allahabad, India</b></td><td>3</td></tr><tr><td>Face Aging Group, Computer Science Department, UNCW, USA</td><td>3</td></tr><tr><td>City University of New York, New York, NY, USA</td><td>3</td></tr><tr><td><b>Department of Computer Science and Digital Technologies, Faculty of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, U.K.</b></td><td>3</td></tr><tr><td><b>Faculty of Information Technology, University of Technology, Sydney, Australia</b></td><td>3</td></tr><tr><td>Department of Computer Science and Engineering, Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India</td><td>3</td></tr><tr><td><b>School of Computing, Communications and Electronics, University of Plymouth, UK</b></td><td>3</td></tr><tr><td>Ghent University, Ghent, Belgium</td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA</b></td><td>3</td></tr><tr><td><b>University of California San Diego, United States of America</b></td><td>3</td></tr><tr><td>Columbia Univeristy, New York, NY, USA</td><td>3</td></tr><tr><td><b>Key Lab of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China</b></td><td>3</td></tr><tr><td>Microsoft Research Cambridge</td><td>3</td></tr><tr><td><b>Singapore University of Technology and Design, Singapore</b></td><td>3</td></tr><tr><td><b>School of Information Science and Technology, Xiamen University, Xiamen, P. R. China</b></td><td>3</td></tr><tr><td><b>Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan</b></td><td>3</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, The University of Queensland</b></td><td>3</td></tr><tr><td>Center for Automation Research, UMIACS University of Maryland, College Park, MD 20742</td><td>3</td></tr><tr><td>School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, U.K.</td><td>3</td></tr><tr><td><b>Advanced Digital Sciences Center (ADSC), University of Illinois at Urbana-Champaign, Singapore</b></td><td>3</td></tr><tr><td><b>University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, University of Hamburg, Germany</b></td><td>3</td></tr><tr><td><b>Department of Computer ScienceMultimedia Processing Laboratory, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>3</td></tr><tr><td><b>West Virginia University, Lane Dept. of CSEE, Morgantown, WV</b></td><td>3</td></tr><tr><td><b>University of California San Diego</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, China</b></td><td>3</td></tr><tr><td><b>School of Information Technologies, The University of Sydney, NSW 2006, Australia, Sydney</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, University of Windsor, Ontario, Canada</b></td><td>3</td></tr><tr><td>School of Information and Communication Engineering, Beijing University of Posts and Telcommunications, Beijing, China</td><td>3</td></tr><tr><td><b>INRIA Grenoble Rhône-Alpes Research Center, 655 avenue de l'Europe, 38 334 Saint Ismier Cedex, France</b></td><td>3</td></tr><tr><td><b>National Institutes of Health, Bethesda, Maryland 20892</b></td><td>3</td></tr><tr><td><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>3</td></tr><tr><td>Gwangju Institute of Science and Technology, 123, Cheomdangwagi-ro, Buk-gu, Gwangju, South Korea</td><td>3</td></tr><tr><td><b>Department of Computing, The Hong Kong Polytechnic University, China</b></td><td>3</td></tr><tr><td><b>Harvard University</b></td><td>3</td></tr><tr><td><b>School of Computing and Information Sciences, Florida International University, Miami, FL</b></td><td>3</td></tr><tr><td><b>College of Electronic Information and Automation, Civil Aviation University of China, Tianjin</b></td><td>3</td></tr><tr><td><b>Department of Automation, Tsinghua University, 100084 Beijing, China</b></td><td>3</td></tr><tr><td><b>NICTA, Canberra ACT, Australia and CECS, Australian National University, Australia</b></td><td>3</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>3</td></tr><tr><td><b>Research Center of Intelligent Robotics, Shanghai Jiao Tong University, Shanghai 200240, P.R China</b></td><td>3</td></tr><tr><td><b>UtopiaCompression Corporation, 11150 W. Olympic Blvd, Suite 820, Los Angeles, CA 90064, USA</b></td><td>3</td></tr><tr><td><b>Chinese Academy of Sciences, China</b></td><td>3</td></tr><tr><td><b>Laboratoire des Systèmes de Télécommunication et Ingénierie de la Décision (LASTID) Université Ibn Tofail BP 133, Kenitra 14000, Maroc</b></td><td>3</td></tr><tr><td><b>Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR 7222, F-75005, Paris, France</b></td><td>3</td></tr><tr><td><b>Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan</b></td><td>3</td></tr><tr><td><b>School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China</b></td><td>3</td></tr><tr><td><b>University of Wisconsin - Madison</b></td><td>3</td></tr><tr><td><b>Mines-Télécom/Télécom Lille, CRIStAL (UMR CNRS 9189), Villeneuve d'Ascq, France</b></td><td>3</td></tr><tr><td><b>Kyung Hee University, Korea</b></td><td>3</td></tr><tr><td><b>Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina</b></td><td>3</td></tr><tr><td><b>Stony Brook University, Stony Brook, NY 11794, USA</b></td><td>3</td></tr><tr><td><b>University of Delaware, Newark, 19716, USA</b></td><td>3</td></tr><tr><td><b>Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Adenauerring 4, 76131, Germany</b></td><td>3</td></tr><tr><td><b>University at Buffalo, The State University of New York, Buffalo, NY 14203, USA</b></td><td>3</td></tr><tr><td><b>UIUC</b></td><td>3</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, 4800 Calhoun Rd., TX, 77004, USA</b></td><td>3</td></tr><tr><td><b>Pattern Recognition and Intelligent Systems Laboratory, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>3</td></tr><tr><td><b>Laboratory of Intelligent Recognition and Image Processing, School of Computer Science and Engineering, Beihang University, 100191, Beijing, China</b></td><td>3</td></tr><tr><td><b>Face Aging Group, UNCW</b></td><td>3</td></tr><tr><td><b>University of Texas at San Antonio, San Antonio, USA</b></td><td>3</td></tr><tr><td><b>College of Computer Science and Technology, Xinjiang Normal University, Urumchi, 830054, China</b></td><td>3</td></tr><tr><td><b>School of Information Technology, Deakin University, Geelong, VIC 3216, Australia</b></td><td>3</td></tr><tr><td>Institute of Mathematical and Computer Sciences, University of Sao Paulo, Sao Paulo, Brazil</td><td>3</td></tr><tr><td>Dept. of Informatics, Aristotle Univ. of Thessaloniki, Greece</td><td>3</td></tr><tr><td><b>Zhejiang University</b></td><td>3</td></tr><tr><td><b>Northwestern Polytechnical University, Xi'an, P. R. China</b></td><td>3</td></tr><tr><td><b>University of Southern California, Institute for Robotics and Intelligent Systems, Los Angeles, CA 90089, USA</b></td><td>3</td></tr><tr><td>NTT Media Intelligence Laboratories, Tokyo, Japan</td><td>3</td></tr><tr><td><b>Computer Science, University of Houston, Texas 77004, United States of America</b></td><td>3</td></tr><tr><td><b>School of Communication and Information Engineering, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>3</td></tr><tr><td>Beijing Institute of Graphic Communication, Beijing</td><td>3</td></tr><tr><td><b>Department of Computer Science and Technology, Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, USA</b></td><td>3</td></tr><tr><td><b>Tsinghua University, Beijing,China</b></td><td>3</td></tr><tr><td><b>Media & Inf. Res. Labs., NEC Corp., Kanagawa, Japan</b></td><td>3</td></tr><tr><td><b>Centre de Visió per Computador, Universitat Autònoma de Barcelona, Barcelona, Spain</b></td><td>3</td></tr><tr><td><b>Department of Electronic Engineering, Shanghai Jiao Tong University, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and TechnologyState Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China</b></td><td>3</td></tr><tr><td><b>School of Software, Tsinghua University, Beijing, P. R. China</b></td><td>3</td></tr><tr><td><b>Research Center of Intelligent Robotics Shanghai Jiao Tong University, Shanghai, 200240, P.R. China</b></td><td>3</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b></td><td>3</td></tr><tr><td><b>School of Software, University of Technology Sydney, New South Wales, Australia</b></td><td>3</td></tr><tr><td><b>School of Telecommunications Engineering, Xidian University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Shenzhen Graduate School, Harbin Institute of Technology, Guangdong 518055, China</b></td><td>3</td></tr><tr><td><b>Azbil Corporation 1-12-2, Kawana, Fujisawa-shi, 251-8522, Japan</b></td><td>3</td></tr><tr><td><b>Graduate School of Information Sciences, Tohoku University, 6-6-05., Aramaki Aza Aoba., Sendai-shi., 980-8579., Japan</b></td><td>3</td></tr><tr><td><b>Australian National University, Canberra, Australia</b></td><td>3</td></tr><tr><td><b>Visualisation Group, University of Warwick, Coventry, UK</b></td><td>3</td></tr><tr><td><b>School of Software Engineering, Chongqing University, Chongqing, China</b></td><td>3</td></tr><tr><td><b>Beijing University of Posts and Telecommunications</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan</b></td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, P. R. China</b></td><td>3</td></tr><tr><td>Nara Institute of Science and Technology, Japan</td><td>3</td></tr><tr><td><b>Institute for Electronics, Signal Processing and Communications (IESK) Otto-von-Guericke-University Magdeburg D-39016 Magdeburg, P.O. Box 4210 Germany</b></td><td>3</td></tr><tr><td>Department of Computer, the University of Suwon, Korea</td><td>3</td></tr><tr><td><b>Institute for Anthropomatics, Karlsruhe Institute of Technology, Germany</b></td><td>3</td></tr><tr><td>Department of Electrical and Computer Engineering, Florida Institute of Technology, Melbourne, USA</td><td>3</td></tr><tr><td><b>Fujian Key laboratory of Sensing and Computing for Smart City, School of Information Science and Technology, Xiamen University, Xiamen, China</b></td><td>3</td></tr><tr><td>Dept. of Computer Science and Engineering, St. Joseph's College of Engineering and Technology, Palai, Kerala, India</td><td>3</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, Beijing, P.R. China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, East Lansing 48824, USA</b></td><td>3</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, UK</b></td><td>3</td></tr><tr><td><b>School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, Indian Institute of Technology Kanpur, PIN 208016, Uttar Pradesh, India</b></td><td>3</td></tr><tr><td>Dept. of Computer Science and Electrical Engineering, University of Missouri-Kansas City, MO, USA</td><td>3</td></tr><tr><td><b>University of North Carolina Wilmington, USA</b></td><td>3</td></tr><tr><td><b>Shenzhen Key Laboratory of Computer Vision and Pattern Recognition, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>3</td></tr><tr><td><b>Visual Media Computing Lab, Department of Multimedia and Graphic Arts, Cyprus University of Technology, Limassol, Cyprus</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Computational Biomedicine Laboratory, University of Houston, Houston, TX, USA</b></td><td>3</td></tr><tr><td><b>Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil</b></td><td>3</td></tr><tr><td><b>Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China</b></td><td>3</td></tr><tr><td>Inha University, Incheon, South Korea</td><td>3</td></tr><tr><td><b>Swiss Federal Institute of Technology, Lausanne (EPFL), Switzerland</b></td><td>3</td></tr><tr><td><b>Australian Centre for Field Robotics University of Sydney, 2006, Australia</b></td><td>3</td></tr><tr><td><b>Université de Lyon, Laboratoire d’InfoRmatique en Image et Systèmes d’information, Centre National de Recherche Scientifique 5205, Ecole Centrale de Lyon, France</b></td><td>3</td></tr><tr><td><b>Department of Computer ScienceFace Aging Group Research Laboratory, Institute for Interdisciplinary Studies in Identity Sciences, University of North Carolina at Wilmington, Wilmington, NC, USA</b></td><td>3</td></tr><tr><td><b>Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA</b></td><td>3</td></tr><tr><td>Center for Research on Intelligent Perception and Computing</td><td>3</td></tr><tr><td><b>UC Merced, USA</b></td><td>3</td></tr><tr><td><b>Centre for Quantum Computation & Information Systems, Faculty of Engineering and IT, University of Technology, Sydney, 235 Jones Street, Ultimo, NSW, Australia</b></td><td>3</td></tr><tr><td><b>Samsung Research Center-Beijing, SAIT China Lab Beijing, China</b></td><td>3</td></tr><tr><td><b>IT - Instituto de Telecomunicações, University of Beira Interior, Portugal</b></td><td>3</td></tr><tr><td>Thiagarajar College of Engineering, Madurai, Tamilnadu, India</td><td>3</td></tr><tr><td><b>Center for Cognitive, Connected & Computational Imaging, College of Engineering & Informatics, NUI Galway, Ireland</b></td><td>3</td></tr><tr><td><b>Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Karlsruhe, Germany</b></td><td>3</td></tr><tr><td><b>Institute of Information Science, Beijing jiaotong University, Beijing, China</b></td><td>3</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Center for Automation Research, University of Maryland, College Park, 20742, USA</b></td><td>3</td></tr><tr><td><b>Hasso Plattner Institute, University of Potsdam, Prof.-Dr.-Helmert-Str. 2-3, 14482, Germany</b></td><td>3</td></tr><tr><td><b>Dalian University of Technology, School of Software Tuqiang St. 321, Dalian, 116620, China</b></td><td>3</td></tr><tr><td><b>Shenzhen Graduate School, Peking University, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, University of Central Florida, Orlando, 32816, United States of America</b></td><td>3</td></tr><tr><td><b>Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China</b></td><td>3</td></tr><tr><td><b>College of Computer Science and Technology, Jilin University, Changchun, China</b></td><td>3</td></tr><tr><td><b>University of Technology, Sydney</b></td><td>3</td></tr><tr><td><b>Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, China</b></td><td>3</td></tr><tr><td><b>Software School, Xiamen University, Xiamen, China</b></td><td>3</td></tr><tr><td><b>University of Nottingham, Ningbo China</b></td><td>3</td></tr><tr><td><b>National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University Chengdu, 610065, China</b></td><td>3</td></tr><tr><td><b>Institute of Forensic Science, Ministry of Justice, Shanghai 200063, China</b></td><td>3</td></tr><tr><td><b>Department of Information Engineering, University of Florence, Florence, Italy</b></td><td>3</td></tr><tr><td>Dept. of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan</td><td>3</td></tr><tr><td><b>West Virginia University, Morgantown, WV, USA</b></td><td>3</td></tr><tr><td><b>EUP Mataró, Spain</b></td><td>3</td></tr><tr><td><b>Université du Québec à Chicoutimi (UQAC)</b></td><td>3</td></tr><tr><td><b>Dept. of Computer Sciences, ASIA Team, Moulay Ismail University, Faculty of Science and Techniques, BP 509 Boutalamine 52000 Errachidia, Morocco</b></td><td>3</td></tr><tr><td>School of Electrical and Electronic Engineering, Singapore</td><td>3</td></tr><tr><td><b>Microsoft Research, Beijing, China</b></td><td>3</td></tr><tr><td><b>Northeastern University, Boston, USA</b></td><td>3</td></tr><tr><td><b>Center for Future Media and School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>3</td></tr><tr><td><b>Advanced Technologies Application Center, 7a #21406 b/ 214 and 216, P.C. 12200, Playa, Havana, Cuba</b></td><td>3</td></tr><tr><td><b>Artificial Vision Laboratory, National Taiwan University of Science and Technology</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India</b></td><td>3</td></tr><tr><td>Universidade Nova Lisboa, Lisboa, Portugal</td><td>3</td></tr><tr><td><b>Wuhan University, Wuhan, China</b></td><td>3</td></tr><tr><td><b>Key Laboratory of Machine Perception (Ministry of Education), Engineering Lab on Intelligent Perception for Internet of Things (ELIP), Shenzhen Graduate School, Peking University, China</b></td><td>3</td></tr><tr><td><b>Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China</b></td><td>3</td></tr><tr><td><b>Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China</b></td><td>3</td></tr><tr><td>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation Chinese Academy of Sciences, Beijing, China 100190</td><td>3</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, İstanbul Teknik Üniversitesi, İstanbul, Türkiye</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Jadavpur University, Kolkata, India</b></td><td>3</td></tr><tr><td><b>Indian Statistical Institute, Kolkata, India</b></td><td>3</td></tr><tr><td><b>Jiangsu University, Zhenjiang, China</b></td><td>3</td></tr><tr><td><b>Sharif University of Technology</b></td><td>3</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology Uttarakhand, Srinagar Garhwal, India</td><td>3</td></tr><tr><td>Dept. of Mediamatics, Delft Univ. of Technol., Netherlands</td><td>3</td></tr><tr><td><b>Disney Research Pittsburgh, Pittsburgh, PA, USA</b></td><td>3</td></tr><tr><td><b>Electrical and Computer Engineering</b></td><td>3</td></tr><tr><td><b>Video Analytics Laboratory, SERC, Indian Institute of Science, Bangalore, India</b></td><td>3</td></tr><tr><td><b>School of Electronics and Information Engineering, Tianjin University, Tianjin, China</b></td><td>3</td></tr><tr><td><b>Cornell University, USA</b></td><td>3</td></tr><tr><td>Department of Information Science and Engineering, Changzhou University, Changzhou, China</td><td>3</td></tr><tr><td><b>International Center of Excellence on Intelligent Robotics and Automation Research, National Taiwan University, Taiwan</b></td><td>3</td></tr><tr><td><b>Department of Informatics, University of Thessaloniki, 54124, Greece</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Dayton, Ohio, USA</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Windsor, Canada</b></td><td>3</td></tr><tr><td><b>Graduate School of Shenzhen, Tsinghua University, Beijing, China</b></td><td>3</td></tr><tr><td><b>Hanoi University of Science and Technology, Hanoi, Vietnam</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Korea</b></td><td>3</td></tr><tr><td><b>Institute of Computational Science, University of Lugano, Switzerland</b></td><td>3</td></tr><tr><td><b>Norwegian Biometrics Laboratory, NTNU - Gjøvik, Norway</b></td><td>3</td></tr><tr><td><b>Institute of Technology and Science, Tokushima University, 2-1 Minamijyousanjima, 770-8506, Japan</b></td><td>3</td></tr><tr><td><b>LTCI, CNRS, Télécom ParisTech, Université Paris-Saclay, 75013, France</b></td><td>3</td></tr><tr><td><b>National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>3</td></tr><tr><td><b>School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Dongchuan Road 800, Minhang District, Shanghai, 200240, China</b></td><td>3</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore</b></td><td>3</td></tr><tr><td><b>Multimedia and Intelligent Software Technology Beijing Municipal Key Lab., College of Computer Science, Beijing University of Technology Beijing, China.</b></td><td>3</td></tr><tr><td><b>Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany</b></td><td>3</td></tr><tr><td><b>Korea University</b></td><td>3</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, NSW, Australia</b></td><td>3</td></tr><tr><td><b>Shenzhen Key Laboratory of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>TCS Research, New Delhi, India</b></td><td>3</td></tr><tr><td><b>University of North Carolina Wilmington, Wilmington, NC</b></td><td>3</td></tr><tr><td><b>Faculty of Electrical Engineering, University of Ljubljana, Trzaska cesta 25, SI-1000 Ljubljana, Slovenia</b></td><td>3</td></tr><tr><td><b>Research Institute of Shenzhen, Wuhan University, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>Shanghai University</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Binghamton University, Binghamton, NY</b></td><td>3</td></tr><tr><td><b>Nanyang Technological University, Singapore, Singapore</b></td><td>3</td></tr><tr><td><b>New York University, New York, NY, USA</b></td><td>3</td></tr><tr><td><b>School of Electronics and Computer Science, University of Southampton, United Kingdom</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, University of Massachusetts Amherst, Amherst MA, 01003</b></td><td>3</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Xidian University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 27 Prague 6, Technická 2 Czech Republic</b></td><td>3</td></tr><tr><td><b>Computer Laboratory, University of Cambridge, United Kingdom</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>3</td></tr><tr><td>Institute for Infocomm Research, A*STAR, Singapore, Singapore</td><td>3</td></tr><tr><td><b>South China University of Technology, China</b></td><td>3</td></tr><tr><td><b>Visionlab, Heriot-Watt University, Edinburgh, UK</b></td><td>3</td></tr><tr><td><b>Institute for Infocomm Research, A*STAR, Singapore</b></td><td>3</td></tr><tr><td><b>Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea</b></td><td>3</td></tr><tr><td><b>Xerox Research Center, Webster, NY, USA</b></td><td>3</td></tr><tr><td>Ashikaga Institute of Technology, Ashikaga, Japan</td><td>3</td></tr><tr><td><b>Department of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, Tyne and Wear</b></td><td>3</td></tr><tr><td><b>College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan</b></td><td>3</td></tr><tr><td>Institute of Applied Computer Science, Kiel University of Applied Sciences, Kiel, Germany</td><td>3</td></tr><tr><td><b>School of Creative Technologies, University of Portsmouth, Portsmouth, POI 2DJ, UK</b></td><td>3</td></tr><tr><td><b>Université de Lyon, CNRS, INSA-Lyon, LIRIS, UMR5205, France</b></td><td>3</td></tr><tr><td><b>Faculty of Electronic Information and Electrical Engineering, School of Information and Communication Engineering, Dalian University of Technology, Dalian, China</b></td><td>3</td></tr><tr><td><b>Affectiva Inc., Waltham, MA, USA</b></td><td>3</td></tr><tr><td><b>Department of Electronics and Communication Engineering, Sun Yat-Sen University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea</b></td><td>3</td></tr><tr><td><b>Dept. of Electrical and Computer Engineering & Centre for Intelligent Machines, McGill University, Montreal, Quebec, Canada</b></td><td>3</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Surrey, UK</b></td><td>3</td></tr><tr><td><b>Computer Vision and Image Processing Lab, Institute for Integrated and Intelligent Systems, Griffith University, Australia</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA</b></td><td>3</td></tr><tr><td><b>Institute of Software, College of Computer, National University of Defense Technology, Changsha, Hunan, China, 410073</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Northeastern University, Boston, USA, 02115</b></td><td>3</td></tr><tr><td><b>AltumView Systems Inc., Burnaby, BC, Canada</b></td><td>3</td></tr><tr><td>Central China Normal University, Wuhan, China</td><td>3</td></tr><tr><td><b>Sapienza University of Rome</b></td><td>3</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b></td><td>3</td></tr><tr><td><b>Computer Vision Lab, Sungkyunkwan University Suwon, South Korea</b></td><td>3</td></tr><tr><td><b>Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Metropolitan Transportation, Beijing University of Technology, Beijing, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Vogt-Koelln-Strasse 30, 22527 Hamburg - Germany</b></td><td>3</td></tr><tr><td><b>Faculty of Engineering, Shinshu University, Nagano, Japan</b></td><td>3</td></tr><tr><td><b>Institute for Creative Technologies, University of Southern California, 12015 E Waterfront Dr, Los Angeles, CA, USA</b></td><td>3</td></tr><tr><td><b>National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, R.O.C</b></td><td>3</td></tr><tr><td><b>Vision Lab in Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, 23529</b></td><td>3</td></tr><tr><td><b>Center for Research of E-life DIgital Technology (CREDIT), Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan</b></td><td>3</td></tr><tr><td><b>Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea</b></td><td>3</td></tr><tr><td><b>E-Comm Research Lab, Infosys Limited, Bangalore, India</b></td><td>3</td></tr><tr><td><b>College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China</b></td><td>3</td></tr><tr><td>Chongqing University of Posts and Telecommunications Chongqing, China</td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Center for Biometrics and Security Research, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>3</td></tr><tr><td>School of Computer Science and Software Engineering University of Wollongong, Australia</td><td>3</td></tr><tr><td>Phonexia, Brno-Krlovo Pole, Czech Republic</td><td>3</td></tr><tr><td><b>Expert Systems, Modena, Italy</b></td><td>3</td></tr><tr><td><b>Chair of Complex & Intelligent Systems, University of Passau, Passau, Germany</b></td><td>3</td></tr><tr><td><b>Stanford University, Palo Alto, CA, USA</b></td><td>3</td></tr><tr><td>Department of Applied Mechanics, Chalmers University of Technology, SE-412 96 Göteborg, Sweden</td><td>3</td></tr><tr><td>Technische Universität München, Munich, Germany</td><td>3</td></tr><tr><td><b>Laboratory for Intelligent and Safe Automobiles, University of California, San Diego, USA</b></td><td>3</td></tr><tr><td><b>Toyota Research Institute</b></td><td>3</td></tr><tr><td><b>Image and Video Research Lab, Queensland University of Technology, 2 George Street, GPO Box 2434, Brisbane, QLD 4001, Australia</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Engineering, Nanjing University of Science and Technology</b></td><td>3</td></tr><tr><td><b>The University of Newcastle, NSW, Australia</b></td><td>3</td></tr><tr><td><b>Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro #1, Tonantzintla, Puebla, Mexico</b></td><td>3</td></tr><tr><td><b>NLPR, Institute of Automation, Chinese Academy of Sciences</b></td><td>3</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100190, China</b></td><td>3</td></tr><tr><td><b>Columbia University, New York, USA</b></td><td>3</td></tr><tr><td><b>Télécom Lille, CRIStAL UMR (CNRS 9189), France</b></td><td>3</td></tr><tr><td><b>IMPCA, Curtin University, Australia</b></td><td>3</td></tr><tr><td><b>Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, 22200 Besut, Terengganu, Malaysia</b></td><td>3</td></tr><tr><td><b>Concordia University</b></td><td>3</td></tr><tr><td><b>State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China</b></td><td>3</td></tr><tr><td>University of California, Los Angeles, CA Dept. of Electrical Engineering</td><td>3</td></tr><tr><td><b>University Of Electronic Science And Technology Of China, China</b></td><td>3</td></tr><tr><td><b>IBM Research</b></td><td>3</td></tr><tr><td>Academia Sinica, Taipei, Taiwan Roc</td><td>3</td></tr><tr><td><b>Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, SI-1000 Ljubljana, Slovenia</b></td><td>3</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, TX, USA</b></td><td>3</td></tr><tr><td><b>Center for Digital Media Computing, Software School, Xiamen University, Xiamen 361005, China</b></td><td>3</td></tr><tr><td><b>University of Milan, Italy</b></td><td>3</td></tr><tr><td><b>State Key Laboratory on Intelligent Technology and Systems, National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, China</b></td><td>3</td></tr><tr><td><b>School of Electronic and Information Engineering, South China University of Technology, Guangzhou, Guangdong, China</b></td><td>3</td></tr><tr><td>Dept. of Cybernetics and Artificial Intelligence, FEI TU of Košice, Slovak Republic</td><td>3</td></tr><tr><td><b>Department of Mathematics and Informatics, University of Florence, Florence, Italy</b></td><td>3</td></tr><tr><td><b>Key Lab of Intelligent Information Processing, Institute of Computer Technology, Chinese Academy of Science (CAS), Beijing, 100190, China</b></td><td>3</td></tr><tr><td>Image and Video Systems Lab, School of Electrical Engineering, KAIST, Republic of Korea</td><td>3</td></tr><tr><td><b>Evolutionary Computation Research Group, Victoria University of Wellington, PO Box 600, Wellington 6140, New Zealand</b></td><td>3</td></tr><tr><td><b>School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Center for Research on Intelligent Perception and Computing, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>3</td></tr><tr><td><b>Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, P.O.Box 217 7500 AE Enschede, The Netherlands</b></td><td>3</td></tr><tr><td><b>MindLAB Research Group, Universidad Nacional de Colombia, Colombia</b></td><td>3</td></tr><tr><td><b>IntelliView Technologies Inc., Calgary, AB, Canada</b></td><td>3</td></tr><tr><td><b>Department of Electronic Engineering, National Taipei University of Technology, Taipei, Taiwan</b></td><td>3</td></tr><tr><td>Information and media processing laboratories, NEC Corporation</td><td>3</td></tr><tr><td>Southern Illinois University at Carbondale, IL, USA</td><td>3</td></tr><tr><td><b>School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, 75080, USA</b></td><td>3</td></tr><tr><td><b>Dept. of Automation and Applied Informatics, Politehnica University of Timisoara, Romania</b></td><td>3</td></tr><tr><td><b>Queen Mary University of London</b></td><td>3</td></tr><tr><td>School of Automation and Electrical Engineering, University of Science and Technology Beijing, 100083, China</td><td>3</td></tr><tr><td><b>Michigan State University, East Lansing, 48824, USA</b></td><td>3</td></tr><tr><td><b>The Hong Kong Polytechnic University, Hong Kong, China</b></td><td>3</td></tr><tr><td><b>Peking University, China / Shanghai Jiao Tong University, China</b></td><td>3</td></tr><tr><td><b>Department of Electronics, AGH University of Science and Technology, Kraków, Poland</b></td><td>3</td></tr><tr><td>School of Software, Jiangxi Normal University, Nanchang, China</td><td>3</td></tr><tr><td>Department of Computer Science, Pontificia Universidad Cato´lica de Chile</td><td>3</td></tr><tr><td><b>Faculty of Information Technology, Ho Chi Minh City University of Science, VNU-HCM, District 5, Ho Chi Minh City, Vietnam</b></td><td>3</td></tr><tr><td>Fujitsu Laboratories, Kawasaki, Kanagawa, Japan</td><td>3</td></tr><tr><td>Department of Electronic and Computer Engineering National Taiwan University of Science and Technology</td><td>3</td></tr><tr><td><b>Georgia Institute of Technology, Atlanta, 30332-0250, USA</b></td><td>3</td></tr><tr><td><b>Tongji University, Shanghai, China</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Vision Laboratory, Old Dominion University, Norfolk, VA, USA</b></td><td>3</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia</b></td><td>3</td></tr><tr><td><b>School of Information Science and Engineering, Xiamen University, Xiamen 361005, China</b></td><td>3</td></tr><tr><td><b>University of California San Diego, USA</b></td><td>3</td></tr><tr><td><b>HCC Lab, Vision & Sensing Group, University of Canberra, Australia</b></td><td>3</td></tr><tr><td><b>Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Educational Software, Guangzhou University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA</b></td><td>3</td></tr><tr><td><b>School of physics and engineering, Sun Yat-Sen University, GuangZhou, China</b></td><td>3</td></tr><tr><td>New York University Abu Dhabi & NYU Tandon School of Engineering, Abu Dhabi, Uae</td><td>3</td></tr><tr><td>Intelligent Vision Research Lab, Department of Computer Science, Federal University of Bahia</td><td>3</td></tr><tr><td><b>FDNA inc., Herzliya, Israel</b></td><td>3</td></tr><tr><td><b>Department of Mathematics & Computer Science, Philipps-Universität Marburg, D-35032, Germany</b></td><td>3</td></tr><tr><td><b>Australian Center for Visual Technologies, and School of Computer Science, The University of Adelaide, Adelaide, Australia</b></td><td>3</td></tr><tr><td>Department of Electronic Measuring systems, Moscow Engineering Physics Institute, National Research Nuclear University MEPhI, Moscow, Russia</td><td>3</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798</b></td><td>3</td></tr><tr><td><b>IT - Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</b></td><td>3</td></tr><tr><td><b>National University of Defence Technology, Changsha 410000, China</b></td><td>2</td></tr><tr><td>National Ilan University, Ilan, Taiwan Roc</td><td>2</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Eskişehir Osmangazi Üniversitesi, Turkey</b></td><td>2</td></tr><tr><td><b>Elektrik - Elektronik Mühendisliği Bölümü, Atılım Üniversitesi, Ankara, Türkiye</b></td><td>2</td></tr><tr><td>China Electronics Standardization Institute, Beijing, 100007</td><td>2</td></tr><tr><td><b>School of Reliability and System Engineering, Science and Technology on Reliability and Environmental Engineering Laboratory, Beihang University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Kent State University, OH 44242, U.S.A.</b></td><td>2</td></tr><tr><td><b>Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India</b></td><td>2</td></tr><tr><td><b>Computational Biomedicine Lab, University of Houston</b></td><td>2</td></tr><tr><td><b>Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown WV 26506, USA</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, İstanbul Teknik Üniversitesi, İstanbul, Turkiye</b></td><td>2</td></tr><tr><td>Universidade Nova de Lisboa, Caparica, Portugal</td><td>2</td></tr><tr><td>Universidad Tecnica Federico Santa Maria, Department of Electronic Engineering, Valparaiso, Chile</td><td>2</td></tr><tr><td>Dept. of Comput. Syst., Univ. of Technol., Sydney, NSW, Australia</td><td>2</td></tr><tr><td><b>Harvard University, Cambridge, MA, USA</b></td><td>2</td></tr><tr><td><b>Michigan State University, East Lansing, MI, U.S.A.</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, National Tsing Hua University, Taiwan</b></td><td>2</td></tr><tr><td>Dept. of Comput. Sci., York Univ., UK</td><td>2</td></tr><tr><td><b>CSE, SUNY at Buffalo, USA</b></td><td>2</td></tr><tr><td><b>Department of Computer Engineering, Mahanakorn University of Technology, 140 Cheum-Sampan Rd., Nong Chok, Bangkok THAILAND 10530</b></td><td>2</td></tr><tr><td>The Australian National University RSCS, ANU, Canberra, Australia</td><td>2</td></tr><tr><td><b>University of Newcastle, Australia</b></td><td>2</td></tr><tr><td>Dept. of Computer Science, YiLi Normal College, Yining, China 835000</td><td>2</td></tr><tr><td>School of Computing and Communications, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia</td><td>2</td></tr><tr><td><b>DISI, University of Trento, Italy</b></td><td>2</td></tr><tr><td><b>LAPI, University Politehnica of Bucharest, Romania</b></td><td>2</td></tr><tr><td><b>University of Colorado at Colorado Springs, Colorado Springs, CO, USA</b></td><td>2</td></tr><tr><td><b>University of Twente, Enschede, Netherlands</b></td><td>2</td></tr><tr><td><b>Department of Mechanical Engineering, National Taiwan University, 10647, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Institution for Infocomm Research, Connexis, Singapore</b></td><td>2</td></tr><tr><td><b>Department of d’Informàtica, Universitat de València, Valencia, Spain</b></td><td>2</td></tr><tr><td><b>Toyota Research Institute, Cambridge, MA, USA</b></td><td>2</td></tr><tr><td><b>Research Centre for Computers, Communication and Social Innovation La Trobe University, Victoria - 3086, Australia</b></td><td>2</td></tr><tr><td><b>IBM Thomas J. Watson, Research Center, Yorktown Heights, New York 10598, USA</b></td><td>2</td></tr><tr><td><b>Institute of Computing, University of Campinas (UNICAMP), SP, 13083-852, Brazil</b></td><td>2</td></tr><tr><td><b>IFRJDL, Institute of Computing Technology, CAS, P.O.Box 2704, Beijing, China, 100080</b></td><td>2</td></tr><tr><td><b>Computer Science Department, University of Southern California, Los Angeles, 90089, United States of America</b></td><td>2</td></tr><tr><td><b>Department of Signal Processing, Tampere University of Technology, Tampere, Finland</b></td><td>2</td></tr><tr><td><b>JD Artificial Intelligence Research, Beijing, China</b></td><td>2</td></tr><tr><td><b>STARS team, Inria Sophia Antipolis-Méditerranée, Sophia Antipolis, France</b></td><td>2</td></tr><tr><td><b>Agency for Science, Technology and Research (A*STAR), Institute of High Performance Computing, Singapore</b></td><td>2</td></tr><tr><td><b>Delft University of Technology</b></td><td>2</td></tr><tr><td><b>Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA</b></td><td>2</td></tr><tr><td>Department of Electrical and Computer Engineering, Singapore</td><td>2</td></tr><tr><td>Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td><b>Department of Computer Science, Wayne State University, Detroit, MI, USA</b></td><td>2</td></tr><tr><td><b>Dept. of Computer Science, Yonsei University, Seoul, South Korea, 120-749</b></td><td>2</td></tr><tr><td><b>Division of Graduate Studies, Tijuana Institute of Technology, México</b></td><td>2</td></tr><tr><td><b>School of Engineering and Digital Arts, University of Kent, Canterbury, Kent CT2 7NT, United Kingdom</b></td><td>2</td></tr><tr><td>Instituto de Telecomunicações & Faculdade de Ciěncias da Universidade do Porto</td><td>2</td></tr><tr><td><b>Faculty of Science and Technology, University of Macau, Macau, China</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering and the Center for Automation Research, UMIACS, University of Maryland, College Park, MD</b></td><td>2</td></tr><tr><td><b>Visual Analysis of People (VAP) laboratory, Aalborg University, Denmark</b></td><td>2</td></tr><tr><td><b>Instituto de Telecomunicações, Instituto Superior Técnico, Universidade de Lisboa, Portugal</b></td><td>2</td></tr><tr><td><b>School of Computer Science, Northwestern Polytechnical University, Xi’an, China</b></td><td>2</td></tr><tr><td><b>Escuela Politecnica Superior, Universidad Autonoma de Madrid, Madrid, Spain</b></td><td>2</td></tr><tr><td><b>SUPELEC / IETR, Avenue de la Boulaie, 35576 Cesson Sevigne, France</b></td><td>2</td></tr><tr><td><b>Dept. of Computer Science & Engineering, University of South Florida, Tampa, 33620, United States of America</b></td><td>2</td></tr><tr><td>Department of Information Management, National Formosa University, Huwei, Yulin 632, Taiwan</td><td>2</td></tr><tr><td>Dept of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Kavala, Greece</td><td>2</td></tr><tr><td><b>Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Fraunhoferstrasse 1, 76131 Karlsruhe, Germany</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, New Jersey Institute of Technology, University Heights, Newark, New Jersey 07102, USA</b></td><td>2</td></tr><tr><td><b>Department of Electronic Engineering, Shanghai Jiao Tong University</b></td><td>2</td></tr><tr><td><b>College of Computer and Information, Hohai University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>Department of Information Systems and Cyber Security and the Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>2</td></tr><tr><td><b>Electronics & Telecommunications Research Institute (ETRI), Daejeon, Korea</b></td><td>2</td></tr><tr><td>University of Ulm, Ulm, Germany</td><td>2</td></tr><tr><td><b>Electrical and Computer Engineering Department, University of Windsor, Ontario, Canada N9B 3P4</b></td><td>2</td></tr><tr><td><b>National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, The University of Hong Kong</b></td><td>2</td></tr><tr><td>Dept. of Eng. Sci., Oxford Univ., UK</td><td>2</td></tr><tr><td><b>Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Adenauerring 4, Karlsruhe, Germany</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea</b></td><td>2</td></tr><tr><td><b>Facial Image Processing and Analysis Group, Institute for Anthropomatics, Karlsruhe Institute of Technology, D-76131 Karlsruhe, P.O. Box 6980 Germany</b></td><td>2</td></tr><tr><td><b>Delft University of Technology, Mekelweg 4, Netherlands</b></td><td>2</td></tr><tr><td>Human-Machines Interaction (HMI) Laboratory, Department of Industrial Informatics, TEI of Kavala, Kavala, Greece</td><td>2</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University</b></td><td>2</td></tr><tr><td>Dept. of ECE, Maryland Univ., College Park, MD, USA</td><td>2</td></tr><tr><td><b>Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China</b></td><td>2</td></tr><tr><td>Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey</td><td>2</td></tr><tr><td><b>National University of Defense and Technology</b></td><td>2</td></tr><tr><td><b>School of Computer Science, CECS, Australian National University, Australia</b></td><td>2</td></tr><tr><td>Electrical & Electronic Engineering Department, Mevlana University Konya, Turkey</td><td>2</td></tr><tr><td><b>Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA</b></td><td>2</td></tr><tr><td><b>Institute of Electronics, National Chiao Tung University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td>GIPSA Laboratory, Image and Signal Department, Grenoble Institute of Technology, Grenoble, France</td><td>2</td></tr><tr><td><b>Florida International University</b></td><td>2</td></tr><tr><td><b>Gradate School of Information Production and System, Waseda University, Kitakyushu, Japan 808-0135</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, India</td><td>2</td></tr><tr><td><b>Graduate School of Information, Production and Systems, Waseda University, Japan</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, National Taiwan Ocean University, No.2, Beining Rd., Keelung 202, Taiwan</td><td>2</td></tr><tr><td><b>Tampere University of Technology, Finland</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, National Chiao Tung University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Biodata Mining Group, Technical Faculty, Bielefeld University, Germany</b></td><td>2</td></tr><tr><td><b>Chungnam National University, Daejeon, South Korea</b></td><td>2</td></tr><tr><td>Bilgisayar Mühendisliği Bölümü, Deniz Harp Okulu, İstanbul, Türkiye</td><td>2</td></tr><tr><td><b>IETR, CNRS UMR 6164, Supelec, Cesson-Sevigne, France</b></td><td>2</td></tr><tr><td><b>Institute of Intelligent Systems and Robotics (ISIR), Pierre and Marie Curie University , Paris, France</b></td><td>2</td></tr><tr><td><b>University of Technology, Sydney, NSW, Australia</b></td><td>2</td></tr><tr><td>Statistical Machine Intelligence & LEarning, School of Computer Science & Engineering University of Electronic Science and Technology of China, 611731, China</td><td>2</td></tr><tr><td><b>Department of Computer Science and Information Engineering, College of Electrical Engineering and Computer Science, National Central University, Jhongli, Taiwan</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, 32610, Perak Malaysia</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore639798</b></td><td>2</td></tr><tr><td><b>West Virginia University</b></td><td>2</td></tr><tr><td><b>Czech Technical University in Prague, Prague, Czech Rep</b></td><td>2</td></tr><tr><td>Masaryk University, Brno, Czech Rep</td><td>2</td></tr><tr><td>Charles University, Prague, Czech Rep</td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada</td><td>2</td></tr><tr><td><b>Nanjing Children's Hospital Affiliated to Nanjing Medical University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>College of Telecommunications & Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China</b></td><td>2</td></tr><tr><td><b>School of Telecommunications Engineering, Xidian University, Xi’an, China</b></td><td>2</td></tr><tr><td><b>Nanjing University of Science and Technology, Xiaolingwei, Xuanwu, Nanjing, China</b></td><td>2</td></tr><tr><td><b>London Healthcare Sciences Centre, London, ON, Canada</b></td><td>2</td></tr><tr><td>Department of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Human Machines Interaction (HMI) Laboratory, 65404 Kavala, Greece</td><td>2</td></tr><tr><td><b>School of Electrical Engineering and Computer Science, Seoul National University, Korea</b></td><td>2</td></tr><tr><td><b>Jordan University of Science and Technology, Irbid, Jordan</b></td><td>2</td></tr><tr><td><b>College of Medical Information Engineering, Guangdong Pharmaceutical University, Guangzhou, China</b></td><td>2</td></tr><tr><td><b>University of Michigan</b></td><td>2</td></tr><tr><td><b>Biometric Technologies Laboratory, Department of Electrical and Computer Engineering, University of Calgary, Alberta, T2N 1N4 Canada</b></td><td>2</td></tr><tr><td><b>Morpho, SAFRAN Group, 11 Boulevard Galliéni 92130 Issy-Les-Moulineaux - France</b></td><td>2</td></tr><tr><td><b>Center for Machine Vision Research, University of Oulu, Finland</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Aalto University, Finland</b></td><td>2</td></tr><tr><td><b>Norwegian Biometrics Laboratory, Norwegian University of Science and Technology (NTNU), 2802 Gj⊘vik, Norway</b></td><td>2</td></tr><tr><td><b>International Institute of Information Technology (IIIT) Hyderabad, India</b></td><td>2</td></tr><tr><td><b>Computer Laboratory, University of Cambridge, Cambridge, UK</b></td><td>2</td></tr><tr><td><b>Department of Electronic Systems, Aalborg University, Denmark</b></td><td>2</td></tr><tr><td><b>Artificial Intelligence and Information Analysis Lab, Department of Informatics, Aristotle University of Thessaloniki, Greece</b></td><td>2</td></tr><tr><td>University of British Columbia Department of Electrical and Computer Engineering</td><td>2</td></tr><tr><td><b>Department of Computer Science, Swansea University, Swansea, UK</b></td><td>2</td></tr><tr><td><b>Computer Science and Technology, IIEST, Shibpur</b></td><td>2</td></tr><tr><td><b>Amirkabir University of Technology, Tehran, Iran</b></td><td>2</td></tr><tr><td><b>EURECOM, Sophia Antipolis, France</b></td><td>2</td></tr><tr><td>School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, USA</b></td><td>2</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, SEOUL, Republic of Korea</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, University of Califonia, San Diego</td><td>2</td></tr><tr><td><b>Department of Computer Science and Technology, Tsinghua University, Beijing</b></td><td>2</td></tr><tr><td>University of Missouri Department of Electrical and Computer Engineering Columbia, MO, USA</td><td>2</td></tr><tr><td><b>School of Electrical and Computer Engineering, RMIT University, Melbourne, Australia</b></td><td>2</td></tr><tr><td>Inf. Syst. Dept., Buckingham Univ., UK</td><td>2</td></tr><tr><td><b>Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China</b></td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA</td><td>2</td></tr><tr><td><b>Department of Computer Science, Edge Hill University</b></td><td>2</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh, PA, 15260, USA</b></td><td>2</td></tr><tr><td><b>The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA</b></td><td>2</td></tr><tr><td><b>National Central University, Taoyuan County, Taiwan</b></td><td>2</td></tr><tr><td>Department of Computer Science & Engineering, POSTECH, Pohang, Sourth Korea, 37673</td><td>2</td></tr><tr><td><b>Anhui University, HeFei, China</b></td><td>2</td></tr><tr><td><b>Signals and Systems Group, Faculty of EEMCS, University of Twente, the Netherlands</b></td><td>2</td></tr><tr><td><b>Research Center of Machine Learning and Data Analysis, School of Computer Science and Technology, Soochow University, Suzhou, China</b></td><td>2</td></tr><tr><td>Coursera and Stanford University</td><td>2</td></tr><tr><td><b>School of Computer Science, University of Windsor, Canada N9B 3P4</b></td><td>2</td></tr><tr><td><b>Laboratory Heudiasyc, University of Technology of Compiègne, BP 20529. F-60205, France</b></td><td>2</td></tr><tr><td><b>Dept. Electrical Engineering, National Taiwan University, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Bahçeşehir Üniversitesi, İstanbul, Turkey</b></td><td>2</td></tr><tr><td><b>University of Notre Dame</b></td><td>2</td></tr><tr><td><b>University of Ljubljana</b></td><td>2</td></tr><tr><td><b>Istanbul Technical University</b></td><td>2</td></tr><tr><td><b>Polytechnic School, University of Pernambuco, Recife, Brazil</b></td><td>2</td></tr><tr><td><b>Faculty of Technical Sciences, Singidunum University, Belgrade 11000, Serbia</b></td><td>2</td></tr><tr><td><b>Dept. of CSEE, University of Maryland, Baltimore County, Baltimore, MD 21250</b></td><td>2</td></tr><tr><td>Dept. of Electron. & Inf., Toyota Technol. Inst., Nagoya, Japan</td><td>2</td></tr><tr><td><b>Department of Computer Science, University of Maryland, College Park, MD</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, POSTECH, Pohang 790-784, Republic of Korea</td><td>2</td></tr><tr><td><b>School of Electronic Engineering and Computer Science, Queen Mary University of London, UK</b></td><td>2</td></tr><tr><td><b>University of the Witwatersrand</b></td><td>2</td></tr><tr><td><b>Star Technologies, USA</b></td><td>2</td></tr><tr><td>Dept. of Comput. Sci., New York State Univ., Binghamton, NY, USA</td><td>2</td></tr><tr><td>Dept. of Electrical Engineering, National Institute of Technology, Rourkela, India 769008</td><td>2</td></tr><tr><td><b>Division of Control, EEE, Nanyang Tech. Univ., Singapore</b></td><td>2</td></tr><tr><td><b>Department of Computer Science & Engineering, University of Ioannina, 45110, Greece</b></td><td>2</td></tr><tr><td><b>Jiangsu University of Science and Technology, Zhenjiang, China</b></td><td>2</td></tr><tr><td><b>University of Valladolid (Spain), Dep. Of Systems Engineering and Automatic Control, Industrial Engineering School</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Mangalore University, India</b></td><td>2</td></tr><tr><td><b>Department of Computer Education, Sungkyunkwan University, Seoul, Republic of Korea</b></td><td>2</td></tr><tr><td>Department of Computer Science, Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>2</td></tr><tr><td><b>Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, China</b></td><td>2</td></tr><tr><td><b>University of Pittsburgh, Pittsburgh, PA, USA</b></td><td>2</td></tr><tr><td><b>Xidian University, Xi'an, China</b></td><td>2</td></tr><tr><td><b>School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China</b></td><td>2</td></tr><tr><td>School of Computer Science and Technology, Tianjin University&Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China</td><td>2</td></tr><tr><td>NPU-VUB Joint AVSP Research Lab, School of Computer Science, Northwestern Polytechnical University (NPU) Shaanxi Key Lab on Speech and Image Information Processing, 127 Youyi Xilu, Xi'an 710072, China</td><td>2</td></tr><tr><td><b>CAS Center for Excellence in Brain Science and Intelligence Technology, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>Australian National University</b></td><td>2</td></tr><tr><td><b>Institute of Computing, University of Campinas (UNICAMP), Campinas, SP, 13083-852, Brazil</b></td><td>2</td></tr><tr><td><b>Sichuan Univ., Chengdu</b></td><td>2</td></tr><tr><td><b>Laboratory for Intelligent and Safe Automobiles, University of California San Diego, La Jolla, CA 92093 USA</b></td><td>2</td></tr><tr><td><b>Department of Computing, Imperial College London, London, 180 Queen’s Gate, UK</b></td><td>2</td></tr><tr><td><b>Australian Center for Visual Technologies, and School of Computer Science, University of Adelaide, Canberra, Australia</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisligi Bölümü, İstanbul Teknik Üniversitesi</b></td><td>2</td></tr><tr><td>Research&Advanced Technology Division of SAIC Motor Corporation Limited, Shanghai 201804, P.R China</td><td>2</td></tr><tr><td>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China</td><td>2</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>Departamento de Computação, Universidade Federal do Piauí, Teresina, Brasil</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Marmara Üniversitesi, İstanbul, Türkiye</b></td><td>2</td></tr><tr><td><b>Le2i FRE2005, CNRS, Arts et Métiers, Univ. Bourgogne Franche-Comté, UTBM, F-90010 Belfort, France</b></td><td>2</td></tr><tr><td><b>Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan</b></td><td>2</td></tr><tr><td><b>Department of Computing, Imperial College London, U.K.</b></td><td>2</td></tr><tr><td>Dept. of Computer Science and Information Engineering, Southern Taiwan University of Science and Technology, Tainan City, Taiwan</td><td>2</td></tr><tr><td><b>Corp. Res. & Dev., Toshiba Corp., Tokyo, Japan</b></td><td>2</td></tr><tr><td>Dept. of Electronics and Telecommunication Engg., KCT's Late G.N. Sapkal college of Engineering, Nashik, India</td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Gebze Teknik Üniversitesi, Kocaeli, 41400, Türkiye</b></td><td>2</td></tr><tr><td><b>State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China</b></td><td>2</td></tr><tr><td>Tencent Inc</td><td>2</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190</b></td><td>2</td></tr><tr><td><b>Faculty of Information Science and Technology (FIST), Multimedia University, Melaka, Malaysia</b></td><td>2</td></tr><tr><td><b>Fraunhofer IOSB, Fraunhoferstrasse 1, 76131 Karlsruhe, Germany</b></td><td>2</td></tr><tr><td>Facebook Inc., Menlo Park, CA, USA</td><td>2</td></tr><tr><td><b>Naval Research Laboratory, Washington DC</b></td><td>2</td></tr><tr><td>Computational Intelligence Lab, Institute of Informatics and Telecommunications, NCSR Demokritos, Athens, Greece</td><td>2</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, TX and Computational Intelligence Lab, Institute of Informatics and Telecommunications, NCSR Demokrit ...</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>SPAWAR Systems Center Pacific, San Diego, California, USA</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, National Taiwan University, Taiwan</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran</b></td><td>2</td></tr><tr><td><b>Artificial Vision Laboratory, Dept. of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan 106</b></td><td>2</td></tr><tr><td><b>Microsoft Corporation, Redmond, WA, USA</b></td><td>2</td></tr><tr><td>Dept. of Electrical Engineering, National Tsing-Hua University, Taiwan</td><td>2</td></tr><tr><td>Department Informatik, Hamburg University of Applied Sciences, Hamburg, Germany</td><td>2</td></tr><tr><td>Department Informatik, Hamburg University of Applied Sciences, Engineering and Computing, University of the West of Scotland</td><td>2</td></tr><tr><td><b>University of Siena, Siena, Italy</b></td><td>2</td></tr><tr><td>Elektronik ve Haberleşme Mühendisliği Bölümü, Yıldız Teknik Üniversitesi, İstanbul, Türkiye</td><td>2</td></tr><tr><td><b>Stony Brook University, Stony Brook, NY</b></td><td>2</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, Ultimo, NSW, Australia</b></td><td>2</td></tr><tr><td><b>Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan, China</b></td><td>2</td></tr><tr><td><b>Department of Artificial Intelligence, Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering of Systems, University of Zaragoza, Escuela Universitaria Politécnica de Teruel, Teruel, Spain</td><td>2</td></tr><tr><td><b>Department of DMC Engineering, Sungkyunkwan University, Suwon, South Korea</b></td><td>2</td></tr><tr><td>Department of Automation, North-China University of Technology, Beijing, China</td><td>2</td></tr><tr><td><b>University of Bern, Neubrückstrasse 10, Bern, Switzerland</b></td><td>2</td></tr><tr><td><b>Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong</b></td><td>2</td></tr><tr><td><b>Computer Science, Fudan University, Shanghai, 201203, China</b></td><td>2</td></tr><tr><td><b>Electronic Engineering and Computer Science, Queen Mary University, London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea</b></td><td>2</td></tr><tr><td><b>Swiss Federal, Institute of Technology, Lausanne (EPFL), Switzerland</b></td><td>2</td></tr><tr><td><b>Disney Research, CH</b></td><td>2</td></tr><tr><td>Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia</td><td>2</td></tr><tr><td><b>Water Optics Technology Pte. Ltd, Singapore</b></td><td>2</td></tr><tr><td><b>School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore</b></td><td>2</td></tr><tr><td><b>Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia</b></td><td>2</td></tr><tr><td><b>National Laboratory of Pattern Recognition, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China</b></td><td>2</td></tr><tr><td><b>Orange Labs International Center Beijing, Beijing, 100876, China</b></td><td>2</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>2</td></tr><tr><td>Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, P.R. China</td><td>2</td></tr><tr><td>Indian Statistical Insitute, Kolkata 700108</td><td>2</td></tr><tr><td>Centre for Secure Information Technologies, Queen’s University Belfast, Belfast, UK</td><td>2</td></tr><tr><td><b>National University of Defense Technology, Hunan, China</b></td><td>2</td></tr><tr><td><b>Rutgers University, Piscataway, USA</b></td><td>2</td></tr><tr><td>Wrocław University of Science and Technology, Wrocław, Poland</td><td>2</td></tr><tr><td><b>Norwegian Biometrics Lab, NTNU, Gj⊘vik, Norway</b></td><td>2</td></tr><tr><td><b>The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Canada</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology, University of Science and Technology of China</b></td><td>2</td></tr><tr><td><b>Zhejiang University, HangZhou, China</b></td><td>2</td></tr><tr><td>Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi, India</td><td>2</td></tr><tr><td>Department of Electronics and Communication Engineering Malaviya National Institute of Technology Jaipur, Rajasthan, India</td><td>2</td></tr><tr><td>Department of Electrical Engineering Malaviya National Institute of Technology Jaipur, Rajasthan, India</td><td>2</td></tr><tr><td><b>Center for Automation Research, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD, USA</b></td><td>2</td></tr><tr><td><b>School of EECS, Queen Mary University of London, UK</b></td><td>2</td></tr><tr><td><b>College of Software, Shenyang Normal University, Shenyang, China</b></td><td>2</td></tr><tr><td><b>Zhejiang University of Technology, Hangzhou, China</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology, Nanjing Normal University, China</b></td><td>2</td></tr><tr><td><b>University of Technology Sydney, Ultimo, NSW, Australia</b></td><td>2</td></tr><tr><td><b>Center for Special Needs Education, Nara University of Education, Takabatake-cho, Nara-shi, Nara, Japan</b></td><td>2</td></tr><tr><td>Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education, Chongqing, China</td><td>2</td></tr><tr><td><b>Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore</b></td><td>2</td></tr><tr><td><b>Samovar CNRS UMR 5157, Télécom SudParis, Université Paris-Saclay, Evry, France</b></td><td>2</td></tr><tr><td><b>Beijing E-Hualu Info Technology Co., Ltd, Beijing, China</b></td><td>2</td></tr><tr><td><b>Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University, Baoding 071002, China</b></td><td>2</td></tr><tr><td><b>Applied Informatics, Faculty of Technology, Bielefeld University, Germany</b></td><td>2</td></tr><tr><td>Osaka University Health Care Center, Japan</td><td>2</td></tr><tr><td><b>Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona, Spain</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Universitat Oberta de Catalunya, Barcelona, Spain</b></td><td>2</td></tr><tr><td><b>University of Groningen, Nijenborgh 9, 9747 AG, The Netherlands</b></td><td>2</td></tr><tr><td><b>University of Science and Technology of China, NO.443, Huangshan Road, Hefei, Anhui, China</b></td><td>2</td></tr><tr><td><b>Shenyang SIASUN Robot & Automation Co., LTD., Shenyang, China</b></td><td>2</td></tr><tr><td><b>State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Bahçeşehir Üniversitesi, İstanbul, Türkiye</b></td><td>2</td></tr><tr><td><b>Department of National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Science Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand</b></td><td>2</td></tr><tr><td><b>Queen Mary University of London, London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Academy of Broadcasting Science, Beijing, P.R. China</b></td><td>2</td></tr><tr><td><b>Engineering Lab on Intelligent Perception for Internet of Things (ELIP), Shenzhen Graduate School, Peking University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Key Laboratory of Machine Perception, Ministry of Eduction, Peking University, Beijing, China</b></td><td>2</td></tr><tr><td><b>College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey</b></td><td>2</td></tr><tr><td><b>Department of Information Engineering, The Chinese University of Hong Kong</b></td><td>2</td></tr><tr><td><b>School of Computing, Teesside University, Middlesbrough, UK</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Digital Technologies, Faculty of Engineering and Environment, Northumbria University, Newcastle, UK, NE1 8ST</b></td><td>2</td></tr><tr><td><b>Faculty of Telecommunications, Technical University of Sofia, Bulgaria</b></td><td>2</td></tr><tr><td><b>Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>Computer Science, University of Haifa, Carmel, 31905, Israel</b></td><td>2</td></tr><tr><td><b>Fernuniversitt in Hagen FUH Hagen, Germany</b></td><td>2</td></tr><tr><td><b>Research institute for Telecommunication and Cooperation, FTK, Dortmund, Germany</b></td><td>2</td></tr><tr><td><b>Core Technology Center, OMRON Corporation, Kyoto, Japan</b></td><td>2</td></tr><tr><td><b>College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 404100, China</b></td><td>2</td></tr><tr><td><b>College of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 404100, China</b></td><td>2</td></tr><tr><td><b>USP - University of São Paulo / ICMC, SSC - LRM (Mobile Robots Lab.), São Carlos, 13566-590, Brazil</b></td><td>2</td></tr><tr><td><b>Department of Automation, Tsinghua National Laboratory for Information Science and Technology (TNList), State Key Lab of Intelligent Technologies and Systems, Tsinghua University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Electric and Electronics, Selçuk University, Konya, Turkey</b></td><td>2</td></tr><tr><td><b>Research Center of Intelligent Robotics, Department of Automation, Shanghai Jiao Tong University, 200240, China</b></td><td>2</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, KAIST, Deajeon, Daejeon, Republic of Korea</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, Tafresh University, Tafresh, Iran</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Chittagong University of Engineering and Technology, Chittagong, 4349, Bangladesh</b></td><td>2</td></tr><tr><td><b>Department of Mechanical Engineering, Chittagong University of Engineering and Technology, Chittagong, 4349, Bangladesh</b></td><td>2</td></tr><tr><td><b>University of Ottawa, Ottawa, ON, Canada</b></td><td>2</td></tr><tr><td><b>Kochi University of Technology, Kochi, 782-8502, Japan</b></td><td>2</td></tr><tr><td><b>Hefei University of Technology, School of Computer and Information, Hefei, Anhui, 230601, China</b></td><td>2</td></tr><tr><td><b>Karlsruhe Institute of Technology, Institute for Anthropomatics, Karlsruhe, Germany</b></td><td>2</td></tr><tr><td><b>Chinese Academy of Sciences, Shenzhen, China</b></td><td>2</td></tr><tr><td><b>Pattern Recognition and Intelligent System Lab., Beijing University of Posts and Telecommunications, China</b></td><td>2</td></tr><tr><td><b>NCCU, USA</b></td><td>2</td></tr><tr><td><b>WVU, USA</b></td><td>2</td></tr><tr><td><b>University of Nottingham Malaysia Campus, Selangor Darul Ehsan, Malaysia</b></td><td>2</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, the Faculty of Engineering and Information Technology, University of Technology, Sydney, Ultimo, Australia</b></td><td>2</td></tr><tr><td>Shahid Bahonar University of Kerman Computer Engineering Department, Kerman, Iran</td><td>2</td></tr><tr><td><b>Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, University of Hawaii, Manoa, Honolulu, HI, 96822</b></td><td>2</td></tr><tr><td><b>Samsung Electronics, SAIT Suwon-si, Korea</b></td><td>2</td></tr><tr><td><b>Department of Automation, University of Science and Technology of China</b></td><td>2</td></tr><tr><td><b>Centre for Intelligent Sensing, Queen Mary University of London, London, U.K.</b></td><td>2</td></tr><tr><td><b>CETUC, Pontifical Catholic University of Rio de Janeiro, Brazil</b></td><td>2</td></tr><tr><td><b>İstanbul Teknik Üniversitesi, İstanbul, Türkiye</b></td><td>2</td></tr><tr><td><b>School of Electronic Engineering, Xidian University, Xi’an, China</b></td><td>2</td></tr><tr><td><b>Islamic Azad University, South Tehran Branch, Electrical Engineering Department, Iran</b></td><td>2</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT) & Università di Torino, Genova, Italy</td><td>2</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT) & Università degli Studi di Genova, Genova, Italy</td><td>2</td></tr><tr><td><b>Shenzhen Graduate School, Harbin Institute of Technology, China</b></td><td>2</td></tr><tr><td><b>Human Language Technology and Pattern Recognition Group, RWTH Aachen University</b></td><td>2</td></tr><tr><td><b>Rensselaer Polytechnic Institute, USA</b></td><td>2</td></tr><tr><td><b>Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran</b></td><td>2</td></tr><tr><td><b>Vision Lab, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, United Kingdom</b></td><td>2</td></tr><tr><td><b>Center for Machine Vision Research, Computer Science and Engineering, University of Oulu, Oulu, Finland</b></td><td>2</td></tr><tr><td><b>University of Southern California, Los Angeles, USA</b></td><td>2</td></tr><tr><td><b>University of Amsterdam, The Netherlands</b></td><td>2</td></tr><tr><td><b>Academia Sinica, Institute of Information Science, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Centre for Communication Systems Research, University of Surrey, Guildford, Surrey, United Kingdom</b></td><td>2</td></tr><tr><td>Norwegian Biometric Laboratory, Norwegian University of Science and Technology (NTNU), Gjøvik, Norway</td><td>2</td></tr><tr><td><b>School of Computer Engineering and Science, Shanghai University</b></td><td>2</td></tr><tr><td><b>Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong, China</b></td><td>2</td></tr><tr><td><b>Corp. Res. & Dev. Center, Toshiba Corp., Kawasaki, Japan</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology, Tianjin University, 300072, China</b></td><td>2</td></tr><tr><td><b>Department of Information & Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain</b></td><td>2</td></tr><tr><td><b>Computer Engineering, Rochester Institute of Technology, USA</b></td><td>2</td></tr><tr><td><b>University of Notre Dame, Notre Dame, Indiana</b></td><td>2</td></tr><tr><td>Department of Computer Applications, National Institute of Technology, Tiruchirappalli, India</td><td>2</td></tr><tr><td>B. Tech Graduate, ECE, MSIT, C-4 Janakpuri, New Delhi, India</td><td>2</td></tr><tr><td><b>Department of Electrical, Computer and IT Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran</b></td><td>2</td></tr><tr><td><b>Computer Vision Institute, School of Computer Science and Software Engineering, and the Shenzhen Key Laboratory of Spatial Information Smart Sensing and Services, Shenzhen University, Shenzhen, China</b></td><td>2</td></tr><tr><td><b>University of Tokyo, Tokyo, Japan</b></td><td>2</td></tr><tr><td><b>RSISE, Australian National University, Australia</b></td><td>2</td></tr><tr><td>San Diego State University, San Diego, CA, USA</td><td>2</td></tr><tr><td><b>University of Memphis, Memphis, TN</b></td><td>2</td></tr><tr><td><b>HumanRobot Interaction Research Center, Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea seojh</b></td><td>2</td></tr><tr><td><b>Panasonic Singapore Laboratories Pte Ltd (PSL), Tai Seng Industrial Estate 534415, Singapore</b></td><td>2</td></tr><tr><td><b>University of Texas at Arlington, Arlington, USA</b></td><td>2</td></tr><tr><td><b>Massachusetts General Hospital, Boston, MA, USA</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA</b></td><td>2</td></tr><tr><td><b>Dept. of Electrical and Electronics Engineering, Bahcesehir University, Istanbul, Turkey</b></td><td>2</td></tr><tr><td>MIT, Cambridge, MA, USA</td><td>2</td></tr><tr><td><b>Department of Computer Science, University of York, York, UK</b></td><td>2</td></tr><tr><td><b>Imaging Software Technol. Center, Fuji Photo Film Co. Ltd., Japan</b></td><td>2</td></tr><tr><td><b>Dept. of ECE & Digital Technology Center, University of Minnesota, USA</b></td><td>2</td></tr><tr><td><b>Shenzhen University, Shenzhen China</b></td><td>2</td></tr><tr><td><b>National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190, Beijing, China</b></td><td>2</td></tr><tr><td><b>Islamic University of Technology, Bangladesh</b></td><td>2</td></tr><tr><td><b>Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan, 70101, Taiwan</b></td><td>2</td></tr><tr><td><b>Technion</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Okayama University, Okayama, Japan</b></td><td>2</td></tr><tr><td><b>Cyprus University of Technology</b></td><td>2</td></tr><tr><td>Dept of Electronics and Communication, Manipal Institute Of Technology, Karnataka, India</td><td>2</td></tr><tr><td><b>University of Technology, Sydney, Sydney, Australia</b></td><td>2</td></tr><tr><td>LMU Munich, Germany</td><td>2</td></tr><tr><td>Polytechnic School of Pernambuco, University of Pernambuco, Recife-PE, Brazil</td><td>2</td></tr><tr><td><b>Dept. of Electrical Engineering, National Taiwan University, Taiwan</b></td><td>2</td></tr><tr><td><b>Research Center for Information Technology Innovation, Academia Sinica, Taiwan</b></td><td>2</td></tr><tr><td><b>University of Illinois at Urbana-Champaign, 201 N Goodwin, 61820, USA</b></td><td>2</td></tr><tr><td><b>Research School of Engineering, The Australian National University, Canberra, ACT, Australia</b></td><td>2</td></tr><tr><td><b>CyLab Biometrics Center and the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA</b></td><td>2</td></tr><tr><td><b>Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands</b></td><td>2</td></tr><tr><td><b>Department of Computing, Imperial College London, London, UK</b></td><td>2</td></tr><tr><td><b>Pittsburgh Univ., PA, USA</b></td><td>2</td></tr><tr><td><b>Computer Vision and Remote Sensing, Berlin University of Technology, Sekr. FR 3-1, Franklinstr. 28/29, 10587, Germany</b></td><td>2</td></tr><tr><td><b>Department of Information Engineering, the Chinese University of Hong Kong, Shatin</b></td><td>2</td></tr><tr><td>Başkent University, Ankara, TURKEY</td><td>2</td></tr><tr><td><b>Department of Signal Processing, Tampere University of Technology, Finland</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Ankara Yıldırım Beyazıt Üniversitesi, Ankara, Türkiye</b></td><td>2</td></tr><tr><td><b>Department of Computer and Information Science, University of Macau, Taipa, Macau</b></td><td>2</td></tr><tr><td>Department of Electronic and Communication Engineering, Universiti Tenaga Nasional Km 7, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia</td><td>2</td></tr><tr><td><b>Senior Member, IEEE, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk, 790-784, South Korea. phone: 82-54-279-2880, 2214; fax: 82-54-279-5594; e-mail: dreaming@postech.ac.kr, syoh@postech.ac.kr</b></td><td>2</td></tr><tr><td><b>Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk, 790-784, South Korea. phone: 82-54-279-2880, 2214; fax: 82-54-279-5594; e-mail: dreaming@postech.ac.kr</b></td><td>2</td></tr><tr><td><b>Center of Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland</b></td><td>2</td></tr><tr><td><b>Key Laboratory of Child Development and Learning Science (Ministry of Education), Research Center for Learning Science, Southeast University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China</b></td><td>2</td></tr><tr><td><b>Dirección General de la Guardia Civil - DGGC Madrid, Spain</b></td><td>2</td></tr><tr><td><b>School of Information Science and Technology, Huaqiao University, Xiamen, China</b></td><td>2</td></tr><tr><td><b>Computer Laboratory, University of Cambridge, UK</b></td><td>2</td></tr><tr><td><b>School of Automation, Southeast University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>Rutgers University, Piscataway</b></td><td>2</td></tr><tr><td><b>University of Hong Kong, China</b></td><td>2</td></tr><tr><td><b>Department of Automation, State Key Laboratory of Intelligent Technologies and Systems, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China</b></td><td>2</td></tr><tr><td><b>School of Electronics and Information Technology, Sun Yat-Sen University</b></td><td>2</td></tr><tr><td><b>Charles Sturt University, Wagga Wagga NSW, Australia</b></td><td>2</td></tr><tr><td>Sunway University, Selangor, Malaysia</td><td>2</td></tr><tr><td><b>Hexi University, Center for Information Technology, Zhangye, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Engineering, Rochester Institute of Technology, Rochester, NY, USA</b></td><td>2</td></tr><tr><td><b>School of Communication and Information Engineering, Shanghai University, Shanghai, China</b></td><td>2</td></tr><tr><td><b>Department of Communications and Computer Engineering, University of Malta, Msida, Malta</b></td><td>2</td></tr><tr><td><b>Multimedia Communications Dept., EURECOM, Sophia Antipolis, France</b></td><td>2</td></tr><tr><td>Northwestern Polytechnical University Xian, P. R. China</td><td>2</td></tr><tr><td><b>Northwestern Polytechnical University, Xian, P. R. China, and UNC-Charlotte, Charlotte, NC</b></td><td>2</td></tr><tr><td><b>Michigan State University, East Lansing, U.S.A.</b></td><td>2</td></tr><tr><td>Dept. of E & TC Engineering, Maharashtra Institute of Technology, Pune, India</td><td>2</td></tr><tr><td><b>Commonwealth Scientific and Industrial Research Organisation, Clayton South, Vic. , Australia</b></td><td>2</td></tr><tr><td><b>Speech, Audio, Image and Video Technology Laboratory, Queensland University of Technology, Brisbane, Australia</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology and the Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin, China</b></td><td>2</td></tr><tr><td><b>School of Electrical Engineering and Computer Science, Queen Mary University of London, London, U.K.</b></td><td>2</td></tr><tr><td><b>Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td>Dept. of ECE and Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td><b>Department of Computer Science, National Tsing Hua University, Taiwan, R.O.C</b></td><td>2</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Hong Kong</td><td>2</td></tr><tr><td>School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, 689-798, Korea</td><td>2</td></tr><tr><td>Dept. of Comp. Sci. and Inf. Eng, Chung Hua University, Hsinchu, Taiwan</td><td>2</td></tr><tr><td><b>Dept. of Comp. Sci, National Chiao Tung University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Department of Computing, Curtin University, Perth, Australia</b></td><td>2</td></tr><tr><td><b>HEUDIASYC Mixed Res. Unit, Compiegne Univ. of Technol., France</b></td><td>2</td></tr><tr><td><b>Università di Salerno v. Ponte don Melillo, 84084, Fisciano (IT)</b></td><td>2</td></tr><tr><td>Shanghai Jiao Tong University & Alibaba Group, Shanghai, China</td><td>2</td></tr><tr><td><b>National Taiwan University of Science and Technology, No.43, Keelung Rd., Sec.4, Da'an Dist., Taipei City 10607, Taiwan</b></td><td>2</td></tr><tr><td>School of Computer Science, Kyungpook National University, Buk-gu, Daegu, The Republic of Korea</td><td>2</td></tr><tr><td><b>Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China</b></td><td>2</td></tr><tr><td>Laboratory LAROSERI, Department of Computer Science, Faculty of Sciences, University of Chouaib Doukkali, El Jadida - Morocco</td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China</b></td><td>2</td></tr><tr><td><b>Computer Vision, Video and Image Processing (CvviP) Research Lab, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia</b></td><td>2</td></tr><tr><td><b>Microsoft Research Asia, China</b></td><td>2</td></tr><tr><td><b>Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering & Information Technology, University of Technology, Sydney, Australia</b></td><td>2</td></tr><tr><td>Microsoft Research India Pvt. Ltd, Bangalore, Karnataka, India</td><td>2</td></tr><tr><td><b>Indiana University Bloomington, Bloomington, IN, USA</b></td><td>2</td></tr><tr><td>Department of Electronics, University of Goa, India</td><td>2</td></tr><tr><td><b>Department of Computer Science, School of Science and Technology, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Graduate School of Science and Technology, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa</b></td><td>2</td></tr><tr><td><b>Multimedia Processing Laboratory, Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA</b></td><td>2</td></tr><tr><td><b>Electric Power Research Institute, State Grid Shanghai Electric Power Company Shanghai, 200093, China</b></td><td>2</td></tr><tr><td><b>South East European University, Tetovo, Macedonia</b></td><td>2</td></tr><tr><td><b>Computer Science and Engineering, Arizona State University, Tempe, AZ</b></td><td>2</td></tr><tr><td><b>Villanova University, Villanova, PA, USA</b></td><td>2</td></tr><tr><td><b>University of Technology Sydney, Sydney, Australia</b></td><td>2</td></tr><tr><td><b>School of EE, Xidian University, Xi'an 710071, China</b></td><td>2</td></tr><tr><td>Department of ECE, National Institute of Technology, Rourkela (Odisha), India</td><td>2</td></tr><tr><td><b>Korea Electronics Technology Institute</b></td><td>2</td></tr><tr><td><b>Computer Science and Engineering Dept., University of North Texas, Denton, TX, USA</b></td><td>2</td></tr><tr><td>Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China</td><td>2</td></tr><tr><td><b>Institute of Information Science, Beijing Jiaotong University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA</b></td><td>2</td></tr><tr><td><b>Computer Science and Engineering Michigan State University, East Lansing, USA</b></td><td>2</td></tr><tr><td><b>College of Information Science and Technology, Beijing Normal University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Organization of Advanced Science and Technology, Kobe University, Japan</b></td><td>2</td></tr><tr><td><b>Center for Research in Computer Vision, University of Central Florida, Orlando, USA</b></td><td>2</td></tr><tr><td><b>IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA</b></td><td>2</td></tr><tr><td><b>International Institute of Information Technology, Hyderabad, India</b></td><td>2</td></tr><tr><td><b>University of Illinois’ Advanced Digital Sciences Center, Singapore</b></td><td>2</td></tr><tr><td><b>Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland 20740 United States</b></td><td>2</td></tr><tr><td>B-DAT Laboratory, School of Information and Control, Nanjing University of Information and Technology, Nanjing, China</td><td>2</td></tr><tr><td><b>University of Cambridge, Cambridge, United Kingdom</b></td><td>2</td></tr><tr><td><b>Intelligent Data Center (IDC) and Department of Mathematics, Sun Yat-Sen University, Guangzhou, China</b></td><td>2</td></tr><tr><td><b>Jaypee Institute of Information Technology</b></td><td>2</td></tr><tr><td><b>Samsung Advanced Institute of Technology (SAIT), Republic of Korea</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Technology, Tsinghua University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Institute of Computing Technology, CAS, Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Beijing, China</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Engineering, University of Aizu, Tsuruga, Ikkimachi, Aizuwakamatsu, Japan</b></td><td>2</td></tr><tr><td><b>Comnuter Science Department, Hong Kong Baptist University</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA</b></td><td>2</td></tr><tr><td><b>Institute of Computing, University of Campinas, Campinas, SP, 13083-852, Brazil</b></td><td>2</td></tr><tr><td><b>Robotics Lab, Futurewei Technologies Inc., Santa Clara, USA</b></td><td>2</td></tr><tr><td><b>Institute of Automatic Control Engineering (LSR), TU München, Germany</b></td><td>2</td></tr><tr><td><b>Image Understanding and Knowledge-Based Systems, TU München, Germany</b></td><td>2</td></tr><tr><td><b>University of Delaware, Newark, DE</b></td><td>2</td></tr><tr><td><b>HRL Laboratories, LLC, Information Systems and Sciences Lab, Malibu, CA 90265 USA</b></td><td>2</td></tr><tr><td><b>Division of Computing Systems, School of Computer Engineering, Nanyang Technological University, Singapore, Singapore</b></td><td>2</td></tr><tr><td><b>School of Computer Science, Communication University of China, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA</b></td><td>2</td></tr><tr><td><b>Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, China</b></td><td>2</td></tr><tr><td>Thales Services, ThereSIS, Palaiseau, France</td><td>2</td></tr><tr><td>School of Electrical and Electronic Engineering, Tianjin University of Technology, China</td><td>2</td></tr><tr><td><b>Faculty of Computers and Information, Cairo University, Egypt</b></td><td>2</td></tr><tr><td><b>Dept. of Electrical and Computer Engineering, National University of Singapore</b></td><td>2</td></tr><tr><td><b>Department of Computing, the Hong Kong Polytechnic University, Hong Kong</b></td><td>2</td></tr><tr><td><b>Institute of Computing, University of Campinas, Campinas, SP, Brazil, 13083-852</b></td><td>2</td></tr><tr><td><b>Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China</b></td><td>2</td></tr><tr><td><b>CyLab Biometrics Center, Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA</b></td><td>2</td></tr><tr><td><b>La Trobe University, Australia</b></td><td>2</td></tr><tr><td><b>State key Laboratory of High Performance Computing, National University of Defense Technology, Changsha, Hunan, China, 410073</b></td><td>2</td></tr><tr><td><b>University of South Carolina, Columbia, SC, USA</b></td><td>2</td></tr><tr><td><b>Science and Engineering Faculty, Queensland University of Technology, Australia</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, Mepco Schlenk Engineering College, Sivakasi, India</td><td>2</td></tr><tr><td><b>Department of Computer Technology, Shanghai Jiao Tong University, Shanghai, China</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Software Engineering, The University of Western Australia, Nedlands, WA, Australia</b></td><td>2</td></tr><tr><td><b>National Tsing Hua University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Rutgers, The State University of New Jersey</b></td><td>2</td></tr><tr><td><b>Dhirubhai Ambani Institute of Information and Communication Technology, India</b></td><td>2</td></tr><tr><td><b>Aix Marseille Univ LIF/CNRS, France</b></td><td>2</td></tr><tr><td><b>Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, San Jose State University, San Jose, CA</b></td><td>2</td></tr><tr><td>IIIT Bangalore, India</td><td>2</td></tr><tr><td>Institut de Robòtica i Informàtica Industrial (CSIC-UPC)</td><td>2</td></tr><tr><td><b>TeV, Fondazione Bruno Kessler, Trento, Italy</b></td><td>2</td></tr><tr><td>Department of Computer Science, IT: Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>2</td></tr><tr><td>Xinjiang University, Urumqi, China</td><td>2</td></tr><tr><td><b>Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, People’s Republic of China</b></td><td>2</td></tr><tr><td><b>Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, 1 University Road, Tainan, Taiwan</b></td><td>2</td></tr><tr><td><b>New Jersey Institute of Technology, Department of Electrical & Computer Engineering, University Heights Newark, NJ 07102 USA</b></td><td>2</td></tr><tr><td><b>Korea Advanced Institute of Science and Technology</b></td><td>2</td></tr><tr><td><b>College of Communication Engineering, Chongqing University, Chongqing, China</b></td><td>2</td></tr><tr><td><b>Department of Forestry and Management of the Environment, Democritus University of Thrace, Orestiada, Greece</b></td><td>2</td></tr><tr><td>School of Computing Science and Engineering, VIT University, Vellore, India</td><td>2</td></tr><tr><td><b>School of Information Science, Japan Advanced Institute of Science and Technology, Asahidai 1-1, Nomi-shi, Ishikawa, Japan, 923-1211</b></td><td>2</td></tr><tr><td><b>Chinese Academy of Sciences, Beijing</b></td><td>2</td></tr><tr><td><b>Tsinghua University, Beijing</b></td><td>2</td></tr><tr><td><b>Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Artificial Intelligence Laboratory, University of Tsukuba, Japan</b></td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA</td><td>2</td></tr><tr><td><b>Brno University of Technology, Brno-střed, Czech Republic</b></td><td>2</td></tr><tr><td><b>Deutsche Welle, Bonn, Germany</b></td><td>2</td></tr><tr><td>GSI Universidad Polit-écnica de Madrid, Madrid, Spain</td><td>2</td></tr><tr><td><b>University of Waterloo, Canada</b></td><td>2</td></tr><tr><td><b>The University of Tokyo, Tokyo, Japan</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, University of Calgary, Calgary, Alberta, Canada</b></td><td>2</td></tr><tr><td><b>National Institute of Standards and Technology (NIST), Gaithersburg, MD</b></td><td>2</td></tr><tr><td><b>Räven AB, SE-411 14 Göteborg, Sweden</b></td><td>2</td></tr><tr><td><b>School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China</b></td><td>2</td></tr><tr><td><b>University of Illinois at Urbana-Champaign, Urbana, USA</b></td><td>2</td></tr><tr><td><b>School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138</b></td><td>2</td></tr><tr><td><b>The Rowland Insitute at Harvard, Harvard University, Cambridge, MA 02142</b></td><td>2</td></tr><tr><td><b>The Open University of Israel, Israel</b></td><td>2</td></tr><tr><td><b>Halmstad University, Halmstad, Sweden</b></td><td>2</td></tr><tr><td>Department of Electronic Engineering, Kwangwoon University, Seoul, Republic of Korea</td><td>2</td></tr><tr><td><b>Division of Information and Computer Engineering, Ajou University, Suwon, Republic of Korea</b></td><td>2</td></tr><tr><td><b>Department of Computer Engineering, Kyung Hee University, Suwon, Republic of Korea</b></td><td>2</td></tr><tr><td><b>School of Computer Science, Carnegie Mellon University, Pittsburgh, USA</b></td><td>2</td></tr><tr><td>Dept. of Appl. Phys. & Electron., Umea Univ., Sweden</td><td>2</td></tr><tr><td>Universidade Federal do Paraná, Curitiba, Brazil</td><td>2</td></tr><tr><td><b>Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR</b></td><td>2</td></tr><tr><td><b>Department of Radiology, University of Pennsylvania, Philadelphia, PA</b></td><td>2</td></tr><tr><td><b>Institute of VLSI Design, Zhejiang University, Hangzhou, China</b></td><td>2</td></tr><tr><td><b>Faculty of Engineering Technology, Hasselt University, Diepenbeek, Belgium</b></td><td>2</td></tr><tr><td><b>DUT-RU International School of Information and Software Engineering, Dalian University of Technology, Dalian, China</b></td><td>2</td></tr><tr><td><b>University of Barcelona, Barcelona, Spain</b></td><td>2</td></tr><tr><td>Università degli Studi di Verona, Verona, Italy</td><td>2</td></tr><tr><td>CEA, Gif-Sur-Yvette, France</td><td>2</td></tr><tr><td>UMR CNRS - Univ. Bourgogne, Dijon, France</td><td>2</td></tr><tr><td><b>Universita degli Studi di Palermo, Dipartimento di Ingegegneria Informatica, Viale delle Scienze, 90128, ITALY</b></td><td>2</td></tr><tr><td><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, USA</b></td><td>2</td></tr><tr><td>Mechatronic Engineering Department, Mevlana University, Konya, Turkey</td><td>2</td></tr><tr><td><b>Tokyo Metropolitan University, Hino, Tokyo 191-0065, Japan</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer, Engineering, University of Denver, Denver, CO 80208</b></td><td>2</td></tr><tr><td>TÜBİITAK-BİILGEM-UEKAE, Anibal Cad., P.K.74, 41470, Gebze-KOCAELİ, Turkey</td><td>2</td></tr><tr><td><b>State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China</b></td><td>2</td></tr><tr><td><b>School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China</b></td><td>2</td></tr><tr><td><b>Department of Electronic Engineering, Tsinghua University, Beijing 100084, P.R. China</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada</b></td><td>2</td></tr><tr><td>The 28th Research Institute of China Electronics Technology Group Corporation, China</td><td>2</td></tr><tr><td><b>Indian Statistical Institute, 203, B. T. Road, Kolkata 700108, India</b></td><td>2</td></tr><tr><td><b>Institute of Neural Information Processing, Ulm University, Ulm, Germany</b></td><td>2</td></tr><tr><td><b>Institute of VLSI Design, Zhejiang University</b></td><td>2</td></tr><tr><td><b>Faculty of Engineering Technology, University Hasselt</b></td><td>2</td></tr><tr><td><b>Massachusetts Institute of Technology, Cambridge, MA</b></td><td>2</td></tr><tr><td><b>Institute of Information Science, Academia Sinica, Taipei, Taiwan Roc</b></td><td>2</td></tr><tr><td><b>Institute of Information Science, Beijing Jiaotong University, 100044, China</b></td><td>2</td></tr><tr><td><b>Department of Computer and Information Sciences, Temple University</b></td><td>2</td></tr><tr><td><b>Department of Computing Sciences, Elon University</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Maryland, College Park, MD</b></td><td>2</td></tr><tr><td>Raytheon BBN Technologies, 10 Moulton St, Cambridge, MA</td><td>2</td></tr><tr><td><b>General Electric Global Research, 1 Research Circle, Niskayuna, NY</b></td><td>2</td></tr><tr><td><b>Concordia University, Montreal, QC, Canada</b></td><td>2</td></tr><tr><td><b>Charles Perkin Centre, Faculty of Medicine, University of Sydney, Australia</b></td><td>2</td></tr><tr><td><b>Charles Perkin Centre, Faculty of Engineering, University of Sydney, Australia</b></td><td>2</td></tr><tr><td><b>Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Nazarbayev University, Astana, Kazakhstan</b></td><td>2</td></tr><tr><td><b>Department of Information and Communication Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan</b></td><td>2</td></tr><tr><td><b>Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA</b></td><td>2</td></tr><tr><td><b>Tsinghua National Lab for Info. Sci. & Tech., Depart. of Computer Sci. & Tech., Tsinghua University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Harbin Institute of Technology</b></td><td>2</td></tr><tr><td><b>National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>2</td></tr><tr><td>School of Electrical Engineering and Computer Science at the University of Newcastle, Callaghan, NSW 2308, Australia</td><td>2</td></tr><tr><td><b>School of Electrical Engineering and Computing, University of Newcastle, Newcastle, Australia</b></td><td>2</td></tr><tr><td><b>School of Computer Science, University of Windsor, Windsor, Canada</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Engineering, Dankook University, Yongin, South Korea</b></td><td>2</td></tr><tr><td>Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India</td><td>2</td></tr><tr><td><b>KTH Royal Institute of Technology, Stockholm, Sweden</b></td><td>2</td></tr><tr><td><b>Division of Graduate Studies of Tijuana Institute Technology, Mexico</b></td><td>2</td></tr><tr><td>Pontifícia Universidade Católica do RS, Porto Alegre-RS, Brazil</td><td>2</td></tr><tr><td><b>Department of Psychology and the Center for Brain Science, Harvard University, Cambridge</b></td><td>2</td></tr><tr><td><b>School of Engineering and Applied Sciences, Department of Molecular and Cellular Biology, and the Center for Brain Science, Harvard University, Cambridge</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, The University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>2</td></tr><tr><td><b>Sch. of Infor. Sci. and Tech., Huizhou Unversity, Huizhou, China</b></td><td>2</td></tr><tr><td><b>Institute of Advanced Manufacturing Technology, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences, Ningbo, China</b></td><td>2</td></tr><tr><td><b>School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China</b></td><td>2</td></tr><tr><td>Waseda University The Graduate School of Information, Production and Systems 2-7, Hibikino, Wakamatsu-ku, Kitakyushu-shi, Fukuoka, Japan</td><td>2</td></tr><tr><td><b>London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Shenzhen VisuCA Key Lab / SIAT, Chinese Academy of Sciences, China</b></td><td>2</td></tr><tr><td><b>Department of Mathematics, Center for Computer Vision, Sun Yat-Sen University, Guangzhou, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Technology, Huaqiao University, Xiamen, China</b></td><td>2</td></tr><tr><td><b>Xiamen University, Fujian, China</b></td><td>2</td></tr><tr><td>Majority Report, France</td><td>2</td></tr><tr><td><b>Imaging Science and Engineering Laboratory Tokyo Institute of Technology Yokohama 226-8503, Japan</b></td><td>2</td></tr><tr><td>SITI Laboratory, National Engineering School of Tunis (ENIT), University of Tunis El Manar, Tunis, Tunisia</td><td>2</td></tr><tr><td>University of Montreal, Department of Computer Science and Operations Research (DIRO), 2920 Chemin de la tour, QC, Canada, H3C 3J7</td><td>2</td></tr><tr><td><b>College of Computer Science and Technology, Harbin Engineering University, Harbin, China</b></td><td>2</td></tr><tr><td><b>Keio University, Kanagawa, Japan</b></td><td>2</td></tr><tr><td><b>Microsoft Research, Haidian, Beijing, P. R. China</b></td><td>2</td></tr><tr><td><b>Video and Image Processing System Laboratory, School of Electronic Engineering, Xidian University , Xi'an, China</b></td><td>2</td></tr><tr><td><b>Department of Computing, Imperial College London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Robert BOSCH Research and Technology Center, Palo Alto, CA 94304, USA</b></td><td>2</td></tr><tr><td>Università di Salerno, Fisciano (SA), Italy</td><td>2</td></tr><tr><td>Advanced Technologies Application Center 7a #21406 b/ 214 and 216, P.C. 12200, Siboney Playa, Havana, Cuba</td><td>2</td></tr><tr><td><b>National Chung Hsing University, Taichung</b></td><td>2</td></tr><tr><td><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing</b></td><td>2</td></tr><tr><td>School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an, China</td><td>2</td></tr><tr><td><b>The University of Tokyo</b></td><td>2</td></tr><tr><td>Department of Sciences and Information Technology, University of Sassari, Viale Mancini 5, 07100 Sassari, Italy</td><td>2</td></tr><tr><td><b>Institute for Information Technology and Communications (IIKT), Otto-von-Guericke-University Magdeburg, D-39016, P.O. Box 4210 Germany</b></td><td>2</td></tr><tr><td><b>ISIR, CNRS UMR 7222, Universite Pierre et Marie Curie, Paris</b></td><td>2</td></tr><tr><td><b>National Taiwan University of Science and Technology, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Beijing Institute of Science and Technology Information</b></td><td>2</td></tr><tr><td><b>University of Maryland, College Park, MD, 20742</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, University of Rochester, Rochester, NY, USA</b></td><td>2</td></tr><tr><td>Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany</td><td>2</td></tr><tr><td><b>State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China</b></td><td>2</td></tr><tr><td><b>Electrical and Computer Engineering, Wayne State University, Detroit, Michigan 48202</b></td><td>2</td></tr><tr><td><b>Bahcesehir University, Istanbul, Turkey</b></td><td>2</td></tr><tr><td><b>University of Udine, Italy</b></td><td>2</td></tr><tr><td>Department of Computer Science and Information Engineering, National Formosa University, Yunlin 632, Taiwan</td><td>2</td></tr><tr><td>Broadcasting & Telecommunications, Convergence Media Research Department, Electronics and Telecommunications Research Institute, Daejeon, Korea</td><td>2</td></tr><tr><td><b>Keio University, Yokohama, Japan</b></td><td>2</td></tr><tr><td><b>Graduate Institute of Networking and Multimedia and the Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, USA</b></td><td>2</td></tr><tr><td><b>Innovation Center, Canon USA Inc., San Jose, California</b></td><td>2</td></tr><tr><td><b>University of Texas at San Antonio, San Antonio, Texas</b></td><td>2</td></tr><tr><td>Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td><b>Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA 24061, USA</b></td><td>2</td></tr><tr><td>FMV IŞIK Üniversitesi, Şile, Istanbul</td><td>2</td></tr><tr><td><b>Istanbul Technical University, Informatics Institute, 34469, Turkey</b></td><td>2</td></tr><tr><td><b>School of Mathematical Sciences, Anhui University, Hefei, China</b></td><td>2</td></tr><tr><td><b>Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48824, USA</b></td><td>2</td></tr><tr><td><b>Agency for Science, Technology and Research, Institute for Infocomm Research, Singapore</b></td><td>2</td></tr><tr><td><b>School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore</b></td><td>2</td></tr><tr><td><b>Artificial Vision Laboratory National Taiwan University of Science and Technology</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Engineering, Myongji University, Yongin 449-728, South Korea</b></td><td>1</td></tr><tr><td><b>Computational Imaging Laboratory, School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, USA</b></td><td>1</td></tr><tr><td>Lehrstuhl für Mustererkennung, FAU Erlangen – Nürnberg, Erlangen, Germany</td><td>1</td></tr><tr><td><b>College of Computer Science and Electronic Engineering, Hunan Key Laboratory of Dependable Systems and Network, Hunan University, Changsha, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, and ASRI, Seoul National University, Republic of Korea</b></td><td>1</td></tr><tr><td><b>Istanbul Technical University, Turkey</b></td><td>1</td></tr><tr><td><b>Sabanci University, Turkey</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Machine Perception(MOE), EECS, Peking University, Beijing, 100871</b></td><td>1</td></tr><tr><td>Nanjing University of Posts and Telecommunications, China</td><td>1</td></tr><tr><td><b>Information Sciences Institute, University of Southern California, Marina del Rey, USA</b></td><td>1</td></tr><tr><td><b>Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung, Taiwan</td><td>1</td></tr><tr><td><b>College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia</b></td><td>1</td></tr><tr><td><b>Griffith University, Australia</b></td><td>1</td></tr><tr><td>Laboratoire d’interprétation et de traitement d’images et vidéo, Polytechnique Montréal, Montreal, Canada</td><td>1</td></tr><tr><td>Laboratoire d’imagerie de vision et d’intelligence artificielle, École de technologie supérieure, Université du Québec, Montreal, Canada</td><td>1</td></tr><tr><td><b>Department of Multimedia Design, National Taichung University of Science and Technology, Taichung, Taiwan</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi, Taiwan</b></td><td>1</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, Surrey GU2 7XH, UK</b></td><td>1</td></tr><tr><td>University of Bern, Bern, Switzerland</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Denver, Denver, USA</b></td><td>1</td></tr><tr><td>School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, PR China</td><td>1</td></tr><tr><td>Department of Computer Science, University of California at Davis, Davis, USA</td><td>1</td></tr><tr><td><b>School of Computer Science, Fudan University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea</b></td><td>1</td></tr><tr><td><b>Korea Institute of Oriental Medicine, Daejeon, South Korea</b></td><td>1</td></tr><tr><td><b>Microsoft Research Asia, 49 Zhichun Road, Beijing, 100190, China</b></td><td>1</td></tr><tr><td>Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, China</td><td>1</td></tr><tr><td><b>School of Software Technology, Dalian University of Technology, Dalian, China</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Shri Shankaracharya Technical Campus, Bhilai, District-Durg, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi, India</td><td>1</td></tr><tr><td><b>Department of Information Engineering, The Chinese University of Hong Kong, China</b></td><td>1</td></tr><tr><td><b>Institute of Education, Xiamen University, Xiamen Shi, China</b></td><td>1</td></tr><tr><td>College of Artificial Intelligenge and Big Data, ChongQing University of Electronic Engineering, Chongqing, China</td><td>1</td></tr><tr><td><b>Harbin Engineering University, Harbin, Heilongjiang, 150001, China</b></td><td>1</td></tr><tr><td>Laboratoire Jean Kuntzmann, Grenoble, France</td><td>1</td></tr><tr><td><b>Electrical and Electronics Engineering Department, Eskisehir Osmangazi University, Eskisehir, Turkey</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Science and Computer Engineering, University of Louisville, KY, USA</b></td><td>1</td></tr><tr><td>Dept. of Advanced Technologies, Alcorn State University, MS, USA</td><td>1</td></tr><tr><td><b>Baiyun District Bureau of Justice, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Guangdong Key Laboratory of Information Security Technology, School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Department of Information Management, Tamkang University, New Taipei City, Taiwan</b></td><td>1</td></tr><tr><td>Department of Industrial Design, Tatung University, Taipei 104, Republic of China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Tatung University, Taipei 104, Republic of China</td><td>1</td></tr><tr><td><b>IBM T. J. Watson Research Center</b></td><td>1</td></tr><tr><td><b>AI Lab, TAL Education Group, College of Electronics and Information Engineering, Sichuan University, Chengdu, China</b></td><td>1</td></tr><tr><td><b>Institute of High Performance Computing, A*STAR, Singapore</b></td><td>1</td></tr><tr><td><b>3OmniVision Technologies Singapore Pte. Ltd., Singapore</b></td><td>1</td></tr><tr><td><b>Department of ECE, National University of Singapore, Singapore</b></td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Yangzhou University, Yangzhou, People’s Republic of China</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Nanjing University of Science & Technology, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Toronto Toronto, Canada</b></td><td>1</td></tr><tr><td><b>School of Information Science and Engineering, Yunnan University, Kunming, P. R. China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, Jiangnan University, Wuxi, China</b></td><td>1</td></tr><tr><td>School of Information Engineering, Yangzhou University, Yangzhou, China</td><td>1</td></tr><tr><td><b>Key Laboratory of Intelligent Processing, Institute of Computing Technology, CAS, Chinese Academy of Sciences (CAS), Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td>Res. Center for Learning Sci., Southeast Univ., Jiangsu, China</td><td>1</td></tr><tr><td>Eedoo Inc, Beijing, China</td><td>1</td></tr><tr><td><b>School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China</b></td><td>1</td></tr><tr><td>CSE, SUNY at Buffalo, USA and Southeast University, China</td><td>1</td></tr><tr><td><b>Knowledge Enterprise Development, Arizona State University, Tempe, 85287-5406 United States</b></td><td>1</td></tr><tr><td><b>Computer Science, Florida State University, Tallahassee, United States</b></td><td>1</td></tr><tr><td><b>Computing Informatics and Decision Systems Engineering, Arizona State University, Tempe, United States</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Northern British Columbia, Prince George, Canada</b></td><td>1</td></tr><tr><td><b>Speech, Audio, Image, and Video Technology Laboratory, Queensland University of Technology , Brisbane, Australia</b></td><td>1</td></tr><tr><td><b>Speech, Audio, Image, and Video Technology Laboratory, Queensland University of Technology, Brisbane, Australia</b></td><td>1</td></tr><tr><td><b>Commonwealth Scientific and Industrial Research Organization, Pullenvale, Australia</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh, Pittsburgh, PA , USA</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA</b></td><td>1</td></tr><tr><td><b>School of computer Science and Engineering, Nanyang Technological University, Singapore</b></td><td>1</td></tr><tr><td><b>Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore</b></td><td>1</td></tr><tr><td><b>Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India</b></td><td>1</td></tr><tr><td><b>Yonsei University, Seoul, South Korea</b></td><td>1</td></tr><tr><td><b>Multimedia University, Melaka, Malaysia</b></td><td>1</td></tr><tr><td>School of Information Technology and Engineering, VIT University, Vellore, India</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, New Jersey, 07030</b></td><td>1</td></tr><tr><td>Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881</td><td>1</td></tr><tr><td>Vulcan Inc, Seattle, WA 98104</td><td>1</td></tr><tr><td><b>Department of Computer Science, Hofstra University, Hempstead, NY 11549</b></td><td>1</td></tr><tr><td>Dept. of Computing, Curtin University of Technology, WA 6102, USA</td><td>1</td></tr><tr><td>School of Software, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td><b>University of Washington, Tacoma & Ghent University, Tacoma, WA, USA</b></td><td>1</td></tr><tr><td>University of California, Santa Cruz & Ghent University, Santa Cruz, CA, USA</td><td>1</td></tr><tr><td>Computer Vision Research lab, Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran</td><td>1</td></tr><tr><td><b>Language Technologies Institute, Carnegie Mellon University, Pittsburgh, PA</b></td><td>1</td></tr><tr><td><b>Center for OPTical Imagery Analysis and Learning, Northwestern Polytechnical University, Shaanxi, China</b></td><td>1</td></tr><tr><td><b>Beijing Etrol Technologies Co., Ltd, Beijing, China</b></td><td>1</td></tr><tr><td><b>Securics, Inc. Colorado Springs, CO, USA</b></td><td>1</td></tr><tr><td><b>Institute of Computing, University of Campinas (Unicamp) Campinas, SP, Brazil</b></td><td>1</td></tr><tr><td>HAN University of Applied Sciences, Arnhem, Netherlands</td><td>1</td></tr><tr><td>Faculty of Information Technology, Barrett Hodgson University, Karachi, Pakistan</td><td>1</td></tr><tr><td>Laboratoire Hubert Curien, UMR5516, Université Jean Monnet, Saint-Etienne, France</td><td>1</td></tr><tr><td>Université de Lyon, CNRS, LIRIS, UMR5205, Université Lyon 1, Lyon, France</td><td>1</td></tr><tr><td>Department of Electrical and Computer Engineering, Saginaw Valley State University, University Ctr, MI- 48710</td><td>1</td></tr><tr><td>TCTS Lab, Faculté Polytechnique de Mons, Belgium</td><td>1</td></tr><tr><td>Speech Technology Group, Technical University of Madrid, Spain</td><td>1</td></tr><tr><td>TALP Research Center, Universitat Politècnica de Catalunya, Spain</td><td>1</td></tr><tr><td><b>Electrical and Electronics Engineering Dept., Bogazici University, Turkey</b></td><td>1</td></tr><tr><td><b>AIIA Lab, Aristotle University of Thessaloniki, Greece</b></td><td>1</td></tr><tr><td>TELE Lab, Université catholique de Louvain, Belgium</td><td>1</td></tr><tr><td><b>DISI, University of Trento, Trento, Italy</b></td><td>1</td></tr><tr><td><b>LAPI, University Politehnica of Bucharest, Bucharest, Romania</b></td><td>1</td></tr><tr><td><b>IDIAP Research Institute, Martigny, Switzerland</b></td><td>1</td></tr><tr><td><b>University of Michigan, Ann, Arbor, MI USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Memorial University of Newfoundland, St. John’s, Canada</b></td><td>1</td></tr><tr><td>INRIA Grenoble-Rhône-Alpes Research Center, France</td><td>1</td></tr><tr><td><b>Institute of Radioelectronics, Warsaw University of Technology, Faculty of Electronics and Information Technology, ul. Nowowiejska 15/19, 00-665 Warsaw, Poland</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Rutgers University, Piscataway, New Jersey 08854, USA</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Information, Anhui Polytechnic University, Wuhu, China</b></td><td>1</td></tr><tr><td><b>Language Technologies Institute, Carnegie Mellon University, Pittsburgh, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Stanford University, Stanford, USA</b></td><td>1</td></tr><tr><td><b>School of Mathematics, Beihang University, Beijing, China</b></td><td>1</td></tr><tr><td>Department of Embedded Systems, Institute for Infocomm Research, Singapore</td><td>1</td></tr><tr><td><b>IBM Research, USA</b></td><td>1</td></tr><tr><td><b>IBM Hursley Labs, UK</b></td><td>1</td></tr><tr><td>E.T.S. Ingenieros Industriales, Universidad de Castilla-La Mancha Campus Universitario, Ciudad Real, Spain</td><td>1</td></tr><tr><td>Universidad de Las Palmas de Gran Canaria, SIANI, Edificio Central del Parque Científico-Tecnológico, Las Palmas, Spain</td><td>1</td></tr><tr><td><b>Monash University, Caulfield East, Australia</b></td><td>1</td></tr><tr><td>School of Math and Geospatial Sciences, Royal Melbourne Institute of Technology University , Melbourne, Australia</td><td>1</td></tr><tr><td><b>Department of Computer Science, Harbin Institute of Technology, China, 150001</b></td><td>1</td></tr><tr><td>Department of Computer Science and Application, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou, China</td><td>1</td></tr><tr><td>School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China</td><td>1</td></tr><tr><td><b>Computer Science Department, School of Information Science and Engineering, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213. Marios.Savvides@ri.cmu.edu</b></td><td>1</td></tr><tr><td><b>Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213. yunghui@cmu.edu</b></td><td>1</td></tr><tr><td><b>College of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Department of Software Engineering, King Saud University, Riyadh, Saudi Arabia</b></td><td>1</td></tr><tr><td><b>Institute of Information Technology, University of Dhaka, Dhaka, Bangladesh</b></td><td>1</td></tr><tr><td><b>Department of Information, The Third Affiliated Hospital, Sun Yat-sen University, China</b></td><td>1</td></tr><tr><td><b>OmniVision Technologies Singapore Pte. Ltd., Singapore</b></td><td>1</td></tr><tr><td><b>Electrical and Computer Engineering, Ryerson University, Toronto, Canada</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computing Engineering, Ryerson University, Toronto, Canada</b></td><td>1</td></tr><tr><td>Department of Electrical and Computer Engineering, Naresuan University, Muang, Thailand</td><td>1</td></tr><tr><td>Department of Computer Science, Christian-Albrechts University, Kiel, Germany</td><td>1</td></tr><tr><td>Engineering Lab on Intelligent Perception for Internet of Things, Peking University Shenzhen Graduate School, Shenzhen, China</td><td>1</td></tr><tr><td><b>MOE Key Laboratory of Machine Perception, Peking University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Eletrical and Computer Engineering Department, Drexel University, Philadelphia, USA</b></td><td>1</td></tr><tr><td><b>TCL Research America, San Jose, CA 95134, USA</b></td><td>1</td></tr><tr><td><b>Dept. of Eng. Sciences and Appl. Mathematics, Northwestern University, Evanston, IL 60208, USA</b></td><td>1</td></tr><tr><td>Delft University of Technology and Sensor Technology, Netherlands Defense Academy</td><td>1</td></tr><tr><td><b>GE Global Research</b></td><td>1</td></tr><tr><td><b>Xerox Research Center India, India</b></td><td>1</td></tr><tr><td><b>Palo Alto Research Center, Webster, NY</b></td><td>1</td></tr><tr><td><b>Facebook, Singapore</b></td><td>1</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Bahçeşehir Üniversitesi, Turkey</b></td><td>1</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Boğaziçi Üniversitesi, Turkey</b></td><td>1</td></tr><tr><td><b>School of Information Technologies, The University of Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td>School of Electrical Engineering and Automation, Qilu University of Technology, Jinan, China</td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China</td><td>1</td></tr><tr><td><b>School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Beijing Advanced Innovation Center for Imaging Technology, Beijing 100048, China</b></td><td>1</td></tr><tr><td><b>Lane Department of CSEE, West Virginia University, Morgantown, WV 26506, USA</b></td><td>1</td></tr><tr><td><b>Institute of Computing, University of Campinas, Campinas-SP, CEP, Brazil</b></td><td>1</td></tr><tr><td>Department of Electronics and Computing and the Electronics and Information Technology Research & Development Center, Universidade Federal do Amazonas, Manaus-AM, CEP, Brazil</td><td>1</td></tr><tr><td><b>National Chiao-Tung University, Hsinchiu, Taiwan</b></td><td>1</td></tr><tr><td><b>General Electric Global Research, Niskayuna, NY, USA</b></td><td>1</td></tr><tr><td><b>Institute of Computing, University of Campinas, Campinas, Brazil</b></td><td>1</td></tr><tr><td>University of California at Merced, Merced, USA</td><td>1</td></tr><tr><td><b>University of Adelaide, Adelaide, Australia</b></td><td>1</td></tr><tr><td>Technische Universität München, Garching, Germany</td><td>1</td></tr><tr><td><b>Department of Mathematics, Wayne State University, Detroit, MI, USA</b></td><td>1</td></tr><tr><td><b>Artificial Intelligence Key Laboratory, of Sichuan Province, Zigong, Sichuan, 643000, P. R. China</b></td><td>1</td></tr><tr><td>School of Big Data and Computer, Science, Guizhou Normal University, Guiyang, Guizhou, 550025, P. R. China</td><td>1</td></tr><tr><td><b>Centre for Robotics and Neural Systems, School of Computing Electronics and Mathematics, Plymouth University, Plymouth, PL4 8AA, UK</b></td><td>1</td></tr><tr><td><b>School of Electrical & Electronic Engineering, Yonsei University, Seoul, South Korea, 120-749</b></td><td>1</td></tr><tr><td><b>Inria Méditerranée, France</b></td><td>1</td></tr><tr><td><b>Microsoft Research, Mountain View, California</b></td><td>1</td></tr><tr><td>University of California at Santa Cruz, Santa Cruz, California</td><td>1</td></tr><tr><td><b>Massachusetts Institute of Technology, Cambridge, MA 02139, USA</b></td><td>1</td></tr><tr><td><b>The Rowland Institute at Harvard, Harvard University, Cambridge, MA 02142, USA</b></td><td>1</td></tr><tr><td><b>School of Electrical and Electronic Engineering, The University of Manchester, Manchester, UK</b></td><td>1</td></tr><tr><td>Network Center, Huizhou University, Huizhou, China</td><td>1</td></tr><tr><td><b>School of Advanced Computing, Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>School of Software, Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td>Faculty of Engineering, Computer Engineering Department, Akdeniz University, Dumlupinar Bulvari, Turkey</td><td>1</td></tr><tr><td>IRCICA, Parc Scientifique de la Haute Borne, Lille 1 University, Villeneuve d’Ascq, France</td><td>1</td></tr><tr><td><b>University of Bath</b></td><td>1</td></tr><tr><td>Data and Analytics Department, KPMG AGWPG, Düsseldorf, Germany</td><td>1</td></tr><tr><td><b>Faculty of Mathematics and Statistics, Hubei University, Wuhan, China</b></td><td>1</td></tr><tr><td><b>West Virginia University, Morgantown, WV</b></td><td>1</td></tr><tr><td><b>Ajou Univ.</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Transient Optics and Photonics, Center for OPTical IMagery Analysis and Learning, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China</b></td><td>1</td></tr><tr><td><b>School of Information Technology, Halmstad University, Halmstad, Sweden</b></td><td>1</td></tr><tr><td><b>Nokia Bell-Labs, Madrid, Spain</b></td><td>1</td></tr><tr><td>Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China</td><td>1</td></tr><tr><td>JiangSu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise, Suzhou, China</td><td>1</td></tr><tr><td>Université de Lorraine, LORIA, UMR 7503</td><td>1</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh, Pittsburgh, USA</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, The City College of New York, New York, USA</td><td>1</td></tr><tr><td>Robótica y Manufactura Avanzada, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ramos Arizpe, Mexico</td><td>1</td></tr><tr><td><b>Technicolor, Paris, France</b></td><td>1</td></tr><tr><td><b>MPI Informatics, Germany</b></td><td>1</td></tr><tr><td>School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, India</td><td>1</td></tr><tr><td>Dept. de Ciência da Computacão, Universidade Federal de Ouro Preto, MG Brazil</td><td>1</td></tr><tr><td><b>Interactive and Digital Media Institute, National University of Singapore, Singapore</b></td><td>1</td></tr><tr><td><b>Alibaba Group, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK</b></td><td>1</td></tr><tr><td><b>Shin-Guang Elementary School, Yulin 646, Taiwan</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Inha University, 253, Yong-Hyun Dong, Nam-Gu, Incheon, South Korea</td><td>1</td></tr><tr><td><b>Department of Computer Science, Brown University, Providence Rhode Island, 02912, USA</b></td><td>1</td></tr><tr><td><b>School of Management, New Jersey Institute of Technology, University Heights, Newark, New Jersey 07102, USA</b></td><td>1</td></tr><tr><td><b>SLAC National Laboratory, Stanford University, Stanford, USA</b></td><td>1</td></tr><tr><td><b>IWE II, RWTH Aachen University, Aachen, Germany</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore</b></td><td>1</td></tr><tr><td>Kodak Alaris Inc., Rochester, NY 14615, USA</td><td>1</td></tr><tr><td><b>School of Electrical Engineering, Nantong University, Nantong, China</b></td><td>1</td></tr><tr><td><b>Vesalis company, Clermont-Ferrand, France</b></td><td>1</td></tr><tr><td><b>University of Calgary, Calgary, T3G 2T6 AB, CANADA</b></td><td>1</td></tr><tr><td><b>University of Louisville, Louisville, KY 40292 USA</b></td><td>1</td></tr><tr><td><b>School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, USA</b></td><td>1</td></tr><tr><td><b>Max Planck Institute for Informatics, Saarbrucken, Germany</b></td><td>1</td></tr><tr><td><b>College of Information Engineering, Capital Normal University, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Automation, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, University of California, Riverside, Riverside CA, California 92521 United States</td><td>1</td></tr><tr><td><b>Art History, University of California, Riverside, Riverside, California United States</b></td><td>1</td></tr><tr><td><b>Electrical Engineering, University of California, Riverside, Riverside, California 92521 United States</b></td><td>1</td></tr><tr><td><b>University of Science & Technology (UST), Daejeon, Korea</b></td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Chongqing, China</b></td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Chongqing, Singapore</b></td><td>1</td></tr><tr><td><b>Universidade Estadual de Campinas, Cx.P. 6176 Campinas-SP, CEP 13084-971, Brazil</b></td><td>1</td></tr><tr><td>Department of CSE, Regional Campus of Anna University, Tirunelveli 627007, India</td><td>1</td></tr><tr><td><b>Embodied Emotion, Cognition and (Inter-)Action Lab, University of Hertfordshire, United Kingdom</b></td><td>1</td></tr><tr><td><b>Institute on Children Studies, University of Minho, Portugal</b></td><td>1</td></tr><tr><td><b>College of Aerospace and Material Engineering, National University of Defense Technology, Changsha, China</b></td><td>1</td></tr><tr><td><b>Air Force Research Lab, Rome, NY, 13441, USA</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>School of Computer Engineering, The Nanyang Technological University, Singapore</b></td><td>1</td></tr><tr><td><b>Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Fraunhoferstrasse 1, Karlsruhe, Germany</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Texas at San Antonio</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Rochester</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Tianjin University, China</b></td><td>1</td></tr><tr><td><b>Institute of Systems Science, National University of Singapore, Singapore, Singapore</b></td><td>1</td></tr><tr><td>Dalian Key Laboratory of Digital Technology for National Culture, Dalian Minzu University, Dalian, China</td><td>1</td></tr><tr><td><b>Institute of Systems Science, Northeastern University, Shenyang, China</b></td><td>1</td></tr><tr><td><b>Philips Research Eindhoven, HTC 34, Netherlands</b></td><td>1</td></tr><tr><td><b>Epson Research and Development Inc., San Jose, CA</b></td><td>1</td></tr><tr><td><b>GE Global Research, Bangalore, India</b></td><td>1</td></tr><tr><td><b>Advanced Media Lab. Samsung Advance Institute of Technology, Republic of Korea</b></td><td>1</td></tr><tr><td>Department of Business Planning & Information Systems, TEI of Crete, Agios Nikolaos, Greece</td><td>1</td></tr><tr><td><b>National Institute of Informatics, Japan</b></td><td>1</td></tr><tr><td>School of Information Technology Jawaharlal Nehru Technological University Hyderabad Andhra Pradesh, India</td><td>1</td></tr><tr><td><b>Department of CSE, Vignan University, Andhra Pradesh, India</b></td><td>1</td></tr><tr><td><b>University of North Carolina at Wilmington, USA</b></td><td>1</td></tr><tr><td><b>UNCW, USA</b></td><td>1</td></tr><tr><td><b>Department of EngineeringFaculty of Engineering and Science, University of Agder, Kristiansand, Norway</b></td><td>1</td></tr><tr><td><b>Yahoo Inc., New York, NY, USA</b></td><td>1</td></tr><tr><td>Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France</td><td>1</td></tr><tr><td><b>Queen Mary, University of London</b></td><td>1</td></tr><tr><td><b>Brunel University</b></td><td>1</td></tr><tr><td><b>Vision & Sensing Group, Faculty of Information Sciences and Engineering, University of Canberra, Australia</b></td><td>1</td></tr><tr><td><b>School of Engineering, CECS, Australian National University, Australia</b></td><td>1</td></tr><tr><td><b>Comput. Control Lab, Nanyang Technol. Univ., Singapore</b></td><td>1</td></tr><tr><td>School of Computer ScienceThe University of Adelaide</td><td>1</td></tr><tr><td><b>Instituto de Sistemas e Robótica, Instituto Superior Técnico, Lisboa, Portugal</b></td><td>1</td></tr><tr><td><b>University of Washington, Seattle, WA, USA</b></td><td>1</td></tr><tr><td>Shanghai Advanced Research Institute, CAS & Qiniu AI Lab, Shanghai, China</td><td>1</td></tr><tr><td>University of Lyon, LIRIS - CNRS, National Institute of Applied Sciences (INSA), Lyon, France</td><td>1</td></tr><tr><td>Sorbonne Universités, UPMC Univ Paris 06, CNRS UMR 7222, Institut des Systèmes Intelligents et de Robotique (ISIR), 4 place Jussieu, 75005 Paris, France</td><td>1</td></tr><tr><td><b>Shenzhen Graduate School, Harbin Institute of Technology, Bio-Computing Research Center, Shenzhen, China</b></td><td>1</td></tr><tr><td>Toyohashi University of Technology, Toyohashi, Japan</td><td>1</td></tr><tr><td><b>Department of Computing, Biometrics Research Centre, The Hong Kong Polytechnic University, Hong Kong</b></td><td>1</td></tr><tr><td><b>School of Computer Science, Nanjing University of Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td>Department of Informatics, King’s College London, Strand, London, UK</td><td>1</td></tr><tr><td><b>Centre for Quantum Computation & Intelligent Systems, University of Technology, Sydney, Australia</b></td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China</td><td>1</td></tr><tr><td><b>CSIE, National Cheng Kung University, Tainan, 701 Taiwan</b></td><td>1</td></tr><tr><td><b>CSIE, National Taiwan University of Science and Technology, Taipei, 106 Taiwan</b></td><td>1</td></tr><tr><td><b>Computer Science and Engineering Department, University of Texas at Arlington, Arlington, TX, USA</b></td><td>1</td></tr><tr><td><b>INSA CVL, Univ. Orléans, PRISME EA 4229, Bourges, France</b></td><td>1</td></tr><tr><td><b>Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FIN-33720 Tampere, Finland</b></td><td>1</td></tr><tr><td><b>LITIS, Universite de Rouen - INSA de Rouen, Rouen, FR</b></td><td>1</td></tr><tr><td>Department of Learning and Digital Technology, Fo Guang University, Yilan, Taiwan</td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong</b></td><td>1</td></tr><tr><td><b>Noah’s Ark Laboratory, Hong Kong</b></td><td>1</td></tr><tr><td><b>Noah.s Ark Laboratory and Hong Kong University of Science and Technology, Hong Kong</b></td><td>1</td></tr><tr><td><b>La Trobe University, Melbourne, Australia</b></td><td>1</td></tr><tr><td>BITS Pilani, India , India</td><td>1</td></tr><tr><td>College of Computer and Information Sciences, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia</td><td>1</td></tr><tr><td><b>COMSATS, Institute of Information Technology, Sahiwal, Pakistan</b></td><td>1</td></tr><tr><td>National University of Computer and Emerging Sciences, Islamabad, Islamabad, Pakistan</td><td>1</td></tr><tr><td><b>Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada</b></td><td>1</td></tr><tr><td>Research Team on Audio Visual Signal Processing (AVSP), Vrije Universiteit Brussel (VUB), Electronics and Informatics Department, VUB-ETRO, Pleinlaan 2, 1050 Brussel, Belgium</td><td>1</td></tr><tr><td><b>School of Engineering and Information Technology, Deakin University, Geelong, Australia</b></td><td>1</td></tr><tr><td><b>Griffith University, Queensland, Australia</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Texas at San Antonio, San Antonio, United States</b></td><td>1</td></tr><tr><td><b>Chongqing Institute of Green and Intelligent Technology, Chinese Academy of China, Hefei University of Technology, Hefei, China</b></td><td>1</td></tr><tr><td><b>Fac. of Mathematics and Computer Sciences, University of Science, Ho Chi Minh City, Viet Nam</b></td><td>1</td></tr><tr><td><b>Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td><b>LAMIA, University of French West Indies and Guiana, EA 4540, Pointe-à-Pitre, France</b></td><td>1</td></tr><tr><td><b>Institute of Intelligent Systems and Robotics (ISIR), Pierre and Marie Curie University, Paris, France</b></td><td>1</td></tr><tr><td><b>Xiamen University of Technology, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Chulalongkorn University Bangkok, Thailand</b></td><td>1</td></tr><tr><td>College of Computer Science and Technology of Huaqiao University Xiamen, Xiamen, China</td><td>1</td></tr><tr><td><b>School of Automation, Huazhong University of Science and Technology, Wuhan, China</b></td><td>1</td></tr><tr><td>Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Taiwan 640, R.O.C.</td><td>1</td></tr><tr><td><b>Bordeaux INP, LaBRI, PICTURA, UMR 5800, F-33400 Talence, France</b></td><td>1</td></tr><tr><td>Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng 475004, China</td><td>1</td></tr><tr><td><b>Department of Systems and Control Engineering, University of Malta, Msida, Malta</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Information Management, College of Management, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Computer Science and Information Engineering, College of Electrical Engineering and Computer Science, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td><b>Fundamental and Applied Science Department, Universiti Teknologi PETRONAS, Seri Iskandar, 32610, Perak Malaysia</b></td><td>1</td></tr><tr><td>Department of Statistics, University of California at Berkeley, Berkeley, USA</td><td>1</td></tr><tr><td>International Computer Science Institute, University of California at Berkeley, Berkeley, USA</td><td>1</td></tr><tr><td><b>Computer Science Department, Rensselaer Polytechnic Institute, Troy, USA</b></td><td>1</td></tr><tr><td>College of Information Science and Technology, Agricultural University of Hebei, Baoding, China</td><td>1</td></tr><tr><td><b>Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Sch. of Electr. Eng. & Comput. Sci., Newcastle Univ., NSW, Australia</b></td><td>1</td></tr><tr><td><b>University of Sassari, Computer Vision Laboratory, PolComing Viale Mancini, 5 07100 Sassari, Italy</b></td><td>1</td></tr><tr><td><b>Centre for Intelligent Machines, McGill University, Montréal, Canada</b></td><td>1</td></tr><tr><td><b>Azure Storage, Microsoft, Seattle, WA, USA</b></td><td>1</td></tr><tr><td>Department of Electronics Engineering, Mokpo National University, Republic of Korea</td><td>1</td></tr><tr><td><b>School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Republic of Korea</b></td><td>1</td></tr><tr><td><b>Institute of Computer Science and Technology, Peking university, Beijing, China</b></td><td>1</td></tr><tr><td>FX Palo Alto Laboratory</td><td>1</td></tr><tr><td>Department of Applied Optics and Photonics, University of Calcutta, Kolkata, India</td><td>1</td></tr><tr><td>Department of Electrical Engineering, Future Institute of Engineering and Management, Kolkata, India</td><td>1</td></tr><tr><td><b>School of Electronics and Information, Northwestern Polytechnical University, Xian, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of North Carolina, Charlotte, USA</b></td><td>1</td></tr><tr><td><b>Graduate Program on Electrical Engineering, Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil</b></td><td>1</td></tr><tr><td><b>Graduate Program on Electrical Engineering, University of Passo Fundo, Passo Fundo, Brazil</b></td><td>1</td></tr><tr><td><b>Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil</b></td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur, India</td><td>1</td></tr><tr><td><b>Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>1</td></tr><tr><td><b>Northwestern Polytechnical University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>Osaka University, Japan</b></td><td>1</td></tr><tr><td>Telecom Division, Centre de Développement des Technologies Avancées, Algiers, Algeria</td><td>1</td></tr><tr><td><b>Delft University of Technology, EEMCS, Delft, The Netherlands, reinierz@gmail.com</b></td><td>1</td></tr><tr><td><b>Imperial College London, Computing Department, London, U.K., m.pantic@imperial.ac.uk</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai, China</b></td><td>1</td></tr><tr><td>Departments of Medical Imaging and Medical Biophysics, University of Western Ontario, London, ON, Canada</td><td>1</td></tr><tr><td><b>St. Joseph’s Health Care, London, ON, Canada</b></td><td>1</td></tr><tr><td><b>Northumbria University, Newcastle upon Tyne, U.K.</b></td><td>1</td></tr><tr><td>Department of Medical Biophysics, University of Western Ontario, London, ON, Canada</td><td>1</td></tr><tr><td><b>School of Computer Science, University of Nottingham, Nottingham, UK</b></td><td>1</td></tr><tr><td><b>School of Electrical Engineering, Kookmin University, Seoul, Korea</b></td><td>1</td></tr><tr><td><b>University of Science and Technology of China, Hefei, P.R. China</b></td><td>1</td></tr><tr><td><b>The School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China</b></td><td>1</td></tr><tr><td>School of Computer Science, Shaanxi Normal University, Xi’an, China</td><td>1</td></tr><tr><td>Engineering Laboratory of Teaching Information Technology of Shaanxi Province, Xi’an, China</td><td>1</td></tr><tr><td>Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi’an, China</td><td>1</td></tr><tr><td><b>College of Automation, Shenyang Aerospace University, China</b></td><td>1</td></tr><tr><td><b>Université de Lyon, CNRS, Ecole Centrale de Lyon, LIRIS UMR5205, F-69134, France</b></td><td>1</td></tr><tr><td>College of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, P.R. China</td><td>1</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China</b></td><td>1</td></tr><tr><td><b>Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur, Malaysia</b></td><td>1</td></tr><tr><td>Nanyang Technological University School of Computer Engineering</td><td>1</td></tr><tr><td><b>College of Engineering, Shibaura Institute of Technology, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>Graduate School of Engineering, Shibaura Institute of Technology, Tokyo, Japan</b></td><td>1</td></tr><tr><td>Department of Electronics and Electrical Engineering, Indian Institute of Technology (IIT) Guwahati, Guwahati, India</td><td>1</td></tr><tr><td>Technology Section, Israel National Police, Jerusalem, Israel</td><td>1</td></tr><tr><td>Department of Electro-Optics Engineering, Ben-Gurion University, Beer Sheva, Israel</td><td>1</td></tr><tr><td>Department of Mathematics, JiaYing University, Meizhou, China</td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China</b></td><td>1</td></tr><tr><td>Hebei University of Technology, School of Science, Tianjin, P. R. China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, College of Engineering, and College of Computer and Information Science (Affiliated), Northeastern University, MA, USA</b></td><td>1</td></tr><tr><td><b>Chongqing University, Chongqing, China</b></td><td>1</td></tr><tr><td><b>Semnan University, Semnan, Iran</b></td><td>1</td></tr><tr><td>YiLi Normal College, Yining, China</td><td>1</td></tr><tr><td><b>Curtin University, Perth WA, Australia</b></td><td>1</td></tr><tr><td>Faculty of Electronic Information and Electrical Engineering, Dalian University, Dalian, China</td><td>1</td></tr><tr><td><b>Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan</b></td><td>1</td></tr><tr><td>Centre for Innovation in IT Services and Applications (iNEXT), University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td>Video Surveillance Laboratory, Guizhou University for Nationalities, Guiyang, China</td><td>1</td></tr><tr><td><b>Institut Mines-Telecom, Telecom ParisTech, CNRS LTCI, Sophia Antipolis, France</b></td><td>1</td></tr><tr><td>College of Arts and Sciences, Shanxi Agricultural University, Shanxi, China</td><td>1</td></tr><tr><td><b>Centre for Intelligent Systems Research, Deakin University, Geelong, VIC, Australia</b></td><td>1</td></tr><tr><td><b>Faculty of Engineering, Technology, and Built Environment, UCSI University, Kuala Lumpur, Malaysia</b></td><td>1</td></tr><tr><td><b>Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, PR China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Cornell University and Cornell NYC Tech</b></td><td>1</td></tr><tr><td><b>Dept of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark , NJ, USA</b></td><td>1</td></tr><tr><td><b>Microsoft Research , Redmond, WA, USA</b></td><td>1</td></tr><tr><td><b>Microsoft Visual Perception Laboratory, Zhejiang University, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>Coll. of Electron. & Inf., Northwestern Polytech. Univ., Xi'an, China</b></td><td>1</td></tr><tr><td><b>Nanyang Technological University and the Institute for Infocomm Research, Singapore</b></td><td>1</td></tr><tr><td><b>Intelligent Systems Laboratory, University of Bristol, Merchant Venturers Building, Woodland Rd, Bristol BS8 1UB, UK</b></td><td>1</td></tr><tr><td>IRDA Group, ADMIR Laboratory, Rabat IT Center, ENSIAS, CNRST (URAC29), Mohammed V University of Rabat, Morocco</td><td>1</td></tr><tr><td>LRIT, CNRST (URAC29), Mohammed V University of Rabat, Morocco</td><td>1</td></tr><tr><td><b>Ajou University</b></td><td>1</td></tr><tr><td>Queen’s University, Kingston, Canada</td><td>1</td></tr><tr><td>University of Science Technology, Wuhan, China</td><td>1</td></tr><tr><td>Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia</td><td>1</td></tr><tr><td>University at Qatar, Doha, Qatar</td><td>1</td></tr><tr><td>University of Istanbul, Istanbul, Turkey</td><td>1</td></tr><tr><td><b>Institute for Information and System Sciences and Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an 710049, PR China</b></td><td>1</td></tr><tr><td><b>Faculty of Applied Mathematics, Guangdong University of Technology, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Faculty of Information Science and Technology, Sun Yat-Sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Tuen Mun, Hong Kong</td><td>1</td></tr><tr><td>PolyU Shenzhen Research Institute, Shenzhen, China</td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Loughborogh</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering and Electronics, University of Liverpool</b></td><td>1</td></tr><tr><td><b>University of Bristol, Bristol, United Kingdom</b></td><td>1</td></tr><tr><td>German National Library of Science and Technology & Leibniz Universität Hannover, Hannover, Germany</td><td>1</td></tr><tr><td>University of Applied Sciences Jena, Jena, Germany</td><td>1</td></tr><tr><td>Department of Creative IT Engineering, POSTECH, Pohang, South Korea, 37673</td><td>1</td></tr><tr><td><b>Viterbi School of Engineering, University of Southern California, Los Angeles, CA</b></td><td>1</td></tr><tr><td><b>Centre for Multimedia Signal Processing and Department of Computing, Hong Kong Polytechnic University, Flat PQ717, Kowloon, Hung Hom, Hong Kong</b></td><td>1</td></tr><tr><td>Department of Computer Science, University of Western Ontario, London, Canada</td><td>1</td></tr><tr><td><b>University of Pittsburgh, USA</b></td><td>1</td></tr><tr><td><b>Anhui University, HeFei, China and Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td><b>Rensselaer Polytechnic Institute, Troy, NY, USA</b></td><td>1</td></tr><tr><td>Vision Laboratory, LARSyS, University of the Algarve, Faro, Portugal</td><td>1</td></tr><tr><td><b>Donghua University, China</b></td><td>1</td></tr><tr><td>Department of Information Management, Yuan Ze University, Taoyuan, China</td><td>1</td></tr><tr><td><b>AI Speech Ltd., Suzhou, China</b></td><td>1</td></tr><tr><td><b>Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China</b></td><td>1</td></tr><tr><td>DICGIM, Universitá degli Studi di Palermo, V.le delle Scienze, Ed. 6, 90128 Palermo, Italy</td><td>1</td></tr><tr><td>Department of Computer Engineering, Karadeniz Technical University, Trabzon, Turkey</td><td>1</td></tr><tr><td>Department of Computer Technologies, Trabzon Vocational School, Karadeniz Technical University, Trabzon, Turkey</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, Kyung Hee University, Yongin, South Korea</b></td><td>1</td></tr><tr><td>Stanford University and Coursera</td><td>1</td></tr><tr><td>Dept. of Comput. Sci. & Info. Eng., National Yunlin Univ. of Science & Technology, Taiwan</td><td>1</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, İstanbul Üniversitesi, Turkey</b></td><td>1</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Bahçeşehir Üniversitesi, İstanbul, Turkey</b></td><td>1</td></tr><tr><td><b>Institute of Industrial Science, The University of Tokyo, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td>Faculty of Mathematics and Statistics, Hubei Key Laboratory of Applied Mathematics, Hubei University, Wuhan, China</td><td>1</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom. k.messer@surrey.ac.uk</b></td><td>1</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom. j.kittler@surrey.ac.uk</b></td><td>1</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom. x.zou@surrey.ac.uk</b></td><td>1</td></tr><tr><td><b>University of Twente, Human Media Interaction Group, Enschede, The Netherlands</b></td><td>1</td></tr><tr><td>Biometric and Imaging Processing Laboratory (BIPLab)</td><td>1</td></tr><tr><td><b>University of Naples Federico II</b></td><td>1</td></tr><tr><td><b>Warsaw University of Technology</b></td><td>1</td></tr><tr><td>Research and Academic Computer Network (NASK)</td><td>1</td></tr><tr><td><b>SensoMotoric Instruments (SMI)</b></td><td>1</td></tr><tr><td><b>Maastricht University</b></td><td>1</td></tr><tr><td><b>Università di Salerno Italy</b></td><td>1</td></tr><tr><td><b>University of Southampton</b></td><td>1</td></tr><tr><td><b>University of Beira Interior, IT: Instituto de Telecomunicações</b></td><td>1</td></tr><tr><td>Philips Applied Technologies, Eindhoven, Netherlands</td><td>1</td></tr><tr><td><b>Delft University of Technology, Delft, Netherlands</b></td><td>1</td></tr><tr><td>Philips Research Eindhoven, Eindhoven, Netherlands</td><td>1</td></tr><tr><td>Key Lab Complex System & Intelligence Science, Institute of Automation, Chinese Academy of Science, Beijing, China</td><td>1</td></tr><tr><td>College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China</td><td>1</td></tr><tr><td><b>State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China</b></td><td>1</td></tr><tr><td><b>SAP Innovation Center Networks, Singapore</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td>National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis, Nizhny Novgorod, Russia</td><td>1</td></tr><tr><td><b>Bioinformatics Institute, A∗STAR, Singapore</b></td><td>1</td></tr><tr><td>Emory University School of Medicine, Atlanta, USA</td><td>1</td></tr><tr><td><b>School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA</b></td><td>1</td></tr><tr><td>Department of Radiology and Imaging Sciences, Winship Cancer Institute, Emory University School of Medicine, Atlanta, USA</td><td>1</td></tr><tr><td><b>iCV Research Group, Institute of Technology, University of Tartu, 50411, Estonia</b></td><td>1</td></tr><tr><td><b>Dept. Mathematics and Informatics, University of Barcelona, Computer Vision Center, Spain</b></td><td>1</td></tr><tr><td><b>Institute of Technology, University of Tartu, 50411, Estonia</b></td><td>1</td></tr><tr><td><b>Amazon.com Cambridge, MA, USA</b></td><td>1</td></tr><tr><td>Dept. of EMPH, Icahn School of Medicine at Mount Sinai, New York, NY 10029</td><td>1</td></tr><tr><td><b>Dept. of ENME College Park, University of Maryland, College Park, MD, 20742</b></td><td>1</td></tr><tr><td><b>Eskişehir Osmangazi Üniversitesi, Bilgisayar Mühendisliği Bölümü, Eskişehir, Türkiye</b></td><td>1</td></tr><tr><td><b>Anadolu Üniversitesi, Elek., Elektronik Mühendisliği Bölümü, Eskişehir, Türkiye</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Texas at San Antonio, San Antonio, TX</b></td><td>1</td></tr><tr><td>Electrical-Electronics Engineering Department, Izmir University of Economics, Balcova, Turkey</td><td>1</td></tr><tr><td><b>Electrical-Electronics Engineering Department, Firat University, Elazig, Turkey</b></td><td>1</td></tr><tr><td><b>Mechatronics Engineering Department, Firat University, Elazig, Turkey</b></td><td>1</td></tr><tr><td>Department of Computer Science, Solapur University, Solapur, India</td><td>1</td></tr><tr><td><b>Vision Semantics Ltd, UK</b></td><td>1</td></tr><tr><td><b>Rutgers University, USA</b></td><td>1</td></tr><tr><td><b>Computer Science, SUNY Stony Brook, Stony Brook, United States</b></td><td>1</td></tr><tr><td>Computer Vision Research Group, School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia</td><td>1</td></tr><tr><td><b>Department of Mathematics, Colorado State University, Fort Collins, CO 80523-1874 U.S.A. peterson@math.colostate.edu</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, Colorado State University, Fort Collins, CO 80523-1874 U.S.A. kirby@math.colostate.edu</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, Colorado State University, Fort Collins, CO 80523-1874 U.S.A. chang@math.colostate.edu</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Faculty of Engineering, Urmia university, Urmia, Iran</b></td><td>1</td></tr><tr><td>Department of Information Technology, Netaji Subhas Engineering College, Kolkata, India</td><td>1</td></tr><tr><td>Computer Engineering College, Jimei University, Xiamen, China</td><td>1</td></tr><tr><td>Fujian Key Laboratory of the Brain-like Intelligent Systems, Xiamen, China</td><td>1</td></tr><tr><td>School of Information, Hunan University of Humanities, Science and Technology, Loudi, China</td><td>1</td></tr><tr><td><b>Cognitive Science Department, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td>Al Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia</td><td>1</td></tr><tr><td>School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Korea</td><td>1</td></tr><tr><td><b>Department of Computer Science, COMSATS, Institute of Information Technology, Sahiwal, Pakistan</b></td><td>1</td></tr><tr><td><b>The University of Electro-Communications, Japan</b></td><td>1</td></tr><tr><td><b>Institute for Infocomm Research, A-star, Singapore</b></td><td>1</td></tr><tr><td><b>Inst. Dalle Molle d'Intelligence Artificielle Perceptive, Martigny, Switzerland</b></td><td>1</td></tr><tr><td><b>Transmural Biotech, Barcelona, Spain</b></td><td>1</td></tr><tr><td><b>George Mason University, Fairfax, VA 22030</b></td><td>1</td></tr><tr><td>Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea</td><td>1</td></tr><tr><td><b>Computational Biomedicine Lab, University of Houston, 4800 Calhoun Rd., Houston, TX 77204, USA</b></td><td>1</td></tr><tr><td><b>Purdue University, West Lafayette, IN, USA</b></td><td>1</td></tr><tr><td><b>Moshanghua Tech Company, Ltd., Beijing, China</b></td><td>1</td></tr><tr><td><b>College of Information Engineering, Xiangtan University, Xiangtan, China</b></td><td>1</td></tr><tr><td><b>CARTIF Centro Tecnológico, Robotics and Computer Vision Division, Boecillo (Valladolid, Spain)</b></td><td>1</td></tr><tr><td><b>University of California, San Diego</b></td><td>1</td></tr><tr><td><b>School of Software Engineering, South China University of Technology, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>School of Computer Science, South China Normal University, Guangzhou, China</b></td><td>1</td></tr><tr><td>Dept. of Computer Science and Information Engineering, Providence University, Taichung, Taiwan</td><td>1</td></tr><tr><td>360 AI Institute, Beijing, China</td><td>1</td></tr><tr><td><b>Tencent YouTu Lab, Tencent Shanghai, China</b></td><td>1</td></tr><tr><td><b>Sun Yat-sen University, China</b></td><td>1</td></tr><tr><td><b>Centeye, Inc.</b></td><td>1</td></tr><tr><td><b>Center for Optical Imagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China</b></td><td>1</td></tr><tr><td><b>Institute of Information and Control, Hangzhou Dianzi University, China</b></td><td>1</td></tr><tr><td><b>Hong Kong Baptist University and BNU-HKBU United International College</b></td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Research Lab, Vrije Universitiet Brussel (VUB), Department of Electronics & Informatics (ETRO) Pleinlaan 2, 1050 Brussel, Belgium</td><td>1</td></tr><tr><td><b>Department of Computer Science, School of Information Science and Engineering, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>School of Communication and Information Engineering, Shanghai University</b></td><td>1</td></tr><tr><td>IRISA, University of Rennes 1</td><td>1</td></tr><tr><td><b>INRIA Rennes-Bretagne-Atlantique</b></td><td>1</td></tr><tr><td><b>Advanced Digital Sciences Center, University of Illinois at Urbana-Champaign, Singapore</b></td><td>1</td></tr><tr><td><b>International Institute of Information Technology, Hyderabad, Telangana, India</b></td><td>1</td></tr><tr><td><b>College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China</b></td><td>1</td></tr><tr><td><b>Shenzhen Graduate School, Harbin Institute of Technology, 518055, China</b></td><td>1</td></tr><tr><td>Research Institution of Intelligent Control and Testing, Graduate School of Tsinghua University at Shenzhen, 518055, China</td><td>1</td></tr><tr><td>Commonwealth Scientific and Industrial Research Organization (CSIRO)</td><td>1</td></tr><tr><td><b>University of Canberra, Austrlia</b></td><td>1</td></tr><tr><td><b>B-DAT Lab, School of Information and Control, Nanjing University of Information Science and Technology, No. 219, Ningliu Road, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Rutgers University, 110 Frelinghuysen Road, Piscataway</b></td><td>1</td></tr><tr><td><b>Ocean University of China, Teaching Center of Fundamental Courses, Qingdao, China</b></td><td>1</td></tr><tr><td>Indiana University-Bloomington, USA</td><td>1</td></tr><tr><td>Key Laboratory of Medical Image Computing (Northeastern University), Ministry of Education, Shenyang, China</td><td>1</td></tr><tr><td><b>School of Information Science and Engineering, Northeastern University, Shenyang, China</b></td><td>1</td></tr><tr><td>Clínica Otocenter, Teresina, Piauí, Brasil</td><td>1</td></tr><tr><td>Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing, China</td><td>1</td></tr><tr><td>Nanjing University of Posts and Telecommunications, Nanjing, China</td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The State University of New York at Buffalo, New York, USA</b></td><td>1</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Trakya Üniversitesi, Edirne, Türkiye</b></td><td>1</td></tr><tr><td>Grupo de Aplicacion de Telecomunicaciones Visuales, Universidad Politecnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain</td><td>1</td></tr><tr><td>Department of Management Information Systems, Universität Regensburg, Universitätsstr. 31, 93053 Regensburg, Germany</td><td>1</td></tr><tr><td><b>Amrita E-Learning Research Laboratory, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, India</b></td><td>1</td></tr><tr><td>Department of Computer Science, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India</td><td>1</td></tr><tr><td>Amrita E-Learning Research Laboratory and the Department of Computer Science, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India</td><td>1</td></tr><tr><td><b>IKERBASQUE, Basque Foundation for Science, and the University of the Basque Country, San Sebastian, Spain</b></td><td>1</td></tr><tr><td><b>Computer Vision Center, Edifici “O” - Campus UAB, 08193 Bellaterra (Barcelona), Spain</b></td><td>1</td></tr><tr><td><b>Amazon Research, Berlin, Germany</b></td><td>1</td></tr><tr><td><b>DISI-Alma Mater Studiorum, Università di Bologna, Bologna, Italy</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China</b></td><td>1</td></tr><tr><td>Department of ECE, PEC University of Technology, Chandigarh, India</td><td>1</td></tr><tr><td>Biomedical Instrumentation (V-02), CSIR-Central Scientific Instruments Organisation (CSIO)|, Chandigarh, India</td><td>1</td></tr><tr><td>CEERI, Pilani, India</td><td>1</td></tr><tr><td>MNIT, Jaipur, India</td><td>1</td></tr><tr><td><b>Samsung Advanced Institute of Technology, Samsung Electronics, Gyeonggi-do, Korea</b></td><td>1</td></tr><tr><td><b>Department of Information Engineering, University of Florence, Firenze, Italy</b></td><td>1</td></tr><tr><td><b>Carnegie Mellon University, Pittsburgh, USA</b></td><td>1</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td>Department of Arts and Humanities, College of Business, Arts and Social Sciences, Brunel University London, Uxbridge, UK</td><td>1</td></tr><tr><td><b>Product/Industrial Design, Northumbria School of Design, Northumbria University, Newcastle upon Tyne, UK</b></td><td>1</td></tr><tr><td>Department of Design, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, India</td><td>1</td></tr><tr><td><b>The Organization of Advanced Science and Technology, Kobe University, Kobe, Japan</b></td><td>1</td></tr><tr><td><b>RIEB, Kobe University, Kobe, Japan</b></td><td>1</td></tr><tr><td>NTT Service Evolution Laboratories, Kanagawa, Japan</td><td>1</td></tr><tr><td><b>Tsinghua National Lab for Information Science and Technology, Beijing, China</b></td><td>1</td></tr><tr><td><b>Universidad Argentina de la Empresa (UADE), Lima 717, Buenos Aires, Argentina</b></td><td>1</td></tr><tr><td><b>Columbia University, NEW YORK, NY, USA</b></td><td>1</td></tr><tr><td>Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia</td><td>1</td></tr><tr><td><b>US Army Research Laboratory, 2800 Powder Mill Rd, Adelphi, MD 20783, USA</b></td><td>1</td></tr><tr><td>Dept. of Comput. Sci., North Carolina Univ., Wilmington, NC, USA</td><td>1</td></tr><tr><td><b>Institute of Applied Mathematics, AMSS, Chinese Academy of Sciences, Beijing 100190</b></td><td>1</td></tr><tr><td><b>Research Center of Precision Sensing and Control, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190</b></td><td>1</td></tr><tr><td><b>Biometrics Engineering Research Center, Yonsei University, Seoul, Korea</b></td><td>1</td></tr><tr><td>University of Washington &Microsoft, Seattle, WA, USA</td><td>1</td></tr><tr><td><b>Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK</b></td><td>1</td></tr><tr><td>Departamento de Informtica e Matemtica Aplicada/University of Rio Grande do Norte, Natal, Brazil</td><td>1</td></tr><tr><td>Computer Engineering Department, Girne American University, Kyrenia, Cyprus 90</td><td>1</td></tr><tr><td><b>School of Engineering and Digital Arts, University of Kent, Canterbury, U.K.</b></td><td>1</td></tr><tr><td><b>Cornell University, New York, NY, USA</b></td><td>1</td></tr><tr><td>Cornell University & Facebook Inc., New York, NY, USA</td><td>1</td></tr><tr><td><b>Office of Naval Research, Arlington</b></td><td>1</td></tr><tr><td>School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, China</td><td>1</td></tr><tr><td>Fujian Provincial Key Laboratory of Information Processing and Intelligent Control, Fuzhou, China</td><td>1</td></tr><tr><td>School of Technology, Nanjing Audit University, Nanjing, China</td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Microsoft Research, Redmond, WA</b></td><td>1</td></tr><tr><td>Adobe Research Department, Adobe Systems Inc, San Jose, CA</td><td>1</td></tr><tr><td><b>Department of Computer Science, National Chung Cheng University, Chiayi, Taiwan</b></td><td>1</td></tr><tr><td><b>School of Information and Control Engineering, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Microsoft, Redmond, WA</b></td><td>1</td></tr><tr><td><b>BIWI, ETH Zurich Zurich, Switzerland</b></td><td>1</td></tr><tr><td><b>Video Analytics Lab, SERC, Indian Institute of Science, Bangalore, India</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, National Chung Hsing University, Taiwan</b></td><td>1</td></tr><tr><td>Integrated Circuits and Electronics Laboratory, Department of Engineering, Aarhus University, Denmark</td><td>1</td></tr><tr><td>Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology (ICT), CAS, Beijing, China</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., California Inst. of Technol., Pasadena, CA, USA</td><td>1</td></tr><tr><td>Utechzone Co. Ltd., New Taipei City, Taiwan 235</td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, PR China</b></td><td>1</td></tr><tr><td>Department of Cognitive Science, University of California, San Diego, CA, USA</td><td>1</td></tr><tr><td><b>Department of Communication Engineering, Shanghai University, Shanghai, China</b></td><td>1</td></tr><tr><td>Department of Electronic Engineering Shanghai Jiao Tong University</td><td>1</td></tr><tr><td><b>Institute of Communication Engineering, National Tsing-Hua University, Taiwan</b></td><td>1</td></tr><tr><td>Innovations Kontakt Stelle (IKS) Hamburg, Hamburg University of Applied Sciences</td><td>1</td></tr><tr><td>School of Engineering and Computing, University of the West of Scotland</td><td>1</td></tr><tr><td>Computer Science Department, Central Washington University (CWU)</td><td>1</td></tr><tr><td>ICT Center, CSIRO</td><td>1</td></tr><tr><td><b>CSE Department, Regional Campus, Anna University, Tirunelveli, India</b></td><td>1</td></tr><tr><td>Technische Universität München, München, Germany</td><td>1</td></tr><tr><td><b>National defense acquisition and system engineering management, National University of Defense Technology, Changsha, Hunan, P.R. China</b></td><td>1</td></tr><tr><td>Electrical Engineering and Computer Science, School of Engineering, University of California at Merced, Merced, USA</td><td>1</td></tr><tr><td><b>Bilişim Teknolojileri Enstitüsü, Tübitak BİLGEM, Kocaeli, Türkiye</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Software Engineering, University of Western Australia, Crawley, Australia</b></td><td>1</td></tr><tr><td><b>College of Engineering & Computer Science, Australian National University, Canberra, Australia</b></td><td>1</td></tr><tr><td>Data61, Commonwealth Scientific and Industrial Research Organization (CSIRO), Canberra, Australia</td><td>1</td></tr><tr><td><b>Human-Centered Technology Research Centre, University of Canberra, Bruce, Australia</b></td><td>1</td></tr><tr><td><b>Karlsruhe Institute of Technology (KIT), Germany</b></td><td>1</td></tr><tr><td><b>Istanbul Technical University (ITU), Turkey</b></td><td>1</td></tr><tr><td><b>École Polytechnique Fédérale de Lausanne (EPFL), Switzerland</b></td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Faculty of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Bangladesh</td><td>1</td></tr><tr><td>Pennsylvania State University, University Park, PA</td><td>1</td></tr><tr><td>University of Sao Paulo</td><td>1</td></tr><tr><td><b>University of Southern California, Southern California, USA</b></td><td>1</td></tr><tr><td>School of Software, Henan University, Kaifeng, China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Texas A&M University, College Station, USA</b></td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, China</td><td>1</td></tr><tr><td><b>Space Application Laboratory, Research Center for Advanced Science and Technology, University of Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>Department of Aeronautics and Astronautics Engineering, Graduate School of Engineering, University of Tokyo, Japan</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, Computer Vision Laboratory, Linköping University, Linköping, Sweden</td><td>1</td></tr><tr><td>Computer Vision Research Laboratory, Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran</td><td>1</td></tr><tr><td>Treelogic, Technological Scientific Park of Asturias, Llanera, Spain</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Oviedo, Gijón, Spain</td><td>1</td></tr><tr><td>Fundación CTIC (Technological Center), Technological Scientific Park of Gijón, Gijón, Spain</td><td>1</td></tr><tr><td><b>University of Central Florida 4000 Central Florida Blvd., Orlando, 328816, USA</b></td><td>1</td></tr><tr><td><b>Carnegie Mellon University 5000 Forbes Ave Pittsburgh, PA 15213, USA</b></td><td>1</td></tr><tr><td><b>School of Tai-an, Shandong University of Science and Technology, Tai-an, China</b></td><td>1</td></tr><tr><td><b>Integrated Management Coastal Research Institute, Universitat Politècnica de València, València, Spain</b></td><td>1</td></tr><tr><td>Department of Computer Science, Madrid Open University, Madrid, Spain</td><td>1</td></tr><tr><td>Department of Research and Diagnostic Methods, Faculty of Education, Pontificia University of Salamanca, Salamanca, Spain</td><td>1</td></tr><tr><td><b>The University of Tokushima, Japan</b></td><td>1</td></tr><tr><td><b>Department of Signal Processing, Tampere University of Technology, FIN-Tampere, 33720, Finland</b></td><td>1</td></tr><tr><td><b>Computer Science Department, University of Maryland, College Park, MD</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Memorial University of Newfoundland, Saint John's, NL, Canada</b></td><td>1</td></tr><tr><td><b>Computer Science Department, Tel-Aviv University, Ramat Aviv, Tel-Aviv, Israel</b></td><td>1</td></tr><tr><td><b>Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>U.S. Army Res. Lab., Adelphi, MD, USA</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Assiut University, Asyut, Egypt</b></td><td>1</td></tr><tr><td>Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan</td><td>1</td></tr><tr><td>Dept. of Information Engineering, Faculty of Engineering, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan</td><td>1</td></tr><tr><td>Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan, +81 25 262 7499</td><td>1</td></tr><tr><td><b>Visual Computation, Queen Mary University, London, United Kingdom</b></td><td>1</td></tr><tr><td><b>University of British Columbia, Canada</b></td><td>1</td></tr><tr><td>NTNU, Norway</td><td>1</td></tr><tr><td>Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland</td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Yeungnam University, Korea</b></td><td>1</td></tr><tr><td><b>Graduate School at Shenzhen, Tsinghua University, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Cornell University, Ithaca, NY, USA</b></td><td>1</td></tr><tr><td>Polish-Japanese Institute of Information Technology, Warszawa, Poland</td><td>1</td></tr><tr><td>Faculty of Applied Informatics and Mathematics, Department of Informatics, Warsaw University of Life Sciences (SGGW), Warsaw, Poland</td><td>1</td></tr><tr><td><b>AGH University of Science and Technology, Kraków, Poland</b></td><td>1</td></tr><tr><td>Polish-Japanese Institute of Information Technology, Warsaw, Poland</td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, Tongji University, Shanghai, China</b></td><td>1</td></tr><tr><td>FernUniversität , Hagen, Germany</td><td>1</td></tr><tr><td>Universidad Tecnica Federico Santa Maria , Valparaiso, Chile</td><td>1</td></tr><tr><td>Staffordshire University , Staffordshire, United Kingdom</td><td>1</td></tr><tr><td><b>The University of North Carolina at Charlotte, Charlotte, USA</b></td><td>1</td></tr><tr><td><b>Walt Disney Imagineering, USA</b></td><td>1</td></tr><tr><td><b>AEBC, Nanyang Environment & Water Research Institute, Nanyang Technological University, Singapore</b></td><td>1</td></tr><tr><td>Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, Kuching, Malaysia</td><td>1</td></tr><tr><td><b>Australian Centre for Visual Technologies, University of Adelaide, Adelaide, Australia</b></td><td>1</td></tr><tr><td><b>Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, P. R. China</b></td><td>1</td></tr><tr><td>University of Massachusetts at Amherst, Amherst, MA, USA</td><td>1</td></tr><tr><td><b>School of Computer Science, The University of Adelaide, Adelaide, SA, Australia</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Rutgers University, Piscataway, USA</b></td><td>1</td></tr><tr><td><b>University of Maryland, College Park, College Park, USA</b></td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Beijing, P.R.China</b></td><td>1</td></tr><tr><td><b>School of Science, Jiangnan University, Wuxi, China</b></td><td>1</td></tr><tr><td><b>School of Internet of Things Engineering, Jiangnan University, Wuxi, China</b></td><td>1</td></tr><tr><td>Department of Engineering and MaintenanceChina Mobile Group, Jiangsu Company, Ltd., Changzhou, China</td><td>1</td></tr><tr><td><b>School of Computer Sciences and Technology, Nanjing Normal University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, Nanjing Normal University, Nanjing, China</b></td><td>1</td></tr><tr><td>Indian Statistical Institute, Kolkata 700108</td><td>1</td></tr><tr><td>Departament d’Informàtica, Universitat de Valencia, Valencia, Spain</td><td>1</td></tr><tr><td><b>Department of Computer Science, George Mason University, Fairfax, USA</b></td><td>1</td></tr><tr><td><b>School of Information Technology, Deakin University, Geelong, Australia</b></td><td>1</td></tr><tr><td><b>School of Sciences, South China University of Technology, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>College of Computer and Information Science, Southwest University, Chongqing, China</b></td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, Gannan Normal University, Ganzhou, People’s Republic of China</td><td>1</td></tr><tr><td><b>Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, Tongji University, Shanghai, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Information Engineering, Zhengzhou University, China</b></td><td>1</td></tr><tr><td>National Laboratory of Pattern Recognition, Beijing, China</td><td>1</td></tr><tr><td><b>National University of Kaohsiung, Kaohsiung, Taiwan</b></td><td>1</td></tr><tr><td>Quang Binh University, Dong Hoi City, Vietnam</td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, China</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Science, Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, Greece</b></td><td>1</td></tr><tr><td><b>Dept. of Medical Physics, Medical School, Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, Greece</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore</b></td><td>1</td></tr><tr><td><b>Dermalog Identification Systems GmbH, Hamburg, Germany</b></td><td>1</td></tr><tr><td>School of Mathematics and Information Technology, Nanjing Xiao Zhuang University, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td><b>Research & Advanced Technology Division of SAIC Motor Corporation Limited, Shanghai, 201804, P.R. China</b></td><td>1</td></tr><tr><td><b>ECSE Department, Rensselaer Polytechnic Institute</b></td><td>1</td></tr><tr><td><b>Centre of Excellence for Research in Computational Intelligence and Applications, School of Computer Science, University of Birmingham, Birmingham, U.K.</b></td><td>1</td></tr><tr><td><b>VUB-NPU Joint AVSP Research Lab, Northwestern Polytechnical University (NPU), Shaanxi Key Lab on Speech and Image Information Processing, 127 Youyi Xilu, X'ian 710072, China</b></td><td>1</td></tr><tr><td><b>Arizona State University, Phoenix, AZ, USA</b></td><td>1</td></tr><tr><td>School of Computing, Electronics and Mathematics, Faculty of Engineering, Environment and Computing, Coventry University, Coventry, UK</td><td>1</td></tr><tr><td><b>Department of Computer Science and Information Engineering, National Taipei University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td>Institute of Computer Science, Christian-Albrechts-Universität Kiel, Kiel, Germany</td><td>1</td></tr><tr><td><b>Institute of Computer Science, Faculty of Electronics and Information Technology, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland</b></td><td>1</td></tr><tr><td>KT Future Technology Laboratory, Seoul, South Korea</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Anhui University, Hefei, China</b></td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>Microsoft Key Laboratory of Visual Perception, Zhejiang University, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Beijing, P.R. China</b></td><td>1</td></tr><tr><td><b>School of Interactive Computing, Georgia Institute of Technology, Atlanta, USA</b></td><td>1</td></tr><tr><td>Microsoft Research Asia, Beijing, P.R. China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea</b></td><td>1</td></tr><tr><td><b>Nanyang Technological University, 50 Nanyang Drive, 637553, Singapore</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Northumbria University, Newcastle, UK</b></td><td>1</td></tr><tr><td><b>School of Automation, Northwestern Polytechnical University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>SAIIP, School of Computer Science, Northwestern Polytechnical University, Xi’an, China</b></td><td>1</td></tr><tr><td>Shanghai Maritime University, Shanghai, China</td><td>1</td></tr><tr><td>Machine Intelligence Research Institute, Rockville, USA</td><td>1</td></tr><tr><td><b>Department of Computer Science, Shenzhen Graduate School, Harbin Institute of Technology, China</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, Liaoning 110004, China</b></td><td>1</td></tr><tr><td><b>University of Pittsburgh and Adjunct Faculty at the Robotics Institute, Carnegie Mellon University: 3137 Sennott Square, 210 S. Bouquet St., PA 15260 USA</b></td><td>1</td></tr><tr><td><b>AI Institute, Qihoo/360 Company, Beijing, China</b></td><td>1</td></tr><tr><td><b>Intelligent Media Technique Research Center, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, P.R. China</b></td><td>1</td></tr><tr><td><b>CAS Center for Excellence in Brain Science and Intelligence Technology, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, P.R. China</b></td><td>1</td></tr><tr><td><b>AI Institute of Qihoo/360 Company, Beijing, P.R. China</b></td><td>1</td></tr><tr><td><b>Advanced Engineering Electronics & Safety, Delphi Deutschland GMBH, Delphiplatz 1, Wuppertal, North Rhine-Westfalia, Germany</b></td><td>1</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China</b></td><td>1</td></tr><tr><td>Orange—France Telecom Division R&D—TECH/IRIS, Cesson Sévigné Cedex, France</td><td>1</td></tr><tr><td>IIT-Madras, Chennai, India</td><td>1</td></tr><tr><td>Department of Computer Science, Innopolis University, Kazan, Russia</td><td>1</td></tr><tr><td><b>Center for Telematics and Information Technology, University of Twente, Enschede, Netherlands</b></td><td>1</td></tr><tr><td>Department of Computer Science, University of Science & Technology, Bannu, Pakistan</td><td>1</td></tr><tr><td><b>Department of Biomedical Engineering, Kyung Hee University, Suwon, Korea</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Kyung Hee University, Suwon, Korea</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, Korea</b></td><td>1</td></tr><tr><td>Naver Labs Europe, Meylan, France</td><td>1</td></tr><tr><td><b>Image and Video Systems Lab, Dept. of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-Gu, Daejeon 305-701, Republic of Korea</b></td><td>1</td></tr><tr><td><b>LIRIS, UMR 5205 CNRS, INSA-Lyon, F-69621, France</b></td><td>1</td></tr><tr><td><b>Orange Labs, R&D, Meylan, France</b></td><td>1</td></tr><tr><td>School of Computer and Systems Sciences, JawaharLal Nehru University, New Delhi 110067, India</td><td>1</td></tr><tr><td>Univ. La Rochelle, La Rochelle, France</td><td>1</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Tsuen Wan, Hong Kong</td><td>1</td></tr><tr><td><b>University of Maryland, Center for Automation Research, 4411 A.V. Williams Building, College Park, MD 20742-3275, USA</b></td><td>1</td></tr><tr><td><b>Teaching and research of section of mathematics, Hebei Information Engineering School, Baoding 071000, China</b></td><td>1</td></tr><tr><td><b>Institute for Creative Technologies, University of Southern California, Los Angeles, CA, USA</b></td><td>1</td></tr><tr><td><b>George Mason University, Fairfax, USA</b></td><td>1</td></tr><tr><td><b>University of Naples Federico II, Napoli, Italy</b></td><td>1</td></tr><tr><td>University of Salerno, Salerno, Italy</td><td>1</td></tr><tr><td><b>Sapienza University of Rome, Rome, Italy</b></td><td>1</td></tr><tr><td><b>RheinAhrCampus der Hochschule Koblenz, Remagen, Germany</b></td><td>1</td></tr><tr><td>Google, Mountain View, USA</td><td>1</td></tr><tr><td>Computer Sciences Department, University of Wisconsin, Madison, USA</td><td>1</td></tr><tr><td>Google, Seattle, USA</td><td>1</td></tr><tr><td>Singapore Polytechnic, 500 Dover Road, Singapore 139651</td><td>1</td></tr><tr><td><b>Singapore University of Technology and Design, 20 Dover Road, Singapore 138682</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Robotics, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, China</b></td><td>1</td></tr><tr><td><b>IIIT Delhi, India</b></td><td>1</td></tr><tr><td><b>Bournemouth University, Poole, UK</b></td><td>1</td></tr><tr><td><b>Technische Universitt Darmstadt, Computer Systems Group, Darmstadt, Germany</b></td><td>1</td></tr><tr><td><b>School of Engineering and Applied Science, Aston University, Birmingham, U.K.</b></td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China</td><td>1</td></tr><tr><td>Centre for Machine Vision, Bristol Robotics Laboratory, University of the West of England, T Block, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, UK</td><td>1</td></tr><tr><td><b>PERCEPTION Team, INRIA Grenoble Rhône-Alpes, France</b></td><td>1</td></tr><tr><td><b>MIR@CL Laboratory, Faculty of Sciences of Sfax (FSS), University of Sfax, Sfax, Tunisia</b></td><td>1</td></tr><tr><td>Saudi Electronic University, Riyadh, Kingdom of Saudi Arabia</td><td>1</td></tr><tr><td><b>MIR@CL Laboratory, Faculty of Economics and Management of Sfax (FSEGS), University of Sfax, Sfax, Tunisia</b></td><td>1</td></tr><tr><td><b>Digital World Research Centre, University of Surrey, UK</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Curtin University, Miri Sarawak, Malaysia</b></td><td>1</td></tr><tr><td>Information Security Group, City University London, London, UK</td><td>1</td></tr><tr><td><b>Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia</b></td><td>1</td></tr><tr><td><b>Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia</b></td><td>1</td></tr><tr><td>School of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou, China</td><td>1</td></tr><tr><td>IIIT Chittoor, SriCity, Andhra Pradesh, India</td><td>1</td></tr><tr><td><b>ARM, Inc., San Jose, CA</b></td><td>1</td></tr><tr><td>Department of Information Engineering, Henan University of Science and Technology, Luoyang, China</td><td>1</td></tr><tr><td><b>School of Computing Sciences, University of East Anglia, Norwich, U.K.</b></td><td>1</td></tr><tr><td>Department of mechatronic technology of National Taiwan Normal University</td><td>1</td></tr><tr><td><b>Department of Computer Science, Taipei Municipal University of Education</b></td><td>1</td></tr><tr><td><b>Computer Vision Center 08193 Bellaterra, Barcelona, SPAIN</b></td><td>1</td></tr><tr><td><b>Computer Science Division, University of Central Florida, Orlando, FL, USA</b></td><td>1</td></tr><tr><td><b>GuangXi Cast Animation Company, Ltd., Nanning, China</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering and Computer Science, Colorado School of Mines, Golden, CO, USA</td><td>1</td></tr><tr><td><b>School of Information Engineering, Xiangtan University, Xiangtan, China</b></td><td>1</td></tr><tr><td><b>Baidu International Technology (Shenzhen) Company, Ltd., Shenzhen, China</b></td><td>1</td></tr><tr><td>The Image Processing and Analysis Laboratory (LAPI), University “Politehnica” of Bucharest, 313 Splaiul Independeţei, Bucharest, Romania</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, The Chinese University of Hong Kong</b></td><td>1</td></tr><tr><td><b>School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China</b></td><td>1</td></tr><tr><td>Division of Digital Media Engineering, Sang-Myung University, Suwon, Republic of Korea</td><td>1</td></tr><tr><td><b>CAS, Key Lab of Intell. Info. Process., Institute of Computing Technology, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computing, Teesside University, UK</b></td><td>1</td></tr><tr><td><b>Teleinfrastructure R&D Lab, Technical University of Sofia, Bulgaria</b></td><td>1</td></tr><tr><td><b>The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td>Facebook AI Research (FAIR), Menlo Park, USA</td><td>1</td></tr><tr><td>Princeton University &Microsoft, Princeton, NJ, USA</td><td>1</td></tr><tr><td>Microsoft &University of Washington, Redmond, WA, USA</td><td>1</td></tr><tr><td>Intel Labs, Pittsburgh PA</td><td>1</td></tr><tr><td>Dept. of Inf. Network Technol., Hsiuping Inst. of Technol., Taichung, Taiwan</td><td>1</td></tr><tr><td>Alibaba Group, Zhejiang, People’s Republic of China</td><td>1</td></tr><tr><td><b>Computer Science, Arizona State University, Tempe, USA</b></td><td>1</td></tr><tr><td><b>Cork Institute of Technology, CIT, Cork Ireland</b></td><td>1</td></tr><tr><td><b>Biomedical Engineering Program, University of Manitoba, Winnipeg, Canada</b></td><td>1</td></tr><tr><td>Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute Troy, Troy, USA</td><td>1</td></tr><tr><td>Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology, University of Science and Technology of China Hefei, Anhui, People’s Republic of China</td><td>1</td></tr><tr><td><b>Department of Computer Science, University of North Carolina Wilmington, Wilmington, United States</b></td><td>1</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea</b></td><td>1</td></tr><tr><td>School of ComputingNational University of Singapore</td><td>1</td></tr><tr><td><b>Centre for Intelligent Machines and Department of Electrical and Computer Engineering, McGill University, Montreal, Canada</b></td><td>1</td></tr><tr><td><b>UFSC - Federal University of Santa Catarina / INE - CTC, Florianópolis, 88040-900, Brazil</b></td><td>1</td></tr><tr><td><b>UDESC - Santa Catarina State University, DCC - CCT, Joinville, 89219-710, Brazil</b></td><td>1</td></tr><tr><td><b>School of Electrical and Electronic Engineering, University of Manchester, Manchester, U.K.</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Information Technology, University of Nottingham, Nottingham, UK</b></td><td>1</td></tr><tr><td><b>Waseda University, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>Computer Science Department, Rutgers University, 110 Frelinghuysen Road, Piscataway, NJ 08854-8019, USA</b></td><td>1</td></tr><tr><td><b>Fordham University, New York, 10023, USA</b></td><td>1</td></tr><tr><td><b>Rapid-Rich Object Search (ROSE) Lab, Nanyang Technological University, Interdisciplinary Graduate School, SingaporeSingapore</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Semnan University, Semnan, Iran</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran</b></td><td>1</td></tr><tr><td>Dept. of EE, UESTC, 2006 Xiyuan Ave, Chengdu, Sichuan 611731, China</td><td>1</td></tr><tr><td>Dept. of Radiation Oncology, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</td><td>1</td></tr><tr><td>Dept. of Electrical & Computer Engineering, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</td><td>1</td></tr><tr><td>University of Nottingham (Malaysia Campus), Malaysia</td><td>1</td></tr><tr><td>South Valley University, Qena, Egypt</td><td>1</td></tr><tr><td>Film Department ELTE University, Budapest, Hungary</td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, Tripura University (A Central University), Suryamaninagar-799022, Tripura, India</td><td>1</td></tr><tr><td>Gipsa-Lab, Saint Martin d’Heres, France</td><td>1</td></tr><tr><td>ICA Laboratory, Grenoble, France</td><td>1</td></tr><tr><td><b>IIIT Hyderabad, 500032, A.P, India</b></td><td>1</td></tr><tr><td>School of Computing and Electrical Engineering, IIT Mandi, H.P, 175001, India</td><td>1</td></tr><tr><td><b>School of Computer Science and Software Engineering, The University of Western Australia, Crawley, WA, Australia</b></td><td>1</td></tr><tr><td><b>School of Engineering, Griffith University, Nathan, QLD, Australia</b></td><td>1</td></tr><tr><td><b>Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA</b></td><td>1</td></tr><tr><td><b>Department of Naval Architecture and Marine Engineering, University of Michigan, Ann Arbor, MI 48109 USA</b></td><td>1</td></tr><tr><td><b>Beijing Key Laboratory of Digital Media, State Key Laboratory of Virtual Reality Technology and Systems, and School of Computer Science and Engineering , Beihang University, China</b></td><td>1</td></tr><tr><td><b>Philips Research , The Netherlands</b></td><td>1</td></tr><tr><td><b>Istanbul Technical University, Faculty of Computer and Informatics, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China</b></td><td>1</td></tr><tr><td>AICTE Emeritus Fellow, </td><td>1</td></tr><tr><td><b>Department of Computer Science & Engineering, Jadavpur University, Kolkata, India</b></td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, GCELT, Kolkata, India</td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Shaanxi, P. R. China</b></td><td>1</td></tr><tr><td><b>University of Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td>Chinese University of Hong Kong, Hong Kong</td><td>1</td></tr><tr><td><b>Signal and Information Processing section (SIP), Department of Electronic Systems, Aalborg University, Denmark</b></td><td>1</td></tr><tr><td><b>Section of Image Analysis and Computer Graphics, DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark</b></td><td>1</td></tr><tr><td>Department of Computer System and Communication, Faculty of Information and Communication, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia</td><td>1</td></tr><tr><td>Division Télécom, Centre de Développement des Technologies Avancées - CDTA, Algiers, Algeria</td><td>1</td></tr><tr><td><b>University of Delaware, USA</b></td><td>1</td></tr><tr><td><b>Department of Cognitive Science, School of Information Science and Engineering, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Taylor's University Lakeside Campus, Selangor Darul Ehsan, Malaysia</b></td><td>1</td></tr><tr><td><b>Department of Mathematical Sciences, Georgia Southern University, Statesboro, USA</b></td><td>1</td></tr><tr><td>School of Computer and Communication Science, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland</td><td>1</td></tr><tr><td><b>Department of Electronic EngineeringCentre for Vision, Speech and Signal Processing, University of Surrey, Surrey, U.K.</b></td><td>1</td></tr><tr><td><b>Department of Electrical EngineeringFaculty of Engineering, Urmia University, Urmia, Iran</b></td><td>1</td></tr><tr><td><b>ICT-ISVISION Joint R&D Lab. for Face Recognition, Chinese Acad. of Sci., Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Electrical and Computer Engineering, Purdue University, West Lafayette, USA</b></td><td>1</td></tr><tr><td>Baidu Research - Institute of Deep Learning, Sunnyvale, USA</td><td>1</td></tr><tr><td>Jiaxing University, Jiaxing, China</td><td>1</td></tr><tr><td><b>International School, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computer Engineering, Nanyang Technological University, Singapore, Singapore</b></td><td>1</td></tr><tr><td><b>Department of Social and Decision Sciences, Carnigie Mellon University, Pittsburgh, PA 15224, USA</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. zhangxiaoxun@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. jiayunde@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. xushuang@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Electronics and Communication, University of Allahabadm Allahabad, India 211002</td><td>1</td></tr><tr><td><b>Microsoft Live Labs Research, China</b></td><td>1</td></tr><tr><td><b>Baidu Research, USA</b></td><td>1</td></tr><tr><td><b>Center for Machine Vision and Signal Analysis, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Applied Network Technology (ANT), Department of Computer Science, Faculty of Science, Khon Kaen University, Khon Kaen, Thailand</b></td><td>1</td></tr><tr><td>Department of Business Computer, Faculty of Management Science, Nakhon Ratchasima Rajabhat University, Nakhon Ratchasima, Thailand</td><td>1</td></tr><tr><td><b>Microsoft Research</b></td><td>1</td></tr><tr><td><b>MIT CSAIL</b></td><td>1</td></tr><tr><td><b>Affectiva</b></td><td>1</td></tr><tr><td>Yahoo! Research</td><td>1</td></tr><tr><td><b>University of Denver, 2390 S York Street, CMK 308, Denver, CO 80210, USA</b></td><td>1</td></tr><tr><td><b>Institute for Computational and Mathematical Engineering, Stanford University</b></td><td>1</td></tr><tr><td><b>Computer Laboratory, University of Cambridge, Cambridge, U.K.</b></td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, University of Cagliari, Italy</td><td>1</td></tr><tr><td><b>Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China</b></td><td>1</td></tr><tr><td><b>School of Information Science and Technology, Southwest Jiaotong University, Chengdou, P.R. China</b></td><td>1</td></tr><tr><td><b>Center for OPTical IMagery Analysis and Learning, State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China</b></td><td>1</td></tr><tr><td><b>Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, U.K.</b></td><td>1</td></tr><tr><td><b>College of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Fotonation LTD, Galway, Ireland</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xian 710072, Shaanxi, China</b></td><td>1</td></tr><tr><td>Universidad de León, León, Spain</td><td>1</td></tr><tr><td>Elektronik ve Haberleşme Mühendisliği Bölümü</td><td>1</td></tr><tr><td>Robert Bosch Engineering and Business Solutions Limited, Bangalore, India</td><td>1</td></tr><tr><td>Department of Instrumentation and Control Engineering, PSG College of Technology, Coimbatore, India</td><td>1</td></tr><tr><td><b>Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Faculty of Computer and Informatics, Istanbul Technical University, Istanbul, Turkey</b></td><td>1</td></tr><tr><td>China Airborne Missile Academy, Luoyang, China</td><td>1</td></tr><tr><td>Electronic Information Engineering College, Henan University of Science and Technology, Luoyang, China</td><td>1</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Amirkabir University of Technology, Electrical Engineering Department, Tehran, Iran</b></td><td>1</td></tr><tr><td><b>School of Computing and Communication, University of Technology Sydney, Sydney, Australia</b></td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Inner Mongolia University of Science and Technology, Baotou, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of Electronic and Information Engineering, Beihang University, Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td>Istituto Italiano di Tecnologia & Università di Verona, Genova, Italy</td><td>1</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT), Genova, Italy</td><td>1</td></tr><tr><td><b>Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany</b></td><td>1</td></tr><tr><td>Office of Safety Research and Development, Federal Highway Administration, U.S. Department of Transportation, Virginia, USA</td><td>1</td></tr><tr><td><b>Department of Applied Mathematics, Beijing Jiaotong University, Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td>Xinjiang Vocational and Technical College of Communications, Wulumuqi, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of Mechatronical Engineering and Automation, Shanghai University, Shanghai, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Guangdong University of Technology, China</b></td><td>1</td></tr><tr><td>College of Mathematics and Informatics, South China Agricultural University, China</td><td>1</td></tr><tr><td><b>Computer Vision and Multimodal Computing, MPI Informatics, Saarbruecken</b></td><td>1</td></tr><tr><td><b>Computer Vision Laboratory, ETH Zurich</b></td><td>1</td></tr><tr><td><b>School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, China</b></td><td>1</td></tr><tr><td>Curtin University Department of Mechanical Engineering, Perth, Western Australia 6012</td><td>1</td></tr><tr><td><b>Department of Mechanical Engineering, Curtin University, Perth, Western Australia 6012</b></td><td>1</td></tr><tr><td>Department of Information Engineering, HeNan Radio and Television University, Zhengzhou, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of Computer and Information Science, Southwest University, Chongqing, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Center for Robotics, Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiamen University, Xiamen, People’s Republic of China</b></td><td>1</td></tr><tr><td>Computer Science Department, School of Information Science and Engineering, Xiamen, University, Xiamen, People’s Republic of China</td><td>1</td></tr><tr><td>PLA University of Science and Technology, China</td><td>1</td></tr><tr><td><b>PLA University of Science and Technology, China and State Key Lab. for Novel Software Technology, Nanjing University, China</b></td><td>1</td></tr><tr><td><b>College of Computer and Information, Hohai University, China</b></td><td>1</td></tr><tr><td><b>College of Computer and Information, Hohai University, China and Key Lab. of Image and Video Understanding for Social Safety, Nanjing University of Science & Technology, China</b></td><td>1</td></tr><tr><td><b>Vols Taipei</b></td><td>1</td></tr><tr><td><b>Intel Labs Europe, London, United Kingdom</b></td><td>1</td></tr><tr><td><b>Technion - Israel Inst. of Technology, Haifa, 32000, Israel</b></td><td>1</td></tr><tr><td><b>The Open University of Israel, Raanana, 43107, Israel</b></td><td>1</td></tr><tr><td><b>Weizmann Institute of Science, Rehovot, 76100, Israel</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, USA</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China</b></td><td>1</td></tr><tr><td><b>Department of Information and Communication Engineering, Chosun University, Gwangju, Korea</b></td><td>1</td></tr><tr><td>School of Electronics and Computer Eng., Chonnam National University, Gwangju, Korea</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA 23529, USA</b></td><td>1</td></tr><tr><td>FAST, Supélec, Avenue de la Boulaie, Cesson-Sévigné, France</td><td>1</td></tr><tr><td>ISIR laboratory, Pierre and Marie Curie university, Paris Cedex 05, France</td><td>1</td></tr><tr><td>Centre for Visual Computing, Faculty of Engineering and Informatics, University of Bradford, Bradford, UK</td><td>1</td></tr><tr><td><b>Faculty of Science and Technology, Communication University of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>Science and Technology Department, Communication University of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>Collaborative Innovation Center, Communication University of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computer Software, Tianjin University, 300072, China</b></td><td>1</td></tr><tr><td><b>Computer Vision Laboratory, ETH Zürich, Zürich, Switzerland</b></td><td>1</td></tr><tr><td>Amsterdam University College, Amsterdam, The Netherlands</td><td>1</td></tr><tr><td><b>Informatics Institute, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands</b></td><td>1</td></tr><tr><td><b>Universitat Pompeu Fabra, Universidad Pompeu Fabra (Edificio França), Passeig de Circumvallacio, 8, Barcelona, Spain</b></td><td>1</td></tr><tr><td><b>Departamento de estadística, Universidad Carlos III de Madrid, Barcelona, Spain</b></td><td>1</td></tr><tr><td><b>Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Computer Science, Rochester Institute of Technology, USA</b></td><td>1</td></tr><tr><td><b>Center for Imaging Science, Rochester Institute of Technology, USA</b></td><td>1</td></tr><tr><td><b>Space and Naval Warfare Systems Center Pacific, San Diego, CA, 92152, United States</b></td><td>1</td></tr><tr><td><b>Electrical and Computer Engineering, University of California, San Diego</b></td><td>1</td></tr><tr><td>Key Laboratory of Intelligent Information Processing, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of Computer Science, Chongqing University, Chongqing, China</b></td><td>1</td></tr><tr><td>Institute of Life Sciences, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>School of Information Science and Engineering, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>FEECS, Department of Computer Science, Technical University of Ostrava, Ostrava-Poruba, Czech Republic</td><td>1</td></tr><tr><td>ECE, Department MSIT, C-4 Janakpuri, New Delhi, India</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., New Jersey Inst. of Technol., Newark, NJ, USA</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan. e-mail: chihming.fu@gmail.com</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan; Informatics Department, Fo-Guang University, I-Lan, Taiwan. e-mail: clhuang@ee.nthu.edu.tw</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan</td><td>1</td></tr><tr><td><b>Research Institute for Future Media Computing, Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>University Politehnica of Bucharest, Bucharest, Romania</b></td><td>1</td></tr><tr><td><b>School of Computer and Information, Anhui Polytechnic University, Wuhu, China</b></td><td>1</td></tr><tr><td><b>Faculty of Information Sciences and Engineering, University of Canberra, Australia</b></td><td>1</td></tr><tr><td><b>Robotics Institute, Carnegie Mellon University, USA</b></td><td>1</td></tr><tr><td><b>Pediatrics Department, University of South Florida, Tampa, FL, USA</b></td><td>1</td></tr><tr><td>Department of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China</td><td>1</td></tr><tr><td><b>Sun Yat-Sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td>University of California at Los Angeles, Los Angeles, CA, USA</td><td>1</td></tr><tr><td><b>University of Queensland, Brisbane, Australia</b></td><td>1</td></tr><tr><td><b>University of Maryland, Baltimore County, Baltimore, MD</b></td><td>1</td></tr><tr><td><b>Jadavpur University, Kolkata, India</b></td><td>1</td></tr><tr><td>Department of Physics, Tripura University (A Central University), Suryamaninagar, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Tripura University (A Central University), Suryamaninagar, India</td><td>1</td></tr><tr><td><b>Raytheon BBN Technologies, Cambridge, MA, USA</b></td><td>1</td></tr><tr><td>Pontifical Catholic University of Minas Gerais - Department of Computer Science, R. Dom Jose Gaspar, 500, Belo Horizonte MG, 30535901, Brazil</td><td>1</td></tr><tr><td><b>College of Computer and Information Science, Southwest University, Chongqing 400715, China</b></td><td>1</td></tr><tr><td><b>Human-Robot Interaction Research Center, Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea</b></td><td>1</td></tr><tr><td><b>Tsinghua University, Beijing, 100084, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea</b></td><td>1</td></tr><tr><td><b>School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Electronics Engineering, Bahcesehir University, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>School of Science, Jiangnan University, Wuxi, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, USA</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Advanced Process Control for Light Industry, Jiangnan University, Ministry of Education, Wuxi, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Internet of Things, Jiangnan University, Wuxi, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada</b></td><td>1</td></tr><tr><td>Department of Statistics and Operational Research, Faculty of Mathematics, Complutense University of Madrid, Madrid, Spain</td><td>1</td></tr><tr><td><b>Distributed Infinity, Inc., Larkspur, CO, USA</b></td><td>1</td></tr><tr><td><b>University of Colorado Denver, Denver, CO, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA</b></td><td>1</td></tr><tr><td><b>Facebook Inc., San Francisco, CA, USA</b></td><td>1</td></tr><tr><td><b>Adobe Systems Inc., San Jose, CA, USA</b></td><td>1</td></tr><tr><td>Dept. of Mathematics and Computer Science, University of Udine, Italy</td><td>1</td></tr><tr><td><b>University of Wisconsin-Madison, Madison, WI, USA</b></td><td>1</td></tr><tr><td>LIMSI-CNRS, Orsay Cedex, France</td><td>1</td></tr><tr><td>Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Pisa, Italy</td><td>1</td></tr><tr><td><b>Faculty of Information Technology, University of Technology, Sydney, Sydney, Australia. email: hintz@it.uts.edu.au</b></td><td>1</td></tr><tr><td><b>Faculty of Information Technology, University of Technology, Sydney, Sydney, Australia. email: jant@it.uts.edu.au</b></td><td>1</td></tr><tr><td><b>Faculty of Information Technology, University of Technology, Sydney, Sydney, Australia. email: pohsiang@it.uts.edu.au</b></td><td>1</td></tr><tr><td>Faculty of Information Sciences and Engineering, Management and Science University, Selangor, Malaysia</td><td>1</td></tr><tr><td>UTM-Big Data Center, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</td><td>1</td></tr><tr><td>Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</td><td>1</td></tr><tr><td><b>School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia</td><td>1</td></tr><tr><td>LAMIA, EA 4540, University of French West Indies and Guyana, Guadeloupe, France</td><td>1</td></tr><tr><td>ISIR, UPMC Univ Paris 06, CNRS, Paris, France</td><td>1</td></tr><tr><td><b>Advanced Electronics System, Academy of Scientific and Industrial Research, CSIR-Central Electronics Research Institute, Pilani, India</b></td><td>1</td></tr><tr><td><b>Mobile Communications Department, Eurecom, Biot, France</b></td><td>1</td></tr><tr><td><b>STARS Team, Institut National de Recherche en Informatique et en Automatique, Sophia Antipolis, France</b></td><td>1</td></tr><tr><td>Merchant Marine College, Shanghai Maritime University, Shanghai 201306, PR China</td><td>1</td></tr><tr><td><b>Institute of Industrial Science, the University of Tokyo, Tokyo, Japan</b></td><td>1</td></tr><tr><td>Department of Informatics, King’s College London, London, UK</td><td>1</td></tr><tr><td><b>DST INSPIRE Fellow, Department of Computer Science and Engineering, Jadavpur University, Kolkata, India</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, KAIST, Korea</td><td>1</td></tr><tr><td><b>Electronic R&D Center, Mando Corp., Korea</b></td><td>1</td></tr><tr><td>Department of New Media, Korean German Institute of Technology, Korea</td><td>1</td></tr><tr><td><b>SAIT Beijing Lab, Samsung Advanced Institute of Technology, China</b></td><td>1</td></tr><tr><td><b>Mechatronics & Manufacturing Technology Center, Samsung Electronics Co., Korea</b></td><td>1</td></tr><tr><td>Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy</td><td>1</td></tr><tr><td><b>Open University of Israel</b></td><td>1</td></tr><tr><td><b>The University of Western Australia, Crawley, Australia</b></td><td>1</td></tr><tr><td><b>Curtin University, Perth, Australia</b></td><td>1</td></tr><tr><td>Pontifical Catholic Univ of Rio de Janei, Department of Informatics, Rio de Janeiro, Brazil</td><td>1</td></tr><tr><td>Department of Informatics, Pontifical Catholic Univ of Rio de Janei, Rio de Janeiro, Brazil</td><td>1</td></tr><tr><td>School of Computing Sciences and Informatics, University of Cincinnati, Cincinnati, USA</td><td>1</td></tr><tr><td><b>Concordia University, Montreal, Canada</b></td><td>1</td></tr><tr><td>Universiti Kuala Lumpur, Kedah</td><td>1</td></tr><tr><td><b>Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, H3G 1T7, Canada</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Concordia University, QC, Canada, H3G 1T7</b></td><td>1</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, 100876, PR China</b></td><td>1</td></tr><tr><td><b>University of KwaZulu-Natal, School of Maths, Statistics & Computer Science, Durban - South Africa</b></td><td>1</td></tr><tr><td>Sudan University of Science and Technology, College of Computer Science and Information Technology, Khartoum - Sudan</td><td>1</td></tr><tr><td>LMU Munich, Germany and Munich University of Applied Sciences, Germany</td><td>1</td></tr><tr><td>Department of Electric and Electronic Engineering, Avrasya University, Trabzon, Turkey</td><td>1</td></tr><tr><td><b>Department of Electric and Electronic Engineering, Selçuk University, Konya, Turkey</b></td><td>1</td></tr><tr><td><b>Digital Media Institute, Hunan University, Changsha, 410082 P.R. China</b></td><td>1</td></tr><tr><td><b>College of information science and engineering, Hunan University, Changsha, 410082 P.R. China</b></td><td>1</td></tr><tr><td>ACM Professional Specialist in Artificial Intelligence</td><td>1</td></tr><tr><td><b>Université du Quebec a Rimouski (UQAR)</b></td><td>1</td></tr><tr><td><b>School of Information Technology & Electrical Engineering, The University of Queensland, Brisbane, Australia</b></td><td>1</td></tr><tr><td><b>School of Computing, National University of Singapore, Singapore, Singapore</b></td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China</td><td>1</td></tr><tr><td><b>Shanghai university</b></td><td>1</td></tr><tr><td>University of Washington and Google Inc.</td><td>1</td></tr><tr><td>Google Inc.</td><td>1</td></tr><tr><td><b>University of Washington</b></td><td>1</td></tr><tr><td><b>CNRS, IMB, UMR 5251, Talence, France</b></td><td>1</td></tr><tr><td><b>UMR 5800, CNRS, LaBRI, Talence, France</b></td><td>1</td></tr><tr><td><b>UMR 5800, University of Bordeaux, LaBRI, Talence, France</b></td><td>1</td></tr><tr><td><b>UMR 5800, Bordeaux INP, LaBRI, Talence, France</b></td><td>1</td></tr><tr><td><b>UMR 5800, LaBRI, Talence, France</b></td><td>1</td></tr><tr><td><b>Dept. of Electrical Engineering, National Chung Hsing University, Taiwan</b></td><td>1</td></tr><tr><td><b>Division of Design of Intelligent Machines, Center for Development of Advanced Technologies, Algiers, Algeria</b></td><td>1</td></tr><tr><td><b>AI Laboratories, Alibaba Group, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an, China</b></td><td>1</td></tr><tr><td>CCCE, Nankai University Jinnan Campus, Tianjin, China</td><td>1</td></tr><tr><td><b>College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, USA</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, University of Houston, Houston, USA</b></td><td>1</td></tr><tr><td><b>Research Group on Intelligent Machines, University of Sfax, ENIS, Sfax, Tunisia</b></td><td>1</td></tr><tr><td><b>Department of Management, Dalian University of Technology, Dalian Liaoning, China</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, Dalian University of Technology, Dalian Liaoning, China</b></td><td>1</td></tr><tr><td><b>College of Communication Engineering, Chongqing University, Shapingba district, Chongqing, China</b></td><td>1</td></tr><tr><td>Department of Computer Science, VHNSN College, Virudhunagar, India</td><td>1</td></tr><tr><td>Department of Computer Science, ANJA College, Sivakasi, India</td><td>1</td></tr><tr><td><b>Department of Information Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong</b></td><td>1</td></tr><tr><td>Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology Tsinghua University, Beijing, China</td><td>1</td></tr><tr><td><b>National ICT Australia, Canberra, ACT, Australia</b></td><td>1</td></tr><tr><td><b>MIT Media Laboratory, Cambridge, MA, USA</b></td><td>1</td></tr><tr><td>Foundation for Research & Technology – Hellas, Heraklion, Crete, Greece</td><td>1</td></tr><tr><td>Vrije Universiteit Amsterdam, Amsterdam, The Netherlands</td><td>1</td></tr><tr><td>Ruhr-Universität Bochum, Bochum, Germany</td><td>1</td></tr><tr><td><b>Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland</b></td><td>1</td></tr><tr><td><b>Industrial Technology Research Institute, Hsinchu, Taiwan</b></td><td>1</td></tr><tr><td><b>Garmin Corporation, New Taipei, Taiwan</b></td><td>1</td></tr><tr><td><b>Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td><b>School of Information Technologies, University of Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>Tencent AI Laboratory, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Malong Technologies Company, Ltd., Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Beijing Normal University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Guangzhou University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Department of Information Engineering, the Chinese University of Hong Kong</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, the Chinese University of Hong Kong, Shatin, Hong Kong</b></td><td>1</td></tr><tr><td>Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro No.1, Tonantzintla, Puebla, México. CP 72840</td><td>1</td></tr><tr><td><b>Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente 225, Gávea, Brasil</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, National Taiwan University of Science and Technology</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Computational Vision Group, University of California at Irvine, Irvine, CA, USA</b></td><td>1</td></tr><tr><td><b>Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, The Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, China</b></td><td>1</td></tr><tr><td>Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, People’s Republic of China</td><td>1</td></tr><tr><td><b>Department of Automation, Shanghai Jiao Tong University, Shanghai, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Psychology, University of Ottawa, Ottawa, Canada</b></td><td>1</td></tr><tr><td><b>School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada</b></td><td>1</td></tr><tr><td><b>Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran</b></td><td>1</td></tr><tr><td><b>Tohoku University, Japan</b></td><td>1</td></tr><tr><td><b>Intelligent Multimedia Technique Research Center, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, PR China</b></td><td>1</td></tr><tr><td>Department of Mechanical Engineering, Universiti Tenaga Nasional Km 7, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia</td><td>1</td></tr><tr><td><b>University of Alberta, Canada</b></td><td>1</td></tr><tr><td><b>China University of Geosciences, Wuhan, China</b></td><td>1</td></tr><tr><td><b>College of Information Science and Engineering, Hunan University, Changsha, China</b></td><td>1</td></tr><tr><td>Dept. of Electron. Eng., Hannam Univ., Daejeon, South Korea</td><td>1</td></tr><tr><td><b>Centre for Autism Research, Philadelphia, US</b></td><td>1</td></tr><tr><td><b>University of Cambridge</b></td><td>1</td></tr><tr><td><b>Department of EE, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea</b></td><td>1</td></tr><tr><td><b>Department of Software and Computer Engineering, Ajou University, Suwon, Korea</b></td><td>1</td></tr><tr><td>Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies, Zhejiang, China</td><td>1</td></tr><tr><td><b>College of Computer Science, Zhejiang University, Zhejiang, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Chang Gung University, Taoyuan, Taiwan</b></td><td>1</td></tr><tr><td><b>School of Information Science and Engineering, Shandong University, Jinan, China</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada</td><td>1</td></tr><tr><td><b>Center for Advance Imaging Innovation and Research, New York University, New York, NY, USA</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Warwick, Coventry, U.K.</b></td><td>1</td></tr><tr><td>Laboratoire MIA, University of La Rochelle, La Rochelle, France</td><td>1</td></tr><tr><td><b>College of Cyber Security, Jinan University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Columbia University, New York</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, College of Computer and Information Science, Northeastern University, Boston, MA, USA</b></td><td>1</td></tr><tr><td>Fraunhofer Institute for Telecommunications, Berlin, Germany</td><td>1</td></tr><tr><td>Fraunhofer Institute for Digital Media Technology, Ilmenau, Germany</td><td>1</td></tr><tr><td>Siemens AG, Corporate Technology, Munich, Germany</td><td>1</td></tr><tr><td><b>School of Engineering, University of Illinois, Urban Champagne, USA</b></td><td>1</td></tr><tr><td>ECIT, School of Electronics, Electrical Engineering & Computer Science, Queen's University Belfast, Belfast, UK</td><td>1</td></tr><tr><td><b>Computer Science, Loughborough University, Loughborough, UK</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Calcutta, Kolkata, India</td><td>1</td></tr><tr><td><b>Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Engineering, Science and Reaserch Branch, Islamic Azad University, Tehran, Iran</b></td><td>1</td></tr><tr><td>School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran</td><td>1</td></tr><tr><td>Luoyang Electro-Optical Equipment Research Institute, Luoyang, People’s Republic of China</td><td>1</td></tr><tr><td><b>Schepens Eye Research Institute, Harvard University, Cambridge, USA</b></td><td>1</td></tr><tr><td><b>Image Processing Center, Beihang University, Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td>Technological Educational Institute of Sterea Ellada, Psahna, Halkida, Greece</td><td>1</td></tr><tr><td>National Centre for Scientific Research “Demokritos”, Agia Paraskevi, Athens, Greece</td><td>1</td></tr><tr><td>University of Maastricht, Maastricht, The Netherlands</td><td>1</td></tr><tr><td>Centre of Research and Technology Hellas, Thermi, Thessaloniki, Greece</td><td>1</td></tr><tr><td><b>School of Computing and Communications, Lancaster University, Lancaster, UK</b></td><td>1</td></tr><tr><td><b>Center for Optical Imagery Analysis and Learning, Northwestern Polytechnical University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing, China</b></td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, P.P.G. Institute of Technology, Coimbatore, India</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Institute of Road and Transport Technology, Erode, India</td><td>1</td></tr><tr><td><b>Wayne State University, Detroit, USA</b></td><td>1</td></tr><tr><td><b>School of Automation, Huazhong University of Science and Technology, Wuhan, China 430074</b></td><td>1</td></tr><tr><td><b>College of Electronics and Information Engineering, Sichuan University, Chengdu, China 610064</b></td><td>1</td></tr><tr><td>Department of Computer Science, Banasthali Vidyapith, Banasthali, India</td><td>1</td></tr><tr><td>Computer Science and Engineering Department, SP Memorial Institute of Technology, Kaushambi, India</td><td>1</td></tr><tr><td><b>Dept. of Comp. Sci. and Tech., Shenzhen Graduate School, Harbin Institute of Technology, China</b></td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, China</td><td>1</td></tr><tr><td><b>Imperial College London</b></td><td>1</td></tr><tr><td><b>Machine Vision Group, University of Oulu, Oulu, Finland</b></td><td>1</td></tr><tr><td>Fujifilm Software, San Jose, USA</td><td>1</td></tr><tr><td><b>Inst. of Autom., Chinese Acad. of Sci., Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computing, Computing 1, 13 Computing Drive, National University of Singapore, Singapore 117417</b></td><td>1</td></tr><tr><td>Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis, Singapore 138632</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576</b></td><td>1</td></tr><tr><td><b>Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, Brazil</b></td><td>1</td></tr><tr><td><b>Computational Brain Science Lab, Department of Computational Science and Technology, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden</b></td><td>1</td></tr><tr><td><b>Graduate Sch. of Inf. Sci. & Technol., Tokyo Univ., Japan</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>National Laboratory of Speech and Language Information Processing, University of Science and Technology of China, Hefei, China</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh/Robotics Institute, Carnegie Mellon University , Pittsburgh, PA, USA</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Dept.of Intelligence Science and Technology, The Kyoto University of JAPAN</b></td><td>1</td></tr><tr><td><b>Dept.of Computational Intelligence and Systems Science, Tokyo Institute of Technology of JAPAN</b></td><td>1</td></tr><tr><td><b>Microsoft Research, Redmond, WA, USA</b></td><td>1</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, People’s Republic of China</b></td><td>1</td></tr><tr><td>HTC Research, Beijing, China</td><td>1</td></tr><tr><td>QCIS, University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td><b>IIIS, Tsinghua University, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, PR China</b></td><td>1</td></tr><tr><td><b>School of Software Technology, Dalian University of Technology</b></td><td>1</td></tr><tr><td>Interuniversity Microelectronics Centre, Heverlee, Belgium</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Lab, Department ETRO, Vrije Universiteit Brussel (VUB), Brussels, Belgium</td><td>1</td></tr><tr><td>Shaanxi Key Laboratory on Speech and Image Information Processing, Xi’an, China</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Lab, School of Computer Science, Northwestern Polytechnical University (NPU), Xi’an, China</td><td>1</td></tr><tr><td><b>School of Computer and Information Science, Southwest University, Chongqing, China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Shandong University, Shandong, China</b></td><td>1</td></tr><tr><td><b>Facebook Inc., Palo Alto, CA, USA</b></td><td>1</td></tr><tr><td><b>Stanford University, USA</b></td><td>1</td></tr><tr><td>Institute of Electronics and Computer Science, Riga, Latvia</td><td>1</td></tr><tr><td>Electrical and Computer Engineering Department, University of California, Santa Barbara, CA 93106 USA</td><td>1</td></tr><tr><td>Psychology Department, University of California, Santa Barbara, CA 93106 USA</td><td>1</td></tr><tr><td><b>Computer Science and Information Engineering Department, National Taiwan Normal University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td>Dept. of Comp. Sci. and Inf. Eng, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>School of Control Science and Engineering DUT, Dalian, China</td><td>1</td></tr><tr><td><b>College of Mechanical and Electrical, Changzhou Textile Garment Institute, Changzhou, China</b></td><td>1</td></tr><tr><td>Information Technology R&D Center, Mitsubishi Electric Corporation, Kamakura, Japan</td><td>1</td></tr><tr><td>School of Information Science and Engineering, Hunan city University, Yiyang, China</td><td>1</td></tr><tr><td><b>School of Electronics and Information Engineering, Tongji University, Shanghai, China</b></td><td>1</td></tr><tr><td>KU Leuven, ESAT - PSI, iMinds, Leuven, Belgium</td><td>1</td></tr><tr><td>Max-Planck-Institut für Informatik, Saarbrücken, Germany</td><td>1</td></tr><tr><td><b>Faculty of Electrical Engineering, Department of Cybernetics, Czech Technical University in Prague, Prague 6, Czech Republic</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Toronto, Toronto, Canada</b></td><td>1</td></tr><tr><td>Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran, Iran</td><td>1</td></tr><tr><td>University of IIllinois, Urbana-Champaign</td><td>1</td></tr><tr><td><b>Department of ECE, National University of Singapore</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Dayton</b></td><td>1</td></tr><tr><td><b>Institut EURECOM, Sophia Antipolis, (France)</b></td><td>1</td></tr><tr><td><b>Sapienza Università di Roma, v. Salaria 113, 00198, Rome, (IT)</b></td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA</b></td><td>1</td></tr><tr><td>Zhejiang University & Alibaba Group, Hangzhou, China</td><td>1</td></tr><tr><td>Laboratory LIM, Department of Computer Science, Faculty of Sciences and Technologies, University Hassan II, Casablanca-Morocco</td><td>1</td></tr><tr><td><b>College of Electrical Engineering and Automation, Anhui University, Hefei, China</b></td><td>1</td></tr><tr><td>Electrical Engineering Department, Yazd University, Yazd, Iran</td><td>1</td></tr><tr><td><b>School of Computer and Science Technology, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td>School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin, China</td><td>1</td></tr><tr><td>Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, Tianjin, China</td><td>1</td></tr><tr><td><b>Research School of Engineering, Australian National University, Canberra, Australia</b></td><td>1</td></tr><tr><td><b>DCNS Research, 5 rue de l'Halbrane, 44340 Bouguenais, France</b></td><td>1</td></tr><tr><td>Adjunct, Effat University, Jeddah, Saudi Arabia</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Miami, Coral Gables, USA</b></td><td>1</td></tr><tr><td>School of Computer Science, Wuyi University, Jiangmen, China</td><td>1</td></tr><tr><td><b>Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia</b></td><td>1</td></tr><tr><td><b>School of Computer Engineering and Science, Shanghai University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Faculty of Education, East China Normal University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Department of Information Engineering and Computer Science, University of Trento, Trento, TN, Italy</b></td><td>1</td></tr><tr><td>Snapchat Research, Venice, CA90291</td><td>1</td></tr><tr><td><b>Beauty Cosmetic Research Lab, Kao Corporation, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>University of Waterloo, Waterloo, Canada</b></td><td>1</td></tr><tr><td><b>Department of CS, University of Texas at San Antonio, 78249, USA</b></td><td>1</td></tr><tr><td>Department of CSE, University at Buffalo (SUNY), NY 14260, USA</td><td>1</td></tr><tr><td><b>University of Waterloo</b></td><td>1</td></tr><tr><td>School of Information and Engineering, Jinhua Polytechnic, Jinhua, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Texas, Arlington, USA</td><td>1</td></tr><tr><td>School of Medical Science, Jinhua Polytechnic, Jinhua, China</td><td>1</td></tr><tr><td><b>College of Information, Capital University of Economics and Business, Beijing, China.sanyecunfu@emails.bjut.edu.cn</b></td><td>1</td></tr><tr><td><b>Bio-Computing Research Center, Harbin Institute of Technology Shenzhen Graduate School, China</b></td><td>1</td></tr><tr><td><b>Guangdong Industry Training Centre, Guangdong Polytechnic Normal University, Guangzhou, China</b></td><td>1</td></tr><tr><td>S. S. College of Business Studies, University of Delhi, Delhi, India</td><td>1</td></tr><tr><td>School of Computer & System Sciences, Jawaharlal Nehru University, New Delhi, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, India</td><td>1</td></tr><tr><td><b>Korea University, Seoul, South Korea</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Ajou University</b></td><td>1</td></tr><tr><td><b>Advanced Digital Sciences Center , Singapore</b></td><td>1</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, 100190, China</b></td><td>1</td></tr><tr><td>Baidu Online Network Technology (Beijing) Co. Ltd, Beijing, China</td><td>1</td></tr><tr><td><b>Computer Science and Electrical Engineering West Virginia University, Morgantown, USA</b></td><td>1</td></tr><tr><td><b>Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Department of ComputingBiometrics Research Centre, The Hong Kong Polytechnic University, Hong Kong</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Information Technology, RMIT University, Melbourne, VIC, Australia</b></td><td>1</td></tr><tr><td>Faculty of Engineering and Computing, Coventry University, UK</td><td>1</td></tr><tr><td>Dept. of Theoretical Electrical Engineering, Technical University of Sofia, Sofia, Bulgaria</td><td>1</td></tr><tr><td><b>Clemson University, Clemson, SC</b></td><td>1</td></tr><tr><td><b>School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>1</td></tr><tr><td><b>School of Digital Media, Jiangnan University Jiangsu Wuxi, PR China</b></td><td>1</td></tr><tr><td><b>School of Digital Media, Jiangnan University, Jiangsu Wuxi, PR China</b></td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, National Institute of Technology Trichy, Trichy 620015, India</td><td>1</td></tr><tr><td><b>School of Maths, Statistics & Computer Science, University of KwaZulu-Natal, Durban, South Africa</b></td><td>1</td></tr><tr><td><b>Faculty of Science and Technology, Sudan University of Science and Technology, Khartoum, Sudan</b></td><td>1</td></tr><tr><td>Lawrence Berkeley National Laboratory, Berkeley, USA</td><td>1</td></tr><tr><td>No.1 Senior Middle School of Wendeng District, Weihai, China</td><td>1</td></tr><tr><td>Standards & Metrology Research Institute of CARS, Beijing, China</td><td>1</td></tr><tr><td>College of Information Science & Technology, Hebei Agricultural University, Baoding, China</td><td>1</td></tr><tr><td><b>Graduate School of System Informatics, Kobe University, Japan</b></td><td>1</td></tr><tr><td>NOVA Laboratory for Computer Science and Informatics, NOVA-LINCS, Departamento de Informática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL</b></td><td>1</td></tr><tr><td><b>Beijing FaceAll Co. Beijing, China</b></td><td>1</td></tr><tr><td><b>University of Science and Technology of China</b></td><td>1</td></tr><tr><td>Amazon, Berkshire, U.K.</td><td>1</td></tr><tr><td>Tianjin Universtiy, Tianjin, China</td><td>1</td></tr><tr><td><b>Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20740 United States</b></td><td>1</td></tr><tr><td><b>Electrical and Computer Engineering, Rutgers University, Piscataway, New Jersey 08854 United States</b></td><td>1</td></tr><tr><td><b>The Computer Laboratory, University of Cambridge, Cambridge, UK</b></td><td>1</td></tr><tr><td><b>New York University, New York City, NY, USA</b></td><td>1</td></tr><tr><td><b>Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology, University of Technology Sydney, 81 Broadway Street, Ultimo, NSW, Australia</b></td><td>1</td></tr><tr><td>University of Lancaster, Lancaster, United Kingdom</td><td>1</td></tr><tr><td>University of Helsinki, Helsinki, Finland</td><td>1</td></tr><tr><td><b>Department of Multimedia and Graphic Arts, Cyprus University of Technology, P.O. Box 50329, 3036, Lemesos, Cyprus</b></td><td>1</td></tr><tr><td><b>Ryerson Multimedia Research Laboratory, Ryerson University, Toronto, Ontario, Canada</b></td><td>1</td></tr><tr><td>Intelligent and Interactive Systems, Institute of Computer Science, University of Innsbruck, Innsbruck, Austria</td><td>1</td></tr><tr><td>Signal and Image Exploitation (INTELSIG), Montefiore Institute, University of Liège, Liège, Belgium</td><td>1</td></tr><tr><td>Megvii Inc., Beijing, China</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong</b></td><td>1</td></tr><tr><td><b>Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC</b></td><td>1</td></tr><tr><td><b>University of Ottawa, Ottawa, Canada</b></td><td>1</td></tr><tr><td><b>National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>Army Research Office, RTP, Raliegh, NC, United States of America</b></td><td>1</td></tr><tr><td><b>The State Key Laboratory of Integrated Services Networks (ISN), Xidian University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>Department of Electronic and Engineering, Xidian University, Xi’an, China</b></td><td>1</td></tr><tr><td>Department of Informatics, Modeling, Electronics, and Systems, University of Calabria, Rende, Italy</td><td>1</td></tr><tr><td><b>The University of New South Wales, Australia</b></td><td>1</td></tr><tr><td>School of Materials Science and Engineering, Central South University, Changsha, China</td><td>1</td></tr><tr><td>Institute of Energy, Jiangxi Academy of Sciences, Nanchang, China</td><td>1</td></tr><tr><td><b>Xiamen Key Laboratory of Computer Vision and Pattern Recognition, Huaqiao University, Xiamen, China</b></td><td>1</td></tr><tr><td>**</td><td>1</td></tr><tr><td><b>Advanced Technologies Application, Center (CENATAV), Cuba</b></td><td>1</td></tr><tr><td><b>Institute of Digital Media, Peking University, Beijing, China</b></td><td>1</td></tr><tr><td><b>GREYC, CNRS UMR6072, University of Caen, Caen, France</b></td><td>1</td></tr><tr><td><b>IDIAP, Martigny, Switzerland</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213. msavvid@cs.cmu.edu</b></td><td>1</td></tr><tr><td><b>Information Sciences Institute, University of Southern California, Marina del Rey, CA 90292. mitra@isi.edu</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: king@cse.cuhk.edu.hk</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: lyu@cse.cuhk.edu.hk</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: jkzhu@cse.cuhk.edu.hk</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: hbdeng@cse.cuhk.edu.hk</b></td><td>1</td></tr><tr><td>Electrical and Electronic Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran</b></td><td>1</td></tr><tr><td><b>Electronics and Telecommunications Research Institute (ETRI), Republic of Korea</b></td><td>1</td></tr><tr><td><b>Xerox Research Center, Europe, France</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Science and Technology on Integrated Information System Laboratory, Institute of Software, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td>College of Mathematics and Information Engineering, Jiaxing University, Jiaxing, China</td><td>1</td></tr><tr><td><b>State Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, Chengdu, China</b></td><td>1</td></tr><tr><td>Dept. of Convergence, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, Korea</td><td>1</td></tr><tr><td><b>Graduate School of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan</b></td><td>1</td></tr><tr><td><b>School of Electronic Science and Engineering, National ASIC Research and Engineering Center, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Human Media Interaction Group, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands</b></td><td>1</td></tr><tr><td>School of Mechanical and Electrical Engineering, Shandong Management University, Jinan, China</td><td>1</td></tr><tr><td>School of Information Science and Technology, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>National Institute of Advanced Industrial Science Technology, Japan</td><td>1</td></tr><tr><td>Tilburg center for Cognition and Communication, Tilburg University, Tilburg, The Netherlands</td><td>1</td></tr><tr><td><b>Massachusetts Institute of Technology, Cambridge, USA</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China</b></td><td>1</td></tr><tr><td><b>MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Department of Automation, State Key Laboratory of Intelligent Technologies and Systems and Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, The University of Sheffield, Sheffield, UK</b></td><td>1</td></tr><tr><td>Automatics Research Group, Universidad Tecnológica de Pereira, Pereira, Colombia</td><td>1</td></tr><tr><td><b>Department of Computer Engineering, College of Computer & Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong, China</b></td><td>1</td></tr><tr><td><b>Laboratory of Media Audio & Video, Communication University of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>Division of Electrical Engineering, School of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-Dong, Yuseong-Gu, Daejeon 305-701, Republic of Korea</b></td><td>1</td></tr><tr><td><b>CNRS LTCI; Télécom ParisTech</b></td><td>1</td></tr><tr><td><b>Institut Mines-Télécom; Télécom ParisTech; CNRS LTCI</b></td><td>1</td></tr><tr><td>School of Science, Southwest Petroleum University, Chengdu, China</td><td>1</td></tr><tr><td><b>Amity University, Noida, India</b></td><td>1</td></tr><tr><td>Infosys Limited, Bhubaneswar, India</td><td>1</td></tr><tr><td><b>Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Quanzhou, China</b></td><td>1</td></tr><tr><td><b>Research Center for Learning Science, Southeast University, China</b></td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Tianjin University of Technology, China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, College of the Computer and Information Science, Northeastern University, Boston, MA, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer and Information Science, University of Massachusetts Dartmouth, Dartmouth, MA, USA</b></td><td>1</td></tr><tr><td>Department of Computer Science, University of Brasília, DF, Brazil 70910-900</td><td>1</td></tr><tr><td>Department of Mechanical Engineering, University of Brasília, DF, Brazil 70910-900</td><td>1</td></tr><tr><td><b>Department of Neurosurgery, University of Pittsburgh, PA 15213, USA</b></td><td>1</td></tr><tr><td><b>Faculty of Computers and Information, Ain Shams University, Egypt</b></td><td>1</td></tr><tr><td><b>Faculty of Computers and Information, BeniSuef University, Egypt</b></td><td>1</td></tr><tr><td><b>Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China</b></td><td>1</td></tr><tr><td>LIAMA, French National Institute for Research in Computer Science and Control, Paris, France</td><td>1</td></tr><tr><td><b>Intel Laboratory China, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computing, National University of Singapore</b></td><td>1</td></tr><tr><td><b>Institute for Infocomm Research, Singapore</b></td><td>1</td></tr><tr><td><b>Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</b></td><td>1</td></tr><tr><td>Leiden University, Leiden, The Netherlands</td><td>1</td></tr><tr><td>TNO, The Hague, The Netherlands</td><td>1</td></tr><tr><td>City University, Kowloon Tong, Hong Kong</td><td>1</td></tr><tr><td>Radboud University, EC Nijmegen, The Netherlands</td><td>1</td></tr><tr><td>TNO, Oude Waalsdorperweg, AK The Hague, The Netherlands</td><td>1</td></tr><tr><td>Liaocheng University, Liaocheng, China</td><td>1</td></tr><tr><td><b>Machine Vision Group, Infotech Oulu and Department of Electrical and Information Engineering, University of Oulu, Finland</b></td><td>1</td></tr><tr><td>Northwestern Polytechnic University, Xi’an, China</td><td>1</td></tr><tr><td>University of Science and Technology Beijing, Beijing, China</td><td>1</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun Donglu, Beijing 100190, China</b></td><td>1</td></tr><tr><td><b>Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China</b></td><td>1</td></tr><tr><td><b>Rapid-Rich Object Search Laboratory, Interdisciplinary Graduate School, Nanyang Technological University, Singapore</b></td><td>1</td></tr><tr><td><b>Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, USA</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, University of Portsmouth, Portsmouth, UK</b></td><td>1</td></tr><tr><td><b>Department of Automation, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, College of Computer, National University of Defense Technology, Changsha, Hunan, China, 410073</b></td><td>1</td></tr><tr><td>Faculty of Information Engineering, China University of Geosciences, Wuhan, China</td><td>1</td></tr><tr><td><b>University of Abertay, Dundee, UK</b></td><td>1</td></tr><tr><td>China University of Geosciences Wuhan, China</td><td>1</td></tr><tr><td>University of Udine, Udine, Italy</td><td>1</td></tr><tr><td>INRS-EMT, Montreal, Canada</td><td>1</td></tr><tr><td><b>Sapienza Univertsity of Rome</b></td><td>1</td></tr><tr><td><b>Queen Mary University of London, London, England UK</b></td><td>1</td></tr><tr><td><b>Fudan University, Shanghai , China</b></td><td>1</td></tr><tr><td><b>Hohai University, No. 1 Xikang Road, Nanjing, Jiangsu Province, China</b></td><td>1</td></tr><tr><td><b>Institute of Intelligent Information Processing, Xidian University, Xi'an, China</b></td><td>1</td></tr><tr><td><b>College of Metropolitan Transportation, Beijing University of Technology, Beijing, China</b></td><td>1</td></tr><tr><td>School of Computer Science and Technology, Harbin Institute of Technology at Weihai, Weihai, China</td><td>1</td></tr><tr><td><b>School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td><b>Institute of Computing Technology, Chinese Academy of Sciences, Key Laboratory of Intelligent Information Processing, Beijing, China</b></td><td>1</td></tr><tr><td><b>University of Southern California, Los Angeles, CA, USA</b></td><td>1</td></tr><tr><td><b>Institute of Computing Technology, CAS, No.6 Kexueyuan South Road, Beijing, 100080, China</b></td><td>1</td></tr><tr><td>School of Computer Science Carnegie Mellon University Pittsburgh, PA, 15213, USA</td><td>1</td></tr><tr><td><b>Dept. of Computer Science, Purdue University</b></td><td>1</td></tr><tr><td><b>Center for Cognitive Ubiquitous Computing, Arizona State University, Tempe, USA</b></td><td>1</td></tr><tr><td><b>Center of Image and Signal Processing, Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur, Malaysia</b></td><td>1</td></tr><tr><td><b>Graduate School of Engineering Science, Department of Systems Innovation, Osaka University, Toyonaka, Japan</b></td><td>1</td></tr><tr><td>College of Information and Technology, Incheon National University, Incheon, Korea</td><td>1</td></tr><tr><td><b>College of Electronics and Information Engineering, Sichuan University, Chengdu, China</b></td><td>1</td></tr><tr><td><b>School of Software Engineering, Beijing Jiaotong University, Beijing, China</b></td><td>1</td></tr><tr><td>Tianjin University & University of South Carolina, Tianjin, China</td><td>1</td></tr><tr><td><b>Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, USA</b></td><td>1</td></tr><tr><td>School of Electronics Engineering, Kyungpook National University, Taegu, South Korea</td><td>1</td></tr><tr><td>Department of Electrical & Electronics Engineering, Kalasalingam University, Krishnankoil, India</td><td>1</td></tr><tr><td><b>Language Technologies Institute, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, USA</b></td><td>1</td></tr><tr><td><b>Pudong Branch, China Mobile Group Shanghai, Company Limited, Shanghai, China</b></td><td>1</td></tr><tr><td><b>School of Mathematics and Statistics, The University of Western Australia, Nedlands, WA, Australia</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Qatar University, Doha, Qatar</b></td><td>1</td></tr><tr><td>School of Computer Engineering, Hanshin University, Osan, Republic of Korea</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Center for Automation Research, University of Maryland, College Park, USA</b></td><td>1</td></tr><tr><td><b>France Telecom - Orange Labs, Lannion, France</b></td><td>1</td></tr><tr><td><b>National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China</b></td><td>1</td></tr><tr><td>School of Computer Science, China University of Geosciences, Wuhan, China</td><td>1</td></tr><tr><td>College of Computer Science and Technology of Huaqiao University, Xiamen, China</td><td>1</td></tr><tr><td><b>Department of Computer Science, Hong Kong Baptist University, Kowloon, Hong Kong</b></td><td>1</td></tr><tr><td><b>University of Windsor, Canada</b></td><td>1</td></tr><tr><td>CEA (iRSTV/BGE), INSERM (U1038), CNRS (FR3425), Université Grenoble-Alpes, Grenoble, France</td><td>1</td></tr><tr><td>NLPR, Institute of Automation, Chinese Academy of Science, Beijing, People’s Republic of China</td><td>1</td></tr><tr><td>Costel, Université de Rennes 2, Rennes, France</td><td>1</td></tr><tr><td>IRISA, Université de Bretagne Sud, Vannes, France</td><td>1</td></tr><tr><td>Research & Development, British Broadcasting Corporation (BBC), London, UK</td><td>1</td></tr><tr><td><b>Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia</b></td><td>1</td></tr><tr><td>Faculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, China</td><td>1</td></tr><tr><td><b>Waseda University</b></td><td>1</td></tr><tr><td>Wide Eyes Technologies</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Illinois at Urbana—Champaign, Champaign, IL, USA</b></td><td>1</td></tr><tr><td><b>ThyssenKrupp Elevator Americas</b></td><td>1</td></tr><tr><td><b>Tsinghua University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Center for Signal and Image Processing, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta</b></td><td>1</td></tr><tr><td>School of Information Engineering, Jiangxi Manufacturing Technology College, Nanchang, China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Nanjing Forestry University and Shandong University, Jinan, China</td><td>1</td></tr><tr><td>Department of Language Studies, Nanjing Forestry University, Nanjing, China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Nanjing Forestry University, Nanjing, China</td><td>1</td></tr><tr><td><b>State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China</b></td><td>1</td></tr><tr><td>Dept. of Autom. Test & Control, Harbin Inst. of Technol., China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Frederick University, Nicosia, Cyprus</td><td>1</td></tr><tr><td><b>Department of Digital Systems, University of Piraeus, Piraeus, Greece</b></td><td>1</td></tr><tr><td>The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense M, Denmark</td><td>1</td></tr><tr><td><b>Department of Information and Control, B-DAT Laboratory, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong</b></td><td>1</td></tr><tr><td><b>University of Electronic Science and Technology of China, China</b></td><td>1</td></tr><tr><td><b>University of Maryland, College Park, USA</b></td><td>1</td></tr><tr><td><b>Institute of Engineering and Management, Kolkata, India</b></td><td>1</td></tr><tr><td><b>Inst. de Telecomunicações, Fac. de Ciências da Universidade do Porto, Porto, Portugal</b></td><td>1</td></tr><tr><td><b>Peking University, Beijing</b></td><td>1</td></tr><tr><td><b>Korea Electronics Technology Institute, Bundang-gu, Seongnam-si, Republic of Korea</b></td><td>1</td></tr><tr><td><b>National Taiwan University, Taiwan</b></td><td>1</td></tr><tr><td><b>Siren Solutions, Dublin, Ireland</b></td><td>1</td></tr><tr><td><b>Paradigma Digital, Madrid, Spain</b></td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, University of Science and Technology of China, Hefei, China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, University of Science and Technology of China, Hefei, China</b></td><td>1</td></tr><tr><td><b>Australian National University, Australia</b></td><td>1</td></tr><tr><td><b>University of Canberra, Australia</b></td><td>1</td></tr><tr><td><b>Institute of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan, ROC</b></td><td>1</td></tr><tr><td>Department of Computer Science, Digital Image Processing Laboratory, Islamia College Peshawar, Peshawar, Pakistan</td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, East Lansing, USA</b></td><td>1</td></tr><tr><td><b>Research Institute for Future Media Computing, School of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Computer Vision Institute, School of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada</b></td><td>1</td></tr><tr><td><b>Faculty of Applied Science, University of British Columbia, Vancouver, British Columbia, Canada</b></td><td>1</td></tr><tr><td>Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan</td><td>1</td></tr><tr><td>Department of Computer Science, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan</td><td>1</td></tr><tr><td><b>Rutgers University, 94 Brett Road, Piscataway, NJ 08854, United States of America</b></td><td>1</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190 Beijing, China</b></td><td>1</td></tr><tr><td><b>Volvo Car Corporation, SE-405 31 Göteborg, Sweden</b></td><td>1</td></tr><tr><td><b>Smart Eye AB, SE-413 27 Göteborg, Sweden</b></td><td>1</td></tr><tr><td>Technische Universität München / Imperial College London, Munich / London, England UK</td><td>1</td></tr><tr><td><b>University of Geneva, Geneva, Switzerland</b></td><td>1</td></tr><tr><td>Department of Mathematics and Informatics, Ecole Centrale de Lyon, Lyon, 69134, France</td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, Jamia Hamdard University, New Delhi, India</td><td>1</td></tr><tr><td><b>Institute of Image Processing & Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Toyota Research Institute - North America</b></td><td>1</td></tr><tr><td><b>Department of Computer Science & Engineering, Arizona State University, Tempe, USA</b></td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, University of Minnesota-Twin Cities, Minneapolis, USA</td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary</td><td>1</td></tr><tr><td>School of Information Science and Technology, Northwest University, Xi’an, China</td><td>1</td></tr><tr><td>Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands</td><td>1</td></tr><tr><td><b>Griffith University</b></td><td>1</td></tr><tr><td><b>School of Computer, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Information, Singapore Management University, Singapore</b></td><td>1</td></tr><tr><td><b>Agency for Science, Technology and Research, Singapore</b></td><td>1</td></tr><tr><td>School of Software, Beijing Institute of Technology, Beijing, China</td><td>1</td></tr><tr><td><b>Department of Software Technology and Enterprize, Korea University, Seoul, Republic of Korea</b></td><td>1</td></tr><tr><td>University of St. Andrews, UK</td><td>1</td></tr><tr><td><b>University of Illinois at Urbana-Champaign, Champaign, IL, USA</b></td><td>1</td></tr><tr><td>University of Tunis El Manar, Tunis, Tunisia</td><td>1</td></tr><tr><td><b>Department of Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Purdue University, West Lafayette, USA</b></td><td>1</td></tr><tr><td>College of Information and Control Engineering, China University of Petroleum, Qingdao, China</td><td>1</td></tr><tr><td><b>Griffith School of Engineering, Queensland Research Laboratory, National ICT Australia, Griffith University, Nathan, Australia</b></td><td>1</td></tr><tr><td><b>Queensland Research Laboratory, National ICT Australia and Institute for Integrated and Intelligent Systems, Griffith University, Nathan, Australia</b></td><td>1</td></tr><tr><td>Intel Labs Europe, Pipers Way, Swindon</td><td>1</td></tr><tr><td><b>PRaDA, Deakin University, Australia</b></td><td>1</td></tr><tr><td>Department of Computer Systems, Universidad Politécnica de Madrid, Madrid, Spain</td><td>1</td></tr><tr><td><b>Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA</b></td><td>1</td></tr><tr><td><b>Neuropsychiatry Section, Department of Psychiatry, University of Pennsylvania</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Illinois at Chicago, Chicago, IL</b></td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, Ursinus College, Collegeville, PA</td><td>1</td></tr><tr><td><b>Center for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td>Systems Engineering Institute, Xi’an Jiaotong University, Xi’an 710049, China</td><td>1</td></tr><tr><td><b>Chongqing University, China</b></td><td>1</td></tr><tr><td><b>University College London, UK, Dept. of Electronic and Electrical Engineering</b></td><td>1</td></tr><tr><td>Institute of Semiconductors, Chinese Academy of Sciences&University of Chinese Academy of Sciences, Beijing, China</td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, DUT-RU International School of Information and Software Engineering, Dalian University of Technology, Dalian, China</b></td><td>1</td></tr><tr><td><b>Computing Department, Imperial College London, UK. M.Pantic@imperial.ic.ac.uk</b></td><td>1</td></tr><tr><td><b>Computing Department, Imperial College London, UK. M.F.Valstar@imperial.ic.ac.uk</b></td><td>1</td></tr><tr><td><b>Consiglio Nazionale delle Ricerche, Istituto di Calcolo e Reti ad Alte Prestazioni, Viale delle Scienze, 90128 Palermo, ITALY</b></td><td>1</td></tr><tr><td>School of Computer Science and Technology, Nanjing University of Science and Technology of China, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td><b>University of Rochester, New York, USA</b></td><td>1</td></tr><tr><td><b>Microsoft Research, Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>University of Science and Technology of China, Hefei, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, China</b></td><td>1</td></tr><tr><td>NTT Network Innovation Laboratories, Nippon Telegraph and Telephone Corp.</td><td>1</td></tr><tr><td><b>Faculty of Engineering, Tunku Abdul Rahman University College, Setapak, Malaysia</b></td><td>1</td></tr><tr><td>Faculty of Computing and Information Technology, Setapak, Malaysia</td><td>1</td></tr><tr><td><b>Dep. Inteligencia Artificial, U. Politécnica Madrid, Spain</b></td><td>1</td></tr><tr><td><b>Dep. Ciencias de la Computación, U. Rey Juan Carlos, Spain</b></td><td>1</td></tr><tr><td><b>Dep. Comp. Sci. and Engr., Fudan University, China</b></td><td>1</td></tr><tr><td><b>Computer Science Department, University of Maryland, College Park, MD, USA</b></td><td>1</td></tr><tr><td><b>Cernium Corporation, Reston, VA, USA</b></td><td>1</td></tr><tr><td>Computer Science Department, University of California, Los Angeles, CA, USA</td><td>1</td></tr><tr><td><b>Department of Computer and Information Science, Temple University, Philadelphia, PA, USA</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering and the College of Computer and Information Science, Northeastern University, Boston, MA</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Northeastern University, Boston, MA</b></td><td>1</td></tr><tr><td><b>School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>1</td></tr><tr><td><b>North Acton, London</b></td><td>1</td></tr><tr><td><b>Imaging Science and Engineering Laboratory, Tokyo Institute of Technology, Kanagawa, Japan</b></td><td>1</td></tr><tr><td><b>Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Kanagawa, Japan</b></td><td>1</td></tr><tr><td><b>Department of ECE, University of Dayton, Dayton, OH, USA</b></td><td>1</td></tr><tr><td><b>ODU Vision Lab, Old Dominion University, Norfolk, VA, USA</b></td><td>1</td></tr><tr><td><b>EURECOM, Route des Chappes, France</b></td><td>1</td></tr><tr><td>INRIA, Sophia Antipolis, France</td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, Dalian University of Technology, Dalian, China</b></td><td>1</td></tr><tr><td>School of Mathematics and Computer Sciences, Gannan Normal University, Ganzhou, China</td><td>1</td></tr><tr><td>University of Maribor, Faculty of Electrical Engineering and Computer Science, Koroška cesta 46, SI-2000, Slovenia</td><td>1</td></tr><tr><td><b>RMIT University, Vietnam</b></td><td>1</td></tr><tr><td><b>Tolendata Singapore R&D Centre Private Limited, Singapore</b></td><td>1</td></tr><tr><td><b>College of Computer Science & Software Engineering, Shenzhen University, China 518060</b></td><td>1</td></tr><tr><td>University of Tours, France</td><td>1</td></tr><tr><td><b>Concordia Institute for Information Systems Engineering (CIISE), 1515 St. Catherine West, Montreal, Quebec H3G 2W1, CANADA</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Science and Software Engineering, Concordia University, 1515 St. Catherine West, Montreal, Quebec H3G 2W1, CANADA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, University of Notre Dame</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Pontificia Universidad Catolica de Chile</b></td><td>1</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology at Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>School of Engineering, The University of Edinburgh, Edinburgh, U.K.</b></td><td>1</td></tr><tr><td><b>Changzhou University, Changzhou, China</b></td><td>1</td></tr><tr><td><b>High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, China</b></td><td>1</td></tr><tr><td><b>Medical Psychology, Ulm University, Ulm, Germany</b></td><td>1</td></tr><tr><td>Department of Information Management, Hwa Hsia University of Technology, New Taipei City, Taiwan</td><td>1</td></tr><tr><td>Department of Electronic Engineering, National Ilan University, Yilan City, Taiwan</td><td>1</td></tr><tr><td><b>School of Computer Science, Guangzhou University, Guangzhou, China</b></td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China</td><td>1</td></tr><tr><td>College of Information and Electrical Engineering, Ludong University, Yantai, China</td><td>1</td></tr><tr><td><b>College of Computing, Georgia Tech</b></td><td>1</td></tr><tr><td><b>Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Korea</b></td><td>1</td></tr><tr><td><b>Taxes Instruments, Dallas, TX, United States</b></td><td>1</td></tr><tr><td>Wakayama University</td><td>1</td></tr><tr><td><b>Energy Research Institute @NTU (ERI@N), Interdisciplinary Graduate School, Nanyang Technological University, Singapore 639798</b></td><td>1</td></tr><tr><td>Computer Science College, Xi’an Polytechnic University, Xi’an, China</td><td>1</td></tr><tr><td><b>Visual Analysis of People Laboratory, Aalborg University, Aalborg, Denmark</b></td><td>1</td></tr><tr><td><b>Computer Vision Team, ARS Traffic & Transport Technology, Trivandrum, India</b></td><td>1</td></tr><tr><td><b>Computer Science Dept., Columbia University, USA</b></td><td>1</td></tr><tr><td>Computer Science Dept., SUNY Stony Brook, USA</td><td>1</td></tr><tr><td><b>Rensselaer Polytechnic Institute</b></td><td>1</td></tr><tr><td>School of Mathematical and Physical Sciences at the University of Newcastle, Callaghan, NSW 2308, Australia</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, JNTU College of Engineering, Hyderabad, India</td><td>1</td></tr><tr><td>Department of Physics, JNTU College of Engineering, Kakinada, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, JNTU College of Engineering, Kakinada, India</td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Collaborative Innovation Center for Geospatial Information Technology, Wuhan, China</b></td><td>1</td></tr><tr><td><b>Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague 6, Czech Republic</b></td><td>1</td></tr><tr><td>Department of Telecommunications and Information Processing, Image Processing and Interpretation, UGent/iMinds, Ghent, Belgium</td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Indian Institute of Science, C.V. Raman Avenue, Bangalore, KA 560-012, India</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada</b></td><td>1</td></tr><tr><td>School of Software, Shenyang University of Technology, Shenyang, China</td><td>1</td></tr><tr><td><b>Department of Internal Medicine, Chung-Ang University, Seoul, South Korea</b></td><td>1</td></tr><tr><td><b>Department of Data Science, Dankook University, Yongin, South Korea</b></td><td>1</td></tr><tr><td><b>Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td>School of Engineering of UABC, University of Baja California, Tijuana, Mexico</td><td>1</td></tr><tr><td>University of Hawaii at Hilo, HI, USA</td><td>1</td></tr><tr><td>Yuncheng University, Shanxi Province, China</td><td>1</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Nazarbayev University, Astana, Kazakhstan</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, Nanjing University of Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td><b>Rochester Institute of Technology, Rochester, NY, USA</b></td><td>1</td></tr><tr><td><b>University of Electronic Science and Technology of China, Chendu, China</b></td><td>1</td></tr><tr><td><b>Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates</b></td><td>1</td></tr><tr><td><b>School of Electronics and Information Engineering, Beihang University, Beijing, China</b></td><td>1</td></tr><tr><td><b>College of Computer Science, Guangdong University of Petrochemical Technology, Maoming, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA, 12180</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Istanbul University, Istanbul, Turkey</b></td><td>1</td></tr><tr><td>Department of Computer Engineering, Bahçeşehir University, Istanbul, Turkey</td><td>1</td></tr><tr><td>Sichuan University West China Hospital of Stomatology, Chengdu, China</td><td>1</td></tr><tr><td><b>Center for Future Media, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>1</td></tr><tr><td>School of Software Engineering, Chengdu University of Information Technology, Chengdu, China</td><td>1</td></tr><tr><td><b>School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>1</td></tr><tr><td><b>National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD 20899, USA</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, People’s Republic of China</td><td>1</td></tr><tr><td><b>Col. of Comp. Sci. and Comm. Eng., Jiangsu University, Zhenjiang, China</b></td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, China</td><td>1</td></tr><tr><td><b>Center for Automation Research, University of Maryland, College Park, MD 20742, USA</b></td><td>1</td></tr><tr><td><b>Delft University of Technology, Delft, The Netherlands</b></td><td>1</td></tr><tr><td>Department of Computer Engineering, Bogaziçi University, Bebek, Turkey</td><td>1</td></tr><tr><td>Department of Electrical and Electronic Engineering, Auckland University of Technology , Auckland, New Zealand</td><td>1</td></tr><tr><td>Department of Computer Engineering, Qazvin Islamic Azad University , Qazvin, Iran</td><td>1</td></tr><tr><td>Shanghai University of Finance and Economics, Shanghai, China</td><td>1</td></tr><tr><td><b>School of Mathematics, Jilin University, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Memorial University of Newfoundland, Canada</b></td><td>1</td></tr><tr><td>Graduate School of Engineering, Nagasaki University, Nagasaki, Japan</td><td>1</td></tr><tr><td>Institute of Management and Information Technologies, Chiba University, Chiba, Japan</td><td>1</td></tr><tr><td>Graduate School of Advanced Integration Science, Chiba University, Chiba, Japan</td><td>1</td></tr><tr><td><b>School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 15213, USA</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Science, Purdue University, West Lafayette, IN, 47907, USA</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea</b></td><td>1</td></tr><tr><td><b>Griffith University, Brisbane</b></td><td>1</td></tr><tr><td><b>Griffith University, Brisbane and University of the South Pacific, Fiji</b></td><td>1</td></tr><tr><td>Vision Semantics Ltd</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong</b></td><td>1</td></tr><tr><td>Department of Film and Digital Media, Seokyeong University, Seoul, Republic of Korea</td><td>1</td></tr><tr><td>Department of MediaSoftware, Sungkyul University, Anyang-si, Republic of Korea</td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea</b></td><td>1</td></tr><tr><td>Pusan National University, Busan, Korea</td><td>1</td></tr><tr><td><b>Graduate School at Shenzhen, Tsinghua University, Shenzhen, China</b></td><td>1</td></tr><tr><td>School of Engineering, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland</td><td>1</td></tr><tr><td>Department of Computer Science, Auckland University of Technology, Auckland, New Zealand</td><td>1</td></tr><tr><td>L3S Research Center, Leibniz Universität Hannover, Hannover, Germany</td><td>1</td></tr><tr><td>German National Library of Science and Technology (TIB), Hannover, Germany</td><td>1</td></tr><tr><td>taglicht media Film- & Fernsehproduktion GmbH, Köln, Germany</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany</td><td>1</td></tr><tr><td><b>The Hong Kong Polytechnic University, Chu Hai College of Higher Education, Hong Kong, China</b></td><td>1</td></tr><tr><td>School of Mathematics and Computational Science, Anqing Normal University, Anqing, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of IoT Engineering, Jiangnan University, Wuxi, People’s Republic of China</b></td><td>1</td></tr><tr><td>Concordia Institute for Information Systems Engineering Concordia University, Montreal, Canada</td><td>1</td></tr><tr><td>IKERBASQUE, Basque Foundation for Science, Bilbao, Spain</td><td>1</td></tr><tr><td>University of the Basque Country UPV/EHU, San Sebastian, Spain</td><td>1</td></tr><tr><td>Computer Vision Center, Edifici “O”, Campus UAB, Bellaterra, Spain</td><td>1</td></tr><tr><td>Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki City, Japan</td><td>1</td></tr><tr><td>Xiamen University of Technology, Fujian, China</td><td>1</td></tr><tr><td><b>Université des Antilles et de la Guyane (UAG), France</b></td><td>1</td></tr><tr><td><b>Institut des Systèmes intelligents et de Robotique, UPMC, France</b></td><td>1</td></tr><tr><td>School of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, China</td><td>1</td></tr><tr><td><b>College of Computer Science and Information Technology, Northeast Normal University, Changchun, China</b></td><td>1</td></tr><tr><td><b>College of Information Science and Engineering, Northeastern University, Shenyang, China</b></td><td>1</td></tr><tr><td>Dept. of Artificial Intelligence, Faculty of Computer Engineering, University of Isfahan, Iran</td><td>1</td></tr><tr><td>Department of Information Processing Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology Yokohama 226-8503, Japan</td><td>1</td></tr><tr><td><b>Research Groups on Intelligent Machines, University of Sfax, Sfax, Tunisia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, University of Queensland, St Lucia, QLD, Australia</b></td><td>1</td></tr><tr><td>Departament d’Informática, Universitat de Valéncia, Av. de la Universitat s/n, 46100-Burjassot, Spain</td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang City 212003, China</b></td><td>1</td></tr><tr><td><b>Microsoft, Bellevue, WA, USA</b></td><td>1</td></tr><tr><td><b>M5001, Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong</b></td><td>1</td></tr><tr><td>Department of Computer Science, University of Texas, San Antonio, TX, USA</td><td>1</td></tr><tr><td><b>School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, USA</b></td><td>1</td></tr><tr><td><b>Imperial College London, London, U.K.</b></td><td>1</td></tr><tr><td><b>University of East Anglia, Norwich, United Kingdom</b></td><td>1</td></tr><tr><td>University of Sheffield, Sheffield, United Kingdom</td><td>1</td></tr><tr><td>Insititute of Automation, Chinese Academy of Sciences (CAS), Beijing, China</td><td>1</td></tr><tr><td><b>Alcohol Countermeasure Systems Corporation, Toronto, ON, Canada</b></td><td>1</td></tr><tr><td><b>Center for Ubiquitous Computing, University of Oulu, Oulu, Finland</b></td><td>1</td></tr><tr><td>School of Computing and Information Systems, University of Melbourne, Melbourne, Australia</td><td>1</td></tr><tr><td><b>Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland</b></td><td>1</td></tr><tr><td><b>Institute of Information and System Sciences, Faculty of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>Research Division, Educational Testing Service, Princeton, NJ, USA</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Division of Biomedical Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR</b></td><td>1</td></tr><tr><td><b>Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR</b></td><td>1</td></tr><tr><td><b>University of York, York, United Kingdom</b></td><td>1</td></tr><tr><td><b>Kumamoto University, Kumamoto, Japan</b></td><td>1</td></tr><tr><td>Sapienza Università di Roma, Roma, Italy</td><td>1</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing (CRIPAC), NLPR, CASIA, Beijing, China</b></td><td>1</td></tr><tr><td><b>National Taichung University of science and Technology, Taichung</b></td><td>1</td></tr><tr><td>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian, University, Xi'an 710071, China</td><td>1</td></tr><tr><td><b>University of Technology Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>SAP Innovation Center Network, Singapore</b></td><td>1</td></tr><tr><td><b>Agency for Science, Technology and Research, Institute of High Performance Computing, Singapore</b></td><td>1</td></tr><tr><td><b>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. venu@cedar.buffalo.edu</b></td><td>1</td></tr><tr><td><b>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. zhizhang@cedar.buffalo.edu</b></td><td>1</td></tr><tr><td><b>CUBRC, Buffalo, NY, USA. slowe@cubrc.org</b></td><td>1</td></tr><tr><td>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. tulyakov@cedar.buffalo.edu</td><td>1</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, USA</b></td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China</td><td>1</td></tr><tr><td><b>Department of Computing, University of Surrey, Guildford, Surrey, GU2 7XH, UK</b></td><td>1</td></tr><tr><td><b>Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, China</b></td><td>1</td></tr><tr><td>College of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China</td><td>1</td></tr><tr><td><b>National ASIC Design and Engineering Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td>LAMIA, EA 4540, University of French West Indies & Guyana</td><td>1</td></tr><tr><td><b>Institut Telecom - Telecom ParisTech CNRS/LTCI, Paris</b></td><td>1</td></tr><tr><td>Peking University & Shanghai Jaio Tong University, Beijing, China</td><td>1</td></tr><tr><td>School of Information Technology, Madurai Kamarai University, Madurai, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, Sanjivani College of Engineering, Kopargaon, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, St.Peter’s University, Chennai, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, Panimalar Engineering College, Chennai, India</td><td>1</td></tr><tr><td>Department of Computer Science, IT-Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>1</td></tr><tr><td>ITI Department Telecom Bretagne, Brest, France</td><td>1</td></tr><tr><td>Adobe Systems Incorporated, San Jose, CA, 95110</td><td>1</td></tr><tr><td><b>University of Technology at Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>College of Engineeing & Informatics, National University of Ireland Galway, Galway, Ireland</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Bogazici University, Bebek, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Istanbul University, Avcilar, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Bahcesehir University, Besiktas, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China</b></td><td>1</td></tr><tr><td><b>Faculty of Electronics and Telecommunications “POLITEHNICA” University from Timişoara Timişoara, România</b></td><td>1</td></tr><tr><td><b>College of Humanities, Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, China</b></td><td>1</td></tr><tr><td><b>Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore</b></td><td>1</td></tr><tr><td><b>Division of Computer Science and Engineering, Center for Advanced Image and Information Technology, Chonbuk National University, Jeonju, Republic of Korea</b></td><td>1</td></tr><tr><td><b>Division of Computer Science and Engineering, Chonbuk National University, Jeonju, Republic of Korea</b></td><td>1</td></tr><tr><td><b>University of Lincoln, U. K.</b></td><td>1</td></tr><tr><td><b>School of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Chang Gung University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td><b>School of Information Technology, Monash University Malaysia, Bandar Sunway, Malaysia</b></td><td>1</td></tr><tr><td><b>College of Engineering, Huaqiao University, Fujian, China</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering and Information Technology, TU Darmstadt, D-64283, Germany</td><td>1</td></tr><tr><td>Institute of Neural Information Processing, University of Ulm, Ulm, Germany</td><td>1</td></tr><tr><td>Institute for Information Technology and Communications (IIKT), Otto-von-Guericke-University Magdeburg, Magdeburg, Germany</td><td>1</td></tr><tr><td>Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran</td><td>1</td></tr><tr><td><b>University of Technology Sydney, Broadway, Australia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Software Engineering, University of Wollongong, Wollongong, Australia</b></td><td>1</td></tr><tr><td>Defence Science and Technology Organisation (DSTO), Edinburgh, Australia</td><td>1</td></tr><tr><td>Reallusion Corporation</td><td>1</td></tr><tr><td><b>National Taiwan Normal University</b></td><td>1</td></tr><tr><td><b>University College London</b></td><td>1</td></tr><tr><td><b>Keio University, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>The University of Tokyo, Bunkyo, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>Keio University, Yokohama City, Kanagawa, Japan</b></td><td>1</td></tr><tr><td><b>Keio University, Yokohama City, Japan</b></td><td>1</td></tr><tr><td>National Institute of Advanced Industrial Science and Technology (AIST), Koto, Tokyo, Japan</td><td>1</td></tr><tr><td><b>Research Center for Institute of Information Science, Academia Sinica, Taiwan</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Information Engineering, National Taiwan University</b></td><td>1</td></tr><tr><td><b>Department of Statistics, Carnegie Mellon University, Pittsburgh, USA</b></td><td>1</td></tr><tr><td>Computer Application Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</td><td>1</td></tr><tr><td>Dept. of EE, Univ. at Buffalo, SUNY, USA</td><td>1</td></tr><tr><td>Department of Computer Science, Minjiang University, Fuzhou, People’s Republic of China</td><td>1</td></tr><tr><td><b>Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, People’s Republic of China</b></td><td>1</td></tr><tr><td>Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Hafez Ave., Tehran, Iran</td><td>1</td></tr><tr><td><b>Istanbul Technical University, Computer Engineering Department, 34469, Turkey</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, City University of Hong Kong, Hong Kong</b></td><td>1</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, the University of Queensland, Brisbane, Qld, Australia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu</b></td><td>1</td></tr><tr><td><b>University of Electronic Science and Technology of China, Chengdu</b></td><td>1</td></tr><tr><td>Institute of High Performance Computing and Networking, National Research Council of Italy (ICAR-CNR), Naples, Italy</td><td>1</td></tr><tr><td><b>IBM Research, Singapore</b></td><td>1</td></tr><tr><td><b>Center for Applied Mathematics, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, School of Science, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td><b>Faculty of Applied Mathematics, Shanxi University of Finance and Economics</b></td><td>1</td></tr></table></body></html>
\ No newline at end of file +<!doctype html><html><head><meta charset='utf-8'><title>Institutions from IEEE</title><link rel='stylesheet' href='reports.css'></head><body><h2>Institutions from IEEE</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore</b></td><td>37</td></tr><tr><td><b>Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece</b></td><td>29</td></tr><tr><td><b>National Taiwan University, Taipei, Taiwan Roc</b></td><td>26</td></tr><tr><td><b>Department of Electrical and Computer Engineering, National University of Singapore, Singapore</b></td><td>21</td></tr><tr><td><b>Fudan University, Shanghai, China</b></td><td>21</td></tr><tr><td><b>National University of Singapore, Singapore, Singapore</b></td><td>20</td></tr><tr><td><b>Universität Hamburg, Hamburg, Germany</b></td><td>19</td></tr><tr><td><b>School of Computer Engineering, Nanyang Technological University, Singapore</b></td><td>19</td></tr><tr><td><b>School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China</b></td><td>18</td></tr><tr><td><b>South China University of Technology, Guangzhou, China</b></td><td>16</td></tr><tr><td><b>Department of Automation, Tsinghua University, Beijing, China</b></td><td>16</td></tr><tr><td><b>School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>15</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b></td><td>14</td></tr><tr><td><b>College of Computer Science and Technology, Zhejiang University, Hangzhou, China</b></td><td>14</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>14</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, China</b></td><td>13</td></tr><tr><td><b>School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China</b></td><td>12</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>12</td></tr><tr><td><b>Université de Lyon, CNRS, INSA-Lyon, LIRIS, UMR5205, F-69621, France</b></td><td>12</td></tr><tr><td><b>Zhejiang University, Hangzhou, China</b></td><td>12</td></tr><tr><td><b>School of Computer Science and Technology, Tianjin University, Tianjin, China</b></td><td>12</td></tr><tr><td><b>College of Computer Science, Sichuan University, Chengdu, China</b></td><td>12</td></tr><tr><td><b>College of Computer Science, Zhejiang University, Hangzhou, China</b></td><td>12</td></tr><tr><td><b>Department of Information Engineering and Computer Science, University of Trento, Trento, Italy</b></td><td>11</td></tr><tr><td><b>National University of Singapore, Singapore</b></td><td>11</td></tr><tr><td><b>Harbin Institute of Technology, Harbin, China</b></td><td>11</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea</b></td><td>11</td></tr><tr><td><b>State Key Laboratory of Management and Control of Complex Systems, CASIA, Beijing, China</b></td><td>10</td></tr><tr><td><b>Shanghai Jiao Tong University</b></td><td>10</td></tr><tr><td><b>Stanford University</b></td><td>10</td></tr><tr><td><b>School of Computing, National University of Singapore, Singapore</b></td><td>10</td></tr><tr><td><b>Northeastern University, Boston, MA, USA</b></td><td>10</td></tr><tr><td><b>University of Maryland, College Park</b></td><td>10</td></tr><tr><td><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore</b></td><td>10</td></tr><tr><td><b>Peking University, Beijing, China</b></td><td>10</td></tr><tr><td><b>Department of Computer Engineering, Kyung Hee University, South Korea</b></td><td>9</td></tr><tr><td><b>Dept. of Computer Science and Information Engineering, National Central University, Jhongli, Taiwan</b></td><td>9</td></tr><tr><td><b>Noblis, Falls Church, VA, U.S.A.</b></td><td>9</td></tr><tr><td><b>School of Electronic Information Engineering, Tianjin University, Tianjin, China</b></td><td>9</td></tr><tr><td><b>Shanghai Jiao Tong University, Shanghai, China</b></td><td>9</td></tr><tr><td><b>Beihang University, Beijing, China</b></td><td>9</td></tr><tr><td><b>National University of Ireland Galway, Galway, Ireland</b></td><td>9</td></tr><tr><td><b>Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China</b></td><td>9</td></tr><tr><td><b>School of Electrical and Electronic Engineering, College of Engineering, Yonsei University, Seoul, South Korea</b></td><td>9</td></tr><tr><td><b>Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan</b></td><td>9</td></tr><tr><td><b>Singapore Management University, Singapore, Singapore</b></td><td>8</td></tr><tr><td><b>P.G. Demidov Yaroslavl State University, Yaroslavl, Russia</b></td><td>8</td></tr><tr><td><b>Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Bratislava, Bratislava, Slovakia</b></td><td>8</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Center for Research on Intelligent Perception and Computing, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>8</td></tr><tr><td><b>Department of Electronic and Information Engineering, The Hong Kong Polytechnic University</b></td><td>8</td></tr><tr><td><b>CAS Center for Excellence in Brain Science and Intelligence Technology; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China</b></td><td>8</td></tr><tr><td><b>Institute of Computer Science and Technology, Peking University, Beijing, P.R. China, 100871</b></td><td>8</td></tr><tr><td><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>8</td></tr><tr><td><b>Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China</b></td><td>8</td></tr><tr><td><b>Tsinghua University, Beijing, China</b></td><td>8</td></tr><tr><td><b>State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China</b></td><td>8</td></tr><tr><td><b>University of Chinese Academy of Sciences, Beijing, China</b></td><td>8</td></tr><tr><td><b>Arizona State University, Tempe, AZ, USA</b></td><td>8</td></tr><tr><td><b>Department of Computing, Imperial College London, London, U.K.</b></td><td>8</td></tr><tr><td><b>Samsung R&D Institute, China</b></td><td>8</td></tr><tr><td><b>University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>8</td></tr><tr><td><b>Department of Computer Science and Engineering, Shanghai Jiao Tong University, China</b></td><td>8</td></tr><tr><td><b>IIIT-Delhi, India</b></td><td>7</td></tr><tr><td><b>University of Texas at Arlington, Arlington, TX, USA</b></td><td>7</td></tr><tr><td><b>National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, China</b></td><td>7</td></tr><tr><td><b>Huazhong University of Science and Technology, Wuhan, China</b></td><td>7</td></tr><tr><td><b>Bio-Computing Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China</b></td><td>7</td></tr><tr><td><b>Stony Brook University, Stony Brook University, NY 11794, USA</b></td><td>7</td></tr><tr><td><b>CyLab Biometrics Center and the Department of Electrical and Computer Engineering (ECE), Carnegie Mellon University, Pittsburgh, USA</b></td><td>7</td></tr><tr><td><b>School of Electronic and Information Engineering, Beihang University, Beijing, China</b></td><td>7</td></tr><tr><td><b>Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia</b></td><td>7</td></tr><tr><td><b>State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China</b></td><td>7</td></tr><tr><td><b>School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>7</td></tr><tr><td><b>Department of Computer Science, Jiangnan University, No. 1800 LiHu Avenue, WuXi, China</b></td><td>7</td></tr><tr><td><b>College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China</b></td><td>7</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences, China</b></td><td>7</td></tr><tr><td><b>School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China</b></td><td>7</td></tr><tr><td><b>Ulm University, Ulm, Germany</b></td><td>7</td></tr><tr><td><b>Center for Automation Research, UMIACS, University of Maryland, College Park, 20740, United States of America</b></td><td>7</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, Beijing, 100876, China</b></td><td>7</td></tr><tr><td><b>Department of Electronic Engineering, Tsinghua University, Beijing, China</b></td><td>7</td></tr><tr><td><b>Visual Computing Group, Microsoft Research, Beijing, China</b></td><td>7</td></tr><tr><td><b>School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea</b></td><td>7</td></tr><tr><td><b>Samsung Advanced Institute of Technology, Korea</b></td><td>7</td></tr><tr><td><b>Indraprastha Institute of Information Technology Delhi, Delhi, India</b></td><td>7</td></tr><tr><td><b>Southeast University, China</b></td><td>6</td></tr><tr><td><b>Department of Electrical Engineering, KAIST, Daejeon, Korea</b></td><td>6</td></tr><tr><td><b>Colorado State University, Fort Collins</b></td><td>6</td></tr><tr><td><b>Indian Institute of Technology (BHU) Varanasi, India</b></td><td>6</td></tr><tr><td><b>Department of Information Engineering and Computer Science, University of Trento, Italy</b></td><td>6</td></tr><tr><td><b>College of Information Technical Science, NanKai University, CITS, TianJin, China</b></td><td>6</td></tr><tr><td><b>SAIT India, Samsung India Software Operations Pvt. Ltd (SISO), Bangalore, India, 560093</b></td><td>6</td></tr><tr><td><b>Fudan University, Shang Hai, China</b></td><td>6</td></tr><tr><td><b>State University of New York at Binghamton, USA</b></td><td>6</td></tr><tr><td><b>Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore</b></td><td>6</td></tr><tr><td><b>Computer Science, U.Illinois at Urbana Champaign, Urbana, United States</b></td><td>6</td></tr><tr><td><b>Indian Statistical Institute, Kolkata</b></td><td>6</td></tr><tr><td>NC A&T State University, Greensboro, NC, USA</td><td>6</td></tr><tr><td><b>Department of Computer Science, Università degli Studi di Milano, Italy</b></td><td>6</td></tr><tr><td><b>College of Information Science and Engineering, Northeastern University, Shenyang, 110819, PR China</b></td><td>6</td></tr><tr><td><b>Wuyi University, Jiangmen, China</b></td><td>6</td></tr><tr><td><b>Advanced Digital Sciences Center, Singapore</b></td><td>6</td></tr><tr><td><b>School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA</b></td><td>6</td></tr><tr><td><b>Dept. of Computer Science, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</b></td><td>6</td></tr><tr><td><b>Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China</b></td><td>6</td></tr><tr><td><b>School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>6</td></tr><tr><td><b>Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China</b></td><td>6</td></tr><tr><td><b>School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China</b></td><td>6</td></tr><tr><td><b>University of Ljubljana, Ljubljana, Slovenia</b></td><td>6</td></tr><tr><td><b>University of Notre Dame, Notre Dame, IN, USA</b></td><td>6</td></tr><tr><td><b>DIA, University of Trieste, Italy</b></td><td>6</td></tr><tr><td><b>Beijing Normal University, China</b></td><td>6</td></tr><tr><td><b>The University of Queensland, Brisbane, Australia</b></td><td>6</td></tr><tr><td><b>University of Houston</b></td><td>6</td></tr><tr><td><b>Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China</b></td><td>6</td></tr><tr><td><b>School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China</b></td><td>6</td></tr><tr><td><b>Center for Machine Vision and Signal Analysis, University of Oulu, Finland</b></td><td>6</td></tr><tr><td>School of Information and Software Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, 610054, China P.R.C</td><td>6</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>6</td></tr><tr><td><b>Department of Automation, University of Science and Technology of China, Hefei, China</b></td><td>6</td></tr><tr><td><b>Department of Mechanical Engineering, Faculty of Engineering, National University of Singapore, 117576, Singapore</b></td><td>6</td></tr><tr><td><b>Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China</b></td><td>6</td></tr><tr><td><b>IIT Guwahati, Guwahati, India</b></td><td>6</td></tr><tr><td><b>School of Software, Dalian University of Technology, Dalian, China</b></td><td>6</td></tr><tr><td><b>Department of Computer Science and Engineering, Varendra University, Rajshahi, Bangladesh</b></td><td>6</td></tr><tr><td><b>Indraprastha Institute of Information Technology Delhi, New Delhi, India</b></td><td>6</td></tr><tr><td><b>School of Computer and Information, Hefei University of Technology, Hefei, China</b></td><td>6</td></tr><tr><td><b>Key Lab of Computing and Communication Software of Anhui Province, School of Computer Science and Technology, University of Science and Technology of China, Hefei, China, 230027</b></td><td>6</td></tr><tr><td><b>Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China</b></td><td>6</td></tr><tr><td><b>Queen Mary University of London, UK</b></td><td>6</td></tr><tr><td><b>Department of Computing, The Hong Kong Polytechnic University, Hong Kong</b></td><td>6</td></tr><tr><td><b>Facultad de Ingeniería, Universidad de la República, Montevideo, Uruguay</b></td><td>6</td></tr><tr><td><b>School of Software, Dalian University of Technology, China 116620</b></td><td>6</td></tr><tr><td><b>School of Computer Science & Technology, Harbin Institute of Technology</b></td><td>6</td></tr><tr><td><b>School of Computer Science and Engineering, South China University of Technology, Guangzhou, China</b></td><td>6</td></tr><tr><td><b>Microsoft Res. Asia, Beijing, China</b></td><td>5</td></tr><tr><td><b>LUNAM Université, LIUM, Le Mans, France</b></td><td>5</td></tr><tr><td><b>Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA</b></td><td>5</td></tr><tr><td><b>School of Electronics and Information, Northwestern Polytechnical University</b></td><td>5</td></tr><tr><td>Electronics and Telecommunications Research Institute, Korea</td><td>5</td></tr><tr><td><b>Institute for Microsensors, Actuators and Systems, University of Bremen, Bremen, Germany</b></td><td>5</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China, 100190</b></td><td>5</td></tr><tr><td><b>Nokia Research Center, Beijing</b></td><td>5</td></tr><tr><td><b>College of Computer Science, Zhejiang University of Technology, Hangzhou, China</b></td><td>5</td></tr><tr><td><b>Frontier Research Group, Samsung India Software Operations, India</b></td><td>5</td></tr><tr><td><b>Faculty of Information Technology, Beijing University of Technology, Beijing, China</b></td><td>5</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Bahçeşehir Üniversitesi, İstanbul, Türkiye</b></td><td>5</td></tr><tr><td><b>School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>5</td></tr><tr><td><b>IIIT-Delhi</b></td><td>5</td></tr><tr><td><b>Georgia Institute of Technology</b></td><td>5</td></tr><tr><td><b>School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea</b></td><td>5</td></tr><tr><td><b>Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China</b></td><td>5</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Science, Beijing, 100190, China</b></td><td>5</td></tr><tr><td><b>Human Language Technology Center of Excellence, The Johns Hopkins University, Baltimore, MD, 21218, USA</b></td><td>5</td></tr><tr><td><b>Department of Electronic Engineering/Graduate School at Shenzhen, Tsinghua University, China</b></td><td>5</td></tr><tr><td><b>Dalian University of Technology, China</b></td><td>5</td></tr><tr><td><b>Chinese Academy of Sciences</b></td><td>5</td></tr><tr><td><b>Nanyang Technological University, Singapore</b></td><td>5</td></tr><tr><td><b>College of Information Science and Technology, Beijing Normal University, Beijing, P.R. China</b></td><td>5</td></tr><tr><td><b>Visea İnovatif Bilgi Teknolojileri, ETGB Teknoparkı, Eskişehir, Türkiye</b></td><td>5</td></tr><tr><td><b>Ocean University of China, Department of Educational Technology, Qingdao, China</b></td><td>5</td></tr><tr><td><b>Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, China</b></td><td>5</td></tr><tr><td><b>Disney Research, UK</b></td><td>5</td></tr><tr><td>Asian Institute of Technology (AIT), Pathum Thani 12120, Thailand</td><td>5</td></tr><tr><td>Chonnam National University, Gwangju, Korea</td><td>5</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, East Lansing, MI</b></td><td>5</td></tr><tr><td><b>Microsoft Research Asia, Beijing, China</b></td><td>5</td></tr><tr><td><b>Carnegie Mellon University, ForbesAvenue, Pittsburgh PA</b></td><td>5</td></tr><tr><td><b>Telecommun. & Ind. Phys., CSIRO, Epping, NSW, Australia</b></td><td>5</td></tr><tr><td><b>Centre for Health Technologies, Faculty of Engineering and Information Technology, University of Technology, Sydney, New South Wales, Australia</b></td><td>5</td></tr><tr><td><b>Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences</b></td><td>5</td></tr><tr><td><b>Pattern Recognition and Intelligent System Laboratory, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>5</td></tr><tr><td><b>Artificial Vision Laboratory, National Taiwan University of Science and Technology, Taipei, Taiwan</b></td><td>5</td></tr><tr><td><b>Hangzhou Dianzi University, Hangzhou, China</b></td><td>5</td></tr><tr><td><b>Department of Automation, Shanghai Jiao Tong University, Shanghai, China</b></td><td>5</td></tr><tr><td><b>Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece</b></td><td>5</td></tr><tr><td><b>University of Trento, Italy, Via Sommarive, Trento (Italy)</b></td><td>5</td></tr><tr><td><b>Biometric Recognition Group - ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 - Campus de Cantoblanco - 28049, Spain</b></td><td>5</td></tr><tr><td><b>Institute of Microelectronics, Tsinghua University, Beijing, China</b></td><td>5</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Durgapur, India</td><td>5</td></tr><tr><td><b>DUT-RU International School of Information & Software Engineering, Dalian University of Technology</b></td><td>5</td></tr><tr><td><b>East China Normal University, Shanghai, China</b></td><td>5</td></tr><tr><td><b>Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>5</td></tr><tr><td><b>Department of Information Science and Engineering, Ritsumeikan University, Shiga, Japan</b></td><td>5</td></tr><tr><td><b>Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>5</td></tr><tr><td><b>Department of Automation, State Key Lab of Intelligent Technologies and Systems and Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing, China</b></td><td>5</td></tr><tr><td>Chongqing Institute of Green and Intelligent Technology, CAS, Chongqing, 400714</td><td>5</td></tr><tr><td><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China</b></td><td>5</td></tr><tr><td><b>School of Data and Computer Science, Sun Yat-Sen University, China</b></td><td>5</td></tr><tr><td><b>Centre of Development of Advanced Computing (CDAC) Mumbai, 400049, India</b></td><td>5</td></tr><tr><td><b>National Institute of Informatics, Tokyo, Japan</b></td><td>5</td></tr><tr><td><b>University of Southern California</b></td><td>5</td></tr><tr><td><b>Chongqing Institute of Technology, China</b></td><td>5</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>5</td></tr><tr><td><b>Northwestern Polytechnical University, Xi'an Shaanxi, China</b></td><td>5</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Haidian District, Beijing, China</b></td><td>5</td></tr><tr><td><b>Chinese Academy of Sciences, Beijing, China</b></td><td>5</td></tr><tr><td>SIAT at Chinese Academy of Sciences, China</td><td>5</td></tr><tr><td><b>IBM China Research Laboratory, Beijing, China</b></td><td>5</td></tr><tr><td><b>Stanford University, Stanford, CA, USA</b></td><td>5</td></tr><tr><td><b>University of California, Merced</b></td><td>5</td></tr><tr><td><b>Tsinghua National Laboratory for Information Science and Technology Institute of Microelectronics, Tsinghua University, Beijing, China</b></td><td>5</td></tr><tr><td>Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy</td><td>5</td></tr><tr><td><b>Hefei University of Technology, Hefei, China</b></td><td>5</td></tr><tr><td><b>Department of Computer Science, Xiamen University, Xiamen, P. R. China</b></td><td>5</td></tr><tr><td>University of Southern California Institute for Creative Technologies, Los Angeles, CA</td><td>5</td></tr><tr><td><b>University of Maryland, College Park, MD, USA</b></td><td>5</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798</b></td><td>5</td></tr><tr><td><b>The Institute of Optics and Electronics Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Chengdu, China</b></td><td>5</td></tr><tr><td><b>Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA</b></td><td>5</td></tr><tr><td><b>Idiap Research Institute, Martigny, Switzerland</b></td><td>5</td></tr><tr><td><b>NICTA, PO Box 6020, St Lucia, QLD 4067, Australia</b></td><td>5</td></tr><tr><td><b>College of Information and Control Engineering, China University of Petroleum, Qingdao, 266580, China</b></td><td>5</td></tr><tr><td>Department of Electronics and Telecommunication Engineering, Don Bosco Institute of Technology, Kurla (W), Mumbai, India</td><td>5</td></tr><tr><td><b>Dept. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, USA</b></td><td>5</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia</b></td><td>5</td></tr><tr><td><b>School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China</b></td><td>5</td></tr><tr><td><b>School of Electronic Engineering, Xidian University, Xi'an, China</b></td><td>5</td></tr><tr><td><b>University of Science and Technology of China, Hefei, Anhui, China</b></td><td>5</td></tr><tr><td>R V College of Engineering, Department of Computer Science and Engineering, Bangalore, India</td><td>5</td></tr><tr><td><b>Centre for Machine Vision Research, University of Oulu, Finland</b></td><td>5</td></tr><tr><td><b>Knowledge Technology Institute, Department of Informatics, University of Hamburg, Hamburg, Germany</b></td><td>5</td></tr><tr><td><b>School of Electrical Engineering Department, Korea University, Rep. of Korea</b></td><td>5</td></tr><tr><td>Inst. Nat. des Telecommun., Evry, France</td><td>5</td></tr><tr><td><b>University of Trento, Trento, Italy</b></td><td>5</td></tr><tr><td><b>National Science and Technology Development Agency, National Electronics and Computer Technology Center, Pathum Thani, 12120, Thailand</b></td><td>4</td></tr><tr><td><b>Dalian University of Technology, Dalian, Liaoning, 116024, China</b></td><td>4</td></tr><tr><td><b>School of Engineering & Applied Science, Ahmedabad University, Gujarat, India 380009</b></td><td>4</td></tr><tr><td>Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering</td><td>4</td></tr><tr><td><b>University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia</b></td><td>4</td></tr><tr><td><b>The Australian Centre for Visual Technologies, The university of Adelaide</b></td><td>4</td></tr><tr><td><b>University of the Western Cape, Bellville, Western Cape</b></td><td>4</td></tr><tr><td><b>School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, 6140, New Zealand</b></td><td>4</td></tr><tr><td><b>Tsinghua University</b></td><td>4</td></tr><tr><td><b>National Taiwan University, Taipei, Taiwan</b></td><td>4</td></tr><tr><td><b>School of Computer Science & Technology, Nanjing University of Science and Technology, China</b></td><td>4</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Rowan University, Glassboro, NJ- 08028</b></td><td>4</td></tr><tr><td><b>School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China, 710049</b></td><td>4</td></tr><tr><td><b>Media Integration and Communication Center - MICC, University of Florence, Italy</b></td><td>4</td></tr><tr><td><b>School of Computer Science, University of the Witwatersrand, Johannesburg, South Africa</b></td><td>4</td></tr><tr><td>Department of Microelectornics and Computer Science, Lodz University of Technology, ul. Wolczanska 221/223, 90-924, Poland</td><td>4</td></tr><tr><td><b>School of Computer Science and Telecommunication Engineering, Jiangsu University, ZhenJiang, Jiangsu, 212013, P. R. China</b></td><td>4</td></tr><tr><td><b>Seoul Nat'l Univ.</b></td><td>4</td></tr><tr><td><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China 100876</b></td><td>4</td></tr><tr><td><b>Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, China</b></td><td>4</td></tr><tr><td><b>Institute of Computer Science and Technology, Peking University, Beijing, China, 100871</b></td><td>4</td></tr><tr><td><b>Department of Electronic Engineering, Tsinghua University, Beijing 100084, China</b></td><td>4</td></tr><tr><td><b>School of Computer Science and Engineering, Nanjing University of Science and Technology, China</b></td><td>4</td></tr><tr><td><b>Faculty of electrical engineering, University of Ljubljana, Slovenia</b></td><td>4</td></tr><tr><td><b>Department of Information Management and Security, Korea University</b></td><td>4</td></tr><tr><td><b>Pattern Recognition and Intelligent System Lab (PRIS) Beijing University of Posts and Telecommunications, Beijing 100876, P. R. China</b></td><td>4</td></tr><tr><td><b>Institute of Intelligence Information Processing, Xidian University, Xi¿an, China, 710071</b></td><td>4</td></tr><tr><td><b>Research Center for Information Technology Innovation (CITI), Academia Sinica, Taipei, 115 Taiwan</b></td><td>4</td></tr><tr><td><b>University of Miami, Coral Gables, FL</b></td><td>4</td></tr><tr><td><b>Univ. Orléans, INSA CVL, PRISME EA 4229, Bourges, France</b></td><td>4</td></tr><tr><td><b>Institute of Systems and Robotics (ISR), University of Coimbra, Portugal</b></td><td>4</td></tr><tr><td><b>Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong</b></td><td>4</td></tr><tr><td><b>School of Electrical and Electronics Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, SEOUL, Republic of Korea</b></td><td>4</td></tr><tr><td><b>School of Information Science and Engineering, Southeast University, Nanjing, 210096, P.R. China</b></td><td>4</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea</b></td><td>4</td></tr><tr><td><b>Hong Kong University of Science and Technology, Hong Kong</b></td><td>4</td></tr><tr><td><b>INRIA Grenoble Rhone-Alpes, FRANCE</b></td><td>4</td></tr><tr><td>North China Electric Power University Department of Electronic and Communication Engineering Baoding, Hebei, China</td><td>4</td></tr><tr><td><b>Seoul National University</b></td><td>4</td></tr><tr><td>School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand</td><td>4</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China</b></td><td>4</td></tr><tr><td><b>School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology Guangxi Guilin, China</b></td><td>4</td></tr><tr><td><b>University of Portsmouth, United Kingdom</b></td><td>4</td></tr><tr><td><b>Carnegie Mellon University</b></td><td>4</td></tr><tr><td><b>Bilgisayar Mühendisliği, Başkent Üniversitesi, Ankara, Türkiye</b></td><td>4</td></tr><tr><td><b>Universidad Autonoma de Madrid</b></td><td>4</td></tr><tr><td><b>University of Oulu, Machine Vision Group, PO Box 4500, 90014, Finland</b></td><td>4</td></tr><tr><td><b>Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea</b></td><td>4</td></tr><tr><td><b>Center for Computer Vision and Department of Mathematics, Sun Yat-Sen University, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland</b></td><td>4</td></tr><tr><td>KU Leuven, Leuven, Belgium</td><td>4</td></tr><tr><td>Academia Sinica, Taipei, Taiwan</td><td>4</td></tr><tr><td><b>Institute of Computer, Hangzhou Dianzi University, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, No.95 East Road of Zhongguancun, Beijing, China</b></td><td>4</td></tr><tr><td>LIARA Laboratory, University of Quebec at Chicoutimi (UQAC), Boulevard de l'Université, Chicoutimi (Quebec), Canada</td><td>4</td></tr><tr><td>Dept. of Computing, Curtin University GPO Box U1987, Perth, WA 6845</td><td>4</td></tr><tr><td><b>Department of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, China</b></td><td>4</td></tr><tr><td>NTT Software Innovation Center, Tokyo, Japan</td><td>4</td></tr><tr><td><b>Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China</b></td><td>4</td></tr><tr><td><b>University of Electronic Science and Technology of China, Chengdu, China</b></td><td>4</td></tr><tr><td><b>Dalle Molle Instituite for Artificial Intelligence (IDSIA), Lugano, Switzerland</b></td><td>4</td></tr><tr><td><b>Dept of Electrical and Computer Engineering, University of Calgary, Calgary, CANADA</b></td><td>4</td></tr><tr><td><b>Department of Computer Science, University of Colorado at Colorado Springs</b></td><td>4</td></tr><tr><td>EECS Department, University of Kansas, Lawrence, KS</td><td>4</td></tr><tr><td><b>Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, Hunan, P.R. China</b></td><td>4</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 100190</b></td><td>4</td></tr><tr><td><b>The Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia</b></td><td>4</td></tr><tr><td><b>School of Information and Communication, Guilin University of Electronic Technology Guangxi Guilin, China</b></td><td>4</td></tr><tr><td><b>College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, P.R. China</b></td><td>4</td></tr><tr><td>Department of Mathematics and Computer Science University of Basel</td><td>4</td></tr><tr><td><b>Xi'an Jiaotong University, Xi'an, China</b></td><td>4</td></tr><tr><td><b>Department of Information Engineering, University of Brescia, Via Branze, 38 - 25123, Italy</b></td><td>4</td></tr><tr><td><b>Department of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China</b></td><td>4</td></tr><tr><td>Goa University, India</td><td>4</td></tr><tr><td><b>University of Texas at Arlington, Arlington, TX</b></td><td>4</td></tr><tr><td><b>Norwegian Biometrics Laboratory, NTNU - Gj⊘vik, Norway</b></td><td>4</td></tr><tr><td><b>Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, U.K.</b></td><td>4</td></tr><tr><td><b>University of Nottingham, UK</b></td><td>4</td></tr><tr><td>Beijing Key Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081, China</td><td>4</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education, International Research Center for Intelligent Perception and Computation, Joint International Research Laboratory of Intelligent Perception and Computation of China, Xidian University, Xi’an, China</b></td><td>4</td></tr><tr><td>VUB-NPU Joint AVSP Research Lab, Vrije Universiteit Brussel (VUB), Deptartment of Electronics & Informatics (ETRO), Pleinlaan 2, 1050 Brussel, Belgium</td><td>4</td></tr><tr><td><b>National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, Chengdu, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, China</b></td><td>4</td></tr><tr><td><b>Department of Electronic and Electrical Engineering, Pohang University of Science and Technology (POSTECH), South Korea</b></td><td>4</td></tr><tr><td><b>University of Canberra, Canberra, Australia</b></td><td>4</td></tr><tr><td>Graduate School of Information Science, Nara Institute of Science and Technology, Takayama-cho 8916-5, Ikoma-shi, Nara, Japan</td><td>4</td></tr><tr><td><b>Department of Computer Science, University of North Carolina, Charlotte, NC, USA</b></td><td>4</td></tr><tr><td><b>Institute of Machine Learning and Systems Biology, College of Electronics and Information Engineering, Tongji University, Caoan Road 4800, Shanghai 201804, China</b></td><td>4</td></tr><tr><td><b>Intel Labs, Hillsboro, Oregon, USA</b></td><td>4</td></tr><tr><td>Smart Surveillance Interest Group, Department of Computer Science, Universidade Federal de Minas Gerais, Minas Gerais, Brazil</td><td>4</td></tr><tr><td><b>Department of Automation, State Key Lab of Intelligent Technologies and Systems, and Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing, China</b></td><td>4</td></tr><tr><td><b>Université de Lyon, CNRS, UMR5205, F-69622, France</b></td><td>4</td></tr><tr><td>Shanghai University School of Communication and Information Engineering Shanghai, China</td><td>4</td></tr><tr><td>Microsoft, Redmond, WA, USA</td><td>4</td></tr><tr><td>Computer Science and Engineering, Pennsylvania State University, PA, USA SiliconScapes, LLC, PA, USA</td><td>4</td></tr><tr><td><b>Key Laboratory of Intelligent Information Processing, Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, China</b></td><td>4</td></tr><tr><td><b>Queen Mary University of London, London</b></td><td>4</td></tr><tr><td>Dept. of Computer Engineering, Keimyung University, Daegu, Korea</td><td>4</td></tr><tr><td><b>Department of Cognitive Science, Xiamen University, Xiamen, Fujian, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China</b></td><td>4</td></tr><tr><td><b>Université de Lyon, CNRS, UMR5205, F-69622, France</b></td><td>4</td></tr><tr><td><b>School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, 116024, China</b></td><td>4</td></tr><tr><td><b>DII, University of Brescia, Brescia, Italy</b></td><td>4</td></tr><tr><td><b>School of Software, Tsinghua University, Beijing, China</b></td><td>4</td></tr><tr><td>National ICT Australia and UNSW, Sydney, Australia</td><td>4</td></tr><tr><td><b>Institute for Creative Technologies, University of Southern California</b></td><td>4</td></tr><tr><td><b>School of Information Science and Technology, Xiamen University, Xiamen, China</b></td><td>4</td></tr><tr><td><b>University of California, San Diego, USA</b></td><td>4</td></tr><tr><td><b>The University of Queensland, School of ITEE, QLD 4072, Australia</b></td><td>4</td></tr><tr><td><b>Department of Computer Science, University of York, UK</b></td><td>4</td></tr><tr><td><b>Department of Automation, State Key Lab of Intelligent Technologies and Systems, Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing, China</b></td><td>4</td></tr><tr><td><b>Dept. of Computer Science, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>4</td></tr><tr><td><b>SRI International, Menlo Park, USA</b></td><td>4</td></tr><tr><td><b>Université de Lyon, CNRS, France</b></td><td>4</td></tr><tr><td><b>School of Computer Science and Technology & Joint International Research Laboratory of Machine Learning and Neuromorphic Computing, Soochow University, Suzhou, China</b></td><td>4</td></tr><tr><td><b>Department of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China</b></td><td>4</td></tr><tr><td><b>Computer Science and Engineering Department, University of South Florida, Tampa, FL, USA</b></td><td>4</td></tr><tr><td><b>Advanced Technologies Application Center 7a #21406 b/ 214 and 216, P.C. 12200, Siboney, Playa, Havana, Cuba</b></td><td>4</td></tr><tr><td><b>Çoğulortam İşaret İşleme ve Örüntü Tanıma Grubu, İstanbul Teknik Üniversitesi, İstanbul, Türkiye</b></td><td>4</td></tr><tr><td>Department of Electrical and Computer Engineering, Beckman Institute Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, IL, USA</td><td>4</td></tr><tr><td><b>National Laboratory of Pattern Recognition, CASIA, Center for Research on Intelligent Perception and Computing, CASIA, Center for Excellence in Brain Science and Intelligence Technology, CAS, University of Chinese Academy of Sciences, Beijing, 100049, China</b></td><td>4</td></tr><tr><td><b>Machine Learning and Cybernetics Research Center, School of Computer Science and Engineering, South China University of Technology, 510006, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>IC Design Group, CSIR-Central Electronics Engineering Research Institute, Pilani, Rajasthan, India</b></td><td>4</td></tr><tr><td><b>College of Information Engineering, Yangzhou University, Yangzhou, China</b></td><td>4</td></tr><tr><td><b>Department of Mathematics, Intelligent Data Center, Sun Yat-sen University, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Electronic Engineering, Tsinghua University, Beijing 100084, China</b></td><td>4</td></tr><tr><td>Universiti Kuala Lumpur, Kuala Lumpur</td><td>4</td></tr><tr><td><b>Max Planck Institute for Informatics, Saarland Informatics Campus, Germany</b></td><td>4</td></tr><tr><td><b>National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China</b></td><td>4</td></tr><tr><td><b>Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>4</td></tr><tr><td>Beijing Normal Univeristy, Beijing, China</td><td>4</td></tr><tr><td><b>Information Sciences Institute, University of Southern California, 4676 Admiralty Way, Marina Del Rey, 90292, USA</b></td><td>4</td></tr><tr><td><b>National University of Defense Technology, China</b></td><td>4</td></tr><tr><td><b>National Digital Switching System Engineering and Technological Research Center, Zhengzhou, China</b></td><td>4</td></tr><tr><td><b>Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong</b></td><td>4</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA</b></td><td>4</td></tr><tr><td><b>University of Tsukuba</b></td><td>4</td></tr><tr><td><b>University of Electronic Science and Technology of China</b></td><td>4</td></tr><tr><td><b>National Taiwan University of Science and Technology</b></td><td>4</td></tr><tr><td><b>Samsung R&D Institute, Bangalore, India</b></td><td>4</td></tr><tr><td><b>Yaroslavl State University, Yaroslavl, Russia</b></td><td>4</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Seoul National University</b></td><td>4</td></tr><tr><td><b>College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China</b></td><td>4</td></tr><tr><td><b>School of Electronics and Information Technology, Sun Yat-sen University, China</b></td><td>4</td></tr><tr><td>University of Tunis, The National Higher school of engineers of Tunis (ENSIT), Laboratory of Signal Image and Energy Mastery, LR13ES03 (SIME), Tunis, Tunisia</td><td>4</td></tr><tr><td><b>College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China</b></td><td>4</td></tr><tr><td><b>Department of Computer Science and Engineering, Sejong University, 98 Gunja, Gwangjin, Seoul 143-747, Korea</b></td><td>4</td></tr><tr><td><b>University of Maryland, College Park, Maryland 20740 United States</b></td><td>4</td></tr><tr><td><b>Face Aging Group, University of North Carolina, Wilmington, NC, USA</b></td><td>4</td></tr><tr><td><b>Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China</b></td><td>4</td></tr><tr><td><b>North Carolina State University, Department of Electrical and Computer Engineering, Raleigh, United States of America</b></td><td>4</td></tr><tr><td><b>Institute of Computer Science and Technology, Peking University, Beijing, China</b></td><td>4</td></tr><tr><td><b>College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>4</td></tr><tr><td>Media Technology Lab, Huawei Technologies Co., Ltd</td><td>4</td></tr><tr><td><b>Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, 28 Xianning West Road, Xi'an, Shaanxi, China</b></td><td>4</td></tr><tr><td><b>Keio University, Japan</b></td><td>4</td></tr><tr><td><b>National University of Defense Technology, Changsha, China</b></td><td>4</td></tr><tr><td><b>Hewlett-Packard Laboratories, Hewlett-Packard Company, Palo Alto, CA, USA</b></td><td>4</td></tr><tr><td><b>School of Computer Science and Engineering, Center for Robotics, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>4</td></tr><tr><td><b>Image Processing Center, Beihang University, Beijing, China</b></td><td>4</td></tr><tr><td><b>School of Electronic and Computer Engineering, Peking University</b></td><td>4</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing University of Surrey, Guildford, UK</b></td><td>4</td></tr><tr><td><b>Shenzhen Key Laboratory of Information Science and Technology, Shenzhen Engineering Laboratory of IS&DCP and the Department of Electronic Engineering, Graduate School at Shenzhen, Tsinghua University, Beijing, China</b></td><td>4</td></tr><tr><td>Department of Computer Graphics and Multimedia, University of Brno, Brno, Czech Republic</td><td>4</td></tr><tr><td><b>Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain</b></td><td>4</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China</b></td><td>4</td></tr><tr><td><b>Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, People's Republic of China</b></td><td>4</td></tr><tr><td><b>Video/Image Modeling and Synthesis Laboratory, Department of Computer and Information Sciences, University of Delaware, Newark, DE</b></td><td>4</td></tr><tr><td><b>Multimedia Processing Lab., Samsung Advanced Institute of Technology (SAIT), Suwon-si, Korea</b></td><td>4</td></tr><tr><td>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA</td><td>4</td></tr><tr><td><b>Osaka university, Japan</b></td><td>4</td></tr><tr><td><b>IBJ, Inc., Tokyo, Japan</b></td><td>4</td></tr><tr><td><b>The University of Tokyo, Japan</b></td><td>4</td></tr><tr><td>Faculty of Engineering, Ain Shams University, Computer and Systems Engineering Department, Cairo, Egypt</td><td>4</td></tr><tr><td>School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, China</td><td>4</td></tr><tr><td><b>College of electronic and information engineer Changchun University of Science and Technology Changchun China</b></td><td>4</td></tr><tr><td><b>School of Electrical, Computer and Telecommunication Engineering, University of Wollongong, NSW 2522, Australia</b></td><td>4</td></tr><tr><td><b>The University of Texas at Austin Austin, Texas, USA</b></td><td>4</td></tr><tr><td><b>Amity University Uttar Pradesh, Noida</b></td><td>4</td></tr><tr><td><b>Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea</b></td><td>4</td></tr><tr><td>Computer Science and Engineering Dept., University of Nevada Reno, USA</td><td>4</td></tr><tr><td><b>Dept of Computer Engineering, Kyung Hee University, Yongin-si, South Korea</b></td><td>4</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, TX, USA</b></td><td>4</td></tr><tr><td><b>University of Surrey, Guildford</b></td><td>4</td></tr><tr><td>Department of Information and Control, B-DAT Laboratory, Nanjing University of Information and Technology, Nanjing, China</td><td>4</td></tr><tr><td><b>State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Robotics, Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, 110016, China</b></td><td>4</td></tr><tr><td>Inha University, South Korea</td><td>4</td></tr><tr><td><b>Sharp Laboratories of America, Camas, WA</b></td><td>4</td></tr><tr><td><b>Department of Informatics, Aristotle University of Thessaloniki, Greece</b></td><td>4</td></tr><tr><td><b>Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Netherlands</b></td><td>4</td></tr><tr><td><b>Center for Biometrics and Security Research and the National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>4</td></tr><tr><td><b>Geintra Research Group, University of Alcala</b></td><td>4</td></tr><tr><td><b>National Engineering Research Center for Multimedia Software, Computer School, Wuhan University, Wuhan, China</b></td><td>4</td></tr><tr><td><b>Electrical and Computer Systems Engineering, School of Engineering, Monash University Malaysia, 46150 Selangor, Malaysia</b></td><td>4</td></tr><tr><td><b>Beijing Laboratory of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing, China</b></td><td>4</td></tr><tr><td><b>Department of Computer Science, Hong Kong Baptist University, Hong Kong</b></td><td>4</td></tr><tr><td><b>University of Science and Technology of China, Hefei, China</b></td><td>4</td></tr><tr><td><b>Beijing, Haidian, China</b></td><td>4</td></tr><tr><td>Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China</td><td>4</td></tr><tr><td><b>School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, U.S.A.</b></td><td>4</td></tr><tr><td>Institute for Human-Machine Communication, Technische Universität München, Germany</td><td>4</td></tr><tr><td><b>Peking University, Shenzhen, China</b></td><td>4</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada</b></td><td>4</td></tr><tr><td>Faculty of Engineering Science, Department of Systems Innovation, Arai Laboratory at Osaka University, Japan</td><td>4</td></tr><tr><td><b>Biometric Recognition Group - ATVS, EPS, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 - Campus de Cantoblanco - 28049 Madrid, Spain</b></td><td>4</td></tr><tr><td><b>Department of MathematicsIntelligent Data Center, Sun Yat-sen University, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>University of Trento, Italy</b></td><td>4</td></tr><tr><td><b>Centre for Imaging Sciences, The University of Manchester, Manchester, United Kingdom</b></td><td>4</td></tr><tr><td><b>National Laboratory of Pattern Recognition, CASIA, University of Chinese Academy of Sciences, Beijing, 100049, China</b></td><td>4</td></tr><tr><td><b>School of Electronic and Electrical Engineering, Shanghai Jiao Tong University, National Engineering Lab on Information Content Analysis Techniques, GT036001 Shanghai, China</b></td><td>4</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences</b></td><td>4</td></tr><tr><td><b>Department of Informatics, University of Oslo, Oslo, Norway</b></td><td>4</td></tr><tr><td><b>Speech, Audio, Image and Video Technology (SAIVT) Laboratory, Queensland University of Technology, Australia</b></td><td>4</td></tr><tr><td><b>Technicolor, France</b></td><td>4</td></tr><tr><td><b>Korea Advanced Institute of Science and Technology, Daejeon, South Korea</b></td><td>4</td></tr><tr><td><b>School of Mathematics and Computational Science, Sun Yat-sen University, Guangzhou, China</b></td><td>4</td></tr><tr><td><b>School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China</b></td><td>3</td></tr><tr><td><b>CyLab Biometrics Center and the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>3</td></tr><tr><td>NTT Corporation, Atsugi, Japan</td><td>3</td></tr><tr><td>Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beersheba, Israel</td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China</b></td><td>3</td></tr><tr><td><b>Vision Lab at Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA 23529, USA</b></td><td>3</td></tr><tr><td>Intel Labs China, Beijing, China</td><td>3</td></tr><tr><td><b>IBM T. J. Watson Research, Yorktown Heights, NY, USA</b></td><td>3</td></tr><tr><td><b>Computer Science and Technology, University of Science and Technology of China</b></td><td>3</td></tr><tr><td><b>School of Information Technologies, University of Sydney, Australia</b></td><td>3</td></tr><tr><td><b>Department of Electronic Engineering, The Chinese University of Hong Kong, China</b></td><td>3</td></tr><tr><td><b>Key Laboratory of Machine Perception (Ministry of Education) Engineering Lab on Intelligent Perception for Internet of Things (ELIP), Shenzhen Graduate School, Peking University, China</b></td><td>3</td></tr><tr><td>School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun, CO 130012 China</td><td>3</td></tr><tr><td><b>Center for Cognitive Ubiquitous Computing, Arizona State University, USA</b></td><td>3</td></tr><tr><td><b>School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Institute of Computing, State University of Campinas, Campinas, Brazil</b></td><td>3</td></tr><tr><td><b>Guangdong Key Laboratory of Data Security and Privacy Preserving, Guangdong Engineering Research Center of Data Security and Privacy Preserving, College of Information Science and Technology, Jinan University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>State Key Laboratory of Intelligent Technology and Systems, Department of Electronic Engineering, Tsinghua University, Beijing 100084, P.R. China</b></td><td>3</td></tr><tr><td><b>CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei 230027, China</b></td><td>3</td></tr><tr><td><b>Tokyo Institute of Technology, Tokyo, Japan</b></td><td>3</td></tr><tr><td>Radboud University, Nijmegen, Netherlands</td><td>3</td></tr><tr><td>Algılayıcılar, Görüntü ve Sinyal İşleme Grubu, HAVELSAN A.Ş. Ankara, Türkiye</td><td>3</td></tr><tr><td><b>C & C Innovation Research Labs, NEC Corporation, Nara, Japan</b></td><td>3</td></tr><tr><td>Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany</td><td>3</td></tr><tr><td><b>Imperial College London, UK</b></td><td>3</td></tr><tr><td>School of Electrical and Computer Engineering, Royal Melbourne Institute of Technology University , Melbourne, Australia</td><td>3</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, The University of Queensland, Australia</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Kyung Hee University, Seoul, South Korea</b></td><td>3</td></tr><tr><td><b>Institute for Infocomm Research, 1 Fusionpolis Way, #21-01, Connexis Singapore 138632, Singapore</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Engineering, South China University of Technology, China</b></td><td>3</td></tr><tr><td><b>Department of Radiology and the Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA</b></td><td>3</td></tr><tr><td><b>Dept. of Electrical Engineering and Comp. Sc., Northwestern University, Evanston, IL 60208, USA</b></td><td>3</td></tr><tr><td><b>School of Electronics and Computer Science, University of Southampton, Southampton, U.K.</b></td><td>3</td></tr><tr><td><b>School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China</b></td><td>3</td></tr><tr><td><b>Program of Electrical Engineering, COPPE/UFRJ, Universidade Federal do Rio de Janeiro, Rio de Janeiro-RJ CEP, Brazil</b></td><td>3</td></tr><tr><td><b>Bilgisayar Mühendisliği, İstanbul Teknik Üniversitesi, İstanbul, Turkey</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering and the Center for Automation Research, UMIACS, University of Maryland, College Park, USA</b></td><td>3</td></tr><tr><td><b>Department of Computer Engineering, Kyung Hee University, Seoul, South Korea</b></td><td>3</td></tr><tr><td><b>Michigan State University, United States of America</b></td><td>3</td></tr><tr><td>School of Engineering, University of Baja California, Tijuana, México</td><td>3</td></tr><tr><td><b>Center for Machine Vision Research, University of Oulu</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, University of South Florida, Tampa, Florida 33620</b></td><td>3</td></tr><tr><td><b>KTH Royal Institute of Technology, 100 44 Stockholm, Sweden</b></td><td>3</td></tr><tr><td><b>School of Software, Huazhong University of Science and Technology, Wuhan, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA</b></td><td>3</td></tr><tr><td>School of Computer Science, Center for Optical Imagery Analysis and Learning (OPTIMAL)</td><td>3</td></tr><tr><td><b>Department of Computing, Curtin University, Perth WA 6102, Australia</b></td><td>3</td></tr><tr><td>Department of Systems and Computing, Federal University of Campina Grande, Av. Apríigio Veloso, 882, 58429-900 Campina Grande, PB, Brazil</td><td>3</td></tr><tr><td><b>Institute of Imaging and Computer Vision, RWTH Aachen University, Templergraben 55, 52056, Aachen, Germany</b></td><td>3</td></tr><tr><td><b>Universidade Federal do Rio de Janeiro, Cx.P. 68504, Rio de Janeiro, RJ, CEP 21945-970, Brazil</b></td><td>3</td></tr><tr><td>R&D Centre Algoritmi, School of Engineering, University of Minho, Portugal</td><td>3</td></tr><tr><td><b>National Laboratory for Parallel and Distributed Processing, School of Computer, College of Computer, National University of Defense Technology, Changsha, China</b></td><td>3</td></tr><tr><td><b>Department of Computer and Information Science, Temple University, Philadelphia, PA, 19122, USA</b></td><td>3</td></tr><tr><td>Department of Control and Computer Engineering, Politecnico di Torino, Italy</td><td>3</td></tr><tr><td><b>Key Laboratory of System Control and Information Processing MOE, Department of Automation, Shanghai Jiao Tong University</b></td><td>3</td></tr><tr><td><b>College of Computer Science, Zhejiang University, China</b></td><td>3</td></tr><tr><td><b>Institute of Industrial Information Technology (IIIT), Karlsruhe Institute of Technology (KIT), 76187 Karlsruhe, Germany</b></td><td>3</td></tr><tr><td><b>School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>Institute for Electronics, Signal Processing and Communications (IESK), Otto-von-Guericke-University Magdeburg, D-39106, P.O. Box 4210 Germany</b></td><td>3</td></tr><tr><td><b>Institute for Human-Machine Communication, TU München, Theresienstrae 90, 80333 München, Germany</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Technology, Harbin Institute of Technology, China</b></td><td>3</td></tr><tr><td><b>Oak Ridge National Laboratory, USA</b></td><td>3</td></tr><tr><td>Center for Research in Intelligent Systems, University of California, Riverside Riverside, CA 92521-0425, USA</td><td>3</td></tr><tr><td><b>Department of CS&E, Indian Institute of Technology, Madras, India</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Windsor, 401 Sunset Avenue, Windsor, N9B 3P4, Canada</b></td><td>3</td></tr><tr><td>Shanghai Advanced Research Institute, CAS, Shanghai, China</td><td>3</td></tr><tr><td><b>Elektrik ve Elektronik Mühendisliği Bölümü, Eskişehir Osmangazi Üniversitesi, Türkiye</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Zhejiang University, Hangzhou, China</b></td><td>3</td></tr><tr><td><b>Software Solution Laboratory, Samsung Advanced Institute of Technology, Suwon-si, South Korea</b></td><td>3</td></tr><tr><td><b>Florida International University, Miami, FL</b></td><td>3</td></tr><tr><td><b>Rice University</b></td><td>3</td></tr><tr><td>Department of electronic engineering, Key Lab of Intelligent Perception and Image Understanding of Ministry of Education, Xi'an, China</td><td>3</td></tr><tr><td><b>Centre of Informatics, Federal University of Pernambuco, Recife-PE, Brazil. Bruno J. T. Fernandes is also with the Polytechnic School, University of Pernambuco, Brazil</b></td><td>3</td></tr><tr><td>Computer Vision Laboratory, ETH Zurich, Sternwartstrasse 7, 8092, Switzerland</td><td>3</td></tr><tr><td><b>VNU HCMC, University of Science, Ho Chi Minh City, Vietnam</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Peking University, Beijing, China</b></td><td>3</td></tr><tr><td><b>Instrumentation, IT and Systems Lab IRSEEM Rouen, FR</b></td><td>3</td></tr><tr><td><b>Aristotle University of Thessaloniki, Greece</b></td><td>3</td></tr><tr><td><b>School of Automation, Northwestern Polytechnical University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Arizona State University, Tempe, AZ, USA</b></td><td>3</td></tr><tr><td>BITS Pilani, Pilani , India</td><td>3</td></tr><tr><td>Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, Howrah-711 103, India</td><td>3</td></tr><tr><td><b>College of Information and Control Engineering, China University of Petroleum (East China), Qingdao, Shandong, 266580, China</b></td><td>3</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences</b></td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition CAS Center for Excellence in Brain Science and Intelligence Technology Institute of Automation, Chinese Academy of Sciences, 100190, China</b></td><td>3</td></tr><tr><td><b>Univ. Bordeaux, LaBRI, PICTURA, UMR 5800, F-33400 Talence, France</b></td><td>3</td></tr><tr><td><b>Tianjin University, China</b></td><td>3</td></tr><tr><td><b>The Univ of Hong Kong, China</b></td><td>3</td></tr><tr><td><b>Advanced Technologies Application Center (CENATAV), 7A ♯21406 Siboney, Playa, P.C.12200, Havana, Cuba</b></td><td>3</td></tr><tr><td><b>GIPSA-Lab, Grenoble, France</b></td><td>3</td></tr><tr><td><b>University of Maryland, Baltimore County, Baltimore, MD, USA</b></td><td>3</td></tr><tr><td>Dept. of CS&E, IIT Madras, India</td><td>3</td></tr><tr><td><b>Samsung Research and Development Institute Bangalore Pvt Ltd., Bangalore, India</b></td><td>3</td></tr><tr><td><b>Inst. of Autom., Shanghai Jiao Tong Univ., China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, New Jersey Institute of Technology, Newark, USA</b></td><td>3</td></tr><tr><td><b>State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Imperial College London, London, U.K.</b></td><td>3</td></tr><tr><td><b>Center for Cognitive Ubiquitous Computing (CUbiC), Arizona State University, Tempe, AZ, USA</b></td><td>3</td></tr><tr><td><b>Department of Computing, Curtin University, Perth WA, Australia</b></td><td>3</td></tr><tr><td><b>SUNY Buffalo</b></td><td>3</td></tr><tr><td>Graduate School of System Design Tokyo Metropolitan University Tokyo, Japan</td><td>3</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, TOBB Ekonomi ve Teknoloji Üniversitesi, Ankara, Türkiye</b></td><td>3</td></tr><tr><td><b>Intelligent Data Center, School of Mathematics and Computational Science, Sun Yat-sen University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>Indian Institute of Information Technology at Allahabad, Allahabad, India</b></td><td>3</td></tr><tr><td>Face Aging Group, Computer Science Department, UNCW, USA</td><td>3</td></tr><tr><td>City University of New York, New York, NY, USA</td><td>3</td></tr><tr><td><b>Department of Computer Science and Digital Technologies, Faculty of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, U.K.</b></td><td>3</td></tr><tr><td><b>Faculty of Information Technology, University of Technology, Sydney, Australia</b></td><td>3</td></tr><tr><td>Department of Computer Science and Engineering, Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India</td><td>3</td></tr><tr><td><b>School of Computing, Communications and Electronics, University of Plymouth, UK</b></td><td>3</td></tr><tr><td>Ghent University, Ghent, Belgium</td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA</b></td><td>3</td></tr><tr><td><b>University of California San Diego, United States of America</b></td><td>3</td></tr><tr><td>Columbia Univeristy, New York, NY, USA</td><td>3</td></tr><tr><td><b>Key Lab of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China</b></td><td>3</td></tr><tr><td>Microsoft Research Cambridge</td><td>3</td></tr><tr><td><b>Singapore University of Technology and Design, Singapore</b></td><td>3</td></tr><tr><td><b>School of Information Science and Technology, Xiamen University, Xiamen, P. R. China</b></td><td>3</td></tr><tr><td><b>Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan</b></td><td>3</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, The University of Queensland</b></td><td>3</td></tr><tr><td>Center for Automation Research, UMIACS University of Maryland, College Park, MD 20742</td><td>3</td></tr><tr><td>School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, U.K.</td><td>3</td></tr><tr><td><b>Advanced Digital Sciences Center (ADSC), University of Illinois at Urbana-Champaign, Singapore</b></td><td>3</td></tr><tr><td><b>University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, University of Hamburg, Germany</b></td><td>3</td></tr><tr><td><b>Department of Computer ScienceMultimedia Processing Laboratory, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>3</td></tr><tr><td><b>West Virginia University, Lane Dept. of CSEE, Morgantown, WV</b></td><td>3</td></tr><tr><td><b>University of California San Diego</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, China</b></td><td>3</td></tr><tr><td><b>School of Information Technologies, The University of Sydney, NSW 2006, Australia, Sydney</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, University of Windsor, Ontario, Canada</b></td><td>3</td></tr><tr><td>School of Information and Communication Engineering, Beijing University of Posts and Telcommunications, Beijing, China</td><td>3</td></tr><tr><td><b>INRIA Grenoble Rhône-Alpes Research Center, 655 avenue de l'Europe, 38 334 Saint Ismier Cedex, France</b></td><td>3</td></tr><tr><td><b>National Institutes of Health, Bethesda, Maryland 20892</b></td><td>3</td></tr><tr><td><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>3</td></tr><tr><td>Gwangju Institute of Science and Technology, 123, Cheomdangwagi-ro, Buk-gu, Gwangju, South Korea</td><td>3</td></tr><tr><td><b>Department of Computing, The Hong Kong Polytechnic University, China</b></td><td>3</td></tr><tr><td><b>Harvard University</b></td><td>3</td></tr><tr><td><b>School of Computing and Information Sciences, Florida International University, Miami, FL</b></td><td>3</td></tr><tr><td><b>College of Electronic Information and Automation, Civil Aviation University of China, Tianjin</b></td><td>3</td></tr><tr><td><b>Department of Automation, Tsinghua University, 100084 Beijing, China</b></td><td>3</td></tr><tr><td><b>NICTA, Canberra ACT, Australia and CECS, Australian National University, Australia</b></td><td>3</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>3</td></tr><tr><td><b>Research Center of Intelligent Robotics, Shanghai Jiao Tong University, Shanghai 200240, P.R China</b></td><td>3</td></tr><tr><td><b>UtopiaCompression Corporation, 11150 W. Olympic Blvd, Suite 820, Los Angeles, CA 90064, USA</b></td><td>3</td></tr><tr><td><b>Chinese Academy of Sciences, China</b></td><td>3</td></tr><tr><td><b>Laboratoire des Systèmes de Télécommunication et Ingénierie de la Décision (LASTID) Université Ibn Tofail BP 133, Kenitra 14000, Maroc</b></td><td>3</td></tr><tr><td><b>Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR 7222, F-75005, Paris, France</b></td><td>3</td></tr><tr><td><b>Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan</b></td><td>3</td></tr><tr><td><b>School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China</b></td><td>3</td></tr><tr><td><b>University of Wisconsin - Madison</b></td><td>3</td></tr><tr><td><b>Mines-Télécom/Télécom Lille, CRIStAL (UMR CNRS 9189), Villeneuve d'Ascq, France</b></td><td>3</td></tr><tr><td><b>Kyung Hee University, Korea</b></td><td>3</td></tr><tr><td><b>Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina</b></td><td>3</td></tr><tr><td><b>Stony Brook University, Stony Brook, NY 11794, USA</b></td><td>3</td></tr><tr><td><b>University of Delaware, Newark, 19716, USA</b></td><td>3</td></tr><tr><td><b>Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Adenauerring 4, 76131, Germany</b></td><td>3</td></tr><tr><td><b>University at Buffalo, The State University of New York, Buffalo, NY 14203, USA</b></td><td>3</td></tr><tr><td><b>UIUC</b></td><td>3</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, 4800 Calhoun Rd., TX, 77004, USA</b></td><td>3</td></tr><tr><td><b>Pattern Recognition and Intelligent Systems Laboratory, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>3</td></tr><tr><td><b>Laboratory of Intelligent Recognition and Image Processing, School of Computer Science and Engineering, Beihang University, 100191, Beijing, China</b></td><td>3</td></tr><tr><td><b>Face Aging Group, UNCW</b></td><td>3</td></tr><tr><td><b>University of Texas at San Antonio, San Antonio, USA</b></td><td>3</td></tr><tr><td><b>College of Computer Science and Technology, Xinjiang Normal University, Urumchi, 830054, China</b></td><td>3</td></tr><tr><td><b>School of Information Technology, Deakin University, Geelong, VIC 3216, Australia</b></td><td>3</td></tr><tr><td>Institute of Mathematical and Computer Sciences, University of Sao Paulo, Sao Paulo, Brazil</td><td>3</td></tr><tr><td>Dept. of Informatics, Aristotle Univ. of Thessaloniki, Greece</td><td>3</td></tr><tr><td><b>Zhejiang University</b></td><td>3</td></tr><tr><td><b>Northwestern Polytechnical University, Xi'an, P. R. China</b></td><td>3</td></tr><tr><td><b>University of Southern California, Institute for Robotics and Intelligent Systems, Los Angeles, CA 90089, USA</b></td><td>3</td></tr><tr><td>NTT Media Intelligence Laboratories, Tokyo, Japan</td><td>3</td></tr><tr><td><b>Computer Science, University of Houston, Texas 77004, United States of America</b></td><td>3</td></tr><tr><td><b>School of Communication and Information Engineering, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>3</td></tr><tr><td>Beijing Institute of Graphic Communication, Beijing</td><td>3</td></tr><tr><td><b>Department of Computer Science and Technology, Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, USA</b></td><td>3</td></tr><tr><td><b>Tsinghua University, Beijing,China</b></td><td>3</td></tr><tr><td><b>Media & Inf. Res. Labs., NEC Corp., Kanagawa, Japan</b></td><td>3</td></tr><tr><td><b>Centre de Visió per Computador, Universitat Autònoma de Barcelona, Barcelona, Spain</b></td><td>3</td></tr><tr><td><b>Department of Electronic Engineering, Shanghai Jiao Tong University, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and TechnologyState Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China</b></td><td>3</td></tr><tr><td><b>School of Software, Tsinghua University, Beijing, P. R. China</b></td><td>3</td></tr><tr><td><b>Research Center of Intelligent Robotics Shanghai Jiao Tong University, Shanghai, 200240, P.R. China</b></td><td>3</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b></td><td>3</td></tr><tr><td><b>School of Software, University of Technology Sydney, New South Wales, Australia</b></td><td>3</td></tr><tr><td><b>School of Telecommunications Engineering, Xidian University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Shenzhen Graduate School, Harbin Institute of Technology, Guangdong 518055, China</b></td><td>3</td></tr><tr><td><b>Azbil Corporation 1-12-2, Kawana, Fujisawa-shi, 251-8522, Japan</b></td><td>3</td></tr><tr><td><b>Graduate School of Information Sciences, Tohoku University, 6-6-05., Aramaki Aza Aoba., Sendai-shi., 980-8579., Japan</b></td><td>3</td></tr><tr><td><b>Australian National University, Canberra, Australia</b></td><td>3</td></tr><tr><td><b>Visualisation Group, University of Warwick, Coventry, UK</b></td><td>3</td></tr><tr><td><b>School of Software Engineering, Chongqing University, Chongqing, China</b></td><td>3</td></tr><tr><td><b>Beijing University of Posts and Telecommunications</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan</b></td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, P. R. China</b></td><td>3</td></tr><tr><td>Nara Institute of Science and Technology, Japan</td><td>3</td></tr><tr><td><b>Institute for Electronics, Signal Processing and Communications (IESK) Otto-von-Guericke-University Magdeburg D-39016 Magdeburg, P.O. Box 4210 Germany</b></td><td>3</td></tr><tr><td>Department of Computer, the University of Suwon, Korea</td><td>3</td></tr><tr><td><b>Institute for Anthropomatics, Karlsruhe Institute of Technology, Germany</b></td><td>3</td></tr><tr><td>Department of Electrical and Computer Engineering, Florida Institute of Technology, Melbourne, USA</td><td>3</td></tr><tr><td><b>Fujian Key laboratory of Sensing and Computing for Smart City, School of Information Science and Technology, Xiamen University, Xiamen, China</b></td><td>3</td></tr><tr><td>Dept. of Computer Science and Engineering, St. Joseph's College of Engineering and Technology, Palai, Kerala, India</td><td>3</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, Beijing, P.R. China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, East Lansing 48824, USA</b></td><td>3</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, UK</b></td><td>3</td></tr><tr><td><b>School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, Indian Institute of Technology Kanpur, PIN 208016, Uttar Pradesh, India</b></td><td>3</td></tr><tr><td>Dept. of Computer Science and Electrical Engineering, University of Missouri-Kansas City, MO, USA</td><td>3</td></tr><tr><td><b>University of North Carolina Wilmington, USA</b></td><td>3</td></tr><tr><td><b>Shenzhen Key Laboratory of Computer Vision and Pattern Recognition, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>3</td></tr><tr><td><b>Visual Media Computing Lab, Department of Multimedia and Graphic Arts, Cyprus University of Technology, Limassol, Cyprus</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Computational Biomedicine Laboratory, University of Houston, Houston, TX, USA</b></td><td>3</td></tr><tr><td><b>Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil</b></td><td>3</td></tr><tr><td><b>Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China</b></td><td>3</td></tr><tr><td>Inha University, Incheon, South Korea</td><td>3</td></tr><tr><td><b>Swiss Federal Institute of Technology, Lausanne (EPFL), Switzerland</b></td><td>3</td></tr><tr><td><b>Australian Centre for Field Robotics University of Sydney, 2006, Australia</b></td><td>3</td></tr><tr><td><b>Université de Lyon, Laboratoire d’InfoRmatique en Image et Systèmes d’information, Centre National de Recherche Scientifique 5205, Ecole Centrale de Lyon, France</b></td><td>3</td></tr><tr><td><b>Department of Computer ScienceFace Aging Group Research Laboratory, Institute for Interdisciplinary Studies in Identity Sciences, University of North Carolina at Wilmington, Wilmington, NC, USA</b></td><td>3</td></tr><tr><td><b>Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA</b></td><td>3</td></tr><tr><td>Center for Research on Intelligent Perception and Computing</td><td>3</td></tr><tr><td><b>UC Merced, USA</b></td><td>3</td></tr><tr><td><b>Centre for Quantum Computation & Information Systems, Faculty of Engineering and IT, University of Technology, Sydney, 235 Jones Street, Ultimo, NSW, Australia</b></td><td>3</td></tr><tr><td><b>Samsung Research Center-Beijing, SAIT China Lab Beijing, China</b></td><td>3</td></tr><tr><td><b>IT - Instituto de Telecomunicações, University of Beira Interior, Portugal</b></td><td>3</td></tr><tr><td>Thiagarajar College of Engineering, Madurai, Tamilnadu, India</td><td>3</td></tr><tr><td><b>Center for Cognitive, Connected & Computational Imaging, College of Engineering & Informatics, NUI Galway, Ireland</b></td><td>3</td></tr><tr><td><b>Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Karlsruhe, Germany</b></td><td>3</td></tr><tr><td><b>Institute of Information Science, Beijing jiaotong University, Beijing, China</b></td><td>3</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Center for Automation Research, University of Maryland, College Park, 20742, USA</b></td><td>3</td></tr><tr><td><b>Hasso Plattner Institute, University of Potsdam, Prof.-Dr.-Helmert-Str. 2-3, 14482, Germany</b></td><td>3</td></tr><tr><td><b>Dalian University of Technology, School of Software Tuqiang St. 321, Dalian, 116620, China</b></td><td>3</td></tr><tr><td><b>Shenzhen Graduate School, Peking University, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, University of Central Florida, Orlando, 32816, United States of America</b></td><td>3</td></tr><tr><td><b>Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China</b></td><td>3</td></tr><tr><td><b>College of Computer Science and Technology, Jilin University, Changchun, China</b></td><td>3</td></tr><tr><td><b>University of Technology, Sydney</b></td><td>3</td></tr><tr><td><b>Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, China</b></td><td>3</td></tr><tr><td><b>Software School, Xiamen University, Xiamen, China</b></td><td>3</td></tr><tr><td><b>University of Nottingham, Ningbo China</b></td><td>3</td></tr><tr><td><b>National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University Chengdu, 610065, China</b></td><td>3</td></tr><tr><td><b>Institute of Forensic Science, Ministry of Justice, Shanghai 200063, China</b></td><td>3</td></tr><tr><td><b>Department of Information Engineering, University of Florence, Florence, Italy</b></td><td>3</td></tr><tr><td>Dept. of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan</td><td>3</td></tr><tr><td><b>West Virginia University, Morgantown, WV, USA</b></td><td>3</td></tr><tr><td><b>EUP Mataró, Spain</b></td><td>3</td></tr><tr><td><b>Université du Québec à Chicoutimi (UQAC)</b></td><td>3</td></tr><tr><td><b>Dept. of Computer Sciences, ASIA Team, Moulay Ismail University, Faculty of Science and Techniques, BP 509 Boutalamine 52000 Errachidia, Morocco</b></td><td>3</td></tr><tr><td>School of Electrical and Electronic Engineering, Singapore</td><td>3</td></tr><tr><td><b>Microsoft Research, Beijing, China</b></td><td>3</td></tr><tr><td><b>Northeastern University, Boston, USA</b></td><td>3</td></tr><tr><td><b>Center for Future Media and School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>3</td></tr><tr><td><b>Advanced Technologies Application Center, 7a #21406 b/ 214 and 216, P.C. 12200, Playa, Havana, Cuba</b></td><td>3</td></tr><tr><td><b>Artificial Vision Laboratory, National Taiwan University of Science and Technology</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India</b></td><td>3</td></tr><tr><td>Universidade Nova Lisboa, Lisboa, Portugal</td><td>3</td></tr><tr><td><b>Wuhan University, Wuhan, China</b></td><td>3</td></tr><tr><td><b>Key Laboratory of Machine Perception (Ministry of Education), Engineering Lab on Intelligent Perception for Internet of Things (ELIP), Shenzhen Graduate School, Peking University, China</b></td><td>3</td></tr><tr><td><b>Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China</b></td><td>3</td></tr><tr><td><b>Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China</b></td><td>3</td></tr><tr><td>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation Chinese Academy of Sciences, Beijing, China 100190</td><td>3</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, İstanbul Teknik Üniversitesi, İstanbul, Türkiye</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Jadavpur University, Kolkata, India</b></td><td>3</td></tr><tr><td><b>Indian Statistical Institute, Kolkata, India</b></td><td>3</td></tr><tr><td><b>Jiangsu University, Zhenjiang, China</b></td><td>3</td></tr><tr><td><b>Sharif University of Technology</b></td><td>3</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology Uttarakhand, Srinagar Garhwal, India</td><td>3</td></tr><tr><td>Dept. of Mediamatics, Delft Univ. of Technol., Netherlands</td><td>3</td></tr><tr><td><b>Disney Research Pittsburgh, Pittsburgh, PA, USA</b></td><td>3</td></tr><tr><td><b>Electrical and Computer Engineering</b></td><td>3</td></tr><tr><td><b>Video Analytics Laboratory, SERC, Indian Institute of Science, Bangalore, India</b></td><td>3</td></tr><tr><td><b>School of Electronics and Information Engineering, Tianjin University, Tianjin, China</b></td><td>3</td></tr><tr><td><b>Cornell University, USA</b></td><td>3</td></tr><tr><td>Department of Information Science and Engineering, Changzhou University, Changzhou, China</td><td>3</td></tr><tr><td><b>International Center of Excellence on Intelligent Robotics and Automation Research, National Taiwan University, Taiwan</b></td><td>3</td></tr><tr><td><b>Department of Informatics, University of Thessaloniki, 54124, Greece</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Dayton, Ohio, USA</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Windsor, Canada</b></td><td>3</td></tr><tr><td><b>Graduate School of Shenzhen, Tsinghua University, Beijing, China</b></td><td>3</td></tr><tr><td><b>Hanoi University of Science and Technology, Hanoi, Vietnam</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Korea</b></td><td>3</td></tr><tr><td><b>Institute of Computational Science, University of Lugano, Switzerland</b></td><td>3</td></tr><tr><td><b>Norwegian Biometrics Laboratory, NTNU - Gjøvik, Norway</b></td><td>3</td></tr><tr><td><b>Institute of Technology and Science, Tokushima University, 2-1 Minamijyousanjima, 770-8506, Japan</b></td><td>3</td></tr><tr><td><b>LTCI, CNRS, Télécom ParisTech, Université Paris-Saclay, 75013, France</b></td><td>3</td></tr><tr><td><b>National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>3</td></tr><tr><td><b>School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Dongchuan Road 800, Minhang District, Shanghai, 200240, China</b></td><td>3</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore</b></td><td>3</td></tr><tr><td><b>Multimedia and Intelligent Software Technology Beijing Municipal Key Lab., College of Computer Science, Beijing University of Technology Beijing, China.</b></td><td>3</td></tr><tr><td><b>Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany</b></td><td>3</td></tr><tr><td><b>Korea University</b></td><td>3</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, NSW, Australia</b></td><td>3</td></tr><tr><td><b>Shenzhen Key Laboratory of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>TCS Research, New Delhi, India</b></td><td>3</td></tr><tr><td><b>University of North Carolina Wilmington, Wilmington, NC</b></td><td>3</td></tr><tr><td><b>Faculty of Electrical Engineering, University of Ljubljana, Trzaska cesta 25, SI-1000 Ljubljana, Slovenia</b></td><td>3</td></tr><tr><td><b>Research Institute of Shenzhen, Wuhan University, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>Shanghai University</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Binghamton University, Binghamton, NY</b></td><td>3</td></tr><tr><td><b>Nanyang Technological University, Singapore, Singapore</b></td><td>3</td></tr><tr><td><b>New York University, New York, NY, USA</b></td><td>3</td></tr><tr><td><b>School of Electronics and Computer Science, University of Southampton, United Kingdom</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, University of Massachusetts Amherst, Amherst MA, 01003</b></td><td>3</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Xidian University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 27 Prague 6, Technická 2 Czech Republic</b></td><td>3</td></tr><tr><td><b>Computer Laboratory, University of Cambridge, United Kingdom</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>3</td></tr><tr><td>Institute for Infocomm Research, A*STAR, Singapore, Singapore</td><td>3</td></tr><tr><td><b>South China University of Technology, China</b></td><td>3</td></tr><tr><td><b>Visionlab, Heriot-Watt University, Edinburgh, UK</b></td><td>3</td></tr><tr><td><b>Institute for Infocomm Research, A*STAR, Singapore</b></td><td>3</td></tr><tr><td><b>Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea</b></td><td>3</td></tr><tr><td><b>Xerox Research Center, Webster, NY, USA</b></td><td>3</td></tr><tr><td>Ashikaga Institute of Technology, Ashikaga, Japan</td><td>3</td></tr><tr><td><b>Department of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, Tyne and Wear</b></td><td>3</td></tr><tr><td><b>College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan</b></td><td>3</td></tr><tr><td>Institute of Applied Computer Science, Kiel University of Applied Sciences, Kiel, Germany</td><td>3</td></tr><tr><td><b>School of Creative Technologies, University of Portsmouth, Portsmouth, POI 2DJ, UK</b></td><td>3</td></tr><tr><td><b>Université de Lyon, CNRS, INSA-Lyon, LIRIS, UMR5205, France</b></td><td>3</td></tr><tr><td><b>Faculty of Electronic Information and Electrical Engineering, School of Information and Communication Engineering, Dalian University of Technology, Dalian, China</b></td><td>3</td></tr><tr><td><b>Affectiva Inc., Waltham, MA, USA</b></td><td>3</td></tr><tr><td><b>Department of Electronics and Communication Engineering, Sun Yat-Sen University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea</b></td><td>3</td></tr><tr><td><b>Dept. of Electrical and Computer Engineering & Centre for Intelligent Machines, McGill University, Montreal, Quebec, Canada</b></td><td>3</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Surrey, UK</b></td><td>3</td></tr><tr><td><b>Computer Vision and Image Processing Lab, Institute for Integrated and Intelligent Systems, Griffith University, Australia</b></td><td>3</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA</b></td><td>3</td></tr><tr><td><b>Institute of Software, College of Computer, National University of Defense Technology, Changsha, Hunan, China, 410073</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Northeastern University, Boston, USA, 02115</b></td><td>3</td></tr><tr><td><b>AltumView Systems Inc., Burnaby, BC, Canada</b></td><td>3</td></tr><tr><td>Central China Normal University, Wuhan, China</td><td>3</td></tr><tr><td><b>Sapienza University of Rome</b></td><td>3</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b></td><td>3</td></tr><tr><td><b>Computer Vision Lab, Sungkyunkwan University Suwon, South Korea</b></td><td>3</td></tr><tr><td><b>Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Metropolitan Transportation, Beijing University of Technology, Beijing, China</b></td><td>3</td></tr><tr><td><b>Department of Computer Science, Vogt-Koelln-Strasse 30, 22527 Hamburg - Germany</b></td><td>3</td></tr><tr><td><b>Faculty of Engineering, Shinshu University, Nagano, Japan</b></td><td>3</td></tr><tr><td><b>Institute for Creative Technologies, University of Southern California, 12015 E Waterfront Dr, Los Angeles, CA, USA</b></td><td>3</td></tr><tr><td><b>National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China</b></td><td>3</td></tr><tr><td><b>Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, R.O.C</b></td><td>3</td></tr><tr><td><b>Vision Lab in Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, 23529</b></td><td>3</td></tr><tr><td><b>Center for Research of E-life DIgital Technology (CREDIT), Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan</b></td><td>3</td></tr><tr><td><b>Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea</b></td><td>3</td></tr><tr><td><b>E-Comm Research Lab, Infosys Limited, Bangalore, India</b></td><td>3</td></tr><tr><td><b>College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China</b></td><td>3</td></tr><tr><td>Chongqing University of Posts and Telecommunications Chongqing, China</td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Center for Biometrics and Security Research, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>3</td></tr><tr><td>School of Computer Science and Software Engineering University of Wollongong, Australia</td><td>3</td></tr><tr><td>Phonexia, Brno-Krlovo Pole, Czech Republic</td><td>3</td></tr><tr><td><b>Expert Systems, Modena, Italy</b></td><td>3</td></tr><tr><td><b>Chair of Complex & Intelligent Systems, University of Passau, Passau, Germany</b></td><td>3</td></tr><tr><td><b>Stanford University, Palo Alto, CA, USA</b></td><td>3</td></tr><tr><td>Department of Applied Mechanics, Chalmers University of Technology, SE-412 96 Göteborg, Sweden</td><td>3</td></tr><tr><td>Technische Universität München, Munich, Germany</td><td>3</td></tr><tr><td><b>Laboratory for Intelligent and Safe Automobiles, University of California, San Diego, USA</b></td><td>3</td></tr><tr><td><b>Toyota Research Institute</b></td><td>3</td></tr><tr><td><b>Image and Video Research Lab, Queensland University of Technology, 2 George Street, GPO Box 2434, Brisbane, QLD 4001, Australia</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Engineering, Nanjing University of Science and Technology</b></td><td>3</td></tr><tr><td><b>The University of Newcastle, NSW, Australia</b></td><td>3</td></tr><tr><td><b>Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro #1, Tonantzintla, Puebla, Mexico</b></td><td>3</td></tr><tr><td><b>NLPR, Institute of Automation, Chinese Academy of Sciences</b></td><td>3</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100190, China</b></td><td>3</td></tr><tr><td><b>Columbia University, New York, USA</b></td><td>3</td></tr><tr><td><b>Télécom Lille, CRIStAL UMR (CNRS 9189), France</b></td><td>3</td></tr><tr><td><b>IMPCA, Curtin University, Australia</b></td><td>3</td></tr><tr><td><b>Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, 22200 Besut, Terengganu, Malaysia</b></td><td>3</td></tr><tr><td><b>Concordia University</b></td><td>3</td></tr><tr><td><b>State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China</b></td><td>3</td></tr><tr><td>University of California, Los Angeles, CA Dept. of Electrical Engineering</td><td>3</td></tr><tr><td><b>University Of Electronic Science And Technology Of China, China</b></td><td>3</td></tr><tr><td><b>IBM Research</b></td><td>3</td></tr><tr><td>Academia Sinica, Taipei, Taiwan Roc</td><td>3</td></tr><tr><td><b>Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, SI-1000 Ljubljana, Slovenia</b></td><td>3</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, TX, USA</b></td><td>3</td></tr><tr><td><b>Center for Digital Media Computing, Software School, Xiamen University, Xiamen 361005, China</b></td><td>3</td></tr><tr><td><b>University of Milan, Italy</b></td><td>3</td></tr><tr><td><b>State Key Laboratory on Intelligent Technology and Systems, National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, China</b></td><td>3</td></tr><tr><td><b>School of Electronic and Information Engineering, South China University of Technology, Guangzhou, Guangdong, China</b></td><td>3</td></tr><tr><td>Dept. of Cybernetics and Artificial Intelligence, FEI TU of Košice, Slovak Republic</td><td>3</td></tr><tr><td><b>Department of Mathematics and Informatics, University of Florence, Florence, Italy</b></td><td>3</td></tr><tr><td><b>Key Lab of Intelligent Information Processing, Institute of Computer Technology, Chinese Academy of Science (CAS), Beijing, 100190, China</b></td><td>3</td></tr><tr><td>Image and Video Systems Lab, School of Electrical Engineering, KAIST, Republic of Korea</td><td>3</td></tr><tr><td><b>Evolutionary Computation Research Group, Victoria University of Wellington, PO Box 600, Wellington 6140, New Zealand</b></td><td>3</td></tr><tr><td><b>School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China</b></td><td>3</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Center for Research on Intelligent Perception and Computing, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>3</td></tr><tr><td><b>Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, P.O.Box 217 7500 AE Enschede, The Netherlands</b></td><td>3</td></tr><tr><td><b>MindLAB Research Group, Universidad Nacional de Colombia, Colombia</b></td><td>3</td></tr><tr><td><b>IntelliView Technologies Inc., Calgary, AB, Canada</b></td><td>3</td></tr><tr><td><b>Department of Electronic Engineering, National Taipei University of Technology, Taipei, Taiwan</b></td><td>3</td></tr><tr><td>Information and media processing laboratories, NEC Corporation</td><td>3</td></tr><tr><td>Southern Illinois University at Carbondale, IL, USA</td><td>3</td></tr><tr><td><b>School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, 75080, USA</b></td><td>3</td></tr><tr><td><b>Dept. of Automation and Applied Informatics, Politehnica University of Timisoara, Romania</b></td><td>3</td></tr><tr><td><b>Queen Mary University of London</b></td><td>3</td></tr><tr><td>School of Automation and Electrical Engineering, University of Science and Technology Beijing, 100083, China</td><td>3</td></tr><tr><td><b>Michigan State University, East Lansing, 48824, USA</b></td><td>3</td></tr><tr><td><b>The Hong Kong Polytechnic University, Hong Kong, China</b></td><td>3</td></tr><tr><td><b>Peking University, China / Shanghai Jiao Tong University, China</b></td><td>3</td></tr><tr><td><b>Department of Electronics, AGH University of Science and Technology, Kraków, Poland</b></td><td>3</td></tr><tr><td>School of Software, Jiangxi Normal University, Nanchang, China</td><td>3</td></tr><tr><td>Department of Computer Science, Pontificia Universidad Cato´lica de Chile</td><td>3</td></tr><tr><td><b>Faculty of Information Technology, Ho Chi Minh City University of Science, VNU-HCM, District 5, Ho Chi Minh City, Vietnam</b></td><td>3</td></tr><tr><td>Fujitsu Laboratories, Kawasaki, Kanagawa, Japan</td><td>3</td></tr><tr><td>Department of Electronic and Computer Engineering National Taiwan University of Science and Technology</td><td>3</td></tr><tr><td><b>Georgia Institute of Technology, Atlanta, 30332-0250, USA</b></td><td>3</td></tr><tr><td><b>Tongji University, Shanghai, China</b></td><td>3</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Vision Laboratory, Old Dominion University, Norfolk, VA, USA</b></td><td>3</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia</b></td><td>3</td></tr><tr><td><b>School of Information Science and Engineering, Xiamen University, Xiamen 361005, China</b></td><td>3</td></tr><tr><td><b>University of California San Diego, USA</b></td><td>3</td></tr><tr><td><b>HCC Lab, Vision & Sensing Group, University of Canberra, Australia</b></td><td>3</td></tr><tr><td><b>Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China</b></td><td>3</td></tr><tr><td><b>REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia</b></td><td>3</td></tr><tr><td><b>School of Computer Science and Educational Software, Guangzhou University, Guangzhou, China</b></td><td>3</td></tr><tr><td><b>IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA</b></td><td>3</td></tr><tr><td><b>School of physics and engineering, Sun Yat-Sen University, GuangZhou, China</b></td><td>3</td></tr><tr><td>New York University Abu Dhabi & NYU Tandon School of Engineering, Abu Dhabi, Uae</td><td>3</td></tr><tr><td>Intelligent Vision Research Lab, Department of Computer Science, Federal University of Bahia</td><td>3</td></tr><tr><td><b>FDNA inc., Herzliya, Israel</b></td><td>3</td></tr><tr><td><b>Department of Mathematics & Computer Science, Philipps-Universität Marburg, D-35032, Germany</b></td><td>3</td></tr><tr><td><b>Australian Center for Visual Technologies, and School of Computer Science, The University of Adelaide, Adelaide, Australia</b></td><td>3</td></tr><tr><td>Department of Electronic Measuring systems, Moscow Engineering Physics Institute, National Research Nuclear University MEPhI, Moscow, Russia</td><td>3</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798</b></td><td>3</td></tr><tr><td><b>IT - Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</b></td><td>3</td></tr><tr><td><b>National University of Defence Technology, Changsha 410000, China</b></td><td>2</td></tr><tr><td>National Ilan University, Ilan, Taiwan Roc</td><td>2</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Eskişehir Osmangazi Üniversitesi, Turkey</b></td><td>2</td></tr><tr><td><b>Elektrik - Elektronik Mühendisliği Bölümü, Atılım Üniversitesi, Ankara, Türkiye</b></td><td>2</td></tr><tr><td>China Electronics Standardization Institute, Beijing, 100007</td><td>2</td></tr><tr><td><b>School of Reliability and System Engineering, Science and Technology on Reliability and Environmental Engineering Laboratory, Beihang University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Kent State University, OH 44242, U.S.A.</b></td><td>2</td></tr><tr><td><b>Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India</b></td><td>2</td></tr><tr><td><b>Computational Biomedicine Lab, University of Houston</b></td><td>2</td></tr><tr><td><b>Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown WV 26506, USA</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, İstanbul Teknik Üniversitesi, İstanbul, Turkiye</b></td><td>2</td></tr><tr><td>Universidade Nova de Lisboa, Caparica, Portugal</td><td>2</td></tr><tr><td>Universidad Tecnica Federico Santa Maria, Department of Electronic Engineering, Valparaiso, Chile</td><td>2</td></tr><tr><td>Dept. of Comput. Syst., Univ. of Technol., Sydney, NSW, Australia</td><td>2</td></tr><tr><td><b>Harvard University, Cambridge, MA, USA</b></td><td>2</td></tr><tr><td><b>Michigan State University, East Lansing, MI, U.S.A.</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, National Tsing Hua University, Taiwan</b></td><td>2</td></tr><tr><td>Dept. of Comput. Sci., York Univ., UK</td><td>2</td></tr><tr><td><b>CSE, SUNY at Buffalo, USA</b></td><td>2</td></tr><tr><td><b>Department of Computer Engineering, Mahanakorn University of Technology, 140 Cheum-Sampan Rd., Nong Chok, Bangkok THAILAND 10530</b></td><td>2</td></tr><tr><td>The Australian National University RSCS, ANU, Canberra, Australia</td><td>2</td></tr><tr><td><b>University of Newcastle, Australia</b></td><td>2</td></tr><tr><td>Dept. of Computer Science, YiLi Normal College, Yining, China 835000</td><td>2</td></tr><tr><td>School of Computing and Communications, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia</td><td>2</td></tr><tr><td><b>DISI, University of Trento, Italy</b></td><td>2</td></tr><tr><td><b>LAPI, University Politehnica of Bucharest, Romania</b></td><td>2</td></tr><tr><td><b>University of Colorado at Colorado Springs, Colorado Springs, CO, USA</b></td><td>2</td></tr><tr><td><b>University of Twente, Enschede, Netherlands</b></td><td>2</td></tr><tr><td><b>Department of Mechanical Engineering, National Taiwan University, 10647, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Institution for Infocomm Research, Connexis, Singapore</b></td><td>2</td></tr><tr><td><b>Department of d’Informàtica, Universitat de València, Valencia, Spain</b></td><td>2</td></tr><tr><td><b>Toyota Research Institute, Cambridge, MA, USA</b></td><td>2</td></tr><tr><td><b>Research Centre for Computers, Communication and Social Innovation La Trobe University, Victoria - 3086, Australia</b></td><td>2</td></tr><tr><td><b>IBM Thomas J. Watson, Research Center, Yorktown Heights, New York 10598, USA</b></td><td>2</td></tr><tr><td><b>Institute of Computing, University of Campinas (UNICAMP), SP, 13083-852, Brazil</b></td><td>2</td></tr><tr><td><b>IFRJDL, Institute of Computing Technology, CAS, P.O.Box 2704, Beijing, China, 100080</b></td><td>2</td></tr><tr><td><b>Computer Science Department, University of Southern California, Los Angeles, 90089, United States of America</b></td><td>2</td></tr><tr><td><b>Department of Signal Processing, Tampere University of Technology, Tampere, Finland</b></td><td>2</td></tr><tr><td><b>JD Artificial Intelligence Research, Beijing, China</b></td><td>2</td></tr><tr><td><b>STARS team, Inria Sophia Antipolis-Méditerranée, Sophia Antipolis, France</b></td><td>2</td></tr><tr><td><b>Agency for Science, Technology and Research (A*STAR), Institute of High Performance Computing, Singapore</b></td><td>2</td></tr><tr><td><b>Delft University of Technology</b></td><td>2</td></tr><tr><td><b>Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA</b></td><td>2</td></tr><tr><td>Department of Electrical and Computer Engineering, Singapore</td><td>2</td></tr><tr><td>Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td><b>Department of Computer Science, Wayne State University, Detroit, MI, USA</b></td><td>2</td></tr><tr><td><b>Dept. of Computer Science, Yonsei University, Seoul, South Korea, 120-749</b></td><td>2</td></tr><tr><td><b>Division of Graduate Studies, Tijuana Institute of Technology, México</b></td><td>2</td></tr><tr><td><b>School of Engineering and Digital Arts, University of Kent, Canterbury, Kent CT2 7NT, United Kingdom</b></td><td>2</td></tr><tr><td>Instituto de Telecomunicações & Faculdade de Ciěncias da Universidade do Porto</td><td>2</td></tr><tr><td><b>Faculty of Science and Technology, University of Macau, Macau, China</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering and the Center for Automation Research, UMIACS, University of Maryland, College Park, MD</b></td><td>2</td></tr><tr><td><b>Visual Analysis of People (VAP) laboratory, Aalborg University, Denmark</b></td><td>2</td></tr><tr><td><b>Instituto de Telecomunicações, Instituto Superior Técnico, Universidade de Lisboa, Portugal</b></td><td>2</td></tr><tr><td><b>School of Computer Science, Northwestern Polytechnical University, Xi’an, China</b></td><td>2</td></tr><tr><td><b>Escuela Politecnica Superior, Universidad Autonoma de Madrid, Madrid, Spain</b></td><td>2</td></tr><tr><td><b>SUPELEC / IETR, Avenue de la Boulaie, 35576 Cesson Sevigne, France</b></td><td>2</td></tr><tr><td><b>Dept. of Computer Science & Engineering, University of South Florida, Tampa, 33620, United States of America</b></td><td>2</td></tr><tr><td>Department of Information Management, National Formosa University, Huwei, Yulin 632, Taiwan</td><td>2</td></tr><tr><td>Dept of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Kavala, Greece</td><td>2</td></tr><tr><td><b>Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Fraunhoferstrasse 1, 76131 Karlsruhe, Germany</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, New Jersey Institute of Technology, University Heights, Newark, New Jersey 07102, USA</b></td><td>2</td></tr><tr><td><b>Department of Electronic Engineering, Shanghai Jiao Tong University</b></td><td>2</td></tr><tr><td><b>College of Computer and Information, Hohai University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>Department of Information Systems and Cyber Security and the Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>2</td></tr><tr><td><b>Electronics & Telecommunications Research Institute (ETRI), Daejeon, Korea</b></td><td>2</td></tr><tr><td>University of Ulm, Ulm, Germany</td><td>2</td></tr><tr><td><b>Electrical and Computer Engineering Department, University of Windsor, Ontario, Canada N9B 3P4</b></td><td>2</td></tr><tr><td><b>National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, The University of Hong Kong</b></td><td>2</td></tr><tr><td>Dept. of Eng. Sci., Oxford Univ., UK</td><td>2</td></tr><tr><td><b>Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Adenauerring 4, Karlsruhe, Germany</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea</b></td><td>2</td></tr><tr><td><b>Facial Image Processing and Analysis Group, Institute for Anthropomatics, Karlsruhe Institute of Technology, D-76131 Karlsruhe, P.O. Box 6980 Germany</b></td><td>2</td></tr><tr><td><b>Delft University of Technology, Mekelweg 4, Netherlands</b></td><td>2</td></tr><tr><td>Human-Machines Interaction (HMI) Laboratory, Department of Industrial Informatics, TEI of Kavala, Kavala, Greece</td><td>2</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University</b></td><td>2</td></tr><tr><td>Dept. of ECE, Maryland Univ., College Park, MD, USA</td><td>2</td></tr><tr><td><b>Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China</b></td><td>2</td></tr><tr><td>Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey</td><td>2</td></tr><tr><td><b>National University of Defense and Technology</b></td><td>2</td></tr><tr><td><b>School of Computer Science, CECS, Australian National University, Australia</b></td><td>2</td></tr><tr><td>Electrical & Electronic Engineering Department, Mevlana University Konya, Turkey</td><td>2</td></tr><tr><td><b>Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA</b></td><td>2</td></tr><tr><td><b>Institute of Electronics, National Chiao Tung University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td>GIPSA Laboratory, Image and Signal Department, Grenoble Institute of Technology, Grenoble, France</td><td>2</td></tr><tr><td><b>Florida International University</b></td><td>2</td></tr><tr><td><b>Gradate School of Information Production and System, Waseda University, Kitakyushu, Japan 808-0135</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, India</td><td>2</td></tr><tr><td><b>Graduate School of Information, Production and Systems, Waseda University, Japan</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, National Taiwan Ocean University, No.2, Beining Rd., Keelung 202, Taiwan</td><td>2</td></tr><tr><td><b>Tampere University of Technology, Finland</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, National Chiao Tung University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Biodata Mining Group, Technical Faculty, Bielefeld University, Germany</b></td><td>2</td></tr><tr><td><b>Chungnam National University, Daejeon, South Korea</b></td><td>2</td></tr><tr><td>Bilgisayar Mühendisliği Bölümü, Deniz Harp Okulu, İstanbul, Türkiye</td><td>2</td></tr><tr><td><b>IETR, CNRS UMR 6164, Supelec, Cesson-Sevigne, France</b></td><td>2</td></tr><tr><td><b>Institute of Intelligent Systems and Robotics (ISIR), Pierre and Marie Curie University , Paris, France</b></td><td>2</td></tr><tr><td><b>University of Technology, Sydney, NSW, Australia</b></td><td>2</td></tr><tr><td>Statistical Machine Intelligence & LEarning, School of Computer Science & Engineering University of Electronic Science and Technology of China, 611731, China</td><td>2</td></tr><tr><td><b>Department of Computer Science and Information Engineering, College of Electrical Engineering and Computer Science, National Central University, Jhongli, Taiwan</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, 32610, Perak Malaysia</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore639798</b></td><td>2</td></tr><tr><td><b>West Virginia University</b></td><td>2</td></tr><tr><td><b>Czech Technical University in Prague, Prague, Czech Rep</b></td><td>2</td></tr><tr><td>Masaryk University, Brno, Czech Rep</td><td>2</td></tr><tr><td>Charles University, Prague, Czech Rep</td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada</td><td>2</td></tr><tr><td><b>Nanjing Children's Hospital Affiliated to Nanjing Medical University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>College of Telecommunications & Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China</b></td><td>2</td></tr><tr><td><b>School of Telecommunications Engineering, Xidian University, Xi’an, China</b></td><td>2</td></tr><tr><td><b>Nanjing University of Science and Technology, Xiaolingwei, Xuanwu, Nanjing, China</b></td><td>2</td></tr><tr><td><b>London Healthcare Sciences Centre, London, ON, Canada</b></td><td>2</td></tr><tr><td>Department of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Human Machines Interaction (HMI) Laboratory, 65404 Kavala, Greece</td><td>2</td></tr><tr><td><b>School of Electrical Engineering and Computer Science, Seoul National University, Korea</b></td><td>2</td></tr><tr><td><b>Jordan University of Science and Technology, Irbid, Jordan</b></td><td>2</td></tr><tr><td><b>College of Medical Information Engineering, Guangdong Pharmaceutical University, Guangzhou, China</b></td><td>2</td></tr><tr><td><b>University of Michigan</b></td><td>2</td></tr><tr><td><b>Biometric Technologies Laboratory, Department of Electrical and Computer Engineering, University of Calgary, Alberta, T2N 1N4 Canada</b></td><td>2</td></tr><tr><td><b>Morpho, SAFRAN Group, 11 Boulevard Galliéni 92130 Issy-Les-Moulineaux - France</b></td><td>2</td></tr><tr><td><b>Center for Machine Vision Research, University of Oulu, Finland</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Aalto University, Finland</b></td><td>2</td></tr><tr><td><b>Norwegian Biometrics Laboratory, Norwegian University of Science and Technology (NTNU), 2802 Gj⊘vik, Norway</b></td><td>2</td></tr><tr><td><b>International Institute of Information Technology (IIIT) Hyderabad, India</b></td><td>2</td></tr><tr><td><b>Computer Laboratory, University of Cambridge, Cambridge, UK</b></td><td>2</td></tr><tr><td><b>Department of Electronic Systems, Aalborg University, Denmark</b></td><td>2</td></tr><tr><td><b>Artificial Intelligence and Information Analysis Lab, Department of Informatics, Aristotle University of Thessaloniki, Greece</b></td><td>2</td></tr><tr><td>University of British Columbia Department of Electrical and Computer Engineering</td><td>2</td></tr><tr><td><b>Department of Computer Science, Swansea University, Swansea, UK</b></td><td>2</td></tr><tr><td><b>Computer Science and Technology, IIEST, Shibpur</b></td><td>2</td></tr><tr><td><b>Amirkabir University of Technology, Tehran, Iran</b></td><td>2</td></tr><tr><td><b>EURECOM, Sophia Antipolis, France</b></td><td>2</td></tr><tr><td>School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, USA</b></td><td>2</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, SEOUL, Republic of Korea</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, University of Califonia, San Diego</td><td>2</td></tr><tr><td><b>Department of Computer Science and Technology, Tsinghua University, Beijing</b></td><td>2</td></tr><tr><td>University of Missouri Department of Electrical and Computer Engineering Columbia, MO, USA</td><td>2</td></tr><tr><td><b>School of Electrical and Computer Engineering, RMIT University, Melbourne, Australia</b></td><td>2</td></tr><tr><td>Inf. Syst. Dept., Buckingham Univ., UK</td><td>2</td></tr><tr><td><b>Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China</b></td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA</td><td>2</td></tr><tr><td><b>Department of Computer Science, Edge Hill University</b></td><td>2</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh, PA, 15260, USA</b></td><td>2</td></tr><tr><td><b>The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA</b></td><td>2</td></tr><tr><td><b>National Central University, Taoyuan County, Taiwan</b></td><td>2</td></tr><tr><td>Department of Computer Science & Engineering, POSTECH, Pohang, Sourth Korea, 37673</td><td>2</td></tr><tr><td><b>Anhui University, HeFei, China</b></td><td>2</td></tr><tr><td><b>Signals and Systems Group, Faculty of EEMCS, University of Twente, the Netherlands</b></td><td>2</td></tr><tr><td><b>Research Center of Machine Learning and Data Analysis, School of Computer Science and Technology, Soochow University, Suzhou, China</b></td><td>2</td></tr><tr><td>Coursera and Stanford University</td><td>2</td></tr><tr><td><b>School of Computer Science, University of Windsor, Canada N9B 3P4</b></td><td>2</td></tr><tr><td><b>Laboratory Heudiasyc, University of Technology of Compiègne, BP 20529. F-60205, France</b></td><td>2</td></tr><tr><td><b>Dept. Electrical Engineering, National Taiwan University, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Bahçeşehir Üniversitesi, İstanbul, Turkey</b></td><td>2</td></tr><tr><td><b>University of Notre Dame</b></td><td>2</td></tr><tr><td><b>University of Ljubljana</b></td><td>2</td></tr><tr><td><b>Istanbul Technical University</b></td><td>2</td></tr><tr><td><b>Polytechnic School, University of Pernambuco, Recife, Brazil</b></td><td>2</td></tr><tr><td><b>Faculty of Technical Sciences, Singidunum University, Belgrade 11000, Serbia</b></td><td>2</td></tr><tr><td><b>Dept. of CSEE, University of Maryland, Baltimore County, Baltimore, MD 21250</b></td><td>2</td></tr><tr><td>Dept. of Electron. & Inf., Toyota Technol. Inst., Nagoya, Japan</td><td>2</td></tr><tr><td><b>Department of Computer Science, University of Maryland, College Park, MD</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, POSTECH, Pohang 790-784, Republic of Korea</td><td>2</td></tr><tr><td><b>School of Electronic Engineering and Computer Science, Queen Mary University of London, UK</b></td><td>2</td></tr><tr><td><b>University of the Witwatersrand</b></td><td>2</td></tr><tr><td><b>Star Technologies, USA</b></td><td>2</td></tr><tr><td>Dept. of Comput. Sci., New York State Univ., Binghamton, NY, USA</td><td>2</td></tr><tr><td>Dept. of Electrical Engineering, National Institute of Technology, Rourkela, India 769008</td><td>2</td></tr><tr><td><b>Division of Control, EEE, Nanyang Tech. Univ., Singapore</b></td><td>2</td></tr><tr><td><b>Department of Computer Science & Engineering, University of Ioannina, 45110, Greece</b></td><td>2</td></tr><tr><td><b>Jiangsu University of Science and Technology, Zhenjiang, China</b></td><td>2</td></tr><tr><td><b>University of Valladolid (Spain), Dep. Of Systems Engineering and Automatic Control, Industrial Engineering School</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Mangalore University, India</b></td><td>2</td></tr><tr><td><b>Department of Computer Education, Sungkyunkwan University, Seoul, Republic of Korea</b></td><td>2</td></tr><tr><td>Department of Computer Science, Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>2</td></tr><tr><td><b>Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, China</b></td><td>2</td></tr><tr><td><b>University of Pittsburgh, Pittsburgh, PA, USA</b></td><td>2</td></tr><tr><td><b>Xidian University, Xi'an, China</b></td><td>2</td></tr><tr><td><b>School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China</b></td><td>2</td></tr><tr><td>School of Computer Science and Technology, Tianjin University&Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China</td><td>2</td></tr><tr><td>NPU-VUB Joint AVSP Research Lab, School of Computer Science, Northwestern Polytechnical University (NPU) Shaanxi Key Lab on Speech and Image Information Processing, 127 Youyi Xilu, Xi'an 710072, China</td><td>2</td></tr><tr><td><b>CAS Center for Excellence in Brain Science and Intelligence Technology, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>Australian National University</b></td><td>2</td></tr><tr><td><b>Institute of Computing, University of Campinas (UNICAMP), Campinas, SP, 13083-852, Brazil</b></td><td>2</td></tr><tr><td><b>Sichuan Univ., Chengdu</b></td><td>2</td></tr><tr><td><b>Laboratory for Intelligent and Safe Automobiles, University of California San Diego, La Jolla, CA 92093 USA</b></td><td>2</td></tr><tr><td><b>Department of Computing, Imperial College London, London, 180 Queen’s Gate, UK</b></td><td>2</td></tr><tr><td><b>Australian Center for Visual Technologies, and School of Computer Science, University of Adelaide, Canberra, Australia</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisligi Bölümü, İstanbul Teknik Üniversitesi</b></td><td>2</td></tr><tr><td>Research&Advanced Technology Division of SAIC Motor Corporation Limited, Shanghai 201804, P.R China</td><td>2</td></tr><tr><td>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China</td><td>2</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>Departamento de Computação, Universidade Federal do Piauí, Teresina, Brasil</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Marmara Üniversitesi, İstanbul, Türkiye</b></td><td>2</td></tr><tr><td><b>Le2i FRE2005, CNRS, Arts et Métiers, Univ. Bourgogne Franche-Comté, UTBM, F-90010 Belfort, France</b></td><td>2</td></tr><tr><td><b>Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan</b></td><td>2</td></tr><tr><td><b>Department of Computing, Imperial College London, U.K.</b></td><td>2</td></tr><tr><td>Dept. of Computer Science and Information Engineering, Southern Taiwan University of Science and Technology, Tainan City, Taiwan</td><td>2</td></tr><tr><td><b>Corp. Res. & Dev., Toshiba Corp., Tokyo, Japan</b></td><td>2</td></tr><tr><td>Dept. of Electronics and Telecommunication Engg., KCT's Late G.N. Sapkal college of Engineering, Nashik, India</td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Gebze Teknik Üniversitesi, Kocaeli, 41400, Türkiye</b></td><td>2</td></tr><tr><td><b>State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China</b></td><td>2</td></tr><tr><td>Tencent Inc</td><td>2</td></tr><tr><td><b>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190</b></td><td>2</td></tr><tr><td><b>Faculty of Information Science and Technology (FIST), Multimedia University, Melaka, Malaysia</b></td><td>2</td></tr><tr><td><b>Fraunhofer IOSB, Fraunhoferstrasse 1, 76131 Karlsruhe, Germany</b></td><td>2</td></tr><tr><td>Facebook Inc., Menlo Park, CA, USA</td><td>2</td></tr><tr><td><b>Naval Research Laboratory, Washington DC</b></td><td>2</td></tr><tr><td>Computational Intelligence Lab, Institute of Informatics and Telecommunications, NCSR Demokritos, Athens, Greece</td><td>2</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, TX and Computational Intelligence Lab, Institute of Informatics and Telecommunications, NCSR Demokrit ...</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>SPAWAR Systems Center Pacific, San Diego, California, USA</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, National Taiwan University, Taiwan</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran</b></td><td>2</td></tr><tr><td><b>Artificial Vision Laboratory, Dept. of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan 106</b></td><td>2</td></tr><tr><td><b>Microsoft Corporation, Redmond, WA, USA</b></td><td>2</td></tr><tr><td>Dept. of Electrical Engineering, National Tsing-Hua University, Taiwan</td><td>2</td></tr><tr><td>Department Informatik, Hamburg University of Applied Sciences, Hamburg, Germany</td><td>2</td></tr><tr><td>Department Informatik, Hamburg University of Applied Sciences, Engineering and Computing, University of the West of Scotland</td><td>2</td></tr><tr><td><b>University of Siena, Siena, Italy</b></td><td>2</td></tr><tr><td>Elektronik ve Haberleşme Mühendisliği Bölümü, Yıldız Teknik Üniversitesi, İstanbul, Türkiye</td><td>2</td></tr><tr><td><b>Stony Brook University, Stony Brook, NY</b></td><td>2</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, Ultimo, NSW, Australia</b></td><td>2</td></tr><tr><td><b>Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan, China</b></td><td>2</td></tr><tr><td><b>Department of Artificial Intelligence, Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur, 50603, Malaysia</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering of Systems, University of Zaragoza, Escuela Universitaria Politécnica de Teruel, Teruel, Spain</td><td>2</td></tr><tr><td><b>Department of DMC Engineering, Sungkyunkwan University, Suwon, South Korea</b></td><td>2</td></tr><tr><td>Department of Automation, North-China University of Technology, Beijing, China</td><td>2</td></tr><tr><td><b>University of Bern, Neubrückstrasse 10, Bern, Switzerland</b></td><td>2</td></tr><tr><td><b>Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong</b></td><td>2</td></tr><tr><td><b>Computer Science, Fudan University, Shanghai, 201203, China</b></td><td>2</td></tr><tr><td><b>Electronic Engineering and Computer Science, Queen Mary University, London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea</b></td><td>2</td></tr><tr><td><b>Swiss Federal, Institute of Technology, Lausanne (EPFL), Switzerland</b></td><td>2</td></tr><tr><td><b>Disney Research, CH</b></td><td>2</td></tr><tr><td>Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia</td><td>2</td></tr><tr><td><b>Water Optics Technology Pte. Ltd, Singapore</b></td><td>2</td></tr><tr><td><b>School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore</b></td><td>2</td></tr><tr><td><b>Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia</b></td><td>2</td></tr><tr><td><b>National Laboratory of Pattern Recognition, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China</b></td><td>2</td></tr><tr><td><b>Orange Labs International Center Beijing, Beijing, 100876, China</b></td><td>2</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>2</td></tr><tr><td>Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, P.R. China</td><td>2</td></tr><tr><td>Indian Statistical Insitute, Kolkata 700108</td><td>2</td></tr><tr><td>Centre for Secure Information Technologies, Queen’s University Belfast, Belfast, UK</td><td>2</td></tr><tr><td><b>National University of Defense Technology, Hunan, China</b></td><td>2</td></tr><tr><td><b>Rutgers University, Piscataway, USA</b></td><td>2</td></tr><tr><td>Wrocław University of Science and Technology, Wrocław, Poland</td><td>2</td></tr><tr><td><b>Norwegian Biometrics Lab, NTNU, Gj⊘vik, Norway</b></td><td>2</td></tr><tr><td><b>The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Canada</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology, University of Science and Technology of China</b></td><td>2</td></tr><tr><td><b>Zhejiang University, HangZhou, China</b></td><td>2</td></tr><tr><td>Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi, India</td><td>2</td></tr><tr><td>Department of Electronics and Communication Engineering Malaviya National Institute of Technology Jaipur, Rajasthan, India</td><td>2</td></tr><tr><td>Department of Electrical Engineering Malaviya National Institute of Technology Jaipur, Rajasthan, India</td><td>2</td></tr><tr><td><b>Center for Automation Research, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD, USA</b></td><td>2</td></tr><tr><td><b>School of EECS, Queen Mary University of London, UK</b></td><td>2</td></tr><tr><td><b>College of Software, Shenyang Normal University, Shenyang, China</b></td><td>2</td></tr><tr><td><b>Zhejiang University of Technology, Hangzhou, China</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology, Nanjing Normal University, China</b></td><td>2</td></tr><tr><td><b>University of Technology Sydney, Ultimo, NSW, Australia</b></td><td>2</td></tr><tr><td><b>Center for Special Needs Education, Nara University of Education, Takabatake-cho, Nara-shi, Nara, Japan</b></td><td>2</td></tr><tr><td>Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education, Chongqing, China</td><td>2</td></tr><tr><td><b>Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore</b></td><td>2</td></tr><tr><td><b>Samovar CNRS UMR 5157, Télécom SudParis, Université Paris-Saclay, Evry, France</b></td><td>2</td></tr><tr><td><b>Beijing E-Hualu Info Technology Co., Ltd, Beijing, China</b></td><td>2</td></tr><tr><td><b>Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University, Baoding 071002, China</b></td><td>2</td></tr><tr><td><b>Applied Informatics, Faculty of Technology, Bielefeld University, Germany</b></td><td>2</td></tr><tr><td>Osaka University Health Care Center, Japan</td><td>2</td></tr><tr><td><b>Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona, Spain</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Universitat Oberta de Catalunya, Barcelona, Spain</b></td><td>2</td></tr><tr><td><b>University of Groningen, Nijenborgh 9, 9747 AG, The Netherlands</b></td><td>2</td></tr><tr><td><b>University of Science and Technology of China, NO.443, Huangshan Road, Hefei, Anhui, China</b></td><td>2</td></tr><tr><td><b>Shenyang SIASUN Robot & Automation Co., LTD., Shenyang, China</b></td><td>2</td></tr><tr><td><b>State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Bahçeşehir Üniversitesi, İstanbul, Türkiye</b></td><td>2</td></tr><tr><td><b>Department of National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Institute of Automation, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Science Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand</b></td><td>2</td></tr><tr><td><b>Queen Mary University of London, London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Academy of Broadcasting Science, Beijing, P.R. China</b></td><td>2</td></tr><tr><td><b>Engineering Lab on Intelligent Perception for Internet of Things (ELIP), Shenzhen Graduate School, Peking University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Key Laboratory of Machine Perception, Ministry of Eduction, Peking University, Beijing, China</b></td><td>2</td></tr><tr><td><b>College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey</b></td><td>2</td></tr><tr><td><b>Department of Information Engineering, The Chinese University of Hong Kong</b></td><td>2</td></tr><tr><td><b>School of Computing, Teesside University, Middlesbrough, UK</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Digital Technologies, Faculty of Engineering and Environment, Northumbria University, Newcastle, UK, NE1 8ST</b></td><td>2</td></tr><tr><td><b>Faculty of Telecommunications, Technical University of Sofia, Bulgaria</b></td><td>2</td></tr><tr><td><b>Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>Computer Science, University of Haifa, Carmel, 31905, Israel</b></td><td>2</td></tr><tr><td><b>Fernuniversitt in Hagen FUH Hagen, Germany</b></td><td>2</td></tr><tr><td><b>Research institute for Telecommunication and Cooperation, FTK, Dortmund, Germany</b></td><td>2</td></tr><tr><td><b>Core Technology Center, OMRON Corporation, Kyoto, Japan</b></td><td>2</td></tr><tr><td><b>College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 404100, China</b></td><td>2</td></tr><tr><td><b>College of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 404100, China</b></td><td>2</td></tr><tr><td><b>USP - University of São Paulo / ICMC, SSC - LRM (Mobile Robots Lab.), São Carlos, 13566-590, Brazil</b></td><td>2</td></tr><tr><td><b>Department of Automation, Tsinghua National Laboratory for Information Science and Technology (TNList), State Key Lab of Intelligent Technologies and Systems, Tsinghua University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Electric and Electronics, Selçuk University, Konya, Turkey</b></td><td>2</td></tr><tr><td><b>Research Center of Intelligent Robotics, Department of Automation, Shanghai Jiao Tong University, 200240, China</b></td><td>2</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, KAIST, Deajeon, Daejeon, Republic of Korea</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, Tafresh University, Tafresh, Iran</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Chittagong University of Engineering and Technology, Chittagong, 4349, Bangladesh</b></td><td>2</td></tr><tr><td><b>Department of Mechanical Engineering, Chittagong University of Engineering and Technology, Chittagong, 4349, Bangladesh</b></td><td>2</td></tr><tr><td><b>University of Ottawa, Ottawa, ON, Canada</b></td><td>2</td></tr><tr><td><b>Kochi University of Technology, Kochi, 782-8502, Japan</b></td><td>2</td></tr><tr><td><b>Hefei University of Technology, School of Computer and Information, Hefei, Anhui, 230601, China</b></td><td>2</td></tr><tr><td><b>Karlsruhe Institute of Technology, Institute for Anthropomatics, Karlsruhe, Germany</b></td><td>2</td></tr><tr><td><b>Chinese Academy of Sciences, Shenzhen, China</b></td><td>2</td></tr><tr><td><b>Pattern Recognition and Intelligent System Lab., Beijing University of Posts and Telecommunications, China</b></td><td>2</td></tr><tr><td><b>NCCU, USA</b></td><td>2</td></tr><tr><td><b>WVU, USA</b></td><td>2</td></tr><tr><td><b>University of Nottingham Malaysia Campus, Selangor Darul Ehsan, Malaysia</b></td><td>2</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, the Faculty of Engineering and Information Technology, University of Technology, Sydney, Ultimo, Australia</b></td><td>2</td></tr><tr><td>Shahid Bahonar University of Kerman Computer Engineering Department, Kerman, Iran</td><td>2</td></tr><tr><td><b>Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, University of Hawaii, Manoa, Honolulu, HI, 96822</b></td><td>2</td></tr><tr><td><b>Samsung Electronics, SAIT Suwon-si, Korea</b></td><td>2</td></tr><tr><td><b>Department of Automation, University of Science and Technology of China</b></td><td>2</td></tr><tr><td><b>Centre for Intelligent Sensing, Queen Mary University of London, London, U.K.</b></td><td>2</td></tr><tr><td><b>CETUC, Pontifical Catholic University of Rio de Janeiro, Brazil</b></td><td>2</td></tr><tr><td><b>İstanbul Teknik Üniversitesi, İstanbul, Türkiye</b></td><td>2</td></tr><tr><td><b>School of Electronic Engineering, Xidian University, Xi’an, China</b></td><td>2</td></tr><tr><td><b>Islamic Azad University, South Tehran Branch, Electrical Engineering Department, Iran</b></td><td>2</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT) & Università di Torino, Genova, Italy</td><td>2</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT) & Università degli Studi di Genova, Genova, Italy</td><td>2</td></tr><tr><td><b>Shenzhen Graduate School, Harbin Institute of Technology, China</b></td><td>2</td></tr><tr><td><b>Human Language Technology and Pattern Recognition Group, RWTH Aachen University</b></td><td>2</td></tr><tr><td><b>Rensselaer Polytechnic Institute, USA</b></td><td>2</td></tr><tr><td><b>Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran</b></td><td>2</td></tr><tr><td><b>Vision Lab, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, United Kingdom</b></td><td>2</td></tr><tr><td><b>Center for Machine Vision Research, Computer Science and Engineering, University of Oulu, Oulu, Finland</b></td><td>2</td></tr><tr><td><b>University of Southern California, Los Angeles, USA</b></td><td>2</td></tr><tr><td><b>University of Amsterdam, The Netherlands</b></td><td>2</td></tr><tr><td><b>Academia Sinica, Institute of Information Science, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Centre for Communication Systems Research, University of Surrey, Guildford, Surrey, United Kingdom</b></td><td>2</td></tr><tr><td>Norwegian Biometric Laboratory, Norwegian University of Science and Technology (NTNU), Gjøvik, Norway</td><td>2</td></tr><tr><td><b>School of Computer Engineering and Science, Shanghai University</b></td><td>2</td></tr><tr><td><b>Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong, China</b></td><td>2</td></tr><tr><td><b>Corp. Res. & Dev. Center, Toshiba Corp., Kawasaki, Japan</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology, Tianjin University, 300072, China</b></td><td>2</td></tr><tr><td><b>Department of Information & Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain</b></td><td>2</td></tr><tr><td><b>Computer Engineering, Rochester Institute of Technology, USA</b></td><td>2</td></tr><tr><td><b>University of Notre Dame, Notre Dame, Indiana</b></td><td>2</td></tr><tr><td>Department of Computer Applications, National Institute of Technology, Tiruchirappalli, India</td><td>2</td></tr><tr><td>B. Tech Graduate, ECE, MSIT, C-4 Janakpuri, New Delhi, India</td><td>2</td></tr><tr><td><b>Department of Electrical, Computer and IT Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran</b></td><td>2</td></tr><tr><td><b>Computer Vision Institute, School of Computer Science and Software Engineering, and the Shenzhen Key Laboratory of Spatial Information Smart Sensing and Services, Shenzhen University, Shenzhen, China</b></td><td>2</td></tr><tr><td><b>University of Tokyo, Tokyo, Japan</b></td><td>2</td></tr><tr><td><b>RSISE, Australian National University, Australia</b></td><td>2</td></tr><tr><td>San Diego State University, San Diego, CA, USA</td><td>2</td></tr><tr><td><b>University of Memphis, Memphis, TN</b></td><td>2</td></tr><tr><td><b>HumanRobot Interaction Research Center, Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea seojh</b></td><td>2</td></tr><tr><td><b>Panasonic Singapore Laboratories Pte Ltd (PSL), Tai Seng Industrial Estate 534415, Singapore</b></td><td>2</td></tr><tr><td><b>University of Texas at Arlington, Arlington, USA</b></td><td>2</td></tr><tr><td><b>Massachusetts General Hospital, Boston, MA, USA</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA</b></td><td>2</td></tr><tr><td><b>Dept. of Electrical and Electronics Engineering, Bahcesehir University, Istanbul, Turkey</b></td><td>2</td></tr><tr><td>MIT, Cambridge, MA, USA</td><td>2</td></tr><tr><td><b>Department of Computer Science, University of York, York, UK</b></td><td>2</td></tr><tr><td><b>Imaging Software Technol. Center, Fuji Photo Film Co. Ltd., Japan</b></td><td>2</td></tr><tr><td><b>Dept. of ECE & Digital Technology Center, University of Minnesota, USA</b></td><td>2</td></tr><tr><td><b>Shenzhen University, Shenzhen China</b></td><td>2</td></tr><tr><td><b>National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190, Beijing, China</b></td><td>2</td></tr><tr><td><b>Islamic University of Technology, Bangladesh</b></td><td>2</td></tr><tr><td><b>Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan, 70101, Taiwan</b></td><td>2</td></tr><tr><td><b>Technion</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Okayama University, Okayama, Japan</b></td><td>2</td></tr><tr><td><b>Cyprus University of Technology</b></td><td>2</td></tr><tr><td>Dept of Electronics and Communication, Manipal Institute Of Technology, Karnataka, India</td><td>2</td></tr><tr><td><b>University of Technology, Sydney, Sydney, Australia</b></td><td>2</td></tr><tr><td>LMU Munich, Germany</td><td>2</td></tr><tr><td>Polytechnic School of Pernambuco, University of Pernambuco, Recife-PE, Brazil</td><td>2</td></tr><tr><td><b>Dept. of Electrical Engineering, National Taiwan University, Taiwan</b></td><td>2</td></tr><tr><td><b>Research Center for Information Technology Innovation, Academia Sinica, Taiwan</b></td><td>2</td></tr><tr><td><b>University of Illinois at Urbana-Champaign, 201 N Goodwin, 61820, USA</b></td><td>2</td></tr><tr><td><b>Research School of Engineering, The Australian National University, Canberra, ACT, Australia</b></td><td>2</td></tr><tr><td><b>CyLab Biometrics Center and the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA</b></td><td>2</td></tr><tr><td><b>Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands</b></td><td>2</td></tr><tr><td><b>Department of Computing, Imperial College London, London, UK</b></td><td>2</td></tr><tr><td><b>Pittsburgh Univ., PA, USA</b></td><td>2</td></tr><tr><td><b>Computer Vision and Remote Sensing, Berlin University of Technology, Sekr. FR 3-1, Franklinstr. 28/29, 10587, Germany</b></td><td>2</td></tr><tr><td><b>Department of Information Engineering, the Chinese University of Hong Kong, Shatin</b></td><td>2</td></tr><tr><td>Başkent University, Ankara, TURKEY</td><td>2</td></tr><tr><td><b>Department of Signal Processing, Tampere University of Technology, Finland</b></td><td>2</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Ankara Yıldırım Beyazıt Üniversitesi, Ankara, Türkiye</b></td><td>2</td></tr><tr><td><b>Department of Computer and Information Science, University of Macau, Taipa, Macau</b></td><td>2</td></tr><tr><td>Department of Electronic and Communication Engineering, Universiti Tenaga Nasional Km 7, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia</td><td>2</td></tr><tr><td><b>Senior Member, IEEE, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk, 790-784, South Korea. phone: 82-54-279-2880, 2214; fax: 82-54-279-5594; e-mail: dreaming@postech.ac.kr, syoh@postech.ac.kr</b></td><td>2</td></tr><tr><td><b>Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk, 790-784, South Korea. phone: 82-54-279-2880, 2214; fax: 82-54-279-5594; e-mail: dreaming@postech.ac.kr</b></td><td>2</td></tr><tr><td><b>Center of Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland</b></td><td>2</td></tr><tr><td><b>Key Laboratory of Child Development and Learning Science (Ministry of Education), Research Center for Learning Science, Southeast University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China</b></td><td>2</td></tr><tr><td><b>Dirección General de la Guardia Civil - DGGC Madrid, Spain</b></td><td>2</td></tr><tr><td><b>School of Information Science and Technology, Huaqiao University, Xiamen, China</b></td><td>2</td></tr><tr><td><b>Computer Laboratory, University of Cambridge, UK</b></td><td>2</td></tr><tr><td><b>School of Automation, Southeast University, Nanjing, China</b></td><td>2</td></tr><tr><td><b>Rutgers University, Piscataway</b></td><td>2</td></tr><tr><td><b>University of Hong Kong, China</b></td><td>2</td></tr><tr><td><b>Department of Automation, State Key Laboratory of Intelligent Technologies and Systems, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China</b></td><td>2</td></tr><tr><td><b>School of Electronics and Information Technology, Sun Yat-Sen University</b></td><td>2</td></tr><tr><td><b>Charles Sturt University, Wagga Wagga NSW, Australia</b></td><td>2</td></tr><tr><td>Sunway University, Selangor, Malaysia</td><td>2</td></tr><tr><td><b>Hexi University, Center for Information Technology, Zhangye, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Engineering, Rochester Institute of Technology, Rochester, NY, USA</b></td><td>2</td></tr><tr><td><b>School of Communication and Information Engineering, Shanghai University, Shanghai, China</b></td><td>2</td></tr><tr><td><b>Department of Communications and Computer Engineering, University of Malta, Msida, Malta</b></td><td>2</td></tr><tr><td><b>Multimedia Communications Dept., EURECOM, Sophia Antipolis, France</b></td><td>2</td></tr><tr><td>Northwestern Polytechnical University Xian, P. R. China</td><td>2</td></tr><tr><td><b>Northwestern Polytechnical University, Xian, P. R. China, and UNC-Charlotte, Charlotte, NC</b></td><td>2</td></tr><tr><td><b>Michigan State University, East Lansing, U.S.A.</b></td><td>2</td></tr><tr><td>Dept. of E & TC Engineering, Maharashtra Institute of Technology, Pune, India</td><td>2</td></tr><tr><td><b>Commonwealth Scientific and Industrial Research Organisation, Clayton South, Vic. , Australia</b></td><td>2</td></tr><tr><td><b>Speech, Audio, Image and Video Technology Laboratory, Queensland University of Technology, Brisbane, Australia</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology and the Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin, China</b></td><td>2</td></tr><tr><td><b>School of Electrical Engineering and Computer Science, Queen Mary University of London, London, U.K.</b></td><td>2</td></tr><tr><td><b>Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td>Dept. of ECE and Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td><b>Department of Computer Science, National Tsing Hua University, Taiwan, R.O.C</b></td><td>2</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Hong Kong</td><td>2</td></tr><tr><td>School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, 689-798, Korea</td><td>2</td></tr><tr><td>Dept. of Comp. Sci. and Inf. Eng, Chung Hua University, Hsinchu, Taiwan</td><td>2</td></tr><tr><td><b>Dept. of Comp. Sci, National Chiao Tung University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Department of Computing, Curtin University, Perth, Australia</b></td><td>2</td></tr><tr><td><b>HEUDIASYC Mixed Res. Unit, Compiegne Univ. of Technol., France</b></td><td>2</td></tr><tr><td><b>Università di Salerno v. Ponte don Melillo, 84084, Fisciano (IT)</b></td><td>2</td></tr><tr><td>Shanghai Jiao Tong University & Alibaba Group, Shanghai, China</td><td>2</td></tr><tr><td><b>National Taiwan University of Science and Technology, No.43, Keelung Rd., Sec.4, Da'an Dist., Taipei City 10607, Taiwan</b></td><td>2</td></tr><tr><td>School of Computer Science, Kyungpook National University, Buk-gu, Daegu, The Republic of Korea</td><td>2</td></tr><tr><td><b>Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China</b></td><td>2</td></tr><tr><td>Laboratory LAROSERI, Department of Computer Science, Faculty of Sciences, University of Chouaib Doukkali, El Jadida - Morocco</td><td>2</td></tr><tr><td><b>Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China</b></td><td>2</td></tr><tr><td><b>Computer Vision, Video and Image Processing (CvviP) Research Lab, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia</b></td><td>2</td></tr><tr><td><b>Microsoft Research Asia, China</b></td><td>2</td></tr><tr><td><b>Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering & Information Technology, University of Technology, Sydney, Australia</b></td><td>2</td></tr><tr><td>Microsoft Research India Pvt. Ltd, Bangalore, Karnataka, India</td><td>2</td></tr><tr><td><b>Indiana University Bloomington, Bloomington, IN, USA</b></td><td>2</td></tr><tr><td>Department of Electronics, University of Goa, India</td><td>2</td></tr><tr><td><b>Department of Computer Science, School of Science and Technology, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, Graduate School of Science and Technology, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa</b></td><td>2</td></tr><tr><td><b>Multimedia Processing Laboratory, Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA</b></td><td>2</td></tr><tr><td><b>Electric Power Research Institute, State Grid Shanghai Electric Power Company Shanghai, 200093, China</b></td><td>2</td></tr><tr><td><b>South East European University, Tetovo, Macedonia</b></td><td>2</td></tr><tr><td><b>Computer Science and Engineering, Arizona State University, Tempe, AZ</b></td><td>2</td></tr><tr><td><b>Villanova University, Villanova, PA, USA</b></td><td>2</td></tr><tr><td><b>University of Technology Sydney, Sydney, Australia</b></td><td>2</td></tr><tr><td><b>School of EE, Xidian University, Xi'an 710071, China</b></td><td>2</td></tr><tr><td>Department of ECE, National Institute of Technology, Rourkela (Odisha), India</td><td>2</td></tr><tr><td><b>Korea Electronics Technology Institute</b></td><td>2</td></tr><tr><td><b>Computer Science and Engineering Dept., University of North Texas, Denton, TX, USA</b></td><td>2</td></tr><tr><td>Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China</td><td>2</td></tr><tr><td><b>Institute of Information Science, Beijing Jiaotong University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA</b></td><td>2</td></tr><tr><td><b>Computer Science and Engineering Michigan State University, East Lansing, USA</b></td><td>2</td></tr><tr><td><b>College of Information Science and Technology, Beijing Normal University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Organization of Advanced Science and Technology, Kobe University, Japan</b></td><td>2</td></tr><tr><td><b>Center for Research in Computer Vision, University of Central Florida, Orlando, USA</b></td><td>2</td></tr><tr><td><b>IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA</b></td><td>2</td></tr><tr><td><b>International Institute of Information Technology, Hyderabad, India</b></td><td>2</td></tr><tr><td><b>University of Illinois’ Advanced Digital Sciences Center, Singapore</b></td><td>2</td></tr><tr><td><b>Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland 20740 United States</b></td><td>2</td></tr><tr><td>B-DAT Laboratory, School of Information and Control, Nanjing University of Information and Technology, Nanjing, China</td><td>2</td></tr><tr><td><b>University of Cambridge, Cambridge, United Kingdom</b></td><td>2</td></tr><tr><td><b>Intelligent Data Center (IDC) and Department of Mathematics, Sun Yat-Sen University, Guangzhou, China</b></td><td>2</td></tr><tr><td><b>Jaypee Institute of Information Technology</b></td><td>2</td></tr><tr><td><b>Samsung Advanced Institute of Technology (SAIT), Republic of Korea</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Technology, Tsinghua University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Institute of Computing Technology, CAS, Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Beijing, China</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Engineering, University of Aizu, Tsuruga, Ikkimachi, Aizuwakamatsu, Japan</b></td><td>2</td></tr><tr><td><b>Comnuter Science Department, Hong Kong Baptist University</b></td><td>2</td></tr><tr><td><b>Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA</b></td><td>2</td></tr><tr><td><b>Institute of Computing, University of Campinas, Campinas, SP, 13083-852, Brazil</b></td><td>2</td></tr><tr><td><b>Robotics Lab, Futurewei Technologies Inc., Santa Clara, USA</b></td><td>2</td></tr><tr><td><b>Institute of Automatic Control Engineering (LSR), TU München, Germany</b></td><td>2</td></tr><tr><td><b>Image Understanding and Knowledge-Based Systems, TU München, Germany</b></td><td>2</td></tr><tr><td><b>University of Delaware, Newark, DE</b></td><td>2</td></tr><tr><td><b>HRL Laboratories, LLC, Information Systems and Sciences Lab, Malibu, CA 90265 USA</b></td><td>2</td></tr><tr><td><b>Division of Computing Systems, School of Computer Engineering, Nanyang Technological University, Singapore, Singapore</b></td><td>2</td></tr><tr><td><b>School of Computer Science, Communication University of China, Beijing, China</b></td><td>2</td></tr><tr><td><b>Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA</b></td><td>2</td></tr><tr><td><b>Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, China</b></td><td>2</td></tr><tr><td>Thales Services, ThereSIS, Palaiseau, France</td><td>2</td></tr><tr><td>School of Electrical and Electronic Engineering, Tianjin University of Technology, China</td><td>2</td></tr><tr><td><b>Faculty of Computers and Information, Cairo University, Egypt</b></td><td>2</td></tr><tr><td><b>Dept. of Electrical and Computer Engineering, National University of Singapore</b></td><td>2</td></tr><tr><td><b>Department of Computing, the Hong Kong Polytechnic University, Hong Kong</b></td><td>2</td></tr><tr><td><b>Institute of Computing, University of Campinas, Campinas, SP, Brazil, 13083-852</b></td><td>2</td></tr><tr><td><b>Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China</b></td><td>2</td></tr><tr><td><b>CyLab Biometrics Center, Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA</b></td><td>2</td></tr><tr><td><b>La Trobe University, Australia</b></td><td>2</td></tr><tr><td><b>State key Laboratory of High Performance Computing, National University of Defense Technology, Changsha, Hunan, China, 410073</b></td><td>2</td></tr><tr><td><b>University of South Carolina, Columbia, SC, USA</b></td><td>2</td></tr><tr><td><b>Science and Engineering Faculty, Queensland University of Technology, Australia</b></td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, Mepco Schlenk Engineering College, Sivakasi, India</td><td>2</td></tr><tr><td><b>Department of Computer Technology, Shanghai Jiao Tong University, Shanghai, China</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Software Engineering, The University of Western Australia, Nedlands, WA, Australia</b></td><td>2</td></tr><tr><td><b>National Tsing Hua University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Rutgers, The State University of New Jersey</b></td><td>2</td></tr><tr><td><b>Dhirubhai Ambani Institute of Information and Communication Technology, India</b></td><td>2</td></tr><tr><td><b>Aix Marseille Univ LIF/CNRS, France</b></td><td>2</td></tr><tr><td><b>Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, San Jose State University, San Jose, CA</b></td><td>2</td></tr><tr><td>IIIT Bangalore, India</td><td>2</td></tr><tr><td>Institut de Robòtica i Informàtica Industrial (CSIC-UPC)</td><td>2</td></tr><tr><td><b>TeV, Fondazione Bruno Kessler, Trento, Italy</b></td><td>2</td></tr><tr><td>Department of Computer Science, IT: Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>2</td></tr><tr><td>Xinjiang University, Urumqi, China</td><td>2</td></tr><tr><td><b>Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>2</td></tr><tr><td><b>School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, People’s Republic of China</b></td><td>2</td></tr><tr><td><b>Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, 1 University Road, Tainan, Taiwan</b></td><td>2</td></tr><tr><td><b>New Jersey Institute of Technology, Department of Electrical & Computer Engineering, University Heights Newark, NJ 07102 USA</b></td><td>2</td></tr><tr><td><b>Korea Advanced Institute of Science and Technology</b></td><td>2</td></tr><tr><td><b>College of Communication Engineering, Chongqing University, Chongqing, China</b></td><td>2</td></tr><tr><td><b>Department of Forestry and Management of the Environment, Democritus University of Thrace, Orestiada, Greece</b></td><td>2</td></tr><tr><td>School of Computing Science and Engineering, VIT University, Vellore, India</td><td>2</td></tr><tr><td><b>School of Information Science, Japan Advanced Institute of Science and Technology, Asahidai 1-1, Nomi-shi, Ishikawa, Japan, 923-1211</b></td><td>2</td></tr><tr><td><b>Chinese Academy of Sciences, Beijing</b></td><td>2</td></tr><tr><td><b>Tsinghua University, Beijing</b></td><td>2</td></tr><tr><td><b>Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan</b></td><td>2</td></tr><tr><td><b>Artificial Intelligence Laboratory, University of Tsukuba, Japan</b></td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA</td><td>2</td></tr><tr><td><b>Brno University of Technology, Brno-střed, Czech Republic</b></td><td>2</td></tr><tr><td><b>Deutsche Welle, Bonn, Germany</b></td><td>2</td></tr><tr><td>GSI Universidad Polit-écnica de Madrid, Madrid, Spain</td><td>2</td></tr><tr><td><b>University of Waterloo, Canada</b></td><td>2</td></tr><tr><td><b>The University of Tokyo, Tokyo, Japan</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, University of Calgary, Calgary, Alberta, Canada</b></td><td>2</td></tr><tr><td><b>National Institute of Standards and Technology (NIST), Gaithersburg, MD</b></td><td>2</td></tr><tr><td><b>Räven AB, SE-411 14 Göteborg, Sweden</b></td><td>2</td></tr><tr><td><b>School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China</b></td><td>2</td></tr><tr><td><b>University of Illinois at Urbana-Champaign, Urbana, USA</b></td><td>2</td></tr><tr><td><b>School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138</b></td><td>2</td></tr><tr><td><b>The Rowland Insitute at Harvard, Harvard University, Cambridge, MA 02142</b></td><td>2</td></tr><tr><td><b>The Open University of Israel, Israel</b></td><td>2</td></tr><tr><td><b>Halmstad University, Halmstad, Sweden</b></td><td>2</td></tr><tr><td>Department of Electronic Engineering, Kwangwoon University, Seoul, Republic of Korea</td><td>2</td></tr><tr><td><b>Division of Information and Computer Engineering, Ajou University, Suwon, Republic of Korea</b></td><td>2</td></tr><tr><td><b>Department of Computer Engineering, Kyung Hee University, Suwon, Republic of Korea</b></td><td>2</td></tr><tr><td><b>School of Computer Science, Carnegie Mellon University, Pittsburgh, USA</b></td><td>2</td></tr><tr><td>Dept. of Appl. Phys. & Electron., Umea Univ., Sweden</td><td>2</td></tr><tr><td>Universidade Federal do Paraná, Curitiba, Brazil</td><td>2</td></tr><tr><td><b>Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR</b></td><td>2</td></tr><tr><td><b>Department of Radiology, University of Pennsylvania, Philadelphia, PA</b></td><td>2</td></tr><tr><td><b>Institute of VLSI Design, Zhejiang University, Hangzhou, China</b></td><td>2</td></tr><tr><td><b>Faculty of Engineering Technology, Hasselt University, Diepenbeek, Belgium</b></td><td>2</td></tr><tr><td><b>DUT-RU International School of Information and Software Engineering, Dalian University of Technology, Dalian, China</b></td><td>2</td></tr><tr><td><b>University of Barcelona, Barcelona, Spain</b></td><td>2</td></tr><tr><td>Università degli Studi di Verona, Verona, Italy</td><td>2</td></tr><tr><td>CEA, Gif-Sur-Yvette, France</td><td>2</td></tr><tr><td>UMR CNRS - Univ. Bourgogne, Dijon, France</td><td>2</td></tr><tr><td><b>Universita degli Studi di Palermo, Dipartimento di Ingegegneria Informatica, Viale delle Scienze, 90128, ITALY</b></td><td>2</td></tr><tr><td><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, USA</b></td><td>2</td></tr><tr><td>Mechatronic Engineering Department, Mevlana University, Konya, Turkey</td><td>2</td></tr><tr><td><b>Tokyo Metropolitan University, Hino, Tokyo 191-0065, Japan</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer, Engineering, University of Denver, Denver, CO 80208</b></td><td>2</td></tr><tr><td>TÜBİITAK-BİILGEM-UEKAE, Anibal Cad., P.K.74, 41470, Gebze-KOCAELİ, Turkey</td><td>2</td></tr><tr><td><b>State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China</b></td><td>2</td></tr><tr><td><b>School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China</b></td><td>2</td></tr><tr><td><b>Department of Electronic Engineering, Tsinghua University, Beijing 100084, P.R. China</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada</b></td><td>2</td></tr><tr><td>The 28th Research Institute of China Electronics Technology Group Corporation, China</td><td>2</td></tr><tr><td><b>Indian Statistical Institute, 203, B. T. Road, Kolkata 700108, India</b></td><td>2</td></tr><tr><td><b>Institute of Neural Information Processing, Ulm University, Ulm, Germany</b></td><td>2</td></tr><tr><td><b>Institute of VLSI Design, Zhejiang University</b></td><td>2</td></tr><tr><td><b>Faculty of Engineering Technology, University Hasselt</b></td><td>2</td></tr><tr><td><b>Massachusetts Institute of Technology, Cambridge, MA</b></td><td>2</td></tr><tr><td><b>Institute of Information Science, Academia Sinica, Taipei, Taiwan Roc</b></td><td>2</td></tr><tr><td><b>Institute of Information Science, Beijing Jiaotong University, 100044, China</b></td><td>2</td></tr><tr><td><b>Department of Computer and Information Sciences, Temple University</b></td><td>2</td></tr><tr><td><b>Department of Computing Sciences, Elon University</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Maryland, College Park, MD</b></td><td>2</td></tr><tr><td>Raytheon BBN Technologies, 10 Moulton St, Cambridge, MA</td><td>2</td></tr><tr><td><b>General Electric Global Research, 1 Research Circle, Niskayuna, NY</b></td><td>2</td></tr><tr><td><b>Concordia University, Montreal, QC, Canada</b></td><td>2</td></tr><tr><td><b>Charles Perkin Centre, Faculty of Medicine, University of Sydney, Australia</b></td><td>2</td></tr><tr><td><b>Charles Perkin Centre, Faculty of Engineering, University of Sydney, Australia</b></td><td>2</td></tr><tr><td><b>Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China</b></td><td>2</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Nazarbayev University, Astana, Kazakhstan</b></td><td>2</td></tr><tr><td><b>Department of Information and Communication Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan</b></td><td>2</td></tr><tr><td><b>Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA</b></td><td>2</td></tr><tr><td><b>Tsinghua National Lab for Info. Sci. & Tech., Depart. of Computer Sci. & Tech., Tsinghua University, Beijing, China</b></td><td>2</td></tr><tr><td><b>Harbin Institute of Technology</b></td><td>2</td></tr><tr><td><b>National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>2</td></tr><tr><td><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>2</td></tr><tr><td>School of Electrical Engineering and Computer Science at the University of Newcastle, Callaghan, NSW 2308, Australia</td><td>2</td></tr><tr><td><b>School of Electrical Engineering and Computing, University of Newcastle, Newcastle, Australia</b></td><td>2</td></tr><tr><td><b>School of Computer Science, University of Windsor, Windsor, Canada</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Engineering, Dankook University, Yongin, South Korea</b></td><td>2</td></tr><tr><td>Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India</td><td>2</td></tr><tr><td><b>KTH Royal Institute of Technology, Stockholm, Sweden</b></td><td>2</td></tr><tr><td><b>Division of Graduate Studies of Tijuana Institute Technology, Mexico</b></td><td>2</td></tr><tr><td>Pontifícia Universidade Católica do RS, Porto Alegre-RS, Brazil</td><td>2</td></tr><tr><td><b>Department of Psychology and the Center for Brain Science, Harvard University, Cambridge</b></td><td>2</td></tr><tr><td><b>School of Engineering and Applied Sciences, Department of Molecular and Cellular Biology, and the Center for Brain Science, Harvard University, Cambridge</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, The University of Texas at San Antonio, San Antonio, TX, USA</b></td><td>2</td></tr><tr><td><b>Sch. of Infor. Sci. and Tech., Huizhou Unversity, Huizhou, China</b></td><td>2</td></tr><tr><td><b>Institute of Advanced Manufacturing Technology, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences, Ningbo, China</b></td><td>2</td></tr><tr><td><b>School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China</b></td><td>2</td></tr><tr><td>Waseda University The Graduate School of Information, Production and Systems 2-7, Hibikino, Wakamatsu-ku, Kitakyushu-shi, Fukuoka, Japan</td><td>2</td></tr><tr><td><b>London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Shenzhen VisuCA Key Lab / SIAT, Chinese Academy of Sciences, China</b></td><td>2</td></tr><tr><td><b>Department of Mathematics, Center for Computer Vision, Sun Yat-Sen University, Guangzhou, China</b></td><td>2</td></tr><tr><td><b>Department of Computer Science and Technology, Huaqiao University, Xiamen, China</b></td><td>2</td></tr><tr><td><b>Xiamen University, Fujian, China</b></td><td>2</td></tr><tr><td>Majority Report, France</td><td>2</td></tr><tr><td><b>Imaging Science and Engineering Laboratory Tokyo Institute of Technology Yokohama 226-8503, Japan</b></td><td>2</td></tr><tr><td>SITI Laboratory, National Engineering School of Tunis (ENIT), University of Tunis El Manar, Tunis, Tunisia</td><td>2</td></tr><tr><td>University of Montreal, Department of Computer Science and Operations Research (DIRO), 2920 Chemin de la tour, QC, Canada, H3C 3J7</td><td>2</td></tr><tr><td><b>College of Computer Science and Technology, Harbin Engineering University, Harbin, China</b></td><td>2</td></tr><tr><td><b>Keio University, Kanagawa, Japan</b></td><td>2</td></tr><tr><td><b>Microsoft Research, Haidian, Beijing, P. R. China</b></td><td>2</td></tr><tr><td><b>Video and Image Processing System Laboratory, School of Electronic Engineering, Xidian University , Xi'an, China</b></td><td>2</td></tr><tr><td><b>Department of Computing, Imperial College London, United Kingdom</b></td><td>2</td></tr><tr><td><b>Robert BOSCH Research and Technology Center, Palo Alto, CA 94304, USA</b></td><td>2</td></tr><tr><td>Università di Salerno, Fisciano (SA), Italy</td><td>2</td></tr><tr><td>Advanced Technologies Application Center 7a #21406 b/ 214 and 216, P.C. 12200, Siboney Playa, Havana, Cuba</td><td>2</td></tr><tr><td><b>National Chung Hsing University, Taichung</b></td><td>2</td></tr><tr><td><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing</b></td><td>2</td></tr><tr><td>School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an, China</td><td>2</td></tr><tr><td><b>The University of Tokyo</b></td><td>2</td></tr><tr><td>Department of Sciences and Information Technology, University of Sassari, Viale Mancini 5, 07100 Sassari, Italy</td><td>2</td></tr><tr><td><b>Institute for Information Technology and Communications (IIKT), Otto-von-Guericke-University Magdeburg, D-39016, P.O. Box 4210 Germany</b></td><td>2</td></tr><tr><td><b>ISIR, CNRS UMR 7222, Universite Pierre et Marie Curie, Paris</b></td><td>2</td></tr><tr><td><b>National Taiwan University of Science and Technology, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Beijing Institute of Science and Technology Information</b></td><td>2</td></tr><tr><td><b>University of Maryland, College Park, MD, 20742</b></td><td>2</td></tr><tr><td><b>Department of Computer Science, University of Rochester, Rochester, NY, USA</b></td><td>2</td></tr><tr><td>Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany</td><td>2</td></tr><tr><td><b>State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China</b></td><td>2</td></tr><tr><td><b>Electrical and Computer Engineering, Wayne State University, Detroit, Michigan 48202</b></td><td>2</td></tr><tr><td><b>Bahcesehir University, Istanbul, Turkey</b></td><td>2</td></tr><tr><td><b>University of Udine, Italy</b></td><td>2</td></tr><tr><td>Department of Computer Science and Information Engineering, National Formosa University, Yunlin 632, Taiwan</td><td>2</td></tr><tr><td>Broadcasting & Telecommunications, Convergence Media Research Department, Electronics and Telecommunications Research Institute, Daejeon, Korea</td><td>2</td></tr><tr><td><b>Keio University, Yokohama, Japan</b></td><td>2</td></tr><tr><td><b>Graduate Institute of Networking and Multimedia and the Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan</b></td><td>2</td></tr><tr><td><b>Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, USA</b></td><td>2</td></tr><tr><td><b>Innovation Center, Canon USA Inc., San Jose, California</b></td><td>2</td></tr><tr><td><b>University of Texas at San Antonio, San Antonio, Texas</b></td><td>2</td></tr><tr><td>Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td><b>Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA 24061, USA</b></td><td>2</td></tr><tr><td>FMV IŞIK Üniversitesi, Şile, Istanbul</td><td>2</td></tr><tr><td><b>Istanbul Technical University, Informatics Institute, 34469, Turkey</b></td><td>2</td></tr><tr><td><b>School of Mathematical Sciences, Anhui University, Hefei, China</b></td><td>2</td></tr><tr><td><b>Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48824, USA</b></td><td>2</td></tr><tr><td><b>Agency for Science, Technology and Research, Institute for Infocomm Research, Singapore</b></td><td>2</td></tr><tr><td><b>School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore</b></td><td>2</td></tr><tr><td><b>Artificial Vision Laboratory National Taiwan University of Science and Technology</b></td><td>2</td></tr><tr><td><b>Computational Imaging Laboratory, School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, USA</b></td><td>1</td></tr><tr><td>Lehrstuhl für Mustererkennung, FAU Erlangen – Nürnberg, Erlangen, Germany</td><td>1</td></tr><tr><td><b>College of Computer Science and Electronic Engineering, Hunan Key Laboratory of Dependable Systems and Network, Hunan University, Changsha, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, and ASRI, Seoul National University, Republic of Korea</b></td><td>1</td></tr><tr><td><b>Istanbul Technical University, Turkey</b></td><td>1</td></tr><tr><td><b>Sabanci University, Turkey</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Machine Perception(MOE), EECS, Peking University, Beijing, 100871</b></td><td>1</td></tr><tr><td>Nanjing University of Posts and Telecommunications, China</td><td>1</td></tr><tr><td><b>Information Sciences Institute, University of Southern California, Marina del Rey, USA</b></td><td>1</td></tr><tr><td><b>Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung, Taiwan</td><td>1</td></tr><tr><td><b>College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia</b></td><td>1</td></tr><tr><td><b>Griffith University, Australia</b></td><td>1</td></tr><tr><td>Laboratoire d’interprétation et de traitement d’images et vidéo, Polytechnique Montréal, Montreal, Canada</td><td>1</td></tr><tr><td>Laboratoire d’imagerie de vision et d’intelligence artificielle, École de technologie supérieure, Université du Québec, Montreal, Canada</td><td>1</td></tr><tr><td><b>Department of Multimedia Design, National Taichung University of Science and Technology, Taichung, Taiwan</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi, Taiwan</b></td><td>1</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, Surrey GU2 7XH, UK</b></td><td>1</td></tr><tr><td>University of Bern, Bern, Switzerland</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Denver, Denver, USA</b></td><td>1</td></tr><tr><td>School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, PR China</td><td>1</td></tr><tr><td>Department of Computer Science, University of California at Davis, Davis, USA</td><td>1</td></tr><tr><td><b>School of Computer Science, Fudan University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea</b></td><td>1</td></tr><tr><td><b>Korea Institute of Oriental Medicine, Daejeon, South Korea</b></td><td>1</td></tr><tr><td><b>Microsoft Research Asia, 49 Zhichun Road, Beijing, 100190, China</b></td><td>1</td></tr><tr><td>Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, China</td><td>1</td></tr><tr><td><b>School of Software Technology, Dalian University of Technology, Dalian, China</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Shri Shankaracharya Technical Campus, Bhilai, District-Durg, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi, India</td><td>1</td></tr><tr><td><b>Department of Information Engineering, The Chinese University of Hong Kong, China</b></td><td>1</td></tr><tr><td><b>Institute of Education, Xiamen University, Xiamen Shi, China</b></td><td>1</td></tr><tr><td>College of Artificial Intelligenge and Big Data, ChongQing University of Electronic Engineering, Chongqing, China</td><td>1</td></tr><tr><td><b>Harbin Engineering University, Harbin, Heilongjiang, 150001, China</b></td><td>1</td></tr><tr><td>Laboratoire Jean Kuntzmann, Grenoble, France</td><td>1</td></tr><tr><td><b>Electrical and Electronics Engineering Department, Eskisehir Osmangazi University, Eskisehir, Turkey</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Science and Computer Engineering, University of Louisville, KY, USA</b></td><td>1</td></tr><tr><td>Dept. of Advanced Technologies, Alcorn State University, MS, USA</td><td>1</td></tr><tr><td><b>Baiyun District Bureau of Justice, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Guangdong Key Laboratory of Information Security Technology, School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Department of Information Management, Tamkang University, New Taipei City, Taiwan</b></td><td>1</td></tr><tr><td>Department of Industrial Design, Tatung University, Taipei 104, Republic of China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Tatung University, Taipei 104, Republic of China</td><td>1</td></tr><tr><td><b>IBM T. J. Watson Research Center</b></td><td>1</td></tr><tr><td><b>AI Lab, TAL Education Group, College of Electronics and Information Engineering, Sichuan University, Chengdu, China</b></td><td>1</td></tr><tr><td><b>Institute of High Performance Computing, A*STAR, Singapore</b></td><td>1</td></tr><tr><td><b>3OmniVision Technologies Singapore Pte. Ltd., Singapore</b></td><td>1</td></tr><tr><td><b>Department of ECE, National University of Singapore, Singapore</b></td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Yangzhou University, Yangzhou, People’s Republic of China</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Nanjing University of Science & Technology, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Toronto Toronto, Canada</b></td><td>1</td></tr><tr><td><b>School of Information Science and Engineering, Yunnan University, Kunming, P. R. China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, Jiangnan University, Wuxi, China</b></td><td>1</td></tr><tr><td>School of Information Engineering, Yangzhou University, Yangzhou, China</td><td>1</td></tr><tr><td><b>Key Laboratory of Intelligent Processing, Institute of Computing Technology, CAS, Chinese Academy of Sciences (CAS), Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td>Res. Center for Learning Sci., Southeast Univ., Jiangsu, China</td><td>1</td></tr><tr><td>Eedoo Inc, Beijing, China</td><td>1</td></tr><tr><td><b>School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China</b></td><td>1</td></tr><tr><td>CSE, SUNY at Buffalo, USA and Southeast University, China</td><td>1</td></tr><tr><td><b>Knowledge Enterprise Development, Arizona State University, Tempe, 85287-5406 United States</b></td><td>1</td></tr><tr><td><b>Computer Science, Florida State University, Tallahassee, United States</b></td><td>1</td></tr><tr><td><b>Computing Informatics and Decision Systems Engineering, Arizona State University, Tempe, United States</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Northern British Columbia, Prince George, Canada</b></td><td>1</td></tr><tr><td><b>Speech, Audio, Image, and Video Technology Laboratory, Queensland University of Technology , Brisbane, Australia</b></td><td>1</td></tr><tr><td><b>Speech, Audio, Image, and Video Technology Laboratory, Queensland University of Technology, Brisbane, Australia</b></td><td>1</td></tr><tr><td><b>Commonwealth Scientific and Industrial Research Organization, Pullenvale, Australia</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh, Pittsburgh, PA , USA</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA</b></td><td>1</td></tr><tr><td><b>School of computer Science and Engineering, Nanyang Technological University, Singapore</b></td><td>1</td></tr><tr><td><b>Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore</b></td><td>1</td></tr><tr><td><b>Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India</b></td><td>1</td></tr><tr><td><b>Yonsei University, Seoul, South Korea</b></td><td>1</td></tr><tr><td><b>Multimedia University, Melaka, Malaysia</b></td><td>1</td></tr><tr><td>School of Information Technology and Engineering, VIT University, Vellore, India</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, New Jersey, 07030</b></td><td>1</td></tr><tr><td>Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881</td><td>1</td></tr><tr><td>Vulcan Inc, Seattle, WA 98104</td><td>1</td></tr><tr><td><b>Department of Computer Science, Hofstra University, Hempstead, NY 11549</b></td><td>1</td></tr><tr><td>Dept. of Computing, Curtin University of Technology, WA 6102, USA</td><td>1</td></tr><tr><td>School of Software, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td><b>University of Washington, Tacoma & Ghent University, Tacoma, WA, USA</b></td><td>1</td></tr><tr><td>University of California, Santa Cruz & Ghent University, Santa Cruz, CA, USA</td><td>1</td></tr><tr><td>Computer Vision Research lab, Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran</td><td>1</td></tr><tr><td><b>Language Technologies Institute, Carnegie Mellon University, Pittsburgh, PA</b></td><td>1</td></tr><tr><td><b>Center for OPTical Imagery Analysis and Learning, Northwestern Polytechnical University, Shaanxi, China</b></td><td>1</td></tr><tr><td><b>Beijing Etrol Technologies Co., Ltd, Beijing, China</b></td><td>1</td></tr><tr><td><b>Securics, Inc. Colorado Springs, CO, USA</b></td><td>1</td></tr><tr><td><b>Institute of Computing, University of Campinas (Unicamp) Campinas, SP, Brazil</b></td><td>1</td></tr><tr><td>HAN University of Applied Sciences, Arnhem, Netherlands</td><td>1</td></tr><tr><td>Faculty of Information Technology, Barrett Hodgson University, Karachi, Pakistan</td><td>1</td></tr><tr><td>Laboratoire Hubert Curien, UMR5516, Université Jean Monnet, Saint-Etienne, France</td><td>1</td></tr><tr><td>Université de Lyon, CNRS, LIRIS, UMR5205, Université Lyon 1, Lyon, France</td><td>1</td></tr><tr><td>Department of Electrical and Computer Engineering, Saginaw Valley State University, University Ctr, MI- 48710</td><td>1</td></tr><tr><td>TCTS Lab, Faculté Polytechnique de Mons, Belgium</td><td>1</td></tr><tr><td>Speech Technology Group, Technical University of Madrid, Spain</td><td>1</td></tr><tr><td>TALP Research Center, Universitat Politècnica de Catalunya, Spain</td><td>1</td></tr><tr><td><b>Electrical and Electronics Engineering Dept., Bogazici University, Turkey</b></td><td>1</td></tr><tr><td><b>AIIA Lab, Aristotle University of Thessaloniki, Greece</b></td><td>1</td></tr><tr><td>TELE Lab, Université catholique de Louvain, Belgium</td><td>1</td></tr><tr><td><b>DISI, University of Trento, Trento, Italy</b></td><td>1</td></tr><tr><td><b>LAPI, University Politehnica of Bucharest, Bucharest, Romania</b></td><td>1</td></tr><tr><td><b>IDIAP Research Institute, Martigny, Switzerland</b></td><td>1</td></tr><tr><td><b>University of Michigan, Ann, Arbor, MI USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Memorial University of Newfoundland, St. John’s, Canada</b></td><td>1</td></tr><tr><td>INRIA Grenoble-Rhône-Alpes Research Center, France</td><td>1</td></tr><tr><td><b>Department of Computer Science, Rutgers University, Piscataway, New Jersey 08854, USA</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Information, Anhui Polytechnic University, Wuhu, China</b></td><td>1</td></tr><tr><td><b>Language Technologies Institute, Carnegie Mellon University, Pittsburgh, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Stanford University, Stanford, USA</b></td><td>1</td></tr><tr><td><b>School of Mathematics, Beihang University, Beijing, China</b></td><td>1</td></tr><tr><td>Department of Embedded Systems, Institute for Infocomm Research, Singapore</td><td>1</td></tr><tr><td><b>IBM Research, USA</b></td><td>1</td></tr><tr><td><b>IBM Hursley Labs, UK</b></td><td>1</td></tr><tr><td>E.T.S. Ingenieros Industriales, Universidad de Castilla-La Mancha Campus Universitario, Ciudad Real, Spain</td><td>1</td></tr><tr><td>Universidad de Las Palmas de Gran Canaria, SIANI, Edificio Central del Parque Científico-Tecnológico, Las Palmas, Spain</td><td>1</td></tr><tr><td><b>Monash University, Caulfield East, Australia</b></td><td>1</td></tr><tr><td>School of Math and Geospatial Sciences, Royal Melbourne Institute of Technology University , Melbourne, Australia</td><td>1</td></tr><tr><td><b>Department of Computer Science, Harbin Institute of Technology, China, 150001</b></td><td>1</td></tr><tr><td>Department of Computer Science and Application, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou, China</td><td>1</td></tr><tr><td>School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China</td><td>1</td></tr><tr><td><b>Computer Science Department, School of Information Science and Engineering, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213. Marios.Savvides@ri.cmu.edu</b></td><td>1</td></tr><tr><td><b>Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213. yunghui@cmu.edu</b></td><td>1</td></tr><tr><td><b>College of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Department of Software Engineering, King Saud University, Riyadh, Saudi Arabia</b></td><td>1</td></tr><tr><td><b>Institute of Information Technology, University of Dhaka, Dhaka, Bangladesh</b></td><td>1</td></tr><tr><td><b>Department of Information, The Third Affiliated Hospital, Sun Yat-sen University, China</b></td><td>1</td></tr><tr><td><b>OmniVision Technologies Singapore Pte. Ltd., Singapore</b></td><td>1</td></tr><tr><td><b>Electrical and Computer Engineering, Ryerson University, Toronto, Canada</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computing Engineering, Ryerson University, Toronto, Canada</b></td><td>1</td></tr><tr><td>Department of Electrical and Computer Engineering, Naresuan University, Muang, Thailand</td><td>1</td></tr><tr><td>Department of Computer Science, Christian-Albrechts University, Kiel, Germany</td><td>1</td></tr><tr><td>Engineering Lab on Intelligent Perception for Internet of Things, Peking University Shenzhen Graduate School, Shenzhen, China</td><td>1</td></tr><tr><td><b>MOE Key Laboratory of Machine Perception, Peking University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Eletrical and Computer Engineering Department, Drexel University, Philadelphia, USA</b></td><td>1</td></tr><tr><td><b>TCL Research America, San Jose, CA 95134, USA</b></td><td>1</td></tr><tr><td><b>Dept. of Eng. Sciences and Appl. Mathematics, Northwestern University, Evanston, IL 60208, USA</b></td><td>1</td></tr><tr><td>Delft University of Technology and Sensor Technology, Netherlands Defense Academy</td><td>1</td></tr><tr><td><b>GE Global Research</b></td><td>1</td></tr><tr><td><b>Xerox Research Center India, India</b></td><td>1</td></tr><tr><td><b>Palo Alto Research Center, Webster, NY</b></td><td>1</td></tr><tr><td><b>Facebook, Singapore</b></td><td>1</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Bahçeşehir Üniversitesi, Turkey</b></td><td>1</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Boğaziçi Üniversitesi, Turkey</b></td><td>1</td></tr><tr><td><b>School of Information Technologies, The University of Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td>School of Electrical Engineering and Automation, Qilu University of Technology, Jinan, China</td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China</td><td>1</td></tr><tr><td><b>School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Beijing Advanced Innovation Center for Imaging Technology, Beijing 100048, China</b></td><td>1</td></tr><tr><td><b>Lane Department of CSEE, West Virginia University, Morgantown, WV 26506, USA</b></td><td>1</td></tr><tr><td><b>Institute of Computing, University of Campinas, Campinas-SP, CEP, Brazil</b></td><td>1</td></tr><tr><td>Department of Electronics and Computing and the Electronics and Information Technology Research & Development Center, Universidade Federal do Amazonas, Manaus-AM, CEP, Brazil</td><td>1</td></tr><tr><td><b>National Chiao-Tung University, Hsinchiu, Taiwan</b></td><td>1</td></tr><tr><td><b>General Electric Global Research, Niskayuna, NY, USA</b></td><td>1</td></tr><tr><td><b>Institute of Computing, University of Campinas, Campinas, Brazil</b></td><td>1</td></tr><tr><td>University of California at Merced, Merced, USA</td><td>1</td></tr><tr><td><b>University of Adelaide, Adelaide, Australia</b></td><td>1</td></tr><tr><td>Technische Universität München, Garching, Germany</td><td>1</td></tr><tr><td><b>Department of Mathematics, Wayne State University, Detroit, MI, USA</b></td><td>1</td></tr><tr><td><b>Artificial Intelligence Key Laboratory, of Sichuan Province, Zigong, Sichuan, 643000, P. R. China</b></td><td>1</td></tr><tr><td>School of Big Data and Computer, Science, Guizhou Normal University, Guiyang, Guizhou, 550025, P. R. China</td><td>1</td></tr><tr><td><b>School of Electrical & Electronic Engineering, Yonsei University, Seoul, South Korea, 120-749</b></td><td>1</td></tr><tr><td><b>Inria Méditerranée, France</b></td><td>1</td></tr><tr><td><b>Microsoft Research, Mountain View, California</b></td><td>1</td></tr><tr><td>University of California at Santa Cruz, Santa Cruz, California</td><td>1</td></tr><tr><td><b>Massachusetts Institute of Technology, Cambridge, MA 02139, USA</b></td><td>1</td></tr><tr><td><b>The Rowland Institute at Harvard, Harvard University, Cambridge, MA 02142, USA</b></td><td>1</td></tr><tr><td><b>School of Electrical and Electronic Engineering, The University of Manchester, Manchester, UK</b></td><td>1</td></tr><tr><td>Network Center, Huizhou University, Huizhou, China</td><td>1</td></tr><tr><td><b>School of Advanced Computing, Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>School of Software, Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td>Faculty of Engineering, Computer Engineering Department, Akdeniz University, Dumlupinar Bulvari, Turkey</td><td>1</td></tr><tr><td>IRCICA, Parc Scientifique de la Haute Borne, Lille 1 University, Villeneuve d’Ascq, France</td><td>1</td></tr><tr><td><b>University of Bath</b></td><td>1</td></tr><tr><td>Data and Analytics Department, KPMG AGWPG, Düsseldorf, Germany</td><td>1</td></tr><tr><td><b>Faculty of Mathematics and Statistics, Hubei University, Wuhan, China</b></td><td>1</td></tr><tr><td><b>West Virginia University, Morgantown, WV</b></td><td>1</td></tr><tr><td><b>Ajou Univ.</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Transient Optics and Photonics, Center for OPTical IMagery Analysis and Learning, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China</b></td><td>1</td></tr><tr><td><b>School of Information Technology, Halmstad University, Halmstad, Sweden</b></td><td>1</td></tr><tr><td><b>Nokia Bell-Labs, Madrid, Spain</b></td><td>1</td></tr><tr><td>Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China</td><td>1</td></tr><tr><td>JiangSu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise, Suzhou, China</td><td>1</td></tr><tr><td>Université de Lorraine, LORIA, UMR 7503</td><td>1</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh, Pittsburgh, USA</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, The City College of New York, New York, USA</td><td>1</td></tr><tr><td>Robótica y Manufactura Avanzada, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ramos Arizpe, Mexico</td><td>1</td></tr><tr><td><b>Technicolor, Paris, France</b></td><td>1</td></tr><tr><td><b>MPI Informatics, Germany</b></td><td>1</td></tr><tr><td>School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, India</td><td>1</td></tr><tr><td>Dept. de Ciência da Computacão, Universidade Federal de Ouro Preto, MG Brazil</td><td>1</td></tr><tr><td><b>Interactive and Digital Media Institute, National University of Singapore, Singapore</b></td><td>1</td></tr><tr><td><b>Alibaba Group, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK</b></td><td>1</td></tr><tr><td><b>Shin-Guang Elementary School, Yulin 646, Taiwan</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Brown University, Providence Rhode Island, 02912, USA</b></td><td>1</td></tr><tr><td><b>School of Management, New Jersey Institute of Technology, University Heights, Newark, New Jersey 07102, USA</b></td><td>1</td></tr><tr><td><b>SLAC National Laboratory, Stanford University, Stanford, USA</b></td><td>1</td></tr><tr><td><b>IWE II, RWTH Aachen University, Aachen, Germany</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore</b></td><td>1</td></tr><tr><td><b>School of Electrical Engineering, Nantong University, Nantong, China</b></td><td>1</td></tr><tr><td><b>Vesalis company, Clermont-Ferrand, France</b></td><td>1</td></tr><tr><td><b>University of Calgary, Calgary, T3G 2T6 AB, CANADA</b></td><td>1</td></tr><tr><td><b>University of Louisville, Louisville, KY 40292 USA</b></td><td>1</td></tr><tr><td><b>School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, USA</b></td><td>1</td></tr><tr><td><b>Max Planck Institute for Informatics, Saarbrucken, Germany</b></td><td>1</td></tr><tr><td><b>College of Information Engineering, Capital Normal University, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Automation, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, University of California, Riverside, Riverside CA, California 92521 United States</td><td>1</td></tr><tr><td><b>Art History, University of California, Riverside, Riverside, California United States</b></td><td>1</td></tr><tr><td><b>Electrical Engineering, University of California, Riverside, Riverside, California 92521 United States</b></td><td>1</td></tr><tr><td><b>University of Science & Technology (UST), Daejeon, Korea</b></td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Chongqing, China</b></td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Chongqing, Singapore</b></td><td>1</td></tr><tr><td><b>Universidade Estadual de Campinas, Cx.P. 6176 Campinas-SP, CEP 13084-971, Brazil</b></td><td>1</td></tr><tr><td>Department of CSE, Regional Campus of Anna University, Tirunelveli 627007, India</td><td>1</td></tr><tr><td><b>Embodied Emotion, Cognition and (Inter-)Action Lab, University of Hertfordshire, United Kingdom</b></td><td>1</td></tr><tr><td><b>Institute on Children Studies, University of Minho, Portugal</b></td><td>1</td></tr><tr><td><b>College of Aerospace and Material Engineering, National University of Defense Technology, Changsha, China</b></td><td>1</td></tr><tr><td><b>Air Force Research Lab, Rome, NY, 13441, USA</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>School of Computer Engineering, The Nanyang Technological University, Singapore</b></td><td>1</td></tr><tr><td><b>Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Fraunhoferstrasse 1, Karlsruhe, Germany</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Texas at San Antonio</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Rochester</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Tianjin University, China</b></td><td>1</td></tr><tr><td><b>Institute of Systems Science, National University of Singapore, Singapore, Singapore</b></td><td>1</td></tr><tr><td>Dalian Key Laboratory of Digital Technology for National Culture, Dalian Minzu University, Dalian, China</td><td>1</td></tr><tr><td><b>Institute of Systems Science, Northeastern University, Shenyang, China</b></td><td>1</td></tr><tr><td><b>Philips Research Eindhoven, HTC 34, Netherlands</b></td><td>1</td></tr><tr><td><b>Epson Research and Development Inc., San Jose, CA</b></td><td>1</td></tr><tr><td><b>GE Global Research, Bangalore, India</b></td><td>1</td></tr><tr><td><b>Advanced Media Lab. Samsung Advance Institute of Technology, Republic of Korea</b></td><td>1</td></tr><tr><td>Department of Business Planning & Information Systems, TEI of Crete, Agios Nikolaos, Greece</td><td>1</td></tr><tr><td><b>National Institute of Informatics, Japan</b></td><td>1</td></tr><tr><td>School of Information Technology Jawaharlal Nehru Technological University Hyderabad Andhra Pradesh, India</td><td>1</td></tr><tr><td><b>Department of CSE, Vignan University, Andhra Pradesh, India</b></td><td>1</td></tr><tr><td><b>University of North Carolina at Wilmington, USA</b></td><td>1</td></tr><tr><td><b>UNCW, USA</b></td><td>1</td></tr><tr><td><b>Department of EngineeringFaculty of Engineering and Science, University of Agder, Kristiansand, Norway</b></td><td>1</td></tr><tr><td><b>Yahoo Inc., New York, NY, USA</b></td><td>1</td></tr><tr><td>Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France</td><td>1</td></tr><tr><td><b>Queen Mary, University of London</b></td><td>1</td></tr><tr><td><b>Brunel University</b></td><td>1</td></tr><tr><td><b>Vision & Sensing Group, Faculty of Information Sciences and Engineering, University of Canberra, Australia</b></td><td>1</td></tr><tr><td><b>School of Engineering, CECS, Australian National University, Australia</b></td><td>1</td></tr><tr><td><b>Comput. Control Lab, Nanyang Technol. Univ., Singapore</b></td><td>1</td></tr><tr><td>School of Computer ScienceThe University of Adelaide</td><td>1</td></tr><tr><td><b>Instituto de Sistemas e Robótica, Instituto Superior Técnico, Lisboa, Portugal</b></td><td>1</td></tr><tr><td><b>University of Washington, Seattle, WA, USA</b></td><td>1</td></tr><tr><td>Shanghai Advanced Research Institute, CAS & Qiniu AI Lab, Shanghai, China</td><td>1</td></tr><tr><td>University of Lyon, LIRIS - CNRS, National Institute of Applied Sciences (INSA), Lyon, France</td><td>1</td></tr><tr><td><b>Shenzhen Graduate School, Harbin Institute of Technology, Bio-Computing Research Center, Shenzhen, China</b></td><td>1</td></tr><tr><td>Toyohashi University of Technology, Toyohashi, Japan</td><td>1</td></tr><tr><td><b>Department of Computing, Biometrics Research Centre, The Hong Kong Polytechnic University, Hong Kong</b></td><td>1</td></tr><tr><td><b>School of Computer Science, Nanjing University of Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td>Department of Informatics, King’s College London, Strand, London, UK</td><td>1</td></tr><tr><td><b>Centre for Quantum Computation & Intelligent Systems, University of Technology, Sydney, Australia</b></td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China</td><td>1</td></tr><tr><td><b>CSIE, National Cheng Kung University, Tainan, 701 Taiwan</b></td><td>1</td></tr><tr><td><b>CSIE, National Taiwan University of Science and Technology, Taipei, 106 Taiwan</b></td><td>1</td></tr><tr><td><b>Computer Science and Engineering Department, University of Texas at Arlington, Arlington, TX, USA</b></td><td>1</td></tr><tr><td><b>INSA CVL, Univ. Orléans, PRISME EA 4229, Bourges, France</b></td><td>1</td></tr><tr><td><b>LITIS, Universite de Rouen - INSA de Rouen, Rouen, FR</b></td><td>1</td></tr><tr><td>Department of Learning and Digital Technology, Fo Guang University, Yilan, Taiwan</td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong</b></td><td>1</td></tr><tr><td><b>Noah’s Ark Laboratory, Hong Kong</b></td><td>1</td></tr><tr><td><b>Noah.s Ark Laboratory and Hong Kong University of Science and Technology, Hong Kong</b></td><td>1</td></tr><tr><td><b>La Trobe University, Melbourne, Australia</b></td><td>1</td></tr><tr><td>BITS Pilani, India , India</td><td>1</td></tr><tr><td>College of Computer and Information Sciences, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia</td><td>1</td></tr><tr><td><b>COMSATS, Institute of Information Technology, Sahiwal, Pakistan</b></td><td>1</td></tr><tr><td>National University of Computer and Emerging Sciences, Islamabad, Islamabad, Pakistan</td><td>1</td></tr><tr><td><b>Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada</b></td><td>1</td></tr><tr><td>Research Team on Audio Visual Signal Processing (AVSP), Vrije Universiteit Brussel (VUB), Electronics and Informatics Department, VUB-ETRO, Pleinlaan 2, 1050 Brussel, Belgium</td><td>1</td></tr><tr><td><b>School of Engineering and Information Technology, Deakin University, Geelong, Australia</b></td><td>1</td></tr><tr><td><b>Griffith University, Queensland, Australia</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Texas at San Antonio, San Antonio, United States</b></td><td>1</td></tr><tr><td><b>Chongqing Institute of Green and Intelligent Technology, Chinese Academy of China, Hefei University of Technology, Hefei, China</b></td><td>1</td></tr><tr><td><b>Fac. of Mathematics and Computer Sciences, University of Science, Ho Chi Minh City, Viet Nam</b></td><td>1</td></tr><tr><td><b>Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td><b>LAMIA, University of French West Indies and Guiana, EA 4540, Pointe-à-Pitre, France</b></td><td>1</td></tr><tr><td><b>Institute of Intelligent Systems and Robotics (ISIR), Pierre and Marie Curie University, Paris, France</b></td><td>1</td></tr><tr><td><b>Xiamen University of Technology, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Chulalongkorn University Bangkok, Thailand</b></td><td>1</td></tr><tr><td>College of Computer Science and Technology of Huaqiao University Xiamen, Xiamen, China</td><td>1</td></tr><tr><td><b>School of Automation, Huazhong University of Science and Technology, Wuhan, China</b></td><td>1</td></tr><tr><td>Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Taiwan 640, R.O.C.</td><td>1</td></tr><tr><td><b>Bordeaux INP, LaBRI, PICTURA, UMR 5800, F-33400 Talence, France</b></td><td>1</td></tr><tr><td>Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng 475004, China</td><td>1</td></tr><tr><td><b>Department of Systems and Control Engineering, University of Malta, Msida, Malta</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Information Management, College of Management, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Computer Science and Information Engineering, College of Electrical Engineering and Computer Science, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td><b>Fundamental and Applied Science Department, Universiti Teknologi PETRONAS, Seri Iskandar, 32610, Perak Malaysia</b></td><td>1</td></tr><tr><td>Department of Statistics, University of California at Berkeley, Berkeley, USA</td><td>1</td></tr><tr><td>International Computer Science Institute, University of California at Berkeley, Berkeley, USA</td><td>1</td></tr><tr><td><b>Computer Science Department, Rensselaer Polytechnic Institute, Troy, USA</b></td><td>1</td></tr><tr><td>College of Information Science and Technology, Agricultural University of Hebei, Baoding, China</td><td>1</td></tr><tr><td><b>Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Sch. of Electr. Eng. & Comput. Sci., Newcastle Univ., NSW, Australia</b></td><td>1</td></tr><tr><td><b>University of Sassari, Computer Vision Laboratory, PolComing Viale Mancini, 5 07100 Sassari, Italy</b></td><td>1</td></tr><tr><td><b>Centre for Intelligent Machines, McGill University, Montréal, Canada</b></td><td>1</td></tr><tr><td><b>Azure Storage, Microsoft, Seattle, WA, USA</b></td><td>1</td></tr><tr><td>Department of Electronics Engineering, Mokpo National University, Republic of Korea</td><td>1</td></tr><tr><td><b>School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Republic of Korea</b></td><td>1</td></tr><tr><td><b>Institute of Computer Science and Technology, Peking university, Beijing, China</b></td><td>1</td></tr><tr><td>FX Palo Alto Laboratory</td><td>1</td></tr><tr><td>Department of Applied Optics and Photonics, University of Calcutta, Kolkata, India</td><td>1</td></tr><tr><td>Department of Electrical Engineering, Future Institute of Engineering and Management, Kolkata, India</td><td>1</td></tr><tr><td><b>School of Electronics and Information, Northwestern Polytechnical University, Xian, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of North Carolina, Charlotte, USA</b></td><td>1</td></tr><tr><td><b>Graduate Program on Electrical Engineering, Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil</b></td><td>1</td></tr><tr><td><b>Graduate Program on Electrical Engineering, University of Passo Fundo, Passo Fundo, Brazil</b></td><td>1</td></tr><tr><td><b>Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil</b></td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur, India</td><td>1</td></tr><tr><td><b>Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>1</td></tr><tr><td><b>Northwestern Polytechnical University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>Osaka University, Japan</b></td><td>1</td></tr><tr><td>Telecom Division, Centre de Développement des Technologies Avancées, Algiers, Algeria</td><td>1</td></tr><tr><td><b>Delft University of Technology, EEMCS, Delft, The Netherlands, reinierz@gmail.com</b></td><td>1</td></tr><tr><td><b>Imperial College London, Computing Department, London, U.K., m.pantic@imperial.ac.uk</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai, China</b></td><td>1</td></tr><tr><td>Departments of Medical Imaging and Medical Biophysics, University of Western Ontario, London, ON, Canada</td><td>1</td></tr><tr><td><b>St. Joseph’s Health Care, London, ON, Canada</b></td><td>1</td></tr><tr><td><b>Northumbria University, Newcastle upon Tyne, U.K.</b></td><td>1</td></tr><tr><td>Department of Medical Biophysics, University of Western Ontario, London, ON, Canada</td><td>1</td></tr><tr><td><b>School of Computer Science, University of Nottingham, Nottingham, UK</b></td><td>1</td></tr><tr><td><b>School of Electrical Engineering, Kookmin University, Seoul, Korea</b></td><td>1</td></tr><tr><td><b>University of Science and Technology of China, Hefei, P.R. China</b></td><td>1</td></tr><tr><td><b>The School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China</b></td><td>1</td></tr><tr><td>School of Computer Science, Shaanxi Normal University, Xi’an, China</td><td>1</td></tr><tr><td>Engineering Laboratory of Teaching Information Technology of Shaanxi Province, Xi’an, China</td><td>1</td></tr><tr><td>Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi’an, China</td><td>1</td></tr><tr><td><b>College of Automation, Shenyang Aerospace University, China</b></td><td>1</td></tr><tr><td><b>Université de Lyon, CNRS, Ecole Centrale de Lyon, LIRIS UMR5205, F-69134, France</b></td><td>1</td></tr><tr><td>College of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, P.R. China</td><td>1</td></tr><tr><td><b>Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China</b></td><td>1</td></tr><tr><td><b>Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur, Malaysia</b></td><td>1</td></tr><tr><td>Nanyang Technological University School of Computer Engineering</td><td>1</td></tr><tr><td><b>College of Engineering, Shibaura Institute of Technology, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>Graduate School of Engineering, Shibaura Institute of Technology, Tokyo, Japan</b></td><td>1</td></tr><tr><td>Department of Electronics and Electrical Engineering, Indian Institute of Technology (IIT) Guwahati, Guwahati, India</td><td>1</td></tr><tr><td>Technology Section, Israel National Police, Jerusalem, Israel</td><td>1</td></tr><tr><td>Department of Electro-Optics Engineering, Ben-Gurion University, Beer Sheva, Israel</td><td>1</td></tr><tr><td>Department of Mathematics, JiaYing University, Meizhou, China</td><td>1</td></tr><tr><td>Hebei University of Technology, School of Science, Tianjin, P. R. China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, College of Engineering, and College of Computer and Information Science (Affiliated), Northeastern University, MA, USA</b></td><td>1</td></tr><tr><td><b>Chongqing University, Chongqing, China</b></td><td>1</td></tr><tr><td><b>Semnan University, Semnan, Iran</b></td><td>1</td></tr><tr><td>YiLi Normal College, Yining, China</td><td>1</td></tr><tr><td><b>Curtin University, Perth WA, Australia</b></td><td>1</td></tr><tr><td>Faculty of Electronic Information and Electrical Engineering, Dalian University, Dalian, China</td><td>1</td></tr><tr><td><b>Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan</b></td><td>1</td></tr><tr><td>Centre for Innovation in IT Services and Applications (iNEXT), University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td>Video Surveillance Laboratory, Guizhou University for Nationalities, Guiyang, China</td><td>1</td></tr><tr><td><b>Institut Mines-Telecom, Telecom ParisTech, CNRS LTCI, Sophia Antipolis, France</b></td><td>1</td></tr><tr><td>College of Arts and Sciences, Shanxi Agricultural University, Shanxi, China</td><td>1</td></tr><tr><td><b>Centre for Intelligent Systems Research, Deakin University, Geelong, VIC, Australia</b></td><td>1</td></tr><tr><td><b>Faculty of Engineering, Technology, and Built Environment, UCSI University, Kuala Lumpur, Malaysia</b></td><td>1</td></tr><tr><td><b>Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, PR China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Cornell University and Cornell NYC Tech</b></td><td>1</td></tr><tr><td><b>Dept of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark , NJ, USA</b></td><td>1</td></tr><tr><td><b>Microsoft Research , Redmond, WA, USA</b></td><td>1</td></tr><tr><td><b>Microsoft Visual Perception Laboratory, Zhejiang University, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>Coll. of Electron. & Inf., Northwestern Polytech. Univ., Xi'an, China</b></td><td>1</td></tr><tr><td><b>Nanyang Technological University and the Institute for Infocomm Research, Singapore</b></td><td>1</td></tr><tr><td><b>Intelligent Systems Laboratory, University of Bristol, Merchant Venturers Building, Woodland Rd, Bristol BS8 1UB, UK</b></td><td>1</td></tr><tr><td>IRDA Group, ADMIR Laboratory, Rabat IT Center, ENSIAS, CNRST (URAC29), Mohammed V University of Rabat, Morocco</td><td>1</td></tr><tr><td>LRIT, CNRST (URAC29), Mohammed V University of Rabat, Morocco</td><td>1</td></tr><tr><td><b>Ajou University</b></td><td>1</td></tr><tr><td>Queen’s University, Kingston, Canada</td><td>1</td></tr><tr><td>University of Science Technology, Wuhan, China</td><td>1</td></tr><tr><td>Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia</td><td>1</td></tr><tr><td>University at Qatar, Doha, Qatar</td><td>1</td></tr><tr><td>University of Istanbul, Istanbul, Turkey</td><td>1</td></tr><tr><td><b>Institute for Information and System Sciences and Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an 710049, PR China</b></td><td>1</td></tr><tr><td><b>Faculty of Applied Mathematics, Guangdong University of Technology, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Faculty of Information Science and Technology, Sun Yat-Sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Tuen Mun, Hong Kong</td><td>1</td></tr><tr><td>PolyU Shenzhen Research Institute, Shenzhen, China</td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Loughborogh</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering and Electronics, University of Liverpool</b></td><td>1</td></tr><tr><td><b>University of Bristol, Bristol, United Kingdom</b></td><td>1</td></tr><tr><td>German National Library of Science and Technology & Leibniz Universität Hannover, Hannover, Germany</td><td>1</td></tr><tr><td>University of Applied Sciences Jena, Jena, Germany</td><td>1</td></tr><tr><td>Department of Creative IT Engineering, POSTECH, Pohang, South Korea, 37673</td><td>1</td></tr><tr><td><b>Viterbi School of Engineering, University of Southern California, Los Angeles, CA</b></td><td>1</td></tr><tr><td><b>Centre for Multimedia Signal Processing and Department of Computing, Hong Kong Polytechnic University, Flat PQ717, Kowloon, Hung Hom, Hong Kong</b></td><td>1</td></tr><tr><td>Department of Computer Science, University of Western Ontario, London, Canada</td><td>1</td></tr><tr><td><b>University of Pittsburgh, USA</b></td><td>1</td></tr><tr><td><b>Anhui University, HeFei, China and Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td><b>Rensselaer Polytechnic Institute, Troy, NY, USA</b></td><td>1</td></tr><tr><td>Vision Laboratory, LARSyS, University of the Algarve, Faro, Portugal</td><td>1</td></tr><tr><td><b>Donghua University, China</b></td><td>1</td></tr><tr><td>Department of Information Management, Yuan Ze University, Taoyuan, China</td><td>1</td></tr><tr><td><b>AI Speech Ltd., Suzhou, China</b></td><td>1</td></tr><tr><td><b>Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China</b></td><td>1</td></tr><tr><td>DICGIM, Universitá degli Studi di Palermo, V.le delle Scienze, Ed. 6, 90128 Palermo, Italy</td><td>1</td></tr><tr><td>Department of Computer Engineering, Karadeniz Technical University, Trabzon, Turkey</td><td>1</td></tr><tr><td>Department of Computer Technologies, Trabzon Vocational School, Karadeniz Technical University, Trabzon, Turkey</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, Kyung Hee University, Yongin, South Korea</b></td><td>1</td></tr><tr><td>Stanford University and Coursera</td><td>1</td></tr><tr><td>Dept. of Comput. Sci. & Info. Eng., National Yunlin Univ. of Science & Technology, Taiwan</td><td>1</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, İstanbul Üniversitesi, Turkey</b></td><td>1</td></tr><tr><td><b>Bilgisayar Mühendisliği Bölümü, Bahçeşehir Üniversitesi, İstanbul, Turkey</b></td><td>1</td></tr><tr><td><b>Institute of Industrial Science, The University of Tokyo, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td>Faculty of Mathematics and Statistics, Hubei Key Laboratory of Applied Mathematics, Hubei University, Wuhan, China</td><td>1</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom. k.messer@surrey.ac.uk</b></td><td>1</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom. j.kittler@surrey.ac.uk</b></td><td>1</td></tr><tr><td><b>Centre for Vision, Speech and Signal Processing, University of Surrey, United Kingdom. x.zou@surrey.ac.uk</b></td><td>1</td></tr><tr><td><b>University of Twente, Human Media Interaction Group, Enschede, The Netherlands</b></td><td>1</td></tr><tr><td>Biometric and Imaging Processing Laboratory (BIPLab)</td><td>1</td></tr><tr><td><b>University of Naples Federico II</b></td><td>1</td></tr><tr><td><b>Warsaw University of Technology</b></td><td>1</td></tr><tr><td>Research and Academic Computer Network (NASK)</td><td>1</td></tr><tr><td><b>SensoMotoric Instruments (SMI)</b></td><td>1</td></tr><tr><td><b>Maastricht University</b></td><td>1</td></tr><tr><td><b>Università di Salerno Italy</b></td><td>1</td></tr><tr><td><b>University of Southampton</b></td><td>1</td></tr><tr><td><b>University of Beira Interior, IT: Instituto de Telecomunicações</b></td><td>1</td></tr><tr><td>Philips Applied Technologies, Eindhoven, Netherlands</td><td>1</td></tr><tr><td><b>Delft University of Technology, Delft, Netherlands</b></td><td>1</td></tr><tr><td>Philips Research Eindhoven, Eindhoven, Netherlands</td><td>1</td></tr><tr><td>Key Lab Complex System & Intelligence Science, Institute of Automation, Chinese Academy of Science, Beijing, China</td><td>1</td></tr><tr><td>College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China</td><td>1</td></tr><tr><td><b>State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China</b></td><td>1</td></tr><tr><td><b>SAP Innovation Center Networks, Singapore</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td>National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis, Nizhny Novgorod, Russia</td><td>1</td></tr><tr><td><b>Bioinformatics Institute, A∗STAR, Singapore</b></td><td>1</td></tr><tr><td>Emory University School of Medicine, Atlanta, USA</td><td>1</td></tr><tr><td><b>School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA</b></td><td>1</td></tr><tr><td>Department of Radiology and Imaging Sciences, Winship Cancer Institute, Emory University School of Medicine, Atlanta, USA</td><td>1</td></tr><tr><td><b>iCV Research Group, Institute of Technology, University of Tartu, 50411, Estonia</b></td><td>1</td></tr><tr><td><b>Dept. Mathematics and Informatics, University of Barcelona, Computer Vision Center, Spain</b></td><td>1</td></tr><tr><td><b>Institute of Technology, University of Tartu, 50411, Estonia</b></td><td>1</td></tr><tr><td><b>Amazon.com Cambridge, MA, USA</b></td><td>1</td></tr><tr><td>Dept. of EMPH, Icahn School of Medicine at Mount Sinai, New York, NY 10029</td><td>1</td></tr><tr><td><b>Dept. of ENME College Park, University of Maryland, College Park, MD, 20742</b></td><td>1</td></tr><tr><td><b>Eskişehir Osmangazi Üniversitesi, Bilgisayar Mühendisliği Bölümü, Eskişehir, Türkiye</b></td><td>1</td></tr><tr><td><b>Anadolu Üniversitesi, Elek., Elektronik Mühendisliği Bölümü, Eskişehir, Türkiye</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Texas at San Antonio, San Antonio, TX</b></td><td>1</td></tr><tr><td>Electrical-Electronics Engineering Department, Izmir University of Economics, Balcova, Turkey</td><td>1</td></tr><tr><td><b>Electrical-Electronics Engineering Department, Firat University, Elazig, Turkey</b></td><td>1</td></tr><tr><td><b>Mechatronics Engineering Department, Firat University, Elazig, Turkey</b></td><td>1</td></tr><tr><td>Department of Computer Science, Solapur University, Solapur, India</td><td>1</td></tr><tr><td><b>Vision Semantics Ltd, UK</b></td><td>1</td></tr><tr><td><b>Rutgers University, USA</b></td><td>1</td></tr><tr><td><b>Computer Science, SUNY Stony Brook, Stony Brook, United States</b></td><td>1</td></tr><tr><td>Computer Vision Research Group, School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia</td><td>1</td></tr><tr><td><b>Department of Mathematics, Colorado State University, Fort Collins, CO 80523-1874 U.S.A. peterson@math.colostate.edu</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, Colorado State University, Fort Collins, CO 80523-1874 U.S.A. kirby@math.colostate.edu</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, Colorado State University, Fort Collins, CO 80523-1874 U.S.A. chang@math.colostate.edu</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Faculty of Engineering, Urmia university, Urmia, Iran</b></td><td>1</td></tr><tr><td>Department of Information Technology, Netaji Subhas Engineering College, Kolkata, India</td><td>1</td></tr><tr><td>Computer Engineering College, Jimei University, Xiamen, China</td><td>1</td></tr><tr><td>Fujian Key Laboratory of the Brain-like Intelligent Systems, Xiamen, China</td><td>1</td></tr><tr><td>School of Information, Hunan University of Humanities, Science and Technology, Loudi, China</td><td>1</td></tr><tr><td><b>Cognitive Science Department, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td>Al Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia</td><td>1</td></tr><tr><td>School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Korea</td><td>1</td></tr><tr><td><b>Department of Computer Science, COMSATS, Institute of Information Technology, Sahiwal, Pakistan</b></td><td>1</td></tr><tr><td><b>The University of Electro-Communications, Japan</b></td><td>1</td></tr><tr><td><b>Institute for Infocomm Research, A-star, Singapore</b></td><td>1</td></tr><tr><td><b>Inst. Dalle Molle d'Intelligence Artificielle Perceptive, Martigny, Switzerland</b></td><td>1</td></tr><tr><td><b>Transmural Biotech, Barcelona, Spain</b></td><td>1</td></tr><tr><td><b>George Mason University, Fairfax, VA 22030</b></td><td>1</td></tr><tr><td>Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea</td><td>1</td></tr><tr><td><b>Computational Biomedicine Lab, University of Houston, 4800 Calhoun Rd., Houston, TX 77204, USA</b></td><td>1</td></tr><tr><td><b>Purdue University, West Lafayette, IN, USA</b></td><td>1</td></tr><tr><td><b>Moshanghua Tech Company, Ltd., Beijing, China</b></td><td>1</td></tr><tr><td><b>College of Information Engineering, Xiangtan University, Xiangtan, China</b></td><td>1</td></tr><tr><td><b>CARTIF Centro Tecnológico, Robotics and Computer Vision Division, Boecillo (Valladolid, Spain)</b></td><td>1</td></tr><tr><td><b>University of California, San Diego</b></td><td>1</td></tr><tr><td><b>School of Software Engineering, South China University of Technology, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>School of Computer Science, South China Normal University, Guangzhou, China</b></td><td>1</td></tr><tr><td>Dept. of Computer Science and Information Engineering, Providence University, Taichung, Taiwan</td><td>1</td></tr><tr><td>360 AI Institute, Beijing, China</td><td>1</td></tr><tr><td><b>Tencent YouTu Lab, Tencent Shanghai, China</b></td><td>1</td></tr><tr><td><b>Sun Yat-sen University, China</b></td><td>1</td></tr><tr><td><b>Centeye, Inc.</b></td><td>1</td></tr><tr><td><b>Center for Optical Imagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China</b></td><td>1</td></tr><tr><td><b>Institute of Information and Control, Hangzhou Dianzi University, China</b></td><td>1</td></tr><tr><td><b>Hong Kong Baptist University and BNU-HKBU United International College</b></td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Research Lab, Vrije Universitiet Brussel (VUB), Department of Electronics & Informatics (ETRO) Pleinlaan 2, 1050 Brussel, Belgium</td><td>1</td></tr><tr><td><b>Department of Computer Science, School of Information Science and Engineering, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>School of Communication and Information Engineering, Shanghai University</b></td><td>1</td></tr><tr><td>IRISA, University of Rennes 1</td><td>1</td></tr><tr><td><b>INRIA Rennes-Bretagne-Atlantique</b></td><td>1</td></tr><tr><td><b>Advanced Digital Sciences Center, University of Illinois at Urbana-Champaign, Singapore</b></td><td>1</td></tr><tr><td><b>International Institute of Information Technology, Hyderabad, Telangana, India</b></td><td>1</td></tr><tr><td><b>Shenzhen Graduate School, Harbin Institute of Technology, 518055, China</b></td><td>1</td></tr><tr><td>Research Institution of Intelligent Control and Testing, Graduate School of Tsinghua University at Shenzhen, 518055, China</td><td>1</td></tr><tr><td>Commonwealth Scientific and Industrial Research Organization (CSIRO)</td><td>1</td></tr><tr><td><b>University of Canberra, Austrlia</b></td><td>1</td></tr><tr><td><b>B-DAT Lab, School of Information and Control, Nanjing University of Information Science and Technology, No. 219, Ningliu Road, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Rutgers University, 110 Frelinghuysen Road, Piscataway</b></td><td>1</td></tr><tr><td><b>Ocean University of China, Teaching Center of Fundamental Courses, Qingdao, China</b></td><td>1</td></tr><tr><td>Indiana University-Bloomington, USA</td><td>1</td></tr><tr><td>Key Laboratory of Medical Image Computing (Northeastern University), Ministry of Education, Shenyang, China</td><td>1</td></tr><tr><td><b>School of Information Science and Engineering, Northeastern University, Shenyang, China</b></td><td>1</td></tr><tr><td>Clínica Otocenter, Teresina, Piauí, Brasil</td><td>1</td></tr><tr><td>Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing, China</td><td>1</td></tr><tr><td>Nanjing University of Posts and Telecommunications, Nanjing, China</td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The State University of New York at Buffalo, New York, USA</b></td><td>1</td></tr><tr><td><b>Elektrik-Elektronik Mühendisliği Bölümü, Trakya Üniversitesi, Edirne, Türkiye</b></td><td>1</td></tr><tr><td>Grupo de Aplicacion de Telecomunicaciones Visuales, Universidad Politecnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain</td><td>1</td></tr><tr><td>Department of Management Information Systems, Universität Regensburg, Universitätsstr. 31, 93053 Regensburg, Germany</td><td>1</td></tr><tr><td><b>Amrita E-Learning Research Laboratory, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, India</b></td><td>1</td></tr><tr><td>Department of Computer Science, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India</td><td>1</td></tr><tr><td>Amrita E-Learning Research Laboratory and the Department of Computer Science, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India</td><td>1</td></tr><tr><td><b>IKERBASQUE, Basque Foundation for Science, and the University of the Basque Country, San Sebastian, Spain</b></td><td>1</td></tr><tr><td><b>Computer Vision Center, Edifici “O” - Campus UAB, 08193 Bellaterra (Barcelona), Spain</b></td><td>1</td></tr><tr><td><b>Amazon Research, Berlin, Germany</b></td><td>1</td></tr><tr><td><b>DISI-Alma Mater Studiorum, Università di Bologna, Bologna, Italy</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China</b></td><td>1</td></tr><tr><td>Department of ECE, PEC University of Technology, Chandigarh, India</td><td>1</td></tr><tr><td>Biomedical Instrumentation (V-02), CSIR-Central Scientific Instruments Organisation (CSIO)|, Chandigarh, India</td><td>1</td></tr><tr><td>CEERI, Pilani, India</td><td>1</td></tr><tr><td>MNIT, Jaipur, India</td><td>1</td></tr><tr><td><b>Samsung Advanced Institute of Technology, Samsung Electronics, Gyeonggi-do, Korea</b></td><td>1</td></tr><tr><td><b>Department of Information Engineering, University of Florence, Firenze, Italy</b></td><td>1</td></tr><tr><td><b>Carnegie Mellon University, Pittsburgh, USA</b></td><td>1</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td>Department of Arts and Humanities, College of Business, Arts and Social Sciences, Brunel University London, Uxbridge, UK</td><td>1</td></tr><tr><td><b>Product/Industrial Design, Northumbria School of Design, Northumbria University, Newcastle upon Tyne, UK</b></td><td>1</td></tr><tr><td>Department of Design, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, India</td><td>1</td></tr><tr><td><b>The Organization of Advanced Science and Technology, Kobe University, Kobe, Japan</b></td><td>1</td></tr><tr><td><b>RIEB, Kobe University, Kobe, Japan</b></td><td>1</td></tr><tr><td>NTT Service Evolution Laboratories, Kanagawa, Japan</td><td>1</td></tr><tr><td><b>Tsinghua National Lab for Information Science and Technology, Beijing, China</b></td><td>1</td></tr><tr><td><b>Universidad Argentina de la Empresa (UADE), Lima 717, Buenos Aires, Argentina</b></td><td>1</td></tr><tr><td><b>Columbia University, NEW YORK, NY, USA</b></td><td>1</td></tr><tr><td>Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia</td><td>1</td></tr><tr><td><b>US Army Research Laboratory, 2800 Powder Mill Rd, Adelphi, MD 20783, USA</b></td><td>1</td></tr><tr><td>Dept. of Comput. Sci., North Carolina Univ., Wilmington, NC, USA</td><td>1</td></tr><tr><td><b>Institute of Applied Mathematics, AMSS, Chinese Academy of Sciences, Beijing 100190</b></td><td>1</td></tr><tr><td><b>Research Center of Precision Sensing and Control, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190</b></td><td>1</td></tr><tr><td><b>Biometrics Engineering Research Center, Yonsei University, Seoul, Korea</b></td><td>1</td></tr><tr><td>University of Washington &Microsoft, Seattle, WA, USA</td><td>1</td></tr><tr><td><b>Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK</b></td><td>1</td></tr><tr><td>Departamento de Informtica e Matemtica Aplicada/University of Rio Grande do Norte, Natal, Brazil</td><td>1</td></tr><tr><td>Computer Engineering Department, Girne American University, Kyrenia, Cyprus 90</td><td>1</td></tr><tr><td><b>School of Engineering and Digital Arts, University of Kent, Canterbury, U.K.</b></td><td>1</td></tr><tr><td><b>Cornell University, New York, NY, USA</b></td><td>1</td></tr><tr><td>Cornell University & Facebook Inc., New York, NY, USA</td><td>1</td></tr><tr><td><b>Office of Naval Research, Arlington</b></td><td>1</td></tr><tr><td>School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, China</td><td>1</td></tr><tr><td>Fujian Provincial Key Laboratory of Information Processing and Intelligent Control, Fuzhou, China</td><td>1</td></tr><tr><td>School of Technology, Nanjing Audit University, Nanjing, China</td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Microsoft Research, Redmond, WA</b></td><td>1</td></tr><tr><td>Adobe Research Department, Adobe Systems Inc, San Jose, CA</td><td>1</td></tr><tr><td><b>Department of Computer Science, National Chung Cheng University, Chiayi, Taiwan</b></td><td>1</td></tr><tr><td><b>School of Information and Control Engineering, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Microsoft, Redmond, WA</b></td><td>1</td></tr><tr><td><b>BIWI, ETH Zurich Zurich, Switzerland</b></td><td>1</td></tr><tr><td><b>Video Analytics Lab, SERC, Indian Institute of Science, Bangalore, India</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, National Chung Hsing University, Taiwan</b></td><td>1</td></tr><tr><td>Integrated Circuits and Electronics Laboratory, Department of Engineering, Aarhus University, Denmark</td><td>1</td></tr><tr><td>Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology (ICT), CAS, Beijing, China</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., California Inst. of Technol., Pasadena, CA, USA</td><td>1</td></tr><tr><td>Utechzone Co. Ltd., New Taipei City, Taiwan 235</td><td>1</td></tr><tr><td>Department of Cognitive Science, University of California, San Diego, CA, USA</td><td>1</td></tr><tr><td><b>Department of Communication Engineering, Shanghai University, Shanghai, China</b></td><td>1</td></tr><tr><td>Department of Electronic Engineering Shanghai Jiao Tong University</td><td>1</td></tr><tr><td><b>Institute of Communication Engineering, National Tsing-Hua University, Taiwan</b></td><td>1</td></tr><tr><td>Innovations Kontakt Stelle (IKS) Hamburg, Hamburg University of Applied Sciences</td><td>1</td></tr><tr><td>School of Engineering and Computing, University of the West of Scotland</td><td>1</td></tr><tr><td>Computer Science Department, Central Washington University (CWU)</td><td>1</td></tr><tr><td>ICT Center, CSIRO</td><td>1</td></tr><tr><td><b>CSE Department, Regional Campus, Anna University, Tirunelveli, India</b></td><td>1</td></tr><tr><td>Technische Universität München, München, Germany</td><td>1</td></tr><tr><td><b>National defense acquisition and system engineering management, National University of Defense Technology, Changsha, Hunan, P.R. China</b></td><td>1</td></tr><tr><td>Electrical Engineering and Computer Science, School of Engineering, University of California at Merced, Merced, USA</td><td>1</td></tr><tr><td><b>Bilişim Teknolojileri Enstitüsü, Tübitak BİLGEM, Kocaeli, Türkiye</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Software Engineering, University of Western Australia, Crawley, Australia</b></td><td>1</td></tr><tr><td><b>College of Engineering & Computer Science, Australian National University, Canberra, Australia</b></td><td>1</td></tr><tr><td>Data61, Commonwealth Scientific and Industrial Research Organization (CSIRO), Canberra, Australia</td><td>1</td></tr><tr><td><b>Human-Centered Technology Research Centre, University of Canberra, Bruce, Australia</b></td><td>1</td></tr><tr><td><b>Karlsruhe Institute of Technology (KIT), Germany</b></td><td>1</td></tr><tr><td><b>Istanbul Technical University (ITU), Turkey</b></td><td>1</td></tr><tr><td><b>École Polytechnique Fédérale de Lausanne (EPFL), Switzerland</b></td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Faculty of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Bangladesh</td><td>1</td></tr><tr><td>Pennsylvania State University, University Park, PA</td><td>1</td></tr><tr><td>University of Sao Paulo</td><td>1</td></tr><tr><td><b>University of Southern California, Southern California, USA</b></td><td>1</td></tr><tr><td>School of Software, Henan University, Kaifeng, China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Texas A&M University, College Station, USA</b></td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, China</td><td>1</td></tr><tr><td><b>Space Application Laboratory, Research Center for Advanced Science and Technology, University of Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>Department of Aeronautics and Astronautics Engineering, Graduate School of Engineering, University of Tokyo, Japan</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, Computer Vision Laboratory, Linköping University, Linköping, Sweden</td><td>1</td></tr><tr><td>Computer Vision Research Laboratory, Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran</td><td>1</td></tr><tr><td>Treelogic, Technological Scientific Park of Asturias, Llanera, Spain</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Oviedo, Gijón, Spain</td><td>1</td></tr><tr><td>Fundación CTIC (Technological Center), Technological Scientific Park of Gijón, Gijón, Spain</td><td>1</td></tr><tr><td><b>University of Central Florida 4000 Central Florida Blvd., Orlando, 328816, USA</b></td><td>1</td></tr><tr><td><b>Carnegie Mellon University 5000 Forbes Ave Pittsburgh, PA 15213, USA</b></td><td>1</td></tr><tr><td><b>School of Tai-an, Shandong University of Science and Technology, Tai-an, China</b></td><td>1</td></tr><tr><td><b>Integrated Management Coastal Research Institute, Universitat Politècnica de València, València, Spain</b></td><td>1</td></tr><tr><td>Department of Computer Science, Madrid Open University, Madrid, Spain</td><td>1</td></tr><tr><td>Department of Research and Diagnostic Methods, Faculty of Education, Pontificia University of Salamanca, Salamanca, Spain</td><td>1</td></tr><tr><td><b>The University of Tokushima, Japan</b></td><td>1</td></tr><tr><td><b>Department of Signal Processing, Tampere University of Technology, FIN-Tampere, 33720, Finland</b></td><td>1</td></tr><tr><td><b>Computer Science Department, University of Maryland, College Park, MD</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Memorial University of Newfoundland, Saint John's, NL, Canada</b></td><td>1</td></tr><tr><td><b>Computer Science Department, Tel-Aviv University, Ramat Aviv, Tel-Aviv, Israel</b></td><td>1</td></tr><tr><td><b>Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>U.S. Army Res. Lab., Adelphi, MD, USA</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Assiut University, Asyut, Egypt</b></td><td>1</td></tr><tr><td>Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan</td><td>1</td></tr><tr><td>Dept. of Information Engineering, Faculty of Engineering, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan</td><td>1</td></tr><tr><td>Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan, +81 25 262 7499</td><td>1</td></tr><tr><td><b>Visual Computation, Queen Mary University, London, United Kingdom</b></td><td>1</td></tr><tr><td><b>University of British Columbia, Canada</b></td><td>1</td></tr><tr><td>NTNU, Norway</td><td>1</td></tr><tr><td>Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland</td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Yeungnam University, Korea</b></td><td>1</td></tr><tr><td><b>Graduate School at Shenzhen, Tsinghua University, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Cornell University, Ithaca, NY, USA</b></td><td>1</td></tr><tr><td>Polish-Japanese Institute of Information Technology, Warszawa, Poland</td><td>1</td></tr><tr><td>Faculty of Applied Informatics and Mathematics, Department of Informatics, Warsaw University of Life Sciences (SGGW), Warsaw, Poland</td><td>1</td></tr><tr><td><b>AGH University of Science and Technology, Kraków, Poland</b></td><td>1</td></tr><tr><td>Polish-Japanese Institute of Information Technology, Warsaw, Poland</td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, Tongji University, Shanghai, China</b></td><td>1</td></tr><tr><td>FernUniversität , Hagen, Germany</td><td>1</td></tr><tr><td>Universidad Tecnica Federico Santa Maria , Valparaiso, Chile</td><td>1</td></tr><tr><td>Staffordshire University , Staffordshire, United Kingdom</td><td>1</td></tr><tr><td><b>The University of North Carolina at Charlotte, Charlotte, USA</b></td><td>1</td></tr><tr><td><b>Walt Disney Imagineering, USA</b></td><td>1</td></tr><tr><td><b>AEBC, Nanyang Environment & Water Research Institute, Nanyang Technological University, Singapore</b></td><td>1</td></tr><tr><td>Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, Kuching, Malaysia</td><td>1</td></tr><tr><td><b>Australian Centre for Visual Technologies, University of Adelaide, Adelaide, Australia</b></td><td>1</td></tr><tr><td><b>Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, P. R. China</b></td><td>1</td></tr><tr><td>University of Massachusetts at Amherst, Amherst, MA, USA</td><td>1</td></tr><tr><td><b>School of Computer Science, The University of Adelaide, Adelaide, SA, Australia</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Rutgers University, Piscataway, USA</b></td><td>1</td></tr><tr><td><b>University of Maryland, College Park, College Park, USA</b></td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Beijing, P.R.China</b></td><td>1</td></tr><tr><td><b>School of Science, Jiangnan University, Wuxi, China</b></td><td>1</td></tr><tr><td><b>School of Internet of Things Engineering, Jiangnan University, Wuxi, China</b></td><td>1</td></tr><tr><td>Department of Engineering and MaintenanceChina Mobile Group, Jiangsu Company, Ltd., Changzhou, China</td><td>1</td></tr><tr><td><b>School of Computer Sciences and Technology, Nanjing Normal University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, Nanjing Normal University, Nanjing, China</b></td><td>1</td></tr><tr><td>Indian Statistical Institute, Kolkata 700108</td><td>1</td></tr><tr><td>Departament d’Informàtica, Universitat de Valencia, Valencia, Spain</td><td>1</td></tr><tr><td><b>Department of Computer Science, George Mason University, Fairfax, USA</b></td><td>1</td></tr><tr><td><b>School of Information Technology, Deakin University, Geelong, Australia</b></td><td>1</td></tr><tr><td><b>School of Sciences, South China University of Technology, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>College of Computer and Information Science, Southwest University, Chongqing, China</b></td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, Gannan Normal University, Ganzhou, People’s Republic of China</td><td>1</td></tr><tr><td><b>Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, Tongji University, Shanghai, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Information Engineering, Zhengzhou University, China</b></td><td>1</td></tr><tr><td>National Laboratory of Pattern Recognition, Beijing, China</td><td>1</td></tr><tr><td><b>National University of Kaohsiung, Kaohsiung, Taiwan</b></td><td>1</td></tr><tr><td>Quang Binh University, Dong Hoi City, Vietnam</td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, China</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Science, Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, Greece</b></td><td>1</td></tr><tr><td><b>Dept. of Medical Physics, Medical School, Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, Greece</b></td><td>1</td></tr><tr><td><b>Dermalog Identification Systems GmbH, Hamburg, Germany</b></td><td>1</td></tr><tr><td>School of Mathematics and Information Technology, Nanjing Xiao Zhuang University, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td><b>Research & Advanced Technology Division of SAIC Motor Corporation Limited, Shanghai, 201804, P.R. China</b></td><td>1</td></tr><tr><td><b>ECSE Department, Rensselaer Polytechnic Institute</b></td><td>1</td></tr><tr><td><b>Centre of Excellence for Research in Computational Intelligence and Applications, School of Computer Science, University of Birmingham, Birmingham, U.K.</b></td><td>1</td></tr><tr><td><b>VUB-NPU Joint AVSP Research Lab, Northwestern Polytechnical University (NPU), Shaanxi Key Lab on Speech and Image Information Processing, 127 Youyi Xilu, X'ian 710072, China</b></td><td>1</td></tr><tr><td><b>Arizona State University, Phoenix, AZ, USA</b></td><td>1</td></tr><tr><td>School of Computing, Electronics and Mathematics, Faculty of Engineering, Environment and Computing, Coventry University, Coventry, UK</td><td>1</td></tr><tr><td><b>Department of Computer Science and Information Engineering, National Taipei University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td>Institute of Computer Science, Christian-Albrechts-Universität Kiel, Kiel, Germany</td><td>1</td></tr><tr><td><b>Institute of Computer Science, Faculty of Electronics and Information Technology, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland</b></td><td>1</td></tr><tr><td>KT Future Technology Laboratory, Seoul, South Korea</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Anhui University, Hefei, China</b></td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>Microsoft Key Laboratory of Visual Perception, Zhejiang University, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Beijing, P.R. China</b></td><td>1</td></tr><tr><td><b>School of Interactive Computing, Georgia Institute of Technology, Atlanta, USA</b></td><td>1</td></tr><tr><td>Microsoft Research Asia, Beijing, P.R. China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea</b></td><td>1</td></tr><tr><td><b>Nanyang Technological University, 50 Nanyang Drive, 637553, Singapore</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Northumbria University, Newcastle, UK</b></td><td>1</td></tr><tr><td><b>School of Automation, Northwestern Polytechnical University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>SAIIP, School of Computer Science, Northwestern Polytechnical University, Xi’an, China</b></td><td>1</td></tr><tr><td>Shanghai Maritime University, Shanghai, China</td><td>1</td></tr><tr><td>Machine Intelligence Research Institute, Rockville, USA</td><td>1</td></tr><tr><td><b>Department of Computer Science, Shenzhen Graduate School, Harbin Institute of Technology, China</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, Liaoning 110004, China</b></td><td>1</td></tr><tr><td><b>University of Pittsburgh and Adjunct Faculty at the Robotics Institute, Carnegie Mellon University: 3137 Sennott Square, 210 S. Bouquet St., PA 15260 USA</b></td><td>1</td></tr><tr><td><b>AI Institute, Qihoo/360 Company, Beijing, China</b></td><td>1</td></tr><tr><td><b>Intelligent Media Technique Research Center, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, P.R. China</b></td><td>1</td></tr><tr><td><b>CAS Center for Excellence in Brain Science and Intelligence Technology, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, P.R. China</b></td><td>1</td></tr><tr><td><b>AI Institute of Qihoo/360 Company, Beijing, P.R. China</b></td><td>1</td></tr><tr><td><b>Advanced Engineering Electronics & Safety, Delphi Deutschland GMBH, Delphiplatz 1, Wuppertal, North Rhine-Westfalia, Germany</b></td><td>1</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China</b></td><td>1</td></tr><tr><td>Orange—France Telecom Division R&D—TECH/IRIS, Cesson Sévigné Cedex, France</td><td>1</td></tr><tr><td>IIT-Madras, Chennai, India</td><td>1</td></tr><tr><td>Department of Computer Science, Innopolis University, Kazan, Russia</td><td>1</td></tr><tr><td><b>Center for Telematics and Information Technology, University of Twente, Enschede, Netherlands</b></td><td>1</td></tr><tr><td>Department of Computer Science, University of Science & Technology, Bannu, Pakistan</td><td>1</td></tr><tr><td><b>Department of Biomedical Engineering, Kyung Hee University, Suwon, Korea</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Kyung Hee University, Suwon, Korea</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, Korea</b></td><td>1</td></tr><tr><td>Naver Labs Europe, Meylan, France</td><td>1</td></tr><tr><td><b>Image and Video Systems Lab, Dept. of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-Gu, Daejeon 305-701, Republic of Korea</b></td><td>1</td></tr><tr><td><b>LIRIS, UMR 5205 CNRS, INSA-Lyon, F-69621, France</b></td><td>1</td></tr><tr><td><b>Orange Labs, R&D, Meylan, France</b></td><td>1</td></tr><tr><td>School of Computer and Systems Sciences, JawaharLal Nehru University, New Delhi 110067, India</td><td>1</td></tr><tr><td>Univ. La Rochelle, La Rochelle, France</td><td>1</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Tsuen Wan, Hong Kong</td><td>1</td></tr><tr><td><b>University of Maryland, Center for Automation Research, 4411 A.V. Williams Building, College Park, MD 20742-3275, USA</b></td><td>1</td></tr><tr><td><b>Teaching and research of section of mathematics, Hebei Information Engineering School, Baoding 071000, China</b></td><td>1</td></tr><tr><td><b>George Mason University, Fairfax, USA</b></td><td>1</td></tr><tr><td><b>University of Naples Federico II, Napoli, Italy</b></td><td>1</td></tr><tr><td>University of Salerno, Salerno, Italy</td><td>1</td></tr><tr><td><b>Sapienza University of Rome, Rome, Italy</b></td><td>1</td></tr><tr><td><b>RheinAhrCampus der Hochschule Koblenz, Remagen, Germany</b></td><td>1</td></tr><tr><td>Google, Mountain View, USA</td><td>1</td></tr><tr><td>Computer Sciences Department, University of Wisconsin, Madison, USA</td><td>1</td></tr><tr><td>Google, Seattle, USA</td><td>1</td></tr><tr><td>Singapore Polytechnic, 500 Dover Road, Singapore 139651</td><td>1</td></tr><tr><td><b>Singapore University of Technology and Design, 20 Dover Road, Singapore 138682</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Robotics, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, China</b></td><td>1</td></tr><tr><td><b>Bournemouth University, Poole, UK</b></td><td>1</td></tr><tr><td><b>Technische Universitt Darmstadt, Computer Systems Group, Darmstadt, Germany</b></td><td>1</td></tr><tr><td><b>School of Engineering and Applied Science, Aston University, Birmingham, U.K.</b></td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China</td><td>1</td></tr><tr><td>Centre for Machine Vision, Bristol Robotics Laboratory, University of the West of England, T Block, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, UK</td><td>1</td></tr><tr><td><b>PERCEPTION Team, INRIA Grenoble Rhône-Alpes, France</b></td><td>1</td></tr><tr><td><b>MIR@CL Laboratory, Faculty of Sciences of Sfax (FSS), University of Sfax, Sfax, Tunisia</b></td><td>1</td></tr><tr><td>Saudi Electronic University, Riyadh, Kingdom of Saudi Arabia</td><td>1</td></tr><tr><td><b>MIR@CL Laboratory, Faculty of Economics and Management of Sfax (FSEGS), University of Sfax, Sfax, Tunisia</b></td><td>1</td></tr><tr><td><b>Digital World Research Centre, University of Surrey, UK</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Curtin University, Miri Sarawak, Malaysia</b></td><td>1</td></tr><tr><td>Information Security Group, City University London, London, UK</td><td>1</td></tr><tr><td><b>Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia</b></td><td>1</td></tr><tr><td><b>Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia</b></td><td>1</td></tr><tr><td>School of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou, China</td><td>1</td></tr><tr><td>IIIT Chittoor, SriCity, Andhra Pradesh, India</td><td>1</td></tr><tr><td><b>ARM, Inc., San Jose, CA</b></td><td>1</td></tr><tr><td>Department of Information Engineering, Henan University of Science and Technology, Luoyang, China</td><td>1</td></tr><tr><td><b>School of Computing Sciences, University of East Anglia, Norwich, U.K.</b></td><td>1</td></tr><tr><td>Department of mechatronic technology of National Taiwan Normal University</td><td>1</td></tr><tr><td><b>Department of Computer Science, Taipei Municipal University of Education</b></td><td>1</td></tr><tr><td><b>Computer Vision Center 08193 Bellaterra, Barcelona, SPAIN</b></td><td>1</td></tr><tr><td><b>Computer Science Division, University of Central Florida, Orlando, FL, USA</b></td><td>1</td></tr><tr><td><b>GuangXi Cast Animation Company, Ltd., Nanning, China</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering and Computer Science, Colorado School of Mines, Golden, CO, USA</td><td>1</td></tr><tr><td><b>School of Information Engineering, Xiangtan University, Xiangtan, China</b></td><td>1</td></tr><tr><td><b>Baidu International Technology (Shenzhen) Company, Ltd., Shenzhen, China</b></td><td>1</td></tr><tr><td>The Image Processing and Analysis Laboratory (LAPI), University “Politehnica” of Bucharest, 313 Splaiul Independeţei, Bucharest, Romania</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, The Chinese University of Hong Kong</b></td><td>1</td></tr><tr><td><b>School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China</b></td><td>1</td></tr><tr><td>Division of Digital Media Engineering, Sang-Myung University, Suwon, Republic of Korea</td><td>1</td></tr><tr><td><b>CAS, Key Lab of Intell. Info. Process., Institute of Computing Technology, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computing, Teesside University, UK</b></td><td>1</td></tr><tr><td><b>Teleinfrastructure R&D Lab, Technical University of Sofia, Bulgaria</b></td><td>1</td></tr><tr><td><b>The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td>Facebook AI Research (FAIR), Menlo Park, USA</td><td>1</td></tr><tr><td>Princeton University &Microsoft, Princeton, NJ, USA</td><td>1</td></tr><tr><td>Microsoft &University of Washington, Redmond, WA, USA</td><td>1</td></tr><tr><td>Intel Labs, Pittsburgh PA</td><td>1</td></tr><tr><td>Dept. of Inf. Network Technol., Hsiuping Inst. of Technol., Taichung, Taiwan</td><td>1</td></tr><tr><td>Alibaba Group, Zhejiang, People’s Republic of China</td><td>1</td></tr><tr><td><b>Computer Science, Arizona State University, Tempe, USA</b></td><td>1</td></tr><tr><td><b>Cork Institute of Technology, CIT, Cork Ireland</b></td><td>1</td></tr><tr><td><b>Biomedical Engineering Program, University of Manitoba, Winnipeg, Canada</b></td><td>1</td></tr><tr><td>Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute Troy, Troy, USA</td><td>1</td></tr><tr><td>Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology, University of Science and Technology of China Hefei, Anhui, People’s Republic of China</td><td>1</td></tr><tr><td><b>Department of Computer Science, University of North Carolina Wilmington, Wilmington, United States</b></td><td>1</td></tr><tr><td><b>School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea</b></td><td>1</td></tr><tr><td>School of ComputingNational University of Singapore</td><td>1</td></tr><tr><td><b>Centre for Intelligent Machines and Department of Electrical and Computer Engineering, McGill University, Montreal, Canada</b></td><td>1</td></tr><tr><td><b>UFSC - Federal University of Santa Catarina / INE - CTC, Florianópolis, 88040-900, Brazil</b></td><td>1</td></tr><tr><td><b>UDESC - Santa Catarina State University, DCC - CCT, Joinville, 89219-710, Brazil</b></td><td>1</td></tr><tr><td><b>School of Electrical and Electronic Engineering, University of Manchester, Manchester, U.K.</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Information Technology, University of Nottingham, Nottingham, UK</b></td><td>1</td></tr><tr><td><b>Waseda University, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>Computer Science Department, Rutgers University, 110 Frelinghuysen Road, Piscataway, NJ 08854-8019, USA</b></td><td>1</td></tr><tr><td><b>Fordham University, New York, 10023, USA</b></td><td>1</td></tr><tr><td><b>Rapid-Rich Object Search (ROSE) Lab, Nanyang Technological University, Interdisciplinary Graduate School, SingaporeSingapore</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Semnan University, Semnan, Iran</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran</b></td><td>1</td></tr><tr><td>Dept. of EE, UESTC, 2006 Xiyuan Ave, Chengdu, Sichuan 611731, China</td><td>1</td></tr><tr><td>Dept. of Radiation Oncology, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</td><td>1</td></tr><tr><td>Dept. of Electrical & Computer Engineering, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</td><td>1</td></tr><tr><td>University of Nottingham (Malaysia Campus), Malaysia</td><td>1</td></tr><tr><td>South Valley University, Qena, Egypt</td><td>1</td></tr><tr><td>Film Department ELTE University, Budapest, Hungary</td><td>1</td></tr><tr><td>Gipsa-Lab, Saint Martin d’Heres, France</td><td>1</td></tr><tr><td>ICA Laboratory, Grenoble, France</td><td>1</td></tr><tr><td><b>IIIT Hyderabad, 500032, A.P, India</b></td><td>1</td></tr><tr><td>School of Computing and Electrical Engineering, IIT Mandi, H.P, 175001, India</td><td>1</td></tr><tr><td><b>School of Computer Science and Software Engineering, The University of Western Australia, Crawley, WA, Australia</b></td><td>1</td></tr><tr><td><b>School of Engineering, Griffith University, Nathan, QLD, Australia</b></td><td>1</td></tr><tr><td><b>Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA</b></td><td>1</td></tr><tr><td><b>Department of Naval Architecture and Marine Engineering, University of Michigan, Ann Arbor, MI 48109 USA</b></td><td>1</td></tr><tr><td><b>Beijing Key Laboratory of Digital Media, State Key Laboratory of Virtual Reality Technology and Systems, and School of Computer Science and Engineering , Beihang University, China</b></td><td>1</td></tr><tr><td><b>Philips Research , The Netherlands</b></td><td>1</td></tr><tr><td><b>Istanbul Technical University, Faculty of Computer and Informatics, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China</b></td><td>1</td></tr><tr><td>AICTE Emeritus Fellow, </td><td>1</td></tr><tr><td><b>Department of Computer Science & Engineering, Jadavpur University, Kolkata, India</b></td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, GCELT, Kolkata, India</td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Shaanxi, P. R. China</b></td><td>1</td></tr><tr><td><b>University of Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td>Chinese University of Hong Kong, Hong Kong</td><td>1</td></tr><tr><td><b>Signal and Information Processing section (SIP), Department of Electronic Systems, Aalborg University, Denmark</b></td><td>1</td></tr><tr><td><b>Section of Image Analysis and Computer Graphics, DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark</b></td><td>1</td></tr><tr><td>Department of Computer System and Communication, Faculty of Information and Communication, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia</td><td>1</td></tr><tr><td>Division Télécom, Centre de Développement des Technologies Avancées - CDTA, Algiers, Algeria</td><td>1</td></tr><tr><td><b>University of Delaware, USA</b></td><td>1</td></tr><tr><td><b>Department of Cognitive Science, School of Information Science and Engineering, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Taylor's University Lakeside Campus, Selangor Darul Ehsan, Malaysia</b></td><td>1</td></tr><tr><td><b>Department of Mathematical Sciences, Georgia Southern University, Statesboro, USA</b></td><td>1</td></tr><tr><td>School of Computer and Communication Science, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland</td><td>1</td></tr><tr><td><b>Department of Electronic EngineeringCentre for Vision, Speech and Signal Processing, University of Surrey, Surrey, U.K.</b></td><td>1</td></tr><tr><td><b>Department of Electrical EngineeringFaculty of Engineering, Urmia University, Urmia, Iran</b></td><td>1</td></tr><tr><td><b>ICT-ISVISION Joint R&D Lab. for Face Recognition, Chinese Acad. of Sci., Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Electrical and Computer Engineering, Purdue University, West Lafayette, USA</b></td><td>1</td></tr><tr><td>Baidu Research - Institute of Deep Learning, Sunnyvale, USA</td><td>1</td></tr><tr><td>Jiaxing University, Jiaxing, China</td><td>1</td></tr><tr><td><b>International School, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computer Engineering, Nanyang Technological University, Singapore, Singapore</b></td><td>1</td></tr><tr><td><b>Department of Social and Decision Sciences, Carnigie Mellon University, Pittsburgh, PA 15224, USA</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. zhangxiaoxun@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. jiayunde@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. xushuang@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Electronics and Communication, University of Allahabadm Allahabad, India 211002</td><td>1</td></tr><tr><td><b>Microsoft Live Labs Research, China</b></td><td>1</td></tr><tr><td><b>Baidu Research, USA</b></td><td>1</td></tr><tr><td><b>Center for Machine Vision and Signal Analysis, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Applied Network Technology (ANT), Department of Computer Science, Faculty of Science, Khon Kaen University, Khon Kaen, Thailand</b></td><td>1</td></tr><tr><td>Department of Business Computer, Faculty of Management Science, Nakhon Ratchasima Rajabhat University, Nakhon Ratchasima, Thailand</td><td>1</td></tr><tr><td><b>Microsoft Research</b></td><td>1</td></tr><tr><td><b>MIT CSAIL</b></td><td>1</td></tr><tr><td><b>Affectiva</b></td><td>1</td></tr><tr><td>Yahoo! Research</td><td>1</td></tr><tr><td><b>University of Denver, 2390 S York Street, CMK 308, Denver, CO 80210, USA</b></td><td>1</td></tr><tr><td><b>Institute for Computational and Mathematical Engineering, Stanford University</b></td><td>1</td></tr><tr><td><b>Computer Laboratory, University of Cambridge, Cambridge, U.K.</b></td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, University of Cagliari, Italy</td><td>1</td></tr><tr><td><b>Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China</b></td><td>1</td></tr><tr><td><b>School of Information Science and Technology, Southwest Jiaotong University, Chengdou, P.R. China</b></td><td>1</td></tr><tr><td><b>Center for OPTical IMagery Analysis and Learning, State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China</b></td><td>1</td></tr><tr><td><b>Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, U.K.</b></td><td>1</td></tr><tr><td><b>College of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Fotonation LTD, Galway, Ireland</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xian 710072, Shaanxi, China</b></td><td>1</td></tr><tr><td>Universidad de León, León, Spain</td><td>1</td></tr><tr><td>Elektronik ve Haberleşme Mühendisliği Bölümü</td><td>1</td></tr><tr><td>Robert Bosch Engineering and Business Solutions Limited, Bangalore, India</td><td>1</td></tr><tr><td>Department of Instrumentation and Control Engineering, PSG College of Technology, Coimbatore, India</td><td>1</td></tr><tr><td><b>Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Faculty of Computer and Informatics, Istanbul Technical University, Istanbul, Turkey</b></td><td>1</td></tr><tr><td>China Airborne Missile Academy, Luoyang, China</td><td>1</td></tr><tr><td>Electronic Information Engineering College, Henan University of Science and Technology, Luoyang, China</td><td>1</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Amirkabir University of Technology, Electrical Engineering Department, Tehran, Iran</b></td><td>1</td></tr><tr><td><b>School of Computing and Communication, University of Technology Sydney, Sydney, Australia</b></td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Inner Mongolia University of Science and Technology, Baotou, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of Electronic and Information Engineering, Beihang University, Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td>Istituto Italiano di Tecnologia & Università di Verona, Genova, Italy</td><td>1</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT), Genova, Italy</td><td>1</td></tr><tr><td><b>Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany</b></td><td>1</td></tr><tr><td>Office of Safety Research and Development, Federal Highway Administration, U.S. Department of Transportation, Virginia, USA</td><td>1</td></tr><tr><td><b>Department of Applied Mathematics, Beijing Jiaotong University, Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td>Xinjiang Vocational and Technical College of Communications, Wulumuqi, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of Mechatronical Engineering and Automation, Shanghai University, Shanghai, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Guangdong University of Technology, China</b></td><td>1</td></tr><tr><td>College of Mathematics and Informatics, South China Agricultural University, China</td><td>1</td></tr><tr><td><b>Computer Vision and Multimodal Computing, MPI Informatics, Saarbruecken</b></td><td>1</td></tr><tr><td><b>Computer Vision Laboratory, ETH Zurich</b></td><td>1</td></tr><tr><td><b>School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, China</b></td><td>1</td></tr><tr><td>Curtin University Department of Mechanical Engineering, Perth, Western Australia 6012</td><td>1</td></tr><tr><td><b>Department of Mechanical Engineering, Curtin University, Perth, Western Australia 6012</b></td><td>1</td></tr><tr><td>Department of Information Engineering, HeNan Radio and Television University, Zhengzhou, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of Computer and Information Science, Southwest University, Chongqing, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Center for Robotics, Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiamen University, Xiamen, People’s Republic of China</b></td><td>1</td></tr><tr><td>Computer Science Department, School of Information Science and Engineering, Xiamen, University, Xiamen, People’s Republic of China</td><td>1</td></tr><tr><td>PLA University of Science and Technology, China</td><td>1</td></tr><tr><td><b>PLA University of Science and Technology, China and State Key Lab. for Novel Software Technology, Nanjing University, China</b></td><td>1</td></tr><tr><td><b>College of Computer and Information, Hohai University, China</b></td><td>1</td></tr><tr><td><b>College of Computer and Information, Hohai University, China and Key Lab. of Image and Video Understanding for Social Safety, Nanjing University of Science & Technology, China</b></td><td>1</td></tr><tr><td><b>Vols Taipei</b></td><td>1</td></tr><tr><td><b>Intel Labs Europe, London, United Kingdom</b></td><td>1</td></tr><tr><td><b>Technion - Israel Inst. of Technology, Haifa, 32000, Israel</b></td><td>1</td></tr><tr><td><b>The Open University of Israel, Raanana, 43107, Israel</b></td><td>1</td></tr><tr><td><b>Weizmann Institute of Science, Rehovot, 76100, Israel</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, USA</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China</b></td><td>1</td></tr><tr><td><b>Department of Information and Communication Engineering, Chosun University, Gwangju, Korea</b></td><td>1</td></tr><tr><td>School of Electronics and Computer Eng., Chonnam National University, Gwangju, Korea</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA 23529, USA</b></td><td>1</td></tr><tr><td>FAST, Supélec, Avenue de la Boulaie, Cesson-Sévigné, France</td><td>1</td></tr><tr><td>ISIR laboratory, Pierre and Marie Curie university, Paris Cedex 05, France</td><td>1</td></tr><tr><td>Centre for Visual Computing, Faculty of Engineering and Informatics, University of Bradford, Bradford, UK</td><td>1</td></tr><tr><td><b>Faculty of Science and Technology, Communication University of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>Science and Technology Department, Communication University of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>Collaborative Innovation Center, Communication University of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computer Software, Tianjin University, 300072, China</b></td><td>1</td></tr><tr><td><b>Computer Vision Laboratory, ETH Zürich, Zürich, Switzerland</b></td><td>1</td></tr><tr><td>Amsterdam University College, Amsterdam, The Netherlands</td><td>1</td></tr><tr><td><b>Informatics Institute, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands</b></td><td>1</td></tr><tr><td><b>Universitat Pompeu Fabra, Universidad Pompeu Fabra (Edificio França), Passeig de Circumvallacio, 8, Barcelona, Spain</b></td><td>1</td></tr><tr><td><b>Departamento de estadística, Universidad Carlos III de Madrid, Barcelona, Spain</b></td><td>1</td></tr><tr><td><b>Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Computer Science, Rochester Institute of Technology, USA</b></td><td>1</td></tr><tr><td><b>Center for Imaging Science, Rochester Institute of Technology, USA</b></td><td>1</td></tr><tr><td><b>Space and Naval Warfare Systems Center Pacific, San Diego, CA, 92152, United States</b></td><td>1</td></tr><tr><td><b>Electrical and Computer Engineering, University of California, San Diego</b></td><td>1</td></tr><tr><td>Key Laboratory of Intelligent Information Processing, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of Computer Science, Chongqing University, Chongqing, China</b></td><td>1</td></tr><tr><td>Institute of Life Sciences, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>School of Information Science and Engineering, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>FEECS, Department of Computer Science, Technical University of Ostrava, Ostrava-Poruba, Czech Republic</td><td>1</td></tr><tr><td>ECE, Department MSIT, C-4 Janakpuri, New Delhi, India</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., New Jersey Inst. of Technol., Newark, NJ, USA</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan. e-mail: chihming.fu@gmail.com</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan; Informatics Department, Fo-Guang University, I-Lan, Taiwan. e-mail: clhuang@ee.nthu.edu.tw</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan</td><td>1</td></tr><tr><td><b>Research Institute for Future Media Computing, Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>University Politehnica of Bucharest, Bucharest, Romania</b></td><td>1</td></tr><tr><td><b>School of Computer and Information, Anhui Polytechnic University, Wuhu, China</b></td><td>1</td></tr><tr><td><b>Faculty of Information Sciences and Engineering, University of Canberra, Australia</b></td><td>1</td></tr><tr><td><b>Robotics Institute, Carnegie Mellon University, USA</b></td><td>1</td></tr><tr><td><b>Pediatrics Department, University of South Florida, Tampa, FL, USA</b></td><td>1</td></tr><tr><td>Department of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China</td><td>1</td></tr><tr><td><b>Sun Yat-Sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td>University of California at Los Angeles, Los Angeles, CA, USA</td><td>1</td></tr><tr><td><b>University of Queensland, Brisbane, Australia</b></td><td>1</td></tr><tr><td><b>University of Maryland, Baltimore County, Baltimore, MD</b></td><td>1</td></tr><tr><td><b>Jadavpur University, Kolkata, India</b></td><td>1</td></tr><tr><td>Department of Physics, Tripura University (A Central University), Suryamaninagar, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Tripura University (A Central University), Suryamaninagar, India</td><td>1</td></tr><tr><td><b>Raytheon BBN Technologies, Cambridge, MA, USA</b></td><td>1</td></tr><tr><td>Pontifical Catholic University of Minas Gerais - Department of Computer Science, R. Dom Jose Gaspar, 500, Belo Horizonte MG, 30535901, Brazil</td><td>1</td></tr><tr><td><b>College of Computer and Information Science, Southwest University, Chongqing 400715, China</b></td><td>1</td></tr><tr><td><b>Human-Robot Interaction Research Center, Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea</b></td><td>1</td></tr><tr><td><b>Tsinghua University, Beijing, 100084, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea</b></td><td>1</td></tr><tr><td><b>School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Electronics Engineering, Bahcesehir University, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>School of Science, Jiangnan University, Wuxi, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, USA</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Advanced Process Control for Light Industry, Jiangnan University, Ministry of Education, Wuxi, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Internet of Things, Jiangnan University, Wuxi, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada</b></td><td>1</td></tr><tr><td>Department of Statistics and Operational Research, Faculty of Mathematics, Complutense University of Madrid, Madrid, Spain</td><td>1</td></tr><tr><td><b>Distributed Infinity, Inc., Larkspur, CO, USA</b></td><td>1</td></tr><tr><td><b>University of Colorado Denver, Denver, CO, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA</b></td><td>1</td></tr><tr><td><b>Facebook Inc., San Francisco, CA, USA</b></td><td>1</td></tr><tr><td><b>Adobe Systems Inc., San Jose, CA, USA</b></td><td>1</td></tr><tr><td>Dept. of Mathematics and Computer Science, University of Udine, Italy</td><td>1</td></tr><tr><td><b>University of Wisconsin-Madison, Madison, WI, USA</b></td><td>1</td></tr><tr><td>LIMSI-CNRS, Orsay Cedex, France</td><td>1</td></tr><tr><td>Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Pisa, Italy</td><td>1</td></tr><tr><td><b>Faculty of Information Technology, University of Technology, Sydney, Sydney, Australia. email: hintz@it.uts.edu.au</b></td><td>1</td></tr><tr><td><b>Faculty of Information Technology, University of Technology, Sydney, Sydney, Australia. email: jant@it.uts.edu.au</b></td><td>1</td></tr><tr><td><b>Faculty of Information Technology, University of Technology, Sydney, Sydney, Australia. email: pohsiang@it.uts.edu.au</b></td><td>1</td></tr><tr><td>Faculty of Information Sciences and Engineering, Management and Science University, Selangor, Malaysia</td><td>1</td></tr><tr><td>UTM-Big Data Center, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</td><td>1</td></tr><tr><td>Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</td><td>1</td></tr><tr><td><b>School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia</td><td>1</td></tr><tr><td>LAMIA, EA 4540, University of French West Indies and Guyana, Guadeloupe, France</td><td>1</td></tr><tr><td>ISIR, UPMC Univ Paris 06, CNRS, Paris, France</td><td>1</td></tr><tr><td><b>Advanced Electronics System, Academy of Scientific and Industrial Research, CSIR-Central Electronics Research Institute, Pilani, India</b></td><td>1</td></tr><tr><td><b>Mobile Communications Department, Eurecom, Biot, France</b></td><td>1</td></tr><tr><td><b>STARS Team, Institut National de Recherche en Informatique et en Automatique, Sophia Antipolis, France</b></td><td>1</td></tr><tr><td>Merchant Marine College, Shanghai Maritime University, Shanghai 201306, PR China</td><td>1</td></tr><tr><td><b>Institute of Industrial Science, the University of Tokyo, Tokyo, Japan</b></td><td>1</td></tr><tr><td>Department of Informatics, King’s College London, London, UK</td><td>1</td></tr><tr><td><b>DST INSPIRE Fellow, Department of Computer Science and Engineering, Jadavpur University, Kolkata, India</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering, KAIST, Korea</td><td>1</td></tr><tr><td><b>Electronic R&D Center, Mando Corp., Korea</b></td><td>1</td></tr><tr><td>Department of New Media, Korean German Institute of Technology, Korea</td><td>1</td></tr><tr><td><b>SAIT Beijing Lab, Samsung Advanced Institute of Technology, China</b></td><td>1</td></tr><tr><td><b>Mechatronics & Manufacturing Technology Center, Samsung Electronics Co., Korea</b></td><td>1</td></tr><tr><td>Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy</td><td>1</td></tr><tr><td><b>Open University of Israel</b></td><td>1</td></tr><tr><td><b>The University of Western Australia, Crawley, Australia</b></td><td>1</td></tr><tr><td><b>Curtin University, Perth, Australia</b></td><td>1</td></tr><tr><td>Pontifical Catholic Univ of Rio de Janei, Department of Informatics, Rio de Janeiro, Brazil</td><td>1</td></tr><tr><td>Department of Informatics, Pontifical Catholic Univ of Rio de Janei, Rio de Janeiro, Brazil</td><td>1</td></tr><tr><td>School of Computing Sciences and Informatics, University of Cincinnati, Cincinnati, USA</td><td>1</td></tr><tr><td><b>Concordia University, Montreal, Canada</b></td><td>1</td></tr><tr><td>Universiti Kuala Lumpur, Kedah</td><td>1</td></tr><tr><td><b>Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, H3G 1T7, Canada</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Concordia University, QC, Canada, H3G 1T7</b></td><td>1</td></tr><tr><td><b>Beijing University of Posts and Telecommunications, 100876, PR China</b></td><td>1</td></tr><tr><td><b>University of KwaZulu-Natal, School of Maths, Statistics & Computer Science, Durban - South Africa</b></td><td>1</td></tr><tr><td>Sudan University of Science and Technology, College of Computer Science and Information Technology, Khartoum - Sudan</td><td>1</td></tr><tr><td>LMU Munich, Germany and Munich University of Applied Sciences, Germany</td><td>1</td></tr><tr><td>Department of Electric and Electronic Engineering, Avrasya University, Trabzon, Turkey</td><td>1</td></tr><tr><td><b>Department of Electric and Electronic Engineering, Selçuk University, Konya, Turkey</b></td><td>1</td></tr><tr><td><b>Digital Media Institute, Hunan University, Changsha, 410082 P.R. China</b></td><td>1</td></tr><tr><td><b>College of information science and engineering, Hunan University, Changsha, 410082 P.R. China</b></td><td>1</td></tr><tr><td>ACM Professional Specialist in Artificial Intelligence</td><td>1</td></tr><tr><td><b>Université du Quebec a Rimouski (UQAR)</b></td><td>1</td></tr><tr><td><b>School of Information Technology & Electrical Engineering, The University of Queensland, Brisbane, Australia</b></td><td>1</td></tr><tr><td><b>School of Computing, National University of Singapore, Singapore, Singapore</b></td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China</td><td>1</td></tr><tr><td><b>Shanghai university</b></td><td>1</td></tr><tr><td>University of Washington and Google Inc.</td><td>1</td></tr><tr><td>Google Inc.</td><td>1</td></tr><tr><td><b>University of Washington</b></td><td>1</td></tr><tr><td><b>CNRS, IMB, UMR 5251, Talence, France</b></td><td>1</td></tr><tr><td><b>UMR 5800, CNRS, LaBRI, Talence, France</b></td><td>1</td></tr><tr><td><b>UMR 5800, University of Bordeaux, LaBRI, Talence, France</b></td><td>1</td></tr><tr><td><b>UMR 5800, Bordeaux INP, LaBRI, Talence, France</b></td><td>1</td></tr><tr><td><b>UMR 5800, LaBRI, Talence, France</b></td><td>1</td></tr><tr><td><b>Dept. of Electrical Engineering, National Chung Hsing University, Taiwan</b></td><td>1</td></tr><tr><td><b>Division of Design of Intelligent Machines, Center for Development of Advanced Technologies, Algiers, Algeria</b></td><td>1</td></tr><tr><td><b>AI Laboratories, Alibaba Group, Hangzhou, China</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an, China</b></td><td>1</td></tr><tr><td>CCCE, Nankai University Jinnan Campus, Tianjin, China</td><td>1</td></tr><tr><td><b>College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, USA</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, University of Houston, Houston, USA</b></td><td>1</td></tr><tr><td><b>Research Group on Intelligent Machines, University of Sfax, ENIS, Sfax, Tunisia</b></td><td>1</td></tr><tr><td><b>Department of Management, Dalian University of Technology, Dalian Liaoning, China</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, Dalian University of Technology, Dalian Liaoning, China</b></td><td>1</td></tr><tr><td><b>College of Communication Engineering, Chongqing University, Shapingba district, Chongqing, China</b></td><td>1</td></tr><tr><td>Department of Computer Science, VHNSN College, Virudhunagar, India</td><td>1</td></tr><tr><td>Department of Computer Science, ANJA College, Sivakasi, India</td><td>1</td></tr><tr><td><b>Department of Information Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong</b></td><td>1</td></tr><tr><td>Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology Tsinghua University, Beijing, China</td><td>1</td></tr><tr><td><b>National ICT Australia, Canberra, ACT, Australia</b></td><td>1</td></tr><tr><td><b>MIT Media Laboratory, Cambridge, MA, USA</b></td><td>1</td></tr><tr><td>Foundation for Research & Technology – Hellas, Heraklion, Crete, Greece</td><td>1</td></tr><tr><td>Vrije Universiteit Amsterdam, Amsterdam, The Netherlands</td><td>1</td></tr><tr><td>Ruhr-Universität Bochum, Bochum, Germany</td><td>1</td></tr><tr><td><b>Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland</b></td><td>1</td></tr><tr><td><b>Industrial Technology Research Institute, Hsinchu, Taiwan</b></td><td>1</td></tr><tr><td><b>Garmin Corporation, New Taipei, Taiwan</b></td><td>1</td></tr><tr><td><b>Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td><b>School of Information Technologies, University of Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>Tencent AI Laboratory, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Malong Technologies Company, Ltd., Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Beijing Normal University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Guangzhou University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Department of Information Engineering, the Chinese University of Hong Kong</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, the Chinese University of Hong Kong, Shatin, Hong Kong</b></td><td>1</td></tr><tr><td>Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro No.1, Tonantzintla, Puebla, México. CP 72840</td><td>1</td></tr><tr><td><b>Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente 225, Gávea, Brasil</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, National Taiwan University of Science and Technology</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Computational Vision Group, University of California at Irvine, Irvine, CA, USA</b></td><td>1</td></tr><tr><td><b>Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, The Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, China</b></td><td>1</td></tr><tr><td>Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, People’s Republic of China</td><td>1</td></tr><tr><td><b>Department of Automation, Shanghai Jiao Tong University, Shanghai, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>School of Psychology, University of Ottawa, Ottawa, Canada</b></td><td>1</td></tr><tr><td><b>School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada</b></td><td>1</td></tr><tr><td><b>Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran</b></td><td>1</td></tr><tr><td><b>Tohoku University, Japan</b></td><td>1</td></tr><tr><td><b>Intelligent Multimedia Technique Research Center, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, PR China</b></td><td>1</td></tr><tr><td>Department of Mechanical Engineering, Universiti Tenaga Nasional Km 7, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia</td><td>1</td></tr><tr><td><b>University of Alberta, Canada</b></td><td>1</td></tr><tr><td><b>China University of Geosciences, Wuhan, China</b></td><td>1</td></tr><tr><td><b>College of Information Science and Engineering, Hunan University, Changsha, China</b></td><td>1</td></tr><tr><td>Dept. of Electron. Eng., Hannam Univ., Daejeon, South Korea</td><td>1</td></tr><tr><td><b>Centre for Autism Research, Philadelphia, US</b></td><td>1</td></tr><tr><td><b>University of Cambridge</b></td><td>1</td></tr><tr><td><b>Department of EE, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea</b></td><td>1</td></tr><tr><td><b>Department of Software and Computer Engineering, Ajou University, Suwon, Korea</b></td><td>1</td></tr><tr><td>Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies, Zhejiang, China</td><td>1</td></tr><tr><td><b>College of Computer Science, Zhejiang University, Zhejiang, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Chang Gung University, Taoyuan, Taiwan</b></td><td>1</td></tr><tr><td><b>School of Information Science and Engineering, Shandong University, Jinan, China</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada</td><td>1</td></tr><tr><td><b>Center for Advance Imaging Innovation and Research, New York University, New York, NY, USA</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Warwick, Coventry, U.K.</b></td><td>1</td></tr><tr><td>Laboratoire MIA, University of La Rochelle, La Rochelle, France</td><td>1</td></tr><tr><td><b>College of Cyber Security, Jinan University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Columbia University, New York</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, College of Computer and Information Science, Northeastern University, Boston, MA, USA</b></td><td>1</td></tr><tr><td>Fraunhofer Institute for Telecommunications, Berlin, Germany</td><td>1</td></tr><tr><td>Fraunhofer Institute for Digital Media Technology, Ilmenau, Germany</td><td>1</td></tr><tr><td>Siemens AG, Corporate Technology, Munich, Germany</td><td>1</td></tr><tr><td><b>School of Engineering, University of Illinois, Urban Champagne, USA</b></td><td>1</td></tr><tr><td>ECIT, School of Electronics, Electrical Engineering & Computer Science, Queen's University Belfast, Belfast, UK</td><td>1</td></tr><tr><td><b>Computer Science, Loughborough University, Loughborough, UK</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Calcutta, Kolkata, India</td><td>1</td></tr><tr><td><b>Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Engineering, Science and Reaserch Branch, Islamic Azad University, Tehran, Iran</b></td><td>1</td></tr><tr><td>School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran</td><td>1</td></tr><tr><td>Luoyang Electro-Optical Equipment Research Institute, Luoyang, People’s Republic of China</td><td>1</td></tr><tr><td><b>Schepens Eye Research Institute, Harvard University, Cambridge, USA</b></td><td>1</td></tr><tr><td><b>Image Processing Center, Beihang University, Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td>Technological Educational Institute of Sterea Ellada, Psahna, Halkida, Greece</td><td>1</td></tr><tr><td>National Centre for Scientific Research “Demokritos”, Agia Paraskevi, Athens, Greece</td><td>1</td></tr><tr><td>University of Maastricht, Maastricht, The Netherlands</td><td>1</td></tr><tr><td>Centre of Research and Technology Hellas, Thermi, Thessaloniki, Greece</td><td>1</td></tr><tr><td><b>School of Computing and Communications, Lancaster University, Lancaster, UK</b></td><td>1</td></tr><tr><td><b>Center for Optical Imagery Analysis and Learning, Northwestern Polytechnical University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing, China</b></td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, P.P.G. Institute of Technology, Coimbatore, India</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Institute of Road and Transport Technology, Erode, India</td><td>1</td></tr><tr><td><b>Wayne State University, Detroit, USA</b></td><td>1</td></tr><tr><td><b>School of Automation, Huazhong University of Science and Technology, Wuhan, China 430074</b></td><td>1</td></tr><tr><td><b>College of Electronics and Information Engineering, Sichuan University, Chengdu, China 610064</b></td><td>1</td></tr><tr><td>Department of Computer Science, Banasthali Vidyapith, Banasthali, India</td><td>1</td></tr><tr><td>Computer Science and Engineering Department, SP Memorial Institute of Technology, Kaushambi, India</td><td>1</td></tr><tr><td><b>Dept. of Comp. Sci. and Tech., Shenzhen Graduate School, Harbin Institute of Technology, China</b></td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, China</td><td>1</td></tr><tr><td><b>Imperial College London</b></td><td>1</td></tr><tr><td><b>Machine Vision Group, University of Oulu, Oulu, Finland</b></td><td>1</td></tr><tr><td>Fujifilm Software, San Jose, USA</td><td>1</td></tr><tr><td><b>Inst. of Autom., Chinese Acad. of Sci., Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computing, Computing 1, 13 Computing Drive, National University of Singapore, Singapore 117417</b></td><td>1</td></tr><tr><td>Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis, Singapore 138632</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576</b></td><td>1</td></tr><tr><td><b>Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, Brazil</b></td><td>1</td></tr><tr><td><b>Computational Brain Science Lab, Department of Computational Science and Technology, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden</b></td><td>1</td></tr><tr><td><b>Graduate Sch. of Inf. Sci. & Technol., Tokyo Univ., Japan</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>National Laboratory of Speech and Language Information Processing, University of Science and Technology of China, Hefei, China</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Pittsburgh/Robotics Institute, Carnegie Mellon University , Pittsburgh, PA, USA</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Dept.of Intelligence Science and Technology, The Kyoto University of JAPAN</b></td><td>1</td></tr><tr><td><b>Dept.of Computational Intelligence and Systems Science, Tokyo Institute of Technology of JAPAN</b></td><td>1</td></tr><tr><td><b>Microsoft Research, Redmond, WA, USA</b></td><td>1</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, People’s Republic of China</b></td><td>1</td></tr><tr><td>HTC Research, Beijing, China</td><td>1</td></tr><tr><td>QCIS, University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td><b>IIIS, Tsinghua University, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, PR China</b></td><td>1</td></tr><tr><td><b>School of Software Technology, Dalian University of Technology</b></td><td>1</td></tr><tr><td>Interuniversity Microelectronics Centre, Heverlee, Belgium</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Lab, Department ETRO, Vrije Universiteit Brussel (VUB), Brussels, Belgium</td><td>1</td></tr><tr><td>Shaanxi Key Laboratory on Speech and Image Information Processing, Xi’an, China</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Lab, School of Computer Science, Northwestern Polytechnical University (NPU), Xi’an, China</td><td>1</td></tr><tr><td><b>School of Computer and Information Science, Southwest University, Chongqing, China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Shandong University, Shandong, China</b></td><td>1</td></tr><tr><td><b>Facebook Inc., Palo Alto, CA, USA</b></td><td>1</td></tr><tr><td><b>Stanford University, USA</b></td><td>1</td></tr><tr><td>Institute of Electronics and Computer Science, Riga, Latvia</td><td>1</td></tr><tr><td>Electrical and Computer Engineering Department, University of California, Santa Barbara, CA 93106 USA</td><td>1</td></tr><tr><td>Psychology Department, University of California, Santa Barbara, CA 93106 USA</td><td>1</td></tr><tr><td><b>Computer Science and Information Engineering Department, National Taiwan Normal University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td>Dept. of Comp. Sci. and Inf. Eng, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>School of Control Science and Engineering DUT, Dalian, China</td><td>1</td></tr><tr><td><b>College of Mechanical and Electrical, Changzhou Textile Garment Institute, Changzhou, China</b></td><td>1</td></tr><tr><td>Information Technology R&D Center, Mitsubishi Electric Corporation, Kamakura, Japan</td><td>1</td></tr><tr><td>School of Information Science and Engineering, Hunan city University, Yiyang, China</td><td>1</td></tr><tr><td><b>School of Electronics and Information Engineering, Tongji University, Shanghai, China</b></td><td>1</td></tr><tr><td>KU Leuven, ESAT - PSI, iMinds, Leuven, Belgium</td><td>1</td></tr><tr><td>Max-Planck-Institut für Informatik, Saarbrücken, Germany</td><td>1</td></tr><tr><td><b>Faculty of Electrical Engineering, Department of Cybernetics, Czech Technical University in Prague, Prague 6, Czech Republic</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Toronto, Toronto, Canada</b></td><td>1</td></tr><tr><td>Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran, Iran</td><td>1</td></tr><tr><td>University of IIllinois, Urbana-Champaign</td><td>1</td></tr><tr><td><b>Department of ECE, National University of Singapore</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, University of Dayton</b></td><td>1</td></tr><tr><td><b>Institut EURECOM, Sophia Antipolis, (France)</b></td><td>1</td></tr><tr><td><b>Sapienza Università di Roma, v. Salaria 113, 00198, Rome, (IT)</b></td><td>1</td></tr><tr><td><b>Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA</b></td><td>1</td></tr><tr><td>Zhejiang University & Alibaba Group, Hangzhou, China</td><td>1</td></tr><tr><td>Laboratory LIM, Department of Computer Science, Faculty of Sciences and Technologies, University Hassan II, Casablanca-Morocco</td><td>1</td></tr><tr><td><b>College of Electrical Engineering and Automation, Anhui University, Hefei, China</b></td><td>1</td></tr><tr><td>Electrical Engineering Department, Yazd University, Yazd, Iran</td><td>1</td></tr><tr><td><b>School of Computer and Science Technology, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td>School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin, China</td><td>1</td></tr><tr><td>Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, Tianjin, China</td><td>1</td></tr><tr><td><b>Research School of Engineering, Australian National University, Canberra, Australia</b></td><td>1</td></tr><tr><td><b>DCNS Research, 5 rue de l'Halbrane, 44340 Bouguenais, France</b></td><td>1</td></tr><tr><td>Adjunct, Effat University, Jeddah, Saudi Arabia</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Miami, Coral Gables, USA</b></td><td>1</td></tr><tr><td>School of Computer Science, Wuyi University, Jiangmen, China</td><td>1</td></tr><tr><td><b>Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia</b></td><td>1</td></tr><tr><td><b>School of Computer Engineering and Science, Shanghai University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Faculty of Education, East China Normal University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Department of Information Engineering and Computer Science, University of Trento, Trento, TN, Italy</b></td><td>1</td></tr><tr><td>Snapchat Research, Venice, CA90291</td><td>1</td></tr><tr><td><b>Beauty Cosmetic Research Lab, Kao Corporation, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>University of Waterloo, Waterloo, Canada</b></td><td>1</td></tr><tr><td><b>Department of CS, University of Texas at San Antonio, 78249, USA</b></td><td>1</td></tr><tr><td>Department of CSE, University at Buffalo (SUNY), NY 14260, USA</td><td>1</td></tr><tr><td><b>University of Waterloo</b></td><td>1</td></tr><tr><td>School of Information and Engineering, Jinhua Polytechnic, Jinhua, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Texas, Arlington, USA</td><td>1</td></tr><tr><td>School of Medical Science, Jinhua Polytechnic, Jinhua, China</td><td>1</td></tr><tr><td><b>College of Information, Capital University of Economics and Business, Beijing, China.sanyecunfu@emails.bjut.edu.cn</b></td><td>1</td></tr><tr><td><b>Bio-Computing Research Center, Harbin Institute of Technology Shenzhen Graduate School, China</b></td><td>1</td></tr><tr><td><b>Guangdong Industry Training Centre, Guangdong Polytechnic Normal University, Guangzhou, China</b></td><td>1</td></tr><tr><td>S. S. College of Business Studies, University of Delhi, Delhi, India</td><td>1</td></tr><tr><td>School of Computer & System Sciences, Jawaharlal Nehru University, New Delhi, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, India</td><td>1</td></tr><tr><td><b>Korea University, Seoul, South Korea</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Ajou University</b></td><td>1</td></tr><tr><td><b>Advanced Digital Sciences Center , Singapore</b></td><td>1</td></tr><tr><td><b>National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, 100190, China</b></td><td>1</td></tr><tr><td>Baidu Online Network Technology (Beijing) Co. Ltd, Beijing, China</td><td>1</td></tr><tr><td><b>Computer Science and Electrical Engineering West Virginia University, Morgantown, USA</b></td><td>1</td></tr><tr><td><b>Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Department of ComputingBiometrics Research Centre, The Hong Kong Polytechnic University, Hong Kong</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Information Technology, RMIT University, Melbourne, VIC, Australia</b></td><td>1</td></tr><tr><td>Faculty of Engineering and Computing, Coventry University, UK</td><td>1</td></tr><tr><td>Dept. of Theoretical Electrical Engineering, Technical University of Sofia, Sofia, Bulgaria</td><td>1</td></tr><tr><td><b>Clemson University, Clemson, SC</b></td><td>1</td></tr><tr><td><b>School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>1</td></tr><tr><td><b>School of Digital Media, Jiangnan University Jiangsu Wuxi, PR China</b></td><td>1</td></tr><tr><td><b>School of Digital Media, Jiangnan University, Jiangsu Wuxi, PR China</b></td><td>1</td></tr><tr><td><b>School of Maths, Statistics & Computer Science, University of KwaZulu-Natal, Durban, South Africa</b></td><td>1</td></tr><tr><td><b>Faculty of Science and Technology, Sudan University of Science and Technology, Khartoum, Sudan</b></td><td>1</td></tr><tr><td>Lawrence Berkeley National Laboratory, Berkeley, USA</td><td>1</td></tr><tr><td>No.1 Senior Middle School of Wendeng District, Weihai, China</td><td>1</td></tr><tr><td>Standards & Metrology Research Institute of CARS, Beijing, China</td><td>1</td></tr><tr><td>College of Information Science & Technology, Hebei Agricultural University, Baoding, China</td><td>1</td></tr><tr><td><b>Graduate School of System Informatics, Kobe University, Japan</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL</b></td><td>1</td></tr><tr><td><b>Beijing FaceAll Co. Beijing, China</b></td><td>1</td></tr><tr><td><b>University of Science and Technology of China</b></td><td>1</td></tr><tr><td>Amazon, Berkshire, U.K.</td><td>1</td></tr><tr><td>Tianjin Universtiy, Tianjin, China</td><td>1</td></tr><tr><td><b>Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20740 United States</b></td><td>1</td></tr><tr><td><b>Electrical and Computer Engineering, Rutgers University, Piscataway, New Jersey 08854 United States</b></td><td>1</td></tr><tr><td><b>The Computer Laboratory, University of Cambridge, Cambridge, UK</b></td><td>1</td></tr><tr><td><b>New York University, New York City, NY, USA</b></td><td>1</td></tr><tr><td><b>Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology, University of Technology Sydney, 81 Broadway Street, Ultimo, NSW, Australia</b></td><td>1</td></tr><tr><td>University of Lancaster, Lancaster, United Kingdom</td><td>1</td></tr><tr><td>University of Helsinki, Helsinki, Finland</td><td>1</td></tr><tr><td><b>Department of Multimedia and Graphic Arts, Cyprus University of Technology, P.O. Box 50329, 3036, Lemesos, Cyprus</b></td><td>1</td></tr><tr><td><b>Ryerson Multimedia Research Laboratory, Ryerson University, Toronto, Ontario, Canada</b></td><td>1</td></tr><tr><td>Intelligent and Interactive Systems, Institute of Computer Science, University of Innsbruck, Innsbruck, Austria</td><td>1</td></tr><tr><td>Signal and Image Exploitation (INTELSIG), Montefiore Institute, University of Liège, Liège, Belgium</td><td>1</td></tr><tr><td>Megvii Inc., Beijing, China</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong</b></td><td>1</td></tr><tr><td><b>Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC</b></td><td>1</td></tr><tr><td><b>University of Ottawa, Ottawa, Canada</b></td><td>1</td></tr><tr><td><b>National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>Army Research Office, RTP, Raliegh, NC, United States of America</b></td><td>1</td></tr><tr><td><b>The State Key Laboratory of Integrated Services Networks (ISN), Xidian University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>Department of Electronic and Engineering, Xidian University, Xi’an, China</b></td><td>1</td></tr><tr><td>Department of Informatics, Modeling, Electronics, and Systems, University of Calabria, Rende, Italy</td><td>1</td></tr><tr><td><b>The University of New South Wales, Australia</b></td><td>1</td></tr><tr><td>School of Materials Science and Engineering, Central South University, Changsha, China</td><td>1</td></tr><tr><td>Institute of Energy, Jiangxi Academy of Sciences, Nanchang, China</td><td>1</td></tr><tr><td><b>Xiamen Key Laboratory of Computer Vision and Pattern Recognition, Huaqiao University, Xiamen, China</b></td><td>1</td></tr><tr><td>**</td><td>1</td></tr><tr><td><b>Advanced Technologies Application, Center (CENATAV), Cuba</b></td><td>1</td></tr><tr><td><b>Institute of Digital Media, Peking University, Beijing, China</b></td><td>1</td></tr><tr><td><b>GREYC, CNRS UMR6072, University of Caen, Caen, France</b></td><td>1</td></tr><tr><td><b>IDIAP, Martigny, Switzerland</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213. msavvid@cs.cmu.edu</b></td><td>1</td></tr><tr><td><b>Information Sciences Institute, University of Southern California, Marina del Rey, CA 90292. mitra@isi.edu</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: king@cse.cuhk.edu.hk</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: lyu@cse.cuhk.edu.hk</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: jkzhu@cse.cuhk.edu.hk</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: hbdeng@cse.cuhk.edu.hk</b></td><td>1</td></tr><tr><td>Electrical and Electronic Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran</b></td><td>1</td></tr><tr><td><b>Electronics and Telecommunications Research Institute (ETRI), Republic of Korea</b></td><td>1</td></tr><tr><td><b>Xerox Research Center, Europe, France</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Science and Technology on Integrated Information System Laboratory, Institute of Software, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td>College of Mathematics and Information Engineering, Jiaxing University, Jiaxing, China</td><td>1</td></tr><tr><td><b>State Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, Chengdu, China</b></td><td>1</td></tr><tr><td>Dept. of Convergence, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, Korea</td><td>1</td></tr><tr><td><b>Graduate School of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan</b></td><td>1</td></tr><tr><td><b>School of Electronic Science and Engineering, National ASIC Research and Engineering Center, Southeast University, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Human Media Interaction Group, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands</b></td><td>1</td></tr><tr><td>School of Mechanical and Electrical Engineering, Shandong Management University, Jinan, China</td><td>1</td></tr><tr><td>School of Information Science and Technology, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>National Institute of Advanced Industrial Science Technology, Japan</td><td>1</td></tr><tr><td>Tilburg center for Cognition and Communication, Tilburg University, Tilburg, The Netherlands</td><td>1</td></tr><tr><td><b>Massachusetts Institute of Technology, Cambridge, USA</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China</b></td><td>1</td></tr><tr><td><b>MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Department of Automation, State Key Laboratory of Intelligent Technologies and Systems and Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, The University of Sheffield, Sheffield, UK</b></td><td>1</td></tr><tr><td>Automatics Research Group, Universidad Tecnológica de Pereira, Pereira, Colombia</td><td>1</td></tr><tr><td><b>Department of Computer Engineering, College of Computer & Information Sciences, King Saud University, Riyadh, Saudi Arabia</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong, China</b></td><td>1</td></tr><tr><td><b>Laboratory of Media Audio & Video, Communication University of China, Beijing, China</b></td><td>1</td></tr><tr><td><b>Division of Electrical Engineering, School of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-Dong, Yuseong-Gu, Daejeon 305-701, Republic of Korea</b></td><td>1</td></tr><tr><td><b>CNRS LTCI; Télécom ParisTech</b></td><td>1</td></tr><tr><td><b>Institut Mines-Télécom; Télécom ParisTech; CNRS LTCI</b></td><td>1</td></tr><tr><td>School of Science, Southwest Petroleum University, Chengdu, China</td><td>1</td></tr><tr><td><b>Amity University, Noida, India</b></td><td>1</td></tr><tr><td>Infosys Limited, Bhubaneswar, India</td><td>1</td></tr><tr><td><b>Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Quanzhou, China</b></td><td>1</td></tr><tr><td><b>Research Center for Learning Science, Southeast University, China</b></td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Tianjin University of Technology, China</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, College of the Computer and Information Science, Northeastern University, Boston, MA, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA</b></td><td>1</td></tr><tr><td><b>Department of Computer and Information Science, University of Massachusetts Dartmouth, Dartmouth, MA, USA</b></td><td>1</td></tr><tr><td>Department of Computer Science, University of Brasília, DF, Brazil 70910-900</td><td>1</td></tr><tr><td>Department of Mechanical Engineering, University of Brasília, DF, Brazil 70910-900</td><td>1</td></tr><tr><td><b>Department of Neurosurgery, University of Pittsburgh, PA 15213, USA</b></td><td>1</td></tr><tr><td><b>Faculty of Computers and Information, Ain Shams University, Egypt</b></td><td>1</td></tr><tr><td><b>Faculty of Computers and Information, BeniSuef University, Egypt</b></td><td>1</td></tr><tr><td>LIAMA, French National Institute for Research in Computer Science and Control, Paris, France</td><td>1</td></tr><tr><td><b>Intel Laboratory China, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Computing, National University of Singapore</b></td><td>1</td></tr><tr><td><b>Institute for Infocomm Research, Singapore</b></td><td>1</td></tr><tr><td><b>Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</b></td><td>1</td></tr><tr><td>Leiden University, Leiden, The Netherlands</td><td>1</td></tr><tr><td>TNO, The Hague, The Netherlands</td><td>1</td></tr><tr><td>City University, Kowloon Tong, Hong Kong</td><td>1</td></tr><tr><td>Radboud University, EC Nijmegen, The Netherlands</td><td>1</td></tr><tr><td>TNO, Oude Waalsdorperweg, AK The Hague, The Netherlands</td><td>1</td></tr><tr><td>Liaocheng University, Liaocheng, China</td><td>1</td></tr><tr><td><b>Machine Vision Group, Infotech Oulu and Department of Electrical and Information Engineering, University of Oulu, Finland</b></td><td>1</td></tr><tr><td>Northwestern Polytechnic University, Xi’an, China</td><td>1</td></tr><tr><td>University of Science and Technology Beijing, Beijing, China</td><td>1</td></tr><tr><td><b>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun Donglu, Beijing 100190, China</b></td><td>1</td></tr><tr><td><b>Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China</b></td><td>1</td></tr><tr><td><b>Rapid-Rich Object Search Laboratory, Interdisciplinary Graduate School, Nanyang Technological University, Singapore</b></td><td>1</td></tr><tr><td><b>Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, USA</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, University of Portsmouth, Portsmouth, UK</b></td><td>1</td></tr><tr><td><b>Department of Automation, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Technology, College of Computer, National University of Defense Technology, Changsha, Hunan, China, 410073</b></td><td>1</td></tr><tr><td>Faculty of Information Engineering, China University of Geosciences, Wuhan, China</td><td>1</td></tr><tr><td><b>University of Abertay, Dundee, UK</b></td><td>1</td></tr><tr><td>China University of Geosciences Wuhan, China</td><td>1</td></tr><tr><td>University of Udine, Udine, Italy</td><td>1</td></tr><tr><td>INRS-EMT, Montreal, Canada</td><td>1</td></tr><tr><td><b>Sapienza Univertsity of Rome</b></td><td>1</td></tr><tr><td><b>Queen Mary University of London, London, England UK</b></td><td>1</td></tr><tr><td><b>Fudan University, Shanghai , China</b></td><td>1</td></tr><tr><td><b>Hohai University, No. 1 Xikang Road, Nanjing, Jiangsu Province, China</b></td><td>1</td></tr><tr><td><b>Institute of Intelligent Information Processing, Xidian University, Xi'an, China</b></td><td>1</td></tr><tr><td><b>College of Metropolitan Transportation, Beijing University of Technology, Beijing, China</b></td><td>1</td></tr><tr><td>School of Computer Science and Technology, Harbin Institute of Technology at Weihai, Weihai, China</td><td>1</td></tr><tr><td><b>School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td><b>Institute of Computing Technology, Chinese Academy of Sciences, Key Laboratory of Intelligent Information Processing, Beijing, China</b></td><td>1</td></tr><tr><td><b>University of Southern California, Los Angeles, CA, USA</b></td><td>1</td></tr><tr><td><b>Institute of Computing Technology, CAS, No.6 Kexueyuan South Road, Beijing, 100080, China</b></td><td>1</td></tr><tr><td>School of Computer Science Carnegie Mellon University Pittsburgh, PA, 15213, USA</td><td>1</td></tr><tr><td><b>Dept. of Computer Science, Purdue University</b></td><td>1</td></tr><tr><td><b>Center for Cognitive Ubiquitous Computing, Arizona State University, Tempe, USA</b></td><td>1</td></tr><tr><td><b>Center of Image and Signal Processing, Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur, Malaysia</b></td><td>1</td></tr><tr><td><b>Graduate School of Engineering Science, Department of Systems Innovation, Osaka University, Toyonaka, Japan</b></td><td>1</td></tr><tr><td>College of Information and Technology, Incheon National University, Incheon, Korea</td><td>1</td></tr><tr><td><b>College of Electronics and Information Engineering, Sichuan University, Chengdu, China</b></td><td>1</td></tr><tr><td><b>School of Software Engineering, Beijing Jiaotong University, Beijing, China</b></td><td>1</td></tr><tr><td>Tianjin University & University of South Carolina, Tianjin, China</td><td>1</td></tr><tr><td><b>Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, USA</b></td><td>1</td></tr><tr><td>School of Electronics Engineering, Kyungpook National University, Taegu, South Korea</td><td>1</td></tr><tr><td>Department of Electrical & Electronics Engineering, Kalasalingam University, Krishnankoil, India</td><td>1</td></tr><tr><td><b>Language Technologies Institute, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, USA</b></td><td>1</td></tr><tr><td><b>Pudong Branch, China Mobile Group Shanghai, Company Limited, Shanghai, China</b></td><td>1</td></tr><tr><td><b>School of Mathematics and Statistics, The University of Western Australia, Nedlands, WA, Australia</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Qatar University, Doha, Qatar</b></td><td>1</td></tr><tr><td>School of Computer Engineering, Hanshin University, Osan, Republic of Korea</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Center for Automation Research, University of Maryland, College Park, USA</b></td><td>1</td></tr><tr><td><b>France Telecom - Orange Labs, Lannion, France</b></td><td>1</td></tr><tr><td><b>National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China</b></td><td>1</td></tr><tr><td>School of Computer Science, China University of Geosciences, Wuhan, China</td><td>1</td></tr><tr><td>College of Computer Science and Technology of Huaqiao University, Xiamen, China</td><td>1</td></tr><tr><td><b>Department of Computer Science, Hong Kong Baptist University, Kowloon, Hong Kong</b></td><td>1</td></tr><tr><td><b>University of Windsor, Canada</b></td><td>1</td></tr><tr><td>CEA (iRSTV/BGE), INSERM (U1038), CNRS (FR3425), Université Grenoble-Alpes, Grenoble, France</td><td>1</td></tr><tr><td>NLPR, Institute of Automation, Chinese Academy of Science, Beijing, People’s Republic of China</td><td>1</td></tr><tr><td>Costel, Université de Rennes 2, Rennes, France</td><td>1</td></tr><tr><td>IRISA, Université de Bretagne Sud, Vannes, France</td><td>1</td></tr><tr><td>Research & Development, British Broadcasting Corporation (BBC), London, UK</td><td>1</td></tr><tr><td><b>Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia</b></td><td>1</td></tr><tr><td>Faculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, China</td><td>1</td></tr><tr><td><b>Waseda University</b></td><td>1</td></tr><tr><td>Wide Eyes Technologies</td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Illinois at Urbana—Champaign, Champaign, IL, USA</b></td><td>1</td></tr><tr><td><b>ThyssenKrupp Elevator Americas</b></td><td>1</td></tr><tr><td><b>Tsinghua University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Center for Signal and Image Processing, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta</b></td><td>1</td></tr><tr><td>School of Information Engineering, Jiangxi Manufacturing Technology College, Nanchang, China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Nanjing Forestry University and Shandong University, Jinan, China</td><td>1</td></tr><tr><td>Department of Language Studies, Nanjing Forestry University, Nanjing, China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Nanjing Forestry University, Nanjing, China</td><td>1</td></tr><tr><td><b>State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China</b></td><td>1</td></tr><tr><td>Dept. of Autom. Test & Control, Harbin Inst. of Technol., China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Frederick University, Nicosia, Cyprus</td><td>1</td></tr><tr><td><b>Department of Digital Systems, University of Piraeus, Piraeus, Greece</b></td><td>1</td></tr><tr><td>The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense M, Denmark</td><td>1</td></tr><tr><td><b>Department of Information and Control, B-DAT Laboratory, Nanjing University of Information Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong</b></td><td>1</td></tr><tr><td><b>University of Electronic Science and Technology of China, China</b></td><td>1</td></tr><tr><td><b>University of Maryland, College Park, USA</b></td><td>1</td></tr><tr><td><b>Institute of Engineering and Management, Kolkata, India</b></td><td>1</td></tr><tr><td><b>Inst. de Telecomunicações, Fac. de Ciências da Universidade do Porto, Porto, Portugal</b></td><td>1</td></tr><tr><td><b>Peking University, Beijing</b></td><td>1</td></tr><tr><td><b>Korea Electronics Technology Institute, Bundang-gu, Seongnam-si, Republic of Korea</b></td><td>1</td></tr><tr><td><b>National Taiwan University, Taiwan</b></td><td>1</td></tr><tr><td><b>Siren Solutions, Dublin, Ireland</b></td><td>1</td></tr><tr><td><b>Paradigma Digital, Madrid, Spain</b></td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, University of Science and Technology of China, Hefei, China</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, University of Science and Technology of China, Hefei, China</b></td><td>1</td></tr><tr><td><b>Australian National University, Australia</b></td><td>1</td></tr><tr><td><b>University of Canberra, Australia</b></td><td>1</td></tr><tr><td><b>Institute of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan, ROC</b></td><td>1</td></tr><tr><td>Department of Computer Science, Digital Image Processing Laboratory, Islamia College Peshawar, Peshawar, Pakistan</td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Michigan State University, East Lansing, USA</b></td><td>1</td></tr><tr><td><b>Research Institute for Future Media Computing, School of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Computer Vision Institute, School of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada</b></td><td>1</td></tr><tr><td><b>Faculty of Applied Science, University of British Columbia, Vancouver, British Columbia, Canada</b></td><td>1</td></tr><tr><td>Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan</td><td>1</td></tr><tr><td>Department of Computer Science, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan</td><td>1</td></tr><tr><td><b>Rutgers University, 94 Brett Road, Piscataway, NJ 08854, United States of America</b></td><td>1</td></tr><tr><td><b>Volvo Car Corporation, SE-405 31 Göteborg, Sweden</b></td><td>1</td></tr><tr><td><b>Smart Eye AB, SE-413 27 Göteborg, Sweden</b></td><td>1</td></tr><tr><td>Technische Universität München / Imperial College London, Munich / London, England UK</td><td>1</td></tr><tr><td><b>University of Geneva, Geneva, Switzerland</b></td><td>1</td></tr><tr><td>Department of Mathematics and Informatics, Ecole Centrale de Lyon, Lyon, 69134, France</td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, Jamia Hamdard University, New Delhi, India</td><td>1</td></tr><tr><td><b>Institute of Image Processing & Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China</b></td><td>1</td></tr><tr><td><b>Toyota Research Institute - North America</b></td><td>1</td></tr><tr><td><b>Department of Computer Science & Engineering, Arizona State University, Tempe, USA</b></td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, University of Minnesota-Twin Cities, Minneapolis, USA</td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary</td><td>1</td></tr><tr><td>School of Information Science and Technology, Northwest University, Xi’an, China</td><td>1</td></tr><tr><td>Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands</td><td>1</td></tr><tr><td><b>Griffith University</b></td><td>1</td></tr><tr><td><b>School of Computer, Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>1</td></tr><tr><td><b>School of Information, Singapore Management University, Singapore</b></td><td>1</td></tr><tr><td><b>Agency for Science, Technology and Research, Singapore</b></td><td>1</td></tr><tr><td>School of Software, Beijing Institute of Technology, Beijing, China</td><td>1</td></tr><tr><td><b>Department of Software Technology and Enterprize, Korea University, Seoul, Republic of Korea</b></td><td>1</td></tr><tr><td>University of St. Andrews, UK</td><td>1</td></tr><tr><td><b>University of Illinois at Urbana-Champaign, Champaign, IL, USA</b></td><td>1</td></tr><tr><td>University of Tunis El Manar, Tunis, Tunisia</td><td>1</td></tr><tr><td><b>Department of Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Purdue University, West Lafayette, USA</b></td><td>1</td></tr><tr><td>College of Information and Control Engineering, China University of Petroleum, Qingdao, China</td><td>1</td></tr><tr><td><b>Griffith School of Engineering, Queensland Research Laboratory, National ICT Australia, Griffith University, Nathan, Australia</b></td><td>1</td></tr><tr><td><b>Queensland Research Laboratory, National ICT Australia and Institute for Integrated and Intelligent Systems, Griffith University, Nathan, Australia</b></td><td>1</td></tr><tr><td>Intel Labs Europe, Pipers Way, Swindon</td><td>1</td></tr><tr><td><b>PRaDA, Deakin University, Australia</b></td><td>1</td></tr><tr><td>Department of Computer Systems, Universidad Politécnica de Madrid, Madrid, Spain</td><td>1</td></tr><tr><td><b>Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA</b></td><td>1</td></tr><tr><td><b>Neuropsychiatry Section, Department of Psychiatry, University of Pennsylvania</b></td><td>1</td></tr><tr><td><b>Department of Psychology, University of Illinois at Chicago, Chicago, IL</b></td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, Ursinus College, Collegeville, PA</td><td>1</td></tr><tr><td><b>Center for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td>Systems Engineering Institute, Xi’an Jiaotong University, Xi’an 710049, China</td><td>1</td></tr><tr><td><b>Chongqing University, China</b></td><td>1</td></tr><tr><td><b>University College London, UK, Dept. of Electronic and Electrical Engineering</b></td><td>1</td></tr><tr><td>Institute of Semiconductors, Chinese Academy of Sciences&University of Chinese Academy of Sciences, Beijing, China</td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, DUT-RU International School of Information and Software Engineering, Dalian University of Technology, Dalian, China</b></td><td>1</td></tr><tr><td><b>Computing Department, Imperial College London, UK. M.Pantic@imperial.ic.ac.uk</b></td><td>1</td></tr><tr><td><b>Computing Department, Imperial College London, UK. M.F.Valstar@imperial.ic.ac.uk</b></td><td>1</td></tr><tr><td><b>Consiglio Nazionale delle Ricerche, Istituto di Calcolo e Reti ad Alte Prestazioni, Viale delle Scienze, 90128 Palermo, ITALY</b></td><td>1</td></tr><tr><td>School of Computer Science and Technology, Nanjing University of Science and Technology of China, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td><b>University of Rochester, New York, USA</b></td><td>1</td></tr><tr><td><b>Microsoft Research, Beijing, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>University of Science and Technology of China, Hefei, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, China</b></td><td>1</td></tr><tr><td>NTT Network Innovation Laboratories, Nippon Telegraph and Telephone Corp.</td><td>1</td></tr><tr><td><b>Faculty of Engineering, Tunku Abdul Rahman University College, Setapak, Malaysia</b></td><td>1</td></tr><tr><td>Faculty of Computing and Information Technology, Setapak, Malaysia</td><td>1</td></tr><tr><td><b>Dep. Inteligencia Artificial, U. Politécnica Madrid, Spain</b></td><td>1</td></tr><tr><td><b>Dep. Ciencias de la Computación, U. Rey Juan Carlos, Spain</b></td><td>1</td></tr><tr><td><b>Dep. Comp. Sci. and Engr., Fudan University, China</b></td><td>1</td></tr><tr><td><b>Computer Science Department, University of Maryland, College Park, MD, USA</b></td><td>1</td></tr><tr><td><b>Cernium Corporation, Reston, VA, USA</b></td><td>1</td></tr><tr><td>Computer Science Department, University of California, Los Angeles, CA, USA</td><td>1</td></tr><tr><td><b>Department of Computer and Information Science, Temple University, Philadelphia, PA, USA</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering and the College of Computer and Information Science, Northeastern University, Boston, MA</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Northeastern University, Boston, MA</b></td><td>1</td></tr><tr><td><b>School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China</b></td><td>1</td></tr><tr><td><b>North Acton, London</b></td><td>1</td></tr><tr><td><b>Imaging Science and Engineering Laboratory, Tokyo Institute of Technology, Kanagawa, Japan</b></td><td>1</td></tr><tr><td><b>Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Kanagawa, Japan</b></td><td>1</td></tr><tr><td><b>Department of ECE, University of Dayton, Dayton, OH, USA</b></td><td>1</td></tr><tr><td><b>ODU Vision Lab, Old Dominion University, Norfolk, VA, USA</b></td><td>1</td></tr><tr><td><b>EURECOM, Route des Chappes, France</b></td><td>1</td></tr><tr><td>INRIA, Sophia Antipolis, France</td><td>1</td></tr><tr><td><b>School of Mathematical Sciences, Dalian University of Technology, Dalian, China</b></td><td>1</td></tr><tr><td>School of Mathematics and Computer Sciences, Gannan Normal University, Ganzhou, China</td><td>1</td></tr><tr><td>University of Maribor, Faculty of Electrical Engineering and Computer Science, Koroška cesta 46, SI-2000, Slovenia</td><td>1</td></tr><tr><td><b>RMIT University, Vietnam</b></td><td>1</td></tr><tr><td><b>Tolendata Singapore R&D Centre Private Limited, Singapore</b></td><td>1</td></tr><tr><td><b>College of Computer Science & Software Engineering, Shenzhen University, China 518060</b></td><td>1</td></tr><tr><td>University of Tours, France</td><td>1</td></tr><tr><td><b>Concordia Institute for Information Systems Engineering (CIISE), 1515 St. Catherine West, Montreal, Quebec H3G 2W1, CANADA</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Science and Software Engineering, Concordia University, 1515 St. Catherine West, Montreal, Quebec H3G 2W1, CANADA</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, University of Notre Dame</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Pontificia Universidad Catolica de Chile</b></td><td>1</td></tr><tr><td><b>Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology at Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>School of Engineering, The University of Edinburgh, Edinburgh, U.K.</b></td><td>1</td></tr><tr><td><b>Changzhou University, Changzhou, China</b></td><td>1</td></tr><tr><td><b>High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, China</b></td><td>1</td></tr><tr><td><b>Medical Psychology, Ulm University, Ulm, Germany</b></td><td>1</td></tr><tr><td>Department of Information Management, Hwa Hsia University of Technology, New Taipei City, Taiwan</td><td>1</td></tr><tr><td>Department of Electronic Engineering, National Ilan University, Yilan City, Taiwan</td><td>1</td></tr><tr><td><b>School of Computer Science, Guangzhou University, Guangzhou, China</b></td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China</td><td>1</td></tr><tr><td>College of Information and Electrical Engineering, Ludong University, Yantai, China</td><td>1</td></tr><tr><td><b>College of Computing, Georgia Tech</b></td><td>1</td></tr><tr><td><b>Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Korea</b></td><td>1</td></tr><tr><td><b>Taxes Instruments, Dallas, TX, United States</b></td><td>1</td></tr><tr><td>Wakayama University</td><td>1</td></tr><tr><td><b>Energy Research Institute @NTU (ERI@N), Interdisciplinary Graduate School, Nanyang Technological University, Singapore 639798</b></td><td>1</td></tr><tr><td>Computer Science College, Xi’an Polytechnic University, Xi’an, China</td><td>1</td></tr><tr><td><b>Visual Analysis of People Laboratory, Aalborg University, Aalborg, Denmark</b></td><td>1</td></tr><tr><td><b>Computer Vision Team, ARS Traffic & Transport Technology, Trivandrum, India</b></td><td>1</td></tr><tr><td><b>Computer Science Dept., Columbia University, USA</b></td><td>1</td></tr><tr><td>Computer Science Dept., SUNY Stony Brook, USA</td><td>1</td></tr><tr><td><b>Rensselaer Polytechnic Institute</b></td><td>1</td></tr><tr><td>School of Mathematical and Physical Sciences at the University of Newcastle, Callaghan, NSW 2308, Australia</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, JNTU College of Engineering, Hyderabad, India</td><td>1</td></tr><tr><td>Department of Physics, JNTU College of Engineering, Kakinada, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, JNTU College of Engineering, Kakinada, India</td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, Xiamen University, Xiamen, China</b></td><td>1</td></tr><tr><td><b>Collaborative Innovation Center for Geospatial Information Technology, Wuhan, China</b></td><td>1</td></tr><tr><td><b>Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague 6, Czech Republic</b></td><td>1</td></tr><tr><td>Department of Telecommunications and Information Processing, Image Processing and Interpretation, UGent/iMinds, Ghent, Belgium</td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Indian Institute of Science, C.V. Raman Avenue, Bangalore, KA 560-012, India</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada</b></td><td>1</td></tr><tr><td>School of Software, Shenyang University of Technology, Shenyang, China</td><td>1</td></tr><tr><td><b>Department of Internal Medicine, Chung-Ang University, Seoul, South Korea</b></td><td>1</td></tr><tr><td><b>Department of Data Science, Dankook University, Yongin, South Korea</b></td><td>1</td></tr><tr><td><b>Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td>School of Engineering of UABC, University of Baja California, Tijuana, Mexico</td><td>1</td></tr><tr><td>University of Hawaii at Hilo, HI, USA</td><td>1</td></tr><tr><td>Yuncheng University, Shanxi Province, China</td><td>1</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Nazarbayev University, Astana, Kazakhstan</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, Nanjing University of Science and Technology, Nanjing, China</b></td><td>1</td></tr><tr><td><b>State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td><b>University of Electronic Science and Technology of China, Chendu, China</b></td><td>1</td></tr><tr><td><b>Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates</b></td><td>1</td></tr><tr><td><b>School of Electronics and Information Engineering, Beihang University, Beijing, China</b></td><td>1</td></tr><tr><td><b>College of Computer Science, Guangdong University of Petrochemical Technology, Maoming, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA, 12180</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Istanbul University, Istanbul, Turkey</b></td><td>1</td></tr><tr><td>Department of Computer Engineering, Bahçeşehir University, Istanbul, Turkey</td><td>1</td></tr><tr><td>Sichuan University West China Hospital of Stomatology, Chengdu, China</td><td>1</td></tr><tr><td><b>Center for Future Media, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>1</td></tr><tr><td>School of Software Engineering, Chengdu University of Information Technology, Chengdu, China</td><td>1</td></tr><tr><td><b>School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China</b></td><td>1</td></tr><tr><td><b>National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD 20899, USA</b></td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, People’s Republic of China</td><td>1</td></tr><tr><td><b>Col. of Comp. Sci. and Comm. Eng., Jiangsu University, Zhenjiang, China</b></td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, China</td><td>1</td></tr><tr><td><b>Center for Automation Research, University of Maryland, College Park, MD 20742, USA</b></td><td>1</td></tr><tr><td><b>Delft University of Technology, Delft, The Netherlands</b></td><td>1</td></tr><tr><td>Department of Computer Engineering, Bogaziçi University, Bebek, Turkey</td><td>1</td></tr><tr><td>Department of Electrical and Electronic Engineering, Auckland University of Technology , Auckland, New Zealand</td><td>1</td></tr><tr><td>Department of Computer Engineering, Qazvin Islamic Azad University , Qazvin, Iran</td><td>1</td></tr><tr><td>Shanghai University of Finance and Economics, Shanghai, China</td><td>1</td></tr><tr><td><b>School of Mathematics, Jilin University, China</b></td><td>1</td></tr><tr><td><b>Department of Computer Science, Memorial University of Newfoundland, Canada</b></td><td>1</td></tr><tr><td>Graduate School of Engineering, Nagasaki University, Nagasaki, Japan</td><td>1</td></tr><tr><td>Institute of Management and Information Technologies, Chiba University, Chiba, Japan</td><td>1</td></tr><tr><td>Graduate School of Advanced Integration Science, Chiba University, Chiba, Japan</td><td>1</td></tr><tr><td><b>School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 15213, USA</b></td><td>1</td></tr><tr><td><b>Dept. of Computer Science, Purdue University, West Lafayette, IN, 47907, USA</b></td><td>1</td></tr><tr><td><b>Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea</b></td><td>1</td></tr><tr><td><b>Griffith University, Brisbane</b></td><td>1</td></tr><tr><td><b>Griffith University, Brisbane and University of the South Pacific, Fiji</b></td><td>1</td></tr><tr><td>Vision Semantics Ltd</td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong</b></td><td>1</td></tr><tr><td>Department of Film and Digital Media, Seokyeong University, Seoul, Republic of Korea</td><td>1</td></tr><tr><td>Department of MediaSoftware, Sungkyul University, Anyang-si, Republic of Korea</td><td>1</td></tr><tr><td><b>Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea</b></td><td>1</td></tr><tr><td>Pusan National University, Busan, Korea</td><td>1</td></tr><tr><td><b>Graduate School at Shenzhen, Tsinghua University, Shenzhen, China</b></td><td>1</td></tr><tr><td>School of Engineering, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland</td><td>1</td></tr><tr><td>Department of Computer Science, Auckland University of Technology, Auckland, New Zealand</td><td>1</td></tr><tr><td>L3S Research Center, Leibniz Universität Hannover, Hannover, Germany</td><td>1</td></tr><tr><td>German National Library of Science and Technology (TIB), Hannover, Germany</td><td>1</td></tr><tr><td>taglicht media Film- & Fernsehproduktion GmbH, Köln, Germany</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany</td><td>1</td></tr><tr><td><b>The Hong Kong Polytechnic University, Chu Hai College of Higher Education, Hong Kong, China</b></td><td>1</td></tr><tr><td>School of Mathematics and Computational Science, Anqing Normal University, Anqing, People’s Republic of China</td><td>1</td></tr><tr><td><b>School of IoT Engineering, Jiangnan University, Wuxi, People’s Republic of China</b></td><td>1</td></tr><tr><td>Concordia Institute for Information Systems Engineering Concordia University, Montreal, Canada</td><td>1</td></tr><tr><td>IKERBASQUE, Basque Foundation for Science, Bilbao, Spain</td><td>1</td></tr><tr><td>University of the Basque Country UPV/EHU, San Sebastian, Spain</td><td>1</td></tr><tr><td>Computer Vision Center, Edifici “O”, Campus UAB, Bellaterra, Spain</td><td>1</td></tr><tr><td>Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki City, Japan</td><td>1</td></tr><tr><td>Xiamen University of Technology, Fujian, China</td><td>1</td></tr><tr><td><b>Université des Antilles et de la Guyane (UAG), France</b></td><td>1</td></tr><tr><td><b>Institut des Systèmes intelligents et de Robotique, UPMC, France</b></td><td>1</td></tr><tr><td>School of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, China</td><td>1</td></tr><tr><td><b>College of Computer Science and Information Technology, Northeast Normal University, Changchun, China</b></td><td>1</td></tr><tr><td><b>College of Information Science and Engineering, Northeastern University, Shenyang, China</b></td><td>1</td></tr><tr><td>Dept. of Artificial Intelligence, Faculty of Computer Engineering, University of Isfahan, Iran</td><td>1</td></tr><tr><td>Department of Information Processing Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology Yokohama 226-8503, Japan</td><td>1</td></tr><tr><td><b>Research Groups on Intelligent Machines, University of Sfax, Sfax, Tunisia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, University of Queensland, St Lucia, QLD, Australia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang City 212003, China</b></td><td>1</td></tr><tr><td><b>Microsoft, Bellevue, WA, USA</b></td><td>1</td></tr><tr><td><b>M5001, Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong</b></td><td>1</td></tr><tr><td>Department of Computer Science, University of Texas, San Antonio, TX, USA</td><td>1</td></tr><tr><td><b>School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, USA</b></td><td>1</td></tr><tr><td><b>Imperial College London, London, U.K.</b></td><td>1</td></tr><tr><td><b>University of East Anglia, Norwich, United Kingdom</b></td><td>1</td></tr><tr><td>University of Sheffield, Sheffield, United Kingdom</td><td>1</td></tr><tr><td>Insititute of Automation, Chinese Academy of Sciences (CAS), Beijing, China</td><td>1</td></tr><tr><td><b>Alcohol Countermeasure Systems Corporation, Toronto, ON, Canada</b></td><td>1</td></tr><tr><td><b>Center for Ubiquitous Computing, University of Oulu, Oulu, Finland</b></td><td>1</td></tr><tr><td>School of Computing and Information Systems, University of Melbourne, Melbourne, Australia</td><td>1</td></tr><tr><td><b>Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland</b></td><td>1</td></tr><tr><td><b>Institute of Information and System Sciences, Faculty of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China</b></td><td>1</td></tr><tr><td><b>Research Division, Educational Testing Service, Princeton, NJ, USA</b></td><td>1</td></tr><tr><td><b>Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, Sun Yat-sen University, Guangzhou, China</b></td><td>1</td></tr><tr><td><b>Division of Biomedical Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR</b></td><td>1</td></tr><tr><td><b>Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR</b></td><td>1</td></tr><tr><td><b>University of York, York, United Kingdom</b></td><td>1</td></tr><tr><td><b>Kumamoto University, Kumamoto, Japan</b></td><td>1</td></tr><tr><td>Sapienza Università di Roma, Roma, Italy</td><td>1</td></tr><tr><td><b>Center for Research on Intelligent Perception and Computing (CRIPAC), NLPR, CASIA, Beijing, China</b></td><td>1</td></tr><tr><td><b>National Taichung University of science and Technology, Taichung</b></td><td>1</td></tr><tr><td><b>University of Technology Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>SAP Innovation Center Network, Singapore</b></td><td>1</td></tr><tr><td><b>Agency for Science, Technology and Research, Institute of High Performance Computing, Singapore</b></td><td>1</td></tr><tr><td><b>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. venu@cedar.buffalo.edu</b></td><td>1</td></tr><tr><td><b>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. zhizhang@cedar.buffalo.edu</b></td><td>1</td></tr><tr><td><b>CUBRC, Buffalo, NY, USA. slowe@cubrc.org</b></td><td>1</td></tr><tr><td>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. tulyakov@cedar.buffalo.edu</td><td>1</td></tr><tr><td><b>Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, USA</b></td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China</td><td>1</td></tr><tr><td><b>Department of Computing, University of Surrey, Guildford, Surrey, GU2 7XH, UK</b></td><td>1</td></tr><tr><td><b>Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, China</b></td><td>1</td></tr><tr><td>College of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China</td><td>1</td></tr><tr><td><b>National ASIC Design and Engineering Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b></td><td>1</td></tr><tr><td>LAMIA, EA 4540, University of French West Indies & Guyana</td><td>1</td></tr><tr><td><b>Institut Telecom - Telecom ParisTech CNRS/LTCI, Paris</b></td><td>1</td></tr><tr><td>Peking University & Shanghai Jaio Tong University, Beijing, China</td><td>1</td></tr><tr><td>School of Information Technology, Madurai Kamarai University, Madurai, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, Sanjivani College of Engineering, Kopargaon, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, St.Peter’s University, Chennai, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, Panimalar Engineering College, Chennai, India</td><td>1</td></tr><tr><td>Department of Computer Science, IT-Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>1</td></tr><tr><td>ITI Department Telecom Bretagne, Brest, France</td><td>1</td></tr><tr><td>Adobe Systems Incorporated, San Jose, CA, 95110</td><td>1</td></tr><tr><td><b>University of Technology at Sydney, Sydney, NSW, Australia</b></td><td>1</td></tr><tr><td><b>College of Engineeing & Informatics, National University of Ireland Galway, Galway, Ireland</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Bogazici University, Bebek, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Istanbul University, Avcilar, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>Department of Computer Engineering, Bahcesehir University, Besiktas, Istanbul, Turkey</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China</b></td><td>1</td></tr><tr><td><b>Faculty of Electronics and Telecommunications “POLITEHNICA” University from Timişoara Timişoara, România</b></td><td>1</td></tr><tr><td><b>College of Humanities, Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, China</b></td><td>1</td></tr><tr><td><b>Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore</b></td><td>1</td></tr><tr><td><b>Division of Computer Science and Engineering, Center for Advanced Image and Information Technology, Chonbuk National University, Jeonju, Republic of Korea</b></td><td>1</td></tr><tr><td><b>Division of Computer Science and Engineering, Chonbuk National University, Jeonju, Republic of Korea</b></td><td>1</td></tr><tr><td><b>University of Lincoln, U. K.</b></td><td>1</td></tr><tr><td><b>School of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou, China</b></td><td>1</td></tr><tr><td><b>Department of Electrical Engineering, Chang Gung University, Taipei, Taiwan</b></td><td>1</td></tr><tr><td><b>School of Information Technology, Monash University Malaysia, Bandar Sunway, Malaysia</b></td><td>1</td></tr><tr><td><b>College of Engineering, Huaqiao University, Fujian, China</b></td><td>1</td></tr><tr><td>Department of Electrical Engineering and Information Technology, TU Darmstadt, D-64283, Germany</td><td>1</td></tr><tr><td>Institute of Neural Information Processing, University of Ulm, Ulm, Germany</td><td>1</td></tr><tr><td>Institute for Information Technology and Communications (IIKT), Otto-von-Guericke-University Magdeburg, Magdeburg, Germany</td><td>1</td></tr><tr><td>Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran</td><td>1</td></tr><tr><td><b>University of Technology Sydney, Broadway, Australia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Software Engineering, University of Wollongong, Wollongong, Australia</b></td><td>1</td></tr><tr><td>Defence Science and Technology Organisation (DSTO), Edinburgh, Australia</td><td>1</td></tr><tr><td>Reallusion Corporation</td><td>1</td></tr><tr><td><b>National Taiwan Normal University</b></td><td>1</td></tr><tr><td><b>University College London</b></td><td>1</td></tr><tr><td><b>Keio University, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>The University of Tokyo, Bunkyo, Tokyo, Japan</b></td><td>1</td></tr><tr><td><b>Keio University, Yokohama City, Kanagawa, Japan</b></td><td>1</td></tr><tr><td><b>Keio University, Yokohama City, Japan</b></td><td>1</td></tr><tr><td>National Institute of Advanced Industrial Science and Technology (AIST), Koto, Tokyo, Japan</td><td>1</td></tr><tr><td><b>Research Center for Institute of Information Science, Academia Sinica, Taiwan</b></td><td>1</td></tr><tr><td><b>Department of Computer Science and Information Engineering, National Taiwan University</b></td><td>1</td></tr><tr><td><b>Department of Statistics, Carnegie Mellon University, Pittsburgh, USA</b></td><td>1</td></tr><tr><td>Computer Application Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</td><td>1</td></tr><tr><td>Dept. of EE, Univ. at Buffalo, SUNY, USA</td><td>1</td></tr><tr><td>Department of Computer Science, Minjiang University, Fuzhou, People’s Republic of China</td><td>1</td></tr><tr><td><b>Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, People’s Republic of China</b></td><td>1</td></tr><tr><td><b>Istanbul Technical University, Computer Engineering Department, 34469, Turkey</b></td><td>1</td></tr><tr><td><b>Department of Electronic Engineering, City University of Hong Kong, Hong Kong</b></td><td>1</td></tr><tr><td><b>School of Information Technology and Electrical Engineering, the University of Queensland, Brisbane, Qld, Australia</b></td><td>1</td></tr><tr><td><b>School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu</b></td><td>1</td></tr><tr><td><b>University of Electronic Science and Technology of China, Chengdu</b></td><td>1</td></tr><tr><td>Institute of High Performance Computing and Networking, National Research Council of Italy (ICAR-CNR), Naples, Italy</td><td>1</td></tr><tr><td><b>IBM Research, Singapore</b></td><td>1</td></tr><tr><td><b>Center for Applied Mathematics, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td><b>Department of Mathematics, School of Science, Tianjin University, Tianjin, China</b></td><td>1</td></tr><tr><td><b>Faculty of Applied Mathematics, Shanxi University of Finance and Economics</b></td><td>1</td></tr></table></body></html>
\ No newline at end of file diff --git a/scraper/reports/doi_institutions_geocoded.csv b/scraper/reports/doi_institutions_geocoded.csv index 1f7c7591..843ab2ba 100644 --- a/scraper/reports/doi_institutions_geocoded.csv +++ b/scraper/reports/doi_institutions_geocoded.csv @@ -118,7 +118,6 @@ 69ad67e204fb3763d4c222a6c3d05d6725b638ed,Capture expression-dependent AU relations for expression recognition,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
69a41c98f6b71764913145dbc2bb4643c9bc4b0a,Learning Match Kernels on Grassmann Manifolds for Action Recognition,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
695426275dee2ec56bc0c0afe1c5b4227a350840,Pooling the Convolutional Layers in Deep ConvNets for Video Action Recognition,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
-69b2a7533e38c2c8c9a0891a728abb423ad2c7e7,Manifold based sparse representation for facial understanding in natural images,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
696236fb6f986f6d5565abb01f402d09db68e5fa,Learning adaptive receptive fields for deep image parsing networks,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
3c1b73509cc09200e96ab9cfb28ebfd9d1d6aa9a,Nonoptimality of the Maximum-Weight Dependence Tree in Classification,Nazarbayev University,Nazarbayev University,"Назарбаев Университет, проспект Туран, BI village, Астана, район Есиль, Астана, 010000, Казахстан",51.09028540,71.39725263,edu,
3cb057a24a8adba6fe964b5d461ba4e4af68af14,Perceptual Annotation: Measuring Human Vision to Improve Computer Vision,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
@@ -252,7 +251,6 @@ 021469757d626a39639e260492eea7d3e8563820,3D Face Processing,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
a4898f55f12e6393b1c078803909ea715bf71730,"Where is the driver looking: Analysis of head, eye and iris for robust gaze zone estimation","University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
a4e75766ef93b43608c463c233b8646439ce2415,Automatic real-time FACS-coder to anonymise drivers in eye tracker videos,"Volvo, Sweden","Volvo Car Corporation, SE-405 31 Göteborg, Sweden","Karossvägen 2, 405 31 Göteborg, Sweden",57.72288600,11.84620530,edu,
-a317083d9aac4062e77aa0854513383c87e47ece,L0-norm Based Structural Sparse Least Square Regression for Feature Selection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
a35ed55dc330d470be2f610f4822f5152fcac4e1,Tattoo recognition technology - challenge (Tatt-C): an open tattoo database for developing tattoo recognition research,NIST,"National Institute of Standards and Technology (NIST), Gaithersburg, MD","100 Bureau Dr, Gaithersburg, MD 20899, USA",39.14004000,-77.21850600,edu,
a3201e955d6607d383332f3a12a7befa08c5a18c,VLAD encoded Deep Convolutional features for unconstrained face verification,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
a3ed0f15824802359e05d9777cacd5488dfa7dba,A Wearable Social Interaction Aid for Children with Autism,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
@@ -360,7 +358,6 @@ d10cfcf206b0991e3bc20ac28df1f61c63516f30,Smile or smirk? Automatic detection of d116bac3b6ad77084c12bea557d42ed4c9d78433,Recognition of occluded facial expressions based on CENTRIST features,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
d1079444ceddb1de316983f371ecd1db7a0c2f38,Sparse residue for occluded face image reconstruction and classification,"Harbin Institute of Technology, Shenzhen","Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China","China, Guangdong, Shenzhen, Nanshan, 平山一路",22.58675200,113.96878000,edu,
d1dd80d77655876fb45b9420fe72444c303b219e,Accumulated motion images for facial expression recognition in videos,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
-d1bd956a8523629ed4e2533b01272f22cea534c6,An illumination normalization model for face recognition under varied lighting conditions,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
d60e3eef429ed2a51bbd806125fa31f5bea072a4,Hajj human event classification system using machine learning techniques,Ain Shams University,"Faculty of Engineering, Ain Shams University, Cairo, Egypt","1 El Sarayat St.، ABBASSEYA، Al Waili, Cairo Governorate 11535, Egypt",30.06456570,31.27886080,edu,
d6ae7941dcec920d5726d50d1b1cdfe4dde34d35,Avatar digitization from a single image for real-time rendering,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
d691440030394c2e00a2ab47aba4f8b5fca5f25a,Tube ConvNets: Better exploiting motion for action recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
@@ -607,7 +604,7 @@ ec5c63609cf56496715b0eba0e906de3231ad6d1,Private and Scalable Personal Data Anal 42a6beed493c69d5bad99ae47ea76497c8e5fdae,Joint salient object detection and existence prediction,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
425ea5656c7cf57f14781bafed51182b2e6da65f,Structured Kernel Dictionary Learning With Correlation Constraint for Object Recognition,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
89e31777f221ddb3bc9940d7f520c8114c4148a2,Integrating Spectral Kernel Learning and Constraints in Semi-Supervised Classification,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
-89497854eada7e32f06aa8f3c0ceedc0e91ecfef,Deep Context-Sensitive Facial Landmark Detection With Tree-Structured Modeling,"AI Laboratories, Alibaba Group, Hangzhou, China","AI Laboratories, Alibaba Group, Hangzhou, China","Hangzhou, Zhejiang, China",30.27408400,120.15507000,company,
+89497854eada7e32f06aa8f3c0ceedc0e91ecfef,Deep Context-Sensitive Facial Landmark Detection With Tree-Structured Modeling,Alibaba,"AI Laboratories, Alibaba Group, Hangzhou, China","Hangzhou, Zhejiang, China",30.27408400,120.15507000,company,
4551194408383b12db19a22cca5db0f185cced5c,Nonlinear Topological Component Analysis: Application to Age-Invariant Face Recognition,"Center for Development of Advanced Technologies, Algeria","Division of Design of Intelligent Machines, Center for Development of Advanced Technologies, Algiers, Algeria","haouch oukil، Cité 20 aout 1956 Baba Hassen 5 juillet 1962، Alger 16303, Algeria",36.68948700,2.98187700,edu,"Center for Development of Advanced Technologies, Algiers, Algeria"
45e043dffc57a9070f483ac4aec2c5cd2cec22cb,SuperpowerGlass: A Wearable Aid for the At-Home Therapy of Children with Autism,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
452ea180cf4d08d7500fc4bc046fd7141fd3d112,A robust approach to facial ethnicity classification on large scale face databases,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
@@ -836,7 +833,6 @@ ec5c63609cf56496715b0eba0e906de3231ad6d1,Private and Scalable Personal Data Anal 919bdc161485615d5ee571b1585c1eb0539822c8,A ranking model for face alignment with Pseudo Census Transform,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
9166f46aa3e58befaefd3537e5a11b31ebeea4d0,Low-complexity HOG for efficient video saliency,Technische Universitt Darmstadt,"Technische Universitt Darmstadt, Computer Systems Group, Darmstadt, Germany","Hochschulstraße 10, 64289 Darmstadt, Germany",49.87741510,8.65461020,edu,
91f0a95b8eb76e8fa24c8267e4a7a17815fc7a11,Robust facial landmark detection and tracking across poses and expressions for in-the-wild monocular video,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
-918fc4c77a436b8a588f63b2b37420b7868fbbf8,Ocular biometrics: A survey of modalities and fusion approaches,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
657e702326a1cbc561e059476e9be4d417c37795,Face detection based on multi task learning and multi layer feature fusion,"SIASUN Robot and Automation, Shenyang, China","Shenyang SIASUN Robot & Automation Co., LTD., Shenyang, China","Shenyang, Liaoning, China",41.80569900,123.43147200,company,
659dc6aa517645a118b79f0f0273e46ab7b53cd9,Age-invariant face recognition using a feature progressing model,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
6584c3c877400e1689a11ef70133daa86a238602,Supervised Committee of Convolutional Neural Networks in Automated Facial Expression Analysis,Universitat Oberta de Catalunya,Universitat Oberta de Catalunya,"Universitat Oberta de Catalunya, 156, Rambla del Poblenou, Provençals del Poblenou, Sant Martí, Barcelona, BCN, CAT, 08018, España",41.40657415,2.19453410,edu,
@@ -844,7 +840,6 @@ ec5c63609cf56496715b0eba0e906de3231ad6d1,Private and Scalable Personal Data Anal 62fddae74c553ac9e34f511a2957b1614eb4f937,Action Recognition Based on Efficient Deep Feature Learning in the Spatio-Temporal Domain,RheinAhrCampus der Hochschule Koblenz,"RheinAhrCampus der Hochschule Koblenz, Remagen, Germany","RheinAhrCampus, 2, Joseph-Rovan-Allee, Remagen, Landkreis Ahrweiler, Rheinland-Pfalz, 53424, Deutschland",50.57225620,7.25318610,edu,
62750d78e819d745b9200b0c5c35fcae6fb9f404,Leveraging implicit demographic information for face recognition using a multi-expert system,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
62e834114b58a58a2ea2d7b6dd7b0ce657a64317,Adaptive facial feature extraction,Bielefeld University,Bielefeld University,"Fachhochschule Bielefeld FB Gestaltung, 3, Lampingstraße, Mitte, Bielefeld, Regierungsbezirk Detmold, Nordrhein-Westfalen, 33615, Deutschland",52.02804210,8.51148270,edu,
-62f017907e19766c76887209d01d4307be0cc573,Exploring the effect of illumination on automatic expression recognition using the ICT-3DRFE database,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
6267dbeb54889be5bdb50c338a7c6ef82287084c,Face recognition based on 2DPCA and fuzzy-rough technique,"Hebei Information Engineering School, Baoding, China","Teaching and research of section of mathematics, Hebei Information Engineering School, Baoding 071000, China","Lianchi, Baoding, Hebei, China, 071000",38.86371910,115.51483260,edu,
963a004e208ce4bd26fa79a570af61d31651b3c3,Computational methods for modeling facial aging: A survey,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
9635493998ad60764d7bbf883351af57a668d159,Cross-validated smooth multi-instance learning,"Beijing E-Hualu Info Technology Co., Ltd, Beijing, China","Beijing E-Hualu Info Technology Co., Ltd, Beijing, China","165 Fushi Rd, Shijingshan Qu, Beijing Shi, China, 100144",39.92532100,116.19579500,company,
@@ -892,7 +887,6 @@ ec5c63609cf56496715b0eba0e906de3231ad6d1,Private and Scalable Personal Data Anal 5efdf48ca56b78e34dc2f2f0ce107a25793d3fc2,Real-Time 3D Eye Performance Reconstruction for RGBD Cameras,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
5bed2453a5b0c54a4a4a294f29c9658658a9881e,Angular-Similarity-Preserving Binary Signatures for Linear Subspaces,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
5b64584d6b01e66dfd0b6025b2552db1447ccdeb,Deep expectation for estimation of fingerprint orientation fields,"Dermalog Identification Systems, Hamburg, Germany","Dermalog Identification Systems GmbH, Hamburg, Germany","Mittelweg 120, 20148 Hamburg, Germany",53.57227000,9.99472000,company,
-5bfad0355cdb62b22970777d140ea388a7057d4c,Facial expression recognition using radial encoding of local Gabor features and classifier synthesis,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
5b4bbba68053d67d12bd3789286e8a9be88f7b9d,An automatic region based methodology for facial expression recognition,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
37c5e3b6175db9eaadee425dc51bc7ce05b69a4e,RETRACTED ARTICLE: Sparse tensor CCA for color face recognition,Jiangsu University of Science and Technology,Jiangsu University of Science and Technology,"江苏科技大学, 学府路, 京口区, 象山街道, 京口区 (Jingkou), 镇江市 / Zhenjiang, 江苏省, 212000, 中国",32.19805500,119.46326791,edu,
378418fdd28f9022b02857ef7dbab6b0b9a02dbe,Intelligent Information and Database Systems,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
@@ -955,7 +949,6 @@ ec5c63609cf56496715b0eba0e906de3231ad6d1,Private and Scalable Personal Data Anal 972b1a7ef8cc9c83c2c6d8d126f94f27b567d7d0,Artificial Neural Networks in Pattern Recognition,University of Siena,University of Siena,"大學 University, 澤祥街 Chak Cheung Street, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.41338620,114.21005800,edu,
978b32ff990d636f7e2050bb05b8df7dfcbb42a1,Age invariant face recognition based on texture embedded discriminative graph model,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
9729930ab0f9cbcd07f1105bc69c540330cda50a,Compressing Fisher Vector for Robust Face Recognition,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
-63c74794aedb40dd6b1650352a2da7a968180302,Recurrent neural network for facial landmark detection,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
635d2696aa597a278dd6563f079be06aa76a33c0,Age estimation via fusion of multiple binary age grouping systems,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
6343bc0013343b6a5f96154f02d18dcd36a3f74c,Compressed domain human action recognition in H.264/AVC video streams,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
6316a4b689706b0f01b40f9a3cef47b92bc52411,Rotation-Invariant Neoperceptron,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
@@ -1021,7 +1014,6 @@ b8f64a94f536b46ef34a0223272e02f9be785ef9,An face-based visual fixation system fo b14e3fe0d320c0d7c09154840250d70bc88bb6c0,The Role of Featural and Configural Information in Face Classification A Simulation of the Expertise Hypothesis,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
b161d261fabb507803a9e5834571d56a3b87d147,Gender recognition from face images using a geometric descriptor,University of Campinas (UNICAMP),"Institute of Computing, University of Campinas (UNICAMP), Campinas, SP, 13083-852, Brazil","Universidade Estadual de Campinas - Av. Albert Einstein, 1251 - Cidade Universitária, Campinas - SP, 13083-852, Brazil",-22.81483740,-47.06477080,edu,
b1efefcc9a5d30be90776571a6cc0071f3679753,BRoPH: A compact and efficient binary 3D feature descriptor,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
-b1bb517bd87a1212174033fc786b2237844b04e6,Cumulative attribute relation regularization learning for human age estimation,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
b11b71b704629357fe13ed97b216b9554b0e7463,ASCERTAIN: Emotion and Personality Recognition Using Commercial Sensors,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
b1534888673e6119f324082246016d28eba249aa,Saliency-based navigation in omnidirectional image,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
ddd0f1c53f76d7fc20e11b7e33bbdc0437516d2b,Deep learning-based learning to rank with ties for image re-ranking,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
@@ -1134,7 +1126,6 @@ e1449be4951ba7519945cd1ad50656c3516113da,Local Gradient Hexa Pattern: A Descript cdf0dc4e06d56259f6c621741b1ada5c88963c6d,Makeup-insensitive face recognition by facial depth reconstruction and Gabor filter bank from women's real-world images,Semnan University,Semnan University,"دانشگاه سمنان, بزرگراه امام رضا, شهرک مسکن مهر مصلی, ناسار, سمنان, بخش مرکزی, شهرستان سمنان, استان سمنان, ایران",35.60374440,53.43445877,edu,
cd85f71907f1c27349947690b48bfb84e44a3db0,Visual Pattern Discovery and Recognition,Chongqing University,Chongqing University,"重庆工商大学, 19, 翠林路, 重庆市, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400067, 中国",29.50841740,106.57858552,edu,
cdfa7dccbc9e9d466f8a5847004973a33c7fcc89,Multiple Subcategories Parts-Based Representation for One Sample Face Identification,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
-cd3b713722ccb1e2ae3b050837ca296b2a2dd82a,Kernel dictionary learning based discriminant analysis,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
cd2f8d661ea2c6d6818a278eb4f0548751c3b1ae,Improving CNN Performance Accuracies With Min–Max Objective,Xi'an Jiaotong University,Xi'an Jiaotong University,"西安交通大学兴庆校区, 文治路, 乐居场, 碑林区 (Beilin), 西安市, 陕西省, 710048, 中国",34.24749490,108.97898751,edu,
ccb95192001b07bb25fc924587f9682b0df3de8e,Head pose estimation for recognizing face images using collaborative representation based classification,"IIEST Shibpur, India","Computer Science and Technology, IIEST, Shibpur","P.O. - Botanic Garden, Howrah, West Bengal 711103, India",22.55518080,88.30713790,edu,
cc70fb1ab585378c79a2ab94776723e597afe379,Detect face in the wild using CNN cascade with feature aggregation at multi-resolution,Swansea University,Swansea University,"Swansea University, University Footbridge, Sketty, Swansea, Wales, SA2 8PZ, UK",51.60915780,-3.97934429,edu,
@@ -1219,7 +1210,6 @@ e75a589ca27dc4f05c2715b9d54206dee37af266,Multiscale Deep Alternative Neural Netw e73f2839fc232c03e9f027c78bc419ee15810fe8,Flexible 3D neighborhood cascade deformable part models for object detection,"University of Science, Vietnam","Fac. of Mathematics and Computer Sciences, University of Science, Ho Chi Minh City, Viet Nam","227 Đường Nguyễn Văn Cừ, Phường 4, Quận 5, Hồ Chí Minh, Vietnam",10.76241650,106.68120130,edu,
e790a2538579c8e2ef9b314962ab26197d6664c6,A jointly local structured sparse deep learning network for face recognition,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
e7e8c0bbee09b5af6f7df1de8f0f26da992737c4,Autoassociative Pyramidal Neural Network for face verification,University of Pernambuco,"University of Pernambuco, Recife-PE, Brazil","Av. Gov. Agamenon Magalhães - Santo Amaro, Recife - PE, 50100-010, Brazil",-8.04406030,-34.88611670,edu,
-cbbd9880fb28bef4e33da418a3795477d3a1616e,Multi-class Support Vector Machine classifiers using intrinsic and penalty graphs,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
cb992fe67f0d4025e876161bfd2dda467eaec741,Random forest-based feature selection for emotion recognition,"University of Orléans, France","Univ. Orléans, INSA CVL, PRISME EA 4229, Bourges, France","Château de la Source, 45100 Orléans, France",47.84457440,1.93369650,edu,
cbc2de9b919bc63590b6ee2dfd9dda134af45286,Direct face detection and video reconstruction from event cameras,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
cbf3e848c5d2130dd640d9bd546403b8d78ce0f9,Local linear discriminant analysis with composite kernel for face recognition,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
@@ -1315,7 +1305,6 @@ e03f69bad7e6537794a50a99da807c9df4ff5186,Unsupervised method of Domain Adaptatio 239e305c24155add73f2a0ba5ccbd66b37f77e14,Fast computation of low-rank matrix approximations,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
23e824d1dfc33f3780dd18076284f07bd99f1c43,Spoofing faces using makeup: An investigative study,INRIA Méditerranée,"Inria Méditerranée, France","2004 Route des Lucioles, 06902 Valbonne, France",43.61581310,7.06838000,edu,"Inria Méditerranée, France"
2340d810c515dc0c9fd319f598fa8012dc0368a0,A collaborative face recognition framework on a social network platform,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
-239958d6778643101ab631ec354ea1bc4d33e7e0,Head pose estimation in the wild using Convolutional Neural Networks and adaptive gradient methods,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
4f03ba35440436cfa06a2ed2a571fea01cb36598,The extended collaborative representation-based classification,"Artificial Intelligence Key Laboratory of Sichuan Province, China","Artificial Intelligence Key Laboratory, of Sichuan Province, Zigong, Sichuan, 643000, P. R. China","Ziliujing, Zigong, Sichuan, China, 643000",29.33909180,104.77858020,gov,
4f1249369127cc2e2894f6b2f1052d399794919a,Deep Age Estimation: From Classification to Ranking,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
8dd3f05071fd70fb1c349460b526b0e69dcc65bf,Local Directional Ternary Pattern for Facial Expression Recognition,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
@@ -1356,7 +1345,6 @@ e03f69bad7e6537794a50a99da807c9df4ff5186,Unsupervised method of Domain Adaptatio 7196b3832065aec49859c61318037b0c8c12363a,Probabilistic modeling of scenes using object frames,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
7644b3a0871b8e0e7e1cdf06099e295f1e5fbdf7,Graph Maximum Margin Criterion for Face Recognition,Anhui Polytechnic University,Anhui Polytechnic University,"安徽工程大学, 鸠江北路, 芜湖市, 芜湖市区, 芜湖市 / Wuhu, 安徽省, 241000, 中国",31.34185955,118.40739712,edu,
76669f166ddd3fb830dbaacb3daa875cfedc24d9,Learning face recognition from limited training data using deep neural networks,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
-76dff7008d9b8bf44ec5348f294d5518877c6182,Discrete area filters in accurate detection of faces and facial features,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
76640cb1a683a479ce2e0d6681d821ff39126d63,Innovative embodiment of job interview in emotionally aware communication robot,"NEC Corporation, Nara, Japan","C & C Innovation Research Labs, NEC Corporation, Nara, Japan","Nara, Nara Prefecture, Japan",34.68508690,135.80500020,edu,
1c25a3c8ef3e2c4dbff337aa727d13f5eba40fb2,Artistic stylization of face photos based on a single exemplar,Memorial University of Newfoundland,Memorial University of Newfoundland,"Memorial University of Newfoundland, Overpass, St. John's, Newfoundland and Labrador, A1B 5S7, Canada",47.57272510,-52.73305444,edu,
1c0acf9c2f2c43be47b34acbd4e7338de360e555,A Multi-Camera Deep Neural Network for Detecting Elevated Alertness in Drivers,Toyota Research Institute,Toyota Research Institute,"Toyota Research Institute, 4440, West El Camino Real, Los Altos, Santa Clara County, California, 94022, USA",37.40253645,-122.11655107,edu,
@@ -1438,6 +1426,5 @@ e03f69bad7e6537794a50a99da807c9df4ff5186,Unsupervised method of Domain Adaptatio 22e121a8dea49e3042de305574356477ecacadda,Directional gradients integration image for illumination insensitive face representation,Hunan University,Hunan University,"Yejin University for Employees, 冶金西路, 和平乡, 珠晖区, 衡阳市 / Hengyang, 湖南省, 中国",26.88111275,112.62850666,edu,
250b73ec5a4f78b7b4ea3aba65c27fc1352154d5,Constrained Multi-View Video Face Clustering,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
256b46b12ab47283e6ada05fad6a2b501de35323,Pose estimation using Spectral and Singular Value recomposition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
-2546dc7e2c2390233de16502413fe1097ecf3fb5,An empirical evaluation on dimensionality reduction schemes for dissimilarity-based classifications,Myongji University,Myongji University,"명지대, 금학로, 역북동, 처인구, 용인시, 경기, 17144, 대한민국",37.23810230,127.19034310,edu,
258b3b1df82186dd76064ef86b28555e91389b73,Initial Shape Pool Construction for Facial Landmark Localization Under Occlusion,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
2564920d6976be68bb22e299b0b8098090bbf259,Face recognition algorithm based on cascading BGP feature fusion,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
diff --git a/scraper/reports/doi_institutions_unknown.csv b/scraper/reports/doi_institutions_unknown.csv index e1a509d9..bc3bc41c 100644 --- a/scraper/reports/doi_institutions_unknown.csv +++ b/scraper/reports/doi_institutions_unknown.csv @@ -5,7 +5,6 @@ 0d9815f62498db21f06ee0a9cc8b166acc93888e,Image recognition system based on novel measures of image similarity and cluster validity,c
0d9815f62498db21f06ee0a9cc8b166acc93888e,Image recognition system based on novel measures of image similarity and cluster validity,d
0d9815f62498db21f06ee0a9cc8b166acc93888e,Image recognition system based on novel measures of image similarity and cluster validity,e
-0d7652652c742149d925c4fb5c851f7c17382ab8,A fast and efficient pre-training method based on layer-by-layer maximum discrimination for deep neural networks,"Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Hafez Ave., Tehran, Iran"
0da3c329ae14a4032b3ba38d4ea808cf6d115c4a,Discriminant feature extraction for image recognition using complete robust maximum margin criterion,"Department of Computer Science, Minjiang University, Fuzhou, People’s Republic of China"
0d75c7d9a00f859cffe7d0bd78dd35d0b4bc7fa6,Active differential CMOS imaging device for human face recognition,"Inst. Nat. des Telecommun., Evry, France"
0d98750028ea7b84b86e6fec3e67d61e4f690d09,Large-scale subspace clustering using random sketching and validation,"Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA"
@@ -40,7 +39,6 @@ 3bcb93aa2a5e5eda039679516292af2f7c0ff9ac,Terrain classification of hyperspectral remote sensing images based on kernel maximum margin criterion,"School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an, China"
3bdaf59665e6effe323a1b61308bcac2da4c1b73,2D spherical spaces for objects recognition under harsh lighting conditions,"Faculty of Engineering Science, Department of Systems Innovation, Arai Laboratory at Osaka University, Japan"
3bf579baf0903ee4d4180a29739bf05cbe8f4a74,Facial Expression Biometrics Using Tracker Displacement Features,"Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. tulyakov@cedar.buffalo.edu"
-6f74c3885b684e52096497b811692bd766071530,Low-rank representation with local constraint for graph construction,"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian, University, Xi'an 710071, China"
6f22324fab61fbc5df1aac2c0c9c497e0a7db608,Volume structured ordinal features with background similarity measure for video face recognition,"Advanced Technologies Application Center 7a #21406 b/ 214 and 216, P.C. 12200, Siboney Playa, Havana, Cuba"
6ff0f804b8412a50ae2beea5cd020c94a5de5764,Measuring sample distortions in face recognition,"Sapienza Università di Roma, Roma, Italy"
6ff0f804b8412a50ae2beea5cd020c94a5de5764,Measuring sample distortions in face recognition,"Università di Salerno, Fisciano (SA), Italy"
@@ -48,7 +46,6 @@ 9b4b2a575641f3a7f8a5ce28b6a06c36694a9ddf,A lighting robust fitting approach of 3D morphable model for face reconstruction,"Insititute of Automation, Chinese Academy of Sciences (CAS), Beijing, China"
9b9f6e5eb6d7fa50300d67502e8fda1006594b84,Learning to Recognise Unseen Classes by A Few Similes,"University of Sheffield, Sheffield, United Kingdom"
9b8830655d4a5a837e3ffe835d14d6d71932a4f2,Multiview Face Recognition: From TensorFace to V-TensorFace and K-TensorFace,"Department of Computer Science, University of Texas, San Antonio, TX, USA"
-9b1a70d6771547cbcf6ba646f8775614c0162aca,Combining feature extraction and expansion to improve classification based similarity learning,"Departament d’Informática, Universitat de Valéncia, Av. de la Universitat s/n, 46100-Burjassot, Spain"
9e5690cdb4dfa30d98dff653be459e1c270cde7f,Multiple path search for action tube detection in videos,Department of Electronic and Computer Engineering National Taiwan University of Science and Technology
9e5809122c0880183c7e42c7edd997f92de6d81e,Eye corner detector robust to shape and illumination changes,"Fujitsu Laboratories, Kawasaki, Kanagawa, Japan"
9e99f818b37d44ec6aac345fb2c5356d83d511c7,Sift-flow registration for facial expression analysis using Gabor wavelets,"University of Montreal, Department of Computer Science and Operations Research (DIRO), 2920 Chemin de la tour, QC, Canada, H3C 3J7"
@@ -248,13 +245,10 @@ eb02daee558e483427ebcf5d1f142f6443a6de6b,The Science and Detection of Tilting,"U ebc2a3e8a510c625353637e8e8f07bd34410228f,Dual Sparse Constrained Cascade Regression for Robust Face Alignment,"B-DAT Laboratory, School of Information and Control, Nanjing University of Information and Technology, Nanjing, China"
ebeb0546efeab2be404c41a94f586c9107952bc3,Multi-cue Augmented Face Clustering,"Tianjin Universtiy, Tianjin, China"
eb8a3948c4be0d23eb7326d27f2271be893b3409,A Probabilistic Approach to People-Centric Photo Selection and Sequencing,"Amazon, Berkshire, U.K."
-c06b13d0ec3f5c43e2782cd22542588e233733c3,Crowdsourcing facial expressions for affective-interaction,"NOVA Laboratory for Computer Science and Informatics, NOVA-LINCS, Departamento de Informática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal"
-eef0be751e9aca7776d83f25c8ffdc1a18201fd8,A dense flow-based framework for real-time object registration under compound motion,f
ee1f9637f372d2eccc447461ef834a9859011ec1,Optimized learning instance-based image retrieval,"College of Information Science & Technology, Hebei Agricultural University, Baoding, China"
ee1f9637f372d2eccc447461ef834a9859011ec1,Optimized learning instance-based image retrieval,"Standards & Metrology Research Institute of CARS, Beijing, China"
ee1f9637f372d2eccc447461ef834a9859011ec1,Optimized learning instance-based image retrieval,"No.1 Senior Middle School of Wendeng District, Weihai, China"
ee1f9637f372d2eccc447461ef834a9859011ec1,Optimized learning instance-based image retrieval,"Lawrence Berkeley National Laboratory, Berkeley, USA"
-eed05da2c0ab7d2b0a3c665a5368efa81b185099,Maximizing Gaussianity using kurtosis measurement in the kernel space for kernel linear discriminant analysis,"Department of Electronics and Communication Engineering, National Institute of Technology Trichy, Trichy 620015, India"
c997744db532767ee757197491d8ac28d10f1c0f,A real-time emotion recognition system for disabled persons,"University of Tunis, The National Higher school of engineers of Tunis (ENSIT), Laboratory of Signal Image and Energy Mastery, LR13ES03 (SIME), Tunis, Tunisia"
c914d2ba06ec3fd1baa0010dcc4d16c7c34fc225,Engineering Applications of Neural Networks,"Dept. of Theoretical Electrical Engineering, Technical University of Sofia, Sofia, Bulgaria"
c914d2ba06ec3fd1baa0010dcc4d16c7c34fc225,Engineering Applications of Neural Networks,"Faculty of Engineering and Computing, Coventry University, UK"
@@ -447,10 +441,9 @@ ecdd83002f69c2ccc644d07abb44dd939542d89d,Linear dimensionality reduction based o 43cbe3522f356fbf07b1ff0def73756391dc3454,Laplacian of smoothed image as representation for face recognition,"School of Computing and Electrical Engineering, IIT Mandi, H.P, 175001, India"
4344ba6e33faaa616d01248368e66799548ca48b,Unsupervised joint face alignment with gradient correlation coefficient,"ICA Laboratory, Grenoble, France"
4344ba6e33faaa616d01248368e66799548ca48b,Unsupervised joint face alignment with gradient correlation coefficient,"Gipsa-Lab, Saint Martin d’Heres, France"
-43bb2b58f906262035ef61e41768375bc8d99ae3,An Approach for Automatic Pain Detection through Facial Expression,"Department of Computer Science & Engineering, Tripura University (A Central University), Suryamaninagar-799022, Tripura, India"
434f1442533754b3098afd4e24abf1e3792b24db,Over-the-shoulder shot detection in art films,"Film Department ELTE University, Budapest, Hungary"
-43c3b6a564b284382fdf8ae33f974f4e7a89600e,An Integrated Signature-Based Framework for Efficient Visual Similarity Detection,"South Valley University, Qena, Egypt"
-43c3b6a564b284382fdf8ae33f974f4e7a89600e,An Integrated Signature-Based Framework for Efficient Visual Similarity Detection,"University of Nottingham (Malaysia Campus), Malaysia"
+43c3b6a564b284382fdf8ae33f974f4e7a89600e,An Integrated Signature-Based Framework for Efficient Visual Similarity Detection and Measurement in Video Shots,"South Valley University, Qena, Egypt"
+43c3b6a564b284382fdf8ae33f974f4e7a89600e,An Integrated Signature-Based Framework for Efficient Visual Similarity Detection and Measurement in Video Shots,"University of Nottingham (Malaysia Campus), Malaysia"
4317856a1458baa427dc00e8ea505d2fc5f118ab,Regularizing face verification nets for pain intensity regression,"Dept. of Electrical & Computer Engineering, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA"
4317856a1458baa427dc00e8ea505d2fc5f118ab,Regularizing face verification nets for pain intensity regression,"Dept. of Radiation Oncology, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA"
4317856a1458baa427dc00e8ea505d2fc5f118ab,Regularizing face verification nets for pain intensity regression,"Dept. of EE, UESTC, 2006 Xiyuan Ave, Chengdu, Sichuan 611731, China"
@@ -458,6 +451,7 @@ ecdd83002f69c2ccc644d07abb44dd939542d89d,Linear dimensionality reduction based o 07dc9f3b34284cc915dea7575f40ef0c04338126,Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition,School of ComputingNational University of Singapore
0701b01bc99bf3b64050690ceadb58a8800e81ed,Facial expression recognition through modeling age-related spatial patterns,"Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology, University of Science and Technology of China Hefei, Anhui, People’s Republic of China"
0701b01bc99bf3b64050690ceadb58a8800e81ed,Facial expression recognition through modeling age-related spatial patterns,"Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute Troy, Troy, USA"
+383ff2d66fecdc2fd02a31ac1fa392f48e578296,An efficient multimodal 2D + 3D feature-based approach to automatic facial expression recognition,f
008528d5e27919ee95c311266041e4fb1711c254,User-adaptive image retrieval via fusing pointwise and pairwise labels,"Alibaba Group, Zhejiang, People’s Republic of China"
00d4c2db10f3a32d505d7b8adc7179e421443dec,Data driven adaptation for QoS aware embedded vision systems,"Computer Science and Engineering, Pennsylvania State University, PA, USA SiliconScapes, LLC, PA, USA"
003ba2001bd2614d309d6ec15e9e2cbe86db03a1,A novel post-nonlinear ICA-based reflectance model for 3D surface reconstruction,"Dept. of Inf. Network Technol., Hsiuping Inst. of Technol., Taichung, Taiwan"
@@ -745,7 +739,6 @@ cb9921d5fc4ffa50be537332e111f03d74622442,Face Occlusion Detection Using Cascaded f812347d46035d786de40c165a158160bb2988f0,Predictive coding as a model of cognition,"Department of Informatics, King’s College London, Strand, London, UK"
f8fe1b57347cdcbea755722bf1ae85c4b26f3e5c,OptiFuzz: a robust illumination invariant face recognition system and its implementation,"Toyohashi University of Technology, Toyohashi, Japan"
f834c50e249c9796eb7f03da7459b71205dc0737,Enhanced Patterns of Oriented Edge Magnitudes for Face Recognition and Image Matching,"GIPSA Laboratory, Image and Signal Department, Grenoble Institute of Technology, Grenoble, France"
-ce3304119ba6391cb6bb25c4b3dff79164df9ac6,Real-time facial action unit intensity prediction with regularized metric learning,"Sorbonne Universités, UPMC Univ Paris 06, CNRS UMR 7222, Institut des Systèmes Intelligents et de Robotique (ISIR), 4 place Jussieu, 75005 Paris, France"
cea2911ccabab40e9c1e5bcc0aa1127cab0c789f,Siamese multi-layer perceptrons for dimensionality reduction and face identification,"University of Lyon, LIRIS - CNRS, National Institute of Applied Sciences (INSA), Lyon, France"
cec8936d97dea2fcf04f175d3facaaeb65e574bf,Large-Scale Video Classification with Elastic Streaming Sequential Data Processing System,"Shanghai Advanced Research Institute, CAS & Qiniu AI Lab, Shanghai, China"
cec8936d97dea2fcf04f175d3facaaeb65e574bf,Large-Scale Video Classification with Elastic Streaming Sequential Data Processing System,"Shanghai Advanced Research Institute, CAS, Shanghai, China"
@@ -765,10 +758,8 @@ e0423788eb91772de9d708a17799179cf3230d63,Age Classification Using an Optimized C 1bcb1c6d6cebc9737f9933fcefbf3da8a612f994,A novel Monogenic Directional Pattern (MDP) and pseudo-Voigt kernel for facilitating the identification of facial emotions,"Department of CSE, Regional Campus of Anna University, Tirunelveli 627007, India"
7782627fa2e545276996ff9e9a1686ac496df081,Enhanced Autocorrelation in Real World Emotion Recognition,"University of Ulm, Ulm, Germany"
77c3574a020757769b2ca807ff4b95a88eaa2a37,Computerized Face Recognition in Renaissance Portrait Art: A quantitative measure for identifying uncertain subjects in ancient portraits,"Department of Electrical Engineering, University of California, Riverside, Riverside CA, California 92521 United States"
-48a6a1c6a0ac5f2b7912b3ccb40b0c07f62ddfdf,Event-enabled intelligent asset selection and grouping for photobook creation,"Kodak Alaris Inc., Rochester, NY 14615, USA"
4848a48a2b8bacd2092e87961cd86818da8e7151,Comparative evaluation of facial fiducial point detection approaches,"Department of Systems and Computing, Federal University of Campina Grande, Av. Apríigio Veloso, 882, 58429-900 Campina Grande, PB, Brazil"
480ccd25cb2a851745f5e6e95d33edb703efb49e,Cross-Modal Message Passing for Two-Stream Fusion,"School of Computer Science, Center for Optical Imagery Analysis and Learning (OPTIMAL)"
-70769def1284fe88fd57a477cde8a9c9a3dff13f,Adaptive feature representation for robust face recognition using context-aware approach,"Department of Computer Science and Engineering, Inha University, 253, Yong-Hyun Dong, Nam-Gu, Incheon, South Korea"
7081958a390d3033f5f33e22bbfec7055ea8d601,Learning Distributions of Image Features by Interactive Fuzzy Lattice Reasoning in Pattern Recognition Applications,"Dept of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Kavala, Greece"
70d8bda4aafb0272ac4b93cd43e2448446b8e94d,Using SVM to design facial expression recognition for shape and texture features,"Department of Information Management, National Formosa University, Huwei, Yulin 632, Taiwan"
1eb1fdc5c933d2483ba1acbfa8c457fae87e71e5,Building semantic understanding beyond deep learning from sound and vision,"Dept. de Ciência da Computacão, Universidade Federal de Ouro Preto, MG Brazil"
diff --git a/scraper/reports/doi_institutions_unknown.html b/scraper/reports/doi_institutions_unknown.html index 66292e82..633f482b 100644 --- a/scraper/reports/doi_institutions_unknown.html +++ b/scraper/reports/doi_institutions_unknown.html @@ -1 +1 @@ -<!doctype html><html><head><meta charset='utf-8'><title>Unknown Institutions from DOI</title><link rel='stylesheet' href='reports.css'></head><body><h2>Unknown Institutions from DOI</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>NC A&T State University, Greensboro, NC, USA</td><td>6</td></tr><tr><td>School of Information and Software Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, 610054, China P.R.C</td><td>6</td></tr><tr><td>Electronics and Telecommunications Research Institute, Korea</td><td>5</td></tr><tr><td>Asian Institute of Technology (AIT), Pathum Thani 12120, Thailand</td><td>5</td></tr><tr><td>Chonnam National University, Gwangju, Korea</td><td>5</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Durgapur, India</td><td>5</td></tr><tr><td>Chongqing Institute of Green and Intelligent Technology, CAS, Chongqing, 400714</td><td>5</td></tr><tr><td>SIAT at Chinese Academy of Sciences, China</td><td>5</td></tr><tr><td>Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy</td><td>5</td></tr><tr><td>University of Southern California Institute for Creative Technologies, Los Angeles, CA</td><td>5</td></tr><tr><td>Department of Electronics and Telecommunication Engineering, Don Bosco Institute of Technology, Kurla (W), Mumbai, India</td><td>5</td></tr><tr><td>R V College of Engineering, Department of Computer Science and Engineering, Bangalore, India</td><td>5</td></tr><tr><td>Inst. Nat. des Telecommun., Evry, France</td><td>5</td></tr><tr><td>Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering</td><td>4</td></tr><tr><td>Department of Microelectornics and Computer Science, Lodz University of Technology, ul. Wolczanska 221/223, 90-924, Poland</td><td>4</td></tr><tr><td>North China Electric Power University Department of Electronic and Communication Engineering Baoding, Hebei, China</td><td>4</td></tr><tr><td>School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand</td><td>4</td></tr><tr><td>KU Leuven, Leuven, Belgium</td><td>4</td></tr><tr><td>Academia Sinica, Taipei, Taiwan</td><td>4</td></tr><tr><td>LIARA Laboratory, University of Quebec at Chicoutimi (UQAC), Boulevard de l'Université, Chicoutimi (Quebec), Canada</td><td>4</td></tr><tr><td>Dept. of Computing, Curtin University GPO Box U1987, Perth, WA 6845</td><td>4</td></tr><tr><td>NTT Software Innovation Center, Tokyo, Japan</td><td>4</td></tr><tr><td>EECS Department, University of Kansas, Lawrence, KS</td><td>4</td></tr><tr><td>Department of Mathematics and Computer Science University of Basel</td><td>4</td></tr><tr><td>Goa University, India</td><td>4</td></tr><tr><td>Beijing Key Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081, China</td><td>4</td></tr><tr><td>VUB-NPU Joint AVSP Research Lab, Vrije Universiteit Brussel (VUB), Deptartment of Electronics & Informatics (ETRO), Pleinlaan 2, 1050 Brussel, Belgium</td><td>4</td></tr><tr><td>Graduate School of Information Science, Nara Institute of Science and Technology, Takayama-cho 8916-5, Ikoma-shi, Nara, Japan</td><td>4</td></tr><tr><td>Smart Surveillance Interest Group, Department of Computer Science, Universidade Federal de Minas Gerais, Minas Gerais, Brazil</td><td>4</td></tr><tr><td>Shanghai University School of Communication and Information Engineering Shanghai, China</td><td>4</td></tr><tr><td>Microsoft, Redmond, WA, USA</td><td>4</td></tr><tr><td>Computer Science and Engineering, Pennsylvania State University, PA, USA SiliconScapes, LLC, PA, USA</td><td>4</td></tr><tr><td>Dept. of Computer Engineering, Keimyung University, Daegu, Korea</td><td>4</td></tr><tr><td>National ICT Australia and UNSW, Sydney, Australia</td><td>4</td></tr><tr><td>Department of Electrical and Computer Engineering, Beckman Institute Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, IL, USA</td><td>4</td></tr><tr><td>Universiti Kuala Lumpur, Kuala Lumpur</td><td>4</td></tr><tr><td>Beijing Normal Univeristy, Beijing, China</td><td>4</td></tr><tr><td>University of Tunis, The National Higher school of engineers of Tunis (ENSIT), Laboratory of Signal Image and Energy Mastery, LR13ES03 (SIME), Tunis, Tunisia</td><td>4</td></tr><tr><td>Media Technology Lab, Huawei Technologies Co., Ltd</td><td>4</td></tr><tr><td>Department of Computer Graphics and Multimedia, University of Brno, Brno, Czech Republic</td><td>4</td></tr><tr><td>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA</td><td>4</td></tr><tr><td>Faculty of Engineering, Ain Shams University, Computer and Systems Engineering Department, Cairo, Egypt</td><td>4</td></tr><tr><td>School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, China</td><td>4</td></tr><tr><td>Computer Science and Engineering Dept., University of Nevada Reno, USA</td><td>4</td></tr><tr><td>Department of Information and Control, B-DAT Laboratory, Nanjing University of Information and Technology, Nanjing, China</td><td>4</td></tr><tr><td>Inha University, South Korea</td><td>4</td></tr><tr><td>Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China</td><td>4</td></tr><tr><td>Institute for Human-Machine Communication, Technische Universität München, Germany</td><td>4</td></tr><tr><td>Faculty of Engineering Science, Department of Systems Innovation, Arai Laboratory at Osaka University, Japan</td><td>4</td></tr><tr><td>NTT Corporation, Atsugi, Japan</td><td>3</td></tr><tr><td>Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beersheba, Israel</td><td>3</td></tr><tr><td>Intel Labs China, Beijing, China</td><td>3</td></tr><tr><td>School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun, CO 130012 China</td><td>3</td></tr><tr><td>Radboud University, Nijmegen, Netherlands</td><td>3</td></tr><tr><td>Algılayıcılar, Görüntü ve Sinyal İşleme Grubu, HAVELSAN A.Ş. Ankara, Türkiye</td><td>3</td></tr><tr><td>Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany</td><td>3</td></tr><tr><td>School of Electrical and Computer Engineering, Royal Melbourne Institute of Technology University , Melbourne, Australia</td><td>3</td></tr><tr><td>School of Engineering, University of Baja California, Tijuana, México</td><td>3</td></tr><tr><td>School of Computer Science, Center for Optical Imagery Analysis and Learning (OPTIMAL)</td><td>3</td></tr><tr><td>Department of Systems and Computing, Federal University of Campina Grande, Av. Apríigio Veloso, 882, 58429-900 Campina Grande, PB, Brazil</td><td>3</td></tr><tr><td>R&D Centre Algoritmi, School of Engineering, University of Minho, Portugal</td><td>3</td></tr><tr><td>Department of Control and Computer Engineering, Politecnico di Torino, Italy</td><td>3</td></tr><tr><td>Center for Research in Intelligent Systems, University of California, Riverside Riverside, CA 92521-0425, USA</td><td>3</td></tr><tr><td>Shanghai Advanced Research Institute, CAS, Shanghai, China</td><td>3</td></tr><tr><td>Department of electronic engineering, Key Lab of Intelligent Perception and Image Understanding of Ministry of Education, Xi'an, China</td><td>3</td></tr><tr><td>Computer Vision Laboratory, ETH Zurich, Sternwartstrasse 7, 8092, Switzerland</td><td>3</td></tr><tr><td>BITS Pilani, Pilani , India</td><td>3</td></tr><tr><td>Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, Howrah-711 103, India</td><td>3</td></tr><tr><td>Dept. of CS&E, IIT Madras, India</td><td>3</td></tr><tr><td>Graduate School of System Design Tokyo Metropolitan University Tokyo, Japan</td><td>3</td></tr><tr><td>Face Aging Group, Computer Science Department, UNCW, USA</td><td>3</td></tr><tr><td>City University of New York, New York, NY, USA</td><td>3</td></tr><tr><td>Department of Computer Science and Engineering, Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India</td><td>3</td></tr><tr><td>Ghent University, Ghent, Belgium</td><td>3</td></tr><tr><td>Columbia Univeristy, New York, NY, USA</td><td>3</td></tr><tr><td>Microsoft Research Cambridge</td><td>3</td></tr><tr><td>Center for Automation Research, UMIACS University of Maryland, College Park, MD 20742</td><td>3</td></tr><tr><td>School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, U.K.</td><td>3</td></tr><tr><td>School of Information and Communication Engineering, Beijing University of Posts and Telcommunications, Beijing, China</td><td>3</td></tr><tr><td>Gwangju Institute of Science and Technology, 123, Cheomdangwagi-ro, Buk-gu, Gwangju, South Korea</td><td>3</td></tr><tr><td>Institute of Mathematical and Computer Sciences, University of Sao Paulo, Sao Paulo, Brazil</td><td>3</td></tr><tr><td>Dept. of Informatics, Aristotle Univ. of Thessaloniki, Greece</td><td>3</td></tr><tr><td>NTT Media Intelligence Laboratories, Tokyo, Japan</td><td>3</td></tr><tr><td>Beijing Institute of Graphic Communication, Beijing</td><td>3</td></tr><tr><td>Nara Institute of Science and Technology, Japan</td><td>3</td></tr><tr><td>Department of Computer, the University of Suwon, Korea</td><td>3</td></tr><tr><td>Department of Electrical and Computer Engineering, Florida Institute of Technology, Melbourne, USA</td><td>3</td></tr><tr><td>Dept. of Computer Science and Engineering, St. Joseph's College of Engineering and Technology, Palai, Kerala, India</td><td>3</td></tr><tr><td>Dept. of Computer Science and Electrical Engineering, University of Missouri-Kansas City, MO, USA</td><td>3</td></tr><tr><td>Inha University, Incheon, South Korea</td><td>3</td></tr><tr><td>Center for Research on Intelligent Perception and Computing</td><td>3</td></tr><tr><td>Thiagarajar College of Engineering, Madurai, Tamilnadu, India</td><td>3</td></tr><tr><td>Dept. of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan</td><td>3</td></tr><tr><td>School of Electrical and Electronic Engineering, Singapore</td><td>3</td></tr><tr><td>Universidade Nova Lisboa, Lisboa, Portugal</td><td>3</td></tr><tr><td>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation Chinese Academy of Sciences, Beijing, China 100190</td><td>3</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology Uttarakhand, Srinagar Garhwal, India</td><td>3</td></tr><tr><td>Dept. of Mediamatics, Delft Univ. of Technol., Netherlands</td><td>3</td></tr><tr><td>Department of Information Science and Engineering, Changzhou University, Changzhou, China</td><td>3</td></tr><tr><td>Institute for Infocomm Research, A*STAR, Singapore, Singapore</td><td>3</td></tr><tr><td>Ashikaga Institute of Technology, Ashikaga, Japan</td><td>3</td></tr><tr><td>Institute of Applied Computer Science, Kiel University of Applied Sciences, Kiel, Germany</td><td>3</td></tr><tr><td>Central China Normal University, Wuhan, China</td><td>3</td></tr><tr><td>Chongqing University of Posts and Telecommunications Chongqing, China</td><td>3</td></tr><tr><td>School of Computer Science and Software Engineering University of Wollongong, Australia</td><td>3</td></tr><tr><td>Phonexia, Brno-Krlovo Pole, Czech Republic</td><td>3</td></tr><tr><td>Department of Applied Mechanics, Chalmers University of Technology, SE-412 96 Göteborg, Sweden</td><td>3</td></tr><tr><td>Technische Universität München, Munich, Germany</td><td>3</td></tr><tr><td>University of California, Los Angeles, CA Dept. of Electrical Engineering</td><td>3</td></tr><tr><td>Academia Sinica, Taipei, Taiwan Roc</td><td>3</td></tr><tr><td>Dept. of Cybernetics and Artificial Intelligence, FEI TU of Košice, Slovak Republic</td><td>3</td></tr><tr><td>Image and Video Systems Lab, School of Electrical Engineering, KAIST, Republic of Korea</td><td>3</td></tr><tr><td>Information and media processing laboratories, NEC Corporation</td><td>3</td></tr><tr><td>Southern Illinois University at Carbondale, IL, USA</td><td>3</td></tr><tr><td>School of Automation and Electrical Engineering, University of Science and Technology Beijing, 100083, China</td><td>3</td></tr><tr><td>School of Software, Jiangxi Normal University, Nanchang, China</td><td>3</td></tr><tr><td>Department of Computer Science, Pontificia Universidad Cato´lica de Chile</td><td>3</td></tr><tr><td>Fujitsu Laboratories, Kawasaki, Kanagawa, Japan</td><td>3</td></tr><tr><td>Department of Electronic and Computer Engineering National Taiwan University of Science and Technology</td><td>3</td></tr><tr><td>New York University Abu Dhabi & NYU Tandon School of Engineering, Abu Dhabi, Uae</td><td>3</td></tr><tr><td>Intelligent Vision Research Lab, Department of Computer Science, Federal University of Bahia</td><td>3</td></tr><tr><td>Department of Electronic Measuring systems, Moscow Engineering Physics Institute, National Research Nuclear University MEPhI, Moscow, Russia</td><td>3</td></tr><tr><td>National Ilan University, Ilan, Taiwan Roc</td><td>2</td></tr><tr><td>China Electronics Standardization Institute, Beijing, 100007</td><td>2</td></tr><tr><td>Universidade Nova de Lisboa, Caparica, Portugal</td><td>2</td></tr><tr><td>Universidad Tecnica Federico Santa Maria, Department of Electronic Engineering, Valparaiso, Chile</td><td>2</td></tr><tr><td>Dept. of Comput. Syst., Univ. of Technol., Sydney, NSW, Australia</td><td>2</td></tr><tr><td>Dept. of Comput. Sci., York Univ., UK</td><td>2</td></tr><tr><td>The Australian National University RSCS, ANU, Canberra, Australia</td><td>2</td></tr><tr><td>Dept. of Computer Science, YiLi Normal College, Yining, China 835000</td><td>2</td></tr><tr><td>School of Computing and Communications, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia</td><td>2</td></tr><tr><td>Department of Electrical and Computer Engineering, Singapore</td><td>2</td></tr><tr><td>Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td>Instituto de Telecomunicações & Faculdade de Ciěncias da Universidade do Porto</td><td>2</td></tr><tr><td>Department of Information Management, National Formosa University, Huwei, Yulin 632, Taiwan</td><td>2</td></tr><tr><td>Dept of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Kavala, Greece</td><td>2</td></tr><tr><td>University of Ulm, Ulm, Germany</td><td>2</td></tr><tr><td>Dept. of Eng. Sci., Oxford Univ., UK</td><td>2</td></tr><tr><td>Human-Machines Interaction (HMI) Laboratory, Department of Industrial Informatics, TEI of Kavala, Kavala, Greece</td><td>2</td></tr><tr><td>Dept. of ECE, Maryland Univ., College Park, MD, USA</td><td>2</td></tr><tr><td>Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey</td><td>2</td></tr><tr><td>Electrical & Electronic Engineering Department, Mevlana University Konya, Turkey</td><td>2</td></tr><tr><td>GIPSA Laboratory, Image and Signal Department, Grenoble Institute of Technology, Grenoble, France</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, India</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, National Taiwan Ocean University, No.2, Beining Rd., Keelung 202, Taiwan</td><td>2</td></tr><tr><td>Bilgisayar Mühendisliği Bölümü, Deniz Harp Okulu, İstanbul, Türkiye</td><td>2</td></tr><tr><td>Statistical Machine Intelligence & LEarning, School of Computer Science & Engineering University of Electronic Science and Technology of China, 611731, China</td><td>2</td></tr><tr><td>Masaryk University, Brno, Czech Rep</td><td>2</td></tr><tr><td>Charles University, Prague, Czech Rep</td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada</td><td>2</td></tr><tr><td>Department of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Human Machines Interaction (HMI) Laboratory, 65404 Kavala, Greece</td><td>2</td></tr><tr><td>University of British Columbia Department of Electrical and Computer Engineering</td><td>2</td></tr><tr><td>School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, University of Califonia, San Diego</td><td>2</td></tr><tr><td>University of Missouri Department of Electrical and Computer Engineering Columbia, MO, USA</td><td>2</td></tr><tr><td>Inf. Syst. Dept., Buckingham Univ., UK</td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA</td><td>2</td></tr><tr><td>Department of Computer Science & Engineering, POSTECH, Pohang, Sourth Korea, 37673</td><td>2</td></tr><tr><td>Coursera and Stanford University</td><td>2</td></tr><tr><td>Dept. of Electron. & Inf., Toyota Technol. Inst., Nagoya, Japan</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, POSTECH, Pohang 790-784, Republic of Korea</td><td>2</td></tr><tr><td>Dept. of Comput. Sci., New York State Univ., Binghamton, NY, USA</td><td>2</td></tr><tr><td>Dept. of Electrical Engineering, National Institute of Technology, Rourkela, India 769008</td><td>2</td></tr><tr><td>Department of Computer Science, Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>2</td></tr><tr><td>School of Computer Science and Technology, Tianjin University&Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China</td><td>2</td></tr><tr><td>NPU-VUB Joint AVSP Research Lab, School of Computer Science, Northwestern Polytechnical University (NPU) Shaanxi Key Lab on Speech and Image Information Processing, 127 Youyi Xilu, Xi'an 710072, China</td><td>2</td></tr><tr><td>Research&Advanced Technology Division of SAIC Motor Corporation Limited, Shanghai 201804, P.R China</td><td>2</td></tr><tr><td>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China</td><td>2</td></tr><tr><td>Dept. of Computer Science and Information Engineering, Southern Taiwan University of Science and Technology, Tainan City, Taiwan</td><td>2</td></tr><tr><td>Dept. of Electronics and Telecommunication Engg., KCT's Late G.N. Sapkal college of Engineering, Nashik, India</td><td>2</td></tr><tr><td>Tencent Inc</td><td>2</td></tr><tr><td>Facebook Inc., Menlo Park, CA, USA</td><td>2</td></tr><tr><td>Computational Intelligence Lab, Institute of Informatics and Telecommunications, NCSR Demokritos, Athens, Greece</td><td>2</td></tr><tr><td>Dept. of Electrical Engineering, National Tsing-Hua University, Taiwan</td><td>2</td></tr><tr><td>Department Informatik, Hamburg University of Applied Sciences, Hamburg, Germany</td><td>2</td></tr><tr><td>Department Informatik, Hamburg University of Applied Sciences, Engineering and Computing, University of the West of Scotland</td><td>2</td></tr><tr><td>Elektronik ve Haberleşme Mühendisliği Bölümü, Yıldız Teknik Üniversitesi, İstanbul, Türkiye</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering of Systems, University of Zaragoza, Escuela Universitaria Politécnica de Teruel, Teruel, Spain</td><td>2</td></tr><tr><td>Department of Automation, North-China University of Technology, Beijing, China</td><td>2</td></tr><tr><td>Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia</td><td>2</td></tr><tr><td>Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, P.R. China</td><td>2</td></tr><tr><td>Indian Statistical Insitute, Kolkata 700108</td><td>2</td></tr><tr><td>Centre for Secure Information Technologies, Queen’s University Belfast, Belfast, UK</td><td>2</td></tr><tr><td>Wrocław University of Science and Technology, Wrocław, Poland</td><td>2</td></tr><tr><td>Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi, India</td><td>2</td></tr><tr><td>Department of Electronics and Communication Engineering Malaviya National Institute of Technology Jaipur, Rajasthan, India</td><td>2</td></tr><tr><td>Department of Electrical Engineering Malaviya National Institute of Technology Jaipur, Rajasthan, India</td><td>2</td></tr><tr><td>Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education, Chongqing, China</td><td>2</td></tr><tr><td>Osaka University Health Care Center, Japan</td><td>2</td></tr><tr><td>Shahid Bahonar University of Kerman Computer Engineering Department, Kerman, Iran</td><td>2</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT) & Università di Torino, Genova, Italy</td><td>2</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT) & Università degli Studi di Genova, Genova, Italy</td><td>2</td></tr><tr><td>Norwegian Biometric Laboratory, Norwegian University of Science and Technology (NTNU), Gjøvik, Norway</td><td>2</td></tr><tr><td>Department of Computer Applications, National Institute of Technology, Tiruchirappalli, India</td><td>2</td></tr><tr><td>B. Tech Graduate, ECE, MSIT, C-4 Janakpuri, New Delhi, India</td><td>2</td></tr><tr><td>San Diego State University, San Diego, CA, USA</td><td>2</td></tr><tr><td>MIT, Cambridge, MA, USA</td><td>2</td></tr><tr><td>Dept of Electronics and Communication, Manipal Institute Of Technology, Karnataka, India</td><td>2</td></tr><tr><td>LMU Munich, Germany</td><td>2</td></tr><tr><td>Polytechnic School of Pernambuco, University of Pernambuco, Recife-PE, Brazil</td><td>2</td></tr><tr><td>Başkent University, Ankara, TURKEY</td><td>2</td></tr><tr><td>Department of Electronic and Communication Engineering, Universiti Tenaga Nasional Km 7, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia</td><td>2</td></tr><tr><td>Sunway University, Selangor, Malaysia</td><td>2</td></tr><tr><td>Northwestern Polytechnical University Xian, P. R. China</td><td>2</td></tr><tr><td>Dept. of E & TC Engineering, Maharashtra Institute of Technology, Pune, India</td><td>2</td></tr><tr><td>Dept. of ECE and Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Hong Kong</td><td>2</td></tr><tr><td>School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, 689-798, Korea</td><td>2</td></tr><tr><td>Dept. of Comp. Sci. and Inf. Eng, Chung Hua University, Hsinchu, Taiwan</td><td>2</td></tr><tr><td>Shanghai Jiao Tong University & Alibaba Group, Shanghai, China</td><td>2</td></tr><tr><td>School of Computer Science, Kyungpook National University, Buk-gu, Daegu, The Republic of Korea</td><td>2</td></tr><tr><td>Laboratory LAROSERI, Department of Computer Science, Faculty of Sciences, University of Chouaib Doukkali, El Jadida - Morocco</td><td>2</td></tr><tr><td>Microsoft Research India Pvt. Ltd, Bangalore, Karnataka, India</td><td>2</td></tr><tr><td>Department of Electronics, University of Goa, India</td><td>2</td></tr><tr><td>Department of ECE, National Institute of Technology, Rourkela (Odisha), India</td><td>2</td></tr><tr><td>Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China</td><td>2</td></tr><tr><td>B-DAT Laboratory, School of Information and Control, Nanjing University of Information and Technology, Nanjing, China</td><td>2</td></tr><tr><td>Thales Services, ThereSIS, Palaiseau, France</td><td>2</td></tr><tr><td>School of Electrical and Electronic Engineering, Tianjin University of Technology, China</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, Mepco Schlenk Engineering College, Sivakasi, India</td><td>2</td></tr><tr><td>IIIT Bangalore, India</td><td>2</td></tr><tr><td>Institut de Robòtica i Informàtica Industrial (CSIC-UPC)</td><td>2</td></tr><tr><td>Department of Computer Science, IT: Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>2</td></tr><tr><td>Xinjiang University, Urumqi, China</td><td>2</td></tr><tr><td>School of Computing Science and Engineering, VIT University, Vellore, India</td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA</td><td>2</td></tr><tr><td>GSI Universidad Polit-écnica de Madrid, Madrid, Spain</td><td>2</td></tr><tr><td>Department of Electronic Engineering, Kwangwoon University, Seoul, Republic of Korea</td><td>2</td></tr><tr><td>Dept. of Appl. Phys. & Electron., Umea Univ., Sweden</td><td>2</td></tr><tr><td>Universidade Federal do Paraná, Curitiba, Brazil</td><td>2</td></tr><tr><td>Università degli Studi di Verona, Verona, Italy</td><td>2</td></tr><tr><td>CEA, Gif-Sur-Yvette, France</td><td>2</td></tr><tr><td>UMR CNRS - Univ. Bourgogne, Dijon, France</td><td>2</td></tr><tr><td>Mechatronic Engineering Department, Mevlana University, Konya, Turkey</td><td>2</td></tr><tr><td>TÜBİITAK-BİILGEM-UEKAE, Anibal Cad., P.K.74, 41470, Gebze-KOCAELİ, Turkey</td><td>2</td></tr><tr><td>The 28th Research Institute of China Electronics Technology Group Corporation, China</td><td>2</td></tr><tr><td>Raytheon BBN Technologies, 10 Moulton St, Cambridge, MA</td><td>2</td></tr><tr><td>School of Electrical Engineering and Computer Science at the University of Newcastle, Callaghan, NSW 2308, Australia</td><td>2</td></tr><tr><td>Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India</td><td>2</td></tr><tr><td>Pontifícia Universidade Católica do RS, Porto Alegre-RS, Brazil</td><td>2</td></tr><tr><td>Waseda University The Graduate School of Information, Production and Systems 2-7, Hibikino, Wakamatsu-ku, Kitakyushu-shi, Fukuoka, Japan</td><td>2</td></tr><tr><td>Majority Report, France</td><td>2</td></tr><tr><td>SITI Laboratory, National Engineering School of Tunis (ENIT), University of Tunis El Manar, Tunis, Tunisia</td><td>2</td></tr><tr><td>University of Montreal, Department of Computer Science and Operations Research (DIRO), 2920 Chemin de la tour, QC, Canada, H3C 3J7</td><td>2</td></tr><tr><td>Università di Salerno, Fisciano (SA), Italy</td><td>2</td></tr><tr><td>Advanced Technologies Application Center 7a #21406 b/ 214 and 216, P.C. 12200, Siboney Playa, Havana, Cuba</td><td>2</td></tr><tr><td>School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an, China</td><td>2</td></tr><tr><td>Department of Sciences and Information Technology, University of Sassari, Viale Mancini 5, 07100 Sassari, Italy</td><td>2</td></tr><tr><td>Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany</td><td>2</td></tr><tr><td>Department of Computer Science and Information Engineering, National Formosa University, Yunlin 632, Taiwan</td><td>2</td></tr><tr><td>Broadcasting & Telecommunications, Convergence Media Research Department, Electronics and Telecommunications Research Institute, Daejeon, Korea</td><td>2</td></tr><tr><td>Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td>FMV IŞIK Üniversitesi, Şile, Istanbul</td><td>2</td></tr><tr><td>Lehrstuhl für Mustererkennung, FAU Erlangen – Nürnberg, Erlangen, Germany</td><td>1</td></tr><tr><td>Nanjing University of Posts and Telecommunications, China</td><td>1</td></tr><tr><td>Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung, Taiwan</td><td>1</td></tr><tr><td>Laboratoire d’interprétation et de traitement d’images et vidéo, Polytechnique Montréal, Montreal, Canada</td><td>1</td></tr><tr><td>Laboratoire d’imagerie de vision et d’intelligence artificielle, École de technologie supérieure, Université du Québec, Montreal, Canada</td><td>1</td></tr><tr><td>University of Bern, Bern, Switzerland</td><td>1</td></tr><tr><td>School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, PR China</td><td>1</td></tr><tr><td>Department of Computer Science, University of California at Davis, Davis, USA</td><td>1</td></tr><tr><td>Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Shri Shankaracharya Technical Campus, Bhilai, District-Durg, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi, India</td><td>1</td></tr><tr><td>College of Artificial Intelligenge and Big Data, ChongQing University of Electronic Engineering, Chongqing, China</td><td>1</td></tr><tr><td>Laboratoire Jean Kuntzmann, Grenoble, France</td><td>1</td></tr><tr><td>Dept. of Advanced Technologies, Alcorn State University, MS, USA</td><td>1</td></tr><tr><td>Department of Industrial Design, Tatung University, Taipei 104, Republic of China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Tatung University, Taipei 104, Republic of China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Yangzhou University, Yangzhou, People’s Republic of China</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Nanjing University of Science & Technology, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td>School of Information Engineering, Yangzhou University, Yangzhou, China</td><td>1</td></tr><tr><td>Res. Center for Learning Sci., Southeast Univ., Jiangsu, China</td><td>1</td></tr><tr><td>Eedoo Inc, Beijing, China</td><td>1</td></tr><tr><td>CSE, SUNY at Buffalo, USA and Southeast University, China</td><td>1</td></tr><tr><td>School of Information Technology and Engineering, VIT University, Vellore, India</td><td>1</td></tr><tr><td>Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881</td><td>1</td></tr><tr><td>Vulcan Inc, Seattle, WA 98104</td><td>1</td></tr><tr><td>Dept. of Computing, Curtin University of Technology, WA 6102, USA</td><td>1</td></tr><tr><td>School of Software, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td>University of California, Santa Cruz & Ghent University, Santa Cruz, CA, USA</td><td>1</td></tr><tr><td>Computer Vision Research lab, Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran</td><td>1</td></tr><tr><td>HAN University of Applied Sciences, Arnhem, Netherlands</td><td>1</td></tr><tr><td>Faculty of Information Technology, Barrett Hodgson University, Karachi, Pakistan</td><td>1</td></tr><tr><td>Laboratoire Hubert Curien, UMR5516, Université Jean Monnet, Saint-Etienne, France</td><td>1</td></tr><tr><td>Université de Lyon, CNRS, LIRIS, UMR5205, Université Lyon 1, Lyon, France</td><td>1</td></tr><tr><td>Department of Electrical and Computer Engineering, Saginaw Valley State University, University Ctr, MI- 48710</td><td>1</td></tr><tr><td>TCTS Lab, Faculté Polytechnique de Mons, Belgium</td><td>1</td></tr><tr><td>Speech Technology Group, Technical University of Madrid, Spain</td><td>1</td></tr><tr><td>TALP Research Center, Universitat Politècnica de Catalunya, Spain</td><td>1</td></tr><tr><td>TELE Lab, Université catholique de Louvain, Belgium</td><td>1</td></tr><tr><td>INRIA Grenoble-Rhône-Alpes Research Center, France</td><td>1</td></tr><tr><td>Department of Embedded Systems, Institute for Infocomm Research, Singapore</td><td>1</td></tr><tr><td>E.T.S. Ingenieros Industriales, Universidad de Castilla-La Mancha Campus Universitario, Ciudad Real, Spain</td><td>1</td></tr><tr><td>Universidad de Las Palmas de Gran Canaria, SIANI, Edificio Central del Parque Científico-Tecnológico, Las Palmas, Spain</td><td>1</td></tr><tr><td>School of Math and Geospatial Sciences, Royal Melbourne Institute of Technology University , Melbourne, Australia</td><td>1</td></tr><tr><td>Department of Computer Science and Application, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou, China</td><td>1</td></tr><tr><td>School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China</td><td>1</td></tr><tr><td>Department of Electrical and Computer Engineering, Naresuan University, Muang, Thailand</td><td>1</td></tr><tr><td>Department of Computer Science, Christian-Albrechts University, Kiel, Germany</td><td>1</td></tr><tr><td>Engineering Lab on Intelligent Perception for Internet of Things, Peking University Shenzhen Graduate School, Shenzhen, China</td><td>1</td></tr><tr><td>Delft University of Technology and Sensor Technology, Netherlands Defense Academy</td><td>1</td></tr><tr><td>School of Electrical Engineering and Automation, Qilu University of Technology, Jinan, China</td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China</td><td>1</td></tr><tr><td>Department of Electronics and Computing and the Electronics and Information Technology Research & Development Center, Universidade Federal do Amazonas, Manaus-AM, CEP, Brazil</td><td>1</td></tr><tr><td>University of California at Merced, Merced, USA</td><td>1</td></tr><tr><td>Technische Universität München, Garching, Germany</td><td>1</td></tr><tr><td>School of Big Data and Computer, Science, Guizhou Normal University, Guiyang, Guizhou, 550025, P. R. China</td><td>1</td></tr><tr><td>University of California at Santa Cruz, Santa Cruz, California</td><td>1</td></tr><tr><td>Network Center, Huizhou University, Huizhou, China</td><td>1</td></tr><tr><td>Faculty of Engineering, Computer Engineering Department, Akdeniz University, Dumlupinar Bulvari, Turkey</td><td>1</td></tr><tr><td>IRCICA, Parc Scientifique de la Haute Borne, Lille 1 University, Villeneuve d’Ascq, France</td><td>1</td></tr><tr><td>Data and Analytics Department, KPMG AGWPG, Düsseldorf, Germany</td><td>1</td></tr><tr><td>Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China</td><td>1</td></tr><tr><td>JiangSu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise, Suzhou, China</td><td>1</td></tr><tr><td>Université de Lorraine, LORIA, UMR 7503</td><td>1</td></tr><tr><td>Department of Electrical Engineering, The City College of New York, New York, USA</td><td>1</td></tr><tr><td>Robótica y Manufactura Avanzada, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ramos Arizpe, Mexico</td><td>1</td></tr><tr><td>School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, India</td><td>1</td></tr><tr><td>Dept. de Ciência da Computacão, Universidade Federal de Ouro Preto, MG Brazil</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Inha University, 253, Yong-Hyun Dong, Nam-Gu, Incheon, South Korea</td><td>1</td></tr><tr><td>Kodak Alaris Inc., Rochester, NY 14615, USA</td><td>1</td></tr><tr><td>Department of Electrical Engineering, University of California, Riverside, Riverside CA, California 92521 United States</td><td>1</td></tr><tr><td>Department of CSE, Regional Campus of Anna University, Tirunelveli 627007, India</td><td>1</td></tr><tr><td>Dalian Key Laboratory of Digital Technology for National Culture, Dalian Minzu University, Dalian, China</td><td>1</td></tr><tr><td>Department of Business Planning & Information Systems, TEI of Crete, Agios Nikolaos, Greece</td><td>1</td></tr><tr><td>School of Information Technology Jawaharlal Nehru Technological University Hyderabad Andhra Pradesh, India</td><td>1</td></tr><tr><td>Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France</td><td>1</td></tr><tr><td>School of Computer ScienceThe University of Adelaide</td><td>1</td></tr><tr><td>Shanghai Advanced Research Institute, CAS & Qiniu AI Lab, Shanghai, China</td><td>1</td></tr><tr><td>University of Lyon, LIRIS - CNRS, National Institute of Applied Sciences (INSA), Lyon, France</td><td>1</td></tr><tr><td>Sorbonne Universités, UPMC Univ Paris 06, CNRS UMR 7222, Institut des Systèmes Intelligents et de Robotique (ISIR), 4 place Jussieu, 75005 Paris, France</td><td>1</td></tr><tr><td>Toyohashi University of Technology, Toyohashi, Japan</td><td>1</td></tr><tr><td>Department of Informatics, King’s College London, Strand, London, UK</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China</td><td>1</td></tr><tr><td>Department of Learning and Digital Technology, Fo Guang University, Yilan, Taiwan</td><td>1</td></tr><tr><td>BITS Pilani, India , India</td><td>1</td></tr><tr><td>College of Computer and Information Sciences, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia</td><td>1</td></tr><tr><td>National University of Computer and Emerging Sciences, Islamabad, Islamabad, Pakistan</td><td>1</td></tr><tr><td>Research Team on Audio Visual Signal Processing (AVSP), Vrije Universiteit Brussel (VUB), Electronics and Informatics Department, VUB-ETRO, Pleinlaan 2, 1050 Brussel, Belgium</td><td>1</td></tr><tr><td>College of Computer Science and Technology of Huaqiao University Xiamen, Xiamen, China</td><td>1</td></tr><tr><td>Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Taiwan 640, R.O.C.</td><td>1</td></tr><tr><td>Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng 475004, China</td><td>1</td></tr><tr><td>Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Information Management, College of Management, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Computer Science and Information Engineering, College of Electrical Engineering and Computer Science, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Statistics, University of California at Berkeley, Berkeley, USA</td><td>1</td></tr><tr><td>International Computer Science Institute, University of California at Berkeley, Berkeley, USA</td><td>1</td></tr><tr><td>College of Information Science and Technology, Agricultural University of Hebei, Baoding, China</td><td>1</td></tr><tr><td>Department of Electronics Engineering, Mokpo National University, Republic of Korea</td><td>1</td></tr><tr><td>FX Palo Alto Laboratory</td><td>1</td></tr><tr><td>Department of Applied Optics and Photonics, University of Calcutta, Kolkata, India</td><td>1</td></tr><tr><td>Department of Electrical Engineering, Future Institute of Engineering and Management, Kolkata, India</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur, India</td><td>1</td></tr><tr><td>Telecom Division, Centre de Développement des Technologies Avancées, Algiers, Algeria</td><td>1</td></tr><tr><td>Departments of Medical Imaging and Medical Biophysics, University of Western Ontario, London, ON, Canada</td><td>1</td></tr><tr><td>Department of Medical Biophysics, University of Western Ontario, London, ON, Canada</td><td>1</td></tr><tr><td>School of Computer Science, Shaanxi Normal University, Xi’an, China</td><td>1</td></tr><tr><td>Engineering Laboratory of Teaching Information Technology of Shaanxi Province, Xi’an, China</td><td>1</td></tr><tr><td>Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi’an, China</td><td>1</td></tr><tr><td>College of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, P.R. China</td><td>1</td></tr><tr><td>Nanyang Technological University School of Computer Engineering</td><td>1</td></tr><tr><td>Department of Electronics and Electrical Engineering, Indian Institute of Technology (IIT) Guwahati, Guwahati, India</td><td>1</td></tr><tr><td>Technology Section, Israel National Police, Jerusalem, Israel</td><td>1</td></tr><tr><td>Department of Electro-Optics Engineering, Ben-Gurion University, Beer Sheva, Israel</td><td>1</td></tr><tr><td>Department of Mathematics, JiaYing University, Meizhou, China</td><td>1</td></tr><tr><td>Hebei University of Technology, School of Science, Tianjin, P. R. China</td><td>1</td></tr><tr><td>YiLi Normal College, Yining, China</td><td>1</td></tr><tr><td>Faculty of Electronic Information and Electrical Engineering, Dalian University, Dalian, China</td><td>1</td></tr><tr><td>Centre for Innovation in IT Services and Applications (iNEXT), University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td>Video Surveillance Laboratory, Guizhou University for Nationalities, Guiyang, China</td><td>1</td></tr><tr><td>College of Arts and Sciences, Shanxi Agricultural University, Shanxi, China</td><td>1</td></tr><tr><td>IRDA Group, ADMIR Laboratory, Rabat IT Center, ENSIAS, CNRST (URAC29), Mohammed V University of Rabat, Morocco</td><td>1</td></tr><tr><td>LRIT, CNRST (URAC29), Mohammed V University of Rabat, Morocco</td><td>1</td></tr><tr><td>Queen’s University, Kingston, Canada</td><td>1</td></tr><tr><td>University of Science Technology, Wuhan, China</td><td>1</td></tr><tr><td>Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia</td><td>1</td></tr><tr><td>University at Qatar, Doha, Qatar</td><td>1</td></tr><tr><td>University of Istanbul, Istanbul, Turkey</td><td>1</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Tuen Mun, Hong Kong</td><td>1</td></tr><tr><td>PolyU Shenzhen Research Institute, Shenzhen, China</td><td>1</td></tr><tr><td>German National Library of Science and Technology & Leibniz Universität Hannover, Hannover, Germany</td><td>1</td></tr><tr><td>University of Applied Sciences Jena, Jena, Germany</td><td>1</td></tr><tr><td>Department of Creative IT Engineering, POSTECH, Pohang, South Korea, 37673</td><td>1</td></tr><tr><td>Department of Computer Science, University of Western Ontario, London, Canada</td><td>1</td></tr><tr><td>Vision Laboratory, LARSyS, University of the Algarve, Faro, Portugal</td><td>1</td></tr><tr><td>Department of Information Management, Yuan Ze University, Taoyuan, China</td><td>1</td></tr><tr><td>DICGIM, Universitá degli Studi di Palermo, V.le delle Scienze, Ed. 6, 90128 Palermo, Italy</td><td>1</td></tr><tr><td>Department of Computer Engineering, Karadeniz Technical University, Trabzon, Turkey</td><td>1</td></tr><tr><td>Department of Computer Technologies, Trabzon Vocational School, Karadeniz Technical University, Trabzon, Turkey</td><td>1</td></tr><tr><td>Stanford University and Coursera</td><td>1</td></tr><tr><td>Dept. of Comput. Sci. & Info. Eng., National Yunlin Univ. of Science & Technology, Taiwan</td><td>1</td></tr><tr><td>Faculty of Mathematics and Statistics, Hubei Key Laboratory of Applied Mathematics, Hubei University, Wuhan, China</td><td>1</td></tr><tr><td>Biometric and Imaging Processing Laboratory (BIPLab)</td><td>1</td></tr><tr><td>Research and Academic Computer Network (NASK)</td><td>1</td></tr><tr><td>Philips Applied Technologies, Eindhoven, Netherlands</td><td>1</td></tr><tr><td>Philips Research Eindhoven, Eindhoven, Netherlands</td><td>1</td></tr><tr><td>Key Lab Complex System & Intelligence Science, Institute of Automation, Chinese Academy of Science, Beijing, China</td><td>1</td></tr><tr><td>College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China</td><td>1</td></tr><tr><td>National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis, Nizhny Novgorod, Russia</td><td>1</td></tr><tr><td>Emory University School of Medicine, Atlanta, USA</td><td>1</td></tr><tr><td>Department of Radiology and Imaging Sciences, Winship Cancer Institute, Emory University School of Medicine, Atlanta, USA</td><td>1</td></tr><tr><td>Dept. of EMPH, Icahn School of Medicine at Mount Sinai, New York, NY 10029</td><td>1</td></tr><tr><td>Electrical-Electronics Engineering Department, Izmir University of Economics, Balcova, Turkey</td><td>1</td></tr><tr><td>Department of Computer Science, Solapur University, Solapur, India</td><td>1</td></tr><tr><td>Computer Vision Research Group, School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia</td><td>1</td></tr><tr><td>Department of Information Technology, Netaji Subhas Engineering College, Kolkata, India</td><td>1</td></tr><tr><td>Computer Engineering College, Jimei University, Xiamen, China</td><td>1</td></tr><tr><td>Fujian Key Laboratory of the Brain-like Intelligent Systems, Xiamen, China</td><td>1</td></tr><tr><td>School of Information, Hunan University of Humanities, Science and Technology, Loudi, China</td><td>1</td></tr><tr><td>Al Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia</td><td>1</td></tr><tr><td>School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Korea</td><td>1</td></tr><tr><td>Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea</td><td>1</td></tr><tr><td>Dept. of Computer Science and Information Engineering, Providence University, Taichung, Taiwan</td><td>1</td></tr><tr><td>360 AI Institute, Beijing, China</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Research Lab, Vrije Universitiet Brussel (VUB), Department of Electronics & Informatics (ETRO) Pleinlaan 2, 1050 Brussel, Belgium</td><td>1</td></tr><tr><td>IRISA, University of Rennes 1</td><td>1</td></tr><tr><td>Research Institution of Intelligent Control and Testing, Graduate School of Tsinghua University at Shenzhen, 518055, China</td><td>1</td></tr><tr><td>Commonwealth Scientific and Industrial Research Organization (CSIRO)</td><td>1</td></tr><tr><td>Indiana University-Bloomington, USA</td><td>1</td></tr><tr><td>Key Laboratory of Medical Image Computing (Northeastern University), Ministry of Education, Shenyang, China</td><td>1</td></tr><tr><td>Clínica Otocenter, Teresina, Piauí, Brasil</td><td>1</td></tr><tr><td>Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing, China</td><td>1</td></tr><tr><td>Nanjing University of Posts and Telecommunications, Nanjing, China</td><td>1</td></tr><tr><td>Grupo de Aplicacion de Telecomunicaciones Visuales, Universidad Politecnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain</td><td>1</td></tr><tr><td>Department of Management Information Systems, Universität Regensburg, Universitätsstr. 31, 93053 Regensburg, Germany</td><td>1</td></tr><tr><td>Department of Computer Science, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India</td><td>1</td></tr><tr><td>Amrita E-Learning Research Laboratory and the Department of Computer Science, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India</td><td>1</td></tr><tr><td>Department of ECE, PEC University of Technology, Chandigarh, India</td><td>1</td></tr><tr><td>Biomedical Instrumentation (V-02), CSIR-Central Scientific Instruments Organisation (CSIO)|, Chandigarh, India</td><td>1</td></tr><tr><td>CEERI, Pilani, India</td><td>1</td></tr><tr><td>MNIT, Jaipur, India</td><td>1</td></tr><tr><td>Department of Arts and Humanities, College of Business, Arts and Social Sciences, Brunel University London, Uxbridge, UK</td><td>1</td></tr><tr><td>Department of Design, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, India</td><td>1</td></tr><tr><td>NTT Service Evolution Laboratories, Kanagawa, Japan</td><td>1</td></tr><tr><td>Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., North Carolina Univ., Wilmington, NC, USA</td><td>1</td></tr><tr><td>University of Washington &Microsoft, Seattle, WA, USA</td><td>1</td></tr><tr><td>Departamento de Informtica e Matemtica Aplicada/University of Rio Grande do Norte, Natal, Brazil</td><td>1</td></tr><tr><td>Computer Engineering Department, Girne American University, Kyrenia, Cyprus 90</td><td>1</td></tr><tr><td>Cornell University & Facebook Inc., New York, NY, USA</td><td>1</td></tr><tr><td>School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, China</td><td>1</td></tr><tr><td>Fujian Provincial Key Laboratory of Information Processing and Intelligent Control, Fuzhou, China</td><td>1</td></tr><tr><td>School of Technology, Nanjing Audit University, Nanjing, China</td><td>1</td></tr><tr><td>Adobe Research Department, Adobe Systems Inc, San Jose, CA</td><td>1</td></tr><tr><td>Integrated Circuits and Electronics Laboratory, Department of Engineering, Aarhus University, Denmark</td><td>1</td></tr><tr><td>Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology (ICT), CAS, Beijing, China</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., California Inst. of Technol., Pasadena, CA, USA</td><td>1</td></tr><tr><td>Utechzone Co. Ltd., New Taipei City, Taiwan 235</td><td>1</td></tr><tr><td>Department of Cognitive Science, University of California, San Diego, CA, USA</td><td>1</td></tr><tr><td>Department of Electronic Engineering Shanghai Jiao Tong University</td><td>1</td></tr><tr><td>Innovations Kontakt Stelle (IKS) Hamburg, Hamburg University of Applied Sciences</td><td>1</td></tr><tr><td>School of Engineering and Computing, University of the West of Scotland</td><td>1</td></tr><tr><td>Computer Science Department, Central Washington University (CWU)</td><td>1</td></tr><tr><td>ICT Center, CSIRO</td><td>1</td></tr><tr><td>Technische Universität München, München, Germany</td><td>1</td></tr><tr><td>Electrical Engineering and Computer Science, School of Engineering, University of California at Merced, Merced, USA</td><td>1</td></tr><tr><td>Data61, Commonwealth Scientific and Industrial Research Organization (CSIRO), Canberra, Australia</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Faculty of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Bangladesh</td><td>1</td></tr><tr><td>Pennsylvania State University, University Park, PA</td><td>1</td></tr><tr><td>University of Sao Paulo</td><td>1</td></tr><tr><td>School of Software, Henan University, Kaifeng, China</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, China</td><td>1</td></tr><tr><td>Department of Electrical Engineering, Computer Vision Laboratory, Linköping University, Linköping, Sweden</td><td>1</td></tr><tr><td>Computer Vision Research Laboratory, Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran</td><td>1</td></tr><tr><td>Treelogic, Technological Scientific Park of Asturias, Llanera, Spain</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Oviedo, Gijón, Spain</td><td>1</td></tr><tr><td>Fundación CTIC (Technological Center), Technological Scientific Park of Gijón, Gijón, Spain</td><td>1</td></tr><tr><td>Department of Computer Science, Madrid Open University, Madrid, Spain</td><td>1</td></tr><tr><td>Department of Research and Diagnostic Methods, Faculty of Education, Pontificia University of Salamanca, Salamanca, Spain</td><td>1</td></tr><tr><td>Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan</td><td>1</td></tr><tr><td>Dept. of Information Engineering, Faculty of Engineering, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan</td><td>1</td></tr><tr><td>Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan, +81 25 262 7499</td><td>1</td></tr><tr><td>NTNU, Norway</td><td>1</td></tr><tr><td>Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland</td><td>1</td></tr><tr><td>Polish-Japanese Institute of Information Technology, Warszawa, Poland</td><td>1</td></tr><tr><td>Faculty of Applied Informatics and Mathematics, Department of Informatics, Warsaw University of Life Sciences (SGGW), Warsaw, Poland</td><td>1</td></tr><tr><td>Polish-Japanese Institute of Information Technology, Warsaw, Poland</td><td>1</td></tr><tr><td>FernUniversität , Hagen, Germany</td><td>1</td></tr><tr><td>Universidad Tecnica Federico Santa Maria , Valparaiso, Chile</td><td>1</td></tr><tr><td>Staffordshire University , Staffordshire, United Kingdom</td><td>1</td></tr><tr><td>Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, Kuching, Malaysia</td><td>1</td></tr><tr><td>University of Massachusetts at Amherst, Amherst, MA, USA</td><td>1</td></tr><tr><td>Department of Engineering and MaintenanceChina Mobile Group, Jiangsu Company, Ltd., Changzhou, China</td><td>1</td></tr><tr><td>Indian Statistical Institute, Kolkata 700108</td><td>1</td></tr><tr><td>Departament d’Informàtica, Universitat de Valencia, Valencia, Spain</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, Gannan Normal University, Ganzhou, People’s Republic of China</td><td>1</td></tr><tr><td>National Laboratory of Pattern Recognition, Beijing, China</td><td>1</td></tr><tr><td>Quang Binh University, Dong Hoi City, Vietnam</td><td>1</td></tr><tr><td>School of Mathematics and Information Technology, Nanjing Xiao Zhuang University, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td>School of Computing, Electronics and Mathematics, Faculty of Engineering, Environment and Computing, Coventry University, Coventry, UK</td><td>1</td></tr><tr><td>Institute of Computer Science, Christian-Albrechts-Universität Kiel, Kiel, Germany</td><td>1</td></tr><tr><td>KT Future Technology Laboratory, Seoul, South Korea</td><td>1</td></tr><tr><td>Microsoft Research Asia, Beijing, P.R. China</td><td>1</td></tr><tr><td>Shanghai Maritime University, Shanghai, China</td><td>1</td></tr><tr><td>Machine Intelligence Research Institute, Rockville, USA</td><td>1</td></tr><tr><td>Orange—France Telecom Division R&D—TECH/IRIS, Cesson Sévigné Cedex, France</td><td>1</td></tr><tr><td>IIT-Madras, Chennai, India</td><td>1</td></tr><tr><td>Department of Computer Science, Innopolis University, Kazan, Russia</td><td>1</td></tr><tr><td>Department of Computer Science, University of Science & Technology, Bannu, Pakistan</td><td>1</td></tr><tr><td>Naver Labs Europe, Meylan, France</td><td>1</td></tr><tr><td>School of Computer and Systems Sciences, JawaharLal Nehru University, New Delhi 110067, India</td><td>1</td></tr><tr><td>Univ. La Rochelle, La Rochelle, France</td><td>1</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Tsuen Wan, Hong Kong</td><td>1</td></tr><tr><td>University of Salerno, Salerno, Italy</td><td>1</td></tr><tr><td>Google, Mountain View, USA</td><td>1</td></tr><tr><td>Computer Sciences Department, University of Wisconsin, Madison, USA</td><td>1</td></tr><tr><td>Google, Seattle, USA</td><td>1</td></tr><tr><td>Singapore Polytechnic, 500 Dover Road, Singapore 139651</td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China</td><td>1</td></tr><tr><td>Centre for Machine Vision, Bristol Robotics Laboratory, University of the West of England, T Block, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, UK</td><td>1</td></tr><tr><td>Saudi Electronic University, Riyadh, Kingdom of Saudi Arabia</td><td>1</td></tr><tr><td>Information Security Group, City University London, London, UK</td><td>1</td></tr><tr><td>School of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou, China</td><td>1</td></tr><tr><td>IIIT Chittoor, SriCity, Andhra Pradesh, India</td><td>1</td></tr><tr><td>Department of Information Engineering, Henan University of Science and Technology, Luoyang, China</td><td>1</td></tr><tr><td>Department of mechatronic technology of National Taiwan Normal University</td><td>1</td></tr><tr><td>Department of Electrical Engineering and Computer Science, Colorado School of Mines, Golden, CO, USA</td><td>1</td></tr><tr><td>The Image Processing and Analysis Laboratory (LAPI), University “Politehnica” of Bucharest, 313 Splaiul Independeţei, Bucharest, Romania</td><td>1</td></tr><tr><td>Division of Digital Media Engineering, Sang-Myung University, Suwon, Republic of Korea</td><td>1</td></tr><tr><td>Facebook AI Research (FAIR), Menlo Park, USA</td><td>1</td></tr><tr><td>Princeton University &Microsoft, Princeton, NJ, USA</td><td>1</td></tr><tr><td>Microsoft &University of Washington, Redmond, WA, USA</td><td>1</td></tr><tr><td>Intel Labs, Pittsburgh PA</td><td>1</td></tr><tr><td>Dept. of Inf. Network Technol., Hsiuping Inst. of Technol., Taichung, Taiwan</td><td>1</td></tr><tr><td>Alibaba Group, Zhejiang, People’s Republic of China</td><td>1</td></tr><tr><td>Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute Troy, Troy, USA</td><td>1</td></tr><tr><td>Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology, University of Science and Technology of China Hefei, Anhui, People’s Republic of China</td><td>1</td></tr><tr><td>School of ComputingNational University of Singapore</td><td>1</td></tr><tr><td>Dept. of EE, UESTC, 2006 Xiyuan Ave, Chengdu, Sichuan 611731, China</td><td>1</td></tr><tr><td>Dept. of Radiation Oncology, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</td><td>1</td></tr><tr><td>Dept. of Electrical & Computer Engineering, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</td><td>1</td></tr><tr><td>University of Nottingham (Malaysia Campus), Malaysia</td><td>1</td></tr><tr><td>South Valley University, Qena, Egypt</td><td>1</td></tr><tr><td>Film Department ELTE University, Budapest, Hungary</td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, Tripura University (A Central University), Suryamaninagar-799022, Tripura, India</td><td>1</td></tr><tr><td>Gipsa-Lab, Saint Martin d’Heres, France</td><td>1</td></tr><tr><td>ICA Laboratory, Grenoble, France</td><td>1</td></tr><tr><td>School of Computing and Electrical Engineering, IIT Mandi, H.P, 175001, India</td><td>1</td></tr><tr><td>AICTE Emeritus Fellow, </td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, GCELT, Kolkata, India</td><td>1</td></tr><tr><td>Chinese University of Hong Kong, Hong Kong</td><td>1</td></tr><tr><td>Department of Computer System and Communication, Faculty of Information and Communication, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia</td><td>1</td></tr><tr><td>Division Télécom, Centre de Développement des Technologies Avancées - CDTA, Algiers, Algeria</td><td>1</td></tr><tr><td>School of Computer and Communication Science, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland</td><td>1</td></tr><tr><td>Baidu Research - Institute of Deep Learning, Sunnyvale, USA</td><td>1</td></tr><tr><td>Jiaxing University, Jiaxing, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. zhangxiaoxun@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. jiayunde@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. xushuang@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Electronics and Communication, University of Allahabadm Allahabad, India 211002</td><td>1</td></tr><tr><td>Department of Business Computer, Faculty of Management Science, Nakhon Ratchasima Rajabhat University, Nakhon Ratchasima, Thailand</td><td>1</td></tr><tr><td>Yahoo! Research</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, University of Cagliari, Italy</td><td>1</td></tr><tr><td>Universidad de León, León, Spain</td><td>1</td></tr><tr><td>Elektronik ve Haberleşme Mühendisliği Bölümü</td><td>1</td></tr><tr><td>Robert Bosch Engineering and Business Solutions Limited, Bangalore, India</td><td>1</td></tr><tr><td>Department of Instrumentation and Control Engineering, PSG College of Technology, Coimbatore, India</td><td>1</td></tr><tr><td>China Airborne Missile Academy, Luoyang, China</td><td>1</td></tr><tr><td>Electronic Information Engineering College, Henan University of Science and Technology, Luoyang, China</td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Inner Mongolia University of Science and Technology, Baotou, People’s Republic of China</td><td>1</td></tr><tr><td>Istituto Italiano di Tecnologia & Università di Verona, Genova, Italy</td><td>1</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT), Genova, Italy</td><td>1</td></tr><tr><td>Office of Safety Research and Development, Federal Highway Administration, U.S. Department of Transportation, Virginia, USA</td><td>1</td></tr><tr><td>Xinjiang Vocational and Technical College of Communications, Wulumuqi, People’s Republic of China</td><td>1</td></tr><tr><td>College of Mathematics and Informatics, South China Agricultural University, China</td><td>1</td></tr><tr><td>Curtin University Department of Mechanical Engineering, Perth, Western Australia 6012</td><td>1</td></tr><tr><td>Department of Information Engineering, HeNan Radio and Television University, Zhengzhou, People’s Republic of China</td><td>1</td></tr><tr><td>Computer Science Department, School of Information Science and Engineering, Xiamen, University, Xiamen, People’s Republic of China</td><td>1</td></tr><tr><td>PLA University of Science and Technology, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, USA</td><td>1</td></tr><tr><td>School of Electronics and Computer Eng., Chonnam National University, Gwangju, Korea</td><td>1</td></tr><tr><td>FAST, Supélec, Avenue de la Boulaie, Cesson-Sévigné, France</td><td>1</td></tr><tr><td>ISIR laboratory, Pierre and Marie Curie university, Paris Cedex 05, France</td><td>1</td></tr><tr><td>Centre for Visual Computing, Faculty of Engineering and Informatics, University of Bradford, Bradford, UK</td><td>1</td></tr><tr><td>Amsterdam University College, Amsterdam, The Netherlands</td><td>1</td></tr><tr><td>Key Laboratory of Intelligent Information Processing, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td>Institute of Life Sciences, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>School of Information Science and Engineering, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>FEECS, Department of Computer Science, Technical University of Ostrava, Ostrava-Poruba, Czech Republic</td><td>1</td></tr><tr><td>ECE, Department MSIT, C-4 Janakpuri, New Delhi, India</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., New Jersey Inst. of Technol., Newark, NJ, USA</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan. e-mail: chihming.fu@gmail.com</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan; Informatics Department, Fo-Guang University, I-Lan, Taiwan. e-mail: clhuang@ee.nthu.edu.tw</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan</td><td>1</td></tr><tr><td>Department of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China</td><td>1</td></tr><tr><td>University of California at Los Angeles, Los Angeles, CA, USA</td><td>1</td></tr><tr><td>Department of Physics, Tripura University (A Central University), Suryamaninagar, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Tripura University (A Central University), Suryamaninagar, India</td><td>1</td></tr><tr><td>Pontifical Catholic University of Minas Gerais - Department of Computer Science, R. Dom Jose Gaspar, 500, Belo Horizonte MG, 30535901, Brazil</td><td>1</td></tr><tr><td>Department of Statistics and Operational Research, Faculty of Mathematics, Complutense University of Madrid, Madrid, Spain</td><td>1</td></tr><tr><td>Dept. of Mathematics and Computer Science, University of Udine, Italy</td><td>1</td></tr><tr><td>LIMSI-CNRS, Orsay Cedex, France</td><td>1</td></tr><tr><td>Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Pisa, Italy</td><td>1</td></tr><tr><td>Faculty of Information Sciences and Engineering, Management and Science University, Selangor, Malaysia</td><td>1</td></tr><tr><td>UTM-Big Data Center, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</td><td>1</td></tr><tr><td>Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia</td><td>1</td></tr><tr><td>LAMIA, EA 4540, University of French West Indies and Guyana, Guadeloupe, France</td><td>1</td></tr><tr><td>ISIR, UPMC Univ Paris 06, CNRS, Paris, France</td><td>1</td></tr><tr><td>Merchant Marine College, Shanghai Maritime University, Shanghai 201306, PR China</td><td>1</td></tr><tr><td>Department of Informatics, King’s College London, London, UK</td><td>1</td></tr><tr><td>Department of Electrical Engineering, KAIST, Korea</td><td>1</td></tr><tr><td>Department of New Media, Korean German Institute of Technology, Korea</td><td>1</td></tr><tr><td>Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy</td><td>1</td></tr><tr><td>Pontifical Catholic Univ of Rio de Janei, Department of Informatics, Rio de Janeiro, Brazil</td><td>1</td></tr><tr><td>Department of Informatics, Pontifical Catholic Univ of Rio de Janei, Rio de Janeiro, Brazil</td><td>1</td></tr><tr><td>School of Computing Sciences and Informatics, University of Cincinnati, Cincinnati, USA</td><td>1</td></tr><tr><td>Universiti Kuala Lumpur, Kedah</td><td>1</td></tr><tr><td>Sudan University of Science and Technology, College of Computer Science and Information Technology, Khartoum - Sudan</td><td>1</td></tr><tr><td>LMU Munich, Germany and Munich University of Applied Sciences, Germany</td><td>1</td></tr><tr><td>Department of Electric and Electronic Engineering, Avrasya University, Trabzon, Turkey</td><td>1</td></tr><tr><td>ACM Professional Specialist in Artificial Intelligence</td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China</td><td>1</td></tr><tr><td>University of Washington and Google Inc.</td><td>1</td></tr><tr><td>Google Inc.</td><td>1</td></tr><tr><td>CCCE, Nankai University Jinnan Campus, Tianjin, China</td><td>1</td></tr><tr><td>Department of Computer Science, VHNSN College, Virudhunagar, India</td><td>1</td></tr><tr><td>Department of Computer Science, ANJA College, Sivakasi, India</td><td>1</td></tr><tr><td>Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology Tsinghua University, Beijing, China</td><td>1</td></tr><tr><td>Foundation for Research & Technology – Hellas, Heraklion, Crete, Greece</td><td>1</td></tr><tr><td>Vrije Universiteit Amsterdam, Amsterdam, The Netherlands</td><td>1</td></tr><tr><td>Ruhr-Universität Bochum, Bochum, Germany</td><td>1</td></tr><tr><td>Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro No.1, Tonantzintla, Puebla, México. CP 72840</td><td>1</td></tr><tr><td>Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, People’s Republic of China</td><td>1</td></tr><tr><td>Department of Mechanical Engineering, Universiti Tenaga Nasional Km 7, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia</td><td>1</td></tr><tr><td>Dept. of Electron. Eng., Hannam Univ., Daejeon, South Korea</td><td>1</td></tr><tr><td>Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies, Zhejiang, China</td><td>1</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada</td><td>1</td></tr><tr><td>Laboratoire MIA, University of La Rochelle, La Rochelle, France</td><td>1</td></tr><tr><td>Fraunhofer Institute for Telecommunications, Berlin, Germany</td><td>1</td></tr><tr><td>Fraunhofer Institute for Digital Media Technology, Ilmenau, Germany</td><td>1</td></tr><tr><td>Siemens AG, Corporate Technology, Munich, Germany</td><td>1</td></tr><tr><td>ECIT, School of Electronics, Electrical Engineering & Computer Science, Queen's University Belfast, Belfast, UK</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Calcutta, Kolkata, India</td><td>1</td></tr><tr><td>School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran</td><td>1</td></tr><tr><td>Luoyang Electro-Optical Equipment Research Institute, Luoyang, People’s Republic of China</td><td>1</td></tr><tr><td>Technological Educational Institute of Sterea Ellada, Psahna, Halkida, Greece</td><td>1</td></tr><tr><td>National Centre for Scientific Research “Demokritos”, Agia Paraskevi, Athens, Greece</td><td>1</td></tr><tr><td>University of Maastricht, Maastricht, The Netherlands</td><td>1</td></tr><tr><td>Centre of Research and Technology Hellas, Thermi, Thessaloniki, Greece</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, P.P.G. Institute of Technology, Coimbatore, India</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Institute of Road and Transport Technology, Erode, India</td><td>1</td></tr><tr><td>Department of Computer Science, Banasthali Vidyapith, Banasthali, India</td><td>1</td></tr><tr><td>Computer Science and Engineering Department, SP Memorial Institute of Technology, Kaushambi, India</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, China</td><td>1</td></tr><tr><td>Fujifilm Software, San Jose, USA</td><td>1</td></tr><tr><td>Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis, Singapore 138632</td><td>1</td></tr><tr><td>HTC Research, Beijing, China</td><td>1</td></tr><tr><td>QCIS, University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td>Interuniversity Microelectronics Centre, Heverlee, Belgium</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Lab, Department ETRO, Vrije Universiteit Brussel (VUB), Brussels, Belgium</td><td>1</td></tr><tr><td>Shaanxi Key Laboratory on Speech and Image Information Processing, Xi’an, China</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Lab, School of Computer Science, Northwestern Polytechnical University (NPU), Xi’an, China</td><td>1</td></tr><tr><td>Institute of Electronics and Computer Science, Riga, Latvia</td><td>1</td></tr><tr><td>Electrical and Computer Engineering Department, University of California, Santa Barbara, CA 93106 USA</td><td>1</td></tr><tr><td>Psychology Department, University of California, Santa Barbara, CA 93106 USA</td><td>1</td></tr><tr><td>Dept. of Comp. Sci. and Inf. Eng, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>School of Control Science and Engineering DUT, Dalian, China</td><td>1</td></tr><tr><td>Information Technology R&D Center, Mitsubishi Electric Corporation, Kamakura, Japan</td><td>1</td></tr><tr><td>School of Information Science and Engineering, Hunan city University, Yiyang, China</td><td>1</td></tr><tr><td>KU Leuven, ESAT - PSI, iMinds, Leuven, Belgium</td><td>1</td></tr><tr><td>Max-Planck-Institut für Informatik, Saarbrücken, Germany</td><td>1</td></tr><tr><td>Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran, Iran</td><td>1</td></tr><tr><td>University of IIllinois, Urbana-Champaign</td><td>1</td></tr><tr><td>Zhejiang University & Alibaba Group, Hangzhou, China</td><td>1</td></tr><tr><td>Laboratory LIM, Department of Computer Science, Faculty of Sciences and Technologies, University Hassan II, Casablanca-Morocco</td><td>1</td></tr><tr><td>Electrical Engineering Department, Yazd University, Yazd, Iran</td><td>1</td></tr><tr><td>School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin, China</td><td>1</td></tr><tr><td>Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, Tianjin, China</td><td>1</td></tr><tr><td>Adjunct, Effat University, Jeddah, Saudi Arabia</td><td>1</td></tr><tr><td>School of Computer Science, Wuyi University, Jiangmen, China</td><td>1</td></tr><tr><td>Snapchat Research, Venice, CA90291</td><td>1</td></tr><tr><td>Department of CSE, University at Buffalo (SUNY), NY 14260, USA</td><td>1</td></tr><tr><td>School of Information and Engineering, Jinhua Polytechnic, Jinhua, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Texas, Arlington, USA</td><td>1</td></tr><tr><td>School of Medical Science, Jinhua Polytechnic, Jinhua, China</td><td>1</td></tr><tr><td>S. S. College of Business Studies, University of Delhi, Delhi, India</td><td>1</td></tr><tr><td>School of Computer & System Sciences, Jawaharlal Nehru University, New Delhi, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, India</td><td>1</td></tr><tr><td>Baidu Online Network Technology (Beijing) Co. Ltd, Beijing, China</td><td>1</td></tr><tr><td>Faculty of Engineering and Computing, Coventry University, UK</td><td>1</td></tr><tr><td>Dept. of Theoretical Electrical Engineering, Technical University of Sofia, Sofia, Bulgaria</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, National Institute of Technology Trichy, Trichy 620015, India</td><td>1</td></tr><tr><td>Lawrence Berkeley National Laboratory, Berkeley, USA</td><td>1</td></tr><tr><td>No.1 Senior Middle School of Wendeng District, Weihai, China</td><td>1</td></tr><tr><td>Standards & Metrology Research Institute of CARS, Beijing, China</td><td>1</td></tr><tr><td>College of Information Science & Technology, Hebei Agricultural University, Baoding, China</td><td>1</td></tr><tr><td>NOVA Laboratory for Computer Science and Informatics, NOVA-LINCS, Departamento de Informática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal</td><td>1</td></tr><tr><td>Amazon, Berkshire, U.K.</td><td>1</td></tr><tr><td>Tianjin Universtiy, Tianjin, China</td><td>1</td></tr><tr><td>University of Lancaster, Lancaster, United Kingdom</td><td>1</td></tr><tr><td>University of Helsinki, Helsinki, Finland</td><td>1</td></tr><tr><td>Intelligent and Interactive Systems, Institute of Computer Science, University of Innsbruck, Innsbruck, Austria</td><td>1</td></tr><tr><td>Signal and Image Exploitation (INTELSIG), Montefiore Institute, University of Liège, Liège, Belgium</td><td>1</td></tr><tr><td>Megvii Inc., Beijing, China</td><td>1</td></tr><tr><td>Department of Informatics, Modeling, Electronics, and Systems, University of Calabria, Rende, Italy</td><td>1</td></tr><tr><td>School of Materials Science and Engineering, Central South University, Changsha, China</td><td>1</td></tr><tr><td>Institute of Energy, Jiangxi Academy of Sciences, Nanchang, China</td><td>1</td></tr><tr><td>**</td><td>1</td></tr><tr><td>Electrical and Electronic Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran</td><td>1</td></tr><tr><td>College of Mathematics and Information Engineering, Jiaxing University, Jiaxing, China</td><td>1</td></tr><tr><td>Dept. of Convergence, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, Korea</td><td>1</td></tr><tr><td>School of Mechanical and Electrical Engineering, Shandong Management University, Jinan, China</td><td>1</td></tr><tr><td>School of Information Science and Technology, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>National Institute of Advanced Industrial Science Technology, Japan</td><td>1</td></tr><tr><td>Tilburg center for Cognition and Communication, Tilburg University, Tilburg, The Netherlands</td><td>1</td></tr><tr><td>Automatics Research Group, Universidad Tecnológica de Pereira, Pereira, Colombia</td><td>1</td></tr><tr><td>School of Science, Southwest Petroleum University, Chengdu, China</td><td>1</td></tr><tr><td>Infosys Limited, Bhubaneswar, India</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Tianjin University of Technology, China</td><td>1</td></tr><tr><td>Department of Computer Science, University of Brasília, DF, Brazil 70910-900</td><td>1</td></tr><tr><td>Department of Mechanical Engineering, University of Brasília, DF, Brazil 70910-900</td><td>1</td></tr><tr><td>LIAMA, French National Institute for Research in Computer Science and Control, Paris, France</td><td>1</td></tr><tr><td>Leiden University, Leiden, The Netherlands</td><td>1</td></tr><tr><td>TNO, The Hague, The Netherlands</td><td>1</td></tr><tr><td>City University, Kowloon Tong, Hong Kong</td><td>1</td></tr><tr><td>Radboud University, EC Nijmegen, The Netherlands</td><td>1</td></tr><tr><td>TNO, Oude Waalsdorperweg, AK The Hague, The Netherlands</td><td>1</td></tr><tr><td>Liaocheng University, Liaocheng, China</td><td>1</td></tr><tr><td>Northwestern Polytechnic University, Xi’an, China</td><td>1</td></tr><tr><td>University of Science and Technology Beijing, Beijing, China</td><td>1</td></tr><tr><td>Faculty of Information Engineering, China University of Geosciences, Wuhan, China</td><td>1</td></tr><tr><td>China University of Geosciences Wuhan, China</td><td>1</td></tr><tr><td>University of Udine, Udine, Italy</td><td>1</td></tr><tr><td>INRS-EMT, Montreal, Canada</td><td>1</td></tr><tr><td>School of Computer Science and Technology, Harbin Institute of Technology at Weihai, Weihai, China</td><td>1</td></tr><tr><td>School of Computer Science Carnegie Mellon University Pittsburgh, PA, 15213, USA</td><td>1</td></tr><tr><td>College of Information and Technology, Incheon National University, Incheon, Korea</td><td>1</td></tr><tr><td>Tianjin University & University of South Carolina, Tianjin, China</td><td>1</td></tr><tr><td>School of Electronics Engineering, Kyungpook National University, Taegu, South Korea</td><td>1</td></tr><tr><td>Department of Electrical & Electronics Engineering, Kalasalingam University, Krishnankoil, India</td><td>1</td></tr><tr><td>School of Computer Engineering, Hanshin University, Osan, Republic of Korea</td><td>1</td></tr><tr><td>School of Computer Science, China University of Geosciences, Wuhan, China</td><td>1</td></tr><tr><td>College of Computer Science and Technology of Huaqiao University, Xiamen, China</td><td>1</td></tr><tr><td>CEA (iRSTV/BGE), INSERM (U1038), CNRS (FR3425), Université Grenoble-Alpes, Grenoble, France</td><td>1</td></tr><tr><td>NLPR, Institute of Automation, Chinese Academy of Science, Beijing, People’s Republic of China</td><td>1</td></tr><tr><td>Costel, Université de Rennes 2, Rennes, France</td><td>1</td></tr><tr><td>IRISA, Université de Bretagne Sud, Vannes, France</td><td>1</td></tr><tr><td>Research & Development, British Broadcasting Corporation (BBC), London, UK</td><td>1</td></tr><tr><td>Faculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, China</td><td>1</td></tr><tr><td>Wide Eyes Technologies</td><td>1</td></tr><tr><td>School of Information Engineering, Jiangxi Manufacturing Technology College, Nanchang, China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Nanjing Forestry University and Shandong University, Jinan, China</td><td>1</td></tr><tr><td>Department of Language Studies, Nanjing Forestry University, Nanjing, China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Nanjing Forestry University, Nanjing, China</td><td>1</td></tr><tr><td>Dept. of Autom. Test & Control, Harbin Inst. of Technol., China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Frederick University, Nicosia, Cyprus</td><td>1</td></tr><tr><td>The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense M, Denmark</td><td>1</td></tr><tr><td>Department of Computer Science, Digital Image Processing Laboratory, Islamia College Peshawar, Peshawar, Pakistan</td><td>1</td></tr><tr><td>Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan</td><td>1</td></tr><tr><td>Department of Computer Science, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan</td><td>1</td></tr><tr><td>Technische Universität München / Imperial College London, Munich / London, England UK</td><td>1</td></tr><tr><td>Department of Mathematics and Informatics, Ecole Centrale de Lyon, Lyon, 69134, France</td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, Jamia Hamdard University, New Delhi, India</td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, University of Minnesota-Twin Cities, Minneapolis, USA</td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary</td><td>1</td></tr><tr><td>School of Information Science and Technology, Northwest University, Xi’an, China</td><td>1</td></tr><tr><td>Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands</td><td>1</td></tr><tr><td>School of Software, Beijing Institute of Technology, Beijing, China</td><td>1</td></tr><tr><td>University of St. Andrews, UK</td><td>1</td></tr><tr><td>University of Tunis El Manar, Tunis, Tunisia</td><td>1</td></tr><tr><td>College of Information and Control Engineering, China University of Petroleum, Qingdao, China</td><td>1</td></tr><tr><td>Intel Labs Europe, Pipers Way, Swindon</td><td>1</td></tr><tr><td>Department of Computer Systems, Universidad Politécnica de Madrid, Madrid, Spain</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, Ursinus College, Collegeville, PA</td><td>1</td></tr><tr><td>Systems Engineering Institute, Xi’an Jiaotong University, Xi’an 710049, China</td><td>1</td></tr><tr><td>Institute of Semiconductors, Chinese Academy of Sciences&University of Chinese Academy of Sciences, Beijing, China</td><td>1</td></tr><tr><td>School of Computer Science and Technology, Nanjing University of Science and Technology of China, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td>NTT Network Innovation Laboratories, Nippon Telegraph and Telephone Corp.</td><td>1</td></tr><tr><td>Faculty of Computing and Information Technology, Setapak, Malaysia</td><td>1</td></tr><tr><td>Computer Science Department, University of California, Los Angeles, CA, USA</td><td>1</td></tr><tr><td>INRIA, Sophia Antipolis, France</td><td>1</td></tr><tr><td>School of Mathematics and Computer Sciences, Gannan Normal University, Ganzhou, China</td><td>1</td></tr><tr><td>University of Maribor, Faculty of Electrical Engineering and Computer Science, Koroška cesta 46, SI-2000, Slovenia</td><td>1</td></tr><tr><td>University of Tours, France</td><td>1</td></tr><tr><td>Department of Information Management, Hwa Hsia University of Technology, New Taipei City, Taiwan</td><td>1</td></tr><tr><td>Department of Electronic Engineering, National Ilan University, Yilan City, Taiwan</td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China</td><td>1</td></tr><tr><td>College of Information and Electrical Engineering, Ludong University, Yantai, China</td><td>1</td></tr><tr><td>Wakayama University</td><td>1</td></tr><tr><td>Computer Science College, Xi’an Polytechnic University, Xi’an, China</td><td>1</td></tr><tr><td>Computer Science Dept., SUNY Stony Brook, USA</td><td>1</td></tr><tr><td>School of Mathematical and Physical Sciences at the University of Newcastle, Callaghan, NSW 2308, Australia</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, JNTU College of Engineering, Hyderabad, India</td><td>1</td></tr><tr><td>Department of Physics, JNTU College of Engineering, Kakinada, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, JNTU College of Engineering, Kakinada, India</td><td>1</td></tr><tr><td>Department of Telecommunications and Information Processing, Image Processing and Interpretation, UGent/iMinds, Ghent, Belgium</td><td>1</td></tr><tr><td>School of Software, Shenyang University of Technology, Shenyang, China</td><td>1</td></tr><tr><td>School of Engineering of UABC, University of Baja California, Tijuana, Mexico</td><td>1</td></tr><tr><td>University of Hawaii at Hilo, HI, USA</td><td>1</td></tr><tr><td>Yuncheng University, Shanxi Province, China</td><td>1</td></tr><tr><td>Department of Computer Engineering, Bahçeşehir University, Istanbul, Turkey</td><td>1</td></tr><tr><td>Sichuan University West China Hospital of Stomatology, Chengdu, China</td><td>1</td></tr><tr><td>School of Software Engineering, Chengdu University of Information Technology, Chengdu, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, People’s Republic of China</td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, China</td><td>1</td></tr><tr><td>Department of Computer Engineering, Bogaziçi University, Bebek, Turkey</td><td>1</td></tr><tr><td>Department of Electrical and Electronic Engineering, Auckland University of Technology , Auckland, New Zealand</td><td>1</td></tr><tr><td>Department of Computer Engineering, Qazvin Islamic Azad University , Qazvin, Iran</td><td>1</td></tr><tr><td>Shanghai University of Finance and Economics, Shanghai, China</td><td>1</td></tr><tr><td>Graduate School of Engineering, Nagasaki University, Nagasaki, Japan</td><td>1</td></tr><tr><td>Institute of Management and Information Technologies, Chiba University, Chiba, Japan</td><td>1</td></tr><tr><td>Graduate School of Advanced Integration Science, Chiba University, Chiba, Japan</td><td>1</td></tr><tr><td>Vision Semantics Ltd</td><td>1</td></tr><tr><td>Department of Film and Digital Media, Seokyeong University, Seoul, Republic of Korea</td><td>1</td></tr><tr><td>Department of MediaSoftware, Sungkyul University, Anyang-si, Republic of Korea</td><td>1</td></tr><tr><td>Pusan National University, Busan, Korea</td><td>1</td></tr><tr><td>School of Engineering, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland</td><td>1</td></tr><tr><td>Department of Computer Science, Auckland University of Technology, Auckland, New Zealand</td><td>1</td></tr><tr><td>L3S Research Center, Leibniz Universität Hannover, Hannover, Germany</td><td>1</td></tr><tr><td>German National Library of Science and Technology (TIB), Hannover, Germany</td><td>1</td></tr><tr><td>taglicht media Film- & Fernsehproduktion GmbH, Köln, Germany</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany</td><td>1</td></tr><tr><td>School of Mathematics and Computational Science, Anqing Normal University, Anqing, People’s Republic of China</td><td>1</td></tr><tr><td>Concordia Institute for Information Systems Engineering Concordia University, Montreal, Canada</td><td>1</td></tr><tr><td>IKERBASQUE, Basque Foundation for Science, Bilbao, Spain</td><td>1</td></tr><tr><td>University of the Basque Country UPV/EHU, San Sebastian, Spain</td><td>1</td></tr><tr><td>Computer Vision Center, Edifici “O”, Campus UAB, Bellaterra, Spain</td><td>1</td></tr><tr><td>Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki City, Japan</td><td>1</td></tr><tr><td>Xiamen University of Technology, Fujian, China</td><td>1</td></tr><tr><td>School of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, China</td><td>1</td></tr><tr><td>Dept. of Artificial Intelligence, Faculty of Computer Engineering, University of Isfahan, Iran</td><td>1</td></tr><tr><td>Department of Information Processing Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology Yokohama 226-8503, Japan</td><td>1</td></tr><tr><td>Departament d’Informática, Universitat de Valéncia, Av. de la Universitat s/n, 46100-Burjassot, Spain</td><td>1</td></tr><tr><td>Department of Computer Science, University of Texas, San Antonio, TX, USA</td><td>1</td></tr><tr><td>University of Sheffield, Sheffield, United Kingdom</td><td>1</td></tr><tr><td>Insititute of Automation, Chinese Academy of Sciences (CAS), Beijing, China</td><td>1</td></tr><tr><td>School of Computing and Information Systems, University of Melbourne, Melbourne, Australia</td><td>1</td></tr><tr><td>Sapienza Università di Roma, Roma, Italy</td><td>1</td></tr><tr><td>Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian, University, Xi'an 710071, China</td><td>1</td></tr><tr><td>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. tulyakov@cedar.buffalo.edu</td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China</td><td>1</td></tr><tr><td>College of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China</td><td>1</td></tr><tr><td>LAMIA, EA 4540, University of French West Indies & Guyana</td><td>1</td></tr><tr><td>Peking University & Shanghai Jaio Tong University, Beijing, China</td><td>1</td></tr><tr><td>School of Information Technology, Madurai Kamarai University, Madurai, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, Sanjivani College of Engineering, Kopargaon, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, St.Peter’s University, Chennai, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, Panimalar Engineering College, Chennai, India</td><td>1</td></tr><tr><td>Department of Computer Science, IT-Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>1</td></tr><tr><td>ITI Department Telecom Bretagne, Brest, France</td><td>1</td></tr><tr><td>Adobe Systems Incorporated, San Jose, CA, 95110</td><td>1</td></tr><tr><td>Department of Electrical Engineering and Information Technology, TU Darmstadt, D-64283, Germany</td><td>1</td></tr><tr><td>Institute of Neural Information Processing, University of Ulm, Ulm, Germany</td><td>1</td></tr><tr><td>Institute for Information Technology and Communications (IIKT), Otto-von-Guericke-University Magdeburg, Magdeburg, Germany</td><td>1</td></tr><tr><td>Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran</td><td>1</td></tr><tr><td>Defence Science and Technology Organisation (DSTO), Edinburgh, Australia</td><td>1</td></tr><tr><td>Reallusion Corporation</td><td>1</td></tr><tr><td>National Institute of Advanced Industrial Science and Technology (AIST), Koto, Tokyo, Japan</td><td>1</td></tr><tr><td>Computer Application Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</td><td>1</td></tr><tr><td>Dept. of EE, Univ. at Buffalo, SUNY, USA</td><td>1</td></tr><tr><td>Department of Computer Science, Minjiang University, Fuzhou, People’s Republic of China</td><td>1</td></tr><tr><td>Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Hafez Ave., Tehran, Iran</td><td>1</td></tr><tr><td>Institute of High Performance Computing and Networking, National Research Council of Italy (ICAR-CNR), Naples, Italy</td><td>1</td></tr></table></body></html>
\ No newline at end of file +<!doctype html><html><head><meta charset='utf-8'><title>Unknown Institutions from DOI</title><link rel='stylesheet' href='reports.css'></head><body><h2>Unknown Institutions from DOI</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>NC A&T State University, Greensboro, NC, USA</td><td>6</td></tr><tr><td>School of Information and Software Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, 610054, China P.R.C</td><td>6</td></tr><tr><td>Electronics and Telecommunications Research Institute, Korea</td><td>5</td></tr><tr><td>Asian Institute of Technology (AIT), Pathum Thani 12120, Thailand</td><td>5</td></tr><tr><td>Chonnam National University, Gwangju, Korea</td><td>5</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Durgapur, India</td><td>5</td></tr><tr><td>Chongqing Institute of Green and Intelligent Technology, CAS, Chongqing, 400714</td><td>5</td></tr><tr><td>SIAT at Chinese Academy of Sciences, China</td><td>5</td></tr><tr><td>Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy</td><td>5</td></tr><tr><td>University of Southern California Institute for Creative Technologies, Los Angeles, CA</td><td>5</td></tr><tr><td>Department of Electronics and Telecommunication Engineering, Don Bosco Institute of Technology, Kurla (W), Mumbai, India</td><td>5</td></tr><tr><td>R V College of Engineering, Department of Computer Science and Engineering, Bangalore, India</td><td>5</td></tr><tr><td>Inst. Nat. des Telecommun., Evry, France</td><td>5</td></tr><tr><td>Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering</td><td>4</td></tr><tr><td>Department of Microelectornics and Computer Science, Lodz University of Technology, ul. Wolczanska 221/223, 90-924, Poland</td><td>4</td></tr><tr><td>North China Electric Power University Department of Electronic and Communication Engineering Baoding, Hebei, China</td><td>4</td></tr><tr><td>School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand</td><td>4</td></tr><tr><td>KU Leuven, Leuven, Belgium</td><td>4</td></tr><tr><td>Academia Sinica, Taipei, Taiwan</td><td>4</td></tr><tr><td>LIARA Laboratory, University of Quebec at Chicoutimi (UQAC), Boulevard de l'Université, Chicoutimi (Quebec), Canada</td><td>4</td></tr><tr><td>Dept. of Computing, Curtin University GPO Box U1987, Perth, WA 6845</td><td>4</td></tr><tr><td>NTT Software Innovation Center, Tokyo, Japan</td><td>4</td></tr><tr><td>EECS Department, University of Kansas, Lawrence, KS</td><td>4</td></tr><tr><td>Department of Mathematics and Computer Science University of Basel</td><td>4</td></tr><tr><td>Goa University, India</td><td>4</td></tr><tr><td>Beijing Key Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081, China</td><td>4</td></tr><tr><td>VUB-NPU Joint AVSP Research Lab, Vrije Universiteit Brussel (VUB), Deptartment of Electronics & Informatics (ETRO), Pleinlaan 2, 1050 Brussel, Belgium</td><td>4</td></tr><tr><td>Graduate School of Information Science, Nara Institute of Science and Technology, Takayama-cho 8916-5, Ikoma-shi, Nara, Japan</td><td>4</td></tr><tr><td>Smart Surveillance Interest Group, Department of Computer Science, Universidade Federal de Minas Gerais, Minas Gerais, Brazil</td><td>4</td></tr><tr><td>Shanghai University School of Communication and Information Engineering Shanghai, China</td><td>4</td></tr><tr><td>Microsoft, Redmond, WA, USA</td><td>4</td></tr><tr><td>Computer Science and Engineering, Pennsylvania State University, PA, USA SiliconScapes, LLC, PA, USA</td><td>4</td></tr><tr><td>Dept. of Computer Engineering, Keimyung University, Daegu, Korea</td><td>4</td></tr><tr><td>National ICT Australia and UNSW, Sydney, Australia</td><td>4</td></tr><tr><td>Department of Electrical and Computer Engineering, Beckman Institute Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, IL, USA</td><td>4</td></tr><tr><td>Universiti Kuala Lumpur, Kuala Lumpur</td><td>4</td></tr><tr><td>Beijing Normal Univeristy, Beijing, China</td><td>4</td></tr><tr><td>University of Tunis, The National Higher school of engineers of Tunis (ENSIT), Laboratory of Signal Image and Energy Mastery, LR13ES03 (SIME), Tunis, Tunisia</td><td>4</td></tr><tr><td>Media Technology Lab, Huawei Technologies Co., Ltd</td><td>4</td></tr><tr><td>Department of Computer Graphics and Multimedia, University of Brno, Brno, Czech Republic</td><td>4</td></tr><tr><td>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA</td><td>4</td></tr><tr><td>Faculty of Engineering, Ain Shams University, Computer and Systems Engineering Department, Cairo, Egypt</td><td>4</td></tr><tr><td>School of Automation and Information Engineering, Xi'an University of Technology, Xi'an, China</td><td>4</td></tr><tr><td>Computer Science and Engineering Dept., University of Nevada Reno, USA</td><td>4</td></tr><tr><td>Department of Information and Control, B-DAT Laboratory, Nanjing University of Information and Technology, Nanjing, China</td><td>4</td></tr><tr><td>Inha University, South Korea</td><td>4</td></tr><tr><td>Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China</td><td>4</td></tr><tr><td>Institute for Human-Machine Communication, Technische Universität München, Germany</td><td>4</td></tr><tr><td>Faculty of Engineering Science, Department of Systems Innovation, Arai Laboratory at Osaka University, Japan</td><td>4</td></tr><tr><td>NTT Corporation, Atsugi, Japan</td><td>3</td></tr><tr><td>Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beersheba, Israel</td><td>3</td></tr><tr><td>Intel Labs China, Beijing, China</td><td>3</td></tr><tr><td>School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun, CO 130012 China</td><td>3</td></tr><tr><td>Radboud University, Nijmegen, Netherlands</td><td>3</td></tr><tr><td>Algılayıcılar, Görüntü ve Sinyal İşleme Grubu, HAVELSAN A.Ş. Ankara, Türkiye</td><td>3</td></tr><tr><td>Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany</td><td>3</td></tr><tr><td>School of Electrical and Computer Engineering, Royal Melbourne Institute of Technology University , Melbourne, Australia</td><td>3</td></tr><tr><td>School of Engineering, University of Baja California, Tijuana, México</td><td>3</td></tr><tr><td>School of Computer Science, Center for Optical Imagery Analysis and Learning (OPTIMAL)</td><td>3</td></tr><tr><td>Department of Systems and Computing, Federal University of Campina Grande, Av. Apríigio Veloso, 882, 58429-900 Campina Grande, PB, Brazil</td><td>3</td></tr><tr><td>R&D Centre Algoritmi, School of Engineering, University of Minho, Portugal</td><td>3</td></tr><tr><td>Department of Control and Computer Engineering, Politecnico di Torino, Italy</td><td>3</td></tr><tr><td>Center for Research in Intelligent Systems, University of California, Riverside Riverside, CA 92521-0425, USA</td><td>3</td></tr><tr><td>Shanghai Advanced Research Institute, CAS, Shanghai, China</td><td>3</td></tr><tr><td>Department of electronic engineering, Key Lab of Intelligent Perception and Image Understanding of Ministry of Education, Xi'an, China</td><td>3</td></tr><tr><td>Computer Vision Laboratory, ETH Zurich, Sternwartstrasse 7, 8092, Switzerland</td><td>3</td></tr><tr><td>BITS Pilani, Pilani , India</td><td>3</td></tr><tr><td>Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, Howrah-711 103, India</td><td>3</td></tr><tr><td>Dept. of CS&E, IIT Madras, India</td><td>3</td></tr><tr><td>Graduate School of System Design Tokyo Metropolitan University Tokyo, Japan</td><td>3</td></tr><tr><td>Face Aging Group, Computer Science Department, UNCW, USA</td><td>3</td></tr><tr><td>City University of New York, New York, NY, USA</td><td>3</td></tr><tr><td>Department of Computer Science and Engineering, Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India</td><td>3</td></tr><tr><td>Ghent University, Ghent, Belgium</td><td>3</td></tr><tr><td>Columbia Univeristy, New York, NY, USA</td><td>3</td></tr><tr><td>Microsoft Research Cambridge</td><td>3</td></tr><tr><td>Center for Automation Research, UMIACS University of Maryland, College Park, MD 20742</td><td>3</td></tr><tr><td>School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, U.K.</td><td>3</td></tr><tr><td>School of Information and Communication Engineering, Beijing University of Posts and Telcommunications, Beijing, China</td><td>3</td></tr><tr><td>Gwangju Institute of Science and Technology, 123, Cheomdangwagi-ro, Buk-gu, Gwangju, South Korea</td><td>3</td></tr><tr><td>Institute of Mathematical and Computer Sciences, University of Sao Paulo, Sao Paulo, Brazil</td><td>3</td></tr><tr><td>Dept. of Informatics, Aristotle Univ. of Thessaloniki, Greece</td><td>3</td></tr><tr><td>NTT Media Intelligence Laboratories, Tokyo, Japan</td><td>3</td></tr><tr><td>Beijing Institute of Graphic Communication, Beijing</td><td>3</td></tr><tr><td>Nara Institute of Science and Technology, Japan</td><td>3</td></tr><tr><td>Department of Computer, the University of Suwon, Korea</td><td>3</td></tr><tr><td>Department of Electrical and Computer Engineering, Florida Institute of Technology, Melbourne, USA</td><td>3</td></tr><tr><td>Dept. of Computer Science and Engineering, St. Joseph's College of Engineering and Technology, Palai, Kerala, India</td><td>3</td></tr><tr><td>Dept. of Computer Science and Electrical Engineering, University of Missouri-Kansas City, MO, USA</td><td>3</td></tr><tr><td>Inha University, Incheon, South Korea</td><td>3</td></tr><tr><td>Center for Research on Intelligent Perception and Computing</td><td>3</td></tr><tr><td>Thiagarajar College of Engineering, Madurai, Tamilnadu, India</td><td>3</td></tr><tr><td>Dept. of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan</td><td>3</td></tr><tr><td>School of Electrical and Electronic Engineering, Singapore</td><td>3</td></tr><tr><td>Universidade Nova Lisboa, Lisboa, Portugal</td><td>3</td></tr><tr><td>State Key Laboratory of Management and Control for Complex Systems, Institute of Automation Chinese Academy of Sciences, Beijing, China 100190</td><td>3</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology Uttarakhand, Srinagar Garhwal, India</td><td>3</td></tr><tr><td>Dept. of Mediamatics, Delft Univ. of Technol., Netherlands</td><td>3</td></tr><tr><td>Department of Information Science and Engineering, Changzhou University, Changzhou, China</td><td>3</td></tr><tr><td>Institute for Infocomm Research, A*STAR, Singapore, Singapore</td><td>3</td></tr><tr><td>Ashikaga Institute of Technology, Ashikaga, Japan</td><td>3</td></tr><tr><td>Institute of Applied Computer Science, Kiel University of Applied Sciences, Kiel, Germany</td><td>3</td></tr><tr><td>Central China Normal University, Wuhan, China</td><td>3</td></tr><tr><td>Chongqing University of Posts and Telecommunications Chongqing, China</td><td>3</td></tr><tr><td>School of Computer Science and Software Engineering University of Wollongong, Australia</td><td>3</td></tr><tr><td>Phonexia, Brno-Krlovo Pole, Czech Republic</td><td>3</td></tr><tr><td>Department of Applied Mechanics, Chalmers University of Technology, SE-412 96 Göteborg, Sweden</td><td>3</td></tr><tr><td>Technische Universität München, Munich, Germany</td><td>3</td></tr><tr><td>University of California, Los Angeles, CA Dept. of Electrical Engineering</td><td>3</td></tr><tr><td>Academia Sinica, Taipei, Taiwan Roc</td><td>3</td></tr><tr><td>Dept. of Cybernetics and Artificial Intelligence, FEI TU of Košice, Slovak Republic</td><td>3</td></tr><tr><td>Image and Video Systems Lab, School of Electrical Engineering, KAIST, Republic of Korea</td><td>3</td></tr><tr><td>Information and media processing laboratories, NEC Corporation</td><td>3</td></tr><tr><td>Southern Illinois University at Carbondale, IL, USA</td><td>3</td></tr><tr><td>School of Automation and Electrical Engineering, University of Science and Technology Beijing, 100083, China</td><td>3</td></tr><tr><td>School of Software, Jiangxi Normal University, Nanchang, China</td><td>3</td></tr><tr><td>Department of Computer Science, Pontificia Universidad Cato´lica de Chile</td><td>3</td></tr><tr><td>Fujitsu Laboratories, Kawasaki, Kanagawa, Japan</td><td>3</td></tr><tr><td>Department of Electronic and Computer Engineering National Taiwan University of Science and Technology</td><td>3</td></tr><tr><td>New York University Abu Dhabi & NYU Tandon School of Engineering, Abu Dhabi, Uae</td><td>3</td></tr><tr><td>Intelligent Vision Research Lab, Department of Computer Science, Federal University of Bahia</td><td>3</td></tr><tr><td>Department of Electronic Measuring systems, Moscow Engineering Physics Institute, National Research Nuclear University MEPhI, Moscow, Russia</td><td>3</td></tr><tr><td>National Ilan University, Ilan, Taiwan Roc</td><td>2</td></tr><tr><td>China Electronics Standardization Institute, Beijing, 100007</td><td>2</td></tr><tr><td>Universidade Nova de Lisboa, Caparica, Portugal</td><td>2</td></tr><tr><td>Universidad Tecnica Federico Santa Maria, Department of Electronic Engineering, Valparaiso, Chile</td><td>2</td></tr><tr><td>Dept. of Comput. Syst., Univ. of Technol., Sydney, NSW, Australia</td><td>2</td></tr><tr><td>Dept. of Comput. Sci., York Univ., UK</td><td>2</td></tr><tr><td>The Australian National University RSCS, ANU, Canberra, Australia</td><td>2</td></tr><tr><td>Dept. of Computer Science, YiLi Normal College, Yining, China 835000</td><td>2</td></tr><tr><td>School of Computing and Communications, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia</td><td>2</td></tr><tr><td>Department of Electrical and Computer Engineering, Singapore</td><td>2</td></tr><tr><td>Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td>Instituto de Telecomunicações & Faculdade de Ciěncias da Universidade do Porto</td><td>2</td></tr><tr><td>Department of Information Management, National Formosa University, Huwei, Yulin 632, Taiwan</td><td>2</td></tr><tr><td>Dept of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Kavala, Greece</td><td>2</td></tr><tr><td>University of Ulm, Ulm, Germany</td><td>2</td></tr><tr><td>Dept. of Eng. Sci., Oxford Univ., UK</td><td>2</td></tr><tr><td>Human-Machines Interaction (HMI) Laboratory, Department of Industrial Informatics, TEI of Kavala, Kavala, Greece</td><td>2</td></tr><tr><td>Dept. of ECE, Maryland Univ., College Park, MD, USA</td><td>2</td></tr><tr><td>Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey</td><td>2</td></tr><tr><td>Electrical & Electronic Engineering Department, Mevlana University Konya, Turkey</td><td>2</td></tr><tr><td>GIPSA Laboratory, Image and Signal Department, Grenoble Institute of Technology, Grenoble, France</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, India</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, National Taiwan Ocean University, No.2, Beining Rd., Keelung 202, Taiwan</td><td>2</td></tr><tr><td>Bilgisayar Mühendisliği Bölümü, Deniz Harp Okulu, İstanbul, Türkiye</td><td>2</td></tr><tr><td>Statistical Machine Intelligence & LEarning, School of Computer Science & Engineering University of Electronic Science and Technology of China, 611731, China</td><td>2</td></tr><tr><td>Masaryk University, Brno, Czech Rep</td><td>2</td></tr><tr><td>Charles University, Prague, Czech Rep</td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada</td><td>2</td></tr><tr><td>Department of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Human Machines Interaction (HMI) Laboratory, 65404 Kavala, Greece</td><td>2</td></tr><tr><td>University of British Columbia Department of Electrical and Computer Engineering</td><td>2</td></tr><tr><td>School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, University of Califonia, San Diego</td><td>2</td></tr><tr><td>University of Missouri Department of Electrical and Computer Engineering Columbia, MO, USA</td><td>2</td></tr><tr><td>Inf. Syst. Dept., Buckingham Univ., UK</td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA</td><td>2</td></tr><tr><td>Department of Computer Science & Engineering, POSTECH, Pohang, Sourth Korea, 37673</td><td>2</td></tr><tr><td>Coursera and Stanford University</td><td>2</td></tr><tr><td>Dept. of Electron. & Inf., Toyota Technol. Inst., Nagoya, Japan</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, POSTECH, Pohang 790-784, Republic of Korea</td><td>2</td></tr><tr><td>Dept. of Comput. Sci., New York State Univ., Binghamton, NY, USA</td><td>2</td></tr><tr><td>Dept. of Electrical Engineering, National Institute of Technology, Rourkela, India 769008</td><td>2</td></tr><tr><td>Department of Computer Science, Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>2</td></tr><tr><td>School of Computer Science and Technology, Tianjin University&Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China</td><td>2</td></tr><tr><td>NPU-VUB Joint AVSP Research Lab, School of Computer Science, Northwestern Polytechnical University (NPU) Shaanxi Key Lab on Speech and Image Information Processing, 127 Youyi Xilu, Xi'an 710072, China</td><td>2</td></tr><tr><td>Research&Advanced Technology Division of SAIC Motor Corporation Limited, Shanghai 201804, P.R China</td><td>2</td></tr><tr><td>Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China</td><td>2</td></tr><tr><td>Dept. of Computer Science and Information Engineering, Southern Taiwan University of Science and Technology, Tainan City, Taiwan</td><td>2</td></tr><tr><td>Dept. of Electronics and Telecommunication Engg., KCT's Late G.N. Sapkal college of Engineering, Nashik, India</td><td>2</td></tr><tr><td>Tencent Inc</td><td>2</td></tr><tr><td>Facebook Inc., Menlo Park, CA, USA</td><td>2</td></tr><tr><td>Computational Intelligence Lab, Institute of Informatics and Telecommunications, NCSR Demokritos, Athens, Greece</td><td>2</td></tr><tr><td>Dept. of Electrical Engineering, National Tsing-Hua University, Taiwan</td><td>2</td></tr><tr><td>Department Informatik, Hamburg University of Applied Sciences, Hamburg, Germany</td><td>2</td></tr><tr><td>Department Informatik, Hamburg University of Applied Sciences, Engineering and Computing, University of the West of Scotland</td><td>2</td></tr><tr><td>Elektronik ve Haberleşme Mühendisliği Bölümü, Yıldız Teknik Üniversitesi, İstanbul, Türkiye</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering of Systems, University of Zaragoza, Escuela Universitaria Politécnica de Teruel, Teruel, Spain</td><td>2</td></tr><tr><td>Department of Automation, North-China University of Technology, Beijing, China</td><td>2</td></tr><tr><td>Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia</td><td>2</td></tr><tr><td>Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, P.R. China</td><td>2</td></tr><tr><td>Indian Statistical Insitute, Kolkata 700108</td><td>2</td></tr><tr><td>Centre for Secure Information Technologies, Queen’s University Belfast, Belfast, UK</td><td>2</td></tr><tr><td>Wrocław University of Science and Technology, Wrocław, Poland</td><td>2</td></tr><tr><td>Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi, India</td><td>2</td></tr><tr><td>Department of Electronics and Communication Engineering Malaviya National Institute of Technology Jaipur, Rajasthan, India</td><td>2</td></tr><tr><td>Department of Electrical Engineering Malaviya National Institute of Technology Jaipur, Rajasthan, India</td><td>2</td></tr><tr><td>Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education, Chongqing, China</td><td>2</td></tr><tr><td>Osaka University Health Care Center, Japan</td><td>2</td></tr><tr><td>Shahid Bahonar University of Kerman Computer Engineering Department, Kerman, Iran</td><td>2</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT) & Università di Torino, Genova, Italy</td><td>2</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT) & Università degli Studi di Genova, Genova, Italy</td><td>2</td></tr><tr><td>Norwegian Biometric Laboratory, Norwegian University of Science and Technology (NTNU), Gjøvik, Norway</td><td>2</td></tr><tr><td>Department of Computer Applications, National Institute of Technology, Tiruchirappalli, India</td><td>2</td></tr><tr><td>B. Tech Graduate, ECE, MSIT, C-4 Janakpuri, New Delhi, India</td><td>2</td></tr><tr><td>San Diego State University, San Diego, CA, USA</td><td>2</td></tr><tr><td>MIT, Cambridge, MA, USA</td><td>2</td></tr><tr><td>Dept of Electronics and Communication, Manipal Institute Of Technology, Karnataka, India</td><td>2</td></tr><tr><td>LMU Munich, Germany</td><td>2</td></tr><tr><td>Polytechnic School of Pernambuco, University of Pernambuco, Recife-PE, Brazil</td><td>2</td></tr><tr><td>Başkent University, Ankara, TURKEY</td><td>2</td></tr><tr><td>Department of Electronic and Communication Engineering, Universiti Tenaga Nasional Km 7, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia</td><td>2</td></tr><tr><td>Sunway University, Selangor, Malaysia</td><td>2</td></tr><tr><td>Northwestern Polytechnical University Xian, P. R. China</td><td>2</td></tr><tr><td>Dept. of E & TC Engineering, Maharashtra Institute of Technology, Pune, India</td><td>2</td></tr><tr><td>Dept. of ECE and Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Hong Kong</td><td>2</td></tr><tr><td>School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, 689-798, Korea</td><td>2</td></tr><tr><td>Dept. of Comp. Sci. and Inf. Eng, Chung Hua University, Hsinchu, Taiwan</td><td>2</td></tr><tr><td>Shanghai Jiao Tong University & Alibaba Group, Shanghai, China</td><td>2</td></tr><tr><td>School of Computer Science, Kyungpook National University, Buk-gu, Daegu, The Republic of Korea</td><td>2</td></tr><tr><td>Laboratory LAROSERI, Department of Computer Science, Faculty of Sciences, University of Chouaib Doukkali, El Jadida - Morocco</td><td>2</td></tr><tr><td>Microsoft Research India Pvt. Ltd, Bangalore, Karnataka, India</td><td>2</td></tr><tr><td>Department of Electronics, University of Goa, India</td><td>2</td></tr><tr><td>Department of ECE, National Institute of Technology, Rourkela (Odisha), India</td><td>2</td></tr><tr><td>Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China</td><td>2</td></tr><tr><td>B-DAT Laboratory, School of Information and Control, Nanjing University of Information and Technology, Nanjing, China</td><td>2</td></tr><tr><td>Thales Services, ThereSIS, Palaiseau, France</td><td>2</td></tr><tr><td>School of Electrical and Electronic Engineering, Tianjin University of Technology, China</td><td>2</td></tr><tr><td>Department of Computer Science and Engineering, Mepco Schlenk Engineering College, Sivakasi, India</td><td>2</td></tr><tr><td>IIIT Bangalore, India</td><td>2</td></tr><tr><td>Institut de Robòtica i Informàtica Industrial (CSIC-UPC)</td><td>2</td></tr><tr><td>Department of Computer Science, IT: Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>2</td></tr><tr><td>Xinjiang University, Urumqi, China</td><td>2</td></tr><tr><td>School of Computing Science and Engineering, VIT University, Vellore, India</td><td>2</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA</td><td>2</td></tr><tr><td>GSI Universidad Polit-écnica de Madrid, Madrid, Spain</td><td>2</td></tr><tr><td>Department of Electronic Engineering, Kwangwoon University, Seoul, Republic of Korea</td><td>2</td></tr><tr><td>Dept. of Appl. Phys. & Electron., Umea Univ., Sweden</td><td>2</td></tr><tr><td>Universidade Federal do Paraná, Curitiba, Brazil</td><td>2</td></tr><tr><td>Università degli Studi di Verona, Verona, Italy</td><td>2</td></tr><tr><td>CEA, Gif-Sur-Yvette, France</td><td>2</td></tr><tr><td>UMR CNRS - Univ. Bourgogne, Dijon, France</td><td>2</td></tr><tr><td>Mechatronic Engineering Department, Mevlana University, Konya, Turkey</td><td>2</td></tr><tr><td>TÜBİITAK-BİILGEM-UEKAE, Anibal Cad., P.K.74, 41470, Gebze-KOCAELİ, Turkey</td><td>2</td></tr><tr><td>The 28th Research Institute of China Electronics Technology Group Corporation, China</td><td>2</td></tr><tr><td>Raytheon BBN Technologies, 10 Moulton St, Cambridge, MA</td><td>2</td></tr><tr><td>School of Electrical Engineering and Computer Science at the University of Newcastle, Callaghan, NSW 2308, Australia</td><td>2</td></tr><tr><td>Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India</td><td>2</td></tr><tr><td>Pontifícia Universidade Católica do RS, Porto Alegre-RS, Brazil</td><td>2</td></tr><tr><td>Waseda University The Graduate School of Information, Production and Systems 2-7, Hibikino, Wakamatsu-ku, Kitakyushu-shi, Fukuoka, Japan</td><td>2</td></tr><tr><td>Majority Report, France</td><td>2</td></tr><tr><td>SITI Laboratory, National Engineering School of Tunis (ENIT), University of Tunis El Manar, Tunis, Tunisia</td><td>2</td></tr><tr><td>University of Montreal, Department of Computer Science and Operations Research (DIRO), 2920 Chemin de la tour, QC, Canada, H3C 3J7</td><td>2</td></tr><tr><td>Università di Salerno, Fisciano (SA), Italy</td><td>2</td></tr><tr><td>Advanced Technologies Application Center 7a #21406 b/ 214 and 216, P.C. 12200, Siboney Playa, Havana, Cuba</td><td>2</td></tr><tr><td>School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an, China</td><td>2</td></tr><tr><td>Department of Sciences and Information Technology, University of Sassari, Viale Mancini 5, 07100 Sassari, Italy</td><td>2</td></tr><tr><td>Department of Electrical Engineering and Computer Science, University of Siegen, Siegen, Germany</td><td>2</td></tr><tr><td>Department of Computer Science and Information Engineering, National Formosa University, Yunlin 632, Taiwan</td><td>2</td></tr><tr><td>Broadcasting & Telecommunications, Convergence Media Research Department, Electronics and Telecommunications Research Institute, Daejeon, Korea</td><td>2</td></tr><tr><td>Dept. of ECE & Digital Technology Center, Univ. of Minnesota, USA</td><td>2</td></tr><tr><td>FMV IŞIK Üniversitesi, Şile, Istanbul</td><td>2</td></tr><tr><td>Lehrstuhl für Mustererkennung, FAU Erlangen – Nürnberg, Erlangen, Germany</td><td>1</td></tr><tr><td>Nanjing University of Posts and Telecommunications, China</td><td>1</td></tr><tr><td>Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung, Taiwan</td><td>1</td></tr><tr><td>Laboratoire d’interprétation et de traitement d’images et vidéo, Polytechnique Montréal, Montreal, Canada</td><td>1</td></tr><tr><td>Laboratoire d’imagerie de vision et d’intelligence artificielle, École de technologie supérieure, Université du Québec, Montreal, Canada</td><td>1</td></tr><tr><td>University of Bern, Bern, Switzerland</td><td>1</td></tr><tr><td>School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, PR China</td><td>1</td></tr><tr><td>Department of Computer Science, University of California at Davis, Davis, USA</td><td>1</td></tr><tr><td>Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Shri Shankaracharya Technical Campus, Bhilai, District-Durg, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi, India</td><td>1</td></tr><tr><td>College of Artificial Intelligenge and Big Data, ChongQing University of Electronic Engineering, Chongqing, China</td><td>1</td></tr><tr><td>Laboratoire Jean Kuntzmann, Grenoble, France</td><td>1</td></tr><tr><td>Dept. of Advanced Technologies, Alcorn State University, MS, USA</td><td>1</td></tr><tr><td>Department of Industrial Design, Tatung University, Taipei 104, Republic of China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Tatung University, Taipei 104, Republic of China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Yangzhou University, Yangzhou, People’s Republic of China</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Nanjing University of Science & Technology, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td>School of Information Engineering, Yangzhou University, Yangzhou, China</td><td>1</td></tr><tr><td>Res. Center for Learning Sci., Southeast Univ., Jiangsu, China</td><td>1</td></tr><tr><td>Eedoo Inc, Beijing, China</td><td>1</td></tr><tr><td>CSE, SUNY at Buffalo, USA and Southeast University, China</td><td>1</td></tr><tr><td>School of Information Technology and Engineering, VIT University, Vellore, India</td><td>1</td></tr><tr><td>Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881</td><td>1</td></tr><tr><td>Vulcan Inc, Seattle, WA 98104</td><td>1</td></tr><tr><td>Dept. of Computing, Curtin University of Technology, WA 6102, USA</td><td>1</td></tr><tr><td>School of Software, Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td>University of California, Santa Cruz & Ghent University, Santa Cruz, CA, USA</td><td>1</td></tr><tr><td>Computer Vision Research lab, Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran</td><td>1</td></tr><tr><td>HAN University of Applied Sciences, Arnhem, Netherlands</td><td>1</td></tr><tr><td>Faculty of Information Technology, Barrett Hodgson University, Karachi, Pakistan</td><td>1</td></tr><tr><td>Laboratoire Hubert Curien, UMR5516, Université Jean Monnet, Saint-Etienne, France</td><td>1</td></tr><tr><td>Université de Lyon, CNRS, LIRIS, UMR5205, Université Lyon 1, Lyon, France</td><td>1</td></tr><tr><td>Department of Electrical and Computer Engineering, Saginaw Valley State University, University Ctr, MI- 48710</td><td>1</td></tr><tr><td>TCTS Lab, Faculté Polytechnique de Mons, Belgium</td><td>1</td></tr><tr><td>Speech Technology Group, Technical University of Madrid, Spain</td><td>1</td></tr><tr><td>TALP Research Center, Universitat Politècnica de Catalunya, Spain</td><td>1</td></tr><tr><td>TELE Lab, Université catholique de Louvain, Belgium</td><td>1</td></tr><tr><td>INRIA Grenoble-Rhône-Alpes Research Center, France</td><td>1</td></tr><tr><td>Department of Embedded Systems, Institute for Infocomm Research, Singapore</td><td>1</td></tr><tr><td>E.T.S. Ingenieros Industriales, Universidad de Castilla-La Mancha Campus Universitario, Ciudad Real, Spain</td><td>1</td></tr><tr><td>Universidad de Las Palmas de Gran Canaria, SIANI, Edificio Central del Parque Científico-Tecnológico, Las Palmas, Spain</td><td>1</td></tr><tr><td>School of Math and Geospatial Sciences, Royal Melbourne Institute of Technology University , Melbourne, Australia</td><td>1</td></tr><tr><td>Department of Computer Science and Application, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou, China</td><td>1</td></tr><tr><td>School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China</td><td>1</td></tr><tr><td>Department of Electrical and Computer Engineering, Naresuan University, Muang, Thailand</td><td>1</td></tr><tr><td>Department of Computer Science, Christian-Albrechts University, Kiel, Germany</td><td>1</td></tr><tr><td>Engineering Lab on Intelligent Perception for Internet of Things, Peking University Shenzhen Graduate School, Shenzhen, China</td><td>1</td></tr><tr><td>Delft University of Technology and Sensor Technology, Netherlands Defense Academy</td><td>1</td></tr><tr><td>School of Electrical Engineering and Automation, Qilu University of Technology, Jinan, China</td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China</td><td>1</td></tr><tr><td>Department of Electronics and Computing and the Electronics and Information Technology Research & Development Center, Universidade Federal do Amazonas, Manaus-AM, CEP, Brazil</td><td>1</td></tr><tr><td>University of California at Merced, Merced, USA</td><td>1</td></tr><tr><td>Technische Universität München, Garching, Germany</td><td>1</td></tr><tr><td>School of Big Data and Computer, Science, Guizhou Normal University, Guiyang, Guizhou, 550025, P. R. China</td><td>1</td></tr><tr><td>University of California at Santa Cruz, Santa Cruz, California</td><td>1</td></tr><tr><td>Network Center, Huizhou University, Huizhou, China</td><td>1</td></tr><tr><td>Faculty of Engineering, Computer Engineering Department, Akdeniz University, Dumlupinar Bulvari, Turkey</td><td>1</td></tr><tr><td>IRCICA, Parc Scientifique de la Haute Borne, Lille 1 University, Villeneuve d’Ascq, France</td><td>1</td></tr><tr><td>Data and Analytics Department, KPMG AGWPG, Düsseldorf, Germany</td><td>1</td></tr><tr><td>Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China</td><td>1</td></tr><tr><td>JiangSu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise, Suzhou, China</td><td>1</td></tr><tr><td>Université de Lorraine, LORIA, UMR 7503</td><td>1</td></tr><tr><td>Department of Electrical Engineering, The City College of New York, New York, USA</td><td>1</td></tr><tr><td>Robótica y Manufactura Avanzada, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ramos Arizpe, Mexico</td><td>1</td></tr><tr><td>School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, India</td><td>1</td></tr><tr><td>Dept. de Ciência da Computacão, Universidade Federal de Ouro Preto, MG Brazil</td><td>1</td></tr><tr><td>Department of Electrical Engineering, University of California, Riverside, Riverside CA, California 92521 United States</td><td>1</td></tr><tr><td>Department of CSE, Regional Campus of Anna University, Tirunelveli 627007, India</td><td>1</td></tr><tr><td>Dalian Key Laboratory of Digital Technology for National Culture, Dalian Minzu University, Dalian, China</td><td>1</td></tr><tr><td>Department of Business Planning & Information Systems, TEI of Crete, Agios Nikolaos, Greece</td><td>1</td></tr><tr><td>School of Information Technology Jawaharlal Nehru Technological University Hyderabad Andhra Pradesh, India</td><td>1</td></tr><tr><td>Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France</td><td>1</td></tr><tr><td>School of Computer ScienceThe University of Adelaide</td><td>1</td></tr><tr><td>Shanghai Advanced Research Institute, CAS & Qiniu AI Lab, Shanghai, China</td><td>1</td></tr><tr><td>University of Lyon, LIRIS - CNRS, National Institute of Applied Sciences (INSA), Lyon, France</td><td>1</td></tr><tr><td>Toyohashi University of Technology, Toyohashi, Japan</td><td>1</td></tr><tr><td>Department of Informatics, King’s College London, Strand, London, UK</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China</td><td>1</td></tr><tr><td>Department of Learning and Digital Technology, Fo Guang University, Yilan, Taiwan</td><td>1</td></tr><tr><td>BITS Pilani, India , India</td><td>1</td></tr><tr><td>College of Computer and Information Sciences, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia</td><td>1</td></tr><tr><td>National University of Computer and Emerging Sciences, Islamabad, Islamabad, Pakistan</td><td>1</td></tr><tr><td>Research Team on Audio Visual Signal Processing (AVSP), Vrije Universiteit Brussel (VUB), Electronics and Informatics Department, VUB-ETRO, Pleinlaan 2, 1050 Brussel, Belgium</td><td>1</td></tr><tr><td>College of Computer Science and Technology of Huaqiao University Xiamen, Xiamen, China</td><td>1</td></tr><tr><td>Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Taiwan 640, R.O.C.</td><td>1</td></tr><tr><td>Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng 475004, China</td><td>1</td></tr><tr><td>Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Information Management, College of Management, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Computer Science and Information Engineering, College of Electrical Engineering and Computer Science, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>Department of Statistics, University of California at Berkeley, Berkeley, USA</td><td>1</td></tr><tr><td>International Computer Science Institute, University of California at Berkeley, Berkeley, USA</td><td>1</td></tr><tr><td>College of Information Science and Technology, Agricultural University of Hebei, Baoding, China</td><td>1</td></tr><tr><td>Department of Electronics Engineering, Mokpo National University, Republic of Korea</td><td>1</td></tr><tr><td>FX Palo Alto Laboratory</td><td>1</td></tr><tr><td>Department of Applied Optics and Photonics, University of Calcutta, Kolkata, India</td><td>1</td></tr><tr><td>Department of Electrical Engineering, Future Institute of Engineering and Management, Kolkata, India</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur, India</td><td>1</td></tr><tr><td>Telecom Division, Centre de Développement des Technologies Avancées, Algiers, Algeria</td><td>1</td></tr><tr><td>Departments of Medical Imaging and Medical Biophysics, University of Western Ontario, London, ON, Canada</td><td>1</td></tr><tr><td>Department of Medical Biophysics, University of Western Ontario, London, ON, Canada</td><td>1</td></tr><tr><td>School of Computer Science, Shaanxi Normal University, Xi’an, China</td><td>1</td></tr><tr><td>Engineering Laboratory of Teaching Information Technology of Shaanxi Province, Xi’an, China</td><td>1</td></tr><tr><td>Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi’an, China</td><td>1</td></tr><tr><td>College of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, P.R. China</td><td>1</td></tr><tr><td>Nanyang Technological University School of Computer Engineering</td><td>1</td></tr><tr><td>Department of Electronics and Electrical Engineering, Indian Institute of Technology (IIT) Guwahati, Guwahati, India</td><td>1</td></tr><tr><td>Technology Section, Israel National Police, Jerusalem, Israel</td><td>1</td></tr><tr><td>Department of Electro-Optics Engineering, Ben-Gurion University, Beer Sheva, Israel</td><td>1</td></tr><tr><td>Department of Mathematics, JiaYing University, Meizhou, China</td><td>1</td></tr><tr><td>Hebei University of Technology, School of Science, Tianjin, P. R. China</td><td>1</td></tr><tr><td>YiLi Normal College, Yining, China</td><td>1</td></tr><tr><td>Faculty of Electronic Information and Electrical Engineering, Dalian University, Dalian, China</td><td>1</td></tr><tr><td>Centre for Innovation in IT Services and Applications (iNEXT), University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td>Video Surveillance Laboratory, Guizhou University for Nationalities, Guiyang, China</td><td>1</td></tr><tr><td>College of Arts and Sciences, Shanxi Agricultural University, Shanxi, China</td><td>1</td></tr><tr><td>IRDA Group, ADMIR Laboratory, Rabat IT Center, ENSIAS, CNRST (URAC29), Mohammed V University of Rabat, Morocco</td><td>1</td></tr><tr><td>LRIT, CNRST (URAC29), Mohammed V University of Rabat, Morocco</td><td>1</td></tr><tr><td>Queen’s University, Kingston, Canada</td><td>1</td></tr><tr><td>University of Science Technology, Wuhan, China</td><td>1</td></tr><tr><td>Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia</td><td>1</td></tr><tr><td>University at Qatar, Doha, Qatar</td><td>1</td></tr><tr><td>University of Istanbul, Istanbul, Turkey</td><td>1</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Tuen Mun, Hong Kong</td><td>1</td></tr><tr><td>PolyU Shenzhen Research Institute, Shenzhen, China</td><td>1</td></tr><tr><td>German National Library of Science and Technology & Leibniz Universität Hannover, Hannover, Germany</td><td>1</td></tr><tr><td>University of Applied Sciences Jena, Jena, Germany</td><td>1</td></tr><tr><td>Department of Creative IT Engineering, POSTECH, Pohang, South Korea, 37673</td><td>1</td></tr><tr><td>Department of Computer Science, University of Western Ontario, London, Canada</td><td>1</td></tr><tr><td>Vision Laboratory, LARSyS, University of the Algarve, Faro, Portugal</td><td>1</td></tr><tr><td>Department of Information Management, Yuan Ze University, Taoyuan, China</td><td>1</td></tr><tr><td>DICGIM, Universitá degli Studi di Palermo, V.le delle Scienze, Ed. 6, 90128 Palermo, Italy</td><td>1</td></tr><tr><td>Department of Computer Engineering, Karadeniz Technical University, Trabzon, Turkey</td><td>1</td></tr><tr><td>Department of Computer Technologies, Trabzon Vocational School, Karadeniz Technical University, Trabzon, Turkey</td><td>1</td></tr><tr><td>Stanford University and Coursera</td><td>1</td></tr><tr><td>Dept. of Comput. Sci. & Info. Eng., National Yunlin Univ. of Science & Technology, Taiwan</td><td>1</td></tr><tr><td>Faculty of Mathematics and Statistics, Hubei Key Laboratory of Applied Mathematics, Hubei University, Wuhan, China</td><td>1</td></tr><tr><td>Biometric and Imaging Processing Laboratory (BIPLab)</td><td>1</td></tr><tr><td>Research and Academic Computer Network (NASK)</td><td>1</td></tr><tr><td>Philips Applied Technologies, Eindhoven, Netherlands</td><td>1</td></tr><tr><td>Philips Research Eindhoven, Eindhoven, Netherlands</td><td>1</td></tr><tr><td>Key Lab Complex System & Intelligence Science, Institute of Automation, Chinese Academy of Science, Beijing, China</td><td>1</td></tr><tr><td>College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China</td><td>1</td></tr><tr><td>National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis, Nizhny Novgorod, Russia</td><td>1</td></tr><tr><td>Emory University School of Medicine, Atlanta, USA</td><td>1</td></tr><tr><td>Department of Radiology and Imaging Sciences, Winship Cancer Institute, Emory University School of Medicine, Atlanta, USA</td><td>1</td></tr><tr><td>Dept. of EMPH, Icahn School of Medicine at Mount Sinai, New York, NY 10029</td><td>1</td></tr><tr><td>Electrical-Electronics Engineering Department, Izmir University of Economics, Balcova, Turkey</td><td>1</td></tr><tr><td>Department of Computer Science, Solapur University, Solapur, India</td><td>1</td></tr><tr><td>Computer Vision Research Group, School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia</td><td>1</td></tr><tr><td>Department of Information Technology, Netaji Subhas Engineering College, Kolkata, India</td><td>1</td></tr><tr><td>Computer Engineering College, Jimei University, Xiamen, China</td><td>1</td></tr><tr><td>Fujian Key Laboratory of the Brain-like Intelligent Systems, Xiamen, China</td><td>1</td></tr><tr><td>School of Information, Hunan University of Humanities, Science and Technology, Loudi, China</td><td>1</td></tr><tr><td>Al Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia</td><td>1</td></tr><tr><td>School of Information and Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Korea</td><td>1</td></tr><tr><td>Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea</td><td>1</td></tr><tr><td>Dept. of Computer Science and Information Engineering, Providence University, Taichung, Taiwan</td><td>1</td></tr><tr><td>360 AI Institute, Beijing, China</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Research Lab, Vrije Universitiet Brussel (VUB), Department of Electronics & Informatics (ETRO) Pleinlaan 2, 1050 Brussel, Belgium</td><td>1</td></tr><tr><td>IRISA, University of Rennes 1</td><td>1</td></tr><tr><td>Research Institution of Intelligent Control and Testing, Graduate School of Tsinghua University at Shenzhen, 518055, China</td><td>1</td></tr><tr><td>Commonwealth Scientific and Industrial Research Organization (CSIRO)</td><td>1</td></tr><tr><td>Indiana University-Bloomington, USA</td><td>1</td></tr><tr><td>Key Laboratory of Medical Image Computing (Northeastern University), Ministry of Education, Shenyang, China</td><td>1</td></tr><tr><td>Clínica Otocenter, Teresina, Piauí, Brasil</td><td>1</td></tr><tr><td>Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing, China</td><td>1</td></tr><tr><td>Nanjing University of Posts and Telecommunications, Nanjing, China</td><td>1</td></tr><tr><td>Grupo de Aplicacion de Telecomunicaciones Visuales, Universidad Politecnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain</td><td>1</td></tr><tr><td>Department of Management Information Systems, Universität Regensburg, Universitätsstr. 31, 93053 Regensburg, Germany</td><td>1</td></tr><tr><td>Department of Computer Science, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India</td><td>1</td></tr><tr><td>Amrita E-Learning Research Laboratory and the Department of Computer Science, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India</td><td>1</td></tr><tr><td>Department of ECE, PEC University of Technology, Chandigarh, India</td><td>1</td></tr><tr><td>Biomedical Instrumentation (V-02), CSIR-Central Scientific Instruments Organisation (CSIO)|, Chandigarh, India</td><td>1</td></tr><tr><td>CEERI, Pilani, India</td><td>1</td></tr><tr><td>MNIT, Jaipur, India</td><td>1</td></tr><tr><td>Department of Arts and Humanities, College of Business, Arts and Social Sciences, Brunel University London, Uxbridge, UK</td><td>1</td></tr><tr><td>Department of Design, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, India</td><td>1</td></tr><tr><td>NTT Service Evolution Laboratories, Kanagawa, Japan</td><td>1</td></tr><tr><td>Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., North Carolina Univ., Wilmington, NC, USA</td><td>1</td></tr><tr><td>University of Washington &Microsoft, Seattle, WA, USA</td><td>1</td></tr><tr><td>Departamento de Informtica e Matemtica Aplicada/University of Rio Grande do Norte, Natal, Brazil</td><td>1</td></tr><tr><td>Computer Engineering Department, Girne American University, Kyrenia, Cyprus 90</td><td>1</td></tr><tr><td>Cornell University & Facebook Inc., New York, NY, USA</td><td>1</td></tr><tr><td>School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, China</td><td>1</td></tr><tr><td>Fujian Provincial Key Laboratory of Information Processing and Intelligent Control, Fuzhou, China</td><td>1</td></tr><tr><td>School of Technology, Nanjing Audit University, Nanjing, China</td><td>1</td></tr><tr><td>Adobe Research Department, Adobe Systems Inc, San Jose, CA</td><td>1</td></tr><tr><td>Integrated Circuits and Electronics Laboratory, Department of Engineering, Aarhus University, Denmark</td><td>1</td></tr><tr><td>Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology (ICT), CAS, Beijing, China</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., California Inst. of Technol., Pasadena, CA, USA</td><td>1</td></tr><tr><td>Utechzone Co. Ltd., New Taipei City, Taiwan 235</td><td>1</td></tr><tr><td>Department of Cognitive Science, University of California, San Diego, CA, USA</td><td>1</td></tr><tr><td>Department of Electronic Engineering Shanghai Jiao Tong University</td><td>1</td></tr><tr><td>Innovations Kontakt Stelle (IKS) Hamburg, Hamburg University of Applied Sciences</td><td>1</td></tr><tr><td>School of Engineering and Computing, University of the West of Scotland</td><td>1</td></tr><tr><td>Computer Science Department, Central Washington University (CWU)</td><td>1</td></tr><tr><td>ICT Center, CSIRO</td><td>1</td></tr><tr><td>Technische Universität München, München, Germany</td><td>1</td></tr><tr><td>Electrical Engineering and Computer Science, School of Engineering, University of California at Merced, Merced, USA</td><td>1</td></tr><tr><td>Data61, Commonwealth Scientific and Industrial Research Organization (CSIRO), Canberra, Australia</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Faculty of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Bangladesh</td><td>1</td></tr><tr><td>Pennsylvania State University, University Park, PA</td><td>1</td></tr><tr><td>University of Sao Paulo</td><td>1</td></tr><tr><td>School of Software, Henan University, Kaifeng, China</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, China</td><td>1</td></tr><tr><td>Department of Electrical Engineering, Computer Vision Laboratory, Linköping University, Linköping, Sweden</td><td>1</td></tr><tr><td>Computer Vision Research Laboratory, Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran</td><td>1</td></tr><tr><td>Treelogic, Technological Scientific Park of Asturias, Llanera, Spain</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Oviedo, Gijón, Spain</td><td>1</td></tr><tr><td>Fundación CTIC (Technological Center), Technological Scientific Park of Gijón, Gijón, Spain</td><td>1</td></tr><tr><td>Department of Computer Science, Madrid Open University, Madrid, Spain</td><td>1</td></tr><tr><td>Department of Research and Diagnostic Methods, Faculty of Education, Pontificia University of Salamanca, Salamanca, Spain</td><td>1</td></tr><tr><td>Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan</td><td>1</td></tr><tr><td>Dept. of Information Engineering, Faculty of Engineering, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan</td><td>1</td></tr><tr><td>Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-Nocho, Nishi-ku Niigata, 950-2181, Japan, +81 25 262 7499</td><td>1</td></tr><tr><td>NTNU, Norway</td><td>1</td></tr><tr><td>Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland</td><td>1</td></tr><tr><td>Polish-Japanese Institute of Information Technology, Warszawa, Poland</td><td>1</td></tr><tr><td>Faculty of Applied Informatics and Mathematics, Department of Informatics, Warsaw University of Life Sciences (SGGW), Warsaw, Poland</td><td>1</td></tr><tr><td>Polish-Japanese Institute of Information Technology, Warsaw, Poland</td><td>1</td></tr><tr><td>FernUniversität , Hagen, Germany</td><td>1</td></tr><tr><td>Universidad Tecnica Federico Santa Maria , Valparaiso, Chile</td><td>1</td></tr><tr><td>Staffordshire University , Staffordshire, United Kingdom</td><td>1</td></tr><tr><td>Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, Kuching, Malaysia</td><td>1</td></tr><tr><td>University of Massachusetts at Amherst, Amherst, MA, USA</td><td>1</td></tr><tr><td>Department of Engineering and MaintenanceChina Mobile Group, Jiangsu Company, Ltd., Changzhou, China</td><td>1</td></tr><tr><td>Indian Statistical Institute, Kolkata 700108</td><td>1</td></tr><tr><td>Departament d’Informàtica, Universitat de Valencia, Valencia, Spain</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, Gannan Normal University, Ganzhou, People’s Republic of China</td><td>1</td></tr><tr><td>National Laboratory of Pattern Recognition, Beijing, China</td><td>1</td></tr><tr><td>Quang Binh University, Dong Hoi City, Vietnam</td><td>1</td></tr><tr><td>School of Mathematics and Information Technology, Nanjing Xiao Zhuang University, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td>School of Computing, Electronics and Mathematics, Faculty of Engineering, Environment and Computing, Coventry University, Coventry, UK</td><td>1</td></tr><tr><td>Institute of Computer Science, Christian-Albrechts-Universität Kiel, Kiel, Germany</td><td>1</td></tr><tr><td>KT Future Technology Laboratory, Seoul, South Korea</td><td>1</td></tr><tr><td>Microsoft Research Asia, Beijing, P.R. China</td><td>1</td></tr><tr><td>Shanghai Maritime University, Shanghai, China</td><td>1</td></tr><tr><td>Machine Intelligence Research Institute, Rockville, USA</td><td>1</td></tr><tr><td>Orange—France Telecom Division R&D—TECH/IRIS, Cesson Sévigné Cedex, France</td><td>1</td></tr><tr><td>IIT-Madras, Chennai, India</td><td>1</td></tr><tr><td>Department of Computer Science, Innopolis University, Kazan, Russia</td><td>1</td></tr><tr><td>Department of Computer Science, University of Science & Technology, Bannu, Pakistan</td><td>1</td></tr><tr><td>Naver Labs Europe, Meylan, France</td><td>1</td></tr><tr><td>School of Computer and Systems Sciences, JawaharLal Nehru University, New Delhi 110067, India</td><td>1</td></tr><tr><td>Univ. La Rochelle, La Rochelle, France</td><td>1</td></tr><tr><td>Department of Computer Science, Chu Hai College of Higher Education, Tsuen Wan, Hong Kong</td><td>1</td></tr><tr><td>University of Salerno, Salerno, Italy</td><td>1</td></tr><tr><td>Google, Mountain View, USA</td><td>1</td></tr><tr><td>Computer Sciences Department, University of Wisconsin, Madison, USA</td><td>1</td></tr><tr><td>Google, Seattle, USA</td><td>1</td></tr><tr><td>Singapore Polytechnic, 500 Dover Road, Singapore 139651</td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China</td><td>1</td></tr><tr><td>Centre for Machine Vision, Bristol Robotics Laboratory, University of the West of England, T Block, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, UK</td><td>1</td></tr><tr><td>Saudi Electronic University, Riyadh, Kingdom of Saudi Arabia</td><td>1</td></tr><tr><td>Information Security Group, City University London, London, UK</td><td>1</td></tr><tr><td>School of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou, China</td><td>1</td></tr><tr><td>IIIT Chittoor, SriCity, Andhra Pradesh, India</td><td>1</td></tr><tr><td>Department of Information Engineering, Henan University of Science and Technology, Luoyang, China</td><td>1</td></tr><tr><td>Department of mechatronic technology of National Taiwan Normal University</td><td>1</td></tr><tr><td>Department of Electrical Engineering and Computer Science, Colorado School of Mines, Golden, CO, USA</td><td>1</td></tr><tr><td>The Image Processing and Analysis Laboratory (LAPI), University “Politehnica” of Bucharest, 313 Splaiul Independeţei, Bucharest, Romania</td><td>1</td></tr><tr><td>Division of Digital Media Engineering, Sang-Myung University, Suwon, Republic of Korea</td><td>1</td></tr><tr><td>Facebook AI Research (FAIR), Menlo Park, USA</td><td>1</td></tr><tr><td>Princeton University &Microsoft, Princeton, NJ, USA</td><td>1</td></tr><tr><td>Microsoft &University of Washington, Redmond, WA, USA</td><td>1</td></tr><tr><td>Intel Labs, Pittsburgh PA</td><td>1</td></tr><tr><td>Dept. of Inf. Network Technol., Hsiuping Inst. of Technol., Taichung, Taiwan</td><td>1</td></tr><tr><td>Alibaba Group, Zhejiang, People’s Republic of China</td><td>1</td></tr><tr><td>Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute Troy, Troy, USA</td><td>1</td></tr><tr><td>Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology, University of Science and Technology of China Hefei, Anhui, People’s Republic of China</td><td>1</td></tr><tr><td>School of ComputingNational University of Singapore</td><td>1</td></tr><tr><td>Dept. of EE, UESTC, 2006 Xiyuan Ave, Chengdu, Sichuan 611731, China</td><td>1</td></tr><tr><td>Dept. of Radiation Oncology, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</td><td>1</td></tr><tr><td>Dept. of Electrical & Computer Engineering, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</td><td>1</td></tr><tr><td>University of Nottingham (Malaysia Campus), Malaysia</td><td>1</td></tr><tr><td>South Valley University, Qena, Egypt</td><td>1</td></tr><tr><td>Film Department ELTE University, Budapest, Hungary</td><td>1</td></tr><tr><td>Gipsa-Lab, Saint Martin d’Heres, France</td><td>1</td></tr><tr><td>ICA Laboratory, Grenoble, France</td><td>1</td></tr><tr><td>School of Computing and Electrical Engineering, IIT Mandi, H.P, 175001, India</td><td>1</td></tr><tr><td>AICTE Emeritus Fellow, </td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, GCELT, Kolkata, India</td><td>1</td></tr><tr><td>Chinese University of Hong Kong, Hong Kong</td><td>1</td></tr><tr><td>Department of Computer System and Communication, Faculty of Information and Communication, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia</td><td>1</td></tr><tr><td>Division Télécom, Centre de Développement des Technologies Avancées - CDTA, Algiers, Algeria</td><td>1</td></tr><tr><td>School of Computer and Communication Science, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland</td><td>1</td></tr><tr><td>Baidu Research - Institute of Deep Learning, Sunnyvale, USA</td><td>1</td></tr><tr><td>Jiaxing University, Jiaxing, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. zhangxiaoxun@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. jiayunde@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing 100081, CHINA. xushuang@bit.edu.cn</td><td>1</td></tr><tr><td>Department of Electronics and Communication, University of Allahabadm Allahabad, India 211002</td><td>1</td></tr><tr><td>Department of Business Computer, Faculty of Management Science, Nakhon Ratchasima Rajabhat University, Nakhon Ratchasima, Thailand</td><td>1</td></tr><tr><td>Yahoo! Research</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, University of Cagliari, Italy</td><td>1</td></tr><tr><td>Universidad de León, León, Spain</td><td>1</td></tr><tr><td>Elektronik ve Haberleşme Mühendisliği Bölümü</td><td>1</td></tr><tr><td>Robert Bosch Engineering and Business Solutions Limited, Bangalore, India</td><td>1</td></tr><tr><td>Department of Instrumentation and Control Engineering, PSG College of Technology, Coimbatore, India</td><td>1</td></tr><tr><td>China Airborne Missile Academy, Luoyang, China</td><td>1</td></tr><tr><td>Electronic Information Engineering College, Henan University of Science and Technology, Luoyang, China</td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Inner Mongolia University of Science and Technology, Baotou, People’s Republic of China</td><td>1</td></tr><tr><td>Istituto Italiano di Tecnologia & Università di Verona, Genova, Italy</td><td>1</td></tr><tr><td>Istituto Italiano di Tecnologia (IIT), Genova, Italy</td><td>1</td></tr><tr><td>Office of Safety Research and Development, Federal Highway Administration, U.S. Department of Transportation, Virginia, USA</td><td>1</td></tr><tr><td>Xinjiang Vocational and Technical College of Communications, Wulumuqi, People’s Republic of China</td><td>1</td></tr><tr><td>College of Mathematics and Informatics, South China Agricultural University, China</td><td>1</td></tr><tr><td>Curtin University Department of Mechanical Engineering, Perth, Western Australia 6012</td><td>1</td></tr><tr><td>Department of Information Engineering, HeNan Radio and Television University, Zhengzhou, People’s Republic of China</td><td>1</td></tr><tr><td>Computer Science Department, School of Information Science and Engineering, Xiamen, University, Xiamen, People’s Republic of China</td><td>1</td></tr><tr><td>PLA University of Science and Technology, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, USA</td><td>1</td></tr><tr><td>School of Electronics and Computer Eng., Chonnam National University, Gwangju, Korea</td><td>1</td></tr><tr><td>FAST, Supélec, Avenue de la Boulaie, Cesson-Sévigné, France</td><td>1</td></tr><tr><td>ISIR laboratory, Pierre and Marie Curie university, Paris Cedex 05, France</td><td>1</td></tr><tr><td>Centre for Visual Computing, Faculty of Engineering and Informatics, University of Bradford, Bradford, UK</td><td>1</td></tr><tr><td>Amsterdam University College, Amsterdam, The Netherlands</td><td>1</td></tr><tr><td>Key Laboratory of Intelligent Information Processing, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td>Institute of Life Sciences, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>School of Information Science and Engineering, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>FEECS, Department of Computer Science, Technical University of Ostrava, Ostrava-Poruba, Czech Republic</td><td>1</td></tr><tr><td>ECE, Department MSIT, C-4 Janakpuri, New Delhi, India</td><td>1</td></tr><tr><td>Dept. of Comput. Sci., New Jersey Inst. of Technol., Newark, NJ, USA</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan. e-mail: chihming.fu@gmail.com</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan; Informatics Department, Fo-Guang University, I-Lan, Taiwan. e-mail: clhuang@ee.nthu.edu.tw</td><td>1</td></tr><tr><td>Electrical Engineering Department, National Tsing-Hua University, Hsin-Chu, Taiwan</td><td>1</td></tr><tr><td>Department of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China</td><td>1</td></tr><tr><td>University of California at Los Angeles, Los Angeles, CA, USA</td><td>1</td></tr><tr><td>Department of Physics, Tripura University (A Central University), Suryamaninagar, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Tripura University (A Central University), Suryamaninagar, India</td><td>1</td></tr><tr><td>Pontifical Catholic University of Minas Gerais - Department of Computer Science, R. Dom Jose Gaspar, 500, Belo Horizonte MG, 30535901, Brazil</td><td>1</td></tr><tr><td>Department of Statistics and Operational Research, Faculty of Mathematics, Complutense University of Madrid, Madrid, Spain</td><td>1</td></tr><tr><td>Dept. of Mathematics and Computer Science, University of Udine, Italy</td><td>1</td></tr><tr><td>LIMSI-CNRS, Orsay Cedex, France</td><td>1</td></tr><tr><td>Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Pisa, Italy</td><td>1</td></tr><tr><td>Faculty of Information Sciences and Engineering, Management and Science University, Selangor, Malaysia</td><td>1</td></tr><tr><td>UTM-Big Data Center, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</td><td>1</td></tr><tr><td>Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia</td><td>1</td></tr><tr><td>LAMIA, EA 4540, University of French West Indies and Guyana, Guadeloupe, France</td><td>1</td></tr><tr><td>ISIR, UPMC Univ Paris 06, CNRS, Paris, France</td><td>1</td></tr><tr><td>Merchant Marine College, Shanghai Maritime University, Shanghai 201306, PR China</td><td>1</td></tr><tr><td>Department of Informatics, King’s College London, London, UK</td><td>1</td></tr><tr><td>Department of Electrical Engineering, KAIST, Korea</td><td>1</td></tr><tr><td>Department of New Media, Korean German Institute of Technology, Korea</td><td>1</td></tr><tr><td>Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy</td><td>1</td></tr><tr><td>Pontifical Catholic Univ of Rio de Janei, Department of Informatics, Rio de Janeiro, Brazil</td><td>1</td></tr><tr><td>Department of Informatics, Pontifical Catholic Univ of Rio de Janei, Rio de Janeiro, Brazil</td><td>1</td></tr><tr><td>School of Computing Sciences and Informatics, University of Cincinnati, Cincinnati, USA</td><td>1</td></tr><tr><td>Universiti Kuala Lumpur, Kedah</td><td>1</td></tr><tr><td>Sudan University of Science and Technology, College of Computer Science and Information Technology, Khartoum - Sudan</td><td>1</td></tr><tr><td>LMU Munich, Germany and Munich University of Applied Sciences, Germany</td><td>1</td></tr><tr><td>Department of Electric and Electronic Engineering, Avrasya University, Trabzon, Turkey</td><td>1</td></tr><tr><td>ACM Professional Specialist in Artificial Intelligence</td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China</td><td>1</td></tr><tr><td>University of Washington and Google Inc.</td><td>1</td></tr><tr><td>Google Inc.</td><td>1</td></tr><tr><td>CCCE, Nankai University Jinnan Campus, Tianjin, China</td><td>1</td></tr><tr><td>Department of Computer Science, VHNSN College, Virudhunagar, India</td><td>1</td></tr><tr><td>Department of Computer Science, ANJA College, Sivakasi, India</td><td>1</td></tr><tr><td>Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology Tsinghua University, Beijing, China</td><td>1</td></tr><tr><td>Foundation for Research & Technology – Hellas, Heraklion, Crete, Greece</td><td>1</td></tr><tr><td>Vrije Universiteit Amsterdam, Amsterdam, The Netherlands</td><td>1</td></tr><tr><td>Ruhr-Universität Bochum, Bochum, Germany</td><td>1</td></tr><tr><td>Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro No.1, Tonantzintla, Puebla, México. CP 72840</td><td>1</td></tr><tr><td>Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, People’s Republic of China</td><td>1</td></tr><tr><td>Department of Mechanical Engineering, Universiti Tenaga Nasional Km 7, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia</td><td>1</td></tr><tr><td>Dept. of Electron. Eng., Hannam Univ., Daejeon, South Korea</td><td>1</td></tr><tr><td>Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies, Zhejiang, China</td><td>1</td></tr><tr><td>Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada</td><td>1</td></tr><tr><td>Laboratoire MIA, University of La Rochelle, La Rochelle, France</td><td>1</td></tr><tr><td>Fraunhofer Institute for Telecommunications, Berlin, Germany</td><td>1</td></tr><tr><td>Fraunhofer Institute for Digital Media Technology, Ilmenau, Germany</td><td>1</td></tr><tr><td>Siemens AG, Corporate Technology, Munich, Germany</td><td>1</td></tr><tr><td>ECIT, School of Electronics, Electrical Engineering & Computer Science, Queen's University Belfast, Belfast, UK</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Calcutta, Kolkata, India</td><td>1</td></tr><tr><td>School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran</td><td>1</td></tr><tr><td>Luoyang Electro-Optical Equipment Research Institute, Luoyang, People’s Republic of China</td><td>1</td></tr><tr><td>Technological Educational Institute of Sterea Ellada, Psahna, Halkida, Greece</td><td>1</td></tr><tr><td>National Centre for Scientific Research “Demokritos”, Agia Paraskevi, Athens, Greece</td><td>1</td></tr><tr><td>University of Maastricht, Maastricht, The Netherlands</td><td>1</td></tr><tr><td>Centre of Research and Technology Hellas, Thermi, Thessaloniki, Greece</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, P.P.G. Institute of Technology, Coimbatore, India</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, Institute of Road and Transport Technology, Erode, India</td><td>1</td></tr><tr><td>Department of Computer Science, Banasthali Vidyapith, Banasthali, India</td><td>1</td></tr><tr><td>Computer Science and Engineering Department, SP Memorial Institute of Technology, Kaushambi, India</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, China</td><td>1</td></tr><tr><td>Fujifilm Software, San Jose, USA</td><td>1</td></tr><tr><td>Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis, Singapore 138632</td><td>1</td></tr><tr><td>HTC Research, Beijing, China</td><td>1</td></tr><tr><td>QCIS, University of Technology, Sydney, Australia</td><td>1</td></tr><tr><td>Interuniversity Microelectronics Centre, Heverlee, Belgium</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Lab, Department ETRO, Vrije Universiteit Brussel (VUB), Brussels, Belgium</td><td>1</td></tr><tr><td>Shaanxi Key Laboratory on Speech and Image Information Processing, Xi’an, China</td><td>1</td></tr><tr><td>NPU-VUB Joint AVSP Lab, School of Computer Science, Northwestern Polytechnical University (NPU), Xi’an, China</td><td>1</td></tr><tr><td>Institute of Electronics and Computer Science, Riga, Latvia</td><td>1</td></tr><tr><td>Electrical and Computer Engineering Department, University of California, Santa Barbara, CA 93106 USA</td><td>1</td></tr><tr><td>Psychology Department, University of California, Santa Barbara, CA 93106 USA</td><td>1</td></tr><tr><td>Dept. of Comp. Sci. and Inf. Eng, National United University, Miaoli, Taiwan</td><td>1</td></tr><tr><td>School of Control Science and Engineering DUT, Dalian, China</td><td>1</td></tr><tr><td>Information Technology R&D Center, Mitsubishi Electric Corporation, Kamakura, Japan</td><td>1</td></tr><tr><td>School of Information Science and Engineering, Hunan city University, Yiyang, China</td><td>1</td></tr><tr><td>KU Leuven, ESAT - PSI, iMinds, Leuven, Belgium</td><td>1</td></tr><tr><td>Max-Planck-Institut für Informatik, Saarbrücken, Germany</td><td>1</td></tr><tr><td>Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran, Iran</td><td>1</td></tr><tr><td>University of IIllinois, Urbana-Champaign</td><td>1</td></tr><tr><td>Zhejiang University & Alibaba Group, Hangzhou, China</td><td>1</td></tr><tr><td>Laboratory LIM, Department of Computer Science, Faculty of Sciences and Technologies, University Hassan II, Casablanca-Morocco</td><td>1</td></tr><tr><td>Electrical Engineering Department, Yazd University, Yazd, Iran</td><td>1</td></tr><tr><td>School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin, China</td><td>1</td></tr><tr><td>Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, Tianjin, China</td><td>1</td></tr><tr><td>Adjunct, Effat University, Jeddah, Saudi Arabia</td><td>1</td></tr><tr><td>School of Computer Science, Wuyi University, Jiangmen, China</td><td>1</td></tr><tr><td>Snapchat Research, Venice, CA90291</td><td>1</td></tr><tr><td>Department of CSE, University at Buffalo (SUNY), NY 14260, USA</td><td>1</td></tr><tr><td>School of Information and Engineering, Jinhua Polytechnic, Jinhua, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, University of Texas, Arlington, USA</td><td>1</td></tr><tr><td>School of Medical Science, Jinhua Polytechnic, Jinhua, China</td><td>1</td></tr><tr><td>S. S. College of Business Studies, University of Delhi, Delhi, India</td><td>1</td></tr><tr><td>School of Computer & System Sciences, Jawaharlal Nehru University, New Delhi, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, India</td><td>1</td></tr><tr><td>Baidu Online Network Technology (Beijing) Co. Ltd, Beijing, China</td><td>1</td></tr><tr><td>Faculty of Engineering and Computing, Coventry University, UK</td><td>1</td></tr><tr><td>Dept. of Theoretical Electrical Engineering, Technical University of Sofia, Sofia, Bulgaria</td><td>1</td></tr><tr><td>Lawrence Berkeley National Laboratory, Berkeley, USA</td><td>1</td></tr><tr><td>No.1 Senior Middle School of Wendeng District, Weihai, China</td><td>1</td></tr><tr><td>Standards & Metrology Research Institute of CARS, Beijing, China</td><td>1</td></tr><tr><td>College of Information Science & Technology, Hebei Agricultural University, Baoding, China</td><td>1</td></tr><tr><td>Amazon, Berkshire, U.K.</td><td>1</td></tr><tr><td>Tianjin Universtiy, Tianjin, China</td><td>1</td></tr><tr><td>University of Lancaster, Lancaster, United Kingdom</td><td>1</td></tr><tr><td>University of Helsinki, Helsinki, Finland</td><td>1</td></tr><tr><td>Intelligent and Interactive Systems, Institute of Computer Science, University of Innsbruck, Innsbruck, Austria</td><td>1</td></tr><tr><td>Signal and Image Exploitation (INTELSIG), Montefiore Institute, University of Liège, Liège, Belgium</td><td>1</td></tr><tr><td>Megvii Inc., Beijing, China</td><td>1</td></tr><tr><td>Department of Informatics, Modeling, Electronics, and Systems, University of Calabria, Rende, Italy</td><td>1</td></tr><tr><td>School of Materials Science and Engineering, Central South University, Changsha, China</td><td>1</td></tr><tr><td>Institute of Energy, Jiangxi Academy of Sciences, Nanchang, China</td><td>1</td></tr><tr><td>**</td><td>1</td></tr><tr><td>Electrical and Electronic Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran</td><td>1</td></tr><tr><td>College of Mathematics and Information Engineering, Jiaxing University, Jiaxing, China</td><td>1</td></tr><tr><td>Dept. of Convergence, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, Korea</td><td>1</td></tr><tr><td>School of Mechanical and Electrical Engineering, Shandong Management University, Jinan, China</td><td>1</td></tr><tr><td>School of Information Science and Technology, Shandong Normal University, Jinan, China</td><td>1</td></tr><tr><td>National Institute of Advanced Industrial Science Technology, Japan</td><td>1</td></tr><tr><td>Tilburg center for Cognition and Communication, Tilburg University, Tilburg, The Netherlands</td><td>1</td></tr><tr><td>Automatics Research Group, Universidad Tecnológica de Pereira, Pereira, Colombia</td><td>1</td></tr><tr><td>School of Science, Southwest Petroleum University, Chengdu, China</td><td>1</td></tr><tr><td>Infosys Limited, Bhubaneswar, India</td><td>1</td></tr><tr><td>School of Computer Science and Engineering, Tianjin University of Technology, China</td><td>1</td></tr><tr><td>Department of Computer Science, University of Brasília, DF, Brazil 70910-900</td><td>1</td></tr><tr><td>Department of Mechanical Engineering, University of Brasília, DF, Brazil 70910-900</td><td>1</td></tr><tr><td>LIAMA, French National Institute for Research in Computer Science and Control, Paris, France</td><td>1</td></tr><tr><td>Leiden University, Leiden, The Netherlands</td><td>1</td></tr><tr><td>TNO, The Hague, The Netherlands</td><td>1</td></tr><tr><td>City University, Kowloon Tong, Hong Kong</td><td>1</td></tr><tr><td>Radboud University, EC Nijmegen, The Netherlands</td><td>1</td></tr><tr><td>TNO, Oude Waalsdorperweg, AK The Hague, The Netherlands</td><td>1</td></tr><tr><td>Liaocheng University, Liaocheng, China</td><td>1</td></tr><tr><td>Northwestern Polytechnic University, Xi’an, China</td><td>1</td></tr><tr><td>University of Science and Technology Beijing, Beijing, China</td><td>1</td></tr><tr><td>Faculty of Information Engineering, China University of Geosciences, Wuhan, China</td><td>1</td></tr><tr><td>China University of Geosciences Wuhan, China</td><td>1</td></tr><tr><td>University of Udine, Udine, Italy</td><td>1</td></tr><tr><td>INRS-EMT, Montreal, Canada</td><td>1</td></tr><tr><td>School of Computer Science and Technology, Harbin Institute of Technology at Weihai, Weihai, China</td><td>1</td></tr><tr><td>School of Computer Science Carnegie Mellon University Pittsburgh, PA, 15213, USA</td><td>1</td></tr><tr><td>College of Information and Technology, Incheon National University, Incheon, Korea</td><td>1</td></tr><tr><td>Tianjin University & University of South Carolina, Tianjin, China</td><td>1</td></tr><tr><td>School of Electronics Engineering, Kyungpook National University, Taegu, South Korea</td><td>1</td></tr><tr><td>Department of Electrical & Electronics Engineering, Kalasalingam University, Krishnankoil, India</td><td>1</td></tr><tr><td>School of Computer Engineering, Hanshin University, Osan, Republic of Korea</td><td>1</td></tr><tr><td>School of Computer Science, China University of Geosciences, Wuhan, China</td><td>1</td></tr><tr><td>College of Computer Science and Technology of Huaqiao University, Xiamen, China</td><td>1</td></tr><tr><td>CEA (iRSTV/BGE), INSERM (U1038), CNRS (FR3425), Université Grenoble-Alpes, Grenoble, France</td><td>1</td></tr><tr><td>NLPR, Institute of Automation, Chinese Academy of Science, Beijing, People’s Republic of China</td><td>1</td></tr><tr><td>Costel, Université de Rennes 2, Rennes, France</td><td>1</td></tr><tr><td>IRISA, Université de Bretagne Sud, Vannes, France</td><td>1</td></tr><tr><td>Research & Development, British Broadcasting Corporation (BBC), London, UK</td><td>1</td></tr><tr><td>Faculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an, China</td><td>1</td></tr><tr><td>Wide Eyes Technologies</td><td>1</td></tr><tr><td>School of Information Engineering, Jiangxi Manufacturing Technology College, Nanchang, China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Nanjing Forestry University and Shandong University, Jinan, China</td><td>1</td></tr><tr><td>Department of Language Studies, Nanjing Forestry University, Nanjing, China</td><td>1</td></tr><tr><td>Department of Computer Science and Technology, Nanjing Forestry University, Nanjing, China</td><td>1</td></tr><tr><td>Dept. of Autom. Test & Control, Harbin Inst. of Technol., China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, Frederick University, Nicosia, Cyprus</td><td>1</td></tr><tr><td>The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense M, Denmark</td><td>1</td></tr><tr><td>Department of Computer Science, Digital Image Processing Laboratory, Islamia College Peshawar, Peshawar, Pakistan</td><td>1</td></tr><tr><td>Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan</td><td>1</td></tr><tr><td>Department of Computer Science, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan</td><td>1</td></tr><tr><td>Technische Universität München / Imperial College London, Munich / London, England UK</td><td>1</td></tr><tr><td>Department of Mathematics and Informatics, Ecole Centrale de Lyon, Lyon, 69134, France</td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, Jamia Hamdard University, New Delhi, India</td><td>1</td></tr><tr><td>Department of Computer Science & Engineering, University of Minnesota-Twin Cities, Minneapolis, USA</td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary</td><td>1</td></tr><tr><td>School of Information Science and Technology, Northwest University, Xi’an, China</td><td>1</td></tr><tr><td>Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands</td><td>1</td></tr><tr><td>School of Software, Beijing Institute of Technology, Beijing, China</td><td>1</td></tr><tr><td>University of St. Andrews, UK</td><td>1</td></tr><tr><td>University of Tunis El Manar, Tunis, Tunisia</td><td>1</td></tr><tr><td>College of Information and Control Engineering, China University of Petroleum, Qingdao, China</td><td>1</td></tr><tr><td>Intel Labs Europe, Pipers Way, Swindon</td><td>1</td></tr><tr><td>Department of Computer Systems, Universidad Politécnica de Madrid, Madrid, Spain</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, Ursinus College, Collegeville, PA</td><td>1</td></tr><tr><td>Systems Engineering Institute, Xi’an Jiaotong University, Xi’an 710049, China</td><td>1</td></tr><tr><td>Institute of Semiconductors, Chinese Academy of Sciences&University of Chinese Academy of Sciences, Beijing, China</td><td>1</td></tr><tr><td>School of Computer Science and Technology, Nanjing University of Science and Technology of China, Nanjing, People’s Republic of China</td><td>1</td></tr><tr><td>NTT Network Innovation Laboratories, Nippon Telegraph and Telephone Corp.</td><td>1</td></tr><tr><td>Faculty of Computing and Information Technology, Setapak, Malaysia</td><td>1</td></tr><tr><td>Computer Science Department, University of California, Los Angeles, CA, USA</td><td>1</td></tr><tr><td>INRIA, Sophia Antipolis, France</td><td>1</td></tr><tr><td>School of Mathematics and Computer Sciences, Gannan Normal University, Ganzhou, China</td><td>1</td></tr><tr><td>University of Maribor, Faculty of Electrical Engineering and Computer Science, Koroška cesta 46, SI-2000, Slovenia</td><td>1</td></tr><tr><td>University of Tours, France</td><td>1</td></tr><tr><td>Department of Information Management, Hwa Hsia University of Technology, New Taipei City, Taiwan</td><td>1</td></tr><tr><td>Department of Electronic Engineering, National Ilan University, Yilan City, Taiwan</td><td>1</td></tr><tr><td>Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China</td><td>1</td></tr><tr><td>College of Information and Electrical Engineering, Ludong University, Yantai, China</td><td>1</td></tr><tr><td>Wakayama University</td><td>1</td></tr><tr><td>Computer Science College, Xi’an Polytechnic University, Xi’an, China</td><td>1</td></tr><tr><td>Computer Science Dept., SUNY Stony Brook, USA</td><td>1</td></tr><tr><td>School of Mathematical and Physical Sciences at the University of Newcastle, Callaghan, NSW 2308, Australia</td><td>1</td></tr><tr><td>Department of Electronics and Communication Engineering, JNTU College of Engineering, Hyderabad, India</td><td>1</td></tr><tr><td>Department of Physics, JNTU College of Engineering, Kakinada, India</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, JNTU College of Engineering, Kakinada, India</td><td>1</td></tr><tr><td>Department of Telecommunications and Information Processing, Image Processing and Interpretation, UGent/iMinds, Ghent, Belgium</td><td>1</td></tr><tr><td>School of Software, Shenyang University of Technology, Shenyang, China</td><td>1</td></tr><tr><td>School of Engineering of UABC, University of Baja California, Tijuana, Mexico</td><td>1</td></tr><tr><td>University of Hawaii at Hilo, HI, USA</td><td>1</td></tr><tr><td>Yuncheng University, Shanxi Province, China</td><td>1</td></tr><tr><td>Department of Computer Engineering, Bahçeşehir University, Istanbul, Turkey</td><td>1</td></tr><tr><td>Sichuan University West China Hospital of Stomatology, Chengdu, China</td><td>1</td></tr><tr><td>School of Software Engineering, Chengdu University of Information Technology, Chengdu, China</td><td>1</td></tr><tr><td>Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, People’s Republic of China</td><td>1</td></tr><tr><td>School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, China</td><td>1</td></tr><tr><td>Department of Computer Engineering, Bogaziçi University, Bebek, Turkey</td><td>1</td></tr><tr><td>Department of Electrical and Electronic Engineering, Auckland University of Technology , Auckland, New Zealand</td><td>1</td></tr><tr><td>Department of Computer Engineering, Qazvin Islamic Azad University , Qazvin, Iran</td><td>1</td></tr><tr><td>Shanghai University of Finance and Economics, Shanghai, China</td><td>1</td></tr><tr><td>Graduate School of Engineering, Nagasaki University, Nagasaki, Japan</td><td>1</td></tr><tr><td>Institute of Management and Information Technologies, Chiba University, Chiba, Japan</td><td>1</td></tr><tr><td>Graduate School of Advanced Integration Science, Chiba University, Chiba, Japan</td><td>1</td></tr><tr><td>Vision Semantics Ltd</td><td>1</td></tr><tr><td>Department of Film and Digital Media, Seokyeong University, Seoul, Republic of Korea</td><td>1</td></tr><tr><td>Department of MediaSoftware, Sungkyul University, Anyang-si, Republic of Korea</td><td>1</td></tr><tr><td>Pusan National University, Busan, Korea</td><td>1</td></tr><tr><td>School of Engineering, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland</td><td>1</td></tr><tr><td>Department of Computer Science, Auckland University of Technology, Auckland, New Zealand</td><td>1</td></tr><tr><td>L3S Research Center, Leibniz Universität Hannover, Hannover, Germany</td><td>1</td></tr><tr><td>German National Library of Science and Technology (TIB), Hannover, Germany</td><td>1</td></tr><tr><td>taglicht media Film- & Fernsehproduktion GmbH, Köln, Germany</td><td>1</td></tr><tr><td>Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany</td><td>1</td></tr><tr><td>School of Mathematics and Computational Science, Anqing Normal University, Anqing, People’s Republic of China</td><td>1</td></tr><tr><td>Concordia Institute for Information Systems Engineering Concordia University, Montreal, Canada</td><td>1</td></tr><tr><td>IKERBASQUE, Basque Foundation for Science, Bilbao, Spain</td><td>1</td></tr><tr><td>University of the Basque Country UPV/EHU, San Sebastian, Spain</td><td>1</td></tr><tr><td>Computer Vision Center, Edifici “O”, Campus UAB, Bellaterra, Spain</td><td>1</td></tr><tr><td>Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki City, Japan</td><td>1</td></tr><tr><td>Xiamen University of Technology, Fujian, China</td><td>1</td></tr><tr><td>School of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, China</td><td>1</td></tr><tr><td>Dept. of Artificial Intelligence, Faculty of Computer Engineering, University of Isfahan, Iran</td><td>1</td></tr><tr><td>Department of Information Processing Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology Yokohama 226-8503, Japan</td><td>1</td></tr><tr><td>Department of Computer Science, University of Texas, San Antonio, TX, USA</td><td>1</td></tr><tr><td>University of Sheffield, Sheffield, United Kingdom</td><td>1</td></tr><tr><td>Insititute of Automation, Chinese Academy of Sciences (CAS), Beijing, China</td><td>1</td></tr><tr><td>School of Computing and Information Systems, University of Melbourne, Melbourne, Australia</td><td>1</td></tr><tr><td>Sapienza Università di Roma, Roma, Italy</td><td>1</td></tr><tr><td>Center for Unified Biometrics and Sensors, University at Buffalo, NY, USA. tulyakov@cedar.buffalo.edu</td><td>1</td></tr><tr><td>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China</td><td>1</td></tr><tr><td>College of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China</td><td>1</td></tr><tr><td>LAMIA, EA 4540, University of French West Indies & Guyana</td><td>1</td></tr><tr><td>Peking University & Shanghai Jaio Tong University, Beijing, China</td><td>1</td></tr><tr><td>School of Information Technology, Madurai Kamarai University, Madurai, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, Sanjivani College of Engineering, Kopargaon, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, St.Peter’s University, Chennai, India</td><td>1</td></tr><tr><td>Computer Science and Engineering, Panimalar Engineering College, Chennai, India</td><td>1</td></tr><tr><td>Department of Computer Science, IT-Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal</td><td>1</td></tr><tr><td>ITI Department Telecom Bretagne, Brest, France</td><td>1</td></tr><tr><td>Adobe Systems Incorporated, San Jose, CA, 95110</td><td>1</td></tr><tr><td>Department of Electrical Engineering and Information Technology, TU Darmstadt, D-64283, Germany</td><td>1</td></tr><tr><td>Institute of Neural Information Processing, University of Ulm, Ulm, Germany</td><td>1</td></tr><tr><td>Institute for Information Technology and Communications (IIKT), Otto-von-Guericke-University Magdeburg, Magdeburg, Germany</td><td>1</td></tr><tr><td>Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran</td><td>1</td></tr><tr><td>Defence Science and Technology Organisation (DSTO), Edinburgh, Australia</td><td>1</td></tr><tr><td>Reallusion Corporation</td><td>1</td></tr><tr><td>National Institute of Advanced Industrial Science and Technology (AIST), Koto, Tokyo, Japan</td><td>1</td></tr><tr><td>Computer Application Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China</td><td>1</td></tr><tr><td>Dept. of EE, Univ. at Buffalo, SUNY, USA</td><td>1</td></tr><tr><td>Department of Computer Science, Minjiang University, Fuzhou, People’s Republic of China</td><td>1</td></tr><tr><td>Institute of High Performance Computing and Networking, National Research Council of Italy (ICAR-CNR), Naples, Italy</td><td>1</td></tr></table></body></html>
\ No newline at end of file diff --git a/scraper/reports/pdf_unknown_bigrams.html b/scraper/reports/pdf_unknown_bigrams.html index e04bafda..a34fbe4d 100644 --- a/scraper/reports/pdf_unknown_bigrams.html +++ b/scraper/reports/pdf_unknown_bigrams.html @@ -1 +1 @@ -<!doctype html><html><head><meta charset='utf-8'><title>PDF Report: Unknown Bigrams</title><link rel='stylesheet' href='reports.css'></head><body><h2>PDF Report: Unknown Bigrams</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>of the</td><td>1403</td></tr><tr><td>computer science</td><td>959</td></tr><tr><td>of computer</td><td>889</td></tr><tr><td>face recognition</td><td>876</td></tr><tr><td>in the</td><td>796</td></tr><tr><td>science and</td><td>536</td></tr><tr><td>member ieee</td><td>531</td></tr><tr><td>facial expression</td><td>507</td></tr><tr><td>of technology</td><td>393</td></tr><tr><td>for the</td><td>374</td></tr><tr><td>to the</td><td>373</td></tr><tr><td>on the</td><td>345</td></tr><tr><td>of electrical</td><td>299</td></tr><tr><td>for face</td><td>296</td></tr><tr><td>expression recognition</td><td>277</td></tr><tr><td>computer vision</td><td>259</td></tr><tr><td>and technology</td><td>259</td></tr><tr><td>facial expressions</td><td>251</td></tr><tr><td>in this</td><td>248</td></tr><tr><td>by the</td><td>247</td></tr><tr><td>and computer</td><td>241</td></tr><tr><td>classi cation</td><td>239</td></tr><tr><td>computer engineering</td><td>234</td></tr><tr><td>and the</td><td>229</td></tr><tr><td>from the</td><td>229</td></tr><tr><td>of engineering</td><td>221</td></tr><tr><td>international journal</td><td>215</td></tr><tr><td>has been</td><td>209</td></tr><tr><td>and engineering</td><td>206</td></tr><tr><td>of information</td><td>202</td></tr><tr><td>beijing china</td><td>197</td></tr><tr><td>of facial</td><td>195</td></tr><tr><td>engineering and</td><td>193</td></tr><tr><td>electrical engineering</td><td>192</td></tr><tr><td>of science</td><td>187</td></tr><tr><td>center for</td><td>177</td></tr><tr><td>is the</td><td>177</td></tr><tr><td>this paper</td><td>176</td></tr><tr><td>with the</td><td>171</td></tr><tr><td>electrical and</td><td>167</td></tr><tr><td>carnegie mellon</td><td>163</td></tr><tr><td>mellon university</td><td>162</td></tr><tr><td>open access</td><td>157</td></tr><tr><td>http www</td><td>153</td></tr><tr><td>of this</td><td>152</td></tr><tr><td>the face</td><td>150</td></tr><tr><td>of california</td><td>146</td></tr><tr><td>recognition using</td><td>143</td></tr><tr><td>of face</td><td>139</td></tr><tr><td>neural networks</td><td>139</td></tr><tr><td>the degree</td><td>138</td></tr><tr><td>of sciences</td><td>136</td></tr><tr><td>that the</td><td>136</td></tr><tr><td>of computing</td><td>135</td></tr><tr><td>senior member</td><td>134</td></tr><tr><td>and information</td><td>134</td></tr><tr><td>hong kong</td><td>132</td></tr><tr><td>face detection</td><td>131</td></tr><tr><td>ieee and</td><td>130</td></tr><tr><td>for facial</td><td>129</td></tr><tr><td>have been</td><td>128</td></tr><tr><td>institute for</td><td>125</td></tr><tr><td>this work</td><td>123</td></tr><tr><td>real time</td><td>122</td></tr><tr><td>fellow ieee</td><td>122</td></tr><tr><td>pattern recognition</td><td>121</td></tr><tr><td>chinese academy</td><td>121</td></tr><tr><td>action recognition</td><td>121</td></tr><tr><td>the university</td><td>120</td></tr><tr><td>information technology</td><td>120</td></tr><tr><td>state university</td><td>118</td></tr><tr><td>the same</td><td>116</td></tr><tr><td>doi org</td><td>109</td></tr><tr><td>student member</td><td>107</td></tr><tr><td>the wild</td><td>106</td></tr><tr><td>in partial</td><td>103</td></tr><tr><td>face images</td><td>103</td></tr><tr><td>this article</td><td>100</td></tr><tr><td>the requirements</td><td>100</td></tr><tr><td>deep learning</td><td>100</td></tr><tr><td>as the</td><td>99</td></tr><tr><td>veri cation</td><td>98</td></tr><tr><td>emotion recognition</td><td>97</td></tr><tr><td>feature extraction</td><td>95</td></tr><tr><td>at the</td><td>92</td></tr><tr><td>vision and</td><td>92</td></tr><tr><td>identi cation</td><td>91</td></tr><tr><td>of philosophy</td><td>91</td></tr><tr><td>national university</td><td>89</td></tr><tr><td>information engineering</td><td>89</td></tr><tr><td>large scale</td><td>87</td></tr><tr><td>in computer</td><td>87</td></tr><tr><td>neural network</td><td>86</td></tr><tr><td>recognition with</td><td>86</td></tr><tr><td>the proposed</td><td>86</td></tr><tr><td>the art</td><td>85</td></tr><tr><td>the most</td><td>84</td></tr><tr><td>machine learning</td><td>83</td></tr><tr><td>the netherlands</td><td>82</td></tr><tr><td>research article</td><td>82</td></tr><tr><td>signal processing</td><td>82</td></tr><tr><td>we propose</td><td>82</td></tr><tr><td>detection and</td><td>81</td></tr><tr><td>of human</td><td>81</td></tr><tr><td>college london</td><td>80</td></tr><tr><td>information science</td><td>79</td></tr><tr><td>learning for</td><td>78</td></tr><tr><td>convolutional neural</td><td>77</td></tr><tr><td>dx doi</td><td>76</td></tr><tr><td>arti cial</td><td>76</td></tr><tr><td>requirements for</td><td>74</td></tr><tr><td>recognition and</td><td>72</td></tr><tr><td>the facial</td><td>71</td></tr><tr><td>face and</td><td>71</td></tr><tr><td>the original</td><td>71</td></tr><tr><td>of psychology</td><td>71</td></tr><tr><td>engineering university</td><td>71</td></tr><tr><td>of advanced</td><td>70</td></tr><tr><td>pa usa</td><td>70</td></tr><tr><td>of maryland</td><td>70</td></tr><tr><td>of informatics</td><td>70</td></tr><tr><td>of electronics</td><td>70</td></tr><tr><td>science university</td><td>70</td></tr><tr><td>recognition system</td><td>70</td></tr><tr><td>united kingdom</td><td>70</td></tr><tr><td>volume issue</td><td>69</td></tr><tr><td>partial ful</td><td>69</td></tr><tr><td>expression analysis</td><td>68</td></tr><tr><td>key laboratory</td><td>68</td></tr><tr><td>face alignment</td><td>68</td></tr><tr><td>for action</td><td>67</td></tr><tr><td>of our</td><td>67</td></tr><tr><td>the image</td><td>67</td></tr><tr><td>analysis and</td><td>66</td></tr><tr><td>ful llment</td><td>66</td></tr><tr><td>in video</td><td>65</td></tr><tr><td>international conference</td><td>65</td></tr><tr><td>age estimation</td><td>65</td></tr><tr><td>under the</td><td>64</td></tr><tr><td>face image</td><td>64</td></tr><tr><td>of hong</td><td>64</td></tr><tr><td>of chinese</td><td>63</td></tr><tr><td>based face</td><td>62</td></tr><tr><td>san diego</td><td>62</td></tr><tr><td>ca usa</td><td>62</td></tr><tr><td>image processing</td><td>62</td></tr><tr><td>human computer</td><td>62</td></tr><tr><td>the problem</td><td>62</td></tr><tr><td>as well</td><td>62</td></tr><tr><td>face veri</td><td>61</td></tr><tr><td>cial intelligence</td><td>61</td></tr><tr><td>that are</td><td>61</td></tr><tr><td>new york</td><td>61</td></tr><tr><td>of these</td><td>61</td></tr><tr><td>college park</td><td>60</td></tr><tr><td>facial feature</td><td>60</td></tr><tr><td>in order</td><td>60</td></tr><tr><td>for example</td><td>60</td></tr><tr><td>science department</td><td>59</td></tr><tr><td>be addressed</td><td>59</td></tr><tr><td>there are</td><td>59</td></tr><tr><td>be used</td><td>59</td></tr><tr><td>is not</td><td>59</td></tr><tr><td>method for</td><td>58</td></tr><tr><td>using the</td><td>58</td></tr><tr><td>robust face</td><td>58</td></tr><tr><td>centre for</td><td>58</td></tr><tr><td>of emotion</td><td>58</td></tr><tr><td>computer and</td><td>57</td></tr><tr><td>in face</td><td>57</td></tr><tr><td>image and</td><td>57</td></tr><tr><td>electronics and</td><td>57</td></tr><tr><td>used for</td><td>56</td></tr><tr><td>research center</td><td>56</td></tr><tr><td>facial landmark</td><td>56</td></tr><tr><td>model for</td><td>56</td></tr><tr><td>creative commons</td><td>56</td></tr><tr><td>real world</td><td>56</td></tr><tr><td>the author</td><td>55</td></tr><tr><td>they are</td><td>55</td></tr><tr><td>the main</td><td>55</td></tr><tr><td>research institute</td><td>55</td></tr><tr><td>show that</td><td>54</td></tr><tr><td>networks for</td><td>54</td></tr><tr><td>an open</td><td>54</td></tr><tr><td>in any</td><td>54</td></tr><tr><td>of automation</td><td>54</td></tr><tr><td>the chinese</td><td>54</td></tr><tr><td>imperial college</td><td>53</td></tr><tr><td>for video</td><td>53</td></tr><tr><td>graduate school</td><td>53</td></tr><tr><td>technology and</td><td>53</td></tr><tr><td>for human</td><td>53</td></tr><tr><td>the data</td><td>53</td></tr><tr><td>facial action</td><td>52</td></tr><tr><td>we present</td><td>52</td></tr><tr><td>recognition based</td><td>52</td></tr><tr><td>the number</td><td>52</td></tr><tr><td>spatio temporal</td><td>52</td></tr><tr><td>chinese university</td><td>52</td></tr><tr><td>in videos</td><td>51</td></tr><tr><td>assistant professor</td><td>51</td></tr><tr><td>component analysis</td><td>51</td></tr><tr><td>recognition from</td><td>51</td></tr><tr><td>pose estimation</td><td>51</td></tr><tr><td>and communication</td><td>51</td></tr><tr><td>and recognition</td><td>51</td></tr><tr><td>for each</td><td>50</td></tr><tr><td>information processing</td><td>50</td></tr><tr><td>and applications</td><td>50</td></tr><tr><td>correspondence should</td><td>50</td></tr><tr><td>local binary</td><td>50</td></tr><tr><td>the other</td><td>50</td></tr><tr><td>for research</td><td>50</td></tr><tr><td>the performance</td><td>49</td></tr><tr><td>information and</td><td>49</td></tr><tr><td>volume article</td><td>49</td></tr><tr><td>support vector</td><td>49</td></tr><tr><td>object detection</td><td>48</td></tr><tr><td>of intelligent</td><td>48</td></tr><tr><td>science engineering</td><td>48</td></tr><tr><td>commons attribution</td><td>48</td></tr><tr><td>head pose</td><td>48</td></tr><tr><td>approach for</td><td>48</td></tr><tr><td>the rst</td><td>48</td></tr><tr><td>of each</td><td>48</td></tr><tr><td>low rank</td><td>48</td></tr><tr><td>facial images</td><td>47</td></tr><tr><td>facial features</td><td>47</td></tr><tr><td>national laboratory</td><td>47</td></tr><tr><td>computing and</td><td>47</td></tr><tr><td>it has</td><td>46</td></tr><tr><td>sparse representation</td><td>46</td></tr><tr><td>ieee transactions</td><td>46</td></tr><tr><td>eth zurich</td><td>46</td></tr><tr><td>of electronic</td><td>46</td></tr><tr><td>in which</td><td>46</td></tr><tr><td>of images</td><td>46</td></tr><tr><td>published online</td><td>46</td></tr><tr><td>computer interaction</td><td>46</td></tr><tr><td>ny usa</td><td>46</td></tr><tr><td>discriminant analysis</td><td>46</td></tr><tr><td>feature selection</td><td>45</td></tr><tr><td>stefanos zafeiriou</td><td>45</td></tr><tr><td>to face</td><td>45</td></tr><tr><td>of pattern</td><td>45</td></tr><tr><td>dictionary learning</td><td>45</td></tr><tr><td>the human</td><td>45</td></tr><tr><td>and face</td><td>45</td></tr><tr><td>automatic facial</td><td>45</td></tr><tr><td>the system</td><td>45</td></tr><tr><td>sciences beijing</td><td>45</td></tr><tr><td>the training</td><td>45</td></tr><tr><td>that can</td><td>45</td></tr><tr><td>to this</td><td>45</td></tr><tr><td>electronic engineering</td><td>45</td></tr><tr><td>technical university</td><td>45</td></tr><tr><td>technical report</td><td>44</td></tr><tr><td>invariant face</td><td>44</td></tr><tr><td>which are</td><td>44</td></tr><tr><td>massachusetts institute</td><td>44</td></tr><tr><td>human face</td><td>44</td></tr><tr><td>semi supervised</td><td>44</td></tr><tr><td>in addition</td><td>43</td></tr><tr><td>key lab</td><td>43</td></tr><tr><td>be inserted</td><td>43</td></tr><tr><td>received date</td><td>43</td></tr><tr><td>accepted date</td><td>43</td></tr><tr><td>ma usa</td><td>43</td></tr><tr><td>features for</td><td>43</td></tr><tr><td>between the</td><td>43</td></tr><tr><td>over the</td><td>43</td></tr><tr><td>rama chellappa</td><td>42</td></tr><tr><td>ef cient</td><td>42</td></tr><tr><td>the editor</td><td>42</td></tr><tr><td>date accepted</td><td>42</td></tr><tr><td>barcelona spain</td><td>42</td></tr><tr><td>and video</td><td>42</td></tr><tr><td>of china</td><td>42</td></tr><tr><td>intelligent systems</td><td>42</td></tr><tr><td>is used</td><td>42</td></tr><tr><td>images and</td><td>42</td></tr><tr><td>action units</td><td>42</td></tr><tr><td>in real</td><td>42</td></tr><tr><td>to improve</td><td>42</td></tr><tr><td>shiguang shan</td><td>42</td></tr><tr><td>corresponding author</td><td>42</td></tr><tr><td>university china</td><td>42</td></tr><tr><td>computer applications</td><td>42</td></tr><tr><td>available online</td><td>41</td></tr><tr><td>network for</td><td>41</td></tr><tr><td>are not</td><td>41</td></tr><tr><td>framework for</td><td>41</td></tr><tr><td>accepted for</td><td>41</td></tr><tr><td>and research</td><td>41</td></tr><tr><td>engineering department</td><td>41</td></tr><tr><td>national institute</td><td>41</td></tr><tr><td>and facial</td><td>41</td></tr><tr><td>high dimensional</td><td>41</td></tr><tr><td>low resolution</td><td>41</td></tr><tr><td>maryland college</td><td>40</td></tr><tr><td>of faces</td><td>40</td></tr><tr><td>the following</td><td>40</td></tr><tr><td>this material</td><td>40</td></tr><tr><td>the creative</td><td>40</td></tr><tr><td>do not</td><td>40</td></tr><tr><td>the recognition</td><td>40</td></tr><tr><td>vol issue</td><td>40</td></tr><tr><td>our method</td><td>40</td></tr><tr><td>and machine</td><td>40</td></tr><tr><td>issn online</td><td>39</td></tr><tr><td>on image</td><td>39</td></tr><tr><td>rights reserved</td><td>39</td></tr><tr><td>machine vision</td><td>39</td></tr><tr><td>dimensionality reduction</td><td>39</td></tr><tr><td>associated with</td><td>39</td></tr><tr><td>of surrey</td><td>39</td></tr><tr><td>of amsterdam</td><td>39</td></tr><tr><td>image analysis</td><td>39</td></tr><tr><td>tsinghua university</td><td>39</td></tr><tr><td>de ned</td><td>39</td></tr><tr><td>robotics institute</td><td>38</td></tr><tr><td>of mathematics</td><td>38</td></tr><tr><td>eurasip journal</td><td>38</td></tr><tr><td>models for</td><td>38</td></tr><tr><td>to cite</td><td>38</td></tr><tr><td>recognition systems</td><td>38</td></tr><tr><td>artificial intelligence</td><td>38</td></tr><tr><td>provided the</td><td>38</td></tr><tr><td>microsoft research</td><td>38</td></tr><tr><td>michigan state</td><td>38</td></tr><tr><td>to recognize</td><td>38</td></tr><tr><td>in many</td><td>38</td></tr><tr><td>features and</td><td>38</td></tr><tr><td>an image</td><td>38</td></tr><tr><td>super resolution</td><td>38</td></tr><tr><td>metric learning</td><td>38</td></tr><tr><td>of texas</td><td>37</td></tr><tr><td>deep neural</td><td>37</td></tr><tr><td>of illinois</td><td>37</td></tr><tr><td>cite this</td><td>37</td></tr><tr><td>experimental results</td><td>37</td></tr><tr><td>technology cas</td><td>37</td></tr><tr><td>and its</td><td>37</td></tr><tr><td>system for</td><td>37</td></tr><tr><td>all rights</td><td>37</td></tr><tr><td>human action</td><td>37</td></tr><tr><td>recognition under</td><td>37</td></tr><tr><td>we are</td><td>37</td></tr><tr><td>the first</td><td>36</td></tr><tr><td>is that</td><td>36</td></tr><tr><td>mathematics and</td><td>36</td></tr><tr><td>pose and</td><td>36</td></tr><tr><td>psychology university</td><td>36</td></tr><tr><td>the visual</td><td>36</td></tr><tr><td>for image</td><td>36</td></tr><tr><td>to extract</td><td>36</td></tr><tr><td>the authors</td><td>36</td></tr><tr><td>to learn</td><td>36</td></tr><tr><td>the state</td><td>35</td></tr><tr><td>maja pantic</td><td>35</td></tr><tr><td>representation for</td><td>35</td></tr><tr><td>action unit</td><td>35</td></tr><tr><td>by using</td><td>35</td></tr><tr><td>is one</td><td>35</td></tr><tr><td>the user</td><td>35</td></tr><tr><td>weakly supervised</td><td>35</td></tr><tr><td>is also</td><td>35</td></tr><tr><td>all the</td><td>35</td></tr><tr><td>for visual</td><td>35</td></tr><tr><td>of oxford</td><td>35</td></tr><tr><td>of image</td><td>35</td></tr><tr><td>based methods</td><td>35</td></tr><tr><td>data and</td><td>35</td></tr><tr><td>of cse</td><td>35</td></tr><tr><td>learning and</td><td>35</td></tr><tr><td>engineering the</td><td>35</td></tr><tr><td>we use</td><td>35</td></tr><tr><td>activity recognition</td><td>35</td></tr><tr><td>to make</td><td>34</td></tr><tr><td>the model</td><td>34</td></tr><tr><td>of thessaloniki</td><td>34</td></tr><tr><td>published version</td><td>34</td></tr><tr><td>max planck</td><td>34</td></tr><tr><td>facial emotion</td><td>34</td></tr><tr><td>or not</td><td>34</td></tr><tr><td>the use</td><td>34</td></tr><tr><td>access article</td><td>34</td></tr><tr><td>distributed under</td><td>34</td></tr><tr><td>distribution and</td><td>34</td></tr><tr><td>original work</td><td>34</td></tr><tr><td>for this</td><td>34</td></tr><tr><td>binary pattern</td><td>34</td></tr><tr><td>analysis for</td><td>34</td></tr><tr><td>when the</td><td>34</td></tr><tr><td>the last</td><td>34</td></tr><tr><td>improve the</td><td>34</td></tr><tr><td>of social</td><td>34</td></tr><tr><td>we also</td><td>34</td></tr><tr><td>is available</td><td>34</td></tr><tr><td>california san</td><td>34</td></tr><tr><td>wang and</td><td>34</td></tr><tr><td>university beijing</td><td>34</td></tr><tr><td>university college</td><td>34</td></tr><tr><td>from video</td><td>34</td></tr><tr><td>of all</td><td>33</td></tr><tr><td>fine grained</td><td>33</td></tr><tr><td>of southern</td><td>33</td></tr><tr><td>southern california</td><td>33</td></tr><tr><td>the work</td><td>33</td></tr><tr><td>urbana champaign</td><td>33</td></tr><tr><td>anil jain</td><td>33</td></tr><tr><td>to achieve</td><td>33</td></tr><tr><td>for informatics</td><td>33</td></tr><tr><td>affective computing</td><td>33</td></tr><tr><td>speech and</td><td>33</td></tr><tr><td>cas beijing</td><td>33</td></tr><tr><td>of applied</td><td>33</td></tr><tr><td>where the</td><td>33</td></tr><tr><td>supervised learning</td><td>33</td></tr><tr><td>visual recognition</td><td>33</td></tr><tr><td>at http</td><td>32</td></tr><tr><td>https doi</td><td>32</td></tr><tr><td>and computing</td><td>32</td></tr><tr><td>van gool</td><td>32</td></tr><tr><td>shuicheng yan</td><td>32</td></tr><tr><td>active appearance</td><td>32</td></tr><tr><td>the best</td><td>32</td></tr><tr><td>permits unrestricted</td><td>32</td></tr><tr><td>is properly</td><td>32</td></tr><tr><td>the feature</td><td>32</td></tr><tr><td>stanford university</td><td>32</td></tr><tr><td>the results</td><td>32</td></tr><tr><td>to solve</td><td>32</td></tr><tr><td>and then</td><td>32</td></tr><tr><td>automatic face</td><td>32</td></tr><tr><td>an important</td><td>32</td></tr><tr><td>video based</td><td>32</td></tr><tr><td>xiaoou tang</td><td>32</td></tr><tr><td>on computer</td><td>32</td></tr><tr><td>thesis submitted</td><td>32</td></tr><tr><td>people with</td><td>31</td></tr><tr><td>intelligent information</td><td>31</td></tr><tr><td>shanghai china</td><td>31</td></tr><tr><td>indian institute</td><td>31</td></tr><tr><td>to facial</td><td>31</td></tr><tr><td>luc van</td><td>31</td></tr><tr><td>the images</td><td>31</td></tr><tr><td>the video</td><td>31</td></tr><tr><td>of features</td><td>31</td></tr><tr><td>planck institute</td><td>31</td></tr><tr><td>of singapore</td><td>31</td></tr><tr><td>object recognition</td><td>31</td></tr><tr><td>zhang and</td><td>31</td></tr><tr><td>tokyo japan</td><td>31</td></tr><tr><td>facial image</td><td>31</td></tr><tr><td>the accuracy</td><td>31</td></tr><tr><td>training data</td><td>31</td></tr><tr><td>and image</td><td>31</td></tr><tr><td>dr ing</td><td>31</td></tr><tr><td>processing and</td><td>31</td></tr><tr><td>research and</td><td>31</td></tr><tr><td>li and</td><td>31</td></tr><tr><td>in our</td><td>31</td></tr><tr><td>engineering national</td><td>31</td></tr><tr><td>model based</td><td>31</td></tr><tr><td>in figure</td><td>31</td></tr><tr><td>and electronic</td><td>31</td></tr><tr><td>of central</td><td>31</td></tr><tr><td>taipei taiwan</td><td>31</td></tr><tr><td>in social</td><td>31</td></tr><tr><td>tehran iran</td><td>31</td></tr><tr><td>on facial</td><td>31</td></tr><tr><td>been accepted</td><td>31</td></tr><tr><td>we will</td><td>31</td></tr><tr><td>the department</td><td>30</td></tr><tr><td>this version</td><td>30</td></tr><tr><td>pose invariant</td><td>30</td></tr><tr><td>not the</td><td>30</td></tr><tr><td>article distributed</td><td>30</td></tr><tr><td>unrestricted use</td><td>30</td></tr><tr><td>any medium</td><td>30</td></tr><tr><td>medium provided</td><td>30</td></tr><tr><td>illumination and</td><td>30</td></tr><tr><td>into the</td><td>30</td></tr><tr><td>during the</td><td>30</td></tr><tr><td>xilin chen</td><td>30</td></tr><tr><td>computing technology</td><td>30</td></tr><tr><td>on face</td><td>30</td></tr><tr><td>and signal</td><td>30</td></tr><tr><td>the development</td><td>30</td></tr><tr><td>as follows</td><td>30</td></tr><tr><td>domain adaptation</td><td>30</td></tr><tr><td>signi cant</td><td>30</td></tr><tr><td>tel aviv</td><td>30</td></tr><tr><td>of washington</td><td>30</td></tr><tr><td>cation and</td><td>30</td></tr><tr><td>subspace clustering</td><td>29</td></tr><tr><td>jeffrey cohn</td><td>29</td></tr><tr><td>the shape</td><td>29</td></tr><tr><td>using deep</td><td>29</td></tr><tr><td>aristotle university</td><td>29</td></tr><tr><td>thessaloniki greece</td><td>29</td></tr><tr><td>landmark localization</td><td>29</td></tr><tr><td>come from</td><td>29</td></tr><tr><td>which permits</td><td>29</td></tr><tr><td>use distribution</td><td>29</td></tr><tr><td>and reproduction</td><td>29</td></tr><tr><td>recent years</td><td>29</td></tr><tr><td>of data</td><td>29</td></tr><tr><td>information sciences</td><td>29</td></tr><tr><td>from face</td><td>29</td></tr><tr><td>of research</td><td>29</td></tr><tr><td>academic editor</td><td>29</td></tr><tr><td>proposed method</td><td>29</td></tr><tr><td>vector machine</td><td>29</td></tr><tr><td>of london</td><td>29</td></tr><tr><td>united states</td><td>29</td></tr><tr><td>methods for</td><td>29</td></tr><tr><td>the scene</td><td>29</td></tr><tr><td>linear discriminant</td><td>29</td></tr><tr><td>facial landmarks</td><td>29</td></tr><tr><td>software engineering</td><td>28</td></tr><tr><td>computer sciences</td><td>28</td></tr><tr><td>information about</td><td>28</td></tr><tr><td>we show</td><td>28</td></tr><tr><td>and pattern</td><td>28</td></tr><tr><td>to detect</td><td>28</td></tr><tr><td>of visual</td><td>28</td></tr><tr><td>attribution license</td><td>28</td></tr><tr><td>image retrieval</td><td>28</td></tr><tr><td>engineering research</td><td>28</td></tr><tr><td>and their</td><td>28</td></tr><tr><td>technische universit</td><td>28</td></tr><tr><td>technological university</td><td>28</td></tr><tr><td>at unchen</td><td>28</td></tr><tr><td>columbia university</td><td>28</td></tr><tr><td>cordelia schmid</td><td>28</td></tr><tr><td>systems and</td><td>28</td></tr><tr><td>use the</td><td>28</td></tr><tr><td>central florida</td><td>28</td></tr><tr><td>human robot</td><td>28</td></tr><tr><td>please contact</td><td>27</td></tr><tr><td>material for</td><td>27</td></tr><tr><td>downloaded from</td><td>27</td></tr><tr><td>principal component</td><td>27</td></tr><tr><td>in facial</td><td>27</td></tr><tr><td>noname manuscript</td><td>27</td></tr><tr><td>appearance models</td><td>27</td></tr><tr><td>advanced technology</td><td>27</td></tr><tr><td>id pages</td><td>27</td></tr><tr><td>properly cited</td><td>27</td></tr><tr><td>of different</td><td>27</td></tr><tr><td>automation chinese</td><td>27</td></tr><tr><td>been proposed</td><td>27</td></tr><tr><td>the computer</td><td>27</td></tr><tr><td>for robust</td><td>27</td></tr><tr><td>queen mary</td><td>27</td></tr><tr><td>liu and</td><td>27</td></tr><tr><td>engineering college</td><td>27</td></tr><tr><td>deep convolutional</td><td>27</td></tr><tr><td>in particular</td><td>27</td></tr><tr><td>this chapter</td><td>27</td></tr><tr><td>peking university</td><td>27</td></tr><tr><td>laboratory for</td><td>27</td></tr><tr><td>for all</td><td>27</td></tr><tr><td>machine intelligence</td><td>27</td></tr><tr><td>we can</td><td>27</td></tr><tr><td>unconstrained face</td><td>27</td></tr><tr><td>in human</td><td>27</td></tr><tr><td>multi task</td><td>26</td></tr><tr><td>of new</td><td>26</td></tr><tr><td>to identify</td><td>26</td></tr><tr><td>in unconstrained</td><td>26</td></tr><tr><td>the paper</td><td>26</td></tr><tr><td>in other</td><td>26</td></tr><tr><td>at urbana</td><td>26</td></tr><tr><td>nd the</td><td>26</td></tr><tr><td>from facial</td><td>26</td></tr><tr><td>cation using</td><td>26</td></tr><tr><td>detection using</td><td>26</td></tr><tr><td>images for</td><td>26</td></tr><tr><td>more information</td><td>26</td></tr><tr><td>whether they</td><td>26</td></tr><tr><td>teaching and</td><td>26</td></tr><tr><td>of massachusetts</td><td>26</td></tr><tr><td>features are</td><td>26</td></tr><tr><td>research group</td><td>26</td></tr><tr><td>we have</td><td>26</td></tr><tr><td>recognition has</td><td>26</td></tr><tr><td>the local</td><td>26</td></tr><tr><td>engineering science</td><td>26</td></tr><tr><td>which can</td><td>26</td></tr><tr><td>of pennsylvania</td><td>26</td></tr><tr><td>this study</td><td>26</td></tr><tr><td>human faces</td><td>26</td></tr><tr><td>expression and</td><td>26</td></tr><tr><td>however the</td><td>26</td></tr><tr><td>ku leuven</td><td>26</td></tr><tr><td>nanyang technological</td><td>26</td></tr><tr><td>seoul korea</td><td>26</td></tr><tr><td>of deep</td><td>26</td></tr><tr><td>md usa</td><td>26</td></tr><tr><td>does not</td><td>26</td></tr><tr><td>communication engineering</td><td>26</td></tr><tr><td>national taiwan</td><td>26</td></tr><tr><td>algorithm for</td><td>26</td></tr><tr><td>learning based</td><td>26</td></tr><tr><td>the past</td><td>26</td></tr><tr><td>intelligence and</td><td>26</td></tr><tr><td>dissertation submitted</td><td>26</td></tr><tr><td>the object</td><td>26</td></tr><tr><td>if the</td><td>26</td></tr><tr><td>for automation</td><td>25</td></tr><tr><td>this problem</td><td>25</td></tr><tr><td>information systems</td><td>25</td></tr><tr><td>vision lab</td><td>25</td></tr><tr><td>of emotional</td><td>25</td></tr><tr><td>personal use</td><td>25</td></tr><tr><td>and systems</td><td>25</td></tr><tr><td>de lausanne</td><td>25</td></tr><tr><td>video processing</td><td>25</td></tr><tr><td>for more</td><td>25</td></tr><tr><td>is multi</td><td>25</td></tr><tr><td>are the</td><td>25</td></tr><tr><td>classi ers</td><td>25</td></tr><tr><td>face analysis</td><td>25</td></tr><tr><td>of pittsburgh</td><td>25</td></tr><tr><td>our approach</td><td>25</td></tr><tr><td>to build</td><td>25</td></tr><tr><td>to obtain</td><td>25</td></tr><tr><td>latex class</td><td>25</td></tr><tr><td>class files</td><td>25</td></tr><tr><td>extracted from</td><td>25</td></tr><tr><td>it can</td><td>25</td></tr><tr><td>than the</td><td>25</td></tr><tr><td>signi cantly</td><td>25</td></tr><tr><td>robust facial</td><td>25</td></tr><tr><td>shape and</td><td>25</td></tr><tr><td>technology sydney</td><td>25</td></tr><tr><td>of tokyo</td><td>25</td></tr><tr><td>of objects</td><td>25</td></tr><tr><td>optical flow</td><td>25</td></tr><tr><td>images are</td><td>25</td></tr><tr><td>research portal</td><td>25</td></tr><tr><td>taiwan university</td><td>25</td></tr><tr><td>at www</td><td>24</td></tr><tr><td>electrical computer</td><td>24</td></tr><tr><td>automation research</td><td>24</td></tr><tr><td>the full</td><td>24</td></tr><tr><td>to publication</td><td>24</td></tr><tr><td>this document</td><td>24</td></tr><tr><td>from public</td><td>24</td></tr><tr><td>thomas huang</td><td>24</td></tr><tr><td>vision center</td><td>24</td></tr><tr><td>images with</td><td>24</td></tr><tr><td>ecole polytechnique</td><td>24</td></tr><tr><td>and dissemination</td><td>24</td></tr><tr><td>the documents</td><td>24</td></tr><tr><td>may come</td><td>24</td></tr><tr><td>or from</td><td>24</td></tr><tr><td>hindawi publishing</td><td>24</td></tr><tr><td>publishing corporation</td><td>24</td></tr><tr><td>the two</td><td>24</td></tr><tr><td>kristen grauman</td><td>24</td></tr><tr><td>and security</td><td>24</td></tr><tr><td>of training</td><td>24</td></tr><tr><td>the journal</td><td>24</td></tr><tr><td>transfer learning</td><td>24</td></tr><tr><td>issn print</td><td>24</td></tr><tr><td>la jolla</td><td>24</td></tr><tr><td>and pose</td><td>24</td></tr><tr><td>correspondence tel</td><td>24</td></tr><tr><td>california berkeley</td><td>24</td></tr><tr><td>the task</td><td>24</td></tr><tr><td>the identity</td><td>24</td></tr><tr><td>the input</td><td>24</td></tr><tr><td>local features</td><td>24</td></tr><tr><td>normal university</td><td>24</td></tr><tr><td>pattern analysis</td><td>24</td></tr><tr><td>of any</td><td>24</td></tr><tr><td>massachusetts amherst</td><td>24</td></tr><tr><td>in section</td><td>24</td></tr><tr><td>learning from</td><td>24</td></tr><tr><td>of latex</td><td>24</td></tr><tr><td>to have</td><td>24</td></tr><tr><td>this journal</td><td>24</td></tr><tr><td>google research</td><td>24</td></tr><tr><td>algorithms for</td><td>23</td></tr><tr><td>and are</td><td>23</td></tr><tr><td>video and</td><td>23</td></tr><tr><td>peer reviewed</td><td>23</td></tr><tr><td>the published</td><td>23</td></tr><tr><td>if you</td><td>23</td></tr><tr><td>no august</td><td>23</td></tr><tr><td>ieee international</td><td>23</td></tr><tr><td>multi disciplinary</td><td>23</td></tr><tr><td>disciplinary open</td><td>23</td></tr><tr><td>rchive for</td><td>23</td></tr><tr><td>the deposit</td><td>23</td></tr><tr><td>deposit and</td><td>23</td></tr><tr><td>of sci</td><td>23</td></tr><tr><td>research documents</td><td>23</td></tr><tr><td>documents whether</td><td>23</td></tr><tr><td>are pub</td><td>23</td></tr><tr><td>documents may</td><td>23</td></tr><tr><td>research institutions</td><td>23</td></tr><tr><td>in france</td><td>23</td></tr><tr><td>or private</td><td>23</td></tr><tr><td>private research</td><td>23</td></tr><tr><td>research centers</td><td>23</td></tr><tr><td>archive ouverte</td><td>23</td></tr><tr><td>ouverte pluridisciplinaire</td><td>23</td></tr><tr><td>pluridisciplinaire hal</td><td>23</td></tr><tr><td>hal est</td><td>23</td></tr><tr><td>la diffusion</td><td>23</td></tr><tr><td>de documents</td><td>23</td></tr><tr><td>de niveau</td><td>23</td></tr><tr><td>niveau recherche</td><td>23</td></tr><tr><td>recherche publi</td><td>23</td></tr><tr><td>ou non</td><td>23</td></tr><tr><td>recherche fran</td><td>23</td></tr><tr><td>des laboratoires</td><td>23</td></tr><tr><td>ou priv</td><td>23</td></tr><tr><td>representations for</td><td>23</td></tr><tr><td>for learning</td><td>23</td></tr><tr><td>of interest</td><td>23</td></tr><tr><td>in terms</td><td>23</td></tr><tr><td>appearance based</td><td>23</td></tr><tr><td>and intelligent</td><td>23</td></tr><tr><td>tel fax</td><td>23</td></tr><tr><td>al this</td><td>23</td></tr><tr><td>the high</td><td>23</td></tr><tr><td>is more</td><td>23</td></tr><tr><td>face representation</td><td>23</td></tr><tr><td>ef icient</td><td>23</td></tr><tr><td>key words</td><td>23</td></tr><tr><td>files vol</td><td>23</td></tr><tr><td>of automatic</td><td>23</td></tr><tr><td>the current</td><td>23</td></tr><tr><td>the ability</td><td>23</td></tr><tr><td>of them</td><td>23</td></tr><tr><td>for vision</td><td>23</td></tr><tr><td>mary university</td><td>23</td></tr><tr><td>large number</td><td>23</td></tr><tr><td>ground truth</td><td>23</td></tr><tr><td>recognition for</td><td>23</td></tr><tr><td>of video</td><td>23</td></tr><tr><td>each other</td><td>23</td></tr><tr><td>singapore singapore</td><td>23</td></tr><tr><td>amsterdam the</td><td>23</td></tr><tr><td>north carolina</td><td>23</td></tr><tr><td>state key</td><td>23</td></tr><tr><td>east lansing</td><td>23</td></tr><tr><td>these methods</td><td>23</td></tr><tr><td>generative adversarial</td><td>23</td></tr><tr><td>of doctor</td><td>23</td></tr><tr><td>andrew zisserman</td><td>23</td></tr><tr><td>speci cally</td><td>23</td></tr><tr><td>istanbul turkey</td><td>23</td></tr><tr><td>of people</td><td>22</td></tr><tr><td>based facial</td><td>22</td></tr><tr><td>video classi</td><td>22</td></tr><tr><td>and tracking</td><td>22</td></tr><tr><td>research online</td><td>22</td></tr><tr><td>was submitted</td><td>22</td></tr><tr><td>extraction and</td><td>22</td></tr><tr><td>nanjing university</td><td>22</td></tr><tr><td>in image</td><td>22</td></tr><tr><td>under varying</td><td>22</td></tr><tr><td>polytechnic university</td><td>22</td></tr><tr><td>to end</td><td>22</td></tr><tr><td>applied sciences</td><td>22</td></tr><tr><td>article was</td><td>22</td></tr><tr><td>www frontiersin</td><td>22</td></tr><tr><td>frontiersin org</td><td>22</td></tr><tr><td>the research</td><td>22</td></tr><tr><td>and illumination</td><td>22</td></tr><tr><td>is very</td><td>22</td></tr><tr><td>feature based</td><td>22</td></tr><tr><td>of two</td><td>22</td></tr><tr><td>of toronto</td><td>22</td></tr><tr><td>stony brook</td><td>22</td></tr><tr><td>received march</td><td>22</td></tr><tr><td>methods have</td><td>22</td></tr><tr><td>for large</td><td>22</td></tr><tr><td>chen and</td><td>22</td></tr><tr><td>still images</td><td>22</td></tr><tr><td>differences between</td><td>22</td></tr><tr><td>such that</td><td>22</td></tr><tr><td>in recent</td><td>22</td></tr><tr><td>decision making</td><td>22</td></tr><tr><td>to determine</td><td>22</td></tr><tr><td>for publication</td><td>22</td></tr><tr><td>cornell university</td><td>21</td></tr><tr><td>for instance</td><td>21</td></tr><tr><td>and low</td><td>21</td></tr><tr><td>and gender</td><td>21</td></tr><tr><td>of twente</td><td>21</td></tr><tr><td>and ioannis</td><td>21</td></tr><tr><td>works for</td><td>21</td></tr><tr><td>for pose</td><td>21</td></tr><tr><td>deep face</td><td>21</td></tr><tr><td>the second</td><td>21</td></tr><tr><td>system and</td><td>21</td></tr><tr><td>jiaotong university</td><td>21</td></tr><tr><td>conference paper</td><td>21</td></tr><tr><td>institute carnegie</td><td>21</td></tr><tr><td>illumination invariant</td><td>21</td></tr><tr><td>recognition rate</td><td>21</td></tr><tr><td>binary patterns</td><td>21</td></tr><tr><td>while the</td><td>21</td></tr><tr><td>learning with</td><td>21</td></tr><tr><td>original research</td><td>21</td></tr><tr><td>of emotions</td><td>21</td></tr><tr><td>expressions are</td><td>21</td></tr><tr><td>studies have</td><td>21</td></tr><tr><td>through the</td><td>21</td></tr><tr><td>gender classi</td><td>21</td></tr><tr><td>and other</td><td>21</td></tr><tr><td>and expression</td><td>21</td></tr><tr><td>expressions and</td><td>21</td></tr><tr><td>low dimensional</td><td>21</td></tr><tr><td>international joint</td><td>21</td></tr><tr><td>electronic and</td><td>21</td></tr><tr><td>recognition via</td><td>21</td></tr><tr><td>about the</td><td>21</td></tr><tr><td>tracking and</td><td>21</td></tr><tr><td>reduce the</td><td>21</td></tr><tr><td>is still</td><td>21</td></tr><tr><td>engineering technology</td><td>21</td></tr><tr><td>using local</td><td>21</td></tr><tr><td>gesture recognition</td><td>21</td></tr><tr><td>on pattern</td><td>21</td></tr><tr><td>face hallucination</td><td>21</td></tr><tr><td>polytechnic institute</td><td>21</td></tr><tr><td>not been</td><td>21</td></tr><tr><td>the dataset</td><td>21</td></tr><tr><td>of computational</td><td>21</td></tr><tr><td>computational intelligence</td><td>21</td></tr><tr><td>of statistics</td><td>21</td></tr><tr><td>event detection</td><td>21</td></tr><tr><td>data points</td><td>21</td></tr><tr><td>article has</td><td>21</td></tr><tr><td>the method</td><td>21</td></tr><tr><td>tx usa</td><td>20</td></tr><tr><td>to address</td><td>20</td></tr><tr><td>matrix factorization</td><td>20</td></tr><tr><td>for inclusion</td><td>20</td></tr><tr><td>of use</td><td>20</td></tr><tr><td>is permitted</td><td>20</td></tr><tr><td>obtained from</td><td>20</td></tr><tr><td>landmark detection</td><td>20</td></tr><tr><td>systems for</td><td>20</td></tr><tr><td>nanjing china</td><td>20</td></tr><tr><td>or the</td><td>20</td></tr><tr><td>recognition algorithms</td><td>20</td></tr><tr><td>our system</td><td>20</td></tr><tr><td>and david</td><td>20</td></tr><tr><td>shenzhen institutes</td><td>20</td></tr><tr><td>electronics engineering</td><td>20</td></tr><tr><td>nicu sebe</td><td>20</td></tr><tr><td>visual attributes</td><td>20</td></tr><tr><td>springer science</td><td>20</td></tr><tr><td>science business</td><td>20</td></tr><tr><td>business media</td><td>20</td></tr><tr><td>illumination variations</td><td>20</td></tr><tr><td>are used</td><td>20</td></tr><tr><td>for real</td><td>20</td></tr><tr><td>to overcome</td><td>20</td></tr><tr><td>vision group</td><td>20</td></tr><tr><td>single image</td><td>20</td></tr><tr><td>and local</td><td>20</td></tr><tr><td>and analysis</td><td>20</td></tr><tr><td>the target</td><td>20</td></tr><tr><td>to human</td><td>20</td></tr><tr><td>sciences cas</td><td>20</td></tr><tr><td>not only</td><td>20</td></tr><tr><td>the person</td><td>20</td></tr><tr><td>wide range</td><td>20</td></tr><tr><td>for recognition</td><td>20</td></tr><tr><td>dacheng tao</td><td>20</td></tr><tr><td>video sequence</td><td>20</td></tr><tr><td>at austin</td><td>20</td></tr><tr><td>of machine</td><td>20</td></tr><tr><td>in part</td><td>20</td></tr><tr><td>this research</td><td>20</td></tr><tr><td>zurich switzerland</td><td>20</td></tr><tr><td>final publication</td><td>20</td></tr><tr><td>based approach</td><td>20</td></tr><tr><td>shanghai jiao</td><td>20</td></tr><tr><td>jiao tong</td><td>20</td></tr><tr><td>natural language</td><td>20</td></tr><tr><td>received july</td><td>20</td></tr><tr><td>to its</td><td>20</td></tr><tr><td>and human</td><td>20</td></tr><tr><td>robotics and</td><td>20</td></tr><tr><td>associate professor</td><td>20</td></tr><tr><td>and peter</td><td>20</td></tr><tr><td>in future</td><td>20</td></tr><tr><td>future issue</td><td>20</td></tr><tr><td>human activity</td><td>20</td></tr><tr><td>doi fpsyg</td><td>20</td></tr><tr><td>in psychology</td><td>20</td></tr><tr><td>university pittsburgh</td><td>19</td></tr><tr><td>the role</td><td>19</td></tr><tr><td>images using</td><td>19</td></tr><tr><td>australian national</td><td>19</td></tr><tr><td>of korea</td><td>19</td></tr><tr><td>non negative</td><td>19</td></tr><tr><td>ioannis pitas</td><td>19</td></tr><tr><td>of defense</td><td>19</td></tr><tr><td>follow this</td><td>19</td></tr><tr><td>and open</td><td>19</td></tr><tr><td>are available</td><td>19</td></tr><tr><td>and texture</td><td>19</td></tr><tr><td>new collective</td><td>19</td></tr><tr><td>to servers</td><td>19</td></tr><tr><td>or lists</td><td>19</td></tr><tr><td>be obtained</td><td>19</td></tr><tr><td>the ieee</td><td>19</td></tr><tr><td>zero shot</td><td>19</td></tr><tr><td>dataset for</td><td>19</td></tr><tr><td>dimitris metaxas</td><td>19</td></tr><tr><td>rutgers university</td><td>19</td></tr><tr><td>archives ouvertes</td><td>19</td></tr><tr><td>learned miller</td><td>19</td></tr><tr><td>of michigan</td><td>19</td></tr><tr><td>that our</td><td>19</td></tr><tr><td>springer verlag</td><td>19</td></tr><tr><td>received december</td><td>19</td></tr><tr><td>the set</td><td>19</td></tr><tr><td>spontaneous facial</td><td>19</td></tr><tr><td>lausanne switzerland</td><td>19</td></tr><tr><td>as conference</td><td>19</td></tr><tr><td>at iclr</td><td>19</td></tr><tr><td>cedex france</td><td>19</td></tr><tr><td>results show</td><td>19</td></tr><tr><td>which the</td><td>19</td></tr><tr><td>face reconstruction</td><td>19</td></tr><tr><td>is based</td><td>19</td></tr><tr><td>shown that</td><td>19</td></tr><tr><td>ai research</td><td>19</td></tr><tr><td>received may</td><td>19</td></tr><tr><td>idiap research</td><td>19</td></tr><tr><td>learning algorithms</td><td>19</td></tr><tr><td>the twenty</td><td>19</td></tr><tr><td>joint conference</td><td>19</td></tr><tr><td>of its</td><td>19</td></tr><tr><td>of biometric</td><td>19</td></tr><tr><td>in cvpr</td><td>19</td></tr><tr><td>and social</td><td>19</td></tr><tr><td>adobe research</td><td>19</td></tr><tr><td>gender and</td><td>19</td></tr><tr><td>note that</td><td>19</td></tr><tr><td>access control</td><td>19</td></tr><tr><td>visual information</td><td>19</td></tr><tr><td>received april</td><td>19</td></tr><tr><td>on machine</td><td>19</td></tr><tr><td>cation with</td><td>19</td></tr><tr><td>los angeles</td><td>19</td></tr><tr><td>notre dame</td><td>19</td></tr><tr><td>tong university</td><td>19</td></tr><tr><td>paris france</td><td>19</td></tr><tr><td>the robotics</td><td>19</td></tr><tr><td>of posts</td><td>19</td></tr><tr><td>posts and</td><td>19</td></tr><tr><td>and telecommunications</td><td>19</td></tr><tr><td>of their</td><td>19</td></tr><tr><td>non verbal</td><td>19</td></tr><tr><td>optimization problem</td><td>19</td></tr><tr><td>professor department</td><td>19</td></tr><tr><td>and cognitive</td><td>19</td></tr><tr><td>we introduce</td><td>19</td></tr><tr><td>video sequences</td><td>19</td></tr><tr><td>th international</td><td>19</td></tr><tr><td>the entire</td><td>19</td></tr><tr><td>has not</td><td>19</td></tr><tr><td>and software</td><td>18</td></tr><tr><td>objects and</td><td>18</td></tr><tr><td>more than</td><td>18</td></tr><tr><td>la torre</td><td>18</td></tr><tr><td>this and</td><td>18</td></tr><tr><td>and additional</td><td>18</td></tr><tr><td>additional works</td><td>18</td></tr><tr><td>free and</td><td>18</td></tr><tr><td>in accordance</td><td>18</td></tr><tr><td>for advertising</td><td>18</td></tr><tr><td>other works</td><td>18</td></tr><tr><td>volume number</td><td>18</td></tr><tr><td>the goal</td><td>18</td></tr><tr><td>been made</td><td>18</td></tr><tr><td>propose novel</td><td>18</td></tr><tr><td>hyderabad india</td><td>18</td></tr><tr><td>of software</td><td>18</td></tr><tr><td>recognition accuracy</td><td>18</td></tr><tr><td>de barcelona</td><td>18</td></tr><tr><td>then the</td><td>18</td></tr><tr><td>the literature</td><td>18</td></tr><tr><td>the key</td><td>18</td></tr></table></body></html>
\ No newline at end of file +<!doctype html><html><head><meta charset='utf-8'><title>PDF Report: Unknown Bigrams</title><link rel='stylesheet' href='reports.css'></head><body><h2>PDF Report: Unknown Bigrams</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>of the</td><td>4760</td></tr><tr><td>in the</td><td>2840</td></tr><tr><td>computer science</td><td>2687</td></tr><tr><td>of computer</td><td>2418</td></tr><tr><td>face recognition</td><td>1920</td></tr><tr><td>science and</td><td>1502</td></tr><tr><td>to the</td><td>1498</td></tr><tr><td>member ieee</td><td>1381</td></tr><tr><td>of technology</td><td>1248</td></tr><tr><td>for the</td><td>1201</td></tr><tr><td>on the</td><td>1161</td></tr><tr><td>and the</td><td>858</td></tr><tr><td>computer vision</td><td>817</td></tr><tr><td>of electrical</td><td>785</td></tr><tr><td>by the</td><td>782</td></tr><tr><td>facial expression</td><td>778</td></tr><tr><td>from the</td><td>773</td></tr><tr><td>in this</td><td>758</td></tr><tr><td>and technology</td><td>719</td></tr><tr><td>and computer</td><td>715</td></tr><tr><td>classi cation</td><td>668</td></tr><tr><td>has been</td><td>653</td></tr><tr><td>with the</td><td>630</td></tr><tr><td>identi cation</td><td>614</td></tr><tr><td>computer engineering</td><td>584</td></tr><tr><td>of science</td><td>582</td></tr><tr><td>of engineering</td><td>576</td></tr><tr><td>international journal</td><td>571</td></tr><tr><td>facial expressions</td><td>570</td></tr><tr><td>center for</td><td>568</td></tr><tr><td>electrical engineering</td><td>565</td></tr><tr><td>that the</td><td>561</td></tr><tr><td>for face</td><td>560</td></tr><tr><td>and engineering</td><td>544</td></tr><tr><td>of information</td><td>543</td></tr><tr><td>of this</td><td>530</td></tr><tr><td>open access</td><td>525</td></tr><tr><td>engineering and</td><td>524</td></tr><tr><td>of psychology</td><td>517</td></tr><tr><td>beijing china</td><td>513</td></tr><tr><td>this paper</td><td>505</td></tr><tr><td>of california</td><td>497</td></tr><tr><td>institute for</td><td>494</td></tr><tr><td>is the</td><td>479</td></tr><tr><td>the university</td><td>462</td></tr><tr><td>http www</td><td>451</td></tr><tr><td>this article</td><td>450</td></tr><tr><td>electrical and</td><td>438</td></tr><tr><td>have been</td><td>437</td></tr><tr><td>of facial</td><td>411</td></tr><tr><td>neural networks</td><td>402</td></tr><tr><td>the degree</td><td>395</td></tr><tr><td>doi org</td><td>394</td></tr><tr><td>of face</td><td>393</td></tr><tr><td>carnegie mellon</td><td>390</td></tr><tr><td>the face</td><td>385</td></tr><tr><td>mellon university</td><td>384</td></tr><tr><td>this work</td><td>384</td></tr><tr><td>re identi</td><td>380</td></tr><tr><td>expression recognition</td><td>380</td></tr><tr><td>the same</td><td>374</td></tr><tr><td>state university</td><td>372</td></tr><tr><td>at the</td><td>369</td></tr><tr><td>and information</td><td>365</td></tr><tr><td>senior member</td><td>356</td></tr><tr><td>as the</td><td>348</td></tr><tr><td>of sciences</td><td>347</td></tr><tr><td>ieee and</td><td>343</td></tr><tr><td>pattern recognition</td><td>341</td></tr><tr><td>real time</td><td>332</td></tr><tr><td>hong kong</td><td>326</td></tr><tr><td>recognition using</td><td>322</td></tr><tr><td>chinese academy</td><td>320</td></tr><tr><td>of computing</td><td>314</td></tr><tr><td>deep learning</td><td>314</td></tr><tr><td>information technology</td><td>313</td></tr><tr><td>pose estimation</td><td>299</td></tr><tr><td>with autism</td><td>297</td></tr><tr><td>in partial</td><td>296</td></tr><tr><td>the most</td><td>296</td></tr><tr><td>the requirements</td><td>292</td></tr><tr><td>object detection</td><td>292</td></tr><tr><td>new york</td><td>288</td></tr><tr><td>autism spectrum</td><td>285</td></tr><tr><td>fellow ieee</td><td>285</td></tr><tr><td>dx doi</td><td>284</td></tr><tr><td>neural network</td><td>283</td></tr><tr><td>of social</td><td>281</td></tr><tr><td>detection and</td><td>275</td></tr><tr><td>national university</td><td>272</td></tr><tr><td>machine learning</td><td>271</td></tr><tr><td>of philosophy</td><td>265</td></tr><tr><td>be addressed</td><td>261</td></tr><tr><td>student member</td><td>259</td></tr><tr><td>research article</td><td>256</td></tr><tr><td>large scale</td><td>255</td></tr><tr><td>of human</td><td>253</td></tr><tr><td>face detection</td><td>253</td></tr><tr><td>science university</td><td>252</td></tr><tr><td>in computer</td><td>248</td></tr><tr><td>convolutional neural</td><td>246</td></tr><tr><td>the proposed</td><td>245</td></tr><tr><td>key laboratory</td><td>244</td></tr><tr><td>vision and</td><td>243</td></tr><tr><td>arti cial</td><td>242</td></tr><tr><td>ca usa</td><td>242</td></tr><tr><td>learning for</td><td>240</td></tr><tr><td>as well</td><td>239</td></tr><tr><td>of these</td><td>237</td></tr><tr><td>individuals with</td><td>233</td></tr><tr><td>the author</td><td>231</td></tr><tr><td>of our</td><td>230</td></tr><tr><td>they are</td><td>227</td></tr><tr><td>of electronics</td><td>225</td></tr><tr><td>requirements for</td><td>224</td></tr><tr><td>engineering university</td><td>224</td></tr><tr><td>with asd</td><td>224</td></tr><tr><td>the netherlands</td><td>224</td></tr><tr><td>emotion recognition</td><td>224</td></tr><tr><td>associated with</td><td>223</td></tr><tr><td>feature extraction</td><td>223</td></tr><tr><td>information engineering</td><td>222</td></tr><tr><td>the art</td><td>220</td></tr><tr><td>for example</td><td>220</td></tr><tr><td>the original</td><td>220</td></tr><tr><td>we propose</td><td>218</td></tr><tr><td>signal processing</td><td>216</td></tr><tr><td>international conference</td><td>212</td></tr><tr><td>under the</td><td>211</td></tr><tr><td>recognition and</td><td>207</td></tr><tr><td>in face</td><td>206</td></tr><tr><td>volume article</td><td>206</td></tr><tr><td>that are</td><td>202</td></tr><tr><td>the image</td><td>201</td></tr><tr><td>research center</td><td>200</td></tr><tr><td>for facial</td><td>200</td></tr><tr><td>is not</td><td>200</td></tr><tr><td>psychology university</td><td>197</td></tr><tr><td>image processing</td><td>197</td></tr><tr><td>united kingdom</td><td>196</td></tr><tr><td>correspondence should</td><td>194</td></tr><tr><td>in social</td><td>194</td></tr><tr><td>face images</td><td>193</td></tr><tr><td>show that</td><td>192</td></tr><tr><td>for human</td><td>192</td></tr><tr><td>cial intelligence</td><td>191</td></tr><tr><td>action recognition</td><td>190</td></tr><tr><td>college london</td><td>190</td></tr><tr><td>information science</td><td>189</td></tr><tr><td>of electronic</td><td>188</td></tr><tr><td>there are</td><td>187</td></tr><tr><td>object recognition</td><td>187</td></tr><tr><td>in order</td><td>186</td></tr><tr><td>in autism</td><td>186</td></tr><tr><td>centre for</td><td>185</td></tr><tr><td>ef cient</td><td>184</td></tr><tr><td>using the</td><td>184</td></tr><tr><td>the human</td><td>184</td></tr><tr><td>electronics and</td><td>184</td></tr><tr><td>of automation</td><td>183</td></tr><tr><td>and communication</td><td>183</td></tr><tr><td>in which</td><td>181</td></tr><tr><td>published online</td><td>180</td></tr><tr><td>analysis and</td><td>178</td></tr><tr><td>image and</td><td>177</td></tr><tr><td>the rst</td><td>177</td></tr><tr><td>san diego</td><td>176</td></tr><tr><td>face processing</td><td>176</td></tr><tr><td>partial ful</td><td>175</td></tr><tr><td>the main</td><td>175</td></tr><tr><td>networks for</td><td>175</td></tr><tr><td>to this</td><td>175</td></tr><tr><td>for visual</td><td>174</td></tr><tr><td>in any</td><td>174</td></tr><tr><td>los angeles</td><td>174</td></tr><tr><td>ful llment</td><td>173</td></tr><tr><td>graduate school</td><td>171</td></tr><tr><td>of hong</td><td>170</td></tr><tr><td>computer and</td><td>169</td></tr><tr><td>rights reserved</td><td>169</td></tr><tr><td>research institute</td><td>168</td></tr><tr><td>human pose</td><td>168</td></tr><tr><td>the authors</td><td>168</td></tr><tr><td>recognition system</td><td>167</td></tr><tr><td>veri cation</td><td>167</td></tr><tr><td>for image</td><td>167</td></tr><tr><td>all rights</td><td>167</td></tr><tr><td>of faces</td><td>166</td></tr><tr><td>corresponding author</td><td>166</td></tr><tr><td>science department</td><td>165</td></tr><tr><td>max planck</td><td>164</td></tr><tr><td>volume issue</td><td>163</td></tr><tr><td>method for</td><td>163</td></tr><tr><td>and research</td><td>163</td></tr><tr><td>an open</td><td>162</td></tr><tr><td>microsoft research</td><td>162</td></tr><tr><td>children with</td><td>162</td></tr><tr><td>model for</td><td>161</td></tr><tr><td>united states</td><td>159</td></tr><tr><td>of advanced</td><td>158</td></tr><tr><td>eth zurich</td><td>158</td></tr><tr><td>the other</td><td>158</td></tr><tr><td>face and</td><td>157</td></tr><tr><td>electronic engineering</td><td>155</td></tr><tr><td>cite this</td><td>155</td></tr><tr><td>do not</td><td>155</td></tr><tr><td>are not</td><td>154</td></tr><tr><td>be used</td><td>154</td></tr><tr><td>the wild</td><td>153</td></tr><tr><td>of visual</td><td>152</td></tr><tr><td>we use</td><td>152</td></tr><tr><td>and social</td><td>151</td></tr><tr><td>network for</td><td>151</td></tr><tr><td>of images</td><td>151</td></tr><tr><td>creative commons</td><td>151</td></tr><tr><td>the data</td><td>150</td></tr><tr><td>technical university</td><td>150</td></tr><tr><td>used for</td><td>150</td></tr><tr><td>in asd</td><td>150</td></tr><tr><td>for person</td><td>149</td></tr><tr><td>in video</td><td>149</td></tr><tr><td>information and</td><td>149</td></tr><tr><td>of informatics</td><td>149</td></tr><tr><td>to cite</td><td>148</td></tr><tr><td>real world</td><td>147</td></tr><tr><td>for each</td><td>147</td></tr><tr><td>an image</td><td>147</td></tr><tr><td>planck institute</td><td>147</td></tr><tr><td>of emotion</td><td>147</td></tr><tr><td>of psychiatry</td><td>147</td></tr><tr><td>between the</td><td>146</td></tr><tr><td>features for</td><td>146</td></tr><tr><td>spectrum disorders</td><td>146</td></tr><tr><td>it has</td><td>145</td></tr><tr><td>the number</td><td>145</td></tr><tr><td>we present</td><td>144</td></tr><tr><td>and its</td><td>143</td></tr><tr><td>recognition with</td><td>143</td></tr><tr><td>approach for</td><td>142</td></tr><tr><td>in addition</td><td>142</td></tr><tr><td>the facial</td><td>142</td></tr><tr><td>massachusetts institute</td><td>142</td></tr><tr><td>spectrum disorder</td><td>141</td></tr><tr><td>ma usa</td><td>141</td></tr><tr><td>studies have</td><td>141</td></tr><tr><td>the amygdala</td><td>141</td></tr><tr><td>or not</td><td>140</td></tr><tr><td>pedestrian detection</td><td>140</td></tr><tr><td>of chinese</td><td>139</td></tr><tr><td>the chinese</td><td>139</td></tr><tr><td>ny usa</td><td>138</td></tr><tr><td>the performance</td><td>138</td></tr><tr><td>of medicine</td><td>138</td></tr><tr><td>intelligent systems</td><td>137</td></tr><tr><td>commons attribution</td><td>137</td></tr><tr><td>technology and</td><td>136</td></tr><tr><td>of pattern</td><td>136</td></tr><tr><td>to learn</td><td>135</td></tr><tr><td>stanford university</td><td>135</td></tr><tr><td>images and</td><td>134</td></tr><tr><td>of china</td><td>133</td></tr><tr><td>and applications</td><td>133</td></tr><tr><td>signi cant</td><td>133</td></tr><tr><td>for research</td><td>133</td></tr><tr><td>conference paper</td><td>133</td></tr><tr><td>the problem</td><td>132</td></tr><tr><td>to make</td><td>132</td></tr><tr><td>framework for</td><td>132</td></tr><tr><td>chinese university</td><td>132</td></tr><tr><td>national laboratory</td><td>132</td></tr><tr><td>based face</td><td>131</td></tr><tr><td>barcelona spain</td><td>131</td></tr><tr><td>information processing</td><td>131</td></tr><tr><td>research and</td><td>131</td></tr><tr><td>the use</td><td>130</td></tr><tr><td>we show</td><td>130</td></tr><tr><td>deep neural</td><td>130</td></tr><tr><td>learning and</td><td>130</td></tr><tr><td>to face</td><td>130</td></tr><tr><td>semantic segmentation</td><td>129</td></tr><tr><td>www frontiersin</td><td>129</td></tr><tr><td>frontiersin org</td><td>129</td></tr><tr><td>computer applications</td><td>128</td></tr><tr><td>of maryland</td><td>128</td></tr><tr><td>for object</td><td>128</td></tr><tr><td>in our</td><td>128</td></tr><tr><td>as conference</td><td>128</td></tr><tr><td>pa usa</td><td>127</td></tr><tr><td>the results</td><td>127</td></tr><tr><td>of mathematics</td><td>127</td></tr><tr><td>shanghai china</td><td>127</td></tr><tr><td>which are</td><td>126</td></tr><tr><td>over the</td><td>126</td></tr><tr><td>and recognition</td><td>126</td></tr><tr><td>at iclr</td><td>126</td></tr><tr><td>suggest that</td><td>124</td></tr><tr><td>is that</td><td>124</td></tr><tr><td>face image</td><td>124</td></tr><tr><td>for this</td><td>123</td></tr><tr><td>we are</td><td>123</td></tr><tr><td>object tracking</td><td>122</td></tr><tr><td>key words</td><td>122</td></tr><tr><td>eye tracking</td><td>122</td></tr><tr><td>for more</td><td>122</td></tr><tr><td>social cognition</td><td>122</td></tr><tr><td>the eyes</td><td>122</td></tr><tr><td>van gool</td><td>121</td></tr><tr><td>be inserted</td><td>121</td></tr><tr><td>does not</td><td>121</td></tr><tr><td>university china</td><td>121</td></tr><tr><td>face perception</td><td>121</td></tr><tr><td>for video</td><td>120</td></tr><tr><td>the following</td><td>120</td></tr><tr><td>the system</td><td>120</td></tr><tr><td>the creative</td><td>120</td></tr><tr><td>of image</td><td>120</td></tr><tr><td>of interest</td><td>120</td></tr><tr><td>the visual</td><td>120</td></tr><tr><td>models for</td><td>119</td></tr><tr><td>of texas</td><td>119</td></tr><tr><td>the first</td><td>119</td></tr><tr><td>accepted 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and</td><td>113</td></tr><tr><td>of research</td><td>113</td></tr><tr><td>the paper</td><td>112</td></tr><tr><td>in many</td><td>112</td></tr><tr><td>during the</td><td>112</td></tr><tr><td>this version</td><td>112</td></tr><tr><td>and their</td><td>112</td></tr><tr><td>provided the</td><td>111</td></tr><tr><td>for computational</td><td>111</td></tr><tr><td>in terms</td><td>111</td></tr><tr><td>and face</td><td>111</td></tr><tr><td>tokyo japan</td><td>110</td></tr><tr><td>eye gaze</td><td>110</td></tr><tr><td>sciences beijing</td><td>110</td></tr><tr><td>of autism</td><td>109</td></tr><tr><td>ieee transactions</td><td>109</td></tr><tr><td>the recognition</td><td>109</td></tr><tr><td>of data</td><td>109</td></tr><tr><td>de ned</td><td>109</td></tr><tr><td>the department</td><td>109</td></tr><tr><td>human face</td><td>109</td></tr><tr><td>support vector</td><td>109</td></tr><tr><td>college park</td><td>108</td></tr><tr><td>ku leuven</td><td>108</td></tr><tr><td>is used</td><td>108</td></tr><tr><td>engineering department</td><td>108</td></tr><tr><td>computational linguistics</td><td>108</td></tr><tr><td>of intelligent</td><td>108</td></tr><tr><td>teaching and</td><td>108</td></tr><tr><td>recognition based</td><td>108</td></tr><tr><td>an important</td><td>107</td></tr><tr><td>of southern</td><td>107</td></tr><tr><td>to improve</td><td>107</td></tr><tr><td>this study</td><td>107</td></tr><tr><td>of oxford</td><td>107</td></tr><tr><td>question answering</td><td>106</td></tr><tr><td>feature selection</td><td>106</td></tr><tr><td>classi ers</td><td>106</td></tr><tr><td>our method</td><td>106</td></tr><tr><td>article was</td><td>106</td></tr><tr><td>in psychology</td><td>106</td></tr><tr><td>science engineering</td><td>106</td></tr><tr><td>data and</td><td>106</td></tr><tr><td>in particular</td><td>106</td></tr><tr><td>available online</td><td>105</td></tr><tr><td>facial features</td><td>105</td></tr><tr><td>of each</td><td>105</td></tr><tr><td>of london</td><td>105</td></tr><tr><td>wang and</td><td>105</td></tr><tr><td>distribution and</td><td>105</td></tr><tr><td>https doi</td><td>105</td></tr><tr><td>where the</td><td>105</td></tr><tr><td>and video</td><td>104</td></tr><tr><td>whether they</td><td>104</td></tr><tr><td>the social</td><td>104</td></tr><tr><td>component analysis</td><td>104</td></tr><tr><td>accepted date</td><td>104</td></tr><tr><td>about the</td><td>104</td></tr><tr><td>we have</td><td>104</td></tr><tr><td>when the</td><td>104</td></tr><tr><td>the development</td><td>103</td></tr><tr><td>by using</td><td>103</td></tr><tr><td>southern california</td><td>103</td></tr><tr><td>to extract</td><td>103</td></tr><tr><td>indian institute</td><td>103</td></tr><tr><td>issn online</td><td>103</td></tr><tr><td>local binary</td><td>103</td></tr><tr><td>laboratory for</td><td>103</td></tr><tr><td>technical report</td><td>102</td></tr><tr><td>than the</td><td>102</td></tr><tr><td>found 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pluridisciplinaire</td><td>91</td></tr><tr><td>pluridisciplinaire hal</td><td>91</td></tr><tr><td>hal est</td><td>91</td></tr><tr><td>la diffusion</td><td>91</td></tr><tr><td>de documents</td><td>91</td></tr><tr><td>de niveau</td><td>91</td></tr><tr><td>niveau recherche</td><td>91</td></tr><tr><td>recherche publi</td><td>91</td></tr><tr><td>ou non</td><td>91</td></tr><tr><td>recherche fran</td><td>91</td></tr><tr><td>des laboratoires</td><td>91</td></tr><tr><td>ou priv</td><td>91</td></tr><tr><td>and pattern</td><td>91</td></tr><tr><td>and machine</td><td>91</td></tr><tr><td>chapel hill</td><td>91</td></tr><tr><td>fine grained</td><td>90</td></tr><tr><td>uc berkeley</td><td>90</td></tr><tr><td>all the</td><td>90</td></tr><tr><td>training data</td><td>90</td></tr><tr><td>article distributed</td><td>90</td></tr><tr><td>facial feature</td><td>90</td></tr><tr><td>thesis submitted</td><td>90</td></tr><tr><td>within the</td><td>90</td></tr><tr><td>communication 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eye</td><td>88</td></tr><tr><td>detection using</td><td>87</td></tr><tr><td>the second</td><td>87</td></tr><tr><td>unrestricted use</td><td>87</td></tr><tr><td>of different</td><td>87</td></tr><tr><td>the best</td><td>87</td></tr><tr><td>experimental results</td><td>87</td></tr><tr><td>been accepted</td><td>87</td></tr><tr><td>signi cantly</td><td>87</td></tr><tr><td>for all</td><td>87</td></tr><tr><td>of latex</td><td>87</td></tr><tr><td>artificial intelligence</td><td>86</td></tr><tr><td>to identify</td><td>86</td></tr><tr><td>michigan state</td><td>86</td></tr><tr><td>at http</td><td>86</td></tr><tr><td>of toronto</td><td>86</td></tr><tr><td>ef icient</td><td>86</td></tr><tr><td>of their</td><td>86</td></tr><tr><td>of cse</td><td>86</td></tr><tr><td>multi view</td><td>85</td></tr><tr><td>the role</td><td>85</td></tr><tr><td>zhang and</td><td>85</td></tr><tr><td>from video</td><td>85</td></tr><tr><td>queen mary</td><td>85</td></tr><tr><td>automation 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and</td><td>78</td></tr><tr><td>transfer learning</td><td>77</td></tr><tr><td>speci cally</td><td>77</td></tr><tr><td>proposed method</td><td>77</td></tr><tr><td>mary university</td><td>77</td></tr><tr><td>facial action</td><td>77</td></tr><tr><td>engineering science</td><td>77</td></tr><tr><td>in figure</td><td>77</td></tr><tr><td>brain and</td><td>77</td></tr><tr><td>de barcelona</td><td>76</td></tr><tr><td>engineering research</td><td>76</td></tr><tr><td>the effect</td><td>76</td></tr><tr><td>archives ouvertes</td><td>76</td></tr><tr><td>vision group</td><td>76</td></tr><tr><td>partial fulfillment</td><td>76</td></tr><tr><td>from single</td><td>76</td></tr><tr><td>information sciences</td><td>76</td></tr><tr><td>of surrey</td><td>76</td></tr><tr><td>and signal</td><td>76</td></tr><tr><td>of object</td><td>76</td></tr><tr><td>ieee international</td><td>76</td></tr><tr><td>for intelligent</td><td>76</td></tr><tr><td>technological university</td><td>76</td></tr><tr><td>the target</td><td>76</td></tr><tr><td>dimensionality reduction</td><td>76</td></tr><tr><td>received april</td><td>76</td></tr><tr><td>asd and</td><td>76</td></tr><tr><td>improve the</td><td>76</td></tr><tr><td>the brain</td><td>76</td></tr><tr><td>shuicheng yan</td><td>75</td></tr><tr><td>id pages</td><td>75</td></tr><tr><td>for robust</td><td>75</td></tr><tr><td>re identification</td><td>75</td></tr><tr><td>of others</td><td>75</td></tr><tr><td>noname manuscript</td><td>75</td></tr><tr><td>and control</td><td>75</td></tr><tr><td>these results</td><td>75</td></tr><tr><td>but also</td><td>75</td></tr><tr><td>human faces</td><td>75</td></tr><tr><td>the user</td><td>75</td></tr><tr><td>paris france</td><td>75</td></tr><tr><td>authors and</td><td>75</td></tr><tr><td>among the</td><td>74</td></tr><tr><td>the state</td><td>74</td></tr><tr><td>learning based</td><td>74</td></tr><tr><td>york university</td><td>74</td></tr><tr><td>dissertation submitted</td><td>74</td></tr><tr><td>model based</td><td>74</td></tr><tr><td>which the</td><td>74</td></tr><tr><td>issn print</td><td>74</td></tr><tr><td>technische universit</td><td>74</td></tr><tr><td>machine intelligence</td><td>74</td></tr><tr><td>to have</td><td>74</td></tr><tr><td>age estimation</td><td>74</td></tr><tr><td>to whom</td><td>74</td></tr><tr><td>to end</td><td>74</td></tr><tr><td>cation and</td><td>74</td></tr><tr><td>the right</td><td>74</td></tr><tr><td>deep convolutional</td><td>73</td></tr><tr><td>central florida</td><td>73</td></tr><tr><td>the images</td><td>73</td></tr><tr><td>to address</td><td>73</td></tr><tr><td>more than</td><td>73</td></tr><tr><td>may not</td><td>73</td></tr><tr><td>and pose</td><td>73</td></tr><tr><td>adversarial networks</td><td>73</td></tr><tr><td>dictionary learning</td><td>73</td></tr><tr><td>bernt schiele</td><td>73</td></tr><tr><td>this journal</td><td>73</td></tr><tr><td>to solve</td><td>73</td></tr><tr><td>which can</td><td>73</td></tr><tr><td>to image</td><td>73</td></tr><tr><td>if the</td><td>73</td></tr><tr><td>the effects</td><td>73</td></tr><tr><td>of ece</td><td>73</td></tr><tr><td>california berkeley</td><td>73</td></tr><tr><td>berlin germany</td><td>73</td></tr><tr><td>for semantic</td><td>72</td></tr><tr><td>multi modal</td><td>72</td></tr><tr><td>dataset for</td><td>72</td></tr><tr><td>cornell university</td><td>72</td></tr><tr><td>vision laboratory</td><td>72</td></tr><tr><td>the study</td><td>72</td></tr><tr><td>the mouth</td><td>72</td></tr><tr><td>features are</td><td>72</td></tr><tr><td>the accuracy</td><td>72</td></tr><tr><td>li and</td><td>72</td></tr><tr><td>springer science</td><td>71</td></tr><tr><td>of use</td><td>71</td></tr><tr><td>if you</td><td>71</td></tr><tr><td>the public</td><td>71</td></tr><tr><td>at urbana</td><td>71</td></tr><tr><td>is more</td><td>71</td></tr><tr><td>this problem</td><td>71</td></tr><tr><td>sagepub com</td><td>71</td></tr><tr><td>australian national</td><td>71</td></tr><tr><td>in facial</td><td>71</td></tr><tr><td>peking university</td><td>71</td></tr><tr><td>the context</td><td>71</td></tr><tr><td>principal component</td><td>71</td></tr><tr><td>demonstrate that</td><td>71</td></tr><tr><td>lausanne switzerland</td><td>71</td></tr><tr><td>it can</td><td>71</td></tr><tr><td>of wisconsin</td><td>71</td></tr><tr><td>magnetic resonance</td><td>71</td></tr><tr><td>seoul korea</td><td>71</td></tr><tr><td>science business</td><td>70</td></tr><tr><td>business media</td><td>70</td></tr><tr><td>multi scale</td><td>70</td></tr><tr><td>information systems</td><td>70</td></tr><tr><td>low level</td><td>70</td></tr><tr><td>xiaogang wang</td><td>70</td></tr><tr><td>in contrast</td><td>70</td></tr><tr><td>based methods</td><td>70</td></tr><tr><td>research group</td><td>70</td></tr><tr><td>no august</td><td>70</td></tr><tr><td>to facial</td><td>70</td></tr><tr><td>with high</td><td>70</td></tr><tr><td>in individuals</td><td>70</td></tr><tr><td>super resolution</td><td>70</td></tr><tr><td>received july</td><td>70</td></tr><tr><td>optical flow</td><td>70</td></tr><tr><td>for any</td><td>70</td></tr><tr><td>de cits</td><td>70</td></tr><tr><td>singapore singapore</td><td>70</td></tr><tr><td>for publication</td><td>70</td></tr><tr><td>or other</td><td>69</td></tr><tr><td>we found</td><td>69</td></tr><tr><td>vision lab</td><td>69</td></tr><tr><td>been proposed</td><td>69</td></tr><tr><td>of features</td><td>69</td></tr><tr><td>fran ais</td><td>69</td></tr><tr><td>autism research</td><td>69</td></tr><tr><td>of software</td><td>69</td></tr><tr><td>nanyang technological</td><td>69</td></tr><tr><td>liu and</td><td>69</td></tr><tr><td>gaze direction</td><td>69</td></tr><tr><td>whom correspondence</td><td>69</td></tr><tr><td>adults with</td><td>69</td></tr><tr><td>eye contact</td><td>69</td></tr><tr><td>resonance imaging</td><td>69</td></tr><tr><td>of north</td><td>69</td></tr><tr><td>learning from</td><td>69</td></tr><tr><td>to publication</td><td>68</td></tr><tr><td>single image</td><td>68</td></tr><tr><td>invariant face</td><td>68</td></tr><tr><td>activity recognition</td><td>68</td></tr><tr><td>stefanos zafeiriou</td><td>68</td></tr><tr><td>intelligent information</td><td>68</td></tr><tr><td>specialty section</td><td>68</td></tr><tr><td>or the</td><td>68</td></tr><tr><td>based image</td><td>68</td></tr><tr><td>to their</td><td>68</td></tr><tr><td>in image</td><td>68</td></tr><tr><td>taipei taiwan</td><td>68</td></tr><tr><td>target tracking</td><td>68</td></tr><tr><td>engineering college</td><td>68</td></tr><tr><td>not been</td><td>68</td></tr><tr><td>for computer</td><td>67</td></tr><tr><td>tx usa</td><td>67</td></tr><tr><td>data set</td><td>67</td></tr><tr><td>electronic and</td><td>67</td></tr><tr><td>disorder asd</td><td>67</td></tr><tr><td>facial landmark</td><td>67</td></tr><tr><td>adobe research</td><td>67</td></tr><tr><td>to its</td><td>67</td></tr><tr><td>typically developing</td><td>67</td></tr><tr><td>of pennsylvania</td><td>67</td></tr><tr><td>zurich switzerland</td><td>67</td></tr><tr><td>dr ing</td><td>67</td></tr><tr><td>high resolution</td><td>67</td></tr><tr><td>has not</td><td>67</td></tr><tr><td>maryland college</td><td>66</td></tr><tr><td>publishing corporation</td><td>66</td></tr><tr><td>of training</td><td>66</td></tr><tr><td>accepted june</td><td>66</td></tr><tr><td>of doctor</td><td>66</td></tr><tr><td>of eye</td><td>66</td></tr><tr><td>information from</td><td>66</td></tr><tr><td>automatic face</td><td>66</td></tr><tr><td>ecole polytechnique</td><td>66</td></tr><tr><td>the video</td><td>66</td></tr><tr><td>binary pattern</td><td>66</td></tr><tr><td>model and</td><td>66</td></tr><tr><td>in their</td><td>66</td></tr><tr><td>received may</td><td>66</td></tr><tr><td>been shown</td><td>66</td></tr><tr><td>social interactions</td><td>66</td></tr><tr><td>in revised</td><td>66</td></tr><tr><td>revised form</td><td>66</td></tr><tr><td>montr eal</td><td>65</td></tr><tr><td>algorithm for</td><td>65</td></tr><tr><td>is often</td><td>65</td></tr><tr><td>hindawi publishing</td><td>65</td></tr><tr><td>ground truth</td><td>65</td></tr><tr><td>of cognitive</td><td>65</td></tr><tr><td>shot learning</td><td>65</td></tr><tr><td>for large</td><td>65</td></tr><tr><td>recent years</td><td>65</td></tr><tr><td>double blind</td><td>65</td></tr><tr><td>with respect</td><td>65</td></tr><tr><td>expression and</td><td>65</td></tr><tr><td>have shown</td><td>65</td></tr><tr><td>karlsruhe germany</td><td>65</td></tr><tr><td>on their</td><td>65</td></tr><tr><td>the research</td><td>65</td></tr><tr><td>columbia university</td><td>65</td></tr><tr><td>associate professor</td><td>65</td></tr><tr><td>facial images</td><td>64</td></tr><tr><td>both the</td><td>64</td></tr><tr><td>dif cult</td><td>64</td></tr><tr><td>human action</td><td>64</td></tr><tr><td>technology cas</td><td>64</td></tr><tr><td>video surveillance</td><td>64</td></tr><tr><td>received december</td><td>64</td></tr><tr><td>the world</td><td>64</td></tr><tr><td>national taiwan</td><td>64</td></tr><tr><td>recognition under</td><td>64</td></tr><tr><td>intelligence and</td><td>64</td></tr><tr><td>video based</td><td>64</td></tr><tr><td>multi target</td><td>64</td></tr><tr><td>and applied</td><td>64</td></tr><tr><td>detection with</td><td>63</td></tr><tr><td>autism and</td><td>63</td></tr><tr><td>this document</td><td>63</td></tr><tr><td>believe that</td><td>63</td></tr><tr><td>human detection</td><td>63</td></tr><tr><td>and more</td><td>63</td></tr><tr><td>university shanghai</td><td>63</td></tr><tr><td>personal use</td><td>63</td></tr><tr><td>wa usa</td><td>63</td></tr><tr><td>cation using</td><td>63</td></tr><tr><td>and intelligent</td><td>63</td></tr><tr><td>ne grained</td><td>63</td></tr><tr><td>on pattern</td><td>63</td></tr><tr><td>applied sciences</td><td>63</td></tr><tr><td>while the</td><td>63</td></tr><tr><td>idiap research</td><td>63</td></tr><tr><td>extracted from</td><td>63</td></tr><tr><td>cation with</td><td>63</td></tr><tr><td>the dataset</td><td>63</td></tr><tr><td>received march</td><td>63</td></tr><tr><td>received june</td><td>62</td></tr><tr><td>multi object</td><td>62</td></tr><tr><td>de montr</td><td>62</td></tr><tr><td>of experimental</td><td>62</td></tr><tr><td>of multiple</td><td>62</td></tr><tr><td>sciences university</td><td>62</td></tr><tr><td>nearest neighbor</td><td>62</td></tr><tr><td>engineering national</td><td>62</td></tr><tr><td>taiwan university</td><td>62</td></tr><tr><td>the goal</td><td>62</td></tr><tr><td>we used</td><td>62</td></tr><tr><td>representations for</td><td>62</td></tr><tr><td>based approach</td><td>62</td></tr><tr><td>data driven</td><td>62</td></tr><tr><td>the computer</td><td>62</td></tr><tr><td>to reduce</td><td>62</td></tr><tr><td>vector machine</td><td>62</td></tr><tr><td>feature based</td><td>62</td></tr><tr><td>june accepted</td><td>61</td></tr><tr><td>at www</td><td>61</td></tr><tr><td>computer graphics</td><td>61</td></tr><tr><td>of tokyo</td><td>61</td></tr><tr><td>international joint</td><td>61</td></tr><tr><td>objects and</td><td>61</td></tr><tr><td>images for</td><td>61</td></tr><tr><td>large number</td><td>61</td></tr><tr><td>shiguang shan</td><td>61</td></tr><tr><td>shaogang gong</td><td>61</td></tr><tr><td>received october</td><td>61</td></tr><tr><td>an object</td><td>61</td></tr><tr><td>this thesis</td><td>61</td></tr><tr><td>are more</td><td>61</td></tr><tr><td>communication and</td><td>61</td></tr><tr><td>with deep</td><td>61</td></tr><tr><td>recognition has</td><td>61</td></tr><tr><td>the appearance</td><td>61</td></tr><tr><td>accepted march</td><td>61</td></tr><tr><td>of two</td><td>61</td></tr><tr><td>and emotion</td><td>61</td></tr><tr><td>human robot</td><td>61</td></tr><tr><td>as follows</td><td>61</td></tr><tr><td>california institute</td><td>61</td></tr><tr><td>of computational</td><td>61</td></tr><tr><td>that they</td><td>60</td></tr><tr><td>peer reviewed</td><td>60</td></tr><tr><td>words and</td><td>60</td></tr><tr><td>the shape</td><td>60</td></tr><tr><td>in each</td><td>60</td></tr><tr><td>th international</td><td>60</td></tr><tr><td>is still</td><td>60</td></tr><tr><td>using deep</td><td>60</td></tr><tr><td>and electrical</td><td>60</td></tr><tr><td>emotional facial</td><td>60</td></tr><tr><td>of its</td><td>60</td></tr><tr><td>showed that</td><td>60</td></tr><tr><td>ann arbor</td><td>60</td></tr><tr><td>these methods</td><td>60</td></tr><tr><td>are used</td><td>60</td></tr><tr><td>stony brook</td><td>60</td></tr><tr><td>supplementary material</td><td>60</td></tr><tr><td>illumination and</td><td>60</td></tr><tr><td>received january</td><td>60</td></tr><tr><td>such that</td><td>60</td></tr><tr><td>linear discriminant</td><td>60</td></tr><tr><td>subspace clustering</td><td>59</td></tr><tr><td>to determine</td><td>59</td></tr><tr><td>il usa</td><td>59</td></tr><tr><td>published october</td><td>59</td></tr><tr><td>entific research</td><td>59</td></tr><tr><td>manant des</td><td>59</td></tr><tr><td>des tablissements</td><td>59</td></tr><tr><td>tablissements enseignement</td><td>59</td></tr><tr><td>ou trangers</td><td>59</td></tr><tr><td>trangers des</td><td>59</td></tr><tr><td>material for</td><td>59</td></tr><tr><td>joint conference</td><td>59</td></tr><tr><td>wide range</td><td>59</td></tr><tr><td>nanjing china</td><td>59</td></tr><tr><td>normal university</td><td>59</td></tr><tr><td>for learning</td><td>59</td></tr><tr><td>for real</td><td>59</td></tr><tr><td>visual information</td><td>59</td></tr><tr><td>that our</td><td>59</td></tr></table></body></html>
\ No newline at end of file diff --git a/scraper/reports/pdf_unknown_terms.html b/scraper/reports/pdf_unknown_terms.html index ff2c563e..d19c2bb0 100644 --- a/scraper/reports/pdf_unknown_terms.html +++ b/scraper/reports/pdf_unknown_terms.html @@ -1 +1 @@ -<!doctype html><html><head><meta charset='utf-8'><title>PDF Report: Unknown Terms</title><link rel='stylesheet' href='reports.css'></head><body><h2>PDF Report: Unknown Terms</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>the</td><td>9970</td></tr><tr><td>and</td><td>8790</td></tr><tr><td>for</td><td>3944</td></tr><tr><td>university</td><td>3631</td></tr><tr><td>face</td><td>2589</td></tr><tr><td>recognition</td><td>2357</td></tr><tr><td>computer</td><td>1860</td></tr><tr><td>facial</td><td>1740</td></tr><tr><td>science</td><td>1495</td></tr><tr><td>with</td><td>1467</td></tr><tr><td>department</td><td>1445</td></tr><tr><td>this</td><td>1375</td></tr><tr><td>engineering</td><td>1348</td></tr><tr><td>that</td><td>1228</td></tr><tr><td>from</td><td>1201</td></tr><tr><td>research</td><td>1193</td></tr><tr><td>are</td><td>1157</td></tr><tr><td>technology</td><td>1085</td></tr><tr><td>based</td><td>1016</td></tr><tr><td>image</td><td>964</td></tr><tr><td>using</td><td>958</td></tr><tr><td>information</td><td>915</td></tr><tr><td>learning</td><td>906</td></tr><tr><td>ieee</td><td>901</td></tr><tr><td>institute</td><td>883</td></tr><tr><td>expression</td><td>772</td></tr><tr><td>images</td><td>699</td></tr><tr><td>china</td><td>660</td></tr><tr><td>video</td><td>645</td></tr><tr><td>human</td><td>643</td></tr><tr><td>analysis</td><td>598</td></tr><tr><td>usa</td><td>592</td></tr><tr><td>feature</td><td>577</td></tr><tr><td>data</td><td>560</td></tr><tr><td>which</td><td>558</td></tr><tr><td>member</td><td>544</td></tr><tr><td>detection</td><td>539</td></tr><tr><td>school</td><td>520</td></tr><tr><td>can</td><td>519</td></tr><tr><td>features</td><td>513</td></tr><tr><td>journal</td><td>509</td></tr><tr><td>has</td><td>475</td></tr><tr><td>vision</td><td>473</td></tr><tr><td>model</td><td>466</td></tr><tr><td>cation</td><td>456</td></tr><tr><td>have</td><td>455</td></tr><tr><td>system</td><td>447</td></tr><tr><td>such</td><td>444</td></tr><tr><td>deep</td><td>437</td></tr><tr><td>systems</td><td>436</td></tr><tr><td>college</td><td>421</td></tr><tr><td>electrical</td><td>416</td></tr><tr><td>expressions</td><td>413</td></tr><tr><td>our</td><td>406</td></tr><tr><td>http</td><td>404</td></tr><tr><td>action</td><td>394</td></tr><tr><td>visual</td><td>389</td></tr><tr><td>these</td><td>389</td></tr><tr><td>faces</td><td>385</td></tr><tr><td>not</td><td>381</td></tr><tr><td>been</td><td>380</td></tr><tr><td>international</td><td>374</td></tr><tr><td>article</td><td>372</td></tr><tr><td>doi</td><td>369</td></tr><tr><td>sciences</td><td>361</td></tr><tr><td>processing</td><td>357</td></tr><tr><td>www</td><td>352</td></tr><tr><td>method</td><td>352</td></tr><tr><td>may</td><td>349</td></tr><tr><td>paper</td><td>348</td></tr><tr><td>center</td><td>342</td></tr><tr><td>one</td><td>341</td></tr><tr><td>wang</td><td>339</td></tr><tr><td>more</td><td>331</td></tr><tr><td>methods</td><td>329</td></tr><tr><td>emotion</td><td>329</td></tr><tr><td>applications</td><td>328</td></tr><tr><td>used</td><td>327</td></tr><tr><td>india</td><td>325</td></tr><tr><td>work</td><td>323</td></tr><tr><td>accepted</td><td>322</td></tr><tr><td>zhang</td><td>320</td></tr><tr><td>neural</td><td>319</td></tr><tr><td>local</td><td>315</td></tr><tr><td>computing</td><td>314</td></tr><tr><td>pose</td><td>314</td></tr><tr><td>classi</td><td>312</td></tr><tr><td>social</td><td>309</td></tr><tr><td>published</td><td>308</td></tr><tr><td>use</td><td>303</td></tr><tr><td>object</td><td>302</td></tr><tr><td>new</td><td>299</td></tr><tr><td>national</td><td>297</td></tr><tr><td>two</td><td>293</td></tr><tr><td>networks</td><td>292</td></tr><tr><td>received</td><td>292</td></tr><tr><td>state</td><td>291</td></tr><tr><td>each</td><td>290</td></tr><tr><td>different</td><td>290</td></tr><tr><td>representation</td><td>289</td></tr><tr><td>problem</td><td>288</td></tr><tr><td>other</td><td>283</td></tr><tr><td>approach</td><td>279</td></tr><tr><td>under</td><td>278</td></tr><tr><td>machine</td><td>278</td></tr><tr><td>laboratory</td><td>277</td></tr><tr><td>pattern</td><td>273</td></tr><tr><td>high</td><td>272</td></tr><tr><td>illumination</td><td>271</td></tr><tr><td>beijing</td><td>270</td></tr><tr><td>time</td><td>268</td></tr><tr><td>chen</td><td>268</td></tr><tr><td>performance</td><td>253</td></tr><tr><td>multi</td><td>251</td></tr><tr><td>all</td><td>251</td></tr><tr><td>training</td><td>250</td></tr><tr><td>robust</td><td>250</td></tr><tr><td>liu</td><td>248</td></tr><tr><td>org</td><td>246</td></tr><tr><td>california</td><td>245</td></tr><tr><td>videos</td><td>245</td></tr><tr><td>models</td><td>244</td></tr><tr><td>results</td><td>243</td></tr><tr><td>real</td><td>242</td></tr><tr><td>low</td><td>239</td></tr><tr><td>yang</td><td>234</td></tr><tr><td>issn</td><td>233</td></tr><tr><td>set</td><td>231</td></tr><tr><td>introduction</td><td>230</td></tr><tr><td>email</td><td>230</td></tr><tr><td>large</td><td>230</td></tr><tr><td>online</td><td>229</td></tr><tr><td>person</td><td>229</td></tr><tr><td>network</td><td>228</td></tr><tr><td>automatic</td><td>228</td></tr><tr><td>proposed</td><td>228</td></tr><tr><td>access</td><td>227</td></tr><tr><td>dataset</td><td>227</td></tr><tr><td>their</td><td>225</td></tr><tr><td>age</td><td>225</td></tr><tr><td>estimation</td><td>224</td></tr><tr><td>lab</td><td>221</td></tr><tr><td>algorithm</td><td>220</td></tr><tr><td>vol</td><td>219</td></tr><tr><td>open</td><td>218</td></tr><tr><td>also</td><td>211</td></tr><tr><td>group</td><td>210</td></tr><tr><td>between</td><td>210</td></tr><tr><td>dept</td><td>208</td></tr><tr><td>most</td><td>207</td></tr><tr><td>was</td><td>205</td></tr><tr><td>mail</td><td>205</td></tr><tr><td>submitted</td><td>204</td></tr><tr><td>when</td><td>203</td></tr><tr><td>its</td><td>203</td></tr><tr><td>number</td><td>201</td></tr><tr><td>will</td><td>199</td></tr><tr><td>shape</td><td>199</td></tr><tr><td>part</td><td>198</td></tr><tr><td>key</td><td>197</td></tr><tr><td>many</td><td>197</td></tr><tr><td>intelligence</td><td>196</td></tr><tr><td>matrix</td><td>195</td></tr><tr><td>however</td><td>195</td></tr><tr><td>faculty</td><td>195</td></tr><tr><td>author</td><td>193</td></tr><tr><td>com</td><td>192</td></tr><tr><td>database</td><td>189</td></tr><tr><td>into</td><td>188</td></tr><tr><td>temporal</td><td>188</td></tr><tr><td>available</td><td>187</td></tr><tr><td>where</td><td>187</td></tr><tr><td>volume</td><td>185</td></tr><tr><td>via</td><td>185</td></tr><tr><td>sparse</td><td>185</td></tr><tr><td>conference</td><td>184</td></tr><tr><td>universit</td><td>182</td></tr><tr><td>people</td><td>182</td></tr><tr><td>issue</td><td>181</td></tr><tr><td>london</td><td>181</td></tr><tr><td>non</td><td>179</td></tr><tr><td>linear</td><td>179</td></tr><tr><td>chinese</td><td>179</td></tr><tr><td>appearance</td><td>178</td></tr><tr><td>hong</td><td>175</td></tr><tr><td>intelligent</td><td>174</td></tr><tr><td>france</td><td>174</td></tr><tr><td>algorithms</td><td>173</td></tr><tr><td>task</td><td>173</td></tr><tr><td>but</td><td>171</td></tr><tr><td>supervised</td><td>169</td></tr><tr><td>interaction</td><td>169</td></tr><tr><td>classification</td><td>168</td></tr><tr><td>they</td><td>167</td></tr><tr><td>techniques</td><td>167</td></tr><tr><td>professor</td><td>166</td></tr><tr><td>emotional</td><td>166</td></tr><tr><td>motion</td><td>166</td></tr><tr><td>scale</td><td>166</td></tr><tr><td>clustering</td><td>165</td></tr><tr><td>student</td><td>165</td></tr><tr><td>some</td><td>165</td></tr><tr><td>class</td><td>165</td></tr><tr><td>space</td><td>165</td></tr><tr><td>carnegie</td><td>164</td></tr><tr><td>mellon</td><td>164</td></tr><tr><td>version</td><td>164</td></tr><tr><td>degree</td><td>162</td></tr><tr><td>than</td><td>161</td></tr><tr><td>level</td><td>161</td></tr><tr><td>study</td><td>160</td></tr><tr><td>how</td><td>159</td></tr><tr><td>any</td><td>158</td></tr><tr><td>there</td><td>158</td></tr><tr><td>tracking</td><td>157</td></tr><tr><td>germany</td><td>157</td></tr><tr><td>subspace</td><td>154</td></tr><tr><td>informatics</td><td>154</td></tr><tr><td>figure</td><td>152</td></tr><tr><td>copyright</td><td>152</td></tr><tr><td>only</td><td>150</td></tr><tr><td>extraction</td><td>150</td></tr><tr><td>vector</td><td>147</td></tr><tr><td>emotions</td><td>147</td></tr><tr><td>well</td><td>147</td></tr><tr><td>then</td><td>146</td></tr><tr><td>senior</td><td>145</td></tr><tr><td>date</td><td>145</td></tr><tr><td>academy</td><td>145</td></tr><tr><td>advanced</td><td>144</td></tr><tr><td>japan</td><td>144</td></tr><tr><td>correspondence</td><td>144</td></tr><tr><td>psychology</td><td>143</td></tr><tr><td>were</td><td>143</td></tr><tr><td>attribute</td><td>142</td></tr><tr><td>june</td><td>142</td></tr><tr><td>both</td><td>141</td></tr><tr><td>over</td><td>141</td></tr><tr><td>given</td><td>141</td></tr><tr><td>while</td><td>141</td></tr><tr><td>convolutional</td><td>140</td></tr><tr><td>huang</td><td>140</td></tr><tr><td>same</td><td>139</td></tr><tr><td>multiple</td><td>139</td></tr><tr><td>identity</td><td>139</td></tr><tr><td>alignment</td><td>138</td></tr><tr><td>kong</td><td>138</td></tr><tr><td>accuracy</td><td>137</td></tr><tr><td>pittsburgh</td><td>136</td></tr><tr><td>recent</td><td>136</td></tr><tr><td>thesis</td><td>136</td></tr><tr><td>biometric</td><td>135</td></tr><tr><td>framework</td><td>135</td></tr><tr><td>approaches</td><td>134</td></tr><tr><td>partial</td><td>134</td></tr><tr><td>objects</td><td>134</td></tr><tr><td>electronics</td><td>134</td></tr><tr><td>regression</td><td>134</td></tr><tr><td>requirements</td><td>134</td></tr><tr><td>signal</td><td>134</td></tr><tr><td>security</td><td>133</td></tr><tr><td>applied</td><td>133</td></tr><tr><td>single</td><td>132</td></tr><tr><td>dynamic</td><td>132</td></tr><tr><td>resolution</td><td>132</td></tr><tr><td>content</td><td>131</td></tr><tr><td>novel</td><td>131</td></tr><tr><td>publication</td><td>131</td></tr><tr><td>fellow</td><td>131</td></tr><tr><td>tel</td><td>131</td></tr><tr><td>important</td><td>131</td></tr><tr><td>section</td><td>131</td></tr><tr><td>communication</td><td>130</td></tr><tr><td>prof</td><td>128</td></tr><tr><td>datasets</td><td>128</td></tr><tr><td>keywords</td><td>127</td></tr><tr><td>hal</td><td>126</td></tr><tr><td>attributes</td><td>126</td></tr><tr><td>computational</td><td>125</td></tr><tr><td>edu</td><td>124</td></tr><tr><td>matching</td><td>124</td></tr><tr><td>understanding</td><td>124</td></tr><tr><td>dimensional</td><td>124</td></tr><tr><td>august</td><td>122</td></tr><tr><td>park</td><td>122</td></tr><tr><td>like</td><td>122</td></tr><tr><td>activity</td><td>122</td></tr><tr><td>singapore</td><td>121</td></tr><tr><td>review</td><td>120</td></tr><tr><td>about</td><td>119</td></tr><tr><td>should</td><td>119</td></tr><tr><td>technical</td><td>118</td></tr><tr><td>localization</td><td>118</td></tr><tr><td>view</td><td>118</td></tr><tr><td>application</td><td>118</td></tr><tr><td>robotics</td><td>116</td></tr><tr><td>through</td><td>116</td></tr><tr><td>first</td><td>115</td></tr><tr><td>david</td><td>115</td></tr><tr><td>september</td><td>115</td></tr><tr><td>example</td><td>114</td></tr><tr><td>des</td><td>114</td></tr><tr><td>eye</td><td>114</td></tr><tr><td>domain</td><td>114</td></tr><tr><td>texture</td><td>113</td></tr><tr><td>perception</td><td>113</td></tr><tr><td>identi</td><td>113</td></tr><tr><td>april</td><td>113</td></tr><tr><td>active</td><td>112</td></tr><tr><td>order</td><td>112</td></tr><tr><td>original</td><td>112</td></tr><tr><td>problems</td><td>112</td></tr><tr><td>natural</td><td>112</td></tr><tr><td>show</td><td>111</td></tr><tr><td>general</td><td>111</td></tr><tr><td>head</td><td>111</td></tr><tr><td>discriminant</td><td>111</td></tr><tr><td>you</td><td>111</td></tr><tr><td>wei</td><td>111</td></tr><tr><td>scene</td><td>111</td></tr><tr><td>conditions</td><td>111</td></tr><tr><td>still</td><td>111</td></tr><tr><td>ing</td><td>111</td></tr><tr><td>very</td><td>111</td></tr><tr><td>input</td><td>110</td></tr><tr><td>december</td><td>110</td></tr><tr><td>user</td><td>110</td></tr><tr><td>wild</td><td>110</td></tr><tr><td>veri</td><td>109</td></tr><tr><td>july</td><td>109</td></tr><tr><td>studies</td><td>109</td></tr><tr><td>selection</td><td>108</td></tr><tr><td>media</td><td>108</td></tr><tr><td>gender</td><td>107</td></tr><tr><td>because</td><td>107</td></tr><tr><td>points</td><td>107</td></tr><tr><td>variations</td><td>107</td></tr><tr><td>march</td><td>107</td></tr><tr><td>due</td><td>107</td></tr><tr><td>several</td><td>107</td></tr><tr><td>propose</td><td>106</td></tr><tr><td>shown</td><td>106</td></tr><tr><td>lin</td><td>106</td></tr><tr><td>present</td><td>106</td></tr><tr><td>distribution</td><td>106</td></tr><tr><td>brain</td><td>106</td></tr><tr><td>inc</td><td>105</td></tr><tr><td>modeling</td><td>105</td></tr><tr><td>works</td><td>105</td></tr><tr><td>https</td><td>104</td></tr><tr><td>component</td><td>104</td></tr><tr><td>sun</td><td>104</td></tr><tr><td>united</td><td>104</td></tr><tr><td>world</td><td>103</td></tr><tr><td>biometrics</td><td>103</td></tr><tr><td>dissertation</td><td>103</td></tr><tr><td>art</td><td>102</td></tr><tr><td>invariant</td><td>102</td></tr><tr><td>yan</td><td>102</td></tr><tr><td>electronic</td><td>102</td></tr><tr><td>search</td><td>101</td></tr><tr><td>report</td><td>101</td></tr><tr><td>canada</td><td>101</td></tr><tr><td>netherlands</td><td>101</td></tr><tr><td>korea</td><td>101</td></tr><tr><td>cross</td><td>100</td></tr><tr><td>january</td><td>100</td></tr><tr><td>centre</td><td>100</td></tr><tr><td>including</td><td>100</td></tr><tr><td>representations</td><td>100</td></tr><tr><td>technologies</td><td>100</td></tr><tr><td>optimization</td><td>99</td></tr><tr><td>zhao</td><td>99</td></tr><tr><td>unsupervised</td><td>99</td></tr><tr><td>unconstrained</td><td>99</td></tr><tr><td>rank</td><td>99</td></tr><tr><td>italy</td><td>98</td></tr><tr><td>spain</td><td>98</td></tr><tr><td>dictionary</td><td>98</td></tr><tr><td>cognitive</td><td>98</td></tr><tr><td>editor</td><td>97</td></tr><tr><td>landmark</td><td>97</td></tr><tr><td>joint</td><td>97</td></tr><tr><td>multimedia</td><td>97</td></tr><tr><td>process</td><td>97</td></tr><tr><td>context</td><td>97</td></tr><tr><td>authors</td><td>97</td></tr><tr><td>philosophy</td><td>97</td></tr><tr><td>surveillance</td><td>96</td></tr><tr><td>tech</td><td>96</td></tr><tr><td>during</td><td>96</td></tr><tr><td>see</td><td>96</td></tr><tr><td>corresponding</td><td>95</td></tr><tr><td>der</td><td>95</td></tr><tr><td>control</td><td>95</td></tr><tr><td>proceedings</td><td>95</td></tr><tr><td>binary</td><td>95</td></tr><tr><td>affective</td><td>95</td></tr><tr><td>automation</td><td>94</td></tr><tr><td>speci</td><td>94</td></tr><tr><td>rights</td><td>94</td></tr><tr><td>label</td><td>94</td></tr><tr><td>michael</td><td>94</td></tr><tr><td>doctor</td><td>94</td></tr><tr><td>prediction</td><td>93</td></tr><tr><td>related</td><td>93</td></tr><tr><td>three</td><td>93</td></tr><tr><td>cnn</td><td>93</td></tr><tr><td>color</td><td>93</td></tr><tr><td>cas</td><td>93</td></tr><tr><td>form</td><td>93</td></tr><tr><td>revised</td><td>93</td></tr><tr><td>zhou</td><td>92</td></tr><tr><td>sample</td><td>92</td></tr><tr><td>terms</td><td>92</td></tr><tr><td>mathematics</td><td>91</td></tr><tr><td>various</td><td>91</td></tr><tr><td>provided</td><td>90</td></tr><tr><td>lighting</td><td>90</td></tr><tr><td>graduate</td><td>90</td></tr><tr><td>attention</td><td>90</td></tr><tr><td>cambridge</td><td>90</td></tr><tr><td>berkeley</td><td>89</td></tr><tr><td>language</td><td>89</td></tr><tr><td>even</td><td>89</td></tr><tr><td>cial</td><td>89</td></tr><tr><td>february</td><td>89</td></tr><tr><td>distance</td><td>89</td></tr><tr><td>rst</td><td>89</td></tr><tr><td>behavior</td><td>89</td></tr><tr><td>hand</td><td>89</td></tr><tr><td>kim</td><td>89</td></tr><tr><td>switzerland</td><td>88</td></tr><tr><td>project</td><td>88</td></tr><tr><td>role</td><td>88</td></tr><tr><td>australia</td><td>88</td></tr><tr><td>manuscript</td><td>88</td></tr><tr><td>graph</td><td>88</td></tr><tr><td>taiwan</td><td>88</td></tr><tr><td>november</td><td>87</td></tr><tr><td>san</td><td>87</td></tr><tr><td>zhu</td><td>87</td></tr><tr><td>evaluation</td><td>87</td></tr><tr><td>lee</td><td>87</td></tr><tr><td>changes</td><td>87</td></tr><tr><td>ali</td><td>87</td></tr><tr><td>kernel</td><td>87</td></tr><tr><td>automated</td><td>87</td></tr><tr><td>october</td><td>87</td></tr><tr><td>imaging</td><td>86</td></tr><tr><td>actions</td><td>86</td></tr><tr><td>current</td><td>86</td></tr><tr><td>discriminative</td><td>86</td></tr><tr><td>retrieval</td><td>86</td></tr><tr><td>make</td><td>85</td></tr><tr><td>tion</td><td>85</td></tr><tr><td>please</td><td>85</td></tr><tr><td>public</td><td>85</td></tr><tr><td>material</td><td>85</td></tr><tr><td>reconstruction</td><td>85</td></tr><tr><td>occlusion</td><td>85</td></tr><tr><td>those</td><td>85</td></tr><tr><td>experimental</td><td>85</td></tr><tr><td>presented</td><td>85</td></tr><tr><td>design</td><td>85</td></tr><tr><td>function</td><td>85</td></tr><tr><td>without</td><td>84</td></tr><tr><td>made</td><td>84</td></tr><tr><td>provide</td><td>84</td></tr><tr><td>barcelona</td><td>84</td></tr><tr><td>box</td><td>84</td></tr><tr><td>personal</td><td>83</td></tr><tr><td>structure</td><td>83</td></tr><tr><td>pca</td><td>83</td></tr><tr><td>what</td><td>83</td></tr><tr><td>them</td><td>83</td></tr><tr><td>frame</td><td>83</td></tr><tr><td>citation</td><td>82</td></tr><tr><td>development</td><td>82</td></tr><tr><td>univ</td><td>82</td></tr><tr><td>digital</td><td>81</td></tr><tr><td>van</td><td>81</td></tr><tr><td>fast</td><td>80</td></tr><tr><td>known</td><td>80</td></tr><tr><td>main</td><td>80</td></tr><tr><td>humans</td><td>80</td></tr><tr><td>software</td><td>79</td></tr><tr><td>maryland</td><td>79</td></tr><tr><td>thomas</td><td>79</td></tr><tr><td>transactions</td><td>79</td></tr><tr><td>coding</td><td>79</td></tr><tr><td>test</td><td>79</td></tr><tr><td>survey</td><td>78</td></tr><tr><td>obtained</td><td>78</td></tr><tr><td>massachusetts</td><td>78</td></tr><tr><td>similarity</td><td>78</td></tr><tr><td>towards</td><td>78</td></tr><tr><td>arti</td><td>78</td></tr><tr><td>semantic</td><td>78</td></tr><tr><td>embedding</td><td>78</td></tr><tr><td>subject</td><td>78</td></tr><tr><td>amsterdam</td><td>78</td></tr><tr><td>ful</td><td>78</td></tr><tr><td>gabor</td><td>77</td></tr><tr><td>event</td><td>77</td></tr><tr><td>robot</td><td>77</td></tr><tr><td>google</td><td>76</td></tr><tr><td>components</td><td>76</td></tr><tr><td>camera</td><td>76</td></tr><tr><td>rate</td><td>76</td></tr><tr><td>patterns</td><td>76</td></tr><tr><td>years</td><td>76</td></tr><tr><td>interactions</td><td>76</td></tr><tr><td>whether</td><td>75</td></tr><tr><td>further</td><td>75</td></tr><tr><td>web</td><td>75</td></tr><tr><td>global</td><td>75</td></tr><tr><td>york</td><td>75</td></tr><tr><td>learn</td><td>75</td></tr><tr><td>region</td><td>75</td></tr><tr><td>fusion</td><td>75</td></tr><tr><td>recognizing</td><td>74</td></tr><tr><td>way</td><td>73</td></tr><tr><td>descriptors</td><td>73</td></tr><tr><td>identification</td><td>73</td></tr><tr><td>documents</td><td>73</td></tr><tr><td>tokyo</td><td>73</td></tr><tr><td>oxford</td><td>73</td></tr><tr><td>often</td><td>73</td></tr><tr><td>parts</td><td>73</td></tr><tr><td>static</td><td>72</td></tr><tr><td>dimensionality</td><td>72</td></tr><tr><td>areas</td><td>72</td></tr><tr><td>support</td><td>71</td></tr><tr><td>medical</td><td>71</td></tr><tr><td>learned</td><td>71</td></tr><tr><td>commons</td><td>71</td></tr><tr><td>compared</td><td>71</td></tr><tr><td>central</td><td>71</td></tr><tr><td>end</td><td>71</td></tr><tr><td>samples</td><td>71</td></tr><tr><td>kingdom</td><td>71</td></tr><tr><td>result</td><td>70</td></tr><tr><td>point</td><td>70</td></tr><tr><td>out</td><td>70</td></tr><tr><td>similar</td><td>70</td></tr><tr><td>metric</td><td>70</td></tr><tr><td>manifold</td><td>70</td></tr><tr><td>address</td><td>69</td></tr><tr><td>found</td><td>69</td></tr><tr><td>challenging</td><td>69</td></tr><tr><td>shanghai</td><td>69</td></tr><tr><td>peter</td><td>69</td></tr><tr><td>tasks</td><td>69</td></tr><tr><td>since</td><td>69</td></tr><tr><td>across</td><td>69</td></tr><tr><td>basis</td><td>69</td></tr><tr><td>databases</td><td>69</td></tr><tr><td>per</td><td>68</td></tr><tr><td>gao</td><td>68</td></tr><tr><td>kumar</td><td>68</td></tr><tr><td>technique</td><td>68</td></tr><tr><td>higher</td><td>68</td></tr><tr><td>improve</td><td>68</td></tr><tr><td>jda</td><td>68</td></tr><tr><td>landmarks</td><td>68</td></tr><tr><td>better</td><td>67</td></tr><tr><td>cient</td><td>67</td></tr><tr><td>fig</td><td>67</td></tr><tr><td>thessaloniki</td><td>67</td></tr><tr><td>dong</td><td>67</td></tr><tr><td>final</td><td>67</td></tr><tr><td>unit</td><td>67</td></tr><tr><td>peng</td><td>67</td></tr><tr><td>limited</td><td>67</td></tr><tr><td>creative</td><td>67</td></tr><tr><td>independent</td><td>67</td></tr><tr><td>recognize</td><td>67</td></tr><tr><td>objective</td><td>67</td></tr><tr><td>could</td><td>67</td></tr><tr><td>shan</td><td>67</td></tr><tr><td>long</td><td>67</td></tr><tr><td>self</td><td>66</td></tr><tr><td>must</td><td>66</td></tr><tr><td>challenge</td><td>66</td></tr><tr><td>best</td><td>66</td></tr><tr><td>experiments</td><td>66</td></tr><tr><td>knowledge</td><td>66</td></tr><tr><td>speech</td><td>66</td></tr><tr><td>quality</td><td>66</td></tr><tr><td>potential</td><td>66</td></tr><tr><td>svm</td><td>66</td></tr><tr><td>segmentation</td><td>66</td></tr><tr><td>llment</td><td>66</td></tr><tr><td>future</td><td>66</td></tr><tr><td>mobile</td><td>65</td></tr><tr><td>diego</td><td>65</td></tr><tr><td>additional</td><td>65</td></tr><tr><td>cheng</td><td>65</td></tr><tr><td>interest</td><td>65</td></tr><tr><td>addressed</td><td>65</td></tr><tr><td>disgust</td><td>65</td></tr><tr><td>states</td><td>65</td></tr><tr><td>statistics</td><td>65</td></tr><tr><td>jun</td><td>65</td></tr><tr><td>participants</td><td>64</td></tr><tr><td>spatial</td><td>64</td></tr><tr><td>assistant</td><td>64</td></tr><tr><td>contact</td><td>64</td></tr><tr><td>labeling</td><td>64</td></tr><tr><td>andrew</td><td>64</td></tr><tr><td>iran</td><td>64</td></tr><tr><td>gaze</td><td>64</td></tr><tr><td>con</td><td>64</td></tr><tr><td>neutral</td><td>64</td></tr><tr><td>small</td><td>64</td></tr><tr><td>signi</td><td>64</td></tr><tr><td>differences</td><td>64</td></tr><tr><td>full</td><td>63</td></tr><tr><td>regions</td><td>63</td></tr><tr><td>thus</td><td>63</td></tr><tr><td>possible</td><td>63</td></tr><tr><td>improved</td><td>63</td></tr><tr><td>etc</td><td>63</td></tr><tr><td>therefore</td><td>63</td></tr><tr><td>within</td><td>63</td></tr><tr><td>cost</td><td>63</td></tr><tr><td>feng</td><td>62</td></tr><tr><td>distributed</td><td>62</td></tr><tr><td>michigan</td><td>62</td></tr><tr><td>accurate</td><td>62</td></tr><tr><td>decision</td><td>62</td></tr><tr><td>target</td><td>62</td></tr><tr><td>song</td><td>62</td></tr><tr><td>semi</td><td>62</td></tr><tr><td>prior</td><td>62</td></tr><tr><td>eecs</td><td>61</td></tr><tr><td>photo</td><td>61</td></tr><tr><td>reference</td><td>61</td></tr><tr><td>previous</td><td>61</td></tr><tr><td>negative</td><td>61</td></tr><tr><td>link</td><td>61</td></tr><tr><td>shenzhen</td><td>61</td></tr><tr><td>complex</td><td>61</td></tr><tr><td>examples</td><td>61</td></tr><tr><td>microsoft</td><td>61</td></tr><tr><td>cse</td><td>61</td></tr><tr><td>singh</td><td>61</td></tr><tr><td>recently</td><td>61</td></tr><tr><td>sequence</td><td>61</td></tr><tr><td>multimodal</td><td>60</td></tr><tr><td>wen</td><td>60</td></tr><tr><td>existing</td><td>60</td></tr><tr><td>performed</td><td>60</td></tr><tr><td>classes</td><td>60</td></tr><tr><td>layer</td><td>60</td></tr><tr><td>tang</td><td>60</td></tr><tr><td>comparison</td><td>59</td></tr><tr><td>effective</td><td>59</td></tr><tr><td>zafeiriou</td><td>59</td></tr><tr><td>solution</td><td>59</td></tr><tr><td>few</td><td>59</td></tr><tr><td>recherche</td><td>59</td></tr><tr><td>among</td><td>59</td></tr><tr><td>reduction</td><td>59</td></tr><tr><td>relative</td><td>59</td></tr><tr><td>license</td><td>59</td></tr><tr><td>labeled</td><td>59</td></tr><tr><td>basic</td><td>59</td></tr><tr><td>florida</td><td>59</td></tr><tr><td>labels</td><td>59</td></tr><tr><td>pages</td><td>58</td></tr><tr><td>top</td><td>58</td></tr><tr><td>adversarial</td><td>58</td></tr><tr><td>academic</td><td>58</td></tr><tr><td>light</td><td>58</td></tr><tr><td>road</td><td>58</td></tr><tr><td>feedback</td><td>58</td></tr><tr><td>categories</td><td>58</td></tr><tr><td>machines</td><td>58</td></tr><tr><td>extract</td><td>58</td></tr><tr><td>tao</td><td>58</td></tr><tr><td>washington</td><td>58</td></tr><tr><td>annotation</td><td>57</td></tr><tr><td>correlation</td><td>57</td></tr><tr><td>details</td><td>57</td></tr><tr><td>document</td><td>57</td></tr><tr><td>generative</td><td>57</td></tr><tr><td>impact</td><td>57</td></tr><tr><td>lei</td><td>57</td></tr><tr><td>chang</td><td>57</td></tr><tr><td>zurich</td><td>57</td></tr><tr><td>improving</td><td>57</td></tr><tr><td>hierarchical</td><td>57</td></tr><tr><td>grenoble</td><td>57</td></tr><tr><td>individual</td><td>57</td></tr><tr><td>parameters</td><td>57</td></tr><tr><td>subjects</td><td>57</td></tr><tr><td>eld</td><td>57</td></tr><tr><td>here</td><td>57</td></tr><tr><td>following</td><td>56</td></tr><tr><td>need</td><td>56</td></tr><tr><td>frames</td><td>56</td></tr><tr><td>hua</td><td>56</td></tr><tr><td>jain</td><td>56</td></tr><tr><td>zheng</td><td>56</td></tr><tr><td>springer</td><td>56</td></tr><tr><td>much</td><td>56</td></tr><tr><td>alexander</td><td>56</td></tr><tr><td>simple</td><td>56</td></tr><tr><td>inria</td><td>56</td></tr><tr><td>individuals</td><td>56</td></tr><tr><td>transfer</td><td>56</td></tr><tr><td>making</td><td>56</td></tr><tr><td>others</td><td>55</td></tr><tr><td>cohn</td><td>55</td></tr><tr><td>master</td><td>55</td></tr><tr><td>street</td><td>55</td></tr><tr><td>second</td><td>55</td></tr><tr><td>guo</td><td>55</td></tr><tr><td>lda</td><td>55</td></tr><tr><td>extracted</td><td>55</td></tr><tr><td>loss</td><td>55</td></tr><tr><td>geometric</td><td>55</td></tr><tr><td>spatio</td><td>55</td></tr><tr><td>area</td><td>55</td></tr><tr><td>last</td><td>55</td></tr><tr><td>random</td><td>55</td></tr><tr><td>authentication</td><td>54</td></tr><tr><td>projection</td><td>54</td></tr><tr><td>stefanos</td><td>54</td></tr><tr><td>include</td><td>54</td></tr><tr><td>mit</td><td>54</td></tr><tr><td>variation</td><td>54</td></tr><tr><td>eth</td><td>54</td></tr><tr><td>change</td><td>54</td></tr><tr><td>eyes</td><td>54</td></tr><tr><td>units</td><td>54</td></tr><tr><td>jean</td><td>54</td></tr><tr><td>queen</td><td>54</td></tr><tr><td>turkey</td><td>54</td></tr><tr><td>imperial</td><td>53</td></tr><tr><td>jiang</td><td>53</td></tr><tr><td>net</td><td>53</td></tr><tr><td>shen</td><td>53</td></tr><tr><td>useful</td><td>53</td></tr><tr><td>pairs</td><td>53</td></tr><tr><td>neuroscience</td><td>53</td></tr><tr><td>factors</td><td>53</td></tr><tr><td>pre</td><td>53</td></tr><tr><td>specific</td><td>53</td></tr><tr><td>jia</td><td>53</td></tr><tr><td>grained</td><td>52</td></tr><tr><td>program</td><td>52</td></tr><tr><td>fully</td><td>52</td></tr><tr><td>greece</td><td>52</td></tr><tr><td>step</td><td>52</td></tr><tr><td>detect</td><td>52</td></tr><tr><td>artificial</td><td>52</td></tr><tr><td>efficient</td><td>52</td></tr><tr><td>developed</td><td>52</td></tr><tr><td>ability</td><td>52</td></tr><tr><td>being</td><td>52</td></tr><tr><td>stimuli</td><td>52</td></tr><tr><td>life</td><td>52</td></tr><tr><td>malaysia</td><td>52</td></tr><tr><td>super</td><td>52</td></tr><tr><td>phase</td><td>52</td></tr><tr><td>photos</td><td>51</td></tr><tr><td>description</td><td>51</td></tr><tr><td>users</td><td>51</td></tr><tr><td>pantic</td><td>51</td></tr><tr><td>james</td><td>51</td></tr><tr><td>ming</td><td>51</td></tr><tr><td>words</td><td>51</td></tr><tr><td>attribution</td><td>51</td></tr><tr><td>memory</td><td>51</td></tr><tr><td>environment</td><td>51</td></tr><tr><td>response</td><td>51</td></tr><tr><td>sequences</td><td>51</td></tr><tr><td>campus</td><td>51</td></tr><tr><td>less</td><td>51</td></tr><tr><td>according</td><td>51</td></tr><tr><td>shi</td><td>51</td></tr><tr><td>associated</td><td>51</td></tr><tr><td>range</td><td>51</td></tr><tr><td>size</td><td>51</td></tr><tr><td>surrey</td><td>51</td></tr><tr><td>optimal</td><td>51</td></tr><tr><td>virginia</td><td>51</td></tr><tr><td>positive</td><td>51</td></tr><tr><td>texas</td><td>50</td></tr><tr><td>common</td><td>50</td></tr><tr><td>frontal</td><td>50</td></tr><tr><td>preserving</td><td>50</td></tr><tr><td>reviewed</td><td>50</td></tr><tr><td>cite</td><td>50</td></tr><tr><td>zhen</td><td>50</td></tr><tr><td>fax</td><td>50</td></tr><tr><td>polytechnic</td><td>50</td></tr><tr><td>martin</td><td>50</td></tr><tr><td>responses</td><td>50</td></tr><tr><td>particular</td><td>50</td></tr><tr><td>cues</td><td>50</td></tr><tr><td>pro</td><td>50</td></tr><tr><td>sensors</td><td>50</td></tr><tr><td>xiang</td><td>49</td></tr><tr><td>chellappa</td><td>49</td></tr><tr><td>pennsylvania</td><td>49</td></tr><tr><td>peer</td><td>49</td></tr><tr><td>stage</td><td>49</td></tr><tr><td>daniel</td><td>49</td></tr><tr><td>max</td><td>49</td></tr><tr><td>lausanne</td><td>49</td></tr><tr><td>signals</td><td>49</td></tr><tr><td>mohammad</td><td>49</td></tr><tr><td>fisher</td><td>49</td></tr><tr><td>detector</td><td>49</td></tr><tr><td>publications</td><td>49</td></tr><tr><td>ekman</td><td>49</td></tr><tr><td>adaptation</td><td>49</td></tr><tr><td>committee</td><td>49</td></tr><tr><td>patients</td><td>49</td></tr><tr><td>effect</td><td>48</td></tr><tr><td>instance</td><td>48</td></tr><tr><td>simon</td><td>48</td></tr><tr><td>israel</td><td>48</td></tr><tr><td>shows</td><td>48</td></tr><tr><td>sets</td><td>48</td></tr><tr><td>norm</td><td>48</td></tr><tr><td>urbana</td><td>48</td></tr><tr><td>principal</td><td>4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d><td>42</td></tr><tr><td>fear</td><td>42</td></tr><tr><td>types</td><td>42</td></tr><tr><td>shiguang</td><td>42</td></tr><tr><td>short</td><td>42</td></tr><tr><td>effects</td><td>41</td></tr><tr><td>team</td><td>41</td></tr><tr><td>interactive</td><td>41</td></tr><tr><td>man</td><td>41</td></tr><tr><td>standard</td><td>41</td></tr><tr><td>eurasip</td><td>41</td></tr><tr><td>transform</td><td>41</td></tr><tr><td>patrick</td><td>41</td></tr><tr><td>generally</td><td>41</td></tr><tr><td>architecture</td><td>41</td></tr><tr><td>leuven</td><td>41</td></tr><tr><td>called</td><td>41</td></tr><tr><td>print</td><td>41</td></tr><tr><td>combination</td><td>41</td></tr><tr><td>library</td><td>41</td></tr><tr><td>william</td><td>41</td></tr><tr><td>jeffrey</td><td>40</td></tr><tr><td>constrained</td><td>40</td></tr><tr><td>boston</td><td>40</td></tr><tr><td>bristol</td><td>40</td></tr><tr><td>mining</td><td>40</td></tr><tr><td>george</td><td>40</td></tr><tr><td>goal</td><td>40</td></tr><tr><td>del</td><td>40</td></tr></table></body></html>
\ No newline at end of file +<!doctype html><html><head><meta charset='utf-8'><title>PDF Report: Unknown Terms</title><link rel='stylesheet' href='reports.css'></head><body><h2>PDF Report: Unknown Terms</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>the</td><td>34336</td></tr><tr><td>and</td><td>31058</td></tr><tr><td>for</td><td>13577</td></tr><tr><td>university</td><td>11911</td></tr><tr><td>with</td><td>6287</td></tr><tr><td>face</td><td>6019</td></tr><tr><td>recognition</td><td>5389</td></tr><tr><td>that</td><td>5185</td></tr><tr><td>computer</td><td>5155</td></tr><tr><td>this</td><td>4892</td></tr><tr><td>department</td><td>4508</td></tr><tr><td>science</td><td>4412</td></tr><tr><td>research</td><td>4154</td></tr><tr><td>from</td><td>4031</td></tr><tr><td>are</td><td>3994</td></tr><tr><td>engineering</td><td>3678</td></tr><tr><td>image</td><td>3423</td></tr><tr><td>facial</td><td>3321</td></tr><tr><td>technology</td><td>3113</td></tr><tr><td>based</td><td>3073</td></tr><tr><td>learning</td><td>2938</td></tr><tr><td>institute</td><td>2876</td></tr><tr><td>using</td><td>2856</td></tr><tr><td>information</td><td>2807</td></tr><tr><td>ieee</td><td>2325</td></tr><tr><td>social</td><td>2209</td></tr><tr><td>human</td><td>2168</td></tr><tr><td>data</td><td>2067</td></tr><tr><td>usa</td><td>1987</td></tr><tr><td>images</td><td>1975</td></tr><tr><td>detection</td><td>1944</td></tr><tr><td>china</td><td>1918</td></tr><tr><td>school</td><td>1894</td></tr><tr><td>which</td><td>1822</td></tr><tr><td>visual</td><td>1819</td></tr><tr><td>have</td><td>1814</td></tr><tr><td>can</td><td>1670</td></tr><tr><td>object</td><td>1633</td></tr><tr><td>faces</td><td>1611</td></tr><tr><td>has</td><td>1600</td></tr><tr><td>processing</td><td>1596</td></tr><tr><td>these</td><td>1594</td></tr><tr><td>our</td><td>1573</td></tr><tr><td>model</td><td>1562</td></tr><tr><td>vision</td><td>1555</td></tr><tr><td>cation</td><td>1554</td></tr><tr><td>not</td><td>1543</td></tr><tr><td>video</td><td>1542</td></tr><tr><td>article</td><td>1507</td></tr><tr><td>features</td><td>1501</td></tr><tr><td>feature</td><td>1478</td></tr><tr><td>doi</td><td>1477</td></tr><tr><td>journal</td><td>1472</td></tr><tr><td>may</td><td>1450</td></tr><tr><td>such</td><td>1439</td></tr><tr><td>analysis</td><td>1433</td></tr><tr><td>member</td><td>1428</td></tr><tr><td>systems</td><td>1362</td></tr><tr><td>expression</td><td>1348</td></tr><tr><td>system</td><td>1338</td></tr><tr><td>more</td><td>1306</td></tr><tr><td>deep</td><td>1296</td></tr><tr><td>http</td><td>1290</td></tr><tr><td>been</td><td>1281</td></tr><tr><td>center</td><td>1268</td></tr><tr><td>neural</td><td>1235</td></tr><tr><td>published</td><td>1221</td></tr><tr><td>sciences</td><td>1191</td></tr><tr><td>multi</td><td>1172</td></tr><tr><td>wang</td><td>1157</td></tr><tr><td>www</td><td>1140</td></tr><tr><td>paper</td><td>1135</td></tr><tr><td>new</td><td>1130</td></tr><tr><td>electrical</td><td>1124</td></tr><tr><td>international</td><td>1121</td></tr><tr><td>autism</td><td>1106</td></tr><tr><td>was</td><td>1095</td></tr><tr><td>college</td><td>1091</td></tr><tr><td>person</td><td>1086</td></tr><tr><td>use</td><td>1084</td></tr><tr><td>one</td><td>1077</td></tr><tr><td>accepted</td><td>1062</td></tr><tr><td>tracking</td><td>1033</td></tr><tr><td>other</td><td>1028</td></tr><tr><td>received</td><td>1010</td></tr><tr><td>their</td><td>1010</td></tr><tr><td>national</td><td>1006</td></tr><tr><td>expressions</td><td>1001</td></tr><tr><td>work</td><td>998</td></tr><tr><td>psychology</td><td>996</td></tr><tr><td>pose</td><td>994</td></tr><tr><td>two</td><td>992</td></tr><tr><td>time</td><td>975</td></tr><tr><td>networks</td><td>970</td></tr><tr><td>models</td><td>970</td></tr><tr><td>emotion</td><td>968</td></tr><tr><td>results</td><td>964</td></tr><tr><td>different</td><td>957</td></tr><tr><td>approach</td><td>956</td></tr><tr><td>high</td><td>948</td></tr><tr><td>classi</td><td>944</td></tr><tr><td>method</td><td>942</td></tr><tr><td>laboratory</td><td>941</td></tr><tr><td>all</td><td>940</td></tr><tr><td>used</td><td>938</td></tr><tr><td>org</td><td>934</td></tr><tr><td>network</td><td>931</td></tr><tr><td>methods</td><td>917</td></tr><tr><td>applications</td><td>915</td></tr><tr><td>group</td><td>910</td></tr><tr><td>state</td><td>907</td></tr><tr><td>performance</td><td>902</td></tr><tr><td>zhang</td><td>891</td></tr><tr><td>each</td><td>880</td></tr><tr><td>between</td><td>865</td></tr><tr><td>also</td><td>860</td></tr><tr><td>india</td><td>854</td></tr><tr><td>germany</td><td>854</td></tr><tr><td>were</td><td>844</td></tr><tr><td>people</td><td>827</td></tr><tr><td>computing</td><td>827</td></tr><tr><td>chen</td><td>814</td></tr><tr><td>training</td><td>810</td></tr><tr><td>than</td><td>806</td></tr><tr><td>brain</td><td>804</td></tr><tr><td>study</td><td>804</td></tr><tr><td>under</td><td>800</td></tr><tr><td>pattern</td><td>797</td></tr><tr><td>california</td><td>796</td></tr><tr><td>when</td><td>792</td></tr><tr><td>emotional</td><td>772</td></tr><tr><td>large</td><td>771</td></tr><tr><td>access</td><td>763</td></tr><tr><td>author</td><td>762</td></tr><tr><td>representation</td><td>762</td></tr><tr><td>online</td><td>754</td></tr><tr><td>task</td><td>753</td></tr><tr><td>asd</td><td>753</td></tr><tr><td>yang</td><td>748</td></tr><tr><td>they</td><td>745</td></tr><tr><td>introduction</td><td>740</td></tr><tr><td>however</td><td>734</td></tr><tr><td>set</td><td>733</td></tr><tr><td>com</td><td>730</td></tr><tr><td>email</td><td>730</td></tr><tr><td>real</td><td>730</td></tr><tr><td>studies</td><td>727</td></tr><tr><td>local</td><td>726</td></tr><tr><td>mail</td><td>725</td></tr><tr><td>estimation</td><td>723</td></tr><tr><td>machine</td><td>721</td></tr><tr><td>but</td><td>716</td></tr><tr><td>number</td><td>715</td></tr><tr><td>beijing</td><td>712</td></tr><tr><td>liu</td><td>710</td></tr><tr><td>level</td><td>710</td></tr><tr><td>dataset</td><td>709</td></tr><tr><td>problem</td><td>708</td></tr><tr><td>eye</td><td>705</td></tr><tr><td>identi</td><td>704</td></tr><tr><td>its</td><td>698</td></tr><tr><td>open</td><td>696</td></tr><tr><td>key</td><td>690</td></tr><tr><td>action</td><td>687</td></tr><tr><td>gaze</td><td>685</td></tr><tr><td>most</td><td>678</td></tr><tr><td>proposed</td><td>677</td></tr><tr><td>correspondence</td><td>671</td></tr><tr><td>vol</td><td>669</td></tr><tr><td>both</td><td>665</td></tr><tr><td>universit</td><td>664</td></tr><tr><td>perception</td><td>660</td></tr><tr><td>low</td><td>655</td></tr><tr><td>france</td><td>651</td></tr><tr><td>conference</td><td>648</td></tr><tr><td>lab</td><td>648</td></tr><tr><td>multiple</td><td>640</td></tr><tr><td>issn</td><td>634</td></tr><tr><td>into</td><td>630</td></tr><tr><td>volume</td><td>626</td></tr><tr><td>submitted</td><td>626</td></tr><tr><td>will</td><td>624</td></tr><tr><td>individuals</td><td>617</td></tr><tr><td>non</td><td>616</td></tr><tr><td>semantic</td><td>615</td></tr><tr><td>many</td><td>612</td></tr><tr><td>robust</td><td>609</td></tr><tr><td>dept</td><td>604</td></tr><tr><td>attention</td><td>600</td></tr><tr><td>via</td><td>598</td></tr><tr><td>any</td><td>593</td></tr><tr><td>how</td><td>588</td></tr><tr><td>part</td><td>586</td></tr><tr><td>scene</td><td>585</td></tr><tr><td>only</td><td>581</td></tr><tr><td>objects</td><td>574</td></tr><tr><td>version</td><td>571</td></tr><tr><td>children</td><td>564</td></tr><tr><td>intelligence</td><td>559</td></tr><tr><td>segmentation</td><td>557</td></tr><tr><td>motion</td><td>550</td></tr><tr><td>keywords</td><td>545</td></tr><tr><td>available</td><td>544</td></tr><tr><td>there</td><td>542</td></tr><tr><td>well</td><td>542</td></tr><tr><td>london</td><td>533</td></tr><tr><td>faculty</td><td>532</td></tr><tr><td>scale</td><td>529</td></tr><tr><td>cognitive</td><td>525</td></tr><tr><td>some</td><td>516</td></tr><tr><td>where</td><td>514</td></tr><tr><td>copyright</td><td>514</td></tr><tr><td>review</td><td>514</td></tr><tr><td>single</td><td>508</td></tr><tr><td>shape</td><td>508</td></tr><tr><td>development</td><td>506</td></tr><tr><td>algorithm</td><td>505</td></tr><tr><td>class</td><td>504</td></tr><tr><td>illumination</td><td>504</td></tr><tr><td>should</td><td>503</td></tr><tr><td>show</td><td>501</td></tr><tr><td>automatic</td><td>498</td></tr><tr><td>chinese</td><td>497</td></tr><tr><td>view</td><td>497</td></tr><tr><td>space</td><td>497</td></tr><tr><td>authors</td><td>495</td></tr><tr><td>while</td><td>494</td></tr><tr><td>degree</td><td>493</td></tr><tr><td>over</td><td>491</td></tr><tr><td>communication</td><td>485</td></tr><tr><td>appearance</td><td>483</td></tr><tr><td>issue</td><td>478</td></tr><tr><td>algorithms</td><td>478</td></tr><tr><td>videos</td><td>477</td></tr><tr><td>hong</td><td>476</td></tr><tr><td>hal</td><td>476</td></tr><tr><td>june</td><td>474</td></tr><tr><td>about</td><td>474</td></tr><tr><td>figure</td><td>474</td></tr><tr><td>interaction</td><td>474</td></tr><tr><td>behavior</td><td>471</td></tr><tr><td>intelligent</td><td>470</td></tr><tr><td>convolutional</td><td>469</td></tr><tr><td>during</td><td>467</td></tr><tr><td>informatics</td><td>465</td></tr><tr><td>given</td><td>464</td></tr><tr><td>same</td><td>464</td></tr><tr><td>computational</td><td>463</td></tr><tr><td>japan</td><td>463</td></tr><tr><td>date</td><td>460</td></tr><tr><td>domain</td><td>460</td></tr><tr><td>publication</td><td>458</td></tr><tr><td>age</td><td>458</td></tr><tr><td>content</td><td>455</td></tr><tr><td>tel</td><td>453</td></tr><tr><td>temporal</td><td>452</td></tr><tr><td>database</td><td>440</td></tr><tr><td>original</td><td>440</td></tr><tr><td>understanding</td><td>438</td></tr><tr><td>then</td><td>437</td></tr><tr><td>novel</td><td>435</td></tr><tr><td>first</td><td>433</td></tr><tr><td>present</td><td>433</td></tr><tr><td>techniques</td><td>431</td></tr><tr><td>thesis</td><td>429</td></tr><tr><td>stimuli</td><td>429</td></tr><tr><td>august</td><td>427</td></tr><tr><td>through</td><td>426</td></tr><tr><td>classification</td><td>423</td></tr><tr><td>identity</td><td>418</td></tr><tr><td>framework</td><td>418</td></tr><tr><td>target</td><td>416</td></tr><tr><td>recent</td><td>414</td></tr><tr><td>sparse</td><td>413</td></tr><tr><td>professor</td><td>413</td></tr><tr><td>search</td><td>412</td></tr><tr><td>requirements</td><td>411</td></tr><tr><td>emotions</td><td>411</td></tr><tr><td>academy</td><td>410</td></tr><tr><td>student</td><td>407</td></tr><tr><td>september</td><td>406</td></tr><tr><td>memory</td><td>406</td></tr><tr><td>joint</td><td>405</td></tr><tr><td>spectrum</td><td>405</td></tr><tr><td>applied</td><td>405</td></tr><tr><td>important</td><td>405</td></tr><tr><td>huang</td><td>404</td></tr><tr><td>supervised</td><td>404</td></tr><tr><td>tasks</td><td>404</td></tr><tr><td>des</td><td>403</td></tr><tr><td>including</td><td>402</td></tr><tr><td>linear</td><td>401</td></tr><tr><td>whether</td><td>401</td></tr><tr><td>speci</td><td>400</td></tr><tr><td>participants</td><td>400</td></tr><tr><td>related</td><td>400</td></tr><tr><td>neuroscience</td><td>400</td></tr><tr><td>language</td><td>398</td></tr><tr><td>carnegie</td><td>398</td></tr><tr><td>italy</td><td>398</td></tr><tr><td>process</td><td>397</td></tr><tr><td>april</td><td>395</td></tr><tr><td>signal</td><td>395</td></tr><tr><td>section</td><td>394</td></tr><tr><td>mellon</td><td>393</td></tr><tr><td>representations</td><td>392</td></tr><tr><td>centre</td><td>392</td></tr><tr><td>australia</td><td>391</td></tr><tr><td>general</td><td>388</td></tr><tr><td>matching</td><td>388</td></tr><tr><td>canada</td><td>388</td></tr><tr><td>david</td><td>387</td></tr><tr><td>example</td><td>387</td></tr><tr><td>senior</td><td>387</td></tr><tr><td>electronic</td><td>385</td></tr><tr><td>accuracy</td><td>385</td></tr><tr><td>amygdala</td><td>385</td></tr><tr><td>partial</td><td>384</td></tr><tr><td>shown</td><td>382</td></tr><tr><td>context</td><td>381</td></tr><tr><td>michael</td><td>381</td></tr><tr><td>july</td><td>381</td></tr><tr><td>pedestrian</td><td>380</td></tr><tr><td>imaging</td><td>379</td></tr><tr><td>biometric</td><td>378</td></tr><tr><td>electronics</td><td>378</td></tr><tr><td>wei</td><td>377</td></tr><tr><td>united</td><td>377</td></tr><tr><td>input</td><td>377</td></tr><tr><td>extraction</td><td>377</td></tr><tr><td>regions</td><td>376</td></tr><tr><td>camera</td><td>375</td></tr><tr><td>spain</td><td>370</td></tr><tr><td>rst</td><td>370</td></tr><tr><td>advanced</td><td>369</td></tr><tr><td>found</td><td>369</td></tr><tr><td>van</td><td>369</td></tr><tr><td>york</td><td>367</td></tr><tr><td>control</td><td>367</td></tr><tr><td>retrieval</td><td>366</td></tr><tr><td>like</td><td>366</td></tr><tr><td>patterns</td><td>365</td></tr><tr><td>inc</td><td>365</td></tr><tr><td>activity</td><td>364</td></tr><tr><td>singapore</td><td>363</td></tr><tr><td>march</td><td>363</td></tr><tr><td>prof</td><td>362</td></tr><tr><td>natural</td><td>362</td></tr><tr><td>kong</td><td>362</td></tr><tr><td>three</td><td>362</td></tr><tr><td>humans</td><td>361</td></tr><tr><td>several</td><td>360</td></tr><tr><td>technical</td><td>359</td></tr><tr><td>resolution</td><td>358</td></tr><tr><td>dynamic</td><td>358</td></tr><tr><td>order</td><td>358</td></tr><tr><td>attributes</td><td>358</td></tr><tr><td>application</td><td>357</td></tr><tr><td>approaches</td><td>355</td></tr><tr><td>you</td><td>355</td></tr><tr><td>terms</td><td>354</td></tr><tr><td>ing</td><td>353</td></tr><tr><td>october</td><td>353</td></tr><tr><td>december</td><td>353</td></tr><tr><td>datasets</td><td>351</td></tr><tr><td>proceedings</td><td>351</td></tr><tr><td>without</td><td>350</td></tr><tr><td>world</td><td>350</td></tr><tr><td>attribute</td><td>348</td></tr><tr><td>rights</td><td>346</td></tr><tr><td>conditions</td><td>346</td></tr><tr><td>clustering</td><td>345</td></tr><tr><td>see</td><td>345</td></tr><tr><td>https</td><td>343</td></tr><tr><td>evaluation</td><td>342</td></tr><tr><td>con</td><td>341</td></tr><tr><td>even</td><td>340</td></tr><tr><td>cross</td><td>340</td></tr><tr><td>revised</td><td>339</td></tr><tr><td>disorders</td><td>338</td></tr><tr><td>vector</td><td>338</td></tr><tr><td>color</td><td>337</td></tr><tr><td>role</td><td>337</td></tr><tr><td>medical</td><td>336</td></tr><tr><td>disorder</td><td>334</td></tr><tr><td>switzerland</td><td>334</td></tr><tr><td>modeling</td><td>334</td></tr><tr><td>surveillance</td><td>333</td></tr><tr><td>dimensional</td><td>333</td></tr><tr><td>tion</td><td>332</td></tr><tr><td>graduate</td><td>331</td></tr><tr><td>presented</td><td>330</td></tr><tr><td>due</td><td>330</td></tr><tr><td>region</td><td>329</td></tr><tr><td>matrix</td><td>326</td></tr><tr><td>january</td><td>326</td></tr><tr><td>individual</td><td>326</td></tr><tr><td>compared</td><td>326</td></tr><tr><td>within</td><td>325</td></tr><tr><td>kim</td><td>323</td></tr><tr><td>design</td><td>322</td></tr><tr><td>korea</td><td>321</td></tr><tr><td>netherlands</td><td>321</td></tr><tr><td>cognition</td><td>321</td></tr><tr><td>november</td><td>320</td></tr><tr><td>february</td><td>320</td></tr><tr><td>fellow</td><td>320</td></tr><tr><td>very</td><td>320</td></tr><tr><td>form</td><td>319</td></tr><tr><td>problems</td><td>319</td></tr><tr><td>robotics</td><td>317</td></tr><tr><td>provide</td><td>317</td></tr><tr><td>function</td><td>317</td></tr><tr><td>binary</td><td>316</td></tr><tr><td>cnn</td><td>316</td></tr><tr><td>distribution</td><td>314</td></tr><tr><td>security</td><td>314</td></tr><tr><td>eyes</td><td>312</td></tr><tr><td>made</td><td>311</td></tr><tr><td>differences</td><td>311</td></tr><tr><td>localization</td><td>310</td></tr><tr><td>often</td><td>310</td></tr><tr><td>across</td><td>310</td></tr><tr><td>experimental</td><td>309</td></tr><tr><td>because</td><td>309</td></tr><tr><td>user</td><td>309</td></tr><tr><td>what</td><td>309</td></tr><tr><td>media</td><td>308</td></tr><tr><td>documents</td><td>305</td></tr><tr><td>edu</td><td>305</td></tr><tr><td>states</td><td>305</td></tr><tr><td>provided</td><td>304</td></tr><tr><td>citation</td><td>304</td></tr><tr><td>make</td><td>304</td></tr><tr><td>others</td><td>304</td></tr><tr><td>report</td><td>303</td></tr><tr><td>evidence</td><td>303</td></tr><tr><td>lin</td><td>303</td></tr><tr><td>depth</td><td>303</td></tr><tr><td>corresponding</td><td>302</td></tr><tr><td>similarity</td><td>301</td></tr><tr><td>question</td><td>301</td></tr><tr><td>shanghai</td><td>301</td></tr><tr><td>main</td><td>300</td></tr><tr><td>body</td><td>300</td></tr><tr><td>spatial</td><td>299</td></tr><tr><td>response</td><td>298</td></tr><tr><td>sun</td><td>296</td></tr><tr><td>those</td><td>296</td></tr><tr><td>zhu</td><td>294</td></tr><tr><td>park</td><td>292</td></tr><tr><td>structure</td><td>292</td></tr><tr><td>selection</td><td>291</td></tr><tr><td>lee</td><td>291</td></tr><tr><td>years</td><td>291</td></tr><tr><td>please</td><td>290</td></tr><tr><td>biometrics</td><td>289</td></tr><tr><td>effect</td><td>289</td></tr><tr><td>addressed</td><td>289</td></tr><tr><td>similar</td><td>289</td></tr><tr><td>pittsburgh</td><td>288</td></tr><tr><td>associated</td><td>288</td></tr><tr><td>san</td><td>288</td></tr><tr><td>effects</td><td>288</td></tr><tr><td>association</td><td>288</td></tr><tr><td>dissertation</td><td>288</td></tr><tr><td>digital</td><td>287</td></tr><tr><td>zhou</td><td>287</td></tr><tr><td>unsupervised</td><td>287</td></tr><tr><td>support</td><td>287</td></tr><tr><td>cambridge</td><td>287</td></tr><tr><td>multimedia</td><td>286</td></tr><tr><td>words</td><td>286</td></tr><tr><td>prediction</td><td>285</td></tr><tr><td>changes</td><td>284</td></tr><tr><td>complex</td><td>282</td></tr><tr><td>subspace</td><td>281</td></tr><tr><td>head</td><td>279</td></tr><tr><td>berkeley</td><td>277</td></tr><tr><td>der</td><td>277</td></tr><tr><td>still</td><td>277</td></tr><tr><td>test</td><td>277</td></tr><tr><td>philosophy</td><td>277</td></tr><tr><td>art</td><td>276</td></tr><tr><td>public</td><td>275</td></tr><tr><td>tech</td><td>275</td></tr><tr><td>self</td><td>275</td></tr><tr><td>technologies</td><td>274</td></tr><tr><td>known</td><td>274</td></tr><tr><td>component</td><td>274</td></tr><tr><td>various</td><td>274</td></tr><tr><td>project</td><td>273</td></tr><tr><td>knowledge</td><td>273</td></tr><tr><td>google</td><td>273</td></tr><tr><td>contact</td><td>273</td></tr><tr><td>propose</td><td>272</td></tr><tr><td>material</td><td>272</td></tr><tr><td>parts</td><td>272</td></tr><tr><td>further</td><td>272</td></tr><tr><td>works</td><td>272</td></tr><tr><td>manuscript</td><td>272</td></tr><tr><td>doctor</td><td>271</td></tr><tr><td>them</td><td>271</td></tr><tr><td>less</td><td>270</td></tr><tr><td>way</td><td>270</td></tr><tr><td>variations</td><td>270</td></tr><tr><td>fusion</td><td>269</td></tr><tr><td>editor</td><td>268</td></tr><tr><td>discriminative</td><td>268</td></tr><tr><td>learn</td><td>268</td></tr><tr><td>behavioral</td><td>268</td></tr><tr><td>barcelona</td><td>267</td></tr><tr><td>identification</td><td>266</td></tr><tr><td>experiments</td><td>265</td></tr><tr><td>automation</td><td>265</td></tr><tr><td>road</td><td>264</td></tr><tr><td>cial</td><td>264</td></tr><tr><td>adversarial</td><td>263</td></tr><tr><td>box</td><td>263</td></tr><tr><td>cues</td><td>262</td></tr><tr><td>distance</td><td>262</td></tr><tr><td>generative</td><td>261</td></tr><tr><td>global</td><td>261</td></tr><tr><td>current</td><td>261</td></tr><tr><td>thus</td><td>260</td></tr><tr><td>arti</td><td>260</td></tr><tr><td>affective</td><td>260</td></tr><tr><td>texture</td><td>260</td></tr><tr><td>interest</td><td>259</td></tr><tr><td>functional</td><td>259</td></tr><tr><td>psychiatry</td><td>259</td></tr><tr><td>points</td><td>258</td></tr><tr><td>small</td><td>258</td></tr><tr><td>yan</td><td>258</td></tr><tr><td>ability</td><td>258</td></tr><tr><td>active</td><td>258</td></tr><tr><td>software</td><td>257</td></tr><tr><td>per</td><td>257</td></tr><tr><td>who</td><td>257</td></tr><tr><td>address</td><td>257</td></tr><tr><td>label</td><td>256</td></tr><tr><td>medicine</td><td>256</td></tr><tr><td>full</td><td>256</td></tr><tr><td>scenes</td><td>256</td></tr><tr><td>thomas</td><td>256</td></tr><tr><td>early</td><td>256</td></tr><tr><td>sample</td><td>255</td></tr><tr><td>among</td><td>255</td></tr><tr><td>cient</td><td>254</td></tr><tr><td>fast</td><td>254</td></tr><tr><td>better</td><td>254</td></tr><tr><td>gender</td><td>254</td></tr><tr><td>mathematics</td><td>254</td></tr><tr><td>out</td><td>254</td></tr><tr><td>interactions</td><td>253</td></tr><tr><td>microsoft</td><td>252</td></tr><tr><td>point</td><td>251</td></tr><tr><td>zhao</td><td>249</td></tr><tr><td>signi</td><td>249</td></tr><tr><td>regression</td><td>248</td></tr><tr><td>link</td><td>248</td></tr><tr><td>higher</td><td>248</td></tr><tr><td>fig</td><td>245</td></tr><tr><td>invariant</td><td>244</td></tr><tr><td>robot</td><td>244</td></tr><tr><td>quality</td><td>243</td></tr><tr><td>speech</td><td>243</td></tr><tr><td>graph</td><td>242</td></tr><tr><td>trained</td><td>241</td></tr><tr><td>size</td><td>241</td></tr><tr><td>here</td><td>241</td></tr><tr><td>end</td><td>241</td></tr><tr><td>massachusetts</td><td>240</td></tr><tr><td>towards</td><td>240</td></tr><tr><td>second</td><td>239</td></tr><tr><td>subject</td><td>238</td></tr><tr><td>negative</td><td>238</td></tr><tr><td>subjects</td><td>238</td></tr><tr><td>hand</td><td>237</td></tr><tr><td>health</td><td>237</td></tr><tr><td>univ</td><td>236</td></tr><tr><td>theory</td><td>235</td></tr><tr><td>eth</td><td>235</td></tr><tr><td>responses</td><td>235</td></tr><tr><td>groups</td><td>235</td></tr><tr><td>max</td><td>234</td></tr><tr><td>pages</td><td>234</td></tr><tr><td>therefore</td><td>234</td></tr><tr><td>core</td><td>233</td></tr><tr><td>would</td><td>233</td></tr><tr><td>additional</td><td>232</td></tr><tr><td>personal</td><td>232</td></tr><tr><td>dif</td><td>232</td></tr><tr><td>long</td><td>232</td></tr><tr><td>oxford</td><td>232</td></tr><tr><td>potential</td><td>231</td></tr><tr><td>taiwan</td><td>229</td></tr><tr><td>samples</td><td>228</td></tr><tr><td>prior</td><td>228</td></tr><tr><td>categories</td><td>227</td></tr><tr><td>range</td><td>227</td></tr><tr><td>distributed</td><td>226</td></tr><tr><td>top</td><td>226</td></tr><tr><td>positive</td><td>226</td></tr><tr><td>recherche</td><td>226</td></tr><tr><td>transfer</td><td>225</td></tr><tr><td>kernel</td><td>225</td></tr><tr><td>area</td><td>225</td></tr><tr><td>central</td><td>224</td></tr><tr><td>effective</td><td>224</td></tr><tr><td>edited</td><td>224</td></tr><tr><td>since</td><td>223</td></tr><tr><td>multimodal</td><td>222</td></tr><tr><td>following</td><td>222</td></tr><tr><td>could</td><td>221</td></tr><tr><td>text</td><td>221</td></tr><tr><td>few</td><td>221</td></tr><tr><td>although</td><td>221</td></tr><tr><td>oxytocin</td><td>220</td></tr><tr><td>instance</td><td>220</td></tr><tr><td>crowd</td><td>220</td></tr><tr><td>areas</td><td>220</td></tr><tr><td>environment</td><td>220</td></tr><tr><td>limited</td><td>219</td></tr><tr><td>commons</td><td>219</td></tr><tr><td>loss</td><td>218</td></tr><tr><td>amsterdam</td><td>218</td></tr><tr><td>future</td><td>217</td></tr><tr><td>right</td><td>217</td></tr><tr><td>rate</td><td>217</td></tr><tr><td>inference</td><td>216</td></tr><tr><td>reviewed</td><td>215</td></tr><tr><td>south</td><td>215</td></tr><tr><td>frame</td><td>215</td></tr><tr><td>embedding</td><td>215</td></tr><tr><td>factors</td><td>215</td></tr><tr><td>peter</td><td>214</td></tr><tr><td>metric</td><td>214</td></tr><tr><td>adults</td><td>214</td></tr><tr><td>web</td><td>213</td></tr><tr><td>learned</td><td>213</td></tr><tr><td>cheng</td><td>212</td></tr><tr><td>activation</td><td>212</td></tr><tr><td>michigan</td><td>212</td></tr><tr><td>reconstruction</td><td>212</td></tr><tr><td>accurate</td><td>211</td></tr><tr><td>kumar</td><td>211</td></tr><tr><td>pca</td><td>211</td></tr><tr><td>after</td><td>211</td></tr><tr><td>optimization</td><td>210</td></tr><tr><td>young</td><td>210</td></tr><tr><td>tokyo</td><td>210</td></tr><tr><td>alignment</td><td>210</td></tr><tr><td>stanford</td><td>210</td></tr><tr><td>occlusion</td><td>210</td></tr><tr><td>city</td><td>209</td></tr><tr><td>driven</td><td>209</td></tr><tr><td>los</td><td>209</td></tr><tr><td>layer</td><td>208</td></tr><tr><td>possible</td><td>207</td></tr><tr><td>sensors</td><td>207</td></tr><tr><td>previous</td><td>206</td></tr><tr><td>adaptive</td><td>206</td></tr><tr><td>basic</td><td>205</td></tr><tr><td>gabor</td><td>205</td></tr><tr><td>ful</td><td>204</td></tr><tr><td>jun</td><td>204</td></tr><tr><td>obtained</td><td>204</td></tr><tr><td>zheng</td><td>204</td></tr><tr><td>comparison</td><td>203</td></tr><tr><td>particular</td><td>203</td></tr><tr><td>statistics</td><td>202</td></tr><tr><td>recognize</td><td>202</td></tr><tr><td>simple</td><td>202</td></tr><tr><td>much</td><td>202</td></tr><tr><td>discriminant</td><td>202</td></tr><tr><td>typically</td><td>202</td></tr><tr><td>bias</td><td>202</td></tr><tr><td>neutral</td><td>202</td></tr><tr><td>kingdom</td><td>201</td></tr><tr><td>actions</td><td>201</td></tr><tr><td>program</td><td>201</td></tr><tr><td>survey</td><td>200</td></tr><tr><td>shen</td><td>200</td></tr><tr><td>mobile</td><td>200</td></tr><tr><td>ali</td><td>200</td></tr><tr><td>processes</td><td>200</td></tr><tr><td>being</td><td>200</td></tr><tr><td>details</td><td>199</td></tr><tr><td>challenging</td><td>199</td></tr><tr><td>challenge</td><td>199</td></tr><tr><td>relative</td><td>199</td></tr><tr><td>daniel</td><td>198</td></tr><tr><td>highly</td><td>198</td></tr><tr><td>existing</td><td>198</td></tr><tr><td>zurich</td><td>197</td></tr><tr><td>inria</td><td>197</td></tr><tr><td>transactions</td><td>196</td></tr><tr><td>common</td><td>196</td></tr><tr><td>perceptual</td><td>196</td></tr><tr><td>recently</td><td>196</td></tr><tr><td>reported</td><td>196</td></tr><tr><td>mental</td><td>196</td></tr><tr><td>architecture</td><td>196</td></tr><tr><td>andrew</td><td>195</td></tr><tr><td>observed</td><td>195</td></tr><tr><td>focus</td><td>195</td></tr><tr><td>stimulus</td><td>195</td></tr><tr><td>song</td><td>195</td></tr><tr><td>direct</td><td>194</td></tr><tr><td>normal</td><td>194</td></tr><tr><td>does</td><td>194</td></tr><tr><td>improve</td><td>194</td></tr><tr><td>components</td><td>193</td></tr><tr><td>must</td><td>193</td></tr><tr><td>category</td><td>193</td></tr><tr><td>cortex</td><td>193</td></tr><tr><td>developmental</td><td>192</td></tr><tr><td>descriptors</td><td>192</td></tr><tr><td>pro</td><td>192</td></tr><tr><td>examples</td><td>192</td></tr><tr><td>source</td><td>192</td></tr><tr><td>creative</td><td>192</td></tr><tr><td>life</td><td>192</td></tr><tr><td>phd</td><td>192</td></tr><tr><td>cite</td><td>191</td></tr><tr><td>veri</td><td>191</td></tr><tr><td>recognizing</td><td>191</td></tr><tr><td>hierarchical</td><td>191</td></tr><tr><td>traits</td><td>191</td></tr><tr><td>tao</td><td>190</td></tr><tr><td>rank</td><td>190</td></tr><tr><td>generation</td><td>189</td></tr><tr><td>sets</td><td>189</td></tr><tr><td>adaptation</td><td>189</td></tr><tr><td>diego</td><td>189</td></tr><tr><td>geometric</td><td>188</td></tr><tr><td>cost</td><td>188</td></tr><tr><td>pre</td><td>187</td></tr><tr><td>license</td><td>187</td></tr><tr><td>alexander</td><td>187</td></tr><tr><td>random</td><td>186</td></tr><tr><td>management</td><td>186</td></tr><tr><td>fully</td><td>186</td></tr><tr><td>jiang</td><td>186</td></tr><tr><td>paris</td><td>186</td></tr><tr><td>users</td><td>185</td></tr><tr><td>labels</td><td>185</td></tr><tr><td>change</td><td>185</td></tr><tr><td>event</td><td>185</td></tr><tr><td>publisher</td><td>184</td></tr><tr><td>suggest</td><td>184</td></tr><tr><td>classes</td><td>184</td></tr><tr><td>dictionary</td><td>184</td></tr><tr><td>final</td><td>183</td></tr><tr><td>making</td><td>183</td></tr><tr><td>result</td><td>183</td></tr><tr><td>fear</td><td>183</td></tr><tr><td>sci</td><td>183</td></tr><tr><td>james</td><td>183</td></tr><tr><td>academic</td><td>183</td></tr><tr><td>net</td><td>182</td></tr><tr><td>street</td><td>182</td></tr><tr><td>specific</td><td>182</td></tr><tr><td>frontiers</td><td>182</td></tr><tr><td>best</td><td>182</td></tr><tr><td>florida</td><td>181</td></tr><tr><td>impact</td><td>181</td></tr><tr><td>shi</td><td>181</td></tr><tr><td>automated</td><td>181</td></tr><tr><td>annotation</td><td>180</td></tr><tr><td>document</td><td>180</td></tr><tr><td>map</td><td>180</td></tr><tr><td>reduced</td><td>179</td></tr><tr><td>texas</td><td>178</td></tr><tr><td>lausanne</td><td>178</td></tr><tr><td>parameters</td><td>178</td></tr><tr><td>grant</td><td>178</td></tr><tr><td>pain</td><td>178</td></tr><tr><td>john</td><td>177</td></tr><tr><td>demonstrate</td><td>177</td></tr><tr><td>showed</td><td>177</td></tr><tr><td>angeles</td><td>177</td></tr><tr><td>typical</td><td>177</td></tr><tr><td>reference</td><td>176</td></tr><tr><td>cas</td><td>176</td></tr><tr><td>geometry</td><td>176</td></tr><tr><td>society</td><td>176</td></tr><tr><td>direction</td><td>176</td></tr><tr><td>washington</td><td>176</td></tr><tr><td>aware</td><td>175</td></tr><tr><td>basis</td><td>175</td></tr><tr><td>springer</td><td>174</td></tr><tr><td>ming</td><td>174</td></tr><tr><td>liang</td><td>174</td></tr><tr><td>chang</td><td>174</td></tr><tr><td>master</td><td>174</td></tr><tr><td>llment</td><td>174</td></tr><tr><td>etc</td><td>174</td></tr><tr><td>need</td><td>173</td></tr><tr><td>energy</td><td>173</td></tr><tr><td>gait</td><td>173</td></tr><tr><td>technique</td><td>172</td></tr><tr><td>improved</td><td>172</td></tr><tr><td>mouth</td><td>172</td></tr><tr><td>behaviors</td><td>172</td></tr><tr><td>reserved</td><td>172</td></tr><tr><td>sequence</td><td>172</td></tr><tr><td>svm</td><td>172</td></tr><tr><td>jean</td><td>172</td></tr><tr><td>christian</td><td>171</td></tr><tr><td>campus</td><td>171</td></tr><tr><td>eld</td><td>171</td></tr><tr><td>step</td><td>171</td></tr><tr><td>condition</td><td>170</td></tr><tr><td>independent</td><td>170</td></tr><tr><td>gao</td><td>170</td></tr><tr><td>shot</td><td>170</td></tr><tr><td>supported</td><td>169</td></tr><tr><td>feng</td><td>168</td></tr><tr><td>another</td><td>168</td></tr><tr><td>static</td><td>168</td></tr><tr><td>attribution</td><td>168</td></tr><tr><td>patients</td><td>168</td></tr><tr><td>tang</td><td>167</td></tr><tr><td>left</td><td>167</td></tr><tr><td>goal</td><td>167</td></tr><tr><td>grained</td><td>166</td></tr><tr><td>personality</td><td>166</td></tr><tr><td>detecting</td><td>165</td></tr><tr><td>location</td><td>165</td></tr><tr><td>planck</td><td>164</td></tr><tr><td>private</td><td>164</td></tr><tr><td>coding</td><td>164</td></tr><tr><td>dong</td><td>164</td></tr><tr><td>black</td><td>164</td></tr><tr><td>either</td><td>164</td></tr><tr><td>variation</td><td>163</td></tr><tr><td>clinical</td><td>163</td></tr><tr><td>wild</td><td>163</td></tr><tr><td>martin</td><td>162</td></tr><tr><td>boston</td><td>162</td></tr><tr><td>psychological</td><td>162</td></tr><tr><td>nanjing</td><td>162</td></tr><tr><td>light</td><td>162</td></tr><tr><td>paul</td><td>161</td></tr><tr><td>eecs</td><td>161</td></tr><tr><td>developed</td><td>161</td></tr><tr><td>collection</td><td>161</td></tr><tr><td>properties</td><td>161</td></tr><tr><td>include</td><td>161</td></tr><tr><td>environments</td><td>161</td></tr><tr><td>latent</td><td>161</td></tr><tr><td>encoding</td><td>161</td></tr><tr><td>case</td><td>160</td></tr><tr><td>decision</td><td>160</td></tr><tr><td>cameras</td><td>160</td></tr><tr><td>error</td><td>160</td></tr><tr><td>east</td><td>160</td></tr><tr><td>reduction</td><td>160</td></tr><tr><td>interactive</td><td>160</td></tr><tr><td>jia</td><td>160</td></tr><tr><td>brazil</td><td>160</td></tr><tr><td>white</td><td>159</td></tr><tr><td>means</td><td>159</td></tr><tr><td>leuven</td><td>159</td></tr><tr><td>surface</td><td>159</td></tr><tr><td>improving</td><td>159</td></tr><tr><td>flow</td><td>159</td></tr><tr><td>peng</td><td>158</td></tr><tr><td>identify</td><td>158</td></tr><tr><td>unconstrained</td><td>158</td></tr><tr><td>literature</td><td>158</td></tr><tr><td>provides</td><td>158</td></tr><tr><td>dense</td><td>158</td></tr><tr><td>singh</td><td>158</td></tr><tr><td>year</td><td>157</td></tr><tr><td>maryland</td><td>157</td></tr><tr><td>publishing</td><td>157</td></tr><tr><td>generated</td><td>157</td></tr><tr><td>luc</td><td>157</td></tr><tr><td>measure</td><td>157</td></tr><tr><td>physical</td><td>157</td></tr><tr><td>performed</td><td>157</td></tr><tr><td>findings</td><td>156</td></tr><tr><td>free</td><td>156</td></tr><tr><td>mechanisms</td><td>155</td></tr><tr><td>mit</td><td>155</td></tr><tr><td>est</td><td>155</td></tr><tr><td>building</td><td>155</td></tr><tr><td>signals</td><td>155</td></tr><tr><td>capture</td><td>154</td></tr><tr><td>background</td><td>154</td></tr><tr><td>detect</td><td>154</td></tr><tr><td>functions</td><td>154</td></tr><tr><td>stage</td><td>153</td></tr><tr><td>down</td><td>153</td></tr><tr><td>fax</td><td>153</td></tr><tr><td>addition</td><td>153</td></tr><tr><td>pixel</td><td>153</td></tr><tr><td>shows</td><td>153</td></tr><tr><td>han</td><td>153</td></tr><tr><td>developing</td><td>153</td></tr><tr><td>universidad</td><td>153</td></tr><tr><td>cnrs</td><td>153</td></tr><tr><td>good</td><td>152</td></tr><tr><td>mapping</td><td>152</td></tr><tr><td>labeling</td><td>152</td></tr><tr><td>queen</td><td>152</td></tr><tr><td>education</td><td>152</td></tr><tr><td>extract</td><td>152</td></tr><tr><td>georgia</td><td>152</td></tr><tr><td>statistical</td><td>151</td></tr><tr><td>labeled</td><td>151</td></tr><tr><td>mean</td><td>151</td></tr><tr><td>north</td><td>151</td></tr><tr><td>able</td><td>151</td></tr><tr><td>tree</td><td>151</td></tr><tr><td>uses</td><td>151</td></tr><tr><td>represent</td><td>150</td></tr><tr><td>relevant</td><td>150</td></tr><tr><td>lighting</td><td>150</td></tr><tr><td>types</td><td>150</td></tr><tr><td>above</td><td>149</td></tr><tr><td>wide</td><td>149</td></tr><tr><td>levels</td><td>149</td></tr><tr><td>dimensionality</td><td>149</td></tr><tr><td>universitat</td><td>148</td></tr><tr><td>challenges</td><td>148</td></tr><tr><td>unit</td><td>148</td></tr><tr><td>transform</td><td>148</td></tr><tr><td>rgb</td><td>148</td></tr><tr><td>lei</td><td>147</td></tr><tr><td>value</td><td>147</td></tr><tr><td>corporation</td><td>147</td></tr><tr><td>permission</td><td>147</td></tr><tr><td>functioning</td><td>147</td></tr><tr><td>might</td><td>147</td></tr><tr><td>antonio</td><td>147</td></tr><tr><td>optimal</td><td>147</td></tr><tr><td>mark</td><td>146</td></tr><tr><td>ltd</td><td>146</td></tr><tr><td>rather</td><td>146</td></tr><tr><td>division</td><td>146</td></tr><tr><td>iclr</td><td>146</td></tr><tr><td>cse</td><td>146</td></tr><tr><td>correlation</td><td>145</td></tr><tr><td>semi</td><td>145</td></tr><tr><td>child</td><td>145</td></tr><tr><td>authentication</td><td>145</td></tr><tr><td>last</td><td>145</td></tr><tr><td>broad</td><td>145</td></tr><tr><td>affect</td><td>145</td></tr><tr><td>fei</td><td>145</td></tr><tr><td>toronto</td><td>145</td></tr><tr><td>detector</td><td>145</td></tr><tr><td>toward</td><td>145</td></tr><tr><td>institut</td><td>144</td></tr><tr><td>labs</td><td>144</td></tr><tr><td>facebook</td><td>144</td></tr><tr><td>happy</td><td>144</td></tr><tr><td>computation</td><td>143</td></tr><tr><td>xiang</td><td>143</td></tr><tr><td>page</td><td>143</td></tr><tr><td>heterogeneous</td><td>143</td></tr><tr><td>extracted</td><td>143</td></tr><tr><td>researchers</td><td>143</td></tr><tr><td>directly</td><td>143</td></tr><tr><td>optical</td><td>143</td></tr><tr><td>lower</td><td>143</td></tr><tr><td>zero</td><td>143</td></tr><tr><td>karlsruhe</td><td>143</td></tr><tr><td>seoul</td><td>142</td></tr><tr><td>projection</td><td>142</td></tr><tr><td>especially</td><td>142</td></tr><tr><td>tong</td><td>142</td></tr><tr><td>tsinghua</td><td>142</td></tr><tr><td>berlin</td><td>141</td></tr><tr><td>describe</td><td>141</td></tr><tr><td>publications</td><td>141</td></tr><tr><td>your</td><td>141</td></tr><tr><td>description</td><td>141</td></tr><tr><td>ned</td><td>141</td></tr><tr><td>reproduction</td><td>141</td></tr><tr><td>automatically</td><td>140</td></tr><tr><td>measures</td><td>140</td></tr><tr><td>categorization</td><td>140</td></tr><tr><td>jan</td><td>140</td></tr><tr><td>orientation</td><td>140</td></tr><tr><td>american</td><td>140</td></tr><tr><td>ased</td><td>140</td></tr><tr><td>pairs</td><td>140</td></tr><tr><td>landmark</td><td>139</td></tr><tr><td>technological</td><td>139</td></tr><tr><td>mining</td><td>139</td></tr><tr><td>average</td><td>139</td></tr><tr><td>train</td><td>139</td></tr><tr><td>autistic</td><td>139</td></tr><tr><td>scienti</td><td>139</td></tr><tr><td>pixels</td><td>139</td></tr></table></body></html>
\ No newline at end of file diff --git a/scraper/reports/pdf_unknown_trigram.html b/scraper/reports/pdf_unknown_trigram.html index e75d48b3..1ea7b358 100644 --- a/scraper/reports/pdf_unknown_trigram.html +++ b/scraper/reports/pdf_unknown_trigram.html @@ -1 +1 @@ -<!doctype html><html><head><meta charset='utf-8'><title>PDF Report: Unknown Trigrams</title><link rel='stylesheet' href='reports.css'></head><body><h2>PDF Report: Unknown Trigrams</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>of computer science</td><td>646</td></tr><tr><td>department of computer</td><td>501</td></tr><tr><td>computer science and</td><td>312</td></tr><tr><td>institute of technology</td><td>224</td></tr><tr><td>facial expression recognition</td><td>208</td></tr><tr><td>science and engineering</td><td>187</td></tr><tr><td>science and technology</td><td>185</td></tr><tr><td>department of electrical</td><td>179</td></tr><tr><td>carnegie mellon university</td><td>161</td></tr><tr><td>university of california</td><td>144</td></tr><tr><td>for face recognition</td><td>142</td></tr><tr><td>university of technology</td><td>137</td></tr><tr><td>school of computer</td><td>136</td></tr><tr><td>of electrical and</td><td>135</td></tr><tr><td>senior member ieee</td><td>133</td></tr><tr><td>for the degree</td><td>129</td></tr><tr><td>academy of sciences</td><td>128</td></tr><tr><td>of electrical engineering</td><td>125</td></tr><tr><td>member ieee and</td><td>121</td></tr><tr><td>and computer engineering</td><td>112</td></tr><tr><td>of science and</td><td>110</td></tr><tr><td>electrical and computer</td><td>108</td></tr><tr><td>student member ieee</td><td>107</td></tr><tr><td>in the wild</td><td>104</td></tr><tr><td>in this paper</td><td>102</td></tr><tr><td>of the requirements</td><td>90</td></tr><tr><td>doctor of philosophy</td><td>89</td></tr><tr><td>state of the</td><td>86</td></tr><tr><td>of the art</td><td>81</td></tr><tr><td>journal of computer</td><td>81</td></tr><tr><td>and computer science</td><td>78</td></tr><tr><td>dx doi org</td><td>76</td></tr><tr><td>http dx doi</td><td>73</td></tr><tr><td>one of the</td><td>73</td></tr><tr><td>of computer engineering</td><td>71</td></tr><tr><td>requirements for the</td><td>71</td></tr><tr><td>of engineering and</td><td>69</td></tr><tr><td>university of science</td><td>69</td></tr><tr><td>in partial ful</td><td>69</td></tr><tr><td>university of maryland</td><td>68</td></tr><tr><td>college of engineering</td><td>67</td></tr><tr><td>electrical engineering and</td><td>66</td></tr><tr><td>engineering and computer</td><td>65</td></tr><tr><td>partial ful llment</td><td>65</td></tr><tr><td>of hong kong</td><td>64</td></tr><tr><td>proceedings of the</td><td>63</td></tr><tr><td>university of hong</td><td>63</td></tr><tr><td>department of information</td><td>62</td></tr><tr><td>of chinese academy</td><td>62</td></tr><tr><td>face veri cation</td><td>61</td></tr><tr><td>arti cial intelligence</td><td>60</td></tr><tr><td>the requirements for</td><td>58</td></tr><tr><td>should be addressed</td><td>57</td></tr><tr><td>submitted in partial</td><td>57</td></tr><tr><td>facial expression analysis</td><td>56</td></tr><tr><td>face recognition using</td><td>56</td></tr><tr><td>computer science department</td><td>55</td></tr><tr><td>computer vision and</td><td>55</td></tr><tr><td>dept of computer</td><td>55</td></tr><tr><td>of information technology</td><td>54</td></tr><tr><td>for facial expression</td><td>54</td></tr><tr><td>department of psychology</td><td>54</td></tr><tr><td>of information science</td><td>54</td></tr><tr><td>computer science university</td><td>52</td></tr><tr><td>pittsburgh pa usa</td><td>51</td></tr><tr><td>based on the</td><td>51</td></tr><tr><td>the chinese university</td><td>50</td></tr><tr><td>of facial expressions</td><td>49</td></tr><tr><td>llment of the</td><td>49</td></tr><tr><td>imperial college london</td><td>47</td></tr><tr><td>for action recognition</td><td>47</td></tr><tr><td>creative commons attribution</td><td>45</td></tr><tr><td>department of computing</td><td>44</td></tr><tr><td>and information engineering</td><td>44</td></tr><tr><td>of sciences beijing</td><td>44</td></tr><tr><td>human computer interaction</td><td>44</td></tr><tr><td>school of electrical</td><td>43</td></tr><tr><td>department of informatics</td><td>42</td></tr><tr><td>expression recognition using</td><td>42</td></tr><tr><td>will be inserted</td><td>42</td></tr><tr><td>inserted by the</td><td>42</td></tr><tr><td>by the editor</td><td>42</td></tr><tr><td>received date accepted</td><td>42</td></tr><tr><td>date accepted date</td><td>42</td></tr><tr><td>sciences beijing china</td><td>42</td></tr><tr><td>of the face</td><td>41</td></tr><tr><td>school of information</td><td>41</td></tr><tr><td>of maryland college</td><td>40</td></tr><tr><td>maryland college park</td><td>40</td></tr><tr><td>computer science engineering</td><td>40</td></tr><tr><td>of pattern recognition</td><td>40</td></tr><tr><td>convolutional neural networks</td><td>39</td></tr><tr><td>engineering and technology</td><td>39</td></tr><tr><td>of electronics and</td><td>39</td></tr><tr><td>in computer vision</td><td>39</td></tr><tr><td>of computer applications</td><td>39</td></tr><tr><td>of this work</td><td>38</td></tr><tr><td>of computer and</td><td>38</td></tr><tr><td>of face recognition</td><td>38</td></tr><tr><td>university of chinese</td><td>38</td></tr><tr><td>school of computing</td><td>38</td></tr><tr><td>university of surrey</td><td>38</td></tr><tr><td>information science and</td><td>38</td></tr><tr><td>university of illinois</td><td>37</td></tr><tr><td>is an open</td><td>37</td></tr><tr><td>an open access</td><td>37</td></tr><tr><td>the creative commons</td><td>37</td></tr><tr><td>all rights reserved</td><td>37</td></tr><tr><td>faculty of engineering</td><td>37</td></tr><tr><td>university of amsterdam</td><td>37</td></tr><tr><td>submitted to the</td><td>36</td></tr><tr><td>invariant face recognition</td><td>36</td></tr><tr><td>faculty of electrical</td><td>36</td></tr><tr><td>of the most</td><td>36</td></tr><tr><td>department of electronics</td><td>36</td></tr><tr><td>michigan state university</td><td>36</td></tr><tr><td>of information engineering</td><td>36</td></tr><tr><td>university of texas</td><td>35</td></tr><tr><td>laboratory of pattern</td><td>35</td></tr><tr><td>face recognition with</td><td>35</td></tr><tr><td>center for research</td><td>35</td></tr><tr><td>university of thessaloniki</td><td>34</td></tr><tr><td>face recognition system</td><td>34</td></tr><tr><td>open access article</td><td>34</td></tr><tr><td>the original work</td><td>34</td></tr><tr><td>university of oxford</td><td>34</td></tr><tr><td>college of computer</td><td>34</td></tr><tr><td>automatic facial expression</td><td>34</td></tr><tr><td>of california san</td><td>34</td></tr><tr><td>california san diego</td><td>34</td></tr><tr><td>university of southern</td><td>33</td></tr><tr><td>of southern california</td><td>33</td></tr><tr><td>robust face recognition</td><td>33</td></tr><tr><td>to cite this</td><td>33</td></tr><tr><td>provided the original</td><td>33</td></tr><tr><td>institute of computing</td><td>33</td></tr><tr><td>cas beijing china</td><td>33</td></tr><tr><td>https doi org</td><td>32</td></tr><tr><td>master of science</td><td>32</td></tr><tr><td>based face recognition</td><td>32</td></tr><tr><td>work is properly</td><td>32</td></tr><tr><td>science and information</td><td>32</td></tr><tr><td>institute of automation</td><td>32</td></tr><tr><td>due to the</td><td>32</td></tr><tr><td>journal of engineering</td><td>32</td></tr><tr><td>face detection and</td><td>31</td></tr><tr><td>in face recognition</td><td>31</td></tr><tr><td>luc van gool</td><td>31</td></tr><tr><td>institute of information</td><td>31</td></tr><tr><td>institute of science</td><td>31</td></tr><tr><td>under the creative</td><td>31</td></tr><tr><td>reproduction in any</td><td>31</td></tr><tr><td>max planck institute</td><td>31</td></tr><tr><td>university of singapore</td><td>31</td></tr><tr><td>has been accepted</td><td>31</td></tr><tr><td>been accepted for</td><td>31</td></tr><tr><td>access article distributed</td><td>30</td></tr><tr><td>article distributed under</td><td>30</td></tr><tr><td>distributed under the</td><td>30</td></tr><tr><td>permits unrestricted use</td><td>30</td></tr><tr><td>in any medium</td><td>30</td></tr><tr><td>any medium provided</td><td>30</td></tr><tr><td>medium provided the</td><td>30</td></tr><tr><td>planck institute for</td><td>30</td></tr><tr><td>university of central</td><td>30</td></tr><tr><td>university college london</td><td>30</td></tr><tr><td>of intelligent information</td><td>29</td></tr><tr><td>which permits unrestricted</td><td>29</td></tr><tr><td>unrestricted use distribution</td><td>29</td></tr><tr><td>use distribution and</td><td>29</td></tr><tr><td>distribution and reproduction</td><td>29</td></tr><tr><td>and information technology</td><td>29</td></tr><tr><td>it has been</td><td>29</td></tr><tr><td>convolutional neural network</td><td>29</td></tr><tr><td>university of washington</td><td>29</td></tr><tr><td>journal of advanced</td><td>28</td></tr><tr><td>institute for informatics</td><td>28</td></tr><tr><td>of psychology university</td><td>28</td></tr><tr><td>cambridge ma usa</td><td>28</td></tr><tr><td>department of engineering</td><td>28</td></tr><tr><td>of computing technology</td><td>28</td></tr><tr><td>university of london</td><td>28</td></tr><tr><td>university beijing china</td><td>28</td></tr><tr><td>lab of intelligent</td><td>27</td></tr><tr><td>in computer science</td><td>27</td></tr><tr><td>image and video</td><td>27</td></tr><tr><td>article id pages</td><td>27</td></tr><tr><td>commons attribution license</td><td>27</td></tr><tr><td>is properly cited</td><td>27</td></tr><tr><td>of automation chinese</td><td>27</td></tr><tr><td>automation chinese academy</td><td>27</td></tr><tr><td>can be used</td><td>27</td></tr><tr><td>part of the</td><td>27</td></tr><tr><td>support vector machine</td><td>27</td></tr><tr><td>face recognition under</td><td>27</td></tr><tr><td>universit at unchen</td><td>27</td></tr><tr><td>deep neural networks</td><td>27</td></tr><tr><td>of central florida</td><td>27</td></tr><tr><td>computer and information</td><td>27</td></tr><tr><td>and pattern recognition</td><td>26</td></tr><tr><td>of facial expression</td><td>26</td></tr><tr><td>recognition in the</td><td>26</td></tr><tr><td>of information and</td><td>26</td></tr><tr><td>department of mathematics</td><td>26</td></tr><tr><td>intelligent information processing</td><td>25</td></tr><tr><td>illinois at urbana</td><td>25</td></tr><tr><td>at urbana champaign</td><td>25</td></tr><tr><td>journal on image</td><td>25</td></tr><tr><td>university of massachusetts</td><td>25</td></tr><tr><td>faces in the</td><td>25</td></tr><tr><td>university of pittsburgh</td><td>25</td></tr><tr><td>latex class files</td><td>25</td></tr><tr><td>image processing and</td><td>25</td></tr><tr><td>and signal processing</td><td>25</td></tr><tr><td>of technology sydney</td><td>25</td></tr><tr><td>head pose estimation</td><td>25</td></tr><tr><td>university of tokyo</td><td>25</td></tr><tr><td>national taiwan university</td><td>25</td></tr><tr><td>recognition of facial</td><td>25</td></tr><tr><td>online at www</td><td>24</td></tr><tr><td>center for automation</td><td>24</td></tr><tr><td>for automation research</td><td>24</td></tr><tr><td>computer vision center</td><td>24</td></tr><tr><td>whether they are</td><td>24</td></tr><tr><td>may come from</td><td>24</td></tr><tr><td>dept of electrical</td><td>24</td></tr><tr><td>in this work</td><td>24</td></tr><tr><td>computing technology cas</td><td>24</td></tr><tr><td>technology cas beijing</td><td>24</td></tr><tr><td>speech and signal</td><td>24</td></tr><tr><td>and electronic engineering</td><td>24</td></tr><tr><td>of massachusetts amherst</td><td>24</td></tr><tr><td>journal of latex</td><td>24</td></tr><tr><td>of latex class</td><td>24</td></tr><tr><td>pose invariant face</td><td>23</td></tr><tr><td>technology of china</td><td>23</td></tr><tr><td>cite this version</td><td>23</td></tr><tr><td>hal is multi</td><td>23</td></tr><tr><td>is multi disciplinary</td><td>23</td></tr><tr><td>multi disciplinary open</td><td>23</td></tr><tr><td>disciplinary open access</td><td>23</td></tr><tr><td>rchive for the</td><td>23</td></tr><tr><td>for the deposit</td><td>23</td></tr><tr><td>the deposit and</td><td>23</td></tr><tr><td>deposit and dissemination</td><td>23</td></tr><tr><td>dissemination of sci</td><td>23</td></tr><tr><td>research documents whether</td><td>23</td></tr><tr><td>documents whether they</td><td>23</td></tr><tr><td>they are pub</td><td>23</td></tr><tr><td>lished or not</td><td>23</td></tr><tr><td>or not the</td><td>23</td></tr><tr><td>not the documents</td><td>23</td></tr><tr><td>the documents may</td><td>23</td></tr><tr><td>documents may come</td><td>23</td></tr><tr><td>teaching and research</td><td>23</td></tr><tr><td>and research institutions</td><td>23</td></tr><tr><td>institutions in france</td><td>23</td></tr><tr><td>broad or from</td><td>23</td></tr><tr><td>or from public</td><td>23</td></tr><tr><td>public or private</td><td>23</td></tr><tr><td>or private research</td><td>23</td></tr><tr><td>private research centers</td><td>23</td></tr><tr><td>archive ouverte pluridisciplinaire</td><td>23</td></tr><tr><td>ouverte pluridisciplinaire hal</td><td>23</td></tr><tr><td>pluridisciplinaire hal est</td><td>23</td></tr><tr><td>et la diffusion</td><td>23</td></tr><tr><td>diffusion de documents</td><td>23</td></tr><tr><td>de niveau recherche</td><td>23</td></tr><tr><td>niveau recherche publi</td><td>23</td></tr><tr><td>publics ou priv</td><td>23</td></tr><tr><td>hindawi publishing corporation</td><td>23</td></tr><tr><td>et al this</td><td>23</td></tr><tr><td>have been proposed</td><td>23</td></tr><tr><td>of engineering science</td><td>23</td></tr><tr><td>class files vol</td><td>23</td></tr><tr><td>queen mary university</td><td>23</td></tr><tr><td>such as the</td><td>23</td></tr><tr><td>information engineering the</td><td>23</td></tr><tr><td>engineering the chinese</td><td>23</td></tr><tr><td>computer vision lab</td><td>22</td></tr><tr><td>video classi cation</td><td>22</td></tr><tr><td>of computer vision</td><td>22</td></tr><tr><td>paper we propose</td><td>22</td></tr><tr><td>facial emotion recognition</td><td>22</td></tr><tr><td>this article was</td><td>22</td></tr><tr><td>www frontiersin org</td><td>22</td></tr><tr><td>university of pennsylvania</td><td>22</td></tr><tr><td>processing of chinese</td><td>22</td></tr><tr><td>university of toronto</td><td>22</td></tr><tr><td>the proposed method</td><td>22</td></tr><tr><td>amsterdam the netherlands</td><td>22</td></tr><tr><td>nanyang technological university</td><td>22</td></tr><tr><td>of california berkeley</td><td>22</td></tr><tr><td>electrical computer engineering</td><td>21</td></tr><tr><td>link to publication</td><td>21</td></tr><tr><td>facial action unit</td><td>21</td></tr><tr><td>of advanced technology</td><td>21</td></tr><tr><td>institute carnegie mellon</td><td>21</td></tr><tr><td>face recognition based</td><td>21</td></tr><tr><td>end to end</td><td>21</td></tr><tr><td>to improve the</td><td>21</td></tr><tr><td>department of electronic</td><td>21</td></tr><tr><td>electrical and electronic</td><td>21</td></tr><tr><td>this article has</td><td>21</td></tr><tr><td>article has been</td><td>21</td></tr><tr><td>university of twente</td><td>20</td></tr><tr><td>institute of engineering</td><td>20</td></tr><tr><td>principal component analysis</td><td>20</td></tr><tr><td>mathematics and computer</td><td>20</td></tr><tr><td>active appearance models</td><td>20</td></tr><tr><td>some of the</td><td>20</td></tr><tr><td>institutes of advanced</td><td>20</td></tr><tr><td>springer science business</td><td>20</td></tr><tr><td>science business media</td><td>20</td></tr><tr><td>local binary pattern</td><td>20</td></tr><tr><td>gender classi cation</td><td>20</td></tr><tr><td>in real time</td><td>20</td></tr><tr><td>texas at austin</td><td>20</td></tr><tr><td>research in computer</td><td>20</td></tr><tr><td>facial landmark localization</td><td>20</td></tr><tr><td>and communication engineering</td><td>20</td></tr><tr><td>pattern analysis and</td><td>20</td></tr><tr><td>shanghai jiao tong</td><td>20</td></tr><tr><td>degree of doctor</td><td>20</td></tr><tr><td>in recent years</td><td>20</td></tr><tr><td>in future issue</td><td>20</td></tr><tr><td>issue of this</td><td>20</td></tr><tr><td>of this journal</td><td>20</td></tr><tr><td>accepted for publication</td><td>20</td></tr><tr><td>of electrical computer</td><td>19</td></tr><tr><td>mellon university pittsburgh</td><td>19</td></tr><tr><td>australian national university</td><td>19</td></tr><tr><td>use of this</td><td>19</td></tr><tr><td>of this material</td><td>19</td></tr><tr><td>material is permitted</td><td>19</td></tr><tr><td>servers or lists</td><td>19</td></tr><tr><td>school of engineering</td><td>19</td></tr><tr><td>university of michigan</td><td>19</td></tr><tr><td>as conference paper</td><td>19</td></tr><tr><td>paper at iclr</td><td>19</td></tr><tr><td>robotics institute carnegie</td><td>19</td></tr><tr><td>local binary patterns</td><td>19</td></tr><tr><td>prof dr ing</td><td>19</td></tr><tr><td>idiap research institute</td><td>19</td></tr><tr><td>of sciences cas</td><td>19</td></tr><tr><td>of the twenty</td><td>19</td></tr><tr><td>international joint conference</td><td>19</td></tr><tr><td>show that the</td><td>19</td></tr><tr><td>human action recognition</td><td>19</td></tr><tr><td>ieee international conference</td><td>19</td></tr><tr><td>for face detection</td><td>19</td></tr><tr><td>on pattern analysis</td><td>19</td></tr><tr><td>analysis and machine</td><td>19</td></tr><tr><td>and machine intelligence</td><td>19</td></tr><tr><td>jiao tong university</td><td>19</td></tr><tr><td>of the same</td><td>19</td></tr><tr><td>university of posts</td><td>19</td></tr><tr><td>of posts and</td><td>19</td></tr><tr><td>department of statistics</td><td>19</td></tr><tr><td>de la torre</td><td>18</td></tr><tr><td>follow this and</td><td>18</td></tr><tr><td>this and additional</td><td>18</td></tr><tr><td>and additional works</td><td>18</td></tr><tr><td>accepted for inclusion</td><td>18</td></tr><tr><td>terms of use</td><td>18</td></tr><tr><td>this material for</td><td>18</td></tr><tr><td>material for advertising</td><td>18</td></tr><tr><td>redistribution to servers</td><td>18</td></tr><tr><td>vol no august</td><td>18</td></tr><tr><td>this is the</td><td>18</td></tr><tr><td>university of oulu</td><td>18</td></tr><tr><td>analysis of facial</td><td>18</td></tr><tr><td>article was submitted</td><td>18</td></tr><tr><td>university of cambridge</td><td>18</td></tr><tr><td>simon fraser university</td><td>18</td></tr><tr><td>tel aviv university</td><td>18</td></tr><tr><td>the robotics institute</td><td>18</td></tr><tr><td>university of north</td><td>18</td></tr><tr><td>university of wollongong</td><td>18</td></tr><tr><td>brought to you</td><td>17</td></tr><tr><td>to you for</td><td>17</td></tr><tr><td>you for free</td><td>17</td></tr><tr><td>for free and</td><td>17</td></tr><tr><td>free and open</td><td>17</td></tr><tr><td>and open access</td><td>17</td></tr><tr><td>ieee personal use</td><td>17</td></tr><tr><td>in partial fulfillment</td><td>17</td></tr><tr><td>of mathematics and</td><td>17</td></tr><tr><td>on image and</td><td>17</td></tr><tr><td>erik learned miller</td><td>17</td></tr><tr><td>research center for</td><td>17</td></tr><tr><td>face recognition systems</td><td>17</td></tr><tr><td>we propose novel</td><td>17</td></tr><tr><td>results show that</td><td>17</td></tr><tr><td>xi an china</td><td>17</td></tr><tr><td>of computing and</td><td>17</td></tr><tr><td>facebook ai research</td><td>17</td></tr><tr><td>universit degli studi</td><td>17</td></tr><tr><td>to this work</td><td>17</td></tr><tr><td>dept of cse</td><td>17</td></tr><tr><td>face recognition from</td><td>17</td></tr><tr><td>sun yat sen</td><td>17</td></tr><tr><td>and electrical engineering</td><td>17</td></tr><tr><td>on computer vision</td><td>17</td></tr><tr><td>and computer vision</td><td>17</td></tr><tr><td>new collective works</td><td>17</td></tr><tr><td>collective works for</td><td>17</td></tr><tr><td>transactions on pattern</td><td>17</td></tr><tr><td>to whom correspondence</td><td>17</td></tr><tr><td>posts and telecommunications</td><td>17</td></tr><tr><td>section of the</td><td>17</td></tr><tr><td>of north carolina</td><td>17</td></tr><tr><td>th international conference</td><td>17</td></tr><tr><td>and information sciences</td><td>17</td></tr><tr><td>linear discriminant analysis</td><td>17</td></tr><tr><td>journal of information</td><td>17</td></tr><tr><td>frontiers in psychology</td><td>17</td></tr><tr><td>neural networks for</td><td>16</td></tr><tr><td>works at http</td><td>16</td></tr><tr><td>by an authorized</td><td>16</td></tr><tr><td>in accordance with</td><td>16</td></tr><tr><td>in other works</td><td>16</td></tr><tr><td>http hdl handle</td><td>16</td></tr><tr><td>hdl handle net</td><td>16</td></tr><tr><td>fulfillment of the</td><td>16</td></tr><tr><td>ming hsuan yang</td><td>16</td></tr><tr><td>and video processing</td><td>16</td></tr><tr><td>for more information</td><td>16</td></tr><tr><td>for face veri</td><td>16</td></tr><tr><td>expression recognition based</td><td>16</td></tr><tr><td>and intelligent systems</td><td>16</td></tr><tr><td>image classi cation</td><td>16</td></tr><tr><td>most of the</td><td>16</td></tr><tr><td>real world applications</td><td>16</td></tr><tr><td>face recognition has</td><td>16</td></tr><tr><td>from face images</td><td>16</td></tr><tr><td>face identi cation</td><td>16</td></tr><tr><td>is an important</td><td>16</td></tr><tr><td>on artificial intelligence</td><td>16</td></tr><tr><td>of the university</td><td>16</td></tr><tr><td>of electronic and</td><td>16</td></tr><tr><td>wang member ieee</td><td>16</td></tr><tr><td>and anil jain</td><td>16</td></tr><tr><td>and rama chellappa</td><td>16</td></tr><tr><td>and engineering university</td><td>16</td></tr><tr><td>electronics and communication</td><td>16</td></tr><tr><td>of electronic engineering</td><td>16</td></tr><tr><td>face recognition and</td><td>16</td></tr><tr><td>whom correspondence should</td><td>16</td></tr><tr><td>the hong kong</td><td>16</td></tr><tr><td>department of cse</td><td>16</td></tr><tr><td>hong kong china</td><td>16</td></tr><tr><td>publication in future</td><td>16</td></tr><tr><td>this journal 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bristol</td><td>15</td></tr><tr><td>creating new collective</td><td>15</td></tr><tr><td>facial landmark detection</td><td>15</td></tr><tr><td>laboratory of intelligent</td><td>15</td></tr><tr><td>www intechopen com</td><td>15</td></tr><tr><td>conference on artificial</td><td>15</td></tr><tr><td>for arti cial</td><td>15</td></tr><tr><td>feature extraction and</td><td>15</td></tr><tr><td>microsoft research asia</td><td>15</td></tr><tr><td>and mobile computing</td><td>15</td></tr><tr><td>the fact that</td><td>15</td></tr><tr><td>expression recognition with</td><td>15</td></tr><tr><td>and facial expression</td><td>15</td></tr><tr><td>zhang member ieee</td><td>15</td></tr><tr><td>for face alignment</td><td>15</td></tr><tr><td>of the data</td><td>15</td></tr><tr><td>of the journal</td><td>15</td></tr><tr><td>of the main</td><td>15</td></tr><tr><td>on the other</td><td>15</td></tr><tr><td>the other hand</td><td>15</td></tr><tr><td>for vision speech</td><td>15</td></tr><tr><td>vision speech 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supervised learning</td><td>14</td></tr><tr><td>institute of computer</td><td>14</td></tr><tr><td>component of this</td><td>14</td></tr><tr><td>department of psychiatry</td><td>14</td></tr><tr><td>research on intelligent</td><td>14</td></tr><tr><td>on intelligent perception</td><td>14</td></tr><tr><td>intelligent perception and</td><td>14</td></tr><tr><td>perception and computing</td><td>14</td></tr><tr><td>in brain science</td><td>14</td></tr><tr><td>brain science and</td><td>14</td></tr><tr><td>report no ucb</td><td>13</td></tr><tr><td>no ucb eecs</td><td>13</td></tr><tr><td>www eecs berkeley</td><td>13</td></tr><tr><td>eecs berkeley edu</td><td>13</td></tr><tr><td>berkeley edu pubs</td><td>13</td></tr><tr><td>edu pubs techrpts</td><td>13</td></tr><tr><td>pubs techrpts eecs</td><td>13</td></tr><tr><td>techrpts eecs html</td><td>13</td></tr><tr><td>performance of face</td><td>13</td></tr><tr><td>we show that</td><td>13</td></tr><tr><td>university shanghai china</td><td>13</td></tr><tr><td>and ioannis pitas</td><td>13</td></tr><tr><td>peer reviewed version</td><td>13</td></tr><tr><td>or promotional purposes</td><td>13</td></tr><tr><td>works for resale</td><td>13</td></tr><tr><td>resale or redistribution</td><td>13</td></tr><tr><td>journal of science</td><td>13</td></tr><tr><td>university of defense</td><td>13</td></tr><tr><td>anil jain fellow</td><td>13</td></tr><tr><td>jain fellow ieee</td><td>13</td></tr><tr><td>more information please</td><td>13</td></tr><tr><td>entific research documents</td><td>13</td></tr><tr><td>scientifiques de niveau</td><td>13</td></tr><tr><td>publi ou non</td><td>13</td></tr><tr><td>manant des tablissements</td><td>13</td></tr><tr><td>des tablissements enseignement</td><td>13</td></tr><tr><td>recherche fran ais</td><td>13</td></tr><tr><td>ais ou trangers</td><td>13</td></tr><tr><td>ou trangers des</td><td>13</td></tr><tr><td>trangers des laboratoires</td><td>13</td></tr><tr><td>face recognition algorithms</td><td>13</td></tr><tr><td>the face recognition</td><td>13</td></tr><tr><td>recognition in videos</td><td>13</td></tr><tr><td>institute of advanced</td><td>13</td></tr><tr><td>of advanced computer</td><td>13</td></tr><tr><td>for real time</td><td>13</td></tr><tr><td>to solve the</td><td>13</td></tr><tr><td>of oulu finland</td><td>13</td></tr><tr><td>support vector machines</td><td>13</td></tr><tr><td>johns hopkins university</td><td>13</td></tr><tr><td>engineering research and</td><td>13</td></tr><tr><td>detection and recognition</td><td>13</td></tr><tr><td>according to the</td><td>13</td></tr><tr><td>submitted for the</td><td>13</td></tr><tr><td>of the image</td><td>13</td></tr><tr><td>college of information</td><td>13</td></tr><tr><td>technology chinese academy</td><td>13</td></tr><tr><td>itet eth zurich</td><td>13</td></tr><tr><td>methods have been</td><td>13</td></tr><tr><td>computer vision group</td><td>13</td></tr><tr><td>neural network for</td><td>13</td></tr><tr><td>queen university belfast</td><td>13</td></tr><tr><td>university of notre</td><td>13</td></tr><tr><td>of notre dame</td><td>13</td></tr><tr><td>of engineering technology</td><td>13</td></tr><tr><td>human robot interaction</td><td>13</td></tr><tr><td>information technology and</td><td>13</td></tr><tr><td>on facial expression</td><td>13</td></tr><tr><td>author to whom</td><td>13</td></tr><tr><td>be addressed mail</td><td>13</td></tr><tr><td>for classi cation</td><td>13</td></tr><tr><td>berkeley ca usa</td><td>13</td></tr><tr><td>kong polytechnic university</td><td>13</td></tr><tr><td>rensselaer polytechnic institute</td><td>13</td></tr><tr><td>of michigan ann</td><td>13</td></tr><tr><td>of biomedical engineering</td><td>13</td></tr><tr><td>unconstrained face recognition</td><td>13</td></tr><tr><td>electrical and electronics</td><td>13</td></tr><tr><td>for all other</td><td>13</td></tr><tr><td>classi cation with</td><td>13</td></tr><tr><td>der technischen universit</td><td>13</td></tr><tr><td>zur erlangung des</td><td>13</td></tr><tr><td>of face images</td><td>13</td></tr><tr><td>politehnica of bucharest</td><td>13</td></tr><tr><td>of the proposed</td><td>13</td></tr><tr><td>human activity recognition</td><td>13</td></tr><tr><td>university istanbul turkey</td><td>13</td></tr><tr><td>af nity matrix</td><td>13</td></tr><tr><td>recognition in video</td><td>12</td></tr><tr><td>yu gang jiang</td><td>12</td></tr><tr><td>of nebraska lincoln</td><td>12</td></tr><tr><td>if you believe</td><td>12</td></tr><tr><td>version of the</td><td>12</td></tr><tr><td>application to face</td><td>12</td></tr><tr><td>of defense technology</td><td>12</td></tr><tr><td>computer engineering department</td><td>12</td></tr><tr><td>polytechnique ed erale</td><td>12</td></tr><tr><td>the author and</td><td>12</td></tr><tr><td>hal id hal</td><td>12</td></tr><tr><td>university nanjing china</td><td>12</td></tr><tr><td>is the author</td><td>12</td></tr><tr><td>and face recognition</td><td>12</td></tr><tr><td>because of the</td><td>12</td></tr><tr><td>advanced computer science</td><td>12</td></tr><tr><td>real time face</td><td>12</td></tr><tr><td>illumination invariant face</td><td>12</td></tr><tr><td>electronics and information</td><td>12</td></tr><tr><td>refers to the</td><td>12</td></tr><tr><td>and classi cation</td><td>12</td></tr><tr><td>processing and analysis</td><td>12</td></tr><tr><td>facial expressions are</td><td>12</td></tr><tr><td>shiguang shan xilin</td><td>12</td></tr><tr><td>shan xilin chen</td><td>12</td></tr><tr><td>of new york</td><td>12</td></tr><tr><td>work was supported</td><td>12</td></tr><tr><td>supported by the</td><td>12</td></tr><tr><td>recognition under varying</td><td>12</td></tr><tr><td>pattern recognition and</td><td>12</td></tr><tr><td>video face recognition</td><td>12</td></tr><tr><td>computer engineering national</td><td>12</td></tr><tr><td>classi cation using</td><td>12</td></tr><tr><td>the facial expression</td><td>12</td></tr><tr><td>low rank representation</td><td>12</td></tr><tr><td>received april accepted</td><td>12</td></tr><tr><td>based on local</td><td>12</td></tr><tr><td>facial expression classification</td><td>12</td></tr><tr><td>university belfast research</td><td>12</td></tr><tr><td>belfast research portal</td><td>12</td></tr><tr><td>taiwan university taipei</td><td>12</td></tr><tr><td>university taipei taiwan</td><td>12</td></tr><tr><td>permission from ieee</td><td>12</td></tr><tr><td>reuse of any</td><td>12</td></tr><tr><td>university of ljubljana</td><td>12</td></tr><tr><td>shown in figure</td><td>12</td></tr><tr><td>this paper presents</td><td>12</td></tr><tr><td>there are many</td><td>12</td></tr><tr><td>in revised form</td><td>12</td></tr><tr><td>of facial images</td><td>12</td></tr><tr><td>hong kong university</td><td>12</td></tr><tr><td>re identi cation</td><td>12</td></tr><tr><td>michigan ann arbor</td><td>12</td></tr><tr><td>conference on arti</td><td>12</td></tr><tr><td>to the same</td><td>12</td></tr><tr><td>facial action units</td><td>12</td></tr><tr><td>arizona state university</td><td>12</td></tr><tr><td>islamic azad university</td><td>12</td></tr><tr><td>information please contact</td><td>12</td></tr><tr><td>natural language processing</td><td>12</td></tr><tr><td>we use the</td><td>12</td></tr><tr><td>of the human</td><td>12</td></tr><tr><td>of arti cial</td><td>12</td></tr><tr><td>university of groningen</td><td>12</td></tr><tr><td>heterogeneous face recognition</td><td>12</td></tr><tr><td>louis philippe morency</td><td>12</td></tr><tr><td>philadelphia pa usa</td><td>12</td></tr><tr><td>final publication citation</td><td>12</td></tr><tr><td>houston tx usa</td><td>11</td></tr><tr><td>this work for</td><td>11</td></tr><tr><td>and maja pantic</td><td>11</td></tr><tr><td>explore bristol research</td><td>11</td></tr><tr><td>obtained from the</td><td>11</td></tr><tr><td>to the department</td><td>11</td></tr><tr><td>to face recognition</td><td>11</td></tr><tr><td>erale de lausanne</td><td>11</td></tr><tr><td>shenzhen key lab</td><td>11</td></tr><tr><td>received december accepted</td><td>11</td></tr><tr><td>and jeffrey cohn</td><td>11</td></tr><tr><td>watson research center</td><td>11</td></tr><tr><td>for age estimation</td><td>11</td></tr><tr><td>in real world</td><td>11</td></tr><tr><td>biometrics and security</td><td>11</td></tr><tr><td>faculty of information</td><td>11</td></tr><tr><td>published as conference</td><td>11</td></tr><tr><td>of engineering research</td><td>11</td></tr><tr><td>ability to recognize</td><td>11</td></tr><tr><td>on face recognition</td><td>11</td></tr><tr><td>expression recognition system</td><td>11</td></tr><tr><td>computer engineering university</td><td>11</td></tr><tr><td>terms of the</td><td>11</td></tr><tr><td>that has been</td><td>11</td></tr><tr><td>can be found</td><td>11</td></tr><tr><td>citation for published</td><td>11</td></tr><tr><td>it is not</td><td>11</td></tr><tr><td>electrical engineering university</td><td>11</td></tr><tr><td>stony brook university</td><td>11</td></tr><tr><td>ieee and anil</td><td>11</td></tr><tr><td>in the eld</td><td>11</td></tr><tr><td>have been developed</td><td>11</td></tr><tr><td>of computing imperial</td><td>11</td></tr><tr><td>computing imperial college</td><td>11</td></tr><tr><td>in the scene</td><td>11</td></tr><tr><td>of applied sciences</td><td>11</td></tr><tr><td>school of electronic</td><td>11</td></tr><tr><td>electronic and information</td><td>11</td></tr><tr><td>chen change loy</td><td>11</td></tr><tr><td>research showcase cmu</td><td>11</td></tr><tr><td>fr ed eric</td><td>11</td></tr><tr><td>ed eric jurie</td><td>11</td></tr><tr><td>faculty of science</td><td>11</td></tr><tr><td>in any current</td><td>11</td></tr><tr><td>state university east</td><td>11</td></tr><tr><td>university east lansing</td><td>11</td></tr><tr><td>lansing mi usa</td><td>11</td></tr><tr><td>university of houston</td><td>11</td></tr><tr><td>machine learning techniques</td><td>11</td></tr><tr><td>that the proposed</td><td>11</td></tr><tr><td>www mdpi com</td><td>11</td></tr><tr><td>mdpi com journal</td><td>11</td></tr><tr><td>computational intelligence and</td><td>11</td></tr><tr><td>dept of computing</td><td>11</td></tr><tr><td>box thessaloniki greece</td><td>11</td></tr><tr><td>school of automation</td><td>11</td></tr><tr><td>in the face</td><td>11</td></tr><tr><td>university of wisconsin</td><td>11</td></tr><tr><td>brain and cognitive</td><td>11</td></tr><tr><td>cial intelligence ijcai</td><td>11</td></tr><tr><td>in partial satisfaction</td><td>11</td></tr><tr><td>volume issue may</td><td>11</td></tr><tr><td>in human computer</td><td>11</td></tr><tr><td>information about this</td><td>11</td></tr><tr><td>university of colorado</td><td>11</td></tr><tr><td>erlangung des akademischen</td><td>11</td></tr><tr><td>des akademischen grades</td><td>11</td></tr><tr><td>the main paper</td><td>11</td></tr><tr><td>hand over face</td><td>11</td></tr><tr><td>tadas baltru saitis</td><td>11</td></tr><tr><td>ur elektrotechnik und</td><td>11</td></tr><tr><td>elektrotechnik und informationstechnik</td><td>11</td></tr><tr><td>computer science the</td><td>11</td></tr><tr><td>publication citation information</td><td>11</td></tr><tr><td>citation information doi</td><td>11</td></tr><tr><td>of advanced research</td><td>10</td></tr><tr><td>and information systems</td><td>10</td></tr><tr><td>to publication record</td><td>10</td></tr><tr><td>take down policy</td><td>10</td></tr><tr><td>you believe that</td><td>10</td></tr><tr><td>science and research</td><td>10</td></tr><tr><td>for pose invariant</td><td>10</td></tr><tr><td>deep face recognition</td><td>10</td></tr><tr><td>pattern recognition casia</td><td>10</td></tr><tr><td>learning for face</td><td>10</td></tr><tr><td>ouvertes fr hal</td><td>10</td></tr><tr><td>southeast university nanjing</td><td>10</td></tr><tr><td>in pattern recognition</td><td>10</td></tr><tr><td>ibm watson research</td><td>10</td></tr><tr><td>of advanced industrial</td><td>10</td></tr><tr><td>in the literature</td><td>10</td></tr><tr><td>representation of the</td><td>10</td></tr><tr><td>vision center uab</td><td>10</td></tr><tr><td>center for biometrics</td><td>10</td></tr><tr><td>for biometrics and</td><td>10</td></tr><tr><td>and security research</td><td>10</td></tr><tr><td>is licensed under</td><td>10</td></tr><tr><td>creativecommons org licenses</td><td>10</td></tr><tr><td>received june accepted</td><td>10</td></tr><tr><td>have shown that</td><td>10</td></tr><tr><td>regression for face</td><td>10</td></tr><tr><td>jean luc dugelay</td><td>10</td></tr><tr><td>computer interaction hci</td><td>10</td></tr><tr><td>is that the</td><td>10</td></tr><tr><td>additional key words</td><td>10</td></tr><tr><td>key words and</td><td>10</td></tr><tr><td>words and phrases</td><td>10</td></tr><tr><td>of our 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expression</td><td>10</td></tr><tr><td>retained by the</td><td>10</td></tr><tr><td>has been made</td><td>10</td></tr><tr><td>on automatic face</td><td>10</td></tr><tr><td>from ieee must</td><td>10</td></tr><tr><td>obtained for all</td><td>10</td></tr><tr><td>republishing this material</td><td>10</td></tr><tr><td>promotional purposes creating</td><td>10</td></tr><tr><td>machine intelligence vol</td><td>10</td></tr><tr><td>advanced technology chinese</td><td>10</td></tr><tr><td>detection in the</td><td>10</td></tr><tr><td>college of technology</td><td>10</td></tr><tr><td>to the faculty</td><td>10</td></tr><tr><td>forbes avenue pittsburgh</td><td>10</td></tr><tr><td>in the image</td><td>10</td></tr><tr><td>science and applications</td><td>10</td></tr><tr><td>facial image analysis</td><td>10</td></tr><tr><td>and technology tsinghua</td><td>10</td></tr><tr><td>technology tsinghua university</td><td>10</td></tr><tr><td>the art methods</td><td>10</td></tr><tr><td>to predict the</td><td>10</td></tr><tr><td>association for computational</td><td>10</td></tr><tr><td>for computational linguistics</td><td>10</td></tr><tr><td>robotics and intelligent</td><td>10</td></tr><tr><td>of wisconsin madison</td><td>10</td></tr><tr><td>department of biomedical</td><td>10</td></tr><tr><td>visual geometry group</td><td>10</td></tr><tr><td>business media llc</td><td>10</td></tr><tr><td>and arti cial</td><td>10</td></tr><tr><td>structure of the</td><td>10</td></tr><tr><td>action coding system</td><td>10</td></tr><tr><td>in the training</td><td>10</td></tr><tr><td>is de ned</td><td>10</td></tr><tr><td>shown in the</td><td>10</td></tr><tr><td>due to its</td><td>10</td></tr><tr><td>accepted june published</td><td>10</td></tr><tr><td>https hal archives</td><td>10</td></tr><tr><td>hal archives ouvertes</td><td>10</td></tr><tr><td>of automatic control</td><td>10</td></tr><tr><td>the most popular</td><td>10</td></tr><tr><td>beijing jiaotong university</td><td>10</td></tr><tr><td>park md usa</td><td>10</td></tr><tr><td>seattle wa usa</td><td>10</td></tr><tr><td>in this section</td><td>10</td></tr><tr><td>deep learning for</td><td>10</td></tr><tr><td>the human face</td><td>10</td></tr><tr><td>pose and illumination</td><td>10</td></tr><tr><td>study of the</td><td>10</td></tr><tr><td>automatic face recognition</td><td>10</td></tr><tr><td>component analysis pca</td><td>10</td></tr><tr><td>at ur elektrotechnik</td><td>10</td></tr><tr><td>generative adversarial networks</td><td>10</td></tr><tr><td>white rose research</td><td>10</td></tr><tr><td>technological university singapore</td><td>10</td></tr><tr><td>in the main</td><td>10</td></tr><tr><td>metric learning for</td><td>10</td></tr><tr><td>people with schizophrenia</td><td>10</td></tr><tr><td>nec laboratories america</td><td>9</td></tr><tr><td>texas at arlington</td><td>9</td></tr><tr><td>acm reference format</td><td>9</td></tr><tr><td>republic of korea</td><td>9</td></tr><tr><td>for video classi</td><td>9</td></tr><tr><td>is made available</td><td>9</td></tr><tr><td>nature of the</td><td>9</td></tr><tr><td>any copyrighted component</td><td>9</td></tr><tr><td>and research ijsr</td><td>9</td></tr><tr><td>on systems man</td><td>9</td></tr><tr><td>man and cybernetics</td><td>9</td></tr><tr><td>and cybernetics part</td><td>9</td></tr><tr><td>rwth aachen university</td><td>9</td></tr><tr><td>mit media lab</td><td>9</td></tr><tr><td>university of the</td><td>9</td></tr><tr><td>provided by the</td><td>9</td></tr><tr><td>at the same</td><td>9</td></tr><tr><td>the experimental results</td><td>9</td></tr><tr><td>ying li tian</td><td>9</td></tr><tr><td>fellow ieee and</td><td>9</td></tr><tr><td>jean philippe thiran</td><td>9</td></tr><tr><td>onoma de barcelona</td><td>9</td></tr><tr><td>action unit recognition</td><td>9</td></tr><tr><td>advanced industrial science</td><td>9</td></tr><tr><td>industrial science and</td><td>9</td></tr><tr><td>show that our</td><td>9</td></tr><tr><td>electrical and information</td><td>9</td></tr><tr><td>expression recognition from</td><td>9</td></tr><tr><td>novel method for</td><td>9</td></tr><tr><td>action classi cation</td><td>9</td></tr><tr><td>expression analysis and</td><td>9</td></tr><tr><td>work is licensed</td><td>9</td></tr><tr><td>cite this article</td><td>9</td></tr><tr><td>high dimensional data</td><td>9</td></tr><tr><td>for robust face</td><td>9</td></tr><tr><td>faculty of informatics</td><td>9</td></tr><tr><td>of technology and</td><td>9</td></tr><tr><td>liu member ieee</td><td>9</td></tr><tr><td>journal of emerging</td><td>9</td></tr><tr><td>emotional facial expressions</td><td>9</td></tr><tr><td>in the case</td><td>9</td></tr><tr><td>on the face</td><td>9</td></tr><tr><td>facial expressions and</td><td>9</td></tr><tr><td>robust facial expression</td><td>9</td></tr><tr><td>paper we present</td><td>9</td></tr><tr><td>in the 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\ No newline at end of file +<!doctype html><html><head><meta charset='utf-8'><title>PDF Report: Unknown Trigrams</title><link rel='stylesheet' href='reports.css'></head><body><h2>PDF Report: Unknown Trigrams</h2><table border='1' cellpadding='3' cellspacing='3'><tr><td>of computer science</td><td>1786</td></tr><tr><td>department of computer</td><td>1320</td></tr><tr><td>computer science and</td><td>820</td></tr><tr><td>institute of technology</td><td>755</td></tr><tr><td>science and technology</td><td>526</td></tr><tr><td>science and engineering</td><td>500</td></tr><tr><td>university of california</td><td>485</td></tr><tr><td>department of electrical</td><td>469</td></tr><tr><td>school of computer</td><td>424</td></tr><tr><td>university of technology</td><td>411</td></tr><tr><td>carnegie mellon university</td><td>381</td></tr><tr><td>re identi cation</td><td>380</td></tr><tr><td>department of psychology</td><td>364</td></tr><tr><td>of electrical engineering</td><td>360</td></tr><tr><td>for the degree</td><td>355</td></tr><tr><td>senior member ieee</td><td>350</td></tr><tr><td>of electrical and</td><td>338</td></tr><tr><td>of science and</td><td>329</td></tr><tr><td>academy of sciences</td><td>326</td></tr><tr><td>member ieee and</td><td>315</td></tr><tr><td>electrical and computer</td><td>287</td></tr><tr><td>and computer engineering</td><td>287</td></tr><tr><td>dx doi org</td><td>284</td></tr><tr><td>facial expression recognition</td><td>280</td></tr><tr><td>in this paper</td><td>279</td></tr><tr><td>http dx doi</td><td>278</td></tr><tr><td>for face recognition</td><td>272</td></tr><tr><td>and computer science</td><td>272</td></tr><tr><td>person re identi</td><td>265</td></tr><tr><td>student member ieee</td><td>256</td></tr><tr><td>of the requirements</td><td>254</td></tr><tr><td>doctor of philosophy</td><td>247</td></tr><tr><td>should be addressed</td><td>246</td></tr><tr><td>proceedings of the</td><td>231</td></tr><tr><td>university of science</td><td>227</td></tr><tr><td>state of the</td><td>223</td></tr><tr><td>journal of computer</td><td>221</td></tr><tr><td>of the art</td><td>211</td></tr><tr><td>requirements for the</td><td>211</td></tr><tr><td>engineering and computer</td><td>205</td></tr><tr><td>electrical engineering and</td><td>201</td></tr><tr><td>one of the</td><td>197</td></tr><tr><td>computer science university</td><td>194</td></tr><tr><td>arti cial intelligence</td><td>189</td></tr><tr><td>college of engineering</td><td>185</td></tr><tr><td>the requirements for</td><td>179</td></tr><tr><td>in partial ful</td><td>175</td></tr><tr><td>university of hong</td><td>169</td></tr><tr><td>of hong kong</td><td>169</td></tr><tr><td>dept of computer</td><td>168</td></tr><tr><td>of computer engineering</td><td>167</td></tr><tr><td>all rights reserved</td><td>166</td></tr><tr><td>partial ful llment</td><td>164</td></tr><tr><td>of engineering and</td><td>159</td></tr><tr><td>of psychology university</td><td>154</td></tr><tr><td>based on the</td><td>153</td></tr><tr><td>face recognition using</td><td>153</td></tr><tr><td>in the wild</td><td>150</td></tr><tr><td>computer science department</td><td>150</td></tr><tr><td>max planck institute</td><td>147</td></tr><tr><td>submitted in partial</td><td>144</td></tr><tr><td>planck institute for</td><td>143</td></tr><tr><td>of electronics and</td><td>139</td></tr><tr><td>to cite this</td><td>138</td></tr><tr><td>computer vision and</td><td>137</td></tr><tr><td>of chinese academy</td><td>134</td></tr><tr><td>department of information</td><td>133</td></tr><tr><td>of information technology</td><td>130</td></tr><tr><td>www frontiersin org</td><td>129</td></tr><tr><td>the chinese university</td><td>128</td></tr><tr><td>as conference paper</td><td>128</td></tr><tr><td>school of information</td><td>126</td></tr><tr><td>university of maryland</td><td>126</td></tr><tr><td>of computer applications</td><td>124</td></tr><tr><td>paper at iclr</td><td>124</td></tr><tr><td>submitted to the</td><td>123</td></tr><tr><td>of computer and</td><td>122</td></tr><tr><td>of this work</td><td>121</td></tr><tr><td>convolutional neural networks</td><td>119</td></tr><tr><td>is an open</td><td>119</td></tr><tr><td>of pattern recognition</td><td>119</td></tr><tr><td>and information engineering</td><td>119</td></tr><tr><td>autism spectrum disorders</td><td>119</td></tr><tr><td>department of psychiatry</td><td>119</td></tr><tr><td>an open access</td><td>118</td></tr><tr><td>creative commons attribution</td><td>118</td></tr><tr><td>llment of the</td><td>118</td></tr><tr><td>of information science</td><td>117</td></tr><tr><td>by the editor</td><td>114</td></tr><tr><td>university of texas</td><td>113</td></tr><tr><td>luc van gool</td><td>113</td></tr><tr><td>open access article</td><td>113</td></tr><tr><td>autism spectrum disorder</td><td>112</td></tr><tr><td>will be inserted</td><td>112</td></tr><tr><td>inserted by the</td><td>112</td></tr><tr><td>school of electrical</td><td>111</td></tr><tr><td>of the face</td><td>111</td></tr><tr><td>school of computing</td><td>109</td></tr><tr><td>department of electronics</td><td>108</td></tr><tr><td>in computer vision</td><td>107</td></tr><tr><td>institute of automation</td><td>106</td></tr><tr><td>this article was</td><td>106</td></tr><tr><td>of sciences beijing</td><td>106</td></tr><tr><td>https doi org</td><td>105</td></tr><tr><td>human pose estimation</td><td>105</td></tr><tr><td>university of oxford</td><td>105</td></tr><tr><td>the creative commons</td><td>104</td></tr><tr><td>it has been</td><td>104</td></tr><tr><td>provided the original</td><td>102</td></tr><tr><td>of southern california</td><td>102</td></tr><tr><td>engineering and technology</td><td>102</td></tr><tr><td>university of illinois</td><td>101</td></tr><tr><td>due to the</td><td>101</td></tr><tr><td>sciences beijing china</td><td>101</td></tr><tr><td>et al and</td><td>100</td></tr><tr><td>university of london</td><td>99</td></tr><tr><td>convolutional neural network</td><td>99</td></tr><tr><td>university of chinese</td><td>98</td></tr><tr><td>university of singapore</td><td>98</td></tr><tr><td>received date accepted</td><td>98</td></tr><tr><td>date accepted date</td><td>98</td></tr><tr><td>institute for informatics</td><td>98</td></tr><tr><td>the original work</td><td>97</td></tr><tr><td>in any medium</td><td>96</td></tr><tr><td>whether they are</td><td>96</td></tr><tr><td>computer vision center</td><td>96</td></tr><tr><td>department of computing</td><td>95</td></tr><tr><td>reproduction in any</td><td>95</td></tr><tr><td>laboratory of pattern</td><td>95</td></tr><tr><td>imperial college london</td><td>94</td></tr><tr><td>of california san</td><td>94</td></tr><tr><td>information science and</td><td>93</td></tr><tr><td>or not the</td><td>93</td></tr><tr><td>may come 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central</td><td>82</td></tr><tr><td>of automation chinese</td><td>82</td></tr><tr><td>section of the</td><td>82</td></tr><tr><td>face veri cation</td><td>82</td></tr><tr><td>faculty of electrical</td><td>82</td></tr><tr><td>technology of china</td><td>81</td></tr><tr><td>school of psychology</td><td>81</td></tr><tr><td>university of southern</td><td>81</td></tr><tr><td>faculty of engineering</td><td>81</td></tr><tr><td>et al this</td><td>80</td></tr><tr><td>unrestricted use distribution</td><td>80</td></tr><tr><td>institute of science</td><td>80</td></tr><tr><td>and pattern recognition</td><td>80</td></tr><tr><td>department of mathematics</td><td>79</td></tr><tr><td>shanghai jiao tong</td><td>79</td></tr><tr><td>master of science</td><td>79</td></tr><tr><td>for facial expression</td><td>78</td></tr><tr><td>jiao tong university</td><td>78</td></tr><tr><td>of california los</td><td>78</td></tr><tr><td>can be used</td><td>77</td></tr><tr><td>of information engineering</td><td>77</td></tr><tr><td>queen mary university</td><td>76</td></tr><tr><td>in partial fulfillment</td><td>76</td></tr><tr><td>computer and information</td><td>76</td></tr><tr><td>center for research</td><td>76</td></tr><tr><td>department of engineering</td><td>76</td></tr><tr><td>human computer interaction</td><td>76</td></tr><tr><td>article id pages</td><td>75</td></tr><tr><td>and information technology</td><td>75</td></tr><tr><td>review as conference</td><td>75</td></tr><tr><td>college of computer</td><td>74</td></tr><tr><td>in computer science</td><td>74</td></tr><tr><td>university of surrey</td><td>74</td></tr><tr><td>children with autism</td><td>74</td></tr><tr><td>is properly cited</td><td>73</td></tr><tr><td>individuals with autism</td><td>73</td></tr><tr><td>of central florida</td><td>72</td></tr><tr><td>dept of electrical</td><td>72</td></tr><tr><td>facial expression analysis</td><td>72</td></tr><tr><td>fulfillment of the</td><td>72</td></tr><tr><td>cambridge ma 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north carolina</td><td>60</td></tr><tr><td>university of tokyo</td><td>59</td></tr><tr><td>we show that</td><td>59</td></tr><tr><td>entific research documents</td><td>59</td></tr><tr><td>scientifiques de niveau</td><td>59</td></tr><tr><td>publi ou non</td><td>59</td></tr><tr><td>manant des tablissements</td><td>59</td></tr><tr><td>des tablissements enseignement</td><td>59</td></tr><tr><td>recherche fran ais</td><td>59</td></tr><tr><td>ais ou trangers</td><td>59</td></tr><tr><td>ou trangers des</td><td>59</td></tr><tr><td>trangers des laboratoires</td><td>59</td></tr><tr><td>degree of doctor</td><td>59</td></tr><tr><td>paper we propose</td><td>59</td></tr><tr><td>magnetic resonance imaging</td><td>59</td></tr><tr><td>faces in the</td><td>58</td></tr><tr><td>face recognition with</td><td>58</td></tr><tr><td>institute of computing</td><td>58</td></tr><tr><td>new york university</td><td>57</td></tr><tr><td>university shanghai china</td><td>57</td></tr><tr><td>and electrical engineering</td><td>57</td></tr><tr><td>international joint conference</td><td>57</td></tr><tr><td>principal component analysis</td><td>57</td></tr><tr><td>and computer vision</td><td>57</td></tr><tr><td>of wisconsin madison</td><td>57</td></tr><tr><td>conference on computer</td><td>57</td></tr><tr><td>research in computer</td><td>57</td></tr><tr><td>online at www</td><td>56</td></tr><tr><td>version of the</td><td>56</td></tr><tr><td>expression recognition using</td><td>56</td></tr><tr><td>amsterdam the netherlands</td><td>56</td></tr><tr><td>image processing and</td><td>56</td></tr><tr><td>face detection and</td><td>55</td></tr><tr><td>to this work</td><td>55</td></tr><tr><td>generative adversarial networks</td><td>55</td></tr><tr><td>and signal processing</td><td>55</td></tr><tr><td>university of pittsburgh</td><td>55</td></tr><tr><td>face recognition based</td><td>55</td></tr><tr><td>this article has</td><td>55</td></tr><tr><td>ming hsuan yang</td><td>54</td></tr><tr><td>research 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cambridge</td><td>49</td></tr><tr><td>universit at unchen</td><td>49</td></tr><tr><td>multi object tracking</td><td>48</td></tr><tr><td>of the proposed</td><td>48</td></tr><tr><td>for object detection</td><td>48</td></tr><tr><td>journal on image</td><td>48</td></tr><tr><td>hal id hal</td><td>48</td></tr><tr><td>of technology sydney</td><td>48</td></tr><tr><td>paper under double</td><td>48</td></tr><tr><td>under double blind</td><td>48</td></tr><tr><td>double blind review</td><td>48</td></tr><tr><td>author to whom</td><td>48</td></tr><tr><td>be addressed mail</td><td>48</td></tr><tr><td>of computing technology</td><td>48</td></tr><tr><td>department of cse</td><td>48</td></tr><tr><td>in autism spectrum</td><td>48</td></tr><tr><td>additional key words</td><td>47</td></tr><tr><td>key words and</td><td>47</td></tr><tr><td>words and phrases</td><td>47</td></tr><tr><td>of computer vision</td><td>47</td></tr><tr><td>http creativecommons org</td><td>47</td></tr><tr><td>brought to 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and</td><td>46</td></tr><tr><td>xi an jiaotong</td><td>46</td></tr><tr><td>simon fraser university</td><td>46</td></tr><tr><td>of computing and</td><td>46</td></tr><tr><td>brain and cognitive</td><td>46</td></tr><tr><td>of california riverside</td><td>46</td></tr><tr><td>of facial expression</td><td>45</td></tr><tr><td>th international conference</td><td>45</td></tr><tr><td>face recognition and</td><td>45</td></tr><tr><td>on pattern analysis</td><td>45</td></tr><tr><td>for large scale</td><td>45</td></tr><tr><td>the fact that</td><td>45</td></tr><tr><td>local binary pattern</td><td>45</td></tr><tr><td>in real time</td><td>45</td></tr><tr><td>deep convolutional neural</td><td>44</td></tr><tr><td>if you believe</td><td>44</td></tr><tr><td>seoul national university</td><td>44</td></tr><tr><td>in psychology www</td><td>44</td></tr><tr><td>psychology www frontiersin</td><td>44</td></tr><tr><td>posts and telecommunications</td><td>44</td></tr><tr><td>www intechopen com</td><td>44</td></tr><tr><td>in which the</td><td>44</td></tr><tr><td>zur erlangung des</td><td>44</td></tr><tr><td>eth zurich switzerland</td><td>44</td></tr><tr><td>on arti cial</td><td>44</td></tr><tr><td>www mdpi com</td><td>44</td></tr><tr><td>mdpi com journal</td><td>44</td></tr><tr><td>authors contributed equally</td><td>44</td></tr><tr><td>citation for published</td><td>43</td></tr><tr><td>retained by the</td><td>43</td></tr><tr><td>and computer sciences</td><td>43</td></tr><tr><td>terms of the</td><td>43</td></tr><tr><td>university of oulu</td><td>43</td></tr><tr><td>works at http</td><td>43</td></tr><tr><td>by an authorized</td><td>43</td></tr><tr><td>mathematics and computer</td><td>43</td></tr><tr><td>www tandfonline com</td><td>43</td></tr><tr><td>for intelligent systems</td><td>43</td></tr><tr><td>head pose estimation</td><td>43</td></tr><tr><td>tsinghua university beijing</td><td>43</td></tr><tr><td>university of trento</td><td>42</td></tr><tr><td>and software engineering</td><td>42</td></tr><tr><td>for arti cial</td><td>42</td></tr><tr><td>accepted for inclusion</td><td>42</td></tr><tr><td>an authorized administrator</td><td>42</td></tr><tr><td>face recognition under</td><td>42</td></tr><tr><td>http www tandfonline</td><td>42</td></tr><tr><td>an jiaotong university</td><td>42</td></tr><tr><td>classi cation and</td><td>42</td></tr><tr><td>of the main</td><td>42</td></tr><tr><td>to improve the</td><td>42</td></tr><tr><td>equally to this</td><td>42</td></tr><tr><td>university of rochester</td><td>42</td></tr><tr><td>department of ece</td><td>42</td></tr><tr><td>we use the</td><td>42</td></tr><tr><td>wang member ieee</td><td>42</td></tr><tr><td>mellon university pittsburgh</td><td>41</td></tr><tr><td>for published version</td><td>41</td></tr><tr><td>well as the</td><td>41</td></tr><tr><td>university of thessaloniki</td><td>41</td></tr><tr><td>be used for</td><td>41</td></tr><tr><td>material is permitted</td><td>41</td></tr><tr><td>and information sciences</td><td>41</td></tr><tr><td>the face recognition</td><td>41</td></tr><tr><td>research showcase cmu</td><td>41</td></tr><tr><td>in children with</td><td>41</td></tr><tr><td>the eye region</td><td>41</td></tr><tr><td>facial emotion recognition</td><td>41</td></tr><tr><td>of psychiatry and</td><td>41</td></tr><tr><td>differences in the</td><td>41</td></tr><tr><td>int comput vis</td><td>40</td></tr><tr><td>saarland informatics campus</td><td>40</td></tr><tr><td>in accordance with</td><td>40</td></tr><tr><td>excellence in brain</td><td>40</td></tr><tr><td>brain science and</td><td>40</td></tr><tr><td>it is not</td><td>40</td></tr><tr><td>of the image</td><td>40</td></tr><tr><td>servers or lists</td><td>40</td></tr><tr><td>of massachusetts amherst</td><td>40</td></tr><tr><td>laboratory of intelligent</td><td>40</td></tr><tr><td>for real time</td><td>40</td></tr><tr><td>and face recognition</td><td>40</td></tr><tr><td>robotics institute carnegie</td><td>40</td></tr><tr><td>face recognition has</td><td>40</td></tr><tr><td>gender classi cation</td><td>40</td></tr><tr><td>university of adelaide</td><td>40</td></tr><tr><td>seattle wa usa</td><td>40</td></tr><tr><td>version of record</td><td>39</td></tr><tr><td>on artificial intelligence</td><td>39</td></tr><tr><td>center for excellence</td><td>39</td></tr><tr><td>in brain science</td><td>39</td></tr><tr><td>science and intelligence</td><td>39</td></tr><tr><td>and intelligence technology</td><td>39</td></tr><tr><td>this work for</td><td>39</td></tr><tr><td>journal of information</td><td>39</td></tr><tr><td>in the same</td><td>39</td></tr><tr><td>faculty of computer</td><td>39</td></tr><tr><td>face recognition systems</td><td>39</td></tr><tr><td>this article should</td><td>39</td></tr><tr><td>information engineering the</td><td>39</td></tr><tr><td>computing technology cas</td><td>39</td></tr><tr><td>the author published</td><td>39</td></tr><tr><td>of the data</td><td>39</td></tr><tr><td>in this study</td><td>39</td></tr><tr><td>but has not</td><td>39</td></tr><tr><td>content may change</td><td>39</td></tr><tr><td>may change prior</td><td>39</td></tr><tr><td>in the past</td><td>39</td></tr><tr><td>of electronic science</td><td>38</td></tr><tr><td>you believe that</td><td>38</td></tr><tr><td>university of western</td><td>38</td></tr><tr><td>on image and</td><td>38</td></tr><tr><td>in the literature</td><td>38</td></tr><tr><td>https hal archives</td><td>38</td></tr><tr><td>hal archives ouvertes</td><td>38</td></tr><tr><td>redistribution to servers</td><td>38</td></tr><tr><td>journal of science</td><td>38</td></tr><tr><td>to the department</td><td>38</td></tr><tr><td>modena and reggio</td><td>38</td></tr><tr><td>and intelligent systems</td><td>38</td></tr><tr><td>is an important</td><td>38</td></tr><tr><td>correspondence concerning this</td><td>38</td></tr><tr><td>concerning this article</td><td>38</td></tr><tr><td>linear discriminant analysis</td><td>38</td></tr><tr><td>school of electronics</td><td>38</td></tr><tr><td>of the amygdala</td><td>38</td></tr><tr><td>of brain and</td><td>38</td></tr><tr><td>publication in future</td><td>38</td></tr><tr><td>this journal but</td><td>38</td></tr><tr><td>journal but has</td><td>38</td></tr><tr><td>not been fully</td><td>38</td></tr><tr><td>been fully edited</td><td>38</td></tr><tr><td>fully edited content</td><td>38</td></tr><tr><td>edited content may</td><td>38</td></tr><tr><td>prior to final</td><td>38</td></tr><tr><td>to final publication</td><td>38</td></tr><tr><td>et al the</td><td>38</td></tr><tr><td>transactions on pattern</td><td>38</td></tr><tr><td>the graduate school</td><td>38</td></tr><tr><td>conference on arti</td><td>38</td></tr><tr><td>received june accepted</td><td>37</td></tr><tr><td>university of waterloo</td><td>37</td></tr><tr><td>conference on artificial</td><td>37</td></tr><tr><td>in the public</td><td>37</td></tr><tr><td>we found that</td><td>37</td></tr><tr><td>object detection and</td><td>37</td></tr><tr><td>republic of korea</td><td>37</td></tr><tr><td>feature extraction and</td><td>37</td></tr><tr><td>ouvertes fr hal</td><td>37</td></tr><tr><td>school of informatics</td><td>37</td></tr><tr><td>http hdl handle</td><td>37</td></tr><tr><td>hdl handle net</td><td>37</td></tr><tr><td>computer engineering department</td><td>37</td></tr><tr><td>hal id tel</td><td>37</td></tr><tr><td>ouvertes fr tel</td><td>37</td></tr><tr><td>work was supported</td><td>37</td></tr><tr><td>received april accepted</td><td>37</td></tr><tr><td>at chapel hill</td><td>37</td></tr><tr><td>oxford university press</td><td>37</td></tr><tr><td>technology cas beijing</td><td>37</td></tr><tr><td>automatic facial expression</td><td>37</td></tr><tr><td>angeles ca usa</td><td>37</td></tr><tr><td>recognition of facial</td><td>37</td></tr><tr><td>respect to the</td><td>37</td></tr><tr><td>science and software</td><td>36</td></tr><tr><td>institute for computer</td><td>36</td></tr><tr><td>of electrical computer</td><td>36</td></tr><tr><td>electrical computer engineering</td><td>36</td></tr><tr><td>edinburgh research explorer</td><td>36</td></tr><tr><td>journal of experimental</td><td>36</td></tr><tr><td>is the author</td><td>36</td></tr><tr><td>ieee personal use</td><td>36</td></tr><tr><td>university of modena</td><td>36</td></tr><tr><td>of modena and</td><td>36</td></tr><tr><td>of new york</td><td>36</td></tr><tr><td>conference on machine</td><td>36</td></tr><tr><td>that the proposed</td><td>36</td></tr><tr><td>of applied sciences</td><td>36</td></tr><tr><td>carolina at chapel</td><td>36</td></tr><tr><td>published by oxford</td><td>36</td></tr><tr><td>by oxford university</td><td>36</td></tr><tr><td>based on their</td><td>36</td></tr><tr><td>processing of chinese</td><td>36</td></tr><tr><td>university of nottingham</td><td>36</td></tr><tr><td>spectrum disorders asd</td><td>36</td></tr><tr><td>university of florida</td><td>36</td></tr><tr><td>cial intelligence ijcai</td><td>36</td></tr><tr><td>de montr eal</td><td>35</td></tr><tr><td>computer graphics and</td><td>35</td></tr><tr><td>university of electronic</td><td>35</td></tr><tr><td>electronic science and</td><td>35</td></tr><tr><td>take down policy</td><td>35</td></tr><tr><td>results suggest that</td><td>35</td></tr><tr><td>access by the</td><td>35</td></tr><tr><td>this material for</td><td>35</td></tr><tr><td>tel aviv university</td><td>35</td></tr><tr><td>of software engineering</td><td>35</td></tr><tr><td>for face detection</td><td>35</td></tr><tr><td>of singapore singapore</td><td>35</td></tr><tr><td>for human pose</td><td>35</td></tr><tr><td>prof dr ing</td><td>35</td></tr><tr><td>of arti cial</td><td>35</td></tr><tr><td>for zero shot</td><td>35</td></tr><tr><td>in signal processing</td><td>35</td></tr><tr><td>classi cation using</td><td>35</td></tr><tr><td>key laboratory for</td><td>35</td></tr><tr><td>of notre dame</td><td>35</td></tr><tr><td>the robotics institute</td><td>35</td></tr><tr><td>permission to make</td><td>34</td></tr><tr><td>to make digital</td><td>34</td></tr><tr><td>acm reference format</td><td>34</td></tr><tr><td>institute of engineering</td><td>34</td></tr><tr><td>university of bonn</td><td>34</td></tr><tr><td>for visual question</td><td>34</td></tr><tr><td>pose invariant face</td><td>34</td></tr><tr><td>university of barcelona</td><td>34</td></tr><tr><td>local binary patterns</td><td>34</td></tr><tr><td>polytechnique ed erale</td><td>34</td></tr><tr><td>advance access publication</td><td>34</td></tr><tr><td>des akademischen grades</td><td>34</td></tr><tr><td>mitsubishi electric research</td><td>34</td></tr><tr><td>onoma de barcelona</td><td>34</td></tr><tr><td>have shown that</td><td>34</td></tr><tr><td>results show that</td><td>34</td></tr><tr><td>the main paper</td><td>34</td></tr><tr><td>school of automation</td><td>34</td></tr><tr><td>of psychiatry university</td><td>34</td></tr><tr><td>dept of cse</td><td>34</td></tr><tr><td>computer engineering university</td><td>34</td></tr><tr><td>university of colorado</td><td>34</td></tr><tr><td>ministry of education</td><td>34</td></tr><tr><td>original research article</td><td>34</td></tr><tr><td>children with asd</td><td>34</td></tr><tr><td>due to its</td><td>34</td></tr><tr><td>for semantic segmentation</td><td>33</td></tr><tr><td>business media new</td><td>33</td></tr><tr><td>media new york</td><td>33</td></tr><tr><td>for the publications</td><td>33</td></tr><tr><td>the publications made</td><td>33</td></tr><tr><td>publications made accessible</td><td>33</td></tr><tr><td>or other copyright</td><td>33</td></tr><tr><td>it is condition</td><td>33</td></tr><tr><td>condition of accessing</td><td>33</td></tr><tr><td>publications that users</td><td>33</td></tr><tr><td>that users recognise</td><td>33</td></tr><tr><td>users recognise and</td><td>33</td></tr><tr><td>legal requirements associated</td><td>33</td></tr><tr><td>california at berkeley</td><td>33</td></tr><tr><td>copies are not</td><td>33</td></tr><tr><td>made or distributed</td><td>33</td></tr><tr><td>deep neural network</td><td>33</td></tr><tr><td>material for advertising</td><td>33</td></tr><tr><td>work in other</td><td>33</td></tr><tr><td>face recognition from</td><td>33</td></tr><tr><td>li fei fei</td><td>33</td></tr><tr><td>in the face</td><td>33</td></tr><tr><td>erale de lausanne</td><td>33</td></tr><tr><td>https tel archives</td><td>33</td></tr><tr><td>tel archives ouvertes</td><td>33</td></tr><tr><td>in the scene</td><td>33</td></tr><tr><td>states of america</td><td>33</td></tr><tr><td>electronics and information</td><td>33</td></tr><tr><td>license which permits</td><td>33</td></tr><tr><td>received december accepted</td><td>33</td></tr><tr><td>erlangung des akademischen</td><td>33</td></tr><tr><td>on face recognition</td><td>33</td></tr><tr><td>has been shown</td><td>33</td></tr><tr><td>electrical engineering university</td><td>33</td></tr><tr><td>journal on advances</td><td>33</td></tr><tr><td>electronic and information</td><td>33</td></tr><tr><td>neural network for</td><td>33</td></tr><tr><td>university of notre</td><td>33</td></tr><tr><td>image to image</td><td>33</td></tr><tr><td>the hong kong</td><td>33</td></tr><tr><td>peer reviewed version</td><td>32</td></tr><tr><td>by the legal</td><td>32</td></tr><tr><td>the legal requirements</td><td>32</td></tr><tr><td>with these rights</td><td>32</td></tr><tr><td>use is granted</td><td>32</td></tr><tr><td>uc san diego</td><td>32</td></tr><tr><td>of the creative</td><td>32</td></tr><tr><td>the th international</td><td>32</td></tr><tr><td>and video processing</td><td>32</td></tr><tr><td>works for resale</td><td>32</td></tr><tr><td>in other works</td><td>32</td></tr><tr><td>must be obtained</td><td>32</td></tr><tr><td>rwth aachen university</td><td>32</td></tr><tr><td>of advanced technology</td><td>32</td></tr><tr><td>this research was</td><td>32</td></tr><tr><td>support vector machines</td><td>32</td></tr><tr><td>of advanced computer</td><td>32</td></tr><tr><td>human action recognition</td><td>32</td></tr><tr><td>of computing science</td><td>32</td></tr><tr><td>enti research documents</td><td>32</td></tr><tr><td>ques de niveau</td><td>32</td></tr><tr><td>es ou non</td><td>32</td></tr><tr><td>emanant des etablissements</td><td>32</td></tr><tr><td>des etablissements enseignement</td><td>32</td></tr><tr><td>recherche fran cais</td><td>32</td></tr><tr><td>cais ou etrangers</td><td>32</td></tr><tr><td>ou etrangers des</td><td>32</td></tr><tr><td>etrangers des laboratoires</td><td>32</td></tr><tr><td>com journal sensors</td><td>32</td></tr><tr><td>for permissions please</td><td>32</td></tr><tr><td>accepted june published</td><td>32</td></tr><tr><td>new collective works</td><td>32</td></tr><tr><td>collective works for</td><td>32</td></tr><tr><td>these authors contributed</td><td>32</td></tr><tr><td>component of this</td><td>32</td></tr><tr><td>for ef cient</td><td>31</td></tr><tr><td>recognition system based</td><td>31</td></tr><tr><td>investigate your claim</td><td>31</td></tr><tr><td>or classroom use</td><td>31</td></tr><tr><td>are not made</td><td>31</td></tr><tr><td>that copies are</td><td>31</td></tr><tr><td>commercial advantage and</td><td>31</td></tr><tr><td>advantage and that</td><td>31</td></tr><tr><td>of the facial</td><td>31</td></tr><tr><td>multi task learning</td><td>31</td></tr><tr><td>of western australia</td><td>31</td></tr><tr><td>under the terms</td><td>31</td></tr><tr><td>and or other</td><td>31</td></tr><tr><td>or promotional purposes</td><td>31</td></tr><tr><td>and facial expression</td><td>31</td></tr><tr><td>and reggio emilia</td><td>31</td></tr><tr><td>in the image</td><td>31</td></tr><tr><td>for vision speech</td><td>31</td></tr><tr><td>electronics and computer</td><td>31</td></tr><tr><td>the author and</td><td>31</td></tr><tr><td>at the same</td><td>31</td></tr><tr><td>expressions of emotion</td><td>31</td></tr><tr><td>in the human</td><td>31</td></tr><tr><td>refers to the</td><td>31</td></tr><tr><td>song chun zhu</td><td>31</td></tr><tr><td>there has been</td><td>31</td></tr><tr><td>amit roy chowdhury</td><td>31</td></tr><tr><td>www elsevier com</td><td>31</td></tr><tr><td>york ny usa</td><td>31</td></tr><tr><td>electrical and electronics</td><td>31</td></tr><tr><td>hong kong polytechnic</td><td>31</td></tr><tr><td>for all other</td><td>31</td></tr><tr><td>of advanced research</td><td>30</td></tr><tr><td>for computer graphics</td><td>30</td></tr><tr><td>other copyright owners</td><td>30</td></tr><tr><td>we will remove</td><td>30</td></tr><tr><td>will remove access</td><td>30</td></tr><tr><td>the work immediately</td><td>30</td></tr><tr><td>http www eecs</td><td>30</td></tr><tr><td>to deal with</td><td>30</td></tr><tr><td>or distributed for</td><td>30</td></tr><tr><td>digital or hard</td><td>30</td></tr><tr><td>or hard copies</td><td>30</td></tr><tr><td>provided that copies</td><td>30</td></tr><tr><td>or commercial advantage</td><td>30</td></tr><tr><td>and luc van</td><td>30</td></tr><tr><td>pattern recognition and</td><td>30</td></tr><tr><td>video classi cation</td><td>30</td></tr><tr><td>italiano di tecnologia</td><td>30</td></tr><tr><td>resale or redistribution</td><td>30</td></tr><tr><td>science and research</td><td>30</td></tr><tr><td>of technology and</td><td>30</td></tr><tr><td>vision speech and</td><td>30</td></tr><tr><td>in the present</td><td>30</td></tr><tr><td>business media llc</td><td>30</td></tr><tr><td>natural language processing</td><td>30</td></tr><tr><td>this paper presents</td><td>30</td></tr><tr><td>stony brook university</td><td>30</td></tr><tr><td>boston ma usa</td><td>30</td></tr><tr><td>center for biometrics</td><td>30</td></tr><tr><td>of michigan ann</td><td>30</td></tr><tr><td>facial expressions are</td><td>30</td></tr><tr><td>college of information</td><td>30</td></tr><tr><td>of the association</td><td>30</td></tr><tr><td>the association for</td><td>30</td></tr><tr><td>in this chapter</td><td>30</td></tr><tr><td>received in revised</td><td>30</td></tr><tr><td>for fine grained</td><td>30</td></tr><tr><td>university of munich</td><td>30</td></tr><tr><td>classi cation with</td><td>30</td></tr><tr><td>hong kong china</td><td>30</td></tr><tr><td>science and applications</td><td>30</td></tr><tr><td>graphics and vision</td><td>29</td></tr><tr><td>and we will</td><td>29</td></tr><tr><td>eecs berkeley edu</td><td>29</td></tr><tr><td>of experimental psychology</td><td>29</td></tr><tr><td>work for personal</td><td>29</td></tr><tr><td>of engineering research</td><td>29</td></tr><tr><td>ibm watson research</td><td>29</td></tr><tr><td>engineering research and</td><td>29</td></tr><tr><td>for the purpose</td><td>29</td></tr><tr><td>of the paper</td><td>29</td></tr><tr><td>advertising or promotional</td><td>29</td></tr><tr><td>creating new collective</td><td>29</td></tr><tr><td>facial action unit</td><td>29</td></tr><tr><td>saarbr ucken germany</td><td>29</td></tr><tr><td>to face recognition</td><td>29</td></tr><tr><td>face recognition algorithms</td><td>29</td></tr><tr><td>institutes of advanced</td><td>29</td></tr><tr><td>technology chinese academy</td><td>29</td></tr><tr><td>fr ed eric</td><td>29</td></tr><tr><td>watson research center</td><td>29</td></tr><tr><td>american psychological association</td><td>29</td></tr><tr><td>advanced computer science</td><td>29</td></tr><tr><td>web of science</td><td>29</td></tr><tr><td>chen change loy</td><td>29</td></tr><tr><td>universitat aut onoma</td><td>29</td></tr><tr><td>department of mechanical</td><td>29</td></tr><tr><td>biometrics and security</td><td>29</td></tr><tr><td>contents lists available</td><td>29</td></tr><tr><td>michigan ann arbor</td><td>29</td></tr><tr><td>emotional facial expressions</td><td>29</td></tr><tr><td>an important role</td><td>29</td></tr><tr><td>school of software</td><td>29</td></tr><tr><td>based image retrieval</td><td>29</td></tr><tr><td>in the presence</td><td>29</td></tr><tr><td>der technischen universit</td><td>29</td></tr><tr><td>advances in signal</td><td>29</td></tr><tr><td>institute of psychology</td><td>29</td></tr><tr><td>and arti cial</td><td>29</td></tr><tr><td>for autism research</td><td>29</td></tr><tr><td>intelligent perception and</td><td>29</td></tr><tr><td>of california davis</td><td>29</td></tr><tr><td>received may accepted</td><td>29</td></tr><tr><td>features of the</td><td>29</td></tr><tr><td>theory of mind</td><td>29</td></tr><tr><td>the twenty sixth</td><td>29</td></tr><tr><td>twenty sixth international</td><td>29</td></tr><tr><td>sixth international joint</td><td>29</td></tr><tr><td>to the faculty</td><td>28</td></tr><tr><td>university of queensland</td><td>28</td></tr><tr><td>university of bristol</td><td>28</td></tr><tr><td>houston tx usa</td><td>28</td></tr><tr><td>report no ucb</td><td>28</td></tr><tr><td>no ucb eecs</td><td>28</td></tr><tr><td>www eecs berkeley</td><td>28</td></tr><tr><td>berkeley edu pubs</td><td>28</td></tr><tr><td>edu pubs techrpts</td><td>28</td></tr><tr><td>pubs techrpts eecs</td><td>28</td></tr><tr><td>techrpts eecs html</td><td>28</td></tr><tr><td>new york usa</td><td>28</td></tr><tr><td>new south wales</td><td>28</td></tr><tr><td>fellow ieee and</td><td>28</td></tr><tr><td>in the paper</td><td>28</td></tr><tr><td>and research ijsr</td><td>28</td></tr><tr><td>information technology and</td><td>28</td></tr><tr><td>university of freiburg</td><td>28</td></tr><tr><td>we propose novel</td><td>28</td></tr><tr><td>degree of master</td><td>28</td></tr><tr><td>to this article</td><td>28</td></tr><tr><td>detection and recognition</td><td>28</td></tr><tr><td>and mobile computing</td><td>28</td></tr><tr><td>of our books</td><td>28</td></tr><tr><td>our books indexed</td><td>28</td></tr><tr><td>of science core</td><td>28</td></tr><tr><td>science core collection</td><td>28</td></tr><tr><td>core collection bkci</td><td>28</td></tr><tr><td>in publishing with</td><td>28</td></tr><tr><td>jean marc odobez</td><td>28</td></tr><tr><td>published version apa</td><td>28</td></tr><tr><td>university of york</td><td>28</td></tr><tr><td>deep learning for</td><td>28</td></tr><tr><td>for biometrics and</td><td>28</td></tr><tr><td>and security research</td><td>28</td></tr><tr><td>university of british</td><td>28</td></tr><tr><td>www pnas org</td><td>28</td></tr><tr><td>human robot interaction</td><td>28</td></tr><tr><td>philadelphia pa usa</td><td>28</td></tr><tr><td>machine learning research</td><td>28</td></tr><tr><td>face to face</td><td>28</td></tr><tr><td>in an image</td><td>28</td></tr><tr><td>pose estimation and</td><td>28</td></tr><tr><td>school of economics</td><td>28</td></tr><tr><td>to the same</td><td>28</td></tr><tr><td>out of the</td><td>28</td></tr><tr><td>faculty of science</td><td>28</td></tr><tr><td>terms and conditions</td><td>28</td></tr><tr><td>year of publication</td><td>27</td></tr><tr><td>breaches copyright please</td><td>27</td></tr><tr><td>providing details and</td><td>27</td></tr><tr><td>personal or classroom</td><td>27</td></tr><tr><td>de la torre</td><td>27</td></tr><tr><td>in the last</td><td>27</td></tr><tr><td>engineering national university</td><td>27</td></tr><tr><td>school of eecs</td><td>27</td></tr><tr><td>of the author</td><td>27</td></tr><tr><td>engineering and information</td><td>27</td></tr><tr><td>because of the</td><td>27</td></tr><tr><td>et al eurasip</td><td>27</td></tr><tr><td>al eurasip journal</td><td>27</td></tr><tr><td>role in the</td><td>27</td></tr><tr><td>automatic face recognition</td><td>27</td></tr><tr><td>assistant professor department</td><td>27</td></tr><tr><td>pattern recognition institute</td><td>27</td></tr><tr><td>are among the</td><td>27</td></tr><tr><td>and brain sciences</td><td>27</td></tr><tr><td>institutes of health</td><td>27</td></tr><tr><td>of british columbia</td><td>27</td></tr><tr><td>permissions please email</td><td>27</td></tr><tr><td>conflict of interest</td><td>27</td></tr><tr><td>is that the</td><td>27</td></tr><tr><td>of this paper</td><td>27</td></tr><tr><td>facial expressions and</td><td>27</td></tr><tr><td>centre for vision</td><td>27</td></tr><tr><td>multiple object tracking</td><td>27</td></tr><tr><td>meeting of the</td><td>27</td></tr><tr><td>center for cognitive</td><td>27</td></tr><tr><td>cole polytechnique rale</td><td>27</td></tr><tr><td>of oriented gradients</td><td>27</td></tr><tr><td>department of automation</td><td>27</td></tr><tr><td>research on intelligent</td><td>27</td></tr><tr><td>on intelligent perception</td><td>27</td></tr><tr><td>perception and computing</td><td>27</td></tr><tr><td>university of sydney</td><td>27</td></tr><tr><td>for object recognition</td><td>27</td></tr><tr><td>reuse of any</td><td>27</td></tr><tr><td>dept of ece</td><td>27</td></tr><tr><td>to image translation</td><td>27</td></tr><tr><td>of this article</td><td>27</td></tr><tr><td>and information science</td><td>27</td></tr><tr><td>kong polytechnic university</td><td>27</td></tr><tr><td>recurrent neural networks</td><td>27</td></tr><tr><td>rale de lausanne</td><td>27</td></tr><tr><td>by the author</td><td>26</td></tr><tr><td>requirements associated with</td><td>26</td></tr><tr><td>access to the</td><td>26</td></tr><tr><td>semi supervised learning</td><td>26</td></tr><tr><td>part of this</td><td>26</td></tr><tr><td>center for automation</td><td>26</td></tr><tr><td>for automation research</td><td>26</td></tr><tr><td>the full citation</td><td>26</td></tr><tr><td>nature of the</td><td>26</td></tr><tr><td>allen institute for</td><td>26</td></tr><tr><td>et al for</td><td>26</td></tr><tr><td>committee on graduate</td><td>26</td></tr><tr><td>application to face</td><td>26</td></tr><tr><td>the relationship between</td><td>26</td></tr><tr><td>from single image</td><td>26</td></tr><tr><td>the human visual</td><td>26</td></tr><tr><td>university of the</td><td>26</td></tr><tr><td>shih fu chang</td><td>26</td></tr><tr><td>provided by the</td><td>26</td></tr><tr><td>link to this</td><td>26</td></tr><tr><td>saarbr cken germany</td><td>26</td></tr><tr><td>over the past</td><td>26</td></tr><tr><td>in the form</td><td>26</td></tr></table></body></html>
\ No newline at end of file diff --git a/scraper/reports/report_coverage.html b/scraper/reports/report_coverage.html index 08ab4630..51e53e72 100644 --- a/scraper/reports/report_coverage.html +++ b/scraper/reports/report_coverage.html @@ -1 +1 @@ -<!doctype html><html><head><meta charset='utf-8'><title>Coverage</title><link rel='stylesheet' href='reports.css'></head><body><h2>Coverage</h2><table border='1' cellpadding='3' cellspacing='3'><th>Paper ID</th><th>Megapixels Key</th><th>Report Link</th><th>PDF Link</th><th>Journal</th><th>Type</th><th>Address</th><th>Lat</th><th>Lng</th><th>Coverage</th><th>Total Citations</th><th>Geocoded Citations</th><th>Unknown Citations</th><th>Empty Citations</th><th>With PDF</th><th>With DOI</th><tr><td>0e986f51fe45b00633de9fd0c94d082d2be51406</td><td></td><td><a href="papers/0e986f51fe45b00633de9fd0c94d082d2be51406.html">Face detection, pose estimation, and landmark localization in the wild</a></td><td><a href="http://vision.ics.uci.edu/papers/ZhuR_CVPR_2012/ZhuR_CVPR_2012.pdf">[pdf]</a></td><td>2012 IEEE Conference on Computer Vision and Pattern Recognition</td><td>edu</td><td>University of California, Irvine</td><td>33.64319010</td><td>-117.84016494</td><td>54%</td><td>999</td><td>541</td><td>458</td><td>52</td><td>601</td><td>303</td></tr><tr><td>b5f2846a506fc417e7da43f6a7679146d99c5e96</td><td>UCF101</td><td><a href="papers/b5f2846a506fc417e7da43f6a7679146d99c5e96.html">UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1212.0402.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td>edu</td><td>University of Central Florida</td><td>28.59899755</td><td>-81.19712501</td><td>57%</td><td>934</td><td>531</td><td>400</td><td>65</td><td>658</td><td>230</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td></td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>50%</td><td>999</td><td>496</td><td>500</td><td>62</td><td>613</td><td>293</td></tr><tr><td>759a3b3821d9f0e08e0b0a62c8b693230afc3f8d</td><td></td><td><a href="papers/759a3b3821d9f0e08e0b0a62c8b693230afc3f8d.html">Attribute and simile classifiers for face verification</a></td><td><a href="http://homes.cs.washington.edu/~neeraj/projects/faceverification/base/papers/nk_iccv2009_attrs.pdf">[pdf]</a></td><td>2009 IEEE 12th International Conference on Computer Vision</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>53%</td><td>862</td><td>457</td><td>405</td><td>46</td><td>556</td><td>232</td></tr><tr><td>18c72175ddbb7d5956d180b65a96005c100f6014</td><td>Yale Face Database B</td><td><a href="papers/18c72175ddbb7d5956d180b65a96005c100f6014.html">From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose</a></td><td><a href="http://pdfs.semanticscholar.org/97bb/c2b439a79d4dc0dc7199d71ed96ad5e3fd0e.pdf">[pdf]</a></td><td>IEEE Trans. Pattern Anal. Mach. Intell.</td><td></td><td></td><td></td><td></td><td>45%</td><td>999</td><td>445</td><td>553</td><td>65</td><td>519</td><td>330</td></tr><tr><td>4d9a02d080636e9666c4d1cc438b9893391ec6c7</td><td></td><td><a href="papers/4d9a02d080636e9666c4d1cc438b9893391ec6c7.html">The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression</a></td><td><a href="http://www.iainm.com/iainm/Publications_files/2010_The%20Extended.pdf">[pdf]</a></td><td>2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops</td><td></td><td></td><td></td><td></td><td>44%</td><td>916</td><td>403</td><td>511</td><td>51</td><td>420</td><td>361</td></tr><tr><td>23fc83c8cfff14a16df7ca497661264fc54ed746</td><td>CK</td><td><a href="papers/23fc83c8cfff14a16df7ca497661264fc54ed746.html">Comprehensive Database for Facial Expression Analysis</a></td><td><a href="http://pdfs.semanticscholar.org/23fc/83c8cfff14a16df7ca497661264fc54ed746.pdf">[pdf]</a></td><td></td><td>edu</td><td>Carnegie Mellon University</td><td>37.41021930</td><td>-122.05965487</td><td>39%</td><td>999</td><td>386</td><td>612</td><td>64</td><td>536</td><td>263</td></tr><tr><td>4d423acc78273b75134e2afd1777ba6d3a398973</td><td></td><td><a href="papers/4d423acc78273b75134e2afd1777ba6d3a398973.html">International Conference on Automatic Face and Gesture Recognition The CMU Pose , Illumination , and Expression ( PIE ) Database</a></td><td><a href="http://pdfs.semanticscholar.org/4d42/3acc78273b75134e2afd1777ba6d3a398973.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>46%</td><td>723</td><td>331</td><td>392</td><td>55</td><td>392</td><td>237</td></tr><tr><td>45c31cde87258414f33412b3b12fc5bec7cb3ba9</td><td>JAFFE</td><td><a href="papers/45c31cde87258414f33412b3b12fc5bec7cb3ba9.html">Coding Facial Expressions with Gabor Wavelets</a></td><td><a href="http://pdfs.semanticscholar.org/45c3/1cde87258414f33412b3b12fc5bec7cb3ba9.pdf">[pdf]</a></td><td></td><td>edu</td><td>Kyushu University</td><td>33.59914655</td><td>130.22359848</td><td>39%</td><td>804</td><td>310</td><td>494</td><td>45</td><td>383</td><td>263</td></tr><tr><td>140438a77a771a8fb656b39a78ff488066eb6b50</td><td>LFWP</td><td><a href="papers/140438a77a771a8fb656b39a78ff488066eb6b50.html">Localizing Parts of Faces Using a Consensus of Exemplars</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2011.5995602">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>54%</td><td>506</td><td>273</td><td>232</td><td>36</td><td>309</td><td>150</td></tr><tr><td>560e0e58d0059259ddf86fcec1fa7975dee6a868</td><td></td><td><a href="papers/560e0e58d0059259ddf86fcec1fa7975dee6a868.html">Face recognition in unconstrained videos with matched background similarity</a></td><td><a href="http://www.cs.tau.ac.il/~wolf/papers/lvfw.pdf">[pdf]</a></td><td>CVPR 2011</td><td>edu</td><td>Open University of Israel</td><td>32.77824165</td><td>34.99565673</td><td>53%</td><td>457</td><td>241</td><td>214</td><td>27</td><td>273</td><td>149</td></tr><tr><td>853bd61bc48a431b9b1c7cab10c603830c488e39</td><td>CAISA Webface</td><td><a href="papers/853bd61bc48a431b9b1c7cab10c603830c488e39.html">Learning Face Representation from Scratch</a></td><td><a href="http://pdfs.semanticscholar.org/b8a2/0ed7e74325da76d7183d1ab77b082a92b447.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>58%</td><td>401</td><td>232</td><td>168</td><td>28</td><td>261</td><td>125</td></tr><tr><td>1ea8085fe1c79d12adffb02bd157b54d799568e4</td><td></td><td><a href="papers/1ea8085fe1c79d12adffb02bd157b54d799568e4.html">Eigenfaces vs. Fisherfaces: Recognition Using Class Speciic Linear Projection</a></td><td><a href="http://pdfs.semanticscholar.org/1ea8/085fe1c79d12adffb02bd157b54d799568e4.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>33%</td><td>583</td><td>194</td><td>388</td><td>44</td><td>300</td><td>162</td></tr><tr><td>9055b155cbabdce3b98e16e5ac9c0edf00f9552f</td><td></td><td><a href="papers/9055b155cbabdce3b98e16e5ac9c0edf00f9552f.html">MORPH: a longitudinal image database of normal adult age-progression</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/FGR.2006.78">[pdf]</a></td><td>7th International Conference on Automatic Face and Gesture Recognition (FGR06)</td><td></td><td></td><td></td><td></td><td>47%</td><td>406</td><td>191</td><td>212</td><td>22</td><td>208</td><td>161</td></tr><tr><td>95f12d27c3b4914e0668a268360948bce92f7db3</td><td>Helen</td><td><a href="papers/95f12d27c3b4914e0668a268360948bce92f7db3.html">Interactive Facial Feature Localization</a></td><td><a href="http://pdfs.semanticscholar.org/95f1/2d27c3b4914e0668a268360948bce92f7db3.pdf">[pdf]</a></td><td></td><td>edu</td><td>University of Illinois, Urbana-Champaign</td><td>40.11116745</td><td>-88.22587665</td><td>54%</td><td>323</td><td>175</td><td>147</td><td>23</td><td>198</td><td>105</td></tr><tr><td>2724ba85ec4a66de18da33925e537f3902f21249</td><td></td><td><a href="papers/2724ba85ec4a66de18da33925e537f3902f21249.html">Robust Face Landmark Estimation under Occlusion</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6751298', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>56%</td><td>296</td><td>167</td><td>128</td><td>14</td><td>179</td><td>99</td></tr><tr><td>044d9a8c61383312cdafbcc44b9d00d650b21c70</td><td></td><td><a href="papers/044d9a8c61383312cdafbcc44b9d00d650b21c70.html">300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge</a></td><td><a href="https://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_iccv_2013_300_w.pdf">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision Workshops</td><td>edu</td><td>University of Twente</td><td>52.23801390</td><td>6.85667610</td><td>56%</td><td>285</td><td>159</td><td>125</td><td>25</td><td>185</td><td>82</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td></td><td><a href="papers/a74251efa970b92925b89eeef50a5e37d9281ad0.html">Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization</a></td><td><a href="http://lrs.icg.tugraz.at/pubs/koestinger_befit_11.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>55%</td><td>278</td><td>153</td><td>125</td><td>30</td><td>195</td><td>65</td></tr><tr><td>2fda164863a06a92d3a910b96eef927269aeb730</td><td></td><td><a href="papers/2fda164863a06a92d3a910b96eef927269aeb730.html">Names and faces in the news</a></td><td><a href="http://www.cs.utexas.edu/~grauman/courses/spring2007/395T/papers/berg_names_and_faces.pdf">[pdf]</a></td><td>Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.</td><td></td><td></td><td></td><td></td><td>41%</td><td>290</td><td>118</td><td>172</td><td>19</td><td>197</td><td>45</td></tr><tr><td>4c170a0dcc8de75587dae21ca508dab2f9343974</td><td>FaceTracer</td><td><a href="papers/4c170a0dcc8de75587dae21ca508dab2f9343974.html">FaceTracer: A Search Engine for Large Collections of Images with Faces</a></td><td><a href="http://pdfs.semanticscholar.org/73a8/1d311eedac8dea3ca24dc15b6990fa4a725e.pdf">[pdf]</a></td><td></td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>49%</td><td>212</td><td>103</td><td>109</td><td>13</td><td>137</td><td>52</td></tr><tr><td>013909077ad843eb6df7a3e8e290cfd5575999d2</td><td></td><td><a href="papers/013909077ad843eb6df7a3e8e290cfd5575999d2.html">A Semi-automatic Methodology for Facial Landmark Annotation</a></td><td><a href="http://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_cvpr_2013_amfg_w.pdf">[pdf]</a></td><td>2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops</td><td>edu</td><td>University of Twente</td><td>52.23801390</td><td>6.85667610</td><td>59%</td><td>169</td><td>100</td><td>69</td><td>14</td><td>112</td><td>49</td></tr><tr><td>140c95e53c619eac594d70f6369f518adfea12ef</td><td>IJB-A</td><td><a href="papers/140c95e53c619eac594d70f6369f518adfea12ef.html">Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2015/app/1B_089_ext.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>47%</td><td>208</td><td>98</td><td>107</td><td>20</td><td>144</td><td>52</td></tr><tr><td>04661729f0ff6afe4b4d6223f18d0da1d479accf</td><td>CelebA</td><td><a href="papers/04661729f0ff6afe4b4d6223f18d0da1d479accf.html">From Facial Parts Responses to Face Detection: A Deep Learning Approach</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.419">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td>edu</td><td>Shenzhen Institutes of Advanced Technology</td><td>22.59805605</td><td>113.98533784</td><td>57%</td><td>150</td><td>86</td><td>63</td><td>12</td><td>93</td><td>48</td></tr><tr><td>291265db88023e92bb8c8e6390438e5da148e8f5</td><td>MsCeleb</td><td><a href="papers/291265db88023e92bb8c8e6390438e5da148e8f5.html">MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/4603/cb8e05258bb0572ae912ad20903b8f99f4b1.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>49%</td><td>150</td><td>73</td><td>76</td><td>14</td><td>115</td><td>29</td></tr><tr><td>133f01aec1534604d184d56de866a4bd531dac87</td><td></td><td><a href="papers/133f01aec1534604d184d56de866a4bd531dac87.html">Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.230">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>42%</td><td>168</td><td>71</td><td>97</td><td>15</td><td>95</td><td>55</td></tr><tr><td>52d7eb0fbc3522434c13cc247549f74bb9609c5d</td><td>WIDER FACE</td><td><a href="papers/52d7eb0fbc3522434c13cc247549f74bb9609c5d.html">WIDER FACE: A Face Detection Benchmark</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1511.06523.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>54%</td><td>129</td><td>70</td><td>59</td><td>11</td><td>89</td><td>34</td></tr><tr><td>1be498d4bbc30c3bfd0029114c784bc2114d67c0</td><td>Adience</td><td><a href="papers/1be498d4bbc30c3bfd0029114c784bc2114d67c0.html">Age and Gender Estimation of Unfiltered Faces</a></td><td><a href="http://www.openu.ac.il/home/hassner/Adience/EidingerEnbarHassner_tifs.pdf">[pdf]</a></td><td>IEEE Transactions on Information Forensics and Security</td><td></td><td></td><td></td><td></td><td>45%</td><td>155</td><td>69</td><td>86</td><td>5</td><td>80</td><td>55</td></tr><tr><td>96e0cfcd81cdeb8282e29ef9ec9962b125f379b0</td><td>MegaFace 2</td><td><a href="papers/96e0cfcd81cdeb8282e29ef9ec9962b125f379b0.html">The MegaFace Benchmark: 1 Million Faces for Recognition at Scale</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2016.527">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>53%</td><td>114</td><td>60</td><td>54</td><td>10</td><td>88</td><td>22</td></tr><tr><td>10195a163ab6348eef37213a46f60a3d87f289c5</td><td></td><td><a href="papers/10195a163ab6348eef37213a46f60a3d87f289c5.html">Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks</a></td><td><a href="https://doi.org/10.1007/s11263-016-0940-3">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>49%</td><td>121</td><td>59</td><td>61</td><td>10</td><td>84</td><td>29</td></tr><tr><td>0d3bb75852098b25d90f31d2f48fd0cb4944702b</td><td>FaceScrub</td><td><a href="papers/0d3bb75852098b25d90f31d2f48fd0cb4944702b.html">A data-driven approach to cleaning large face datasets</a></td><td><a href="https://doi.org/10.1109/ICIP.2014.7025068">[pdf]</a></td><td>2014 IEEE International Conference on Image Processing (ICIP)</td><td>edu</td><td>University of Illinois, Urbana-Champaign</td><td>40.11116745</td><td>-88.22587665</td><td>48%</td><td>120</td><td>57</td><td>63</td><td>5</td><td>93</td><td>24</td></tr><tr><td>04c2cda00e5536f4b1508cbd80041e9552880e67</td><td></td><td><a href="papers/04c2cda00e5536f4b1508cbd80041e9552880e67.html">Hipster Wars: Discovering Elements of Fashion Styles</a></td><td><a href="http://pdfs.semanticscholar.org/04c2/cda00e5536f4b1508cbd80041e9552880e67.pdf">[pdf]</a></td><td></td><td>edu</td><td>Tohoku University</td><td>38.25309450</td><td>140.87365930</td><td>58%</td><td>85</td><td>49</td><td>36</td><td>3</td><td>55</td><td>19</td></tr><tr><td>e4754afaa15b1b53e70743880484b8d0736990ff</td><td></td><td><a href="papers/e4754afaa15b1b53e70743880484b8d0736990ff.html">300 Faces In-The-Wild Challenge: database and results</a></td><td><a href="{'url': 'http://doi.org/10.1016/j.imavis.2016.01.002', 'linkType': 'doi'}">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>47%</td><td>103</td><td>48</td><td>55</td><td>10</td><td>65</td><td>30</td></tr><tr><td>8355d095d3534ef511a9af68a3b2893339e3f96b</td><td></td><td><a href="papers/8355d095d3534ef511a9af68a3b2893339e3f96b.html">DEX: Deep EXpectation of Apparent Age from a Single Image</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7406390', 'linkType': 'ieee'}">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision Workshop (ICCVW)</td><td></td><td></td><td></td><td></td><td>44%</td><td>102</td><td>45</td><td>54</td><td>5</td><td>61</td><td>28</td></tr><tr><td>0b3a146c474166bba71e645452b3a8276ac05998</td><td></td><td><a href="papers/0b3a146c474166bba71e645452b3a8276ac05998.html">Whos In the Picture</a></td><td><a href="http://pdfs.semanticscholar.org/c6e5/17eb85bc6c68dff5d3fadb2d817e839c966b.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>39%</td><td>99</td><td>39</td><td>60</td><td>6</td><td>65</td><td>23</td></tr><tr><td>636b8ffc09b1b23ff714ac8350bb35635e49fa3c</td><td></td><td><a href="papers/636b8ffc09b1b23ff714ac8350bb35635e49fa3c.html">Pruning training sets for learning of object categories</a></td><td><a href="{'url': 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Technology</td><td>22.59805605</td><td>113.98533784</td><td>60%</td><td>43</td><td>26</td><td>17</td><td>1</td><td>30</td><td>12</td></tr><tr><td>37d6f0eb074d207b53885bd2eb78ccc8a04be597</td><td></td><td><a href="papers/37d6f0eb074d207b53885bd2eb78ccc8a04be597.html">Can facial cosmetics affect the matching accuracy of face recognition systems?</a></td><td><a href="http://www.cse.msu.edu/~climer/DantchevaChenRossFaceCosmetics_BTAS2012.pdf">[pdf]</a></td><td>2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td></td><td></td><td></td><td></td><td>50%</td><td>46</td><td>23</td><td>23</td><td>0</td><td>17</td><td>22</td></tr><tr><td>c34532fe6bfbd1e6df477c9ffdbb043b77e7804d</td><td></td><td><a href="papers/c34532fe6bfbd1e6df477c9ffdbb043b77e7804d.html">A 3D Morphable Eye Region Model for Gaze Estimation</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/0d43/3b9435b874a1eea6d7999e86986c910fa285.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td>edu</td><td>Carnegie Mellon University</td><td>37.41021930</td><td>-122.05965487</td><td>71%</td><td>21</td><td>15</td><td>6</td><td>0</td><td>17</td><td>4</td></tr><tr><td>31b05f65405534a696a847dd19c621b7b8588263</td><td></td><td><a href="papers/31b05f65405534a696a847dd19c621b7b8588263.html">UMDFaces: An annotated face dataset for training deep networks</a></td><td><a href="http://arxiv.org/abs/1611.01484">[pdf]</a></td><td>2017 IEEE International Joint Conference on Biometrics (IJCB)</td><td></td><td></td><td></td><td></td><td>48%</td><td>29</td><td>14</td><td>15</td><td>4</td><td>20</td><td>6</td></tr><tr><td>45e616093a92e5f1e61a7c6037d5f637aa8964af</td><td></td><td><a href="papers/45e616093a92e5f1e61a7c6037d5f637aa8964af.html">Fine-grained evaluation on face detection in the wild</a></td><td><a href="http://www.cs.toronto.edu/~byang/papers/malf_fg15.pdf">[pdf]</a></td><td>2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>Chinese Academy of Sciences</td><td>40.00447950</td><td>116.37023800</td><td>71%</td><td>17</td><td>12</td><td>5</td><td>0</td><td>13</td><td>4</td></tr><tr><td>28d4e027c7e90b51b7d8908fce68128d1964668a</td><td>MegaFace 2</td><td><a href="papers/28d4e027c7e90b51b7d8908fce68128d1964668a.html">Level Playing Field for Million Scale Face Recognition</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1705.00393.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>41%</td><td>27</td><td>11</td><td>16</td><td>2</td><td>22</td><td>4</td></tr><tr><td>ca3e88d87e1344d076c964ea89d91a75c417f5ee</td><td></td><td><a href="papers/ca3e88d87e1344d076c964ea89d91a75c417f5ee.html">Indian Movie Face Database: A benchmark for face recognition under wide variations</a></td><td><span class="gray">[pdf]</a></td><td>2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)</td><td></td><td></td><td></td><td></td><td>64%</td><td>14</td><td>9</td><td>5</td><td>0</td><td>10</td><td>4</td></tr><tr><td>6dcf418c778f528b5792104760f1fbfe90c6dd6a</td><td></td><td><a href="papers/6dcf418c778f528b5792104760f1fbfe90c6dd6a.html">AgeDB: The First Manually Collected, In-the-Wild Age Database</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8014984', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>70%</td><td>10</td><td>7</td><td>2</td><td>1</td><td>9</td><td>0</td></tr><tr><td>bd26dabab576adb6af30484183c9c9c8379bf2e0</td><td>SCUT-FBP</td><td><a href="papers/bd26dabab576adb6af30484183c9c9c8379bf2e0.html">SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1511.02459.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2015 IEEE International Conference on Systems, Man, and Cybernetics</td><td>edu</td><td>South China University of Technology</td><td>23.05020420</td><td>113.39880323</td><td>43%</td><td>14</td><td>6</td><td>8</td><td>3</td><td>5</td><td>7</td></tr><tr><td>1a40092b493c6b8840257ab7f96051d1a4dbfeb2</td><td></td><td><a href="papers/1a40092b493c6b8840257ab7f96051d1a4dbfeb2.html">Sports Videos in the Wild (SVW): A video dataset for sports analysis</a></td><td><a href="http://web.cse.msu.edu/~liuxm/publication/Safdarnejad_Liu_Udpa_Andrus_Wood_Craven_FG2015.pdf">[pdf]</a></td><td>2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>Michigan State University</td><td>42.71856800</td><td>-84.47791571</td><td>67%</td><td>6</td><td>4</td><td>2</td><td>1</td><td>5</td><td>0</td></tr><tr><td>137aa2f891d474fce1e7a1d1e9b3aefe21e22b34</td><td></td><td><a href="papers/137aa2f891d474fce1e7a1d1e9b3aefe21e22b34.html">Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset</a></td><td><a href="https://doi.org/10.1109/BTAS.2013.6712710">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of North Carolina Wilmington</td><td>34.23755810</td><td>-77.92701290</td><td>57%</td><td>7</td><td>4</td><td>3</td><td>1</td><td>2</td><td>4</td></tr><tr><td>0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e</td><td></td><td><a href="papers/0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e.html">Large Age-Gap face verification by feature injection in deep networks</a></td><td><a href="http://pdfs.semanticscholar.org/0d2d/d4fc016cb6a517d8fb43a7cc3ff62964832e.pdf">[pdf]</a></td><td>Pattern Recognition Letters</td><td></td><td></td><td></td><td></td><td>40%</td><td>5</td><td>2</td><td>3</td><td>0</td><td>2</td><td>2</td></tr><tr><td>56ae6d94fc6097ec4ca861f0daa87941d1c10b70</td><td>CMDP</td><td><a href="papers/56ae6d94fc6097ec4ca861f0daa87941d1c10b70.html">Distance Estimation of an Unknown Person from a Portrait</a></td><td><a href="http://pdfs.semanticscholar.org/56ae/6d94fc6097ec4ca861f0daa87941d1c10b70.pdf">[pdf]</a></td><td></td><td>edu</td><td>California Institute of Technology</td><td>34.13710185</td><td>-118.12527487</td><td>25%</td><td>8</td><td>2</td><td>6</td><td>0</td><td>5</td><td>1</td></tr><tr><td>670637d0303a863c1548d5b19f705860a23e285c</td><td></td><td><a href="papers/670637d0303a863c1548d5b19f705860a23e285c.html">Face swapping: automatically replacing faces in photographs</a></td><td><a href="https://classes.cs.uoregon.edu/16F/cis607photo/faces.pdf">[pdf]</a></td><td>ACM Trans. Graph.</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>100%</td><td>2</td><td>2</td><td>0</td><td>0</td><td>1</td><td>1</td></tr><tr><td>3c8db0d86a6aa51b64ec09c7d25a721adcdfb7a3</td><td></td><td><a href="papers/3c8db0d86a6aa51b64ec09c7d25a721adcdfb7a3.html">Ordered trajectories for human action recognition with large number of classes</a></td><td><a href="https://doi.org/10.1016/j.imavis.2015.06.009">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>100%</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td></tr><tr><td>c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8</td><td></td><td><a href="papers/c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8.html">Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.</a></td><td><a href="http://pdfs.semanticscholar.org/c652/6dd3060d63a6c90e8b7ff340383c4e0e0dd8.pdf">[pdf]</a></td><td>Scientific reports</td><td>edu</td><td>University College London</td><td>51.52316070</td><td>-0.12820370</td><td>25%</td><td>4</td><td>1</td><td>3</td><td>0</td><td>2</td><td>2</td></tr><tr><td>23e824d1dfc33f3780dd18076284f07bd99f1c43</td><td></td><td><a href="papers/23e824d1dfc33f3780dd18076284f07bd99f1c43.html">Spoofing faces using makeup: An investigative study</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7947686', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)</td><td>edu</td><td>INRIA Méditerranée</td><td>43.61581310</td><td>7.06838000</td><td>33%</td><td>3</td><td>1</td><td>2</td><td>0</td><td>1</td><td>2</td></tr><tr><td>75da1df4ed319926c544eefe17ec8d720feef8c0</td><td>FDDB</td><td><a href="papers/75da1df4ed319926c544eefe17ec8d720feef8c0.html">FDDB: A Benchmark for Face Detection in Unconstrained Settings</a></td><td><a href="http://pdfs.semanticscholar.org/75da/1df4ed319926c544eefe17ec8d720feef8c0.pdf">[pdf]</a></td><td></td><td>edu</td><td>University of Massachusetts</td><td>42.38897850</td><td>-72.52869870</td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>447d8893a4bdc29fa1214e53499ffe67b28a6db5</td><td></td><td><a href="papers/447d8893a4bdc29fa1214e53499ffe67b28a6db5.html">Electronic Transport in Quantum Confined Systems</a></td><td><a href="http://pdfs.semanticscholar.org/447d/8893a4bdc29fa1214e53499ffe67b28a6db5.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td></tr></table></body></html>
\ No newline at end of file +<!doctype html><html><head><meta charset='utf-8'><title>Coverage</title><link rel='stylesheet' href='reports.css'></head><body><h2>Coverage</h2><table border='1' cellpadding='3' cellspacing='3'><th>Paper ID</th><th>Megapixels Key</th><th>Megapixels Name</th><th>Report Link</th><th>PDF Link</th><th>Journal</th><th>Type</th><th>Address</th><th>Lat</th><th>Lng</th><th>Coverage</th><th>Total Citations</th><th>Geocoded Citations</th><th>Unknown Citations</th><th>Empty Citations</th><th>With PDF</th><th>With DOI</th><tr><td>b5f2846a506fc417e7da43f6a7679146d99c5e96</td><td>ucf_101</td><td>UCF101</td><td><a href="papers/b5f2846a506fc417e7da43f6a7679146d99c5e96.html">UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1212.0402.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td>edu</td><td>University of Central Florida</td><td>28.59899755</td><td>-81.19712501</td><td>54%</td><td>999</td><td>535</td><td>464</td><td>73</td><td>708</td><td>212</td></tr><tr><td>0e986f51fe45b00633de9fd0c94d082d2be51406</td><td>afw</td><td>AFW</td><td><a href="papers/0e986f51fe45b00633de9fd0c94d082d2be51406.html">Face detection, pose estimation, and landmark localization in the wild</a></td><td><a href="http://vision.ics.uci.edu/papers/ZhuR_CVPR_2012/ZhuR_CVPR_2012.pdf">[pdf]</a></td><td>2012 IEEE Conference on Computer Vision and Pattern Recognition</td><td>edu</td><td>University of California, Irvine</td><td>33.64319010</td><td>-117.84016494</td><td>52%</td><td>999</td><td>521</td><td>478</td><td>59</td><td>607</td><td>273</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td>3dddb_unconstrained</td><td>3D Dynamic</td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>47%</td><td>999</td><td>472</td><td>526</td><td>71</td><td>619</td><td>260</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td>ar_facedb</td><td>AR Face</td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>47%</td><td>999</td><td>472</td><td>526</td><td>71</td><td>619</td><td>260</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td>m2vtsdb_extended</td><td>xm2vtsdb</td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>47%</td><td>999</td><td>472</td><td>526</td><td>71</td><td>619</td><td>260</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td>put_face</td><td>Put Face</td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>47%</td><td>999</td><td>472</td><td>526</td><td>71</td><td>619</td><td>260</td></tr><tr><td>759a3b3821d9f0e08e0b0a62c8b693230afc3f8d</td><td>pubfig</td><td>PubFig</td><td><a href="papers/759a3b3821d9f0e08e0b0a62c8b693230afc3f8d.html">Attribute and simile classifiers for face verification</a></td><td><a href="http://homes.cs.washington.edu/~neeraj/projects/faceverification/base/papers/nk_iccv2009_attrs.pdf">[pdf]</a></td><td>2009 IEEE 12th International Conference on Computer Vision</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>51%</td><td>894</td><td>454</td><td>440</td><td>55</td><td>587</td><td>222</td></tr><tr><td>4d9a02d080636e9666c4d1cc438b9893391ec6c7</td><td>cohn_kanade_plus</td><td>CK+</td><td><a href="papers/4d9a02d080636e9666c4d1cc438b9893391ec6c7.html">The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression</a></td><td><a href="http://www.iainm.com/iainm/Publications_files/2010_The%20Extended.pdf">[pdf]</a></td><td>2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops</td><td></td><td></td><td></td><td></td><td>41%</td><td>975</td><td>403</td><td>572</td><td>65</td><td>460</td><td>345</td></tr><tr><td>2e384f057211426ac5922f1b33d2aa8df5d51f57</td><td>a_pascal_yahoo</td><td>aPascal</td><td><a href="papers/2e384f057211426ac5922f1b33d2aa8df5d51f57.html">Describing objects by their attributes</a></td><td><a href="http://www-2.cs.cmu.edu/~dhoiem/publications/cvpr2009_attributes.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>39%</td><td>999</td><td>393</td><td>606</td><td>71</td><td>727</td><td>73</td></tr><tr><td>162ea969d1929ed180cc6de9f0bf116993ff6e06</td><td>vgg_faces</td><td>VGG Face</td><td><a href="papers/162ea969d1929ed180cc6de9f0bf116993ff6e06.html">Deep Face Recognition</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/f372/ab9b3270d4e4f6a0258c83c2736c3a5c0454.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>39%</td><td>999</td><td>393</td><td>606</td><td>71</td><td>621</td><td>156</td></tr><tr><td>23fc83c8cfff14a16df7ca497661264fc54ed746</td><td>cohn_kanade</td><td>CK</td><td><a href="papers/23fc83c8cfff14a16df7ca497661264fc54ed746.html">Comprehensive Database for Facial Expression Analysis</a></td><td><a href="http://pdfs.semanticscholar.org/23fc/83c8cfff14a16df7ca497661264fc54ed746.pdf">[pdf]</a></td><td></td><td>edu</td><td>Carnegie Mellon University</td><td>37.41021930</td><td>-122.05965487</td><td>38%</td><td>999</td><td>380</td><td>619</td><td>75</td><td>555</td><td>252</td></tr><tr><td>01959ef569f74c286956024866c1d107099199f7</td><td>vqa</td><td>VQA</td><td><a href="papers/01959ef569f74c286956024866c1d107099199f7.html">VQA: Visual Question Answering</a></td><td><a href="http://arxiv.org/pdf/1505.00468v3.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>47%</td><td>731</td><td>344</td><td>387</td><td>47</td><td>628</td><td>4</td></tr><tr><td>6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4</td><td>celeba</td><td>CelebA</td><td><a href="papers/6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4.html">Deep Learning Face Attributes in the Wild</a></td><td><a href="http://arxiv.org/pdf/1411.7766v2.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>42%</td><td>808</td><td>340</td><td>468</td><td>69</td><td>666</td><td>50</td></tr><tr><td>4d423acc78273b75134e2afd1777ba6d3a398973</td><td>cmu_pie</td><td>CMU PIE</td><td><a href="papers/4d423acc78273b75134e2afd1777ba6d3a398973.html">International Conference on Automatic Face and Gesture Recognition The CMU Pose , Illumination , and Expression ( PIE ) Database</a></td><td><a href="http://pdfs.semanticscholar.org/4d42/3acc78273b75134e2afd1777ba6d3a398973.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>44%</td><td>742</td><td>330</td><td>412</td><td>61</td><td>410</td><td>232</td></tr><tr><td>abe9f3b91fd26fa1b50cd685c0d20debfb372f73</td><td>voc</td><td>VOC</td><td><a href="papers/abe9f3b91fd26fa1b50cd685c0d20debfb372f73.html">The Pascal Visual Object Classes Challenge: A Retrospective</a></td><td><a href="http://homepages.inf.ed.ac.uk/ckiw/postscript/ijcv_voc14.pdf">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>32%</td><td>999</td><td>315</td><td>684</td><td>75</td><td>698</td><td>6</td></tr><tr><td>45c31cde87258414f33412b3b12fc5bec7cb3ba9</td><td>jaffe</td><td>JAFFE</td><td><a href="papers/45c31cde87258414f33412b3b12fc5bec7cb3ba9.html">Coding Facial Expressions with Gabor Wavelets</a></td><td><a href="http://pdfs.semanticscholar.org/45c3/1cde87258414f33412b3b12fc5bec7cb3ba9.pdf">[pdf]</a></td><td></td><td>edu</td><td>Kyushu University</td><td>33.59914655</td><td>130.22359848</td><td>36%</td><td>848</td><td>308</td><td>540</td><td>56</td><td>413</td><td>255</td></tr><tr><td>31b58ced31f22eab10bd3ee2d9174e7c14c27c01</td><td>tiny_images</td><td>Tiny Images</td><td><a href="papers/31b58ced31f22eab10bd3ee2d9174e7c14c27c01.html">Nonparametric Object and Scene Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/31b5/8ced31f22eab10bd3ee2d9174e7c14c27c01.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>31%</td><td>999</td><td>305</td><td>694</td><td>93</td><td>670</td><td>9</td></tr><tr><td>140438a77a771a8fb656b39a78ff488066eb6b50</td><td>lfw_p</td><td>LFWP</td><td><a href="papers/140438a77a771a8fb656b39a78ff488066eb6b50.html">Localizing Parts of Faces Using a Consensus of Exemplars</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2011.5995602">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>53%</td><td>521</td><td>274</td><td>247</td><td>40</td><td>321</td><td>144</td></tr><tr><td>18ae7c9a4bbc832b8b14bc4122070d7939f5e00e</td><td>frgc</td><td>FRGC</td><td><a href="papers/18ae7c9a4bbc832b8b14bc4122070d7939f5e00e.html">Overview of the face recognition grand challenge</a></td><td><a href="http://www3.nd.edu/~kwb/PhillipsEtAlCVPR_2005.pdf">[pdf]</a></td><td>2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)</td><td></td><td></td><td></td><td></td><td>25%</td><td>999</td><td>253</td><td>746</td><td>110</td><td>572</td><td>64</td></tr><tr><td>32cde90437ab5a70cf003ea36f66f2de0e24b3ab</td><td>cityscapes</td><td>Cityscapes</td><td><a href="papers/32cde90437ab5a70cf003ea36f66f2de0e24b3ab.html">The Cityscapes Dataset for Semantic Urban Scene Understanding</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1604.01685.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>33%</td><td>771</td><td>252</td><td>519</td><td>54</td><td>622</td><td>0</td></tr><tr><td>32cde90437ab5a70cf003ea36f66f2de0e24b3ab</td><td>cityscapes</td><td>Cityscapes</td><td><a href="papers/32cde90437ab5a70cf003ea36f66f2de0e24b3ab.html">The Cityscapes Dataset for Semantic Urban Scene Understanding</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1604.01685.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>33%</td><td>771</td><td>252</td><td>519</td><td>54</td><td>622</td><td>0</td></tr><tr><td>2ad0ee93d029e790ebb50574f403a09854b65b7e</td><td>yale_faces</td><td>YaleFaces</td><td><a href="papers/2ad0ee93d029e790ebb50574f403a09854b65b7e.html">Acquiring linear subspaces for face recognition under variable lighting</a></td><td><a href="http://vision.cornell.edu/se3/wp-content/uploads/2014/09/pami05.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>25%</td><td>999</td><td>251</td><td>748</td><td>110</td><td>509</td><td>113</td></tr><tr><td>2ad0ee93d029e790ebb50574f403a09854b65b7e</td><td>yale_faces</td><td>YaleFaces</td><td><a href="papers/2ad0ee93d029e790ebb50574f403a09854b65b7e.html">Acquiring linear subspaces for face recognition under variable lighting</a></td><td><a href="http://vision.cornell.edu/se3/wp-content/uploads/2014/09/pami05.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>25%</td><td>999</td><td>251</td><td>748</td><td>110</td><td>509</td><td>113</td></tr><tr><td>560e0e58d0059259ddf86fcec1fa7975dee6a868</td><td>youtube_faces</td><td>YouTubeFaces</td><td><a href="papers/560e0e58d0059259ddf86fcec1fa7975dee6a868.html">Face recognition in unconstrained videos with matched background similarity</a></td><td><a href="http://www.cs.tau.ac.il/~wolf/papers/lvfw.pdf">[pdf]</a></td><td>CVPR 2011</td><td>edu</td><td>Open University of Israel</td><td>32.77824165</td><td>34.99565673</td><td>50%</td><td>485</td><td>244</td><td>240</td><td>32</td><td>290</td><td>140</td></tr><tr><td>3607afdb204de9a5a9300ae98aa4635d9effcda2</td><td>sheffield</td><td>Sheffield Face</td><td><a href="papers/3607afdb204de9a5a9300ae98aa4635d9effcda2.html">Face Description with Local Binary Patterns: Application to Face Recognition</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.244">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>24%</td><td>999</td><td>238</td><td>761</td><td>65</td><td>483</td><td>87</td></tr><tr><td>853bd61bc48a431b9b1c7cab10c603830c488e39</td><td>casia_webface</td><td>CASIA Webface</td><td><a href="papers/853bd61bc48a431b9b1c7cab10c603830c488e39.html">Learning Face Representation from Scratch</a></td><td><a href="http://pdfs.semanticscholar.org/b8a2/0ed7e74325da76d7183d1ab77b082a92b447.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>53%</td><td>436</td><td>233</td><td>203</td><td>32</td><td>284</td><td>115</td></tr><tr><td>2830fb5282de23d7784b4b4bc37065d27839a412</td><td>h3d</td><td>H3D</td><td><a href="papers/2830fb5282de23d7784b4b4bc37065d27839a412.html">Poselets: Body part detectors trained using 3D human pose annotations</a></td><td><a href="http://vision.stanford.edu/teaching/cs231b_spring1213/papers/ICCV09_BourdevMalik.pdf">[pdf]</a></td><td>2009 IEEE 12th International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>32%</td><td>707</td><td>223</td><td>484</td><td>62</td><td>482</td><td>18</td></tr><tr><td>10d6b12fa07c7c8d6c8c3f42c7f1c061c131d4c5</td><td>inria_person</td><td>INRIA Pedestrian</td><td><a href="papers/10d6b12fa07c7c8d6c8c3f42c7f1c061c131d4c5.html">Histograms of oriented gradients for human detection</a></td><td><a href="http://nichol.as/papers/Dalai/Histograms%20of%20oriented%20gradients%20for%20human%20detection.pdf">[pdf]</a></td><td>2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)</td><td></td><td></td><td></td><td></td><td>22%</td><td>999</td><td>217</td><td>782</td><td>67</td><td>520</td><td>22</td></tr><tr><td>55206f0b5f57ce17358999145506cd01e570358c</td><td>orl</td><td>ORL</td><td><a href="papers/55206f0b5f57ce17358999145506cd01e570358c.html">O M 4 . 1 The Subject Database 4 . 2 Experiment Plan 5 . 1 Varying the Overlap 4 Experimental Setup 5 Parameterisation Results</a></td><td><a href="http://pdfs.semanticscholar.org/5520/6f0b5f57ce17358999145506cd01e570358c.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>21%</td><td>999</td><td>214</td><td>785</td><td>96</td><td>550</td><td>57</td></tr><tr><td>9055b155cbabdce3b98e16e5ac9c0edf00f9552f</td><td>morph</td><td>MORPH Commercial</td><td><a href="papers/9055b155cbabdce3b98e16e5ac9c0edf00f9552f.html">MORPH: a longitudinal image database of normal adult age-progression</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/FGR.2006.78">[pdf]</a></td><td>7th International Conference on Automatic Face and Gesture Recognition (FGR06)</td><td></td><td></td><td></td><td></td><td>46%</td><td>424</td><td>195</td><td>229</td><td>27</td><td>231</td><td>155</td></tr><tr><td>9055b155cbabdce3b98e16e5ac9c0edf00f9552f</td><td>morph_nc</td><td>MORPH Non-Commercial</td><td><a href="papers/9055b155cbabdce3b98e16e5ac9c0edf00f9552f.html">MORPH: a longitudinal image database of normal adult age-progression</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/FGR.2006.78">[pdf]</a></td><td>7th International Conference on Automatic Face and Gesture Recognition (FGR06)</td><td></td><td></td><td></td><td></td><td>46%</td><td>424</td><td>195</td><td>229</td><td>27</td><td>231</td><td>155</td></tr><tr><td>93884e46c49f7ae1c7c34046fbc28882f2bd6341</td><td>kdef</td><td>KDEF</td><td><a href="papers/93884e46c49f7ae1c7c34046fbc28882f2bd6341.html">Gaze fixation and the neural circuitry of face processing in autism</a></td><td><a href="{'url': 'http://doi.org/10.1038/nn1421', 'linkType': 'nature'}">[pdf]</a></td><td>Nature Neuroscience</td><td></td><td></td><td></td><td></td><td>31%</td><td>608</td><td>190</td><td>418</td><td>92</td><td>463</td><td>0</td></tr><tr><td>8a3c5507237957d013a0fe0f082cab7f757af6ee</td><td>mafl</td><td>MAFL</td><td><a href="papers/8a3c5507237957d013a0fe0f082cab7f757af6ee.html">Facial Landmark Detection by Deep Multi-task Learning</a></td><td><a href="http://pdfs.semanticscholar.org/fcd7/1c18192928a2e0b264edd4d919ab2f8f652a.pdf">[pdf]</a></td><td></td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>48%</td><td>383</td><td>182</td><td>201</td><td>25</td><td>259</td><td>60</td></tr><tr><td>8a3c5507237957d013a0fe0f082cab7f757af6ee</td><td>mafl</td><td>MAFL</td><td><a href="papers/8a3c5507237957d013a0fe0f082cab7f757af6ee.html">Facial Landmark Detection by Deep Multi-task Learning</a></td><td><a href="http://pdfs.semanticscholar.org/fcd7/1c18192928a2e0b264edd4d919ab2f8f652a.pdf">[pdf]</a></td><td></td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>48%</td><td>383</td><td>182</td><td>201</td><td>25</td><td>259</td><td>60</td></tr><tr><td>8a3c5507237957d013a0fe0f082cab7f757af6ee</td><td>mtfl</td><td>MTFL</td><td><a href="papers/8a3c5507237957d013a0fe0f082cab7f757af6ee.html">Facial Landmark Detection by Deep Multi-task Learning</a></td><td><a href="http://pdfs.semanticscholar.org/fcd7/1c18192928a2e0b264edd4d919ab2f8f652a.pdf">[pdf]</a></td><td></td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>48%</td><td>383</td><td>182</td><td>201</td><td>25</td><td>259</td><td>60</td></tr><tr><td>8a3c5507237957d013a0fe0f082cab7f757af6ee</td><td>mtfl</td><td>MTFL</td><td><a href="papers/8a3c5507237957d013a0fe0f082cab7f757af6ee.html">Facial Landmark Detection by Deep Multi-task Learning</a></td><td><a href="http://pdfs.semanticscholar.org/fcd7/1c18192928a2e0b264edd4d919ab2f8f652a.pdf">[pdf]</a></td><td></td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>48%</td><td>383</td><td>182</td><td>201</td><td>25</td><td>259</td><td>60</td></tr><tr><td>6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3</td><td>cuhk03</td><td>CUHK03</td><td><a href="papers/6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3.html">DeepReID: Deep Filter Pairing Neural Network for Person Re-identification</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Li_DeepReID_Deep_Filter_2014_CVPR_paper.pdf">[pdf]</a></td><td>2014 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>35%</td><td>512</td><td>180</td><td>332</td><td>29</td><td>323</td><td>4</td></tr><tr><td>3325860c0c82a93b2eac654f5324dd6a776f609e</td><td>mpii_human_pose</td><td>MPII Human Pose</td><td><a href="papers/3325860c0c82a93b2eac654f5324dd6a776f609e.html">2D Human Pose Estimation: New Benchmark and State of the Art Analysis</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6909866', 'linkType': 'ieee'}">[pdf]</a></td><td>2014 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>50%</td><td>356</td><td>179</td><td>177</td><td>21</td><td>299</td><td>3</td></tr><tr><td>95f12d27c3b4914e0668a268360948bce92f7db3</td><td>helen</td><td>Helen</td><td><a href="papers/95f12d27c3b4914e0668a268360948bce92f7db3.html">Interactive Facial Feature Localization</a></td><td><a href="http://pdfs.semanticscholar.org/95f1/2d27c3b4914e0668a268360948bce92f7db3.pdf">[pdf]</a></td><td></td><td>edu</td><td>University of Illinois, Urbana-Champaign</td><td>40.11116745</td><td>-88.22587665</td><td>52%</td><td>339</td><td>177</td><td>162</td><td>27</td><td>208</td><td>100</td></tr><tr><td>2724ba85ec4a66de18da33925e537f3902f21249</td><td>cofw</td><td>COFW</td><td><a href="papers/2724ba85ec4a66de18da33925e537f3902f21249.html">Robust Face Landmark Estimation under Occlusion</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6751298', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>55%</td><td>305</td><td>167</td><td>138</td><td>16</td><td>186</td><td>95</td></tr><tr><td>6273b3491e94ea4dd1ce42b791d77bdc96ee73a8</td><td>viper</td><td>VIPeR</td><td><a href="papers/6273b3491e94ea4dd1ce42b791d77bdc96ee73a8.html">Evaluating Appearance Models for Recognition, Reacquisition, and Tracking</a></td><td><a href="http://pdfs.semanticscholar.org/6273/b3491e94ea4dd1ce42b791d77bdc96ee73a8.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>27%</td><td>584</td><td>159</td><td>425</td><td>38</td><td>336</td><td>9</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td>aflw</td><td>AFLW</td><td><a href="papers/a74251efa970b92925b89eeef50a5e37d9281ad0.html">Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization</a></td><td><a href="http://lrs.icg.tugraz.at/pubs/koestinger_befit_11.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>53%</td><td>292</td><td>155</td><td>137</td><td>38</td><td>207</td><td>59</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td>imm_face</td><td>IMM Face Dataset</td><td><a href="papers/a74251efa970b92925b89eeef50a5e37d9281ad0.html">Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization</a></td><td><a href="http://lrs.icg.tugraz.at/pubs/koestinger_befit_11.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>53%</td><td>292</td><td>155</td><td>137</td><td>38</td><td>207</td><td>59</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td>muct</td><td>MUCT</td><td><a href="papers/a74251efa970b92925b89eeef50a5e37d9281ad0.html">Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization</a></td><td><a href="http://lrs.icg.tugraz.at/pubs/koestinger_befit_11.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>53%</td><td>292</td><td>155</td><td>137</td><td>38</td><td>207</td><td>59</td></tr><tr><td>4308bd8c28e37e2ed9a3fcfe74d5436cce34b410</td><td>market_1501</td><td>Market 1501</td><td><a href="papers/4308bd8c28e37e2ed9a3fcfe74d5436cce34b410.html">Scalable Person Re-identification: A Benchmark</a></td><td><a href="https://www.microsoft.com/en-us/research/wp-content/uploads/2017/01/ICCV15-ReIDDataset.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>38%</td><td>394</td><td>149</td><td>245</td><td>18</td><td>271</td><td>3</td></tr><tr><td>2a75f34663a60ab1b04a0049ed1d14335129e908</td><td>mmi_facial_expression</td><td>MMI Facial Expression Dataset</td><td><a href="papers/2a75f34663a60ab1b04a0049ed1d14335129e908.html">Web-based database for facial expression analysis</a></td><td><a href="http://ibug.doc.ic.ac.uk/media/uploads/documents/PanticEtAl-ICME2005-final.pdf">[pdf]</a></td><td>2005 IEEE International Conference on Multimedia and Expo</td><td></td><td></td><td></td><td></td><td>32%</td><td>440</td><td>142</td><td>298</td><td>44</td><td>258</td><td>82</td></tr><tr><td>639937b3a1b8bded3f7e9a40e85bd3770016cf3c</td><td>bfm</td><td>BFM</td><td><a href="papers/639937b3a1b8bded3f7e9a40e85bd3770016cf3c.html">A 3D Face Model for Pose and Illumination Invariant Face Recognition</a></td><td><a href="https://pdfs.semanticscholar.org/6399/37b3a1b8bded3f7e9a40e85bd3770016cf3c.pdf">[pdf]</a></td><td>2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance</td><td></td><td></td><td></td><td></td><td>41%</td><td>323</td><td>131</td><td>192</td><td>29</td><td>221</td><td>25</td></tr><tr><td>cc589c499dcf323fe4a143bbef0074c3e31f9b60</td><td>bu_3dfe</td><td>BU-3DFE</td><td><a href="papers/cc589c499dcf323fe4a143bbef0074c3e31f9b60.html">A 3D facial expression database for facial behavior research</a></td><td><a href="http://www.cs.binghamton.edu/~lijun/Research/3DFE/Yin_FGR06_a.pdf">[pdf]</a></td><td>7th International Conference on Automatic Face and Gesture Recognition (FGR06)</td><td>edu</td><td>SUNY Binghamton</td><td>42.08779975</td><td>-75.97066066</td><td>24%</td><td>555</td><td>131</td><td>424</td><td>47</td><td>283</td><td>48</td></tr><tr><td>696ca58d93f6404fea0fc75c62d1d7b378f47628</td><td>coco</td><td>COCO</td><td><a href="papers/696ca58d93f6404fea0fc75c62d1d7b378f47628.html">Microsoft COCO Captions: Data Collection and Evaluation Server</a></td><td><a href="http://pdfs.semanticscholar.org/ba95/81c33a7eebe87c50e61763e4c8d1723538f2.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>46%</td><td>283</td><td>129</td><td>154</td><td>16</td><td>231</td><td>4</td></tr><tr><td>4053e3423fb70ad9140ca89351df49675197196a</td><td>bio_id</td><td>BioID Face</td><td><a href="papers/4053e3423fb70ad9140ca89351df49675197196a.html">Robust Face Detection Using the Hausdorff Distance</a></td><td><a href="http://pdfs.semanticscholar.org/4053/e3423fb70ad9140ca89351df49675197196a.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>26%</td><td>498</td><td>127</td><td>371</td><td>55</td><td>319</td><td>32</td></tr><tr><td>3765df816dc5a061bc261e190acc8bdd9d47bec0</td><td>rafd</td><td>RaFD</td><td><a href="papers/3765df816dc5a061bc261e190acc8bdd9d47bec0.html">Presentation and validation of the Radboud Faces Database</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/3765/df816dc5a061bc261e190acc8bdd9d47bec0.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>28%</td><td>446</td><td>127</td><td>319</td><td>43</td><td>307</td><td>19</td></tr><tr><td>2fda164863a06a92d3a910b96eef927269aeb730</td><td>names_and_faces_news</td><td>News Dataset</td><td><a href="papers/2fda164863a06a92d3a910b96eef927269aeb730.html">Names and faces in the news</a></td><td><a href="http://www.cs.utexas.edu/~grauman/courses/spring2007/395T/papers/berg_names_and_faces.pdf">[pdf]</a></td><td>Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.</td><td></td><td></td><td></td><td></td><td>41%</td><td>294</td><td>120</td><td>174</td><td>24</td><td>207</td><td>45</td></tr><tr><td>4b1d23d17476fcf78f4cbadf69fb130b1aa627c0</td><td>leeds_sports_pose</td><td>Leeds Sports Pose</td><td><a href="papers/4b1d23d17476fcf78f4cbadf69fb130b1aa627c0.html">Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation</a></td><td><a href="http://pdfs.semanticscholar.org/4b1d/23d17476fcf78f4cbadf69fb130b1aa627c0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>278</td><td>119</td><td>159</td><td>12</td><td>198</td><td>2</td></tr><tr><td>2258e01865367018ed6f4262c880df85b94959f8</td><td>mot</td><td>MOT</td><td><a href="papers/2258e01865367018ed6f4262c880df85b94959f8.html">Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics</a></td><td><a href="http://pdfs.semanticscholar.org/2e0b/00f4043e2d4b04c59c88bb54bcd907d0dcd4.pdf">[pdf]</a></td><td>EURASIP J. Image and Video Processing</td><td></td><td></td><td></td><td></td><td>20%</td><td>586</td><td>119</td><td>467</td><td>48</td><td>336</td><td>3</td></tr><tr><td>2258e01865367018ed6f4262c880df85b94959f8</td><td>mot</td><td>MOT</td><td><a href="papers/2258e01865367018ed6f4262c880df85b94959f8.html">Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics</a></td><td><a href="http://pdfs.semanticscholar.org/2e0b/00f4043e2d4b04c59c88bb54bcd907d0dcd4.pdf">[pdf]</a></td><td>EURASIP J. Image and Video Processing</td><td></td><td></td><td></td><td></td><td>20%</td><td>586</td><td>119</td><td>467</td><td>48</td><td>336</td><td>3</td></tr><tr><td>2258e01865367018ed6f4262c880df85b94959f8</td><td>mot</td><td>MOT</td><td><a href="papers/2258e01865367018ed6f4262c880df85b94959f8.html">Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics</a></td><td><a href="http://pdfs.semanticscholar.org/2e0b/00f4043e2d4b04c59c88bb54bcd907d0dcd4.pdf">[pdf]</a></td><td>EURASIP J. Image and Video Processing</td><td></td><td></td><td></td><td></td><td>20%</td><td>586</td><td>119</td><td>467</td><td>48</td><td>336</td><td>3</td></tr><tr><td>4b1d23d17476fcf78f4cbadf69fb130b1aa627c0</td><td>stickmen_pascal</td><td>Stickmen PASCAL</td><td><a href="papers/4b1d23d17476fcf78f4cbadf69fb130b1aa627c0.html">Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation</a></td><td><a href="http://pdfs.semanticscholar.org/4b1d/23d17476fcf78f4cbadf69fb130b1aa627c0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>278</td><td>119</td><td>159</td><td>12</td><td>198</td><td>2</td></tr><tr><td>4b1d23d17476fcf78f4cbadf69fb130b1aa627c0</td><td>stickmen_pascal</td><td>Stickmen PASCAL</td><td><a href="papers/4b1d23d17476fcf78f4cbadf69fb130b1aa627c0.html">Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation</a></td><td><a href="http://pdfs.semanticscholar.org/4b1d/23d17476fcf78f4cbadf69fb130b1aa627c0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>278</td><td>119</td><td>159</td><td>12</td><td>198</td><td>2</td></tr><tr><td>6dd0597f8513dc100cd0bc1b493768cde45098a9</td><td>stickmen_buffy</td><td>Buffy Stickmen</td><td><a href="papers/6dd0597f8513dc100cd0bc1b493768cde45098a9.html">Learning to parse images of articulated bodies</a></td><td><a href="http://pdfs.semanticscholar.org/9cd7/4c43dbf9be0b9caae4606ee53e6d45850471.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>31%</td><td>373</td><td>117</td><td>256</td><td>30</td><td>238</td><td>2</td></tr><tr><td>6dd0597f8513dc100cd0bc1b493768cde45098a9</td><td>stickmen_buffy</td><td>Buffy Stickmen</td><td><a href="papers/6dd0597f8513dc100cd0bc1b493768cde45098a9.html">Learning to parse images of articulated bodies</a></td><td><a href="http://pdfs.semanticscholar.org/9cd7/4c43dbf9be0b9caae4606ee53e6d45850471.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>31%</td><td>373</td><td>117</td><td>256</td><td>30</td><td>238</td><td>2</td></tr><tr><td>3316521a5527c7700af8ae6aef32a79a8b83672c</td><td>tud_campus</td><td>TUD-Campus</td><td><a href="papers/3316521a5527c7700af8ae6aef32a79a8b83672c.html">People-tracking-by-detection and people-detection-by-tracking</a></td><td><a href="http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/Conference/data/papers/243.pdf">[pdf]</a></td><td>2008 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>22%</td><td>529</td><td>116</td><td>413</td><td>41</td><td>316</td><td>1</td></tr><tr><td>3316521a5527c7700af8ae6aef32a79a8b83672c</td><td>tud_crossing</td><td>TUD-Crossing</td><td><a href="papers/3316521a5527c7700af8ae6aef32a79a8b83672c.html">People-tracking-by-detection and people-detection-by-tracking</a></td><td><a href="http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/Conference/data/papers/243.pdf">[pdf]</a></td><td>2008 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>22%</td><td>529</td><td>116</td><td>413</td><td>41</td><td>316</td><td>1</td></tr><tr><td>3316521a5527c7700af8ae6aef32a79a8b83672c</td><td>tud_pedestrian</td><td>TUD-Pedestrian</td><td><a href="papers/3316521a5527c7700af8ae6aef32a79a8b83672c.html">People-tracking-by-detection and people-detection-by-tracking</a></td><td><a href="http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/Conference/data/papers/243.pdf">[pdf]</a></td><td>2008 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>22%</td><td>529</td><td>116</td><td>413</td><td>41</td><td>316</td><td>1</td></tr><tr><td>140c95e53c619eac594d70f6369f518adfea12ef</td><td>ijb_a</td><td>IJB-A</td><td><a href="papers/140c95e53c619eac594d70f6369f518adfea12ef.html">Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2015/app/1B_089_ext.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>48%</td><td>222</td><td>107</td><td>115</td><td>21</td><td>158</td><td>48</td></tr><tr><td>4c170a0dcc8de75587dae21ca508dab2f9343974</td><td>face_tracer</td><td>FaceTracer</td><td><a href="papers/4c170a0dcc8de75587dae21ca508dab2f9343974.html">FaceTracer: A Search Engine for Large Collections of Images with Faces</a></td><td><a href="http://pdfs.semanticscholar.org/73a8/1d311eedac8dea3ca24dc15b6990fa4a725e.pdf">[pdf]</a></td><td></td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>48%</td><td>218</td><td>105</td><td>113</td><td>17</td><td>146</td><td>52</td></tr><tr><td>4c170a0dcc8de75587dae21ca508dab2f9343974</td><td>face_tracer</td><td>FaceTracer</td><td><a href="papers/4c170a0dcc8de75587dae21ca508dab2f9343974.html">FaceTracer: A Search Engine for Large Collections of Images with Faces</a></td><td><a href="http://pdfs.semanticscholar.org/73a8/1d311eedac8dea3ca24dc15b6990fa4a725e.pdf">[pdf]</a></td><td></td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>48%</td><td>218</td><td>105</td><td>113</td><td>17</td><td>146</td><td>52</td></tr><tr><td>7808937b46acad36e43c30ae4e9f3fd57462853d</td><td>berkeley_pose</td><td>BPAD</td><td><a href="papers/7808937b46acad36e43c30ae4e9f3fd57462853d.html">Describing people: A poselet-based approach to attribute classification</a></td><td><a href="http://ttic.uchicago.edu/~smaji/papers/attributes-iccv11.pdf">[pdf]</a></td><td>2011 International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>43%</td><td>221</td><td>96</td><td>125</td><td>14</td><td>160</td><td>23</td></tr><tr><td>e8de844fefd54541b71c9823416daa238be65546</td><td>visual_phrases</td><td>Phrasal Recognition</td><td><a href="papers/e8de844fefd54541b71c9823416daa238be65546.html">Recognition using visual phrases</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5995711', 'linkType': 'ieee'}">[pdf]</a></td><td>CVPR 2011</td><td></td><td></td><td></td><td></td><td>41%</td><td>233</td><td>95</td><td>138</td><td>18</td><td>174</td><td>5</td></tr><tr><td>16c7c31a7553d99f1837fc6e88e77b5ccbb346b8</td><td>prid</td><td>PRID</td><td><a href="papers/16c7c31a7553d99f1837fc6e88e77b5ccbb346b8.html">Person Re-identification by Descriptive and Discriminative Classification</a></td><td><a href="http://pdfs.semanticscholar.org/4c1b/f0592be3e535faf256c95e27982db9b3d3d3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>27%</td><td>352</td><td>94</td><td>258</td><td>26</td><td>195</td><td>3</td></tr><tr><td>1dc35905a1deff8bc74688f2d7e2f48fd2273275</td><td>caltech_pedestrians</td><td>Caltech Pedestrians</td><td><a href="papers/1dc35905a1deff8bc74688f2d7e2f48fd2273275.html">Pedestrian detection: A benchmark</a></td><td><a href="http://vision.ucsd.edu/~pdollar/files/papers/DollarCVPR09peds.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>17%</td><td>519</td><td>89</td><td>430</td><td>27</td><td>286</td><td>2</td></tr><tr><td>1dc35905a1deff8bc74688f2d7e2f48fd2273275</td><td>caltech_pedestrians</td><td>Caltech Pedestrians</td><td><a href="papers/1dc35905a1deff8bc74688f2d7e2f48fd2273275.html">Pedestrian detection: A benchmark</a></td><td><a href="http://vision.ucsd.edu/~pdollar/files/papers/DollarCVPR09peds.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>17%</td><td>519</td><td>89</td><td>430</td><td>27</td><td>286</td><td>2</td></tr><tr><td>35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62</td><td>coco_qa</td><td>COCO QA</td><td><a href="papers/35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62.html">Exploring Models and Data for Image Question Answering</a></td><td><a href="http://pdfs.semanticscholar.org/aa79/9c29c0d44ece1864467af520fe70540c069b.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>191</td><td>83</td><td>108</td><td>12</td><td>163</td><td>1</td></tr><tr><td>291265db88023e92bb8c8e6390438e5da148e8f5</td><td>msceleb</td><td>MsCeleb</td><td><a href="papers/291265db88023e92bb8c8e6390438e5da148e8f5.html">MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/4603/cb8e05258bb0572ae912ad20903b8f99f4b1.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>50%</td><td>167</td><td>83</td><td>84</td><td>15</td><td>131</td><td>27</td></tr><tr><td>13f06b08f371ba8b5d31c3e288b4deb61335b462</td><td>eth_andreas_ess</td><td>ETHZ Pedestrian</td><td><a href="papers/13f06b08f371ba8b5d31c3e288b4deb61335b462.html">Depth and Appearance for Mobile Scene Analysis</a></td><td><a href="http://www.mmp.rwth-aachen.de/publications/pdf/ess-depthandappearance-iccv07.pdf/at_download/file">[pdf]</a></td><td>2007 IEEE 11th International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>25%</td><td>319</td><td>79</td><td>240</td><td>27</td><td>192</td><td>0</td></tr><tr><td>52d7eb0fbc3522434c13cc247549f74bb9609c5d</td><td>wider_face</td><td>WIDER FACE</td><td><a href="papers/52d7eb0fbc3522434c13cc247549f74bb9609c5d.html">WIDER FACE: A Face Detection Benchmark</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1511.06523.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>53%</td><td>148</td><td>78</td><td>70</td><td>16</td><td>107</td><td>34</td></tr><tr><td>2485c98aa44131d1a2f7d1355b1e372f2bb148ad</td><td>cas_peal</td><td>CAS-PEAL</td><td><a href="papers/2485c98aa44131d1a2f7d1355b1e372f2bb148ad.html">The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations</a></td><td><a href="https://doi.org/10.1109/TSMCA.2007.909557">[pdf]</a></td><td>IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans</td><td></td><td></td><td></td><td></td><td>18%</td><td>415</td><td>76</td><td>339</td><td>39</td><td>182</td><td>35</td></tr><tr><td>1aad2da473888cb7ebc1bfaa15bfa0f1502ce005</td><td>jpl_pose</td><td>JPL-Interaction dataset</td><td><a href="papers/1aad2da473888cb7ebc1bfaa15bfa0f1502ce005.html">First-Person Activity Recognition: What Are They Doing to Me?</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2013/papers/Ryoo_First-Person_Activity_Recognition_2013_CVPR_paper.pdf">[pdf]</a></td><td>2013 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>51%</td><td>148</td><td>76</td><td>72</td><td>8</td><td>109</td><td>3</td></tr><tr><td>2485c98aa44131d1a2f7d1355b1e372f2bb148ad</td><td>m2vts</td><td>m2vts</td><td><a href="papers/2485c98aa44131d1a2f7d1355b1e372f2bb148ad.html">The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations</a></td><td><a href="https://doi.org/10.1109/TSMCA.2007.909557">[pdf]</a></td><td>IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans</td><td></td><td></td><td></td><td></td><td>18%</td><td>415</td><td>76</td><td>339</td><td>39</td><td>182</td><td>35</td></tr><tr><td>436f798d1a4e54e5947c1e7d7375c31b2bdb4064</td><td>tud_multiview</td><td>TUD-Multiview</td><td><a href="papers/436f798d1a4e54e5947c1e7d7375c31b2bdb4064.html">Monocular 3D pose estimation and tracking by detection</a></td><td><a href="http://lmb.informatik.uni-freiburg.de/lectures/seminar_brox/seminar_ws1011/cvpr10_andriluka.pdf">[pdf]</a></td><td>2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>25%</td><td>302</td><td>76</td><td>226</td><td>32</td><td>199</td><td>1</td></tr><tr><td>436f798d1a4e54e5947c1e7d7375c31b2bdb4064</td><td>tud_stadtmitte</td><td>TUD-Stadtmitte</td><td><a href="papers/436f798d1a4e54e5947c1e7d7375c31b2bdb4064.html">Monocular 3D pose estimation and tracking by detection</a></td><td><a href="http://lmb.informatik.uni-freiburg.de/lectures/seminar_brox/seminar_ws1011/cvpr10_andriluka.pdf">[pdf]</a></td><td>2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>25%</td><td>302</td><td>76</td><td>226</td><td>32</td><td>199</td><td>1</td></tr><tr><td>133f01aec1534604d184d56de866a4bd531dac87</td><td>lfw_a</td><td>LFW-a</td><td><a href="papers/133f01aec1534604d184d56de866a4bd531dac87.html">Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.230">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>42%</td><td>177</td><td>75</td><td>102</td><td>15</td><td>102</td><td>54</td></tr><tr><td>1be498d4bbc30c3bfd0029114c784bc2114d67c0</td><td>adience</td><td>Adience</td><td><a href="papers/1be498d4bbc30c3bfd0029114c784bc2114d67c0.html">Age and Gender Estimation of Unfiltered Faces</a></td><td><a href="http://www.openu.ac.il/home/hassner/Adience/EidingerEnbarHassner_tifs.pdf">[pdf]</a></td><td>IEEE Transactions on Information Forensics and Security</td><td></td><td></td><td></td><td></td><td>43%</td><td>168</td><td>72</td><td>96</td><td>7</td><td>89</td><td>53</td></tr><tr><td>21d9d0deed16f0ad62a4865e9acf0686f4f15492</td><td>images_of_groups</td><td>Images of Groups</td><td><a href="papers/21d9d0deed16f0ad62a4865e9acf0686f4f15492.html">Understanding images of groups of people</a></td><td><a href="http://amp.ece.cmu.edu/people/Andy/Andy_files/cvpr09.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>36%</td><td>202</td><td>72</td><td>130</td><td>12</td><td>126</td><td>24</td></tr><tr><td>18010284894ed0edcca74e5bf768ee2e15ef7841</td><td>deep_fashion</td><td>DeepFashion</td><td><a href="papers/18010284894ed0edcca74e5bf768ee2e15ef7841.html">DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7780493', 'linkType': 'ieee'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>47%</td><td>150</td><td>71</td><td>79</td><td>4</td><td>111</td><td>8</td></tr><tr><td>18010284894ed0edcca74e5bf768ee2e15ef7841</td><td>deep_fashion</td><td>DeepFashion</td><td><a href="papers/18010284894ed0edcca74e5bf768ee2e15ef7841.html">DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7780493', 'linkType': 'ieee'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>47%</td><td>150</td><td>71</td><td>79</td><td>4</td><td>111</td><td>8</td></tr><tr><td>4e4746094bf60ee83e40d8597a6191e463b57f76</td><td>leeds_sports_pose_extended</td><td>Leeds Sports Pose Extended</td><td><a href="papers/4e4746094bf60ee83e40d8597a6191e463b57f76.html">Learning effective human pose estimation from inaccurate annotation</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5995318', 'linkType': 'ieee'}">[pdf]</a></td><td>CVPR 2011</td><td></td><td></td><td></td><td></td><td>40%</td><td>173</td><td>70</td><td>103</td><td>9</td><td>116</td><td>2</td></tr><tr><td>2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9</td><td>graz</td><td>Graz Pedestrian</td><td><a href="papers/2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9.html">Generic object recognition with boosting</a></td><td><a href="http://www.emt.tu-graz.ac.at/~pinz/onlinepapers/Reprint_Vol_28_No_3_2006.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>24%</td><td>286</td><td>69</td><td>217</td><td>16</td><td>189</td><td>0</td></tr><tr><td>2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9</td><td>graz</td><td>Graz Pedestrian</td><td><a href="papers/2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9.html">Generic object recognition with boosting</a></td><td><a href="http://www.emt.tu-graz.ac.at/~pinz/onlinepapers/Reprint_Vol_28_No_3_2006.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>24%</td><td>286</td><td>69</td><td>217</td><td>16</td><td>189</td><td>0</td></tr><tr><td>2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9</td><td>graz</td><td>Graz Pedestrian</td><td><a href="papers/2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9.html">Generic object recognition with boosting</a></td><td><a href="http://www.emt.tu-graz.ac.at/~pinz/onlinepapers/Reprint_Vol_28_No_3_2006.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>24%</td><td>286</td><td>69</td><td>217</td><td>16</td><td>189</td><td>0</td></tr><tr><td>44484d2866f222bbb9b6b0870890f9eea1ffb2d0</td><td>cuhk01</td><td>CUHK01</td><td><a href="papers/44484d2866f222bbb9b6b0870890f9eea1ffb2d0.html">Human Reidentification with Transferred Metric Learning</a></td><td><a href="http://pdfs.semanticscholar.org/4448/4d2866f222bbb9b6b0870890f9eea1ffb2d0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>26%</td><td>258</td><td>67</td><td>191</td><td>12</td><td>141</td><td>1</td></tr><tr><td>96e0cfcd81cdeb8282e29ef9ec9962b125f379b0</td><td>megaface</td><td>MegaFace</td><td><a href="papers/96e0cfcd81cdeb8282e29ef9ec9962b125f379b0.html">The MegaFace Benchmark: 1 Million Faces for Recognition at Scale</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2016.527">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>55%</td><td>121</td><td>66</td><td>55</td><td>11</td><td>98</td><td>20</td></tr><tr><td>96e0cfcd81cdeb8282e29ef9ec9962b125f379b0</td><td>megaface</td><td>MegaFace</td><td><a href="papers/96e0cfcd81cdeb8282e29ef9ec9962b125f379b0.html">The MegaFace Benchmark: 1 Million Faces for Recognition at Scale</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2016.527">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>55%</td><td>121</td><td>66</td><td>55</td><td>11</td><td>98</td><td>20</td></tr><tr><td>9361b784e73e9238d5cefbea5ac40d35d1e3103f</td><td>towncenter</td><td>TownCenter</td><td><a href="papers/9361b784e73e9238d5cefbea5ac40d35d1e3103f.html">Stable Multi-Target Tracking in Real-Time Surveillance Video (Preprint)</a></td><td><a href="http://pdfs.semanticscholar.org/9361/b784e73e9238d5cefbea5ac40d35d1e3103f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>21%</td><td>310</td><td>64</td><td>246</td><td>24</td><td>177</td><td>4</td></tr><tr><td>10195a163ab6348eef37213a46f60a3d87f289c5</td><td>imdb_wiki</td><td>IMDB</td><td><a href="papers/10195a163ab6348eef37213a46f60a3d87f289c5.html">Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks</a></td><td><a href="https://doi.org/10.1007/s11263-016-0940-3">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>44%</td><td>133</td><td>59</td><td>74</td><td>14</td><td>90</td><td>28</td></tr><tr><td>10195a163ab6348eef37213a46f60a3d87f289c5</td><td>imdb_wiki</td><td>IMDB</td><td><a href="papers/10195a163ab6348eef37213a46f60a3d87f289c5.html">Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks</a></td><td><a href="https://doi.org/10.1007/s11263-016-0940-3">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>44%</td><td>133</td><td>59</td><td>74</td><td>14</td><td>90</td><td>28</td></tr><tr><td>2acf7e58f0a526b957be2099c10aab693f795973</td><td>bosphorus</td><td>The Bosphorus</td><td><a href="papers/2acf7e58f0a526b957be2099c10aab693f795973.html">Bosphorus Database for 3D Face Analysis</a></td><td><a href="http://pdfs.semanticscholar.org/4254/fbba3846008f50671edc9cf70b99d7304543.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>18%</td><td>328</td><td>58</td><td>270</td><td>18</td><td>143</td><td>37</td></tr><tr><td>27a2fad58dd8727e280f97036e0d2bc55ef5424c</td><td>duke_mtmc</td><td>Duke MTMC</td><td><a href="papers/27a2fad58dd8727e280f97036e0d2bc55ef5424c.html">Performance Measures and a Data Set for Multi-target, Multi-camera Tracking</a></td><td><a href="http://pdfs.semanticscholar.org/b5f2/4f49f9a5e47d6601399dc068158ad88d7651.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>136</td><td>58</td><td>78</td><td>6</td><td>107</td><td>0</td></tr><tr><td>56ffa7d906b08d02d6d5a12c7377a57e24ef3391</td><td>unbc_shoulder_pain</td><td>UNBC-McMaster Pain</td><td><a href="papers/56ffa7d906b08d02d6d5a12c7377a57e24ef3391.html">Painful data: The UNBC-McMaster shoulder pain expression archive database</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5771462', 'linkType': 'ieee'}">[pdf]</a></td><td>Face and Gesture 2011</td><td></td><td></td><td></td><td></td><td>32%</td><td>184</td><td>58</td><td>126</td><td>23</td><td>112</td><td>23</td></tr><tr><td>38b55d95189c5e69cf4ab45098a48fba407609b4</td><td>cuhk02</td><td>CUHK02</td><td><a href="papers/38b55d95189c5e69cf4ab45098a48fba407609b4.html">Locally Aligned Feature Transforms across Views</a></td><td><a href="http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/IEEE_CVPR2013/data/Papers/4989d594.pdf">[pdf]</a></td><td>2013 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>24%</td><td>242</td><td>57</td><td>185</td><td>17</td><td>139</td><td>1</td></tr><tr><td>2f5d44dc3e1b5955942133ff872ebd31716ec604</td><td>frav3d</td><td>FRAV3D</td><td><a href="papers/2f5d44dc3e1b5955942133ff872ebd31716ec604.html">2D and 3D face recognition: A survey</a></td><td><a href="http://pdfs.semanticscholar.org/2f5d/44dc3e1b5955942133ff872ebd31716ec604.pdf">[pdf]</a></td><td>Pattern Recognition Letters</td><td></td><td></td><td></td><td></td><td>15%</td><td>389</td><td>57</td><td>332</td><td>28</td><td>198</td><td>17</td></tr><tr><td>a6e695ddd07aad719001c0fc1129328452385949</td><td>yfcc_100m</td><td>YFCC100M</td><td><a href="papers/a6e695ddd07aad719001c0fc1129328452385949.html">The New Data and New Challenges in Multimedia Research</a></td><td><span class="gray">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>36%</td><td>160</td><td>57</td><td>103</td><td>11</td><td>105</td><td>4</td></tr><tr><td>0d3bb75852098b25d90f31d2f48fd0cb4944702b</td><td>face_scrub</td><td>FaceScrub</td><td><a href="papers/0d3bb75852098b25d90f31d2f48fd0cb4944702b.html">A data-driven approach to cleaning large face datasets</a></td><td><a href="https://doi.org/10.1109/ICIP.2014.7025068">[pdf]</a></td><td>2014 IEEE International Conference on Image Processing (ICIP)</td><td>edu</td><td>University of Illinois, Urbana-Champaign</td><td>40.11116745</td><td>-88.22587665</td><td>46%</td><td>123</td><td>56</td><td>67</td><td>6</td><td>95</td><td>21</td></tr><tr><td>b91f54e1581fbbf60392364323d00a0cd43e493c</td><td>bp4d_spontanous</td><td>BP4D-Spontanous</td><td><a href="papers/b91f54e1581fbbf60392364323d00a0cd43e493c.html">A high-resolution spontaneous 3D dynamic facial expression database</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6553788', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>SUNY Binghamton</td><td>42.08779975</td><td>-75.97066066</td><td>36%</td><td>151</td><td>54</td><td>97</td><td>7</td><td>85</td><td>26</td></tr><tr><td>4f93cd09785c6e77bf4bc5a788e079df524c8d21</td><td>soton</td><td>SOTON HiD</td><td><a href="papers/4f93cd09785c6e77bf4bc5a788e079df524c8d21.html">On a large sequence-based human gait database</a></td><td><a href="http://pdfs.semanticscholar.org/4f93/cd09785c6e77bf4bc5a788e079df524c8d21.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>36%</td><td>148</td><td>54</td><td>94</td><td>16</td><td>98</td><td>0</td></tr><tr><td>0df0d1adea39a5bef318b74faa37de7f3e00b452</td><td>mpii_gaze</td><td>MPIIGaze</td><td><a href="papers/0df0d1adea39a5bef318b74faa37de7f3e00b452.html">Appearance-based gaze estimation in the wild</a></td><td><a href="https://scalable.mpi-inf.mpg.de/files/2015/09/zhang_CVPR15.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Max Planck Institute for Informatics</td><td>49.25795660</td><td>7.04577417</td><td>38%</td><td>138</td><td>52</td><td>86</td><td>3</td><td>94</td><td>7</td></tr><tr><td>e4754afaa15b1b53e70743880484b8d0736990ff</td><td>fiw_300</td><td>300-W</td><td><a href="papers/e4754afaa15b1b53e70743880484b8d0736990ff.html">300 Faces In-The-Wild Challenge: database and results</a></td><td><a href="{'url': 'http://doi.org/10.1016/j.imavis.2016.01.002', 'linkType': 'doi'}">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>45%</td><td>114</td><td>51</td><td>63</td><td>10</td><td>70</td><td>31</td></tr><tr><td>e4754afaa15b1b53e70743880484b8d0736990ff</td><td>fiw_300</td><td>300-W</td><td><a href="papers/e4754afaa15b1b53e70743880484b8d0736990ff.html">300 Faces In-The-Wild Challenge: database and results</a></td><td><a href="{'url': 'http://doi.org/10.1016/j.imavis.2016.01.002', 'linkType': 'doi'}">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>45%</td><td>114</td><td>51</td><td>63</td><td>10</td><td>70</td><td>31</td></tr><tr><td>e4754afaa15b1b53e70743880484b8d0736990ff</td><td>fiw_300</td><td>300-W</td><td><a href="papers/e4754afaa15b1b53e70743880484b8d0736990ff.html">300 Faces In-The-Wild Challenge: database and results</a></td><td><a href="{'url': 'http://doi.org/10.1016/j.imavis.2016.01.002', 'linkType': 'doi'}">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>45%</td><td>114</td><td>51</td><td>63</td><td>10</td><td>70</td><td>31</td></tr><tr><td>c0387e788a52f10bf35d4d50659cfa515d89fbec</td><td>mars</td><td>MARS</td><td><a href="papers/c0387e788a52f10bf35d4d50659cfa515d89fbec.html">MARS: A Video Benchmark for Large-Scale Person Re-Identification</a></td><td><a href="http://pdfs.semanticscholar.org/c038/7e788a52f10bf35d4d50659cfa515d89fbec.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>34%</td><td>146</td><td>49</td><td>97</td><td>6</td><td>96</td><td>0</td></tr><tr><td>04c2cda00e5536f4b1508cbd80041e9552880e67</td><td>hipsterwars</td><td>Hipsterwars</td><td><a href="papers/04c2cda00e5536f4b1508cbd80041e9552880e67.html">Hipster Wars: Discovering Elements of Fashion Styles</a></td><td><a href="http://pdfs.semanticscholar.org/04c2/cda00e5536f4b1508cbd80041e9552880e67.pdf">[pdf]</a></td><td></td><td>edu</td><td>Tohoku University</td><td>38.25309450</td><td>140.87365930</td><td>53%</td><td>91</td><td>48</td><td>43</td><td>5</td><td>60</td><td>15</td></tr><tr><td>109df0e8e5969ddf01e073143e83599228a1163f</td><td>multi_pie</td><td>MULTIPIE</td><td><a href="papers/109df0e8e5969ddf01e073143e83599228a1163f.html">Scheduling heterogeneous multi-cores through performance impact estimation (PIE)</a></td><td><a href="http://dl.acm.org/citation.cfm?id=2337184">[pdf]</a></td><td>2012 39th Annual International Symposium on Computer Architecture (ISCA)</td><td></td><td></td><td></td><td></td><td>25%</td><td>192</td><td>48</td><td>144</td><td>8</td><td>99</td><td>0</td></tr><tr><td>32c801cb7fbeb742edfd94cccfca4934baec71da</td><td>ucf_crowd</td><td>UCF-CC-50</td><td><a href="papers/32c801cb7fbeb742edfd94cccfca4934baec71da.html">Multi-source Multi-scale Counting in Extremely Dense Crowd Images</a></td><td><a href="http://www.cs.ucf.edu/~haroon/datafiles/Idrees_Counting_CVPR_2013.pdf">[pdf]</a></td><td>2013 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>38%</td><td>125</td><td>48</td><td>77</td><td>6</td><td>72</td><td>1</td></tr><tr><td>66e6f08873325d37e0ec20a4769ce881e04e964e</td><td>sun_attributes</td><td>SUN</td><td><a href="papers/66e6f08873325d37e0ec20a4769ce881e04e964e.html">The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding</a></td><td><a href="http://www.cc.gatech.edu/~hays/papers/attribute_ijcv.pdf">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>38%</td><td>112</td><td>43</td><td>69</td><td>14</td><td>83</td><td>2</td></tr><tr><td>66e6f08873325d37e0ec20a4769ce881e04e964e</td><td>sun_attributes</td><td>SUN</td><td><a href="papers/66e6f08873325d37e0ec20a4769ce881e04e964e.html">The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding</a></td><td><a href="http://www.cc.gatech.edu/~hays/papers/attribute_ijcv.pdf">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>38%</td><td>112</td><td>43</td><td>69</td><td>14</td><td>83</td><td>2</td></tr><tr><td>6ad5a38df8dd4cdddd74f31996ce096d41219f72</td><td>tud_brussels</td><td>TUD-Brussels</td><td><a href="papers/6ad5a38df8dd4cdddd74f31996ce096d41219f72.html">Multi-cue onboard pedestrian detection</a></td><td><a href="https://www.mpi-inf.mpg.de/fileadmin/inf/d2/wojek/poster_cwojek_cvpr09.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>19%</td><td>217</td><td>41</td><td>176</td><td>14</td><td>131</td><td>1</td></tr><tr><td>6ad5a38df8dd4cdddd74f31996ce096d41219f72</td><td>tud_motionpairs</td><td>TUD-Motionparis</td><td><a href="papers/6ad5a38df8dd4cdddd74f31996ce096d41219f72.html">Multi-cue onboard pedestrian detection</a></td><td><a href="https://www.mpi-inf.mpg.de/fileadmin/inf/d2/wojek/poster_cwojek_cvpr09.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>19%</td><td>217</td><td>41</td><td>176</td><td>14</td><td>131</td><td>1</td></tr><tr><td>0486214fb58ee9a04edfe7d6a74c6d0f661a7668</td><td>chokepoint</td><td>ChokePoint</td><td><a href="papers/0486214fb58ee9a04edfe7d6a74c6d0f661a7668.html">Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition</a></td><td><a href="http://conradsanderson.id.au/pdfs/wong_face_selection_cvpr_biometrics_2011.pdf">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>University of Queensland</td><td>-27.49741805</td><td>153.01316956</td><td>30%</td><td>128</td><td>39</td><td>89</td><td>6</td><td>68</td><td>14</td></tr><tr><td>2a4bbee0b4cf52d5aadbbc662164f7efba89566c</td><td>peta</td><td>PETA</td><td><a href="papers/2a4bbee0b4cf52d5aadbbc662164f7efba89566c.html">Pedestrian Attribute Recognition At Far Distance</a></td><td><a href="http://personal.ie.cuhk.edu.hk/~pluo/pdf/mm14.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>46%</td><td>80</td><td>37</td><td>43</td><td>2</td><td>51</td><td>3</td></tr><tr><td>636b8ffc09b1b23ff714ac8350bb35635e49fa3c</td><td>caltech_10k_web_faces</td><td>Caltech 10K Web Faces</td><td><a href="papers/636b8ffc09b1b23ff714ac8350bb35635e49fa3c.html">Pruning training sets for learning of object categories</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1467308', 'linkType': 'ieee'}">[pdf]</a></td><td>2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)</td><td></td><td></td><td></td><td></td><td>58%</td><td>60</td><td>35</td><td>25</td><td>5</td><td>42</td><td>12</td></tr><tr><td>3b5b6d19d4733ab606c39c69a889f9e67967f151</td><td>qmul_grid</td><td>GRID</td><td><a href="papers/3b5b6d19d4733ab606c39c69a889f9e67967f151.html">Multi-camera activity correlation analysis</a></td><td><a href="http://vision.lbl.gov/Conferences/cvpr/Papers/data/papers/0163.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>25%</td><td>138</td><td>35</td><td>103</td><td>8</td><td>76</td><td>1</td></tr><tr><td>3b5b6d19d4733ab606c39c69a889f9e67967f151</td><td>qmul_grid</td><td>GRID</td><td><a href="papers/3b5b6d19d4733ab606c39c69a889f9e67967f151.html">Multi-camera activity correlation analysis</a></td><td><a href="http://vision.lbl.gov/Conferences/cvpr/Papers/data/papers/0163.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>25%</td><td>138</td><td>35</td><td>103</td><td>8</td><td>76</td><td>1</td></tr><tr><td>214c966d1f9c2a4b66f4535d9a0d4078e63a5867</td><td>brainwash</td><td>Brainwash</td><td><a href="papers/214c966d1f9c2a4b66f4535d9a0d4078e63a5867.html">Brainwash: A Data System for Feature Engineering</a></td><td><a href="http://pdfs.semanticscholar.org/ae44/8015b2ff2bd3b8a5c9a3266f954f5af9ffa9.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>60%</td><td>57</td><td>34</td><td>23</td><td>2</td><td>50</td><td>0</td></tr><tr><td>0dc11a37cadda92886c56a6fb5191ded62099c28</td><td>stickmen_family</td><td>We Are Family Stickmen</td><td><a href="papers/0dc11a37cadda92886c56a6fb5191ded62099c28.html">We Are Family: Joint Pose Estimation of Multiple Persons</a></td><td><a href="http://pdfs.semanticscholar.org/0dc1/1a37cadda92886c56a6fb5191ded62099c28.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>44%</td><td>77</td><td>34</td><td>43</td><td>4</td><td>57</td><td>1</td></tr><tr><td>4df3143922bcdf7db78eb91e6b5359d6ada004d2</td><td>cfd</td><td>CFD</td><td><a href="papers/4df3143922bcdf7db78eb91e6b5359d6ada004d2.html">The Chicago face database: A free stimulus set of faces and norming data.</a></td><td><a href="http://pdfs.semanticscholar.org/4df3/143922bcdf7db78eb91e6b5359d6ada004d2.pdf">[pdf]</a></td><td>Behavior research methods</td><td></td><td></td><td></td><td></td><td>39%</td><td>83</td><td>32</td><td>51</td><td>2</td><td>62</td><td>3</td></tr><tr><td>c900e0ad4c95948baaf0acd8449fde26f9b4952a</td><td>emotio_net</td><td>EmotioNet Database</td><td><a href="papers/c900e0ad4c95948baaf0acd8449fde26f9b4952a.html">EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7780969', 'linkType': 'ieee'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>44%</td><td>72</td><td>32</td><td>40</td><td>7</td><td>54</td><td>8</td></tr><tr><td>0c4a139bb87c6743c7905b29a3cfec27a5130652</td><td>feret</td><td>FERET</td><td><a href="papers/0c4a139bb87c6743c7905b29a3cfec27a5130652.html">The FERET Verification Testing Protocol for Face Recognition Algorithms</a></td><td><a href="http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>28%</td><td>112</td><td>31</td><td>81</td><td>12</td><td>76</td><td>4</td></tr><tr><td>0c4a139bb87c6743c7905b29a3cfec27a5130652</td><td>feret</td><td>FERET</td><td><a href="papers/0c4a139bb87c6743c7905b29a3cfec27a5130652.html">The FERET Verification Testing Protocol for Face Recognition Algorithms</a></td><td><a href="http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>28%</td><td>112</td><td>31</td><td>81</td><td>12</td><td>76</td><td>4</td></tr><tr><td>0c4a139bb87c6743c7905b29a3cfec27a5130652</td><td>feret</td><td>FERET</td><td><a href="papers/0c4a139bb87c6743c7905b29a3cfec27a5130652.html">The FERET Verification Testing Protocol for Face Recognition Algorithms</a></td><td><a href="http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>28%</td><td>112</td><td>31</td><td>81</td><td>12</td><td>76</td><td>4</td></tr><tr><td>0c4a139bb87c6743c7905b29a3cfec27a5130652</td><td>feret</td><td>FERET</td><td><a href="papers/0c4a139bb87c6743c7905b29a3cfec27a5130652.html">The FERET Verification Testing Protocol for Face Recognition Algorithms</a></td><td><a href="http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>28%</td><td>112</td><td>31</td><td>81</td><td>12</td><td>76</td><td>4</td></tr><tr><td>3cd40bfa1ff193a96bde0207e5140a399476466c</td><td>tvhi</td><td>TVHI</td><td><a href="papers/3cd40bfa1ff193a96bde0207e5140a399476466c.html">High Five: Recognising human interactions in TV shows</a></td><td><a href="http://pdfs.semanticscholar.org/3cd4/0bfa1ff193a96bde0207e5140a399476466c.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>34%</td><td>91</td><td>31</td><td>60</td><td>11</td><td>64</td><td>1</td></tr><tr><td>6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c</td><td>afad</td><td>AFAD</td><td><a href="papers/6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c.html">Ordinal Regression with Multiple Output CNN for Age Estimation</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2016.532">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>44%</td><td>68</td><td>30</td><td>38</td><td>8</td><td>49</td><td>7</td></tr><tr><td>fcc6fe6007c322641796cb8792718641856a22a7</td><td>miw</td><td>MIW</td><td><a href="papers/fcc6fe6007c322641796cb8792718641856a22a7.html">Automatic facial makeup detection with application in face recognition</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6612994', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 International Conference on Biometrics (ICB)</td><td>edu</td><td>West Virginia University</td><td>39.65404635</td><td>-79.96475355</td><td>65%</td><td>46</td><td>30</td><td>16</td><td>1</td><td>18</td><td>21</td></tr><tr><td>0a85bdff552615643dd74646ac881862a7c7072d</td><td>pipa</td><td>PIPA</td><td><a href="papers/0a85bdff552615643dd74646ac881862a7c7072d.html">Beyond frontal faces: Improving Person Recognition using multiple cues</a></td><td><a href="https://doi.org/10.1109/CVPR.2015.7299113">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>60%</td><td>50</td><td>30</td><td>19</td><td>2</td><td>40</td><td>4</td></tr><tr><td>51eba481dac6b229a7490f650dff7b17ce05df73</td><td>imsitu</td><td>imSitu</td><td><a href="papers/51eba481dac6b229a7490f650dff7b17ce05df73.html">Situation Recognition: Visual Semantic Role Labeling for Image Understanding</a></td><td><a href="http://grail.cs.washington.edu/wp-content/uploads/2016/09/yatskar2016srv.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>60%</td><td>48</td><td>29</td><td>19</td><td>2</td><td>45</td><td>2</td></tr><tr><td>7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22</td><td>lfw</td><td>LFW</td><td><a href="papers/7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22.html">Labeled Faces in the Wild: A Survey</a></td><td><a href="http://pdfs.semanticscholar.org/7de6/e81d775e9cd7becbfd1bd685f4e2a5eebb22.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>29%</td><td>99</td><td>29</td><td>70</td><td>9</td><td>63</td><td>12</td></tr><tr><td>7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22</td><td>lfw</td><td>LFW</td><td><a href="papers/7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22.html">Labeled Faces in the Wild: A Survey</a></td><td><a href="http://pdfs.semanticscholar.org/7de6/e81d775e9cd7becbfd1bd685f4e2a5eebb22.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>29%</td><td>99</td><td>29</td><td>70</td><td>9</td><td>63</td><td>12</td></tr><tr><td>7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22</td><td>lfw</td><td>LFW</td><td><a href="papers/7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22.html">Labeled Faces in the Wild: A Survey</a></td><td><a href="http://pdfs.semanticscholar.org/7de6/e81d775e9cd7becbfd1bd685f4e2a5eebb22.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>29%</td><td>99</td><td>29</td><td>70</td><td>9</td><td>63</td><td>12</td></tr><tr><td>2bf8541199728262f78d4dced6fb91479b39b738</td><td>clothing_co_parsing</td><td>CCP</td><td><a href="papers/2bf8541199728262f78d4dced6fb91479b39b738.html">Clothing Co-parsing by Joint Image Segmentation and Labeling</a></td><td><a href="https://arxiv.org/pdf/1502.00739v1.pdf">[pdf]</a></td><td>2014 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>47%</td><td>60</td><td>28</td><td>32</td><td>0</td><td>36</td><td>6</td></tr><tr><td>42505464808dfb446f521fc6ff2cfeffd4d68ff1</td><td>gavab_db</td><td>Gavab</td><td><a href="papers/42505464808dfb446f521fc6ff2cfeffd4d68ff1.html">Expression invariant 3D face recognition with a Morphable Model</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4813376', 'linkType': 'ieee'}">[pdf]</a></td><td>2008 8th IEEE International Conference on Automatic Face & Gesture Recognition</td><td></td><td></td><td></td><td></td><td>29%</td><td>94</td><td>27</td><td>67</td><td>10</td><td>57</td><td>5</td></tr><tr><td>066000d44d6691d27202896691f08b27117918b9</td><td>psu</td><td>PSU</td><td><a href="papers/066000d44d6691d27202896691f08b27117918b9.html">Vision-Based Analysis of Small Groups in Pedestrian Crowds</a></td><td><a href="http://vision.cse.psu.edu/publications/pdfs/GeCollinsRubackPAMI2011.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>18%</td><td>151</td><td>27</td><td>124</td><td>9</td><td>78</td><td>2</td></tr><tr><td>3b4ec8af470948a72a6ed37a9fd226719a874ebc</td><td>sdu_vid</td><td>SDU-VID</td><td><a href="papers/3b4ec8af470948a72a6ed37a9fd226719a874ebc.html">A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.434">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>32%</td><td>85</td><td>27</td><td>58</td><td>9</td><td>51</td><td>0</td></tr><tr><td>3b4ec8af470948a72a6ed37a9fd226719a874ebc</td><td>sdu_vid</td><td>SDU-VID</td><td><a href="papers/3b4ec8af470948a72a6ed37a9fd226719a874ebc.html">A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.434">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>32%</td><td>85</td><td>27</td><td>58</td><td>9</td><td>51</td><td>0</td></tr><tr><td>3b4ec8af470948a72a6ed37a9fd226719a874ebc</td><td>sdu_vid</td><td>SDU-VID</td><td><a href="papers/3b4ec8af470948a72a6ed37a9fd226719a874ebc.html">A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.434">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>32%</td><td>85</td><td>27</td><td>58</td><td>9</td><td>51</td><td>0</td></tr><tr><td>47aeb3b82f54b5ae8142b4bdda7b614433e69b9a</td><td>am_fed</td><td>AM-FED</td><td><a href="papers/47aeb3b82f54b5ae8142b4bdda7b614433e69b9a.html">Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"</a></td><td><a href="http://pdfs.semanticscholar.org/5d06/437656dd94616d7d87260d5eb77513ded30f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>36%</td><td>73</td><td>26</td><td>47</td><td>6</td><td>39</td><td>16</td></tr><tr><td>356b431d4f7a2a0a38cf971c84568207dcdbf189</td><td>wider</td><td>WIDER</td><td><a href="papers/356b431d4f7a2a0a38cf971c84568207dcdbf189.html">Recognize complex events from static images by fusing deep channels</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Xiong_Recognize_Complex_Events_2015_CVPR_paper.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Shenzhen Institutes of Advanced Technology</td><td>22.59805605</td><td>113.98533784</td><td>58%</td><td>45</td><td>26</td><td>19</td><td>1</td><td>30</td><td>12</td></tr><tr><td>9c23859ec7313f2e756a3e85575735e0c52249f4</td><td>facebook_100</td><td>Facebook100</td><td><a href="papers/9c23859ec7313f2e756a3e85575735e0c52249f4.html">Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5981788', 'linkType': 'ieee'}">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>Harvard University</td><td>42.36782045</td><td>-71.12666653</td><td>50%</td><td>50</td><td>25</td><td>25</td><td>3</td><td>39</td><td>4</td></tr><tr><td>0b84f07af44f964817675ad961def8a51406dd2e</td><td>prw</td><td>PRW</td><td><a href="papers/0b84f07af44f964817675ad961def8a51406dd2e.html">Person Re-identification in the Wild</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2017.357">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Technology Sydney</td><td>-33.88096510</td><td>151.20107299</td><td>38%</td><td>65</td><td>25</td><td>40</td><td>1</td><td>46</td><td>0</td></tr><tr><td>9c23859ec7313f2e756a3e85575735e0c52249f4</td><td>pubfig_83</td><td>pubfig83</td><td><a href="papers/9c23859ec7313f2e756a3e85575735e0c52249f4.html">Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5981788', 'linkType': 'ieee'}">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>Harvard University</td><td>42.36782045</td><td>-71.12666653</td><td>50%</td><td>50</td><td>25</td><td>25</td><td>3</td><td>39</td><td>4</td></tr><tr><td>2160788824c4c29ffe213b2cbeb3f52972d73f37</td><td>3d_rma</td><td>3D-RMA</td><td><a href="papers/2160788824c4c29ffe213b2cbeb3f52972d73f37.html">Automatic 3D face authentication</a></td><td><a href="http://pdfs.semanticscholar.org/2160/788824c4c29ffe213b2cbeb3f52972d73f37.pdf">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>25%</td><td>95</td><td>24</td><td>71</td><td>8</td><td>60</td><td>2</td></tr><tr><td>37d6f0eb074d207b53885bd2eb78ccc8a04be597</td><td>vmu</td><td>VMU</td><td><a href="papers/37d6f0eb074d207b53885bd2eb78ccc8a04be597.html">Can facial cosmetics affect the matching accuracy of face recognition systems?</a></td><td><a href="http://www.cse.msu.edu/~climer/DantchevaChenRossFaceCosmetics_BTAS2012.pdf">[pdf]</a></td><td>2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td></td><td></td><td></td><td></td><td>49%</td><td>49</td><td>24</td><td>25</td><td>0</td><td>18</td><td>22</td></tr><tr><td>37d6f0eb074d207b53885bd2eb78ccc8a04be597</td><td>youtube_makeup</td><td>YMU</td><td><a href="papers/37d6f0eb074d207b53885bd2eb78ccc8a04be597.html">Can facial cosmetics affect the matching accuracy of face recognition systems?</a></td><td><a href="http://www.cse.msu.edu/~climer/DantchevaChenRossFaceCosmetics_BTAS2012.pdf">[pdf]</a></td><td>2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td></td><td></td><td></td><td></td><td>49%</td><td>49</td><td>24</td><td>25</td><td>0</td><td>18</td><td>22</td></tr><tr><td>37d6f0eb074d207b53885bd2eb78ccc8a04be597</td><td>youtube_makeup</td><td>YMU</td><td><a href="papers/37d6f0eb074d207b53885bd2eb78ccc8a04be597.html">Can facial cosmetics affect the matching accuracy of face recognition systems?</a></td><td><a href="http://www.cse.msu.edu/~climer/DantchevaChenRossFaceCosmetics_BTAS2012.pdf">[pdf]</a></td><td>2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td></td><td></td><td></td><td></td><td>49%</td><td>49</td><td>24</td><td>25</td><td>0</td><td>18</td><td>22</td></tr><tr><td>070de852bc6eb275d7ca3a9cdde8f6be8795d1a3</td><td>d3dfacs</td><td>D3DFACS</td><td><a href="papers/070de852bc6eb275d7ca3a9cdde8f6be8795d1a3.html">A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling</a></td><td><a href="http://www.cs.bath.ac.uk/~dpc/D3DFACS/ICCV_final_2011.pdf">[pdf]</a></td><td>2011 International Conference on Computer Vision</td><td>edu</td><td>Jacobs University</td><td>53.41291480</td><td>-2.96897915</td><td>44%</td><td>52</td><td>23</td><td>29</td><td>5</td><td>37</td><td>4</td></tr><tr><td>3394168ff0719b03ff65bcea35336a76b21fe5e4</td><td>penn_fudan</td><td>Penn Fudan</td><td><a href="papers/3394168ff0719b03ff65bcea35336a76b21fe5e4.html">Object Detection Combining Recognition and Segmentation</a></td><td><a href="http://pdfs.semanticscholar.org/f531/a554cade14b9b340de6730683a28c292dd74.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>23%</td><td>101</td><td>23</td><td>78</td><td>11</td><td>58</td><td>0</td></tr><tr><td>2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e</td><td>3dpes</td><td>3DPeS</td><td><a href="papers/2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e.html">3DPeS: 3D people dataset for surveillance and forensics</a></td><td><a href="http://doi.acm.org/10.1145/2072572.2072590">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>18%</td><td>122</td><td>22</td><td>100</td><td>11</td><td>71</td><td>1</td></tr><tr><td>eb027969f9310e0ae941e2adee2d42cdf07d938c</td><td>vgg_faces2</td><td>VGG Face2</td><td><a href="papers/eb027969f9310e0ae941e2adee2d42cdf07d938c.html">VGGFace2: A Dataset for Recognising Faces across Pose and Age</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1710.08092.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)</td><td>edu</td><td>University of Oxford</td><td>51.75345380</td><td>-1.25400997</td><td>38%</td><td>56</td><td>21</td><td>35</td><td>6</td><td>50</td><td>3</td></tr><tr><td>f1af714b92372c8e606485a3982eab2f16772ad8</td><td>mug_faces</td><td>MUG Faces</td><td><a href="papers/f1af714b92372c8e606485a3982eab2f16772ad8.html">The MUG facial expression database</a></td><td><a href="http://ieeexplore.ieee.org/document/5617662/">[pdf]</a></td><td>11th International Workshop on Image Analysis for Multimedia Interactive Services WIAMIS 10</td><td>edu</td><td>Aristotle University of Thessaloniki</td><td>40.62984145</td><td>22.95889350</td><td>28%</td><td>68</td><td>19</td><td>49</td><td>5</td><td>28</td><td>19</td></tr><tr><td>31b05f65405534a696a847dd19c621b7b8588263</td><td>umd_faces</td><td>UMD</td><td><a href="papers/31b05f65405534a696a847dd19c621b7b8588263.html">UMDFaces: An annotated face dataset for training deep networks</a></td><td><a href="http://arxiv.org/abs/1611.01484">[pdf]</a></td><td>2017 IEEE International Joint Conference on Biometrics (IJCB)</td><td></td><td></td><td></td><td></td><td>54%</td><td>35</td><td>19</td><td>16</td><td>5</td><td>28</td><td>6</td></tr><tr><td>31b05f65405534a696a847dd19c621b7b8588263</td><td>umd_faces</td><td>UMD</td><td><a href="papers/31b05f65405534a696a847dd19c621b7b8588263.html">UMDFaces: An annotated face dataset for training deep networks</a></td><td><a href="http://arxiv.org/abs/1611.01484">[pdf]</a></td><td>2017 IEEE International Joint Conference on Biometrics (IJCB)</td><td></td><td></td><td></td><td></td><td>54%</td><td>35</td><td>19</td><td>16</td><td>5</td><td>28</td><td>6</td></tr><tr><td>8b2dd5c61b23ead5ae5508bb8ce808b5ea266730</td><td>10k_US_adult_faces</td><td>10K US Adult Faces</td><td><a href="papers/8b2dd5c61b23ead5ae5508bb8ce808b5ea266730.html">The intrinsic memorability of face photographs.</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/8b2d/d5c61b23ead5ae5508bb8ce808b5ea266730.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Journal of experimental psychology. General</td><td></td><td></td><td></td><td></td><td>36%</td><td>47</td><td>17</td><td>30</td><td>3</td><td>33</td><td>1</td></tr><tr><td>69a68f9cf874c69e2232f47808016c2736b90c35</td><td>celeba_plus</td><td>CelebFaces+</td><td><a href="papers/69a68f9cf874c69e2232f47808016c2736b90c35.html">Learning Deep Representation for Imbalanced Classification</a></td><td><a href="http://personal.ie.cuhk.edu.hk/~ccloy/files/cvpr_2016_imbalanced.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Shenzhen Institutes of Advanced Technology</td><td>22.59805605</td><td>113.98533784</td><td>33%</td><td>51</td><td>17</td><td>34</td><td>1</td><td>39</td><td>2</td></tr><tr><td>79828e6e9f137a583082b8b5a9dfce0c301989b8</td><td>mapillary</td><td>Mapillary</td><td><a href="papers/79828e6e9f137a583082b8b5a9dfce0c301989b8.html">The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8237796', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>39%</td><td>44</td><td>17</td><td>27</td><td>0</td><td>36</td><td>0</td></tr><tr><td>5194cbd51f9769ab25260446b4fa17204752e799</td><td>violent_flows</td><td>Violent Flows</td><td><a href="papers/5194cbd51f9769ab25260446b4fa17204752e799.html">Violent flows: Real-time detection of violent crowd behavior</a></td><td><a href="http://www.wisdom.weizmann.ac.il/mathusers/kliper/Papers/violent_flows.pdf">[pdf]</a></td><td>2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</td><td></td><td></td><td></td><td></td><td>20%</td><td>83</td><td>17</td><td>66</td><td>6</td><td>42</td><td>2</td></tr><tr><td>20388099cc415c772926e47bcbbe554e133343d1</td><td>cafe</td><td>CAFE</td><td><a href="papers/20388099cc415c772926e47bcbbe554e133343d1.html">The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults</a></td><td><a href="http://pdfs.semanticscholar.org/2038/8099cc415c772926e47bcbbe554e133343d1.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>48%</td><td>33</td><td>16</td><td>17</td><td>3</td><td>28</td><td>1</td></tr><tr><td>c34532fe6bfbd1e6df477c9ffdbb043b77e7804d</td><td>columbia_gaze</td><td>Columbia Gaze</td><td><a href="papers/c34532fe6bfbd1e6df477c9ffdbb043b77e7804d.html">A 3D Morphable Eye Region Model for Gaze Estimation</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/0d43/3b9435b874a1eea6d7999e86986c910fa285.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td>edu</td><td>Carnegie Mellon University</td><td>37.41021930</td><td>-122.05965487</td><td>67%</td><td>24</td><td>16</td><td>8</td><td>0</td><td>18</td><td>4</td></tr><tr><td>47662d1a368daf70ba70ef2d59eb6209f98b675d</td><td>fia</td><td>CMU FiA</td><td><a href="papers/47662d1a368daf70ba70ef2d59eb6209f98b675d.html">The CMU Face In Action (FIA) Database</a></td><td><a href="http://pdfs.semanticscholar.org/bb47/a03401811f9d2ca2da12138697acbc7b97a3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>29%</td><td>55</td><td>16</td><td>39</td><td>5</td><td>38</td><td>7</td></tr><tr><td>213a579af9e4f57f071b884aa872651372b661fd</td><td>bbc_pose</td><td>BBC Pose</td><td><a href="papers/213a579af9e4f57f071b884aa872651372b661fd.html">Automatic and Efficient Human Pose Estimation for Sign Language Videos</a></td><td><a href="https://doi.org/10.1007/s11263-013-0672-6">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>60%</td><td>25</td><td>15</td><td>10</td><td>1</td><td>18</td><td>1</td></tr><tr><td>1e3df3ca8feab0b36fd293fe689f93bb2aaac591</td><td>immediacy</td><td>Immediacy</td><td><a href="papers/1e3df3ca8feab0b36fd293fe689f93bb2aaac591.html">Multi-task Recurrent Neural Network for Immediacy Prediction</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.383">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>60%</td><td>25</td><td>15</td><td>10</td><td>2</td><td>20</td><td>0</td></tr><tr><td>a5a44a32a91474f00a3cda671a802e87c899fbb4</td><td>moments_in_time</td><td>Moments in Time</td><td><a href="papers/a5a44a32a91474f00a3cda671a802e87c899fbb4.html">Moments in Time Dataset: one million videos for event understanding</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1801.03150.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>60%</td><td>25</td><td>15</td><td>10</td><td>2</td><td>25</td><td>0</td></tr><tr><td>4946ba10a4d5a7d0a38372f23e6622bd347ae273</td><td>coco_action</td><td>COCO-a</td><td><a href="papers/4946ba10a4d5a7d0a38372f23e6622bd347ae273.html">RONCHI AND PERONA: DESCRIBING COMMON HUMAN VISUAL ACTIONS IN IMAGES 1 Describing Common Human Visual Actions in Images</a></td><td><a href="http://pdfs.semanticscholar.org/b38d/cf5fa5174c0d718d65cc4f3889b03c4a21df.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>54%</td><td>26</td><td>14</td><td>12</td><td>0</td><td>25</td><td>0</td></tr><tr><td>2161f6b7ee3c0acc81603b01dc0df689683577b9</td><td>large_scale_person_search</td><td>Large Scale Person Search</td><td><a href="papers/2161f6b7ee3c0acc81603b01dc0df689683577b9.html">End-to-End Deep Learning for Person Search</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/2161/f6b7ee3c0acc81603b01dc0df689683577b9.pdf', 'linkType': 's2'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>34%</td><td>41</td><td>14</td><td>27</td><td>2</td><td>27</td><td>0</td></tr><tr><td>1c2802c2199b6d15ecefe7ba0c39bfe44363de38</td><td>youtube_poses</td><td>YouTube Pose</td><td><a href="papers/1c2802c2199b6d15ecefe7ba0c39bfe44363de38.html">Personalizing Human Video Pose Estimation</a></td><td><a href="http://arxiv.org/pdf/1511.06676v1.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>44%</td><td>32</td><td>14</td><td>18</td><td>2</td><td>27</td><td>0</td></tr><tr><td>ea050801199f98a1c7c1df6769f23f658299a3ae</td><td>mpi_large</td><td>Large MPI Facial Expression</td><td><a href="papers/ea050801199f98a1c7c1df6769f23f658299a3ae.html">The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions</a></td><td><a href="http://pdfs.semanticscholar.org/ea05/0801199f98a1c7c1df6769f23f658299a3ae.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>46%</td><td>28</td><td>13</td><td>15</td><td>4</td><td>24</td><td>3</td></tr><tr><td>ea050801199f98a1c7c1df6769f23f658299a3ae</td><td>mpi_small</td><td>Small MPI Facial Expression</td><td><a href="papers/ea050801199f98a1c7c1df6769f23f658299a3ae.html">The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions</a></td><td><a href="http://pdfs.semanticscholar.org/ea05/0801199f98a1c7c1df6769f23f658299a3ae.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>46%</td><td>28</td><td>13</td><td>15</td><td>4</td><td>24</td><td>3</td></tr><tr><td>16e8b0a1e8451d5f697b94c0c2b32a00abee1d52</td><td>umb</td><td>UMB</td><td><a href="papers/16e8b0a1e8451d5f697b94c0c2b32a00abee1d52.html">UMB-DB: A database of partially occluded 3D faces</a></td><td><a href="https://doi.org/10.1109/ICCVW.2011.6130509">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>29%</td><td>45</td><td>13</td><td>32</td><td>2</td><td>20</td><td>3</td></tr><tr><td>d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae</td><td>b3d_ac</td><td>B3D(AC)</td><td><a href="papers/d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae.html">A 3-D Audio-Visual Corpus of Affective Communication</a></td><td><a href="http://files.is.tue.mpg.de/jgall/download/jgall_avcorpus_mm10.pdf">[pdf]</a></td><td>IEEE Transactions on Multimedia</td><td></td><td></td><td></td><td></td><td>31%</td><td>39</td><td>12</td><td>27</td><td>2</td><td>27</td><td>7</td></tr><tr><td>0b440695c822a8e35184fb2f60dcdaa8a6de84ae</td><td>kinectface</td><td>KinectFaceDB</td><td><a href="papers/0b440695c822a8e35184fb2f60dcdaa8a6de84ae.html">KinectFaceDB: A Kinect Database for Face Recognition</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6866883', 'linkType': 'ieee'}">[pdf]</a></td><td>IEEE Transactions on Systems, Man, and Cybernetics: Systems</td><td></td><td></td><td></td><td></td><td>16%</td><td>75</td><td>12</td><td>63</td><td>6</td><td>25</td><td>8</td></tr><tr><td>45e616093a92e5f1e61a7c6037d5f637aa8964af</td><td>malf</td><td>MALF</td><td><a href="papers/45e616093a92e5f1e61a7c6037d5f637aa8964af.html">Fine-grained evaluation on face detection in the wild</a></td><td><a href="http://www.cs.toronto.edu/~byang/papers/malf_fg15.pdf">[pdf]</a></td><td>2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>Chinese Academy of Sciences</td><td>40.00447950</td><td>116.37023800</td><td>71%</td><td>17</td><td>12</td><td>5</td><td>0</td><td>13</td><td>4</td></tr><tr><td>09d78009687bec46e70efcf39d4612822e61cb8c</td><td>raid</td><td>RAiD</td><td><a href="papers/09d78009687bec46e70efcf39d4612822e61cb8c.html">Consistent Re-identification in a Camera Network</a></td><td><a href="http://pdfs.semanticscholar.org/c27f/099e6e7e3f7f9979cbe9e0a5175fc5848ea0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>27%</td><td>45</td><td>12</td><td>33</td><td>7</td><td>34</td><td>1</td></tr><tr><td>22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b</td><td>saivt</td><td>SAIVT SoftBio</td><td><a href="papers/22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b.html">A Database for Person Re-Identification in Multi-Camera Surveillance Networks</a></td><td><a href="http://eprints.qut.edu.au/53437/3/Bialkowski_Database4PersonReID_DICTA.pdf">[pdf]</a></td><td>2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)</td><td></td><td></td><td></td><td></td><td>21%</td><td>58</td><td>12</td><td>46</td><td>7</td><td>40</td><td>1</td></tr><tr><td>44d23df380af207f5ac5b41459c722c87283e1eb</td><td>wider_attribute</td><td>WIDER Attribute</td><td><a href="papers/44d23df380af207f5ac5b41459c722c87283e1eb.html">Human Attribute Recognition by Deep Hierarchical Contexts</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/8e28/07f2dd53b03a759e372e07f7191cae65c9fd.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>67%</td><td>18</td><td>12</td><td>6</td><td>0</td><td>16</td><td>0</td></tr><tr><td>221c18238b829c12b911706947ab38fd017acef7</td><td>rap_pedestrian</td><td>RAP</td><td><a href="papers/221c18238b829c12b911706947ab38fd017acef7.html">A Richly Annotated Dataset for Pedestrian Attribute Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/221c/18238b829c12b911706947ab38fd017acef7.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>52%</td><td>21</td><td>11</td><td>10</td><td>0</td><td>18</td><td>0</td></tr><tr><td>4d58f886f5150b2d5e48fd1b5a49e09799bf895d</td><td>texas_3dfrd</td><td>Texas 3DFRD</td><td><a href="papers/4d58f886f5150b2d5e48fd1b5a49e09799bf895d.html">Texas 3D Face Recognition Database</a></td><td><a href="http://live.ece.utexas.edu/publications/2010/sg_ssiai_may10.pdf">[pdf]</a></td><td>2010 IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI)</td><td></td><td></td><td></td><td></td><td>18%</td><td>61</td><td>11</td><td>50</td><td>3</td><td>36</td><td>2</td></tr><tr><td>4d58f886f5150b2d5e48fd1b5a49e09799bf895d</td><td>texas_3dfrd</td><td>Texas 3DFRD</td><td><a href="papers/4d58f886f5150b2d5e48fd1b5a49e09799bf895d.html">Texas 3D Face Recognition Database</a></td><td><a href="http://live.ece.utexas.edu/publications/2010/sg_ssiai_may10.pdf">[pdf]</a></td><td>2010 IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI)</td><td></td><td></td><td></td><td></td><td>18%</td><td>61</td><td>11</td><td>50</td><td>3</td><td>36</td><td>2</td></tr><tr><td>488e475eeb3bb39a145f23ede197cd3620f1d98a</td><td>apis</td><td>APiS1.0</td><td><a href="papers/488e475eeb3bb39a145f23ede197cd3620f1d98a.html">Pedestrian Attribute Classification in Surveillance: Database and Evaluation</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_iccv_workshops_2013/W10/papers/Zhu_Pedestrian_Attribute_Classification_2013_ICCV_paper.pdf">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision Workshops</td><td></td><td></td><td></td><td></td><td>38%</td><td>26</td><td>10</td><td>16</td><td>1</td><td>13</td><td>2</td></tr><tr><td>53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4</td><td>bp4d_plus</td><td>BP4D+</td><td><a href="papers/53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4.html">Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhang_Multimodal_Spontaneous_Emotion_CVPR_2016_paper.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>25%</td><td>40</td><td>10</td><td>30</td><td>0</td><td>20</td><td>6</td></tr><tr><td>298cbc3dfbbb3a20af4eed97906650a4ea1c29e0</td><td>ferplus</td><td>FER+</td><td><a href="papers/298cbc3dfbbb3a20af4eed97906650a4ea1c29e0.html">Training deep networks for facial expression recognition with crowd-sourced label distribution</a></td><td><a href="http://arxiv.org/pdf/1608.01041v1.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>34%</td><td>29</td><td>10</td><td>19</td><td>0</td><td>15</td><td>3</td></tr><tr><td>488e475eeb3bb39a145f23ede197cd3620f1d98a</td><td>svs</td><td>SVS</td><td><a href="papers/488e475eeb3bb39a145f23ede197cd3620f1d98a.html">Pedestrian Attribute Classification in Surveillance: Database and Evaluation</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_iccv_workshops_2013/W10/papers/Zhu_Pedestrian_Attribute_Classification_2013_ICCV_paper.pdf">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision Workshops</td><td></td><td></td><td></td><td></td><td>38%</td><td>26</td><td>10</td><td>16</td><td>1</td><td>13</td><td>2</td></tr><tr><td>5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725</td><td>50_people_one_question</td><td>50 People One Question</td><td><a href="papers/5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725.html">Merging Pose Estimates Across Space and Time</a></td><td><a href="http://pdfs.semanticscholar.org/63b2/f5348af0f969dfc2afb4977732393c6459ec.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>60%</td><td>15</td><td>9</td><td>6</td><td>0</td><td>11</td><td>2</td></tr><tr><td>6dcf418c778f528b5792104760f1fbfe90c6dd6a</td><td>agedb</td><td>AgeDB</td><td><a href="papers/6dcf418c778f528b5792104760f1fbfe90c6dd6a.html">AgeDB: The First Manually Collected, In-the-Wild Age Database</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8014984', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>82%</td><td>11</td><td>9</td><td>2</td><td>0</td><td>10</td><td>0</td></tr><tr><td>0ceda9dae8b9f322df65ca2ef02caca9758aec6f</td><td>casablanca</td><td>Casablanca</td><td><a href="papers/0ceda9dae8b9f322df65ca2ef02caca9758aec6f.html">Context-Aware CNNs for Person Head Detection</a></td><td><a href="http://arxiv.org/pdf/1511.07917v1.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>33%</td><td>27</td><td>9</td><td>18</td><td>1</td><td>22</td><td>0</td></tr><tr><td>0ceda9dae8b9f322df65ca2ef02caca9758aec6f</td><td>hollywood_headset</td><td>HollywoodHeads</td><td><a href="papers/0ceda9dae8b9f322df65ca2ef02caca9758aec6f.html">Context-Aware CNNs for Person Head Detection</a></td><td><a href="http://arxiv.org/pdf/1511.07917v1.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>33%</td><td>27</td><td>9</td><td>18</td><td>1</td><td>22</td><td>0</td></tr><tr><td>faf40ce28857aedf183e193486f5b4b0a8c478a2</td><td>iit_dehli_ear</td><td>IIT Dehli Ear</td><td><a href="papers/faf40ce28857aedf183e193486f5b4b0a8c478a2.html">Automated Human Identification Using Ear Imaging</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/faf4/0ce28857aedf183e193486f5b4b0a8c478a2.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>13%</td><td>70</td><td>9</td><td>61</td><td>6</td><td>28</td><td>1</td></tr><tr><td>ca3e88d87e1344d076c964ea89d91a75c417f5ee</td><td>imfdb</td><td>IMFDB</td><td><a href="papers/ca3e88d87e1344d076c964ea89d91a75c417f5ee.html">Indian Movie Face Database: A benchmark for face recognition under wide variations</a></td><td><span class="gray">[pdf]</a></td><td>2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)</td><td></td><td></td><td></td><td></td><td>60%</td><td>15</td><td>9</td><td>6</td><td>0</td><td>10</td><td>4</td></tr><tr><td>7ace44190729927e5cb0dd5d363fcae966fe13f7</td><td>nudedetection</td><td>Nude Detection</td><td><a href="papers/7ace44190729927e5cb0dd5d363fcae966fe13f7.html">A bag-of-features approach based on Hue-SIFT descriptor for nude detection</a></td><td><a href="http://ieeexplore.ieee.org/document/7077625/">[pdf]</a></td><td>2009 17th European Signal Processing Conference</td><td></td><td></td><td></td><td></td><td>18%</td><td>51</td><td>9</td><td>42</td><td>1</td><td>18</td><td>0</td></tr><tr><td>4e6ee936eb50dd032f7138702fa39b7c18ee8907</td><td>dartmouth_children</td><td>Dartmouth Children</td><td><a href="papers/4e6ee936eb50dd032f7138702fa39b7c18ee8907.html">The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set</a></td><td><a href="http://pdfs.semanticscholar.org/4e6e/e936eb50dd032f7138702fa39b7c18ee8907.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>40%</td><td>20</td><td>8</td><td>12</td><td>2</td><td>16</td><td>0</td></tr><tr><td>fd8168f1c50de85bac58a8d328df0a50248b16ae</td><td>nd_2006</td><td>ND-2006</td><td><a href="papers/fd8168f1c50de85bac58a8d328df0a50248b16ae.html">Using a Multi-Instance Enrollment Representation to Improve 3D Face Recognition</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4401928', 'linkType': 'ieee'}">[pdf]</a></td><td>2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems</td><td></td><td></td><td></td><td></td><td>25%</td><td>32</td><td>8</td><td>24</td><td>3</td><td>16</td><td>1</td></tr><tr><td>774cbb45968607a027ae4729077734db000a1ec5</td><td>urban_tribes</td><td>Urban Tribes</td><td><a href="papers/774cbb45968607a027ae4729077734db000a1ec5.html">From Bikers to Surfers: Visual Recognition of Urban Tribes</a></td><td><a href="http://pdfs.semanticscholar.org/774c/bb45968607a027ae4729077734db000a1ec5.pdf">[pdf]</a></td><td></td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>47%</td><td>17</td><td>8</td><td>9</td><td>1</td><td>12</td><td>1</td></tr><tr><td>2624d84503bc2f8e190e061c5480b6aa4d89277a</td><td>afew_va</td><td>AFEW-VA</td><td><a href="papers/2624d84503bc2f8e190e061c5480b6aa4d89277a.html">AFEW-VA database for valence and arousal estimation in-the-wild</a></td><td><a href="http://pdfs.semanticscholar.org/2624/d84503bc2f8e190e061c5480b6aa4d89277a.pdf">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>47%</td><td>15</td><td>7</td><td>8</td><td>1</td><td>10</td><td>3</td></tr><tr><td>2624d84503bc2f8e190e061c5480b6aa4d89277a</td><td>afew_va</td><td>AFEW-VA</td><td><a href="papers/2624d84503bc2f8e190e061c5480b6aa4d89277a.html">AFEW-VA database for valence and arousal estimation in-the-wild</a></td><td><a href="http://pdfs.semanticscholar.org/2624/d84503bc2f8e190e061c5480b6aa4d89277a.pdf">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>47%</td><td>15</td><td>7</td><td>8</td><td>1</td><td>10</td><td>3</td></tr><tr><td>84fe5b4ac805af63206012d29523a1e033bc827e</td><td>awe_ears</td><td>AWE Ears</td><td><a href="papers/84fe5b4ac805af63206012d29523a1e033bc827e.html">Ear recognition: More than a survey</a></td><td><a href="http://pdfs.semanticscholar.org/84fe/5b4ac805af63206012d29523a1e033bc827e.pdf">[pdf]</a></td><td>Neurocomputing</td><td></td><td></td><td></td><td></td><td>29%</td><td>24</td><td>7</td><td>17</td><td>0</td><td>11</td><td>0</td></tr><tr><td>5801690199c1917fa58c35c3dead177c0b8f9f2d</td><td>camel</td><td>CAMEL</td><td><a href="papers/5801690199c1917fa58c35c3dead177c0b8f9f2d.html">Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis</a></td><td><a href="http://pdfs.semanticscholar.org/5801/690199c1917fa58c35c3dead177c0b8f9f2d.pdf">[pdf]</a></td><td>Remote Sensing</td><td></td><td></td><td></td><td></td><td>37%</td><td>19</td><td>7</td><td>12</td><td>1</td><td>16</td><td>0</td></tr><tr><td>0297448f3ed948e136bb06ceff10eccb34e5bb77</td><td>ilids_mcts</td><td></td><td><a href="papers/0297448f3ed948e136bb06ceff10eccb34e5bb77.html">Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems</a></td><td><span class="gray">[pdf]</a></td><td>Proceedings 40th Annual 2006 International Carnahan Conference on Security Technology</td><td></td><td></td><td></td><td></td><td>22%</td><td>32</td><td>7</td><td>25</td><td>2</td><td>17</td><td>0</td></tr><tr><td>ec792ad2433b6579f2566c932ee414111e194537</td><td>msmt_17</td><td>MSMT17</td><td><a href="papers/ec792ad2433b6579f2566c932ee414111e194537.html">Person Transfer GAN to Bridge Domain Gap for Person Re-Identification</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1711.08565.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>50%</td><td>14</td><td>7</td><td>7</td><td>1</td><td>11</td><td>0</td></tr><tr><td>b92a1ed9622b8268ae3ac9090e25789fc41cc9b8</td><td>pornodb</td><td>Pornography DB</td><td><a href="papers/b92a1ed9622b8268ae3ac9090e25789fc41cc9b8.html">Pooling in image representation: The visual codeword point of view</a></td><td><a href="http://pdfs.semanticscholar.org/b92a/1ed9622b8268ae3ac9090e25789fc41cc9b8.pdf">[pdf]</a></td><td>Computer Vision and Image Understanding</td><td></td><td></td><td></td><td></td><td>9%</td><td>77</td><td>7</td><td>70</td><td>7</td><td>43</td><td>2</td></tr><tr><td>19d1b811df60f86cbd5e04a094b07f32fff7a32a</td><td>york_3d</td><td>UOY 3D Face Database</td><td><a href="papers/19d1b811df60f86cbd5e04a094b07f32fff7a32a.html">Three-dimensional face recognition: an eigensurface approach</a></td><td><a href="http://www-users.cs.york.ac.uk/~nep/research/3Dface/tomh/3DFaceRecognition-Eigensurface-ICIP(web)2.pdf">[pdf]</a></td><td>2004 International Conference on Image Processing, 2004. ICIP '04.</td><td></td><td></td><td></td><td></td><td>19%</td><td>36</td><td>7</td><td>29</td><td>4</td><td>25</td><td>1</td></tr><tr><td>2a171f8d14b6b8735001a11c217af9587d095848</td><td>expw</td><td>ExpW</td><td><a href="papers/2a171f8d14b6b8735001a11c217af9587d095848.html">Learning Social Relation Traits from Face Images</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.414">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>30%</td><td>20</td><td>6</td><td>14</td><td>5</td><td>15</td><td>0</td></tr><tr><td>2a171f8d14b6b8735001a11c217af9587d095848</td><td>expw</td><td>ExpW</td><td><a href="papers/2a171f8d14b6b8735001a11c217af9587d095848.html">Learning Social Relation Traits from Face Images</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.414">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>30%</td><td>20</td><td>6</td><td>14</td><td>5</td><td>15</td><td>0</td></tr><tr><td>25474c21613607f6bb7687a281d5f9d4ffa1f9f3</td><td>faceplace</td><td>Face Place</td><td><a href="papers/25474c21613607f6bb7687a281d5f9d4ffa1f9f3.html">Recognizing disguised faces</a></td><td><a href="http://pdfs.semanticscholar.org/d936/7ceb0be378c3a9ddf7cb741c678c1a3c574c.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>25%</td><td>24</td><td>6</td><td>18</td><td>0</td><td>16</td><td>1</td></tr><tr><td>0cb2dd5f178e3a297a0c33068961018659d0f443</td><td>ijb_b</td><td>IJB-B</td><td><a href="papers/0cb2dd5f178e3a297a0c33068961018659d0f443.html">IARPA Janus Benchmark-B Face Dataset</a></td><td><a href="http://www.vislab.ucr.edu/Biometrics2017/program_slides/Noblis_CVPRW_IJBB.pdf">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>24%</td><td>25</td><td>6</td><td>19</td><td>6</td><td>21</td><td>3</td></tr><tr><td>bd26dabab576adb6af30484183c9c9c8379bf2e0</td><td>scut_fbp</td><td>SCUT-FBP</td><td><a href="papers/bd26dabab576adb6af30484183c9c9c8379bf2e0.html">SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1511.02459.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2015 IEEE International Conference on Systems, Man, and Cybernetics</td><td>edu</td><td>South China University of Technology</td><td>23.05020420</td><td>113.39880323</td><td>43%</td><td>14</td><td>6</td><td>8</td><td>3</td><td>5</td><td>7</td></tr><tr><td>4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06</td><td>distance_nighttime</td><td>Long Distance Heterogeneous Face</td><td><a href="papers/4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06.html">Nighttime Face Recognition at Long Distance: Cross-Distance and Cross-Spectral Matching</a></td><td><a href="http://pdfs.semanticscholar.org/4156/b7e88f2e0ab0a7c095b9bab199ae2b23bd06.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>24%</td><td>21</td><td>5</td><td>16</td><td>3</td><td>11</td><td>1</td></tr><tr><td>6f3c76b7c0bd8e1d122c6ea808a271fd4749c951</td><td>ward</td><td>WARD</td><td><a href="papers/6f3c76b7c0bd8e1d122c6ea808a271fd4749c951.html">Re-identify people in wide area camera network</a></td><td><a href="https://doi.org/10.1109/CVPRW.2012.6239203">[pdf]</a></td><td>2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</td><td></td><td></td><td></td><td></td><td>9%</td><td>55</td><td>5</td><td>50</td><td>2</td><td>35</td><td>0</td></tr><tr><td>6403117f9c005ae81f1e8e6d1302f4a045e3d99d</td><td>alert_airport</td><td>ALERT Airport</td><td><a href="papers/6403117f9c005ae81f1e8e6d1302f4a045e3d99d.html">A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1605.09653.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>IEEE transactions on pattern analysis and machine intelligence</td><td></td><td></td><td></td><td></td><td>27%</td><td>15</td><td>4</td><td>11</td><td>1</td><td>10</td><td>0</td></tr><tr><td>014b8df0180f33b9fea98f34ae611c6447d761d2</td><td>buhmap_db</td><td>BUHMAP-DB </td><td><a href="papers/014b8df0180f33b9fea98f34ae611c6447d761d2.html">Facial feature tracking and expression recognition for sign language</a></td><td><a href="http://www.cmpe.boun.edu.tr/pilab/pilabfiles/databases/buhmap/files/ari2008facialfeaturetracking.pdf">[pdf]</a></td><td>2008 23rd International Symposium on Computer and Information Sciences</td><td></td><td></td><td></td><td></td><td>16%</td><td>25</td><td>4</td><td>21</td><td>1</td><td>10</td><td>2</td></tr><tr><td>57fe081950f21ca03b5b375ae3e84b399c015861</td><td>cvc_01_barcelona</td><td>CVC-01</td><td><a href="papers/57fe081950f21ca03b5b375ae3e84b399c015861.html">Adaptive Image Sampling and Windows Classification for On–board Pedestrian Detection</a></td><td><a href="http://pdfs.semanticscholar.org/57fe/081950f21ca03b5b375ae3e84b399c015861.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>9%</td><td>44</td><td>4</td><td>40</td><td>1</td><td>21</td><td>0</td></tr><tr><td>b71d1aa90dcbe3638888725314c0d56640c1fef1</td><td>ifdb</td><td>IFDB</td><td><a href="papers/b71d1aa90dcbe3638888725314c0d56640c1fef1.html">Iranian Face Database with age, pose and expression</a></td><td><span class="gray">[pdf]</a></td><td>2007 International Conference on Machine Vision</td><td></td><td></td><td></td><td></td><td>20%</td><td>20</td><td>4</td><td>16</td><td>2</td><td>11</td><td>3</td></tr><tr><td>b71d1aa90dcbe3638888725314c0d56640c1fef1</td><td>ifdb</td><td>IFDB</td><td><a href="papers/b71d1aa90dcbe3638888725314c0d56640c1fef1.html">Iranian Face Database with age, pose and expression</a></td><td><span class="gray">[pdf]</a></td><td>2007 International Conference on Machine Vision</td><td></td><td></td><td></td><td></td><td>20%</td><td>20</td><td>4</td><td>16</td><td>2</td><td>11</td><td>3</td></tr><tr><td>2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d</td><td>kin_face</td><td>UB KinFace</td><td><a href="papers/2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d.html">Genealogical face recognition based on UB KinFace database</a></td><td><a href="https://doi.org/10.1109/CVPRW.2011.5981801">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>SUNY Buffalo</td><td>42.93362780</td><td>-78.88394479</td><td>13%</td><td>30</td><td>4</td><td>26</td><td>1</td><td>9</td><td>5</td></tr><tr><td>2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d</td><td>kin_face</td><td>UB KinFace</td><td><a href="papers/2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d.html">Genealogical face recognition based on UB KinFace database</a></td><td><a href="https://doi.org/10.1109/CVPRW.2011.5981801">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>SUNY Buffalo</td><td>42.93362780</td><td>-78.88394479</td><td>13%</td><td>30</td><td>4</td><td>26</td><td>1</td><td>9</td><td>5</td></tr><tr><td>2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d</td><td>kin_face</td><td>UB KinFace</td><td><a href="papers/2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d.html">Genealogical face recognition based on UB KinFace database</a></td><td><a href="https://doi.org/10.1109/CVPRW.2011.5981801">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>SUNY Buffalo</td><td>42.93362780</td><td>-78.88394479</td><td>13%</td><td>30</td><td>4</td><td>26</td><td>1</td><td>9</td><td>5</td></tr><tr><td>e27ef52c641c2b5100a1b34fd0b819e84a31b4df</td><td>sarc3d</td><td>Sarc3D</td><td><a href="papers/e27ef52c641c2b5100a1b34fd0b819e84a31b4df.html">SARC3D: A New 3D Body Model for People Tracking and Re-identification</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/e27e/f52c641c2b5100a1b34fd0b819e84a31b4df.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>14%</td><td>29</td><td>4</td><td>25</td><td>3</td><td>17</td><td>0</td></tr><tr><td>22f656d0f8426c84a33a267977f511f127bfd7f3</td><td>social_relation</td><td>Social Relation</td><td><a href="papers/22f656d0f8426c84a33a267977f511f127bfd7f3.html">From Facial Expression Recognition to Interpersonal Relation Prediction</a></td><td><a href="http://arxiv.org/abs/1609.06426">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>44%</td><td>9</td><td>4</td><td>5</td><td>0</td><td>5</td><td>1</td></tr><tr><td>22f656d0f8426c84a33a267977f511f127bfd7f3</td><td>social_relation</td><td>Social Relation</td><td><a href="papers/22f656d0f8426c84a33a267977f511f127bfd7f3.html">From Facial Expression Recognition to Interpersonal Relation Prediction</a></td><td><a href="http://arxiv.org/abs/1609.06426">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>44%</td><td>9</td><td>4</td><td>5</td><td>0</td><td>5</td><td>1</td></tr><tr><td>1a40092b493c6b8840257ab7f96051d1a4dbfeb2</td><td>sports_videos_in_the_wild</td><td>SVW</td><td><a href="papers/1a40092b493c6b8840257ab7f96051d1a4dbfeb2.html">Sports Videos in the Wild (SVW): A video dataset for sports analysis</a></td><td><a href="http://web.cse.msu.edu/~liuxm/publication/Safdarnejad_Liu_Udpa_Andrus_Wood_Craven_FG2015.pdf">[pdf]</a></td><td>2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>Michigan State University</td><td>42.71856800</td><td>-84.47791571</td><td>67%</td><td>6</td><td>4</td><td>2</td><td>1</td><td>5</td><td>0</td></tr><tr><td>7ebb153704706e457ab57b432793d2b6e5d12592</td><td>vgg_celebs_in_places</td><td>CIP</td><td><a href="papers/7ebb153704706e457ab57b432793d2b6e5d12592.html">Faces in Places: compound query retrieval</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/7ebb/153704706e457ab57b432793d2b6e5d12592.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td>edu</td><td>University of Oxford</td><td>51.75345380</td><td>-1.25400997</td><td>80%</td><td>5</td><td>4</td><td>1</td><td>0</td><td>4</td><td>0</td></tr><tr><td>8d5998cd984e7cce307da7d46f155f9db99c6590</td><td>chalearn</td><td>ChaLearn</td><td><a href="papers/8d5998cd984e7cce307da7d46f155f9db99c6590.html">ChaLearn looking at people: A review of events and resources</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1701.02664.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2017 International Joint Conference on Neural Networks (IJCNN)</td><td></td><td></td><td></td><td></td><td>30%</td><td>10</td><td>3</td><td>7</td><td>1</td><td>6</td><td>0</td></tr><tr><td>a5acda0e8c0937bfed013e6382da127103e41395</td><td>disfa</td><td>DISFA</td><td><a href="papers/a5acda0e8c0937bfed013e6382da127103e41395.html">Extended DISFA Dataset: Investigating Posed and Spontaneous Facial Expressions</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7789672', 'linkType': 'ieee'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>38%</td><td>8</td><td>3</td><td>5</td><td>1</td><td>5</td><td>0</td></tr><tr><td>137aa2f891d474fce1e7a1d1e9b3aefe21e22b34</td><td>hrt_transgender</td><td>HRT Transgender</td><td><a href="papers/137aa2f891d474fce1e7a1d1e9b3aefe21e22b34.html">Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset</a></td><td><a href="https://doi.org/10.1109/BTAS.2013.6712710">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of North Carolina Wilmington</td><td>34.23755810</td><td>-77.92701290</td><td>43%</td><td>7</td><td>3</td><td>4</td><td>1</td><td>2</td><td>3</td></tr><tr><td>137aa2f891d474fce1e7a1d1e9b3aefe21e22b34</td><td>hrt_transgender</td><td>HRT Transgender</td><td><a href="papers/137aa2f891d474fce1e7a1d1e9b3aefe21e22b34.html">Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset</a></td><td><a href="https://doi.org/10.1109/BTAS.2013.6712710">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of North Carolina Wilmington</td><td>34.23755810</td><td>-77.92701290</td><td>43%</td><td>7</td><td>3</td><td>4</td><td>1</td><td>2</td><td>3</td></tr><tr><td>137aa2f891d474fce1e7a1d1e9b3aefe21e22b34</td><td>hrt_transgender</td><td>HRT Transgender</td><td><a href="papers/137aa2f891d474fce1e7a1d1e9b3aefe21e22b34.html">Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset</a></td><td><a href="https://doi.org/10.1109/BTAS.2013.6712710">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of North Carolina Wilmington</td><td>34.23755810</td><td>-77.92701290</td><td>43%</td><td>7</td><td>3</td><td>4</td><td>1</td><td>2</td><td>3</td></tr><tr><td>57178b36c21fd7f4529ac6748614bb3374714e91</td><td>ijb_c</td><td>IJB-C</td><td><a href="papers/57178b36c21fd7f4529ac6748614bb3374714e91.html">IARPA Janus Benchmark - C: Face Dataset and Protocol</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8411217', 'linkType': 'ieee'}">[pdf]</a></td><td>2018 International Conference on Biometrics (ICB)</td><td></td><td></td><td></td><td></td><td>33%</td><td>9</td><td>3</td><td>6</td><td>2</td><td>9</td><td>0</td></tr><tr><td>07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1</td><td>uccs</td><td>UCCS</td><td><a href="papers/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1.html">Large scale unconstrained open set face database</a></td><td><a href="http://www.vast.uccs.edu/~tboult/PAPERS/BTAS13-Sapkota-Boult-UCCSFaceDB.pdf">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of Colorado at Colorado Springs</td><td>38.89646790</td><td>-104.80505940</td><td>60%</td><td>5</td><td>3</td><td>2</td><td>0</td><td>3</td><td>0</td></tr><tr><td>8627f019882b024aef92e4eb9355c499c733e5b7</td><td>used</td><td>USED Social Event Dataset</td><td><a href="papers/8627f019882b024aef92e4eb9355c499c733e5b7.html">USED: a large-scale social event detection dataset</a></td><td><a href="http://doi.acm.org/10.1145/2910017.2910624">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>7</td><td>3</td><td>4</td><td>0</td><td>3</td><td>2</td></tr><tr><td>4563b46d42079242f06567b3f2e2f7a80cb3befe</td><td>vadana</td><td>VADANA</td><td><a href="papers/4563b46d42079242f06567b3f2e2f7a80cb3befe.html">VADANA: A dense dataset for facial image analysis</a></td><td><a href="http://vims.cis.udel.edu/publications/VADANA_BeFIT2011.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>19%</td><td>16</td><td>3</td><td>13</td><td>0</td><td>6</td><td>6</td></tr><tr><td>56ae6d94fc6097ec4ca861f0daa87941d1c10b70</td><td>cmdp</td><td>CMDP</td><td><a href="papers/56ae6d94fc6097ec4ca861f0daa87941d1c10b70.html">Distance Estimation of an Unknown Person from a Portrait</a></td><td><a href="http://pdfs.semanticscholar.org/56ae/6d94fc6097ec4ca861f0daa87941d1c10b70.pdf">[pdf]</a></td><td></td><td>edu</td><td>California Institute of Technology</td><td>34.13710185</td><td>-118.12527487</td><td>22%</td><td>9</td><td>2</td><td>7</td><td>0</td><td>6</td><td>1</td></tr><tr><td>dd65f71dac86e36eecbd3ed225d016c3336b4a13</td><td>families_in_the_wild</td><td>FIW</td><td><a href="papers/dd65f71dac86e36eecbd3ed225d016c3336b4a13.html">Visual Kinship Recognition of Families in the Wild</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8337841', 'linkType': 'ieee'}">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>67%</td><td>3</td><td>2</td><td>1</td><td>0</td><td>2</td><td>0</td></tr><tr><td>6dbe8e5121c534339d6e41f8683e85f87e6abf81</td><td>gallagher</td><td>Gallagher</td><td><a href="papers/6dbe8e5121c534339d6e41f8683e85f87e6abf81.html">Clothing Cosegmentation for Shopping Images With Cluttered Background</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7423747', 'linkType': 'ieee'}">[pdf]</a></td><td>IEEE Transactions on Multimedia</td><td></td><td></td><td></td><td></td><td>33%</td><td>6</td><td>2</td><td>4</td><td>0</td><td>3</td><td>2</td></tr><tr><td>8f02ec0be21461fbcedf51d864f944cfc42c875f</td><td>hda_plus</td><td>HDA+</td><td><a href="papers/8f02ec0be21461fbcedf51d864f944cfc42c875f.html">The HDA+ Data Set for Research on Fully Automated Re-identification Systems</a></td><td><a href="http://pdfs.semanticscholar.org/8f02/ec0be21461fbcedf51d864f944cfc42c875f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>12%</td><td>17</td><td>2</td><td>15</td><td>2</td><td>11</td><td>0</td></tr><tr><td>8f02ec0be21461fbcedf51d864f944cfc42c875f</td><td>hda_plus</td><td>HDA+</td><td><a href="papers/8f02ec0be21461fbcedf51d864f944cfc42c875f.html">The HDA+ Data Set for Research on Fully Automated Re-identification Systems</a></td><td><a href="http://pdfs.semanticscholar.org/8f02/ec0be21461fbcedf51d864f944cfc42c875f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>12%</td><td>17</td><td>2</td><td>15</td><td>2</td><td>11</td><td>0</td></tr><tr><td>99eb4cea0d9bc9fe777a5c5172f8638a37a7f262</td><td>ilids_vid_reid</td><td>iLIDS-VID</td><td><a href="papers/99eb4cea0d9bc9fe777a5c5172f8638a37a7f262.html">Person Re-identification by Exploiting Spatio-Temporal Cues and Multi-view Metric Learning</a></td><td><a href="https://doi.org/10.1109/LSP.2016.2574323">[pdf]</a></td><td>IEEE Signal Processing Letters</td><td></td><td></td><td></td><td></td><td>29%</td><td>7</td><td>2</td><td>5</td><td>0</td><td>4</td><td>0</td></tr><tr><td>0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e</td><td>lag</td><td>LAG</td><td><a href="papers/0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e.html">Large Age-Gap face verification by feature injection in deep networks</a></td><td><a href="http://pdfs.semanticscholar.org/0d2d/d4fc016cb6a517d8fb43a7cc3ff62964832e.pdf">[pdf]</a></td><td>Pattern Recognition Letters</td><td></td><td></td><td></td><td></td><td>29%</td><td>7</td><td>2</td><td>5</td><td>0</td><td>3</td><td>2</td></tr><tr><td>a7fe834a0af614ce6b50dc093132b031dd9a856b</td><td>market1203</td><td>Market 1203</td><td><a href="papers/a7fe834a0af614ce6b50dc093132b031dd9a856b.html">Orientation Driven Bag of Appearances for Person Re-identification</a></td><td><a href="http://pdfs.semanticscholar.org/a7fe/834a0af614ce6b50dc093132b031dd9a856b.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>29%</td><td>7</td><td>2</td><td>5</td><td>0</td><td>3</td><td>0</td></tr><tr><td>ad01687649d95cd5b56d7399a9603c4b8e2217d7</td><td>mrp_drone</td><td>MRP Drone</td><td><a href="papers/ad01687649d95cd5b56d7399a9603c4b8e2217d7.html">Investigating Open-World Person Re-identi cation Using a Drone</a></td><td><a href="http://pdfs.semanticscholar.org/ad01/687649d95cd5b56d7399a9603c4b8e2217d7.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>40%</td><td>5</td><td>2</td><td>3</td><td>0</td><td>3</td><td>0</td></tr><tr><td>a7fe834a0af614ce6b50dc093132b031dd9a856b</td><td>pku_reid</td><td>PKU-Reid</td><td><a href="papers/a7fe834a0af614ce6b50dc093132b031dd9a856b.html">Orientation Driven Bag of Appearances for Person Re-identification</a></td><td><a href="http://pdfs.semanticscholar.org/a7fe/834a0af614ce6b50dc093132b031dd9a856b.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>29%</td><td>7</td><td>2</td><td>5</td><td>0</td><td>3</td><td>0</td></tr><tr><td>041d3eedf5e45ce5c5229f0181c5c576ed1fafd6</td><td>ucf_selfie</td><td>UCF Selfie</td><td><a href="papers/041d3eedf5e45ce5c5229f0181c5c576ed1fafd6.html">How to Take a Good Selfie?</a></td><td><a href="http://doi.acm.org/10.1145/2733373.2806365">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>22%</td><td>9</td><td>2</td><td>7</td><td>0</td><td>5</td><td>0</td></tr><tr><td>4b4106614c1d553365bad75d7866bff0de6056ed</td><td>czech_news_agency</td><td>UFI</td><td><a href="papers/4b4106614c1d553365bad75d7866bff0de6056ed.html">Unconstrained Facial Images: Database for Face Recognition Under Real-World Conditions</a></td><td><a href="http://pdfs.semanticscholar.org/4b41/06614c1d553365bad75d7866bff0de6056ed.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>10%</td><td>10</td><td>1</td><td>9</td><td>0</td><td>4</td><td>2</td></tr><tr><td>563c940054e4b456661762c1ab858e6f730c3159</td><td>data_61</td><td>Data61 Pedestrian</td><td><a href="papers/563c940054e4b456661762c1ab858e6f730c3159.html">A Multi-modal Graphical Model for Scene Analysis</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/WACV.2015.139">[pdf]</a></td><td>2015 IEEE Winter Conference on Applications of Computer Vision</td><td></td><td></td><td></td><td></td><td>12%</td><td>8</td><td>1</td><td>7</td><td>0</td><td>5</td><td>0</td></tr><tr><td>c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8</td><td>face_research_lab</td><td>Face Research Lab London</td><td><a href="papers/c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8.html">Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.</a></td><td><a href="http://pdfs.semanticscholar.org/c652/6dd3060d63a6c90e8b7ff340383c4e0e0dd8.pdf">[pdf]</a></td><td>Scientific reports</td><td>edu</td><td>University College London</td><td>51.52316070</td><td>-0.12820370</td><td>25%</td><td>4</td><td>1</td><td>3</td><td>0</td><td>2</td><td>2</td></tr><tr><td>17b46e2dad927836c689d6787ddb3387c6159ece</td><td>geofaces</td><td>GeoFaces</td><td><a href="papers/17b46e2dad927836c689d6787ddb3387c6159ece.html">GeoFaceExplorer: exploring the geo-dependence of facial attributes</a></td><td><a href="http://doi.acm.org/10.1145/2676440.2676443">[pdf]</a></td><td></td><td>edu</td><td>University of Kentucky</td><td>38.03337420</td><td>-84.50177580</td><td>50%</td><td>2</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>55c40cbcf49a0225e72d911d762c27bb1c2d14aa</td><td>ifad</td><td>IFAD</td><td><a href="papers/55c40cbcf49a0225e72d911d762c27bb1c2d14aa.html">Indian Face Age Database : A Database for Face Recognition with Age Variation</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/55c4/0cbcf49a0225e72d911d762c27bb1c2d14aa.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>50%</td><td>2</td><td>1</td><td>1</td><td>0</td><td>2</td><td>0</td></tr><tr><td>e3e44385a71a52fd483c58eb3cdf8d03960c0b70</td><td>mcgill</td><td>McGill Real World</td><td><a href="papers/e3e44385a71a52fd483c58eb3cdf8d03960c0b70.html">A Hierarchical Graphical Model for Recognizing Human Actions and Interactions in Video</a></td><td><a href="http://pdfs.semanticscholar.org/e3e4/4385a71a52fd483c58eb3cdf8d03960c0b70.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>50%</td><td>2</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>e3e44385a71a52fd483c58eb3cdf8d03960c0b70</td><td>mcgill</td><td>McGill Real World</td><td><a href="papers/e3e44385a71a52fd483c58eb3cdf8d03960c0b70.html">A Hierarchical Graphical Model for Recognizing Human Actions and Interactions in Video</a></td><td><a href="http://pdfs.semanticscholar.org/e3e4/4385a71a52fd483c58eb3cdf8d03960c0b70.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>50%</td><td>2</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>d80a3d1f3a438e02a6685e66ee908446766fefa9</td><td>megaage</td><td>MegaAge</td><td><a href="papers/d80a3d1f3a438e02a6685e66ee908446766fefa9.html">Quantifying Facial Age by Posterior of Age Comparisons</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1708.09687.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>25%</td><td>4</td><td>1</td><td>3</td><td>1</td><td>4</td><td>0</td></tr><tr><td>23e824d1dfc33f3780dd18076284f07bd99f1c43</td><td>mifs</td><td>MIFS</td><td><a href="papers/23e824d1dfc33f3780dd18076284f07bd99f1c43.html">Spoofing faces using makeup: An investigative study</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7947686', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)</td><td>edu</td><td>INRIA Méditerranée</td><td>43.61581310</td><td>7.06838000</td><td>20%</td><td>5</td><td>1</td><td>4</td><td>0</td><td>1</td><td>2</td></tr><tr><td>fb82681ac5d3487bd8e52dbb3d1fa220eeac855e</td><td>pilot_parliament</td><td>PPB</td><td><a href="papers/fb82681ac5d3487bd8e52dbb3d1fa220eeac855e.html">1 Network Notebook</a></td><td><a href="http://pdfs.semanticscholar.org/fb82/681ac5d3487bd8e52dbb3d1fa220eeac855e.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>9%</td><td>11</td><td>1</td><td>10</td><td>1</td><td>10</td><td>0</td></tr><tr><td>9e5378e7b336c89735d3bb15cf67eff96f86d39a</td><td>precarious</td><td>Precarious</td><td><a href="papers/9e5378e7b336c89735d3bb15cf67eff96f86d39a.html">Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1703.06283.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>8%</td><td>12</td><td>1</td><td>11</td><td>1</td><td>10</td><td>0</td></tr><tr><td>54983972aafc8e149259d913524581357b0f91c3</td><td>reseed</td><td>ReSEED</td><td><a href="papers/54983972aafc8e149259d913524581357b0f91c3.html">ReSEED: social event dEtection dataset</a></td><td><a href="https://pub.uni-bielefeld.de/download/2663466/2686734">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>17%</td><td>6</td><td>1</td><td>5</td><td>1</td><td>1</td><td>1</td></tr><tr><td>c9bda86e23cab9e4f15ea0c4cbb6cc02b9dfb709</td><td>stanford_drone</td><td>Stanford Drone</td><td><a href="papers/c9bda86e23cab9e4f15ea0c4cbb6cc02b9dfb709.html">Learning to predict human behaviour in crowded scenes</a></td><td><a href="http://pdfs.semanticscholar.org/c9bd/a86e23cab9e4f15ea0c4cbb6cc02b9dfb709.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>20%</td><td>5</td><td>1</td><td>4</td><td>1</td><td>5</td><td>0</td></tr><tr><td>9696ad8b164f5e10fcfe23aacf74bd6168aebb15</td><td>4dfab</td><td>4DFAB</td><td><a href="papers/9696ad8b164f5e10fcfe23aacf74bd6168aebb15.html">4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1712.01443.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>0%</td><td>4</td><td>0</td><td>4</td><td>0</td><td>2</td><td>0</td></tr><tr><td>f152b6ee251cca940dd853c54e6a7b78fbc6b235</td><td>affectnet</td><td>AffectNet</td><td><a href="papers/f152b6ee251cca940dd853c54e6a7b78fbc6b235.html">Skybiometry and AffectNet on Facial Emotion Recognition Using Supervised Machine Learning Algorithms</a></td><td><a href="{'url': 'http://dl.acm.org/citation.cfm?id=3232665', 'linkType': 'acm'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>1ed1a49534ad8dd00f81939449f6389cfbc25321</td><td>bjut_3d</td><td>BJUT-3D</td><td><a href="papers/1ed1a49534ad8dd00f81939449f6389cfbc25321.html">A novel face recognition method based on 3D face model</a></td><td><a href="https://doi.org/10.1109/ROBIO.2007.4522202">[pdf]</a></td><td>2007 IEEE International Conference on Robotics and Biomimetics (ROBIO)</td><td></td><td></td><td></td><td></td><td>0%</td><td>2</td><td>0</td><td>2</td><td>0</td><td>1</td><td>1</td></tr><tr><td>65355cbb581a219bd7461d48b3afd115263ea760</td><td>complex_activities</td><td>Ongoing Complex Activities</td><td><a href="papers/65355cbb581a219bd7461d48b3afd115263ea760.html">Recognition of ongoing complex activities by sequence prediction over a hierarchical label space</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/WACV.2016.7477586">[pdf]</a></td><td>2016 IEEE Winter Conference on Applications of Computer Vision (WACV)</td><td></td><td></td><td></td><td></td><td>0%</td><td>2</td><td>0</td><td>2</td><td>0</td><td>2</td><td>0</td></tr><tr><td>f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4</td><td>europersons</td><td>EuroCity Persons</td><td><a href="papers/f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4.html">The EuroCity Persons Dataset: A Novel Benchmark for Object Detection</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1805.07193.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>75da1df4ed319926c544eefe17ec8d720feef8c0</td><td>fddb</td><td>FDDB</td><td><a href="papers/75da1df4ed319926c544eefe17ec8d720feef8c0.html">FDDB: A Benchmark for Face Detection in Unconstrained Settings</a></td><td><a href="http://pdfs.semanticscholar.org/75da/1df4ed319926c544eefe17ec8d720feef8c0.pdf">[pdf]</a></td><td></td><td>edu</td><td>University of Massachusetts</td><td>42.38897850</td><td>-72.52869870</td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>b6b1b0632eb9d4ab1427278f5e5c46f97753c73d</td><td>fei</td><td>FEI</td><td><a href="papers/b6b1b0632eb9d4ab1427278f5e5c46f97753c73d.html">Generalização cartográfica automatizada para um banco de dados cadastral</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/b6b1/b0632eb9d4ab1427278f5e5c46f97753c73d.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>3dc3f0b64ef80f573e3a5f96e456e52ee980b877</td><td>georgia_tech_face_database</td><td>Georgia Tech Face</td><td><a href="papers/3dc3f0b64ef80f573e3a5f96e456e52ee980b877.html">Maximum Likelihood Training of the Embedded HMM for Face Detection and Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/3dc3/f0b64ef80f573e3a5f96e456e52ee980b877.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>3</td><td>0</td><td>3</td><td>0</td><td>2</td><td>0</td></tr><tr><td>24830e3979d4ed01b9fd0feebf4a8fd22e0c35fd</td><td>hi4d_adsip</td><td>Hi4D-ADSIP</td><td><a href="papers/24830e3979d4ed01b9fd0feebf4a8fd22e0c35fd.html">High-resolution comprehensive 3-D dynamic database for facial articulation analysis</a></td><td><a href="http://www.researchgate.net/profile/Wei_Quan3/publication/221430048_High-resolution_comprehensive_3-D_dynamic_database_for_facial_articulation_analysis/links/0deec534309495805d000000.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>0%</td><td>5</td><td>0</td><td>5</td><td>0</td><td>1</td><td>0</td></tr><tr><td>ad62c6e17bc39b4dec20d32f6ac667ae42d2c118</td><td>jiku_mobile</td><td>Jiku Mobile Video Dataset</td><td><a href="papers/ad62c6e17bc39b4dec20d32f6ac667ae42d2c118.html">A Synchronization Ground Truth for the Jiku Mobile Video Dataset</a></td><td><a href="http://pdfs.semanticscholar.org/ad62/c6e17bc39b4dec20d32f6ac667ae42d2c118.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>079a0a3bf5200994e1f972b1b9197bf2f90e87d4</td><td>mit_cbcl</td><td>MIT CBCL</td><td><a href="papers/079a0a3bf5200994e1f972b1b9197bf2f90e87d4.html">Component-Based Face Recognition with 3D Morphable Models</a></td><td><a href="http://www.bheisele.com/avbpa2003.pdf">[pdf]</a></td><td>2004 Conference on Computer Vision and Pattern Recognition Workshop</td><td></td><td></td><td></td><td></td><td>0%</td><td>12</td><td>0</td><td>12</td><td>0</td><td>8</td><td>0</td></tr><tr><td>c06b13d0ec3f5c43e2782cd22542588e233733c3</td><td>nova_emotions</td><td>Novaemötions Dataset</td><td><a href="papers/c06b13d0ec3f5c43e2782cd22542588e233733c3.html">Crowdsourcing facial expressions for affective-interaction</a></td><td><a href="https://doi.org/10.1016/j.cviu.2016.02.001">[pdf]</a></td><td>Computer Vision and Image Understanding</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>c06b13d0ec3f5c43e2782cd22542588e233733c3</td><td>nova_emotions</td><td>Novaemötions Dataset</td><td><a href="papers/c06b13d0ec3f5c43e2782cd22542588e233733c3.html">Crowdsourcing facial expressions for affective-interaction</a></td><td><a href="https://doi.org/10.1016/j.cviu.2016.02.001">[pdf]</a></td><td>Computer Vision and Image Understanding</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>22909dd19a0ec3b6065334cb5be5392cb24d839d</td><td>pets</td><td>PETS 2017</td><td><a href="papers/22909dd19a0ec3b6065334cb5be5392cb24d839d.html">PETS 2017: Dataset and Challenge</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8014998', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>0%</td><td>8</td><td>0</td><td>8</td><td>0</td><td>2</td><td>0</td></tr><tr><td>f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f</td><td>pku</td><td>PKU</td><td><a href="papers/f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f.html">Swiss-System Based Cascade Ranking for Gait-Based Person Re-Identification</a></td><td><a href="http://pdfs.semanticscholar.org/f6c8/d5e35d7e4d60a0104f233ac1a3ab757da53f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>3</td><td>0</td><td>3</td><td>0</td><td>1</td><td>0</td></tr><tr><td>c866a2afc871910e3282fd9498dce4ab20f6a332</td><td>qmul_surv_face</td><td>QMUL-SurvFace</td><td><a href="papers/c866a2afc871910e3282fd9498dce4ab20f6a332.html">Surveillance Face Recognition Challenge</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1804.09691.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>f3b84a03985de3890b400b68e2a92c0a00afd9d0</td><td>scface</td><td>SCface</td><td><a href="papers/f3b84a03985de3890b400b68e2a92c0a00afd9d0.html">Large Variability Surveillance Camera Face Database</a></td><td><span class="gray">[pdf]</a></td><td>2015 Seventh International Conference on Computational Intelligence, Modelling and Simulation (CIMSim)</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9</td><td>stair_actions</td><td>STAIR Action</td><td><a href="papers/d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9.html">STAIR Actions: A Video Dataset of Everyday Home Actions</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1804.04326.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>377f2b65e6a9300448bdccf678cde59449ecd337</td><td>ufdd</td><td>UFDD</td><td><a href="papers/377f2b65e6a9300448bdccf678cde59449ecd337.html">Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1804.10275.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td>edu</td><td>Johns Hopkins University</td><td>39.32905300</td><td>-76.61942500</td><td>0%</td><td>2</td><td>0</td><td>2</td><td>0</td><td>2</td><td>0</td></tr><tr><td>922e0a51a3b8c67c4c6ac09a577ff674cbd28b34</td><td>v47</td><td>V47</td><td><a href="papers/922e0a51a3b8c67c4c6ac09a577ff674cbd28b34.html">Re-identification of pedestrians with variable occlusion and scale</a></td><td><a href="https://doi.org/10.1109/ICCVW.2011.6130477">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>0%</td><td>10</td><td>0</td><td>10</td><td>2</td><td>6</td><td>0</td></tr><tr><td>9b9bf5e623cb8af7407d2d2d857bc3f1b531c182</td><td>who_goes_there</td><td>WGT</td><td><a href="papers/9b9bf5e623cb8af7407d2d2d857bc3f1b531c182.html">Who goes there?: approaches to mapping facial appearance diversity</a></td><td><a href="http://doi.acm.org/10.1145/2996913.2996997">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>77c81c13a110a341c140995bedb98101b9e84f7f</td><td>wildtrack</td><td>WildTrack</td><td><a href="papers/77c81c13a110a341c140995bedb98101b9e84f7f.html">WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/fe1c/ec4e4995b8615855572374ae3efc94949105.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>5ad4e9f947c1653c247d418f05dad758a3f9277b</td><td>wlfdb</td><td></td><td><a href="papers/5ad4e9f947c1653c247d418f05dad758a3f9277b.html">WLFDB: Weakly Labeled Face Databases</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/5ad4/e9f947c1653c247d418f05dad758a3f9277b.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>a94cae786d515d3450d48267e12ca954aab791c4</td><td>yawdd</td><td>YawDD</td><td><a href="papers/a94cae786d515d3450d48267e12ca954aab791c4.html">YawDD: a yawning detection dataset</a></td><td><a href="http://www.site.uottawa.ca/~shervin/pubs/CogniVue-Dataset-ACM-MMSys2014.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>14</td><td>0</td><td>14</td><td>1</td><td>2</td><td>1</td></tr></table></body></html>
\ No newline at end of file diff --git a/scraper/reports/report_index.html b/scraper/reports/report_index.html index d876ee3a..a84a6295 100644 --- a/scraper/reports/report_index.html +++ b/scraper/reports/report_index.html @@ -1 +1 @@ -<!doctype html><html><head><meta charset='utf-8'><title>All Papers</title><link rel='stylesheet' href='reports.css'></head><body><h2>All Papers</h2><table border='1' cellpadding='3' cellspacing='3'><th>Paper ID</th><th>Megapixels Key</th><th>Report Link</th><th>PDF Link</th><th>Journal</th><th>Type</th><th>Address</th><th>Lat</th><th>Lng</th><th>Coverage</th><th>Total Citations</th><th>Geocoded Citations</th><th>Unknown Citations</th><th>Empty Citations</th><th>With PDF</th><th>With DOI</th><tr><td>e4754afaa15b1b53e70743880484b8d0736990ff</td><td></td><td><a href="papers/e4754afaa15b1b53e70743880484b8d0736990ff.html">300 Faces In-The-Wild Challenge: database and results</a></td><td><a href="{'url': 'http://doi.org/10.1016/j.imavis.2016.01.002', 'linkType': 'doi'}">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>47%</td><td>103</td><td>48</td><td>55</td><td>10</td><td>65</td><td>30</td></tr><tr><td>044d9a8c61383312cdafbcc44b9d00d650b21c70</td><td></td><td><a href="papers/044d9a8c61383312cdafbcc44b9d00d650b21c70.html">300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge</a></td><td><a href="https://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_iccv_2013_300_w.pdf">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision Workshops</td><td>edu</td><td>University of Twente</td><td>52.23801390</td><td>6.85667610</td><td>56%</td><td>285</td><td>159</td><td>125</td><td>25</td><td>185</td><td>82</td></tr><tr><td>c34532fe6bfbd1e6df477c9ffdbb043b77e7804d</td><td></td><td><a href="papers/c34532fe6bfbd1e6df477c9ffdbb043b77e7804d.html">A 3D Morphable Eye Region Model for Gaze Estimation</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/0d43/3b9435b874a1eea6d7999e86986c910fa285.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td>edu</td><td>Carnegie Mellon University</td><td>37.41021930</td><td>-122.05965487</td><td>71%</td><td>21</td><td>15</td><td>6</td><td>0</td><td>17</td><td>4</td></tr><tr><td>013909077ad843eb6df7a3e8e290cfd5575999d2</td><td></td><td><a href="papers/013909077ad843eb6df7a3e8e290cfd5575999d2.html">A Semi-automatic Methodology for Facial Landmark Annotation</a></td><td><a href="http://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_cvpr_2013_amfg_w.pdf">[pdf]</a></td><td>2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops</td><td>edu</td><td>University of Twente</td><td>52.23801390</td><td>6.85667610</td><td>59%</td><td>169</td><td>100</td><td>69</td><td>14</td><td>112</td><td>49</td></tr><tr><td>0d3bb75852098b25d90f31d2f48fd0cb4944702b</td><td>FaceScrub</td><td><a href="papers/0d3bb75852098b25d90f31d2f48fd0cb4944702b.html">A data-driven approach to cleaning large face datasets</a></td><td><a href="https://doi.org/10.1109/ICIP.2014.7025068">[pdf]</a></td><td>2014 IEEE International Conference on Image Processing (ICIP)</td><td>edu</td><td>University of Illinois, Urbana-Champaign</td><td>40.11116745</td><td>-88.22587665</td><td>48%</td><td>120</td><td>57</td><td>63</td><td>5</td><td>93</td><td>24</td></tr><tr><td>1be498d4bbc30c3bfd0029114c784bc2114d67c0</td><td>Adience</td><td><a href="papers/1be498d4bbc30c3bfd0029114c784bc2114d67c0.html">Age and Gender Estimation of Unfiltered Faces</a></td><td><a href="http://www.openu.ac.il/home/hassner/Adience/EidingerEnbarHassner_tifs.pdf">[pdf]</a></td><td>IEEE Transactions on Information Forensics and Security</td><td></td><td></td><td></td><td></td><td>45%</td><td>155</td><td>69</td><td>86</td><td>5</td><td>80</td><td>55</td></tr><tr><td>6dcf418c778f528b5792104760f1fbfe90c6dd6a</td><td></td><td><a href="papers/6dcf418c778f528b5792104760f1fbfe90c6dd6a.html">AgeDB: The First Manually Collected, In-the-Wild Age Database</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8014984', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>70%</td><td>10</td><td>7</td><td>2</td><td>1</td><td>9</td><td>0</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td></td><td><a href="papers/a74251efa970b92925b89eeef50a5e37d9281ad0.html">Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization</a></td><td><a href="http://lrs.icg.tugraz.at/pubs/koestinger_befit_11.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>55%</td><td>278</td><td>153</td><td>125</td><td>30</td><td>195</td><td>65</td></tr><tr><td>c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8</td><td></td><td><a href="papers/c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8.html">Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.</a></td><td><a href="http://pdfs.semanticscholar.org/c652/6dd3060d63a6c90e8b7ff340383c4e0e0dd8.pdf">[pdf]</a></td><td>Scientific reports</td><td>edu</td><td>University College London</td><td>51.52316070</td><td>-0.12820370</td><td>25%</td><td>4</td><td>1</td><td>3</td><td>0</td><td>2</td><td>2</td></tr><tr><td>759a3b3821d9f0e08e0b0a62c8b693230afc3f8d</td><td></td><td><a href="papers/759a3b3821d9f0e08e0b0a62c8b693230afc3f8d.html">Attribute and simile classifiers for face verification</a></td><td><a href="http://homes.cs.washington.edu/~neeraj/projects/faceverification/base/papers/nk_iccv2009_attrs.pdf">[pdf]</a></td><td>2009 IEEE 12th International Conference on Computer Vision</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>53%</td><td>862</td><td>457</td><td>405</td><td>46</td><td>556</td><td>232</td></tr><tr><td>fcc6fe6007c322641796cb8792718641856a22a7</td><td></td><td><a href="papers/fcc6fe6007c322641796cb8792718641856a22a7.html">Automatic facial makeup detection with application in face recognition</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6612994', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 International Conference on Biometrics (ICB)</td><td>edu</td><td>West Virginia University</td><td>39.65404635</td><td>-79.96475355</td><td>67%</td><td>43</td><td>29</td><td>14</td><td>0</td><td>16</td><td>21</td></tr><tr><td>0a85bdff552615643dd74646ac881862a7c7072d</td><td></td><td><a href="papers/0a85bdff552615643dd74646ac881862a7c7072d.html">Beyond frontal faces: Improving Person Recognition using multiple cues</a></td><td><a href="https://doi.org/10.1109/CVPR.2015.7299113">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>64%</td><td>45</td><td>29</td><td>15</td><td>2</td><td>37</td><td>5</td></tr><tr><td>37d6f0eb074d207b53885bd2eb78ccc8a04be597</td><td></td><td><a href="papers/37d6f0eb074d207b53885bd2eb78ccc8a04be597.html">Can facial cosmetics affect the matching accuracy of face recognition systems?</a></td><td><a href="http://www.cse.msu.edu/~climer/DantchevaChenRossFaceCosmetics_BTAS2012.pdf">[pdf]</a></td><td>2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td></td><td></td><td></td><td></td><td>50%</td><td>46</td><td>23</td><td>23</td><td>0</td><td>17</td><td>22</td></tr><tr><td>45c31cde87258414f33412b3b12fc5bec7cb3ba9</td><td>JAFFE</td><td><a href="papers/45c31cde87258414f33412b3b12fc5bec7cb3ba9.html">Coding Facial Expressions with Gabor Wavelets</a></td><td><a href="http://pdfs.semanticscholar.org/45c3/1cde87258414f33412b3b12fc5bec7cb3ba9.pdf">[pdf]</a></td><td></td><td>edu</td><td>Kyushu University</td><td>33.59914655</td><td>130.22359848</td><td>39%</td><td>804</td><td>310</td><td>494</td><td>45</td><td>383</td><td>263</td></tr><tr><td>23fc83c8cfff14a16df7ca497661264fc54ed746</td><td>CK</td><td><a href="papers/23fc83c8cfff14a16df7ca497661264fc54ed746.html">Comprehensive Database for Facial Expression Analysis</a></td><td><a href="http://pdfs.semanticscholar.org/23fc/83c8cfff14a16df7ca497661264fc54ed746.pdf">[pdf]</a></td><td></td><td>edu</td><td>Carnegie Mellon University</td><td>37.41021930</td><td>-122.05965487</td><td>39%</td><td>999</td><td>386</td><td>612</td><td>64</td><td>536</td><td>263</td></tr><tr><td>8355d095d3534ef511a9af68a3b2893339e3f96b</td><td></td><td><a href="papers/8355d095d3534ef511a9af68a3b2893339e3f96b.html">DEX: Deep EXpectation of Apparent Age from a Single Image</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7406390', 'linkType': 'ieee'}">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision Workshop (ICCVW)</td><td></td><td></td><td></td><td></td><td>44%</td><td>102</td><td>45</td><td>54</td><td>5</td><td>61</td><td>28</td></tr><tr><td>10195a163ab6348eef37213a46f60a3d87f289c5</td><td></td><td><a href="papers/10195a163ab6348eef37213a46f60a3d87f289c5.html">Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks</a></td><td><a href="https://doi.org/10.1007/s11263-016-0940-3">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>49%</td><td>121</td><td>59</td><td>61</td><td>10</td><td>84</td><td>29</td></tr><tr><td>56ae6d94fc6097ec4ca861f0daa87941d1c10b70</td><td>CMDP</td><td><a href="papers/56ae6d94fc6097ec4ca861f0daa87941d1c10b70.html">Distance Estimation of an Unknown Person from a Portrait</a></td><td><a href="http://pdfs.semanticscholar.org/56ae/6d94fc6097ec4ca861f0daa87941d1c10b70.pdf">[pdf]</a></td><td></td><td>edu</td><td>California Institute of Technology</td><td>34.13710185</td><td>-118.12527487</td><td>25%</td><td>8</td><td>2</td><td>6</td><td>0</td><td>5</td><td>1</td></tr><tr><td>133f01aec1534604d184d56de866a4bd531dac87</td><td></td><td><a href="papers/133f01aec1534604d184d56de866a4bd531dac87.html">Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.230">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>42%</td><td>168</td><td>71</td><td>97</td><td>15</td><td>95</td><td>55</td></tr><tr><td>1ea8085fe1c79d12adffb02bd157b54d799568e4</td><td></td><td><a href="papers/1ea8085fe1c79d12adffb02bd157b54d799568e4.html">Eigenfaces vs. Fisherfaces: Recognition Using Class Speciic Linear Projection</a></td><td><a href="http://pdfs.semanticscholar.org/1ea8/085fe1c79d12adffb02bd157b54d799568e4.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>33%</td><td>583</td><td>194</td><td>388</td><td>44</td><td>300</td><td>162</td></tr><tr><td>447d8893a4bdc29fa1214e53499ffe67b28a6db5</td><td></td><td><a href="papers/447d8893a4bdc29fa1214e53499ffe67b28a6db5.html">Electronic Transport in Quantum Confined Systems</a></td><td><a href="http://pdfs.semanticscholar.org/447d/8893a4bdc29fa1214e53499ffe67b28a6db5.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>75da1df4ed319926c544eefe17ec8d720feef8c0</td><td>FDDB</td><td><a href="papers/75da1df4ed319926c544eefe17ec8d720feef8c0.html">FDDB: A Benchmark for Face Detection in Unconstrained Settings</a></td><td><a href="http://pdfs.semanticscholar.org/75da/1df4ed319926c544eefe17ec8d720feef8c0.pdf">[pdf]</a></td><td></td><td>edu</td><td>University of Massachusetts</td><td>42.38897850</td><td>-72.52869870</td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>0e986f51fe45b00633de9fd0c94d082d2be51406</td><td></td><td><a href="papers/0e986f51fe45b00633de9fd0c94d082d2be51406.html">Face detection, pose estimation, and landmark localization in the wild</a></td><td><a href="http://vision.ics.uci.edu/papers/ZhuR_CVPR_2012/ZhuR_CVPR_2012.pdf">[pdf]</a></td><td>2012 IEEE Conference on Computer Vision and Pattern Recognition</td><td>edu</td><td>University of California, Irvine</td><td>33.64319010</td><td>-117.84016494</td><td>54%</td><td>999</td><td>541</td><td>458</td><td>52</td><td>601</td><td>303</td></tr><tr><td>560e0e58d0059259ddf86fcec1fa7975dee6a868</td><td></td><td><a href="papers/560e0e58d0059259ddf86fcec1fa7975dee6a868.html">Face recognition in unconstrained videos with matched background similarity</a></td><td><a href="http://www.cs.tau.ac.il/~wolf/papers/lvfw.pdf">[pdf]</a></td><td>CVPR 2011</td><td>edu</td><td>Open University of Israel</td><td>32.77824165</td><td>34.99565673</td><td>53%</td><td>457</td><td>241</td><td>214</td><td>27</td><td>273</td><td>149</td></tr><tr><td>670637d0303a863c1548d5b19f705860a23e285c</td><td></td><td><a href="papers/670637d0303a863c1548d5b19f705860a23e285c.html">Face swapping: automatically replacing faces in photographs</a></td><td><a href="https://classes.cs.uoregon.edu/16F/cis607photo/faces.pdf">[pdf]</a></td><td>ACM Trans. Graph.</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>100%</td><td>2</td><td>2</td><td>0</td><td>0</td><td>1</td><td>1</td></tr><tr><td>4c170a0dcc8de75587dae21ca508dab2f9343974</td><td>FaceTracer</td><td><a href="papers/4c170a0dcc8de75587dae21ca508dab2f9343974.html">FaceTracer: A Search Engine for Large Collections of Images with Faces</a></td><td><a href="http://pdfs.semanticscholar.org/73a8/1d311eedac8dea3ca24dc15b6990fa4a725e.pdf">[pdf]</a></td><td></td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>49%</td><td>212</td><td>103</td><td>109</td><td>13</td><td>137</td><td>52</td></tr><tr><td>45e616093a92e5f1e61a7c6037d5f637aa8964af</td><td></td><td><a href="papers/45e616093a92e5f1e61a7c6037d5f637aa8964af.html">Fine-grained evaluation on face detection in the wild</a></td><td><a href="http://www.cs.toronto.edu/~byang/papers/malf_fg15.pdf">[pdf]</a></td><td>2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>Chinese Academy of Sciences</td><td>40.00447950</td><td>116.37023800</td><td>71%</td><td>17</td><td>12</td><td>5</td><td>0</td><td>13</td><td>4</td></tr><tr><td>04661729f0ff6afe4b4d6223f18d0da1d479accf</td><td>CelebA</td><td><a href="papers/04661729f0ff6afe4b4d6223f18d0da1d479accf.html">From Facial Parts Responses to Face Detection: A Deep Learning Approach</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.419">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td>edu</td><td>Shenzhen Institutes of Advanced Technology</td><td>22.59805605</td><td>113.98533784</td><td>57%</td><td>150</td><td>86</td><td>63</td><td>12</td><td>93</td><td>48</td></tr><tr><td>18c72175ddbb7d5956d180b65a96005c100f6014</td><td>Yale Face Database B</td><td><a href="papers/18c72175ddbb7d5956d180b65a96005c100f6014.html">From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose</a></td><td><a href="http://pdfs.semanticscholar.org/97bb/c2b439a79d4dc0dc7199d71ed96ad5e3fd0e.pdf">[pdf]</a></td><td>IEEE Trans. Pattern Anal. Mach. Intell.</td><td></td><td></td><td></td><td></td><td>45%</td><td>999</td><td>445</td><td>553</td><td>65</td><td>519</td><td>330</td></tr><tr><td>04c2cda00e5536f4b1508cbd80041e9552880e67</td><td></td><td><a href="papers/04c2cda00e5536f4b1508cbd80041e9552880e67.html">Hipster Wars: Discovering Elements of Fashion Styles</a></td><td><a href="http://pdfs.semanticscholar.org/04c2/cda00e5536f4b1508cbd80041e9552880e67.pdf">[pdf]</a></td><td></td><td>edu</td><td>Tohoku University</td><td>38.25309450</td><td>140.87365930</td><td>58%</td><td>85</td><td>49</td><td>36</td><td>3</td><td>55</td><td>19</td></tr><tr><td>ca3e88d87e1344d076c964ea89d91a75c417f5ee</td><td></td><td><a href="papers/ca3e88d87e1344d076c964ea89d91a75c417f5ee.html">Indian Movie Face Database: A benchmark for face recognition under wide variations</a></td><td><span class="gray">[pdf]</a></td><td>2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)</td><td></td><td></td><td></td><td></td><td>64%</td><td>14</td><td>9</td><td>5</td><td>0</td><td>10</td><td>4</td></tr><tr><td>95f12d27c3b4914e0668a268360948bce92f7db3</td><td>Helen</td><td><a href="papers/95f12d27c3b4914e0668a268360948bce92f7db3.html">Interactive Facial Feature Localization</a></td><td><a href="http://pdfs.semanticscholar.org/95f1/2d27c3b4914e0668a268360948bce92f7db3.pdf">[pdf]</a></td><td></td><td>edu</td><td>University of Illinois, Urbana-Champaign</td><td>40.11116745</td><td>-88.22587665</td><td>54%</td><td>323</td><td>175</td><td>147</td><td>23</td><td>198</td><td>105</td></tr><tr><td>4d423acc78273b75134e2afd1777ba6d3a398973</td><td></td><td><a href="papers/4d423acc78273b75134e2afd1777ba6d3a398973.html">International Conference on Automatic Face and Gesture Recognition The CMU Pose , Illumination , and Expression ( PIE ) Database</a></td><td><a href="http://pdfs.semanticscholar.org/4d42/3acc78273b75134e2afd1777ba6d3a398973.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>46%</td><td>723</td><td>331</td><td>392</td><td>55</td><td>392</td><td>237</td></tr><tr><td>137aa2f891d474fce1e7a1d1e9b3aefe21e22b34</td><td></td><td><a href="papers/137aa2f891d474fce1e7a1d1e9b3aefe21e22b34.html">Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset</a></td><td><a href="https://doi.org/10.1109/BTAS.2013.6712710">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of North Carolina Wilmington</td><td>34.23755810</td><td>-77.92701290</td><td>57%</td><td>7</td><td>4</td><td>3</td><td>1</td><td>2</td><td>4</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td></td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>50%</td><td>999</td><td>496</td><td>500</td><td>62</td><td>613</td><td>293</td></tr><tr><td>0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e</td><td></td><td><a href="papers/0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e.html">Large Age-Gap face verification by feature injection in deep networks</a></td><td><a href="http://pdfs.semanticscholar.org/0d2d/d4fc016cb6a517d8fb43a7cc3ff62964832e.pdf">[pdf]</a></td><td>Pattern Recognition Letters</td><td></td><td></td><td></td><td></td><td>40%</td><td>5</td><td>2</td><td>3</td><td>0</td><td>2</td><td>2</td></tr><tr><td>853bd61bc48a431b9b1c7cab10c603830c488e39</td><td>CAISA Webface</td><td><a href="papers/853bd61bc48a431b9b1c7cab10c603830c488e39.html">Learning Face Representation from Scratch</a></td><td><a href="http://pdfs.semanticscholar.org/b8a2/0ed7e74325da76d7183d1ab77b082a92b447.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>58%</td><td>401</td><td>232</td><td>168</td><td>28</td><td>261</td><td>125</td></tr><tr><td>28d4e027c7e90b51b7d8908fce68128d1964668a</td><td>MegaFace 2</td><td><a href="papers/28d4e027c7e90b51b7d8908fce68128d1964668a.html">Level Playing Field for Million Scale Face Recognition</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1705.00393.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>41%</td><td>27</td><td>11</td><td>16</td><td>2</td><td>22</td><td>4</td></tr><tr><td>140438a77a771a8fb656b39a78ff488066eb6b50</td><td>LFWP</td><td><a href="papers/140438a77a771a8fb656b39a78ff488066eb6b50.html">Localizing Parts of Faces Using a Consensus of Exemplars</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2011.5995602">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>54%</td><td>506</td><td>273</td><td>232</td><td>36</td><td>309</td><td>150</td></tr><tr><td>9055b155cbabdce3b98e16e5ac9c0edf00f9552f</td><td></td><td><a href="papers/9055b155cbabdce3b98e16e5ac9c0edf00f9552f.html">MORPH: a longitudinal image database of normal adult age-progression</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/FGR.2006.78">[pdf]</a></td><td>7th International Conference on Automatic Face and Gesture Recognition (FGR06)</td><td></td><td></td><td></td><td></td><td>47%</td><td>406</td><td>191</td><td>212</td><td>22</td><td>208</td><td>161</td></tr><tr><td>291265db88023e92bb8c8e6390438e5da148e8f5</td><td>MsCeleb</td><td><a href="papers/291265db88023e92bb8c8e6390438e5da148e8f5.html">MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/4603/cb8e05258bb0572ae912ad20903b8f99f4b1.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>49%</td><td>150</td><td>73</td><td>76</td><td>14</td><td>115</td><td>29</td></tr><tr><td>203009d3608bdc31ffc3991a0310b9e98b630c4d</td><td></td><td><a href="papers/203009d3608bdc31ffc3991a0310b9e98b630c4d.html">Moving faces, looking places: validation of the Amsterdam Dynamic Facial Expression Set (ADFES).</a></td><td><span class="gray">[pdf]</a></td><td>Emotion</td><td></td><td></td><td></td><td></td><td>39%</td><td>77</td><td>30</td><td>47</td><td>6</td><td>52</td><td>14</td></tr><tr><td>2fda164863a06a92d3a910b96eef927269aeb730</td><td></td><td><a href="papers/2fda164863a06a92d3a910b96eef927269aeb730.html">Names and faces in the news</a></td><td><a href="http://www.cs.utexas.edu/~grauman/courses/spring2007/395T/papers/berg_names_and_faces.pdf">[pdf]</a></td><td>Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.</td><td></td><td></td><td></td><td></td><td>41%</td><td>290</td><td>118</td><td>172</td><td>19</td><td>197</td><td>45</td></tr><tr><td>3c8db0d86a6aa51b64ec09c7d25a721adcdfb7a3</td><td></td><td><a href="papers/3c8db0d86a6aa51b64ec09c7d25a721adcdfb7a3.html">Ordered trajectories for human action recognition with large number of classes</a></td><td><a href="https://doi.org/10.1016/j.imavis.2015.06.009">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>100%</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td></tr><tr><td>636b8ffc09b1b23ff714ac8350bb35635e49fa3c</td><td></td><td><a href="papers/636b8ffc09b1b23ff714ac8350bb35635e49fa3c.html">Pruning training sets for learning of object categories</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1467308', 'linkType': 'ieee'}">[pdf]</a></td><td>2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)</td><td></td><td></td><td></td><td></td><td>58%</td><td>60</td><td>35</td><td>25</td><td>4</td><td>41</td><td>12</td></tr><tr><td>140c95e53c619eac594d70f6369f518adfea12ef</td><td>IJB-A</td><td><a href="papers/140c95e53c619eac594d70f6369f518adfea12ef.html">Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2015/app/1B_089_ext.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>47%</td><td>208</td><td>98</td><td>107</td><td>20</td><td>144</td><td>52</td></tr><tr><td>356b431d4f7a2a0a38cf971c84568207dcdbf189</td><td></td><td><a href="papers/356b431d4f7a2a0a38cf971c84568207dcdbf189.html">Recognize complex events from static images by fusing deep channels</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Xiong_Recognize_Complex_Events_2015_CVPR_paper.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Shenzhen Institutes of Advanced Technology</td><td>22.59805605</td><td>113.98533784</td><td>60%</td><td>43</td><td>26</td><td>17</td><td>1</td><td>30</td><td>12</td></tr><tr><td>2724ba85ec4a66de18da33925e537f3902f21249</td><td></td><td><a href="papers/2724ba85ec4a66de18da33925e537f3902f21249.html">Robust Face Landmark Estimation under Occlusion</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6751298', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>56%</td><td>296</td><td>167</td><td>128</td><td>14</td><td>179</td><td>99</td></tr><tr><td>bd26dabab576adb6af30484183c9c9c8379bf2e0</td><td>SCUT-FBP</td><td><a href="papers/bd26dabab576adb6af30484183c9c9c8379bf2e0.html">SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1511.02459.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2015 IEEE International Conference on Systems, Man, and Cybernetics</td><td>edu</td><td>South China University of Technology</td><td>23.05020420</td><td>113.39880323</td><td>43%</td><td>14</td><td>6</td><td>8</td><td>3</td><td>5</td><td>7</td></tr><tr><td>51eba481dac6b229a7490f650dff7b17ce05df73</td><td>imSitu</td><td><a href="papers/51eba481dac6b229a7490f650dff7b17ce05df73.html">Situation Recognition: Visual Semantic Role Labeling for Image Understanding</a></td><td><a href="http://grail.cs.washington.edu/wp-content/uploads/2016/09/yatskar2016srv.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>64%</td><td>44</td><td>28</td><td>16</td><td>2</td><td>41</td><td>2</td></tr><tr><td>23e824d1dfc33f3780dd18076284f07bd99f1c43</td><td></td><td><a href="papers/23e824d1dfc33f3780dd18076284f07bd99f1c43.html">Spoofing faces using makeup: An investigative study</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7947686', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)</td><td>edu</td><td>INRIA Méditerranée</td><td>43.61581310</td><td>7.06838000</td><td>33%</td><td>3</td><td>1</td><td>2</td><td>0</td><td>1</td><td>2</td></tr><tr><td>1a40092b493c6b8840257ab7f96051d1a4dbfeb2</td><td></td><td><a href="papers/1a40092b493c6b8840257ab7f96051d1a4dbfeb2.html">Sports Videos in the Wild (SVW): A video dataset for sports analysis</a></td><td><a href="http://web.cse.msu.edu/~liuxm/publication/Safdarnejad_Liu_Udpa_Andrus_Wood_Craven_FG2015.pdf">[pdf]</a></td><td>2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>Michigan State University</td><td>42.71856800</td><td>-84.47791571</td><td>67%</td><td>6</td><td>4</td><td>2</td><td>1</td><td>5</td><td>0</td></tr><tr><td>4d9a02d080636e9666c4d1cc438b9893391ec6c7</td><td></td><td><a href="papers/4d9a02d080636e9666c4d1cc438b9893391ec6c7.html">The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression</a></td><td><a href="http://www.iainm.com/iainm/Publications_files/2010_The%20Extended.pdf">[pdf]</a></td><td>2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops</td><td></td><td></td><td></td><td></td><td>44%</td><td>916</td><td>403</td><td>511</td><td>51</td><td>420</td><td>361</td></tr><tr><td>96e0cfcd81cdeb8282e29ef9ec9962b125f379b0</td><td>MegaFace 2</td><td><a href="papers/96e0cfcd81cdeb8282e29ef9ec9962b125f379b0.html">The MegaFace Benchmark: 1 Million Faces for Recognition at Scale</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2016.527">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>53%</td><td>114</td><td>60</td><td>54</td><td>10</td><td>88</td><td>22</td></tr><tr><td>b5f2846a506fc417e7da43f6a7679146d99c5e96</td><td>UCF101</td><td><a href="papers/b5f2846a506fc417e7da43f6a7679146d99c5e96.html">UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1212.0402.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td>edu</td><td>University of Central Florida</td><td>28.59899755</td><td>-81.19712501</td><td>57%</td><td>934</td><td>531</td><td>400</td><td>65</td><td>658</td><td>230</td></tr><tr><td>31b05f65405534a696a847dd19c621b7b8588263</td><td></td><td><a href="papers/31b05f65405534a696a847dd19c621b7b8588263.html">UMDFaces: An annotated face dataset for training deep networks</a></td><td><a href="http://arxiv.org/abs/1611.01484">[pdf]</a></td><td>2017 IEEE International Joint Conference on Biometrics (IJCB)</td><td></td><td></td><td></td><td></td><td>48%</td><td>29</td><td>14</td><td>15</td><td>4</td><td>20</td><td>6</td></tr><tr><td>52d7eb0fbc3522434c13cc247549f74bb9609c5d</td><td>WIDER FACE</td><td><a href="papers/52d7eb0fbc3522434c13cc247549f74bb9609c5d.html">WIDER FACE: A Face Detection Benchmark</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1511.06523.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>54%</td><td>129</td><td>70</td><td>59</td><td>11</td><td>89</td><td>34</td></tr><tr><td>0b3a146c474166bba71e645452b3a8276ac05998</td><td></td><td><a href="papers/0b3a146c474166bba71e645452b3a8276ac05998.html">Whos In the Picture</a></td><td><a href="http://pdfs.semanticscholar.org/c6e5/17eb85bc6c68dff5d3fadb2d817e839c966b.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>39%</td><td>99</td><td>39</td><td>60</td><td>6</td><td>65</td><td>23</td></tr></table></body></html>
\ No newline at end of file +<!doctype html><html><head><meta charset='utf-8'><title>All Papers</title><link rel='stylesheet' href='reports.css'></head><body><h2>All Papers</h2><table border='1' cellpadding='3' cellspacing='3'><th>Paper ID</th><th>Megapixels Key</th><th>Megapixels Name</th><th>Report Link</th><th>PDF Link</th><th>Journal</th><th>Type</th><th>Address</th><th>Lat</th><th>Lng</th><th>Coverage</th><th>Total Citations</th><th>Geocoded Citations</th><th>Unknown Citations</th><th>Empty Citations</th><th>With PDF</th><th>With DOI</th><tr><td>fb82681ac5d3487bd8e52dbb3d1fa220eeac855e</td><td>pilot_parliament</td><td>PPB</td><td><a href="papers/fb82681ac5d3487bd8e52dbb3d1fa220eeac855e.html">1 Network Notebook</a></td><td><a href="http://pdfs.semanticscholar.org/fb82/681ac5d3487bd8e52dbb3d1fa220eeac855e.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>9%</td><td>11</td><td>1</td><td>10</td><td>1</td><td>10</td><td>0</td></tr><tr><td>3325860c0c82a93b2eac654f5324dd6a776f609e</td><td>mpii_human_pose</td><td>MPII Human Pose</td><td><a href="papers/3325860c0c82a93b2eac654f5324dd6a776f609e.html">2D Human Pose Estimation: New Benchmark and State of the Art Analysis</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6909866', 'linkType': 'ieee'}">[pdf]</a></td><td>2014 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>50%</td><td>356</td><td>179</td><td>177</td><td>21</td><td>299</td><td>3</td></tr><tr><td>2f5d44dc3e1b5955942133ff872ebd31716ec604</td><td>frav3d</td><td>FRAV3D</td><td><a href="papers/2f5d44dc3e1b5955942133ff872ebd31716ec604.html">2D and 3D face recognition: A survey</a></td><td><a href="http://pdfs.semanticscholar.org/2f5d/44dc3e1b5955942133ff872ebd31716ec604.pdf">[pdf]</a></td><td>Pattern Recognition Letters</td><td></td><td></td><td></td><td></td><td>15%</td><td>389</td><td>57</td><td>332</td><td>28</td><td>198</td><td>17</td></tr><tr><td>e4754afaa15b1b53e70743880484b8d0736990ff</td><td>fiw_300</td><td>300-W</td><td><a href="papers/e4754afaa15b1b53e70743880484b8d0736990ff.html">300 Faces In-The-Wild Challenge: database and results</a></td><td><a href="{'url': 'http://doi.org/10.1016/j.imavis.2016.01.002', 'linkType': 'doi'}">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>45%</td><td>114</td><td>51</td><td>63</td><td>10</td><td>70</td><td>31</td></tr><tr><td>e4754afaa15b1b53e70743880484b8d0736990ff</td><td>fiw_300</td><td>300-W</td><td><a href="papers/e4754afaa15b1b53e70743880484b8d0736990ff.html">300 Faces In-The-Wild Challenge: database and results</a></td><td><a href="{'url': 'http://doi.org/10.1016/j.imavis.2016.01.002', 'linkType': 'doi'}">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>45%</td><td>114</td><td>51</td><td>63</td><td>10</td><td>70</td><td>31</td></tr><tr><td>e4754afaa15b1b53e70743880484b8d0736990ff</td><td>fiw_300</td><td>300-W</td><td><a href="papers/e4754afaa15b1b53e70743880484b8d0736990ff.html">300 Faces In-The-Wild Challenge: database and results</a></td><td><a href="{'url': 'http://doi.org/10.1016/j.imavis.2016.01.002', 'linkType': 'doi'}">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>45%</td><td>114</td><td>51</td><td>63</td><td>10</td><td>70</td><td>31</td></tr><tr><td>2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e</td><td>3dpes</td><td>3DPeS</td><td><a href="papers/2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e.html">3DPeS: 3D people dataset for surveillance and forensics</a></td><td><a href="http://doi.acm.org/10.1145/2072572.2072590">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>18%</td><td>122</td><td>22</td><td>100</td><td>11</td><td>71</td><td>1</td></tr><tr><td>9696ad8b164f5e10fcfe23aacf74bd6168aebb15</td><td>4dfab</td><td>4DFAB</td><td><a href="papers/9696ad8b164f5e10fcfe23aacf74bd6168aebb15.html">4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1712.01443.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>0%</td><td>4</td><td>0</td><td>4</td><td>0</td><td>2</td><td>0</td></tr><tr><td>d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae</td><td>b3d_ac</td><td>B3D(AC)</td><td><a href="papers/d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae.html">A 3-D Audio-Visual Corpus of Affective Communication</a></td><td><a href="http://files.is.tue.mpg.de/jgall/download/jgall_avcorpus_mm10.pdf">[pdf]</a></td><td>IEEE Transactions on Multimedia</td><td></td><td></td><td></td><td></td><td>31%</td><td>39</td><td>12</td><td>27</td><td>2</td><td>27</td><td>7</td></tr><tr><td>639937b3a1b8bded3f7e9a40e85bd3770016cf3c</td><td>bfm</td><td>BFM</td><td><a href="papers/639937b3a1b8bded3f7e9a40e85bd3770016cf3c.html">A 3D Face Model for Pose and Illumination Invariant Face Recognition</a></td><td><a href="https://pdfs.semanticscholar.org/6399/37b3a1b8bded3f7e9a40e85bd3770016cf3c.pdf">[pdf]</a></td><td>2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance</td><td></td><td></td><td></td><td></td><td>41%</td><td>323</td><td>131</td><td>192</td><td>29</td><td>221</td><td>25</td></tr><tr><td>c34532fe6bfbd1e6df477c9ffdbb043b77e7804d</td><td>columbia_gaze</td><td>Columbia Gaze</td><td><a href="papers/c34532fe6bfbd1e6df477c9ffdbb043b77e7804d.html">A 3D Morphable Eye Region Model for Gaze Estimation</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/0d43/3b9435b874a1eea6d7999e86986c910fa285.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td>edu</td><td>Carnegie Mellon University</td><td>37.41021930</td><td>-122.05965487</td><td>67%</td><td>24</td><td>16</td><td>8</td><td>0</td><td>18</td><td>4</td></tr><tr><td>cc589c499dcf323fe4a143bbef0074c3e31f9b60</td><td>bu_3dfe</td><td>BU-3DFE</td><td><a href="papers/cc589c499dcf323fe4a143bbef0074c3e31f9b60.html">A 3D facial expression database for facial behavior research</a></td><td><a href="http://www.cs.binghamton.edu/~lijun/Research/3DFE/Yin_FGR06_a.pdf">[pdf]</a></td><td>7th International Conference on Automatic Face and Gesture Recognition (FGR06)</td><td>edu</td><td>SUNY Binghamton</td><td>42.08779975</td><td>-75.97066066</td><td>24%</td><td>555</td><td>131</td><td>424</td><td>47</td><td>283</td><td>48</td></tr><tr><td>22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b</td><td>saivt</td><td>SAIVT SoftBio</td><td><a href="papers/22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b.html">A Database for Person Re-Identification in Multi-Camera Surveillance Networks</a></td><td><a href="http://eprints.qut.edu.au/53437/3/Bialkowski_Database4PersonReID_DICTA.pdf">[pdf]</a></td><td>2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)</td><td></td><td></td><td></td><td></td><td>21%</td><td>58</td><td>12</td><td>46</td><td>7</td><td>40</td><td>1</td></tr><tr><td>070de852bc6eb275d7ca3a9cdde8f6be8795d1a3</td><td>d3dfacs</td><td>D3DFACS</td><td><a href="papers/070de852bc6eb275d7ca3a9cdde8f6be8795d1a3.html">A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling</a></td><td><a href="http://www.cs.bath.ac.uk/~dpc/D3DFACS/ICCV_final_2011.pdf">[pdf]</a></td><td>2011 International Conference on Computer Vision</td><td>edu</td><td>Jacobs University</td><td>53.41291480</td><td>-2.96897915</td><td>44%</td><td>52</td><td>23</td><td>29</td><td>5</td><td>37</td><td>4</td></tr><tr><td>e3e44385a71a52fd483c58eb3cdf8d03960c0b70</td><td>mcgill</td><td>McGill Real World</td><td><a href="papers/e3e44385a71a52fd483c58eb3cdf8d03960c0b70.html">A Hierarchical Graphical Model for Recognizing Human Actions and Interactions in Video</a></td><td><a href="http://pdfs.semanticscholar.org/e3e4/4385a71a52fd483c58eb3cdf8d03960c0b70.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>50%</td><td>2</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>e3e44385a71a52fd483c58eb3cdf8d03960c0b70</td><td>mcgill</td><td>McGill Real World</td><td><a href="papers/e3e44385a71a52fd483c58eb3cdf8d03960c0b70.html">A Hierarchical Graphical Model for Recognizing Human Actions and Interactions in Video</a></td><td><a href="http://pdfs.semanticscholar.org/e3e4/4385a71a52fd483c58eb3cdf8d03960c0b70.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>50%</td><td>2</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>563c940054e4b456661762c1ab858e6f730c3159</td><td>data_61</td><td>Data61 Pedestrian</td><td><a href="papers/563c940054e4b456661762c1ab858e6f730c3159.html">A Multi-modal Graphical Model for Scene Analysis</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/WACV.2015.139">[pdf]</a></td><td>2015 IEEE Winter Conference on Applications of Computer Vision</td><td></td><td></td><td></td><td></td><td>12%</td><td>8</td><td>1</td><td>7</td><td>0</td><td>5</td><td>0</td></tr><tr><td>221c18238b829c12b911706947ab38fd017acef7</td><td>rap_pedestrian</td><td>RAP</td><td><a href="papers/221c18238b829c12b911706947ab38fd017acef7.html">A Richly Annotated Dataset for Pedestrian Attribute Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/221c/18238b829c12b911706947ab38fd017acef7.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>52%</td><td>21</td><td>11</td><td>10</td><td>0</td><td>18</td><td>0</td></tr><tr><td>3b4ec8af470948a72a6ed37a9fd226719a874ebc</td><td>sdu_vid</td><td>SDU-VID</td><td><a href="papers/3b4ec8af470948a72a6ed37a9fd226719a874ebc.html">A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.434">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>32%</td><td>85</td><td>27</td><td>58</td><td>9</td><td>51</td><td>0</td></tr><tr><td>3b4ec8af470948a72a6ed37a9fd226719a874ebc</td><td>sdu_vid</td><td>SDU-VID</td><td><a href="papers/3b4ec8af470948a72a6ed37a9fd226719a874ebc.html">A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.434">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>32%</td><td>85</td><td>27</td><td>58</td><td>9</td><td>51</td><td>0</td></tr><tr><td>3b4ec8af470948a72a6ed37a9fd226719a874ebc</td><td>sdu_vid</td><td>SDU-VID</td><td><a href="papers/3b4ec8af470948a72a6ed37a9fd226719a874ebc.html">A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.434">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>32%</td><td>85</td><td>27</td><td>58</td><td>9</td><td>51</td><td>0</td></tr><tr><td>ad62c6e17bc39b4dec20d32f6ac667ae42d2c118</td><td>jiku_mobile</td><td>Jiku Mobile Video Dataset</td><td><a href="papers/ad62c6e17bc39b4dec20d32f6ac667ae42d2c118.html">A Synchronization Ground Truth for the Jiku Mobile Video Dataset</a></td><td><a href="http://pdfs.semanticscholar.org/ad62/c6e17bc39b4dec20d32f6ac667ae42d2c118.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>6403117f9c005ae81f1e8e6d1302f4a045e3d99d</td><td>alert_airport</td><td>ALERT Airport</td><td><a href="papers/6403117f9c005ae81f1e8e6d1302f4a045e3d99d.html">A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1605.09653.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>IEEE transactions on pattern analysis and machine intelligence</td><td></td><td></td><td></td><td></td><td>27%</td><td>15</td><td>4</td><td>11</td><td>1</td><td>10</td><td>0</td></tr><tr><td>7ace44190729927e5cb0dd5d363fcae966fe13f7</td><td>nudedetection</td><td>Nude Detection</td><td><a href="papers/7ace44190729927e5cb0dd5d363fcae966fe13f7.html">A bag-of-features approach based on Hue-SIFT descriptor for nude detection</a></td><td><a href="http://ieeexplore.ieee.org/document/7077625/">[pdf]</a></td><td>2009 17th European Signal Processing Conference</td><td></td><td></td><td></td><td></td><td>18%</td><td>51</td><td>9</td><td>42</td><td>1</td><td>18</td><td>0</td></tr><tr><td>0d3bb75852098b25d90f31d2f48fd0cb4944702b</td><td>face_scrub</td><td>FaceScrub</td><td><a href="papers/0d3bb75852098b25d90f31d2f48fd0cb4944702b.html">A data-driven approach to cleaning large face datasets</a></td><td><a href="https://doi.org/10.1109/ICIP.2014.7025068">[pdf]</a></td><td>2014 IEEE International Conference on Image Processing (ICIP)</td><td>edu</td><td>University of Illinois, Urbana-Champaign</td><td>40.11116745</td><td>-88.22587665</td><td>46%</td><td>123</td><td>56</td><td>67</td><td>6</td><td>95</td><td>21</td></tr><tr><td>b91f54e1581fbbf60392364323d00a0cd43e493c</td><td>bp4d_spontanous</td><td>BP4D-Spontanous</td><td><a href="papers/b91f54e1581fbbf60392364323d00a0cd43e493c.html">A high-resolution spontaneous 3D dynamic facial expression database</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6553788', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>SUNY Binghamton</td><td>42.08779975</td><td>-75.97066066</td><td>36%</td><td>151</td><td>54</td><td>97</td><td>7</td><td>85</td><td>26</td></tr><tr><td>1ed1a49534ad8dd00f81939449f6389cfbc25321</td><td>bjut_3d</td><td>BJUT-3D</td><td><a href="papers/1ed1a49534ad8dd00f81939449f6389cfbc25321.html">A novel face recognition method based on 3D face model</a></td><td><a href="https://doi.org/10.1109/ROBIO.2007.4522202">[pdf]</a></td><td>2007 IEEE International Conference on Robotics and Biomimetics (ROBIO)</td><td></td><td></td><td></td><td></td><td>0%</td><td>2</td><td>0</td><td>2</td><td>0</td><td>1</td><td>1</td></tr><tr><td>2624d84503bc2f8e190e061c5480b6aa4d89277a</td><td>afew_va</td><td>AFEW-VA</td><td><a href="papers/2624d84503bc2f8e190e061c5480b6aa4d89277a.html">AFEW-VA database for valence and arousal estimation in-the-wild</a></td><td><a href="http://pdfs.semanticscholar.org/2624/d84503bc2f8e190e061c5480b6aa4d89277a.pdf">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>47%</td><td>15</td><td>7</td><td>8</td><td>1</td><td>10</td><td>3</td></tr><tr><td>2624d84503bc2f8e190e061c5480b6aa4d89277a</td><td>afew_va</td><td>AFEW-VA</td><td><a href="papers/2624d84503bc2f8e190e061c5480b6aa4d89277a.html">AFEW-VA database for valence and arousal estimation in-the-wild</a></td><td><a href="http://pdfs.semanticscholar.org/2624/d84503bc2f8e190e061c5480b6aa4d89277a.pdf">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>47%</td><td>15</td><td>7</td><td>8</td><td>1</td><td>10</td><td>3</td></tr><tr><td>2ad0ee93d029e790ebb50574f403a09854b65b7e</td><td>yale_faces</td><td>YaleFaces</td><td><a href="papers/2ad0ee93d029e790ebb50574f403a09854b65b7e.html">Acquiring linear subspaces for face recognition under variable lighting</a></td><td><a href="http://vision.cornell.edu/se3/wp-content/uploads/2014/09/pami05.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>25%</td><td>999</td><td>251</td><td>748</td><td>110</td><td>509</td><td>113</td></tr><tr><td>2ad0ee93d029e790ebb50574f403a09854b65b7e</td><td>yale_faces</td><td>YaleFaces</td><td><a href="papers/2ad0ee93d029e790ebb50574f403a09854b65b7e.html">Acquiring linear subspaces for face recognition under variable lighting</a></td><td><a href="http://vision.cornell.edu/se3/wp-content/uploads/2014/09/pami05.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>25%</td><td>999</td><td>251</td><td>748</td><td>110</td><td>509</td><td>113</td></tr><tr><td>57fe081950f21ca03b5b375ae3e84b399c015861</td><td>cvc_01_barcelona</td><td>CVC-01</td><td><a href="papers/57fe081950f21ca03b5b375ae3e84b399c015861.html">Adaptive Image Sampling and Windows Classification for On–board Pedestrian Detection</a></td><td><a href="http://pdfs.semanticscholar.org/57fe/081950f21ca03b5b375ae3e84b399c015861.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>9%</td><td>44</td><td>4</td><td>40</td><td>1</td><td>21</td><td>0</td></tr><tr><td>47aeb3b82f54b5ae8142b4bdda7b614433e69b9a</td><td>am_fed</td><td>AM-FED</td><td><a href="papers/47aeb3b82f54b5ae8142b4bdda7b614433e69b9a.html">Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"</a></td><td><a href="http://pdfs.semanticscholar.org/5d06/437656dd94616d7d87260d5eb77513ded30f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>36%</td><td>73</td><td>26</td><td>47</td><td>6</td><td>39</td><td>16</td></tr><tr><td>1be498d4bbc30c3bfd0029114c784bc2114d67c0</td><td>adience</td><td>Adience</td><td><a href="papers/1be498d4bbc30c3bfd0029114c784bc2114d67c0.html">Age and Gender Estimation of Unfiltered Faces</a></td><td><a href="http://www.openu.ac.il/home/hassner/Adience/EidingerEnbarHassner_tifs.pdf">[pdf]</a></td><td>IEEE Transactions on Information Forensics and Security</td><td></td><td></td><td></td><td></td><td>43%</td><td>168</td><td>72</td><td>96</td><td>7</td><td>89</td><td>53</td></tr><tr><td>6dcf418c778f528b5792104760f1fbfe90c6dd6a</td><td>agedb</td><td>AgeDB</td><td><a href="papers/6dcf418c778f528b5792104760f1fbfe90c6dd6a.html">AgeDB: The First Manually Collected, In-the-Wild Age Database</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8014984', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>82%</td><td>11</td><td>9</td><td>2</td><td>0</td><td>10</td><td>0</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td>aflw</td><td>AFLW</td><td><a href="papers/a74251efa970b92925b89eeef50a5e37d9281ad0.html">Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization</a></td><td><a href="http://lrs.icg.tugraz.at/pubs/koestinger_befit_11.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>53%</td><td>292</td><td>155</td><td>137</td><td>38</td><td>207</td><td>59</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td>imm_face</td><td>IMM Face Dataset</td><td><a href="papers/a74251efa970b92925b89eeef50a5e37d9281ad0.html">Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization</a></td><td><a href="http://lrs.icg.tugraz.at/pubs/koestinger_befit_11.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>53%</td><td>292</td><td>155</td><td>137</td><td>38</td><td>207</td><td>59</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td>muct</td><td>MUCT</td><td><a href="papers/a74251efa970b92925b89eeef50a5e37d9281ad0.html">Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization</a></td><td><a href="http://lrs.icg.tugraz.at/pubs/koestinger_befit_11.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>53%</td><td>292</td><td>155</td><td>137</td><td>38</td><td>207</td><td>59</td></tr><tr><td>c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8</td><td>face_research_lab</td><td>Face Research Lab London</td><td><a href="papers/c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8.html">Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.</a></td><td><a href="http://pdfs.semanticscholar.org/c652/6dd3060d63a6c90e8b7ff340383c4e0e0dd8.pdf">[pdf]</a></td><td>Scientific reports</td><td>edu</td><td>University College London</td><td>51.52316070</td><td>-0.12820370</td><td>25%</td><td>4</td><td>1</td><td>3</td><td>0</td><td>2</td><td>2</td></tr><tr><td>0df0d1adea39a5bef318b74faa37de7f3e00b452</td><td>mpii_gaze</td><td>MPIIGaze</td><td><a href="papers/0df0d1adea39a5bef318b74faa37de7f3e00b452.html">Appearance-based gaze estimation in the wild</a></td><td><a href="https://scalable.mpi-inf.mpg.de/files/2015/09/zhang_CVPR15.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Max Planck Institute for Informatics</td><td>49.25795660</td><td>7.04577417</td><td>38%</td><td>138</td><td>52</td><td>86</td><td>3</td><td>94</td><td>7</td></tr><tr><td>5801690199c1917fa58c35c3dead177c0b8f9f2d</td><td>camel</td><td>CAMEL</td><td><a href="papers/5801690199c1917fa58c35c3dead177c0b8f9f2d.html">Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis</a></td><td><a href="http://pdfs.semanticscholar.org/5801/690199c1917fa58c35c3dead177c0b8f9f2d.pdf">[pdf]</a></td><td>Remote Sensing</td><td></td><td></td><td></td><td></td><td>37%</td><td>19</td><td>7</td><td>12</td><td>1</td><td>16</td><td>0</td></tr><tr><td>759a3b3821d9f0e08e0b0a62c8b693230afc3f8d</td><td>pubfig</td><td>PubFig</td><td><a href="papers/759a3b3821d9f0e08e0b0a62c8b693230afc3f8d.html">Attribute and simile classifiers for face verification</a></td><td><a href="http://homes.cs.washington.edu/~neeraj/projects/faceverification/base/papers/nk_iccv2009_attrs.pdf">[pdf]</a></td><td>2009 IEEE 12th International Conference on Computer Vision</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>51%</td><td>894</td><td>454</td><td>440</td><td>55</td><td>587</td><td>222</td></tr><tr><td>faf40ce28857aedf183e193486f5b4b0a8c478a2</td><td>iit_dehli_ear</td><td>IIT Dehli Ear</td><td><a href="papers/faf40ce28857aedf183e193486f5b4b0a8c478a2.html">Automated Human Identification Using Ear Imaging</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/faf4/0ce28857aedf183e193486f5b4b0a8c478a2.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>13%</td><td>70</td><td>9</td><td>61</td><td>6</td><td>28</td><td>1</td></tr><tr><td>2160788824c4c29ffe213b2cbeb3f52972d73f37</td><td>3d_rma</td><td>3D-RMA</td><td><a href="papers/2160788824c4c29ffe213b2cbeb3f52972d73f37.html">Automatic 3D face authentication</a></td><td><a href="http://pdfs.semanticscholar.org/2160/788824c4c29ffe213b2cbeb3f52972d73f37.pdf">[pdf]</a></td><td>Image Vision Comput.</td><td></td><td></td><td></td><td></td><td>25%</td><td>95</td><td>24</td><td>71</td><td>8</td><td>60</td><td>2</td></tr><tr><td>213a579af9e4f57f071b884aa872651372b661fd</td><td>bbc_pose</td><td>BBC Pose</td><td><a href="papers/213a579af9e4f57f071b884aa872651372b661fd.html">Automatic and Efficient Human Pose Estimation for Sign Language Videos</a></td><td><a href="https://doi.org/10.1007/s11263-013-0672-6">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>60%</td><td>25</td><td>15</td><td>10</td><td>1</td><td>18</td><td>1</td></tr><tr><td>fcc6fe6007c322641796cb8792718641856a22a7</td><td>miw</td><td>MIW</td><td><a href="papers/fcc6fe6007c322641796cb8792718641856a22a7.html">Automatic facial makeup detection with application in face recognition</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6612994', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 International Conference on Biometrics (ICB)</td><td>edu</td><td>West Virginia University</td><td>39.65404635</td><td>-79.96475355</td><td>65%</td><td>46</td><td>30</td><td>16</td><td>1</td><td>18</td><td>21</td></tr><tr><td>0a85bdff552615643dd74646ac881862a7c7072d</td><td>pipa</td><td>PIPA</td><td><a href="papers/0a85bdff552615643dd74646ac881862a7c7072d.html">Beyond frontal faces: Improving Person Recognition using multiple cues</a></td><td><a href="https://doi.org/10.1109/CVPR.2015.7299113">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>60%</td><td>50</td><td>30</td><td>19</td><td>2</td><td>40</td><td>4</td></tr><tr><td>2acf7e58f0a526b957be2099c10aab693f795973</td><td>bosphorus</td><td>The Bosphorus</td><td><a href="papers/2acf7e58f0a526b957be2099c10aab693f795973.html">Bosphorus Database for 3D Face Analysis</a></td><td><a href="http://pdfs.semanticscholar.org/4254/fbba3846008f50671edc9cf70b99d7304543.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>18%</td><td>328</td><td>58</td><td>270</td><td>18</td><td>143</td><td>37</td></tr><tr><td>214c966d1f9c2a4b66f4535d9a0d4078e63a5867</td><td>brainwash</td><td>Brainwash</td><td><a href="papers/214c966d1f9c2a4b66f4535d9a0d4078e63a5867.html">Brainwash: A Data System for Feature Engineering</a></td><td><a href="http://pdfs.semanticscholar.org/ae44/8015b2ff2bd3b8a5c9a3266f954f5af9ffa9.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>60%</td><td>57</td><td>34</td><td>23</td><td>2</td><td>50</td><td>0</td></tr><tr><td>37d6f0eb074d207b53885bd2eb78ccc8a04be597</td><td>vmu</td><td>VMU</td><td><a href="papers/37d6f0eb074d207b53885bd2eb78ccc8a04be597.html">Can facial cosmetics affect the matching accuracy of face recognition systems?</a></td><td><a href="http://www.cse.msu.edu/~climer/DantchevaChenRossFaceCosmetics_BTAS2012.pdf">[pdf]</a></td><td>2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td></td><td></td><td></td><td></td><td>49%</td><td>49</td><td>24</td><td>25</td><td>0</td><td>18</td><td>22</td></tr><tr><td>37d6f0eb074d207b53885bd2eb78ccc8a04be597</td><td>youtube_makeup</td><td>YMU</td><td><a href="papers/37d6f0eb074d207b53885bd2eb78ccc8a04be597.html">Can facial cosmetics affect the matching accuracy of face recognition systems?</a></td><td><a href="http://www.cse.msu.edu/~climer/DantchevaChenRossFaceCosmetics_BTAS2012.pdf">[pdf]</a></td><td>2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td></td><td></td><td></td><td></td><td>49%</td><td>49</td><td>24</td><td>25</td><td>0</td><td>18</td><td>22</td></tr><tr><td>37d6f0eb074d207b53885bd2eb78ccc8a04be597</td><td>youtube_makeup</td><td>YMU</td><td><a href="papers/37d6f0eb074d207b53885bd2eb78ccc8a04be597.html">Can facial cosmetics affect the matching accuracy of face recognition systems?</a></td><td><a href="http://www.cse.msu.edu/~climer/DantchevaChenRossFaceCosmetics_BTAS2012.pdf">[pdf]</a></td><td>2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td></td><td></td><td></td><td></td><td>49%</td><td>49</td><td>24</td><td>25</td><td>0</td><td>18</td><td>22</td></tr><tr><td>8d5998cd984e7cce307da7d46f155f9db99c6590</td><td>chalearn</td><td>ChaLearn</td><td><a href="papers/8d5998cd984e7cce307da7d46f155f9db99c6590.html">ChaLearn looking at people: A review of events and resources</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1701.02664.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2017 International Joint Conference on Neural Networks (IJCNN)</td><td></td><td></td><td></td><td></td><td>30%</td><td>10</td><td>3</td><td>7</td><td>1</td><td>6</td><td>0</td></tr><tr><td>2bf8541199728262f78d4dced6fb91479b39b738</td><td>clothing_co_parsing</td><td>CCP</td><td><a href="papers/2bf8541199728262f78d4dced6fb91479b39b738.html">Clothing Co-parsing by Joint Image Segmentation and Labeling</a></td><td><a href="https://arxiv.org/pdf/1502.00739v1.pdf">[pdf]</a></td><td>2014 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>47%</td><td>60</td><td>28</td><td>32</td><td>0</td><td>36</td><td>6</td></tr><tr><td>6dbe8e5121c534339d6e41f8683e85f87e6abf81</td><td>gallagher</td><td>Gallagher</td><td><a href="papers/6dbe8e5121c534339d6e41f8683e85f87e6abf81.html">Clothing Cosegmentation for Shopping Images With Cluttered Background</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7423747', 'linkType': 'ieee'}">[pdf]</a></td><td>IEEE Transactions on Multimedia</td><td></td><td></td><td></td><td></td><td>33%</td><td>6</td><td>2</td><td>4</td><td>0</td><td>3</td><td>2</td></tr><tr><td>4b1d23d17476fcf78f4cbadf69fb130b1aa627c0</td><td>leeds_sports_pose</td><td>Leeds Sports Pose</td><td><a href="papers/4b1d23d17476fcf78f4cbadf69fb130b1aa627c0.html">Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation</a></td><td><a href="http://pdfs.semanticscholar.org/4b1d/23d17476fcf78f4cbadf69fb130b1aa627c0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>278</td><td>119</td><td>159</td><td>12</td><td>198</td><td>2</td></tr><tr><td>4b1d23d17476fcf78f4cbadf69fb130b1aa627c0</td><td>stickmen_pascal</td><td>Stickmen PASCAL</td><td><a href="papers/4b1d23d17476fcf78f4cbadf69fb130b1aa627c0.html">Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation</a></td><td><a href="http://pdfs.semanticscholar.org/4b1d/23d17476fcf78f4cbadf69fb130b1aa627c0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>278</td><td>119</td><td>159</td><td>12</td><td>198</td><td>2</td></tr><tr><td>4b1d23d17476fcf78f4cbadf69fb130b1aa627c0</td><td>stickmen_pascal</td><td>Stickmen PASCAL</td><td><a href="papers/4b1d23d17476fcf78f4cbadf69fb130b1aa627c0.html">Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation</a></td><td><a href="http://pdfs.semanticscholar.org/4b1d/23d17476fcf78f4cbadf69fb130b1aa627c0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>278</td><td>119</td><td>159</td><td>12</td><td>198</td><td>2</td></tr><tr><td>45c31cde87258414f33412b3b12fc5bec7cb3ba9</td><td>jaffe</td><td>JAFFE</td><td><a href="papers/45c31cde87258414f33412b3b12fc5bec7cb3ba9.html">Coding Facial Expressions with Gabor Wavelets</a></td><td><a href="http://pdfs.semanticscholar.org/45c3/1cde87258414f33412b3b12fc5bec7cb3ba9.pdf">[pdf]</a></td><td></td><td>edu</td><td>Kyushu University</td><td>33.59914655</td><td>130.22359848</td><td>36%</td><td>848</td><td>308</td><td>540</td><td>56</td><td>413</td><td>255</td></tr><tr><td>079a0a3bf5200994e1f972b1b9197bf2f90e87d4</td><td>mit_cbcl</td><td>MIT CBCL</td><td><a href="papers/079a0a3bf5200994e1f972b1b9197bf2f90e87d4.html">Component-Based Face Recognition with 3D Morphable Models</a></td><td><a href="http://www.bheisele.com/avbpa2003.pdf">[pdf]</a></td><td>2004 Conference on Computer Vision and Pattern Recognition Workshop</td><td></td><td></td><td></td><td></td><td>0%</td><td>12</td><td>0</td><td>12</td><td>0</td><td>8</td><td>0</td></tr><tr><td>23fc83c8cfff14a16df7ca497661264fc54ed746</td><td>cohn_kanade</td><td>CK</td><td><a href="papers/23fc83c8cfff14a16df7ca497661264fc54ed746.html">Comprehensive Database for Facial Expression Analysis</a></td><td><a href="http://pdfs.semanticscholar.org/23fc/83c8cfff14a16df7ca497661264fc54ed746.pdf">[pdf]</a></td><td></td><td>edu</td><td>Carnegie Mellon University</td><td>37.41021930</td><td>-122.05965487</td><td>38%</td><td>999</td><td>380</td><td>619</td><td>75</td><td>555</td><td>252</td></tr><tr><td>09d78009687bec46e70efcf39d4612822e61cb8c</td><td>raid</td><td>RAiD</td><td><a href="papers/09d78009687bec46e70efcf39d4612822e61cb8c.html">Consistent Re-identification in a Camera Network</a></td><td><a href="http://pdfs.semanticscholar.org/c27f/099e6e7e3f7f9979cbe9e0a5175fc5848ea0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>27%</td><td>45</td><td>12</td><td>33</td><td>7</td><td>34</td><td>1</td></tr><tr><td>0ceda9dae8b9f322df65ca2ef02caca9758aec6f</td><td>casablanca</td><td>Casablanca</td><td><a href="papers/0ceda9dae8b9f322df65ca2ef02caca9758aec6f.html">Context-Aware CNNs for Person Head Detection</a></td><td><a href="http://arxiv.org/pdf/1511.07917v1.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>33%</td><td>27</td><td>9</td><td>18</td><td>1</td><td>22</td><td>0</td></tr><tr><td>0ceda9dae8b9f322df65ca2ef02caca9758aec6f</td><td>hollywood_headset</td><td>HollywoodHeads</td><td><a href="papers/0ceda9dae8b9f322df65ca2ef02caca9758aec6f.html">Context-Aware CNNs for Person Head Detection</a></td><td><a href="http://arxiv.org/pdf/1511.07917v1.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>33%</td><td>27</td><td>9</td><td>18</td><td>1</td><td>22</td><td>0</td></tr><tr><td>c06b13d0ec3f5c43e2782cd22542588e233733c3</td><td>nova_emotions</td><td>Novaemötions Dataset</td><td><a href="papers/c06b13d0ec3f5c43e2782cd22542588e233733c3.html">Crowdsourcing facial expressions for affective-interaction</a></td><td><a href="https://doi.org/10.1016/j.cviu.2016.02.001">[pdf]</a></td><td>Computer Vision and Image Understanding</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>c06b13d0ec3f5c43e2782cd22542588e233733c3</td><td>nova_emotions</td><td>Novaemötions Dataset</td><td><a href="papers/c06b13d0ec3f5c43e2782cd22542588e233733c3.html">Crowdsourcing facial expressions for affective-interaction</a></td><td><a href="https://doi.org/10.1016/j.cviu.2016.02.001">[pdf]</a></td><td>Computer Vision and Image Understanding</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>10195a163ab6348eef37213a46f60a3d87f289c5</td><td>imdb_wiki</td><td>IMDB</td><td><a href="papers/10195a163ab6348eef37213a46f60a3d87f289c5.html">Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks</a></td><td><a href="https://doi.org/10.1007/s11263-016-0940-3">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>44%</td><td>133</td><td>59</td><td>74</td><td>14</td><td>90</td><td>28</td></tr><tr><td>10195a163ab6348eef37213a46f60a3d87f289c5</td><td>imdb_wiki</td><td>IMDB</td><td><a href="papers/10195a163ab6348eef37213a46f60a3d87f289c5.html">Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks</a></td><td><a href="https://doi.org/10.1007/s11263-016-0940-3">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>44%</td><td>133</td><td>59</td><td>74</td><td>14</td><td>90</td><td>28</td></tr><tr><td>162ea969d1929ed180cc6de9f0bf116993ff6e06</td><td>vgg_faces</td><td>VGG Face</td><td><a href="papers/162ea969d1929ed180cc6de9f0bf116993ff6e06.html">Deep Face Recognition</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/f372/ab9b3270d4e4f6a0258c83c2736c3a5c0454.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>39%</td><td>999</td><td>393</td><td>606</td><td>71</td><td>621</td><td>156</td></tr><tr><td>6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4</td><td>celeba</td><td>CelebA</td><td><a href="papers/6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4.html">Deep Learning Face Attributes in the Wild</a></td><td><a href="http://arxiv.org/pdf/1411.7766v2.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>42%</td><td>808</td><td>340</td><td>468</td><td>69</td><td>666</td><td>50</td></tr><tr><td>18010284894ed0edcca74e5bf768ee2e15ef7841</td><td>deep_fashion</td><td>DeepFashion</td><td><a href="papers/18010284894ed0edcca74e5bf768ee2e15ef7841.html">DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7780493', 'linkType': 'ieee'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>47%</td><td>150</td><td>71</td><td>79</td><td>4</td><td>111</td><td>8</td></tr><tr><td>18010284894ed0edcca74e5bf768ee2e15ef7841</td><td>deep_fashion</td><td>DeepFashion</td><td><a href="papers/18010284894ed0edcca74e5bf768ee2e15ef7841.html">DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7780493', 'linkType': 'ieee'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>47%</td><td>150</td><td>71</td><td>79</td><td>4</td><td>111</td><td>8</td></tr><tr><td>6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3</td><td>cuhk03</td><td>CUHK03</td><td><a href="papers/6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3.html">DeepReID: Deep Filter Pairing Neural Network for Person Re-identification</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Li_DeepReID_Deep_Filter_2014_CVPR_paper.pdf">[pdf]</a></td><td>2014 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>35%</td><td>512</td><td>180</td><td>332</td><td>29</td><td>323</td><td>4</td></tr><tr><td>13f06b08f371ba8b5d31c3e288b4deb61335b462</td><td>eth_andreas_ess</td><td>ETHZ Pedestrian</td><td><a href="papers/13f06b08f371ba8b5d31c3e288b4deb61335b462.html">Depth and Appearance for Mobile Scene Analysis</a></td><td><a href="http://www.mmp.rwth-aachen.de/publications/pdf/ess-depthandappearance-iccv07.pdf/at_download/file">[pdf]</a></td><td>2007 IEEE 11th International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>25%</td><td>319</td><td>79</td><td>240</td><td>27</td><td>192</td><td>0</td></tr><tr><td>2e384f057211426ac5922f1b33d2aa8df5d51f57</td><td>a_pascal_yahoo</td><td>aPascal</td><td><a href="papers/2e384f057211426ac5922f1b33d2aa8df5d51f57.html">Describing objects by their attributes</a></td><td><a href="http://www-2.cs.cmu.edu/~dhoiem/publications/cvpr2009_attributes.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>39%</td><td>999</td><td>393</td><td>606</td><td>71</td><td>727</td><td>73</td></tr><tr><td>7808937b46acad36e43c30ae4e9f3fd57462853d</td><td>berkeley_pose</td><td>BPAD</td><td><a href="papers/7808937b46acad36e43c30ae4e9f3fd57462853d.html">Describing people: A poselet-based approach to attribute classification</a></td><td><a href="http://ttic.uchicago.edu/~smaji/papers/attributes-iccv11.pdf">[pdf]</a></td><td>2011 International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>43%</td><td>221</td><td>96</td><td>125</td><td>14</td><td>160</td><td>23</td></tr><tr><td>56ae6d94fc6097ec4ca861f0daa87941d1c10b70</td><td>cmdp</td><td>CMDP</td><td><a href="papers/56ae6d94fc6097ec4ca861f0daa87941d1c10b70.html">Distance Estimation of an Unknown Person from a Portrait</a></td><td><a href="http://pdfs.semanticscholar.org/56ae/6d94fc6097ec4ca861f0daa87941d1c10b70.pdf">[pdf]</a></td><td></td><td>edu</td><td>California Institute of Technology</td><td>34.13710185</td><td>-118.12527487</td><td>22%</td><td>9</td><td>2</td><td>7</td><td>0</td><td>6</td><td>1</td></tr><tr><td>84fe5b4ac805af63206012d29523a1e033bc827e</td><td>awe_ears</td><td>AWE Ears</td><td><a href="papers/84fe5b4ac805af63206012d29523a1e033bc827e.html">Ear recognition: More than a survey</a></td><td><a href="http://pdfs.semanticscholar.org/84fe/5b4ac805af63206012d29523a1e033bc827e.pdf">[pdf]</a></td><td>Neurocomputing</td><td></td><td></td><td></td><td></td><td>29%</td><td>24</td><td>7</td><td>17</td><td>0</td><td>11</td><td>0</td></tr><tr><td>133f01aec1534604d184d56de866a4bd531dac87</td><td>lfw_a</td><td>LFW-a</td><td><a href="papers/133f01aec1534604d184d56de866a4bd531dac87.html">Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.230">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>42%</td><td>177</td><td>75</td><td>102</td><td>15</td><td>102</td><td>54</td></tr><tr><td>c900e0ad4c95948baaf0acd8449fde26f9b4952a</td><td>emotio_net</td><td>EmotioNet Database</td><td><a href="papers/c900e0ad4c95948baaf0acd8449fde26f9b4952a.html">EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7780969', 'linkType': 'ieee'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>44%</td><td>72</td><td>32</td><td>40</td><td>7</td><td>54</td><td>8</td></tr><tr><td>2161f6b7ee3c0acc81603b01dc0df689683577b9</td><td>large_scale_person_search</td><td>Large Scale Person Search</td><td><a href="papers/2161f6b7ee3c0acc81603b01dc0df689683577b9.html">End-to-End Deep Learning for Person Search</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/2161/f6b7ee3c0acc81603b01dc0df689683577b9.pdf', 'linkType': 's2'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>34%</td><td>41</td><td>14</td><td>27</td><td>2</td><td>27</td><td>0</td></tr><tr><td>6273b3491e94ea4dd1ce42b791d77bdc96ee73a8</td><td>viper</td><td>VIPeR</td><td><a href="papers/6273b3491e94ea4dd1ce42b791d77bdc96ee73a8.html">Evaluating Appearance Models for Recognition, Reacquisition, and Tracking</a></td><td><a href="http://pdfs.semanticscholar.org/6273/b3491e94ea4dd1ce42b791d77bdc96ee73a8.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>27%</td><td>584</td><td>159</td><td>425</td><td>38</td><td>336</td><td>9</td></tr><tr><td>2258e01865367018ed6f4262c880df85b94959f8</td><td>mot</td><td>MOT</td><td><a href="papers/2258e01865367018ed6f4262c880df85b94959f8.html">Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics</a></td><td><a href="http://pdfs.semanticscholar.org/2e0b/00f4043e2d4b04c59c88bb54bcd907d0dcd4.pdf">[pdf]</a></td><td>EURASIP J. Image and Video Processing</td><td></td><td></td><td></td><td></td><td>20%</td><td>586</td><td>119</td><td>467</td><td>48</td><td>336</td><td>3</td></tr><tr><td>2258e01865367018ed6f4262c880df85b94959f8</td><td>mot</td><td>MOT</td><td><a href="papers/2258e01865367018ed6f4262c880df85b94959f8.html">Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics</a></td><td><a href="http://pdfs.semanticscholar.org/2e0b/00f4043e2d4b04c59c88bb54bcd907d0dcd4.pdf">[pdf]</a></td><td>EURASIP J. Image and Video Processing</td><td></td><td></td><td></td><td></td><td>20%</td><td>586</td><td>119</td><td>467</td><td>48</td><td>336</td><td>3</td></tr><tr><td>2258e01865367018ed6f4262c880df85b94959f8</td><td>mot</td><td>MOT</td><td><a href="papers/2258e01865367018ed6f4262c880df85b94959f8.html">Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics</a></td><td><a href="http://pdfs.semanticscholar.org/2e0b/00f4043e2d4b04c59c88bb54bcd907d0dcd4.pdf">[pdf]</a></td><td>EURASIP J. Image and Video Processing</td><td></td><td></td><td></td><td></td><td>20%</td><td>586</td><td>119</td><td>467</td><td>48</td><td>336</td><td>3</td></tr><tr><td>9e5378e7b336c89735d3bb15cf67eff96f86d39a</td><td>precarious</td><td>Precarious</td><td><a href="papers/9e5378e7b336c89735d3bb15cf67eff96f86d39a.html">Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1703.06283.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>8%</td><td>12</td><td>1</td><td>11</td><td>1</td><td>10</td><td>0</td></tr><tr><td>35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62</td><td>coco_qa</td><td>COCO QA</td><td><a href="papers/35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62.html">Exploring Models and Data for Image Question Answering</a></td><td><a href="http://pdfs.semanticscholar.org/aa79/9c29c0d44ece1864467af520fe70540c069b.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>191</td><td>83</td><td>108</td><td>12</td><td>163</td><td>1</td></tr><tr><td>42505464808dfb446f521fc6ff2cfeffd4d68ff1</td><td>gavab_db</td><td>Gavab</td><td><a href="papers/42505464808dfb446f521fc6ff2cfeffd4d68ff1.html">Expression invariant 3D face recognition with a Morphable Model</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4813376', 'linkType': 'ieee'}">[pdf]</a></td><td>2008 8th IEEE International Conference on Automatic Face & Gesture Recognition</td><td></td><td></td><td></td><td></td><td>29%</td><td>94</td><td>27</td><td>67</td><td>10</td><td>57</td><td>5</td></tr><tr><td>a5acda0e8c0937bfed013e6382da127103e41395</td><td>disfa</td><td>DISFA</td><td><a href="papers/a5acda0e8c0937bfed013e6382da127103e41395.html">Extended DISFA Dataset: Investigating Posed and Spontaneous Facial Expressions</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7789672', 'linkType': 'ieee'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>38%</td><td>8</td><td>3</td><td>5</td><td>1</td><td>5</td><td>0</td></tr><tr><td>75da1df4ed319926c544eefe17ec8d720feef8c0</td><td>fddb</td><td>FDDB</td><td><a href="papers/75da1df4ed319926c544eefe17ec8d720feef8c0.html">FDDB: A Benchmark for Face Detection in Unconstrained Settings</a></td><td><a href="http://pdfs.semanticscholar.org/75da/1df4ed319926c544eefe17ec8d720feef8c0.pdf">[pdf]</a></td><td></td><td>edu</td><td>University of Massachusetts</td><td>42.38897850</td><td>-72.52869870</td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>3607afdb204de9a5a9300ae98aa4635d9effcda2</td><td>sheffield</td><td>Sheffield Face</td><td><a href="papers/3607afdb204de9a5a9300ae98aa4635d9effcda2.html">Face Description with Local Binary Patterns: Application to Face Recognition</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.244">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>24%</td><td>999</td><td>238</td><td>761</td><td>65</td><td>483</td><td>87</td></tr><tr><td>0e986f51fe45b00633de9fd0c94d082d2be51406</td><td>afw</td><td>AFW</td><td><a href="papers/0e986f51fe45b00633de9fd0c94d082d2be51406.html">Face detection, pose estimation, and landmark localization in the wild</a></td><td><a href="http://vision.ics.uci.edu/papers/ZhuR_CVPR_2012/ZhuR_CVPR_2012.pdf">[pdf]</a></td><td>2012 IEEE Conference on Computer Vision and Pattern Recognition</td><td>edu</td><td>University of California, Irvine</td><td>33.64319010</td><td>-117.84016494</td><td>52%</td><td>999</td><td>521</td><td>478</td><td>59</td><td>607</td><td>273</td></tr><tr><td>560e0e58d0059259ddf86fcec1fa7975dee6a868</td><td>youtube_faces</td><td>YouTubeFaces</td><td><a href="papers/560e0e58d0059259ddf86fcec1fa7975dee6a868.html">Face recognition in unconstrained videos with matched background similarity</a></td><td><a href="http://www.cs.tau.ac.il/~wolf/papers/lvfw.pdf">[pdf]</a></td><td>CVPR 2011</td><td>edu</td><td>Open University of Israel</td><td>32.77824165</td><td>34.99565673</td><td>50%</td><td>485</td><td>244</td><td>240</td><td>32</td><td>290</td><td>140</td></tr><tr><td>4c170a0dcc8de75587dae21ca508dab2f9343974</td><td>face_tracer</td><td>FaceTracer</td><td><a href="papers/4c170a0dcc8de75587dae21ca508dab2f9343974.html">FaceTracer: A Search Engine for Large Collections of Images with Faces</a></td><td><a href="http://pdfs.semanticscholar.org/73a8/1d311eedac8dea3ca24dc15b6990fa4a725e.pdf">[pdf]</a></td><td></td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>48%</td><td>218</td><td>105</td><td>113</td><td>17</td><td>146</td><td>52</td></tr><tr><td>4c170a0dcc8de75587dae21ca508dab2f9343974</td><td>face_tracer</td><td>FaceTracer</td><td><a href="papers/4c170a0dcc8de75587dae21ca508dab2f9343974.html">FaceTracer: A Search Engine for Large Collections of Images with Faces</a></td><td><a href="http://pdfs.semanticscholar.org/73a8/1d311eedac8dea3ca24dc15b6990fa4a725e.pdf">[pdf]</a></td><td></td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>48%</td><td>218</td><td>105</td><td>113</td><td>17</td><td>146</td><td>52</td></tr><tr><td>7ebb153704706e457ab57b432793d2b6e5d12592</td><td>vgg_celebs_in_places</td><td>CIP</td><td><a href="papers/7ebb153704706e457ab57b432793d2b6e5d12592.html">Faces in Places: compound query retrieval</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/7ebb/153704706e457ab57b432793d2b6e5d12592.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td>edu</td><td>University of Oxford</td><td>51.75345380</td><td>-1.25400997</td><td>80%</td><td>5</td><td>4</td><td>1</td><td>0</td><td>4</td><td>0</td></tr><tr><td>8a3c5507237957d013a0fe0f082cab7f757af6ee</td><td>mafl</td><td>MAFL</td><td><a href="papers/8a3c5507237957d013a0fe0f082cab7f757af6ee.html">Facial Landmark Detection by Deep Multi-task Learning</a></td><td><a href="http://pdfs.semanticscholar.org/fcd7/1c18192928a2e0b264edd4d919ab2f8f652a.pdf">[pdf]</a></td><td></td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>48%</td><td>383</td><td>182</td><td>201</td><td>25</td><td>259</td><td>60</td></tr><tr><td>8a3c5507237957d013a0fe0f082cab7f757af6ee</td><td>mafl</td><td>MAFL</td><td><a href="papers/8a3c5507237957d013a0fe0f082cab7f757af6ee.html">Facial Landmark Detection by Deep Multi-task Learning</a></td><td><a href="http://pdfs.semanticscholar.org/fcd7/1c18192928a2e0b264edd4d919ab2f8f652a.pdf">[pdf]</a></td><td></td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>48%</td><td>383</td><td>182</td><td>201</td><td>25</td><td>259</td><td>60</td></tr><tr><td>8a3c5507237957d013a0fe0f082cab7f757af6ee</td><td>mtfl</td><td>MTFL</td><td><a href="papers/8a3c5507237957d013a0fe0f082cab7f757af6ee.html">Facial Landmark Detection by Deep Multi-task Learning</a></td><td><a href="http://pdfs.semanticscholar.org/fcd7/1c18192928a2e0b264edd4d919ab2f8f652a.pdf">[pdf]</a></td><td></td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>48%</td><td>383</td><td>182</td><td>201</td><td>25</td><td>259</td><td>60</td></tr><tr><td>8a3c5507237957d013a0fe0f082cab7f757af6ee</td><td>mtfl</td><td>MTFL</td><td><a href="papers/8a3c5507237957d013a0fe0f082cab7f757af6ee.html">Facial Landmark Detection by Deep Multi-task Learning</a></td><td><a href="http://pdfs.semanticscholar.org/fcd7/1c18192928a2e0b264edd4d919ab2f8f652a.pdf">[pdf]</a></td><td></td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>48%</td><td>383</td><td>182</td><td>201</td><td>25</td><td>259</td><td>60</td></tr><tr><td>014b8df0180f33b9fea98f34ae611c6447d761d2</td><td>buhmap_db</td><td>BUHMAP-DB </td><td><a href="papers/014b8df0180f33b9fea98f34ae611c6447d761d2.html">Facial feature tracking and expression recognition for sign language</a></td><td><a href="http://www.cmpe.boun.edu.tr/pilab/pilabfiles/databases/buhmap/files/ari2008facialfeaturetracking.pdf">[pdf]</a></td><td>2008 23rd International Symposium on Computer and Information Sciences</td><td></td><td></td><td></td><td></td><td>16%</td><td>25</td><td>4</td><td>21</td><td>1</td><td>10</td><td>2</td></tr><tr><td>45e616093a92e5f1e61a7c6037d5f637aa8964af</td><td>malf</td><td>MALF</td><td><a href="papers/45e616093a92e5f1e61a7c6037d5f637aa8964af.html">Fine-grained evaluation on face detection in the wild</a></td><td><a href="http://www.cs.toronto.edu/~byang/papers/malf_fg15.pdf">[pdf]</a></td><td>2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>Chinese Academy of Sciences</td><td>40.00447950</td><td>116.37023800</td><td>71%</td><td>17</td><td>12</td><td>5</td><td>0</td><td>13</td><td>4</td></tr><tr><td>1aad2da473888cb7ebc1bfaa15bfa0f1502ce005</td><td>jpl_pose</td><td>JPL-Interaction dataset</td><td><a href="papers/1aad2da473888cb7ebc1bfaa15bfa0f1502ce005.html">First-Person Activity Recognition: What Are They Doing to Me?</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2013/papers/Ryoo_First-Person_Activity_Recognition_2013_CVPR_paper.pdf">[pdf]</a></td><td>2013 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>51%</td><td>148</td><td>76</td><td>72</td><td>8</td><td>109</td><td>3</td></tr><tr><td>774cbb45968607a027ae4729077734db000a1ec5</td><td>urban_tribes</td><td>Urban Tribes</td><td><a href="papers/774cbb45968607a027ae4729077734db000a1ec5.html">From Bikers to Surfers: Visual Recognition of Urban Tribes</a></td><td><a href="http://pdfs.semanticscholar.org/774c/bb45968607a027ae4729077734db000a1ec5.pdf">[pdf]</a></td><td></td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>47%</td><td>17</td><td>8</td><td>9</td><td>1</td><td>12</td><td>1</td></tr><tr><td>22f656d0f8426c84a33a267977f511f127bfd7f3</td><td>social_relation</td><td>Social Relation</td><td><a href="papers/22f656d0f8426c84a33a267977f511f127bfd7f3.html">From Facial Expression Recognition to Interpersonal Relation Prediction</a></td><td><a href="http://arxiv.org/abs/1609.06426">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>44%</td><td>9</td><td>4</td><td>5</td><td>0</td><td>5</td><td>1</td></tr><tr><td>22f656d0f8426c84a33a267977f511f127bfd7f3</td><td>social_relation</td><td>Social Relation</td><td><a href="papers/22f656d0f8426c84a33a267977f511f127bfd7f3.html">From Facial Expression Recognition to Interpersonal Relation Prediction</a></td><td><a href="http://arxiv.org/abs/1609.06426">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>44%</td><td>9</td><td>4</td><td>5</td><td>0</td><td>5</td><td>1</td></tr><tr><td>93884e46c49f7ae1c7c34046fbc28882f2bd6341</td><td>kdef</td><td>KDEF</td><td><a href="papers/93884e46c49f7ae1c7c34046fbc28882f2bd6341.html">Gaze fixation and the neural circuitry of face processing in autism</a></td><td><a href="{'url': 'http://doi.org/10.1038/nn1421', 'linkType': 'nature'}">[pdf]</a></td><td>Nature Neuroscience</td><td></td><td></td><td></td><td></td><td>31%</td><td>608</td><td>190</td><td>418</td><td>92</td><td>463</td><td>0</td></tr><tr><td>2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d</td><td>kin_face</td><td>UB KinFace</td><td><a href="papers/2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d.html">Genealogical face recognition based on UB KinFace database</a></td><td><a href="https://doi.org/10.1109/CVPRW.2011.5981801">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>SUNY Buffalo</td><td>42.93362780</td><td>-78.88394479</td><td>13%</td><td>30</td><td>4</td><td>26</td><td>1</td><td>9</td><td>5</td></tr><tr><td>2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d</td><td>kin_face</td><td>UB KinFace</td><td><a href="papers/2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d.html">Genealogical face recognition based on UB KinFace database</a></td><td><a href="https://doi.org/10.1109/CVPRW.2011.5981801">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>SUNY Buffalo</td><td>42.93362780</td><td>-78.88394479</td><td>13%</td><td>30</td><td>4</td><td>26</td><td>1</td><td>9</td><td>5</td></tr><tr><td>2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d</td><td>kin_face</td><td>UB KinFace</td><td><a href="papers/2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d.html">Genealogical face recognition based on UB KinFace database</a></td><td><a href="https://doi.org/10.1109/CVPRW.2011.5981801">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>SUNY Buffalo</td><td>42.93362780</td><td>-78.88394479</td><td>13%</td><td>30</td><td>4</td><td>26</td><td>1</td><td>9</td><td>5</td></tr><tr><td>b6b1b0632eb9d4ab1427278f5e5c46f97753c73d</td><td>fei</td><td>FEI</td><td><a href="papers/b6b1b0632eb9d4ab1427278f5e5c46f97753c73d.html">Generalização cartográfica automatizada para um banco de dados cadastral</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/b6b1/b0632eb9d4ab1427278f5e5c46f97753c73d.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9</td><td>graz</td><td>Graz Pedestrian</td><td><a href="papers/2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9.html">Generic object recognition with boosting</a></td><td><a href="http://www.emt.tu-graz.ac.at/~pinz/onlinepapers/Reprint_Vol_28_No_3_2006.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>24%</td><td>286</td><td>69</td><td>217</td><td>16</td><td>189</td><td>0</td></tr><tr><td>2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9</td><td>graz</td><td>Graz Pedestrian</td><td><a href="papers/2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9.html">Generic object recognition with boosting</a></td><td><a href="http://www.emt.tu-graz.ac.at/~pinz/onlinepapers/Reprint_Vol_28_No_3_2006.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>24%</td><td>286</td><td>69</td><td>217</td><td>16</td><td>189</td><td>0</td></tr><tr><td>2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9</td><td>graz</td><td>Graz Pedestrian</td><td><a href="papers/2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9.html">Generic object recognition with boosting</a></td><td><a href="http://www.emt.tu-graz.ac.at/~pinz/onlinepapers/Reprint_Vol_28_No_3_2006.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>24%</td><td>286</td><td>69</td><td>217</td><td>16</td><td>189</td><td>0</td></tr><tr><td>17b46e2dad927836c689d6787ddb3387c6159ece</td><td>geofaces</td><td>GeoFaces</td><td><a href="papers/17b46e2dad927836c689d6787ddb3387c6159ece.html">GeoFaceExplorer: exploring the geo-dependence of facial attributes</a></td><td><a href="http://doi.acm.org/10.1145/2676440.2676443">[pdf]</a></td><td></td><td>edu</td><td>University of Kentucky</td><td>38.03337420</td><td>-84.50177580</td><td>50%</td><td>2</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>3cd40bfa1ff193a96bde0207e5140a399476466c</td><td>tvhi</td><td>TVHI</td><td><a href="papers/3cd40bfa1ff193a96bde0207e5140a399476466c.html">High Five: Recognising human interactions in TV shows</a></td><td><a href="http://pdfs.semanticscholar.org/3cd4/0bfa1ff193a96bde0207e5140a399476466c.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>34%</td><td>91</td><td>31</td><td>60</td><td>11</td><td>64</td><td>1</td></tr><tr><td>24830e3979d4ed01b9fd0feebf4a8fd22e0c35fd</td><td>hi4d_adsip</td><td>Hi4D-ADSIP</td><td><a href="papers/24830e3979d4ed01b9fd0feebf4a8fd22e0c35fd.html">High-resolution comprehensive 3-D dynamic database for facial articulation analysis</a></td><td><a href="http://www.researchgate.net/profile/Wei_Quan3/publication/221430048_High-resolution_comprehensive_3-D_dynamic_database_for_facial_articulation_analysis/links/0deec534309495805d000000.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>0%</td><td>5</td><td>0</td><td>5</td><td>0</td><td>1</td><td>0</td></tr><tr><td>04c2cda00e5536f4b1508cbd80041e9552880e67</td><td>hipsterwars</td><td>Hipsterwars</td><td><a href="papers/04c2cda00e5536f4b1508cbd80041e9552880e67.html">Hipster Wars: Discovering Elements of Fashion Styles</a></td><td><a href="http://pdfs.semanticscholar.org/04c2/cda00e5536f4b1508cbd80041e9552880e67.pdf">[pdf]</a></td><td></td><td>edu</td><td>Tohoku University</td><td>38.25309450</td><td>140.87365930</td><td>53%</td><td>91</td><td>48</td><td>43</td><td>5</td><td>60</td><td>15</td></tr><tr><td>10d6b12fa07c7c8d6c8c3f42c7f1c061c131d4c5</td><td>inria_person</td><td>INRIA Pedestrian</td><td><a href="papers/10d6b12fa07c7c8d6c8c3f42c7f1c061c131d4c5.html">Histograms of oriented gradients for human detection</a></td><td><a href="http://nichol.as/papers/Dalai/Histograms%20of%20oriented%20gradients%20for%20human%20detection.pdf">[pdf]</a></td><td>2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)</td><td></td><td></td><td></td><td></td><td>22%</td><td>999</td><td>217</td><td>782</td><td>67</td><td>520</td><td>22</td></tr><tr><td>041d3eedf5e45ce5c5229f0181c5c576ed1fafd6</td><td>ucf_selfie</td><td>UCF Selfie</td><td><a href="papers/041d3eedf5e45ce5c5229f0181c5c576ed1fafd6.html">How to Take a Good Selfie?</a></td><td><a href="http://doi.acm.org/10.1145/2733373.2806365">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>22%</td><td>9</td><td>2</td><td>7</td><td>0</td><td>5</td><td>0</td></tr><tr><td>44d23df380af207f5ac5b41459c722c87283e1eb</td><td>wider_attribute</td><td>WIDER Attribute</td><td><a href="papers/44d23df380af207f5ac5b41459c722c87283e1eb.html">Human Attribute Recognition by Deep Hierarchical Contexts</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/8e28/07f2dd53b03a759e372e07f7191cae65c9fd.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>67%</td><td>18</td><td>12</td><td>6</td><td>0</td><td>16</td><td>0</td></tr><tr><td>44484d2866f222bbb9b6b0870890f9eea1ffb2d0</td><td>cuhk01</td><td>CUHK01</td><td><a href="papers/44484d2866f222bbb9b6b0870890f9eea1ffb2d0.html">Human Reidentification with Transferred Metric Learning</a></td><td><a href="http://pdfs.semanticscholar.org/4448/4d2866f222bbb9b6b0870890f9eea1ffb2d0.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>26%</td><td>258</td><td>67</td><td>191</td><td>12</td><td>141</td><td>1</td></tr><tr><td>57178b36c21fd7f4529ac6748614bb3374714e91</td><td>ijb_c</td><td>IJB-C</td><td><a href="papers/57178b36c21fd7f4529ac6748614bb3374714e91.html">IARPA Janus Benchmark - C: Face Dataset and Protocol</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8411217', 'linkType': 'ieee'}">[pdf]</a></td><td>2018 International Conference on Biometrics (ICB)</td><td></td><td></td><td></td><td></td><td>33%</td><td>9</td><td>3</td><td>6</td><td>2</td><td>9</td><td>0</td></tr><tr><td>0cb2dd5f178e3a297a0c33068961018659d0f443</td><td>ijb_b</td><td>IJB-B</td><td><a href="papers/0cb2dd5f178e3a297a0c33068961018659d0f443.html">IARPA Janus Benchmark-B Face Dataset</a></td><td><a href="http://www.vislab.ucr.edu/Biometrics2017/program_slides/Noblis_CVPRW_IJBB.pdf">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>24%</td><td>25</td><td>6</td><td>19</td><td>6</td><td>21</td><td>3</td></tr><tr><td>0297448f3ed948e136bb06ceff10eccb34e5bb77</td><td>ilids_mcts</td><td></td><td><a href="papers/0297448f3ed948e136bb06ceff10eccb34e5bb77.html">Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems</a></td><td><span class="gray">[pdf]</a></td><td>Proceedings 40th Annual 2006 International Carnahan Conference on Security Technology</td><td></td><td></td><td></td><td></td><td>22%</td><td>32</td><td>7</td><td>25</td><td>2</td><td>17</td><td>0</td></tr><tr><td>55c40cbcf49a0225e72d911d762c27bb1c2d14aa</td><td>ifad</td><td>IFAD</td><td><a href="papers/55c40cbcf49a0225e72d911d762c27bb1c2d14aa.html">Indian Face Age Database : A Database for Face Recognition with Age Variation</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/55c4/0cbcf49a0225e72d911d762c27bb1c2d14aa.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>50%</td><td>2</td><td>1</td><td>1</td><td>0</td><td>2</td><td>0</td></tr><tr><td>ca3e88d87e1344d076c964ea89d91a75c417f5ee</td><td>imfdb</td><td>IMFDB</td><td><a href="papers/ca3e88d87e1344d076c964ea89d91a75c417f5ee.html">Indian Movie Face Database: A benchmark for face recognition under wide variations</a></td><td><span class="gray">[pdf]</a></td><td>2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)</td><td></td><td></td><td></td><td></td><td>60%</td><td>15</td><td>9</td><td>6</td><td>0</td><td>10</td><td>4</td></tr><tr><td>95f12d27c3b4914e0668a268360948bce92f7db3</td><td>helen</td><td>Helen</td><td><a href="papers/95f12d27c3b4914e0668a268360948bce92f7db3.html">Interactive Facial Feature Localization</a></td><td><a href="http://pdfs.semanticscholar.org/95f1/2d27c3b4914e0668a268360948bce92f7db3.pdf">[pdf]</a></td><td></td><td>edu</td><td>University of Illinois, Urbana-Champaign</td><td>40.11116745</td><td>-88.22587665</td><td>52%</td><td>339</td><td>177</td><td>162</td><td>27</td><td>208</td><td>100</td></tr><tr><td>4d423acc78273b75134e2afd1777ba6d3a398973</td><td>cmu_pie</td><td>CMU PIE</td><td><a href="papers/4d423acc78273b75134e2afd1777ba6d3a398973.html">International Conference on Automatic Face and Gesture Recognition The CMU Pose , Illumination , and Expression ( PIE ) Database</a></td><td><a href="http://pdfs.semanticscholar.org/4d42/3acc78273b75134e2afd1777ba6d3a398973.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>44%</td><td>742</td><td>330</td><td>412</td><td>61</td><td>410</td><td>232</td></tr><tr><td>ad01687649d95cd5b56d7399a9603c4b8e2217d7</td><td>mrp_drone</td><td>MRP Drone</td><td><a href="papers/ad01687649d95cd5b56d7399a9603c4b8e2217d7.html">Investigating Open-World Person Re-identi cation Using a Drone</a></td><td><a href="http://pdfs.semanticscholar.org/ad01/687649d95cd5b56d7399a9603c4b8e2217d7.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>40%</td><td>5</td><td>2</td><td>3</td><td>0</td><td>3</td><td>0</td></tr><tr><td>b71d1aa90dcbe3638888725314c0d56640c1fef1</td><td>ifdb</td><td>IFDB</td><td><a href="papers/b71d1aa90dcbe3638888725314c0d56640c1fef1.html">Iranian Face Database with age, pose and expression</a></td><td><span class="gray">[pdf]</a></td><td>2007 International Conference on Machine Vision</td><td></td><td></td><td></td><td></td><td>20%</td><td>20</td><td>4</td><td>16</td><td>2</td><td>11</td><td>3</td></tr><tr><td>b71d1aa90dcbe3638888725314c0d56640c1fef1</td><td>ifdb</td><td>IFDB</td><td><a href="papers/b71d1aa90dcbe3638888725314c0d56640c1fef1.html">Iranian Face Database with age, pose and expression</a></td><td><span class="gray">[pdf]</a></td><td>2007 International Conference on Machine Vision</td><td></td><td></td><td></td><td></td><td>20%</td><td>20</td><td>4</td><td>16</td><td>2</td><td>11</td><td>3</td></tr><tr><td>137aa2f891d474fce1e7a1d1e9b3aefe21e22b34</td><td>hrt_transgender</td><td>HRT Transgender</td><td><a href="papers/137aa2f891d474fce1e7a1d1e9b3aefe21e22b34.html">Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset</a></td><td><a href="https://doi.org/10.1109/BTAS.2013.6712710">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of North Carolina Wilmington</td><td>34.23755810</td><td>-77.92701290</td><td>43%</td><td>7</td><td>3</td><td>4</td><td>1</td><td>2</td><td>3</td></tr><tr><td>137aa2f891d474fce1e7a1d1e9b3aefe21e22b34</td><td>hrt_transgender</td><td>HRT Transgender</td><td><a href="papers/137aa2f891d474fce1e7a1d1e9b3aefe21e22b34.html">Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset</a></td><td><a href="https://doi.org/10.1109/BTAS.2013.6712710">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of North Carolina Wilmington</td><td>34.23755810</td><td>-77.92701290</td><td>43%</td><td>7</td><td>3</td><td>4</td><td>1</td><td>2</td><td>3</td></tr><tr><td>137aa2f891d474fce1e7a1d1e9b3aefe21e22b34</td><td>hrt_transgender</td><td>HRT Transgender</td><td><a href="papers/137aa2f891d474fce1e7a1d1e9b3aefe21e22b34.html">Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset</a></td><td><a href="https://doi.org/10.1109/BTAS.2013.6712710">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of North Carolina Wilmington</td><td>34.23755810</td><td>-77.92701290</td><td>43%</td><td>7</td><td>3</td><td>4</td><td>1</td><td>2</td><td>3</td></tr><tr><td>0b440695c822a8e35184fb2f60dcdaa8a6de84ae</td><td>kinectface</td><td>KinectFaceDB</td><td><a href="papers/0b440695c822a8e35184fb2f60dcdaa8a6de84ae.html">KinectFaceDB: A Kinect Database for Face Recognition</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6866883', 'linkType': 'ieee'}">[pdf]</a></td><td>IEEE Transactions on Systems, Man, and Cybernetics: Systems</td><td></td><td></td><td></td><td></td><td>16%</td><td>75</td><td>12</td><td>63</td><td>6</td><td>25</td><td>8</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td>3dddb_unconstrained</td><td>3D Dynamic</td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>47%</td><td>999</td><td>472</td><td>526</td><td>71</td><td>619</td><td>260</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td>ar_facedb</td><td>AR Face</td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>47%</td><td>999</td><td>472</td><td>526</td><td>71</td><td>619</td><td>260</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td>m2vtsdb_extended</td><td>xm2vtsdb</td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>47%</td><td>999</td><td>472</td><td>526</td><td>71</td><td>619</td><td>260</td></tr><tr><td>370b5757a5379b15e30d619e4d3fb9e8e13f3256</td><td>put_face</td><td>Put Face</td><td><a href="papers/370b5757a5379b15e30d619e4d3fb9e8e13f3256.html">Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments</a></td><td><a href="http://pdfs.semanticscholar.org/c6b3/ca4f939e36a9679a70e14ce8b1bbbc5618f3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>47%</td><td>999</td><td>472</td><td>526</td><td>71</td><td>619</td><td>260</td></tr><tr><td>7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22</td><td>lfw</td><td>LFW</td><td><a href="papers/7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22.html">Labeled Faces in the Wild: A Survey</a></td><td><a href="http://pdfs.semanticscholar.org/7de6/e81d775e9cd7becbfd1bd685f4e2a5eebb22.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>29%</td><td>99</td><td>29</td><td>70</td><td>9</td><td>63</td><td>12</td></tr><tr><td>7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22</td><td>lfw</td><td>LFW</td><td><a href="papers/7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22.html">Labeled Faces in the Wild: A Survey</a></td><td><a href="http://pdfs.semanticscholar.org/7de6/e81d775e9cd7becbfd1bd685f4e2a5eebb22.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>29%</td><td>99</td><td>29</td><td>70</td><td>9</td><td>63</td><td>12</td></tr><tr><td>7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22</td><td>lfw</td><td>LFW</td><td><a href="papers/7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22.html">Labeled Faces in the Wild: A Survey</a></td><td><a href="http://pdfs.semanticscholar.org/7de6/e81d775e9cd7becbfd1bd685f4e2a5eebb22.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>29%</td><td>99</td><td>29</td><td>70</td><td>9</td><td>63</td><td>12</td></tr><tr><td>0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e</td><td>lag</td><td>LAG</td><td><a href="papers/0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e.html">Large Age-Gap face verification by feature injection in deep networks</a></td><td><a href="http://pdfs.semanticscholar.org/0d2d/d4fc016cb6a517d8fb43a7cc3ff62964832e.pdf">[pdf]</a></td><td>Pattern Recognition Letters</td><td></td><td></td><td></td><td></td><td>29%</td><td>7</td><td>2</td><td>5</td><td>0</td><td>3</td><td>2</td></tr><tr><td>f3b84a03985de3890b400b68e2a92c0a00afd9d0</td><td>scface</td><td>SCface</td><td><a href="papers/f3b84a03985de3890b400b68e2a92c0a00afd9d0.html">Large Variability Surveillance Camera Face Database</a></td><td><span class="gray">[pdf]</a></td><td>2015 Seventh International Conference on Computational Intelligence, Modelling and Simulation (CIMSim)</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1</td><td>uccs</td><td>UCCS</td><td><a href="papers/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1.html">Large scale unconstrained open set face database</a></td><td><a href="http://www.vast.uccs.edu/~tboult/PAPERS/BTAS13-Sapkota-Boult-UCCSFaceDB.pdf">[pdf]</a></td><td>2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)</td><td>edu</td><td>University of Colorado at Colorado Springs</td><td>38.89646790</td><td>-104.80505940</td><td>60%</td><td>5</td><td>3</td><td>2</td><td>0</td><td>3</td><td>0</td></tr><tr><td>69a68f9cf874c69e2232f47808016c2736b90c35</td><td>celeba_plus</td><td>CelebFaces+</td><td><a href="papers/69a68f9cf874c69e2232f47808016c2736b90c35.html">Learning Deep Representation for Imbalanced Classification</a></td><td><a href="http://personal.ie.cuhk.edu.hk/~ccloy/files/cvpr_2016_imbalanced.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Shenzhen Institutes of Advanced Technology</td><td>22.59805605</td><td>113.98533784</td><td>33%</td><td>51</td><td>17</td><td>34</td><td>1</td><td>39</td><td>2</td></tr><tr><td>853bd61bc48a431b9b1c7cab10c603830c488e39</td><td>casia_webface</td><td>CASIA Webface</td><td><a href="papers/853bd61bc48a431b9b1c7cab10c603830c488e39.html">Learning Face Representation from Scratch</a></td><td><a href="http://pdfs.semanticscholar.org/b8a2/0ed7e74325da76d7183d1ab77b082a92b447.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>53%</td><td>436</td><td>233</td><td>203</td><td>32</td><td>284</td><td>115</td></tr><tr><td>2a171f8d14b6b8735001a11c217af9587d095848</td><td>expw</td><td>ExpW</td><td><a href="papers/2a171f8d14b6b8735001a11c217af9587d095848.html">Learning Social Relation Traits from Face Images</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.414">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>30%</td><td>20</td><td>6</td><td>14</td><td>5</td><td>15</td><td>0</td></tr><tr><td>2a171f8d14b6b8735001a11c217af9587d095848</td><td>expw</td><td>ExpW</td><td><a href="papers/2a171f8d14b6b8735001a11c217af9587d095848.html">Learning Social Relation Traits from Face Images</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.414">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>30%</td><td>20</td><td>6</td><td>14</td><td>5</td><td>15</td><td>0</td></tr><tr><td>4e4746094bf60ee83e40d8597a6191e463b57f76</td><td>leeds_sports_pose_extended</td><td>Leeds Sports Pose Extended</td><td><a href="papers/4e4746094bf60ee83e40d8597a6191e463b57f76.html">Learning effective human pose estimation from inaccurate annotation</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5995318', 'linkType': 'ieee'}">[pdf]</a></td><td>CVPR 2011</td><td></td><td></td><td></td><td></td><td>40%</td><td>173</td><td>70</td><td>103</td><td>9</td><td>116</td><td>2</td></tr><tr><td>6dd0597f8513dc100cd0bc1b493768cde45098a9</td><td>stickmen_buffy</td><td>Buffy Stickmen</td><td><a href="papers/6dd0597f8513dc100cd0bc1b493768cde45098a9.html">Learning to parse images of articulated bodies</a></td><td><a href="http://pdfs.semanticscholar.org/9cd7/4c43dbf9be0b9caae4606ee53e6d45850471.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>31%</td><td>373</td><td>117</td><td>256</td><td>30</td><td>238</td><td>2</td></tr><tr><td>6dd0597f8513dc100cd0bc1b493768cde45098a9</td><td>stickmen_buffy</td><td>Buffy Stickmen</td><td><a href="papers/6dd0597f8513dc100cd0bc1b493768cde45098a9.html">Learning to parse images of articulated bodies</a></td><td><a href="http://pdfs.semanticscholar.org/9cd7/4c43dbf9be0b9caae4606ee53e6d45850471.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>31%</td><td>373</td><td>117</td><td>256</td><td>30</td><td>238</td><td>2</td></tr><tr><td>c9bda86e23cab9e4f15ea0c4cbb6cc02b9dfb709</td><td>stanford_drone</td><td>Stanford Drone</td><td><a href="papers/c9bda86e23cab9e4f15ea0c4cbb6cc02b9dfb709.html">Learning to predict human behaviour in crowded scenes</a></td><td><a href="http://pdfs.semanticscholar.org/c9bd/a86e23cab9e4f15ea0c4cbb6cc02b9dfb709.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>20%</td><td>5</td><td>1</td><td>4</td><td>1</td><td>5</td><td>0</td></tr><tr><td>140438a77a771a8fb656b39a78ff488066eb6b50</td><td>lfw_p</td><td>LFWP</td><td><a href="papers/140438a77a771a8fb656b39a78ff488066eb6b50.html">Localizing Parts of Faces Using a Consensus of Exemplars</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2011.5995602">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td>edu</td><td>Columbia University</td><td>40.84198360</td><td>-73.94368971</td><td>53%</td><td>521</td><td>274</td><td>247</td><td>40</td><td>321</td><td>144</td></tr><tr><td>38b55d95189c5e69cf4ab45098a48fba407609b4</td><td>cuhk02</td><td>CUHK02</td><td><a href="papers/38b55d95189c5e69cf4ab45098a48fba407609b4.html">Locally Aligned Feature Transforms across Views</a></td><td><a href="http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/IEEE_CVPR2013/data/Papers/4989d594.pdf">[pdf]</a></td><td>2013 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>24%</td><td>242</td><td>57</td><td>185</td><td>17</td><td>139</td><td>1</td></tr><tr><td>c0387e788a52f10bf35d4d50659cfa515d89fbec</td><td>mars</td><td>MARS</td><td><a href="papers/c0387e788a52f10bf35d4d50659cfa515d89fbec.html">MARS: A Video Benchmark for Large-Scale Person Re-Identification</a></td><td><a href="http://pdfs.semanticscholar.org/c038/7e788a52f10bf35d4d50659cfa515d89fbec.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>34%</td><td>146</td><td>49</td><td>97</td><td>6</td><td>96</td><td>0</td></tr><tr><td>9055b155cbabdce3b98e16e5ac9c0edf00f9552f</td><td>morph</td><td>MORPH Commercial</td><td><a href="papers/9055b155cbabdce3b98e16e5ac9c0edf00f9552f.html">MORPH: a longitudinal image database of normal adult age-progression</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/FGR.2006.78">[pdf]</a></td><td>7th International Conference on Automatic Face and Gesture Recognition (FGR06)</td><td></td><td></td><td></td><td></td><td>46%</td><td>424</td><td>195</td><td>229</td><td>27</td><td>231</td><td>155</td></tr><tr><td>9055b155cbabdce3b98e16e5ac9c0edf00f9552f</td><td>morph_nc</td><td>MORPH Non-Commercial</td><td><a href="papers/9055b155cbabdce3b98e16e5ac9c0edf00f9552f.html">MORPH: a longitudinal image database of normal adult age-progression</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/FGR.2006.78">[pdf]</a></td><td>7th International Conference on Automatic Face and Gesture Recognition (FGR06)</td><td></td><td></td><td></td><td></td><td>46%</td><td>424</td><td>195</td><td>229</td><td>27</td><td>231</td><td>155</td></tr><tr><td>291265db88023e92bb8c8e6390438e5da148e8f5</td><td>msceleb</td><td>MsCeleb</td><td><a href="papers/291265db88023e92bb8c8e6390438e5da148e8f5.html">MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/4603/cb8e05258bb0572ae912ad20903b8f99f4b1.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>50%</td><td>167</td><td>83</td><td>84</td><td>15</td><td>131</td><td>27</td></tr><tr><td>3dc3f0b64ef80f573e3a5f96e456e52ee980b877</td><td>georgia_tech_face_database</td><td>Georgia Tech Face</td><td><a href="papers/3dc3f0b64ef80f573e3a5f96e456e52ee980b877.html">Maximum Likelihood Training of the Embedded HMM for Face Detection and Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/3dc3/f0b64ef80f573e3a5f96e456e52ee980b877.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>3</td><td>0</td><td>3</td><td>0</td><td>2</td><td>0</td></tr><tr><td>5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725</td><td>50_people_one_question</td><td>50 People One Question</td><td><a href="papers/5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725.html">Merging Pose Estimates Across Space and Time</a></td><td><a href="http://pdfs.semanticscholar.org/63b2/f5348af0f969dfc2afb4977732393c6459ec.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>60%</td><td>15</td><td>9</td><td>6</td><td>0</td><td>11</td><td>2</td></tr><tr><td>696ca58d93f6404fea0fc75c62d1d7b378f47628</td><td>coco</td><td>COCO</td><td><a href="papers/696ca58d93f6404fea0fc75c62d1d7b378f47628.html">Microsoft COCO Captions: Data Collection and Evaluation Server</a></td><td><a href="http://pdfs.semanticscholar.org/ba95/81c33a7eebe87c50e61763e4c8d1723538f2.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>46%</td><td>283</td><td>129</td><td>154</td><td>16</td><td>231</td><td>4</td></tr><tr><td>a5a44a32a91474f00a3cda671a802e87c899fbb4</td><td>moments_in_time</td><td>Moments in Time</td><td><a href="papers/a5a44a32a91474f00a3cda671a802e87c899fbb4.html">Moments in Time Dataset: one million videos for event understanding</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1801.03150.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>60%</td><td>25</td><td>15</td><td>10</td><td>2</td><td>25</td><td>0</td></tr><tr><td>436f798d1a4e54e5947c1e7d7375c31b2bdb4064</td><td>tud_multiview</td><td>TUD-Multiview</td><td><a href="papers/436f798d1a4e54e5947c1e7d7375c31b2bdb4064.html">Monocular 3D pose estimation and tracking by detection</a></td><td><a href="http://lmb.informatik.uni-freiburg.de/lectures/seminar_brox/seminar_ws1011/cvpr10_andriluka.pdf">[pdf]</a></td><td>2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>25%</td><td>302</td><td>76</td><td>226</td><td>32</td><td>199</td><td>1</td></tr><tr><td>436f798d1a4e54e5947c1e7d7375c31b2bdb4064</td><td>tud_stadtmitte</td><td>TUD-Stadtmitte</td><td><a href="papers/436f798d1a4e54e5947c1e7d7375c31b2bdb4064.html">Monocular 3D pose estimation and tracking by detection</a></td><td><a href="http://lmb.informatik.uni-freiburg.de/lectures/seminar_brox/seminar_ws1011/cvpr10_andriluka.pdf">[pdf]</a></td><td>2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>25%</td><td>302</td><td>76</td><td>226</td><td>32</td><td>199</td><td>1</td></tr><tr><td>3b5b6d19d4733ab606c39c69a889f9e67967f151</td><td>qmul_grid</td><td>GRID</td><td><a href="papers/3b5b6d19d4733ab606c39c69a889f9e67967f151.html">Multi-camera activity correlation analysis</a></td><td><a href="http://vision.lbl.gov/Conferences/cvpr/Papers/data/papers/0163.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>25%</td><td>138</td><td>35</td><td>103</td><td>8</td><td>76</td><td>1</td></tr><tr><td>3b5b6d19d4733ab606c39c69a889f9e67967f151</td><td>qmul_grid</td><td>GRID</td><td><a href="papers/3b5b6d19d4733ab606c39c69a889f9e67967f151.html">Multi-camera activity correlation analysis</a></td><td><a href="http://vision.lbl.gov/Conferences/cvpr/Papers/data/papers/0163.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>25%</td><td>138</td><td>35</td><td>103</td><td>8</td><td>76</td><td>1</td></tr><tr><td>6ad5a38df8dd4cdddd74f31996ce096d41219f72</td><td>tud_brussels</td><td>TUD-Brussels</td><td><a href="papers/6ad5a38df8dd4cdddd74f31996ce096d41219f72.html">Multi-cue onboard pedestrian detection</a></td><td><a href="https://www.mpi-inf.mpg.de/fileadmin/inf/d2/wojek/poster_cwojek_cvpr09.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>19%</td><td>217</td><td>41</td><td>176</td><td>14</td><td>131</td><td>1</td></tr><tr><td>6ad5a38df8dd4cdddd74f31996ce096d41219f72</td><td>tud_motionpairs</td><td>TUD-Motionparis</td><td><a href="papers/6ad5a38df8dd4cdddd74f31996ce096d41219f72.html">Multi-cue onboard pedestrian detection</a></td><td><a href="https://www.mpi-inf.mpg.de/fileadmin/inf/d2/wojek/poster_cwojek_cvpr09.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>19%</td><td>217</td><td>41</td><td>176</td><td>14</td><td>131</td><td>1</td></tr><tr><td>32c801cb7fbeb742edfd94cccfca4934baec71da</td><td>ucf_crowd</td><td>UCF-CC-50</td><td><a href="papers/32c801cb7fbeb742edfd94cccfca4934baec71da.html">Multi-source Multi-scale Counting in Extremely Dense Crowd Images</a></td><td><a href="http://www.cs.ucf.edu/~haroon/datafiles/Idrees_Counting_CVPR_2013.pdf">[pdf]</a></td><td>2013 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>38%</td><td>125</td><td>48</td><td>77</td><td>6</td><td>72</td><td>1</td></tr><tr><td>1e3df3ca8feab0b36fd293fe689f93bb2aaac591</td><td>immediacy</td><td>Immediacy</td><td><a href="papers/1e3df3ca8feab0b36fd293fe689f93bb2aaac591.html">Multi-task Recurrent Neural Network for Immediacy Prediction</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.383">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>60%</td><td>25</td><td>15</td><td>10</td><td>2</td><td>20</td><td>0</td></tr><tr><td>53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4</td><td>bp4d_plus</td><td>BP4D+</td><td><a href="papers/53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4.html">Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhang_Multimodal_Spontaneous_Emotion_CVPR_2016_paper.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>25%</td><td>40</td><td>10</td><td>30</td><td>0</td><td>20</td><td>6</td></tr><tr><td>2fda164863a06a92d3a910b96eef927269aeb730</td><td>names_and_faces_news</td><td>News Dataset</td><td><a href="papers/2fda164863a06a92d3a910b96eef927269aeb730.html">Names and faces in the news</a></td><td><a href="http://www.cs.utexas.edu/~grauman/courses/spring2007/395T/papers/berg_names_and_faces.pdf">[pdf]</a></td><td>Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.</td><td></td><td></td><td></td><td></td><td>41%</td><td>294</td><td>120</td><td>174</td><td>24</td><td>207</td><td>45</td></tr><tr><td>4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06</td><td>distance_nighttime</td><td>Long Distance Heterogeneous Face</td><td><a href="papers/4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06.html">Nighttime Face Recognition at Long Distance: Cross-Distance and Cross-Spectral Matching</a></td><td><a href="http://pdfs.semanticscholar.org/4156/b7e88f2e0ab0a7c095b9bab199ae2b23bd06.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>24%</td><td>21</td><td>5</td><td>16</td><td>3</td><td>11</td><td>1</td></tr><tr><td>31b58ced31f22eab10bd3ee2d9174e7c14c27c01</td><td>tiny_images</td><td>Tiny Images</td><td><a href="papers/31b58ced31f22eab10bd3ee2d9174e7c14c27c01.html">Nonparametric Object and Scene Recognition</a></td><td><a href="http://pdfs.semanticscholar.org/31b5/8ced31f22eab10bd3ee2d9174e7c14c27c01.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>31%</td><td>999</td><td>305</td><td>694</td><td>93</td><td>670</td><td>9</td></tr><tr><td>55206f0b5f57ce17358999145506cd01e570358c</td><td>orl</td><td>ORL</td><td><a href="papers/55206f0b5f57ce17358999145506cd01e570358c.html">O M 4 . 1 The Subject Database 4 . 2 Experiment Plan 5 . 1 Varying the Overlap 4 Experimental Setup 5 Parameterisation Results</a></td><td><a href="http://pdfs.semanticscholar.org/5520/6f0b5f57ce17358999145506cd01e570358c.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>21%</td><td>999</td><td>214</td><td>785</td><td>96</td><td>550</td><td>57</td></tr><tr><td>3394168ff0719b03ff65bcea35336a76b21fe5e4</td><td>penn_fudan</td><td>Penn Fudan</td><td><a href="papers/3394168ff0719b03ff65bcea35336a76b21fe5e4.html">Object Detection Combining Recognition and Segmentation</a></td><td><a href="http://pdfs.semanticscholar.org/f531/a554cade14b9b340de6730683a28c292dd74.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>23%</td><td>101</td><td>23</td><td>78</td><td>11</td><td>58</td><td>0</td></tr><tr><td>4f93cd09785c6e77bf4bc5a788e079df524c8d21</td><td>soton</td><td>SOTON HiD</td><td><a href="papers/4f93cd09785c6e77bf4bc5a788e079df524c8d21.html">On a large sequence-based human gait database</a></td><td><a href="http://pdfs.semanticscholar.org/4f93/cd09785c6e77bf4bc5a788e079df524c8d21.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>36%</td><td>148</td><td>54</td><td>94</td><td>16</td><td>98</td><td>0</td></tr><tr><td>6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c</td><td>afad</td><td>AFAD</td><td><a href="papers/6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c.html">Ordinal Regression with Multiple Output CNN for Age Estimation</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2016.532">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>44%</td><td>68</td><td>30</td><td>38</td><td>8</td><td>49</td><td>7</td></tr><tr><td>a7fe834a0af614ce6b50dc093132b031dd9a856b</td><td>market1203</td><td>Market 1203</td><td><a href="papers/a7fe834a0af614ce6b50dc093132b031dd9a856b.html">Orientation Driven Bag of Appearances for Person Re-identification</a></td><td><a href="http://pdfs.semanticscholar.org/a7fe/834a0af614ce6b50dc093132b031dd9a856b.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>29%</td><td>7</td><td>2</td><td>5</td><td>0</td><td>3</td><td>0</td></tr><tr><td>a7fe834a0af614ce6b50dc093132b031dd9a856b</td><td>pku_reid</td><td>PKU-Reid</td><td><a href="papers/a7fe834a0af614ce6b50dc093132b031dd9a856b.html">Orientation Driven Bag of Appearances for Person Re-identification</a></td><td><a href="http://pdfs.semanticscholar.org/a7fe/834a0af614ce6b50dc093132b031dd9a856b.pdf">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>29%</td><td>7</td><td>2</td><td>5</td><td>0</td><td>3</td><td>0</td></tr><tr><td>18ae7c9a4bbc832b8b14bc4122070d7939f5e00e</td><td>frgc</td><td>FRGC</td><td><a href="papers/18ae7c9a4bbc832b8b14bc4122070d7939f5e00e.html">Overview of the face recognition grand challenge</a></td><td><a href="http://www3.nd.edu/~kwb/PhillipsEtAlCVPR_2005.pdf">[pdf]</a></td><td>2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)</td><td></td><td></td><td></td><td></td><td>25%</td><td>999</td><td>253</td><td>746</td><td>110</td><td>572</td><td>64</td></tr><tr><td>22909dd19a0ec3b6065334cb5be5392cb24d839d</td><td>pets</td><td>PETS 2017</td><td><a href="papers/22909dd19a0ec3b6065334cb5be5392cb24d839d.html">PETS 2017: Dataset and Challenge</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8014998', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</td><td></td><td></td><td></td><td></td><td>0%</td><td>8</td><td>0</td><td>8</td><td>0</td><td>2</td><td>0</td></tr><tr><td>56ffa7d906b08d02d6d5a12c7377a57e24ef3391</td><td>unbc_shoulder_pain</td><td>UNBC-McMaster Pain</td><td><a href="papers/56ffa7d906b08d02d6d5a12c7377a57e24ef3391.html">Painful data: The UNBC-McMaster shoulder pain expression archive database</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5771462', 'linkType': 'ieee'}">[pdf]</a></td><td>Face and Gesture 2011</td><td></td><td></td><td></td><td></td><td>32%</td><td>184</td><td>58</td><td>126</td><td>23</td><td>112</td><td>23</td></tr><tr><td>0486214fb58ee9a04edfe7d6a74c6d0f661a7668</td><td>chokepoint</td><td>ChokePoint</td><td><a href="papers/0486214fb58ee9a04edfe7d6a74c6d0f661a7668.html">Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition</a></td><td><a href="http://conradsanderson.id.au/pdfs/wong_face_selection_cvpr_biometrics_2011.pdf">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>University of Queensland</td><td>-27.49741805</td><td>153.01316956</td><td>30%</td><td>128</td><td>39</td><td>89</td><td>6</td><td>68</td><td>14</td></tr><tr><td>488e475eeb3bb39a145f23ede197cd3620f1d98a</td><td>apis</td><td>APiS1.0</td><td><a href="papers/488e475eeb3bb39a145f23ede197cd3620f1d98a.html">Pedestrian Attribute Classification in Surveillance: Database and Evaluation</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_iccv_workshops_2013/W10/papers/Zhu_Pedestrian_Attribute_Classification_2013_ICCV_paper.pdf">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision Workshops</td><td></td><td></td><td></td><td></td><td>38%</td><td>26</td><td>10</td><td>16</td><td>1</td><td>13</td><td>2</td></tr><tr><td>488e475eeb3bb39a145f23ede197cd3620f1d98a</td><td>svs</td><td>SVS</td><td><a href="papers/488e475eeb3bb39a145f23ede197cd3620f1d98a.html">Pedestrian Attribute Classification in Surveillance: Database and Evaluation</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_iccv_workshops_2013/W10/papers/Zhu_Pedestrian_Attribute_Classification_2013_ICCV_paper.pdf">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision Workshops</td><td></td><td></td><td></td><td></td><td>38%</td><td>26</td><td>10</td><td>16</td><td>1</td><td>13</td><td>2</td></tr><tr><td>2a4bbee0b4cf52d5aadbbc662164f7efba89566c</td><td>peta</td><td>PETA</td><td><a href="papers/2a4bbee0b4cf52d5aadbbc662164f7efba89566c.html">Pedestrian Attribute Recognition At Far Distance</a></td><td><a href="http://personal.ie.cuhk.edu.hk/~pluo/pdf/mm14.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>46%</td><td>80</td><td>37</td><td>43</td><td>2</td><td>51</td><td>3</td></tr><tr><td>1dc35905a1deff8bc74688f2d7e2f48fd2273275</td><td>caltech_pedestrians</td><td>Caltech Pedestrians</td><td><a href="papers/1dc35905a1deff8bc74688f2d7e2f48fd2273275.html">Pedestrian detection: A benchmark</a></td><td><a href="http://vision.ucsd.edu/~pdollar/files/papers/DollarCVPR09peds.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>17%</td><td>519</td><td>89</td><td>430</td><td>27</td><td>286</td><td>2</td></tr><tr><td>1dc35905a1deff8bc74688f2d7e2f48fd2273275</td><td>caltech_pedestrians</td><td>Caltech Pedestrians</td><td><a href="papers/1dc35905a1deff8bc74688f2d7e2f48fd2273275.html">Pedestrian detection: A benchmark</a></td><td><a href="http://vision.ucsd.edu/~pdollar/files/papers/DollarCVPR09peds.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>17%</td><td>519</td><td>89</td><td>430</td><td>27</td><td>286</td><td>2</td></tr><tr><td>3316521a5527c7700af8ae6aef32a79a8b83672c</td><td>tud_campus</td><td>TUD-Campus</td><td><a href="papers/3316521a5527c7700af8ae6aef32a79a8b83672c.html">People-tracking-by-detection and people-detection-by-tracking</a></td><td><a href="http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/Conference/data/papers/243.pdf">[pdf]</a></td><td>2008 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>22%</td><td>529</td><td>116</td><td>413</td><td>41</td><td>316</td><td>1</td></tr><tr><td>3316521a5527c7700af8ae6aef32a79a8b83672c</td><td>tud_crossing</td><td>TUD-Crossing</td><td><a href="papers/3316521a5527c7700af8ae6aef32a79a8b83672c.html">People-tracking-by-detection and people-detection-by-tracking</a></td><td><a href="http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/Conference/data/papers/243.pdf">[pdf]</a></td><td>2008 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>22%</td><td>529</td><td>116</td><td>413</td><td>41</td><td>316</td><td>1</td></tr><tr><td>3316521a5527c7700af8ae6aef32a79a8b83672c</td><td>tud_pedestrian</td><td>TUD-Pedestrian</td><td><a href="papers/3316521a5527c7700af8ae6aef32a79a8b83672c.html">People-tracking-by-detection and people-detection-by-tracking</a></td><td><a href="http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/Conference/data/papers/243.pdf">[pdf]</a></td><td>2008 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>22%</td><td>529</td><td>116</td><td>413</td><td>41</td><td>316</td><td>1</td></tr><tr><td>27a2fad58dd8727e280f97036e0d2bc55ef5424c</td><td>duke_mtmc</td><td>Duke MTMC</td><td><a href="papers/27a2fad58dd8727e280f97036e0d2bc55ef5424c.html">Performance Measures and a Data Set for Multi-target, Multi-camera Tracking</a></td><td><a href="http://pdfs.semanticscholar.org/b5f2/4f49f9a5e47d6601399dc068158ad88d7651.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>136</td><td>58</td><td>78</td><td>6</td><td>107</td><td>0</td></tr><tr><td>16c7c31a7553d99f1837fc6e88e77b5ccbb346b8</td><td>prid</td><td>PRID</td><td><a href="papers/16c7c31a7553d99f1837fc6e88e77b5ccbb346b8.html">Person Re-identification by Descriptive and Discriminative Classification</a></td><td><a href="http://pdfs.semanticscholar.org/4c1b/f0592be3e535faf256c95e27982db9b3d3d3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>27%</td><td>352</td><td>94</td><td>258</td><td>26</td><td>195</td><td>3</td></tr><tr><td>99eb4cea0d9bc9fe777a5c5172f8638a37a7f262</td><td>ilids_vid_reid</td><td>iLIDS-VID</td><td><a href="papers/99eb4cea0d9bc9fe777a5c5172f8638a37a7f262.html">Person Re-identification by Exploiting Spatio-Temporal Cues and Multi-view Metric Learning</a></td><td><a href="https://doi.org/10.1109/LSP.2016.2574323">[pdf]</a></td><td>IEEE Signal Processing Letters</td><td></td><td></td><td></td><td></td><td>29%</td><td>7</td><td>2</td><td>5</td><td>0</td><td>4</td><td>0</td></tr><tr><td>0b84f07af44f964817675ad961def8a51406dd2e</td><td>prw</td><td>PRW</td><td><a href="papers/0b84f07af44f964817675ad961def8a51406dd2e.html">Person Re-identification in the Wild</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2017.357">[pdf]</a></td><td>2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Technology Sydney</td><td>-33.88096510</td><td>151.20107299</td><td>38%</td><td>65</td><td>25</td><td>40</td><td>1</td><td>46</td><td>0</td></tr><tr><td>ec792ad2433b6579f2566c932ee414111e194537</td><td>msmt_17</td><td>MSMT17</td><td><a href="papers/ec792ad2433b6579f2566c932ee414111e194537.html">Person Transfer GAN to Bridge Domain Gap for Person Re-Identification</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1711.08565.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>50%</td><td>14</td><td>7</td><td>7</td><td>1</td><td>11</td><td>0</td></tr><tr><td>1c2802c2199b6d15ecefe7ba0c39bfe44363de38</td><td>youtube_poses</td><td>YouTube Pose</td><td><a href="papers/1c2802c2199b6d15ecefe7ba0c39bfe44363de38.html">Personalizing Human Video Pose Estimation</a></td><td><a href="http://arxiv.org/pdf/1511.06676v1.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>44%</td><td>32</td><td>14</td><td>18</td><td>2</td><td>27</td><td>0</td></tr><tr><td>b92a1ed9622b8268ae3ac9090e25789fc41cc9b8</td><td>pornodb</td><td>Pornography DB</td><td><a href="papers/b92a1ed9622b8268ae3ac9090e25789fc41cc9b8.html">Pooling in image representation: The visual codeword point of view</a></td><td><a href="http://pdfs.semanticscholar.org/b92a/1ed9622b8268ae3ac9090e25789fc41cc9b8.pdf">[pdf]</a></td><td>Computer Vision and Image Understanding</td><td></td><td></td><td></td><td></td><td>9%</td><td>77</td><td>7</td><td>70</td><td>7</td><td>43</td><td>2</td></tr><tr><td>2830fb5282de23d7784b4b4bc37065d27839a412</td><td>h3d</td><td>H3D</td><td><a href="papers/2830fb5282de23d7784b4b4bc37065d27839a412.html">Poselets: Body part detectors trained using 3D human pose annotations</a></td><td><a href="http://vision.stanford.edu/teaching/cs231b_spring1213/papers/ICCV09_BourdevMalik.pdf">[pdf]</a></td><td>2009 IEEE 12th International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>32%</td><td>707</td><td>223</td><td>484</td><td>62</td><td>482</td><td>18</td></tr><tr><td>3765df816dc5a061bc261e190acc8bdd9d47bec0</td><td>rafd</td><td>RaFD</td><td><a href="papers/3765df816dc5a061bc261e190acc8bdd9d47bec0.html">Presentation and validation of the Radboud Faces Database</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/3765/df816dc5a061bc261e190acc8bdd9d47bec0.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>28%</td><td>446</td><td>127</td><td>319</td><td>43</td><td>307</td><td>19</td></tr><tr><td>636b8ffc09b1b23ff714ac8350bb35635e49fa3c</td><td>caltech_10k_web_faces</td><td>Caltech 10K Web Faces</td><td><a href="papers/636b8ffc09b1b23ff714ac8350bb35635e49fa3c.html">Pruning training sets for learning of object categories</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1467308', 'linkType': 'ieee'}">[pdf]</a></td><td>2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)</td><td></td><td></td><td></td><td></td><td>58%</td><td>60</td><td>35</td><td>25</td><td>5</td><td>42</td><td>12</td></tr><tr><td>377f2b65e6a9300448bdccf678cde59449ecd337</td><td>ufdd</td><td>UFDD</td><td><a href="papers/377f2b65e6a9300448bdccf678cde59449ecd337.html">Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1804.10275.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td>edu</td><td>Johns Hopkins University</td><td>39.32905300</td><td>-76.61942500</td><td>0%</td><td>2</td><td>0</td><td>2</td><td>0</td><td>2</td><td>0</td></tr><tr><td>140c95e53c619eac594d70f6369f518adfea12ef</td><td>ijb_a</td><td>IJB-A</td><td><a href="papers/140c95e53c619eac594d70f6369f518adfea12ef.html">Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2015/app/1B_089_ext.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>48%</td><td>222</td><td>107</td><td>115</td><td>21</td><td>158</td><td>48</td></tr><tr><td>d80a3d1f3a438e02a6685e66ee908446766fefa9</td><td>megaage</td><td>MegaAge</td><td><a href="papers/d80a3d1f3a438e02a6685e66ee908446766fefa9.html">Quantifying Facial Age by Posterior of Age Comparisons</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1708.09687.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>25%</td><td>4</td><td>1</td><td>3</td><td>1</td><td>4</td><td>0</td></tr><tr><td>4946ba10a4d5a7d0a38372f23e6622bd347ae273</td><td>coco_action</td><td>COCO-a</td><td><a href="papers/4946ba10a4d5a7d0a38372f23e6622bd347ae273.html">RONCHI AND PERONA: DESCRIBING COMMON HUMAN VISUAL ACTIONS IN IMAGES 1 Describing Common Human Visual Actions in Images</a></td><td><a href="http://pdfs.semanticscholar.org/b38d/cf5fa5174c0d718d65cc4f3889b03c4a21df.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>54%</td><td>26</td><td>14</td><td>12</td><td>0</td><td>25</td><td>0</td></tr><tr><td>922e0a51a3b8c67c4c6ac09a577ff674cbd28b34</td><td>v47</td><td>V47</td><td><a href="papers/922e0a51a3b8c67c4c6ac09a577ff674cbd28b34.html">Re-identification of pedestrians with variable occlusion and scale</a></td><td><a href="https://doi.org/10.1109/ICCVW.2011.6130477">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>0%</td><td>10</td><td>0</td><td>10</td><td>2</td><td>6</td><td>0</td></tr><tr><td>6f3c76b7c0bd8e1d122c6ea808a271fd4749c951</td><td>ward</td><td>WARD</td><td><a href="papers/6f3c76b7c0bd8e1d122c6ea808a271fd4749c951.html">Re-identify people in wide area camera network</a></td><td><a href="https://doi.org/10.1109/CVPRW.2012.6239203">[pdf]</a></td><td>2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</td><td></td><td></td><td></td><td></td><td>9%</td><td>55</td><td>5</td><td>50</td><td>2</td><td>35</td><td>0</td></tr><tr><td>54983972aafc8e149259d913524581357b0f91c3</td><td>reseed</td><td>ReSEED</td><td><a href="papers/54983972aafc8e149259d913524581357b0f91c3.html">ReSEED: social event dEtection dataset</a></td><td><a href="https://pub.uni-bielefeld.de/download/2663466/2686734">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>17%</td><td>6</td><td>1</td><td>5</td><td>1</td><td>1</td><td>1</td></tr><tr><td>65355cbb581a219bd7461d48b3afd115263ea760</td><td>complex_activities</td><td>Ongoing Complex Activities</td><td><a href="papers/65355cbb581a219bd7461d48b3afd115263ea760.html">Recognition of ongoing complex activities by sequence prediction over a hierarchical label space</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/WACV.2016.7477586">[pdf]</a></td><td>2016 IEEE Winter Conference on Applications of Computer Vision (WACV)</td><td></td><td></td><td></td><td></td><td>0%</td><td>2</td><td>0</td><td>2</td><td>0</td><td>2</td><td>0</td></tr><tr><td>e8de844fefd54541b71c9823416daa238be65546</td><td>visual_phrases</td><td>Phrasal Recognition</td><td><a href="papers/e8de844fefd54541b71c9823416daa238be65546.html">Recognition using visual phrases</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5995711', 'linkType': 'ieee'}">[pdf]</a></td><td>CVPR 2011</td><td></td><td></td><td></td><td></td><td>41%</td><td>233</td><td>95</td><td>138</td><td>18</td><td>174</td><td>5</td></tr><tr><td>356b431d4f7a2a0a38cf971c84568207dcdbf189</td><td>wider</td><td>WIDER</td><td><a href="papers/356b431d4f7a2a0a38cf971c84568207dcdbf189.html">Recognize complex events from static images by fusing deep channels</a></td><td><a href="http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Xiong_Recognize_Complex_Events_2015_CVPR_paper.pdf">[pdf]</a></td><td>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Shenzhen Institutes of Advanced Technology</td><td>22.59805605</td><td>113.98533784</td><td>58%</td><td>45</td><td>26</td><td>19</td><td>1</td><td>30</td><td>12</td></tr><tr><td>25474c21613607f6bb7687a281d5f9d4ffa1f9f3</td><td>faceplace</td><td>Face Place</td><td><a href="papers/25474c21613607f6bb7687a281d5f9d4ffa1f9f3.html">Recognizing disguised faces</a></td><td><a href="http://pdfs.semanticscholar.org/d936/7ceb0be378c3a9ddf7cb741c678c1a3c574c.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>25%</td><td>24</td><td>6</td><td>18</td><td>0</td><td>16</td><td>1</td></tr><tr><td>4053e3423fb70ad9140ca89351df49675197196a</td><td>bio_id</td><td>BioID Face</td><td><a href="papers/4053e3423fb70ad9140ca89351df49675197196a.html">Robust Face Detection Using the Hausdorff Distance</a></td><td><a href="http://pdfs.semanticscholar.org/4053/e3423fb70ad9140ca89351df49675197196a.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>26%</td><td>498</td><td>127</td><td>371</td><td>55</td><td>319</td><td>32</td></tr><tr><td>2724ba85ec4a66de18da33925e537f3902f21249</td><td>cofw</td><td>COFW</td><td><a href="papers/2724ba85ec4a66de18da33925e537f3902f21249.html">Robust Face Landmark Estimation under Occlusion</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6751298', 'linkType': 'ieee'}">[pdf]</a></td><td>2013 IEEE International Conference on Computer Vision</td><td></td><td></td><td></td><td></td><td>55%</td><td>305</td><td>167</td><td>138</td><td>16</td><td>186</td><td>95</td></tr><tr><td>e27ef52c641c2b5100a1b34fd0b819e84a31b4df</td><td>sarc3d</td><td>Sarc3D</td><td><a href="papers/e27ef52c641c2b5100a1b34fd0b819e84a31b4df.html">SARC3D: A New 3D Body Model for People Tracking and Re-identification</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/e27e/f52c641c2b5100a1b34fd0b819e84a31b4df.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>14%</td><td>29</td><td>4</td><td>25</td><td>3</td><td>17</td><td>0</td></tr><tr><td>bd26dabab576adb6af30484183c9c9c8379bf2e0</td><td>scut_fbp</td><td>SCUT-FBP</td><td><a href="papers/bd26dabab576adb6af30484183c9c9c8379bf2e0.html">SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1511.02459.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2015 IEEE International Conference on Systems, Man, and Cybernetics</td><td>edu</td><td>South China University of Technology</td><td>23.05020420</td><td>113.39880323</td><td>43%</td><td>14</td><td>6</td><td>8</td><td>3</td><td>5</td><td>7</td></tr><tr><td>d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9</td><td>stair_actions</td><td>STAIR Action</td><td><a href="papers/d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9.html">STAIR Actions: A Video Dataset of Everyday Home Actions</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1804.04326.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>4308bd8c28e37e2ed9a3fcfe74d5436cce34b410</td><td>market_1501</td><td>Market 1501</td><td><a href="papers/4308bd8c28e37e2ed9a3fcfe74d5436cce34b410.html">Scalable Person Re-identification: A Benchmark</a></td><td><a href="https://www.microsoft.com/en-us/research/wp-content/uploads/2017/01/ICCV15-ReIDDataset.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>38%</td><td>394</td><td>149</td><td>245</td><td>18</td><td>271</td><td>3</td></tr><tr><td>9c23859ec7313f2e756a3e85575735e0c52249f4</td><td>facebook_100</td><td>Facebook100</td><td><a href="papers/9c23859ec7313f2e756a3e85575735e0c52249f4.html">Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5981788', 'linkType': 'ieee'}">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>Harvard University</td><td>42.36782045</td><td>-71.12666653</td><td>50%</td><td>50</td><td>25</td><td>25</td><td>3</td><td>39</td><td>4</td></tr><tr><td>9c23859ec7313f2e756a3e85575735e0c52249f4</td><td>pubfig_83</td><td>pubfig83</td><td><a href="papers/9c23859ec7313f2e756a3e85575735e0c52249f4.html">Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5981788', 'linkType': 'ieee'}">[pdf]</a></td><td>CVPR 2011 WORKSHOPS</td><td>edu</td><td>Harvard University</td><td>42.36782045</td><td>-71.12666653</td><td>50%</td><td>50</td><td>25</td><td>25</td><td>3</td><td>39</td><td>4</td></tr><tr><td>109df0e8e5969ddf01e073143e83599228a1163f</td><td>multi_pie</td><td>MULTIPIE</td><td><a href="papers/109df0e8e5969ddf01e073143e83599228a1163f.html">Scheduling heterogeneous multi-cores through performance impact estimation (PIE)</a></td><td><a href="http://dl.acm.org/citation.cfm?id=2337184">[pdf]</a></td><td>2012 39th Annual International Symposium on Computer Architecture (ISCA)</td><td></td><td></td><td></td><td></td><td>25%</td><td>192</td><td>48</td><td>144</td><td>8</td><td>99</td><td>0</td></tr><tr><td>51eba481dac6b229a7490f650dff7b17ce05df73</td><td>imsitu</td><td>imSitu</td><td><a href="papers/51eba481dac6b229a7490f650dff7b17ce05df73.html">Situation Recognition: Visual Semantic Role Labeling for Image Understanding</a></td><td><a href="http://grail.cs.washington.edu/wp-content/uploads/2016/09/yatskar2016srv.pdf">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>60%</td><td>48</td><td>29</td><td>19</td><td>2</td><td>45</td><td>2</td></tr><tr><td>f152b6ee251cca940dd853c54e6a7b78fbc6b235</td><td>affectnet</td><td>AffectNet</td><td><a href="papers/f152b6ee251cca940dd853c54e6a7b78fbc6b235.html">Skybiometry and AffectNet on Facial Emotion Recognition Using Supervised Machine Learning Algorithms</a></td><td><a href="{'url': 'http://dl.acm.org/citation.cfm?id=3232665', 'linkType': 'acm'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>23e824d1dfc33f3780dd18076284f07bd99f1c43</td><td>mifs</td><td>MIFS</td><td><a href="papers/23e824d1dfc33f3780dd18076284f07bd99f1c43.html">Spoofing faces using makeup: An investigative study</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7947686', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)</td><td>edu</td><td>INRIA Méditerranée</td><td>43.61581310</td><td>7.06838000</td><td>20%</td><td>5</td><td>1</td><td>4</td><td>0</td><td>1</td><td>2</td></tr><tr><td>1a40092b493c6b8840257ab7f96051d1a4dbfeb2</td><td>sports_videos_in_the_wild</td><td>SVW</td><td><a href="papers/1a40092b493c6b8840257ab7f96051d1a4dbfeb2.html">Sports Videos in the Wild (SVW): A video dataset for sports analysis</a></td><td><a href="http://web.cse.msu.edu/~liuxm/publication/Safdarnejad_Liu_Udpa_Andrus_Wood_Craven_FG2015.pdf">[pdf]</a></td><td>2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)</td><td>edu</td><td>Michigan State University</td><td>42.71856800</td><td>-84.47791571</td><td>67%</td><td>6</td><td>4</td><td>2</td><td>1</td><td>5</td><td>0</td></tr><tr><td>9361b784e73e9238d5cefbea5ac40d35d1e3103f</td><td>towncenter</td><td>TownCenter</td><td><a href="papers/9361b784e73e9238d5cefbea5ac40d35d1e3103f.html">Stable Multi-Target Tracking in Real-Time Surveillance Video (Preprint)</a></td><td><a href="http://pdfs.semanticscholar.org/9361/b784e73e9238d5cefbea5ac40d35d1e3103f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>21%</td><td>310</td><td>64</td><td>246</td><td>24</td><td>177</td><td>4</td></tr><tr><td>c866a2afc871910e3282fd9498dce4ab20f6a332</td><td>qmul_surv_face</td><td>QMUL-SurvFace</td><td><a href="papers/c866a2afc871910e3282fd9498dce4ab20f6a332.html">Surveillance Face Recognition Challenge</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1804.09691.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f</td><td>pku</td><td>PKU</td><td><a href="papers/f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f.html">Swiss-System Based Cascade Ranking for Gait-Based Person Re-Identification</a></td><td><a href="http://pdfs.semanticscholar.org/f6c8/d5e35d7e4d60a0104f233ac1a3ab757da53f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>3</td><td>0</td><td>3</td><td>0</td><td>1</td><td>0</td></tr><tr><td>4d58f886f5150b2d5e48fd1b5a49e09799bf895d</td><td>texas_3dfrd</td><td>Texas 3DFRD</td><td><a href="papers/4d58f886f5150b2d5e48fd1b5a49e09799bf895d.html">Texas 3D Face Recognition Database</a></td><td><a href="http://live.ece.utexas.edu/publications/2010/sg_ssiai_may10.pdf">[pdf]</a></td><td>2010 IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI)</td><td></td><td></td><td></td><td></td><td>18%</td><td>61</td><td>11</td><td>50</td><td>3</td><td>36</td><td>2</td></tr><tr><td>4d58f886f5150b2d5e48fd1b5a49e09799bf895d</td><td>texas_3dfrd</td><td>Texas 3DFRD</td><td><a href="papers/4d58f886f5150b2d5e48fd1b5a49e09799bf895d.html">Texas 3D Face Recognition Database</a></td><td><a href="http://live.ece.utexas.edu/publications/2010/sg_ssiai_may10.pdf">[pdf]</a></td><td>2010 IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI)</td><td></td><td></td><td></td><td></td><td>18%</td><td>61</td><td>11</td><td>50</td><td>3</td><td>36</td><td>2</td></tr><tr><td>2485c98aa44131d1a2f7d1355b1e372f2bb148ad</td><td>cas_peal</td><td>CAS-PEAL</td><td><a href="papers/2485c98aa44131d1a2f7d1355b1e372f2bb148ad.html">The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations</a></td><td><a href="https://doi.org/10.1109/TSMCA.2007.909557">[pdf]</a></td><td>IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans</td><td></td><td></td><td></td><td></td><td>18%</td><td>415</td><td>76</td><td>339</td><td>39</td><td>182</td><td>35</td></tr><tr><td>2485c98aa44131d1a2f7d1355b1e372f2bb148ad</td><td>m2vts</td><td>m2vts</td><td><a href="papers/2485c98aa44131d1a2f7d1355b1e372f2bb148ad.html">The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations</a></td><td><a href="https://doi.org/10.1109/TSMCA.2007.909557">[pdf]</a></td><td>IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans</td><td></td><td></td><td></td><td></td><td>18%</td><td>415</td><td>76</td><td>339</td><td>39</td><td>182</td><td>35</td></tr><tr><td>47662d1a368daf70ba70ef2d59eb6209f98b675d</td><td>fia</td><td>CMU FiA</td><td><a href="papers/47662d1a368daf70ba70ef2d59eb6209f98b675d.html">The CMU Face In Action (FIA) Database</a></td><td><a href="http://pdfs.semanticscholar.org/bb47/a03401811f9d2ca2da12138697acbc7b97a3.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>29%</td><td>55</td><td>16</td><td>39</td><td>5</td><td>38</td><td>7</td></tr><tr><td>4df3143922bcdf7db78eb91e6b5359d6ada004d2</td><td>cfd</td><td>CFD</td><td><a href="papers/4df3143922bcdf7db78eb91e6b5359d6ada004d2.html">The Chicago face database: A free stimulus set of faces and norming data.</a></td><td><a href="http://pdfs.semanticscholar.org/4df3/143922bcdf7db78eb91e6b5359d6ada004d2.pdf">[pdf]</a></td><td>Behavior research methods</td><td></td><td></td><td></td><td></td><td>39%</td><td>83</td><td>32</td><td>51</td><td>2</td><td>62</td><td>3</td></tr><tr><td>20388099cc415c772926e47bcbbe554e133343d1</td><td>cafe</td><td>CAFE</td><td><a href="papers/20388099cc415c772926e47bcbbe554e133343d1.html">The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults</a></td><td><a href="http://pdfs.semanticscholar.org/2038/8099cc415c772926e47bcbbe554e133343d1.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>48%</td><td>33</td><td>16</td><td>17</td><td>3</td><td>28</td><td>1</td></tr><tr><td>32cde90437ab5a70cf003ea36f66f2de0e24b3ab</td><td>cityscapes</td><td>Cityscapes</td><td><a href="papers/32cde90437ab5a70cf003ea36f66f2de0e24b3ab.html">The Cityscapes Dataset for Semantic Urban Scene Understanding</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1604.01685.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>33%</td><td>771</td><td>252</td><td>519</td><td>54</td><td>622</td><td>0</td></tr><tr><td>32cde90437ab5a70cf003ea36f66f2de0e24b3ab</td><td>cityscapes</td><td>Cityscapes</td><td><a href="papers/32cde90437ab5a70cf003ea36f66f2de0e24b3ab.html">The Cityscapes Dataset for Semantic Urban Scene Understanding</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1604.01685.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td></td><td></td><td></td><td></td><td>33%</td><td>771</td><td>252</td><td>519</td><td>54</td><td>622</td><td>0</td></tr><tr><td>4e6ee936eb50dd032f7138702fa39b7c18ee8907</td><td>dartmouth_children</td><td>Dartmouth Children</td><td><a href="papers/4e6ee936eb50dd032f7138702fa39b7c18ee8907.html">The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set</a></td><td><a href="http://pdfs.semanticscholar.org/4e6e/e936eb50dd032f7138702fa39b7c18ee8907.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>40%</td><td>20</td><td>8</td><td>12</td><td>2</td><td>16</td><td>0</td></tr><tr><td>f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4</td><td>europersons</td><td>EuroCity Persons</td><td><a href="papers/f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4.html">The EuroCity Persons Dataset: A Novel Benchmark for Object Detection</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1805.07193.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td></tr><tr><td>4d9a02d080636e9666c4d1cc438b9893391ec6c7</td><td>cohn_kanade_plus</td><td>CK+</td><td><a href="papers/4d9a02d080636e9666c4d1cc438b9893391ec6c7.html">The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression</a></td><td><a href="http://www.iainm.com/iainm/Publications_files/2010_The%20Extended.pdf">[pdf]</a></td><td>2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops</td><td></td><td></td><td></td><td></td><td>41%</td><td>975</td><td>403</td><td>572</td><td>65</td><td>460</td><td>345</td></tr><tr><td>0c4a139bb87c6743c7905b29a3cfec27a5130652</td><td>feret</td><td>FERET</td><td><a href="papers/0c4a139bb87c6743c7905b29a3cfec27a5130652.html">The FERET Verification Testing Protocol for Face Recognition Algorithms</a></td><td><a href="http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>28%</td><td>112</td><td>31</td><td>81</td><td>12</td><td>76</td><td>4</td></tr><tr><td>0c4a139bb87c6743c7905b29a3cfec27a5130652</td><td>feret</td><td>FERET</td><td><a href="papers/0c4a139bb87c6743c7905b29a3cfec27a5130652.html">The FERET Verification Testing Protocol for Face Recognition Algorithms</a></td><td><a href="http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>28%</td><td>112</td><td>31</td><td>81</td><td>12</td><td>76</td><td>4</td></tr><tr><td>0c4a139bb87c6743c7905b29a3cfec27a5130652</td><td>feret</td><td>FERET</td><td><a href="papers/0c4a139bb87c6743c7905b29a3cfec27a5130652.html">The FERET Verification Testing Protocol for Face Recognition Algorithms</a></td><td><a href="http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>28%</td><td>112</td><td>31</td><td>81</td><td>12</td><td>76</td><td>4</td></tr><tr><td>0c4a139bb87c6743c7905b29a3cfec27a5130652</td><td>feret</td><td>FERET</td><td><a href="papers/0c4a139bb87c6743c7905b29a3cfec27a5130652.html">The FERET Verification Testing Protocol for Face Recognition Algorithms</a></td><td><a href="http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>28%</td><td>112</td><td>31</td><td>81</td><td>12</td><td>76</td><td>4</td></tr><tr><td>8f02ec0be21461fbcedf51d864f944cfc42c875f</td><td>hda_plus</td><td>HDA+</td><td><a href="papers/8f02ec0be21461fbcedf51d864f944cfc42c875f.html">The HDA+ Data Set for Research on Fully Automated Re-identification Systems</a></td><td><a href="http://pdfs.semanticscholar.org/8f02/ec0be21461fbcedf51d864f944cfc42c875f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>12%</td><td>17</td><td>2</td><td>15</td><td>2</td><td>11</td><td>0</td></tr><tr><td>8f02ec0be21461fbcedf51d864f944cfc42c875f</td><td>hda_plus</td><td>HDA+</td><td><a href="papers/8f02ec0be21461fbcedf51d864f944cfc42c875f.html">The HDA+ Data Set for Research on Fully Automated Re-identification Systems</a></td><td><a href="http://pdfs.semanticscholar.org/8f02/ec0be21461fbcedf51d864f944cfc42c875f.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>12%</td><td>17</td><td>2</td><td>15</td><td>2</td><td>11</td><td>0</td></tr><tr><td>ea050801199f98a1c7c1df6769f23f658299a3ae</td><td>mpi_large</td><td>Large MPI Facial Expression</td><td><a href="papers/ea050801199f98a1c7c1df6769f23f658299a3ae.html">The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions</a></td><td><a href="http://pdfs.semanticscholar.org/ea05/0801199f98a1c7c1df6769f23f658299a3ae.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>46%</td><td>28</td><td>13</td><td>15</td><td>4</td><td>24</td><td>3</td></tr><tr><td>ea050801199f98a1c7c1df6769f23f658299a3ae</td><td>mpi_small</td><td>Small MPI Facial Expression</td><td><a href="papers/ea050801199f98a1c7c1df6769f23f658299a3ae.html">The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions</a></td><td><a href="http://pdfs.semanticscholar.org/ea05/0801199f98a1c7c1df6769f23f658299a3ae.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>46%</td><td>28</td><td>13</td><td>15</td><td>4</td><td>24</td><td>3</td></tr><tr><td>f1af714b92372c8e606485a3982eab2f16772ad8</td><td>mug_faces</td><td>MUG Faces</td><td><a href="papers/f1af714b92372c8e606485a3982eab2f16772ad8.html">The MUG facial expression database</a></td><td><a href="http://ieeexplore.ieee.org/document/5617662/">[pdf]</a></td><td>11th International Workshop on Image Analysis for Multimedia Interactive Services WIAMIS 10</td><td>edu</td><td>Aristotle University of Thessaloniki</td><td>40.62984145</td><td>22.95889350</td><td>28%</td><td>68</td><td>19</td><td>49</td><td>5</td><td>28</td><td>19</td></tr><tr><td>79828e6e9f137a583082b8b5a9dfce0c301989b8</td><td>mapillary</td><td>Mapillary</td><td><a href="papers/79828e6e9f137a583082b8b5a9dfce0c301989b8.html">The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8237796', 'linkType': 'ieee'}">[pdf]</a></td><td>2017 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>39%</td><td>44</td><td>17</td><td>27</td><td>0</td><td>36</td><td>0</td></tr><tr><td>96e0cfcd81cdeb8282e29ef9ec9962b125f379b0</td><td>megaface</td><td>MegaFace</td><td><a href="papers/96e0cfcd81cdeb8282e29ef9ec9962b125f379b0.html">The MegaFace Benchmark: 1 Million Faces for Recognition at Scale</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2016.527">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>55%</td><td>121</td><td>66</td><td>55</td><td>11</td><td>98</td><td>20</td></tr><tr><td>96e0cfcd81cdeb8282e29ef9ec9962b125f379b0</td><td>megaface</td><td>MegaFace</td><td><a href="papers/96e0cfcd81cdeb8282e29ef9ec9962b125f379b0.html">The MegaFace Benchmark: 1 Million Faces for Recognition at Scale</a></td><td><a href="http://doi.ieeecomputersociety.org/10.1109/CVPR.2016.527">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>University of Washington</td><td>47.65432380</td><td>-122.30800894</td><td>55%</td><td>121</td><td>66</td><td>55</td><td>11</td><td>98</td><td>20</td></tr><tr><td>a6e695ddd07aad719001c0fc1129328452385949</td><td>yfcc_100m</td><td>YFCC100M</td><td><a href="papers/a6e695ddd07aad719001c0fc1129328452385949.html">The New Data and New Challenges in Multimedia Research</a></td><td><span class="gray">[pdf]</a></td><td>CoRR</td><td></td><td></td><td></td><td></td><td>36%</td><td>160</td><td>57</td><td>103</td><td>11</td><td>105</td><td>4</td></tr><tr><td>abe9f3b91fd26fa1b50cd685c0d20debfb372f73</td><td>voc</td><td>VOC</td><td><a href="papers/abe9f3b91fd26fa1b50cd685c0d20debfb372f73.html">The Pascal Visual Object Classes Challenge: A Retrospective</a></td><td><a href="http://homepages.inf.ed.ac.uk/ckiw/postscript/ijcv_voc14.pdf">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>32%</td><td>999</td><td>315</td><td>684</td><td>75</td><td>698</td><td>6</td></tr><tr><td>66e6f08873325d37e0ec20a4769ce881e04e964e</td><td>sun_attributes</td><td>SUN</td><td><a href="papers/66e6f08873325d37e0ec20a4769ce881e04e964e.html">The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding</a></td><td><a href="http://www.cc.gatech.edu/~hays/papers/attribute_ijcv.pdf">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>38%</td><td>112</td><td>43</td><td>69</td><td>14</td><td>83</td><td>2</td></tr><tr><td>66e6f08873325d37e0ec20a4769ce881e04e964e</td><td>sun_attributes</td><td>SUN</td><td><a href="papers/66e6f08873325d37e0ec20a4769ce881e04e964e.html">The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding</a></td><td><a href="http://www.cc.gatech.edu/~hays/papers/attribute_ijcv.pdf">[pdf]</a></td><td>International Journal of Computer Vision</td><td></td><td></td><td></td><td></td><td>38%</td><td>112</td><td>43</td><td>69</td><td>14</td><td>83</td><td>2</td></tr><tr><td>8b2dd5c61b23ead5ae5508bb8ce808b5ea266730</td><td>10k_US_adult_faces</td><td>10K US Adult Faces</td><td><a href="papers/8b2dd5c61b23ead5ae5508bb8ce808b5ea266730.html">The intrinsic memorability of face photographs.</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/8b2d/d5c61b23ead5ae5508bb8ce808b5ea266730.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Journal of experimental psychology. General</td><td></td><td></td><td></td><td></td><td>36%</td><td>47</td><td>17</td><td>30</td><td>3</td><td>33</td><td>1</td></tr><tr><td>19d1b811df60f86cbd5e04a094b07f32fff7a32a</td><td>york_3d</td><td>UOY 3D Face Database</td><td><a href="papers/19d1b811df60f86cbd5e04a094b07f32fff7a32a.html">Three-dimensional face recognition: an eigensurface approach</a></td><td><a href="http://www-users.cs.york.ac.uk/~nep/research/3Dface/tomh/3DFaceRecognition-Eigensurface-ICIP(web)2.pdf">[pdf]</a></td><td>2004 International Conference on Image Processing, 2004. ICIP '04.</td><td></td><td></td><td></td><td></td><td>19%</td><td>36</td><td>7</td><td>29</td><td>4</td><td>25</td><td>1</td></tr><tr><td>298cbc3dfbbb3a20af4eed97906650a4ea1c29e0</td><td>ferplus</td><td>FER+</td><td><a href="papers/298cbc3dfbbb3a20af4eed97906650a4ea1c29e0.html">Training deep networks for facial expression recognition with crowd-sourced label distribution</a></td><td><a href="http://arxiv.org/pdf/1608.01041v1.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>34%</td><td>29</td><td>10</td><td>19</td><td>0</td><td>15</td><td>3</td></tr><tr><td>b5f2846a506fc417e7da43f6a7679146d99c5e96</td><td>ucf_101</td><td>UCF101</td><td><a href="papers/b5f2846a506fc417e7da43f6a7679146d99c5e96.html">UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1212.0402.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>CoRR</td><td>edu</td><td>University of Central Florida</td><td>28.59899755</td><td>-81.19712501</td><td>54%</td><td>999</td><td>535</td><td>464</td><td>73</td><td>708</td><td>212</td></tr><tr><td>16e8b0a1e8451d5f697b94c0c2b32a00abee1d52</td><td>umb</td><td>UMB</td><td><a href="papers/16e8b0a1e8451d5f697b94c0c2b32a00abee1d52.html">UMB-DB: A database of partially occluded 3D faces</a></td><td><a href="https://doi.org/10.1109/ICCVW.2011.6130509">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>29%</td><td>45</td><td>13</td><td>32</td><td>2</td><td>20</td><td>3</td></tr><tr><td>31b05f65405534a696a847dd19c621b7b8588263</td><td>umd_faces</td><td>UMD</td><td><a href="papers/31b05f65405534a696a847dd19c621b7b8588263.html">UMDFaces: An annotated face dataset for training deep networks</a></td><td><a href="http://arxiv.org/abs/1611.01484">[pdf]</a></td><td>2017 IEEE International Joint Conference on Biometrics (IJCB)</td><td></td><td></td><td></td><td></td><td>54%</td><td>35</td><td>19</td><td>16</td><td>5</td><td>28</td><td>6</td></tr><tr><td>31b05f65405534a696a847dd19c621b7b8588263</td><td>umd_faces</td><td>UMD</td><td><a href="papers/31b05f65405534a696a847dd19c621b7b8588263.html">UMDFaces: An annotated face dataset for training deep networks</a></td><td><a href="http://arxiv.org/abs/1611.01484">[pdf]</a></td><td>2017 IEEE International Joint Conference on Biometrics (IJCB)</td><td></td><td></td><td></td><td></td><td>54%</td><td>35</td><td>19</td><td>16</td><td>5</td><td>28</td><td>6</td></tr><tr><td>8627f019882b024aef92e4eb9355c499c733e5b7</td><td>used</td><td>USED Social Event Dataset</td><td><a href="papers/8627f019882b024aef92e4eb9355c499c733e5b7.html">USED: a large-scale social event detection dataset</a></td><td><a href="http://doi.acm.org/10.1145/2910017.2910624">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>43%</td><td>7</td><td>3</td><td>4</td><td>0</td><td>3</td><td>2</td></tr><tr><td>4b4106614c1d553365bad75d7866bff0de6056ed</td><td>czech_news_agency</td><td>UFI</td><td><a href="papers/4b4106614c1d553365bad75d7866bff0de6056ed.html">Unconstrained Facial Images: Database for Face Recognition Under Real-World Conditions</a></td><td><a href="http://pdfs.semanticscholar.org/4b41/06614c1d553365bad75d7866bff0de6056ed.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>10%</td><td>10</td><td>1</td><td>9</td><td>0</td><td>4</td><td>2</td></tr><tr><td>21d9d0deed16f0ad62a4865e9acf0686f4f15492</td><td>images_of_groups</td><td>Images of Groups</td><td><a href="papers/21d9d0deed16f0ad62a4865e9acf0686f4f15492.html">Understanding images of groups of people</a></td><td><a href="http://amp.ece.cmu.edu/people/Andy/Andy_files/cvpr09.pdf">[pdf]</a></td><td>2009 IEEE Conference on Computer Vision and Pattern Recognition</td><td></td><td></td><td></td><td></td><td>36%</td><td>202</td><td>72</td><td>130</td><td>12</td><td>126</td><td>24</td></tr><tr><td>fd8168f1c50de85bac58a8d328df0a50248b16ae</td><td>nd_2006</td><td>ND-2006</td><td><a href="papers/fd8168f1c50de85bac58a8d328df0a50248b16ae.html">Using a Multi-Instance Enrollment Representation to Improve 3D Face Recognition</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4401928', 'linkType': 'ieee'}">[pdf]</a></td><td>2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems</td><td></td><td></td><td></td><td></td><td>25%</td><td>32</td><td>8</td><td>24</td><td>3</td><td>16</td><td>1</td></tr><tr><td>4563b46d42079242f06567b3f2e2f7a80cb3befe</td><td>vadana</td><td>VADANA</td><td><a href="papers/4563b46d42079242f06567b3f2e2f7a80cb3befe.html">VADANA: A dense dataset for facial image analysis</a></td><td><a href="http://vims.cis.udel.edu/publications/VADANA_BeFIT2011.pdf">[pdf]</a></td><td>2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)</td><td></td><td></td><td></td><td></td><td>19%</td><td>16</td><td>3</td><td>13</td><td>0</td><td>6</td><td>6</td></tr><tr><td>eb027969f9310e0ae941e2adee2d42cdf07d938c</td><td>vgg_faces2</td><td>VGG Face2</td><td><a href="papers/eb027969f9310e0ae941e2adee2d42cdf07d938c.html">VGGFace2: A Dataset for Recognising Faces across Pose and Age</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1710.08092.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)</td><td>edu</td><td>University of Oxford</td><td>51.75345380</td><td>-1.25400997</td><td>38%</td><td>56</td><td>21</td><td>35</td><td>6</td><td>50</td><td>3</td></tr><tr><td>01959ef569f74c286956024866c1d107099199f7</td><td>vqa</td><td>VQA</td><td><a href="papers/01959ef569f74c286956024866c1d107099199f7.html">VQA: Visual Question Answering</a></td><td><a href="http://arxiv.org/pdf/1505.00468v3.pdf">[pdf]</a></td><td>2015 IEEE International Conference on Computer Vision (ICCV)</td><td></td><td></td><td></td><td></td><td>47%</td><td>731</td><td>344</td><td>387</td><td>47</td><td>628</td><td>4</td></tr><tr><td>5194cbd51f9769ab25260446b4fa17204752e799</td><td>violent_flows</td><td>Violent Flows</td><td><a href="papers/5194cbd51f9769ab25260446b4fa17204752e799.html">Violent flows: Real-time detection of violent crowd behavior</a></td><td><a href="http://www.wisdom.weizmann.ac.il/mathusers/kliper/Papers/violent_flows.pdf">[pdf]</a></td><td>2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</td><td></td><td></td><td></td><td></td><td>20%</td><td>83</td><td>17</td><td>66</td><td>6</td><td>42</td><td>2</td></tr><tr><td>066000d44d6691d27202896691f08b27117918b9</td><td>psu</td><td>PSU</td><td><a href="papers/066000d44d6691d27202896691f08b27117918b9.html">Vision-Based Analysis of Small Groups in Pedestrian Crowds</a></td><td><a href="http://vision.cse.psu.edu/publications/pdfs/GeCollinsRubackPAMI2011.pdf">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>18%</td><td>151</td><td>27</td><td>124</td><td>9</td><td>78</td><td>2</td></tr><tr><td>dd65f71dac86e36eecbd3ed225d016c3336b4a13</td><td>families_in_the_wild</td><td>FIW</td><td><a href="papers/dd65f71dac86e36eecbd3ed225d016c3336b4a13.html">Visual Kinship Recognition of Families in the Wild</a></td><td><a href="{'url': 'http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8337841', 'linkType': 'ieee'}">[pdf]</a></td><td>IEEE Transactions on Pattern Analysis and Machine Intelligence</td><td></td><td></td><td></td><td></td><td>67%</td><td>3</td><td>2</td><td>1</td><td>0</td><td>2</td><td>0</td></tr><tr><td>52d7eb0fbc3522434c13cc247549f74bb9609c5d</td><td>wider_face</td><td>WIDER FACE</td><td><a href="papers/52d7eb0fbc3522434c13cc247549f74bb9609c5d.html">WIDER FACE: A Face Detection Benchmark</a></td><td><a href="{'url': 'https://arxiv.org/pdf/1511.06523.pdf', 'linkType': 'arxiv'}">[pdf]</a></td><td>2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</td><td>edu</td><td>Chinese University of Hong Kong</td><td>22.42031295</td><td>114.20788644</td><td>53%</td><td>148</td><td>78</td><td>70</td><td>16</td><td>107</td><td>34</td></tr><tr><td>77c81c13a110a341c140995bedb98101b9e84f7f</td><td>wildtrack</td><td>WildTrack</td><td><a href="papers/77c81c13a110a341c140995bedb98101b9e84f7f.html">WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/fe1c/ec4e4995b8615855572374ae3efc94949105.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>5ad4e9f947c1653c247d418f05dad758a3f9277b</td><td>wlfdb</td><td></td><td><a href="papers/5ad4e9f947c1653c247d418f05dad758a3f9277b.html">WLFDB: Weakly Labeled Face Databases</a></td><td><a href="{'url': 'https://pdfs.semanticscholar.org/5ad4/e9f947c1653c247d418f05dad758a3f9277b.pdf', 'linkType': 's2'}">[pdf]</a></td><td>Unknown</td><td></td><td></td><td></td><td></td><td>0%</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><td>0dc11a37cadda92886c56a6fb5191ded62099c28</td><td>stickmen_family</td><td>We Are Family Stickmen</td><td><a href="papers/0dc11a37cadda92886c56a6fb5191ded62099c28.html">We Are Family: Joint Pose Estimation of Multiple Persons</a></td><td><a href="http://pdfs.semanticscholar.org/0dc1/1a37cadda92886c56a6fb5191ded62099c28.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>44%</td><td>77</td><td>34</td><td>43</td><td>4</td><td>57</td><td>1</td></tr><tr><td>2a75f34663a60ab1b04a0049ed1d14335129e908</td><td>mmi_facial_expression</td><td>MMI Facial Expression Dataset</td><td><a href="papers/2a75f34663a60ab1b04a0049ed1d14335129e908.html">Web-based database for facial expression analysis</a></td><td><a href="http://ibug.doc.ic.ac.uk/media/uploads/documents/PanticEtAl-ICME2005-final.pdf">[pdf]</a></td><td>2005 IEEE International Conference on Multimedia and Expo</td><td></td><td></td><td></td><td></td><td>32%</td><td>440</td><td>142</td><td>298</td><td>44</td><td>258</td><td>82</td></tr><tr><td>9b9bf5e623cb8af7407d2d2d857bc3f1b531c182</td><td>who_goes_there</td><td>WGT</td><td><a href="papers/9b9bf5e623cb8af7407d2d2d857bc3f1b531c182.html">Who goes there?: approaches to mapping facial appearance diversity</a></td><td><a href="http://doi.acm.org/10.1145/2996913.2996997">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>100%</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>a94cae786d515d3450d48267e12ca954aab791c4</td><td>yawdd</td><td>YawDD</td><td><a href="papers/a94cae786d515d3450d48267e12ca954aab791c4.html">YawDD: a yawning detection dataset</a></td><td><a href="http://www.site.uottawa.ca/~shervin/pubs/CogniVue-Dataset-ACM-MMSys2014.pdf">[pdf]</a></td><td></td><td></td><td></td><td></td><td></td><td>0%</td><td>14</td><td>0</td><td>14</td><td>1</td><td>2</td><td>1</td></tr></table></body></html>
\ No newline at end of file diff --git a/scraper/reports/stats/empty_papers.csv b/scraper/reports/stats/empty_papers.csv index 19507314..d0af596c 100644 --- a/scraper/reports/stats/empty_papers.csv +++ b/scraper/reports/stats/empty_papers.csv @@ -1,264 +1,951 @@ +61668aeeb60bd2ede1f9b0873f0e19f6f845a029,The role of image understanding in contour detection,2012 IEEE Conference on Computer Vision and Pattern Recognition,2012
61084a25ebe736e8f6d7a6e53b2c20d9723c4608,Face recognition for web-scale datasets,Computer Vision and Image Understanding,2014
+6128190a8c18cde6b94e0fae934d6fcc406ea0bb,STAIR Captions: Constructing a Large-Scale Japanese Image Caption Dataset,,2017
+619d215c2e80eedcc5a65c00fdcf5852f9cdedf8,Feature selection and classification of imbalanced datasets: Application to PET images of children with autistic spectrum disorders,NeuroImage,2011
+6187f91f1e53cf6f62afe30e01c7b1ed43505c9e,Localizing and Orienting Street Views Using Overhead Imagery,Unknown,2016
+611b1301b3bd13c518d0ec93d695e08b794766f7,When coding meets ranking: A joint framework based on local learning,CoRR,2014
+0d3d290e93ac76d5ef2d6c8bbced79fb3101ad36,Conditional Adversarial Synthesis of 3D Facial Action Units,CoRR,2018
+0deca8c53adcc13d8da72050d9a4b638da52264b,"A Comprehensive Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets",CoRR,2016
+0dc11a37cadda92886c56a6fb5191ded62099c28,We Are Family: Joint Pose Estimation of Multiple Persons,,2010
0d467adaf936b112f570970c5210bdb3c626a717,"""FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks""",,2016
+0d4fce2853a867e055a0062c2ef2f8accfc623f3,Snap2Play: A Mixed-Reality Game Based on Scene Identification,,2008
0db8e6eb861ed9a70305c1839eaef34f2c85bbaf,Towards Large-Pose Face Frontalization in the Wild,2017 IEEE International Conference on Computer Vision (ICCV),2017
+0d902541c26f03ff95221e0e71d67c39e094a61d,Multivariate Time-Series Classification Using the Hidden-Unit Logistic Model,IEEE Transactions on Neural Networks and Learning Systems,2018
0dbf4232fcbd52eb4599dc0760b18fcc1e9546e9,Early facial expression recognition using early RankBoost,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+0d555309828e4c31b79bbdea55066ac175720f86,Homeomorphic Manifold Analysis (HMA): Generalized separation of style and content on manifolds,Image Vision Comput.,2013
0d087aaa6e2753099789cd9943495fbbd08437c0,Folded Recurrent Neural Networks for Future Video Prediction,CoRR,2017
0d8415a56660d3969449e77095be46ef0254a448,Nonlinear Discriminant Analysis on Embedded Manifold,IEEE Transactions on Circuits and Systems for Video Technology,2007
+0d232056ee26b5da9b6b0658be12053a76484d2b,Hierarchical Spatial Sum-Product Networks for Action Recognition in Still Images,IEEE Trans. Circuits Syst. Video Techn.,2018
+0d028a924d8fce70d9fc42daecf77eb7caea67d8,Auxiliary Training Information Assisted Visual Recognition,IPSJ Trans. Computer Vision and Applications,2015
0d735e7552af0d1dcd856a8740401916e54b7eee,EMPATH: a neural network that categorizes facial expressions.,Journal of cognitive neuroscience,2002
0d06b3a4132d8a2effed115a89617e0a702c957a,Achieving stable subspace clustering by post-processing generic clustering results,2016 International Joint Conference on Neural Networks (IJCNN),2016
0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e,Large Age-Gap face verification by feature injection in deep networks,Pattern Recognition Letters,2017
+95ed9e883b6321658b95a8db28d0704e90973a9d,Improving Image Annotation via Ranking-Oriented Neighbor Search and Learning-Based Keyword Propagation,,2013
+9594cc518db7890c3f20073525e9a335b2049e02,Semantic Visual Localization,CoRR,2017
+95704293fcaa01473e5c0b389d8afdcc0178d8c7,Accurate Human Detection by Appearance and Motion,IEICE Transactions,2010
+95f7dc555d6ee4deaf3e30d4ed4c8a806bccb424,Feature space locality constraint for kernel based nonlinear discriminant analysis,Pattern Recognition,2012
+952283f21ab30a1026b26911c160433ca147bf8c,Affective Facial Expression Processing via Simulation: A Probabilistic Model,CoRR,2014
+95c5908d856010aa9836a4f1a6cebf3828bcb9f6,3D Shape Reconstruction from 2D Landmarks: A Convex Formulation,CoRR,2014
+59cdafed4eeb8ff7c9bb2d4ecd0edeb8a361ffc1,"International Journal of Computer Application Issue 2, Volume 3 (june 2012) Issn: 2250-1797",,2012
+59a76bab968ac4cd740eb376ce9a26f6c1b103e4,People Re-Identification with Local Distance Comparison Using Learned Metric,IEICE Transactions,2014
590628a9584e500f3e7f349ba7e2046c8c273fcf,Generating Natural Questions About an Image,CoRR,2016
+5996e84f482b7335cdb08ca218d450d37501e182,A Game-Theoretic Approach to Hypergraph Clustering,IEEE Transactions on Pattern Analysis and Machine Intelligence,2009
+5991f26b871c8fd8f675c11e44c445e3cebfbe7d,Field Studies with Multimedia Big Data: Opportunities and Challenges (Extended Ver,CoRR,2017
+92cc2cecbf065c4b55a3bceb0d9e475fcd70f8c7,Detection of social events in streams of social multimedia,International Journal of Multimedia Information Retrieval,2015
+9214e71ca44d87a9f43ba719f411d5307d78fc4a,Face recognition under varying illuminations using logarithmic fractal dimension-based complete eight local directional patterns,Neurocomputing,2016
+9209095ac450f14c603582ac01692b0f11c9c33b,Usability Test of Exercise Games Designed for Rehabilitation of Elderly Patients After Hip Replacement Surgery: Pilot Study,,2017
92fada7564d572b72fd3be09ea3c39373df3e27c,Feature selection in the independent component subspace for face recognition,Pattern Recognition Letters,2004
+929218b75858e244c1ca99a6bec07ed9465737c7,Multi-voxel pattern analysis of fMRI data predicts clinical symptom severity,NeuroImage,2011
+0c06d6e0336f6cb6c80beb445ec5fec51b5c735d,Novel coarse-to-fine dual scale technique for tuberculosis cavity detection in chest radiographs,EURASIP J. Image and Video Processing,2013
+0c41e4e699bd4f64d744ad0bc820ab20da367499,Neighborhood Discriminant Projection for Face Recognition,18th International Conference on Pattern Recognition (ICPR'06),2006
+0c1f066a2246fd8d817318e3081f6fe3589f42ea,Cortical 3D Face Recognition Framework,,2011
+0cc2dd2900339836e6d42f2cb0e542bbe5627454,Learning for Real-World Image Applications,,2012
0cccf576050f493c8b8fec9ee0238277c0cfd69a,Incremental Tube Construction for Human Action Detection,CoRR,2017
+0c4a139bb87c6743c7905b29a3cfec27a5130652,The FERET Verification Testing Protocol for Face Recognition Algorithms,,1998
+0c642068ff8e4a437f8c16656b08d1ce3c47d59b,"Development of high-speed and real-time vision platform, H3 vision",,2009
+0ca2304166acc90c3ffb5934f9a6343aeb80bd03,Supervised methods for detection and segmentation of tissues in clinical lumbar MRI,Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society,2014
+0cbe9732bc80761d7770e952275d5757b1acaea2,Transfer metric learning for action similarity using high-level semantics,Pattern Recognition Letters,2016
+0cb7a27177a782a091916bca3d8edb02f88577b5,Contour based object detection using part bundles,Computer vision and image understanding : CVIU,2010
+0cc22d1dab50d9bab9501008e9b359cd9e51872a,SuperParsing: Scalable Nonparametric Image Parsing with Superpixels,,2010
0c54e9ac43d2d3bab1543c43ee137fc47b77276e,Spontaneous subtle expression detection and recognition based on facial strain,Sig. Proc.: Image Comm.,2016
+0c7608a158207052e0d615cd86d886a50d1f33da,Designing various multivariate analysis at will via generalized pairwise expression ∗,,2012
+0c166b1e5ae46c157301da4965a453295ec85658,Adaptive appearance model tracking for still-to-video face recognition,Pattern Recognition,2016
+0cd79b2193ef5086fe17f621a449ef3d67f5b3c4,Pose sentences: A new representation for action recognition using sequence of pose words,2008 19th International Conference on Pattern Recognition,2008
0c60eebe10b56dbffe66bb3812793dd514865935,Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks,IEEE Transactions on Pattern Analysis and Machine Intelligence,2018
+661bf7aa2de455f966f114d900f92a43f973ae49,"The New Modality: Emoji Challenges in Prediction, Anticipation, and Retrieval",CoRR,2018
+66af0fb424e4bc07cc28e08c7bf3a8b70c094d60,Facial feature detection using distance vector fields,Pattern Recognition,2009
+66759e18b1a1d53178fc79d8275e301e4d2f4ee8,Visualizing Support Vectors and topological data mapping for improved generalization capabilities,The 2010 International Joint Conference on Neural Networks (IJCNN),2010
66886997988358847615375ba7d6e9eb0f1bb27f,Prototype-Based Discriminative Feature Learning for Kinship Verification,IEEE Transactions on Cybernetics,2015
66837add89caffd9c91430820f49adb5d3f40930,"A New Face Recognition Method using PCA , LDA and Neural Network",Unknown,2012
+6623d8efb11bdca7348249c357902a5527a71e84,A new descriptor of gradients Self-Similarity for smile detection in unconstrained scenarios,Neurocomputing,2016
+66313d48a6352e731e40450f80a66c64aabae817,Exploring new representations and applications for motion analysis,,2009
3ee7a8107a805370b296a53e355d111118e96b7c,Bayesian Learning of Sparse Gaussian Graphical Models,,2011
+3e1aa21ab4a5c242f54f23fbbeb5da29f9a965a6,FiLM: Visual Reasoning with a General Conditioning Layer,CoRR,2017
+3e1d799e5b7d5bd7e0d3b3bffb292878d27c5b7e,Adversarial-Playground: A Visualization Suite for Adversarial Sample Generation,CoRR,2017
+3ec05713a1eed6fa9b57fef718f369f68bbbe09f,Wildlife recognition in nature documentaries with weak supervision from subtitles and external data,Pattern Recognition Letters,2016
+3ee096aff93ab9a2374cdde06973db1996331d86,Artistic Style Transfer for Videos,,2016
+3ec5afaee732157a1039d25b953aec38bc151638,Distributed Submodular Maximization,Journal of Machine Learning Research,2016
+3ea3bbdc9aedd24fe0b5122e04b1d59e7e14135c,Mastering the Dungeon: Grounded Language Learning by Mechanical Turker Descent,CoRR,2017
+3eaa860f2735fce8b839237397455c13dfad1ed1,Dynamic belief fusion for object detection,2016 IEEE Winter Conference on Applications of Computer Vision (WACV),2016
+3e01f0bac3d5df0744caf8f42ae189e113d0758d,Structured learning for detection of social groups in crowd,2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance,2013
+3e7f54801c886ea2061650fd24fc481e39be152f,Towards Viewpoint Invariant 3D Human Pose Estimation,,2016
+3edc43e336be075dca77c7e173b555b6c14274d8,Travelmedia: An intelligent management system for media captured in travel,J. Visual Communication and Image Representation,2011
+3e734cc79496091e8b08df8d781d005651885c38,Object Recognition Using Deep Neural Networks: A Survey,CoRR,2014
+3ea27ba44a3e8a13148236807e569b909517ed89,Visual Route Recognition with a Handful of Bits,,2012
+50f7d3faeeaca41748df4b8fd1187712add72bb4,"Global consistency, local sparsity and pixel correlation: A unified framework for face hallucination",Pattern Recognition,2014
500b92578e4deff98ce20e6017124e6d2053b451,Incremental Face Alignment in the Wild,2014 IEEE Conference on Computer Vision and Pattern Recognition,2014
+500ddabbfa3bb1064b6250cdd3d5fe207f7aed67,Towards Improved Cartoon Face Detection and Recognition Systems,CoRR,2018
+50bcbdcd9a21b88c2c3e640894081d1e225a5b80,Human Computing and Machine Understanding of Human Behavior: A Survey,,2006
+50a4a7725ee35124cca4e72a52bdf71f5088faf2,Trinary-Projection Trees for Approximate Nearest Neighbor Search,IEEE Transactions on Pattern Analysis and Machine Intelligence,2013
+50bada01c37daf2ed11350b4b0d2be28d9bafd0a,A MAP approach to landmarking,,2007
+506e76681d02dc3a3748e326fb57c4e4ab66778e,Predicting Functional Regions of Objects,,2013
68a3f12382003bc714c51c85fb6d0557dcb15467,Learning the Visual Interpretation of Sentences,2013 IEEE International Conference on Computer Vision,2013
+68bf7fc874c2db44d0446cdbb1e05f19c2239282,Fast Kernel Matrix Computation for Big Data Clustering,,2015
68cf263a17862e4dd3547f7ecc863b2dc53320d8,A comparative study on illumination preprocessing in face recognition,Pattern Recognition,2013
+6880f27e9fef716b0a67d0da37104e5f767bf5dc,Improving object localization using macrofeature layout selection,2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops),2011
68bf34e383092eb827dd6a61e9b362fcba36a83a,"Multi-view, High-resolution Face Image Analysis",,2014
+68150d92e2ca3141ff3f4ab3d770e07f6ca13961,Using a Discrete Hidden Markov Model Kernel for lip-based biometric identification,Image Vision Comput.,2014
+68dd150767f947a596d347afdba5ef76c350f9c7,Multi-view fast object detection by using extended haar filters in uncontrolled environments,Pattern Recognition Letters,2012
+6801c8ea1fcb2f76799234a9a81c6199dd61b24c,Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise Relations,,2014
+68aea17b80e7e98245a8717cbce01bc229b0f175,Hand Pose Estimation through Weakly-Supervised Learning of a Rich Intermediate Representation,CoRR,2015
+68c586e81f593904221598f7ababb97570dbfe63,An improved collaborative representation based classification with regularized least square (CRC-RLS) method for robust face recognition,Neurocomputing,2016
574751dbb53777101502419127ba8209562c4758,Gender classification from unaligned facial images using support subspaces,Inf. Sci.,2013
+57fe081950f21ca03b5b375ae3e84b399c015861,Adaptive Image Sampling and Windows Classification for On–board Pedestrian Detection,,2007
57b8b28f8748d998951b5a863ff1bfd7ca4ae6a5,Symmetry-Aware Mesh Segmentation into Uniform Overlapping Patches (Supplementary Material),,2016
+57c929b6f30eec954dc5f17a52fbce290d8e3ca9,Performance characterization in computer vision: A guide to best practices,Computer Vision and Image Understanding,2008
57101b29680208cfedf041d13198299e2d396314,Oxytocin differentially modulates eye gaze to naturalistic social signals of happiness and anger.,Psychoneuroendocrinology,2013
57893403f543db75d1f4e7355283bdca11f3ab1b,A Dynamic Texture-Based Approach to Recognition of Facial Actions and Their Temporal Models,IEEE Transactions on Pattern Analysis and Machine Intelligence,2010
+57cf990bb3d64668614787708efa7cb06d548d06,Learning representations for object classification using multi-stage optimal component analysis,Neural networks : the official journal of the International Neural Network Society,2008
5721216f2163d026e90d7cd9942aeb4bebc92334,Objective Micro-Facial Movement Detection Using FACS-Based Regions and Baseline Evaluation,CoRR,2016
+574f05ab2f135fad33ccbde85debdd12bb41bc87,Proposal-free Network for Instance-level Object Segmentation,CoRR,2015
5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725,Merging Pose Estimates Across Space and Time,,2013
+578e755e669caee147964f9412c23943cd0f0789,"l2, 1 Regularized correntropy for robust feature selection",,2012
+57ce2a7078dbd8e98266270e1c3c78e71c7c9bd3,Disinhibited reactive attachment disorder symptoms impair social judgements from faces.,Psychiatry research,2014
3b1260d78885e872cf2223f2c6f3d6f6ea254204,Face Tracking and Recognition at a Distance: A Coaxial & Concentric PTZ Camera System,,2011
+3b9eaf8d913f99adeb9192f68808efb7d2c0fac5,A Statistical Multiresolution Approach for Face Recognition Using Structural Hidden Markov Models,EURASIP J. Adv. Sig. Proc.,2008
3b80bf5a69a1b0089192d73fa3ace2fbb52a4ad5,"""Magic Mirror in my Hand, what is the Sentiment in the Lens?"": an Action Unit based Approach for Mining Sentiments from Multimedia Contents",,2014
+3b6d7df0cc0aebb0736f3664da4ea8a03e559db9,Manifold-based Similarity Adaptation for Label Propagation,,2013
+3bd8f6577bd4dab492f9a0836bee1d99e461f028,Reduced GABAA receptors and benzodiazepine binding sites in the posterior cingulate cortex and fusiform gyrus in autism.,Brain research,2011
3be7b7eb11714e6191dd301a696c734e8d07435f,Capturing the Visual Language of Social Media Exploiting Web Image Search for User Interest Profiling,,2015
+3be8a8ddb40399f1b0c02156440167152f8b0cba,"Autism : A Review of Biological Bases , Assessment , and Intervention",Unknown,2008
+6f07560cb2ad1d15746df6da0f992601c7bb8815,Determining the best suited semantic events for cognitive surveillance,Expert Syst. Appl.,2011
6f2dc51d607f491dbe6338711c073620c85351ac,Capturing correlations of local features for image representation,Neurocomputing,2016
6f75697a86d23d12a14be5466a41e5a7ffb79fad,Recognition and intensity estimation of facial expression using ensemble classifiers,2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS),2016
+6f0dd01fd7cac346a82618982dd81516387079de,Illumination compensation and normalization in eigenspace-based face recognition: A comparative study of different pre-processing approaches,Pattern Recognition Letters,2008
+03a6cc09984669e3e85c779363a93ae7c7b5f124,Dense 3D Face Correspondence,IEEE transactions on pattern analysis and machine intelligence,2017
03d9ccce3e1b4d42d234dba1856a9e1b28977640,"Facial Affect ""In-the-Wild"": A Survey and a New Database",,2016
+033998b0ac8dd5b86693bd0d27cd3daa00459c17,tartle modulation in autism: Positive affective stimuli enhance startle response,,2009
+0391dca8171f52015eba4fb0e4be3be071950fc9,Computational Paradigm to Elucidate the Effects of Arts-Based Approaches and Interventions: Individual and Collective Emerging Behaviors in Artwork Construction,,2015
+036839afdfe7ae59bfcddd22d2c688b03bef3bee,Learning Hough regression models via bridge partial least squares for object detection,Neurocomputing,2015
+03e6b8f173012cc2e1410404f9c3bb97e0881c00,The effects of Pose on Facial Expression Recognition,,2009
+031497b0061f4536eb431545af69161d3a2b2d42,Image restoration using online photo collections,2009 IEEE 12th International Conference on Computer Vision,2009
03104f9e0586e43611f648af1132064cadc5cc07,Subspace clustering using a symmetric low-rank representation,Knowl.-Based Syst.,2017
0334cc0374d9ead3dc69db4816d08c917316c6c4,Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition,CoRR,2017
+031c721ce468a136b9bac87da7274229e7b967b0,Autism and the development of face processing.,Clinical neuroscience research,2006
03e88bf3c5ddd44ebf0e580d4bd63072566613ad,How intelligent are convolutional neural networks?,CoRR,2017
+0390e80ffde8a6e6cd544c6b91b19ec747c73637,Fast Estimation of Approximate Matrix Ranks Using Spectral Densities,Neural computation,2017
+03b149f6ae3e366fb45ec09e0350b55cf5ac0459,Associative hierarchical CRFs for object class image segmentation,2009 IEEE 12th International Conference on Computer Vision,2009
+034c2ed71c31cb0d984d66c7ca753ef2cb6196ca,Feature learning via partial differential equation with applications to face recognition,Pattern Recognition,2017
+9b2c813a94cee031325b3e76e20db7072063549f,A scalable and flexible framework for smart video surveillance,Computer Vision and Image Understanding,2016
+9b7884c7522fbd8ea52234a2c1bc1454a81f7426,Accurate Iris Recognition At-a-distance and Under Less Constrained Environments,,2014
9b000ccc04a2605f6aab867097ebf7001a52b459,PCANet: An energy perspective,CoRR,2016
9bc01fa9400c231e41e6a72ec509d76ca797207c,Emotion Classification using Adaptive SVMs,Unknown,2012
+9b7a41215af8950ac8cc791aba4a90e5eb908836,A new perspective to null linear discriminant analysis method and its fast implementation using random matrix multiplication with scatter matrices,Pattern Recognition,2012
+9bec10a2dfa925259470843058aa9ea5fe7004fd,Application of BW-ELM model on traffic sign recognition,Neurocomputing,2014
+9b976f7bfa636d89510fe5ad7fb7a8057b86a57f,Feature encoding in band-limited distributed surveillance systems,"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",2017
+9baf0509f63a3322d127ae4374aa5b0f9d5439b8,Two Birds with One Stone: Transforming and Generating Facial Images with Iterative GAN,,2017
+9b4532181847d2a28c059e3c07a45c4ee8452cc6,Statistical Learning for Multimedia Information Retrieval and Their Applications Approved by Supervising,,2008
+9e36963aba45f76b9ee5056a92f1cc10894f7a77,Multi-dimensional subspace based feature selection for face recognition,,2010
+9ea992f009492888c482d5f4006281eaa8b758e7,"X2Face: A Network for Controlling Face Generation Using Images, Audio, and Pose Codes",Unknown,2018
9e5c2d85a1caed701b68ddf6f239f3ff941bb707,Facial Expression Recognition Based on Significant Face Components Using Steerable Pyramid Transform,,2013
04bb3fa0824d255b01e9db4946ead9f856cc0b59,Maximum A Posteriori Estimation of Distances Between Deep Features in Still-to-Video Face Recognition,CoRR,2017
+04b194d6358957e5a48b3e33a0738de59cf7cccf,Detecting Violent Crowds using Temporal Analysis of GLCM Texture,CoRR,2016
+0416f5d1564d1f2a597acac04e81b02b2eff67d2,A High Performance CRF Model for Clothes Parsing,,2014
+04e7a4ff6635552183e6a07b4ba7b415986b758b,3D face recognition using topographic high-order derivatives,2013 IEEE International Conference on Image Processing,2013
+04a1f6d15815957562932f030ce7590521a27763,"Autism, oxytocin and interoception",,2014
+042e83c87d9cd16eb2309d08b71ad955fc8a65d1,Probing short-term face memory in developmental prosopagnosia.,Cortex; a journal devoted to the study of the nervous system and behavior,2015
+049584922a6bb15ceb25fa1f771f834b9befbcae,Beyond visual features: A weak semantic image representation using exemplar classifiers for classification,Neurocomputing,2013
04470861408d14cc860f24e73d93b3bb476492d0,Face Recognition using Features Combination and a New Non-linear Kernel,,2011
+044ca9f2194aca3cef7fbc6b94eb9857819a17be,Synthetic on-line signature generation. Part I: Methodology and algorithms,Pattern Recognition,2012
+04072a097a2ac6a0ee9132bb61bc95bd68bb0621,Non-Linear Subspace Clustering with Learned Low-Rank Kernels,,2017
+042daa253452d0e7e4b5920f5d56b3c7d8d7507b,Tracking Randomly Moving Objects on Edge Box Proposals,CoRR,2015
+04c6810b810f0e06f68954efb937a28de506aa43,Inferring tracklets for multi-object tracking,CVPR 2011 WORKSHOPS,2011
04250e037dce3a438d8f49a4400566457190f4e2,A direct LDA algorithm for high-dimensional data - with application to face recognition,Pattern Recognition,2001
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+04d3299b91413aef9b412deace3da92409cd6639,"The effects of age, sex, and hormones on emotional conflict-related brain response during adolescence.",Brain and cognition,2015
+6aeee62bd32ebc3c5349689f9e4283afe8d162b4,Vs-star: A visual interpretation system for visual surveillance,Pattern Recognition Letters,2010
6ad107c08ac018bfc6ab31ec92c8a4b234f67d49,Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors,CoRR,2018
6a184f111d26787703f05ce1507eef5705fdda83,Mu desynchronization during observation and execution of facial expressions in 30-month-old children,,2016
+6a4f694b028b3d8392cbb185a34e49a657245265,IAIR-CarPed: A psychophysically annotated dataset with fine-grained and layered semantic labels for object recognition,Pattern Recognition Letters,2012
+6a0279c043eadaa09b5b486593c0f2f4f68adeb0,Monocular human pose tracking using multi frame part dynamics,2009 Workshop on Motion and Video Computing (WMVC),2009
6aa43f673cc42ed2fa351cbc188408b724cb8d50,Field Studies with Multimedia Big Data: Opportunities and Challenges (Extended Ver,CoRR,2017
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+6a203565275610eac73461438f4cff1a35d5075c,Abnormal behavior detection using hybrid agents in crowded scenes,Pattern Recognition Letters,2014
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6a1beb34a2dfcdf36ae3c16811f1aef6e64abff2,Cardiac vagal tone predicts inhibited attention to fearful faces.,Emotion,2012
+32ffc4f2665f0061b556f60c4db0f3f5999ef004,Guided saccades modulate face- and body-sensitive activation in the occipitotemporal cortex during social perception.,Brain and cognition,2008
+32d555faaaa0a6f6f9dfc9263e4dba75a38c3193,Sparse discriminative multi-manifold embedding for one-sample face identification,Pattern Recognition,2016
+32510e7f88bc0767fbbc811397ba068dbc4cf549,Boosted Multiple Deformable Trees for Parsing Human Poses,,2007
+32bdafb45d38f7743dd5cd3ca4173beda7bdacc1,A two-layer Conditional Random Field for the classification of partially occluded objects,CoRR,2013
32b8c9fd4e3f44c371960eb0074b42515f318ee7,Learning Human Pose Models from Synthesized Data for Robust RGB-D Action Recognition,CoRR,2017
+32d072ce790b62750fbe343d9dd8620939d84975,Improvements to Frank-Wolfe optimization for multi-detector multi-object tracking,CoRR,2017
+32a336e2a99eb113eeba7cbf622b463cd46d3138,A mid-level video representation based on binary descriptors: A case study for pornography detection,Neurocomputing,2016
+32ea1ed0155cd7d68eac5719693328620fd308f2,Contributions to Object Detection and Human Action Recognition,,2010
+3261a6ca620845566a61ebd0205dfb75d1c0d0f8,Learning visual biases from human imagination,,2015
+3291aff20c171927eed7896eba659ce599ccb666,F-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation,CoRR,2015
+35b6a0d001de8d58d2bcf5dfe8922d59576a87e2,Faces of Pain: Automated Measurement of Spontaneous Facial Expressions of Genuine and Posed Pain,,2007
+351550aa56b81de2eef4b8379dc85722366635dd,Mobile Biometry (mobio) Face and Speaker Verification Evaluation,,2010
+352fa54953cfe0da7f1547bc6fdc43e0e53595cd,General multivariate linear modeling of surface shapes using SurfStat,NeuroImage,2010
357963a46dfc150670061dbc23da6ba7d6da786e,Online Regression with Model Selection,,2018
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35f1bcff4552632419742bbb6e1927ef5e998eb4,Unsupervised Visual-Linguistic Reference Resolution in Instructional Videos,2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017
+3554ed270f27f8c3d6f8d847f6c6b2c17a9668dd,Validating and Extending Semantic Knowledge Bases using Video Games with a Purpose,,2014
35c973dba6e1225196566200cfafa150dd231fa8,A graphical model based solution to the facial feature point tracking problem,Image Vision Comput.,2011
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+351158e4481e3197bd63acdafd73a5df8336143b,Measuring Gender Bias in News Images,,2015
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697b0b9630213ca08a1ae1d459fabc13325bdcbb,Learning to Invert Local Binary Patterns,,2016
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+69da91e45d74db80e8eb436db31d384f5322c1b6,Multi-Scale Gabor Feature Based Eye Localization,,2007
69de532d93ad8099f4d4902c4cad28db958adfea,Face Attention Network: An Effective Face Detector for the Occluded Faces,CoRR,2017
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69a9da55bd20ce4b83e1680fbc6be2c976067631,"""Here's looking at you, kid"". Detecting people looking at each other in videos",,2011
+69026120a20aafa64bed9fd3beccf546758642f8,3D face reconstructions from photometric stereo using near infrared and visible light,Computer Vision and Image Understanding,2010
6974449ce544dc208b8cc88b606b03d95c8fd368,Local Evidence Aggregation for Regression-Based Facial Point Detection,IEEE Transactions on Pattern Analysis and Machine Intelligence,2013
+696ca58d93f6404fea0fc75c62d1d7b378f47628,Microsoft COCO Captions: Data Collection and Evaluation Server,CoRR,2015
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3c03d95084ccbe7bf44b6d54151625c68f6e74d0,Contextual constraints based linear discriminant analysis,Pattern Recognition Letters,2011
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+3cdb1364c3e66443e1c2182474d44b2fb01cd584,SegNet: A Deep Convolutional Encoder-Decoder Architecture for Scene Segmentation,,2016
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+3ce0cecc16b49385d8d45044bef44a66e08b08bc,Multi-algorithm fusion with template protection,"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems",2009
3cb64217ca2127445270000141cfa2959c84d9e7,Can body expressions contribute to automatic depression analysis?,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
3cd5da596060819e2b156e8b3a28331ef633036b,Dynamic composite faces are processed holistically,Vision Research,2015
+3cb1f4c1650f7e55b78abba5a00b56a90b8e0567,sTrack: Secure Tracking in Community Surveillance,,2014
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+56662bb8a29e7d0064a35fb38cbabaef4578f3e0,DeepCAMP: Deep Convolutional Action&Attribute Mid-Level Patterns,,2016
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51528cdce7a92835657c0a616c0806594de7513b,Visual Comparison of Images Using Multiple Kernel Learning for Ranking,,2015
+516c59a82888f9b401db596ff067a0e4f9bf3db3,Comparing and combining depth and texture cues for face recognition,Image Vision Comput.,2005
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+51673c4e2f92c04245c94b2b77065239b6a4922b,Tracking Gaze and Visual Focus of Attention of People Involved in Social Interaction,CoRR,2017
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51dc127f29d1bb076d97f515dca4cc42dda3d25b,3D Corpus of Spontaneous Complex Mental States,,2011
3db75962857a602cae65f60f202d311eb4627b41,Deep Embedding Network for Clustering,2014 22nd International Conference on Pattern Recognition,2014
+3dbae414346398645001197a1d1ce37f5953aeae,Minimal Support Vector Machine,CoRR,2018
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3dc522a6576c3475e4a166377cbbf4ba389c041f,The iNaturalist Challenge 2017 Dataset,CoRR,2017
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3d6ee995bc2f3e0f217c053368df659a5d14d5b5,Learning a Two-Dimensional Fuzzy Discriminant Locality Preserving Subspace for Visual Recognition,IEICE Transactions,2014
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3d6943f1573f992d6897489b73ec46df983d776c,Unifying Low-Rank Models for Visual Learning,,2015
+3d1c9151929aece2c0cec96aa77f7d6ad30afbc9,Cross-architecture prediction based scheduling for energy efficient execution on single-ISA heterogeneous chip-multiprocessors,Microprocessors and Microsystems - Embedded Hardware Design,2015
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5859774103306113707db02fe2dd3ac9f91f1b9e,"Generalization to Novel Views: Universal, Class-based, and Model-based Processing",International Journal of Computer Vision,1998
5850aab97e1709b45ac26bb7d205e2accc798a87,Multimodal learning for facial expression recognition,Pattern Recognition,2015
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58cb1414095f5eb6a8c6843326a6653403a0ee17,Face recognition using multiple facial features,Pattern Recognition Letters,2007
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677477e6d2ba5b99633aee3d60e77026fb0b9306,Multi-View Dynamic Facial Action Unit Detection,CoRR,2017
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679b72d23a9cfca8a7fe14f1d488363f2139265f,A New Approach to Face Recognition Using Dual Dimension Reduction,Unknown,2006
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67a50752358d5d287c2b55e7a45cc39be47bf7d0,Correction: Low-Rank and Eigenface Based Sparse Representation for Face Recognition,,2015
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+67dca5503eb4068c6ed5be34b7488a4aad6686a2,Development of an Efficient Face Recognition System Based on Linear and Nonlinear Algorithms,,2017
+6709e3b3b860ddda5f79b30a0bb6080c6b747816,Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols,,2017
+67a496908ff624d0e8d8ac2412231c53f1424d59,Motion perception induced by dynamic grouping: A probe for the compositional structure of objects,Vision Research,2012
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+0b64351566cc0145ef9c963edcafe8229fcb1fd5,Robust Distance Metric Learning with Auxiliary Knowledge,,2009
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0ba64f4157d80720883a96a73e8d6a5f5b9f1d9b,Convolutional Point-set Representation: A Convolutional Bridge Between a Densely Annotated Image and 3D Face Alignment,,2018
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0ba99a709cd34654ac296418a4f41a9543928149,Image Clustering Using Local Discriminant Models and Global Integration,IEEE Transactions on Image Processing,2010
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0b3f354e6796ef7416bf6dde9e0779b2fcfabed2,Color Face Recognition using Quaternionic Gabor Filters,,2005
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+93d80d544b5e5e5f84605b29f3fdb9b502f2e99b,Localization and Object Recognition for Mobile Robots,,2010
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+9329523dc0bd4e2896d5f63cf2440f21b7a16f16,"Do They All Look the Same? Deciphering Chinese, Japanese and Koreans by Fine-Grained Deep Learning",CoRR,2016
+93a93ee535980ee30e3a5e473a37d89ecb20c4a7,Feature-based affine-invariant detection and localization of faces,,2004
+94a7c97d1e3eb5dbfb20b180780451486597a9be,Facial attributes for active authentication on mobile devices,Image Vision Comput.,2017
94aa8a3787385b13ee7c4fdd2b2b2a574ffcbd81,Real-time generic face tracking in the wild with CUDA,,2014
94325522c9be8224970f810554611d6a73877c13,Comparator Networks,CoRR,2018
+94f74c6314ffd02db581e8e887b5fd81ce288dbf,A Light CNN for Deep Face Representation with Noisy Labels,,2015
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94ac3008bf6be6be6b0f5140a0bea738d4c75579,Accelerating Convolutional Neural Networks for Continuous Mobile Vision via Cache Reuse,CoRR,2017
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+0ea53c86d24b1b80389eefaf0a84fb9b2108b795,Extracting Human Body based on Background Estimation in Modified HLS Color Space,,2009
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0e8760fc198a7e7c9f4193478c0e0700950a86cd,"Brute-Force Facial Landmark Analysis With A 140, 000-Way Classifier",CoRR,2018
0e3840ea3227851aaf4633133dd3cbf9bbe89e5b,ChaLearn Looking at People: Events and Resources,CoRR,2017
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+0e181a1b4c63143466c9ac858d46491f1ad11092,A Track Creation and Deletion Framework for Long-Term Online Multi-Face Tracking,,2012
6080f26675e44f692dd722b61905af71c5260af8,Descriptor transition tables for object retrieval using unconstrained cluttered video acquired using a consumer level handheld mobile device,2016 International Joint Conference on Neural Networks (IJCNN),2016
60d765f2c0a1a674b68bee845f6c02741a49b44e,An efficient illumination normalization method for face recognition,Pattern Recognition Letters,2006
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+60093318820f49b5a105352a6b8512d1601af153,Automatic and Efficient Long Term Arm and Hand Tracking for Continuous Sign Language TV Broadcasts,,2012
+600c8fcef0480b7061574532861369c1c631de75,Unsupervised Deep Representations for Learning Audience Facial Behaviors,CoRR,2018
6097ea6fd21a5f86a10a52e6e4dd5b78a436d5bf,Multi-Region bilinear convolutional neural networks for person re-identification,2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS),2017
60643bdab1c6261576e6610ea64ea0c0b200a28d,Multi-manifold metric learning for face recognition based on image sets,J. Visual Communication and Image Representation,2014
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34a41ec648d082270697b9ee264f0baf4ffb5c8d,Integration of multi-feature fusion and dictionary learning for face recognition,Image Vision Comput.,2013
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34b7e826db49a16773e8747bc8dfa48e344e425d,Learning sign language by watching TV (using weakly aligned subtitles),2009 IEEE Conference on Computer Vision and Pattern Recognition,2009
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+5a6c021f80d82f3fae283865b259e398f9ed0f32,The neurobiology of emotion–cognition interactions: fundamental questions and strategies for future research,,2015
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5a029a0b0ae8ae7fc9043f0711b7c0d442bfd372,Autoencoder Feature Selector,CoRR,2017
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+5a383940c769660e53558d8f4bfcca7f5c730e75,Atypical neural networks for social orienting in autism spectrum disorders,NeuroImage,2011
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5f64a2a9b6b3d410dd60dc2af4a58a428c5d85f9,Scalable Object Detection for Stylized Objects,CoRR,2017
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5fa0e6da81acece7026ac1bc6dcdbd8b204a5f0a,On applying linear discriminant analysis for multi-labeled problems,Pattern Recognition Letters,2008
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5fa932be4d30cad13ea3f3e863572372b915bec8,Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction,Pattern Recognition Letters,2012
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33aa980544a9d627f305540059828597354b076c,Face Recognition Using Eigen face Coefficients and Principal Component Analysis,Unknown,2010
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+33430277086192476fa6c32eae88688b0cb21228,The developmental neurobiology of autism spectrum disorder.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2006
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33403e9b4bbd913ae9adafc6751b52debbd45b0e,Pose Invariant Affect Analysis using Thin - Plate Splines,,
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0562fc7eca23d47096472a1d42f5d4d086e21871,On the Integration of Optical Flow and Action Recognition,CoRR,2017
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056294ff40584cdce81702b948f88cebd731a93e,Unsupervised Semantic Parsing of Video Collections,2015 IEEE International Conference on Computer Vision (ICCV),2015
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05f4d907ee2102d4c63a3dc337db7244c570d067,Face recognition from a single image per person: A survey,Pattern Recognition,2006
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+05caf67982ce3416a28550f291211bd1459f9aeb,Face Recognition Using Holistic Features and Linear Discriminant Analysis Simplification,,2012
+056d1637fac0510146431a03d81de1cbf1147d65,UHDB11 Database for 3D-2D Face Recognition,,2013
05e96d76ed4a044d8e54ef44dac004f796572f1a,Three-Dimensional Face Recognition,International Journal of Computer Vision,2005
+9d1e20c3d2d0d67d3c2f06dbfc336170c772f2fd,Attribute-Graph: A Graph Based Approach to Image Ranking,2015 IEEE International Conference on Computer Vision (ICCV),2015
9cfb3a68fb10a59ec2a6de1b24799bf9154a8fd1,Semi-supervised learning in Spectral Dimensionality Reduction,,2016
+9c1fa04553e96ccc59b9c0026e6e25fb2c7dae77,Transductive Zero-Shot Learning with a Self-training dictionary approach,CoRR,2017
+9c03db9ad53be4862625256a24f56cc7b0a79c23,Hyperdrive: A Systolically Scalable Binary-Weight CNN Inference Engine for mW IoT End-Nodes,,2018
+9c571732af31360b79cee46b1809d98a42423dc1,"Autism spectrum disorder, but not amygdala lesions, impairs social attention in visual search.",Neuropsychologia,2014
+9cd8a2d07f07d888fcf50aa0735d0831edcf5e46,Bag of contour fragments for robust shape classification,Pattern Recognition,2014
+027bdb0f502cc61b73be32427a8dd56e213cc2b8,Deep Neural Networks Under Stress,2016 IEEE International Conference on Image Processing (ICIP),2016
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029b53f32079063047097fa59cfc788b2b550c4b,Continuous Conditional Neural Fields for Structured Regression,,2014
+026168fd2bcfbcd02012e379f35b7cfdc4c95ee1,Novel Fisher discriminant classifiers,Pattern Recognition,2012
02bd665196bd50c4ecf05d6852a4b9ba027cd9d0,Feature Selection with Annealing for Computer Vision and Big Data Learning,IEEE Transactions on Pattern Analysis and Machine Intelligence,2016
+0217fb2a54a4f324ddf82babc6ec6692a3f6194f,InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets,,2016
02c993d361dddba9737d79e7251feca026288c9c,Automatic player detection and recognition in images using AdaBoost,Proceedings of 2012 9th International Bhurban Conference on Applied Sciences & Technology (IBCAST),2012
+02c7740af5540f23a2da23d1769e64a8042ec62e,Big Data : The Management,,2012
+a4b09fe27dc38a7646877440d76947cdcc895d4c,Learning occlusion with likelihoods for visual tracking,2011 International Conference on Computer Vision,2011
a46283e90bcdc0ee35c680411942c90df130f448,Moment-based local binary patterns: A novel descriptor for invariant pattern recognition applications,Neurocomputing,2013
+a48a8e337a155d01a9652f3ea36675710e600222,Spatio-temporal crowd density model in a human detection and tracking framework,Sig. Proc.: Image Comm.,2015
+a4e47b6cbadfe5085c0a83f39513bda0ed3e9a92,Precise Eye Localization through a General-to-specific Model Definition,,2006
+a4cd3fc63ddc8468d3f684f32cb0578e41fed226,Generative Adversarial Style Transfer Networks for Face Aging,Unknown,2018
a4cc626da29ac48f9b4ed6ceb63081f6a4b304a2,KCRC-LCD: Discriminative kernel collaborative representation with locality constrained dictionary for visual categorization,Pattern Recognition,2015
+a4874a54a2afd74d2cbed50f2276c91c49f12ccb,Feature and label relation modeling for multiple-facial action unit classification and intensity estimation,Pattern Recognition,2017
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a33f20773b46283ea72412f9b4473a8f8ad751ae,ISTANBUL TECHNICAL UNIVERSITY F INFORMATICS INSTITUTE ROBUST FACE RECOGNITION ON NONLINEAR MANIFOLDS Ph.D. THESIS,,2012
+a30efa3271161dc7409530fe0ea76bad62a6f191,Mirror mirror on the wall... An intelligent multisensory mirror for well-being self-assessment,,2015
+a3239de6f4c300b135d5c417890ab68be8e90801,Vulnerabilities and Attack Protection in Security Systems Based on Biometric Recognition –tesis Doctoral– Vulnerabilidades Y Protección Frente a Ataques En Sistemas De Seguridad Basados En,,2010
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+b5e4b4cf5178b06e0bb5fd016b8ff5f609eddc8e,Multi-Scale Gabor Feature Based Eye Localization,Unknown,2007
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b59f441234d2d8f1765a20715e227376c7251cd7,Deep Continuous Clustering,CoRR,2018
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d9739d1b4478b0bf379fe755b3ce5abd8c668f89,Unsupervised approach for the accurate localization of the pupils in near-frontal facial images,J. Electronic Imaging,2013
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d9a1dd762383213741de4c1c1fd9fccf44e6480d,Reconstruction and analysis of multi-pose face images based on nonlinear dimensionality reduction,Pattern Recognition,2004
+d90e292c4bc2fdbeec5e494c92194e4d3420d760,Pairwise clustering based on the mutual-information criterion,Neurocomputing,2016
aca273a9350b10b6e2ef84f0e3a327255207d0f5,On soft biometrics,Pattern Recognition Letters,2015
+ac79059866be081a8492c642291be159220979a5,Predicting psychological attributions from face photographs with a deep neural network,CoRR,2015
+ac5ab8f71edde6d1a2129da12d051ed03a8446a1,Comparator Networks,Unknown,2018
ac0d3f6ed5c42b7fc6d7c9e1a9bb80392742ad5e,ViCom: Benchmark and Methods for Video Comprehension,CoRR,2016
ac820d67b313c38b9add05abef8891426edd5afb,Fuzzy human motion analysis: A review,Pattern Recognition,2015
+ac6b280f2a43516fbaf92073304002f9f4da0188,Eyes closeness detection from still images with multi-scale histograms of principal oriented gradients,Pattern Recognition,2014
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+add020816e4eea7ec547d0c3233b15abf3413fd2,Content Extraction from Marketing Flyers,,2015
+ad08c6b0b42db6d6ba30387d558f5e427e39b7dc,Attribute CNNs for word spotting in handwritten documents,International Journal on Document Analysis and Recognition (IJDAR),2018
+ad8e7c9bf20a0507acb90b17574da631b3d8b7cd,Temporal dynamic appearance modeling for online multi-person tracking,Computer Vision and Image Understanding,2016
ad6745dd793073f81abd1f3246ba4102046da022,A Coupled Hidden Markov Random Field model for simultaneous face clustering and tracking in videos,Pattern Recognition,2017
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bb557f4af797cae9205d5c159f1e2fdfe2d8b096,A distributed framework for trimmed Kernel k-Means clustering,Pattern Recognition,2015
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bbe1332b4d83986542f5db359aee1fd9b9ba9967,Convolutional neural network on three orthogonal planes for dynamic texture classification,Pattern Recognition,2018
+bb9b45f4b97935a95272c409d212589bc2a9a0cc,Efficient Multi-cue Scene Segmentation,,2013
+bbaebcc0a2d65dea32fe1cf2a2aa12c65bb1b3da,Track based relevance feedback for tracing persons in surveillance videos,Computer Vision and Image Understanding,2013
+bb1a6080072bd54eaa5afa1d29cc02525946d7bb,Functional brain correlates of social and nonsocial processes in autism spectrum disorders: an activation likelihood estimation meta-analysis.,Biological psychiatry,2009
bbf01aa347982592b3e4c9e4f433e05d30e71305,Markov network-based multiple classifier for face image retrieval,2013 IEEE International Conference on Image Processing,2013
bbf1396eb826b3826c5a800975047beabde2f0de,Illumination insensitive recognition using eigenspaces,Computer Vision and Image Understanding,2004
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+bb750b4c485bc90a47d4b2f723be4e4b74229f7a,Robust Computer Vision: Theory and Applications,,2003
d78077a7aa8a302d4a6a09fb9737ab489ae169a6,Robust face recognition with structural binary gradient patterns,Pattern Recognition,2017
d7312149a6b773d1d97c0c2b847609c07b5255ec,An Experimentation Engine for Data-Driven Fashion Systems,,2017
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d78373de773c2271a10b89466fe1858c3cab677f,Pain intensity estimation by a self-taught selection of histograms of topographical features,Image Vision Comput.,2016
+d71a2baecdf28fd946458a34bfbc034681a82694,Integrate the original face image and its mirror image for face recognition,Neurocomputing,2014
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d03baf17dff5177d07d94f05f5791779adf3cd5f,Real time face and mouth recognition using radial basis function neural networks,Expert Syst. Appl.,2009
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+b3e51092fa8b127bef0e46c2e54f24bdaedf30c3,Automatic Face Recognition System for Hidden Markov Model Techniques,,2012
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+b36833aacc1ae72f9ccb9eee9d9623df19802fe0,An on-line learning method for face association in personal photo collection,Image Vision Comput.,2012
b3afa234996f44852317af382b98f5f557cab25a,A Closer Look at Spatiotemporal Convolutions for Action Recognition,CoRR,2017
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dfabe7ef245ca68185f4fcc96a08602ee1afb3f7,Group-aware deep feature learning for facial age estimation,Pattern Recognition,2017
+df3d2f514d41c0c37293d88d4a594e5cfc6c3bea,Happy mouth and sad eyes: scanning emotional facial expressions.,Emotion,2011
+dfdc683a113c6543de36c5bec9325bbf4a2ad25c,A novel feature descriptor based on biologically inspired feature for head pose estimation,Neurocomputing,2013
+df0090524461ac8e16987a6e30d4287f7c8e0c8c,Finger vein recognition with manifold learning,J. Network and Computer Applications,2010
+daee91e5f88efcdf154dbf6f123a97ed8c5bb643,Shape analysis of local facial patches for 3D facial expression recognition,Pattern Recognition,2011
da15344a4c10b91d6ee2e9356a48cb3a0eac6a97,Exploiting IoT technologies for enhancing Health Smart Homes through patient identification and emotion recognition,Computer Communications,2016
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da5bfddcfe703ca60c930e79d6df302920ab9465,An analysis of facial expression recognition under partial facial image occlusion,Image Vision Comput.,2008
daba8f0717f3f47c272f018d0a466a205eba6395,Neither Global Nor Local: Regularized Patch-Based Representation for Single Sample Per Person Face Recognition,International Journal of Computer Vision,2014
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b4d7ca26deb83cec1922a6964c1193e8dd7270e7,Learning to score and summarize figure skating sport videos,CoRR,2018
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+a228ba020bd321d29ab24485cb2988a62707fd64,Using objective ground-truth labels created by multiple annotators for improved video classification: A comparative study,Computer Vision and Image Understanding,2013
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a2d9c9ed29bbc2619d5e03320e48b45c15155195,Facial expression recognition based on anatomy,Computer Vision and Image Understanding,2014
a2b54f4d73bdb80854aa78f0c5aca3d8b56b571d,Computer Recognition of Facial Actions: A study of co-articulation effects,,2001
+a2fe4f7bdfbdc32393ab6102c8e1063542229758,Two retinotopic visual areas in human lateral occipital cortex.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2006
+a2344004f0e1409c0c9473d071a5cfd74bff0a5d,Learnable PINs: Cross-modal Embeddings for Person Identity,Unknown,2018
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+a5173a67c7f32582739849cfa5e07278ee6746ab,Local contrast phase descriptor for fingerprint liveness detection,Pattern Recognition,2015
+a53fe4347da39dcf61ac37cee66c945e79a5052e,Category Independent Object Proposals,,2010
+a57995ecac8275b4c7d614f17538cf771b0b1657,A training-free nose tip detection method from face range images,Pattern Recognition,2011
+a509f0528c5fbb36993324922b13a9a303ce82ee,Evaluation of the Modelling of Local Areas and Errors of Localization in FRGC' 05,,2005
+a57b92ed2d8aa5b41fe513c3e98cbf83b7141741,Relevant Component Analysis for static facial expression classification,,2005
a5c04f2ad6a1f7c50b6aa5b1b71c36af76af06be,Combined Support Vector Machines and Hidden Markov Models for Modeling Facial Action Temporal Dynamics,,2007
a503eb91c0bce3a83bf6f524545888524b29b166,A Generative Approach to Zero-Shot and Few-Shot Action Recognition,CoRR,2018
+a562180056cc4906d6d5ef9d2b4ed098d8512317,Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators,CoRR,2018
+bd36544bfecd5b9ea58d0eab186968b3c9d181aa,Weakly supervised 3D Reconstruction with Adversarial Constraint,,2017
+bd6333229199e7b4ac4b9ae7a7cae50ff9b9f5b2,A neural network with a single recurrent unit for associative memories based on linear optimization,Neurocomputing,2013
bd9eb65d9f0df3379ef96e5491533326e9dde315,Graph Distillation for Action Detection with Privileged Information,CoRR,2017
bd8e2d27987be9e13af2aef378754f89ab20ce10,Facial feature points detecting based on Gaussian Mixture Models,Pattern Recognition Letters,2015
+bd0d93e67c0b439caf372b704a377670f0c89be8,Assessing the precision of gaze following using a stereoscopic 3D virtual reality setting,Vision Research,2015
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+d154df56ac4382a0a81eb24b190bdba240546d87,Using Gaussian distribution to construct fitness functions in genetic programming for multiclass object classification,Pattern Recognition Letters,2006
+d13f176178f90efa6f91e9f45f710e72e5675c9a,Pedestrian Counting using Deep Models Trained on Synthetically Generated Images,Unknown,2017
+d18ee185ab659f218c97db53e22a2b98f3c642a3,Top-Down Feedback for Crowd Counting Convolutional Neural Network,Unknown,2018
+d6a4a34829b3b55497210ddbe88ad63ff801faae,Object Referring in Visual Scene with Spoken Language,CoRR,2017
d6fb606e538763282e3942a5fb45c696ba38aee6,Affective Body Expression Perception and Recognition: A Survey,IEEE Transactions on Affective Computing,2013
+d6d7a248b1f59981277121b9c0626ee8d5495757,Superpixel clustering with deep features for unsupervised road segmentation,CoRR,2017
+bc704680b5032eadf78c4e49f548ba14040965bf,"Face Normals ""In-the-Wild"" Using Fully Convolutional Networks",,2017
bcc346f4a287d96d124e1163e4447bfc47073cd8,Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition,Unknown,2016
bcfeac1e5c31d83f1ed92a0783501244dde5a471,Achieving robust face recognition from video by combining a weak photometric model and a learnt generic face invariant,Pattern Recognition,2013
+bcc5cbbb540ee66dc8b9a3453b506e895d8395de,Joint Estimation of Pose and Face Landmark,,2014
bc2852fa0a002e683aad3fb0db5523d1190d0ca5,Learning from Ambiguously Labeled Face Images,IEEE transactions on pattern analysis and machine intelligence,2017
bcb99d5150d792001a7d33031a3bd1b77bea706b,Facial descriptors for human interaction recognition in still images,Pattern Recognition Letters,2016
+ae42dc9ef4a03caf69c23c117621108211977405,Visible-light and near-infrared face recognition at a distance,J. Visual Communication and Image Representation,2016
aed321909bb87c81121c841b21d31509d6c78f69,"Unfamiliar Sides , Video , Image Enhancement in Face Recognition",,2016
ae936628e78db4edb8e66853f59433b8cc83594f,Person Re-identification via Structured Prediction,CoRR,2014
+ae19008898ea1347cf0f7ecb81b71aa18137085a,Time-slice Prediction of Dyadic Human Activities,,2015
+aeb0f4ffb57e40c93606458707622c0b37ea3790,Video-Based Person Re-Identification via Self Paced Weighting,Unknown,2018
+ae6c9610297186e0e1d4347a2d203fe5f86dd42b,Adaptive ensembles for face recognition in changing video surveillance environments,Inf. Sci.,2014
+aeedc6b7f2ceaaf9d9cd8e327ca979128c1947e9,Locality-sensitive dictionary learning for sparse representation based classification,Pattern Recognition,2013
+ae2ee60219d63475c56fcb6c3f2b3664b3c4dbd9,The MAHNOB Mimicry Database: A database of naturalistic human interactions,Pattern Recognition Letters,2015
+ae872749c88331a93f8078aebf3a8d7f6d9c48fa,Modeling local behavior for predicting social interactions towards human tracking,Pattern Recognition,2014
ae4e2c81c8a8354c93c4b21442c26773352935dd,On the kernel Extreme Learning Machine classifier,Pattern Recognition Letters,2015
+d81253d750f2c204899e71fd68ad60680f9c8d57,Impaired perception of facial emotion in developmental,,
+d8e5362a16914e779a135a5285775be49d60dccb,"Fast, Robust and Non-convex Subspace Recovery",,2014
+d84e075d571193bc616218a84951375e63ab20c8,"Driving Scene Perception Network: Real-time Joint Detection, Depth Estimation and Semantic Segmentation",,2018
+d8cbe136dd95d287786d0ed5f0d0e53f143bca7f,Glucose metabolic changes in the prefrontal cortex are associated with HPA axis response to a psychosocial stressor.,Psychoneuroendocrinology,2008
+abc5ee7fc8129c82fde8d151408042e4673762f6,Multi-part body segmentation based on depth maps for soft biometry analysis,Pattern Recognition Letters,2015
+abb68f5f393f60695ab16dcee08f2638ab3c7809,Probabilistic Zero-shot Classification with Semantic Rankings,CoRR,2015
+ab4c2e8071d99bdc8c1bff9bc0d6817300ee371a,Snapshot Spectral and Polarimetric Imaging; Target Identification with,,2013
+ab368172c8acc87ec1dc87d1ad607546b2ea8f6a,Gender Classification of Face Images: The Role of Global and Feature-Based Information,,2004
+ab9d368b2ebcc34e38046de49437b7bb224c5b56,Domain Adaptation of Deformable Part-Based Models,IEEE Transactions on Pattern Analysis and Machine Intelligence,2014
+abb74644e2bb1d1e8610e9782a6050192c3ceddf,3D human face description: landmarks measures and geometrical features,Image Vision Comput.,2012
+abd555f397abb6f46aad81c683b279cbd6d22637,Transfer between pose and expression training in face recognition,Vision Research,2009
ab1dfcd96654af0bf6e805ffa2de0f55a73c025d,Higher order orthogonal moments for invariant facial expression recognition,Digital Signal Processing,2010
ab1900b5d7cf3317d17193e9327d57b97e24d2fc,Expression transfer for facial sketch animation,Signal Processing,2011
e5737ffc4e74374b0c799b65afdbf0304ff344cb,A literature survey on robust and efficient eye localization in real-life scenarios,Pattern Recognition,2013
+e5781730c9f1c81b08cf4b4a924f1058efe77908,Real-Time Human Detection Using Local Features Based on Depth Information,,2010
+e50ee29ca12028cb903cd498bb9cacd41bd5ce3a,Single-view-based 3D facial reconstruction method robust against pose variations,Pattern Recognition,2015
e5dfd17dbfc9647ccc7323a5d62f65721b318ba9,Using Correlated Regression Models to Calculate Cumulative Attributes for Age Estimation,IEICE Transactions,2015
+e5d27e52fafde2b09ae6568fc6bde28468f5517e,Information extraction from shadowed regions in images: An eye movement study,Vision Research,2015
e27c92255d7ccd1860b5fb71c5b1277c1648ed1e,Multilinear class-specific discriminant analysis,Pattern Recognition Letters,2017
+e22979cdf147a63be74f3816ef59ef11f3508919,Learning Image Representations by Completing Damaged Jigsaw Puzzles,CoRR,2018
+e2bf47d2e3339f366de8947cbb5a894608b91bf9,"Face Recognition for Newborns , Toddlers , and Pre-School Children : A Deep Learning Approach",Unknown,2018
+e2ff4d1bbd6333763292d9f605855b14c27b550b,Overreactive brain responses to sensory stimuli in youth with autism spectrum disorders.,Journal of the American Academy of Child and Adolescent Psychiatry,2013
e200c3f2849d56e08056484f3b6183aa43c0f13a,The C-loss function for pattern classification,Pattern Recognition,2014
+e224d8fd66e3594cf27bcd06cc2ed25fc4419b7f,Geometrical descriptors for human face morphological analysis and recognition,Robotics and Autonomous Systems,2012
+e2d37596f1ad4823fe042f37137ff54048231de2,Sketch retrieval via local dense stroke features,Image Vision Comput.,2016
+e260ce226de2c945967a7c8d8363f22af02dd2bb,Performing Facial Expression Synthesis on Robot Faces: A Real-time Software System,,2015
+f4f5a68c8e7a90865c4e1a653db4ae788e387bb1,Transductive Zero-Shot Recognition via Shared Model Space Learning,,2016
f4c01fc79c7ead67899f6fe7b79dd1ad249f71b0,Pose-invariant face recognition by matching on multi-resolution MRFs linked by supercoupling transform,Computer Vision and Image Understanding,2011
+f47e7253f0763579c6c045cd3fa5b34b0697f254,Perception-driven facial expression synthesis,Computers & Graphics,2012
+f48b89fa0aa7435cfb7fcd801a51b2504b9c4515,Disentangling the Impact of Social Groups on Response Times and Movement Dynamics in Evacuations,,2015
+f48665764089d42bb0123914e4ed0a3770f5d706,Shape matching using a binary search tree structure of weak classifiers,Pattern Recognition,2012
f3fcaae2ea3e998395a1443c87544f203890ae15,Robust part-based face matching with multiple templates,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+f3196b1bcd1af733347edc923d43018724fc73c9,Person re-identification using visual attention,2017 IEEE International Conference on Image Processing (ICIP),2017
f355e54ca94a2d8bbc598e06e414a876eb62ef99,"A survey on heterogeneous face recognition: Sketch, infra-red, 3D and low-resolution",Image Vision Comput.,2016
+eb724fed2a6457a2ee41a205892004116180bbfd,Pii: S0262-8856(99)00059-1,,2000
ebedc841a2c1b3a9ab7357de833101648281ff0e,Facial landmarking for in-the-wild images with local inference based on global appearance,Image Vision Comput.,2015
+eb5b1dfe580722c0fc5ca202a1259b0bd62354c9,Transforming the mirror: power fundamentally changes facial responding to emotional expressions.,Journal of experimental psychology. General,2014
+eb65354fe51a177b2366f8d10b8140912e883d62,Estimating the Success of Unsupervised Image to Image Translation,Unknown,2018
+eb6b8359909749e52efff9b78b037a88468101fd,Tracking and Recognizing Multiple Faces Using Kalman Filter and ModularPCA,,2011
ebb9d53668205c5797045ba130df18842e3eadef,Fully Context-Aware Video Prediction,CoRR,2017
+ebb139368e425d720d47a13dcd269014027b40ae,A secure biometric discretization scheme for face template protection,Future Generation Comp. Syst.,2012
+eb72dcf0ba423d0e12d63cd7881f2ac5dfda7984,Associative Compression Networks,,2018
+eb98feac659ff5c7e27bc8eb4f425bb158e3fc5e,Biometrics Selection and Their Influence over the Life Cycle of Electronic Identity Documents,,2017
+c79fe054f971a454406f46b62b5a397b95240046,Comparing and combining lighting insensitive approaches for face recognition,Computer Vision and Image Understanding,2010
+c784ba7120e807e244f508c71e96cd7677fe1109,An efficient 3D face recognition approach based on the fusion of novel local low-level features,Pattern Recognition,2013
+c0a7ffb06bf23cffc49e67d6359b1fb5db336edc,Geo-distinctive Visual Element Matching for Location Estimation of Images,CoRR,2016
+c0d1d9a585ef961f1c8e6a1e922822811181615c,Face and gaze perception in borderline personality disorder: An electrical neuroimaging study,Psychiatry Research: Neuroimaging,2017
c0d5c3aab87d6e8dd3241db1d931470c15b9e39d,Bag of visual words and fusion methods for action recognition: Comprehensive study and good practice,Computer Vision and Image Understanding,2016
+c09032896722aa35a905d8905c1cfe67cead6e01,Three-dimensional face recognition using combinations of surface feature map subspace components,Image Vision Comput.,2008
+c0efa1a3cea5b1f450283b81eee9942defaad4d2,Similar exemplar pooling processes underlie the learning of facial identity and handwriting style: Evidence from typical observers and individuals with Autism.,Neuropsychologia,2016
ee461d060da58d6053d2f4988b54eff8655ecede,Modelling facial colour and identity with Gaussian mixtures,Pattern Recognition,1998
+ee4c659ad75c302b223a3815a65aa2e304cccc30,Binary Biometrics: An Analytic Framework to Estimate the Bit Error Probability under Gaussian Assumption,"2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems",2008
+eea0640261e2d9bb6b851a519ef1a036093ec04f,The integration of visual context information in facial emotion recognition in 5- to 15-year-olds.,Journal of experimental child psychology,2016
+ee4bd9419405e051b709d90b63d9d264bd2fd796,Automatic head pose estimation with Synchronized sub manifold embedding and Random Regression Forests,,2014
+ee267e831aba3a2ead7ce6109b48afd41a30323f,Enhancing Anger Perception With Transcranial Alternating Current Stimulation Induced Gamma Oscillations.,Brain stimulation,2015
c903af0d69edacf8d1bff3bfd85b9470f6c4c243,Nyström-based approximate kernel subspace learning,Pattern Recognition,2016
+c95cd791ad0cb0a08cb39e987f725eabe3a08648,Are all objects equal? Deep spatio-temporal importance prediction in driving videos,Pattern Recognition,2017
+c9bda86e23cab9e4f15ea0c4cbb6cc02b9dfb709,Learning to predict human behaviour in crowded scenes,,2017
+c9d3b06d71f69dad7a9d3f312cf9dd008e2634ef,A multi-class classification strategy for Fisher scores: Application to signer independent sign language recognition,Pattern Recognition,2010
+c9168495c99b37ce601bc778419c2667f34cb29b,Image Matching: An Application-oriented Benchmark,Unknown,2017
+fcd7407d0df030d03e3a8879f184d4b3ceac4fb2,NISTIR 7923 Ground Truth Systems for Object Recognition and Tracking,,2013
+fc369a73eea045497f82634e6ea0c13477728f2e,Circularity and self-similarity analysis for the precise location of the pupils,2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance,2013
fc516a492cf09aaf1d319c8ff112c77cfb55a0e5,"XBadges. Identifying and training soft skills with commercial video games. Improving persistence, risk taking & spatial reasoning with commercial video games and facial and emotional recognition system",,2017
+fc6c5ef8d97d0c4d7f2a8576f8f5fe8e0ed83fbb,3D Face Reconstruction with Geometry Details from a Single Image,CoRR,2017
+fc2be7dbdd8f5cbcb6fdf5d18241ddd630d03864,Human pose estimation via multi-layer composite models,Signal Processing,2015
+fdaba5860f753b1e5714d582db9851cd0aa29139,Evolutionary Hough Games for coherent object detection,Computer Vision and Image Understanding,2012
+fd38fd64398502c0f0fc010939e7f61d44a7b5a6,A Survey of Recent Advances in Texture Representation,CoRR,2018
+f2490341a21e54a800e5ac7a1c0a25b60f0e0c36,Gaze aversion during social style interactions in autism spectrum disorder and Williams syndrome.,Research in developmental disabilities,2013
f2c568fe945e5743635c13fe5535af157b1903d1,Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods,,2018
f26097a1a479fb6f32b27a93f8f32609cfe30fdc,What is the best way for extracting meaningful attributes from pictures?,Pattern Recognition,2017
f214bcc6ecc3309e2efefdc21062441328ff6081,Speaker verification in score-ageing-quality classification space,Computer Speech & Language,2013
+f5c5f5fb2bfd11b65265a7a088b50185bdc7bccd,CovGa: A novel descriptor based on symmetry of regions for head pose estimation,Neurocomputing,2014
+f5541330741315b98e590e405c96c72bac49d51c,Biometric Score Calibration for Forensic Face Recognition,,2014
e3657ab4129a7570230ff25ae7fbaccb4ba9950c,Recovering Joint and Individual Components in Facial Data,,2018
+e3a3a6c1f4802ea1cd0c34d0b34e4c83689895ac,An effective unconstrained correlation filter and its kernelization for face recognition,Neurocomputing,2013
+e381edad6f9040712e6a50caf9c82465722aa04c,Image classification based on complex wavelet structural similarity,Sig. Proc.: Image Comm.,2013
+e3cc912b9ca074e3d419c1dd289fd1b067fb61d5,Identifying multiple objects from their appearance in inaccurate detections,Computer Vision and Image Understanding,2015
cfa572cd6ba8dfc2ee8ac3cc7be19b3abff1a8a2,Toward Use of Facial Thermal Features in Dynamic Assessment of Affect and Arousal Level,IEEE Transactions on Affective Computing,2017
+cfbffa4d143a72476d962906e413c5ed6306b09c,Why neuroscience matters to cognitive neuropsychology,Synthese,2007
+cfa205874bd192ab949132631a7eda995ecc57af,"Modeling the Contribution of Central Versus Peripheral Vision in Scene, Object, and Face Recognition",CoRR,2016
cfb8bc66502fb5f941ecdb22aec1fdbfdb73adce,Git Loss for Deep Face Recognition,Unknown,2018
+cf682939be6828d1a70161618024e02af660d1bb,Structured learning of metric ensembles with application to person re-identification,Computer Vision and Image Understanding,2017
cf54a133c89f730adc5ea12c3ac646971120781c,A comparative study for feature integration strategies in dynamic saliency estimation,Sig. Proc.: Image Comm.,2017
cac8bb0e393474b9fb3b810c61efdbc2e2c25c29,Visual Segmentation of Simple Objects for Robots,,2011
+cae25b66b485b5b76fb6f3d383b294f3456519a3,Two-dimensional nearest neighbor discriminant analysis,Neurocomputing,2007
+ca627984743536d9403cbc25c00d033bcc1cb839,"Analyzing Computer Vision Data - The Good, the Bad and the Ugly",,2017
+ca83053d9a790319b11a04eac5ab412e7fcab914,Efficient generic face model fitting to images and videos,Image Vision Comput.,2014
+ca17025fe9519b0eec7738995902be2992040a87,A survey of video datasets for human action and activity recognition,Computer Vision and Image Understanding,2013
e465f596d73f3d2523dbf8334d29eb93a35f6da0,"On Face Segmentation, Face Swapping, and Face Perception",CoRR,2017
+e49c59d19c1d652040f1bbd749c1e69a69f4b66c,On the Integration of Optical Flow and Action Recognition,CoRR,2017
e4aeaf1af68a40907fda752559e45dc7afc2de67,Exponential Discriminative Metric Embedding in Deep Learning,,2018
e4c3d5d43cb62ac5b57d74d55925bdf76205e306,Average Biased ReLU Based CNN Descriptor for Improved Face Retrieval,,2018
+e44b644dba198a4f8de553c9795aee77c0d23f37,Social effects of oxytocin in humans: context and person matter.,Trends in cognitive sciences,2011
+e45374e8d9491fe396497fc9fd91bd2f2f036315,Improving Hough Based Pedestrian Detection Accuracy by Using Segmentation and Pose Subspaces,IEICE Transactions,2014
e476cbcb7c1de73a7bcaeab5d0d59b8b3c4c1cbf,Robust Kernel Representation With Statistical Local Features for Face Recognition,IEEE Transactions on Neural Networks and Learning Systems,2013
fe7c0bafbd9a28087e0169259816fca46db1a837,Seeing Voices and Hearing Faces: Cross-modal biometric matching,CoRR,2018
+feba048e15c1931086f909d4be04ade134942947,The role of emotion regulation in autism spectrum disorder.,Journal of the American Academy of Child and Adolescent Psychiatry,2013
fe48f0e43dbdeeaf4a03b3837e27f6705783e576,Supervised Transformer Network for Efficient Face Detection,Unknown,2016
+fe4609fdf8fc8ea18204ffe673c2b06acbe8d0fd,The surprisingly high human efficiency at learning to recognize faces,Vision Research,2009
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fe108803ee97badfa2a4abb80f27fa86afd9aad9,Kernel discriminant transformation for image set-based face recognition,Pattern Recognition,2011
c82c147c4f13e79ad49ef7456473d86881428b89,Facial Expression Recognition and Analysis: A Comparison Study of Feature Descriptors,IPSJ Trans. Computer Vision and Applications,2015
+c86bdec7c4aa6aa1b5872badb5e48193ff5920e8,Face Identi®cation Using One Spike per Neuron: Resistance to Image Degradations,,2001
+c86afba9c77a9b1085ccc6c44c36fa3a1fdb51c5,New Losses for Generative Adversarial Learning,CoRR,2018
+c8279a389738f3011edc6e9ddfefb0410df380ef,Robust pedestrian detection in thermal infrared imagery using a shape distribution histogram feature and modified sparse representation classification,Pattern Recognition,2015
+fb19c7cec103193ea4f4265a2d9534a20893b2a8,Zernike velocity moments for sequence-based description of moving features,Image Vision Comput.,2006
fb5280b80edcf088f9dd1da769463d48e7b08390,The impact of weak ground truth and facial expressiveness on affect detection accuracy from time-continuous videos of facial expressions,Inf. Sci.,2013
+fb9673f0373ca4c72fe9059648ae618d45fd8c90,Why Is Facial Occlusion a Challenging Problem?,,2009
+ed717bd09e8344c2cfa81ceedfb8baf2105708f5,Binary-image comparison with local-dissimilarity quantification,Pattern Recognition,2008
+ede1f00c2ac27ac90dbeb0df1840ac757447af34,Neural Network Based Approach for Face Detection cum Face Recognition,Unknown,2012
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+eda501bb1e610098648667eb25273adc4a4dc98d,"Fusing audio, visual and textual clues for sentiment analysis from multimodal content",Neurocomputing,2016
+ed702537d487de0737582f7ef7e937f4fe9b28fd,"Pattern Recognition in Latin America in the ""Big Data"" Era",Pattern Recognition,2015
c178a86f4c120eca3850a4915134fff44cbccb48,Normalization Discriminant Independent Component Analysis,,2013
+c14781a995933e2b89d40a95ca1247845ddfe3ab,"Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system",Computer Vision and Image Understanding,2016
+c16cc7006ad3ba5f2c5ce022bfc97a6fbfff847b,Increasing the Stability of CNNs using a Denoising Layer Regularized by Local Lipschitz Constant in Road Understanding Problems,Unknown,2017
c1fc70e0952f6a7587b84bf3366d2e57fc572fd7,Efficient clustering on Riemannian manifolds: A kernelised random projection approach,Pattern Recognition,2016
c1482491f553726a8349337351692627a04d5dbe,When Follow is Just One Click Away: Understanding Twitter Follow Behavior in the 2016 U.S. Presidential Election,,2017
c1e76c6b643b287f621135ee0c27a9c481a99054,Multi-point Regression Voting for Shape Model Matching,,2016
+c610db0ee2d111452f70ce4854e48ab9d5c2b1ab,Fast and Robust Multi-people Tracking from RGB-D Data for a Mobile Robot,,2012
+c6ea6fee4823b511eecf41f6c2574a0728055baf,HoloFace: Augmenting Human-to-Human Interactions on HoloLens,CoRR,2018
+c61a5961a344748272fe51ddf4584b22d9c10cde,Is anyone looking at me? Direct gaze detection in children with and without autism.,Brain and cognition,2008
+ece02507e17c7e6a5ce4d58f990f3e01c6555aa4,Improving pedestrian detection with selective gradient self-similarity feature,Pattern Recognition,2015
+ecdd4731e197f4afda804602f533565c19ffc271,Vision in autism spectrum disorders,Vision Research,2009
+ec2bf43338959e263d7fd5e3b2ef8665fa023ed9,A hybrid parallel projection approach to object-based image restoration,Pattern Recognition Letters,2006
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ec22eaa00f41a7f8e45ed833812d1ac44ee1174e,A novel phase congruency based descriptor for dynamic facial expression analysis,Pattern Recognition Letters,2014
+ec0239b3547639195c95d322632b6a83b648e8df,Robust visual tracking with structured sparse representation appearance model,Pattern Recognition,2012
+4e729427f5cd4be22dad7bef0eb241e93497dbf4,Model-Driven Domain Adaptation on Product Manifolds for Unconstrained Face Recognition,International Journal of Computer Vision,2014
+4e93a8a47473bf57e24aec048cb870ab366a43d6,Face authentication for multiple subjects using eigen#ow,,2001
+4ea759e13b0991772c61a4ede058d59d5e33a71b,"Scale resilient, rotation invariant articulated object matching",2012 IEEE Conference on Computer Vision and Pattern Recognition,2012
+4e4a4359c7dd25af7e2ef0910928cd9faa5d0cfb,End-to-End 3D Face Reconstruction with Deep Neural Networks,2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017
+4e9f46a80ffaffa2dabde4fb48d6ac72398ef829,Deep Hybrid Similarity Learning for Person Re-identification,CoRR,2017
4e444db884b5272f3a41e4b68dc0d453d4ec1f4c,Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition,CoRR,2017
4e7ebf3c4c0c4ecc48348a769dd6ae1ebac3bf1b,"Towards the automatic detection of spontaneous agreement and disagreement based on nonverbal behaviour: A survey of related cues, databases, and tools",Image Vision Comput.,2013
+4e4311a5fd99b17bed31b7006a572d29a58cdcf3,A support vector machine classifier with automatic confidence and its application to gender classification,Neurocomputing,2011
4e4e8fc9bbee816e5c751d13f0d9218380d74b8f,Tone-aware sparse representation for face recognition,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+4efc523df04fe19b600e372b9cfc9acf2e0b21d8,LSTM stack-based Neural Multi-sequence Alignment TeCHnique (NeuMATCH),,2018
20a88cc454a03d62c3368aa1f5bdffa73523827b,Face recognition using a kernel fractional-step discriminant analysis algorithm,Pattern Recognition,2007
+20ca3dc873d7c986d7b1b233fdcf85e78b92914e,Patch to the Future: Unsupervised Visual Prediction,2014 IEEE Conference on Computer Vision and Pattern Recognition,2014
+209e1d36f36b8e7db3147b0e424874e54df9012e,Variational Tempering,,2016
20767ca3b932cbc7b8112db21980d7b9b3ea43a3,Dynamic Concept Composition for Zero-Example Event Detection,,2016
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20c2a5166206e7ffbb11a23387b9c5edf42b5230,Examining visible articulatory features in clear and plain speech,Speech Communication,2015
2098983dd521e78746b3b3fa35a22eb2fa630299,Second-order Temporal Pooling for Action Recognition,CoRR,2017
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206fbe6ab6a83175a0ef6b44837743f8d5f9b7e8,Unsupervised learning of object frames by dense equivariant image labelling,Unknown,2017
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18206e1b988389eaab86ef8c852662accf3c3663,Compressed Video Action Recognition,CoRR,2017
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184750382fe9b722e78d22a543e852a6290b3f70,Projection functions for eye detection,Pattern Recognition,2004
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+18d19cf4d09ac340428d091b24af561a3d5de3ea,Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs,CoRR,2018
+1828b1b0f5395b163fef087a72df0605249300c2,On-line Adaption of Class-specific Codebooks for Instance Tracking,,2010
+1802aebb98424af6fa8f3d4dc024da2f1d3ea1e5,The Human Face as a Dynamic Tool for Social Communication,Current Biology,2015
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18dfc2434a95f149a6cbb583cca69a98c9de9887,Hough Networks for Head Pose Estimation and Facial Feature Localization,,2014
+189c0e5df2611dea909e51256b30c3ce3d25b5a4,Detecting Vanishing Points in Natural Scenes with Application in Photo Composition Analysis,CoRR,2016
+2771e262e54948ad2c35a80caabc7af181521d39,Co-localization with Category-Consistent CNN Features and Geodesic Distance Co-Propagation,CoRR,2016
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27d709f7b67204e1e5e05fe2cfac629afa21699d,"Learning the Latent ""Look"": Unsupervised Discovery of a Style-Coherent Embedding from Fashion Images",,2017
+27c9ddb72360f4cd0f715cd7ea82fa399af91f11,Multiresolution face recognition,Image Vision Comput.,2005
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+2727927c7493cef9785b3a06a38f5c1ce126fc23,Semi-supervised FusedGAN for Conditional Image Generation,Unknown,2018
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+27d9d09126c1f2138f6aa719c4937da0bf8a8b87,Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation,,2018
27da432cf2b9129dce256e5bf7f2f18953eef5a5,Face Recognition in Low Quality Images: A Survey,CoRR,2018
+27e9f54586475d495e68b4218fdbd6e926c0accf,Development of a Person Following Robot and Its Experimental Evaluation,,2010
274f87ad659cd90382ef38f7c6fafc4fc7f0d74d,Latent Tensor Transfer Learning for RGB-D Action Recognition,,2014
+27a2fad58dd8727e280f97036e0d2bc55ef5424c,"Performance Measures and a Data Set for Multi-target, Multi-camera Tracking",,2016
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4bbbee93519a4254736167b31be69ee1e537f942,Learning to Score Olympic Events,2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),2017
4b6be933057d939ddfa665501568ec4704fabb39,Graph Transduction as a Non-cooperative Game,,2011
+4b1d23d17476fcf78f4cbadf69fb130b1aa627c0,Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation,,2010
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+11cf7aa5d940d0680e287b6e7f13490a619fdf47,"Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications",2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017
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11367581c308f4ba6a32aac1b4a7cdb32cd63137,3D face shape approximation from intensities using Partial Least Squares,2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops,2008
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112780a7fe259dc7aff2170d5beda50b2bfa7bda,Learnable PINs: Cross-Modal Embeddings for Person Identity,CoRR,2018
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29c1f733a80c1e07acfdd228b7bcfb136c1dff98,Discriminatively Trained Latent Ordinal Model for Video Classification,IEEE transactions on pattern analysis and machine intelligence,2017
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29f27448e8dd843e1c4d2a78e01caeaea3f46a2d,Similar gait action recognition using an inertial sensor,Pattern Recognition,2015
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29156e4fe317b61cdcc87b0226e6f09e416909e0,Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach,IEEE transactions on pattern analysis and machine intelligence,2017
293ade202109c7f23637589a637bdaed06dc37c9,Material for : Adaptive Cascaded Regression,,2016
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+7c38572093b0d0ef72d828f59f95b3a6a067fe27,WESPE: Weakly Supervised Photo Enhancer for Digital Cameras,CoRR,2017
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7ce03597b703a3b6754d1adac5fbc98536994e8f,On the Intrinsic Dimensionality of Face Representation,,2018
+7cb4ab1bfff61bf0d1ebec6c4402b7e45e62c609,Hierarchical Multiresolution Models for fast Object Detection,,2012
16de1324459fe8fdcdca80bba04c3c30bb789bdf,Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs,CoRR,2017
16892074764386b74b6040fe8d6946b67a246a0b,Virtual Faces Expressing Emotions: An Initial Concomitant and Construct Validity Study,,2014
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1679943d22d60639b4670eba86665371295f52c3,Facial feature extraction using complex dual-tree wavelet transform,Computer Vision and Image Understanding,2008
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169076ffe5e7a2310e98087ef7da25aceb12b62d,Emotional restraint is good for men only: The influence of emotional restraint on perceptions of competence.,Emotion,2016
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+42d0193edad27f4a4505f1bf7a9122f0ac1a0e9e,Facial Shape Estimation in the Presence of Cast Shadows,,2006
429c3588ce54468090cc2cf56c9b328b549a86dc,Thermal and reflectance based personal identification methodology under variable illumination,Pattern Recognition,2010
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424259e9e917c037208125ccc1a02f8276afb667,Walk and Learn: Facial Attribute Representation Learning from Egocentric Video and Contextual Data,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
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42e0127a3fd6a96048e0bc7aab6d0ae88ba00fb0,AU-aware Deep Networks for facial expression recognition,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
89de30a75d3258816c2d4d5a733d2bef894b66b9,Relative Hidden Markov Models for Video-Based Evaluation of Motion Skills in Surgical Training,IEEE Transactions on Pattern Analysis and Machine Intelligence,2015
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+45a6add58dcb5587f607b8eedd92078560c313c5,Multi-Modality Vertebra Recognition in Arbitrary,,2015
+45a2d0b9d5361742a567bd1978036c0c14c5bd1f,Similar image search with a tiny bag-of-delegates representation,,2012
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45f3bf505f1ce9cc600c867b1fb2aa5edd5feed8,Fully automatic facial feature point detection using Gabor feature based boosted classifiers,"2005 IEEE International Conference on Systems, Man and Cybernetics",2005
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45fbeed124a8956477dbfc862c758a2ee2681278,Pose Invariant Approach for Face Recognition at Distance,,2012
4511e09ee26044cb46073a8c2f6e1e0fbabe33e8,A Graph Based Approach for Finding People in News,,2007
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+1f6576ef2f8b986b44f06bb83b4238d1ffb6c990,Salient feature and reliable classifier selection for facial expression classification,Pattern Recognition,2010
1fd2ed45fb3ba77f10c83f0eef3b66955645dfe0,Generalized Unsupervised Manifold Alignment,,2014
1f2d12531a1421bafafe71b3ad53cb080917b1a7,Joint optimization of manifold learning and sparse representations for face and gesture analysis,,2015
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80193dd633513c2d756c3f568ffa0ebc1bb5213e,Wavelet Subspace Method for Real-Time Face Tracking,,2001
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+8031b81338c05d5fe4e2e5f8820d185b32734fb6,Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks,,2017
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747d5fe667519acea1bee3df5cf94d9d6f874f20,Transferring Common-Sense Knowledge for Object Detection,,2018
+74ac172076ac9550b32cce7b8e8989f1eb113515,Zero-Shot Learning with Multi-Battery Factor Analysis,Signal Processing,2017
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745b42050a68a294e9300228e09b5748d2d20b81,Temporal Human Action Segmentation via Dynamic Clustering,,2018
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1a9337d70a87d0e30966ecd1d7a9b0bbc7be161f,"A novel binary adaptive weight GSA based feature selection for face recognition using local gradient patterns, modified census transform, and local binary patterns",Eng. Appl. of AI,2014
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1a1118cd4339553ad0544a0a131512aee50cf7de,Semantic Image Retrieval via Active Grounding of Visual Situations,CoRR,2017
+2845cc51262f3af6aafbad62690a23e9bc847b07,Looking at my own Face: Visual Processing Strategies in Physical Self-representation,,2017
28e0ed749ebe7eb778cb13853c1456cb6817a166,C-Mantec: A novel constructive neural network algorithm incorporating competition between neurons,Neural networks : the official journal of the International Neural Network Society,2012
28b9d92baea72ec665c54d9d32743cf7bc0912a7,Parametric temporal alignment for the detection of facial action temporal segments,,2014
+283a2bb8aece06b975a1109aaa8daecdf4d3df42,Summary Transfer: Exemplar-based Subset Selection for Video Summarizatio,,2016
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282a3ee79a08486f0619caf0ada210f5c3572367,Accelerated Training for Massive Classification via Dynamic Class Selection,CoRR,2018
288dbc40c027af002298b38954d648fddd4e2fd3,Local Higher-Order Statistics (LHS) for Texture Categorization and Facial Analysis,,2012
28312c3a47c1be3a67365700744d3d6665b86f22,Face Recognition: A Literature Survey1,,2000
287900f41dd880802aa57f602e4094a8a9e5ae56,Expressive deformation profiles for cross expression face recognition,Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012),2012
+2819ac49d1967a3e51e7e65730a666a76ba9a687,Internet Visual Media Processing for Graphics and Vision Applications: A Survey,,2012
28d4e027c7e90b51b7d8908fce68128d1964668a,Level Playing Field for Million Scale Face Recognition,2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017
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+28121cd9150250fe51de62521065c7e2246a73e9,Blind Image Deconvolution using Deep Generative Priors,,2018
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17035089959a14fe644ab1d3b160586c67327db2,VLAD: Encoding Dynamics of Deep Features for Action Recognition,,
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75e9a141b85d902224f849ea61ab135ae98e7bfb,Quantifying human sensitivity to spatio-temporal information in dynamic faces,Vision Research,2014
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2f9c173ccd8c1e6b88d7fb95d6679838bc9ca51d,Gaussian Process Domain Experts for Model Adaptation in Facial Behavior Analysis,2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),2016
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4300fa1221beb9dc81a496cd2f645c990a7ede53,A comparison of generalized linear discriminant analysis algorithms,Pattern Recognition,2008
+43016e51bc6e7939521ec3c2fcff78f35bfc5e92,Explorer Eye - movements reveal attention to social information in autism spectrum disorder,,
+43123e77108e059098194deacae1d1a6044703a2,Manifold Regularized Discriminative Nonnegative Matrix Factorization With Fast Gradient Descent,IEEE Transactions on Image Processing,2011
+4354ed06582b37e52bc23d0b1e86993d88c00e92,MLRank: Multi-correlation Learning to Rank for image annotation,Pattern Recognition,2013
43aa40eaa59244c233f83d81f86e12eba8d74b59,Fast pose invariant face recognition using super coupled multiresolution Markov Random Fields on a GPU,Pattern Recognition Letters,2014
43e268c118ac25f1f0e984b57bc54f0119ded520,Generalized Conditional Gradient for Sparse Estimation,Journal of Machine Learning Research,2017
+430ff8b02caf541377749673dbf71c4d95213f5e,Non-parametric image super-resolution using multiple images,IEEE International Conference on Image Processing 2005,2005
437a720c6f6fc1959ba95e48e487eb3767b4e508,Full interpretation of minimal images.,Cognition,2018
436d80cc1b52365ed7b2477c0b385b6fbbb51d3b,Probabilistic Knowledge Transfer for Deep Representation Learning,,2018
+43b7f3d356ae89b3772f3e64d4456ff0f442d4d3,Bi-level Relative Information Analysis for Multiple-Shot Person Re-Identification,IEICE Transactions,2013
430c4d7ad76e51d83bbd7ec9d3f856043f054915,Two decades of local binary patterns: A survey,CoRR,2016
+885e6f1ef99d04a057d2543cbf2ffc9e7bcfb309,Upper Body Pose Estimation for Team Sports Videos Using a Poselet-Regressor of Spine Pose and Body Orientation Classifiers Conditioned by the Spine Angle Prior,IPSJ Trans. Computer Vision and Applications,2015
+88ad82e6f2264f75f7783232ba9185a2f931a5d1,Facial Expression Analysis under Partial Occlusion: A Survey,CoRR,2018
+88e1580e975ec0edab7327783f59665dc711ee7c,"An evaluation of crowd counting methods, features and regression models",Computer Vision and Image Understanding,2015
+88a9b3043a951c622667dcd5f70acd2c850b3950,A review of motion analysis methods for human Nonverbal Communication Computing,Image Vision Comput.,2013
+884e63b5371883a1502f5c39a08e5100c89a5427,New Advances in Automatic Gait Recognition,Inf. Sec. Techn. Report,2002
+8877c5afa16b025452e444e0798292fe7ee4dca6,Occlusion Robust Symbol Level Fusion for Multiple People Tracking,Unknown,2017
+88e453bd1f05fca156697a9dbab86d0c37fe3940,A Novel Neighborhood Defined Feature Selection on Phase Congruency Images for Recognition of Faces with Extreme Variations,Unknown,2006
+882c1e78bd8e89200fc639076eab19843d118432,Articulated human body parts detection based on cluster background subtraction and foreground matching,Neurocomputing,2013
+88c307c51594c6d802080a0780d0d654e2e2891f,Visual question answering: A survey of methods and datasets,Computer Vision and Image Understanding,2017
+9fb372fd2fb79571de1cc388154d4a3f0547d440,PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence,,2018
6b333b2c6311e36c2bde920ab5813f8cfcf2b67b,Pain Level Detection From Facial Image Captured by Smartphone,JIP,2016
6b9aa288ce7740ec5ce9826c66d059ddcfd8dba9,BNU-LSVED 2.0: Spontaneous multimodal student affect database with multi-dimensional labels,Sig. Proc.: Image Comm.,2017
+6b5d7223239f02a091db8b9d3624b59994402419,Improving Twitter Sentiment Classification via Multi-Level Sentiment-Enriched Word Embeddings,CoRR,2016
+6b43dcc17e7219f6b8b76c65dc1a62271b11b2dc,Can We Boost the Power of the Viola-Jones Face Detector Using Pre-processing? An Empirical Study,CoRR,2017
+6b327af674145a34597986ec60f2a49cff7ed155,Defense-gan: Protecting Classifiers against Adversarial Attacks Using Generative Models,,2017
+6bed9d0aec57a121b7950149f294e35ddf8902a2,An Improved Face Recognition Algorithm Using Histogram-Based Features in Spatial and Frequency Domains,Unknown,2016
+6b3c5ad668d793893dd5169c771c23bc9ffeff31,Mixture of related regressions for head pose estimation,2013 IEEE International Conference on Image Processing,2013
+6bb95a0f3668cd36407c85899b71c9fe44bf9573,Face Attribute Prediction Using Off-The-Shelf Deep Learning Networks,CoRR,2016
6b1b43d58faed7b457b1d4e8c16f5f7e7d819239,A multi-task model for simultaneous face identification and facial expression recognition,Neurocomputing,2016
+6b57526152a6093171a05499cb62840ba28da660,Weakly Supervised Object Detection with Pointwise Mutual Information,CoRR,2018
6b35b15ceba2f26cf949f23347ec95bbbf7bed64,"RSILC: Rotation- and Scale-Invariant, Line-based Color-aware descriptor",Image Vision Comput.,2015
6bb630dfa797168e6627d972560c3d438f71ea99,Sequential Deep Trajectory Descriptor for Action Recognition With Three-Stream CNN,IEEE Transactions on Multimedia,2017
+07eeb8f39f7d397a2ab236ce830c3b5c19adf9d7,Op-brai130094 1..16,,2013
+07c3c015cbe635ede679a87a9725a65902aa4a17,Optimal solutions for semantic image decomposition,Image Vision Comput.,2012
071af21377cc76d5c05100a745fb13cb2e40500f,Structured Prediction for Event Detection,,2016
+079edd5cf7968ac4759dfe72af2042cf6e990efc,Delving Deeper into Convolutional Networks for Learning Video Representations,CoRR,2015
+0781498a38ac67722bb690cd04f69a80e07a55ae,Supplementary Materials: Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification,,2016
+07cb6efa6734b5cc22a38b0855189d12791a0551,Running head: ATTENTION TO FACE IN ASD Faces Do Not Capture Special Attention in Children with Autism Spectrum Disorder: A Change Blindness Study,,2016
073eaa49ccde15b62425cda1d9feab0fea03a842,Delft University of Technology On detecting the playing/non-playing activity of musicians in symphonic music videos,,2017
+07c80339af2dc54c94c03c01db71a3d7d2bb9ea8,Learning Without Forgetting,,2016
+07d95be4922670ef2f8b11997e0c00eb643f3fca,The First Facial Landmark Tracking in-the-Wild Challenge: Benchmark and Results,2015 IEEE International Conference on Computer Vision Workshop (ICCVW),2015
+0756e1de70c4e3a58c78f2e9cdb2646555386724,Recognizing scene viewpoint using panoramic place representation Citation,,2012
+07fc8b4ba4a0f61cf1ea7c0bfefc556d44fb334d,Improving object detection with boosted histograms,Image Vision Comput.,2009
+38a75d92684122da464a7fb1f9adc8f6acec74da,Joint representation classification for collective face recognition,Pattern Recognition,2017
380dd0ddd5d69adc52defc095570d1c22952f5cc,Improving Smiling Detection with Race and Gender Diversity,CoRR,2017
+38b8f80b05db035f1ba9eb2e76629ce937fc956c,Robust bilinear factorization with missing and grossly corrupted observations,Inf. Sci.,2015
+3825b2ccbf2b305fa051bd7b62306108d61a753e,Neuroimaging in child clinical populations: considerations for a successful research program.,Journal of the American Academy of Child and Adolescent Psychiatry,2012
+38fb6eada1e62e0c25c45023107ca8ab3426c162,A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition,Computer Vision and Image Understanding,2006
+38fb67d26d27653f7aa538a1f0237e281d5a4e6d,Humans have idiosyncratic and task-specific scanpaths for judging faces,Vision Research,2015
+38558bd53b5bab485ca4abca35a0401c0c387883,Illumination Invariant Face Recognition Using Quaternion-Based Correlation Filters,Journal of Mathematical Imaging and Vision,2012
+384af919a685fbcb8dce37475a45cbf8dfe5c8f5,Using Richer Models for Articulated Pose Estimation of Footballers,,2012
385750bcf95036c808d63db0e0b14768463ff4c6,Autoencoding beyond pixels using a learned similarity metric,,2016
+3805cd9f0db2a71bd33cb72ad6ca7bd23fe95e35,A support vector approach for cross-modal search of images and texts,Computer Vision and Image Understanding,2017
+38308a4fc038611797a5193c6d3abb593a6a3a37,Structured Sparse Linear Discriminant Analysis,2012 19th IEEE International Conference on Image Processing,2012
38861d0d3a0292c1f54153b303b0d791cbba1d50,Making risk minimization tolerant to label noise,Neurocomputing,2015
+384112e458d887c036fb313953a217173eea5f93,Kernel Conditional Ordinal Random Fields for Temporal Segmentation of Facial Action Units,,2012
38192a0f9261d9727b119e294a65f2e25f72d7e6,Facial feature point detection: A comprehensive survey,Neurocomputing,2018
+384156c658b312946eebab736235f03f726c787a,Static topographic modeling for facial expression recognition and analysis,Computer Vision and Image Understanding,2007
+000b27b8725432580ef9d5b9c5402fc7b76fd68b,Neural correlates of biased social fear learning and interaction in an intergroup context,,2015
+00b0ea36d426b35994b8a586a18651abf1dd1f93,Sparse Dictionary-based Attributes for Action Recognition and Summarization,CoRR,2013
+007394c2bae389cf43e46db4567dafe206355c25,MISE: Providing performance predictability and improving fairness in shared main memory systems,2013 IEEE 19th International Symposium on High Performance Computer Architecture (HPCA),2013
+00c3ccc8d7e799a39ca15415775e89e2b41a3972,Tracking many vehicles in wide area aerial surveillance,2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops,2012
0004f72a00096fa410b179ad12aa3a0d10fc853c,Visual Interpretation of Human Body Language for Interactive Scenarios,Unknown,2012
+00ab6bb0df7fd605038d64eb5798b31481a39dd0,Delayed-Dynamic-Selective (DDS) Prediction for Reducing Extreme Tail Latency in Web Search,,2015
+005f4fb2256c6fa293e738bb53ebf437a5b98d73,CrowdCam: Instantaneous Navigation of Crowd Images Using Angled Graph Citation,,2013
+008baae7037a47f69804c2eb8438d366a6e67486,3D Human Pose Estimation via Deep Learning from 2D Annotations,2016 Fourth International Conference on 3D Vision (3DV),2016
+0020207f7e004a5f3faeee9b7c3ee86ceae88a2d,Weakly Supervised Top-down Salient Object Detection,CoRR,2016
+00cb5ee9c7f016a8ece5dd3b34e74ee65ee19e2d,Seeing it differently: visual processing in autism.,Trends in cognitive sciences,2006
+00fe3d95d0fd5f1433d81405bee772c4fe9af9c6,What value high level concepts in vision to language problems?,,2015
+0021e292c9d8fd19f5edd1cde5bc99c112f1992d,Fast multi-scale local phase quantization histogram for face recognition,Pattern Recognition Letters,2012
+006415b0ae3ac6ff9a2b482bc3d23ad15e8f09f2,Pedestrian Detection by Boosting-based Feature Co-occurrence Representation *,,2009
0059b3dfc7056f26de1eabaafd1ad542e34c2c2e,Can Help You Change! An Empathic Virtual Agent Delivers Behavior Change Health Interventions,,2014
+00ae6ce99eb9ccefd8409e4ef5e3bbb5248821d6,Geometry Issues of Gaze Estimation,,2008
6eaf446dec00536858548fe7cc66025b70ce20eb,GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks,CoRR,2017
+6e7c2f13bc2cf5547f4d8a845dc115108e52b27a,Emotional and effortful control abilities in 42-month-old very preterm and full-term children.,Early human development,2014
+6eeeb96350c676bbb9bf765851362e590e32eaed,Max-Margin Zero-Shot Learning for Multi-class Classification,,2015
+6eb5f375d67dd690ec3b134de7caecde461e8c72,Learning to Detect Concepts from Webly-Labeled Video Data,,2016
6eaeac9ae2a1697fa0aa8e394edc64f32762f578,Constraint Score: A new filter method for feature selection with pairwise constraints,Pattern Recognition,2008
6ee2ea416382d659a0dddc7a88fc093accc2f8ee,Graph-Preserving Sparse Nonnegative Matrix Factorization With Application to Facial Expression Recognition,"IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)",2011
+6ef28af882e408ff63f83ca670392a008d203fbc,Learning relational object categories using behavioral exploration and multimodal perception,2014 IEEE International Conference on Robotics and Automation (ICRA),2014
6e12ba518816cbc2d987200c461dc907fd19f533,A computational approach to body mass index prediction from face images,Image Vision Comput.,2013
+6ecd8ee110381e073fe6b4e79029fbb59d2b0e02,Face recognition via adaptive sparse representations of random patches,2014 IEEE International Workshop on Information Forensics and Security (WIFS),2014
+9ac7bb9be33f41d02754bc33a39974496ead0b27,Integrated local binary pattern texture features for classification of breast tissue imaged by optical coherence microscopy,Medical image analysis,2017
+9a0331bac634f67c2a993c36da95481fe53709bf,Second-order extended Kalman filter for extended object and group tracking,2016 19th International Conference on Information Fusion (FUSION),2016
+9a99c23aaac3598180c115e3843d06faa4211fe4,Scalable Mobile Visual Classification by Kernel Preserving Projection Over High-Dimensional Features,IEEE Trans. Multimedia,2014
+9af4d310415afb925e157e7120b7aa596298888c,Neurobiological correlates of social functioning in autism.,Clinical psychology review,2010
+9a3fe4631e8507e3409631d506de3cbe793f0b42,Hybrid eye center localization using cascaded regression and hand-crafted model fitting,Image Vision Comput.,2018
36b40c75a3e53c633c4afb5a9309d10e12c292c7,Facial Expression Recognition Based on Fusion of Multiple Gabor Features,18th International Conference on Pattern Recognition (ICPR'06),2006
+367951ba687e4e52ca4ee1327627b332afc45fae,Consistent Optical Flow Maps for Full and Micro Facial Expression Recognition,Unknown,2017
365f67fe670bf55dc9ccdcd6888115264b2a2c56,Improving facial analysis and performance driven animation through disentangling identity and expression,Image Vision Comput.,2016
+36d76954bcb4f381f3590598d5f00bb842ffddf7,Human Pose Estimation Using Consistent Max Covering,IEEE Transactions on Pattern Analysis and Machine Intelligence,2009
+369634f497852e05d5e72b12874e2a3db2d3945f,Description of interest regions with local binary patterns,Pattern Recognition,2009
+36e4578e29adacc5b44edd3bf9f2a77561b0f2e0,Directional binary code with application to PolyU near-infrared face database,Pattern Recognition Letters,2010
+36c5421d477697a8692fe6a51ce62473e690c62f,Group Affect Prediction Using Emotion Heatmaps and Scene Information,CoRR,2017
+36ea75e14b69bed454fde6076ea6b85ed87fbb14,Face Recognition using a Kernelization of Graph Embedding Pang,,
366d20f8fd25b4fe4f7dc95068abc6c6cabe1194,Are facial attributes adversarially robust?,2016 23rd International Conference on Pattern Recognition (ICPR),2016
362ba8317aba71c78dafca023be60fb71320381d,Nighttime face recognition at large standoff: Cross-distance and cross-spectral matching,Pattern Recognition,2014
+3624ca25f09f3acbcf4d3a4c40b9e45a29c22b94,Face recognition using second-order discriminant tensor subspace analysis,Neurocomputing,2011
5c4ce36063dd3496a5926afd301e562899ff53ea,A Survey on Content-Aware Video Analysis for Sports,CoRR,2017
5c2a7518fb26a37139cebff76753d83e4da25159,De-identification for privacy protection in multimedia content: A survey,Sig. Proc.: Image Comm.,2016
+5cfe70ccacd302938620662190c573cb6f19bdfb,Searching the Past: An Improved Shape Descriptor to Retrieve,,2011
5c473cfda1d7c384724fbb139dfe8cb39f79f626,Facial expression recognition based on meta probability codes,Pattern Analysis and Applications,2012
+5cd47df260e65b2650a1123a2136ee5bc918d4c6,Deep learning for source camera identification on mobile devices,CoRR,2017
+5cd2425bfbfbc1413c5c853d27c35f8ce5d8f144,Face Recognition Using Discrete Orthogonal Hahn Moments,Unknown,2015
+5ce80b41443518a14d800f6b93b4057bbb007432,BenchIP: Benchmarking Intelligence Processors,Journal of Computer Science and Technology,2018
+5ce035891b920e4728a50af7e4afb54e088f5183,Modelling the perceptual similarity of facial expressions from image statistics and neural responses,NeuroImage,2016
+097dc32f712550f655facf74212a70ce3828d98c,Image classification using object detectors,2013 IEEE International Conference on Image Processing,2013
+09ae4b2c851a06e0bde3f4e00b9b7c6e5ac3ddac,Recognition of natural scenes from global properties: Seeing the forest without representing the trees,,2009
+09e63de98c7551079486f66bddb62a253fc596b7,Efficient parametrization of multi-domain deep neural networks,CoRR,2018
0952ac6ce94c98049d518d29c18d136b1f04b0c0,Incremental Kernel PCA for Efficient Non-linear Feature Extraction,,2006
+09af91e913324255bd8358e62cd3b8a25f7141ec,Comparing strategies for 3D face recognition from a 3D sensor,2013 IEEE RO-MAN,2013
+09fbcd901db726caec1f3bcbda5266ca72c7deb6,Fusion of Heterogeneous Data in Convolutional Networks for Urban Semantic Labeling (Invited Paper),CoRR,2017
+0922e7d583d02f6078e59974a3de4452382ca9dd,Local approach for face verification in polar frequency domain,Image Vision Comput.,2006
+0997f69e081bc460923a34e55b525a2aa3c4548a,Learning locality-constrained collaborative representation for robust face recognition,Pattern Recognition,2014
+0949548b95e225dcb0ab88ba21f385ac6b5d81ae,Learning Driving Models with a Surround-View Camera System and a Route Planner,,2018
+0921548f06db5d4959126c823cda0bbeae542937,Cognitive Science in the era of Artificial Intelligence: A roadmap for reverse-engineering the infant language-learner,Cognition,2018
+091d0c7b3576fd6f3bb2bec344deb8f81fc1f7c6,Yin and Yang: Balancing and Answering Binary Visual Questions,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
+097f1f58f1cb8dc9e0622e001d7f6cbb624d542c,Partner naming and forgetting: Recall of network members,Social networks,2007
+09fded4954d2df2ccabf5812a0cf5040e627a312,Face Recognition With Contiguous Occlusion Using Markov Random Fields,,2009
+09a05ecae987d9ababf5fe52323f69fa3e889d83,Part Bricolage: Flow-Assisted Part-Based Graphs for Detecting Activities in Videos,,2014
+09798b13739edabd55830fc5589d8ed263d62c82,"A cross-syndrome study of the development of holistic face recognition in children with autism, Down syndrome, and Williams syndrome.",Journal of experimental child psychology,2009
097104fc731a15fad07479f4f2c4be2e071054a2,Texture and shape information fusion for facial expression and facial action unit recognition,Pattern Recognition,2008
09111da0aedb231c8484601444296c50ca0b5388,"Joint estimation of age, gender and ethnicity: CCA vs. PLS",2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+092a4a0f16287c26dcc833958b87b32346546c8b,Multiple Object Tracking with Kernelized Correlation Filters in Urban Mixed Traffic,2017 14th Conference on Computer and Robot Vision (CRV),2017
+09fb440dd2daf2b93e36dd5df93950f0f3bda685,Symmetric low-rank representation for subspace clustering,Neurocomputing,2016
+5db25e8c1e45bcdb64b743f81dbdc69f32c70004,Shadow detection: A survey and comparative evaluation of recent methods,Pattern Recognition,2012
5d485501f9c2030ab33f97972aa7585d3a0d59a7,Learning Bayesian network parameters under incomplete data with domain knowledge,Pattern Recognition,2009
+5d9d1b95d5afd58f6e53512b7ddd04b78d62864c,Fast approximate k-means via cluster closures,2012 IEEE Conference on Computer Vision and Pattern Recognition,2012
5dc056fe911a3e34a932513abe637076250d96da,Real-time facial feature detection using conditional regression forests,2012 IEEE Conference on Computer Vision and Pattern Recognition,2012
+5d76a25936366c6619d2b5e6b74106cdb53a4978,Detecting violent and abnormal crowd activity using temporal analysis of grey level co-occurrence matrix (GLCM)-based texture measures,Machine Vision and Applications,2017
+5dbae8c58341d1f6e475ebd03aa6b8abbc9d149d,Hallucinating optimal high-dimensional subspaces,Pattern Recognition,2014
5dcf78de4d3d867d0fd4a3105f0defae2234b9cb,A method for improving consistency in photometric databases,,2012
+5d7070067a75f57c841d0d30b23e21101da606b2,Generative Modeling using the Sliced Wasserstein Distance,CoRR,2018
+5d8ab5c473eb9e083ceb35ebeb00a062114ee6ac,A Reinforcement Learning Approach to Target Tracking in a Camera Network,CoRR,2018
+5d44c675addcb6e74cbc5a9c48df0d754bdbcd98,Emotion Classification using Adaptive SVMs,,2012
+5dc14823862ff1f07dec483d5b4860727055ea79,Multi-Instance Dynamic Ordinal Random Fields for Weakly-supervised Facial Behavior Analysis,,2018
5d01283474b73a46d80745ad0cc0c4da14aae194,Classification schemes based on Partial Least Squares for face identification,J. Visual Communication and Image Representation,2015
31aa20911cc7a2b556e7d273f0bdd5a2f0671e0a,Patch-based Face Recognition using a Hierarchical Multi-label Matcher,,2018
31b05f65405534a696a847dd19c621b7b8588263,UMDFaces: An annotated face dataset for training deep networks,2017 IEEE International Joint Conference on Biometrics (IJCB),2017
+3180192694594f345f6fc5bed5a473762dfec522,An online spatio-temporal tensor learning model for visual tracking and its applications to facial expression recognition,Expert Syst. Appl.,2017
+31b0f482908d16d82826f2fc5fba67128cb07e4e,Context Generation with Image Based Sensors: An Interdisciplinary Enquiry on Technical and Social Issues and their Implications for System Design,,2012
31e57fa83ac60c03d884774d2b515813493977b9,Face alignment with cascaded semi-parametric deep greedy neural forests,Pattern Recognition Letters,2018
+318b52b1f37669c24415f4aab6266c72a3b255fe,Oxytocin's impact on social face processing is stronger in homosexual than heterosexual men,Psychoneuroendocrinology,2014
+31cd61f05ea86a3eb08e06f1d0c2aa810805282f,On the effect of hyperedge weights on hypergraph learning,Image Vision Comput.,2017
31b58ced31f22eab10bd3ee2d9174e7c14c27c01,Nonparametric Object and Scene Recognition,,2008
+3148c4ca284d6521769dfde54e3e7693228bda06,Neurodevelopmental changes across adolescence in viewing and labeling dynamic peer emotions,Developmental Cognitive Neuroscience,2017
+318a81acdd15a0ab2f706b5f53ee9d4d5d86237f,Multi-label learning: a review of the state of the art and ongoing research,Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery,2014
+31af1f2614823504d1d643d1b019c6f9d2150b15,Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs,CoRR,2017
312afff739d1e0fcd3410adf78be1c66b3480396,Facial Attributes: Accuracy and Adversarial Robustness,CoRR,2018
+31a22514efe2b25088a91d8d4db9bb31ae1e9575,Proposing Plausible Answers for Open-ended Visual Question Answering,CoRR,2016
+311fcda76dc7b7cf50b17c705a2aaaaab5ed6a04,Learning Distributed Representations of Sentences from Unlabelled Data,,2016
+313387fc6c5b5561f23fdc63a546b18f54f6bebc,Convex Non-negative Matrix Factorization in the Wild,2009 Ninth IEEE International Conference on Data Mining,2009
31bb49ba7df94b88add9e3c2db72a4a98927bb05,Static and dynamic 3D facial expression recognition: A comprehensive survey,Image Vision Comput.,2012
+91816b4b5fb74710144b3294dec61aab4de12fd3,"The more you learn, the less you store: Memory-controlled incremental SVM for visual place recognition",Image Vision Comput.,2010
91883dabc11245e393786d85941fb99a6248c1fb,Face alignment in-the-wild: A Survey,Computer Vision and Image Understanding,2017
919d0e681c4ef687bf0b89fe7c0615221e9a1d30,Fractal Techniques for Face Recognition,,2009
912a6a97af390d009773452814a401e258b77640,An on-line variational Bayesian model for multi-person tracking from cluttered scenes,Computer Vision and Image Understanding,2016
+913352e569d3e5eeb90de2a7979533355e02acc9,3D Motion Data aided Human Action Recognition and Pose Estimation,,2013
918b72a47b7f378bde0ba29c908babf6dab6f833,Uncorrelated trace ratio linear discriminant analysis for undersampled problems,Pattern Recognition Letters,2011
91d2fe6fdf180e8427c65ffb3d895bf9f0ec4fa0,Tensor reduction error analysis - Applications to video compression and classification,,2008
+91027fd707aed714c9095551e3d63b3e18ee138b,Prediction as a Rule for Unsupervised Learning in Deep Neural Networks,,2017
+654ad3b6f7c6de7184a9e8eec724e56274f27e3f,Alternating Back-Propagation for Generator Network,,2017
+6512f42fd70b42300ea3f318e860d270cd6d3b0a,Joint multi-person detection and tracking from overlapping cameras,Computer Vision and Image Understanding,2014
+65ef33636f07d4d1aa1b22a5b67f1f402d6a5900,PartBook for image parsing,2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops,2012
+65ee4de888e5b934429dcb126ee0ae544156c9bd,Face recognition using linear representation ensembles,Pattern Recognition,2016
+625d68fdb0db5c3ad27c8defd608c3841086392d,Revisiting Additive Quantization,,2016
620339aef06aed07a78f9ed1a057a25433faa58b,Human Action Recognition and Prediction: A Survey,CoRR,2018
62b3598b401c807288a113796f424612cc5833ca,"X2Face: A network for controlling face generation by using images, audio, and pose codes",CoRR,2018
6257a622ed6bd1b8759ae837b50580657e676192,Unsupervised Learning aids Prediction: Using Future Representation Learning Variantial Autoencoder for Human Action Prediction,CoRR,2017
+62e878445851c9d5e89a0ef8d49f11acd77e78ec,A log square average case algorithm to make insertions in fast similarity search,Pattern Recognition Letters,2012
620e1dbf88069408b008347cd563e16aeeebeb83,FaceDCAPTCHA: Face detection based color image CAPTCHA,Future Generation Comp. Syst.,2014
+96c298354bee7c6c8dcc58f8fa749cfa75f5452e,Semantic segmentation of images exploiting DCT based features and random forest,Pattern Recognition,2016
+96f77524d0a26c27775162b1474915c1452f346f,Learning multiple visual domains with residual adapters,Unknown,2017
+96faccdddef887673d6007fed8ff2574580cae1f,"Multi-path Region-Based Convolutional Neural Network for Accurate Detection of Unconstrained ""Hard Faces""",,2017
+960ad662c2bb454d69006492cc3f52d1550de55d,Visualizing Graphs and Clusters as Maps,IEEE Computer Graphics and Applications,2010
964a3196d44f0fefa7de3403849d22bbafa73886,Uncorrelated slow feature discriminant analysis using globality preserving projections for feature extraction,Neurocomputing,2015
+969dd8bc1179c047523d257516ade5d831d701ad,A weakly supervised method for makeup-invariant face verification,Pattern Recognition,2017
9636c7d3643fc598dacb83d71f199f1d2cc34415,Automatic facial attribute analysis via adaptive sparse representation of random patches,Pattern Recognition Letters,2015
+3a8245748a5b682845784dab131f6d8240b09f7a,Content based Medical Image Retrieval: use of Generalized Gaussian Density to model BEMD's IMF,,2009
+3aa9d370378bce52238f2a8290926949ab38f0ae,A two-stage linear discriminant analysis for face-recognition,Pattern Recognition Letters,2012
+3af9e70e81ea67729953c9c0e5269881b35e3cc7,Coupling-and-decoupling: A hierarchical model for occlusion-free object detection,Pattern Recognition,2014
+3a415f3fc013bf3d045d9a45c7ed5d83996f4556,Expression modeling for expression-invariant face recognition,Computers & Graphics,2010
+3a3087c03f0403c3e180f47f9001509e852b82b3,Likelihood ratio based mixed resolution facial comparison,3rd International Workshop on Biometrics and Forensics (IWBF 2015),2015
+3a2f235fa82b41aee2a45194c1b159f777abffe0,Kernel sparse representation with pixel-level and region-level local feature kernels for face recognition,Neurocomputing,2014
+3a3c47b6da1ea1b8d57ce41d9ddb54a774e1914d,High-Level Prediction Signals in a Low-Level Area of the Macaque Face-Processing Hierarchy.,Neuron,2017
+3adbf4ed5e4e3f59afb7509119667c8701c7cf37,Activity-conditioned continuous human pose estimation for performance analysis of athletes using the example of swimming,CoRR,2018
+544fd5065c0f4f6b0a9ba1805785b5ef3cd68231,Bag-of-Genres for Video Genre Retrieval,CoRR,2015
+549afb73666202ec3c02a59de611387f723c1cf9,"Compact, Adaptive and Discriminative Spatial Pyramid for Improved Scene and Object Classification",,2012
+542a2ddc53d80d58a8791ab1a72dad660035e114,A Survey of Recent Advances in CNN-based Single Image Crowd Counting and Density Estimation,CoRR,2017
+5480bfe964e85770615a73837e5451888bfaf689,The Detection of Concept Frames Using Clustering Multi-instance Learning,2010 20th International Conference on Pattern Recognition,2010
+54760ceffc46a7a5425260834840fcfe910e0f3b,Viewing it differently: social scene perception in Williams syndrome and autism.,Neuropsychologia,2008
+543a005dd1c6118c73e099e65119ae10c790969e,The Effect of Image Resolution on the Performance of a Face Recognition System,"2006 9th International Conference on Control, Automation, Robotics and Vision",2006
+54bac87151febb2e9eecf237d6498f8ed8ac3b1e,A case study on appearance based feature extraction techniques and their susceptibility to image degradations for the task of face recognition,Unknown,2009
98b2f21db344b8b9f7747feaf86f92558595990c,Semantically Decomposing the Latent Spaces of Generative Adversarial Networks,CoRR,2017
+987f73c1e17540716f47e2b4bd434a09ceab5074,Extensive articulated human detection by voting Cluster Boosted Tree,2009 Workshop on Applications of Computer Vision (WACV),2009
+980fd3fb067215017af8d13381e1d95fe3a34727,SPECIAL SECTION BRIEF REPORT Autism and the Extraction of Emotion From Briefly Presented Facial Expressions: Stumbling at the First Step of Empathy,,2008
+98aa4bc56aa6aa15735727a91bb3711bc90e73b2,Fast Low-Rank Subspace Segmentation,IEEE Transactions on Knowledge and Data Engineering,2014
+98a120802aef324599e8b9014decfeb2236a78a3,Crowdsourced Facial Expression Mapping Using a 3D Avatar,,2016
982fed5c11e76dfef766ad9ff081bfa25e62415a,Undersampled Face Recognition via Robust Auxiliary Dictionary Learning,IEEE Transactions on Image Processing,2015
+9857eeded6b7608ff862174742b38946102f5008,Interpretable Facial Relational Network Using Relational Importance,CoRR,2017
+53288f4c3bcb993f8561b4af1776ec3145d7a051,Im2Text and Text2Im: Associating Images and Texts for Cross-Modal Retrieval (Extended Abstract),,2014
+531a40720f2809c560840e6d3afb11a31ad0b9a0,Development of social attention 1 Running head: DEVELOPMENT OF SOCIAL ATTENTION Measuring the development of social attention using free-viewing,,2010
+537fb9d35e56be9436b42a9e5e3405523c2f1e0e,Visual Analysis of Eye State and Head Pose for Driver Alertness Monitoring,IEEE Transactions on Intelligent Transportation Systems,2013
5334ac0a6438483890d5eef64f6db93f44aacdf4,Minh Hoai: Regularizedmax Pooling for Image Categorization,,2014
53dd25350d3b3aaf19beb2104f1e389e3442df61,Evolutionary Eigenspace Learning using CCIPCA and IPCA for Face Recognition,Unknown,2009
+53f0d493c64c908c479f28b4b0cc38aa2124697d,"mdBRIEF - a fast online-adaptable, distorted binary descriptor for real-time applications using calibrated wide-angle or fisheye cameras",Computer Vision and Image Understanding,2017
+536b37fe90a2f0bd8b40b7eb7ecf89b25a1c8ede,Computer Science and Artificial Intelligence Laboratory Receptive Field Structures for Recognition,,2005
+531fd9be964d18ba7970bd1ca6c3b9dc91b8d2ab,From the heart to the mind's eye: cardiac vagal tone is related to visual perception of fearful faces at high spatial frequency.,Biological psychology,2012
530243b61fa5aea19b454b7dbcac9f463ed0460e,ReenactGAN: Learning to Reenact Faces via Boundary Transfer,CoRR,2018
539ca9db570b5e43be0576bb250e1ba7a727d640,A Large-Scale Database of Images and Captions for Automatic Face Naming,,2011
53c8cbc4a3a3752a74f79b74370ed8aeed97db85,Learning person-specific models for facial expression and action unit recognition,Pattern Recognition Letters,2013
+53e8781bb152e8e05ffe03737082448ac3378e37,A unified framework for event summarization and rare event detection,2012 IEEE Conference on Computer Vision and Pattern Recognition,2012
530ce1097d0681a0f9d3ce877c5ba31617b1d709,A component based approach for classifying the seven universal facial expressions of emotion,2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC),2013
+3f4b8fe5edfac918c1c74317242b2d91346d5fb6,Adaptive discriminant analysis for face recognition from single sample per person,Face and Gesture 2011,2011
+3fd970da1fd9ebcf1b97f4d16f5274b25666471b,Clothing-invariant gait identification using part-based clothing categorization and adaptive weight control,Pattern Recognition,2010
+3fd203807fab28243f84d2360572796869ccde90,Deep Video Code for Efficient Face Video Retrieval,,2016
+3f775e3be9e1a00ebf4fd281e524932e88cec0ae,Deep Contextual Recurrent Residual Networks for Scene Labeling,CoRR,2017
3f5cf3771446da44d48f1d5ca2121c52975bb3d3,All the Images of an Outdoor Scene,,2002
+3f7c4fb00be2124fe8e2e9d48caf86265b6471b7,Active Subspace: Toward Scalable Low-Rank Learning,Neural computation,2012
+3f85020032ae335baf57aaf65c4831b67e4030c9,MonoPerfCap: Human Performance Capture from Monocular Video,CoRR,2017
+3f8537c2141ba19a03876c7bb5c1e71a01b56838,Face image super-resolution using 2D CCA,Signal Processing,2014
+3f45d73a7b8d10a59a68688c11950e003f4852fc,Joint Dimension Reduction and Metric Learning for Person Re-identification,CoRR,2014
+3f04caa9d17e6b26e4446578c020bf3b35df9de3,Video Captioning with Multi-Faceted Attention,CoRR,2016
+30801beeb4436ce1f15e641b74a3daae836b0a0d,Deep Convolutional Inverse Graphics Network,,2015
+3039381ced50a910234ceca5133a69aceb324faf,3D face recognition using passive stereo vision,IEEE International Conference on Image Processing 2005,2005
+307dae1bfa57c0c5dcf2abd22f2e16f7e894fa29,Local Kernel Feature Analysis (LKFA) for object recognition,Neurocomputing,2011
303065c44cf847849d04da16b8b1d9a120cef73a,"3D Face Morphable Models ""In-the-Wild""",,2017
+30aa681ab80a830c3890090b0da3f1e786bd66ff,Unconstrained Face Detection and Open-Set Face Recognition Challenge,2017 IEEE International Joint Conference on Biometrics (IJCB),2017
+300ce2d1ff744fea95fda05d2f3d48766c283042,Semantic Stixels: Depth is not enough,2016 IEEE Intelligent Vehicles Symposium (IV),2016
+30b74c53bd7a9b364920e5074b52b3f737a71c89,LSTM Pose Machines,CoRR,2017
+30af3e6e0165ebc9a641420d14ca285105550205,LIFT: A new framework of learning from testing data for face recognition,Neurocomputing,2011
+3093a57be04309e2380ac98b568dd8fcb8077ada,Leveraging local neighborhood topology for large scale person re-identification,Pattern Recognition,2014
+30e6cf0c3cb38997acb05a2f5ed86269643ae3ed,Weakly Supervised Semantic Labelling and Instance Segmentation,CoRR,2016
+3068dad264ece487e21fbb689d8f47d498c5aaa4,Minmin Chen 2013,,2013
+30b74e60ec11c0ebc4e640637d56d85872dd17ce,Large-Scale Human Activity Mapping using Geo-Tagged Videos,CoRR,2017
+304baa0481562d468fb7cfa1f89e726f82701a39,Towards Optimal Symbolization for Time Series Comparisons,2013 IEEE 13th International Conference on Data Mining Workshops,2013
304a306d2a55ea41c2355bd9310e332fa76b3cb0,Variable-state Latent Conditional Random Field models for facial expression analysis,Image Vision Comput.,2017
+3064424c1abe01dd2f4d2c9022f5ee1312e3cec9,Configural processing in autism and its relationship to face processing.,Neuropsychologia,2006
+5e4fb9b216657cbed1125b3be359ee482168c3e3,Discriminative graph regularized extreme learning machine and its application to face recognition,Neurocomputing,2015
+5e0f8c355a37a5a89351c02f174e7a5ddcb98683,Microsoft COCO: Common Objects in Context,,2014
+5e56c8776b5aa6edce068255134ea31670755b0c,Robust indoor speaker recognition in a network of audio and video sensors,Signal Processing,2016
+5eb25ec961c6a86c93001a44d38b3eb894e7e5fb,FPGA Hardware with Target-Reconfigurable Object Detector,IEICE Transactions,2015
5e821cb036010bef259046a96fe26e681f20266e,The Local Binary Pattern Approach and its Applications to Face Analysis,"2008 First Workshops on Image Processing Theory, Tools and Applications",2008
+5ec89f73a8d1e817ebf654f91318d28c9cfebead,Semantically Guided Depth Upsampling,,2016
+5b8164fc9c65cd96fb529c3c8db551027009d4d1,A Low-Dimensional Representation for Robust Partial Isometric Correspondences Computation,Graphical Models,2014
+5b90bf3ebad1583beebcae5f892db2add248bcad,", C . F . F . Costa Filho and M . G . F . Costa Evaluation of Haar Cascade Classifiers Designed for Face Detection",,
+5b74a57508069c719cff3c5410984be76f6b7785,Monotonicity and error type differentiability in performance measures for target detection and tracking in video,2012 IEEE Conference on Computer Vision and Pattern Recognition,2012
+5b35bde1c144cbc96f25c5359ff44e898191dbe1,Semi-Supervised Active Learning with Cross-Class Sample Transfer,,2016
+5b27999b3f066137de537e78113faf4bd942b7c7,EEG analysis for implicit tagging of video data,2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops,2009
+5b5962bdb75c72848c1fb4b34c113ff6101b5a87,Finding Celebrities in Billions of Web Images,IEEE Transactions on Multimedia,2012
+5bcc8ef74efbb959407adfda15a01dad8fcf1648,Understanding Deep Architectures by Interpretable Visual Summaries,CoRR,2018
5b2cfee6e81ef36507ebf3c305e84e9e0473575a,GoDP: Globally Optimized Dual Pathway deep network architecture for facial landmark localization in-the-wild,Image Vision Comput.,2018
+5b14d9264ea1020f05d4e2fc6144e5021986d917,Gabor feature constrained statistical model for efficient landmark localization and face recognition,Pattern Recognition Letters,2009
+5bdb6ad866f52a3fa439e81a88b11d7a78904b07,A video-based door monitoring system using local appearance-based face models,Computer Vision and Image Understanding,2010
+5b5d8b55e3365f74f4dbdbfdf7b72452a688692f,DelugeNets: Deep Networks with Massive and Flexible Cross-layer Information Inflows,CoRR,2016
5b0ebb8430a04d9259b321fc3c1cc1090b8e600e,The One-Shot similarity kernel,2009 IEEE 12th International Conference on Computer Vision,2009
3765c26362ad1095dfe6744c6d52494ea106a42c,I know what you did last summer: object-level auto-annotation of holiday snaps,2009 IEEE 12th International Conference on Computer Vision,2009
3727ac3d50e31a394b200029b2c350073c1b69e3,Facial Expression Recognition from World Wild Web,2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),2016
+37a892395061206b58127f04fee0e4d2db33803a,Holistic Human Pose Estimation with Regression Forests,,2014
+37faa075574e4abd323ff5ec85934464a5b93a83,Tracking of Facial Feature Points by Combining Singular Tracking Results with a 3D Active Shape Model,,2010
377c6563f97e76a4dc836a0bd23d7673492b1aae,Motion deblurring of faces,,2018
+37fe5b28d4531c93668d4a56d2e3411c2c5978b0,Efficient and Effective Gabor Feature Representation for Face Detection,,2012
+3749eb18758e0f8e97b086e6b36a98fda6e6f945,Emotion Classification using Adaptive SVMs,Unknown,2012
+37fdb70003ab93267ee6c75a333cb62d9e4d0798,Impaired sadness recognition is linked to social interaction deficit in autism.,Neuropsychologia,2007
+3719960f974173f23b88a207a42d67d7a393a89a,Towards better exploiting convolutional neural networks for remote sensing scene classification,Pattern Recognition,2017
+37a3e7a01655b4806df2b95aad193a2965e48a5c,Spatial-Temporal Memory Networks for Video Object Detection,CoRR,2017
+08fe9658c086b842980e86c66bde3cef95bb6bec,Deformable part models are convolutional neural networks,2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2015
+08bf83aeb7ec36815afd1183d8268ab4e10a2961,Learning invariant face recognition from examples.,Neural networks : the official journal of the International Neural Network Society,2013
+084145b7b828d93a5bb5f5dd04f3ccd003dcd5c1,Joint Deep Learning for Car Detection,CoRR,2014
+0878d67f1bca06d3ea8a9354901fba9bf0135cd4,On Available Corpora for Empirical Methods in Vision & Language,CoRR,2015
081a431107eb38812b74a8cd036ca5e97235b499,Nonnegative Matrix Factorization in Polynomial Feature Space,IEEE Transactions on Neural Networks,2008
0831a511435fd7d21e0cceddb4a532c35700a622,Structured occlusion coding for robust face recognition,Neurocomputing,2016
+08c66211b17a0ac7cad53995b15b0098cad8135a,Tri-Subject Kinship Verification: Understanding the Core of A Family,IEEE Transactions on Multimedia,2015
08c1f8f0e69c0e2692a2d51040ef6364fb263a40,Beyond Eigenfaces: Probabilistic Matching for Face Recognition,,1998
0830c9b9f207007d5e07f5269ffba003235e4eff,Jointly Learning Multiple Measures of Similarities from Triplet Comparisons,,2015
+08b25aa0cca422d3a896aa1fdd865a7e970666db,Hybrid Linear Modeling via Local Best-Fit Flats,International Journal of Computer Vision,2012
081fb4e97d6bb357506d1b125153111b673cc128,Island Loss for Learning Discriminative Features in Facial Expression Recognition,CoRR,2017
+08d25f86d9ba5d2443bd3852aab01334a3a96dce,A Multiple Component Matching Framework for Person Re-identification,,2011
+08a78e0c57d0b6474c09ef8c6d118b3e95da1e18,Biometric Based Cryptographic Key Generation from Faces,9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007),2007
082ad50ac59fc694ba4369d0f9b87430553b11db,Discriminative dictionary learning with low-rank regularization for face recognition,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+6d8a42dce4d79435c42bf8eefddbea0e38951f4e,Pixelwise Instance Segmentation with a Dynamically Instantiated Network,2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017
6de18708218988b0558f6c2f27050bb4659155e4,Learning Long-Term Dependencies for Action Recognition with a Biologically-Inspired Deep Network,2017 IEEE International Conference on Computer Vision (ICCV),2017
6d91da37627c05150cb40cac323ca12a91965759,Gender Politics in the 2016 U.S. Presidential Election: A Computer Vision Approach,,2017
+6d43831c4501ff44ed0ea70ef696e1c496b68a1d,Exploiting Privileged Information from Web Data for Image Categorization,,2014
016cbf0878db5c40566c1fbc237686fbad666a33,Efficient illumination independent appearance-based face tracking,Image Vision Comput.,2009
+01e77cd46ab75bab8f4b176455f0daa592e5f979,Modelling search for people in 900 scenes: A combined source model of eye guidance,,2009
01e12be4097fa8c94cabeef0ad61498c8e7762f2,Simultaneous Active Learning of Classifiers & Attributes via Relative Feedback,,2013
+01d83dcb526a8b751df80ec493caf1937ba99155,Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas,,2010
01beab8f8293a30cf48f52caea6ca0fb721c8489,Face alignment using local hough voting,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
0178929595f505ef7655272cc2c339d7ed0b9507,Label distribution based facial attractiveness computation by deep residual learning,CoRR,2016
+014892cc24798d04a066c50e33630bb3f1b882fe,Content Based Image Retrieval Using Multiscale Top Points A Feasibility Study,,2003
01b4b32c5ef945426b0396d32d2a12c69c282e29,Blockwise Linear Regression for Face Alignment,,2013
+01e5c95aa20a44eed21b5037697043e57f606f3a,A fine-grained analysis of facial expression processing in high-functioning adults with autism.,Neuropsychologia,2007
+0170158c227ee1ccf0a6a2d642699ff184c84bab,3D/4D facial expression analysis: An advanced annotated face model approach,Image Vision Comput.,2012
+018e730f8947173e1140210d4d1760d05c9d3854,Zero-shot recognition with unreliable attributes,,2014
+06be17bcc4136476855fc594759dddc6f8b6150f,MMGAN: Manifold Matching Generative Adversarial Network for Generating Images,CoRR,2017
+0632a9ace74f540e8793f89a84bb7555ba9deece,Weakly Supervised Localization and Learning with Generic Knowledge,International Journal of Computer Vision,2012
+06d30fda7559ae1a6ac49ff7a9fb9280aaad2be8,Supplementary material: Strengthening the Effectiveness of Pedestrian Detection with Spatially Pooled Features,,2014
+06ce9ba74589ca179296318a76e882fe610b729b,Adaptive affinity matrix for unsupervised metric learning,2016 IEEE International Conference on Multimedia and Expo (ICME),2016
+069bb452e015ef53f0ef30e9690e460ccc73cf03,Multicolumn Networks for Face Recognition,Unknown,2018
+0679d05c11c8cd54a597fea870a23b3556c07e1a,Indexing through laplacian spectra,Computer Vision and Image Understanding,2008
+0665853ee87112bc27a9aaec70672f521b91d38e,Çoklu Gauss Karışım Modeli Tabanlı Yüz Öznitelikleri Bulma Algoritması Multi-stream Gaussian Mixture Model based Facial Feature Localization,,2009
+06ab50dccff619c58bb699ee182824b5dca65000,Developing constructs for psychopathology research: research domain criteria.,Journal of abnormal psychology,2010
06526c52a999fdb0a9fd76e84f9795a69480cecf,IMOTION - A Content-Based Video Retrieval Engine,,2015
+068f8b19a3847a2eaf0c65f6d85ec60060750d3c,3D Face Recognition using Log-Gabor Templates,,2006
+065b4890957866a831ccf35694056dcec6f48acc,Road Damage Detection Using Deep Neural Networks with Images Captured Through a Smartphone,CoRR,2018
+0677dd5377895b3c61cea0e6a143f38b84f1ebd7,Super-Resolution via Deep Learning,CoRR,2017
0653dcdff992ad980cd5ea5bc557efb6e2a53ba1,Regularized Robust Coding and Dictionary Learning for Face Recognition,,2012
+063792ff9a139a5b8375afcd35e4ae6c8d83c352,Rapid stereo-vision enhanced face detection,2009 16th IEEE International Conference on Image Processing (ICIP),2009
+06e5d9ad3363b8834229bf7e055a94092994e097,A comparative study on texture and surface descriptors for ear biometrics,2014 International Carnahan Conference on Security Technology (ICCST),2014
+06bdbcfc590359a8f5d10c482d1f010c61f829a4,Long-Range Pedestrian Detection using stereo and a cascade of convolutional network classifiers,2012 IEEE/RSJ International Conference on Intelligent Robots and Systems,2012
+06cea45f1b965b9820d80ca1107661b54cdb7e8e,Semantic hierarchies for image annotation: A survey,Pattern Recognition,2012
+06e7648e945b39b8ccaa9120c796adc170dc81e4,DVQA: Understanding Data Visualizations via Question Answering,CoRR,2018
+6c06452671a501edd6fb66c2c05ded614045a9ec,Pseudo 2D Hidden Markov Model and Neural Network Coefficients in Face Recognition,,2010
+6cda4d23983298ef2c9bd719805e66f4fda7e6fc,Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic Segmentation,,2016
+6c896ca9bafd7479c8291d0448e2910117ee059f,Pedestrian detection with a Large-Field-Of-View deep network,2015 IEEE International Conference on Robotics and Automation (ICRA),2015
39ce143238ea1066edf0389d284208431b53b802,Facial expression transfer method based on frequency analysis,Pattern Recognition,2016
39ce2232452c0cd459e32a19c1abe2a2648d0c3f,Neural computation as a tool to differentiate perceptual from emotional processes: the case of anger superiority effect.,Cognition,2009
397aeaea61ecdaa005b09198942381a7a11cd129,Multi-Scale Video Frame-Synthesis Network with Transitive Consistency Loss,CoRR,2017
+3949967b873dca8c8adf0761777e2702415c67d4,Recognizability assessment of facial images for automated teller machine applications,Pattern Recognition,2012
39b22bcbd452d5fea02a9ee63a56c16400af2b83,Multi-task Learning of Facial Landmarks and Expression,2014 Canadian Conference on Computer and Robot Vision,2014
399a2c23bd2592ebe20aa35a8ea37d07c14199da,Inferring facial expressions from videos: Tool and application,Sig. Proc.: Image Comm.,2007
+392245913bf63c8a9f44881628f8f3f587e08189,Fast Kernel Sparse Representation,2011 International Conference on Digital Image Computing: Techniques and Applications,2011
392425be1c9d9c2ee6da45de9df7bef0d278e85f,Vision for Intelligent Vehicles & Applications (VIVA): Face Detection and Head Pose Challenge,,2016
3947b64dcac5bcc1d3c8e9dcb50558efbb8770f1,Action Recognition with Dynamic Image Networks,IEEE transactions on pattern analysis and machine intelligence,2017
-3965d61c4f3b72044f43609c808f8760af8781a2,Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes,CoRR,2018
+3965d61c4f3b72044f43609c808f8760af8781a2,Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes,Unknown,2018
395bf182983e0917f33b9701e385290b64e22f9a,Facial Expressions Animation and Lip Tracking Using Facial Characteristic Points and Deformable Model,Unknown,2004
39b452453bea9ce398613d8dd627984fd3a0d53c,Spatiotemporal Residual Networks for Video Action Recognition,Unknown,2016
+39905f28acee51506352c34736577d49ceb2f318,Combining Statistics of Geometrical and Correlative Features for 3D Face Recognition,,2006
39b5f6d6f8d8127b2b97ea1a4987732c0db6f9df,An evaluation of bi-modal facial appearance+facial expression face biometrics,2008 19th International Conference on Pattern Recognition,2008
+995b2868326837cde96e01390f87b2dee6239bdb,Feature Detection and Tracking with Constrained Local Models,,2006
+9976b88d15f89b6c82b16564735d489a7524821d,Learning Visual N-Grams from Web Data,2017 IEEE International Conference on Computer Vision (ICCV),2017
+993acefc2e350f9661125bb74df136e2b614ea23,People detection on the Pepper Robot using Convolutional Neural Networks and 3D Blob detection,,2017
+997fea9df7057cd342299e90c1c6e6e9f1cc5a88,Human movement summarization and depiction from videos,2013 IEEE International Conference on Multimedia and Expo (ICME),2013
9931c6b050e723f5b2a189dd38c81322ac0511de,From pose to activity: Surveying datasets and introducing CONVERSE,Computer Vision and Image Understanding,2016
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+992655a7eaa846cdf755bb1be93693d7b6fe9094,Accurate eye localization in the Short Waved Infrared Spectrum through summation range filters,Computer Vision and Image Understanding,2015
+99b8e5b8544ed6aa45726311afb0679363c875ed,Region-based Quality Estimation Network for Large-scale Person Re-identification,CoRR,2017
+520901f189d7943ff060239d4152b34edc0524ae,Large-scale image annotation using visual synset,2011 International Conference on Computer Vision,2011
+52162b19e058f11b5d010f6b9f1f4944ce8db3a6,Hashing with Locally Linear Projections,,2014
521482c2089c62a59996425603d8264832998403,Landmark localization on 3D/4D range data using a shape index-based statistical shape model with global and local constraints,Computer Vision and Image Understanding,2015
521b625eebea73b5deb171a350e3709a4910eebf,Improving Human Action Recognition by Non-action Classification,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
+5291304833a3565f8a2b6c13c1f12e6841925a87,"Detecting Actions, Poses, and Objects with Relational Phraselets",,2012
527dda77a3864d88b35e017d542cb612f275a4ec,Facial 3D model registration under occlusions with sensiblepoints-based reinforced hypothesis refinement,2017 IEEE International Joint Conference on Biometrics (IJCB),2017
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+52a9f957f776c8b3d913cfcd20452b9e31c27845,OPML: A one-pass closed-form solution for online metric learning,Pattern Recognition,2018
52f23e1a386c87b0dab8bfdf9694c781cd0a3984,DropELM: Fast neural network regularization with Dropout and DropConnect,Neurocomputing,2015
550858b7f5efaca2ebed8f3969cb89017bdb739f,"""Wii Using Only 'We'"": Using background subtraction and human pose recognition to eliminate game controllers",,2011
+551a62f43a9da5ceb9564358ad25523736fd48dc,Low-resolution face recognition with single sample per person,Signal Processing,2017
+5578be51e09379061f526e8d0fee65e3613eee8a,Shape-aware Instance Segmentation,CoRR,2016
+55cc90968e5e6ed413dd607af2a850ac2f54e378,Active subclustering,Computer Vision and Image Understanding,2014
+55c6cd3b3a0c0335de050468f55a5cc4bdc30681,Gaze allocation in a dynamic situation: effects of social status and speaking.,Cognition,2010
+55c16592502db5c2cc30711f4d04e4d3aa04d278,Universum Prescription: Regularization Using Unlabeled Data,,2017
+55d8052477e599125442de86cf4b05bc6ea0fbf8,Extended CRC: Face Recognition with a Single Training Image per Person via Intraclass Variant Dictionary,IEICE Transactions,2013
5506a1a1e1255353fde05d9188cb2adc20553af5,Dictionary Integration using 3D Morphable Face Models for Pose-invariant Collaborative-representation-based Classification,CoRR,2016
+55b55426fcba3e298a20a4b95753a906956fc2ac,Tensor linear Laplacian discrimination (TLLD) for feature extraction,Pattern Recognition,2009
55c81f15c89dc8f6eedab124ba4ccab18cf38327,Discriminative Training of Hyper-feature Models for Object Identification,,2006
+55e28e4c174bb7ad2fd80be3c13a033bbd91ac7a,Detection and Tracking of General Movable Objects in Large 3D Maps,CoRR,2017
+9730a140831f51a6640236e42059b948c5466d0c,Thumbs up or thumbs down? Effects of neuroticism and depressive symptoms on psychophysiological responses to social evaluation in healthy students,,2016
+9703e31a7f873eb9fc41c81c303d83a7416fffc8,Effects of Image Segmentation for Approximating Object Appearance Under Near Lighting,,2006
+9773cb8fff5e3735b34018212e83023cba227345,Enhancing ELM-based Facial Image Classification by Exploiting Multiple Facial Views,,2015
97540905e4a9fdf425989a794f024776f28a3fa9,NDDR-CNN: Layer-wise Feature Fusing in Multi-Task CNN by Neural Discriminative Dimensionality Reduction,CoRR,2018
+9746186205ed5e559d17e87d7ede9e3dd3922e54,Face recognition based on 3D ridge images obtained from range data,Pattern Recognition,2009
+63856e83b69ac15e1252c1c3d89114dcf806fbcc,DeepIU: An Architecture for Image Understanding,,2016
635158d2da146e9de559d2742a2fa234e06b52db,Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns,,2015
+63a3e425c634d0280198ae1b70ef3aec27fc95cc,An efficient face verification method in a transformed domain,Pattern Recognition Letters,2007
+63ac85ec1bff6009bb36f0b24ef189438836bc91,Deep linear discriminant analysis on fisher networks: A hybrid architecture for person re-identification,Pattern Recognition,2017
+630d2c5b60e28ff8710f415a8adb7a73f8162d9c,3D Face Recognition,,2012
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63d8d69e90e79806a062cb8654ad78327c8957bb,A efficient and practical 3D face scanner using near infrared and visible photometric stereo,,2010
+63216e4bbb8736c5587b41ebbd92043656b374c6,A dynamic geometry-based approach for 4D facial expressions recognition,European Workshop on Visual Information Processing (EUVIP),2013
+63199f9d0034e82a0a7c9519d1a5bd31cc9de39f,InterpNET: Neural Introspection for Interpretable Deep Learning,CoRR,2017
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63eefc775bcd8ccad343433fc7a1dd8e1e5ee796,Correlation Metric for Generalized Feature Extraction,IEEE Transactions on Pattern Analysis and Machine Intelligence,2008
+63111778d25b1105fec5e09bedf9122eafe34fd1,Optasia: A Relational Platform for Eõcient Large-Scale Video Analytics,,2016
+632c114e12a6b88bd488ddfb1960d669f101ca3f,Multi-face tracking by extended bag-of-tracklets in egocentric photo-streams,Computer Vision and Image Understanding,2016
+63ce37da6c0c789099307337bb913e1104473854,Transfer Learning with One-Class Data,,2013
+63e1ce7de0fdbce6e03d25b5001c670c30139aa8,Deep Feature Learning via Structured Graph Laplacian Embedding for Person Re-Identification,CoRR,2017
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0f9bf5d8f9087fcba419379600b86ae9e9940013,Hybrid human detection and recognition in surveillance,Neurocomputing,2016
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+0fd877cb088e38b00b44f52f5483be8f356788c2,Contour Context Selection for Object Detection: A Set-to-Set Contour Matching Approach,,2008
+0f0146855de3cc6e0fd1e3c6a7bd0d3df19653bf,An interpolation method for the reconstruction and recognition of face images,,2007
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0a511058edae582e8327e8b9d469588c25152dc6,Memory Constrained Face Recognition Ashish Kapoor,,
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0ad4a814b30e096ad0e027e458981f812c835aa0,Leveraging mid-level deep representations for predicting face attributes in the wild,2016 IEEE International Conference on Image Processing (ICIP),2016
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6448d23f317babb8d5a327f92e199aaa45f0efdc,Classifying Facial Attributes using a 2-D Gabor Wavelet Representation and Discriminant Analysis,,1999
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642c66df8d0085d97dc5179f735eed82abf110d0,Coupled kernel-based subspace learning,2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05),2005
641f34deb3bdd123c6b6e7b917519c3e56010cb7,Extended SRC: Undersampled Face Recognition via Intraclass Variant Dictionary,IEEE Transactions on Pattern Analysis and Machine Intelligence,2012
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90ac0f32c0c29aa4545ed3d5070af17f195d015f,An Improved Illumination Normalization based on Anisotropic Smoothing for Face Recognition,Unknown,2012
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+90b7619eabe94731722ae884d0802256462457dc,Behavior Discovery and Alignment of Articulated Object Classes from Unstructured Video,International Journal of Computer Vision,2016
+90dcaeeed3cc5c6001a06e9fa674845a8fd471bd,Self-Supervised Depth Learning for Urban Scene Understanding,CoRR,2017
90b11e095c807a23f517d94523a4da6ae6b12c76,Blind Facial Image Quality Enhancement Using Non-Rigid Semantic Patches,IEEE Transactions on Image Processing,2017
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d4c7d1a7a03adb2338704d2be7467495f2eb6c7b,Towards a Neural,,2017
+d4ca67160781e5c74b0385c3d45f35dcc0f79b8a,Polygonal Representation of Digital Curves,,2012
d4ebf0a4f48275ecd8dbc2840b2a31cc07bd676d,A Fusion of Appearance based CNNs and Temporal evolution of Skeleton with LSTM for Daily Living Action Recognition,CoRR,2018
d44a93027208816b9e871101693b05adab576d89,On the Capacity of Face Representation,CoRR,2017
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+ba227bb94ea9414bad8846673c904a10d813e443,Deep 360 Pilot: Learning a Deep Agent for Piloting through 360° Sports Videos,,2017
ba29ba8ec180690fca702ad5d516c3e43a7f0bb8,Do less and achieve more: Training CNNs for action recognition utilizing action images from the Web,Pattern Recognition,2017
bab88235a30e179a6804f506004468aa8c28ce4f,Joint discriminative dimensionality reduction and dictionary learning for face recognition,Pattern Recognition,2013
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a74251efa970b92925b89eeef50a5e37d9281ad0,"Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization",2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops),2011
+a7a7d4be51d0918cbec78d84dd1f7363535fd60c,Emotional facial expressions reduce neural adaptation to face identity.,Social cognitive and affective neuroscience,2014
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b8378ab83bc165bc0e3692f2ce593dcc713df34a,"A 3D Approach to Facial Landmarks: Detection, Refinement, and Tracking",2014 22nd International Conference on Pattern Recognition,2014
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+b1c80444ecf42c303dbf65e47bea999af7a172bf,Exploring Generative Perspective of Convolutional Neural Networks by Learning Random Field Models,,2016
+b1f42e2b1b560c2451a1d704430633aed71f2bb9,Lighting invariant urban street classification,2014 IEEE International Conference on Robotics and Automation (ICRA),2014
b171f9e4245b52ff96790cf4f8d23e822c260780,ROBOTICS INSTITUTE Summer Scholars ( RISS ) Working Papers JOURNAL VOLUME 2 FALL 2014,,2014
b1301c722886b6028d11e4c2084ee96466218be4,Facial Aging and Rejuvenation by Conditional Multi-Adversarial Autoencoder with Ordinal Regression,,2018
b1c5581f631dba78927aae4f86a839f43646220c,A scalable metric learning-based voting method for expression recognition,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+b14d06fa5dae7428b946db9ea48baa81a4f5a4cd,A Greedy Part Assignment Algorithm for Real-time Multi-person 2D Pose Estimation,CoRR,2017
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dd600e7d6e4443ebe87ab864d62e2f4316431293,Improving facial expression analysis using histograms of Log-Transformed Nonnegative Sparse Representation with a Spatial Pyramid Structure,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+dc6b40252885249f1e71831f57d9ddbaae8df635,Fast task-specific target detection via graph based constraints representation and checking,2017 IEEE International Conference on Robotics and Automation (ICRA),2017
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+b65bbf24479d4df65dcde2ac343f5c7cf96be3ef,Fitting 3D morphable models using implicit representations,JVRB,2007
+b6bf9d357f280ba8bb8338b2448f0f90773f5c57,A Testing Methodology for Face Recognition Algorithms,,2005
b6c047ab10dd86b1443b088029ffe05d79bbe257,Using robust dispersion estimation in support vector machines,Pattern Recognition,2013
+b63957152a0f37ddc99904a5bddb60b3f056b8cf,Eye tracking young children with autism.,Journal of visualized experiments : JoVE,2012
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b6c53891dff24caa1f2e690552a1a5921554f994,Deeply Learning Deformable Facial Action Parts Model for Dynamic Expression Analysis,,2014
+b64bf3dab761d27a19f2ff4049691dc47369595d,Cascade of descriptors to detect and track objects across any network of cameras,Computer Vision and Image Understanding,2010
b656abc4d1e9c8dc699906b70d6fcd609fae8182,Integrating monolithic and free-parts representations for improved face verification in the presence of pose mismatch,Pattern Recognition Letters,2007
+a9fb2ec954dbb8e1ee6b3a33e0e5c06db2d89d3c,Obese parents – obese children? Psychological-psychiatric risk factors of parental behavior and experience for the development of obesity in children aged 0–3: study protocol,,2013
a92adfdd8996ab2bd7cdc910ea1d3db03c66d34f,ConvNet Architecture Search for Spatiotemporal Feature Learning,CoRR,2017
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+a9f7ab254a8c73a51f0eba5a8e13b48924b542c0,Face morphology: Can it tell us something about body weight and fat?,Computers in biology and medicine,2016
+a9a6cd6d40b563a02ed899114559a6e14f2f39a1,Numerical Coordinate Regression with Convolutional Neural Networks,CoRR,2018
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+d541986a647e7ab10cc8f882e1a1f5e6d725d8a2,Emotion Recognition from Geometric Facial Patterns,,2015
d50751da2997e7ebc89244c88a4d0d18405e8507,Real time 3D face alignment with Random Forests-based Active Appearance Models,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
d511e903a882658c9f6f930d6dd183007f508eda,Privileged information-based conditional regression forest for facial feature detection,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
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d5e1173dcb2a51b483f86694889b015d55094634,PCA and LDA in DCT domain,Pattern Recognition Letters,2005
+d2a8779b4f533e1dce709ced55196ef28e9a4c90,SI: EMOTION REGULATION AND PSYCHIATRIC COMORBIDITY IN ASD Fear of Negative Evaluation Influences Eye Gaze in Adolescents with Autism Spectrum Disorder: A Pilot Study,Unknown,2015
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aafb271684a52a0b23debb3a5793eb618940c5dd,Supplementary Material: Hierarchical Semantic Indexing for Large Scale Image Retrieval,,2011
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aa331fe378056b6d6031bb8fe6676e035ed60d6d,Object detection using boosted local binaries,Pattern Recognition,2016
af8fe1b602452cf7fc9ecea0fd4508ed4149834e,A pose-wise linear illumination manifold model for face recognition using video,Computer Vision and Image Understanding,2009
+af6af58ba12920762638e1d0b8310a0d9961b7be,Sketch-to-Image Generation Using Deep Contextual Completion,CoRR,2017
+afeac9270149b927b592e2299d11095fbdf8d308,Accurate 3D Multi-marker Tracking in X-ray Cardiac Sequences Using a Two-Stage Graph Modeling Approach,,2013
af6cae71f24ea8f457e581bfe1240d5fa63faaf7,Multi-Task Zipping via Layer-wise Neuron Sharing,CoRR,2018
+afd29ac2de84c8a6d48232477be018ec57d6f564,Deep Metric Learning for Practical Person Re-Identification,CoRR,2014
af54dd5da722e104740f9b6f261df9d4688a9712,Portability: A New Challenge on Designing Family Image Database,,2010
+afd1e4157245d56711d4f16a5b7c9fd1f39a5139,Nearest-neighbor method using multiple neighborhood similarities for social media data mining,Neurocomputing,2012
+b7b5fd3e2cfc39967e389b974c1cb418b2bf1b8f,Heuristic Search for Structural Constraints in Data Association,CoRR,2017
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b75cee96293c11fe77ab733fc1147950abbe16f9,A Single Classifier for View-Invariant Multiple Object Class Recognition,,2006
+b786a16ca5d84257bb98024751429c9f42005e62,A Fine-Grained Approach to Scene Text Script Identification,2016 12th IAPR Workshop on Document Analysis Systems (DAS),2016
+b7740dba37a3cbd5c832a8deb9a710a28966486a,The development of emotion concepts: a story superiority effect in older children and adolescents.,Journal of experimental child psychology,2015
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+b7cff43f653279a65e23a7a85c48b12a484148ef,Face and Facial Feature Detection Evaluation - Performance Evaluation of Public Domain Haar Detectors for Face and Facial Feature Detection,,2008
+b7239d619c5ad3d80a170bb33ca427bb4278f4a1,Pedestrian detection in single frame by edgelet-LBP part detectors,2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance,2013
+b767abb865fba93f35312127b61ba351a2a91a44,Face processing regions are sensitive to distinct aspects of temporal sequence in facial dynamics,NeuroImage,2014
b747fcad32484dfbe29530a15776d0df5688a7db,Background suppressing Gabor energy filtering,Pattern Recognition Letters,2015
+b79412cee14e583a5c6816c1124913f560303a95,Learning fine-grained features via a CNN Tree for Large-scale Classification,Neurocomputing,2018
+b717d84d551de252300b9f161a5551162a936119,Query-driven iterated neighborhood graph search for large scale indexing,,2012
+dbbaa5d4a5d04267e5be454624f8d3be8265fe7c,"Fusiform function in children with an autism spectrum disorder is a matter of ""who"".",Biological psychiatry,2008
dbab6ac1a9516c360cdbfd5f3239a351a64adde7,Cascaded regression with sparsified feature covariance matrix for facial landmark detection,Pattern Recognition Letters,2016
+dbc04694ef17c83bb12b3ad34da6092eab68ae68,Modeling cognitive deficits following neurodegenerative diseases and traumatic brain injuries with deep convolutional neural networks.,Brain and cognition,2018
+db5d1b4c295adb24c8cb58ec995ce11b569cbb77,Graph optimization for dimensionality reduction with sparsity constraints,Pattern Recognition,2012
+dbec415ba09ab66ea5855aaa1267796b75ef7e7b,Person Re-identification in Appearance Impaired Scenarios,CoRR,2016
+db35faccd8d9fcf25c363b4781cb50dbd76649b4,Full body human attribute detection in indoor surveillance environment using color-depth information,2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance,2013
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+a8be27b214a75642d43c726b8f1e92aa8e4c3768,A NOVEL CONIC SECTION CLASSIFIER WITH TRACTABLE GEOMETRIC LEARNING ALGORITHMS By SANTHOSH KODIPAKA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY,,2009
+de801c4bb4b420417d9514631a6cc4099fc64df2,Crowd counting in public video surveillance by label distribution learning,Neurocomputing,2015
+de6ba16ee8ad07e2f02d685b1e98b8be5045cb1b,Adaptive discriminant learning for face recognition,Pattern Recognition,2013
+de10f93b0a3656822aa7c0b5d62074ff5eac60b2,Measuring the Accuracy of Object Detectors and Trackers,,2017
+de0157390682eebc838e271f4fe8f704251ddef1,A reaction time advantage for calculating beliefs over public representations signals domain specificity for 'theory of mind'.,Cognition,2010
ded41c9b027c8a7f4800e61b7cfb793edaeb2817,DYAN: A Dynamical Atoms Network for Video Prediction,,2018
b0c512fcfb7bd6c500429cbda963e28850f2e948,A Fast and Accurate Unconstrained Face Detector,IEEE Transactions on Pattern Analysis and Machine Intelligence,2016
+b018f4ea4b46701103046c472468631cc28ab311,Generative Adversarial Perturbations,CoRR,2017
+b06b0086e84038abbe5088f3429603778f2b8fdf,Distributed Data Association in Smart Camera Networks via Dual Decomposition,Information Fusion,2018
+b01de5e9554109a006a0cface1f11d45922abc0b,Geometric Neural Phrase Pooling: Modeling the Spatial Co-occurrence of Neurons,,2016
b03d6e268cde7380e090ddaea889c75f64560891,Automatic Acquisition of High-fidelity Facial Performances Using Monocular Videos: Supplementary Material,,2014
+b0d52bb1c9cff9416fe766e9cba94ceeab12d51f,Object Detection Using Deep CNNs Trained on Synthetic Images,CoRR,2017
+a643302a89805bb8d3d204660a3a60420fee36e2,Facial point detection using boosted regression and graph models,2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2010
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+a65b93c01518755291e19a0545c1a3d20e401c0a,"A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning",,2016
a6583c8daa7927eedb3e892a60fc88bdfe89a486,Toward semantic attributes in dictionary learning and non-negative matrix factorization,Pattern Recognition Letters,2016
a6db73f10084ce6a4186363ea9d7475a9a658a11,ActionFlowNet: Learning Motion Representation for Action Recognition,CoRR,2016
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+b99957df60ee58e38ad71ed70b9973c22d5c26cc,Impact of money on emotional expression☆,,2015
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+b92f276ecf9077f7c09ce410336f8b9a819df4fc,A 3D face and hand biometric system for robust user-friendly authentication,Pattern Recognition Letters,2007
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c3418f866a86dfd947c2b548cbdeac8ca5783c15,Disentangling the Modes of Variation in Unlabelled Data,,2018
+c3980cbaf613cad1fbd0ab6da472c789cda583a9,Robust arbitrary view gait recognition based on parametric 3D human body reconstruction and virtual posture synthesis,Pattern Recognition,2016
c3a3f7758bccbead7c9713cb8517889ea6d04687,Funnel-structured cascade for multi-view face detection with alignment-awareness,Neurocomputing,2017
+c36ae7c5e9f9f992a5939e07283183707ee0a787,StuffNet: Using 'Stuff' to Improve Object Detection,,2017
+c397408e784004240e866d0f31cea7b9e44fdd0c,Face image super-resolution through locality-induced support regression,Signal Processing,2014
c3638b026c7f80a2199b5ae89c8fcbedfc0bd8af,Shape Matching and Object Recognition,,2005
+c478faecfa337bb2d37ac7c63aca47d4148ffc6a,Spontaneous facial micro-expression analysis using Spatiotemporal Completed Local Quantized Patterns,Neurocomputing,2016
+c472436764a30278337aca9681eee456bee95c34,The inherently contextualized nature of facial emotion perception.,Current opinion in psychology,2017
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ea96bc017fb56593a59149e10d5f14011a3744a0,Local coordinate based graph-regularized NMF for image representation,Signal Processing,2016
+ea3801a15f4568856581357cfc4e5bb2de185a2e,Structure-Aware and Temporally Coherent 3D Human Pose Estimation,CoRR,2017
+e10f4d5c0e0e294e00ce3a92b2057c4b2a5acf09,Face Recognition at a Distance: a study of super resolution M.Sc. Thesis,,2011
e10a257f1daf279e55f17f273a1b557141953ce2,A survey of approaches and trends in person re-identification,Image Vision Comput.,2014
e171fba00d88710e78e181c3e807c2fdffc6798a,Pose-invariant face recognition using a 3D deformable model,Pattern Recognition,2003
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e16efd2ae73a325b7571a456618bfa682b51aef8,Semi-Supervised Adaptive Label Distribution Learning for Facial Age Estimation,,2017
e13360cda1ebd6fa5c3f3386c0862f292e4dbee4,Range Loss for Deep Face Recognition with Long-tail,CoRR,2016
+e1740c8a562901ac1b94c78b33c4416500cedebc,Joint-VAE: Learning Disentangled Joint Continuous and Discrete Representations,,2018
+cd7c007f5831b294160eaf1cc6270af4a0ca9bf4,Person re-identification with block sparse recovery,Image Vision Comput.,2017
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ccbfc004e29b3aceea091056b0ec536e8ea7c47e,Tensor-based factor decomposition for relighting,IEEE International Conference on Image Processing 2005,2005
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cc8bf03b3f5800ac23e1a833447c421440d92197,Improving mixture of experts for view-independent face recognition using teacher-directed learning,Machine Vision and Applications,2009
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e6540d70e5ffeed9f447602ea3455c7f0b38113e,Video pornography detection through deep learning techniques and motion information,Neurocomputing,2017
e6ee36444038de5885473693fb206f49c1369138,SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction,CoRR,2018
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f913bb65b62b0a6391ffa8f59b1d5527b7eba948,On improving robustness of LDA and SRDA by using tangent vectors,Pattern Recognition Letters,2013
+f97e9818a8055668f9db7967b076dd036d25c417,Self-Supervised Video Hashing with Hierarchical Binary Auto-encoder,CoRR,2018
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f96bdd1e2a940030fb0a89abbe6c69b8d7f6f0c1,Comparison of human and computer performance across face recognition experiments,Image Vision Comput.,2014
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+f0fc82cabfbb7d7a8505ef1f78becaf179b9d72c,Abnormal cerebral effective connectivity during explicit emotional processing in adults with autism spectrum disorder.,Social cognitive and affective neuroscience,2008
f06b015bb19bd3c39ac5b1e4320566f8d83a0c84,Classification and weakly supervised pain localization using multiple segment representation,Image and vision computing,2014
f7dea4454c2de0b96ab5cf95008ce7144292e52a,Facial Landmark Detection: A Literature Survey,International Journal of Computer Vision,2018
+f793970c7b57c3470561e9830cebbdd590a38bf4,Photo-realistic Facial Texture Transfer,CoRR,2017
f7452a12f9bd927398e036ea6ede02da79097e6e,Attributes as Operators,,2018
f78863f4e7c4c57744715abe524ae4256be884a9,Differential optical flow applied to automatic facial expression recognition,Neurocomputing,2011
e8410c4cd1689829c15bd1f34995eb3bd4321069,Decoding mixed emotions from expression map of face images,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+e896b084a247213f48b703c98f2ec6f55a02a2f5,Brain regions involved in processing facial identity and expression are differentially selective for surface and edge information,,2014
+e87b1ae1d9af4182e7c5b62c9bd01b15979dd59d,Addressing ambiguity in multi-target tracking by hierarchical strategy,2017 IEEE International Conference on Image Processing (ICIP),2017
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faead8f2eb54c7bc33bc7d0569adc7a4c2ec4c3b,Combining Data-driven and Model-driven Methods for Robust Facial Landmark Detection,CoRR,2016
faf5583063682e70dedc4466ac0f74eeb63169e7,Holistic person processing: faces with bodies tell the whole story.,Journal of personality and social psychology,2012
+fa7689cedcf2f0ddb6fa4a3c0dbefc6fa63e1a14,Cross-modal influences of affect across social and non-social domains in individuals with Williams syndrome.,Neuropsychologia,2010
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ff60d4601adabe04214c67e12253ea3359f4e082,Video-based emotion recognition in the wild using deep transfer learning and score fusion,Image Vision Comput.,2017
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c5fe40875358a286594b77fa23285fcfb7bda68e,Face identification using reference-based features with message passing model,Neurocomputing,2013
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f68ed499e9d41f9c3d16d843db75dc12833d988d,Multi-view Common Component Discriminant Analysis for Cross-view Classification,CoRR,2018
f6abecc1f48f6ec6eede4143af33cc936f14d0d0,Adaptive Detrending to Accelerate Convolutional Gated Recurrent Unit Training for Contextual Video Recognition,CoRR,2017
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+e9ce1ab4a1b6204114446cb255c1d7639adc9a80,On the Importance of the Grid Size for Gender Recognition using Full Body Static Images,,2011
+e92c934c047d0ec23e7ed3a749e14a0150dc1bc8,Privacy-Preserving Photo Sharing based on a Public Key Infrastructure,,2015
+e9c000b765ba5519050a61726e007c430cd5bfcb,Multi-class Multi-object Tracking Using Changing Point Detection,,2016
+e90816e1a0e14ea1e7039e0b2782260999aef786,Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers,CoRR,2018
f1748303cc02424704b3a35595610890229567f9,Learning-based encoding with soft assignment for age estimation under unconstrained imaging conditions,Image Vision Comput.,2012
+f10f6c294130c76981f0e584af5811c44636eda5,The Re-identification Challenge,,2014
e726acda15d41b992b5a41feabd43617fab6dc23,Evolutionary feature synthesis for facial expression recognition,Pattern Recognition Letters,2006
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+e75255911aa88fda7c0ce8b42b0ca2d2a43bf33e,Reduced gaze aftereffects are related to difficulties categorising gaze direction in children with autism,,2013
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+cbadf6b89571d387eb5f1d56ae5671ad16ed1155,Face processing in autism spectrum disorders: From brain regions to brain networks.,Neuropsychologia,2015
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cb9092fe74ea6a5b2bb56e9226f1c88f96094388,A distributed perception infrastructure for robot assisted living,Robotics and Autonomous Systems,2014
+f8ebba8188c9f6b1688ba7ba76f297215e6cc7c7,Triplet-Based Deep Similarity Learning for Person Re-Identification,2017 IEEE International Conference on Computer Vision Workshops (ICCVW),2017
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f869601ae682e6116daebefb77d92e7c5dd2cb15,Regularized Diffusion Process for Visual Retrieval,,2017
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cef841f27535c0865278ee9a4bc8ee113b4fb9f3,Fusion of feature sets and classifiers for facial expression recognition,Expert Syst. Appl.,2013
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ce691a37060944c136d2795e10ed7ba751cd8394,"Unsupervised Depth Estimation, 3D Face Rotation and Replacement",,2018
+ce9a9f178018fc266fbf554bbde63155a48eaedb,Face recognition under pose variation with local Gabor features enhanced by Active Shape and Statistical Models,Pattern Recognition,2015
ce3f3088d0c0bf236638014a299a28e492069753,Online Action Recognition Using Covariance of Shape and Motion,,2014
+ce7a385b791686f318313e94a0b573c456c1297f,Quantifying privacy and security of biometric fuzzy commitment,2011 International Joint Conference on Biometrics (IJCB),2011
e0c081a007435e0c64e208e9918ca727e2c1c44e,Universidad De Las Palmas,,2005
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e0765de5cabe7e287582532456d7f4815acd74c1,Representing images of a rotating object with cyclic permutation for view-based pose estimation,Computer Vision and Image Understanding,2009
46e86cdb674440f61b6658ef3e84fea95ea51fb4,Robust Face Recognition Using Eigen Faces and Karhunen-Loeve Algorithm,,2010
+46bd4df6176345097b0d239b3c8937f67130a69b,Bootstrapping Boosted Random Ferns for discriminative and efficient object classification,Pattern Recognition,2012
464de30d3310123644ab81a1f0adc51598586fd2,Covariance descriptor based on bio-inspired features for person re-identification and face verification,Image Vision Comput.,2014
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+46c00c4c4dfaee99976705209fc2ac1972081ab9,Relational HOG Feature and Masking of Binary by Using Wild - Card for Object,,2011
+46c65ee1a3e49bb77c7c73dcbfeb5d86db7fc3ee,Deep-neural-network based sinogram synthesis for sparse-view CT image reconstruction,,2018
+4699f98cfdb19e57c2c14c046d0a658ed2267aa7,Online Hashing,IEEE transactions on neural networks and learning systems,2013
46196735a201185db3a6d8f6e473baf05ba7b68f,Principal Component Analysis by $L_{p}$ -Norm Maximization,IEEE transactions on cybernetics,2014
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2cbb4a2f8fd2ddac86f8804fd7ffacd830a66b58,Age and gender classification using convolutional neural networks,2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),2015
2c61a9e26557dd0fe824909adeadf22a6a0d86b0,Convolutional Channel Features: Tailoring CNN to Diverse Tasks,,2015
+2ca78bafe32dbca5f9f64ed4de5a893aa5ca03f7,Seeking the Strongest Rigid Detector,2013 IEEE Conference on Computer Vision and Pattern Recognition,2013
+2c5bfdf6b4f9c06a42280e99d101e628a1dc597f,"Multiple Target, Multiple Type Visual Tracking using a Tri-GM-PHD Filter",Unknown,2017
+2c13e817232e8693ecbd7a139cfb1825a720ff96,Learning Pose Grammar to Encode Human Body Configuration for 3D Pose Estimation,,2017
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2c7c3a74da960cc76c00965bd3e343958464da45,Interactive Facial-Geometric-Feature Animation for Generating Expressions of Novel Faces,IEICE Transactions,2011
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+2c3138782317a97526a83a7ce264c0c772ddf7e3,Zero-Shot Learning by Generating Pseudo Feature Representations,CoRR,2017
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79581c364cefe53bff6bdd224acd4f4bbc43d6d4,Descriptors and regions of interest fusion for in- and cross-database gender classification in the wild,Image Vision Comput.,2017
+795aa8064b34c4bf4acdd8be3f1e5d06da5a7756,Face-MagNet: Magnifying Feature Maps to Detect Small Faces,,2018
795ea140df2c3d29753f40ccc4952ef24f46576c,Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection,CoRR,2017
+790ad3255083ac475185d9de8159ae3cf2e0068b,The role of the right hemisphere in semantic control: A case-series comparison of right and left hemisphere stroke,,2016
79dc84a3bf76f1cb983902e2591d913cee5bdb0e,Grounded Compositional Semantics for Finding and Describing Images with Sentences,TACL,2014
+79519f181ca9378e72bdb41ca647ba6d2e65b106,Two can play this Game: Visual Dialog with Discriminative Question Generation and Answering,CoRR,2018
79c3a7131c6c176b02b97d368cd0cd0bc713ff7e,A New Weighted LDA Method in Comparison to Some Versions of LDA,Unknown,2006
+7942d0c6e5d1a2440061f2ea4bc27e32badb9c3d,Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.,Journal of biomedical informatics,2017
793e7f1ba18848908da30cbad14323b0389fd2a8,End-to-end Face Detection and Cast Grouping in Movies Using Erdős-Rényi Clustering: Supplementary Material,,2017
+2dfba157e0b5db5becb99b3c412ac729cf3bb32d,Automatic Detection and Tracking of Pedestrians in Videos with Various Crowd Densities,,2014
2dd6c988b279d89ab5fb5155baba65ce4ce53c1e,Learning deformable shape manifolds,Pattern recognition,2012
+2d83dbf4c8eabc6bdef3326c4a30d5f33ffc944e,Multimodal Residual Learning for Visual QA,,2016
2d1f86e2c7ba81392c8914edbc079ac64d29b666,Deep Heterogeneous Feature Fusion for Template-Based Face Recognition,2017 IEEE Winter Conference on Applications of Computer Vision (WACV),2017
+2d2102d3fe127444e203a2ab11c2b3d5f56874cc,Wasserstein Auto-Encoders,CoRR,2017
+2d69b3965685066081e533b29fde3364a6cc21e7,Object Instance Sharing by Enhanced Bounding Box Correspondence,,2012
+2dd91115091f1691ea37c4b14788ca4199354012,Semi-supervised Learning by Sparse Representation,,2009
+2d36f8444581d806ce6e36ec1d9bdede193db005,Visual Memory QA: Your Personal Photo and Video Search Agent,,2017
+2da1a80955df1612766ffdf63916a6a374780161,Generating steganographic images via adversarial training,Unknown,2017
+41b38da2f4137c957537908f9cb70cbd2fac8bc1,Greedy search for descriptive spatial face features,"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",2017
+41915a85714bbfea53af9e65abc01a7b54e5cd13,Reliable non-invasive measurement of human neurochemistry using proton spectroscopy with an anatomically defined amygdala-specific voxel,NeuroImage,2012
+419fec1a76d9233dcaa8d2c98ea622d19f663261,Unsupervised learning of object frames by dense equivariant image labelling,Unknown,2017
41b997f6cec7a6a773cd09f174cb6d2f036b36cd,Local binary patterns for multi-view facial expression recognition,Computer Vision and Image Understanding,2011
+419279b5d21234737b10715fd785eeb51b317767,Haar-like features with optimally weighted rectangles for rapid object detection,Pattern Recognition,2010
830e5b1043227fe189b3f93619ef4c58868758a7,"A survey on face detection in the wild: Past, present and future",Computer Vision and Image Understanding,2015
+834ff8e06ed3f01c10958a276f1526fce7ffd387,Automatic Adaptation of Person Association for Multiview Tracking in Group Activities,CoRR,2018
83ac942d71ba908c8d76fc68de6173151f012b38,Class dependent factor analysis and its application to face recognition,Pattern Recognition,2012
+8359f65fd0e0ada2a3de8aead37a6680b53de2a6,Estimating smile intensity: A better way,,2014
+1b32284d732e0aec506411b71e6150df53d167f7,"Configurable, Photorealistic Image Rendering and Ground Truth Synthesis by Sampling Stochastic Grammars Representing Indoor Scenes",CoRR,2017
1bd50926079e68a6e32dc4412e9d5abe331daefb,Fisher Discrimination Dictionary Learning for sparse representation,2011 International Conference on Computer Vision,2011
+1ba4d5d3b0cb46d61f23279f70ae42735601a60c,Crowd Counting via Weighted VLAD on Dense Attribute Feature Maps,CoRR,2016
+1b612877c4fb6fb7faf395357cd8092e5ec5dae7,A survey on still image based human action recognition,Pattern Recognition,2014
+1b510618969a298225764eaee54ee700fefb2d23,Depth Structure Association for RGB-D Multi-target Tracking,2014 22nd International Conference on Pattern Recognition,2014
+1bc8cc908cd722cf560b36e14a3333bf7b6114f4,Classification and Feature Extraction by Simplexization,IEEE Transactions on Information Forensics and Security,2008
+1bf01e83fba634bab085ec5f0ab86a1a67da8577,An equalised global graphical model-based approach for multi-camera object tracking,CoRR,2015
+1baeaa776c4f1cf17e690a73f8b38b8064c0e794,A spatio-temporal Long-term Memory approach for visual place recognition in mobile robotic navigation,Robotics and Autonomous Systems,2013
1bc214c39536c940b12c3a2a6b78cafcbfddb59a,Leveraging Gabor Phase for Face Identification in Controlled Scenarios,,2016
+1b5a19828a1dd486ccab1e9c107dfe7bae20cfb7,Pedestrian detection from still images based on multi-feature covariances,2013 IEEE International Conference on Information and Automation (ICIA),2013
+1be32039596ff52fa09772f4606b65845d1c5853,Analysis-by-synthesis: Pedestrian tracking with crowd simulation models in a multi-camera video network,Computer Vision and Image Understanding,2015
+1b31d4a584818ce0f140026d172601116c6bc714,A Multi-layer Composite Model for Human Pose Estimation,,2012
+1bdb09190fc0c66f7e1a6deb7a0ebbaba6b2a42c,Voronoi-Based Compact Image Descriptors: Efficient Region-of-Interest Retrieval With VLAD and Deep-Learning-Based Descriptors,IEEE Transactions on Multimedia,2017
1b79628af96eb3ad64dbb859dae64f31a09027d5,Modeling Recognition Memory Using the Similarity Structure of Natural Input,,2006
1b589016fbabe607a1fb7ce0c265442be9caf3a9,Development of perceptual expertise in emotion recognition.,Cognition,2009
1b27ca161d2e1d4dd7d22b1247acee5c53db5104,Facial soft biometric features for forensic face recognition.,Forensic science international,2015
+1b781faee797beff41ef67703dd80bd6da3c8b23,"A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions",IEEE Transactions on Pattern Analysis and Machine Intelligence,2007
+77cc3e55ff5e18eecc29f2fad1ced236ce9b0689,ENCARA2: Real-time detection of multiple faces at different resolutions in video streams,J. Visual Communication and Image Representation,2007
+77f064553b780471a2812ed2cb667d7332433bdb,Automatic Gait Recognition via Fourier Descriptors of Deformable Objects,,2003
+77addbb49abb80ccd3ebfb5b6f2d3b0687ce90f7,Sparsely-distributed organization of face and limb activations in human ventral temporal cortex,NeuroImage,2010
+77bb7759e09b47b35d5447d1d6fe07957f939f68,Experimental Analysis of Insertion Costs in a Naïve Dynamic MDF-Tree,,2009
776835eb176ed4655d6e6c308ab203126194c41e,Audio-Visual Affective Expression Recognition Through Multistream Fused HMM,IEEE Trans. Multimedia,2008
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+7781ce5bb1b53533d2060aefaf8ddb95a6c77316,A Novel Framework for Robustness Analysis of Visual QA Models,CoRR,2017
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+48c494a8f1fdda835417ccc395a42fe210efec2c,Efficient Spatio-Temporal Data Association Using Multidimensional Assignment for Multi-Camera Multi-Target Tracking,,2015
+48a7c9f9f810b5b5befe7675e8c7ffe40cf473ff,A new algorithm for age recognition from facial images,Signal Processing,2010
4866a5d6d7a40a26f038fc743e16345c064e9842,Stratified sampling for feature subspace selection in random forests for high dimensional data,Pattern Recognition,2013
+483351de2bdf58e21bf8a68a5d75e79a025956d6,Estimating Depth from Monocular Images as Classification Using Deep Fully Convolutional Residual Networks,CoRR,2016
+48832468be331e0257afd88ea71b807503551ca0,Supplementary material for the paper Are Sparse Representations Really Relevant for Image Classification,,2011
48f211a9764f2bf6d6dda4a467008eda5680837a,Predicting occupation via human clothing and contexts,2011 International Conference on Computer Vision,2011
4858d014bb5119a199448fcd36746c413e60f295,Deformable Part Models with Individual Part Scaling,,2013
+487668cc36443a67378f253afe05a550eda2c4f1,Continuous adaptation of multi-camera person identification models through sparse non-redundant representative selection,Computer Vision and Image Understanding,2017
+4879d56e5edc07ba5a34bc08700f0eed72131131,Optimization of Robust Loss Functions for Weakly-Labeled Image Taxonomies: An ImageNet Case Study,,2011
+70d71c2f8c865438c0158bed9f7d64e57e245535,"Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation",,2013
+701d2c119733809f65311bc96733330b3ab59dce,ar X iv : 1 31 2 . 61 84 v 5 [ cs . L G ] 2 1 Fe b 20 14 Do Deep Nets Really Need to be Deep ?,,
703890b7a50d6535900a5883e8d2a6813ead3a03,A spatial-temporal framework based on histogram of gradients and optical flow for facial expression recognition in video sequences,Pattern Recognition,2015
+70111f6868ffab46cf32534d8b2175693c1bbc26,SHOE: Supervised Hashing with Output Embeddings,CoRR,2015
+7066ca7d19a714012dd899f3ac0a84e4c0dc92e7,Processing of novel and familiar faces in infants at average and high risk for autism,Developmental Cognitive Neuroscience,2012
+700af3eb255ecfc9cb93d33fee763047875252ef,Large-Scale Face Image Retrieval: A Wyner-Ziv Coding Approach,,2012
+702ac86ca51e18a3a50ab0ba7c379673c077d97a,Multiscale 3D feature extraction and matching with an application to 3D face recognition,Graphical Models,2013
1ea8085fe1c79d12adffb02bd157b54d799568e4,Eigenfaces vs. Fisherfaces: Recognition Using Class Speciic Linear Projection,,1996
1ebdfceebad642299e573a8995bc5ed1fad173e3,Fisher Kernel Temporal Variation-based Relevance Feedback for video retrieval,Computer Vision and Image Understanding,2016
+1e516f45f87a94ceca466c9a101a01720a535117,A survey on image-based continuum-body motion estimation,Image Vision Comput.,2011
+1e335a6d3cdfe8f53540766b1495c45f72d8fb2f,Multi-Target Tracking and Occlusion Handling with Learned Variational Bayesian Clusters and a Social Force Model,IEEE Trans. Signal Processing,2016
+1e2cfa23aa2a9981bdc7f8f007121de541c387a7,Action Recognition from a Single Web Image Based on an Ensemble of Pose Experts,,2014
1ef4aac0ebc34e76123f848c256840d89ff728d0,Rapid Synthesis of Massive Face Sets for Improved Face Recognition,2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017),2017
+1e94ae83bd49cc9c6366a7f486ed5956e5fa0e14,On the purity of training and testing data for learning: The case of pedestrian detection,Neurocomputing,2015
+1e5fab737794d18f4fb385a53d5ec0fc5c74f32b,Automatic Face Recognition System Based on Local Fourier-Bessel Features,,2005
+1eb27702acf0ec3e36d695f03385fab96b1e3c1e,Coupling camera-tracked humans with a simulated virtual crowd,2014 International Conference on Computer Graphics Theory and Applications (GRAPP),2014
+1e46af829a955dc5ca9c53f94eb416bcd9e2a2ce,Learning better image representations using 'flobject analysis',,2011
+1e5c8fded283dd4c305a1e4c9c1fc8e0988f9c01,Moving obstacle detection in highly dynamic scenes,2009 IEEE International Conference on Robotics and Automation,2009
+8453d03942c2a96a9158ea8e7b23e023fb8b4704,bi-layered artificial neural network and a Counterpropagation,,2008
84fe5b4ac805af63206012d29523a1e033bc827e,Ear recognition: More than a survey,Neurocomputing,2017
84dcf04802743d9907b5b3ae28b19cbbacd97981,Face Detection using Deep Learning: An Improved Faster RCNN Approach,CoRR,2017
+84908a9162b7243e70bff6861d084813ed011f0f,Zero-Shot Learning via Latent Space Encoding,CoRR,2017
+84e48da837978a0660184a0df7647e4b22b078e7,Low Rank Subspace Clustering (LRSC),,2013
+84e9de36dd7915f9334db5cc1fe567e17d717495,Fine-grained categorization via CNN-based automatic extraction and integration of object-level and part-level features,Image Vision Comput.,2017
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+8458e49fb08d2cca3a8d7355465e182c30785220,Visual long-term memory has a massive storage capacity for object details.,Proceedings of the National Academy of Sciences of the United States of America,2008
+4a3b28e5ad2ae2c2f17d681f6177da212e51ca32,An Efficient Method for Service Level Agreement AssessmentI,,2011
+4a9145d52184b20f7241f52509034819c79ee162,Facial Deblur Inference Using Subspace Analysis for Recognition of Blurred Faces,IEEE Transactions on Pattern Analysis and Machine Intelligence,2011
+4add5fda38b0a651295ca2886a9a39ace48dcb3e,An Approach for Energy Efficient Execution of Hybrid Parallel Programs,2015 IEEE International Parallel and Distributed Processing Symposium,2015
+4a12d2c80ae7a4622bf500400ad6fcff83dfb5de,Fusion of Multiple Facial Features for Age Estimation,IEICE Transactions,2009
+4a6049e1926cc8e574301cfb229599cdc0a64e62,Characterizing the performance of an image-based recognizer for planar mechanical linkages in textbook graphics and hand-drawn sketches,Computers & Graphics,2015
+4a1eacd06dbeed8acef3e4ad68b28af3bcebda56,MonoCap: Monocular Human Motion Capture using a CNN Coupled with a Geometric Prior,CoRR,2017
+4ad702b784d0a2fef099a4f0336c92c92a412009,FigureQA: An Annotated Figure Dataset for Visual Reasoning,CoRR,2017
+4a53062c8e0a1ce54adff22d79f409876fdfeea7,CRF - based semantic labeling in miniaturized road scenes ( Extended Abstract ),,2014
+24e64e9fd79f138cf4d90f65da06eacf031ec635,Mapping Cropland in Smallholder-Dominated Savannas: Integrating Remote Sensing Techniques and Probabilistic Modeling,Remote Sensing,2015
24aac045f1e1a4c13a58eab4c7618dccd4c0e671,Video Imagination from a Single Image with Transformation Generation,,2017
240d5390af19bb43761f112b0209771f19bfb696,Towards an intelligent framework for multimodal affective data analysis,Neural networks : the official journal of the International Neural Network Society,2015
+24977d59a5de4eb597347bef00f0c097a641a8dd,Random projection-based partial feature extraction for robust face recognition,Neurocomputing,2015
+24486f70e0fa7a44844adefe352b18aaeb04fdb0,Increased BOLD signal in the fusiform gyrus during implicit emotion processing in anorexia nervosa☆,,2014
+2492bb313093cbfe885d1f3f9da2feba4923baf5,Observing and interpreting complex human activities in everyday environments,Unknown,2010
+249c9034959448e4ca96e9e753570c20ccbd90c9,On the Importance of Objects in Human Action Classification,CoRR,2015
24d376e4d580fb28fd66bc5e7681f1a8db3b6b78,Multi-Branch Fully Convolutional Network for Face Detection,CoRR,2017
+24b31c4d044fc8a625a229fd8296b71836d4a422,"Image classification by non-negative sparse coding, correlation constrained low-rank and sparse decomposition",Computer Vision and Image Understanding,2014
24bf94f8090daf9bda56d54e42009067839b20df,"Automatic Analysis of Facial Affect: A Survey of Registration, Representation, and Recognition",IEEE Transactions on Pattern Analysis and Machine Intelligence,2015
23fdbef123bcda0f07d940c72f3b15704fd49a98,Matrix Completion for Multi-label Image Classification,,2011
+23b3b07cb484bd3aaeaa3728f8977c44f50443f6,A unified tensor framework for face recognition,Pattern Recognition,2009
23ebbbba11c6ca785b0589543bf5675883283a57,Spatio-Temporal Tube data representation and Kernel design for SVM-based video object retrieval system,Multimedia Tools and Applications,2010
+231af7dc01a166cac3b5b01ca05778238f796e41,GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium,CoRR,2017
+23231becd8ca7bd3f1f10660e1709554a21c64bf,Semantic Edge Detection with Diverse Deep Supervision,,2018
+23d5b2dccd48a17e743d3a5a4d596111a2f16c41,3D shape estimation in video sequences provides high precision evaluation of facial expressions,Image Vision Comput.,2012
+23086a13b83d1b408b98346cf44f3e11920b404d,Cascade of Tasks for facial expression analysis,Image Vision Comput.,2016
+2329b177c71c7087013ab4bfdc3154a6ba87ff8c,Real-time and robust object tracking in video via low-rank coherency analysis in feature space,Pattern Recognition,2015
4fd29e5f4b7186e349ba34ea30738af7860cf21f,Circulant Temporal Encoding for Video Retrieval and Temporal Alignment,International Journal of Computer Vision,2015
+4f298d6d0c8870acdbf94fe473ebf6814681bd1f,Going deeper into action recognition: A survey,Image Vision Comput.,2017
4fbef7ce1809d102215453c34bf22b5f9f9aab26,Robust Face Recognition for Data Mining,,2009
4fa0d73b8ba114578744c2ebaf610d2ca9694f45,Rethinking Spatiotemporal Feature Learning For Video Understanding,CoRR,2017
+4f9001753ceb18ee06f825687abe0e3d292e71e0,Non-parametric score normalization for biometric verification systems,Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012),2012
+4fc67275bd9d68895933c3baddec266402cc2412,A Correlation Based Feature Representation for First-Person Activity Recognition,CoRR,2017
4f0bf2508ae801aee082b37f684085adf0d06d23,Max-margin Non-negative Matrix Factorization,Image Vision Comput.,2012
+4f7d9c5fc3e0fd1b1a4860003bf2b482a215f721,Building and using fuzzy multimedia ontologies for semantic image annotation,Multimedia Tools and Applications,2013
+4f5ceebe7d166b2b96ef080e179e8f58f7787e5d,"Cognitive Tomography Reveals Complex, Task-Independent Mental Representations",,2013
+8d2d27753d316494574c4e8ac51190921e0765bb,Partially-supervised learning from facial trajectories for face recognition in video surveillance,Information Fusion,2015
+8d3b9a07483a9a80e7e8d67d9042ab6557c578d2,Head detection and orientation estimation for pedestrian safety,17th International IEEE Conference on Intelligent Transportation Systems (ITSC),2014
8d71872d5877c575a52f71ad445c7e5124a4b174,Shadow compensation in 2D images for face recognition,Pattern Recognition,2007
+8d5ea0c79eecc9e6c857eac5d494d57960e0f587,Watch-List Screening Using Ensembles Based on Multiple Face Representations,2014 22nd International Conference on Pattern Recognition,2014
+8d96fbc52ffd784dee573d44e0c47a3577fd0266,Face identity recognition in autism spectrum disorders: a review of behavioral studies.,Neuroscience and biobehavioral reviews,2012
+8de026cf8a9a82d55743aaa4ec18c86029fda096,Bayesian Semantic Instance Segmentation in Open Set World,Unknown,2018
+8dc81389a61d4d80644f44e1fcfd35ccfb332082,Understanding and Predicting The Attractiveness of Human Action Shot,CoRR,2017
8dbe79830713925affc48d0afa04ed567c54724b,Automatic facial age estimation,,2015
+8dc2b137b2a1a3713f6ce5e78f621a9f0f036bf8,Non-myopic information theoretic sensor management of a single pan-tilt-zoom camera for multiple object detection and tracking,Computer Vision and Image Understanding,2015
8d712cef3a5a8a7b1619fb841a191bebc2a17f15,Non-verbal communication analysis in Victim-Offender Mediations,Pattern Recognition Letters,2015
+15860bc14c38c89256a4263b0d31eb67fd8ed923,Mel-cepstral methods for image feature extraction,2010 IEEE International Conference on Image Processing,2010
+1523ca87c74e967870e2aab738d9b25c15c03e8a,RoboCupRescue 2010 - Robot League Team,,2010
+15f795d436aaa9e77ccccb00b9df49bf0127f8b1,"Dissociation between face perception and face memory in adults, but not children, with developmental prosopagnosia",Developmental Cognitive Neuroscience,2014
+150f4d8a46dd90048acada63c42c12392c5706f5,Automatic Facial Expression Recognition using Bags of Motion Words,,2010
+15c99ba792bfb0496694884af5075c81a266ee46,Reconstructing Evolving Tree Structures in Time Lapse Sequences by Enforcing Time-Consistency - Appendix,,2017
+15b07dae17f184c8e6efbc9d2b58526d8e8dc9d4,Sketched Subspace Clustering,IEEE Transactions on Signal Processing,2018
+15e28e884fb6c7eba2610e3dfcd5b40dadb14155,DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection,CoRR,2014
+155219f3e6dcf5d5f44815a7493b6b7cc8e02263,Fully convolutional neural networks for dynamic object detection in grid maps,2017 IEEE Intelligent Vehicles Symposium (IV),2017
+15e27e189fe9549d674ebd0f55a7bf1fa026cb85,A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects,CoRR,2016
1513949773e3a47e11ab87d9a429864716aba42d,Demographic classification from face videos using manifold learning,Neurocomputing,2013
+1550518a37d58e708023b9a1d457940a9c465717,Isometric deformation invariant 3D shape recognition,Pattern Recognition,2012
+1212af29cc596e8d058c1dc450b2040c51be6d6c,Multi-modal human aggression detection,Computer Vision and Image Understanding,2016
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+12feba45b219f129b5f12c16b5ffb5c1687b66e0,Learning a Fully Convolutional Network for Object Recognition using very few Data,CoRR,2017
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+1203b4fe233bb7514d7ba257089392c16a83a17b,Performance Analysis of Joint Opportunistic Scheduling and Receiver Design for MIMO-SDMA Downlink,,2011
+123286df95d93600f4281c60a60c69121c6440c7,Deep self-paced learning for person re-identification,Pattern Recognition,2018
1287bfe73e381cc8042ac0cc27868ae086e1ce3b,Computational Mid-Level Vision: From Border Ownership to Categorical Object Recognition,Unknown,2015
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12c713166c46ac87f452e0ae383d04fb44fe4eb2,Fusion Classifier for Open-Set Face Recognition with Pose Variations,,2009
+12bbd57ce427a9f847fdf4456eab3bd5caeb5891,Multiple Viewpoint Recognition and Localization,,2010
+12b2ae1ebbaed2e664a028b3d845456061722a6a,Greedy algorithm for real-time multi-object tracking,2014 IEEE International Conference on Image Processing (ICIP),2014
+128335bef19faa51f127e6a07a434b8949f59b0b,Human Attention in Visual Question Answering: Do Humans and Deep Networks look at the same regions?,Computer Vision and Image Understanding,2016
8cb3f421b55c78e56c8a1c1d96f23335ebd4a5bf,Facial expression recognition and synthesis based on an appearance model,Sig. Proc.: Image Comm.,2004
+8cb3e0c4ad37dd7e0abd2eedd704d4d27edb0a17,Vehicle Detection in Aerial Images,CoRR,2018
855bfc17e90ec1b240efba9100fb760c068a8efa,Facial expression recognition using tracked facial actions: Classifier performance analysis,Eng. Appl. of AI,2013
+852ff0d410a25ebb7936043a05efe2469c699e4b,Learning local binary patterns for gender classification on real-world face images,Pattern Recognition Letters,2012
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1dbbec4ad8429788e16e9f3a79a80549a0d7ac7b,Global Sensitivity Analysis for MAP Inference in Graphical Models,,2014
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1d846934503e2bd7b8ea63b2eafe00e29507f06a,Manifold Based Analysis of Facial Expression,2004 Conference on Computer Vision and Pattern Recognition Workshop,2004
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760a712f570f7a618d9385c0cee7e4d0d6a78ed2,Sparse Representation with Kernels,,2012
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2e20ed644e7d6e04dd7ab70084f1bf28f93f75e9,DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification,,2008
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2e0e056ed5927a4dc6e5c633715beb762628aeb0,Multilinear Supervised Neighborhood Preserving Embedding Analysis of Local Descriptor Tensor,,2012
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2ee8900bbde5d3c81b7ed4725710ed46cc7e91cd,Graph embedding: a general framework for dimensionality reduction,2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05),2005
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2e19371a2d797ab9929b99c80d80f01a1fbf9479,"L2, 1-based regression and prediction accumulation across views for robust facial landmark detection",Image Vision Comput.,2016
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2e86402b354516d0a8392f75430156d629ca6281,Joint Unsupervised Learning of Deep Representations and Image Clusters,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
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2b3ceb40dced78a824cf67054959e250aeaa573b,Differentially private subspace clustering,,2015
2baec98c19804bf19b480a9a0aa814078e28bb3d,Multi-conditional Latent Variable Model for Joint Facial Action Unit Detection,2015 IEEE International Conference on Computer Vision (ICCV),2015
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47f8b3b3f249830b6e17888df4810f3d189daac1,Translational photometric alignment of single-view image sequences,Computer Vision and Image Understanding,2012
47aeb3b82f54b5ae8142b4bdda7b614433e69b9a,"Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected ""In-the-Wild""",,2013
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47e14fdc6685f0b3800f709c32e005068dfc8d47,Secure Face Matching Using Fully Homomorphic Encryption,CoRR,2018
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78a4cabf0afc94da123e299df5b32550cd638939,Multi-view face recognition from single RGBD models of the faces,Computer Vision and Image Understanding,2017
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7897c8a9361b427f7b07249d21eb9315db189496,Feature selection via simultaneous sparse approximation for person specific face verification,2011 18th IEEE International Conference on Image Processing,2011
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78a11b7d2d7e1b19d92d2afd51bd3624eca86c3c,Improved Deep Metric Learning with Multi-class N-pair Loss Objective,,2016
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788a7b59ea72e23ef4f86dc9abb4450efefeca41,Robust Statistical Face Frontalization,2015 IEEE International Conference on Computer Vision (ICCV),2015
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8b8728edc536020bc4871dc66b26a191f6658f7c,Robust gender recognition by exploiting facial attributes dependencies,Pattern Recognition Letters,2014
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+8b98aa8be775eb4618779a682ba994b36adba24e,The role of priors in Bayesian models of perception,,2013
+133f42368e63928dc860cce7618f30ee186d328c,Local Zernike Moment Representation for Facial Affect Recognition,,2013
+137f8195eaa8e68f133395a9b9a232bffa7b2fc3,F Face Recognition Using Singular Value Decomposition along with Seven State,,2013
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+131130f105661a47e0ffb85c2fe21595785f948a,Supplemental Material: Unsupervised Feature Extraction Inspired by Latent Low-Rank Representation,,2014
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13fd0a4d06f30a665fc0f6938cea6572f3b496f7,Regularized Extreme Learning Machine for Large-scale Media Content Analysis,,2015
+1339188247e3b8fd102b37501eb93cbeab71b870,Measuring the performance of face localization systems,Image Vision Comput.,2006
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+7fb6bc6c920ca574677f0d3a40c5c377a095885b,Statistical synthesis of facial expressions for the portrayal of emotion,,2004
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7a85b3ab0efb6b6fcb034ce13145156ee9d10598,Inter-image outliers and their application to image classification,Pattern Recognition,2010
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14e949f5754f9e5160e8bfa3f1364dd92c2bb8d6,Multi-subregion based correlation filter bank for robust face recognition,Pattern Recognition,2014
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141eab5f7e164e4ef40dd7bc19df9c31bd200c5e,Local Linear Regression (LLR) for Pose Invariant Face Recognition,7th International Conference on Automatic Face and Gesture Recognition (FGR06),2006
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1473a233465ea664031d985e10e21de927314c94,Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks,IEEE transactions on neural networks and learning systems,2016
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8ed32c8fad924736ebc6d99c5c319312ba1fa80b,Centralized Gradient Pattern for Face Recognition,IEICE Transactions,2013
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225fb9181545f8750061c7693661b62d715dc542,Multi-Level ResNets with Stacked SRUs for Action Recognition,CoRR,2017
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22a7f1aebdb57eecd64be2a1f03aef25f9b0e9a7,Attribute-restricted latent topic model for person re-identification,Pattern Recognition,2012
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+25d75339720787e7003f2f103cf38cee8175972a,Optimistic and Pessimistic Neural Networks for Scene and Object Recognition,CoRR,2016
+259e35fa5a57cf16010621639957777ebad72367,Tied Factor Analysis for Face Recognition Across Large Pose Changes,,2006
+25fce91ce1b974865506c14d2e4714d8db2672d1,Towards a Practical Face Recognition System: Robust Alignment and Illumination by Sparse Representation,,2011
+256c91400aa7e92160c889654614f70213947f06,Abrupt motion tracking via nearest neighbor field driven stochastic sampling,Neurocomputing,2015
+2557e2ed0a19cbe2d78e3d4daa5d39e62be5d009,"Detection and Segmentation of Multiple, Partially Occluded Objects by Grouping, Merging, Assigning Part Detection Responses",2008 IEEE Conference on Computer Vision and Pattern Recognition,2008
+2582ba3b7ca215f1ab98c6dbcc0190f754c54059,Robust Recovery of Subspace Structures by Low-Rank Representation,IEEE Transactions on Pattern Analysis and Machine Intelligence,2013
+256ef946b4cecd8889df8d799d0c9175ae986af9,Human Facial Expression Recognition Using Stepwise Linear Discriminant Analysis and Hidden Conditional Random Fields,IEEE Transactions on Image Processing,2015
+25b367dd1cc584a89e8fd7b34a7d98d212a9f168,A novel statistical generative model dedicated to face recognition,Image Vision Comput.,2010
+25b215169540e9109107a048c9e68159af82b771,Contrast invariant features for human detection in far infrared images,2012 IEEE Intelligent Vehicles Symposium,2012
2574860616d7ffa653eb002bbaca53686bc71cdd,Culture shapes 7-month-olds’ perceptual strategies in discriminating facial expressions of emotion,Current Biology,2016
+25366ca0d124ca6222c7edf72681943969055024,Human activity prediction by mapping grouplets to recurrent Self-Organizing Map,Neurocomputing,2016
25728e08b0ee482ee6ced79c74d4735bb5478e29,Thermal spatio-temporal data for stress recognition,EURASIP J. Image and Video Processing,2014
diff --git a/scraper/reports/stats/geocoded_papers.csv b/scraper/reports/stats/geocoded_papers.csv index 67316468..2001c0cf 100644 --- a/scraper/reports/stats/geocoded_papers.csv +++ b/scraper/reports/stats/geocoded_papers.csv @@ -1,75 +1,219 @@ 611961abc4dfc02b67edd8124abb08c449f5280a,Exploiting Image-trained CNN Architectures for Unconstrained Video Classification,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
611961abc4dfc02b67edd8124abb08c449f5280a,Exploiting Image-trained CNN Architectures for Unconstrained Video Classification,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+61efa60e16c06e2820d863bc55f3c60e86f3f6e7,Pose Estimation of Players in Hockey Videos using Convolutional Neural Networks,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+616b7093cfe6ec679f25d63f62c16e937227258f,Bayesian Multi-object Tracking Using Motion Context from Multiple Objects,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
+616e69647b02e69cffa7eeb83cf3e72b8c532653,Spatiotemporal Networks for Video Emotion Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+616e69647b02e69cffa7eeb83cf3e72b8c532653,Spatiotemporal Networks for Video Emotion Recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+616e69647b02e69cffa7eeb83cf3e72b8c532653,Spatiotemporal Networks for Video Emotion Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+616e69647b02e69cffa7eeb83cf3e72b8c532653,Spatiotemporal Networks for Video Emotion Recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+6115445ca062b8f865f0b447c059813088b9dd49,A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering,Polytechnique Montreal,Polytechnique Montr´eal,"2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4, Canada",45.50438400,-73.61288290,edu,"Polytechnique Montreal, Montreal, Quebec, Canada"
+61b288d120a44a0d92bae6e940eade40b1f26484,Accurate Object Detection with Joint Classification-Regression Random Forests,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+61dfbdfe718aca026cafa06adc63055bd0fc562e,A Multi-scale Triplet Deep Convolutional Neural Network for Person Re-identification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+61dfbdfe718aca026cafa06adc63055bd0fc562e,A Multi-scale Triplet Deep Convolutional Neural Network for Person Re-identification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+61dfbdfe718aca026cafa06adc63055bd0fc562e,A Multi-scale Triplet Deep Convolutional Neural Network for Person Re-identification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+61e8584f5f37e6f47bdd2be2f93251ed5934cf48,Learning Binary Codes and Binary Weights for Efficient Classification,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+61933c42ed53f4fff5653489fb376ee967934701,Spatio-Temporal Person Retrieval via Natural Language Queries,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
6156eaad00aad74c90cbcfd822fa0c9bd4eb14c2,Complex Bingham Distribution for Facial Feature Detection,University of Louisville,University of Louisville,"University of Louisville, South Brook Street, Louisville, Jefferson County, Kentucky, 40208, USA",38.21675650,-85.75725023,edu,
6156eaad00aad74c90cbcfd822fa0c9bd4eb14c2,Complex Bingham Distribution for Facial Feature Detection,Alexandria University,Alexandria University,"جامعة الإسكندرية, الكورنيش, إبراهيمية, الإسكندرية, 21522, مصر",31.21051105,29.91314562,edu,
61ffedd8a70a78332c2bbdc9feba6c3d1fd4f1b8,Greedy Feature Selection for Subspace Clustering Greedy Feature Selection for Subspace Clustering,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
61ffedd8a70a78332c2bbdc9feba6c3d1fd4f1b8,Greedy Feature Selection for Subspace Clustering Greedy Feature Selection for Subspace Clustering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
61ffedd8a70a78332c2bbdc9feba6c3d1fd4f1b8,Greedy Feature Selection for Subspace Clustering Greedy Feature Selection for Subspace Clustering,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
+614a547cb976fae955e276feb2ccc9a33f1c7806,Classifier-as-a-Service: Online Query of Cascades and Operating Points,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
61542874efb0b4c125389793d8131f9f99995671,Fair comparison of skin detection approaches on publicly available datasets,University of Bologna,Università di Bologna,"Via Zamboni, 33, 40126 Bologna BO, Italy",44.49623180,11.35415700,edu,
61f93ed515b3bfac822deed348d9e21d5dffe373,Deep Image Set Hashing,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
61f93ed515b3bfac822deed348d9e21d5dffe373,Deep Image Set Hashing,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+611849b55ef6b164f21e52cefd05300041e72152,A MultiTask Deep Network for Person Re-Identification,University of Dundee,University of Dundee,"University of Dundee, Park Wynd, Law, Dundee, Dundee City, Scotland, DD1 4HN, UK",56.45796755,-2.98214831,edu,
+61be9e8b1f2d642eb0b91a6097fe1c50c37a285c,Face Alignment Based on 3D Face Shape Model and Markov Random Field,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
612075999e82596f3b42a80e6996712cc52880a3,CNNs with cross-correlation matching for face recognition in video surveillance using a single training sample per person,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
61efeb64e8431cfbafa4b02eb76bf0c58e61a0fa,Merging datasets through deep learning,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
61efeb64e8431cfbafa4b02eb76bf0c58e61a0fa,Merging datasets through deep learning,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+6111832ed676ad0789d030577c87d4a539242bd3,CU-Net: Coupled U-Nets,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+6111832ed676ad0789d030577c87d4a539242bd3,CU-Net: Coupled U-Nets,Binghamton University,Binghamton University,"Binghamton University Downtown Center, Washington Street, Downtown, Binghamton, Broome County, New York, 13901, USA",42.09580770,-75.91455689,edu,
61e9e180d3d1d8b09f1cc59bdd9f98c497707eff,Semi-supervised Learning of Facial Attributes in Video,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+611c8dcb8cc4c328f0b3be7961adb47689b371c1,The utility of multiple synthesized views in the recognition of unfamiliar faces,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
+611c8dcb8cc4c328f0b3be7961adb47689b371c1,The utility of multiple synthesized views in the recognition of unfamiliar faces,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
6193c833ad25ac27abbde1a31c1cabe56ce1515b,Trojaning Attack on Neural Networks,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+6123e52c1a560c88817d8720e05fbff8565271fb,Gated Siamese Convolutional Neural Network Architecture for Human Re-identification,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
614079f1a0d0938f9c30a1585f617fa278816d53,Automatic Detection of ADHD and ASD from Expressive Behaviour in RGBD Data,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
614079f1a0d0938f9c30a1585f617fa278816d53,Automatic Detection of ADHD and ASD from Expressive Behaviour in RGBD Data,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+61acd4e07657094c2720bb60299dba0014ec89a6,Image annotation by kNN-sparse graph-based label propagation over noisily tagged web images,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+61acd4e07657094c2720bb60299dba0014ec89a6,Image annotation by kNN-sparse graph-based label propagation over noisily tagged web images,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+61acd4e07657094c2720bb60299dba0014ec89a6,Image annotation by kNN-sparse graph-based label propagation over noisily tagged web images,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+61acd4e07657094c2720bb60299dba0014ec89a6,Image annotation by kNN-sparse graph-based label propagation over noisily tagged web images,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+6196fa926ae752f927cd550b74259069e18abc71,Unsupervised Holistic Image Generation from Key Local Patches,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+61a7aae4f90ce5214fe899647e58e803b70ba5eb,Emotionally aware automated portrait painting,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+61a7aae4f90ce5214fe899647e58e803b70ba5eb,Emotionally aware automated portrait painting,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+61a7aae4f90ce5214fe899647e58e803b70ba5eb,Emotionally aware automated portrait painting,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+61847a342471d9482129bc2d6e0c79089f331040,Pose search: Retrieving people using their pose,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+6184ddbe780cb934f036b04dd1d28226b6bcbcce,Supervised hashing with kernels,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+6184ddbe780cb934f036b04dd1d28226b6bcbcce,Supervised hashing with kernels,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+6184ddbe780cb934f036b04dd1d28226b6bcbcce,Supervised hashing with kernels,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
0d746111135c2e7f91443869003d05cde3044beb,Partial face detection for continuous authentication,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
0d746111135c2e7f91443869003d05cde3044beb,Partial face detection for continuous authentication,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+0d1d7471e8b08a4577b60a63b35fbd88dbf38ec0,A dataset for workflow recognition in industrial scenes,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
0da75b0d341c8f945fae1da6c77b6ec345f47f2a,The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People With Visual Impairments,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
0da75b0d341c8f945fae1da6c77b6ec345f47f2a,The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People With Visual Impairments,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
0db43ed25d63d801ce745fe04ca3e8b363bf3147,Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape Models,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
0daf696253a1b42d2c9d23f1008b32c65a9e4c1e,Unsupervised discovery of facial events,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
0daf696253a1b42d2c9d23f1008b32c65a9e4c1e,Unsupervised discovery of facial events,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0d7810ba414b746b0d4f73aa94042bb0ea8f324d,Attention-based Few-Shot Person Re-identification Using Meta Learning,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
+0d5f898d59ce592ce5cc62643753aee72c4153ce,Backprojection Revisited: Scalable Multi-view Object Detection and Similarity Metrics for Detections,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
+0da2a7ee04092645867614db3574cb261f33b6e2,Watching Unlabeled Video Helps Learn New Human Actions from Very Few Labeled Snapshots,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
0de91641f37b0a81a892e4c914b46d05d33fd36e,RAPS: Robust and Efficient Automatic Construction of Person-Specific Deformable Models,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
0de91641f37b0a81a892e4c914b46d05d33fd36e,RAPS: Robust and Efficient Automatic Construction of Person-Specific Deformable Models,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+0d6f874b5a0772d1ea88e85a010a01e381d02982,Sparse Kernel Clustering of Massive High-Dimensional Data sets with Large Number of Clusters,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+0db41739f514c4c911c54a4c90ab5f07db3862dc,NCA-Net for Tracking Multiple Objects across Multiple Cameras,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
0df0d1adea39a5bef318b74faa37de7f3e00b452,Appearance-based gaze estimation in the wild,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+0d3018c0630fe3f44f96c7cb4c6cabc1517b100a,Fully Convolutional Crowd Counting on Highly Congested Scenes,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+0df90f86da6e92c7a351be6d5f7cf9c1452124d0,Person Search by Multi-Scale Matching,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+0d08ab78ce86e053ff3003aef951a5174d56beb8,A Thermal Infrared Video Benchmark for Visual Analysis,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+0d08ab78ce86e053ff3003aef951a5174d56beb8,A Thermal Infrared Video Benchmark for Visual Analysis,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+0db6a58927a671c01089c53248b0e1c36bdc3231,Efficient Point Process Inference for Large-Scale Object Detection,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
0d3bb75852098b25d90f31d2f48fd0cb4944702b,A data-driven approach to cleaning large face datasets,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0d5bb6e4d2394e78c25ef9312ccbb3085d294d66,Spatial-Temporal Synergic Residual Learning for Video Person Re-Identification,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+0d0a348510cb2fbefbb3225ee18fafc1479eaeef,Multi-Language Image Description with Neural Sequence Models,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+0d0a348510cb2fbefbb3225ee18fafc1479eaeef,Multi-Language Image Description with Neural Sequence Models,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
0d0b880e2b531c45ee8227166a489bf35a528cb9,Structure Preserving Object Tracking,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+0d57d3d2d04fc96d731cac99a7a8ef79050dac75,Not Everybody's Special: Using Neighbors in Referring Expressions with Uncertain Attributes,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+0daaa56d724c11e64338996e99a257fa69900236,Recurrent Convolutional Neural Network Regression for Continuous Pain Intensity Estimation in Video,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+0d75052f1d7350fa035a35566555ce7b65d1cd2f,Oracle Performance for Visual Captioning,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+0dc49271dc30794c8d4e7f9da025880fcdc8498b,Cascaded Mutual Modulation for Visual Reasoning,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
0d3068b352c3733c9e1cc75e449bf7df1f7b10a4,Context Based Facial Expression Analysis in the Wild,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
0dfa460a35f7cab4705726b6367557b9f7842c65,Modeling Spatial-Temporal Clues in a Hybrid Deep Learning Framework for Video Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+0da5384dbd1646ed722bd9dc7f7387cbcadcb41f,Learning Deep Representation with Large-Scale Attributes,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+0d2e29f07275fe05a44b04f16cd3edd0c3f448f0,Development of the Korean Facial Emotion Stimuli: Korea University Facial Expression Collection 2nd Edition,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+0d2e29f07275fe05a44b04f16cd3edd0c3f448f0,Development of the Korean Facial Emotion Stimuli: Korea University Facial Expression Collection 2nd Edition,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+0de0c329e07ffb91d100424259a4a18973d731a9,Functionally Modular and Interpretable Temporal Filtering for Robust Segmentation,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+0d35ab4d59c3731986965dcc935d11074832bc1d,Detecting adversarial example attacks to deep neural networks,University of Pisa,University of Pisa,"Dipartimento di Fisica 'E. Fermi', 3, Largo Bruno Pontecorvo, San Francesco, Pisa, PI, TOS, 56127, Italia",43.72012990,10.40789760,edu,
0d14261e69a4ad4140ce17c1d1cea76af6546056,Adding Facial Actions into 3D Model Search to Analyse Behaviour in an Unconstrained Environment,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
0dbacb4fd069462841ebb26e1454b4d147cd8e98,Recent advances in discriminant non-negative Matrix Factorization,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
0db36bf08140d53807595b6313201a7339470cfe,Moving vistas: Exploiting motion for describing scenes,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+0dceca6bb3ac648c611f7097cf52a9b7f59be6f9,An Egocentric Look at Video Photographer Identity,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
0d781b943bff6a3b62a79e2c8daf7f4d4d6431ad,EmotiW 2016: video and group-level emotion recognition challenges,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
0d781b943bff6a3b62a79e2c8daf7f4d4d6431ad,EmotiW 2016: video and group-level emotion recognition challenges,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
0d781b943bff6a3b62a79e2c8daf7f4d4d6431ad,EmotiW 2016: video and group-level emotion recognition challenges,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
0d781b943bff6a3b62a79e2c8daf7f4d4d6431ad,EmotiW 2016: video and group-level emotion recognition challenges,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
0d781b943bff6a3b62a79e2c8daf7f4d4d6431ad,EmotiW 2016: video and group-level emotion recognition challenges,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+0d4c620aa869585e31ca7018c813569f3ec1a028,Survey on Vision-Based Path Prediction,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+0d4c620aa869585e31ca7018c813569f3ec1a028,Survey on Vision-Based Path Prediction,Hiroshima University,Hiroshima University,"Hiroshima University 広島大学 東広島キャンパス, 出会いの道 Deai-no-michi Str., 西条下見, 東広島市, 広島県, 中国地方, 739-0047, 日本",34.40197660,132.71231950,edu,
+0d7f770c3b6857d5ef5dfe5f1b23e69f4a575fd3,Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+0d7f770c3b6857d5ef5dfe5f1b23e69f4a575fd3,Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+0d7f770c3b6857d5ef5dfe5f1b23e69f4a575fd3,Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+0dcff2dbf287a6e2937f495e1cd887297863296d,A Novel Method for Estimating Free Space 3D Point-of-Regard Using Pupillary Reflex and Line-of-Sight Convergence Points,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+0dcff2dbf287a6e2937f495e1cd887297863296d,A Novel Method for Estimating Free Space 3D Point-of-Regard Using Pupillary Reflex and Line-of-Sight Convergence Points,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2,Effects of emotional expressions on persuasion,University of Nebraska - Lincoln,University of Nebraska - Lincoln,"Sheldon Museum of Art, North 12th Street, West Lincoln, Lincoln, Lancaster County, Nebraska, 68588-0300, USA",40.81747230,-96.70444680,edu,
0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+0d5fa5be4bfe085de8f88dbee1c3b2a6e5ab9ee2,ICNet for Real-Time Semantic Segmentation on High-Resolution Images,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+95f858658c2955924c00e8abc2018c68c3837e83,Harmonious Attention Network for Person Re-Identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+95df7770a5036c87104df23f333aa05e67723cdc,DeepDiary: Automatically Captioning Lifelogging Image Streams,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+9507e5c59c45e68b964fdaf40e39569dcc754be3,A Hybrid Supervised-unsupervised Method on Image Topic Visualization with Convolutional Neural Network and LDA,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
951368a1a8b3c5cd286726050b8bdf75a80f7c37,A family of online boosting algorithms,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
951368a1a8b3c5cd286726050b8bdf75a80f7c37,A family of online boosting algorithms,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
951368a1a8b3c5cd286726050b8bdf75a80f7c37,A family of online boosting algorithms,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+95616c511e1eada5c4fba090fe739a4554711e22,Lip Contour Localization using Statistical Shape Models,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
956e9b69b3366ed3e1670609b53ba4a7088b8b7e,Semi-supervised dimensionality reduction for image retrieval,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+95a5cb872321addb28d5dc22ffad9586f113738a,MinMax Radon Barcodes for Medical Image Retrieval,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+95a5cb872321addb28d5dc22ffad9586f113738a,MinMax Radon Barcodes for Medical Image Retrieval,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+95a5cb872321addb28d5dc22ffad9586f113738a,MinMax Radon Barcodes for Medical Image Retrieval,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+9534a04de5e99a44df76ea30140f66a62e83fdaa,Iteratively Trained Interactive Segmentation,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+95a0c9f41d0cc6f45853d616d5476b8aee54ff0a,Deep Variational Inference Without Pixel-Wise Reconstruction,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+9528e2e8c20517ab916f803c0371abb4f0ed488b,Shallow and Deep Convolutional Networks for Saliency Prediction,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+9563456bfdd8b18df7f764400c04976771eb8728,Pay Attention to Those Sets! Learning Quantification from Images,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+9563456bfdd8b18df7f764400c04976771eb8728,Pay Attention to Those Sets! Learning Quantification from Images,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+956d6e48598cac9aa6129a87a7f8cdb634917aa1,R 2 SDH : Robust Rotated Supervised Discrete Hashing,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+9507b1a7af5442f8c247451a63400893de34d9f9,Distributed learning of CNNs on heterogeneous CPU/GPU architectures,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
+9507b1a7af5442f8c247451a63400893de34d9f9,Distributed learning of CNNs on heterogeneous CPU/GPU architectures,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
+95052cd12cfca8b0f8162dc53fe5615fc9c06b22,Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
95f26d1c80217706c00b6b4b605a448032b93b75,New Robust Face Recognition Methods Based on Linear Regression,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
95f12d27c3b4914e0668a268360948bce92f7db3,Interactive Facial Feature Localization,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+954af3d46d023d73c7ee97f2264451080f542084,The Interplay between Emotion and Cognition in Autism Spectrum Disorder: Implications for Developmental Theory,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+95a3af61b398976c13d96baa32481e1bf4a31984,Geometric Enclosing Networks,Deakin University,Deakin University,"Deakin University, Pigdons Lane, Waurn Ponds, Geelong, City of Greater Geelong, Barwon South West, Victoria, 3216, Australia",-38.19928505,144.30365229,edu,
+95a3af61b398976c13d96baa32481e1bf4a31984,Geometric Enclosing Networks,Deakin University,Deakin University,"Deakin University, Pigdons Lane, Waurn Ponds, Geelong, City of Greater Geelong, Barwon South West, Victoria, 3216, Australia",-38.19928505,144.30365229,edu,
+95a3af61b398976c13d96baa32481e1bf4a31984,Geometric Enclosing Networks,Deakin University,Deakin University,"Deakin University, Pigdons Lane, Waurn Ponds, Geelong, City of Greater Geelong, Barwon South West, Victoria, 3216, Australia",-38.19928505,144.30365229,edu,
+956466b5c3036ada2e18f8f7c1b7bf0650779d08,Learning patch-dependent kernel forest for person re-identification,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
955e2a39f51c0b6f967199942d77625009e580f9,Naming Faces on the Web,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+95bc6f4ff5033a091b6ddc6a4290a58c7e6ddc66,FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+95bc6f4ff5033a091b6ddc6a4290a58c7e6ddc66,FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+9541e80b15ee3e1793f2caafc3502a6fd6947b24,Discriminative Semi-Supervised Dictionary Learning with Entropy Regularization for Pattern Classification,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+9541e80b15ee3e1793f2caafc3502a6fd6947b24,Discriminative Semi-Supervised Dictionary Learning with Entropy Regularization for Pattern Classification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+95cfe8da0d8225c8f6304713719846a7716894cf,Integrating Perception and Cognition for AGI,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+95cfe8da0d8225c8f6304713719846a7716894cf,Integrating Perception and Cognition for AGI,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+95cfe8da0d8225c8f6304713719846a7716894cf,Integrating Perception and Cognition for AGI,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+95debf4c4f88d48a71bae9bfea4032355805aa2f,Bounding the Probability of Error for High Precision Optical Character Recognition,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+95debf4c4f88d48a71bae9bfea4032355805aa2f,Bounding the Probability of Error for High Precision Optical Character Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+95debf4c4f88d48a71bae9bfea4032355805aa2f,Bounding the Probability of Error for High Precision Optical Character Recognition,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+9563d6fafb6ba09c082a57e8d9b31494029a45ac,Building a Large-scale Multimodal Knowledge Base for Visual Question Answering,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+9563d6fafb6ba09c082a57e8d9b31494029a45ac,Building a Large-scale Multimodal Knowledge Base for Visual Question Answering,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
950171acb24bb24a871ba0d02d580c09829de372,Speeding up 2 D-Warping for Pose-Invariant Face Recognition,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+954909051c1d7d5a8ba885f1c09afe04c8aab0fb,IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+955aa3e7317e236e41f05ec2853b64236c252af0,SAM-RCNN: Scale-Aware Multi-Resolution Multi-Channel Pedestrian Detection,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+95896eef75a5fc6c8a7ac2531e76c423d678d2e7,Image Generation from Sketch Constraint Using Contextual GAN,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+95896eef75a5fc6c8a7ac2531e76c423d678d2e7,Image Generation from Sketch Constraint Using Contextual GAN,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+95f4b88d4b0a725d786b34558b60af47f5442230,Reconfigurable Processor for Deep Learning in Autonomous Vehicles,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+95f4b88d4b0a725d786b34558b60af47f5442230,Reconfigurable Processor for Deep Learning in Autonomous Vehicles,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+95f4b88d4b0a725d786b34558b60af47f5442230,Reconfigurable Processor for Deep Learning in Autonomous Vehicles,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+59f83e94a7f52cbb728d434426f6fe85f756259c,An Improved Illumination Normalization Approach based on Wavelet Tranform for Face Recognition from Single Training Image Per Person,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
59be98f54bb4ed7a2984dc6a3c84b52d1caf44eb,A deep-learning approach to facial expression recognition with candid images,CUNY City College,CUNY City College,"CUNY City College, 205 East 42nd Street, New York, NY 10017",45.55466080,5.40652550,edu,
591a737c158be7b131121d87d9d81b471c400dba,Affect valence inference from facial action unit spectrograms,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+59b095bdbd4b3f4a8240ad011b1d0b318b526d78,Recognizing and Filtering Web Images Based on People's Existence,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+591a4dddbebd3d3ce3d86f9910be40aafcb73a90,Multi-person Tracking by Multicut and Deep Matching,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+5955e31c413a4a08d149de8af843355ac45525bc,Supervised Kernel Locally Principle Component Analysis for Face Recognition,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
+59778de271938df6de938deac17fd614f4640ac5,Cleaning up after a face tracker: False positive removal,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+59778de271938df6de938deac17fd614f4640ac5,Cleaning up after a face tracker: False positive removal,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
+59a0b3537bf4f764c192812c4b48049f5c8fccc3,Unsupervised Object Discovery from Images by Mining Local Features Using Hashing,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
593234ba1d2e16a887207bf65d6b55bbc7ea2247,Combining Language Sources and Robust Semantic Relatedness for Attribute-Based Knowledge Transfer,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+59f77456b4e2ffe84f99ac33796ee409143dbdac,ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+59e91bd46492391beadce041806297e856af6ee6,Escaping from Collapsing Modes in a Constrained Space,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
59e2037f5079794cb9128c7f0900a568ced14c2a,Clothing and People - A Social Signal Processing Perspective,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
59dac8b460a89e03fa616749a08e6149708dcc3a,A Convergent Solution to Matrix Bidirectional Projection Based Feature Extraction with Application to Face Recognition,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+59444832eb559c0060020b57cddbb899efc4567b,Vision-Based Fallen Person Detection for the Elderly,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
59e9934720baf3c5df3a0e1e988202856e1f83ce,UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
+59138911e0526dd1d8c5466b2793b6bb02c35ca9,Describing Objects via Attribute Detection,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
59bece468ed98397d54865715f40af30221aa08c,Deformable part-based robust face detection under occlusion by using face decomposition into face components,University of Zagreb,"University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia","Unska ul. 3, 10000, Zagreb, Croatia",45.80112100,15.97084090,edu,
+594cd8ed19aad3ce29d11c74d2c5fbf1a864be0c,Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+594cd8ed19aad3ce29d11c74d2c5fbf1a864be0c,Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+594cd8ed19aad3ce29d11c74d2c5fbf1a864be0c,Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+5996001b797ab2a0f55d5355cb168f25bfe56bbd,Content-Based Video Search over 1 Million Videos with 1 Core in 1 Second,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
59420fd595ae745ad62c26ae55a754b97170b01f,Objects as Attributes for Scene Classification,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
599adc0dcd4ebcc2a868feedd243b5c3c1bd1d0a,How Robust is 3D Human Pose Estimation to Occlusion?,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+59b2edf39e0490892d8865b8252bd7f11e2b2228,Face Recognition Using a Unified 3D Morphable Model,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+59b2edf39e0490892d8865b8252bd7f11e2b2228,Face Recognition Using a Unified 3D Morphable Model,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+591f04d62f44c22d1d82c9e074b066c21b420394,Learning What and Where to Draw,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+591f04d62f44c22d1d82c9e074b066c21b420394,Learning What and Where to Draw,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+59cee3d54dca04207f57b19c3d1a31402a75c3c3,L1-(2D)2PCANet: A Deep Learning Network for Face Recognition,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
5922e26c9eaaee92d1d70eae36275bb226ecdb2e,Boosting Classification Based Similarity Learning by using Standard Distances,Universitat de València,Universitat de València,"Campus dels Tarongers, Plaza de Manuel Broseta i Pont, Ciutat Jardí, Algirós, València, Comarca de València, València / Valencia, Comunitat Valenciana, 46022, España",39.47787665,-0.34257711,edu,
+596e414872debe1441b5e40216febe8788df9b35,Spatiotemporal dynamics of similarity-based neural representations of facial identity.,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+59948ee0f334ccdc4e94e5bb6a7a019c764e1815,Deployment of Practical Methods for Counting Bicycle and Pedestrian Use of a Transportation Facility,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+59d10820e0a04d2d1acc43bb18a76c52e9946721,Attention to eyes and mouth in high-functioning children with autism.,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
+59d10820e0a04d2d1acc43bb18a76c52e9946721,Attention to eyes and mouth in high-functioning children with autism.,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
59d8fa6fd91cdb72cd0fa74c04016d79ef5a752b,The Menpo Facial Landmark Localisation Challenge: A Step Towards the Solution,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+592b108b241d2d062c3035b6a5ba827180885bb7,Research on Gradient Local Binary Patterns Method for Human Detection,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
+592bbab1e073908c75584879bc00911e7246aebf,Exploiting feature Representations Through Similarity Learning and Ranking Aggregation for Person Re-identification,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+592bbab1e073908c75584879bc00911e7246aebf,Exploiting feature Representations Through Similarity Learning and Ranking Aggregation for Person Re-identification,Universitat Autònoma de Barcelona,Universitat Autònoma de Barcelona,"Centre de Visió per Computador (CVC), Carrer de l'Albareda, Serraperera, UAB, Cerdanyola del Vallès, Vallès Occidental, BCN, CAT, 08214, España",41.50078110,2.11143663,edu,
+590739cab80ad1219143401be0d929bc2885901b,Sherlock: Modeling Structured Knowledge in Images,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
59e75aad529b8001afc7e194e21668425119b864,Membrane Nonrigid Image Registration,Drexel University,Drexel University,"Drexel University, Arch Street, Powelton Village, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.95740000,-75.19026706,edu,
+592e555ebe4bd2d821230e7074d7e9626af716b0,Open Set Adversarial Examples,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
59d45281707b85a33d6f50c6ac6b148eedd71a25,Rank Minimization across Appearance and Shape for AAM Ensemble Fitting,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+59d88030c99de99d18d16dd5ffab7c0bcf6ac58e,Collaborative Annotation of Semantic Objects in Images with Multi-granularity Supervisions,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
59319c128c8ac3c88b4ab81088efe8ae9c458e07,Effective Computer Model For Recognizing Nationality From Frontal Image,University of the Humanities,The University of the Humanities,"Хүмүүнлэгийн ухааны их сургууль, Ж.Самбуугийн гудамж, Гандан, Улаанбаатар, 975, Монгол улс",47.92189370,106.91955240,edu,
59a6c9333c941faf2540979dcfcb5d503a49b91e,Sampling Clustering,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+928ccc8c4ae415202d187a229009dd48e57871ba,Winner-Take-All Multiple Category Boosting for Multi-view Face Detection,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+928ccc8c4ae415202d187a229009dd48e57871ba,Winner-Take-All Multiple Category Boosting for Multi-view Face Detection,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+927ec8dde9eb0e3bc5bf0b1a0ae57f9cf745fd9c,Learning Discriminative Features with Multiple Granularities for Person Re-Identification,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+92b9c19da2c144257617e39bc8ace7293e710914,"Automatic Tracking, Super-Resolution and Recognition of Human Faces from Surveillance Video",Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+92d5fd4ef31cf86a650c7b01c26f0ac93304f98a,Attention-Based Natural Language Person Retrieval,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
9264b390aa00521f9bd01095ba0ba4b42bf84d7e,Displacement Template with Divide-&-Conquer Algorithm for Significantly Improving Descriptor Based Face Recognition Approaches,University of Northern British Columbia,University of Northern British Columbia,"UNBC, Campus Ring Road, College Heights, Prince George, Regional District of Fraser-Fort George, British Columbia, V2M 5K7, Canada",53.89256620,-122.81471592,edu,
9264b390aa00521f9bd01095ba0ba4b42bf84d7e,Displacement Template with Divide-&-Conquer Algorithm for Significantly Improving Descriptor Based Face Recognition Approaches,Aberystwyth University,Aberystwyth University,"Aberystwyth University, Llanbadarn Campus, Cefn Esgair, Waun Fawr, Comins Coch, Ceredigion, Wales, SY23 3JG, UK",52.41073580,-4.05295501,edu,
+92166eb883b0505040c2d61c758985e5ec051f83,Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
92be73dffd3320fe7734258961fe5a5f2a43390e,Transferring Face Verification Nets To Pain and Expression Regression,Johns Hopkins University,"Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA","3400 N Charles St, Baltimore, MD 21218, USA",39.32905300,-76.61942500,edu,
92be73dffd3320fe7734258961fe5a5f2a43390e,Transferring Face Verification Nets To Pain and Expression Regression,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+92a3d5ab3eb540a11eddf1b836c1db28640b2746,Face Recognition using 3D Facial Shape and Color Map Information: Comparison and Combination,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+928857c96ef837f43ec87135de69780f6667cc70,Reconstruction Network for Video Captioning,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+92891d260e46adeff84ec5ea0817c0b6a70c253d,Model-Based Gait Enrolment in Real-World Imagery,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
924b14a9e36d0523a267293c6d149bca83e73f3b,Development and Evaluation of a Method Employed to Identify Internal State Utilizing Eye Movement Data,Keio University,Keio University,"綱島市民の森, けつわり坂, 港北区, 横浜市, 神奈川県, 関東地方, 223-0053, 日本",35.54169690,139.63471840,edu,
924b14a9e36d0523a267293c6d149bca83e73f3b,Development and Evaluation of a Method Employed to Identify Internal State Utilizing Eye Movement Data,Keio University,Keio University,"綱島市民の森, けつわり坂, 港北区, 横浜市, 神奈川県, 関東地方, 223-0053, 日本",35.54169690,139.63471840,edu,
928b8eb47288a05611c140d02441660277a7ed54,Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
@@ -78,38 +222,118 @@ 922838dd98d599d1d229cc73896d55e7a769aa7c,Learning hierarchical representations for face verification with convolutional deep belief networks,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
922838dd98d599d1d229cc73896d55e7a769aa7c,Learning hierarchical representations for face verification with convolutional deep belief networks,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
922838dd98d599d1d229cc73896d55e7a769aa7c,Learning hierarchical representations for face verification with convolutional deep belief networks,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+92a25b281f1637d125cefefcbfc382f48f456f4c,Feature Extraction for Incomplete Data via Low-rank Tucker Decomposition,Hong Kong Baptist University,Hong Kong Baptist University,"香港浸會大學 Hong Kong Baptist University, 安明街 On Ming Street, 石門 Shek Mun, 石古壟 Shek Kwu Lung, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1132, 中国",22.38742010,114.20822220,edu,
+92a25b281f1637d125cefefcbfc382f48f456f4c,Feature Extraction for Incomplete Data via Low-rank Tucker Decomposition,Guangdong University of Technology,Guangdong University of Technology,"广东工业大学, 东风东路, 黄花岗街道, 越秀区 (Yuexiu), 广州市, 广东省, 510080, 中国",23.13538360,113.29470496,edu,
9294739e24e1929794330067b84f7eafd286e1c8,Expression Recognition Using Elastic Graph Matching,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
9294739e24e1929794330067b84f7eafd286e1c8,Expression Recognition Using Elastic Graph Matching,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+925811b9fdd6c0d901bdd63245ead6a781f38bcb,Informed Haar-Like Features Improve Pedestrian Detection,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+92de2ed3805968d6d95da4fa9c44423ef50a6a37,SegStereo: Exploiting Semantic Information for Disparity Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+9257c88484247ac19e25c34de2261d34e7a06b41,CoMaL Tracking: Tracking Points at the Object Boundaries,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+92104ae97d3b57489751528a315966c0242a6efb,Input Stage-1 : Regression Stage-2 : Contextual Copy-Pasting qi pi [ ] ... Pixel Representation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+925b634cc26a8e74c2ee8889472a77e7af37874d,Shape Models of the Human Body for Distributed Inference,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+920246280e7e70900762ddfa7c41a79ec4517350,(MP)2T: Multiple People Multiple Parts Tracker,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+92175241bd9b55b53403b9f6ffd3a6c956733490,Migration Cost Aware Task Scheduling,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+92175241bd9b55b53403b9f6ffd3a6c956733490,Migration Cost Aware Task Scheduling,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+925e907458e7621ed4390db20d170e98d155d693,Question Answering under Instructor Guidance with Memory Networks,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
923ec0da8327847910e8dd71e9d801abcbc93b08,Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-Supervised Object and Action Localization,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+92574a72c660a86a7ded738a1350851f416bec03,Scene Parsing via Dense Recurrent Neural Networks with Attentional Selection,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+92f2c4f5583f0b58799f4834bc2808ee785e27f1,Kernel-Based Clustering of Big Data,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
0c741fa0966ba3ee4fc326e919bf2f9456d0cd74,Facial Age Estimation by Learning from Label Distributions,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
0c741fa0966ba3ee4fc326e919bf2f9456d0cd74,Facial Age Estimation by Learning from Label Distributions,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
0c741fa0966ba3ee4fc326e919bf2f9456d0cd74,Facial Age Estimation by Learning from Label Distributions,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
0c435e7f49f3e1534af0829b7461deb891cf540a,Capturing Global Semantic Relationships for Facial Action Unit Recognition,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
0c435e7f49f3e1534af0829b7461deb891cf540a,Capturing Global Semantic Relationships for Facial Action Unit Recognition,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
0c435e7f49f3e1534af0829b7461deb891cf540a,Capturing Global Semantic Relationships for Facial Action Unit Recognition,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+0cd8d70a2476d91c4fd6699de0e106c94aa2d9ef,Visual Reasoning with Multi-hop Feature Modulation,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
+0c56f414251d6c9f43623ee683dc6cae3be1045a,Towards Understanding Action Recognition,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+0c56f414251d6c9f43623ee683dc6cae3be1045a,Towards Understanding Action Recognition,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
0c30f6303dc1ff6d05c7cee4f8952b74b9533928,Pareto discriminant analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
0c30f6303dc1ff6d05c7cee4f8952b74b9533928,Pareto discriminant analysis,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
0c30f6303dc1ff6d05c7cee4f8952b74b9533928,Pareto discriminant analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
0c30f6303dc1ff6d05c7cee4f8952b74b9533928,Pareto discriminant analysis,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+0cb5079c39933bd8897fde7edecf156ff57830d7,Runway to Realway: Visual Analysis of Fashion,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
0ccc535d12ad2142a8310d957cc468bbe4c63647,Better Exploiting OS-CNNs for Better Event Recognition in Images,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+0cd87a66028f9d3c519a9459a213905b42b4c3b0,Cross-Domain Forensic Shoeprint Matching,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+0cd87a66028f9d3c519a9459a213905b42b4c3b0,Cross-Domain Forensic Shoeprint Matching,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+0cd87a66028f9d3c519a9459a213905b42b4c3b0,Cross-Domain Forensic Shoeprint Matching,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
0c79a39a870d9b56dc00d5252d2a1bfeb4c295f1,Face Recognition in Videos by Label Propagation,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
0cdb49142f742f5edb293eb9261f8243aee36e12,Combined Learning of Salient Local Descriptors and Distance Metrics for Image Set Face Verification,"CSIRO, Australia","NICTA, PO Box 6020, St Lucia, QLD 4067, Australia","Research Way, Clayton VIC 3168, Australia",-37.90627370,145.13194490,edu,f.k.a. NICTA
0cdb49142f742f5edb293eb9261f8243aee36e12,Combined Learning of Salient Local Descriptors and Distance Metrics for Image Set Face Verification,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+0c6eff59e210c3af9865207302199412f3f91914,Parsing human motion with stretchable models,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+0cfab1c2839ddacc19bc9af2e821d5c5fd4f28c1,3D Pictorial Structures for Multiple Human Pose Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+0c2de1b4fe7c5da8adf6351533a9c39503ad7a4c,Deeply-Fused Nets,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+0c2de1b4fe7c5da8adf6351533a9c39503ad7a4c,Deeply-Fused Nets,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+0c8ac71e174a941ea7e14e7b503a12ae7eeca9db,Visual Semantic Complex Network for Web Images,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+0c8ac71e174a941ea7e14e7b503a12ae7eeca9db,Visual Semantic Complex Network for Web Images,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
0cf2eecf20cfbcb7f153713479e3206670ea0e9c,Privacy-Protective-GAN for Face De-identification,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+0cba3c4ec4c1dd85b637a078b9c05244196009e9,Automatic Expansion of a Food Image Dataset Leveraging Existing Categories with Domain Adaptation,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+0cd736baf31dceea1cc39ac72e00b65587f5fb9e,Learning Hash Functions Using Column Generation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+0c2d0734a2c9d3e4d8a585b3f2ad4f642bf06dea,Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+0cf4105ec11fb5846e5ea1b9dea11f8ba16e391f,Strokelets: A Learned Multi-scale Representation for Scene Text Recognition,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
0c1d85a197a1f5b7376652a485523e616a406273,Joint Registration and Representation Learning for Unconstrained Face Identification,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
0c1d85a197a1f5b7376652a485523e616a406273,Joint Registration and Representation Learning for Unconstrained Face Identification,Khalifa University,Khalifa University,"Khalifa University, شارع طَوِي مُوَيلِح, قصر الشاطئ, حدبة الزَّعْفرانة, أبوظبي, أبو ظبي, 31757, الإمارات العربية المتحدة",24.44690250,54.39425630,edu,
+0ca2f48fad7f69fb415ecbb99945250cbf8f011c,Outliers Cleaning in Dynamic Systems,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+0ca2f48fad7f69fb415ecbb99945250cbf8f011c,Outliers Cleaning in Dynamic Systems,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
0ca66283f4fb7dbc682f789fcf6d6732006befd5,Active Dictionary Learning for Image Representation,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+0c07b1faeb4c63c603bcd124640c6ffe07df801c,Unsupervised Selection of Negative Examples for Grounded Language Learning,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+0c9f715835bee028a358701cf5a73ecbc3a7e242,Semi-supervised Facial Expression Recognition Algorithm on The Condition of Multi-pose,Beijing University of Technology,Beijing University of Technology,"北京工业大学, 银杏大道, 大郊亭村, 朝阳区 / Chaoyang, 北京市, 3208, 中国",39.87391435,116.47722285,edu,
+0c1531a2fa4d6a270b9a09cde86bb0669f5975ff,Processing of Crawled Urban Imagery for Building Use Classification,University of Stuttgart,University of Stuttgart,"Pädagogische Hochschule Ludwigsburg, 46, Reuteallee, Ludwigsburg-Nord, Ludwigsburg, Landkreis Ludwigsburg, Regierungsbezirk Stuttgart, Baden-Württemberg, 71634, Deutschland",48.90953380,9.18318920,edu,
0c7f27d23a162d4f3896325d147f412c40160b52,Models and Algorithms for Vision through the Atmosphere,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+0ca35af582b95fbab3829f98308d104359c3b632,Recognizing objects by piecing together the Segmentation Puzzle,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+0c75db5e3c27bcb0d07311a950d0d25cb57c731e,Neural conditional ordinal random fields for agreement level estimation,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+0c75db5e3c27bcb0d07311a950d0d25cb57c731e,Neural conditional ordinal random fields for agreement level estimation,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+0cebf440622050f8149d14b803a969917348844b,Learning to Search Efficiently in High Dimensions,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
0c20fd90d867fe1be2459223a3cb1a69fa3d44bf,A Monte Carlo Strategy to Integrate Detection and Model-Based Face Analysis,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+0c553e57cb6fe7bdf3212fbf86bcc869958db27f,Straight until proven gay: A systematic bias toward straight categorizations in sexual orientation judgments.,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+0c553e57cb6fe7bdf3212fbf86bcc869958db27f,Straight until proven gay: A systematic bias toward straight categorizations in sexual orientation judgments.,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+0c553e57cb6fe7bdf3212fbf86bcc869958db27f,Straight until proven gay: A systematic bias toward straight categorizations in sexual orientation judgments.,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
0c2875bb47db3698dbbb3304aca47066978897a4,Recurrent Models for Situation Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0c6fa98b7b99d807df7c027e8e97751f1bbb9140,Data programming with DDLite: putting humans in a different part of the loop,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+0c663a7224a60488502a937ed3bc2b869260b6c0,Activity Auto-Completion: Predicting Human Activities from Partial Videos,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0c663a7224a60488502a937ed3bc2b869260b6c0,Activity Auto-Completion: Predicting Human Activities from Partial Videos,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+0c663a7224a60488502a937ed3bc2b869260b6c0,Activity Auto-Completion: Predicting Human Activities from Partial Videos,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
0cbc4dcf2aa76191bbf641358d6cecf38f644325,Visage: A Face Interpretation Engine for Smartphone Applications,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+0c7aac75ccd17d696cff2e1ce95db0493f5c18a2,VideoMatch: Matching Based Video Object Segmentation,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0cbbbfac2fe925479c6b34712e056f840a10fa4d,Quality Evaluation Methods for Crowdsourced Image Segmentation,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0cbbbfac2fe925479c6b34712e056f840a10fa4d,Quality Evaluation Methods for Crowdsourced Image Segmentation,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
+0cbbbfac2fe925479c6b34712e056f840a10fa4d,Quality Evaluation Methods for Crowdsourced Image Segmentation,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
0ce8a45a77e797e9d52604c29f4c1e227f604080,Zernike Moment-based Feature Extraction for Facial Recognition of Identical Twins,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
0ce3a786aed896d128f5efdf78733cc675970854,Learning the Face Prior for Bayesian Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+0c7844b63a05ec086fba231ad9eb3114ffb4139e,Automated Facial Trait Judgment and Election Outcome Prediction: Social Dimensions of Face,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+0c7844b63a05ec086fba231ad9eb3114ffb4139e,Automated Facial Trait Judgment and Election Outcome Prediction: Social Dimensions of Face,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+0c7844b63a05ec086fba231ad9eb3114ffb4139e,Automated Facial Trait Judgment and Election Outcome Prediction: Social Dimensions of Face,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
+0c882588ed7436f7122af2b324c598adbede49c1,Random mesh projectors for inverse problems,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0c882588ed7436f7122af2b324c598adbede49c1,Random mesh projectors for inverse problems,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0c882588ed7436f7122af2b324c598adbede49c1,Random mesh projectors for inverse problems,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
+0c882588ed7436f7122af2b324c598adbede49c1,Random mesh projectors for inverse problems,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0c8769bf0501fdd7fbc94ca81601de4a40679295,On Duality Of Multiple Target Tracking and Segmentation,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+0cc5804c5f113c60ee5894f25ab7078364eef986,Epitomize Your Photos,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+0c5f74c8e323861d18d6090d8cce05dde22660d0,Enhancing Person Re-identification by Robust Structural Metric Learning,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
0c59071ddd33849bd431165bc2d21bbe165a81e0,Person Recognition in Personal Photo Collections,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
0c12cbb9b9740dfa2816b8e5cde69c2f5a715c58,Memory-Augmented Attribute Manipulation Networks for Interactive Fashion Search,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
0c12cbb9b9740dfa2816b8e5cde69c2f5a715c58,Memory-Augmented Attribute Manipulation Networks for Interactive Fashion Search,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+0ce08f1cc6684495d12c2da157a056c7b88ffcd9,Multi-Modality Feature Transform: An Interactive Image Segmentation Approach,Alexandria University,Alexandria University,"جامعة الإسكندرية, الكورنيش, إبراهيمية, الإسكندرية, 21522, مصر",31.21051105,29.91314562,edu,
+0cd7ff53729dafe9175009d7f04570dbbf41a608,Modelling the Effect of View Angle Variation on Appearance-Based Gait Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0c4d99f49654fe04a8e229a20a6e0e0f0d81337b,Multi-Scale Human Pose Tracking in 2D Monocular Images,Curtin University,Curtin University,"Curtin University, Brand Drive, Waterford, Perth, Western Australia, 6102, Australia",-32.00686365,115.89691775,edu,
+0c5b03a6083950aacd9aee2d276a232e6ce3213c,The Main Memory System: Challenges and Opportunities,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0c5b03a6083950aacd9aee2d276a232e6ce3213c,The Main Memory System: Challenges and Opportunities,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0c5b03a6083950aacd9aee2d276a232e6ce3213c,The Main Memory System: Challenges and Opportunities,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0c5b03a6083950aacd9aee2d276a232e6ce3213c,The Main Memory System: Challenges and Opportunities,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0c124734ce6015bd4c506b101038aebc1412da49,Human Face Reconstruction Using Bayesian Deformable Models,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+0c678d593cec6ff51c18bde3847fffbf58a66282,"TOTAL BREGMAN DIVERGENCE, A ROBUST DIVERGENCE MEASURE, AND ITS APPLICATIONS By MEIZHU LIU A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY",University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
0c6e29d82a5a080dc1db9eeabbd7d1529e78a3dc,Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0c940ccba1bd9380a0ac723d791777fc1746a060,Scheduling for HPC Systems with Process Variation Heterogeneity,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0c61d6a33b9d3c190b4adc15658cfe969dedfbdf,Self-supervised Learning of Motion Capture,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0c61d6a33b9d3c190b4adc15658cfe969dedfbdf,Self-supervised Learning of Motion Capture,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+0c6602439185ad8268ebcd99d1ac4afd66fb4c7b,"Learning Robust, Transferable Sentence Representations for Text Classification","University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+0c0dc5c307483642e15283d0d52a4159483d3df6,Multicamera Video Summarization from Optimal Reconstruction,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
+0cbc3221a07db517c30b9d6605cbe9d103e19955,How Smart Does Your Profile Image Look?: Estimating Intelligence from Social Network Profile Images,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+0cbc3221a07db517c30b9d6605cbe9d103e19955,How Smart Does Your Profile Image Look?: Estimating Intelligence from Social Network Profile Images,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
0c05f60998628884a9ac60116453f1a91bcd9dda,Optimizing Open-Ended Crowdsourcing: The Next Frontier in Crowdsourced Data Management,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0c0f353dbac84311ea4f1485d4a8ac0b0459be8c,Nexus : A GPU Cluster for Accelerating Neural Networks for Video Analysis,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+66284b8894bab0165c4210cd2df749f0b015c88e,Semi-Supervised Ranking for Re-identification with Few Labeled Image Pairs,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+663cca096b98c8f0444608b188e464028ee34368,CASENet: Deep Category-Aware Semantic Edge Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+66ef0364f2e865c35ce5003e129ba6fc57a2afa4,Semantic Segmentation Using Multiple Graphs with Block-Diagonal Constraints,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
66aad5b42b7dda077a492e5b2c7837a2a808c2fa,A Novel PCA-Based Bayes Classifier and Face Analysis,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
66b9d954dd8204c3a970d86d91dd4ea0eb12db47,Evaluation of Gabor-Wavelet-Based Facial Action Unit Recognition in Image Sequences of Increasing Complexity,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
66b9d954dd8204c3a970d86d91dd4ea0eb12db47,Evaluation of Gabor-Wavelet-Based Facial Action Unit Recognition in Image Sequences of Increasing Complexity,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
@@ -117,38 +341,174 @@ 66dcd855a6772d2731b45cfdd75f084327b055c2,Quality Classified Image Analysis with Application to Face Detection and Recognition,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
666939690c564641b864eed0d60a410b31e49f80,What Visual Attributes Characterize an Object Class?,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
66330846a03dcc10f36b6db9adf3b4d32e7a3127,Polylingual Multimodal Learning,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+66cd8e7338b20999786343651658520ca9544006,Pedestrian detection aided by deep learning semantic tasks,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
666300af8ffb8c903223f32f1fcc5c4674e2430b,Changing Fashion Cultures,Tokyo Denki University,Tokyo Denki University,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
66029f1be1a5cee9a4e3e24ed8fcb65d5d293720,HWANG AND GRAUMAN: ACCOUNTING FOR IMPORTANCE IN IMAGE RETRIEVAL 1 Accounting for the Relative Importance of Objects in Image Retrieval,University of Texas,The University of Texas,"The University of Texas at Tyler, 3900, University Boulevard, Tyler, Smith County, Texas, 75799, USA",32.31630780,-95.25369944,edu,
+669b9fd79eb39f712527ee616e35e50eea7fd2fa,Human Pose Estimation Using Body Parts Dependent Joint Regressors,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
6691dfa1a83a04fdc0177d8d70e3df79f606b10f,Illumination Modeling and Normalization for Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+66fb1e7a65abbfa171a3fd92dc67006490df7450,Design of Continuous Authentication using Face Recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+665265289471d08a4b472329eb42965b51ac485a,Fairness GAN,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+6625349c4705d25844ab6eb019e5962b012e9256,Identifying Emotions Using Topographic Conditioning Maps,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+665f0763ad7f320cb59fcb6a745906d3d6799d99,Deep Multitask Gaze Estimation with a Constrained Landmark-Gaze Model,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+66652367a369d18e1845dd14220dc94a9748c9fd,Learning Spatial Regularization with Image-Level Supervisions for Multi-label Image Classification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+66652367a369d18e1845dd14220dc94a9748c9fd,Learning Spatial Regularization with Image-Level Supervisions for Multi-label Image Classification,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+66652367a369d18e1845dd14220dc94a9748c9fd,Learning Spatial Regularization with Image-Level Supervisions for Multi-label Image Classification,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+66a4a03ea58792e4be90b20c60ddc65de736537e,Learning auxiliary dictionaries for undersampled face recognition,"Academia Sinica, Taiwan","Research Center for Institute of Information Science, Academia Sinica, Taiwan","115, Taiwan, Taipei City, Nangang District, 研究院路二段128號",25.04117270,121.61465180,edu,
+669ddd0b5f742876fe84cfb3dd7ff30bcaab52be,Learning image similarities via Probabilistic Feature Matching,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+66cc90ea586c914e6a3b50fe703f4379d530fad7,Automatic integration of social information in emotion recognition.,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+668d39ceb83d06c61ab58cb689a1b744ff520669,Fast Video Classification via Adaptive Cascading of Deep Models,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+66c84abd01fdd84d9cd241dea8e487580f4f8922,Bridging Languages through Images with Deep Partial Canonical Correlation Analysis,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+66c84abd01fdd84d9cd241dea8e487580f4f8922,Bridging Languages through Images with Deep Partial Canonical Correlation Analysis,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+66986f4359c3507d671bad021d6fb2d6fa6aa2c0,Appearance Sharing for Collective Human Pose Estimation,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
66f02fbcad13c6ee5b421be2fc72485aaaf6fcb5,"Using Co-Captured Face, Gaze and Verbal Reactions to Images of Using Co-Captured Face, Gaze and Verbal Reactions to Images of",Muhlenberg College,Muhlenberg College,"Muhlenberg College, 2400, West Chew Street, Rose Garden, Allentown, Lehigh County, Pennsylvania, 18104, USA",40.59676370,-75.51240620,edu,
66f02fbcad13c6ee5b421be2fc72485aaaf6fcb5,"Using Co-Captured Face, Gaze and Verbal Reactions to Images of Using Co-Captured Face, Gaze and Verbal Reactions to Images of",Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
66f02fbcad13c6ee5b421be2fc72485aaaf6fcb5,"Using Co-Captured Face, Gaze and Verbal Reactions to Images of Using Co-Captured Face, Gaze and Verbal Reactions to Images of",Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+6681ec516067747a4576f737f10f8d9bbca2d8d1,Perturbative Neural Networks ( Supplementary Material ),Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6681ec516067747a4576f737f10f8d9bbca2d8d1,Perturbative Neural Networks ( Supplementary Material ),Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+6681ec516067747a4576f737f10f8d9bbca2d8d1,Perturbative Neural Networks ( Supplementary Material ),Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6604fd47f92ce66dd0c669dd66b347b80e17ebc9,Simultaneous Cascaded Regression,Institute of Systems and Robotics,Institute of Systems and Robotics,"Institut für Robotik und Kognitive Systeme, 160, Ratzeburger Allee, Strecknitz, Sankt Jürgen, Strecknitz, Lübeck, Schleswig-Holstein, 23562, Deutschland",53.83383710,10.70359390,edu,
66e9fb4c2860eb4a15f713096020962553696e12,A New Urban Objects Detection Framework Using Weakly Annotated Sets,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+666aa18ed45a0a92959d91d0f9a4c928aceb1450,Material : Modelling and unsupervised learning of symmetric deformable object categories,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+666aa18ed45a0a92959d91d0f9a4c928aceb1450,Material : Modelling and unsupervised learning of symmetric deformable object categories,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+66080593dc4ea2347d4ff8c10e4b4dedf0d16ad2,Improving biometric identification through quality-based face and fingerprint biometric fusion,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+663981cfc5fc843ec2682b77ae427ac351bc2180,Detecting Repeating Objects Using Patch Correlation Analysis,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
3e69ed088f588f6ecb30969bc6e4dbfacb35133e,Improving Performance of Texture Based Face Recognition Systems by Segmenting Face Region,Manonmaniam Sundaranar University,Manonmaniam Sundaranar University,"Manonmaniam Sundaranar University, Tenkasi-Tirunelveli, Gandhi Nagar, Tirunelveli, Tirunelveli Kattabo, Tamil Nadu, 627808, India",8.76554685,77.65100445,edu,
+3e56cbce67d312af2b3a7d0981e9cb33d2236bea,Boosting attribute recognition with latent topics by matrix factorization,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+3e56cbce67d312af2b3a7d0981e9cb33d2236bea,Boosting attribute recognition with latent topics by matrix factorization,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+3e56cbce67d312af2b3a7d0981e9cb33d2236bea,Boosting attribute recognition with latent topics by matrix factorization,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+3e56cbce67d312af2b3a7d0981e9cb33d2236bea,Boosting attribute recognition with latent topics by matrix factorization,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
3e0a1884448bfd7f416c6a45dfcdfc9f2e617268,Understanding and Controlling User Linkability in Decentralized Learning,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+3efb04a9847284680b48214855eb0a962efa5c7b,De-identification for Privacy Protection in Surveillance Videos,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+3e211a93388dcf29dda4cd6d3d515042f2cffee7,Breaking the Chain: Liberation from the Temporal Markov Assumption for Tracking Human Poses,Oak Ridge National Laboratory,Oak Ridge National Laboratory,"Oak Ridge National Laboratory, Oak Ridge, Roane County, Tennessee, USA",35.93006535,-84.31240032,edu,
+3e211a93388dcf29dda4cd6d3d515042f2cffee7,Breaking the Chain: Liberation from the Temporal Markov Assumption for Tracking Human Poses,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
3ebce6710135d1f9b652815e59323858a7c60025,Component-based Face Detection,University of Siena,University of Siena,"大學 University, 澤祥街 Chak Cheung Street, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.41338620,114.21005800,edu,
+3e2ec9cea926bd02072aa41bd81eb4c593e205e9,Adversarial Information Factorization,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+3e2ec9cea926bd02072aa41bd81eb4c593e205e9,Adversarial Information Factorization,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+3e2ec9cea926bd02072aa41bd81eb4c593e205e9,Adversarial Information Factorization,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+3eb5f1d466228c1345d92f906ab31ab93c160837,Single-Pedestrian Detection Aided by Multi-pedestrian Detection,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+3eb5f1d466228c1345d92f906ab31ab93c160837,Single-Pedestrian Detection Aided by Multi-pedestrian Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+3ef997bf6306d157c062f0744ea0d8ce8f390e2a,Visual Choice of Plausible Alternatives: An Evaluation of Image-based Commonsense Causal Reasoning,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+3ef997bf6306d157c062f0744ea0d8ce8f390e2a,Visual Choice of Plausible Alternatives: An Evaluation of Image-based Commonsense Causal Reasoning,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+3ef997bf6306d157c062f0744ea0d8ce8f390e2a,Visual Choice of Plausible Alternatives: An Evaluation of Image-based Commonsense Causal Reasoning,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+3e2e9ac490726c37a0797792dd2aa9d20404b9b0,Learning Invariant Riemannian Geometric Representations Using Deep Nets,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+3e2e9ac490726c37a0797792dd2aa9d20404b9b0,Learning Invariant Riemannian Geometric Representations Using Deep Nets,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+3ec653164169c1a1b5c12ece2130326606a24e6c,A Phase Discrepancy Analysis of Object Motion,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+3ec653164169c1a1b5c12ece2130326606a24e6c,A Phase Discrepancy Analysis of Object Motion,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+3ec653164169c1a1b5c12ece2130326606a24e6c,A Phase Discrepancy Analysis of Object Motion,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+3eca8ed3164324698d0171e62dec24e8abda9e26,Human emotion recognition using real 3D visual features from Gabor library,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
+3e4bd67a10e291ad6d5614a6e97efb69b2dd051a,Learning Spatio-temporal Features with Partial Expression Sequences for on-the-Fly Prediction,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
+3e42e336d67dad79ab6355c02f1f045f8a71a18f,Autism spectrum traits in normal individuals: a preliminary VBM analysis,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+3e42e336d67dad79ab6355c02f1f045f8a71a18f,Autism spectrum traits in normal individuals: a preliminary VBM analysis,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+3e98719cc0b570c7a0c7c903efb010075dd267e7,Real Time Person Tracking and Behavior Interpretation in Multi Camera Scenarios Applying Homography and Coupled HMMs,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+3ed9730e5ec8716e8cdf55f207ef973a9c854574,Visual Compiler: Synthesizing a Scene-Specific Pedestrian Detector and Pose Estimator,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3ed81d552fb33fe64c766407570f3d8b062fb292,Data-Driven Edge Computing Resource Scheduling for Protest Crowds Incident Management,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+3ed81d552fb33fe64c766407570f3d8b062fb292,Data-Driven Edge Computing Resource Scheduling for Protest Crowds Incident Management,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+3e90a70d768415e28fbf0dd56e53f8933784c416,Highly Efficient Regression for Scalable Person Re-Identification,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+3eb298bfcc33f6e40bfd2e8788b13b256d2c0391,Towards Unified Human Parsing and Pose Estimation,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+3e421fd1775413bf89abd8e39a35e5e29d1a4dab,Addressing bias in machine learning algorithms: A pilot study on emotion recognition for intelligent systems,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+3e421fd1775413bf89abd8e39a35e5e29d1a4dab,Addressing bias in machine learning algorithms: A pilot study on emotion recognition for intelligent systems,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+3e58fbb8cb96880e018ca18a60e2d86e3cb0c10a,Generative Partition Networks for Multi-Person Pose Estimation,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+3e58fbb8cb96880e018ca18a60e2d86e3cb0c10a,Generative Partition Networks for Multi-Person Pose Estimation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+3ec77809aaa7bd30858a4274e3c28a2a0259b30c,Latent trees for estimating intensity of Facial Action Units,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+3ec77809aaa7bd30858a4274e3c28a2a0259b30c,Latent trees for estimating intensity of Facial Action Units,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+3ec77809aaa7bd30858a4274e3c28a2a0259b30c,Latent trees for estimating intensity of Facial Action Units,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+3ed2ebfd783298a9a2e412529ffabdeb98bd552d,Modelling of Orthogonal Craniofacial Profiles,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+3e7ffb5658cf99968633ede18785c5cfdd6aa9eb,Semi-Supervised Deep Learning for Monocular Depth Map Prediction,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+3e03435792619833d4e2aa14344761b003c10c67,A Simultaneously Calibration Approach for Installation and Attitude Errors of an INS/GPS/LDS Target Tracker,Harbin Engineering University,Harbin Engineering University,"哈尔滨工程大学, 文庙街 - Wenmiao Street, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.77445695,126.67684917,edu,
+3e03435792619833d4e2aa14344761b003c10c67,A Simultaneously Calibration Approach for Installation and Attitude Errors of an INS/GPS/LDS Target Tracker,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+3eda9f9c29cec4f44e210d40b54810de525d75fb,"Image Annotation Incorporating Low-Rankness, Tag and Visual Correlation and Inhomogeneous Errors",Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
3e51d634faacf58e7903750f17111d0d172a0bf1,A compressible template protection scheme for face recognition based on sparse representation,Tokyo Metropolitan University,Tokyo Metropolitan University,"首都大学東京, 由木緑道, 八王子市, 東京都, 関東地方, 1920364, 日本",35.62009250,139.38296706,edu,
+3ebbacf0bfe95781e70ee37085bb2addf30a40a7,Scalable Vision System for Mouse Homecage Ethology,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+3ebbacf0bfe95781e70ee37085bb2addf30a40a7,Scalable Vision System for Mouse Homecage Ethology,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
3e40991ab1daa2a4906eb85a5d6a01a958b6e674,LipNet: End-to-End Sentence-level Lipreading,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3eadf02a7ac57a2a0cc794180bf0b46b45a9e0a2,Discriminant Mutual Subspace Learning for Indoor and Outdoor Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+3eadf02a7ac57a2a0cc794180bf0b46b45a9e0a2,Discriminant Mutual Subspace Learning for Indoor and Outdoor Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+3eadf02a7ac57a2a0cc794180bf0b46b45a9e0a2,Discriminant Mutual Subspace Learning for Indoor and Outdoor Face Recognition,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+3ed60f021fe469f2423d04917e69864251d23e08,Metadata of the chapter that will be visualized in SpringerLink,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+3e78402eab72d87eda1f0b44ca7ff54ba0b6b914,Hierarchical object groups for scene classification,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
3e3a87eb24628ab075a3d2bde3abfd185591aa4c,Effects of sparseness and randomness of pairwise distance matrix on t-SNE results,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+3ea0bc7cd58d4214d4ed20e8acfa76054f73654d,Recycled linear classifiers for multiclass classification,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+3e76496aa3840bca2974d6d087bfa4267a390768,Dictionary Learning in Optimal Metric Subspace,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+3e76496aa3840bca2974d6d087bfa4267a390768,Dictionary Learning in Optimal Metric Subspace,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+3e682d368422ff31632760611039372a07eeabc6,Articulated Multi-person Tracking in the Wild,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
3e207c05f438a8cef7dd30b62d9e2c997ddc0d3f,Objects as context for detecting their semantic parts,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+5017d635ba8dd630fc0375bfa71cf2a3397fae8d,Multiset Feature Learning for Highly Imbalanced Data Classification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+5017d635ba8dd630fc0375bfa71cf2a3397fae8d,Multiset Feature Learning for Highly Imbalanced Data Classification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+5017d635ba8dd630fc0375bfa71cf2a3397fae8d,Multiset Feature Learning for Highly Imbalanced Data Classification,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+5017d635ba8dd630fc0375bfa71cf2a3397fae8d,Multiset Feature Learning for Highly Imbalanced Data Classification,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
5040f7f261872a30eec88788f98326395a44db03,Generalised Scalable Robust Principal Component Analysis,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+505ea4493e4b733352c921401a96d92b4e6d4448,Coupled Discriminative Feature Learning for Heterogeneous Face Recognition,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+505ea4493e4b733352c921401a96d92b4e6d4448,Coupled Discriminative Feature Learning for Heterogeneous Face Recognition,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
500fbe18afd44312738cab91b4689c12b4e0eeee,ChaLearn looking at people 2015 new competitions: Age estimation and cultural event recognition,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
500fbe18afd44312738cab91b4689c12b4e0eeee,ChaLearn looking at people 2015 new competitions: Age estimation and cultural event recognition,Universitat Oberta de Catalunya,Universitat Oberta de Catalunya,"Universitat Oberta de Catalunya, 156, Rambla del Poblenou, Provençals del Poblenou, Sant Martí, Barcelona, BCN, CAT, 08018, España",41.40657415,2.19453410,edu,
500fbe18afd44312738cab91b4689c12b4e0eeee,ChaLearn looking at people 2015 new competitions: Age estimation and cultural event recognition,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
500fbe18afd44312738cab91b4689c12b4e0eeee,ChaLearn looking at people 2015 new competitions: Age estimation and cultural event recognition,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
500fbe18afd44312738cab91b4689c12b4e0eeee,ChaLearn looking at people 2015 new competitions: Age estimation and cultural event recognition,University of Venezia,University of Venezia,"University, Fondamenta Toffetti, Dorsoduro, Venezia-Murano-Burano, Venezia, VE, VEN, 30123, Italia",45.43127420,12.32653770,edu,
+50c4ece0f07f2fbc3cf2fef98df24aeea0145899,Pedestrian Counting with Occlusion Handling Using Stereo Thermal Cameras,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
506c2fbfa9d16037d50d650547ad3366bb1e1cde,Convolutional Channel Features : Tailoring CNN to Diverse Tasks,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+50137d663802224e683951c48970496b38b02141,DETRAC: A New Benchmark and Protocol for Multi-Object Tracking,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
504028218290d68859f45ec686f435f473aa326c,Multi-Fiber Networks for Video Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+50e5aac9037380108099c09ac53f8cc3f1b31bf3,Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+50e5aac9037380108099c09ac53f8cc3f1b31bf3,Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+50e5aac9037380108099c09ac53f8cc3f1b31bf3,Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
+50e5aac9037380108099c09ac53f8cc3f1b31bf3,Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+50a8dc4c1d40967a95b684eb421edd03415fb7ab,Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+50a8dc4c1d40967a95b684eb421edd03415fb7ab,Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+50a8dc4c1d40967a95b684eb421edd03415fb7ab,Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+509be79bd94d56ef7cd1af54e2be88983805bbe9,Thread Progress Equalization: Dynamically Adaptive Power-Constrained Performance Optimization of Multi-Threaded Applications,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+509be79bd94d56ef7cd1af54e2be88983805bbe9,Thread Progress Equalization: Dynamically Adaptive Power-Constrained Performance Optimization of Multi-Threaded Applications,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+509be79bd94d56ef7cd1af54e2be88983805bbe9,Thread Progress Equalization: Dynamically Adaptive Power-Constrained Performance Optimization of Multi-Threaded Applications,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+50399793a5334654dedcea635cad291dda77de96,Humanising GrabCut: Learning to segment humans using the Kinect,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+508d5e0ef6cbce1997d968c5d4534a7baba84948,Multi-view Pictorial Structures for 3D Human Pose Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+50b58becaf67e92a6d9633e0eea7d352157377c3,Dependency-Aware Attention Control for Unconstrained Face Recognition with Image Sets,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+50d1021392b6b226cb6a022b69b55396dfec99fa,Leveraging single for multi-target tracking using a novel trajectory overlap affinity measure,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
+50fc40ec6166dc33c6e59ef5dd75230651076f44,Efficient feature selection for linear discriminant analysis and its application to face recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+50131e57e14eafd385d94fb31e63f86a5bab9b9f,Detection and Segmentation of Brain Metastases with Deep Convolutional Networks,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+50ed931266a22bc166afef38f4b217fe9b4d5d74,Efficient eye typing with 9-direction gaze estimation,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+504c1cc2ddea7db0f684269be3df05e9e95b6e2c,"Automatic 3D Face Detection, Normalization and Recognition",University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
5050807e90a925120cbc3a9cd13431b98965f4b9,Unsupervised Learning of Discriminative Relative Visual Attributes,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
5050807e90a925120cbc3a9cd13431b98965f4b9,Unsupervised Learning of Discriminative Relative Visual Attributes,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
+50894e607cd5eb616913b520c4e238a73f432b86,Neural correlates of eye gaze processing in the infant broader autism phenotype.,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
508702ed2bf7d1b0655ea7857dd8e52d6537e765,Saliency-Informed Spatio-Temporal Vector of Locally Aggregated Descriptors and Fisher Vectors for Visual Action Recognition,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+5061f591aa8ff224cd20cdcb3b62d156fb187bed,One Model To Learn Them All,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
50e45e9c55c9e79aaae43aff7d9e2f079a2d787b,Unbiased Feature Selection in Learning Random Forests for High-Dimensional Data,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
50e45e9c55c9e79aaae43aff7d9e2f079a2d787b,Unbiased Feature Selection in Learning Random Forests for High-Dimensional Data,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
50e45e9c55c9e79aaae43aff7d9e2f079a2d787b,Unbiased Feature Selection in Learning Random Forests for High-Dimensional Data,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
50e45e9c55c9e79aaae43aff7d9e2f079a2d787b,Unbiased Feature Selection in Learning Random Forests for High-Dimensional Data,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
5003754070f3a87ab94a2abb077c899fcaf936a6,Evaluation of LC - KSVD on UCF 101 Action Dataset,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+50af3b6f7192951b42c2531ee931c8244e505a5c,Weakly Supervised Learning for Attribute Localization in Outdoor Scenes,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+504002dbd2de78f8d55c860a76a6ee322eb816a8,3D Pose from Motion for Cross-View Action Recognition via Non-linear Circulant Temporal Encoding,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+5047cae1b6f47ac1715479abfa3daf1c1a063977,Predictor Combination at Test Time — Supplemental Document,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+5047cae1b6f47ac1715479abfa3daf1c1a063977,Predictor Combination at Test Time — Supplemental Document,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+5047cae1b6f47ac1715479abfa3daf1c1a063977,Predictor Combination at Test Time — Supplemental Document,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
503db524b9a99220d430e741c44cd9c91ce1ddf8,"Who's Better, Who's Best: Skill Determination in Video using Deep Ranking",University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+50953b9a15aca6ef3351e613e7215abdcae1435e,Learning coarse-to-fine sparselets for efficient object detection and scene classification,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+5060e2e7d94e002a5376f4edfd2e48ac01d6221f,"Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures",University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+5060e2e7d94e002a5376f4edfd2e48ac01d6221f,"Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures",Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+5060e2e7d94e002a5376f4edfd2e48ac01d6221f,"Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+5060e2e7d94e002a5376f4edfd2e48ac01d6221f,"Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures",Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
+5060e2e7d94e002a5376f4edfd2e48ac01d6221f,"Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures",University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+5060e2e7d94e002a5376f4edfd2e48ac01d6221f,"Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures",University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
+5060e2e7d94e002a5376f4edfd2e48ac01d6221f,"Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures",University of Copenhagen,University of Copenhagen,"Københavns Universitet, Krystalgade, Kødbyen, Vesterbro, København, Københavns Kommune, Region Hovedstaden, 1165, Danmark",55.68015020,12.57232700,edu,
+501bfe67683ddfecf3710f5946c3b77f1ffe9adf,Pillar Networks++: Distributed non-parametric deep and wide networks,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+50797bf1a167ba294f640d3ae237cee962427cf0,Harry Potter's Marauder's Map: Localizing and Tracking Multiple Persons-of-Interest by Nonnegative Discretization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+50bf4f77d8b66ec838ad59a869630eace7e0e4a7,Deeply-Learned Part-Aligned Representations for Person Re-identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+50bf4f77d8b66ec838ad59a869630eace7e0e4a7,Deeply-Learned Part-Aligned Representations for Person Re-identification,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+50d80e2020698b4cf49e6b820df0aea497d8fdd3,Charades-Ego: A Large-Scale Dataset of Paired Third and First Person Videos,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+50d2fa4e3a4e961cf35cef6d11ea745f9d1b3839,Spotlight the Negatives: A Generalized Discriminative Latent Model,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+500c096c3be8c6dc084cdbf1b24288926b2dfefc,Using Psychophysical Methods to Understand Mechanisms of Face Identification in a Deep Neural Network,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+500c096c3be8c6dc084cdbf1b24288926b2dfefc,Using Psychophysical Methods to Understand Mechanisms of Face Identification in a Deep Neural Network,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+500c096c3be8c6dc084cdbf1b24288926b2dfefc,Using Psychophysical Methods to Understand Mechanisms of Face Identification in a Deep Neural Network,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+500c096c3be8c6dc084cdbf1b24288926b2dfefc,Using Psychophysical Methods to Understand Mechanisms of Face Identification in a Deep Neural Network,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+500c096c3be8c6dc084cdbf1b24288926b2dfefc,Using Psychophysical Methods to Understand Mechanisms of Face Identification in a Deep Neural Network,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+50bf19a06915778a0bcbdef700f91b56258a4e1f,Common and distinct neural features of social and non-social reward processing in autism and social anxiety disorder.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+50bf19a06915778a0bcbdef700f91b56258a4e1f,Common and distinct neural features of social and non-social reward processing in autism and social anxiety disorder.,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+507af6591900a7165c529eca9fd370008c1ac87c,"For Black men, being tall increases threat stereotyping and police stops.",University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+507af6591900a7165c529eca9fd370008c1ac87c,"For Black men, being tall increases threat stereotyping and police stops.",Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
50c0de2cccf7084a81debad5fdb34a9139496da0,"The Influence of Annotation, Corpus Design, and Evaluation on the Outcome of Automatic Classification of Human Emotions",Ulm University,Ulm University,"HNU, John-F.-Kennedy-Straße, Vorfeld, Wiley, Neu-Ulm, Landkreis Neu-Ulm, Schwaben, Bayern, 89231, Deutschland",48.38044335,10.01010115,edu,
+68c3e61cefcfe4812df54be12625dabe66fb06a4,A Compact Deep Learning Model for Robust Facial Expression Recognition,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+68245f308f8049dc40f146e296d6e6a6bdba1ff4,Private and Shared Taste in Art and Face Appreciation,University of Vienna,University of Vienna,"Uni Wien, 1, Universitätsring, Schottenviertel, KG Innere Stadt, Innere Stadt, Wien, 1010, Österreich",48.21313020,16.36068653,edu,
+6861552bf6730529d3fac5d6f2bb7e0f491edea2,Neural Self Talk: Image Understanding via Continuous Questioning and Answering,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
68f89c1ee75a018c8eff86e15b1d2383c250529b,Final Report for Project Localizing Objects and Actions in Videos Using Accompanying Text,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
68f89c1ee75a018c8eff86e15b1d2383c250529b,Final Report for Project Localizing Objects and Actions in Videos Using Accompanying Text,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
68f89c1ee75a018c8eff86e15b1d2383c250529b,Final Report for Project Localizing Objects and Actions in Videos Using Accompanying Text,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
@@ -158,45 +518,111 @@ 68f89c1ee75a018c8eff86e15b1d2383c250529b,Final Report for Project Localizing Objects and Actions in Videos Using Accompanying Text,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
68f89c1ee75a018c8eff86e15b1d2383c250529b,Final Report for Project Localizing Objects and Actions in Videos Using Accompanying Text,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
68f89c1ee75a018c8eff86e15b1d2383c250529b,Final Report for Project Localizing Objects and Actions in Videos Using Accompanying Text,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+688550a6c72f14cb8f2d9d86802c7cfc3d3d800e,Discovering Influential Factors in Variational Autoencoder,University at Buffalo,State University of New York at Buffalo,"Buffalo, NY 14260, USA",43.00080930,-78.78896970,edu,
+68147c43ad2ddebf223bd14a7928cbe26c7f270e,RNN Encoder Decoder 3 D Skeleton Converter 2 D Pose Sequence Generator Input Image 2 D Pose Heatmaps 3 D Skeleton Hourglass network,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
68c5238994e3f654adea0ccd8bca29f2a24087fc,pLSA-based zero-shot learning,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
+68ce1572b18c95fe9c60bc11d9d33f8310902154,Budgeted Nonparametric Learning from Data Streams,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
68e9c837431f2ba59741b55004df60235e50994d,Detecting Faces Using Region-based Fully Convolutional Networks,Tencent,"Tencent AI Lab, China","Ke Ji Zhong Yi Lu, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057",22.54471540,113.93571640,company,"Keji Middle 1st Rd, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057"
687e17db5043661f8921fb86f215e9ca2264d4d2,A robust elastic and partial matching metric for face recognition,Microsoft,"Microsoft Corporation, Redmond, WA, USA","One Microsoft Way, Redmond, WA 98052, USA",47.64233180,-122.13693020,company,
+68c6df1249e1ee56835f79e1877506a16d8418f4,Criteria for Human-Compatible AI in Two-Player Vision-Language Tasks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+68c6df1249e1ee56835f79e1877506a16d8418f4,Criteria for Human-Compatible AI in Two-Player Vision-Language Tasks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+68249064f7d5046abef785ada541244fa67b4346,"Contribution of Developmental Psychology to the Study of Social Interactions: Some Factors in Play, Joint Attention and Joint Action and Implications for Robotics",University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
68c4a1d438ea1c6dfba92e3aee08d48f8e7f7090,AgeNet: Deeply Learned Regressor and Classifier for Robust Apparent Age Estimation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
68f69e6c6c66cfde3d02237a6918c9d1ee678e1b,Enhancing Concept Detection by Pruning Data with MCA-Based Transaction Weights,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
68f69e6c6c66cfde3d02237a6918c9d1ee678e1b,Enhancing Concept Detection by Pruning Data with MCA-Based Transaction Weights,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
+6880013eb0b91a2b334e0be0dced0a1a79943469,Discrimination-aware Channel Pruning for Deep Neural Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+6880013eb0b91a2b334e0be0dced0a1a79943469,Discrimination-aware Channel Pruning for Deep Neural Networks,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
682760f2f767fb47e1e2ca35db3becbb6153756f,The Effect of Pets on Happiness: A Large-Scale Multi-Factor Analysis Using Social Multimedia,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
682760f2f767fb47e1e2ca35db3becbb6153756f,The Effect of Pets on Happiness: A Large-Scale Multi-Factor Analysis Using Social Multimedia,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
682760f2f767fb47e1e2ca35db3becbb6153756f,The Effect of Pets on Happiness: A Large-Scale Multi-Factor Analysis Using Social Multimedia,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
683ec608442617d11200cfbcd816e86ce9ec0899,Dual Linear Regression Based Classification for Face Cluster Recognition,University of Northern British Columbia,University of Northern British Columbia,"UNBC, Campus Ring Road, College Heights, Prince George, Regional District of Fraser-Fort George, British Columbia, V2M 5K7, Canada",53.89256620,-122.81471592,edu,
+6890af11d4c0a3189e974ffe7cf03088cf532ab7,3D landmark model discovery from a registered set of organic shapes,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+683f5c838ea2c9c50f3f5c5fa064c00868751733,3D Visual Proxemics: Recognizing Human Interactions in 3D from a Single Image,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
6821113166b030d2123c3cd793dd63d2c909a110,Acquisition and Indexing of Rgb-d Recordings for Facial Expressions and Emotion Recognition1,Gdansk University of Technology,Gdansk University of Technology,"PG, Romualda Traugutta, Królewska Dolina, Wrzeszcz Górny, Gdańsk, pomorskie, 80-233, RP",54.37086525,18.61716016,edu,
+68eb46d2920d2e7568d543de9fa2fc42cb8f5cbb,FACE2GPS: Estimating geographic location from facial features,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+6834a469562cb563bc91ae08f4e2aa6b03e27b1a,Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+6834a469562cb563bc91ae08f4e2aa6b03e27b1a,Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+68a677a326a290a82bc08686465019414ebe1d98,ImageSpirit: Verbal Guided Image Parsing,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+68a677a326a290a82bc08686465019414ebe1d98,ImageSpirit: Verbal Guided Image Parsing,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+68a677a326a290a82bc08686465019414ebe1d98,ImageSpirit: Verbal Guided Image Parsing,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
68a04a3ae2086986877fee2c82ae68e3631d0356,Thermal & Reflectance Based Identification in Challenging Variable Illuminations,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+687fc9ffea3ca36d87817faf37492941ec6eb0b9,Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+578e002828e5e106dd660c7273ebcb014e8068a6,Distantly Supervised Road Segmentation,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
57f5711ca7ee5c7110b7d6d12c611d27af37875f,Illumination invariance for face verification,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
57f5711ca7ee5c7110b7d6d12c611d27af37875f,Illumination invariance for face verification,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
570308801ff9614191cfbfd7da88d41fb441b423,Unsupervised Synchrony Discovery in Human Interaction,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
570308801ff9614191cfbfd7da88d41fb441b423,Unsupervised Synchrony Discovery in Human Interaction,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
570308801ff9614191cfbfd7da88d41fb441b423,Unsupervised Synchrony Discovery in Human Interaction,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
57bf9888f0dfcc41c5ed5d4b1c2787afab72145a,Robust Facial Expression Recognition Based on Local Directional Pattern,Kyung Hee University,Kyung Hee University,"Kyung Hee Tae Kwon Do, Vons 2370 Truck Service Ramp, University City, San Diego, San Diego County, California, 92122, USA",32.85363330,-117.20352860,edu,
+57522ff758642e054d7c50753ec1c3fe598533f0,Information-Based Boundary Equilibrium Generative Adversarial Networks with Interpretable Representation Learning,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
57ebeff9273dea933e2a75c306849baf43081a8c,Deep Convolutional Network Cascade for Facial Point Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
57ebeff9273dea933e2a75c306849baf43081a8c,Deep Convolutional Network Cascade for Facial Point Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
57ebeff9273dea933e2a75c306849baf43081a8c,Deep Convolutional Network Cascade for Facial Point Detection,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+575d6a05bb27316ad677f19e79473e314e6c6f94,Stacked What-Where Auto-encoders,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+572791e2f290dc0ecb05e56bfa714c4b7af79b08,Extended MHT algorithm for multiple object tracking,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+572791e2f290dc0ecb05e56bfa714c4b7af79b08,Extended MHT algorithm for multiple object tracking,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
5778d49c8d8d127351eee35047b8d0dc90defe85,Probabilistic Subpixel Temporal Registration for Facial Expression Analysis,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+579b2962ac567a39742601cafe3fc43cf7a7109c,Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+579b2962ac567a39742601cafe3fc43cf7a7109c,Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
57ee3a8b0cafe211d1e9b477d210bb78b9d43bc1,Modeling the joint density of two images under a variety of transformations,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
57ee3a8b0cafe211d1e9b477d210bb78b9d43bc1,Modeling the joint density of two images under a variety of transformations,University of Frankfurt,University of Frankfurt,"Frankfurt University of Applied Sciences, Kleiststraße, Nordend West, Frankfurt, Regierungsbezirk Darmstadt, Hessen, 60318, Deutschland",50.13053055,8.69234224,edu,
57ee3a8b0cafe211d1e9b477d210bb78b9d43bc1,Modeling the joint density of two images under a variety of transformations,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+57df27685196fad070bd2da14ed865fda87d93a9,Determining the best attributes for surveillance video keywords generation,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+57bd01c042a5f64659b3a9f91c048b8594f762f6,Advances in fine-grained visual categorization,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
571f493c0ade12bbe960cfefc04b0e4607d8d4b2,Review on Content Based Image Retrieval: From Its Origin to the New Age,Mahatma Gandhi Institute of Technology,Mahatma Gandhi Institute of Technology,"Gandipet Main Rd, Kokapet, Hyderabad, Telangana 500075, India",17.39084720,78.32176670,edu,
+57412e2966a04c106657c926bcfdcb5c3842444d,Camera and microphone array for 3D audiovisual face data collection,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+57412e2966a04c106657c926bcfdcb5c3842444d,Camera and microphone array for 3D audiovisual face data collection,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+57488aa24092fa7118aa5374c90b282a32473cf9,A Weakly Supervised Adaptive DenseNet for Classifying Thoracic Diseases and Identifying Abnormalities,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+57488aa24092fa7118aa5374c90b282a32473cf9,A Weakly Supervised Adaptive DenseNet for Classifying Thoracic Diseases and Identifying Abnormalities,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+57488aa24092fa7118aa5374c90b282a32473cf9,A Weakly Supervised Adaptive DenseNet for Classifying Thoracic Diseases and Identifying Abnormalities,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
574b62c845809fd54cc168492424c5fac145bc83,Learning Warped Guidance for Blind Face Restoration,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
574b62c845809fd54cc168492424c5fac145bc83,Learning Warped Guidance for Blind Face Restoration,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
574b62c845809fd54cc168492424c5fac145bc83,Learning Warped Guidance for Blind Face Restoration,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+576bfffd7d58a9c70ff73e39033f31739e6f09b2,Using Both Latent and Supervised Shared Topics for Multitask Learning,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+576bfffd7d58a9c70ff73e39033f31739e6f09b2,Using Both Latent and Supervised Shared Topics for Multitask Learning,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+57ec50237ee588d3b40640c4f98410cbd996ee84,Toward Guaranteed Illumination Models for Non-convex Objects,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+57ec50237ee588d3b40640c4f98410cbd996ee84,Toward Guaranteed Illumination Models for Non-convex Objects,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+5727ac51ad6fb67d81cc3ef2c04440c179bd53ab,Oxytocin attenuates amygdala responses to emotional faces regardless of valence.,University of Zurich,University of Zurich,"ZHAW, Rosenstrasse, Heiligberg, Altstadt, Winterthur, Bezirk Winterthur, Zürich, 8400, Schweiz/Suisse/Svizzera/Svizra",47.49684760,8.72981767,edu,
+57d33c0f8d6998d665a7ec6672a56cf8e7729c14,Detection of facial characteristics based on edge information,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+57efdcf4d56f15846c9c5104ce2cd414532ced7d,"The development of the Athens Emotional States Inventory (AESI): collection, validation and automatic processing of emotionally loaded sentences.",University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+57efdcf4d56f15846c9c5104ce2cd414532ced7d,"The development of the Athens Emotional States Inventory (AESI): collection, validation and automatic processing of emotionally loaded sentences.",National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
+5793b25e2492d47f5faf9b93b8c0fe36802de8b6,Robust Optimization for Deep Regression,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+5793b25e2492d47f5faf9b93b8c0fe36802de8b6,Robust Optimization for Deep Regression,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
575141e42740564f64d9be8ab88d495192f5b3bc,Age Estimation Based on Multi-Region Convolutional Neural Network,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
575141e42740564f64d9be8ab88d495192f5b3bc,Age Estimation Based on Multi-Region Convolutional Neural Network,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
5789f8420d8f15e7772580ec373112f864627c4b,Efficient Global Illumination for Morphable Models,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+57588971cfef4be8e0706f30cfafbf6c293fed3b,Semantic Autoencoder for Zero-Shot Learning,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+577c1d59e43f04a4bfda95b0b9e3b41d893bc0a2,Faster Evaluation of Labor-Intensive Features,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
574ad7ef015995efb7338829a021776bf9daaa08,AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
+5741255d30f4848273c921ad177b32ff1cfe0671,DLD Journal F01,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+57632f82553f34bce21cc8419bc5381d50096592,A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+57632f82553f34bce21cc8419bc5381d50096592,A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+57632f82553f34bce21cc8419bc5381d50096592,A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
57b052cf826b24739cd7749b632f85f4b7bcf90b,Fast Fashion Guided Clothing Image Retrieval: Delving Deeper into What Feature Makes Fashion,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
57f7d8c6ec690bd436e70d7761bc5f46e993be4c,Facial expression recognition using histogram variances faces,University of Aizu,University of Aizu,"会津大学, 磐越自動車道, 会津若松市, 福島県, 東北地方, 965-8580, 日本",37.52367280,139.93807246,edu,
+57db5b35f2473fc3608fe3519d6763c1d4984eed,Learning from interaction : models and applications,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+5746dcc8164ab95dcf8569bd4f37dec58e1112a3,Recognizing Artificial Faces Using Wavelet Based Adapted Median Binary Patterns,University of Louisville,University of Louisville,"University of Louisville, South Brook Street, Louisville, Jefferson County, Kentucky, 40208, USA",38.21675650,-85.75725023,edu,
+57417c4a523d93801c8901d6f3c3740eaa65c9ae,Inverse Visual Question Answering,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+57417c4a523d93801c8901d6f3c3740eaa65c9ae,Inverse Visual Question Answering,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+3ba5aa0995f129d2854d9690adb6d982bba4e675,Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+3ba5aa0995f129d2854d9690adb6d982bba4e675,Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+3ba5aa0995f129d2854d9690adb6d982bba4e675,Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+3b4ec8af470948a72a6ed37a9fd226719a874ebc,A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+3b4ec8af470948a72a6ed37a9fd226719a874ebc,A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+3b964d6a527f24b1a1f8499b0f4dbb0ed982d5e2,GADAM: Genetic-Evolutionary ADAM for Deep Neural Network Optimization,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+3b964d6a527f24b1a1f8499b0f4dbb0ed982d5e2,GADAM: Genetic-Evolutionary ADAM for Deep Neural Network Optimization,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+3b152bdeedb97d68dd69bbb806c60c205e6fa696,Patch-Based Principal Component Analysis for Face Recognition,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+3bb724ee496100e12087ced6564198d63d843259,Recognizing Degraded Handwritten Characters,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
+3b6602e64e62e5703151d17475d4728bd2095256,Brief Communication Oxytocin Modulates Neural Circuitry for Social Cognition and Fear in Humans,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+3b6602e64e62e5703151d17475d4728bd2095256,Brief Communication Oxytocin Modulates Neural Circuitry for Social Cognition and Fear in Humans,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
3b092733f428b12f1f920638f868ed1e8663fe57,On the size of Convolutional Neural Networks and generalization performance,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
3b73f8a2b39751efb7d7b396bf825af2aaadee24,Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
3b2d5585af59480531616fe970cb265bbdf63f5b,Robust Face Recognition under Varying Light Based on 3D Recovery,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
3b64efa817fd609d525c7244a0e00f98feacc8b4,A Comprehensive Survey on Pose-Invariant Face Recognition,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+3b5128bfe35875d0cead04b7d19024d841b605f9,Multispectral pedestrian detection: Benchmark dataset and baseline,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
+3b01a839d174dad6f2635cff7ebe7e1aaad701a4,Image Co-localization by Mimicking a Good Detector's Confidence Score Distribution,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+3be9286e5d6a9d9167c64b05be6fb0712ffbba35,Recurrent Autoregressive Networks for Online Multi-object Tracking,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+3b788fd0817336b3db3e111fa2ff50b665070e95,"Multi-view traffic sign detection, recognition, and 3D localisation",Katholieke Universiteit Leuven,Katholieke Universiteit Leuven,"Laboratorium voor Bos, natuur en landschap, 102, Vital Decosterstraat, Sint-Maartensdal, Leuven, Vlaams-Brabant, Vlaanderen, 3000, België / Belgique / Belgien",50.88306860,4.70195030,edu,
3b7f6035a113b560760c5e8000540fc46f91fed5,Coupling Alignments with Recognition for Still-to-Video Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
3b2a2357b12cf0a5c99c8bc06ef7b46e40dd888e,Learning Person Trajectory Representations for Team Activity Analysis,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
3bd1d41a656c8159305ba2aa395f68f41ab84f31,Entity-Based Opinion Mining from Text and Multimedia,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
@@ -204,6 +630,7 @@ 3b9c08381282e65649cd87dfae6a01fe6abea79b,CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
3b9c08381282e65649cd87dfae6a01fe6abea79b,CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
3b84d074b8622fac125f85ab55b63e876fed4628,End-to-End Localization and Ranking for Relative Attributes,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+3b67645cd512898806aaf1df1811035f2d957f6b,SCNet: Learning Semantic Correspondence,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
3b4fd2aec3e721742f11d1ed4fa3f0a86d988a10,"Demo: Glimpse - Continuous, Real-Time Object Recognition on Mobile Devices",MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
3b4fd2aec3e721742f11d1ed4fa3f0a86d988a10,"Demo: Glimpse - Continuous, Real-Time Object Recognition on Mobile Devices",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
3b4fd2aec3e721742f11d1ed4fa3f0a86d988a10,"Demo: Glimpse - Continuous, Real-Time Object Recognition on Mobile Devices",MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
@@ -212,27 +639,72 @@ 3be8f1f7501978287af8d7ebfac5963216698249,Deep Cascaded Regression for Face Alignment,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
3be8f1f7501978287af8d7ebfac5963216698249,Deep Cascaded Regression for Face Alignment,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
3bc376f29bc169279105d33f59642568de36f17f,Active shape models with SIFT descriptors and MARS,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
+3b8a5be5508f809a2d68a78d21cbf1690db57d5c,Large Scale Sketch Based Image Retrieval Using Patch Hashing,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+3b6680a28c87dec9f369263b8428e41a3844ac5f,Action Recognition from a Small Number of Frames,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
+3b6680a28c87dec9f369263b8428e41a3844ac5f,Action Recognition from a Small Number of Frames,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
3b38c06caf54f301847db0dd622a6622c3843957,Gender differences in emotion perception and self-reported emotional intelligence: A test of the emotion sensitivity hypothesis,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+3b5787604b619c273bf98232b0bd3bce5d4a34ee,Learning Discriminative Hidden Structural Parts for Visual Tracking,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+3b5787604b619c273bf98232b0bd3bce5d4a34ee,Learning Discriminative Hidden Structural Parts for Visual Tracking,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+3b9d48a09510ebd8bd5045ba455279abb0a9baf8,OPERATORS and THEIR APPLICATIONS,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
+3ba5e820f160dfd02544120ab6c1678421fb2c3b,Future Semantic Segmentation with Convolutional LSTM,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+3bebff841ce7d40f0309bbc0e8cc454694061e82,Segmenting Scenes by Matching Image Composites,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+3bebff841ce7d40f0309bbc0e8cc454694061e82,Segmenting Scenes by Matching Image Composites,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3b0b706fc94b35a1eddd830685e07870315b9565,Task-Driven Dynamic Fusion: Reducing Ambiguity in Video Description,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+3b0b706fc94b35a1eddd830685e07870315b9565,Task-Driven Dynamic Fusion: Reducing Ambiguity in Video Description,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+3b0b706fc94b35a1eddd830685e07870315b9565,Task-Driven Dynamic Fusion: Reducing Ambiguity in Video Description,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+3b466bb66ee79c8e9bcdb6cf9acb54b864dda735,"Joint inference of groups, events and human roles in aerial videos",Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+3bdef2961f9572d2d0f35148a7fa8a3a81f50dea,Finding the weakest link in person detectors,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+3bdf9c8ba5f5cf1845fe69b3874f0036ea8c245a,Latent Space Optimal Transport for Generative Models,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+3bdf9c8ba5f5cf1845fe69b3874f0036ea8c245a,Latent Space Optimal Transport for Generative Models,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
+3bdf9c8ba5f5cf1845fe69b3874f0036ea8c245a,Latent Space Optimal Transport for Generative Models,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
3b9b200e76a35178da940279d566bbb7dfebb787,Learning Channel Inter-dependencies at Multiple Scales on Dense Networks for Face Recognition,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
3b408a3ca6fb39b0fda4d77e6a9679003b2dc9ab,Improving Classification by Improving Labelling: Introducing Probabilistic Multi-Label Object Interaction Recognition,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+3bac7069b9d3051f40ef4eecacc517d02107ba4a,Early Recognition of Human Activities from First-Person Videos Using Onset Representations,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+3bac7069b9d3051f40ef4eecacc517d02107ba4a,Early Recognition of Human Activities from First-Person Videos Using Onset Representations,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+3bdcc99f45b58e4ddf4ffde5f58bea1ddada2744,Conversational Image Editing: Incremental Intent Identification in a New Dialogue Task,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
3b02aaccc9f063ae696c9d28bb06a8cd84b2abb8,"Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study",Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
3b02aaccc9f063ae696c9d28bb06a8cd84b2abb8,"Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study",Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
3b02aaccc9f063ae696c9d28bb06a8cd84b2abb8,"Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study",Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
3b02aaccc9f063ae696c9d28bb06a8cd84b2abb8,"Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study",University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
3bb6570d81685b769dc9e74b6e4958894087f3f1,Hu-Fu: Hardware and Software Collaborative Attack Framework Against Neural Networks,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+3bad18554678ab46bbbf9de41d36423bc8083c83,Weakly Supervised Object Boundaries,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
3b3482e735698819a6a28dcac84912ec01a9eb8a,Individual recognition using gait energy image,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
3b37d95d2855c8db64bd6b1ee5659f87fce36881,Adversarially Optimizing Intersection over Union for Object Localization Tasks,University of Illinois at Chicago,University of Illinois at Chicago,"University of Illinois at Chicago, West Taylor Street, Greektown, Chicago, Cook County, Illinois, 60607, USA",41.86898915,-87.64856256,edu,
3b37d95d2855c8db64bd6b1ee5659f87fce36881,Adversarially Optimizing Intersection over Union for Object Localization Tasks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3b37d95d2855c8db64bd6b1ee5659f87fce36881,Adversarially Optimizing Intersection over Union for Object Localization Tasks,University of Illinois at Chicago,University of Illinois at Chicago,"University of Illinois at Chicago, West Taylor Street, Greektown, Chicago, Cook County, Illinois, 60607, USA",41.86898915,-87.64856256,edu,
3be027448ad49a79816cd21dcfcce5f4e1cec8a8,Actively selecting annotations among objects and attributes,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
3bd56f4cf8a36dd2d754704bcb71415dcbc0a165,Robust Regression,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+3b23c39f21156f9ea86ad8bb2ca53b2cf56b4181,Predictable Performance and Fairness Through Accurate Slowdown Estimation in Shared Main Memory Systems,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+3b23c39f21156f9ea86ad8bb2ca53b2cf56b4181,Predictable Performance and Fairness Through Accurate Slowdown Estimation in Shared Main Memory Systems,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
3b470b76045745c0ef5321e0f1e0e6a4b1821339,Consensus of Regression for Occlusion-Robust Facial Feature Localization,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+6f9c01a9b861882c6676227942005cef13f3cb29,Cross Quality Distillation,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+6f71862aa00d61fc8fd7f205de35ee8af458ec0c,Semi - supervised Learning of Instance - level Recognition from Video,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+6f4a596c80b5ccaf44a076760761c4f132920b11,Integrating Visual and Linguistic Information to Describe Properties of Objects,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+6f4a671537c9e60f042808451ff0fc06032d1221,Play and Learn: Using Video Games to Train Computer Vision Models,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+6f8de996c9659459d4dc6a10cb3d8a43cb846422,Explainable Neural Computation via Stack Neural Module Networks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+6f8de996c9659459d4dc6a10cb3d8a43cb846422,Explainable Neural Computation via Stack Neural Module Networks,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+6faab65a009b36ee3f79d3e4afdf3cc84d57cd67,Adversarial Learning for Semi-supervised Semantic Segmentation,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+6faab65a009b36ee3f79d3e4afdf3cc84d57cd67,Adversarial Learning for Semi-supervised Semantic Segmentation,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+6f68ca4cc05ef8db344f0bf1ee394e93d519e77e,Matrix Factorization as Search,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+6f44303f9664a4ceabd0f4bc74cb3886aad5012f,An Integral Pose Regression System for the ECCV2018 PoseTrack Challenge,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+6f44303f9664a4ceabd0f4bc74cb3886aad5012f,An Integral Pose Regression System for the ECCV2018 PoseTrack Challenge,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
6fa0c206873dcc5812f7ea74a48bb4bf4b273494,Real-Time Mobile Facial Expression Recognition System -- A Case Study,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
6f9824c5cb5ac08760b08e374031cbdabc953bae,Unconstrained human identification using comparative facial soft biometrics,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+6fc1e886659838b2ca08dbaca291420785fd51bd,Total Capture: 3D Human Pose Estimation Fusing Video and Inertial Sensors,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+6f491fcff042991767a8d5c3a919ce169e0e65f0,Dual-Agent Deep Reinforcement Learning for Deformable Face Tracking,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
6fed504da4e192fe4c2d452754d23d3db4a4e5e3,Learning Deep Features via Congenerous Cosine Loss for Person Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+6fee701352f0f5c4abea3e918ddcf078243253cc,Alcohol and Remembering Sexual,Loughborough University,Loughborough University,"Computer Science, University Road, Charnwood, Leicestershire, East Midlands, England, LE11 3TP, UK",52.76635770,-1.22924610,edu,
+6fbc58272384ede0efa72753d78f1ef6db381ad7,Robust Face Recognition with Deeply Normalized Depth Images,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+6fb33358bc7e1a73e88b4a87fb0962366ab959c9,Fuzzy 3D Face Ethnicity Categorization,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
6f26ab7edd971148723d9b4dc8ddf71b36be9bf7,Differences in Abundances of Cell-Signalling Proteins in Blood Reveal Novel Biomarkers for Early Detection Of Clinical Alzheimer's Disease,University of Newcastle,University of Newcastle,"University of Newcastle Central Coast Campus, Technology Bridge, Ourimbah, Central Coast, NSW, 2258, Australia",-33.35788990,151.37834708,edu,
+6f73807e309b262c5761c7a73c6a5609679f9f02,Shadow and Specular Removal by Photometric Linearization based on PCA with Outlier Exclusion,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
6f7a8b3e8f212d80f0fb18860b2495be4c363eac,Creating Capsule Wardrobes from Fashion Images,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
6f7a8b3e8f212d80f0fb18860b2495be4c363eac,Creating Capsule Wardrobes from Fashion Images,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+6f640d448f00321b9b3bddb3a787cacd2f45cd1a,Stereo 3D Object Trajectory Reconstruction,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+6ff9b66aec16d84b1133850e7e8ce188a5a9a7f4,Do-gooder derogation in children: the social costs of generosity,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+6ff9b66aec16d84b1133850e7e8ce188a5a9a7f4,Do-gooder derogation in children: the social costs of generosity,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+6ff9b66aec16d84b1133850e7e8ce188a5a9a7f4,Do-gooder derogation in children: the social costs of generosity,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+6fac6fb9b2fff94e2babc4906646cf6427c591a0,PKU-NEC @ TRECVid 2011 SED: Sequence-Based Event Detection in Surveillance Video*,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
6f0900a7fe8a774a1977c5f0a500b2898bcbe149,Quotient Based Multiresolution Image Fusion of Thermal and Visual Images Using Daubechies Wavelet Transform for Human Face Recognition,Jadavpur University,Jadavpur University,"Jadavpur University, Chingrighata Flyover, Basani Devi Colony, Kolkata, Hāora, West Bengal, 700098, India",22.56115370,88.41310194,edu,
6fea198a41d2f6f73e47f056692f365c8e6b04ce,Video Captioning with Boundary-aware Hierarchical Language Decoding and Joint Video Prediction,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
6fea198a41d2f6f73e47f056692f365c8e6b04ce,Video Captioning with Boundary-aware Hierarchical Language Decoding and Joint Video Prediction,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
@@ -240,91 +712,252 @@ 6fea198a41d2f6f73e47f056692f365c8e6b04ce,Video Captioning with Boundary-aware Hierarchical Language Decoding and Joint Video Prediction,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
6fbb179a4ad39790f4558dd32316b9f2818cd106,Input Aggregated Network for Face Video Representation,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
6f84e61f33564e5188136474f9570b1652a0606f,Dual Motion GAN for Future-Flow Embedded Video Prediction,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6f4ec006b6b9da4982169adea2914aa3d14ee753,Adversarial Robustness: Softmax versus Openmax,"University of Colorado, Colorado Springs",University of Colorado Colorado Springs,"Main Hall, The Spine, Colorado Springs, El Paso County, Colorado, 80907, USA",38.89207560,-104.79716389,edu,
+6f70e85442959079bfb67b925c660fe86cb4ba24,Person Re-Identification with Correspondence Structure Learning,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+6f70e85442959079bfb67b925c660fe86cb4ba24,Person Re-Identification with Correspondence Structure Learning,Zhengzhou University,Zhengzhou University,"科学大道, 中原区 (Zhongyuan), 郑州市 / Zhengzhou, 河南省, 450001, 中国",34.80881680,113.53526640,edu,
+6f70e85442959079bfb67b925c660fe86cb4ba24,Person Re-Identification with Correspondence Structure Learning,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+6f70e85442959079bfb67b925c660fe86cb4ba24,Person Re-Identification with Correspondence Structure Learning,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
6fda12c43b53c679629473806c2510d84358478f,A Training Model for Fuzzy Classification System,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+6f813ccf106360cc9c3d6df849cc04d881d0a6e8,"360◦ User Profiling: Past, Future, and Applications",National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+6f813ccf106360cc9c3d6df849cc04d881d0a6e8,"360◦ User Profiling: Past, Future, and Applications",Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
6fef65bd7287b57f0c3b36bf8e6bc987fd161b7d,Deep Discriminative Model for Video Classification,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+03a83517298203605b502648ded886fee5a7436e,"Extraction and recognition of periodically deforming objects by continuous, spatio-temporal shape description",University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+031716b430e4256c09d5b3559ca9f0be51cb30b6,ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
036c41d67b49e5b0a578a401eb31e5f46b3624e0,The Tower Game Dataset: A multimodal dataset for analyzing social interaction predicates,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
036c41d67b49e5b0a578a401eb31e5f46b3624e0,The Tower Game Dataset: A multimodal dataset for analyzing social interaction predicates,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
03b03f5a301b2ff88ab3bb4969f54fd9a35c7271,Pillar Networks for action recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
03ce2ff688f9b588b6f264ca79c6857f0d80ceae,Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+033c3114f4951d338e34af67e1699ef779ab258d,Prioritization of arbitrary faces associated to self: An EEG study,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
03b99f5abe0e977ff4c902412c5cb832977cf18e,Of Gods and Goats: Weakly Supervised Learning of Figurative Art,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+0344f29da9641edc36bc4952e1f7a4bfd8dd9bb3,Facial expression at retrieval affects recognition of facial identity,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0344f29da9641edc36bc4952e1f7a4bfd8dd9bb3,Facial expression at retrieval affects recognition of facial identity,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
+0344f29da9641edc36bc4952e1f7a4bfd8dd9bb3,Facial expression at retrieval affects recognition of facial identity,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+0344f29da9641edc36bc4952e1f7a4bfd8dd9bb3,Facial expression at retrieval affects recognition of facial identity,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+0344f29da9641edc36bc4952e1f7a4bfd8dd9bb3,Facial expression at retrieval affects recognition of facial identity,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
03167776e17bde31b50f294403f97ee068515578,Chapter 11. Facial Expression Analysis,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
03167776e17bde31b50f294403f97ee068515578,Chapter 11. Facial Expression Analysis,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
03167776e17bde31b50f294403f97ee068515578,Chapter 11. Facial Expression Analysis,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+0353fe24ecd237f4d9ae4dbc277a6a67a69ce8ed,Discriminative Feature Representation for Person Re-identification by Batch-contrastive Loss,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
0334a8862634988cc684dacd4279c5c0d03704da,FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+032ede597491cfbdf7424d221bd74742b6707397,Spectral Latent Variable Models for Perceptual Inference,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+032ede597491cfbdf7424d221bd74742b6707397,Spectral Latent Variable Models for Perceptual Inference,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+032ede597491cfbdf7424d221bd74742b6707397,Spectral Latent Variable Models for Perceptual Inference,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+030c43389bafdfefb4d6c7db0d121d0335d71342,Unsupervised metric fusion by cross diffusion,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+030c43389bafdfefb4d6c7db0d121d0335d71342,Unsupervised metric fusion by cross diffusion,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
030ef31b51bd4c8d0d8f4a9a32b80b9192fe4c3f,Inhibition-Induced Forgetting Results from Resource Competition between Response Inhibition and Memory Encoding Processes.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
030ef31b51bd4c8d0d8f4a9a32b80b9192fe4c3f,Inhibition-Induced Forgetting Results from Resource Competition between Response Inhibition and Memory Encoding Processes.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
03f98c175b4230960ac347b1100fbfc10c100d0c,Supervised Descent Method and Its Applications to Face Alignment,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0371b7cba37970f22040a10bd29219778dcc3947,Taming Social Tags: Computational Linguistic Analysis of Tags for Images in Museums,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
03264e2e2709d06059dd79582a5cc791cbef94b1,Convolutional Neural Networks for Facial Attribute-based Active Authentication on Mobile Devices,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
03264e2e2709d06059dd79582a5cc791cbef94b1,Convolutional Neural Networks for Facial Attribute-based Active Authentication on Mobile Devices,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+0385b65a4941899340ef59f605fb3e943d62330c,Representing 3D texture on mesh manifolds for retrieval and recognition applications,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+03dd7ca6fdf2f4785089e286969f7ee5ccea0a02,From interactive to semantic image segmentation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
03fc466fdbc8a2efb6e3046fcc80e7cb7e86dc20,A real time system for model-based interpretation of the dynamics of facial expressions,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+03a721080a69be37db3a2d56c006c60f472b419d,Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+03a24d15533dae78de78fd9d5f6c9050fb97f186,Pedestrian detection aided by scale-discriminative network,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+035886f58b550be140b1d4dbba0ea0479030589f,Trajectory bundle estimation For perception-driven planning,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+03ca829e8680ab4cdabd491b3b42639c58f4cdce,A graph-based algorithm for multi-target tracking with occlusion,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
+03eb382e04cca8cca743f7799070869954f1402a,CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+032ab4966465facd284531865529b124ef173a0e,Web image prediction using multivariate point processes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+032ab4966465facd284531865529b124ef173a0e,Web image prediction using multivariate point processes,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+032ab4966465facd284531865529b124ef173a0e,Web image prediction using multivariate point processes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+03ea1c3f867703f840c0e65df86e09055ad6f774,Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+0353903b504d6246edcdc6b2c7d32e59b5c0a863,Dynamic Processing Allocation in Video,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+03f98bfb129028b80ce98686c573830671ee1e3d,Examining Cooperation in Visual Dialog Models,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+03f98bfb129028b80ce98686c573830671ee1e3d,Examining Cooperation in Visual Dialog Models,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+03f98bfb129028b80ce98686c573830671ee1e3d,Examining Cooperation in Visual Dialog Models,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+03f98bfb129028b80ce98686c573830671ee1e3d,Examining Cooperation in Visual Dialog Models,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+03f98bfb129028b80ce98686c573830671ee1e3d,Examining Cooperation in Visual Dialog Models,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
03c48d8376990cff9f541d542ef834728a2fcda2,Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
0319332ded894bf1afe43f174f5aa405b49305f0,Shearlet Network-based Sparse Coding Augmented by Facial Texture Features for Face Recognition,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
0319332ded894bf1afe43f174f5aa405b49305f0,Shearlet Network-based Sparse Coding Augmented by Facial Texture Features for Face Recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+03ce07616628ac7c7dac92ea714313b674217811,Deep Learning of Scene-Specific Classifier for Pedestrian Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+03ce07616628ac7c7dac92ea714313b674217811,Deep Learning of Scene-Specific Classifier for Pedestrian Detection,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+0324a22f71927bee2a448f800287cde562dc2726,People detection in crowded scenes by context-driven label propagation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+03593afd7976bae2c105277f61f335b64fc3cd19,Visual Discovery at Pinterest,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+03d89c8eac079df1ff9acbded0336352cdb04624,End-to-End Video Captioning with Multitask Reinforcement Learning,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+03d364f8545dbcf0d7240c5bb8dc39636c698ddb,Fusion of Head and Full-Body Detectors for Multi-Object Tracking,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
03baf00a3d00887dd7c828c333d4a29f3aacd5f5,Entropy Based Feature Selection for 3D Facial Expression Recognition,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
0359f7357ea8191206b9da45298902de9f054c92,Going deeper in facial expression recognition using deep neural networks,University of Denver,University of Denver,"University of Denver, Driscoll Bridge, Denver, Denver County, Colorado, 80208, USA",39.67665410,-104.96220300,edu,
+03563dfaf4d2cfa397d3c12d742e9669f4e95bab,Deep learning from temporal coherence in video,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+03c6a002268c066fd6947452533e6b316f8576a6,Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+0369baf2366fca2f2afdf86efec4874dc8fad194,A scalable app for measuring autism risk behaviors in young children: A technical validity and feasibility study,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0369baf2366fca2f2afdf86efec4874dc8fad194,A scalable app for measuring autism risk behaviors in young children: A technical validity and feasibility study,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0369baf2366fca2f2afdf86efec4874dc8fad194,A scalable app for measuring autism risk behaviors in young children: A technical validity and feasibility study,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0369baf2366fca2f2afdf86efec4874dc8fad194,A scalable app for measuring autism risk behaviors in young children: A technical validity and feasibility study,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0369baf2366fca2f2afdf86efec4874dc8fad194,A scalable app for measuring autism risk behaviors in young children: A technical validity and feasibility study,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+03184ac97ebf0724c45a29ab49f2a8ce59ac2de3,Evaluation of output embeddings for fine-grained image classification,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+03184ac97ebf0724c45a29ab49f2a8ce59ac2de3,Evaluation of output embeddings for fine-grained image classification,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+0389a3b0fcdb4c244628e603ffaff620f6575bfc,Incorporating Deep Visual Features into Multiobjective based Multi-view Search Results Clustering,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+0389a3b0fcdb4c244628e603ffaff620f6575bfc,Incorporating Deep Visual Features into Multiobjective based Multi-view Search Results Clustering,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
03bd58a96f635059d4bf1a3c0755213a51478f12,Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
03bd58a96f635059d4bf1a3c0755213a51478f12,Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+0382a1301094c6ba60b18ffa8d12da6ca0863339,Online Learned Discriminative Part-Based Appearance Models for Multi-human Tracking,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+03bf59f6db62b5da617e42913e9cbb1e58b79f28,Automatic discovery of groups of objects for scene understanding,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+03bf59f6db62b5da617e42913e9cbb1e58b79f28,Automatic discovery of groups of objects for scene understanding,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+03af78f067ed1f6ea0108a4d2ab7120e7ef852ac,Strong supervision from weak annotation: Interactive training of deformable part models,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+03af78f067ed1f6ea0108a4d2ab7120e7ef852ac,Strong supervision from weak annotation: Interactive training of deformable part models,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+0310d31020ae59bf3d6ac61b6206dfc0e79b4efe,A Differential Approach for Gaze Estimation with Calibration,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+03d10c88aebd7aabe603d455c7bafa9231c7cf51,Hyperconnectivity of the Right Posterior Temporo-parietal Junction Predicts Social Difficulties in Boys with Autism Spectrum Disorder.,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+03d10c88aebd7aabe603d455c7bafa9231c7cf51,Hyperconnectivity of the Right Posterior Temporo-parietal Junction Predicts Social Difficulties in Boys with Autism Spectrum Disorder.,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
03fe3d031afdcddf38e5cc0d908b734884542eeb,Engagement with Artificial Intelligence through Natural Interaction Models,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
03fe3d031afdcddf38e5cc0d908b734884542eeb,Engagement with Artificial Intelligence through Natural Interaction Models,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
03fe3d031afdcddf38e5cc0d908b734884542eeb,Engagement with Artificial Intelligence through Natural Interaction Models,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+9b9f3ec91e8ba185b0c7fd7545b0721e0cba9ba7,Regularity Guaranteed Human Pose Correction,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+9bbc952adb3e3c6091d45d800e806d3373a52bac,Learning Visual Classifiers using Human-centric Annotations,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+9b9b6d34deebb534de66017381be7578e13b761d,"Submitted to the Alfred P . Sloan School of Management in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY IN MANAGEMENT at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February , 2007",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
9be94fa0330dd493f127d51e4ef7f9fd64613cfc,Effects of pose and image resolution on automatic face recognition,North Dakota State University,North Dakota State University,"North Dakota State University, 15th Avenue North, Fargo, Cass County, North Dakota, 58102, USA",46.89715500,-96.81827603,edu,
9be94fa0330dd493f127d51e4ef7f9fd64613cfc,Effects of pose and image resolution on automatic face recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
9bd35145c48ce172b80da80130ba310811a44051,Face Detection with End-to-End Integration of a ConvNet and a 3D Model,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
9bd35145c48ce172b80da80130ba310811a44051,Face Detection with End-to-End Integration of a ConvNet and a 3D Model,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+9ba3e2b8b678910c4fdf379c278dbc007c19aa38,Face Verification via ECOC,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+9bd9050c53d90dfa86cb22501812afe6fc897406,Fine-Grained and Layered Object Recognition,Xi'an Jiaotong University,Xi'an Jiaotong University,"西安交通大学兴庆校区, 文治路, 乐居场, 碑林区 (Beilin), 西安市, 陕西省, 710048, 中国",34.24749490,108.97898751,edu,
+9bd9050c53d90dfa86cb22501812afe6fc897406,Fine-Grained and Layered Object Recognition,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
9b0489f2d5739213ef8c3e2e18739c4353c3a3b7,Visual Data Augmentation through Learning,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
9b0489f2d5739213ef8c3e2e18739c4353c3a3b7,Visual Data Augmentation through Learning,Middlesex University,Middlesex University,"Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK",51.59029705,-0.22963221,edu,
+9b2a272d4526b3eeeda0beb0d399074d5380a2b3,Learning to Align Images Using Weak Geometric Supervision,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+9b2a272d4526b3eeeda0beb0d399074d5380a2b3,Learning to Align Images Using Weak Geometric Supervision,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
9b928c0c7f5e47b4480cb9bfdf3d5b7a29dfd493,Close the loop: Joint blind image restoration and recognition with sparse representation prior,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
9b928c0c7f5e47b4480cb9bfdf3d5b7a29dfd493,Close the loop: Joint blind image restoration and recognition with sparse representation prior,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+9b75cc65a03e5d817c89d71b24404e791f79eb6a,TextureGAN: Controlling Deep Image Synthesis with Texture Patches,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+9be696618cfcea90879747a8512f21b10cceac48,Structural Consistency and Controllability for Diverse Colorization,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+9bfe2732a905cb0aab370d1146a29b9d4129321d,Social Judgments Are Influenced by Both Facial Expression and Direction of Eye Gaze,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+9bfe2732a905cb0aab370d1146a29b9d4129321d,Social Judgments Are Influenced by Both Facial Expression and Direction of Eye Gaze,University of Newcastle,University of Newcastle,"University of Newcastle Central Coast Campus, Technology Bridge, Ourimbah, Central Coast, NSW, 2258, Australia",-33.35788990,151.37834708,edu,
+9bd7f95a4c752a44e96d2205ceb6fcefe9232c8b,Fine-grained Video Captioning for Sports Narrative,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+9bd36eff633c52c6f6e8ead009367f6b6c43f16f,"Image tag refinement towards low-rank, content-tag prior and error sparsity",National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+9bd36eff633c52c6f6e8ead009367f6b6c43f16f,"Image tag refinement towards low-rank, content-tag prior and error sparsity","University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+9bd36eff633c52c6f6e8ead009367f6b6c43f16f,"Image tag refinement towards low-rank, content-tag prior and error sparsity",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+9bdc406ad9e9fc0ce356e6d0e53780534f418849,DeepDiary: Automatic Caption Generation for Lifelogging Image Streams,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
9b2c359c36c38c289c5bacaeb5b1dd06b464f301,Dense Face Alignment,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+9b7878eb0681d107a3892c2a166beeb6c0e2d36f,A vision-grounded dataset for predicting typical locations for verbs,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+9b2607d4a8f7252bf13628afa1b5e5cb55ca65a6,Seeing the face through the eyes: a developmental perspective on face expertise.,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+9b8d73e83c111268745311e03f0c0f7f6c92c9f0,Incremental Convolutional Neural Network Training,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+9b7c922d00a6bebc60607168ebbda2ebdc703db7,Detection and Recognition in Natural Scene Images,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
9b1bcef8bfef0fb5eb5ea9af0b699aa0534fceca,Position-Squeeze and Excitation Block for Facial Attribute Analysis,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
9b07084c074ba3710fee59ed749c001ae70aa408,Computational Models of Face Perception.,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+9babe1957e56fadebb32a64338d54fce794c7094,An Enhanced Sparse Representation Strategy for Signal Classification,University of Delaware,University of Delaware,"University of Delaware, South College Avenue, Newark, New Castle County, Delaware, 19713, USA",39.68103280,-75.75401840,edu,
9be653e1bc15ef487d7f93aad02f3c9552f3ee4a,Computer Vision for Head Pose Estimation: Review of a Competition,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+9bfda2f5144867d5712a8fcbea9dd5fa69d3312b,Image Super-Resolution Using VDSR-ResNeXt and SRCGAN,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
9b246c88a0435fd9f6d10dc88f47a1944dd8f89e,PiCoDes: Learning a Compact Code for Novel-Category Recognition,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
9b246c88a0435fd9f6d10dc88f47a1944dd8f89e,PiCoDes: Learning a Compact Code for Novel-Category Recognition,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
9b93406f3678cf0f16451140ea18be04784faeee,A Bayesian Approach to Alignment-Based Image Hallucination,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+9bac3639b2671dcdbdbbd36e8e9022d7334a3796,VSE++: Improving Visual-Semantic Embeddings with Hard Negatives,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+9bda68ea52bddf5365e3230761c95424ff1ddec5,SSP: Supervised Sparse Projections for Large-Scale Retrieval in High Dimensions,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+9bd0c4082a13de0be6c7daba999b55061011f3a5,1-2011 Image Matching with Distinctive Visual Vocabulary,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9bd0c4082a13de0be6c7daba999b55061011f3a5,1-2011 Image Matching with Distinctive Visual Vocabulary,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+9bd0c4082a13de0be6c7daba999b55061011f3a5,1-2011 Image Matching with Distinctive Visual Vocabulary,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9bd0c4082a13de0be6c7daba999b55061011f3a5,1-2011 Image Matching with Distinctive Visual Vocabulary,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9bd0c4082a13de0be6c7daba999b55061011f3a5,1-2011 Image Matching with Distinctive Visual Vocabulary,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
9b684e2e2bb43862f69b12c6be94db0e7a756187,Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
9b684e2e2bb43862f69b12c6be94db0e7a756187,Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
9b684e2e2bb43862f69b12c6be94db0e7a756187,Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+9b401be9fe35b759ae48c9dd5e9b7e4382511a55,Incremental learning of object detectors using a visual shape alphabet,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+9b401be9fe35b759ae48c9dd5e9b7e4382511a55,Incremental learning of object detectors using a visual shape alphabet,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+9b48372c7adb3780873df7c6d4134f93c2b0aebb,Robust multilinear principal component analysis,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
9ea223c070ec9a00f4cb5ca0de35d098eb9a8e32,Exploring Temporal Preservation Networks for Precise Temporal Action Localization,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
9e42d44c07fbd800f830b4e83d81bdb9d106ed6b,Learning Discriminative Aggregation Network for Video-Based Face Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+9e97dc079139f009c5c98617c28825dca0d70ae3,A survey: face recognition techniques under partial occlusion,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+9e48808f283598edb5a78ec2590a35ff163cc8ed,Stochastic Segmentation Trees for Multiple Ground Truths,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+9e1c3c7f1dce662a877727a821bdf41c5cd906bb,Learning Disentangling and Fusing Networks for Face Completion Under Structured Occlusions,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
9eb86327c82b76d77fee3fd72e2d9eff03bbe5e0,Max-Margin Invariant Features from Transformed Unlabelled Data,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9e3d697dfd0364314aac51522ce3778bc542b17a,Gabor-Based Kernel Partial-Least-Squares Discrimination Features for Face Recognition,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+9ea337ffdf652803c805074d61b2d6a8d7040e95,Ph.D. DISSERTATION PATTERN RECOGNITION USING COMPOSITE FEATURES,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+9e3db0bd1dfa9e033a2a055a9ac03728cd28e930,Coupled Marginalized Auto-Encoders for Cross-Domain Multi-View Learning,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+9ea25c97f3dee29f7861ab4110ca90b4ec0af01b,Robust Out-of-Sample Data Recovery,Anhui University,Anhui University,"安徽大学(磬苑校区), 111, 九龙路, 弘泰苑, 合肥国家级经济技术开发区, 芙蓉社区, 合肥经济技术开发区, 合肥市区, 合肥市, 安徽省, 230601, 中国",31.76909325,117.17795091,edu,
+9ea25c97f3dee29f7861ab4110ca90b4ec0af01b,Robust Out-of-Sample Data Recovery,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+9ed7d774684a1770445c1c53e276011a8364b9e2,Uncovering Temporal Context for Video Question and Answering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9ed7d774684a1770445c1c53e276011a8364b9e2,Uncovering Temporal Context for Video Question and Answering,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
9ed943f143d2deaac2efc9cf414b3092ed482610,Independent Subspace of Dynamic Gabor Features for Facial Expression Classification,Japan Advanced Institute of Science and Technology,Japan Advanced Institute of Science and Technology,"JAIST (北陸先端科学技術大学院大学), 石川県道55号小松辰口線, Ishikawa Science Park, 能美市, 石川県, 中部地方, 923-1206, 日本",36.44429490,136.59285870,edu,
9e1c3b8b1653337094c1b9dba389e8533bc885b0,Demographic Classification with Local Binary Patterns,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+9e8f9786ea868f042f7d984cddbd9a6dc23969ee,Robust Clothing-Invariant Gait Recognition,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+9e1a21c9af589fc2148ce96aa93c9df4a9e5ae02,Undoing the Damage of Dataset Bias,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9e1a21c9af589fc2148ce96aa93c9df4a9e5ae02,Undoing the Damage of Dataset Bias,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+9e1a21c9af589fc2148ce96aa93c9df4a9e5ae02,Undoing the Damage of Dataset Bias,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+9e1a21c9af589fc2148ce96aa93c9df4a9e5ae02,Undoing the Damage of Dataset Bias,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9e1a21c9af589fc2148ce96aa93c9df4a9e5ae02,Undoing the Damage of Dataset Bias,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+9e1a21c9af589fc2148ce96aa93c9df4a9e5ae02,Undoing the Damage of Dataset Bias,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9e1a21c9af589fc2148ce96aa93c9df4a9e5ae02,Undoing the Damage of Dataset Bias,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+9ec74521d03d41f4157a458513c79017dd066a38,Semantic Stixels fusing LIDAR for Scene Perception,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+9e8f95503bebdfb623d4e5b51347f72677d89d99,Multi-dimensional local binary pattern texture descriptors and their application for medical image analysis,Loughborough University,Loughborough University,"Computer Science, University Road, Charnwood, Leicestershire, East Midlands, England, LE11 3TP, UK",52.76635770,-1.22924610,edu,
+9eb891b89443bdfc8434e4c9e08dda0253fd242c,Evaluation of Probabilistic Occupancy Map for Player Tracking in Team Sports,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+9e384187941e939453fc0c7585c1a8e76d535c02,A Robust Approach to Automatic Iris Localization,Myongji University,Myongji University,"명지대, 금학로, 역북동, 처인구, 용인시, 경기, 17144, 대한민국",37.23810230,127.19034310,edu,
+9e504d225a566fc57ff203f82cb1cb56b902a7f5,Gradient Local Auto-Correlations and Extreme Learning Machine for Depth-Based Activity Recognition,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+9e504d225a566fc57ff203f82cb1cb56b902a7f5,Gradient Local Auto-Correlations and Extreme Learning Machine for Depth-Based Activity Recognition,Changzhou University,"Changzhou University, Changzhou, China","1 Gehu Middle Rd, Wujin Qu, Changzhou Shi, Jiangsu Sheng, China",31.68423700,119.95514100,edu,
+9e504d225a566fc57ff203f82cb1cb56b902a7f5,Gradient Local Auto-Correlations and Extreme Learning Machine for Depth-Based Activity Recognition,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+9e1b3cf334aead8d2c29747f6ee7d1291dd83708,Netizen-Style Commenting on Fashion Photos: Dataset and Diversity Measures,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+9ef9046cc26946acedda3f515d9149a76e19cd6e,A Unified Multi-Faceted Video Summarization System,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
9ed4ad41cbad645e7109e146ef6df73f774cd75d,RPM: Random Points Matching for Pair wise Face-Similarity,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
9ed4ad41cbad645e7109e146ef6df73f774cd75d,RPM: Random Points Matching for Pair wise Face-Similarity,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+9e5378e7b336c89735d3bb15cf67eff96f86d39a,Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+9e5378e7b336c89735d3bb15cf67eff96f86d39a,Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+9e1a96e0fc5d8867e82e6262a8d9499b3ae806e5,Spoofing 2D face recognition systems with 3D masks,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
9e182e0cd9d70f876f1be7652c69373bcdf37fb4,Talking Face Generation by Adversarially Disentangled Audio-Visual Representation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
9e8d87dc5d8a6dd832716a3f358c1cdbfa97074c,What makes an image popular?,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+9e4cd22ab92adcd74014709167b6cbb97baa3d1c,BEAR MOUSE DOG TIGER Compatibility function : Classification model : Inference function : Objective function : Optimization TRAINING TESTING Seen Objects Seen Labels Unseen Objects Unseen Labels Feature Embedding Semantic Embedding Feature Extraction Semantic Extraction,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+9e8b20ac34f560ae12bb51f3e3713ea755d36c85,Learning to Write Stylized Chinese Characters by Reading a Handful of Examples,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
044d9a8c61383312cdafbcc44b9d00d650b21c70,300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
044d9a8c61383312cdafbcc44b9d00d650b21c70,300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
044d9a8c61383312cdafbcc44b9d00d650b21c70,300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
04f0292d9a062634623516edd01d92595f03bd3f,Distribution-based iterative pairwise classification of emotions in the wild using LGBP-TOP,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
04f0292d9a062634623516edd01d92595f03bd3f,Distribution-based iterative pairwise classification of emotions in the wild using LGBP-TOP,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
04f0292d9a062634623516edd01d92595f03bd3f,Distribution-based iterative pairwise classification of emotions in the wild using LGBP-TOP,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+041115cb5509466f7449451709387268a008aba2,Teaching Machines to Understand Baseball Games: Large-Scale Baseball Video Database for Multiple Video Understanding Tasks,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+04aca8c96971acce8ac4303bf514e83c87e692ce,A hand shape recognizer from simple sketches,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+044e0d86e2db70d4c0b767bf0994913e90e105e3,Answer-Type Prediction for Visual Question Answering,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
04522dc16114c88dfb0ebd3b95050fdbd4193b90,Minimum Bayes error features for visual recognition by sequential feature selection and extraction,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
04522dc16114c88dfb0ebd3b95050fdbd4193b90,Minimum Bayes error features for visual recognition by sequential feature selection and extraction,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
0486214fb58ee9a04edfe7d6a74c6d0f661a7668,Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
043efe5f465704ced8d71a067d2b9d5aa5b59c29,Occlusion-aware 3D Morphable Face Models,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+040ec1bab630b4609cb55c3e0e2dbd4c3064d8c4,Detection of social signals for recognizing engagement in human-robot interaction,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+04b2cddc8e04a02d685d6476f00d0d25d4dd5e72,The Scope and Limits of Simulation in Cognitive Models,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+04b2cddc8e04a02d685d6476f00d0d25d4dd5e72,The Scope and Limits of Simulation in Cognitive Models,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
04661729f0ff6afe4b4d6223f18d0da1d479accf,From Facial Parts Responses to Face Detection: A Deep Learning Approach,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
04661729f0ff6afe4b4d6223f18d0da1d479accf,From Facial Parts Responses to Face Detection: A Deep Learning Approach,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+043e7a08398b1d634fa2bf3ddb81942686effb30,Improved 3D Model Search for Facial Feature Location and Pose Estimation in 2D images,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+0493b82694d8754582bf54802c4dbf64586ab9c4,Symmetry-Factored Statistical Modelling of Craniofacial Shape,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+0471eb1882bb7f538b40a0f76c7073992e7bf213,X-GANs: Image Reconstruction Made Easy for Extreme Cases,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+04964e2697778dc843671c7764f0f912e46991ca,Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+047cd38ebf2ce7eeb885f654ed64d405a0421fab,Face Detection Using Statistical and Multi-Resolution Texture Features,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+04b22b008669fa981602c7723b44cb4a5cb2d480,Facial responsiveness of psychopaths to the emotional expressions of others,Ulm University,Ulm University,"HNU, John-F.-Kennedy-Straße, Vorfeld, Wiley, Neu-Ulm, Landkreis Neu-Ulm, Schwaben, Bayern, 89231, Deutschland",48.38044335,10.01010115,edu,
04c2cda00e5536f4b1508cbd80041e9552880e67,Hipster Wars: Discovering Elements of Fashion Styles,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
04c2cda00e5536f4b1508cbd80041e9552880e67,Hipster Wars: Discovering Elements of Fashion Styles,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
04ff69aa20da4eeccdabbe127e3641b8e6502ec0,Sequential Face Alignment via Person-Specific Modeling in the Wild,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
04ff69aa20da4eeccdabbe127e3641b8e6502ec0,Sequential Face Alignment via Person-Specific Modeling in the Wild,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
04ff69aa20da4eeccdabbe127e3641b8e6502ec0,Sequential Face Alignment via Person-Specific Modeling in the Wild,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+04ef0b28534cdac18a2059f73ecfe940d6bed277,Non-Linear Stationary Subspace Analysis -0.09cm with Application to Video Classification,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
046a694bbb3669f2ff705c6c706ca3af95db798c,Conditional Convolutional Neural Network for Modality-Aware Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
046a694bbb3669f2ff705c6c706ca3af95db798c,Conditional Convolutional Neural Network for Modality-Aware Face Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+0443b7a4372fb7bdcd69a0b55945f937c8b7d35b,Semi-supervised Coupled Dictionary Learning for Person Re-identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+0443b7a4372fb7bdcd69a0b55945f937c8b7d35b,Semi-supervised Coupled Dictionary Learning for Person Re-identification,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+040ab6a70bef710b61e3b6a183c2d81947ac8f88,"4D Cardiff Conversation Database (4D CCDb): a 4D database of natural, dyadic conversations",Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+048ff69503ea4937f10f69b1f29f655594253246,Isolating Sources of Disentanglement in Variational Autoencoders,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+0419726a00e16ea89868792ca94f5b1b262c5597,An analytical formulation of global occlusion reasoning for multi-target tracking,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
046865a5f822346c77e2865668ec014ec3282033,Discovering informative social subgraphs and predicting pairwise relationships from group photos,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+04df36ea27f14f96bb1b33d76103d1dee7c6e0ca,Blur invariant pattern recognition and registration in the Fourier domain,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+04eda7eee3e0282de50e54554f50870dd17defa1,How Hard Can It Be? Estimating the Difficulty of Visual Search in an Image,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+04be04189fe77a3bbd108b8c0ef78d63b0bd5118,EDeN: Ensemble of Deep Networks for Vehicle Classification,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
047bb1b1bd1f19b6c8d7ee7d0324d5ecd1a3efff,Unsupervised Training for 3D Morphable Model Regression,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
047bb1b1bd1f19b6c8d7ee7d0324d5ecd1a3efff,Unsupervised Training for 3D Morphable Model Regression,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+0496d10bcdd29395846d05c2de711db62be10630,Grouplet: A structured image representation for recognizing human and object interactions,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+0480b71244b59ed13cfe844c8bac8883a0c40573,Efficient Second Order Multi-Target Tracking with Exclusion Constraints,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+0480b71244b59ed13cfe844c8bac8883a0c40573,Efficient Second Order Multi-Target Tracking with Exclusion Constraints,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+6a4ac9ac5ddfeeb8adcff1795eccd39de25a00c4,Composite Feature-Based Face Detection Using Skin Color Modeling and SVM Classification,Utah State University,Utah State University,"Utah State University, Champ Drive, Logan, Cache County, Utah, 84322, USA",41.74115040,-111.81223090,edu,
+6a4ac9ac5ddfeeb8adcff1795eccd39de25a00c4,Composite Feature-Based Face Detection Using Skin Color Modeling and SVM Classification,Utah State University,Utah State University,"Utah State University, Champ Drive, Logan, Cache County, Utah, 84322, USA",41.74115040,-111.81223090,edu,
+6ab6c1334c70db6e7705455a2db359e8d83042f9,Rationale for a 3D heterogeneous multi-core processor,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
6a67e6fbbd9bcd3f724fe9e6cecc9d48d1b6ad4d,Cooperative Learning with Visual Attributes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6a2b83c4ae18651f1a3496e48a35b0cd7a2196df,Top Rank Supervised Binary Coding for Visual Search,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
6a2b83c4ae18651f1a3496e48a35b0cd7a2196df,Top Rank Supervised Binary Coding for Visual Search,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+6aaa77e241fe55ae0c4ad281e27886ea778f9e23,F-Formation Detection: Individuating Free-Standing Conversational Groups in Images,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
6a5fe819d2b72b6ca6565a0de117c2b3be448b02,Supervised and Projected Sparse Coding for Image Classification,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
6afeb764ee97fbdedfa8f66810dfc22feae3fa1f,Robust Principal Component Analysis with Complex Noise,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
6afeb764ee97fbdedfa8f66810dfc22feae3fa1f,Robust Principal Component Analysis with Complex Noise,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
6aa61d28750629febe257d1cb69379e14c66c67f,Kernel Hebbian Algorithm for Iterative Kernel Principal Component Analysis,Max Planck Institute for Biological Cybernetics,Max Planck Institute for Biological Cybernetics,"Max-Planck-Institut für Biologische Kybernetik, 8, Max-Planck-Ring, Max-Planck-Institut, Wanne, Tübingen, Landkreis Tübingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72076, Deutschland",48.53691250,9.05922533,edu,
+6ae9f4dc7433ba3433b39ee932b22fd57922c2ee,Using Facially Expressive Robots to Calibrate Clinical Pain Perception,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+6ae9f4dc7433ba3433b39ee932b22fd57922c2ee,Using Facially Expressive Robots to Calibrate Clinical Pain Perception,University of Louisville,University of Louisville,"University of Louisville, South Brook Street, Louisville, Jefferson County, Kentucky, 40208, USA",38.21675650,-85.75725023,edu,
6ae96f68187f1cdb9472104b5431ec66f4b2470f,Improving Task Performance in an Affect-mediated Computing System,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6ae96f68187f1cdb9472104b5431ec66f4b2470f,Improving Task Performance in an Affect-mediated Computing System,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6ae4f3ff909ae6171ad54e8c5d942d1c83706e45,Multi-Label Zero-Shot Learning with Structured Knowledge Graphs,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+6ae4f3ff909ae6171ad54e8c5d942d1c83706e45,Multi-Label Zero-Shot Learning with Structured Knowledge Graphs,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6a4419ce2338ea30a570cf45624741b754fa52cb,Statistical transformer networks: learning shape and appearance models via self supervision,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
6af65e2a1eba6bd62843e7bf717b4ccc91bce2b8,A New Weighted Sparse Representation Based on MSLBP and Its Application to Face Recognition,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
6a657995b02bc9dee130701138ea45183c18f4ae,The Timing of Facial Motion in posed and Spontaneous Smiles,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
@@ -333,11 +966,32 @@ 6ab33fa51467595f18a7a22f1d356323876f8262,Ordinal hyperplanes ranker with cost sensitivities for age estimation,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
6ab33fa51467595f18a7a22f1d356323876f8262,Ordinal hyperplanes ranker with cost sensitivities for age estimation,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
6ab33fa51467595f18a7a22f1d356323876f8262,Ordinal hyperplanes ranker with cost sensitivities for age estimation,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+6ab30c67fa966b6bcee61de6294245e2dd8604d8,3D Face Recognition Based on G-H Shape Variation,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
6a2ac4f831bd0f67db45e7d3cdaeaaa075e7180a,Excitation Dropout: Encouraging Plasticity in Deep Neural Networks,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+6a8d382d34143143e98b040e006f473bd450502d,Object Relation Detection Based on One-shot Learning,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
6a4ebd91c4d380e21da0efb2dee276897f56467a,HOG active appearance models,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
+6a7efb6f3471a2aff702d5e8080e066636335de4,Sparsely Grouped Multi-Task Generative Adversarial Networks for Facial Attribute Manipulation,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+6a7efb6f3471a2aff702d5e8080e066636335de4,Sparsely Grouped Multi-Task Generative Adversarial Networks for Facial Attribute Manipulation,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+6a7efb6f3471a2aff702d5e8080e066636335de4,Sparsely Grouped Multi-Task Generative Adversarial Networks for Facial Attribute Manipulation,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+6a7efb6f3471a2aff702d5e8080e066636335de4,Sparsely Grouped Multi-Task Generative Adversarial Networks for Facial Attribute Manipulation,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+6a7efb6f3471a2aff702d5e8080e066636335de4,Sparsely Grouped Multi-Task Generative Adversarial Networks for Facial Attribute Manipulation,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+32c801cb7fbeb742edfd94cccfca4934baec71da,Multi-source Multi-scale Counting in Extremely Dense Crowd Images,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+32c801cb7fbeb742edfd94cccfca4934baec71da,Multi-source Multi-scale Counting in Extremely Dense Crowd Images,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
32d8e555441c47fc27249940991f80502cb70bd5,Machine Learning Models that Remember Too Much,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+322eff0dbf5d7dc18688be29ad5fd7eb8c8d6d54,SLTP: A Fast Descriptor for People Detection in Depth Images,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+322eff0dbf5d7dc18688be29ad5fd7eb8c8d6d54,SLTP: A Fast Descriptor for People Detection in Depth Images,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
3294e27356c3b1063595885a6d731d625b15505a,Illumination Face Spaces Are Idiosyncratic,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+32ac4e5a8dee203c0b99e15484893fd9d62de43a,Hallucinating Faces: Global Linear Modal Based Super-Resolution and Position Based Residue Compensation,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+320fa825e86f3b74ba3b3ebaef14e1186784f1ec,Exploit the Unknown Gradually : One-Shot Video-Based Person Re-Identification by Stepwise Learning,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+320fa825e86f3b74ba3b3ebaef14e1186784f1ec,Exploit the Unknown Gradually : One-Shot Video-Based Person Re-Identification by Stepwise Learning,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+32b7b671c786aa74f7d8f9817b12b3a59c0b84c2,A Bayesian Model of Grounded Color Semantics,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+32b7b671c786aa74f7d8f9817b12b3a59c0b84c2,A Bayesian Model of Grounded Color Semantics,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+32cd02519928aa91dca18074778a59b2cba19765,Forecasting crowd dynamics through coarse-grained data analysis,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+32cd02519928aa91dca18074778a59b2cba19765,Forecasting crowd dynamics through coarse-grained data analysis,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+321d1f8d13075275b207dd048e9b655aa8846d57,Thermal Tracking of Sports Players,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
3240c9359061edf7a06bfeb7cc20c103a65904c2,PPR-FCN: Weakly Supervised Visual Relation Detection via Parallel Pairwise R-FCN,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+3210666306517c4ef9a4c1a4463c728b0e3aeb72,Angle Tree: Nearest Neighbor Search in High Dimensions with Low Intrinsic Dimensionality,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+324608bf8fecc064bc491da21291465ab42fa6b6,Matching-CNN meets KNN: Quasi-parametric human parsing,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
32ecbbd76fdce249f9109594eee2d52a1cafdfc7,Object Specific Deep Learning Feature and Its Application to Face Detection,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
32ecbbd76fdce249f9109594eee2d52a1cafdfc7,Object Specific Deep Learning Feature and Its Application to Face Detection,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
32ecbbd76fdce249f9109594eee2d52a1cafdfc7,Object Specific Deep Learning Feature and Its Application to Face Detection,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
@@ -345,74 +999,219 @@ 32c20afb5c91ed7cdbafb76408c3a62b38dd9160,Viewing Real-World Faces in 3D,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
32a40c43a9bc1f1c1ed10be3b9f10609d7e0cb6b,Lighting Aware Preprocessing for Face Recognition across Varying Illumination,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
32a40c43a9bc1f1c1ed10be3b9f10609d7e0cb6b,Lighting Aware Preprocessing for Face Recognition across Varying Illumination,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+325723a7fa69f9976feeab5ba9abd3c11e3f7c80,Beyond Textures: Learning from Multi-domain Artistic Images for Arbitrary Style Transfer,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+3283477ebd49488e1f3c78e6e828678ea2bb815b,Cauchy Principal Component Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+3239f9fb3c11cc29c65664254133beb339f13f40,Low-Resolution Vision for Autonomous Mobile Robots,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+322a7dad274f440a92548faa8f2b2be666b2d01f,Pyramid Scene Parsing Network,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+322a7dad274f440a92548faa8f2b2be666b2d01f,Pyramid Scene Parsing Network,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
329394480fc5e9e96de4250cc1a2b060c3677c94,Improved Dense Trajectory with Cross Streams,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
329394480fc5e9e96de4250cc1a2b060c3677c94,Improved Dense Trajectory with Cross Streams,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
329394480fc5e9e96de4250cc1a2b060c3677c94,Improved Dense Trajectory with Cross Streams,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+32eeba2ff1ef4259de7802c8ee8cecb6d6c581a3,Isometric Projection,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+32eeba2ff1ef4259de7802c8ee8cecb6d6c581a3,Isometric Projection,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
32c9ebd2685f522821eddfc19c7c91fd6b3caf22,Finding Correspondence from Multiple Images via Sparse and Low-Rank Decomposition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
32c9ebd2685f522821eddfc19c7c91fd6b3caf22,Finding Correspondence from Multiple Images via Sparse and Low-Rank Decomposition,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
+328bc4d5495723f9a1037660b5d9c1176713bf24,Unimpaired Attentional Disengagement and Social Orienting in Children With Autism,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+32f37cbc7806c37e8b618d935800bdcd6e7108cc,Rhythmic Gait Signatures from Videowithoutmotion Capture,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+32f37cbc7806c37e8b618d935800bdcd6e7108cc,Rhythmic Gait Signatures from Videowithoutmotion Capture,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+324c91551c3cde44bbcb9d97bc14db7ca6d31850,"Infancy and autism: progress, prospects, and challenges.",University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
3270b2672077cc345f188500902eaf7809799466,Multibiometric Systems: Fusion Strategies and Template Security,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+326b9c8391e89f5bd032aebd1b65e925083c269b,Automatic Pain Intensity Estimation with Heteroscedastic Conditional Ordinal Random Fields,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+326b9c8391e89f5bd032aebd1b65e925083c269b,Automatic Pain Intensity Estimation with Heteroscedastic Conditional Ordinal Random Fields,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+326b9c8391e89f5bd032aebd1b65e925083c269b,Automatic Pain Intensity Estimation with Heteroscedastic Conditional Ordinal Random Fields,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+323f9ae6bdd2a4e4dce4168f7f7e19c70585c9b5,Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
321c8ba38db118d8b02c0ba209be709e6792a2c7,Learn to Combine Multiple Hypotheses for Accurate Face Alignment,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+3213390558a08e35222eec6fb028c8cfaa0c80c2,Non-sparse linear representations for visual tracking with online reservoir metric learning,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+3209e3af49b7b9c253100b7a39fcf8d013fe36a4,Coherence Constraints in Facial Expression Recognition,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+3209e3af49b7b9c253100b7a39fcf8d013fe36a4,Coherence Constraints in Facial Expression Recognition,University of Siena,University of Siena,"大學 University, 澤祥街 Chak Cheung Street, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.41338620,114.21005800,edu,
+3209e3af49b7b9c253100b7a39fcf8d013fe36a4,Coherence Constraints in Facial Expression Recognition,University of Siena,University of Siena,"大學 University, 澤祥街 Chak Cheung Street, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.41338620,114.21005800,edu,
+32c7e4f6d7848676922705484a00c94dac803af9,Learning Articulated Object Models from Language and Vision,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+321dc2958e7874a3896e7df96213cd808d3b2b27,Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+321dc2958e7874a3896e7df96213cd808d3b2b27,Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+321dc2958e7874a3896e7df96213cd808d3b2b27,Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+32799cee51933ac4e1999358bad64817985826d7,Player Experience Extraction from Gameplay Video,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
329d58e8fb30f1bf09acb2f556c9c2f3e768b15c,Leveraging Intra and Inter-Dataset Variations for Robust Face Alignment,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
329d58e8fb30f1bf09acb2f556c9c2f3e768b15c,Leveraging Intra and Inter-Dataset Variations for Robust Face Alignment,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+32c45df9e11e6751bcea1b928f398f6c134d22c6,Towards Unified Object Detection and Semantic Segmentation,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+35b9f09ed66955765dc7703e9cada605948c71d0,Similarity Measure Using Local Phase Features and Its Application to Biometric Recognition,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
353b6c1f431feac6edde12b2dde7e6e702455abd,Multi-scale Patch Based Collaborative Representation for Face Recognition with Margin Distribution Optimization,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
353b6c1f431feac6edde12b2dde7e6e702455abd,Multi-scale Patch Based Collaborative Representation for Face Recognition with Margin Distribution Optimization,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+35f2541ef1b5dc2df8283143b1b98c6309ed47dd,View Based Approach to Forensic Face Recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
350da18d8f7455b0e2920bc4ac228764f8fac292,Automatic Detecting Neutral Face for Face Authentication and Facial Expression Analysis,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+350af77e01e78e8e3534f42b80b5dd35a602e73c,Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+35fc0b28d0d674b28dd625d170bc641a36b17318,CSI: Composite Statistical Inference Techniques for Semantic Segmentation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+35fc0b28d0d674b28dd625d170bc641a36b17318,CSI: Composite Statistical Inference Techniques for Semantic Segmentation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+35fc0b28d0d674b28dd625d170bc641a36b17318,CSI: Composite Statistical Inference Techniques for Semantic Segmentation,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+35498b80ee457e409c0962e03a6e170a917c83af,Look into Person: Self-Supervised Structure-Sensitive Learning and a New Benchmark for Human Parsing,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+35498b80ee457e409c0962e03a6e170a917c83af,Look into Person: Self-Supervised Structure-Sensitive Learning and a New Benchmark for Human Parsing,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+35700f9a635bd3c128ab41718b040a0c28d6361a,DeepGait: A Learning Deep Convolutional Representation for View-Invariant Gait Recognition Using Joint Bayesian,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+35700f9a635bd3c128ab41718b040a0c28d6361a,DeepGait: A Learning Deep Convolutional Representation for View-Invariant Gait Recognition Using Joint Bayesian,Zhejiang University of Technology,Zhejiang University of Technology,"浙江工业大学, 潮王路, 朝晖街道, 杭州市 Hangzhou, 浙江省, 310014, 中国",30.29315340,120.16204580,edu,
+3548cb9ee54bd4c8b3421f1edd393da9038da293,(Unseen) event recognition via semantic compositionality,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+3548415e23b536b9e41aa3d92c18880f38a1d80c,Superpixel-Based Feature for Aerial Image Scene Recognition,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+3548415e23b536b9e41aa3d92c18880f38a1d80c,Superpixel-Based Feature for Aerial Image Scene Recognition,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+3548415e23b536b9e41aa3d92c18880f38a1d80c,Superpixel-Based Feature for Aerial Image Scene Recognition,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
35f03f5cbcc21a9c36c84e858eeb15c5d6722309,Placing Broadcast News Videos in their Social Media Context Using Hashtags,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
356b431d4f7a2a0a38cf971c84568207dcdbf189,Recognize complex events from static images by fusing deep channels,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
356b431d4f7a2a0a38cf971c84568207dcdbf189,Recognize complex events from static images by fusing deep channels,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+35cdd4df9f039f475247bf03fdcc605e40683dce,Eye Detection and Face Recognition Using Evolutionary Computation,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+351c7e6c2e2fd894626be20a480fa5749e016dc7,LinkNet: Exploiting encoder representations for efficient semantic segmentation,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+351c7e6c2e2fd894626be20a480fa5749e016dc7,LinkNet: Exploiting encoder representations for efficient semantic segmentation,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+35ab5978376ea8113ff476076f18a677b4136d92,RT-GENE: Real-Time Eye Gaze Estimation in Natural Environments,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+35cbf049074382e757bbfc8cc45ccbe467833a7a,A simple neural network module for relational reasoning,"London, United Kingdom","London, United Kingdom","London, Greater London, England, SW1A 2DU, UK",51.50732190,-0.12764740,edu,
+3573dd5b2982e1406f2ef6a1680149d4f9bd95d1,LearningWord Embeddings for Low-resource Languages by PU Learning,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
+3573dd5b2982e1406f2ef6a1680149d4f9bd95d1,LearningWord Embeddings for Low-resource Languages by PU Learning,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62,Exploring Models and Data for Image Question Answering,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+35f6e4a61bb3541348300be3347ab56d0be75744,Tinkering Under The Hood: Interactive Zero-Shot Learning with Pictorial Classifiers,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+35ec869dd0637c933d35ab823202c13b9b5d9aad,Effective Community Search for Large Attributed Graphs,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
35f921def890210dda4b72247849ad7ba7d35250,Exemplar-Based Graph Matching for Robust Facial Landmark Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+35c473bae9d146072625cc3d452c8f6b84c8cc47,ZoomNet: Deep Aggregation Learning for High-Performance Small Pedestrian Detection,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+35c473bae9d146072625cc3d452c8f6b84c8cc47,ZoomNet: Deep Aggregation Learning for High-Performance Small Pedestrian Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+359fda4ff19dbd3634b867fbb3ef3cb6812691c5,Temporal Perception and Prediction in Ego-Centric Video,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+35d7b5738350a1bbfd8d7a591433d1664f909009,VisemeNet: Audio-Driven Animator-Centric Speech Animation,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+35d7b5738350a1bbfd8d7a591433d1664f909009,VisemeNet: Audio-Driven Animator-Centric Speech Animation,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+35d7b5738350a1bbfd8d7a591433d1664f909009,VisemeNet: Audio-Driven Animator-Centric Speech Animation,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+35d7b5738350a1bbfd8d7a591433d1664f909009,VisemeNet: Audio-Driven Animator-Centric Speech Animation,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+35d7b5738350a1bbfd8d7a591433d1664f909009,VisemeNet: Audio-Driven Animator-Centric Speech Animation,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+35d7b5738350a1bbfd8d7a591433d1664f909009,VisemeNet: Audio-Driven Animator-Centric Speech Animation,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
35ec9b8811f2d755c7ad377bdc29741b55b09356,"Efficient, Robust and Accurate Fitting of a 3D Morphable Model",University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+35b9af6057801fb2f28881840c8427c9cf648757,Deep Reinforcement Learning Attention Selection For Person Re-Identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+35472424eb5662d05928017942c32f4537cb5d5c,Robust object recognition via third-party collaborative representation,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+352fbe52e9bcbcf8625a408dfca36b30460c8251,3D Facial Landmark Detection & Face Registration A 3D Facial Landmark Model & 3D Local Shape Descriptors Approach,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+3502544f66da8fdeda0daf8f6671a16c52e8e353,Learning to Reconstruct Shapes from Unseen Classes,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+3502544f66da8fdeda0daf8f6671a16c52e8e353,Learning to Reconstruct Shapes from Unseen Classes,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+3502544f66da8fdeda0daf8f6671a16c52e8e353,Learning to Reconstruct Shapes from Unseen Classes,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+3502544f66da8fdeda0daf8f6671a16c52e8e353,Learning to Reconstruct Shapes from Unseen Classes,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+3502544f66da8fdeda0daf8f6671a16c52e8e353,Learning to Reconstruct Shapes from Unseen Classes,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+3502544f66da8fdeda0daf8f6671a16c52e8e353,Learning to Reconstruct Shapes from Unseen Classes,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
3505c9b0a9631539e34663310aefe9b05ac02727,A Joint Discriminative Generative Model for Deformable Model Construction and Classification,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
3505c9b0a9631539e34663310aefe9b05ac02727,A Joint Discriminative Generative Model for Deformable Model Construction and Classification,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
3506518d616343d3083f4fe257a5ee36b376b9e1,Unsupervised Domain Adaptation for Personalized Facial Emotion Recognition,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
3506518d616343d3083f4fe257a5ee36b376b9e1,Unsupervised Domain Adaptation for Personalized Facial Emotion Recognition,University of Perugia,University of Perugia,"Caffe Perugia, 2350, Health Sciences Mall, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.26224210,-123.24500520,edu,
3506518d616343d3083f4fe257a5ee36b376b9e1,Unsupervised Domain Adaptation for Personalized Facial Emotion Recognition,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+356a0c92b61a56699211d5c5d9e4d78c9373e819,Multiple Object Tracking Using Local Motion Patterns,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+35f84e0020c26715691825594e2cf5553467a0e4,Fast Bilateral Solver for Semantic Video Segmentation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+35f84e0020c26715691825594e2cf5553467a0e4,Fast Bilateral Solver for Semantic Video Segmentation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+3514f66f155c271981a734f1523572edcd8fd10e,A complementary local feature descriptor for face identification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+3514f66f155c271981a734f1523572edcd8fd10e,A complementary local feature descriptor for face identification,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
+35140ebfa0b6d75fd096aed72d40b16ea6a3828b,Support Discrimination Dictionary Learning for Image Classification,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+35140ebfa0b6d75fd096aed72d40b16ea6a3828b,Support Discrimination Dictionary Learning for Image Classification,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+35140ebfa0b6d75fd096aed72d40b16ea6a3828b,Support Discrimination Dictionary Learning for Image Classification,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+69ad645516fa5cd4cd45fc217edcbf83bc0f65be,Multi-camera People Tracking with Hierarchical Likelihood Grids,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+69556424ec4daaa2b932790dba7bc8b826abc574,"Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow","University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
6964af90cf8ac336a2a55800d9c510eccc7ba8e1,Temporal Relational Reasoning in Videos,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+692bc33f7466278900dd73f7f40c563f72cb6754,Fourth-person Captioning: Describing Daily Events by Uni-supervised and Tri-regularized Training,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+692bc33f7466278900dd73f7f40c563f72cb6754,Fourth-person Captioning: Describing Daily Events by Uni-supervised and Tri-regularized Training,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+692bc33f7466278900dd73f7f40c563f72cb6754,Fourth-person Captioning: Describing Daily Events by Uni-supervised and Tri-regularized Training,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+694d831156293642e63103cd1921eed37e77a68f,Detection of Multiple Pedestrians using Motion Information and Adaboost Algorithm,Yeungnam University,Yeungnam University,"영남대, 대학로, 부적리, 경산시, 경북, 712-749, 대한민국",35.83654030,128.75343090,edu,
+69291d44eb4fdf848a06defe99a74cb75026c70b,Automatic Detection of a Driver's Complex Mental States,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+69291d44eb4fdf848a06defe99a74cb75026c70b,Automatic Detection of a Driver's Complex Mental States,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+690f5d35489c63ec7309b9e4d77c929815065257,Complementary effects of gaze direction and early saliency in guiding fixations during free viewing.,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+690f5d35489c63ec7309b9e4d77c929815065257,Complementary effects of gaze direction and early saliency in guiding fixations during free viewing.,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+690f5d35489c63ec7309b9e4d77c929815065257,Complementary effects of gaze direction and early saliency in guiding fixations during free viewing.,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+690f5d35489c63ec7309b9e4d77c929815065257,Complementary effects of gaze direction and early saliency in guiding fixations during free viewing.,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
69adbfa7b0b886caac15ebe53b89adce390598a3,Face hallucination using cascaded super-resolution and identity priors,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
69adbfa7b0b886caac15ebe53b89adce390598a3,Face hallucination using cascaded super-resolution and identity priors,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+693e0da15094071de5eebd2f36f8b4023f91f161,Can facial metrology predict gender?,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
69d29012d17cdf0a2e59546ccbbe46fa49afcd68,Subspace clustering of dimensionality-reduced data,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+69b5dd48d0f6f95f4dba5ad8b35b51de446b632f,MGGAN: Solving Mode Collapse using Manifold Guided Training,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+697e6552326bc04a80b510f91e3a83c23159fa4b,Are You Talking to Me? Detecting Attention in First-Person Interactions,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
69a68f9cf874c69e2232f47808016c2736b90c35,Learning Deep Representation for Imbalanced Classification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
69a68f9cf874c69e2232f47808016c2736b90c35,Learning Deep Representation for Imbalanced Classification,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
69a68f9cf874c69e2232f47808016c2736b90c35,Learning Deep Representation for Imbalanced Classification,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+696bfa059fcc459c30af21c84d116ad77fb11197,Isoradius Contours: New Representations and Techniques for 3D Face Registration and Matching,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+6926676e0b710717e373926e1302bfb441c5c503,Fisher Non-negative Matrix Factorization with Pairwise Weighting,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
69b18d62330711bfd7f01a45f97aaec71e9ea6a5,M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice,SUNY Polytechnic Institute,State University of New York Polytechnic Institute,"State University of New York Polytechnic Institute, 100, Seymour Road, Maynard, Town of Marcy, Oneida County, New York, 13502, USA",43.13800205,-75.22943591,edu,
+6965de4410921cff014a48b071f2c4c52c1da0fd,Human object estimation via backscattered radio frequency signal,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+6965de4410921cff014a48b071f2c4c52c1da0fd,Human object estimation via backscattered radio frequency signal,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+69a7c8bca699ee4100fbe6a83b72459c132a6f10,Resource Aware Person Re-identification across Multiple Resolutions,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
6993bca2b3471f26f2c8a47adfe444bfc7852484,The Do’s and Don’ts for CNN-Based Face Verification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+69b647afe6526256a93033eac14ce470204e7bae,Training Deep Neural Networks via Direct Loss Minimization,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+69b647afe6526256a93033eac14ce470204e7bae,Training Deep Neural Networks via Direct Loss Minimization,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
69eb6c91788e7c359ddd3500d01fb73433ce2e65,CAMGRAPH: Distributed Graph Processing for Camera Networks,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
691964c43bfd282f6f4d00b8b0310c554b613e3b,Temporal Hallucinating for Action Recognition with Few Still Images,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+69abd57a49c6b430a83d9a1e09dce5a347c9c63e,Face Recognition from Multiple Images per Subject,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+69abd57a49c6b430a83d9a1e09dce5a347c9c63e,Face Recognition from Multiple Images per Subject,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+69c2b7565e080740e2bdb664e6b00fd760609889,Enriched Long-Term Recurrent Convolutional Network for Facial Micro-Expression Recognition,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+69c2b7565e080740e2bdb664e6b00fd760609889,Enriched Long-Term Recurrent Convolutional Network for Facial Micro-Expression Recognition,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+69c2b7565e080740e2bdb664e6b00fd760609889,Enriched Long-Term Recurrent Convolutional Network for Facial Micro-Expression Recognition,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
69c2ac04693d53251500557316c854a625af84ee,"50 years of biometric research: Accomplishments, challenges, and opportunities",Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+696d114f57aa6798a5d16aaf847a78942ab9949f,Efficient Similarity Derived from Kernel-Based Transition Probability,National Institute of Advanced Industrial Science and Technology,National Institute of Advanced Industrial Science and Technology,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+69870df2c7a6d2e2bfef201968aecd24eb18794d,We are Humor Beings: Understanding and Predicting Visual Humor,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+69522bd70f1c64e9073753ccf335382be5aa1cd9,Geometric Feature Based Age Classification Using Facial Images,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+69522bd70f1c64e9073753ccf335382be5aa1cd9,Geometric Feature Based Age Classification Using Facial Images,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
69fb98e11df56b5d7ec7d45442af274889e4be52,Harnessing the Deep Net Object Models for Enhancing Human Action Recognition,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
69fb98e11df56b5d7ec7d45442af274889e4be52,Harnessing the Deep Net Object Models for Enhancing Human Action Recognition,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+69e054acbf09a4bebac1c4b14c3f6a1ac6d199b0,Can feature-based inductive transfer learning help person re-identification?,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+69e054acbf09a4bebac1c4b14c3f6a1ac6d199b0,Can feature-based inductive transfer learning help person re-identification?,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
3c78b642289d6a15b0fb8a7010a1fb829beceee2,Analysis of Facial Dynamics Using a Tensor Framework,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
3c78b642289d6a15b0fb8a7010a1fb829beceee2,Analysis of Facial Dynamics Using a Tensor Framework,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+3c1e1961db0f0a351d5a4e21cd30bcbd9f88be57,Discovering states and transformations in image collections,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
3cb488a3b71f221a8616716a1fc2b951dd0de549,Facial Age Estimation by Adaptive Label Distribution Learning,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+3cf1f89d73ca4b25399c237ed3e664a55cd273a2,Face Sketch Matching via Coupled Deep Transform Learning,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+3c84e2ed018dd1d971b526f87e9d7c1f08e6230f,Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+3c84e2ed018dd1d971b526f87e9d7c1f08e6230f,Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
3c563542db664321aa77a9567c1601f425500f94,TV-GAN: Generative Adversarial Network Based Thermal to Visible Face Recognition,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+3c8cf97f00cd8b4303eccc4134fa79b15cc3d564,Data-driven image captioning via salient region discovery,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
+3c8cf97f00cd8b4303eccc4134fa79b15cc3d564,Data-driven image captioning via salient region discovery,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+3ce4a61ada2720713535d7262e8229b33c5df79f,Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+3cb52304ec2aa2fd4437ce0e170a0b16409c0cdb,3D Segmentation in CT Imagery with Conditional Random Fields and Histograms of Oriented Gradients,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
3c6cac7ecf546556d7c6050f7b693a99cc8a57b3,Robust facial landmark detection in the wild,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
3c6cac7ecf546556d7c6050f7b693a99cc8a57b3,Robust facial landmark detection in the wild,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
3c57e28a4eb463d532ea2b0b1ba4b426ead8d9a0,Defeating Image Obfuscation with Deep Learning,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
3cd9b0a61bdfa1bb8a0a1bf0369515a76ecd06e3,Distance Metric Learning with Eigenvalue Optimization,University of Exeter,University of Exeter,"University of Exeter, Stocker Road, Exwick, Exeter, Devon, South West England, England, EX4 4QN, UK",50.73693020,-3.53647672,edu,
3cd9b0a61bdfa1bb8a0a1bf0369515a76ecd06e3,Distance Metric Learning with Eigenvalue Optimization,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+3cea3aba77649d718991d0cb30135887267c11e8,Adversarial Attack Type I: Generating False Positives,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+3cea3aba77649d718991d0cb30135887267c11e8,Adversarial Attack Type I: Generating False Positives,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+3cea3aba77649d718991d0cb30135887267c11e8,Adversarial Attack Type I: Generating False Positives,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+3cea3aba77649d718991d0cb30135887267c11e8,Adversarial Attack Type I: Generating False Positives,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+3cfc8c00d390abe5f94ba7a1251e085a794b35bb,A Convex Optimization Framework for Active Learning,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+3cfc8c00d390abe5f94ba7a1251e085a794b35bb,A Convex Optimization Framework for Active Learning,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+3cfc8c00d390abe5f94ba7a1251e085a794b35bb,A Convex Optimization Framework for Active Learning,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
3c97c32ff575989ef2869f86d89c63005fc11ba9,Face Detection with the Faster R-CNN,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
3c97c32ff575989ef2869f86d89c63005fc11ba9,Face Detection with the Faster R-CNN,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+3cd9411181cd4f12798c64f0442c199cc24a56a7,Leveraging from group classification for video concept detection,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+3cd40bfa1ff193a96bde0207e5140a399476466c,High Five: Recognising human interactions in TV shows,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3c051c8721b65fca8c506de68068dc8fca6adcc5,It Takes (Only) Two: Adversarial Generator-Encoder Networks,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3c8f916264e8d15ba1bc618c6adf395e86dd7b40,Generating Descriptions with Grounded and Co-referenced People,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
3c1aef7c2d32a219bdbc89a44d158bc2695e360a,Adversarial Attack Type I: Generating False Positives,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
3c1aef7c2d32a219bdbc89a44d158bc2695e360a,Adversarial Attack Type I: Generating False Positives,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
3c1aef7c2d32a219bdbc89a44d158bc2695e360a,Adversarial Attack Type I: Generating False Positives,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
3c1aef7c2d32a219bdbc89a44d158bc2695e360a,Adversarial Attack Type I: Generating False Positives,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+3c8db2ca155ce4e15ec8a2c4c4b979de654fb296,Holistically-Nested Edge Detection,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+3c8db2ca155ce4e15ec8a2c4c4b979de654fb296,Holistically-Nested Edge Detection,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+3ce92cac0f3694be2f2918bf122679c6664a1e16,Deep Relative Attributes,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+3ce92cac0f3694be2f2918bf122679c6664a1e16,Deep Relative Attributes,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
3c11a1f2bd4b9ce70f699fb6ad6398171a8ad3bd,Simulating Pareidolia of Faces for Architectural Image Analysis,University of Newcastle,University of Newcastle,"University of Newcastle Central Coast Campus, Technology Bridge, Ourimbah, Central Coast, NSW, 2258, Australia",-33.35788990,151.37834708,edu,
3c11a1f2bd4b9ce70f699fb6ad6398171a8ad3bd,Simulating Pareidolia of Faces for Architectural Image Analysis,University of Newcastle,University of Newcastle,"University of Newcastle Central Coast Campus, Technology Bridge, Ourimbah, Central Coast, NSW, 2258, Australia",-33.35788990,151.37834708,edu,
3cd8ab6bb4b038454861a36d5396f4787a21cc68,Video-Based Facial Expression Recognition Using Hough Forest,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
3ca5d3b8f5f071148cb50f22955fd8c1c1992719,Evaluating race and sex diversity in the world's largest companies using deep neural networks,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3c9f2444b1de1bf960664d8c3109f8b8d5dee44b,Automatic Facial Feature Extraction for Face Recognition,Università degli Studi di Milano,Università degli Studi di Milano,"Università degli Studi di Milano, Via Camillo Golgi, Città Studi, Milano, MI, LOM, 20133, Italia",45.47567215,9.23336232,edu,
+3cafea5212ff4217beb293e2de8ca0f160ad623a,A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+3cafea5212ff4217beb293e2de8ca0f160ad623a,A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+3cafea5212ff4217beb293e2de8ca0f160ad623a,A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+3c6be0034477b07222f41f6fc558a64f0222a192,Egocentric Video Biometrics,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
3cc46bf79fb9225cf308815c7d41c8dd5625cc29,Age interval and gender prediction using PARAFAC2 applied to speech utterances,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
3cc46bf79fb9225cf308815c7d41c8dd5625cc29,Age interval and gender prediction using PARAFAC2 applied to speech utterances,Cyprus University of Technology,Cyprus University of Technology,"Mitropoli Building - Cyprus University of Technology, Anexartisias, Limasol - Λεμεσός, Limassol - Λεμεσός, Κύπρος - Kıbrıs, 3036, Κύπρος - Kıbrıs",34.67567405,33.04577648,edu,
+3c2bdfc703a77ecd0a991b03e620e8a911d5f8f4,Combining Facial Appearance and Dynamics for Face Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+3c90f2603ef99222697b76d7ab123f513a1f4baa,The Effects of Alcohol Intoxication on Accuracy and the Confidence–Accuracy Relationship in Photographic Simultaneous Line‐ups,Loughborough University,Loughborough University,"Computer Science, University Road, Charnwood, Leicestershire, East Midlands, England, LE11 3TP, UK",52.76635770,-1.22924610,edu,
+3c90f2603ef99222697b76d7ab123f513a1f4baa,The Effects of Alcohol Intoxication on Accuracy and the Confidence–Accuracy Relationship in Photographic Simultaneous Line‐ups,Edge Hill University,Edge Hill University,"Edge Hill University, St Helens Road, West Lancashire, Lancs, North West England, England, L39 4QP, UK",53.55821550,-2.86904651,edu,
56c700693b63e3da3b985777da6d9256e2e0dc21,Global refinement of random forest,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
56c700693b63e3da3b985777da6d9256e2e0dc21,Global refinement of random forest,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
56359d2b4508cc267d185c1d6d310a1c4c2cc8c2,Shape driven kernel adaptation in Convolutional Neural Network for robust facial trait recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
56359d2b4508cc267d185c1d6d310a1c4c2cc8c2,Shape driven kernel adaptation in Convolutional Neural Network for robust facial trait recognition,Chinese Academy of Science,"Key Lab of Intelligent Information Processing, Institute of Computer Technology, Chinese Academy of Science (CAS), Beijing, 100190, China","Beijing, China",39.90419990,116.40739630,edu,
56359d2b4508cc267d185c1d6d310a1c4c2cc8c2,Shape driven kernel adaptation in Convolutional Neural Network for robust facial trait recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+56d831143008ec10f8122e5086f5a55aec770ea1,A DIKW Paradigm to Cognitive Engineering,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
56e079f4eb40744728fd1d7665938b06426338e5,Bayesian Approaches to Distribution Regression,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
56e079f4eb40744728fd1d7665938b06426338e5,Bayesian Approaches to Distribution Regression,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
56e079f4eb40744728fd1d7665938b06426338e5,Bayesian Approaches to Distribution Regression,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
56e079f4eb40744728fd1d7665938b06426338e5,Bayesian Approaches to Distribution Regression,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+5684d284310582ae0f69c5b7a4d6b791a13fcf49,Learning to Track at 100 FPS with Deep Regression Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
56e6f472090030a6f172a3e2f46ef9daf6cad757,Asian Face Image Database PF 01 Intelligent Multimedia Lab,Pohang University of Science and Technology,Pohang University of Science and Technology,"포스텍, 77, 청암로, 효곡동, 남구, 포항시, 경북, 37673, 대한민국",36.01773095,129.32107509,edu,
+56d3df5ce2ffb695728c091252087979be31f0c7,RMPE: Regional Multi-person Pose Estimation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
56f86bef26209c85f2ef66ec23b6803d12ca6cd6,Pyramidal RoR for image classification,North China Electric Power University,North China Electric Power University,"华北电力大学, 永华北大街, 莲池区, 保定市, 莲池区 (Lianchi), 保定市, 河北省, 071000, 中国",38.87604460,115.49738730,edu,
+567078a51ea63b70396dca5dabb50a10a736d991,Conditional Generative Adversarial Network for Structured Domain Adaptation,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+567078a51ea63b70396dca5dabb50a10a736d991,Conditional Generative Adversarial Network for Structured Domain Adaptation,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+567078a51ea63b70396dca5dabb50a10a736d991,Conditional Generative Adversarial Network for Structured Domain Adaptation,University at Buffalo,State University of New York at Buffalo,"Buffalo, NY 14260, USA",43.00080930,-78.78896970,edu,
566a39d753c494f57b4464d6bde61bf3593f7ceb,A Critical Review of Action Recognition Benchmarks,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
56c2fb2438f32529aec604e6fc3b06a595ddbfcc,Comparison of Recent Machine Learning Techniques for Gender Recognition from Facial Images,Central Washington University,Central Washington University,"Central Washington University, Dean Nicholson Boulevard, Ellensburg, Kittitas County, Washington, 98926, USA",47.00646895,-120.53673040,edu,
56c2fb2438f32529aec604e6fc3b06a595ddbfcc,Comparison of Recent Machine Learning Techniques for Gender Recognition from Facial Images,Central Washington University,Central Washington University,"Central Washington University, Dean Nicholson Boulevard, Ellensburg, Kittitas County, Washington, 98926, USA",47.00646895,-120.53673040,edu,
@@ -421,45 +1220,87 @@ 56f231fc40424ed9a7c93cbc9f5a99d022e1d242,Age Estimation Based on a Single Network with Soft Softmax of Aging Modeling,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
56f231fc40424ed9a7c93cbc9f5a99d022e1d242,Age Estimation Based on a Single Network with Soft Softmax of Aging Modeling,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
56f231fc40424ed9a7c93cbc9f5a99d022e1d242,Age Estimation Based on a Single Network with Soft Softmax of Aging Modeling,Macau University of Science and Technology,Macau University of Science and Technology,"Universidade de Ciência e Tecnologia de Macau 澳門科技大學 Macau University of Science and Technology, 偉龍馬路 Avenida Wai Long, 氹仔Taipa, 氹仔舊城區 Vila de Taipa, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, 澳門 Macau, 853, 中国",22.15263985,113.56803206,edu,
+56143653c9bb0f01fb8a58da02b7ef7241170eec,Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+56d5c8bee7d28d2fc6a2b1d00d80285f84618797,Multi-glimpse LSTM with color-depth feature fusion for human detection,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+56d5c8bee7d28d2fc6a2b1d00d80285f84618797,Multi-glimpse LSTM with color-depth feature fusion for human detection,HoHai University,HoHai University,"河海大学, 河海路, 小市桥, 鼓楼区, 南京市, 江苏省, 210013, 中国",32.05765485,118.75500040,edu,
+563143c5f4fed0184c1f3e661917da94cfed1d46,Informed Democracy: Voting-based Novelty Detection for Action Recognition,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
561ae67de137e75e9642ab3512d3749b34484310,DeepGestalt - Identifying Rare Genetic Syndromes Using Deep Learning,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
561ae67de137e75e9642ab3512d3749b34484310,DeepGestalt - Identifying Rare Genetic Syndromes Using Deep Learning,Rheinische-Friedrich-Wilhelms University,Rheinische-Friedrich-Wilhelms University,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+56c701467da819088c3f734f3ba36a793d645992,Title Underconnectivity of the Superior Temporal Sulcus Predicts Emotion Recognition Deficits in Autism Social Cognitive and Affective Neuroscience Advance Access Published Number of Words,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+56f942a738022cb9af243f3336ba1f035783f73c,A general framework for efficient clustering of large datasets based on activity detection,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
568cff415e7e1bebd4769c4a628b90db293c1717,Concepts Not Alone: Exploring Pairwise Relationships for Zero-Shot Video Activity Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
568cff415e7e1bebd4769c4a628b90db293c1717,Concepts Not Alone: Exploring Pairwise Relationships for Zero-Shot Video Activity Recognition,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
568cff415e7e1bebd4769c4a628b90db293c1717,Concepts Not Alone: Exploring Pairwise Relationships for Zero-Shot Video Activity Recognition,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+562989741c0627b2f966d3abd5f87047503d0fb8,From Same Photo: Cheating on Visual Kinship Challenges,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+562989741c0627b2f966d3abd5f87047503d0fb8,From Same Photo: Cheating on Visual Kinship Challenges,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+562989741c0627b2f966d3abd5f87047503d0fb8,From Same Photo: Cheating on Visual Kinship Challenges,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+560b46547720b3a892f90a337835875f74f4f4ec,Discriminating Color Faces for Recognition,New Jersey Institute of Technology,New Jersey Institute of Technology,"New Jersey Institute of Technology, Warren Street, University Heights, Newark, Essex County, New Jersey, 07103, USA",40.74230250,-74.17928172,edu,
+561ed7e47524fb3218e6a38f41cd877a9c33d3b9,StyleNet: Generating Attractive Visual Captions with Styles,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+561ed7e47524fb3218e6a38f41cd877a9c33d3b9,StyleNet: Generating Attractive Visual Captions with Styles,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+569dbb5c8a84d3b378cb2e38bb86ad7d826c8d10,Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
560e0e58d0059259ddf86fcec1fa7975dee6a868,Face recognition in unconstrained videos with matched background similarity,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
560e0e58d0059259ddf86fcec1fa7975dee6a868,Face recognition in unconstrained videos with matched background similarity,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
+563523dc73375693314c20e1fe2a65e34915cd8f,Human Pose Estimation from Monocular Images: A Comprehensive Survey,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
56a677c889e0e2c9f68ab8ca42a7e63acf986229,Mining Spatial and Spatio-Temporal ROIs for Action Recognition,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+56ffece2817a0363f551210733a611830ba1155d,Aligning where to see and what to tell: image caption with region-based attention and scene factorization,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+56e25056153a15eae2a6b10c109f812d2b753cee,Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+56e25056153a15eae2a6b10c109f812d2b753cee,Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
+56fcb57a328caf184c1634d934271b18b86b53e8,Multimodal Named Entity Recognition for Short Social Media Posts,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+56d162799d5e004723341492f776399693d76433,Learning Hypergraph-regularized Attribute Predictors,Chongqing University,Chongqing University,"重庆工商大学, 19, 翠林路, 重庆市, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400067, 中国",29.50841740,106.57858552,edu,
+56d162799d5e004723341492f776399693d76433,Learning Hypergraph-regularized Attribute Predictors,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
56ae6d94fc6097ec4ca861f0daa87941d1c10b70,Distance Estimation of an Unknown Person from a Portrait,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
56f812661c3248ed28859d3b2b39e033b04ae6ae,Multiple feature fusion by subspace learning,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
56f812661c3248ed28859d3b2b39e033b04ae6ae,Multiple feature fusion by subspace learning,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
56f812661c3248ed28859d3b2b39e033b04ae6ae,Multiple feature fusion by subspace learning,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
56f812661c3248ed28859d3b2b39e033b04ae6ae,Multiple feature fusion by subspace learning,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+56bb321e0e180f72be9c4e9eb791b251073750e2,Labeling and modeling large databases of videos,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+5136f69da8a61447a300a50c67d80d84a31b1257,Deep Association Learning for Unsupervised Video Person Re-identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
512befa10b9b704c9368c2fbffe0dc3efb1ba1bf,Evidence and a computational explanation of cultural differences in facial expression recognition.,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
512befa10b9b704c9368c2fbffe0dc3efb1ba1bf,Evidence and a computational explanation of cultural differences in facial expression recognition.,Ritsumeikan University,Ritsumeikan University,"立命館大学 (Ritsumeikan University), 衣笠宇多野線, 北区, 京都市, 京都府, 近畿地方, 6038577, 日本",35.03332810,135.72491540,edu,
512befa10b9b704c9368c2fbffe0dc3efb1ba1bf,Evidence and a computational explanation of cultural differences in facial expression recognition.,Kogakuin University,Kogakuin University,"工学院大学, 東通り, 新宿区, 東京都, 関東地方, 163-8677, 日本",35.69027840,139.69540096,edu,
512befa10b9b704c9368c2fbffe0dc3efb1ba1bf,Evidence and a computational explanation of cultural differences in facial expression recognition.,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
512befa10b9b704c9368c2fbffe0dc3efb1ba1bf,Evidence and a computational explanation of cultural differences in facial expression recognition.,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+51e2f8f402c3d972368483169503221fd3088383,End-to-end Recovery of Human Shape and Pose,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
516d0d9eb08825809e4618ca73a0697137ebabd5,Regularizing Long Short Term Memory with 3D Human-Skeleton Sequences for Action Recognition,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
519a724426b5d9ad384d38aaf2a4632d3824f243,Learning Models for Object Recognition from Natural Language Descriptions,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
5180df9d5eb26283fb737f491623395304d57497,Scalable Angular Discriminative Deep Metric Learning for Face Recognition,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+51cb2116c5a32d076f54b1a192cf4e850390f665,On Machine Learning and Structure for Mobile Robots,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
518edcd112991a1717856841c1a03dd94a250090,Rice University Endogenous Sparse Recovery by Eva L . Dyer,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
518edcd112991a1717856841c1a03dd94a250090,Rice University Endogenous Sparse Recovery by Eva L . Dyer,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+51c4ecf4539f56c4b1035b890f743b3a91dd758b,Situational object boundary detection,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+51c4ecf4539f56c4b1035b890f743b3a91dd758b,Situational object boundary detection,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+51e9630e2d3f353d43834d06ef5b75fbccf0243a,Random Forests of Local Experts for Pedestrian Detection,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+5191781bbfe562cfee0c57675a9fbe79a85473b9,Face Flow,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+51c02f135d6c960b1141bde539059a279f9beb78,Subspace clustering using a symmetric low-rank representation,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+510d2879c03a2a0fa01ac6d6b95eb1067f2d1bf9,Multimodal Hierarchical Reinforcement Learning Policy for Task-Oriented Visual Dialog,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+510d2879c03a2a0fa01ac6d6b95eb1067f2d1bf9,Multimodal Hierarchical Reinforcement Learning Policy for Task-Oriented Visual Dialog,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+510d2879c03a2a0fa01ac6d6b95eb1067f2d1bf9,Multimodal Hierarchical Reinforcement Learning Policy for Task-Oriented Visual Dialog,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
51683eac8bbcd2944f811d9074a74d09d395c7f3,"Automatic Analysis of Facial Actions: Learning from Transductive, Supervised and Unsupervised Frameworks",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
51683eac8bbcd2944f811d9074a74d09d395c7f3,"Automatic Analysis of Facial Actions: Learning from Transductive, Supervised and Unsupervised Frameworks",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
51683eac8bbcd2944f811d9074a74d09d395c7f3,"Automatic Analysis of Facial Actions: Learning from Transductive, Supervised and Unsupervised Frameworks",Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
51faacfa4fb1e6aa252c6970e85ff35c5719f4ff,Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
51faacfa4fb1e6aa252c6970e85ff35c5719f4ff,Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
51faacfa4fb1e6aa252c6970e85ff35c5719f4ff,Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+51e8e8c4cac8260ef21c25f9f2a0a68aedbc6d58,Deep Generative Adversarial Compression Artifact Removal,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+512ef8e228329e02b651e2963260f569a72b4dde,3D Signatures for Fast 3D Face Recognition,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+513b8dc73a9fbc467e1ac130fe8c842b5839ca51,Dissertation Scalable Visual Navigation for Micro Aerial Vehicles using Geometric Prior Knowledge,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
51cb09ee04831b95ae02e1bee9b451f8ac4526e3,Beyond short snippets: Deep networks for video classification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
51cb09ee04831b95ae02e1bee9b451f8ac4526e3,Beyond short snippets: Deep networks for video classification,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
51cb09ee04831b95ae02e1bee9b451f8ac4526e3,Beyond short snippets: Deep networks for video classification,Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
514a74aefb0b6a71933013155bcde7308cad2b46,Carnegie Mellon University Optimal Classifier Ensembles for Improved Biometric Verification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
514a74aefb0b6a71933013155bcde7308cad2b46,Carnegie Mellon University Optimal Classifier Ensembles for Improved Biometric Verification,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+512f7507034e35d7259845bc5e4e174ef2f652cf,SPIGAN: Privileged Adversarial Learning from Simulation,Toyota Research Institute,Toyota Research Institute,"Toyota Research Institute, 4440, West El Camino Real, Los Altos, Santa Clara County, California, 94022, USA",37.40253645,-122.11655107,edu,
+512f7507034e35d7259845bc5e4e174ef2f652cf,SPIGAN: Privileged Adversarial Learning from Simulation,Toyota Research Institute,Toyota Research Institute,"Toyota Research Institute, 4440, West El Camino Real, Los Altos, Santa Clara County, California, 94022, USA",37.40253645,-122.11655107,edu,
+512f7507034e35d7259845bc5e4e174ef2f652cf,SPIGAN: Privileged Adversarial Learning from Simulation,Toyota Research Institute,Toyota Research Institute,"Toyota Research Institute, 4440, West El Camino Real, Los Altos, Santa Clara County, California, 94022, USA",37.40253645,-122.11655107,edu,
+51273a7abfe2018ccf2789a8e25d0c2ae565bc77,Learning Detailed Face Reconstruction from a Single Image,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
51a8dabe4dae157aeffa5e1790702d31368b9161,Face recognition under generic illumination based on harmonic relighting,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+516668a41d6106232a7cd56d20d3b3da343e5f36,Predicting Deeper into the Future of Semantic Segmentation,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
512b4c8f0f3fb23445c0c2dab768bcd848fa8392,Analysis and Synthesis of Facial Expressions by Feature- Points Tracking and Deformable Model,University of Tabriz,University of Tabriz,"دانشگاه تبریز, شهید ایرج خلوتی, کوی انقلاب, تبریز, بخش مرکزی, شهرستان تبریز, استان آذربایجان شرقی, 5166616471, ایران",38.06125530,46.32984840,edu,
51eba481dac6b229a7490f650dff7b17ce05df73,Situation Recognition: Visual Semantic Role Labeling for Image Understanding,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
5173a20304ea7baa6bfe97944a5c7a69ea72530f,Best Basis Selection Method Using Learning Weights for Face Recognition,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
51ed4c92cab9336a2ac41fa8e0293c2f5f9bf3b6,"A Survey of Face Detection, Extraction and Recognition",Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+51236676c3bba877d82c31b393db1af4846527ac,Improving Sampling from Generative Autoencoders with Markov Chains,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+5147c249aadf9dd20d24a025995e79f5d6e4e5f4,Systems Analysis of the WEKA Machine Learning Workbench for Affective Computing,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
5141cf2e59fb2ec9bb489b9c1832447d3cd93110,Learning Person Trajectory Representations for Team Activity Analysis,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
5185f2a40836a754baaa7419a1abdd1e7ffaf2ad,A Multimodality Framework for Creating Speaker/Non-Speaker Profile Databases for Real-World Video,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
5185f2a40836a754baaa7419a1abdd1e7ffaf2ad,A Multimodality Framework for Creating Speaker/Non-Speaker Profile Databases for Real-World Video,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
@@ -468,234 +1309,600 @@ 5185f2a40836a754baaa7419a1abdd1e7ffaf2ad,A Multimodality Framework for Creating Speaker/Non-Speaker Profile Databases for Real-World Video,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
5185f2a40836a754baaa7419a1abdd1e7ffaf2ad,A Multimodality Framework for Creating Speaker/Non-Speaker Profile Databases for Real-World Video,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
511a8cdf2127ef8aa07cbdf9660fe9e0e2dfbde7,A Community Detection Approach to Cleaning Extremely Large Face Database,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+518f3cb2c9f2481cdce7741c5a821c26378b75e9,The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
51d048b92f6680aca4a8adf07deb380c0916c808,"State of the Art on Monocular 3D Face Reconstruction, Tracking, and Applications",Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
51d048b92f6680aca4a8adf07deb380c0916c808,"State of the Art on Monocular 3D Face Reconstruction, Tracking, and Applications",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+517e5e6d8e17511fd74fc58ef53bdd57bb7b4651,TallyQA: Answering Complex Counting Questions,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+51972609a7c0070bf517c29f108f3e7240b94e59,3D Extended Histogram of Oriented Gradients (3DHOG) for Classification of Road Users in Urban Scenes,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
5134353bd01c4ea36bd007c460e8972b1541d0ad,Face Recognition with Multi-Resolution Spectral Feature Images,Anhui University,Anhui University,"安徽大学(磬苑校区), 111, 九龙路, 弘泰苑, 合肥国家级经济技术开发区, 芙蓉社区, 合肥经济技术开发区, 合肥市区, 合肥市, 安徽省, 230601, 中国",31.76909325,117.17795091,edu,
5134353bd01c4ea36bd007c460e8972b1541d0ad,Face Recognition with Multi-Resolution Spectral Feature Images,University of Newcastle,University of Newcastle,"University of Newcastle Central Coast Campus, Technology Bridge, Ourimbah, Central Coast, NSW, 2258, Australia",-33.35788990,151.37834708,edu,
5134353bd01c4ea36bd007c460e8972b1541d0ad,Face Recognition with Multi-Resolution Spectral Feature Images,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
5160569ca88171d5fa257582d161e9063c8f898d,Local binary patterns as an image preprocessing for face authentication,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+3dc0a3803c6e1c3c32192a5378100faa2a57ee3e,FlipDial: A Generative Model for Two-Way Visual Dialogue,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3dc0a3803c6e1c3c32192a5378100faa2a57ee3e,FlipDial: A Generative Model for Two-Way Visual Dialogue,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3dc0a3803c6e1c3c32192a5378100faa2a57ee3e,FlipDial: A Generative Model for Two-Way Visual Dialogue,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3dc0a3803c6e1c3c32192a5378100faa2a57ee3e,FlipDial: A Generative Model for Two-Way Visual Dialogue,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
3d18ce183b5a5b4dcaa1216e30b774ef49eaa46f,Face Alignment in Full Pose Range: A 3D Total Solution,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
3d18ce183b5a5b4dcaa1216e30b774ef49eaa46f,Face Alignment in Full Pose Range: A 3D Total Solution,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+3ddfa1e5e57c8f439796d092b3059075600198b1,Linear Representation Learning Using Sphere Factor Analysis,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+3ddfa1e5e57c8f439796d092b3059075600198b1,Linear Representation Learning Using Sphere Factor Analysis,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
3d143cfab13ecd9c485f19d988242e7240660c86,Discriminative Collaborative Representation for Classification,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
3d143cfab13ecd9c485f19d988242e7240660c86,Discriminative Collaborative Representation for Classification,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+3d88b669e7a412f765f1dfa54724937b8f563611,Reasoning About Fine-Grained Attribute Phrases Using Reference Games,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+3d3fdeb8792859543d791e34af4005a80f348eed,Children's racial bias in perceptions of others' pain.,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
+3d3fdeb8792859543d791e34af4005a80f348eed,Children's racial bias in perceptions of others' pain.,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
+3d69d634f79dfcc717e18f73c886b854a157a3ef,Mix-and-Match Tuning for Self-Supervised Semantic Segmentation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
3dabf7d853769cfc4986aec443cc8b6699136ed0,Data Mining Spontaneous Facial Behavior with Automatic Expression Coding,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
3dabf7d853769cfc4986aec443cc8b6699136ed0,Data Mining Spontaneous Facial Behavior with Automatic Expression Coding,Sabanci University,Sabanci University,"Sabanci Universitesi, Preveze Cad., Orta Mahallesi, Tepeören, Tuzla, İstanbul, Marmara Bölgesi, 34953, Türkiye",40.89271590,29.37863323,edu,
+3d0a787aac818909a01e039dd1878fbee52e8765,Viewpoint-aware Attentive Multiview Inference for Vehicle Re-identification,University of East Anglia,University of East Anglia,"Arts (Lower Walkway Level), The Square, Westfield View, Earlham, Norwich, Norfolk, East of England, England, NR4 7TJ, UK",52.62215710,1.24091360,edu,
+3d5575e9ba02128d94c20330f4525fc816411ec2,Learning Video Object Segmentation from Static Images,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+3d741315108b95cdb56d312648f5ad1c002c9718,Image-based face recognition under illumination and pose variations.,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+3dc6f72bda1707e6a96174ff943991bb2b7ff319,Visalogy: Answering Visual Analogy Questions,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+3dc6f72bda1707e6a96174ff943991bb2b7ff319,Visalogy: Answering Visual Analogy Questions,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+3dc6f72bda1707e6a96174ff943991bb2b7ff319,Visalogy: Answering Visual Analogy Questions,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+3d22f972448a2336677ae6ff2877fae010c7dfa2,What is the Role of Recurrent Neural Networks (RNNs) in an Image Caption Generator?,University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
+3d22f972448a2336677ae6ff2877fae010c7dfa2,What is the Role of Recurrent Neural Networks (RNNs) in an Image Caption Generator?,University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
+3d275a4e4f44d452f21e0e0ff6145a5e18e6cf87,CIDEr: Consensus-based image description evaluation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
3d1a6a5fd5915e0efb953ede5af0b23debd1fc7f,Bimodal Human Emotion Classification in the Speaker-Dependent Scenario,University of Peshawar,University of Peshawar,"University of Peshawar, Road 2, JAHANGIR ABAD / جهانگیرآباد, پشاور, Peshāwar District, خیبر پختونخوا, 2500, پاکستان",34.00920040,71.48774947,edu,
3d1a6a5fd5915e0efb953ede5af0b23debd1fc7f,Bimodal Human Emotion Classification in the Speaker-Dependent Scenario,University of Peshawar,University of Peshawar,"University of Peshawar, Road 2, JAHANGIR ABAD / جهانگیرآباد, پشاور, Peshāwar District, خیبر پختونخوا, 2500, پاکستان",34.00920040,71.48774947,edu,
+3d58204f9f89b66db916278dc2d269e1f79ffc43,Learning and recognizing faces: from still images to video sequences,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
3d0379688518cc0e8f896e30815d0b5e8452d4cd,Autotagging Facebook: Social network context improves photo annotation,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
3d0379688518cc0e8f896e30815d0b5e8452d4cd,Autotagging Facebook: Social network context improves photo annotation,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+3d6b71b359d5db96a69ca322a5336110d89fb10d,Partially-Supervised Image Captioning,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
3d24b386d003bee176a942c26336dbe8f427aadd,Sequential Person Recognition in Photo Albums with a Recurrent Network,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
3d0f9a3031bee4b89fab703ff1f1d6170493dc01,SVDD-Based Illumination Compensation for Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3d0f9a3031bee4b89fab703ff1f1d6170493dc01,SVDD-Based Illumination Compensation for Face Recognition,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
3d0c21d4780489bd624a74b07e28c16175df6355,Deep or Shallow Facial Descriptors? A Case for Facial Attribute Classification and Face Retrieval,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
3d0c21d4780489bd624a74b07e28c16175df6355,Deep or Shallow Facial Descriptors? A Case for Facial Attribute Classification and Face Retrieval,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+3d25eb8241345f86101fda145d95d89c27844fd1,Distributed Submodular Maximization: Identifying Representative Elements in Massive Data,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+3d204dbc13f59f1a1678c773b30a1d85e305f548,Modern Facial Attractiveness: Investigating Gendered Preferences for Dominance and Personality,"University of Colorado, Boulder","University of Colorado, Boulder","Naropa University, Arapahoe Avenue, The Hill, Boulder, Boulder County, Colorado, 80309, USA",40.01407945,-105.26695944,edu,
+3d0660e18c17db305b9764bb86b21a429241309e,Counting Everyday Objects in Everyday Scenes,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
3df8cc0384814c3fb05c44e494ced947a7d43f36,The Pose Knows: Video Forecasting by Generating Pose Futures,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3dfd94d3fad7e17f52a8ae815eb9cc5471172bc0,Face2Text: Collecting an Annotated Image Description Corpus for the Generation of Rich Face Descriptions,University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
3dfd94d3fad7e17f52a8ae815eb9cc5471172bc0,Face2Text: Collecting an Annotated Image Description Corpus for the Generation of Rich Face Descriptions,University of Copenhagen,University of Copenhagen,"Københavns Universitet, Krystalgade, Kødbyen, Vesterbro, København, Københavns Kommune, Region Hovedstaden, 1165, Danmark",55.68015020,12.57232700,edu,
3dbfd2fdbd28e4518e2ae05de8374057307e97b3,Improving Face Detection,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
+3d4e6fb9c238c490f57aed72bcf9a81ea5f28972,A Discriminative Model for Learning Semantic and Geometric Interactions in Indoor Scenes∗,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
3d68cedd80babfbb04ab197a0b69054e3c196cd9,Bimodal information analysis for emotion recognition,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
3dfb822e16328e0f98a47209d7ecd242e4211f82,Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environments,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+3dd5a70191613e0867d32f368fad6ec25c63cfb4,Tensor-Based Cortical Surface Morphometry via Weighted Spherical Harmonic Representation,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+3d00fad9ebc9c4cd13bef710de91f4c9d1870887,LETHA: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images,"CSIC-UPC, Barcelona, Spain","Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona, Spain","C/ Llorens i Artigas 4-6, 08028 Barcelona, Spain",41.38295500,2.11573820,edu,
+3d00fad9ebc9c4cd13bef710de91f4c9d1870887,LETHA: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+3d00fad9ebc9c4cd13bef710de91f4c9d1870887,LETHA: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images,École Polytechnique Fédérale de Lausanne,"École Polytechnique Fédérale de Lausanne (EPFL), Switzerland","Bibliothèque de l'EPFL, Route des Noyerettes, Ecublens, District de l'Ouest lausannois, Vaud, 1024, Schweiz/Suisse/Svizzera/Svizra",46.51841210,6.56846540,edu,
+3d33f16ffb3f56e63b8b5c51147b1a07840d734a,Developing Cognitions about Race: White 5- to 10-Year-Olds’ Perceptions of Hardship and Pain Running head: DEVELOPING COGNITIONS ABOUT RACE,University of Delaware,University of Delaware,"University of Delaware, South College Avenue, Newark, New Castle County, Delaware, 19713, USA",39.68103280,-75.75401840,edu,
+3d33f16ffb3f56e63b8b5c51147b1a07840d734a,Developing Cognitions about Race: White 5- to 10-Year-Olds’ Perceptions of Hardship and Pain Running head: DEVELOPING COGNITIONS ABOUT RACE,University of Delaware,University of Delaware,"University of Delaware, South College Avenue, Newark, New Castle County, Delaware, 19713, USA",39.68103280,-75.75401840,edu,
3d948e4813a6856e5b8b54c20e50cc5050e66abe,A Smart Phone Image Database for Single Image Recapture Detection,"A*STAR, Singapore","Institute for Infocomm Research, A*STAR, Singapore","1 Fusionopolis Way, #21-01 Connexis, Singapore 138632",1.29889260,103.78731070,edu,
3d948e4813a6856e5b8b54c20e50cc5050e66abe,A Smart Phone Image Database for Single Image Recapture Detection,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
3d948e4813a6856e5b8b54c20e50cc5050e66abe,A Smart Phone Image Database for Single Image Recapture Detection,New Jersey Institute of Technology,New Jersey Institute of Technology,"New Jersey Institute of Technology, Warren Street, University Heights, Newark, Essex County, New Jersey, 07103, USA",40.74230250,-74.17928172,edu,
+3dafecf541e7aba8b6431f6deb50d37e7ea8a8ff,Random Exemplar Hashing,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+3d855f0665a912ff2c7736cecf9b8eae3effc281,Evaluation of Deep Learning based Pose Estimation for Sign Language,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+3d855f0665a912ff2c7736cecf9b8eae3effc281,Evaluation of Deep Learning based Pose Estimation for Sign Language,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+3d855f0665a912ff2c7736cecf9b8eae3effc281,Evaluation of Deep Learning based Pose Estimation for Sign Language,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
3d9db1cacf9c3bb7af57b8112787b59f45927355,Improving Medical Students’ Awareness of Their Non-Verbal Communication through Automated Non-Verbal Behavior Feedback,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
3d9db1cacf9c3bb7af57b8112787b59f45927355,Improving Medical Students’ Awareness of Their Non-Verbal Communication through Automated Non-Verbal Behavior Feedback,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
3d9db1cacf9c3bb7af57b8112787b59f45927355,Improving Medical Students’ Awareness of Their Non-Verbal Communication through Automated Non-Verbal Behavior Feedback,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
3d9db1cacf9c3bb7af57b8112787b59f45927355,Improving Medical Students’ Awareness of Their Non-Verbal Communication through Automated Non-Verbal Behavior Feedback,Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
+3d5a4b31e6e25cd0cfefa0b5925674377cdaea7d,Training VAEs Under Structured Residuals,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+3d5a4b31e6e25cd0cfefa0b5925674377cdaea7d,Training VAEs Under Structured Residuals,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
580f86f1ace1feed16b592d05c2b07f26c429b4b,Dense-Captioning Events in Videos,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+58622d45472f454ea64fd456d9b52ed9f7dad7f4,Web-scale computer vision using MapReduce for multimedia data mining,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
58d47c187b38b8a2bad319c789a09781073d052d,Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
58d47c187b38b8a2bad319c789a09781073d052d,Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
58d47c187b38b8a2bad319c789a09781073d052d,Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+58eba9930b63cc14715368acf40017293b8dc94f,What Do I See? Modeling Human Visual Perception for Multi-person Tracking,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+589951bd421e2b701225fe6626fe980d94ad2770,Overview of ImageCLEF 2018 Medical Domain Visual Question Answering Task,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+58f445fa45d4bdafac43893a55b21348f9e1e6c2,To Join or Not to Join?: Thinking Twice about Joins before Feature Selection,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+58be1f5b9437d2da2240c71ef56cbc06b34acff3,Optimizing Matrix Mapping with Data Dependent Kernel for Image Classification,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
582edc19f2b1ab2ac6883426f147196c8306685a,Do We Really Need to Collect Millions of Faces for Effective Face Recognition?,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
+586f7cafee0456c25e850dcf42b38195a8a80055,Generic Instance Search and Re-identification from One Example via Attributes and Categories,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+586f7cafee0456c25e850dcf42b38195a8a80055,Generic Instance Search and Re-identification from One Example via Attributes and Categories,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+58c3e04e8105cf8f2721c4a4a6487db752bb8852,Choose Your Neuron: Incorporating Domain Knowledge Through Neuron-Importance,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+58c3e04e8105cf8f2721c4a4a6487db752bb8852,Choose Your Neuron: Incorporating Domain Knowledge Through Neuron-Importance,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
+58ed094f1359394fa216e957bb48a726862165ce,Neural Arithmetic Logic Units,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+58ef0c54f01073e43ae5e9662f450002540355e9,Semi-Supervised Zero-Shot Classification with Label Representation Learning,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+58ef0c54f01073e43ae5e9662f450002540355e9,Semi-Supervised Zero-Shot Classification with Label Representation Learning,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+582519e667fe1520dedaa04ffacbb2161b6a5b84,On GANs and GMMs,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
+582519e667fe1520dedaa04ffacbb2161b6a5b84,On GANs and GMMs,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
+5806ff24d62e868b73312f704e7ad8d74eecfbc0,Estimating 3D Human Pose from Single Images Using Iterative Refinement of the Prior,Swansea University,Swansea University,"Swansea University, University Footbridge, Sketty, Swansea, Wales, SA2 8PZ, UK",51.60915780,-3.97934429,edu,
+589b1677d6de28c47693c5816c32698860c32d10,"Tri-modal Person Re-identification with RGB, Depth and Thermal Features",Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
+5812d8239d691e99d4108396f8c26ec0619767a6,GhostVLAD for set-based face recognition,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+5830e0816667e08bb0efca538d892ea329307daa,Filling the Joints : Completion and Recovery of Incomplete 3 D Human Poses †,University of Crete,University of Crete,"House of Europe, Μακεδονίας, Ρέθυμνο, Δήμος Ρεθύμνης, Περιφερειακή Ενότητα Ρεθύμνου, Περιφέρεια Κρήτης, Κρήτη, 930100, Ελλάδα",35.37130240,24.47544080,edu,
+5809d5eedbbc5d9ec7e64dbe1c4a9ed4f126ffb6,Face Recognition with L1-norm Subspaces,SUNY Buffalo,SUNY Buffalo,"SUNY College at Buffalo, Academic Drive, Elmwood Village, Buffalo, Erie County, New York, 14222, USA",42.93362780,-78.88394479,edu,
+58d76380d194248b3bb291b8c7c5137a0a376897,FaceID-GAN : Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+58d76380d194248b3bb291b8c7c5137a0a376897,FaceID-GAN : Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+589d06db45e2319b29fc96582ea6c8be369f57ed,Convolutional LSTM Networks for Video-based Person Re-identification ∗,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
584909d2220b52c0d037e8761d80cb22f516773f,OCR-Free Transcript Alignment,Open University,The Open University,"The Open University, East Lane, Walton, Monkston, Milton Keynes, South East, England, MK7 6AE, UK",52.02453775,-0.70927481,edu,
584909d2220b52c0d037e8761d80cb22f516773f,OCR-Free Transcript Alignment,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
584909d2220b52c0d037e8761d80cb22f516773f,OCR-Free Transcript Alignment,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+58303432a25cc86bfe9c77cf4c04f91695a24304,Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+58303432a25cc86bfe9c77cf4c04f91695a24304,Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+586bfd960cbdba91eecbb06de994dacd38b9ab0f,Unsupervised Surveillance Video Retrieval Based on Human Action and Appearance,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+5853875ecc400b3b365f73cbf44e8680da2bc5ca,Harvesting visual concepts for image search with complex queries,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+584f9ccba8576ecab61fd4575da7484c8f9a7bf2,Modular Generative Adversarial Networks,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
580e48d3e7fe1ae0ceed2137976139852b1755df,THE EFFECTS OF MOTION AND ORIENTATION ON PERCEPTION OF FACIAL EXPRESSIONS AND FACE RECOGNITION by,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+588a21c28ea77a71efab5b2ed4f307eda49b6d1b,Adaptive color transformation for person re-identification in camera networks,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+58a3f4d9e1611e29e6378bc2d7cbad7600fe806e,Ofa : an Optimized Fuzzy Approach to Solve Head Pose Estimation Problem,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
585260468d023ffc95f0e539c3fa87254c28510b,Cardea: Context-Aware Visual Privacy Protection from Pervasive Cameras,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+5849635e61ed7d6358f65f5a228a5148e4fea3b8,Deep Watershed Transform for Instance Segmentation,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+58ecbe5e7d10b4176ceaecc36ae05e15908289c2,Intelligent Health Recommendation System for Computer Users,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+58ecbe5e7d10b4176ceaecc36ae05e15908289c2,Intelligent Health Recommendation System for Computer Users,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
58628e64e61bd2776a2a7258012eabe3c79ca90c,Active Grounding of Visual Situations,Portland State University,Portland State University,"Portland State University, Southwest Park Avenue, University District, Portland Downtown, Portland, Multnomah County, Oregon, 97201, USA",45.51181205,-122.68492999,edu,
58628e64e61bd2776a2a7258012eabe3c79ca90c,Active Grounding of Visual Situations,Santa Fe Institute,Santa Fe Institute,"Santa Fe Institute, Hyde Park Road, Santa Fe, Santa Fe County, New Mexico, 87501, USA",35.70028780,-105.90864847,edu,
+58bac838068df358b536850a84ff806a23f061fc,An information theoretic approach to joint probabilistic face detection and tracking,University of Thessaloniki,University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+580f3ef6e77753ce0b157ebc02656f346080d9a8,A Robust and Scalable Approach to Face Identification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
676a136f5978783f75b5edbb38e8bb588e8efbbe,Matrix completion for resolving label ambiguity,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+6746292c46975ba575a48c2b05b09ab056c26967,The Relationship between Anxiety and the Social Judgements of Approachability And Trustworthiness,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+67545a21b41ec6dd60376aff84bc0945cdb79590,Person-specific expression recognition with transfer learning,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
676f9eabf4cfc1fd625228c83ff72f6499c67926,Face Identification and Clustering,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
679b7fa9e74b2aa7892eaea580def6ed4332a228,Communication and automatic interpretation of affect from facial expressions,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
679b7fa9e74b2aa7892eaea580def6ed4332a228,Communication and automatic interpretation of affect from facial expressions,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
679b7fa9e74b2aa7892eaea580def6ed4332a228,Communication and automatic interpretation of affect from facial expressions,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+67620ee24ddefbbbdfcb35e385795afc9cc30df9,Statutory Declaration,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+678166999912492688251a1ce98dfb79d3c60ddd,Estimation of Squared-Loss Mutual Information from Positive and Unlabeled Data,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+67538df7950dbba0ab7885a23b7abf6f56f39537,Person Re-identification by Salience Matching,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+67c25e73b89166563cf5b70ffc043bbff23a321c,Handling of False Stationary Detections in Background Subtraction in Video Preprocessing,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+67296e6cd0084c301339889c4ef1f71a04406b3d,The Periodic Table of Data Structures,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+67ab22dff1c21e8680f94948d80b77314b325d66,Learning for MultiTask Classification of Visual Attributes,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+67ab22dff1c21e8680f94948d80b77314b325d66,Learning for MultiTask Classification of Visual Attributes,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
+67e3fac91c699c085d47774990572d8ccdc36f15,Multiple Skip Connections and Dilated Convolutions for Semantic Segmentation,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+67e3fac91c699c085d47774990572d8ccdc36f15,Multiple Skip Connections and Dilated Convolutions for Semantic Segmentation,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+67e3fac91c699c085d47774990572d8ccdc36f15,Multiple Skip Connections and Dilated Convolutions for Semantic Segmentation,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+67e3fac91c699c085d47774990572d8ccdc36f15,Multiple Skip Connections and Dilated Convolutions for Semantic Segmentation,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+67134d7bf637f7ac4e354bcb374d7c28c7740ab8,Scale-Adaptive Low-Resolution Person Re-Identification via Learning a Discriminating Surface,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+67134d7bf637f7ac4e354bcb374d7c28c7740ab8,Scale-Adaptive Low-Resolution Person Re-Identification via Learning a Discriminating Surface,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+673952e036b92617d56deac4166aea3064da7fed,Neural Aesthetic Image Reviewer,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
67c3c1194ee72c54bc011b5768e153a035068c43,Street Scenes: towards scene understanding in still images,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
673d4885370b27c863e11a4ece9189a6a45931cc,Recurrent Residual Module for Fast Inference in Videos,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+67a3cc056a539d17f00b0be550a2fc7cb2118dc5,Scalable Image Retrieval by Sparse Product Quantization,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
6754c98ba73651f69525c770fb0705a1fae78eb5,Joint Cascade Face Detection and Alignment,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
6754c98ba73651f69525c770fb0705a1fae78eb5,Joint Cascade Face Detection and Alignment,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+67b38b88f3b3acb4ebba3c1941cbab7290bf59fa,Object-Based Visual Sentiment Concept Analysis and Application,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
672fae3da801b2a0d2bad65afdbbbf1b2320623e,Pose-Selective Max Pooling for Measuring Similarity,Johns Hopkins University,"Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA","3400 N Charles St, Baltimore, MD 21218, USA",39.32905300,-76.61942500,edu,
+67598e0b447294ad7414b8c73819c7ff395eb63e,Fast Semantic Segmentation on Video Using Block Motion-Based Feature Interpolation,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+6729895ecfd8eed9e73e898b54d6c7f18c095a91,Learning Neural Network Classifiers with Low Model Complexity,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+676733fb6d457401962305204155d6f4b7df5059,An overview of face de-identification in still images and videos,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+6729fec79b6cb472b4326745a67c6dde5772ed95,Large-Scale Visual Active Learning with Deep Probabilistic Ensembles,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
677ebde61ba3936b805357e27fce06c44513a455,Facial Expression Recognition Based on Facial Components Detection and HOG Features,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+67e488d4d31d65a31d4bc2a3337c587720af2a12,Cross-Class Sample Synthesis for Zero-shot Learning,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+671697cf84dfbe53a1cb0bed29b9f649c653bbc5,Multispectral Deep Neural Networks for Pedestrian Detection,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
0bc53b338c52fc635687b7a6c1e7c2b7191f42e5,Loglet SIFT for Part Description in Deformable Part Models: Application to Face Alignment,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+0bd949f948f8f7afc0578d23d065b36c5c03c509,Regional Gating Neural Networks for Multi-label Image Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+0bd949f948f8f7afc0578d23d065b36c5c03c509,Regional Gating Neural Networks for Multi-label Image Classification,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+0bd949f948f8f7afc0578d23d065b36c5c03c509,Regional Gating Neural Networks for Multi-label Image Classification,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+0b5e4ac8a04c0ffd0f9045901525201db03c789d,Annotated reconstruction of 3D spaces using drones,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+0b5e4ac8a04c0ffd0f9045901525201db03c789d,Annotated reconstruction of 3D spaces using drones,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+0b5e4ac8a04c0ffd0f9045901525201db03c789d,Annotated reconstruction of 3D spaces using drones,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+0bc3e6618786c5133b7f8b0033f8917e61b42a91,Enhancing Gloss-Based Corpora with Facial Features Using Active Appearance Models,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+0b62ece314846fa257d76e84dd9d002d1fcd21ae,Pedestrian Recognition with a Learned Metric,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+0b62ece314846fa257d76e84dd9d002d1fcd21ae,Pedestrian Recognition with a Learned Metric,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
0b8b8776684009e537b9e2c0d87dbd56708ddcb4,Adversarial Discriminative Heterogeneous Face Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+0bcde128b115af74d0986306184502ae7c8822f6,Learning Scalable Discriminative Dictionary with Sample Relatedness,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+0b0eb6363a0c5b80c544aff091d547122986131b,Remembering faces with emotional expressions,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
+0b0eb6363a0c5b80c544aff091d547122986131b,Remembering faces with emotional expressions,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0b0eb6363a0c5b80c544aff091d547122986131b,Remembering faces with emotional expressions,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+0b0eb6363a0c5b80c544aff091d547122986131b,Remembering faces with emotional expressions,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0b79f0999eab1e2ac586a97dfc9a71809e7ab262,Joint Modeling of Algorithm Behavior and Image Quality for Algorithm Performance Prediction,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
0b78fd881d0f402fd9b773249af65819e48ad36d,Analysis and Modeling of Affective Audio Visual Speech Based on PAD Emotion Space,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
0b835284b8f1f45f87b0ce004a4ad2aca1d9e153,Cartooning for Enhanced Privacy in Lifelogging and Streaming Videos,Indiana University Bloomington,Indiana University Bloomington,"Indiana University Bloomington, East 17th Street, Bloomington, Monroe County, Indiana, 47408, USA",39.17720475,-86.51540030,edu,
+0be936107834d08f381018f374979e0949e6b932,Scalable Learning Through Error-correcting Codes based Clustering in Autonomous Systems,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+0ba87571341beaf6a5c9a30e049be7b1fc9a4c60,Choosing Linguistics over Vision to Describe Images,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+0b609b048b75d45fb17bf1e2763d83735db7d7da,Region-based representations for face recognition,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+0bcc4ccbe7b12166bb6e8669ab6b5c7edfe6294e,Beyond Object Recognition: Visual Sentiment Analysis with Deep Coupled Adjective and Noun Neural Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+0bcc4ccbe7b12166bb6e8669ab6b5c7edfe6294e,Beyond Object Recognition: Visual Sentiment Analysis with Deep Coupled Adjective and Noun Neural Networks,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+0bc695e580d41ad163d5ec601bdcf384a0bf91cd,A Linear Approach of 3D Face Shape and Texture Recovery using a 3D Morphable Model,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
0b51197109813d921835cb9c4153b9d1e12a9b34,The University of Chicago Jointly Learning Multiple Similarity Metrics from Triplet Constraints a Dissertation Submitted to the Faculty of the Division of the Physical Sciences in Candidacy for the Degree of Master of Science Department of Computer Science By,University of Chicago,THE UNIVERSITY OF CHICAGO,"University of Chicago, South Ellis Avenue, Woodlawn, Chicago, Cook County, Illinois, 60637, USA",41.78468745,-87.60074933,edu,
0bf3513d18ec37efb1d2c7934a837dabafe9d091,Robust Subspace Clustering via Thresholding Ridge Regression,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+0b574f70d0965d66986bb9e89df693126652a4a6,Discriminative learning of multiset integrated canonical correlation analysis for feature fusion,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+0b3be3656a90edf9d8e7c88c89927eb42e674aa6,Automatic landmark annotation and dense correspondence registration for 3D human facial images,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
0be2245b2b016de1dcce75ffb3371a5e4b1e731b,On the Variants of the Self-Organizing Map That Are Based on Order Statistics,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+0b6314e9e741d19346d936eaaa7d6fcf46dd3ed7,Deep Learning in the Wild,Ulm University,Ulm University,"HNU, John-F.-Kennedy-Straße, Vorfeld, Wiley, Neu-Ulm, Landkreis Neu-Ulm, Schwaben, Bayern, 89231, Deutschland",48.38044335,10.01010115,edu,
0b85b50b6ff03a7886c702ceabad9ab8c8748fdc,Is there a dynamic advantage for facial expressions?,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
0b84f07af44f964817675ad961def8a51406dd2e,Person Re-identification in the Wild,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+0b9c5bfb4d8349bb3f6ddd6fb612b7f9657c93f8,Inverting and Visualizing Features for Object Detection,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
0b242d5123f79defd5f775d49d8a7047ad3153bc,How Important Is Weight Symmetry in Backpropagation?,McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
0ba1d855cd38b6a2c52860ae4d1a85198b304be4,Variable-state latent conditional random fields for facial expression recognition and action unit detection,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
0ba1d855cd38b6a2c52860ae4d1a85198b304be4,Variable-state latent conditional random fields for facial expression recognition and action unit detection,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+0b6f64c78c44dc043e2972fa7bfe2a5753768609,A future for learning semantic models of man-made environments,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
0b50e223ad4d9465bb92dbf17a7b79eccdb997fb,Implicit elastic matching with random projections for pose-variant face recognition,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
0b50e223ad4d9465bb92dbf17a7b79eccdb997fb,Implicit elastic matching with random projections for pose-variant face recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
0badf61e8d3b26a0d8b60fe94ba5c606718daf0b,Facial Expression Recognition Using Deep Belief Network,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
0badf61e8d3b26a0d8b60fe94ba5c606718daf0b,Facial Expression Recognition Using Deep Belief Network,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+0b4901e6724e533f6d5d2510e1c0199eea898c81,High Quality Bidirectional Generative Adversarial Networks,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
0b2966101fa617b90510e145ed52226e79351072,Beyond verbs: Understanding actions in videos with text,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
0b2966101fa617b90510e145ed52226e79351072,Beyond verbs: Understanding actions in videos with text,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+0b55b31765f101535eac0d50b9da377f82136d2f,Biometric binary string generation with detection rate optimized bit allocation,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+0b48e1bd69c5b87f197397f933ce7f5261fa00bb,A Joint Model of Language and Perception for Grounded Attribute Learning,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
0ba0f000baf877bc00a9e144b88fa6d373db2708,Facial Expression Recognition Based on Local Directional Pattern Using SVM Decision-level Fusion,Normal University,Normal University,"云南师范大学, 一二一大街, 志城家园, 五华区, 五华区 (Wuhua), 昆明市 (Kunming), 云南省, 650030, 中国",25.05805090,102.69552410,edu,
0be80da851a17dd33f1e6ffdd7d90a1dc7475b96,Weighted Feature Gaussian Kernel SVM for Emotion Recognition,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+0be8b12f194fb604be69c139a195799e8ab53fd3,Talking Heads: Detecting Humans and Recognizing Their Interactions,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
0b183f5260667c16ef6f640e5da50272c36d599b,Spatio-temporal Event Classification Using Time-Series Kernel Based Structured Sparsity,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
0b183f5260667c16ef6f640e5da50272c36d599b,Spatio-temporal Event Classification Using Time-Series Kernel Based Structured Sparsity,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
0b183f5260667c16ef6f640e5da50272c36d599b,Spatio-temporal Event Classification Using Time-Series Kernel Based Structured Sparsity,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
0be764800507d2e683b3fb6576086e37e56059d1,Learning from Geometry,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0baee7f68c08f1a6b5190755adebc57145d18ccf,Unsupervised Discovery of Mid-Level Discriminative Patches,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
0b642f6d48a51df64502462372a38c50df2051b1,A domain adaptation approach to improve speaker turn embedding using face representation,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
0b7d1386df0cf957690f0fe330160723633d2305,Learning American English Accents Using Ensemble Learning with GMMs,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
0b7d1386df0cf957690f0fe330160723633d2305,Learning American English Accents Using Ensemble Learning with GMMs,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
0b6616f3ebff461e4b6c68205fcef1dae43e2a1a,Rectifying Self Organizing Maps for Automatic Concept Learning from Web Images,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
0b6616f3ebff461e4b6c68205fcef1dae43e2a1a,Rectifying Self Organizing Maps for Automatic Concept Learning from Web Images,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+0b90cd2e8abd6b23e7f8133f02e3e6d121cf4903,Advanced Steel Microstructural Classification by Deep Learning Methods,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
0ba402af3b8682e2aa89f76bd823ddffdf89fa0a,Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
0ba402af3b8682e2aa89f76bd823ddffdf89fa0a,Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
0ba402af3b8682e2aa89f76bd823ddffdf89fa0a,Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
0bf0029c9bdb0ac61fda35c075deb1086c116956,Modelling of Orthogonal Craniofacial Profiles,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+93cba94ff0ff96f865ce24ea01e9c006369d75ff,Knowledge Aided Consistency for Weakly Supervised Phrase Grounding,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
935a7793cbb8f102924fa34fce1049727de865c2,Age estimation under changes in image quality: An experimental study,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+93b623ffb25fc32898f3c876c9aba0f5ec22d3ac,Understanding Visual Ads by Aligning Symbols and Objects using Co-Attention,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
9326d1390e8601e2efc3c4032152844483038f3f,Landmark Based Facial Component Reconstruction for Recognition across Pose,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
+93a66d470c1840d11eaa96ead3b600450b3cc9f8,Gaze aversion as a cognitive load management strategy in autism spectrum disorder and Williams syndrome,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+9397e7acd062245d37350f5c05faf56e9cfae0d6,DeepFruits: A Fruit Detection System Using Deep Neural Networks,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
93747de3d40376761d1ef83ffa72ec38cd385833,Team members' emotional displays as indicators of team functioning.,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
93747de3d40376761d1ef83ffa72ec38cd385833,Team members' emotional displays as indicators of team functioning.,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
93747de3d40376761d1ef83ffa72ec38cd385833,Team members' emotional displays as indicators of team functioning.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
93747de3d40376761d1ef83ffa72ec38cd385833,Team members' emotional displays as indicators of team functioning.,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+938d9dd3e35cb8af5fb6b8b3f7c7ff9d6ba8b253,"Corrigendum: Does Seeing Faces of Young Black Boys Facilitate the +Identification of Threatening Stimuli?",University of Iowa,University of Iowa,"University of Iowa, Hawkeye Court, Iowa City, Johnson County, Iowa, 52246, USA",41.66590000,-91.57310307,edu,
93721023dd6423ab06ff7a491d01bdfe83db7754,Robust Face Alignment Using Convolutional Neural Networks,Orange,Orange Labs,"78 Rue Olivier de Serres, 75015 Paris, France",48.83321220,2.29421550,company,"78 Rue Olivier de Serres, Paris, 75015"
+935e639bebf905af2e35e8b1e7aa0538d7122185,A Network Structure to Explicitly Reduce Confusion Errors in Semantic Segmentation,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+93a8dbd0823cc1924bfe37d88af36d4f0545bb12,RGB-D multi-view object detection with object proposals and shape context,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+936a4af585f9a7d3b95c078ad31e8e41e22cb406,Adaptive sampling for large scale boosting,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
93971a49ef6cc88a139420349a1dfd85fb5d3f5c,Scalable Probabilistic Models: Applied to Face Identification in the Wild,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
93420d9212dd15b3ef37f566e4d57e76bb2fab2f,An All-In-One Convolutional Neural Network for Face Analysis,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
93af36da08bf99e68c9b0d36e141ed8154455ac2,A Dditive M Argin S Oftmax for F Ace V Erification,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
93af36da08bf99e68c9b0d36e141ed8154455ac2,A Dditive M Argin S Oftmax for F Ace V Erification,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
93af36da08bf99e68c9b0d36e141ed8154455ac2,A Dditive M Argin S Oftmax for F Ace V Erification,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+93f9607034c9b7b7693c60e9d2631adc15a2a524,Learning to Model the Tail,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+9358123bab4c98f75ac9b0c59b574ea2d7ff6b5a,Blind Recognition of Touched Keys on Mobile Devices,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+9358123bab4c98f75ac9b0c59b574ea2d7ff6b5a,Blind Recognition of Touched Keys on Mobile Devices,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+9358123bab4c98f75ac9b0c59b574ea2d7ff6b5a,Blind Recognition of Touched Keys on Mobile Devices,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+9358123bab4c98f75ac9b0c59b574ea2d7ff6b5a,Blind Recognition of Touched Keys on Mobile Devices,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+9358123bab4c98f75ac9b0c59b574ea2d7ff6b5a,Blind Recognition of Touched Keys on Mobile Devices,University of Macau,University of Macau,"研究生宿舍 Residência de Estudantes de Pós-Graduação da Universidade de Macau, 澳門大學 Universidade de Macau, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, Universidade de Macau em Ilha de Montanha 澳門大學橫琴校區, 中国",22.12401870,113.54510901,edu,
937ffb1c303e0595317873eda5ce85b1a17f9943,Eyes do not lie: spontaneous versus posed smiles,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+9340efcb976f6c28c7242480502e16f795895f28,Learning Deep Energy Models: Contrastive Divergence vs. Amortized MLE,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+934350482f3f19d431f35960a14dc249bd069303,Visual Question Answering as a Meta Learning Task,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+937729cea19a955147e059a6f0ef0571cc6785c4,An Analysis on Invertibility of Cancelable Biometrics based on BioHashing,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
93f37c69dd92c4e038710cdeef302c261d3a4f92,Compressed Video Action Recognition,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
93f37c69dd92c4e038710cdeef302c261d3a4f92,Compressed Video Action Recognition,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+9363bf52a5bb2ac94bf247ca56e7cf55fb29ee4e,Online Multi-person Tracking by Tracker Hierarchy,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+93a28e5131a762aeb888b76bcc6689e8696ab8d2,Pose Embeddings: A Deep Architecture for Learning to Match Human Poses,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
936227f7483938097cc1cdd3032016df54dbd5b6,Learning to generalize to new compositions in image understanding,Bar-Ilan University,Bar-Ilan University,"אוניברסיטת בר אילן, כביש גהה, גבעת שמואל, קריית מטלון, גבעת שמואל, מחוז תל אביב, NO, ישראל",32.06932925,34.84334339,edu,
936227f7483938097cc1cdd3032016df54dbd5b6,Learning to generalize to new compositions in image understanding,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
939123cf21dc9189a03671484c734091b240183e,Within- and cross- database evaluations for face gender classification via befit protocols,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+938acfc9001174fdf9007e5dea2cfc993a0b9a09,Disentangling Factors of Variation by Mixing Them,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+936a60174ccc8f9448d38b269a53bc212125370e,Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning,"University of Colorado, Boulder","University of Colorado, Boulder","Naropa University, Arapahoe Avenue, The Hill, Boulder, Boulder County, Colorado, 80309, USA",40.01407945,-105.26695944,edu,
938ae9597f71a21f2e47287cca318d4a2113feb2,Classifier Learning with Prior Probabilities for Facial Action Unit Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
938ae9597f71a21f2e47287cca318d4a2113feb2,Classifier Learning with Prior Probabilities for Facial Action Unit Recognition,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+945cd58065f923e3cdc46a28c2b3f0c22ebfca9e,"Mutual eye gaze facilitates person categorization for typically developing children, but not for children with autism.",University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
946017d5f11aa582854ac4c0e0f1b18b06127ef1,Tracking Persons-of-Interest via Adaptive Discriminative Features,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
946017d5f11aa582854ac4c0e0f1b18b06127ef1,Tracking Persons-of-Interest via Adaptive Discriminative Features,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
946017d5f11aa582854ac4c0e0f1b18b06127ef1,Tracking Persons-of-Interest via Adaptive Discriminative Features,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+94e008564e4f091a887fdda379e7d26d90920c54,Stereological Study of Amygdala Glial Populations in Adolescents and Adults with Autism Spectrum Disorder,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+944ab8c7d73bf2ca439205543c906b7797c269f5,Efficient Construction of Neighborhood Graphs by the Multiple Sorting Method,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+94f093ce723a7112d5698a1e88f437503d2d40af,Identifying The Most Informative Features Using A Structurally Interacting Elastic Net,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+94f093ce723a7112d5698a1e88f437503d2d40af,Identifying The Most Informative Features Using A Structurally Interacting Elastic Net,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+94d5ebe936c101699e678f6f0cddd8a732986814,What you see is what you get: contextual modulation of face scanning in typical and atypical development,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+94d5ebe936c101699e678f6f0cddd8a732986814,What you see is what you get: contextual modulation of face scanning in typical and atypical development,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+94d5ebe936c101699e678f6f0cddd8a732986814,What you see is what you get: contextual modulation of face scanning in typical and atypical development,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+94d0c0ed5bb9c13c2c8231adfdd9d96cf837514a,Generalized Background Subtraction Using Superpixels with Label Integrated Motion Estimation,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
+9445d51fd7977fb11a34a0e522efdcdee0d5cd95,First-Person Activity Forecasting with Online Inverse Reinforcement Learning,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+9405a9180139f23f4dd9d90aa4e86944b35b8c88,Weakly-Supervised Visual Grounding of Phrases with Linguistic Structures,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+9405a9180139f23f4dd9d90aa4e86944b35b8c88,Weakly-Supervised Visual Grounding of Phrases with Linguistic Structures,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+943262361be04747aba71d45fb4854cf72019851,Pose-Sensitive Embedding by Nonlinear NCA Regression,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+94d48f61cea7ce848af500f4a02f3ea4459bce27,A Neural Compositional Paradigm for Image Captioning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+94d48f61cea7ce848af500f4a02f3ea4459bce27,A Neural Compositional Paradigm for Image Captioning,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+94bf6b804dfcedb0bf6b0d5c711bb7fe305f3704,Looking at faces: autonomous perspective invariant facial gaze analysis,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+94106ca511a60fb4fa8402fef4bf22b9ebef83e9,Invariant Object Recognition Using Radon-based Transform,AGH University of Science and Technology,AGH University of Science and Technology,"AGH, Władysława Reymonta, Czarna Wieś, Krowodrza, Kraków, małopolskie, 30-059, RP",50.06570330,19.91895867,edu,
+947bd44270618f5a1b046b68f1ada3c11d97b440,GazeDPM: Early Integration of Gaze Information in Deformable Part Models,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+943a1e218b917172199e524944006aa349f58968,Joint Learning of Intrinsic Images and Semantic Segmentation,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
9487cea80f23afe9bccc94deebaa3eefa6affa99,"Fast, Dense Feature SDM on an iPhone",Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
9487cea80f23afe9bccc94deebaa3eefa6affa99,"Fast, Dense Feature SDM on an iPhone",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+94490145def938ca1f8bb265d10b66924937a367,Iterative Local Model Selection for tracking and mapping,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+94490145def938ca1f8bb265d10b66924937a367,Iterative Local Model Selection for tracking and mapping,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
949699d0b865ef35b36f11564f9a4396f5c9cddb,"Processing of facial identity and expression: a psychophysical, physiological, and computational perspective.",Max Planck Institute for Biological Cybernetics,Max Planck Institute for Biological Cybernetics,"Max-Planck-Institut für Biologische Kybernetik, 8, Max-Planck-Ring, Max-Planck-Institut, Wanne, Tübingen, Landkreis Tübingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72076, Deutschland",48.53691250,9.05922533,edu,
949699d0b865ef35b36f11564f9a4396f5c9cddb,"Processing of facial identity and expression: a psychophysical, physiological, and computational perspective.",University of Zurich,University of Zurich,"ZHAW, Rosenstrasse, Heiligberg, Altstadt, Winterthur, Bezirk Winterthur, Zürich, 8400, Schweiz/Suisse/Svizzera/Svizra",47.49684760,8.72981767,edu,
94e259345e82fa3015a381d6e91ec6cded3971b4,Classification of Photometric Factors Based on Photometric Linearization,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
94e259345e82fa3015a381d6e91ec6cded3971b4,Classification of Photometric Factors Based on Photometric Linearization,Okayama University,Okayama University,"岡山大学, 津高法界院停車場線, 津島東2, 津島東, 北区, 岡山市, 岡山県, 中国地方, 700-0081, 日本",34.68933930,133.92222720,edu,
+949d20c44387918cde21f800d8d1cdf53f016bb4,Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+949d20c44387918cde21f800d8d1cdf53f016bb4,Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+94ac7f52e2e94ecf1fd3bac53028967b7dd62f36,Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+944efd74c6fd812c6c495a11e7b045c9b778702e,RCAA: Relational Context-Aware Agents for Person Search,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+944efd74c6fd812c6c495a11e7b045c9b778702e,RCAA: Relational Context-Aware Agents for Person Search,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+944efd74c6fd812c6c495a11e7b045c9b778702e,RCAA: Relational Context-Aware Agents for Person Search,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+0e2af97f07625cb3cf5e30f1c9d807124cbbc850,From Large Scale Image Categorization to Entry-Level Categories,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+0ee59e5baed4271ab85c85332550ca1539733a19,Atypical Modulations of N170 Component during Emotional Processing and Their Links to Social Behaviors in Ex-combatants,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
+0ee59e5baed4271ab85c85332550ca1539733a19,Atypical Modulations of N170 Component during Emotional Processing and Their Links to Social Behaviors in Ex-combatants,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+0e08cf0b19f0600dadce0f6694420d643ea9828b,The Middle Child Problem: Revisiting Parametric Min-Cut and Seeds for Object Proposals,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+0e08cf0b19f0600dadce0f6694420d643ea9828b,The Middle Child Problem: Revisiting Parametric Min-Cut and Seeds for Object Proposals,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+0e41bb49b2b3b1fc4fadce856f164af51549bcb4,Max-Margin Structured Output Regression for Spatio-Temporal Action Localization,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
0e5dcc6ae52625fd0637c6bba46a973e46d58b9c,Pareto Models for Multiclass Discriminative Linear Dimensionality Reduction,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
0e5dcc6ae52625fd0637c6bba46a973e46d58b9c,Pareto Models for Multiclass Discriminative Linear Dimensionality Reduction,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
0e5dcc6ae52625fd0637c6bba46a973e46d58b9c,Pareto Models for Multiclass Discriminative Linear Dimensionality Reduction,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+0eae752f8949d97e41831e509da721ad673dfc2b,Beyond Tree Structure Models: A New Occlusion Aware Graphical Model for Human Pose Estimation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0e312aee6b03a697d112a1bd8d25d84d1a122d8e,An inner-loop free solution to inverse problems using deep neural networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0e312aee6b03a697d112a1bd8d25d84d1a122d8e,An inner-loop free solution to inverse problems using deep neural networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0e312aee6b03a697d112a1bd8d25d84d1a122d8e,An inner-loop free solution to inverse problems using deep neural networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0e312aee6b03a697d112a1bd8d25d84d1a122d8e,An inner-loop free solution to inverse problems using deep neural networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
0e73d2b0f943cf8559da7f5002414ccc26bc77cd,Similarity Comparisons for Interactive Fine-Grained Categorization,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
0e73d2b0f943cf8559da7f5002414ccc26bc77cd,Similarity Comparisons for Interactive Fine-Grained Categorization,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+0ee7990e2ae054aab5f1fc08670fe5eddb96fb19,Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+0e67717484684d90ae9d4e1bb9cdceb74b194910,Mining Pixels: Weakly Supervised Semantic Segmentation Using Image Labels,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+0e25527a7df08c8cda5e86c7a255806289b0ff64,Automatic Eye Detection using Fast Corner Detector of North East Indian (NEI) Face Images,Jadavpur University,Jadavpur University,"Jadavpur University, Chingrighata Flyover, Basani Devi Colony, Kolkata, Hāora, West Bengal, 700098, India",22.56115370,88.41310194,edu,
+0e8defaafbbde9031fb2942eccaf980b2f20f04e,Regenerative morphing,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
+0e8defaafbbde9031fb2942eccaf980b2f20f04e,Regenerative morphing,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
0ed0e48b245f2d459baa3d2779bfc18fee04145b,Semi-Supervised Dimensionality Reduction,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
0ed0e48b245f2d459baa3d2779bfc18fee04145b,Semi-Supervised Dimensionality Reduction,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+0e62b741d4421b284cc6a27cea0b1e95b799882e,Forest Walk Methods for Localizing Body Joints from Single Depth Image,Hankuk University of Foreign Studies,Hankuk University of Foreign Studies,"외대앞, 휘경로, 이문동, 이문2동, 동대문구, 서울특별시, 02407, 대한민국",37.59539790,127.06304990,edu,
+0e62b741d4421b284cc6a27cea0b1e95b799882e,Forest Walk Methods for Localizing Body Joints from Single Depth Image,Ajou University,Ajou University,"아주대학교, 성호대교, 이의동, 영통구, 수원시, 경기, 16499, 대한민국",37.28300030,127.04548469,edu,
0ef96d97365899af797628e80f8d1020c4c7e431,Improving the Speed of Kernel PCA on Large Scale Datasets,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
0e7f277538142fb50ce2dd9179cffdc36b794054,Combining image captions and visual analysis for image concept classification,Queen Mary University,Queen Mary University,"Universitatea Creștină Partium - Clădirea Sulyok, 27, Strada Primăriei, Orașul Nou, Oradea, Bihor, 410209, România",47.05702220,21.92270900,edu,
0e7f277538142fb50ce2dd9179cffdc36b794054,Combining image captions and visual analysis for image concept classification,Queen Mary University,Queen Mary University,"Universitatea Creștină Partium - Clădirea Sulyok, 27, Strada Primăriei, Orașul Nou, Oradea, Bihor, 410209, România",47.05702220,21.92270900,edu,
+0e7d8ae484d8a0ecf65855dad9e7514730b4e07f,Knowing a Good HOG Filter When You See It: Efficient Selection of Filters for Detection,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+0e7d8ae484d8a0ecf65855dad9e7514730b4e07f,Knowing a Good HOG Filter When You See It: Efficient Selection of Filters for Detection,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+0ee91554aedcb2cc4e2d2a15eb07eed1bbbac2c2,Fast Energy Minimization Using Learned State Filters,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+0e46943b2b12a8df6a62202651555a1d464cebec,Person Re-identification by Efficient Impostor-Based Metric Learning,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+0e923b74fd41f73f57e22f66397feeea67e834f0,Invariant encoding schemes for visual recognition,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+0e1f6abdd24a4e929511740168e2f67351751302,Zero-Shot Recognition via Direct Classifier Learning with Transferred Samples and Pseudo Labels,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+0e1f6abdd24a4e929511740168e2f67351751302,Zero-Shot Recognition via Direct Classifier Learning with Transferred Samples and Pseudo Labels,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+0e96646eb97bade66848b1fe50a9fc6ab946ed42,Learning Like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
0ec0fc9ed165c40b1ef4a99e944abd8aa4e38056,The Role of Perspective-Taking on Ability to Recognize Fear,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
0ec0fc9ed165c40b1ef4a99e944abd8aa4e38056,The Role of Perspective-Taking on Ability to Recognize Fear,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
0ec0fc9ed165c40b1ef4a99e944abd8aa4e38056,The Role of Perspective-Taking on Ability to Recognize Fear,Virginia Tech Carilion Research Institute,Virginia Tech Carilion Research Institute,"Virginia Tech Carilion Research Institute, South Jefferson Street, Crystal Spring, Roanoke, Virginia, 24016, USA",37.25795480,-79.94233291,edu,
0ec0fc9ed165c40b1ef4a99e944abd8aa4e38056,The Role of Perspective-Taking on Ability to Recognize Fear,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
0e652a99761d2664f28f8931fee5b1d6b78c2a82,Making a Science of Model Search,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+0e8f56d7e0b639e182d1d9693b79653cfd98aaa3,Auto-colorization Exploiting Annotated Dataset,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+0e64a202a673ebb9265d600d97c2ccff8acf64c9,Side-View Face Recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+0e0179eb4b43016691f0f1473a08089dda21f8f0,The Art of Detection,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+0e950d7ad2282d49e8cada91d5d6b50b42a23979,Attribute Recognition by Joint Recurrent Learning of Context and Correlation,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
0ea7b7fff090c707684fd4dc13e0a8f39b300a97,Integrated Face Analytics Networks through Cross-Dataset Hybrid Training,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
0ea7b7fff090c707684fd4dc13e0a8f39b300a97,Integrated Face Analytics Networks through Cross-Dataset Hybrid Training,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
0ea7b7fff090c707684fd4dc13e0a8f39b300a97,Integrated Face Analytics Networks through Cross-Dataset Hybrid Training,Beijing Institute of Technology,Beijing Institute of Technology University,"北京理工大学, 5, 中关村南大街, 中关村, 稻香园南社区, 海淀区, 北京市, 100872, 中国",39.95866520,116.30971281,edu,
0e36ada8cb9c91f07c9dcaf196d036564e117536,Much Ado About Time: Exhaustive Annotation of Temporal Data,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0eea197144b631b33857821559886b6ea063b68c,Robust Multi-resolution Pedestrian Detection in Traffic Scenes,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
0ebc50b6e4b01eb5eba5279ce547c838890b1418,Similarity-Preserving Binary Signature for Linear Subspaces,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
0ebc50b6e4b01eb5eba5279ce547c838890b1418,Similarity-Preserving Binary Signature for Linear Subspaces,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
0ebc50b6e4b01eb5eba5279ce547c838890b1418,Similarity-Preserving Binary Signature for Linear Subspaces,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+0e41758075d91e58412f012c2d03531c5baf7cdc,Visual category recognition using Spectral Regression and Kernel Discriminant Analysis,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+0e41758075d91e58412f012c2d03531c5baf7cdc,Visual category recognition using Spectral Regression and Kernel Discriminant Analysis,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
0ec1673609256b1e457f41ede5f21f05de0c054f,Blessing of Dimensionality: High-Dimensional Feature and Its Efficient Compression for Face Verification,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+0e815b773e480ef20a680dd35cd72ab26a141d2f,Person re-identification via efficient inference in fully connected CRF,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+0e815b773e480ef20a680dd35cd72ab26a141d2f,Person re-identification via efficient inference in fully connected CRF,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+0ee3aa2a78f9680bb65a823bd9195c879572ec1c,What Makes an Object Memorable?,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+0ee3aa2a78f9680bb65a823bd9195c879572ec1c,What Makes an Object Memorable?,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+0ee3aa2a78f9680bb65a823bd9195c879572ec1c,What Makes an Object Memorable?,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+0edc70f3b5550f997d9011c6d4860feec136cea9,Face Recognition: Holistic Approaches an Analytical Survey,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+0edc70f3b5550f997d9011c6d4860feec136cea9,Face Recognition: Holistic Approaches an Analytical Survey,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
0ea38a5ba0c8739d1196da5d20efb13406bb6550,Relative attributes,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
0e21c9e5755c3dab6d8079d738d1188b03128a31,Constrained Clustering and Its Application to Face Clustering in Videos,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+0e1403f2182609fb64ed72913f7294fea7d02bd6,Learning Support Vectors for Face Verification and Recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+0e1403f2182609fb64ed72913f7294fea7d02bd6,Learning Support Vectors for Face Verification and Recognition,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
0e93a5a7f6dbdb3802173dca05717d27d72bfec0,Attribute Recognition by Joint Recurrent Learning of Context and Correlation,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
0ed1c1589ed284f0314ed2aeb3a9bbc760dcdeb5,Max-Margin Early Event Detectors,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+0e4c87100aa7f585ccd969aa71dd5dfdf26e732d,Laplacian regularized low rank subspace clustering,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+0e9f55c0ff758a91c6764f833b14b09ca788db20,Locality preserving hashing,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+0ec03a13063e5811ec9461cf7af04f4f3110ccaa,Visual Question Answering with Question Representation Update (QRU),Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
0ec2049a1dd7ae14c7a4c22c5bcd38472214f44d,Fast Subspace Search via Grassmannian Based Hashing,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
0ec2049a1dd7ae14c7a4c22c5bcd38472214f44d,Fast Subspace Search via Grassmannian Based Hashing,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
0ec2049a1dd7ae14c7a4c22c5bcd38472214f44d,Fast Subspace Search via Grassmannian Based Hashing,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+0e986ac9484e0587b6ccf01a5db735b9bf185157,Refining Architectures of Deep Convolutional Neural Networks,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
0ec67c69e0975cfcbd8ba787cc0889aec4cc5399,Locating Salient Object Features,Manchester University,Manchester University,"Manchester Metropolitan University – All Saints Campus, Lower Ormond Street, Hulme, Manchester, Greater Manchester, North West England, England, M15 6BX, UK",53.47020165,-2.23932183,edu,
0e1983e9d0e8cb4cbffef7af06f6bc8e3f191a64,Estimating illumination parameters in real space with application to image relighting,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+0ef0db6b7bf2244459497a3bf24e56c7850cf369,Weakly Supervised Phrase Localization with Multi-Scale Anchored Transformer Network,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
0ee5c4112208995bf2bb0fb8a87efba933a94579,Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
0e1a18576a7d3b40fe961ef42885101f4e2630f8,Automated Detection and Identification of Persons in Video,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+0e01db4197f71450118f81ae5a69ce4916b46421,Weakly-supervised Discovery of Visual Pattern Configurations,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+6044b30751c19b3231782fb0475c9ca438940690,Real-time Action Recognition with Dissimilarity-based Training of Specialized Module Networks,Alexandria University,Alexandria University,"جامعة الإسكندرية, الكورنيش, إبراهيمية, الإسكندرية, 21522, مصر",31.21051105,29.91314562,edu,
60a006bdfe5b8bf3243404fae8a5f4a9d58fa892,A reference-based framework for pose invariant face recognition,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
6043006467fb3fd1e9783928d8040ee1f1db1f3a,Face recognition with learning-based descriptor,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
6043006467fb3fd1e9783928d8040ee1f1db1f3a,Face recognition with learning-based descriptor,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
6043006467fb3fd1e9783928d8040ee1f1db1f3a,Face recognition with learning-based descriptor,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
6043006467fb3fd1e9783928d8040ee1f1db1f3a,Face recognition with learning-based descriptor,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+60eea6b85ba791ab85b198cfe7473adec29bcfd2,Video Question Answering via Attribute-Augmented Attention Network Learning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+60aa6b163fd8bc16965807fdd47634bedb04989d,Autonomous exploration using rapid perception of low-resolution image information,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+607bfdbf583c4dfa29491eedc3934f2293e1fa96,A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function.,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+607bfdbf583c4dfa29491eedc3934f2293e1fa96,A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function.,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+600f164c81dbaa0327e7bd659fd9eb7f511f9e9a,A benchmark study of large-scale unconstrained face recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
60c24e44fce158c217d25c1bae9f880a8bd19fc3,Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+603bfd8e1230816526e213855c5de172443f9ee1,CAKE: a Compact and Accurate K-dimensional representation of Emotion,Orange,Orange Labs,"78 Rue Olivier de Serres, 75015 Paris, France",48.83321220,2.29421550,company,"78 Rue Olivier de Serres, Paris, 75015"
+601e0569028924cca9b5f1afbca6f52aa7212c39,Single View Stereo Matching,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+601e0569028924cca9b5f1afbca6f52aa7212c39,Single View Stereo Matching,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
60542b1a857024c79db8b5b03db6e79f74ec8f9f,Learning to Detect Human-Object Interactions,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
60d4cef56efd2f5452362d4d9ac1ae05afa970d1,Learning End-to-end Video Classification with Rank-Pooling,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
60d4cef56efd2f5452362d4d9ac1ae05afa970d1,Learning End-to-end Video Classification with Rank-Pooling,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+608dede56161fd5f76bcf9228b4dd8c639d65b02,SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+606cfdcc43203351dbb944a3bb3719695e557e37,Ex Paucis Plura : Learning Affordance Segmentation from Very Few Examples,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
60c699b9ec71f7dcbc06fa4fd98eeb08e915eb09,Long-term video interpolation with bidirectional predictive network,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
60970e124aa5fb964c9a2a5d48cd6eee769c73ef,Subspace Clustering for Sequential Data,Charles Sturt University,Charles Sturt University,"Charles Sturt University, Wagga Wagga, NSW, 2678, Australia",-35.06360710,147.35522340,edu,
+60593c176ba39e8cb63ba6a7bf936553984bb67c,From Categories to Individuals in Real Time -- A Unified Boosting Approach,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+604b79c12304af6826db4ea844dec6b2a2ca4e50,Faceted Navigation for Browsing Large Video Collection,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+603dee8661aa9bf0d7af6c61fe5fa2e85227f166,Customizing First Person Image Through Desired Actions,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+603dee8661aa9bf0d7af6c61fe5fa2e85227f166,Customizing First Person Image Through Desired Actions,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+603dee8661aa9bf0d7af6c61fe5fa2e85227f166,Customizing First Person Image Through Desired Actions,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+608305c25aae19dd346153dadedac851f0b7f9ff,A Fisher Kernel Approach for Multiple Instance Based Object Retrieval in Video Surveillance,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
60a20d5023f2bcc241eb9e187b4ddece695c2b9b,Invertible Nonlinear Dimensionality Reduction via Joint Dictionary Learning,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+60115d62f7d0e918af4d3040624df57353f76053,Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+60115d62f7d0e918af4d3040624df57353f76053,Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+6066d0a5f1123b9e158185113c1e18c4687610c4,Hierarchical Feature Pooling with Structure Learning: A New Method for Pedestrian Detection,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+601c9ac5859021c5c1321adeb38b177ebad346f0,Salient Color Names for Person Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+601c9ac5859021c5c1321adeb38b177ebad346f0,Salient Color Names for Person Re-identification,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
60737db62fb5fab742371709485e4b2ddf64b7b2,Crowdsourced Selection on Multi-Attribute Data,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+60c3b9a6622e359a90c384bf81fc0d46caacf469,Multimodal Visual Concept Learning with Weakly Supervised Techniques,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
+603ecf880ad770b566c4ffa49ffeb06340375194,An expectation maximization approach to the synergy between image segmentation and object categorization,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
+6008213e4270e88cb414459de759c961469b92dd,"Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning",University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
60496b400e70acfbbf5f2f35b4a49de2a90701b5,Avoiding Boosting Overfitting by Removing Confusing Samples,Moscow State University,Moscow State University,"ul. Leninskiye Gory, 1, Moskva, Russia, 119991",55.70393490,37.52866960,edu,
+603e10c9dbadd51ad0938e32b730221c020d677d,It's all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+606e920681b6bd2910a1cccda2403ba7e361a3a9,Feedback Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+344a5802999dddd0a6d1c4d511910af2eb922231,DroneFace: An Open Dataset for Drone Research,Feng Chia University,Feng Chia University,"逢甲大學, 100, 文華路, 西平里, 西屯區, 臺中市, 40724, 臺灣",24.18005755,120.64836072,edu,
+34ed02e82e9816e7491b1af9f6f65d7fff87ff84,Active nonrigid ICP algorithm,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+34ed02e82e9816e7491b1af9f6f65d7fff87ff84,Active nonrigid ICP algorithm,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
34bb11bad04c13efd575224a5b4e58b9249370f3,Towards Good Practices for Action Video Encoding,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
34bb11bad04c13efd575224a5b4e58b9249370f3,Towards Good Practices for Action Video Encoding,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
34bb11bad04c13efd575224a5b4e58b9249370f3,Towards Good Practices for Action Video Encoding,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+34fd4689d406d28100709b3be71958721d6ef11a,Object Skeleton Extraction in Natural Images by Fusing Scale-Associated Deep Side Outputs,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+34fd4689d406d28100709b3be71958721d6ef11a,Object Skeleton Extraction in Natural Images by Fusing Scale-Associated Deep Side Outputs,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+34fd4689d406d28100709b3be71958721d6ef11a,Object Skeleton Extraction in Natural Images by Fusing Scale-Associated Deep Side Outputs,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
3411ef1ff5ad11e45106f7863e8c7faf563f4ee1,Image Retrieval and Ranking via Consistently Reconstructing Multi-attribute Queries,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
3411ef1ff5ad11e45106f7863e8c7faf563f4ee1,Image Retrieval and Ranking via Consistently Reconstructing Multi-attribute Queries,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
3411ef1ff5ad11e45106f7863e8c7faf563f4ee1,Image Retrieval and Ranking via Consistently Reconstructing Multi-attribute Queries,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
3411ef1ff5ad11e45106f7863e8c7faf563f4ee1,Image Retrieval and Ranking via Consistently Reconstructing Multi-attribute Queries,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+3445cc781ebdcf65840bd6314bc0c8c634f1ef5e,A Neural Autoregressive Approach to Attention-based Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+3445cc781ebdcf65840bd6314bc0c8c634f1ef5e,A Neural Autoregressive Approach to Attention-based Recognition,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+3445cc781ebdcf65840bd6314bc0c8c634f1ef5e,A Neural Autoregressive Approach to Attention-based Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
345cc31c85e19cea9f8b8521be6a37937efd41c2,Deep Manifold Traversal: Changing Labels with Convolutional Features,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+3434ba5677e5c98e82ee17a1f2d0ddef66d0b009,Interactive tracking and action retrieval to support human behavior analysis,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+3436b30d5c09a089252cea893fced7b3a5cbc675,The Singularity and the State of the Art in Artificial Intelligence: The technological singularity (Ubiquity symposium),New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
34ce703b7e79e3072eed7f92239a4c08517b0c55,What impacts skin color in digital photos?,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
345bea5f7d42926f857f395c371118a00382447f,Transfiguring portraits,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+349f305fff405c0f38b9df2e1648450eb841fcea,Multi-target Tracking with Motion Context in Tensor Power Iteration,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+3410a1489d04ec6fcfbb3d76d39055117931ccf0,Learning Collections of Part Models for Object Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+349668b75c4398c075fc681f563a80ad7cf6b4f2,Real-time face pose estimation from single range images,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
3463f12ad434d256cd5f94c1c1bfd2dd6df36947,Facial Expression Recognition with Fusion Features Extracted from Salient Facial Areas,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
346c9100b2fab35b162d7779002c974da5f069ee,Photo search by face positions and facial attributes on touch devices,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
34863ecc50722f0972e23ec117f80afcfe1411a9,An efficient face recognition algorithm based on robust principal component analysis,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
34863ecc50722f0972e23ec117f80afcfe1411a9,An efficient face recognition algorithm based on robust principal component analysis,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+349c50a22c9f5b46f4ed0f03912706b2c9d484d5,Zero-Shot Learning Across Heterogeneous Overlapping Domains,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+3445e917f0712be391591442bfa1bca82b7ebd1a,Layout Estimation of Highly Cluttered Indoor Scenes Using Geometric and Semantic Cues,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
34108098e1a378bc15a5824812bdf2229b938678,Reconstructive Sparse Code Transfer for Contour Detection and Semantic Labeling,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
348a16b10d140861ece327886b85d96cce95711e,Finding Good Features for Object Recognition,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
3419af6331e4099504255a38de6f6b7b3b1e5c14,Modified Eigenimage Algorithm for Painting Image Retrieval,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+34a256eb89fde78d61c2184787f5c3183dae49cc,Convex Co-embedding,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+34a256eb89fde78d61c2184787f5c3183dae49cc,Convex Co-embedding,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+34a256eb89fde78d61c2184787f5c3183dae49cc,Convex Co-embedding,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+34994e291f2ddfbb2938599730a5f7a79498dfe1,Single camera pose estimation using Bayesian filtering and Kinect motion priors,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+34ce6a2b0f4404ef4f2a7d3eb68718454840fb10,Affective Responses by Adults with Autism Are Reduced to Social Images but Elevated to Images Related to Circumscribed Interests,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+34ce6a2b0f4404ef4f2a7d3eb68718454840fb10,Affective Responses by Adults with Autism Are Reduced to Social Images but Elevated to Images Related to Circumscribed Interests,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+34aa3dca30dc5cbf86c92d5035e35d264540a829,Person Re-identification by Attributes,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+34032cf0f94cc6645b7fb5df821c72039151c0fa,Feature Level Fusion Based Bimodal Biometric Using Transformation Domine Techniques,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
34c8de02a5064e27760d33b861b7e47161592e65,Video Action Recognition Based on Deeper Convolution Networks with Pair-Wise Frame Motion Concatenation,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
34c8de02a5064e27760d33b861b7e47161592e65,Video Action Recognition Based on Deeper Convolution Networks with Pair-Wise Frame Motion Concatenation,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+34f2aef5aa519d20379037259645d4c84526662c,An Anti-fraud System for Car Insurance Claim Based on Visual Evidence,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+34d8287c2c84b30ef056c0a07f13404ca5ec9471,Locating Facial Features with an Extended Active Shape Model,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
+34626bed8996e105e562119e1b4aa290114c89bf,Visual to Sound: Generating Natural Sound for Videos in the Wild,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
34ccdec6c3f1edeeecae6a8f92e8bdb290ce40fd,A Virtual Assistant to Help Dysphagia Patients Eat Safely at Home,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
34b42bcf84d79e30e26413f1589a9cf4b37076f9,Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+342067ae1d5b52b62c2f31b1426bad933ef90e38,Pedestrian Detection with Semantic Regions of Interest,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+342067ae1d5b52b62c2f31b1426bad933ef90e38,Pedestrian Detection with Semantic Regions of Interest,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+342067ae1d5b52b62c2f31b1426bad933ef90e38,Pedestrian Detection with Semantic Regions of Interest,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+349db48589d9c2177b2067b112b8411513242e95,Object recognition with hierarchical kernel descriptors,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+34022637860443c052375c45c4f700afcb438cd0,Automatic Recognition of Emotions and Membership in Group Videos,Queen Mary University,Queen Mary University,"Universitatea Creștină Partium - Clădirea Sulyok, 27, Strada Primăriei, Orașul Nou, Oradea, Bihor, 410209, România",47.05702220,21.92270900,edu,
+34022637860443c052375c45c4f700afcb438cd0,Automatic Recognition of Emotions and Membership in Group Videos,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+34022637860443c052375c45c4f700afcb438cd0,Automatic Recognition of Emotions and Membership in Group Videos,Queen Mary University,Queen Mary University,"Universitatea Creștină Partium - Clădirea Sulyok, 27, Strada Primăriei, Orașul Nou, Oradea, Bihor, 410209, România",47.05702220,21.92270900,edu,
+34510d3b68b23cc829c5435ac12a5041a8adc50a,RTSeg: Real-Time Semantic Segmentation Comparative Study,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+34b925a111ba29f73f5c0d1b363f357958d563c1,SAPPHIRE: An always-on context-aware computer vision system for portable devices,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+34b925a111ba29f73f5c0d1b363f357958d563c1,SAPPHIRE: An always-on context-aware computer vision system for portable devices,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+5ab2c97ada652ff8f641e1b30cc27050c0ffa7e0,Comparing Emotion Recognition Skills among Children with and without Jailed Parents,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+5ab2c97ada652ff8f641e1b30cc27050c0ffa7e0,Comparing Emotion Recognition Skills among Children with and without Jailed Parents,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
+5a97dbd14958386aa0d969b5a926bb64cfd01b4a,Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+5a97dbd14958386aa0d969b5a926bb64cfd01b4a,Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+5a97dbd14958386aa0d969b5a926bb64cfd01b4a,Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+5a5ae31263517355d15b7b09d74cb03e40093046,Super Resolution and Face Recognition Based People Activity Monitoring Enhancement Using Surveillance Camera,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
+5a11ba25cd048f384a83882a5a4dc25db9493b80,Massive City-Scale Surface Condition Analysis Using Ground and Aerial Imagery,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+5a11ba25cd048f384a83882a5a4dc25db9493b80,Massive City-Scale Surface Condition Analysis Using Ground and Aerial Imagery,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5aa63f9c0310c4dd64801b379266b778f4778445,Brain Network Activity During Face Perception: The Impact of Perceptual Familiarity and Individual Differences in Childhood Experience.,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
5a87bc1eae2ec715a67db4603be3d1bb8e53ace2,A Novel Convergence Scheme for Active Appearance Models,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
5aad56cfa2bac5d6635df4184047e809f8fecca2,A visual dictionary attack on Picture Passwords,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
5a8ca0cfad32f04449099e2e3f3e3a1c8f6541c0,Automatic Frontal Face Reconstruction Approach for Pose Invariant Face Recognition,Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
+5a15eedcd836337b50a2bfab82ded7a9b939aca5,Perception of temporal asymmetries in dynamic facial expressions,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+5a15eedcd836337b50a2bfab82ded7a9b939aca5,Perception of temporal asymmetries in dynamic facial expressions,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
5ac80e0b94200ee3ecd58a618fe6afd077be0a00,Unifying Geometric Features and Facial Action Units for Improved Performance of Facial Expression Analysis,Kent State University,Kent State University,"Kent State University, Lester A. Lefton Esplanade, Whitehall Terrace, Kent, Portage County, Ohio, 44242-0001, USA",41.14435250,-81.33982833,edu,
+5a716a15b94a84ef3a76edce1e9dadc0f633e498,Crowd Counting with Deep Negative Correlation Learning,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+5a716a15b94a84ef3a76edce1e9dadc0f633e498,Crowd Counting with Deep Negative Correlation Learning,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
5aadd85e2a77e482d44ac2a215c1f21e4a30d91b,Face Recognition using Principle Components and Linear Discriminant Analysis,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
+5ac63895a7d3371a739d066bb1631fc178d8276a,Learning Semantic Feature Map for Visual Content Recognition,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+5ac63895a7d3371a739d066bb1631fc178d8276a,Learning Semantic Feature Map for Visual Content Recognition,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
5a5f9e0ed220ce51b80cd7b7ede22e473a62062c,Videos as Space-Time Region Graphs,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+5acf8478d39c3e521436c66cfeec6187c0526e55,Aspects of cognitive understanding of the environment by vision-based semantic mapping,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+5a1c2ca8b81f924bc7584c2ea873c024cc979a1d,Deep Structured Energy-Based Image Inpainting,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
5ac946fc6543a445dd1ee6d5d35afd3783a31353,Featureless: Bypassing feature extraction in action categorization,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+5a96f2bfa2deae2bc35b250251d5fbe82ef4932b,Tensor Fusion Network for Multimodal Sentiment Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5a4ef8b9db11833e01ca8e715c6eec928bc80df0,Every Smile is Unique: Landmark-Guided Diverse Smile Generation,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+5a3800bee147ad58ab7d6c55d8a2be484c17a511,From Images to Sentences through Scene Description Graphs using Commonsense Reasoning and Knowledge,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+5a3800bee147ad58ab7d6c55d8a2be484c17a511,From Images to Sentences through Scene Description Graphs using Commonsense Reasoning and Knowledge,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+5aa7f33cdc00787284b609aa63f5eb5c0a3212f6,Multiplicative mixing of object identity and image attributes in single inferior temporal neurons,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+5a226afa04f03086e402b22ee2c43089b68fa3ba,Multiview RGB-D Dataset for Object Instance Detection,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+5ad0e283c4c2aa7b9985012979835d0131fe73d8,Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5a48999cf31b26191e2db60d80794163d5f8c43d,Recognition of Activities of Daily Living with Egocentric Vision: A Review,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
5ae970294aaba5e0225122552c019eb56f20af74,Establishing Dense Correspondence of High Resolution 3D Faces via Möbius Transformations,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+5a672a0e5c95dd70041989d60672b7b2017f7018,Attention in Multimodal Neural Networks for Person Re-identification,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
5aa57a12444dbde0f5645bd9bcec8cb2f573c6a0,Face recognition using adaptive margin fisher's criterion and linear discriminant analysis (AMFC-LDA),"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
-5a07945293c6b032e465d64f2ec076b82e113fa6,Pulling Actions out of Context: Explicit Separation for Effective Combination,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+5a07945293c6b032e465d64f2ec076b82e113fa6,Pulling Actions out of Context : Explicit Separation for Effective Combination,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+5f0facd360d54bc0d532c90ec2ced4c54043d15b,One-Shot Learning of Scene Locations via Feature Trajectory Transfer,University of Salzburg,University of Salzburg,"Universität Salzburg - Unipark, 1, Erzabt-Klotz-Straße, Nonntal, Salzburg, 5020, Österreich",47.79475945,13.05417525,edu,
5f771fed91c8e4b666489ba2384d0705bcf75030,Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
5f771fed91c8e4b666489ba2384d0705bcf75030,Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
5fa04523ff13a82b8b6612250a39e1edb5066521,Dockerface: an easy to install and use Faster R-CNN face detector in a Docker container,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+5f94e354faeba1d330088b926d1f7886067bc93f,RefineNet: Multi-Path Refinement Networks with Identity Mappings for High-Resolution Semantic Segmentation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+5fe89653d22d35cf98a6fe6e6793da82a55f5c9f,Collaborative Deep Reinforcement Learning for Multi-object Tracking,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+5fcbdbc0ffd5ce2c5eb3b4c18d7ad2edb00d85d1,Focus On What's Important: Self-Attention Model for Human Pose Estimation,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+5fd80e47d53c64512a0b85a4c7a0beb24bc35766,Semi-supervised Zero-Shot Learning by a Clustering-based Approach,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+5f790739bb4e11bdf4fef85c293edc04aae903a3,Using Genetic Programming for Multiclass Classification by Simultaneously Solving Component Binary Classification Problems,Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
+5ff708d399962a07f77c9bbc0d5efda52aa6915e,Pedestrian Prediction by Planning Using Deep Neural Networks,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
5f6ab4543cc38f23d0339e3037a952df7bcf696b,Video2vec: Learning semantic spatio-temporal embeddings for video representation,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
5f6ab4543cc38f23d0339e3037a952df7bcf696b,Video2vec: Learning semantic spatio-temporal embeddings for video representation,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
5f6ab4543cc38f23d0339e3037a952df7bcf696b,Video2vec: Learning semantic spatio-temporal embeddings for video representation,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+5f0b1f37fc9c65c56106438b9aa4c6e0909d6fc0,3D object class detection in the wild,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
5f7c4c20ae2731bfb650a96b69fd065bf0bb950e,A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+5f2a8e79d02ac5bf91109f29f999aa13be0983bb,Recognizing Disguised Faces: Human and Machine Evaluation,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+5fdd81fd5e4caa852b6be3e6bf7891578248d662,A Distributed Weighted Voting Approach for Accurate Eye Center Estimation,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
5f94969b9491db552ffebc5911a45def99026afe,Multimodal Learning and Reasoning for Visual Question Answering,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
5f94969b9491db552ffebc5911a45def99026afe,Multimodal Learning and Reasoning for Visual Question Answering,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
5f94969b9491db552ffebc5911a45def99026afe,Multimodal Learning and Reasoning for Visual Question Answering,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+5f593354fec6d6ab770a3e000684b9280cef5bbc,Active Shape Models Using Local Binary Patterns,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+5f593354fec6d6ab770a3e000684b9280cef5bbc,Active Shape Models Using Local Binary Patterns,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
5f758a29dae102511576c0a5c6beda264060a401,Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+5fcaa87dbde0c4ac437a6b674843927c70f76a78,Scaling the Indian Buffet Process via Submodular Maximization,Cambridge University,Cambridge University,"University, Cambridge Road, Old Portsmouth, Portsmouth, South East, England, PO1 2HB, UK",50.79440260,-1.09717480,edu,
+5feacd9dd73827fb438a6bf6c8b406f4f11aa2fa,Slanted Stixels: Representing San Francisco's Steepest Streets,Universitat Autònoma de Barcelona,Universitat Autònoma de Barcelona,"Centre de Visió per Computador (CVC), Carrer de l'Albareda, Serraperera, UAB, Cerdanyola del Vallès, Vallès Occidental, BCN, CAT, 08214, España",41.50078110,2.11143663,edu,
+5feacd9dd73827fb438a6bf6c8b406f4f11aa2fa,Slanted Stixels: Representing San Francisco's Steepest Streets,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+5f9c3b25eaca97af3c86460d365a3dd485ecbf96,Presentation Attack Detection for Cadaver Iris,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
+5f9c3b25eaca97af3c86460d365a3dd485ecbf96,Presentation Attack Detection for Cadaver Iris,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
5feb1341a49dd7a597f4195004fe9b59f67e6707,A Deep Ranking Model for Spatio-Temporal Highlight Detection from a 360 Video,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+5fb23b55de1c613517f55a1b878bc68bd4b543e3,Multi-shot Person Re-identification through Set Distance with Visual Distributional Representation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
5f0d4a0b5f72d8700cdf8cb179263a8fa866b59b,Memo No . 85 06 / 2018 Deep Regression Forests for Age Estimation,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+5f39d07dd39e5d7cfba535ada3a0ab9d5d0efb5b,Perceptual dehumanization of faces is activated by norm violations and facilitates norm enforcement.,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
5f57a1a3a1e5364792b35e8f5f259f92ad561c1f,Implicit Sparse Code Hashing,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
5f27ed82c52339124aa368507d66b71d96862cb7,"Semi-supervised Learning of Classifiers : Theory , Algorithms and Their Application to Human-Computer Interaction",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
5f27ed82c52339124aa368507d66b71d96862cb7,"Semi-supervised Learning of Classifiers : Theory , Algorithms and Their Application to Human-Computer Interaction","University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+5fd6863a59e88b45f62e82bb72dff3fb52c49be1,Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+5fd6863a59e88b45f62e82bb72dff3fb52c49be1,Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+5fd6863a59e88b45f62e82bb72dff3fb52c49be1,Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
5fea26746f3140b12317fcf3bc1680f2746e172e,Semantic Jitter: Dense Supervision for Visual Comparisons via Synthetic Images,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
5fea26746f3140b12317fcf3bc1680f2746e172e,Semantic Jitter: Dense Supervision for Visual Comparisons via Synthetic Images,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+5f7fd05f09dd6433cb273a1d33bdf75873509983,A Complete View Depended Volleyball Video Dataset under the Uncontrolled Conditions,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+5f7fd05f09dd6433cb273a1d33bdf75873509983,A Complete View Depended Volleyball Video Dataset under the Uncontrolled Conditions,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+5fc662287842e5cb2d23b5fa917354e957c573bf,DenseNet: Implementing Efficient ConvNet Descriptor Pyramids,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
5f676d6eca4c72d1a3f3acf5a4081c29140650fb,To skip or not to skip? A dataset of spontaneous affective response of online advertising (SARA) for audience behavior analysis,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
5f676d6eca4c72d1a3f3acf5a4081c29140650fb,To skip or not to skip? A dataset of spontaneous affective response of online advertising (SARA) for audience behavior analysis,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+5f26ab1b415e3cfa9d9f20cc93154939f3c28ebc,Classifying covert photographs,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+5f9e6f2f84a6a9a64b1d5868e2782b4bae82b567,Robust 3D face recognition using adapted statistical models,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+5fb50e750f700f920f06b3982bd16ea920d11f68,Learning Temporal Transformations from Time-Lapse Videos,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+5f4379b83102d1147876007e328e1b209e4b59af,REP-2008-451: Face Relighting for Recognition,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+5ffa8cfea2f5bea0ec7cecfdf76f9478ca87df89,Context-Aware Captions from Context-Agnostic Supervision,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
5f453a35d312debfc993d687fd0b7c36c1704b16,A Training Assistant Tool for the Automated Visual Inspection System,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
5f453a35d312debfc993d687fd0b7c36c1704b16,A Training Assistant Tool for the Automated Visual Inspection System,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+5f724a84647c5a70865509910070077962433dca,Reconstructive Memory for Abstract Selective Recall,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+5f50b2c187718e3ecba68a1eee492f6f1a0c3355,Simultaneous Edge Alignment and Learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5f50b2c187718e3ecba68a1eee492f6f1a0c3355,Simultaneous Edge Alignment and Learning,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+5f50b2c187718e3ecba68a1eee492f6f1a0c3355,Simultaneous Edge Alignment and Learning,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
5fac62a3de11125fc363877ba347122529b5aa50,AMTnet: Action-Micro-Tube Regression by End-to-end Trainable Deep Architecture,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+5f2989f2c323a4fb5de8720cdfbbae1887d8e6bb,A Belief Based Correlated Topic Model for Semantic Region Analysis in Far-Field Video Surveillance Systems,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+5f69d59ad195a69618231ad83c4ad6342a569074,Face Super-Resolution Through Wasserstein GANs,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+5f68e2131d9275d56092e9fca05bcfc65abea0d8,Cross-Modal Similarity Learning: A Low Rank Bilinear Formulation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+5f68e2131d9275d56092e9fca05bcfc65abea0d8,Cross-Modal Similarity Learning: A Low Rank Bilinear Formulation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+5f68e2131d9275d56092e9fca05bcfc65abea0d8,Cross-Modal Similarity Learning: A Low Rank Bilinear Formulation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+5f68e2131d9275d56092e9fca05bcfc65abea0d8,Cross-Modal Similarity Learning: A Low Rank Bilinear Formulation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
5fba1b179ac80fee80548a0795d3f72b1b6e49cd,Virtual U: Defeating Face Liveness Detection by Building Virtual Models from Your Public Photos,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+33526226231cce669317ece44e6af262b8395dd9,CRF-CNN: Modeling Structured Information in Human Pose Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+33526226231cce669317ece44e6af262b8395dd9,CRF-CNN: Modeling Structured Information in Human Pose Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+33526226231cce669317ece44e6af262b8395dd9,CRF-CNN: Modeling Structured Information in Human Pose Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+33526226231cce669317ece44e6af262b8395dd9,CRF-CNN: Modeling Structured Information in Human Pose Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
33f7e78950455c37236b31a6318194cfb2c302a4,Parameterizing Object Detectors in the Continuous Pose Space,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+33f885a7e1369128534aa5f3b867bd42de9ec683,Annotation and taxonomy of gestures in lecture videos,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
33548531f9ed2ce6f87b3a1caad122c97f1fd2e9,Facial Expression Recognition in Video using Adaboost and SVM,Amity University,Amity University,"Amity University, Faizabad Road, Uttardhauna, Gomti Nagar, Tiwariganj, Lucknow, Uttar Pradesh, 226010, India",26.85095965,81.04950965,edu,
33548531f9ed2ce6f87b3a1caad122c97f1fd2e9,Facial Expression Recognition in Video using Adaboost and SVM,Amity University,Amity University,"Amity University, Faizabad Road, Uttardhauna, Gomti Nagar, Tiwariganj, Lucknow, Uttar Pradesh, 226010, India",26.85095965,81.04950965,edu,
33548531f9ed2ce6f87b3a1caad122c97f1fd2e9,Facial Expression Recognition in Video using Adaboost and SVM,Amity University,Amity University,"Amity University, Faizabad Road, Uttardhauna, Gomti Nagar, Tiwariganj, Lucknow, Uttar Pradesh, 226010, India",26.85095965,81.04950965,edu,
33ac7fd3a622da23308f21b0c4986ae8a86ecd2b,Building an On-Demand Avatar-Based Health Intervention for Behavior Change,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
33ac7fd3a622da23308f21b0c4986ae8a86ecd2b,Building an On-Demand Avatar-Based Health Intervention for Behavior Change,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+33f3b212d665d769a209b7a278dd9907ae2be952,Recognising Human-Object Interaction via Exemplar Based Modelling,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+33f3b212d665d769a209b7a278dd9907ae2be952,Recognising Human-Object Interaction via Exemplar Based Modelling,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+33f3b212d665d769a209b7a278dd9907ae2be952,Recognising Human-Object Interaction via Exemplar Based Modelling,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+331429a6994b73c25ca0c4d0e2794e9119ac870c,Sidestepping Intractable Inference with Structured Ensemble Cascades,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
33030c23f6e25e30b140615bb190d5e1632c3d3b,Toward a General Framework for Words and Pictures,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
33030c23f6e25e30b140615bb190d5e1632c3d3b,Toward a General Framework for Words and Pictures,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
33030c23f6e25e30b140615bb190d5e1632c3d3b,Toward a General Framework for Words and Pictures,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
@@ -706,6 +1913,8 @@ 33030c23f6e25e30b140615bb190d5e1632c3d3b,Toward a General Framework for Words and Pictures,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
33030c23f6e25e30b140615bb190d5e1632c3d3b,Toward a General Framework for Words and Pictures,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
33ba256d59aefe27735a30b51caf0554e5e3a1df,Early Active Learning via Robust Representation and Structured Sparsity,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+33e1398b73c9789debed1168536c93632c6f3f10,Efficiently Scaling Out-of-Order Cores for Simultaneous Multithreading,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+33801601485eaa27b838a17e073d81796d8b78d9,A Method to Track Targets in Three-Dimensional Space Using an Imaging Sonar,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
33c3702b0eee6fc26fc49f79f9133f3dd7fa3f13,Machine learning techniques for automated analysis of facial expressions,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
33aff42530c2fd134553d397bf572c048db12c28,From Emotions to Action Units with Hidden and Semi-Hidden-Task Learning,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
33aff42530c2fd134553d397bf572c048db12c28,From Emotions to Action Units with Hidden and Semi-Hidden-Task Learning,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
@@ -713,18 +1922,59 @@ 3328413ee9944de1cc7c9c1d1bf2fece79718ba1,Co-Training of Audio and Video Representations from Self-Supervised Temporal Synchronization,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
3328413ee9944de1cc7c9c1d1bf2fece79718ba1,Co-Training of Audio and Video Representations from Self-Supervised Temporal Synchronization,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
3399f8f0dff8fcf001b711174d29c9d4fde89379,Face R-CNN,Tencent,"Tencent AI Lab, China","Ke Ji Zhong Yi Lu, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057",22.54471540,113.93571640,company,"Keji Middle 1st Rd, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057"
+335af998fd86806422a4500ee6defc26df8a5388,Nonlinear Dimensionality Reduction Applied to the Binary Classification of Images,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+335af998fd86806422a4500ee6defc26df8a5388,Nonlinear Dimensionality Reduction Applied to the Binary Classification of Images,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+3394168ff0719b03ff65bcea35336a76b21fe5e4,Object Detection Combining Recognition and Segmentation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+3394168ff0719b03ff65bcea35336a76b21fe5e4,Object Detection Combining Recognition and Segmentation,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+3394168ff0719b03ff65bcea35336a76b21fe5e4,Object Detection Combining Recognition and Segmentation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+3394168ff0719b03ff65bcea35336a76b21fe5e4,Object Detection Combining Recognition and Segmentation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+3394168ff0719b03ff65bcea35336a76b21fe5e4,Object Detection Combining Recognition and Segmentation,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+33595d1135d9eecbda62bc568d2545aa3161276d,Resampling for Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+336067ade694c79b5838b2e8158acf18546bc5a5,Visually-Aware Personalized Recommendation using Interpretable Image Representations,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+336067ade694c79b5838b2e8158acf18546bc5a5,Visually-Aware Personalized Recommendation using Interpretable Image Representations,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+33737f966cca541d5dbfb72906da2794c692b65b,Spotting Audio-Visual Inconsistencies (SAVI) in Manipulated Video,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
+33737f966cca541d5dbfb72906da2794c692b65b,Spotting Audio-Visual Inconsistencies (SAVI) in Manipulated Video,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+332740a7ababbfa0dbc974433bd5a213197c0dd1,Spectral error correcting output codes for efficient multiclass recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+332740a7ababbfa0dbc974433bd5a213197c0dd1,Spectral error correcting output codes for efficient multiclass recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+334e559e8decadcedbe8e495b3f5430536cff32c,"The Attentional Suppressive Surround: Eccentricity, Location-Based and Feature-Based Effects and Interactions",York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+334e559e8decadcedbe8e495b3f5430536cff32c,"The Attentional Suppressive Surround: Eccentricity, Location-Based and Feature-Based Effects and Interactions",York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+334e559e8decadcedbe8e495b3f5430536cff32c,"The Attentional Suppressive Surround: Eccentricity, Location-Based and Feature-Based Effects and Interactions",University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+334e559e8decadcedbe8e495b3f5430536cff32c,"The Attentional Suppressive Surround: Eccentricity, Location-Based and Feature-Based Effects and Interactions",University of Dundee,University of Dundee,"University of Dundee, Park Wynd, Law, Dundee, Dundee City, Scotland, DD1 4HN, UK",56.45796755,-2.98214831,edu,
+33f2761d08da1c5b1b6a8f65ee6930075cf9927e,Hyperspectral Image Classification Using Convolutional Neural Networks and Multiple Feature Learning,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+33f2761d08da1c5b1b6a8f65ee6930075cf9927e,Hyperspectral Image Classification Using Convolutional Neural Networks and Multiple Feature Learning,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
3312eb79e025b885afe986be8189446ba356a507,MOON: A Mixed Objective Optimization Network for the Recognition of Facial Attributes,University of Colorado at Colorado Springs,University of Colorado at Colorado Springs,"1420 Austin Bluffs Pkwy, Colorado Springs, CO 80918, USA",38.89646790,-104.80505940,edu,
+3303f6694fa1c48afbd6e104b72e98b7f52b1651,Perceptual Adversarial Networks for Image-to-Image Transformation,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+3303f6694fa1c48afbd6e104b72e98b7f52b1651,Perceptual Adversarial Networks for Image-to-Image Transformation,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+3342018e8defb402896d2133cda0417e49f1e9aa,Face Verification Across Age Progression,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
33402ee078a61c7d019b1543bb11cc127c2462d2,Self-Supervised Video Representation Learning with Odd-One-Out Networks,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+337dd4aaca2c5f9b5d2de8e0e2401b5a8feb9958,Data-specific Adaptive Threshold for Face Recognition and Authentication,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
+33133bf1625a469b7c6ac6a2c05c6849584d87bf,Active Learning in Face Recognition: Using Tracking to Build a Face Model,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
33f2b44742cc828347ccc5ec488200c25838b664,Pooling the Convolutional Layers in Deep ConvNets for Action Recognition,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
33f2b44742cc828347ccc5ec488200c25838b664,Pooling the Convolutional Layers in Deep ConvNets for Action Recognition,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+33867c617e9f264c9e857d73358e0fd5b60a149a,Face Reconstruction on Mobile Devices Using a Height Map Shape Model and Fast Regularization,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+33867c617e9f264c9e857d73358e0fd5b60a149a,Face Reconstruction on Mobile Devices Using a Height Map Shape Model and Fast Regularization,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+337e67c8c5247695bb384c35272beaf47d464c75,Deep Adaptive Learning for Writer Identification based on Single Handwritten Word Images,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
334ac2a459190b41923be57744aa6989f9a54a51,Apples to Oranges: Evaluating Image Annotations from Natural Language Processing Systems,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
33ef419dffef85443ec9fe89a93f928bafdc922e,SelfKin: Self Adjusted Deep Model For Kinship Verification,Bar-Ilan University,Bar-Ilan University,"אוניברסיטת בר אילן, כביש גהה, גבעת שמואל, קריית מטלון, גבעת שמואל, מחוז תל אביב, NO, ישראל",32.06932925,34.84334339,edu,
+33f73cf297065ace7f27e8d449765f1c51ef163c,Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
33ad23377eaead8955ed1c2b087a5e536fecf44e,Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
33ad23377eaead8955ed1c2b087a5e536fecf44e,Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+33594e1bfe93fc6c74c2bcfc1bc39c524fa9e2ca,Alternating Regression Forests for Object Detection and Pose Estimation,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+33d682c52eb24875c556ec007bc38068d3e682c0,VisDA: The Visual Domain Adaptation Challenge,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+33d682c52eb24875c556ec007bc38068d3e682c0,VisDA: The Visual Domain Adaptation Challenge,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+3373ca46fa2c19112aebd772983ce70183ac1690,Somatosensory Representations Link the Perception of Emotional Expressions and Sensory Experience123,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+05904c87cb1d0b1f17fcb018fa0344c020694f36,Modulation of the composite face effect by unintended emotion cues,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
053b263b4a4ccc6f9097ad28ebf39c2957254dfb,Cost-Effective HITs for Relative Similarity Comparisons,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
053b263b4a4ccc6f9097ad28ebf39c2957254dfb,Cost-Effective HITs for Relative Similarity Comparisons,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
053b263b4a4ccc6f9097ad28ebf39c2957254dfb,Cost-Effective HITs for Relative Similarity Comparisons,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+05a26e093a101a9e6d9cac4e39a29afd6f1ca77e,Computational modeling of social face perception in humans : Leveraging the active appearance model,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+05a26e093a101a9e6d9cac4e39a29afd6f1ca77e,Computational modeling of social face perception in humans : Leveraging the active appearance model,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+05a26e093a101a9e6d9cac4e39a29afd6f1ca77e,Computational modeling of social face perception in humans : Leveraging the active appearance model,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
056d5d942084428e97c374bb188efc386791e36d,Temporally Robust Global Motion Compensation by Keypoint-Based Congealing,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+05e45f61dc7577c50114a382abc6e952ae24cdac,"Object Detection and Recognition in Natural Settings by George William Dittmar A thesis submitted in partial fulfilment of the requirements of the degree Master of Science in Computer Science Thesis Committee: Melanie Mitchell, Chair",Portland State University,Portland State University,"Portland State University, Southwest Park Avenue, University District, Portland Downtown, Portland, Multnomah County, Oregon, 97201, USA",45.51181205,-122.68492999,edu,
+050836151004b1997972c3fcbff0b85de8308e38,Matching and Predicting Street Level Images,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+050836151004b1997972c3fcbff0b85de8308e38,Matching and Predicting Street Level Images,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+05bac1f503ad77b095730f3b55214f7785b3f65d,A Multi-Layer Feature-Assisted Approach in Crowd-Labelling,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
0595d18e8d8c9fb7689f636341d8a55cc15b3e6a,Discriminant Analysis on Riemannian Manifold of Gaussian Distributions for Face Recognition With Image Sets,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
0595d18e8d8c9fb7689f636341d8a55cc15b3e6a,Discriminant Analysis on Riemannian Manifold of Gaussian Distributions for Face Recognition With Image Sets,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
0573f3d2754df3a717368a6cbcd940e105d67f0b,Emotion recognition in the wild challenge 2013,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
@@ -733,32 +1983,95 @@ 0573f3d2754df3a717368a6cbcd940e105d67f0b,Emotion recognition in the wild challenge 2013,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
05a0d04693b2a51a8131d195c68ad9f5818b2ce1,Dual-reference Face Retrieval: What Does He/She Look Like at Age 'X'?,University of East Anglia,University of East Anglia,"Arts (Lower Walkway Level), The Square, Westfield View, Earlham, Norwich, Norfolk, East of England, England, NR4 7TJ, UK",52.62215710,1.24091360,edu,
05a0d04693b2a51a8131d195c68ad9f5818b2ce1,Dual-reference Face Retrieval: What Does He/She Look Like at Age 'X'?,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+059bf35362d896dddd5ebcd5b1b93682efa9f46f,Additive Component Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0593bd23851b9f545ff7218887c09f4c62b7aaad,Detectability prediction in dynamic scenes for enhanced environment perception,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+0535101387033bf0b5ddf662a8c4d98caa1adc52,Fast Neighborhood Graph Search Using Cartesian Concatenation,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+0535101387033bf0b5ddf662a8c4d98caa1adc52,Fast Neighborhood Graph Search Using Cartesian Concatenation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
05a312478618418a2efb0a014b45acf3663562d7,Accelerated sampling for the Indian Buffet Process,Cambridge University,Cambridge University,"University, Cambridge Road, Old Portsmouth, Portsmouth, South East, England, PO1 2HB, UK",50.79440260,-1.09717480,edu,
+0568497f77d21122a6991e3d7147d5205451873a,Optimal feature selection for 3D facial expression recognition using coarse-to-fine classification,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
+05818eddd8a35fed7f3041d591ef966f8e79bd9a,Web scale photo hash clustering on a single machine,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
055de0519da7fdf27add848e691087e0af166637,Joint Unsupervised Face Alignment and Behaviour Analysis,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
0515e43c92e4e52254a14660718a9e498bd61cf5,Machine Learning Systems for Detecting Driver Drowsiness,Sabanci University,Sabanci University,"Sabanci Universitesi, Preveze Cad., Orta Mahallesi, Tepeören, Tuzla, İstanbul, Marmara Bölgesi, 34953, Türkiye",40.89271590,29.37863323,edu,
0515e43c92e4e52254a14660718a9e498bd61cf5,Machine Learning Systems for Detecting Driver Drowsiness,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
05891725f5b27332836cf058f04f18d74053803f,One-shot Action Localization by Learning Sequence Matching Network,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
05891725f5b27332836cf058f04f18d74053803f,One-shot Action Localization by Learning Sequence Matching Network,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+052651838d27835f39270101e140055e60a59d68,Enhancing Exemplar SVMs using Part Level Transfer Regularization,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+059582bee125512b127296364e7700ebd9f80436,Action-driven 3D indoor scene evolution,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+059582bee125512b127296364e7700ebd9f80436,Action-driven 3D indoor scene evolution,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+059582bee125512b127296364e7700ebd9f80436,Action-driven 3D indoor scene evolution,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+059582bee125512b127296364e7700ebd9f80436,Action-driven 3D indoor scene evolution,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
0568fc777081cbe6de95b653644fec7b766537b2,Learning Expressionlets on Spatio-temporal Manifold for Dynamic Facial Expression Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
0568fc777081cbe6de95b653644fec7b766537b2,Learning Expressionlets on Spatio-temporal Manifold for Dynamic Facial Expression Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
0568fc777081cbe6de95b653644fec7b766537b2,Learning Expressionlets on Spatio-temporal Manifold for Dynamic Facial Expression Recognition,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+05929f5a20147fe4349b6fe76819c023e53ad8f6,Minimizing Supervision for Free-space Segmentation,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+05929f5a20147fe4349b6fe76819c023e53ad8f6,Minimizing Supervision for Free-space Segmentation,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+05fa7085663bbbd1057c0d240158091930c59c6a,MovieQA: Understanding Stories in Movies through Question-Answering,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
05d80c59c6fcc4652cfc38ed63d4c13e2211d944,On sampling-based approximate spectral decomposition,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+05fdd29536d55fe3ad00689b6f60ada8bc761e91,HOGgles: Visualizing Object Detection Features,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+0574dc64c8275b09ed587dc3977f4d3c990bd4df,Context-Aware Visual Policy Network for Sequence-Level Image Captioning,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+05f0b43fe16282656cf1fdce919ac0f9d433f4a5,Future Person Localization in First-Person Videos,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+05f0b43fe16282656cf1fdce919ac0f9d433f4a5,Future Person Localization in First-Person Videos,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+05f0b43fe16282656cf1fdce919ac0f9d433f4a5,Future Person Localization in First-Person Videos,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+05f0b43fe16282656cf1fdce919ac0f9d433f4a5,Future Person Localization in First-Person Videos,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+05bb9a8877a82a474db3a0ee65772028a715e8cd,Learning mid-level features from object hierarchy for image classification,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+05bb9a8877a82a474db3a0ee65772028a715e8cd,Learning mid-level features from object hierarchy for image classification,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
055530f7f771bb1d5f352e2758d1242408d34e4d,A Facial Expression Recognition System from Depth Video,SungKyunKwan University,SungKyunKwan University,"성균관대, 덕영대로, 천천동, 장안구, 수원시, 경기, 16357, 대한민국",37.30031270,126.97212300,edu,
+05812833afba3b2a5a4b54853b0a1ed1cc8932d1,Fast planar object detection and tracking via edgel templates,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+053a4e5a89716f3f9e71bd09718bd9021a5114e0,Privacy considerations for a pervasive eye tracking world,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+053a4e5a89716f3f9e71bd09718bd9021a5114e0,Privacy considerations for a pervasive eye tracking world,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
050eda213ce29da7212db4e85f948b812a215660,Combining Models and Exemplars for Face Recognition: An Illuminating Example,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
050eda213ce29da7212db4e85f948b812a215660,Combining Models and Exemplars for Face Recognition: An Illuminating Example,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+059dc8bbf912caed67f287ad8811d3fb41fa2eba,Exemplar-based linear discriminant analysis for robust object tracking,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+05b6c32304dd1673c14f1e1efce4e4d5c4402275,What are the Visual Features Underlying Rapid Object Recognition?,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+05b6c32304dd1673c14f1e1efce4e4d5c4402275,What are the Visual Features Underlying Rapid Object Recognition?,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+05014b04223562c7c7485a1277552564d0ddc6de,Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN),"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
05e3acc8afabc86109d8da4594f3c059cf5d561f,Actor-Action Semantic Segmentation with Grouping Process Models,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+053f5a00d58541c417693a4e08a76005e135486e,Generating Animations by Sketching in Conceptual Space,Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
+05455f5e3c3989be4991cb74b73cdfd0d6522622,Learning Warped Guidance for Blind Face Restoration,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+05455f5e3c3989be4991cb74b73cdfd0d6522622,Learning Warped Guidance for Blind Face Restoration,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+05455f5e3c3989be4991cb74b73cdfd0d6522622,Learning Warped Guidance for Blind Face Restoration,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
052f994898c79529955917f3dfc5181586282cf8,Unsupervised Domain Adaptation for Face Recognition in Unlabeled Videos,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
05318a267226f6d855d83e9338eaa9e718b2a8dd,Age estimation from face images: challenging problem for audience measurement systems,Yaroslavl State University,Yaroslavl State University,"ЯрГУ им. Демидова (Экономический факультет), 3, Комсомольская улица, Кировский район, Ярославль, городской округ Ярославль, Ярославская область, ЦФО, 150000, РФ",57.62521030,39.88456560,edu,
+05f3cc64e640a9aca2d0e6086aa6efaf103a3fe2,Robot-centric Activity Recognition from First-Person RGB-D Videos,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+05f3cc64e640a9aca2d0e6086aa6efaf103a3fe2,Robot-centric Activity Recognition from First-Person RGB-D Videos,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+05b0383b4cfe007bbad92e72ee361f95e7e9a458,Fast Matching of Binary Features,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
057d5f66a873ec80f8ae2603f937b671030035e6,Newtonian Image Understanding: Unfolding the Dynamics of Objects in Static Images,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+0549dc0290fe988ede74c4e030ae485c13eaa54a,Development of Vision Based Multiview Gait Recognition System with MMUGait Database,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+05f3f8f6f97db00bafa2efd2ac9aac570603c0c6,TGIF: A New Dataset and Benchmark on Animated GIF Description,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+05f3f8f6f97db00bafa2efd2ac9aac570603c0c6,TGIF: A New Dataset and Benchmark on Animated GIF Description,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+05b603d7c6004de3c028e40b4434804f752290b9,Combining Skeletal Pose with Local Motion for Human Activity Recognition,University at Buffalo,State University of New York at Buffalo,"Buffalo, NY 14260, USA",43.00080930,-78.78896970,edu,
050a3346e44ca720a54afbf57d56b1ee45ffbe49,Multi-cue Zero-Shot Learning with Strong Supervision,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
0517d08da7550241fb2afb283fc05d37fce5d7b7,Combination of Local Multiple Patterns and Exponential Discriminant Analysis for Facial Recognition,Chongqing University,Chongqing University,"重庆工商大学, 19, 翠林路, 重庆市, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400067, 中国",29.50841740,106.57858552,edu,
+053f9b10532a87e346fad281e0be81337cb525a5,Session Variability Modelling for Face Authentication,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+058d50af5456665dccda2b41b17bdfead72bdec8,Learning Non-Metric Visual Similarity for Image Retrieval,Aston University,Aston University,"Aston University, Aston Street, Digbeth, Birmingham, West Midlands Combined Authority, West Midlands, England, B4, UK",52.48620785,-1.88849915,edu,
+058d50af5456665dccda2b41b17bdfead72bdec8,Learning Non-Metric Visual Similarity for Image Retrieval,Aston University,Aston University,"Aston University, Aston Street, Digbeth, Birmingham, West Midlands Combined Authority, West Midlands, England, B4, UK",52.48620785,-1.88849915,edu,
053931267af79a89791479b18d1b9cde3edcb415,Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
05f3d1e9fb254b275354ca69018e9ed321dd8755,Face Recognition using Optimal Representation Ensemble,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
051f03bc25ec633592aa2ff5db1d416b705eac6c,Partial face recognition: An alignment free approach,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+9d4c467adc09fb50c5e799fc124f3e82da8c3c22,Temporal Sequence Distillation: Towards Few-Frame Action Recognition in Videos,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+9d4c467adc09fb50c5e799fc124f3e82da8c3c22,Temporal Sequence Distillation: Towards Few-Frame Action Recognition in Videos,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
9d8ff782f68547cf72b7f3f3beda9dc3e8ecfce6,Improved Pseudoinverse Linear Discriminant Analysis Method for Dimensionality Reduction,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
9d55ec73cab779403cd933e6eb557fb04892b634,Kernel principal component analysis network for image classification,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+9d5ec256ee5a6ee2d9602f651e88132f2669f690,A novel M-estimator for robust PCA,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+9d5ec256ee5a6ee2d9602f651e88132f2669f690,A novel M-estimator for robust PCA,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+9dfd1e9daea4c54a05b06df905bf8ee1faccaa72,"New l2, 1-Norm Relaxation of Multi-Way Graph Cut for Clustering",Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+9dfd1e9daea4c54a05b06df905bf8ee1faccaa72,"New l2, 1-Norm Relaxation of Multi-Way Graph Cut for Clustering",Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+9dfd1e9daea4c54a05b06df905bf8ee1faccaa72,"New l2, 1-Norm Relaxation of Multi-Way Graph Cut for Clustering",Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+9d422e2c318ab63e6b49c83053757b4636f8308b,Object localization in ImageNet by looking out of the window,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+9dd227edfeb472076346cbe2c49811d1778a43a8,Domain-Invariant Projection Learning for Zero-Shot Recognition,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+9ded64e83d3ba51513ea00de27c0c770a02b0cf4,Image Classification using Transfer Learning from Siamese Networks based on Text Metadata Similarity,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
9d66de2a59ec20ca00a618481498a5320ad38481,POP: Privacy-Preserving Outsourced Photo Sharing and Searching for Mobile Devices,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
9d66de2a59ec20ca00a618481498a5320ad38481,POP: Privacy-Preserving Outsourced Photo Sharing and Searching for Mobile Devices,Illinois Institute of Technology,Illinois Institute of Technology,"Illinois Institute of Technology, South State Street, Bronzeville, Chicago, Cook County, Illinois, 60616, USA",41.83619630,-87.62655913,edu,
+9d3472849dc2cadf194ae29adbf46bdda861d8b7,Learning to Ask: Neural Question Generation for Reading Comprehension,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+9d3472849dc2cadf194ae29adbf46bdda861d8b7,Learning to Ask: Neural Question Generation for Reading Comprehension,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+9db7af606e6eb6238ca900145c8270245e9d2959,PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+9db7af606e6eb6238ca900145c8270245e9d2959,PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+9d6c5dc5b212d8a8e94e7c52b0a2e4550aa2e117,Eye tracking studies of normative and atypical development q,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+9d4ebcd84c4ba2241cca3242e22888558b62a0e0,Demonstration of Santoku: Optimizing Machine Learning over Normalized Data,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+9d9106d48e30c07d45ab07c21f8c35d11ae4d35d,Under Review as a Conference Paper at Iclr 2017 Learning to Draw Samples: with Application to Amortized Mle for Generative Adversar- Ial Learning,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+9d7edd114f788763bb16280249fae97c4aa2c102,Image Quality Assessment Techniques Show Improved Training and Evaluation of Autoencoder Generative Adversarial Networks,Carleton University,Carleton University,"Carleton University, 1125, Colonel By Drive, Billings Bridge, Capital, Ottawa, Ontario, K1S 5B7, Canada",45.38608430,-75.69539267,edu,
+9de6b3f7a60cea9749ae38ad9b700a7350212350,Non-frontal view facial expression recognition based on ergodic hidden Markov model supervectors,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+9d146936d7d06622e271764c8a050a92bc168f3c,GAD: General Activity Detection for Fast Clustering on Large Data,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
9dcc6dde8d9f132577290d92a1e76b5decc6d755,Facial Expression Analysis Based on Optimized Gabor Features,Istanbul University,Istanbul University,"İstanbul Üniversitesi, Besim Ömerpaşa Caddesi, Süleymaniye, Fatih, İstanbul, Marmara Bölgesi, 34116, Türkiye",41.01324240,28.96376090,edu,
9dcc6dde8d9f132577290d92a1e76b5decc6d755,Facial Expression Analysis Based on Optimized Gabor Features,Bahçeşehir University,Bahcesehir University,"BAU Galata, 24, Kemeraltı Caddesi, Müeyyedzade, Beyoğlu, İstanbul, Marmara Bölgesi, 34425, Türkiye",41.02451875,28.97697953,edu,
9d57c4036a0e5f1349cd11bc342ac515307b6720,Landmark Weighting for 3DMM Shape Fitting,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
@@ -767,198 +2080,533 @@ 9d941a99e6578b41e4e32d57ece580c10d578b22,Illumination-Invariant and Deformation-Tolerant Inner Knuckle Print Recognition Using Portable Devices,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
9d941a99e6578b41e4e32d57ece580c10d578b22,Illumination-Invariant and Deformation-Tolerant Inner Knuckle Print Recognition Using Portable Devices,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
9d941a99e6578b41e4e32d57ece580c10d578b22,Illumination-Invariant and Deformation-Tolerant Inner Knuckle Print Recognition Using Portable Devices,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+9db7bc834ad534d48b22a87ab5f706833cc18d79,Applications of Scene Attributes,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
9d896605fbf93315b68d4ee03be0770077f84e40,Baby Talk: Understanding and Generating Image Descriptions,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
9d896605fbf93315b68d4ee03be0770077f84e40,Baby Talk: Understanding and Generating Image Descriptions,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
9d61b0beb3c5903fc3032655dc0fd834ec0b2af3,Learning a Locality Preserving Subspace for Visual Recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+9d7b2d1f3d6705bc8a4656fa27fb6dde20033f25,A discriminative key pose sequence model for recognizing human interactions,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+9ded7bd7ee896de568cbb0281ec553c21de93131,Face recognition using a novel image representation scheme and multi-scale local features,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+9ded7bd7ee896de568cbb0281ec553c21de93131,Face recognition using a novel image representation scheme and multi-scale local features,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+9ded7bd7ee896de568cbb0281ec553c21de93131,Face recognition using a novel image representation scheme and multi-scale local features,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
+9dd47158cd7ee3725be3aa7a2ce9b25a7d4aed74,Clustering-driven Deep Embedding with Pairwise Constraints,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+9dd47158cd7ee3725be3aa7a2ce9b25a7d4aed74,Clustering-driven Deep Embedding with Pairwise Constraints,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+9dd47158cd7ee3725be3aa7a2ce9b25a7d4aed74,Clustering-driven Deep Embedding with Pairwise Constraints,Bar-Ilan University,Bar-Ilan University,"אוניברסיטת בר אילן, כביש גהה, גבעת שמואל, קריית מטלון, גבעת שמואל, מחוז תל אביב, NO, ישראל",32.06932925,34.84334339,edu,
+9dd47158cd7ee3725be3aa7a2ce9b25a7d4aed74,Clustering-driven Deep Embedding with Pairwise Constraints,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
9d3aa3b7d392fad596b067b13b9e42443bbc377c,Facial Biometric Templates and Aging: Problems and Challenges for Artificial Intelligence,Cyprus University of Technology,Cyprus University of Technology,"Mitropoli Building - Cyprus University of Technology, Anexartisias, Limasol - Λεμεσός, Limassol - Λεμεσός, Κύπρος - Kıbrıs, 3036, Κύπρος - Kıbrıs",34.67567405,33.04577648,edu,
9db4b25df549555f9ffd05962b5adf2fd9c86543,Nonlinear 3D Face Morphable Model,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+9d3a6e459e0cecda20a8afd69d182877ff0224cf,A Framework for Articulated Hand Pose Estimation and Evaluation,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
9d06d43e883930ddb3aa6fe57c6a865425f28d44,Clustering Appearances of Objects Under Varying Illumination Conditions,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+9c513b0f304b1bb29de478a1227ddb201ed50217,A Simple and Effective Technique for Face Clustering in TV Series,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+9c2aea0bd67c7fe232cca54ee2440b9d666479ea,Recycle-GAN: Unsupervised Video Retargeting,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9c7d3d2a524aedb8bf687441f26dac5ed8c490c5,Visual Explanations from Hadamard Product in Multimodal Deep Networks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+9c7d3d2a524aedb8bf687441f26dac5ed8c490c5,Visual Explanations from Hadamard Product in Multimodal Deep Networks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+9ca0626366e136dac6bfd628cec158e26ed959c7,In-the-wild Facial Expression Recognition in Extreme Poses,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
9c9ef6a46fb6395702fad622f03ceeffbada06e5,Exchanging Faces in Images,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
9c1cdb795fd771003da4378f9a0585730d1c3784,Stacked Deformable Part Model with Shape Regression for Object Part Localization,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+9cd0d36af668c354b0ff17f2e21cdde2c16b0d4e,Generative One-Class Models for Text-based Person Retrieval in Forensic Applications,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+9c43b59177cb5539ea649c188387fe374663bbb1,Learning Discriminative Latent Attributes for Zero-Shot Classification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+9c9ba660ff8fdf74a81ceaae5ee2e590c7659cf8,Real-Time Pedestrian Tracking with Bacterial Foraging Optimization,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+9c85d54a9f6c6a522a267bfdf375251947caef5e,Recognition of Blurred Faces via Facial Deblurring Combined with Blur-Tolerant Descriptors,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+9c85d54a9f6c6a522a267bfdf375251947caef5e,Recognition of Blurred Faces via Facial Deblurring Combined with Blur-Tolerant Descriptors,Institute of Industrial Science,Institute of Industrial Science,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+9c85d54a9f6c6a522a267bfdf375251947caef5e,Recognition of Blurred Faces via Facial Deblurring Combined with Blur-Tolerant Descriptors,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
9c25e89c80b10919865b9c8c80aed98d223ca0c6,Gender Prediction by Gait Analysis Based on Time Series Variation of Joint Positions,Meiji University,Meiji University,"明治大学, 錦華坂, 猿楽町1, 猿楽町, 東京, 千代田区, 東京都, 関東地方, 101-0051, 日本",35.69750290,139.76139175,edu,
9c25e89c80b10919865b9c8c80aed98d223ca0c6,Gender Prediction by Gait Analysis Based on Time Series Variation of Joint Positions,Meiji University,Meiji University,"明治大学, 錦華坂, 猿楽町1, 猿楽町, 東京, 千代田区, 東京都, 関東地方, 101-0051, 日本",35.69750290,139.76139175,edu,
+9c09b9410da8b1c5f0e3f6b65502160734214782,Pedestrian Attribute Detection Using CNN,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+9c09b9410da8b1c5f0e3f6b65502160734214782,Pedestrian Attribute Detection Using CNN,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
9c7444c6949427994b430787a153d5cceff46d5c,Boosting Kernel Discriminative Common Vectors for Face Recognition,Bharathidasan University,Bharathidasan University,"Bharathidasan University Road, Kajamalai, Ponmalai, Ponmalai Zone, Tiruchchirāppalli, Tiruchchirappalli district, Tamil Nadu, 620020, India",10.77788450,78.69663190,edu,
9c373438285101d47ab9332cdb0df6534e3b93d1,Occupancy Detection in Vehicles Using Fisher Vector Image Representation,Xerox Research Center,Xerox Research Center,"Xerox Research Centre of Canada, 2660, Speakman Drive, Sheridan Park, Erin Mills, Ont., Peel Region, Ontario, L5J 2M4, Canada",43.51291090,-79.66640762,edu,
9c373438285101d47ab9332cdb0df6534e3b93d1,Occupancy Detection in Vehicles Using Fisher Vector Image Representation,Xerox Research Center,Xerox Research Center,"Xerox Research Centre of Canada, 2660, Speakman Drive, Sheridan Park, Erin Mills, Ont., Peel Region, Ontario, L5J 2M4, Canada",43.51291090,-79.66640762,edu,
9cbb6e42a35f26cf1d19f4875cd7f6953f10b95d,Expression Recognition with Ri-HOG Cascade,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
9cbb6e42a35f26cf1d19f4875cd7f6953f10b95d,Expression Recognition with Ri-HOG Cascade,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+9cc43e3a756485b78b991605f44eec9be3530350,A Planar Light Probe,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+9c62f4b09ca590f74c75115184fc1a9833625edc,Empathic arousal and social understanding in individuals with autism: evidence from fMRI and ERP measurements.,University of Chicago,THE UNIVERSITY OF CHICAGO,"University of Chicago, South Ellis Avenue, Woodlawn, Chicago, Cook County, Illinois, 60637, USA",41.78468745,-87.60074933,edu,
+9c958322235a3ea1f239e3dde9bb865931cf34ed,Locality-Constrained Low-Rank Coding for Image Classification,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+9c71e6f4e27b3a6f0f872ec683b0f6dfe0966c05,"Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey",Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
9c4cc11d0df2de42d6593f5284cfdf3f05da402a,Enhanced Fisher linear discriminant models for face recognition,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
9cd6a81a519545bf8aa9023f6e879521f85d4cd1,Domain-invariant Face Recognition using Learned Low-rank Transformation,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
9cd6a81a519545bf8aa9023f6e879521f85d4cd1,Domain-invariant Face Recognition using Learned Low-rank Transformation,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
9cd6a81a519545bf8aa9023f6e879521f85d4cd1,Domain-invariant Face Recognition using Learned Low-rank Transformation,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+9c2e5e2ba7c5b3a555c6c72f518e3631aab23c19,RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
9cadd166893f1b8aaecb27280a0915e6694441f5,Multi-Modal Emotion Recognition Fusing Video and Audio,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
9cadd166893f1b8aaecb27280a0915e6694441f5,Multi-Modal Emotion Recognition Fusing Video and Audio,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+02607f5d3c7638d0207279d96f39d435f102bf4d,Assignment 4: Reading Comprehension,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+02b1a5d4b113211198e9c66d51153eb63ca680e2,Scene Invariant Crowd Segmentation and Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG),University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+02b1a5d4b113211198e9c66d51153eb63ca680e2,Scene Invariant Crowd Segmentation and Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG),University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+02c3432b5d97b4ed7b8522c1fc4388bd4eda8e67,Using context to improve cascaded pedestrian detection,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
02cc96ad997102b7c55e177ac876db3b91b4e72c,"MuseumVisitors: A dataset for pedestrian and group detection, gaze estimation and behavior understanding",University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
02cc96ad997102b7c55e177ac876db3b91b4e72c,"MuseumVisitors: A dataset for pedestrian and group detection, gaze estimation and behavior understanding",Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+02c44e0a7bb179be03601a7abedb006a28ad4e23,Treepedia 2.0: Applying Deep Learning for Large-Scale Quantification of Urban Tree Cover,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+02227c94dd41fe0b439e050d377b0beb5d427cda,Reading Digits in Natural Images with Unsupervised Feature Learning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
023ed32ac3ea6029f09b8c582efbe3866de7d00a,Discriminative learning from partially annotated examples,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
023ed32ac3ea6029f09b8c582efbe3866de7d00a,Discriminative learning from partially annotated examples,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+02d2c2b0ee77fec8d85c114c20fdae318e95a1bd,Human - Computer interaction for smart environment applications using hand gestures and facial expressions,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
0290523cabea481e3e147b84dcaab1ef7a914612,Generated Motion Maps,Tokyo Denki University,Tokyo Denki University,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
0229829e9a1eed5769a2b5eccddcaa7cd9460b92,Pooled motion features for first-person videos,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+02e05ad42dbe99257eee1bff3e28feaa005e5924,Remembering Who Was Where: A Happy Expression Advantage for Face Identity-Location Binding in Working Memory,University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
+02e05ad42dbe99257eee1bff3e28feaa005e5924,Remembering Who Was Where: A Happy Expression Advantage for Face Identity-Location Binding in Working Memory,University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
+02b852e698dfe85df39c24e7dd39dedf484893dd,Collaborative Learning for Weakly Supervised Object Detection,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
025720574ef67672c44ba9e7065a83a5d6075c36,Unsupervised Learning of Video Representations using LSTMs,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+02c04a8b7c1232646ebc882caf3793327a510ba6,Cost-Effectiveness of Seven Approaches to Map Vegetation Communities - A Case Study from Northern Australia's Tropical Savannas,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
026e4ee480475e63ae68570d73388f8dfd4b4cde,Evaluating gender portrayal in Bangladeshi TV,Eastern University,Eastern University,"Eastern University, Huston Road, Radnor Township, Delaware County, Pennsylvania, 19087, USA",40.05056720,-75.37109326,edu,
026e4ee480475e63ae68570d73388f8dfd4b4cde,Evaluating gender portrayal in Bangladeshi TV,Dhaka University,Dhaka University,"Faculty of Social Welfare, Dhaka University, Azimpur Koborsthan Road, বস্তি, হাজারীবাগ, ঢাকা, ঢাকা বিভাগ, 1950, বাংলাদেশ",23.73179150,90.38056250,edu,
026e4ee480475e63ae68570d73388f8dfd4b4cde,Evaluating gender portrayal in Bangladeshi TV,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
02e628e99f9a1b295458cb453c09863ea1641b67,Two-Stage Convolutional Part Heatmap Regression for the 1st 3D Face Alignment in the Wild (3DFAW) Challenge,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+02f8c803fbf02bae0cd4ba8943fe3acccdf37402,The Bogazici face database: Standardized photographs of Turkish faces with supporting materials,Universitat Autònoma de Barcelona,Universitat Autònoma de Barcelona,"Centre de Visió per Computador (CVC), Carrer de l'Albareda, Serraperera, UAB, Cerdanyola del Vallès, Vallès Occidental, BCN, CAT, 08214, España",41.50078110,2.11143663,edu,
+02ddda27cef81c363ffffc4edfdfbd1dea14149e,Predicting People's 3D Poses from Short Sequences,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
02f4b900deabbe7efa474f2815dc122a4ddb5b76,Local and Global Optimization Techniques in Graph-based Clustering,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+02be981d45a8ca14e30e1cf9dfffd977f85e6ee4,Top-down saliency with Locality-constrained Contextual Sparse Coding,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+02fa3f9517bfede1c2b61570f792f6ed8de364f3,Detection of Human Rights Violations in Images: Can Convolutional Neural Networks Help?,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
+02fa3f9517bfede1c2b61570f792f6ed8de364f3,Detection of Human Rights Violations in Images: Can Convolutional Neural Networks Help?,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
026b5b8062e5a8d86c541cfa976f8eee97b30ab8,MDLFace: Memorability augmented deep learning for video face recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
0235b2d2ae306b7755483ac4f564044f46387648,Recognition of Facial Attributes Using Adaptive Sparse Representations of Random Patches,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+02a2fa826a348cc3bc46a1a31a49dce8d06ca366,Individual differences in the spontaneous recruitment of brain regions supporting mental state understanding when viewing natural social scenes.,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+02a2fa826a348cc3bc46a1a31a49dce8d06ca366,Individual differences in the spontaneous recruitment of brain regions supporting mental state understanding when viewing natural social scenes.,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+02218fcd3aece5a7bd19255d74b12f63dfa5c1a7,ShapeWorld - A new test methodology for multimodal language understanding,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+02218fcd3aece5a7bd19255d74b12f63dfa5c1a7,ShapeWorld - A new test methodology for multimodal language understanding,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
02467703b6e087799e04e321bea3a4c354c5487d,Grouper: Optimizing Crowdsourced Face Annotations,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
02e39f23e08c2cb24d188bf0ca34141f3cc72d47,Removing illumination artifacts from face images using the nuisance attribute projection,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+022c485c5617bbf0b7f40475f9758cddd11a91af,Describing Textures in the Wild,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+022c485c5617bbf0b7f40475f9758cddd11a91af,Describing Textures in the Wild,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
023be757b1769ecb0db810c95c010310d7daf00b,Face Alignment Assisted by Head Pose Estimation,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
023be757b1769ecb0db810c95c010310d7daf00b,Face Alignment Assisted by Head Pose Estimation,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
023be757b1769ecb0db810c95c010310d7daf00b,Face Alignment Assisted by Head Pose Estimation,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+0239d0af254c5304414db1672ea25ad2e1cdf2ee,Implicit Shape Kernel for Discriminative Learning of the Hough Transform Detector,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+0269312a7d49209fd9f1875e24df6a1d178fb15c,Subject centric group feature for person re-identification,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
0209389b8369aaa2a08830ac3b2036d4901ba1f1,DenseReg: Fully Convolutional Dense Shape Regression In-the-Wild,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
0209389b8369aaa2a08830ac3b2036d4901ba1f1,DenseReg: Fully Convolutional Dense Shape Regression In-the-Wild,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
02239ae5e922075a354169f75f684cad8fdfd5ab,Commonly Uncommon: Semantic Sparsity in Situation Recognition,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
02239ae5e922075a354169f75f684cad8fdfd5ab,Commonly Uncommon: Semantic Sparsity in Situation Recognition,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
+02aa54dbb461f6bde6fe8ba0591c3c5cabed7e59,Residual Attention Networks for Image Classification,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
02d650d8a3a9daaba523433fbe93705df0a7f4b1,How Does Aging Affect Facial Components?,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
0294f992f8dfd8748703f953925f9aee14e1b2a2,Blur-Robust Face Recognition via Transformation Learning,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
02820c1491b10a1ff486fed32c269e4077c36551,Active user authentication for smartphones: A challenge data set and benchmark results,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
02820c1491b10a1ff486fed32c269e4077c36551,Active user authentication for smartphones: A challenge data set and benchmark results,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+027f769aed0cfcb3169ef60f182ce1decc0e99eb,Local Directional Pattern (LDP) for face recognition,Kyung Hee University,Kyung Hee University,"Kyung Hee Tae Kwon Do, Vons 2370 Truck Service Ramp, University City, San Diego, San Diego County, California, 92122, USA",32.85363330,-117.20352860,edu,
+02c8de83c3bd2226a918c925400628902b6f175a,"Size Matters! How Thumbnail Number, Size, and Motion Influence Mobile Video Retrieval",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+021c3e8c3c64c25126315911f31cab1edca82ab3,DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
a40edf6eb979d1ddfe5894fac7f2cf199519669f,Improving Facial Attribute Prediction Using Semantic Segmentation,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+a45ec771ca2db81088c52c173eed9ec2022a8a70,Impaired recognition of negative basic emotions in autism: a test of the amygdala theory.,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+a45ec771ca2db81088c52c173eed9ec2022a8a70,Impaired recognition of negative basic emotions in autism: a test of the amygdala theory.,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+a43c3ebeee65d44bbedac7548483485a14eacf52,Vocabulary-informed Extreme Value Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+a43c3ebeee65d44bbedac7548483485a14eacf52,Vocabulary-informed Extreme Value Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+a43c3ebeee65d44bbedac7548483485a14eacf52,Vocabulary-informed Extreme Value Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+a4d5ff6f1fb8b304c3e6fd5f1a7abd9b5c52955c,Spoofing 2D Face Detection: Machines See People Who Aren't There,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+a40b4bf3a921f07f4d07838f9092416189e077b5,Local Binary Convolutional Neural Networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a40b4bf3a921f07f4d07838f9092416189e077b5,Local Binary Convolutional Neural Networks,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+a40b4bf3a921f07f4d07838f9092416189e077b5,Local Binary Convolutional Neural Networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
a4876b7493d8110d4be720942a0f98c2d116d2a0,Multi-velocity neural networks for gesture recognition in videos,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+a4bb4474e38140d183241f0c8cee13167a6d2c60,Person Re-identification Using Clustering Ensemble Prototypes,"National Institute of Technology, Rourkela",National Institute of Technology Rourkela,"National Institute of Technology, inside the department, Koel Nagar, Rourkela, Sundargarh, Odisha, 769002, India",22.25015890,84.90668557,edu,
+a470a81f989d5354239f1044c90e07b78c6beed7,RPAN: An End-to-End Recurrent Pose-Attention Network for Action Recognition in Videos,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+a470a81f989d5354239f1044c90e07b78c6beed7,RPAN: An End-to-End Recurrent Pose-Attention Network for Action Recognition in Videos,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+a470a81f989d5354239f1044c90e07b78c6beed7,RPAN: An End-to-End Recurrent Pose-Attention Network for Action Recognition in Videos,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
a46086e210c98dcb6cb9a211286ef906c580f4e8,Fusing Multi-Stream Deep Networks for Video Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+a4f29217d2120ed1490aea7e1c5b78c3b76e972f,Enhanced object detection via fusion with prior beliefs from image classification,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+a4acd75470152933faf9957f04579aa662a912a0,Energy efficient job scheduling in single-ISA heterogeneous chip-multiprocessors,Louisiana State University,Louisiana State University,"LSU, Gourrier Avenue, Baton Rouge, East Baton Rouge Parish, Louisiana, 70803, USA",30.40550035,-91.18620474,edu,
+a46d4f5bf9c5baca38b52874e74d1e3f9b3b12cd,Evolutionary Generative Adversarial Networks,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+a46d4f5bf9c5baca38b52874e74d1e3f9b3b12cd,Evolutionary Generative Adversarial Networks,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+a46d4f5bf9c5baca38b52874e74d1e3f9b3b12cd,Evolutionary Generative Adversarial Networks,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
+a47f834281c39b1b851757b807c92f43dc975206,Multi task sequence learning for depression scale prediction from video,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+a47f834281c39b1b851757b807c92f43dc975206,Multi task sequence learning for depression scale prediction from video,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+a47f834281c39b1b851757b807c92f43dc975206,Multi task sequence learning for depression scale prediction from video,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+a47f834281c39b1b851757b807c92f43dc975206,Multi task sequence learning for depression scale prediction from video,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
a481e394f58f2d6e998aa320dad35c0d0e15d43c,Selectively guiding visual concept discovery,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+a30d5b636086d80791578cbd0e0b02d87ab42d27,Actionness-Assisted Recognition of Actions,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+a39d318b68a2c262b6351a05f447dfcb0555da88,Facial Expression Recognition Based on Local Fourier Coefficients and Facial Fourier Descriptors,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
a322479a6851f57a3d74d017a9cb6d71395ed806,Towards Pose Invariant Face Recognition in the Wild,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
a322479a6851f57a3d74d017a9cb6d71395ed806,Towards Pose Invariant Face Recognition in the Wild,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
a322479a6851f57a3d74d017a9cb6d71395ed806,Towards Pose Invariant Face Recognition in the Wild,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
a322479a6851f57a3d74d017a9cb6d71395ed806,Towards Pose Invariant Face Recognition in the Wild,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+a343bc9239a209af45c43f94b86651fd0074a364,Learning To Simulate,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+a35338cb4686cff66710b7f8102e5eabfc38adb8,Attribute-Augmented Semantic Hierarchy: Towards a Unified Framework for Content-Based Image Retrieval,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+a35338cb4686cff66710b7f8102e5eabfc38adb8,Attribute-Augmented Semantic Hierarchy: Towards a Unified Framework for Content-Based Image Retrieval,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+a35338cb4686cff66710b7f8102e5eabfc38adb8,Attribute-Augmented Semantic Hierarchy: Towards a Unified Framework for Content-Based Image Retrieval,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+a35338cb4686cff66710b7f8102e5eabfc38adb8,Attribute-Augmented Semantic Hierarchy: Towards a Unified Framework for Content-Based Image Retrieval,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+a35338cb4686cff66710b7f8102e5eabfc38adb8,Attribute-Augmented Semantic Hierarchy: Towards a Unified Framework for Content-Based Image Retrieval,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+a35338cb4686cff66710b7f8102e5eabfc38adb8,Attribute-Augmented Semantic Hierarchy: Towards a Unified Framework for Content-Based Image Retrieval,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
a301ddc419cbd900b301a95b1d9e4bb770afc6a3,DECK: Discovering Event Composition Knowledge from Web Images for Zero-Shot Event Detection and Recounting in Videos,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+a3c93737a4497350768b0dda08dbc0826670dc5b,Diagnosing state-of-the-art object proposal methods,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+a361e820a85fa91f23091068f8177c58489304b1,Hard to “tune in”: neural mechanisms of live face-to-face interaction with high-functioning autistic spectrum disorder,Nagoya University,Nagoya University,"SuperDARN (Hokkaido West), 太辛第1支線林道, 陸別町, 足寄郡, 十勝総合振興局, 北海道, 北海道地方, 日本",43.53750985,143.60768225,edu,
+a33edec6f5e544cde888409fd028b468a2e0bfba,Robust Subspace Clustering via Half-Quadratic Minimization,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+a34fb5c4b8b58ca19c376b1312e4d9955fe1d857,Deep Learning for Image Captioning,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
a3f684930c5c45fcb56a2b407d26b63879120cbf,LPM for Fast Action Recognition with Large Number of Classes,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
+a3825a14676c5f88478af2cd254ba4c531d5e92c,Multi-modal Cycle-Consistent Generalized Zero-Shot Learning,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+a36f8947c7e33f73157d3ffb0660776403fc197c,3D Geometry-Aware Semantic Labeling of Outdoor Street Scenes,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+a353d425a602d04f1dfde2142650fe0fb5193159,An Incremental Structured Part Model for Image Classification,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+a312599f9a842cf686c6cf80b770e05840d32a5a,MTS: A Multiple Temporal Scale Tracker Handling Occlusion and Abrupt Motion Variation,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+a3d0ebb50d49116289fb176d28ea98a92badada6,Unsupervised Learning of Object Landmarks through Conditional Image Generation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+a3d0ebb50d49116289fb176d28ea98a92badada6,Unsupervised Learning of Object Landmarks through Conditional Image Generation,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+a303fca91c181f1084d94948169ab73c45e2073e,Impact of Small Groups with Heterogeneous Preference on Behavioral Evolution in Population Evacuation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+a303fca91c181f1084d94948169ab73c45e2073e,Impact of Small Groups with Heterogeneous Preference on Behavioral Evolution in Population Evacuation,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+a36aa784e00d479bb0e6cb8aa6b6cd2dfeadfe1b,Evaluation of different features for face recognition in video,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
+a360526696a2698ad31dfca4c529e098d2dbdbd1,Image Captioning with Semantic Attention,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+a3fa023d7355662d066882df8dead0cac6a8321e,Supplementary Material for “Adversarial Inverse Graphics Networks: Learning 2D-to-3D Lifting and Image-to-Image Translation from Unpaired Supervision”,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a3f4f163e87b28901389e189bb7f0f655995793f,End-to-End Instance Segmentation and Counting with Recurrent Attention,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+a3f4f163e87b28901389e189bb7f0f655995793f,End-to-End Instance Segmentation and Counting with Recurrent Attention,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+a3f68fe7c296f6fa6ad508d1cf19d0f01f50e63f,Surveillance Face Super-Resolution via Shape Clustering and Subspace Learning,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+a3f68fe7c296f6fa6ad508d1cf19d0f01f50e63f,Surveillance Face Super-Resolution via Shape Clustering and Subspace Learning,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
a32d4195f7752a715469ad99cb1e6ebc1a099de6,The Potential of Using Brain Images for Authentication,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
a3d78bc94d99fdec9f44a7aa40c175d5a106f0b9,Recognizing Violence in Movies,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
a3d78bc94d99fdec9f44a7aa40c175d5a106f0b9,Recognizing Violence in Movies,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
a3d78bc94d99fdec9f44a7aa40c175d5a106f0b9,Recognizing Violence in Movies,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
a3d78bc94d99fdec9f44a7aa40c175d5a106f0b9,Recognizing Violence in Movies,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+a3dab83995f27ec8d09cbc06fe815ade88232d10,Probabilistic Group Testing under Sum Observations: A Parallelizable 2-Approximation for Entropy Loss,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+a3dab83995f27ec8d09cbc06fe815ade88232d10,Probabilistic Group Testing under Sum Observations: A Parallelizable 2-Approximation for Entropy Loss,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+a3dab83995f27ec8d09cbc06fe815ade88232d10,Probabilistic Group Testing under Sum Observations: A Parallelizable 2-Approximation for Entropy Loss,Portland State University,Portland State University,"Portland State University, Southwest Park Avenue, University District, Portland Downtown, Portland, Multnomah County, Oregon, 97201, USA",45.51181205,-122.68492999,edu,
a308077e98a611a977e1e85b5a6073f1a9bae6f0,Intelligent Screening Systems for Cervical Cancer,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
+a31b862f1addbed64a2dac64d7d416e129cad6ad,DeepGarment : 3D Garment Shape Estimation from a Single Image,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
a35dd69d63bac6f3296e0f1d148708cfa4ba80f6,Audio Visual Emotion Recognition with Temporal Alignment and Perception Attention,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+a33c5b508c64d1b01f3d4567835de6a4242b6911,High-fidelity facial and speech animation for VR HMDs,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+a33c5b508c64d1b01f3d4567835de6a4242b6911,High-fidelity facial and speech animation for VR HMDs,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
a36c8a4213251d3fd634e8893ad1b932205ad1ca,Videos from the 2013 Boston Marathon : An Event Reconstruction Dataset for Synchronization and Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
a3a2f3803bf403262b56ce88d130af15e984fff0,Building a Compact Relevant Sample Coverage for Relevance Feedback in Content-Based Image Retrieval,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+a3b70bf7e676f92ebb6dec3e2889c9131634f8b9,Use of 3D faces facilitates facial expression recognition in children,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+a3d11e98794896849ab2304a42bf83e2979e5fb5,In Defense of the Triplet Loss for Person Re-Identification,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
b56f3a7c50bfcd113d0ba84e6aa41189e262d7ae,Harvesting Motion Patterns in Still Images from the Internet,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
b5968e7bb23f5f03213178c22fd2e47af3afa04c,Multiple-Human Parsing in the Wild,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
b5968e7bb23f5f03213178c22fd2e47af3afa04c,Multiple-Human Parsing in the Wild,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
b5cd9e5d81d14868f1a86ca4f3fab079f63a366d,Tag-based video retrieval by embedding semantic content in a continuous word space,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
b5cd9e5d81d14868f1a86ca4f3fab079f63a366d,Tag-based video retrieval by embedding semantic content in a continuous word space,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+b5e3beb791cc17cdaf131d5cca6ceb796226d832,Novel Dataset for Fine-Grained Image Categorization: Stanford Dogs,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+b5184bd428b9a89255900dce50b4320741706744,Discovering Disentangled Representations with the F Statistic Loss,"University of Colorado, Boulder","University of Colorado, Boulder","Naropa University, Arapahoe Avenue, The Hill, Boulder, Boulder County, Colorado, 80309, USA",40.01407945,-105.26695944,edu,
+b56ffd4b244b2c3094cdb930ee569fb4e3bd95f0,SitNet: Discrete Similarity Transfer Network for Zero-shot Hashing,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+b56ffd4b244b2c3094cdb930ee569fb4e3bd95f0,SitNet: Discrete Similarity Transfer Network for Zero-shot Hashing,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
+b59df3832c3914c9aefc7f11017360a24bd11480,Identifying First-Person Camera Wearers in Third-Person Videos,Indiana University Bloomington,Indiana University Bloomington,"Indiana University Bloomington, East 17th Street, Bloomington, Monroe County, Indiana, 47408, USA",39.17720475,-86.51540030,edu,
+b59df3832c3914c9aefc7f11017360a24bd11480,Identifying First-Person Camera Wearers in Third-Person Videos,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+b5c90dc06b63099c3d35c86c97fa24ebf9d41fb6,Learning to Classify Psychiatric Disorders based on fMR Images: Autism vs Healthy and ADHD vs Healthy,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+b5c90dc06b63099c3d35c86c97fa24ebf9d41fb6,Learning to Classify Psychiatric Disorders based on fMR Images: Autism vs Healthy and ADHD vs Healthy,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+b5354bcad6c11983f9614546371262c454c994ed,Maximum Similarity Based Feature Matching and Adaptive Multiple Kernel Learning for Object Recognition,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+b5354bcad6c11983f9614546371262c454c994ed,Maximum Similarity Based Feature Matching and Adaptive Multiple Kernel Learning for Object Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
b5f2846a506fc417e7da43f6a7679146d99c5e96,UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
b5da4943c348a6b4c934c2ea7330afaf1d655e79,Facial Landmarks Detection by Self-Iterative Regression based Landmarks-Attention Network,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
b5da4943c348a6b4c934c2ea7330afaf1d655e79,Facial Landmarks Detection by Self-Iterative Regression based Landmarks-Attention Network,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
b5402c03a02b059b76be829330d38db8e921e4b5,Hybridized KNN and SVM for gene expression data classification,Zhengzhou University,Zhengzhou University,"科学大道, 中原区 (Zhongyuan), 郑州市 / Zhengzhou, 河南省, 450001, 中国",34.80881680,113.53526640,edu,
+b5bd67ada6de799d96f65ef0f1b6ba1cb85e3dd8,Residual Codean Autoencoder for Facial Attribute Analysis,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+b593f13f974cf444a5781bbd487e1c69e056a1f7,Query Image Query Image Retrievals Retrievals Transferred Poses Transferred Poses,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
b52c0faba5e1dc578a3c32a7f5cfb6fb87be06ad,Robust Face Recognition Technique under Varying Illumination,National Autonomous University of Mexico,Centro de Ciencias Aplicadas y Desarrollo Tecnológico,"University City, Mexico City, CDMX, Mexico",19.31888950,-99.18436760,edu,National Autonomous University of Mexico
b56530be665b0e65933adec4cc5ed05840c37fc4,Reducing correspondence ambiguity in loosely labeled training data,University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
+b5fabc72ecdebd832fb02f1ea2e85672f2ef125e,Bregman Divergences for Infinite Dimensional Covariance Matrices,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
b5f4e617ac3fc4700ec8129fcd0dcf5f71722923,Hierarchical Wavelet Networks for Facial Feature Localization,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
b5f4e617ac3fc4700ec8129fcd0dcf5f71722923,Hierarchical Wavelet Networks for Facial Feature Localization,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+b5940250c0a136b85a4706b1bb13f52be0037837,3D Face Recognition Based on Multiple Keypoint Descriptors and Sparse Representation,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+b534163cf101520e0868c46a754748fd0e4e0ef9,Multiple-Shot Person Re-identification via Riemannian Discriminative Learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+b534163cf101520e0868c46a754748fd0e4e0ef9,Multiple-Shot Person Re-identification via Riemannian Discriminative Learning,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
b51b4ef97238940aaa4f43b20a861eaf66f67253,Unsupervised Modeling of Objects and Their Hierarchical Contextual Interactions,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+b5c945e04cdf204358e7964290867b38435ef458,Sliding-Window Optimization on an Ambiguity-Clearness Graph for Multi-object Tracking,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
b5d7c5aba7b1ededdf61700ca9d8591c65e84e88,Data pruning for template-based automatic speech recognition,Katholieke Universiteit Leuven,Katholieke Universiteit Leuven,"Laboratorium voor Bos, natuur en landschap, 102, Vital Decosterstraat, Sint-Maartensdal, Leuven, Vlaams-Brabant, Vlaanderen, 3000, België / Belgique / Belgien",50.88306860,4.70195030,edu,
b5c749f98710c19b6c41062c60fb605e1ef4312a,Evaluating Two-Stream CNN for Video Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+b53259a81dcfa9913495bb47f62627c51e20f086,DYAN: A Dynamical Atoms-Based Network for Video Prediction,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+b50eb94ab9c9a6ecb76a40a0043a74fc48d5f554,Tackling the Story Ending Biases in The Story Cloze Test,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+b56e4f61bfd6da098941d2aee8a3ab1221ce834a,Augmented Reality Meets Deep Learning for Car Instance Segmentation in Urban Scenes,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+b5b620774304e6245a660b14c1207386d3abad17,SketchNet: Sketch Classification with Web Images,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+b5b620774304e6245a660b14c1207386d3abad17,SketchNet: Sketch Classification with Web Images,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
b5930275813a7e7a1510035a58dd7ba7612943bc,Face Recognition Using L-Fisherfaces,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
b5930275813a7e7a1510035a58dd7ba7612943bc,Face Recognition Using L-Fisherfaces,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
b5930275813a7e7a1510035a58dd7ba7612943bc,Face Recognition Using L-Fisherfaces,Shandong University of Science and Technology,Shandong University of Science and Technology,"山东科技大学, 579, 前湾港路, 牛王庙, 北下庄, 黄岛区 (Huangdao), 青岛市, 山东省, 266500, 中国",36.00146435,120.11624057,edu,
b59c8b44a568587bc1b61d130f0ca2f7a2ae3b88,An Enhanced Intelligent Agent with Image Description Generation,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
b59cee1f647737ec3296ccb3daa25c890359c307,Continuously Reproducing Toolchains in Pattern Recognition and Machine Learning Experiments,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
b249f10a30907a80f2a73582f696bc35ba4db9e2,Improved graph-based SFA: Information preservation complements the slowness principle,Ruhr-University Bochum,Ruhr-University Bochum,"RUB, 150, Universitätsstraße, Ruhr-Universität, Querenburg, Bochum-Süd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland",51.44415765,7.26096541,edu,
+b281f6cf99eeb8dbb9bb0c31a57827c8c0493e7f,Multi-target Tracking by Rank-1 Tensor Approximation,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+b2fde24de782d2979b946c49986cabdb12e84eba,Latent Hough Transform for Object Detection,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
+b28eb219db9370cf20063288225cc2f3e6e5f984,Fast and Accurate Head Pose Estimation via Random Projection Forests,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
b2a0e5873c1a8f9a53a199eecae4bdf505816ecb,Hybrid VAE: Improving Deep Generative Models using Partial Observations,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
b2cd92d930ed9b8d3f9dfcfff733f8384aa93de8,"HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition",University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+b2b28eeeaa2b613bf30b5bfee5ec4272ce184bf3,Measuring Collectiveness via Refined Topological Similarity,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+b2b28eeeaa2b613bf30b5bfee5ec4272ce184bf3,Measuring Collectiveness via Refined Topological Similarity,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+b2d4ed138816c671c3f698290557d26600377025,Image Caption Validation,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+b29c83b6ee10857e09ac3503916ae1b129642cae,Mo 2 Cap 2 : Real-time Mo bile 3 D Mo tion Cap ture with a Cap-mounted Fisheye Camera,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
b234cd7788a7f7fa410653ad2bafef5de7d5ad29,Unsupervised Temporal Ensemble Alignment for Rapid Annotation,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
b234cd7788a7f7fa410653ad2bafef5de7d5ad29,Unsupervised Temporal Ensemble Alignment for Rapid Annotation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
b2c60061ad32e28eb1e20aff42e062c9160786be,Diverse and Controllable Image Captioning with Part-of-Speech Guidance,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+b255474d62f082fa97f50ea1174bf339522f6c99,Facial mimicry in its social setting,University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+b239b39c08a08d9c3b1da68a7bce162b580a746e,Gaze selection in complex social scenes,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+b239b39c08a08d9c3b1da68a7bce162b580a746e,Gaze selection in complex social scenes,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+b2d9877443ec7da2490027ccc932468f05c7bf85,Robust Canonical Time Warping for the Alignment of Grossly Corrupted Sequences,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+b2d9877443ec7da2490027ccc932468f05c7bf85,Robust Canonical Time Warping for the Alignment of Grossly Corrupted Sequences,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+b288a369c6f05443cb794048065b7a86139733d3,Convolutional gated recurrent networks for video segmentation,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+b2180fc4f5cb46b5b5394487842399c501381d67,Learning a Deep Compact Image Representation for Visual Tracking,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+b29fa452d737e2b6aa16d6f82a9a8daaea655287,Spontaneous Facial Actions Map onto Emotional Experiences in a Non-social Context: Toward a Component-Based Approach,Hiroshima University,Hiroshima University,"Hiroshima University 広島大学 東広島キャンパス, 出会いの道 Deai-no-michi Str., 西条下見, 東広島市, 広島県, 中国地方, 739-0047, 日本",34.40197660,132.71231950,edu,
+b29fa452d737e2b6aa16d6f82a9a8daaea655287,Spontaneous Facial Actions Map onto Emotional Experiences in a Non-social Context: Toward a Component-Based Approach,University of Vienna,University of Vienna,"Uni Wien, 1, Universitätsring, Schottenviertel, KG Innere Stadt, Innere Stadt, Wien, 1010, Österreich",48.21313020,16.36068653,edu,
+b29fa452d737e2b6aa16d6f82a9a8daaea655287,Spontaneous Facial Actions Map onto Emotional Experiences in a Non-social Context: Toward a Component-Based Approach,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+b2e7b1a8bd7375a043ad4eb1c88dbc7d436d9634,Effective face recognition using bag of features with additive kernels,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+b2e7b1a8bd7375a043ad4eb1c88dbc7d436d9634,Effective face recognition using bag of features with additive kernels,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
b29b42f7ab8d25d244bfc1413a8d608cbdc51855,Effective face landmark localization via single deep network,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+b29f348e8675f75ff160ec65ebeeb3f3979b65d8,An objective and subjective evaluation of content-based privacy protection of face images in video surveillance systems using JPEG XR,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
+b29f348e8675f75ff160ec65ebeeb3f3979b65d8,An objective and subjective evaluation of content-based privacy protection of face images in video surveillance systems using JPEG XR,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
b2e5df82c55295912194ec73f0dca346f7c113f6,CUHK&SIAT Submission for THUMOS15 Action Recognition Challenge,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
b2e5df82c55295912194ec73f0dca346f7c113f6,CUHK&SIAT Submission for THUMOS15 Action Recognition Challenge,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
b2e6944bebab8e018f71f802607e6e9164ad3537,Mixed Error Coding for Face Recognition with Mixed Occlusions,Zhejiang University of Technology,Zhejiang University of Technology,"浙江工业大学, 潮王路, 朝晖街道, 杭州市 Hangzhou, 浙江省, 310014, 中国",30.29315340,120.16204580,edu,
+b2e308649c7a502456a8e3c95ac7fbe6f8216e51,Recurrent Regression for Face Recognition,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+b285337ba61c2bb54181dbbb4f4863efe1aa6ec2,Realtime 3D eye gaze animation using a single RGB camera,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
b239a756f22201c2780e46754d06a82f108c1d03,Robust multimodal recognition via multitask multivariate low-rank representations,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+b242124e3bf1ebfc57b5279d4d75ade924a5d1e3,Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+b242124e3bf1ebfc57b5279d4d75ade924a5d1e3,Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+b242124e3bf1ebfc57b5279d4d75ade924a5d1e3,Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+b242124e3bf1ebfc57b5279d4d75ade924a5d1e3,Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
b20cfbb2348984b4e25b6b9174f3c7b65b6aed9e,Learning with Ambiguous Label Distribution for Apparent Age Estimation,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+d9912256502b9578cea7d149142832e0998d97ff,Metric Embedded Discriminative Vocabulary Learning for High-Level Person Representation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
d949fadc9b6c5c8b067fa42265ad30945f9caa99,Rethinking Feature Discrimination and Polymerization for Large-scale Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
d93baa5ecf3e1196b34494a79df0a1933fd2b4ec,Precise Temporal Action Localization by Evolving Temporal Proposals,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
d93baa5ecf3e1196b34494a79df0a1933fd2b4ec,Precise Temporal Action Localization by Evolving Temporal Proposals,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
d93baa5ecf3e1196b34494a79df0a1933fd2b4ec,Precise Temporal Action Localization by Evolving Temporal Proposals,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
d93baa5ecf3e1196b34494a79df0a1933fd2b4ec,Precise Temporal Action Localization by Evolving Temporal Proposals,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
d961617db4e95382ba869a7603006edc4d66ac3b,Experimenting Motion Relativity for Action Recognition with a Large Number of Classes,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+d9bda208addf00a55df23821f6d4abdb85e73599,Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+d925540a8cdedb92c7f20ebfd9b8baf36fe6caa4,The utility of 3D landmarks for arbitrary pose face recognition,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+d92c9295a050b09db921b8ef986264dc5d7eba22,On the Flip Side: Identifying Counterexamples in Visual Question Answering,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+d92c9295a050b09db921b8ef986264dc5d7eba22,On the Flip Side: Identifying Counterexamples in Visual Question Answering,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+d92c9295a050b09db921b8ef986264dc5d7eba22,On the Flip Side: Identifying Counterexamples in Visual Question Answering,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+d9358de0d80f4f4d89c91b2b16fd52279b4834e4,Exploring Correlations for Multiple Facial Attributes Recognition through Graph Attention Network,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+d934eec76a2588934094098987de72bdf1214d48,One-Shot Unsupervised Cross Domain Translation,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+d95213a0ef820c93bf0a41e1ce24aea1dc9f137d,Pose-Guided Human Parsing by an AND/OR Graph Using Pose-Context Features,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+d91d1fc3f54fafaa66df12b9db2f83b477992e37,SPIN: Seamless Operating System Integration of Peer-to-Peer DMA Between SSDs and GPUs,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+d91d1fc3f54fafaa66df12b9db2f83b477992e37,SPIN: Seamless Operating System Integration of Peer-to-Peer DMA Between SSDs and GPUs,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+d91d1fc3f54fafaa66df12b9db2f83b477992e37,SPIN: Seamless Operating System Integration of Peer-to-Peer DMA Between SSDs and GPUs,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
d9c4586269a142faee309973e2ce8cde27bda718,Contextual Visual Similarity,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
d9c4586269a142faee309973e2ce8cde27bda718,Contextual Visual Similarity,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
d912b8d88d63a2f0cb5d58164e7414bfa6b41dfa,Facial identification problem: A tracking based approach,University of Milan,University of Milan,"Milan Avenue, Ray Mar Terrace, University City, St. Louis County, Missouri, 63130, USA",38.67966620,-90.32628160,edu,
+d9533bede70753bf1fba1e4cc7ad492b88ccf373,STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+d972b4da29aebf5da7c02e77a9118b0f60895985,Embedding Network for Visual Relation Detection,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+d94969ec95d4c8cd7d0d4da3e83131b6f76cd7c4,Non-local NetVLAD Encoding for Video Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+d9584adbbb214465e4f2d4dfae1b12d33de7630b,Context Embedding Networks,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+d9b69093a82ee7cb9ad499c76c9b0d30aa377454,"PReMVOS : Proposal-generation , Refinement and Merging for the YouTube-VOS Challenge on Video Object Segmentation 2018",RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+d9bbaa38d7997f334ef8d662fd2ce380d495545a,Face Recognition System Based on Spectral Graph Wavelet Theory,Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
d963e640d0bf74120f147329228c3c272764932b,Image Processing for Face Recognition Rate Enhancement,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+d95ce873ed42b7c7facaa4c1e9c72b57b4e279f6,Generalizing a Person Retrieval Model Hetero- and Homogeneously,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+d95ce873ed42b7c7facaa4c1e9c72b57b4e279f6,Generalizing a Person Retrieval Model Hetero- and Homogeneously,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+d95ce873ed42b7c7facaa4c1e9c72b57b4e279f6,Generalizing a Person Retrieval Model Hetero- and Homogeneously,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+d9fdc9c63bb4838031eac017ba9b8e9bda3cb845,Trading-off performance and complexity in identification problem,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+d99ec70dac11292c63b7726c58c24dfacddb2889,Learning visual attribute from image and text,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
d915e634aec40d7ee00cbea96d735d3e69602f1a,Two-Stream convolutional nets for action recognition in untrimmed video,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
d915e634aec40d7ee00cbea96d735d3e69602f1a,Two-Stream convolutional nets for action recognition in untrimmed video,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+d90026a9ca2489707aff2807617f3782f78097be,"Survey on audiovisual emotion recognition: databases, features, and data fusion strategies",Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
+d94395882da6da17cee0a6ea6f1058314f091f05,Inter-BMV: Interpolation with Block Motion Vectors for Fast Semantic Segmentation on Video,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
ac1d97a465b7cc56204af5f2df0d54f819eef8a6,A Look at Eye Detection for Unconstrained Environments,University of Colorado at Colorado Springs,University of Colorado at Colorado Springs,"1420 Austin Bluffs Pkwy, Colorado Springs, CO 80918, USA",38.89646790,-104.80505940,edu,
ac2e44622efbbab525d4301c83cb4d5d7f6f0e55,"A 3D Morphable Model Learnt from 10,000 Faces",University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+acc550d31b50c8d95794dc35dd1e271f979a0854,Optimized Kernel-based Projection Space of Riemannian Manifolds,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+acc550d31b50c8d95794dc35dd1e271f979a0854,Optimized Kernel-based Projection Space of Riemannian Manifolds,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+acc550d31b50c8d95794dc35dd1e271f979a0854,Optimized Kernel-based Projection Space of Riemannian Manifolds,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
ac6c3b3e92ff5fbcd8f7967696c7aae134bea209,Deep Cascaded Bi-Network for Face Hallucination,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
ac6c3b3e92ff5fbcd8f7967696c7aae134bea209,Deep Cascaded Bi-Network for Face Hallucination,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
ac6c3b3e92ff5fbcd8f7967696c7aae134bea209,Deep Cascaded Bi-Network for Face Hallucination,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
ac855f0de9086e9e170072cb37400637f0c9b735,Fast Geometrically-Perturbed Adversarial Faces,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+acdc333f7b32d987e65ce15f21db64e850ca9471,Direct Loss Minimization for Training Deep Neural Nets,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+acdc333f7b32d987e65ce15f21db64e850ca9471,Direct Loss Minimization for Training Deep Neural Nets,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+ac207f5e368e285b0dd54387e3a898c550249b20,Stacked RNNs for Encoder-Decoder Networks: Accurate Machine Understanding of Images,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
ac21c8aceea6b9495574f8f9d916e571e2fc497f,Pose-Independent Identity-based Facial Image Retrieval using Contextual Similarity,"King Abdullah University of Science and Technology, Saudi Arabia",King Abdullah University of Science and Technology 4700,"KAUST, Collaboration Avenue, ثول, منطقة مكة المكرمة, 23955, السعودية",22.31055485,39.10515486,edu,
+ac768ff426a3a04a835cdc627481afc898a138f9,Learning Joint Feature Adaptation for Zero-Shot Recognition,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
aca75c032cfb0b2eb4c0ae56f3d060d8875e43f9,Co-Regularized Ensemble for Feature Selection,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
aca75c032cfb0b2eb4c0ae56f3d060d8875e43f9,Co-Regularized Ensemble for Feature Selection,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+ac5d9753a53b0d69308596908032f85b416c0056,Selectivity of Face Distortion Aftereffects for Differences in Expression or Gender,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+ac5d9753a53b0d69308596908032f85b416c0056,Selectivity of Face Distortion Aftereffects for Differences in Expression or Gender,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+ac5d9753a53b0d69308596908032f85b416c0056,Selectivity of Face Distortion Aftereffects for Differences in Expression or Gender,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+ac9516a589901f1421e8ce905dd8bc5b689317ca,A Practical Framework for Executing Complex Queries over Encrypted Multimedia Data,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+ac9bdf668852dea5fa8ec4262f10562eda9bedd2,Deep Structured Learning for Facial Expression Intensity Estimation,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+ac9bdf668852dea5fa8ec4262f10562eda9bedd2,Deep Structured Learning for Facial Expression Intensity Estimation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+ac9227ff4262405b8eec8ebe4802b763bd6f55e1,Surface Matching and Registration by Landmark Curve-Driven Canonical Quasiconformal Mapping,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
+ac9227ff4262405b8eec8ebe4802b763bd6f55e1,Surface Matching and Registration by Landmark Curve-Driven Canonical Quasiconformal Mapping,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+acfb90f474209f56455c4d1ae60d524d8c4c9df8,Pixel-wise Attentional Gating for Parsimonious Pixel Labeling,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+aca57cd3f1f4edea9918814aabd0460c682cd56e,Discriminant Projective Non-Negative Matrix Factorization,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+aca57cd3f1f4edea9918814aabd0460c682cd56e,Discriminant Projective Non-Negative Matrix Factorization,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+ac68dacd66ebe1c7eab56aaee9a8bef478be9a23,Sparkle: adaptive sample based scheduling for cluster computing,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
ac51d9ddbd462d023ec60818bac6cdae83b66992,An Efficient Robust Eye Localization by Learning the Convolution Distribution Using Eye Template,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
ac51d9ddbd462d023ec60818bac6cdae83b66992,An Efficient Robust Eye Localization by Learning the Convolution Distribution Using Eye Template,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+ac32cdb3e0a996c75d5df2973c1a2444a81c0a5e,Defense Against Adversarial Attacks with Saak Transform,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
+ac32cdb3e0a996c75d5df2973c1a2444a81c0a5e,Defense Against Adversarial Attacks with Saak Transform,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
acc548285f362e6b08c2b876b628efceceeb813e,Objectifying Facial Expressivity Assessment of Parkinson's Patients: Preliminary Study,Vrije Universiteit Brussel,Vrije Universiteit Brussel,"Vrije Universiteit Brussel, 170, Quai de l'Industrie - Nijverheidskaai, Anderlecht, Brussel-Hoofdstad - Bruxelles-Capitale, Région de Bruxelles-Capitale - Brussels Hoofdstedelijk Gewest, 1070, België / Belgique / Belgien",50.84110070,4.32377555,edu,
acc548285f362e6b08c2b876b628efceceeb813e,Objectifying Facial Expressivity Assessment of Parkinson's Patients: Preliminary Study,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
acc548285f362e6b08c2b876b628efceceeb813e,Objectifying Facial Expressivity Assessment of Parkinson's Patients: Preliminary Study,Vrije Universiteit Brussel,Vrije Universiteit Brussel,"Vrije Universiteit Brussel, 170, Quai de l'Industrie - Nijverheidskaai, Anderlecht, Brussel-Hoofdstad - Bruxelles-Capitale, Région de Bruxelles-Capitale - Brussels Hoofdstedelijk Gewest, 1070, België / Belgique / Belgien",50.84110070,4.32377555,edu,
acc548285f362e6b08c2b876b628efceceeb813e,Objectifying Facial Expressivity Assessment of Parkinson's Patients: Preliminary Study,Vrije Universiteit Brussel,Vrije Universiteit Brussel,"Vrije Universiteit Brussel, 170, Quai de l'Industrie - Nijverheidskaai, Anderlecht, Brussel-Hoofdstad - Bruxelles-Capitale, Région de Bruxelles-Capitale - Brussels Hoofdstedelijk Gewest, 1070, België / Belgique / Belgien",50.84110070,4.32377555,edu,
+ac8269a3033ede3c1ce4381b1fef61375a54cfb9,Coordinating the Design and Management of Heterogeneous Datacenter Resources,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
acee2201f8a15990551804dd382b86973eb7c0a8,To boost or not to boost? On the limits of boosted trees for object detection,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
ac9a331327cceda4e23f9873f387c9fd161fad76,Deep Convolutional Neural Network for Age Estimation based on VGG-Face Model,University of Bridgeport,University of Bridgeport,"University of Bridgeport, Park Avenue, Bridgeport Downtown South Historic District, Bridgeport, Fairfield County, Connecticut, 06825, USA",41.16648580,-73.19205640,edu,
ac9a331327cceda4e23f9873f387c9fd161fad76,Deep Convolutional Neural Network for Age Estimation based on VGG-Face Model,University of Bridgeport,University of Bridgeport,"University of Bridgeport, Park Avenue, Bridgeport Downtown South Historic District, Bridgeport, Fairfield County, Connecticut, 06825, USA",41.16648580,-73.19205640,edu,
+ac56b4d6f9775211dfc966e9151862fd508d3142,Three-dimensional information in face recognition: an eye-tracking study.,University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+ac56b4d6f9775211dfc966e9151862fd508d3142,Three-dimensional information in face recognition: an eye-tracking study.,University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+acaa781f353c769ae5f6101aab140f51b2d33cd2,Recent advances in correlation filter theory and applications,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+acaa781f353c769ae5f6101aab140f51b2d33cd2,Recent advances in correlation filter theory and applications,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+acc9821b61ea804bd1e0b0e23a45f08fbf760a37,Smile Detection in the Wild Based on Transfer Learning,University of Delaware,University of Delaware,"University of Delaware, South College Avenue, Newark, New Castle County, Delaware, 19713, USA",39.68103280,-75.75401840,edu,
+ac752e998ea646411438fd517c36e1e8c6507d15,Guided saccades modulate object and face-specific activity in the fusiform gyrus.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+acfa01182d18d8f3fbbd7df6be0998269116ba6d,Character Image Patterns as Big Data,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+acfe5b5c99be70fa3120d410e7be55b9fe299f40,Factorizable Net: An Efficient Subgraph-Based Framework for Scene Graph Generation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+acfe5b5c99be70fa3120d410e7be55b9fe299f40,Factorizable Net: An Efficient Subgraph-Based Framework for Scene Graph Generation,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+acfe5b5c99be70fa3120d410e7be55b9fe299f40,Factorizable Net: An Efficient Subgraph-Based Framework for Scene Graph Generation,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
ac86ccc16d555484a91741e4cb578b75599147b2,Morphable Face Models - An Open Framework,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+ac5b3e24a7dd2970c323ca7679625a7d29602480,Warsaw set of emotional facial expression pictures: a validation study of facial display photographs,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+ac5b3e24a7dd2970c323ca7679625a7d29602480,Warsaw set of emotional facial expression pictures: a validation study of facial display photographs,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
ac75c662568cbb7308400cc002469a14ff25edfd,Regularization studies on LDA for face recognition,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+ac0e595afa57db8c9310d72b2a2eb0758dc1e48f,Discriminative Learning of Latent Features for Zero-Shot Recognition,University of Dundee,University of Dundee,"University of Dundee, Park Wynd, Law, Dundee, Dundee City, Scotland, DD1 4HN, UK",56.45796755,-2.98214831,edu,
ac9dfbeb58d591b5aea13d13a83b1e23e7ef1fea,From Gabor Magnitude to Gabor Phase Features: Tackling the Problem of Face Recognition under Severe Illumination Changes,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+ac5a1b5a90dfeb4d22c37d806385cb9046e5edcb,Modeling Camera Effects to Improve Visual Learning from Synthetic Data,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+ac7031769c08423774ae4346f7492f6814176268,Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
+ac7031769c08423774ae4346f7492f6814176268,Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
+ac392dba43796a25c2eee5f08671537634a77029,CyCADA: Cycle-Consistent Adversarial Domain Adaptation,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+ac61f5e442e653e2503aea85425f0b9dba9f768a,MagnifyMe: Aiding Cross Resolution Face Recognition via Identity Aware Synthesis,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+ac559888f996923c06b1cf90db6b57b12e582289,Benchmarking neuromorphic vision: lessons learnt from computer vision,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+ac559888f996923c06b1cf90db6b57b12e582289,Benchmarking neuromorphic vision: lessons learnt from computer vision,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+ac559888f996923c06b1cf90db6b57b12e582289,Benchmarking neuromorphic vision: lessons learnt from computer vision,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+ac559888f996923c06b1cf90db6b57b12e582289,Benchmarking neuromorphic vision: lessons learnt from computer vision,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+ac2881bdf7b57dc1672a17b221d68a438d79fce8,Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+acfecef9e56ff36455aed13f8e6be1a79b42f20f,Hit or Run: Exploring Aggressive and Avoidant Reactions to Interpersonal Provocation Using a Novel Fight-or-Escape Paradigm (FOE),University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+ad01687649d95cd5b56d7399a9603c4b8e2217d7,Investigating Open-World Person Re-identi cation Using a Drone,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+ada53a115e1551f3fbad3dc5930c1187473a78a4,Efficient Object Category Recognition Using Classemes,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+ad1f223e83338b0b08779b3736d5a3b7ccfec592,Deep Kinematic Pose Regression,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+ad1f223e83338b0b08779b3736d5a3b7ccfec592,Deep Kinematic Pose Regression,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+ad1f223e83338b0b08779b3736d5a3b7ccfec592,Deep Kinematic Pose Regression,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
ad8540379884ec03327076b562b63bc47e64a2c7,Bee royalty offspring algorithm for improvement of facial expressions classification model,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+adaed4e92c93eb005198e41f87cf079e46050b5a,Discriminative Invariant Kernel Features: A Bells-and-Whistles-Free Approach to Unsupervised Face Recognition and Pose Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+adaed4e92c93eb005198e41f87cf079e46050b5a,Discriminative Invariant Kernel Features: A Bells-and-Whistles-Free Approach to Unsupervised Face Recognition and Pose Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+adaed4e92c93eb005198e41f87cf079e46050b5a,Discriminative Invariant Kernel Features: A Bells-and-Whistles-Free Approach to Unsupervised Face Recognition and Pose Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
adce9902dca7f4e8a9b9cf6686ec6a7c0f2a0ba6,"Two Birds, One Stone: Jointly Learning Binary Code for Large-Scale Face Image Retrieval and Attributes Prediction",Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
adce9902dca7f4e8a9b9cf6686ec6a7c0f2a0ba6,"Two Birds, One Stone: Jointly Learning Binary Code for Large-Scale Face Image Retrieval and Attributes Prediction",University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+adc0b5d9f010f8b7d9900fcb1703c3882e340d65,Nasal Oxytocin Treatment Biases Dogs’ Visual Attention and Emotional Response toward Positive Human Facial Expressions,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+ad6b23435649d3d88a6b33154b9e6e3e5648a33d,Visual Curiosity: Learning to Ask Questions to Learn Visual Recognition,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+ad9ecacca5c28b098096ad0cbd81fe84405924e3,1 Face Recognition by Sparse Representation,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+ad7dfaadf9d99eadbb001ff0e0974f53704012b1,Single Image Action Recognition Using Semantic Body Part Actions,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+adf423f2a76301e34aed59d4e6d6f5378dcdadb4,A Soft Computing Based Approach for Multi-Accent Classification in IVR Systems,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
add50a7d882eb38e35fe70d11cb40b1f0059c96f,High-fidelity Pose and Expression Normalization for face recognition in the wild,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+ad5d2146a629b786712eb21d4dbfa31394ca07b4,Sputnik Tracker: Having a Companion Improves Robustness of the Tracker,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
ad784332cc37720f03df1c576e442c9c828a587a,Face recognition based on face-specific subspace,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
ad784332cc37720f03df1c576e442c9c828a587a,Face recognition based on face-specific subspace,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+ad836360812f87e45795f8345de3bdc6b13add81,Kernelized structural SVM learning for supervised object segmentation,Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
ada42b99f882ba69d70fff68c9ccbaff642d5189,Semantic Image Segmentation and Web-Supervised Visual Learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+ad467baa4f59d18ed998757bcba3df3c2a753df8,Realtime Multilevel Crowd Tracking Using Reciprocal Velocity Obstacles,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+ada1a5f2d2a3fb471de4a561ed13c52d0904b578,InverseFaceNet : Deep Monocular Inverse Face Rendering — Supplemental Material —,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+ada1a5f2d2a3fb471de4a561ed13c52d0904b578,InverseFaceNet : Deep Monocular Inverse Face Rendering — Supplemental Material —,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
ad0d4d5c61b55a3ab29764237cd97be0ebb0ddff,Weakly Supervised Action Localization by Sparse Temporal Pooling Network,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+addbddc42462975a02f4933d36f430b874b3d52b,"Social attention and real-world scenes: the roles of action, competition and social content.",University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+addbddc42462975a02f4933d36f430b874b3d52b,"Social attention and real-world scenes: the roles of action, competition and social content.",University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+addbddc42462975a02f4933d36f430b874b3d52b,"Social attention and real-world scenes: the roles of action, competition and social content.",University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+addbddc42462975a02f4933d36f430b874b3d52b,"Social attention and real-world scenes: the roles of action, competition and social content.",University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+ad5950257e053b08657ea298f7b89ba358b8bfcf,Textually Enriched Neural Module Networks for Visual Question Answering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+ad46f1de2001474cce1047d88703f61580c8a5de,Face Recognition,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+ada13fd37da7a28e74aaed4a413533fa4f4b3b37,Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
ad9cb522cc257e3c5d7f896fe6a526f6583ce46f,Real-Time Recognition of Facial Expressions for Affective Computing Applications,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+ad62c6e17bc39b4dec20d32f6ac667ae42d2c118,A Synchronization Ground Truth for the Jiku Mobile Video Dataset,Institute of Information Technology,Institute of Information Technology,"Institute of Information Technology, Sir Sayed Road, ফকিরাপুল, সিদ্দিক বাজার, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.72898990,90.39826820,edu,
ad08c97a511091e0f59fc6a383615c0cc704f44a,Towards the improvement of self-service systems via emotional virtual agents,University of Abertay,University of Abertay,"Abertay University, Bell Street, City Centre, Dundee, Dundee City, Scotland, DD1 1HG, UK",56.46323375,-2.97447512,edu,
ad08c97a511091e0f59fc6a383615c0cc704f44a,Towards the improvement of self-service systems via emotional virtual agents,University of Abertay,University of Abertay,"Abertay University, Bell Street, City Centre, Dundee, Dundee City, Scotland, DD1 1HG, UK",56.46323375,-2.97447512,edu,
ad08c97a511091e0f59fc6a383615c0cc704f44a,Towards the improvement of self-service systems via emotional virtual agents,University of Abertay,University of Abertay,"Abertay University, Bell Street, City Centre, Dundee, Dundee City, Scotland, DD1 1HG, UK",56.46323375,-2.97447512,edu,
ad08c97a511091e0f59fc6a383615c0cc704f44a,Towards the improvement of self-service systems via emotional virtual agents,University of Abertay,University of Abertay,"Abertay University, Bell Street, City Centre, Dundee, Dundee City, Scotland, DD1 1HG, UK",56.46323375,-2.97447512,edu,
ad2339c48ad4ffdd6100310dcbb1fb78e72fac98,Video Fill In the Blank Using LR/RL LSTMs with Spatial-Temporal Attentions,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+ad7e2dd9ce31c2093d5b611372c44654d8d594de,Improving Consistency-Based Semi-Supervised Learning with Weight Averaging,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+ad2cb5c255e555d9767d526721a4c7053fa2ac58,Longitudinal Study of Child Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+ad2cb5c255e555d9767d526721a4c7053fa2ac58,Longitudinal Study of Child Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
ad247138e751cefa3bb891c2fe69805da9c293d7,A Novel Hybrid Method for Face Recognition Based on 2d Wavelet and Singular Value Decomposition,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+adc2a323af5f8be790b7fe5ded8b5b276f0a1b31,Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+adc2a323af5f8be790b7fe5ded8b5b276f0a1b31,Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+ad8f0b5dd8d89c0b0805a77dc27a9ce22caf6c59,"The computational magic of the ventral stream : sketch of a theory ( and why some deep architectures work ) . December 30 , 2012 DRAFT",McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
+adef82b510dd72999bb04e13660c9a77b5abeb4c,Face recognition by fractal transformations,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+ad84f49b2cd1b85a6d7df2304144a093f5b610a8,Learning from Noisy Labels with Deep Neural Networks,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+bbf56398dba5593a2aed1c3857fa011442b3aed6,Mind Your Language: Learning Visually Grounded Dialog in a Multi-Agent Setting,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+bbc4bdab563b8b4cea55dfd6a7ea32680e082933,Normalized Autobinomial Markov Channels For Pedestrian Detection,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
+bb31312a7f07486676cae4f7a2ad7da43b0700e2,The impact of privacy protection filters on gender recognition,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+bb31312a7f07486676cae4f7a2ad7da43b0700e2,The impact of privacy protection filters on gender recognition,Orange,Orange Labs,"78 Rue Olivier de Serres, 75015 Paris, France",48.83321220,2.29421550,company,"78 Rue Olivier de Serres, Paris, 75015"
bbc4b376ebd296fb9848b857527a72c82828fc52,Attributes for Improved Attributes,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
bbc4b376ebd296fb9848b857527a72c82828fc52,Attributes for Improved Attributes,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+bb4362bd6f0bc5bb467fc8f169723243caa97d1d,"Joint learning of visual attributes, object classes and visual saliency","University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+bb4362bd6f0bc5bb467fc8f169723243caa97d1d,"Joint learning of visual attributes, object classes and visual saliency","University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+bbd9b5e4d4761d923d21a060513e826bf5bfc620,Harvesting Multiple Views for Marker-Less 3D Human Pose Annotations,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+bbd9b5e4d4761d923d21a060513e826bf5bfc620,Harvesting Multiple Views for Marker-Less 3D Human Pose Annotations,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
+bbb71cbca731295758563acdc67273b99618e1c0,SwapNet: Image Based Garment Transfer,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+bbb71cbca731295758563acdc67273b99618e1c0,SwapNet: Image Based Garment Transfer,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
bb06ef67a49849c169781657be0bb717587990e0,Impact of temporal subsampling on accuracy and performance in practical video classification,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
bb06ef67a49849c169781657be0bb717587990e0,Impact of temporal subsampling on accuracy and performance in practical video classification,University of Bologna,Università di Bologna,"Via Zamboni, 33, 40126 Bologna BO, Italy",44.49623180,11.35415700,edu,
bbf28f39e5038813afd74cf1bc78d55fcbe630f1,Style Aggregated Network for Facial Landmark Detection,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
bbe949c06dc4872c7976950b655788555fe513b8,Automatic Frequency Band Selection for Illumination Robust Face Recognition,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+bbcf6f54d3e991f85a949544abf20b781d5ba2ed,Weighted principal component extraction with genetic algorithms,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
bbcb4920b312da201bf4d2359383fb4ee3b17ed9,Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
bb6bf94bffc37ef2970410e74a6b6dc44a7f4feb,Situation Recognition with Graph Neural Networks Supplementary Material,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+bb1bc9df5e9cec3e8a03a027b8016b8fc25be73a,Improving Bi-directional Generation between Different Modalities with Variational Autoencoders,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+bba153ebdf11e6fb8716e35749c671ac96c14176,Image Crowd Counting Using Convolutional Neural Network and Markov Random Field,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+bba153ebdf11e6fb8716e35749c671ac96c14176,Image Crowd Counting Using Convolutional Neural Network and Markov Random Field,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+bb21a57edd10c042bd137b713fcbf743021ab232,The More You Know: Using Knowledge Graphs for Image Classification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+bb491d3bd43d8fb018cb7f14ca4a17738225bafb,De-genderization by body contours reshaping,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+bb6f922cc6f94beacc93aead7af53e9bcb9fe3b4,A Multi-scale CNN for Affordance Segmentation in RGB Images,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+bb65479d3f38b73826596e5da9dbf5ee4199d42c,Scale Aggregation Network for Accurate and Efficient Crowd Counting,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+bb030eaf7c25953369ee111dc1555f4f85409bb4,Scenarios: A New Representation for Complex Scene Understanding,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+bbfe095e11ecfdb9d9e8577e119bbd67170d6925,DeepSIC: Deep Semantic Image Compression,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+bbfe095e11ecfdb9d9e8577e119bbd67170d6925,DeepSIC: Deep Semantic Image Compression,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+bbfe095e11ecfdb9d9e8577e119bbd67170d6925,DeepSIC: Deep Semantic Image Compression,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+bb0071e21e1f00568ea80dd22c5bcef06bdebe2c,Surface Reconstruction of Rotating Objects from Monocular Video,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
bbc5f4052674278c96abe7ff9dc2d75071b6e3f3,Nonlinear Hierarchical Part-Based Regression for Unconstrained Face Alignment,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
bbfe0527e277e0213aafe068113d719b2e62b09c,Dog Breed Classification Using Part Localization,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
bbfe0527e277e0213aafe068113d719b2e62b09c,Dog Breed Classification Using Part Localization,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+bbb274a7f79c94eb2862ca99dcb23de43b9ff8ae,A Geometric Morphometric Approach to the Analysis of Lip Shape during Speech: Development of a Clinical Outcome Measure,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+bbb274a7f79c94eb2862ca99dcb23de43b9ff8ae,A Geometric Morphometric Approach to the Analysis of Lip Shape during Speech: Development of a Clinical Outcome Measure,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+d74e14de664be4b784813d93e260abe379e2602d,Supplementary Material for : Video Prediction with Appearance and Motion Conditions,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
d73d2c9a6cef79052f9236e825058d5d9cdc1321,Cutting the visual world into bigger slices for improved video concept detection. (Amélioration de la détection des concepts dans les vidéos en coupant de plus grandes tranches du monde visuel),EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
d794ffece3533567d838f1bd7f442afee13148fd,Hand Detection and Tracking in Videos for Fine-Grained Action Recognition,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
d7593148e4319df7a288180d920f2822eeecea0b,A Differential Approach for Gaze Estimation with Calibration,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
d7cbedbee06293e78661335c7dd9059c70143a28,MobileFaceNets: Efficient CNNs for Accurate Real-time Face Verification on Mobile Devices,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
d7d9c1fa77f3a3b3c2eedbeb02e8e7e49c955a2f,Automating Image Analysis by Annotating Landmarks with Deep Neural Networks,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
d7d9c1fa77f3a3b3c2eedbeb02e8e7e49c955a2f,Automating Image Analysis by Annotating Landmarks with Deep Neural Networks,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+d7d6f1b1e832bc7f52ed34131e3f200badb601e3,EC : A Uniform Platform for Security Analysis of Deep Learning Model,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+d7d6f1b1e832bc7f52ed34131e3f200badb601e3,EC : A Uniform Platform for Security Analysis of Deep Learning Model,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+d7c094f5be41a13a579d8922ec4d50c70be1c276,Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods,Marquette University,Marquette University,"Marquette University, West Wisconsin Avenue, University Hill, Milwaukee, Milwaukee County, Wisconsin, 53226, USA",43.03889625,-87.93155450,edu,
+d7f5f0066cecaf8760433e7dfb0eaaaf61aa6ef6,Relaxed collaborative representation for pattern classification,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
d78734c54f29e4474b4d47334278cfde6efe963a,Exploring Disentangled Feature Representation Beyond Face Identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
d78734c54f29e4474b4d47334278cfde6efe963a,Exploring Disentangled Feature Representation Beyond Face Identification,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
d785fcf71cb22f9c33473cba35f075c1f0f06ffc,Learning active facial patches for expression analysis,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
d785fcf71cb22f9c33473cba35f075c1f0f06ffc,Learning active facial patches for expression analysis,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
d785fcf71cb22f9c33473cba35f075c1f0f06ffc,Learning active facial patches for expression analysis,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
d79365336115661b0e8dbbcd4b2aa1f504b91af6,Variational methods for conditional multimodal deep learning,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+d75a9e646500d543094f7c0ab80c9f5c30808304,Features for Multi-Target Multi-Camera Tracking and Re-Identification,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+d7221695df4de3f34d5e4a877b71c14bc88760d2,Proposal Incorporating Structural Bias into Neural Networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+d7f11ebb73bfe74a57c33f7e75f7981ad9385580,Real-Time Resource Allocation for Tracking Systems,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+d7f11ebb73bfe74a57c33f7e75f7981ad9385580,Real-Time Resource Allocation for Tracking Systems,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+d7f11ebb73bfe74a57c33f7e75f7981ad9385580,Real-Time Resource Allocation for Tracking Systems,University of Liverpool,University of Liverpool,"Victoria Building, Brownlow Hill, Knowledge Quarter, Liverpool, North West England, England, L3, UK",53.40617900,-2.96670819,edu,
+d7f11ebb73bfe74a57c33f7e75f7981ad9385580,Real-Time Resource Allocation for Tracking Systems,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+d787f691af05a56eb0e91437fc6b1dfe5fbccbb9,The Effect of Affective Context on Visuocortical Processing of Neutral Faces in Social Anxiety,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+d7ebd31d4616c297292a36785727f1bc5b470290,Sensitivity to eye gaze in autism: is it normal? Is it automatic? Is it social?,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+d73a0c3db0b347bc6f3796eb89d1342bf9ccee9b,Fast Multi-aspect 2D Human Detection,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+d7d01406bf8bec7e48b70e886d93e935b8885815,The perception of emotion in artificial agents,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+d7d01406bf8bec7e48b70e886d93e935b8885815,The perception of emotion in artificial agents,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+d7cbd030b282a7b0fe397df04a6a3c860608982f,Gaussian Descriptor Based on Local Features for Person Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
d78fbd11f12cbc194e8ede761d292dc2c02d38a2,Enhancing Gray Scale Images for Face Detection under Unstable Lighting Condition,University of Dschang,University of Dschang,"Université de Dschang, Départementale 65, Fokoué, Menoua, OU, Cameroun",5.44094480,10.07120561,edu,
d78fbd11f12cbc194e8ede761d292dc2c02d38a2,Enhancing Gray Scale Images for Face Detection under Unstable Lighting Condition,University of Dschang,University of Dschang,"Université de Dschang, Départementale 65, Fokoué, Menoua, OU, Cameroun",5.44094480,10.07120561,edu,
d72973a72b5d891a4c2d873daeb1bc274b48cddf,A New Supervised Dimensionality Reduction Algorithm Using Linear Discriminant Analysis and Locality Preserving Projection,Guangdong Medical College,Guangdong Medical College,"医学院, 真如路, 凤凰新村, 天河区, 广州市, 广东省, 510635, 中国",23.12944890,113.34376110,edu,
d72973a72b5d891a4c2d873daeb1bc274b48cddf,A New Supervised Dimensionality Reduction Algorithm Using Linear Discriminant Analysis and Locality Preserving Projection,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+d7c9bd2587204071b87feaad01d631e7ea591c6b,Cmu - Ucr - Bosch @ Trecvid 2017 : Video to Text Retrieval,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
d700aedcb22a4be374c40d8bee50aef9f85d98ef,Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+d7431a266a151fb92abb7ff93fd458f21c6c3c41,Probabilistic sequence models for image sequence processing and recognition,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+d01067340615131f9109f71590ff66f418ce8f97,Deep View-Sensitive Pedestrian Attribute Inference in an end-to-end Model,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
d0e895a272d684a91c1b1b1af29747f92919d823,Classification of Mouth Action Units using Local Binary Patterns,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
d0e895a272d684a91c1b1b1af29747f92919d823,Classification of Mouth Action Units using Local Binary Patterns,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
d082f35534932dfa1b034499fc603f299645862d,"TAMING WILD FACES: WEB-SCALE, OPEN-UNIVERSE FACE IDENTIFICATION IN STILL AND VIDEO IMAGERY by ENRIQUE",University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
d0ac9913a3b1784f94446db2f1fb4cf3afda151f,Exploiting Multi-modal Curriculum in Noisy Web Data for Large-scale Concept Learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
d0471d5907d6557cf081edf4c7c2296c3c221a38,A Constrained Deep Neural Network for Ordinal Regression,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+d0f81c31e11af1783644704321903a3d2bd83fd6,3D Façade Labeling over Complex Scenarios: A Case Study Using Convolutional Neural Network and Structure-From-Motion,University of Stuttgart,University of Stuttgart,"Pädagogische Hochschule Ludwigsburg, 46, Reuteallee, Ludwigsburg-Nord, Ludwigsburg, Landkreis Ludwigsburg, Regierungsbezirk Stuttgart, Baden-Württemberg, 71634, Deutschland",48.90953380,9.18318920,edu,
+d0f81c31e11af1783644704321903a3d2bd83fd6,3D Façade Labeling over Complex Scenarios: A Case Study Using Convolutional Neural Network and Structure-From-Motion,University of Exeter,University of Exeter,"University of Exeter, Stocker Road, Exwick, Exeter, Devon, South West England, England, EX4 4QN, UK",50.73693020,-3.53647672,edu,
+d0a188debff9baca296787dfb207f151cb78300a,Physical Representation-based Predicate Optimization for a Visual Analytics Database,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+d0a188debff9baca296787dfb207f151cb78300a,Physical Representation-based Predicate Optimization for a Visual Analytics Database,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+d0a188debff9baca296787dfb207f151cb78300a,Physical Representation-based Predicate Optimization for a Visual Analytics Database,Toyota Research Institute,Toyota Research Institute,"Toyota Research Institute, 4440, West El Camino Real, Los Altos, Santa Clara County, California, 94022, USA",37.40253645,-122.11655107,edu,
+d0a188debff9baca296787dfb207f151cb78300a,Physical Representation-based Predicate Optimization for a Visual Analytics Database,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+d09d663055b3b6d588bf4de2f386bb144d09aea8,Deep Adaptive Temporal Pooling for Activity Recognition,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
+d09d663055b3b6d588bf4de2f386bb144d09aea8,Deep Adaptive Temporal Pooling for Activity Recognition,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
+d095bafdecbae3a234d92ee96005b45cb5b1f55f,Finger Vein Recognition based on Personalized Discriminative Bit Map,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+d0e684f9614ab97a8f4ec47775124242ce493f26,Group Tracking: Exploring Mutual Relations for Multiple Object Tracking,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+d0d58e1885db56bdaa3890a1cd32c6d6a42f5f49,Person Identification Using Face and Iris Multimodal Biometric System,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
d06c8e3c266fbae4026d122ec9bd6c911fcdf51d,Role for 2D image generated 3D face models in the rehabilitation of facial palsy,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
d074b33afd95074d90360095b6ecd8bc4e5bb6a2,Human-Robot Collaboration: a Survey,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+d0137881f6c791997337b9cc7f1efbd61977270d,"University of Dundee An automated pattern recognition system for classifying indirect immunofluorescence images for HEp-2 cells and specimens Manivannan,",University of Dundee,University of Dundee,"University of Dundee, Park Wynd, Law, Dundee, Dundee City, Scotland, DD1 4HN, UK",56.45796755,-2.98214831,edu,
d04d5692461d208dd5f079b98082eda887b62323,Subspace learning with frequency regularizer: Its application to face recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
d05513c754966801f26e446db174b7f2595805ba,Everything is in the Face? Represent Faces with Object Bank,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
d05513c754966801f26e446db174b7f2595805ba,Everything is in the Face? Represent Faces with Object Bank,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
d05513c754966801f26e446db174b7f2595805ba,Everything is in the Face? Represent Faces with Object Bank,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+d0d1a18469bd41b9464b393b56d209d53869bd77,Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+d060a7a715f2e233dd09777bf651be10fa19f3d3,Versatile Auxiliary Classifier + Generative Adversarial Network (VAC+GAN); Training Conditional Generators,National University of Ireland Galway,National University of Ireland Galway,"National University of Ireland, Galway, Earl's Island, Townparks, Nun's Island, Galway Municipal District, Cathair na Gaillimhe, County Galway, Connacht, H91 F5TE, Ireland",53.27639715,-9.05829961,edu,
+d060a7a715f2e233dd09777bf651be10fa19f3d3,Versatile Auxiliary Classifier + Generative Adversarial Network (VAC+GAN); Training Conditional Generators,National University of Ireland Galway,National University of Ireland Galway,"National University of Ireland, Galway, Earl's Island, Townparks, Nun's Island, Galway Municipal District, Cathair na Gaillimhe, County Galway, Connacht, H91 F5TE, Ireland",53.27639715,-9.05829961,edu,
+d060a7a715f2e233dd09777bf651be10fa19f3d3,Versatile Auxiliary Classifier + Generative Adversarial Network (VAC+GAN); Training Conditional Generators,National University of Ireland Galway,National University of Ireland Galway,"National University of Ireland, Galway, Earl's Island, Townparks, Nun's Island, Galway Municipal District, Cathair na Gaillimhe, County Galway, Connacht, H91 F5TE, Ireland",53.27639715,-9.05829961,edu,
d0509afe9c2c26fe021889f8efae1d85b519452a,Visual Psychophysics for Making Face Recognition Algorithms More Explainable,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
d0509afe9c2c26fe021889f8efae1d85b519452a,Visual Psychophysics for Making Face Recognition Algorithms More Explainable,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+d02bf4082850a667bf0b7b6205df1cf9c1899233,Quantifying the visual concreteness of words and topics in multimodal datasets,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+d02bf4082850a667bf0b7b6205df1cf9c1899233,Quantifying the visual concreteness of words and topics in multimodal datasets,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+d02bf4082850a667bf0b7b6205df1cf9c1899233,Quantifying the visual concreteness of words and topics in multimodal datasets,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
d02e27e724f9b9592901ac1f45830341d37140fe,DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks (with Supplementary Materials),Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
d02e27e724f9b9592901ac1f45830341d37140fe,DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks (with Supplementary Materials),Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
-d02b32b012ffba2baeb80dca78e7857aaeececb0,Human Pose Estimation: Extension and Application,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+d02b32b012ffba2baeb80dca78e7857aaeececb0,Human Pose Estimation : Extension and Application,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+d055f36e7975fa5b7785575dd64b5f95b9088465,PixelNet: Towards a General Pixel-level Architecture,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+d0933550b75237c285c8bb2393185475014dbc2d,An Intelligent Automated Door Control System Based on a Smart Camera,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
+d0fe63de22729bcecf12a84554cdfbccdb44c391,SpatialVOC2K: A Multilingual Dataset of Images with Annotations and Features for Spatial Relations between Objects,University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
d0d7671c816ed7f37b16be86fa792a1b29ddd79b,Exploring Semantic Inter-Class Relationships (SIR) for Zero-Shot Action Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
d0d7671c816ed7f37b16be86fa792a1b29ddd79b,Exploring Semantic Inter-Class Relationships (SIR) for Zero-Shot Action Recognition,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
d0d7671c816ed7f37b16be86fa792a1b29ddd79b,Exploring Semantic Inter-Class Relationships (SIR) for Zero-Shot Action Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
@@ -966,6 +2614,7 @@ d0d7671c816ed7f37b16be86fa792a1b29ddd79b,Exploring Semantic Inter-Class Relation d01303062b21cd9ff46d5e3ff78897b8499480de,Multi-task Learning by Maximizing Statistical Dependence,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
d01303062b21cd9ff46d5e3ff78897b8499480de,Multi-task Learning by Maximizing Statistical Dependence,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
d01303062b21cd9ff46d5e3ff78897b8499480de,Multi-task Learning by Maximizing Statistical Dependence,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+d0dcef424ab6b32d00bdc66e8d4a61ebe911fff8,Working Memory Capacity and Fluid Intelligence,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
d0f54b72e3a3fe7c0e65d7d5a3b30affb275f4c5,Towards Universal Representation for Unseen Action Recognition,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
d0f54b72e3a3fe7c0e65d7d5a3b30affb275f4c5,Towards Universal Representation for Unseen Action Recognition,Newcastle University,Newcastle University,"Newcastle University, Claremont Walk, Haymarket, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE1 7RU, UK",54.98023235,-1.61452627,edu,
be86d88ecb4192eaf512f29c461e684eb6c35257,Automatic Attribute Discovery and Characterization from Noisy Web Data,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
@@ -981,56 +2630,177 @@ be4a20113bc204019ea79c6557a0bece23da1121,DeepCache: Principled Cache for Mobile be4a20113bc204019ea79c6557a0bece23da1121,DeepCache: Principled Cache for Mobile Deep Vision,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
be4a20113bc204019ea79c6557a0bece23da1121,DeepCache: Principled Cache for Mobile Deep Vision,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
be4a20113bc204019ea79c6557a0bece23da1121,DeepCache: Principled Cache for Mobile Deep Vision,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+bec2c65a8419b9ecaf04e8c854b5ad391894a6f1,Construction of a bird image dataset for ecological investigations,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+be22647956f1bc8cf6f936ae3c85f5637492b6b8,Ambiguity Helps: Classification with Disagreements in Crowdsourced Annotations,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
becd5fd62f6301226b8e150e1a5ec3180f748ff8,Robust and Practical Face Recognition via Structured Sparsity,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
becd5fd62f6301226b8e150e1a5ec3180f748ff8,Robust and Practical Face Recognition via Structured Sparsity,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
becd5fd62f6301226b8e150e1a5ec3180f748ff8,Robust and Practical Face Recognition via Structured Sparsity,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
bebb8a97b2940a4e5f6e9d3caf6d71af21585eda,Mapping Emotional Status to Facial Expressions,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
be4f7679797777f2bc1fd6aad8af67cce5e5ce87,Interestingness Prediction by Robust Learning to Rank,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
be4f7679797777f2bc1fd6aad8af67cce5e5ce87,Interestingness Prediction by Robust Learning to Rank,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+beeadf57a976f23f4fd6fa8a330eac6c81d3e3cd,ESGM : Event Enrichment and Summarization by Graph Model,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+beeadf57a976f23f4fd6fa8a330eac6c81d3e3cd,ESGM : Event Enrichment and Summarization by Graph Model,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+beeadf57a976f23f4fd6fa8a330eac6c81d3e3cd,ESGM : Event Enrichment and Summarization by Graph Model,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
be28ed1be084385f5d389db25fd7f56cd2d7f7bf,Exploring computation-communication tradeoffs in camera systems,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
be28ed1be084385f5d389db25fd7f56cd2d7f7bf,Exploring computation-communication tradeoffs in camera systems,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+beecaf2d6e9d102b6b2459ea38e15179a4b55ffd,Surveillance Video Parsing with Single Frame Supervision,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+bea0bb77c0d75c3d70fefc274bfbff93a3eff015,Video Captioning with Transferred Semantic Attributes,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+bea0bb77c0d75c3d70fefc274bfbff93a3eff015,Video Captioning with Transferred Semantic Attributes,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+bee512a8117ef26e5c9fbcc36da8d0d0fabcc5d5,Online Adaptative Curriculum Learning for GANs,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+bee512a8117ef26e5c9fbcc36da8d0d0fabcc5d5,Online Adaptative Curriculum Learning for GANs,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+bee512a8117ef26e5c9fbcc36da8d0d0fabcc5d5,Online Adaptative Curriculum Learning for GANs,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+bea56c0e615e6cea496f52331432bbc344d55192,Pose - Invariant Multimodal ( 2 D + 3 D ) Face Recognition using Geodesic Distance Map,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
+bea56c0e615e6cea496f52331432bbc344d55192,Pose - Invariant Multimodal ( 2 D + 3 D ) Face Recognition using Geodesic Distance Map,Griffith University,Griffith University,"Griffith University Nathan Campus, Johnson Path, Nathan, Nathan Heights, QLD, 4111, Australia",-27.55339750,153.05336234,edu,
+be7bb84581b09f47668966d0cb70df0876c84a21,Fixation detection for head-mounted eye tracking based on visual similarity of gaze targets,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+be7bb84581b09f47668966d0cb70df0876c84a21,Fixation detection for head-mounted eye tracking based on visual similarity of gaze targets,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+be7bb84581b09f47668966d0cb70df0876c84a21,Fixation detection for head-mounted eye tracking based on visual similarity of gaze targets,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
bec31269632c17206deb90cd74367d1e6586f75f,Large-scale Datasets: Faces with Partial Occlusions and Pose Variations in the Wild,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
be5276e9744c4445fe5b12b785650e8f173f56ff,Spatio-Temporal VLAD Encoding for Human Action Recognition in Videos,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
be5276e9744c4445fe5b12b785650e8f173f56ff,Spatio-Temporal VLAD Encoding for Human Action Recognition in Videos,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
be5276e9744c4445fe5b12b785650e8f173f56ff,Spatio-Temporal VLAD Encoding for Human Action Recognition in Videos,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+bef6daed8cd1ac90ee1c0a42e5c019bbf523491c,"Total Variation, Cheeger Cuts","University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+bed8a74e75ed96868ce81ed1080433ef5be66a52,Supervising the New with the Old: Learning SFM from SFM,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+bec26ea7335ed723a1c4360d6365f2dd846161e7,A method to Suppress Facial Expression in Posed and Spontaneous Videos,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+be9cab9e9040b667e7902a4d9fbf1a358b350d60,Pedestrian Detection and Tracking Using HOG and Oriented-LBP Features,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+bec3c3e6bb9c738dad942f00fc69848018c3b1cc,Part-Activated Deep Reinforcement Learning for Action Prediction,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+bec3c3e6bb9c738dad942f00fc69848018c3b1cc,Part-Activated Deep Reinforcement Learning for Action Prediction,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+beb0239feac388e4ee04492159a45f7e2c71e1e3,POI: Multiple Object Tracking with High Performance Detection and Appearance Feature,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+beb0239feac388e4ee04492159a45f7e2c71e1e3,POI: Multiple Object Tracking with High Performance Detection and Appearance Feature,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
be57d2aaab615ec8bc1dd2dba8bee41a4d038b85,Automatic Analysis of Naturalistic Hand-Over-Face Gestures,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
be4f18e25b06f430e2de0cc8fddcac8585b00beb,A New Face Recognition Algorithm based on Dictionary Learning for a Single Training Sample per Person,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+be2ce56434c8cf50c08f8be6f4f9b9f7c716eabd,A Convnet for Non-maximum Suppression,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+b38c7a58b4c5298705b8f63dcb6a1c21ee297af8,"Fusing Deep Learned and Hand-Crafted Features of Appearance, Shape, and Dynamics for Automatic Pain Estimation",University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+b38c7a58b4c5298705b8f63dcb6a1c21ee297af8,"Fusing Deep Learned and Hand-Crafted Features of Appearance, Shape, and Dynamics for Automatic Pain Estimation",University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
b3b532e8ea6304446b1623e83b0b9a96968f926c,Joint Network based Attention for Action Recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
b3b532e8ea6304446b1623e83b0b9a96968f926c,Joint Network based Attention for Action Recognition,Beijing Institute of Technology,Beijing Institute of Technology University,"北京理工大学, 5, 中关村南大街, 中关村, 稻香园南社区, 海淀区, 北京市, 100872, 中国",39.95866520,116.30971281,edu,
+b370eb9839be558e7db8390ce342312bd4835be9,Object Localization Does Not Imply Awareness of Object Category at the Break of Continuous Flash Suppression,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+b306bd9b485c6a6c1e4550beb1910ed9b6585359,Learning generative models of mid-level structure in natural images,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
b3154d981eca98416074538e091778cbc031ca29,Pedestrian Attribute Analysis Using a Top-View Camera in a Public Space,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
b3154d981eca98416074538e091778cbc031ca29,Pedestrian Attribute Analysis Using a Top-View Camera in a Public Space,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+b3cc2554449fb10002250bbc178e1009fc2fdb70,Face Recognition Based on Local Zernike Moments,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
+b3e50a64709a62628105546e392cf796f95ea0fb,Clustering via Boundary Erosion,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+b3e50a64709a62628105546e392cf796f95ea0fb,Clustering via Boundary Erosion,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+b352bd38298608afab5df341857313c146c1418c,One-Shot Learning of Sketch Categories with Co-regularized Sparse Coding,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+b352bd38298608afab5df341857313c146c1418c,One-Shot Learning of Sketch Categories with Co-regularized Sparse Coding,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
b3200539538eca54a85223bf0ec4f3ed132d0493,Action Anticipation with RBF Kernelized Feature Mapping RNN,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+b33e062f36dec4e49558133426b50c2536cb0a1b,A Learning-Style Theory for Understanding Autistic Behaviors,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+b33e062f36dec4e49558133426b50c2536cb0a1b,A Learning-Style Theory for Understanding Autistic Behaviors,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+b33e062f36dec4e49558133426b50c2536cb0a1b,A Learning-Style Theory for Understanding Autistic Behaviors,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+b33e062f36dec4e49558133426b50c2536cb0a1b,A Learning-Style Theory for Understanding Autistic Behaviors,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+b395e6a9f28c5acbf81a58599283753c033b9540,Online Face Recognition System Based on Local Binary Patterns and Facial Landmark Tracking,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
b3b467961ba66264bb73ffe00b1830d7874ae8ce,Finding Tiny Faces,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
b3b467961ba66264bb73ffe00b1830d7874ae8ce,Finding Tiny Faces,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
b3ba7ab6de023a0d58c741d6abfa3eae67227caf,Zero-Shot Activity Recognition with Verb Attribute Induction,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
b3330adb131fb4b6ebbfacce56f1aec2a61e0869,Emotion recognition using facial images,SASTRA University,SASTRA University,"SASTRA University, SRC Campus, Big Bazaar Street, கும்பகோணம், Thanjavur district, Tamil Nadu, 612001, India",10.96286550,79.38530651,edu,
+b3c8752cada163af9f72d37d2781ecd49b4c8c52,Nonparametric guidance of autoencoder representations using label information,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+b3c8752cada163af9f72d37d2781ecd49b4c8c52,Nonparametric guidance of autoencoder representations using label information,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+b3345c179be86c3fa7f3fece7d1f0db93e2cf8dc,Perceptual Differences between Men and Women: A 3D Facial Morphometric Perspective,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+b3ee1a0ff6cb36621c65c4a7b05a5179db280d35,Neural Caption Generation for News Images,Aston University,Aston University,"Aston University, Aston Street, Digbeth, Birmingham, West Midlands Combined Authority, West Midlands, England, B4, UK",52.48620785,-1.88849915,edu,
b3f3d6be11ace907c804c2d916830c85643e468d,A Logical Framework for Trust - Related Emotions : Formal and Behavioral Results by Manh Hung NGUYEN Co - supervisors,University of Toulouse,University of Toulouse,"Toulouse, Lake Charles, Calcasieu Parish, Louisiana, 70605, USA",30.17818160,-93.23605810,edu,
+b3e856729f89b082b4108561479ff09394bb6553,Pose Robust Video - Based Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+b3b920c797259d1340fcd2cee619203821dabe23,Alpha-Beta Divergences Discover Micro and Macro Structures in Data,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+b3a82f7df6d19898da0d0a01285b8331e099cea4,Gait-Based Person Identification Using Motion Interchange Patterns,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+b3376f115f8b13695f1b8c1a7f00f4cfea4cae53,Human Body Orientation Estimation in Multiview Scenarios,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
b3658514a0729694d86a8b89c875a66cde20480c,Improving the Robustness of Subspace Learning Techniques for Facial Expression Recognition,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+b357576afb70465e47144aef96955b1e4b9cc1f7,Oriented Response Networks,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+b357576afb70465e47144aef96955b1e4b9cc1f7,Oriented Response Networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+b3d592bfbdeddd4074cf7aa8a832f13cd9d3be0d,Visual Relationship Prediction via Label Clustering and Incorporation of Depth Information,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+b3416a5f7339c7e83d68ba1d00d00576880a8f04,Behavior-grounded multi-sensory object perception and exploration by a humanoid robot,Iowa State University,Iowa State University,"Iowa State University, Farm House Road, Ames, Story County, Iowa, 50014, USA",42.02791015,-93.64464415,edu,
b3b4a7e29b9186e00d2948a1d706ee1605fe5811,Image Preprocessing for Illumination Invariant Face Verification,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
+b36faeba2383cef082f9f3f509dd2098a926e2f5,Speed Up Learning based Descriptor for Face Verification,Pohang University of Science and Technology,Pohang University of Science and Technology,"포스텍, 77, 청암로, 효곡동, 남구, 포항시, 경북, 37673, 대한민국",36.01773095,129.32107509,edu,
b33e8db8ccabdfc49211e46d78d09b14557d4cba,Face Expression Recognition and Analysis: The State of the Art,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+b3a45118534144f50a56653dac8109c73fc2c0e8,A Dataset for Persistent Multi-target Multi-camera Tracking in RGB-D,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+b341a33f098ce9dc6dbf5c50e8a1f7fe43fb21f2,Deep learning evaluation using deep linguistic processing,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+b341a33f098ce9dc6dbf5c50e8a1f7fe43fb21f2,Deep learning evaluation using deep linguistic processing,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+b3014317cea72345a711d82d27f2c03c53932a31,Model-based Human Pose Estimation Using Labelled Voxels by ICP,Hunan University,Hunan University,"Yejin University for Employees, 冶金西路, 和平乡, 珠晖区, 衡阳市 / Hengyang, 湖南省, 中国",26.88111275,112.62850666,edu,
+b3014317cea72345a711d82d27f2c03c53932a31,Model-based Human Pose Estimation Using Labelled Voxels by ICP,Hunan University,Hunan University,"Yejin University for Employees, 冶金西路, 和平乡, 珠晖区, 衡阳市 / Hengyang, 湖南省, 中国",26.88111275,112.62850666,edu,
dfd934ae448a1b8947d404b01303951b79b13801,The importance of internal facial features in learning new faces.,University of Plymouth,University of Plymouth,"Charles Seale-Hayne Library, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37525010,-4.13927692,edu,
dfd934ae448a1b8947d404b01303951b79b13801,The importance of internal facial features in learning new faces.,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
dfd934ae448a1b8947d404b01303951b79b13801,The importance of internal facial features in learning new faces.,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
dfd934ae448a1b8947d404b01303951b79b13801,The importance of internal facial features in learning new faces.,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
+df724040bf460858b3e325fab0a4dd3374a647a7,Capsules for Object Segmentation,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+df724040bf460858b3e325fab0a4dd3374a647a7,Capsules for Object Segmentation,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+dfe823d9851d222f299ad26283c7de4b4a3941e8,Kernel Fisher Discriminant Analysis in Full Eigenspace,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+df45ca54171804193c0b499e8f3d282cc8b06998,LVreID: Person Re-Identification with Long Sequence Videos,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+df45ca54171804193c0b499e8f3d282cc8b06998,LVreID: Person Re-Identification with Long Sequence Videos,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+df45ca54171804193c0b499e8f3d282cc8b06998,LVreID: Person Re-Identification with Long Sequence Videos,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
df0e280cae018cebd5b16ad701ad101265c369fa,Deep Attributes from Context-Aware Regional Neural Codes,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
df0e280cae018cebd5b16ad701ad101265c369fa,Deep Attributes from Context-Aware Regional Neural Codes,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+df7e3f5cb90230f6bed1473c4984f336b56615c8,A Multi-Stage Approach to Facial Feature Detection,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+dfe5849fc844bd7b747b3ecbe0f28ffb7e6ee917,Semantically Consistent Image Completion with Fine-grained Details,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+df9a08016fa553a169d893ce2d3fca375bab4781,Partially-Supervised Image Captioning,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
df2c685aa9c234783ab51c1aa1bf1cb5d71a3dbb,SREFI: Synthesis of realistic example face images,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+df8341b479434721d3738cc672cf976c080ab7e2,Learning Deep Networks from Noisy Labels with Dropout Regularization,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+df8341b479434721d3738cc672cf976c080ab7e2,Learning Deep Networks from Noisy Labels with Dropout Regularization,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+df8341b479434721d3738cc672cf976c080ab7e2,Learning Deep Networks from Noisy Labels with Dropout Regularization,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+df8717e1153c48e457ea5ace1aa97c30ee7374bb,RenderNet: A deep convolutional network for differentiable rendering from 3D shapes,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+df8717e1153c48e457ea5ace1aa97c30ee7374bb,RenderNet: A deep convolutional network for differentiable rendering from 3D shapes,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+df58cf3fe7502a91a7d319be11680ee5b1c78e6d,Eye Detection and Gaze Estimation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+df58cf3fe7502a91a7d319be11680ee5b1c78e6d,Eye Detection and Gaze Estimation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+df8a4d17bd48cd9c9f1e74396fa95cdf3381012b,Distinct Neurophysiological Mechanisms Support the Online Formation of Individual and Across-Episode Memory Representations.,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+df8a4d17bd48cd9c9f1e74396fa95cdf3381012b,Distinct Neurophysiological Mechanisms Support the Online Formation of Individual and Across-Episode Memory Representations.,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+dfbf941adeea19f5dff4a70a466ddd1b77f3b727,Models for supervised learning in sequence data,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
dfd8602820c0e94b624d02f2e10ce6c798193a25,Structured Analysis Dictionary Learning for Image Classification,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+df01f6be9573a7864e86d960db7cf3cef3a8199d,Multi-Agent Reinforcement Learning for Multi-Object Tracking,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
dff838ba0567ef0a6c8fbfff9837ea484314efc6,"Progress Report, MSc. Dissertation: On-line Random Forest for Face Detection",University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+df9a016950ffaaa8526e7332f0a6568ad43d054f,A Fast Stereo-based System for Detecting and Tracking Pedestrians from a Moving Vehicle,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+df7312cbabb7d75d915ba0d91dea77100ded5c56,Preliminary Studies on a Large Face Database,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+df7312cbabb7d75d915ba0d91dea77100ded5c56,Preliminary Studies on a Large Face Database,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
df71a00071d5a949f9c31371c2e5ee8b478e7dc8,Using opportunistic face logging from smartphone to infer mental health: challenges and future directions,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
df71a00071d5a949f9c31371c2e5ee8b478e7dc8,Using opportunistic face logging from smartphone to infer mental health: challenges and future directions,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
df71a00071d5a949f9c31371c2e5ee8b478e7dc8,Using opportunistic face logging from smartphone to infer mental health: challenges and future directions,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+df3c2ac15c71b6cdc07f4268ee83d4fc1984545f,Random field topic model for semantic region analysis in crowded scenes from tracklets,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+df3c2ac15c71b6cdc07f4268ee83d4fc1984545f,Random field topic model for semantic region analysis in crowded scenes from tracklets,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+df3c2ac15c71b6cdc07f4268ee83d4fc1984545f,Random field topic model for semantic region analysis in crowded scenes from tracklets,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
df9269657505fcdc1e10cf45bbb8e325678a40f5,Open-Domain Audio-Visual Speech Recognition: A Deep Learning Approach,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
dfb6aa168177d4685420fcb184def0aa7db7cddb,The Effect of Lighting Direction/Condition on the Performance of Face Recognition Algorithms,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
dfb6aa168177d4685420fcb184def0aa7db7cddb,The Effect of Lighting Direction/Condition on the Performance of Face Recognition Algorithms,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
df2841a1d2a21a0fc6f14fe53b6124519f3812f9,Learning Image Attributes using the Indian Buffet Process,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
df2841a1d2a21a0fc6f14fe53b6124519f3812f9,Learning Image Attributes using the Indian Buffet Process,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+df31e9c882dfb3ea5a3abe3b139ceacb1d90a302,DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture Model,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+df9491cc46eacf66bb963a699b73ec1a82aec4eb,Learning Attributes from the Crowdsourced Relative Labels,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+df969647a0ee9ea25b23589f44be5240b5097236,How robust is familiar face recognition? A repeat detection study of more than 1000 faces,Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
+df969647a0ee9ea25b23589f44be5240b5097236,How robust is familiar face recognition? A repeat detection study of more than 1000 faces,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+dae0a4ef50b347f145ed6de8f6c7fb94d350f937,Managing Heterogeneous Datacenters with Tokens,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+dae0a4ef50b347f145ed6de8f6c7fb94d350f937,Managing Heterogeneous Datacenters with Tokens,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+dae0a4ef50b347f145ed6de8f6c7fb94d350f937,Managing Heterogeneous Datacenters with Tokens,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+dae0a4ef50b347f145ed6de8f6c7fb94d350f937,Managing Heterogeneous Datacenters with Tokens,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+dae0a4ef50b347f145ed6de8f6c7fb94d350f937,Managing Heterogeneous Datacenters with Tokens,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+daf74c34f7da0695b154f645c8b78a7397a98f16,ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+daf74c34f7da0695b154f645c8b78a7397a98f16,ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+da0b41c22e0918c99ba89a04eed4f8ed58cc1d66,Subspace Clustering using Ensembles of $K$-Subspaces,Portland State University,Portland State University,"Portland State University, Southwest Park Avenue, University District, Portland Downtown, Portland, Multnomah County, Oregon, 97201, USA",45.51181205,-122.68492999,edu,
+da0b41c22e0918c99ba89a04eed4f8ed58cc1d66,Subspace Clustering using Ensembles of $K$-Subspaces,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+da7fc2231134fef949882bc193bc1802b318c6ff,Qualitative Pose Estimation by Discriminative Deformable Part Models,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+da8eb0d7666d481ba0d50a03067dbc1913131495,Physics-based face database for color research,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
daf05febbe8406a480306683e46eb5676843c424,Robust Subspace Segmentation with Block-Diagonal Prior,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
daf05febbe8406a480306683e46eb5676843c424,Robust Subspace Segmentation with Block-Diagonal Prior,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
daf05febbe8406a480306683e46eb5676843c424,Robust Subspace Segmentation with Block-Diagonal Prior,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+da1049ae56eaca2e7d65946cf87b1e504d9fcb70,VisDA : A Synthetic-to-Real Benchmark for Visual Domain Adaptation,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+da1049ae56eaca2e7d65946cf87b1e504d9fcb70,VisDA : A Synthetic-to-Real Benchmark for Visual Domain Adaptation,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+da90c9ff02e76a7e686ffe13bcdedbf949c86dfa,Adaptive workload-aware task scheduling for single-ISA asymmetric multicore architectures,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+da115fc803e692d18802400940855eb6c78691e4,Deep Convolutional Neural Networks with Merge-and-Run Mappings,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+da115fc803e692d18802400940855eb6c78691e4,Deep Convolutional Neural Networks with Merge-and-Run Mappings,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+da44881db32c132eb9cdef524618e3c8ed340b47,Annotation-Free and One-Shot Learning for Instance Segmentation of Homogeneous Object Clusters,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+da11b7bba74c4abbfb181bd7d07c4e6480d6c3e2,Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+da11b7bba74c4abbfb181bd7d07c4e6480d6c3e2,Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination,"National Institute of Informatics, Japan","National Institute of Informatics, Japan","2 Chome-1-２ Hitotsubashi, Chiyoda, Tokyo 100-0003, Japan",35.69248530,139.75825330,edu,
+da11b7bba74c4abbfb181bd7d07c4e6480d6c3e2,Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+da11b7bba74c4abbfb181bd7d07c4e6480d6c3e2,Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+da67293fe8ab15539dd045675fa2395435f239b6,View-independent coding of face identity in frontal and temporal cortices is modulated by familiarity: an event-related fMRI study.,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+da67293fe8ab15539dd045675fa2395435f239b6,View-independent coding of face identity in frontal and temporal cortices is modulated by familiarity: an event-related fMRI study.,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
daa52dd09b61ee94945655f0dde216cce0ebd505,Recognizing Micro-Actions and Reactions from Paired Egocentric Videos,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
daa52dd09b61ee94945655f0dde216cce0ebd505,Recognizing Micro-Actions and Reactions from Paired Egocentric Videos,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
daa52dd09b61ee94945655f0dde216cce0ebd505,Recognizing Micro-Actions and Reactions from Paired Egocentric Videos,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+da5075fa79da6cd7b81e5d3dc24161217ef86368,ViP-CNN: A Visual Phrase Reasoning Convolutional Neural Network for Visual Relationship Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+daba4ff9ad8015f6c9626dbdfee950fda401424f,IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+da4137396f26bf3e76d04eeed0c94e11b7824aa6,Transferable Semi-Supervised Semantic Segmentation,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+da4137396f26bf3e76d04eeed0c94e11b7824aa6,Transferable Semi-Supervised Semantic Segmentation,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+da4137396f26bf3e76d04eeed0c94e11b7824aa6,Transferable Semi-Supervised Semantic Segmentation,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+daf9c461bc515736749e14da67045d8a542c24a1,Neighborhood MinMax Projections,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+b4843913e5ba0f1bfc12f179587d3789676c3310,4 DFAB : A Large Scale 4 DDatabase for Facial Expression Analysis and Biometric Applications,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+b4843913e5ba0f1bfc12f179587d3789676c3310,4 DFAB : A Large Scale 4 DDatabase for Facial Expression Analysis and Biometric Applications,Middlesex University,Middlesex University,"Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK",51.59029705,-0.22963221,edu,
+b4288f34528fbda2d2781454aadccae0d578d59a,Bayesian 3D Tracking from Monocular Video,University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
+b4288f34528fbda2d2781454aadccae0d578d59a,Bayesian 3D Tracking from Monocular Video,University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
+b4288f34528fbda2d2781454aadccae0d578d59a,Bayesian 3D Tracking from Monocular Video,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
b4d694961d3cde43ccef7d8fcf1061fe0d8f97f3,Rapid face recognition using hashing,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
b4d694961d3cde43ccef7d8fcf1061fe0d8f97f3,Rapid face recognition using hashing,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
b4ee1b468bf7397caa7396cfee2ab5f5ed6f2807,A short review and primer on electromyography in human computer interaction applications,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
@@ -1039,29 +2809,96 @@ b446bcd7fb78adfe346cf7a01a38e4f43760f363,To appear in ICB 2018 Longitudinal Stud b446bcd7fb78adfe346cf7a01a38e4f43760f363,To appear in ICB 2018 Longitudinal Study of Child Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
b417b90fa0c288bbaab1aceb8ebc7ec1d3f33172,Face Aging with Contextual Generative Adversarial Nets,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
b417b90fa0c288bbaab1aceb8ebc7ec1d3f33172,Face Aging with Contextual Generative Adversarial Nets,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+b411448a978e48352e1959addb9ca8dc762262a3,Probabilistic Subspace Clustering Via Sparse Representations,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+b411448a978e48352e1959addb9ca8dc762262a3,Probabilistic Subspace Clustering Via Sparse Representations,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+b446cf353744a4b640af88d1848a1b958169c9f2,Multi-attribute sparse representation with group constraints for face recognition under different variations,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
b42a97fb47bcd6bfa72e130c08960a77ee96f9ab,Based on Graph-preserving Sparse Non-negative Matrix Factorization,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
b42a97fb47bcd6bfa72e130c08960a77ee96f9ab,Based on Graph-preserving Sparse Non-negative Matrix Factorization,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
b4d209845e1c67870ef50a7c37abaf3770563f3e,"Video Time: Properties, Encoders and Evaluation",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+b47602296ccda89bec7dfa592965dacf17ca1483,Conditional Image-to-Image Translation,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+b4720674dcd92d28978e24727d5b40edb363dfe9,Input Fast-Forwarding for Better Deep Learning,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
+b4720674dcd92d28978e24727d5b40edb363dfe9,Input Fast-Forwarding for Better Deep Learning,Alexandria University,Alexandria University,"جامعة الإسكندرية, الكورنيش, إبراهيمية, الإسكندرية, 21522, مصر",31.21051105,29.91314562,edu,
+b4720674dcd92d28978e24727d5b40edb363dfe9,Input Fast-Forwarding for Better Deep Learning,Benha University,Benha University,"كلية الهندسة بشبرا جامعة بنها, شارع اليازجي, روض الفرج, القاهرة, محافظة القاهرة, 2466, مصر",30.08187270,31.24454841,edu,
+b4ad2bdbf82c8bd1454f6d743b956bcfbad54101,Learning from Experience in Manipulation Planning: Setting the Right Goals,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+b4ad2bdbf82c8bd1454f6d743b956bcfbad54101,Learning from Experience in Manipulation Planning: Setting the Right Goals,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+b4ad2bdbf82c8bd1454f6d743b956bcfbad54101,Learning from Experience in Manipulation Planning: Setting the Right Goals,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+b4ad2bdbf82c8bd1454f6d743b956bcfbad54101,Learning from Experience in Manipulation Planning: Setting the Right Goals,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+b4ad2bdbf82c8bd1454f6d743b956bcfbad54101,Learning from Experience in Manipulation Planning: Setting the Right Goals,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+b41d2d4750ba7fdfe072d253f408e5b60c75eb1f,Single versus Multiple Sorting in All Pairs Similarity Search,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+b4e889af57295dff9498ba476893a359a91b8a3e,Improving Speaker Turn Embedding by Crossmodal Transfer Learning from Face Embedding,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+b438dc16bf97c1324ac66771efa67bdb9b853346,Evaluating asymmetric multiprocessing for mobile applications,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+b42a8325d5cabefd11cee59f4b2b5901eb7f18c6,Curriculum Learning of Visual Attribute Clusters for Multi-Task Classification,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+b42a8325d5cabefd11cee59f4b2b5901eb7f18c6,Curriculum Learning of Visual Attribute Clusters for Multi-Task Classification,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
+b4c60fe73d1e788ebe0e24b0c8989e4fda110ac5,Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+b4c60fe73d1e788ebe0e24b0c8989e4fda110ac5,Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+b4c60fe73d1e788ebe0e24b0c8989e4fda110ac5,Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+b4c60fe73d1e788ebe0e24b0c8989e4fda110ac5,Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+b4a60cfe62d78e315ed4206d455022ead27ecbf0,Deep hashing with triplet quantization loss,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+b46e7d361a030f96d54a9717127f17d0cc833e32,Contextualized Bilinear Attention Networks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+b47dae9d6499c6a777847a26297a647f0de49214,Aberrant Social Attention and Its Underlying Neural Correlates in Adults with Autism Spectrum Disorder,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
b4362cd87ad219790800127ddd366cc465606a78,A Smartphone-Based Automatic Diagnosis System for Facial Nerve Palsy,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
b4362cd87ad219790800127ddd366cc465606a78,A Smartphone-Based Automatic Diagnosis System for Facial Nerve Palsy,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
b4362cd87ad219790800127ddd366cc465606a78,A Smartphone-Based Automatic Diagnosis System for Facial Nerve Palsy,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+b4ee6b62f6a89feede06da5fb7e5ad6ec0265175,Recurrent 3D Pose Sequence Machines,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+b4a09b6a7c78c3d54a0ce59ae3ebb6d4ebfd7d06,"Weight, Sex, and Facial Expressions: On the Manipulation of Attributes in Generative 3D Face Models",University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+b4fe4bdd0e42aadf3f7046e9c681d3585ba8a205,Improving dual-tree algorithms,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+b4fe4bdd0e42aadf3f7046e9c681d3585ba8a205,Improving dual-tree algorithms,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+b45549a95120a744e6b882216f8a86481fedd255,Local feature hierarchy for face recognition across pose and illumination,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
b4f4b0d39fd10baec34d3412d53515f1a4605222,Every Picture Tells a Story: Generating Sentences from Images,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+b41c90bce7fecdcf5980a9990f8693ff07997b65,Categorizing Concepts with Basic Level for Vision-to-Language,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+b41c90bce7fecdcf5980a9990f8693ff07997b65,Categorizing Concepts with Basic Level for Vision-to-Language,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+b47add32c0b26e72f5670644618076dfd8bc1404,Attribute-Guided Face Generation Using Conditional CycleGAN,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
b43b6551ecc556557b63edb8b0dc39901ed0343b,ICA and Gabor representation for facial expression recognition,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+b4f5cf797a1c857f32e5740d53d9990bc925af2b,Review of Segmentation with Deep Learning and Discover Its Application in Ultrasound Images,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+b4f67b4286ea99e7f0a57536282445e801b97847,Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking,"University of Colorado, Denver",University of Colorado Denver,"University of Colorado (Denver Auraria campus), Lawrence Way, Auraria, Denver, Denver County, Colorado, 80217, USA",39.74287785,-105.00596398,edu,
+b4f67b4286ea99e7f0a57536282445e801b97847,Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking,"University of Colorado, Denver",University of Colorado Denver,"University of Colorado (Denver Auraria campus), Lawrence Way, Auraria, Denver, Denver County, Colorado, 80217, USA",39.74287785,-105.00596398,edu,
a255a54b8758050ea1632bf5a88a201cd72656e1,Nonparametric Facial Feature Localization,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
a2b9cee7a3866eb2db53a7d81afda72051fe9732,Reconstructing a Fragmented Face from an Attacked Secure Identification Protocol,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
a2bd81be79edfa8dcfde79173b0a895682d62329,Multi-Objective Vehicle Routing Problem Applied to Large Scale Post Office Deliveries,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
+a20210d875221088d6428330787606e12605c68f,Person Independent Head Pose Estimation by Non-Linear Regression and Manifold Embedding,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+a287643d3eddca3dcc09b3532f2b070a28d4a022,Real-time Human Pose Estimation from Video with Convolutional Neural Networks,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+a287643d3eddca3dcc09b3532f2b070a28d4a022,Real-time Human Pose Estimation from Video with Convolutional Neural Networks,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
a2eb90e334575d9b435c01de4f4bf42d2464effc,A new sparse image representation algorithm applied to facial expression recognition,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+a251171bb335608b3019f7b05b167b7e49a8dc23,Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+a251171bb335608b3019f7b05b167b7e49a8dc23,Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
+a2e29b757f4021ed5b9eb7eebf78a0bddb460790,Visual scenes are categorized by function.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+a2e29b757f4021ed5b9eb7eebf78a0bddb460790,Visual scenes are categorized by function.,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+a2e29b757f4021ed5b9eb7eebf78a0bddb460790,Visual scenes are categorized by function.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
a25106a76af723ba9b09308a7dcf4f76d9283589,Local Octal Pattern: A Proficient Feature Extraction for Face Recognition,Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
a29a22878e1881d6cbf6acff2d0b209c8d3f778b,Benchmarking Still-to-Video Face Recognition via Partial and Local Linear Discriminant Analysis on COX-S2V Dataset,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
a29a22878e1881d6cbf6acff2d0b209c8d3f778b,Benchmarking Still-to-Video Face Recognition via Partial and Local Linear Discriminant Analysis on COX-S2V Dataset,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
a29a22878e1881d6cbf6acff2d0b209c8d3f778b,Benchmarking Still-to-Video Face Recognition via Partial and Local Linear Discriminant Analysis on COX-S2V Dataset,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+a2e86c23cde8899ac39d0df43d6c5e4dcf0ae2e6,Deep Collaborative Learning for Visual Recognition,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
a2429cc2ccbabda891cc5ae340b24ad06fcdbed5,Discovering the Signatures of Joint Attention in Child-Caregiver Interaction,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
a2429cc2ccbabda891cc5ae340b24ad06fcdbed5,Discovering the Signatures of Joint Attention in Child-Caregiver Interaction,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
a2429cc2ccbabda891cc5ae340b24ad06fcdbed5,Discovering the Signatures of Joint Attention in Child-Caregiver Interaction,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
a2429cc2ccbabda891cc5ae340b24ad06fcdbed5,Discovering the Signatures of Joint Attention in Child-Caregiver Interaction,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+a2e3c367995a238155f0b180743d5487ecdf8df5,Novel Modular Weightless Neural Architectures for Biometrics-based Recognition,University of Kent,University of Kent,"University of Kent, St. Stephen's Hill, Hackington, Canterbury, Kent, South East, England, CT2 7AS, UK",51.29753440,1.07296165,edu,
+a20f132a30e99541aa7ba6dddac86e6a393778e8,Self Attention Grid for Person Re-Identification,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+a2f69a94380ccfd463886d26f07c4dba791f84d4,5-HT1A-receptor agonist modified amygdala activity and amygdala-associated social behavior in a valproate-induced rat autism model.,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+a2f69a94380ccfd463886d26f07c4dba791f84d4,5-HT1A-receptor agonist modified amygdala activity and amygdala-associated social behavior in a valproate-induced rat autism model.,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+a2f69a94380ccfd463886d26f07c4dba791f84d4,5-HT1A-receptor agonist modified amygdala activity and amygdala-associated social behavior in a valproate-induced rat autism model.,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+a2cdd215586701c883dc3959c80f53ee5c091fe7,FaceLooks: A Smart Headband for Signaling Face-to-Face Behavior,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+a2cdd215586701c883dc3959c80f53ee5c091fe7,FaceLooks: A Smart Headband for Signaling Face-to-Face Behavior,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+a2cdd215586701c883dc3959c80f53ee5c091fe7,FaceLooks: A Smart Headband for Signaling Face-to-Face Behavior,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+a29566375836f37173ccaffa47dea25eb1240187,Vehicle Re-Identification in Context,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+a21685146f68de1f87e206c0a22dbc0188d55b2d,Robust Tracking and Human Activity Recognition,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+a2ab16c6eff749d2081d11ddc0b9e310eda62061,Attributes as Operators: Factorizing Unseen Attribute-Object Compositions,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
a2bcfba155c990f64ffb44c0a1bb53f994b68a15,The Photoface database,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
a2bcfba155c990f64ffb44c0a1bb53f994b68a15,The Photoface database,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+a22c372911680793c7f94e3fd0b3843a2019f085,Designing Deep Convolutional Neural Networks for Continuous Object Orientation Estimation,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+a247c12bc54f7792e381c6e71d98348f8059ca15,Learning Efficient Object Detection Models with Knowledge Distillation,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+a247c12bc54f7792e381c6e71d98348f8059ca15,Learning Efficient Object Detection Models with Knowledge Distillation,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+a25f1b02c63857482dcaa621f3a52e2b34d8b022,A System for Multimodal Context-Awareness,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+a2d1818eb461564a5153c74028e53856cf0b40fd,Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition,Tencent,"Tencent AI Lab, China","Ke Ji Zhong Yi Lu, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057",22.54471540,113.93571640,company,"Keji Middle 1st Rd, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057"
+a25d12d3eaaba6ec8ef4a2690068e9fbd74b977a,Morph: Flexible Acceleration for 3D CNN-based Video Understanding,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+a2183537ccf24eb95e8e7520b33f9aa8f190e80e,Subspace-Based Holistic Registration for Low-Resolution Facial Images,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+a2a17b7421bd46224127e35e3451b1af36528a6a,Nested multi-instance classification,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+a2a17b7421bd46224127e35e3451b1af36528a6a,Nested multi-instance classification,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
a59cdc49185689f3f9efdf7ee261c78f9c180789,A New Approach for Learning Discriminative Dictionary for Pattern Classification,Hanoi University of Science and Technology,Hanoi University of Science and Technology,"HUST, Trần Đại Nghĩa, Hai Bà Trưng, Hà Nội, 10999, Việt Nam",21.00395200,105.84360183,edu,
+a5ae7d662ed086bc5b0c9a2c1dc54fcb23635000,Relief R-CNN : Utilizing Convolutional Feature Interrelationship for Fast Object Detection Deployment,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+a5ae7d662ed086bc5b0c9a2c1dc54fcb23635000,Relief R-CNN : Utilizing Convolutional Feature Interrelationship for Fast Object Detection Deployment,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+a5bc960e186391ca0ba0718aec70069abb5134e5,Age Invariant Face Recognition Using Convolutional Neural Networks and Set Distances,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
a5c8fc1ca4f06a344b53dc81ebc6d87f54896722,Learning to see people like people,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
a5c8fc1ca4f06a344b53dc81ebc6d87f54896722,Learning to see people like people,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
a5c8fc1ca4f06a344b53dc81ebc6d87f54896722,Learning to see people like people,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
@@ -1069,22 +2906,62 @@ a5c8fc1ca4f06a344b53dc81ebc6d87f54896722,Learning to see people like people,"Uni a5ade88747fa5769c9c92ffde9b7196ff085a9eb,Why is facial expression analysis in the wild challenging?,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
a5ade88747fa5769c9c92ffde9b7196ff085a9eb,Why is facial expression analysis in the wild challenging?,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
a5ade88747fa5769c9c92ffde9b7196ff085a9eb,Why is facial expression analysis in the wild challenging?,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+a54fcdcb02da0844d28b3191145bbc99675714df,"FATAUVA-Net: An Integrated Deep Learning Framework for Facial Attribute Recognition, Action Unit Detection, and Valence-Arousal Estimation",National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+a5219fff98dfe3ec81dee95c4ead69a8e24cc802,Dual-Glance Model for Deciphering Social Relationships,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+a5219fff98dfe3ec81dee95c4ead69a8e24cc802,Dual-Glance Model for Deciphering Social Relationships,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+a59800f16ad02f550c600fff4179167bad0b8654,Neonatal Pain Expression Recognition Using Transfer Learning,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+a58bef564df2bebbcb24c58c4a69bc6c51ab2d39,Kernel Implicit Variational Inference,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+a58bef564df2bebbcb24c58c4a69bc6c51ab2d39,Kernel Implicit Variational Inference,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
a5f11c132eaab258a7cea2d681875af09cddba65,A spatiotemporal model with visual attention for video classification,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+a59978ac12815cada0936dce760a6ff6aef376d9,Multi-Scale Face Restoration With Sequential Gating Ensemble Network,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+a5ee4693668d976dbd79a753c62e0614af2f5060,Hybrid Knowledge Routed Modules for Large-scale Object Detection,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+a5ee4693668d976dbd79a753c62e0614af2f5060,Hybrid Knowledge Routed Modules for Large-scale Object Detection,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+a5ee4693668d976dbd79a753c62e0614af2f5060,Hybrid Knowledge Routed Modules for Large-scale Object Detection,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+a5766dd5f2efe0b44879799dd5499edfb6b44839,Illumination Quality Assessment for Face Images: A Benchmark and a Convolutional Neural Networks Based Model,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+a5766dd5f2efe0b44879799dd5499edfb6b44839,Illumination Quality Assessment for Face Images: A Benchmark and a Convolutional Neural Networks Based Model,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
a538b05ebb01a40323997629e171c91aa28b8e2f,Rectified Linear Units Improve Restricted Boltzmann Machines,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
a57ee5a8fb7618004dd1def8e14ef97aadaaeef5,Fringe Projection Techniques: Whither we are?,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+a576d19473a12e16262266989376ad1e77e8e817,Unmanned Aerial Vehicle Object Tracking by Correlation Filter with Adaptive Appearance Model,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+a576d19473a12e16262266989376ad1e77e8e817,Unmanned Aerial Vehicle Object Tracking by Correlation Filter with Adaptive Appearance Model,Aberystwyth University,Aberystwyth University,"Aberystwyth University, Llanbadarn Campus, Cefn Esgair, Waun Fawr, Comins Coch, Ceredigion, Wales, SY23 3JG, UK",52.41073580,-4.05295501,edu,
+a50099f5364d3d4e82991418647c727f0f9c297c,A Generic Bi-Layer Data-Driven Crowd Behaviors Modeling Approach,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+a5ee556c355392db1750df92ae2dc8867073e771,Improved Local Coordinate Coding using Local Tangents,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+a566780ffbaf2e1ee88a821be4d0ffade934c518,Greedy Representative Selection for Unsupervised Data Analysis,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
a51882cfd0706512bf50e12c0a7dd0775285030d,Cross-Modal Face Matching: Beyond Viewed Sketches,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+a51cdc57f35f536468325a40a7777954c864935b,Fast and Robust Realtime Storefront Logo Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
a52581a7b48138d7124afc7ccfcf8ec3b48359d0,Pose and Illumination Invariant Face Recognition Based on 3D Face Reconstruction,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+a5bec55a9668b103265bcf84ecca94128a6769cc,Accounting for Aliasing in Correlation Filters : Zero-Aliasing and Partial-Aliasing Correlation Filters,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a5bec55a9668b103265bcf84ecca94128a6769cc,Accounting for Aliasing in Correlation Filters : Zero-Aliasing and Partial-Aliasing Correlation Filters,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a5f094bd197126025cabc50b30e0f03d56d8c594,Online Motion Agreement Tracking,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+bdbaf77951b845859a7203a33d91b6a595f5f9f3,Tracking Revisited using RGBD Camera: Baseline and Benchmark,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+bdbaf77951b845859a7203a33d91b6a595f5f9f3,Tracking Revisited using RGBD Camera: Baseline and Benchmark,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
bd0265ba7f391dc3df9059da3f487f7ef17144df,Data-Driven Sparse Sensor Placement,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
bd0265ba7f391dc3df9059da3f487f7ef17144df,Data-Driven Sparse Sensor Placement,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
bd0265ba7f391dc3df9059da3f487f7ef17144df,Data-Driven Sparse Sensor Placement,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
bd572e9cbec095bcf5700cb7cd73d1cdc2fe02f4,Deep Learning for Computer Vision: A Brief Review,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
bd6099429bb7bf248b1fd6a1739e744512660d55,"Regularized Discriminant Analysis, Ridge Regression and Beyond",Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+bd5802008156ed1ee6919ccaf21ba6c06bad2a4c,Robust eye contact detection in natural multi-person interactions using gaze and speaking behaviour,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+bd5802008156ed1ee6919ccaf21ba6c06bad2a4c,Robust eye contact detection in natural multi-person interactions using gaze and speaking behaviour,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+bd5802008156ed1ee6919ccaf21ba6c06bad2a4c,Robust eye contact detection in natural multi-person interactions using gaze and speaking behaviour,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+bd5802008156ed1ee6919ccaf21ba6c06bad2a4c,Robust eye contact detection in natural multi-person interactions using gaze and speaking behaviour,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+bd6158bed42b038863c8ace0c96700e87c1c0231,"Action Unit Detection with Region Adaptation, Multi-labeling Learning and Optimal Temporal Fusing",CUNY City College,CUNY City College,"CUNY City College, 205 East 42nd Street, New York, NY 10017",45.55466080,5.40652550,edu,
+bde3c1298d4136369c8607dd5dc3f0800a27a8df,Extracting adaptive contextual cues from unlabeled regions,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+bde3c1298d4136369c8607dd5dc3f0800a27a8df,Extracting adaptive contextual cues from unlabeled regions,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+bdf46e52b9cc967628f423b1a69555a1114cc3e3,Spontaneous vs. Posed Facial Expression Analysis Using Deformable Feature Models and Aggregated Classifiers,Khalifa University,Khalifa University,"Khalifa University, شارع طَوِي مُوَيلِح, قصر الشاطئ, حدبة الزَّعْفرانة, أبوظبي, أبو ظبي, 31757, الإمارات العربية المتحدة",24.44690250,54.39425630,edu,
+bdf46e52b9cc967628f423b1a69555a1114cc3e3,Spontaneous vs. Posed Facial Expression Analysis Using Deformable Feature Models and Aggregated Classifiers,Khalifa University,Khalifa University,"Khalifa University, شارع طَوِي مُوَيلِح, قصر الشاطئ, حدبة الزَّعْفرانة, أبوظبي, أبو ظبي, 31757, الإمارات العربية المتحدة",24.44690250,54.39425630,edu,
bd8f3fef958ebed5576792078f84c43999b1b207,BUAA-iCC at ImageCLEF 2015 Scalable Concept Image Annotation Challenge,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+bd65efb5d1fbff19dcd3cd24452f359013eac188,Unsupervised Feature Learning With Symmetrically Connected Convolutional Denoising Auto-encoders,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+bd65efb5d1fbff19dcd3cd24452f359013eac188,Unsupervised Feature Learning With Symmetrically Connected Convolutional Denoising Auto-encoders,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
bd0201b32e7eca7818468f2b5cb1fb4374de75b9,Facial Emotion Expressions Recognition with Brain Activites Using Kinect Sensor V2,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
bd0201b32e7eca7818468f2b5cb1fb4374de75b9,Facial Emotion Expressions Recognition with Brain Activites Using Kinect Sensor V2,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
bd236913cfe07896e171ece9bda62c18b8c8197e,Deep Learning with Energy-efficient Binary Gradient Cameras,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+bd433d471af50b571d7284afb5ee435654ace99f,Going Deeper with Convolutional Neural Network for Intelligent Transportation,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+bd8a85acaa45d4068fca584e8d9e3bd3bb4eea4d,Toward Scene Recognition by Discovering Semantic Structures and Parts,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+bd8a85acaa45d4068fca584e8d9e3bd3bb4eea4d,Toward Scene Recognition by Discovering Semantic Structures and Parts,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+bd8a85acaa45d4068fca584e8d9e3bd3bb4eea4d,Toward Scene Recognition by Discovering Semantic Structures and Parts,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+bd1d466299f585f2f67500a6ceef19008c4cb637,Pose and Illumination Invariant Face Recognition Using Video Sequences,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
bd379f8e08f88729a9214260e05967f4ca66cd65,Learning Compositional Visual Concepts with Mutual Consistency,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
bd379f8e08f88729a9214260e05967f4ca66cd65,Learning Compositional Visual Concepts with Mutual Consistency,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+bd98a68ef57d60aa6c939504d06d95fe08e2aceb,ViS-HuD: Using Visual Saliency to Improve Human Detection with Convolutional Neural Networks,Ahmedabad University,Ahmedabad University,"School of Science and Technology, University Road, Gurukul, Gulbai tekra, Ahmedabad, Ahmedabad District, Gujarat, 380001, India",23.03787430,72.55180046,edu,
bd21109e40c26af83c353a3271d0cd0b5c4b4ade,Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
bd21109e40c26af83c353a3271d0cd0b5c4b4ade,Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
bd21109e40c26af83c353a3271d0cd0b5c4b4ade,Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
@@ -1097,15 +2974,52 @@ bd8f77b7d3b9d272f7a68defc1412f73e5ac3135,SphereFace: Deep Hypersphere Embedding bd26dabab576adb6af30484183c9c9c8379bf2e0,SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
bd9c9729475ba7e3b255e24e7478a5acb393c8e9,Interpretable Partitioned Embedding for Customized Fashion Outfit Composition,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
bd9c9729475ba7e3b255e24e7478a5acb393c8e9,Interpretable Partitioned Embedding for Customized Fashion Outfit Composition,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+bdb1fca40fd98a966b627ba9b0f4a0ac801dffdc,"Multi-Scale , Multi-Temporal Vegetation Mapping and Assessment of Ecosystem Degradation at Gashaka Gumti National Park ( Nigeria )",University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
bd9157331104a0708aa4f8ae79b7651a5be797c6,SLAC: A Sparsely Labeled Dataset for Action Classification and Localization,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+bd4f2e7a196c0d6033a49390ee8836f4f551b7c8,ICDAR 2015 competition on Robust Reading,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+bd4f2e7a196c0d6033a49390ee8836f4f551b7c8,ICDAR 2015 competition on Robust Reading,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+bdaed05eefddd2829c937978852fcf3cedc84620,Multifactor Analysis for Face Recognition Based on Factor-Dependent Geometry,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+bdaed05eefddd2829c937978852fcf3cedc84620,Multifactor Analysis for Face Recognition Based on Factor-Dependent Geometry,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+bdaed05eefddd2829c937978852fcf3cedc84620,Multifactor Analysis for Face Recognition Based on Factor-Dependent Geometry,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+bd5c222323d6b46ea71f329cafe11d38533f6f3a,Repetition Suppression and Memory for Faces is Reduced in Adults with Autism Spectrum Conditions,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+bd17484e0a6773a74c51c41e773e202080682b3b,2D-3D Pose Consistency-based Conditional Random Fields for 3D Human Pose Estimation,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
bd70f832e133fb87bae82dfaa0ae9d1599e52e4b,Combining Classifier for Face Identification at Unknown Views with a Single Model Image,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+d1c204da4e0ab653c32ae8fc325d5b69641b6ed7,Learning Globally Optimized Object Detector via Policy Gradient,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+d1c204da4e0ab653c32ae8fc325d5b69641b6ed7,Learning Globally Optimized Object Detector via Policy Gradient,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+d1c204da4e0ab653c32ae8fc325d5b69641b6ed7,Learning Globally Optimized Object Detector via Policy Gradient,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
d185f4f05c587e23c0119f2cdfac8ea335197ac0,"Facial Expression Analysis, Modeling and Synthesis: Overcoming the Limitations of Artificial Intelligence with the Art of the Soluble",Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
d185f4f05c587e23c0119f2cdfac8ea335197ac0,"Facial Expression Analysis, Modeling and Synthesis: Overcoming the Limitations of Artificial Intelligence with the Art of the Soluble",Ritsumeikan University,Ritsumeikan University,"立命館大学 (Ritsumeikan University), 衣笠宇多野線, 北区, 京都市, 京都府, 近畿地方, 6038577, 日本",35.03332810,135.72491540,edu,
+d10f8d58bf50f5b097b4344dc8cccbbe0c330bd9,Hard-Aware Deeply Cascaded Embedding,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+d10f8d58bf50f5b097b4344dc8cccbbe0c330bd9,Hard-Aware Deeply Cascaded Embedding,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+d10f8d58bf50f5b097b4344dc8cccbbe0c330bd9,Hard-Aware Deeply Cascaded Embedding,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
d140c5add2cddd4a572f07358d666fe00e8f4fe1,Statistically Learned Deformable Eye Models,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+d1ba33106567c880bf99daba2bd31fe88df4ecba,Deep Adaptive Feature Embedding with Local Sample Distributions for Person Re-identification,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+d1ba33106567c880bf99daba2bd31fe88df4ecba,Deep Adaptive Feature Embedding with Local Sample Distributions for Person Re-identification,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+d1ba33106567c880bf99daba2bd31fe88df4ecba,Deep Adaptive Feature Embedding with Local Sample Distributions for Person Re-identification,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+d10eff69699591d26dbb69ed17d8afe06bc581db,Wasserstein Introspective Neural Networks,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+d182c6d9ac4777b5ad73afdd64b7b68d76037212,Aligned Image-Word Representations Improve Inductive Transfer Across Vision-Language Tasks,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+d16968e5baac6d26b9cef5034f9d84bcc3ec627c,"Children Facial Expression Production: Influence of Age, Gender, Emotion Subtype, Elicitation Condition and Culture",Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+d16968e5baac6d26b9cef5034f9d84bcc3ec627c,"Children Facial Expression Production: Influence of Age, Gender, Emotion Subtype, Elicitation Condition and Culture",Hiroshima University,Hiroshima University,"Hiroshima University 広島大学 東広島キャンパス, 出会いの道 Deai-no-michi Str., 西条下見, 東広島市, 広島県, 中国地方, 739-0047, 日本",34.40197660,132.71231950,edu,
+d1d90bbc6bb4fdb0d928ff74bfd8671aaafa070e,Neural Person Search Machines,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+d1d90bbc6bb4fdb0d928ff74bfd8671aaafa070e,Neural Person Search Machines,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+d1d90bbc6bb4fdb0d928ff74bfd8671aaafa070e,Neural Person Search Machines,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
d115c4a66d765fef596b0b171febca334cea15b5,Combining Stacked Denoising Autoencoders and Random Forests for Face Detection,Swansea University,Swansea University,"Swansea University, University Footbridge, Sketty, Swansea, Wales, SA2 8PZ, UK",51.60915780,-3.97934429,edu,
+d1f3fb7e8be9d8db50f29403ffbbf6ec58623e61,Embodied Question Answering,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+d1b0d2ec2f01c3aab06119192cf9ba23146cc662,"Explanatory Dialogs : Towards Actionable , Interactive Explanations Gagan Bansal",University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+d1d15291dadc44f0cd192dc88bab3b10e2b07ccd,"“I Look in Your Eyes, Honey”: Internal Face + Features Induce Spatial Frequency Preference for Human Face Processing",University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+d13e81c7a3d6f62948a68663acfecc3a480d9b1c,Scaling Distributed All-Pairs Algorithms: Manage Computation and Limit Data Replication with Quorums,Iowa State University,Iowa State University,"Iowa State University, Farm House Road, Ames, Story County, Iowa, 50014, USA",42.02791015,-93.64464415,edu,
+d13bb317e87f3f6da10da11059ebf4350b754814,"Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation",University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
d1959ba4637739dcc6cc6995e10fd41fd6604713,Deep Learning for Semantic Video Understanding,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
d1881993c446ea693bbf7f7d6e750798bf958900,Large-Scale YouTube-8M Video Understanding with Deep Neural Networks,"Institute for System Programming, Moscow",Institute for System Programming,"ИСП РАН, 25, улица Александра Солженицына, Швивая горка, Таганский район, Центральный административный округ, Москва, ЦФО, 109004, РФ",55.74498810,37.66450421,edu,
d1881993c446ea693bbf7f7d6e750798bf958900,Large-Scale YouTube-8M Video Understanding with Deep Neural Networks,"Institute for System Programming, Moscow",Institute for System Programming,"ИСП РАН, 25, улица Александра Солженицына, Швивая горка, Таганский район, Центральный административный округ, Москва, ЦФО, 109004, РФ",55.74498810,37.66450421,edu,
+d1d9e6027288cdd64509ea62f88a3cbd9320c180,Automated Markerless Analysis of Human Gait Motion for Recognition and Classification,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+d1bca67dd26d719b3e7a51acecd7c54c7b78b34a,Spatial Pyramid Convolutional Neural Network for Social Event Detection in Static Image,Kumamoto University,Kumamoto University,"熊本大学黒髪キャンパス, 熊本菊陽線, 中央区, 熊本市, 熊本県, 九州地方, 860-0863, 日本",32.81641780,130.72703969,edu,
+d1e388269ea8ce7074f804f79e158038f629a0df,Batch-Based Activity Recognition from Egocentric Photo-Streams,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+d67277eb00d58d20eaa18c346761fe4eeaab9c49,Multi-Level Fusion based 3 D Object Detection from Monocular Images,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+d6b2d4f1bc08dc3d3922fb43b1b8e3614349f539,"Burçin Buket Oğul in partial fulfillment of the requirements for the degree of Master of Science in Information Systems , Middle East Technical",Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+d6b1c0c2107abb01ee4241963eab26e261510f12,Weakly supervised learning of semantic colour terms,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+d6b1b0e60e1764982ef95d4ade8fcaa10bfb156a,A Sketch-based Approach for Multimedia Retrieval,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
d69719b42ee53b666e56ed476629a883c59ddf66,Learning Facial Action Units from Web Images with Scalable Weakly Supervised Clustering,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
d69719b42ee53b666e56ed476629a883c59ddf66,Learning Facial Action Units from Web Images with Scalable Weakly Supervised Clustering,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
d647099e571f9af3a1762f895fd8c99760a3916e,Exploring facial expressions with compositional features,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
@@ -1116,63 +3030,206 @@ d6ca3dc01de060871839d5536e8112b551a7f9ff,Sleep-deprived fatigue pattern analysis d6ca3dc01de060871839d5536e8112b551a7f9ff,Sleep-deprived fatigue pattern analysis using large-scale selfies from social media,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
d6ca3dc01de060871839d5536e8112b551a7f9ff,Sleep-deprived fatigue pattern analysis using large-scale selfies from social media,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
d61e794ec22a4d4882181da17316438b5b24890f,Detecting Sensor Level Spoof Attacks Using Joint Encoding of Temporal and Spatial Features,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+d675a54dd5e353f99a1bec3b2ddab925a6563653,Thin-Slicing Network: A Deep Structured Model for Pose Estimation in Videos,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
+d6b1e14d211145bbc083b230d1724826de430fb7,Eye detection in the Middle-Wave Infrared spectrum: Towards recognition in the dark,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+d6d7b7e882a65663fafe470f0582afb4279879b7,Active Learning & its Applications,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
d67dcaf6e44afd30c5602172c4eec1e484fc7fb7,Illumination Normalization for Robust Face Recognition Using Discrete Wavelet Transform,Mahanakorn University of Technology,Mahanakorn University of Technology,"มหาวิทยาลัยเทคโนโลยีมหานคร, 140, ถนนเชื่อมสัมพันธ์, กรุงเทพมหานคร, เขตหนองจอก, กรุงเทพมหานคร, 10530, ประเทศไทย",13.84450465,100.85620818,edu,
+d6c4069044b976c48c384c4562338942a842cf55,3D Human Pose Estimation with 2D Marginal Heatmaps,La Trobe University,La Trobe University,"La Trobe University, Keck Street, Flora Hill, Bendigo, City of Greater Bendigo, Loddon Mallee, Victoria, 3550, Australia",-36.77847540,144.29804700,edu,
d68dbb71b34dfe98dee0680198a23d3b53056394,VIVA Face-off Challenge: Dataset Creation and Balancing Privacy,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
d666ce9d783a2d31550a8aa47da45128a67304a7,On Relating Visual Elements to City Statistics,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
d666ce9d783a2d31550a8aa47da45128a67304a7,On Relating Visual Elements to City Statistics,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
d666ce9d783a2d31550a8aa47da45128a67304a7,On Relating Visual Elements to City Statistics,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+d6143ddbee74c10996d291c666fa17bd87f9d4e2,CT-GAN: Conditional Transformation Generative Adversarial Network for Image Attribute Modification,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+d6daaec16ac90de8f99640f687ad7e9e92a46840,Can gait biometrics be Spoofed?,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+d6daaec16ac90de8f99640f687ad7e9e92a46840,Can gait biometrics be Spoofed?,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+d6ad7334d6e2575d61f86f91b8edac8053af8c35,A framework for automatic question generation from text using deep reinforcement learning,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
+d670583c4065132282dbcb4387ee6a83e85f8af1,"A Study of Question Effectiveness Using Reddit ""Ask Me Anything"" Threads",University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+bc21bf4c733e117d2d969fd5605bba4251467243,Fusion of dynamic and static features for gait recognition over time,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+bce887343456e4344b8174b99cea641a97a7bfa6,On gait as a biometric: Progress and prospects,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+bcab55f8bf0623df71623e673c767eed2159f05a,Deep Hybrid Scattering Image Learning,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+bce36092b1910ff3d492f86aa3a39ed8faaf72d2,Chapter 17 Face Recognition Using 3 D Images,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+bce61a182c7a1028eed0c0f67e779753a86503c2,Soft Activation Mapping of Lung Nodules in Low-Dose CT images,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+bce61a182c7a1028eed0c0f67e779753a86503c2,Soft Activation Mapping of Lung Nodules in Low-Dose CT images,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+bce61a182c7a1028eed0c0f67e779753a86503c2,Soft Activation Mapping of Lung Nodules in Low-Dose CT images,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+bc7a3573a464bca2cdca71f6f32e798464b85ee6,Exploiting Semantic Contextualization for Interpretation of Human Activity in Videos,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+bc7a3573a464bca2cdca71f6f32e798464b85ee6,Exploiting Semantic Contextualization for Interpretation of Human Activity in Videos,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+bc7a3573a464bca2cdca71f6f32e798464b85ee6,Exploiting Semantic Contextualization for Interpretation of Human Activity in Videos,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
bc9003ad368cb79d8a8ac2ad025718da5ea36bc4,Facial expression recognition with a three-dimensional face model,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+bc7e6175aed6538eca08962e133aede11fc75bcf,Multi-Scale Supervised Network for Human Pose Estimation,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+bc494a3442ec7adff4527e60947214c0015f3b3a,Convolutional Image Captioning,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+bcd59b43aaef7f466eda609e3f887a3db4ae3b41,Graph Correspondence Transfer for Person Re-identification,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+bcd59b43aaef7f466eda609e3f887a3db4ae3b41,Graph Correspondence Transfer for Person Re-identification,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+bcd59b43aaef7f466eda609e3f887a3db4ae3b41,Graph Correspondence Transfer for Person Re-identification,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+bcd59b43aaef7f466eda609e3f887a3db4ae3b41,Graph Correspondence Transfer for Person Re-identification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+bca7d615cc143a255c0dc65235ba1acbac86ba32,Learning to Adapt Structured Output Space for Semantic Segmentation,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+bcc0a12f8dbc3efcd3ef353b0173c49a8889e763,Automatic Face Anonymization in Visual Data: Are we really well protected?,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
bc15a2fd09df7046e7e8c7c5b054d7f06c3cefe9,Using deep autoencoders for facial expression recognition,"COMSATS Institute of Information Technology, Islamabad","COMSATS Institute of Information Technology, Islamabad","COMSATS Institute of Information Technology, Fence, Chak Shehzad, وفاقی دارالحکومت اسلام آباد, 45550, پاکستان",33.65010145,73.15514949,edu,
bc15a2fd09df7046e7e8c7c5b054d7f06c3cefe9,Using deep autoencoders for facial expression recognition,Information Technology University,Information Technology University (ITU),"Information Technology University (ITU), Ferozepur Road, Sher Shah Block, Garden Town, Al Noor Town, Lahore District, پنجاب, 54600, پاکستان",31.47602990,74.34275260,edu,
bc15a2fd09df7046e7e8c7c5b054d7f06c3cefe9,Using deep autoencoders for facial expression recognition,National University of Sciences and Technology,National University of Sciences and Technology,"National University of Sciences and Technology (NUST), Kashmir Highway, جی - 10, ICT, وفاقی دارالحکومت اسلام آباد, 44000, پاکستان",33.64434700,72.98850790,edu,
+bc25f5e10c839d08ac8827fbe7724cd713008803,Properties of Patch Based Approaches for the Recognition of Visual Object Classes,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+bc3a7dcc237041aa4b0d70e07c9bc441dbbc9c97,Passive and Motivated Perception of Emotional Faces: Qualitative and Quantitative Changes in the Face Processing Network,University of Chicago,THE UNIVERSITY OF CHICAGO,"University of Chicago, South Ellis Avenue, Woodlawn, Chicago, Cook County, Illinois, 60637, USA",41.78468745,-87.60074933,edu,
+bc3a7dcc237041aa4b0d70e07c9bc441dbbc9c97,Passive and Motivated Perception of Emotional Faces: Qualitative and Quantitative Changes in the Face Processing Network,University of Chicago,THE UNIVERSITY OF CHICAGO,"University of Chicago, South Ellis Avenue, Woodlawn, Chicago, Cook County, Illinois, 60637, USA",41.78468745,-87.60074933,edu,
bc27434e376db89fe0e6ef2d2fabc100d2575ec6,Faceless Person Recognition; Privacy Implications in Social Media,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+bc3e01016c4b2b75e9163c91fa65b64dcfb1acc9,Relaxed Softmax : Efficient Confidence Auto-Calibration for Safe Pedestrian Detection,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+bc2953c2d177b18f0870ff9e7439e00a904a0b33,Please smile,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+bc2953c2d177b18f0870ff9e7439e00a904a0b33,Please smile,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+bc2953c2d177b18f0870ff9e7439e00a904a0b33,Please smile,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
bc12715a1ddf1a540dab06bf3ac4f3a32a26b135,Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
bc12715a1ddf1a540dab06bf3ac4f3a32a26b135,Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+bc9f3c466c6f6b386f4ef1195853d498cf3c182e,Mapping Instructions and Visual Observations to Actions with Reinforcement Learning,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+bc9f3c466c6f6b386f4ef1195853d498cf3c182e,Mapping Instructions and Visual Observations to Actions with Reinforcement Learning,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
bc910ca355277359130da841a589a36446616262,Conditional High-Order Boltzmann Machine: A Supervised Learning Model for Relation Learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+bca6e77e7e0db8f632af7395e99028025854ea0d,A Multiview-Based Parameter Free Framework for Group Detection,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+bccfda60d53fd1ca114355f606fcfcc2bc9da529,Person Re-identification with Cascaded Pairwise Convolutions,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+bccfda60d53fd1ca114355f606fcfcc2bc9da529,Person Re-identification with Cascaded Pairwise Convolutions,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+bc871497626afb469d25c4975aa657159269aefe,Adaptive learning algorithm for pattern classification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+bc871497626afb469d25c4975aa657159269aefe,Adaptive learning algorithm for pattern classification,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+bc27c0d99e6f21b8a4fac6a0cf1079f6755554cc,Adaptive Sparse Kernel Principal Component Analysis for Computation and Store Space Constrained-based Feature Extraction,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+bc27c0d99e6f21b8a4fac6a0cf1079f6755554cc,Adaptive Sparse Kernel Principal Component Analysis for Computation and Store Space Constrained-based Feature Extraction,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+bc99f98b5f1fd158cc31d693061c402a36222dbb,Recent advances in understanding the neural bases of autism spectrum disorder.,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
bc866c2ced533252f29cf2111dd71a6d1724bd49,A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
bc8e11b8cdf0cfbedde798a53a0318e8d6f67e17,Deep Learning for Fixed Model Reuse,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+bc2856e70ad3c8fe439dec6cc6a2e03d6e090fb7,What value high level concepts in vision to language problems ?,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+bcfd771ee51f2813e910b339d08d10057af1e294,Analysis of face recognition under varying facial expression: a survey,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+bc6a0a107068b5a1715510e815c0103eaf80672a,Cross-pose Face Recognition by Canonical Correlation Analysis,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+bc6a0a107068b5a1715510e815c0103eaf80672a,Cross-pose Face Recognition by Canonical Correlation Analysis,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+bc6a0a107068b5a1715510e815c0103eaf80672a,Cross-pose Face Recognition by Canonical Correlation Analysis,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+bc6a0a107068b5a1715510e815c0103eaf80672a,Cross-pose Face Recognition by Canonical Correlation Analysis,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+ae5b2b449f59ae0f46f6a31ed4826d98241c394c,Accurate real-time people counting for crowded environments,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+ae5b2b449f59ae0f46f6a31ed4826d98241c394c,Accurate real-time people counting for crowded environments,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+ae5b2b449f59ae0f46f6a31ed4826d98241c394c,Accurate real-time people counting for crowded environments,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+aec46facf3131a5be4fc23db4ebfb5514e904ae3,Audio to the rescue,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+aea50d3414ecb20dc2ba77b0277d0df59bde2c2c,The #selfiestation: Design and Use of a Kiosk for Taking Selfies in the Enterprise,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
ae0765ebdffffd6e6cc33c7705df33b7e8478627,Self-Reinforced Cascaded Regression for Face Alignment,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
ae0765ebdffffd6e6cc33c7705df33b7e8478627,Self-Reinforced Cascaded Regression for Face Alignment,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
aefc7c708269b874182a5c877fb6dae06da210d4,Deep Learning of Invariant Features via Simulated Fixations in Video,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
aefc7c708269b874182a5c877fb6dae06da210d4,Deep Learning of Invariant Features via Simulated Fixations in Video,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+ae233a6f07d61e2c032bd09d92bdf20c27305c1f,Assessment of Pain Using Facial Pictures Taken with a Smartphone,Marquette University,Marquette University,"Marquette University, West Wisconsin Avenue, University Hill, Milwaukee, Milwaukee County, Wisconsin, 53226, USA",43.03889625,-87.93155450,edu,
+ae233a6f07d61e2c032bd09d92bdf20c27305c1f,Assessment of Pain Using Facial Pictures Taken with a Smartphone,Marquette University,Marquette University,"Marquette University, West Wisconsin Avenue, University Hill, Milwaukee, Milwaukee County, Wisconsin, 53226, USA",43.03889625,-87.93155450,edu,
aeaf5dbb3608922246c7cd8a619541ea9e4a7028,Weakly Supervised Facial Action Unit Recognition through Adversarial Training,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
ae836e2be4bb784760e43de88a68c97f4f9e44a1,Semi-SupervisedDimensionalityReduction ∗,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
ae836e2be4bb784760e43de88a68c97f4f9e44a1,Semi-SupervisedDimensionalityReduction ∗,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+aece472ba64007f2e86300cc3486c84597f02ec7,Analyzing Image-Text Relations for Semantic Media Adaptation and Personalization,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
ae5bb02599244d6d88c4fe466a7fdd80aeb91af4,"Analysis of Recognition Algorithms using Linear, Generalized Linear, and Generalized Linear Mixed Models",Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
ae5bb02599244d6d88c4fe466a7fdd80aeb91af4,"Analysis of Recognition Algorithms using Linear, Generalized Linear, and Generalized Linear Mixed Models",Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
ae18ccb35a1a5d7b22f2a5760f706b1c11bf39a9,Sensing Highly Non-Rigid Objects with RGBD Sensors for Robotic Systems,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+aecce5d8e06da797c087fb361732e84e62c04c4f,Bilateral Ordinal Relevance Multi-instance Regression for Facial Action Unit Intensity Estimation,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+aecce5d8e06da797c087fb361732e84e62c04c4f,Bilateral Ordinal Relevance Multi-instance Regression for Facial Action Unit Intensity Estimation,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+aef59def2a65901de9d520d0442b42bb4a448f06,Facial Expression Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+aed124c053b9c510487d68e0faf32aff2a84c3b5,FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+aed124c053b9c510487d68e0faf32aff2a84c3b5,FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+aed124c053b9c510487d68e0faf32aff2a84c3b5,FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge,Binghamton University,Binghamton University,"Binghamton University Downtown Center, Washington Street, Downtown, Binghamton, Broome County, New York, 13901, USA",42.09580770,-75.91455689,edu,
+aed124c053b9c510487d68e0faf32aff2a84c3b5,FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+aed124c053b9c510487d68e0faf32aff2a84c3b5,FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+aed124c053b9c510487d68e0faf32aff2a84c3b5,FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
ae1de0359f4ed53918824271c888b7b36b8a5d41,Low-cost Automatic Inpainting for Artifact Suppression in Facial Images,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
ae4390873485c9432899977499c3bf17886fa149,Facial Expression Recognition Using Digitalised Facial Features Based on Active Shape Model,Glyndwr University,Glyndwr University,"Glyndŵr University, Mold Road, Rhosrobin, Wrexham, Wales, LL11 2AW, UK",53.05373795,-3.00482075,edu,
+ae60fccb686272d12e909c9de99efb652e0934ec,The impact of internalizing symptoms on autistic traits in adolescents with restrictive anorexia nervosa,University of Pisa,University of Pisa,"Dipartimento di Fisica 'E. Fermi', 3, Largo Bruno Pontecorvo, San Francesco, Pisa, PI, TOS, 56127, Italia",43.72012990,10.40789760,edu,
+ae7ebf1c6111af9d00dfeceec4b48b528b437956,Exploring Human Cognition Using Large Image Databases,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+ae6e8851dfd9c97e37e1cbd61b21cc54d5e2b9c7,Paraphrasing Complex Network: Network Compression via Factor Transfer,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+ae85ff7fb5a7e7a232793c743ad11baf849a61bb,Exploring the Identity Manifold: Constrained Operations in Face Space,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+ae6193531d42fc20c9c991143ce323034d7aaa8d,Going Deeper with Semantics : Video Activity Interpretation using Semantic Contextualization,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+ae6193531d42fc20c9c991143ce323034d7aaa8d,Going Deeper with Semantics : Video Activity Interpretation using Semantic Contextualization,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+ae6193531d42fc20c9c991143ce323034d7aaa8d,Going Deeper with Semantics : Video Activity Interpretation using Semantic Contextualization,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
aea4128ba18689ff1af27b90c111bbd34013f8d5,Efficient k-Support Matrix Pursuit,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
aea4128ba18689ff1af27b90c111bbd34013f8d5,Efficient k-Support Matrix Pursuit,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
aea4128ba18689ff1af27b90c111bbd34013f8d5,Efficient k-Support Matrix Pursuit,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
aea4128ba18689ff1af27b90c111bbd34013f8d5,Efficient k-Support Matrix Pursuit,South China Normal University,South China Normal University,"华师, 五山路, 华南理工大学南新村, 天河区, 广州市, 广东省, 510630, 中国",23.14319700,113.34009651,edu,
+ae587a4a8842fbe01b9a043b66f762a89dca5074,Multi-view Supervision for Single-View Reconstruction via Differentiable Ray Consistency,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
ae2c71080b0e17dee4e5a019d87585f2987f0508,Emotional Face Recognition in Children With Attention Deficit/Hyperactivity Disorder: Evidence From Event Related Gamma Oscillation,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
ae2c71080b0e17dee4e5a019d87585f2987f0508,Emotional Face Recognition in Children With Attention Deficit/Hyperactivity Disorder: Evidence From Event Related Gamma Oscillation,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
+aefb110f14dd8d59c5465c7d91bd8b34a7c69597,A sequential guiding network with attention for image captioning,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+aefb110f14dd8d59c5465c7d91bd8b34a7c69597,A sequential guiding network with attention for image captioning,North China Electric Power University,North China Electric Power University,"华北电力大学, 永华北大街, 莲池区, 保定市, 莲池区 (Lianchi), 保定市, 河北省, 071000, 中国",38.87604460,115.49738730,edu,
+aec84e5aec1b6d83baeb4d447cde399864e25467,Automatic landmarking for non-cooperative 3D face recognition,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+ae47e73c25755427c9f5904425a35d7db737829b,Multi-scale convolutional neural networks for crowd counting,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
ae5f32e489c4d52e7311b66060c7381d932f4193,Appearance-and-Relation Networks for Video Classification,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
ae71f69f1db840e0aa17f8c814316f0bd0f6fbbf,That personal profile image might jeopardize your rental opportunity! On the relative impact of the seller's facial expressions upon buying behavior on Airbnb™,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+aeef1fcaeb3e5f3eac93ee275426a7f5eb586e0b,Alive Caricature from 2 D to 3 D,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+aeef1fcaeb3e5f3eac93ee275426a7f5eb586e0b,Alive Caricature from 2 D to 3 D,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+aeef1fcaeb3e5f3eac93ee275426a7f5eb586e0b,Alive Caricature from 2 D to 3 D,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+aef8456577768f2ff029107149c9c6713e8707f6,Multiplexed fluorescence unmixing,Bar-Ilan University,Bar-Ilan University,"אוניברסיטת בר אילן, כביש גהה, גבעת שמואל, קריית מטלון, גבעת שמואל, מחוז תל אביב, NO, ישראל",32.06932925,34.84334339,edu,
d893f75206b122973cdbf2532f506912ccd6fbe0,Facial Expressions with Some Mixed Expressions Recognition Using Neural Networks,Pondicherry Engineering College,Pondicherry Engineering College,"Pondicherry Engineering College, PEC MAIN ROAD, Sri Ma, Puducherry, Puducherry district, Puducherry, 605001, India",12.01486930,79.84809104,edu,
+d802ed7d8b7aea71a10bd0d700fd11fde5729993,Development of an Active Shape Model Using the Discrete Cosine Transform,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+d802ed7d8b7aea71a10bd0d700fd11fde5729993,Development of an Active Shape Model Using the Discrete Cosine Transform,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
+d814981606fe5954148e45c737f1debe7b5b36c4,Visual Textbook Network: Watch Carefully before Answering Visual Questions,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+d8f837265fe76e26c99052229c4997fbec20573a,View-Adaptive Metric Learning for Multi-view Person Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+d8f837265fe76e26c99052229c4997fbec20573a,View-Adaptive Metric Learning for Multi-view Person Re-identification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+d8b2e37eb9d2ee0e84bceafce84812cfa0b88211,Mgan: Training Generative Adversarial Nets with Multiple Generators,Deakin University,Deakin University,"Deakin University, Pigdons Lane, Waurn Ponds, Geelong, City of Greater Geelong, Barwon South West, Victoria, 3216, Australia",-38.19928505,144.30365229,edu,
d84a48f7d242d73b32a9286f9b148f5575acf227,Global and Local Consistent Age Generative Adversarial Networks,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+d84dccf9afffaf4e0cbb73f1ade34362a9fbe770,Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+d84dccf9afffaf4e0cbb73f1ade34362a9fbe770,Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+d84dccf9afffaf4e0cbb73f1ade34362a9fbe770,Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+d84dccf9afffaf4e0cbb73f1ade34362a9fbe770,Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
d8722ffbca906a685abe57f3b7b9c1b542adfa0c,Facial Expression Analysis for Human Computer Interaction,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
d8896861126b7fd5d2ceb6fed8505a6dff83414f,In-plane Rotational Alignment of Faces by Eye and Eye-pair Detection,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+d8d08bdcafdf892e3fc6ff3c38c2503ff9d41996,Learning image-to-image translation using paired and unpaired training samples,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+d8ddaddfd4843d483505718f3487e312310ba23e,Classification of Hematoxylin and Eosin Images Using Local Binary Patterns and 1-d Sift Algorithm,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+d8214e68bc7af0e24558fd9e79b2d777e46f2edc,Making Fisher Discriminant Analysis Scalable,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+d8214e68bc7af0e24558fd9e79b2d777e46f2edc,Making Fisher Discriminant Analysis Scalable,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+d8214e68bc7af0e24558fd9e79b2d777e46f2edc,Making Fisher Discriminant Analysis Scalable,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+d8214e68bc7af0e24558fd9e79b2d777e46f2edc,Making Fisher Discriminant Analysis Scalable,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+d8586c794456f88400231db046b0d33be7781185,Pedestrian Verification for Multi-Camera Detection,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
+d847d2b75bf301007a9e67889bdae5b147559ed3,Detangling People: Individuating Multiple Close People and Their Body Parts via Region Assembly,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
+d847d2b75bf301007a9e67889bdae5b147559ed3,Detangling People: Individuating Multiple Close People and Their Body Parts via Region Assembly,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+d8b251cbcda6289bbeaff56692da963aa5a80cd2,Multi-Task Multi-Sample Learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+d8b3aafb25c235be5c62da07881807872ac3e831,AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+d84230a2fc9950fccfd37f0291d65e634b5ffc32,Historical and Modern Image-to-Image Translation with Generative Adversarial Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+d84230a2fc9950fccfd37f0291d65e634b5ffc32,Historical and Modern Image-to-Image Translation with Generative Adversarial Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+d84230a2fc9950fccfd37f0291d65e634b5ffc32,Historical and Modern Image-to-Image Translation with Generative Adversarial Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
d8bf148899f09a0aad18a196ce729384a4464e2b,Facial Expression Recognition and Expression Intensity Estimation,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+d8ce4c55d04b93bdb94c1d0427cfe40431bef941,"Simultaneous Human Segmentation, Depth and Pose Estimation via Dual Decomposition",Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+d8ce4c55d04b93bdb94c1d0427cfe40431bef941,"Simultaneous Human Segmentation, Depth and Pose Estimation via Dual Decomposition",Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
d80a3d1f3a438e02a6685e66ee908446766fefa9,Quantifying Facial Age by Posterior of Age Comparisons,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
d80a3d1f3a438e02a6685e66ee908446766fefa9,Quantifying Facial Age by Posterior of Age Comparisons,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+d822a13d173db2c5244b7f7d31babb513143f5a9,Unsupervised Feature Analysis with Class Margin Optimization,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+d822a13d173db2c5244b7f7d31babb513143f5a9,Unsupervised Feature Analysis with Class Margin Optimization,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+d822a13d173db2c5244b7f7d31babb513143f5a9,Unsupervised Feature Analysis with Class Margin Optimization,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+d822a13d173db2c5244b7f7d31babb513143f5a9,Unsupervised Feature Analysis with Class Margin Optimization,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+d81b0a79558cabaaf3db22caf89454f4e012f21b,iParaphrasing: Extracting Visually Grounded Paraphrases via an Image,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
ab734bac3994b00bf97ce22b9abc881ee8c12918,Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
ab734bac3994b00bf97ce22b9abc881ee8c12918,Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+ab05988c3af93e7753de79996cc409be0a8d2bd1,Approximate LDA Technique for Dimensionality Reduction in the Small Sample Size Case,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+ab44a7585b45e72affe1746fc302baccd6412969,Multiview Depth-based Pose Estimation,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
+ab44a7585b45e72affe1746fc302baccd6412969,Multiview Depth-based Pose Estimation,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
abb396490ba8b112f10fbb20a0a8ce69737cd492,Robust Face Recognition Using Color Information,New Jersey Institute of Technology,New Jersey Institute of Technology,"New Jersey Institute of Technology, Warren Street, University Heights, Newark, Essex County, New Jersey, 07103, USA",40.74230250,-74.17928172,edu,
+ab0d227b63b702ba80f70fd053175cd1b2fd28cc,Boosting Pseudo Census Transform Features for Face Alignment,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
abac0fa75281c9a0690bf67586280ed145682422,Describable Visual Attributes for Face Images,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+abb7c66487009ea20967b9c6708f660fd4197bbb,In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+ab1728e84ac682ca0c53435f712a512ac139e9c8,University of Groningen Comparative Study Between Deep Learning and Bag of Visual Words for Wild-Animal,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+ab368594b9bd569e8d0fcf5c6010f1c31e3aa39e,"Node-Adapt, Path-Adapt and Tree-Adapt: Model-Transfer Domain Adaptation for Random Forest",Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+ab368594b9bd569e8d0fcf5c6010f1c31e3aa39e,"Node-Adapt, Path-Adapt and Tree-Adapt: Model-Transfer Domain Adaptation for Random Forest",Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+aba742ca4edc7dd37ff481d12e4b94c153baae77,Pose-Guided Human Parsing with Deep Learned Features,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+abc618b5c4f69a34c655bbb93c6003cc671b0f72,Is Faster R-CNN Doing Well for Pedestrian Detection?,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+abc618b5c4f69a34c655bbb93c6003cc671b0f72,Is Faster R-CNN Doing Well for Pedestrian Detection?,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+ab6ed75e1b1952e4461fc603bcfd042bb462635f,Cross-View Person Identification by Matching Human Poses Estimated with Confidence on Each Body Joint,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
+ab6ed75e1b1952e4461fc603bcfd042bb462635f,Cross-View Person Identification by Matching Human Poses Estimated with Confidence on Each Body Joint,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+ab0715642330502d5efca948e4753651cb004d84,Soft-NMS — Improving Object Detection with One Line of Code,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+ab567ca60fc3f72f27746b4d9e505042ab282ca3,Guidelines for studying developmental prosopagnosia in adults and children.,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+ab567ca60fc3f72f27746b4d9e505042ab282ca3,Guidelines for studying developmental prosopagnosia in adults and children.,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+ab567ca60fc3f72f27746b4d9e505042ab282ca3,Guidelines for studying developmental prosopagnosia in adults and children.,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
abba1bf1348a6f1b70a26aac237338ee66764458,Facial Action Unit Detection Using Attention and Relation Learning,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
abba1bf1348a6f1b70a26aac237338ee66764458,Facial Action Unit Detection Using Attention and Relation Learning,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
abba1bf1348a6f1b70a26aac237338ee66764458,Facial Action Unit Detection Using Attention and Relation Learning,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
abba1bf1348a6f1b70a26aac237338ee66764458,Facial Action Unit Detection Using Attention and Relation Learning,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
abdd17e411a7bfe043f280abd4e560a04ab6e992,Pose-Robust Face Recognition via Deep Residual Equivariant Mapping,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+ab134c9244c762f1429ccb7d737610d17d95f019,Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+ab84d00079d0a29e44bdc4c83037dc76b0fbef05,Visual Text Correction,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
ab427f0c7d4b0eb22c045392107509451165b2ba,Learning scale ranges for the extraction of regions of interest,Western Kentucky University,Western Kentucky University,"Western Kentucky University, Avenue of Champions, Bowling Green, Warren County, Kentucky, 42101, USA",36.98453170,-86.45764430,edu,
+ab1f057bfe02b80a14f4c011abb9ceb2a9c98b6c,Dress Like a Star: Retrieving Fashion Products from Videos,Aston University,Aston University,"Aston University, Aston Street, Digbeth, Birmingham, West Midlands Combined Authority, West Midlands, England, B4, UK",52.48620785,-1.88849915,edu,
+ab1f057bfe02b80a14f4c011abb9ceb2a9c98b6c,Dress Like a Star: Retrieving Fashion Products from Videos,Aston University,Aston University,"Aston University, Aston Street, Digbeth, Birmingham, West Midlands Combined Authority, West Midlands, England, B4, UK",52.48620785,-1.88849915,edu,
+ab39b26d623aee22cd43f78d9cb1f5e0e55808fd,Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+ab39b26d623aee22cd43f78d9cb1f5e0e55808fd,Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+ab39b26d623aee22cd43f78d9cb1f5e0e55808fd,Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+ab34ed858412b08441259374a83f4b3adb615789,Multimedia Annotation Through Search and Mining,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+e5954958314b2184d7c7017ef2b8e1be47da23e5,The Variational Homoencoder: Learning to learn high capacity generative models from few examples,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
e5e5f31b81ed6526c26d277056b6ab4909a56c6c,Revisit Multinomial Logistic Regression in Deep Learning: Data Dependent Model Initialization for Image Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
e506cdb250eba5e70c5147eb477fbd069714765b,Heterogeneous Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+e5ee85c412942bdfd9df8cc519d4af31d6d08a67,Improved Training with Curriculum GANs,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
e572c42d8ef2e0fadedbaae77c8dfe05c4933fbf,A Century of Portraits: A Visual Historical Record of American High School Yearbooks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
e572c42d8ef2e0fadedbaae77c8dfe05c4933fbf,A Century of Portraits: A Visual Historical Record of American High School Yearbooks,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
e572c42d8ef2e0fadedbaae77c8dfe05c4933fbf,A Century of Portraits: A Visual Historical Record of American High School Yearbooks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+e5a1864f6073f35920a8f7a0a368ff66b9dc6284,A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-Ranking,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+e5687f9584deca1fafb68b50fa79b9fcfbd1d379,Zero-Shot Object Recognition Using Semantic Label Vectors,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
e59813940c5c83b1ce63f3f451d03d34d2f68082,A Real-Time Facial Expression Recognition System for Online Games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
e59813940c5c83b1ce63f3f451d03d34d2f68082,A Real-Time Facial Expression Recognition System for Online Games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
e59813940c5c83b1ce63f3f451d03d34d2f68082,A Real-Time Facial Expression Recognition System for Online Games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
@@ -1180,145 +3237,419 @@ e59813940c5c83b1ce63f3f451d03d34d2f68082,A Real-Time Facial Expression Recogniti e59813940c5c83b1ce63f3f451d03d34d2f68082,A Real-Time Facial Expression Recognition System for Online Games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
e5b301ee349ba8e96ea6c71782295c4f06be6c31,The Case for Onloading Continuous High-Datarate Perception to the Phone,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
e5b301ee349ba8e96ea6c71782295c4f06be6c31,The Case for Onloading Continuous High-Datarate Perception to the Phone,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+e534582cfc1b98001fa1ad17cc1df47aeab1257f,Are We Looking in the Wrong Place? Implications for Behavioural-Based Pain Assessment in Rabbits (Oryctolagus cuniculi) and Beyond?,Newcastle University,Newcastle University,"Newcastle University, Claremont Walk, Haymarket, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE1 7RU, UK",54.98023235,-1.61452627,edu,
+e59e1c43ee86e3e68b83d8a9916ebe6375606bb3,Zero-Shot Transfer VQA Dataset,"Baidu Research, USA","Baidu Research, USA","1195 Bordeaux Dr, Sunnyvale, CA 94089, USA",37.40922650,-122.02366150,company,
+e50682179979e32c8d916c6c289d12d35cc0d0b2,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+e50682179979e32c8d916c6c289d12d35cc0d0b2,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+e50682179979e32c8d916c6c289d12d35cc0d0b2,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+e50682179979e32c8d916c6c289d12d35cc0d0b2,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+e50682179979e32c8d916c6c289d12d35cc0d0b2,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+e50682179979e32c8d916c6c289d12d35cc0d0b2,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+e597aca96ea1c928f13d15b7c4b46e3d41861afe,Mitigation of Effects of Occlusion on Object Recognition with Deep Neural Networks through Low-Level Image Completion,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
e569f4bd41895028c4c009e5b46b935056188e91,"FISHER VECTOR FACES IN THE WILD 3 Facial landmark detection Aligned and cropped face Dense SIFT , GMM , and FV Discriminative dim",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+e5b4700a615cde23b91be3eadf1c99642cd33e42,Joint Learning for Attribute-Consistent Person Re-Identification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
e5fbffd3449a2bfe0acb4ec339a19f5b88fff783,Self-supervised learning of a facial attribute embedding from video,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
e5d53a335515107452a30b330352cad216f88fc3,Generalized Loss-Sensitive Adversarial Learning with Manifold Margins,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+e5533c70706109ee8d0b2a4360fbe73fd3b0f35d,"How Far are We from Solving the 2D & 3D Face Alignment Problem? (and a Dataset of 230,000 3D Facial Landmarks)",University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+e2e920dfcaab27528c6fa65b6613d9af24793cb0,A comprehensive evaluation of multiband-accelerated sequences and their effects on statistical outcome measures in fMRI,University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
+e2e920dfcaab27528c6fa65b6613d9af24793cb0,A comprehensive evaluation of multiband-accelerated sequences and their effects on statistical outcome measures in fMRI,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+e2e920dfcaab27528c6fa65b6613d9af24793cb0,A comprehensive evaluation of multiband-accelerated sequences and their effects on statistical outcome measures in fMRI,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+e2e920dfcaab27528c6fa65b6613d9af24793cb0,A comprehensive evaluation of multiband-accelerated sequences and their effects on statistical outcome measures in fMRI,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+e2e920dfcaab27528c6fa65b6613d9af24793cb0,A comprehensive evaluation of multiband-accelerated sequences and their effects on statistical outcome measures in fMRI,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
e22adcd2a6a7544f017ec875ce8f89d5c59e09c8,Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding Arbitrary Gender Classifiers,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+e2b2bb648cfb60ee18bd66bc6e8a6f9daf7c9d74,Improving Context Modelling in Multimodal Dialogue Generation,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+e2b615e3b78aa18c293e7f03eb96591ccb721b55,Recurrent Segmentation for Variable Computational Budgets,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+e212b2bc41645fe467a73d004067fcf1ca77d87f,Deep Active Contours,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+e2888084b375163f7c956adff102fdbc9fe7fb40,Hierarchical Label Inference for Video Classification,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+e2888084b375163f7c956adff102fdbc9fe7fb40,Hierarchical Label Inference for Video Classification,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+e2888084b375163f7c956adff102fdbc9fe7fb40,Hierarchical Label Inference for Video Classification,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+e26b87ff2e1553f4ee0d8b657295187abc6f312c,Whodunnit? Crime Drama as a Case for Natural Language Understanding,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+e2fb33d0ba0fe5e0c33b576e090b10fa4741d12d,Anonymizing k Facial Attributes via Adversarial Perturbations,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+e28915617dcad57c84f5feb2b93763548a44defd,Action-Affect Classification and Morphing using Multi-Task Representation Learning,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
+e2d1e72fdb7e0b7a3ebb9ddc4cc161566ab74de2,Person Search via a Mask-Guided Two-Stream CNN Model,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+e2d1e72fdb7e0b7a3ebb9ddc4cc161566ab74de2,Person Search via a Mask-Guided Two-Stream CNN Model,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+e20ab84ac7fa0a5d36d4cf2266b7065c60e1c804,Stacked U-Nets for Ground Material Segmentation in Remote Sensing Imagery,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
e293a31260cf20996d12d14b8f29a9d4d99c4642,LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+e2b4a1747e66f72baae9929f908ab064a4263f9e,WebCaricature: a benchmark for caricature face recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+e2b4a1747e66f72baae9929f908ab064a4263f9e,WebCaricature: a benchmark for caricature face recognition,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+e24ab3b2a7b5938a48ea3c8c4bc29be2b02299fb,A Face Recognition System for Automated Door Opening with parallel Health Status Validation Using the Kinect v2,Keio University,Keio University,"綱島市民の森, けつわり坂, 港北区, 横浜市, 神奈川県, 関東地方, 223-0053, 日本",35.54169690,139.63471840,edu,
+e2113e6c136c87802a35e75122db7e4e57c9774d,Grounding Referring Expressions in Images by Variational Context,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+e24a5e843d2ea999393b9f278f4b5c80f8a651d1,Learning to Learn with Compound HD Models,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+e22022de2db3432b3d77a49180b58d29058750d2,3D GLOH features for human action recognition,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+e22022de2db3432b3d77a49180b58d29058750d2,3D GLOH features for human action recognition,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+e22022de2db3432b3d77a49180b58d29058750d2,3D GLOH features for human action recognition,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+e2272f50ffa33b8e41509e4b795ad5a4eb27bb46,Region-based semantic segmentation with end-to-end training,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+e20abf7143f4a224824c3db7213049dee2573b4e,An investigation of the relationship between activation of a social cognitive neural network and social functioning.,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+e2b093c6ebe4352ba9a1b281c621b798aae8d71c,NNEval: Neural Network Based Evaluation Metric for Image Captioning,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+e225a7cbfce4f7c9c29507c04190e6d6b6b46f7f,Label Denoising Adversarial Network ( LDAN ) for Inverse Lighting of Faces,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
e20e2db743e8db1ff61279f4fda32bf8cf381f8e,Deep Cross Polarimetric Thermal-to-Visible Face Recognition,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+e205faa8febcb7e33c482b00f84939b153575292,An information theoretic formulation of the Dictionary Learning and Sparse Coding Problems on Statistical Manifolds,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+e217382ceed42605eb2a9b570c55f9622635e111,Efficient Clothing Retrieval with Semantic-Preserving Visual Phrases,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+e217382ceed42605eb2a9b570c55f9622635e111,Efficient Clothing Retrieval with Semantic-Preserving Visual Phrases,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+f46097e264c7b0e47c4b1d1b476e5e6c1db9cc30,Bird Nest Images Classification Based on Canny Edge Detection and Local Binary Pattern,University of Delaware,University of Delaware,"University of Delaware, South College Avenue, Newark, New Castle County, Delaware, 19713, USA",39.68103280,-75.75401840,edu,
f437b3884a9e5fab66740ca2a6f1f3a5724385ea,Human identification technical challenges,DARPA,DARPA,"3701 Fairfax Dr, Arlington, VA 22203, USA",38.88334130,-77.10459770,mil,"3701 N. Fairfax Dr., Arlington, VA 22203"
+f42d3225afd9e463ddb7a355f64b54af8bd14227,Stacked U-Nets: A No-Frills Approach to Natural Image Segmentation,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
f43eeb578e0ca48abfd43397bbd15825f94302e4,Optical computer recognition of facial expressions associated with stress induced by performance demands.,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+f4b15fdcaaa3ad604b82df05f5d7f59dbcfe861d,An Event Reconstruction Tool for Conflict Monitoring Using Social Media,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
f4f9697f2519f1fe725ee7e3788119ed217dca34,Selfie-Presentation in Everyday Life: A Large-Scale Characterization of Selfie Contexts on Instagram,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+f4421adced24d729d5ed22559308c2b4719b44c2,End-to-end 3 D face reconstruction with deep neural networks,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
f4210309f29d4bbfea9642ecadfb6cf9581ccec7,An Agreement and Sparseness-based Learning Instance Selection and its Application to Subjective Speech Phenomena,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
f4210309f29d4bbfea9642ecadfb6cf9581ccec7,An Agreement and Sparseness-based Learning Instance Selection and its Application to Subjective Speech Phenomena,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+f4dc1ca2051dc191751eb92a753f028228134e62,In Defense of Single-column Networks for Crowd Counting,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+f4dc1ca2051dc191751eb92a753f028228134e62,In Defense of Single-column Networks for Crowd Counting,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f4dc1ca2051dc191751eb92a753f028228134e62,In Defense of Single-column Networks for Crowd Counting,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f4dc1ca2051dc191751eb92a753f028228134e62,In Defense of Single-column Networks for Crowd Counting,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+f4dc1ca2051dc191751eb92a753f028228134e62,In Defense of Single-column Networks for Crowd Counting,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f499e84b489b0b4afe86e303803871700e561063,"A Framework for Fashion Data Gathering, Hierarchical-Annotation and Analysis for Social Media and Online Shop TOOLKIT FOR DETAILED STYLE ANNOTATIONS FOR ENHANCED FASHION RECOMMENDATION","KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+f4065d13bcad78b563108075f650c29a2f3f1917,Cost Effective Conceptual Design for Semantic Annotation,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+f4065d13bcad78b563108075f650c29a2f3f1917,Cost Effective Conceptual Design for Semantic Annotation,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+f4557028562003c13eeca41b175dd4f4a03659bd,Part-based Deformable Object Detection with a Single Silhouette Sketch,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+f4557028562003c13eeca41b175dd4f4a03659bd,Part-based Deformable Object Detection with a Single Silhouette Sketch,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+f408ee71b9db38ec1b1b785057d50d6e0d9b30ba,LiDAR-Video Driving Dataset : Learning Driving Policies Effectively,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
f4d30896c5f808a622824a2d740b3130be50258e,"DS++: A flexible, scalable and provably tight relaxation for matching problems",Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
f4aed1314b2d38fd8f1b9d2bc154295bbd45f523,Subspace Clustering using Ensembles of $K$-Subspaces,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+f4c029044afa6cb3b08d5e47701d532b3aed9a40,A Clustering Based Approach for Realistic and Efficient Data-Driven Crowd Simulation,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+f442e57e13d1da68723d68cb68d7c78e1788cc7f,Running head: AUTOMATIC MENTAL STATE DETECTION 1 Automated Mental State Detection for Mental Healthcare,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
f3ca2c43e8773b7062a8606286529c5bc9b3ce25,Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
f3ca2c43e8773b7062a8606286529c5bc9b3ce25,Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
f3ca2c43e8773b7062a8606286529c5bc9b3ce25,Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
f3ca2c43e8773b7062a8606286529c5bc9b3ce25,Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+f3a57b32a53db39b188879c4ce2c22d6929f43e0,SOT for MOT,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+f3a57b32a53db39b188879c4ce2c22d6929f43e0,SOT for MOT,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f3a57b32a53db39b188879c4ce2c22d6929f43e0,SOT for MOT,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f3a57b32a53db39b188879c4ce2c22d6929f43e0,SOT for MOT,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f3a57b32a53db39b188879c4ce2c22d6929f43e0,SOT for MOT,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f39b94e1ab8beeaf05f28c7bbc08664b7c37ed8c,Cross-domain attribute representation based on convolutional neural network,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+f39b94e1ab8beeaf05f28c7bbc08664b7c37ed8c,Cross-domain attribute representation based on convolutional neural network,Soochow University,Soochow University,"苏州大学（天赐庄校区）, 清荫路, 钟楼社区, 双塔街道, 姑苏区, 苏州市, 江苏省, 215001, 中国",31.30709510,120.63573987,edu,
+f33ef5b2707078528f23e067565f992f4b03f4a7,Actor and Observer: Joint Modeling of First and Third-Person Videos,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+f3a9baff7b059c528a7f72dd458db569892ee29c,"Spectral Matching, Learning, and Inference using Pairwise Interactions",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+f3a9baff7b059c528a7f72dd458db569892ee29c,"Spectral Matching, Learning, and Inference using Pairwise Interactions",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+f3a9baff7b059c528a7f72dd458db569892ee29c,"Spectral Matching, Learning, and Inference using Pairwise Interactions",University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+f3fc96377dc3456948fd3431ce940258926ce04e,Advancing Bag-of-Visual-Words Representations for Lesion Classification in Retinal Images,Khalifa University,Khalifa University,"Khalifa University, شارع طَوِي مُوَيلِح, قصر الشاطئ, حدبة الزَّعْفرانة, أبوظبي, أبو ظبي, 31757, الإمارات العربية المتحدة",24.44690250,54.39425630,edu,
+f35acbb0b2870e5735561196d246463aec8ae7aa,Representations and Techniques for 3D Object Recognition and Scene Interpretation,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+f35acbb0b2870e5735561196d246463aec8ae7aa,Representations and Techniques for 3D Object Recognition and Scene Interpretation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+f38ad869023c43b59431a3bb55f2fe8fb6ff0f05,A systematic review and meta-analysis of the fMRI investigation of autism spectrum disorders.,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+f38ad869023c43b59431a3bb55f2fe8fb6ff0f05,A systematic review and meta-analysis of the fMRI investigation of autism spectrum disorders.,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+f38ad869023c43b59431a3bb55f2fe8fb6ff0f05,A systematic review and meta-analysis of the fMRI investigation of autism spectrum disorders.,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+f3880d1067915bbbaa0c47a736f46f488185250e,Illumination Normalization for Outdoor Face Recognition by Using Ayofa-filters,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+f3880d1067915bbbaa0c47a736f46f488185250e,Illumination Normalization for Outdoor Face Recognition by Using Ayofa-filters,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+f3880d1067915bbbaa0c47a736f46f488185250e,Illumination Normalization for Outdoor Face Recognition by Using Ayofa-filters,Nagoya University,Nagoya University,"SuperDARN (Hokkaido West), 太辛第1支線林道, 陸別町, 足寄郡, 十勝総合振興局, 北海道, 北海道地方, 日本",43.53750985,143.60768225,edu,
+f3880d1067915bbbaa0c47a736f46f488185250e,Illumination Normalization for Outdoor Face Recognition by Using Ayofa-filters,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
f3015be0f9dbc1a55b6f3dc388d97bb566ff94fe,A Study on the Effective Approach to Illumination-Invariant Face Recognition Based on a Single Image,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+f302185b1416d8b47620c67b3942a8675bbb4679,Domain Adapted Word Embeddings for Improved Sentiment Classification,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
f3a59d85b7458394e3c043d8277aa1ffe3cdac91,Query-Free Attacks on Industry-Grade Face Recognition Systems under Resource Constraints,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+f3ec43a7b22f6e5414fec473acda8ffd843e7baf,A Coupled Evolutionary Network for Age Estimation,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+f39fc7c420277616eea29754d0d367297c6f02c1,Feature Extraction Based on Co-occurrence of Adjacent Local Binary Patterns,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
f3f77b803b375f0c63971b59d0906cb700ea24ed,Feature Extraction for Facial Expression Recognition based on Hybrid Face Regions,RMIT University,RMIT University,"RMIT University, 124, La Trobe Street, Melbourne City, City of Melbourne, Victoria, 3000, Australia",-37.80874650,144.96388750,edu,
+f39d3ed10131f986be5fb8a10b77d44bc9feada8,Boosting with Side Information,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+f39d3ed10131f986be5fb8a10b77d44bc9feada8,Boosting with Side Information,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
f3df296de36b7c114451865778e211350d153727,Spatio-Temporal Facial Expression Recognition Using Convolutional Neural Networks and Conditional Random Fields,University of Denver,University of Denver,"University of Denver, Driscoll Bridge, Denver, Denver County, Colorado, 80208, USA",39.67665410,-104.96220300,edu,
+f3906c390e378ece7f785fb553e0b89c2cbfeeb2,Automatic 3D Facial Region Retrieval from Multi-pose Facial Datasets,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
f3fed71cc4fc49b02067b71c2df80e83084b2a82,Learning Sparse Latent Representations with the Deep Copula Information Bottleneck,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+f312fce73aabd97bf4fc02fe2829f6959e251b1e,Runtime Support for Human-in-the-Loop Feature Engineering System,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+f312fce73aabd97bf4fc02fe2829f6959e251b1e,Runtime Support for Human-in-the-Loop Feature Engineering System,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+f312fce73aabd97bf4fc02fe2829f6959e251b1e,Runtime Support for Human-in-the-Loop Feature Engineering System,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+f367feef8f486966916bd0769de8c7b5a59250b1,Direct Shot Correspondence Matching,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+f367feef8f486966916bd0769de8c7b5a59250b1,Direct Shot Correspondence Matching,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+f3e2fd2388c33b09df32c29f381e71b48dc227ab,Learning Hybrid Part Filters for Scene Recognition,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
f35a493afa78a671b9d2392c69642dcc3dd2cdc2,Automatic Attribute Discovery with Neural Activations,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
f35a493afa78a671b9d2392c69642dcc3dd2cdc2,Automatic Attribute Discovery with Neural Activations,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+f397b8c835425e4b18cc7d9088b7f810c6cf2563,Yimo Guo IMAGE AND VIDEO ANALYSIS BY LOCAL DESCRIPTORS AND DEFORMABLE IMAGE REGISTRATION,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+f328137ba1924c8b451be32c7bd8d1d9a5c392d6,Relative Attribute Learning with Deep Attentive Cross-image Representation,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
eb100638ed73b82e1cce8475bb8e180cb22a09a2,Temporal Action Detection with Structured Segment Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+eb0cf5727275f89323e2cbb4c0f0515b8ece75f8,A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera,Universität Hamburg,Universität Hamburg,"Informatikum, 30, Vogt-Kölln-Straße, Stellingen, Eimsbüttel, Hamburg, 22527, Deutschland",53.59948200,9.93353436,edu,
+ebb527dad52f28610f9153952c10a95d8f01f5f9,How Can Selection of Biologically Inspired Features Improve the Performance of a Robust Object Recognition Model?,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
eb6ee56e085ebf473da990d032a4249437a3e462,Age/gender classification with whole-component convolutional neural networks (WC-CNN),University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
eb8519cec0d7a781923f68fdca0891713cb81163,Temporal Non-volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
eb8519cec0d7a781923f68fdca0891713cb81163,Temporal Non-volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
ebb1c29145d31c4afa3c9be7f023155832776cd3,CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
ebb1c29145d31c4afa3c9be7f023155832776cd3,CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
ebb1c29145d31c4afa3c9be7f023155832776cd3,CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+eb22aecb7b59ab01acdf498b33f5ba9ef1b64f64,A Multiple Motion Model Tracker Handling Occlusion and Rapid Motion Variation,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+eb43002e771de05db5e3e7e8eb6fcc75de0e30c4,Dataset Localization / Segmentation By dCNN Top Garments Bottom Garments Feature Extraction Feature Extraction Top Bottom A Table of Joint Distribution Inventory Dataset Localization / Segmentation By dCNN Feature Extraction Query garment Localization / Segmentation By dCNN Feature Extraction Recomm,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+eb43002e771de05db5e3e7e8eb6fcc75de0e30c4,Dataset Localization / Segmentation By dCNN Top Garments Bottom Garments Feature Extraction Feature Extraction Top Bottom A Table of Joint Distribution Inventory Dataset Localization / Segmentation By dCNN Feature Extraction Query garment Localization / Segmentation By dCNN Feature Extraction Recomm,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+ebb5eedb6ce41317971885ff33da17ae2c9e8f7a,Disguised Face Identification (DFI) with Facial KeyPoints Using Spatial Fusion Convolutional Network,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+ebb5eedb6ce41317971885ff33da17ae2c9e8f7a,Disguised Face Identification (DFI) with Facial KeyPoints Using Spatial Fusion Convolutional Network,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+eb2d1d406405537773e70f7e949df656ee8779aa,ShapeLearner: Towards Shape-Based Visual Knowledge Harvesting,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+ebca525383c4c451e97e801f2e2532d65e88dfeb,A Nonlinear Orthogonal Non-Negative Matrix Factorization Approach to Subspace Clustering,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
eb70c38a350d13ea6b54dc9ebae0b64171d813c9,"On Graph-Structured Discrete Labelling Problems in Computer Vision : Learning , Inference and Applications",Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
eb70c38a350d13ea6b54dc9ebae0b64171d813c9,"On Graph-Structured Discrete Labelling Problems in Computer Vision : Learning , Inference and Applications",Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
eb70c38a350d13ea6b54dc9ebae0b64171d813c9,"On Graph-Structured Discrete Labelling Problems in Computer Vision : Learning , Inference and Applications",Banaras Hindu University,Banaras Hindu University,"काशी हिन्दू विश्वविद्यालय, Semi Circle Road 2, ワーラーナシー, Jodhpur Colony, Vārānasi, Varanasi, Uttar Pradesh, 221005, India",25.26628870,82.99279690,edu,
eb70c38a350d13ea6b54dc9ebae0b64171d813c9,"On Graph-Structured Discrete Labelling Problems in Computer Vision : Learning , Inference and Applications",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+eb9c20e96f22b9c890f7978878c5479d9e64bb47,Learning descriptive models of objects and activities from egocentric video,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+eb1208a7f535de6c6180e4dbeb6eef2a27500c52,"To be or Not to be Threatening, but What was the Question? Biased Face Evaluation in Social Anxiety and Depression Depends on How You Frame the Query",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
eb027969f9310e0ae941e2adee2d42cdf07d938c,VGGFace2: A Dataset for Recognising Faces across Pose and Age,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+ebe8408052d9bf05dc2007d01559dda6129840eb,Where to Focus: Deep Attention-based Spatially Recurrent Bilinear Networks for Fine-Grained Visual Recognition,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+ebe8408052d9bf05dc2007d01559dda6129840eb,Where to Focus: Deep Attention-based Spatially Recurrent Bilinear Networks for Fine-Grained Visual Recognition,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+ebd28f04c2ab1e61430d309ecbf7c832173d65a5,Feedback based Neural Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+ebd28f04c2ab1e61430d309ecbf7c832173d65a5,Feedback based Neural Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+ebd28f04c2ab1e61430d309ecbf7c832173d65a5,Feedback based Neural Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
eb7b387a3a006609b89ca5ed0e6b3a1d5ecb5e5a,Facial Expression Recognition using Neural Network,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+eba3fd6a446cb043c0347c9b4ce40567f1ce9110,Multi-task Relative Attributes Prediction by Incorporating Local Context and Global Style Information Features,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+eba0510f6d34320857b0554627b5f2925553f820,MouseFree Vision-Based Human-Computer Interaction through Real-Time Hand Tracking and Gesture Recognition,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+eba0510f6d34320857b0554627b5f2925553f820,MouseFree Vision-Based Human-Computer Interaction through Real-Time Hand Tracking and Gesture Recognition,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+eba0510f6d34320857b0554627b5f2925553f820,MouseFree Vision-Based Human-Computer Interaction through Real-Time Hand Tracking and Gesture Recognition,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+ebad62ebe00fe0f0c19ce04c3f7250506137fc71,Evaluating Auto-adaptation Methods for Fine-Grained Adaptable Processors,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+eb91eb5912de3d15f052a94cd0a188f553df90e7,On Detecting Domestic Abuse via Faces,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+eb4d7688cd03f3863a175149f5fa293140f9df30,On classification of distorted images with deep convolutional neural networks,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
+ebe44c125f6d5c893df73d20b602e479a38e5b23,Algorithmic Identification of Looted Archaeological Sites from Space,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
c71f36c9376d444075de15b1102b4974481be84d,"3D morphable models : data pre-processing, statistical analysis and fitting",University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+c7fc1a9dd3c0b2653b0c9ff668cafaff7670da92,An Image-Based Bayesian Framework for Face Detection,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
c7c53d75f6e963b403057d8ba5952e4974a779ad,Aging effects in automated face recognition,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
c7c53d75f6e963b403057d8ba5952e4974a779ad,Aging effects in automated face recognition,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
c79cf7f61441195404472102114bcf079a72138a,Pose-Invariant 2 D Face Recognition by Matching Using Graphical Models,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
c79cf7f61441195404472102114bcf079a72138a,Pose-Invariant 2 D Face Recognition by Matching Using Graphical Models,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
c73dd452c20460f40becb1fd8146239c88347d87,Manifold Constrained Low-Rank Decomposition,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+c79eb3b4d8324eb824493e53bfcb4d3980398523,Tracking people within groups with RGB-D data,University of Padova,University of Padova,"Via Giovanni Gradenigo, 6, 35131 Padova PD, Italy",45.40811720,11.89437860,edu,"University of Padova, Via Gradenigo, 6 - 35131- Padova, Italy"
+c79178a47403f317f837e4a8aa9fd03bfed1dfc7,Multiclass object detection by combining local appearances and context,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+c79178a47403f317f837e4a8aa9fd03bfed1dfc7,Multiclass object detection by combining local appearances and context,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+c72ac3dec0d0b2d5ca4945b07bd6b72c365bdc13,Shorter spontaneous fixation durations in infants with later emerging autism,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+c733e4a14b51623120da9b4571b4409bc99ab0cd,Mainstream: Dynamic Stem-Sharing for Multi-Tenant Video Processing,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
c72e6992f44ce75a40f44be4365dc4f264735cfb,Story Understanding in Video Advertisements,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
c74aba9a096379b3dbe1ff95e7af5db45c0fd680,Neuro-Fuzzy Analysis of Facial Action Units and Expressions,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+c7756864268459069a59c2276cf482377d5f997a,TorontoCity: Seeing the World with a Million Eyes,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+c784d4918ad33f4dd2991155ea583b4789ba3c11,Bimodal Vein Recognition Based on Task-Specific Transfer Learning,China University of Mining and Technology,China University of Mining and Technology,"China University of Mining and Technology, 1号, 大学路, 泉山区 (Quanshan), 徐州市 / Xuzhou, 江苏省, 221116, 中国",34.21525380,117.13985410,edu,
+c71db5d3546e22227662ee0f0ce586495ef18899,SALICON: Saliency in Context,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+c7dd846c0abc896e5fd0940ac07927553cc55734,Neurofunctional Underpinnings of Audiovisual Emotion Processing in Teens with Autism Spectrum Disorders,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
+c7dd846c0abc896e5fd0940ac07927553cc55734,Neurofunctional Underpinnings of Audiovisual Emotion Processing in Teens with Autism Spectrum Disorders,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
+c7dd846c0abc896e5fd0940ac07927553cc55734,Neurofunctional Underpinnings of Audiovisual Emotion Processing in Teens with Autism Spectrum Disorders,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+c7dd846c0abc896e5fd0940ac07927553cc55734,Neurofunctional Underpinnings of Audiovisual Emotion Processing in Teens with Autism Spectrum Disorders,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
+c7c61d35025943031a0cefeece9a9215fd4019e5,Egocentric Visual Event Classification with Location-Based Priors,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+c75ba6ef724c0c3a9c9510a70da4cc8729b59a35,FaceWarehouse: A 3D Facial Expression Database for Visual Computing,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+c75ba6ef724c0c3a9c9510a70da4cc8729b59a35,FaceWarehouse: A 3D Facial Expression Database for Visual Computing,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+c753521ba6fb06c12369d6fff814bb704c682ef5,Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-Identification,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+c76b611a986a2e09df22603d93b2d9125aaff369,Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
c7c5f0fe1fcaf3787c7f78f7dc62f3497dcfdf3c,The Impact of Product Photo on Online Consumer Purchase Intention: an Image-Processing Enabled Empirical Study,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
c7c5f0fe1fcaf3787c7f78f7dc62f3497dcfdf3c,The Impact of Product Photo on Online Consumer Purchase Intention: an Image-Processing Enabled Empirical Study,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
c7c5f0fe1fcaf3787c7f78f7dc62f3497dcfdf3c,The Impact of Product Photo on Online Consumer Purchase Intention: an Image-Processing Enabled Empirical Study,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+c7752341b28a0ff96e8b63986afc669fada6cd50,Thinking Outside the Box: Spatial Anticipation of Semantic Categories,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
c71217b2b111a51a31cf1107c71d250348d1ff68,One Network to Solve Them All — Solving Linear Inverse Problems Using Deep Projection Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+c72b063e23b8b45b57a42ebc2f9714297c539a6f,TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-rays,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+c793a38c3d16b093c12ba8a9d12dfa88159ecd38,Neurons in the fusiform gyrus are fewer and smaller in autism.,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
+c793a38c3d16b093c12ba8a9d12dfa88159ecd38,Neurons in the fusiform gyrus are fewer and smaller in autism.,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+c793a38c3d16b093c12ba8a9d12dfa88159ecd38,Neurons in the fusiform gyrus are fewer and smaller in autism.,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
c76f64e87f88475069f7707616ad9df1719a6099,T-RECS: Training for Rate-Invariant Embeddings by Controlling Speed for Action Recognition,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+c76eee7a6656664bc37890f3754ae202255ffff3,Matching 3D Faces with Partial Data,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
c7f0c0636d27a1d45b8fcef37e545b902195d937,Towards Around-Device Interaction using Corneal Imaging,Coburg University,Coburg University,"Hochschule für angewandte Wissenschaften Coburg, 2, Friedrich-Streib-Straße, Callenberg, Coburg, Oberfranken, Bayern, 96450, Deutschland",50.26506145,10.95196483,edu,
c7f0c0636d27a1d45b8fcef37e545b902195d937,Towards Around-Device Interaction using Corneal Imaging,Coburg University,Coburg University,"Hochschule für angewandte Wissenschaften Coburg, 2, Friedrich-Streib-Straße, Callenberg, Coburg, Oberfranken, Bayern, 96450, Deutschland",50.26506145,10.95196483,edu,
+c71b0ed402437470f229b3fdabb88ad044c092ea,Dynamic Conditional Networks for Few-Shot Learning,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+c71b0ed402437470f229b3fdabb88ad044c092ea,Dynamic Conditional Networks for Few-Shot Learning,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
c74b1643a108939c6ba42ae4de55cb05b2191be5,Non-negative Matrix Factorization for Face Illumination Analysis,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
c74b1643a108939c6ba42ae4de55cb05b2191be5,Non-negative Matrix Factorization for Face Illumination Analysis,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
c74b1643a108939c6ba42ae4de55cb05b2191be5,Non-negative Matrix Factorization for Face Illumination Analysis,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
c75e6ce54caf17b2780b4b53f8d29086b391e839,"ExpNet: Landmark-Free, Deep, 3D Facial Expressions",Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
+c747c45c2fb3d678954bf1a16a3d9cc4dd4b8f01,Allelic Variation in the Oxytocin Receptor Gene and Early- Emerging Social Behaviors in Boys and Girls,University of Tampere,University of Tampere,"Tampereen yliopisto, 4, Kalevantie, Ratinanranta, Tulli, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33100, Suomi",61.49412325,23.77920678,edu,
c0723e0e154a33faa6ff959d084aebf07770ffaf,Interpolation Between Eigenspaces Using Rotation in Multiple Dimensions,Nagoya University,Nagoya University,"SuperDARN (Hokkaido West), 太辛第1支線林道, 陸別町, 足寄郡, 十勝総合振興局, 北海道, 北海道地方, 日本",43.53750985,143.60768225,edu,
+c02c914de25034ecd2c3287c2e731ab1130e7bee,Multi-Scale Structure-Aware Network for Human Pose Estimation,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+c0387e788a52f10bf35d4d50659cfa515d89fbec,MARS: A Video Benchmark for Large-Scale Person Re-Identification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+c0825a62bbf6a906ec812d0f668478f001c24279,Recognition at a long distance: Very low resolution face recognition and hallucination,"Academia Sinica, Taiwan","Research Center for Institute of Information Science, Academia Sinica, Taiwan","115, Taiwan, Taipei City, Nangang District, 研究院路二段128號",25.04117270,121.61465180,edu,
+c02cc6af3cc93e86e86fb66412212babda8fb858,Interocularly merged face percepts eliminate binocular rivalry,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+c0ef854f4119a74b37211aa4cc36b8c1addd9057,Training object class detectors with click supervision Dim,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
c03e01717b2d93f04cce9b5fd2dcfd1143bcc180,Locality-Constrained Active Appearance Model,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
c03e01717b2d93f04cce9b5fd2dcfd1143bcc180,Locality-Constrained Active Appearance Model,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+c031d1792f088c4feca14ed8ee05423a7f77fe8d,Cardinal sparse partial least square feature selection and its application in face recognition,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+c048513689fbba0a12a1ab9cb08ab3a533918519,Model SelectionWithin a Bayesian Approach to Extraction of Walker Motion,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+c0c80aeccb1628926738ea8f09d238061a8daa29,GBoost: A Generative Framework for Boosting with Applications to Real-Time Eye Coding ?,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+c06ca26b33ab2e9ce118ca02018be5834e8164a6,Robust Ear Recognition Using Gradient Ordinal Relationship Pattern,Indian Institute of Technology Kanpur,Indian Institute of Technology Kanpur,"Indian Institute of Technology Kanpur, 4th Avenue, Panki, Kanpur, Kanpur Nagar, Uttar Pradesh, 208016, India",26.51318800,80.23651945,edu,
+c074dcc5000320ebf13e7a974befced1ab70a08f,Attentional Pooling for Action Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+c05f9e4979cb33090db984226ff3cff6e2dc1950,Counting in Dense Crowds using Deep Features,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
c035c193eed5d72c7f187f0bc880a17d217dada0,"Local Gradient Gabor Pattern (LGGP) with Applications in Face Recognition, Cross-spectral Matching and Soft Biometrics",West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
c035c193eed5d72c7f187f0bc880a17d217dada0,"Local Gradient Gabor Pattern (LGGP) with Applications in Face Recognition, Cross-spectral Matching and Soft Biometrics",Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+c0262e24324a6a4e6af5bd99fc79e2eb802519b3,Learning Scene-specific Object Detectors Based on a Generative-Discriminative Model with Minimal Supervision,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+c0262e24324a6a4e6af5bd99fc79e2eb802519b3,Learning Scene-specific Object Detectors Based on a Generative-Discriminative Model with Minimal Supervision,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+c0ead9bada2fb7cdebf7dadbc8548d08387966ae,Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+c0ead9bada2fb7cdebf7dadbc8548d08387966ae,Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+c0ead9bada2fb7cdebf7dadbc8548d08387966ae,Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+c0ead9bada2fb7cdebf7dadbc8548d08387966ae,Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+c0006a2268d299644e9f1b455601bcbe89ddc2b5,Semantic Video Segmentation by Gated Recurrent Flow Propagation,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
c0cdaeccff78f49f4604a6d263dc6eb1bb8707d5,MLP Neural Network Based Approach for Facial Expression Analysis,Kent State University,Kent State University,"Kent State University, Lester A. Lefton Esplanade, Whitehall Terrace, Kent, Portage County, Ohio, 44242-0001, USA",41.14435250,-81.33982833,edu,
c00f402b9cfc3f8dd2c74d6b3552acbd1f358301,Learning deep representation from coarse to fine for face alignment,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
c089c7d8d1413b54f59fc410d88e215902e51638,TVParser: An automatic TV video parsing method,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
c0ee89dc2dad76147780f96294de9e421348c1f4,Efficiently detecting outlying behavior in video-game players,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
c0ee89dc2dad76147780f96294de9e421348c1f4,Efficiently detecting outlying behavior in video-game players,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
c0ca6b992cbe46ea3003f4e9b48f4ef57e5fb774,A Two-Layer Representation For Large-Scale Action Recognition,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+c01876292b5d1ce6e746fd2e2053453847905bb2,DF-Net: Unsupervised Joint Learning of Depth and Flow Using Cross-Task Consistency,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
c00df53bd46f78ae925c5768d46080159d4ef87d,Learning Bag-of-Features Pooling for Deep Convolutional Neural Networks,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+c09cd44a4413de704bd74d825ca435b742b73ded,Illumination Compensation and Enhancement for Face Recognition,Ocean University of China,Ocean University of China,"中国海洋大学, 238, 松岭路 Sōnglǐng Road, 朱家洼, 崂山区 (Laoshan), 青岛市, 山东省, 266100, 中国",36.16161795,120.49355276,edu,
+c0e0b878ec8c56679faccb3c3f5e2ae968182da5,A Multifactor Extension of Linear Discriminant Analysis for Face Recognition under Varying Pose and Illumination,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
c05441dd1bc418fb912a6fafa84c0659a6850bf0,Face recognition under varying illumination based on adaptive homomorphic eight local directional patterns,Utah State University,Utah State University,"Utah State University, Champ Drive, Logan, Cache County, Utah, 84322, USA",41.74115040,-111.81223090,edu,
+ee0d7a1dd5f0821b6f48113a283b9196a38d1c6c,"Show, Attend and Translate: Unsupervised Image Translation with Self-Regularization and Attention",University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+eea931e63c523599ba75524938a0be9ea36e9c2b,A Latent Clothing Attribute Approach for Human Pose Estimation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+eecd9a070ed333077a066bfdcf776c51c2c74406,Deep image representations using caption generators,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
ee6b503ab512a293e3088fdd7a1c893a77902acb,Automatic Name-Face Alignment to Enable Cross-Media News Retrieval,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
ee6b503ab512a293e3088fdd7a1c893a77902acb,Automatic Name-Face Alignment to Enable Cross-Media News Retrieval,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+ee661eb1d6ebfdef0d0b0784529221c951cd1188,"3 D Human Sensing , Action and Emotion Recognition in Robot Assisted Therapy of Children with Autism",Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
eeb6d084f9906c53ec8da8c34583105ab5ab8284,Generation of Facial Expression Map using Supervised and Unsupervised Learning,Akita Prefectural University,Akita Prefectural University,"秋田県立大学, 秋田天王線, 潟上市, 秋田県, 東北地方, 011-0946, 日本",39.80114990,140.04591160,edu,
eeb6d084f9906c53ec8da8c34583105ab5ab8284,Generation of Facial Expression Map using Supervised and Unsupervised Learning,Akita University,Akita University,"秋田大学手形キャンパス, 秋田八郎潟線, 手形字扇田, 広面, 秋田市, 秋田県, 東北地方, 010-0864, 日本",39.72781420,140.13322566,edu,
ee815f60dc4a090fa9fcfba0135f4707af21420d,EAC-Net: A Region-Based Deep Enhancing and Cropping Approach for Facial Action Unit Detection,CUNY City College,CUNY City College,"CUNY City College, 205 East 42nd Street, New York, NY 10017",45.55466080,5.40652550,edu,
eed7920682789a9afd0de4efd726cd9a706940c8,Computers to Help with Conversations : Affective Framework to Enhance Human Nonverbal Skills,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
ee7093e91466b81d13f4d6933bcee48e4ee63a16,Discovering Person Identity via Large-Scale Observations,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
ee7093e91466b81d13f4d6933bcee48e4ee63a16,Discovering Person Identity via Large-Scale Observations,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+ee7034a5ef168f6bcb1b5892177870fc2563a646,Probabilistic State Space Decomposition for Human Motion Capture,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+ee0f87a93fee7a7dc8d13760464dbd6ce1526626,Constrained Semi-Supervised Learning Using Attributes and Comparative Attributes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+ee89b903af1d8f26a8894a3773915c74f038883e,Half-CNN: A General Framework for Whole-Image Regression,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+ee89b903af1d8f26a8894a3773915c74f038883e,Half-CNN: A General Framework for Whole-Image Regression,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+ee5fa8ac1c33fcf9a10a185ae23f0ea0534e770f,Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+ee5fa8ac1c33fcf9a10a185ae23f0ea0534e770f,Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
ee418372b0038bd3b8ae82bd1518d5c01a33a7ec,CSE 255 Winter 2015 Assignment 1: Eye Detection using Histogram of Oriented Gradients and Adaboost Classifier,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
eee06d68497be8bf3a8aba4fde42a13aa090b301,CR-GAN: Learning Complete Representations for Multi-view Generation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
eee06d68497be8bf3a8aba4fde42a13aa090b301,CR-GAN: Learning Complete Representations for Multi-view Generation,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
+eee4cc389ca85d23700cba9627fa11e5ee65d740,Adversarial Open-World Person Re-Identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+eedf9480de99e3373d2321f61ee5b71ea3ebf493,Altered Social Reward and Attention in Anorexia Nervosa,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+eedf9480de99e3373d2321f61ee5b71ea3ebf493,Altered Social Reward and Attention in Anorexia Nervosa,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+eedf9480de99e3373d2321f61ee5b71ea3ebf493,Altered Social Reward and Attention in Anorexia Nervosa,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+eedf9480de99e3373d2321f61ee5b71ea3ebf493,Altered Social Reward and Attention in Anorexia Nervosa,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+ee04c6c9c672fedf39f601a466f64a98541cbe19,Analysis and Improvement of Low Rank Representation for Subspace segmentation,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
eee2d2ac461f46734c8e674ae14ed87bbc8d45c6,Generalized Rank Pooling for Activity Recognition,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
eed93d2e16b55142b3260d268c9e72099c53d5bc,ICFVR 2017: 3rd international competition on finger vein recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+c919a9f61656cdcd3a26076057ee006c48e8f609,High-Value Target Detection,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
+c94fd258a8f1e8f4033a7fe491f1372dcf7d3cd6,TS ^2 2 C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+c94fd258a8f1e8f4033a7fe491f1372dcf7d3cd6,TS ^2 2 C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+c96bd1a584d0e5d86148cfcab0f573825bc3fb5b,Single-Shot Multi-Person 3D Body Pose Estimation From Monocular RGB Input,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+c96bd1a584d0e5d86148cfcab0f573825bc3fb5b,Single-Shot Multi-Person 3D Body Pose Estimation From Monocular RGB Input,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
c94b3a05f6f41d015d524169972ae8fd52871b67,The Fastest Deformable Part Model for Object Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
c9424d64b12a4abe0af201e7b641409e182babab,"Which, When, and How: Hierarchical Clustering with Human-Machine Cooperation",Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+c9c1255057652584603945508b7151206e9e9069,On Sampling and Greedy MAP Inference of Constrained Determinantal Point Processes,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
c97a5f2241cc6cd99ef0c4527ea507a50841f60b,Person Search in Videos with One Portrait Through Visual and Temporal Links,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
c97a5f2241cc6cd99ef0c4527ea507a50841f60b,Person Search in Videos with One Portrait Through Visual and Temporal Links,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
c95cd36779fcbe45e3831ffcd3314e19c85defc5,Face recognition using multi-modal low-rank dictionary learning,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
c9e955cb9709f16faeb0c840f4dae92eb875450a,Proposal of Novel Histogram Features for Face Detection,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+c9b98c98357a154bceb2287c427c5fa9c17b4a07,Virtual CNN Branching: Efficient Feature Ensemble for Person Re-Identification,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+c904fb8be3e9948ccbf4f3c2549f0390a1f4903d,Towards social pattern characterization in egocentric photo-streams,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+c904fb8be3e9948ccbf4f3c2549f0390a1f4903d,Towards social pattern characterization in egocentric photo-streams,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+c9987af05f7df6539c5742072c027dfcf0394354,"DS++: a flexible, scalable and provably tight relaxation for matching problems",Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
c92bb26238f6e30196b0c4a737d8847e61cfb7d4,Beyond Context: Exploring Semantic Similarity for Tiny Face Detection,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
c92bb26238f6e30196b0c4a737d8847e61cfb7d4,Beyond Context: Exploring Semantic Similarity for Tiny Face Detection,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
c92bb26238f6e30196b0c4a737d8847e61cfb7d4,Beyond Context: Exploring Semantic Similarity for Tiny Face Detection,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+c92f26b4a7116ab923e84e351662d1c8a6048b47,Illuminating Pedestrians via Simultaneous Detection and Segmentation,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+c9e4e1bb544a892fe07c99cc9a999f0762237cc3,Natural Language Person Retrieval,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
c9bbd7828437e70cc3e6863b278aa56a7d545150,Unconstrained Fashion Landmark Detection via Hierarchical Recurrent Transformer Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
c9bbd7828437e70cc3e6863b278aa56a7d545150,Unconstrained Fashion Landmark Detection via Hierarchical Recurrent Transformer Networks,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
c9f588d295437009994ddaabb64fd4e4c499b294,Predicting Professions through Probabilistic Model under Social Context,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+c9d9cb2c647c6489814098438a9fbd916a8a1918,ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
c92da368a6a886211dc759fe7b1b777a64d8b682,Face Recognition System based on Face Pose Estimation and Frontal Face Pose Synthesis,National Chiao Tung University,National Chiao Tung University,"NCTU;交大;交通大學;交大光復校區;交通大學光復校區, 1001, 大學路, 光明里, 赤土崎, 東區, 新竹市, 30010, 臺灣",24.78676765,120.99724412,edu,
c92da368a6a886211dc759fe7b1b777a64d8b682,Face Recognition System based on Face Pose Estimation and Frontal Face Pose Synthesis,National Chiao Tung University,National Chiao Tung University,"NCTU;交大;交通大學;交大光復校區;交通大學光復校區, 1001, 大學路, 光明里, 赤土崎, 東區, 新竹市, 30010, 臺灣",24.78676765,120.99724412,edu,
c98983592777952d1751103b4d397d3ace00852d,Face Synthesis from Facial Identity Features,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
c9367ed83156d4d682cefc59301b67f5460013e0,Geometry-Contrastive Generative Adversarial Network for Facial Expression Synthesis,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+c9baea734a14e4302829769ac39fe8c48fbae5a1,Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector,Polytechnique Montreal,Polytechnique Montr´eal,"2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4, Canada",45.50438400,-73.61288290,edu,"Polytechnique Montreal, Montreal, Quebec, Canada"
+c901524f01c7a0db3bb01afa1d5828913c84628a,Image Region Selection and Ensemble for Face Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+fc8d33f351111ed43f56ba6809558d5227d4dcbe,Attention-Aware Compositional Network for Person Re-identification,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+fc8d33f351111ed43f56ba6809558d5227d4dcbe,Attention-Aware Compositional Network for Person Re-identification,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+fc3ee00a751ca4871e3ba40b81120b1bc3a57fc0,How2: A Large-scale Dataset for Multimodal Language Understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+fc3ee00a751ca4871e3ba40b81120b1bc3a57fc0,How2: A Large-scale Dataset for Multimodal Language Understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+fc3ee00a751ca4871e3ba40b81120b1bc3a57fc0,How2: A Large-scale Dataset for Multimodal Language Understanding,University of Copenhagen,University of Copenhagen,"Københavns Universitet, Krystalgade, Kødbyen, Vesterbro, København, Københavns Kommune, Region Hovedstaden, 1165, Danmark",55.68015020,12.57232700,edu,
+fc3ee00a751ca4871e3ba40b81120b1bc3a57fc0,How2: A Large-scale Dataset for Multimodal Language Understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+fcd9df8238605f70a54492fb0c6bdc9f29afda98,3D Vehicle Trajectory Reconstruction in Monocular Video Data Using Environment Structure Constraints,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+fcc82154067dfe778423c2df4ed69f0bec6e1534,Automatic Analysis of Affect and Membership in Group Settings,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+fcc82154067dfe778423c2df4ed69f0bec6e1534,Automatic Analysis of Affect and Membership in Group Settings,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+fc857cebd4150e3fe3aee212f128241b178f0d0a,Amygdala damage impairs eye contact during conversations with real people.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+fc857cebd4150e3fe3aee212f128241b178f0d0a,Amygdala damage impairs eye contact during conversations with real people.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
fc5bdb98ff97581d7c1e5eb2d24d3f10714aa192,Initialization Strategies of Spatio-Temporal Convolutional Neural Networks,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
fc20149dfdff5fdf020647b57e8a09c06e11434b,Local Discriminant Wavelet Packet Coordinates for Face Recognition,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
fc0f5859a111fb17e6dcf6ba63dd7b751721ca61,Design of an Automatic Facial Expression Detector,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
fcbec158e6a4ace3d4311b26195482b8388f0ee9,Face Recognition from Still Images and Videos,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+fcc1ae9761926e9e7dbd23c2cb95ca39b0a71073,Assistive tagging: A survey of multimedia tagging with human-computer joint exploration,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+fcc1ae9761926e9e7dbd23c2cb95ca39b0a71073,Assistive tagging: A survey of multimedia tagging with human-computer joint exploration,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+fc450e42aa2a491ff0afda144718d4f73d4d89f2,An Analysis of Visual Question Answering Algorithms,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+fc027fccb19512a439fc17181c34ee1c3aad51b5,Joint Multi-person Pose Estimation and Semantic Part Segmentation,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
fcf91995dc4d9b0cee84bda5b5b0ce5b757740ac,Asymmetric Discrete Graph Hashing,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+fc950b230a0189cc63b2e2295b2dc761d5b2270c,Health care providers' judgments in chronic pain: the influence of gender and trustworthiness.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+fc950b230a0189cc63b2e2295b2dc761d5b2270c,Health care providers' judgments in chronic pain: the influence of gender and trustworthiness.,University of Northern British Columbia,University of Northern British Columbia,"UNBC, Campus Ring Road, College Heights, Prince George, Regional District of Fraser-Fort George, British Columbia, V2M 5K7, Canada",53.89256620,-122.81471592,edu,
+fc950b230a0189cc63b2e2295b2dc761d5b2270c,Health care providers' judgments in chronic pain: the influence of gender and trustworthiness.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+fc5a100c117cd7291d626f1ec3402bec235f2635,IQA: Visual Question Answering in Interactive Environments,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
fc798314994bf94d1cde8d615ba4d5e61b6268b6,"Face Recognition : face in video , age invariance , and facial marks",Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+fc7cd432db404e7724df7671d6e010109fe0c944,Pedestrian Detection Image Processing with FPGA,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+fc7cd432db404e7724df7671d6e010109fe0c944,Pedestrian Detection Image Processing with FPGA,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
fc23a386c2189f221b25dbd0bb34fcd26ccf60fa,A Discriminative Latent Model of Object Classes and Attributes,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+fc72b2bb34f6a8216767df80ae13e09d1ef0ebda,Combating Human Trafficking with Deep Multimodal Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
fc68c5a3ab80d2d31e6fd4865a7ff2b4ab66ca9f,Evaluation Criteria for Affect-Annotated Databases,Gdansk University of Technology,Gdansk University of Technology,"PG, Romualda Traugutta, Królewska Dolina, Wrzeszcz Górny, Gdańsk, pomorskie, 80-233, RP",54.37086525,18.61716016,edu,
fc2bad3544c7c8dc7cd182f54888baf99ed75e53,Efficient Retrieval for Large Scale Metric Learning,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+fccd0406749aecf76741460de7499689ebf4c676,Integrating Egocentric Videos in Top-View Surveillance Videos: Joint Identification and Temporal Alignment,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+fc18642d17785ef1853749b5323bf87adb329537,Exploring Prior Knowledge for Pedestrian Detection,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+fca9ebaa30d69ccec8bb577c31693c936c869e72,Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+fca9ebaa30d69ccec8bb577c31693c936c869e72,Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+fd9d7efd0ecff49249844a0096e77b2f864fae0d,Language Guided Fashion Image Manipulation with Feature-wise Transformations,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
fdff2da5bdca66e0ab5874ef58ac2205fb088ed7,Continuous Supervised Descent Method for Facial Landmark Localisation,Universitat Oberta de Catalunya,Universitat Oberta de Catalunya,"Universitat Oberta de Catalunya, 156, Rambla del Poblenou, Provençals del Poblenou, Sant Martí, Barcelona, BCN, CAT, 08018, España",41.40657415,2.19453410,edu,
fdff2da5bdca66e0ab5874ef58ac2205fb088ed7,Continuous Supervised Descent Method for Facial Landmark Localisation,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
fdff2da5bdca66e0ab5874ef58ac2205fb088ed7,Continuous Supervised Descent Method for Facial Landmark Localisation,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
fdfd57d4721174eba288e501c0c120ad076cdca8,An Analysis of Action Recognition Datasets for Language and Vision Tasks,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
fd33df02f970055d74fbe69b05d1a7a1b9b2219b,Single Shot Temporal Action Detection,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
fd33df02f970055d74fbe69b05d1a7a1b9b2219b,Single Shot Temporal Action Detection,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+fdc0754852b9c8366341972f1b5b4320b48d64a9,Visual Relationship Detection with Internal and External Linguistic Knowledge Distillation,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
fd15e397629e0241642329fc8ee0b8cd6c6ac807,Semi-Supervised Clustering with Neural Networks,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+fdfceb0fd9561723e604bed586bca9a8450c207e,Graph R-CNN for Scene Graph Generation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
fde41dc4ec6ac6474194b99e05b43dd6a6c4f06f,Multi-Expert Gender Classification on Age Group by Integrating Deep Neural Networks,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+fde5e4538967f325916c1f944242304466edb41d,Urban Vehicle Tracking Using a Combined 3D Model Detector and Classifier,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
fd9feb21b3d1fab470ff82e3f03efce6a0e67a1f,Deep Verification Learning,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+fd67d0efbd94c9d8f9d2f0a972edd7320bc7604f,Real-Time Semantic Clothing Segmentation,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+fde6d64175c459a26037a249e31c34cc0c9e3f7a,Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+fd36e838ffc2f56afdbd87a98f1dc4e05d20ed33,Robot-Centric Activity Recognition 'in the Wild',University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
fd53be2e0a9f33080a9db4b5a5e416e24ae8e198,Apparent Age Estimation Using Ensemble of Deep Learning Models,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
fd71ae9599e8a51d8a61e31e6faaaf4a23a17d81,Action Detection from a Robot-Car Perspective,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+fdabbcb3b49201a942fd36836563ef4ead86bc28,End-to-end learning potentials for structured attribute prediction,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+fd18475cf9165b33de1587a303fc68c5e77ed630,Visual Question Answering Using Various Methods,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
fd10b0c771a2620c0db294cfb82b80d65f73900d,Identifying The Most Informative Features Using A Structurally Interacting Elastic Net,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
fd10b0c771a2620c0db294cfb82b80d65f73900d,Identifying The Most Informative Features Using A Structurally Interacting Elastic Net,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
fd7b6c77b46420c27725757553fcd1fb24ea29a8,MEXSVMs: Mid-level Features for Scalable Action Recognition,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+fd7173634abac857405c78564e366c311a1cf4b3,Sliced-Wasserstein Autoencoder: An Embarrassingly Simple Generative Model,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
fdbacf2ff0fc21e021c830cdcff7d347f2fddd8e,Recognizing Frustration of Drivers From Face Video Recordings and Brain Activation Measurements With Functional Near-Infrared Spectroscopy,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
fd892e912149e3f5ddd82499e16f9ea0f0063fa3,Isyn Initialization Minimizing E ( Φ ) Analysis Synthesis Fitted model Redirection optical ow Warp eyelids Overlay eyeballs Stage 1 : Eye region tracking Stage 2 : Eye gaze redirection Input image Iobs New gaze target g ’ Iobs,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
fd892e912149e3f5ddd82499e16f9ea0f0063fa3,Isyn Initialization Minimizing E ( Φ ) Analysis Synthesis Fitted model Redirection optical ow Warp eyelids Overlay eyeballs Stage 1 : Eye region tracking Stage 2 : Eye gaze redirection Input image Iobs New gaze target g ’ Iobs,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+fdcc1e66697a724bd2d0d2da368de04a7eaf9209,The Devil is in the Decoder,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+fdcc1e66697a724bd2d0d2da368de04a7eaf9209,The Devil is in the Decoder,Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
fdf8e293a7618f560e76bd83e3c40a0788104547,Interspecies Knowledge Transfer for Facial Keypoint Detection,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
fdf8e293a7618f560e76bd83e3c40a0788104547,Interspecies Knowledge Transfer for Facial Keypoint Detection,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
fdf8e293a7618f560e76bd83e3c40a0788104547,Interspecies Knowledge Transfer for Facial Keypoint Detection,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+fd451222670d2f185ae3211b5450fd6951e6af51,Surface Normals with Modular Approach and Weighted Voting Scheme in 3D Facial Expression Classification,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+fd451222670d2f185ae3211b5450fd6951e6af51,Surface Normals with Modular Approach and Weighted Voting Scheme in 3D Facial Expression Classification,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
+f27b8b8f2059248f77258cf8595e9434cf0b0228,Deep Alignment Network: A Convolutional Neural Network for Robust Face Alignment,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
+f2bc0ab0cdf34a1df441ed9678489cb810474c84,The Imaginary Part of Coherency in Autism: Differences in Cortical Functional Connectivity in Preschool Children,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+f2bc0ab0cdf34a1df441ed9678489cb810474c84,The Imaginary Part of Coherency in Autism: Differences in Cortical Functional Connectivity in Preschool Children,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+f2bc0ab0cdf34a1df441ed9678489cb810474c84,The Imaginary Part of Coherency in Autism: Differences in Cortical Functional Connectivity in Preschool Children,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+f22b157fb9f9963b21a82860cb47585556bd79d5,3 D GLOH Features for Human Action Recognition,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+f22b157fb9f9963b21a82860cb47585556bd79d5,3 D GLOH Features for Human Action Recognition,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+f22b157fb9f9963b21a82860cb47585556bd79d5,3 D GLOH Features for Human Action Recognition,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+f254cbfe9710de5e41589f8b7898112b06872ed2,DenseNet : Implementing Efficient ConvNet,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+f2da70f632db70eb42cf5bc5e2428f4bc53909ad,Association of Genetic Variation in the Promoter Region of OXTR with Differences in Social Affective Neural Processing,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+f2da70f632db70eb42cf5bc5e2428f4bc53909ad,Association of Genetic Variation in the Promoter Region of OXTR with Differences in Social Affective Neural Processing,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+f2da70f632db70eb42cf5bc5e2428f4bc53909ad,Association of Genetic Variation in the Promoter Region of OXTR with Differences in Social Affective Neural Processing,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+f2eb8b38e5366dd98350af304c678c42d858017c,Support Neighbor Loss for Person Re-Identification,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+f2eb8b38e5366dd98350af304c678c42d858017c,Support Neighbor Loss for Person Re-Identification,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+f2843da00dc202eb8748b1b690f7b5dd0849af20,Regularized Bayesian Metric Learning for Person Re-identification,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
+f2843da00dc202eb8748b1b690f7b5dd0849af20,Regularized Bayesian Metric Learning for Person Re-identification,Chongqing University,Chongqing University,"重庆工商大学, 19, 翠林路, 重庆市, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400067, 中国",29.50841740,106.57858552,edu,
f22d6d59e413ee255e5e0f2104f1e03be1a6722e,Lattice Long Short-Term Memory for Human Action Recognition,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
f22d6d59e413ee255e5e0f2104f1e03be1a6722e,Lattice Long Short-Term Memory for Human Action Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
f22d6d59e413ee255e5e0f2104f1e03be1a6722e,Lattice Long Short-Term Memory for Human Action Recognition,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
f24e379e942e134d41c4acec444ecf02b9d0d3a9,Analysis of Facial Images across Age Progression by Humans,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
f24e379e942e134d41c4acec444ecf02b9d0d3a9,Analysis of Facial Images across Age Progression by Humans,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
f24e379e942e134d41c4acec444ecf02b9d0d3a9,Analysis of Facial Images across Age Progression by Humans,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+f2b5177d7c4f568295f6c2b9e02078e36d9ed286,Challenges on Large Scale Surveillance Video Analysis,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+f2b5177d7c4f568295f6c2b9e02078e36d9ed286,Challenges on Large Scale Surveillance Video Analysis,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+f2b5177d7c4f568295f6c2b9e02078e36d9ed286,Challenges on Large Scale Surveillance Video Analysis,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+f2b5177d7c4f568295f6c2b9e02078e36d9ed286,Challenges on Large Scale Surveillance Video Analysis,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
f2b13946d42a50fa36a2c6d20d28de2234aba3b4,Adaptive facial expression recognition using inter-modal top-down context,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
f2b13946d42a50fa36a2c6d20d28de2234aba3b4,Adaptive facial expression recognition using inter-modal top-down context,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
f2c30594d917ea915028668bc2a481371a72a14d,Scene Understanding Using Internet Photo Collections,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+f27bdc4f7ec2006425f999055df071d64640836e,Preserved Crossmodal Integration of Emotional Signals in Binge Drinking,Universitat de València,Universitat de València,"Campus dels Tarongers, Plaza de Manuel Broseta i Pont, Ciutat Jardí, Algirós, València, Comarca de València, València / Valencia, Comunitat Valenciana, 46022, España",39.47787665,-0.34257711,edu,
f2ad9b43bac8c2bae9dea694f6a4e44c760e63da,A Study on Illumination Invariant Face Recognition Methods Based on Multiple Eigenspaces,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
f2ad9b43bac8c2bae9dea694f6a4e44c760e63da,A Study on Illumination Invariant Face Recognition Methods Based on Multiple Eigenspaces,North Dakota State University,North Dakota State University,"North Dakota State University, 15th Avenue North, Fargo, Cass County, North Dakota, 58102, USA",46.89715500,-96.81827603,edu,
+f2977284cc3c6653df957d886101cc485de1a9f9,Learning Robust Objective Functions with Application to Face Model Fitting,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
+f2977284cc3c6653df957d886101cc485de1a9f9,Learning Robust Objective Functions with Application to Face Model Fitting,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+f26b3a916aaa50fe6ef554fff744559815ccf954,Serotonin transporter genotype impacts amygdala habituation in youth with autism spectrum disorders.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+f26b3a916aaa50fe6ef554fff744559815ccf954,Serotonin transporter genotype impacts amygdala habituation in youth with autism spectrum disorders.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+f2d07a77711a8d74bbfa48a0436dae18a698b05a,Composite Statistical Learning and Inference for Semantic Segmentation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+f2d07a77711a8d74bbfa48a0436dae18a698b05a,Composite Statistical Learning and Inference for Semantic Segmentation,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
+f2d07a77711a8d74bbfa48a0436dae18a698b05a,Composite Statistical Learning and Inference for Semantic Segmentation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+f2d07a77711a8d74bbfa48a0436dae18a698b05a,Composite Statistical Learning and Inference for Semantic Segmentation,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
f257300b2b4141aab73f93c146bf94846aef5fa1,Eigen Evolution Pooling for Human Action Recognition,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+f249c266321d661ae398c26ddb8c7409f6455ba1,Revisiting Faster R-CNN: A Deeper Look at Region Proposal Network,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+f2e9616577a0eb866e78e6fd68c67809e4fce11c,Digital innovations in L 2 motivation : Harnessing the power of the Ideal L 2 Self,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+f2e9616577a0eb866e78e6fd68c67809e4fce11c,Digital innovations in L 2 motivation : Harnessing the power of the Ideal L 2 Self,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+f2abaa1476fe1f00358f3eaa77dde2f348f58982,Towards an Unequivocal Representation of Actions,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+f2abaa1476fe1f00358f3eaa77dde2f348f58982,Towards an Unequivocal Representation of Actions,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+f2abaa1476fe1f00358f3eaa77dde2f348f58982,Towards an Unequivocal Representation of Actions,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+f22a8c28a6de723e5451ce577a3ef8dfb26f5e2a,A CNN-Based Method of Vehicle Detection from Aerial Images Using Hard Example Mining,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+f2e70cc1603100548df96eef6cd9e28c547801b8,Submodular Optimzation via Reinforcement Learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
f28b7d62208fdaaa658716403106a2b0b527e763,Clustering-driven Deep Embedding with Pairwise Constraints,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
f28b7d62208fdaaa658716403106a2b0b527e763,Clustering-driven Deep Embedding with Pairwise Constraints,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
f28b7d62208fdaaa658716403106a2b0b527e763,Clustering-driven Deep Embedding with Pairwise Constraints,Bar-Ilan University,Bar-Ilan University,"אוניברסיטת בר אילן, כביש גהה, גבעת שמואל, קריית מטלון, גבעת שמואל, מחוז תל אביב, NO, ישראל",32.06932925,34.84334339,edu,
@@ -1326,27 +3657,60 @@ f28b7d62208fdaaa658716403106a2b0b527e763,Clustering-driven Deep Embedding with P f5149fb6b455a73734f1252a96a9ce5caa95ae02,Low-Rank-Sparse Subspace Representation for Robust Regression,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
f5149fb6b455a73734f1252a96a9ce5caa95ae02,Low-Rank-Sparse Subspace Representation for Robust Regression,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
f5149fb6b455a73734f1252a96a9ce5caa95ae02,Low-Rank-Sparse Subspace Representation for Robust Regression,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+f524b1aac4f2a29dab45d7e8726517798dbc9782,Anger superiority effect: The importance of dynamic emotional facial expressions,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+f524b1aac4f2a29dab45d7e8726517798dbc9782,Anger superiority effect: The importance of dynamic emotional facial expressions,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
f58d584c4ac93b4e7620ef6e5a8f20c6f6da295e,Feature Selection Guided Auto-Encoder,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
f5eb0cf9c57716618fab8e24e841f9536057a28a,Rethinking Feature Distribution for Loss Functions in Image Classification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+f55deed4fa5d6d806790610dad9cf7505c1adde8,Goal Driven Detection in Natural Scenes Anonymous,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
f571fe3f753765cf695b75b1bd8bed37524a52d2,Submodular Attribute Selection for Action Recognition in Video,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
f571fe3f753765cf695b75b1bd8bed37524a52d2,Submodular Attribute Selection for Action Recognition in Video,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
f571fe3f753765cf695b75b1bd8bed37524a52d2,Submodular Attribute Selection for Action Recognition in Video,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+f5fba67fa306d8692525c6f9d034ea6e99ad17f7,Vision-Based Intersection Monitoring : Behavior Analysis & Safety Issues,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+f53b8e719dbbdacf7365e4a0e5ecae875d00c3a9,StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+f54d9dbad1f60de83485232707c945f209af867e,Vision as an Interlingua: Learning Multilingual Semantic Embeddings of Untranscribed Speech,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
f5fae7810a33ed67852ad6a3e0144cb278b24b41,Multilingual Gender Classification with Multi-view Deep Learning: Notebook for PAN at CLEF 2018,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
f5af4e9086b0c3aee942cb93ece5820bdc9c9748,Enhancing Person Annotation,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+f565ca9590820c341f1d29084e2d54ae490ffd41,Improving Deep Learning with Generic Data Augmentation,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
+f565ca9590820c341f1d29084e2d54ae490ffd41,Improving Deep Learning with Generic Data Augmentation,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
+f5db05adb6e89986d9ae2da0b81e1ce7c8efd9ba,Making Archetypal Analysis Practical,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+f563ef1a0fd024edb91a889b17b64aca84624be6,Gait-Based Pedestrian Detection for Automated Surveillance,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
f5aee1529b98136194ef80961ba1a6de646645fe,Large-scale learning of discriminative image representations,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
f52efc206432a0cb860155c6d92c7bab962757de,Mugshot Database Acquisition in Video Surveillance Networks Using Incremental Auto-Clustering Quality Measures,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+f568eff0b3d8b9ae527e6b4483e2bc2ce5fd01bb,Multi-context Attention for Human Pose Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+f568eff0b3d8b9ae527e6b4483e2bc2ce5fd01bb,Multi-context Attention for Human Pose Estimation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+f57364601b020dccca729c967b11c4a5da43f3f6,Robust Learning from Normals for 3D Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+f57364601b020dccca729c967b11c4a5da43f3f6,Robust Learning from Normals for 3D Face Recognition,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
f519723238701849f1160d5a9cedebd31017da89,Impact of multi-focused images on recognition of soft biometric traits,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+f5350ef1d45574e33f5b0f1c013a5bb00e1b1c55,Decoding Strategies for Neural Referring Expression Generation,Bielefeld University,Bielefeld University,"Fachhochschule Bielefeld FB Gestaltung, 3, Lampingstraße, Mitte, Bielefeld, Regierungsbezirk Detmold, Nordrhein-Westfalen, 33615, Deutschland",52.02804210,8.51148270,edu,
+f523c55a0a8057c5b08add761353ca79946feb07,Visual Translation Embedding Network for Visual Relation Detection,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
f5eb411217f729ad7ae84bfd4aeb3dedb850206a,Tackling Low Resolution for Better Scene Understanding,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+f58ee95c2c4bdb1432e15d981dcbdb2038a55184,Multi-View Clustering via Deep Matrix Factorization,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+f58ee95c2c4bdb1432e15d981dcbdb2038a55184,Multi-View Clustering via Deep Matrix Factorization,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+f50b6aba0254809ba83c55d2b144508007c23c58,Online learning of robust object detectors during unstable tracking,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+f5af3c28b290dc797c499283e2d0662570f9ed02,GenLR-Net : Deep framework for very low resolution face and object recognition with generalization to unseen categories,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+e3fae8109ff2f91ebfa1bced01452a3998c40ade,Kernel-Based Nonparametric Fisher Classifier for Hyperspectral Remote Sensing Imagery,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
e35b09879a7df814b2be14d9102c4508e4db458b,Optimal Sensor Placement and Enhanced Sparsity for Classification,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
e35b09879a7df814b2be14d9102c4508e4db458b,Optimal Sensor Placement and Enhanced Sparsity for Classification,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
e3b324101157daede3b4d16bdc9c2388e849c7d4,"Robust Real-Time 3 D Face Tracking from RGBD Videos under Extreme Pose , Depth , and Expression Variations",Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+e344cfff1ec2a46e230983157ef34efba5d65340,What makes an Image Iconic? A Fine-Grained Case Study,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+e3faabdc800d2400f072eb5b48e9ad6dc94d7625,Locally Linear Embedded Eigenspace Analysis,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+e37f0b9dadc0bc6dc56ab0fb2c348dcca436bcc0,Preschool negative emotionality predicts activity and connectivity of the fusiform face area and amygdala in later childhood,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+e37f0b9dadc0bc6dc56ab0fb2c348dcca436bcc0,Preschool negative emotionality predicts activity and connectivity of the fusiform face area and amygdala in later childhood,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+e3cc5d86b2032d01c1b40de0da3b7f4458c9c0ee,Globally Consistent Multi-People Tracking using Motion Patterns,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+e3f0e0dbc8e14e3dfb8fe9f9ecf6dab2c4713823,Human Action Recognition Based on Oriented Motion Salient Regions,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+e3f0e0dbc8e14e3dfb8fe9f9ecf6dab2c4713823,Human Action Recognition Based on Oriented Motion Salient Regions,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
e3c011d08d04c934197b2a4804c90be55e21d572,How to Train Triplet Networks with 100K Identities?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
e3c011d08d04c934197b2a4804c90be55e21d572,How to Train Triplet Networks with 100K Identities?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
e3c011d08d04c934197b2a4804c90be55e21d572,How to Train Triplet Networks with 100K Identities?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+e3c433ab9608d7329f944552ba1721e277a42d74,Transferring Rich Feature Hierarchies for Robust Visual Tracking,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+e3c433ab9608d7329f944552ba1721e277a42d74,Transferring Rich Feature Hierarchies for Robust Visual Tracking,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
e3bb83684817c7815f5005561a85c23942b1f46b,Face Verification using Correlation Filters,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
e3bb83684817c7815f5005561a85c23942b1f46b,Face Verification using Correlation Filters,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
e3bb83684817c7815f5005561a85c23942b1f46b,Face Verification using Correlation Filters,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+e3a7fca5f94d85814b600e870b90259eefedaf6e,Composable Unpaired Image to Image Translation,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+e3a7fca5f94d85814b600e870b90259eefedaf6e,Composable Unpaired Image to Image Translation,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
e3e2c106ccbd668fb9fca851498c662add257036,"Appearance, context and co-occurrence ensembles for identity recognition in personal photo collections",University of Colorado at Colorado Springs,University of Colorado at Colorado Springs,"1420 Austin Bluffs Pkwy, Colorado Springs, CO 80918, USA",38.89646790,-104.80505940,edu,
+e3b20cf421812dc96477a2074d0bb1ee83e6c98b,Mapping Urban Tree Species Using Very High Resolution Satellite Imagery: Comparing Pixel-Based and Object-Based Approaches,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
e379e73e11868abb1728c3acdc77e2c51673eb0d,Face Databases,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
e39a66a6d1c5e753f8e6c33cd5d335f9bc9c07fa,Weakly Supervised Learning for Unconstrained Face Processing,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
e39a66a6d1c5e753f8e6c33cd5d335f9bc9c07fa,Weakly Supervised Learning for Unconstrained Face Processing,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
@@ -1355,35 +3719,125 @@ e3a6e9ddbbfc4c5160082338d46808cea839848a,Vision-Based Classification of Developm e3a6e9ddbbfc4c5160082338d46808cea839848a,Vision-Based Classification of Developmental Disorders Using Eye-Movements,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
e3a6e9ddbbfc4c5160082338d46808cea839848a,Vision-Based Classification of Developmental Disorders Using Eye-Movements,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
e3a6e9ddbbfc4c5160082338d46808cea839848a,Vision-Based Classification of Developmental Disorders Using Eye-Movements,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+e34840e4b952444d291619c784cb1f02dfae1e1d,Label Efficient Learning of Transferable Representations across Domains and Tasks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+e34840e4b952444d291619c784cb1f02dfae1e1d,Label Efficient Learning of Transferable Representations across Domains and Tasks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+e35f4238bbc6c4acf4fce9591fa5cebf64fd0c2e,2017 / 2018 Mini-Project Creating Spaces that Understand People Employing Sensor Technologies to Inform the Design and Operation of Human-centred Spaces,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+e35f4238bbc6c4acf4fce9591fa5cebf64fd0c2e,2017 / 2018 Mini-Project Creating Spaces that Understand People Employing Sensor Technologies to Inform the Design and Operation of Human-centred Spaces,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
e3c8e49ffa7beceffca3f7f276c27ae6d29b35db,Families in the Wild (FIW): Large-Scale Kinship Image Database and Benchmarks,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
e3c8e49ffa7beceffca3f7f276c27ae6d29b35db,Families in the Wild (FIW): Large-Scale Kinship Image Database and Benchmarks,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+e33b5e91eb12ee3d7a5d134669994cbde6673df9,Automatic learning of British Sign Language from signed TV broadcasts,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+e37c8e2823cc3429caca4420f19adf329c62d313,Unsupervised Learning for Large-Scale Fiber Detection and Tracking in Microscopic Material Images,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
+e38c7d4f8a4399f402ab6bb364ec662fe897bed1,"PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation",RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+e3e98557ece5247661d849dc2d168f7498209e59,Learning Feature Hierarchies for Object Recognition,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+e3906b524a18cfa329c20cc422de78ed66d05f01,The Facial Appearance of CEOs: Faces Signal Selection but Not Performance,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+e3906b524a18cfa329c20cc422de78ed66d05f01,The Facial Appearance of CEOs: Faces Signal Selection but Not Performance,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
e38371b69be4f341baa95bc854584e99b67c6d3a,DYAN: A Dynamical Atoms-Based Network for Video Prediction,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+e351beaa000aa5875d00fef12eb14e1cb91530bf,Learning Pain from Action Unit Combinations: A Weakly Supervised Approach via Multiple Instance Learning,University of Illinois at Chicago,University of Illinois at Chicago,"University of Illinois at Chicago, West Taylor Street, Greektown, Chicago, Cook County, Illinois, 60607, USA",41.86898915,-87.64856256,edu,
+e351beaa000aa5875d00fef12eb14e1cb91530bf,Learning Pain from Action Unit Combinations: A Weakly Supervised Approach via Multiple Instance Learning,University of Illinois at Chicago,University of Illinois at Chicago,"University of Illinois at Chicago, West Taylor Street, Greektown, Chicago, Cook County, Illinois, 60607, USA",41.86898915,-87.64856256,edu,
+e351beaa000aa5875d00fef12eb14e1cb91530bf,Learning Pain from Action Unit Combinations: A Weakly Supervised Approach via Multiple Instance Learning,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
e328d19027297ac796aae2470e438fe0bd334449,Automatic Micro-expression Recognition from Long Video Using a Single Spotted Apex,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
e328d19027297ac796aae2470e438fe0bd334449,Automatic Micro-expression Recognition from Long Video Using a Single Spotted Apex,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
e328d19027297ac796aae2470e438fe0bd334449,Automatic Micro-expression Recognition from Long Video Using a Single Spotted Apex,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+e3e36ccd836458d51676789fb133b092d42dac16,Deep learning prototype domains for person re-identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
e3a6e5a573619a97bd6662b652ea7d088ec0b352,Compare and Contrast: Learning Prominent Visual Differences,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+e3b3ab8ccb2c2998e4a6f326a4d4ac5f9b99dc7b,Video2Shop: Exact Matching Clothes in Videos to Online Shopping Images,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
+cfc14272b915828a232e29dfc2099f842b144974,Challenging Images For Minds and Machines,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
cfeb26245b57dd10de8f187506d4ed5ce1e2b7dd,CapsNet comparative performance evaluation for image classification,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+cff0e53006c6145d96322e6401e840f405b6ed02,Guest Editorial: Apparent Personality Analysis,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+cf18432bb77bf41377c477b5aaab9abd0f1f306c,ReabsNet: Detecting and Revising Adversarial Examples,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+cf393385803f4a8501d0690250c848c7149338ac,A Neural Multi-sequence Alignment TeCHnique (NeuMATCH),University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+cf94200a476dc15d6da95db809349db4cfd8e92c,Leveraging Motion Priors in Videos for Improving Human Segmentation,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+cf4e94d0337744280da87ff351412bbe702af2b7,An Informed Framework for Training Classifiers from Social Media,Hankuk University of Foreign Studies,Hankuk University of Foreign Studies,"외대앞, 휘경로, 이문동, 이문2동, 동대문구, 서울특별시, 02407, 대한민국",37.59539790,127.06304990,edu,
cffebdf88e406c27b892857d1520cb2d7ccda573,Learning from Large-scale Visual Data for Robots,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+cfb1b2006d24a81bc3f489ca0eb391e7f03788d6,Nonlinear 3D Face Morphable Model,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+cf80b4f78e639504cbf056f29bc1efecf31b1bb2,Joint Flow: Temporal Flow Fields for Multi Person Tracking,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+cf54d15a176ac0d8e30eb0af2fdbb3a9908064f8,Implicit models for automatic pose estimation in static images,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+cf54d15a176ac0d8e30eb0af2fdbb3a9908064f8,Implicit models for automatic pose estimation in static images,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+cf75d967bb47e1085fd120d8373e32db835d515b,Pictorial Human Spaces: How Well Do Humans Perceive a 3D Articulated Pose?,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+cfd700cb28529a9119824389451ddde9c041275e,Sub-Selective Quantization for Large-Scale Image Search,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+cfd700cb28529a9119824389451ddde9c041275e,Sub-Selective Quantization for Large-Scale Image Search,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
cf5c9b521c958b84bb63bea9d5cbb522845e4ba7,Towards Arbitrary-View Face Alignment by Recommendation Trees,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
cf5c9b521c958b84bb63bea9d5cbb522845e4ba7,Towards Arbitrary-View Face Alignment by Recommendation Trees,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
cfa931e6728a825caada65624ea22b840077f023,Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry,Harbin Engineering University,Harbin Engineering University,"哈尔滨工程大学, 文庙街 - Wenmiao Street, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.77445695,126.67684917,edu,
+cf814b618fcbc9a556cdce225e74a8806867ba84,Facial Expression Recognition Using 3D Facial Feature Distances,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
cff911786b5ac884bb71788c5bc6acf6bf569eff,Multi-task Learning of Cascaded CNN for Facial Attribute Classification,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+cf528f9fe6588b71efa94c219979ce111fc9c1c9,On Evaluation of 6D Object Pose Estimation,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
cf09e2cb82961128302b99a34bff91ec7d198c7c,Office Entrance Control with Face Recognition,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
cf09e2cb82961128302b99a34bff91ec7d198c7c,Office Entrance Control with Face Recognition,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
-cfc4aa456d9da1a6fabd7c6ca199332f03e35b29,"University of Amsterdam and Renmin University at TRECVID 2016: Searching Video, Detecting Events and Describing Video",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
-cfc4aa456d9da1a6fabd7c6ca199332f03e35b29,"University of Amsterdam and Renmin University at TRECVID 2016: Searching Video, Detecting Events and Describing Video",Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
-cfc4aa456d9da1a6fabd7c6ca199332f03e35b29,"University of Amsterdam and Renmin University at TRECVID 2016: Searching Video, Detecting Events and Describing Video","Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+cfc4aa456d9da1a6fabd7c6ca199332f03e35b29,"Searching Video , Detecting Events and Describing Video",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+cfc4aa456d9da1a6fabd7c6ca199332f03e35b29,"Searching Video , Detecting Events and Describing Video",Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+cfc4aa456d9da1a6fabd7c6ca199332f03e35b29,"Searching Video , Detecting Events and Describing Video","Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+cf64cdc889a4edaf641a307aa2b11d89d4d10a09,High-performance and energy-efficient mobile web browsing on big/little systems,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
cfdc4d0f8e1b4b9ced35317d12b4229f2e3311ab,Quaero at TRECVID 2010: Semantic Indexing,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+ca50b25eaad0c9146fc5a4a2cd4c472c77b970ba,Face Recognition Using Histogram-based Features in Spatial and Frequency Domains,Kogakuin University,Kogakuin University,"工学院大学, 東通り, 新宿区, 東京都, 関東地方, 163-8677, 日本",35.69027840,139.69540096,edu,
+ca50b25eaad0c9146fc5a4a2cd4c472c77b970ba,Face Recognition Using Histogram-based Features in Spatial and Frequency Domains,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+ca50b25eaad0c9146fc5a4a2cd4c472c77b970ba,Face Recognition Using Histogram-based Features in Spatial and Frequency Domains,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+ca11dc3a8064583aaf79061866bbcf04caece162,Disentangled Representations in Neural Models,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+caab1c1d53718315f54bc4df42eb9a727fa18483,"Show, Tell and Discriminate: Image Captioning by Self-retrieval with Partially Labeled Data",Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+ca42b7f881437976a6c60de0229ebbf31b58c3bd,Learn the Distribution ? S Ome T Heory and E Mpirics,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+ca42b7f881437976a6c60de0229ebbf31b58c3bd,Learn the Distribution ? S Ome T Heory and E Mpirics,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+ca42b7f881437976a6c60de0229ebbf31b58c3bd,Learn the Distribution ? S Ome T Heory and E Mpirics,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+ca8c296c5c74d351d866ac317d9680626b0bc6a7,LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+caa2ded6d8d5de97c824d29b0c7a18d220c596c8,Learning to Segment Breast Biopsy Whole Slide Images,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+caa2ded6d8d5de97c824d29b0c7a18d220c596c8,Learning to Segment Breast Biopsy Whole Slide Images,University of Vermont,University of Vermont,"University of Vermont, Colchester Avenue, Burlington, Chittenden County, Vermont, 05401, USA",44.48116865,-73.20021790,edu,
+ca22c95ccea3e5ceaf95956811cb507af1bdd672,Electroconvulsive therapy selectively enhanced feedforward connectivity from fusiform face area to amygdala in major depressive disorder,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+ca4580c5c5d8475801de42e493c5f97096677927,Face Metamorphosis and Face Caricature: A User’s Guide,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+cabc9a1fef57fb2cad91bdb0a84e18934ee5bdbe,Virtual to Real Reinforcement Learning for Autonomous Driving,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+cabc9a1fef57fb2cad91bdb0a84e18934ee5bdbe,Virtual to Real Reinforcement Learning for Autonomous Driving,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+cabc9a1fef57fb2cad91bdb0a84e18934ee5bdbe,Virtual to Real Reinforcement Learning for Autonomous Driving,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+cabc9a1fef57fb2cad91bdb0a84e18934ee5bdbe,Virtual to Real Reinforcement Learning for Autonomous Driving,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+ca56ac26cd7e1fdc35033228b4936bf70a090825,Score Level Fusion of Ear and Face Local 3D Features for Fast and Expression-Invariant Human Recognition,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+caf912b716905ccbf46d6d00d6a0b622834a7cd9,Measuring Machine Intelligence Through Visual Question Answering,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
ca54d0a128b96b150baef392bf7e498793a6371f,Improve Pedestrian Attribute Classification by Weighted Interactions from Other Attributes,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+ca283c6fdf43b7ad59949207834a6a573381a9c9,Facial Identity Recognition in the Broader Autism Phenotype,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+ca283c6fdf43b7ad59949207834a6a573381a9c9,Facial Identity Recognition in the Broader Autism Phenotype,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+ca6b78e3d12134e12305fa4bcdf050ac102781df,OCNet: Object Context Network for Scene Parsing,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+cada850299f0aa71ecd9b37a2496802ad8d48455,Cost-effective conceptual design using taxonomies,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+cada850299f0aa71ecd9b37a2496802ad8d48455,Cost-effective conceptual design using taxonomies,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+ca1c710c14f95c3b0cf027fb068d53d595809a5c,Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+ca1c710c14f95c3b0cf027fb068d53d595809a5c,Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
e48fb3ee27eef1e503d7ba07df8eb1524c47f4a6,Illumination invariant face recognition and impostor rejection using different MINACE filter algorithms,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+e483f644eb20d79402bab1f5d96025598e101f82,Heterogeneous Multilayer Generalized Operational Perceptron,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+e483f644eb20d79402bab1f5d96025598e101f82,Heterogeneous Multilayer Generalized Operational Perceptron,Qatar University,Qatar University,"Qatar University, Roindabout 3, Al Tarfa (68), أم صلال, 24685, قطر",25.37461295,51.48980354,edu,
+e4433daf01a4e55ffca764c1e161f83552db081f,Exposure Is Not Enough: Suppressing Stimuli from Awareness Can Abolish the Mere Exposure Effect,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
e4bc529ced68fae154e125c72af5381b1185f34e,Perceptual Goal Specifications for Reinforcement Learning,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+e4450b61f1ccbe5bbec1e777baad5dd69fd6edbe,Neuro-IoU: Learning a Surrogate Loss for Semantic Segmentation,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+e4183e539b90ac02f55ccf16eb154bc269576290,The Unusual Effectiveness of Averaging in GAN Training,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+e4183e539b90ac02f55ccf16eb154bc269576290,The Unusual Effectiveness of Averaging in GAN Training,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+e4183e539b90ac02f55ccf16eb154bc269576290,The Unusual Effectiveness of Averaging in GAN Training,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
+e483482e19b022a1cd7081dc2757bb8a85774ed7,"HOAI, LADICKÝ, ZISSERMAN: ACTION FROMWEAK ALIGNMENT OF BODY PARTS 1 Action Recognition From Weak Alignment of Body Parts",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+e483482e19b022a1cd7081dc2757bb8a85774ed7,"HOAI, LADICKÝ, ZISSERMAN: ACTION FROMWEAK ALIGNMENT OF BODY PARTS 1 Action Recognition From Weak Alignment of Body Parts",Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+e483482e19b022a1cd7081dc2757bb8a85774ed7,"HOAI, LADICKÝ, ZISSERMAN: ACTION FROMWEAK ALIGNMENT OF BODY PARTS 1 Action Recognition From Weak Alignment of Body Parts",ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+e42d055d59f6b5b0bf677975d21544aad26a5417,Learning to Appreciate the Aesthetic Effects of Clothing,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+e42d055d59f6b5b0bf677975d21544aad26a5417,Learning to Appreciate the Aesthetic Effects of Clothing,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
e42998bbebddeeb4b2bedf5da23fa5c4efc976fa,Generic Active Appearance Models Revisited,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
e42998bbebddeeb4b2bedf5da23fa5c4efc976fa,Generic Active Appearance Models Revisited,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
+e4b88898d8ac1086e82ecc2fba82fb174bf9adaa,PacGAN: The power of two samples in generative adversarial networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+e4a6d0ce979c2067c6d0aec9e7a22113b8d3b7d7,Fine-grained Activity Recognition in Baseball Videos,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
e4df83b7424842ff5864c10fa55d38eae1c45fac,Locally Linear Discriminate Embedding for Face Recognition,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+e459158c2217904d5fe9a409896bd49622f17ebe,Face Video Retrieval via Deep Learning of Binary Hash Representations,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+e459158c2217904d5fe9a409896bd49622f17ebe,Face Video Retrieval via Deep Learning of Binary Hash Representations,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+e4cb27d2a3e1153cb517d97d61de48ff0483c988,Viktoria Plemakova Vehicle Detection Based on Convolutional Neural Networks,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
e4e3faa47bb567491eaeaebb2213bf0e1db989e1,Empirical Risk Minimization for Metric Learning Using Privileged Information,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
e4e3faa47bb567491eaeaebb2213bf0e1db989e1,Empirical Risk Minimization for Metric Learning Using Privileged Information,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+e405c59d9e13c4d72050535f00cd3696ac004740,Robust Estimation via Robust Gradient Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+e4236c286787cc608ec42abba2e51eb36f108b14,Deep Word Embeddings for Visual Speech Recognition,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+e4444820fb3f6d1f41c6ea51c6b2ab8ceb04a3a5,View-Driven Deduplication with Active Learning,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
e43045a061421bd79713020bc36d2cf4653c044d,A New Representation of Skeleton Sequences for 3D Action Recognition,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
e475deadd1e284428b5e6efd8fe0e6a5b83b9dcd,Are you eligible? Predicting adulthood from face images via class specific mean autoencoder,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+e417e88c13e0f3d5bbd02e6682823b0514f4bc78,Deep Bi-Dense Networks for Image Super-Resolution,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+fe9a6a93af9c32f6b0454a7cf6897409124514bd,Designing a smart card face verification system,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+fe9a6a93af9c32f6b0454a7cf6897409124514bd,Designing a smart card face verification system,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+fef3efeffade0e39f2c279653b4785b372be410e,Near infrared face recognition: A literature survey,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+fef3efeffade0e39f2c279653b4785b372be410e,Near infrared face recognition: A literature survey,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+fe5c43aa19da5cbbf5a42e4697659875f7389b91,Tracking People in Broadcast Sports,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+febff0f6faa8dde77848845e4b3e6f6c91180d33,Embedding Deep Metric for Person Re-identification: A Study Against Large Variations,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+febff0f6faa8dde77848845e4b3e6f6c91180d33,Embedding Deep Metric for Person Re-identification: A Study Against Large Variations,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+febff0f6faa8dde77848845e4b3e6f6c91180d33,Embedding Deep Metric for Person Re-identification: A Study Against Large Variations,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+fe68d6fe52df8c28f7cf81b338c491e5bac6e33c,SCAN: Self-and-Collaborative Attention Network for Video Person Re-identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+fe68d6fe52df8c28f7cf81b338c491e5bac6e33c,SCAN: Self-and-Collaborative Attention Network for Video Person Re-identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+fe60d81f726c8e20948b927b456a94a96d78fa26,"Multimodal Utterance-level Affect Analysis using Visual, Audio and Text Features",Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+fe60d81f726c8e20948b927b456a94a96d78fa26,"Multimodal Utterance-level Affect Analysis using Visual, Audio and Text Features","University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
fe464b2b54154d231671750053861f5fd14454f5,Multi Joint Action in CoTeSys-Setup and Challenges-Technical report CoTeSys-TR-1001,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
fe464b2b54154d231671750053861f5fd14454f5,Multi Joint Action in CoTeSys-Setup and Challenges-Technical report CoTeSys-TR-1001,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
fe464b2b54154d231671750053861f5fd14454f5,Multi Joint Action in CoTeSys-Setup and Challenges-Technical report CoTeSys-TR-1001,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
@@ -1391,6 +3845,7 @@ fe464b2b54154d231671750053861f5fd14454f5,Multi Joint Action in CoTeSys-Setup and fe464b2b54154d231671750053861f5fd14454f5,Multi Joint Action in CoTeSys-Setup and Challenges-Technical report CoTeSys-TR-1001,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
fe5df5fe0e4745d224636a9ae196649176028990,Using Context to Enhance the Understanding of Face Images,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
fe5df5fe0e4745d224636a9ae196649176028990,Using Context to Enhance the Understanding of Face Images,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+feb4367aafc60159c8dedcaba2d5a66fdd64066c,Explaining unexplainable food choices,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
fe961cbe4be0a35becd2d722f9f364ec3c26bd34,"Computer-based Tracking, Analysis, and Visualization of Linguistically Significant Nonmanual Events in American Sign Language (ASL)",Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
fe961cbe4be0a35becd2d722f9f364ec3c26bd34,"Computer-based Tracking, Analysis, and Visualization of Linguistically Significant Nonmanual Events in American Sign Language (ASL)",Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
feb6e267923868bff6e2108603d00fdfd65251ca,Unsupervised Discovery of Visual Face Categories,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
@@ -1398,36 +3853,118 @@ feb6e267923868bff6e2108603d00fdfd65251ca,Unsupervised Discovery of Visual Face C feb6e267923868bff6e2108603d00fdfd65251ca,Unsupervised Discovery of Visual Face Categories,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
feb6e267923868bff6e2108603d00fdfd65251ca,Unsupervised Discovery of Visual Face Categories,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
feb6e267923868bff6e2108603d00fdfd65251ca,Unsupervised Discovery of Visual Face Categories,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
+feb5b8bf315a6b6222f62dd9533b1e0f891a27bd,The Nature and Consequences of Essentialist Beliefs About Race in Early Childhood.,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+feb5b8bf315a6b6222f62dd9533b1e0f891a27bd,The Nature and Consequences of Essentialist Beliefs About Race in Early Childhood.,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+fe8a8c4133698e4b68018d99c6a2bcec870c5464,A New Large Scale Dynamic Texture Dataset with Application to ConvNet Understanding,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+fecad388186269e3d8d71a75c42f56e661861c3e,Discovering Geo-Informative Attributes for Location Recognition and Exploration,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+fe5e1e869510d18d4c771b1fe924fca0a01f7222,Towards Energy-Efficient Mobile Sensing: Architectures and Frameworks for Heterogeneous Sensing and Computing,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+fe82d072a8d13cfefcd575db893f3374251f04a8,Multi-fiber Networks for Video Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+fe710adb0e9e647d7ede0583b40d2aeb36c1fc7f,Human Appearance Transfer,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+fe6409e8e09d47758d4e71981ad951423bdce212,Camera-based vehicle velocity estimation from monocular video,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+fec2a5a06a3aab5efe923a78d208ec747d5e4894,Generalizing to Unseen Domains via Adversarial Data Augmentation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+fec2a5a06a3aab5efe923a78d208ec747d5e4894,Generalizing to Unseen Domains via Adversarial Data Augmentation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+fec2a5a06a3aab5efe923a78d208ec747d5e4894,Generalizing to Unseen Domains via Adversarial Data Augmentation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
feeb0fd0e254f38b38fe5c1022e84aa43d63f7cc,Search Pruning with Soft Biometric Systems: Efficiency-Reliability Tradeoff,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+fe0cf8eaa5a5f59225197ef1bb8613e603cd96d4,Improved Face Verification with Simple Weighted Feature Combination,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+fed618637ac9d2fbdb0711f64ea752370dfaca61,Human Body Poses Recognition Using Neural Networks with Class Based Data Augmentation,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
+fe95b902eb362ad39f91e2325300d3f7a9119c48,Modeling invariant object processing based on tight integration of simulated and empirical data in a Common Brain Space,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
+fe95b902eb362ad39f91e2325300d3f7a9119c48,Modeling invariant object processing based on tight integration of simulated and empirical data in a Common Brain Space,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
+c89ddb0e978b78c062fbf9ea992da83e4b38778e,2D and 3D Multimodal Hybrid Face Recognition,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+c8be6a59b1c29a1a44a0792985baf365298123e2,Visual Surveillance on DSP-Based Embedded Platforms,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+c8a5c5c8e1293b7e877a848b7a9e5426c5400651,FaceShop: Deep Sketch-based Face Image Editing,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+c8e20a4981e907c77ccbfe6ae39673aa43249f41,Neuromorphic Hardware Accelerated Adaptive Authentication System,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
c87f7ee391d6000aef2eadb49f03fc237f4d1170,A real-time and unsupervised face Re-Identification system for Human-Robot Interaction,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+c8c714c100a754baf7d86d240ec35207fcf84b06,Person Re-identification Meets Image Search,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+c8c714c100a754baf7d86d240ec35207fcf84b06,Person Re-identification Meets Image Search,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+c87035f4b5cdb8597db20e9dc319c2a06d752197,Learning Latent Subspaces in Variational Autoencoders,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
c8ca6a2dc41516c16ea0747e9b3b7b1db788dbdd,Track Facial Points in Unconstrained Videos,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
c8292aa152a962763185e12fd7391a1d6df60d07,Camera Distance from Face Images,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+c8c83ab64d99b16ef3248cbeccc95f7049e324d5,Nearest Prime Simplicial Complex for Object Recognition,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+c8c83ab64d99b16ef3248cbeccc95f7049e324d5,Nearest Prime Simplicial Complex for Object Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
c829be73584966e3162f7ccae72d9284a2ebf358,shuttleNet: A biologically-inspired RNN with loop connection and parameter sharing,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
c829be73584966e3162f7ccae72d9284a2ebf358,shuttleNet: A biologically-inspired RNN with loop connection and parameter sharing,Beijing Institute of Technology,Beijing Institute of Technology University,"北京理工大学, 5, 中关村南大街, 中关村, 稻香园南社区, 海淀区, 北京市, 100872, 中国",39.95866520,116.30971281,edu,
c87d5036d3a374c66ec4f5870df47df7176ce8b9,Temporal Dynamics of Natural Static Emotional Facial Expressions Decoding: A Study Using Event- and Eye Fixation-Related Potentials,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+c88173aac29baa13d615c5be858290a14f0493c9,Generic Object Recognition with Local Receptive Fields Based Extreme Learning Machine,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+c8dc902b82831e1f1b587c590cdc34b5d12bdc5c,DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pairs,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+c8a22550297a25dadd283089f009015bc0df5eed,Neural circuits in the brain that are activated when mitigating criminal sentences,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+c8da81fb5551941295ad815051d39dc461008751,Hybrid forests for left ventricle segmentation using only the first slice label,Moulay Ismail University,Moulay Ismail University,"Marjane 2, BP: 298، Meknes 50050, Morocco",33.85611100,-5.57439100,edu,Moulay Ismail University
c8e84cdff569dd09f8d31e9f9ba3218dee65e961,Dictionaries for image and video-based face recognition [Invited].,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
c8e84cdff569dd09f8d31e9f9ba3218dee65e961,Dictionaries for image and video-based face recognition [Invited].,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+c86ce9fc2bd5aea98869cf1f31d03e05e7ec672c,FOIL it! Find One mismatch between Image and Language caption,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
c8829013bbfb19ccb731bd54c1a885c245b6c7d7,Flexible Template and Model Matching Using Image Intensity,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+c84b2cda2d645475f25d8b8f34b8f21ad3aa059c,Human Face Detection and Eye Localization in Video Using Wavelets,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+c8b4df94686ae4d308e859eddc0e00921a17fe75,GraphBit : Bitwise Interaction Mining via Deep Reinforcement Learning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+c8fc81a54ccef6d8111e7253283fc55e7e0f8ebd,High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+c8fc81a54ccef6d8111e7253283fc55e7e0f8ebd,High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+c8fc81a54ccef6d8111e7253283fc55e7e0f8ebd,High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+c8fc81a54ccef6d8111e7253283fc55e7e0f8ebd,High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
c88ce5ef33d5e544224ab50162d9883ff6429aa3,Face Match for Family Reunification: Real-World Face Image Retrieval,Central Washington University,Central Washington University,"Central Washington University, Dean Nicholson Boulevard, Ellensburg, Kittitas County, Washington, 98926, USA",47.00646895,-120.53673040,edu,
c822bd0a005efe4ec1fea74de534900a9aa6fb93,Face recognition committee machines: dynamic vs. static structures,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
c88c21eb9a8e08b66c981db35f6556f4974d27a8,Attribute Learning using Joint Human and Machine Computation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
c88c21eb9a8e08b66c981db35f6556f4974d27a8,Attribute Learning using Joint Human and Machine Computation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+c8d15a58794e4b383424d2d057a518689a278b8d,Field Effect Deep Networks for Image Recognition with Incomplete Data,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+c8d15a58794e4b383424d2d057a518689a278b8d,Field Effect Deep Networks for Image Recognition with Incomplete Data,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+c8d15a58794e4b383424d2d057a518689a278b8d,Field Effect Deep Networks for Image Recognition with Incomplete Data,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+c8c5944ec503744304e026284182fce26d74cd92,Pose Guided Visual Attention for Action Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+fbedfe317e60e5ec83c8fd0554bc345404ca90f5,Scene Graph Parsing as Dependency Parsing,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+fbedfe317e60e5ec83c8fd0554bc345404ca90f5,Scene Graph Parsing as Dependency Parsing,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+fb210da5526e967a6aaaa1a4cc1134fa0976ad11,DRPose3D: Depth Ranking in 3D Human Pose Estimation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+fb210da5526e967a6aaaa1a4cc1134fa0976ad11,DRPose3D: Depth Ranking in 3D Human Pose Estimation,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+fb210da5526e967a6aaaa1a4cc1134fa0976ad11,DRPose3D: Depth Ranking in 3D Human Pose Estimation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+fb210da5526e967a6aaaa1a4cc1134fa0976ad11,DRPose3D: Depth Ranking in 3D Human Pose Estimation,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+fb210da5526e967a6aaaa1a4cc1134fa0976ad11,DRPose3D: Depth Ranking in 3D Human Pose Estimation,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
fb2cc3501fc89f92f5ee130d66e69854f8a9ddd1,Learning Discriminative Features via Label Consistent Neural Network,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+fba539b41786f837acc5e5d876aaa7c6f3fc376c,Neural Generative Models for 3D Faces with Application in 3D Texture Free Face Recognition,University of Bridgeport,University of Bridgeport,"University of Bridgeport, Park Avenue, Bridgeport Downtown South Historic District, Bridgeport, Fairfield County, Connecticut, 06825, USA",41.16648580,-73.19205640,edu,
+fba539b41786f837acc5e5d876aaa7c6f3fc376c,Neural Generative Models for 3D Faces with Application in 3D Texture Free Face Recognition,University of Bridgeport,University of Bridgeport,"University of Bridgeport, Park Avenue, Bridgeport Downtown South Historic District, Bridgeport, Fairfield County, Connecticut, 06825, USA",41.16648580,-73.19205640,edu,
fbb6ee4f736519f7231830a8e337b263e91f06fe,Illumination Robust Facial Feature Detection via Decoupled Illumination and Texture Features,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+fb62fae47f2ccef2e11eefb112765cdbbe4f0400,Tensor-Variate Restricted Boltzmann Machines,Deakin University,Deakin University,"Deakin University, Pigdons Lane, Waurn Ponds, Geelong, City of Greater Geelong, Barwon South West, Victoria, 3216, Australia",-38.19928505,144.30365229,edu,
+fb62fae47f2ccef2e11eefb112765cdbbe4f0400,Tensor-Variate Restricted Boltzmann Machines,Curtin University,Curtin University,"Curtin University, Brand Drive, Waterford, Perth, Western Australia, 6102, Australia",-32.00686365,115.89691775,edu,
fb87045600da73b07f0757f345a937b1c8097463,Reflective Regression of 2D-3D Face Shape Across Large Pose,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
fb85867c989b9ee6b7899134136f81d6372526a9,Learning to Align Images using Weak Geometric Supervision,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
fb85867c989b9ee6b7899134136f81d6372526a9,Learning to Align Images using Weak Geometric Supervision,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+fbfb0de017d57c5f282050dadb77797d97785ba5,Enabling EBGM Face Authentication on mobile devices,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+fb3bce3a6221eb65451584efa898ecbe211bdab6,Video to Text Summary: Joint Video Summarization and Captioning with Recurrent Neural Networks,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+fbd5c9bbfb43aa4734cde7863897600fd42eb8ff,Person Detection in the Restaurant of the Future,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+fb193923274c9b028254075c3b6decdae70b2ec0,Learning Social Image Embedding with Deep Multimodal Attention Networks,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
fb54d3c37dc82891ff9dc7dd8caf31de00c40d6a,Beauty and the Burst: Remote Identification of Encrypted Video Streams,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
fb54d3c37dc82891ff9dc7dd8caf31de00c40d6a,Beauty and the Burst: Remote Identification of Encrypted Video Streams,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+fba95853ca3135cc52a4b2bc67089041c2a9408c,Disguised Faces in the Wild,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+fba95853ca3135cc52a4b2bc67089041c2a9408c,Disguised Faces in the Wild,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+fb3844521f9719e4904e5d3d7e1e549e5881b1f4,An Event-Related Potential Study on the Effects of Cannabis on Emotion Processing.,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+fb3844521f9719e4904e5d3d7e1e549e5881b1f4,An Event-Related Potential Study on the Effects of Cannabis on Emotion Processing.,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+fb22404e46dd46b2c2cb9a85227a1ab6a8ae4f52,Micro-analytics for Student Performance Prediction Leveraging fine-grained learning analytics to predict performance,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+fb35a3dadbe6d9a1823eb12e33fccf9a3db3c2a2,Avoidant Responses to Interpersonal Provocation Are Associated with Increased Amygdala and Decreased Mentalizing Network Activity,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
fb084b1fe52017b3898c871514cffcc2bdb40b73,Illumination Normalization of Face Image Based on Illuminant Direction Estimation and Improved Retinex,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
fb084b1fe52017b3898c871514cffcc2bdb40b73,Illumination Normalization of Face Image Based on Illuminant Direction Estimation and Improved Retinex,University Politehnica Timisoara,University POLITEHNICA Timisoara,"UPT, Bulevardul Vasile Pârvan, Elisabetin, Timișoara, Timiș, 300223, România",45.74618900,21.22755075,edu,
+ed74afbd3e36f0fdf54da1e4fcb773c21b5de9b9,An Overview of Computational Approaches for Analyzing Interpretation,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
ed0cf5f577f5030ac68ab62fee1cf065349484cc,Revisiting data normalization for appearance-based gaze estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
ed0cf5f577f5030ac68ab62fee1cf065349484cc,Revisiting data normalization for appearance-based gaze estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+eddc4989cdb20c8cdfb22e989bdb2cb9031d0439,Binge Watching: Scaling Affordance Learning from Sitcoms,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
edde81b2bdd61bd757b71a7b3839b6fef81f4be4,Part Localization using Multi-Proposal Consensus for Fine-Grained Categorization,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+eda6da71c261df17b4b9da5e72aad7893a871a84,Moonshine: Distilling with Cheap Convolutions,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+eda6da71c261df17b4b9da5e72aad7893a871a84,Moonshine: Distilling with Cheap Convolutions,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+eda6da71c261df17b4b9da5e72aad7893a871a84,Moonshine: Distilling with Cheap Convolutions,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
edf98a925bb24e39a6e6094b0db839e780a77b08,Simplex Representation for Subspace Clustering,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+ed173a39f4cd980eef319116b6ba39cec1b37c42,Associative Embedding: End-to-End Learning for Joint Detection and Grouping,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+ed173a39f4cd980eef319116b6ba39cec1b37c42,Associative Embedding: End-to-End Learning for Joint Detection and Grouping,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+ed173a39f4cd980eef319116b6ba39cec1b37c42,Associative Embedding: End-to-End Learning for Joint Detection and Grouping,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
ed9d11e995baeec17c5d2847ec1a8d5449254525,Efficient Gender Classification Using a Deep LDA-Pruned Net,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+edb5813a32ce1167feb263ca2803d0ae934d902c,Invisible Steganography via Generative Adversarial Networks,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+ed432ecd59021a96d8995269a34678c4c2774507,End-to-end Learning of Multi-sensor 3D Tracking by Detection,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
ed07856461da6c7afa4f1782b5b607b45eebe9f6,D Morphable Models as Spatial Transformer Networks,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
ed07856461da6c7afa4f1782b5b607b45eebe9f6,D Morphable Models as Spatial Transformer Networks,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+ed2f711cf9bcd9d7ab039d746af109ed9573421a,Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+ed2f711cf9bcd9d7ab039d746af109ed9573421a,Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+ed7f167c84372512dcbf9dd38d39879edde6819e,Iterative Visual Reasoning Beyond Convolutions,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+eda8796530fd9ba23b39d50cf349fee01ccee144,Interactive Sketch-Driven Image Synthesis,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
ed1886e233c8ecef7f414811a61a83e44c8bbf50,Deep Alignment Network: A Convolutional Neural Network for Robust Face Alignment,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
edd7504be47ebc28b0d608502ca78c0aea6a65a2,Recurrent Residual Learning for Action Recognition,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
ed388878151a3b841f95a62c42382e634d4ab82e,DenseImage Network: Video Spatial-Temporal Evolution Encoding and Understanding,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
@@ -1442,33 +3979,110 @@ edff76149ec44f6849d73f019ef9bded534a38c2,Privacy-Preserving Visual Learning Usin ed96f2eb1771f384df2349879970065a87975ca7,Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
ed96f2eb1771f384df2349879970065a87975ca7,Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
c180f22a9af4a2f47a917fd8f15121412f2d0901,Facial Expression Recognition by ICA with Selective Prior,Japan Advanced Institute of Science and Technology,Japan Advanced Institute of Science and Technology,"JAIST (北陸先端科学技術大学院大学), 石川県道55号小松辰口線, Ishikawa Science Park, 能美市, 石川県, 中部地方, 923-1206, 日本",36.44429490,136.59285870,edu,
+c1a18684feeb2b966e2f03c2622f9a702e14204c,Eye Detection using Wavelets and ANN,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+c1a18684feeb2b966e2f03c2622f9a702e14204c,Eye Detection using Wavelets and ANN,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
c146aa6d56233ce700032f1cb179700778557601,3D Morphable Models as Spatial Transformer Networks,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
c146aa6d56233ce700032f1cb179700778557601,3D Morphable Models as Spatial Transformer Networks,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
c1f07ec629be1c6fe562af0e34b04c54e238dcd1,A Novel Facial Feature Localization Method Using Probabilistic-like Output,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+c1bf99570889a43ba2b16e6141b365d74608973d,Comparing social attention in autism and amygdala lesions: effects of stimulus and task condition.,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+c1bf99570889a43ba2b16e6141b365d74608973d,Comparing social attention in autism and amygdala lesions: effects of stimulus and task condition.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+c1bf99570889a43ba2b16e6141b365d74608973d,Comparing social attention in autism and amygdala lesions: effects of stimulus and task condition.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+c127ac138a22c155a79f362562a52c070e2b4022,Describing Natural Images Containing Novel Objects with Knowledge Guided Assitance,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+c127ac138a22c155a79f362562a52c070e2b4022,Describing Natural Images Containing Novel Objects with Knowledge Guided Assitance,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+c127ac138a22c155a79f362562a52c070e2b4022,Describing Natural Images Containing Novel Objects with Knowledge Guided Assitance,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+c127ac138a22c155a79f362562a52c070e2b4022,Describing Natural Images Containing Novel Objects with Knowledge Guided Assitance,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+c1ee2e1d53f9ffc9fca5e3e8da7c89dc2a2133d9,A Multifaceted Independent Performance Analysis of Facial Subspace Recognition Algorithms,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+c1ee2e1d53f9ffc9fca5e3e8da7c89dc2a2133d9,A Multifaceted Independent Performance Analysis of Facial Subspace Recognition Algorithms,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
c1cc2a2a1ab66f6c9c6fabe28be45d1440a57c3d,Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
c1cc2a2a1ab66f6c9c6fabe28be45d1440a57c3d,Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+c17ed26650a67e80151f5312fa15b5c423acc797,Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+c17ed26650a67e80151f5312fa15b5c423acc797,Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+c17ed26650a67e80151f5312fa15b5c423acc797,Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration,Institute of Industrial Science,Institute of Industrial Science,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+c17ed26650a67e80151f5312fa15b5c423acc797,Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+c17ed26650a67e80151f5312fa15b5c423acc797,Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+c136e338606acb0e3a0752a75cf1cef7db5de0a6,Combining features and decisions for face detection,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+c13291eaf9ca1b91ef3feb9d58a9a894130631e3,Relation Networks for Object Detection,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+c1aa52ad21d0ec20102eb5402c60ac91c49612bb,Spatial-Temporal Granularity-Tunable Gradients Partition (STGGP) Descriptors for Human Detection,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+c1586ee25e660f31cba0ca9ba5bf39ffcc020aab,A Modulation Module for Multi-task Learning with Applications in Image Retrieval,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+c1586ee25e660f31cba0ca9ba5bf39ffcc020aab,A Modulation Module for Multi-task Learning with Applications in Image Retrieval,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
c17a332e59f03b77921942d487b4b102b1ee73b6,Learning an appearance-based gaze estimator from one million synthesised images,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
c17a332e59f03b77921942d487b4b102b1ee73b6,Learning an appearance-based gaze estimator from one million synthesised images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
c17a332e59f03b77921942d487b4b102b1ee73b6,Learning an appearance-based gaze estimator from one million synthesised images,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+c11c89e303a6b46de324efa01a0f749b4246c516,A Novel Approach to Design a Customized Image Editor and Real-Time Control of Hand-Gesture Mimicking Robotic Movements on an I-Robot Create,Oklahoma State University,Oklahoma State University,"Walmart East Bus Stop, East Virginia Avenue, Stillwater, Payne County, Oklahoma, 74075, USA",36.12447560,-97.05004383,edu,
+c1980e5d5c998ddec31cda9da148c354406a5eca,Jointly Optimizing 3D Model Fitting and Fine-Grained Classification,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+c1980e5d5c998ddec31cda9da148c354406a5eca,Jointly Optimizing 3D Model Fitting and Fine-Grained Classification,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+c1cf5dda56c72b65e86f3a678f76644f22212748,Face Hallucination via Semi-kernel Partial Least Squares,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+c16479cfa79fe9996ca16fc30add9099815abb04,Robust Face Recognition after Plastic Surgery Using Local Region Analysis,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
c10b0a6ba98aa95d740a0d60e150ffd77c7895ad,Deep Fisher Faces,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
c1298120e9ab0d3764512cbd38b47cd3ff69327b,Disguised Faces in the Wild,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
c1298120e9ab0d3764512cbd38b47cd3ff69327b,Disguised Faces in the Wild,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+c64da9bbdc9942decc4566f89e13d991a6303683,Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+c64da9bbdc9942decc4566f89e13d991a6303683,Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+c64da9bbdc9942decc4566f89e13d991a6303683,Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
c65e4ffa2c07a37b0bb7781ca4ec2ed7542f18e3,Recurrent Neural Networks for Facial Action Unit Recognition from Image Sequences,University of Witwatersrand,University of Witwatersrand,"University of the Witwatersrand, Empire Road, Johannesburg Ward 60, Johannesburg, City of Johannesburg Metropolitan Municipality, Gauteng, 2001, South Africa",-26.18888130,28.02479073,edu,
c65e4ffa2c07a37b0bb7781ca4ec2ed7542f18e3,Recurrent Neural Networks for Facial Action Unit Recognition from Image Sequences,University of the Western Cape,University of the Western Cape,"University of the Western Cape, Park Road, Cape Town Ward 9, Bellville, City of Cape Town, Western Cape, 7493, South Africa",-33.93277620,18.62915407,edu,
c65e4ffa2c07a37b0bb7781ca4ec2ed7542f18e3,Recurrent Neural Networks for Facial Action Unit Recognition from Image Sequences,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+c69ea9367e1244bfa5d3fc290b8a33be3abd8c24,"Many faces, one rule: the role of perceptual expertise in infants’ sequential rule learning",Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+c644a4fb7f8d30b7c7c0358e2b66a53553fb534c,Image Information Distance Analysis and Applications,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
c6096986b4d6c374ab2d20031e026b581e7bf7e9,A Framework for Using Context to Understand Images of People,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+c6e99ff40ccae0d7ce8e32666ed7f75e3a381d9b,How does the topic of conversation affect verbal exchange and eye gaze? A comparison between typical development and high-functioning autism.,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+c6e99ff40ccae0d7ce8e32666ed7f75e3a381d9b,How does the topic of conversation affect verbal exchange and eye gaze? A comparison between typical development and high-functioning autism.,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
c6608fdd919f2bc4f8d7412bab287527dcbcf505,Unsupervised Alignment of Natural Language with Video,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+c63b614865bd9e5b4944894083e5e9d4aba82d86,Large Scale Similarity Learning Using Similar Pairs for Person Verification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+c6bceb0eb8aded28edbe2607ecbe2f5ee2b57bdc,Random projections on manifolds of Symmetric Positive Definite matrices for image classification,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+c6bceb0eb8aded28edbe2607ecbe2f5ee2b57bdc,Random projections on manifolds of Symmetric Positive Definite matrices for image classification,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+c6657c1263bac59b006d1da1174ec4bcea0dff3d,Global-local visual processing in high functioning children with autism: structural vs. implicit task biases.,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+c6657c1263bac59b006d1da1174ec4bcea0dff3d,Global-local visual processing in high functioning children with autism: structural vs. implicit task biases.,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+c6657c1263bac59b006d1da1174ec4bcea0dff3d,Global-local visual processing in high functioning children with autism: structural vs. implicit task biases.,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
+c6657c1263bac59b006d1da1174ec4bcea0dff3d,Global-local visual processing in high functioning children with autism: structural vs. implicit task biases.,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+c6657c1263bac59b006d1da1174ec4bcea0dff3d,Global-local visual processing in high functioning children with autism: structural vs. implicit task biases.,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+c66eb0e17076bff559d8f94a8f967d52db2bab01,Video Classification System for Moments in Time Challenge 2018,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+c66eb0e17076bff559d8f94a8f967d52db2bab01,Video Classification System for Moments in Time Challenge 2018,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
c62c910264658709e9bf0e769e011e7944c45c90,Recent Progress of Face Image Synthesis,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+c6e2641d99c72bbffef8a97ec019dd9379dd8b3a,Temporal Action Detection by Joint Identification-Verification,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
c678920facffd35853c9d185904f4aebcd2d8b49,Learning to Anonymize Faces for Privacy Preserving Action Detection,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+c660f261615f4a0185fda548b0ffb0e997a918ea,Finding Human Poses in Videos Using Concurrent Matching and Segmentation,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
c660500b49f097e3af67bb14667de30d67db88e3,Facial Asymmetry Quantification for Expression Invariant Human Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
c660500b49f097e3af67bb14667de30d67db88e3,Facial Asymmetry Quantification for Expression Invariant Human Identification,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
c660500b49f097e3af67bb14667de30d67db88e3,Facial Asymmetry Quantification for Expression Invariant Human Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
c6241e6fc94192df2380d178c4c96cf071e7a3ac,Action recognition with trajectory-pooled deep-convolutional descriptors,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
c6241e6fc94192df2380d178c4c96cf071e7a3ac,Action recognition with trajectory-pooled deep-convolutional descriptors,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+c6ce8eb37dafed09e1c55735fd1f1e9dc9c6bfe2,Joint background reconstruction and foreground segmentation via a two-stage convolutional neural network,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+c6ce8eb37dafed09e1c55735fd1f1e9dc9c6bfe2,Joint background reconstruction and foreground segmentation via a two-stage convolutional neural network,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8,Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8,Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+c6f58adf4a5ee8499cbc9b9bc1e6f1c39f1f8eae,Earn to P Ay a Ttention,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+c6d78245ab09c5690e483962dd51e0408fbf5cc7,Neural responses to emotional expression information in high- and low-spatial frequency in autism: evidence for a cortical dysfunction,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+c6481bdef3a75f74b7c28bb957755f75003d869d,"MAPTrack - A Probabilistic Real Time Tracking Framework by Integrating Motion, Appearance and Position Models",Louisiana State University,Louisiana State University,"LSU, Gourrier Avenue, Baton Rouge, East Baton Rouge Parish, Louisiana, 70803, USA",30.40550035,-91.18620474,edu,
+c666aea88c48b287080de410d4830f64f0b5ca2a,Improved Object Detection and Pose Using Part-Based Models,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+c6df59e1d77d84f418666235979cbce6d400d3ca,Spectral Clustering Based on Local PCA,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+c6df59e1d77d84f418666235979cbce6d400d3ca,Spectral Clustering Based on Local PCA,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+c6df59e1d77d84f418666235979cbce6d400d3ca,Spectral Clustering Based on Local PCA,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+c6542d17b212d808cba48cd2b1536446b14e38b3,You said that?,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
c65a394118d34beda5dd01ae0df163c3db88fceb,Finding the Best Picture: Cross-Media Retrieval of Content,Katholieke Universiteit Leuven,Katholieke Universiteit Leuven,"Laboratorium voor Bos, natuur en landschap, 102, Vital Decosterstraat, Sint-Maartensdal, Leuven, Vlaams-Brabant, Vlaanderen, 3000, België / Belgique / Belgien",50.88306860,4.70195030,edu,
ec8ec2dfd73cf3667f33595fef84c95c42125945,Pose-Invariant Face Alignment with a Single CNN,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+ec792ad2433b6579f2566c932ee414111e194537,Person Transfer GAN to Bridge Domain Gap for Person Re-Identification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+ec792ad2433b6579f2566c932ee414111e194537,Person Transfer GAN to Bridge Domain Gap for Person Re-Identification,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+ec9f036195ccfdac51b6daf241c45ce7010d0d78,"Towards Open Ended Learning: Budgets, Model Selection, and Representation",California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+ec0177cfdee435c6522ca4ee8a5f97ac0412472e,Reconstruction of images from Gabor graphs with applications in facial image processing,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+ec0177cfdee435c6522ca4ee8a5f97ac0412472e,Reconstruction of images from Gabor graphs with applications in facial image processing,Ruhr-University Bochum,Ruhr-University Bochum,"RUB, 150, Universitätsstraße, Ruhr-Universität, Querenburg, Bochum-Süd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland",51.44415765,7.26096541,edu,
+ec83c63e28ae2a658bc76a6750e078c3a54b9760,Deep Descriptor Transforming for Image Co-Localization,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+ec83c63e28ae2a658bc76a6750e078c3a54b9760,Deep Descriptor Transforming for Image Co-Localization,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+ec488139105565477bb8a3c6cb3c874c35fcb2b6,Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+ece80165040e9d8304c5dd808a6cdb29c8ecbf5b,Looking at People Using Partial Least Squares,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+ece80165040e9d8304c5dd808a6cdb29c8ecbf5b,Looking at People Using Partial Least Squares,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+ecd473cfbce5f058a3c9388b220b21de1ece8eb8,Trajectory Shape Analysis and Anomaly Detection Utilizing Information Theory Tools,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+ecc2ea05877d720b725fb89bc3b0586a51cabdc7,Object Recognition in 3D Point Clouds Using Web Data and Domain Adaptation,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+ec2ee72168368537ddb0eaac50f9e8c1b1d52a8c,Classification and Representation via Separable Subspaces: Performance Limits and Algorithms,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+ec949cb716fb33cb9273fc90f36b0351056ef0e0,An Abnormal Crowd Behavior Detection Algorithm Based on Fluid Mechanics,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+ec949cb716fb33cb9273fc90f36b0351056ef0e0,An Abnormal Crowd Behavior Detection Algorithm Based on Fluid Mechanics,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+ec9c20ed6cce15e9b63ac96bb5a6d55e69661e0b,Robust Pedestrian Detection for Semi-automatic Construction of a Crowded Person Re-Identification Dataset,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+ec9c20ed6cce15e9b63ac96bb5a6d55e69661e0b,Robust Pedestrian Detection for Semi-automatic Construction of a Crowded Person Re-Identification Dataset,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
+ece390deb6576dbc1fdf132f182a1cc75eb67832,Interleaved Group Convolutions for Deep Neural Networks,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+ece390deb6576dbc1fdf132f182a1cc75eb67832,Interleaved Group Convolutions for Deep Neural Networks,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+ec5f89e822d9fcbc7b7422dc401478fc29f9c02d,Those Virtual People all Look the Same to me: Computer-Rendered Faces Elicit a Higher False Alarm Rate Than Real Human Faces in a Recognition Memory Task,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
+ec5f89e822d9fcbc7b7422dc401478fc29f9c02d,Those Virtual People all Look the Same to me: Computer-Rendered Faces Elicit a Higher False Alarm Rate Than Real Human Faces in a Recognition Memory Task,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+ec3472acc24fe5ef9eb07a31697f2cd446c8facc,"PixelNet: Representation of the pixels, by the pixels, and for the pixels",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - Recent Deep Learning Approaches,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - Recent Deep Learning Approaches,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - Recent Deep Learning Approaches,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
@@ -1476,98 +4090,283 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 4e7ed13e541b8ed868480375785005d33530e06d,Face recognition using deep multi-pose representations,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
4e7ed13e541b8ed868480375785005d33530e06d,Face recognition using deep multi-pose representations,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
4e7ed13e541b8ed868480375785005d33530e06d,Face recognition using deep multi-pose representations,Open University,The Open University,"The Open University, East Lane, Walton, Monkston, Milton Keynes, South East, England, MK7 6AE, UK",52.02453775,-0.70927481,edu,
+4e1ade72128a6e530577dbbe69bd0afa0ef0e140,Pose Partition Networks for Multi-person Pose Estimation,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+4e1ade72128a6e530577dbbe69bd0afa0ef0e140,Pose Partition Networks for Multi-person Pose Estimation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+4e8b61165c8908284619acc62c46c7afac85d8a0,Deep unsupervised multi-view detection of video game stream highlights,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+4e8b61165c8908284619acc62c46c7afac85d8a0,Deep unsupervised multi-view detection of video game stream highlights,"London, United Kingdom","London, United Kingdom","London, Greater London, England, SW1A 2DU, UK",51.50732190,-0.12764740,edu,
+4e8b61165c8908284619acc62c46c7afac85d8a0,Deep unsupervised multi-view detection of video game stream highlights,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+4e8b61165c8908284619acc62c46c7afac85d8a0,Deep unsupervised multi-view detection of video game stream highlights,"London, United Kingdom","London, United Kingdom","London, Greater London, England, SW1A 2DU, UK",51.50732190,-0.12764740,edu,
+4eba5f6824f29533e0cd2660e49f2699c7e6501f,Gradient Band-based Adversarial Training for Generalized Attack Immunity of A3C Path Finding,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
4e30107ee6a2e087f14a7725e7fc5535ec2f5a5f,Представление новостных сюжетов с помощью событийных фотографий (News Stories Representation Using Event Photos),Lomonosov Moscow State University,Lomonosov Moscow State University,"МГУ, улица Академика Хохлова, Московский государственный университет им. М. В. Ломоносова, район Раменки, Западный административный округ, Москва, ЦФО, 119234, РФ",55.70229715,37.53179777,edu,
4e5dc3b397484326a4348ccceb88acf309960e86,Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
4e5dc3b397484326a4348ccceb88acf309960e86,Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4e5dc3b397484326a4348ccceb88acf309960e86,Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+4e9dd2f7982dc71db5505dba7d7264d263dd93d6,Learning a sequential search for landmarks,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
4e6c17966efae956133bf8f22edeffc24a0470c1,Face Classification: A Specialized Benchmark Study,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
4e6c17966efae956133bf8f22edeffc24a0470c1,Face Classification: A Specialized Benchmark Study,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
4e6c17966efae956133bf8f22edeffc24a0470c1,Face Classification: A Specialized Benchmark Study,Macau University of Science and Technology,Macau University of Science and Technology,"Universidade de Ciência e Tecnologia de Macau 澳門科技大學 Macau University of Science and Technology, 偉龍馬路 Avenida Wai Long, 氹仔Taipa, 氹仔舊城區 Vila de Taipa, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, 澳門 Macau, 853, 中国",22.15263985,113.56803206,edu,
4e1836914bbcf94dc00e604b24b1b0d6d7b61e66,Dynamic Facial Expression Recognition Using Boosted Component-Based Spatiotemporal Features and Multi-classifier Fusion,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
4e1836914bbcf94dc00e604b24b1b0d6d7b61e66,Dynamic Facial Expression Recognition Using Boosted Component-Based Spatiotemporal Features and Multi-classifier Fusion,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+4ed4143034fc6303737c7ad5118a72d9a5d12cf2,Web Survey Gamification - Increasing Data Quality in Web Surveys by using Game Design Elements,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+4ed4143034fc6303737c7ad5118a72d9a5d12cf2,Web Survey Gamification - Increasing Data Quality in Web Surveys by using Game Design Elements,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+4ed4143034fc6303737c7ad5118a72d9a5d12cf2,Web Survey Gamification - Increasing Data Quality in Web Surveys by using Game Design Elements,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
4e4fa167d772f34dfffc374e021ab3044566afc3,Learning Low-Rank Representations with Classwise Block-Diagonal Structure for Robust Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
4e4fa167d772f34dfffc374e021ab3044566afc3,Learning Low-Rank Representations with Classwise Block-Diagonal Structure for Robust Face Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
4e4fa167d772f34dfffc374e021ab3044566afc3,Learning Low-Rank Representations with Classwise Block-Diagonal Structure for Robust Face Recognition,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+4e5e6d405331aa4aafc88e3ab31c7f45720c00b2,Pose Tolerant Surface Alignment for 3D Face Verification with Symmetry Test Reject Option,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
4ed54d5093d240cc3644e4212f162a11ae7d1e3b,Learning Visual Compound Models from Parallel Image-Text Datasets,Bielefeld University,Bielefeld University,"Fachhochschule Bielefeld FB Gestaltung, 3, Lampingstraße, Mitte, Bielefeld, Regierungsbezirk Detmold, Nordrhein-Westfalen, 33615, Deutschland",52.02804210,8.51148270,edu,
4ed54d5093d240cc3644e4212f162a11ae7d1e3b,Learning Visual Compound Models from Parallel Image-Text Datasets,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+4efaa2a1a14ba6e8bea779eae49d6220fc771f2a,"Individual Differences in the Speed of Facial Emotion Recognition Show Little Specificity but Are Strongly Related with General Mental Speed: Psychometric, Neural and Genetic Evidence",Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+4efaa2a1a14ba6e8bea779eae49d6220fc771f2a,"Individual Differences in the Speed of Facial Emotion Recognition Show Little Specificity but Are Strongly Related with General Mental Speed: Psychometric, Neural and Genetic Evidence",University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+4efaa2a1a14ba6e8bea779eae49d6220fc771f2a,"Individual Differences in the Speed of Facial Emotion Recognition Show Little Specificity but Are Strongly Related with General Mental Speed: Psychometric, Neural and Genetic Evidence",Universität Hamburg,Universität Hamburg,"Informatikum, 30, Vogt-Kölln-Straße, Stellingen, Eimsbüttel, Hamburg, 22527, Deutschland",53.59948200,9.93353436,edu,
4e8c608fc4b8198f13f8a68b9c1a0780f6f50105,How Related Exemplars Help Complex Event Detection in Web Videos?,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
4e8c608fc4b8198f13f8a68b9c1a0780f6f50105,How Related Exemplars Help Complex Event Detection in Web Videos?,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
4e8c608fc4b8198f13f8a68b9c1a0780f6f50105,How Related Exemplars Help Complex Event Detection in Web Videos?,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4e559f23bcf502c752f2938ad7f0182047b8d1e4,A Fast Approximate AIB Algorithm for Distributional Word Clustering,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
4ed2d7ecb34a13e12474f75d803547ad2ad811b2,Common Action Discovery and Localization in Unconstrained Videos,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+4ee9efbeb26f684557fd8d39afc8e90e9958a495,Multimodal Unsupervised Image-to-Image Translation,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
4e8168fbaa615009d1618a9d6552bfad809309e9,Deep Convolutional Neural Network Features and the Original Image,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
4e8168fbaa615009d1618a9d6552bfad809309e9,Deep Convolutional Neural Network Features and the Original Image,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+4e370791915e4b56603451b4fd1bd0105f1bcefb,Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+4e370791915e4b56603451b4fd1bd0105f1bcefb,Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+4e370791915e4b56603451b4fd1bd0105f1bcefb,Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+4e99eaf58aa5fb4665dffec0009e2464feb0f66c,An Indexing Method for Efficient Model-Based Search,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
4e0636a1b92503469b44e2807f0bb35cc0d97652,Adversarial Localization Network,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
4e0636a1b92503469b44e2807f0bb35cc0d97652,Adversarial Localization Network,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
4e0636a1b92503469b44e2807f0bb35cc0d97652,Adversarial Localization Network,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+4eb2903ecfc5dee98c5671c9459bcea71c59c79d,Appearance-Based 3D Gaze Estimation with Personal Calibration,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+4efb9e426e349968523e1b1cdbbdbfd3e1912f84,Mean Box Pooling: A Rich Image Representation and Output Embedding for the Visual Madlibs Task,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+4e29533438d5c612ab24b80c840446eafcb5995f,Tradeoffs in Neural Variational Inference,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
4ea4116f57c5d5033569690871ba294dc3649ea5,Multi-View Face Alignment Using 3D Shape Model for View Estimation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+4ea9bfcb7791cc07882f78b4747b8c8064ec6f7d,Exemplar Cut,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+4e47a5eee68b2828bf7d36e7ef70e1d0f6920678,Analysis of the CMU Localization Algorithm Under Varied Conditions,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+4e47a5eee68b2828bf7d36e7ef70e1d0f6920678,Analysis of the CMU Localization Algorithm Under Varied Conditions,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4e4d034caa72dce6fca115e77c74ace826884c66,Sex differences in facial emotion recognition across varying expression intensity levels from videos,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+4e2873a2ea525507f5cd08e54ba363b06bc10e0a,Multi-Modal Information Extraction in a Question-Answer Framework,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+4e2873a2ea525507f5cd08e54ba363b06bc10e0a,Multi-Modal Information Extraction in a Question-Answer Framework,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+4e2873a2ea525507f5cd08e54ba363b06bc10e0a,Multi-Modal Information Extraction in a Question-Answer Framework,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+4ed613b6f0427d3ec4cad6c51dcc451786812959,Spatio-Temporal Attention Models for Grounded Video Captioning,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+4e614e344ecbb36770d45fc14d3b5152b653aa97,Exploration on Grounded Word Embedding: Matching Words and Images with Image-Enhanced Skip-Gram Model,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+4ed727bfef7d61023d391fdcb95cfa1df901be5e,Face Recognition using Simplified Probabilistic Linear Discriminant Analysis,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+4e4ba3783e7fe7dcf4a3b4de1fe1d5b603029f3a,Efficient Iris Spoof Detection via Boosted Local Binary Patterns,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+4e39951c2f8b4600239dec7e10b7ee1ba3a000dd,The Body as a Tool for Anger Awareness—Differential Effects of Angry Facial and Bodily Expressions on Suppression from Awareness,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
+4e71ac257b104bbc161331ab2a66e86515427146,Deep Bimodal Regression for Apparent Personality Analysis,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+4e6305b9c9ec58db62548c666357521fb4b3f6f9,Iterative Crowd Counting,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+4e91defcc0b5ddf18fa70c34d91ce94a0be0f4d7,Causalgan: Learning Causal Implicit Gener-,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+4e6ee936eb50dd032f7138702fa39b7c18ee8907,The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+4e6ee936eb50dd032f7138702fa39b7c18ee8907,The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+2081f94fb82ab8d05ca92742fe949fc97147f926,CoQA: A Conversational Question Answering Challenge,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+205e895e03969c96f3c482b0bd26308b16a12bd0,Image Captioning with an Intermediate Attributes Layer,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+20d397c8d8865133ca7bbbd824e217e9fbf5a51a,Binarized Convolutional Neural Networks for Efficient Inference on GPUs,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+20d17ffeb8adcbbe7cfe7b73cc998a1d20a91553,Unsupervised Class-Specific Deblurring,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+20f8057b602ae9e24ef4ee436250f35dd9757327,AMNet: Memorability Estimation with Attention,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
20b994a78cd1db6ba86ea5aab7211574df5940b3,Enriched Long-Term Recurrent Convolutional Network for Facial Micro-Expression Recognition,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
20b994a78cd1db6ba86ea5aab7211574df5940b3,Enriched Long-Term Recurrent Convolutional Network for Facial Micro-Expression Recognition,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
20b994a78cd1db6ba86ea5aab7211574df5940b3,Enriched Long-Term Recurrent Convolutional Network for Facial Micro-Expression Recognition,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
2050847bc7a1a0453891f03aeeb4643e360fde7d,Accio: A Data Set for Face Track Retrieval in Movies Across Age,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
2050847bc7a1a0453891f03aeeb4643e360fde7d,Accio: A Data Set for Face Track Retrieval in Movies Across Age,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+2056fb4cfe4aaa8a5d833f7494589499c2c5e8f5,Dependent Choices in Employee Selection: Modeling Choice Compensation and Consistency,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+2056fb4cfe4aaa8a5d833f7494589499c2c5e8f5,Dependent Choices in Employee Selection: Modeling Choice Compensation and Consistency,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+2088d93e7f4fa27b8498428d2ed64f144ab8cf3e,Deep Regression Tracking with Shrinkage Loss,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+2088d93e7f4fa27b8498428d2ed64f144ab8cf3e,Deep Regression Tracking with Shrinkage Loss,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+20044724665208227ad54d9ea98b08dfb1420689,Evaluation of local features for person re-identification in image sequences,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
20a16efb03c366fa4180659c2b2a0c5024c679da,Screening Rules for Overlapping Group Lasso,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+20da5315cfe5eab69d99bbda270e73ab488a49ba,Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+20da5315cfe5eab69d99bbda270e73ab488a49ba,Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+20da5315cfe5eab69d99bbda270e73ab488a49ba,Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+20da5315cfe5eab69d99bbda270e73ab488a49ba,Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+203ea8ab1d9c48977be97e6caf3fdbcc84101354,Video Segmentation by Tracking Many Figure-Ground Segments,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
20e505cef6d40f896e9508e623bfc01aa1ec3120,Fast Online Incremental Attribute-based Object Classification using Stochastic Gradient Descent and Self- Organizing Incremental Neural Network,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
205e4d6e0de81c7dd6c83b737ffdd4519f4f7ffa,A model-based facial expression recognition algorithm using Principal Components Analysis,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+20adfee9f931b48ad6ae236dc50b8106573d03f7,"AREA Annotation , Recognition and Evaluation of Actions PROCEEDINGS",University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
20b437dc4fc44c17f131713ffcbb4a8bd672ef00,Head Pose Tracking from RGBD Sensor Based on Direct Motion Estimation,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
206e24f7d4b3943b35b069ae2d028143fcbd0704,Learning Structure and Strength of CNN Filters for Small Sample Size Training,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+2068f66a10254d457cdb5fab74b0128b24bfdb65,Learning Language-Visual Embedding for Movie Understanding with Natural-Language,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+20dbdf02497aa84510970d0f5e8b599073bca1bc,Ask Me Anything: Free-Form Visual Question Answering Based on Knowledge from External Sources,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+20fa38fca576d983b1658127d5cf058962b23179,Image as Data: Automated Visual Content Analysis for Political Science,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
208a2c50edb5271a050fa9f29d3870f891daa4dc,The resolution of facial expressions of emotion.,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
208a2c50edb5271a050fa9f29d3870f891daa4dc,The resolution of facial expressions of emotion.,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
207798603e3089a1c807c93e5f36f7767055ec06,Modeling the correlation between modality semantics and facial expressions,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
207798603e3089a1c807c93e5f36f7767055ec06,Modeling the correlation between modality semantics and facial expressions,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
207798603e3089a1c807c93e5f36f7767055ec06,Modeling the correlation between modality semantics and facial expressions,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2031b062f4c41f43a32835430b1d55a422baa564,VNect: real-time 3D human pose estimation with a single RGB camera,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
20be15dac7d8a5ba4688bf206ad24cab57d532d6,Face Shape Recovery and Recognition Using a Surface Gradient Based Statistical Model,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
2042aed660796b14925db17c0a8b9fbdd7f3ebac,Saliency in Crowd,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+20daf06cea3dbc0b92f7ba4adb8fe7d95d27455e,"Robust Face Recognition using Wavelet and DCT based Lighting Normalization, and Shifting-mean LDA",Kumamoto University,Kumamoto University,"熊本大学黒髪キャンパス, 熊本菊陽線, 中央区, 熊本市, 熊本県, 九州地方, 860-0863, 日本",32.81641780,130.72703969,edu,
+20daf06cea3dbc0b92f7ba4adb8fe7d95d27455e,"Robust Face Recognition using Wavelet and DCT based Lighting Normalization, and Shifting-mean LDA",Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+20b5cfa2d35ff437bcc81d4c7f82f8b1f69dcec3,Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Input,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+2011d4da646f794456bebb617d1500ddf71989ed,Transductive Centroid Projection for Semi-supervised Large-Scale Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2011d4da646f794456bebb617d1500ddf71989ed,Transductive Centroid Projection for Semi-supervised Large-Scale Recognition,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+20d320529adf99aff7ca7bd562123caeaa8e7af7,Faithful Multimodal Explanation for Visual Question Answering,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+203a1ecdf7e488d81e5661a6735b767c4fe2b37d,Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+203a1ecdf7e488d81e5661a6735b767c4fe2b37d,Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
202dc3c6fda654aeb39aee3e26a89340fb06802a,Spatio-Temporal Instance Learning: Action Tubes from Class Supervision,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
20ebbcb6157efaacf7a1ceb99f2f3e2fdf1384e6,Comparative Assessment of Independent Component Analysis (ICA) for Face Recognition,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+20405902028e631e239cbc0ff6148f5f1d8050a0,Sherlock: Modeling Structured Knowledge in Images,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+207e0ac5301a3c79af862951b70632ed650f74f7,Learning a Discriminative Null Space for Person Re-identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+20b4a81c0aeafb891f9888797eac78e242db9aeb,"Affective Computing and Interaction : Psychological , Cognitive and Neuroscientific Perspectives",Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+20b4a81c0aeafb891f9888797eac78e242db9aeb,"Affective Computing and Interaction : Psychological , Cognitive and Neuroscientific Perspectives",Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+20388099cc415c772926e47bcbbe554e133343d1,The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+20388099cc415c772926e47bcbbe554e133343d1,The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+20523cbb076af203ae2a293074a0445fe95309e9,Classification of weather situations on single color images,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
+20b038c50cc7148dfb364e2de51cde120c907c9f,Integrated perception with recurrent multi-task neural networks,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+205cbac63de77af22e003c0c98c1a4a351747708,Attribute Guided Dictionary Learning,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+205cbac63de77af22e003c0c98c1a4a351747708,Attribute Guided Dictionary Learning,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+205cbac63de77af22e003c0c98c1a4a351747708,Attribute Guided Dictionary Learning,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
20cfb4136c1a984a330a2a9664fcdadc2228b0bc,Sparse Coding Trees with application to emotion classification,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
20c02e98602f6adf1cebaba075d45cef50de089f,Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
20c02e98602f6adf1cebaba075d45cef50de089f,Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
20c02e98602f6adf1cebaba075d45cef50de089f,Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
2020e8c0be8fa00d773fd99b6da55029a6a83e3d,An Evaluation of the Invariance Properties of a Biologically-Inspired System for Unconstrained Face Recognition,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+209df2d7724bc6defe87618b502e1d7c800a819f,Beyond KernelBoost,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+20289282fedfd60d9d4a7153f460f5c8e0a502b8,Goal Driven Detection in Natural Scenes,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+189619de93e83cdc26e275bc7652463328ab3f5c,Privacy-Aware Database System for Retrieving Facial Images,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
189b1859f77ddc08027e1e0f92275341e5c0fdc6,Sparse Representations and Distance Learning for Attribute Based Category Recognition,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
18a9f3d855bd7728ed4f988675fa9405b5478845,An Illumination Invariant Texture Based Face Recognition,Manonmaniam Sundaranar University,Manonmaniam Sundaranar University,"Manonmaniam Sundaranar University, Tenkasi-Tirunelveli, Gandhi Nagar, Tirunelveli, Tirunelveli Kattabo, Tamil Nadu, 627808, India",8.76554685,77.65100445,edu,
18166432309000d9a5873f989b39c72a682932f5,Learning a Warped Subspace Model of Faces with Images of Unknown Pose and Illumination,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+1862f2df2e278505c9ca970f9c5a25ea3aeb9686,Merging Deep Neural Networks for Mobile Devices,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
+18095a530b532a70f3b615fef2f59e6fdacb2d84,Deep Structured Scene Parsing by Learning with Image Descriptions,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+18095a530b532a70f3b615fef2f59e6fdacb2d84,Deep Structured Scene Parsing by Learning with Image Descriptions,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
18c6c92c39c8a5a2bb8b5673f339d3c26b8dcaae,Learning invariant representations and applications to face verification,McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
18c6c92c39c8a5a2bb8b5673f339d3c26b8dcaae,Learning invariant representations and applications to face verification,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+18dd8e04ecb5421b13aac39c288cd8dc3a541178,Unsupervised Selective Transfer Learning for Object Recognition,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+182496e9533ad3a5eef6a06b815a276c18eaea2e,High autistic trait individuals do not modulate gaze behaviour in response to social presence but look away more when actively engaged in an interaction,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+184c3e66a746376716d5e816d95e1a7cb8e04390,Unsupervised learning of a scene-specific coarse gaze estimator,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
185263189a30986e31566394680d6d16b0089772,Efficient Annotation of Objects for Video Analysis,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
-18b9dc55e5221e704f90eea85a81b41dab51f7da,Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+186d6d47855cb00c5bc99497932422b8963510cd,Image Retrieval with a Bayesian Model of Relevance Feedback,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+186d6d47855cb00c5bc99497932422b8963510cd,Image Retrieval with a Bayesian Model of Relevance Feedback,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+186370ecc1f05ef8d3f611873a039fcde3af68b5,Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152),University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+188e012533977266355bfabc62d6adbf0f92d6b1,Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+18b9dc55e5221e704f90eea85a81b41dab51f7da,Attention-Based Temporal Weighted Convolutional Neural Network for Action Recognition,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+18fe63c013983bea53be7d559ef36a1f385ca6ea,Supervision Beyond Human Annotations for Learning Visual Representations,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+185aaed9d48f42463791726f1ddf4e1be64a47d9,Person Re-Identification with Vision and Language,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+185aaed9d48f42463791726f1ddf4e1be64a47d9,Person Re-Identification with Vision and Language,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+185aaed9d48f42463791726f1ddf4e1be64a47d9,Person Re-Identification with Vision and Language,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+18078e72bddefffc24a6e882790aca8531773bed,Sublinear scaling of country attractiveness observed from Flickr dataset,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+18f70d8e1697bc0b85753db2d4d64aeb696b052a,Evolutionary Discriminant Feature Extraction with Application to Face Recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+18f70d8e1697bc0b85753db2d4d64aeb696b052a,Evolutionary Discriminant Feature Extraction with Application to Face Recognition,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+18c515d42666c95079f9a98eab59ac1cdfb10859,An ASM fitting method based on machine learning that provides a robust parameter initialization for AAM fitting,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
+18c515d42666c95079f9a98eab59ac1cdfb10859,An ASM fitting method based on machine learning that provides a robust parameter initialization for AAM fitting,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+180953265b3ad550682c8f0dc693eda87b82ec91,Thinking of Images as What They Are: Compound Matrix Regression for Image Classification,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+180953265b3ad550682c8f0dc693eda87b82ec91,Thinking of Images as What They Are: Compound Matrix Regression for Image Classification,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+183c8da12a07e2002fd71edbabeca5b3bfb45d66,Grounding Natural Language Instructions with Unknown Object References using Learned Visual Attributes,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
182470fd0c18d0c5979dff75d089f1da176ceeeb,A Multimodal Annotation Schema for Non-Verbal Affective Analysis in the Health-Care Domain,Ulm University,Ulm University,"HNU, John-F.-Kennedy-Straße, Vorfeld, Wiley, Neu-Ulm, Landkreis Neu-Ulm, Schwaben, Bayern, 89231, Deutschland",48.38044335,10.01010115,edu,
182470fd0c18d0c5979dff75d089f1da176ceeeb,A Multimodal Annotation Schema for Non-Verbal Affective Analysis in the Health-Care Domain,Information Technologies Institute,Information Technologies Institute,"公益財団法人九州先端科学技術研究所, Fukuoka SRP Center Building 7F, 百道ランプ下り入り口, 早良区, 福岡市, 福岡県, 九州地方, 814-0001, 日本",33.59345390,130.35578370,edu,
+18cf63b20521964f2115f6c939f70e582999bff5,Analysing False Positives and 3D Structure to Create Intelligent Thresholding and Weighting Functions for SIFT Features,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
1862cb5728990f189fa91c67028f6d77b5ac94f6,Speeding Up Tracking by Ignoring Features,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+18219d85bb14f851fc4714df19cc7f38dff8ddc3,Online Adaptation of Convolutional Neural Networks for the 2017 DAVIS Challenge on Video Object Segmentation,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
1862bfca2f105fddfc79941c90baea7db45b8b16,Annotator rationales for visual recognition,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
187d4d9ba8e10245a34f72be96dd9d0fb393b1aa,Mining Visual Actions from Movies,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
182f3aa4b02248ff9c0f9816432a56d3c8880706,Sparse Coding for Classification via Discrimination Ensemble,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+1839830486082578d2612e46a89e0e727ea1773a,Learning Hash Codes with Listwise Supervision,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+1839830486082578d2612e46a89e0e727ea1773a,Learning Hash Codes with Listwise Supervision,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+1839830486082578d2612e46a89e0e727ea1773a,Learning Hash Codes with Listwise Supervision,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+1839830486082578d2612e46a89e0e727ea1773a,Learning Hash Codes with Listwise Supervision,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+188951263d3140b3b5f5579e7a745317356e75ce,Face-space architectures: evidence for the use of independent color-based features.,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+18c57ddc9c0164ee792661f43a5578f7a00d0330,ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+187480101af3fb195993da1e2c17d917df24eb23,Unsupervised Visual Representation Learning by Context Prediction,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+187480101af3fb195993da1e2c17d917df24eb23,Unsupervised Visual Representation Learning by Context Prediction,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+18200e8db6fc63f16d5ed098b5abc17bf0939333,The Fastest Pedestrian Detector in the West,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+18200e8db6fc63f16d5ed098b5abc17bf0939333,The Fastest Pedestrian Detector in the West,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+18804d8e981fa66135c0ffa6fdb2b8b3fec6d753,Predicting human gaze beyond pixels.,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+18804d8e981fa66135c0ffa6fdb2b8b3fec6d753,Predicting human gaze beyond pixels.,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+18804d8e981fa66135c0ffa6fdb2b8b3fec6d753,Predicting human gaze beyond pixels.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+18804d8e981fa66135c0ffa6fdb2b8b3fec6d753,Predicting human gaze beyond pixels.,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+18804d8e981fa66135c0ffa6fdb2b8b3fec6d753,Predicting human gaze beyond pixels.,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+1875b2325b3efcb49dec51c6416f40862db4fe74,Functional abnormalities of the default network during self- and other-reflection in autism.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+18d8c54c1977f41b7ed71c1eeebf162298323c6f,Spatial Frequency Information Modulates Response Inhibition and Decision-Making Processes,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
18941b52527e6f15abfdf5b86a0086935706e83b,DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture Model,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+188d26a005b6aac1448b9c52529b93a186c33685,Predictive network with leveraging clinical measures as auxiliary task,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+188d26a005b6aac1448b9c52529b93a186c33685,Predictive network with leveraging clinical measures as auxiliary task,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+188d26a005b6aac1448b9c52529b93a186c33685,Predictive network with leveraging clinical measures as auxiliary task,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+18e1863e70cc93759a041b8aa745d0c0da51ad31,IBVis: Interactive Visual Analytics for Information Bottleneck Based Trajectory Clustering,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+181d0534f2c0233804a6f90c75c919d868fd58e1,Distinguishing Posed and Spontaneous Smiles by Facial Dynamics,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+18ab9be9af94f2bf4d3828161ffb232d1462526a,SHaPE: A Novel Graph Theoretic Algorithm for Making Consensus-Based Decisions in Person Re-identification Systems,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+18ab9be9af94f2bf4d3828161ffb232d1462526a,SHaPE: A Novel Graph Theoretic Algorithm for Making Consensus-Based Decisions in Person Re-identification Systems,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+18ced9c7bab4d7fa69ccf2d3c8783317ba94e59f,Pitfalls in Designing Zero-Effort Deauthentication: Opportunistic Human Observation Attacks,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+18193194b7000f442c9df5ab16735a1f3ccbb630,Do Explanations make VQA Models more Predictable to a Human?,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+18aaeaba26d95482fc40d560c49f0a7f22ea0870,Automatic Detection of Learning-Centered Affective States in the Wild,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+18aaeaba26d95482fc40d560c49f0a7f22ea0870,Automatic Detection of Learning-Centered Affective States in the Wild,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+18aaeaba26d95482fc40d560c49f0a7f22ea0870,Automatic Detection of Learning-Centered Affective States in the Wild,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+277c41ce2a485f09a842d793e599553ad751d34a,Robust Person Detection by Classifier Cubes and Local Verification,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+2744d19a3026a516431ad92f1b60a9237aa2ef6d,"The Development of Visuo-spatial Processing in Children with Autism, down Syndrome and Williams Syndrome",University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+2744d19a3026a516431ad92f1b60a9237aa2ef6d,"The Development of Visuo-spatial Processing in Children with Autism, down Syndrome and Williams Syndrome",University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
27a00f2490284bc0705349352d36e9749dde19ab,VoxCeleb2: Deep Speaker Recognition,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
271e2856e332634eccc5e80ba6fa9bbccf61f1be,3D Spatio-Temporal face recognition using dynamic range model sequences,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
+27b9e75bcaf9e12127f7181bcb7f1fcb105462c4,Local frequency descriptor for low-resolution face recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+27b9e75bcaf9e12127f7181bcb7f1fcb105462c4,Local frequency descriptor for low-resolution face recognition,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+272b364f0ed647dbdbc4ae80f10ddaf8ada3a07d,A Novel Method for Tracking Individuals of Fruit Fly Swarms Flying in a Laboratory Flight Arena,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
27846b464369095f4909f093d11ed481277c8bba,Real-Time Face Detection and Recognition in Complex Background,Illinois Institute of Technology,Illinois Institute of Technology,"Illinois Institute of Technology, South State Street, Bronzeville, Chicago, Cook County, Illinois, 60616, USA",41.83619630,-87.62655913,edu,
27eb7a6e1fb6b42516041def6fe64bd028b7614d,Joint Unsupervised Deformable Spatio-Temporal Alignment of Sequences,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
27eb7a6e1fb6b42516041def6fe64bd028b7614d,Joint Unsupervised Deformable Spatio-Temporal Alignment of Sequences,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
2717998d89d34f45a1cca8b663b26d8bf10608a9,Real-Time Action Recognition with Enhanced Motion Vector CNNs,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
2717998d89d34f45a1cca8b663b26d8bf10608a9,Real-Time Action Recognition with Enhanced Motion Vector CNNs,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+27405836469652ca9bfaf948c0c9dadd6465a566,"The Use of Lexical Basis Functions to Characterize Faces, and to Measure Their Perceived Similarity",Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
27c66b87e0fbb39f68ddb783d11b5b7e807c76e8,Fast Simplex-HMM for One-Shot Learning Activity Recognition,Zaragoza University,Zaragoza University,"Colegio Mayor Universitario Santa Isabel, Calle de Domingo Miral, Romareda, Zaragoza, Aragón, 50009, España",41.64062180,-0.90079399,edu,
27c66b87e0fbb39f68ddb783d11b5b7e807c76e8,Fast Simplex-HMM for One-Shot Learning Activity Recognition,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
+279edb192f630f057516d8e56eae61713b6a1895,"SfSNet : Learning Shape, Reflectance and Illuminance of Faces in the Wild",University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+2753c410a4072d40a8eea5de392414999b7f4b6a,Deep Convolutional Poses for Human Interaction Recognition in Monocular Videos,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+27eb092a9adbfcb3aea1b13bde580f1fd5c7b8f0,xytocin Increases Gaze to the Eye Region f Human Faces dam,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+27eb092a9adbfcb3aea1b13bde580f1fd5c7b8f0,xytocin Increases Gaze to the Eye Region f Human Faces dam,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+27fb07897db51ce23db4ef93e2621717ee1db64c,Affect Infusion and Detection through Faces in Computer-mediated Knowledge-sharing Decisions,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
+27c4369463ff28f4ab16e9d9eba6f48102c8793e,Triangle Generative Adversarial Networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
271df16f789bd2122f0268c3e2fa46bc0cb5f195,Mining discriminative co-occurrence patterns for visual recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
271df16f789bd2122f0268c3e2fa46bc0cb5f195,Mining discriminative co-occurrence patterns for visual recognition,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+27ccf0cdf0c7a74640697dfb5d1cf85969a5da2e,Multilingual Image Description with Neural Sequence Models,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+27ccf0cdf0c7a74640697dfb5d1cf85969a5da2e,Multilingual Image Description with Neural Sequence Models,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
275b5091c50509cc8861e792e084ce07aa906549,Leveraging the User's Face as a Known Object in Handheld Augmented Reality,University of Munich,Universität München,"Geschwister-Scholl-Platz 1, 80539 München, Germany",48.15080600,11.58043000,edu,
27218ff58c3f0e7d7779fba3bb465d746749ed7c,Active Learning for Image Ranking Over Relative Visual Attributes,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+270f029b03ee1bdfeae4ff4c5167b450d185a981,Combining local appearance and holistic view: Dual-Source Deep Neural Networks for human pose estimation,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
+272c6b6ccf144954a154b83bf5789341ee3f9ed2,A brain-computer interface for potential non-verbal facial communication based on EEG signals related to specific emotions,University of Tokushima,The University of Tokushima,"大学前, 国道11号, 徳島市, 徳島県, 四国地方, 770-0815, 日本",34.07880680,134.55898100,edu,
+272c6b6ccf144954a154b83bf5789341ee3f9ed2,A brain-computer interface for potential non-verbal facial communication based on EEG signals related to specific emotions,University of Tokushima,The University of Tokushima,"大学前, 国道11号, 徳島市, 徳島県, 四国地方, 770-0815, 日本",34.07880680,134.55898100,edu,
27c6cd568d0623d549439edc98f6b92528d39bfe,Regressive Tree Structured Model for Facial Landmark Localization,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
+2788f382e4396290acfc8b21df45cc811586e66e,Deep Attributes Driven Multi-camera Person Re-identification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+2788f382e4396290acfc8b21df45cc811586e66e,Deep Attributes Driven Multi-camera Person Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+2788f382e4396290acfc8b21df45cc811586e66e,Deep Attributes Driven Multi-camera Person Re-identification,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
273b0511588ab0a81809a9e75ab3bd93d6a0f1e3,Recognition of facial expressions based on salient geometric features and support vector machines,Korea Electronics Technology Institute,Korea Electronics Technology Institute,"South Korea, Gyeonggi-do, Seongnam-si, Bundang-gu, 새나리로 25 (야탑동) KETI 전자부품연구원",37.40391700,127.15978600,edu,
273b0511588ab0a81809a9e75ab3bd93d6a0f1e3,Recognition of facial expressions based on salient geometric features and support vector machines,Chonbuk National University,Chonbuk National University,"전북대학교, 567, 백제대로, 금암동, 덕진구, 전주시, 전북, 54896, 대한민국",35.84658875,127.13501330,edu,
273b0511588ab0a81809a9e75ab3bd93d6a0f1e3,Recognition of facial expressions based on salient geometric features and support vector machines,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
27961bc8173ac84fdbecacd01e5ed6f7ed92d4bd,Automatic multi-view face recognition via 3D model based pose regularization,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+2776d11afa421ec7403606f902dc757de95583b2,Label Propagation from ImageNet to 3D Point Clouds,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
2784d9212dee2f8a660814f4b85ba564ec333720,Learning class-specific image transformations with higher-order Boltzmann machines,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
2717b044ae9933f9ab87f16d6c611352f66b2033,GNAS: A Greedy Neural Architecture Search Method for Multi-Attribute Learning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+279acfde0286bb76dd7717abebc3c8acf12d2c5f,Local Gradient Order Pattern for Face Representation and Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+27d90cdd54bcc8f8ecfa60d886143288977a5c63,On the possibility of instance-based stroke recovery,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+274e8c0c513ff82713f2f332694cf2b29b7c3bb1,0 Multi Channel-Kernel Canonical Correlation Analysis for Cross-View Person Re-Identification,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+274e8c0c513ff82713f2f332694cf2b29b7c3bb1,0 Multi Channel-Kernel Canonical Correlation Analysis for Cross-View Person Re-Identification,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+274e8c0c513ff82713f2f332694cf2b29b7c3bb1,0 Multi Channel-Kernel Canonical Correlation Analysis for Cross-View Person Re-Identification,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+274e8c0c513ff82713f2f332694cf2b29b7c3bb1,0 Multi Channel-Kernel Canonical Correlation Analysis for Cross-View Person Re-Identification,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+27bcdd21f1be3d0990f86a231d29d46a5537e5cd,Rendering Portraitures from Monocular Camera and Beyond,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+27bcdd21f1be3d0990f86a231d29d46a5537e5cd,Rendering Portraitures from Monocular Camera and Beyond,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+274959f26d04848f71a355c09500fd7ebc271d69,Two-Stream Flow-Guided Convolutional Attention Networks for Action Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
27883967d3dac734c207074eed966e83afccb8c3,Two-Dimensional Maximum Local Variation Based on Image Euclidean Distance for Face Recognition,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
27883967d3dac734c207074eed966e83afccb8c3,Two-Dimensional Maximum Local Variation Based on Image Euclidean Distance for Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
270e5266a1f6e76954dedbc2caf6ff61a5fbf8d0,EmotioNet Challenge: Recognition of facial expressions of emotion in the wild,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
2742a61d32053761bcc14bd6c32365bfcdbefe35,Learning transformations for clustering and classification,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
2742a61d32053761bcc14bd6c32365bfcdbefe35,Learning transformations for clustering and classification,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+2781de1aa6f4c9621ad3af38fc58b894696f1791,FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+2781de1aa6f4c9621ad3af38fc58b894696f1791,FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+27c6b0883e51ec901e587963070eb2ad96871a33,Performance Modeling of Multithreaded Programs for Mobile Asymmetric Chip Multiprocessors,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+27c6b0883e51ec901e587963070eb2ad96871a33,Performance Modeling of Multithreaded Programs for Mobile Asymmetric Chip Multiprocessors,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+2788a2461ed0067e2f7aaa63c449a24a237ec341,Random Erasing Data Augmentation,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
27dafedccd7b049e87efed72cabaa32ec00fdd45,Unsupervised visual alignment with similarity graphs,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+273b9b7c63ac9196fb12734b49b74d0523ca4df4,The Secrets of Salient Object Segmentation,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+273b9b7c63ac9196fb12734b49b74d0523ca4df4,The Secrets of Salient Object Segmentation,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+27caf667432ad7dbb01921696857303641b34f83,Entropy Driven Hierarchical Search for 3D Human Pose Estimation,Swansea University,Swansea University,"Swansea University, University Footbridge, Sketty, Swansea, Wales, SA2 8PZ, UK",51.60915780,-3.97934429,edu,
+273dc39c3e7a18aac3cbd5f2db93969e9cc7613f,Exemplar-based Human Interaction Recognition: Features and Key Pose Sequence Model,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
27a299b834a18e45d73e0bf784bbb5b304c197b3,Social Role Discovery in Human Events,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
27a299b834a18e45d73e0bf784bbb5b304c197b3,Social Role Discovery in Human Events,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+277bfd1bc89044b4a523ef23f48bd053d5560657,Large-Scale Object Discovery and Detector Adaptation from Unlabeled Video,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+2701bd6850dc1b811ef7697cc1cd19405b99f990,Privacy Preserving Multi-target Tracking,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+4b1682da96af72ce0ddaa9384ce294611807a8b3,Graph Distillation for Action Detection with Privileged Information,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+4bab23e4ce9b6c65a067953fe202c20c387f00c8,Sparse Patch-Histograms for Object Classification in Cluttered Images,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+4b70374555c32c6a1e0db43674a7183170083450,Kernelized View Adaptive Subspace Learning for Person Re-identification,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+4b70374555c32c6a1e0db43674a7183170083450,Kernelized View Adaptive Subspace Learning for Person Re-identification,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+4b70374555c32c6a1e0db43674a7183170083450,Kernelized View Adaptive Subspace Learning for Person Re-identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4b8d80f91d271f61b26db5ad627e24e59955c56a,Learning Long-Range Vision for an Offroad Robot,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+4b8d80f91d271f61b26db5ad627e24e59955c56a,Learning Long-Range Vision for an Offroad Robot,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
4bb03b27bc625e53d8d444c0ba3ee235d2f17e86,Reading between the Lines: Object Localization Using Implicit Cues from Image Tags,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+4b39b981133a91052956cc42d2967f349a95cd89,Towards Understanding Articulated Objects,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
4bc9a767d7e63c5b94614ebdc24a8775603b15c9,Understanding Visual Information: from Unsupervised Discovery to Minimal Effort Domain Adaptation,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
4b519e2e88ccd45718b0fc65bfd82ebe103902f7,A Discriminative Model for Age Invariant Face Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
4b519e2e88ccd45718b0fc65bfd82ebe103902f7,A Discriminative Model for Age Invariant Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
@@ -1577,11 +4376,28 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 4b7c110987c1d89109355b04f8597ce427a7cd72,Feature- and Face-Exchange illusions: new insights and applications for the study of the binding problem,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
4b7c110987c1d89109355b04f8597ce427a7cd72,Feature- and Face-Exchange illusions: new insights and applications for the study of the binding problem,American University,American University,"American University, 4400, Massachusetts Avenue Northwest, Spring Valley, American University Park, D.C., 20016, USA",38.93804505,-77.08939224,edu,
4bd088ba3f42aa1e43ae33b1988264465a643a1f,"IDE 0852 , May 2008 Multiview Face Detection Using Gabor Filters and Support Vector Machine",Halmstad University,Halmstad University,"Högskolan i Halmstad, 3, Kristian IV:s väg, Larsfrid, Nyhem, Halmstad, Hallands län, Götaland, 301 18, Sverige",56.66340325,12.87929727,edu,
+4b4d8169664dcfc87cf7ab68d4a49ecd160d89f3,The pursuit of social acceptance: aberrant conformity in social anxiety disorder,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+4b4d8169664dcfc87cf7ab68d4a49ecd160d89f3,The pursuit of social acceptance: aberrant conformity in social anxiety disorder,Beijing Normal University,Beijing Normal University,"北京师范大学, 19, 新街口外大街, 西城区, 100875, 中国",39.96014155,116.35970438,edu,
+4b4d8169664dcfc87cf7ab68d4a49ecd160d89f3,The pursuit of social acceptance: aberrant conformity in social anxiety disorder,Beijing Normal University,Beijing Normal University,"北京师范大学, 19, 新街口外大街, 西城区, 100875, 中国",39.96014155,116.35970438,edu,
+4b4d8169664dcfc87cf7ab68d4a49ecd160d89f3,The pursuit of social acceptance: aberrant conformity in social anxiety disorder,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+4b4d8169664dcfc87cf7ab68d4a49ecd160d89f3,The pursuit of social acceptance: aberrant conformity in social anxiety disorder,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
4bfce41cc72be315770861a15e467aa027d91641,Active Annotation Translation,University of Iceland,University of Iceland,"Háskóli Íslands, Sturlugata, Háskóli, Reykjavík, Reykjavíkurborg, Höfuðborgarsvæðið, 121, Ísland",64.13727400,-21.94561454,edu,
4b61d8490bf034a2ee8aa26601d13c83ad7f843a,A Modulation Module for Multi-task Learning with Applications in Image Retrieval,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
4b61d8490bf034a2ee8aa26601d13c83ad7f843a,A Modulation Module for Multi-task Learning with Applications in Image Retrieval,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4bd3de97b256b96556d19a5db71dda519934fd53,Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face Recognition,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
4bd3de97b256b96556d19a5db71dda519934fd53,Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+4b1abc5b52db2ba854101b137d1fe3aed9e21274,The role of dictionary learning on sparse representation-based classification,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+4b18303edf701e41a288da36f8f1ba129da67eb7,An embarrassingly simple approach to zero-shot learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+4b18303edf701e41a288da36f8f1ba129da67eb7,An embarrassingly simple approach to zero-shot learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+4b86e711658003a600666d3ccfa4a9905463df1c,Fusion of Appearance Image and Passive Stereo Depth Map for Face Recognition Based on the Bilateral 2DLDA,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+4b3c1af4369c9ed6714451643ef9c06969849e73,Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+4b3c1af4369c9ed6714451643ef9c06969849e73,Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4b3c1af4369c9ed6714451643ef9c06969849e73,Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4b421db0f57608470ac1e26077ecb8a6cdccade5,Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4b1e80211f34b731667a31f0f27937376866993a,Online Metric-Weighted Linear Representations for Robust Visual Tracking,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+4b1e80211f34b731667a31f0f27937376866993a,Online Metric-Weighted Linear Representations for Robust Visual Tracking,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+4ba3f9792954ee3ba894e1e330cd77da4668fa22,Nearest Neighbor Discriminant Analysis,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+4ba3f9792954ee3ba894e1e330cd77da4668fa22,Nearest Neighbor Discriminant Analysis,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
4b74f2d56cd0dda6f459319fec29559291c61bff,Person-Specific Subspace Analysis for Unconstrained Familiar Face Identification,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
4b74f2d56cd0dda6f459319fec29559291c61bff,Person-Specific Subspace Analysis for Unconstrained Familiar Face Identification,Rowland Institute,Rowland Institute,"Rowland Research Institute, Land Boulevard, East Cambridge, Cambridge, Middlesex County, Massachusetts, 02142, USA",42.36398620,-71.07782930,edu,
4b74f2d56cd0dda6f459319fec29559291c61bff,Person-Specific Subspace Analysis for Unconstrained Familiar Face Identification,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
@@ -1600,109 +4416,237 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 4b0a2937f64df66cadee459a32ad7ae6e9fd7ed2,"Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
4b4ecc1cb7f048235605975ab37bb694d69f63e5,Nonlinear Embedding Transform for Unsupervised Domain Adaptation,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
4be774af78f5bf55f7b7f654f9042b6e288b64bd,Variational methods for Conditional Multimodal Learning: Generating Human Faces from Attributes,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+4b004f3c524778d524bfb0cda923bc6e895f9ea9,Quantifying and Detecting Collective Motion by Manifold Learning,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+4b004f3c524778d524bfb0cda923bc6e895f9ea9,Quantifying and Detecting Collective Motion by Manifold Learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
4b321065f6a45e55cb7f9d7b1055e8ac04713b41,Affective Computing Models for Character Animation,Liverpool John Moores University,Liverpool John Moores University,"John Lennon Art and Design Building, Duckinfield Street, Knowledge Quarter, Liverpool, North West England, England, L3 5YD, UK",53.40507470,-2.97030029,edu,
4b605e6a9362485bfe69950432fa1f896e7d19bf,A Comparison of Human and Automated Face Verification Accuracy on Unconstrained Image Sets,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+4be79ee47771c670aa63bcdaff870f9dd8575a0d,phi-LSTM: A Phrase-based Hierarchical LSTM Model for Image Captioning,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
4b3dd18882ff2738aa867b60febd2b35ab34dffc,Facial Feature Analysis of Spontaneous Facial Expression,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
4b3dd18882ff2738aa867b60febd2b35ab34dffc,Facial Feature Analysis of Spontaneous Facial Expression,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
11a2ef92b6238055cf3f6dcac0ff49b7b803aee3,Towards reduction of the training and search running time complexities for non-rigid object segmentation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
11dc744736a30a189f88fa81be589be0b865c9fa,A Unified Multiplicative Framework for Attribute Learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
11dc744736a30a189f88fa81be589be0b865c9fa,A Unified Multiplicative Framework for Attribute Learning,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+114b34fd2a2a2acd4a968cbaeb5e0d2251fb2835,Combining Appearance and Structure from Motion Features for Road Scene Understanding,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
11a210835b87ccb4989e9ba31e7559bb7a9fd292,A fuzzy approximator with Gaussian membership functions to estimate a human's head pose,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
11a210835b87ccb4989e9ba31e7559bb7a9fd292,A fuzzy approximator with Gaussian membership functions to estimate a human's head pose,Ferdowsi University of Mashhad,Ferdowsi University of Mashhad,"دانشگاه فردوسی مشهد, بولوار دانش, رضاشهر, منطقه ۹, مشهد, شهرستان مشهد, استان خراسان رضوی, 9177146164, ایران",36.30766160,59.52690511,edu,
118ca3b2e7c08094e2a50137b1548ada7935e505,A Dataset To Evaluate The Representations Learned By Video Prediction Models,Toyota Research Institute,Toyota Research Institute,"Toyota Research Institute, 4440, West El Camino Real, Los Altos, Santa Clara County, California, 94022, USA",37.40253645,-122.11655107,edu,
11aa527c01e61ec3a7a67eef8d7ffe9d9ce63f1d,"Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.",California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
11aa527c01e61ec3a7a67eef8d7ffe9d9ce63f1d,"Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.",California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+111ac5d013ac59aa8da919a470cdf83b437f9721,Improved Class-Specific Codebook with Two-Step Classification for Scene-Level Classification of High Resolution Remote Sensing Images,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+114907f89466987b3c41c8d530e50b2ac67179cf,Face Identification by a Cascade of Rejection Classifiers,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
113c22eed8383c74fe6b218743395532e2897e71,MODEC: Multimodal Decomposable Models for Human Pose Estimation,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
11408af8861fb0a977412e58c1a23d61b8df458c,A robust learning algorithm based on SURF and PSM for facial expression recognition,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
11408af8861fb0a977412e58c1a23d61b8df458c,A robust learning algorithm based on SURF and PSM for facial expression recognition,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
11cc0774365b0cc0d3fa1313bef3d32c345507b1,Face Recognition Using Active Near-IR Illumination,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+117aae1dc5b3aee679a690f7dab84e9a23add930,Age and Video Captioning,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+115808104b2a9c3ab6e2e60582ab7e33b937b754,Visual7W: Grounded Question Answering in Images,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
11269e98f072095ff94676d3dad34658f4876e0e,Facial expression recognition with multithreaded cascade of rotation-invariant HOG,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
11269e98f072095ff94676d3dad34658f4876e0e,Facial expression recognition with multithreaded cascade of rotation-invariant HOG,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
11269e98f072095ff94676d3dad34658f4876e0e,Facial expression recognition with multithreaded cascade of rotation-invariant HOG,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+116170983869d56780343823621f2f30f62aa38e,"4D Cardiff Conversation Database (4D CCDb): a 4D database of natural, dyadic conversations",Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
113e5678ed8c0af2b100245057976baf82fcb907,Facing Imbalanced Data--Recommendations for the Use of Performance Metrics,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
113e5678ed8c0af2b100245057976baf82fcb907,Facing Imbalanced Data--Recommendations for the Use of Performance Metrics,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+117c7cf24b9310ed785ef6fb84e95c73186f61e6,Historical Heterogeneity Predicts Smiling: Evidence from Large-Scale Observational Analyses,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+117c7cf24b9310ed785ef6fb84e95c73186f61e6,Historical Heterogeneity Predicts Smiling: Evidence from Large-Scale Observational Analyses,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+113ced4a8c5ecb6da1b2eb63c1300cd8df982917,Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+113ced4a8c5ecb6da1b2eb63c1300cd8df982917,Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
11c04c4f0c234a72f94222efede9b38ba6b2306c,Real-time human action recognition by luminance field trajectory analysis,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
11c04c4f0c234a72f94222efede9b38ba6b2306c,Real-time human action recognition by luminance field trajectory analysis,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
1128a4f57148cec96c0ef4ae3b5a0fbf07efbad9,Action Recognition by Learning Deep Multi-Granular Spatio-Temporal Video Representation,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
1128a4f57148cec96c0ef4ae3b5a0fbf07efbad9,Action Recognition by Learning Deep Multi-Granular Spatio-Temporal Video Representation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
1128a4f57148cec96c0ef4ae3b5a0fbf07efbad9,Action Recognition by Learning Deep Multi-Granular Spatio-Temporal Video Representation,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+11824658170994e4d4655e8f688bace16a0d3e48,Multi-person Head Segmentation in Low Resolution Crowd Scenes Using Convolutional Encoder-Decoder Framework,Qatar University,Qatar University,"Qatar University, Roindabout 3, Al Tarfa (68), أم صلال, 24685, قطر",25.37461295,51.48980354,edu,
+11824658170994e4d4655e8f688bace16a0d3e48,Multi-person Head Segmentation in Low Resolution Crowd Scenes Using Convolutional Encoder-Decoder Framework,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+11138173fa5e72a6bba314881d8d5dd74c1ac83f,Optimizing Mean Reciprocal Rank for person re-identification,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+110e44112bb0b742ca2c8ee607fc359698ee1198,Semantic Label Sharing for Learning with Many Categories,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+110e44112bb0b742ca2c8ee607fc359698ee1198,Semantic Label Sharing for Learning with Many Categories,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+116888b8f08419f027f5047f0ff1557b16f69d5a,Fearful contextual expression impairs the encoding and recognition of target faces: an ERP study,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+116888b8f08419f027f5047f0ff1557b16f69d5a,Fearful contextual expression impairs the encoding and recognition of target faces: an ERP study,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+11a1e99fc65fb8567d7f52dce941231ea949db0a,Subgraph decomposition for multi-target tracking,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
11a47a91471f40af5cf00449954474fd6e9f7694,NIRFaceNet: A Convolutional Neural Network for Near-Infrared Face Identification,Southwest University,Southwest University,"西南大学, 天生路, 北碚区 (Beibei), 北碚区, 北碚区 (Beibei), 重庆市, 400711, 中国",29.82366295,106.42050016,edu,
+118e87ee5a8e0faa71b6ca5af6ff38f875132464,Pose Invariant Embedding for Deep Person Re-identification,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+11b45236b2798091ddab35c572a35f447bb8d717,The Case for Personal Data-Driven Decision Making,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+11a6af9b32a93c4053dc12f70afac64a4138b2d1,Multi-hypothesis motion planning for visual object tracking,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+11a6af9b32a93c4053dc12f70afac64a4138b2d1,Multi-hypothesis motion planning for visual object tracking,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+11fa5abb5d5d09efbf9dacae6a6ceb9b2647f877,DCTNet: A simple learning-free approach for face recognition,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
11b3877df0213271676fa8aa347046fd4b1a99ad,Unsupervised Identification of Multiple Objects of Interest from Multiple Images: dISCOVER,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1167136efcb52cf49e89b90949149312bab19cc3,Multi-camera Pedestrian Tracking using Group Structure,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+1167136efcb52cf49e89b90949149312bab19cc3,Multi-camera Pedestrian Tracking using Group Structure,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+1188c925d90e93a205c5fc15d11fb2ae02660f2e,Deep Photovoltaic Nowcasting,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
1130c38e88108cf68b92ecc61a9fc5aeee8557c9,Dynamically encoded actions based on spacetime saliency,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
11b89011298e193d9e6a1d99302221c1d8645bda,Structured Feature Selection,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+11fa30ccbf62a64f650844b9cc39797e5faa82d5,A Spatial and Temporal Features Mixture Model with Body Parts for Video-based Person Re-Identification,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+11fa30ccbf62a64f650844b9cc39797e5faa82d5,A Spatial and Temporal Features Mixture Model with Body Parts for Video-based Person Re-Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+111ae23b60284927f2545dfc59b0147bb3423792,Classroom Data Collection and Analysis using Computer Vision,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+11f476a5da2366cfa6e4b4e2654a0833fa7d4fa4,Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
1177977134f6663fff0137f11b81be9c64c1f424,Multi-manifold deep metric learning for image set classification,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
1177977134f6663fff0137f11b81be9c64c1f424,Multi-manifold deep metric learning for image set classification,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
1177977134f6663fff0137f11b81be9c64c1f424,Multi-manifold deep metric learning for image set classification,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
1177977134f6663fff0137f11b81be9c64c1f424,Multi-manifold deep metric learning for image set classification,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
1177977134f6663fff0137f11b81be9c64c1f424,Multi-manifold deep metric learning for image set classification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+11f515ead5b4a7259668f2620e808fa8ba5ea65c,Phrase Localization and Visual Relationship Detection with Comprehensive Image-Language Cues,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
1190cba0cae3c8bb81bf80d6a0a83ae8c41240bc,Squared Earth Mover ’ s Distance Loss for Training Deep Neural Networks on Ordered-Classes,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+114d6a2503847a72afeb38e79243ad10abc7e123,Building Unified Human Descriptors For Multi-Type Activity Recognition,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
11ac88aebe0230e743c7ea2c2a76b5d4acbfecd0,Hybrid Cascade Model for Face Detection in the Wild Based on Normalized Pixel Difference and a Deep Convolutional Neural Network,University of Zagreb,"University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia","Unska ul. 3, 10000, Zagreb, Croatia",45.80112100,15.97084090,edu,
117f164f416ea68e8b88a3005e55a39dbdf32ce4,Neuroaesthetics in fashion: Modeling the perception of fashionability,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+7d520f474f2fc59422d910b980f8485716ce0a3e,Designing Convolutional Neural Networks for Urban Scene Understanding,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+7d520f474f2fc59422d910b980f8485716ce0a3e,Designing Convolutional Neural Networks for Urban Scene Understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
7dda2eb0054eb1aeda576ed2b27a84ddf09b07d4,Face Recognition and Representation by Tensor-based MPCA Approach,Chosun University,Chosun University,"조선대역, 서남로, 남동, 동구, 광주, 61473, 대한민국",35.14410310,126.92578580,edu,
7d2556d674ad119cf39df1f65aedbe7493970256,Now You Shake Me : Towards Automatic 4 D Cinema,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
7d94fd5b0ca25dd23b2e36a2efee93244648a27b,Convolutional Network for Attribute-driven and Identity-preserving Human Face Generation,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
7d94fd5b0ca25dd23b2e36a2efee93244648a27b,Convolutional Network for Attribute-driven and Identity-preserving Human Face Generation,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
7d8c2d29deb80ceed3c8568100376195ce0914cb,Identity-Aware Textual-Visual Matching with Latent Co-attention,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
7d306512b545df98243f87cb8173df83b4672b18,Flag Manifolds for the Characterization of Geometric Structure in Large Data Sets,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+7db5404feaa08e3e53bbf4fea7d89bcf509cfdbd,An Enhanced Default Approach Bias Following Human Amygdala Lesions,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+7db5404feaa08e3e53bbf4fea7d89bcf509cfdbd,An Enhanced Default Approach Bias Following Human Amygdala Lesions,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+7d52c9da079a4929faa0b39d8acb92240eb3a1f4,Vision-based real estate price estimation,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+7d52c9da079a4929faa0b39d8acb92240eb3a1f4,Vision-based real estate price estimation,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+7d7b564aba3161231c789169cafec38342a18ea7,Forecasting user attention during everyday mobile interactions using device-integrated and wearable sensors,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+7d7b564aba3161231c789169cafec38342a18ea7,Forecasting user attention during everyday mobile interactions using device-integrated and wearable sensors,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+7d7b564aba3161231c789169cafec38342a18ea7,Forecasting user attention during everyday mobile interactions using device-integrated and wearable sensors,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+7d7b564aba3161231c789169cafec38342a18ea7,Forecasting user attention during everyday mobile interactions using device-integrated and wearable sensors,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
7d41b67a641426cb8c0f659f0ba74cdb60e7159a,Soft biometric retrieval to describe and identify surveillance images,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+7d7ab791ae3cfa72b4feacf1e09a4493c1a5a87c,Individualness and Determinantal Point Processes for Pedestrian Detection,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
7d1688ce0b48096e05a66ead80e9270260cb8082,Real vs. Fake Emotion Challenge: Learning to Rank Authenticity from Facial Activity Descriptors,Otto von Guericke University,Otto von Guericke University,"Otto-von-Guericke-Universität Magdeburg, 2, Universitätsplatz, Krökentorviertel/Breiter Weg NA, Alte Neustadt, Magdeburg, Sachsen-Anhalt, 39106, Deutschland",52.14005065,11.64471248,edu,
7d53678ef6009a68009d62cd07c020706a2deac3,Facial Feature Point Extraction Using the Adaptive Mean Shape in Active Shape Model,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
+7d2df9b943a666caa9154dbc1a0ba3dda8cf423b,Automatic extraction of facial interest points based on 2D and 3D data,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
7d7be6172fc2884e1da22d1e96d5899a29831ad2,L2GSCI: Local to Global Seam Cutting and Integrating for Accurate Face Contour Extraction,South China University of China,South China University of China,"华工站, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.04900470,113.39715710,edu,
7d7be6172fc2884e1da22d1e96d5899a29831ad2,L2GSCI: Local to Global Seam Cutting and Integrating for Accurate Face Contour Extraction,South China University of China,South China University of China,"华工站, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.04900470,113.39715710,edu,
7d7be6172fc2884e1da22d1e96d5899a29831ad2,L2GSCI: Local to Global Seam Cutting and Integrating for Accurate Face Contour Extraction,Education University of Hong Kong,The Education University of Hong Kong,"香港教育大學 The Education University of Hong Kong, 露屏路 Lo Ping Road, 鳳園 Fung Yuen, 下坑 Ha Hang, 新界 New Territories, HK, DD5 1119, 中国",22.46935655,114.19474194,edu,
7d7be6172fc2884e1da22d1e96d5899a29831ad2,L2GSCI: Local to Global Seam Cutting and Integrating for Accurate Face Contour Extraction,South China University of China,South China University of China,"华工站, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.04900470,113.39715710,edu,
+7d0ff6d0621b3846e8543bc162fd0215d8adfaf0,Efficient Large-Scale Similarity Search Using Matrix Factorization,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+7ddb2e298acbe29ccaea131e8a6475d451eb90ad,A Deep-Learning-Based Fashion Attributes Detection Model,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+7dacb063f783df07f89934c962c3e170acb166cc,Multi-modal Factorized Bilinear Pooling with Co-attention Learning for Visual Question Answering,Hangzhou Dianzi University,Hangzhou Dianzi University,"杭州电子科技大学, 2号大街, 白杨街道, 江干区 (Jianggan), 杭州市 Hangzhou, 浙江省, 310018, 中国",30.31255250,120.34309460,edu,
+7dacb063f783df07f89934c962c3e170acb166cc,Multi-modal Factorized Bilinear Pooling with Co-attention Learning for Visual Question Answering,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
+7dacb063f783df07f89934c962c3e170acb166cc,Multi-modal Factorized Bilinear Pooling with Co-attention Learning for Visual Question Answering,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
7df4f96138a4e23492ea96cf921794fc5287ba72,A Jointly Learned Deep Architecture for Facial Attribute Analysis and Face Detection in the Wild,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
7dd578878e84337d6d0f5eb593f22cabeacbb94c,Classifiers for Driver Activity Monitoring,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+7d941dbab0bb645af81781bd3867ebde11c3641d,Handwritten Hangul recognition using deep convolutional neural networks,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+7d1ac241fb603a4237cb681dbcf163a9f89e906a,Supplementary Material : Switching Convolutional Neural Network for Crowd Counting,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
7df268a3f4da7d747b792882dfb0cbdb7cc431bc,Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
7df268a3f4da7d747b792882dfb0cbdb7cc431bc,Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+7d621ec871a03a01f5aa65253e9ae6c8aadaf798,Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+7d621ec871a03a01f5aa65253e9ae6c8aadaf798,Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
7de386bf2a1b2436c836c0cc1f1f23fccb24aad6,Finding What the Driver Does Final Report Prepared by : Harini Veeraraghavan,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+7de1d463fef3c63cb228f5b4a6a72e62f66630e6,Cascaded Interactional Targeting Network for Egocentric Video Analysis,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+7de1d463fef3c63cb228f5b4a6a72e62f66630e6,Cascaded Interactional Targeting Network for Egocentric Video Analysis,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+7de1d463fef3c63cb228f5b4a6a72e62f66630e6,Cascaded Interactional Targeting Network for Egocentric Video Analysis,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+29ed326a7da1678880db02e5d0e7cb7376dffb98,A square-root sampling approach to fast histogram-based search,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+29ed326a7da1678880db02e5d0e7cb7376dffb98,A square-root sampling approach to fast histogram-based search,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
2914e8c62f0432f598251fae060447f98141e935,Activity Analysis of Spectator Performer Videos Using Motion Trajectories,University of Nebraska - Lincoln,University of Nebraska - Lincoln,"Sheldon Museum of Art, North 12th Street, West Lincoln, Lincoln, Lancaster County, Nebraska, 68588-0300, USA",40.81747230,-96.70444680,edu,
+291dba3baa7d42f1e30b26a714e525cb73c05af1,Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+29954bf080407f23c8ac140202bd2ae5a48fdede,Abnormal Event Detection Based on Saliency Information,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+29b96e41948e35a5bc4a9e7ae978808bc5b0c841,Automatic collection of Web video shots corresponding to specific actions using Web images,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
2902f62457fdf7e8e8ee77a9155474107a2f423e,Non-rigid 3D Shape Registration using an Adaptive Template,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
29d3ed0537e9ef62fd9ccffeeb72c1beb049e1ea,Parametric Dictionaries and Feature Augmentation for Continuous Domain Adaptation,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
29d3ed0537e9ef62fd9ccffeeb72c1beb049e1ea,Parametric Dictionaries and Feature Augmentation for Continuous Domain Adaptation,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+29d2b60bdd998479df7f088859905379e30967a5,Toward a Taxonomy and Computational Models of Abnormalities in Images,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+29d2b60bdd998479df7f088859905379e30967a5,Toward a Taxonomy and Computational Models of Abnormalities in Images,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+29d2b60bdd998479df7f088859905379e30967a5,Toward a Taxonomy and Computational Models of Abnormalities in Images,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+29d2b60bdd998479df7f088859905379e30967a5,Toward a Taxonomy and Computational Models of Abnormalities in Images,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+297c27c74e5cc731b5bd1ad95726b4192e3b902d,Face Super-Resolution Guided by Facial Component Heatmaps,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+29b3be93a60bbc5fe842826030853f99753b08bd,Hierarchical Scene Annotation,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
29fc4de6b680733e9447240b42db13d5832e408f,Recognition of Facial Expressions Based on Tracking and Selection of Discriminative Geometric Features,Korea Electronics Technology Institute,Korea Electronics Technology Institute,"South Korea, Gyeonggi-do, Seongnam-si, Bundang-gu, 새나리로 25 (야탑동) KETI 전자부품연구원",37.40391700,127.15978600,edu,
29fc4de6b680733e9447240b42db13d5832e408f,Recognition of Facial Expressions Based on Tracking and Selection of Discriminative Geometric Features,Chonbuk National University,Chonbuk National University,"전북대학교, 567, 백제대로, 금암동, 덕진구, 전주시, 전북, 54896, 대한민국",35.84658875,127.13501330,edu,
29fc4de6b680733e9447240b42db13d5832e408f,Recognition of Facial Expressions Based on Tracking and Selection of Discriminative Geometric Features,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+29a8492f5aaa212ad81c2e903c73937e7ced73ee,High-precision Immune Computation for Secure Face Recognition,Donghua University,Donghua University,"东华大学, 新华路, 长宁区, 上海市, 210011, 中国",31.20619390,121.41047101,edu,
+29a8492f5aaa212ad81c2e903c73937e7ced73ee,High-precision Immune Computation for Secure Face Recognition,Donghua University,Donghua University,"东华大学, 新华路, 长宁区, 上海市, 210011, 中国",31.20619390,121.41047101,edu,
+29a8492f5aaa212ad81c2e903c73937e7ced73ee,High-precision Immune Computation for Secure Face Recognition,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+29936a4dcc91adf9708b938f0d3fc0f38409eaff,MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+29f21bf4aa648f0996b41b03fc11b07a0e550f46,3D Face Recognition using Mapped Depth Images,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
2912c3ea67678a1052d7d5cbe734a6ad90fc360e,Facial Feature Detection using a Virtual Structuring Element,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
29f4ac49fbd6ddc82b1bb697820100f50fa98ab6,The benefits and challenges of collecting richer object annotations,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
2910fcd11fafee3f9339387929221f4fc1160973,Evaluating Open-Universe Face Identification on the Web,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
2910fcd11fafee3f9339387929221f4fc1160973,Evaluating Open-Universe Face Identification on the Web,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+29a606ba5b9ae9bc16d05a832d4e54d769c63dae,Activation of mGluR2/3 underlies the effects of N-acetylcystein on amygdala-associated autism-like phenotypes in a valproate-induced rat model of autism,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+29a606ba5b9ae9bc16d05a832d4e54d769c63dae,Activation of mGluR2/3 underlies the effects of N-acetylcystein on amygdala-associated autism-like phenotypes in a valproate-induced rat model of autism,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+29732d196d199acdb9d5122207b4613bb3aedf8e,Neural correlates of affective context in facial expression analysis: A simultaneous EEG-fNIRS study,New Jersey Institute of Technology,New Jersey Institute of Technology,"New Jersey Institute of Technology, Warren Street, University Heights, Newark, Essex County, New Jersey, 07103, USA",40.74230250,-74.17928172,edu,
+29732d196d199acdb9d5122207b4613bb3aedf8e,Neural correlates of affective context in facial expression analysis: A simultaneous EEG-fNIRS study,Drexel University,Drexel University,"Drexel University, Arch Street, Powelton Village, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.95740000,-75.19026706,edu,
29479bb4fe8c04695e6f5ae59901d15f8da6124b,Multiple instance learning for labeling faces in broadcasting news video,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
29479bb4fe8c04695e6f5ae59901d15f8da6124b,Multiple instance learning for labeling faces in broadcasting news video,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
29479bb4fe8c04695e6f5ae59901d15f8da6124b,Multiple instance learning for labeling faces in broadcasting news video,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+293cefbe481a5a472d830a88ff140dfcc1869c31,Virtual Immortality: Reanimating Characters from TV Shows,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
291f527598c589fb0519f890f1beb2749082ddfd,Seeing People in Social Context: Recognizing People and Social Relationships,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
291265db88023e92bb8c8e6390438e5da148e8f5,MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
29c340c83b3bbef9c43b0c50b4d571d5ed037cbd,Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+291e5377df2eec4835b5c6889896941831a11c69,Recovering 6D Object Pose: Multi-modal Analyses on Challenges,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+291e5377df2eec4835b5c6889896941831a11c69,Recovering 6D Object Pose: Multi-modal Analyses on Challenges,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+2976605dc3b73377696537291d45f09f1ab1fbf5,Cross-Stitch Networks for Multi-task Learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+29693ce8b14c552e4e46d05d55cbff3942f95c30,Machine Perception for Occupational Therapy,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+29693ce8b14c552e4e46d05d55cbff3942f95c30,Machine Perception for Occupational Therapy,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+2953fa360c79f2c77bbc53c8154f49136333bfa6,Compact Tensor Pooling for Visual Question Answering,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+2953fa360c79f2c77bbc53c8154f49136333bfa6,Compact Tensor Pooling for Visual Question Answering,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
297d3df0cf84d24f7efea44f87c090c7d9be4bed,Appearance-Based 3-D Face Recognition from Video,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
297d3df0cf84d24f7efea44f87c090c7d9be4bed,Appearance-Based 3-D Face Recognition from Video,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
29b86534d4b334b670914038c801987e18eb5532,Total Cluster: A person agnostic clustering method for broadcast videos,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
29b86534d4b334b670914038c801987e18eb5532,Total Cluster: A person agnostic clustering method for broadcast videos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
29b86534d4b334b670914038c801987e18eb5532,Total Cluster: A person agnostic clustering method for broadcast videos,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+299b65d5d3914dad9aae2f936165dcebcf78db88,Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation,Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
+299b65d5d3914dad9aae2f936165dcebcf78db88,Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation,Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
+29db046dd1f8100b279c3f5f5c5ef19bdbf5af9a,Recent Progress of Face Image Synthesis,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
29631ca6cff21c9199c70bcdbbcd5f812d331a96,Error Rates in Users of Automatic Face Recognition Software,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
29631ca6cff21c9199c70bcdbbcd5f812d331a96,Error Rates in Users of Automatic Face Recognition Software,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+2954deae38c40a244f6a9c0714987d786c69db7c,Human detection and pose estimation for motion picture logging and visualisation,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
2983efadb1f2980ab5ef20175f488f77b6f059d7,Emotion in Human–computer Interaction,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+291de30ceecb5dcf0644c35e2b5935d341ea148b,Explainable Black-Box Attacks Against Model-based Authentication,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+291de30ceecb5dcf0644c35e2b5935d341ea148b,Explainable Black-Box Attacks Against Model-based Authentication,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+291de30ceecb5dcf0644c35e2b5935d341ea148b,Explainable Black-Box Attacks Against Model-based Authentication,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+291de30ceecb5dcf0644c35e2b5935d341ea148b,Explainable Black-Box Attacks Against Model-based Authentication,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+29be6e76d9ed777ca032c40a6ab374a44bde38bd,Latent SVMs for Human Detection with a Locally Affine Deformation Field,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+29be6e76d9ed777ca032c40a6ab374a44bde38bd,Latent SVMs for Human Detection with a Locally Affine Deformation Field,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+29fa7b334543b6b6a4927ea2c7ae4c6fa8f6a7c4,Latent Boosting for Action Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+29fa7b334543b6b6a4927ea2c7ae4c6fa8f6a7c4,Latent Boosting for Action Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
2911e7f0fb6803851b0eddf8067a6fc06e8eadd6,Joint Fine-Tuning in Deep Neural Networks for Facial Expression Recognition,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
+291e6f2a365913100de8bd1071810b8155095f08,Efficient and Exact MAP-MRF Inference using Branch and Bound,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+2917808d9018386af42e249ba4fb94bafcda54e5,Compact CNN for indexing egocentric videos,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
+29fc5339e299b47c3d4f871974069a2971b4b8b6,Personalized Automatic Estimation of Self-Reported Pain Intensity from Facial Expressions,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+29fc5339e299b47c3d4f871974069a2971b4b8b6,Personalized Automatic Estimation of Self-Reported Pain Intensity from Facial Expressions,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+29445acb03961fb27ac9221875c0a25171502144,An Efficient Face Tracker Using Active Shape Model,Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
+29445acb03961fb27ac9221875c0a25171502144,An Efficient Face Tracker Using Active Shape Model,Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
29921072d8628544114f68bdf84deaf20a8c8f91,Multi-task Curriculum Transfer Deep Learning of Clothing Attributes,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+29b737cdb317e47e7cc219b438ea38e8fdceb45c,Approximate Distribution Matching for Sequence-to-Sequence Learning,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
2969f822b118637af29d8a3a0811ede2751897b5,Cascaded Shape Space Pruning for Robust Facial Landmark Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+290a96c9aa653eb6dd64d5b0fa5bae7bf208ae14,Joint Pose and Expression Modeling for Facial Expression Recognition,Jiangsu University,Jiangsu University,"江苏大学, 301, 学府路, 京口区, 象山街道, 京口区 (Jingkou), 镇江市 / Zhenjiang, 江苏省, 212013, 中国",32.20302965,119.50968362,edu,
29f0414c5d566716a229ab4c5794eaf9304d78b6,Biometric Template Security,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+7cab6a3247f56e0e2fc38133ea0fb89c48dadda7,Spatiotemporal Modeling for Crowd Counting in Videos,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+7cdd8c0f3c672000506696a6f8b96b9a99e778ae,Video Monitoring and Analysis of Human Behavior for Diagnosis of Obstructive Sleep Apnoea,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
+7c02a578734af8008177bb3f27549198b2503178,Segmenting video into classes of algorithm-suitability,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
7c61d21446679776f7bdc7afd13aedc96f9acac1,Hierarchical Label Inference for Video Classification,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
7c61d21446679776f7bdc7afd13aedc96f9acac1,Hierarchical Label Inference for Video Classification,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
7c61d21446679776f7bdc7afd13aedc96f9acac1,Hierarchical Label Inference for Video Classification,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
7c7ab59a82b766929defd7146fd039b89d67e984,Improving multiview face detection with multi-task deep convolutional neural networks,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
7ca337735ec4c99284e7c98f8d61fb901dbc9015,Driver activity monitoring through supervised and unsupervised learning,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+7ca08c7a1b61258a8f36435be7a96abde64be081,Focal Visual-Text Attention for Visual Question Answering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
7c1cfab6b60466c13f07fe028e5085a949ec8b30,Deep Feature Consistent Variational Autoencoder,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
7c1cfab6b60466c13f07fe028e5085a949ec8b30,Deep Feature Consistent Variational Autoencoder,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
7c1cfab6b60466c13f07fe028e5085a949ec8b30,Deep Feature Consistent Variational Autoencoder,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
7c1cfab6b60466c13f07fe028e5085a949ec8b30,Deep Feature Consistent Variational Autoencoder,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+7c0bd7ce51c62671d5ffc1506786b0b7861ce00a,Utility-based acceleration of multithreaded applications on asymmetric CMPs,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+7c0bd7ce51c62671d5ffc1506786b0b7861ce00a,Utility-based acceleration of multithreaded applications on asymmetric CMPs,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7cd3062284a9f93df05cb11161d16114be945a5b,Deep Spatiotemporal Representation of the Face for Automatic Pain Intensity Estimation,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+7ce25a0852e2345be1a1bd02b8eb4cefb9d47073,Composite Cores: Pushing Heterogeneity Into a Core,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
7c17280c9193da3e347416226b8713b99e7825b8,VideoCapsuleNet: A Simplified Network for Action Detection,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
7cffcb4f24343a924a8317d560202ba9ed26cd0b,The unconstrained ear recognition challenge,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
7cffcb4f24343a924a8317d560202ba9ed26cd0b,The unconstrained ear recognition challenge,"University of Colorado, Colorado Springs",University of Colorado Colorado Springs,"Main Hall, The Spine, Colorado Springs, El Paso County, Colorado, 80907, USA",38.89207560,-104.79716389,edu,
7cffcb4f24343a924a8317d560202ba9ed26cd0b,The unconstrained ear recognition challenge,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
7cffcb4f24343a924a8317d560202ba9ed26cd0b,The unconstrained ear recognition challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+7c5dde400571fd357d1093e1829a8bd7917d8fcd,Retrospective Higher-Order Markov Processes for User Trails,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+7c5dde400571fd357d1093e1829a8bd7917d8fcd,Retrospective Higher-Order Markov Processes for User Trails,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+7c79d3a40c1a1f5b9692ed23396b0f13453c225c,The influence of vocal training and acting experience on measures of voice quality and emotional genuineness,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
+7c79d3a40c1a1f5b9692ed23396b0f13453c225c,The influence of vocal training and acting experience on measures of voice quality and emotional genuineness,University of Vienna,University of Vienna,"Uni Wien, 1, Universitätsring, Schottenviertel, KG Innere Stadt, Innere Stadt, Wien, 1010, Österreich",48.21313020,16.36068653,edu,
+7c79d3a40c1a1f5b9692ed23396b0f13453c225c,The influence of vocal training and acting experience on measures of voice quality and emotional genuineness,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+7c79d3a40c1a1f5b9692ed23396b0f13453c225c,The influence of vocal training and acting experience on measures of voice quality and emotional genuineness,University of Vienna,University of Vienna,"Uni Wien, 1, Universitätsring, Schottenviertel, KG Innere Stadt, Innere Stadt, Wien, 1010, Österreich",48.21313020,16.36068653,edu,
+7c79d3a40c1a1f5b9692ed23396b0f13453c225c,The influence of vocal training and acting experience on measures of voice quality and emotional genuineness,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
+7c62f5e4a62758f44bd98f087f92b6b6b1f2043b,Combination features and models for human detection,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
7c4c442e9c04c6b98cd2aa221e9d7be15efd8663,Classifier learning with hidden information,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+7c132e0a2b7e13c78784287af38ad74378da31e5,Salient Parts based Multi-people Tracking,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
7c2ec6f4ab3eae86e0c1b4f586e9c158fb1d719d,Dissimilarity-Based Classifications in Eigenspaces,Myongji University,Myongji University,"명지대, 금학로, 역북동, 처인구, 용인시, 경기, 17144, 대한민국",37.23810230,127.19034310,edu,
+7cd5d7f8295b219b029a4231ae5cffb261e00ebe,Early Active Learning with Pairwise Constraint for Person Re-identification,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+7cd5d7f8295b219b029a4231ae5cffb261e00ebe,Early Active Learning with Pairwise Constraint for Person Re-identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
7cf8a841aad5b7bdbea46a7bb820790e9ce12d0b,Supervised Heat Kernel Lpp Method for Face Recognition,Utah State University,Utah State University,"Utah State University, Champ Drive, Logan, Cache County, Utah, 84322, USA",41.74115040,-111.81223090,edu,
+7c9f884137a22c3bb5cefcd7dfc55e3a83979771,Person tracking-by-detection with efficient selection of part-detectors,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
7c9622ad1d8971cd74cc9e838753911fe27ccac4,Representation Learning with Smooth Autoencoder,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+7c622df16f06d9f1c1af7262e91c54906e1b7e0e,Locating Facial Features and Pose Estimation Using a 3D Shape Model,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
7c2c9b083817f7a779d819afee383599d2e97ed8,"Disentangling Motion, Foreground and Background Features in Videos",Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
7c2c9b083817f7a779d819afee383599d2e97ed8,"Disentangling Motion, Foreground and Background Features in Videos","Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
7c2c9b083817f7a779d819afee383599d2e97ed8,"Disentangling Motion, Foreground and Background Features in Videos",Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
@@ -1712,15 +4656,31 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 7c36afc9828379de97f226e131390af719dbc18d,Unsupervised face-name association via commute distance,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
7c36afc9828379de97f226e131390af719dbc18d,Unsupervised face-name association via commute distance,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
7ca7255c2e0c86e4adddbbff2ce74f36b1dc522d,Stereo Matching for Unconstrained Face Recognition Ph . D . Proposal,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+7c428ce264662bceae0b78f915d4d4797a2492f2,Transductive Unbiased Embedding for Zero-Shot Learning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+7c428ce264662bceae0b78f915d4d4797a2492f2,Transductive Unbiased Embedding for Zero-Shot Learning,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+7c428ce264662bceae0b78f915d4d4797a2492f2,Transductive Unbiased Embedding for Zero-Shot Learning,"Alibaba Group, Hangzhou, China","Alibaba Group, Hangzhou, China","Alibaba Group, 五常街道, 余杭区 (Yuhang), 杭州市 Hangzhou, 浙江省, 中国",30.28106540,120.02139087,edu,
7c42371bae54050dbbf7ded1e7a9b4109a23a482,Optimized features selection using hybrid PSO-GA for multi-view gender classification,Foundation University Rawalpindi Campus,Foundation University Rawalpindi Campus,"Foundation University Rawalpindi Campus, Main Parking Road, Police Lines, راولپنڈی, Rawalpindi Cantt, پنجاب, 46600, پاکستان",33.56095040,73.07125966,edu,
7c42371bae54050dbbf7ded1e7a9b4109a23a482,Optimized features selection using hybrid PSO-GA for multi-view gender classification,University of Central Punjab,University of Central Punjab,"University of Central Punjab, Khyaban-e-Jinnah, PECHS, Wapda Town, بحریہ ٹاؤن, Lahore District, پنجاب, 54000, پاکستان",31.44661490,74.26797620,edu,
7c42371bae54050dbbf7ded1e7a9b4109a23a482,Optimized features selection using hybrid PSO-GA for multi-view gender classification,University of Dammam,University of Dammam,"University of Dammam, King Faisal Rd, العقربية, الخبر, المنطقة الشرقية, ٣١٩٥٢, السعودية",26.39793625,50.19807924,edu,
7c953868cd51f596300c8231192d57c9c514ae17,Detecting and Aligning Faces by Image Retrieval,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+7cf8440b1c02c021f6ba8543ad490b4788bbe280,"Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations",University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+7cf8440b1c02c021f6ba8543ad490b4788bbe280,"Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations",University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+7cf8440b1c02c021f6ba8543ad490b4788bbe280,"Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations",University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+7cf8440b1c02c021f6ba8543ad490b4788bbe280,"Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations",University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+7cf8440b1c02c021f6ba8543ad490b4788bbe280,"Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations",University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+7c7a23e8e846c1e1a6c63925d73d0d0806a040ef,Visual Analysis of Tag Co-occurrence on Nouns and Adjectives,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
7c6dbaebfe14878f3aee400d1378d90d61373921,A Novel Biometric Feature Extraction Algorithm using Two Dimensional Fisherface in 2DPCA subspace for Face Recognition,University of Newcastle,University of Newcastle,"University of Newcastle Central Coast Campus, Technology Bridge, Ourimbah, Central Coast, NSW, 2258, Australia",-33.35788990,151.37834708,edu,
+7c2f6424b0bb2c28f282fbc0b4e98bf85d5584eb,Relief R-CNN: Utilizing Convolutional Feature Interrelationship for Fast Object Detection Deployment,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+7c2f6424b0bb2c28f282fbc0b4e98bf85d5584eb,Relief R-CNN: Utilizing Convolutional Feature Interrelationship for Fast Object Detection Deployment,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+7cd097f3866d56114c1778c0d9ac1c4a9a35cff9,MODELLING MULTI-OBJECT ACTIVITY BY GAUSSIAN PROCESSES 3 2 Activity Modelling and Anomaly Detection 2 . 1 Activity Representation,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
7c80d91db5977649487388588c0c823080c9f4b4,DocFace: Matching ID Document Photos to Selfies,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
7c30ea47f5ae1c5abd6981d409740544ed16ed16,Informed Democracy: Voting-based Novelty Detection for Action Recognition,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+1693e615c3a7a843880eb5bbf4e3f1beb0580f5c,Nonparametric scene parsing: Label transfer via dense scene alignment,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
1648cf24c042122af2f429641ba9599a2187d605,Boosting cross-age face verification via generative age normalization,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+166d069ea056fbb42b10ca660956fee881e6c875,Inverse Rendering with a Morphable Model: A Multilinear Approach,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
16fdd6d842475e6fbe58fc809beabbed95f0642e,Learning Temporal Embeddings for Complex Video Analysis,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+16dd9ea784a862c45d1d2af6d2fb83198f567719,Human Pose Estimation with Parsing Induced Learner,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+16dd9ea784a862c45d1d2af6d2fb83198f567719,Human Pose Estimation with Parsing Induced Learner,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
16bce9f940bb01aa5ec961892cc021d4664eb9e4,Mutual Component Analysis for Heterogeneous Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
16bce9f940bb01aa5ec961892cc021d4664eb9e4,Mutual Component Analysis for Heterogeneous Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
16bce9f940bb01aa5ec961892cc021d4664eb9e4,Mutual Component Analysis for Heterogeneous Face Recognition,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
@@ -1728,82 +4688,205 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 16bce9f940bb01aa5ec961892cc021d4664eb9e4,Mutual Component Analysis for Heterogeneous Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
16bce9f940bb01aa5ec961892cc021d4664eb9e4,Mutual Component Analysis for Heterogeneous Face Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
16bce9f940bb01aa5ec961892cc021d4664eb9e4,Mutual Component Analysis for Heterogeneous Face Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+16727cd69372019267589a27574147e8cf3b25f8,Human Attribute Recognition by Rich Appearance Dictionary,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+16727cd69372019267589a27574147e8cf3b25f8,Human Attribute Recognition by Rich Appearance Dictionary,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+1665fe64f8439a1854595e2e73394517d44c35b4,An improved LBP algorithm for avatar face recognition,University of Louisville,University of Louisville,"University of Louisville, South Brook Street, Louisville, Jefferson County, Kentucky, 40208, USA",38.21675650,-85.75725023,edu,
+1633c30909f4f3d91ea4256c76c71abf62a52bd8,Deep Feature Learning for Hyperspectral Image Classification and Land Cover Estimation,University of Crete,University of Crete,"House of Europe, Μακεδονίας, Ρέθυμνο, Δήμος Ρεθύμνης, Περιφερειακή Ενότητα Ρεθύμνου, Περιφέρεια Κρήτης, Κρήτη, 930100, Ελλάδα",35.37130240,24.47544080,edu,
1677d29a108a1c0f27a6a630e74856e7bddcb70d,Efficient Misalignment-Robust Representation for Real-Time Face Recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+16eb964a5a0f5fa3692440f07dd60b23354f5f58,Observing the Natural World with Flickr,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+1601ac8e682622f489b4a18792025c0843d47b86,Transferring a generic pedestrian detector towards specific scenes,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+16c3f99f8f48d4ccb71b782f79601d5efeab8461,Pedestrian Detection Based on Informed Haar-like Features and Switchable Deep Network,Anhui Polytechnic University,Anhui Polytechnic University,"安徽工程大学, 鸠江北路, 芜湖市, 芜湖市区, 芜湖市 / Wuhu, 安徽省, 241000, 中国",31.34185955,118.40739712,edu,
16b9d258547f1eccdb32111c9f45e2e4bbee79af,NormFace: L2 Hypersphere Embedding for Face Verification,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
16b9d258547f1eccdb32111c9f45e2e4bbee79af,NormFace: L2 Hypersphere Embedding for Face Verification,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+162ea969d1929ed180cc6de9f0bf116993ff6e06,Deep Face Recognition,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+16d3954f0418bd9a2ac20a2be6db93d49213c680,CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+16d3954f0418bd9a2ac20a2be6db93d49213c680,CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+16f76f040f08448cf0a3984168d69197ea4af039,"Now you see race, now you don’t: Verbal cues influence children’s racial stability judgments",University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
162dfd0d2c9f3621d600e8a3790745395ab25ebc,Head Pose Estimation Based on Multivariate Label Distribution,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
16f940b4b5da79072d64a77692a876627092d39c,A framework for automated measurement of the intensity of non-posed Facial Action Units,University of Denver,University of Denver,"University of Denver, Driscoll Bridge, Denver, Denver County, Colorado, 80208, USA",39.67665410,-104.96220300,edu,
16f940b4b5da79072d64a77692a876627092d39c,A framework for automated measurement of the intensity of non-posed Facial Action Units,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
16f940b4b5da79072d64a77692a876627092d39c,A framework for automated measurement of the intensity of non-posed Facial Action Units,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
16f940b4b5da79072d64a77692a876627092d39c,A framework for automated measurement of the intensity of non-posed Facial Action Units,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+16a431d87d0f01c6d70d2b7476dfb3948064b740,Face recognition on smartphones via optimised Sparse Representation Classification,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+16344102d21291483d1fa7484be28b563df434ce,Comparison of 2D/3D Features and Their Adaptive Score Level Fusion for 3D Face Recognition,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
+16701e3cbd43b52e32d567649a194245dcd31829,Crossing-Line Crowd Counting with Two-Phase Deep Neural Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+166e7fd811d104254155c90506f2f7e77947534c,Hidden Hands: Tracking Hands with an Occlusion Aware Tracker,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
16572c545384174f8136d761d2b0866e968120a8,Sequential Max-Margin Event Detectors,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
16820ccfb626dcdc893cc7735784aed9f63cbb70,Real-time embedded age and gender classification in unconstrained video,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
+16f341786f7fa8b117e8812a58742771c089e68f,Reducing Overfitting in Deep Networks by Decorrelating Representations,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
164b0e2a03a5a402f66c497e6c327edf20f8827b,Sparse Deep Transfer Learning for Convolutional Neural Network,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
164b0e2a03a5a402f66c497e6c327edf20f8827b,Sparse Deep Transfer Learning for Convolutional Neural Network,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
1667a77db764e03a87a3fd167d88b060ef47bb56,Alternative Semantic Representations for Zero-Shot Human Action Recognition,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
169618b8dc9b348694a31c6e9e17b989735b4d39,Unsupervised Representation Learning by Sorting Sequences,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+160da454cc64c1117c3a164b9bf375d73fb81720,Scalable Metric Learning via Weighted Approximate Rank Component Analysis,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+16d2ead2c3e98aa1ee9c948855a027e1da2b8eea,Multi-view Deep Network for Cross-View Classification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
16e95a907b016951da7c9327927bb039534151da,3D Face Recognition Using Spherical Vector Norms Map,Beijing Union University,Beijing Union University,"北京联合大学, 北四环东路, 飘亮阳光广场, 太阳宫乡, 朝阳区 / Chaoyang, 北京市, 100012, 中国",39.98900680,116.42067718,edu,
16e95a907b016951da7c9327927bb039534151da,3D Face Recognition Using Spherical Vector Norms Map,Beijing Union University,Beijing Union University,"北京联合大学, 北四环东路, 飘亮阳光广场, 太阳宫乡, 朝阳区 / Chaoyang, 北京市, 100012, 中国",39.98900680,116.42067718,edu,
16e95a907b016951da7c9327927bb039534151da,3D Face Recognition Using Spherical Vector Norms Map,Capital Normal University,Capital Normal University,"首都师范大学, 岭南路, 西冉村, 海淀区, 100048, 中国",39.92864575,116.30104052,edu,
+163e07487115641046022d57fcbc6dc9fd2669f2,Complementary feature extraction for branded handbag recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
16d6737b50f969247339a6860da2109a8664198a,Convolutional Neural Networks for Age and Gender Classification,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+16815ef660ef9e4091a81044d430591348df72ee,Combining Texture and Shape Cues for Object Recognition with Minimal Supervision,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+16283efecc7332e363c9419d7129bbd5d95cbf4d,Recognizing actions from still images,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
1610d2d4947c03a89c0fda506a74ba1ae2bc54c2,"Robust Real-Time 3D Face Tracking from RGBD Videos under Extreme Pose, Depth, and Expression Variation",Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+164f3b9740d9ceb14658237fddede0f86b5e0c47,CASENet: Deep Category-Aware Semantic Edge Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
1659a8b91c3f428f1ba6aeba69660f2c9d0a85c6,Recent developments in social signal processing,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
1659a8b91c3f428f1ba6aeba69660f2c9d0a85c6,Recent developments in social signal processing,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
1659a8b91c3f428f1ba6aeba69660f2c9d0a85c6,Recent developments in social signal processing,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+164251f012186767d9f00a3baf8735dd2180fee7,ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks,Moscow State University,Moscow State University,"ul. Leninskiye Gory, 1, Moskva, Russia, 119991",55.70393490,37.52866960,edu,
+166d8f840c502c5095c8651540dd393743d63ce9,Kernel Descriptors for Visual Recognition,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
167736556bea7fd57cfabc692ec4ae40c445f144,Improved Motion Description for Action Classification,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
167ea1631476e8f9332cef98cf470cb3d4847bc6,Visual Search at Pinterest,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+16243557482241171beccbbd694976103cc941ef,Learning Multiple Tasks with Deep Relationship Networks,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+16243557482241171beccbbd694976103cc941ef,Learning Multiple Tasks with Deep Relationship Networks,University of Illinois at Chicago,University of Illinois at Chicago,"University of Illinois at Chicago, West Taylor Street, Greektown, Chicago, Cook County, Illinois, 60607, USA",41.86898915,-87.64856256,edu,
+16161051ee13dd3d836a39a280df822bf6442c84,Learning Efficient Object Detection Models with Knowledge Distillation,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+16161051ee13dd3d836a39a280df822bf6442c84,Learning Efficient Object Detection Models with Knowledge Distillation,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+16fda65f258ca22d856bb0252891deecc59efc3d,Is Enough Enough? What Is Sufficiency in Biometric Data?,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+16c7c31a7553d99f1837fc6e88e77b5ccbb346b8,Person Re-identification by Descriptive and Discriminative Classification,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
420782499f38c1d114aabde7b8a8104c9e40a974,Fashion Style in 128 Floats: Joint Ranking and Classification Using Weak Data for Feature Extraction,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
+42f422a9a67ba71a9ac699205940d8cc2dca8317,On-demand Learning for Deep Image Restoration,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+422e46aa845435822b7d93c2fb9103cd94128a21,PKU-NEC @ TRECVid 2012 SED: Uneven-Sequence Based Event Detection in Surveillance Video,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+423b941641728a21e37f41359a691815cdd84ceb,Reversible Recursive Instance-Level Object Segmentation,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+426f20cf5f836f410b6ed31a990ed1bbaaf6733b,Unlocking the urban photographic record through 4D scene modeling,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
4217473596b978f13a211cdf47b7d3f6588c785f,An efficient approach for clustering face images,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+42efcb8cac3889ac25368770058e000249f68d13,Analysing Soft Clothing Biometrics for Retrieval,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+4209f140d64ce6fb891eb6ada26eaeb40af123e2,Deep Fully-Connected Part-Based Models for Human Pose Estimation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+4209f140d64ce6fb891eb6ada26eaeb40af123e2,Deep Fully-Connected Part-Based Models for Human Pose Estimation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+4209f140d64ce6fb891eb6ada26eaeb40af123e2,Deep Fully-Connected Part-Based Models for Human Pose Estimation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+4209f140d64ce6fb891eb6ada26eaeb40af123e2,Deep Fully-Connected Part-Based Models for Human Pose Estimation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
4223666d1b0b1a60c74b14c2980069905088edc6,A Convergent Incoherent Dictionary Learning Algorithm for Sparse Coding,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
42afe6d016e52c99e2c0d876052ade9c192d91e7,Spontaneous vs. posed facial behavior: automatic analysis of brow actions,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
42afe6d016e52c99e2c0d876052ade9c192d91e7,Spontaneous vs. posed facial behavior: automatic analysis of brow actions,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
42afe6d016e52c99e2c0d876052ade9c192d91e7,Spontaneous vs. posed facial behavior: automatic analysis of brow actions,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+42d9ddd942ec89a3fc6a7beed174fd75c3dabff7,The Conditional Lucas & Kanade Algorithm,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+42d9ddd942ec89a3fc6a7beed174fd75c3dabff7,The Conditional Lucas & Kanade Algorithm,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+420c46d7cafcb841309f02ad04cf51cb1f190a48,Multi-Scale Context Aggregation by Dilated Convolutions,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+4233b07033a1ef8af188383f30602a5fd0aa2181,Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
42765c170c14bd58e7200b09b2e1e17911eed42b,Feature Extraction Based on Wavelet Moments and Moment Invariants in Machine Vision Systems,Democritus University of Thrace,Democritus University of Thrace,"Δημοκρίτειο Πανεπιστήμιο Θράκης, Μάκρη - Αλεξανδρούπολη, Αλεξανδρούπολη, Δήμος Αλεξανδρούπολης, Περιφερειακή Ενότητα Έβρου, Περιφέρεια Ανατολικής Μακεδονίας και Θράκης, Μακεδονία - Θράκη, 68100, Ελλάδα",40.84941785,25.83444939,edu,
+4226c9b155ef3c5c78bd122d870fec42ae695ad7,What is the Right Illumination Normalization for Face Recognition?,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
+4226c9b155ef3c5c78bd122d870fec42ae695ad7,What is the Right Illumination Normalization for Face Recognition?,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
+428818a9edfb547431be6d7ec165c6af576c83d5,Recurrent Topic-Transition GAN for Visual Paragraph Generation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+428818a9edfb547431be6d7ec165c6af576c83d5,Recurrent Topic-Transition GAN for Visual Paragraph Generation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+428818a9edfb547431be6d7ec165c6af576c83d5,Recurrent Topic-Transition GAN for Visual Paragraph Generation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+428818a9edfb547431be6d7ec165c6af576c83d5,Recurrent Topic-Transition GAN for Visual Paragraph Generation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+428818a9edfb547431be6d7ec165c6af576c83d5,Recurrent Topic-Transition GAN for Visual Paragraph Generation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+42e640fc7d37c51b157e7007117eacb78d7789a9,Emotional Speech of Mentally and Physically Disabled Individuals: Introducing the EmotAsS Database and First Findings,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+42e640fc7d37c51b157e7007117eacb78d7789a9,Emotional Speech of Mentally and Physically Disabled Individuals: Introducing the EmotAsS Database and First Findings,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+4203f10b41e7931a63598989aa14478c04b725c9,Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+42fc202713cb5205bba8be8a3b85a8be1e65d63f,QCC: A novel cluster algorithm based on Quasi-Cluster Centers,Chongqing University,Chongqing University,"重庆工商大学, 19, 翠林路, 重庆市, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400067, 中国",29.50841740,106.57858552,edu,
+42e9bfa84eecbafe32e1d2f5d52acfd617b57d18,Exploiting Temporal Information for 3D Human Pose Estimation,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
4223917177405eaa6bdedca061eb28f7b440ed8e,B-spline Shape from Motion & Shading: An Automatic Free-form Surface Modeling for Face Reconstruction,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
4223917177405eaa6bdedca061eb28f7b440ed8e,B-spline Shape from Motion & Shading: An Automatic Free-form Surface Modeling for Face Reconstruction,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
4223917177405eaa6bdedca061eb28f7b440ed8e,B-spline Shape from Motion & Shading: An Automatic Free-form Surface Modeling for Face Reconstruction,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+428cfbd3c237d04edb06690a7e9e9a40c62fc8da,"Algorithmic clothing: hybrid recommendation, from street-style-to-shop",University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+428cfbd3c237d04edb06690a7e9e9a40c62fc8da,"Algorithmic clothing: hybrid recommendation, from street-style-to-shop",Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
42eda7c20db9dc0f42f72bb997dd191ed8499b10,Gaze Embeddings for Zero-Shot Image Classification,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
42eda7c20db9dc0f42f72bb997dd191ed8499b10,Gaze Embeddings for Zero-Shot Image Classification,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
42c9394ca1caaa36f535721fa9a64b2c8d4e0dee,Label Efficient Learning of Transferable Representations across Domains and Tasks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
42c9394ca1caaa36f535721fa9a64b2c8d4e0dee,Label Efficient Learning of Transferable Representations across Domains and Tasks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+423be52973dab29c31a845ea54c9050aba0d650a,Walking on Minimax Paths for k-NN Search,Pohang University of Science and Technology,Pohang University of Science and Technology,"포스텍, 77, 청암로, 효곡동, 남구, 포항시, 경북, 37673, 대한민국",36.01773095,129.32107509,edu,
+428d1777846efa8e86b694791b8dbf114e188f30,Towards 4D Coupled Models of Conversational Facial Expression Interactions,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+428d1777846efa8e86b694791b8dbf114e188f30,Towards 4D Coupled Models of Conversational Facial Expression Interactions,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+42854a0175d866f190378a3034406e11cd160568,Joint Graph Decomposition and Node Labeling by Local Search,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+421a7b0b6cf45ccba3df41a99fbb272d324489d9,Facilitating Autism Research.,University of Connecticut,University of Connecticut,"University of Connecticut, Glenbrook Road, Storrs, Tolland County, Connecticut, 06269, USA",41.80937790,-72.25364140,edu,
4205cb47ba4d3c0f21840633bcd49349d1dc02c1,Action recognition with gradient boundary convolutional network,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
4205cb47ba4d3c0f21840633bcd49349d1dc02c1,Action recognition with gradient boundary convolutional network,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
4205cb47ba4d3c0f21840633bcd49349d1dc02c1,Action recognition with gradient boundary convolutional network,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+42bb241681c4bec1fa36211a204fa0dc8158e5ff,Localizing Objects While Learning Their Appearance,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
42ded74d4858bea1070dadb08b037115d9d15db5,Exigent: An Automatic Avatar Generation System,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+421046882e42a0572c8654ae1df06bc789088c2f,Human Semantic Parsing for Person Re-identification,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+421046882e42a0572c8654ae1df06bc789088c2f,Human Semantic Parsing for Person Re-identification,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
42ea8a96eea023361721f0ea34264d3d0fc49ebd,Parameterized Principal Component Analysis,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
42f6f5454dda99d8989f9814989efd50fe807ee8,Conditional generative adversarial nets for convolutional face generation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+42c1111c9cbb74b2755f58c6e9e84e7d1d11cc6e,Object Recognition Based on Amounts of Unlabeled Data,Beijing Institute of Technology,Beijing Institute of Technology University,"北京理工大学, 5, 中关村南大街, 中关村, 稻香园南社区, 海淀区, 北京市, 100872, 中国",39.95866520,116.30971281,edu,
+42c1111c9cbb74b2755f58c6e9e84e7d1d11cc6e,Object Recognition Based on Amounts of Unlabeled Data,Beijing Institute of Technology,Beijing Institute of Technology University,"北京理工大学, 5, 中关村南大街, 中关村, 稻香园南社区, 海淀区, 北京市, 100872, 中国",39.95866520,116.30971281,edu,
+42a712dbfe07262ba2b479e800008f08ad1c1388,Learning to Sample Using Stein Discrepancy,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+425833b5fe892b00dcbeb6e3975008e9a73a5a72,A Review of Performance Evaluation for Biometrics Systems,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
4276eb27e2e4fc3e0ceb769eca75e3c73b7f2e99,Face Recognition From Video,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+429961112a9b4f08f6b68acce8868b3468d72c6e,Learning Dilation Factors for Semantic Segmentation of Street Scenes,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+89dcf3d6f42f1a2fcdb0c81982ac1ea9e4ce2339,Convolutional Neural Networks for Detecting and Mapping Crowds in First Person Vision Applications,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
+89c7f6a765aec6e7c754063bd723b1313f058948,Automatic Naming of Speakers in Video via Name-Face Mapping,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+8916cbd3eb66475182a177ade018ed8a3eed26b7,Fashion apparel detection: The role of deep convolutional neural network and pose-dependent priors,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
89002a64e96a82486220b1d5c3f060654b24ef2a,PIEFA: Personalized Incremental and Ensemble Face Alignment,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
+8973910c8acfd296922d9691a533b3c5061ec815,Supplementary Material for Efficient Online Local Metric Adaptation via Negative Samples for Person Re-Identification,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
89e7d23e0c6a1d636f2da68aaef58efee36b718b,Lucas-Kanade Scale Invariant Feature Transform for Uncontrolled Viewpoint Face Recognition,Chonbuk National University,Chonbuk National University,"전북대학교, 567, 백제대로, 금암동, 덕진구, 전주시, 전북, 54896, 대한민국",35.84658875,127.13501330,edu,
89f4bcbfeb29966ab969682eae235066a89fc151,A comparison of photometric normalisation algorithms for face verification,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+891ecd15c285aeb7286762b8a02e9897cd9df5a1,Driving recorder based on-road pedestrian tracking using visual SLAM and Constrained Multiple-Kernel,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+891ecd15c285aeb7286762b8a02e9897cd9df5a1,Driving recorder based on-road pedestrian tracking using visual SLAM and Constrained Multiple-Kernel,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+89f9fcc6b6bbc3c8c13f37d602d42a5c7196bcdd,Video Captioning via Hierarchical Reinforcement Learning,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
+892db59add66fc581ae1a7338ff8bd6b7aa0f2b4,FPGA-based Normalization for Modified Gram-Schmidt Orthogonalization,New Jersey Institute of Technology,New Jersey Institute of Technology,"New Jersey Institute of Technology, Warren Street, University Heights, Newark, Essex County, New Jersey, 07103, USA",40.74230250,-74.17928172,edu,
892c911ca68f5b4bad59cde7eeb6c738ec6c4586,"The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English",Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
8986585975c0090e9ad97bec2ba6c4b437419dae,Unsupervised Hard Example Mining from Videos for Improved Object Detection,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
89cabb60aa369486a1ebe586dbe09e3557615ef8,Bayesian Networks as Generative Models for Face Recognition,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+89887e95169efb35726cbeecf6a252de6fbcac3b,GroupCap : Group-based Image Captioning with Structured Relevance and Diversity Constraints,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+89887e95169efb35726cbeecf6a252de6fbcac3b,GroupCap : Group-based Image Captioning with Structured Relevance and Diversity Constraints,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
8983485996d5d9d162e70d66399047c5d01ac451,Deep feature-based face detection on mobile devices,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
8983485996d5d9d162e70d66399047c5d01ac451,Deep feature-based face detection on mobile devices,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+89e4f5a1eb6a97459bb748f4f7bc5c2696354aad,Semantics from Sound: Modeling Audio and Text Thesis Proposal,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
8981be3a69cd522b4e57e9914bf19f034d4b530c,Fast Automatic Video Retrieval using Web Images,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+891433740bf6d318782c468638722aebf8bef2f5,Multi-Frame Video Super-Resolution Using Convolutional Neural Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+891433740bf6d318782c468638722aebf8bef2f5,Multi-Frame Video Super-Resolution Using Convolutional Neural Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+89f73328e509e3ab2df01481cf55cb53050f6343,Cortical Surface Thickness as a Classifier: Boosting for Autism Classification,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+89f73328e509e3ab2df01481cf55cb53050f6343,Cortical Surface Thickness as a Classifier: Boosting for Autism Classification,University at Buffalo,State University of New York at Buffalo,"Buffalo, NY 14260, USA",43.00080930,-78.78896970,edu,
+89cdedb35b487bcf07d6f53aa91463ea2de8da66,Sketch and Match: Scene Montage Using a Huge Image Collection,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+89cdedb35b487bcf07d6f53aa91463ea2de8da66,Sketch and Match: Scene Montage Using a Huge Image Collection,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+89b4111f14cdf342188f96d3962581fd0afa042f,A Study and Comparison of Human and Deep Learning Recognition Performance under Visual Distortions,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+89dbfb9b75d3902748d73bfb5965e7d11e83c10e,Learning Discriminative Appearance-Based Models Using Partial Least Squares,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+893292315f5ecc73e84c5585900c53072de38550,Uncertainty Flow Facilitates Zero-Shot Multi-Label Learning in Affective Facial Analysis,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+898ef892b4cb9c206afc2daae04eacb1a7c7f956,Dump Truck Recognition Based on SCPSR in Videos,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+894a3ab0a3ef82352b2c294dd2bde2bd3403da8c,Recommending Outfits from Personal Closet,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
896f4d87257abd0f628c1ffbbfdac38c86a56f50,Action and Gesture Temporal Spotting with Super Vector Representation,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
896f4d87257abd0f628c1ffbbfdac38c86a56f50,Action and Gesture Temporal Spotting with Super Vector Representation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
896f4d87257abd0f628c1ffbbfdac38c86a56f50,Action and Gesture Temporal Spotting with Super Vector Representation,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+89c45ace90d377502dc84825e5039290927ae9e2,"Changes in vegetation persistence across global savanna landscapes , 1982 – 2010",University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+89c45ace90d377502dc84825e5039290927ae9e2,"Changes in vegetation persistence across global savanna landscapes , 1982 – 2010",University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
451b6409565a5ad18ea49b063561a2645fa4281b,Action Sets: Weakly Supervised Action Segmentation without Ordering Constraints,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+4576b59a44f75120f6a2d17a4e9c52e894297661,Learning Geo-Temporal Image Features,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+45483f17551d9c6b550474dc7168ec31302e5d7b,Face recognition via collaborative representation based multiple one-dimensional embedding,University of Macau,University of Macau,"研究生宿舍 Residência de Estudantes de Pós-Graduação da Universidade de Macau, 澳門大學 Universidade de Macau, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, Universidade de Macau em Ilha de Montanha 澳門大學橫琴校區, 中国",22.12401870,113.54510901,edu,
+45a44e61236f7c144d9ec11561e236b2960c7cf6,Multi-object Tracking with Neural Gating Using Bilinear LSTM,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+45a44e61236f7c144d9ec11561e236b2960c7cf6,Multi-object Tracking with Neural Gating Using Bilinear LSTM,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+454f403857e487d6a885180e0e0f7216a342fb0e,Unsupervised Learning of Multi-Level Descriptors for Person Re-Identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
455204fa201e9936b42756d362f62700597874c4,A Region Based Methodology for Facial Expression Recognition,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
455204fa201e9936b42756d362f62700597874c4,A Region Based Methodology for Facial Expression Recognition,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
+456abee9c8d31f004b2f0a3b47222043e20f5042,Unsupervised Visual Sense Disambiguation for Verbs using Multimodal Embeddings,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
4541c9b4b7e6f7a232bdd62ae653ba5ec0f8bbf6,The role of structural facial asymmetry in asymmetry of peak facial expressions.,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
4541c9b4b7e6f7a232bdd62ae653ba5ec0f8bbf6,The role of structural facial asymmetry in asymmetry of peak facial expressions.,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4541c9b4b7e6f7a232bdd62ae653ba5ec0f8bbf6,The role of structural facial asymmetry in asymmetry of peak facial expressions.,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4558338873556d01fd290de6ddc55721c633a1ad,Training Constrained Deconvolutional Networks for Road Scene Semantic Segmentation,Cambridge University,Cambridge University,"University, Cambridge Road, Old Portsmouth, Portsmouth, South East, England, PO1 2HB, UK",50.79440260,-1.09717480,edu,
4552f4d46a2cc67ccc4dd8568e5c95aa2eedb4ec,Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
4552f4d46a2cc67ccc4dd8568e5c95aa2eedb4ec,Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+45619a2b7b41fea02345badf880530519d3d4c8f,Learning Generalized Linear Models Over Normalized Data,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
459960be65dd04317dd325af5b7cbb883d822ee4,The Meme Quiz: A Facial Expression Game Combining Human Agency and Machine Involvement,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
45f858f9e8d7713f60f52618e54089ba68dfcd6d,What Actions are Needed for Understanding Human Actions in Videos?,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+45518c2350b9e727adf59f1626610917f71aea1e,Cross-Layer Design Space Exploration of Heterogeneous Multicore Processors With Predictive Models,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+45518c2350b9e727adf59f1626610917f71aea1e,Cross-Layer Design Space Exploration of Heterogeneous Multicore Processors With Predictive Models,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+45f4b06b7c9fa4cf548d33e40b2295b2d6ff806e,3D Generic Elastic Models for 2D Pose Synthesis and Face Recognition,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+45f4b06b7c9fa4cf548d33e40b2295b2d6ff806e,3D Generic Elastic Models for 2D Pose Synthesis and Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+45f4b06b7c9fa4cf548d33e40b2295b2d6ff806e,3D Generic Elastic Models for 2D Pose Synthesis and Face Recognition,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+45f4b06b7c9fa4cf548d33e40b2295b2d6ff806e,3D Generic Elastic Models for 2D Pose Synthesis and Face Recognition,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
45215e330a4251801877070c85c81f42c2da60fb,Domain Adaptive Dictionary Learning,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
45215e330a4251801877070c85c81f42c2da60fb,Domain Adaptive Dictionary Learning,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
457cf73263d80a1a1338dc750ce9a50313745d1d,Decomposing Motion and Content for Natural Video Sequence Prediction,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
457cf73263d80a1a1338dc750ce9a50313745d1d,Decomposing Motion and Content for Natural Video Sequence Prediction,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
45e616093a92e5f1e61a7c6037d5f637aa8964af,Fine-grained evaluation on face detection in the wild,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+45ff38add61df32a027048624f58952a67a7c5f5,Deep Context Convolutional Neural Networks for Semantic Segmentation,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+451eed7fd8ae281d1cc76ca8cdecbaf47816e55a,Close Yet Distinctive Domain Adaptation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+459b4d0ed3031e2fe5b3b3f176a5204dfb28157a,3D face landmark labelling,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+459b4d0ed3031e2fe5b3b3f176a5204dfb28157a,3D face landmark labelling,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+459b4d0ed3031e2fe5b3b3f176a5204dfb28157a,3D face landmark labelling,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+454dd76eb0a82286c054a6dd9d9413e09ad66801,Graph-Structured Representations for Visual Question Answering,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+4597b7c4f13e1dfc456d156c6c05502fc5d38eec,Human Action Adverb Recognition: ADHA Dataset and A Three-Stream Hybrid Model,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
45c31cde87258414f33412b3b12fc5bec7cb3ba9,Coding Facial Expressions with Gabor Wavelets,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+45e8ef229fae18b0a2ab328037d8e520866c3c81,Learning Feature Pyramids for Human Pose Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+45e8ef229fae18b0a2ab328037d8e520866c3c81,Learning Feature Pyramids for Human Pose Estimation,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
4542273a157bfd4740645a6129d1784d1df775d2,FaceRipper Automatic Face Indexer and Tagger for Personal Albums and Videos,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+4543052aeaf52fdb01fced9b3ccf97827582cef5,Quantized Densely Connected U-Nets for Efficient Landmark Localization,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+4543052aeaf52fdb01fced9b3ccf97827582cef5,Quantized Densely Connected U-Nets for Efficient Landmark Localization,Binghamton University,Binghamton University,"Binghamton University Downtown Center, Washington Street, Downtown, Binghamton, Broome County, New York, 13901, USA",42.09580770,-75.91455689,edu,
+4543052aeaf52fdb01fced9b3ccf97827582cef5,Quantized Densely Connected U-Nets for Efficient Landmark Localization,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
45513d0f2f5c0dac5b61f9ff76c7e46cce62f402,Face Discovery with Social Context,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+45a3ba54fc2210cf8a4fba0cbdce9dad3cefc826,Complete Cross-Validation for Nearest Neighbor Classifiers,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+45c182f8d003a2d505e4d1d491b5d03159a70b81,Training Generative Adversarial Networks Via Turing Test,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
450c6a57f19f5aa45626bb08d7d5d6acdb863b4b,Towards Interpretable Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+1f03f21ba6c1bf66b025029b10d4bc9bd7f65a81,VISCERAL: Towards Large Data in Medical Imaging - Challenges and Directions,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
1f9b2f70c24a567207752989c5bd4907442a9d0f,Deep Representations to Model User 'Likes',Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
1f9b2f70c24a567207752989c5bd4907442a9d0f,Deep Representations to Model User 'Likes',"Institute for Infocomm Research, Singapore","Institute for Infocomm Research, Singapore","1 Fusionopolis Way, #21-01 Connexis, Singapore 138632",1.29889260,103.78731070,edu,
1fe1bd6b760e3059fff73d53a57ce3a6079adea1,Fast-BoW: Scaling Bag-of-Visual-Words Generation,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
@@ -1816,100 +4899,276 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 1f89439524e87a6514f4fbe7ed34bda4fd1ce286,Devising Face Authentication System and Performance Evaluation Based on Statistical Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
1f89439524e87a6514f4fbe7ed34bda4fd1ce286,Devising Face Authentication System and Performance Evaluation Based on Statistical Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
1f89439524e87a6514f4fbe7ed34bda4fd1ce286,Devising Face Authentication System and Performance Evaluation Based on Statistical Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1f9102f425f28552e477cf71af0846550f3f9ed9,Incremental Domain Adaptation of Deformable Part-based Models,Universitat Autònoma de Barcelona,Universitat Autònoma de Barcelona,"Centre de Visió per Computador (CVC), Carrer de l'Albareda, Serraperera, UAB, Cerdanyola del Vallès, Vallès Occidental, BCN, CAT, 08214, España",41.50078110,2.11143663,edu,
1fd6004345245daf101c98935387e6ef651cbb55,Learning Symmetry Features for Face Detection Based on Sparse Group Lasso,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+1fc867b43092fe83c4e0bfa38a9a45ffaea86deb,Deep Speaker Embeddings for Short-Duration Speaker Verification,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+1f7b2087dd0784a04ba4d2a68c2db9588f36c33a,Modeling Sub-Event Dynamics in First-Person Action Recognition,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+1f7b2087dd0784a04ba4d2a68c2db9588f36c33a,Modeling Sub-Event Dynamics in First-Person Action Recognition,National University of Sciences and Technology,National University of Sciences and Technology,"National University of Sciences and Technology (NUST), Kashmir Highway, جی - 10, ICT, وفاقی دارالحکومت اسلام آباد, 44000, پاکستان",33.64434700,72.98850790,edu,
+1fd7e1f5dd4c514bfb3d77fceb454bc01de83ec8,Holistic Shape-Based Object Recognition Using Bottom-Up Image Structures,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+1fd7e1f5dd4c514bfb3d77fceb454bc01de83ec8,Holistic Shape-Based Object Recognition Using Bottom-Up Image Structures,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+1f61c1ba961c6328923f4c6219c6889ccb538506,"Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures","CSIRO, Australia","NICTA, PO Box 6020, St Lucia, QLD 4067, Australia","Research Way, Clayton VIC 3168, Australia",-37.90627370,145.13194490,edu,f.k.a. NICTA
+1f61c1ba961c6328923f4c6219c6889ccb538506,"Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures",University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+1f27f9c0da385080f05f8cfaf0771e5aee6d9ab2,Towards Robust 3D Face Verification using Gaussian Mixture Models,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+1f4b741a9da2fb7623ff68c8e1df3f3cce5e2542,Activity Recognition in Egocentric Life-Logging Videos,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
+1f4b741a9da2fb7623ff68c8e1df3f3cce5e2542,Activity Recognition in Egocentric Life-Logging Videos,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
1fe59275142844ce3ade9e2aed900378dd025880,Facial Landmark Detection via Progressive Initialization,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+1f1b4e91c6e6699a2191d1d62a0304870163e48e,Attention on Attention: Architectures for Visual Question Answering (VQA),Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1f1b4e91c6e6699a2191d1d62a0304870163e48e,Attention on Attention: Architectures for Visual Question Answering (VQA),Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1f1b4e91c6e6699a2191d1d62a0304870163e48e,Attention on Attention: Architectures for Visual Question Answering (VQA),Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1f527b5406356018e6dc401a4be8098a5a451891,Multiple Vehicle-like Target Tracking Based on the Velodyne LiDAR ?,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+1f527b5406356018e6dc401a4be8098a5a451891,Multiple Vehicle-like Target Tracking Based on the Velodyne LiDAR ?,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+1f527b5406356018e6dc401a4be8098a5a451891,Multiple Vehicle-like Target Tracking Based on the Velodyne LiDAR ?,Jacobs University,Jacobs University,"Liverpool Hope University, Shaw Street, Everton, Liverpool, North West England, England, L6 1HP, UK",53.41291480,-2.96897915,edu,
+1f877687022f7b222c7ae1ec4ec21655a290220d,Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+1f877687022f7b222c7ae1ec4ec21655a290220d,Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+1f877687022f7b222c7ae1ec4ec21655a290220d,Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis,South China Normal University,South China Normal University,"华师, 五山路, 华南理工大学南新村, 天河区, 广州市, 广东省, 510630, 中国",23.14319700,113.34009651,edu,
1fe121925668743762ce9f6e157081e087171f4c,Unsupervised learning of overcomplete face descriptors,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
1fefb2f8dd1efcdb57d5c2966d81f9ab22c1c58d,vExplorer: A Search Method to Find Relevant YouTube Videos for Health Researchers,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
1fdeba9c4064b449231eac95e610f3288801fd3e,Fine-Grained Head Pose Estimation Without Keypoints,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+1f2497491ee465f299eaa8a769640cf4f084ee09,Crowd Counting via Adversarial Cross-Scale Consistency Pursuit,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+1f56d8442452c527140909d9f5b857b7eb7c997d,A Robust and Compact Descriptor Based on Center-Symmetric LBP,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
1f745215cda3a9f00a65166bd744e4ec35644b02,Facial cosmetics database and impact analysis on automatic face recognition,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
1fd3dbb6e910708fa85c8a86e17ba0b6fef5617c,Age interval and gender prediction using PARAFAC2 on speech recordings and face images,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+1f4aa88107d7c4b91b1436b721b7630b93ce7d06,Deeply Learned Compositional Models for Human Pose Estimation,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
1f24cef78d1de5aa1eefaf344244dcd1972797e8,Outlier-Robust Tensor PCA,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
1fe990ca6df273de10583860933d106298655ec8,A Wavelet-Based Image Preprocessing Method or Illumination Insensitive Face Recognition,Hunan University,Hunan University,"Yejin University for Employees, 冶金西路, 和平乡, 珠晖区, 衡阳市 / Hengyang, 湖南省, 中国",26.88111275,112.62850666,edu,
1feeab271621128fe864e4c64bab9b2e2d0ed1f1,Perception-Link Behavior Model: Supporting a Novel Operator Interface for a Customizable Anthropomorphic Telepresence Robot,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
73b90573d272887a6d835ace89bfaf717747c59b,Feature Disentangling Machine - A Novel Approach of Feature Selection and Disentangling in Facial Expression Analysis,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
+7363cc7e0c5b43ec12ba47bca587a325f719398a,Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+73298c5610004a8337baeb79f33c1519c0ba59e4,Computing Egomotion with Local Loop Closures for Egocentric Videos,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+73298c5610004a8337baeb79f33c1519c0ba59e4,Computing Egomotion with Local Loop Closures for Egocentric Videos,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+73acee80dbcf4ed119d863e4ad6c7bf1bcc542ca,Using Human Knowledge to Judge Part Goodness: Interactive Part Selection,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+737f3cf354f40a6a7fd8a2058fe2803b8dd6c56b,Image Crowd Counting Using Convolutional Neural Network and Markov Random Field,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+737f3cf354f40a6a7fd8a2058fe2803b8dd6c56b,Image Crowd Counting Using Convolutional Neural Network and Markov Random Field,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+735418826055951ba8660bb008d92bfe6910330e,An Evaluation of Local Action Descriptors for Human Action Classification in the Presence of Occlusion,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+73f4be4b6e56f5bde875a8987f90ba799dde35b2,Deep Spatial Regression Model for Image Crowd Counting,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+73f4be4b6e56f5bde875a8987f90ba799dde35b2,Deep Spatial Regression Model for Image Crowd Counting,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+73ea06787925157df519a15ee01cc3dc1982a7e0,Fast Face Image Synthesis with Minimal Training,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+7372c1e9cb87dad88bc160536263e461bb7ab04c,Trajectory Energy Minimisation for Cell Growth Tracking and Genealogy Analysis,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+7357f37a193992f06eba68ee71faef8c093e8aba,Pose-Invariant Face Recognition in Hyperspectral Images,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+7358fe63042e186c03df0fb2d5f933eda94cb36a,It Takes Two to Tango: Towards Theory of AI's Mind,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
739d400cb6fb730b894182b29171faaae79e3f01,A New Regularized Orthogonal Local Fisher Discriminant Analysis for Image Feature Extraction,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+73d15a975b0595e0cc2e0981a9396a89c474dc7e,Gender Effect on Face Recognition for a Large Longitudinal Database,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
732e4016225280b485c557a119ec50cffb8fee98,Are all training examples equally valuable?,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
732e4016225280b485c557a119ec50cffb8fee98,Are all training examples equally valuable?,Universitat Oberta de Catalunya,Universitat Oberta de Catalunya,"Universitat Oberta de Catalunya, 156, Rambla del Poblenou, Provençals del Poblenou, Sant Martí, Barcelona, BCN, CAT, 08018, España",41.40657415,2.19453410,edu,
732e4016225280b485c557a119ec50cffb8fee98,Are all training examples equally valuable?,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
732e4016225280b485c557a119ec50cffb8fee98,Are all training examples equally valuable?,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
732e4016225280b485c557a119ec50cffb8fee98,Are all training examples equally valuable?,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+73e4076a532ec6a0633aed5cf6009414cdaf1f6a,Illumination Normalization Using Self-lighting Ratios for 3D2D Face Recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
738a985fba44f9f5acd516e07d0d9578f2ffaa4e,Machine Learning Techniques for Face Analysis,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
73fd7e74457e0606704c5c3d3462549f1b2de1ad,Learning Predictable and Discriminative Attributes for Visual Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
73c5bab5c664afa96b1c147ff21439135c7d968b,Whitened LDA for face recognition,Kyung Hee University,Kyung Hee University,"Kyung Hee Tae Kwon Do, Vons 2370 Truck Service Ramp, University City, San Diego, San Diego County, California, 92122, USA",32.85363330,-117.20352860,edu,
73c5bab5c664afa96b1c147ff21439135c7d968b,Whitened LDA for face recognition,Kyung Hee University,Kyung Hee University,"Kyung Hee Tae Kwon Do, Vons 2370 Truck Service Ramp, University City, San Diego, San Diego County, California, 92122, USA",32.85363330,-117.20352860,edu,
73c5bab5c664afa96b1c147ff21439135c7d968b,Whitened LDA for face recognition,SungKyunKwan University,SungKyunKwan University,"성균관대, 덕영대로, 천천동, 장안구, 수원시, 경기, 16357, 대한민국",37.30031270,126.97212300,edu,
+738fadaf40249146f33da5b9efbb72a1fdf8767d,Unsupervised Learning of Invariant Representations in Hierarchical Architectures,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+739e67fe178d1f96419846b34d6b2a90e6f7d3c1,A Pursuit Method for Video Annotation by Zoltan Foley-Fisher A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+87defac1045bfa9af0162cd248d193e9be6eb25b,Out of Time: Automated Lip Sync in the Wild,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+87a4711136040f5d6929d7e31d8dae881afa5d3f,Hand-tremor frequency estimation in videos,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+87cf55164a7cc676b68e84b7f39fcdbf7610ece4,Choosing Multi-illumination training Images based on the degree of linear independency,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
877100f430b72c5d60de199603ab5c65f611ce17,Within-person variability in men’s facial width-to-height ratio,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+8797c870c0881cd30fda186affee4bdec54aeecd,Binary Biometric Representation through Pairwise Adaptive Phase Quantization,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+87e05a26fb4c45dbe2b0b10c8ab20e7662d46912,Face engagement during infancy predicts later face recognition ability in younger siblings of children with autism.,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
870433ba89d8cab1656e57ac78f1c26f4998edfb,Regressing Robust and Discriminative 3D Morphable Models with a Very Deep Neural Network,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
872dfdeccf99bbbed7c8f1ea08afb2d713ebe085,L2-constrained Softmax Loss for Discriminative Face Verification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
87e6cb090aecfc6f03a3b00650a5c5f475dfebe1,Holistically Constrained Local Model: Going Beyond Frontal Poses for Facial Landmark Detection,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
87e6cb090aecfc6f03a3b00650a5c5f475dfebe1,Holistically Constrained Local Model: Going Beyond Frontal Poses for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+87d1283ccc9bfb0c550ebed8ec0b025dc14b160f,"TVQA: Localized, Compositional Video Question Answering",University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+87b5d74ae97a991bf5b45f0f947525234c37d370,Noise Modelling for Denoising and 3 D Face Recognition Algorithms Performance Evaluation,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+87e4d8e0fc4019405001683678cd199fc9936369,Kernelized Multiview Projection,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+878634c30842b5812c56fe772719424bab69e7ad,Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+8758775ff9fa05b05f98a43cf5effe6b08cc1241,Deep Hashing via Discrepancy Minimization,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+8758775ff9fa05b05f98a43cf5effe6b08cc1241,Deep Hashing via Discrepancy Minimization,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+8758775ff9fa05b05f98a43cf5effe6b08cc1241,Deep Hashing via Discrepancy Minimization,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+87b763bdb23ed72e849f25a19879722dc2255ab1,Unsupervised Adversarial Depth Estimation Using Cycled Generative Networks,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+87b763bdb23ed72e849f25a19879722dc2255ab1,Unsupervised Adversarial Depth Estimation Using Cycled Generative Networks,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
8724fc4d6b91eebb79057a7ce3e9dfffd3b1426f,Ordered Pooling of Optical Flow Sequences for Action Recognition,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+8748c232a93cfe595de6938f209a170fca51c1d5,Eye Tracking for Everyone,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+87dd1c52a3805c59eeab527b8c8c1214415026a6,A Generative-Discriminative Hybrid Method for Multi-View Object Detection,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+87dd1c52a3805c59eeab527b8c8c1214415026a6,A Generative-Discriminative Hybrid Method for Multi-View Object Detection,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
87309bdb2b9d1fb8916303e3866eca6e3452c27d,Kernel Coding: General Formulation and Special Cases,"Australian National University, Canberra","Australian National University, Canberra","Australian National University, Garran Road, Acton, Canberra, Canberra Central, Australian Capital Territory, 2601, Australia",-35.28121335,149.11665331,edu,
+87d0c3359a9a99fddfbc5a388e211762a79ed5d7,Why Did the Person Cross the Road (There)? Scene Understanding Using Probabilistic Logic Models and Common Sense Reasoning,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+87cd95dbe885762ec0f733bc9d232eb4d63cc995,Multilinear Hyperplane Hashing,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+87cd95dbe885762ec0f733bc9d232eb4d63cc995,Multilinear Hyperplane Hashing,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+87cd95dbe885762ec0f733bc9d232eb4d63cc995,Multilinear Hyperplane Hashing,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+87a66ccc68374ffb704ee6fb9fa7df369718095c,Multi-person Pose Estimation with Local Joint-to-Person Associations,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+871e6c1de2e0ba86bad8975b8411ad76a6a9aef9,Geometric Modeling of 3D-Face Features and Its Applications,Indian Institute of Technology Kanpur,Indian Institute of Technology Kanpur,"Indian Institute of Technology Kanpur, 4th Avenue, Panki, Kanpur, Kanpur Nagar, Uttar Pradesh, 208016, India",26.51318800,80.23651945,edu,
+87747b6a1bff0944fc3e4891de9c3ba8868aef66,Body pose based pedestrian tracking in a particle filtering framework,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
87147418f863e3d8ff8c97db0b42695a1c28195b,Attributes for Improved Attributes: A Multi-Task Network for Attribute Classification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+87204e4e1a96b8f59cb91828199dacd192292231,Towards Real-Time Detection and Tracking of Basketball Players using Deep Neural Networks,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+8732d702aeb08e9c604b36dcaa5933aea91a228d,Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+8732d702aeb08e9c604b36dcaa5933aea91a228d,Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+87b9d7d4f5fcef5680b9e74ce50c76be504c70a5,Scene specific people detection by simple human interaction,University of Padova,University of Padova,"Via Giovanni Gradenigo, 6, 35131 Padova PD, Italy",45.40811720,11.89437860,edu,"University of Padova, Via Gradenigo, 6 - 35131- Padova, Italy"
+87b9d7d4f5fcef5680b9e74ce50c76be504c70a5,Scene specific people detection by simple human interaction,University of Padova,University of Padova,"Via Giovanni Gradenigo, 6, 35131 Padova PD, Italy",45.40811720,11.89437860,edu,"University of Padova, Via Gradenigo, 6 - 35131- Padova, Italy"
+87e207fa31099d20450e60f056a0b1304dbc1bfa,Probabilistic fusion of regional scores in 3D face recognition,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+877397982198554e9294f0ddddd8d971cc87cefe,Understanding Degeneracies and Ambiguities in Attribute Transfer,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+80488ff21f7b69c1c9d20d88514a42bdad2602f4,"Unsupervised Depth Estimation, 3D Face Rotation and Replacement",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+806f466034e0c3e609e672559e23d5d8bea6fe3d,Adaptive memory: The mnemonic value of contamination,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+8052bc5f9beb389b3144d423e7b5d6fcf5d0cc4f,Adapting attributes by selecting features similar across domains,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+806d7b97c3535a3c62ce243fe7008149062d14c1,Learning to Count with CNN Boosting,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+80433f3c41f383abf495ff2b368616af6d545694,Robust Scene Text Detection with Convolution Neural Network Induced MSER Trees,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+80433f3c41f383abf495ff2b368616af6d545694,Robust Scene Text Detection with Convolution Neural Network Induced MSER Trees,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+8042b633b35aee9402bc2369b5c25413d2abc271,Nonnegative matrix factorization with α-divergence,Pohang University of Science and Technology,Pohang University of Science and Technology,"포스텍, 77, 청암로, 효곡동, 남구, 포항시, 경북, 37673, 대한민국",36.01773095,129.32107509,edu,
+80471bb250eca1be53a455489e187c0152ac78b9,DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
808b685d09912cbef4a009e74e10476304b4cccf,From Understanding to Controlling Privacy against Automatic Person Recognition in Social Media,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+80c8f118f37f990905205eee4f3b3811e0488bf9,Spatio-temporal Matching for Human Detection in Video,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+80c8f118f37f990905205eee4f3b3811e0488bf9,Spatio-temporal Matching for Human Detection in Video,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8050f9b0f9ee0953e6125cd9b8211bb792953642,Pose and Shape Estimation with Discriminatively Learned Parts,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+80f53cece53b82915e096f3ad1730f9ce7ee5808,Ensemble of Randomized Linear Discriminant Analysis for face recognition with single sample per person,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+80f53cece53b82915e096f3ad1730f9ce7ee5808,Ensemble of Randomized Linear Discriminant Analysis for face recognition with single sample per person,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+80f53cece53b82915e096f3ad1730f9ce7ee5808,Ensemble of Randomized Linear Discriminant Analysis for face recognition with single sample per person,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
80277fb3a8a981933533cf478245f262652a33b5,Synergy-Based Learning of Facial Identity,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+80f5443b0204f28c44ee2dd94e72f8dbfa22910d,Visual Object Categorization using Topic Models,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
80840df0802399838fe5725cce829e1b417d7a2e,Fast Approximate L_infty Minimization: Speeding Up Robust Regression,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
80840df0802399838fe5725cce829e1b417d7a2e,Fast Approximate L_infty Minimization: Speeding Up Robust Regression,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+80eab89ff1c5c2cfc1ea62e2088cfc9b62de8d35,Emergent Translation in Multi-Agent Communication,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+80eab89ff1c5c2cfc1ea62e2088cfc9b62de8d35,Emergent Translation in Multi-Agent Communication,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
809ea255d144cff780300440d0f22c96e98abd53,ArcFace: Additive Angular Margin Loss for Deep Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
809ea255d144cff780300440d0f22c96e98abd53,ArcFace: Additive Angular Margin Loss for Deep Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+805b42d42a52e1e5e20de8950dc18ec9323575a7,Recurrent Neural Networks for Person Re-identification Revisited,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+805b42d42a52e1e5e20de8950dc18ec9323575a7,Recurrent Neural Networks for Person Re-identification Revisited,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+80fcc4e66906d04e14f5ebc68b0a17d4e5ff0194,Predictor Combination at Test Time,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+80fcc4e66906d04e14f5ebc68b0a17d4e5ff0194,Predictor Combination at Test Time,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+80fcc4e66906d04e14f5ebc68b0a17d4e5ff0194,Predictor Combination at Test Time,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+8027f50bbcee3938196c6d5519464df16c275f8d,On Human Motion Prediction Using Recurrent Neural Networks,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
80be8624771104ff4838dcba9629bacfe6b3ea09,Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
80be8624771104ff4838dcba9629bacfe6b3ea09,Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
80be8624771104ff4838dcba9629bacfe6b3ea09,Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
80be8624771104ff4838dcba9629bacfe6b3ea09,Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
8000c4f278e9af4d087c0d0895fff7012c5e3d78,Multi-task warped Gaussian process for personalized age estimation,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
80bd795930837330e3ced199f5b9b75398336b87,Relative Forest for Attribute Prediction,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+74fcbd059e6749ee5073b7323d121132799f97a1,Gait-Assisted Person Re-identification in Wide Area Surveillance,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+74cefa1d796c84dc4343fdf383f15ca1e8ebb6ba,Low Resolution Camera for Human Detection and Tracking,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
74de03923a069ffc0fb79e492ee447299401001f,On Film Character Retrieval in Feature-Length Films,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
74de03923a069ffc0fb79e492ee447299401001f,On Film Character Retrieval in Feature-Length Films,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
74f643579949ccd566f2638b85374e7a6857a9fc,Monogenic Binary Pattern (MBP): A Novel Feature Extraction and Representation Model for Face Recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+7481b7d5272326f4e9efcd49d31c7f42adb8ec4b,Weighted Bilinear Coding over Salient Body Parts for Person Re-identification,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+7481b7d5272326f4e9efcd49d31c7f42adb8ec4b,Weighted Bilinear Coding over Salient Body Parts for Person Re-identification,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+7481b7d5272326f4e9efcd49d31c7f42adb8ec4b,Weighted Bilinear Coding over Salient Body Parts for Person Re-identification,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+7481b7d5272326f4e9efcd49d31c7f42adb8ec4b,Weighted Bilinear Coding over Salient Body Parts for Person Re-identification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
74ce7e5e677a4925489897665c152a352c49d0a2,SPG-Net: Segmentation Prediction and Guidance Network for Image Inpainting,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+74e1efe5e3564c4c6a9aebcb18103e941e31e335,High Fidelity Semantic Shape Completion for Point Clouds using Latent Optimization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+74e1efe5e3564c4c6a9aebcb18103e941e31e335,High Fidelity Semantic Shape Completion for Point Clouds using Latent Optimization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+741e2682b45a3dccab341cf272312a3c75c4b49a,A Diverse Dataset for Pedestrian Detection,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+741e2682b45a3dccab341cf272312a3c75c4b49a,A Diverse Dataset for Pedestrian Detection,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
740e095a65524d569244947f6eea3aefa3cca526,Towards Human-like Performance Face Detection: A Convolutional Neural Network Approach,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
74e869bc7c99093a5ff9f8cfc3f533ccf1b135d8,Context and Subcategories for SlidingWindowObject Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
74e869bc7c99093a5ff9f8cfc3f533ccf1b135d8,Context and Subcategories for SlidingWindowObject Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
741485741734a99e933dd0302f457158c6842adf,A Novel Automatic Facial Expression Recognition Method Based on AAM,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+747fdee12e633addeae3b74c12643cbac2c925ec,Deep Differential Recurrent Neural Networks,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+747fdee12e633addeae3b74c12643cbac2c925ec,Deep Differential Recurrent Neural Networks,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+747fdee12e633addeae3b74c12643cbac2c925ec,Deep Differential Recurrent Neural Networks,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+74cce11cfd25618b0fee0bcceb2f23376121a1f6,Exploring Inter-Observer Differences in First-Person Object Views Using Deep Learning Models,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+74cce11cfd25618b0fee0bcceb2f23376121a1f6,Exploring Inter-Observer Differences in First-Person Object Views Using Deep Learning Models,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+74113bb67eef4cfa28ebfa8bd38a614c82bdfdea,Neural responses to facial expressions support the role of the amygdala in processing threat.,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+74113bb67eef4cfa28ebfa8bd38a614c82bdfdea,Neural responses to facial expressions support the role of the amygdala in processing threat.,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
748e72af01ba4ee742df65e9c030cacec88ce506,Discriminative Regions Selection for Facial Expression Recognition,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
748e72af01ba4ee742df65e9c030cacec88ce506,Discriminative Regions Selection for Facial Expression Recognition,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
74875368649f52f74bfc4355689b85a724c3db47,Object detection by labeling superpixels,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+744499b779a751bcc3a43a45eab6f7704140a701,Propagating LSTM: 3D Pose Estimation Based on Joint Interdependency,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
7492c611b1df6bce895bee6ba33737e7fc7f60a6,The 3D Menpo Facial Landmark Tracking Challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
7492c611b1df6bce895bee6ba33737e7fc7f60a6,The 3D Menpo Facial Landmark Tracking Challenge,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
7492c611b1df6bce895bee6ba33737e7fc7f60a6,The 3D Menpo Facial Landmark Tracking Challenge,University of Exeter,University of Exeter,"University of Exeter, Stocker Road, Exwick, Exeter, Devon, South West England, England, EX4 4QN, UK",50.73693020,-3.53647672,edu,
+74ba4ba7a2c97826690b9d45edcc82532d1039bc,Gait Gate: An Online Walk-Through Multimodal Biometric Verification System Using a Single RGB-D Sensor,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+74ba4ba7a2c97826690b9d45edcc82532d1039bc,Gait Gate: An Online Walk-Through Multimodal Biometric Verification System Using a Single RGB-D Sensor,Benha University,Benha University,"كلية الهندسة بشبرا جامعة بنها, شارع اليازجي, روض الفرج, القاهرة, محافظة القاهرة, 2466, مصر",30.08187270,31.24454841,edu,
+74dbcc09a3456ddacf5cece640b84045ebdf6be1,Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+74dbcc09a3456ddacf5cece640b84045ebdf6be1,Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+743c7e1aef6461d6582cf8deeb5d518e45215f89,Looking you in the mouth: abnormal gaze in autism resulting from impaired top-down modulation of visual attention.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+743c7e1aef6461d6582cf8deeb5d518e45215f89,Looking you in the mouth: abnormal gaze in autism resulting from impaired top-down modulation of visual attention.,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+74b9d1e80d3df707963fad57c50d7c25936da535,Reward Learning from Narrated Demonstrations,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7489990ea3d6ab4c1c86c9ed9f049399961dfaef,Normalized cutswith soft must-link constraints for image segmentation and clustering,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+74f17647637fe068e237d8d5a8cc37e081ec03d0,Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+74f17647637fe068e237d8d5a8cc37e081ec03d0,Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+1a229f1d21abe442520cba31a6e08663b3d31777,The heterogeneous block architecture,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1afdc0b42d25df25a7cd4b304493e9b521c84f0f,Algorithm 1 Dynamic Graph Matching ( DGM ) Input : Unlabelled features,Hong Kong Baptist University,Hong Kong Baptist University,"香港浸會大學 Hong Kong Baptist University, 安明街 On Ming Street, 石門 Shek Mun, 石古壟 Shek Kwu Lung, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1132, 中国",22.38742010,114.20822220,edu,
+1afdc0b42d25df25a7cd4b304493e9b521c84f0f,Algorithm 1 Dynamic Graph Matching ( DGM ) Input : Unlabelled features,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
1a41e5d93f1ef5b23b95b7163f5f9aedbe661394,Alignment-Free and High-Frequency Compensation in Face Hallucination,Ritsumeikan University,Ritsumeikan University,"立命館大学 (Ritsumeikan University), 衣笠宇多野線, 北区, 京都市, 京都府, 近畿地方, 6038577, 日本",35.03332810,135.72491540,edu,
+1ac20a7a76f7b83ccd8ea0aab64e2b24ecd23915,Impaired social brain network for processing dynamic facial expressions in autism spectrum disorders,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
1a65cc5b2abde1754b8c9b1d932a68519bcb1ada,Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
1a65cc5b2abde1754b8c9b1d932a68519bcb1ada,Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
1aa766bbd49bac8484e2545c20788d0f86e73ec2,"Baseline face detection, head pose estimation, and coarse direction detection for facial data in the SHRP2 naturalistic driving study",Oak Ridge National Laboratory,Oak Ridge National Laboratory,"Oak Ridge National Laboratory, Oak Ridge, Roane County, Tennessee, USA",35.93006535,-84.31240032,edu,
1a46d3a9bc1e4aff0ccac6403b49a13c8a89fc1d,Online robust image alignment via iterative convex optimization,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
1a46d3a9bc1e4aff0ccac6403b49a13c8a89fc1d,Online robust image alignment via iterative convex optimization,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+1a5340212809bbbce6e0d61720209179dcaa8a26,Backing Off: Hierarchical Decomposition of Activity for 3D Novel Pose Recovery,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+1a5340212809bbbce6e0d61720209179dcaa8a26,Backing Off: Hierarchical Decomposition of Activity for 3D Novel Pose Recovery,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+1ab56eb6128da34027242b1314e51b9b18b960db,Object Detection by 3D Aspectlets and Occlusion Reasoning,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+1ab56eb6128da34027242b1314e51b9b18b960db,Object Detection by 3D Aspectlets and Occlusion Reasoning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1a257ff73b1dd95f905dbbce9bb233033d09e959,A New Gabor Phase Difference Pattern for Face and Ear Recognition,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+1a30e44d6b70d11f7b270c87eac099b75b2263f1,Understanding the Nature of First-Person Videos: Characterization and Classification Using Low-Level Features,"Institute for Infocomm Research, Singapore","Institute for Infocomm Research, Singapore","1 Fusionopolis Way, #21-01 Connexis, Singapore 138632",1.29889260,103.78731070,edu,
+1a86eb42952412ee02e3f6da06f874f1946eff6b,Deep Cross-Modal Projection Learning for Image-Text Matching,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
+1a5d52e026f877f682bec19d0edb81aedc6e14a1,Robust Gaze Estimation via Normalized Iris Center-Eye Corner Vector,University of Portsmouth,University of Portsmouth,"University of Portsmouth - North Zone, Portland Street, Portsea, Portsmouth, South East, England, PO1 3DE, UK",50.79805775,-1.09834911,edu,
+1a5d52e026f877f682bec19d0edb81aedc6e14a1,Robust Gaze Estimation via Normalized Iris Center-Eye Corner Vector,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
1ac2882559a4ff552a1a9956ebeadb035cb6df5b,How much training data for facial action unit detection?,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
1ac2882559a4ff552a1a9956ebeadb035cb6df5b,How much training data for facial action unit detection?,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
1a7a17c4f97c68d68fbeefee1751d349b83eb14a,Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+1a39ce3f624844a1288b6deff545f6c4d79c4fae,DeePM: A Deep Part-Based Model for Object Detection and Semantic Part Localization,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
1aef6f7d2e3565f29125a4871cd60c4d86c48361,Subhashini VenugopalanProposal,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+1adbcca753c7b4f22cf3d6bc3a9579573d4d5846,Sample-Specific SVM Learning for Person Re-identification,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
1a167e10fe57f6d6eff0bb9e45c94924d9347a3e,Boosting VLAD with double assignment using deep features for action recognition in videos,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
1a167e10fe57f6d6eff0bb9e45c94924d9347a3e,Boosting VLAD with double assignment using deep features for action recognition in videos,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
1a167e10fe57f6d6eff0bb9e45c94924d9347a3e,Boosting VLAD with double assignment using deep features for action recognition in videos,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
1a167e10fe57f6d6eff0bb9e45c94924d9347a3e,Boosting VLAD with double assignment using deep features for action recognition in videos,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
1a167e10fe57f6d6eff0bb9e45c94924d9347a3e,Boosting VLAD with double assignment using deep features for action recognition in videos,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+1a86568fdba2b85a9f0b69d563dd22aa5a8d3562,Perceptual Fidelity Aware Mean Squared Error,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+1a86568fdba2b85a9f0b69d563dd22aa5a8d3562,Perceptual Fidelity Aware Mean Squared Error,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+1adb6341dd9bfe88d631009992fe8a4ef80e2f2b,A Simple and Fast Word Spotting Method,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
1a140d9265df8cf50a3cd69074db7e20dc060d14,Face Parts Localization Using Structured-Output Regression Forests,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+1ac85387b1d5a05f752ddf671763f02e923a2a03,Deep Learning with Sets and Point Clouds,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
1a85956154c170daf7f15f32f29281269028ff69,Active Pictorial Structures,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+1aad2da473888cb7ebc1bfaa15bfa0f1502ce005,First-Person Activity Recognition: What Are They Doing to Me?,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+1a1f63cbd8465d1bbee9bca24124b52ea4ec2762,Multilinear Multitask Learning,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+1a1f63cbd8465d1bbee9bca24124b52ea4ec2762,Multilinear Multitask Learning,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+1a1f63cbd8465d1bbee9bca24124b52ea4ec2762,Multilinear Multitask Learning,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+1a5a79b4937b89420049bc279a7b7f765d143881,Are Rich People Perceived as More Trustworthy? Perceived Socioeconomic Status Modulates Judgments of Trustworthiness and Trust Behavior Based on Facial Appearance,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+1a5a79b4937b89420049bc279a7b7f765d143881,Are Rich People Perceived as More Trustworthy? Perceived Socioeconomic Status Modulates Judgments of Trustworthiness and Trust Behavior Based on Facial Appearance,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+1a5a79b4937b89420049bc279a7b7f765d143881,Are Rich People Perceived as More Trustworthy? Perceived Socioeconomic Status Modulates Judgments of Trustworthiness and Trust Behavior Based on Facial Appearance,Virginia Commonwealth University,Virginia Commonwealth University,"Virginia Commonwealth University, The Compass, Oregon Hill, Richmond, Richmond City, Virginia, 23284, USA",37.54821500,-77.45306424,edu,
+1a12eec3ceb1c81cde4ae6e8f27aac08b36317d4,Real-time Distracted Driver Posture Classification,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
+1a12eec3ceb1c81cde4ae6e8f27aac08b36317d4,Real-time Distracted Driver Posture Classification,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
+1a790c7669943af5868e49d15cf282cbbd506f02,An Overview of Recent Progress in Volumetric Semantic 3 D Reconstruction ( Invited Paper ),ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
1a4b6ee6cd846ef5e3030a6ae59f026e5f50eda6,Deep Learning for Video Classification and Captioning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
1af52c853ff1d0ddb8265727c1d70d81b4f9b3a9,Face Recognition Under Illumination Variation Using Shadow Compensation and Pixel Selection,Dankook University,Dankook University,"단국대학교 치과병원, 죽전로, 죽전동, 수지구, 용인시, 경기, 16900, 대한민국",37.32195750,127.12507230,edu,
+1a0a06e659eb075d414286d61bd36931770db799,Relaxed Pairwise Learned Metric for Person Re-identification,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+1a398504e8822e4d079167be9684096fe862c0d5,Handling Data Imbalance in Automatic Facial Action Intensity Estimation,Otto von Guericke University,Otto von Guericke University,"Otto-von-Guericke-Universität Magdeburg, 2, Universitätsplatz, Krökentorviertel/Breiter Weg NA, Alte Neustadt, Magdeburg, Sachsen-Anhalt, 39106, Deutschland",52.14005065,11.64471248,edu,
1a40092b493c6b8840257ab7f96051d1a4dbfeb2,Sports Videos in the Wild (SVW): A video dataset for sports analysis,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
1a6c9ef99bf0ab9835a91fe5f1760d98a0606243,ConceptMap: Mining Noisy Web Data for Concept Learning,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+1ae3dd081b93c46cda4d72100d8b1d59eb585157,Online Motion Agreement Tracking,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+1a660d8576ed749610e0e040076d27973aee44ee,Tracking by Identification Using Computer Vision and Radio,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+1a2e9a56e5f71bf95a2f68b6e67e2aaa1c6bf91e,FPM: Fine Pose Parts-Based Model with 3D CAD Models,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+1a07d9213a6082d69f40bb5373da60ba0d19f2d6,Video Person Re-identification with Competitive Snippet-similarity Aggregation and Co-attentive Snippet Embedding,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+1ab881ec87167af9071b2ad8ff6d4ce3eee38477,Finding Happiest Moments in a Social Context,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+1ab881ec87167af9071b2ad8ff6d4ce3eee38477,Finding Happiest Moments in a Social Context,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
1afdedba774f6689eb07e048056f7844c9083be9,Markov Random Field Structures for Facial Action Unit Intensity Estimation,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
1afdedba774f6689eb07e048056f7844c9083be9,Markov Random Field Structures for Facial Action Unit Intensity Estimation,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
1a2b3fa1b933042687eb3d27ea0a3fcb67b66b43,Max-margin Latent Dirichlet Allocation for Image Classification and Annotation,Fraser University,Fraser University,"Fraser, 3333, University Avenue Southeast, Prospect Park - East River Road, Minneapolis, Hennepin County, Minnesota, 55414, USA",44.96898360,-93.20941629,edu,
+285356448b8d6e4bd84c67758502a76336f30b0e,A Dataset and Architecture for Visual Reasoning with a Working Memory,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+285356448b8d6e4bd84c67758502a76336f30b0e,A Dataset and Architecture for Visual Reasoning with a Working Memory,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
2878b06f3c416c98496aad6fc2ddf68d2de5b8f6,Two-Stage Optimal Component Analysis,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
2878b06f3c416c98496aad6fc2ddf68d2de5b8f6,Two-Stage Optimal Component Analysis,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
2878b06f3c416c98496aad6fc2ddf68d2de5b8f6,Two-Stage Optimal Component Analysis,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+28b8d20162f007eab1acd9d7cdb8baac914de820,Unlimited Road-scene Synthetic Annotation (URSA) Dataset,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
28a900a07c7cbce6b6297e4030be3229e094a950,Local directional pattern variance (ldpv): a robust feature descriptor for facial expression recognition,Kyung Hee University,Kyung Hee University,"Kyung Hee Tae Kwon Do, Vons 2370 Truck Service Ramp, University City, San Diego, San Diego County, California, 92122, USA",32.85363330,-117.20352860,edu,
282503fa0285240ef42b5b4c74ae0590fe169211,Feeding Hand-Crafted Features for Enhancing the Performance of Convolutional Neural Networks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
282503fa0285240ef42b5b4c74ae0590fe169211,Feeding Hand-Crafted Features for Enhancing the Performance of Convolutional Neural Networks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+28dac6b73df69f35b11f8f10ef023674a2f39af5,Deep Learning of Graph Matching,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+286f443fa85bc9d892ab54878c0ace0264d0dcff,Principled Parallel Mean-Field Inference for Discrete Random Fields,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
283d226e346ac3e7685dd9a4ba8ae55ee4f2fe43,Bayesian Data Association for Temporal Scene Understanding,University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
+2829288498cf03d87301f12a5bebf7f9faca0884,Face recognition using OPRA-faces,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
28f5138d63e4acafca49a94ae1dc44f7e9d84827,MahNMF: Manhattan Non-negative Matrix Factorization,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
28f5138d63e4acafca49a94ae1dc44f7e9d84827,MahNMF: Manhattan Non-negative Matrix Factorization,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
28f5138d63e4acafca49a94ae1dc44f7e9d84827,MahNMF: Manhattan Non-negative Matrix Factorization,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
28f5138d63e4acafca49a94ae1dc44f7e9d84827,MahNMF: Manhattan Non-negative Matrix Factorization,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+28c4103d1e27b4312115d3a6baacf3afbba01a55,Learning by Asking Questions,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+28e287d5aae3eb2c2ddbe3791e76a4cafdca7ef1,Recovering the Missing Link: Predicting Class-Attribute Associations for Unsupervised Zero-Shot Learning,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+289d833a35c2156b7e332e67d1cb099fd0683025,HICO: A Benchmark for Recognizing Human-Object Interactions in Images,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
28e1668d7b61ce21bf306009a62b06593f1819e3,"Correction: Validation of the Amsterdam Dynamic Facial Expression Set – Bath Intensity Variations (ADFES-BIV): A Set of Videos Expressing Low, Intermediate, and High Intensity Emotions",University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+28737575297a20d431dd2b777a79a8be2c9c2bbd,Object Ranking on Deformable Part Models with Bagged LambdaMART,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+289c6413c9b1d37c0608ee0027d28466ef3a552f,Facial Action Unit Recognition and Inference for Facial Expression Analysis,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+28b59fcd3d642f8d92a7c868c0076b00bd7f55cf,Multi-target tracking in team-sports videos via multi-level context-conditioned latent behaviour models,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
+28b59fcd3d642f8d92a7c868c0076b00bd7f55cf,Multi-target tracking in team-sports videos via multi-level context-conditioned latent behaviour models,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
+28b59fcd3d642f8d92a7c868c0076b00bd7f55cf,Multi-target tracking in team-sports videos via multi-level context-conditioned latent behaviour models,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
286adff6eff2f53e84fe5b4d4eb25837b46cae23,Single-Image Depth Perception in the Wild,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+2804e97b5c9dbaf4cb057c14478600cb2f9984de,Facial Model Fitting Based on Perturbation Learning and It's Evaluation on Challenging Real-World Diversities Images,Nagoya University,Nagoya University,"SuperDARN (Hokkaido West), 太辛第1支線林道, 陸別町, 足寄郡, 十勝総合振興局, 北海道, 北海道地方, 日本",43.53750985,143.60768225,edu,
286812ade95e6f1543193918e14ba84e5f8e852e,Robust 3D Face Shape Reconstruction from Single Images via Two-Fold Coupled Structure Learning,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+284bf12324805f23b920bec0174be003c248cc9b,Lower Sensitivity to Happy and Angry Facial Emotions in Young Adults with Psychiatric Problems,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+284bf12324805f23b920bec0174be003c248cc9b,Lower Sensitivity to Happy and Angry Facial Emotions in Young Adults with Psychiatric Problems,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
28f311b16e4fe4cc0ff6560aae3bbd0cb6782966,Learning Language from Perceptual Context,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
28d06fd508d6f14cd15f251518b36da17909b79e,What's in a Name? First Names as Facial Attributes,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
28d06fd508d6f14cd15f251518b36da17909b79e,What's in a Name? First Names as Facial Attributes,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
@@ -1917,36 +5176,84 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 281486d172cf0c78d348ce7d977a82ff763efccd,A Cost-Sensitive Visual Question-Answer Framework for Mining a Deep And-OR Object Semantics from Web Images,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
288964068cd87d97a98b8bc927d6e0d2349458a2,Mean-Variance Loss for Deep Age Estimation from a Face,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
288964068cd87d97a98b8bc927d6e0d2349458a2,Mean-Variance Loss for Deep Age Estimation from a Face,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+28af188e26836934c9beea8b2bc8cd53447197fa,Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+28af188e26836934c9beea8b2bc8cd53447197fa,Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+28bf3aee9eecc2f7a7b4ac71bfe89534d3fe5f19,Occlusion-Aware R-CNN: Detecting Pedestrians in a Crowd,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+28bf3aee9eecc2f7a7b4ac71bfe89534d3fe5f19,Occlusion-Aware R-CNN: Detecting Pedestrians in a Crowd,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+28bf3aee9eecc2f7a7b4ac71bfe89534d3fe5f19,Occlusion-Aware R-CNN: Detecting Pedestrians in a Crowd,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+28bf3aee9eecc2f7a7b4ac71bfe89534d3fe5f19,Occlusion-Aware R-CNN: Detecting Pedestrians in a Crowd,Macau University of Science and Technology,Macau University of Science and Technology,"Universidade de Ciência e Tecnologia de Macau 澳門科技大學 Macau University of Science and Technology, 偉龍馬路 Avenida Wai Long, 氹仔Taipa, 氹仔舊城區 Vila de Taipa, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, 澳門 Macau, 853, 中国",22.15263985,113.56803206,edu,
+28646c6220848db46c6944967298d89a6559c700,It takes two to tango : Cascading off-the-shelf face detectors,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+28633f80f1eae857d670cb245fbeb5d4e6e47a58,Explicit Reasoning over End-to-End Neural Architectures for Visual Question Answering,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
28c0cb56e7f97046d6f3463378d084e9ea90a89a,Automatic face recognition for film character retrieval in feature-length films,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
28be652db01273289499bc6e56379ca0237506c0,FaLRR: A fast low rank representation solver,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+286b5b80bc76dbb63094a85951bb8e8895ee9f14,TriKon: A hypervisor aware manycore processor,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+2862615e5767a8a81257138f04de6c5bd33e2984,Egocentric Future Localization,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+28226aedf1972af2008509cf3d1e7c6646c77f7b,Nuclear-L1 Norm Joint Regression for Face Reconstruction and Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
2836d68c86f29bb87537ea6066d508fde838ad71,Personalized Age Progression with Aging Dictionary,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
2836d68c86f29bb87537ea6066d508fde838ad71,Personalized Age Progression with Aging Dictionary,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
28de411a5b3eb8411e7bcb0003c426aa91f33e97,Emotion Detection Using Facial Expressions -A Review,Kurukshetra University,Kurukshetra University,"Kurukshetra University, SH6, Kurukshetra, Haryana, 132118, India",29.95826275,76.81563045,edu,
28de411a5b3eb8411e7bcb0003c426aa91f33e97,Emotion Detection Using Facial Expressions -A Review,Kurukshetra University,Kurukshetra University,"Kurukshetra University, SH6, Kurukshetra, Haryana, 132118, India",29.95826275,76.81563045,edu,
+28df3f11894ce0c48dd8aee65a6ec76d9009cbbd,Recurrent Flow-Guided Semantic Forecasting,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
28b26597a7237f9ea6a9255cde4e17ee18122904,Network Interactions Explain Sensitivity to Dynamic Faces in the Superior Temporal Sulcus,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+281e961f0d8dd6251e3124b43944820faba8a53f,Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+280d632ef3234c5ab06018c6eaccead75bc173b3,Efficient Image and Video Co-localization with Frank-Wolfe Algorithm,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
28d99dc2d673d62118658f8375b414e5192eac6f,Using Ranking-CNN for Age Estimation,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
28d99dc2d673d62118658f8375b414e5192eac6f,Using Ranking-CNN for Age Estimation,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+28ce99940265407517faf7c45755675054ef78c4,Distinct facial expressions represent pain and pleasure across cultures,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+28ce99940265407517faf7c45755675054ef78c4,Distinct facial expressions represent pain and pleasure across cultures,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+28ce99940265407517faf7c45755675054ef78c4,Distinct facial expressions represent pain and pleasure across cultures,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
280bc9751593897091015aaf2cab39805768b463,Gender Perception From Faces Using Boosted LBPH (Local Binary Patten Histograms),"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+282cee05661a690aa525f21b47c6ee39fb26a7c2,Build a Robust Learning Feature Descriptor by Using a New Image Visualization Method for Indoor Scenario Recognition,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+28ff4c98b7a922f4502c69003f686fe0f94083a6,On the regularization of image semantics by modal expansion,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+286e4e6b0360c06f659d351ac885aafb62a6b73d,Gait Verification Using Probabilistic Methods,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+2803c3247c11a30a8075dbc2db6ff96f58c2ae97,Perspective-Adjusting Appearance Model for Distributed Multi-View Person Tracking,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+28bdaf9b7fc5af73482e324d45acf91722f07340,Joint Object and Part Segmentation Using Deep Learned Potentials,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+28858a6e956d712331986b31d1646d6b497ff1a9,Independent Neural Computation of Value from Other People's Confidence.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+28858a6e956d712331986b31d1646d6b497ff1a9,Independent Neural Computation of Value from Other People's Confidence.,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+2850aa5324998b6d656d9d9c20f0eaf9d8946e2f,Indoor-outdoor classification with human accuracies: Image or edge gist?,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
+2850aa5324998b6d656d9d9c20f0eaf9d8946e2f,Indoor-outdoor classification with human accuracies: Image or edge gist?,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
288d2704205d9ca68660b9f3a8fda17e18329c13,Studying Very Low Resolution Recognition Using Deep Networks,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+289fb3709475f5c87df8d97f129af54029d27fee,Compositional Attention Networks for Machine Reasoning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+289fb3709475f5c87df8d97f129af54029d27fee,Compositional Attention Networks for Machine Reasoning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
17b46e2dad927836c689d6787ddb3387c6159ece,GeoFaceExplorer: exploring the geo-dependence of facial attributes,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
17b46e2dad927836c689d6787ddb3387c6159ece,GeoFaceExplorer: exploring the geo-dependence of facial attributes,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+178b55ded04d351c5a7df2e94a81aa3051d7fd8b,Visual Question Answering with Memory-Augmented Networks,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
1768909f779869c0e83d53f6c91764f41c338ab5,A large-scale car dataset for fine-grained categorization and verification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1768909f779869c0e83d53f6c91764f41c338ab5,A large-scale car dataset for fine-grained categorization and verification,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
1768909f779869c0e83d53f6c91764f41c338ab5,A large-scale car dataset for fine-grained categorization and verification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
171ca25bc2cdfc79cad63933bcdd420d35a541ab,Calibration-Free Gaze Estimation Using Human Gaze Patterns,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
176bd61cc843d0ed6aa5af83c22e3feb13b89fe1,Investigating Spontaneous Facial Action Recognition through AAM Representations of the Face,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+171a4ef673e40d09d7091082c7fd23b3758fc3c2,Video-based face recognition using ensemble of haar-like deep convolutional neural networks,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+17555c227941654bc19d613742e2508f209c6d86,Albumentations: fast and flexible image augmentations,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
17d01f34dfe2136b404e8d7f59cebfb467b72b26,Riemannian Similarity Learning,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+17d4fd92352baf6f0039ec64d43ca572c8252384,MoE-SPNet: A mixture-of-experts scene parsing network,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+1774b5a76d139a5532284f797ea7a36318bbcefd,Recognizing Complex Events Using Large Margin Joint Low-Level Event Model,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
176f26a6a8e04567ea71677b99e9818f8a8819d0,MEG: Multi-Expert Gender Classification from Face Images in a Demographics-Balanced Dataset,Sapienza University of Rome,Sapienza University of Rome,"Piazzale Aldo Moro, 5, 00185 Roma RM, Italy",41.90376260,12.51443840,edu,
176f26a6a8e04567ea71677b99e9818f8a8819d0,MEG: Multi-Expert Gender Classification from Face Images in a Demographics-Balanced Dataset,University of Naples Federico II,University of Naples Federico II,"Corso Umberto I, 40, 80138 Napoli NA, Italy",40.84549200,14.25780580,edu,
+1727601f148b937a49df10194edcee4800852a97,Deep Mutual Learning,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
+1727601f148b937a49df10194edcee4800852a97,Deep Mutual Learning,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+1727601f148b937a49df10194edcee4800852a97,Deep Mutual Learning,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+173a1110e3f5fe6a5518d7ceb025730b073bad62,Divided Local Binary Pattern ( DLBP ) Features Description Method For Facial Expression Recognition ⋆,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+17f9b24a4871d29ca1a83fae12e4b96bce0fba63,Person Re-Identification Using Kernel-Based Metric Learning Methods,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+17f3358d219c05f3cb8d68bdfaf6424567d66984,Adversarial Examples for Generative Models,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+17f3358d219c05f3cb8d68bdfaf6424567d66984,Adversarial Examples for Generative Models,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
17370f848801871deeed22af152489e39b6e1454,Undersampled face recognition with one-pass dictionary learning,"Academia Sinica, Taiwan","Research Center for Institute of Information Science, Academia Sinica, Taiwan","115, Taiwan, Taipei City, Nangang District, 研究院路二段128號",25.04117270,121.61465180,edu,
17479e015a2dcf15d40190e06419a135b66da4e0,Predicting First Impressions With Deep Learning,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+173a38768848cfe57a6b20b5ae019ce613e58781,Knowledge Acquisition for Visual Question Answering via Iterative Querying,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+173a38768848cfe57a6b20b5ae019ce613e58781,Knowledge Acquisition for Visual Question Answering via Iterative Querying,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+171042ba12818238e3c0994ff08d71f8c28d4134,Learning to Describe E-Commerce Images from Noisy Online Data,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
17fa1c2a24ba8f731c8b21f1244463bc4b465681,Deep multi-scale video prediction beyond mean square error,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
17579791ead67262fcfb62ed8765e115fb5eca6f,Real-Time Fashion-guided Clothing Semantic Parsing: a Lightweight Multi-Scale Inception Neural Network and Benchmark,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
17579791ead67262fcfb62ed8765e115fb5eca6f,Real-Time Fashion-guided Clothing Semantic Parsing: a Lightweight Multi-Scale Inception Neural Network and Benchmark,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+17e7a53456539dac2c9cf8631174c6388f64e24b,Learning to Detect Multiple Photographic Defects,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
+175e9bb50cc062c6c1742a5d90c8dfe31d2e4e22,Where to Look: Focus Regions for Visual Question Answering,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+17614bcb0f96d576dee34e1349f8be3d56786dd2,Detecting Partially Occluded Objects with an Implicit Shape Model Random Field,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
177d1e7bbea4318d379f46d8d17720ecef3086ac,Learning Multi-channel Deep Feature Representations for Face Recognition,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
177d1e7bbea4318d379f46d8d17720ecef3086ac,Learning Multi-channel Deep Feature Representations for Face Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+17f472a7cb25bf1e76ff29181b1d40585e2ae5c1,Fusing binary templates for multi-biometric cryptosystems,Hong Kong Baptist University,Hong Kong Baptist University,"香港浸會大學 Hong Kong Baptist University, 安明街 On Ming Street, 石門 Shek Mun, 石古壟 Shek Kwu Lung, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1132, 中国",22.38742010,114.20822220,edu,
170a5f5da9ac9187f1c88f21a88d35db38b4111a,Online Real-Time Multiple Spatiotemporal Action Localisation and Prediction,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
170a5f5da9ac9187f1c88f21a88d35db38b4111a,Online Real-Time Multiple Spatiotemporal Action Localisation and Prediction,Oxford University,Oxford University,"University College, Logic Lane, Grandpont, Oxford, Oxon, South East, England, OX1 4EX, UK",51.75208490,-1.25166460,edu,
+17b6eb93b41baeb5e1b0a16ecb0673a72368a34b,Generic Object Recognition,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
17a8d1b1b4c23a630b051f35e47663fc04dcf043,Differential Angular Imaging for Material Recognition,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
17a8d1b1b4c23a630b051f35e47663fc04dcf043,Differential Angular Imaging for Material Recognition,Drexel University,Drexel University,"Drexel University, Arch Street, Powelton Village, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.95740000,-75.19026706,edu,
171d8a39b9e3d21231004f7008397d5056ff23af,"Simultaneous Facial Landmark Detection, Pose and Deformation Estimation Under Facial Occlusion",Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
@@ -1956,95 +5263,291 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 17045163860fc7c38a0f7d575f3e44aaa5fa40d7,Boosting VLAD with Supervised Dictionary Learning and High-Order Statistics,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
17045163860fc7c38a0f7d575f3e44aaa5fa40d7,Boosting VLAD with Supervised Dictionary Learning and High-Order Statistics,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
17045163860fc7c38a0f7d575f3e44aaa5fa40d7,Boosting VLAD with Supervised Dictionary Learning and High-Order Statistics,Hengyang Normal University,Hengyang Normal University,"衡阳师范学院, 黄白路, 雁峰区, 衡阳市 / Hengyang, 湖南省, 中国",26.86611360,112.62092122,edu,
+170862138b7be1b8d92c3abf7cf2466bc435f1ec,Alive Caricature from 2D to 3D,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+170862138b7be1b8d92c3abf7cf2466bc435f1ec,Alive Caricature from 2D to 3D,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+170862138b7be1b8d92c3abf7cf2466bc435f1ec,Alive Caricature from 2D to 3D,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
17e563af203d469c456bb975f3f88a741e43fb71,Naming TV characters by watching and analyzing dialogs,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
171389529df11cc5a8b1fbbe659813f8c3be024d,Manifold Estimation in View-Based Feature Space for Face Synthesis across Poses,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+17f29dba3809527c3b9533247045a488417ec21c,Removal of 3D facial expressions: A learning-based approach,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+17f8f5fe7a6730ee8d735d055ccc12231aff4435,A Large-scale Distributed Video Parsing and Evaluation Platform,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
17d5e5c9a9ee4cf85dfbb9d9322968a6329c3735,Study on Parameter Selection Using SampleBoost,University of North Texas,University of North Texas,"University of North Texas, West Highland Street, Denton, Denton County, Texas, 76201, USA",33.20988790,-97.15147488,edu,
17cf6195fd2dfa42670dc7ada476e67b381b8f69,Automatic Face Region Tracking for Highly Accurate Face Recognition in Unconstrained Environments,Chung-Ang University,Chung-Ang University,"중앙대학교, 서달로15길, 흑석동, 동작구, 서울특별시, 06981, 대한민국",37.50882000,126.96190000,edu,
17cf6195fd2dfa42670dc7ada476e67b381b8f69,Automatic Face Region Tracking for Highly Accurate Face Recognition in Unconstrained Environments,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
174f46eccb5852c1f979d8c386e3805f7942bace,The Shape-Time Random Field for Semantic Video Labeling,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+17113b0f647ce05b2e50d1d40c856370f94da7de,Zoom Better to See Clearer: Human Part Segmentation with Auto Zoom Net,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+172cd5d213cefd99e93039eaf3d8824b3ba203e4,Learned vs. Hand-Crafted Features for Pedestrian Gender Recognition,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
17670b60dcfb5cbf8fdae0b266e18cf995f6014c,Longitudinal Face Modeling via Temporal Deep Restricted Boltzmann Machines,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
17670b60dcfb5cbf8fdae0b266e18cf995f6014c,Longitudinal Face Modeling via Temporal Deep Restricted Boltzmann Machines,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
17027a05c1414c9a06a1c5046899abf382a1142d,Articulated motion discovery using pairs of trajectories,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
17ded725602b4329b1c494bfa41527482bf83a6f,Compact Convolutional Neural Network Cascade for Face Detection,Tomsk Polytechnic University,Tomsk Polytechnic University,"Томский политехнический университет, улица Пирогова, Южная, Кировский район, Томск, городской округ Томск, Томская область, СФО, 634034, РФ",56.46255985,84.95565495,edu,
17ded725602b4329b1c494bfa41527482bf83a6f,Compact Convolutional Neural Network Cascade for Face Detection,Tomsk Polytechnic University,Tomsk Polytechnic University,"Томский политехнический университет, улица Пирогова, Южная, Кировский район, Томск, городской округ Томск, Томская область, СФО, 634034, РФ",56.46255985,84.95565495,edu,
+179ae598004d76c56dcc95c5aab3419ec8996af1,Person independent 3D gaze estimation from remote RGB-D cameras,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+17423fe480b109e1d924314c1dddb11b084e8a42,Deep Disguised Faces Recognition,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
177bc509dd0c7b8d388bb47403f28d6228c14b5c,"Deep Learning Face Representation from Predicting 10,000 Classes",Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
177bc509dd0c7b8d388bb47403f28d6228c14b5c,"Deep Learning Face Representation from Predicting 10,000 Classes",Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
177bc509dd0c7b8d388bb47403f28d6228c14b5c,"Deep Learning Face Representation from Predicting 10,000 Classes",Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+171585599fcc0cb2c2c190a3ff395c2f5bd331dc,3-D–2-D spatiotemporal registration for sports motion analysis,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+7b4e0a98dcb4ba34afcc5901f51384ba727473a0,Introduction to Emotion Recognition,Jadavpur University,Jadavpur University,"Jadavpur University, Chingrighata Flyover, Basani Devi Colony, Kolkata, Hāora, West Bengal, 700098, India",22.56115370,88.41310194,edu,
7b63ed54345d8c06523f6b03c41a09b5c8f227e2,Facial expression recognition based on combination of spatio-temporal and spectral features in local facial regions,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+7b3231245a3d518085c8e747e2c2232963f49bc5,Tracking millions of humans in crowded space in crowded spaces,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
7bf0a1aa1d0228a51d24c0c3a83eceb937a6ae25,"Video-based Car Surveillance: License Plate, Make, and Model Recognition","University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+7b3b2912c1d7a70839bc71a150e33f8634d0fff3,Convolutional Neural Network-Based Embarrassing Situation Detection under Camera for Social Robot in Smart Homes,Oklahoma State University,Oklahoma State University,"Walmart East Bus Stop, East Virginia Avenue, Stillwater, Payne County, Oklahoma, 74075, USA",36.12447560,-97.05004383,edu,
+7b21db9efc3403fa054739921e29aedcc81b1fb1,Exploring Correlations in Multiple Facial Attributes through Graph Attention Network,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+7bcb505d93175d0b89ff7aca76caf579ddf12339,PixelNN: Example-based Image Synthesis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7b8baf809d9b643145e089b7a1650923487cf451,Do Deep Convolutional Nets Really Need to be Deep and Convolutional?,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+7b8baf809d9b643145e089b7a1650923487cf451,Do Deep Convolutional Nets Really Need to be Deep and Convolutional?,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+7b8baf809d9b643145e089b7a1650923487cf451,Do Deep Convolutional Nets Really Need to be Deep and Convolutional?,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+7b8baf809d9b643145e089b7a1650923487cf451,Do Deep Convolutional Nets Really Need to be Deep and Convolutional?,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+7bc1318403cdb4895a4437993d288068a8e85f5f,Fast-Converging Conditional Generative Adversarial Networks for Image Synthesis,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
+7b4d985d03ebf8465757877f0eeaea00fa77676b,Dyadic Dynamics: The Impact of Emotional Responses to Facial Expressions on the Perception of Power,University of Haifa,University of Haifa,"אוניברסיטת חיפה, חיפה, מחוז חיפה, ישראל",32.76162915,35.01986304,edu,
+7b4d985d03ebf8465757877f0eeaea00fa77676b,Dyadic Dynamics: The Impact of Emotional Responses to Facial Expressions on the Perception of Power,University of Haifa,University of Haifa,"אוניברסיטת חיפה, חיפה, מחוז חיפה, ישראל",32.76162915,35.01986304,edu,
+7b4d985d03ebf8465757877f0eeaea00fa77676b,Dyadic Dynamics: The Impact of Emotional Responses to Facial Expressions on the Perception of Power,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+7bc8d81a38899b60704681125ec4fc584a3e7ba4,Look me in the eyes: constraining gaze in the eye-region provokes abnormally high subcortical activation in autism,Cambridge University,Cambridge University,"University, Cambridge Road, Old Portsmouth, Portsmouth, South East, England, PO1 2HB, UK",50.79440260,-1.09717480,edu,
7b43326477795a772c08aee750d3e433f00f20be,Computational Methods for Behavior Analysis,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+7bf04c79f2659a404c9b9b91e0375e1450c3adbe,Mahalanobis Distance Based Non-negative Sparse Representation for Face Recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+7b79a754a8583f887857c539895a9dda6331ca2e,Binary-Decomposed DCNN for Accelerating Computation and Compressing Model Without Retraining,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+7b79a754a8583f887857c539895a9dda6331ca2e,Binary-Decomposed DCNN for Accelerating Computation and Compressing Model Without Retraining,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+7b79a754a8583f887857c539895a9dda6331ca2e,Binary-Decomposed DCNN for Accelerating Computation and Compressing Model Without Retraining,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+7b79a754a8583f887857c539895a9dda6331ca2e,Binary-Decomposed DCNN for Accelerating Computation and Compressing Model Without Retraining,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+7bdab6e725ab1bbf8fcd6d7c451f6c4cc215ada9,Complex Wavelet Transform-Based Face Recognition,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
7be60f8c34a16f30735518d240a01972f3530e00,Facial expression recognition with temporal modeling of shapes,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+7b3fe45f887a37f78bb356874702adae91dda105,High Distortion and Non-Structural Image Matching via Feature Co-occurrence,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+7b45aa509184b05064eafb362f80ba5778566a4e,High-Level Interpretation of Urban Road Maps Fusing Deep Learning-Based Pixelwise Scene Segmentation and Digital Navigation Maps,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+7bd837a934c6cd6ee858bdfd4ee0f8fa3663fed7,A Generic Model to Compose Vision Modules for Holistic Scene Understanding,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+7bd837a934c6cd6ee858bdfd4ee0f8fa3663fed7,A Generic Model to Compose Vision Modules for Holistic Scene Understanding,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+7b8b1571639f901275da22ee8f1de852350bf38e,Improved Deep Learning of Object Category Using Pose Information,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+7b74b65983ae0abb09a540b6413a5a36b2df027a,Gated Transfer Network for Transfer Learning,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+7b0c88bc555e3ced093e5cecb5dc1996f42eeeec,Solving Linear Inverse Problems Using Gan Priors: An Algorithm with Provable Guarantees,Iowa State University,Iowa State University,"Iowa State University, Farm House Road, Ames, Story County, Iowa, 50014, USA",42.02791015,-93.64464415,edu,
+8fe99c3d5ad9af54641dcd6b55e2b083a363d515,Fashion and Apparel Classification using Convolutional Neural Networks,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
8fe38962c24300129391f6d7ac24d7783e0fddd0,Visual Text Correction,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
8f3e120b030e6c1d035cb7bd9c22f6cc75782025,Bayesian Networks and the Imprecise Dirichlet Model Applied to Recognition Problems,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+8f0b6845689a0b6adda2feb52b9345f9d9a2a8b3,Social Attention in the Two Species of Pan: Bonobos Make More Eye Contact than Chimpanzees,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+8f0b6845689a0b6adda2feb52b9345f9d9a2a8b3,Social Attention in the Two Species of Pan: Bonobos Make More Eye Contact than Chimpanzees,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+8f0b6845689a0b6adda2feb52b9345f9d9a2a8b3,Social Attention in the Two Species of Pan: Bonobos Make More Eye Contact than Chimpanzees,University of St Andrews,University of St Andrews,"University of St Andrews, North Street, Albany Park Student accommodation, Carngour, St Andrews, Fife, Scotland, KY16 9AJ, UK",56.34119840,-2.79309380,edu,
+8f0b6845689a0b6adda2feb52b9345f9d9a2a8b3,Social Attention in the Two Species of Pan: Bonobos Make More Eye Contact than Chimpanzees,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+8f48c9ca2ea3101083be19344633372fe1a2efcd,Distinctive-attribute Extraction for Image Captioning,Korea Electronics Technology Institute,Korea Electronics Technology Institute,"South Korea, Gyeonggi-do, Seongnam-si, Bundang-gu, 새나리로 25 (야탑동) KETI 전자부품연구원",37.40391700,127.15978600,edu,
+8f5a2750f7ed015efa85887db3f6c6d2c0cb7b11,Social perception in synaesthesia Social perception in synaesthesia for colour,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+8f5a2750f7ed015efa85887db3f6c6d2c0cb7b11,Social perception in synaesthesia Social perception in synaesthesia for colour,Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
+8f5a2750f7ed015efa85887db3f6c6d2c0cb7b11,Social perception in synaesthesia Social perception in synaesthesia for colour,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+8f5a2750f7ed015efa85887db3f6c6d2c0cb7b11,Social perception in synaesthesia Social perception in synaesthesia for colour,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
8fed5ea3b69ea441a8b02f61473eafee25fb2374,Two-Dimensional PCA with F-Norm Minimization,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
8fed5ea3b69ea441a8b02f61473eafee25fb2374,Two-Dimensional PCA with F-Norm Minimization,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+8f1ac3c8fe6bcb1da2cdef60bc218ba1e264074f,Unsupervised Template Learning for Fine-Grained Object Recognition,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+8f1ac3c8fe6bcb1da2cdef60bc218ba1e264074f,Unsupervised Template Learning for Fine-Grained Object Recognition,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
8f3da45ff0c3e1777c3a7830f79c10f5896bcc21,Riding Role Agent Vehicle Place Role Agent Vehicle Place Value Man Horse outside Value Dog Skateboard,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
8ff8c64288a2f7e4e8bf8fda865820b04ab3dbe8,Age Estimation Using Expectation of Label Distribution Learning,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
8ff8c64288a2f7e4e8bf8fda865820b04ab3dbe8,Age Estimation Using Expectation of Label Distribution Learning,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+8faa4f2e287ff1bcaba2e0cd84d82a66bb2982f5,Pedestrian Detection with RCNN,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
8f08b2101d43b1c0829678d6a824f0f045d57da5,Supplementary Material for: Active Pictorial Structures,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+8f81eb82cd046891c88163bc7b472dcc779f5f08,TokyoTechCanon at TRECVID 2012,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+8f0b2d24dab016764eebeaa2070d31801948f6f5,Unified Perceptual Parsing for Scene Understanding,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+8f0b2d24dab016764eebeaa2070d31801948f6f5,Unified Perceptual Parsing for Scene Understanding,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+8ffc49aead99fdacb0b180468a36984759f2fc1e,Sparse Label Smoothing for Semi-supervised Person Re-Identification,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+8ff967ed7130f81abc896d7b84f7c629aed5cf49,Unified probabilistic framework for simultaneous detection and tracking of multiple objects with application to bio-image sequences,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
+8f3d5f9ad240c186971edc652f8385dc2a53d2eb,Model-Based Background Subtraction System Application Domain: Pedestrian Tracking,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
8fbec9105d346cd23d48536eb20c80b7c2bbbe30,The effectiveness of face detection algorithms in unconstrained crowd scenes,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
8f8a5be9dc16d73664285a29993af7dc6a598c83,Neural Network based Face Recognition with Gabor Filters,Jahangirnagar University,Jahangirnagar University,"Jahangirnagar University, 1342, University Main Road, সাভার, সাভার উপজেলা, ঢাকা জেলা, ঢাকা বিভাগ, 1342, বাংলাদেশ",23.88331200,90.26939210,edu,
8f5ce25e6e1047e1bf5b782d045e1dac29ca747e,A Novel Discriminant Non-Negative Matrix Factorization Algorithm With Applications to Facial Image Characterization Problems,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
8f92cccacf2c84f5d69db3597a7c2670d93be781,Facial expression synthesis through facial expressions statistical analysis,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+8f48b2da711417d1f1f39069501577c84abb8d37,Elevated amygdala response to faces and gaze aversion in autism spectrum disorder.,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
8f6263e4d3775757e804796e104631c7a2bb8679,Characterizing Visual Representations within Convolutional Neural Networks: Toward a Quantitative Approach,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
8f6263e4d3775757e804796e104631c7a2bb8679,Characterizing Visual Representations within Convolutional Neural Networks: Toward a Quantitative Approach,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
8f60c343f76913c509ce623467bf086935bcadac,Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+8fa290b5d92c1f427edb62d29988056383e02047,Absence of preferential unconscious processing of eye contact in adolescents with autism spectrum disorder.,Tokyo Denki University,Tokyo Denki University,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+8fa290b5d92c1f427edb62d29988056383e02047,Absence of preferential unconscious processing of eye contact in adolescents with autism spectrum disorder.,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+8fa290b5d92c1f427edb62d29988056383e02047,Absence of preferential unconscious processing of eye contact in adolescents with autism spectrum disorder.,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+8fa290b5d92c1f427edb62d29988056383e02047,Absence of preferential unconscious processing of eye contact in adolescents with autism spectrum disorder.,University of Tampere,University of Tampere,"Tampereen yliopisto, 4, Kalevantie, Ratinanranta, Tulli, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33100, Suomi",61.49412325,23.77920678,edu,
+8fa290b5d92c1f427edb62d29988056383e02047,Absence of preferential unconscious processing of eye contact in adolescents with autism spectrum disorder.,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+8f27df2d4fb7dd7ed5587640dcbe4dc1eb37acfb,Unseen Action Recognition with Multimodal Learning,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+8f27df2d4fb7dd7ed5587640dcbe4dc1eb37acfb,Unseen Action Recognition with Multimodal Learning,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+8fe0a35dc47698b45f3812bb502b0921b349ae56,Online multi-person tracking via robust collaborative model,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
8f5facdc0a2a79283864aad03edc702e2a400346,Estimation Framework using Bio - Inspired Features for Facial Image,Bangalore Institute of Technology,Bangalore Institute of Technology,"Bangalore Institute of Technology, Krishna Rajendra Road, Mavalli, Vishveshwara Puram, South Zone, Bengaluru, Bangalore Urban, Karnataka, 560004, India",12.95512590,77.57419850,edu,
8a3c5507237957d013a0fe0f082cab7f757af6ee,Facial Landmark Detection by Deep Multi-task Learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
8af411697e73f6cfe691fe502d4bfb42510b4835,Dynamic Local Ternary Pattern for Face Recognition and Verification,Institute of Information Technology,Institute of Information Technology,"Institute of Information Technology, Sir Sayed Road, ফকিরাপুল, সিদ্দিক বাজার, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.72898990,90.39826820,edu,
8af411697e73f6cfe691fe502d4bfb42510b4835,Dynamic Local Ternary Pattern for Face Recognition and Verification,University of Dhaka,University of Dhaka,"World War Memorial, Shahid Minar Rd, Jagannath Hall, DU, জিগাতলা, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.73169570,90.39652750,edu,
8af411697e73f6cfe691fe502d4bfb42510b4835,Dynamic Local Ternary Pattern for Face Recognition and Verification,Hankuk University of Foreign Studies,Hankuk University of Foreign Studies,"외대앞, 휘경로, 이문동, 이문2동, 동대문구, 서울특별시, 02407, 대한민국",37.59539790,127.06304990,edu,
+8ad12d3ee186403b856639b58d7797aa4b89a6c7,Temporal Relational Reasoning in Videos,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
8a1ed5e23231e86216c9bdd62419c3b05f1e0b4d,Facial Keypoint Detection,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+8a6b52fd31ebaf00e7abe57c4c50dee4683aee4b,VOP: Architecture of a Processor for Vector Operations in On-Line Learning of Neural Networks,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+8ae92b73020dac2c98c72cbaf823cff1567bd91b,Semantic Image Inpainting with Perceptual and Contextual Losses,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+8a7bd4202e49fcdb947d71c9f2da0e7a953c7021,Privacy and security assessment of biometric template protection,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+8a3f85c80c698f15639ced90b4e9d4baa23b572e,MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+8a3f85c80c698f15639ced90b4e9d4baa23b572e,MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+8a26431833b0ea8659ef1d24bff3ac9e56dcfcd0,VoxCeleb: a large-scale speaker identification dataset,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8a3eaaef13bdaee26142fd2784de07e1d24926ca,Design and evaluation of photometric image quality measures for effective face recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
8a8861ad6caedc3993e31d46e7de6c251a8cda22,StreetStyle: Exploring world-wide clothing styles from millions of photos,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+8aff946f5d678f689cc9476e48d8b122671205ae,"Neuron numbers increase in the human amygdala from birth to adulthood, but not in autism",New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+8a2a77062770bbdbfdbfe06ad7c3ab1728a4c59a,Video Action Detection with Relational Dynamic-Poselets,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+8a2a77062770bbdbfdbfe06ad7c3ab1728a4c59a,Video Action Detection with Relational Dynamic-Poselets,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+8a2a77062770bbdbfdbfe06ad7c3ab1728a4c59a,Video Action Detection with Relational Dynamic-Poselets,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+8a6ee59cda77eeb7e126e3bc3d82e742ae1b3e58,"DeeperCut: A Deeper, Stronger, and Faster Multi-person Pose Estimation Model",Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+8a6ee59cda77eeb7e126e3bc3d82e742ae1b3e58,"DeeperCut: A Deeper, Stronger, and Faster Multi-person Pose Estimation Model",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
8a3bb63925ac2cdf7f9ecf43f71d65e210416e17,ShearFace: Efficient Extraction of Anisotropic Features for Face Recognition,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
8a0159919ee4e1a9f4cbfb652a1be212bf0554fd,"Application of power laws to biometrics, forensics and network traffic analysis",University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
8ad0d8cf4bcb5c7eccf09f23c8b7d25439c4ae2b,Predicting the Future with Transformational States,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+8a722c17e6bda2df13f03ca522119f4c8b5bfff8,Connecting Missing Links: Object Discovery from Sparse Observations Using 5 Million Product Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8a722c17e6bda2df13f03ca522119f4c8b5bfff8,Connecting Missing Links: Object Discovery from Sparse Observations Using 5 Million Product Images,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+8a722c17e6bda2df13f03ca522119f4c8b5bfff8,Connecting Missing Links: Object Discovery from Sparse Observations Using 5 Million Product Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8a722c17e6bda2df13f03ca522119f4c8b5bfff8,Connecting Missing Links: Object Discovery from Sparse Observations Using 5 Million Product Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8a722c17e6bda2df13f03ca522119f4c8b5bfff8,Connecting Missing Links: Object Discovery from Sparse Observations Using 5 Million Product Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8acbf69f5877dac506bf04dc1802f327247cc27e,FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+8acbf69f5877dac506bf04dc1802f327247cc27e,FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+8a37b56c92fa18c1129ca029935db0e837b73675,Co-occurrence flow for pedestrian detection,Cambridge Research Laboratory,Cambridge Research Laboratory,"Strangeways Research Laboratory, Babraham Road, Romsey, Cambridge, Cambridgeshire, East of England, England, CB1 8RN, UK",52.17333465,0.14989946,edu,
+8a37b56c92fa18c1129ca029935db0e837b73675,Co-occurrence flow for pedestrian detection,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+8a5099b2ae6912b4df22534a1b3065e147c38b9c,Face Hallucination with Tiny Unaligned Images by Transformative Discriminative Neural Networks,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+8a091254ba45ab9fe7d72c8104409bee5aa8f199,Efficient Object Detection Using Orthogonal NMF Descriptor Hierarchies,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+8af9f7c920a87acb3ae127756f498a51b535790a,Exploring Contextual Engagement for Trauma Recovery,University of Colorado at Colorado Springs,University of Colorado at Colorado Springs,"1420 Austin Bluffs Pkwy, Colorado Springs, CO 80918, USA",38.89646790,-104.80505940,edu,
8a0d10a7909b252d0e11bf32a7f9edd0c9a8030b,Animals on the Web,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
8a0d10a7909b252d0e11bf32a7f9edd0c9a8030b,Animals on the Web,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+8a8224266b8ab1483f6548307ab96227147f34da,Zero-Shot Visual Question Answering,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+8a1294d2093b7f339e3d33da46e008aca3528893,FoveaNet: Perspective-Aware Urban Scene Parsing,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+8a05ac5e375ebf80b5fb88f207a9d33d5765c27b,2D-3D Hybrid Face Recognition Based on PCA and Feature Modelling,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+8a7882f765822ecc1f72610277037228c24e7bf7,Examining Performance of Sketch-to-Image Translation Models with Multiclass Automatically Generated Paired Training Data,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+8aef5b3cfc80fafdcefc24c72a4796ca40f4bc8b,Person Re-Identification by Support Vector Ranking,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+8a12edaf81fd38f81057cf9577c822eb09ff6fc1,Measuring and mitigating targeted biometric impersonation,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+8a12edaf81fd38f81057cf9577c822eb09ff6fc1,Measuring and mitigating targeted biometric impersonation,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+7e1e189fff0b0cef3c231e6b2d01b65bef6027e7,A Concept of Bimodal Visual Emotion Recognition in Computer Users,AGH University of Science and Technology,AGH University of Science and Technology,"AGH, Władysława Reymonta, Czarna Wieś, Krowodrza, Kraków, małopolskie, 30-059, RP",50.06570330,19.91895867,edu,
7ed3b79248d92b255450c7becd32b9e5c834a31e,L 1-regularized Logistic Regression Stacking and Transductive CRF Smoothing for Action Recognition in Video,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
7ed3b79248d92b255450c7becd32b9e5c834a31e,L 1-regularized Logistic Regression Stacking and Transductive CRF Smoothing for Action Recognition in Video,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
7ed3b79248d92b255450c7becd32b9e5c834a31e,L 1-regularized Logistic Regression Stacking and Transductive CRF Smoothing for Action Recognition in Video,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
7ed3b79248d92b255450c7becd32b9e5c834a31e,L 1-regularized Logistic Regression Stacking and Transductive CRF Smoothing for Action Recognition in Video,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
7e8016bef2c180238f00eecc6a50eac473f3f138,Immersive Interactive Data Mining and Machine Learning Algorithms for Big Data Visualization,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+7e02b0bce72a88f2f70b199c5dc87a01fe217832,Learning Multi-target Tracking with Quadratic Object Interactions,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
7ed2c84fdfc7d658968221d78e745dfd1def6332,Evaluation of linear combination of views for object recognition on real and synthetic datasets,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+7e49a6f11a8843b2ff5bdbf7cf95617c6219f757,Multi-Modal Fusion for Moment in Time Video Classification,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+7ea35b35392c6ef5738635cec7d17b24fe3e4f04,Deep Forest,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
7eaa97be59019f0d36aa7dac27407b004cad5e93,Sampling Generative Networks,Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
7eb895e7de883d113b75eda54389460c61d63f67,Can You Tell a Face from a HEVC Bitstream?,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
7e467e686f9468b826133275484e0a1ec0f5bde6,Efficient On-the-fly Category Retrieval using ConvNets and GPUs,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+7e4b638e028498e900747b600f46cd723f1f231e,Data Augmentation for Visual Question Answering,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+7e988b6f688f248d803be9846a4cbd4126afc785,Learning Locality-Constrained Collaborative Representation for Face Recognition,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+7e988b6f688f248d803be9846a4cbd4126afc785,Learning Locality-Constrained Collaborative Representation for Face Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+7ee610cd384cf1950d6254562e00490ad05eec57,Selecting Optimal Orientations of Gabor Wavelet Filters for Facial Image Analysis,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+7ee610cd384cf1950d6254562e00490ad05eec57,Selecting Optimal Orientations of Gabor Wavelet Filters for Facial Image Analysis,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+7e984bbad042b145d1ff8351c4a7c5fb6a81e0b1,Graininess-Aware Deep Feature Learning for Pedestrian Detection,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+7e3147a01108607fa65ace289094e5b5b525929c,Automatic Beautification for Group-Photo Facial Expressions Using Novel Bayesian GANs,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
7e00fb79576fe213853aeea39a6bc51df9fdca16,Online multi-face detection and tracking using detector confidence and structured SVMs,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
+7ee17d2001c9fcef63e3a56610cacc743861d944,Extracting Databases from Dark Data with DeepDive,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+7ee17d2001c9fcef63e3a56610cacc743861d944,Extracting Databases from Dark Data with DeepDive,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+7e435d78693aec1b87b6f690a8716a60a5e5ff8c,Multimodal sentiment analysis with word-level fusion and reinforcement learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7e435d78693aec1b87b6f690a8716a60a5e5ff8c,Multimodal sentiment analysis with word-level fusion and reinforcement learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7e435d78693aec1b87b6f690a8716a60a5e5ff8c,Multimodal sentiment analysis with word-level fusion and reinforcement learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7e435d78693aec1b87b6f690a8716a60a5e5ff8c,Multimodal sentiment analysis with word-level fusion and reinforcement learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7e435d78693aec1b87b6f690a8716a60a5e5ff8c,Multimodal sentiment analysis with word-level fusion and reinforcement learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7e435d78693aec1b87b6f690a8716a60a5e5ff8c,Multimodal sentiment analysis with word-level fusion and reinforcement learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
7e2cfbfd43045fbd6aabd9a45090a5716fc4e179,Global Norm-Aware Pooling for Pose-Robust Face Recognition at Low False Positive Rate,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
7e18b5f5b678aebc8df6246716bf63ea5d8d714e,Increased Loss Aversion in Unmedicated Patients with Obsessive–Compulsive Disorder,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
7e18b5f5b678aebc8df6246716bf63ea5d8d714e,Increased Loss Aversion in Unmedicated Patients with Obsessive–Compulsive Disorder,Southwest University,Southwest University,"西南大学, 天生路, 北碚区 (Beibei), 北碚区, 北碚区 (Beibei), 重庆市, 400711, 中国",29.82366295,106.42050016,edu,
7e18b5f5b678aebc8df6246716bf63ea5d8d714e,Increased Loss Aversion in Unmedicated Patients with Obsessive–Compulsive Disorder,Beijing Normal University,Beijing Normal University,"北京师范大学, 19, 新街口外大街, 西城区, 100875, 中国",39.96014155,116.35970438,edu,
7e18b5f5b678aebc8df6246716bf63ea5d8d714e,Increased Loss Aversion in Unmedicated Patients with Obsessive–Compulsive Disorder,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+7e526c32a9ba12d3aeb69c70ee38b178ba203d6e,Mixture of Heterogeneous Attribute Analyzers for Human Action Detection,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
7eb85bcb372261bad707c05e496a09609e27fdb3,A Compute-Efficient Algorithm for Robust Eyebrow Detection,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+7ef41e2be5116912fe8a4906b4fb89ac9dcf819d,A hybrid face recognition method using Markov random fields,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+7e2a443cb069f1e3b0d7c41fecf55774ac584895,The Role of Color in Face Processing and Autism Spectrum Disorders,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+7e2a443cb069f1e3b0d7c41fecf55774ac584895,The Role of Color in Face Processing and Autism Spectrum Disorders,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+7e2a443cb069f1e3b0d7c41fecf55774ac584895,The Role of Color in Face Processing and Autism Spectrum Disorders,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+7e01ce7a1c14971088afa3ee73f92db451e2c536,A Task-Oriented Approach for Cost-Sensitive Recognition,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+7e6f7ce8ec6f62c4bf68f84207973914fc8e79b9,Exploring bounding box context for multi-object tracker fusion,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+7e6b11674e989d6a86afda241a51f7fa3790b93e,Optimized Kernel-based Projection Space of Riemannian Manifolds,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+7e6b11674e989d6a86afda241a51f7fa3790b93e,Optimized Kernel-based Projection Space of Riemannian Manifolds,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+7e6b11674e989d6a86afda241a51f7fa3790b93e,Optimized Kernel-based Projection Space of Riemannian Manifolds,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
7ebb153704706e457ab57b432793d2b6e5d12592,Faces in Places: compound query retrieval,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+7e225e3e61527f35b7bf44d47e12cbadfc9441f8,Generating High-Quality Crowd Density Maps Using Contextual Pyramid CNNs,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
7ec7163ec1bc237c4c2f2841c386f2dbfd0cc922,Skiing and Thinking About It: Moment-to-Moment and Retrospective Analysis of Emotions in an Extreme Sport,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+7e19f7a82528fa79349f1fc61c7f0d35a9ad3a5e,Face Recognition: A Hybrid Neural Network Approach,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+7e19f7a82528fa79349f1fc61c7f0d35a9ad3a5e,Face Recognition: A Hybrid Neural Network Approach,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
7e0c75ce731131e613544e1a85ae0f2c28ee4c1f,Regression-based Estimation of Pain and Facial Expression Intensity,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+7eff2b26a16e0898ebdd141e930d011a3d3e4e8b,Clothing retrieval with visual attention model,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+7eff2b26a16e0898ebdd141e930d011a3d3e4e8b,Clothing retrieval with visual attention model,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
7ef44b7c2b5533d00001ae81f9293bdb592f1146,Détection des émotions à partir de vidéos dans un environnement non contrôlé Detection of emotions from video in non-controlled environment,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
+7ed27f10ff2961611bb8604096a64adfa38c9022,Deep Structured Learning for Facial Action Unit Intensity Estimation,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+7ed27f10ff2961611bb8604096a64adfa38c9022,Deep Structured Learning for Facial Action Unit Intensity Estimation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+7ed27f10ff2961611bb8604096a64adfa38c9022,Deep Structured Learning for Facial Action Unit Intensity Estimation,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+7e186b41f5d2cfdf1940009e61d4e34a47b33c7c,Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-identification,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
7e1ea2679a110241ed0dd38ff45cd4dfeb7a8e83,Extensions of Hierarchical Slow Feature Analysis for Efficient Classification and Regression on High-Dimensional Data,Ruhr-University Bochum,Ruhr-University Bochum,"RUB, 150, Universitätsstraße, Ruhr-Universität, Querenburg, Bochum-Süd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland",51.44415765,7.26096541,edu,
+7e51a42049193726e9ac547b76e929d803e441f3,Holistic processing of the mouth but not the eyes in developmental prosopagnosia.,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+7e51a42049193726e9ac547b76e929d803e441f3,Holistic processing of the mouth but not the eyes in developmental prosopagnosia.,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+7e45b27ec7339dc557866b31e74c71a52e99fd32,Statistical Inference of Motion in the Invisible,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+10b36c003542545f1e2d73e8897e022c0c260c32,Towards a Principled Integration of Multi-camera Re-identification and Tracking Through Optimal Bayes Filters,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+108d44bee37d4190883a268274ff78a8fd20de54,Competitive Sparse Representation Classification for Face Recognition,Chongqing University of Posts and Telecommunications,Chongqing University of Posts and Telecommunications,"重庆邮电大学, 崇文路, 渝中区, 黄桷垭, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400065, 中国",29.53570460,106.60482474,edu,
+108d44bee37d4190883a268274ff78a8fd20de54,Competitive Sparse Representation Classification for Face Recognition,Chongqing University of Posts and Telecommunications,Chongqing University of Posts and Telecommunications,"重庆邮电大学, 崇文路, 渝中区, 黄桷垭, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400065, 中国",29.53570460,106.60482474,edu,
+108d44bee37d4190883a268274ff78a8fd20de54,Competitive Sparse Representation Classification for Face Recognition,Chongqing University of Posts and Telecommunications,Chongqing University of Posts and Telecommunications,"重庆邮电大学, 崇文路, 渝中区, 黄桷垭, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400065, 中国",29.53570460,106.60482474,edu,
+108d44bee37d4190883a268274ff78a8fd20de54,Competitive Sparse Representation Classification for Face Recognition,Chongqing University of Posts and Telecommunications,Chongqing University of Posts and Telecommunications,"重庆邮电大学, 崇文路, 渝中区, 黄桷垭, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400065, 中国",29.53570460,106.60482474,edu,
+10ad82949b65bae59410aaab5aac88d2caa6a3d7,Detecting and Synthesizing Synchronous Joint Action in Human-Robot Teams,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+102280e80470ace006e14d6ec9adda082603dea1,Transformation on Computer-Generated Facial Image to Avoid Detection by Spoofing Detector,"National Institute of Informatics, Japan","National Institute of Informatics, Japan","2 Chome-1-２ Hitotsubashi, Chiyoda, Tokyo 100-0003, Japan",35.69248530,139.75825330,edu,
+102280e80470ace006e14d6ec9adda082603dea1,Transformation on Computer-Generated Facial Image to Avoid Detection by Spoofing Detector,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
10550ee13855bd7403946032354b0cd92a10d0aa,Accelerating neuromorphic vision algorithms for recognition,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+102e7bd7660357e1814c821c7f697f2eccececa4,Predicting Motivations of Actions by Leveraging Text,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+102e7bd7660357e1814c821c7f697f2eccececa4,Predicting Motivations of Actions by Leveraging Text,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+10793d1475607929fedc6d9a677911ad16843e58,Unsupervised Learning of Edges,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
10e12d11cb98ffa5ae82343f8904cfe321ae8004,A New Simplex Sparse Learning Model to Measure Data Similarity for Clustering,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+10464196584476a7f3d887fda42444d08f5f8ad4,Generalized Local Binary Patterns for Texture Classification,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+10126b467391e153d36f1a496ef5618097775ad1,An Active Age Estimation of Facial image using Anthropometric Model and Fast ICA,Bangalore Institute of Technology,Bangalore Institute of Technology,"Bangalore Institute of Technology, Krishna Rajendra Road, Mavalli, Vishveshwara Puram, South Zone, Bengaluru, Bangalore Urban, Karnataka, 560004, India",12.95512590,77.57419850,edu,
100105d6c97b23059f7aa70589ead2f61969fbc3,Frontal to profile face verification in the wild,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
100105d6c97b23059f7aa70589ead2f61969fbc3,Frontal to profile face verification in the wild,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+10a36dea0167511b66deca65fdca978aa9afdb11,Simple Baseline for Visual Question Answering,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
100da509d4fa74afc6e86a49352751d365fceee5,Multiclass recognition and part localization with humans in the loop,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
100da509d4fa74afc6e86a49352751d365fceee5,Multiclass recognition and part localization with humans in the loop,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+101d1cff1aa5590a1f79bc485cbfec094a995f74,Persuasive Faces: Generating Faces in Advertisements (Supplementary Material),University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+10ffdfdbc0aafb89d94528f359425de0c7a81986,Interacting HiddenMarkovModels for Video Understanding,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
10af69f11301679b6fbb23855bf10f6af1f3d2e6,Beyond Gaussian Pyramid: Multi-skip Feature Stacking for action recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
100428708e4884300e4c1ac1f84cbb16e7644ccf,Regularized Shearlet Network for face recognition using single sample per person,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
100428708e4884300e4c1ac1f84cbb16e7644ccf,Regularized Shearlet Network for face recognition using single sample per person,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+1091ee239b2344a526a5617233914345389b04fe,Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
10f17534dba06af1ddab96c4188a9c98a020a459,People-LDA: Anchoring Topics to People using Face Recognition,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+102c02bd78c2a4d9a028b779933ff2f164e1e927,Instance Map Based Image Synthesis With a Denoising Generative Adversarial Network,Ocean University of China,Ocean University of China,"中国海洋大学, 238, 松岭路 Sōnglǐng Road, 朱家洼, 崂山区 (Laoshan), 青岛市, 山东省, 266100, 中国",36.16161795,120.49355276,edu,
10e0e6f1ec00b20bc78a5453a00c792f1334b016,Temporal Selective Max Pooling Towards Practical Face Recognition,Johns Hopkins University,"Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA","3400 N Charles St, Baltimore, MD 21218, USA",39.32905300,-76.61942500,edu,
102b968d836177f9c436141e382915a4f8549276,Affective multimodal human-computer interaction,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
102b968d836177f9c436141e382915a4f8549276,Affective multimodal human-computer interaction,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
102b968d836177f9c436141e382915a4f8549276,Affective multimodal human-computer interaction,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
102b968d836177f9c436141e382915a4f8549276,Affective multimodal human-computer interaction,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+10f3d78cf8ae69a5889bea88d3ebe2c6507e5720,LDMNet: Low Dimensional Manifold Regularized Neural Networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+10f3d78cf8ae69a5889bea88d3ebe2c6507e5720,LDMNet: Low Dimensional Manifold Regularized Neural Networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+1096445f1185265c56edb1be3bde6ac4e8d91386,Aspects of facial biometrics for verification of personal identity,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+1096445f1185265c56edb1be3bde6ac4e8d91386,Aspects of facial biometrics for verification of personal identity,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+108961c7366e36825ffed94ac9eab603e05b6bc6,Deep Visual-Semantic Alignments for Generating Image Descriptions,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+102caab9bdf31c1bb4838529be45608ef29efbbd,Nebula feature: A space-time feature for posed and spontaneous 4D facial behavior analysis,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
+107c5030f2c55e0a7cf4c6159cbbd4f719b0d9fb,ViP-CNN: Visual Phrase Guided Convolutional Neural Network,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+108c973b51514f54cf2a078ca243ff0cde091f4b,3D face recognition on low-cost depth sensors,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+10a98632ed618c23c58af93e17d90ef654b1845f,Performance Evaluation of Illumination Invariant Face Recognition Algorthims,Punjabi University Patiala,Punjabi University Patiala,"Punjabi University Patiala, Rajpura Road, Patiala, Punjab, 147001, India",30.35689810,76.45512720,edu,
+10d255fb0bb651b6e9cc69855a970c44f121f2c9,Learning Pose Grammar to Encode Human Body Configuration for 3D Pose Estimation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+10723c39f9dcfcbd45d4ed7460006dba78c6b67f,An accurate 3D human face model reconstruction scheme,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
101d4cfbd6f8a7a10bd33505e2b183183f1d8770,The 2013 SESAME Multimedia Event Detection and Recounting System,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
106092fafb53e36077eba88f06feecd07b9e78e7,Attend and Interact: Higher-Order Object Interactions for Video Understanding,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+10bbdbf86b3dd9a60f9be01401e0585250c97477,"ROY, MARCEL: HLBP FEATURE FOR FAST ILLUMINATION INVARIANT FACE DETECTION1 Haar Local Binary Pattern Feature for Fast Illumination Invariant Face Detection",IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+10b1794dae6128480e5c56ee83f0113930c101cf,Learning Instance-Aware Object Detection Using Determinantal Point Processes,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+10b1794dae6128480e5c56ee83f0113930c101cf,Learning Instance-Aware Object Detection Using Determinantal Point Processes,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+10b1794dae6128480e5c56ee83f0113930c101cf,Learning Instance-Aware Object Detection Using Determinantal Point Processes,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
103c8eaca2a2176babab2cc6e9b25d48870d6928,Panning for gold: finding relevant semantic content for grounded language learning,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+10d85459ab6a9350931fcb4709bba171cd31bbde,Two-person interaction detection using body-pose features and multiple instance learning,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+10d85459ab6a9350931fcb4709bba171cd31bbde,Two-person interaction detection using body-pose features and multiple instance learning,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
10f66f6550d74b817a3fdcef7fdeba13ccdba51c,Benchmarking Face Alignment,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+10d003ba5062c048f0e324c897f849b0c9bc2aab,What to Transfer? High-Level Semantics in Transfer Metric Learning for Action Similarity,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+10f3ead41bf8de97aee9c25b345b8b7495a99aab,Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+10f3ead41bf8de97aee9c25b345b8b7495a99aab,Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
+10156890bc53cb6be97bd144a68fde693bf13612,Face Recognition Using Sparse Representation-Based Classification on K-Nearest Subspace,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
107fc60a6c7d58a6e2d8572ad8c19cc321a9ef53,Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
107fc60a6c7d58a6e2d8572ad8c19cc321a9ef53,Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+1057137d8ebbbfc4e816d74edd7ab04f61a893f8,Craniofacial Aging,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
+1057137d8ebbbfc4e816d74edd7ab04f61a893f8,Craniofacial Aging,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
+1057137d8ebbbfc4e816d74edd7ab04f61a893f8,Craniofacial Aging,Virginia Commonwealth University,Virginia Commonwealth University,"Virginia Commonwealth University, The Compass, Oregon Hill, Richmond, Richmond City, Virginia, 23284, USA",37.54821500,-77.45306424,edu,
+10c49dc22d5c7d885cba238634390013aeda6e0e,Machine-based Multimodal Pain Assessment Tool for Infants: A Review,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+1037664753b281543ce300fed0852a64d24334ba,Binary - Feature Based Recognition and Cryptographic Key Generation from Face Biometrics,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+1037664753b281543ce300fed0852a64d24334ba,Binary - Feature Based Recognition and Cryptographic Key Generation from Face Biometrics,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+1037664753b281543ce300fed0852a64d24334ba,Binary - Feature Based Recognition and Cryptographic Key Generation from Face Biometrics,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+1037664753b281543ce300fed0852a64d24334ba,Binary - Feature Based Recognition and Cryptographic Key Generation from Face Biometrics,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+103a7c3eba36792886ae8005f6492332e6b05bad,Facial Recognition with Encoded Local Projections,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+103a7c3eba36792886ae8005f6492332e6b05bad,Facial Recognition with Encoded Local Projections,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+107231a511fa981ac8d13723d7aea52847580930,Manipulated Object Proposal: A Discriminative Object Extraction and Feature Fusion Framework for First-Person Daily Activity Recognition,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+107231a511fa981ac8d13723d7aea52847580930,Manipulated Object Proposal: A Discriminative Object Extraction and Feature Fusion Framework for First-Person Daily Activity Recognition,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
+107231a511fa981ac8d13723d7aea52847580930,Manipulated Object Proposal: A Discriminative Object Extraction and Feature Fusion Framework for First-Person Daily Activity Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+107231a511fa981ac8d13723d7aea52847580930,Manipulated Object Proposal: A Discriminative Object Extraction and Feature Fusion Framework for First-Person Daily Activity Recognition,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
10ca2e03ff995023a701e6d8d128455c6e8db030,Modeling Stylized Character Expressions via Deep Learning,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+10b987b076fe56e08c89693cdb7207c13b870540,Anticipating Visual Representations from Unlabeled Video,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+10b987b076fe56e08c89693cdb7207c13b870540,Anticipating Visual Representations from Unlabeled Video,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
1921e0a97904bdf61e17a165ab159443414308ed,Informatics Bachelor Thesis Retrieval of Web Images for Computer Vision Research,Bielefeld University,Bielefeld University,"Fachhochschule Bielefeld FB Gestaltung, 3, Lampingstraße, Mitte, Bielefeld, Regierungsbezirk Detmold, Nordrhein-Westfalen, 33615, Deutschland",52.02804210,8.51148270,edu,
+19150b001031cc6d964e83cd28553004f653cc24,Visual Relationship Detection with Language Priors,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1927d01b6b9acf865401b544e25b62a7ddbac5fa,An Enhanced Region Proposal Network for object detection using deep learning method,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
1922ad4978ab92ce0d23acc4c7441a8812f157e5,Face alignment by coarse-to-fine shape searching,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1922ad4978ab92ce0d23acc4c7441a8812f157e5,Face alignment by coarse-to-fine shape searching,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
19e62a56b6772bbd37dfc6b8f948e260dbb474f5,Cross-Domain Metric Learning Based on Information Theory,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
@@ -2053,14 +5556,42 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 193debca0be1c38dabc42dc772513e6653fd91d8,Mnemonic Descent Method: A Recurrent Process Applied for End-to-End Face Alignment,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
193debca0be1c38dabc42dc772513e6653fd91d8,Mnemonic Descent Method: A Recurrent Process Applied for End-to-End Face Alignment,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
193debca0be1c38dabc42dc772513e6653fd91d8,Mnemonic Descent Method: A Recurrent Process Applied for End-to-End Face Alignment,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
-1921795408345751791b44b379f51b7dd54ebfa2,From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
-1921795408345751791b44b379f51b7dd54ebfa2,From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+192c7672216dcfb60da0e7953c1b044d1c209d3d,Marker-Less 3D Human Motion Capture with Monocular Image Sequence and Height-Maps,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+192c7672216dcfb60da0e7953c1b044d1c209d3d,Marker-Less 3D Human Motion Capture with Monocular Image Sequence and Height-Maps,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+192c7672216dcfb60da0e7953c1b044d1c209d3d,Marker-Less 3D Human Motion Capture with Monocular Image Sequence and Height-Maps,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+1987f56cb6bcba142f9a0a580c4351fb3e407b8c,GANerated Hands for Real-time 3D Hand Tracking from Monocular RGB,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1921795408345751791b44b379f51b7dd54ebfa2,From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+1921795408345751791b44b379f51b7dd54ebfa2,From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+1903276bb462d3ccd4f1fac3a8e34a53045ef8a1,Attention-Aware Face Hallucination via Deep Reinforcement Learning,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+19cd6053bbb9b9c67da0c0881e31019f9ce28154,Random Laplace Feature Maps for Semigroup Kernels on Histograms,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+19cd6053bbb9b9c67da0c0881e31019f9ce28154,Random Laplace Feature Maps for Semigroup Kernels on Histograms,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+19458454308a9f56b7de76bf7d8ff8eaa52b0173,Deep Features for Recognizing Disguised Faces in the Wild,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+19a3e5495b420c1f5da283bf39708a6e833a6cc5,Attributes and categories for generic instance search from one example,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+19a3e5495b420c1f5da283bf39708a6e833a6cc5,Attributes and categories for generic instance search from one example,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
19e0cc41b9f89492b6b8c2a8a58d01b8242ce00b,Improving Heterogeneous Face Recognition with Conditional Adversarial Networks,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+19bcd3bd41825a67f48db701a68030c5e6763152,Partial Person Re-Identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+19bcd3bd41825a67f48db701a68030c5e6763152,Partial Person Re-Identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+19bcd3bd41825a67f48db701a68030c5e6763152,Partial Person Re-Identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
19e7bdf8310f9038e1a9cf412b8dd2c77ff64c54,Facial Action Coding Using Multiple Visual Cues and a Hierarchy of Particle Filters,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
1938d85feafdaa8a65cb9c379c9a81a0b0dcd3c4,Monogenic Binary Coding: An Efficient Local Feature Extraction Approach to Face Recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+19d1b811df60f86cbd5e04a094b07f32fff7a32a,Three-dimensional face recognition: an eigensurface approach,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+1958da636ce92d36c0985a6cb00696d90b2475f3,Upper Body Pose Estimation with Temporal Sequential Forests,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
+1958da636ce92d36c0985a6cb00696d90b2475f3,Upper Body Pose Estimation with Temporal Sequential Forests,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+19fed85436eff43e60b9476e3d8742dfedba6384,A Novel Multiple Kernel Sparse Representation based Classification for Face Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
199c2df5f2847f685796c2523221c6436f022464,Self quotient image for face recognition,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
19c0069f075b5b2d8ac48ad28a7409179bd08b86,Modifying the Memorability of Face Photographs,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+19676dd4422301a11aa5fe5e5316e2c412987302,Synthesizing Samples for Zero-shot Learning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+19676dd4422301a11aa5fe5e5316e2c412987302,Synthesizing Samples for Zero-shot Learning,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
+1947791685597368400ca0429695658d1f68541c,Physiological responses to social and nonsocial stimuli in neurotypical adults with high and low levels of autistic traits: implications for understanding nonsocial drive in autism spectrum disorders.,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+1947791685597368400ca0429695658d1f68541c,Physiological responses to social and nonsocial stimuli in neurotypical adults with high and low levels of autistic traits: implications for understanding nonsocial drive in autism spectrum disorders.,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+19997d39447e570c7030a214eb4d81e3669ffd1f,Ultrasound confidence maps and applications in medical image processing,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+19bfe748ec8957ec82a7fef0f2585bb14ab8bdd4,Cross-connected Networks for Multi-task Learning of Detection and Segmentation,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+19d1855e021561d6da9d0200bb18e47f51cddda6,Visual Storytelling,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+19d1855e021561d6da9d0200bb18e47f51cddda6,Visual Storytelling,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+19be4580df2e76b70a39af6e749bf189e1ca3975,Adversarial Binary Coding for Efficient Person Re-identification,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
19a9f658ea14701502d169dc086651b1d9b2a8ea,Structural models for face detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+19242af1c54b2c876b3a930f2406b9553f294fba,Learning Subjective Adjectives from Images by Stacked Convolutional Auto-Encoders,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+197c406b95340dfcdef542db532e0f7a967b9cda,Softer-NMS: Rethinking Bounding Box Regression for Accurate Object Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
19d3b02185ad36fb0b792f2a15a027c58ac91e8e,Im2Text: Describing Images Using 1 Million Captioned Photographs,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
19da9f3532c2e525bf92668198b8afec14f9efea,Challenge: Face verification across age progression using real-world data,University of Delaware,University of Delaware,"University of Delaware, South College Avenue, Newark, New Castle County, Delaware, 19713, USA",39.68103280,-75.75401840,edu,
19868a469dc25ee0db00947e06c804b88ea94fd0,SP-SVM: Large Margin Classifier for Data on Multiple Manifolds,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
@@ -2072,18 +5603,40 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 19878141fbb3117d411599b1a74a44fc3daf296d,Eye-State Action Unit Detection by Gabor Wavelets,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
19878141fbb3117d411599b1a74a44fc3daf296d,Eye-State Action Unit Detection by Gabor Wavelets,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
19f076998ba757602c8fec04ce6a4ca674de0e25,Fast and de-noise support vector machine training method based on fuzzy clustering method for large real world datasets,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+191f8b564c4f90d2ba7423fcce4efd7e902f4f77,"Weakly Supervised Learning of Objects, Attributes and Their Associations",University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+4c130b216126434c8cd857431c9c4a7a7c10aca8,Can Saliency Information Benefit Image Captioning Models?,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+4c130b216126434c8cd857431c9c4a7a7c10aca8,Can Saliency Information Benefit Image Captioning Models?,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
4cb8a691a15e050756640c0a35880cdd418e2b87,Class-Based Matching of Object Parts,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
+4c16fe03bb96328b715acfe40491a90034858800,The development of emotion-related neural circuitry in health and psychopathology.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
4cc681239c8fda3fb04ba7ac6a1b9d85b68af31d,Mining Spatial and Spatio-Temporal ROIs for Action Recognition,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+4cfd770ccecae1c0b4248bc800d7fd35c817bbbd,A Discriminative Feature Learning Approach for Deep Face Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+4cfd770ccecae1c0b4248bc800d7fd35c817bbbd,A Discriminative Feature Learning Approach for Deep Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+4c462a76517f70588a8406ad2a9fa290b7d77e5a,Zero-Shot Recognition via Structured Prediction,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
4c87aafa779747828054cffee3125fcea332364d,View-Constrained Latent Variable Model for Multi-view Facial Expression Classification,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
4c87aafa779747828054cffee3125fcea332364d,View-Constrained Latent Variable Model for Multi-view Facial Expression Classification,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+4cb36aea73a328da8ffcdc616407bae3c908aa07,Re-ranking Person Re-identification with k-Reciprocal Encoding,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+4cb36aea73a328da8ffcdc616407bae3c908aa07,Re-ranking Person Re-identification with k-Reciprocal Encoding,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
4cdae53cebaeeebc3d07cf6cd36fecb2946f3e56,Photorealistic Facial Texture Inference Using Deep Neural Networks,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+4c293a98e929edaff6ed70c22a844c04e604e9fc,Clustering by fast search and merge of local density peaks for gene expression microarray data,Beijing Normal University,Beijing Normal University,"北京师范大学, 19, 新街口外大街, 西城区, 100875, 中国",39.96014155,116.35970438,edu,
+4c293a98e929edaff6ed70c22a844c04e604e9fc,Clustering by fast search and merge of local density peaks for gene expression microarray data,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
4c8e5fc0877d066516bb63e6c31eb1b8b5f967eb,"MODI, KOVASHKA: CONFIDENCE AND DIVERSITY FOR ACTIVE SELECTION 1 Confidence and Diversity for Active Selection of Feedback in Image Retrieval",University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4c02d6874a761182f3776a5a04142e713cd939fa,Crowd Counting using Deep Recurrent Spatial-Aware Network,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+4c02d6874a761182f3776a5a04142e713cd939fa,Crowd Counting using Deep Recurrent Spatial-Aware Network,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
4c8ef4f98c6c8d340b011cfa0bb65a9377107970,Sentiment Recognition in Egocentric Photostreams,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
4c8ef4f98c6c8d340b011cfa0bb65a9377107970,Sentiment Recognition in Egocentric Photostreams,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
4c822785c29ceaf67a0de9c699716c94fefbd37d,A Key Volume Mining Deep Framework for Action Recognition,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
4c822785c29ceaf67a0de9c699716c94fefbd37d,A Key Volume Mining Deep Framework for Action Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
4c822785c29ceaf67a0de9c699716c94fefbd37d,A Key Volume Mining Deep Framework for Action Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+4c33746fc5688da61059daa93978ac887f04cce8,Trainable performance upper bounds for image and video captioning,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+4c971c934a3c56d08af92117cc8b505e03754262,Sparse composite quantization,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+4c971c934a3c56d08af92117cc8b505e03754262,Sparse composite quantization,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+4c971c934a3c56d08af92117cc8b505e03754262,Sparse composite quantization,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+4c971c934a3c56d08af92117cc8b505e03754262,Sparse composite quantization,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+4c7c1c2d6eebd227b1e768eaafa5a61e27552567,A Secure and Privacy Friendly 2D+3D Face Authentication System Robust Under Pose and Illumation Variation,University of Piraeus,University of Piraeus,"Πανεπιστήμιο Πειραιώς, 80, Καραολή και Δημητρίου, Απόλλωνας, Νέο Φάληρο, Πειραιάς, Δήμος Πειραιώς, Περιφερειακή Ενότητα Πειραιώς, Περιφέρεια Αττικής, Αττική, 185 34, Ελλάδα",37.94173275,23.65303262,edu,
+4c8c89670a55e65ad9b92327d3386b5701dddabb,Automatic Eye Detection Error as a Predictor of Face Recognition Performance,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+4cefd47f3327b6d30bf99e61651b18319c4ee829,JUST at VQA-Med: A VGG-Seq2Seq Model,Jordan University of Science and Technology,Jordan University of Science and Technology,"Jordan University of Science and Technology, شارع الأردن, إربد, إربد, الأردن",32.49566485,35.99160717,edu,
4ccf64fc1c9ca71d6aefdf912caf8fea048fb211,Light-weight Head Pose Invariant Gaze Tracking,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+4cc0bcc342647693c21a0ca2cd1e4064faf2fb47,"THE SMILING BEHAVIOR OF INFANTS AT HIGH- AND LOW-RISK FOR AUTISM, THEIR MOTHERS, AND AN UNFAMILIAR ADULT: THE EFFECTS OF INTERACTION TASK, INFANT RISK-STATUS, AND INFANT AGE by",University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
4cdb6144d56098b819076a8572a664a2c2d27f72,Face Synthesis for Eyeglass-Robust Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
4cdb6144d56098b819076a8572a664a2c2d27f72,Face Synthesis for Eyeglass-Robust Face Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
4c6233765b5f83333f6c675d3389bbbf503805e3,Real-time high performance deformable model for face detection in the wild,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
@@ -2091,33 +5644,125 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 4cfa8755fe23a8a0b19909fa4dec54ce6c1bd2f7,Efficient likelihood Bayesian constrained local model,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
4cac9eda716a0addb73bd7ffea2a5fb0e6ec2367,Representing Videos based on Scene Layouts for Recognizing Agent-in-Place Actions,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
4c4236b62302957052f1bbfbd34dbf71ac1650ec,Semi-supervised face recognition with LDA self-training,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+4cca640761c980c77a696a64ad3c1e95b82109be,Evaluating New Variants of Motion Interchange Patterns,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
4cd0da974af9356027a31b8485a34a24b57b8b90,Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+4c56f119ebf7c71f2a83e4d79e8d88314b8e6044,An other-race effect for face recognition algorithms,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+4c56f119ebf7c71f2a83e4d79e8d88314b8e6044,An other-race effect for face recognition algorithms,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+4c302936f43c30430b0b07debd6ed6ef260b5225,Learning Sparse Basis Vectors in Small-Sample Datasets through Regularized Non-Negative Matrix Factorization,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
+4c302936f43c30430b0b07debd6ed6ef260b5225,Learning Sparse Basis Vectors in Small-Sample Datasets through Regularized Non-Negative Matrix Factorization,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
+4c2f3c6384888ee81453b01bb81f35871f618c3f,Automatic 3D modelling of craniofacial form,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
4c170a0dcc8de75587dae21ca508dab2f9343974,FaceTracer: A Search Engine for Large Collections of Images with Faces,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+4c6decd726d04b916d9a2cdd468c64a8a0fc2fdb,Semantic Part Segmentation with Deep Learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+4cf0c6d3da8e20d6f184a4eaa6865d61680982b8,Face recognition based on 3D mesh model,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
4c5b38ac5d60ab0272145a5a4d50872c7b89fe1b,Facial expression recognition with emotion-based feature fusion,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
4c523db33c56759255b2c58c024eb6112542014e,Patch-based within-object classification,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
4c523db33c56759255b2c58c024eb6112542014e,Patch-based within-object classification,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+261a7be6c650de797c7490aeeefba98662acaa20,Shell PCA: Statistical Shape Modelling in Shell Space,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+261a7be6c650de797c7490aeeefba98662acaa20,Shell PCA: Statistical Shape Modelling in Shell Space,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+267bd60e442d87c44eaae3290610138e63d663ab,PoseTrack: Joint Multi-person Pose Estimation and Tracking,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+267bd60e442d87c44eaae3290610138e63d663ab,PoseTrack: Joint Multi-person Pose Estimation and Tracking,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+2607f0093fecd4fee5244d56fcf3f53ff22e949e,Attribute-augmented semantic hierarchy: towards bridging semantic gap and intention gap in image retrieval,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+2607f0093fecd4fee5244d56fcf3f53ff22e949e,Attribute-augmented semantic hierarchy: towards bridging semantic gap and intention gap in image retrieval,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+2607f0093fecd4fee5244d56fcf3f53ff22e949e,Attribute-augmented semantic hierarchy: towards bridging semantic gap and intention gap in image retrieval,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+26b906ad166ed81e59d999ed9bb577f30de81e97,Forecasting Human Dynamics from Static Images,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
261c3e30bae8b8bdc83541ffa9331b52fcf015e6,Shape-from-shading Driven 3D Morphable Models for Illumination Insensitive Face Recognition,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+2625314d30a8dfaf918e93a8e7b243b2e078d191,An Adversarial Approach to Hard Triplet Generation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+2625314d30a8dfaf918e93a8e7b243b2e078d191,An Adversarial Approach to Hard Triplet Generation,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
26f03693c50eb50a42c9117f107af488865f3dc1,Eigenhill vs. Eigenface and Eigenedge,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
+26029a63b2377ef81e3898f55bb204fd853c3e31,PRISM: PRincipled Implicit Shape Model,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+264a2b946fae4af23c646cc08fc56947b5be82cf,Robust object recognition in RGB-D egocentric videos based on Sparse Affine Hull Kernel,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+2637a5d0b677eb3145e5bc484337f99b8486014f,L0 Regularized Stationary Time Estimation for Crowd Group Analysis,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+269248eb8a44da5248cef840f7079b1294dbf237,The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+269248eb8a44da5248cef840f7079b1294dbf237,The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
2609079d682998da2bc4315b55a29bafe4df414e,On rank aggregation for face recognition from videos,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+268e91262c85ff1ce99dfc5751e2b6e44c808325,Frequency Domain Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
26d407b911d1234e8e3601e586b49316f0818c95,[POSTER] Feasibility of Corneal Imaging for Handheld Augmented Reality,Coburg University,Coburg University,"Hochschule für angewandte Wissenschaften Coburg, 2, Friedrich-Streib-Straße, Callenberg, Coburg, Oberfranken, Bayern, 96450, Deutschland",50.26506145,10.95196483,edu,
+264175a074c56667f90db9780580368925944577,Constructing Unrestricted Adversarial Examples with Generative Models,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+264175a074c56667f90db9780580368925944577,Constructing Unrestricted Adversarial Examples with Generative Models,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+264175a074c56667f90db9780580368925944577,Constructing Unrestricted Adversarial Examples with Generative Models,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+264175a074c56667f90db9780580368925944577,Constructing Unrestricted Adversarial Examples with Generative Models,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+26a471a491c2fb162ad403ed932b481d386306c7,Fast Zero-Shot Image Tagging,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+26c58e24687ccbe9737e41837aab74e4a499d259,"Codemaps - Segment, Classify and Search Objects Locally",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+264837a7c36ac409119cf71b22415d5c227a1870,Facial expression recognition under a wide range of head poses,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+2633ee01b41edf9df7bf399e55e14d0c7412523a,Robust Face Recognition through Local Graph Matching,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+2633ee01b41edf9df7bf399e55e14d0c7412523a,Robust Face Recognition through Local Graph Matching,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
26a44feb7a64db7986473ca801c251aa88748477,Unsupervised Learning of Mixture Models with a Uniform Background Component,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
26a44feb7a64db7986473ca801c251aa88748477,Unsupervised Learning of Mixture Models with a Uniform Background Component,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
264f7ab36ff2e23a1514577a6404229d7fe1242b,Facial Expression Recognition by De-expression Residue Learning,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
+260fca0b9eb144fc54f1872b8cc418ae3fdce756,Class-specific nonlinear subspace learning based on optimized class representation,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+26acc572c644d57445170a309daf7765aca6ab45,Learning for Sequential Classification,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+263977d8867a68ac52ca4f7e19048ba2a51cda21,A Quantitative Assessment of 3D Facial Key Point Localization Fitting 2D Shape Models to Curvature Information,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+2670c4b556264605c32326f49ab4a8b4e83ab57f,Looking ahead: Anticipatory cueing of attention to objects others will look at.,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
+2670c4b556264605c32326f49ab4a8b4e83ab57f,Looking ahead: Anticipatory cueing of attention to objects others will look at.,University of East Anglia,University of East Anglia,"Arts (Lower Walkway Level), The Square, Westfield View, Earlham, Norwich, Norfolk, East of England, England, NR4 7TJ, UK",52.62215710,1.24091360,edu,
+260928b80e6bb414f70aa8ed678d8808d214036b,Periocular Recognition Using CNN Features Off-the-Shelf,Halmstad University,Halmstad University,"Högskolan i Halmstad, 3, Kristian IV:s väg, Larsfrid, Nyhem, Halmstad, Hallands län, Götaland, 301 18, Sverige",56.66340325,12.87929727,edu,
+26aa0aff1ea1baf848a521363cc455044690e090,A 2D + 3D Rich Data Approach to Scene Understanding,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+260a975bb1562127634e3447890447d593e4d6dc,Tree-Structured Stick Breaking for Hierarchical Data,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+260a975bb1562127634e3447890447d593e4d6dc,Tree-Structured Stick Breaking for Hierarchical Data,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
266ed43dcea2e7db9f968b164ca08897539ca8dd,Beyond Principal Components: Deep Boltzmann Machines for face modeling,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
266ed43dcea2e7db9f968b164ca08897539ca8dd,Beyond Principal Components: Deep Boltzmann Machines for face modeling,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+26eb2c900814707ae962184ad4173e754247a80a,Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+266b61c5696c83c069e67d242ad5b7d0f5f1dee9,DVQA: Understanding Data Visualizations via Question Answering,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+26cd9c812c279347ae96db31cee1cbee0f646fa4,Harnessing ISA diversity: Design of a heterogeneous-ISA chip multiprocessor,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+260aed27abfe751b3d90aad9c0805d35c359ebd5,Efficient Learning of Domain-invariant Image Representations,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
2642810e6c74d900f653f9a800c0e6a14ca2e1c7,Projection Bank: From High-Dimensional Data to Medium-Length Binary Codes,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+26c591cbb35d4d031d13e27a59adccb74bc89bc6,Learning to Forecast and Refine Residual Motion for Image-to-Video Generation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+26c591cbb35d4d031d13e27a59adccb74bc89bc6,Learning to Forecast and Refine Residual Motion for Image-to-Video Generation,Binghamton University,Binghamton University,"Binghamton University Downtown Center, Washington Street, Downtown, Binghamton, Broome County, New York, 13901, USA",42.09580770,-75.91455689,edu,
+26dacf88181021939c09ffb3529ffd2854fc7ee6,A Layered Approach for Robust Spatial Virtual Human Pose Reconstruction Using a Still Image,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+26c9e57116061594ef843141a6a8bc49759f766c,Beyond Physical Connections: Tree Models in Human Pose Estimation,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+26d86dba4455e8322bd9ea53f490f3bbf95784d5,Geometry-Contrastive GAN for Facial Expression Transfer,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
2654ef92491cebeef0997fd4b599ac903e48d07a,Facial expression recognition from near-infrared video sequences,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
2679e4f84c5e773cae31cef158eb358af475e22f,Adaptive Deep Metric Learning for Identity-Aware Facial Expression Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
2679e4f84c5e773cae31cef158eb358af475e22f,Adaptive Deep Metric Learning for Identity-Aware Facial Expression Recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
2679e4f84c5e773cae31cef158eb358af475e22f,Adaptive Deep Metric Learning for Identity-Aware Facial Expression Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+26919156cec1cc5bec03f63f566c934b55b682cd,From Pictorial Structures to deformable structures,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+26d3f57dd09efff6315ae0064cdad4877f5297d7,Multiple Object Tracking by Learning Feature Representation and Distance Metric Jointly,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+26d3f57dd09efff6315ae0064cdad4877f5297d7,Multiple Object Tracking by Learning Feature Representation and Distance Metric Jointly,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+265c53ce3fbdb3f2623c4b20f38b94d3ed1d878c,Face Destylization,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+265c53ce3fbdb3f2623c4b20f38b94d3ed1d878c,Face Destylization,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+265c53ce3fbdb3f2623c4b20f38b94d3ed1d878c,Face Destylization,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+212165422ce25ccabb4d354fae2d2352b60f2b7d,Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+212165422ce25ccabb4d354fae2d2352b60f2b7d,Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+212165422ce25ccabb4d354fae2d2352b60f2b7d,Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+21c99706bb26e9012bfb4d8d48009a3d45af59b2,Neural Module Networks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
217a21d60bb777d15cd9328970cab563d70b5d23,Hidden Factor Analysis for Age Invariant Face Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
217a21d60bb777d15cd9328970cab563d70b5d23,Hidden Factor Analysis for Age Invariant Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
21a2f67b21905ff6e0afa762937427e92dc5aa0b,Extra Facial Landmark Localization via Global Shape Reconstruction,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+2179e34ef3cca174101f57e3cef8e2360fc64303,InverseNet: Solving Inverse Problems with Splitting Networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+215f26774779e260087c66eda49e22429619db94,Attributes Make Sense on Segmented Objects,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
21258aa3c48437a2831191b71cd069c05fb84cf7,A Robust and Efficient Doubly Regularized Metric Learning Approach,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+21f5652d4f88ac039c58aa530328e65a39eb7b38,Neural Processing of Facial Identity and Emotion in Infants at High-Risk for Autism Spectrum Disorders,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+21f5652d4f88ac039c58aa530328e65a39eb7b38,Neural Processing of Facial Identity and Emotion in Infants at High-Risk for Autism Spectrum Disorders,City University of New York,The City University of New York,"Lehman College of the City University of New York, 250, Bedford Park Boulevard West, Bedford Park, The Bronx, Bronx County, NYC, New York, 10468, USA",40.87228250,-73.89489171,edu,
+21f5652d4f88ac039c58aa530328e65a39eb7b38,Neural Processing of Facial Identity and Emotion in Infants at High-Risk for Autism Spectrum Disorders,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+21f5652d4f88ac039c58aa530328e65a39eb7b38,Neural Processing of Facial Identity and Emotion in Infants at High-Risk for Autism Spectrum Disorders,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+214eb90d0386379972cded05e9f57b884edb1675,Continuous Pain Intensity Estimation from Facial Expressions,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+212ffbe247d3cc3cb32a12c43a74a1146e3fe18c,3D Human Pose Estimation = 2D Pose Estimation + Matching,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+212ffbe247d3cc3cb32a12c43a74a1146e3fe18c,3D Human Pose Estimation = 2D Pose Estimation + Matching,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
21bd9374c211749104232db33f0f71eab4df35d5,Integrating facial makeup detection into multimodal biometric user verification system,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+214c966d1f9c2a4b66f4535d9a0d4078e63a5867,Brainwash: A Data System for Feature Engineering,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
21104bcf07ef0269ab133471a3200b9bf94b2948,Beyond Comparing Image Pairs: Setwise Active Learning for Relative Attributes,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+215f43a46ad30cf0574a2a10cd81fe7741768746,Virtual Human Bodies with Clothing and Hair: From Images to Animation,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+215f43a46ad30cf0574a2a10cd81fe7741768746,Virtual Human Bodies with Clothing and Hair: From Images to Animation,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+215f43a46ad30cf0574a2a10cd81fe7741768746,Virtual Human Bodies with Clothing and Hair: From Images to Animation,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+212211d642aa75f66f8ad3ec04da3a4cc089a5b3,Learning to Localize Little Landmarks,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+21bdcd9be2e9e75ec1d060d8d748a372d9ced230,Neural mechanisms in Williams syndrome: a unique window to genetic influences on cognition and behaviour,University of Louisville,University of Louisville,"University of Louisville, South Brook Street, Louisville, Jefferson County, Kentucky, 40208, USA",38.21675650,-85.75725023,edu,
+218982f0878a3de667fac2bb18b9f50949aefc1c,Multi-pose multi-target tracking for activity understanding,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+218982f0878a3de667fac2bb18b9f50949aefc1c,Multi-pose multi-target tracking for activity understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+211435a4e14d00f4aaed191acfb548185ee800b9,Visual Saliency Based Multiple Objects Segmentation and its Parallel Implementation for Real-Time Vision Processing,Akita Prefectural University,Akita Prefectural University,"秋田県立大学, 秋田天王線, 潟上市, 秋田県, 東北地方, 011-0946, 日本",39.80114990,140.04591160,edu,
+2112edee4a60602e9e5dc5e4f9e352f983f0c8c1,Improved Foreground Detection via Block-Based Classifier Cascade With Probabilistic Decision Integration,"CSIRO, Australia","NICTA, PO Box 6020, St Lucia, QLD 4067, Australia","Research Way, Clayton VIC 3168, Australia",-37.90627370,145.13194490,edu,f.k.a. NICTA
+2112edee4a60602e9e5dc5e4f9e352f983f0c8c1,Improved Foreground Detection via Block-Based Classifier Cascade With Probabilistic Decision Integration,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+21f990f3bb8c7dfe57f31d912fb555819f1a64bd,Randomness and sparsity induced codebook learning with application to cancer image classification,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+21f990f3bb8c7dfe57f31d912fb555819f1a64bd,Randomness and sparsity induced codebook learning with application to cancer image classification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+214f552070a7eb5ef5efe0d6ffeaaa594a3c3535,Learning Everything about Anything: Webly-Supervised Visual Concept Learning,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+2106de484c3f1e3a21f2708effc181f51ca7d709,Social interaction detection using a multi-sensor approach,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+2161f6b7ee3c0acc81603b01dc0df689683577b9,End-to-End Deep Learning for Person Search,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2161f6b7ee3c0acc81603b01dc0df689683577b9,End-to-End Deep Learning for Person Search,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
217de4ff802d4904d3f90d2e24a29371307942fe,"POOF: Part-Based One-vs.-One Features for Fine-Grained Categorization, Face Verification, and Attribute Estimation",Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
217de4ff802d4904d3f90d2e24a29371307942fe,"POOF: Part-Based One-vs.-One Features for Fine-Grained Categorization, Face Verification, and Attribute Estimation",Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+2103bb6772bf01e43a8a4e8e34f16baac7d7c331,Information theoretic sensor management for multi-target tracking with a single pan-tilt-zoom camera,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+21d1315761131ea6b3e2afe7a745b606341616fd,Generative Adversarial Network with Spatial Attention for Face Attribute Editing,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+21d1315761131ea6b3e2afe7a745b606341616fd,Generative Adversarial Network with Spatial Attention for Face Attribute Editing,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+211fe99400bde5116efea3b42719d00a34931dcd,Multimodal Differential Network for Visual Question Generation,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+21e158bcda4e10da88ee8da3799a6144b60d791f,Population Matching Discrepancy and Applications in Deep Learning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
2135a3d9f4b8f5771fa5fc7c7794abf8c2840c44,Lessons from collecting a million biometric samples,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
2135a3d9f4b8f5771fa5fc7c7794abf8c2840c44,Lessons from collecting a million biometric samples,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
210b98394c3be96e7fd75d3eb11a391da1b3a6ca,Spatiotemporal Derivative Pattern: A Dynamic Texture Descriptor for Video Matching,Tafresh University,Tafresh University,"دانشگاه تفرش, پاسداران, خرازان, بخش مرکزی, شهرستان تفرش, استان مرکزی, ایران",34.68092465,50.05341352,edu,
@@ -2125,45 +5770,130 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 210b98394c3be96e7fd75d3eb11a391da1b3a6ca,Spatiotemporal Derivative Pattern: A Dynamic Texture Descriptor for Video Matching,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
21765df4c0224afcc25eb780bef654cbe6f0bc3a,Multi-channel Correlation Filters,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
21765df4c0224afcc25eb780bef654cbe6f0bc3a,Multi-channel Correlation Filters,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+21fa37258834c2e3f075a8465d8de1c178cdaaf5,Shape-based pedestrian parsing,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+216c6d29a6f57c37ef8f26f88b6ec9be5b855a66,From VQA to Multimodal CQA: Adapting Visual QA Models for Community QA Tasks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+216c6d29a6f57c37ef8f26f88b6ec9be5b855a66,From VQA to Multimodal CQA: Adapting Visual QA Models for Community QA Tasks,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
+21bebef8ced5d1e77667c667b54287782556eebc,Image processing and recognition for biological images,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+214959c01b73e2d6eb4a39607de6fdc062526047,Collaborative Sparse Approximation for Multiple-Shot Across-Camera Person Re-identification,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+214959c01b73e2d6eb4a39607de6fdc062526047,Collaborative Sparse Approximation for Multiple-Shot Across-Camera Person Re-identification,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
212608e00fc1e8912ff845ee7a4a67f88ba938fc,Coupled Deep Learning for Heterogeneous Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+210fd81446006bf542b595fa0743b808cb86acbf,Combining Orientational Pooling Features for Scene Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+210fd81446006bf542b595fa0743b808cb86acbf,Combining Orientational Pooling Features for Scene Recognition,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+21cfe8372be299be84818b4bcbe07fa6736540b6,Articulated Pose Estimation Using Discriminative Armlet Classifiers,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
+4dc056cfe5d06cb9e4cbf60ef5044f956ab92b91,Investigating Gait Recognition in the Short-Wave Infrared (SWIR) Spectrum: Dataset and Challenges,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+4dc056cfe5d06cb9e4cbf60ef5044f956ab92b91,Investigating Gait Recognition in the Short-Wave Infrared (SWIR) Spectrum: Dataset and Challenges,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+4d925db7c9e3cca2e8fed644f750d218a48cd081,Automatic Concept Discovery from Parallel Text and Visual Corpora,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
4d625677469be99e0a765a750f88cfb85c522cce,Understanding Hand-Object Manipulation with Grasp Types and Object Attributes,Institute of Industrial Science,Institute of Industrial Science,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
4d625677469be99e0a765a750f88cfb85c522cce,Understanding Hand-Object Manipulation with Grasp Types and Object Attributes,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
4d625677469be99e0a765a750f88cfb85c522cce,Understanding Hand-Object Manipulation with Grasp Types and Object Attributes,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
4d625677469be99e0a765a750f88cfb85c522cce,Understanding Hand-Object Manipulation with Grasp Types and Object Attributes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4d625677469be99e0a765a750f88cfb85c522cce,Understanding Hand-Object Manipulation with Grasp Types and Object Attributes,Institute of Industrial Science,Institute of Industrial Science,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
4d625677469be99e0a765a750f88cfb85c522cce,Understanding Hand-Object Manipulation with Grasp Types and Object Attributes,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+4dcc09fc3718721b41460dda559c1c6f507287b7,A Comprehensive Study on Upper-Body Detection with Deep Neural Networks,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+4dcc09fc3718721b41460dda559c1c6f507287b7,A Comprehensive Study on Upper-Body Detection with Deep Neural Networks,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+4d1757aacbc49c74a5d4e53259c92ab0e47544da,Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+4dcd40005726e66a0e4ed33635b38bb8107a671a,Tasting families of features for image classification,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
4d15254f6f31356963cc70319ce416d28d8924a3,Quo vadis Face Recognition?,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
4d15254f6f31356963cc70319ce416d28d8924a3,Quo vadis Face Recognition?,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4d15254f6f31356963cc70319ce416d28d8924a3,Quo vadis Face Recognition?,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4d89a8228bcf17f444d82ea271a548cb16fd0786,Multiclass Object Recognition Inspired by the Ventral Visual Pathway,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+4d89a8228bcf17f444d82ea271a548cb16fd0786,Multiclass Object Recognition Inspired by the Ventral Visual Pathway,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+4dff129a6f988d78c457ece463b774c3d81ac5c7,Emotion recognition in the wild from videos using images,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+4dff129a6f988d78c457ece463b774c3d81ac5c7,Emotion recognition in the wild from videos using images,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+4dff129a6f988d78c457ece463b774c3d81ac5c7,Emotion recognition in the wild from videos using images,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+4dff129a6f988d78c457ece463b774c3d81ac5c7,Emotion recognition in the wild from videos using images,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+4d42d42de4445545b5e3045be296f917acd33ab5,Convolutional Neural Networks for Aerial Multi-Label Pedestrian Detection,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+4d9c64750ef4565dc47cec0c513458b53dd5c9a7,Unmanned Aerial Vehicle Images,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+4d9c64750ef4565dc47cec0c513458b53dd5c9a7,Unmanned Aerial Vehicle Images,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+4da5f0c1d07725a06c6b4a2646e31ea3a5f14435,End-to-End Training of Hybrid CNN-CRF Models for Semantic Segmentation using Structured Learning,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
4d6462fb78db88afff44561d06dd52227190689c,Face-to-Face Social Activity Detection Using Data Collected with a Wearable Device,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+4d6e98fb5fcb7b5983f615a45ac1d81d1b570ca0,Unsupervised Cross-Dataset Transfer Learning for Person Re-identification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+4d6e98fb5fcb7b5983f615a45ac1d81d1b570ca0,Unsupervised Cross-Dataset Transfer Learning for Person Re-identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+4dd00e37f4129b0c62e111906fd8b239520c08e9,Learning to Separate Domains in Generalized Zero-Shot and Open Set Learning: a probabilistic perspective,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+4dd00e37f4129b0c62e111906fd8b239520c08e9,Learning to Separate Domains in Generalized Zero-Shot and Open Set Learning: a probabilistic perspective,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
4dd71a097e6b3cd379d8c802460667ee0cbc8463,Real-time multi-view facial landmark detector learned by the structured output SVM,"National Institute of Informatics, Japan","National Institute of Informatics, Japan","2 Chome-1-２ Hitotsubashi, Chiyoda, Tokyo 100-0003, Japan",35.69248530,139.75825330,edu,
4db0968270f4e7b3fa73e41c50d13d48e20687be,Fashion Forward: Forecasting Visual Style in Fashion,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
4db0968270f4e7b3fa73e41c50d13d48e20687be,Fashion Forward: Forecasting Visual Style in Fashion,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+4d803109f3d9cca7c514db21a0494972d5681faa,Attribute Adaptation for Personalized Image Search,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
4d9c02567e7b9e065108eb83ea3f03fcff880462,Towards Facial Expression Recognition in the Wild: A New Database and Deep Recognition System,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
4d3c4c3fe8742821242368e87cd72da0bd7d3783,Hybrid Deep Learning for Face Verification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
4d3c4c3fe8742821242368e87cd72da0bd7d3783,Hybrid Deep Learning for Face Verification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
4d3c4c3fe8742821242368e87cd72da0bd7d3783,Hybrid Deep Learning for Face Verification,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
4d01d78544ae0de3075304ff0efa51a077c903b7,ART Network based Face Recognition with Gabor Filters,Jahangirnagar University,Jahangirnagar University,"Jahangirnagar University, 1342, University Main Road, সাভার, সাভার উপজেলা, ঢাকা জেলা, ঢাকা বিভাগ, 1342, বাংলাদেশ",23.88331200,90.26939210,edu,
4dd2be07b4f0393995b57196f8fc79d666b3aec5,Sparse localized facial motion dictionary learning for facial expression recognition,Yeungnam University,Yeungnam University,"영남대, 대학로, 부적리, 경산시, 경북, 712-749, 대한민국",35.83654030,128.75343090,edu,
+4db6456b6933d0ae60bd1d7bb7ae01cea2ca9a9d,Deep Learning in Information Security,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
+4db6456b6933d0ae60bd1d7bb7ae01cea2ca9a9d,Deep Learning in Information Security,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
4d8ce7669d0346f63b20393ffaa438493e7adfec,Similarity Features for Facial Event Analysis,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
4d8ce7669d0346f63b20393ffaa438493e7adfec,Similarity Features for Facial Event Analysis,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+4d1e46b1dcec1c9cbc4e7ff80dbf73e5e7ebcd67,WebCaricature: a benchmark for caricature recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+4d1e46b1dcec1c9cbc4e7ff80dbf73e5e7ebcd67,WebCaricature: a benchmark for caricature recognition,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
4d16337cc0431cd43043dfef839ce5f0717c3483,A Scalable and Privacy-Aware IoT Service for Live Video Analytics,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4d16337cc0431cd43043dfef839ce5f0717c3483,A Scalable and Privacy-Aware IoT Service for Live Video Analytics,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4d16337cc0431cd43043dfef839ce5f0717c3483,A Scalable and Privacy-Aware IoT Service for Live Video Analytics,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4d16337cc0431cd43043dfef839ce5f0717c3483,A Scalable and Privacy-Aware IoT Service for Live Video Analytics,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4d16337cc0431cd43043dfef839ce5f0717c3483,A Scalable and Privacy-Aware IoT Service for Live Video Analytics,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
4d0b3921345ae373a4e04f068867181647d57d7d,Learning Attributes from Human Gaze,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4d58f886f5150b2d5e48fd1b5a49e09799bf895d,Texas 3D Face Recognition Database,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+4d7b66a123135d37689005816aa15ab31167b6d3,Evaluation of the Impetuses of Scan Path in Real Scene Searching,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+4d0e64da142299039841660ea03f24575174afa8,Deformation Analysis for 3D Face Matching,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+4d653b19ce1c7cba79fc2f11271fb90f7744c95c,Light-Weight RefineNet for Real-Time Semantic Segmentation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+4d267098356dc4cfcd3f5aefcc26588ffb23b8dc,Smart Hashing Update for Fast Response,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+75aef130afb8c862575d457db6e168e8d77ae4f0,Content-based search and browsing in semantic multimedia retrieval,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
7574f999d2325803f88c4915ba8f304cccc232d1,Transfer Learning for Cross-Dataset Recognition: A Survey,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
7574f999d2325803f88c4915ba8f304cccc232d1,Transfer Learning for Cross-Dataset Recognition: A Survey,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
7574f999d2325803f88c4915ba8f304cccc232d1,Transfer Learning for Cross-Dataset Recognition: A Survey,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
75fcbb01bc7e53e9de89cb1857a527f97ea532ce,"Detection of Facial Landmarks from Neutral, Happy, and Disgust Facial Images",University of Tampere,University of Tampere,"Tampereen yliopisto, 4, Kalevantie, Ratinanranta, Tulli, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33100, Suomi",61.49412325,23.77920678,edu,
+756eed9fe591cf53c7ebbaba05ceeb39b212f802,Learning to Refine Human Pose Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+75e5a1a64d9d27dbb054fc8b8d47f0e23cbbbfa4,The importance of internal facial features in learning new faces.,University of Plymouth,University of Plymouth,"Charles Seale-Hayne Library, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37525010,-4.13927692,edu,
+75e5a1a64d9d27dbb054fc8b8d47f0e23cbbbfa4,The importance of internal facial features in learning new faces.,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
+75e5a1a64d9d27dbb054fc8b8d47f0e23cbbbfa4,The importance of internal facial features in learning new faces.,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+75e5a1a64d9d27dbb054fc8b8d47f0e23cbbbfa4,The importance of internal facial features in learning new faces.,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
+756275128fae4ffe8389261e498f9bb49a8381b2,Designing and Testing an Anonymous Face Recognition System,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+759f4f7601292c37e2f1c4a5a9f53075e9e355ec,Instance Retrieval at Fine-grained Level Using Multi-Attribute Recognition,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
757e4cb981e807d83539d9982ad325331cb59b16,Demographics versus Biometric Automatic Interoperability,Sapienza University of Rome,Sapienza University of Rome,"Piazzale Aldo Moro, 5, 00185 Roma RM, Italy",41.90376260,12.51443840,edu,
757e4cb981e807d83539d9982ad325331cb59b16,Demographics versus Biometric Automatic Interoperability,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+75f302f1372136c5e43e523bacc0a2ddf04c3237,Schema Independent Relational Learning,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+75f302f1372136c5e43e523bacc0a2ddf04c3237,Schema Independent Relational Learning,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+75f302f1372136c5e43e523bacc0a2ddf04c3237,Schema Independent Relational Learning,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+75f302f1372136c5e43e523bacc0a2ddf04c3237,Schema Independent Relational Learning,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+75c30403bad798381afa70f225e402ee7d84cd34,Learning to generate images with perceptual similarity metrics,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+759f7f9e4a363223dc06903ef88fed27a3a64826,Modeling and Analysis of Dynamic Behaviors of Web Image Collections,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+759f7f9e4a363223dc06903ef88fed27a3a64826,Modeling and Analysis of Dynamic Behaviors of Web Image Collections,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+759f7f9e4a363223dc06903ef88fed27a3a64826,Modeling and Analysis of Dynamic Behaviors of Web Image Collections,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+759f7f9e4a363223dc06903ef88fed27a3a64826,Modeling and Analysis of Dynamic Behaviors of Web Image Collections,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
75fd9acf5e5b7ed17c658cc84090c4659e5de01d,Project-Out Cascaded Regression with an application to face alignment,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+75a54f49fccee29faca8931fa8ba700030dcaa75,Ringtail: A Generalized Nowcasting System,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+75a54f49fccee29faca8931fa8ba700030dcaa75,Ringtail: A Generalized Nowcasting System,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+75a54f49fccee29faca8931fa8ba700030dcaa75,Ringtail: A Generalized Nowcasting System,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+75a54f49fccee29faca8931fa8ba700030dcaa75,Ringtail: A Generalized Nowcasting System,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+75a54f49fccee29faca8931fa8ba700030dcaa75,Ringtail: A Generalized Nowcasting System,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+75b1d8339085ab03f45c0316b976755b6c5da9e9,SMD: A Locally Stable Monotonic Change Invariant Feature Descriptor,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+7523ead2a91191f0ecfb88fba5c0f2deeddaa256,Generating Chinese Captions for Flickr30K Images,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+7523ead2a91191f0ecfb88fba5c0f2deeddaa256,Generating Chinese Captions for Flickr30K Images,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+7552a6dbee4a915b578453ed9f35a4c6cc114aa1,Now You Shake Me : Towards Automatic 4 D Cinema,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
75bf3b6109d7a685236c8589f8ead7d769ea863f,Model Selection with Nonlinear Embedding for Unsupervised Domain Adaptation,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+75003c069da53911f714d8d28b121ed9b29e0911,SORT: Second-Order Response Transform for Visual Recognition,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+75003c069da53911f714d8d28b121ed9b29e0911,SORT: Second-Order Response Transform for Visual Recognition,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
759cf57215fcfdd8f59c97d14e7f3f62fafa2b30,Real-time Distracted Driver Posture Classification,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
751970d4fb6f61d1b94ca82682984fd03c74f127,Array-based Electromyographic Silent Speech Interface,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+759b28cb6527f8820f1cffc3581884c5caa19091,Neighbor-Sensitive Hashing,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+759b28cb6527f8820f1cffc3581884c5caa19091,Neighbor-Sensitive Hashing,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+759b28cb6527f8820f1cffc3581884c5caa19091,Neighbor-Sensitive Hashing,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+756db84f76d745211464b5686a67bfdc23e18c19,How to generate realistic images using gated MRF’s,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+75776ce56e649dda68d9a8f13a9df911662e5b79,Face Modelling and Tracking from Range Scans,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
75ebe1e0ae9d42732e31948e2e9c03d680235c39,Hello! My name is... Buffy'' -- Automatic Naming of Characters in TV Video,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+7573ff84d71de19fe7d387bb4a6de73cb28402f4,Zero-Shot Hashing via Transferring Supervised Knowledge,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+751e352fe52946ca3d0f51956706313ce521b658,Hierarchical power management for asymmetric multi-core in dark silicon era,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+754ee07789f6ff28fc121bb9f771895e971ac28c,Beyond Triplet Loss: A Deep Quadruplet Network for Person Re-identification,University of Dundee,University of Dundee,"University of Dundee, Park Wynd, Law, Dundee, Dundee City, Scotland, DD1 4HN, UK",56.45796755,-2.98214831,edu,
+75b20672a6290a8e2769ba0226d9187c0ccd5843,Development of response inhibition in the context of relevant versus irrelevant emotions,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+7566032327a19f9ba770022677de34d7e7aeaac8,What Makes Natural Scene Memorable?,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+7566032327a19f9ba770022677de34d7e7aeaac8,What Makes Natural Scene Memorable?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+7566032327a19f9ba770022677de34d7e7aeaac8,What Makes Natural Scene Memorable?,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+7566032327a19f9ba770022677de34d7e7aeaac8,What Makes Natural Scene Memorable?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+7566032327a19f9ba770022677de34d7e7aeaac8,What Makes Natural Scene Memorable?,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+7566032327a19f9ba770022677de34d7e7aeaac8,What Makes Natural Scene Memorable?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+7566032327a19f9ba770022677de34d7e7aeaac8,What Makes Natural Scene Memorable?,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+7566032327a19f9ba770022677de34d7e7aeaac8,What Makes Natural Scene Memorable?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
751b26e7791b29e4e53ab915bfd263f96f531f56,Mood meter: counting smiles in the wild,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
75da1df4ed319926c544eefe17ec8d720feef8c0,FDDB: A Benchmark for Face Detection in Unconstrained Settings,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
75da1df4ed319926c544eefe17ec8d720feef8c0,FDDB: A Benchmark for Face Detection in Unconstrained Settings,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
@@ -2171,207 +5901,619 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 754f7f3e9a44506b814bf9dc06e44fecde599878,Quantized Densely Connected U-Nets for Efficient Landmark Localization,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
754f7f3e9a44506b814bf9dc06e44fecde599878,Quantized Densely Connected U-Nets for Efficient Landmark Localization,Binghamton University,Binghamton University,"Binghamton University Downtown Center, Washington Street, Downtown, Binghamton, Broome County, New York, 13901, USA",42.09580770,-75.91455689,edu,
754f7f3e9a44506b814bf9dc06e44fecde599878,Quantized Densely Connected U-Nets for Efficient Landmark Localization,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+75b1790ffcf51489fcfbf14b11f1b90a076345cc,A Coarse-Fine Network for Keypoint Localization,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+75b1790ffcf51489fcfbf14b11f1b90a076345cc,A Coarse-Fine Network for Keypoint Localization,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+75064b7675553c22112b76b5687e0aed4089b0ea,COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+75064b7675553c22112b76b5687e0aed4089b0ea,COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+751223e9636f4624551b37d8891f0e06eeb64a5d,Multilinear Wavelets: A Statistical Shape Space for Human Faces,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+7536b6a9f3cb4ae810e2ef6d0219134b4e546dd0,Semi-Automatic Image Labelling Using Depth Information,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+755416b8d2080f5d9e894130e5115a471e9d8793,Learning to Recognize Objects by Retaining Other Factors of Variation,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+7525e1fed92a780b6cb78190da360a3a7b611885,Data-specific concept correlation estimation for video annotation refinement,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
75d2ecbbcc934563dff6b39821605dc6f2d5ffcc,Capturing Subtle Facial Motions in 3D Face Tracking,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
75d2ecbbcc934563dff6b39821605dc6f2d5ffcc,Capturing Subtle Facial Motions in 3D Face Tracking,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+8102311b200c68e7928eb28563fd99cd5e8fbfc1,"Occlusion-Aware Object Localization, Segmentation and Pose Estimation",Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+81f63e7344cc242416e37d791f7eb83ec2c07681,Multimodal Co-Training for Selecting Good Examples from Webly Labeled Video,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+81363f85b2827c5d972b7b0691498464e922fdea,Transfer Learning via Unsupervised Task Discovery for Visual Question Answering,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+8150f267cd2852f27639d4d85c3a311360346c88,Salient Montages from Unconstrained Videos,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+81825711c2aaa1b9d3ead1a300e71c4353a41382,End-to-end training of object class detectors for mean average precision,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+81d0ab3201fbaef5aff57e9df2c12c7b4f228987,Talking Face Generation by Conditional Recurrent Adversarial Network,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
816bd8a7f91824097f098e4f3e0f4b69f481689d,Latent semantic analysis of facial action codes for automatic facial expression recognition,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
816bd8a7f91824097f098e4f3e0f4b69f481689d,Latent semantic analysis of facial action codes for automatic facial expression recognition,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+81ba5202424906f64b77f68afca063658139fbb2,Social Scene Understanding: End-to-End Multi-person Action Localization and Collective Activity Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+81ba5202424906f64b77f68afca063658139fbb2,Social Scene Understanding: End-to-End Multi-person Action Localization and Collective Activity Recognition,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+8145ff6adab3397a5ac52cc62a7c53dae59763db,ERP responses differentiate inverted but not upright face processing in adults with ASD.,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+81884e1de00e59f24bc20254584d73a1a1806933,Super-Identity Convolutional Neural Network for Face Hallucination,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+81884e1de00e59f24bc20254584d73a1a1806933,Super-Identity Convolutional Neural Network for Face Hallucination,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+81884e1de00e59f24bc20254584d73a1a1806933,Super-Identity Convolutional Neural Network for Face Hallucination,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+810cb5228315ac027bb8fbca94f6f8faa6ff8016,A Unified Contour-Pixel Model for Figure-Ground Segmentation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+810cb5228315ac027bb8fbca94f6f8faa6ff8016,A Unified Contour-Pixel Model for Figure-Ground Segmentation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+81c7d56f1a77097c8fa14b76cb359d7f436741a0,Looking at Outfit to Parse Clothing,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+81c7d56f1a77097c8fa14b76cb359d7f436741a0,Looking at Outfit to Parse Clothing,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+81c7d56f1a77097c8fa14b76cb359d7f436741a0,Looking at Outfit to Parse Clothing,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
81e11e33fc5785090e2d459da3ac3d3db5e43f65,A Novel Face Recognition Approach Using a Multimodal Feature Vector,"National Institute of Technology, Durgapur","National Institute of Technology, Durgapur, India","National Institute Of Technology, Durgapur, Priyadarshini Indira Sarani, Durgapur, Bānkurā, West Bengal, 713209, India",23.54869625,87.29105712,edu,
+810baa46ed829553bdb478dad2782cef2278ca60,A Scalable Approach to Column-Based Low-Rank Matrix Approximation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+810baa46ed829553bdb478dad2782cef2278ca60,A Scalable Approach to Column-Based Low-Rank Matrix Approximation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+810baa46ed829553bdb478dad2782cef2278ca60,A Scalable Approach to Column-Based Low-Rank Matrix Approximation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+810baa46ed829553bdb478dad2782cef2278ca60,A Scalable Approach to Column-Based Low-Rank Matrix Approximation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+810baa46ed829553bdb478dad2782cef2278ca60,A Scalable Approach to Column-Based Low-Rank Matrix Approximation,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+8112972b8a6e0c7f9443dbcdfb4ed65c7484f8c2,Privacy-preserving Machine Learning through Data Obfuscation,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+8112972b8a6e0c7f9443dbcdfb4ed65c7484f8c2,Privacy-preserving Machine Learning through Data Obfuscation,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+8112972b8a6e0c7f9443dbcdfb4ed65c7484f8c2,Privacy-preserving Machine Learning through Data Obfuscation,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+8175f126198c126f9708fa8a04f57af830fba6aa,"DCGANs for image super-resolution, denoising and debluring",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+8175f126198c126f9708fa8a04f57af830fba6aa,"DCGANs for image super-resolution, denoising and debluring",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
81e366ed1834a8d01c4457eccae4d57d169cb932,Pose-Configurable Generic Tracking of Elongated Objects,Gdansk University of Technology,Gdansk University of Technology,"PG, Romualda Traugutta, Królewska Dolina, Wrzeszcz Górny, Gdańsk, pomorskie, 80-233, RP",54.37086525,18.61716016,edu,
+8189e4f5fc09ae691c77bbd0d4e09b8853b02edf,Pose estimation of anime/manga characters: a case for synthetic data,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+8189e4f5fc09ae691c77bbd0d4e09b8853b02edf,Pose estimation of anime/manga characters: a case for synthetic data,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
8164ebc07f51c9e0db4902980b5ac3f5a8d8d48c,Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+81fe36a1a49eabe38c7d98602447eec518af1aa2,Graph Regularised Hashing,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
81fc86e86980a32c47410f0ba7b17665048141ec,Segment-based Methods for Facial Attribute Detection from Partial Faces,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+818ecc8c8d4dc398b01a852df90cb8d972530fa5,Unsupervised Training for 3D Morphable Model Regression,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+818ecc8c8d4dc398b01a852df90cb8d972530fa5,Unsupervised Training for 3D Morphable Model Regression,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+8170d124e78a3f127c2da291aa1116e85c13c02e,Automatic adaptation of fingerprint liveness detector to new spoof materials,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+81dbc36c38b820dff88bcca177bb644f55a4926f,Minimal Neighborhood Mean Projection Function and Its Application to Eye Location,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+81bf7a4b8b3c21d42cb82f946f762c94031e11b8,Segmentation of Nerve on Ultrasound Images Using Deep Adversarial Network,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+81bf7a4b8b3c21d42cb82f946f762c94031e11b8,Segmentation of Nerve on Ultrasound Images Using Deep Adversarial Network,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+815e77b8f2e8f17205e46162b3addd02b2ea8ff0,Marker-less Pose Estimation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+81a8b2e55bcea9d9b26e67fcbb5a30ca8a8defc3,Database size effects on performance on a smart card face verification system,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+81e31899aa9f0f54db069f0f4c2a29ed9587fe89,MTLE: A Multitask Learning Encoder of Visual Feature Representations for Video and Movie Description,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+81e31899aa9f0f54db069f0f4c2a29ed9587fe89,MTLE: A Multitask Learning Encoder of Visual Feature Representations for Video and Movie Description,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+81e31899aa9f0f54db069f0f4c2a29ed9587fe89,MTLE: A Multitask Learning Encoder of Visual Feature Representations for Video and Movie Description,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+812e06a4cee26629e198a0a6d991616933ab14d8,Improving Multiple Object Tracking with Optical Flow and Edge Preprocessing,Polytechnique Montreal,Polytechnique Montr´eal,"2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4, Canada",45.50438400,-73.61288290,edu,"Polytechnique Montreal, Montreal, Quebec, Canada"
+812e06a4cee26629e198a0a6d991616933ab14d8,Improving Multiple Object Tracking with Optical Flow and Edge Preprocessing,Polytechnique Montreal,Polytechnique Montr´eal,"2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4, Canada",45.50438400,-73.61288290,edu,"Polytechnique Montreal, Montreal, Quebec, Canada"
+814a3acea78a7a79a499c52ff2efc57254f8d02c,3D Pick&Mix: Object Part Blending in Joint Shape and Image Manifolds,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+814a3acea78a7a79a499c52ff2efc57254f8d02c,3D Pick&Mix: Object Part Blending in Joint Shape and Image Manifolds,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
81da427270c100241c07143885ba3051ec4a2ecb,Learning the Synthesizability of Dynamic Texture Samples,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+8120e2d8233f5335b09e673e63395a76ae0e6bae,Recent Advances in Deep Learning: An Overview,Chittagong University of Engineering and Technology,Chittagong University of Engineering and Technology,"Shaheed Tareq Huda Hall, Goal Chattar, চট্টগ্রাম, চট্টগ্রাম জেলা, চট্টগ্রাম বিভাগ, 4349, বাংলাদেশ",22.46221665,91.96942263,edu,
+867596b7c4a2e108dc5a024f85cdfd77a574f5a7,Sparse kernel logistic regression based on L 1/2 regularization,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
861c650f403834163a2c27467a50713ceca37a3e,Probabilistic Elastic Part Model for Unsupervised Face Detector Adaptation,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
86f191616423efab8c0d352d986126a964983219,Visual to Sound: Generating Natural Sound for Videos in the Wild,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+8670fea0d92c6a0e767d089083a39d5896db8534,"Monocular Depth Estimation with Affinity, Vertical Pooling, and Label Enhancement",SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+8670fea0d92c6a0e767d089083a39d5896db8534,"Monocular Depth Estimation with Affinity, Vertical Pooling, and Label Enhancement",Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+8670fea0d92c6a0e767d089083a39d5896db8534,"Monocular Depth Estimation with Affinity, Vertical Pooling, and Label Enhancement",Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+86cf00b2c22200745276239d32451ff14ee65296,Boosting Associated Pairing Comparison Features for pedestrian detection,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+8656f48aa77f25462b3ad2edf2b1aa965b2b7b38,Paradigms for the Construction and Annotation of Emotional Corpora for Real-world Human-Computer-Interaction,Ulm University,Ulm University,"HNU, John-F.-Kennedy-Straße, Vorfeld, Wiley, Neu-Ulm, Landkreis Neu-Ulm, Schwaben, Bayern, 89231, Deutschland",48.38044335,10.01010115,edu,
+8656f48aa77f25462b3ad2edf2b1aa965b2b7b38,Paradigms for the Construction and Annotation of Emotional Corpora for Real-world Human-Computer-Interaction,Ulm University,Ulm University,"HNU, John-F.-Kennedy-Straße, Vorfeld, Wiley, Neu-Ulm, Landkreis Neu-Ulm, Schwaben, Bayern, 89231, Deutschland",48.38044335,10.01010115,edu,
+8627e6ccb42c909b5c1f94304af986472effb6f1,Understanding Convolutional Neural Networks in Terms of Category-Level Attributes,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+863ffd74d39c33b6351dea90c6f7f1e2bdf2d97c,A Baseline Algorithm for Face Detection and Tracking in Video,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+863ffd74d39c33b6351dea90c6f7f1e2bdf2d97c,A Baseline Algorithm for Face Detection and Tracking in Video,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+863f2a473e9e60dbfffe9f7eb576b9bbe3d3a6b4,The Intelligent Robot Contents for Children with Speech-Language Disorder,SungKyunKwan University,SungKyunKwan University,"성균관대, 덕영대로, 천천동, 장안구, 수원시, 경기, 16357, 대한민국",37.30031270,126.97212300,edu,
86c5478f21c4a9f9de71b5ffa90f2a483ba5c497,"Kernel Selection using Multiple Kernel Learning and Domain Adaptation in Reproducing Kernel Hilbert Space, for Face Recognition under Surveillance Scenario",Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+86c158ef6caaf247d5d14e07c5edded0147df8b7,Spatial Memory for Context Reasoning in Object Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8628edf89482aef7fba204f3f0a9e9f5b12ec477,Compositional Obverter Communication Learning From Raw Visual Input,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+86a84b3a61f67f59c5bc5545bc88296e46681ca5,Using Models of Objects with Deformable Parts for Joint Categorization and Segmentation of Objects,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
86ed5b9121c02bcf26900913f2b5ea58ba23508f,Actions ~ Transformations,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
86ed5b9121c02bcf26900913f2b5ea58ba23508f,Actions ~ Transformations,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+86204fc037936754813b91898377e8831396551a,Dense Face Alignment,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
86b6afc667bb14ff4d69e7a5e8bb2454a6bbd2cd,Attentional Alignment Networks,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
86b6afc667bb14ff4d69e7a5e8bb2454a6bbd2cd,Attentional Alignment Networks,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
86b6afc667bb14ff4d69e7a5e8bb2454a6bbd2cd,Attentional Alignment Networks,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
862d17895fe822f7111e737cbcdd042ba04377e8,Semi-Latent GAN: Learning to generate and modify facial images from attributes,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+860cc25e1cee40d70d001180ff665809c6e36594,Efficient Boosted Weak Classifiers for Object Detection,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+860cc25e1cee40d70d001180ff665809c6e36594,Efficient Boosted Weak Classifiers for Object Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
86d0127e1fd04c3d8ea78401c838af621647dc95,A Novel Multi-Task Tensor Correlation Neural Network for Facial Attribute Prediction,Hunan University,Hunan University,"Yejin University for Employees, 冶金西路, 和平乡, 珠晖区, 衡阳市 / Hengyang, 湖南省, 中国",26.88111275,112.62850666,edu,
86d0127e1fd04c3d8ea78401c838af621647dc95,A Novel Multi-Task Tensor Correlation Neural Network for Facial Attribute Prediction,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
86d0127e1fd04c3d8ea78401c838af621647dc95,A Novel Multi-Task Tensor Correlation Neural Network for Facial Attribute Prediction,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+86f17e74b905c8251223caf9b4e99784264c6252,Video retrieval by mimicking poses,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+86f17e74b905c8251223caf9b4e99784264c6252,Video retrieval by mimicking poses,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+86f17e74b905c8251223caf9b4e99784264c6252,Video retrieval by mimicking poses,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+86e005b54819ca54d35daa2ae7ead498f41d84ce,Weakly Supervised Object Recognition and Localization with Invariant High Order Features,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+86eab1845deb3614233360b6bc33ce1ff074458e,Learning Deep Neural Networks for Vehicle Re-ID with Visual-spatio-Temporal Path Proposals,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+86eab1845deb3614233360b6bc33ce1ff074458e,Learning Deep Neural Networks for Vehicle Re-ID with Visual-spatio-Temporal Path Proposals,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
86f3552b822f6af56cb5079cc31616b4035ccc4e,Towards Miss Universe automatic prediction: The evening gown competition,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
86a8b3d0f753cb49ac3250fa14d277983e30a4b7,Exploiting Unlabeled Ages for Aging Pattern Analysis on a Large Database,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
860588fafcc80c823e66429fadd7e816721da42a,Unsupervised Discovery of Object Landmarks as Structural Representations,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+86a200647f89ed81db8031ccfbcb5368a32bed6c,SHOE: Sibling Hashing with Output Embeddings,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+861f4aac1178bf1c4dd1373dbf2794be54c195d4,Survey of Image Processing Techniques for Brain Pathology Diagnosis: Challenges and Opportunities,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+861f4aac1178bf1c4dd1373dbf2794be54c195d4,Survey of Image Processing Techniques for Brain Pathology Diagnosis: Challenges and Opportunities,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
86374bb8d309ad4dbde65c21c6fda6586ae4147a,Detect-and-Track: Efficient Pose Estimation in Videos,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
86374bb8d309ad4dbde65c21c6fda6586ae4147a,Detect-and-Track: Efficient Pose Estimation in Videos,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
86374bb8d309ad4dbde65c21c6fda6586ae4147a,Detect-and-Track: Efficient Pose Estimation in Videos,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
72282287f25c5419dc6fd9e89ec9d86d660dc0b5,A Rotation Invariant Latent Factor Model for Moveme Discovery from Static Poses,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+727067392502bb44cadcd55680156e9517a3fd65,Does this Smile Make me Look White ? Exploring the Effects of Emotional Expressions on the Categorization of Multiracial Children,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+72aa01cc6dbadc631407b4d2d0addec172dc5037,Low-rank matrix recovery with structural incoherence for robust face recognition,"Academia Sinica, Taiwan","Research Center for Institute of Information Science, Academia Sinica, Taiwan","115, Taiwan, Taipei City, Nangang District, 研究院路二段128號",25.04117270,121.61465180,edu,
+7237b27dac6dfe5c07a2c6c36ad848e6bcc7ac77,Person Depth ReID: Robust Person Re-identification with Commodity Depth Sensors,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+7237b27dac6dfe5c07a2c6c36ad848e6bcc7ac77,Person Depth ReID: Robust Person Re-identification with Commodity Depth Sensors,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+7237b27dac6dfe5c07a2c6c36ad848e6bcc7ac77,Person Depth ReID: Robust Person Re-identification with Commodity Depth Sensors,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+7237b27dac6dfe5c07a2c6c36ad848e6bcc7ac77,Person Depth ReID: Robust Person Re-identification with Commodity Depth Sensors,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+7292510a78ef9dfda8aa54dab318a7780b2e8faf,Hardware for machine learning: Challenges and opportunities,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+72a672cd20a3b7b2a123772ac0f9a27cfe96effe,Image-based Ear Biometric Smartphone App for Patient Identification in Field Settings,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+72969929a95227fd7f9a1abaa832097c0c93dd71,Appearance Descriptors for Person Re-identification: a Comprehensive Review,University of Cagliari,"University of Cagliari, Italy","Via Università, 40, 09124 Cagliari CA, Italy",39.21736570,9.11492180,edu,
+72e8010136460340683a52c2aee4edaee0b48559,Repulsion Loss: Detecting Pedestrians in a Crowd,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+72e8010136460340683a52c2aee4edaee0b48559,Repulsion Loss: Detecting Pedestrians in a Crowd,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+72e8010136460340683a52c2aee4edaee0b48559,Repulsion Loss: Detecting Pedestrians in a Crowd,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
72a5e181ee8f71b0b153369963ff9bfec1c6b5b0,Expression Recognition in Videos Using a Weighted Component-Based Feature Descriptor,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
72a5e181ee8f71b0b153369963ff9bfec1c6b5b0,Expression Recognition in Videos Using a Weighted Component-Based Feature Descriptor,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+72458e19f8561e74471449fb4cfd97c8b9b527e8,A Computational Model of Observer Stress,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+72eab1e61706519e8c05cc042f0597b439874413,Genetic Programming for Multiclass Object Classification,Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
+72903a6b9894f13facf46a81bd7b659740b488e5,Worldwide AI,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
7224d58a7e1f02b84994b60dc3b84d9fe6941ff5,When Face Recognition Meets with Deep Learning: An Evaluation of Convolutional Neural Networks for Face Recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
7224d58a7e1f02b84994b60dc3b84d9fe6941ff5,When Face Recognition Meets with Deep Learning: An Evaluation of Convolutional Neural Networks for Face Recognition,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
7224d58a7e1f02b84994b60dc3b84d9fe6941ff5,When Face Recognition Meets with Deep Learning: An Evaluation of Convolutional Neural Networks for Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+720e06688e1038026070253891037652f5d0d9f5,Chess Q&A : Question Answering on Chess Games,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+72b34e9536665f776b0f282ddb63120afa21c84e,An experimental examination of catastrophizing-related interpretation bias for ambiguous facial expressions of pain using an incidental learning task,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
72e10a2a7a65db7ecdc7d9bd3b95a4160fab4114,Face alignment using cascade Gaussian process regression trees,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
72160aae43cd9b2c3aae5574acc0d00ea0993b9e,Boosting Facial Expression Recognition in a Noisy Environment Using LDSP-Local Distinctive Star Pattern,Stamford University Bangladesh,Stamford University Bangladesh,"Stamford University Bangladesh, Siddeshwari Road, ফকিরাপুল, Paltan, ঢাকা, ঢাকা বিভাগ, 1217, বাংলাদেশ",23.74481660,90.40843514,edu,
72160aae43cd9b2c3aae5574acc0d00ea0993b9e,Boosting Facial Expression Recognition in a Noisy Environment Using LDSP-Local Distinctive Star Pattern,Stamford University Bangladesh,Stamford University Bangladesh,"Stamford University Bangladesh, Siddeshwari Road, ফকিরাপুল, Paltan, ঢাকা, ঢাকা বিভাগ, 1217, বাংলাদেশ",23.74481660,90.40843514,edu,
72160aae43cd9b2c3aae5574acc0d00ea0993b9e,Boosting Facial Expression Recognition in a Noisy Environment Using LDSP-Local Distinctive Star Pattern,Stamford University Bangladesh,Stamford University Bangladesh,"Stamford University Bangladesh, Siddeshwari Road, ফকিরাপুল, Paltan, ঢাকা, ঢাকা বিভাগ, 1217, বাংলাদেশ",23.74481660,90.40843514,edu,
72cbbdee4f6eeee8b7dd22cea6092c532271009f,Masquer Hunter: Adversarial Occlusion-aware Face Detection,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+723f879b93097c22ffa4fe6b587d3a070a67136b,Learning Spatial Interest Regions from Videos to Inform Action Recognition in Still Images,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+72edfb91e4b3d42547591be9e8c6eb07e7190499,Do Children See in Black and White? Children's and Adults' Categorizations of Multiracial Individuals.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
721e5ba3383b05a78ef1dfe85bf38efa7e2d611d,"BULAT, TZIMIROPOULOS: CONVOLUTIONAL AGGREGATION OF LOCAL EVIDENCE 1 Convolutional aggregation of local evidence for large pose face alignment",University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+72007faf3bc77e1d98d3552f36c0b6b74aa9e379,The Relationship between Amygdala Activation and Passive Exposure Time to an Aversive Cue during a Continuous Performance Task,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+72a4390a6c3b2bc2c3e7d83fc1f99e65e6137573,Collective Activity Localization with Contextual Spatial Pyramid,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+72c69a7a791ff86f84f082b73e09733bb90edfd7,Face photo retrieval by sketch example,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+72c69a7a791ff86f84f082b73e09733bb90edfd7,Face photo retrieval by sketch example,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+72635f4e479e234a9ceb9c836153830621b308c7,Exemplar-Based Colour Constancy,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+7249e94317ff7cb5dc39441f3473a2d4f1c1d30b,Action Attribute Detection from Sports Videos with Contextual Constraints,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+72ed3be320e435a1dc093c84071a22d3d64fd997,Eye Spy: Improving Vision through Dialog,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+721b890875660e87e7e3d9dd6917709b5fc5e34d,On optimizing subspaces for face recognition,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+72a7eb68f0955564e1ceafa75aeeb6b5bbb14e7e,Face Recognition with Contrastive Convolution,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+72a7eb68f0955564e1ceafa75aeeb6b5bbb14e7e,Face Recognition with Contrastive Convolution,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+72fd97d21d6465d4bb407b6f8f3accd4419a2fb4,Automated Identification of Individual Great White Sharks from Unrestricted Fin Imagery,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
72450d7e5cbe79b05839c30a4f0284af5aa80053,Natural Facial Expression Recognition Using Dynamic and Static Schemes,University of the Basque Country,University of the Basque Country,"Euskal Herriko Unibertsitatea, Ibaeta Campusa, Paseo Arriola pasealekua, Ibaeta, Donostia/San Sebastián, Donostialdea, Gipuzkoa, Euskadi, 20008, España",43.30927695,-2.01066785,edu,
+72b4b8f4a9f25cac5686231b44a2220945fd2ff6,Face Verification Using Modeled Eigenspectrum,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
725c3605c2d26d113637097358cd4c08c19ff9e1,Deep Reasoning with Knowledge Graph for Social Relationship Understanding,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+72dd9ecc3a1f32d53b4aeb03ea3db14236fbcb27,Let the Shape Speak - Discriminative Face Alignment using Conjugate Priors,Institute of Systems and Robotics,Institute of Systems and Robotics,"Institut für Robotik und Kognitive Systeme, 160, Ratzeburger Allee, Strecknitz, Sankt Jürgen, Strecknitz, Lübeck, Schleswig-Holstein, 23562, Deutschland",53.83383710,10.70359390,edu,
+72dd9ecc3a1f32d53b4aeb03ea3db14236fbcb27,Let the Shape Speak - Discriminative Face Alignment using Conjugate Priors,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
+72e14386d0ef1aa09c52e07086fc310c440db16f,Gait Analysis of Gender and Age Using a Large-Scale Multi-view Gait Database,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+72e9acdd64e71fc2084acaf177aafaa2e075bd8c,The 2017 Hands in the Million Challenge on 3D Hand Pose Estimation,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
445461a34adc4bcdccac2e3c374f5921c93750f8,Emotional Expression Classification Using Time-Series Kernels,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
445461a34adc4bcdccac2e3c374f5921c93750f8,Emotional Expression Classification Using Time-Series Kernels,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+446fbff6a2a7c9989b0a0465f960e236d9a5e886,Context Encoders: Feature Learning by Inpainting,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+44e6ce12b857aeade03a6e5d1b7fb81202c39489,VoxCeleb2: Deep Speaker Recognition,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+44508e337a90223e935485d87d6fda15aaddd77a,Text detection and recognition in natural scene images,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
443acd268126c777bc7194e185bec0984c3d1ae7,Retrieving relative soft biometrics for semantic identification,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+44054c64ae7ee16a8a8348bb57345aae95a8ddae,Social Orienting and Attention Is Influenced by the Presence of Competing Nonsocial Information in Adolescents with Autism,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+44054c64ae7ee16a8a8348bb57345aae95a8ddae,Social Orienting and Attention Is Influenced by the Presence of Competing Nonsocial Information in Adolescents with Autism,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+44ae568a8cafbd4f4d495bf612bd6bb5c5116425,Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+449b87347fe7f9c3f17e969fab1617fbfd9ccb1b,Flat vs. Expressive Storytelling: Young Children’s Learning and Retention of a Social Robot’s Narrative,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+449b87347fe7f9c3f17e969fab1617fbfd9ccb1b,Flat vs. Expressive Storytelling: Young Children’s Learning and Retention of a Social Robot’s Narrative,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+449b87347fe7f9c3f17e969fab1617fbfd9ccb1b,Flat vs. Expressive Storytelling: Young Children’s Learning and Retention of a Social Robot’s Narrative,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
44f23600671473c3ddb65a308ca97657bc92e527,Convolutional Two-Stream Network Fusion for Video Action Recognition,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
44f23600671473c3ddb65a308ca97657bc92e527,Convolutional Two-Stream Network Fusion for Video Action Recognition,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
44f23600671473c3ddb65a308ca97657bc92e527,Convolutional Two-Stream Network Fusion for Video Action Recognition,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+442cf9b24661c9ea5c2a1dcabd4a5b8af1cd89da,Beyond One-hot Encoding: lower dimensional target embedding,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+44fbbd3def64d52c956277628a89aba77b24686b,Context Modulates Congruency Effects in Selective Attention to Social Cues,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+44fbbd3def64d52c956277628a89aba77b24686b,Context Modulates Congruency Effects in Selective Attention to Social Cues,Teesside University,Teesside University,"Teesside University, Southfield Road, Southfield, Linthorpe, Middlesbrough, North East England, England, TS1 3BZ, UK",54.57036950,-1.23509662,edu,
4467a1ae8ddf0bc0e970c18a0cdd67eb83c8fd6f,Learning features from Improved Dense Trajectories using deep convolutional networks for Human Activity Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
4467a1ae8ddf0bc0e970c18a0cdd67eb83c8fd6f,Learning features from Improved Dense Trajectories using deep convolutional networks for Human Activity Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+44bfa5311f0921664e9036f63cadd71049a35f35,Faster R-CNN-Based Glomerular Detection in Multistained Human Whole Slide Images,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+44bfa5311f0921664e9036f63cadd71049a35f35,Faster R-CNN-Based Glomerular Detection in Multistained Human Whole Slide Images,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+446f003afd16aa932aa87c73543348f62eba0e67,Suspect identification based on descriptive facial attributes,"Noblis, Falls Church, VA, U.S.A.","Noblis, Falls Church, VA, U.S.A.","2002 Edmund Halley Dr, Reston, VA 20191, USA",38.95187000,-77.36325900,company,
+446f003afd16aa932aa87c73543348f62eba0e67,Suspect identification based on descriptive facial attributes,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
+446f003afd16aa932aa87c73543348f62eba0e67,Suspect identification based on descriptive facial attributes,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+448c24fbe400ac164f3b97bce3cefc1577f91cca,Incremental sparse Bayesian ordinal regression,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+4469d0d0ac2f6f0221dc865b132958df33faa95e,Region-Based Interactive Ranking Optimization for Person Re-identification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+4469d0d0ac2f6f0221dc865b132958df33faa95e,Region-Based Interactive Ranking Optimization for Person Re-identification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
44f48a4b1ef94a9104d063e53bf88a69ff0f55f3,Automatically Building Face Datasets of New Domains from Weakly Labeled Data with Pretrained Models,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+44482010dbd63fba4f7457cbdb7cf61e44c78617,Efficient activity detection with max-subgraph search,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+44ec89df8d9f42e323ea90599f23ae58e3a8925a,Recognizing human actions by attributes,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
44aeda8493ad0d44ca1304756cc0126a2720f07b,Face Alive Icons,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4417258e4fe9e60d044a72197cb67471272991a5,Encoding Cortical Surface by Spherical Harmonics,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+4417258e4fe9e60d044a72197cb67471272991a5,Encoding Cortical Surface by Spherical Harmonics,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+44bf7e376bf6d0a64134de99ac92df11546c055d,Perception driven 3D facial expression analysis based on reverse correlation and normal component,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
44d23df380af207f5ac5b41459c722c87283e1eb,Human Attribute Recognition by Deep Hierarchical Contexts,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+44484d2866f222bbb9b6b0870890f9eea1ffb2d0,Human Reidentification with Transferred Metric Learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
44c9b5c55ca27a4313daf3760a3f24a440ce17ad,Revisiting hand-crafted feature for action recognition: a set of improved dense trajectories,Hiroshima University,Hiroshima University,"Hiroshima University 広島大学 東広島キャンパス, 出会いの道 Deai-no-michi Str., 西条下見, 東広島市, 広島県, 中国地方, 739-0047, 日本",34.40197660,132.71231950,edu,
44c9b5c55ca27a4313daf3760a3f24a440ce17ad,Revisiting hand-crafted feature for action recognition: a set of improved dense trajectories,Hiroshima University,Hiroshima University,"Hiroshima University 広島大学 東広島キャンパス, 出会いの道 Deai-no-michi Str., 西条下見, 東広島市, 広島県, 中国地方, 739-0047, 日本",34.40197660,132.71231950,edu,
+44ce0051d9482d96169ff5564085fe9867eb3193,Differential activation of the amygdala and the 'social brain' during fearful face-processing in Asperger Syndrome.,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+44ce0051d9482d96169ff5564085fe9867eb3193,Differential activation of the amygdala and the 'social brain' during fearful face-processing in Asperger Syndrome.,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
44fbbaea6271e47ace47c27701ed05e15da8f7cf,Pupil Mimicry Correlates With Trust in In-Group Partners With Dilating Pupils.,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+4407cde7ab8fc38ccb22f2799ab6f0ff7ab65283,Face Verification Using Error Correcting Output Codes,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+4459593cf12181988b8cec7e43f834f6831826cc,Mid-level Elements for Object Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
441bf5f7fe7d1a3939d8b200eca9b4bb619449a9,Head pose estimation in the wild using approximate view manifolds,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
441bf5f7fe7d1a3939d8b200eca9b4bb619449a9,Head pose estimation in the wild using approximate view manifolds,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
449808b7aa9ee6b13ad1a21d9f058efaa400639a,Recovering 3D facial shape via coupled 2D/3D space learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
449808b7aa9ee6b13ad1a21d9f058efaa400639a,Recovering 3D facial shape via coupled 2D/3D space learning,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+44787df6079918c6c4bf3dc871e2cad5a62c0e58,Super-Resolved Faces for Improved Face Recognition from Surveillance Video,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+44f18ef0800e276617e458bc21502947f35a7f94,EgoCap: egocentric marker-less motion capture with two fisheye cameras,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+44f18ef0800e276617e458bc21502947f35a7f94,EgoCap: egocentric marker-less motion capture with two fisheye cameras,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
2a65d7d5336b377b7f5a98855767dd48fa516c0f,Fast Supervised LDA for Discovering Micro-Events in Large-Scale Video Datasets,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
2af2b74c3462ccff3a6881ff7cf4f321b3242fa9,"Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues",Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
2af2b74c3462ccff3a6881ff7cf4f321b3242fa9,"Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues",City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
2af2b74c3462ccff3a6881ff7cf4f321b3242fa9,"Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues",Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
2af2b74c3462ccff3a6881ff7cf4f321b3242fa9,"Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues",Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+2a7e02ebdb7622815dbce8cf227189e2c92d026c,Zero-Shot Object Detection by Hybrid Region Embedding,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+2a7e02ebdb7622815dbce8cf227189e2c92d026c,Zero-Shot Object Detection by Hybrid Region Embedding,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
+2ad9e4596f38d58019a6f8073f238803f52a2773,Data-Driven 3D Primitives for Single Image Understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2a77e3221d0512aa5674cf6f9041c1ce81fc07f0,An Automatic Hybrid Segmentation Approach for Aligned Face Portrait Images,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+2aad85de05e8b9137558926678c94442371d37ec,Head Pose Estimation Using Sparse Representation,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+2a4117849c88d4728c33b1becaa9fb6ed7030725,Memory Bounded Deep Convolutional Networks,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+2a4117849c88d4728c33b1becaa9fb6ed7030725,Memory Bounded Deep Convolutional Networks,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+2ab8956fef9526741c1e68c94d9a9da74a87960c,Learning to Disambiguate by Asking Discriminative Questions,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2ab8956fef9526741c1e68c94d9a9da74a87960c,Learning to Disambiguate by Asking Discriminative Questions,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
2af620e17d0ed67d9ccbca624250989ce372e255,Meta-class features for large-scale object categorization on a budget,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
2a35d20b2c0a045ea84723f328321c18be6f555c,Boost Picking: A Universal Method on Converting Supervised Classification to Semi-supervised Classification,Beijing Institute of Technology,Beijing Institute of Technology University,"北京理工大学, 5, 中关村南大街, 中关村, 稻香园南社区, 海淀区, 北京市, 100872, 中国",39.95866520,116.30971281,edu,
2a35d20b2c0a045ea84723f328321c18be6f555c,Boost Picking: A Universal Method on Converting Supervised Classification to Semi-supervised Classification,Beijing Institute of Technology,Beijing Institute of Technology University,"北京理工大学, 5, 中关村南大街, 中关村, 稻香园南社区, 海淀区, 北京市, 100872, 中国",39.95866520,116.30971281,edu,
2a35d20b2c0a045ea84723f328321c18be6f555c,Boost Picking: A Universal Method on Converting Supervised Classification to Semi-supervised Classification,Beijing Institute of Technology,Beijing Institute of Technology University,"北京理工大学, 5, 中关村南大街, 中关村, 稻香园南社区, 海淀区, 北京市, 100872, 中国",39.95866520,116.30971281,edu,
2a9b398d358cf04dc608a298d36d305659e8f607,Facial action unit recognition with sparse representation,University of Denver,University of Denver,"University of Denver, Driscoll Bridge, Denver, Denver County, Colorado, 80208, USA",39.67665410,-104.96220300,edu,
2a9b398d358cf04dc608a298d36d305659e8f607,Facial action unit recognition with sparse representation,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+2af680736f32ae37d579a8b5656eec1c6b158dec,Biologically Significant Facial Landmarks: How Significant Are They for Gender Classification?,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+2a7b1257ec819688b46272024855c1858e031db6,Minimum Spectral Connectivity Projection Pursuit for Unsupervised Classification,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
+2a7b1257ec819688b46272024855c1858e031db6,Minimum Spectral Connectivity Projection Pursuit for Unsupervised Classification,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
+2a7b1257ec819688b46272024855c1858e031db6,Minimum Spectral Connectivity Projection Pursuit for Unsupervised Classification,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
+2ad7100498f3e4d00ec4424099b90fddb659e972,Another probabilistic method proposed to distinguish between fixations and saccades are Kalman filters,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+2ad7100498f3e4d00ec4424099b90fddb659e972,Another probabilistic method proposed to distinguish between fixations and saccades are Kalman filters,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
2ac21d663c25d11cda48381fb204a37a47d2a574,Interpreting Hand-Over-Face Gestures,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+2a73b610bd8d670f3b57debcbad7930db80f40e1,Stacking With Auxiliary Features: Improved Ensembling for Natural Language and Vision,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
2a4153655ad1169d482e22c468d67f3bc2c49f12,Face Alignment Across Large Poses: A 3D Solution,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
2a4153655ad1169d482e22c468d67f3bc2c49f12,Face Alignment Across Large Poses: A 3D Solution,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+2a869bc7c1488023c6e791e9c9071badfbad749d,NUS-WIDE: a real-world web image database from National University of Singapore,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+2a869bc7c1488023c6e791e9c9071badfbad749d,NUS-WIDE: a real-world web image database from National University of Singapore,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+2a3768ac4f6b3bfbcce4001c0c2fd35cfcc7679d,Face Recognition with Variation in Pose Angle Using Face Graphs,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
2aa2b312da1554a7f3e48f71f2fce7ade6d5bf40,Estimating Sheep Pain Level Using Facial Action Unit Detection,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+2af9ee8ee3ab4a89ae0098a1f9caa1aa9dad4e8a,2D and 3D Pose Recovery from a Single Uncalibrated Video - A View and Activity Independent Framework,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
+2a4fc35acaf09517e9c63821cadd428a84832416,Learning object class detectors from weakly annotated video,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+2a5823a387e248c4e7312d49cfbb02a25519251a,Weakly-supervised Deep Convolutional Neural Network Learning for Facial Action Unit Intensity Estimation,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+2a5823a387e248c4e7312d49cfbb02a25519251a,Weakly-supervised Deep Convolutional Neural Network Learning for Facial Action Unit Intensity Estimation,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
2a3e19d7c54cba3805115497c69069dd5a91da65,Looking at Hands in Autonomous Vehicles: A ConvNet Approach using Part Affinity Fields,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+2a31b4bf2a294b6e67956a6cd5ed6d875af548e0,Learning Affinity via Spatial Propagation Networks,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
2af19b5ff2ca428fa42ef4b85ddbb576b5d9a5cc,Multi-Region Probabilistic Histograms for Robust and Scalable Identity Inference,"CSIRO, Australia","NICTA, PO Box 6020, St Lucia, QLD 4067, Australia","Research Way, Clayton VIC 3168, Australia",-37.90627370,145.13194490,edu,f.k.a. NICTA
2af19b5ff2ca428fa42ef4b85ddbb576b5d9a5cc,Multi-Region Probabilistic Histograms for Robust and Scalable Identity Inference,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+2afde5e414aa94e20e2b30a5aa277ac36ca41d6a,Optimizing kd-trees for scalable visual descriptor indexing,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
2a14b6d9f688714dc60876816c4b7cf763c029a9,Combining multiple sources of knowledge in deep CNNs for action recognition,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+2a31169e3a0f87987537220b743bbf6e79c440e5,Multi-view Feature Fusion Network for Vehicle Re- Identification,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+2a8d0125c8d27699ccd75c76bda774e065060709,A translational neuroscience framework for the development of socioemotional functioning in health and psychopathology.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+2a92b610d2eed67b934ef2075264e243e6e1ea91,Learning Multi-Modal Navigation for Unmanned Ground Vehicles,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2a92b610d2eed67b934ef2075264e243e6e1ea91,Learning Multi-Modal Navigation for Unmanned Ground Vehicles,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2a92b610d2eed67b934ef2075264e243e6e1ea91,Learning Multi-Modal Navigation for Unmanned Ground Vehicles,University at Buffalo,State University of New York at Buffalo,"Buffalo, NY 14260, USA",43.00080930,-78.78896970,edu,
2a88541448be2eb1b953ac2c0c54da240b47dd8a,Discrete Graph Hashing,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
2a88541448be2eb1b953ac2c0c54da240b47dd8a,Discrete Graph Hashing,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
2a5903bdb3fdfb4d51f70b77f16852df3b8e5f83,The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
2a5903bdb3fdfb4d51f70b77f16852df3b8e5f83,The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+2a051c1f2787690fa9fa916fd548b62ce571f778,Dense CNN Learning with Equivalent Mappings,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+2a75f34663a60ab1b04a0049ed1d14335129e908,Web-based database for facial expression analysis,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
2a171f8d14b6b8735001a11c217af9587d095848,Learning Social Relation Traits from Face Images,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2a0cec7f0f8b63f182ea0c52cb935580acabafcc,Uous and Discrete Addressing Schemes,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+2a4bbee0b4cf52d5aadbbc662164f7efba89566c,Pedestrian Attribute Recognition At Far Distance,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2a547bf34d185f80a0d476148721b6f05c276256,"Detection, Description and Tracking of Ants in Video Sequences",Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
2a0623ae989f2236f5e1fe3db25ab708f5d02955,3D Face Modelling for 2D+3D Face Recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
2a0623ae989f2236f5e1fe3db25ab708f5d02955,3D Face Modelling for 2D+3D Face Recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
2afdda6fb85732d830cea242c1ff84497cd5f3cb,Face image retrieval by using Haar features,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
2afdda6fb85732d830cea242c1ff84497cd5f3cb,Face image retrieval by using Haar features,Tamkang University,Tamkang University,"淡江大學, 151, 英專路, 中興里, 鬼仔坑, 淡水區, 新北市, 25137, 臺灣",25.17500615,121.45076751,edu,
+2a06b31e778bed978055cec7596bdf2690d13b49,Deformable part models revisited: A performance evaluation for object category pose estimation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+2aa531b4aaf005db13ff93cc1bea7602d7fe2efb,Lidar-based Vehicle Localization in an Autonomous Valet Parking Scenario,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+2a2fd2538e19652721bc664f92056fbd08c604fd,Surveillance Video Analysis with External Knowledge and Internal Constraints,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2a2fd2538e19652721bc664f92056fbd08c604fd,Surveillance Video Analysis with External Knowledge and Internal Constraints,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2a2fd2538e19652721bc664f92056fbd08c604fd,Surveillance Video Analysis with External Knowledge and Internal Constraints,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2a2fd2538e19652721bc664f92056fbd08c604fd,Surveillance Video Analysis with External Knowledge and Internal Constraints,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2aa06417fd361832df384cf7c003ed1d3c5ee8df,Learning people detection models from few training samples,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
2ab034e1f54c37bfc8ae93f7320160748310dc73,Siamese Capsule Networks,University of Liverpool,University of Liverpool,"Victoria Building, Brownlow Hill, Knowledge Quarter, Liverpool, North West England, England, L3, UK",53.40617900,-2.96670819,edu,
+2a3991ae72740f3661f98d2ad58a0595bbcd07ad,Human Re-identification by Matching Compositional Template with Cluster Sampling,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+2a3991ae72740f3661f98d2ad58a0595bbcd07ad,Human Re-identification by Matching Compositional Template with Cluster Sampling,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+2fd96238a7e372146cdf6c2338edc932031dd1f0,Face Aging with Contextual Generative Adversarial Nets,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+2fd96238a7e372146cdf6c2338edc932031dd1f0,Face Aging with Contextual Generative Adversarial Nets,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
2ff9ffedfc59422a8c7dac418a02d1415eec92f1,Face Verification Using Boosted Cross-Image Features,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
2ff9ffedfc59422a8c7dac418a02d1415eec92f1,Face Verification Using Boosted Cross-Image Features,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
2ff9ffedfc59422a8c7dac418a02d1415eec92f1,Face Verification Using Boosted Cross-Image Features,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+2fad06ed34169a5b1f736112364c58140577a6b4,Pedestrian Color Naming via Convolutional Neural Network,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2f20cf49eb6a0818313c29d64eb6d30ddfb8d747,Ranking Preserving Hashing for Fast Similarity Search,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+2f41c7ba65fa3d2819469fba450754266c98740e,Stixels Motion Estimation without Optical Flow Computation,Katholieke Universiteit Leuven,Katholieke Universiteit Leuven,"Laboratorium voor Bos, natuur en landschap, 102, Vital Decosterstraat, Sint-Maartensdal, Leuven, Vlaams-Brabant, Vlaanderen, 3000, België / Belgique / Belgien",50.88306860,4.70195030,edu,
2f53b97f0de2194d588bc7fb920b89cd7bcf7663,Facial Expression Recognition Using Sparse Gaussian Conditional Random Field,Shiraz University,Shiraz University,"دانشگاه شیراز, میدان ارم, محدوده شهرداری منطقه یک - شهرداری شیراز, شیراز, بخش مرکزی شهرستان شیراز, شهرستان شیراز, استان فارس, 71348-34689, ایران",29.63854740,52.52457060,edu,
2f53b97f0de2194d588bc7fb920b89cd7bcf7663,Facial Expression Recognition Using Sparse Gaussian Conditional Random Field,Shiraz University,Shiraz University,"دانشگاه شیراز, میدان ارم, محدوده شهرداری منطقه یک - شهرداری شیراز, شیراز, بخش مرکزی شهرستان شیراز, شهرستان شیراز, استان فارس, 71348-34689, ایران",29.63854740,52.52457060,edu,
+2f21c68ff9fbd82a3241f79f985ec7e1dcdac41a,Semantic Single-Image Dehazing,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
2f16baddac6af536451b3216b02d3480fc361ef4,Web-scale training for face identification,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
2f2aa67c5d6dbfaf218c104184a8c807e8b29286,Video analytics for surveillance camera networks,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
-2fc43c2c3f7ad1ca7a1ce32c5a9a98432725fb9a,Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
-2fc43c2c3f7ad1ca7a1ce32c5a9a98432725fb9a,Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
-2fc43c2c3f7ad1ca7a1ce32c5a9a98432725fb9a,Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+2fb71cb0f08102fe8c9ba5929c1dc96d87737039,Supervised and Unsupervised Transfer Learning for Question Answering,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+2f72cee2b9ae3d4271bda9f9bda1f11ad84ef616,End-to-End Detection and Re-identification Integrated Net for Person Search,Chongqing University,Chongqing University,"重庆工商大学, 19, 翠林路, 重庆市, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400067, 中国",29.50841740,106.57858552,edu,
+2f72cee2b9ae3d4271bda9f9bda1f11ad84ef616,End-to-End Detection and Re-identification Integrated Net for Person Search,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+2fc43c2c3f7ad1ca7a1ce32c5a9a98432725fb9a,Hierarchical Video Generation From Orthogonal Information: Optical Flow and Texture,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+2fc43c2c3f7ad1ca7a1ce32c5a9a98432725fb9a,Hierarchical Video Generation From Orthogonal Information: Optical Flow and Texture,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+2fc43c2c3f7ad1ca7a1ce32c5a9a98432725fb9a,Hierarchical Video Generation From Orthogonal Information: Optical Flow and Texture,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+2f951dcba9539270ca3feb9becc4539feb89e80a,A Generalized Probabilistic Framework for Compact Codebook Creation,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+2f951dcba9539270ca3feb9becc4539feb89e80a,A Generalized Probabilistic Framework for Compact Codebook Creation,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
+2f951dcba9539270ca3feb9becc4539feb89e80a,A Generalized Probabilistic Framework for Compact Codebook Creation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+2f1b1cbdc1ea04be6f8c3ff08628b5eba9f01771,Boosted deformable model for human body alignment,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+2fa1037496dbcc04b705fcc4e9ed58cdc85df46e,Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+2fa1037496dbcc04b705fcc4e9ed58cdc85df46e,Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+2fa941ed0f9546796499782e285a14cabf0186de,ClassMap: Efficient Multiclass Recognition via Embeddings,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+2fa941ed0f9546796499782e285a14cabf0186de,ClassMap: Efficient Multiclass Recognition via Embeddings,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+2fa04fc0bcbc92886902a62dbf538c490084efa4,Visual field bias in hearing and deaf adults during judgments of facial expression and identity,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+2fa04fc0bcbc92886902a62dbf538c490084efa4,Visual field bias in hearing and deaf adults during judgments of facial expression and identity,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+2fa04fc0bcbc92886902a62dbf538c490084efa4,Visual field bias in hearing and deaf adults during judgments of facial expression and identity,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+2f52b6cd87e6d72a11168fef0865743dde9ea0ae,Adversarial Attacks Beyond the Image Space,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+2f52b6cd87e6d72a11168fef0865743dde9ea0ae,Adversarial Attacks Beyond the Image Space,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+2f52b6cd87e6d72a11168fef0865743dde9ea0ae,Adversarial Attacks Beyond the Image Space,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+2fb1ecd1451dc0c016cfe4cc43cb9620a766f1b2,Maximizing AUC with Deep Learning for Classification of Imbalanced Mammogram Datasets,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+2f5aa539fb27962aa4ba5b264ee503e6921bf531,Transfer re-identification: From person to set-based verification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+2f5aa539fb27962aa4ba5b264ee503e6921bf531,Transfer re-identification: From person to set-based verification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
2f2406551c693d616a840719ae1e6ea448e2f5d3,Age estimation from face images: Human vs. machine performance,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+2fbe4ffef775bb9c2cea535a07ecd48ef30adcaf,Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+2fbe4ffef775bb9c2cea535a07ecd48ef30adcaf,Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+2fbe4ffef775bb9c2cea535a07ecd48ef30adcaf,Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+2fa2a186dfae16958bb3bc8752c57a749ccb4f41,Robust Depth Image Acquisition Using Modulated Pattern Projection and Probabilistic Graphical Models,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
2f7fc778e3dec2300b4081ba2a1e52f669094fcd,Action Representation Using Classifier Decision Boundaries,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
2f0e5a4b0ef89dd2cf55a4ef65b5c78101c8bfa1,Facial Expression Recognition Using a Hybrid CNN-SIFT Aggregator,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
2f5e057e35a97278a9d824545d7196c301072ebf,Capturing Long-Tail Distributions of Object Subcategories,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
2f5e057e35a97278a9d824545d7196c301072ebf,Capturing Long-Tail Distributions of Object Subcategories,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
2f04ba0f74df046b0080ca78e56898bd4847898b,Aggregate channel features for multi-view face detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+43694e7d5861a8bc8aa5884dba3efe2d387511c6,Supplementary Material: Annotating Object Instances with a Polygon-RNN,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+4300c7773a130b4995f60ba5ed920dd1782a3527,Support Vector Machines in face recognition with occlusions,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
43010792bf5cdb536a95fba16b8841c534ded316,Towards general motion-based face recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+4320b0b7e65607e96326990675ac15880dc08b89,A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
438c4b320b9a94a939af21061b4502f4a86960e3,Reconstruction-Based Disentanglement for Pose-Invariant Face Recognition,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+43f0e2207d628deba1f91c810c38f33a1978cd58,Learning with Marginalized Corrupted Features,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+43f0e2207d628deba1f91c810c38f33a1978cd58,Learning with Marginalized Corrupted Features,Washington University,Washington University,"Dero, Wallace Drive, St. Louis County, Missouri, MO 63130, USA",38.64804450,-90.30996670,edu,
+439b6a5b91f1c5a751846bed7dd27c698a7ee2c4,Depth Information Guided Crowd Counting for Complex Crowd Scenes,Zhengzhou University,Zhengzhou University,"科学大道, 中原区 (Zhongyuan), 郑州市 / Zhengzhou, 河南省, 450001, 中国",34.80881680,113.53526640,edu,
+439b6a5b91f1c5a751846bed7dd27c698a7ee2c4,Depth Information Guided Crowd Counting for Complex Crowd Scenes,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
43e99b76ca8e31765d4571d609679a689afdc99e,Learning Dense Facial Correspondences in Unconstrained Images,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+431f013143de3159c0c0033fee2fb4840d213b6f,Preferential attention to animals and people is independent of the amygdala.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+431f013143de3159c0c0033fee2fb4840d213b6f,Preferential attention to animals and people is independent of the amygdala.,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
+431f013143de3159c0c0033fee2fb4840d213b6f,Preferential attention to animals and people is independent of the amygdala.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+431f013143de3159c0c0033fee2fb4840d213b6f,Preferential attention to animals and people is independent of the amygdala.,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
4377b03bbee1f2cf99950019a8d4111f8de9c34a,Selective Encoding for Recognizing Unreliably Localized Faces,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
43a03cbe8b704f31046a5aba05153eb3d6de4142,Towards Robust Face Recognition from Video,Oak Ridge National Laboratory,Oak Ridge National Laboratory,"Oak Ridge National Laboratory, Oak Ridge, Roane County, Tennessee, USA",35.93006535,-84.31240032,edu,
4307e8f33f9e6c07c8fc2aeafc30b22836649d8c,Supervised Earth Mover's Distance Learning and Its Computer Vision Applications,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
435642641312364e45f4989fac0901b205c49d53,Face Model Compression by Distilling Knowledge from Neurons,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
435642641312364e45f4989fac0901b205c49d53,Face Model Compression by Distilling Knowledge from Neurons,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
435642641312364e45f4989fac0901b205c49d53,Face Model Compression by Distilling Knowledge from Neurons,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+435bc494d3606d1137fb8b70d481bd6497f15090,Object Recognition by Integrated Information Using Web Images,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+435bc494d3606d1137fb8b70d481bd6497f15090,Object Recognition by Integrated Information Using Web Images,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+435bc494d3606d1137fb8b70d481bd6497f15090,Object Recognition by Integrated Information Using Web Images,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+439f3a865dfb7b42c600a095a6fcee1c1f4768ad,Applying deep learning to classify pornographic images and videos,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
+438f1841a0b09c96759dc870d663d837d07388e3,Emotional Context Influences Micro-Expression Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+438f1841a0b09c96759dc870d663d837d07388e3,Emotional Context Influences Micro-Expression Recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+4335805938a35a47cf86c985e993f73060405679,Automatic red-eye effect removal using combined intensity and colour information,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+4335805938a35a47cf86c985e993f73060405679,Automatic red-eye effect removal using combined intensity and colour information,Myongji University,Myongji University,"명지대, 금학로, 역북동, 처인구, 용인시, 경기, 17144, 대한민국",37.23810230,127.19034310,edu,
+435514bc2103deb604d762095d8faf77be544b9a,Feature Localisation in Three-Dimensional Faces,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+436b2f5bf23bc0bd80680ee2ed279cbd55939b86,Visual Saliency Maps Can Apply to Facial Expression Recognition,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+436b2f5bf23bc0bd80680ee2ed279cbd55939b86,Visual Saliency Maps Can Apply to Facial Expression Recognition,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+43e5817c18ec570d614669e3940d82791d285a10,Learning Class Prototypes via Structure Alignment for Zero-Shot Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+43e5817c18ec570d614669e3940d82791d285a10,Learning Class Prototypes via Structure Alignment for Zero-Shot Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+43f37a725dd58015bdca53937518042d81ca1078,Probabilistic fusion of gait features for biometric verification,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+43f37a725dd58015bdca53937518042d81ca1078,Probabilistic fusion of gait features for biometric verification,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+43f37a725dd58015bdca53937518042d81ca1078,Probabilistic fusion of gait features for biometric verification,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
434d6726229c0f556841fad20391c18316806f73,Detecting Visual Relationships with Deep Relational Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+431e80aeee80a74f41d8af1336016340cd8e4848,Mapping Brain-Behavior Partial Correlations: Application to Autism,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+431e80aeee80a74f41d8af1336016340cd8e4848,Mapping Brain-Behavior Partial Correlations: Application to Autism,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+43b3dc931cd43a490de3206fd041e118e3651d8a,Learning Hierarchical Semantic Image Manipulation through Structured Representations,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
435dc062d565ce87c6c20a5f49430eb9a4b573c4,Lighting Condition Adaptation for Perceived Age Estimation,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
433a6d6d2a3ed8a6502982dccc992f91d665b9b3,Transferring Landmark Annotations for Cross-Dataset Face Alignment,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
433a6d6d2a3ed8a6502982dccc992f91d665b9b3,Transferring Landmark Annotations for Cross-Dataset Face Alignment,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
438e7999c937b94f0f6384dbeaa3febff6d283b6,"Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild",University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
438e7999c937b94f0f6384dbeaa3febff6d283b6,"Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild",Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
43776d1bfa531e66d5e9826ff5529345b792def7,Automatic Critical Event Extraction and Semantic Interpretation by Looking-Inside,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+4308bd8c28e37e2ed9a3fcfe74d5436cce34b410,Scalable Person Re-identification: A Benchmark,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+4308bd8c28e37e2ed9a3fcfe74d5436cce34b410,Scalable Person Re-identification: A Benchmark,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
432d8cba544bf7b09b0455561fea098177a85db1,Towards a Neural Statistician,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
432d8cba544bf7b09b0455561fea098177a85db1,Towards a Neural Statistician,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+437edf4b1e8939a3833d8eb814447d9132d7d758,Image matching with distinctive visual vocabulary,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4348c8706b92a9bd90dbbd735f824ec79e96dd71,Pitfalls in Designing Zero-Effort Deauthentication: Opportunistic Human Observation Attacks,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+43bb4b073f7b2b9b626c7f3263cc61932271ab74,User-guided Hierarchical Attention Network for Multi-modal Social Image Popularity Prediction,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+43bb4b073f7b2b9b626c7f3263cc61932271ab74,User-guided Hierarchical Attention Network for Multi-modal Social Image Popularity Prediction,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+43bb4b073f7b2b9b626c7f3263cc61932271ab74,User-guided Hierarchical Attention Network for Multi-modal Social Image Popularity Prediction,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+43bb4b073f7b2b9b626c7f3263cc61932271ab74,User-guided Hierarchical Attention Network for Multi-modal Social Image Popularity Prediction,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+432d5eca44ff558642491f3bb7f44f500993fd38,Accurate face alignment and adaptive patch selection for heart rate estimation from videos under realistic scenarios,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
439647914236431c858535a2354988dde042ef4d,Face illumination normalization on large and small scale features,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
439647914236431c858535a2354988dde042ef4d,Face illumination normalization on large and small scale features,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
439647914236431c858535a2354988dde042ef4d,Face illumination normalization on large and small scale features,Hong Kong Baptist University,Hong Kong Baptist University,"香港浸會大學 Hong Kong Baptist University, 安明街 On Ming Street, 石門 Shek Mun, 石古壟 Shek Kwu Lung, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1132, 中国",22.38742010,114.20822220,edu,
+43d36a22629114e14a0952675e15c9c76f1f024c,Deep Lambertian Networks,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
439ca6ded75dffa5ddea203dde5e621dc4a88c3e,Robust real-time performance-driven 3D face tracking,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
439ca6ded75dffa5ddea203dde5e621dc4a88c3e,Robust real-time performance-driven 3D face tracking,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
88e090ffc1f75eed720b5afb167523eb2e316f7f,Attribute-Based Transfer Learning for Object Categorization with Zero/One Training Example,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
8877e0b2dc3d2e8538c0cfee86b4e8657499a7c4,Automatic facial expression recognition for affective computing based on bag of distances,National Chung Cheng University,National Chung Cheng University,"國立中正大學, 168, 鳳凰大道, 民雄鄉, 嘉義縣, 62102, 臺灣",23.56306355,120.47510531,edu,
8877e0b2dc3d2e8538c0cfee86b4e8657499a7c4,Automatic facial expression recognition for affective computing based on bag of distances,National Taichung University of Science and Technology,National Taichung University of science and Technology,"臺中科大, 129, 三民路三段, 錦平里, 賴厝廍, 北區, 臺中市, 40401, 臺灣",24.15031065,120.68325501,edu,
+886fc74b943011ce5ce192ff98d6ea9dcac7ef11,Atypical scanpaths in schizophrenia: evidence of a trait- or state-dependent phenomenon?,University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
+886fc74b943011ce5ce192ff98d6ea9dcac7ef11,Atypical scanpaths in schizophrenia: evidence of a trait- or state-dependent phenomenon?,University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
+886fc74b943011ce5ce192ff98d6ea9dcac7ef11,Atypical scanpaths in schizophrenia: evidence of a trait- or state-dependent phenomenon?,University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
+88af2da57863b60ddd3776d61113b552e827d3b8,3 D Face Recognition by Sliding Complex Wavelet Structural Similarity Index on Detail Geometry Images ⋆,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
88f7a3d6f0521803ca59fde45601e94c3a34a403,Semantic Aware Video Transcription Using Random Forest Classifiers,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
8812aef6bdac056b00525f0642702ecf8d57790b,A Unified Features Approach to Human Face Image Analysis and Interpretation,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+88f8519f442826f9b7b2649c1cfcbc5c82160428,Gender Classification Based on Support Vector Machine with Automatic Confidence,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+887502ea2d8a335d8e72deb23fec2784df713b8d,Nonlinear Local Metric Learning for Person Re-identification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+887502ea2d8a335d8e72deb23fec2784df713b8d,Nonlinear Local Metric Learning for Person Re-identification,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
88e2574af83db7281c2064e5194c7d5dfa649846,A Robust Shape Reconstruction Method for Facial Feature Point Detection,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
88bef50410cea3c749c61ed68808fcff84840c37,Sparse representations of image gradient orientations for visual recognition and tracking,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
88bef50410cea3c749c61ed68808fcff84840c37,Sparse representations of image gradient orientations for visual recognition and tracking,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+88a0ff6b180703a2d90bc86b40520e35a08fe02c,The Normalized Distance Preserving Binary Codes and Distance Table,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+8856fbf333b2aba7b9f1f746e16a2b7f083ee5b8,Analyzing animal behavior via classifying each video frame using convolutional neural networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
8820d1d3fa73cde623662d92ecf2e3faf1e3f328,Continuous Video to Simple Signals for Swimming Stroke Detection with Convolutional Neural Networks,La Trobe University,La Trobe University,"La Trobe University, Keck Street, Flora Hill, Bendigo, City of Greater Bendigo, Loddon Mallee, Victoria, 3550, Australia",-36.77847540,144.29804700,edu,
8820d1d3fa73cde623662d92ecf2e3faf1e3f328,Continuous Video to Simple Signals for Swimming Stroke Detection with Convolutional Neural Networks,Australian Institute of Sport,Australian Institute of Sport,"Australian Institute of Sport, Glenn McGrath Street, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.24737535,149.10445427,edu,
8818b12aa0ff3bf0b20f9caa250395cbea0e8769,Fashion Conversation Data on Instagram_ICWSM 2017,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
8862a573a42bbaedd392e9e634c1ccbfd177a01d,Real-Time 3D Face Fitting and Texture Fusion on In-the-Wild Videos,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
8862a573a42bbaedd392e9e634c1ccbfd177a01d,Real-Time 3D Face Fitting and Texture Fusion on In-the-Wild Videos,Reutlingen University,Reutlingen University,"Campus Hohbuch, Campus Hochschule Reutlingen, Reutlingen, Landkreis Reutlingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72762, Deutschland",48.48187645,9.18682404,edu,
+88e30a988d4a496d61eb241d4cafe5cc88688ae6,Using attributes for word spotting and recognition in polytonic greek documents,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
+8824638e8077f62283d292804006ce94c92764bf,M2M-GAN: Many-to-Many Generative Adversarial Transfer Learning for Person Re-Identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+88cd4209db62a34d9cba0b9cbe9d45d1e57d21e5,Runtime Neural Pruning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+88cd4209db62a34d9cba0b9cbe9d45d1e57d21e5,Runtime Neural Pruning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+88cd4209db62a34d9cba0b9cbe9d45d1e57d21e5,Runtime Neural Pruning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+88cd4209db62a34d9cba0b9cbe9d45d1e57d21e5,Runtime Neural Pruning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
8895d6ae9f095a8413f663cc83f5b7634b3dc805,BEHL ET AL: INCREMENTAL TUBE CONSTRUCTION FOR HUMAN ACTION DETECTION 1 Incremental Tube Construction for Human Action Detection,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
8895d6ae9f095a8413f663cc83f5b7634b3dc805,BEHL ET AL: INCREMENTAL TUBE CONSTRUCTION FOR HUMAN ACTION DETECTION 1 Incremental Tube Construction for Human Action Detection,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+883767948f535ea2bf8a0c03047ca9064e1b078f,A Combination of Object Recognition and Localisation for an Autonomous Racecar,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+88bf14cd272fda73e5bc8fb48102a93149792e37,Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+88bf14cd272fda73e5bc8fb48102a93149792e37,Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
+8880af06d8497e9deda01e0a0eabacf9e1cf0490,Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+880760777e3671593ba50b7a17b0d30b655fc86d,"Visual Question Answering : Datasets , Methods , Challenges and Oppurtunities",Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
887745c282edf9af40d38425d5fdc9b3fe139c08,FAME: Face Association through Model Evolution,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
887745c282edf9af40d38425d5fdc9b3fe139c08,FAME: Face Association through Model Evolution,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+9f59d0a003558066d2ff4fc1c77f461b4d233663,Training Convolutional Networks with Noisy Labels,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+9f59d0a003558066d2ff4fc1c77f461b4d233663,Training Convolutional Networks with Noisy Labels,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+9f59d0a003558066d2ff4fc1c77f461b4d233663,Training Convolutional Networks with Noisy Labels,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+9f59d0a003558066d2ff4fc1c77f461b4d233663,Training Convolutional Networks with Noisy Labels,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+9fec253eb41438a9ab13bd5156a18c2c08ff610a,Yum-Me: A Personalized Nutrient-Based Meal Recommender System,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+9fec253eb41438a9ab13bd5156a18c2c08ff610a,Yum-Me: A Personalized Nutrient-Based Meal Recommender System,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+9fec253eb41438a9ab13bd5156a18c2c08ff610a,Yum-Me: A Personalized Nutrient-Based Meal Recommender System,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+9fec253eb41438a9ab13bd5156a18c2c08ff610a,Yum-Me: A Personalized Nutrient-Based Meal Recommender System,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+9fec253eb41438a9ab13bd5156a18c2c08ff610a,Yum-Me: A Personalized Nutrient-Based Meal Recommender System,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+9fec253eb41438a9ab13bd5156a18c2c08ff610a,Yum-Me: A Personalized Nutrient-Based Meal Recommender System,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+9fec253eb41438a9ab13bd5156a18c2c08ff610a,Yum-Me: A Personalized Nutrient-Based Meal Recommender System,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+9f949f6e40e604ef05ed690ad732a2f6625997b1,Understanding Everyday Hands in Action from RGB-D Images,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+9f949f6e40e604ef05ed690ad732a2f6625997b1,Understanding Everyday Hands in Action from RGB-D Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9f33fe98e70c049ddf932247a44b9c9af85cf9cb,Detection of Anchor Points for 3D Face Veri.cation,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+9f5ce56dd0900368ff6f0bc4a4055e6f4ceb0bc7,Beauty-in-averageness and its contextual modulations : A Bayesian statistical account,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+9f5ce56dd0900368ff6f0bc4a4055e6f4ceb0bc7,Beauty-in-averageness and its contextual modulations : A Bayesian statistical account,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
9f6d04ce617d24c8001a9a31f11a594bd6fe3510,Attentional bias towards angry faces in trait-reappraisal,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+9f0c6797560de7f23bd3b016c9c328787c4cebf9,Automating Generation of Low Precision Deep Learning Operators,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+9f0c6797560de7f23bd3b016c9c328787c4cebf9,Automating Generation of Low Precision Deep Learning Operators,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+9f0c6797560de7f23bd3b016c9c328787c4cebf9,Automating Generation of Low Precision Deep Learning Operators,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+9f0c6797560de7f23bd3b016c9c328787c4cebf9,Automating Generation of Low Precision Deep Learning Operators,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
9f499948121abb47b31ca904030243e924585d5f,Hierarchical Attention Network for Action Recognition in Videos,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
9f499948121abb47b31ca904030243e924585d5f,Hierarchical Attention Network for Action Recognition in Videos,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
9f499948121abb47b31ca904030243e924585d5f,Hierarchical Attention Network for Action Recognition in Videos,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+9f2d7b7f5d983cfc02dc3b06dadddc4902afdd83,Semi-supervised learning for scalable and robust visual search,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+9fb7a23910f6464902f1b653025f3aeaa20b90dd,CNN-Based cascaded multi-task learning of high-level prior and density estimation for crowd counting,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+9f61362052e7675b3053a9d1b682ad917ce0e3d1,Social relevance drives viewing behavior independent of low-level salience in rhesus macaques,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+9f61362052e7675b3053a9d1b682ad917ce0e3d1,Social relevance drives viewing behavior independent of low-level salience in rhesus macaques,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+9f61362052e7675b3053a9d1b682ad917ce0e3d1,Social relevance drives viewing behavior independent of low-level salience in rhesus macaques,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+9f61362052e7675b3053a9d1b682ad917ce0e3d1,Social relevance drives viewing behavior independent of low-level salience in rhesus macaques,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+9f6ca02ade848368a5e762cc3cf55a881c082faa,Motion Feature Network: Fixed Motion Filter for Action Recognition,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+9fb93b7c2bae866608f26c4254e5bd69cc5031d6,Fast Geometrically-Perturbed Adversarial Faces,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
9fc04a13eef99851136eadff52e98eb9caac919d,Rethinking the Camera Pipeline for Computer Vision,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
9fc04a13eef99851136eadff52e98eb9caac919d,Rethinking the Camera Pipeline for Computer Vision,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
9fc04a13eef99851136eadff52e98eb9caac919d,Rethinking the Camera Pipeline for Computer Vision,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
9f4078773c8ea3f37951bf617dbce1d4b3795839,Leveraging Inexpensive Supervision Signals for Visual Learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
9f4078773c8ea3f37951bf617dbce1d4b3795839,Leveraging Inexpensive Supervision Signals for Visual Learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9f829eb41c2ecb850fe20329e7da06eb369151f9,Deep Representation Learning with Target Coding,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+9f829eb41c2ecb850fe20329e7da06eb369151f9,Deep Representation Learning with Target Coding,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+9f829eb41c2ecb850fe20329e7da06eb369151f9,Deep Representation Learning with Target Coding,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+9f5a73e6282c8c1c569622ce9eb505be237c2971,Localizing Actions from Video Labels and Pseudo-Annotations,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+9f5a73e6282c8c1c569622ce9eb505be237c2971,Localizing Actions from Video Labels and Pseudo-Annotations,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
9f65319b8a33c8ec11da2f034731d928bf92e29d,Taking Roll: a Pipeline for Face Recognition,Louisiana State University,Louisiana State University,"LSU, Gourrier Avenue, Baton Rouge, East Baton Rouge Parish, Louisiana, 70803, USA",30.40550035,-91.18620474,edu,
+9f5383ec6ee5e810679e4a7e0a3f153f0ed3bb73,3D Shape and Pose Estimation of Face Images Using the Nonlinear Least-Squares Model,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+9f5383ec6ee5e810679e4a7e0a3f153f0ed3bb73,3D Shape and Pose Estimation of Face Images Using the Nonlinear Least-Squares Model,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+9fe55487c40983b1da71c073104cdc2d6f5cc7bf,"Hybrid Human-Machine Vision Systems: Image Annotation using Crowds, Experts and Machines",California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+9fa5d5b2cd6d625973d735e70d44824eb0118a33,Contour-Based Large Scale Image Retrieval,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+9fb31d0375552500bd494af20ab0c3109c9be3d2,Video Fill in the Blank with Merging LSTMs,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+9fbc0135e76b0fd972517e06e833593ecf6ac49a,Human emotions track changes in the acoustic environment.,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+9fbc0135e76b0fd972517e06e833593ecf6ac49a,Human emotions track changes in the acoustic environment.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+9f1b39e8d157b74181c666e85e5d55550d762409,Three-Stream Convolutional Networks for Video-based Person Re-Identification,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
+9fae24003bbedecdb617f9779215d79d06b90dd8,Where Are the Blobs: Counting by Localization with Point Supervision,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
9fdfe1695adac2380f99d3d5cb6879f0ac7f2bfd,Active Tracking and Cloning of Facial Expressions Using Spatio-Temporal Information,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
9fdfe1695adac2380f99d3d5cb6879f0ac7f2bfd,Active Tracking and Cloning of Facial Expressions Using Spatio-Temporal Information,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+6b011aa54aeabae8ac172a0cf0dd4333d1bfd327,Supervised algorithm selection for flow and other computer vision problems,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
6b3e360b80268fda4e37ff39b7f303e3684e8719,Face Recognition from Sketches Using Advanced Correlation Filters Using Hybrid Eigenanalysis for Face Synthesis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6bfb0f8dd1a2c0b44347f09006dc991b8a08559c,Multiview discriminative learning for age-invariant face recognition,Lomonosov Moscow State University,Lomonosov Moscow State University,"МГУ, улица Академика Хохлова, Московский государственный университет им. М. В. Ломоносова, район Раменки, Западный административный округ, Москва, ЦФО, 119234, РФ",55.70229715,37.53179777,edu,
+6bfb0f8dd1a2c0b44347f09006dc991b8a08559c,Multiview discriminative learning for age-invariant face recognition,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
+6bfb0f8dd1a2c0b44347f09006dc991b8a08559c,Multiview discriminative learning for age-invariant face recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+6bfb0f8dd1a2c0b44347f09006dc991b8a08559c,Multiview discriminative learning for age-invariant face recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+6b6866fbb4354e30ab34db9d6a8a07da4bf25777,Biometrics of Next Generation : An Overview,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+6b6866fbb4354e30ab34db9d6a8a07da4bf25777,Biometrics of Next Generation : An Overview,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+6b359aefefe6b6c511c41afb873820462f5f42cc,Multi-view Gait Based Biometric System,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+6b359aefefe6b6c511c41afb873820462f5f42cc,Multi-view Gait Based Biometric System,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+6b1f12995c88412607d8c36b3d5b0aa6a5cba7a3,Learning semantic attributes via a common latent space,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+6b9e8acef979c13fa9ecc8fe9b635b312fedbcbe,Multiple Structured-Instance Learning for Semantic Segmentation with Uncertain Training Data,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+6bda5819d9bc2e174902d839a12127a57fdb43f7,A Precise Eye Localization Method Based on Ratio Local Binary Pattern,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+6bdfd62ae9eb026dbc37f6f2db897fbee5cf8a5d,Randomised Manifold Forests for Principal Angle-Based Face Recognition,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+6bdfd62ae9eb026dbc37f6f2db897fbee5cf8a5d,Randomised Manifold Forests for Principal Angle-Based Face Recognition,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
6bca0d1f46b0f7546ad4846e89b6b842d538ee4e,Face Recognition from Surveillance - Quality Video,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+6b6afc9557dc0670bf2792bde4c4389ac52c707f,What Action Causes This? Towards Naive Physical Action-Effect Prediction,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+6b6afc9557dc0670bf2792bde4c4389ac52c707f,What Action Causes This? Towards Naive Physical Action-Effect Prediction,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
6b8d0569fffce5cc221560d459d6aa10c4db2f03,Interlinked Convolutional Neural Networks for Face Parsing,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+6b68e3388ddecfcb0671dee6fba9a895aaf3d4e3,Fusing Shape and Appearance Information for Object Category Detection,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+6b68e3388ddecfcb0671dee6fba9a895aaf3d4e3,Fusing Shape and Appearance Information for Object Category Detection,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
6bcee7dba5ed67b3f9926d2ae49f9a54dee64643,Assessment of Time Dependency in Face Recognition: An Initial Study,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+6bb51f431f348b2b3e1db859827e80f97a576c30,Irregular Convolutional Neural Networks,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+6b5f32d129f73bd1e2aa8323bf78cec3ed12c539,Facial Expression Recognition Based on 3D Dynamic Range Model Sequences,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
+6b5cf028b9fa3191119067f087b189d97017d31f,Online Invigilation: A Holistic Approach: Process for Automated Online Invigilation,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+6b5cf028b9fa3191119067f087b189d97017d31f,Online Invigilation: A Holistic Approach: Process for Automated Online Invigilation,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+6b5cf028b9fa3191119067f087b189d97017d31f,Online Invigilation: A Holistic Approach: Process for Automated Online Invigilation,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
6b7f7817b2e5a7e7d409af2254a903fc0d6e02b6,Feature Extraction through Cross-Phase Congruency for Facial Expression Analysis,University of Oradea,University of Oradea,"Universitatea Creștină Partium - Clădirea Sulyok, 27, Strada Primăriei, Orașul Nou, Oradea, Bihor, 410209, România",47.05702220,21.92270900,edu,
+6bb8a5f9e2ddf1bdcd42aa7212eb0499992c1e9e,A Siamese Long Short-Term Memory Architecture for Human Re-identification,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+6bb8a5f9e2ddf1bdcd42aa7212eb0499992c1e9e,A Siamese Long Short-Term Memory Architecture for Human Re-identification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+6bb8a5f9e2ddf1bdcd42aa7212eb0499992c1e9e,A Siamese Long Short-Term Memory Architecture for Human Re-identification,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3,DeepReID: Deep Filter Pairing Neural Network for Person Re-identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
6bb0425baac448297fbd29a00e9c9b9926ce8870,Facial Expression Recognition Using Log-Gabor Filters and Local Binary Pattern Operators,RMIT University,RMIT University,"RMIT University, 124, La Trobe Street, Melbourne City, City of Melbourne, Victoria, 3000, Australia",-37.80874650,144.96388750,edu,
+6bccfe8068da78fe3caa43bba686919513fe451f,"Statistical Part-Based Models: Theory and Applications in Image Similarity, Object Detection and Region Labeling",Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+6bc459c548bba7a04e2e255845b28060ec390407,The red one!: On learning to refer to things based on their discriminative properties,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
6b17b219bd1a718b5cd63427032d93c603fcf24f,Videos from the 2013 Boston Marathon: An Event Reconstruction Dataset for Synchronization and Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6b17b219bd1a718b5cd63427032d93c603fcf24f,Videos from the 2013 Boston Marathon: An Event Reconstruction Dataset for Synchronization and Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6b17b219bd1a718b5cd63427032d93c603fcf24f,Videos from the 2013 Boston Marathon: An Event Reconstruction Dataset for Synchronization and Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6b17b219bd1a718b5cd63427032d93c603fcf24f,Videos from the 2013 Boston Marathon: An Event Reconstruction Dataset for Synchronization and Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6b17b219bd1a718b5cd63427032d93c603fcf24f,Videos from the 2013 Boston Marathon: An Event Reconstruction Dataset for Synchronization and Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6b17b219bd1a718b5cd63427032d93c603fcf24f,Videos from the 2013 Boston Marathon: An Event Reconstruction Dataset for Synchronization and Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6bb19408458dbae075be7f1612b969b565b4767a,Approximate Log-Hilbert-Schmidt Distances between Covariance Operators for Image Classification,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+6b47b1c5a628ddb939d0088b36753ca29b3f9b76,Real-time Three-stage Eye Feature Extraction,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+6b47b1c5a628ddb939d0088b36753ca29b3f9b76,Real-time Three-stage Eye Feature Extraction,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
07377c375ac76a34331c660fe87ebd7f9b3d74c4,Detailed Human Avatars from Monocular Video,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
0729628db4bb99f1f70dd6cb2353d7b76a9fce47,Separating pose and expression in face images: a manifold learning approach,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+07f4ba45b771ed123b08261d88acda19406a7987,Real-Time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-Identification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+0744143542ffcb45b1ad83078c23efa9d3ec2be4,Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+0790c400bfe6fbefe88ef7791476e1abf1952089,Deep Gaussian Conditional Random Field Network: A Model-Based Deep Network for Discriminative Denoising,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
07c90e85ac0f74b977babe245dea0f0abcf177e3,An Image Preprocessing Algorithm for Illumination Invariant Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1,Large scale unconstrained open set face database,University of Colorado at Colorado Springs,University of Colorado at Colorado Springs,"1420 Austin Bluffs Pkwy, Colorado Springs, CO 80918, USA",38.89646790,-104.80505940,edu,
076d3fc800d882445c11b9af466c3af7d2afc64f,Face attribute classification using attribute-aware correlation map and gated convolutional neural networks,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
+07ed099e7d9c88d8e272d7191a4c7c5a68e3a6bd,Exploring Local Context for Multi-target Tracking in Wide Area Aerial Surveillance,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
0773c320713dae62848fceac5a0ac346ba224eca,Digital facial augmentation for interactive entertainment,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+07a29f43713833da42b24e3915b63601c39d7627,Action Recognition and Localization by Hierarchical Space-Time Segments,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+07a29f43713833da42b24e3915b63601c39d7627,Action Recognition and Localization by Hierarchical Space-Time Segments,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
+0701f2ee5a06e9ab760ab9326a33b1d4b8d83414,How many pixels make an image?,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+071777bc168e9940bb04b207d3b061bbd5a0c01a,Improving Point of View Scene Recognition by Considering Textual Data,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
070de852bc6eb275d7ca3a9cdde8f6be8795d1a3,A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
070de852bc6eb275d7ca3a9cdde8f6be8795d1a3,A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling,Jacobs University,Jacobs University,"Liverpool Hope University, Shaw Street, Everton, Liverpool, North West England, England, L6 1HP, UK",53.41291480,-2.96897915,edu,
070de852bc6eb275d7ca3a9cdde8f6be8795d1a3,A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+076fd6fd85b93858155a1c775f1897f83d52b4c2,Improving an Object Detector and Extracting Regions Using Superpixels,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+07191c2047b5b643dd72a0583c1d537ba59f977a,Interactive Segmentation from 1-Bit Feedback,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+074acb048b09fc95a2201ff00f67fd743b73e1fd,Looking around the backyard helps to recognize faces and digits,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+07050b9fcf949487e32aa30d0534e46d7eea58b0,Audio-Video Biometric System with Liveness Checks,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
07a472ea4b5a28b93678a2dcf89028b086e481a2,Head Dynamic Analysis: A Multi-view Framework,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+079e20d0d870a5bade46cc9b4338a3d637399654,"Semantic Segmentation , Urban Navigation , and Research Directions",Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+07faf42fe021a0965a07ef7273d89a452aec6b90,End-to-End Eye Movement Detection Using Convolutional Neural Networks,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+07faf42fe021a0965a07ef7273d89a452aec6b90,End-to-End Eye Movement Detection Using Convolutional Neural Networks,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+075d9baf2ac827327a5fe63bb1f873c4f54f95df,Robust multi-pose face tracking by multi-stage tracklet association,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+075d9baf2ac827327a5fe63bb1f873c4f54f95df,Robust multi-pose face tracking by multi-stage tracklet association,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
07fa153b8e6196ee6ef6efd8b743de8485a07453,Action Prediction From Videos via Memorizing Hard-to-Predict Samples,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
07fa153b8e6196ee6ef6efd8b743de8485a07453,Action Prediction From Videos via Memorizing Hard-to-Predict Samples,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
07fa153b8e6196ee6ef6efd8b743de8485a07453,Action Prediction From Videos via Memorizing Hard-to-Predict Samples,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
0708059e3bedbea1cbfae1c8cd6b7259d4b56b5b,Graph-regularized multi-class support vector machines for face and action recognition,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
074af31bd9caa61fea3c4216731420bd7c08b96a,Face verification using sparse representations,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
074af31bd9caa61fea3c4216731420bd7c08b96a,Face verification using sparse representations,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+0740f71446e99273b89d89fa05ab439dc58c12e1,Reliable mapping and partitioning of performance-constrained openCL applications on CPU-GPU MPSoCs,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+074c658fac7d7ebd88be8a24b46f2b301a9aeeeb,Alternating Decision Forests,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
07f31bef7a7035792e3791473b3c58d03928abbf,Lessons from collecting a million biometric samples,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
07f31bef7a7035792e3791473b3c58d03928abbf,Lessons from collecting a million biometric samples,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+07b8a9a225b738c4074a50cf80ee5fe516878421,Convolutional Simplex Projection Network for Weakly Supervised Semantic Segmentation,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+07b358a22cbfba084189d287ba1ba50055c3cd09,TernausNetV2: Fully Convolutional Network for Instance Segmentation,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
07de8371ad4901356145722aa29abaeafd0986b9,Towards Usable Multimedia Event Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+07eb30d6bcb96d7d66192f0cf43038eabd6fdd13,Multivariate Amygdala Shape Modeling,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
07e639abf1621ceff27c9e3f548fadfa2052c912,5-HTTLPR Expression Outside the Skin: An Experimental Test of the Emotional Reactivity Hypothesis in Children,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
07e639abf1621ceff27c9e3f548fadfa2052c912,5-HTTLPR Expression Outside the Skin: An Experimental Test of the Emotional Reactivity Hypothesis in Children,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
07da958db2e561cc7c24e334b543d49084dd1809,Dictionary learning based dimensionality reduction for classification,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+07d249512522ae946089460c086b98205bcd17f3,Complex loss optimization via dual decomposition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+0700d9c983b9c52341a4e17b70bdaff59cb539e5,Discovering Semantic Vocabularies for Cross-Media Retrieval,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
07d986b1005593eda1aeb3b1d24078db864f8f6a,Facial Expression Recognition Using Local Facial Features,National University of Kaohsiung,National University of Kaohsiung,"國立高雄大學, 中央廣場, 藍田, 藍田里, 楠梓區, 高雄市, 811, 臺灣",22.73424255,120.28349755,edu,
07d986b1005593eda1aeb3b1d24078db864f8f6a,Facial Expression Recognition Using Local Facial Features,National University of Kaohsiung,National University of Kaohsiung,"國立高雄大學, 中央廣場, 藍田, 藍田里, 楠梓區, 高雄市, 811, 臺灣",22.73424255,120.28349755,edu,
+07e6d293498c4f9048ee5a67ad32ca42d6af9b51,Video-based Side-view Face Recognition for Home Safety,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+07fd87460b3f454c2e7c971aca55df85a374bf8d,An Object-Based Bayesian Framework for Top-Down Visual Attention,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+07fd87460b3f454c2e7c971aca55df85a374bf8d,An Object-Based Bayesian Framework for Top-Down Visual Attention,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+07a17771ca169bc01deb8f7dac1ff0c574ddc512,User-generated Pornographic Video Detection Using Shot-based Sensor Pattern Noise,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
+38b9f2faaffbc7c6ad7fb3fb01c387f3155de68f,Part-Based Feature Synthesis for Human Detection,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+383fae9c0b9b13af0ce5c5e88fa8ad40c7a3e7aa,"An Indoor and Outdoor, Multimodal, Multispectral and Multi-Illuminant Database for Face Recognition",University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
+380d50f3ccc07fa4f41282395a78c51e33985c39,Deep Attention Neural Tensor Network for Visual Question Answering,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+380d50f3ccc07fa4f41282395a78c51e33985c39,Deep Attention Neural Tensor Network for Visual Question Answering,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
3802c97f925cb03bac91d9db13d8b777dfd29dcc,Non-parametric Bayesian Constrained Local Models,Institute of Systems and Robotics,Institute of Systems and Robotics,"Institut für Robotik und Kognitive Systeme, 160, Ratzeburger Allee, Strecknitz, Sankt Jürgen, Strecknitz, Lübeck, Schleswig-Holstein, 23562, Deutschland",53.83383710,10.70359390,edu,
38a2661b6b995a3c4d69e7d5160b7596f89ce0e6,Randomized Intraclass-Distance Minimizing Binary Codes for face recognition,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
38a2661b6b995a3c4d69e7d5160b7596f89ce0e6,Randomized Intraclass-Distance Minimizing Binary Codes for face recognition,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+38c61c11554135e09a2353afa536d010c7a53cbb,Learning the Detection of Faces in Natural Images,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+3868c75855df640a73b1fcdfa5df1bb92b878099,Labelled pupils in the wild: a dataset for studying pupil detection in unconstrained environments,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+38525bca4b1c5f9b8108743f57fd468492713bca,A Joint Speaker-Listener-Reinforcer Model for Referring Expressions,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+3836b6c5e29a7d0ff58c73e5d5c03dc7e8603819,Multimodal Neural Machine Translation for Low-resource Language Pairs using Synthetic Data,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+3836b6c5e29a7d0ff58c73e5d5c03dc7e8603819,Multimodal Neural Machine Translation for Low-resource Language Pairs using Synthetic Data,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+3836b6c5e29a7d0ff58c73e5d5c03dc7e8603819,Multimodal Neural Machine Translation for Low-resource Language Pairs using Synthetic Data,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+38b55d95189c5e69cf4ab45098a48fba407609b4,Locally Aligned Feature Transforms across Views,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+3837cd26a92e6c20b4351b3fd7e83a422e56cb89,Mobile Robots and Marching Humans: Measuring Synchronous Joint Action While in Motion,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+38f88655debf4bf32978a7b39fbd56aea6ee5752,Class Rectification Hard Mining for Imbalanced Deep Learning,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+38f88655debf4bf32978a7b39fbd56aea6ee5752,Class Rectification Hard Mining for Imbalanced Deep Learning,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
38787338ba659f0bfbeba11ec5b7748ffdbb1c3d,Evaluation of the discrimination power of features extracted from 2-D and 3-D facial images for facial expression analysis,University of Piraeus,University of Piraeus,"Πανεπιστήμιο Πειραιώς, 80, Καραολή και Δημητρίου, Απόλλωνας, Νέο Φάληρο, Πειραιάς, Δήμος Πειραιώς, Περιφερειακή Ενότητα Πειραιώς, Περιφέρεια Αττικής, Αττική, 185 34, Ελλάδα",37.94173275,23.65303262,edu,
+3857ffcf39ec6183f0cbbe8c5f565b1ccd0dce5d,Multi-Level Factorisation Net for Person Re-Identification,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+38eb71578f82477f4b032481bd401f19f14eaf25,Efficient Resource-constrained Retrospective Analysis of Long Video Sequences,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
3803b91e784922a2dacd6a18f61b3100629df932,Temporal Multimodal Fusion for Video Emotion Classification in the Wild,Orange,Orange Labs,"78 Rue Olivier de Serres, 75015 Paris, France",48.83321220,2.29421550,company,"78 Rue Olivier de Serres, Paris, 75015"
3803b91e784922a2dacd6a18f61b3100629df932,Temporal Multimodal Fusion for Video Emotion Classification in the Wild,Orange,Orange Labs,"78 Rue Olivier de Serres, 75015 Paris, France",48.83321220,2.29421550,company,"78 Rue Olivier de Serres, Paris, 75015"
+3884b78a06ccfde3249c16ac450b5254d033126a,Dual Path Networks for Multi-Person Human Pose Estimation,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
38c901a58244be9a2644d486f9a1284dc0edbf8a,Multi-Camera Action Dataset for Cross-Camera Action Recognition Benchmarking,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
38c901a58244be9a2644d486f9a1284dc0edbf8a,Multi-Camera Action Dataset for Cross-Camera Action Recognition Benchmarking,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
38c901a58244be9a2644d486f9a1284dc0edbf8a,Multi-Camera Action Dataset for Cross-Camera Action Recognition Benchmarking,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+38ede8e62e82d5012b3a165e55c9bd84442967db,Deep Analysis of Facial Behavioral Dynamics,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+38ede8e62e82d5012b3a165e55c9bd84442967db,Deep Analysis of Facial Behavioral Dynamics,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+38abaa549c4f398079dc5b1e5957315f66918e23,A fast method for estimating transient scene attributes,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
3852968082a16db8be19b4cb04fb44820ae823d4,Unsupervised Learning of Long-Term Motion Dynamics for Videos,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
38cc2f1c13420170c7adac30f9dfac69b297fb76,Recognition of human activities and expressions in video sequences using shape context descriptor,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
38cbb500823057613494bacd0078aa0e57b30af8,Deep Face Deblurring,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
@@ -2379,116 +6521,309 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 38f06a75eb0519ae1d4582a86ef4730cc8fb8d7f,Shrinkage Expansion Adaptive Metric Learning,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
38f06a75eb0519ae1d4582a86ef4730cc8fb8d7f,Shrinkage Expansion Adaptive Metric Learning,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
38f06a75eb0519ae1d4582a86ef4730cc8fb8d7f,Shrinkage Expansion Adaptive Metric Learning,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+38211dc39e41273c0007889202c69f841e02248a,ImageNet: A large-scale hierarchical image database,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+389db56845978baef0141b876774ea06cfb13e04,Information-theoretic criteria for the design of compressive subspace classifiers,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
384945abd53f6a6af51faf254ba8ef0f0fb3f338,Visual Recognition with Humans in the Loop,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
384945abd53f6a6af51faf254ba8ef0f0fb3f338,Visual Recognition with Humans in the Loop,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+381416c19b636c9bbab6ec5ebb1c1fa1be6faeca,Mirage cores: the illusion of many out-of-order cores using in-order hardware,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+381416c19b636c9bbab6ec5ebb1c1fa1be6faeca,Mirage cores: the illusion of many out-of-order cores using in-order hardware,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+381416c19b636c9bbab6ec5ebb1c1fa1be6faeca,Mirage cores: the illusion of many out-of-order cores using in-order hardware,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+381416c19b636c9bbab6ec5ebb1c1fa1be6faeca,Mirage cores: the illusion of many out-of-order cores using in-order hardware,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
38d8ff137ff753f04689e6b76119a44588e143f3,When 3D-Aided 2D Face Recognition Meets Deep Learning: An extended UR2D for Pose-Invariant Face Recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+381d15951b5beb2456ac016ac7f15fd27aa07d1c,"The prodrome of autism: early behavioral and biological signs, regression, peri- and post-natal development and genetics.",Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
+3859d584d3fb794c2b74b42f0f195d16ce8e3820,Combining Recognition and Geometry for Data - Driven 3 D Reconstruction,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
3896c62af5b65d7ba9e52f87505841341bb3e8df,Face Recognition from Still Images and Video,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+3813d74ddf2540c06aa48fc42468bd0d97f51708,Asynchronous Multi-task Learning,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+3813d74ddf2540c06aa48fc42468bd0d97f51708,Asynchronous Multi-task Learning,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+3813d74ddf2540c06aa48fc42468bd0d97f51708,Asynchronous Multi-task Learning,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
38bbca5f94d4494494860c5fe8ca8862dcf9676e,"Probabilistic , Features - based Object Recognition",California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+38b5a83f7941fea5fd82466f8ce1ce4ed7749f59,Improving multi-target tracking via social grouping,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
38183fe28add21693729ddeaf3c8a90a2d5caea3,Scale-Aware Face Detection,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+38a9dfdf72d67cea75298cf29d3ea563e9ce3137,Temporal Segmentation of Egocentric Videos,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
+38283e35371f2a426305dee60e80cd28abb4f349,CMU-AML Submission to Moments in Time Challenge 2018,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+38283e35371f2a426305dee60e80cd28abb4f349,CMU-AML Submission to Moments in Time Challenge 2018,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
38a9ca2c49a77b540be52377784b9f734e0417e4,Face verification using large feature sets and one shot similarity,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
38a9ca2c49a77b540be52377784b9f734e0417e4,Face verification using large feature sets and one shot similarity,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
38a9ca2c49a77b540be52377784b9f734e0417e4,Face verification using large feature sets and one shot similarity,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
+385e45a0b9e88929ffe8a341c886a6de41d372f3,Robust Pose Features for Action Recognition,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+38ea19546355e41ee1d57febc07613e7d3122607,Dynamic Functional Brain Connectivity for Face Perception,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+38ea19546355e41ee1d57febc07613e7d3122607,Dynamic Functional Brain Connectivity for Face Perception,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+38ea19546355e41ee1d57febc07613e7d3122607,Dynamic Functional Brain Connectivity for Face Perception,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+38ea19546355e41ee1d57febc07613e7d3122607,Dynamic Functional Brain Connectivity for Face Perception,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+00c4325c669c52db182390b2ab4a2b9c20f06b8d,A False Trail to Follow: Differential Effects of the Facial Feedback Signals From the Upper and Lower Face on the Recognition of Micro-Expressions,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
00f7f7b72a92939c36e2ef9be97397d8796ee07c,3D ConvNets with Optical Flow Based Regularization,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+00f5bfc2fb760249ba4e9c72b72eea4574068339,VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+00f5bfc2fb760249ba4e9c72b72eea4574068339,VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
0021f46bda27ea105d722d19690f5564f2b8869e,Deep Region and Multi-label Learning for Facial Action Unit Detection,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
0081e2188c8f34fcea3e23c49fb3e17883b33551,Training Deep Face Recognition Systems with Synthetic Data,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+00732bed67ca05a601afe8376b5121545d5c7450,Path Aggregation Network for Instance Segmentation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+003927ec8deedf8cb515ad3b145ef2a5a556cbf4,On Autoencoders and Score Matching for Energy Based Models,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+003927ec8deedf8cb515ad3b145ef2a5a556cbf4,On Autoencoders and Score Matching for Energy Based Models,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+004ec53d1f12cc4c0a7c809bf3b7acaee2180fd9,An Affectively Aware Virtual Therapist for Depression Counseling,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+004ec53d1f12cc4c0a7c809bf3b7acaee2180fd9,An Affectively Aware Virtual Therapist for Depression Counseling,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
00dc942f23f2d52ab8c8b76b6016d9deed8c468d,Advanced Correlation-Based Character Recognition Applied to the Archimedes Palimpsest,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+000aac6ba1c67150d2d6fcc9acbe484b24de4c06,A Picture Is Worth a Thousand Tags: Automatic Web Based Image Tag Expansion,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+0000fcfd467a19cf0e59169c2f07d730a0f3a8b9,Exploring Visual Relationship for Image Captioning,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
0055c7f32fa6d4b1ad586d5211a7afb030ca08cc,Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
0055c7f32fa6d4b1ad586d5211a7afb030ca08cc,Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+004aa2cb4b68850ee006af8a6807b3c1a6a198f0,Deep Classifiers from Image Tags in the Wild,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+004aa2cb4b68850ee006af8a6807b3c1a6a198f0,Deep Classifiers from Image Tags in the Wild,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
009cd18ff06ff91c8c9a08a91d2516b264eee48e,Face and Automatic Target Recognition Based on Super-Resolved Discriminant Subspace,Chulalongkorn University,Chulalongkorn University,"จุฬาลงกรณ์มหาวิทยาลัย, 254, ถนนพญาไท, สยาม, แขวงปทุมวัน, เขตปทุมวัน, กรุงเทพมหานคร, 10330, ประเทศไทย",13.74311795,100.53287901,edu,
+0005a23c0db792ac9d0f5d408c39240ffe4c1d57,Understanding Fake Faces,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
+00514ba3949302705b3b88af5eeef2d05cf8497d,Region-based Segmentation and Object Detection,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+00514ba3949302705b3b88af5eeef2d05cf8497d,Region-based Segmentation and Object Detection,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+00b543d51bf6d16b4027ded325387518cb7fcfe1,Tracking Ants Through Occlusions,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
+00b543d51bf6d16b4027ded325387518cb7fcfe1,Tracking Ants Through Occlusions,University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
+0095564f9e0afe920324fc75cf0b76d3f4825206,Geometry Aware Constrained Optimization Techniques for Deep Learning ∗,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+007ab5528b3bd310a80d553cccad4b78dc496b02,Bidirectional Attention Flow for Machine Comprehension,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+008936436a5dada1366ccf239786f913a47c340d,Scribbler: Controlling Deep Image Synthesis with Sketch and Color,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+008936436a5dada1366ccf239786f913a47c340d,Scribbler: Controlling Deep Image Synthesis with Sketch and Color,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+005227ea30edc2907ca2c01d0729e247e2d9a350,A Semi-supervised Deep Generative Model for Human Body Analysis,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+00d0ad219577c70a3d6295e8839841b2f1898e29,Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+00d0ad219577c70a3d6295e8839841b2f1898e29,Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+00d0ad219577c70a3d6295e8839841b2f1898e29,Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
00b08d22abc85361e1c781d969a1b09b97bc7010,Who is the hero? semi-supervised person re-identification in videos,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
007250c2dce81dd839a55f9108677b4f13f2640a,Advances in Component Based Face Detection,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+00e4f90555b98e2286d4d07c87220a6766c441f0,Localization of Multi-pose and Occluded Facial Features via Sparse Shape Representation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
00e3957212517a252258baef833833921dd308d4,Adaptively Weighted Multi-task Deep Network for Person Attribute Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
00e3957212517a252258baef833833921dd308d4,Adaptively Weighted Multi-task Deep Network for Person Attribute Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+006af49a030aa5b17046cfaf40de8f9246b96adf,Super-Resolution on Image and Video,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+006af49a030aa5b17046cfaf40de8f9246b96adf,Super-Resolution on Image and Video,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+006af49a030aa5b17046cfaf40de8f9246b96adf,Super-Resolution on Image and Video,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+00e8968c5922b71bf3be2e9733fce82f3c40cf44,Neuronal fiber pathway abnormalities in autism: an initial MRI diffusion tensor tracking study of hippocampo-fusiform and amygdalo-fusiform pathways.,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
009a18d04a5e3ec23f8ffcfc940402fd8ec9488f,Action Recognition by Weakly-Supervised Discriminative Region Localization,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
0066caed1238de95a431d836d8e6e551b3cde391,Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+001973a77bf8fa82314de667af5b041d856b0069,Trajectory Factory: Tracklet Cleaving and Re-Connection by Deep Siamese Bi-GRU for Multiple Object Tracking,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
00075519a794ea546b2ca3ca105e2f65e2f5f471,"Generating a Large, Freely-Available Dataset for Face-Related Algorithms",Amherst College,Amherst College,"Amherst College, Boltwood Avenue, Amherst, Hampshire, Massachusetts, 01004, USA",42.37289000,-72.51881400,edu,
0019925779bff96448f0c75492717e4473f88377,Deep Heterogeneous Face Recognition Networks Based on Cross-Modal Distillation and an Equitable Distance Metric,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+007e86cb55f0ba0415a7764a1e9f9566c1e8784b,Adversarial Feature Learning,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+00b202871ec41b8049e8393e463660525ecb61b5,Subspace clustering based on low rank representation and weighted nuclear norm minimization,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+00f1cccba86736cb6b6f39759ca6749f819252f0,Transfer Metric Learning for Kinship Verification with Locality-Constrained Sparse Features,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+00434a4491b6710308c653c430784872849d1f36,Evaluating Scientific Workflow Execution on an Asymmetric Multicore Processor,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+0074ccd17382bf077bf08d649a97541ad64478fd,Answer-Aware Attention on Grounded Question Answering in Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+00f1b6927785b6f4305cc35c1b0bfbbe2010c31f,Universal Conditional Machine,Lomonosov Moscow State University,Lomonosov Moscow State University,"МГУ, улица Академика Хохлова, Московский государственный университет им. М. В. Ломоносова, район Раменки, Западный административный округ, Москва, ЦФО, 119234, РФ",55.70229715,37.53179777,edu,
+00bc6570d7bec88593cdeafc0feafa32c81aeea9,3D facial expression recognition using swarm intelligence,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
00e9011f58a561500a2910a4013e6334627dee60,Facial expression recognition using angle-related information from facial meshes,University of Thessaloniki,University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+000cd8d20d91ded078949dfcde76817221ea96c8,Learning Visual Attributes from Image and Text,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+0041ea67f32bef4949fedcef97562ad16fe5a7f9,Gradient based efficient feature selection,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+00bf7bcf31ee71f5f325ca5307883157ba3d580f,Efficient Online Local Metric Adaptation via Negative Samples for Person Re-identification,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
00a967cb2d18e1394226ad37930524a31351f6cf,Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
00a967cb2d18e1394226ad37930524a31351f6cf,Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
00a967cb2d18e1394226ad37930524a31351f6cf,Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+00dec7b4e082e9345e1b34e36d42669f12c129f2,Lost in binarization: query-adaptive ranking for similar image search with compact codes,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
00f1e5e954f9eb7ffde3ca74009a8c3c27358b58,Unsupervised clustering for google searches of celebrity images,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+009678c2034cf4a9924a78d533d2ec81303a946e,"Connecting Gaze, Scene, and Attention: Generalized Attention Estimation via Joint Modeling of Gaze and Scene Saliency",Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+00a6d711f2bf7974384d2f4b5e61d0bbc493a6b7,Adaptive Margin Nearest Neighbor for Person Re-Identification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
0058cbe110933f73c21fa6cc9ae0cd23e974a9c7,"Biswas, Jacobs: an Efficient Algorithm for Learning Distances",University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
0058cbe110933f73c21fa6cc9ae0cd23e974a9c7,"Biswas, Jacobs: an Efficient Algorithm for Learning Distances",University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
00ebc3fa871933265711558fa9486057937c416e,Collaborative Representation based Classification for Face Recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
00ebc3fa871933265711558fa9486057937c416e,Collaborative Representation based Classification for Face Recognition,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
00b29e319ff8b3a521b1320cb8ab5e39d7f42281,Towards Transparent Systems: Semantic Characterization of Failure Modes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
00b29e319ff8b3a521b1320cb8ab5e39d7f42281,Towards Transparent Systems: Semantic Characterization of Failure Modes,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+00823e6c0b6f1cf22897b8d0b2596743723ec51c,Understanding and Comparing Deep Neural Networks for Age and Gender Classification,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
+000f90380d768a85e2316225854fc377c079b5c4,Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+0068204e6f250c7e8a26e5dcccc37b36808bca32,Seafloor image compression with large tilesize vector quantization,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+0037d05fe2fc9553e58206f40ca39760396b5911,Automated Insect Identification through Concatenated Histograms of Local Appearance Features,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+0037d05fe2fc9553e58206f40ca39760396b5911,Automated Insect Identification through Concatenated Histograms of Local Appearance Features,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
6e60536c847ac25dba4c1c071e0355e5537fe061,Computer Vision and Natural Language Processing: Recent Approaches in Multimedia and Robotics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
6e60536c847ac25dba4c1c071e0355e5537fe061,Computer Vision and Natural Language Processing: Recent Approaches in Multimedia and Robotics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
6e60536c847ac25dba4c1c071e0355e5537fe061,Computer Vision and Natural Language Processing: Recent Approaches in Multimedia and Robotics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+6e1c597fdad6c43ce6e404f14f336576d8373acd,Efficiently and Effectively Learning Models of Similarity from Human Feeback,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+6e1c597fdad6c43ce6e404f14f336576d8373acd,Efficiently and Effectively Learning Models of Similarity from Human Feeback,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
6e173ad91b288418c290aa8891193873933423b3,Are you from North or South India? A hard race classification task reveals systematic representational differences between humans and machines,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
6e91be2ad74cf7c5969314b2327b513532b1be09,Dimensionality Reduction with Subspace Structure Preservation,SUNY Buffalo,SUNY Buffalo,"SUNY College at Buffalo, Academic Drive, Elmwood Village, Buffalo, Erie County, New York, 14222, USA",42.93362780,-78.88394479,edu,
+6e61641c9a9cddb38948b6600c0ebc3d2057c697,Pyramid Center-Symmetric Local Binary/Trinary Patterns for Effective Pedestrian Detection,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+6e61641c9a9cddb38948b6600c0ebc3d2057c697,Pyramid Center-Symmetric Local Binary/Trinary Patterns for Effective Pedestrian Detection,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+6e7a9779dee831658e973ee26ac8bfed2d6da033,Human Pose Estimation for Multiple Frames,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+6e7a9779dee831658e973ee26ac8bfed2d6da033,Human Pose Estimation for Multiple Frames,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+6e7a9779dee831658e973ee26ac8bfed2d6da033,Human Pose Estimation for Multiple Frames,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
6eddea1d991e81c1c3024a6cea422bc59b10a1dc,Towards automatic analysis of gestures and body expressions in depression,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
6eddea1d991e81c1c3024a6cea422bc59b10a1dc,Towards automatic analysis of gestures and body expressions in depression,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+6e025c0415c9ff0705d4e4439a48e8fffe7d44c1,Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+6e647a430d603f4d82e44b4a87de580a0fcaec88,BigSUR: large-scale structured urban reconstruction,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+6e647a430d603f4d82e44b4a87de580a0fcaec88,BigSUR: large-scale structured urban reconstruction,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+6eb8e193687c16f0edc3742d3549ad175ef648d1,Working memory load disrupts gaze-cued orienting of attention,University of East Anglia,University of East Anglia,"Arts (Lower Walkway Level), The Square, Westfield View, Earlham, Norwich, Norfolk, East of England, England, NR4 7TJ, UK",52.62215710,1.24091360,edu,
6e97a99b2879634ecae962ddb8af7c1a0a653a82,Towards Context-aware Interaction Recognition,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+6e428db07a54a824f77a4c1a8fe9e70d6049e79c,Hierarchical Feature Hashing for Fast Dimensionality Reduction,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6e9a8a34ab5b7cdc12ea52d94e3462225af2c32c,Fusing Aligned and Non-aligned Face Information for Automatic Affect Recognition in the Wild: A Deep Learning Approach,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
+6ebfec00388b6975c8c38aed1ebe006eae79bcfe,Modeling Instance Appearance for Recognition – Can We Do Better Than EM?,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+6ebfec00388b6975c8c38aed1ebe006eae79bcfe,Modeling Instance Appearance for Recognition – Can We Do Better Than EM?,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+6e968f74fd6b4b3b172c787f298b3d4746ec5cc9,A 3D Polygonal Line Chains Matching Method for Face Recognition,Griffith University,Griffith University,"Griffith University Nathan Campus, Johnson Path, Nathan, Nathan Heights, QLD, 4111, Australia",-27.55339750,153.05336234,edu,
+6e968f74fd6b4b3b172c787f298b3d4746ec5cc9,A 3D Polygonal Line Chains Matching Method for Face Recognition,Griffith University,Griffith University,"Griffith University Nathan Campus, Johnson Path, Nathan, Nathan Heights, QLD, 4111, Australia",-27.55339750,153.05336234,edu,
+6e209d7d33c0be8afae863f4e4e9c3e86826711f,Weakly-supervised segmentation by combining CNN feature maps and object saliency maps,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+6eebd8762996501b28d3d94a7c166c79d37e7a57,Sequential Spectral Learning to Hash with Multiple Representations,Pohang University of Science and Technology,Pohang University of Science and Technology,"포스텍, 77, 청암로, 효곡동, 남구, 포항시, 경북, 37673, 대한민국",36.01773095,129.32107509,edu,
+6e69de19576ea2dfa4cb84a450ce18eccd183a95,Easy Minimax Estimation with Random Forests for Human Pose Estimation,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+6e12226cf0da453dc4b9879d7af6b43af3c31d2b,Efficient Action Detection in Untrimmed Videos via Multi-task Learning,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+6ef190ad2c9c6e11d12bc1b51a4c8a11a4692fb8,Annotating Object Instances with a Polygon-RNN,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
6e00a406edb508312108f683effe6d3c1db020fb,Faces as Lighting Probes via Unsupervised Deep Highlight Extraction,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
6e00a406edb508312108f683effe6d3c1db020fb,Faces as Lighting Probes via Unsupervised Deep Highlight Extraction,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
6e00a406edb508312108f683effe6d3c1db020fb,Faces as Lighting Probes via Unsupervised Deep Highlight Extraction,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+6e40b120bf46807ef28ebdd8860e3109708bb888,Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
6e94c579097922f4bc659dd5d6c6238a428c4d22,Graph Based Multi-class Semi-supervised Learning Using Gaussian Process,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+6eeff23d6e0127cfbbd0374a83341173a418ba7f,Dual Attention Network for Visual Question Answering,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+6e6923a8b39cd22d714ae9364d18bec8178e5632,Generating Image Descriptions Using Semantic Similarities in the Output Space,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
6eb1e006b7758b636a569ca9e15aafd038d2c1b1,Human Capabilities on Video-based Facial Expression Recognition,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
6eb1e006b7758b636a569ca9e15aafd038d2c1b1,Human Capabilities on Video-based Facial Expression Recognition,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
6eece104e430829741677cadc1dfacd0e058d60f,Use of Automated Facial Image Analysis for Measurement of Emotion Expression,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
6eece104e430829741677cadc1dfacd0e058d60f,Use of Automated Facial Image Analysis for Measurement of Emotion Expression,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
6eece104e430829741677cadc1dfacd0e058d60f,Use of Automated Facial Image Analysis for Measurement of Emotion Expression,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6ee5dbbc167167105162abd888ca4824a048fae0,Face recognition using non-linear image reconstruction,Orange,Orange Labs,"78 Rue Olivier de Serres, 75015 Paris, France",48.83321220,2.29421550,company,"78 Rue Olivier de Serres, Paris, 75015"
+6ef78987104b7e66c1a71f87b94c4b0ebf34330e,Incorporating Side Information by Adaptive Convolution,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
6eb1b5935b0613a41b72fd9e7e53a3c0b32651e9,LEGO Pictorial Scales for Assessing Affective Responses,University of Canterbury,University of Canterbury,"University of Canterbury, Uni-Cycle, Ilam, Christchurch, Christchurch City, Canterbury, 8040, New Zealand/Aotearoa",-43.52405280,172.58030625,edu,
6eb1b5935b0613a41b72fd9e7e53a3c0b32651e9,LEGO Pictorial Scales for Assessing Affective Responses,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
6eb1b5935b0613a41b72fd9e7e53a3c0b32651e9,LEGO Pictorial Scales for Assessing Affective Responses,University of Canterbury,University of Canterbury,"University of Canterbury, Uni-Cycle, Ilam, Christchurch, Christchurch City, Canterbury, 8040, New Zealand/Aotearoa",-43.52405280,172.58030625,edu,
+6e12b8cb01abd5d6af6023e284009d417c53d160,Coarse-to-fine : A RNN-based hierarchical attention model for vehicle re-identification ?,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+6e12b8cb01abd5d6af6023e284009d417c53d160,Coarse-to-fine : A RNN-based hierarchical attention model for vehicle re-identification ?,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+6ea6be2c270f7d366e9e93ced7ea5a17d3a24c1a,Real-Time Semantic Segmentation Benchmarking Framework,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+6e80ad43c5f383c1d87b1ced2a336fe5cd44e044,Faster R-CNN for Robust Pedestrian Detection Using Semantic Segmentation Network,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
6e782073a013ce3dbc5b9b56087fd0300c510f67,Real Time Facial Emotion Recognition using Kinect V2 Sensor,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
+6e4e5ef25f657de8fb383c8dfeb8e229eea28bb9,RON: Reverse Connection with Objectness Prior Networks for Object Detection,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+6eb5db8e6a79ad59bf4f4a5fccdd5b10237408d7,Cross Talk: The Microbiota and Neurodevelopmental Disorders,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+9a36bbabea698a9fe0e11e2cf77a013dd7769f42,Predicting Aggressive Tendencies by Visual Attention Bias Associated with Hostile Emotions,National Central University,National Central University,"NCU, 300, 中大路, 上三座屋, 五權里, 樹林子, 中壢區, 桃園市, 320, 臺灣",24.96841805,121.19139696,edu,
+9a36bbabea698a9fe0e11e2cf77a013dd7769f42,Predicting Aggressive Tendencies by Visual Attention Bias Associated with Hostile Emotions,National Central University,National Central University,"NCU, 300, 中大路, 上三座屋, 五權里, 樹林子, 中壢區, 桃園市, 320, 臺灣",24.96841805,121.19139696,edu,
+9a36bbabea698a9fe0e11e2cf77a013dd7769f42,Predicting Aggressive Tendencies by Visual Attention Bias Associated with Hostile Emotions,Tamkang University,Tamkang University,"淡江大學, 151, 英專路, 中興里, 鬼仔坑, 淡水區, 新北市, 25137, 臺灣",25.17500615,121.45076751,edu,
+9a6268d2bc1221ea154097feadea0c58f234d02f,Co-Attending Free-Form Regions and Detections With Multi-Modal Multiplicative Feature Embedding for Visual Question Answering,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+9a6268d2bc1221ea154097feadea0c58f234d02f,Co-Attending Free-Form Regions and Detections With Multi-Modal Multiplicative Feature Embedding for Visual Question Answering,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+9a6268d2bc1221ea154097feadea0c58f234d02f,Co-Attending Free-Form Regions and Detections With Multi-Modal Multiplicative Feature Embedding for Visual Question Answering,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+9a81f46fcf8c6c0efbe34649552b5056ce419a3d,Deep person re-identification with improved embedding and efficient training,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+9a45abde5e2ad08dcb6c267fba30a02fcd2e516e,Realistic Texture Extraction for 3 D Face Models Robust to Self-Occlusion,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
9a0c7a4652c49a177460b5d2fbbe1b2e6535e50a,Automatic and quantitative evaluation of attribute discovery methods,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
9ac43a98fe6fde668afb4fcc115e4ee353a6732d,Survey of Face Detection on Low-Quality Images,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+9a5473662819063cb60c1b29e6544b9314b9b29f,Predicting Social Interactions for Visual Tracking,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
9a4c45e5c6e4f616771a7325629d167a38508691,A facial features detector integrating holistic facial information and part-based model,University of Louisville,University of Louisville,"University of Louisville, South Brook Street, Louisville, Jefferson County, Kentucky, 40208, USA",38.21675650,-85.75725023,edu,
9a4c45e5c6e4f616771a7325629d167a38508691,A facial features detector integrating holistic facial information and part-based model,Alexandria University,Alexandria University,"جامعة الإسكندرية, الكورنيش, إبراهيمية, الإسكندرية, 21522, مصر",31.21051105,29.91314562,edu,
9a4c45e5c6e4f616771a7325629d167a38508691,A facial features detector integrating holistic facial information and part-based model,Assiut University,Assiut University,"Assiut University, El Shaheed Ellwaa Hasn Kamel street, الوليدية, أسيوط, مصر",27.18794105,31.17009498,edu,
+9a5c896a527fb6b72508d7a6309c5c375cb2967c,The IJCB 2014 PaSC video face and person recognition competition,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+9a5c896a527fb6b72508d7a6309c5c375cb2967c,The IJCB 2014 PaSC video face and person recognition competition,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
+9a5c896a527fb6b72508d7a6309c5c375cb2967c,The IJCB 2014 PaSC video face and person recognition competition,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+9a5c896a527fb6b72508d7a6309c5c375cb2967c,The IJCB 2014 PaSC video face and person recognition competition,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
9af9a88c60d9e4b53e759823c439fc590a4b5bc5,Learning Deep Convolutional Embeddings for Face Representation Using Joint Sample- and Set-Based Supervision,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+9a27d5efc7b74ba23c07d3a45f20285998bf1577,MONET: Multiview Semi-supervised Keypoint via Epipolar Divergence,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
9a3535cabf5d0f662bff1d897fb5b777a412d82e,Large-scale geo-facial image analysis,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
9a3535cabf5d0f662bff1d897fb5b777a412d82e,Large-scale geo-facial image analysis,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
9a3535cabf5d0f662bff1d897fb5b777a412d82e,Large-scale geo-facial image analysis,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
9a3535cabf5d0f662bff1d897fb5b777a412d82e,Large-scale geo-facial image analysis,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
9a3535cabf5d0f662bff1d897fb5b777a412d82e,Large-scale geo-facial image analysis,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+9a7b7d61481e3a5bca1ef809358d46ac87405f67,Neural circuitry of emotional face processing in autism spectrum disorders.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+9a781a01b5a9c210dd2d27db8b73b7d62bc64837,An Attempt to Build Object Detection Models by Reusing Parts,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
9abd35b37a49ee1295e8197aac59bde802a934f3,Depth2Action: Exploring Embedded Depth for Large-Scale Action Recognition,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+9a9570bfebd3c970879f8d99804e74093d9bb6e9,Living a discrete life in a continuous world: Reference with distributed representations,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
+9a9570bfebd3c970879f8d99804e74093d9bb6e9,Living a discrete life in a continuous world: Reference with distributed representations,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+9ac625867c50ce839d56a52ade92d3b971caff43,Accelerating Machine Learning Kernel in Hadoop Using FPGAs,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+9abd6bac662e8fdf4f71ccc26a89f7e360b7b879,Object Level Visual Reasoning in Videos,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+9a5a1763e0342d41cb1d1eef18a007be6e8dba89,Image Annotation with Discriminative Model and Annotation Refinement by Visual Similarity Matching,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+9a601fd18aea081d28408d133140ffb1f6dfcda6,Novel Pose-Variant Face Detection Method for Human-Robot Interaction Application,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+9adbbd9dadaf7b15bb585555e7a2e2223e711296,Identity information content depends on the type of facial movement,Max Planck Institute for Biological Cybernetics,Max Planck Institute for Biological Cybernetics,"Max-Planck-Institut für Biologische Kybernetik, 8, Max-Planck-Ring, Max-Planck-Institut, Wanne, Tübingen, Landkreis Tübingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72076, Deutschland",48.53691250,9.05922533,edu,
+9adbbd9dadaf7b15bb585555e7a2e2223e711296,Identity information content depends on the type of facial movement,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+9a7fcd09afd8c3ae227e621795168c94ffbac71d,Action unit recognition transfer across datasets,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+36597e65169d576d0a68dca7023c57efcfee5c4f,Multiclass transfer learning from unconstrained priors,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+363cb83220451baa9f785a1fa738e41178e015c7,SPID: Surveillance Pedestrian Image Dataset and Performance Evaluation for Pedestrian Detection,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+36f1110aed28165483f2dc7250fd187412467f61,Evaluating the WordsEye Text-to-Scene System: Imaginative and Realistic Sentences,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+364f357d4894aa004e442a5a92896a9b14a46862,Recovering 3-D Shape and Reflectance From a Small Number of Photographs,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+36972f34d35acab784359ddac4789e19118ac6d4,Graph-based Inference with Constraints for Object Detection and Segmentation,Lehigh University,Lehigh University,"Lehigh University, Library Drive, Sayre Park, Bethlehem, Northampton County, Pennsylvania, 18015, USA",40.60680280,-75.37824880,edu,
+36d858eb19bba43244b92f7faabfce47b13f2403,Materialization optimizations for feature selection workloads,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+36d858eb19bba43244b92f7faabfce47b13f2403,Materialization optimizations for feature selection workloads,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+364c79d2d98819b27641c651cf6553142ef747bf,Hedging your bets: Optimizing accuracy-specificity trade-offs in large scale visual recognition,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+36132cf4fea1717f7d39150d1a0cc79ad78b069e,Attribute-Centered Loss for Soft-Biometrics Guided Face Sketch-Photo Recognition,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+36fd702e5686f91b7e45434f8e2f6ef51feb2d54,Kernel-PCA Analysis of Surface Normals for Shape-from-Shading,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+36a0961cc64c4d3033aec820073d50c6470caa41,Indexing Methods for Efficient Multiclass Recognition Indexing Methods for Efficient Multiclass Recognition Indexing Methods for Efficient Multiclass Recognition,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+36d487129fd0b828255e417e0d10cf13d7f525cf,Reduced functional integration and segregation of distributed neural systems underlying social and emotional information processing in autism spectrum disorders.,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
36a3a96ef54000a0cd63de867a5eb7e84396de09,Automatic Photo Orientation Detection with Convolutional Neural Networks,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+360bb1bafa00dd1fa90a89766f5ef75061cfde75,Common-near-neighbor analysis for person re-identification,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+360bb1bafa00dd1fa90a89766f5ef75061cfde75,Common-near-neighbor analysis for person re-identification,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+36ddf5d08ce753fe00efc844be3769f09dda9f91,Towards incremental and large scale face recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+3676c29babe1563ee64a1149d2ae2f9f1369fe25,Visual saliency computation for image analysis,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+3676c29babe1563ee64a1149d2ae2f9f1369fe25,Visual saliency computation for image analysis,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
360d66e210f7011423364327b7eccdf758b5fdd2,Local feature extraction methods for facial expression recognition,RMIT University,RMIT University,"RMIT University, 124, La Trobe Street, Melbourne City, City of Melbourne, Victoria, 3000, Australia",-37.80874650,144.96388750,edu,
+36c948efd76f58ff1a5e42a2b69fbdc04913f7c4,A Review on Image Texture Analysis Methods,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
361c9ba853c7d69058ddc0f32cdbe94fbc2166d5,Deep Reinforcement Learning of Video Games,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
361c9ba853c7d69058ddc0f32cdbe94fbc2166d5,Deep Reinforcement Learning of Video Games,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
368e99f669ea5fd395b3193cd75b301a76150f9d,One-to-many face recognition with bilinear CNNs,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+362d884ff43d8c7cd6bce184944cfc04cdd57c18,Octopus-Man: QoS-driven task management for heterogeneous multicores in warehouse-scale computers,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+362d884ff43d8c7cd6bce184944cfc04cdd57c18,Octopus-Man: QoS-driven task management for heterogeneous multicores in warehouse-scale computers,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+361aa2cfbc51ece34be511986205095363db94c5,Automatic landmark detection and face recognition for side-view face images,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+3615bbdd4fe81acd9e5d166af731b5556b19a2cd,Efficient object localization using Convolutional Networks,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+36a95f1a9fbe518427bbf33293488c71161313a9,Multi-Context Label Embedding,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
36df81e82ea5c1e5edac40b60b374979a43668a5,On-the-fly specific person retrieval,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+36091ff6b5d5a53d9641f5c3388b8c31b9ad4b49,Temporal Modular Networks for Retrieving Complex Compositional Activities in Videos,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
3619a9b46ad4779d0a63b20f7a6a8d3d49530339,Fisher Vector Faces in the Wild,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
36e8ef2e5d52a78dddf0002e03918b101dcdb326,Multiview Active Shape Models with SIFT Descriptors for the 300-W Face Landmark Challenge,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
36e8ef2e5d52a78dddf0002e03918b101dcdb326,Multiview Active Shape Models with SIFT Descriptors for the 300-W Face Landmark Challenge,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
367f2668b215e32aff9d5122ce1f1207c20336c8,Speaker-Dependent Human Emotion Recognition in Unimodal and Bimodal Scenarios,University of Peshawar,University of Peshawar,"University of Peshawar, Road 2, JAHANGIR ABAD / جهانگیرآباد, پشاور, Peshāwar District, خیبر پختونخوا, 2500, پاکستان",34.00920040,71.48774947,edu,
367f2668b215e32aff9d5122ce1f1207c20336c8,Speaker-Dependent Human Emotion Recognition in Unimodal and Bimodal Scenarios,University of Peshawar,University of Peshawar,"University of Peshawar, Road 2, JAHANGIR ABAD / جهانگیرآباد, پشاور, Peshāwar District, خیبر پختونخوا, 2500, پاکستان",34.00920040,71.48774947,edu,
+36c2715522c3df4237d8e034dfe49d67eafd6382,"Scene Graph Generation from Objects, Phrases and Region Captions",Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+36c2715522c3df4237d8e034dfe49d67eafd6382,"Scene Graph Generation from Objects, Phrases and Region Captions",University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+36c2715522c3df4237d8e034dfe49d67eafd6382,"Scene Graph Generation from Objects, Phrases and Region Captions",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
36c2db5ff76864d289781f93cbb3e6351f11984c,One colored image based 2.5D human face reconstruction,Newcastle University,Newcastle University,"Newcastle University, Claremont Walk, Haymarket, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE1 7RU, UK",54.98023235,-1.61452627,edu,
+3686c59fac958de0b3911d5b08213994836ee96e,Efficient Articulated Trajectory Reconstruction Using Dynamic Programming and Filters,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+3686c59fac958de0b3911d5b08213994836ee96e,Efficient Articulated Trajectory Reconstruction Using Dynamic Programming and Filters,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+36e21168155720d0210b8cc4ae031091d96701c8,Research Problems and Opportunities in Memory Systems,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+36e21168155720d0210b8cc4ae031091d96701c8,Research Problems and Opportunities in Memory Systems,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+36e21168155720d0210b8cc4ae031091d96701c8,Research Problems and Opportunities in Memory Systems,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3661a34f302883c759b9fa2ce03de0c7173d2bb2,Peak-Piloted Deep Network for Facial Expression Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
3661a34f302883c759b9fa2ce03de0c7173d2bb2,Peak-Piloted Deep Network for Facial Expression Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
36c473fc0bf3cee5fdd49a13cf122de8be736977,Temporal Segment Networks: Towards Good Practices for Deep Action Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
36c473fc0bf3cee5fdd49a13cf122de8be736977,Temporal Segment Networks: Towards Good Practices for Deep Action Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+361164861d8e4676079219f6d099358a31fc4025,Multiple Hypothesis Tracking Revisited,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+361164861d8e4676079219f6d099358a31fc4025,Multiple Hypothesis Tracking Revisited,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
368d59cf1733af511ed8abbcbeb4fb47afd4da1c,To Frontalize or Not To Frontalize: A Study of Face Pre-Processing Techniques and Their Impact on Recognition,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
368d59cf1733af511ed8abbcbeb4fb47afd4da1c,To Frontalize or Not To Frontalize: A Study of Face Pre-Processing Techniques and Their Impact on Recognition,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+3632ac78294d39f8d51bb8f2ec270cf9c115d0f6,Typeface Completion with Generative Adversarial Networks,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
36b9f46c12240898bafa10b0026a3fb5239f72f3,Collaborative Deep Reinforcement Learning for Joint Object Search,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
36b9f46c12240898bafa10b0026a3fb5239f72f3,Collaborative Deep Reinforcement Learning for Joint Object Search,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
36b9f46c12240898bafa10b0026a3fb5239f72f3,Collaborative Deep Reinforcement Learning for Joint Object Search,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
36b9f46c12240898bafa10b0026a3fb5239f72f3,Collaborative Deep Reinforcement Learning for Joint Object Search,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+360f8874e42894af71ede97cd153853e09238350,Extracting Moving People from Internet Videos,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+36e25994cfeab3dc487f9a82139c08f26cebf92f,Annealed Generative Adversarial Networks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
361d6345919c2edc5c3ce49bb4915ed2b4ee49be,Models for supervised learning in sequence data,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+36d18202745ec9abb70d8f7e6a4f28a55871e657,Pairwise Body-Part Attention for Recognizing Human-Object Interactions,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+3605647befd040a819f00b1539a6e3cc5ffb53b8,Vision-based bicyclist detection and tracking for intelligent vehicles,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+3605647befd040a819f00b1539a6e3cc5ffb53b8,Vision-based bicyclist detection and tracking for intelligent vehicles,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3634b4dd263c0f330245c086ce646c9bb748cd6b,Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web Images,Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
367a786cfe930455cd3f6bd2492c304d38f6f488,A Training Assistant Tool for the Automated Visual Inspection System,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+5c812e8968b88c25d18a066f8a28c0421555d2c9,Highly-Economized Multi-view Binary Compression for Scalable Image Clustering,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+5c812e8968b88c25d18a066f8a28c0421555d2c9,Highly-Economized Multi-view Binary Compression for Scalable Image Clustering,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+5cd2a7ec2b47086b1e9ff6ebc096eae5e03d2f67,Simultaneous super-resolution and feature extraction for recognition of low-resolution faces,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5ce84883ab78e7e61a4e84a80cce8c86265f6ae9,Deep Sparse Coding for Invariant Multimodal Halle Berry Neurons,Villanova University,Villanova University,"Villanova University, East Lancaster Avenue, Radnor Township, Delaware County, Pennsylvania, 19010, USA",40.03677740,-75.34202332,edu,
5cbe1445d683d605b31377881ac8540e1d17adf0,On 3D face reconstruction via cascaded regression in shape space,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
5ca23ceb0636dfc34c114d4af7276a588e0e8dac,Texture representation in AAM using Gabor wavelet and local binary patterns,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
5ca23ceb0636dfc34c114d4af7276a588e0e8dac,Texture representation in AAM using Gabor wavelet and local binary patterns,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
5ca23ceb0636dfc34c114d4af7276a588e0e8dac,Texture representation in AAM using Gabor wavelet and local binary patterns,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
5ca23ceb0636dfc34c114d4af7276a588e0e8dac,Texture representation in AAM using Gabor wavelet and local binary patterns,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+5c6215a32fa943d07cd2d0401d646f93faaf34e1,Latent Semantic Representation Learning for Scene Classification,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+5cf549ca5680491f12a5ac5d42b171a64088da22,FRVT 2006: Quo Vidas Face Quality,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+5cf549ca5680491f12a5ac5d42b171a64088da22,FRVT 2006: Quo Vidas Face Quality,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+5cf549ca5680491f12a5ac5d42b171a64088da22,FRVT 2006: Quo Vidas Face Quality,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+5cbc66ace06eb35a22a3196cc13f75ddb0b7cefa,SHADHO: Massively Scalable Hardware-Aware Distributed Hyperparameter Optimization,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
5c493c42bfd93e4d08517438983e3af65e023a87,Multimodal Keyless Attention Fusion for Video Classification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+5c9cfeb77f7e5040a4ca3775e524247a0bcb73db,The truth about cats and dogs,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+5c9cfeb77f7e5040a4ca3775e524247a0bcb73db,The truth about cats and dogs,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+5cac869f7e47c290ba14d27a5d6b5aadaddfaa69,Semantically Selective Augmentation for Deep Compact Person Re-Identification,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
5cb83eba8d265afd4eac49eb6b91cdae47def26d,Face Recognition with Local Line Binary Pattern,Mahanakorn University of Technology,Mahanakorn University of Technology,"มหาวิทยาลัยเทคโนโลยีมหานคร, 140, ถนนเชื่อมสัมพันธ์, กรุงเทพมหานคร, เขตหนองจอก, กรุงเทพมหานคร, 10530, ประเทศไทย",13.84450465,100.85620818,edu,
5c8672c0d2f28fd5d2d2c4b9818fcff43fb01a48,Robust Face Detection by Simple Means,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
5c3dce55c61ee86073575ac75cc882a215cb49e6,Neural Codes for Image Retrieval,"Moscow Institute of Physics and Technology, Russia","Moscow Institute of Physics and Technology, Russia","МФТИ, 9, Институтский переулок, Виноградовские Горки, Лихачёво, Долгопрудный, городской округ Долгопрудный, Московская область, ЦФО, 141700, РФ",55.92903500,37.51866808,edu,
+5ccb73fa509b4c56c765cf5ef850060ca8686bfa,Identification by a hybrid 3D/2D gait recognition algorithm,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+5c97cef9cebf101b74699f583f3e324aebccde32,Multi-view multi-modal person authentication from a single walking image sequence,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+5cbef6da9c2cc630722f1e48a59c3aa84a00c44a,Binary Pattern Analysis for 3D Facial Action Unit Detection,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+5cbef6da9c2cc630722f1e48a59c3aa84a00c44a,Binary Pattern Analysis for 3D Facial Action Unit Detection,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+5c6841db352d54ba6e18f362b8cc6509a15a8fd3,Exploring object-centric and scene-centric CNN features and their complementarity for human rights violations recognition in images,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
5c820e47981d21c9dddde8d2f8020146e600368f,Extended Supervised Descent Method for Robust Face Alignment,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+5c07464391cda9440cf05c67ab5f3b2b777459d6,Person Re-Identification by Localizing Discriminative Regions,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+5c70bca2b3dd0a47b6259d384a709be55a60369e,Model-based approaches for predicting gait changes over time,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
5c7adde982efb24c3786fa2d1f65f40a64e2afbf,Ranking Domain-Specific Highlights by Analyzing Edited Videos,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+5c48d6ea9b022c077b1873ec48ea4f37a91ac77a,A Structural Filter Approach to Human Detection,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+5c48d6ea9b022c077b1873ec48ea4f37a91ac77a,A Structural Filter Approach to Human Detection,"OMRON Corporation, Kyoto, Japan","Core Technology Center, OMRON Corporation, Kyoto, Japan","Kyoto, Kyoto Prefecture, Japan",35.01163630,135.76802940,company,
5c36d8bb0815fd4ff5daa8351df4a7e2d1b32934,GeePS: scalable deep learning on distributed GPUs with a GPU-specialized parameter server,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
5cfbeae360398de9e20e4165485837bd42b93217,Comparison Of Hog (Histogram of Oriented Gradients) and Haar Cascade Algorithms with a Convolutional Neural Network Based Face Detection Approaches,Firat University,Firat University,"Erzincan Üniversitesi Hukuk Fakültesi Dekanlığı, Sivas-Erzincan yolu, Üçkonak, Erzincan, Erzincan merkez, Erzincan, Doğu Anadolu Bölgesi, 24000, Türkiye",39.72750370,39.47127034,edu,
5cfbeae360398de9e20e4165485837bd42b93217,Comparison Of Hog (Histogram of Oriented Gradients) and Haar Cascade Algorithms with a Convolutional Neural Network Based Face Detection Approaches,Firat University,Firat University,"Erzincan Üniversitesi Hukuk Fakültesi Dekanlığı, Sivas-Erzincan yolu, Üçkonak, Erzincan, Erzincan merkez, Erzincan, Doğu Anadolu Bölgesi, 24000, Türkiye",39.72750370,39.47127034,edu,
+5cb8fe6b51813600d5b43a63ca4b8c1cb1237793,PortraitGAN for Flexible Portrait Manipulation,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+5c3d8cf726f17bbb326551253c810429d332d3f3,Complementing the Execution of AI Systems with Human Computation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+5c3d8cf726f17bbb326551253c810429d332d3f3,Complementing the Execution of AI Systems with Human Computation,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
5ca14fa73da37855bfa880b549483ee2aba26669,Face Recognition under Varying Illuminations Using Local Binary Pattern And Local Ternary Pattern Fusion,Punjabi University Patiala,Punjabi University Patiala,"Punjabi University Patiala, Rajpura Road, Patiala, Punjab, 147001, India",30.35689810,76.45512720,edu,
5ca14fa73da37855bfa880b549483ee2aba26669,Face Recognition under Varying Illuminations Using Local Binary Pattern And Local Ternary Pattern Fusion,Punjabi University Patiala,Punjabi University Patiala,"Punjabi University Patiala, Rajpura Road, Patiala, Punjab, 147001, India",30.35689810,76.45512720,edu,
+5cd58501fd184a0fe5c05026ba1965ad12e68205,It’s All in the Eyes: Subcortical and Cortical Activation during Grotesqueness Perception in Autism,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+5c4c2e8181d50c74e26d2ad793d5aec668f61e23,Multi-view fusion for activity recognition using deep neural networks,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+5c4c2e8181d50c74e26d2ad793d5aec668f61e23,Multi-view fusion for activity recognition using deep neural networks,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
5c8ae37d532c7bb8d7f00dfde84df4ba63f46297,DiscrimNet: Semi-Supervised Action Recognition from Videos using Generative Adversarial Networks,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
5c8ae37d532c7bb8d7f00dfde84df4ba63f46297,DiscrimNet: Semi-Supervised Action Recognition from Videos using Generative Adversarial Networks,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
5ce2cb4c76b0cdffe135cf24b9cda7ae841c8d49,Facial Expression Intensity Estimation Using Ordinal Information,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
@@ -2496,112 +6831,302 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 5c4d4fd37e8c80ae95c00973531f34a6d810ea3a,The Open World of Micro-Videos,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
09b80d8eea809529b08a8b0ff3417950c048d474,Adding Unlabeled Samples to Categories by Learned Attributes,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
09b80d8eea809529b08a8b0ff3417950c048d474,Adding Unlabeled Samples to Categories by Learned Attributes,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+09348656bbbe88881d1257650a170af5e22f1008,Parsing clothing in fashion photographs,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+09fd76c02abdd1bca7b98ab9fa66450cec33b9dc,User qualified ? N Feedback Pass ? Pass ? Annotator training Annotating images,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
09f58353e48780c707cf24a0074e4d353da18934,Unconstrained face recognition: Establishing baseline human performance via crowdsourcing,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
09f58353e48780c707cf24a0074e4d353da18934,Unconstrained face recognition: Establishing baseline human performance via crowdsourcing,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
09f58353e48780c707cf24a0074e4d353da18934,Unconstrained face recognition: Establishing baseline human performance via crowdsourcing,"Noblis, Falls Church, VA, U.S.A.","Noblis, Falls Church, VA, U.S.A.","2002 Edmund Halley Dr, Reston, VA 20191, USA",38.95187000,-77.36325900,company,
+09066d7d0bb6273bf996c8538d7b34c38ea6a500,"Yes, IoU loss is submodular - as a function of the mispredictions",Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+09b5b34d06fff4c76866d92516108ac68ac25ccf,Using Regression Techniques for Coping with the One-Sample-Size Problem of Face Recognition,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+0903b956a68073eee3760572059abd5b24b026da,Probabilistic Label Trees for Efficient Large Scale Image Classification,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
0969e0dc05fca21ff572ada75cb4b703c8212e80,Semi-Supervised Classification Based on Low Rank Representation,Southwest University,Southwest University,"西南大学, 天生路, 北碚区 (Beibei), 北碚区, 北碚区 (Beibei), 重庆市, 400711, 中国",29.82366295,106.42050016,edu,
09dd01e19b247a33162d71f07491781bdf4bfd00,Efficiently Scaling Up Video Annotation with Crowdsourced Marketplaces,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
09cf3f1764ab1029f3a7d57b70ae5d5954486d69,Comparison of ICA approaches for facial expression recognition,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
09fa54f1ab7aaa83124d2415bfc6eb51e4b1f081,Where to Buy It: Matching Street Clothing Photos in Online Shops,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
09fa54f1ab7aaa83124d2415bfc6eb51e4b1f081,Where to Buy It: Matching Street Clothing Photos in Online Shops,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+09ca15b1c1d65012e5bc07e5a44bad7b72609a02,Discriminative Hough Forests for Object Detection,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+0959ef8fefe9e7041f508c2448fc026bc9e08393,Material recognition in the wild with the Materials in Context Database,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
0951f42abbf649bb564a21d4ff5dddf9a5ea54d9,Joint Estimation of Age and Gender from Unconstrained Face Images Using Lightweight Multi-Task CNN for Mobile Applications,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
09628e9116e7890bc65ebeabaaa5f607c9847bae,Semantically Consistent Regularization for Zero-Shot Recognition,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
09733129161ca7d65cf56a7ad63c17f493386027,Face Recognition under Varying Illumination,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
09733129161ca7d65cf56a7ad63c17f493386027,Face Recognition under Varying Illumination,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
09733129161ca7d65cf56a7ad63c17f493386027,Face Recognition under Varying Illumination,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
+096e389c28cdd15b8765baa29ae55d98f8c3c4b4,Passive Profiling and Natural Interaction Metaphors for Personalized Multimedia Museum Experiences,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
097340d3ac939ce181c829afb6b6faff946cdce0,Adding New Tasks to a Single Network with Weight Trasformations using Binary Masks,Sapienza University of Rome,Sapienza University of Rome,"Piazzale Aldo Moro, 5, 00185 Roma RM, Italy",41.90376260,12.51443840,edu,
+097d3892f5f2ba7be43a81908279f42a618839ec,Dynamic context driven human detection and tracking in meeting scenarios,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
09507f1f1253101d04a975fc5600952eac868602,Motion Feature Network: Fixed Motion Filter for Action Recognition,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+09669da2fe4764196eb0e2eff240291d54607882,Deep Disentangled Representations for Volumetric Reconstruction,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+09a8ae8fc95bd3c9fb8022da2c32c519d5fc06bc,A Multiple Kernel Learning Approach to Joint Multi-class Object Detection,Max Planck Institute for Biological Cybernetics,Max Planck Institute for Biological Cybernetics,"Max-Planck-Institut für Biologische Kybernetik, 8, Max-Planck-Ring, Max-Planck-Institut, Wanne, Tübingen, Landkreis Tübingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72076, Deutschland",48.53691250,9.05922533,edu,
+0914eb61b743300828c84f9e235ce6165a171be5,Analyzing the Behavior of Visual Question Answering Models,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+09edba9db405dde61630c70bba00ae9c5dd7ed37,Learning From Disagreements: Discriminative Performance Evaluation,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
+09d03b792923695deb0492d8fc3582a50e5f1a1e,Band-Sifting Decomposition for Image-Based Material Editing,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
098a1ccc13b8d6409aa333c8a1079b2c9824705b,Attribute Pivots for Guiding Relevance Feedback in Image Search,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+09232b786e009655c5e03d2b3fcd7b40d75382bf,The Representation of Emotion in Autonomic and Central Nervous System Activity,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+091433bc8791bb66797b519811834a8a53af622d,simNet: Stepwise Image-Topic Merging Network for Generating Detailed and Comprehensive Image Captions,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+091433bc8791bb66797b519811834a8a53af622d,simNet: Stepwise Image-Topic Merging Network for Generating Detailed and Comprehensive Image Captions,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+097f482c548075305b5866d7d0fde7b67c30c52d,Unsupervised Learning of Generative Topic Saliency for Person Re-identification,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+09750ce4a8fa0a0fc596bdda8bf58db74fa9a0e1,Synthesizing Training Images for Boosting Human 3D Pose Estimation,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
090ff8f992dc71a1125636c1adffc0634155b450,Topic-Aware Deep Auto-Encoders (TDA) for Face Alignment,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
090ff8f992dc71a1125636c1adffc0634155b450,Topic-Aware Deep Auto-Encoders (TDA) for Face Alignment,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
090ff8f992dc71a1125636c1adffc0634155b450,Topic-Aware Deep Auto-Encoders (TDA) for Face Alignment,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+090b341def78df92d562e7d8e7f9d131a68ca769,A Novel Benchmark RGBD Dataset for Dormant Apple Trees and Its Application to Automatic Pruning,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
09b43b59879d59493df2a93c216746f2cf50f4ac,Deep Transfer Metric Learning,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+09c5fe448694eea3cf3166ccccb2c81048fe0601,Clustered Exemplar-SVM: Discovering sub-categories for visual recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+0947c7c46943ebbb6a4b5c795c9b54552c8e0b5a,"QMAS: Querying, Mining and Summarization of Multi-modal Databases",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0947c7c46943ebbb6a4b5c795c9b54552c8e0b5a,"QMAS: Querying, Mining and Summarization of Multi-modal Databases",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0947c7c46943ebbb6a4b5c795c9b54552c8e0b5a,"QMAS: Querying, Mining and Summarization of Multi-modal Databases",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+093da3310d98b3c09e2770c2a6aa49eeca58cebe,Trimmed Event Recognition : submission to ActivityNet Challenge 2018,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
09b0ef3248ff8f1a05b8704a1b4cf64951575be9,Recognizing Activities of Daily Living with a Wrist-Mounted Camera,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+090b3189391f3e1917649b3a62696febbf0429e1,Taking the Perfect Selfie: Investigating the Impact of Perspective on the Perception of Higher Cognitive Variables,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+090b3189391f3e1917649b3a62696febbf0429e1,Taking the Perfect Selfie: Investigating the Impact of Perspective on the Perception of Higher Cognitive Variables,La Trobe University,La Trobe University,"La Trobe University, Keck Street, Flora Hill, Bendigo, City of Greater Bendigo, Loddon Mallee, Victoria, 3550, Australia",-36.77847540,144.29804700,edu,
+098f1939afa5a071e133c767ca49703b16443b9a,Combining Face and Iris Biometrics for Identity Verification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+098f1939afa5a071e133c767ca49703b16443b9a,Combining Face and Iris Biometrics for Identity Verification,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+096bd380a2f653dc5e43069b97e1505186c47d5b,Min Norm Point Algorithm for Higher Order MRF-MAP Inference,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
094357c1a2ba3fda22aa6dd9e496530d784e1721,A Unified Probabilistic Approach Modeling Relationships between Attributes and Objects,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+09e1072c509e1d24a34dfbbaba1c3700e1eb1338,Visualization of Time-Series Data in Parameter Space for Understanding Facial Dynamics,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+09e1072c509e1d24a34dfbbaba1c3700e1eb1338,Visualization of Time-Series Data in Parameter Space for Understanding Facial Dynamics,Swansea University,Swansea University,"Swansea University, University Footbridge, Sketty, Swansea, Wales, SA2 8PZ, UK",51.60915780,-3.97934429,edu,
+098a0bd7c948e9c94704ac5e8c768c8d430e1842,Cascaded Models for Articulated Pose Estimation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+098a0bd7c948e9c94704ac5e8c768c8d430e1842,Cascaded Models for Articulated Pose Estimation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+098a0bd7c948e9c94704ac5e8c768c8d430e1842,Cascaded Models for Articulated Pose Estimation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+098a0bd7c948e9c94704ac5e8c768c8d430e1842,Cascaded Models for Articulated Pose Estimation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
09ce14b84af2dc2f76ae1cf227356fa0ba337d07,Face reconstruction in the wild,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+09a106feed520651d785fd8a2df26910f5928f2e,"Think Leader, Think White? Capturing and Weakening an Implicit Pro-White Leadership Bias",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
090e4713bcccff52dcd0c01169591affd2af7e76,What Do You Do? Occupation Recognition in a Photo via Social Context,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
090e4713bcccff52dcd0c01169591affd2af7e76,What Do You Do? Occupation Recognition in a Photo via Social Context,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+5d2a01e3a445a92ecdce5f20656fd87e65982708,Learning Convolutional Feature Hierarchies for Visual Recognition,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+5da9a5367bd70c004ad9b7e8cee95059490e33fc,The TUM-DLR Multimodal Earth Observation Evaluation Benchmark,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+5d28a54b1b27280482463df85bb66bc2914ff893,Multi-Object Tracking with Correlation Filter for Autonomous Vehicle,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+5d58d4164493924906231a28153e50342fdf1198,Leveraging Long-Term Predictions and Online Learning in Agent-Based Multiple Person Tracking,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+5d58d4164493924906231a28153e50342fdf1198,Leveraging Long-Term Predictions and Online Learning in Agent-Based Multiple Person Tracking,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+5d494e5517a25365fe204eaae3c3247f7e57260e,Membership representation for detecting block-diagonal structure in low-rank or sparse subspace clustering,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
+5d494e5517a25365fe204eaae3c3247f7e57260e,Membership representation for detecting block-diagonal structure in low-rank or sparse subspace clustering,Ajou University,Ajou University,"아주대학교, 성호대교, 이의동, 영통구, 수원시, 경기, 16499, 대한민국",37.28300030,127.04548469,edu,
+5d494e5517a25365fe204eaae3c3247f7e57260e,Membership representation for detecting block-diagonal structure in low-rank or sparse subspace clustering,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+5d1ffb7ba3c53ecc5a90d40380ae235043c16344,On Label-Aware Community Search,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
5de5848dc3fc35e40420ffec70a407e4770e3a8d,WebVision Database: Visual Learning and Understanding from Web Data,ETH Zurich,"Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland","Sternwartstrasse 7, 8092 Zürich, Switzerland",47.37723980,8.55216180,edu,
+5df0fed3b37ffac6d0ae7c0a3ccce41c7044e8e8,Groupwise Tracking of Crowded Similar-Appearance Targets from Low-Continuity Image Sequences,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
+5d2d797ee4053dada784639d7462abbfb2220031,Guided Open Vocabulary Image Captioning with Constrained Beam Search,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+5da8e841871e4a97534d981ee20002b183b45508,BSN: Boundary Sensitive Network for Temporal Action Proposal Generation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+5d92531e74c4c2cdce91fdcd3c7ff090c8c29504,Synthesizing Scenes for Instance Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5d92531e74c4c2cdce91fdcd3c7ff090c8c29504,Synthesizing Scenes for Instance Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5dc52c64991c655a12936867594326cf6352eb8e,Constructing Local Binary Pattern Statistics by Soft Voting,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+5d7f52a7d9814688c13b84ab35526fc9bf57d1bf,Large-Scale Category Structure Aware Image Categorization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5d7f52a7d9814688c13b84ab35526fc9bf57d1bf,Large-Scale Category Structure Aware Image Categorization,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+5d7f52a7d9814688c13b84ab35526fc9bf57d1bf,Large-Scale Category Structure Aware Image Categorization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5d3b6c9a0a8b71b875a565f5cd133d83817fdc38,3D facial expression recognition based on automatically selected features,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+5d02f269e3b9764a3bf5d254a385fd61759a84a7,AVEC 2011-The First International Audio/Visual Emotion Challenge,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+5d02f269e3b9764a3bf5d254a385fd61759a84a7,AVEC 2011-The First International Audio/Visual Emotion Challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
5dd496e58cfedfc11b4b43c4ffe44ac72493bf55,Discriminative convolutional Fisher vector network for action recognition,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+5d2b396447fae5a64cbe6b5ef5e99ca2b88c2914,Vehicle Re-Identification with the Space-Time Prior,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
5d88702cdc879396b8b2cc674e233895de99666b,Exploiting Feature Hierarchies with Convolutional Neural Networks for Cultural Event Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
5d88702cdc879396b8b2cc674e233895de99666b,Exploiting Feature Hierarchies with Convolutional Neural Networks for Cultural Event Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5df93d7da8ab46f1d0e9deadd4e5e5568acd7651,Delving Deep into Multiscale Pedestrian Detection via Single Scale Feature Maps,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+5df93d7da8ab46f1d0e9deadd4e5e5568acd7651,Delving Deep into Multiscale Pedestrian Detection via Single Scale Feature Maps,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+5df93d7da8ab46f1d0e9deadd4e5e5568acd7651,Delving Deep into Multiscale Pedestrian Detection via Single Scale Feature Maps,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
5d479f77ecccfac9f47d91544fd67df642dfab3c,"Linking People in Videos with ""Their"" Names Using Coreference Resolution",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
5d479f77ecccfac9f47d91544fd67df642dfab3c,"Linking People in Videos with ""Their"" Names Using Coreference Resolution",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+5d5533b8b95f25f63e07786cf3e063c8db356f1f,Human Observers and Automated Assessment of Dynamic Emotional Facial Expressions: KDEF-dyn Database Validation,Universität Hamburg,Universität Hamburg,"Informatikum, 30, Vogt-Kölln-Straße, Stellingen, Eimsbüttel, Hamburg, 22527, Deutschland",53.59948200,9.93353436,edu,
5df376748fe5ccd87a724ef31d4fdb579dab693f,A Dashboard for Affective E-learning: Data Visualization for Monitoring Online Learner Emotions,Carleton University,Carleton University,"Carleton University, 1125, Colonel By Drive, Billings Bridge, Capital, Ottawa, Ontario, K1S 5B7, Canada",45.38608430,-75.69539267,edu,
+5dc7c33475b545271d1de726fd88bb68dfb7e11b,Generating Video Description using RNN with Semantic Attention,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+5dc7c33475b545271d1de726fd88bb68dfb7e11b,Generating Video Description using RNN with Semantic Attention,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+5d56587ee5652fc9bd7e3bdf5a533b4f627b6487,A Graph-Based Algorithm for Supervised Image Classification,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+310dbc59aa3309f2a3813728783d81a9f7f1c939,Estimating contact dynamics,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+31ffe7b6447221ade78c71c36e8e86279a8478b6,Batch-normalized recurrent highway networks,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
3167f415a861f19747ab5e749e78000179d685bc,RankBoost with l1 regularization for facial expression recognition and intensity estimation,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
3107316f243233d45e3c7e5972517d1ed4991f91,CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+3164189f84710de9f8150385a41a7079a57186df,Object detection using edge histogram of oriented gradient,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+31e0303d98fd1bb6a1074d4fe0b14228e91b388b,基於稀疏表示之語者識別 (Sparse Representation Based Speaker Identification) [In Chinese],National Central University,National Central University,"NCU, 300, 中大路, 上三座屋, 五權里, 樹林子, 中壢區, 桃園市, 320, 臺灣",24.96841805,121.19139696,edu,
+31e0303d98fd1bb6a1074d4fe0b14228e91b388b,基於稀疏表示之語者識別 (Sparse Representation Based Speaker Identification) [In Chinese],National Central University,National Central University,"NCU, 300, 中大路, 上三座屋, 五權里, 樹林子, 中壢區, 桃園市, 320, 臺灣",24.96841805,121.19139696,edu,
+31f5eebfebac54cf5817deea7da32994637a5b28,Multi-view Metric Learning for Multi-view Video Summarization,Anhui University,Anhui University,"安徽大学(磬苑校区), 111, 九龙路, 弘泰苑, 合肥国家级经济技术开发区, 芙蓉社区, 合肥经济技术开发区, 合肥市区, 合肥市, 安徽省, 230601, 中国",31.76909325,117.17795091,edu,
+31f5eebfebac54cf5817deea7da32994637a5b28,Multi-view Metric Learning for Multi-view Video Summarization,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
313d5eba97fe064bdc1f00b7587a4b3543ef712a,Compact Deep Aggregation for Set Retrieval,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+3167c8a1d0415eb7dc241e395f55d559c43a99f9,Noisy Sparse Subspace Clustering,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+3167c8a1d0415eb7dc241e395f55d559c43a99f9,Noisy Sparse Subspace Clustering,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+3150fd3b0065372f898b42a3628318210fcd566b,Beyond parametric score normalisation in biometric verification systems,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+3136cab00cfb223ceb9aff78af2c165b6e71a878,Open source biometric recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+3136cab00cfb223ceb9aff78af2c165b6e71a878,Open source biometric recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+3136cab00cfb223ceb9aff78af2c165b6e71a878,Open source biometric recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
3137a3fedf23717c411483c7b4bd2ed646258401,Joint Learning of Discriminative Prototypes and Large Margin Nearest Neighbor Classifiers,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
31c34a5b42a640b824fa4e3d6187e3675226143e,Shape and texture based facial action and emotion recognition,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+3154d7479881c7efd8a50909af921cfa8cff8e2e,Recognizing hand-object interactions in wearable camera videos,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+31531ff4f106d1e196e619b859d0dc510e01c5a8,A Convex Formulation for Spectral Shrunk Clustering,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+31531ff4f106d1e196e619b859d0dc510e01c5a8,A Convex Formulation for Spectral Shrunk Clustering,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+31531ff4f106d1e196e619b859d0dc510e01c5a8,A Convex Formulation for Spectral Shrunk Clustering,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+31531ff4f106d1e196e619b859d0dc510e01c5a8,A Convex Formulation for Spectral Shrunk Clustering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+31531ff4f106d1e196e619b859d0dc510e01c5a8,A Convex Formulation for Spectral Shrunk Clustering,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
31ea88f29e7f01a9801648d808f90862e066f9ea,Deep Multi-task Representation Learning: A Tensor Factorisation Approach,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+31e1d021bd06054bbfcd915794e84448ae681000,Joint Deep Learning for Pedestrian Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
31835472821c7e3090abb42e57c38f7043dc3636,Flow Counting Using Realboosted Multi-sized Window Detectors,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+3163d481923cc75d53c2ca940e23a07e7c85069c,Kinship verification from videos using spatio-temporal texture features and deep learning,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+3163d481923cc75d53c2ca940e23a07e7c85069c,Kinship verification from videos using spatio-temporal texture features and deep learning,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+3147bb14bf4228735ecf4bc2a421590b3de86c0f,Efficient PSD Constrained Asymmetric Metric Learning for Person Re-Identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+31c5d8109f3110fc8b7eeb6265e832e809cdaa39,Recursive Fréchet Mean Computation on the Grassmannian and Its Applications to Computer Vision,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
312b2566e315dd6e65bd42cfcbe4d919159de8a1,An Accurate Algorithm for Generating a Music Playlist based on Facial Expressions,Amity University,Amity University,"Amity University, Faizabad Road, Uttardhauna, Gomti Nagar, Tiwariganj, Lucknow, Uttar Pradesh, 226010, India",26.85095965,81.04950965,edu,
3152e89963b8a4028c4abf6e1dc19e91c4c5a8f4,Exploring Stereotypes and Biased Data with the Crowd,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
3152e89963b8a4028c4abf6e1dc19e91c4c5a8f4,Exploring Stereotypes and Biased Data with the Crowd,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+313e508202a6f4f2fc40a78b6237e52c2c0d22a2,Domain Adaptation for Ear Recognition Using Deep Convolutional Neural Networks,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
+319aeaba5dfb4f7de44668bbedbbfdcb7ebc50fa,Gait Learning-Based Regenerative Model: A Level Set Approach,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
316d51aaa37891d730ffded7b9d42946abea837f,Unsupervised learning of clutter-resistant visual representations from natural videos,McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
31d60b2af2c0e172c1a6a124718e99075818c408,Robust Facial Expression Recognition Using Near Infrared Cameras,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+316486bada6023816c785c0d4eb401658737be3f,QoS-Aware scheduling in heterogeneous datacenters with paragon,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
31f1e711fcf82c855f27396f181bf5e565a2f58d,Unconstrained Age Estimation with Deep Convolutional Neural Networks,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
31f1e711fcf82c855f27396f181bf5e565a2f58d,Unconstrained Age Estimation with Deep Convolutional Neural Networks,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+3127738c7a634d7b651405cb31fbc52ec7d5806a,Robust Subspace Recovery via Bi-Sparsity Pursuit,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+315a90543d60a5b6c5d1716fe9076736f0e90d24,Illumination invariant human face recognition: frequency or resonance?,University of Windsor,University of Windsor,"Bridge AA, Ambassador Bridge, Windsor, Essex, Ontario, N9C 2J9, Canada",42.30791465,-83.07176915,edu,
3107085973617bbfc434c6cb82c87f2a952021b7,Spatio-temporal human action localisation and instance segmentation in temporally untrimmed videos,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
3107085973617bbfc434c6cb82c87f2a952021b7,Spatio-temporal human action localisation and instance segmentation in temporally untrimmed videos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+315ff3853dd408b765fbf83344974eda9ac37705,Predicting the Category and Attributes of Visual Search Targets Using Deep Gaze Pooling,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
31182c5ffc8c5d8772b6db01ec98144cd6e4e897,3D Face Reconstruction with Region Based Best Fit Blending Using Mobile Phone for Virtual Reality Based Social Media,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
+312620fb93a30b0448ec8ffd728b8ee2858ef74c,Compact Real-time avoidance on a Humanoid Robot for Human-robot Interaction,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+312620fb93a30b0448ec8ffd728b8ee2858ef74c,Compact Real-time avoidance on a Humanoid Robot for Human-robot Interaction,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
3146fabd5631a7d1387327918b184103d06c2211,Person-Independent 3D Gaze Estimation Using Face Frontalization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3146fabd5631a7d1387327918b184103d06c2211,Person-Independent 3D Gaze Estimation Using Face Frontalization,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+91fe43fd76571513c8caf3aca20a405f5d99f3fd,What is the Ground? Continuous Maps for Grounding Perceptual Primitives,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+91c184e7fb0c7cce5319b8db85c1488b3861976f,Visual Question Answer Diversity,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+91c184e7fb0c7cce5319b8db85c1488b3861976f,Visual Question Answer Diversity,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+91c184e7fb0c7cce5319b8db85c1488b3861976f,Visual Question Answer Diversity,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
91495c689e6e614247495c3f322d400d8098de43,A Deep-Learning Approach to Facial Expression Recognition with Candid Images,CUNY City College,CUNY City College,"CUNY City College, 205 East 42nd Street, New York, NY 10017",45.55466080,5.40652550,edu,
910524c0d0fe062bf806bb545627bf2c9a236a03,Master Thesis Improvement of Facial Expression Recognition through the Evaluation of Dynamic and Static Features in Video Sequences,Otto von Guericke University,Otto von Guericke University,"Otto-von-Guericke-Universität Magdeburg, 2, Universitätsplatz, Krökentorviertel/Breiter Weg NA, Alte Neustadt, Magdeburg, Sachsen-Anhalt, 39106, Deutschland",52.14005065,11.64471248,edu,
910524c0d0fe062bf806bb545627bf2c9a236a03,Master Thesis Improvement of Facial Expression Recognition through the Evaluation of Dynamic and Static Features in Video Sequences,Otto von Guericke University,Otto von Guericke University,"Otto-von-Guericke-Universität Magdeburg, 2, Universitätsplatz, Krökentorviertel/Breiter Weg NA, Alte Neustadt, Magdeburg, Sachsen-Anhalt, 39106, Deutschland",52.14005065,11.64471248,edu,
91df860368cbcebebd83d59ae1670c0f47de171d,"COCO Attributes: Attributes for People, Animals, and Objects",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
91df860368cbcebebd83d59ae1670c0f47de171d,"COCO Attributes: Attributes for People, Animals, and Objects",Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+9151f229e7b4e318b0b12afe99993da0ee5e0e34,Adversarial Multi-task Learning for Text Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+9151f229e7b4e318b0b12afe99993da0ee5e0e34,Adversarial Multi-task Learning for Text Classification,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+91bd017c1b19c36e430a22929d8de3af0795dfa4,Learning Linear Transformations for Fast Arbitrary Style Transfer,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
9110c589c6e78daf4affd8e318d843dc750fb71a,Facial Expression Synthesis Based on Emotion Dimensions for Affective Talking Avatar,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
9110c589c6e78daf4affd8e318d843dc750fb71a,Facial Expression Synthesis Based on Emotion Dimensions for Affective Talking Avatar,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
9110c589c6e78daf4affd8e318d843dc750fb71a,Facial Expression Synthesis Based on Emotion Dimensions for Affective Talking Avatar,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+9184b0c04013bfdfd82f4f271b5f017396c2f085,Semantic Segmentation for Line Drawing Vectorization Using Neural Networks,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+919b1f80f818c2c1710a674536d4957890bbfd82,Targeted Kernel Networks: Faster Convolutions with Attentive Regularization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+916498961a51f56a592c3551b0acc25978571fa7,Optimal landmark detection using shape models and branch and bound,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+916498961a51f56a592c3551b0acc25978571fa7,Optimal landmark detection using shape models and branch and bound,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+918ab79e963d5e339a2696ee4aed123599f291e6,Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+918ab79e963d5e339a2696ee4aed123599f291e6,Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+918ab79e963d5e339a2696ee4aed123599f291e6,Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+918ab79e963d5e339a2696ee4aed123599f291e6,Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+918ab79e963d5e339a2696ee4aed123599f291e6,Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+918ab79e963d5e339a2696ee4aed123599f291e6,Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+918ab79e963d5e339a2696ee4aed123599f291e6,Machine Learning Methods for Solving Assignment Problems in Multi-Target Tracking,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+91e435fe71861a8da569a089b4841522ac9aa369,ST-GAN: Unsupervised Facial Image Semantic Transformation Using Generative Adversarial Networks,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+91e435fe71861a8da569a089b4841522ac9aa369,ST-GAN: Unsupervised Facial Image Semantic Transformation Using Generative Adversarial Networks,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+91e435fe71861a8da569a089b4841522ac9aa369,ST-GAN: Unsupervised Facial Image Semantic Transformation Using Generative Adversarial Networks,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+919327d4f264775bd4ab2923d7786d5b2c859409,An X-T slice based method for action recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+91ea1d8f11c4e3a20234888f6ea5309678975563,Disconnected Manifold Learning for Generative Adversarial Networks,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+91ea1d8f11c4e3a20234888f6ea5309678975563,Disconnected Manifold Learning for Generative Adversarial Networks,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+911ee14fbd3f0b9ccbd91090fbe4aa65d73f46f5,AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+911ee14fbd3f0b9ccbd91090fbe4aa65d73f46f5,AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+911ee14fbd3f0b9ccbd91090fbe4aa65d73f46f5,AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks,Education University of Hong Kong,The Education University of Hong Kong,"香港教育大學 The Education University of Hong Kong, 露屏路 Lo Ping Road, 鳳園 Fung Yuen, 下坑 Ha Hang, 新界 New Territories, HK, DD5 1119, 中国",22.46935655,114.19474194,edu,
+912f107002506ab8c7ae411c8d34c200ba567b02,Optimal UV spaces for facial morphable model construction,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
91e507d2d8375bf474f6ffa87788aa3e742333ce,Robust Face Recognition Using Probabilistic Facial Trait Code,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+91cc3981c304227e13ae151a43fbb124419bc0ce,Fast Person Re-identification via Cross-Camera Semantic Binary Transformation,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+91cc3981c304227e13ae151a43fbb124419bc0ce,Fast Person Re-identification via Cross-Camera Semantic Binary Transformation,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+91cc3981c304227e13ae151a43fbb124419bc0ce,Fast Person Re-identification via Cross-Camera Semantic Binary Transformation,University of East Anglia,University of East Anglia,"Arts (Lower Walkway Level), The Square, Westfield View, Earlham, Norwich, Norfolk, East of England, England, NR4 7TJ, UK",52.62215710,1.24091360,edu,
+91a4ebf1ca0314a74c436729700ef09bddaa6222,Detailed Human Avatars from Monocular Video,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+9114f5247562c0a71ea9aef23d474e06dd96d8cb,Neural Sign Language Translation,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+9114f5247562c0a71ea9aef23d474e06dd96d8cb,Neural Sign Language Translation,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+91d216e72a774b10c1eac9bce5b1046fac8c8a97,Garments Texture Design Class Identification Using Deep Convolutional Neural Network,University of Dhaka,University of Dhaka,"World War Memorial, Shahid Minar Rd, Jagannath Hall, DU, জিগাতলা, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.73169570,90.39652750,edu,
+91f9f6623abc51086183cf1d2ea9954f503061fe,A2-Nets: Double Attention Networks,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+91f9f6623abc51086183cf1d2ea9954f503061fe,A2-Nets: Double Attention Networks,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+91f9f6623abc51086183cf1d2ea9954f503061fe,A2-Nets: Double Attention Networks,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+91f9f6623abc51086183cf1d2ea9954f503061fe,A2-Nets: Double Attention Networks,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
9103148dd87e6ff9fba28509f3b265e1873166c9,Face Analysis using 3D Morphable Models,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
9103148dd87e6ff9fba28509f3b265e1873166c9,Face Analysis using 3D Morphable Models,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+91b8f1e4299b0f7ad716ece76565c6689d5d1b98,"How clever is the FiLM model, and how clever can it be?",University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+91b8f1e4299b0f7ad716ece76565c6689d5d1b98,"How clever is the FiLM model, and how clever can it be?",University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+91b8f1e4299b0f7ad716ece76565c6689d5d1b98,"How clever is the FiLM model, and how clever can it be?",University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+9194c206269a09c251cb3d1c878f9f11639b053a,A New Feature Extraction Method Based on the Information Fusion of Entropy Matrix and Covariance Matrix and Its Application in Face Recognition,Yunnan University,Yunnan University,"云南大学, 一二一大街, 志城家园, 五华区, 五华区 (Wuhua), 昆明市 (Kunming), 云南省, 650030, 中国",25.05703205,102.70027525,edu,
+91bf682708317b1c84365ce9589c4c1d9fc014e8,Style Separation and Synthesis via Generative Adversarial Networks,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+91bf682708317b1c84365ce9589c4c1d9fc014e8,Style Separation and Synthesis via Generative Adversarial Networks,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+91bf682708317b1c84365ce9589c4c1d9fc014e8,Style Separation and Synthesis via Generative Adversarial Networks,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
65b737e5cc4a565011a895c460ed8fd07b333600,Transfer Learning for Cross-Dataset Recognition: A Survey,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
65b737e5cc4a565011a895c460ed8fd07b333600,Transfer Learning for Cross-Dataset Recognition: A Survey,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
65b737e5cc4a565011a895c460ed8fd07b333600,Transfer Learning for Cross-Dataset Recognition: A Survey,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
+6555ef4e6f9582b5cb06199a70d4f54df04314ff,Part-based clothing segmentation for person retrieval,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+65f0b05052c3145a58c2653821e5429ca62555ce,Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
65b1760d9b1541241c6c0222cc4ee9df078b593a,Enhanced Pictorial Structures for Precise Eye Localization Under Uncontrolled Conditions,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+65355cbb581a219bd7461d48b3afd115263ea760,Recognition of ongoing complex activities by sequence prediction over a hierarchical label space,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+65bccb76384bc95c8fe53f2d2a8e3f048fd880bf,Bi-label Propagation for Generic Multiple Object Tracking,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+65bccb76384bc95c8fe53f2d2a8e3f048fd880bf,Bi-label Propagation for Generic Multiple Object Tracking,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
65d7f95fcbabcc3cdafc0ad38e81d1f473bb6220,Face Recognition for the Visually Impaired,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
+65150ea455cf30ff75a73c1d25df84687d4930e4,3D Object Retrieval and Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
65bba9fba03e420c96ec432a2a82521ddd848c09,Connectionist Temporal Modeling for Weakly Supervised Action Labeling,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
656531036cee6b2c2c71954bb6540ef6b2e016d0,Jointly Learning Non-negative Projection and Dictionary with Discriminative Graph Constraints for Classification,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
656531036cee6b2c2c71954bb6540ef6b2e016d0,Jointly Learning Non-negative Projection and Dictionary with Discriminative Graph Constraints for Classification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
656531036cee6b2c2c71954bb6540ef6b2e016d0,Jointly Learning Non-negative Projection and Dictionary with Discriminative Graph Constraints for Classification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+65683bd97720bc18a022b23755b32c8c988e8d5c,Discovering social groups via latent structure learning.,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+65683bd97720bc18a022b23755b32c8c988e8d5c,Discovering social groups via latent structure learning.,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
652aac54a3caf6570b1c10c993a5af7fa2ef31ff,"Carnegie Mellon University Statistical Modeling for Networked Video : Coding Optimization , Error Concealment and Traffic Analysis",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
652aac54a3caf6570b1c10c993a5af7fa2ef31ff,"Carnegie Mellon University Statistical Modeling for Networked Video : Coding Optimization , Error Concealment and Traffic Analysis",Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+6506f9a8a2e73eeaea185273df909feccb68f944,Research on Dynamic Facial Expressions Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
656ef752b363a24f84cc1aeba91e4fa3d5dd66ba,Robust Open-Set Face Recognition for Small-Scale Convenience Applications,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+656268296532913eb34929e82ee19808429de06a,Amygdala Engagement in Response to Subthreshold Presentations of Anxious Face Stimuli in Adults with Autism Spectrum Disorders: Preliminary Insights,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
+656268296532913eb34929e82ee19808429de06a,Amygdala Engagement in Response to Subthreshold Presentations of Anxious Face Stimuli in Adults with Autism Spectrum Disorders: Preliminary Insights,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
+65b51d3e0b46e80236d496b25b424d22c6de4348,Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
6577c76395896dd4d352f7b1ee8b705b1a45fa90,Towards computational models of kinship verification,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
6577c76395896dd4d352f7b1ee8b705b1a45fa90,Towards computational models of kinship verification,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+6577a11fc1e022670a0867ca2622b72ef225616e,Conservative learning for learning object detectors,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+65fbd8c6b6a8814c3d8b28b4e14b2e262e60c58c,Bridging Cognitive Programs and Machine Learning,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+6583e5e9c01da5d70a9ccba799fd53bc4ec015d6,Deep Regression Bayesian Network and Its Applications,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+65c978a97f54cf255f01c6846d6c51b37c61f836,A Glimpse Far into the Future: Understanding Long-term Crowd Worker Accuracy,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
650bfe7acc3f03eb4ba91d9f93da8ef0ae8ba772,A Deep Learning Approach for Subject Independent Emotion Recognition from Facial Expressions,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+6577d30abd8bf5b21901572504bd82101a7eed75,Ear Biometrics in Human,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
65293ecf6a4c5ab037a2afb4a9a1def95e194e5f,"Face , Age and Gender Recognition using Local Descriptors",Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
65293ecf6a4c5ab037a2afb4a9a1def95e194e5f,"Face , Age and Gender Recognition using Local Descriptors",University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
+658eb1fd14808d10e0f4fee99c5506a1bb0e351a,Multi-Discriminant Classification Algorithm for Face Verification,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
6515fe829d0b31a5e1f4dc2970a78684237f6edb,Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
6515fe829d0b31a5e1f4dc2970a78684237f6edb,Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+65086cbda9714c538417f7b25f9cf661e6d72833,Tracking Using Motion Patterns for Very Crowded Scenes,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+65821b839b8c6ecf6cba7be0ca132da59075e1b4,"Preliminary studies on the Good, the Bad, and the Ugly face recognition challenge problem",Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
6261eb75066f779e75b02209fbd3d0f02d3e1e45,Fudan-Huawei at MediaEval 2015: Detecting Violent Scenes and Affective Impact in Movies with Deep Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
622daa25b5e6af69f0dac3a3eaf4050aa0860396,Greedy feature selection for subspace clustering,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
622daa25b5e6af69f0dac3a3eaf4050aa0860396,Greedy feature selection for subspace clustering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
622daa25b5e6af69f0dac3a3eaf4050aa0860396,Greedy feature selection for subspace clustering,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
+624706748e2e62a4e07ae761543da6d41e3f8fcd,Language Grounding in Massive Online Data,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+62d9750adb300cd53fb107b174cb6a07fb8b96b5,Using 3D Models to Recognize 2D Faces in the Wild,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+6293d33e176ba7ccd59e94f8a137876c1d581e1f,Holistic features for real-time crowd behaviour anomaly detection,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
628a3f027b7646f398c68a680add48c7969ab1d9,Plan for Final Year Project : HKU-Face : A Large Scale Dataset for Deep Face Recognition,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
626913b8fcbbaee8932997d6c4a78fe1ce646127,Learning from Millions of 3D Scans for Large-scale 3D Face Recognition,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+621227db6a9b0ad374cf737fea3760b49c4de42c,Hardware Trojan Attacks on Neural Networks,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
6226f2ea345f5f4716ac4ddca6715a47162d5b92,Object Detection: Current and Future Directions,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
6226f2ea345f5f4716ac4ddca6715a47162d5b92,Object Detection: Current and Future Directions,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
6226f2ea345f5f4716ac4ddca6715a47162d5b92,Object Detection: Current and Future Directions,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
6226f2ea345f5f4716ac4ddca6715a47162d5b92,Object Detection: Current and Future Directions,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
6226f2ea345f5f4716ac4ddca6715a47162d5b92,Object Detection: Current and Future Directions,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
62e913431bcef5983955e9ca160b91bb19d9de42,Facial Landmark Detection with Tweaked Convolutional Neural Networks,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
+62beb92e4de7b682619eba0aa39c14a39c95718f,Towards Effective Deep Embedding for Zero-Shot Learning,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+62beb92e4de7b682619eba0aa39c14a39c95718f,Towards Effective Deep Embedding for Zero-Shot Learning,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
624e9d9d3d941bab6aaccdd93432fc45cac28d4b,Object-Scene Convolutional Neural Networks for event recognition in images,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
624e9d9d3d941bab6aaccdd93432fc45cac28d4b,Object-Scene Convolutional Neural Networks for event recognition in images,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
624496296af19243d5f05e7505fd927db02fd0ce,Gauss-Newton Deformable Part Models for Face Alignment In-the-Wild,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
624496296af19243d5f05e7505fd927db02fd0ce,Gauss-Newton Deformable Part Models for Face Alignment In-the-Wild,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+62f7de0e26f5716beb32b9d14e646e76b3a2e2af,Continuous Hyper-parameter Learning for Support Vector Machines,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
62fd622b3ca97eb5577fd423fb9efde9a849cbef,Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
62fd622b3ca97eb5577fd423fb9efde9a849cbef,Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
62fd622b3ca97eb5577fd423fb9efde9a849cbef,Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
621ff353960d5d9320242f39f85921f72be69dc8,Explicit occlusion detection based deformable fitting for facial landmark localization,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+62b83bf64f200ebb9fa16dfb7108b85e390b2207,Semantic Labeling in Very High Resolution Images via a Self-Cascaded Convolutional Neural Network,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+62b83bf64f200ebb9fa16dfb7108b85e390b2207,Semantic Labeling in Very High Resolution Images via a Self-Cascaded Convolutional Neural Network,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+62b83bf64f200ebb9fa16dfb7108b85e390b2207,Semantic Labeling in Very High Resolution Images via a Self-Cascaded Convolutional Neural Network,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
621e8882c41cdaf03a2c4a986a6404f0272ba511,On robust biometric identity verification via sparse encoding of faces: Holistic vs local approaches,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
621f656fedda378ceaa9c0096ebb1556a42e5e0f,Single Sample Face Recognition from Video via Stacked Supervised Auto-Encoder,Rio de Janeiro State University,Rio de Janeiro State University,"UERJ, 524, Rua São Francisco Xavier, Maracanã, Zona Norte do Rio de Janeiro, Rio de Janeiro, Microrregião Rio de Janeiro, Região Metropolitana do Rio de Janeiro, RJ, Região Sudeste, 20550-900, Brasil",-22.91117105,-43.23577971,edu,
+62aaa33c46a7c4c2d8a80c81954101576200799d,Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+629b1bdf4d96bb41f7d3fce5c7d5617515303b71,Diving Deeper into IM2GPS,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+629b1bdf4d96bb41f7d3fce5c7d5617515303b71,Diving Deeper into IM2GPS,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+62dc594c1eac220d2116506d187d9fdd5ff8e795,Robust multi-view pedestrian tracking using neural networks,University of Dayton,University of Dayton,"University of Dayton, Caldwell Street, South Park Historic District, Dayton, Montgomery, Ohio, 45409, USA",39.73844400,-84.17918747,edu,
+62035628c85e13c10db4dfe2acedc5741874fc2e,Auto-Context R-CNN,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+9635d5e2b33b2fec49b31cb80928c28763a90d85,Semantic Image Inpainting with Deep Generative Models,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
965f8bb9a467ce9538dec6bef57438964976d6d9,Recognizing human faces under disguise and makeup,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
961a5d5750f18e91e28a767b3cb234a77aac8305,Face Detection without Bells and Whistles,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+96fb791de077106501397151d5cb4f245330ddba,Recurrent Transformer Networks for Semantic Correspondence,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
96f0e7416994035c91f4e0dfa40fd45090debfc5,Unsupervised Learning of Face Representations,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+9677d2f6a994f598c1d631038d49401c5f707ee0,"See, Hear, and Read: Deep Aligned Representations",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+96fda2ce5803979ba0295413b2750e9733619dd5,Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+96fda2ce5803979ba0295413b2750e9733619dd5,Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+96fda2ce5803979ba0295413b2750e9733619dd5,Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+96ad3c4455a9b05fb6db749495b4ae26a6fb2fab,HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+96ad3c4455a9b05fb6db749495b4ae26a6fb2fab,HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+96416b1b44fb05302c6e9a8ab1b74d9204995e73,Learning Effective Binary Visual Representations with Deep Networks,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+96c866f07ff999ee11459519aa361fa4fdfc2139,Consensus-based Sequence Training for Video Captioning,"National Institute of Informatics, Japan","National Institute of Informatics, Japan","2 Chome-1-２ Hitotsubashi, Chiyoda, Tokyo 100-0003, Japan",35.69248530,139.75825330,edu,
+96921b313f4c8dd6cb2299de1a24d4e9803ffdc1,Discovery of Visual Semantics by Unsupervised and Self-Supervised Representation Learning,University of Chicago,THE UNIVERSITY OF CHICAGO,"University of Chicago, South Ellis Avenue, Woodlawn, Chicago, Cook County, Illinois, 60637, USA",41.78468745,-87.60074933,edu,
963d0d40de8780161b70d28d2b125b5222e75596,Convolutional Experts Constrained Local Model for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
963d0d40de8780161b70d28d2b125b5222e75596,Convolutional Experts Constrained Local Model for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
963d0d40de8780161b70d28d2b125b5222e75596,Convolutional Experts Constrained Local Model for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
@@ -2610,51 +7135,152 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 969fd48e1a668ab5d3c6a80a3d2aeab77067c6ce,End-To-End Face Detection and Recognition,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
969fd48e1a668ab5d3c6a80a3d2aeab77067c6ce,End-To-End Face Detection and Recognition,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
96a9ca7a8366ae0efe6b58a515d15b44776faf6e,Grid Loss: Detecting Occluded Faces,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+969c4d89d7b22b36d8fc569156ca6e040b31565d,Soft Biometric Recognition from Comparative Crowdsourced Annotations,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+968ab65077c4be1c1071120052b2e4b4f3d3c59a,"""Seeing is believing: the quest for multimodal knowledge"" by Gerard de Melo and Niket Tandon, with Martin Vesely as coordinator",Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+968ab65077c4be1c1071120052b2e4b4f3d3c59a,"""Seeing is believing: the quest for multimodal knowledge"" by Gerard de Melo and Niket Tandon, with Martin Vesely as coordinator",Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+9612fd66fcd3902bc267a62c146398eb8d30830e,Classifying Actions and Measuring Action Similarity by Modeling the Mutual Context of Objects and Human Poses,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+96eacc464c0177efc4f802f220888c7f675f24af,Deep Semantic Face Deblurring Supplementary Material,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+9648a3790c62cee4253299f21368ce8028e3c8a6,MESO: Perceptual Memory to Support Online Learning in Adaptive Software,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
96e1ccfe96566e3c96d7b86e134fa698c01f2289,Semi-adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
96e1ccfe96566e3c96d7b86e134fa698c01f2289,Semi-adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+96bf907ec08df2d3176be66f369e3cc3d6cdc7f7,Environment Upgrade Reinforcement Learning for Non-differentiable Multi-stage Pipelines,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+96bf907ec08df2d3176be66f369e3cc3d6cdc7f7,Environment Upgrade Reinforcement Learning for Non-differentiable Multi-stage Pipelines,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+9696ad8b164f5e10fcfe23aacf74bd6168aebb15,4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+9696ad8b164f5e10fcfe23aacf74bd6168aebb15,4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications,Middlesex University,Middlesex University,"Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK",51.59029705,-0.22963221,edu,
9627f28ea5f4c389350572b15968386d7ce3fe49,Load Balanced GANs for Multi-view Face Image Synthesis,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
966e36f15b05ef8436afecf57a97b73d6dcada94,Dimensionality Reduction using Relative Attributes,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+96b4124cf7626301ed3bb2d2b2233a490804e35e,Saliency-Based Deformable Model for Pedestrian Detection,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+96b4124cf7626301ed3bb2d2b2233a490804e35e,Saliency-Based Deformable Model for Pedestrian Detection,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+96b4124cf7626301ed3bb2d2b2233a490804e35e,Saliency-Based Deformable Model for Pedestrian Detection,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+961e411c99d8ca6807076c4fb18e2d63a383aa0f,Non-negative matrix factorization methods for face recognition under extreme lighting variations,University of Oradea,University of Oradea,"Universitatea Creștină Partium - Clădirea Sulyok, 27, Strada Primăriei, Orașul Nou, Oradea, Bihor, 410209, România",47.05702220,21.92270900,edu,
+965faca4b89047ca0c90df0f12c06bc4cb9ec2dc,Statistical binary pattern and post-competitive representation for pattern recognition,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
+965faca4b89047ca0c90df0f12c06bc4cb9ec2dc,Statistical binary pattern and post-competitive representation for pattern recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
96578785836d7416bf2e9c154f687eed8f93b1e4,Automated video-based facial expression analysis of neuropsychiatric disorders.,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+96858cea5e9c72a93d438b6ba8d9e027db5416a7,Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+96858cea5e9c72a93d438b6ba8d9e027db5416a7,Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+969ed0575736943c2db62793583f99365d10fbac,Elevated amygdala response to faces following early deprivation.,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+969ed0575736943c2db62793583f99365d10fbac,Elevated amygdala response to faces following early deprivation.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+960870523484a7f66cf8afbe833afd7d343b68f5,Improving Gait Biometrics under Spoofing Attacks,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+960870523484a7f66cf8afbe833afd7d343b68f5,Improving Gait Biometrics under Spoofing Attacks,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+96094b030013ca2d9b6d5a14b6f1fbbc57eb8a89,What is in that picture ? Visual Question Answering System,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
96e0cfcd81cdeb8282e29ef9ec9962b125f379b0,The MegaFace Benchmark: 1 Million Faces for Recognition at Scale,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
96c6f50ce8e1b9e8215b8791dabd78b2bbd5f28d,Dynamic Attention-Controlled Cascaded Shape Regression Exploiting Training Data Augmentation and Fuzzy-Set Sample Weighting,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
96c6f50ce8e1b9e8215b8791dabd78b2bbd5f28d,Dynamic Attention-Controlled Cascaded Shape Regression Exploiting Training Data Augmentation and Fuzzy-Set Sample Weighting,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
96e731e82b817c95d4ce48b9e6b08d2394937cf8,Unconstrained face verification using deep CNN features,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
3a27d164e931c422d16481916a2fa6401b74bcef,Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+3a345ab83d1bfe4a63d3d44bc4ed243e10255a59,JOANNEUM RESEARCH and Vienna University of Technology at TRECVID 2010,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
3af8d38469fb21368ee947d53746ea68cd64eeae,Multimodal Intelligent Affect Detection with Kinect (Doctoral Consortium),Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
3af8d38469fb21368ee947d53746ea68cd64eeae,Multimodal Intelligent Affect Detection with Kinect (Doctoral Consortium),Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
3af8d38469fb21368ee947d53746ea68cd64eeae,Multimodal Intelligent Affect Detection with Kinect (Doctoral Consortium),Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+3aa53e8bb0a1a7e6d5fe4de146af92cd816755f4,Machine Understanding of Human Behavior,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+3aa53e8bb0a1a7e6d5fe4de146af92cd816755f4,Machine Understanding of Human Behavior,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+3aa53e8bb0a1a7e6d5fe4de146af92cd816755f4,Machine Understanding of Human Behavior,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+3aa53e8bb0a1a7e6d5fe4de146af92cd816755f4,Machine Understanding of Human Behavior,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+3a3a4408432408b62e2dc22de7820a5a2f7bbe9e,No Spare Parts: Sharing Part Detectors for Image Categorization,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+3a3a4408432408b62e2dc22de7820a5a2f7bbe9e,No Spare Parts: Sharing Part Detectors for Image Categorization,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+3aea679168c72c6df7ead45d4f7f1fd7f3680a11,Towards Accurate Multi-person Pose Estimation in the Wild,Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
+3ad6bd5c34b0866019b54f5976d644326069cb3d,Towards Next Generation Touring: Personalized Group Tours,RMIT University,RMIT University,"RMIT University, 124, La Trobe Street, Melbourne City, City of Melbourne, Victoria, 3000, Australia",-37.80874650,144.96388750,edu,
3a3f75e0ffdc0eef07c42b470593827fcd4020b4,Normal Similarity Network for Generative Modelling,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
3a76e9fc2e89bdd10a9818f7249fbf61d216efc4,Face Sketch Matching via Coupled Deep Transform Learning,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
3a2c90e0963bfb07fc7cd1b5061383e9a99c39d2,End-to-End Deep Learning for Steering Autonomous Vehicles Considering Temporal Dependencies,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
+3a95bfa1d4a989b162e07fa69b85cb6d31a674ab,Linear Ranking Analysis,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
3a0ea368d7606030a94eb5527a12e6789f727994,Categorization by Learning and Combining Object Parts,University of Siena,University of Siena,"大學 University, 澤祥街 Chak Cheung Street, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.41338620,114.21005800,edu,
3a04eb72aa64760dccd73e68a3b2301822e4cdc3,Scalable Sparse Subspace Clustering,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+3a40059e9dc4b19ae7f49b8746d8dda22456767f,Geometry-Aware Face Completion and Editing,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+3a53bad58f8467092477857ff9c2ae904d7108d2,Simultaneous perceptual and response biases on sequential face attractiveness judgments.,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+3a53bad58f8467092477857ff9c2ae904d7108d2,Simultaneous perceptual and response biases on sequential face attractiveness judgments.,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+3a1c3307f57ef09577ac0dc8cd8b090a4fe8091f,Thermal-to-visible face recognition using partial least squares.,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
3af130e2fd41143d5fc49503830bbd7bafd01f8b,How Do We Evaluate the Quality of Computational Editing Systems?,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
3a2cf589f5e11ca886417b72c2592975ff1d8472,Spontaneously Emerging Object Part Segmentation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3a2cf589f5e11ca886417b72c2592975ff1d8472,Spontaneously Emerging Object Part Segmentation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3ada7640b1c525056e6fcd37eea26cd638815cd6,Abnormal Object Recognition: A Comprehensive Study,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
3ada7640b1c525056e6fcd37eea26cd638815cd6,Abnormal Object Recognition: A Comprehensive Study,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+3a4779f3f73d2ebfaccbc0dad0bdbf7ac0570c0d,Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+3ab93fe26a46f8bc0999e68af71a0907a63a5e65,ESTHER: Extremely Simple Image Translation Through Self-Regularization,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+3a55188f8ee3abe6d179d16984885be6e3b6daf5,Learning Cross-Modal Deep Representations for Robust Pedestrian Detection,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+3a55188f8ee3abe6d179d16984885be6e3b6daf5,Learning Cross-Modal Deep Representations for Robust Pedestrian Detection,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+3a4a908350d856577ac48caec10c0809e8396acf,"Zero-effort payments: design, deployment, and lessons",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+3a2d3514b5cdccdb4c13aadb3929f3a78c03f020,"Deep semantic segmentation for automated driving: Taxonomy, roadmap and challenges",University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+3a27bdb9925d5b247868950a9575823b3194ac8b,Adaptation across the cortical hierarchy: low-level curve adaptation affects high-level facial-expression judgments.,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+3a5f5aca6138abcf22ede1af5572e01eb0f761d1,Optimizing Multivariate Performance Measures from Multi-View Data,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+3ac78d0fd4f0c01650277bb25eab6957d4eeb655,Multimodal Memory Modelling for Video Captioning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
3af1a375c7c1decbcf5c3a29774e165cafce390c,Quantifying Facial Expression Abnormality in Schizophrenia by Combining 2D and 3D Features,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
3af1a375c7c1decbcf5c3a29774e165cafce390c,Quantifying Facial Expression Abnormality in Schizophrenia by Combining 2D and 3D Features,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+3ad2b6c283b1c4687c4f782efb64a209d3cf4cfe,Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+3ad2b6c283b1c4687c4f782efb64a209d3cf4cfe,Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
3a2a37ca2bdc82bba4c8e80b45d9f038fe697c7d,Handling Uncertain Tags in Visual Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+3a888bf996bcac3feb7e130543df9ec8287db515,End-to-End Learning of Driving Models from Large-Scale Video Datasets,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+3a307b7e2e742dd71b6d1ca7fde7454f9ebd2811,Bilinear CNN Models for Fine-Grained Visual Recognition,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+3a818a5fe2c36ff29212b4da9f4fba3280dfd497,Mobile Product Image Search by Automatic Query Object Extraction,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+3ab0b3c02f4fa7f1d14315599f4f91563ae565f8,Canonical Time Warping for Alignment of Human Behavior,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+3ab0b3c02f4fa7f1d14315599f4f91563ae565f8,Canonical Time Warping for Alignment of Human Behavior,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+3ab0b3c02f4fa7f1d14315599f4f91563ae565f8,Canonical Time Warping for Alignment of Human Behavior,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+3ab0b3c02f4fa7f1d14315599f4f91563ae565f8,Canonical Time Warping for Alignment of Human Behavior,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+3a6ebdfb6375093885e846153a48139ef1ecfae6,The treasure beneath convolutional layers: Cross-convolutional-layer pooling for image classification,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+3a39cb039fb0f569ab88dfb058d98650a17c9f5c,Structured max-margin learning for multi-label image annotation,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+3a39cb039fb0f569ab88dfb058d98650a17c9f5c,Structured max-margin learning for multi-label image annotation,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+3a387304d18f2786ee83804bd38efecc2a5fd323,Person Re-Identification Using Multiple Experts with Random Subspaces,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+3ad9f6c1d10a2d1e86c93a4182ee3b260a6f3edd,Object Detection and Tracking in Wide Area Surveillance Using Thermal Imagery,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
54948ee407b5d32da4b2eee377cc44f20c3a7e0c,Right for the Right Reason: Training Agnostic Networks,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+544519fa0794d41a04307973156016b6c679ffa5,Switchable Deep Network for Pedestrian Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+544519fa0794d41a04307973156016b6c679ffa5,Switchable Deep Network for Pedestrian Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+544519fa0794d41a04307973156016b6c679ffa5,Switchable Deep Network for Pedestrian Detection,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+545388d4a8e79cab605cea9b3e1ff1da0f848f8e,Fast Online Upper Body Pose Estimation from Video,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+545388d4a8e79cab605cea9b3e1ff1da0f848f8e,Fast Online Upper Body Pose Estimation from Video,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+54ffc4c83974d5915025f80e54e350cd30ef96d7,Sparse dictionary-based representation and recognition of action attributes,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+54abfe3acd987b5041878c29ec74204a11e73ad1,Holistic Planimetric prediction to Local Volumetric prediction for 3D Human Pose Estimation,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+54abfe3acd987b5041878c29ec74204a11e73ad1,Holistic Planimetric prediction to Local Volumetric prediction for 3D Human Pose Estimation,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+54abfe3acd987b5041878c29ec74204a11e73ad1,Holistic Planimetric prediction to Local Volumetric prediction for 3D Human Pose Estimation,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
54bb25a213944b08298e4e2de54f2ddea890954a,"AgeDB: The First Manually Collected, In-the-Wild Age Database",Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
54bb25a213944b08298e4e2de54f2ddea890954a,"AgeDB: The First Manually Collected, In-the-Wild Age Database",Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
54bb25a213944b08298e4e2de54f2ddea890954a,"AgeDB: The First Manually Collected, In-the-Wild Age Database",Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
54bb25a213944b08298e4e2de54f2ddea890954a,"AgeDB: The First Manually Collected, In-the-Wild Age Database",Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
54bb25a213944b08298e4e2de54f2ddea890954a,"AgeDB: The First Manually Collected, In-the-Wild Age Database",Middlesex University,Middlesex University,"Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK",51.59029705,-0.22963221,edu,
54bb25a213944b08298e4e2de54f2ddea890954a,"AgeDB: The First Manually Collected, In-the-Wild Age Database",Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+54171243dfae9d7343c78026c9b94004df3853bb,"ResnetCrowd: A residual deep learning architecture for crowd counting, violent behaviour detection and crowd density level classification",Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+549d55a06c5402696e063ce36b411f341a64f8a9,Learning Deep Structure-Preserving Image-Text Embeddings,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+549d55a06c5402696e063ce36b411f341a64f8a9,Learning Deep Structure-Preserving Image-Text Embeddings,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+5484ad04ac0a256b51fd1a3eae48483480862ab1,A survey on ear biometrics,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+5484ad04ac0a256b51fd1a3eae48483480862ab1,A survey on ear biometrics,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+5484ad04ac0a256b51fd1a3eae48483480862ab1,A survey on ear biometrics,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+5484ad04ac0a256b51fd1a3eae48483480862ab1,A survey on ear biometrics,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
54bae57ed37ce50e859cbc4d94d70cc3a84189d5,Face recognition committee machine,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
54f442c7fa4603f1814ebd8eba912a00dceb5cb2,The Indian Buffet Process: Scalable Inference and Extensions,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+548318d42e251b3ed7d98748a07cfcfcd0594575,Automatic Object Detection and Segmentation of the Histocytology Images Using Reshapable Agents,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+5418242dafa134e6021a30ecc8c566ac83823b56,Disentangled Person Image Generation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+541d69fdf97e5ded611ad0dd46f62bb9d2e19a51,SHESHADRI ET AL.: EXEMPLAR DRIVEN CHARACTER RECOGNITION IN THE WILD 1 Exemplar Driven Character Recognition in the Wild,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+541d69fdf97e5ded611ad0dd46f62bb9d2e19a51,SHESHADRI ET AL.: EXEMPLAR DRIVEN CHARACTER RECOGNITION IN THE WILD 1 Exemplar Driven Character Recognition in the Wild,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+54fc3551b3b08767d5d731092f10ba4573a2c822,Assessment of H.264 Video Compression on Automated Face Recognition Performance in Surveillance and Mobile Video Scenarios,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
54a9ed950458f4b7e348fa78a718657c8d3d0e05,Learning Neural Models for End-to-End Clustering,Ulm University,Ulm University,"HNU, John-F.-Kennedy-Straße, Vorfeld, Wiley, Neu-Ulm, Landkreis Neu-Ulm, Schwaben, Bayern, 89231, Deutschland",48.38044335,10.01010115,edu,
541f1436c8ffef1118a0121088584ddbfd3a0a8a,A Spatio-temporal Feature Based on Triangulation of Dense SURF,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
54ce3ff2ab6e4465c2f94eb4d636183fa7878ab7,Local Centroids Structured Non-Negative Matrix Factorization,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
54ce3ff2ab6e4465c2f94eb4d636183fa7878ab7,Local Centroids Structured Non-Negative Matrix Factorization,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+5409d9ff06ad715ee6996e44c88f930b9dd074fa,See all by looking at a few: Sparse modeling for finding representative objects,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+542015e2c78c51203963b76632b7ea2a6c46aa74,DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+54b16b233e6130354e7d3f0d001cc5491f85e998,Real-time fMRI-based neurofeedback in depression,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+5417bd72d1b787ade0c485f1188189474c199f4d,MAGAN: Margin Adaptation for Generative Adversarial Networks,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+54568bdce3405ffbe2a6f5820711f966e2d2faf3,How Do We Update Faces? Effects of Gaze Direction and Facial Expressions on Working Memory Updating,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+54d97ea9a5f92761dddd148fb0e602c2293e7c16,Associating Inter-image Salient Instances for Weakly Supervised Semantic Segmentation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+54d97ea9a5f92761dddd148fb0e602c2293e7c16,Associating Inter-image Salient Instances for Weakly Supervised Semantic Segmentation,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+545dc167a4879ce2d61836cb300479c305f8e096,Event-Centric Twitter Photo Summarization,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+544c06584c95bfdcafbd62e04fb796e575981476,Human Identification from Body Shape,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
5495e224ac7b45b9edc5cfeabbb754d8a40a879b,Feature Reconstruction Disentangling for Pose-invariant Face Recognition Supplementary Material,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+548a0523c9e66b793f2145dbd05dcb4d32fccfec,Joint Action Unit localisation and intensity estimation through heatmap regression,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
54204e28af73c7aca073835a14afcc5d8f52a515,Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+540831094fd9b80469c8dacb9320b7e342b50e03,Emotion Recognition in Speech using Cross-Modal Transfer in the Wild,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+54c5fad54492650f6eccb90bafcab8c2b779ee2f,Real-time text tracking in natural scenes,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+98324ad5027c6b163d7a670570ffe2f8df70717c,LSTM Pose Machines,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+98a18702cd9be53341f12c0e711df9d985120ad7,Feature Extraction and Localisation using Scale-Invariant Feature Transform on 2.5D Image,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
98142103c311b67eeca12127aad9229d56b4a9ff,GazeDirector: Fully Articulated Eye Gaze Redirection in Video,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
98142103c311b67eeca12127aad9229d56b4a9ff,GazeDirector: Fully Articulated Eye Gaze Redirection in Video,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
9820920d4544173e97228cb4ab8b71ecf4548475,Automated facial coding software outperforms people in recognizing neutral faces as neutral from standardized datasets,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
9820920d4544173e97228cb4ab8b71ecf4548475,Automated facial coding software outperforms people in recognizing neutral faces as neutral from standardized datasets,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+98143f005c6d18ecb9e5b21a8ac6fb9f0b6b5005,Coherent Object Detection with 3D Geometric Context from a Single Image,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+98b54eb04e531c34a20320e19b55f6721bd0d651,Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+988aa2583c63ada43ca260dd8b5a4a543725a483,Choosing the Right Home Location Definition Method for the Given Dataset,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+98bb029afe2a1239c3fdab517323066f0957b81b,Person Re-identification by Video Ranking,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+98bb029afe2a1239c3fdab517323066f0957b81b,Person Re-identification by Video Ranking,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+98f7081ed27e250d1f974d89377d1fbd3f78a347,Towards Automated Inferencing of Emotional State from Face Images,University of Piraeus,University of Piraeus,"Πανεπιστήμιο Πειραιώς, 80, Καραολή και Δημητρίου, Απόλλωνας, Νέο Φάληρο, Πειραιάς, Δήμος Πειραιώς, Περιφερειακή Ενότητα Πειραιώς, Περιφέρεια Αττικής, Αττική, 185 34, Ελλάδα",37.94173275,23.65303262,edu,
989332c5f1b22604d6bb1f78e606cb6b1f694e1a,Recurrent Face Aging,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
989332c5f1b22604d6bb1f78e606cb6b1f694e1a,Recurrent Face Aging,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
989332c5f1b22604d6bb1f78e606cb6b1f694e1a,Recurrent Face Aging,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
@@ -2662,110 +7288,310 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 98af221afd64a23e82c40fd28d25210c352e41b7,Exploring visual features through Gabor representations for facial expression detection,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
98af221afd64a23e82c40fd28d25210c352e41b7,Exploring visual features through Gabor representations for facial expression detection,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
98af221afd64a23e82c40fd28d25210c352e41b7,Exploring visual features through Gabor representations for facial expression detection,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+98cfbe37a68406ef194354de7e5ea453c4ea9adf,Generating Synthetic X-ray Images of a Person from the Surface Geometry,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+98cfbe37a68406ef194354de7e5ea453c4ea9adf,Generating Synthetic X-ray Images of a Person from the Surface Geometry,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
9893865afdb1de55fdd21e5d86bbdb5daa5fa3d5,Illumination Normalization Using Logarithm Transforms for Face Authentication,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9838ba7a31a096503def7b69bf48e5d327f95caa,Emotion-Based Crowd Representation for Abnormality Detection,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+98025d3d44e9379736adb1228919272ded9298ae,Visual Question Answering Dataset for Bilingual Image Understanding: A Study of Cross-Lingual Transfer Using Attention Maps,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
9887ab220254859ffc7354d5189083a87c9bca6e,Generic Image Classification Approaches Excel on Face Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
9887ab220254859ffc7354d5189083a87c9bca6e,Generic Image Classification Approaches Excel on Face Recognition,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+9802885e39e0847374a2efae801b8b719c09c64c,"An Effective Two-Finger, Two-Stage Biometric Strategy for the US-VISIT Program",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+9899eb0ae24aa8c992244afe5f4455e9f96c1f18,"Characteristics of Brains in Autism Spectrum Disorder: Structure, Function and Connectivity across the Lifespan.",Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
985cd420c00d2f53965faf63358e8c13d1951fa8,Pixel-Level Hand Detection with Shape-Aware Structured Forests,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+98d04187f091f402a90a6a9a2108393ca5f91563,ADVIO: An Authentic Dataset for Visual-Inertial Odometry,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+98d04187f091f402a90a6a9a2108393ca5f91563,ADVIO: An Authentic Dataset for Visual-Inertial Odometry,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+989ca38616b52f23c2720ba5c6df2493dc025d0a,Markerless Feature Extraction for Gait Analysis,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+983f03659e42407b1779e407388ea86fa58043c6,Transferring activities: Updating human behavior analysis,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+98bda8768fd4a384695ecc736876a87f51c4ca0e,Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+98bda8768fd4a384695ecc736876a87f51c4ca0e,Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+987a649cb33302c41412419f8eeb77048aa5513e,Visual Psychophysics for Making Face Recognition Algorithms More Explainable,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+987a649cb33302c41412419f8eeb77048aa5513e,Visual Psychophysics for Making Face Recognition Algorithms More Explainable,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
9821669a989a3df9d598c1b4332d17ae8e35e294,Minimal Correlation Classification,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
9865fe20df8fe11717d92b5ea63469f59cf1635a,Wildest Faces: Face Detection and Recognition in Violent Settings,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
9865fe20df8fe11717d92b5ea63469f59cf1635a,Wildest Faces: Face Detection and Recognition in Violent Settings,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
98c2053e0c31fab5bcb9ce5386335b647160cc09,A Distributed Framework for Spatio-Temporal Analysis on Large-Scale Camera Networks,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
98c2053e0c31fab5bcb9ce5386335b647160cc09,A Distributed Framework for Spatio-Temporal Analysis on Large-Scale Camera Networks,University of Stuttgart,University of Stuttgart,"Pädagogische Hochschule Ludwigsburg, 46, Reuteallee, Ludwigsburg-Nord, Ludwigsburg, Landkreis Ludwigsburg, Regierungsbezirk Stuttgart, Baden-Württemberg, 71634, Deutschland",48.90953380,9.18318920,edu,
98c2053e0c31fab5bcb9ce5386335b647160cc09,A Distributed Framework for Spatio-Temporal Analysis on Large-Scale Camera Networks,SUNY Buffalo,SUNY Buffalo,"SUNY College at Buffalo, Academic Drive, Elmwood Village, Buffalo, Erie County, New York, 14222, USA",42.93362780,-78.88394479,edu,
+983bfb10fa228ecd1047ab4ac1d78c96448de059,Towards Person Identification and Re-identification with Attributes,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+989282f579fdca0ebdc890cf05cac88c29f9eb49,Benchmarking and Error Diagnosis in Multi-instance Pose Estimation,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
98fb3890c565f1d32049a524ec425ceda1da5c24,A Robust Learning Framework Using PSM and Ameliorated SVMs for Emotional Recognition,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+9841df3cc4dc89379039092816ef19af949257a8,LBP-based Hierarchical Sparse Patch Learning for Face Recognition,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+989c7cdafa9b90ab2ea0a9d8fa60634cc698f174,YoloFlow Real - time Object Tracking in Video CS 229 Course Project,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
9825c4dddeb2ed7eaab668b55403aa2c38bc3320,Aerial Imagery for Roof Segmentation: A Large-Scale Dataset towards Automatic Mapping of Buildings,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
9825c4dddeb2ed7eaab668b55403aa2c38bc3320,Aerial Imagery for Roof Segmentation: A Large-Scale Dataset towards Automatic Mapping of Buildings,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+985d032bd45c3b1a6434d19526f9209ade72691a,Robust Low-Rank Regularized Regression for Face Recognition with Occlusion,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+985d032bd45c3b1a6434d19526f9209ade72691a,Robust Low-Rank Regularized Regression for Face Recognition with Occlusion,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
980266ad6807531fea94252e8f2b771c20e173b3,Continuous Regression for Non-rigid Image Alignment,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+535ed3850e79ccd51922601546ef0fc48c5fb468,A feature embedding strategy for high-level CNN representations from multiple convnets,University of Windsor,University of Windsor,"Bridge AA, Ambassador Bridge, Windsor, Essex, Ontario, N9C 2J9, Canada",42.30791465,-83.07176915,edu,
+535ed3850e79ccd51922601546ef0fc48c5fb468,A feature embedding strategy for high-level CNN representations from multiple convnets,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
53d78c8dbac7c9be8eb148c6a9e1d672f1dd72f9,"Discriminative vs . Generative Object Recognition : Objects , Faces , and the Web",California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
533d14e539ae5cdca0ece392487a2b19106d468a,Bidirectional Multirate Reconstruction for Temporal Modeling in Videos,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+53eeb83d2c8085d5457b364354525730805b4332,Seeing 3D objects in a single 2D image,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+532f070082eb565704a2f6481ed64bdbc7e6aa24,Learning to Track at 100 FPS with Deep Regression Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+537328af75f50d49696972a6c34bca97c14bc762,Exploiting Unintended Feature Leakage in Collaborative Learning,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+532c089b43983935e1001c5e35aa35440263beaf,G-Distillation: Reducing Overconfident Errors on Novel Samples,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
53698b91709112e5bb71eeeae94607db2aefc57c,Two-Stream Convolutional Networks for Action Recognition in Videos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+536b1db1b1db8d4cfef813575304421ebe8332f7,A Procrustean Markov Process for Non-rigid Structure Recovery,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+53cf087dbcbe0c4b145297fb0a32732ab2b18b66,PSANet: Point-wise Spatial Attention Network for Scene Parsing,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+53cf087dbcbe0c4b145297fb0a32732ab2b18b66,PSANet: Point-wise Spatial Attention Network for Scene Parsing,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+5369b021f2abf5daa77fa5602569bb3b8bb18546,GMMCP tracker: Globally optimal Generalized Maximum Multi Clique problem for multiple object tracking,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+533d91cbb5e306c96b71b6f776382f3956e5dc7d,Faster Feature Engineering by Approximate Evaluation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+533d91cbb5e306c96b71b6f776382f3956e5dc7d,Faster Feature Engineering by Approximate Evaluation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+538c6000369594084b122c37b3219ad15b58cb37,Hierarchical Cascade of Classifiers for Efficient Poselet Evaluation,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
5394d42fd27b7e14bd875ec71f31fdd2fcc8f923,Visual Recognition Using Directional Distribution Distance,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+532f91d59d96d28379e09043592903d143218f4b,Cross-Domain Hallucination Network for Fine-Grained Object Recognition,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+532f91d59d96d28379e09043592903d143218f4b,Cross-Domain Hallucination Network for Fine-Grained Object Recognition,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
5397c34a5e396658fa57e3ca0065a2878c3cced7,Lighting normalization with generic intrinsic illumination subspace for face recognition,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
539287d8967cdeb3ef60d60157ee93e8724efcac,Learning Deep $\ell_0$ Encoders,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
539287d8967cdeb3ef60d60157ee93e8724efcac,Learning Deep $\ell_0$ Encoders,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
532f7ec8e0c8f7331417dd4a45dc2e8930874066,Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+532837c431617d37c03361ba5a7d5fdb082c55f4,Connecting Language and Vision to Actions,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+532837c431617d37c03361ba5a7d5fdb082c55f4,Connecting Language and Vision to Actions,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+5388638c7801b11958d937c89ece764bc769e298,Identity processing in multiple-face tracking.,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+5388638c7801b11958d937c89ece764bc769e298,Identity processing in multiple-face tracking.,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+5388638c7801b11958d937c89ece764bc769e298,Identity processing in multiple-face tracking.,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+5388638c7801b11958d937c89ece764bc769e298,Identity processing in multiple-face tracking.,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+5388638c7801b11958d937c89ece764bc769e298,Identity processing in multiple-face tracking.,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+5388638c7801b11958d937c89ece764bc769e298,Identity processing in multiple-face tracking.,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+5388638c7801b11958d937c89ece764bc769e298,Identity processing in multiple-face tracking.,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+539923c8f2f4641f71056b71e5628d1b9b633835,Mining actionlet ensemble for action recognition with depth cameras,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+539923c8f2f4641f71056b71e5628d1b9b633835,Mining actionlet ensemble for action recognition with depth cameras,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+539923c8f2f4641f71056b71e5628d1b9b633835,Mining actionlet ensemble for action recognition with depth cameras,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+5375149a74361b51d734613be5d2ccba0c6b6955,Boundary-Seeking Generative Adversarial Networks,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+5375149a74361b51d734613be5d2ccba0c6b6955,Boundary-Seeking Generative Adversarial Networks,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4,Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis,Binghamton University,Binghamton University,"Binghamton University Downtown Center, Washington Street, Downtown, Binghamton, Broome County, New York, 13901, USA",42.09580770,-75.91455689,edu,
+534f41985a7350261a03b8c0dc54e218115dc4a5,A Hierarchical Model of Shape and Appearance for Human Action Classification,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+534f41985a7350261a03b8c0dc54e218115dc4a5,A Hierarchical Model of Shape and Appearance for Human Action Classification,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+53d0227c40b354cc438c035951da801c9dcd87b7,Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+53d0227c40b354cc438c035951da801c9dcd87b7,Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+534ac5cd8e2503b333efcc94d92e5359b54190b1,3d Face Reconstruction Using Stereo Vision a Thesis Submitted to the Graduate School of Natural and Applied Sciences of Middle East Technical University by Mehmet Di̇kmen in Partial Fullfillment of the Requirements for the Degree of Master of Science,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+53c14feecdf23c40c594c25a0075c7150fa2f9e2,Blockwise Parallel Decoding for Deep Autoregressive Models,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
53bfe2ab770e74d064303f3bd2867e5bf7b86379,Learning to Synthesize and Manipulate Natural Images,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+53ee7e9839e1ac76e1168480a7e3227d568f4062,An Adaptive Descriptor Design for Object Recognition in the Wild,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+536b5739c2162301bff19730a65bfbe8b86179b6,Posebits for Monocular Human Pose Estimation,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
537d8c4c53604fd419918ec90d6ef28d045311d0,Active collaborative ensemble tracking,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+53df7d12472ee0c466a2bb59c4a17274858345de,Fine-Grained Visual Categorization with 2D-Warping,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
53ce84598052308b86ba79d873082853022aa7e9,Optimized Method for Real-Time Face Recognition System Based on PCA and Multiclass Support Vector Machine,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
3fe4109ded039ac9d58eb9f5baa5327af30ad8b6,Spatio-Temporal GrabCut human segmentation for face and pose recovery,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
3fefc856a47726d19a9f1441168480cee6e9f5bb,Perceptually Valid Dynamics for Smiles and Blinks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3fefc856a47726d19a9f1441168480cee6e9f5bb,Perceptually Valid Dynamics for Smiles and Blinks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+3f6474bc611ec790444ffa6e644a258f3d2aed37,Variational Capsules for Image Analysis and Synthesis,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
3f7cf52fb5bf7b622dce17bb9dfe747ce4a65b96,Person Identity Label Propagation in Stereo Videos,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+3f42db34a79cf600b416a246ad3fd146a4afbdf4,Context-Sensitive Decision Forests for Object Detection,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+3f4684674d2f62e24b46140e2c5df29d061ffea1,Deep Ordinal Regression Network for Monocular Depth Estimation,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+3f4684674d2f62e24b46140e2c5df29d061ffea1,Deep Ordinal Regression Network for Monocular Depth Estimation,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+3f4684674d2f62e24b46140e2c5df29d061ffea1,Deep Ordinal Regression Network for Monocular Depth Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3f0c51989c516a7c5dee7dec4d7fb474ae6c28d9,Not Afraid of the Dark: NIR-VIS Face Recognition via Cross-Spectral Hallucination and Low-Rank Embedding,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+3f3ce530fe7e75c648b6959980008b0b1f99727a,Multi-Instance Visual-Semantic Embedding,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
3fb26f3abcf0d287243646426cd5ddeee33624d4,Joint Training of Cascaded CNN for Face Detection,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
3f9ca2526013e358cd8caeb66a3d7161f5507cbc,Improving Sparse Representation-Based Classification Using Local Principal Component Analysis,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
3f57c3fc2d9d4a230ccb57eed1d4f0b56062d4d5,Face Recognition across Poses Using a Single 3D Reference Model,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
3feb69531653e83d0986a0643e4a6210a088e3e5,Using Group Prior to Identify People in Consumer Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
3feb69531653e83d0986a0643e4a6210a088e3e5,Using Group Prior to Identify People in Consumer Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+3f5741b49573122d278d1bff416ec34e1067a75a,A systemic approach to automatic metadata extraction from multimedia content,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
+3f5741b49573122d278d1bff416ec34e1067a75a,A systemic approach to automatic metadata extraction from multimedia content,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
3f12701449a82a5e01845001afab3580b92da858,Joint Object Class Sequencing and Trajectory Triangulation (JOST),University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
3fde656343d3fd4223e08e0bc835552bff4bda40,Character Identification Using Graph Matching Algorithm,Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
+3fee5c6343c969f33a7db4c7f7da1e152effd911,Patterns of fixation during face recognition: Differences in autism across age.,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+3fee5c6343c969f33a7db4c7f7da1e152effd911,Patterns of fixation during face recognition: Differences in autism across age.,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+3fee5c6343c969f33a7db4c7f7da1e152effd911,Patterns of fixation during face recognition: Differences in autism across age.,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+3fb054dbdff35b7ac3940c167e7292c7646e1ad9,Dictionary Learning and Sparse Coding on Statistical Manifolds,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+3ff4784d3f28c87f41c82ed9778c8c919b486cd4,Neural Baby Talk,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+3f9f5a8966c035dc179a60c042b160aee2bf8f53,Deep Second-Order Siamese Network for Pedestrian Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+3f9f5a8966c035dc179a60c042b160aee2bf8f53,Deep Second-Order Siamese Network for Pedestrian Re-identification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
3f957142ef66f2921e7c8c7eadc8e548dccc1327,Merging SVMs with Linear Discriminant Analysis: A Combined Model,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
3f957142ef66f2921e7c8c7eadc8e548dccc1327,Merging SVMs with Linear Discriminant Analysis: A Combined Model,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
3fdfd6fa7a1cc9142de1f53e4ac7c2a7ac64c2e3,Intensity-Depth Face Alignment Using Cascade Shape Regression,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
3fdfd6fa7a1cc9142de1f53e4ac7c2a7ac64c2e3,Intensity-Depth Face Alignment Using Cascade Shape Regression,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+3faedba96bd6b72c6669bdcb82ae0788cdcb3a43,A Study of Identification Performance of Facial Regions from CCTV Images,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
3f540faf85e1f8de6ce04fb37e556700b67e4ad3,Face Verification with Multi-Task and Multi-Scale Feature Fusion,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+3f4ba94a2964e62c52e7f283bea764ac19cffd40,A master-slave approach for object detection and matching with fixed and mobile cameras,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
3f4bfa4e3655ef392eb5ad609d31c05f29826b45,Robust multi-camera view face recognition,"Dr. B. C. Roy Engineering College, India",Dr. B. C. Roy Engineering College,"Dr. B. C. Roy Engineering College, Lenin Sarani, Durgapur, Bānkurā, West Bengal, 713200, India",23.54409755,87.34269707,edu,
3f4bfa4e3655ef392eb5ad609d31c05f29826b45,Robust multi-camera view face recognition,"National Institute of Technology, Rourkela",National Institute of Technology Rourkela,"National Institute of Technology, inside the department, Koel Nagar, Rourkela, Sundargarh, Odisha, 769002, India",22.25015890,84.90668557,edu,
3f4bfa4e3655ef392eb5ad609d31c05f29826b45,Robust multi-camera view face recognition,Indian Institute of Technology Kanpur,Indian Institute of Technology Kanpur,"Indian Institute of Technology Kanpur, 4th Avenue, Panki, Kanpur, Kanpur Nagar, Uttar Pradesh, 208016, India",26.51318800,80.23651945,edu,
3f4bfa4e3655ef392eb5ad609d31c05f29826b45,Robust multi-camera view face recognition,Jadavpur University,Jadavpur University,"Jadavpur University, Chingrighata Flyover, Basani Devi Colony, Kolkata, Hāora, West Bengal, 700098, India",22.56115370,88.41310194,edu,
+3f0f97d8256c6fe22a346bc54f8df67f6f674f22,Through-Wall Human Pose Estimation Using Radio Signals,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
3fb4bf38d34f7f7e5b3df36de2413d34da3e174a,Persuasive Faces: Generating Faces in Advertisements,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+3f2dbb34932edcb69295e57d4b8d6a8f68e28df4,Real-Time Compressive Tracking,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+3f3d0852249ff7924e152efe948d0aee87d4238f,Learning a mixture of sparse distance metrics for classification and dimensionality reduction,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+3f688723fb984bce9b60329f8f1ec3346be7f7e3,"Patterns of eye movements when male and female observers judge female attractiveness, body fat and waist-to-hip ratio",University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+3f688723fb984bce9b60329f8f1ec3346be7f7e3,"Patterns of eye movements when male and female observers judge female attractiveness, body fat and waist-to-hip ratio",Newcastle University,Newcastle University,"Newcastle University, Claremont Walk, Haymarket, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE1 7RU, UK",54.98023235,-1.61452627,edu,
+3f4607f71888df5b69719cc926e8d07988f82dd9,A socio-technical approach for event detection in security critical infrastructure,Vienna University of Technology,Vienna University of Technology,"TU Wien, Hauptgebäude, Hoftrakt, Freihausviertel, KG Wieden, Wieden, Wien, 1040, Österreich",48.19853965,16.36986168,edu,
3f623bb0c9c766a5ac612df248f4a59288e4d29f,"Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data",Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
3f4798c7701da044bdb7feb61ebdbd1d53df5cfe,Vector quantization with constrained likelihood for face recognition,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
3f4c262d836b2867a53eefb959057350bf7219c9,Recognizing Faces under Facial Expression Variations and Partial Occlusions,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
+3f4377109a92cf4e422b7e2ae95ef3144323ea72,Bridging the Gap Between Synthetic and Real Data,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+3f8b082c10561edd3ffc5d67a3d675cfdff6d94c,Information Bottleneck Learning Using Privileged Information for Visual Recognition,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
3f5e8f884e71310d7d5571bd98e5a049b8175075,Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+3f3a483402a3a2b800cf2c86506a37f6ef1a5332,DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+3f3a483402a3a2b800cf2c86506a37f6ef1a5332,DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+3f4b67309e6a2a9a1e303fbc0606225df0d3c2ab,Human-Object Interactions Are More than the Sum of Their Parts.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+3f4b67309e6a2a9a1e303fbc0606225df0d3c2ab,Human-Object Interactions Are More than the Sum of Their Parts.,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+3fd7bfd90f0dfc3369bfe718e27aff30cf268c23,Learning Mid-level Filters for Person Re-identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+3f0126f467802562505d5f551dfb6bd138180268,Occluded Pedestrian Detection Through Guided Attention in CNNs,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+3f0126f467802562505d5f551dfb6bd138180268,Occluded Pedestrian Detection Through Guided Attention in CNNs,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
3f5693584d7dab13ffc12122d6ddbf862783028b,Ranking CGANs: Subjective Control over Semantic Image Attributes,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+30193451e552286645baa00db7dcd05780d9e1da,On Available Corpora for Empirical Methods in Vision & Language,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+309dd5555dad9dfc3f3889cf11b5dec8ab797da6,Optimal Scheduling for Asymmetric Multi-core Server Processors,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+30caeca74168cd841759cef951c947f44ef0f547,Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+30caeca74168cd841759cef951c947f44ef0f547,Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
3039627fa612c184228b0bed0a8c03c7f754748c,Robust regression on image manifolds for ordered label denoising,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
+30e2b97b06590b7e39e6e53976c5b8265ed7392c,Zero-Shot Event Detection by Multimodal Distributional Semantic Embedding of Videos,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
+30d8fbb9345cdf1096635af7d39a9b04af9b72f9,Watching plants grow - a position paper on computer vision and Arabidopsis thaliana,Aberystwyth University,Aberystwyth University,"Aberystwyth University, Llanbadarn Campus, Cefn Esgair, Waun Fawr, Comins Coch, Ceredigion, Wales, SY23 3JG, UK",52.41073580,-4.05295501,edu,
+30654fd93360a339e271d4b194b7f7463b2c5dac,COSTA: Co-Occurrence Statistics for Zero-Shot Classification,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
303a7099c01530fa0beb197eb1305b574168b653,Occlusion-Free Face Alignment: Deep Regression Networks Coupled with De-Corrupt AutoEncoders,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
303a7099c01530fa0beb197eb1305b574168b653,Occlusion-Free Face Alignment: Deep Regression Networks Coupled with De-Corrupt AutoEncoders,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+3027727790598d913a8ff9a1bab4538176ad9fc8,BlinkML : Approximate Machine Learning with Probabilistic Guarantees,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
30cd39388b5c1aae7d8153c0ab9d54b61b474ffe,Deep Cascaded Regression for Face Alignment,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
30cd39388b5c1aae7d8153c0ab9d54b61b474ffe,Deep Cascaded Regression for Face Alignment,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
303517dfc327c3004ae866a6a340f16bab2ee3e3,Using Locality Preserving Projections in Face Recognition,DIT University,DIT UNIVERSITY,"DIT University, Dehradun-Mussoorie Road, Rājpur, Kincraig, Dehra Dūn, Uttarakhand, 248009, India",30.39833960,78.07534550,edu,
30fd1363fa14965e3ab48a7d6235e4b3516c1da1,A Deep Semi-NMF Model for Learning Hidden Representations,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+30e28beb92239447aff0718119195c0539aa58d8,Data Summarization at Scale: A Two-Stage Submodular Approach,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+303be881f6cd4907c5e357bc1bb5547d8ea1da5a,Individual Differences in the Recognition of Enjoyment Smiles: No Role for Perceptual–Attentional Factors and Autistic-Like Traits,Katholieke Universiteit Leuven,Katholieke Universiteit Leuven,"Laboratorium voor Bos, natuur en landschap, 102, Vital Decosterstraat, Sint-Maartensdal, Leuven, Vlaams-Brabant, Vlaanderen, 3000, België / Belgique / Belgien",50.88306860,4.70195030,edu,
+303be881f6cd4907c5e357bc1bb5547d8ea1da5a,Individual Differences in the Recognition of Enjoyment Smiles: No Role for Perceptual–Attentional Factors and Autistic-Like Traits,University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
+305887fe0fce91470c6cb042616cb36486dc0e3b,SelfKin: Self Adjusted Deep Model For Kinship Verification,Bar-Ilan University,Bar-Ilan University,"אוניברסיטת בר אילן, כביש גהה, גבעת שמואל, קריית מטלון, גבעת שמואל, מחוז תל אביב, NO, ישראל",32.06932925,34.84334339,edu,
+3002b5180c4b4fbf9c07145b5b435846c729c724,Reconstruction of Partially Occluded Face by Fast Recursive PCA,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+30e18a16d4c7092694d55743ff92965e5dec2692,"Hormonal contraceptives, menstrual cycle and brain response to faces.",University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+30e18a16d4c7092694d55743ff92965e5dec2692,"Hormonal contraceptives, menstrual cycle and brain response to faces.",University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
+30052dfa6397cf9732a7385dc55f207a0ad24ca4,Energy-Efficient Run-Time Mapping and Thread Partitioning of Concurrent OpenCL Applications on CPU-GPU MPSoCs,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+30052dfa6397cf9732a7385dc55f207a0ad24ca4,Energy-Efficient Run-Time Mapping and Thread Partitioning of Concurrent OpenCL Applications on CPU-GPU MPSoCs,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+30052dfa6397cf9732a7385dc55f207a0ad24ca4,Energy-Efficient Run-Time Mapping and Thread Partitioning of Concurrent OpenCL Applications on CPU-GPU MPSoCs,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+30052dfa6397cf9732a7385dc55f207a0ad24ca4,Energy-Efficient Run-Time Mapping and Thread Partitioning of Concurrent OpenCL Applications on CPU-GPU MPSoCs,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+30052dfa6397cf9732a7385dc55f207a0ad24ca4,Energy-Efficient Run-Time Mapping and Thread Partitioning of Concurrent OpenCL Applications on CPU-GPU MPSoCs,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+30052dfa6397cf9732a7385dc55f207a0ad24ca4,Energy-Efficient Run-Time Mapping and Thread Partitioning of Concurrent OpenCL Applications on CPU-GPU MPSoCs,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+309acdd149f5f0ea12acb103b36bb59e6e631671,Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+309acdd149f5f0ea12acb103b36bb59e6e631671,Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+309acdd149f5f0ea12acb103b36bb59e6e631671,Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
3026722b4cbe9223eda6ff2822140172e44ed4b1,Jointly estimating demographics and height with a calibrated camera,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+30a3eee5e9302108416f6234d739373dde68d373,Learning to Count Objects in Natural Images for Visual Question Answering,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+30d21b5baf9514d26da749c6683c49b4fa55f2b5,Towards a unified account of face (and maybe object) processing,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
304b1f14ca6a37552dbfac443f3d5b36dbe1a451,Collaborative Low-Rank Subspace Clustering,Charles Sturt University,Charles Sturt University,"Charles Sturt University, Wagga Wagga, NSW, 2678, Australia",-35.06360710,147.35522340,edu,
304b1f14ca6a37552dbfac443f3d5b36dbe1a451,Collaborative Low-Rank Subspace Clustering,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
304b1f14ca6a37552dbfac443f3d5b36dbe1a451,Collaborative Low-Rank Subspace Clustering,Western Sydney University,Western Sydney University,"Western Sydney University, Parramatta City Campus, Smith Street, Parramatta, Sydney, Parramatta, NSW, 2150, Australia",-33.81608480,151.00560034,edu,
306127c3197eb5544ab1e1bf8279a01e0df26120,Sparse Coding and Dictionary Learning with Linear Dynamical Systems,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+3073eff17368262d7c605bbcaf3b2fb015754d39,Voice conversion versus speaker verification: an overview,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+3073eff17368262d7c605bbcaf3b2fb015754d39,Voice conversion versus speaker verification: an overview,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+30723ada764c6ec186927522d666eaa8eeae35b1,Deep Covariance Descriptors for Facial Expression Recognition,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
30180f66d5b4b7c0367e4b43e2b55367b72d6d2a,Template Adaptation for Face Verification and Identification,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+30a29f6c407749e97bc7c2db5674a62773af9d27,Tracking and Visual Quality Inspection in Harsh Environments (print-version),Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+303225eaedd489f61ac36e1f39cd04db7fd8bd41,Facial Affect Recognition for Cognitive-behavioural Therapy,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+304fa45de90874e89b7a5511c88551994ea8c89d,Charting the typical and atypical development of the social brain.,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+302bf028487b50bed33bc6d36971b8ecf06393ab,Landmark Localisation in 3D Face Data,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+30a4637cbc461838c151073b265fb08e00492ff4,Weakly Supervised Object Localization with Progressive Domain Adaptation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+30fcfc6b7fe1809d79ea6ce08f50e2e53c203800,Deep Manifold Learning of Symmetric Positive Definite Matrices with Application to Face Recognition,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+30998485c920f62c307c29c4832b70bbce748eaf,Local Similarity-Aware Deep Feature Embedding,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+301662c2a6ed86e48f21c1d24bfc67b403201b0c,Repetition Suppression in Ventral Visual Cortex Is Diminished as a Function of Increasing Autistic Traits,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+301662c2a6ed86e48f21c1d24bfc67b403201b0c,Repetition Suppression in Ventral Visual Cortex Is Diminished as a Function of Increasing Autistic Traits,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
3083d2c6d4f456e01cbb72930dc2207af98a6244,Perceived Age Estimation from Face Images,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+30722904751c2e1cf287f268befdec2e4223b086,Accurate Eye Center Localization via Hierarchical Adaptive Convolution,University of Portsmouth,University of Portsmouth,"University of Portsmouth - North Zone, Portland Street, Portsea, Portsmouth, South East, England, PO1 3DE, UK",50.79805775,-1.09834911,edu,
+30722904751c2e1cf287f268befdec2e4223b086,Accurate Eye Center Localization via Hierarchical Adaptive Convolution,University of Plymouth,University of Plymouth,"Charles Seale-Hayne Library, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37525010,-4.13927692,edu,
+30def55b6277f1e636dfebe12799b12a1b3f48a2,Recurrent Neural Network for Learning DenseDepth and Ego-Motion from Video,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
30cbd41e997445745b6edd31f2ebcc7533453b61,What Makes a Video a Video : Analyzing Temporal Information in Video Understanding Models and Datasets,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+30a14aabde46aa236a7b437a4942a92d417f3653,Incremental Learning Framework for Indoor Scene Recognition,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+30e547dfab832ea0428b137d9e4824a22d8efd0b,Lazier Than Lazy Greedy,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+30f49d6595359a4a18c728ec83f99346d1e16348,Intact Reflexive but Deficient Voluntary Social Orienting in Autism Spectrum Disorder,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
+30f49d6595359a4a18c728ec83f99346d1e16348,Intact Reflexive but Deficient Voluntary Social Orienting in Autism Spectrum Disorder,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+30f49d6595359a4a18c728ec83f99346d1e16348,Intact Reflexive but Deficient Voluntary Social Orienting in Autism Spectrum Disorder,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+301486e8dad7a41a1a99fd6fba28ce153fe1e56e,Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+3075baf2abc1849d2dc2f1448c272ca2f8b7694d,Learning Segmentation Masks with the Independence Prior,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+3075baf2abc1849d2dc2f1448c272ca2f8b7694d,Learning Segmentation Masks with the Independence Prior,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+3070a1bd503c3767def898bbd50c7eea2bbf29c9,Wider or Deeper: Revisiting the ResNet Model for Visual Recognition,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
5e59193a0fc22a0c37301fb05b198dd96df94266,Example-Based Modeling of Facial Texture from Deficient Data,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+5e8677eb21c3a5d24c52bcb93404416f7eeebc31,Enhancing Probabilistic Appearance-Based Object Tracking with Depth Information: Object Tracking under Occlusion,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
5e7e055ef9ba6e8566a400a8b1c6d8f827099553,On the role of cortex-basal ganglia interactions for category learning: A neuro-computational approach.,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+5e74d92d841d1bc1c9c2d80219f98bf892f239c4,Developmental changes in face visual scanning in autism spectrum disorder as assessed by data-based analysis,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+5ee96d5c4d467d00909472e3bc0d2c2d82ccb961,Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+5ee96d5c4d467d00909472e3bc0d2c2d82ccb961,Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+5ee96d5c4d467d00909472e3bc0d2c2d82ccb961,Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+5e84fd5c73dfeea9d51e1cf59ea6f8ecf2097603,Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+5e84fd5c73dfeea9d51e1cf59ea6f8ecf2097603,Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+5e09a85527a2c471ce35b21a3b22ae1620c80176,Facial image analysis based on two-dimensional linear discriminant analysis exploiting symmetry,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+5e3c8cd50301a13ad53a3fc9e3567ede63a76215,Learning to Cluster for Proposal-Free Instance Segmentation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+5e3c8cd50301a13ad53a3fc9e3567ede63a76215,Learning to Cluster for Proposal-Free Instance Segmentation,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+5e3c8cd50301a13ad53a3fc9e3567ede63a76215,Learning to Cluster for Proposal-Free Instance Segmentation,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+5ec7e6b9cf06ab90cca7bda8e7a4b54ecb6859ac,CoDeL: A Human Co-detection and Labeling Framework,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
5e16f10f2d667d17c029622b9278b6b0a206d394,Learning to Rank Binary Codes,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
5e16f10f2d667d17c029622b9278b6b0a206d394,Learning to Rank Binary Codes,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
5e16f10f2d667d17c029622b9278b6b0a206d394,Learning to Rank Binary Codes,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+5e525d319af3739ccb205a890d0eb8bbed811d20,Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+5e525d319af3739ccb205a890d0eb8bbed811d20,Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
5ef3e7a2c8d2876f3c77c5df2bbaea8a777051a7,Rendering or normalization? An analysis of the 3D-aided pose-invariant face recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
5ea165d2bbd305dc125415487ef061bce75dac7d,Efficient human action recognition by luminance field trajectory and geometry information,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+5ed062553280d48a42b688bc63ed3f81f3507dbc,Parallel Distributed Face Search System for National and Border Security,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+5ed062553280d48a42b688bc63ed3f81f3507dbc,Parallel Distributed Face Search System for National and Border Security,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
5ea9cba00f74d2e113a10c484ebe4b5780493964,Automated Drowsiness Detection For Improved Driving Safety,Sabanci University,Sabanci University,"Sabanci Universitesi, Preveze Cad., Orta Mahallesi, Tepeören, Tuzla, İstanbul, Marmara Bölgesi, 34953, Türkiye",40.89271590,29.37863323,edu,
5ea9cba00f74d2e113a10c484ebe4b5780493964,Automated Drowsiness Detection For Improved Driving Safety,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+5e1514de6d20d3b1d148d6925edc89a6c891ce47,Consistent-Aware Deep Learning for Person Re-identification in a Camera Network,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+5e1514de6d20d3b1d148d6925edc89a6c891ce47,Consistent-Aware Deep Learning for Person Re-identification in a Camera Network,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+5e821a4d0e26db7ee41a7f0f25036ba4ec094ac8,"Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation",University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
+5e821a4d0e26db7ee41a7f0f25036ba4ec094ac8,"Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation",Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+5e821a4d0e26db7ee41a7f0f25036ba4ec094ac8,"Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+5e821a4d0e26db7ee41a7f0f25036ba4ec094ac8,"Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation",Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+5e821a4d0e26db7ee41a7f0f25036ba4ec094ac8,"Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation",University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+5ef25b78dc947f1f4674da44945b050e3f4b9e17,3 D Face Recognition Based on Multiple Keypoint Descriptors and Sparse Representation,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+5edfa28559c054b23acc43ce0f975a04ae27b331,Multiple Tree Models for Occlusion and Spatial Constraints in Human Pose Estimation,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+5eec4db50ad8237d881562d036c275d87dd14683,End-to-End Deep Kronecker-Product Matching for Person Re-identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
5e80e2ffb264b89d1e2c468fbc1b9174f0e27f43,Naming every individual in news video monologues,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5e706ba3d5c7237a580716aacda350b867c85e5f,Predicting Useful Neighborhoods for Lazy Local Learning,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+5e706ba3d5c7237a580716aacda350b867c85e5f,Predicting Useful Neighborhoods for Lazy Local Learning,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
5e0e516226413ea1e973f1a24e2fdedde98e7ec0,The Invariance Hypothesis and the Ventral Stream,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+5e55d9dabe06ee6b4d4b31dfd3723f6016a6c937,Visualization of Automated and Manual Trajectories in Wide-Area Motion Imagery,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+5e07d6951b7bc0c4113313a9586ce8178eacdf57,Learning to Reason: End-to-End Module Networks for Visual Question Answering,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+5e07d6951b7bc0c4113313a9586ce8178eacdf57,Learning to Reason: End-to-End Module Networks for Visual Question Answering,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
5e7cb894307f36651bdd055a85fdf1e182b7db30,A Comparison of Multi-class Support Vector Machine Methods for Face Recognition,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
5b693cb3bedaa2f1e84161a4261df9b3f8e77353,"Robust Face Localisation Using Motion, Colour and Fusion",Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
5b73b7b335f33cda2d0662a8e9520f357b65f3ac,Intensity Rank Estimation of Facial Expressions Based on a Single Image,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
5b73b7b335f33cda2d0662a8e9520f357b65f3ac,Intensity Rank Estimation of Facial Expressions Based on a Single Image,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
5b6d05ce368e69485cb08dd97903075e7f517aed,Robust Active Shape Model for Landmarking Frontal Faces,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
5b0bf1063b694e4b1575bb428edb4f3451d9bf04,Facial Shape Tracking via Spatio-Temporal Cascade Shape Regression,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+5b249cf39370503f22fc7d4b257d735555d647ce,DeepID-Net: Deformable deep convolutional neural networks for object detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
5b59e6b980d2447b2f3042bd811906694e4b0843,Two-stage cascade model for unconstrained face detection,University of Zagreb,"University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia","Unska ul. 3, 10000, Zagreb, Croatia",45.80112100,15.97084090,edu,
+5b4abeb466a2c97a99b9621e0c83c95f4326e99b,Adversarial Examples: Attacks and Defenses for Deep Learning,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
5bb53fb36a47b355e9a6962257dd465cd7ad6827,Mask-off: Synthesizing Face Images in the Presence of Head-mounted Displays,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
5bb53fb36a47b355e9a6962257dd465cd7ad6827,Mask-off: Synthesizing Face Images in the Presence of Head-mounted Displays,North Carolina Central University,North Carolina Central University,"North Carolina Central University, George Street, Hayti, Durham, Durham County, North Carolina, 27707, USA",35.97320905,-78.89755054,edu,
+5b16f0870546cd57a934f2ee039136a09abb96b9,Versatile Auxiliary Regressor with Generative Adversarial network (VAR+GAN),National University of Ireland Galway,National University of Ireland Galway,"National University of Ireland, Galway, Earl's Island, Townparks, Nun's Island, Galway Municipal District, Cathair na Gaillimhe, County Galway, Connacht, H91 F5TE, Ireland",53.27639715,-9.05829961,edu,
+5b24ef13fc9a51a9892f164bc142ffefc0b7a8ee,You said that?,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+5b9dc0f10704b5663c06c7dde2732d4a6076de55,Is Sparsity Really Relevant for Image Classification?,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
5b89744d2ac9021f468b3ffd32edf9c00ed7fed7,Beyond Mahalanobis metric: Cayley-Klein metric learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
5b7cb9b97c425b52b2e6f41ba8028836029c4432,Smooth Representation Clustering,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
5b7cb9b97c425b52b2e6f41ba8028836029c4432,Smooth Representation Clustering,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+5b2bc289b607ca1a0634555158464f28fe68a6d3,Where's Waldo: Matching people in images of crowds,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+5b2bc289b607ca1a0634555158464f28fe68a6d3,Where's Waldo: Matching people in images of crowds,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+5b2bc289b607ca1a0634555158464f28fe68a6d3,Where's Waldo: Matching people in images of crowds,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
5b9d41e2985fa815c0f38a2563cca4311ce82954,Exploitation of 3D images for face authentication under pose and illumination variations,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+5bd91c5aa3468d3435ff33d03b3d8348724f96da,3D Human Pose Estimation from Monocular Image Sequences,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
5b6593a6497868a0d19312952d2b753232414c23,Face Recognition by 3D Registration for the Visually Impaired Using a RGB-D Sensor,City College of New York,"The City College of New York, New York, NY 10031, USA","CCNY, 160, Convent Avenue, Manhattanville, Manhattan, Manhattan Community Board 9, New York County, NYC, New York, 10031, USA",40.81819805,-73.95100898,edu,
5b6593a6497868a0d19312952d2b753232414c23,Face Recognition by 3D Registration for the Visually Impaired Using a RGB-D Sensor,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+5bf2132de8be99547af4aee6013fec8226c763b5,Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+5bf2132de8be99547af4aee6013fec8226c763b5,Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+5bf2132de8be99547af4aee6013fec8226c763b5,Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+5b9693d2f6b7b731f9abdbfa5c35d641b881daff,Modeling Human Motion Using Manifold Learning and Factorized Generative Models,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+5b70beeadc31ac8421bd9fe54fbe696b90eba1cf,Three-dimensional proxies for hand-drawn characters,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+5bfec86bb67a1c49359e8a171917311d48688068,Natural Language Understanding with Distributed Representation,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
5b719410e7829c98c074bc2947697fac3b505b64,Active Appearance Models for Affect Recognition Using Facial Expressions,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
-5b0008ba87667085912ea474025d2323a14bfc90,SoS-RSC: A Sum-of-Squares Polynomial Approach to Robustifying Subspace Clustering Algorithms,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
-5b0008ba87667085912ea474025d2323a14bfc90,SoS-RSC: A Sum-of-Squares Polynomial Approach to Robustifying Subspace Clustering Algorithms,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+5b0008ba87667085912ea474025d2323a14bfc90,SoS-RSC : A Sum-of-Squares Polynomial Approach to Robustifying Subspace Clustering Algorithms,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+5b0008ba87667085912ea474025d2323a14bfc90,SoS-RSC : A Sum-of-Squares Polynomial Approach to Robustifying Subspace Clustering Algorithms,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
5b97e997b9b654373bd129b3baf5b82c2def13d1,3D Face Tracking and Texture Fusion in the Wild,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
5b97e997b9b654373bd129b3baf5b82c2def13d1,3D Face Tracking and Texture Fusion in the Wild,Reutlingen University,Reutlingen University,"Campus Hohbuch, Campus Hochschule Reutlingen, Reutlingen, Landkreis Reutlingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72762, Deutschland",48.48187645,9.18682404,edu,
5bd3d08335bb4e444a86200c5e9f57fd9d719e14,3 D Face Morphable Models “ Inthe-Wild ”,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
5bd3d08335bb4e444a86200c5e9f57fd9d719e14,3 D Face Morphable Models “ Inthe-Wild ”,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+5b79ae0d1fd60d61d1b7e37ffe499f50088554c0,"Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF",Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+5b79ae0d1fd60d61d1b7e37ffe499f50088554c0,"Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF",National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+5b600cfabfb3c99085ca949fc432684e7ac86471,Representation Independent Analytics Over Structured Data,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+5b600cfabfb3c99085ca949fc432684e7ac86471,Representation Independent Analytics Over Structured Data,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+5b600cfabfb3c99085ca949fc432684e7ac86471,Representation Independent Analytics Over Structured Data,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
5bf70c1afdf4c16fd88687b4cf15580fd2f26102,Residual Codean Autoencoder for Facial Attribute Analysis,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+5b4fddc0b86deea2fc139c43ee07892ad211a2dd,Compositional Human Pose Regression,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
5b4b84ce3518c8a14f57f5f95a1d07fb60e58223,Diagnosing Error in Object Detectors,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+5b042a76c6e61d411f68b8193ec67ad8dd1abc5e,iSAX 2.0: Indexing and Mining One Billion Time Series,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+5b7cf29f164ec59a15ddb55b4af84ca07231f35d,"The role of features, algorithms and data in visual recognition",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+5bce272adc5bd6934fe31ae3c648b4b62191353d,The Evolution of First Person Vision Methods: A Survey,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
+5b7856b7669a5746b7f14d2ae5452aa2dc89d454,Domain-Adaptive Discriminative One-Shot Learning of Gestures,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+5b7856b7669a5746b7f14d2ae5452aa2dc89d454,Domain-Adaptive Discriminative One-Shot Learning of Gestures,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
5b6ecbf5f1eecfe1a9074d31fe2fb030d75d9a79,Improving 3D Face Details Based on Normal Map of Hetero-source Images,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
5b86c36e3eb59c347b81125d5dd57dd2a2c377a9,Name Identification of People in News Video by Face Matching,Nagoya University,Nagoya University,"SuperDARN (Hokkaido West), 太辛第1支線林道, 陸別町, 足寄郡, 十勝総合振興局, 北海道, 北海道地方, 日本",43.53750985,143.60768225,edu,
+5ba8bb7d204e7a5a29a043792546577500e2e5c1,Background Appearance Modeling with Applications to Visual Object Detection in an Open-Pit Mine,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+5ba8bb7d204e7a5a29a043792546577500e2e5c1,Background Appearance Modeling with Applications to Visual Object Detection in an Open-Pit Mine,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
5bc0a89f4f73523967050374ed34d7bc89e4d9e1,The role of emotion transition for the perception of social dominance and affiliation.,University of Haifa,University of Haifa,"אוניברסיטת חיפה, חיפה, מחוז חיפה, ישראל",32.76162915,35.01986304,edu,
5bc0a89f4f73523967050374ed34d7bc89e4d9e1,The role of emotion transition for the perception of social dominance and affiliation.,Humboldt University,Humboldt University,"Humboldt-Universität zu Berlin, Dorotheenstraße, Spandauer Vorstadt, Mitte, Berlin, 10117, Deutschland",52.51875685,13.39356049,edu,
5bde1718253ec28a753a892b0ba82d8e553b6bf3,Variational Relevance Vector Machine for Tabular Data,Lomonosov Moscow State University,Lomonosov Moscow State University,"МГУ, улица Академика Хохлова, Московский государственный университет им. М. В. Ломоносова, район Раменки, Западный административный округ, Москва, ЦФО, 119234, РФ",55.70229715,37.53179777,edu,
@@ -2778,14 +7604,37 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 378ae5ca649f023003021f5a63e393da3a4e47f0,Multi-class object localization by combining local contextual interactions,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
37619564574856c6184005830deda4310d3ca580,A deep pyramid Deformable Part Model for face detection,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
37ce1d3a6415d6fc1760964e2a04174c24208173,Pose-Invariant 3D Face Alignment,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+372688ad240474724683703e65a02f30e8d293ff,Putting the Scientist in the Loop -- Accelerating Scientific Progress with Interactive Machine Learning,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+372688ad240474724683703e65a02f30e8d293ff,Putting the Scientist in the Loop -- Accelerating Scientific Progress with Interactive Machine Learning,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+372688ad240474724683703e65a02f30e8d293ff,Putting the Scientist in the Loop -- Accelerating Scientific Progress with Interactive Machine Learning,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+3737961f634876f59d4ffd5bbd198bf38b2cfdda,Study the Behavior of Autistic Patients and Analysis of Amygdala Region of Brain to Explore Autism,Jahangirnagar University,Jahangirnagar University,"Jahangirnagar University, 1342, University Main Road, সাভার, সাভার উপজেলা, ঢাকা জেলা, ঢাকা বিভাগ, 1342, বাংলাদেশ",23.88331200,90.26939210,edu,
+373813010983b274401b9b65157df57ce50f7011,"Focus on quality, predicting FRVT 2006 performance",Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+373813010983b274401b9b65157df57ce50f7011,"Focus on quality, predicting FRVT 2006 performance",Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+373813010983b274401b9b65157df57ce50f7011,"Focus on quality, predicting FRVT 2006 performance",National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+373813010983b274401b9b65157df57ce50f7011,"Focus on quality, predicting FRVT 2006 performance",Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+373813010983b274401b9b65157df57ce50f7011,"Focus on quality, predicting FRVT 2006 performance",Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
+379aaada226a3629408dbb223c7a7252dcc425b8,Naturalistic Pain Synthesis for Virtual Patients,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+37e1fc37a3ee90f24d85ad6fd3e5c51d3f5ab4fd,Attentive Explanations: Justifying Decisions and Pointing to the Evidence,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
37ba12271d09d219dd1a8283bc0b4659faf3a6c6,Domain transfer for person re-identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+372fefe66aa693e271ec6298fac1695208f36aee,Face Deidentification with Generative Deep Neural Networks,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+372fefe66aa693e271ec6298fac1695208f36aee,Face Deidentification with Generative Deep Neural Networks,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
+372fefe66aa693e271ec6298fac1695208f36aee,Face Deidentification with Generative Deep Neural Networks,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+37b3637dab65b91a5c91bb6a583e69c448823cc1,Learning a Hierarchical Latent-Variable Model of 3D Shapes,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+3759b4fa10eabe047ff417b3076458b44132dc8b,Person-of-interest detection system using cloud-supported computerized-eyewear,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+37bb9b45c6385789b819573b3716fe56a9e627db,Location Augmentation for CNN,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
377f2b65e6a9300448bdccf678cde59449ecd337,Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results,Johns Hopkins University,"Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA","3400 N Charles St, Baltimore, MD 21218, USA",39.32905300,-76.61942500,edu,
377f2b65e6a9300448bdccf678cde59449ecd337,Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+3714a415e63204e9c331b919cff6a14f7121c902,Improving 3d Face Recognition Model Generation and Biometrics,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
370b6b83c7512419188f5373a962dd3175a56a9b,Face Alignment Refinement via Exploiting Low-Rank property and Temporal Stability,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
370b6b83c7512419188f5373a962dd3175a56a9b,Face Alignment Refinement via Exploiting Low-Rank property and Temporal Stability,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
370b6b83c7512419188f5373a962dd3175a56a9b,Face Alignment Refinement via Exploiting Low-Rank property and Temporal Stability,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
370b6b83c7512419188f5373a962dd3175a56a9b,Face Alignment Refinement via Exploiting Low-Rank property and Temporal Stability,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
370b6b83c7512419188f5373a962dd3175a56a9b,Face Alignment Refinement via Exploiting Low-Rank property and Temporal Stability,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
+37a4199e63312f7901af853998951883e52ab062,Future Localization from an Egocentric Depth Image,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+37aa876f5202d1db6919f0a0dd5a0f76508c02fb,Occlusion-Aware Hand Pose Estimation Using Hierarchical Mixture Density Network,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+37d7cb06c0a1e632dedcc1f23db22cbdc130e6aa,Pyramid Person Matching Network for Person Re-identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+37d7cb06c0a1e632dedcc1f23db22cbdc130e6aa,Pyramid Person Matching Network for Person Re-identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+378b6d94bacffb0fcc1063476a7b9694e877ba12,Scalable Hardware Efficient Deep Spatio-Temporal Inference Networks,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
37ef18d71c1ca71c0a33fc625ef439391926bfbb,Extraction of Subject-Specific Facial Expression Categories and Generation of Facial Expression Feature Space using Self-Mapping,Akita Prefectural University,Akita Prefectural University,"秋田県立大学, 秋田天王線, 潟上市, 秋田県, 東北地方, 011-0946, 日本",39.80114990,140.04591160,edu,
37ef18d71c1ca71c0a33fc625ef439391926bfbb,Extraction of Subject-Specific Facial Expression Categories and Generation of Facial Expression Feature Space using Self-Mapping,Akita University,Akita University,"秋田大学手形キャンパス, 秋田八郎潟線, 手形字扇田, 広面, 秋田市, 秋田県, 東北地方, 010-0864, 日本",39.72781420,140.13322566,edu,
081189493ca339ca49b1913a12122af8bb431984,Supplemental Material for Photorealistic Facial Texture Inference Using Deep Neural Networks,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
@@ -2793,17 +7642,42 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 08ee541925e4f7f376538bc289503dd80399536f,Runtime Neural Pruning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
08ee541925e4f7f376538bc289503dd80399536f,Runtime Neural Pruning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
08ee541925e4f7f376538bc289503dd80399536f,Runtime Neural Pruning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+08b28a8f2699501d46d87956cbaa37255000daa3,MaskReID: A Mask Based Deep Ranking Neural Network for Person Re-identification,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+08b28a8f2699501d46d87956cbaa37255000daa3,MaskReID: A Mask Based Deep Ranking Neural Network for Person Re-identification,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
+081e540e0f3b4741c1f27092f52fef01bb81f06d,Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+081e540e0f3b4741c1f27092f52fef01bb81f06d,Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+081e540e0f3b4741c1f27092f52fef01bb81f06d,Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+08c2fdbe89fda66ec26453c4ea3f190e3e3d794f,A Biophysical 3D Morphable Model of Face Appearance,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+08eaa845a72a2b78e08e58592d8785942fced649,What's in a Question: Using Visual Questions as a Form of Supervision,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0824768412cf2c3e9f550025eee06bb34e5f3afd,Latent Data Association: Bayesian Model Selection for Multi-target Tracking,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+0824768412cf2c3e9f550025eee06bb34e5f3afd,Latent Data Association: Bayesian Model Selection for Multi-target Tracking,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
08f6ad0a3e75b715852f825d12b6f28883f5ca05,Face recognition: Some challenges in forensics,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+08aaaf56277f7f9897353a6b09a63ea90b4cc554,Chapter 15 MULTIMEDIA INFORMATION NETWORKS IN SOCIAL MEDIA,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
084bd02d171e36458f108f07265386f22b34a1ae,Face Alignment at 3000 FPS via Regressing Local Binary Features,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
084bd02d171e36458f108f07265386f22b34a1ae,Face Alignment at 3000 FPS via Regressing Local Binary Features,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
081cb09791e7ff33c5d86fd39db00b2f29653fa8,Square Loss based regularized LDA for face recognition using image sets,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
081cb09791e7ff33c5d86fd39db00b2f29653fa8,Square Loss based regularized LDA for face recognition using image sets,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+0816b525b03e47d995b3d97f1f9132a4f7a2cf9d,Gaze-enabled egocentric video summarization via constrained submodular maximization,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+0816b525b03e47d995b3d97f1f9132a4f7a2cf9d,Gaze-enabled egocentric video summarization via constrained submodular maximization,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+087a507075819e5b7ad886fad3097b23470f35f2,Using false colors to protect visual privacy of sensitive content,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+08d2a558ea2deb117dd8066e864612bf2899905b,Person Re-identification with Deep Similarity-Guided Graph Neural Network,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+08e3a0f80f10fc40cc1c043cbc4c873a76a6f6e8,Enhanced Pavlovian aversive conditioning to positive emotional stimuli.,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+08e3a0f80f10fc40cc1c043cbc4c873a76a6f6e8,Enhanced Pavlovian aversive conditioning to positive emotional stimuli.,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
086131159999d79adf6b31c1e604b18809e70ba8,Deep Action Unit classification using a binned intensity loss and semantic context model,Villanova University,Villanova University,"Villanova University, East Lancaster Avenue, Radnor Township, Delaware County, Pennsylvania, 19010, USA",40.03677740,-75.34202332,edu,
086131159999d79adf6b31c1e604b18809e70ba8,Deep Action Unit classification using a binned intensity loss and semantic context model,Villanova University,Villanova University,"Villanova University, East Lancaster Avenue, Radnor Township, Delaware County, Pennsylvania, 19010, USA",40.03677740,-75.34202332,edu,
+080d9658e40581c7ba8c0cc1d86d1157eda92a3e,Periocular biometric recognition using image sets,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
089513ca240c6d672c79a46fa94a92cde28bd567,RNN Fisher Vectors for Action Recognition and Image Annotation,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
089513ca240c6d672c79a46fa94a92cde28bd567,RNN Fisher Vectors for Action Recognition and Image Annotation,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+086a91d8db2780a14a21335260e97a9b7b27f546,Iterative object and part transfer for fine-grained recognition,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+08d6aecf1ee531f8c62c22a256b2c2e58081df9d,Blocks That Shout: Distinctive Parts for Scene Classification,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+08d6aecf1ee531f8c62c22a256b2c2e58081df9d,Blocks That Shout: Distinctive Parts for Scene Classification,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
089b5e8eb549723020b908e8eb19479ba39812f5,A Cross Benchmark Assessment of a Deep Convolutional Neural Network for Face Recognition,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+0843ec2b76ef9401e60654fbfe71bac44ed19fae,A Two-Stage Approach for Bag Detection in Pedestrian Images,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
08a1fc55d03e4a73cad447e5c9ec79a6630f3e2d,Tom-vs-Pete Classifiers and Identity-Preserving Alignment for Face Verification,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+08e69a871487b52510699c07859b4aaec122d3df,Visual Coreference Resolution in Visual Dialog Using Neural Module Networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+08e69a871487b52510699c07859b4aaec122d3df,Visual Coreference Resolution in Visual Dialog Using Neural Module Networks,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+084352b63e98d3b3310521fb3bda8cb4a77a0254,Part-based multiple-person tracking with partial occlusion handling,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+084352b63e98d3b3310521fb3bda8cb4a77a0254,Part-based multiple-person tracking with partial occlusion handling,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
087002ab569e35432cdeb8e63b2c94f1abc53ea9,Spatiotemporal analysis of RGB-D-T facial images for multimodal pain level recognition,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
087002ab569e35432cdeb8e63b2c94f1abc53ea9,Spatiotemporal analysis of RGB-D-T facial images for multimodal pain level recognition,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
08cb294a08365e36dd7ed4167b1fd04f847651a9,Examining visible articulatory features in clear and conversational speech,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
@@ -2816,126 +7690,401 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 08d55271589f989d90a7edce3345f78f2468a7e0,Quality Aware Network for Set to Set Recognition,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
08d55271589f989d90a7edce3345f78f2468a7e0,Quality Aware Network for Set to Set Recognition,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
08d55271589f989d90a7edce3345f78f2468a7e0,Quality Aware Network for Set to Set Recognition,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+08ba1a7d91ce9b4ac26869bfe4bb7c955b0d1a24,Reducing JointBoost-based multiclass classification to proximity search,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+08ba1a7d91ce9b4ac26869bfe4bb7c955b0d1a24,Reducing JointBoost-based multiclass classification to proximity search,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
08a98822739bb8e6b1388c266938e10eaa01d903,SensorSift: balancing sensor data privacy and utility in automated face understanding,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
084bebc5c98872e9307cd8e7f571d39ef9c1b81e,A Discriminative Feature Learning Approach for Deep Face Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
084bebc5c98872e9307cd8e7f571d39ef9c1b81e,A Discriminative Feature Learning Approach for Deep Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+083ac08287af7df220d88dca2fbf5b1812e35ee8,Abnormal functional connectivity in autism spectrum disorders during face processing.,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+083ac08287af7df220d88dca2fbf5b1812e35ee8,Abnormal functional connectivity in autism spectrum disorders during face processing.,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+08bc0dd59187eaf919dfedf1d5849d1a875835df,On-line Hough Forests,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+08bc0dd59187eaf919dfedf1d5849d1a875835df,On-line Hough Forests,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
08f1e9e14775757298afd9039f46ec56e80677f9,Attentional Push: Augmenting Salience with Shared Attention Modeling,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+0862940a255d980d46ef041ab20f153276f96214,3D Object Representations for Fine-Grained Categorization,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+0862940a255d980d46ef041ab20f153276f96214,3D Object Representations for Fine-Grained Categorization,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+084cf3858b07d64fc29cb7f0f4dc0653c6246d3d,A tool for fast ground truth generation for object detection and tracking from video,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
08d41d2f68a2bf0091dc373573ca379de9b16385,Recursive Chaining of Reversible Image-to-image Translators For Face Aging,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+08aab46667dbcd875751f1e8ce2daed0df643b12,Query-adaptive late fusion for image search and person re-identification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+08aab46667dbcd875751f1e8ce2daed0df643b12,Query-adaptive late fusion for image search and person re-identification,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
6d0fe30444c6f4e4db3ad8b02fb2c87e2b33c58d,Robust Deep Appearance Models,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
6d0fe30444c6f4e4db3ad8b02fb2c87e2b33c58d,Robust Deep Appearance Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6dbdb07ce2991db0f64c785ad31196dfd4dae721,Seeing Small Faces from Robust Anchor's Perspective,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6d7a32f594d46f4087b71e2a2bb66a4b25da5e30,Towards Person Authentication by Fusing Visual and Thermal Face Biometrics,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+6d43bac8348a76ca5e3b765ad5b4d8c302c186f1,i-RevNet: Deep Invertible Networks,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
6d2ca1ddacccc8c865112bd1fbf8b931c2ee8e75,ROC speak: semi-automated personalized feedback on nonverbal behavior from recorded videos,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+6d6834a094767356474d34b099a2f042ddb44e69,TripletGAN: Training Generative Model with Triplet Loss,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+6d6834a094767356474d34b099a2f042ddb44e69,TripletGAN: Training Generative Model with Triplet Loss,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+6d6834a094767356474d34b099a2f042ddb44e69,TripletGAN: Training Generative Model with Triplet Loss,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+6d6834a094767356474d34b099a2f042ddb44e69,TripletGAN: Training Generative Model with Triplet Loss,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+6d741691b7164b636678340dbb5823e437e1c5a9,"Beyond Controllers Human Segmentation, Pose, and Depth Estimation as Game Input Mechanisms",Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+6dbe18855b85bc6f218c53993cf289e2607518b1,Learning Policies to Forecast Agent Behavior with Visual Data,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6dbe18855b85bc6f218c53993cf289e2607518b1,Learning Policies to Forecast Agent Behavior with Visual Data,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+6d0177bb1cd292a2ad4a14e7b9173fcc8b72569c,Leveraging Textural Features for Recognizing Actions in Low Quality Videos,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+6d1cfdb82122cefbc0f27ee7a02d6a22483d6a05,Static Pose Estimation from Depth Images using Random Regression Forests and Hough Voting,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
6d97e69bbba5d1f5c353f9a514d62aff63bc0fb1,Semi-supervised learning for facial expression recognition,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
6d97e69bbba5d1f5c353f9a514d62aff63bc0fb1,Semi-supervised learning for facial expression recognition,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+6da446b59944db9b3d7412ad0efc6c189812d56a,Facial Expression Recognition Using Depth Information and Spatiotemporal Features,SungKyunKwan University,SungKyunKwan University,"성균관대, 덕영대로, 천천동, 장안구, 수원시, 경기, 16357, 대한민국",37.30031270,126.97212300,edu,
+6dd3a95bd46e3ab9c3f649a2034bf5ddba19c710,Learning deep representations for semantic image parsing: a comprehensive overview,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+6d3c8c5869b512090b1283fba28f01c2748b0ebc,Recurrent neural networks for object detection in video sequences,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
6d07e176c754ac42773690d4b4919a39df85d7ec,Face Attribute Prediction Using Off-The-Shelf Deep Learning Networks,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
6dd2a0f9ca8a5fee12edec1485c0699770b4cfdf,Webly-Supervised Video Recognition by Mutually Voting for Relevant Web Images and Web Video Frames,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
6dd2a0f9ca8a5fee12edec1485c0699770b4cfdf,Webly-Supervised Video Recognition by Mutually Voting for Relevant Web Images and Web Video Frames,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+6d8612f7856f569f5635ff07a6b94480a9c7c284,Ensemble perception of emotions in autistic and typical children and adolescents,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+6d8612f7856f569f5635ff07a6b94480a9c7c284,Ensemble perception of emotions in autistic and typical children and adolescents,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
+6d8612f7856f569f5635ff07a6b94480a9c7c284,Ensemble perception of emotions in autistic and typical children and adolescents,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+6d8612f7856f569f5635ff07a6b94480a9c7c284,Ensemble perception of emotions in autistic and typical children and adolescents,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+6d8612f7856f569f5635ff07a6b94480a9c7c284,Ensemble perception of emotions in autistic and typical children and adolescents,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+6d8612f7856f569f5635ff07a6b94480a9c7c284,Ensemble perception of emotions in autistic and typical children and adolescents,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+6d8612f7856f569f5635ff07a6b94480a9c7c284,Ensemble perception of emotions in autistic and typical children and adolescents,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+6d77eef66324951d70d98d6dc99c0e95e5b2fdf6,Modelling Multi-object Activity by Gaussian Processes,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+6dff2bcbfad53238d24f4467a9504ce33ecdfa4d,Illumination Normalization for Color Face Images,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+6d60c427036e63957f1ce72930146964c5743749,Deep Convolutional Neural Networks for Smile Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+6de1299a192fdb852846e3cfa4a428b8fe81523f,Learning Inverse Mapping by AutoEncoder Based Generative Adversarial Nets,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
6dc1f94b852538d572e4919238ddb10e2ee449a4,Objects as context for detecting their semantic parts,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+6dbe76f51091ca6a626a62846a946ce687c3dbe8,INCREMENTAL OBJECT MATCHING WITH PROBABILISTIC METHODS Doctoral dissertation,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+6d4559883ffb8cc611644dce9f1422a98139a7eb,Preserving Semantic Relations for Zero-Shot Learning,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
6d4e3616d0b27957c4107ae877dc0dd4504b69ab,Unsupervised Learning using Sequential Verification for Action Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6d5125c9407c7762620eeea7570af1a8ee7d76f3,Video Frame Interpolation by Plug-and-Play Deep Locally Linear Embedding,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
6d8e3f3a83514381f890ab7cd2a1f1c5be597b69,Improving Text Recognition in Images of Natural Scenes,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
6d8e3f3a83514381f890ab7cd2a1f1c5be597b69,Improving Text Recognition in Images of Natural Scenes,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
6d8eef8f8d6cd8436c55018e6ca5c5907b31ac19,Understanding Representations and Reducing their Redundancy in Deep Networks,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
+6d0b4f5b3391463376c013a6c00d76daf38da578,"A Simple, Fast Diverse Decoding Algorithm for Neural Generation",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+6dc784e98680f417d8dd1a78a417b8ce803ec143,Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+6dc784e98680f417d8dd1a78a417b8ce803ec143,Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+6dc784e98680f417d8dd1a78a417b8ce803ec143,Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+6d5e12ee5d75d5f8c04a196dd94173f96dc8603f,"Learning a similarity metric discriminatively, with application to face verification",Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+6d5e12ee5d75d5f8c04a196dd94173f96dc8603f,"Learning a similarity metric discriminatively, with application to face verification",New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+0159b548d04a21938f066adc44bd7ca95bcb226b,Spectral Clustering with a Convex Regularizer on Millions of Images,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
016800413ebd1a87730a5cf828e197f43a08f4b3,Learning Attributes Equals Multi-Source Domain Generalization,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
016800413ebd1a87730a5cf828e197f43a08f4b3,Learning Attributes Equals Multi-Source Domain Generalization,University of Iowa,University of Iowa,"University of Iowa, Hawkeye Court, Iowa City, Johnson County, Iowa, 52246, USA",41.66590000,-91.57310307,edu,
+0136d9114d62aaedcfbb50ed9594d18e10424179,Learning Visual Models of Social Engagement,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+01239e3c4dd6b7b271df08c17398ceb260979ced,A Signal Processing Approach To Malware Analysis,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+01c840aa27a6c234c0e55e9a5874719bb4d8fbe3,Probabilistic Label Relation Graphs with Ising Models,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
01c9dc5c677aaa980f92c4680229db482d5860db,Temporal Action Detection Using a Statistical Language Model,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
013909077ad843eb6df7a3e8e290cfd5575999d2,A Semi-automatic Methodology for Facial Landmark Annotation,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
013909077ad843eb6df7a3e8e290cfd5575999d2,A Semi-automatic Methodology for Facial Landmark Annotation,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
013909077ad843eb6df7a3e8e290cfd5575999d2,A Semi-automatic Methodology for Facial Landmark Annotation,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
01c7a778cde86ad1b89909ea809d55230e569390,A Supervised Low-Rank Method for Learning Invariant Subspaces,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+01085ce83c6e8781f3d59bf8fb6a2f14c7fda9d6,Nearest neighbor based collection OCR,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+0149b14428de816bd62f80bbfd89238b765edaf7,Classification via Minimum Incremental Coding Length (MICL),"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+01576b5fe525d8dee025fd3776337d74dacdf224,Regression using Gaussian Process manifold kernel dimensionality reduction,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
0115f260069e2e501850a14845feb400142e2443,"An On-Line Handwriting Recognizer with Fisher Matching, Hypotheses Propagation Network and Context Constraint Models",New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+013b72b0941eec78c6a23bb8e94b9447793b7833,Head pose estimation and its application in TV viewers' behavior analysis,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+013b72b0941eec78c6a23bb8e94b9447793b7833,Head pose estimation and its application in TV viewers' behavior analysis,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
01cc8a712e67384f9ef9f30580b7415bfd71e980,Failing to ignore: paradoxical neural effects of perceptual load on early attentional selection in normal aging.,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
01cc8a712e67384f9ef9f30580b7415bfd71e980,Failing to ignore: paradoxical neural effects of perceptual load on early attentional selection in normal aging.,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+013af5a24ec62b000d00d86c1a504573c0f35a3e,Image-guided Non-local Dense Matching with Three-steps Optimization,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
01dc1e03f39901e212bdf291209b7686266aeb13,Actionness Estimation Using Hybrid Fully Convolutional Networks,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
01dc1e03f39901e212bdf291209b7686266aeb13,Actionness Estimation Using Hybrid Fully Convolutional Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
016f49a54b79ec787e701cc8c7d0280273f9b1ef,Self Organizing Maps for Reducing the Number of Clusters by One on Simplex Subspaces,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+01ae6eac1b235dc2057773d5e0bb7b08d7dda7aa,Depth Sweep Regression Forests for Estimating 3D Human Pose from Images,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+01ae6eac1b235dc2057773d5e0bb7b08d7dda7aa,Depth Sweep Regression Forests for Estimating 3D Human Pose from Images,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+01853c864e7eaf0c61cdb2315681224d6a14bde4,Discovering human interactions in videos with limited data labeling,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+01853c864e7eaf0c61cdb2315681224d6a14bde4,Discovering human interactions in videos with limited data labeling,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+0108504305468275985da608b77dbbbe4aee34c7,An efficient branch-and-bound algorithm for optimal human pose estimation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+016eb7b32d1fdec0899151fb03799378bf59bbe5,Point Linking Network for Object Detection,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+01a078cd25b7ce1049efc07bd754980771150775,Visual object detection by parts-based modeling using extended histogram of gradients,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+01a31f75c9c3296cf3cb45b7bad97acb300b7459,Part-Aligned Bilinear Representations for Person Re-identification,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+01a31f75c9c3296cf3cb45b7bad97acb300b7459,Part-Aligned Bilinear Representations for Person Re-identification,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+01a8c7335f0d9321c95d6a57f2dd9f128735f1d7,One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
01125e3c68edb420b8d884ff53fb38d9fbe4f2b8,Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
01125e3c68edb420b8d884ff53fb38d9fbe4f2b8,Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
01c09acf0c046296643de4c8b55a9330e9c8a419,Manifold Learning Using Euclidean -nearest Neighbor Graphs,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
01d23cbac762b0e46251f5dbde08f49f2d13b9f8,Combining Face Verification Experts,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
014143aa16604ec3f334c1407ceaa496d2ed726e,Large-scale manifold learning,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+016b1080c108718fc59e58e47b4867baebd57d8e,Cepstral Methods for Image Feature Extraction,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+014e249422b6bd6ff32b3f7d385b5a0e8c4c9fcf,Attention driven person re-identification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+014e249422b6bd6ff32b3f7d385b5a0e8c4c9fcf,Attention driven person re-identification,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
0182d090478be67241392df90212d6cd0fb659e6,Discovering localized attributes for fine-grained recognition,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
0182d090478be67241392df90212d6cd0fb659e6,Discovering localized attributes for fine-grained recognition,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+0106a2f6251dc9ffc90709c6f0d9b54c1e82326b,Applying scattering operators for face recognition: A comparative study,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
+0106a2f6251dc9ffc90709c6f0d9b54c1e82326b,Applying scattering operators for face recognition: A comparative study,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+01d2b2bffd1c6d77398cfe7011d4cbd3a0bc7fd1,A Dual-Source Approach for 3D Pose Estimation from a Single Image,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+01d2b2bffd1c6d77398cfe7011d4cbd3a0bc7fd1,A Dual-Source Approach for 3D Pose Estimation from a Single Image,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
016a8ed8f6ba49bc669dbd44de4ff31a79963078,Face relighting for face recognition under generic illumination,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+015a5fde8c9c89ae9ae8349183018acb8f0e741f,Egocentric Height Estimation,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+015a5fde8c9c89ae9ae8349183018acb8f0e741f,Egocentric Height Estimation,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+019c5cb085dbbc8a0fc78645e385aa4e0b468fb8,Continuous Learning of Context-dependent Processing in Neural Networks,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+019c5cb085dbbc8a0fc78645e385aa4e0b468fb8,Continuous Learning of Context-dependent Processing in Neural Networks,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+011d461718c39c9d196cb84b2e881c1660ef8f55,Context Aware Active Learning of Activity Recognition Models,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+0141c695e4cf87cc58e0d552004bcb53258c4915,Lying Pose Recognition for Elderly Fall Detection,Orange,Orange Labs,"78 Rue Olivier de Serres, 75015 Paris, France",48.83321220,2.29421550,company,"78 Rue Olivier de Serres, Paris, 75015"
+0141c695e4cf87cc58e0d552004bcb53258c4915,Lying Pose Recognition for Elderly Fall Detection,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+0162e84bbe995ec06e8e59dd9023c67d8f0e8880,Learning to Hash with Partial Tags: Exploring Correlation between Tags and Hashing Bits for Large Scale Image Retrieval,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+016dd886d5cb01c55a0204e2988274cf9417b564,Strong Appearance and Expressive Spatial Models for Human Pose Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+01018a509f32601e1bbf7f0159aad1a513e23f92,Computers in the Human Interaction Loop,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+012e281061126caf2e2c94ca6ba0116c8a8930fb,Human Body Detection and Safety Care System for a Flying Robot,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
+01424c2510fbca67c3cb016ac919f6a58e37541f,2D Human Pose Estimation in TV Shows,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+015df3b57e44b8ddc51c87e5255fa4940bd91963,DSFD: Dual Shot Face Detector,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+01a903739564f575b81c87f7a9e2cb7b609f7ada,Image retrieval using scene graphs,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+0139eb62a87649bf7d259542b5afc6be121b094b,Unsupervised Feature Selection Using Nonnegative Spectral Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0139eb62a87649bf7d259542b5afc6be121b094b,Unsupervised Feature Selection Using Nonnegative Spectral Analysis,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+014043cd53e4faf203e8938f1f32cc494bb414af,Domain Adaptive Subspace Clustering,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+01c687f0cb8c8e1002376f834c9b43b4b653a52f,Beyond shape: incorporating color invariance into a biologically inspired feedforward model of category recognition,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+01c687f0cb8c8e1002376f834c9b43b4b653a52f,Beyond shape: incorporating color invariance into a biologically inspired feedforward model of category recognition,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+01c687f0cb8c8e1002376f834c9b43b4b653a52f,Beyond shape: incorporating color invariance into a biologically inspired feedforward model of category recognition,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+01c687f0cb8c8e1002376f834c9b43b4b653a52f,Beyond shape: incorporating color invariance into a biologically inspired feedforward model of category recognition,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+01dfd60c0851c4e5a99176e99aa369e1b5f606b7,Disentangled Variational Representation for Heterogeneous Face Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+01dfd60c0851c4e5a99176e99aa369e1b5f606b7,Disentangled Variational Representation for Heterogeneous Face Recognition,Johns Hopkins University,"Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA","3400 N Charles St, Baltimore, MD 21218, USA",39.32905300,-76.61942500,edu,
+01efec88d36070dc3bc49f341a77476f74d373bc,Generation and Comprehension of Unambiguous Object Descriptions,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+01efec88d36070dc3bc49f341a77476f74d373bc,Generation and Comprehension of Unambiguous Object Descriptions,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+015d24c1a8621bcb6b6beac3c4d5a34af5589ec6,Classification and feature selection with human performance data,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
+01aad32349489cabfcb619024b297d8f854e9d1f,From visual attributes to adjectives through decompositional distributional semantics,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
019e471667c72b5b3728b4a9ba9fe301a7426fb2,Cross-age face verification by coordinating with cross-face age verification,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+064a79968f593d17934c1cd14def70aac56aecb9,Pose Transferrable Person Re-Identification,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
067126ce1f1a205f98e33db7a3b77b7aec7fb45a,On Improving Dissimilarity-Based Classifications Using a Statistical Similarity Measure,Myongji University,Myongji University,"명지대, 금학로, 역북동, 처인구, 용인시, 경기, 17144, 대한민국",37.23810230,127.19034310,edu,
067126ce1f1a205f98e33db7a3b77b7aec7fb45a,On Improving Dissimilarity-Based Classifications Using a Statistical Similarity Measure,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
06466276c4955257b15eff78ebc576662100f740,Where is who: large-scale photo retrieval by facial attributes and canvas layout,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+06096a9927d45ff82eed34e6b3d6c8fbdc397756,Image In painter Mask Generator Object Classifier Real / Fake ? Is there a person ?,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+06b4522433beca98aea99f924fbaeb8f861df8cd,Selection and combination of local Gabor classifiers for robust face verification,Bogazici University,Bogazici University,"Boğaziçi Üniversitesi Kuzey Yerleşkesi, Okulaltı 1. Sokak, Rumelihisarı, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34467, Türkiye",41.08688410,29.04413167,edu,
+06b4522433beca98aea99f924fbaeb8f861df8cd,Selection and combination of local Gabor classifiers for robust face verification,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+06b4522433beca98aea99f924fbaeb8f861df8cd,Selection and combination of local Gabor classifiers for robust face verification,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
06f585a3a05dd3371cd600a40dc35500e2f82f9b,Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
06f8aa1f436a33014e9883153b93581eea8c5c70,Leaving Some Stones Unturned: Dynamic Feature Prioritization for Activity Detection in Streaming Video,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+065ffca373469c95db28891889289d79e873e2a2,Ensemble Methods for Robust 3D Face Recognition Using Commodity Depth Sensors,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+06aec820d7d4b15f8c49ac4b8246377015693abd,Content Based Image Retrieval Using Signature Representation,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+06b6606e47e071bbe070093c78120207578126fd,Total Moving Face Reconstruction,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+06ba3492e3a9a2e98df2c81b91ec94787e3f97fb,"VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions",University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
061c84a4143e859a7caf6e6d283dfb30c23ee56e,DEEP-CARVING: Discovering visual attributes by carving deep neural nets,Cambridge University,Cambridge University,"University, Cambridge Road, Old Portsmouth, Portsmouth, South East, England, PO1 2HB, UK",50.79440260,-1.09717480,edu,
061e29eae705f318eee703b9e17dc0989547ba0c,Enhancing Expression Recognition in the Wild with Unlabeled Reference Data,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0612832338287cd6569cad32f147bed6df134223,A Comparative Study of Real-time Semantic Segmentation for Autonomous Driving,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+0612832338287cd6569cad32f147bed6df134223,A Comparative Study of Real-time Semantic Segmentation for Autonomous Driving,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+067a40d9fe0942abfc8a31342a95f165a88ca5d6,Optimal Neighborhood Preserving Visualization by Maximum Satisfiability,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+067a40d9fe0942abfc8a31342a95f165a88ca5d6,Optimal Neighborhood Preserving Visualization by Maximum Satisfiability,University of Tampere,University of Tampere,"Tampereen yliopisto, 4, Kalevantie, Ratinanranta, Tulli, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33100, Suomi",61.49412325,23.77920678,edu,
+067a40d9fe0942abfc8a31342a95f165a88ca5d6,Optimal Neighborhood Preserving Visualization by Maximum Satisfiability,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+067a40d9fe0942abfc8a31342a95f165a88ca5d6,Optimal Neighborhood Preserving Visualization by Maximum Satisfiability,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
06850b60e33baa4ea9473811d58c0d5015da079e,A Survey of the Trends in Facial and Expression Recognition Databases and Methods,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
06850b60e33baa4ea9473811d58c0d5015da079e,A Survey of the Trends in Facial and Expression Recognition Databases and Methods,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
06a6347ac14fd0c6bb3ad8190cbe9cdfa5d59efc,Active image clustering: Seeking constraints from humans to complement algorithms,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+06554235c2c9361a14c0569206b58a355a63f01b,Zero-Shot Learning Through Cross-Modal Transfer,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+06eafdc0b281edb8ab4d65012da5d0c94b55970b,Face Recognition with Disparity Corrected Gabor Phase Differences,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+0687e472b5accce40299a6dd109c38e4167fea94,Learning Image Representations for Efficient Recognition of Novel Classes,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+06890d068a7fb82fa78443038ad26ca7623f7a98,Socially-Aware Large-Scale Crowd Forecasting,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+06890d068a7fb82fa78443038ad26ca7623f7a98,Socially-Aware Large-Scale Crowd Forecasting,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+06cf3f55b2bd959d9228d29e1aa3e71ba7cece94,Features for image retrieval: an experimental comparison,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+0630b3677323c8c987f16f37545ac6073293de8d,Enhancement and stylization of photographs by Vladimir Leonid,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
06bad0cdda63e3fd054e7b334a5d8a46d8542817,Sharing features between objects and their attributes,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
06bad0cdda63e3fd054e7b334a5d8a46d8542817,Sharing features between objects and their attributes,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+06ca83cc7def5b0d582f4d933057c4370a6345d7,Training Object Class Detectors with Click Supervision,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+061d303381266e1ee751f5b7551d25324c043bed,Parametric Image Segmentation of Humans with Structural Shape Priors,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+0672976bb2c3b4bde4381f28bf4bbdeeabd3a22e,Mo2Cap2: Real-time Mobile 3D Motion Capture with a Cap-mounted Fisheye Camera,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+06d656c53b17ad7c4ca6345d19cbca271d93ef02,Social and Egocentric Image Classification for Scientific and Privacy Applications,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
0641dbee7202d07b6c78a39eecd312c17607412e,Null space clustering with applications to motion segmentation and face clustering,"Australian National University, Canberra","Australian National University, Canberra","Australian National University, Garran Road, Acton, Canberra, Canberra Central, Australian Capital Territory, 2601, Australia",-35.28121335,149.11665331,edu,
06400a24526dd9d131dfc1459fce5e5189b7baec,Event Recognition in Photo Collections with a Stopwatch HMM,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
062d67af7677db086ef35186dc936b4511f155d7,They are Not Equally Reliable: Semantic Event Search Using Differentiated Concept Classifiers,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
062d67af7677db086ef35186dc936b4511f155d7,They are Not Equally Reliable: Semantic Event Search Using Differentiated Concept Classifiers,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
06c2086f7f72536bf970ca629151b16927104df3,Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+0608313884bea3c286d6cf95ccf9bbff4c77c9f5,Discovering Groups of People in Images,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+0608313884bea3c286d6cf95ccf9bbff4c77c9f5,Discovering Groups of People in Images,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+066476a38f8751696f5f7b47c0fb7f1d8ecdac1a,Automatic adaptation of a generic pedestrian detector to a specific traffic scene,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+063f78c20405158d87114a8aef1bb7557230bd89,An improved deep learning architecture for person re-identification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+060ea3f72ee63d909600caad168cb26b4777b19e,Fusion of Likelihood Ratio Classifier with ICP-based Matcher for 3D Face Recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
060034b59275c13746413ca9c67d6304cba50da6,Ordered Trajectories for Large Scale Human Action Recognition,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
060034b59275c13746413ca9c67d6304cba50da6,Ordered Trajectories for Large Scale Human Action Recognition,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+0611dae4ae932e0c5f28f08676d234dd9233732f,Challenge of multi-camera tracking,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+06f2df0ec9ab6968411e34f581dd8f5d40500d7f,The fusiform face area: a cortical region specialized for the perception of faces.,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+06f2df0ec9ab6968411e34f581dd8f5d40500d7f,The fusiform face area: a cortical region specialized for the perception of faces.,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+063146e2b400cad120d41371a024de319eb67c05,Automatic recognition by gait: progress and prospects,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+06a632adff4f89e8ccb001bfffa1b8a558015938,BubbleView: An Interface for Crowdsourcing Image Importance Maps and Tracking Visual Attention,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+06a632adff4f89e8ccb001bfffa1b8a558015938,BubbleView: An Interface for Crowdsourcing Image Importance Maps and Tracking Visual Attention,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+06a632adff4f89e8ccb001bfffa1b8a558015938,BubbleView: An Interface for Crowdsourcing Image Importance Maps and Tracking Visual Attention,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+061ffd3967540424ac4e4066f4a605d8318bab90,Dirichlet-Based Histogram Feature Transform for Image Classification,National Institute of Advanced Industrial Science and Technology,National Institute of Advanced Industrial Science and Technology,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+061bba574c7c2ef0ba9de91afc4fcab70feddd4f,Paying Attention to Descriptions Generated by Image Captioning Models,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+061bba574c7c2ef0ba9de91afc4fcab70feddd4f,Paying Attention to Descriptions Generated by Image Captioning Models,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
064cd41d323441209ce1484a9bba02a22b625088,Selective Transfer Machine for Personalized Facial Action Unit Detection,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
064cd41d323441209ce1484a9bba02a22b625088,Selective Transfer Machine for Personalized Facial Action Unit Detection,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+0670849811a6ba4fbfcbe11126b811dd94e06e66,Robust Metric and Alignment for Profile-Based Face Recognition: An Experimental Comparison,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+0688c0568f3ab418719260d443cc0d86c3af2914,Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+06625b0c5747ccb8524fec9f44e4a8aa1ecc2151,Nuclear Norm Based Matrix Regression with Applications to Face Recognition with Occlusion and Illumination Changes,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+06c8fcb0429afd3aee153ba42e1fd8aa93f7214f,Social roles in hierarchical models for human activity recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
06c2dfe1568266ad99368fc75edf79585e29095f,Bayesian Active Appearance Models,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
06f39834e870278243dda826658319be2d5d8ded,Recognizing unseen actions in a domain-adapted embedding space,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+06325345f9ffef958d9d7c704b28e6cbb3021b8c,Price theory based power management for heterogeneous multi-cores,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+0657da204bbd5f1e92882b2ccdf4f883659ccd37,Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+06a6976d9a3deac30b0a571d31f85c11ae4eb8ad,A Novel Human Detection Approach Based on Depth Map via Kinect,Curtin University,Curtin University,"Curtin University, Brand Drive, Waterford, Perth, Western Australia, 6102, Australia",-32.00686365,115.89691775,edu,
+06a6976d9a3deac30b0a571d31f85c11ae4eb8ad,A Novel Human Detection Approach Based on Depth Map via Kinect,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+0691b9cd1b9b44bff297a62277be514ede9df01d,Inferring semantic concepts from community-contributed images and noisy tags,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+0691b9cd1b9b44bff297a62277be514ede9df01d,Inferring semantic concepts from community-contributed images and noisy tags,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
06d7ef72fae1be206070b9119fb6b61ce4699587,On One-Shot Similarity Kernels: Explicit Feature Maps and Properties,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
06d7ef72fae1be206070b9119fb6b61ce4699587,On One-Shot Similarity Kernels: Explicit Feature Maps and Properties,University of Patras,University of Patras,"Πανεπιστήμιο Πατρών, Λεωφ. Ιπποκράτους, κ. Ρίου (Αγίου Γεωργίου Ρίου), Πάτρα, Δήμος Πατρέων, Περιφερειακή Ενότητα Αχαΐας, Περιφέρεια Δυτικής Ελλάδας, Πελοπόννησος, Δυτική Ελλάδα και Ιόνιο, 26443, Ελλάδα",38.28994820,21.78864690,edu,
06d7ef72fae1be206070b9119fb6b61ce4699587,On One-Shot Similarity Kernels: Explicit Feature Maps and Properties,Middlesex University,Middlesex University,"Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK",51.59029705,-0.22963221,edu,
+06cb7c6601b7ee0d89cccd5311dcda9e5316e02d,A system for large-scale analysis of distributed cameras,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
062d0813815c2b9864cd9bb4f5a1dc2c580e0d90,Encouraging LSTMs to Anticipate Actions Very Early,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
06a9ed612c8da85cb0ebb17fbe87f5a137541603,Deep Learning of Player Trajectory Representations for Team Activity Analysis,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+6ca21247f5963f6d459e09278812d60c35d10335,Appearance-Based Gaze Estimation via Evaluation-Guided Asymmetric Regression,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+6ca21247f5963f6d459e09278812d60c35d10335,Appearance-Based Gaze Estimation via Evaluation-Guided Asymmetric Regression,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+6ca21247f5963f6d459e09278812d60c35d10335,Appearance-Based Gaze Estimation via Evaluation-Guided Asymmetric Regression,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+6ce111fdfb7ebc8f1fe23ceaf859f7be799d5c91,Activity understanding and unusual event detection in surveillance videos,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
6c66ae815e7e508e852ecb122fb796abbcda16a8,Expression Recognition Databases and Methods,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+6ce1a8240b0eba18c40136370e143209dec4a5a7,Predicting Future Instance Segmentation by Forecasting Convolutional Features,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+6c3b2fd0cb23ddb6ed707d6c9986a78d6b76bf43,Interleaved Group Convolutions for Deep Neural Networks,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+6c3b2fd0cb23ddb6ed707d6c9986a78d6b76bf43,Interleaved Group Convolutions for Deep Neural Networks,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
6ca2c5ff41e91c34696f84291a458d1312d15bf2,LipNet: Sentence-level Lipreading,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+6c06ad0b4b7c981089b5a8037d5b9f9e5b928196,Image Retrieval with Structured Object Queries Using Latent Ranking SVM,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+6c06ad0b4b7c981089b5a8037d5b9f9e5b928196,Image Retrieval with Structured Object Queries Using Latent Ranking SVM,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
6c690af9701f35cd3c2f6c8d160b8891ad85822a,Multi-Task Learning with Low Rank Attribute Embedding for Person Re-Identification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
6c690af9701f35cd3c2f6c8d160b8891ad85822a,Multi-Task Learning with Low Rank Attribute Embedding for Person Re-Identification,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
6c690af9701f35cd3c2f6c8d160b8891ad85822a,Multi-Task Learning with Low Rank Attribute Embedding for Person Re-Identification,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
6c5fbf156ef9fc782be0089309074cc52617b868,Controllable Video Generation with Sparse Trajectories,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
6ce23cf4f440021b7b05aa3c1c2700cc7560b557,Learning Local Convolutional Features for Face Recognition with 2D-Warping,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+6c0e0c3e66622023c64c664c3411a6fe1c87d5c5,Efficient Fine-Grained Classification and Part Localization Using One Compact Network,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+6c0e0c3e66622023c64c664c3411a6fe1c87d5c5,Efficient Fine-Grained Classification and Part Localization Using One Compact Network,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+6c0e0c3e66622023c64c664c3411a6fe1c87d5c5,Efficient Fine-Grained Classification and Part Localization Using One Compact Network,SRI International,SRI International,"SRI International Building, West 1st Street, Menlo Park, San Mateo County, California, 94025, USA",37.45857960,-122.17560525,edu,
6c80c834d426f0bc4acd6355b1946b71b50cbc0b,Pose-Based Two-Stream Relational Networks for Action Recognition in Videos,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+6c032a08fba885960e531a02641d121b81cb7c32,Representation Of Objects In A Volumetric Frequency Domain With Application To Face Recognition,University of Illinois at Chicago,University of Illinois at Chicago,"University of Illinois at Chicago, West Taylor Street, Greektown, Chicago, Cook County, Illinois, 60607, USA",41.86898915,-87.64856256,edu,
+6c78add400f749c897dc3eb93996eda1c796e91c,Enhanced Random Forest with Image/Patch-Level Learning for Image Understanding,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
+6c78add400f749c897dc3eb93996eda1c796e91c,Enhanced Random Forest with Image/Patch-Level Learning for Image Understanding,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+6c78add400f749c897dc3eb93996eda1c796e91c,Enhanced Random Forest with Image/Patch-Level Learning for Image Understanding,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+6ca45b402a204351691c6f12a84cba3be1c5fd56,An overview of content-based image retrieval techniques ( CBIR ),Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+6cf9322009fb8f36c01fc54d213e9cd745e62468,Semi-supervised distance metric learning for person re-identification,Yunnan University,Yunnan University,"云南大学, 一二一大街, 志城家园, 五华区, 五华区 (Wuhua), 昆明市 (Kunming), 云南省, 650030, 中国",25.05703205,102.70027525,edu,
+6c388fc4503636245fd464a05a9f843b303ad79a,Cross camera people counting with perspective estimation and occlusion handling,"Academia Sinica, Taiwan","Research Center for Institute of Information Science, Academia Sinica, Taiwan","115, Taiwan, Taipei City, Nangang District, 研究院路二段128號",25.04117270,121.61465180,edu,
+6c388fc4503636245fd464a05a9f843b303ad79a,Cross camera people counting with perspective estimation and occlusion handling,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
+6c97af4c5d9908c288626d833818d7095f635765,Multi-Task Learning Improves Disease Models fromWeb Search,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+6c97af4c5d9908c288626d833818d7095f635765,Multi-Task Learning Improves Disease Models fromWeb Search,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+6c97af4c5d9908c288626d833818d7095f635765,Multi-Task Learning Improves Disease Models fromWeb Search,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+6c26743e131a67b25738beffcee05da6af5d87d9,First Person Action Recognition Using Deep Learned Descriptors,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+6c4e173fdafa89ac7b40e1dddf953dcc833db92d,Photometric Normalization for Face Recognition using Local discrete cosine Transform,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+6c9ed3378dd53a5ad9e30613ba2e1ef363bd1f9d,Atoms of recognition in human and computer vision.,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
+6c9ed3378dd53a5ad9e30613ba2e1ef363bd1f9d,Atoms of recognition in human and computer vision.,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
6c6bb85a08b0bdc50cf8f98408d790ccdb418798,Recognition of facial expressions in presence of partial occlusion,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
6c705285c554985ecfe1117e854e1fe1323f8c21,DIY Human Action Data Set Generation,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+6caa275cc502513550bde0a32416a3b32470161b,Sparse shape modelling for 3D face analysis,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+6c7a36efbe07ab295ddebc60c834cf74ec30ba50,Group Consistent Similarity Learning via Deep CRF for Person Re-Identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+6c7a36efbe07ab295ddebc60c834cf74ec30ba50,Group Consistent Similarity Learning via Deep CRF for Person Re-Identification,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+6c182ec9bd85cf61b01c90955c81d71926b0198a,A Deeply-Recursive Convolutional Network For Crowd Counting,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+6c182ec9bd85cf61b01c90955c81d71926b0198a,A Deeply-Recursive Convolutional Network For Crowd Counting,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+6c70cad229cf3f02d3d490b42c7bd92c6eade1d1,Towards Good Practices on Building Effective CNN Baseline Model for Person Re-identification,"A*STAR, Singapore","Institute for Infocomm Research, A*STAR, Singapore","1 Fusionopolis Way, #21-01 Connexis, Singapore 138632",1.29889260,103.78731070,edu,
+6c61e496afd6577aa330b1f48ad0cec1d35b32d0,Deep Interactive Evolution,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+6c61e496afd6577aa330b1f48ad0cec1d35b32d0,Deep Interactive Evolution,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+6c61e496afd6577aa330b1f48ad0cec1d35b32d0,Deep Interactive Evolution,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+3920a205990abc7883c70cc96a0410a2d056c2a8,Fast Object Segmentation in Unconstrained Video,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+3920a205990abc7883c70cc96a0410a2d056c2a8,Fast Object Segmentation in Unconstrained Video,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+397f572e759aed28ffd4deb2d3acf18c991e8cf9,Associative Embeddings for Large-Scale Knowledge Transfer with Self-Assessment,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+397f343180dc4c9f40c1c706217956126a09d157,Face-Cap: Image Captioning using Facial Expression Analysis,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+391af839051826ec317a6ea61010734baf536551,Question-Guided Hybrid Convolution for Visual Question Answering,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+393a62cab9e2a1cc82c1663fdbbf1aefb781c36b,Chained Predictions Using Convolutional Neural Networks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+390cc673792dbf47939f621aef5bb774ca01dc46,Isotropic Granularity-tunable gradients partition (IGGP) descriptors for human detection,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+396aacab076a3607429f58ce442d5d57b5aaa794,Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
3991223b1dc3b87883cec7af97cf56534178f74a,A unified framework for context assisted face clustering,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+39db629b96eda72a23a49d54f32689e0651ca4ae,Applying artificial vision models to human scene understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+39db629b96eda72a23a49d54f32689e0651ca4ae,Applying artificial vision models to human scene understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+39db629b96eda72a23a49d54f32689e0651ca4ae,Applying artificial vision models to human scene understanding,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+39db629b96eda72a23a49d54f32689e0651ca4ae,Applying artificial vision models to human scene understanding,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+39db629b96eda72a23a49d54f32689e0651ca4ae,Applying artificial vision models to human scene understanding,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
+3900fb44902396f94fb070be41199b4beecc9081,Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
396a19e29853f31736ca171a3f40c506ef418a9f,Real World Real-time Automatic Recognition of Facial Expressions,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+39f48090df19dd0122590ef839226f8b2bcbe609,The MPI Emotional Body Expressions Database for Narrative Scenarios,Max Planck Institute for Biological Cybernetics,Max Planck Institute for Biological Cybernetics,"Max-Planck-Institut für Biologische Kybernetik, 8, Max-Planck-Ring, Max-Planck-Institut, Wanne, Tübingen, Landkreis Tübingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72076, Deutschland",48.53691250,9.05922533,edu,
+39f48090df19dd0122590ef839226f8b2bcbe609,The MPI Emotional Body Expressions Database for Narrative Scenarios,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
392d35bb359a3b61cca1360272a65690a97a2b3f,Multi-Task Transfer Methods to Improve One-Shot Learning for Multimedia Event Detection,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+398dbeafe5c96b90a243d408b1280524be5bbab2,VGAN-Based Image Representation Learning for Privacy-Preserving Facial Expression Recognition,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+398dbeafe5c96b90a243d408b1280524be5bbab2,VGAN-Based Image Representation Learning for Privacy-Preserving Facial Expression Recognition,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+398dbeafe5c96b90a243d408b1280524be5bbab2,VGAN-Based Image Representation Learning for Privacy-Preserving Facial Expression Recognition,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
39c48309b930396a5a8903fdfe781d3e40d415d0,Learning Spatial and Temporal Cues for Multi-Label Facial Action Unit Detection,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
39c48309b930396a5a8903fdfe781d3e40d415d0,Learning Spatial and Temporal Cues for Multi-Label Facial Action Unit Detection,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+39742f9b3a9f7adefbe936de68249148576b90da,Alcohol and remembering a hypothetical sexual assault: Can people who were under the influence of alcohol during the event provide accurate testimony?,Loughborough University,Loughborough University,"Computer Science, University Road, Charnwood, Leicestershire, East Midlands, England, LE11 3TP, UK",52.76635770,-1.22924610,edu,
+39bbe9885ad1e12e79bc620d83f7768d2fc04994,Autism is characterized by dorsal anterior cingulate hyperactivation during social target detection.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+39b741be40e093f92519cd15cd2deb6e114d6200,Joint Probabilistic Data Association Revisited,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+39b741be40e093f92519cd15cd2deb6e114d6200,Joint Probabilistic Data Association Revisited,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+3947fe473d8cfa443ea4cf6571d2aebe7b2066b6,Evolutionary Architecture Search For Deep Multitask Networks,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+39c254cd706b9fb89b369b41b1c4d3949cb554f8,DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
39f525f3a0475e6bbfbe781ae3a74aca5b401125,Deep Joint Face Hallucination and Recognition,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
39f525f3a0475e6bbfbe781ae3a74aca5b401125,Deep Joint Face Hallucination and Recognition,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
39f525f3a0475e6bbfbe781ae3a74aca5b401125,Deep Joint Face Hallucination and Recognition,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
39f525f3a0475e6bbfbe781ae3a74aca5b401125,Deep Joint Face Hallucination and Recognition,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
3946b8f862ecae64582ef0912ca2aa6d3f6f84dc,Who and Where: People and Location Co-Clustering,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
3933416f88c36023a0cba63940eb92f5cef8001a,Learning Robust Subspace Clustering,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+39c118c4f3c02daf7edcf207dfc690814967e8e8,Simultaneous alignment and clustering for an image ensemble,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
39150acac6ce7fba56d54248f9c0badbfaeef0ea,"Digital Signal Processing for in - Vehicle and mobile systems , Istanbul , Turkey , June 2007 . MACHINE LEARNING SYSTEMS FOR DETECTING DRIVER DROWSINESS",Sabanci University,Sabanci University,"Sabanci Universitesi, Preveze Cad., Orta Mahallesi, Tepeören, Tuzla, İstanbul, Marmara Bölgesi, 34953, Türkiye",40.89271590,29.37863323,edu,
+39e55283e6eb3f0f9db07cf1b20e0de8d5aac10e,Diverse Image Captioning via GroupTalk,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+39c54d22a0f29605f96ab57720cde8c6aa743c10,Human Instance Segmentation from Video using Detector-based Conditional Random Fields,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+39c54d22a0f29605f96ab57720cde8c6aa743c10,Human Instance Segmentation from Video using Detector-based Conditional Random Fields,Oxford University,Oxford University,"University College, Logic Lane, Grandpont, Oxford, Oxon, South East, England, OX1 4EX, UK",51.75208490,-1.25166460,edu,
39f03d1dfd94e6f06c1565d7d1bb14ab0eee03bc,Simultaneous Local Binary Feature Learning and Encoding for Face Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
39f03d1dfd94e6f06c1565d7d1bb14ab0eee03bc,Simultaneous Local Binary Feature Learning and Encoding for Face Recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+3983370efe7a7521bde255017171724d845b3383,Learning Discriminators as Energy Networks in Adversarial Learning,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+3983370efe7a7521bde255017171724d845b3383,Learning Discriminators as Energy Networks in Adversarial Learning,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+3983370efe7a7521bde255017171724d845b3383,Learning Discriminators as Energy Networks in Adversarial Learning,University of Iowa,University of Iowa,"University of Iowa, Hawkeye Court, Iowa City, Johnson County, Iowa, 52246, USA",41.66590000,-91.57310307,edu,
+3983370efe7a7521bde255017171724d845b3383,Learning Discriminators as Energy Networks in Adversarial Learning,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+395e007cf11dd3082d059b8c96dcffae628ffb4f,Learning-Based Incremental Creation of Web Image Databases,Alexandria University,Alexandria University,"جامعة الإسكندرية, الكورنيش, إبراهيمية, الإسكندرية, 21522, مصر",31.21051105,29.91314562,edu,
+394bf41cd8578ec10cd34452c688c3e3de1c16a7,Multi-view to Novel View: Synthesizing Novel Views With Self-learned Confidence,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+397349476582198639abc7a8b933e350cbc24c37,2D&3D-ComFusFace: 2D and 3D Face Recognition by Scalable Fusion of Common Features,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+397349476582198639abc7a8b933e350cbc24c37,2D&3D-ComFusFace: 2D and 3D Face Recognition by Scalable Fusion of Common Features,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+3991c704ef1030c5bfead2b58463d39842b52985,Can Facial Uniqueness be Inferred from Impostor Scores?,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
3983637022992a329f1d721bed246ae76bc934f7,Wide-baseline stereo for face recognition with large pose variation,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
39ecdbad173e45964ffe589b9ced9f1ebfe2d44e,Automatic recognition of lower facial action units,Vrije Universiteit Brussel,Vrije Universiteit Brussel,"Vrije Universiteit Brussel, 170, Quai de l'Industrie - Nijverheidskaai, Anderlecht, Brussel-Hoofdstad - Bruxelles-Capitale, Région de Bruxelles-Capitale - Brussels Hoofdstedelijk Gewest, 1070, België / Belgique / Belgien",50.84110070,4.32377555,edu,
+99e9ae76ee720314a90968be5f889d233c67054c,A Window to Your Smartphone: Exploring Interaction and Communication in Immersive VR with Augmented Virtuality,Memorial University of Newfoundland,Memorial University of Newfoundland,"Memorial University of Newfoundland, Overpass, St. John's, Newfoundland and Labrador, A1B 5S7, Canada",47.57272510,-52.73305444,edu,
+995495e36f4a2af999875ea4f197ca98c5e5c8de,Dynamic Task Prioritization for Multitask Learning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
999289b0ef76c4c6daa16a4f42df056bf3d68377,The Role of Color and Contrast in Facial Age Estimation,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
999289b0ef76c4c6daa16a4f42df056bf3d68377,The Role of Color and Contrast in Facial Age Estimation,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+99911a8effd2ab3af4b4ba802920f3e1720a83e6,Integral Human Pose Regression,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+99911a8effd2ab3af4b4ba802920f3e1720a83e6,Integral Human Pose Regression,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+99911a8effd2ab3af4b4ba802920f3e1720a83e6,Integral Human Pose Regression,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+9941a52ef4db2eb338eec061a950af6a95f82510,Encoding Neuroanatomical Information using Weighted Spherical Harmonic Representation,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+99c69fe118efbc47efc91ceaa3b2e711405eef20,Scale-Adaptive Convolutions for Scene Parsing,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+99c69fe118efbc47efc91ceaa3b2e711405eef20,Scale-Adaptive Convolutions for Scene Parsing,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+999cdddf1ca23e4a72028d2a88537cf4a7aa9396,Hyperprior Induced Unsupervised Disentanglement of Latent Representations,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+9954f7ee5288724184f9420e39cca9165efa6822,Estimation of object functions using deformable part model,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+9954f7ee5288724184f9420e39cca9165efa6822,Estimation of object functions using deformable part model,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+9954f7ee5288724184f9420e39cca9165efa6822,Estimation of object functions using deformable part model,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
+9937a4d3fa66c0eea48b2090b5a9b6c51a1cce66,Human Pose Estimation Using Global and Local Normalization,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+9937a4d3fa66c0eea48b2090b5a9b6c51a1cce66,Human Pose Estimation Using Global and Local Normalization,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+9937a4d3fa66c0eea48b2090b5a9b6c51a1cce66,Human Pose Estimation Using Global and Local Normalization,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
995d55fdf5b6fe7fb630c93a424700d4bc566104,The One Triangle Three Parallelograms Sampling Strategy and Its Application in Shape Regression,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
993d189548e8702b1cb0b02603ef02656802c92b,Highly-Economized Multi-View Binary Compression for Scalable Image Clustering,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
993d189548e8702b1cb0b02603ef02656802c92b,Highly-Economized Multi-View Binary Compression for Scalable Image Clustering,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+992eca71ee8314ede9bf680b6966730f6bb77bc5,Likability’s Effect on Interpersonal Motor Coordination: Exploring Natural Gaze Direction,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+992eca71ee8314ede9bf680b6966730f6bb77bc5,Likability’s Effect on Interpersonal Motor Coordination: Exploring Natural Gaze Direction,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+99b41df501f25f4aee9c1f94a75510b2fbcc6bed,Title Impaired social brain network for processing dynamic facialexpressions in autism spectrum disorders,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+99bc96eea249e28b3e741fbe15757a38d52631bc,Streaming Behaviour : Live Streaming as a Paradigm for Multiview Analysis of Emotional and Social Signals,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+99bc96eea249e28b3e741fbe15757a38d52631bc,Streaming Behaviour : Live Streaming as a Paradigm for Multiview Analysis of Emotional and Social Signals,"London, United Kingdom","London, United Kingdom","London, Greater London, England, SW1A 2DU, UK",51.50732190,-0.12764740,edu,
+99bc96eea249e28b3e741fbe15757a38d52631bc,Streaming Behaviour : Live Streaming as a Paradigm for Multiview Analysis of Emotional and Social Signals,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+99bc96eea249e28b3e741fbe15757a38d52631bc,Streaming Behaviour : Live Streaming as a Paradigm for Multiview Analysis of Emotional and Social Signals,"London, United Kingdom","London, United Kingdom","London, Greater London, England, SW1A 2DU, UK",51.50732190,-0.12764740,edu,
+9952d6630a2fcadf34e356de07ebd2254651c95e,Dual-Feature Bayesian MAP Classification: Exploiting Temporal Information for Video-Based Face Recognition,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+9952d6630a2fcadf34e356de07ebd2254651c95e,Dual-Feature Bayesian MAP Classification: Exploiting Temporal Information for Video-Based Face Recognition,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+9947687ffe0bd2d6cd4fe717e534cfcb59302a4e,Data-driven photographic style using local transfer,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
994b52bf884c71a28b4f5be4eda6baaacad1beee,Categorizing Big Video Data on the Web: Challenges and Opportunities,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+99783c792947f17e41c94ddaac31766277809049,Switching Convolutional Neural Network for Crowd Counting,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+995dd15671993b2165860c54bf5acbbe421c5f45,Learning a Context Aware Dictionary for Sparse Representation,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+99029377dac51a3f60063f61cdc5471866c348be,Making Third Person Techniques Recognize First-Person Actions in Egocentric Videos,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
99001ac9fdaf7649c0d0bd8d2078719bafd216d9,General Tensor Discriminant Analysis and Gabor Features for Gait Recognition,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
99001ac9fdaf7649c0d0bd8d2078719bafd216d9,General Tensor Discriminant Analysis and Gabor Features for Gait Recognition,University of Vermont,University of Vermont,"University of Vermont, Colchester Avenue, Burlington, Chittenden County, Vermont, 05401, USA",44.48116865,-73.20021790,edu,
+992b93ab9d016640551a8cebcaf4757288154f32,Nested Pictorial Structures,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
9901f473aeea177a55e58bac8fd4f1b086e575a4,Human and sheep facial landmarks localisation by triplet interpolated features,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+990bf0171deae7f788f4867c155a276fca5c891a,An Overview of First Person Vision and Egocentric Video Analysis for Personal Mobile Wearable Devices,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
99facca6fc50cc30f13b7b6dd49ace24bc94f702,VIPLFaceNet: an open source deep face recognition SDK,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
99facca6fc50cc30f13b7b6dd49ace24bc94f702,VIPLFaceNet: an open source deep face recognition SDK,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+99eddbd03e39c86260e282c7a0993617710d5cb1,An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+99eddbd03e39c86260e282c7a0993617710d5cb1,An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+99daa2839213f904e279aec7cef26c1dfb768c43,DocFace: Matching ID Document Photos to Selfies,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
523854a7d8755e944bd50217c14481fe1329a969,A Differentially Private Kernel Two-Sample Test,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
523854a7d8755e944bd50217c14481fe1329a969,A Differentially Private Kernel Two-Sample Test,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+52d9477a8293d44b0f8be5c07d56d468d035b0b0,The Power of Randomization: Distributed Submodular Maximization on Massive Datasets,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+52d9477a8293d44b0f8be5c07d56d468d035b0b0,The Power of Randomization: Distributed Submodular Maximization on Massive Datasets,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+52d9477a8293d44b0f8be5c07d56d468d035b0b0,The Power of Randomization: Distributed Submodular Maximization on Massive Datasets,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
521cfbc1949289a7ffc3ff90af7c55adeb43db2a,Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
521cfbc1949289a7ffc3ff90af7c55adeb43db2a,Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
521cfbc1949289a7ffc3ff90af7c55adeb43db2a,Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+529073b49fb28e8919d6862f2ae445477c7337bd,Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+529073b49fb28e8919d6862f2ae445477c7337bd,Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning,University of Massachusetts Dartmouth,University of Massachusetts Dartmouth,"University of Massachusetts Dartmouth, University Ring Road, Dartmouth, Bristol County, Massachusetts, 02747, USA",41.62772475,-71.00724501,edu,
+529073b49fb28e8919d6862f2ae445477c7337bd,Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+520d586b50ecaa9753f714c6e76e6b819663d1a4,On the Dimensionality Reduction for Sparse Representation Based Face Recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+525eb080b158a492bfd02b421891c7383303dac5,Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+5288e1e7e914f73bf65c745f328844907226cd3e,Learning Deep Binary Descriptor with Multi-quantization,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+5288e1e7e914f73bf65c745f328844907226cd3e,Learning Deep Binary Descriptor with Multi-quantization,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+520796fed11df39bba7ea03844f4f465a6bf0655,"Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion Recognition",Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+520796fed11df39bba7ea03844f4f465a6bf0655,"Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion Recognition",Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+520796fed11df39bba7ea03844f4f465a6bf0655,"Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion Recognition",Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+528c03761682f73eed7d736c19551856fe92b1e1,"Uncovering Interactions and Interactors: Joint Estimation of Head, Body Orientation and F-Formations from Surveillance Videos","University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+528c03761682f73eed7d736c19551856fe92b1e1,"Uncovering Interactions and Interactors: Joint Estimation of Head, Body Orientation and F-Formations from Surveillance Videos",University of Perugia,University of Perugia,"Caffe Perugia, 2350, Health Sciences Mall, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.26224210,-123.24500520,edu,
+528c03761682f73eed7d736c19551856fe92b1e1,"Uncovering Interactions and Interactors: Joint Estimation of Head, Body Orientation and F-Formations from Surveillance Videos","University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
5253c94f955146ba7d3566196e49fe2edea1c8f4,Internet Based Morphable Model,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
529b1f33aed49dbe025a99ac1d211c777ad881ec,Fast and exact bi-directional fitting of active appearance models,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
529b1f33aed49dbe025a99ac1d211c777ad881ec,Fast and exact bi-directional fitting of active appearance models,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
523b2cbc48decfabffb66ecaeced4fe6a6f2ac78,Photorealistic facial expression synthesis by the conditional difference adversarial autoencoder,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
52472ec859131844f38fc7d57944778f01d109ac,Improving Speaker Turn Embedding by Crossmodal Transfer Learning from Face Embedding,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+52c89ca39a9fcad716e1e43c0bd4e40101c15d64,Robust Face Recognition via Sparse Representation,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+52c89ca39a9fcad716e1e43c0bd4e40101c15d64,Robust Face Recognition via Sparse Representation,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
5287d8fef49b80b8d500583c07e935c7f9798933,Generative Adversarial Text to Image Synthesis,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
5287d8fef49b80b8d500583c07e935c7f9798933,Generative Adversarial Text to Image Synthesis,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+529b933b0dc9c657cf829fd9bb7ff7c47d5e6d19,Integrating crowd simulation for pedestrian tracking in a multi-camera system,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
52c59f9f4993c8248dd3d2d28a4946f1068bcbbe,Structural similarity and distance in learning,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
52c59f9f4993c8248dd3d2d28a4946f1068bcbbe,Structural similarity and distance in learning,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
52c59f9f4993c8248dd3d2d28a4946f1068bcbbe,Structural similarity and distance in learning,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
@@ -2944,49 +8093,141 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 52bf00df3b970e017e4e2f8079202460f1c0e1bd,Learning High-level Prior with Convolutional Neural Networks for Semantic Segmentation,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
52bf00df3b970e017e4e2f8079202460f1c0e1bd,Learning High-level Prior with Convolutional Neural Networks for Semantic Segmentation,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
52c91fcf996af72d191520d659af44e310f86ef9,Interactive Image Search with Attribute-based Guidance and Personalization,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+52f8eb239997d9a324d4794529c60522db8d08bf,Learning Multi-scale Block Local Binary Patterns for Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+52572058f015761f2113aa25a341c607a286fca4,Real-Time Simultaneous Pose and Shape Estimation for Articulated Objects Using a Single Depth Camera,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
52885fa403efbab5ef21274282edd98b9ca70cbf,Discriminant Graph Structures for Facial Expression Recognition,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
52885fa403efbab5ef21274282edd98b9ca70cbf,Discriminant Graph Structures for Facial Expression Recognition,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+527dd9647c474490ac33ac5b0a19aa76b226610d,Intact perception but abnormal orientation towards face-like objects in young children with ASD,University of Toulouse,University of Toulouse,"Toulouse, Lake Charles, Calcasieu Parish, Louisiana, 70605, USA",30.17818160,-93.23605810,edu,
+5284e9d84ef74683c306314e7a79786438514c90,Exploring the Long Tail of Social Media Tags,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+52a152b985b298be4b382d0b6045e31f43850c6f,Rank Persistence: Assessing the Temporal Performance of Real-World Person Re-Identification,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+52b0104a43f55c5652001c06dfabfc4c327018bf,Hybrid-Indexing Multi-type Features for Large-Scale Image Search,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+52b0104a43f55c5652001c06dfabfc4c327018bf,Hybrid-Indexing Multi-type Features for Large-Scale Image Search,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+52bfa4a8b3e3b8e0c0031ae53caddb4c067c04e3,Procrustean Normal Distribution for Non-Rigid Structure from Motion,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+52049fb96156729ce0ad88f86fa617ecf7d237e1,Book chapter for Machine Learning for Human Motion Analysis: Theory and Practice,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+52049fb96156729ce0ad88f86fa617ecf7d237e1,Book chapter for Machine Learning for Human Motion Analysis: Theory and Practice,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
52d7eb0fbc3522434c13cc247549f74bb9609c5d,WIDER FACE: A Face Detection Benchmark,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
528069963f0bd0861f380f53270c96c269a3ea1c,4D (3D Dynamic) statistical models of conversational expressions and the synthesis of highly-realistic 4D facial expression sequences,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+52bc0f02e34ed1e2ce1f77d8f07aea2b87813e89,Face and Eye Detection for Person Authentication in Mobile Phones,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+523303e477d3b5f27373047c576b9b6dbe478f8d,Everyday Eye Contact Detection Using Unsupervised Gaze Target Discovery,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+5240941af3b263609acaa168f96e1decdb0b3fe4,Action classification in still images using human eye movements,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+5257c447f9c50ee8bb2011fb72f8bd40bc0291d8,Automatic gait recognition using area-based metrics,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
556b9aaf1bc15c928718bc46322d70c691111158,Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+55e4cf29055d1556baf72cd17d2bdb692c8554c0,Do deep features retrieve X?: A tool for quick inspection of deep visual similarities,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+55089f9bc858ae7e9addf30502ac11be4347c05a,A Privacy-Preserving Deep Learning Approach for Face Recognition with Edge Computing,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+55089f9bc858ae7e9addf30502ac11be4347c05a,A Privacy-Preserving Deep Learning Approach for Face Recognition with Edge Computing,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+55089f9bc858ae7e9addf30502ac11be4347c05a,A Privacy-Preserving Deep Learning Approach for Face Recognition with Edge Computing,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+55089f9bc858ae7e9addf30502ac11be4347c05a,A Privacy-Preserving Deep Learning Approach for Face Recognition with Edge Computing,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+554f10d7b8933e9590551a4f891d034b9b8e8642,Learning Individualized Facial Expressions in an Avatar with PSO and Tabu Search,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+553ffb04c193eedde286c944f4816d46248d9822,"Hi, magic closet, tell me what to wear!",National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
558fc9a2bce3d3993a9c1f41b6c7f290cefcf92f,Efficient and Effective Solutions for Video Classification,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
558fc9a2bce3d3993a9c1f41b6c7f290cefcf92f,Efficient and Effective Solutions for Video Classification,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
55138c2b127ebdcc508503112bf1d1eeb5395604,Ensemble Nystrom Method,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+55af4918d6b20d13c58c482d7e31e17db53c6ab5,When Fashion Meets Big Data: Discriminative Mining of Best Selling Clothing Features,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+55af4918d6b20d13c58c482d7e31e17db53c6ab5,When Fashion Meets Big Data: Discriminative Mining of Best Selling Clothing Features,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+55bb6235eaec0459183b5442f46501d29b824a9b,Re-identification of persons in multi-camera surveillance under varying viewpoints and illumination,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
55e18e0dde592258882134d2dceeb86122b366ab,Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+55206f0b5f57ce17358999145506cd01e570358c,O M 4 . 1 The Subject Database 4 . 2 Experiment Plan 5 . 1 Varying the Overlap 4 Experimental Setup 5 Parameterisation Results,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+55d0eaf7393bb6bd0483c98894f16269d275c2bd,MMGAN: Manifold Matching Generative Adversarial Network,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+55d0eaf7393bb6bd0483c98894f16269d275c2bd,MMGAN: Manifold Matching Generative Adversarial Network,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+55d0eaf7393bb6bd0483c98894f16269d275c2bd,MMGAN: Manifold Matching Generative Adversarial Network,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+55d0eaf7393bb6bd0483c98894f16269d275c2bd,MMGAN: Manifold Matching Generative Adversarial Network,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+55d0eaf7393bb6bd0483c98894f16269d275c2bd,MMGAN: Manifold Matching Generative Adversarial Network,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+55d0eaf7393bb6bd0483c98894f16269d275c2bd,MMGAN: Manifold Matching Generative Adversarial Network,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+55eb5691479268718627a39237fadbe649b34ecc,Bayesian Optimization with an Empirical Hardness Model for approximate Nearest Neighbour Search,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+55f2626b7250b3b24dd0d2bab3ef3c3bbd9b3758,Answering Image Riddles using Vision and Reasoning through Probabilistic Soft Logic,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+55f2626b7250b3b24dd0d2bab3ef3c3bbd9b3758,Answering Image Riddles using Vision and Reasoning through Probabilistic Soft Logic,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+5583a131ab89aef81cee3e60d32160685c24d694,Gabor-feature-based local generic representation for face recognition with single sample per person,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+5583a131ab89aef81cee3e60d32160685c24d694,Gabor-feature-based local generic representation for face recognition with single sample per person,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+5583a131ab89aef81cee3e60d32160685c24d694,Gabor-feature-based local generic representation for face recognition with single sample per person,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
55966926e7c28b1eee1c7eb7a0b11b10605a1af0,Surpassing Human-Level Face Verification Performance on LFW with GaussianFace,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
552c55c71bccfc6de7ce1343a1cd12208e9a63b3,Accurate eye center location and tracking using isophote curvature,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+555f5ef266335af8189714297ccbcd6ab77d83f2,Marginalized CNN: Learning Deep Invariant Representations,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
5517b28795d7a68777c9f3b2b46845dcdb425b2c,Deep video gesture recognition using illumination invariants,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
55e87050b998eb0a8f0b16163ef5a28f984b01fa,Can you Find a Face in a HEVC Bitstream?,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
55bc7abcef8266d76667896bbc652d081d00f797,Impact of facial cosmetics on automatic gender and age estimation algorithms,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
55bc7abcef8266d76667896bbc652d081d00f797,Impact of facial cosmetics on automatic gender and age estimation algorithms,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
55b4b1168c734eeb42882082bd131206dbfedd5b,Learning to Align from Scratch,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
55b4b1168c734eeb42882082bd131206dbfedd5b,Learning to Align from Scratch,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+550c8162757b9fb649efab8529d86daa99700fb1,Athlete Pose Estimation by a Global-Local Network,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+555f75077a02f33a05841f9b63a1388ec5fbcba5,A Survey on Periocular Biometrics Research,Halmstad University,Halmstad University,"Högskolan i Halmstad, 3, Kristian IV:s väg, Larsfrid, Nyhem, Halmstad, Hallands län, Götaland, 301 18, Sverige",56.66340325,12.87929727,edu,
55804f85613b8584d5002a5b0ddfe86b0d0e3325,Data Complexity in Machine Learning,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+557890cef6e9285909904fa141ccddddc0da90dd,Target Identity-aware Network Flow for online multiple target tracking,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+557890cef6e9285909904fa141ccddddc0da90dd,Target Identity-aware Network Flow for online multiple target tracking,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+55c0113534c62b7f3f238210cf501b42d91cc33a,Hand Keypoint Detection in Single Images Using Multiview Bootstrapping,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
55eb7ec9b9740f6c69d6e62062a24bfa091bbb0c,CAS(ME)2: A Database of Spontaneous Macro-expressions and Micro-expressions,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
55eb7ec9b9740f6c69d6e62062a24bfa091bbb0c,CAS(ME)2: A Database of Spontaneous Macro-expressions and Micro-expressions,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
55eb7ec9b9740f6c69d6e62062a24bfa091bbb0c,CAS(ME)2: A Database of Spontaneous Macro-expressions and Micro-expressions,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
55b9b1c1c5487f5f62b44340104a9c4cc2ed7c96,The Color of the Cat is Gray: 1 Million Full-Sentences Visual Question Answering (FSVQA),University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+558540d73fec6fd3856fe0695ad8d9c0b5fe1773,Type-hover-swipe in 96 bytes: a motion sensing mechanical keyboard,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+55249d73df3c38aca08f45a60ff54d9ac8b678a0,General Regression and Representation Model for Face Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+97463b5a0fef72a576367f55d46aa3eb7576ae01,Methodical Analysis of Western-Caucasian and East-Asian Basic Facial Expressions of Emotions Based on Specific Facial Regions,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+97d3708dfcae89cbcbd260029601f2c1de4d7017,Semantic Localisation via Globally Unique Instance Segmentation,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+97ffadd639eb27d73b86fd5520d9d6b81772b891,Deep Generative Models for Distribution-Preserving Lossy Compression,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+970b4d2ed1249af97cdf2fffdc7b4beae458db89,HMDB: A large video database for human motion recognition,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+970b4d2ed1249af97cdf2fffdc7b4beae458db89,HMDB: A large video database for human motion recognition,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+97b3185d948c45a00a190ce0a26abd23e77c9edf,Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
9788b491ddc188941dadf441fc143a4075bff764,LOGAN: Membership Inference Attacks Against Generative Models∗,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+977beecdf0b5c3487d03738cff501c79770f0858,"Show, Reward and Tell: Automatic Generation of Narrative Paragraph from Photo Stream by Adversarial Training",Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+977beecdf0b5c3487d03738cff501c79770f0858,"Show, Reward and Tell: Automatic Generation of Narrative Paragraph from Photo Stream by Adversarial Training",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+974b9f0af3af675c092b96e7ac68e391cffdcf49,Person Re-identification Using Data-Driven Metric Adaptation,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+974b9f0af3af675c092b96e7ac68e391cffdcf49,Person Re-identification Using Data-Driven Metric Adaptation,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+97711a255ead64265fe3736ce8a2392ef5c75ff0,Cross-Dataset Person Re-identification Using Similarity Preserved Generative Adversarial Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
970c0d6c0fd2ebe7c5921a45bc70f6345c844ff3,Discriminative Log-Euclidean Feature Learning for Sparse Representation-Based Recognition of Faces from Videos,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+97f665219a42faa8e625625257cc35f5dcbaf0ba,Multi-View Pose and Facial Expression Recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+9716416a15e79a36e3481bcdad79cdc905603e6d,Gaussian Word Embedding with a Wasserstein Distance Loss,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+9716416a15e79a36e3481bcdad79cdc905603e6d,Gaussian Word Embedding with a Wasserstein Distance Loss,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+974cadd15684c96618d04f845794cec5568a86a6,Greedy Inference Algorithms for Structured and Neural Models,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
+97b930a4fa4670a609b6ee8811409090fe55b313,Integrating Gaze Tracking and Head-Motion Prediction for Mobile Device Authentication: A Proof of Concept,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+97b930a4fa4670a609b6ee8811409090fe55b313,Integrating Gaze Tracking and Head-Motion Prediction for Mobile Device Authentication: A Proof of Concept,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
97137d5154a9f22a5d9ecc32e8e2b95d07a5a571,Facial expression recognition based on local region specific features and support vector machines,Korea Electronics Technology Institute,Korea Electronics Technology Institute,"South Korea, Gyeonggi-do, Seongnam-si, Bundang-gu, 새나리로 25 (야탑동) KETI 전자부품연구원",37.40391700,127.15978600,edu,
9730b9cd998c0a549601c554221a596deda8af5b,Spatio-Temporal Person Retrieval via Natural Language Queries,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+97265d64859e06900c11ae5bb5f03f3bd265f858,Multilabel Image Classification With Regional Latent Semantic Dependencies,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+97265d64859e06900c11ae5bb5f03f3bd265f858,Multilabel Image Classification With Regional Latent Semantic Dependencies,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+97265d64859e06900c11ae5bb5f03f3bd265f858,Multilabel Image Classification With Regional Latent Semantic Dependencies,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
978a219e07daa046244821b341631c41f91daccd,Emotional Intelligence: Giving Computers Effective Emotional Skills to Aid Interaction,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
976e0264bb57786952a987d4456850e274714fb8,Improving Semantic Concept Detection through the Dictionary of Visually-Distinct Elements,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
9758f3fd94239a8d974217fe12599f88fb413f3d,UC-HCC Submission to Thumos 2014,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
97e569159d5658760eb00ca9cb662e6882d2ab0e,Correlation Filters for Object Alignment,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
97e569159d5658760eb00ca9cb662e6882d2ab0e,Correlation Filters for Object Alignment,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
97e569159d5658760eb00ca9cb662e6882d2ab0e,Correlation Filters for Object Alignment,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+9772ccb519268f067da7707fc199ad942ac63c42,New approaches of ensemble learning and transfer learning for image classificaion,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+97295e92dfe49f37de65c5130097ccab84cfe2f7,Inner Space Preserving Generative Pose Machine,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+9785429538389146c8061ec856e74e957a246f2d,DARI: Distance Metric and Representation Integration for Person Verification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
975978ee6a32383d6f4f026b944099e7739e5890,Privacy-Preserving Age Estimation for Content Rating,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
975978ee6a32383d6f4f026b944099e7739e5890,Privacy-Preserving Age Estimation for Content Rating,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
975978ee6a32383d6f4f026b944099e7739e5890,Privacy-Preserving Age Estimation for Content Rating,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
975978ee6a32383d6f4f026b944099e7739e5890,Privacy-Preserving Age Estimation for Content Rating,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
975978ee6a32383d6f4f026b944099e7739e5890,Privacy-Preserving Age Estimation for Content Rating,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+97304c55262bbd9354aa78d2f52eb73d0a13c9ff,Deep Disentangled Representations for Volumetric Reconstruction,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+975af82c9ce82a1fad760d58ba0a661217689aa9,Answerer in Questioner's Mind for Goal-Oriented Visual Dialogue,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+635e5b6219a655b73f47ae74751ae43577d22da6,Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+63da9079437f6090b44eec60ec3986c25c13be73,Top down saliency estimation via superpixel-based discriminative dictionaries,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
63d8110ac76f57b3ba8a5947bc6bdbb86f25a342,On Modeling Variations for Face Authentication,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+635e3ce6fb0b28f38fb77f25770911bf08f0ff03,Face-to-face interference in typical and atypical development,Newcastle University,Newcastle University,"Newcastle University, Claremont Walk, Haymarket, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE1 7RU, UK",54.98023235,-1.61452627,edu,
+635e3ce6fb0b28f38fb77f25770911bf08f0ff03,Face-to-face interference in typical and atypical development,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+638e04272c312d64337b14f001529084f2c40bef,Modeling Naive Psychology of Characters in Simple Commonsense Stories,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+638e04272c312d64337b14f001529084f2c40bef,Modeling Naive Psychology of Characters in Simple Commonsense Stories,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
632b24ddd42fda4aebc5a8af3ec44f7fd3ecdc6c,Real-Time Facial Segmentation and Performance Capture from RGB Input,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+63b20102be65bbb3453152e504e79c2af2eb9059,"Automatic Discovery, Association Estimation and Learning of Semantic Attributes for a Thousand Categories",Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+63fd747875052931aed46a37c6da7d7ebb7768ec,Venues in Social Media: Examining Ambiance Perception Through Scene Semantics,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+63fd747875052931aed46a37c6da7d7ebb7768ec,Venues in Social Media: Examining Ambiance Perception Through Scene Semantics,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+63660c50e2669a5115c2379e622549d8ed79be00,Deep Salient Object Detection by Integrating Multi-level Cues,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+63660c50e2669a5115c2379e622549d8ed79be00,Deep Salient Object Detection by Integrating Multi-level Cues,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+634e02d6107529d672cbbdf5b97990966e289829,Cost-Effective Training of Deep CNNs with Active Model Adaptation,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+630af2eb466fac956f9a43bf877be0eae6d80027,CariGANs: Unpaired Photo-to-Caricature Translation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+630af2eb466fac956f9a43bf877be0eae6d80027,CariGANs: Unpaired Photo-to-Caricature Translation,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+630af2eb466fac956f9a43bf877be0eae6d80027,CariGANs: Unpaired Photo-to-Caricature Translation,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+637de43801f26fab8f567787485c57ab92273ce5,Mask-aware Photorealistic Face Attribute Manipulation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+637de43801f26fab8f567787485c57ab92273ce5,Mask-aware Photorealistic Face Attribute Manipulation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
6324fada2fb00bd55e7ff594cf1c41c918813030,Uncertainty Reduction for Active Image Clustering via a Hybrid Global-Local Uncertainty Model,University at Buffalo,State University of New York at Buffalo,"Buffalo, NY 14260, USA",43.00080930,-78.78896970,edu,
6308e9c991125ee6734baa3ec93c697211237df8,Learning the sparse representation for classification,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+6345eef2ffe46da6d77d07446c1329da7ea00f45,Trajectory Ensemble: Multiple Persons Consensus Tracking Across Non-overlapping Multiple Cameras over Randomly Dropped Camera Networks,Nagoya University,Nagoya University,"SuperDARN (Hokkaido West), 太辛第1支線林道, 陸別町, 足寄郡, 十勝総合振興局, 北海道, 北海道地方, 日本",43.53750985,143.60768225,edu,
6342a4c54835c1e14159495373ab18b4233d2d9b,Towards Pose-robust Face Recognition on Video,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+6355f7fd956466e8e9f09b297e6cdd155d66740e,EgoReID: Cross-view Self-Identification and Human Re-identification in Egocentric and Surveillance Videos,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+63c7c8dff73ec6798e38ed7466a4f8ff8a87f879,Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+63f367d50b248680138cb4b3aec3143fad3a7112,Ordinal Random Forests for Object Detection,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
63b29886577a37032c7e32d8899a6f69b11a90de,Image-Set Based Face Recognition Using Boosted Global and Local Principal Angles,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+632029daf2a667cb87cd3078a853d68412ea6896,Clustering-Based Joint Feature Selection for Semantic Attribute Prediction,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
63a6c256ec2cf2e0e0c9a43a085f5bc94af84265,Complexity of multiverse networks and their multilayer generalization,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
63213d080a43660ac59ea12e3c35e6953f6d7ce8,ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
630d1728435a529d0b0bfecb0e7e335f8ea2596d,Facial Action Unit Detection by Cascade of Tasks,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
@@ -2994,17 +8235,37 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 630d1728435a529d0b0bfecb0e7e335f8ea2596d,Facial Action Unit Detection by Cascade of Tasks,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
633101e794d7b80f55f466fd2941ea24595e10e6,Face Attribute Prediction with classification CNN,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
63a2e2155193dc2da9764ae7380cdbd044ff2b94,A Dense SURF and Triangulation Based Spatio-temporal Feature for Action Recognition,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+633f4e4d1e29d336a5472a9cf43163fdceafecfa,PatchFCN for Intracranial Hemorrhage Detection,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+631c4ca00eaa65b801c63d32c0f564e974009ddd,Self-attention Learning for Person Re-identification,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+631c4ca00eaa65b801c63d32c0f564e974009ddd,Self-attention Learning for Person Re-identification,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
63d865c66faaba68018defee0daf201db8ca79ed,Deep Regression for Face Alignment,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
63cff99eff0c38b633c8a3a2fec8269869f81850,Feature Correlation Filter for Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
6341274aca0c2977c3e1575378f4f2126aa9b050,A multi-scale cascade fully convolutional network face detector,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
632441c9324cd29489cee3da773a9064a46ae26b,Video-based Cardiac Physiological Measurements Using Joint Blind Source Separation Approaches,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
632441c9324cd29489cee3da773a9064a46ae26b,Video-based Cardiac Physiological Measurements Using Joint Blind Source Separation Approaches,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+0fd53d7e1ab8f42c710cb77b5ec4cc2b22158a4c,Combined Data Association and Evolving Particle Filter for Tracking of Multiple Articulated Objects,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
+0f3b3688af4e87b27ad38bf70aeffb64288bfe27,Unsupervised Construction of Human Body Models Using Principles of Organic Computing,Ruhr-University Bochum,Ruhr-University Bochum,"RUB, 150, Universitätsstraße, Ruhr-Universität, Querenburg, Bochum-Süd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland",51.44415765,7.26096541,edu,
+0f9fe80fff218573a4805437ba7010fa823ca0e6,DIY Human Action Data Set Generation,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+0f92f0cf1fb1d37f7f723892976ca61419768995,Gabor-based gradient orientation pyramid for kinship verification under uncontrolled environments,Capital Normal University,Capital Normal University,"首都师范大学, 岭南路, 西冉村, 海淀区, 100048, 中国",39.92864575,116.30104052,edu,
+0f92f0cf1fb1d37f7f723892976ca61419768995,Gabor-based gradient orientation pyramid for kinship verification under uncontrolled environments,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+0fa24e602d65af82fc429edb4e0980dc534d4b16,Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+0f0a5d8a7a087204026a6b67000887dbf5b6a20f,Generating objects going well with the surroundings,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+0fe8b5503681128da84a8454a4cc94470adc09ea,Sparsity Potentials for Detecting Objects with the Hough Transform,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+0fe8b5503681128da84a8454a4cc94470adc09ea,Sparsity Potentials for Detecting Objects with the Hough Transform,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+0f7bf963a06682d69387c54632cec9e835423617,Gamesourcing to acquire labeled human pose estimation data,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
+0f4724cc069609a9544ca7d9a429b52cfe89c182,"PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model",Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
+0f6d068ca799e99100fa5ff7503163fd1c9ae581,Common Subspace for Model and Similarity: Phrase Learning for Caption Generation from Images,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
0fc254272db096a9305c760164520ad9914f4c9e,Unsupervised convolutional neural networks for motion estimation,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+0f96eee0407b9ce9ea01629ed01bcf6802f97272,Attribute Learning for Understanding Unstructured Social Activity,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
0fae5d9d2764a8d6ea691b9835d497dd680bbccd,Face Recognition using Canonical Correlation Analysis,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
0fae5d9d2764a8d6ea691b9835d497dd680bbccd,Face Recognition using Canonical Correlation Analysis,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
0f32df6ae76402b98b0823339bd115d33d3ec0a0,Emotion recognition from embedded bodily expressions and speech during dyadic interactions,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
0f32df6ae76402b98b0823339bd115d33d3ec0a0,Emotion recognition from embedded bodily expressions and speech during dyadic interactions,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+0f349677a24dce888851dcf44f5c886d9f4681ec,Running Head: FACIAL EXPRESSION ANIMATION 1 FACSGen 2.0 Animation Software: Generating 3D FACS-Valid Facial Expressions for Emotion Research,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+0f349677a24dce888851dcf44f5c886d9f4681ec,Running Head: FACIAL EXPRESSION ANIMATION 1 FACSGen 2.0 Animation Software: Generating 3D FACS-Valid Facial Expressions for Emotion Research,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
0f829fee12e86f980a581480a9e0cefccb59e2c5,Bird Part Localization Using Exemplar-Based Models with Enforced Pose and Subcategory Consistency,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+0f7fdd7f98ee5fbfa7d293e0f1fa399b7a4ec13a,Two-Granularity Tracking: Mediating Trajectory and Detection Graphs for Tracking under Occlusions,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+0f5700e8aa4cba32828ca12cd4e3732a33148951,Spatio-Temporal Modeling and Prediction of Visual Attention in Graphical User Interfaces,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
0faee699eccb2da6cf4307ded67ba8434368257b,TAIGMAN: MULTIPLE ONE-SHOTS FOR UTILIZING CLASS LABEL INFORMATION 1 Multiple One-Shots for Utilizing Class Label Information,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
0faee699eccb2da6cf4307ded67ba8434368257b,TAIGMAN: MULTIPLE ONE-SHOTS FOR UTILIZING CLASS LABEL INFORMATION 1 Multiple One-Shots for Utilizing Class Label Information,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
0fabb4a40f2e3a2502cd935e54e090a304006c1c,Regularized Robust Coding for Face Recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
@@ -3013,14 +8274,29 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 0fd3a7ee228bbc3dd4a111dae04952a1ee58a8cd,Hair style retrieval by semantic mapping on informative patches,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
0f533bc9fdfb75a3680d71c84f906bbd59ee48f1,Illumination invariant feature extraction based on natural images statistics — Taking face images as an example,"Academia Sinica, Taiwan","Research Center for Institute of Information Science, Academia Sinica, Taiwan","115, Taiwan, Taipei City, Nangang District, 研究院路二段128號",25.04117270,121.61465180,edu,
0f533bc9fdfb75a3680d71c84f906bbd59ee48f1,Illumination invariant feature extraction based on natural images statistics — Taking face images as an example,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+0f22005f8f2bc134f02c4a76cde30349e3389b8d,ShuffleSeg: Real-time Semantic Segmentation Network,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
0f4eb63402a4f3bae8f396e12133684fb760def1,"LONG, LIU, SHAO: ATTRIBUTE EMBEDDING WITH VSAR FOR ZERO-SHOT LEARNING 1 Attribute Embedding with Visual-Semantic Ambiguity Removal for Zero-shot Learning",Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+0fbc9584cc276ba54d133730624199a631a2c6db,Extreme Clicking for Efficient Object Annotation,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+0f2f1e6e23e4bb9f16ba969d50582e0064ac471c,Basis mapping based boosting for object detection,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
0fba39bf12486c7684fd3d51322e3f0577d3e4e8,Task Specific Local Region Matching,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
0fb8317a8bf5feaf297af8e9b94c50c5ed0e8277,Detecting Hands in Egocentric Videos: Towards Action Recognition,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+0f2f4edb7599de34c97f680cf356943e57088345,Stacked Hourglass Networks for Human Pose Estimation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+0fca9a022f4910dda7f8bdc92bbbe8a9c6e35303,Accelerating t-SNE using tree-based algorithms,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
0fe96806c009e8d095205e8f954d41b2b9fd5dcf,On-the-Job Learning with Bayesian Decision Theory,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
0fe96806c009e8d095205e8f954d41b2b9fd5dcf,On-the-Job Learning with Bayesian Decision Theory,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
0fe96806c009e8d095205e8f954d41b2b9fd5dcf,On-the-Job Learning with Bayesian Decision Theory,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
0fe96806c009e8d095205e8f954d41b2b9fd5dcf,On-the-Job Learning with Bayesian Decision Theory,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+0f6d6a67d4439c021dcbaaeab61b6b29e88d45d9,A Semi-Supervised Data Augmentation Approach using 3D Graphical Engines,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+0fb17e7f2bb70ca6ad66bb13599fc6a33be9916b,Deep Canonical Time Warping,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+0fb17e7f2bb70ca6ad66bb13599fc6a33be9916b,Deep Canonical Time Warping,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+0f22251fa9c4bb120f00767053430fbab141fac3,Support Vector Guided Dictionary Learning,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+0f22251fa9c4bb120f00767053430fbab141fac3,Support Vector Guided Dictionary Learning,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+0f22251fa9c4bb120f00767053430fbab141fac3,Support Vector Guided Dictionary Learning,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+0f22251fa9c4bb120f00767053430fbab141fac3,Support Vector Guided Dictionary Learning,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+0f42c64a74bc6e3e83821aa8ab5dd8e3a4b797cd,Controlled scanpath variation alters fusiform face activation.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+0f1539368f90918fc3c4d5431e384986ad768506,Person Re-Identification by Deep Joint Learning of Multi-Loss Classification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
0f940d2cdfefc78c92ec6e533a6098985f47a377,A hierarchical framework for simultaneous facial activity tracking,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+0fa88943665de1176b0fc6de4ed7469b40cdb08c,Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
0f21a39fa4c0a19c4a5b4733579e393cb1d04f71,Evaluation of optimization components of a 3D to 2D landmark fitting algorithm for head pose estimation,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
0f21a39fa4c0a19c4a5b4733579e393cb1d04f71,Evaluation of optimization components of a 3D to 2D landmark fitting algorithm for head pose estimation,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
0faeec0d1c51623a511adb779dabb1e721a6309b,Seeing is Worse than Believing: Reading People's Minds Better than Computer-Vision Methods Recognize Actions,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
@@ -3031,17 +8307,36 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 0faeec0d1c51623a511adb779dabb1e721a6309b,Seeing is Worse than Believing: Reading People's Minds Better than Computer-Vision Methods Recognize Actions,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
0faeec0d1c51623a511adb779dabb1e721a6309b,Seeing is Worse than Believing: Reading People's Minds Better than Computer-Vision Methods Recognize Actions,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
0faeec0d1c51623a511adb779dabb1e721a6309b,Seeing is Worse than Believing: Reading People's Minds Better than Computer-Vision Methods Recognize Actions,National University of Ireland Maynooth,National University of Ireland Maynooth,"National University of Ireland Maynooth, River Apartments, Maynooth, Maynooth ED, Maynooth Municipal District, County Kildare, Leinster, KILDARE, Ireland",53.38469750,-6.60039458,edu,
+0f6911bc1e6abee8bbf9dd3f8d54d40466429da7,Zero-shot Learning with Semantic Output Codes,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+0f6911bc1e6abee8bbf9dd3f8d54d40466429da7,Zero-shot Learning with Semantic Output Codes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0f6911bc1e6abee8bbf9dd3f8d54d40466429da7,Zero-shot Learning with Semantic Output Codes,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+0f6911bc1e6abee8bbf9dd3f8d54d40466429da7,Zero-shot Learning with Semantic Output Codes,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0fa956029110bd82b34208cd18a77ca34d2c5eed,"Query-Focused Video Summarization: Dataset, Evaluation, and a Memory Network Based Approach",University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
0f81b0fa8df5bf3fcfa10f20120540342a0c92e5,"Mirror, mirror on the wall, tell me, is the error small?",Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
0f81b0fa8df5bf3fcfa10f20120540342a0c92e5,"Mirror, mirror on the wall, tell me, is the error small?",Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+0fbdd4b8eb9e4c4cfbe5b76ab29ab8b0219fbdc0,Constrained Convolutional Neural Networks for Weakly Supervised Segmentation,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
0f0241124d6092a0bb56259ac091467c2c6938ca,Associating Faces and Names in Japanese Photo News Articles on the Web,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+0fb3b63090f95af97723efe565893eb25ea9188c,Anticipating the future by watching unlabeled video,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+0f945f796a9343b51a3dc69941c0fa1a98c0f448,Local Hypersphere Coding Based on Edges between Visual Words,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+0f8b4a64eea40c1f0aa655d4e77e46543ff558b7,Curvilinear Structure Tracking by Low Rank Tensor Approximation with Model Propagation,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+0f8b4a64eea40c1f0aa655d4e77e46543ff558b7,Curvilinear Structure Tracking by Low Rank Tensor Approximation with Model Propagation,University of Delaware,University of Delaware,"University of Delaware, South College Avenue, Newark, New Castle County, Delaware, 19713, USA",39.68103280,-75.75401840,edu,
+0fdb6823669959cb709fdb3070e7e5efeebb046a,Robust Recognition against Illumination Variations Based on SIFT,University of Tabriz,University of Tabriz,"دانشگاه تبریز, شهید ایرج خلوتی, کوی انقلاب, تبریز, بخش مرکزی, شهرستان تبریز, استان آذربایجان شرقی, 5166616471, ایران",38.06125530,46.32984840,edu,
+0a52919e4473eb7bc20982094e8497570d797b13,Building Class Sensitive Models for Tracking Applications,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
+0a808a17f5c86413bd552a324ee6ba180a12f46d,Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+0ae910ef0cb2f193a43d3a592b7b62ef8bd13058,Weakly Supervised Saliency Detection with A Category-Driven Map Generator,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
0a64f4fec592662316764283575d05913eb2135b,Joint Pixel and Feature-level Domain Adaptation in the Wild,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
0a0321785c8beac1cbaaec4d8ad0cfd4a0d6d457,Learning Invariant Deep Representation for NIR-VIS Face Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
0a2ddf88bd1a6c093aad87a8c7f4150bfcf27112,Patch-based models for visual object classes,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
0a2ddf88bd1a6c093aad87a8c7f4150bfcf27112,Patch-based models for visual object classes,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+0a789733ccb300d0dd9df6174faaa7e8c64e0409,High-Resolution Multispectral Dataset for Semantic Segmentation,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+0a5718f6a60ca18e6b6de5660c49040ac0045d7a,Automatic classification of the Parkinson’s patient stiffness from a single videosequence,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+0a5718f6a60ca18e6b6de5660c49040ac0045d7a,Automatic classification of the Parkinson’s patient stiffness from a single videosequence,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
0a5ffc55b584da7918c2650f9d8602675d256023,Efficient Face Alignment via Locality-constrained Representation for Robust Recognition,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
0a5ffc55b584da7918c2650f9d8602675d256023,Efficient Face Alignment via Locality-constrained Representation for Robust Recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
0a5ffc55b584da7918c2650f9d8602675d256023,Efficient Face Alignment via Locality-constrained Representation for Robust Recognition,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
0a5ffc55b584da7918c2650f9d8602675d256023,Efficient Face Alignment via Locality-constrained Representation for Robust Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0a04d8b0099708fbceb63b58faa61ae0c772c8c4,Log-Gabor Weber Descriptor for Face Recognition,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+0aa0e5f96d512fcd2357129ad4363d6ae961327e,Unsupervised Hard Example Mining from Videos for Improved Object Detection,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
0aeb5020003e0c89219031b51bd30ff1bceea363,Sparsifying Neural Network Connections for Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
0aeb5020003e0c89219031b51bd30ff1bceea363,Sparsifying Neural Network Connections for Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
0aeb5020003e0c89219031b51bd30ff1bceea363,Sparsifying Neural Network Connections for Face Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
@@ -3051,12 +8346,42 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 0aa74ad36064906e165ac4b79dec298911a7a4db,Variational Inference for the Indian Buffet Process,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
0abf67e7bd470d9eb656ea2508beae13ca173198,Going Deeper into First-Person Activity Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
0af33f6b5fcbc5e718f24591b030250c6eec027a,Text Analysis for Automatic Image Annotation,Katholieke Universiteit Leuven,Katholieke Universiteit Leuven,"Laboratorium voor Bos, natuur en landschap, 102, Vital Decosterstraat, Sint-Maartensdal, Leuven, Vlaams-Brabant, Vlaanderen, 3000, België / Belgique / Belgien",50.88306860,4.70195030,edu,
+0ad6dc4554fd5c0212993677c160af31fd27e243,Measuring Crowd Collectiveness,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+0ad6dc4554fd5c0212993677c160af31fd27e243,Measuring Crowd Collectiveness,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+0ad6dc4554fd5c0212993677c160af31fd27e243,Measuring Crowd Collectiveness,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+0a850a9fc853c358aea1167e1f965cda8980b7fd,INDREX: in-database distributional relation extraction,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+0ae8377a984125802a69a93df7c9fe640b55aeac,Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
+0ae8377a984125802a69a93df7c9fe640b55aeac,Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
+0ae8377a984125802a69a93df7c9fe640b55aeac,Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
+0a814669f4a0198e46a3a0d91a1bbb81bb089216,"Deficits in facial, body movement and vocal emotional processing in autism spectrum disorders.",University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+0a814669f4a0198e46a3a0d91a1bbb81bb089216,"Deficits in facial, body movement and vocal emotional processing in autism spectrum disorders.",University of St Andrews,University of St Andrews,"University of St Andrews, North Street, Albany Park Student accommodation, Carngour, St Andrews, Fife, Scotland, KY16 9AJ, UK",56.34119840,-2.79309380,edu,
+0a814669f4a0198e46a3a0d91a1bbb81bb089216,"Deficits in facial, body movement and vocal emotional processing in autism spectrum disorders.",University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+0a814669f4a0198e46a3a0d91a1bbb81bb089216,"Deficits in facial, body movement and vocal emotional processing in autism spectrum disorders.",University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+0a814669f4a0198e46a3a0d91a1bbb81bb089216,"Deficits in facial, body movement and vocal emotional processing in autism spectrum disorders.",University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+0af7632427f70f2327cdf5188b814fa55d7551df,Hidden Markov models for face recognition,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+0a84a63acef89a0f632ef08cb0b00af77ed8e7f5,Amphisbaena: Modeling two orthogonal ways to hunt on heterogeneous many-cores,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0a84a63acef89a0f632ef08cb0b00af77ed8e7f5,Amphisbaena: Modeling two orthogonal ways to hunt on heterogeneous many-cores,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0a84a63acef89a0f632ef08cb0b00af77ed8e7f5,Amphisbaena: Modeling two orthogonal ways to hunt on heterogeneous many-cores,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+0ad1fefa54f69d9efa0112f2e60c19841d5e9346,ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+0ad1fefa54f69d9efa0112f2e60c19841d5e9346,ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
0a34fe39e9938ae8c813a81ae6d2d3a325600e5c,FacePoseNet: Making a Case for Landmark-Free Face Alignment,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
+0a24a16cb9f6d95453d4cd6d0bd5bdad4199e3cc,Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+0a24a16cb9f6d95453d4cd6d0bd5bdad4199e3cc,Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+0a24a16cb9f6d95453d4cd6d0bd5bdad4199e3cc,Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+0ae80aa149764e91544bbe45b80bb50434e7bda9,Ambient Sound Provides Supervision for Visual Learning,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
0ad8149318912b5449085187eb3521786a37bc78,CP-mtML: Coupled Projection Multi-Task Metric Learning for Large Scale Face Retrieval,University of Caen,University of Caen,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
0a9d204db13d395f024067cf70ac19c2eeb5f942,Viewpoint-aware Video Summarization,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
0aae88cf63090ea5b2c80cd014ef4837bcbaadd8,3D Face Structure Extraction from Images at Arbitrary Poses and under Arbitrary Illumination Conditions,Drexel University,Drexel University,"Drexel University, Arch Street, Powelton Village, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.95740000,-75.19026706,edu,
+0aa303109a3402aa5a203877847d549c4a24d933,Who Do I Look Like? Determining Parent-Offspring Resemblance via Gated Autoencoders,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+0ad119275960fd1b68004feeb84d41b91bc273c8,Object Detection Using Generalization and Efficiency Balanced Co-Occurrence Features,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+0a3a33b872c84dac88bcd6f5bd460ef03584e0f7,Abnormal Neural Activation to Faces in the Parents of Children with Autism.,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+0a3a33b872c84dac88bcd6f5bd460ef03584e0f7,Abnormal Neural Activation to Faces in the Parents of Children with Autism.,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+0a3a33b872c84dac88bcd6f5bd460ef03584e0f7,Abnormal Neural Activation to Faces in the Parents of Children with Autism.,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+0a3a33b872c84dac88bcd6f5bd460ef03584e0f7,Abnormal Neural Activation to Faces in the Parents of Children with Autism.,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
0a82860d11fcbf12628724333f1e7ada8f3cd255,Action Temporal Localization in Untrimmed Videos via Multi-stage CNNs,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+0a267d927cfae039cf0a9c995a59ded563344eb6,Model Selection Management Systems: The Next Frontier of Advanced Analytics,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
0a4fc9016aacae9cdf40663a75045b71e64a70c9,Illumination Normalization Based on Homomorphic Wavelet Filtering for Face Recognition,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+0a0d5283439f088c158fcec732e2593bb3cd57ad,Who Blocks Who: Simultaneous clothing segmentation for grouping images,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
0a85afebaa19c80fddb660110a4352fd22eb2801,Neural Animation and Reenactment of Human Actor Videos,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
0a85afebaa19c80fddb660110a4352fd22eb2801,Neural Animation and Reenactment of Human Actor Videos,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
0a85afebaa19c80fddb660110a4352fd22eb2801,Neural Animation and Reenactment of Human Actor Videos,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
@@ -3064,151 +8389,413 @@ ec05078be14a11157ac0e1c6b430ac886124589b,Longitudinal Face Aging in the Wild - R 0a85afebaa19c80fddb660110a4352fd22eb2801,Neural Animation and Reenactment of Human Actor Videos,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
0a85afebaa19c80fddb660110a4352fd22eb2801,Neural Animation and Reenactment of Human Actor Videos,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
0a85afebaa19c80fddb660110a4352fd22eb2801,Neural Animation and Reenactment of Human Actor Videos,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+0a13581afdae66bcf52755bfb53410e6e54c1840,Restricting Greed in Training of Generative Adversarial Network,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
0ac442bb570b086d04c4d51a8410fcbfd0b1779d,WarpNet: Weakly Supervised Matching for Single-View Reconstruction,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+0acc526e1fbef5bed4c63623e370a4710206e997,Shape guided contour grouping with particle filters,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+0acc526e1fbef5bed4c63623e370a4710206e997,Shape guided contour grouping with particle filters,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+0acc526e1fbef5bed4c63623e370a4710206e997,Shape guided contour grouping with particle filters,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+0acc526e1fbef5bed4c63623e370a4710206e997,Shape guided contour grouping with particle filters,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+0af3c97068638ec2b79b93ff8b3fde9bd999f153,Deep Approximately Orthogonal Nonnegative Matrix Factorization for Clustering,Guangdong University of Technology,Guangdong University of Technology,"广东工业大学, 东风东路, 黄花岗街道, 越秀区 (Yuexiu), 广州市, 广东省, 510080, 中国",23.13538360,113.29470496,edu,
+0af3c97068638ec2b79b93ff8b3fde9bd999f153,Deep Approximately Orthogonal Nonnegative Matrix Factorization for Clustering,Guangdong University of Technology,Guangdong University of Technology,"广东工业大学, 东风东路, 黄花岗街道, 越秀区 (Yuexiu), 广州市, 广东省, 510080, 中国",23.13538360,113.29470496,edu,
+0af3c97068638ec2b79b93ff8b3fde9bd999f153,Deep Approximately Orthogonal Nonnegative Matrix Factorization for Clustering,Guangdong University of Technology,Guangdong University of Technology,"广东工业大学, 东风东路, 黄花岗街道, 越秀区 (Yuexiu), 广州市, 广东省, 510080, 中国",23.13538360,113.29470496,edu,
+0a01d9b6b468f3e25867a028244ce4376b5e8d82,Cross-modality pose-invariant facial expression,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
0ac664519b2b8abfb8966dafe60d093037275573,Facial action unit detection using kernel partial least squares,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
0a9345ea6e488fb936e26a9ba70b0640d3730ba7,Deep Bi-directional Cross-triplet Embedding for Cross-Domain Clothing Retrieval,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
0a9345ea6e488fb936e26a9ba70b0640d3730ba7,Deep Bi-directional Cross-triplet Embedding for Cross-Domain Clothing Retrieval,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+0a561e6f0aecd182ddaf526220acc75f6583816e,CollageParsing: Nonparametric Scene Parsing by Adaptive Overlapping Windows,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+0a70401d161c6c180d84e8139ee8bfbaadb2baad,Image retagging,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
0a79d0ba1a4876086e64fc0041ece5f0de90fbea,Face Illumination Normalization with Shadow Consideration,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+0aa74a922604e200fb92194301d4a4786cc1a74c,Human Factors in Forensic Face Identification,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+0aa74a922604e200fb92194301d4a4786cc1a74c,Human Factors in Forensic Face Identification,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+0aa74a922604e200fb92194301d4a4786cc1a74c,Human Factors in Forensic Face Identification,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+0a602b85c80cef7d38209226188aaab94d5349e8,THE FLORIDA STATE UNIVERSITY COLLEGE OF ARTS AND SCIENCES AUTOMATED FACE TRACKING AND RECOGNITION By MATTHEW,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
0a11b82aa207d43d1b4c0452007e9388a786be12,Feature Level Multiple Model Fusion Using Multilinear Subspace Analysis with Incomplete Training Set and Its Application to Face Image Analysis,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
0a11b82aa207d43d1b4c0452007e9388a786be12,Feature Level Multiple Model Fusion Using Multilinear Subspace Analysis with Incomplete Training Set and Its Application to Face Image Analysis,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+0ae247153afd87f98829359a8b5df0f68d788d75,A Corpus for Reasoning About Natural Language Grounded in Photographs,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+0ae247153afd87f98829359a8b5df0f68d788d75,A Corpus for Reasoning About Natural Language Grounded in Photographs,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+0ae74fabc585cfd1cf60ea3f9e218c59a4539091,Learning Models for Actions and Person-Object Interactions with Transfer to Question Answering,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+0a71b71421d8a33c41625963d19d5df85685dffc,Analyzing Behavior Specialized Acceleration,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+0ab1734693b15bd1aeae06c5736fc7ad12f90aa0,GLAD: Global-Local-Alignment Descriptor for Pedestrian Retrieval,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+0ab1734693b15bd1aeae06c5736fc7ad12f90aa0,GLAD: Global-Local-Alignment Descriptor for Pedestrian Retrieval,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+0ab1734693b15bd1aeae06c5736fc7ad12f90aa0,GLAD: Global-Local-Alignment Descriptor for Pedestrian Retrieval,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+0ab1734693b15bd1aeae06c5736fc7ad12f90aa0,GLAD: Global-Local-Alignment Descriptor for Pedestrian Retrieval,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+6424add0f4f99cb582ecc50c4a33ae18d9236021,Unconstrained Monocular 3D Human Pose Estimation by Action Detection and Cross-Modality Regression Forest,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+6424add0f4f99cb582ecc50c4a33ae18d9236021,Unconstrained Monocular 3D Human Pose Estimation by Action Detection and Cross-Modality Regression Forest,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+6424add0f4f99cb582ecc50c4a33ae18d9236021,Unconstrained Monocular 3D Human Pose Estimation by Action Detection and Cross-Modality Regression Forest,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+64b1de5ebd431354816ea2ebe04dd21b1953bd4f,The Phenomenology of Eye Movement Intentions and their Disruption in Goal-Directed Actions,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+64b1de5ebd431354816ea2ebe04dd21b1953bd4f,The Phenomenology of Eye Movement Intentions and their Disruption in Goal-Directed Actions,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+64d83ccbcb1d87bfafee57f0c2d49043ee3f565b,Super-Bit Locality-Sensitive Hashing,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+64d83ccbcb1d87bfafee57f0c2d49043ee3f565b,Super-Bit Locality-Sensitive Hashing,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+64d83ccbcb1d87bfafee57f0c2d49043ee3f565b,Super-Bit Locality-Sensitive Hashing,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+64d83ccbcb1d87bfafee57f0c2d49043ee3f565b,Super-Bit Locality-Sensitive Hashing,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
6409b8879c7e61acf3ca17bcc62f49edca627d4c,Learning Finite Beta-Liouville Mixture Models via Variational Bayes for Proportional Data Clustering,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
6409b8879c7e61acf3ca17bcc62f49edca627d4c,Learning Finite Beta-Liouville Mixture Models via Variational Bayes for Proportional Data Clustering,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
6409b8879c7e61acf3ca17bcc62f49edca627d4c,Learning Finite Beta-Liouville Mixture Models via Variational Bayes for Proportional Data Clustering,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
+64b90c3220c43f58cb38da9af1a1b77da3dde63e,Recurrent Attention Models for Depth-Based Person Identification,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+645736f2027c5cc64e8ca98ef46f28ae9b1b0110,Distant Human Interaction Recognition with Kinect,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+6424574cb92b316928c37232869bfadcb5b4c20f,C-WSL: Count-Guided Weakly Supervised Localization,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+64c1d9a031ec0e6785dc92edc0d00cc0802e32b0,Key Person Aided Re-identification in Partially Ordered Pedestrian Set,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+64c1d9a031ec0e6785dc92edc0d00cc0802e32b0,Key Person Aided Re-identification in Partially Ordered Pedestrian Set,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+6425b6fb2465fbac50d084b66d93d5cc4fc81ae2,Priming Neural Networks,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+64e053ab54c44968a1e6fa146a72f59f101bc951,Personalized 3D-Aided 2D Facial Landmark Localization,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+64afa85b79c7ad60d8f3f9265259c654c03a01e8,Multi-task Learning Using Multi-modal Encoder-Decoder Networks with Shared Skip Connections,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+64afa85b79c7ad60d8f3f9265259c654c03a01e8,Multi-task Learning Using Multi-modal Encoder-Decoder Networks with Shared Skip Connections,National Institute of Advanced Industrial Science and Technology,National Institute of Advanced Industrial Science and Technology,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+64753fe167a46208e28237fa98db8daedbef83e4,Normal social cognition in developmental prosopagnosia.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
64ec0c53dd1aa51eb15e8c2a577701e165b8517b,Online Regression with Feature Selection in Stochastic Data Streams,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
64ec0c53dd1aa51eb15e8c2a577701e165b8517b,Online Regression with Feature Selection in Stochastic Data Streams,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+640aa9d6b87d893d1a75e3c49067b9ca1a2babe6,Integration of colour and uniform interlaced derivative patterns for object tracking,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
+64e0690dd176a93de9d4328f6e31fc4afe1e7536,Tracking Multiple People Online and in Real Time,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
6459f1e67e1ea701b8f96177214583b0349ed964,Generalized subspace based high dimensional density estimation,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
6459f1e67e1ea701b8f96177214583b0349ed964,Generalized subspace based high dimensional density estimation,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
+64a5709d41f4c2ef0383cee9932e89bb58085588,Surgeon Technical Skill Assessment using Computer Vision based Analysis,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+64a5709d41f4c2ef0383cee9932e89bb58085588,Surgeon Technical Skill Assessment using Computer Vision based Analysis,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+64a5709d41f4c2ef0383cee9932e89bb58085588,Surgeon Technical Skill Assessment using Computer Vision based Analysis,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+6495d989fe33b19d2b7755f9077d8b5bf3190151,Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
64cf86ba3b23d3074961b485c16ecb99584401de,Single Image 3D Interpreter Network,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
64cf86ba3b23d3074961b485c16ecb99584401de,Single Image 3D Interpreter Network,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4,Deep Learning Face Attributes in the Wild,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4,Deep Learning Face Attributes in the Wild,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+645766177de2ef61619572bc09ce239c232d7d5c,Is the left hemisphere androcentric? Evidence of the learned categorical perception of gender,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+645766177de2ef61619572bc09ce239c232d7d5c,Is the left hemisphere androcentric? Evidence of the learned categorical perception of gender,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+64281b49a34786912085396bafd67429725f1bcf,Metaface learning for sparse representation based face recognition,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+64281b49a34786912085396bafd67429725f1bcf,Metaface learning for sparse representation based face recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
6479b61ea89e9d474ffdefa71f068fbcde22cc44,Some topics on similarity metric learning,University of Exeter,University of Exeter,"University of Exeter, Stocker Road, Exwick, Exeter, Devon, South West England, England, EX4 4QN, UK",50.73693020,-3.53647672,edu,
+64b22e5af5dc07309c85a742728ff6f476bd71d1,Modeling Collective Crowd Behaviors in Video,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
64e75f53ff3991099c3fb72ceca55b76544374e5,Simultaneous Feature Selection and Classifier Training via Linear Programming: A Case Study for Face Expression Recognition,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+642486fd468e818fddb8a2ec156535a9d74fa4dc,From Superpixel to Human Shape Modelling for Carried Object Detection,Polytechnique Montreal,Polytechnique Montr´eal,"2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4, Canada",45.50438400,-73.61288290,edu,"Polytechnique Montreal, Montreal, Quebec, Canada"
+64aeab4a2678efa0a60a4d57bf81e3ab640cd476,GenFace: Improving Cyber Security Using Realistic Synthetic Face Generation,University of Haifa,University of Haifa,"אוניברסיטת חיפה, חיפה, מחוז חיפה, ישראל",32.76162915,35.01986304,edu,
+64aeab4a2678efa0a60a4d57bf81e3ab640cd476,GenFace: Improving Cyber Security Using Realistic Synthetic Face Generation,University of Kent,University of Kent,"University of Kent, St. Stephen's Hill, Hackington, Canterbury, Kent, South East, England, CT2 7AS, UK",51.29753440,1.07296165,edu,
+64aeab4a2678efa0a60a4d57bf81e3ab640cd476,GenFace: Improving Cyber Security Using Realistic Synthetic Face Generation,University of Kent,University of Kent,"University of Kent, St. Stephen's Hill, Hackington, Canterbury, Kent, South East, England, CT2 7AS, UK",51.29753440,1.07296165,edu,
+64b14354afc0e33b1786c0c5ab1af46e76b4631c,Enhanced Fine-Form Perception Does Not Contribute to Gestalt Face Perception in Autism Spectrum Disorder,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+64a44e1d5cbefbb403811360a88f4d93e569ffbd,"Perspective distortion modeling, learning and compensation","University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+64b06918add69292c088455b62c4b0f06c727b1b,Virtual-to-Real: Learning to Control in Visual Semantic Segmentation,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
64f9519f20acdf703984f02e05fd23f5e2451977,Learning Temporal Alignment Uncertainty for Efficient Event Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+64da1bfef7db423f31ff92713fbbe1994ad4124d,Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
64782a2bc5da11b1b18ca20cecf7bdc26a538d68,Facial Expression Recognition using Spectral Supervised Canonical Correlation Analysis,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
64782a2bc5da11b1b18ca20cecf7bdc26a538d68,Facial Expression Recognition using Spectral Supervised Canonical Correlation Analysis,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
64d5772f44efe32eb24c9968a3085bc0786bfca7,Morphable Displacement Field Based Image Matching for Face Recognition across Pose,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
64d7e62f46813b5ad08289aed5dc4825d7ec5cff,Mix and Match: Joint Model for Clothing and Attribute Recognition,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
90298f9f80ebe03cb8b158fd724551ad711d4e71,A Pursuit of Temporal Accuracy in General Activity Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+90e55d06f0c0234712bb133df05a24ccfe7fc87c,Recognizing human actions from still images with latent poses,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+90465149a7cb3f581697922f3c1b87de5be246cf,Interpolation-based Object Detection Using Motion Vectors for Embedded Real-time Tracking Systems,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
900207b3bc3a4e5244cae9838643a9685a84fee0,Reconstructing Geometry from Its Latent Structures,Drexel University,Drexel University,"Drexel University, Arch Street, Powelton Village, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.95740000,-75.19026706,edu,
+9004a833c65b89c88d2f50835dc47f2319a2c3d5,Augmented Attribute Representations,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+9016d7e5461aa3328efcfb74a7624487c4db2ffa,Brain structure anomalies in autism spectrum disorder--a meta-analysis of VBM studies using anatomic likelihood estimation.,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+90a2c7db91c3a2ad1249a4c9e6d7d872529cae6a,Unsupervised construction of human body models,Ruhr-University Bochum,Ruhr-University Bochum,"RUB, 150, Universitätsstraße, Ruhr-Universität, Querenburg, Bochum-Süd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland",51.44415765,7.26096541,edu,
90498b95fe8b299ce65d5cafaef942aa58bd68b7,Face Recognition: Primates in the Wild,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+90fbeb4c871d3916c2b428645a1e1482f05826e1,"Encode, Review, and Decode: Reviewer Module for Caption Generation",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
90cc2f08a6c2f0c41a9dd1786bae097f9292105e,Top-down Attention Recurrent VLAD Encoding for Action Recognition in Videos,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+90621c2f4390d5fe75d16ec0ca1fa4eb190904b3,Exploiting Texture Cues for Clothing Parsing in Fashion Images,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+90a4125974564a5ab6c2ce2ff685fc36e9cf0680,Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+90a4125974564a5ab6c2ce2ff685fc36e9cf0680,Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+90918dfd9d754e1cd07ed6acafec9001a4685ce5,Human detection using partial least squares analysis,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+90d07df2d165b034e38ec04b3f6343d483f6cb38,Using Generative Adversarial Networks to Design Shoes: The Preliminary Steps,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+90d07df2d165b034e38ec04b3f6343d483f6cb38,Using Generative Adversarial Networks to Design Shoes: The Preliminary Steps,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+90d07df2d165b034e38ec04b3f6343d483f6cb38,Using Generative Adversarial Networks to Design Shoes: The Preliminary Steps,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
90c4f15f1203a3a8a5bf307f8641ba54172ead30,A 2D Morphable Model of Craniofacial Profile and Its Application to Craniosynostosis,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+90282cd8e122e102124b765ecbb22025a238f249,Co-domain Embedding using Deep Quadruplet Networks for Unseen Traffic Sign Recognition,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+903727c8d2973c98aa215a1143f851847a3d5e66,Sparse Exact PGA on Riemannian Manifolds,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+90ea3a35e946af97372c3f32a170b179fe8352aa,Discriminant Learning for Face Recognition,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+9078307c58d74ed6aab70363a5addc054db7fd1d,A Maternal Influence on Reading the Mind in the Eyes Mediated by Executive Function: Differential Parental Influences on Full and Half-Siblings,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
90ad0daa279c3e30b360f9fe9371293d68f4cebf,Spatio-temporal Framework and Algorithms for Video-based Face Recognition,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+904949e9bf204c275ce366237ec1d3ebcf864a1a,Generating captions without looking beyond objects,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+907189aacae7bff389d6c6592d6e2586dab5168d,A Framework for Applying Point Clouds Grabbed by Multi-Beam LIDAR in Perceiving the Driving Environment,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+907189aacae7bff389d6c6592d6e2586dab5168d,A Framework for Applying Point Clouds Grabbed by Multi-Beam LIDAR in Perceiving the Driving Environment,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+90fbcea84f621ee5d73482c5cb02479778aecccd,Pose-Invariant Face Recognition via RGB-D Images,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+90fbcea84f621ee5d73482c5cb02479778aecccd,Pose-Invariant Face Recognition via RGB-D Images,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
90a754f597958a2717862fbaa313f67b25083bf9,A Review of Human Activity Recognition Methods,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
90a754f597958a2717862fbaa313f67b25083bf9,A Review of Human Activity Recognition Methods,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
90a754f597958a2717862fbaa313f67b25083bf9,A Review of Human Activity Recognition Methods,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
90a754f597958a2717862fbaa313f67b25083bf9,A Review of Human Activity Recognition Methods,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
90a754f597958a2717862fbaa313f67b25083bf9,A Review of Human Activity Recognition Methods,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+90a46cf5ca0f13154864aeefe3e8e30e9fde754c,Learning Hierarchical Feature Representation in Depth Image,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+90a46cf5ca0f13154864aeefe3e8e30e9fde754c,Learning Hierarchical Feature Representation in Depth Image,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
90d9209d5dd679b159051a8315423a7f796d704d,Temporal Sequence Distillation: Towards Few-Frame Action Recognition in Videos,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
90d9209d5dd679b159051a8315423a7f796d704d,Temporal Sequence Distillation: Towards Few-Frame Action Recognition in Videos,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+90b4470032f2796a347a0080bcd833c2db0e8bf0,Improving Image Clustering With Multiple Pretrained CNN Feature Extractors,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
90dd2a53236b058c79763459b9d8a7ba5e58c4f1,Capturing Correlations Among Facial Parts for Facial Expression Analysis,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
90c2d4d9569866a0b930e91713ad1da01c2a6846,Dimensionality Reduction Based on Low Rank Representation,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+9019286143f89561509506c3164f36f0e7e3a364,DeepNav: Learning to Navigate Large Cities,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+9019286143f89561509506c3164f36f0e7e3a364,DeepNav: Learning to Navigate Large Cities,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+9039b8097a78f460db9718bc961fdc7d89784092,3D Face Recognition Based on Local Shape Patterns and Sparse Representation Classifier,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+905ba09d4db4f5e150457599553610fc2cb7e105,Efficient Pose and Cell Segmentation using Column Generation,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
+9067f14f5708b3ca1c6a8194b2d550fdffb3c1bd,A Pedestrian Detection Method Based on the HOG-LBP Feature and Gentle AdaBoost,Hunan University,Hunan University,"Yejin University for Employees, 冶金西路, 和平乡, 珠晖区, 衡阳市 / Hengyang, 湖南省, 中国",26.88111275,112.62850666,edu,
+90943f17cb224c287d1bf117441781d43d2f9b49,Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+900bdd3fc700ebf9417c58df15a05eed8c52a90d,Comparative Deep Learning of Hybrid Representations for Image Recommendations,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+bfd3d184c3a9f5ee59cb2d1ab92cc1a7124319fb,Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+bfd3d184c3a9f5ee59cb2d1ab92cc1a7124319fb,Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+bfd3d184c3a9f5ee59cb2d1ab92cc1a7124319fb,Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+bfd3d184c3a9f5ee59cb2d1ab92cc1a7124319fb,Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+bfd3d184c3a9f5ee59cb2d1ab92cc1a7124319fb,Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+bfd3d184c3a9f5ee59cb2d1ab92cc1a7124319fb,Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+bfd3d184c3a9f5ee59cb2d1ab92cc1a7124319fb,Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+bfd3d184c3a9f5ee59cb2d1ab92cc1a7124319fb,Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+bff1e1ecf00c37ec91edc7c5c85c1390726c3687,Constrained Deep Metric Learning for Person Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
bf03f0fe8f3ba5b118bdcbb935bacb62989ecb11,Effect of Facial Expressions on Feature-Based Landmark Localization in Static Grey Scale Images,University of Tampere,University of Tampere,"Tampereen yliopisto, 4, Kalevantie, Ratinanranta, Tulli, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33100, Suomi",61.49412325,23.77920678,edu,
bf961e4a57a8f7e9d792e6c2513ee1fb293658e9,Robust Face Image Matching under Illumination Variations,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
bf961e4a57a8f7e9d792e6c2513ee1fb293658e9,Robust Face Image Matching under Illumination Variations,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
bf961e4a57a8f7e9d792e6c2513ee1fb293658e9,Robust Face Image Matching under Illumination Variations,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+bf87e84403589f33b7dd076c6e34b0c7eb39a7a7,The First 3D Face Alignment in the Wild (3DFAW) Challenge,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+bf87e84403589f33b7dd076c6e34b0c7eb39a7a7,The First 3D Face Alignment in the Wild (3DFAW) Challenge,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+bf87e84403589f33b7dd076c6e34b0c7eb39a7a7,The First 3D Face Alignment in the Wild (3DFAW) Challenge,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
+bfc04ce7752fac884cf5a78b30ededfd5a0ad109,A Hybrid Model for Identity Obfuscation by Face Replacement,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
bf54b5586cdb0b32f6eed35798ff91592b03fbc4,Methodical Analysis of Western-Caucasian and East-Asian Basic Facial Expressions of Emotions Based on Specific Facial Regions,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+bfdc7cde3bbfcba738a5eefe9143417ebf7d8f5c,"Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds",Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+bfdc7cde3bbfcba738a5eefe9143417ebf7d8f5c,"Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds",Qatar University,Qatar University,"Qatar University, Roindabout 3, Al Tarfa (68), أم صلال, 24685, قطر",25.37461295,51.48980354,edu,
+bfdc7cde3bbfcba738a5eefe9143417ebf7d8f5c,"Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds",University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+bfdc7cde3bbfcba738a5eefe9143417ebf7d8f5c,"Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds",University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+bf6913250ed359fdf130d6465b90b2a0b6fae04e,Pragmatically Informative Image Captioning with Character-Level Reference,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
bf0f0eb0fb31ee498da4ae2ca9b467f730ea9103,Emotion Regulation in Adolescent Males with Attention-Deficit Hyperactivity Disorder: Testing the Effects of Comorbid Conduct Disorder,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
bf0f0eb0fb31ee498da4ae2ca9b467f730ea9103,Emotion Regulation in Adolescent Males with Attention-Deficit Hyperactivity Disorder: Testing the Effects of Comorbid Conduct Disorder,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+bf5c5c346e5d378731030edb53fd0c8a49781468,Bayesian Deep Generative Models for Semi-Supervised and Active Learning,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+bffe37791ee7aa277ba6d7c5ff2cb9bddddea09f,Neural correlates of emotion processing during observed self-face recognition in individuals with autism spectrum disorders,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+bf47f87ccf1b2f9ad18cabf29a715114185648a0,A Component-based Framework for Face Detection and Identification,McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
bf3f8726f2121f58b99b9e7287f7fbbb7ab6b5f5,Visual face scanning and emotion perception analysis between autistic and typically developing children,University of Dhaka,University of Dhaka,"World War Memorial, Shahid Minar Rd, Jagannath Hall, DU, জিগাতলা, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.73169570,90.39652750,edu,
bf3f8726f2121f58b99b9e7287f7fbbb7ab6b5f5,Visual face scanning and emotion perception analysis between autistic and typically developing children,University of Dhaka,University of Dhaka,"World War Memorial, Shahid Minar Rd, Jagannath Hall, DU, জিগাতলা, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.73169570,90.39652750,edu,
+bf3a09f7598afe4e3ab925636f167e55f2b70a9e,Multiple Human Pose Estimation with Temporally Consistent 3D Pictorial Structures,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+bf9b34433bdf14e595a1ed89a23c416990639215,Smart Stadium for Smarter Living: Enriching the Fan Experience,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
bf8a520533f401347e2f55da17383a3e567ef6d8,Bounded-Distortion Metric Learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
bf8a520533f401347e2f55da17383a3e567ef6d8,Bounded-Distortion Metric Learning,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
bf8a520533f401347e2f55da17383a3e567ef6d8,Bounded-Distortion Metric Learning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
bf8a520533f401347e2f55da17383a3e567ef6d8,Bounded-Distortion Metric Learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+bf3d0e41e4d0a2ef6dbdd3018e3c7f728b5efceb,Non-Euclidean dissimilarity data in pattern recognition,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
bff567c58db554858c7f39870cff7c306523dfee,Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+bf179c196b321bbcd58291e52b8259c3f4c1190c,Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
+bf179c196b321bbcd58291e52b8259c3f4c1190c,Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
+bf179c196b321bbcd58291e52b8259c3f4c1190c,Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network,Eindhoven University of Technology,Eindhoven University of Technology,"Technische Universiteit Eindhoven, 2, De Rondom, Villapark, Eindhoven, Noord-Brabant, Nederland, 5600 MB, Nederland",51.44866020,5.49039957,edu,
+bfe9560daea296350c9fb4a9b2b9bf9d10fc1a3e,DualNet: Domain-invariant network for visual question answering,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+bf107f242abea2e52d82dcd834e58b774205ec84,Crowd Counting by Adapting Convolutional Neural Networks with Side Information,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+bf107f242abea2e52d82dcd834e58b774205ec84,Crowd Counting by Adapting Convolutional Neural Networks with Side Information,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+bf107f242abea2e52d82dcd834e58b774205ec84,Crowd Counting by Adapting Convolutional Neural Networks with Side Information,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
bffbd04ee5c837cd919b946fecf01897b2d2d432,Facial Feature Tracking and Occlusion Recovery in American Sign Language,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+bf63599a05692ba4c18476f696edf98bc28a4f3d,Fully Convolutional Neural Networks for Crowd Segmentation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
d35534f3f59631951011539da2fe83f2844ca245,Semantically Decomposing the Latent Spaces of Generative Adversarial Networks,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
d35534f3f59631951011539da2fe83f2844ca245,Semantically Decomposing the Latent Spaces of Generative Adversarial Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
d35534f3f59631951011539da2fe83f2844ca245,Semantically Decomposing the Latent Spaces of Generative Adversarial Networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
d35534f3f59631951011539da2fe83f2844ca245,Semantically Decomposing the Latent Spaces of Generative Adversarial Networks,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+d315396cf26613a552a41630a9698b71b6fb5f9a,On-the-fly global activity prediction and anomaly detection,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+d38af10096aa90dfccd7e4cec9757900bf6958bd,MultiPoseNet: Fast Multi-Person Pose Estimation Using Pose Residual Network,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+d3b832f3c4e8b6d81eac24d6e070f756b9e8a7a1,Examples-Rules Guided Deep Neural Network for Makeup Recommendation,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
d3edbfe18610ce63f83db83f7fbc7634dde1eb40,Large Graph Hashing with Spectral Rotation,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+d372629db7d6516c4729c847eb3f6484ee86de94,The VQA-Machine: Learning How to Use Existing Vision Algorithms to Answer New Questions,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
d3424761e06a8f5f3c1f042f1f1163a469872129,"Pose - invariant , model - based object recognition , using linear combination of views and Bayesian statistics . Vasileios",University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+d377e648734f429ae50c889c43b7b2e9c5ca2d66,"Development of face discrimination abilities, and relationship to magnocellular pathway development, between childhood and adulthood.",Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
d33b26794ea6d744bba7110d2d4365b752d7246f,Transfer Feature Representation via Multiple Kernel Learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+d3015812feb640c79ca8a098e7e27c35f4355ede,Online Nearest Neighbor Search in Hamming Space,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+d3b5a52062e5f5415df527705cb24af9b0846617,Advances and Challenges in 3D and 2D+3D Human Face Recognition,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+d37fa0caee9b598149f73ccc593f54eb2e0ffb58,Application of Self-quotient ε- Filter to Impulse Noise Corrupted Image,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
d3d5d86afec84c0713ec868cf5ed41661fc96edc,A Comprehensive Analysis of Deep Learning Based Representation for Face Recognition,Sabanci University,Sabanci University,"Sabanci Universitesi, Preveze Cad., Orta Mahallesi, Tepeören, Tuzla, İstanbul, Marmara Bölgesi, 34953, Türkiye",40.89271590,29.37863323,edu,
d3d5d86afec84c0713ec868cf5ed41661fc96edc,A Comprehensive Analysis of Deep Learning Based Representation for Face Recognition,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
+d392098688a999c70589c995bd4427c212eff69d,Object Repositioning Based on the Perspective in a Single Image,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+d3d37a44a7a0453445e6e433a527b0164ec99b88,Efficient Use of Geometric Constraints for Sliding-Window Object Detection in Video,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
d3e04963ff42284c721f2bc6a90b7a9e20f0242f,On Forensic Use of Biometrics,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
d35c82588645b94ce3f629a0b98f6a531e4022a3,Scalable Online Annotation & Object Localisation For Broadcast Media Production,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
d35c82588645b94ce3f629a0b98f6a531e4022a3,Scalable Online Annotation & Object Localisation For Broadcast Media Production,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+d3dcdd5bd1592ff8555629068e046ce0741d6062,Sparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel Approach,"CSIRO, Australia","NICTA, PO Box 6020, St Lucia, QLD 4067, Australia","Research Way, Clayton VIC 3168, Australia",-37.90627370,145.13194490,edu,f.k.a. NICTA
+d3dcdd5bd1592ff8555629068e046ce0741d6062,Sparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel Approach,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+d3dcdd5bd1592ff8555629068e046ce0741d6062,Sparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel Approach,"Australian National University, Canberra","Australian National University, Canberra","Australian National University, Garran Road, Acton, Canberra, Canberra Central, Australian Capital Territory, 2601, Australia",-35.28121335,149.11665331,edu,
+d3a1322c988b50049986365c27dcfce42828d2ca,van Gent Clustering Faces from the National Archives of Estonia Bachelor ’ s Thesis ( 9 ECTS ),University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
+d3516392214e7c0dde80a2ea8ba45e70e462fea6,In Defense of the Classification Loss for Person Re-Identification,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+d399a5dc23866e4590d7a76174154a582b93a18d,Guiding Optical Flow Estimation,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
d394bd9fbaad1f421df8a49347d4b3fca307db83,Recognizing facial expressions at low resolution,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+d31e827d7570de3088f7ce582a4be2dbd38dc1b0,Amygdala activity for the modulation of goal-directed behavior in emotional contexts,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+d350e3753756b1c6946d5d9150626b2de4f7a8e4,Toward Diverse Text Generation with Inverse Reinforcement Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+d350e3753756b1c6946d5d9150626b2de4f7a8e4,Toward Diverse Text Generation with Inverse Reinforcement Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
d3b550e587379c481392fb07f2cbbe11728cf7a6,Small Sample Size Face Recognition using Random Quad-Tree based Ensemble Algorithm,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
d307a766cc9c728a24422313d4c3dcfdb0d16dd5,Deep Keyframe Detection in Human Action Videos,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
d307a766cc9c728a24422313d4c3dcfdb0d16dd5,Deep Keyframe Detection in Human Action Videos,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
d307a766cc9c728a24422313d4c3dcfdb0d16dd5,Deep Keyframe Detection in Human Action Videos,Hunan University,Hunan University,"Yejin University for Employees, 冶金西路, 和平乡, 珠晖区, 衡阳市 / Hengyang, 湖南省, 中国",26.88111275,112.62850666,edu,
d307a766cc9c728a24422313d4c3dcfdb0d16dd5,Deep Keyframe Detection in Human Action Videos,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
d31af74425719a3840b496b7932e0887b35e9e0d,A Multimodal Deep Log-Based User Experience (UX) Platform for UX Evaluation,Kyung Hee University,Kyung Hee University,"Kyung Hee Tae Kwon Do, Vons 2370 Truck Service Ramp, University City, San Diego, San Diego County, California, 92122, USA",32.85363330,-117.20352860,edu,
+d3312da8c703ed7842285289c3d9478f333dbd48,See the Forest for the Trees: Joint Spatial and Temporal Recurrent Neural Networks for Video-Based Person Re-identification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
d3b0839324d0091e70ce34f44c979b9366547327,Precise Box Score: Extract More Information from Datasets to Improve the Performance of Face Detection,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
d30050cfd16b29e43ed2024ae74787ac0bbcf2f7,Facial Expression Classification Using Convolutional Neural Network and Support Vector Machine,Marquette University,Marquette University,"Marquette University, West Wisconsin Avenue, University Hill, Milwaukee, Milwaukee County, Wisconsin, 53226, USA",43.03889625,-87.93155450,edu,
d3faed04712b4634b47e1de0340070653546deb2,Neural Best-Buddies: Sparse Cross-Domain Correspondence,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
d3faed04712b4634b47e1de0340070653546deb2,Neural Best-Buddies: Sparse Cross-Domain Correspondence,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
d3faed04712b4634b47e1de0340070653546deb2,Neural Best-Buddies: Sparse Cross-Domain Correspondence,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
d3faed04712b4634b47e1de0340070653546deb2,Neural Best-Buddies: Sparse Cross-Domain Correspondence,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+d37013e4ce0f5dd6b61a4ffadecc401274966602,Reading affect in the face and voice: neural correlates of interpreting communicative intent in children and adolescents with autism spectrum disorders.,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+d4ea0438b6c0479a7d7611130a0dc242a22f93eb,Pose2Instance: Harnessing Keypoints for Person Instance Segmentation,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
d4a5eaf2e9f2fd3e264940039e2cbbf08880a090,An Occluded Stacked Hourglass Approach to Facial Landmark Localization and Occlusion Estimation,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+d45e856d22714d6ea7bd80a8c73d2be3b1f16f27,Learning Interpretable Spatial Operations in a Rich 3D Blocks World,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+d45e856d22714d6ea7bd80a8c73d2be3b1f16f27,Learning Interpretable Spatial Operations in a Rich 3D Blocks World,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+d453e0d308919867b5814beb1394cd0cc1cb2378,STOIC: A database of dynamic and static faces expressing highly recognizable emotions,University of Glasgow,University of Glasgow,"University of Glasgow, University Avenue, Yorkhill, Hillhead, Glasgow, Glasgow City, Scotland, G, UK",55.87231535,-4.28921784,edu,
+d4a925cb0ca66b1cacec325751f4a85e5b74790d,Adversarially Learned Inference,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
d444e010049944c1b3438c9a25ae09b292b17371,Structure Preserving Video Prediction,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+d462d514c0a177eb82aec8175bf431189218e393,Face recognition using regularised generalised discriminant locality preserving projections,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
d46fda4b49bbc219e37ef6191053d4327e66c74b,Facial Expression Recognition Based on Complexity Perception Classification Algorithm,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
d448d67c6371f9abf533ea0f894ef2f022b12503,Weakly supervised collective feature learning from curated media,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+d406ec45ab1d1453cc207fff265077101154d613,Horizontal Pyramid Matching for Person Re-identification,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+d4b34e327b62b7f3fbddfc403e4642b17245a3b7,Partial Person Re-identification with Alignment and Hallucination,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
d492dbfaa42b4f8b8a74786d7343b3be6a3e9a1d,Deep Cost-Sensitive and Order-Preserving Feature Learning for Cross-Population Age Estimation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
d492dbfaa42b4f8b8a74786d7343b3be6a3e9a1d,Deep Cost-Sensitive and Order-Preserving Feature Learning for Cross-Population Age Estimation,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+d428aa4c1c84da422f8c99eb0147a49439d16f0d,Audio-Visual Spontaneous Emotion Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+d46509935f7d485295587d4fc201c42108760379,Facial Image Analysis by CNN with Weighted Heterogeneous Learning,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
+d4448f8aa320f04066cc43201d55ddd023eb712e,Clothing Change Aware Person Identification,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+d4448f8aa320f04066cc43201d55ddd023eb712e,Clothing Change Aware Person Identification,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
d46b4e6871fc9974542215f001e92e3035aa08d9,A Gabor Quotient Image for Face Recognition under Varying Illumination,Mahanakorn University of Technology,Mahanakorn University of Technology,"มหาวิทยาลัยเทคโนโลยีมหานคร, 140, ถนนเชื่อมสัมพันธ์, กรุงเทพมหานคร, เขตหนองจอก, กรุงเทพมหานคร, 10530, ประเทศไทย",13.84450465,100.85620818,edu,
+d4f1eb008eb80595bcfdac368e23ae9754e1e745,Unconstrained Face Detection and Open-Set Face Recognition Challenge,"University of Colorado, Colorado Springs",University of Colorado Colorado Springs,"Main Hall, The Spine, Colorado Springs, El Paso County, Colorado, 80907, USA",38.89207560,-104.79716389,edu,
d454ad60b061c1a1450810a0f335fafbfeceeccc,Deep Regression Forests for Age Estimation,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
d40cd10f0f3e64fd9b0c2728089e10e72bea9616,Enhancing Face Identification Using Local Binary Patterns and K-Nearest Neighbors,Hangzhou Dianzi University,Hangzhou Dianzi University,"杭州电子科技大学, 2号大街, 白杨街道, 江干区 (Jianggan), 杭州市 Hangzhou, 浙江省, 310018, 中国",30.31255250,120.34309460,edu,
+d46a5bba21f897f1c4b3366dcb663820ef1c282d,Cerebral Hemodynamic Response to Faces,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+d476b357c5bbc7bfae06a3876a5c0852d31d1b6e,A Novel Visual Organization Based on Topological Perception,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+d476b357c5bbc7bfae06a3876a5c0852d31d1b6e,A Novel Visual Organization Based on Topological Perception,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
d46e793b945c4f391031656357625e902c4405e8,Face-off: automatic alteration of facial features,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
d4c2d26523f577e2d72fc80109e2540c887255c8,Face-space Action Recognition by Face-Object Interactions,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
+d4d2014f05e17869b72f180fd0065358c722ac65,UNIVERSITY OF CALGARY A MULTIMODAL BIOMETRIC SYSTEM BASED ON RANK LEVEL FUSION by MD. MARUF MONWAR A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+d467035d83fb4e86c4a47b2ca87894388deb8c44,Relief R-CNN : Utilizing Convolutional Feature Interrelationship for Object Detection,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+d437a69d631b48583acc19c946b48e7d601d7853,Trace Norm Regularised Deep Multi-Task Learning,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+ba21fd28003994480f713b0a1276160fea2e89b5,Identification of Individuals from Ears in Real World Conditions,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+ba21fd28003994480f713b0a1276160fea2e89b5,Identification of Individuals from Ears in Real World Conditions,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
baaaf73ec28226d60d923bc639f3c7d507345635,Emotion Classification on face images,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
ba2bbef34f05551291410103e3de9e82fdf9dddd,A Study on Cross-Population Age Estimation,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
ba2bbef34f05551291410103e3de9e82fdf9dddd,A Study on Cross-Population Age Estimation,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+baff74e4a9880d7477799822d8e68224466f3e76,What Can Help Pedestrian Detection?,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+baff74e4a9880d7477799822d8e68224466f3e76,What Can Help Pedestrian Detection?,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+baff74e4a9880d7477799822d8e68224466f3e76,What Can Help Pedestrian Detection?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+baff74e4a9880d7477799822d8e68224466f3e76,What Can Help Pedestrian Detection?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+bafd1978d6a68db89b4b75008e1bb53aea81f632,DeMIAN: Deep Modality Invariant Adversarial Network,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
baa0fe4d0ac0c7b664d4c4dd00b318b6d4e09143,Facial Expression Analysis using Active Shape Model,University of Portsmouth,University of Portsmouth,"University of Portsmouth - North Zone, Portland Street, Portsea, Portsmouth, South East, England, PO1 3DE, UK",50.79805775,-1.09834911,edu,
+ba25c219b52d675b579941364ce6ee6700cea8e8,8D-THERMO CAM: Combination of Geometry with Physiological Information for Face Recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+bacc83feb1146bb3d4cb3fa6304090c2ceb6e0d0,Attribute Learning for Network Intrusion Detection,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
+baa1e6894024223a928aa00be698247ae253e7cb,"Patterns of eye movements when male and female observers judge female attractiveness , body fat and waist-to-hip ratio",University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+baa1e6894024223a928aa00be698247ae253e7cb,"Patterns of eye movements when male and female observers judge female attractiveness , body fat and waist-to-hip ratio",Newcastle University,Newcastle University,"Newcastle University, Claremont Walk, Haymarket, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE1 7RU, UK",54.98023235,-1.61452627,edu,
+ba82f4ebd5e62c049387dcb6a1bffbc5d23aea2b,Ordinal Depth Supervision for 3D Human Pose Estimation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+ba82f4ebd5e62c049387dcb6a1bffbc5d23aea2b,Ordinal Depth Supervision for 3D Human Pose Estimation,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
badcfb7d4e2ef0d3e332a19a3f93d59b4f85668e,The Application of Extended Geodesic Distance in Head Poses Estimation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
badcfb7d4e2ef0d3e332a19a3f93d59b4f85668e,The Application of Extended Geodesic Distance in Head Poses Estimation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
badcfb7d4e2ef0d3e332a19a3f93d59b4f85668e,The Application of Extended Geodesic Distance in Head Poses Estimation,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+ba26bf9ffd328d23faca2deea9ebb3292bddcd93,Neural Styling for Interpretable Fair Representations,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+ba9e967208976f24a09730af94086e7ae0417067,An Open Source Framework for Standardized Comparisons of Face Recognition Algorithms,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
bac11ce0fb3e12c466f7ebfb6d036a9fe62628ea,Weakly Supervised Learning of Heterogeneous Concepts in Videos,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+ba0ac513d656eef49666ea2231b516bab286661b,"SUBSPACE CLUSTERING BY (k, k)-SPARSE MATRIX FACTORIZATION",Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
ba7b12c8e2ff3c5e4e0f70b58215b41b18ff8feb,Natural and Effective Obfuscation by Head Inpainting,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+bab65e5a5e0768fbddfaa0fa85f9fe9a51d38b6c,Personalized Modeling of Facial Action Unit Intensity,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+bab65e5a5e0768fbddfaa0fa85f9fe9a51d38b6c,Personalized Modeling of Facial Action Unit Intensity,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+bab65e5a5e0768fbddfaa0fa85f9fe9a51d38b6c,Personalized Modeling of Facial Action Unit Intensity,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+a05e84f77e1dacaa1c59ba0d92919bdcfe4debbb,Video Question Answering via Hierarchical Spatio-Temporal Attention Networks,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+a05e84f77e1dacaa1c59ba0d92919bdcfe4debbb,Video Question Answering via Hierarchical Spatio-Temporal Attention Networks,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+a01d22166ed62f5ad485ae32827c70d583a88564,Zero-Shot Learning by Convex Combination of Semantic Embeddings,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+a01d22166ed62f5ad485ae32827c70d583a88564,Zero-Shot Learning by Convex Combination of Semantic Embeddings,Google,"Google, Inc.","1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA",37.42199990,-122.08405750,company,"Google, Mountain View, CA"
a065080353d18809b2597246bb0b48316234c29a,FHEDN: A based on context modeling Feature Hierarchy Encoder-Decoder Network for face detection,Chongqing University,Chongqing University,"重庆工商大学, 19, 翠林路, 重庆市, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400067, 中国",29.50841740,106.57858552,edu,
+a0dc8911c47c3d0e1643ecfaa7032cee6fb5eb64,Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
a0f193c86e3dd7e0020c0de3ec1e24eaff343ce4,A New Classification Approach using Discriminant Functions,Sakarya University,Sakarya University,"Sakarya Üniversitesi Diş Hekimliği Fakültesi, Adnan Menderes Caddesi, Güneşler, Adapazarı, Sakarya, Marmara Bölgesi, 54050, Türkiye",40.76433515,30.39407875,edu,
+a07a894108b5ddc19d18e66e969f47a3b2a6e006,On-the-Fly Performance Evaluation of Large-Scale Fiber Track- ing,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
a0dc68c546e0fc72eb0d9ca822cf0c9ccb4b4c4f,Fusing with context: A Bayesian approach to combining descriptive attributes,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
a0dc68c546e0fc72eb0d9ca822cf0c9ccb4b4c4f,Fusing with context: A Bayesian approach to combining descriptive attributes,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
+a0c670e76594bb72992a92fd8d51b42cee868a50,Hierarchical Cross Network for Person Re-identification,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
a0021e3bbf942a88e13b67d83db7cf52e013abfd,Human concerned object detecting in video,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+a082b1ee9a5bafe678539e694197c0910d4a09b2,Point-pair descriptors for 3D facial landmark localisation,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
a0d6390dd28d802152f207940c7716fe5fae8760,Bayesian Face Revisited: A Joint Formulation,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
a0d6390dd28d802152f207940c7716fe5fae8760,Bayesian Face Revisited: A Joint Formulation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
a0d6390dd28d802152f207940c7716fe5fae8760,Bayesian Face Revisited: A Joint Formulation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+a04273851ae262e884b175c22decd56cbd24e14e,Correcting the Triplet Selection Bias for Triplet Loss,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+a04273851ae262e884b175c22decd56cbd24e14e,Correcting the Triplet Selection Bias for Triplet Loss,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+a04273851ae262e884b175c22decd56cbd24e14e,Correcting the Triplet Selection Bias for Triplet Loss,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a0ddf6e9697631f771d73b721a3d871db6a04f6c,Multi-view Facial Expressions Recognition using Local Linear Regression of Sparse Codes,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
a0aa32bb7f406693217fba6dcd4aeb6c4d5a479b,Cascaded Regressor based 3D Face Reconstruction from a Single Arbitrary View Image,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+a06f0b2d569cbef0822ae5e8625b4cb2a7f1d78c,Effective scaling registration approach by imposing the emphasis on the scale factor,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
+a0e9064d59cb3b23b425bb954dd8c77fdc8637c8,The Neural Painter: Multi-Turn Image Generation,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
a06b6d30e2b31dc600f622ab15afe5e2929581a7,Robust Joint and Individual Variance Explained,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
a06b6d30e2b31dc600f622ab15afe5e2929581a7,Robust Joint and Individual Variance Explained,Middlesex University,Middlesex University,"Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK",51.59029705,-0.22963221,edu,
a0b1990dd2b4cd87e4fd60912cc1552c34792770,Deep Constrained Local Models for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
a0b1990dd2b4cd87e4fd60912cc1552c34792770,Deep Constrained Local Models for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
a0b1990dd2b4cd87e4fd60912cc1552c34792770,Deep Constrained Local Models for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a06a7b1236c16d3628b39e3c37d566499c3446f0,Global Binary Patterns: A Novel Shape Descriptor,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
a0e7f8771c7d83e502d52c276748a33bae3d5f81,Ensemble Nyström,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
+a0d1e2934e6fbf42175fe6f04c281a976dc33975,"Social Attention, Affective Arousal and Empathy in Men with Klinefelter Syndrome (47,XXY): Evidence from Eyetracking and Skin Conductance",Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+a08f09c5923dd2a114da1504379e57e8eb87ced6,Estimation of psychological stress levels using Facial Expression Spatial Charts,Akita Prefectural University,Akita Prefectural University,"秋田県立大学, 秋田天王線, 潟上市, 秋田県, 東北地方, 011-0946, 日本",39.80114990,140.04591160,edu,
a0061dae94d916f60a5a5373088f665a1b54f673,Lensless computational imaging through deep learning,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
a0061dae94d916f60a5a5373088f665a1b54f673,Lensless computational imaging through deep learning,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+a02f070080d4bd0fcef8b3234ca6b8ee7c97fb50,A principled approach to remove false alarms by modelling the context of a face detector,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+a00a757b26d5c4f53b628a9c565990cdd0e51876,The BURCHAK corpus: a Challenge Data Set for Interactive Learning of Visually Grounded Word Meanings,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+a00a757b26d5c4f53b628a9c565990cdd0e51876,The BURCHAK corpus: a Challenge Data Set for Interactive Learning of Visually Grounded Word Meanings,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+a00a757b26d5c4f53b628a9c565990cdd0e51876,The BURCHAK corpus: a Challenge Data Set for Interactive Learning of Visually Grounded Word Meanings,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+a00a757b26d5c4f53b628a9c565990cdd0e51876,The BURCHAK corpus: a Challenge Data Set for Interactive Learning of Visually Grounded Word Meanings,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
a0848d7b1bb43f4b4f1b4016e58c830f40944817,Face Matching for Post-Disaster Family Reunification,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+a0c81783ec60bd64aefc49285eb082a8185d49c1,TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+a7dab944b42c87c52df2abe016158eafb110b2af,A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA) Utilizing Raster Attribute Tables,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+a7dab944b42c87c52df2abe016158eafb110b2af,A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA) Utilizing Raster Attribute Tables,Aberystwyth University,Aberystwyth University,"Aberystwyth University, Llanbadarn Campus, Cefn Esgair, Waun Fawr, Comins Coch, Ceredigion, Wales, SY23 3JG, UK",52.41073580,-4.05295501,edu,
+a7dab944b42c87c52df2abe016158eafb110b2af,A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA) Utilizing Raster Attribute Tables,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+a75095fcfa78972dd222810fb3e39d77ff6493aa,Fusing Complementary Operators to Enhance Foreground/Background Segmentation,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+a71d0bf3b8fa6cf0069fe12f3fe6d695fac7dd44,DRAG: A Database for Recognition and Analysis of Gait,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+a71d0bf3b8fa6cf0069fe12f3fe6d695fac7dd44,DRAG: A Database for Recognition and Analysis of Gait,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+a754989741afb89e588b52de375054dffbeda39d,Max-Margin Multiple-Instance Dictionary Learning,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+a77e462997e903fec8d831af11b7f61b209c27a6,Free Space Estimation using Occupancy Grids and Dynamic Object Detection,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+a77342abe136fdbef8da9b43055356e3596c570c,Revealing the Secret of FaceHashing,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+a77342abe136fdbef8da9b43055356e3596c570c,Revealing the Secret of FaceHashing,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+a70650358cc226e7f613b49f93d7eca044ca608e,Modeling multimodal cues in a deep learning-based framework for emotion recognition in the wild,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+a70650358cc226e7f613b49f93d7eca044ca608e,Modeling multimodal cues in a deep learning-based framework for emotion recognition in the wild,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+a7fc39214fe447f650441d033401ca73b45c6633,Weakly Supervised Learning of Affordances,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
a70e36daf934092f40a338d61e0fe27be633f577,Enhanced facial feature tracking of spontaneous and continuous expressions,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
+a72821008c41032e82f377b53bd96b5f7f8be025,Action Recognition Using Discriminative Structured Trajectory Groups,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+a7a66d713776e78ae60617eee2715443a8565a23,Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
a7191958e806fce2505a057196ccb01ea763b6ea,Convolutional Neural Network based Age Estimation from Facial Image and Depth Prediction from Single Image,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
a7191958e806fce2505a057196ccb01ea763b6ea,Convolutional Neural Network based Age Estimation from Facial Image and Depth Prediction from Single Image,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
a7e1327bd76945a315f2869bfae1ce55bb94d165,Kernel Fisher Discriminant Analysis with Locality Preserving for Feature Extraction and Recognition,Guangdong Medical College,Guangdong Medical College,"医学院, 真如路, 凤凰新村, 天河区, 广州市, 广东省, 510635, 中国",23.12944890,113.34376110,edu,
a7e1327bd76945a315f2869bfae1ce55bb94d165,Kernel Fisher Discriminant Analysis with Locality Preserving for Feature Extraction and Recognition,Guangdong Medical College,Guangdong Medical College,"医学院, 真如路, 凤凰新村, 天河区, 广州市, 广东省, 510635, 中国",23.12944890,113.34376110,edu,
a7c39a4e9977a85673892b714fc9441c959bf078,Automated Individualization of Deformable Eye Region Model and Its Application to Eye Motion Analysis,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
a7c39a4e9977a85673892b714fc9441c959bf078,Automated Individualization of Deformable Eye Region Model and Its Application to Eye Motion Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a7a0099caf89bedbf4de1c61499f999ea4fc7d98,Combining Class Taxonomies and Multi Task Learning To Regularize Fine-grained Recognition,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+a7e5c01e3dca9284f8acffad750cdbb29689d3fb,Introduction to the special issue on learning semantics,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+a7e5c01e3dca9284f8acffad750cdbb29689d3fb,Introduction to the special issue on learning semantics,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+a7e5c01e3dca9284f8acffad750cdbb29689d3fb,Introduction to the special issue on learning semantics,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+a7e5c01e3dca9284f8acffad750cdbb29689d3fb,Introduction to the special issue on learning semantics,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
a75edf8124f5b52690c08ff35b0c7eb8355fe950,Authentic Emotion Detection in Real-Time Video,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
a75edf8124f5b52690c08ff35b0c7eb8355fe950,Authentic Emotion Detection in Real-Time Video,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+a74bd6c9c4631117a036ce0e1c8e3d2a0b1f1f5e,Accelerated Learning-Based Interactive Image Segmentation Using Pairwise Constraints,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+a765b506d29cb46420e125c86ab6ff442905e9d6,DPatch: An Adversarial Patch Attack on Object Detectors,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+a765b506d29cb46420e125c86ab6ff442905e9d6,DPatch: An Adversarial Patch Attack on Object Detectors,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+a7b4291b1feebaed4a36808df2a17a3e452b9efa,"Zero-Shot Learning — The Good, the Bad and the Ugly",Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+a7b4291b1feebaed4a36808df2a17a3e452b9efa,"Zero-Shot Learning — The Good, the Bad and the Ugly",University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+a77008329c785c0d5d4dcb3d9c79073df85a9b4e,Neural codes of seeing architectural styles,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+a77008329c785c0d5d4dcb3d9c79073df85a9b4e,Neural codes of seeing architectural styles,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+a776acc53591c3eb0b53501d9758d984e2e52a97,Weakly Supervised Instance Segmentation using Class Peak Response,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+a776acc53591c3eb0b53501d9758d984e2e52a97,Weakly Supervised Instance Segmentation using Class Peak Response,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+a7e9d230bc44dfbe56757f3025d5b4caa49032f3,Unity in Diversity: Discovering Topics from Words - Information Theoretic Co-clustering for Visual Categorization,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
a75dfb5a839f0eb4b613d150f54a418b7812aa90,Multibiometric secure system based on deep learning,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+b88b83d2ffd30bf3bc3be3fb7492fd88f633b2fe,Subcategory-Aware Object Classification,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+b8b2acc7e5bd94651c8bb025b6311c108c7a7d37,Iteratively Learning from the Best,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+b8b0f0ca35cb02334aaa3192559fb35f0c90f8fa,Face Recognition in Low-resolution Images by Using Local Zernike Moments,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
b88ceded6467e9b286f048bb1b17be5998a077bd,Sparse Subspace Clustering via Diffusion Process,Curtin University,Curtin University,"Curtin University, Brand Drive, Waterford, Perth, Western Australia, 6102, Australia",-32.00686365,115.89691775,edu,
+b85308870c2b6b8b46ec78908bfd3140ed1398ad,Learning Latent Super-Events to Detect Multiple Activities in Videos,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
b8375ff50b8a6f1a10dd809129a18df96888ac8b,Natural Video Sequence Prediction,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
b8375ff50b8a6f1a10dd809129a18df96888ac8b,Natural Video Sequence Prediction,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
b88d5e12089f6f598b8c72ebeffefc102cad1fc0,Robust 2DPCA and Its Application,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
b88d5e12089f6f598b8c72ebeffefc102cad1fc0,Robust 2DPCA and Its Application,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
b84b7b035c574727e4c30889e973423fe15560d7,Human Age Estimation Using Ranking SVM,HoHai University,HoHai University,"河海大学, 河海路, 小市桥, 鼓楼区, 南京市, 江苏省, 210013, 中国",32.05765485,118.75500040,edu,
b84b7b035c574727e4c30889e973423fe15560d7,Human Age Estimation Using Ranking SVM,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+b849bfe51138d88f6cae2d602b5e2a42565fb1c7,Weakly Supervised Object Localization with Stable Segmentations,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+b85e71d4e68588211c877fff8cda267b3a6bb6c9,"End-to-end learning of motion , appearance and interaction cues for multi-target tracking",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+b85e71d4e68588211c877fff8cda267b3a6bb6c9,"End-to-end learning of motion , appearance and interaction cues for multi-target tracking",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+b85e71d4e68588211c877fff8cda267b3a6bb6c9,"End-to-end learning of motion , appearance and interaction cues for multi-target tracking",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+b8a70bfba1cb51b92a3f168458f8b0af7f90df14,Action-Agnostic Human Pose Forecasting,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+b8d61dc56a4112e0317c6a7323417ee649476148,Cross Pixel Optical Flow Similarity for Self-Supervised Learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+b8349ba39a034d7bc693b6613f2bc173f0ac27b8,Dissertation Object Detection from Aerial Image NGUYEN,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+b83155a18b95dcb551a0787b135d61d99eb82ac5,Three-dimensional Face Imaging and Recognition: a Sensor Design and Comparative Study,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
b8caf1b1bc3d7a26a91574b493c502d2128791f6,As Far as the Eye Can See: Relationship between Psychopathic Traits and Pupil Response to Affective Stimuli,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
b8caf1b1bc3d7a26a91574b493c502d2128791f6,As Far as the Eye Can See: Relationship between Psychopathic Traits and Pupil Response to Affective Stimuli,Swansea University,Swansea University,"Swansea University, University Footbridge, Sketty, Swansea, Wales, SA2 8PZ, UK",51.60915780,-3.97934429,edu,
+b8af24279c58a718091817236f878c805a7843e1,Context Aware Anomalous Behaviour Detection in Crowded Surveillance,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
b8084d5e193633462e56f897f3d81b2832b72dff,DeepID3: Face Recognition with Very Deep Neural Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
b8084d5e193633462e56f897f3d81b2832b72dff,DeepID3: Face Recognition with Very Deep Neural Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
b8084d5e193633462e56f897f3d81b2832b72dff,DeepID3: Face Recognition with Very Deep Neural Networks,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+b8556e7ace156cee0199c057c5bf6eacaae45e7c,Automatic fetal face detection by locating fetal facial features from 3D ultrasound images for navigating fetoscopic tracheal occlusion surgeries,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
+b8556e7ace156cee0199c057c5bf6eacaae45e7c,Automatic fetal face detection by locating fetal facial features from 3D ultrasound images for navigating fetoscopic tracheal occlusion surgeries,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+b873246d9c474bf7799d6f45deb1155144dbd6b5,Image Analysis for Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+b81a5b676e5e8eee7dc99d5319ecb963f22d05c5,T ^2 2 Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Tasks,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+b8c08c1330779283b3fbf06d133faf8bd55ea941,Online Regression with Feature Selection in Stochastic Data Streams,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+b8c08c1330779283b3fbf06d133faf8bd55ea941,Online Regression with Feature Selection in Stochastic Data Streams,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+b8c08c1330779283b3fbf06d133faf8bd55ea941,Online Regression with Feature Selection in Stochastic Data Streams,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
b8ebda42e272d3617375118542d4675a0c0e501d,Deep Hashing Network for Unsupervised Domain Adaptation,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
b87b0fa1ac0aad0ca563844daecaeecb2df8debf,Non-photorealistic rendering of portraits,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
b87db5ac17312db60e26394f9e3e1a51647cca66,Semi-definite Manifold Alignment,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
b87db5ac17312db60e26394f9e3e1a51647cca66,Semi-definite Manifold Alignment,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+b8df2c2fa02a37d09b73277ca4edde654ac80953,Exploiting Facial Landmarks for Emotion Recognition in the Wild,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+b859d1fc1a7ad756815490527319d458fa9af3d2,Learning Structure and Strength of CNN Filters for Small Sample Size Training,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
b81cae2927598253da37954fb36a2549c5405cdb,Experiments on Visual Information Extraction with the Faces of Wikipedia,Polytechnique Montreal,Polytechnique Montr´eal,"2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4, Canada",45.50438400,-73.61288290,edu,"Polytechnique Montreal, Montreal, Quebec, Canada"
+b10427999fbde2d90e3541c477e2f6ba4c8f08cc,Bridge Video and Text with Cascade Syntactic Structure,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+b13b6e3dfdf6d708a923c547113d99047f1a0374,Neural activation to emotional faces in adolescents with autism spectrum disorders.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+b13b6e3dfdf6d708a923c547113d99047f1a0374,Neural activation to emotional faces in adolescents with autism spectrum disorders.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
b191aa2c5b8ece06c221c3a4a0914e8157a16129,Deep Spatio-temporal Manifold Network for Action Recognition,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
b191aa2c5b8ece06c221c3a4a0914e8157a16129,Deep Spatio-temporal Manifold Network for Action Recognition,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
b191aa2c5b8ece06c221c3a4a0914e8157a16129,Deep Spatio-temporal Manifold Network for Action Recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
@@ -3216,34 +8803,79 @@ b13bf657ca6d34d0df90e7ae739c94a7efc30dc3,Attribute and Simile Classifiers for Fa b13bf657ca6d34d0df90e7ae739c94a7efc30dc3,Attribute and Simile Classifiers for Face Verification (In submission please do not distribute.),Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
b13bf657ca6d34d0df90e7ae739c94a7efc30dc3,Attribute and Simile Classifiers for Face Verification (In submission please do not distribute.),Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
b13bf657ca6d34d0df90e7ae739c94a7efc30dc3,Attribute and Simile Classifiers for Face Verification (In submission please do not distribute.),Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+b1177aad0db8bd6b605ffe0d68addaf97b1f9a6b,Visual Representations and Models: From Latent SVM to Deep Learning,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
b13a882e6168afc4058fe14cc075c7e41434f43e,Recognition of Humans and Their Activities Using Video,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
b1665e1ddf9253dcaebecb48ac09a7ab4095a83e,Emotion Recognition Using Facial Expressions with Active Appearance Models,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
b1665e1ddf9253dcaebecb48ac09a7ab4095a83e,Emotion Recognition Using Facial Expressions with Active Appearance Models,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
b16580d27bbf4e17053f2f91bc1d0be12045e00b,Pose-Invariant Face Recognition with a Two-Level Dynamic Programming Algorithm,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+b13e819c48bcb2362614c18cdcd7a53d90944fea,3D Face Recognition in the Presence of Expression: A Guidance-based Constraint Deformation Approach,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
b1b993a1fbcc827bcb99c4cc1ba64ae2c5dcc000,Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
b11bb6bd63ee6f246d278dd4edccfbe470263803,Joint Voxel and Coordinate Regression for Accurate 3D Facial Landmark Localization,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+b1e8476673ee55f3e33bfb7c5f309032522c4c1f,Context-Dependent Diffusion Network for Visual Relationship Detection,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+b1e8476673ee55f3e33bfb7c5f309032522c4c1f,Context-Dependent Diffusion Network for Visual Relationship Detection,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+b1d2001e877bb36c8ccc97bee62d9824a3b8874d,Top-Down Attention Recurrent VLAD Encoding for Action Recognition in Videos,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
b13e2e43672e66ba45d1b852a34737e4ce04226b,Face Painting: querying art with photos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
b1e4f8c15ff30cc7d35ab25ff3eddaf854e0a87c,Conveying facial expressions to blind and visually impaired persons through a wearable vibrotactile device,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
b1e4f8c15ff30cc7d35ab25ff3eddaf854e0a87c,Conveying facial expressions to blind and visually impaired persons through a wearable vibrotactile device,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+b1e218046a28d10ec0be3272809608dea378eddc,Overview of the Multiple Biometrics Grand Challenge,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
b18858ad6ec88d8b443dffd3e944e653178bc28b,Trojaning Attack on Neural Networks,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
b18858ad6ec88d8b443dffd3e944e653178bc28b,Trojaning Attack on Neural Networks,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
b18858ad6ec88d8b443dffd3e944e653178bc28b,Trojaning Attack on Neural Networks,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
b18858ad6ec88d8b443dffd3e944e653178bc28b,Trojaning Attack on Neural Networks,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
b18858ad6ec88d8b443dffd3e944e653178bc28b,Trojaning Attack on Neural Networks,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
b18858ad6ec88d8b443dffd3e944e653178bc28b,Trojaning Attack on Neural Networks,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+b10319193be303038a9f58e7552632791e3f1ada,From One-Trick Ponies to All-Rounders: On-Demand Learning for Image Restoration,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
b133b2d7df9b848253b9d75e2ca5c68e21eba008,"Kobe University, NICT and University of Siegen at TRECVID 2017 AVS Task",Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
b133b2d7df9b848253b9d75e2ca5c68e21eba008,"Kobe University, NICT and University of Siegen at TRECVID 2017 AVS Task",Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
b1df214e0f1c5065f53054195cd15012e660490a,Supplementary Material to Sparse Coding and Dictionary Learning with Linear Dynamical Systems,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+b136b5f3fb84867ba89ad5e2ef3266e09d54e232,Training Convolutional Neural Networks with Limited Training Data for Ear Recognition in the Wild,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+b136b5f3fb84867ba89ad5e2ef3266e09d54e232,Training Convolutional Neural Networks with Limited Training Data for Ear Recognition in the Wild,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+b11872621d9550ec2f1d09f2f02237182744e2ee,Less is More: Unified Model for Unsupervised Multi-Domain Image-to-Image Translation,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+b11872621d9550ec2f1d09f2f02237182744e2ee,Less is More: Unified Model for Unsupervised Multi-Domain Image-to-Image Translation,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+b11872621d9550ec2f1d09f2f02237182744e2ee,Less is More: Unified Model for Unsupervised Multi-Domain Image-to-Image Translation,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+b11872621d9550ec2f1d09f2f02237182744e2ee,Less is More: Unified Model for Unsupervised Multi-Domain Image-to-Image Translation,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+b11872621d9550ec2f1d09f2f02237182744e2ee,Less is More: Unified Model for Unsupervised Multi-Domain Image-to-Image Translation,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
b185f0a39384ceb3c4923196aeed6d68830a069f,Describing Clothing by Semantic Attributes,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
b185f0a39384ceb3c4923196aeed6d68830a069f,Describing Clothing by Semantic Attributes,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+b19e8bce7a3180456f8748caabade89dd802ea84,Inferring and Executing Programs for Visual Reasoning Supplementary Material,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
b1429e4d3dd3412e92a37d2f9e0721ea719a9b9e,Person re-identification using multiple first-person-views on wearable devices,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
b1fdd4ae17d82612cefd4e78b690847b071379d3,Supervised Descent Method,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
b1fdd4ae17d82612cefd4e78b690847b071379d3,Supervised Descent Method,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+dddfc10d9649a936cc440c1f3590b14e51a81daa,Bringing Background into the Foreground: Making All Classes Equal in Weakly-Supervised Video Semantic Segmentation,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+dda95e28395324aa87027d9692423b3a6f42dd4a,Improved Multi-Person Tracking with Active Occlusion Handling,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+dd7875abad93418e275825116e029766ada9b9c6,Kinect-based automatic 3D high-resolution face modeling,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+dd173dc349312810ec45ed4b346190ff2250ddd8,PaDNet: Pan-Density Crowd Counting,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+dd609e4bd83cfcdbf64fc794da73a36398076890,Recurrent Human Pose Estimation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+dd609e4bd83cfcdbf64fc794da73a36398076890,Recurrent Human Pose Estimation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+ddf25fe84789821d204fd09026bb02d891d50399,Multi-Shot Human Re-Identification Using Adaptive Fisher Discriminant Analysis,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+dd471f321ead8b405da6194057b2778ef3db7ea7,Multi-Task Adversarial Network for Disentangled Feature Learning,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+dda403e6d9b61e3fa84fafb3aa2f70884d03a944,Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
dd85b6fdc45bf61f2b3d3d92ce5056c47bd8d335,Unsupervised Learning and Segmentation of Complex Activities from Video,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+dda0b381c162695f21b8d1149aab22188b3c2bc0,Occluded Person Re-Identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+dda0b381c162695f21b8d1149aab22188b3c2bc0,Occluded Person Re-Identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+dd7faa9ebacb64bcf4210c3be76202c592e3d637,"Comparison of Visible, Thermal Infra-Red and Range Images for Face Recognition",University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+dd6b6beba7202deb1ceeb241438fdfd48e88b394,Multiple Granularity Descriptors for Fine-Grained Categorization,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
dda35768681f74dafd02a667dac2e6101926a279,Multi-layer temporal graphical model for head pose estimation in real-world videos,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+ddeececa11517bea0d21804e3f724612dac1a5c5,"""Factual"" or ""Emotional"": Stylized Image Captioning with Adaptive Learning and Attention",University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+ddeececa11517bea0d21804e3f724612dac1a5c5,"""Factual"" or ""Emotional"": Stylized Image Captioning with Adaptive Learning and Attention",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+dd0aef0d44e740580212d6efb5286446494729ba,Multi-feature canonical correlation analysis for face photo-sketch image retrieval,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+dd0aef0d44e740580212d6efb5286446494729ba,Multi-feature canonical correlation analysis for face photo-sketch image retrieval,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
dd033d4886f2e687b82d893a2c14dae02962ea70,Facial Expression Recognition Using New Feature Extraction Algorithm,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+dd0be14c30714c77421dfe6cba31ed0b523434ae,Reducing Physical-attractiveness bias in hiring decisions: An experimental investigation,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+ddb49e36570af09d96059b3b6f08f9124aafe24f,A Non-Iterative Approach to Reconstruct Face Templates from Match Scores,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+dd900526f95079e6532a26d0423357bf8ad43afc,Modeling Image Virality with Pairwise Spatial Transformer Networks,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+dd0262d63ab7e2a9ab90478394b9fb56d17ed71c,Triple consistency loss for pairing distributions in GAN-based face synthesis,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+dd30d7e32046c333de78a9380ac6b76f4ce307b0,Probabilistic Siamese Network for Learning Representations,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
ddaa8add8528857712424fd57179e5db6885df7c,Localizing Actions from Video Labels and Pseudo-Annotations,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
ddaa8add8528857712424fd57179e5db6885df7c,Localizing Actions from Video Labels and Pseudo-Annotations,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+dd096d3cac4a9f26d38e135f803621d932c84f83,Hallucinating very low-resolution and obscured face images,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+dda1be806ab56ca58187621a0c2e4d2b8ad429ac,Visual Tracking via Spatially Aligned Correlation Filters Network,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+dcea75410fefbe70a4736fabbf178a951b6743ed,Computer vision based interfaces for computer games,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+dc947dc7a948aa8cb8b82f18c0de8707f6064a7d,"""But You Promised"": Methods to Improve Crowd Engagement In Non-Ground Truth Tasks",Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+dc947dc7a948aa8cb8b82f18c0de8707f6064a7d,"""But You Promised"": Methods to Improve Crowd Engagement In Non-Ground Truth Tasks",Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+dcca36085752eec824d489ed556378159464a0c8,Person Re-identification via Recurrent Feature Aggregation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+dcca36085752eec824d489ed556378159464a0c8,Person Re-identification via Recurrent Feature Aggregation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+dca12da787c023c97058cdb7d56e18ef287084f7,Zebrafish tracking using convolutional neural networks,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
dcf71245addaf66a868221041aabe23c0a074312,S^3FD: Single Shot Scale-Invariant Face Detector,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
dcf71245addaf66a868221041aabe23c0a074312,S^3FD: Single Shot Scale-Invariant Face Detector,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
dcc38db6c885444694f515d683bbb50521ff3990,Learning to Hallucinate Face Images via Component Generation and Enhancement,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
@@ -3252,21 +8884,64 @@ dcc38db6c885444694f515d683bbb50521ff3990,Learning to Hallucinate Face Images via dc5cde7e4554db012d39fc41ac8580f4f6774045,Video Segmentation by Non-Local Consensus voting,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
dc7df544d7c186723d754e2e7b7217d38a12fcf7,Facial expression recognition using salient facial patches,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
dc7df544d7c186723d754e2e7b7217d38a12fcf7,Facial expression recognition using salient facial patches,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
+dc83f97a2dd241bf1a9f53ad11d8f10eeb4f5dd6,Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+dc83f97a2dd241bf1a9f53ad11d8f10eeb4f5dd6,Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+dcb0afca54aa2bde50319ad5720d613a6eca36c3,Deep Pose Consensus Networks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+dcb0afca54aa2bde50319ad5720d613a6eca36c3,Deep Pose Consensus Networks,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
+dc7203d64a985b86f2f44bf064220801ef279382,Multi-scale local Binary Pattern Histogram for Face Recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+dc7203d64a985b86f2f44bf064220801ef279382,Multi-scale local Binary Pattern Histogram for Face Recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
dc77287bb1fcf64358767dc5b5a8a79ed9abaa53,Fashion Conversation Data on Instagram,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+dc81be32ca84d43f99a4c94d4a686c84956d30fd,Visual Question Reasoning on General Dependency Tree,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+dcc1512561b342c003b489f9235c0fca527ac0b0,Cross-Task Contributions of Frontobasal Ganglia Circuitry in Response Inhibition and Conflict-Induced Slowing.,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+dcc1512561b342c003b489f9235c0fca527ac0b0,Cross-Task Contributions of Frontobasal Ganglia Circuitry in Response Inhibition and Conflict-Induced Slowing.,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+dcc1512561b342c003b489f9235c0fca527ac0b0,Cross-Task Contributions of Frontobasal Ganglia Circuitry in Response Inhibition and Conflict-Induced Slowing.,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+dcc1512561b342c003b489f9235c0fca527ac0b0,Cross-Task Contributions of Frontobasal Ganglia Circuitry in Response Inhibition and Conflict-Induced Slowing.,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
dced05d28f353be971ea2c14517e85bc457405f3,Multimodal Priority Verification of Face and Speech Using Momentum Back-Propagation Neural Network,Chung-Ang University,Chung-Ang University,"중앙대학교, 서달로15길, 흑석동, 동작구, 서울특별시, 06981, 대한민국",37.50882000,126.96190000,edu,
+dc22d96593e552700f98dd4bf76ee838f9f11145,A Review of Artificial Intelligence Algorithms Used for Smart Machine Tools,National Chung Hsing University,National Chung Hsing University,"國立中興大學, 145, 興大路, 積善里, 頂橋子頭, 南區, 臺中市, 402, 臺灣",24.12084345,120.67571165,edu,
dce5e0a1f2cdc3d4e0e7ca0507592860599b0454,Facelet-Bank for Fast Portrait Manipulation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+dcda558e15e309d8e3158bf2cf8e921cdb59cf5f,Target Aware Network Adaptation for Efficient Representation Learning,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+dce15becf620afd938818ce5ebd793c798782b70,A New Face Recognition Algorithm based on Dictionary Learning for a Single Training Sample per Person,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
dc9d62087ff93a821e6bb8a15a8ae2da3e39dcdd,Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
dcce3d7e8d59041e84fcdf4418702fb0f8e35043,Probabilistic identity characterization for face recognition,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+dc72dd4690f4373a7dd14223a53ea4cc16bd5210,Framework for Objective Evaluation of Privacy Filters,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
dce3dff9216d63c4a77a2fcb0ec1adf6d2489394,Manifold Learning for Gender Classification from Face Sequences,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+dc3d7128e15ed8d97f9b29021216fc1d4053fbaa,Coarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+dc3d7128e15ed8d97f9b29021216fc1d4053fbaa,Coarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+dc3d7128e15ed8d97f9b29021216fc1d4053fbaa,Coarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+dc16b42a64741df2881604f28788f421e422d297,Cross-view image synthesis using geometry-guided conditional GANs,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+b64c2baf82c51a7538136c32f5193bdfef946297,UA-DETRAC 2017: Report of AVSS2017 & IWT4S Challenge on Advanced Traffic Monitoring,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+b64c2baf82c51a7538136c32f5193bdfef946297,UA-DETRAC 2017: Report of AVSS2017 & IWT4S Challenge on Advanced Traffic Monitoring,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
b6f758be954d34817d4ebaa22b30c63a4b8ddb35,A Proximity-Aware Hierarchical Clustering of Faces,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+b657702aed7aff8f1a86fa32d30a07197f8348c5,Adaptive Contour Fitting for Pose-Invariant 3D Face Shape Reconstruction,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+b6bf15f123a814538fff5db757a474be6fc0c72f,Event-Centric Twitter Photo Summarization,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+b69fbf046faf685655b5fa52fef07fb77e75eff4,Modeling guidance and recognition in categorical search: bridging human and computer object detection.,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+b69fbf046faf685655b5fa52fef07fb77e75eff4,Modeling guidance and recognition in categorical search: bridging human and computer object detection.,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+b69fbf046faf685655b5fa52fef07fb77e75eff4,Modeling guidance and recognition in categorical search: bridging human and computer object detection.,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+b69fbf046faf685655b5fa52fef07fb77e75eff4,Modeling guidance and recognition in categorical search: bridging human and computer object detection.,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+b69fbf046faf685655b5fa52fef07fb77e75eff4,Modeling guidance and recognition in categorical search: bridging human and computer object detection.,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
b62571691a23836b35719fc457e093b0db187956,A Novel approach for securing biometric template,Kurukshetra University,Kurukshetra University,"Kurukshetra University, SH6, Kurukshetra, Haryana, 132118, India",29.95826275,76.81563045,edu,
b62571691a23836b35719fc457e093b0db187956,A Novel approach for securing biometric template,Kurukshetra University,Kurukshetra University,"Kurukshetra University, SH6, Kurukshetra, Haryana, 132118, India",29.95826275,76.81563045,edu,
b69b239217d4e9a20fe4fe1417bf26c94ded9af9,A Temporally-Aware Interpolation Network for Video Frame Inpainting,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
b6052dc718c72f2506cfd9d29422642ecf3992ef,A Survey on Human Motion Analysis from Depth Data,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
b6052dc718c72f2506cfd9d29422642ecf3992ef,A Survey on Human Motion Analysis from Depth Data,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
b6145d3268032da70edc9cfececa1f9ffa4e3f11,Face Recognition Using the Discrete Cosine Transform,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+b68881f3528fc39226ffa44220ddb41a467910b5,A preliminary investigation on the sensitivity of COTS face recognition systems to forensic analyst-style face processing for occlusions,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+b68881f3528fc39226ffa44220ddb41a467910b5,A preliminary investigation on the sensitivity of COTS face recognition systems to forensic analyst-style face processing for occlusions,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+b61a3f8b80bbd44f24544dc915f52fd30bbdf485,"Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+b68e8550eb4be5f36b30b15487a15226729ae379,Extracting biometric binary strings with minimal area under the FRR curve for the hamming distance classifier,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+b61c0b11b1c25958d202b4f7ca772e1d95ee1037,Bridging Category-level and Instance-level Semantic Image Segmentation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+b67fade804ad0ab12e484582190899fea14bc799,Making Better Use of the Crowd,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+b6555e6d52c3c9a7e04bf6debe6a6f476c1c79d5,Rotation Invariant Kernels and Their Application to Shape Analysis,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+b62ffb6a17d75363c8873a236f1d8c49d07c8a0e,An MRF-Poselets Model for Detecting Highly Articulated Humans,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
b6ef158d95042f39765df04373c01546524c9ccd,Im 2 vid : Future Video Prediction for Static Image Action Recognition,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
b68150bfdec373ed8e025f448b7a3485c16e3201,Adversarial Image Perturbation for Privacy Protection A Game Theory Perspective,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+b6810adcfd507b2e019ebc8afe4f44f953faf946,ML-LocNet: Improving Object Localization with Multi-view Learning Network,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+b6810adcfd507b2e019ebc8afe4f44f953faf946,ML-LocNet: Improving Object Localization with Multi-view Learning Network,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+b613ea6c4fb5efdf17af090d64e9bdce41e28711,Where and When to Look? Spatio-temporal Attention for Action Recognition in Videos,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+b613ea6c4fb5efdf17af090d64e9bdce41e28711,Where and When to Look? Spatio-temporal Attention for Action Recognition in Videos,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+b613ea6c4fb5efdf17af090d64e9bdce41e28711,Where and When to Look? Spatio-temporal Attention for Action Recognition in Videos,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+b613ea6c4fb5efdf17af090d64e9bdce41e28711,Where and When to Look? Spatio-temporal Attention for Action Recognition in Videos,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+b603bcd53a045c7c991106423c79d5a2975b3da4,Unpaired Multi-Domain Image Generation via Regularized Conditional GANs,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
b64cfb39840969b1c769e336a05a30e7f9efcd61,CRF-Based Context Modeling for Person Identification in Broadcast Videos,"National Institute of Informatics, Japan","National Institute of Informatics, Japan","2 Chome-1-２ Hitotsubashi, Chiyoda, Tokyo 100-0003, Japan",35.69248530,139.75825330,edu,
b64cfb39840969b1c769e336a05a30e7f9efcd61,CRF-Based Context Modeling for Person Identification in Broadcast Videos,Nagoya University,Nagoya University,"SuperDARN (Hokkaido West), 太辛第1支線林道, 陸別町, 足寄郡, 十勝総合振興局, 北海道, 北海道地方, 日本",43.53750985,143.60768225,edu,
b689d344502419f656d482bd186a5ee6b0140891,Structural resemblance to emotional expressions predicts evaluation of emotionally neutral faces.,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
@@ -3277,25 +8952,92 @@ b689d344502419f656d482bd186a5ee6b0140891,Structural resemblance to emotional exp b6d3caccdcb3fbce45ce1a68bb5643f7e68dadb3,Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
b6d3caccdcb3fbce45ce1a68bb5643f7e68dadb3,Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
b6d0e461535116a675a0354e7da65b2c1d2958d4,Deep Directional Statistics: Pose Estimation with Uncertainty Quantification,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+b6a3802075d460093977f8566c451f950edf7a47,Facilitating and Exploring Planar Homogeneous Texture for Indoor Scene Understanding,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
b6a01cd4572b5f2f3a82732ef07d7296ab0161d3,Kernel-Based Supervised Discrete Hashing for Image Retrieval,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+b6862bb11e7e72f7c2e71de9d8e5aa731f8a0df7,Probabilistic combination of static and dynamic gait features for verification,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+b6d977251b551471f5dddfb0a2e8f9c542e684d2,Recurrent Tubelet Proposal and Recognition Networks for Action Detection,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+b6d977251b551471f5dddfb0a2e8f9c542e684d2,Recurrent Tubelet Proposal and Recognition Networks for Action Detection,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+a9721f9680bb21a0849a912ed24eec9ba50def9e,Benchmarking face tracking,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+a9f652787e5669168c7b8f632c3a343dfbaa6f4b,Mining Spatial and Spatio-Temporal ROIs for Action Recognition,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+a9877bb6c56e32e3c3552e379fca67e5031ccce5,A HIERARCHICAL DYNAMIC MODEL FOR OBJECT RECOGNITION By RAKESH CHALASANI A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+a91c74e3bdbc560653e25fdb02d337a8d20186f4,Multiple Human Tracking in RGB-D Data: A Survey,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+a9e99d6efadcf5d8f67949c5fd4e1f1c024868de,Human Action Recognition in Still Images using Bag of Latent Poselets,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
+a90e6751ae32cb2983891ef2216293311cd6a8e9,Clustering using Ensemble Clustering Technique,Chongqing University,Chongqing University,"重庆工商大学, 19, 翠林路, 重庆市, 重庆市中心, 南岸区 (Nan'an), 重庆市, 400067, 中国",29.50841740,106.57858552,edu,
+a996f22a2d0c685f7e4972df9f45e99efc3cbb76,Towards the Success Rate of One: Real-Time Unconstrained Salient Object Detection,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+a9ab913cd7d2330b93e0cdab3d5fe6cc47d74513,Beyond Flickr: Not All Image Tagging Is Created Equal,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+a9ae68734f2a8116917f75a02dc9c1f432b6c8eb,HUMAN POSE ESTIMATION FROM A SINGLE VIEW POINT by,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+a941a3e8299fb7897fbba7467a52d14e13e7a706,Exploring Human-like Attention Supervision in Visual Question Answering,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+a941a3e8299fb7897fbba7467a52d14e13e7a706,Exploring Human-like Attention Supervision in Visual Question Answering,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+a941a3e8299fb7897fbba7467a52d14e13e7a706,Exploring Human-like Attention Supervision in Visual Question Answering,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+a96b6e645a8d3eb8efc7358a852cbfbaa32ae245,Small Group Detection in Crowds using Interaction Information,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
a9fc23d612e848250d5b675e064dba98f05ad0d9,Face Age Estimation Approach based on Deep Learning and Principle Component Analysis,Benha University,Benha University,"كلية الهندسة بشبرا جامعة بنها, شارع اليازجي, روض الفرج, القاهرة, محافظة القاهرة, 2466, مصر",30.08187270,31.24454841,edu,
a9fc23d612e848250d5b675e064dba98f05ad0d9,Face Age Estimation Approach based on Deep Learning and Principle Component Analysis,Benha University,Benha University,"كلية الهندسة بشبرا جامعة بنها, شارع اليازجي, روض الفرج, القاهرة, محافظة القاهرة, 2466, مصر",30.08187270,31.24454841,edu,
+a910f0468ffaf85aad72c96a7214565945cd2819,Learning Comment Generation by Leveraging User-Generated Data,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+a95c9d51b7fb53cf22cb13a806a780aa1f9d47e1,CNNs for Face Detection and Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+a95c9d51b7fb53cf22cb13a806a780aa1f9d47e1,CNNs for Face Detection and Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+a95c9d51b7fb53cf22cb13a806a780aa1f9d47e1,CNNs for Face Detection and Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+a96c3b0e4ba2949053a9e1e00751b76ef5b05816,Object Recognition with Hidden Attributes,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
a967426ec9b761a989997d6a213d890fc34c5fe3,Relative ranking of facial attractiveness,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+a947448d1db19d99abe6de2f6b6d67804786a8b1,Unsupervised Triplet Hashing for Fast Image Retrieval,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+a94cae786d515d3450d48267e12ca954aab791c4,YawDD: a yawning detection dataset,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
+a9e0e667537c9059b3050a64d22b8fe86787d913,"Detecting and Tracking Vehicles , Pedestrians , and Bicyclists at Intersections with a Stationary Lidar",Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+a9e0e667537c9059b3050a64d22b8fe86787d913,"Detecting and Tracking Vehicles , Pedestrians , and Bicyclists at Intersections with a Stationary Lidar",Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+a9a414604cff39f1a03c5547385dc421e6c8452e,Fully-Convolutional Siamese Networks for Object Tracking,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
a9be20954e9177d8b2bc39747acdea4f5496f394,Event-Specific Image Importance,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+a951f9b3aa95fe53cd9b19e15ebfdbde3fd5af62,Facial electromyographic responses to emotional information from faces and voices in individuals with pervasive developmental disorder.,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
d5afd7b76f1391321a1340a19ba63eec9e0f9833,Statistical Analysis of Human Facial Expressions,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
d5afd7b76f1391321a1340a19ba63eec9e0f9833,Statistical Analysis of Human Facial Expressions,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
d5375f51eeb0c6eff71d6c6ad73e11e9353c1f12,Manifold Ranking-Based Locality Preserving Projections,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+d5607567305b690f914fe8b043f3ca48aed57fc9,A Fast Face Detection Method via Convolutional Neural Network,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
d5d7e89e6210fcbaa52dc277c1e307632cd91dab,DOTA: A Large-scale Dataset for Object Detection in Aerial Images,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
d5d7e89e6210fcbaa52dc277c1e307632cd91dab,DOTA: A Large-scale Dataset for Object Detection in Aerial Images,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+d58f1d2fc5ea941253ff71aac7683fd3909cc71f,A Unified Framework of Subspace and Distance Metric Learning for Face Recognition,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
d5fa9d98c8da54a57abf353767a927d662b7f026,Age Estimation based on Neural Networks using Face Features,"Islamic University of Gaza, Palestine",Islamic University of Gaza - Palestine,"The Islamic University of Gaza, Mostafa Hafez Street, South Remal, محافظة غزة, قطاع غزة, PO BOX 108, الأراضي الفلسطينية",31.51368535,34.44019341,edu,
+d5440779ca69a2f010e57250f53a9be0116305e3,Emotional face expression modulates occipital-frontal effective connectivity during memory formation in a bottom-up fashion,University of Zurich,University of Zurich,"ZHAW, Rosenstrasse, Heiligberg, Altstadt, Winterthur, Bezirk Winterthur, Zürich, 8400, Schweiz/Suisse/Svizzera/Svizra",47.49684760,8.72981767,edu,
+d5440779ca69a2f010e57250f53a9be0116305e3,Emotional face expression modulates occipital-frontal effective connectivity during memory formation in a bottom-up fashion,University of Zurich,University of Zurich,"ZHAW, Rosenstrasse, Heiligberg, Altstadt, Winterthur, Bezirk Winterthur, Zürich, 8400, Schweiz/Suisse/Svizzera/Svizra",47.49684760,8.72981767,edu,
+d5440779ca69a2f010e57250f53a9be0116305e3,Emotional face expression modulates occipital-frontal effective connectivity during memory formation in a bottom-up fashion,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+d5440779ca69a2f010e57250f53a9be0116305e3,Emotional face expression modulates occipital-frontal effective connectivity during memory formation in a bottom-up fashion,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+d5440779ca69a2f010e57250f53a9be0116305e3,Emotional face expression modulates occipital-frontal effective connectivity during memory formation in a bottom-up fashion,University of Zurich,University of Zurich,"ZHAW, Rosenstrasse, Heiligberg, Altstadt, Winterthur, Bezirk Winterthur, Zürich, 8400, Schweiz/Suisse/Svizzera/Svizra",47.49684760,8.72981767,edu,
+d522d63e0e8bdbee314b45085baf40caa08fd6b1,Survey of Hashing Techniques for Compact Bit Representations of Images,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+d517b13f2b152c913b81ce534a149493517dbdad,Big Data Deep Learning: Challenges and Perspectives,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+d517b13f2b152c913b81ce534a149493517dbdad,Big Data Deep Learning: Challenges and Perspectives,Oakland University,Oakland University,"Oakland University, 201, Meadow Brook Road, Rochester Hills, Oakland County, Michigan, 48309-4401, USA",42.66663325,-83.20655752,edu,
+d56c5f0a23ecef2eeaad1b882829d709fa172632,A Temporally-Aware Interpolation Network for Video Frame Inpainting,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+d5795049ff374404231e4d0aaa7725c2afcc73c3,Image-to-Video Person Re-Identification by Reusing Cross-modal Embeddings,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
d5b0e73b584be507198b6665bcddeba92b62e1e5,Multi-Region Ensemble Convolutional Neural Networks for High-Accuracy Age Estimation,Macau University of Science and Technology,Macau University of Science and Technology,"Universidade de Ciência e Tecnologia de Macau 澳門科技大學 Macau University of Science and Technology, 偉龍馬路 Avenida Wai Long, 氹仔Taipa, 氹仔舊城區 Vila de Taipa, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, 澳門 Macau, 853, 中国",22.15263985,113.56803206,edu,
d5b0e73b584be507198b6665bcddeba92b62e1e5,Multi-Region Ensemble Convolutional Neural Networks for High-Accuracy Age Estimation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
d5b0e73b584be507198b6665bcddeba92b62e1e5,Multi-Region Ensemble Convolutional Neural Networks for High-Accuracy Age Estimation,University of Dundee,University of Dundee,"University of Dundee, Park Wynd, Law, Dundee, Dundee City, Scotland, DD1 4HN, UK",56.45796755,-2.98214831,edu,
+d5d472266aae563010e12ae90fe5fe6f3c484cba,Demystifying MMD GANs,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+d5d472266aae563010e12ae90fe5fe6f3c484cba,Demystifying MMD GANs,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+d561f8bb5d09e47348c86b40b5f6e4fe524fed36,Hierarchical Context Modeling Using Incremental Deep Boltzmann Machines,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+d561f8bb5d09e47348c86b40b5f6e4fe524fed36,Hierarchical Context Modeling Using Incremental Deep Boltzmann Machines,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+d589e218cc3f1b10e77d272cca5df3525e06fc95,Multi-View Image Generation from a Single-View,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
+d589e218cc3f1b10e77d272cca5df3525e06fc95,Multi-View Image Generation from a Single-View,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+d5525d00bc2099700711751e33f0fae9a58577ca,Beyond Holistic Object Recognition: Enriching Image Understanding with Part States,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+d58c44bd9b464d9ac1db1344445c31364925f75a,TBN: Convolutional Neural Network with Ternary Inputs and Binary Weights,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+d56b65d0f65afdfdc217c880e9c8fdcafb23bfbe,Face Image Relighting using Locally Constrained Global Optimization,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
d28d32af7ef9889ef9cb877345a90ea85e70f7f1,Local-Global Landmark Confidences for Face Recognition,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
d28d32af7ef9889ef9cb877345a90ea85e70f7f1,Local-Global Landmark Confidences for Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+d26891a7769397bce150a2619ddae1636eae8263,Dynamic Context for Tracking behind Occlusions,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+d2c9f842ed2e36b14b9ea2bb2253159cf5c495ed,Unbiasing Semantic Segmentation For Robot Perception using Synthetic Data Feature Transfer,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+d22a8bac307e1550a9542c3d4e316496b968bf4f,Advancing large scale object retrieval,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
d28d697b578867500632b35b1b19d3d76698f4a9,Face Recognition Using Shape and Texture,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+d29279725abfae6bffb81e59296443f3d5f7a689,Post Processing Pedestrian Detection with Background Cues,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+d23ec100432d860b12308941f8539af82a28843f,Adversarial Semantic Scene Completion from a Single Depth Image,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
d29eec5e047560627c16803029d2eb8a4e61da75,Feature Transfer Learning for Deep Face Recognition with Long-Tail Data,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+d2d5d61dfdae1c6492d15eae5f0f37f460ba4030,Non-rigid object tracking in video sequences,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+d2d5d61dfdae1c6492d15eae5f0f37f460ba4030,Non-rigid object tracking in video sequences,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
d280bcbb387b1d548173917ae82cb6944e3ceca6,Facial grid transformation: A novel face registration approach for improving facial action unit recognition,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
+d22dd4a6752a5ffa40aebd260ff63d2c2a9e1da1,Pose Invariant 3D Face Reconstruction,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
+d22dd4a6752a5ffa40aebd260ff63d2c2a9e1da1,Pose Invariant 3D Face Reconstruction,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
+d20efdf05444a9d7509b85f6d5cd59359b1062f2,First Person Action Recognition,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+d291569f332a216e2a12238a117d747b0f4ba880,Semantic Part Segmentation with Deep Learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+d23bf3200adece389d6e7c866ca9105d999b23fa,Skill Assessment using Computer Vision based Analysis,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+d23bf3200adece389d6e7c866ca9105d999b23fa,Skill Assessment using Computer Vision based Analysis,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+d23bf3200adece389d6e7c866ca9105d999b23fa,Skill Assessment using Computer Vision based Analysis,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+d2336dbae3916135bc26dd064514441ea94a8a2b,Pairwise Kernels for Human Interaction Recognition,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+d2044b92486248f87bafe937779cd2167efe170c,"Connecting Deep Neural Networks to Physical, Perceptual, and Electrophysiological Auditory Signals",University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+d2044b92486248f87bafe937779cd2167efe170c,"Connecting Deep Neural Networks to Physical, Perceptual, and Electrophysiological Auditory Signals",Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+d2b2cb1d5cc1aa30cf5be7bcb0494198934caabb,A Restricted Visual Turing Test for Deep Scene and Event Understanding,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
d26b443f87df76034ff0fa9c5de9779152753f0c,A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
d2cd9a7f19600370bce3ea29aba97d949fe0ceb9,Separability Oriented Preprocessing for Illumination-Insensitive Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
d2cd9a7f19600370bce3ea29aba97d949fe0ceb9,Separability Oriented Preprocessing for Illumination-Insensitive Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
@@ -3306,6 +9048,10 @@ aac39ca161dfc52aade063901f02f56d01a1693c,The Analysis of Parameters t and k of L aadf4b077880ae5eee5dd298ab9e79a1b0114555,Using Hankel matrices for dynamics-based facial emotion recognition and pain detection,University of Palermo,DICGIM - University of Palermo,"Edificio 8, Viale delle Scienze, 90128 Palermo PA, Italy",38.10427160,13.34723540,edu,
aa127e6b2dc0aaccfb85e93e8b557f83ebee816b,Advancing human pose and gesture recognition,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
aa127e6b2dc0aaccfb85e93e8b557f83ebee816b,Advancing human pose and gesture recognition,Wolfson College,Wolfson College,"Wolfson College, Linton Road, Norham Manor, Oxford, Oxon, South East, England, OX2 6UD, UK",51.77110760,-1.25361700,edu,
+aabe235a028a4d533053d78034f85bea39690d4f,Active Learning with Cross-Class Similarity Transfer,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+aabe235a028a4d533053d78034f85bea39690d4f,Active Learning with Cross-Class Similarity Transfer,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+aa299218f9b7cda78c440117f12f193c3c4a86cb,Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+aacd2fefca976b963701669a77808fde973c1d02,Landmark classification in large-scale image collections,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
aa8ef6ba6587c8a771ec4f91a0dd9099e96f6d52,Improved face tracking thanks to local features correspondence,University of Brescia,University of Brescia,"Brescia University, West 7th Street, Owensboro, Daviess County, Kentucky, 42303, USA",37.76893740,-87.11138590,edu,
aab3561acbd19f7397cbae39dd34b3be33220309,Quantization Mimic: Towards Very Tiny CNN for Object Detection,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
aab3561acbd19f7397cbae39dd34b3be33220309,Quantization Mimic: Towards Very Tiny CNN for Object Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
@@ -3313,101 +9059,315 @@ aab3561acbd19f7397cbae39dd34b3be33220309,Quantization Mimic: Towards Very Tiny C aab3561acbd19f7397cbae39dd34b3be33220309,Quantization Mimic: Towards Very Tiny CNN for Object Detection,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
aa912375eaf50439bec23de615aa8a31a3395ad3,Implementation of a New Methodology to Reduce the Effects of Changes of Illumination in Face Recognition-based Authentication,Howard University,Howard University,"Howard University, College Street Northwest, Howard University, Washington, D.C., 20001, USA",38.92152500,-77.01953566,edu,
aa912375eaf50439bec23de615aa8a31a3395ad3,Implementation of a New Methodology to Reduce the Effects of Changes of Illumination in Face Recognition-based Authentication,Howard University,Howard University,"Howard University, College Street Northwest, Howard University, Washington, D.C., 20001, USA",38.92152500,-77.01953566,edu,
+aa4928142b99224e96536d402ef8869b8391cf79,Fusing Individual Algorithms and Humans Improves Face Recognition Accuracy,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+aa4928142b99224e96536d402ef8869b8391cf79,Fusing Individual Algorithms and Humans Improves Face Recognition Accuracy,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
aaeb8b634bb96a372b972f63ec1dc4db62e7b62a,Facial Expression Recognition System: A Digital Printing Application,Jadavpur University,Jadavpur University,"Jadavpur University, Chingrighata Flyover, Basani Devi Colony, Kolkata, Hāora, West Bengal, 700098, India",22.56115370,88.41310194,edu,
aaeb8b634bb96a372b972f63ec1dc4db62e7b62a,Facial Expression Recognition System: A Digital Printing Application,Jadavpur University,Jadavpur University,"Jadavpur University, Chingrighata Flyover, Basani Devi Colony, Kolkata, Hāora, West Bengal, 700098, India",22.56115370,88.41310194,edu,
+aaa29212a3f9e6a35f78600231a690b4a3c83fd5,Distributional Learning of Appearance,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+aadc142d4e216432899326c7162540955f8b5590,Middle-Out Decoding,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+aadc142d4e216432899326c7162540955f8b5590,Middle-Out Decoding,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
aa0c30bd923774add6e2f27ac74acd197b9110f2,Dynamic Probabilistic Linear Discriminant Analysis for video classification,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
aa0c30bd923774add6e2f27ac74acd197b9110f2,Dynamic Probabilistic Linear Discriminant Analysis for video classification,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
aa0c30bd923774add6e2f27ac74acd197b9110f2,Dynamic Probabilistic Linear Discriminant Analysis for video classification,Middlesex University,Middlesex University,"Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK",51.59029705,-0.22963221,edu,
aa0c30bd923774add6e2f27ac74acd197b9110f2,Dynamic Probabilistic Linear Discriminant Analysis for video classification,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
aac934f2eed758d4a27562dae4e9c5415ff4cdb7,TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity Recognition,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+aa2ddae22760249729ac2c2c4e24c8b665bcd40e,Interpretable Basis Decomposition for Visual Explanation,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+aaf4d938f2e66d158d5e635a9c1d279cdc7639c0,Toward visual understanding of everyday object,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+aa7e7637f3443a823ee799a560ab84103b0e9a7f,Autonomous Driving in Reality with Reinforcement Learning and Image Translation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+aa54d0ac723c1a45e31df69433a72f6dc711706a,Robust 3D Face Recognition Using Learned Visual Codebook,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
aa3c9de34ef140ec812be85bb8844922c35eba47,Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
aff92784567095ee526a705e21be4f42226bbaab,Face recognition in uncontrolled environments,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
aff8705fb2f2ae460cb3980b47f2e85c2e6dd41a,Attributes in Multiple Facial Images,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+af3d8552d31843136acc8eae994842c0cd5262b5,Deep Dual Pyramid Network for Barcode Segmentation using Barcode-30k Database,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+af3d8552d31843136acc8eae994842c0cd5262b5,Deep Dual Pyramid Network for Barcode Segmentation using Barcode-30k Database,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+afe987d36438efaa2b5116c444b5fc47462f11d9,SALL-E: Situated Agent for Language Learning,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+af2531b3834b92275a3353e4b2426217ddc4a839,Probabilistic multiple face detection and tracking using entropy measures,University of Thessaloniki,University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+af2531b3834b92275a3353e4b2426217ddc4a839,Probabilistic multiple face detection and tracking using entropy measures,University of Thessaloniki,University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
af13c355a2a14bb74847aedeafe990db3fc9cbd4,Happy and agreeable?: multi-label classification of impressions in social video,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
af13c355a2a14bb74847aedeafe990db3fc9cbd4,Happy and agreeable?: multi-label classification of impressions in social video,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+af2c7b9adbf898b251d3d5d0659fd21fcd0197ba,Contextual Combination of Appearance and Motion for Intersection Videos with Vehicles and Pedestrians,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+afb3bc6854003c7cc9e94cb16d62ef353b5a6569,Human layout estimation using structured output learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
afdf9a3464c3b015f040982750f6b41c048706f5,A Recurrent Encoder-Decoder Network for Sequential Face Alignment,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
afdf9a3464c3b015f040982750f6b41c048706f5,A Recurrent Encoder-Decoder Network for Sequential Face Alignment,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+af370cbe392b7fb2b9f26476a7e063e0f4c46815,Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+af370cbe392b7fb2b9f26476a7e063e0f4c46815,Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
afe9cfba90d4b1dbd7db1cf60faf91f24d12b286,Principal Directions of Synthetic Exact Filters for Robust Real-Time Eye Localization,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
afa84ff62c9f5b5c280de2996b69ad9fa48b7bc3,Two-Stream Flow-Guided Convolutional Attention Networks for Action Recognition,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+af58701bdd28a49d234ba87d8f1b90d1f001184e,Part-based pose estimation with local and non-local contextual information,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+af7cab9b4a2a2a565a3efe0a226c517f47289077,Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+af7cab9b4a2a2a565a3efe0a226c517f47289077,Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+af6c3c4826137ef638ded6ea1664e14a53d23798,Crowdsourcing Question-Answer Meaning Representations,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
af278274e4bda66f38fd296cfa5c07804fbc26ee,A Novel Maximum Entropy Markov Model for Human Facial Expression Recognition,SungKyunKwan University,SungKyunKwan University,"성균관대, 덕영대로, 천천동, 장안구, 수원시, 경기, 16357, 대한민국",37.30031270,126.97212300,edu,
af278274e4bda66f38fd296cfa5c07804fbc26ee,A Novel Maximum Entropy Markov Model for Human Facial Expression Recognition,Kyung Hee University,Kyung Hee University,"Kyung Hee Tae Kwon Do, Vons 2370 Truck Service Ramp, University City, San Diego, San Diego County, California, 92122, USA",32.85363330,-117.20352860,edu,
+afd492a598476b5a9b13e2b6d28a76b0707c0a35,Open-set Person Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+af1a6c35f5d75122756d37faed062d5b5cd6bc71,Emotion Modelling and Facial Affect Recognition in Human-Computer and Human-Robot Interaction,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
+afde6c95ca696de65599a27590b31112a3eb6f6d,A Framework for Sign Language Recognition using Support Vector Machines and Active Learning for Skin Segmentation and Boosted Temporal Sub-units,Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
+afb3a84b7daa92d6e1894f5fefe9b38904976d7d,Generative adversarial network-based image super-resolution using perceptual content losses,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+af1eab707e690e73a5b9073ed07a0436fd4e0b66,Adult Content Recognition from Images Using a Mixture of Convolutional Neural Networks,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+af1eab707e690e73a5b9073ed07a0436fd4e0b66,Adult Content Recognition from Images Using a Mixture of Convolutional Neural Networks,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+af1eab707e690e73a5b9073ed07a0436fd4e0b66,Adult Content Recognition from Images Using a Mixture of Convolutional Neural Networks,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+af386bb1b5e8c9f65b3ae836198a93aa860d6331,Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
af654a7ec15168b16382bd604889ea07a967dac6,Face recognition committee machine,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+b76d6bb7aef87d03b6de039f01d3dba9224834b6,Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
b7426836ca364603ccab0e533891d8ac54cf2429,A Review on Human Activity Recognition Using Vision-Based Method,Ocean University of China,Ocean University of China,"中国海洋大学, 238, 松岭路 Sōnglǐng Road, 朱家洼, 崂山区 (Laoshan), 青岛市, 山东省, 266100, 中国",36.16161795,120.49355276,edu,
b7426836ca364603ccab0e533891d8ac54cf2429,A Review on Human Activity Recognition Using Vision-Based Method,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+b73ba189d0d1a3e2502716fee60c6865a7964d6e,Towards Open-Universe Image Parsing with Broad Coverage,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+b73ba189d0d1a3e2502716fee60c6865a7964d6e,Towards Open-Universe Image Parsing with Broad Coverage,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
b73795963dc623a634d218d29e4a5b74dfbc79f1,Identity Preserving Face Completion for Large Ocular Region Occlusion,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
b73795963dc623a634d218d29e4a5b74dfbc79f1,Identity Preserving Face Completion for Large Ocular Region Occlusion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
b73795963dc623a634d218d29e4a5b74dfbc79f1,Identity Preserving Face Completion for Large Ocular Region Occlusion,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
b750b3d8c34d4e57ecdafcd5ae8a15d7fa50bc24,Unified Solution to Nonnegative Data Factorization Problems,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
b750b3d8c34d4e57ecdafcd5ae8a15d7fa50bc24,Unified Solution to Nonnegative Data Factorization Problems,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+b787113305ddef424def20920b8b098c7f18bd98,Sensor-Based Detection Approach for Passenger Flow Safety in Chinese High-speed Railway Transport Hub,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+b787113305ddef424def20920b8b098c7f18bd98,Sensor-Based Detection Approach for Passenger Flow Safety in Chinese High-speed Railway Transport Hub,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+b769007cb6931464168f63ebb4571e46d8c804b7,Human Pose Estimation and Activity Classification Using Convolutional Neural Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+b769007cb6931464168f63ebb4571e46d8c804b7,Human Pose Estimation and Activity Classification Using Convolutional Neural Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+b7676adde75c6d1bcabf56c7e2f7fa484155e8a8,ChaLearn Looking at People Challenge 2014: Dataset and Results,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+b7676adde75c6d1bcabf56c7e2f7fa484155e8a8,ChaLearn Looking at People Challenge 2014: Dataset and Results,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+b7bc85b4f6a186e01365dd42993029ea06909c8f,"Pedestrian Detection, Tracking and Re-Identification for Search in Visual Surveillance Data",Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+b755e80ce1985fc300e1983adefc8f14830702c4,"Totally Looks Like - How Humans Compare, Compared to Machines",York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+b7b421be7c1dcbb8d41edb11180ba6ec87511976,A Deep Face Identification Network Enhanced by Facial Attributes Prediction,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
b7820f3d0f43c2ce613ebb6c3d16eb893c84cf89,Visual Data Synthesis via GAN for Zero-Shot Video Classification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+b78e611c32dc0daf762cfa93044558cdb545d857,Temporal Action Detection with Structured Segment Networks Supplementary Materials,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+b76ddd8e9098c4b361ef72ddaef42bf3c85f5825,Finding Coherent Motions and Semantic Regions in Crowd Scenes: A Diffusion and Clustering Approach,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
b7c5f885114186284c51e863b58292583047a8b4,GAdaBoost: Accelerating Adaboost Feature Selection with Genetic Algorithms,American University in Cairo,The American University in Cairo,"الجامعة الأمريكية بالقاهرة, شارع القصر العينى, القاهرة القديمة, جاردن سيتي, القاهرة, محافظة القاهرة, 11582, مصر",30.04287695,31.23664139,edu,
+b7c8452ac9791563d9a739bd079b05e518b20aea,Web Video in Numbers - An Analysis of Web-Video Metadata,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+b73d82be8270db40577b002789a26e4a226df1ef,Lessons Learned in Multilingual Grounded Language Learning,University of Copenhagen,University of Copenhagen,"Københavns Universitet, Krystalgade, Kødbyen, Vesterbro, København, Københavns Kommune, Region Hovedstaden, 1165, Danmark",55.68015020,12.57232700,edu,
+b7407b2ea67b8c82246f013f4966c4cac1507e60,Object Detection via End-to-End Integration of Aspect Ratio and Context Aware Part-based Models and Fully Convolutional Networks,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+b7407b2ea67b8c82246f013f4966c4cac1507e60,Object Detection via End-to-End Integration of Aspect Ratio and Context Aware Part-based Models and Fully Convolutional Networks,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
b73d9e1af36aabb81353f29c40ecdcbdf731dbed,Head Pose Estimation on Top of Haar-Like Face Detection: A Study Using the Kinect Sensor,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
+b7cff2a6fb3861f36bc779984b312ebae9f1f365,On Learning Associations of Faces and Voices,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+b72c72e2c3d140c3064eae3aff17e0c0c177c963,3D-Aware Scene Manipulation via Inverse Graphics,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+b72c72e2c3d140c3064eae3aff17e0c0c177c963,3D-Aware Scene Manipulation via Inverse Graphics,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+b72c72e2c3d140c3064eae3aff17e0c0c177c963,3D-Aware Scene Manipulation via Inverse Graphics,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+b72c72e2c3d140c3064eae3aff17e0c0c177c963,3D-Aware Scene Manipulation via Inverse Graphics,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+b72c72e2c3d140c3064eae3aff17e0c0c177c963,3D-Aware Scene Manipulation via Inverse Graphics,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+b72c72e2c3d140c3064eae3aff17e0c0c177c963,3D-Aware Scene Manipulation via Inverse Graphics,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+b72c72e2c3d140c3064eae3aff17e0c0c177c963,3D-Aware Scene Manipulation via Inverse Graphics,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+b711d50a6c467f3db266f2199a9031f7391b184f,Deep Multi-Modal Image Correspondence Learning,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+b711d50a6c467f3db266f2199a9031f7391b184f,Deep Multi-Modal Image Correspondence Learning,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+b7a9fa746f22aa543c1e682554a834329b17d1c2,A Person Re-Identification System for Mobile Devices,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+b75c93c70e8534553006c084ddc72de39517ded4,Learnable Pooling Regions for Image Classification,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+b75c93c70e8534553006c084ddc72de39517ded4,Learnable Pooling Regions for Image Classification,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
db848c3c32464d12da33b2f4c3a29fe293fc35d1,Pose Guided Human Video Generation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+dbb202b5dc073a2284044b4903a6057ac54c034f,Semi-Supervised Ground-to-Aerial Adaptation with Heterogeneous Features Learning for Scene Classification,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+dbd98092268bf3ebf8c63b2b40bdd01872358fa2,Deep Adversarial Subspace Clustering,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
db1f48a7e11174d4a724a4edb3a0f1571d649670,Joint Constrained Clustering and Feature Learning based on Deep Neural Networks,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
db1f48a7e11174d4a724a4edb3a0f1571d649670,Joint Constrained Clustering and Feature Learning based on Deep Neural Networks,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+dbbdb23bb2512ef0922c5396cb95f713257b6ac8,Infinite-Label Learning with Semantic Output Codes,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+dbbdb23bb2512ef0922c5396cb95f713257b6ac8,Infinite-Label Learning with Semantic Output Codes,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+dbbdb23bb2512ef0922c5396cb95f713257b6ac8,Infinite-Label Learning with Semantic Output Codes,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+dbbdb23bb2512ef0922c5396cb95f713257b6ac8,Infinite-Label Learning with Semantic Output Codes,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
dbb16032dd8f19bdfd045a1fc0fc51f29c70f70a,Deep Face Recognition,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+dbda7c3a09ada41ad45f6dfa1aa803e2a87ddbcd,From what we perceive to what we remember: Characterizing representational dynamics of visual memorability,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+dbda7c3a09ada41ad45f6dfa1aa803e2a87ddbcd,From what we perceive to what we remember: Characterizing representational dynamics of visual memorability,McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
+dbda7c3a09ada41ad45f6dfa1aa803e2a87ddbcd,From what we perceive to what we remember: Characterizing representational dynamics of visual memorability,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+db0a4af734dab1854c2e8dfe499fe0e353226e45,Hot Anchors: A Heuristic Anchors Sampling Method in RCNN-Based Object Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+db0a4af734dab1854c2e8dfe499fe0e353226e45,Hot Anchors: A Heuristic Anchors Sampling Method in RCNN-Based Object Detection,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+dbd3b57b942cb860207c377ac41d777f51ceabfa,An Inverse Kinematic Mathematical Model Using Groebner Basis Theory for Arm Swing Movement in the Gait Cycle,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+dbbfb8ab9355d00ec3b2a9be12747e2e20458bb5,Data Analysis Project : Using Knowledge Graphs for Image Classification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+dbc749490275db26337c7e3201027e8cef8e371c,Multi-band Gradient Component Pattern (MGCP): A New Statistical Feature for Face Recognition,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
db5a00984fa54b9d2a1caad0067a9ff0d0489517,Supplementary Material for Multi-Task Adversarial Network for Disentangled Feature Learning,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
dbd958ffedc3eae8032be67599ec281310c05630,Automated Restyling of Human Portrait Based on Facial Expression Recognition and 3 D Reconstruction,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
dbed26cc6d818b3679e46677abc9fa8e04e8c6a6,A Hierarchical Generative Model for Eye Image Synthesis and Eye Gaze Estimation,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
db3545a983ffd24c97c18bf7f068783102548ad7,Enriching the Student Model in an Intelligent Tutoring System,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
db3545a983ffd24c97c18bf7f068783102548ad7,Enriching the Student Model in an Intelligent Tutoring System,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
+db84c6fd771a073023f2b42e48a68eb2d9d31e4a,A Deep Variational Autoencoder Approach for Robust Facial Symmetrization,Shandong University of Science and Technology,Shandong University of Science and Technology,"山东科技大学, 579, 前湾港路, 牛王庙, 北下庄, 黄岛区 (Huangdao), 青岛市, 山东省, 266500, 中国",36.00146435,120.11624057,edu,
+db84c6fd771a073023f2b42e48a68eb2d9d31e4a,A Deep Variational Autoencoder Approach for Robust Facial Symmetrization,Ocean University of China,Ocean University of China,"中国海洋大学, 238, 松岭路 Sōnglǐng Road, 朱家洼, 崂山区 (Laoshan), 青岛市, 山东省, 266100, 中国",36.16161795,120.49355276,edu,
dba493caf6647214c8c58967a8251641c2bda4c2,Automatic 3D Facial Expression Editing in Videos,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
+db49a5e6d73de616c66904138a8a19ce0a329c4d,Learning Multiple Categories on Deep Convolution Networks,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+dbcab35c43c78411da8ceba4bdebe69f79308568,Social Style Characterization from Egocentric Photo-streams,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+dbcab35c43c78411da8ceba4bdebe69f79308568,Social Style Characterization from Egocentric Photo-streams,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
db36e682501582d1c7b903422993cf8d70bb0b42,Deep Trans-layer Unsupervised Networks for Representation Learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
db36e682501582d1c7b903422993cf8d70bb0b42,Deep Trans-layer Unsupervised Networks for Representation Learning,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+db299ad09f629a0fcd45b74fa567da476d83a4f3,Dilated Residual Networks,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+db299ad09f629a0fcd45b74fa567da476d83a4f3,Dilated Residual Networks,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+dbf6d2619bd41ce4c36488e15d114a2da31b51c9,Data-Driven Modeling of Group Entitativity in Virtual Environments,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+dbf6d2619bd41ce4c36488e15d114a2da31b51c9,Data-Driven Modeling of Group Entitativity in Virtual Environments,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+dbf6d2619bd41ce4c36488e15d114a2da31b51c9,Data-Driven Modeling of Group Entitativity in Virtual Environments,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+dbf6d2619bd41ce4c36488e15d114a2da31b51c9,Data-Driven Modeling of Group Entitativity in Virtual Environments,University of North Carolina,University of North Carolina,"University of North Carolina, Emergency Room Drive, Chapel Hill, Orange County, North Carolina, 27599, USA",35.90503535,-79.04775327,edu,
+dbf6d2619bd41ce4c36488e15d114a2da31b51c9,Data-Driven Modeling of Group Entitativity in Virtual Environments,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
dbe0e533d715f8543bcf197f3b8e5cffa969dfc0,"A Comprehensive Comparative Performance Analysis of Eigenfaces, Laplacianfaces and Orthogonal Laplacianfaces for Face Recognition",Amity University,Amity University,"Amity University, Faizabad Road, Uttardhauna, Gomti Nagar, Tiwariganj, Lucknow, Uttar Pradesh, 226010, India",26.85095965,81.04950965,edu,
dbe0e533d715f8543bcf197f3b8e5cffa969dfc0,"A Comprehensive Comparative Performance Analysis of Eigenfaces, Laplacianfaces and Orthogonal Laplacianfaces for Face Recognition",Amity University,Amity University,"Amity University, Faizabad Road, Uttardhauna, Gomti Nagar, Tiwariganj, Lucknow, Uttar Pradesh, 226010, India",26.85095965,81.04950965,edu,
+db056590e54d7be16fb1c96deb9e94914ea9f838,Awareness of Road Scene Participants for Autonomous Driving,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+db3ce18f318ee732dab2e2f574062c94f7398943,"Image Semantic Transformation: Faster, Lighter and Stronger",Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+db6344e4f8a41c619573c8579595612a7cdfb080,Research on Face Recognition based on Wavelet Transformation and Improved Sparse Representation,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+db3acf0653d6e69887d184c7ebb1958f74a4d0b1,Weighting Deep and Classic Representation via l 2 Regularization for Image Classification,University of Macau,University of Macau,"研究生宿舍 Residência de Estudantes de Pós-Graduação da Universidade de Macau, 澳門大學 Universidade de Macau, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, Universidade de Macau em Ilha de Montanha 澳門大學橫琴校區, 中国",22.12401870,113.54510901,edu,
+db3acf0653d6e69887d184c7ebb1958f74a4d0b1,Weighting Deep and Classic Representation via l 2 Regularization for Image Classification,University of Macau,University of Macau,"研究生宿舍 Residência de Estudantes de Pós-Graduação da Universidade de Macau, 澳門大學 Universidade de Macau, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, Universidade de Macau em Ilha de Montanha 澳門大學橫琴校區, 中国",22.12401870,113.54510901,edu,
+db3acf0653d6e69887d184c7ebb1958f74a4d0b1,Weighting Deep and Classic Representation via l 2 Regularization for Image Classification,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+db3acf0653d6e69887d184c7ebb1958f74a4d0b1,Weighting Deep and Classic Representation via l 2 Regularization for Image Classification,Jiangsu University,Jiangsu University,"江苏大学, 301, 学府路, 京口区, 象山街道, 京口区 (Jingkou), 镇江市 / Zhenjiang, 江苏省, 212013, 中国",32.20302965,119.50968362,edu,
+dbede5113e4e91a3a26058e8b7253438a1df04c9,Online Dictionary Learning for Approximate Archetypal Analysis,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+db640eddc51258cf6b11e442745d9a4bd5d6995b,Simple Baselines for Human Pose Estimation and Tracking,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
db82f9101f64d396a86fc2bd05b352e433d88d02,A Spatio-Temporal Probabilistic Framework for Dividing and Predicting Facial Action Units,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
db428d03e3dfd98624c23e0462817ad17ef14493,Oxford Trecvid 2006 – Notebook Paper 1 High-level Feature Extraction 1.1 Bag of Visual Word Representation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+a8068de468ae9e1d6ebf021433467a449703acae,"Deep, Dense, and Low-Rank Gaussian Conditional Random Fields",University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+a8d665fa7357f696dcfd188b91fda88da47b964e,Scaling Video Analytics Systems to Large Camera Deployments,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+a8d665fa7357f696dcfd188b91fda88da47b964e,Scaling Video Analytics Systems to Large Camera Deployments,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+a8d665fa7357f696dcfd188b91fda88da47b964e,Scaling Video Analytics Systems to Large Camera Deployments,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+a8fa12c662447903fbb751eaa967f861ea33abff,"Finding People Using Scale, Rotation and Articulation Invariant Matching",Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
+a838a1184cb9ca86ae910509bb318266101ae656,Question Relevance in Visual Question Answering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a838a1184cb9ca86ae910509bb318266101ae656,Question Relevance in Visual Question Answering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a838a1184cb9ca86ae910509bb318266101ae656,Question Relevance in Visual Question Answering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a826646a8e4e8a746111d3a6915c8f0fcfcc3a00,Scheduling multithreaded applications onto heterogeneous composite cores architecture,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+a84c039818d2abeba21f792c0522e9f75582518e,Prototypical Priors: From Improving Classification to Zero-Shot Learning,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+a8b63bede77e752ead39453838a8ab66aed7b970,The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+a8b63bede77e752ead39453838a8ab66aed7b970,The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+a8b63bede77e752ead39453838a8ab66aed7b970,The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+a8b63bede77e752ead39453838a8ab66aed7b970,The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+a80355dcee5156b064e31b39c6b72037044ed87c,L-Tree: A Local-Area-Learning-Based Tree Induction Algorithm for Image Classification,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
a896ddeb0d253739c9aaef7fc1f170a2ba8407d3,SSH: Single Stage Headless Face Detector,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+a825680aeb853fc34c65b5844c4c4391148f18c3,SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again,Toyota Research Institute,Toyota Research Institute,"Toyota Research Institute, 4440, West El Camino Real, Los Altos, Santa Clara County, California, 94022, USA",37.40253645,-122.11655107,edu,
a820941eaf03077d68536732a4d5f28d94b5864a,Leveraging Datasets with Varying Annotations for Face Alignment via Deep Regression Network,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
a820941eaf03077d68536732a4d5f28d94b5864a,Leveraging Datasets with Varying Annotations for Face Alignment via Deep Regression Network,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+a86ea8041bcc91097a8bbb450cb94a616ee85ae6,Diverse and Coherent Paragraph Generation from Images,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+a87bc818f7409ac97c8719aa8fae2c40d214ebbc,Deep Computational Phenotyping,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
a8035ca71af8cc68b3e0ac9190a89fed50c92332,IIIT-CFW: A Benchmark Database of Cartoon Faces in the Wild,Indian Institute of Technology Sri City,"IIIT Chittoor, Sri City, India","630 Gnan Marg, Sri City, Andhra Pradesh 517646, India",13.55681710,80.02612830,edu,
+a89e1fc2681a9a399cc5008ea34b5ec3fe7ca845,Improving Fast Segmentation With Teacher-Student Learning,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+a89e1fc2681a9a399cc5008ea34b5ec3fe7ca845,Improving Fast Segmentation With Teacher-Student Learning,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
a803453edd2b4a85b29da74dcc551b3c53ff17f9,Pose Invariant Face Recognition Under Arbitrary Illumination Based on 3D Face Reconstruction,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
a8d52265649c16f95af71d6f548c15afc85ac905,Situation Recognition with Graph Neural Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
a8583e80a455507a0f146143abeb35e769d25e4e,A Distance-accuracy Hybrid Weighted Voting Scheme for Partial Face Recognition,Feng Chia University,Feng Chia University,"逢甲大學, 100, 文華路, 西平里, 西屯區, 臺中市, 40724, 臺灣",24.18005755,120.64836072,edu,
a8583e80a455507a0f146143abeb35e769d25e4e,A Distance-accuracy Hybrid Weighted Voting Scheme for Partial Face Recognition,National Chiao Tung University,National Chiao Tung University,"NCTU;交大;交通大學;交大光復校區;交通大學光復校區, 1001, 大學路, 光明里, 赤土崎, 東區, 新竹市, 30010, 臺灣",24.78676765,120.99724412,edu,
+a8896fa513ff0587e2e8dea0f3ef585d4d04feff,Production-level facial performance capture using deep convolutional neural networks,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+a8896fa513ff0587e2e8dea0f3ef585d4d04feff,Production-level facial performance capture using deep convolutional neural networks,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+a8896fa513ff0587e2e8dea0f3ef585d4d04feff,Production-level facial performance capture using deep convolutional neural networks,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+a8896fa513ff0587e2e8dea0f3ef585d4d04feff,Production-level facial performance capture using deep convolutional neural networks,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
a87e37d43d4c47bef8992ace408de0f872739efc,A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
a87e37d43d4c47bef8992ace408de0f872739efc,A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+a8ef9a39e68bbc7f6f25a8155cab52aab6708886,Generative Compression,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
a8c8a96b78e7b8e0d4a4a422fcb083e53ad06531,3D Human Action Recognition using Hu Moment Invariants and Euclidean Distance Classifier,University of Arkansas at Little Rock,University of Arkansas at Little Rock,"University of Arkansas At Little Rock (UALR), 2801, U A L R Campus Drive, Little Rock, Pulaski County, Arkansas, 72204, USA",34.72236805,-92.33830255,edu,
a8c8a96b78e7b8e0d4a4a422fcb083e53ad06531,3D Human Action Recognition using Hu Moment Invariants and Euclidean Distance Classifier,University of Arkansas at Little Rock,University of Arkansas at Little Rock,"University of Arkansas At Little Rock (UALR), 2801, U A L R Campus Drive, Little Rock, Pulaski County, Arkansas, 72204, USA",34.72236805,-92.33830255,edu,
a8c8a96b78e7b8e0d4a4a422fcb083e53ad06531,3D Human Action Recognition using Hu Moment Invariants and Euclidean Distance Classifier,University of Arkansas at Little Rock,University of Arkansas at Little Rock,"University of Arkansas At Little Rock (UALR), 2801, U A L R Campus Drive, Little Rock, Pulaski County, Arkansas, 72204, USA",34.72236805,-92.33830255,edu,
+a84934a2db769b7523399c8eaf6d2d7582415c5c,Convolutional Pose Machines: A Deep Architecture for Estimating Articulated Poses,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a84934a2db769b7523399c8eaf6d2d7582415c5c,Convolutional Pose Machines: A Deep Architecture for Estimating Articulated Poses,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a89eae439dfa7cb727bd5193a5130ae6afcd42e8,On Recognizing Actions in Still Images via Multiple Features,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+a89eae439dfa7cb727bd5193a5130ae6afcd42e8,On Recognizing Actions in Still Images via Multiple Features,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
+a84f80ca4e29b49cab1035ed8c7877caf2dbe914,Effects of Facial Symmetry and Gaze Direction on Perception of Social Attributes: A Study in Experimental Art History,University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+a84f80ca4e29b49cab1035ed8c7877caf2dbe914,Effects of Facial Symmetry and Gaze Direction on Perception of Social Attributes: A Study in Experimental Art History,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
a8748a79e8d37e395354ba7a8b3038468cb37e1f,Seeing the Forest from the Trees: A Holistic Approach to Near-Infrared Heterogeneous Face Recognition,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
a8748a79e8d37e395354ba7a8b3038468cb37e1f,Seeing the Forest from the Trees: A Holistic Approach to Near-Infrared Heterogeneous Face Recognition,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
a8a61badec9b8bc01f002a06e1426a623456d121,Joint Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+a8682d432865a9417b30a482b462a9e07c66c0d7,Matching Pixels using Co-Occurrence Statistics,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+a8682d432865a9417b30a482b462a9e07c66c0d7,Matching Pixels using Co-Occurrence Statistics,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+a8682d432865a9417b30a482b462a9e07c66c0d7,Matching Pixels using Co-Occurrence Statistics,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+a8123a4e68642b602b5094f2f670ed7aefdd2f58,Online Video Object Detection Using Association LSTM,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
a8154d043f187c6640cb6aedeaa8385a323e46cf,Image Retrieval with Mixed Initiative and Multimodal Feedback,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+a8e2b2b1b76491336036005d81be57d256acdd0c,Fusing subcategory probabilities for texture classification,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
a812368fe1d4a186322bf72a6d07e1cf60067234,Gaussian processes for modeling of facial expressions,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
de7f5e4ccc2f38e0c8f3f72a930ae1c43e0fdcf0,Merge or Not? Learning to Group Faces via Imitation Learning,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
de7f5e4ccc2f38e0c8f3f72a930ae1c43e0fdcf0,Merge or Not? Learning to Group Faces via Imitation Learning,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
de7f5e4ccc2f38e0c8f3f72a930ae1c43e0fdcf0,Merge or Not? Learning to Group Faces via Imitation Learning,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
de7f5e4ccc2f38e0c8f3f72a930ae1c43e0fdcf0,Merge or Not? Learning to Group Faces via Imitation Learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
de8381903c579a4fed609dff3e52a1dc51154951,Shape and Appearance Based Analysis of Facial Images for Assessing ICAO Compliance,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+de46cbf18c7da9efc9368241463919e22230b0b0,What We Have Learned about Autism Spectrum Disorder from Valproic Acid,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+dedc7b080b8e13d72f8dc33e248e7637d191fdbf,Beyond Dataset Bias: Multi-task Unaligned Shared Knowledge Transfer,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+dedc7b080b8e13d72f8dc33e248e7637d191fdbf,Beyond Dataset Bias: Multi-task Unaligned Shared Knowledge Transfer,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+de0cfd94d16468cdaaa0fe725e214930587ed8ce,Scalable Person Re-identification on Supervised Smoothed Manifold,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+de2e8127105a37ff1f59be13a010ab0d3f4fa650,Analyzing Hands with First-person Computer Vision,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
def569db592ed1715ae509644444c3feda06a536,Discovery and usage of joint attention in images,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
def569db592ed1715ae509644444c3feda06a536,Discovery and usage of joint attention in images,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
def569db592ed1715ae509644444c3feda06a536,Discovery and usage of joint attention in images,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
def569db592ed1715ae509644444c3feda06a536,Discovery and usage of joint attention in images,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
+de3245c795bc50ebdb5d929c8da664341238264a,Generative Model With Coordinate Metric Learning for Object Recognition Based on 3D Models,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+decc4de8b6964ba473744741c3a46ac37f2d6e3e,A Pose Invariant 3 D Face Recognition Method,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
+de8a01d36df1c3a881523c3748fcfa988710fa15,Physical adversarial examples for semantic image segmentation,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+de8303e9206096dd9f4ba9d876057345ff1f164a,Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+de8303e9206096dd9f4ba9d876057345ff1f164a,Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+de8303e9206096dd9f4ba9d876057345ff1f164a,Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+de92ac27693598254554531d8cadfd4728c423a1,Online Multi-object Tracking Using CNN-Based Single Object Tracker with Spatial-Temporal Attention Mechanism,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+de92ac27693598254554531d8cadfd4728c423a1,Online Multi-object Tracking Using CNN-Based Single Object Tracker with Spatial-Temporal Attention Mechanism,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+defbca385b48173d3dbd7bb8b8fbd35ba06239c3,Motion-Appearance Co-Memory Networks for Video Question Answering,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+def2983576001bac7d6461d78451159800938112,The Do’s and Don’ts for CNN-Based Face Verification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
de15af84b1257211a11889b6c2adf0a2bcf59b42,Anomaly detection in non-stationary and distributed environments,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
de15af84b1257211a11889b6c2adf0a2bcf59b42,Anomaly detection in non-stationary and distributed environments,Institute for Communication Systems,Institute for Communication Systems,"Institute for Communication Systems, Spine Road, Woodbridge Hill, Guildford, Surrey, South East, England, GU2 7XS, UK",51.24336920,-0.59322090,edu,
de15af84b1257211a11889b6c2adf0a2bcf59b42,Anomaly detection in non-stationary and distributed environments,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
de3285da34df0262a4548574c2383c51387a24bf,Two-Stream Convolutional Networks for Dynamic Texture Synthesis,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
-dec0c26855da90876c405e9fd42830c3051c2f5f,Supplementary Material: Learning Compositional Visual Concepts with Mutual Consistency,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
-dec0c26855da90876c405e9fd42830c3051c2f5f,Supplementary Material: Learning Compositional Visual Concepts with Mutual Consistency,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+de0c4459c46c5efbad02cd9a1f4687a12883c5d7,Pedestrian Detection and Tracking in Urban Context Using a Mono-Camera,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
+de725093e13cdc90209d981bea69730c7f6ee03d,A Sparse Coding Based Transfer Learning Framework for Pedestrian Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+de725093e13cdc90209d981bea69730c7f6ee03d,A Sparse Coding Based Transfer Learning Framework for Pedestrian Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+dec0c26855da90876c405e9fd42830c3051c2f5f,Supplementary Material : Learning Compositional Visual Concepts with Mutual Consistency,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+dec0c26855da90876c405e9fd42830c3051c2f5f,Supplementary Material : Learning Compositional Visual Concepts with Mutual Consistency,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+ded2eaddaf214e63aae6be34f4f319df0a10c13e,Gender Classification of Consumer Face Images using Gabor Filters,University of Gujrat,University of Gujrat,"University of Gujrat, University Road, Chandhar, Gujrāt District, پنجاب, 50700, پاکستان",32.63744845,74.16174558,edu,
+deb78e302c2efdac51b742f4d3e8041b5838e533,Learning to Evaluate Image Captioning,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+deae19c928571d3c1101660b0d643d7a7ee893b2,Improved Human Parsing with a Full Relational Model,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+b0c66e95b5eb36471bcdcdaad7d9368556110109,Fuzzy Rule Based Quality Measures for Adaptive Multimodal Biometric Fusion at Operation Time,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+b0c66e95b5eb36471bcdcdaad7d9368556110109,Fuzzy Rule Based Quality Measures for Adaptive Multimodal Biometric Fusion at Operation Time,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+b06254f76e13d5f6ac0230fd8bdac35b901f9480,Parameterizing Region Covariance: An Efficient Way To Apply Sparse Codes On Second Order Statistics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+b06254f76e13d5f6ac0230fd8bdac35b901f9480,Parameterizing Region Covariance: An Efficient Way To Apply Sparse Codes On Second Order Statistics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+b06254f76e13d5f6ac0230fd8bdac35b901f9480,Parameterizing Region Covariance: An Efficient Way To Apply Sparse Codes On Second Order Statistics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+b06254f76e13d5f6ac0230fd8bdac35b901f9480,Parameterizing Region Covariance: An Efficient Way To Apply Sparse Codes On Second Order Statistics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
b03b4d8b4190361ed2de66fcbb6fda0c9a0a7d89,Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action Recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
b03b4d8b4190361ed2de66fcbb6fda0c9a0a7d89,Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action Recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+b0bf1be8731c60b2caf3a27f1e95b73875c4220b,Submission to Moments in Time Challenge 2018,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+b0bf1be8731c60b2caf3a27f1e95b73875c4220b,Submission to Moments in Time Challenge 2018,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+b0bf1be8731c60b2caf3a27f1e95b73875c4220b,Submission to Moments in Time Challenge 2018,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+b0bf1be8731c60b2caf3a27f1e95b73875c4220b,Submission to Moments in Time Challenge 2018,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+b0c820c6996b9cf9798d778a46860d28f1beae64,Dynamics Analysis of Facial Expressions for Person Identification,Keio University,Keio University,"綱島市民の森, けつわり坂, 港北区, 横浜市, 神奈川県, 関東地方, 223-0053, 日本",35.54169690,139.63471840,edu,
+b0a1f562a55aae189d6a5cb826582b2e7fb06d3c,Multi-modal Mean-Fields via Cardinality-Based Clamping,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+b0b07732a9ab9b2b9d9dba41e1b9811629fa43dc,An Efficient Vision-Based Pedestrian Detection and Tracking System for ITS Applications,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+b0b07732a9ab9b2b9d9dba41e1b9811629fa43dc,An Efficient Vision-Based Pedestrian Detection and Tracking System for ITS Applications,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
+b05633a18a48d9c18735fd0a186a2654297ae543,Development of holistic vs. featural processing in face recognition,Bournemouth University,Bournemouth University,"Bournemouth University, BU footpaths, Poole, South West England, England, BH10 4HX, UK",50.74223495,-1.89433739,edu,
+b04d06b737bc8e9543d5ac6a1afa33aaeb3619c0,A pr 2 01 4 Robust and Efficient Subspace Segmentation via Least Squares Regression,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+b04d06b737bc8e9543d5ac6a1afa33aaeb3619c0,A pr 2 01 4 Robust and Efficient Subspace Segmentation via Least Squares Regression,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+b04d06b737bc8e9543d5ac6a1afa33aaeb3619c0,A pr 2 01 4 Robust and Efficient Subspace Segmentation via Least Squares Regression,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+b04d06b737bc8e9543d5ac6a1afa33aaeb3619c0,A pr 2 01 4 Robust and Efficient Subspace Segmentation via Least Squares Regression,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+b06f2949eb748331c40a8b2381517fa09757ad17,Illumination Normalization in Face Recognition Using DCT and Supporting Vector Machine (SVM),National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+b06f2949eb748331c40a8b2381517fa09757ad17,Illumination Normalization in Face Recognition Using DCT and Supporting Vector Machine (SVM),National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
b013cce42dd769db754a57351d49b7410b8e82ad,Automatic point-based facial trait judgments evaluation,Universitat Oberta de Catalunya,Universitat Oberta de Catalunya,"Universitat Oberta de Catalunya, 156, Rambla del Poblenou, Provençals del Poblenou, Sant Martí, Barcelona, BCN, CAT, 08018, España",41.40657415,2.19453410,edu,
b013cce42dd769db754a57351d49b7410b8e82ad,Automatic point-based facial trait judgments evaluation,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
b017963d83b3edf71e1673d7ffdec13a6d350a87,View Independent Face Detection Based on Combination of Local and Global Kernels,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
+b01ed5c62abdc37c7318c155e12e366238bdc2f5,Multimodal Dual Attention Memory for Video Story Question Answering,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+b0abf048d97a7beffc75fec1480d9bfe04a838a7,Learning Robust Representations for Computer Vision,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+b0abf048d97a7beffc75fec1480d9bfe04a838a7,Learning Robust Representations for Computer Vision,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+b06b960293b1c7744580e03539713c9fd83c0b63,Distributed Submodular Cover: Succinctly Summarizing Massive Data,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+b0724a7b4b63d58e249379b889656a899455e0c2,Easy Identification from Better Constraints : Multi-Shot Person Re-Identification from Reference Constraints,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
b084683e5bab9b2bc327788e7b9a8e049d5fff8f,Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+b099dfc5c823be79f9ca96168263c40d0020b92e,Co-Training for Demographic Classification Using Deep Learning from Label Proportions,Illinois Institute of Technology,Illinois Institute of Technology,"Illinois Institute of Technology, South State Street, Bronzeville, Chicago, Cook County, Illinois, 60616, USA",41.83619630,-87.62655913,edu,
+b099dfc5c823be79f9ca96168263c40d0020b92e,Co-Training for Demographic Classification Using Deep Learning from Label Proportions,Illinois Institute of Technology,Illinois Institute of Technology,"Illinois Institute of Technology, South State Street, Bronzeville, Chicago, Cook County, Illinois, 60616, USA",41.83619630,-87.62655913,edu,
b03446a2de01126e6a06eb5d526df277fa36099f,A Torch Library for Action Recognition and Detection Using CNNs and LSTMs,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
b018fa5cb9793e260b8844ae155bd06380988584,Project STAR IST - 2000 - 28764 Deliverable D 6 . 3 Enhanced face and arm / hand detector,Katholieke Universiteit Leuven,Katholieke Universiteit Leuven,"Laboratorium voor Bos, natuur en landschap, 102, Vital Decosterstraat, Sint-Maartensdal, Leuven, Vlaams-Brabant, Vlaanderen, 3000, België / Belgique / Belgien",50.88306860,4.70195030,edu,
+b05faf0ae510cbd7510a6242aafdda7de3088282,Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+b05faf0ae510cbd7510a6242aafdda7de3088282,Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+b05faf0ae510cbd7510a6242aafdda7de3088282,Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+b0a96954377390e80de59f0063e5703a21391eb3,Emotionally Representative Image Discovery for Social Events,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+b082f440ee91e2751701401919584203b37e1e1a,SeedNet : Automatic Seed Generation with Deep Reinforcement Learning for Robust Interactive Segmentation,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+b051715249e47fa7e987e1a5504830af0521c38c,Sentribute: image sentiment analysis from a mid-level perspective,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+b051715249e47fa7e987e1a5504830af0521c38c,Sentribute: image sentiment analysis from a mid-level perspective,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+b051715249e47fa7e987e1a5504830af0521c38c,Sentribute: image sentiment analysis from a mid-level perspective,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+b051715249e47fa7e987e1a5504830af0521c38c,Sentribute: image sentiment analysis from a mid-level perspective,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+b0b4ce1962ad6732965aa7f4b3dd1bfd32f0ae5c,A Database of Morphed Facial Expressions of Emotions,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+b0d61c3e9851bb83cda8bc079e92d73a43e479bc,A Thin Shell Approach to the Registration of Implicit Surfaces,University of Vienna,University of Vienna,"Uni Wien, 1, Universitätsring, Schottenviertel, KG Innere Stadt, Innere Stadt, Wien, 1010, Österreich",48.21313020,16.36068653,edu,
+b0d61c3e9851bb83cda8bc079e92d73a43e479bc,A Thin Shell Approach to the Registration of Implicit Surfaces,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
a6f81619158d9caeaa0863738ab400b9ba2d77c2,Face Recognition using Convolutional Neural Network and Simple Logistic Classifier,K.N. Toosi University of Technology,K.N. Toosi University of Technology,"دانشکده مهندسی عمران و نقشه برداری, ولی عصر, کاووسیه, منطقه ۳ شهر تهران, تجریش, بخش رودبارقصران, شهرستان شمیرانات, استان تهران, 1968653111, ایران",35.76427925,51.40970276,edu,
+a67da2dd79c01e8cc4029ecc5a05b97967403862,On Selecting Helpful Unlabeled Data for Improving Semi-Supervised Support Vector Machines,Myongji University,Myongji University,"명지대, 금학로, 역북동, 처인구, 용인시, 경기, 17144, 대한민국",37.23810230,127.19034310,edu,
+a6ac6463b5c89ac9eb013c978f213b309cc6a5c7,iSPA-Net: Iterative Semantic Pose Alignment Network,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+a6ac6463b5c89ac9eb013c978f213b309cc6a5c7,iSPA-Net: Iterative Semantic Pose Alignment Network,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+a6ac6463b5c89ac9eb013c978f213b309cc6a5c7,iSPA-Net: Iterative Semantic Pose Alignment Network,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+a6ac6463b5c89ac9eb013c978f213b309cc6a5c7,iSPA-Net: Iterative Semantic Pose Alignment Network,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
a6d7cf29f333ea3d2aeac67cde39a73898e270b7,Gender Classification from Facial Images Using Texture Descriptors,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
a6d7cf29f333ea3d2aeac67cde39a73898e270b7,Gender Classification from Facial Images Using Texture Descriptors,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
a6d7cf29f333ea3d2aeac67cde39a73898e270b7,Gender Classification from Facial Images Using Texture Descriptors,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
+a6f4d114dae7664a5161a21fc2bdc76c86a2d69b,A 2D Human Body Model Dressed in Eigen Clothing,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
a611c978e05d7feab01fb8a37737996ad6e88bd9,Benchmarking 3D Pose Estimation for Face Recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+a63104ad235f98bc5ee0b44fefbcdb49e32c205a,Has My Algorithm Succeeded? An Evaluator for Human Pose Estimators,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+a63104ad235f98bc5ee0b44fefbcdb49e32c205a,Has My Algorithm Succeeded? An Evaluator for Human Pose Estimators,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+a62bcfa204fca20acc7b90aaac01b55d315fc971,Automatically Learning the Objective Function for Model Fitting,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+a6582fda1ddd10c210e367119e01dfbec4a65b16,Implementing a Robust Explanatory Bias in a Person Re-identification Network,Naval Research Laboratory,Naval Research Laboratory,"Naval Research Laboratory Post Office, 4555, Overlook Avenue Southwest, Washington, D.C., 20375, USA",38.82313810,-77.01789020,mil,
+a6582fda1ddd10c210e367119e01dfbec4a65b16,Implementing a Robust Explanatory Bias in a Person Re-identification Network,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+a6582fda1ddd10c210e367119e01dfbec4a65b16,Implementing a Robust Explanatory Bias in a Person Re-identification Network,Naval Research Laboratory,Naval Research Laboratory,"Naval Research Laboratory Post Office, 4555, Overlook Avenue Southwest, Washington, D.C., 20375, USA",38.82313810,-77.01789020,mil,
a6e8a8bb99e30a9e80dbf80c46495cf798066105,Ranking Generative Adversarial Networks: Subjective Control over Semantic Image Attributes,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+a663e729cb44cd02eda2d2a08d9117839dc67ca1,Deep Generative Models with Learnable Knowledge Constraints,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
a6ffe238eaf8632b4a8a6f718c8917e7f3261546,Dynamic facial prosthetics for sufferers of facial paralysis.,Nottingham Trent University,Nottingham Trent University,"Nottingham Trent University, Waverley Terrace, Lace Market, The Park, City of Nottingham, East Midlands, England, NG1 5JD, UK",52.95773220,-1.15617099,edu,
a6ffe238eaf8632b4a8a6f718c8917e7f3261546,Dynamic facial prosthetics for sufferers of facial paralysis.,Nottingham University Hospital,Nottingham University Hospital,"Nottingham University Hospital, Central Route, Dunkirk, Wollaton, City of Nottingham, East Midlands, England, NG7 2UH, UK",52.94349670,-1.18631123,edu,
a6ffe238eaf8632b4a8a6f718c8917e7f3261546,Dynamic facial prosthetics for sufferers of facial paralysis.,Nottingham Trent University,Nottingham Trent University,"Nottingham Trent University, Waverley Terrace, Lace Market, The Park, City of Nottingham, East Midlands, England, NG1 5JD, UK",52.95773220,-1.15617099,edu,
+a60540a8407fd117fd8e6857d4728e661f53dcc8,Deep Domain Generalization via Conditional Invariant Adversarial Networks,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+a60540a8407fd117fd8e6857d4728e661f53dcc8,Deep Domain Generalization via Conditional Invariant Adversarial Networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a60540a8407fd117fd8e6857d4728e661f53dcc8,Deep Domain Generalization via Conditional Invariant Adversarial Networks,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+a60540a8407fd117fd8e6857d4728e661f53dcc8,Deep Domain Generalization via Conditional Invariant Adversarial Networks,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+a6e039f0b4f586c2014e42c36ea173e249636f28,Fusion of Depth and Vision Information for Human Detection ⋆,Donghua University,Donghua University,"东华大学, 新华路, 长宁区, 上海市, 210011, 中国",31.20619390,121.41047101,edu,
+a6e039f0b4f586c2014e42c36ea173e249636f28,Fusion of Depth and Vision Information for Human Detection ⋆,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+a62cbd84251d325ea9e91642a9b37f3026cd3e20,Domain Transfer Through Deep Activation Matching,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+a62cbd84251d325ea9e91642a9b37f3026cd3e20,Domain Transfer Through Deep Activation Matching,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
a660390654498dff2470667b64ea656668c98ecc,Facial expression recognition based on graph-preserving sparse non-negative matrix factorization,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
a660390654498dff2470667b64ea656668c98ecc,Facial expression recognition based on graph-preserving sparse non-negative matrix factorization,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
a60907b7ee346b567972074e3e03c82f64d7ea30,Head Motion Signatures from Egocentric Videos,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
@@ -3417,281 +9377,924 @@ a6496553fb9ab9ca5d69eb45af1bdf0b60ed86dc,Semi-supervised Neighborhood Preserving a6b5ffb5b406abfda2509cae66cdcf56b4bb3837,One Shot Similarity Metric Learning for Action Recognition,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
a6b5ffb5b406abfda2509cae66cdcf56b4bb3837,One Shot Similarity Metric Learning for Action Recognition,Open University,The Open University,"The Open University, East Lane, Walton, Monkston, Milton Keynes, South East, England, MK7 6AE, UK",52.02453775,-0.70927481,edu,
a6b5ffb5b406abfda2509cae66cdcf56b4bb3837,One Shot Similarity Metric Learning for Action Recognition,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+a6bc69831dea3efc5804b8ab65cf5a06688ddae0,Crossing Generative Adversarial Networks for Cross-View Person Re-identification,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+a6bc69831dea3efc5804b8ab65cf5a06688ddae0,Crossing Generative Adversarial Networks for Cross-View Person Re-identification,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+a68c07cb446f63fa6b48eda04c93392219c09700,Averted eye-gaze disrupts configural face encoding,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
a6e25cab2251a8ded43c44b28a87f4c62e3a548a,Let's Dance: Learning From Online Dance Videos,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
a6270914cf5f60627a1332bcc3f5951c9eea3be0,Joint Attention in Driver-Pedestrian Interaction: from Theory to Practice,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+a6c40d0fb4c0420d1d974f9fbfae83da514ebfbe,Individual and group tracking with the evaluation of social interactions,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+a6e43499f0884b4ec4d69460b798021b6e2ae73e,Spatial Bag of Features Learning for Large Scale Face Image Retrieval,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+a6b2c5c527557cc86ae2ce4332b18a7850ee4e1e,Exploring the Spatial Hierarchy of Mixture Models for Human Pose Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a6b2c5c527557cc86ae2ce4332b18a7850ee4e1e,Exploring the Spatial Hierarchy of Mixture Models for Human Pose Estimation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+a624f18087e663dbdbf176de45b863cc59bb2bb8,Aesthetic Evaluation of Facial Portraits Using Compositional Augmentation for Deep CNNs,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
a6b1d79bc334c74cde199e26a7ef4c189e9acd46,Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
a6b1d79bc334c74cde199e26a7ef4c189e9acd46,Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+a6bbd477851c5642a67817e43302d22bc4a95aaf,Density-Adaptive Kernel based Re-Ranking for Person Re-Identification,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+a6bd679c8a9346a39a003f536f36b7f77c0e09df,Enhanced Pavlovian Aversive Conditioning to Positive Emotional Stimuli,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+a6bd679c8a9346a39a003f536f36b7f77c0e09df,Enhanced Pavlovian Aversive Conditioning to Positive Emotional Stimuli,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
a6e21438695dbc3a184d33b6cf5064ddf655a9ba,PKU-MMD: A Large Scale Benchmark for Continuous Multi-Modal Human Action Understanding,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+b9bed097cb806ba48cd0245ab50d1a123022eafc,Living a discrete life in a continuous world: Reference in cross-modal entity tracking,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
+b9bed097cb806ba48cd0245ab50d1a123022eafc,Living a discrete life in a continuous world: Reference in cross-modal entity tracking,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+b984c9815fd556cc845adae1f9a206d2a0fa2d33,Hierarchical Relational Networks for Group Activity Recognition and Retrieval,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+b959d5655a3b2f92c2c1a8a7896fecafafea979d,Ambientgan: Generative Models from Lossy Measurements,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+b959d5655a3b2f92c2c1a8a7896fecafafea979d,Ambientgan: Generative Models from Lossy Measurements,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+b959d5655a3b2f92c2c1a8a7896fecafafea979d,Ambientgan: Generative Models from Lossy Measurements,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+b9e6f9e22134d4b5ac66fbf2ec7b7b702c6f4eb7,MASON: A Model AgnoStic ObjectNess Framework,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
b9081856963ceb78dcb44ac410c6fca0533676a3,UntrimmedNets for Weakly Supervised Action Recognition and Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+b986a535e45751cef684a30631a74476e911a749,Improved Person Re-Identification Based on Saliency and Semantic Parsing with Deep Neural Network Models,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
+b97a155bdd86491c8d32f02d6dfe5b73aaef4549,Eliminating the mere exposure effect through changes in context between exposure and test.,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+b97a155bdd86491c8d32f02d6dfe5b73aaef4549,Eliminating the mere exposure effect through changes in context between exposure and test.,University of Plymouth,University of Plymouth,"Charles Seale-Hayne Library, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37525010,-4.13927692,edu,
+b94ec9abc3009cfcd1e45647926b4e5084d95136,Classifying Unseen Instances by Learning Class-Independent Similarity Functions,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+b9d73e86a98e93d558366fc3dd002393677808a3,Adversarial Scene Editing: Automatic Object Removal from Weak Supervision,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+b92f984f328851a5572e38ee816ebdcc515f2a0a,Deep Learning Based Surveillance System for Open Critical Areas,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+b907537c602b95948da809f7d4aff4bc959d8ba1,Superhuman Accuracy on the SNEMI3D Connectomics Challenge,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+b907537c602b95948da809f7d4aff4bc959d8ba1,Superhuman Accuracy on the SNEMI3D Connectomics Challenge,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
b93bf0a7e449cfd0db91a83284d9eba25a6094d8,Supplementary Material for : Active Pictorial Structures,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
b9c9c7ef82f31614c4b9226e92ab45de4394c5f6,Face Recognition under Varying Illumination,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+b9054aadbbb91f74d373cc82d70b7c513e47139c,Visual Decoding of Targets During Visual Search From Human Eye Fixations,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+b9054aadbbb91f74d373cc82d70b7c513e47139c,Visual Decoding of Targets During Visual Search From Human Eye Fixations,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+b9054aadbbb91f74d373cc82d70b7c513e47139c,Visual Decoding of Targets During Visual Search From Human Eye Fixations,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+b9eb55c2c573e2fffd686b00a39185f0142ef816,The participation payoff: challenges and opportunities for multimedia access in networked communities,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+b9eb55c2c573e2fffd686b00a39185f0142ef816,The participation payoff: challenges and opportunities for multimedia access in networked communities,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+b9262301b11a4d41c8346626a86b603cd2e63992,A Survey of Major Techniques of Clothing in Vision ⋆,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
a1af7ec84472afba0451b431dfdb59be323e35b7,LikeNet: A Siamese Motion Estimation Network Trained in an Unsupervised Way,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+a1f0188029436169002d75af8f23f7ebdad969dd,"Operational Automatic Remote Sensing Image Understanding Systems: Beyond Geographic Object-Based and Object-Oriented Image Analysis (GEOBIA/GEOOIA). Part 2: Novel system Architecture, Information/Knowledge Representation, Algorithm Design and Implementation",University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
a1dd806b8f4f418d01960e22fb950fe7a56c18f1,Interactively building a discriminative vocabulary of nameable attributes,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+a1f9ef1236ddb57efc1ebbd87a1a69db9bc38c4b,Neuroanatomical and neurofunctional markers of social cognition in autism spectrum disorder.,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
+a1d6c9a03075848014e9bd9baa6edda25e512963,A Fully Convolutional Tri-Branch Network (FCTN) for Domain Adaptation,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+a1c1970f7c728cc96aea798d65d38df7c9ea61dc,Eye Location Using Genetic Algorithm,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+a1fdf45e6649b0020eb533c70d6062b9183561ff,Where's YOUR focus: Personalized Attention,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+a1fdf45e6649b0020eb533c70d6062b9183561ff,Where's YOUR focus: Personalized Attention,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+a165619977bc69a910a771e1096551073122775b,Computational Crowd Camera : Enabling Remote - Vision via Sparse Collective Plenoptic Sampling,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
a14db48785d41cd57d4eac75949a6b79fc684e70,Fast High Dimensional Vector Multiplication Face Recognition,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
a14db48785d41cd57d4eac75949a6b79fc684e70,Fast High Dimensional Vector Multiplication Face Recognition,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
a14db48785d41cd57d4eac75949a6b79fc684e70,Fast High Dimensional Vector Multiplication Face Recognition,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
a14db48785d41cd57d4eac75949a6b79fc684e70,Fast High Dimensional Vector Multiplication Face Recognition,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+a1ee55d529e04a80f4eae3b30d0961a985a64fa4,Enabling low bitrate mobile visual recognition: a performance versus bandwidth evaluation,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
a1b7bb2a4970b7c479aff3324cc7773c1daf3fc1,Longitudinal Study of Child Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
a1b7bb2a4970b7c479aff3324cc7773c1daf3fc1,Longitudinal Study of Child Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+a155fcf9063a7a33368488123578180a0d1a5a78,An Autonomous Indoor Navigation System Based on Visual Scene Recognition Using Deep Neural Networks,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+a1b6aed0b998f0e6e049fcc209287c8b2801d054,An Expression Deformation Approach to Non-rigid 3D Face Recognition,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+a1a49e2c1a424ef2dc6a5cf787d5eadf8421aaa1,Human Body Segmentation based on Background Estimation in Modified HLS Color Space,Dankook University,Dankook University,"단국대학교 치과병원, 죽전로, 죽전동, 수지구, 용인시, 경기, 16900, 대한민국",37.32195750,127.12507230,edu,
a14ed872503a2f03d2b59e049fd6b4d61ab4d6ca,Attentional Pooling for Action Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a1b89c488a723cc496cf931d97e2538ecf9b2991,Low Resolution Face Recognition in Surveillance Systems,Curtin University,Curtin University,"Curtin University, Brand Drive, Waterford, Perth, Western Australia, 6102, Australia",-32.00686365,115.89691775,edu,
a125bc55bdf4bec7484111eea9ae537be314ec62,Real-time Facial Expression Recognition in Image Sequences Using an AdaBoost-based Multi-classifier,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
a125bc55bdf4bec7484111eea9ae537be314ec62,Real-time Facial Expression Recognition in Image Sequences Using an AdaBoost-based Multi-classifier,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
+a1497db913ea4031315e24a1027177ad0c4b680a,Robust emotion recognition from low quality and low bit rate video: A deep learning approach,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+a1497db913ea4031315e24a1027177ad0c4b680a,Robust emotion recognition from low quality and low bit rate video: A deep learning approach,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
+a1497db913ea4031315e24a1027177ad0c4b680a,Robust emotion recognition from low quality and low bit rate video: A deep learning approach,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+a1497db913ea4031315e24a1027177ad0c4b680a,Robust emotion recognition from low quality and low bit rate video: A deep learning approach,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+a1dd88f44d045b360569a9a8721f728afbd951c3,Relief Impression Image Detection : Unsupervised Extracting Objects Directly From Feature Arrangements of Deep CNN,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+a1e1e7e976c22af9de26d9b74c2ece282e20218c,Looking at My Own Face: Visual Processing Strategies in Self–Other Face Recognition,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+a19904e76b5ded44e6aeb9af85997d160de6bb22,TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+a1bbe8b9eab55cdf58746fbf790eeaf626878615,Deep Poselets for Human Detection,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+a1be53dead395b2d83a4009bec76729fce95af83,Tree Identification from Images,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+a1653e88be986aee2f37792c3fb05f0ee7fbef94,Generative Semantic Manipulation with Mask-Contrasting GAN,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+a1653e88be986aee2f37792c3fb05f0ee7fbef94,Generative Semantic Manipulation with Mask-Contrasting GAN,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+a1ffab629c19b9c04fb047dae0471d3de73f3738,Leveraging Unlabeled Data for Crowd Counting by Learning to Rank,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+a1557a512ff254a27c11810d362609c237ff6e30,Predicting Images using Convolutional Networks : Visual Scene Understanding with Pixel Maps,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
a1ee0176a9c71863d812fe012b5c6b9c15f9aa8a,Affective recommender systems: the role of emotions in recommender systems,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
a1ee0176a9c71863d812fe012b5c6b9c15f9aa8a,Affective recommender systems: the role of emotions in recommender systems,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
a1ee0176a9c71863d812fe012b5c6b9c15f9aa8a,Affective recommender systems: the role of emotions in recommender systems,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
a1dd9038b1e1e59c9d564e252d3e14705872fdec,Attributes as Operators: Factorizing Unseen Attribute-Object Compositions,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
a16fb74ea66025d1f346045fda00bd287c20af0e,A Coupled Evolutionary Network for Age Estimation,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+effa69fab7c4fdb30265a4bb404f869d327ae326,Recognizing Human Actions by Their Pose,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+ef3b777cbe362a5e97c5ef27eb3289ebfdb70b53,Improving Reinforcement Learning Based Image Captioning with Natural Language Prior,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
efd28eabebb9815e34031316624e7f095c7dfcfe,Combining Face with Face-Part Detectors under Gaussian Assumption,University of Salzburg,University of Salzburg,"Universität Salzburg - Unipark, 1, Erzabt-Klotz-Straße, Nonntal, Salzburg, 5020, Österreich",47.79475945,13.05417525,edu,
eff87ecafed67cc6fc4f661cb077fed5440994bb,Evaluation of Expression Recognition Techniques,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
eff87ecafed67cc6fc4f661cb077fed5440994bb,Evaluation of Expression Recognition Techniques,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+efa2aacb0fbee857015fad1dba72767f56be6f39,Aggregating Crowdsourced Image Segmentations,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+efa2aacb0fbee857015fad1dba72767f56be6f39,Aggregating Crowdsourced Image Segmentations,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
+efa2aacb0fbee857015fad1dba72767f56be6f39,Aggregating Crowdsourced Image Segmentations,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+efc7a620e21abbc882d5a26f0e7a78ae6960be20,Feed-back Method Based on Image Processing for Detecting Human Body Via,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
ef458499c3856a6e9cd4738b3e97bef010786adb,Learning Type-Aware Embeddings for Fashion Compatibility,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
ef2a5a26448636570986d5cda8376da83d96ef87,Recurrent Neural Networks and Transfer Learning for Action Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
ef2a5a26448636570986d5cda8376da83d96ef87,Recurrent Neural Networks and Transfer Learning for Action Recognition,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+ef29e5515b9ae3af358e511a7faa8cdc69bd073b,Neural bases for impaired social cognition in schizophrenia and autism spectrum disorders.,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+ef2e36daf429899bb48d80ce6804731c3f99bb85,"Debnath, Banerjee, Namboodiri: Adapting Ransac-svm to Detect Outliers for Robust Classification",Indian Institute of Technology Kanpur,Indian Institute of Technology Kanpur,"Indian Institute of Technology Kanpur, 4th Avenue, Panki, Kanpur, Kanpur Nagar, Uttar Pradesh, 208016, India",26.51318800,80.23651945,edu,
ef8de1bd92e9ee9d0d2dee73095d4d348dc54a98,Fine-grained Activity Recognition with Holistic and Pose based Features,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
ef8de1bd92e9ee9d0d2dee73095d4d348dc54a98,Fine-grained Activity Recognition with Holistic and Pose based Features,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+c391478faa3a8903678a7bbc4ab17c8f9601e273,Human Identification Based on Extracted Gait Features,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+c391478faa3a8903678a7bbc4ab17c8f9601e273,Human Identification Based on Extracted Gait Features,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+c37b5c43b58f2810bba78fcf2251d5b631428b48,Grounding affect recognition on a low-level description of body posture,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+c37b5c43b58f2810bba78fcf2251d5b631428b48,Grounding affect recognition on a low-level description of body posture,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+c39ef5554b9964f578572d403522380e95802650,Generative mixture of networks,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+c39ef5554b9964f578572d403522380e95802650,Generative mixture of networks,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+c39ef5554b9964f578572d403522380e95802650,Generative mixture of networks,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+c3fd3b9e0de036241d6e0f94fdc5364551e10b6b,The Amygdala Excitatory/Inhibitory Balance in a Valproate-Induced Rat Autism Model,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+c3fd3b9e0de036241d6e0f94fdc5364551e10b6b,The Amygdala Excitatory/Inhibitory Balance in a Valproate-Induced Rat Autism Model,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+c3f5cf5594e66dbbeb1af72ddfe7d5e24a4f56c0,Learning-Based Run-Time Power and Energy Management of Multi/Many-Core Systems: Current and Future Trends,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+c3f5cf5594e66dbbeb1af72ddfe7d5e24a4f56c0,Learning-Based Run-Time Power and Energy Management of Multi/Many-Core Systems: Current and Future Trends,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+c31fe741266d60177975754d23241879ade0279c,Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+c397acf6a2876afe25bb07824f2d6030816cb009,Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+c397acf6a2876afe25bb07824f2d6030816cb009,Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+c322706351370b598612dc1e73b8bee78e0e8a5e,Face-specific and domain-general visual processing deficits in children with developmental prosopagnosia.,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
+c322706351370b598612dc1e73b8bee78e0e8a5e,Face-specific and domain-general visual processing deficits in children with developmental prosopagnosia.,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
c34532fe6bfbd1e6df477c9ffdbb043b77e7804d,A 3D Morphable Eye Region Model for Gaze Estimation,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
c34532fe6bfbd1e6df477c9ffdbb043b77e7804d,A 3D Morphable Eye Region Model for Gaze Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
c34532fe6bfbd1e6df477c9ffdbb043b77e7804d,A 3D Morphable Eye Region Model for Gaze Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
c394a5dfe5bea5fbab4c2b6b90d2d03e01fb29c0,Person Reidentification and Recognition in Video,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+c34030a215f0731ead15b358d947f03c33e828bb,Identity Aware Synthesis for Cross Resolution Face Recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+c34787b4708b34742774ba3abba8ace39c6b9052,Input Image : Smile Intensity Generated Responses : Input Question : Input,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+c34787b4708b34742774ba3abba8ace39c6b9052,Input Image : Smile Intensity Generated Responses : Input Question : Input,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+c37c3853ab428725f13906bb0ff4936ffe15d6af,Unsupervised Person Re-identification by Deep Learning Tracklet Association,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+c37c3853ab428725f13906bb0ff4936ffe15d6af,Unsupervised Person Re-identification by Deep Learning Tracklet Association,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
c30982d6d9bbe470a760c168002ed9d66e1718a2,Multi-camera head pose estimation using an ensemble of exemplars,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
c39ffc56a41d436748b9b57bdabd8248b2d28a32,Residual Attention Network for Image Classification,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
c39ffc56a41d436748b9b57bdabd8248b2d28a32,Residual Attention Network for Image Classification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
c32cd207855e301e6d1d9ddd3633c949630c793a,On the Effect of Illumination and Face Recognition,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+c306c207ac7299872280b47c88f28db4811a319f,Adversarial Inverse Graphics Networks: Learning 2D-to-3D Lifting and Image-to-Image Translation from Unpaired Supervision,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+c3dd6c1ddbb9cfcc1bed6383ffaa0b1ce4d13625,TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+c3e1ab13bb3c64ed129e286cec17465fc6bff0e1,Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+c3e1ab13bb3c64ed129e286cec17465fc6bff0e1,Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+c3e1ab13bb3c64ed129e286cec17465fc6bff0e1,Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+c3e1ab13bb3c64ed129e286cec17465fc6bff0e1,Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+c3e1ab13bb3c64ed129e286cec17465fc6bff0e1,Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+c3e1ab13bb3c64ed129e286cec17465fc6bff0e1,Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+c3e1ab13bb3c64ed129e286cec17465fc6bff0e1,Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
c32c8bfadda8f44d40c6cd9058a4016ab1c27499,Unconstrained Face Recognition From a Single Image,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+c3cdf580a667a7b91191bbe149cd27b2054cbc43,R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+c3cdf580a667a7b91191bbe149cd27b2054cbc43,R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+c3cdf580a667a7b91191bbe149cd27b2054cbc43,R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+c4f4122d16e1fdb77cb94152d0d1222b69ddc32b,Face Image Superresolution via Locality Preserving Projection and Sparse Coding,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+c42adbb77919328fad1fdbcc1ae7cdf12c118134,Privacy-Preserving Human Activity Recognition from Extreme Low Resolution,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+c42adbb77919328fad1fdbcc1ae7cdf12c118134,Privacy-Preserving Human Activity Recognition from Extreme Low Resolution,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
c418a3441f992fea523926f837f4bfb742548c16,A Computer Approach for Face Aging Problems,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
c4fb2de4a5dc28710d9880aece321acf68338fde,Interactive Generative Adversarial Networks for Facial Expression Generation in Dyadic Interactions,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+c44177896137e5010a2b336b943c23df1f3f92d3,Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
+c44177896137e5010a2b336b943c23df1f3f92d3,Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
+c44177896137e5010a2b336b943c23df1f3f92d3,Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
+c42b28d722dcf2b276fe41da1a811e6bf9e68010,Pose Normalization for Eye Gaze Estimation and Facial Attribute Description from Still Images,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
c44c84540db1c38ace232ef34b03bda1c81ba039,Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
c44c84540db1c38ace232ef34b03bda1c81ba039,Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+c4458cc521d8da6faeedc8c4f09505dace844a05,Automatic Detection of Emotion Valence on Faces Using Consumer Depth Cameras,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+c4458cc521d8da6faeedc8c4f09505dace844a05,Automatic Detection of Emotion Valence on Faces Using Consumer Depth Cameras,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+c4458cc521d8da6faeedc8c4f09505dace844a05,Automatic Detection of Emotion Valence on Faces Using Consumer Depth Cameras,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+c43d8a3d36973e3b830684e80a035bbb6856bcf7,Image Super-Resolution Using Very Deep Residual Channel Attention Networks,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+c43d8a3d36973e3b830684e80a035bbb6856bcf7,Image Super-Resolution Using Very Deep Residual Channel Attention Networks,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
c46a4db7247d26aceafed3e4f38ce52d54361817,A CNN Cascade for Landmark Guided Semantic Part Segmentation,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+c433ef13220c2ed4d2558283f8515b0e6e09bcad,A Public Video Dataset for Road Transportation Applications,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+c433ef13220c2ed4d2558283f8515b0e6e09bcad,A Public Video Dataset for Road Transportation Applications,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+c433ef13220c2ed4d2558283f8515b0e6e09bcad,A Public Video Dataset for Road Transportation Applications,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+c433ef13220c2ed4d2558283f8515b0e6e09bcad,A Public Video Dataset for Road Transportation Applications,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+c433ef13220c2ed4d2558283f8515b0e6e09bcad,A Public Video Dataset for Road Transportation Applications,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+c433ef13220c2ed4d2558283f8515b0e6e09bcad,A Public Video Dataset for Road Transportation Applications,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
c41de506423e301ef2a10ea6f984e9e19ba091b4,Modeling Attributes from Category-Attribute Proportions,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
c41de506423e301ef2a10ea6f984e9e19ba091b4,Modeling Attributes from Category-Attribute Proportions,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+c45681fa9d9c36a6a196017ef283ac38904f91bb,Pixel-wise object tracking,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+c437d0485217685f9ea42c33e492090b58de1db6,Mining Histopathological Images via Composite Hashing and Online Learning,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+c437d0485217685f9ea42c33e492090b58de1db6,Mining Histopathological Images via Composite Hashing and Online Learning,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
c4934d9f9c41dbc46f4173aad2775432fe02e0e6,Generalization to New Compositions of Known Entities in Image Understanding,Bar-Ilan University,Bar-Ilan University,"אוניברסיטת בר אילן, כביש גהה, גבעת שמואל, קריית מטלון, גבעת שמואל, מחוז תל אביב, NO, ישראל",32.06932925,34.84334339,edu,
c4934d9f9c41dbc46f4173aad2775432fe02e0e6,Generalization to New Compositions of Known Entities in Image Understanding,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
c40c23e4afc81c8b119ea361e5582aa3adecb157,Coupled Marginal Fisher Analysis for Low-Resolution Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+c4be56287fd666f9cfff257018a42e00dc56499d,The role of the fusiform-amygdala system in the pathophysiology of autism.,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
c49aed65fcf9ded15c44f9cbb4b161f851c6fa88,Multiscale Facial Expression Recognition Using Convolutional Neural Networks,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+c458db5d616058fbd9de19acc6c82827396cf195,Person Re-Identification with Discriminatively Trained Viewpoint Invariant Dictionaries,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+c40174aeb1be3998a2f8faae28d6689611bb7aad,"Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories",Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+c40174aeb1be3998a2f8faae28d6689611bb7aad,"Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+c40174aeb1be3998a2f8faae28d6689611bb7aad,"Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories",Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+c43ed9b34cad1a3976bac7979808eb038d88af84,Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+c43ed9b34cad1a3976bac7979808eb038d88af84,Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+c4ac98154efdd73fd3ec9954dfb5ed32b95f7ca5,Face Recognition Based on Improved Space Variant,Chonbuk National University,Chonbuk National University,"전북대학교, 567, 백제대로, 금암동, 덕진구, 전주시, 전북, 54896, 대한민국",35.84658875,127.13501330,edu,
+c48ee576130473efe6dc3ee47f552bc581aa68b2,Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+c48ee576130473efe6dc3ee47f552bc581aa68b2,Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
c466ad258d6262c8ce7796681f564fec9c2b143d,Pose-Invariant Face Recognition Using A Single 3D Reference Model,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
+ea3b13e512c846e2bb29d99f5f97fcf8c7f52836,Adding the Third Dimension to Spatial Relation Detection in 2D Images,University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
+ea00489323104d70dd43bac5e15390ec4d6dfe8f,Transfer for Person Re-identification,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+ea00489323104d70dd43bac5e15390ec4d6dfe8f,Transfer for Person Re-identification,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+ea00489323104d70dd43bac5e15390ec4d6dfe8f,Transfer for Person Re-identification,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+ea00489323104d70dd43bac5e15390ec4d6dfe8f,Transfer for Person Re-identification,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
ea46951b070f37ad95ea4ed08c7c2a71be2daedc,Using phase instead of optical flow for action recognition,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
ea46951b070f37ad95ea4ed08c7c2a71be2daedc,Using phase instead of optical flow for action recognition,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
-ea80a050d20c0e24e0625a92e5c03e5c8db3e786,Face Verification and Face Image Synthesis under Illumination Changes using Neural Networks,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
+ea985e35b36f05156f82ac2025ad3fe8037be0cd,CERTH/CEA LIST at MediaEval Placing Task 2015,Information Technologies Institute,Information Technologies Institute,"公益財団法人九州先端科学技術研究所, Fukuoka SRP Center Building 7F, 百道ランプ下り入り口, 早良区, 福岡市, 福岡県, 九州地方, 814-0001, 日本",33.59345390,130.35578370,edu,
+ea3f9321d4609ac3a659b66aae204f0b0e2a8ba1,Distractor-Aware Siamese Networks for Visual Object Tracking,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+ea3f9321d4609ac3a659b66aae204f0b0e2a8ba1,Distractor-Aware Siamese Networks for Visual Object Tracking,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+ea3f9321d4609ac3a659b66aae204f0b0e2a8ba1,Distractor-Aware Siamese Networks for Visual Object Tracking,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
+ea80a050d20c0e24e0625a92e5c03e5c8db3e786,Face Verification and Face Image Synthesis under Illumination Changes using Neural Networks by,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
eacba5e8fbafb1302866c0860fc260a2bdfff232,VOS-GAN: Adversarial Learning of Visual-Temporal Dynamics for Unsupervised Dense Prediction in Videos,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+ea8707f8d527018c063a688bbd5a88f74506b288,Be Your Own Prada: Fashion Synthesis with Structural Coherence,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+ea8707f8d527018c063a688bbd5a88f74506b288,Be Your Own Prada: Fashion Synthesis with Structural Coherence,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+ea050801199f98a1c7c1df6769f23f658299a3ae,The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+ea32e570ddf5661cdb030132e15e68e30ba6b24a,People Re-identification Based on Bags of Semantic Features,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+ea4a93a97bf0bff059034c707fa75a2ca13d8048,Extracting Minimalistic Corridor Geometry from Low-Resolution Images,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+ead1db02b36146ef5c3ef29a1cc411a8f01bc56b,A Overview About Image Segmentation,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+eadbad2a715bd1b0822ec3790c65765c61924549,Scalable Deep $k$-Subspace Clustering,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+ea923da826b9e6f89159cc960db7aac91b5ecbd6,Approved by Major Professor(s): Approved by Head of Graduate Program: Date of Graduate Program Head's Approval: Abhilasha Bhargav-Spantzel Protocols and Systems for Privacy Preserving Protection of Digital Identity Doctor of Philosophy,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+ea4098d86802dff863fe9f91cbc75b195d452d34,"Tensorize , Factorize and Regularize : Robust Visual Relationship Learning",University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+ea4098d86802dff863fe9f91cbc75b195d452d34,"Tensorize , Factorize and Regularize : Robust Visual Relationship Learning",University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+ea7fbfd02bf17b310e1e7f4be12d106b4990c33d,Image Generation and Editing with Variational Info Generative AdversarialNetworks,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+ea6207e553a5c8a3e171a8f6b6297688ab43f92d,DeepObfuscation: Securing the Structure of Convolutional Neural Networks via Knowledge Distillation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+ea6207e553a5c8a3e171a8f6b6297688ab43f92d,DeepObfuscation: Securing the Structure of Convolutional Neural Networks via Knowledge Distillation,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
ea890846912f16a0f3a860fce289596a7dac575f,Benefits of social vs. non-social feedback on learning and generosity. Results from the Tipping Game,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
ea890846912f16a0f3a860fce289596a7dac575f,Benefits of social vs. non-social feedback on learning and generosity. Results from the Tipping Game,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
eaaed082762337e7c3f8a1b1dfea9c0d3ca281bf,Algebraic Simplification of Genetic Programs during Evolution,Victoria University of Wellington,Victoria University of Wellington,"Victoria University of Wellington, Waiteata Road, Aro Valley, Wellington, Wellington City, Wellington, 6040, New Zealand/Aotearoa",-41.29052775,174.76846919,edu,
ea218cebea2228b360680cb85ca133e8c2972e56,Recover Canonical-View Faces in the Wild with Deep Neural Networks,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
e1630014a5ae3d2fb7ff6618f1470a567f4d90f5,"Look, Listen and Learn - A Multimodal LSTM for Speaker Identification",SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
e1630014a5ae3d2fb7ff6618f1470a567f4d90f5,"Look, Listen and Learn - A Multimodal LSTM for Speaker Identification",University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+e1e2e32f29cf7d23881e98dfe018d9049bdb070d,Image Understanding using Vision and Reasoning through Scene Description Graph,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+e1e2e32f29cf7d23881e98dfe018d9049bdb070d,Image Understanding using Vision and Reasoning through Scene Description Graph,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
e19fb22b35c352f57f520f593d748096b41a4a7b,"Modeling Context for Image Understanding : When , For What , and How ?",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+e1d1ed79174cd8442409bcb3f296101852ddcb95,Theory and Practice of Globally Optimal Deformation Estimation,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+e1d1ed79174cd8442409bcb3f296101852ddcb95,Theory and Practice of Globally Optimal Deformation Estimation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+e1d1ed79174cd8442409bcb3f296101852ddcb95,Theory and Practice of Globally Optimal Deformation Estimation,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+e1d1ed79174cd8442409bcb3f296101852ddcb95,Theory and Practice of Globally Optimal Deformation Estimation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+e1e6a4146c082e5465cde38e9511de3d150b4ede,Targeting static and dynamic workloads with a reconfigurable VLIW processor,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
e1c59e00458b4dee3f0e683ed265735f33187f77,Spectral Rotation versus K-Means in Spectral Clustering,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+e1e490b5d0a179b8eea022b64e83bbd611114d4e,Gradient-based learning of higher-order image features,University of Frankfurt,University of Frankfurt,"Frankfurt University of Applied Sciences, Kleiststraße, Nordend West, Frankfurt, Regierungsbezirk Darmstadt, Hessen, 60318, Deutschland",50.13053055,8.69234224,edu,
+e121bf6f18e1cb114216a521df63c55030d10fbe,Robust Facial Component Detection for Face Alignment Applications,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+e103fa24d7fa297cd206b22b3bf670bfda6c65c4,Object Detection in Very High-Resolution Aerial Images Using One-Stage Densely Connected Feature Pyramid Network,Chonbuk National University,Chonbuk National University,"전북대학교, 567, 백제대로, 금암동, 덕진구, 전주시, 전북, 54896, 대한민국",35.84658875,127.13501330,edu,
+e103fa24d7fa297cd206b22b3bf670bfda6c65c4,Object Detection in Very High-Resolution Aerial Images Using One-Stage Densely Connected Feature Pyramid Network,Chonbuk National University,Chonbuk National University,"전북대학교, 567, 백제대로, 금암동, 덕진구, 전주시, 전북, 54896, 대한민국",35.84658875,127.13501330,edu,
+e11247abf2c359428d414a97ea21e0744e2ef9ac,Face Recognition from Sequential Sparse 3D data via Deep Registration,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+e188aa199d4307fdbbf60e9e6612bcb001e1cab6,Say Cheese: Personal Photography Layout Recommendation Using 3D Aesthetics Estimation,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
e1ab3b9dee2da20078464f4ad8deb523b5b1792e,Pre-Training CNNs Using Convolutional Autoencoders,TU Berlin,TU Berlin,"Franklinstraße 28-29, 10587 Berlin, Germany",52.51806410,13.32504250,edu,"Franklinstr. 28/29, 10587, Germany"
e1ab3b9dee2da20078464f4ad8deb523b5b1792e,Pre-Training CNNs Using Convolutional Autoencoders,TU Berlin,TU Berlin,"Franklinstraße 28-29, 10587 Berlin, Germany",52.51806410,13.32504250,edu,"Franklinstr. 28/29, 10587, Germany"
e1ab3b9dee2da20078464f4ad8deb523b5b1792e,Pre-Training CNNs Using Convolutional Autoencoders,TU Berlin,TU Berlin,"Franklinstraße 28-29, 10587 Berlin, Germany",52.51806410,13.32504250,edu,"Franklinstr. 28/29, 10587, Germany"
e1ab3b9dee2da20078464f4ad8deb523b5b1792e,Pre-Training CNNs Using Convolutional Autoencoders,TU Berlin,TU Berlin,"Franklinstraße 28-29, 10587 Berlin, Germany",52.51806410,13.32504250,edu,"Franklinstr. 28/29, 10587, Germany"
e1f6e2651b7294951b5eab5d2322336af1f676dc,Emotional Avatars: Appearance Augmentation and Animation based on Facial Expression Analysis,Sejong University,"Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea","209 Neungdong-ro, Gunja-dong, Gwangjin-gu, Seoul, South Korea",37.55025960,127.07313900,edu,
+e1af55ad7bb26e5e1acde3ec6c5c43cffe884b04,Person Re-identification by Mid-level Attribute and Part-based Identity Learning,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
+e10ca043fae02972f19292efacddd8e0f216b70c,Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Concepts,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
e1256ff535bf4c024dd62faeb2418d48674ddfa2,Towards Open-Set Identity Preserving Face Synthesis,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
e1256ff535bf4c024dd62faeb2418d48674ddfa2,Towards Open-Set Identity Preserving Face Synthesis,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+e1bf18d2933e5f24d598fcaa5318c45cea373c39,Large-Scale Machine Learning for Classification and Search,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+cd6aaa37fffd0b5c2320f386be322b8adaa1cc68,Deep Face Recognition: A Survey,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+cd32d7383b1e987329d2412f2907b7db6dd8d396,Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
+cd32d7383b1e987329d2412f2907b7db6dd8d396,Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
cdc7bd87a2c9983dab728dbc8aac74d8c9ed7e66,l 1 l 2 l 3 l 4 l 5 ( a ) Class-Agnostic Temporal,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+cd1349619415202e82475353e2b2a60da2e5bd65,Optimal Illumination for Three-Image Photometric Stereo using Sensitivity Analysis,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
cd4941cbef1e27d7afdc41b48c1aff5338aacf06,MovieGraphs: Towards Understanding Human-Centric Situations from Videos,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
cdef0eaff4a3c168290d238999fc066ebc3a93e8,Contrastive-center loss for deep neural networks,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
cd23dc3227ee2a3ab0f4de1817d03ca771267aeb,Face Recognition via Deep Sparse Graph Neural Networks,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
+cd323dc4b67965a4f16b5b0a55fcc1ff0396b375,Action 2 Vec : A Crossmodal Embedding Approach to Action Learning,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
cdb1d32bc5c1a9bb0d9a5b9c9222401eab3e9ca0,Functional Faces: Groupwise Dense Correspondence Using Functional Maps,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+cd9d654c6a4250e0cf8bcfddc2afab9e70ee6cae,Object Detection with Mask-based Feature Encoding,University of South Carolina,University of South Carolina,"University of South Carolina, Wheat Street, Columbia, Richland County, South Carolina, 29205, USA",33.99282980,-81.02685168,edu,
+cd9d654c6a4250e0cf8bcfddc2afab9e70ee6cae,Object Detection with Mask-based Feature Encoding,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+cdc535719aa041b7bbd529eab4582619a04b706e,Multi-channel Convolutional Neural Network Ensemble for Pedestrian Detection,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+cd0503a31a9f9040736ccfb24086dc934508cfc7,Maximizing Resource Utilization In Video Streaming Systems,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+cd0503a31a9f9040736ccfb24086dc934508cfc7,Maximizing Resource Utilization In Video Streaming Systems,Wayne State University,Wayne State University,"Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA",42.35775700,-83.06286711,edu,
+cd2605b31feb84fb53a5a56b21499f4ebff20385,DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+cd2605b31feb84fb53a5a56b21499f4ebff20385,DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+cd2605b31feb84fb53a5a56b21499f4ebff20385,DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+cda6c8904c324e4eb32e83cada17cd1a7d47a348,Unsupervised Multi-Domain Image Translation with Domain-Specific Encoders/Decoders,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+cd22375bf1d917b928aee006b65cd92c7bfe0927,FMCode: A 3D In-the-Air Finger Motion Based User Login Framework for Gesture Interface,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+cd22375bf1d917b928aee006b65cd92c7bfe0927,FMCode: A 3D In-the-Air Finger Motion Based User Login Framework for Gesture Interface,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+cd4850de71e4e858be5f5e6ef7f48d5bf7decea6,Distribution Entropy Boosted VLAD for Image Retrieval,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+cd4850de71e4e858be5f5e6ef7f48d5bf7decea6,Distribution Entropy Boosted VLAD for Image Retrieval,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+cd4850de71e4e858be5f5e6ef7f48d5bf7decea6,Distribution Entropy Boosted VLAD for Image Retrieval,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+cd4850de71e4e858be5f5e6ef7f48d5bf7decea6,Distribution Entropy Boosted VLAD for Image Retrieval,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+cd4850de71e4e858be5f5e6ef7f48d5bf7decea6,Distribution Entropy Boosted VLAD for Image Retrieval,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+cd4850de71e4e858be5f5e6ef7f48d5bf7decea6,Distribution Entropy Boosted VLAD for Image Retrieval,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+cd6cab9357f333ad9966abc76f830c190a1b7911,"Recognition, reorganisation, reconstruction and reinteraction for scene understanding",Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+cd87fea30b68ad1c9ebcb71a224c53cde3516adb,EXTRACTING THE X FACTOR IN HUMAN PARSING 3 Factored module Factored task Aggregation module Input Main task Shared features Silhouette Body parts The X Factor bottleneck layers bottleneck layers bottleneck layers Initial module bottleneck layers initial block,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+cd2221518485f829d3fad81e33ef4033ffa66f75,Multiple Images Recovery Using a Single Affine Transformation,Anhui University,Anhui University,"安徽大学(磬苑校区), 111, 九龙路, 弘泰苑, 合肥国家级经济技术开发区, 芙蓉社区, 合肥经济技术开发区, 合肥市区, 合肥市, 安徽省, 230601, 中国",31.76909325,117.17795091,edu,
+cd2221518485f829d3fad81e33ef4033ffa66f75,Multiple Images Recovery Using a Single Affine Transformation,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+cd44668fd6b7e8d2606f8c634a5b571d172693ff,Convolutional Neural Networks for Iris Presentation Attack Detection : Toward Cross-Dataset and Cross-Sensor Generalization,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+cdb293381ff396d6e9c0f5e9578d411e759347fd,3 DR 2 N 2 : A Unified Approach for Single and Multiview 3 D Object Reconstruction,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+cd4cce724c8a33f72b068a267cd6152c31851013,Scanning Strategies Do Not Modulate Face Identification: Eye-Tracking and Near-Infrared Spectroscopy Study,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+cd000f4a7a64db5e00b200b93cc3f13c9e313c01,Attributes as Operators,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
cd436f05fb4aeeda5d1085f2fe0384526571a46e,Information Bottleneck Domain Adaptation with Privileged Information for Visual Recognition,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+cd468236213273b96d985dcc859f24c0a19e3077,Hopc : a Novel Similarity Metric Based on Geometric Structural Properties for Multi-modal Remote Sensing Image Matching,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
+cd468236213273b96d985dcc859f24c0a19e3077,Hopc : a Novel Similarity Metric Based on Geometric Structural Properties for Multi-modal Remote Sensing Image Matching,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
+cd010fc089c580c87c5cff4aa6a9b1d6d41e2470,"Digital Images Authentication Technique Based on DWT, DCT and Local Binary Patterns",University of Kent,University of Kent,"University of Kent, St. Stephen's Hill, Hackington, Canterbury, Kent, South East, England, CT2 7AS, UK",51.29753440,1.07296165,edu,
+cd1758d3b86c4f1caf01ec222b45daf15888d1a8,MMD GAN: Towards Deeper Understanding of Moment Matching Network,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+cd1758d3b86c4f1caf01ec222b45daf15888d1a8,MMD GAN: Towards Deeper Understanding of Moment Matching Network,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
cd2c54705c455a4379f45eefdf32d8d10087e521,A Hybrid Model for Identity Obfuscation by Face Replacement,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+cd9f1f429b41c4c125df231bab8872e012ff5316,STEM inSight: Developing a Research Skills Course for First- and Second-Year Students,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+cd9f1f429b41c4c125df231bab8872e012ff5316,STEM inSight: Developing a Research Skills Course for First- and Second-Year Students,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+cdf2510d1fa51e911ef8f2618d41707b0c037d3f,Face Identi cation in Multimedia Archives,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+cde8186c38c04dacac2e1fac1c3c68cf46516b9f,Hierarchical Network for Facial Palsy Detection,National Taiwan University of Science and Technology,National Taiwan University of Science and Technology,"臺科大, 43, 基隆路四段, 學府里, 下內埔, 大安區, 臺北市, 10607, 臺灣",25.01353105,121.54173736,edu,
cd023d2d067365c83d8e27431e83e7e66082f718,Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
cd023d2d067365c83d8e27431e83e7e66082f718,Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+cdde9cfb726e177b781dffbbb41d15cf58d7f888,A New SIFT-Based Image Descriptor Applicable for Content Based Image Retrieval,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
cca9ae621e8228cfa787ec7954bb375536160e0d,Learning to Collaborate for User-Controlled Privacy,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
cca9ae621e8228cfa787ec7954bb375536160e0d,Learning to Collaborate for User-Controlled Privacy,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+ccc57280e2c50381a692a67ed53124ad1b735686,Self-Reflective Risk-Aware Artificial Cognitive Modeling for Robot Response to Human Behaviors,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
+ccf413e4a730ee228769c82a8af1fddc2857fbe8,Deep Learning Based Multi-modal Addressee Recognition in Visual Scenes with Utterances,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
cc589c499dcf323fe4a143bbef0074c3e31f9b60,A 3D facial expression database for facial behavior research,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
+cc4fc9a309f300e711e09712701b1509045a8e04,Continuous Supervised Descent Method for Facial Landmark Localisation,Universitat Oberta de Catalunya,Universitat Oberta de Catalunya,"Universitat Oberta de Catalunya, 156, Rambla del Poblenou, Provençals del Poblenou, Sant Martí, Barcelona, BCN, CAT, 08018, España",41.40657415,2.19453410,edu,
+cc4fc9a309f300e711e09712701b1509045a8e04,Continuous Supervised Descent Method for Facial Landmark Localisation,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+cc4fc9a309f300e711e09712701b1509045a8e04,Continuous Supervised Descent Method for Facial Landmark Localisation,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
cc2eaa182f33defbb33d69e9547630aab7ed9c9c,Surpassing Humans and Computers with JELLYBEAN: Crowd-Vision-Hybrid Counting Algorithms,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
cc2eaa182f33defbb33d69e9547630aab7ed9c9c,Surpassing Humans and Computers with JELLYBEAN: Crowd-Vision-Hybrid Counting Algorithms,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
cc2eaa182f33defbb33d69e9547630aab7ed9c9c,Surpassing Humans and Computers with JELLYBEAN: Crowd-Vision-Hybrid Counting Algorithms,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
cc2eaa182f33defbb33d69e9547630aab7ed9c9c,Surpassing Humans and Computers with JELLYBEAN: Crowd-Vision-Hybrid Counting Algorithms,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+cc3ef62b4a7eb6c4e45302deb89df2e547b6efcc,Creating Picture Legends for Group Photos,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+cc353489ceaba1f58bd44f54316bc8319eba5fb9,Program Synthesis from Visual Specification,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+cc5a1cf7ad9d644f21a5df799ffbcb8d1e24abe1,MonoPerfCap: Human Performance Capture from Monocular Video,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
ccdea57234d38c7831f1e9231efcb6352c801c55,Illumination Processing in Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+ccd7a6b9f23e983a3fc6a70cc3b9c9673d70bf2c,Symmetrical Two-Dimensional PCA with Image Measures in Face Recognition,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+ccd7a6b9f23e983a3fc6a70cc3b9c9673d70bf2c,Symmetrical Two-Dimensional PCA with Image Measures in Face Recognition,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+ccb9ffa26b28dffc4f7d613821d1a9f0d60ea3f4,Online Adaptation of Convolutional Neural Networks for Video Object Segmentation,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+cc2cf8f69cd2d16c9bee2bb6c598548e7ff7cb05,Unsupervised Learning of Invariant Representations in Visual Cortex ( and in Deep Learning Architectures ),McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
+cc2cf8f69cd2d16c9bee2bb6c598548e7ff7cb05,Unsupervised Learning of Invariant Representations in Visual Cortex ( and in Deep Learning Architectures ),MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+ccd3dcbccae7d903608530bddf6381db8e723a7d,Unsupervised Domain Adaptation for Semantic Segmentation with GANs,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+ccd3dcbccae7d903608530bddf6381db8e723a7d,Unsupervised Domain Adaptation for Semantic Segmentation with GANs,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
cc38942825d3a2c9ee8583c153d2c56c607e61a7,Database Cross Matching: A Novel Source of Fictitious Forensic Cases,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+cc94b423c298003f0f164e63e63177d443291a77,Multi-View Semantic Labeling of 3D Point Clouds for Automated Plant Phenotyping,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+ccebecf0e24f76262d85f55712010632ea04c0af,Stepwise Nearest Neighbor Discriminant Analysis,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+ccf119021cf246fd75d37863646ccb85accee6a8,Unsupervised Learning and Segmentation of Complex Activities from Video,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+ccf934a335793fe416b0115183783d2c355b64ed,Query Based Adaptive Re-ranking for Person Re-identification,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+cc70f4af018de5e5bdc8075dbdf1bbe49a6f0b4a,Generative adversarial network-based synthesis of visible faces from polarimetrie thermal faces,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+ccb0353fd1aa19b50fca8d69f9b9c9f1752dd55b,Towards Better Understanding the Clothing Fashion Styles: A Multimodal Deep Learning Approach,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+ccb0353fd1aa19b50fca8d69f9b9c9f1752dd55b,Towards Better Understanding the Clothing Fashion Styles: A Multimodal Deep Learning Approach,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+ccb0353fd1aa19b50fca8d69f9b9c9f1752dd55b,Towards Better Understanding the Clothing Fashion Styles: A Multimodal Deep Learning Approach,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+ccdf24d85fc14b4710dcee268355548f166ba870,Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+ccdf24d85fc14b4710dcee268355548f166ba870,Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+ccdf24d85fc14b4710dcee268355548f166ba870,Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+ccc65463198ee0a0db9b303a3dc903c762dbccaa,Adaptive Selection of Deep Learning Models on Embedded Systems,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
+ccc65463198ee0a0db9b303a3dc903c762dbccaa,Adaptive Selection of Deep Learning Models on Embedded Systems,Lancaster University,Lancaster University,"Lancaster University, Library Avenue, Bowland College, Hala, Lancaster, Lancs, North West England, England, LA1 4AP, UK",54.00975365,-2.78757491,edu,
+cceab479d37060b0952439d9bd6fbbba5de1d550,VizWiz Grand Challenge: Answering Visual Questions from Blind People,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
cc7e66f2ba9ac0c639c80c65534ce6031997acd7,Facial Descriptors for Identity-Preserving Multiple People Tracking,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
cc9057d2762e077c53e381f90884595677eceafa,On the Exploration of Joint Attribute Learning for Person Re-identification,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
ccf16bcf458e4d7a37643b8364594656287f5bfc,Cascade for Landmark Guided Semantic Part Segmentation,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+e64fa00da02cc774559db5be88bc2862afbfd432,Histogram of Oriented Normal Vectors for Object Recognition with a Depth Sensor,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+e686e9a642880662e56558b13d3d32f051d549b3,Human face orientation detection using power spectrum based measurements,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+e6ac47a768188971d0b478182db9026221a0807d,Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+e6ac47a768188971d0b478182db9026221a0807d,Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
e69ac130e3c7267cce5e1e3d9508ff76eb0e0eef,Addressing the illumination challenge in two-dimensional face recognition: a survey,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+e6d9d3a2f1560e507a24b8cfe3d2f4369c79e0f6,Impact of eye detection error on face recognition performance,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+e6d9d3a2f1560e507a24b8cfe3d2f4369c79e0f6,Impact of eye detection error on face recognition performance,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+e659221538d256b2c3e0724deff749eda903fc7d,Fine-Grained Head Pose Estimation Without Keypoints,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+e6d4c0ac2352f108a078a4fd3f908a03b8571f2b,Racial Bias in Judgments of Physical Size and Formidability,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+e607b91f69ea2bff3194b07c5d22b4625bbe306e,Learning to See People Like People: Predicting Social Impressions of Faces,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+e64e5449d0d10cfcf63edc8a0b28fc96d09d3535,GLAC Net: GLocal Attention Cascading Networks for Multi-image Cued Story Generation,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+e67e757a3d94b71b94e16c5a6a90d77bf61e9aab,Limited-Memory Fast Gradient Descent Method for Graph Regularized Nonnegative Matrix Factorization,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
e6f20e7431172c68f7fce0d4595100445a06c117,Searching Action Proposals via Spatial Actionness Estimation and Temporal Path Inference and Tracking,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+e61a7a02cd2b68043012231f8da1d7077e665040,Utilization-aware load balancing for the energy efficient operation of the big.LITTLE processor,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+e608ccf3ac353cf7204ccf5659983d69bd09f515,Cross-Domain Image Retrieval with Attention Modeling,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+e65da9b728493c4619beca5728f622f6e91c9dd7,Histogram of Structure Tensors: Application to Pattern Clustering,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
+e6eda2bfec3036cf431a45fa021070ab21bb3488,Mirror Representation for Modeling View-Specific Transform in Person Re-Identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+e6020915b9530fa585453f60a8934aed30558be4,Improving Neural Question Generation using Answer Separation,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+e6020915b9530fa585453f60a8934aed30558be4,Improving Neural Question Generation using Answer Separation,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+f9c563ec6c8238aaf420327bd7f9d8fbf8de3bce,An Evaluation on Color Invariant Based Local Spatiotemporal Features for Action Recognition,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
+f97342323ec16d67fcdd8969e5312e43d4a6edf8,Physical Models of Human Motion for Estimation and Scene Analysis,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+f9a1132c777b24e9361b1bcbccb9fcfc737f3194,VIPL-HR: A Multi-modal Database for Pulse Estimation from Less-constrained Face Video,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+f9a1132c777b24e9361b1bcbccb9fcfc737f3194,VIPL-HR: A Multi-modal Database for Pulse Estimation from Less-constrained Face Video,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+f9717a0056ad863c5f9dc00916ab87bdf1cdf5f7,Pose Flow: Efficient Online Pose Tracking,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+f9d171019bfeb71733fe36f7fae14f342ca9e51c,Hough Forests Revisited: An Approach to Multiple Instance Tracking from Multiple Cameras,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+f942739b7f9bc3c0b84f760bb2fd4895e1363ec0,Students Wearing Police Uniforms Exhibit Biased Attention toward Individuals Wearing Hoodies,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
+f942739b7f9bc3c0b84f760bb2fd4895e1363ec0,Students Wearing Police Uniforms Exhibit Biased Attention toward Individuals Wearing Hoodies,Curtin University,Curtin University,"Curtin University, Brand Drive, Waterford, Perth, Western Australia, 6102, Australia",-32.00686365,115.89691775,edu,
+f942739b7f9bc3c0b84f760bb2fd4895e1363ec0,Students Wearing Police Uniforms Exhibit Biased Attention toward Individuals Wearing Hoodies,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+f9b8539d48d6350435ab5550fd47451e779d2466,Accelerating image recognition on mobile devices using GPGPU,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+f9e92f5768998fbb876fb41facb1bba17b10c7af,ConceptFusion: A Flexible Scene Classification Framework,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+f9e92f5768998fbb876fb41facb1bba17b10c7af,ConceptFusion: A Flexible Scene Classification Framework,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+f9e92f5768998fbb876fb41facb1bba17b10c7af,ConceptFusion: A Flexible Scene Classification Framework,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+f984a5ad2d379b4e4b51005a73cdbd978ce3d810,ExplainGAN: Model Explanation via Decision Boundary Crossing Transformations,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+f9f01af981f8d25f0c96ea06d88be62dabb79256,Terahertz Image Detection with the Improved Faster Region-Based Convolutional Neural Network,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+f90b97008d921004487d1232ad20dcd9d678435f,Toward Marker-Free 3D Pose Estimation in Lifting: A Deep Multi-View Solution,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+f90b97008d921004487d1232ad20dcd9d678435f,Toward Marker-Free 3D Pose Estimation in Lifting: A Deep Multi-View Solution,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+f90b97008d921004487d1232ad20dcd9d678435f,Toward Marker-Free 3D Pose Estimation in Lifting: A Deep Multi-View Solution,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+f9034d80a0c318a8c564ce3aa9d8545d871b9663,Facial Expression Recognition with Inconsistently Annotated Datasets,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+f9034d80a0c318a8c564ce3aa9d8545d871b9663,Facial Expression Recognition with Inconsistently Annotated Datasets,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+f91388f87e10674226f4def4cda411adc01da496,Failure to Affect Decision Criteria During Recognition Memory With Continuous Theta Burst Stimulation,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
+f95d53ff893305741d60e234772003ec8579828b,A 3D Morphable Model of the Eye Region,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+f95d53ff893305741d60e234772003ec8579828b,A 3D Morphable Model of the Eye Region,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+f95d53ff893305741d60e234772003ec8579828b,A 3D Morphable Model of the Eye Region,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
f963967e52a5fd97fa3ebd679fd098c3cb70340e,"Analysis, Interpretation, and Recognition of Facial Action Units and Expressions Using Neuro-Fuzzy Modeling",Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
f9e0209dc9e72d64b290d0622c1c1662aa2cc771,Contributions to Biometric Recognition: Matching Identical Twins and Latent Fingerprints,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
f92ade569cbe54344ffd3bb25efd366dcd8ad659,Effect of Super Resolution on High Dimensional Features for Unsupervised Face Recognition in the Wild,University of Bridgeport,University of Bridgeport,"University of Bridgeport, Park Avenue, Bridgeport Downtown South Historic District, Bridgeport, Fairfield County, Connecticut, 06825, USA",41.16648580,-73.19205640,edu,
+f9cf3bbca1598a0309c1395c5a46f17f774f4094,Convex Class Model on Symmetric Positive Definite Manifolds,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+f9b90d3c1e2c3d0f3d9a94e6a0aea5e3047bca78,Analysis of photometric factors based on photometric linearization.,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+f9b90d3c1e2c3d0f3d9a94e6a0aea5e3047bca78,Analysis of photometric factors based on photometric linearization.,Okayama University,Okayama University,"岡山大学, 津高法界院停車場線, 津島東2, 津島東, 北区, 岡山市, 岡山県, 中国地方, 700-0081, 日本",34.68933930,133.92222720,edu,
+f989a20fbcc2d576c0c4514a0e5085c741580778,Co-localization with Category-Consistent Features and Geodesic Distance Propagation,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+f989a20fbcc2d576c0c4514a0e5085c741580778,Co-localization with Category-Consistent Features and Geodesic Distance Propagation,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+f989a20fbcc2d576c0c4514a0e5085c741580778,Co-localization with Category-Consistent Features and Geodesic Distance Propagation,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+f970cc735d87ad8484a29a5bad69f529dd557471,000 Tiny Videos : A Large Dataset for Non-Parametric Content-Based Retrieval and Recognition,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
f94f366ce14555cf0d5d34248f9467c18241c3ee,Deep Convolutional Neural Network in Deformable Part Models for Face Detection,Japan Advanced Institute of Science and Technology,Japan Advanced Institute of Science and Technology,"JAIST (北陸先端科学技術大学院大学), 石川県道55号小松辰口線, Ishikawa Science Park, 能美市, 石川県, 中部地方, 923-1206, 日本",36.44429490,136.59285870,edu,
f909d04c809013b930bafca12c0f9a8192df9d92,Single Image Subspace for Face Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
f909d04c809013b930bafca12c0f9a8192df9d92,Single Image Subspace for Face Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+f9570079f33ab11394175d57db0aa94251c48c61,Compositional GAN: Learning Conditional Image Composition,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+f9e388544ae371cdd1d73b2e444cb46d9532f530,Image Quality Assessment Guided Deep Neural Networks Training,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+f9e388544ae371cdd1d73b2e444cb46d9532f530,Image Quality Assessment Guided Deep Neural Networks Training,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+f9e388544ae371cdd1d73b2e444cb46d9532f530,Image Quality Assessment Guided Deep Neural Networks Training,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+f94f79168c1cfaebb8eab5151e01d56478ab0b73,Optimizing Region Selection for Weakly Supervised Object Detection,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
f9ccfe000092121a2016639732cdb368378256d5,Cognitive behaviour analysis based on facial information using depth sensors,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
f08e425c2fce277aedb51d93757839900d591008,Neural Motifs: Scene Graph Parsing with Global Context,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
f08e425c2fce277aedb51d93757839900d591008,Neural Motifs: Scene Graph Parsing with Global Context,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
f02f0f6fcd56a9b1407045de6634df15c60a85cd,Learning Low-shot facial representations via 2D warping,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+f029e3fc47cab0b23da307dd2ec6d2a064091f83,Appearance and motion based data association for pedestrian tracking,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+f02feec9f8d15f929018e0f0aa14446f47112d22,Cross-Resolution Person Re-identification with Deep Antithetical Learning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+f0c21345a13c0e1da2b74aef4e8b987feb266bb5,Deep Multitask Architecture for Integrated 2D and 3D Human Sensing,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+f0864a4e2f7dc4b3bacc36a0617a1860bcb6aba1,Multi-pedestrian detection in crowded scenes: A global view,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
f0ca31fd5cad07e84b47d50dc07db9fc53482a46,Feature Patch Illumination Spaces and Karcher Compression for Face Recognition via Grassmannians,Colorado State University,Colorado State University,"Colorado State University, West Pitkin Street, Woodwest, Fort Collins, Larimer County, Colorado, 80526-2002, USA",40.57093580,-105.08655256,edu,
f074e86e003d5b7a3b6e1780d9c323598d93f3bc,Characteristic Number: Theory and Its Application to Shape Analysis,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
f074e86e003d5b7a3b6e1780d9c323598d93f3bc,Characteristic Number: Theory and Its Application to Shape Analysis,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
+f06b30bf5874ad6168615b4443d011dd44e1ceda,Sparsity-Based Occlusion Handling Method for Person Re-identification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+f06b30bf5874ad6168615b4443d011dd44e1ceda,Sparsity-Based Occlusion Handling Method for Person Re-identification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+f049ea3ca734c217c380a1802d15a6d85378f55d,Efficient misbehaving user detection in online video chat services,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+f049ea3ca734c217c380a1802d15a6d85378f55d,Efficient misbehaving user detection in online video chat services,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
f0a4a3fb6997334511d7b8fc090f9ce894679faf,Generative Face Completion,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+f06f4bc74dc0be0a628e99a5c86ab3e00ed00276,Heated-Up Softmax Embedding,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
f0681fc08f4d7198dcde803d69ca62f09f3db6c5,Spatiotemporal Features for Effective Facial Expression Recognition,Bogazici University,Bogazici University,"Boğaziçi Üniversitesi Kuzey Yerleşkesi, Okulaltı 1. Sokak, Rumelihisarı, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34467, Türkiye",41.08688410,29.04413167,edu,
f0f501e1e8726148d18e70c8e9f6feea9360d119,Jukka Komulainen SOFTWARE - BASED COUNTERMEASURES TO 2 D FACIAL,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
f0398ee5291b153b716411c146a17d4af9cb0edc,Learning Optical Flow via Dilated Networks and Occlusion Reasoning,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
f0f0e94d333b4923ae42ee195df17c0df62ea0b1,Scaling Manifold Ranking Based Image Retrieval,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+f03b9b0895f5fb3351bbf3db4b1139af85650543,Where is Misty? Interpreting Spatial Descriptors by Modeling Regions in Space,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+f0ae665f5b4a9314c77dc9ec285a335ee6ecc15b,A Heuristic Deformable Pedestrian Detection Method,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
f0a3f12469fa55ad0d40c21212d18c02be0d1264,Sparsity Sharing Embedding for Face Verification,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
f05ad40246656a977cf321c8299158435e3f3b61,Face Recognition Using Face Patch Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+f0e26f749fb67182a5d3864e62a3460ac333e5e4,Spatial Knowledge Distillation to aid Visual Reasoning,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
f02a6bccdaee14ab55ad94263539f4f33f1b15bb,Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+f76a04bdc43f1e440b274b299b07ce2e423431e6,Face Recognition from Video: a Review,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+f7a91f74b0f8ac03459770bf4ba20af58a72a559,Visual Scan Paths and Recognition of Facial Identity in Autism Spectrum Disorder and Typical Development,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+f7bed3080668246b517a0c787698b53f67140a7d,Weighted Hausdorff Distance: A Loss Function For Object Localization,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
f781e50caa43be13c5ceb13f4ccc2abc7d1507c5,Towards Flexible and Intelligent Vision Systems -- From Thresholding to CHLAC --,National Institute of Advanced Industrial Science and Technology,National Institute of Advanced Industrial Science and Technology,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+f730990ad4f10e7ce09e7680b7864751787445dd,JointFlow : Temporal Flow Fields for Multi Person Pose Tracking,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
f7b4bc4ef14349a6e66829a0101d5b21129dcf55,Towards Light-weight Annotations: Fuzzy Interpolative Reasoning for Zero-shot Image Classificaiton,Newcastle University,Newcastle University,"Newcastle University, Claremont Walk, Haymarket, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE1 7RU, UK",54.98023235,-1.61452627,edu,
+f7e16e57b93b9dac11280427c7575a0a0ae4e0a8,Handcrafting vs Deep Learning: An Evaluation of NTraj+ Features for Pose Based Action Recognition,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
f7b422df567ce9813926461251517761e3e6cda0,Face aging with conditional generative adversarial networks,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
f7824758800a7b1a386db5bd35f84c81454d017a,KEPLER: Keypoint and Pose Estimation of Unconstrained Faces by Learning Efficient H-CNN Regressors,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+f74b62933362cce595ac247fc6f54ede68697d75,An Example-Based Two-Step Face Hallucination Method through Coefficient Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
f74917fc0e55f4f5682909dcf6929abd19d33e2e,Gan Quality Index (gqi) by Gan-induced Classifier,City University of New York,The City University of New York,"Lehman College of the City University of New York, 250, Bedford Park Boulevard West, Bedford Park, The Bronx, Bronx County, NYC, New York, 10468, USA",40.87228250,-73.89489171,edu,
f74917fc0e55f4f5682909dcf6929abd19d33e2e,Gan Quality Index (gqi) by Gan-induced Classifier,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
f74917fc0e55f4f5682909dcf6929abd19d33e2e,Gan Quality Index (gqi) by Gan-induced Classifier,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+f7040d2109cb42b373b1785ccb7a03faea824873,Human Detection in Video over Large Viewpoint Changes,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+f7040d2109cb42b373b1785ccb7a03faea824873,Human Detection in Video over Large Viewpoint Changes,"OMRON Corporation, Kyoto, Japan","Core Technology Center, OMRON Corporation, Kyoto, Japan","Kyoto, Kyoto Prefecture, Japan",35.01163630,135.76802940,company,
+f7ab8e56fc68575a0a5a94d315841f25630cf8a1,Exploiting Colour Information for Better Scene Text Recognition,Loughborough University,Loughborough University,"Computer Science, University Road, Charnwood, Leicestershire, East Midlands, England, LE11 3TP, UK",52.76635770,-1.22924610,edu,
+f7ab8e56fc68575a0a5a94d315841f25630cf8a1,Exploiting Colour Information for Better Scene Text Recognition,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+f7fdf862b7edeb5fd9d8fad7062c1f029b419769,Visual interpretability for deep learning: a survey,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+f73b7efa3bec07c582ec4e42fbc43a4f4993c6bb,Learning a Discriminative Feature Network for Semantic Segmentation,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+f73b7efa3bec07c582ec4e42fbc43a4f4993c6bb,Learning a Discriminative Feature Network for Semantic Segmentation,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
f78fe101b21be36e98cd3da010051bb9b9829a1e,Unsupervised Domain Adaptation for Facial Expression Recognition Using Generative Adversarial Networks,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
f78fe101b21be36e98cd3da010051bb9b9829a1e,Unsupervised Domain Adaptation for Facial Expression Recognition Using Generative Adversarial Networks,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+f726738954e7055bb3615fa7e8f59f136d3e0bdc,Are you eligible? Predicting adulthood from face images via class specific mean autoencoder,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
f7a271acccf9ec66c9b114d36eec284fbb89c7ef,Does attractiveness influence condom use intentions in heterosexual men? An experimental study,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
f7a271acccf9ec66c9b114d36eec284fbb89c7ef,Does attractiveness influence condom use intentions in heterosexual men? An experimental study,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
f7a271acccf9ec66c9b114d36eec284fbb89c7ef,Does attractiveness influence condom use intentions in heterosexual men? An experimental study,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
f7093b138fd31956e30d411a7043741dcb8ca4aa,Hierarchical Clustering in Face Similarity Score Space,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+f7ed39dec6e9060dc3dc58656ddf823916a2a643,Delta-encoder: an effective sample synthesis method for few-shot object recognition,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+f7ed39dec6e9060dc3dc58656ddf823916a2a643,Delta-encoder: an effective sample synthesis method for few-shot object recognition,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+f7943ecda36b38725efda73d68b7ea70272451b8,Superimposition-guided Facial Reconstruction from Skull,Louisiana State University,Louisiana State University,"LSU, Gourrier Avenue, Baton Rouge, East Baton Rouge Parish, Louisiana, 70803, USA",30.40550035,-91.18620474,edu,
+f7943ecda36b38725efda73d68b7ea70272451b8,Superimposition-guided Facial Reconstruction from Skull,Louisiana State University,Louisiana State University,"LSU, Gourrier Avenue, Baton Rouge, East Baton Rouge Parish, Louisiana, 70803, USA",30.40550035,-91.18620474,edu,
+f76dee0d19c9ee8d59466ad1e3bb91cae5a17ac5,Beyond bag of words: image representation in sub-semantic space,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+f76dee0d19c9ee8d59466ad1e3bb91cae5a17ac5,Beyond bag of words: image representation in sub-semantic space,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+f76dee0d19c9ee8d59466ad1e3bb91cae5a17ac5,Beyond bag of words: image representation in sub-semantic space,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f76dee0d19c9ee8d59466ad1e3bb91cae5a17ac5,Beyond bag of words: image representation in sub-semantic space,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+f76dee0d19c9ee8d59466ad1e3bb91cae5a17ac5,Beyond bag of words: image representation in sub-semantic space,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+f76dee0d19c9ee8d59466ad1e3bb91cae5a17ac5,Beyond bag of words: image representation in sub-semantic space,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
+f76dee0d19c9ee8d59466ad1e3bb91cae5a17ac5,Beyond bag of words: image representation in sub-semantic space,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+f759880a3314850d3a712bcd96494b62f60d5ece,Pigeonring: A Principle for Faster Thresholded Similarity Search,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+f759880a3314850d3a712bcd96494b62f60d5ece,Pigeonring: A Principle for Faster Thresholded Similarity Search,Nagoya University,Nagoya University,"SuperDARN (Hokkaido West), 太辛第1支線林道, 陸別町, 足寄郡, 十勝総合振興局, 北海道, 北海道地方, 日本",43.53750985,143.60768225,edu,
+f7a2424eb5af9613544a945772addcf2e19b5f92,Multi-view gait based human identification system with covariate analysis,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
f7c50d2be9fba0e4527fd9fbe3095e9d9a94fdd3,Large Margin Multi-metric Learning for Face and Kinship Verification in the Wild,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
f7c50d2be9fba0e4527fd9fbe3095e9d9a94fdd3,Large Margin Multi-metric Learning for Face and Kinship Verification in the Wild,"Advanced Digital Sciences Center, Singapore","Advanced Digital Sciences Center, Singapore","1 Create Way, 14-02 Create Tower, Singapore 138602",1.30372570,103.77377630,edu,
+f7af6fe6fb6393f7780163ae37c5931ce566daac,Synthetically Trained 3 D Visual Tracker of Underwater Vehicles,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+f7f1c57d38748d718309d7d55ce79e41d60f0940,Palmprint Recognition Using Deep Scattering Convolutional Network,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+f76808d6811cb3790e7fc3ddb08c733febbdefba,Robust Object Categorization and Segmentation Motivated by Visual Contexts in the Human Visual System,Yeungnam University,Yeungnam University,"영남대, 대학로, 부적리, 경산시, 경북, 712-749, 대한민국",35.83654030,128.75343090,edu,
+f7ac8523770b5965aadc27cb5364d77853113be4,Face Authentication Based on Multiple Profiles Extracted from Range Data,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+f775be87ca71180d1cf97d81678f4fd713343e01,Curriculum Learning for Multi-task Classification of Visual Attributes,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+f775be87ca71180d1cf97d81678f4fd713343e01,Curriculum Learning for Multi-task Classification of Visual Attributes,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
+f735188dbcb276cd1da248110712fde0d1b2aec7,Classification and clustering via dictionary learning with structured incoherence and shared features,University of Minnesota,University of Minnesota,"WeismanArt, 333, East River Parkway, Marcy-Holmes, Phillips, Minneapolis, Hennepin County, Minnesota, 55455, USA",44.97308605,-93.23708813,edu,
e82360682c4da11f136f3fccb73a31d7fd195694,Online Face Recognition with Application to Proactive Augmented Reality,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+e8391fd7ef979a63c389ab0fa7c00fe67e4498f8,Multiple object tracking with combinatorial model based on appearance and local features,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+e88b1040dc8a546f181fcd973227ae6121f15b70,Segmentation of Floors in Corridor Images for Mobile Robot Navigation,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
+e8096f4f625441ddb4914b17d1b9da3f80bae92e,Transfer Learning of Artist Group Factors to Musical Genre Classification,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+e8096f4f625441ddb4914b17d1b9da3f80bae92e,Transfer Learning of Artist Group Factors to Musical Genre Classification,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
+e8096f4f625441ddb4914b17d1b9da3f80bae92e,Transfer Learning of Artist Group Factors to Musical Genre Classification,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
+e8096f4f625441ddb4914b17d1b9da3f80bae92e,Transfer Learning of Artist Group Factors to Musical Genre Classification,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
e8f0f9b74db6794830baa2cab48d99d8724e8cb6,Active Image Labeling and Its Application to Facial Action Labeling,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
e8f0f9b74db6794830baa2cab48d99d8724e8cb6,Active Image Labeling and Its Application to Facial Action Labeling,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+e8875b317c2e0ed6fba0c908d599b3772a400bdd,Non-rigid 3D Shape Registration using an Adaptive Template,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
e87d6c284cdd6828dfe7c092087fbd9ff5091ee4,Unsupervised Creation of Parameterized Avatars,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+e8d8a42d0ee8849bbaf99c52cadeb2f1ebe564b0,Building Data-driven Models with Microstructural Images: Generalization and Interpretability,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
e8523c4ac9d7aa21f3eb4062e09f2a3bc1eedcf7,Toward End-to-End Face Recognition Through Alignment Learning,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
e85a255a970ee4c1eecc3e3d110e157f3e0a4629,Fusing Hierarchical Convolutional Features for Human Body Segmentation and Clothing Fashion Classification,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+e8327930af0c719e3084d0ffb284704888976515,Exemplar-SVMs for Action Recognition,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+e8327930af0c719e3084d0ffb284704888976515,Exemplar-SVMs for Action Recognition,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
e8c9dcbf56714db53063b9c367e3e44300141ff6,Get the FACS fast: Automated FACS face analysis benefits from the addition of velocity,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
e8c9dcbf56714db53063b9c367e3e44300141ff6,Get the FACS fast: Automated FACS face analysis benefits from the addition of velocity,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
e8c9dcbf56714db53063b9c367e3e44300141ff6,Get the FACS fast: Automated FACS face analysis benefits from the addition of velocity,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+e8d9f431ac20f0ef88291cf1b370fbbca028315a,Unravelling Robustness of Deep Learning Based Face Recognition Against Adversarial Attacks,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+e883cf759c3abecf59bf9f13053b1eb59bde01a6,Deep Multitask Attribute-driven Ranking for Fine-grained Sketch-based Image Retrieval,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+e86e2106dbedbb6d8b1195b77540971b9d58a198,Violent Behaviour Detection using Local Trajectory Response,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+e86e2106dbedbb6d8b1195b77540971b9d58a198,Violent Behaviour Detection using Local Trajectory Response,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+e8f9a45fdd76fa33855d9a7a6e70ff1821d0e2e1,Parametric surface denoising,Iowa State University,Iowa State University,"Iowa State University, Farm House Road, Ames, Story County, Iowa, 50014, USA",42.02791015,-93.64464415,edu,
e8b3a257a0a44d2859862cdec91c8841dc69144d,Liquid Pouring Monitoring via Rich Sensory Inputs,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
e8b3a257a0a44d2859862cdec91c8841dc69144d,Liquid Pouring Monitoring via Rich Sensory Inputs,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+e8ef22b6da1dd3a4e014b96e6073a7b610fd97ea,Faces as Lighting Probes via Unsupervised Deep Highlight Extraction,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+e8ef22b6da1dd3a4e014b96e6073a7b610fd97ea,Faces as Lighting Probes via Unsupervised Deep Highlight Extraction,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+e8ef22b6da1dd3a4e014b96e6073a7b610fd97ea,Faces as Lighting Probes via Unsupervised Deep Highlight Extraction,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+fae76d0e710545972807f18e45936ec5c6f1fe5d,RPIfield : A New Dataset for Temporally Evaluating Person Re-Identification ∗,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+faefb598a66284e31154251b94cdb3e1bda53122,Deep Transfer Network: Unsupervised Domain Adaptation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+faefb598a66284e31154251b94cdb3e1bda53122,Deep Transfer Network: Unsupervised Domain Adaptation,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+faabc70615649169b559403d7f15d45fca537cbd,HDFD - A High Deformation Facial Dynamics Benchmark for Evaluation of Non-Rigid Surface Registration and Classification,Swansea University,Swansea University,"Swansea University, University Footbridge, Sketty, Swansea, Wales, SA2 8PZ, UK",51.60915780,-3.97934429,edu,
+faabc70615649169b559403d7f15d45fca537cbd,HDFD - A High Deformation Facial Dynamics Benchmark for Evaluation of Non-Rigid Surface Registration and Classification,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+faabc70615649169b559403d7f15d45fca537cbd,HDFD - A High Deformation Facial Dynamics Benchmark for Evaluation of Non-Rigid Surface Registration and Classification,Swansea University,Swansea University,"Swansea University, University Footbridge, Sketty, Swansea, Wales, SA2 8PZ, UK",51.60915780,-3.97934429,edu,
+fa72b7140f9fa4fb975344109e597e9566c65f4a,Automatic 3D Face Recognition Using Discriminant Common Vectors,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+fa50b5a54aa340d6fe7f46feb02229f1ab0f12c0,Joint Image Captioning and Question Answering,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
fa90b825346a51562d42f6b59a343b98ea2e501a,Modeling Naive Psychology of Characters in Simple Commonsense Stories,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
fa90b825346a51562d42f6b59a343b98ea2e501a,Modeling Naive Psychology of Characters in Simple Commonsense Stories,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
faeefc5da67421ecd71d400f1505cfacb990119c,PastVision+: Thermovisual Inference of Recent Medicine Intake by Detecting Heated Objects and Cooled Lips,Halmstad University,Halmstad University,"Högskolan i Halmstad, 3, Kristian IV:s väg, Larsfrid, Nyhem, Halmstad, Hallands län, Götaland, 301 18, Sverige",56.66340325,12.87929727,edu,
faeefc5da67421ecd71d400f1505cfacb990119c,PastVision+: Thermovisual Inference of Recent Medicine Intake by Detecting Heated Objects and Cooled Lips,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
fa4f59397f964a23e3c10335c67d9a24ef532d5c,"DAP3D-Net: Where, what and how actions occur in videos?",Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+fa518a033b1f6299d1826389bd1520cf52291b56,Facial Age Simulation using Age-specific 3D Models and Recursive PCA,Cyprus University of Technology,Cyprus University of Technology,"Mitropoli Building - Cyprus University of Technology, Anexartisias, Limasol - Λεμεσός, Limassol - Λεμεσός, Κύπρος - Kıbrıs, 3036, Κύπρος - Kıbrıs",34.67567405,33.04577648,edu,
+fab04dfcb35a29a46504d2ad3acbc642c602c7e8,Trajectory-based 3 D Convolutional Descriptors for Action Recognition in Videos,Jiangsu University,Jiangsu University,"江苏大学, 301, 学府路, 京口区, 象山街道, 京口区 (Jingkou), 镇江市 / Zhenjiang, 江苏省, 212013, 中国",32.20302965,119.50968362,edu,
fab2fc6882872746498b362825184c0fb7d810e4,Right wing authoritarianism is associated with race bias in face detection,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+fabbebafe1f7b1680f66edc8b4fff345658a58c3,Face recognition by fusion of local and global matching scores using DS theory: An evaluation with uni-classifier and multi-classifier paradigm,Jadavpur University,Jadavpur University,"Jadavpur University, Chingrighata Flyover, Basani Devi Colony, Kolkata, Hāora, West Bengal, 700098, India",22.56115370,88.41310194,edu,
fac8cff9052fc5fab7d5ef114d1342daba5e4b82,Modeling Phase Spectra Using Gaussian Mixture Models for Human Face Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
fac8cff9052fc5fab7d5ef114d1342daba5e4b82,Modeling Phase Spectra Using Gaussian Mixture Models for Human Face Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
fac8cff9052fc5fab7d5ef114d1342daba5e4b82,Modeling Phase Spectra Using Gaussian Mixture Models for Human Face Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
fac8cff9052fc5fab7d5ef114d1342daba5e4b82,Modeling Phase Spectra Using Gaussian Mixture Models for Human Face Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
fac8cff9052fc5fab7d5ef114d1342daba5e4b82,Modeling Phase Spectra Using Gaussian Mixture Models for Human Face Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
faa29975169ba3bbb954e518bc9814a5819876f6,Evolution-Preserving Dense Trajectory Descriptors,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+fa747db22e9e6cd7a64019eec6e0dd53e94be4b3,DGPose: Disentangled Semi-supervised Deep Generative Models for Human Body Analysis,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+faef5bedb0b1e92730febce4e6af33b803bd463a,GANimation: Anatomically-Aware Facial Animation from a Single Image,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+fa5aca45965e312362d2d75a69312a0678fdf5d7,Fast and Accurate Head Pose Estimation via Random Projection Forests: Supplementary Material,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+fa33e20a3265d9a506c11a392cde9c367c30284e,Commonsense Justification for Action Explanation,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+fa4e709a7008248869584feca81250a8da8291e4,Biometric Quantization through Detection Rate Optimized Bit Allocation,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+fa9aabaa364732ddfb1d228cb8e93fa12c3bf52c,Facial Features Extraction based on Active Shape Model,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+fa9aabaa364732ddfb1d228cb8e93fa12c3bf52c,Facial Features Extraction based on Active Shape Model,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+fa9aabaa364732ddfb1d228cb8e93fa12c3bf52c,Facial Features Extraction based on Active Shape Model,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+faacebeb542792fae28745f51a943892be8d36a6,A Simple Yet Effective Baseline for 3d Human Pose Estimation,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+fa2d02343be1de448ac51c3a668c29f231b362f8,RAM: A Region-Aware Deep Model for Vehicle Re-Identification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+fa2d02343be1de448ac51c3a668c29f231b362f8,RAM: A Region-Aware Deep Model for Vehicle Re-Identification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
fae83b145e5eeda8327de9f19df286edfaf5e60c,Towards an Interactive E-learning System Based on Emotions and Affective Cognition,Ionian University,Ionian University,"Πανεπιστήμιο Πατρών, Λεωφ. Ιπποκράτους, κ. Ρίου (Αγίου Γεωργίου Ρίου), Πάτρα, Δήμος Πατρέων, Περιφερειακή Ενότητα Αχαΐας, Περιφέρεια Δυτικής Ελλάδας, Πελοπόννησος, Δυτική Ελλάδα και Ιόνιο, 26443, Ελλάδα",38.28994820,21.78864690,edu,
+fa3fb32fe0cd392960549b0adb7a535eb3656abd,The Devil is in the Middle: Exploiting Mid-level Representations for Cross-Domain Instance Matching,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+fa3fb32fe0cd392960549b0adb7a535eb3656abd,The Devil is in the Middle: Exploiting Mid-level Representations for Cross-Domain Instance Matching,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+fff755ee8522d5ab0931babeaded2f9113c44b95,A Hybrid Supervised-unsupervised Method on Image Topic Visualization with Convolutional Neural Network and LDA,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
ffea8775fc9c32f573d1251e177cd283b4fe09c9,Transformation on Computer-Generated Facial Image to Avoid Detection by Spoofing Detector,"National Institute of Informatics, Japan","National Institute of Informatics, Japan","2 Chome-1-２ Hitotsubashi, Chiyoda, Tokyo 100-0003, Japan",35.69248530,139.75825330,edu,
ffea8775fc9c32f573d1251e177cd283b4fe09c9,Transformation on Computer-Generated Facial Image to Avoid Detection by Spoofing Detector,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+fff32fd598e41ec6dd6903082d77f43f16908cfd,Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+ff9af51b07a7e80706361cd064a25d99cde64236,Prajna: Towards Recognizing Whatever You Want from Images without Image Labeling,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
ffc5a9610df0341369aa75c0331ef021de0a02a9,Transferred Dimensionality Reduction,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+ff948365684d3aa1a834deb49f326e264b56677a,"Animal, but not human, faces engage the distributed face network in adolescents with autism.",Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
ff061f7e46a6213d15ac2eb2c49d9d3003612e49,Morphable Human Face Modelling,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
ff1f45bdad41d8b35435098041e009627e60d208,"NAGRANI, ZISSERMAN: FROM BENEDICT CUMBERBATCH TO SHERLOCK HOLMES 1 From Benedict Cumberbatch to Sherlock Holmes: Character Identification in TV series without a Script",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+ff5a3b2fae2ee1cf4f1c32ff7e5fdccf72815578,Multi-Person Pose Estimation via Column Generation,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
+ff5a3b2fae2ee1cf4f1c32ff7e5fdccf72815578,Multi-Person Pose Estimation via Column Generation,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+ff5c698e1f451c7e6fc4f036fb79ba6ff899285f,Adaptive Unsupervised Multi-view Feature Selection for Visual Concept Recognition,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+ff5c698e1f451c7e6fc4f036fb79ba6ff899285f,Adaptive Unsupervised Multi-view Feature Selection for Visual Concept Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
ffe4bb47ec15f768e1744bdf530d5796ba56cfc1,AFIF4: Deep Gender Classification based on AdaBoost-based Fusion of Isolated Facial Features and Foggy Faces,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
ffe4bb47ec15f768e1744bdf530d5796ba56cfc1,AFIF4: Deep Gender Classification based on AdaBoost-based Fusion of Isolated Facial Features and Foggy Faces,Assiut University,Assiut University,"Assiut University, El Shaheed Ellwaa Hasn Kamel street, الوليدية, أسيوط, مصر",27.18794105,31.17009498,edu,
+ffc7de9e2519f54b0c843879013e24cb7ee2a2ac,A Hierarchical Generative Model for Eye Image Synthesis and Eye Gaze Estimation,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+ffe0f43206169deef3a2bf64cec90fe35bb1a8e5,"Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans +",Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+ffe0f43206169deef3a2bf64cec90fe35bb1a8e5,"Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans +",Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+ffe0f43206169deef3a2bf64cec90fe35bb1a8e5,"Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans +",University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+ff11cb09e409996020a2dc3a8afc3b535e6b2482,Faster Bounding Box Annotation for Object Detection in Indoor Scenes,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
ffaad0204f4af763e3390a2f6053c0e9875376be,Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining,Donghua University,Donghua University,"东华大学, 新华路, 长宁区, 上海市, 210011, 中国",31.20619390,121.41047101,edu,
ffaad0204f4af763e3390a2f6053c0e9875376be,Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+ff825a46f0a4e9f6ad748aeefd18f34f6b4addfb,"The ""reading the mind in films"" task: complex emotion recognition in adults with and without autism spectrum conditions.",Cambridge University,Cambridge University,"University, Cambridge Road, Old Portsmouth, Portsmouth, South East, England, PO1 2HB, UK",50.79440260,-1.09717480,edu,
fffa2943808509fdbd2fc817cc5366752e57664a,Combined Ordered and Improved Trajectories for Large Scale Human Action Recognition,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
fffa2943808509fdbd2fc817cc5366752e57664a,Combined Ordered and Improved Trajectories for Large Scale Human Action Recognition,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+ffd0ba45cc6b0c8f72a09617144786ffb26be771,Data-Free Knowledge Distillation for Deep Neural Networks,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+ffd0ba45cc6b0c8f72a09617144786ffb26be771,Data-Free Knowledge Distillation for Deep Neural Networks,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+ffd0ba45cc6b0c8f72a09617144786ffb26be771,Data-Free Knowledge Distillation for Deep Neural Networks,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+ffa4bbfc1981fb5c44b09fe22a38b91573814e11,A High Precision Feature Based on LBP and Gabor Theory for Face Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+ff311fbb5600234fd639c96522d1b450b6190cdd,AnchorNet: A Weakly Supervised Network to Learn Geometry-Sensitive Features for Semantic Matching,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+c5cad01443d4de135250d2784f0d070defd6120a,Large Graph Exploration via Subgraph Discovery and Decomposition,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+c5cad01443d4de135250d2784f0d070defd6120a,Large Graph Exploration via Subgraph Discovery and Decomposition,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+c5cad01443d4de135250d2784f0d070defd6120a,Large Graph Exploration via Subgraph Discovery and Decomposition,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+c5cad01443d4de135250d2784f0d070defd6120a,Large Graph Exploration via Subgraph Discovery and Decomposition,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
c5468665d98ce7349d38afb620adbf51757ab86f,Pose-Encoded Spherical Harmonics for Robust Face Recognition Using a Single Image,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+c5b6b81a75f7ec3211473eb1ca58897a6537a085,Exploiting Best Practice of Deep CNNs Features for National Costume Image Retrieval,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
c5d13e42071813a0a9dd809d54268712eba7883f,Face recognition robust to head pose changes based on the RGB-D sensor,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+c526f3e27c7d8ed5e07cf57ab378f17e1c548ebe,Learning Human Identity Using View-Invariant Multi-view Movement Representation,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+c5fcea39a6d3e0abdfcf15ff62cec0950813ed0a,Human Face Verification by Robust 3D Surface Alignment,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
c50d73557be96907f88b59cfbd1ab1b2fd696d41,Semiconductor sidewall shape estimation,Oak Ridge National Laboratory,Oak Ridge National Laboratory,"Oak Ridge National Laboratory, Oak Ridge, Roane County, Tennessee, USA",35.93006535,-84.31240032,edu,
+c51fb195bd9fe3b7d001179a3a39bb8252304f1b,A Survey of Advances in Biometric Gait Recognition,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+c595863b90b904a7b3197667b62efa16b0fd5ff6,Are Key-Foreign Key Joins Safe to Avoid when Learning High-Capacity Classifiers?,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+c595863b90b904a7b3197667b62efa16b0fd5ff6,Are Key-Foreign Key Joins Safe to Avoid when Learning High-Capacity Classifiers?,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+c5ee2621e5a0692677890df9a10963293ab14fc2,Feature Engineering for Knowledge Base Construction,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+c5ee2621e5a0692677890df9a10963293ab14fc2,Feature Engineering for Knowledge Base Construction,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+c5392bdc97e525403a38563ba19caef342879116,Multi-Instance Dynamic Ordinal Random Fields for Weakly-Supervised Pain Intensity Estimation,Universitat Pompeu Fabra,Universitat Pompeu Fabra,"Dipòsit de les Aigües, Carrer de Wellington, la Vila Olímpica del Poblenou, Ciutat Vella, Barcelona, BCN, CAT, 08071, España",41.39044285,2.18891949,edu,
+c5392bdc97e525403a38563ba19caef342879116,Multi-Instance Dynamic Ordinal Random Fields for Weakly-Supervised Pain Intensity Estimation,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+c5392bdc97e525403a38563ba19caef342879116,Multi-Instance Dynamic Ordinal Random Fields for Weakly-Supervised Pain Intensity Estimation,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+c5f71486c16add42c3394edb41b8c064b0123824,Ularized with a Unified Embedding,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+c5c4503a331b6fc09e01e66280a531bb9db0290d,Fast Bounding Box Estimation based Face Detection,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+c55b0bcd8081999f265468f87f281959bfc786f7,Extraction and Classification of Human Gait Features,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+c55b0bcd8081999f265468f87f281959bfc786f7,Extraction and Classification of Human Gait Features,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
c5935b92bd23fd25cae20222c7c2abc9f4caa770,Spatiotemporal Multiplier Networks for Video Action Recognition,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
c5935b92bd23fd25cae20222c7c2abc9f4caa770,Spatiotemporal Multiplier Networks for Video Action Recognition,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
c5935b92bd23fd25cae20222c7c2abc9f4caa770,Spatiotemporal Multiplier Networks for Video Action Recognition,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+c5ddfc020a3d1a4cb5d83c725a683f54a7bf7f1d,The processing of dynamic faces in the human brain : Support for an integrated neural framework of face processing,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+c5ddfc020a3d1a4cb5d83c725a683f54a7bf7f1d,The processing of dynamic faces in the human brain : Support for an integrated neural framework of face processing,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+c5ddfc020a3d1a4cb5d83c725a683f54a7bf7f1d,The processing of dynamic faces in the human brain : Support for an integrated neural framework of face processing,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+c5ddfc020a3d1a4cb5d83c725a683f54a7bf7f1d,The processing of dynamic faces in the human brain : Support for an integrated neural framework of face processing,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
c5421a18583f629b49ca20577022f201692c4f5d,Facial Age Classification using Subpattern-based Approaches,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
+c57579b067c1a5f5b764344d3c7df227eeba9155,"People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting",Dublin City University,DUBLIN CITY UNIVERSITY,"Dublin City University Glasnevin Campus, Lower Car Park, Wad, Whitehall A ED, Dublin 9, Dublin, County Dublin, Leinster, D09 FW22, Ireland",53.38522185,-6.25740874,edu,
c5be0feacec2860982fbbb4404cf98c654142489,Semi-Qualitative Probabilistic Networks in Computer Vision Problems,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
c5be0feacec2860982fbbb4404cf98c654142489,Semi-Qualitative Probabilistic Networks in Computer Vision Problems,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
c5be0feacec2860982fbbb4404cf98c654142489,Semi-Qualitative Probabilistic Networks in Computer Vision Problems,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
c5be0feacec2860982fbbb4404cf98c654142489,Semi-Qualitative Probabilistic Networks in Computer Vision Problems,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
c58b7466f2855ffdcff1bebfad6b6a027b8c5ee1,Ultra-Resolving Face Images by Discriminative Generative Networks,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+c5c1575565e04cd0afc57d7ac7f7a154c573b38f,Face Refinement through a Gradient Descent Alignment Approach,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+c5ba4e0a8abadb68b3de135e3da522059a99b2cd,Performance evaluation of the 1st and 2nd generation Kinect for multimedia applications,University of Padova,University of Padova,"Via Giovanni Gradenigo, 6, 35131 Padova PD, Italy",45.40811720,11.89437860,edu,"University of Padova, Via Gradenigo, 6 - 35131- Padova, Italy"
+c51fbd2574e488e486483e39702a3d7754cc769b,Face Recognition from Still Images to Video Sequences: A Local-Feature-Based Framework,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+c5ab6895710b5eb7bb783456421dab70684c017c,Instance Segmentation and Object Detection with Bounding Shape Masks,Ajou University,Ajou University,"아주대학교, 성호대교, 이의동, 영통구, 수원시, 경기, 16499, 대한민국",37.28300030,127.04548469,edu,
+c5ab6895710b5eb7bb783456421dab70684c017c,Instance Segmentation and Object Detection with Bounding Shape Masks,Ajou University,Ajou University,"아주대학교, 성호대교, 이의동, 영통구, 수원시, 경기, 16499, 대한민국",37.28300030,127.04548469,edu,
c5f1ae9f46dc44624591db3d5e9f90a6a8391111,Application of non-negative and local non negative matrix factorization to facial expression recognition,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
c53352a4239568cc915ad968aff51c49924a3072,Transfer Representation-Learning for Anomaly Detection,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
c53352a4239568cc915ad968aff51c49924a3072,Transfer Representation-Learning for Anomaly Detection,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+c563a1a197e8e9b5119063a8fd57fa5a7ca0da03,"Gaze cues in complex, real-world scenes direct the attention of high-functioning adults with autism",University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+c563a1a197e8e9b5119063a8fd57fa5a7ca0da03,"Gaze cues in complex, real-world scenes direct the attention of high-functioning adults with autism",University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+c563a1a197e8e9b5119063a8fd57fa5a7ca0da03,"Gaze cues in complex, real-world scenes direct the attention of high-functioning adults with autism",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+c28745625f048d86f2ad0f38a41ddc0683d36a96,"Looking, seeing and believing in autism: Eye movements reveal how subtle cognitive processing differences impact in the social domain.",University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+c28745625f048d86f2ad0f38a41ddc0683d36a96,"Looking, seeing and believing in autism: Eye movements reveal how subtle cognitive processing differences impact in the social domain.",University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
c2c5206f6a539b02f5d5a19bdb3a90584f7e6ba4,Affective Computing: A Review,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
c2fa83e8a428c03c74148d91f60468089b80c328,Optimal Mean Robust Principal Component Analysis,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+c29ca739fa740b3155c755655d590582305ef9a8,Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+c286b2539ce1cbc11338409062f0c28a37dbc4c0,Heterogeneous Multilayer Generalized Operational Perceptron Dat,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+c232d4989ad1bd9ee19d8309cf0fdec2a5c3895f,Point-Triplet Descriptors for 3D Facial Landmark Localisation,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+c2d102743e265d1b7c6073b087d030425786deb9,Time-varying-geometry Object Surveillance Using a Multi-camera Active-vision System,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+c268c0d62eac349468f786ac50342213ef7865e0,Visual Motif Discovery via First-Person Vision,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+c268c0d62eac349468f786ac50342213ef7865e0,Visual Motif Discovery via First-Person Vision,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+c2148f81ffffeaff3fed49448fa5485f65917865,Micro-Attention for Micro-Expression recognition,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+c2148f81ffffeaff3fed49448fa5485f65917865,Micro-Attention for Micro-Expression recognition,Southwest University,Southwest University,"西南大学, 天生路, 北碚区 (Beibei), 北碚区, 北碚区 (Beibei), 重庆市, 400711, 中国",29.82366295,106.42050016,edu,
+c2c058afe227f2099aae4f204688b22239d6837a,Threatening faces fail to guide attention for adults with autistic-like traits.,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+c2c058afe227f2099aae4f204688b22239d6837a,Threatening faces fail to guide attention for adults with autistic-like traits.,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+c2021ac068c23ba6a5360312fbfa0c0d2cfb47fd,Multi-modal fusion for flasher detection in a mobile video chat application,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
c23153aade9be0c941390909c5d1aad8924821db,Efficient and Accurate Tracking for Face Diarization via Periodical Detection,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
c207fd762728f3da4cddcfcf8bf19669809ab284,Face Alignment Using Boosting and Evolutionary Search,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
c207fd762728f3da4cddcfcf8bf19669809ab284,Face Alignment Using Boosting and Evolutionary Search,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
c207fd762728f3da4cddcfcf8bf19669809ab284,Face Alignment Using Boosting and Evolutionary Search,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+c2af954c89972a716968f97a67cc3841290937d3,Derivative Variation Pattern for Illumination-invariant Image Representation,Tafresh University,Tafresh University,"دانشگاه تفرش, پاسداران, خرازان, بخش مرکزی, شهرستان تفرش, استان مرکزی, ایران",34.68092465,50.05341352,edu,
+c2af954c89972a716968f97a67cc3841290937d3,Derivative Variation Pattern for Illumination-invariant Image Representation,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+c2d7bc19196dd4a7ed1a08d60081d16e0c14f463,Gated Fusion Network for Joint Image Deblurring and Super-Resolution,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+c2d054f0d7f455d94f1d92959e0e549443977c55,SdcNet: A Computation-Efficient CNN for Object Recognition,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
+c2d054f0d7f455d94f1d92959e0e549443977c55,SdcNet: A Computation-Efficient CNN for Object Recognition,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
c2e03efd8c5217188ab685e73cc2e52c54835d1a,Deep tree-structured face: A unified representation for multi-task facial biometrics,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
c28461e266fe0f03c0f9a9525a266aa3050229f0,Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models,Universitat Oberta de Catalunya,Universitat Oberta de Catalunya,"Universitat Oberta de Catalunya, 156, Rambla del Poblenou, Provençals del Poblenou, Sant Martí, Barcelona, BCN, CAT, 08018, España",41.40657415,2.19453410,edu,
+c2fafcbbf334447e8e3a18a2339eaff63ed2b4e3,Gamma Activation in Young People with Autism Spectrum Disorders and Typically-Developing Controls When Viewing Emotions on Faces,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+c2fafcbbf334447e8e3a18a2339eaff63ed2b4e3,Gamma Activation in Young People with Autism Spectrum Disorders and Typically-Developing Controls When Viewing Emotions on Faces,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+c2b3bf311a9182b1452f5ade82fb6db6263e2ddc,Metric Learning-based Generative Adversarial Network,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+c2be88c6d99605abca7a7377935c8809eb8d328e,Open Set Chinese Character Recognition using Multi-typed Attributes,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+c253694c153cc016d745df089bae0220e7f297ee,Image Retrieval with Mixed Initiative and Multimodal Feedback,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
f60a85bd35fa85739d712f4c93ea80d31aa7de07,VisDA: The Visual Domain Adaptation Challenge,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
f60a85bd35fa85739d712f4c93ea80d31aa7de07,VisDA: The Visual Domain Adaptation Challenge,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+f6c814f6efff8031b9ebc62cdf0f3b343441e7d3,XOGAN: One-to-Many Unsupervised Image-to-Image Translation,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
f69de2b6770f0a8de6d3ec1a65cb7996b3c99317,Face Recognition System Based on Sparse Codeword Analysis,Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
+f68263a6f541429a8645ca2f4b0658cdbbd66638,Setting a world record in 3D Face Recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+f61b4aa14b052e143db302402cf976ee93cb4eee,Real-time Semantic Image Segmentation via Spatial Sparsity,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+f678f31e7bb5eda34098b0fed608cfad5e372509,Discriminative Kernel Feature Extraction and Learning for Object Recognition and Detection,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+f65c03004e3b2ef4b4224396f7a31ee75a252d85,End-to-End Multi-Task Learning with Attention,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+f68255269d509ff617c2532bd2da71edf9576efc,New chaff point based fuzzy vault for multimodal biometric cryptosystem using particle swarm optimization,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
f6149fc5b39fa6b33220ccee32a8ee3f6bbcaf4a,Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+f69a289a3bc6b61c612ba6ff4033f122100daccb,Morphing between expressions dissociates continuous from categorical representations of facial expression in the human brain.,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f,Swiss-System Based Cascade Ranking for Gait-Based Person Re-Identification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
f66f3d1e6e33cb9e9b3315d3374cd5f121144213,Top-down control of visual responses to fear by the amygdala.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
-f61d5f2a082c65d5330f21b6f36312cc4fab8a3b,Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+f6c7f1cbfa412fb6244992b7fb2eda0a9e0d933e,Expertise Moderates Incidentally Learned Associations Between Words and Images,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+f6c7f1cbfa412fb6244992b7fb2eda0a9e0d933e,Expertise Moderates Incidentally Learned Associations Between Words and Images,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+f6c7f1cbfa412fb6244992b7fb2eda0a9e0d933e,Expertise Moderates Incidentally Learned Associations Between Words and Images,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+f6c7f1cbfa412fb6244992b7fb2eda0a9e0d933e,Expertise Moderates Incidentally Learned Associations Between Words and Images,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+f6c7f1cbfa412fb6244992b7fb2eda0a9e0d933e,Expertise Moderates Incidentally Learned Associations Between Words and Images,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+f6c7f1cbfa412fb6244992b7fb2eda0a9e0d933e,Expertise Moderates Incidentally Learned Associations Between Words and Images,Bielefeld University,Bielefeld University,"Fachhochschule Bielefeld FB Gestaltung, 3, Lampingstraße, Mitte, Bielefeld, Regierungsbezirk Detmold, Nordrhein-Westfalen, 33615, Deutschland",52.02804210,8.51148270,edu,
+f611f46455ed6ad9af85eeb22e294082dced9bed,Learning of Visual Attribute Clusters for MultiTask Classification,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+f611f46455ed6ad9af85eeb22e294082dced9bed,Learning of Visual Attribute Clusters for MultiTask Classification,University of Ioannina,University of Ioannina,"Πανεπιστήμιο Ιωαννίνων, Πανεπιστημίου, Κάτω Νεοχωρόπουλο, Νεοχωρόπουλο, Δήμος Ιωαννιτών, Π.Ε. Ιωαννίνων, Περιφέρεια Ηπείρου, Ήπειρος - Δυτική Μακεδονία, 45110, Ελλάδα",39.61623060,20.83963011,edu,
+f61d5f2a082c65d5330f21b6f36312cc4fab8a3b,Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+f62d71e701c9fd021610e2076b5e0f5b2c7c86ca,Mahalanobis Distance Learning for Person Re-identification,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+f6328f02ab64c992d76967dbfd1a66d325173723,Mel- and Mellin-cepstral Feature Extraction Algorithms for Face Recognition,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+f6ff469fc4b3043530f64e8642ed822d119b42c9,"SeDAR - Semantic Detection and Ranging: Humans can Localise without LiDAR, can Robots?",University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+f6ff469fc4b3043530f64e8642ed822d119b42c9,"SeDAR - Semantic Detection and Ranging: Humans can Localise without LiDAR, can Robots?",University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+f6ff469fc4b3043530f64e8642ed822d119b42c9,"SeDAR - Semantic Detection and Ranging: Humans can Localise without LiDAR, can Robots?",University of Exeter,University of Exeter,"University of Exeter, Stocker Road, Exwick, Exeter, Devon, South West England, England, EX4 4QN, UK",50.73693020,-3.53647672,edu,
+f6ff469fc4b3043530f64e8642ed822d119b42c9,"SeDAR - Semantic Detection and Ranging: Humans can Localise without LiDAR, can Robots?",University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+f632790471b2bed7ba7c28b12cda9360ec586a63,Deep Binaries: Encoding Semantic-Rich Cues for Efficient Textual-Visual Cross Retrieval,University of East Anglia,University of East Anglia,"Arts (Lower Walkway Level), The Square, Westfield View, Earlham, Norwich, Norfolk, East of England, England, NR4 7TJ, UK",52.62215710,1.24091360,edu,
+f632790471b2bed7ba7c28b12cda9360ec586a63,Deep Binaries: Encoding Semantic-Rich Cues for Efficient Textual-Visual Cross Retrieval,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+f6f12e0fbfce067d02445abde76be0522e4db329,Online Multiple targets Detection and Tracking from Mobile robot in Cluttered indoor Environments with Depth Camera,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+f6f12e0fbfce067d02445abde76be0522e4db329,Online Multiple targets Detection and Tracking from Mobile robot in Cluttered indoor Environments with Depth Camera,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+f6ef7200c08170aa1bf68a2fafed10bb4296c595,Towards Understanding End-of-trip Instructions in a Taxi Ride Scenario,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+f6c7fbd84e6ac61af40e670e589ec52fa435f396,An Automated System for Garment Texture Design Class Identification,Institute of Information Technology,Institute of Information Technology,"Institute of Information Technology, Sir Sayed Road, ফকিরাপুল, সিদ্দিক বাজার, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.72898990,90.39826820,edu,
f6e00d6430cbbaa64789d826d093f7f3e323b082,Visual Object Recognition,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
f6e00d6430cbbaa64789d826d093f7f3e323b082,Visual Object Recognition,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+e9b8f2ee742b32ae272c950cc6fa2d5a2d05f028,Hourglass-ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery,Vrije Universiteit Brussel,Vrije Universiteit Brussel,"Vrije Universiteit Brussel, 170, Quai de l'Industrie - Nijverheidskaai, Anderlecht, Brussel-Hoofdstad - Bruxelles-Capitale, Région de Bruxelles-Capitale - Brussels Hoofdstedelijk Gewest, 1070, België / Belgique / Belgien",50.84110070,4.32377555,edu,
+e9b8f2ee742b32ae272c950cc6fa2d5a2d05f028,Hourglass-ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
e9a5a38e7da3f0aa5d21499149536199f2e0e1f7,A Bayesian Scene-Prior-Based Deep Network Model for Face Verification,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
e9a5a38e7da3f0aa5d21499149536199f2e0e1f7,A Bayesian Scene-Prior-Based Deep Network Model for Face Verification,Curtin University,Curtin University,"Curtin University, Brand Drive, Waterford, Perth, Western Australia, 6102, Australia",-32.00686365,115.89691775,edu,
+e94dfdc5581f6bc0338e21ad555b5f1734f8697e,Learning to Anonymize Faces for Privacy Preserving Action Detection,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+e9f82ce15b332767c0d9e6326e46bdd6a15fc689,Deep Low-Resolution Person Re-Identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+e9f82ce15b332767c0d9e6326e46bdd6a15fc689,Deep Low-Resolution Person Re-Identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+e9f82ce15b332767c0d9e6326e46bdd6a15fc689,Deep Low-Resolution Person Re-Identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+e97d824b8e80670d49d53c402f99e0fbeaafacdb,Neural Best-Buddies: Sparse Cross-Domain Correspondence,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+e97d824b8e80670d49d53c402f99e0fbeaafacdb,Neural Best-Buddies: Sparse Cross-Domain Correspondence,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+e97d824b8e80670d49d53c402f99e0fbeaafacdb,Neural Best-Buddies: Sparse Cross-Domain Correspondence,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+e97d824b8e80670d49d53c402f99e0fbeaafacdb,Neural Best-Buddies: Sparse Cross-Domain Correspondence,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+e912481d2d885244b1c72e5d74932429394a5789,Adaptive Appearance Rendering,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+e90a925fea8456718527a73a3621fba9b848de28,D Eep L Earning with S Ets and P Oint C Louds,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
e90e12e77cab78ba8f8f657db2bf4ae3dabd5166,Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
e90e12e77cab78ba8f8f657db2bf4ae3dabd5166,Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
e90e12e77cab78ba8f8f657db2bf4ae3dabd5166,Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+e9c7d47fb82de9b71bdde1ad9b81eb2b2970b8fa,DarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+e985e7ec130ce4552222d7fb4b2d2f923fd2a501,Orthogonal and Idempotent Transformations for Learning Deep Neural Networks,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+e985e7ec130ce4552222d7fb4b2d2f923fd2a501,Orthogonal and Idempotent Transformations for Learning Deep Neural Networks,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+e902bad28f1370d5252e44fe4b7d0563aa9a2383,Let Features Decide for Themselves: Feature Mask Network for Person Re-identification,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
e9c008d31da38d9eef67a28d2c77cb7daec941fb,Noisy Softmax: Improving the Generalization Ability of DCNN via Postponing the Early Softmax Saturation,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
e9c008d31da38d9eef67a28d2c77cb7daec941fb,Noisy Softmax: Improving the Generalization Ability of DCNN via Postponing the Early Softmax Saturation,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+e9f4624cc9c2d7e1b9fa2545982e7678b9a5aaae,Dynamic-structured Semantic Propagation Network,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+e9ccd438d6d55ba0d11a63eb95c773d63b3ea4e5,Will you remember me ? Cultural differences in own-group face recognition biases ☆,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
e9e40e588f8e6510fa5537e0c9e083ceed5d07ad,Fast Face Detection Using Graphics Processor,"National Institute of Technology, Karnataka",National Institute of Technology Karnataka,"National Institute of Technology, Karnataka, NH66, ದಕ್ಷಿಣ ಕನ್ನಡ, Mangaluru taluk, Dakshina Kannada, Karnataka, 575025, India",13.01119095,74.79498825,edu,
+e996da9beadff6f6694540c6b1794312f814dbae,Age and gender classification from ear images,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
+e959a426d02dd014c1346131ac38ed50114c17b7,A Focused Dynamic Attention Model for Visual Question Answering,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+e9e39e31419d9a22790b327bc1d6107fa832bdab,Face recognition using adaptively weighted patch PZM array from a single exemplar image per person,Griffith University,Griffith University,"Griffith University Nathan Campus, Johnson Path, Nathan, Nathan Heights, QLD, 4111, Australia",-27.55339750,153.05336234,edu,
+e90e23a757c346170df4f403d0c18bcea2874ed7,Conditional Inference in Pre-trained Variational Autoencoders via Cross-coding,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+e90e23a757c346170df4f403d0c18bcea2874ed7,Conditional Inference in Pre-trained Variational Autoencoders via Cross-coding,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
e9bb045e702ee38e566ce46cc1312ed25cb59ea7,Integrating Geometric and Textural Features for Facial Emotion Classification Using SVM Frameworks,Indian Institute of Technology Roorkee,"Indian Institute of Technology, Roorkee","Indian Institute of Technology (IIT), Roorkee, LBS Jogging Track, Roorkee, Haridwar, Uttarakhand, 247667, India",29.86624610,77.89587081,edu,
e9bb045e702ee38e566ce46cc1312ed25cb59ea7,Integrating Geometric and Textural Features for Facial Emotion Classification Using SVM Frameworks,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+e984017c5849ea78e3f50e374a5539770989536d,Bilinear Discriminant Analysis for Face Recognition,École Centrale de Lyon,Laboratoire LIRIS,"40 Avenue Guy de Collongue, 69130 Écully, France",45.78359660,4.76789480,edu,
+e9835bb131287d711e5e5435a5df8ce5302acb31,Person Re-identification by Unsupervised `1 Graph Learning,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+e9c2b7677660820019ac5fe0fff9ac3409555b63,Multi-Entity Bayesian Networks for Knowledge-Driven Analysis of ICH Content,Information Technologies Institute,Information Technologies Institute,"公益財団法人九州先端科学技術研究所, Fukuoka SRP Center Building 7F, 百道ランプ下り入り口, 早良区, 福岡市, 福岡県, 九州地方, 814-0001, 日本",33.59345390,130.35578370,edu,
+e9bbe558c73de60e40ce2bd8c7cb7a47dacfe594,Can White children grow up to be Black? Children's reasoning about the stability of emotion and race.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+e9bbe558c73de60e40ce2bd8c7cb7a47dacfe594,Can White children grow up to be Black? Children's reasoning about the stability of emotion and race.,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+e9bb5cf8eca585fb1b5b7e3ade05937cbb3ee040,Toward image-based facial hair modeling,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+e9bb5cf8eca585fb1b5b7e3ade05937cbb3ee040,Toward image-based facial hair modeling,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+e9bb5cf8eca585fb1b5b7e3ade05937cbb3ee040,Toward image-based facial hair modeling,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+e9ba629fd9533131735e2305929faf0c2c46538b,Holistic and Feature-based Information Towards Dynamic Multi-expressions Recognition,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+e93a65ff1c7c29736cef5701f079f75ecfb76f5f,From image statistics to scene gist: evoked neural activity reveals transition from low-level natural image structure to scene category.,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
e9f1cdd9ea95810efed306a338de9e0de25990a0,FEPS: An Easy-to-Learn Sensory Substitution System to Perceive Facial Expressions,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
e9f1cdd9ea95810efed306a338de9e0de25990a0,FEPS: An Easy-to-Learn Sensory Substitution System to Perceive Facial Expressions,University of Memphis,University of Memphis,"The University of Memphis, Desoto Avenue, Memphis, Shelby County, Tennessee, 38152, USA",35.11893870,-89.93721960,edu,
+e97f4151b67e0569df7e54063d7c198c911edbdc,A New Information Fusion Method for Bimodal Robotic Emotion Recognition,National Chiao Tung University,National Chiao Tung University,"NCTU;交大;交通大學;交大光復校區;交通大學光復校區, 1001, 大學路, 光明里, 赤土崎, 東區, 新竹市, 30010, 臺灣",24.78676765,120.99724412,edu,
f1250900074689061196d876f551ba590fc0a064,Learning to Recognize Actions From Limited Training Examples Using a Recurrent Spiking Neural Model,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+f1a772608cae0d3189ad1293d5b7631435f02e44,Saliency-based Bayesian modeling of dynamic viewing of static scenes,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
f1b4583c576d6d8c661b4b2c82bdebf3ba3d7e53,Faster than Real-Time Facial Alignment: A 3D Spatial Transformer Network Approach in Unconstrained Poses,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+f1368b0001e454381eafc35324740c928cb2ad1e,Automated audio captioning with recurrent neural networks,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+f1278b44acc73b41c2993574392047f8d10e997f,Skeleton-Based Pose Estimation of Human Figures Dual Degree Project Report,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+f193ca76a878af87603ae8ac823a3e6d1c2e3c7e,Recurrent Multi-frame Single Shot Detector for Video Object Detection,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+f14872986435c015c562a92c6c0d142bbdf1b1fb,Action Completion: A Temporal Model for Moment Detection,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+f187b0ed2224b2861442a73ad2966c1789afc09a,Zero-Shot Learning via Revealing Data Distribution,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+f187b0ed2224b2861442a73ad2966c1789afc09a,Zero-Shot Learning via Revealing Data Distribution,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+f1cec5f837638efd8fd592cf5493f33ed1fb6995,Learning to detect violent videos using convolutional long short-term memory,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+f179f7888934b11dc5a2d8ff9205d1ca8b8a1599,Illuminant direction estimation for a single image based on local region complexity analysis and average gray value.,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+f10ddad356ac9376e8c982f96cead7f6bdee3251,Riemannian Set-level Common-Near-Neighbor Analysis for Multiple-shot Person Re-identification,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+f10ddad356ac9376e8c982f96cead7f6bdee3251,Riemannian Set-level Common-Near-Neighbor Analysis for Multiple-shot Person Re-identification,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+f1d3fee0a4dbd4cd30195d1218423bf22e23286d,Asking Friendly Strangers: Non-Semantic Attribute Transfer,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+f1245d318eb3d775e101355f5f085a9bc4a0339b,Face Verification with Disguise Variations via Deep Disguise,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+f106ff6b2dd497650e7e2096b24a23d620a2306b,Toward A Deep Understanding of What Makes a Scientific Visualization Memorable,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+f153cbec29d86a58b5f15231fd14e7037a210682,Lost in the categorical shuffle: evidence for the social non-prototypicality of black women.,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+f153cbec29d86a58b5f15231fd14e7037a210682,Lost in the categorical shuffle: evidence for the social non-prototypicality of black women.,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+f147057dfe4bbb4f9499de432cb2393547f2f339,CNN-based Facial Affect Analysis on Mobile Devices,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+f147057dfe4bbb4f9499de432cb2393547f2f339,CNN-based Facial Affect Analysis on Mobile Devices,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+f121154f0a7625fbb1613bd4cc2e705f9de8fd0c,Boosted Regression Active Shape Models,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+f1a62862bf3ab26588f880ec8d6f04d14b6cc2e7,FADA: An Efficient Dimension Reduction Scheme for Image Classification,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+f1a62862bf3ab26588f880ec8d6f04d14b6cc2e7,FADA: An Efficient Dimension Reduction Scheme for Image Classification,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+f110f7be74261469fe9b0cc5a3b4ef35e2092d5b,Somatosensory Representations Link the Perception of Emotional Expressions and Sensory Experience123,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+f15b8efe8b9511207bb1261e218a54bcfa20349b,Sparse analysis model based dictionary learning and signal reconstruction,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+f15b8efe8b9511207bb1261e218a54bcfa20349b,Sparse analysis model based dictionary learning and signal reconstruction,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+f1ac9370bdf4c408fdc242719cceb3eae19b9a16,Face Recognition after Plastic Surgery: A Comprehensive Study,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+f1ac9370bdf4c408fdc242719cceb3eae19b9a16,Face Recognition after Plastic Surgery: A Comprehensive Study,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+e78fdd62f67c38fcc6ac1421f045c9437f352b86,Deep Imbalanced Attribute Classification Using Visual Attention Aggregation,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+e79bfb8dc4ebbdeb971545bd31ffc1392ea0ad4c,Action Recognition with Exemplar Based 2.5D Graph Matching,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+e78042d77765c0fd3c09651b679e15ffd6b7e8a1,Optimized Projection for Sparse Representation Based Classification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+e78042d77765c0fd3c09651b679e15ffd6b7e8a1,Optimized Projection for Sparse Representation Based Classification,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
e793f8644c94b81b7a0f89395937a7f8ad428a89,LPM for Action Recognition in Temporally Untrimmed Videos,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
e726174d516605f80ff359e71f68b6e8e6ec6d5d,3D Face Recognition Using Patched Locality Preserving Projections,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
e726174d516605f80ff359e71f68b6e8e6ec6d5d,3D Face Recognition Using Patched Locality Preserving Projections,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+e771661fa441f008c111ea786eb275153919da6e,Globally Optimal Object Tracking with Fully Convolutional Networks,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+e73a14bbf3d00fb72b710b6c62639d65bf4ee415,Scheduling and Tuning for Low Energy in Heterogeneous and Configurable Multicore Systems,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+e73a14bbf3d00fb72b710b6c62639d65bf4ee415,Scheduling and Tuning for Low Energy in Heterogeneous and Configurable Multicore Systems,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+e7bd805c001e04b3c015b7ec11497cd5247a1a77,Facial Component Extraction and Face Recognition with Support Vector Machines,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+e7397f7f0e83494825d63b75bdd40c3879f369cd,Open-world Person Re-Identification by Multi-Label Assignment Inference,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
e7b2b0538731adaacb2255235e0a07d5ccf09189,Learning Deep Representations with Probabilistic Knowledge Transfer,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
e74816bc0803460e20edbd30a44ab857b06e288e,Semi-Automated Annotation of Discrete States in Large Video Datasets,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
e74816bc0803460e20edbd30a44ab857b06e288e,Semi-Automated Annotation of Discrete States in Large Video Datasets,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+e7a922049a9bf54a0b13cd1d475a58e36c7c9b3e,The conceptual structure of face impressions.,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+e7a922049a9bf54a0b13cd1d475a58e36c7c9b3e,The conceptual structure of face impressions.,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+e7a922049a9bf54a0b13cd1d475a58e36c7c9b3e,The conceptual structure of face impressions.,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+e762f25f13d6dbb95dc59af5e6fbb2160fcf4d55,Zero-Shot Detection,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
e73b9b16adcf4339ff4d6723e61502489c50c2d9,Anefficient Featureextractionmethodwith Localregionzernikemoment for Facial Recognition of Identicaltwins,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
e73b9b16adcf4339ff4d6723e61502489c50c2d9,Anefficient Featureextractionmethodwith Localregionzernikemoment for Facial Recognition of Identicaltwins,Azad University,Azad University,"پل دانشگاه آزاد, باراجین, پونک ۳, قزوین, بخش مرکزی, شهرستان قزوین, استان قزوین, ایران",36.31734320,50.03672860,edu,
+e7a8549865978b478699647bd259f71c516c4479,Multiple People Tracking-by-Detection in a Multi-camera Environment,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+cb985b696085fdfdc664c74114b841d58382397c,Recurrent Scene Parsing with Perspective Understanding in the Loop,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+cb522158aa3c91fda3089d152b0005605056852b,3D Face Recognition Using Anthropometric and Curvelet Features Fusion,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
+cb522158aa3c91fda3089d152b0005605056852b,3D Face Recognition Using Anthropometric and Curvelet Features Fusion,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
+cb1e34d7fcb7fae914fcb65cb9cf25199d49cec9,SLAQ: quality-driven scheduling for distributed machine learning,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
cbbd13c29d042743f0139f1e044b6bca731886d0,Not-So-CLEVR: learning same-different relations strains feedforward neural networks.,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
cba45a87fc6cf12b3b0b6f57ba1a5282ef7fee7a,"Emotion AI, Real-Time Emotion Detection using CNN",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
cba45a87fc6cf12b3b0b6f57ba1a5282ef7fee7a,"Emotion AI, Real-Time Emotion Detection using CNN",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+cba130014e6cc590a09aaeca0590623b496f126b,HeteroVisor: Exploiting Resource Heterogeneity to Enhance the Elasticity of Cloud Platforms,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+cbf69bc3e4c9b7d8cd33be81686d45f6a5f2d544,Mouth Region Localization based on Gabor Features and Active Appearance Models,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+cbf69bc3e4c9b7d8cd33be81686d45f6a5f2d544,Mouth Region Localization based on Gabor Features and Active Appearance Models,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+cbf69bc3e4c9b7d8cd33be81686d45f6a5f2d544,Mouth Region Localization based on Gabor Features and Active Appearance Models,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+cb0c9a9882d8c3ef86cc8747b6ff8d68579dec61,Computer-Aided Detection of Acinar Shadows in Chest Radiographs,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+cb0c9a9882d8c3ef86cc8747b6ff8d68579dec61,Computer-Aided Detection of Acinar Shadows in Chest Radiographs,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+cb0c9a9882d8c3ef86cc8747b6ff8d68579dec61,Computer-Aided Detection of Acinar Shadows in Chest Radiographs,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
cb2917413c9b36c3bb9739bce6c03a1a6eb619b3,MiCT: Mixed 3D/2D Convolutional Tube for Human Action Recognition,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+cbb141925e919aef18f9168b79b4c4aeb871ccff,A Study Of Statistical Methods For Facial Shape-from-shading,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
cb13e29fb8af6cfca568c6dc523da04d1db1fff5,"A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges",Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
cb13e29fb8af6cfca568c6dc523da04d1db1fff5,"A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges",Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
cb13e29fb8af6cfca568c6dc523da04d1db1fff5,"A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges",University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
cb13e29fb8af6cfca568c6dc523da04d1db1fff5,"A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges",Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
cb13e29fb8af6cfca568c6dc523da04d1db1fff5,"A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges",Monash University Malaysia,Monash University Malaysia,"Monash University Malaysia, Jalan Lagoon Selatan, Kampung Lembah Kinrara, SS13, Subang Jaya, Selangor, 47500, Malaysia",3.06405715,101.60059740,edu,
+cb2bbc19ba323ac8a7d0530fb605462c8e608e1d,Concept Mask: Large-Scale Segmentation from Semantic Concepts,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+cb5dcd048b0eaa78a887a014be26a8a7b1325d36,Joint Learning of Set Cardinality and State Distribution,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
cb1b5e8b35609e470ce519303915236b907b13b6,On the vulnerability of ECG verification to online presentation attacks,University of Connecticut,University of Connecticut,"University of Connecticut, Glenbrook Road, Storrs, Tolland County, Connecticut, 06269, USA",41.80937790,-72.25364140,edu,
cb1b5e8b35609e470ce519303915236b907b13b6,On the vulnerability of ECG verification to online presentation attacks,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
-cbb27980eb04f68d9f10067d3d3c114efa9d0054,An Attention Model for group-level emotion recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
-cbb27980eb04f68d9f10067d3d3c114efa9d0054,An Attention Model for group-level emotion recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
-cbb27980eb04f68d9f10067d3d3c114efa9d0054,An Attention Model for group-level emotion recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+cb5ea214f4a3ddd50e821efea003340a8036408c,Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism,Huaqiao University,Huaqiao University,"华侨大学站 HuaQiao University (BRT), 集美大道, 集美区, 集美区 (Jimei), 厦门市 / Xiamen, 福建省, 361024, 中国",24.60047120,118.08165740,edu,
+cbb27980eb04f68d9f10067d3d3c114efa9d0054,An Attention Model for Group-Level Emotion Recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+cbb27980eb04f68d9f10067d3d3c114efa9d0054,An Attention Model for Group-Level Emotion Recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+cbb27980eb04f68d9f10067d3d3c114efa9d0054,An Attention Model for Group-Level Emotion Recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+cba3061a883cdfb45c6d26fdee7dd53e6614d388,Per-patch Descriptor Selection Using Surface and Scene Properties,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+cb9057a47f6d3367a6756507ceb1b1f9b596eb7a,Fearful faces have a sensory advantage in the competition for awareness.,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+cb9057a47f6d3367a6756507ceb1b1f9b596eb7a,Fearful faces have a sensory advantage in the competition for awareness.,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+cb9057a47f6d3367a6756507ceb1b1f9b596eb7a,Fearful faces have a sensory advantage in the competition for awareness.,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+cb3010ae04bb144b49eb0c1061b695998d3a7441,Scene Parsing with Global Context Embedding,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+cba8b9949e71ff485a4ecba33128e2f206651cac,An RGBD segmentation model for robot vision learned from synthetic data,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+cbe1a5b67c1d19aa1fca10473c6e88b4a444f77b,MCGraph: multi-criterion representation for scene understanding,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
f86ddd6561f522d115614c93520faad122eb3b56,Visual Imagination from Texts,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+f8bebca34cc787dd2652deb182cf66d346d06094,Local Response Context Applied to Pedestrian Detection,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
+f8bebca34cc787dd2652deb182cf66d346d06094,Local Response Context Applied to Pedestrian Detection,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+f8809a55945c283d249f4c4adb5d74e452cdfaa0,Being Negative but Constructively: Lessons Learnt from Creating Better Visual Question Answering Datasets,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
f8015e31d1421f6aee5e17fc3907070b8e0a5e59,Towards Usable Multimedia Event Detection from Web Videos,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
f83dd9ff002a40228bbe3427419b272ab9d5c9e4,Facial Features Matching using a Virtual Structuring Element,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+f8beb25e944004d283e1b347e3473089da244335,Diminished Medial Prefrontal Activity behind Autistic Social Judgments of Incongruent Information,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+f8beb25e944004d283e1b347e3473089da244335,Diminished Medial Prefrontal Activity behind Autistic Social Judgments of Incongruent Information,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+f8beb25e944004d283e1b347e3473089da244335,Diminished Medial Prefrontal Activity behind Autistic Social Judgments of Incongruent Information,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+f8daab1e4f63051b78eb43e98ab723f6c425a6b5,Speaker Naming in Movies,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
f8f2d2910ce8b81cb4bbf84239f9229888158b34,A Generative Model for Recognizing Mixed Group Activities in Still Images,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+f8599ad5332cdf2c9919988ba300bb4b438b5834,Transitive Invariance for Self-Supervised Visual Representation Learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+f832fdf1fac092b4140bf81d38e6bc6af5c1ea65,Instance-Level Human Parsing via Part Grouping Network,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+f88a0f44ff7ec5fe0facf0facac0a094c7bd6cb8,Augmenting Image Question Answering Dataset by Exploiting Image Captions,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
f8ddb2cac276812c25021b5b79bf720e97063b1e,A Comprehensive Empirical Study on Linear Subspace Methods for Facial Expression Analysis,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+f8e64dd25c3174dff87385db56abc48101b69009,Disentangling 3D Pose in A Dendritic CNN for Unconstrained 2D Face Alignment,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+f83e563288e5d7a54444bbcf28a28a37b72a0644,Fused DNN: A Deep Neural Network Fusion Approach to Fast and Robust Pedestrian Detection,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+f867cd63fa18da1c52061ba22954ee9d138906dd,Creating Body Shapes From Verbal Descriptions by Linking Similarity Spaces.,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+f8ae3654c41b6ef5c5035a6db65b80137ad9a267,Anticipation Effect after Implicit Distributional Learning,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+f89edc5a4d938bf6df0a780163b872b9edeef5d8,Unified Cortical Surface Morphometry and Its Application to Quantifying Amount of Gray Matter,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
f87b22e7f0c66225824a99cada71f9b3e66b5742,Robust emotion recognition from low quality and low bit rate video: A deep learning approach,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
f87b22e7f0c66225824a99cada71f9b3e66b5742,Robust emotion recognition from low quality and low bit rate video: A deep learning approach,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
f87b22e7f0c66225824a99cada71f9b3e66b5742,Robust emotion recognition from low quality and low bit rate video: A deep learning approach,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
f87b22e7f0c66225824a99cada71f9b3e66b5742,Robust emotion recognition from low quality and low bit rate video: A deep learning approach,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+f89e5b1f61b221c7b00db55b64239a28f8ba9fe0,Ensemble Learning-Based Person Re-identification with Multiple Feature Representations,Yunnan University,Yunnan University,"云南大学, 一二一大街, 志城家园, 五华区, 五华区 (Wuhua), 昆明市 (Kunming), 云南省, 650030, 中国",25.05703205,102.70027525,edu,
+f89e5b1f61b221c7b00db55b64239a28f8ba9fe0,Ensemble Learning-Based Person Re-identification with Multiple Feature Representations,Yunnan University,Yunnan University,"云南大学, 一二一大街, 志城家园, 五华区, 五华区 (Wuhua), 昆明市 (Kunming), 云南省, 650030, 中国",25.05703205,102.70027525,edu,
ce6d60b69eb95477596535227958109e07c61e1e,Unconstrained face verification using fisher vectors computed from frontalized faces,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
ceb763d6657a07b47e48e8a2956bcfdf2cf10818,An Efficient Feature Extraction Method with Pseudo-zernike Moment for Facial Recognition of Identical Twins,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
ceb763d6657a07b47e48e8a2956bcfdf2cf10818,An Efficient Feature Extraction Method with Pseudo-zernike Moment for Facial Recognition of Identical Twins,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
+ceac30061d8f7985987448f4712c49eeb98efad2,MemexQA: Visual Memex Question Answering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
cefd9936e91885ba7af9364d50470f6cb54315a4,Expectation and surprise determine neural population responses in the ventral visual stream.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
cefd9936e91885ba7af9364d50470f6cb54315a4,Expectation and surprise determine neural population responses in the ventral visual stream.,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
cefd9936e91885ba7af9364d50470f6cb54315a4,Expectation and surprise determine neural population responses in the ventral visual stream.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+ce386ab4511f38a7671576a9cd32e5557853180e,"Comparatives, Quantifiers, Proportions: A Multi-Task Model for the Learning of Quantities from Vision",University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+ce386ab4511f38a7671576a9cd32e5557853180e,"Comparatives, Quantifiers, Proportions: A Multi-Task Model for the Learning of Quantities from Vision",University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+ce37e11f4046a4b766b0e3228870ae4f26dddd67,Learning One-Shot Exemplar SVM from the Web for Face Verification,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+ce0aa94c79f60c35073f434a7fd6987180f81527,Achieving Anonymity against Major Face Recognition Algorithms,Ruhr-University Bochum,Ruhr-University Bochum,"RUB, 150, Universitätsstraße, Ruhr-Universität, Querenburg, Bochum-Süd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland",51.44415765,7.26096541,edu,
+ce0aa94c79f60c35073f434a7fd6987180f81527,Achieving Anonymity against Major Face Recognition Algorithms,Ruhr-University Bochum,Ruhr-University Bochum,"RUB, 150, Universitätsstraße, Ruhr-Universität, Querenburg, Bochum-Süd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland",51.44415765,7.26096541,edu,
+ceca60c4bf1a5c4e5893ae6685e7a9f80ca47f27,Visual Question: Predicting If a Crowd Will Agree on the Answer,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+ce93f83d69ee6ee981124ed1f20102335caf7b09,Deep Residual Network with Enhanced Upscaling Module for Super-Resolution,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+cee66bd89d1e25355e78573220adcd017a2d97d8,Spatio-temporal human action localisation and instance segmentation in temporally untrimmed videos,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+cee66bd89d1e25355e78573220adcd017a2d97d8,Spatio-temporal human action localisation and instance segmentation in temporally untrimmed videos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
ce5eac297174c17311ee28bda534faaa1d559bae,Automatic analysis of malaria infected red blood cell digitized microscope images,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
ce5eac297174c17311ee28bda534faaa1d559bae,Automatic analysis of malaria infected red blood cell digitized microscope images,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+ce4ad1ad4134d9131af21d4213e598f03475cfd3,A CNN Based Approach for Garments Texture Design Classification,Institute of Information Technology,Institute of Information Technology,"Institute of Information Technology, Sir Sayed Road, ফকিরাপুল, সিদ্দিক বাজার, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.72898990,90.39826820,edu,
+ce6dbde2ad8b5b9aee2ccf4a7e33e63ccfc3689a,Overcoming Language Priors in Visual Question Answering with Adversarial Regularization,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+ce300b006f42c1b64ca0e53d1cf28d11a98ece8f,Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l 1-Norm Distances,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+ce2e1bb891ffc0b114855a92f78e8aed289073af,GazeGAN - Unpaired Adversarial Image Generation for Gaze Estimation,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+ce13682b1771c221f0e0ed36da1cc3aaddc52188,ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+ce4df7862bbf7e70d0052470e4bced479bf83703,Generic Motion based Object Segmentation for Assisted Navigation,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+ce4df7862bbf7e70d0052470e4bced479bf83703,Generic Motion based Object Segmentation for Assisted Navigation,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
ce450e4849490924488664b44769b4ca57f1bc1a,Procedural Generation of Videos to Train Deep Action Recognition Networks,Toyota Research Institute,Toyota Research Institute,"Toyota Research Institute, 4440, West El Camino Real, Los Altos, Santa Clara County, California, 94022, USA",37.40253645,-122.11655107,edu,
ceeb67bf53ffab1395c36f1141b516f893bada27,Face Alignment by Local Deep Descriptor Regression,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
ceeb67bf53ffab1395c36f1141b516f893bada27,Face Alignment by Local Deep Descriptor Regression,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
ceeb67bf53ffab1395c36f1141b516f893bada27,Face Alignment by Local Deep Descriptor Regression,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
ceeb67bf53ffab1395c36f1141b516f893bada27,Face Alignment by Local Deep Descriptor Regression,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+ced73382d686dee6232c313f014bc21ca7536db0,Detection of Tongue Protrusion Gestures from Video,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+ce1cbcf0f671423eada02e6699d637afbd9ef570,Max-Margin Boltzmann Machines for Object Segmentation,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+ce83369da319607fe2832485913b0f30c00920aa,Human Detection Based on Large Feature Sets Using Graphics Processing Units,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
ce032dae834f383125cdd852e7c1bc793d4c3ba3,Motion Interchange Patterns for Action Recognition in Unconstrained Videos,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
ce032dae834f383125cdd852e7c1bc793d4c3ba3,Motion Interchange Patterns for Action Recognition in Unconstrained Videos,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
ce032dae834f383125cdd852e7c1bc793d4c3ba3,Motion Interchange Patterns for Action Recognition in Unconstrained Videos,Open University,The Open University,"The Open University, East Lane, Walton, Monkston, Milton Keynes, South East, England, MK7 6AE, UK",52.02453775,-0.70927481,edu,
ce9e1dfa7705623bb67df3a91052062a0a0ca456,Deep Feature Interpolation for Image Content Changes,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
ce56be1acffda599dec6cc2af2b35600488846c9,Inferring Sentiment from Web Images with Joint Inference on Visual and Social Cues: A Regulated Matrix Factorization Approach,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
ce56be1acffda599dec6cc2af2b35600488846c9,Inferring Sentiment from Web Images with Joint Inference on Visual and Social Cues: A Regulated Matrix Factorization Approach,IBM Almaden Research Center,IBM Almaden Research Center,"IBM Almaden Research Center, San José, Santa Clara County, California, USA",37.21095605,-121.80748668,company,
+ce2fd44a8c43642b76f219fe32291c1b2644cb73,Human Pose Forecasting via Deep Markov Models,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+ce3edf04c9f0c9da462832cbf8c5a1982e3e6bf8,Learning Kinematic Descriptions using SPARE: Simulated and Physical ARticulated Extendable dataset,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+ce3edf04c9f0c9da462832cbf8c5a1982e3e6bf8,Learning Kinematic Descriptions using SPARE: Simulated and Physical ARticulated Extendable dataset,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
e03bda45248b4169e2a20cb9124ae60440cad2de,"Learning a Dictionary of Shape-Components in Visual Cortex : Comparison with Neurons , Humans and Machines by Thomas Serre",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
e03e86ac61cfac9148b371d75ce81a55e8b332ca,Unsupervised Learning using Sequential Verification for Action Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+e088a2537492ed5a22885e871a51102a95c97cb6,On the effect of Batch Normalization and Weight Normalization in Generative Adversarial Networks,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+e06d0d7513a42755ad8b33c21ec4c1660f5e0cc5,Selective Zero-Shot Classification with Augmented Attributes,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+e06d0d7513a42755ad8b33c21ec4c1660f5e0cc5,Selective Zero-Shot Classification with Augmented Attributes,"Alibaba Group, Hangzhou, China","Alibaba Group, Hangzhou, China","Alibaba Group, 五常街道, 余杭区 (Yuhang), 杭州市 Hangzhou, 浙江省, 中国",30.28106540,120.02139087,edu,
+e06d0d7513a42755ad8b33c21ec4c1660f5e0cc5,Selective Zero-Shot Classification with Augmented Attributes,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+e00c26e3d16a44baf7be389e94ed0025a0ea3867,An Evaluation of Super-Resolution for Face Recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+e0b5815b0d3d6c02a114ee27dc6ea2d2c40a4458,Videos as Space-Time Region Graphs,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+e06f94ebf10b511d121725c318cd289c55349c2d,Training an adaptive dialogue policy for interactive learning of visually grounded word meanings,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+e06f94ebf10b511d121725c318cd289c55349c2d,Training an adaptive dialogue policy for interactive learning of visually grounded word meanings,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+e06f94ebf10b511d121725c318cd289c55349c2d,Training an adaptive dialogue policy for interactive learning of visually grounded word meanings,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
e0638e0628021712ac76e3472663ccc17bd8838c,Sign Language Recognition: State of the Art,Sharda University,Sharda University,"Sharda University, Yamuna Expressway, Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, 201308, India",28.47375120,77.48361480,edu,
+e0da17d5a8460ab74d4e8db338779feb2bb9fbbe,Labelless Scene Classification with Semantic Matching,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+e0da17d5a8460ab74d4e8db338779feb2bb9fbbe,Labelless Scene Classification with Semantic Matching,Carleton University,Carleton University,"Carleton University, 1125, Colonel By Drive, Billings Bridge, Capital, Ottawa, Ontario, K1S 5B7, Canada",45.38608430,-75.69539267,edu,
+e04428ce77d6d459b7063d6bda7a8f72a539f284,RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes,Hacettepe University,Hacettepe University,"Hacettepe Üniversitesi Beytepe Kampüsü, Hacettepe-Beytepe Kampüs Yolu, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.86742125,32.73519072,edu,
e0d878cc095eaae220ad1f681b33d7d61eb5e425,Temporal and Fine-Grained Pedestrian Action Recognition on Driving Recorder Database,Keio University,Keio University,"綱島市民の森, けつわり坂, 港北区, 横浜市, 神奈川県, 関東地方, 223-0053, 日本",35.54169690,139.63471840,edu,
e0d878cc095eaae220ad1f681b33d7d61eb5e425,Temporal and Fine-Grained Pedestrian Action Recognition on Driving Recorder Database,Tokyo Metropolitan University,Tokyo Metropolitan University,"首都大学東京, 由木緑道, 八王子市, 東京都, 関東地方, 1920364, 日本",35.62009250,139.38296706,edu,
e00d4e4ba25fff3583b180db078ef962bf7d6824,Face Verification with Multi-Task and Multi-Scale Features Fusion,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+e030697c19dd1919dbdd889b69df7ab002a8af19,The expectancy bias : Expectancy-violating faces evoke earlier pupillary dilation than neutral or negative faces,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
+e030697c19dd1919dbdd889b69df7ab002a8af19,The expectancy bias : Expectancy-violating faces evoke earlier pupillary dilation than neutral or negative faces,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+e030697c19dd1919dbdd889b69df7ab002a8af19,The expectancy bias : Expectancy-violating faces evoke earlier pupillary dilation than neutral or negative faces,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
e01bb53b611c679141494f3ffe6f0b91953af658,FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
e01bb53b611c679141494f3ffe6f0b91953af658,FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
e01bb53b611c679141494f3ffe6f0b91953af658,FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+e042c4d038373a68cca109336598c0323e7a9b60,Culture moderates the relationship between interdependence and face recognition,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+e042c4d038373a68cca109336598c0323e7a9b60,Culture moderates the relationship between interdependence and face recognition,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
+e042c4d038373a68cca109336598c0323e7a9b60,Culture moderates the relationship between interdependence and face recognition,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
e0bfcf965b402f3f209f26ae20ee88bc4d0002ab,AI Thinking for Cloud Education Platform with Personalized Learning,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
e0bfcf965b402f3f209f26ae20ee88bc4d0002ab,AI Thinking for Cloud Education Platform with Personalized Learning,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
e0bfcf965b402f3f209f26ae20ee88bc4d0002ab,AI Thinking for Cloud Education Platform with Personalized Learning,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
e0bfcf965b402f3f209f26ae20ee88bc4d0002ab,AI Thinking for Cloud Education Platform with Personalized Learning,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
e0bfcf965b402f3f209f26ae20ee88bc4d0002ab,AI Thinking for Cloud Education Platform with Personalized Learning,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+e032f5bbee040b3898170b3f9091384658caf0d2,Navigation Behavior Design and Representations for a People Aware Mobile Robot System,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+e096db52fc8316e66273b456c58b073f9b689074,Harnessing Repetitive Behaviours to Engage Attention and Learning in a Novel Therapy for Autism: An Exploratory Analysis,University of Chicago,THE UNIVERSITY OF CHICAGO,"University of Chicago, South Ellis Avenue, Woodlawn, Chicago, Cook County, Illinois, 60637, USA",41.78468745,-87.60074933,edu,
+e096db52fc8316e66273b456c58b073f9b689074,Harnessing Repetitive Behaviours to Engage Attention and Learning in a Novel Therapy for Autism: An Exploratory Analysis,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+e096db52fc8316e66273b456c58b073f9b689074,Harnessing Repetitive Behaviours to Engage Attention and Learning in a Novel Therapy for Autism: An Exploratory Analysis,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+e096db52fc8316e66273b456c58b073f9b689074,Harnessing Repetitive Behaviours to Engage Attention and Learning in a Novel Therapy for Autism: An Exploratory Analysis,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+e096db52fc8316e66273b456c58b073f9b689074,Harnessing Repetitive Behaviours to Engage Attention and Learning in a Novel Therapy for Autism: An Exploratory Analysis,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
e00d391d7943561f5c7b772ab68e2bb6a85e64c4,Robust continuous clustering.,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
e00d391d7943561f5c7b772ab68e2bb6a85e64c4,Robust continuous clustering.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
e00241f00fb31c660df6c6f129ca38370e6eadb3,What have we learned from deep representations for action recognition?,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
@@ -3703,174 +10306,486 @@ e0244a8356b57a5721c101ead351924bcfb2eef4,Power as an emotional liability: Implic e0244a8356b57a5721c101ead351924bcfb2eef4,Power as an emotional liability: Implications for perceived authenticity and trust after a transgression.,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
e0244a8356b57a5721c101ead351924bcfb2eef4,Power as an emotional liability: Implications for perceived authenticity and trust after a transgression.,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
e0244a8356b57a5721c101ead351924bcfb2eef4,Power as an emotional liability: Implications for perceived authenticity and trust after a transgression.,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+e059650472dd7bfd6907b02de491e312a0cb6d4e,Parallel Genetic Algorithms and Machine Learning,University of Portsmouth,University of Portsmouth,"University of Portsmouth - North Zone, Portland Street, Portsea, Portsmouth, South East, England, PO1 3DE, UK",50.79805775,-1.09834911,edu,
e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Beijing University of Technology,Beijing University of Technology,"北京工业大学, 银杏大道, 大郊亭村, 朝阳区 / Chaoyang, 北京市, 3208, 中国",39.87391435,116.47722285,edu,
e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+e083d6f5084d8a8582af797999185c4e0d2c841a,R-CNNs for Pose Estimation and Action Detection,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+e083d6f5084d8a8582af797999185c4e0d2c841a,R-CNNs for Pose Estimation and Action Detection,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+e083d6f5084d8a8582af797999185c4e0d2c841a,R-CNNs for Pose Estimation and Action Detection,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+e083d6f5084d8a8582af797999185c4e0d2c841a,R-CNNs for Pose Estimation and Action Detection,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+4678a2ae263e7952887df31f76ab404df74a4649,High Performance Human Face Recognition using Gabor Based Pseudo Hidden Markov Model,Jadavpur University,Jadavpur University,"Jadavpur University, Chingrighata Flyover, Basani Devi Colony, Kolkata, Hāora, West Bengal, 700098, India",22.56115370,88.41310194,edu,
468c8f09d2ad8b558b65d11ec5ad49208c4da2f2,MSR-CNN: Applying motion salient region based descriptors for action recognition,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
468c8f09d2ad8b558b65d11ec5ad49208c4da2f2,MSR-CNN: Applying motion salient region based descriptors for action recognition,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+46d7f41189c5e262df9ad1165d5a40d2b685bb0f,Discriminative Multiple Target Tracking,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+46d7f41189c5e262df9ad1165d5a40d2b685bb0f,Discriminative Multiple Target Tracking,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
466184b10fb7ce9857e6b5bd6b4e5003e09a0b16,Extended Grassmann Kernels for Subspace-Based Learning,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
466184b10fb7ce9857e6b5bd6b4e5003e09a0b16,Extended Grassmann Kernels for Subspace-Based Learning,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+46773c8a2fa5012f7b3e16b44214de0da3f68859,DisturbLabel: Regularizing CNN on the Loss Layer,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+46773c8a2fa5012f7b3e16b44214de0da3f68859,DisturbLabel: Regularizing CNN on the Loss Layer,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+46773c8a2fa5012f7b3e16b44214de0da3f68859,DisturbLabel: Regularizing CNN on the Loss Layer,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+46773c8a2fa5012f7b3e16b44214de0da3f68859,DisturbLabel: Regularizing CNN on the Loss Layer,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+46a70d4020609c175bfc9f19e99aebd1c8edb20b,Fast Human Pose Estimation,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+46a70d4020609c175bfc9f19e99aebd1c8edb20b,Fast Human Pose Estimation,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+46f698dacdb5f76d6b4dae67cb1ae4da2b789398,Deformable Distributed Multiple Detector Fusion for Multi-Person Tracking,Hong Kong Baptist University,Hong Kong Baptist University,"香港浸會大學 Hong Kong Baptist University, 安明街 On Ming Street, 石門 Shek Mun, 石古壟 Shek Kwu Lung, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1132, 中国",22.38742010,114.20822220,edu,
+4696031ddcdfab8b768817fd974b601b6b68c7f1,3D Pose Estimation from a Single Monocular Image,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+465c34c3334f29de28f973b7702a235509649429,Stereopsis via deep learning,University of Frankfurt,University of Frankfurt,"Frankfurt University of Applied Sciences, Kleiststraße, Nordend West, Frankfurt, Regierungsbezirk Darmstadt, Hessen, 60318, Deutschland",50.13053055,8.69234224,edu,
46b7ee97d7dfbd61cc3745e8dfdd81a15ab5c1d4,3D facial geometric features for constrained local model,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
46ae4d593d89b72e1a479a91806c39095cd96615,A conditional random field approach for face identification in broadcast news using overlaid text,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
467b602a67cfd7c347fe7ce74c02b38c4bb1f332,Large Margin Local Metric Learning,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+46702e0127e16a4d6a1feda3ffc5f0f123957e87,Revisit Multinomial Logistic Regression in Deep Learning: Data Dependent Model Initialization for Image Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
466f80b066215e85da63e6f30e276f1a9d7c843b,Joint Head Pose Estimation and Face Alignment Framework Using Global and Local CNN Features,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+46e46dffe4f8b724ec51179b3be1ae321fdb2d39,Collaborative Deep Reinforcement Learning,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+46e46dffe4f8b724ec51179b3be1ae321fdb2d39,Collaborative Deep Reinforcement Learning,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+46e46dffe4f8b724ec51179b3be1ae321fdb2d39,Collaborative Deep Reinforcement Learning,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+46bdfee362a4de978d24d53fd704d64d82273718,Crowd Tracking with Dynamic Evolution of Group Structures,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+46bdfee362a4de978d24d53fd704d64d82273718,Crowd Tracking with Dynamic Evolution of Group Structures,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+46bdfee362a4de978d24d53fd704d64d82273718,Crowd Tracking with Dynamic Evolution of Group Structures,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+46ee0288c382c7af7fa4f3a5e3c74d60a12c519a,Memory Based Online Learning of Deep Representations from Video Streams,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
465d5bb11912005f0a4f0569c6524981df18a7de,IMOTION - Searching for Video Sequences Using Multi-Shot Sketch Queries,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
46c87fded035c97f35bb991fdec45634d15f9df2,Spatial-Aware Object Embeddings for Zero-Shot Localization and Classification of Actions,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
46e72046a9bb2d4982d60bcf5c63dbc622717f0f,Learning Discriminative Features with Class Encoder,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
46f32991ebb6235509a6d297928947a8c483f29e,Recognizing Expression Variant Faces from a Single Sample Image per Class,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+4610b1e9b18f913fbbdb5bee6502f55a47610ff5,Removing image artifacts due to dirty camera lenses and thin occluders,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+4610b1e9b18f913fbbdb5bee6502f55a47610ff5,Removing image artifacts due to dirty camera lenses and thin occluders,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+4610b1e9b18f913fbbdb5bee6502f55a47610ff5,Removing image artifacts due to dirty camera lenses and thin occluders,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+46149723fef89d3b04019b4f62e4c0ceff7c76a0,Diagnostics in Semantic Segmentation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
4641986af5fc8836b2c883ea1a65278d58fe4577,Scene Graph Generation by Iterative Message Passing,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
4641986af5fc8836b2c883ea1a65278d58fe4577,Scene Graph Generation by Iterative Message Passing,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
464b3f0824fc1c3a9eaf721ce2db1b7dfe7cb05a,Deep Adaptive Temporal Pooling for Activity Recognition,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
464b3f0824fc1c3a9eaf721ce2db1b7dfe7cb05a,Deep Adaptive Temporal Pooling for Activity Recognition,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
+46d85e1dc7057bef62647bd9241601e9896a1b02,Improving object proposals with multi-thresholding straddling expansion,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+46836605c2ef5f78796644da3d385f66825518ba,Action Detection in Crowd,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+468c97bdfb67614d458ba63eee04756add5631b3,Beyond Kmedoids: Sparse Model Based Medoids Algorithm for Representative Selection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+468c97bdfb67614d458ba63eee04756add5631b3,Beyond Kmedoids: Sparse Model Based Medoids Algorithm for Representative Selection,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+46d29ee2b97362299ef83c06ffc4461906f1ccda,It’s Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+46d29ee2b97362299ef83c06ffc4461906f1ccda,It’s Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+464cd3c5f0e9a05dd685a7b71fe88b913da520b4,Increasing CNN Robustness to Occlusions by Reducing Filter Support,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+464cd3c5f0e9a05dd685a7b71fe88b913da520b4,Increasing CNN Robustness to Occlusions by Reducing Filter Support,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+4698ed97f4a78e724c903ec1dd6e5538203237c8,Using phase instead of optical flow for action recognition,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+4698ed97f4a78e724c903ec1dd6e5538203237c8,Using phase instead of optical flow for action recognition,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
4657d87aebd652a5920ed255dca993353575f441,Image Normalization for Illumination Compensation in Facial Images,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
4622b82a8aff4ac1e87b01d2708a333380b5913b,Multi-label CNN based pedestrian attribute learning for soft biometrics,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
46e866f58419ff4259c65e8256c1d4f14927b2c6,On the Generalization Power of Face and Gait Gender Recognition Methods,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
46072f872eee3413f9d05482be6446f6b96b6c09,Trace Quotient Problems Revisited,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
46072f872eee3413f9d05482be6446f6b96b6c09,Trace Quotient Problems Revisited,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
4698a599425c3a6bae1c698456029519f8f2befe,Transferring Rich Deep Features for Facial Beauty Prediction,University of North Texas,University of North Texas,"University of North Texas, West Highland Street, Denton, Denton County, Texas, 76201, USA",33.20988790,-97.15147488,edu,
+2cdb8df791cb15eef805443293319ec8690ff88f,An Effective Approach to Pose Invariant 3D Face Recognition,Singapore Management University,Singapore Management University,"Singapore Management University, Fort Canning Tunnel, Clarke Quay, City Hall, Singapore, Central, 178895, Singapore",1.29500195,103.84909214,edu,
+2cdb8df791cb15eef805443293319ec8690ff88f,An Effective Approach to Pose Invariant 3D Face Recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+2cdb8df791cb15eef805443293319ec8690ff88f,An Effective Approach to Pose Invariant 3D Face Recognition,Singapore Management University,Singapore Management University,"Singapore Management University, Fort Canning Tunnel, Clarke Quay, City Hall, Singapore, Central, 178895, Singapore",1.29500195,103.84909214,edu,
+2cdb8df791cb15eef805443293319ec8690ff88f,An Effective Approach to Pose Invariant 3D Face Recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+2ce38dbb4d4228ae4a7016b0422155a274b88659,Automatic 3D Face Extraction from Raw Scanned Triangle Mesh,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+2ce38dbb4d4228ae4a7016b0422155a274b88659,Automatic 3D Face Extraction from Raw Scanned Triangle Mesh,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
2c424f21607ff6c92e640bfe3da9ff105c08fac4,Learning Structured Output Representation using Deep Conditional Generative Models,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+2c13e0f614712c6a478adea3ce011750d5e77587,Identity Verification Via the 3Bid Face Alignment System,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+2c29f5245e20b49acad4c63220a17f3b1fb8cd00,Preserving Modes and Messages via Diverse Particle Selection,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+2c29f5245e20b49acad4c63220a17f3b1fb8cd00,Preserving Modes and Messages via Diverse Particle Selection,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+2cd9a7eefc126469b566fc429657bb889d13b4fa,Robust object tracking based on RGB-D camera,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+2cd9a7eefc126469b566fc429657bb889d13b4fa,Robust object tracking based on RGB-D camera,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
2c258eec8e4da9e65018f116b237f7e2e0b2ad17,Deep Quantization: Encoding Convolutional Activations with Deep Generative Model,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
2c258eec8e4da9e65018f116b237f7e2e0b2ad17,Deep Quantization: Encoding Convolutional Activations with Deep Generative Model,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+2cb7b6c6456735e5cf778ef9864bf590f7813ccf,Generative Dual Adversarial Network for Generalized Zero-shot Learning,University of Illinois at Chicago,University of Illinois at Chicago,"University of Illinois at Chicago, West Taylor Street, Greektown, Chicago, Cook County, Illinois, 60607, USA",41.86898915,-87.64856256,edu,
+2cb7b6c6456735e5cf778ef9864bf590f7813ccf,Generative Dual Adversarial Network for Generalized Zero-shot Learning,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+2ce073da76e6ed87eda2da08da0e00f4f060f1a6,Deep Saliency with Encoded Low Level Distance Map and High Level Features,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
2c203050a6cca0a0bff80e574bda16a8c46fe9c2,Discriminative Deep Hashing for Scalable Face Image Retrieval,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+2ce3dbf18c10e62f1ffdeba5f3b16cf6c4c53c6c,Crafting 3D faces using free form portrait sketching and plausible texture inference,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+2ce3dbf18c10e62f1ffdeba5f3b16cf6c4c53c6c,Crafting 3D faces using free form portrait sketching and plausible texture inference,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+2ce3dbf18c10e62f1ffdeba5f3b16cf6c4c53c6c,Crafting 3D faces using free form portrait sketching and plausible texture inference,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+2ce3dbf18c10e62f1ffdeba5f3b16cf6c4c53c6c,Crafting 3D faces using free form portrait sketching and plausible texture inference,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+2ce3dbf18c10e62f1ffdeba5f3b16cf6c4c53c6c,Crafting 3D faces using free form portrait sketching and plausible texture inference,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
2c3430e0cbe6c8d7be3316a88a5c13a50e90021d,Multi-feature Spectral Clustering with Minimax Optimization,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
2cde051e04569496fb525d7f1b1e5ce6364c8b21,Sparse 3D convolutional neural networks,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
2c1ffb0feea5f707c890347d2c2882be0494a67a,The Variational Homoencoder: Learning to learn high capacity generative models from few examples,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
2cdc40f20b70ca44d9fd8e7716080ee05ca7924a,Real-time Convolutional Neural Networks for Emotion and Gender Classification,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+2c963e79a88a3f8ba71cd8d5c9f9f92c925f534c,An Effective Approach for Point Clouds Registration Based on the Hard and Soft Assignments,University of North Carolina at Charlotte,University of North Carolina at Charlotte,"Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA",35.31034410,-80.73261617,edu,
+2c2371629ad7bcde46e62859b2e812f6e5fc64cf,Action Recognition in the Presence of One Egocentric and Multiple Static Cameras,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
2cac70f9c8140a12b6a55cef834a3d7504200b62,Reconstructing High Quality Face-Surfaces using Model Based Stereo,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
2cac70f9c8140a12b6a55cef834a3d7504200b62,Reconstructing High Quality Face-Surfaces using Model Based Stereo,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
2c1f8ddbfbb224271253a27fed0c2425599dfe47,Understanding and Comparing Deep Neural Networks for Age and Gender Classification,Singapore University of Technology and Design,Singapore University of Technology and Design,"Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore",1.34021600,103.96508900,edu,
2ca43325a5dbde91af90bf850b83b0984587b3cc,For Your Eyes Only – Biometric Protection of PDF Documents,Gdansk University of Technology,Gdansk University of Technology,"PG, Romualda Traugutta, Królewska Dolina, Wrzeszcz Górny, Gdańsk, pomorskie, 80-233, RP",54.37086525,18.61716016,edu,
+2c2261212051ae0d2586b90715cc411344570916,Considerations for Evaluating Models of Language Understanding and Reasoning,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+2c7946d5d2f1572c20e9843eb2033b8eb9771bf3,THEORETICAL REVIEW Mechanisms for Widespread Hippocampal Involvement in Cognition,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+2c7946d5d2f1572c20e9843eb2033b8eb9771bf3,THEORETICAL REVIEW Mechanisms for Widespread Hippocampal Involvement in Cognition,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+2c7946d5d2f1572c20e9843eb2033b8eb9771bf3,THEORETICAL REVIEW Mechanisms for Widespread Hippocampal Involvement in Cognition,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+2c7946d5d2f1572c20e9843eb2033b8eb9771bf3,THEORETICAL REVIEW Mechanisms for Widespread Hippocampal Involvement in Cognition,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+2cf6d4a3481b7ec40b704472017493ec17565e6f,Deep cross-domain building extraction for selective depth estimation from oblique aerial imagery,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
2cfc28a96b57e0817cc9624a5d553b3aafba56f3,P2F2: Privacy-preserving face finder,New Jersey Institute of Technology,New Jersey Institute of Technology,"New Jersey Institute of Technology, Warren Street, University Heights, Newark, Essex County, New Jersey, 07103, USA",40.74230250,-74.17928172,edu,
2cae619d0209c338dc94593892a787ee712d9db0,Selective hidden random fields: Exploiting domain-specific saliency for event classification,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
2c0acaec54ab2585ff807e18b6b9550c44651eab,Face Quality Assessment for Face Verification in Video,Lomonosov Moscow State University,Lomonosov Moscow State University,"МГУ, улица Академика Хохлова, Московский государственный университет им. М. В. Ломоносова, район Раменки, Западный административный округ, Москва, ЦФО, 119234, РФ",55.70229715,37.53179777,edu,
+2ceaa8d6ee74105a6b5561661db299c885f9135b,Learning to Decode for Future Success,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+2c7934a2f1671286370cd9adebc2872c6dd318f5,Visual Scene Understanding through Semantic Segmentation,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
+2c7934a2f1671286370cd9adebc2872c6dd318f5,Visual Scene Understanding through Semantic Segmentation,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
2c62b9e64aeddf12f9d399b43baaefbca8e11148,Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
2c62b9e64aeddf12f9d399b43baaefbca8e11148,Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
2c62b9e64aeddf12f9d399b43baaefbca8e11148,Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
2c62b9e64aeddf12f9d399b43baaefbca8e11148,Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild,Reutlingen University,Reutlingen University,"Campus Hohbuch, Campus Hochschule Reutlingen, Reutlingen, Landkreis Reutlingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72762, Deutschland",48.48187645,9.18682404,edu,
+2c0c5c40f98d9b645549f235a680be5b729ebe48,A Scanner Darkly: Protecting User Privacy from Perceptual Applications,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+2c0c5c40f98d9b645549f235a680be5b729ebe48,A Scanner Darkly: Protecting User Privacy from Perceptual Applications,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+2c761495cf3dd320e229586f80f868be12360d4e,Revisiting Unreasonable Effectiveness of Data in Deep Learning Era,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2cbb2c7c0f3f78574b5e8cf197774d5b556b1202,Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+2cbb2c7c0f3f78574b5e8cf197774d5b556b1202,Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions,University of Perugia,University of Perugia,"Caffe Perugia, 2350, Health Sciences Mall, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.26224210,-123.24500520,edu,
+2cbb2c7c0f3f78574b5e8cf197774d5b556b1202,Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
+2cbb2c7c0f3f78574b5e8cf197774d5b556b1202,Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+2cbb2c7c0f3f78574b5e8cf197774d5b556b1202,Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+2cff3c291e03dda9ed6cf9747eeffc5642762e52,A Survey: Face Recognition Techniques,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+2cff3c291e03dda9ed6cf9747eeffc5642762e52,A Survey: Face Recognition Techniques,National University of Sciences and Technology,National University of Sciences and Technology,"National University of Sciences and Technology (NUST), Kashmir Highway, جی - 10, ICT, وفاقی دارالحکومت اسلام آباد, 44000, پاکستان",33.64434700,72.98850790,edu,
+2ca761938bd789b82d1a4ca85e7b8d5661093660,Enhancing Music Information Retrieval by Incorporating Image-Based Local Features,Open University,The Open University,"The Open University, East Lane, Walton, Monkston, Milton Keynes, South East, England, MK7 6AE, UK",52.02453775,-0.70927481,edu,
+2ca761938bd789b82d1a4ca85e7b8d5661093660,Enhancing Music Information Retrieval by Incorporating Image-Based Local Features,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+2c55ac6330ce91a24131a81807237807134ec371,Visual Phrase Learning and Its Application in Computed Tomographic Colonography,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+2c4def184f940e2dd4302bdc130999c27054de3e,A new spontaneous expression database and a study of classification-based expression analysis methods,Loughborough University,Loughborough University,"Computer Science, University Road, Charnwood, Leicestershire, East Midlands, England, LE11 3TP, UK",52.76635770,-1.22924610,edu,
+2c4def184f940e2dd4302bdc130999c27054de3e,A new spontaneous expression database and a study of classification-based expression analysis methods,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
2c19d3d35ef7062061b9e16d040cebd7e45f281d,End-to-end Video-level Representation Learning for Action Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+2c797d2daefba6cfceb8510219163dc7dcfa0a66,Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation,Ocean University of China,Ocean University of China,"中国海洋大学, 238, 松岭路 Sōnglǐng Road, 朱家洼, 崂山区 (Laoshan), 青岛市, 山东省, 266100, 中国",36.16161795,120.49355276,edu,
+2c3cac0f568ae9261ff9c80eeda55a13e83ae7fb,A discriminative framework for modelling object classes,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
2c17d36bab56083293456fe14ceff5497cc97d75,Unconstrained Face Alignment via Cascaded Compositional Learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
2c17d36bab56083293456fe14ceff5497cc97d75,Unconstrained Face Alignment via Cascaded Compositional Learning,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
2c17d36bab56083293456fe14ceff5497cc97d75,Unconstrained Face Alignment via Cascaded Compositional Learning,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
2cd7821fcf5fae53a185624f7eeda007434ae037,Exploring the geo-dependence of human face appearance,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
2cd7821fcf5fae53a185624f7eeda007434ae037,Exploring the geo-dependence of human face appearance,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+2c3c72fffcbbf66cbb649b64aa51199722140ad1,TVT: Two-View Transformer Network for Video Captioning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+7901a33fe442fca87be7f8bb295091feb25f69bc,Bayesian and Information-Theoretic Learning of High Dimensional Data,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+798d042a70b2c824998b3fc39a6e21799b588832,Face sketch recognition by Local Radon Binary Pattern: LRBP,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
794ddb1f3b7598985d4d289b5b0664be736a50c4,Exploiting Competition Relationship for Robust Visual Recognition,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+79e1b9e425621dd5a683026b7158479c10f6780a,Vehicle Detection Method Based on Edge Information and Local Transform Histogram,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
+79e1b9e425621dd5a683026b7158479c10f6780a,Vehicle Detection Method Based on Edge Information and Local Transform Histogram,Hanyang University,Hanyang University,"한양대, 206, 왕십리로, 사근동, 성동구, 서울특별시, 04763, 대한민국",37.55572710,127.04366420,edu,
+793651f4cf210bd81922d173346b037d66f2b4a4,Bayes Optimality in Linear Discriminant Analysis,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+79d3cb01f4907e895a7afced8b090427c39b9b84,Spatial-Aware Object Embeddings for Zero-Shot Localization and Classification of Actions,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+794f76c111ba1a4ca718e84ae74ee8d2a67c4173,Ventromedial prefrontal cortex mediates visual attention during facial emotion recognition.,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+794f76c111ba1a4ca718e84ae74ee8d2a67c4173,Ventromedial prefrontal cortex mediates visual attention during facial emotion recognition.,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+794f76c111ba1a4ca718e84ae74ee8d2a67c4173,Ventromedial prefrontal cortex mediates visual attention during facial emotion recognition.,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+794f76c111ba1a4ca718e84ae74ee8d2a67c4173,Ventromedial prefrontal cortex mediates visual attention during facial emotion recognition.,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+794f76c111ba1a4ca718e84ae74ee8d2a67c4173,Ventromedial prefrontal cortex mediates visual attention during facial emotion recognition.,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+79a36b19ea363c14af27a1f4112a9eccdd582837,The scope of social attention deficits in autism: prioritized orienting to people and animals in static natural scenes.,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+79a36b19ea363c14af27a1f4112a9eccdd582837,The scope of social attention deficits in autism: prioritized orienting to people and animals in static natural scenes.,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+79894ddf290d3c7a768d634eceb7888564b5cf19,Query-Guided Regression Network with Context Policy for Phrase Grounding,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+7934c91f09e5bf819519d4348aafdda7c99267bb,Discovering gender differences in facial emotion recognition via implicit behavioral cues,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+7934c91f09e5bf819519d4348aafdda7c99267bb,Discovering gender differences in facial emotion recognition via implicit behavioral cues,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+7934c91f09e5bf819519d4348aafdda7c99267bb,Discovering gender differences in facial emotion recognition via implicit behavioral cues,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+799537fa855caf53a6a3a7cf20301a81e90da127,High-Order Attention Models for Visual Question Answering,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+799537fa855caf53a6a3a7cf20301a81e90da127,High-Order Attention Models for Visual Question Answering,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+799537fa855caf53a6a3a7cf20301a81e90da127,High-Order Attention Models for Visual Question Answering,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+79443a311d75fc0187314d21f8b065b33e5b41cd,The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
79744fc71bea58d2e1918c9e254b10047472bd76,Disentangling 3D Pose in A Dendritic CNN for Unconstrained 2D Face Alignment,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+79cc0f893af976fe1052240518f47f3bee56c6f6,Template Matching for Wide-Baseline Panoramic Images from a Vehicle-Borne Multi-Camera Rig,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+79cc0f893af976fe1052240518f47f3bee56c6f6,Template Matching for Wide-Baseline Panoramic Images from a Vehicle-Borne Multi-Camera Rig,Capital Normal University,Capital Normal University,"首都师范大学, 岭南路, 西冉村, 海淀区, 100048, 中国",39.92864575,116.30104052,edu,
794c0dc199f0bf778e2d40ce8e1969d4069ffa7b,Odd Leaf Out: Improving Visual Recognition with Games,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
794c0dc199f0bf778e2d40ce8e1969d4069ffa7b,Odd Leaf Out: Improving Visual Recognition with Games,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+79f9a15b4e838d6db91249a85d72fadb07aee927,Less is More: Zero-Shot Learning from Online Textual Documents with Noise Suppression,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+794d344d6aa97e3cb67a44739207aa9c1360db8d,Probabilistic Low-Rank Subspace Clustering,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+794d344d6aa97e3cb67a44739207aa9c1360db8d,Probabilistic Low-Rank Subspace Clustering,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+7965b2ce7d64991218515e20fc1fc0459fd20a38,Video-based Person Re-identification Using Spatial-Temporal Attention Networks,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+7965b2ce7d64991218515e20fc1fc0459fd20a38,Video-based Person Re-identification Using Spatial-Temporal Attention Networks,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+7965b2ce7d64991218515e20fc1fc0459fd20a38,Video-based Person Re-identification Using Spatial-Temporal Attention Networks,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
799c02a3cde2c0805ea728eb778161499017396b,PersonRank: Detecting Important People in Images,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
799c02a3cde2c0805ea728eb778161499017396b,PersonRank: Detecting Important People in Images,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+7958893d88c007d6569c1f2f9771d1c63b99422f,Structured Uncertainty Prediction Networks,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+7958893d88c007d6569c1f2f9771d1c63b99422f,Structured Uncertainty Prediction Networks,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+795b76ebf17c559d82ea6976f1749096036d6817,Automatic Curation of Golf Highlights Using Multimodal Excitement Features,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+79ef25ed4863311000975b955651c0515fe38f45,Pyramid Attention Network for Semantic Segmentation,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+79ef25ed4863311000975b955651c0515fe38f45,Pyramid Attention Network for Semantic Segmentation,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+79ef25ed4863311000975b955651c0515fe38f45,Pyramid Attention Network for Semantic Segmentation,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+79ef25ed4863311000975b955651c0515fe38f45,Pyramid Attention Network for Semantic Segmentation,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+792928e5e539dfbba334c36bee337449c4918d6a,Learning to Transfer: Transferring Latent Task Structures and Its Application to Person-Specific Facial Action Unit Detection,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
7966146d72f9953330556baa04be746d18702047,Harnessing Human Manipulation,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+79eb06c8acce1feef4a8654287d9cf5081e19600,Self-supervised learning of a facial attribute embedding from video,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
79fa57dedafddd3f3720ca26eb41c82086bfb332,Modeling facial expression space for recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
79fa57dedafddd3f3720ca26eb41c82086bfb332,Modeling facial expression space for recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
79fa57dedafddd3f3720ca26eb41c82086bfb332,Modeling facial expression space for recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
79fa57dedafddd3f3720ca26eb41c82086bfb332,Modeling facial expression space for recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
79fa57dedafddd3f3720ca26eb41c82086bfb332,Modeling facial expression space for recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
79fa57dedafddd3f3720ca26eb41c82086bfb332,Modeling facial expression space for recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+79a3a07661b8c6a36070fd767344e15c847a30ef,Contextual Pooling in Image Classification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+79d50641eec7fbb6588909f96aeaef4a7b42c9e9,DSSLIC: Deep Semantic Segmentation-based Layered Image Compression,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+7933a312c4a4ba431eb0357fd05e8609ca66eaa7,Backpropagation for Implicit Spectral Densities,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+7969cc315bbafcd38a637eb8cd5d45ba897be319,An enhanced deep feature representation for person re-identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
79db191ca1268dc88271abef3179c4fe4ee92aed,Facial Expression Based Automatic Album Creation,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
79db191ca1268dc88271abef3179c4fe4ee92aed,Facial Expression Based Automatic Album Creation,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
79db191ca1268dc88271abef3179c4fe4ee92aed,Facial Expression Based Automatic Album Creation,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
+2d2b1f9446e9b4cdb46327cda32a8d9621944e29,Information revelation and privacy in online social networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
2d990b04c2bd61d3b7b922b8eed33aeeeb7b9359,Discriminative Dictionary Learning with Pairwise Constraints,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+2d7aa6af536a703471c56cc94bfd99471963b305,Learning to Separate Object Sounds by Watching Unlabeled Video,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
2d25045ec63f9132371841c0beccd801d3733908,Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
+2d4c5768a65f05f96ae71a269422d0c3d371b26a,Semantics-Aware Deep Correspondence Structure Learning for Robust Person Re-Identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+2d68cac1bd2f18631051cfbd4a46b67be1a939fe,PSSDL: Probabilistic Semi-supervised Dictionary Learning,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+2d4215a73e4cabc12a8ea5f49a3661d741add0c4,Unsupervised Detection of Regions of Interest Using Iterative Link Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2d4215a73e4cabc12a8ea5f49a3661d741add0c4,Unsupervised Detection of Regions of Interest Using Iterative Link Analysis,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+2dd3dff173686d66af70e7180fabd8755dd1307d,Coupling detection and data association for multiple object tracking,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
2d080662a1653f523321974a57518e7cb67ecb41,On Constrained Local Model Feature Normalization for Facial Expression Recognition,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
2d4b9fe3854ccce24040074c461d0c516c46baf4,Temporal Action Localization by Structured Maximal Sums,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
2d4b9fe3854ccce24040074c461d0c516c46baf4,Temporal Action Localization by Structured Maximal Sums,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+2d64839bcf82e0a89d7e4874909c6114083c8a4f,Real-Time Multi-Person Tracking with Time-Constrained Detection,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+2d638ee3e358732f3c052b854dc16949fdd4a2c3,Challenges in Executing Data Intensive Biometric Workloads on a Desktop Grid,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
2d9e58ea582e054e9d690afca8b6a554c3687ce6,Learning local feature aggregation functions with backpropagation,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
2d164f88a579ba53e06b601d39959aaaae9016b7,Dynamic Facial Expression Recognition Using A Bayesian Temporal Manifold Model,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+2d96178c760b08a6892647fb53b0d46b113db163,Localization of Humans in Images Using Convolutional Networks,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
2d8001ffee6584b3f4d951d230dc00a06e8219f8,Feature Agglomeration Networks for Single Stage Face Detection,Singapore Management University,Singapore Management University,"Singapore Management University, Fort Canning Tunnel, Clarke Quay, City Hall, Singapore, Central, 178895, Singapore",1.29500195,103.84909214,edu,
2d8001ffee6584b3f4d951d230dc00a06e8219f8,Feature Agglomeration Networks for Single Stage Face Detection,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
2d23fa205acca9c21e3e1a04674f1e5a9528550e,The Fast and the Flexible: Extended Pseudo Two-Dimensional Warping for Face Recognition,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+2d02cf53bc0f2d919b89bec8f9160b50916bb625,Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
2d244d70ed1a2ba03d152189f1f90ff2b4f16a79,An Analytical Mapping for LLE and Its Application in Multi-Pose Face Synthesis,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
2d31ab536b3c8a05de0d24e0257ca4433d5a7c75,Materials discovery: Fine-grained classification of X-ray scattering images,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
2dbde64ca75e7986a0fa6181b6940263bcd70684,Pose Independent Face Recognition by Localizing Local Binary Patterns via Deformation Components,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
2dbde64ca75e7986a0fa6181b6940263bcd70684,Pose Independent Face Recognition by Localizing Local Binary Patterns via Deformation Components,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
2d0363a3ebda56d91d704d5ff5458a527775b609,Attribute2Image: Conditional Image Generation from Visual Attributes,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+2d48557e4107d93126e7f7b74fb04517697f6a52,Self-Training Ensemble Networks for Zero-Shot Image Recognition,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+2d48557e4107d93126e7f7b74fb04517697f6a52,Self-Training Ensemble Networks for Zero-Shot Image Recognition,Carleton University,Carleton University,"Carleton University, 1125, Colonel By Drive, Billings Bridge, Capital, Ottawa, Ontario, K1S 5B7, Canada",45.38608430,-75.69539267,edu,
2d93a9aa8bed51d0d1b940c73ac32c046ebf1eb8,Perceptual Reward Functions,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
2d93a9aa8bed51d0d1b940c73ac32c046ebf1eb8,Perceptual Reward Functions,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
2dd2c7602d7f4a0b78494ac23ee1e28ff489be88,Large scale metric learning from equivalence constraints,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+2d05fd37ef8f148711819d777757bdcacfaaf175,3D Multi-Spectrum Sensor System with Face Recognition,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
2d84e30c61281d3d7cdd11676683d6e66a68aea6,Automatic Construction of Action Datasets Using Web Videos with Density-Based Cluster Analysis and Outlier Detection,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
2d98a1cb0d1a37c79a7ebcb727066f9ccc781703,Coupled Support Vector Machines for Supervised Domain Adaptation,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+2def47989c6f9143184b5eaaf3aca3f2833f3e05,Learning from Unscripted Deictic Gesture and Language for Human-Robot Interactions,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+2dd46b83a1cf5c7c811a462728d9797c270c2cb4,Recurrent Human Pose Estimation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
2dced31a14401d465cd115902bf8f508d79de076,Can a Humanoid Face be Expressive? A Psychophysiological Investigation,University of Pisa,University of Pisa,"Dipartimento di Fisica 'E. Fermi', 3, Largo Bruno Pontecorvo, San Francesco, Pisa, PI, TOS, 56127, Italia",43.72012990,10.40789760,edu,
2dced31a14401d465cd115902bf8f508d79de076,Can a Humanoid Face be Expressive? A Psychophysiological Investigation,University of Pisa,University of Pisa,"Dipartimento di Fisica 'E. Fermi', 3, Largo Bruno Pontecorvo, San Francesco, Pisa, PI, TOS, 56127, Italia",43.72012990,10.40789760,edu,
2dced31a14401d465cd115902bf8f508d79de076,Can a Humanoid Face be Expressive? A Psychophysiological Investigation,Qatar University,Qatar University,"Qatar University, Roindabout 3, Al Tarfa (68), أم صلال, 24685, قطر",25.37461295,51.48980354,edu,
2dced31a14401d465cd115902bf8f508d79de076,Can a Humanoid Face be Expressive? A Psychophysiological Investigation,University of Pisa,University of Pisa,"Dipartimento di Fisica 'E. Fermi', 3, Largo Bruno Pontecorvo, San Francesco, Pisa, PI, TOS, 56127, Italia",43.72012990,10.40789760,edu,
+2deed841cfde51ce3b4e90880894efbbfdc18f18,Privacy-Preserving Egocentric Activity Recognition from Extreme Low Resolution,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+2deed841cfde51ce3b4e90880894efbbfdc18f18,Privacy-Preserving Egocentric Activity Recognition from Extreme Low Resolution,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+2da0f99ae90ea3e6ccbd3f43e52dbf5aa1553363,To Track or To Detect? An Ensemble Framework for Optimal Selection,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
2dfe0e7e81f65716b09c590652a4dd8452c10294,Incongruence Between Observers’ and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
2dfe0e7e81f65716b09c590652a4dd8452c10294,Incongruence Between Observers’ and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
2dd5f1d69e0e8a95a10f3f07f2c0c7fa172994b3,Machine Analysis of Facial Expressions,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+2d105eea4f594519bd337298c55b9af3da178293,Deep Randomized Ensembles for Metric Learning,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
2d38fd1df95f5025e2cee5bc439ba92b369a93df,Scalable Object-Class Search via Sparse Retrieval Models and Approximate Ranking,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
2d83ba2d43306e3c0587ef16f327d59bf4888dc3,Large-Scale Video Classification with Convolutional Neural Networks,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
2d79d338c114ece1d97cde1aa06ab4cf17d38254,iLab-20M: A Large-Scale Controlled Object Dataset to Investigate Deep Learning,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
2d79d338c114ece1d97cde1aa06ab4cf17d38254,iLab-20M: A Large-Scale Controlled Object Dataset to Investigate Deep Learning,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
2d3482dcff69c7417c7b933f22de606a0e8e42d4,Labeled Faces in the Wild : Updates and New Reporting Procedures,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+2d1e009a7b7a6304903ba183e39395c358f652e8,ResearchDoom and CocoDoom: Learning Computer Vision with Games,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+2d1e009a7b7a6304903ba183e39395c358f652e8,ResearchDoom and CocoDoom: Learning Computer Vision with Games,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+2d1e009a7b7a6304903ba183e39395c358f652e8,ResearchDoom and CocoDoom: Learning Computer Vision with Games,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+2d1e009a7b7a6304903ba183e39395c358f652e8,ResearchDoom and CocoDoom: Learning Computer Vision with Games,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+2dc7d439e99f15a499cd2dcbdfbc1c0c7648964d,Computational Understanding of Image Memorability by Zoya Bylinskii,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
2d4a3e9361505616fa4851674eb5c8dd18e0c3cf,Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study,Texas A&M University,Texas A&M University,"Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA",30.61083650,-96.35212800,edu,
+2d21e6f8bd9e9f647f3517f51347ad89b4381a7f,Identifying Individual Facial Expressions by Deconstructing a Neural Network,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+2df5e2adf01a803405341af1943651f6d8658bce,Taking mobile multi-object tracking to the next level,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
2d748f8ee023a5b1fbd50294d176981ded4ad4ee,Triplet Similarity Embedding for Face Verification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+2dbff0b15221234e00bec4a00b4897c631904fcf,Learning Efficient Image Representation for Person Re-Identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
2d3c17ced03e4b6c4b014490fe3d40c62d02e914,Video-driven state-aware facial animation,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
41f26101fed63a8d149744264dd5aa79f1928265,Spot On: Action Localization from Pointly-Supervised Proposals,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
41f26101fed63a8d149744264dd5aa79f1928265,Spot On: Action Localization from Pointly-Supervised Proposals,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
416b559402d0f3e2b785074fcee989d44d82b8e5,Multi-view Super Vector for Action Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
416b559402d0f3e2b785074fcee989d44d82b8e5,Multi-view Super Vector for Action Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
416364cfdbc131d6544582e552daf25f585c557d,Synthesis and recognition of facial expressions in virtual 3D views,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+414315d44a489d09c6e1933033ffba6396974ee1,Video Visual Relation Detection,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+41199678ad9370ff8ca7e9e3c2617b62a297fac3,Multitask Deep Learning models for real-time deployment in embedded systems,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
411ee9236095f8f5ca3b9ef18fd3381c1c68c4b8,An Empirical Evaluation of the Local Texture Description Framework-Based Modified Local Directional Number Pattern with Various Classifiers for Face Recognition,Manonmaniam Sundaranar University,Manonmaniam Sundaranar University,"Manonmaniam Sundaranar University, Tenkasi-Tirunelveli, Gandhi Nagar, Tirunelveli, Tirunelveli Kattabo, Tamil Nadu, 627808, India",8.76554685,77.65100445,edu,
+411278b73afedca6976f02a8d3a38cdec3337f87,Cross-View Projective Dictionary Learning for Person Re-Identification,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+411278b73afedca6976f02a8d3a38cdec3337f87,Cross-View Projective Dictionary Learning for Person Re-Identification,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+411278b73afedca6976f02a8d3a38cdec3337f87,Cross-View Projective Dictionary Learning for Person Re-Identification,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
411318684bd2d42e4b663a37dcf0532a48f0146d,Improved Face Verification with Simple Weighted Feature Combination,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+41d9fbf55ea7142b13b68d8ddfe764896569cd32,Efficient Mining of Frequent and Distinctive Feature Configurations,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
4140498e96a5ff3ba816d13daf148fffb9a2be3f,Constrained Ensemble Initialization for Facial Landmark Tracking in Video,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4168fd6fd9e672223fefc9706596121d653e39ff,Early and late stage processing abnormalities in autism spectrum disorders: An ERP study,Southwest University,Southwest University,"西南大学, 天生路, 北碚区 (Beibei), 北碚区, 北碚区 (Beibei), 重庆市, 400711, 中国",29.82366295,106.42050016,edu,
+4168fd6fd9e672223fefc9706596121d653e39ff,Early and late stage processing abnormalities in autism spectrum disorders: An ERP study,University of Macau,University of Macau,"研究生宿舍 Residência de Estudantes de Pós-Graduação da Universidade de Macau, 澳門大學 Universidade de Macau, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, Universidade de Macau em Ilha de Montanha 澳門大學橫琴校區, 中国",22.12401870,113.54510901,edu,
41f8477a6be9cd992a674d84062108c68b7a9520,An Automated System for Visual Biometrics,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+412a82b94129477d3cce2f737365219103715db2,A novel symbolization technique for time-series outlier detection,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+412a82b94129477d3cce2f737365219103715db2,A novel symbolization technique for time-series outlier detection,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+41be021880a916305c82199ddc2298eb271f6590,Benchmarks for Image Classification and Other High-dimensional Pattern Recognition Problems,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+419f05c5888804e0a9d9f2dc60839f2d8d65a7a6,Image Feature Extraction Using 2D Mel-Cepstrum,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
41aa8c1c90d74f2653ef4b3a2e02ac473af61e47,Compositional Structure Learning for Action Understanding,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
41aa8c1c90d74f2653ef4b3a2e02ac473af61e47,Compositional Structure Learning for Action Understanding,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
41971dfbf404abeb8cf73fea29dc37b9aae12439,Detection of Facial Feature Points Using Anthropometric Face Model,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
+41da7c52a09072fd9c5275f03f4fa6f6d41e1aed,Viewpoint Invariant 3D Human Pose Estimation with Recurrent Error Feedback,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
4157e45f616233a0874f54a59c3df001b9646cd7,Diagnostically relevant facial gestalt information from ordinary photos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
4157e45f616233a0874f54a59c3df001b9646cd7,Diagnostically relevant facial gestalt information from ordinary photos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
4157e45f616233a0874f54a59c3df001b9646cd7,Diagnostically relevant facial gestalt information from ordinary photos,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+416087bc2df1e5150231d85b8103d816fc32a2a3,Local normal binary patterns for 3D facial action unit detection,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+416087bc2df1e5150231d85b8103d816fc32a2a3,Local normal binary patterns for 3D facial action unit detection,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+41b2068f134adf9afb3dae2d8811e2d21f471e3d,Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+412b3ef02c85087e5f1721176114672c722b17a4,A Taxonomy of Deep Convolutional Neural Nets for Computer Vision,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+412b3ef02c85087e5f1721176114672c722b17a4,A Taxonomy of Deep Convolutional Neural Nets for Computer Vision,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+412b3ef02c85087e5f1721176114672c722b17a4,A Taxonomy of Deep Convolutional Neural Nets for Computer Vision,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+413c98ff2d95b5b945825268fd8ffdc65880f715,Human Pose Estimation in Videos,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+41cbf0750fa0d08880068f9a89be92232795f357,Can the Early Human Visual System Compete with Deep Neural Networks?,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+41612c66beaad320af9b7d34407c7d0f4ca7bfea,Inhibition or Ideology ? The Neural Mechanisms of Evaluating Race-Targeted Government Assistance,University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
4136a4c4b24c9c386d00e5ef5dffdd31ca7aea2c,Multi-Modal Person-Profiles from Broadcast News Video,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+41e1084e74564ced3e1fa845250162d6d0f2b9c3,A Texture-based Approach to Face Detection,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+411dc8874fd7b3a9a4c1fd86bb5b583788027776,Direct Shape Regression Networks for End-to-End Face Alignment,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+411dc8874fd7b3a9a4c1fd86bb5b583788027776,Direct Shape Regression Networks for End-to-End Face Alignment,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+4189862b2ce9c71e1b451deb58dd42f50c7d04a1,Autistic trait interactions underlie sex-dependent facial recognition abilities in the normal population,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+4189862b2ce9c71e1b451deb58dd42f50c7d04a1,Autistic trait interactions underlie sex-dependent facial recognition abilities in the normal population,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+41c87d3342a85712a3591b6d49d99be8fc8d35d9,Face-trait inferences show robust child – adult agreement : Evidence from three types of faces,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
41aa209e9d294d370357434f310d49b2b0baebeb,Beyond caption to narrative: Video captioning with multiple sentences,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+4156746cdc99a509549c4028c7122eb6dc90b1a1,CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+4156f9fc5983b09eb97ad3d9abc248b15440b955,"2 Subspace Methods for Face Recognition : Singularity , Regularization , and Robustness",Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+41b1069c06735a20f9b4281001285ee2167da309,Intra-View and Inter-View Supervised Correlation Analysis for Multi-View Feature Learning,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+41b1069c06735a20f9b4281001285ee2167da309,Intra-View and Inter-View Supervised Correlation Analysis for Multi-View Feature Learning,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+41b1069c06735a20f9b4281001285ee2167da309,Intra-View and Inter-View Supervised Correlation Analysis for Multi-View Feature Learning,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+4115652b7fad7a474b5af1f4c063b1f9717b1bf8,Exploring the Feasibility of Prompting Daily Task Execution using the NAO Humanoid Robot with Children with Autism Spectrum Disorder,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+417df443367334351111a064a601355450b2531f,Building structural similarity database for metric learning,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+419550e7b918c64785f087b17f7fde6c94bc6d4e,Distributional semantics with eyes: using image analysis to improve computational representations of word meaning,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+419550e7b918c64785f087b17f7fde6c94bc6d4e,Distributional semantics with eyes: using image analysis to improve computational representations of word meaning,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
839a2155995acc0a053a326e283be12068b35cb8,Handcrafted Local Features are Convolutional Neural Networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
83fd2d2d5ad6e4e153672c9b6d1a3785f754b60e,Quantifying naturalistic social gaze in fragile X syndrome using a novel eye tracking paradigm.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
83fd2d2d5ad6e4e153672c9b6d1a3785f754b60e,Quantifying naturalistic social gaze in fragile X syndrome using a novel eye tracking paradigm.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+837635f647c42d03812a7f4ab5f87c5a49372a0b,Gait Recognition Using Gait Entropy Image,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
8356832f883207187437872742d6b7dc95b51fde,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
8356832f883207187437872742d6b7dc95b51fde,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
8356832f883207187437872742d6b7dc95b51fde,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
8356832f883207187437872742d6b7dc95b51fde,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
8356832f883207187437872742d6b7dc95b51fde,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
8356832f883207187437872742d6b7dc95b51fde,Adversarial Perturbations Against Real-Time Video Classification Systems,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+83a811fd947415df2413d15386dbc558f07595cb,Fine-grained Discriminative Localization via Saliency-guided Faster R-CNN,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+83a811fd947415df2413d15386dbc558f07595cb,Fine-grained Discriminative Localization via Saliency-guided Faster R-CNN,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
835e510fcf22b4b9097ef51b8d0bb4e7b806bdfd,Unsupervised Learning of Sequence Representations by Autoencoders,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+832ed998ff123d4e0f86e6e3fd0d9f5428864600,"PReMVOS : Proposal-generation , Refinement and Merging for the DAVIS Challenge on Video Object Segmentation 2018",RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+83d16fb8f53156c9e2b28d75abb6532af515440f,Large-scale Document Labeling using Supervised Sequence Embedding,Drexel University,Drexel University,"Drexel University, Arch Street, Powelton Village, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.95740000,-75.19026706,edu,
831d661d657d97a07894da8639a048c430c5536d,Weakly Supervised Facial Analysis with Dense Hyper-Column Features,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8370912226ee7783c459368593bc3f88310b1414,"Biometrics : An Overview of the Technology , Issues and Applications",Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
+832b37fab195a8ed71614c87666b9f6e71e367c6,Robustness to Occlusions by Reducing Filter Support,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
+832b37fab195a8ed71614c87666b9f6e71e367c6,Robustness to Occlusions by Reducing Filter Support,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
83295bce2340cb87901499cff492ae6ff3365475,Deep Multi-Center Learning for Face Alignment,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
83295bce2340cb87901499cff492ae6ff3365475,Deep Multi-Center Learning for Face Alignment,East China Normal University,East China Normal University,"华东师范大学, 3663, 中山北路, 曹家渡, 普陀区, 普陀区 (Putuo), 上海市, 200062, 中国",31.22849230,121.40211389,edu,
83e96ed8a4663edaa3a5ca90b7ce75a1bb595b05,Recognition from Appearance Subspaces across Image Sets of Variable Scale,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+83e8bbbccb8613de490b1a362dd3fedc411cbfe0,A3FD: Accurate 3D Face Detection,University of Milan,University of Milan,"Milan Avenue, Ray Mar Terrace, University City, St. Louis County, Missouri, 63130, USA",38.67966620,-90.32628160,edu,
831226405bb255527e9127b84e8eaedd7eb8e9f9,A Motion-Based Feature for Event-Based Pattern Recognition,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
831226405bb255527e9127b84e8eaedd7eb8e9f9,A Motion-Based Feature for Event-Based Pattern Recognition,Portland State University,Portland State University,"Portland State University, Southwest Park Avenue, University District, Portland Downtown, Portland, Multnomah County, Oregon, 97201, USA",45.51181205,-122.68492999,edu,
+8328ced86dffd1bfe300dca9e960ee328ae9ab0d,Gradient-Domain Techniques for Image & Video Processing,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
8384e104796488fa2667c355dd15b65d6d5ff957,A Discriminative Latent Model of Image Region and Object Tag Correspondence,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
8384e104796488fa2667c355dd15b65d6d5ff957,A Discriminative Latent Model of Image Region and Object Tag Correspondence,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
8323529cf37f955fb3fc6674af6e708374006a28,Evaluation of Face Resolution for Expression Analysis,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+832377d50d133da3514ae3c51c0e6043ab856eea,Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+832377d50d133da3514ae3c51c0e6043ab856eea,Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+837792b672a3a4a06a22b2c26a8ecd3812fe8330,A Unified Bayesian Framework for Adaptive Visual Tracking,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+833c1c0180ca36ea07ecfe44caf2b739c94f511e,Predicting Ground-Level Scene Layout from Aerial Imagery,University of Kentucky,University of Kentucky,"University of Kentucky, Columbia Avenue, Sorority Circle, Lexington, Fayette County, Kentucky, 40508, USA",38.03337420,-84.50177580,edu,
+83c695de8b42e592b3f23948f90b699b82c0b068,Fusing Crowd Density Maps and Visual Object Trackers for People Tracking in Crowd Scenes,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+833b6e61468fe655b5067ca91608fc37246c767b,FERA 2015 - second Facial Expression Recognition and Analysis challenge,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+833b6e61468fe655b5067ca91608fc37246c767b,FERA 2015 - second Facial Expression Recognition and Analysis challenge,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+833b6e61468fe655b5067ca91608fc37246c767b,FERA 2015 - second Facial Expression Recognition and Analysis challenge,Binghamton University,Binghamton University,"Binghamton University Downtown Center, Washington Street, Downtown, Binghamton, Broome County, New York, 13901, USA",42.09580770,-75.91455689,edu,
+833b6e61468fe655b5067ca91608fc37246c767b,FERA 2015 - second Facial Expression Recognition and Analysis challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+833b6e61468fe655b5067ca91608fc37246c767b,FERA 2015 - second Facial Expression Recognition and Analysis challenge,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+833b6e61468fe655b5067ca91608fc37246c767b,FERA 2015 - second Facial Expression Recognition and Analysis challenge,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+83acde484baf81ee3a09c30ec250c11c111d2c0a,Tracking articulated human movements witha component based approach to boosted multiple instance learning,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+838ed2aae603dec5851ebf5e4bc64b54db7f34be,Real-Time Ensemble Based Face Recognition System for Humanoid Robots,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
+8318f563f915031c677decc3d133c2aee803591d,Efficient Sparse Representation Classification Using Adaptive Clustering,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+83d956ed39127058e02395924f96b68e2f8289e0,Efficient video multicast in wireless surveillance networks for intelligent building,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+83d956ed39127058e02395924f96b68e2f8289e0,Efficient video multicast in wireless surveillance networks for intelligent building,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+836a4ee4bffafba259e2d824fc89020de86daab0,Identification of Structurally Damaged Areas in Airborne Oblique Images Using a Visual-Bag-of-Words Approach,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
8334da483f1986aea87b62028672836cb3dc6205,Fully Associative Patch-Based 1-to-N Matcher for Face Recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
831b4d8b0c0173b0bac0e328e844a0fbafae6639,Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
831b4d8b0c0173b0bac0e328e844a0fbafae6639,Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
831b4d8b0c0173b0bac0e328e844a0fbafae6639,Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+1b8290ff2fe1b04df14f2504b38beb749e2e75ca,Classifying Unseen Instances by Learning Class-Independent Similarity Functions,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+1b7f9cc57ab8f3f551bdb0d5f153191ec403895e,Learning Multiple Tasks with Multilinear Relationship Networks,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+1be8aa30f905577c1d60150fb6ba84ddaabb2f6e,Motionlets: Mid-level 3D Parts for Human Motion Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+1be8aa30f905577c1d60150fb6ba84ddaabb2f6e,Motionlets: Mid-level 3D Parts for Human Motion Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+1b3e66bef13f114943d460b4f942e941b4761ba2,Subspace Approximation of Face Recognition Algorithms: An Empirical Study,University of South Florida,University of South Florida,"University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA",28.05999990,-82.41383619,edu,
+1b3e66bef13f114943d460b4f942e941b4761ba2,Subspace Approximation of Face Recognition Algorithms: An Empirical Study,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
+1b92fdffa3f87c1081e88c41b5fb0d7d31b3873e,Illumination Insensitive Face Representation for Face Recognition Based on Modified Weberface,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+1b92fdffa3f87c1081e88c41b5fb0d7d31b3873e,Illumination Insensitive Face Representation for Face Recognition Based on Modified Weberface,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
1b635f494eff2e5501607ebe55eda7bdfa8263b8,USC at THUMOS 2014,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+1b1d31dcd365c48ca39b4eadcdabf1c70104e490,On use of biometrics in forensics: Gait and ear,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+1bbe0371ca22c2fdb6e0d098049bbf6430324bdb,"Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval",University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+1bbe0371ca22c2fdb6e0d098049bbf6430324bdb,"Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1bbe0371ca22c2fdb6e0d098049bbf6430324bdb,"Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval",University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+1bbe0371ca22c2fdb6e0d098049bbf6430324bdb,"Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval",University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+1be9ee50f4d4f59b9761a366bba9127213dc4f33,You cannot gamble on others: Dissociable systems for strategic uncertainty and risk in the brain,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+1bcc4f0f58848190ae0b2098eadf06002d5f70b4,Scalable object-class retrieval with approximate and top-k ranking,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+1b2ad281ef74e366ec58221b13edc6eefdb170f8,Use and Usefulness of Dynamic Face Stimuli for Face Perception Studies—a Review of Behavioral Findings and Methodology,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+1b2ad281ef74e366ec58221b13edc6eefdb170f8,Use and Usefulness of Dynamic Face Stimuli for Face Perception Studies—a Review of Behavioral Findings and Methodology,Max Planck Institute for Biological Cybernetics,Max Planck Institute for Biological Cybernetics,"Max-Planck-Institut für Biologische Kybernetik, 8, Max-Planck-Ring, Max-Planck-Institut, Wanne, Tübingen, Landkreis Tübingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72076, Deutschland",48.53691250,9.05922533,edu,
+1b2ad281ef74e366ec58221b13edc6eefdb170f8,Use and Usefulness of Dynamic Face Stimuli for Face Perception Studies—a Review of Behavioral Findings and Methodology,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+1b2ad281ef74e366ec58221b13edc6eefdb170f8,Use and Usefulness of Dynamic Face Stimuli for Face Perception Studies—a Review of Behavioral Findings and Methodology,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+1b2ad281ef74e366ec58221b13edc6eefdb170f8,Use and Usefulness of Dynamic Face Stimuli for Face Perception Studies—a Review of Behavioral Findings and Methodology,Universität Hamburg,Universität Hamburg,"Informatikum, 30, Vogt-Kölln-Straße, Stellingen, Eimsbüttel, Hamburg, 22527, Deutschland",53.59948200,9.93353436,edu,
+1b5866c5b3715b410bfb4ccca6d42b32162d4ef1,Now You See Me: Deep Face Hallucination for Unviewed Sketches,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+1b5866c5b3715b410bfb4ccca6d42b32162d4ef1,Now You See Me: Deep Face Hallucination for Unviewed Sketches,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+1bb652545b316701faf582d673a98060ee426f37,Robust Object Co-detection,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+1bb652545b316701faf582d673a98060ee426f37,Robust Object Co-detection,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
1b5875dbebc76fec87e72cee7a5263d325a77376,Learnt Quasi-Transitive Similarity for Retrieval from Large Collections of Faces,University of St Andrews,University of St Andrews,"University of St Andrews, North Street, Albany Park Student accommodation, Carngour, St Andrews, Fife, Scotland, KY16 9AJ, UK",56.34119840,-2.79309380,edu,
+1be10b1f05fe7a5dd28cbb63d61a992c5d9b611a,Light-weight Head Pose Invariant Gaze Tracking,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+1bd1645a629f1b612960ab9bba276afd4cf7c666,End-to-End People Detection in Crowded Scenes,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1bd1645a629f1b612960ab9bba276afd4cf7c666,End-to-End People Detection in Crowded Scenes,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
1bdfb3deae6e6c0df6537efcd1d7edcb4d7a96e9,Groupwise Constrained Reconstruction for Subspace Clustering,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+1babf4bc962593593c83ac70f3b7ee64b3e5a680,Detecting Objects Using Deformation Dictionaries,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+1babf4bc962593593c83ac70f3b7ee64b3e5a680,Detecting Objects Using Deformation Dictionaries,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+1b21acf8daaf86c4f2228fa3f5e9aa38ab8ad30d,Cross-scene crowd counting via deep convolutional neural networks,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+1b21acf8daaf86c4f2228fa3f5e9aa38ab8ad30d,Cross-scene crowd counting via deep convolutional neural networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+1b21acf8daaf86c4f2228fa3f5e9aa38ab8ad30d,Cross-scene crowd counting via deep convolutional neural networks,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+1b73bd672c6abe6918f91812f4334db23189d1d6,Adversarial PoseNet: A Structure-Aware Convolutional Network for Human Pose Estimation,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+1b73bd672c6abe6918f91812f4334db23189d1d6,Adversarial PoseNet: A Structure-Aware Convolutional Network for Human Pose Estimation,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+1b73bd672c6abe6918f91812f4334db23189d1d6,Adversarial PoseNet: A Structure-Aware Convolutional Network for Human Pose Estimation,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
1b794b944fd462a2742b6c2f8021fecc663004c9,A Hierarchical Probabilistic Model for Facial Feature Detection,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+1bca1a09e2ef62b1960c23ff6653ae2d5aef5718,Comparison of human face matching behavior and computational image similarity measure,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+1bca1a09e2ef62b1960c23ff6653ae2d5aef5718,Comparison of human face matching behavior and computational image similarity measure,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
1b7ae509c8637f3c123cf6151a3089e6b8a0d5b2,From Few to Many: Generative Models for Recognition Under Variable Pose and Illumination,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
1b7ae509c8637f3c123cf6151a3089e6b8a0d5b2,From Few to Many: Generative Models for Recognition Under Variable Pose and Illumination,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
1b7ae509c8637f3c123cf6151a3089e6b8a0d5b2,From Few to Many: Generative Models for Recognition Under Variable Pose and Illumination,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
1b41d4ffb601d48d7a07dbbae01343f4eb8cc38c,Exploiting Temporal Information for DCNN-Based Fine-Grained Object Classification,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
1b41d4ffb601d48d7a07dbbae01343f4eb8cc38c,Exploiting Temporal Information for DCNN-Based Fine-Grained Object Classification,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
1b41d4ffb601d48d7a07dbbae01343f4eb8cc38c,Exploiting Temporal Information for DCNN-Based Fine-Grained Object Classification,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+1b248ed8e7c9514648cd598960fadf9ab17e7fe8,"From apparent to real age: gender, age, ethnic, makeup, and expression bias analysis in real age estimation",University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
+1b248ed8e7c9514648cd598960fadf9ab17e7fe8,"From apparent to real age: gender, age, ethnic, makeup, and expression bias analysis in real age estimation",University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+1b248ed8e7c9514648cd598960fadf9ab17e7fe8,"From apparent to real age: gender, age, ethnic, makeup, and expression bias analysis in real age estimation",University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
+1bbf4275c1dbe3203b0e2261114850fbe8ca7e0e,Higher level techniques for the artistic rendering of images and video,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+1b715b4cef51be6bd5dd73c0d30257d853411a52,Fourth-Person Sensing for Pro-active Services,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
1b60b8e70859d5c85ac90510b370b501c5728620,Using Detailed Independent 3D Sub-models to Improve Facial Feature Localisation and Pose Estimation,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+1bc5c938b79f23afb9931c99377d6ce7a99bf8fb,Multi-view 3D face reconstruction with deep recurrent neural networks,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
1bc9aaa41c08bbd0c01dd5d7d7ebf3e48ae78113,k-Same-Net: k-Anonymity with Generative Deep Neural Networks for Face Deidentification,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
1bc9aaa41c08bbd0c01dd5d7d7ebf3e48ae78113,k-Same-Net: k-Anonymity with Generative Deep Neural Networks for Face Deidentification,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+1b93698c1784db4abf72b500e51d4806e6430522,Re-id: Hunting Attributes in the Wild,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
1bcbf2a4500d27d036e0f9d36d7af71c72f8ab61,Recognizing facial expression: machine learning and application to spontaneous behavior,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+1b5baa2ff3b6f88865fd244d87d39d58282d8597,Large-Scale Image Classification using High Performance Clustering,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+1b72222651c5b0295981e26d1333fadfcfb6a480,High-Quality Face Image SR Using Conditional Generative Adversarial Networks,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+1b72222651c5b0295981e26d1333fadfcfb6a480,High-Quality Face Image SR Using Conditional Generative Adversarial Networks,National Chung Hsing University,National Chung Hsing University,"國立中興大學, 145, 興大路, 積善里, 頂橋子頭, 南區, 臺中市, 402, 臺灣",24.12084345,120.67571165,edu,
1bad8a9640cdbc4fe7de12685651f44c4cff35ce,THETIS: Three Dimensional Tennis Shots a Human Action Dataset,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
1be0ce87bb5ba35fa2b45506ad997deef6d6a0a8,EXMOVES: Classifier-based Features for Scalable Action Recognition,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+1b6f3139b1e59b90ab1aaf978359229b75985b49,Learning with a Wasserstein Loss,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+1b6f3139b1e59b90ab1aaf978359229b75985b49,Learning with a Wasserstein Loss,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+1b6f3139b1e59b90ab1aaf978359229b75985b49,Learning with a Wasserstein Loss,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
1badfeece64d1bf43aa55c141afe61c74d0bd25e,"OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning",Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+1bd65302bca0c1a593490088a0ce85988f3cc90a,"Ten Years of Pedestrian Detection, What Have We Learned?",Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+7710f1fc67f11a91afaa951f1b26e07e280391c5,Msee: Stochastic Cognitive Linguistic Behavior Models for Semantic Sensing,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
+77fe6c859a59ac4438794d38d018d1e3c02d36dd,The µ-opioid system promotes visual attention to faces and eyes.,University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+77fe6c859a59ac4438794d38d018d1e3c02d36dd,The µ-opioid system promotes visual attention to faces and eyes.,University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+77fe6c859a59ac4438794d38d018d1e3c02d36dd,The µ-opioid system promotes visual attention to faces and eyes.,University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+77fe6c859a59ac4438794d38d018d1e3c02d36dd,The µ-opioid system promotes visual attention to faces and eyes.,University of Oslo,University of Oslo,"UiO, Moltke Moes vei, Blindern, Nordre Aker, Oslo, 0851, Norge",59.93891665,10.72170765,edu,
+778ce81457383bd5e3fdb11b145ded202ebb4970,Semantic Compositional Networks for Visual Captioning,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+7778068b0ea08bf85824d49045a8facbf90c4803,Deep Subspace Clustering Networks,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
7735f63e5790006cb3d989c8c19910e40200abfc,Multispectral Imaging For Face Recognition Over Varying Illumination,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
+7710232a3d8bb1ef4ab0b5b6042bed19380bf0de,Image description with a goal: Building efficient discriminating expressions for images,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+7710232a3d8bb1ef4ab0b5b6042bed19380bf0de,Image description with a goal: Building efficient discriminating expressions for images,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
+7710232a3d8bb1ef4ab0b5b6042bed19380bf0de,Image description with a goal: Building efficient discriminating expressions for images,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+7710232a3d8bb1ef4ab0b5b6042bed19380bf0de,Image description with a goal: Building efficient discriminating expressions for images,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+7710232a3d8bb1ef4ab0b5b6042bed19380bf0de,Image description with a goal: Building efficient discriminating expressions for images,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
77b1db2281292372c38926cc4aca32ef056011dc,Children’s Interpretation of Facial Expressions: The Long Path from Valence-Based to Specific Discrete Categories,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
+77ee75f96e6498ccc7bb7ebcca2acd7cc4e33229,Sinkhorn AutoEncoders,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+77ee75f96e6498ccc7bb7ebcca2acd7cc4e33229,Sinkhorn AutoEncoders,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+77cfe37cd98910de3601795131305bea639a435a,Accelerated learning of Generalized Sammon Mappings,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+779db93204bee4a9540db1e79ceb0b45e5af77e9,Learning actions from the Web,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+779eb6a059990b9cee55e0add7bc34aed87b3733,3D Human Pose Estimation in the Wild by Adversarial Learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+779eb6a059990b9cee55e0add7bc34aed87b3733,3D Human Pose Estimation in the Wild by Adversarial Learning,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+779eb6a059990b9cee55e0add7bc34aed87b3733,3D Human Pose Estimation in the Wild by Adversarial Learning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
77c53ec6ea448db4dad586e002a395c4a47ecf66,Face Recognition Based on Facial Features,National University of Sciences and Technology,National University of Sciences and Technology,"National University of Sciences and Technology (NUST), Kashmir Highway, جی - 10, ICT, وفاقی دارالحکومت اسلام آباد, 44000, پاکستان",33.64434700,72.98850790,edu,
+77685c77a1fa39890006fe13f43738aac49a2c51,Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+775be2fe9e6d7ca97209692ee3f85fb0f1b125af,ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+77a0e3e366e061b0ceb4a7a901ee18e420185447,Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+77a53d4141a8081657ce08b13dc3328ac4a4e689,You'll never walk alone: Modeling social behavior for multi-target tracking,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
774cbb45968607a027ae4729077734db000a1ec5,From Bikers to Surfers: Visual Recognition of Urban Tribes,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+775c51b965e8ff37646a265aab64136b4a620526,Three viewpoints toward exemplar SVM,National Institute of Advanced Industrial Science and Technology,National Institute of Advanced Industrial Science and Technology,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+77acef6d0146465b9e9ad5817ad3e2c20ae64566,Informative Features for Model Comparison,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+77acef6d0146465b9e9ad5817ad3e2c20ae64566,Informative Features for Model Comparison,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+7729b0d1d3e26ce0eec1f019f3a98d6c7d926e10,Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+7729b0d1d3e26ce0eec1f019f3a98d6c7d926e10,Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+771431afa9b5c936dc970db8d02ae06f49d68638,TabletGaze : Dataset and Algorithm for Unconstrained Appearance-based Gaze Estimation in Mobile Tablets,Rice University,Rice University,"Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA",29.71679145,-95.40478113,edu,
+779e5beb515ed26c47dbfc08304fe49233063c1b,Generating more realistic images using gated MRF's,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+778eefd9f0f6189456fc25b7cdd2c3f4403a37a8,Audiovisual diarization of people in video content,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+77be85f6c3c465ef8e17d3ec6251794cf4ff5940,Generative Domain-Migration Hashing for Sketch-to-Image Retrieval,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+771e78ccea7a03dd94bca10a7215dfe3b0f4623b,Supervised Geodesic Propagation for Semantic Label Transfer,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
7792fbc59f3eafc709323cdb63852c5d3a4b23e9,Pose from Action: Unsupervised Learning of Pose Features based on Motion,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
7792fbc59f3eafc709323cdb63852c5d3a4b23e9,Pose from Action: Unsupervised Learning of Pose Features based on Motion,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
77fbbf0c5729f97fcdbfdc507deee3d388cd4889,Pose-Robust 3D Facial Landmark Estimation from a Single 2D Image,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
776362314f1479f5319aaf989624ac604ba42c65,Attribute Learning in Large-Scale Datasets,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+773ecf8cfa7e544ac48cf146b71df19146e1400e,Improving Shape Deformation in Unsupervised Image-to-Image Translation,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+773ecf8cfa7e544ac48cf146b71df19146e1400e,Improving Shape Deformation in Unsupervised Image-to-Image Translation,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+774b649c75078e10759b3b6c8ea581e68fc45a40,Robust Anchor Embedding for Unsupervised Video Person re-IDentification in the Wild,Hong Kong Baptist University,Hong Kong Baptist University,"香港浸會大學 Hong Kong Baptist University, 安明街 On Ming Street, 石門 Shek Mun, 石古壟 Shek Kwu Lung, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1132, 中国",22.38742010,114.20822220,edu,
+77eba8289e257df835e16ce8e0919acebd02f7e4,Face Mosaicing for Pose Robust Video-Based Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+7771807cd05f78a4591f2d0b094ddd3e0bd5339a,Adaptive Feeding: Achieving Fast and Accurate Detections by Adaptively Combining Object Detectors,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
77fb9e36196d7bb2b505340b6b94ba552a58b01b,Detecting the Moment of Completion: Temporal Models for Localising Action Completion,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+48059da276a8a93e0bb3faaa8421589f09377559,Eigengaze - covert behavioral biometric exploiting visual attention characteristics,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
486840f4f524e97f692a7f6b42cd19019ee71533,DeepVisage: Making Face Recognition Simple Yet With Powerful Generalization Skills,École Centrale de Lyon,Laboratoire LIRIS,"40 Avenue Guy de Collongue, 69130 Écully, France",45.78359660,4.76789480,edu,
486840f4f524e97f692a7f6b42cd19019ee71533,DeepVisage: Making Face Recognition Simple Yet With Powerful Generalization Skills,Safran Identity and Security,Safran Identity & Security,"11 Boulevard Gallieni, 92130 Issy-les-Moulineaux, France",48.83249300,2.26747400,company,
+48810b60f1fe6fcb344538d5de8c54e5d64c20bb,Deep Sketch-Photo Face Recognition Assisted by Facial Attributes,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
48463a119f67ff2c43b7c38f0a722a32f590dfeb,Intelligent Method for Face Recognition of Infant,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
48463a119f67ff2c43b7c38f0a722a32f590dfeb,Intelligent Method for Face Recognition of Infant,Banaras Hindu University,Banaras Hindu University,"काशी हिन्दू विश्वविद्यालय, Semi Circle Road 2, ワーラーナシー, Jodhpur Colony, Vārānasi, Varanasi, Uttar Pradesh, 221005, India",25.26628870,82.99279690,edu,
48463a119f67ff2c43b7c38f0a722a32f590dfeb,Intelligent Method for Face Recognition of Infant,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
@@ -3880,11 +10795,24 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 488d3e32d046232680cc0ba80ce3879f92f35cac,Facial Expression Recognition Using Texture Description of Displacement Image,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
488d3e32d046232680cc0ba80ce3879f92f35cac,Facial Expression Recognition Using Texture Description of Displacement Image,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
488d3e32d046232680cc0ba80ce3879f92f35cac,Facial Expression Recognition Using Texture Description of Displacement Image,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+482a31cd4705f3d56e468cc33486847fc100f568,Dynamic Probabilistic CCA for Analysis of Affective Behaviour,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+482a31cd4705f3d56e468cc33486847fc100f568,Dynamic Probabilistic CCA for Analysis of Affective Behaviour,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
+482a31cd4705f3d56e468cc33486847fc100f568,Dynamic Probabilistic CCA for Analysis of Affective Behaviour,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+48381007b85e8a3b74e5401b2dfc1a5dfc897622,Sparse Representation and Dictionary Learning for Biometrics and Object Tracking,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+48381007b85e8a3b74e5401b2dfc1a5dfc897622,Sparse Representation and Dictionary Learning for Biometrics and Object Tracking,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+48b9f9ddf17bd29b957b09f9000576e53acf8719,Ringtail: Feature Selection For Easier Nowcasting,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+48b9f9ddf17bd29b957b09f9000576e53acf8719,Ringtail: Feature Selection For Easier Nowcasting,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+48b9f9ddf17bd29b957b09f9000576e53acf8719,Ringtail: Feature Selection For Easier Nowcasting,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+48b9f9ddf17bd29b957b09f9000576e53acf8719,Ringtail: Feature Selection For Easier Nowcasting,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+480040b64a972bf51f8debabc4f9421fd2c7b829,"Towards recognizing ""cool"": can end users help computer vision recognize subjective attributes of objects in images?",Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+48019c177ec1e650d0d67feaaf38ae12a74fa644,Markov Network-Based Unified Classifier for Face Identification,Korea Advanced Institute of Science and Technology,Korea Advanced Institute of Science and Technology,"카이스트, 291, 대학로, 온천2동, 온천동, 유성구, 대전, 34141, 대한민국",36.36971910,127.36253700,edu,
+48d66e07041b8aa042d7a3d263fddc624bbc1e32,Multiclass Learning with Simplex Coding,McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
48fea82b247641c79e1994f4ac24cad6b6275972,Mining discriminative components with low-rank and sparsity constraints for face recognition,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
48734cb558b271d5809286447ff105fd2e9a6850,Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural Networks,University of Denver,University of Denver,"University of Denver, Driscoll Bridge, Denver, Denver County, Colorado, 80208, USA",39.67665410,-104.96220300,edu,
48a417cfeba06feb4c7ab30f06c57ffbc288d0b5,Robust Dictionary Learning by Error Source Decomposition,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
48c41ffab7ff19d24e8df3092f0b5812c1d3fb6e,Multi-modal Embedding for Main Product Detection in Fashion,Waseda University,Waseda University,"早稲田大学 北九州キャンパス, 2-2, 有毛引野線, 八幡西区, 北九州市, 福岡県, 九州地方, 808-0135, 日本",33.88987280,130.70856205,edu,
488a61e0a1c3768affdcd3c694706e5bb17ae548,Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+48ffb705e94dde426b7241108ca915a5ecab6414,The Human Factor: Behavioral and Neural Correlates of Humanized Perception in Moral Decision Making,University of Vienna,University of Vienna,"Uni Wien, 1, Universitätsring, Schottenviertel, KG Innere Stadt, Innere Stadt, Wien, 1010, Österreich",48.21313020,16.36068653,edu,
48910f9b6ccc40226cd4f105ed5291571271b39e,Learning Discriminative Fisher Kernels,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
48a9241edda07252c1aadca09875fabcfee32871,Convolutional Experts Constrained Local Model for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
48a9241edda07252c1aadca09875fabcfee32871,Convolutional Experts Constrained Local Model for Facial Landmark Detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
@@ -3895,109 +10823,337 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 48174c414cfce7f1d71c4401d2b3d49ba91c5338,Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
48174c414cfce7f1d71c4401d2b3d49ba91c5338,Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
48174c414cfce7f1d71c4401d2b3d49ba91c5338,Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+48143b1270a2df096577e6681b1f1ceadacf73e8,An Improved Evaluation Framework for Generative Adversarial Networks,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+4895bc6e7ebb894e73c08b9dea50eea293c8dcbc,A Deep Learning Pipeline for Image Understanding and Acoustic Modeling,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+480888bad59b314236f2d947ebf308ae146c98e4,Zoom Better to See Clearer: Human and Object Parsing with Hierarchical Auto-Zoom Net,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+483e19f50ff47b0bf5e57b0cea65a7f084779b92,Annotation Artifacts in Natural Language Inference Data,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+483e19f50ff47b0bf5e57b0cea65a7f084779b92,Annotation Artifacts in Natural Language Inference Data,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+483e19f50ff47b0bf5e57b0cea65a7f084779b92,Annotation Artifacts in Natural Language Inference Data,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+483e19f50ff47b0bf5e57b0cea65a7f084779b92,Annotation Artifacts in Natural Language Inference Data,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
488375ae857a424febed7c0347cc9590989f01f7,Convolutional neural networks for the analysis of broadcasted tennis games,University of Crete,University of Crete,"House of Europe, Μακεδονίας, Ρέθυμνο, Δήμος Ρεθύμνης, Περιφερειακή Ενότητα Ρεθύμνου, Περιφέρεια Κρήτης, Κρήτη, 930100, Ελλάδα",35.37130240,24.47544080,edu,
4836b084a583d2e794eb6a94982ea30d7990f663,Cascaded Face Alignment via Intimacy Definition Feature,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+4889d2927a9120931978ec487f55114d99eeb65d,Comparing Generative Adversarial Network Techniques for Image Creation and Modification,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+4889d2927a9120931978ec487f55114d99eeb65d,Comparing Generative Adversarial Network Techniques for Image Creation and Modification,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+482e8a9323fca1e27fccf03d2a58a36873d0ae10,Assessing Social Cognition of Persons with Schizophrenia in a Chinese Population: A Pilot Study,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+482e8a9323fca1e27fccf03d2a58a36873d0ae10,Assessing Social Cognition of Persons with Schizophrenia in a Chinese Population: A Pilot Study,University of Texas at Dallas,University of Texas at Dallas,"University of Texas at Dallas, Richardson, Dallas County, Texas, 78080, USA",32.98207990,-96.75662780,edu,
+482321a30da9edc4da8efb73f8e7d763c56811f2,Categorizing Turn-Taking Interactions,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+488fff23542ff397cdb1ced64db2c96320afc560,Weakly supervised localization of novel objects using appearance transfer,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+48cdb6a640b4259c61c476fb529d7c176e8345a9,Eyelid-openness and mouth curvature influence perceived intelligence beyond attractiveness.,University of St Andrews,University of St Andrews,"University of St Andrews, North Street, Albany Park Student accommodation, Carngour, St Andrews, Fife, Scotland, KY16 9AJ, UK",56.34119840,-2.79309380,edu,
+48cdb6a640b4259c61c476fb529d7c176e8345a9,Eyelid-openness and mouth curvature influence perceived intelligence beyond attractiveness.,University of St Andrews,University of St Andrews,"University of St Andrews, North Street, Albany Park Student accommodation, Carngour, St Andrews, Fife, Scotland, KY16 9AJ, UK",56.34119840,-2.79309380,edu,
+486c9a0e5eb1e0bf107c31c2bf9689b25e18383b,Face Recognition: Primates in the Wild,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+48d784e556646cf1a42eff051cb2083a2d8e3234,Automatic action unit detection in infants using convolutional neural network,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+48d784e556646cf1a42eff051cb2083a2d8e3234,Automatic action unit detection in infants using convolutional neural network,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4813d9332a1f3ef2bf5846e81005895322310bed,3D Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+488370572904a8fd97f5bc68fbdf0b3b3984cc76,Alibaba-Venus at ActivityNet Challenge 2018-Task C Trimmed Event Recognition ( Moments in Time ),"Alibaba Group, Hangzhou, China","Alibaba Group, Hangzhou, China","Alibaba Group, 五常街道, 余杭区 (Yuhang), 杭州市 Hangzhou, 浙江省, 中国",30.28106540,120.02139087,edu,
4896909796f9bd2f70a2cb24bf18daacd6a12128,Spatial Bag of Features Learning for Large Scale Face Image Retrieval,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+484c380c322b2b5cb5756c9e94608949fb5d5e4d,Temporal face embedding and propagation in photo collections,Technion,Technion,"Haifa, 3200003, Israel",32.77677830,35.02312710,edu,
481fb0a74528fa7706669a5cce6a212ac46eaea3,Recognizing RGB Images by Learning from RGB-D Data,"Institute for Infocomm Research, Singapore","Institute for Infocomm Research, Singapore","1 Fusionopolis Way, #21-01 Connexis, Singapore 138632",1.29889260,103.78731070,edu,
481fb0a74528fa7706669a5cce6a212ac46eaea3,Recognizing RGB Images by Learning from RGB-D Data,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+4822c1bf765cf99193a231c000c19ae5d0c10a00,Multi-object Tracking via Constrained Sequential Labeling,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+480492ca998b3393b370d176d1f990a3db1c8e12,Factorized Binary Codes for Large-Scale Nearest Neighbor Search,University of British Columbia,University of British Columbia,"University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.25839375,-123.24658161,edu,
+481fde422a31e21ac12644e0df95cf66528f52c2,Integration of Local Image Cues for Probabilistic 2D Pose Recovery,Kingston University,Kingston University,"Kingston University, Kingston Hill, Kingston Vale, Kingston-upon-Thames, London, Greater London, England, KT2 7TF, UK",51.42930860,-0.26840440,edu,
+4823dcfb0bdc1af20e4da85035b8fc2c71a6add1,Exploring Structural Information and Fusing Multiple Features for Person Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+706b1123217febf934ee5c33b4af27507a85771a,AVEC 2013: the continuous audio/visual emotion and depression recognition challenge,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+706b1123217febf934ee5c33b4af27507a85771a,AVEC 2013: the continuous audio/visual emotion and depression recognition challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+706b1123217febf934ee5c33b4af27507a85771a,AVEC 2013: the continuous audio/visual emotion and depression recognition challenge,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+706b1123217febf934ee5c33b4af27507a85771a,AVEC 2013: the continuous audio/visual emotion and depression recognition challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+706b1123217febf934ee5c33b4af27507a85771a,AVEC 2013: the continuous audio/visual emotion and depression recognition challenge,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+70eeacf9f86ba08fceb3dd703cf015016dac1930,Coupled information-theoretic encoding for face photo-sketch recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+70eeacf9f86ba08fceb3dd703cf015016dac1930,Coupled information-theoretic encoding for face photo-sketch recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+70eeacf9f86ba08fceb3dd703cf015016dac1930,Coupled information-theoretic encoding for face photo-sketch recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+70eeacf9f86ba08fceb3dd703cf015016dac1930,Coupled information-theoretic encoding for face photo-sketch recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
70580ed8bc482cad66e059e838e4a779081d1648,Gender Classification using Multi-Level Wavelets on Real World Face Images,Shaheed Zulfikar Ali Bhutto Institute of Science and Technology,Shaheed Zulfikar Ali Bhutto Institute of,"Shaheed Zulfikar Ali Bhutto Institute of Science and Technology - Karachi Campus, Block 5, Clifton Block 5, CBC, ڪراچي Karachi, Karāchi District, سنڌ, 75600, پاکستان",24.81865870,67.03165850,edu,
+70cbbf1ac971a89e18240e70d86fde2ac5190bad,Mammoth Data in the Cloud: Clustering Social Images,Indiana University Bloomington,Indiana University Bloomington,"Indiana University Bloomington, East 17th Street, Bloomington, Monroe County, Indiana, 47408, USA",39.17720475,-86.51540030,edu,
703dc33736939f88625227e38367cfb2a65319fe,Trespassing the Boundaries: Labeling Temporal Bounds for Object Interactions in Egocentric Video,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+7060f6062ba1cbe9502eeaaf13779aa1664224bb,A Glimpse Far into the Future: Understanding Long-term Crowd Worker Quality,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+7033b916a7f2510ca9766b7a8ed15920a9f9e2f3,Which concepts are worth extracting?,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+7033b916a7f2510ca9766b7a8ed15920a9f9e2f3,Which concepts are worth extracting?,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
70db3a0d2ca8a797153cc68506b8650908cb0ada,An Overview of Research Activities in Facial Age Estimation Using the FG-NET Aging Database,Cyprus University of Technology,Cyprus University of Technology,"Mitropoli Building - Cyprus University of Technology, Anexartisias, Limasol - Λεμεσός, Limassol - Λεμεσός, Κύπρος - Kıbrıs, 3036, Κύπρος - Kıbrıs",34.67567405,33.04577648,edu,
+70c012367fd77d6b6dbd97620724fcdf72bb15ea,ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+70c012367fd77d6b6dbd97620724fcdf72bb15ea,ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+70c012367fd77d6b6dbd97620724fcdf72bb15ea,ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
701f56f0eac9f88387de1f556acef78016b05d52,Direct Shape Regression Networks for End-to-End Face Alignment,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
701f56f0eac9f88387de1f556acef78016b05d52,Direct Shape Regression Networks for End-to-End Face Alignment,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
7002d6fc3e0453320da5c863a70dbb598415e7aa,Understanding Discrete Facial Expressions in Video Using an Emotion Avatar Image,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
7071cd1ee46db4bc1824c4fd62d36f6d13cad08a,Face Detection through Scale-Friendly Deep Convolutional Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+7004e0808b0905761b583d74524b932ba66c20dd,Paper Doll Parsing: Retrieving Similar Styles to Parse Clothing Items,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
707a542c580bcbf3a5a75cce2df80d75990853cc,Disentangled Variational Representation for Heterogeneous Face Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
707a542c580bcbf3a5a75cce2df80d75990853cc,Disentangled Variational Representation for Heterogeneous Face Recognition,Johns Hopkins University,"Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA","3400 N Charles St, Baltimore, MD 21218, USA",39.32905300,-76.61942500,edu,
70569810e46f476515fce80a602a210f8d9a2b95,Apparent Age Estimation from Face Images Combining General and Children-Specialized Deep Learning Models,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
704d88168bdfabe31b6ff484507f4a2244b8c52b,MLtuner: System Support for Automatic Machine Learning Tuning,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+703f8f9ed65ab87e67716cbfbee0e323aed5b9f5,Fully Convolutional Adaptation Networks for Semantic Segmentation,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+703f8f9ed65ab87e67716cbfbee0e323aed5b9f5,Fully Convolutional Adaptation Networks for Semantic Segmentation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+709198f1a7d42fb87d46a8f5dc48e23e6564df1c,Visual and semantic similarity in ImageNet,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
703c9c8f20860a1b1be63e6df1622b2021b003ca,Flip-Invariant Motion Representation,National Institute of Advanced Industrial Science and Technology,National Institute of Advanced Industrial Science and Technology,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+70ab0ec5358e40fdcf7247f31e6e927cb21442f1,Exploiting skeletal structure in computer vision annotation with Benders decomposition,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
70a69569ba61f3585cd90c70ca5832e838fa1584,Friendly Faces: Weakly Supervised Character Identification,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+7017a4c7a972d546ef2d59d29bf7c0ba6888e2ba,Human Pose and Shape Estimation from Multi-View Images for Virtual Dressing Rooms,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+704fe3839742e8d022fdc110f3a502e42a0ef89e,Running Head: RACIAL BIAS AND AGE 1 The Generalization of Implicit Racial Bias to Young Black Boys: Automatic Stereotyping or Automatic Prejudice?,University of Iowa,University of Iowa,"University of Iowa, Hawkeye Court, Iowa City, Johnson County, Iowa, 52246, USA",41.66590000,-91.57310307,edu,
+704fe3839742e8d022fdc110f3a502e42a0ef89e,Running Head: RACIAL BIAS AND AGE 1 The Generalization of Implicit Racial Bias to Young Black Boys: Automatic Stereotyping or Automatic Prejudice?,University of Iowa,University of Iowa,"University of Iowa, Hawkeye Court, Iowa City, Johnson County, Iowa, 52246, USA",41.66590000,-91.57310307,edu,
+70af9756f10bf6128a47fef4509df7e8bb9a290e,Sidekick Policy Learning for Active Visual Exploration,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+70be5432677c0fbe000ac0c28dda351a950e0536,Detecting Social Groups in Crowded Surveillance Videos Using Visual Attention,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+70be5432677c0fbe000ac0c28dda351a950e0536,Detecting Social Groups in Crowded Surveillance Videos Using Visual Attention,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+70a3bea7e9a4f7af6e80832d467a457c18d2389a,Generative Adversarial Forests for Better Conditioned Adversarial Learning,Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
70c9d11cad12dc1692a4507a97f50311f1689dbf,Video Frame Synthesis Using Deep Voxel Flow,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
70c9d11cad12dc1692a4507a97f50311f1689dbf,Video Frame Synthesis Using Deep Voxel Flow,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+7031d7fde9f184b72416759f8a9be4155616f456,Benchmarking Face Detection in a Mobile/Tablet Environment,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+1e3df3ca8feab0b36fd293fe689f93bb2aaac591,Multi-task Recurrent Neural Network for Immediacy Prediction,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1e5ca4183929929a4e6f09b1e1d54823b8217b8e,Classification in the Presence of Heavy Label Noise: A Markov Chain Sampling Framework,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
1ef4815f41fa3a9217a8a8af12cc385f6ed137e1,Rendering of Eyes for Eye-Shape Registration and Gaze Estimation,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
1ef4815f41fa3a9217a8a8af12cc385f6ed137e1,Rendering of Eyes for Eye-Shape Registration and Gaze Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
-1ea74780d529a458123a08250d8fa6ef1da47a25,Videos from the 2013 Boston Marathon,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1e8e3a954762f58501b970928071ed1b58b4fe40,Self Scaled Regularized Robust Regression,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+1e394f669c4f63c593677d2850c3d022a6fc1ac8,Multi-view Registration Based on Weighted Low Rank and Sparse Matrix Decomposition of Motions,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
+1ef368e79d1a33d700905221696e552745e1ec7f,On Crater Verification Using Mislocalized Crater Regions,University of Nevada,University of Nevada,"Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA",39.54694490,-119.81346566,edu,
+1ea74780d529a458123a08250d8fa6ef1da47a25,Videos from the 2013 Boston Marathon : An Event Reconstruction Dataset for Synchronization and Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
1e07500b00fcd0f65cf30a11f9023f74fe8ce65c,Whole space subclass discriminant analysis for face recognition,"A*STAR, Singapore","Institute for Infocomm Research, A*STAR, Singapore","1 Fusionopolis Way, #21-01 Connexis, Singapore 138632",1.29889260,103.78731070,edu,
+1e8c87181ac8db93431a0c7470c71561e1ee565f,Convolutional Neural Networks for Aerial Vehicle Detection and Recognition,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+1e8c87181ac8db93431a0c7470c71561e1ee565f,Convolutional Neural Networks for Aerial Vehicle Detection and Recognition,University of Liverpool,University of Liverpool,"Victoria Building, Brownlow Hill, Knowledge Quarter, Liverpool, North West England, England, L3, UK",53.40617900,-2.96670819,edu,
1e19ea6e7f1c04a18c952ce29386252485e4031e,MATLAB Based Face Recognition System Using PCA and Neural Network,Kurukshetra University,Kurukshetra University,"Kurukshetra University, SH6, Kurukshetra, Haryana, 132118, India",29.95826275,76.81563045,edu,
+1ed39db202e606f25aff93f3e4fe135283a50cc2,Video text detection and recognition: Dataset and benchmark,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+1ed39db202e606f25aff93f3e4fe135283a50cc2,Video text detection and recognition: Dataset and benchmark,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
1ec98785ac91808455b753d4bc00441d8572c416,Curriculum Learning for Facial Expression Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
1ed6c7e02b4b3ef76f74dd04b2b6050faa6e2177,Face Detection with a 3D Model,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
1ed6c7e02b4b3ef76f74dd04b2b6050faa6e2177,Face Detection with a 3D Model,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
1efacaa0eaa7e16146c34cd20814d1411b35538e,Action Completion: A Temporal Model for Moment Detection,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+1e3a9b0cfdeca614c5689a3419016c89bf9fbdfa,Facial color is an efficient mechanism to visually transmit emotion,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+1e3a9b0cfdeca614c5689a3419016c89bf9fbdfa,Facial color is an efficient mechanism to visually transmit emotion,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
1eba6fc35a027134aa8997413647b49685f6fbd1,Superpower glass: delivering unobtrusive real-time social cues in wearable systems,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1eafc8e7316d7257955ef09f903d318d55fac1fc,Ensemble of furthest subspace pairs for enhanced image set matching,"CSIRO, Australia","NICTA, PO Box 6020, St Lucia, QLD 4067, Australia","Research Way, Clayton VIC 3168, Australia",-37.90627370,145.13194490,edu,f.k.a. NICTA
+1eafc8e7316d7257955ef09f903d318d55fac1fc,Ensemble of furthest subspace pairs for enhanced image set matching,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
1e1d7cbbef67e9e042a3a0a9a1bcefcc4a9adacf,A Multi-level Contextual Model for Person Recognition in Photo Albums,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
+1e3739716e163fce6fded71eda078a18334aa83b,The HFB Face Database for Heterogeneous Face Biometrics research,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+1e54025a6b399bfc210a52a8c3314e8f570c2204,DenseCap: Fully Convolutional Localization Networks for Dense Captioning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1e92c074ab9082863a48fecdbf212f1897687a74,Improving Deep Learning using Generic Data Augmentation,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
+1e92c074ab9082863a48fecdbf212f1897687a74,Improving Deep Learning using Generic Data Augmentation,University of Cape Town,University of Cape Town,"University of Cape Town, Engineering Mall, Cape Town Ward 59, Cape Town, City of Cape Town, Western Cape, CAPE TOWN, South Africa",-33.95828745,18.45997349,edu,
1ef5ce743a44d8a454dbfc2657e1e2e2d025e366,Accurate Corner Detection Methods using Two Step Approach,Thapar University,Thapar University,"Thapar University, Hostel Road, Patiala, Punjab, 147001, India",30.35566105,76.36581641,edu,
+1eb249b515f7c09ae2663c1b5c49243906aabf22,Learning Structured Semantic Embeddings for Visual Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
1e58d7e5277288176456c66f6b1433c41ca77415,Bootstrapping Fine-Grained Classifiers: Active Learning with a Crowd in the Loop,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
1e5a1619fe5586e5ded2c7a845e73f22960bbf5a,Group Membership Prediction,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+1e747986c9efd481d380b28896115812eed54f8f,Bayesian Face Recognition Based on Markov Random Field Modeling,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+1ecd20f7fc34344e396825d27bc5a9871ab0d0c2,SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+1ed5d99fe46c0b5083f97e65841cd8535a9451c1,Dating Historical Color Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1ed5d99fe46c0b5083f97e65841cd8535a9451c1,Dating Historical Color Images,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+1ed5d99fe46c0b5083f97e65841cd8535a9451c1,Dating Historical Color Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1ed5d99fe46c0b5083f97e65841cd8535a9451c1,Dating Historical Color Images,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+1ed5d99fe46c0b5083f97e65841cd8535a9451c1,Dating Historical Color Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1e0fc2e5537db53080ec9a875df614dd8018c873,Mixture of Counting CNNs: Adaptive Integration of CNNs Specialized to Specific Appearance for Crowd Counting,Hiroshima University,Hiroshima University,"Hiroshima University 広島大学 東広島キャンパス, 出会いの道 Deai-no-michi Str., 西条下見, 東広島市, 広島県, 中国地方, 739-0047, 日本",34.40197660,132.71231950,edu,
1e9f1bbb751fe538dde9f612f60eb946747defaa,Identity-aware convolutional neural networks for facial expression recognition,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
1e917fe7462445996837934a7e46eeec14ebc65f,Expression Classification using Wavelet Packet Method on Asymmetry Faces,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
1e917fe7462445996837934a7e46eeec14ebc65f,Expression Classification using Wavelet Packet Method on Asymmetry Faces,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1e43d706d38cbacac563de9d0659230de00d73f2,Paragon: QoS-aware scheduling for heterogeneous datacenters,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1eab1ffed59092d6bf19900b7fb283e6dd0d01a2,Learning Socially Embedded Visual Representation from Scratch,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+1e7032e91fa01b90896c3cbfe5edf4f35ffd9628,A mixture model for aggregation of multiple pre-trained weak classifiers,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+1edc9eefb555e044f12d8c8cd56e8cc950abf8bb,Global Alignment for Dynamic 3D Morphable Model Construction,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
+1e0dd12f2bff234a4df71641bc95068733506858,Handwritten Word Spotting with Corrected Attributes,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+1e57ace361b941d9d210e59a9bbac7697b6bcff5,Maximizing all margins: Pushing face recognition with Kernel Plurality,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+1e57ace361b941d9d210e59a9bbac7697b6bcff5,Maximizing all margins: Pushing face recognition with Kernel Plurality,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+1ee896784275d0517963815b7c7ae1c788940409,A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+1ee896784275d0517963815b7c7ae1c788940409,A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+1e006cb837d4d01efcc92167443ccf3282329f89,Mask-guided Contrastive Attention Model for Person Re-Identification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+1e006cb837d4d01efcc92167443ccf3282329f89,Mask-guided Contrastive Attention Model for Person Re-Identification,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+1e99c95ea015a0639448fdf60f9694fed5464500,Interactive Object Counting,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1e516273554d87bbe1902fa0298179c493299035,Age Classification in Unconstrained Conditions Using LBP Variants,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+1e8ead5045c4b4de598c4eb570bfd9da14970129,A General Two-Step Approach to Learning-Based Hashing,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+1e95a366f9212654f79027894dbedf1ef44ca4c3,From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis,University of East Anglia,University of East Anglia,"Arts (Lower Walkway Level), The Square, Westfield View, Earlham, Norwich, Norfolk, East of England, England, NR4 7TJ, UK",52.62215710,1.24091360,edu,
+1e95a366f9212654f79027894dbedf1ef44ca4c3,From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+1e95a366f9212654f79027894dbedf1ef44ca4c3,From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+1e95a366f9212654f79027894dbedf1ef44ca4c3,From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis,Northumbria University,Northumbria University,"Northumbria University, Birkdale Close, High Heaton, Newcastle upon Tyne, Tyne and Wear, North East England, England, NE7 7TP, UK",55.00306320,-1.57463231,edu,
+1eb596303ce1f90e8070090be02c768e91fd75ed,Using Viseme Recognition to Improve a Sign Language Translation System,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
1e94cc91c5293c8fc89204d4b881552e5b2ce672,Unsupervised Alignment of Actions in Video with Text Descriptions,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
1e94cc91c5293c8fc89204d4b881552e5b2ce672,Unsupervised Alignment of Actions in Video with Text Descriptions,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+1e7995220c6f17dc649b0caeab34c617248aa167,Adversarial Geometry-Aware Human Motion Prediction,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1e4822f64f105a3f27888cc463e7e49e95c1e0f0,Facial Expression Recognition Based on Anatomical Structure of Human Face,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
+1e9758d282568763b209252bc3aeb7b47d269881,Learning Ordered Representations with Nested Dropout,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+1e9758d282568763b209252bc3aeb7b47d269881,Learning Ordered Representations with Nested Dropout,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+1e9758d282568763b209252bc3aeb7b47d269881,Learning Ordered Representations with Nested Dropout,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+1e944bd5a3907546d633691b8c83fec77d880657,Learning Kinematic Models for Articulated Objects,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1e9461b2e48e11638b85c2f2dc7bca043f9d60a8,Gait Representation Using Flow Fields,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+1e254f77ccbf3bd796ac3f60001384f59eba4ec2,Human Context: Modeling Human-Human Interactions for Monocular 3D Pose Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+1e1ab3d08fd71ab7368464d9adf78be1170fa728,Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+1e0a5ce5204f3f7503c39df6d200627cc331efe2,Automatic Arabic Image Captioning using RNN-LSTM-Based Language Model and CNN,King Saud University,King Saud University,"King Saud University جامعة الملك سعود, road_16, King Saud University District, Al Maather Municipality, الرياض, منطقة الرياض, 12393 4057, السعودية",24.72464030,46.62335012,edu,
1e8eec6fc0e4538e21909ab6037c228547a678ba,enVisage : Face Recognition in Videos,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
1e6ed6ca8209340573a5e907a6e2e546a3bf2d28,Pooling Faces: Template Based Face Recognition with Pooled Face Images,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
+84984c7201a7e5bc8ef4c01f0a7cfbe08c2c523b,GNAS: A Greedy Neural Architecture Search Method for Multi-Attribute Learning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+84af45a22535589053d0b00c9d6050c1150f9eaf,Exploiting Processor Heterogeneity for Interactive Services,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
841855205818d3a6d6f85ec17a22515f4f062882,Low Resolution Face Recognition in the Wild,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+84e21140422935d0a18ef0a616ed1ce1541112b0,Probabilistic Joint Face-Skull Modelling for Facial Reconstruction,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
84c0f814951b80c3b2e39caf3925b56a9b2e1733,16 Computation and Palaeography : Potentials and Limits,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
841bf196ee0086c805bd5d1d0bddfadc87e424ec,Locally Kernel-based Nonlinear Regression for Face Recognition,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
841bf196ee0086c805bd5d1d0bddfadc87e424ec,Locally Kernel-based Nonlinear Regression for Face Recognition,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
+844bfcee3bc559960ae7a2b1fd68fcf7a926dc5a,SPICE: Semantic Propositional Image Caption Evaluation,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+842ad1d5b6ea8a982be544b562ec91d907f879bd,Synthesis-Based Low-Cost Gaze Analysis,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+84eac516ed3b75233c5110468d3fddaec83a2895,Test-Time Adaptation for 3D Human Pose Estimation,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+84eac516ed3b75233c5110468d3fddaec83a2895,Test-Time Adaptation for 3D Human Pose Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+84eac516ed3b75233c5110468d3fddaec83a2895,Test-Time Adaptation for 3D Human Pose Estimation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
842d82081f4b27ca2d4bc05c6c7e389378f0c7b8,Usage of affective computing in recommender systems,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+84d665608c7c005d38290df392b0ba0157ba32ee,Social Cognitive Training Improves Emotional Processing and Reduces Aggressive Attitudes in Ex-combatants,Maastricht University,Maastricht University,"UNS60, Professor Ten Hoorlaan, Randwyck, Maastricht, Limburg, Nederland, 6229EV, Nederland",50.83367120,5.71589000,edu,
+84d665608c7c005d38290df392b0ba0157ba32ee,Social Cognitive Training Improves Emotional Processing and Reduces Aggressive Attitudes in Ex-combatants,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+84d665608c7c005d38290df392b0ba0157ba32ee,Social Cognitive Training Improves Emotional Processing and Reduces Aggressive Attitudes in Ex-combatants,University of Basel,University of Basel,"Faculty of Psychology, University of Basel, 60-62, Missionsstrasse, Grossbasel, Am Ring, Basel, Basel-Stadt, 4055, Schweiz/Suisse/Svizzera/Svizra",47.56126510,7.57529610,edu,
+84efa16406c8838550cbbed48f0355b936bbe845,Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+84676c330e4f8962703ca531db761c96bfda8067,Scalable misbehavior detection in online video chat services,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
84e6669b47670f9f4f49c0085311dce0e178b685,Face frontalization for Alignment and Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
84e6669b47670f9f4f49c0085311dce0e178b685,Face frontalization for Alignment and Recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+8432320153aa3a348138e27ef80ae3e8631bb6f8,Optimization of neural networks via finite-value quantum fluctuations,Tohoku University,Tohoku University,"Tohoku University, 五橋通, 青葉区, 仙台市, 宮城県, 東北地方, 980-0811, 日本",38.25309450,140.87365930,edu,
+84cf838be40e2ab05732fbefbb93ccb2afb0cb48,Recognizing Handwritten Characters,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+8488610866b29f279461f67ae948a3cfc72f6961,Sign language recognition using dynamic time warping and hand shape distance based on histogram of oriented gradient features,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+8488610866b29f279461f67ae948a3cfc72f6961,Sign language recognition using dynamic time warping and hand shape distance based on histogram of oriented gradient features,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+8488610866b29f279461f67ae948a3cfc72f6961,Sign language recognition using dynamic time warping and hand shape distance based on histogram of oriented gradient features,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+84c01c9760cd294718bd7c4b4c93596db1e5e068,Unsupervised Monocular Depth Estimation with Left-Right Consistency,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+84e3629b1c1c169125f777870e2009d8bcfdc2d7,Low-Latency Video Semantic Segmentation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+84e3629b1c1c169125f777870e2009d8bcfdc2d7,Low-Latency Video Semantic Segmentation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+84a0f6db2b7155a83728101728794713898a859a,Learning 3D Keypoint Descriptors for Non-rigid Shape Matching,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
847e07387142c1bcc65035109ccce681ef88362c,Feature Synthesis Using Genetic Programming for Face Expression Recognition,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+8473ccaa87f506f3d27e52d04ec4078668d7fc2e,Object Recognition Using Junctions,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
843e6f1e226480e8a6872d8fd7b7b2cd74b637a4,Palmprint Recognition Using Directional Representation and Compresses Sensing,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
84f904a71bee129a1cf00dc97f6cdbe1011657e6,Fashioning with Networks: Neural Style Transfer to Design Clothes,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
84f904a71bee129a1cf00dc97f6cdbe1011657e6,Fashioning with Networks: Neural Style Transfer to Design Clothes,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
84f904a71bee129a1cf00dc97f6cdbe1011657e6,Fashioning with Networks: Neural Style Transfer to Design Clothes,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
849f891973ad2b6c6f70d7d43d9ac5805f1a1a5b,ResNet Backbone Proposals Classification Loss Regression Loss Classification Loss Regression Loss RPN Classification Branch Box Regression Branch Conv Conv,Tencent,"Tencent AI Lab, China","Ke Ji Zhong Yi Lu, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057",22.54471540,113.93571640,company,"Keji Middle 1st Rd, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057"
846c028643e60fefc86bae13bebd27341b87c4d1,Face Recognition Under Varying Illumination Based on MAP Estimation Incorporating Correlation Between Surface Points,Institute of Industrial Science,Institute of Industrial Science,"産業技術総合研究所；西事業所, 学園西大通り, Onogawa housing complex, つくば市, 茨城県, 関東地方, 305-0051, 日本",36.05238585,140.11852361,edu,
+8455d208f43ec69971eabfcb28fddf64c3c9896b,Quality-adaptive deep learning for pedestrian detection,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+8455d208f43ec69971eabfcb28fddf64c3c9896b,Quality-adaptive deep learning for pedestrian detection,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+845299d67c87dc7f5f610b0c4380feb4daa4d0cc,Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+845299d67c87dc7f5f610b0c4380feb4daa4d0cc,Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+845299d67c87dc7f5f610b0c4380feb4daa4d0cc,Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+4a374a6fe2ecd5f4889d7141a0521dea087ee667,Dissertation S cene specific object detection and tracking,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
4a14a321a9b5101b14ed5ad6aa7636e757909a7c,Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
4a14a321a9b5101b14ed5ad6aa7636e757909a7c,Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
4aa286914f17cd8cefa0320e41800a99c142a1cd,Leveraging Context to Support Automated Food Recognition in Restaurants,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
4a9d906935c9de019c61aedc10b77ee10e3aec63,Cross Modal Distillation for Supervision Transfer,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+4aeebd1c9b4b936ed2e4d988d8d28e27f129e6f1,See the Difference: Direct Pre-Image Reconstruction and Pose Estimation by Differentiating HOG,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+4a44381f7c639451a797b2d3016b1d4cb54736dc,Pedestrian Travel Time Estimation in Crowded Scenes,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+4a44381f7c639451a797b2d3016b1d4cb54736dc,Pedestrian Travel Time Estimation in Crowded Scenes,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+4a8b8746def96caa3efd65548040c5c597c4312a,Building and using a semantivisual image hierarchy,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+4a8b8746def96caa3efd65548040c5c597c4312a,Building and using a semantivisual image hierarchy,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+4a07fe50742c31daffd77cdcac15eaca72070b2a,Examining CNN Representations With Respect to Dataset Bias,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
4ae59d2a28abd76e6d9fb53c9e7ece833dce7733,A Survey on Mobile Affective Computing,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
4ab10174a4f98f7e2da7cf6ccfeb9bc64c8e7da8,Efficient Metric Learning for Real-World Face Recognition,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
4a484d97e402ed0365d6cf162f5a60a4d8000ea0,A Crowdsourcing Approach for Finding Misidentifications of Bibliographic Records,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+4a83d9d07cbac4a8a279073e3873d01f3215f2f8,Anticipating Accidents in Dashcam Videos,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+4a83d9d07cbac4a8a279073e3873d01f3215f2f8,Anticipating Accidents in Dashcam Videos,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+4a3ba4a8f6945382b50d053b58aa0fc7c5199b4d,Efficient Evaluation of SVM Classifiers Using Error Space Encoding,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+4a8f521b929f72da2e9ee4af9f43e941f02bd114,Data-Driven Scene Understanding from 3D Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4a8f521b929f72da2e9ee4af9f43e941f02bd114,Data-Driven Scene Understanding from 3D Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4afded694bb067c45b591c98e0951e8988d7d2d6,3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+4afded694bb067c45b591c98e0951e8988d7d2d6,3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+4afdb1c53d0173030868a9fecee4c0216dc45c9e,An analysis-by-synthesis method based on sparse representation for heterogeneous face biometrics,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+4afdb1c53d0173030868a9fecee4c0216dc45c9e,An analysis-by-synthesis method based on sparse representation for heterogeneous face biometrics,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
4aa093d1986b4ad9b073ac9edfb903f62c00e0b0,Facial Recognition with Encoded Local Projections,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
4aa093d1986b4ad9b073ac9edfb903f62c00e0b0,Facial Recognition with Encoded Local Projections,University of Waterloo,University of Waterloo,"University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada",43.47061295,-80.54724732,edu,
4aabd6db4594212019c9af89b3e66f39f3108aac,The Mere Exposure Effect and Classical Conditioning,"University of Colorado, Boulder","University of Colorado, Boulder","Naropa University, Arapahoe Avenue, The Hill, Boulder, Boulder County, Colorado, 80309, USA",40.01407945,-105.26695944,edu,
4adb97b096b700af9a58d00e45a2f980136fcbb5,Exploring Temporal Preservation Networks for Precise Temporal Action Localization,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+4a2ba5d7b41ae1d8334c5b8bb1e76ce29e4367ee,Relational divergence based classification on Riemannian manifolds,"CSIRO, Australia","NICTA, PO Box 6020, St Lucia, QLD 4067, Australia","Research Way, Clayton VIC 3168, Australia",-37.90627370,145.13194490,edu,f.k.a. NICTA
+4a2ba5d7b41ae1d8334c5b8bb1e76ce29e4367ee,Relational divergence based classification on Riemannian manifolds,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+4ac61814d0f624ebda190b240ede72f0b156ff22,Face Recognition by Support Vector Machines,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+4a691bd830cd0fdbb4a13ba91160e973386250dd,Viewpoint Adaptation for Person Detection,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
4ae291b070ad7940b3c9d3cb10e8c05955c9e269,Automatic Detection of Naturalistic Hand-over-Face Gesture Descriptors,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+4a06ae9d41b384d6b1954b42a63385310b5d43fc,Facial feature detection and tracking with automatic template selection,University of Manchester,University of Manchester,"University of Manchester - Main Campus, Brunswick Street, Curry Mile, Ardwick, Manchester, Greater Manchester, North West England, England, M13 9NR, UK",53.46600455,-2.23300881,edu,
+4ae234a7eda3fc4e28fadbc75ee2603a0e078fcb,Understanding Human Motion : Recognition and Retrieval of Human Activities,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
4aa8db1a3379f00db2403bba7dade5d6e258b9e9,Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
4ac4e8d17132f2d9812a0088594d262a9a0d339b,Rank Constrained Recognition under Unknown Illuminations,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+4a77c8ab5d538541ac5f37ae6200d34360ff36b6,Calibration in Eye Tracking Using Transfer Learning,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+4af50ecb45709829a840a75ddc84f56f288c5a64,Learning Detectors Quickly with Stationary Statistics,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+4af50ecb45709829a840a75ddc84f56f288c5a64,Learning Detectors Quickly with Stationary Statistics,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4aeb5520a941fb59f20093cbeaf4b84b35df78fc,Gait Representation Using Flow Fields,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+4ab4e283c6c635bee029b4857be670504fa9d1b9,Feature Extraction Based on Direct Calculation of Mutual Information,Ajou University,Ajou University,"아주대학교, 성호대교, 이의동, 영통구, 수원시, 경기, 16499, 대한민국",37.28300030,127.04548469,edu,
+4af4098deffc22cf901f38b4634d316df68975ab,Image segmentation with patch-pair density priors,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+4af4098deffc22cf901f38b4634d316df68975ab,Image segmentation with patch-pair density priors,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+4ab69672e1116427d685bf7c1edb5b1fd0573b5e,Spatial pooling of heterogeneous features for image applications,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+4ab69672e1116427d685bf7c1edb5b1fd0573b5e,Spatial pooling of heterogeneous features for image applications,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
4acd683b5f91589002e6f50885df51f48bc985f4,Bridging computer vision and social science: A multi-camera vision system for social interaction training analysis,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
4a1d640f5e25bb60bb2347d36009718249ce9230,Towards Multi-view and Partially-Occluded Face Alignment,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+4ae33d64f8515a023f10e20af20f62a2a5a76f13,Sketch Recognition with Deep Visual-Sequential Fusion Model,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
+4ae33d64f8515a023f10e20af20f62a2a5a76f13,Sketch Recognition with Deep Visual-Sequential Fusion Model,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+4a0707131dab1c64c03bfa0809b050d34fafeeb5,Cell Lineage Tracing in Lens-Free Microscopy Videos,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+4a961dda9fc9a07d6a0bfbe59cc38b2605e61d2f,Robust model adaptation for tracking with online weighted color and shape feature,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+4a79923948c6ccda965077287dc6fd1d3728d680,Dropout Training for Support Vector Machines,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+4a1a7e5d52e097d1defb523575fb8de1a5b24171,Multicore Construction of k-d Trees for High Dimensional Point Data,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+4a9086cf2637b7ea54855187b978af7a89bfceff,Atypical neural specialization for social percepts in autism spectrum disorder.,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+2453dd38cde21f3248b55d281405f11d58168fa9,Multi-scale Patch Aggregation (MPA) for Simultaneous Detection and Segmentation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
24b37016fee57057cf403fe2fc3dda78476a8262,Automatic Recognition of Eye Blinking in Spontaneously Occurring Behavior,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
24b37016fee57057cf403fe2fc3dda78476a8262,Automatic Recognition of Eye Blinking in Spontaneously Occurring Behavior,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+24fe0a4a2304da39b8ff5630ba9a64d505326d0e,Progressive Operational Perceptron with Memory,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+24fe0a4a2304da39b8ff5630ba9a64d505326d0e,Progressive Operational Perceptron with Memory,Qatar University,Qatar University,"Qatar University, Roindabout 3, Al Tarfa (68), أم صلال, 24685, قطر",25.37461295,51.48980354,edu,
247cab87b133bd0f4f9e8ce5e7fc682be6340eac,Robust Eye Center Localization through Face Alignment and Invariant Isocentric Patterns,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
247cab87b133bd0f4f9e8ce5e7fc682be6340eac,Robust Eye Center Localization through Face Alignment and Invariant Isocentric Patterns,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
247cab87b133bd0f4f9e8ce5e7fc682be6340eac,Robust Eye Center Localization through Face Alignment and Invariant Isocentric Patterns,"Joint Research Institute, Foshan, China","Joint Research Institute, Foshan, China","广东顺德中山大学卡内基梅隆大学国际联合研究院, 南国东路, 顺德区, 五村, 顺德区 (Shunde), 佛山市 / Foshan, 广东省, 0757, 中国",22.83388935,113.28541825,edu,
+24fc311970e097efc317c0f98d2df37b828bfbad,Semi-supervised hierarchical semantic object parsing,Amirkabir University of Technology,Amirkabir University of Technology,"دانشگاه صنعتی امیرکبیر, ولی عصر, میدان ولیعصر, منطقه ۶ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, نبش برادران مظفر, ایران",35.70451400,51.40972058,edu,
24cb375a998f4af278998f8dee1d33603057e525,Projection Metric Learning on Grassmann Manifold with Application to Video based Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
24cb375a998f4af278998f8dee1d33603057e525,Projection Metric Learning on Grassmann Manifold with Application to Video based Face Recognition,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+247ca98c5a46616044cf6ae32b0d5b4140a7a161,High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+24065d385bae5579be07607a1f63eb79cebf8773,Incremental Learning of NCM Forests for Large-Scale Image Classification,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
24f9248f01df3020351347c2a3f632e01de72090,Reconstructing a fragmented face from a cryptographic identification protocol,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+24662ce3f3499ec8c5ecc546dac69dbffad578c6,Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+24662ce3f3499ec8c5ecc546dac69dbffad578c6,Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
24959d1a9c9faf29238163b6bcaf523e2b05a053,High Accuracy Head Pose Tracking Survey,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
24f1febcdf56cd74cb19d08010b6eb5e7c81c362,Synergistic methods for using language in robotics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
24f1febcdf56cd74cb19d08010b6eb5e7c81c362,Synergistic methods for using language in robotics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
24f1febcdf56cd74cb19d08010b6eb5e7c81c362,Synergistic methods for using language in robotics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
24f1febcdf56cd74cb19d08010b6eb5e7c81c362,Synergistic methods for using language in robotics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+248e2d3079f4f59789770a7f57244a434e8467d0,The Many Moods of Emotion,Orange,Orange Labs,"78 Rue Olivier de Serres, 75015 Paris, France",48.83321220,2.29421550,company,"78 Rue Olivier de Serres, Paris, 75015"
24cf9fe9045f50c732fc9c602358af89ae40a9f7,Attribute Recognition from Adaptive Parts,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
24cf9fe9045f50c732fc9c602358af89ae40a9f7,Attribute Recognition from Adaptive Parts,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
24cf9fe9045f50c732fc9c602358af89ae40a9f7,Attribute Recognition from Adaptive Parts,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
24cf9fe9045f50c732fc9c602358af89ae40a9f7,Attribute Recognition from Adaptive Parts,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
24f022d807352abf071880877c38e53a98254dcd,Are screening methods useful in feature selection? An empirical study,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+24475686f64825c6eb503e57636fc1fcda724407,Hough Regions for Joining Instance Localization and Segmentation,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+245f8b05bdd1ac65a09a476440dc4b05ac05d4a0,An Online Learning Approach to Generative Adversarial Networks,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+24dbe0a133908500d25753542bbb720d71678c42,Multi-modal Person Localization And Emergency Detection Using The Kinect,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+24dbe0a133908500d25753542bbb720d71678c42,Multi-modal Person Localization And Emergency Detection Using The Kinect,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+24dbe0a133908500d25753542bbb720d71678c42,Multi-modal Person Localization And Emergency Detection Using The Kinect,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+24078db5422dfddf14b00fa79c38efa553845a10,"RGBD Datasets: Past, Present and Future",University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
241d2c517dbc0e22d7b8698e06ace67de5f26fdf,"Online, Real-Time Tracking Using a Category-to-Individual Detector",California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+24d45df91ebcfac7a49cdfb7116e971e12880612,UNICITY: A depth maps database for people detection in security airlocks,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
24e6a28c133b7539a57896393a79d43dba46e0f6,Robust Bayesian method for simultaneous block sparse signal recovery with applications to face recognition,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+242dc739b7cc49a7f54967a7d75d8a82f92bef59,Affinity Derivation and Graph Merge for Instance Segmentation,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+242dc739b7cc49a7f54967a7d75d8a82f92bef59,Affinity Derivation and Graph Merge for Instance Segmentation,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+242dc739b7cc49a7f54967a7d75d8a82f92bef59,Affinity Derivation and Graph Merge for Instance Segmentation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
248db911e3a6a63ecd5ff6b7397a5d48ac15e77a,Enriching Texture Analysis with Semantic Data,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+241b86d3c71d14b8cc6044a425b047a0724cfdc9,Following Gaze in Video,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
24f1e2b7a48c2c88c9e44de27dc3eefd563f6d39,Recognition of Action Units in the Wild with Deep Nets and a New Global-Local Loss,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
+24ab0116bf4f56290aa8f8dd98524bb43fab6d85,Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+24ab0116bf4f56290aa8f8dd98524bb43fab6d85,Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
243e9d490fe98d139003bb8dc95683b366866c57,Distinctive Parts for Relative attributes,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+24d630946023cb421b9d960dd9983b4b5dcb800d,Efficient Detector Adaptation for Object Detection in a Video,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+248291285074203eb9ee8e0b8b517ac4ce7dc4aa,The Way Dogs (Canis familiaris) Look at Human Emotional Faces Is Modulated by Oxytocin. An Eye-Tracking Study,University of Padova,University of Padova,"Via Giovanni Gradenigo, 6, 35131 Padova PD, Italy",45.40811720,11.89437860,edu,"University of Padova, Via Gradenigo, 6 - 35131- Padova, Italy"
+24c6240c511f4daa7cf51e28b0a9fb15e365d4cc,Can Ground Truth Label Propagation from Video Help Semantic Segmentation?,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+24be26a04906987e7958c1544834bf9f18a92571,Referring Image Segmentation via Recurrent Refinement Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
240eb0b34872c431ecf9df504671281f59e7da37,Cutout-search: Putting a name to the picture,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
240eb0b34872c431ecf9df504671281f59e7da37,Cutout-search: Putting a name to the picture,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+23ed7f18100717ba814b2859196e10c5d4fed216,Incorporating External Knowledge to Answer Open-Domain Visual Questions with Dynamic Memory Networks,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+23e6e8ab8f62d8f67525313c823e3cb4424ac578,Exploiting Convolution Filter Patterns for Transfer Learning,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
+231b769f2e13724754fa09e7e5ab7d4b843075a0,IOD-CNN: Integrating object detection networks for event recognition,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+23b22f10d3e0a5726f58ae10c494a28103979c6f,Scalable k-NN graph construction for visual descriptors,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+23b22f10d3e0a5726f58ae10c494a28103979c6f,Scalable k-NN graph construction for visual descriptors,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
23aef683f60cb8af239b0906c45d11dac352fb4e,Incorporating Context Information into Deep Neural Network Acoustic Models,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
235d5620d05bb7710f5c4fa6fceead0eb670dec5,Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+23afec5c3edf6c65fc28d360a82820d34bbdc8a8,Confidence Preserving Machine for Facial Action Unit Detection,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+23afec5c3edf6c65fc28d360a82820d34bbdc8a8,Confidence Preserving Machine for Facial Action Unit Detection,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+23afec5c3edf6c65fc28d360a82820d34bbdc8a8,Confidence Preserving Machine for Facial Action Unit Detection,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+23a84a4a77b6662d553c9252331e6b7920053125,Latent Model Ensemble with Auto-localization,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
+23a84a4a77b6662d553c9252331e6b7920053125,Latent Model Ensemble with Auto-localization,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+231e545fdb1a516e29604fbd740e207b6f25c7dc,Perception of dynamic changes in facial affect and identity in autism.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+231e545fdb1a516e29604fbd740e207b6f25c7dc,Perception of dynamic changes in facial affect and identity in autism.,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+231e545fdb1a516e29604fbd740e207b6f25c7dc,Perception of dynamic changes in facial affect and identity in autism.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+234e3f821c31d0b5b7c59c3c013ad258fa6f5912,Attention Directs Emotion : Directed Attention Drives Emotional Intensity and Distinctiveness of Facial Perception,"University of Colorado, Boulder","University of Colorado, Boulder","Naropa University, Arapahoe Avenue, The Hill, Boulder, Boulder County, Colorado, 80309, USA",40.01407945,-105.26695944,edu,
+235f8e797bc10561ecd684023d2c980d990ea217,End-to-End Learning of Deformable Mixture of Parts and Deep Convolutional Neural Networks for Human Pose Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
23ce6f404c504592767b8bec7d844d87b462de71,A Deep Face Identification Network Enhanced by Facial Attributes Prediction,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+2313c827d3cb9a291b6a00d015c29580862bbdcc,Weakly- and Semi-supervised Panoptic Segmentation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+2328b0b5d4e9d4b78b1b9002407a533c21ff66f1,Evaluation of dimensionality reduction methods for image auto-annotation,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+23a450a075d752f1ec2b1e5e225de13d3bc37636,Subspace Learning in Krein Spaces: Complete Kernel Fisher Discriminant Analysis with Indefinite Kernels,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+23a432a388552ab52437d428e5af2b6c195be635,D O D Eep C Onvolutional N Ets R Eally N Eed to Be D Eep and C Onvolutional ?,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+23a432a388552ab52437d428e5af2b6c195be635,D O D Eep C Onvolutional N Ets R Eally N Eed to Be D Eep and C Onvolutional ?,University of Alberta,University of Alberta,"University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada",53.52385720,-113.52282665,edu,
+23a432a388552ab52437d428e5af2b6c195be635,D O D Eep C Onvolutional N Ets R Eally N Eed to Be D Eep and C Onvolutional ?,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+23a432a388552ab52437d428e5af2b6c195be635,D O D Eep C Onvolutional N Ets R Eally N Eed to Be D Eep and C Onvolutional ?,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
23fd653b094c7e4591a95506416a72aeb50a32b5,Emotion Recognition using Fuzzy Rule- based System,Amity University,Amity University,"Amity University, Faizabad Road, Uttardhauna, Gomti Nagar, Tiwariganj, Lucknow, Uttar Pradesh, 226010, India",26.85095965,81.04950965,edu,
23fd653b094c7e4591a95506416a72aeb50a32b5,Emotion Recognition using Fuzzy Rule- based System,Amity University,Amity University,"Amity University, Faizabad Road, Uttardhauna, Gomti Nagar, Tiwariganj, Lucknow, Uttar Pradesh, 226010, India",26.85095965,81.04950965,edu,
231a6d2ee1cc76f7e0c5912a530912f766e0b459,Shape Primitive Histogram: A Novel Low-Level Face Representation for Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+23fc6c6e1cd52a77215a285a462840cbb96aec39,"Cortical patterns of category-selective activation for faces, places and objects in adults with autism.",New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+23fc6c6e1cd52a77215a285a462840cbb96aec39,"Cortical patterns of category-selective activation for faces, places and objects in adults with autism.",University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+23b466abb866e3f160f4573a69666f861aef59cc,"EmotiW 2018: Audio-Video, Student Engagement and Group-Level Affect Prediction",University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
+23b466abb866e3f160f4573a69666f861aef59cc,"EmotiW 2018: Audio-Video, Student Engagement and Group-Level Affect Prediction",Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+2359c3f763e96e0ee62b1119c897a32ce9715a77,Neural Computing on a Raspberry Pi : Applications to Zebrafish Behavior Monitoring,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+23bdd2d82068419bf4923e6a0198fc0fa4468807,Bird Species Categorization Using Pose Normalized Deep Convolutional Nets,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
23fc83c8cfff14a16df7ca497661264fc54ed746,Comprehensive Database for Facial Expression Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
23fc83c8cfff14a16df7ca497661264fc54ed746,Comprehensive Database for Facial Expression Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
23fc83c8cfff14a16df7ca497661264fc54ed746,Comprehensive Database for Facial Expression Analysis,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
@@ -4005,78 +11161,236 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 23fc83c8cfff14a16df7ca497661264fc54ed746,Comprehensive Database for Facial Expression Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
23fc83c8cfff14a16df7ca497661264fc54ed746,Comprehensive Database for Facial Expression Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
23fc83c8cfff14a16df7ca497661264fc54ed746,Comprehensive Database for Facial Expression Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+233913367b5006277b04a8f7651f51425f13697e,Efficient Inference with Multiple Heterogeneous Part Detectors for Human Pose Estimation,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+23339e409363a89cb5fe64e18e78a36286724de0,Semi-interactive tracing of persons in real-life surveillance data,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+23339e409363a89cb5fe64e18e78a36286724de0,Semi-interactive tracing of persons in real-life surveillance data,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+23c7465c16ea9343f74a400f92b970e84878b65a,Automatic classification of Chinese female facial beauty using Support Vector Machine,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
232b6e2391c064d483546b9ee3aafe0ba48ca519,Optimization Problems for Fast AAM Fitting in-the-Wild,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
232b6e2391c064d483546b9ee3aafe0ba48ca519,Optimization Problems for Fast AAM Fitting in-the-Wild,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
237eba4822744a9eabb121fe7b50fd2057bf744c,Facial Expression Synthesis Using PAD Emotional Parameters for a Chinese Expressive Avatar,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
237eba4822744a9eabb121fe7b50fd2057bf744c,Facial Expression Synthesis Using PAD Emotional Parameters for a Chinese Expressive Avatar,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2311d2488707655b79cf2b115e3c720bd4791918,Multi-Channel Pyramid Person Matching Network for Person Re-Identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+2311d2488707655b79cf2b115e3c720bd4791918,Multi-Channel Pyramid Person Matching Network for Person Re-Identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+232d99697a18c3065f2ba7c5f2d93d87731690f5,Robustifying eye center localization by head pose cues,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+23ca7c4367f7317c61ebb0574e3d04cfd9bc3893,Aberrant brain activation during gaze processing in boys with fragile X syndrome.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+23000287004800912e3469772f3a2a48704dd303,Power SVM: Generalization with exemplar classification uncertainty,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+23000287004800912e3469772f3a2a48704dd303,Power SVM: Generalization with exemplar classification uncertainty,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
23e75f5ce7e73714b63f036d6247fa0172d97cb6,Facial expression (mood) recognition from facial images using committee neural networks,University of Akron,University of Akron,"University of Akron, East State Street, Stadium District, Cascade Valley, Akron, Summit County, Ohio, 44308, USA",41.07890350,-81.51971272,edu,
23e75f5ce7e73714b63f036d6247fa0172d97cb6,Facial expression (mood) recognition from facial images using committee neural networks,University of Akron,University of Akron,"University of Akron, East State Street, Stadium District, Cascade Valley, Akron, Summit County, Ohio, 44308, USA",41.07890350,-81.51971272,edu,
23429ef60e7a9c0e2f4d81ed1b4e47cc2616522f,A Domain Based Approach to Social Relation Recognition,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+236171d2c673194045b4c2e2837ddcc4a2041b8a,A Hierarchical Pose-Based Approach to Complex Action Understanding Using Dictionaries of Actionlets and Motion Poselets,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+2385007824daaf9eac9476fccb1501b7ac166ceb,Task-driven Visual Saliency and Attention-based Visual Question Answering,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
23aba7b878544004b5dfa64f649697d9f082b0cf,Locality-constrained discriminative learning and coding,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
2303d07d839e8b20f33d6e2ec78d1353cac256cf,Squeeze-and-Excitation on Spatial and Temporal Deep Feature Space for Action Recognition,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
+23e19cc9d2318b07eeaf8a9d34245131eb1a58be,Hierarchical Convolutional Deep Learning in Computer Vision,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+23b48110cead14510ebb22dc388324466fd56c95,Robust Principal Component Analysis with Missing Data,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+23b48110cead14510ebb22dc388324466fd56c95,Robust Principal Component Analysis with Missing Data,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
23c3eb6ad8e5f18f672f187a6e9e9b0d94042970,Deep domain adaptation for describing people based on fine-grained clothing attributes,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
-23dd8d17ce09c22d367e4d62c1ccf507bcbc64da,Deep Density Clustering of Unconstrained Faces (Supplementary Material),University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+23e2b9d1ac20e114f48850ab32b3d9136bec6826,DeepSkeleton: Skeleton Map for 3D Human Pose Regression,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+23e2b9d1ac20e114f48850ab32b3d9136bec6826,DeepSkeleton: Skeleton Map for 3D Human Pose Regression,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+23e2b9d1ac20e114f48850ab32b3d9136bec6826,DeepSkeleton: Skeleton Map for 3D Human Pose Regression,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+232ff2dab49cb5a1dae1012fd7ba53382909ec18,Semantic Video Segmentation from Occlusion Relations within a Convex Optimization Framework,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+23a59bfb96c4f543673e05b3cf6dc01b4173745b,ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+23a59bfb96c4f543673e05b3cf6dc01b4173745b,ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+23dd8d17ce09c22d367e4d62c1ccf507bcbc64da,Deep Density Clustering of Unconstrained Faces ( Supplementary Material ),University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+23b8a55785318ce90957a392607e24f620c4fccc,Bayesian Optimization with Inequality Constraints,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+4fc3c9aa51cd7922820bfd5547cf544ff99b415b,Generalized Zero-Shot Learning with Deep Calibration Network,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+4fc3c9aa51cd7922820bfd5547cf544ff99b415b,Generalized Zero-Shot Learning with Deep Calibration Network,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
4f9e00aaf2736b79e415f5e7c8dfebda3043a97d,"Machine Audition : Principles , Algorithms and Systems",University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+4f93cd09785c6e77bf4bc5a788e079df524c8d21,On a large sequence-based human gait database,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
4f0d9200647042e41dea71c35eb59e598e6018a7,Experiments of Image Retrieval Using Weak Attributes,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+4ffd50725b9cdff4ab0f13c9182cf3fdb671e76c,Portable performance on Asymmetric Multicore Processors,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+4ffd50725b9cdff4ab0f13c9182cf3fdb671e76c,Portable performance on Asymmetric Multicore Processors,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+4f19d33e808a6675f11fb624499d303368deafa1,Learning Monocular Depth by Distilling Cross-Domain Stereo Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+4f5e1e70f51b30e4606f991ed0e912c84af90251,Using maximum consistency context for multiple target association in wide area traffic scenes,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+4f6e1fe403b13279cd4674615d6d07ce002c9dec,Is there a connection between face symmetry and face recognition?,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
4f7967158b257e86d66bdabfdc556c697d917d24,Guaranteed Parameter Estimation of Discrete Energy Minimization for 3D Scene Parsing,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4f69ad0e52e37ba06db1c2b89c180f3ba331cc4a,Automatic Generation of Grounded Visual Questions,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+4f69ad0e52e37ba06db1c2b89c180f3ba331cc4a,Automatic Generation of Grounded Visual Questions,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+4f922f6602f39baae94f63954005776e1da05671,Peer-Mediated Theatrical Engagement for Improving Reciprocal Social Interaction in Autism Spectrum Disorder,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
+4f922f6602f39baae94f63954005776e1da05671,Peer-Mediated Theatrical Engagement for Improving Reciprocal Social Interaction in Autism Spectrum Disorder,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
+4ffe93dfb895c86ebad874c70113c4870c9bd5e3,Pose Machines: Articulated Pose Estimation via Inference Machines,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4f1a74cfa7c8383a5dea97cb48c197da5b4f5ee0,LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+4f1a74cfa7c8383a5dea97cb48c197da5b4f5ee0,LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+4f1a74cfa7c8383a5dea97cb48c197da5b4f5ee0,LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+4f1a74cfa7c8383a5dea97cb48c197da5b4f5ee0,LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+4f1a74cfa7c8383a5dea97cb48c197da5b4f5ee0,LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+4f36755fd732684b977a041ee3b0acc3492e5b6e,Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras,Chung-Ang University,Chung-Ang University,"중앙대학교, 서달로15길, 흑석동, 동작구, 서울특별시, 06981, 대한민국",37.50882000,126.96190000,edu,
4fcd19b0cc386215b8bd0c466e42934e5baaa4b7,Human Action Recognition Using Factorized Spatio-Temporal Convolutional Networks,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
4fcd19b0cc386215b8bd0c466e42934e5baaa4b7,Human Action Recognition Using Factorized Spatio-Temporal Convolutional Networks,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
4fcd19b0cc386215b8bd0c466e42934e5baaa4b7,Human Action Recognition Using Factorized Spatio-Temporal Convolutional Networks,University of Macau,University of Macau,"研究生宿舍 Residência de Estudantes de Pós-Graduação da Universidade de Macau, 澳門大學 Universidade de Macau, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, Universidade de Macau em Ilha de Montanha 澳門大學橫琴校區, 中国",22.12401870,113.54510901,edu,
+4fa2b00f78b2a73b63ad014f3951ec902b8b24ae,Semi-supervised hashing for scalable image retrieval,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+4fa2b00f78b2a73b63ad014f3951ec902b8b24ae,Semi-supervised hashing for scalable image retrieval,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+4fcf1bfc2a8989412adb67c97ce1bee72a996fff,3D morphable model construction for robust ear and face recognition,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+4f81f0c0019862046710d70b6ea880f989949e9a,An Efficient Approach for Differentiating Alzheimer's Disease from Normal Elderly Based on Multicenter MRI Using Gray-Level Invariant Features,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+4f81f0c0019862046710d70b6ea880f989949e9a,An Efficient Approach for Differentiating Alzheimer's Disease from Normal Elderly Based on Multicenter MRI Using Gray-Level Invariant Features,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
4f9958946ad9fc71c2299847e9ff16741401c591,Facial Expression Recognition with Recurrent Neural Networks,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
4f773c8e7ca98ece9894ba3a22823127a70c6e6c,A Real-Time System for Head Tracking and Pose Estimation,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+4f3f08bcc36778d45dfd5c6f6b8aff070bcfe9a4,FBI-Pose: Towards Bridging the Gap between 2D Images and 3D Human Poses using Forward-or-Backward Information,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+4fd74b807b47a5975e9b0ab354bfd780e0d921d2,Armadillo: An Open Source C++ Linear Algebra Library for Fast Prototyping and Computationally Intensive Experiments,"CSIRO, Australia","NICTA, PO Box 6020, St Lucia, QLD 4067, Australia","Research Way, Clayton VIC 3168, Australia",-37.90627370,145.13194490,edu,f.k.a. NICTA
4ff11512e4fde3d1a109546d9c61a963d4391add,Selecting Vantage Points for an Autonomous Quadcopter Videographer,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
4f028efe6708fc252851eee4a14292b7ce79d378,An integrated shape and intensity coding scheme for face recognition,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
4ff4c27e47b0aa80d6383427642bb8ee9d01c0ac,Deep Convolutional Neural Networks and Support Vector Machines for Gender Recognition,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
4fefd1bc8dc4e0ab37ee3324ddfa43ad9d6a04a7,Fashion Landmark Detection in the Wild,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+4f10a7697fb2a2c626d1190db2afba83c4ffe856,Cartoon-to-Photo Facial Translation with Generative Adversarial Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+4f10a7697fb2a2c626d1190db2afba83c4ffe856,Cartoon-to-Photo Facial Translation with Generative Adversarial Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+4f10a7697fb2a2c626d1190db2afba83c4ffe856,Cartoon-to-Photo Facial Translation with Generative Adversarial Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+4f10a7697fb2a2c626d1190db2afba83c4ffe856,Cartoon-to-Photo Facial Translation with Generative Adversarial Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+4f10a7697fb2a2c626d1190db2afba83c4ffe856,Cartoon-to-Photo Facial Translation with Generative Adversarial Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+4f10a7697fb2a2c626d1190db2afba83c4ffe856,Cartoon-to-Photo Facial Translation with Generative Adversarial Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
4f0b8f730273e9f11b2bfad2415485414b96299f,BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
4f0b8f730273e9f11b2bfad2415485414b96299f,BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+4f3484a1b08b332479f0cc0197528e9007292a90,Stream-Based Active Unusual Event Detection,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+4fc96ad5c9c0155961ace769f3a73b728854fa98,Three-Dimensional Face Recognition Using Surface Space Combinations,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
+4f0eab1ee02f015313ebbbfada22407d1badd5d4,Sliced Wasserstein Distance for Learning Gaussian Mixture Models,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
4f7b92bd678772552b3c3edfc9a7c5c4a8c60a8e,Deep Density Clustering of Unconstrained Faces,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+4fde52cd3af5c698f0807bc3b821ebb3a270a986,Impaired fixation to eyes during facial emotion labelling in children with bipolar disorder or severe mood dysregulation.,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+4fde52cd3af5c698f0807bc3b821ebb3a270a986,Impaired fixation to eyes during facial emotion labelling in children with bipolar disorder or severe mood dysregulation.,University of Denver,University of Denver,"University of Denver, Driscoll Bridge, Denver, Denver County, Colorado, 80208, USA",39.67665410,-104.96220300,edu,
+4fde52cd3af5c698f0807bc3b821ebb3a270a986,Impaired fixation to eyes during facial emotion labelling in children with bipolar disorder or severe mood dysregulation.,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+4fde52cd3af5c698f0807bc3b821ebb3a270a986,Impaired fixation to eyes during facial emotion labelling in children with bipolar disorder or severe mood dysregulation.,University of Denver,University of Denver,"University of Denver, Driscoll Bridge, Denver, Denver County, Colorado, 80208, USA",39.67665410,-104.96220300,edu,
4f36c14d1453fc9d6481b09c5a09e91d8d9ee47a,Video-Based Face Recognition Using the Intra/Extra-Personal Difference Dictionary,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
4f36c14d1453fc9d6481b09c5a09e91d8d9ee47a,Video-Based Face Recognition Using the Intra/Extra-Personal Difference Dictionary,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+4fb9f05dc03eb4983d8f9a815745bb47970f1b93,"On Robust Face Recognition via Sparse Encoding: the Good, the Bad, and the Ugly",National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+4fb9f05dc03eb4983d8f9a815745bb47970f1b93,"On Robust Face Recognition via Sparse Encoding: the Good, the Bad, and the Ugly",University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+4fb9f05dc03eb4983d8f9a815745bb47970f1b93,"On Robust Face Recognition via Sparse Encoding: the Good, the Bad, and the Ugly",Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+4f6ab8af1b059e6130d5fd8c4e4adee4079ae2e6,Selective Search for Object Recognition,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+4f09328793b907074adc8d4e10d2d763d7a4b513,NTUA-SLP at SemEval-2018 Task 1: Predicting Affective Content in Tweets with Deep Attentive RNNs and Transfer Learning,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
+8d6344658fa9673b1f4ac0d0bad53617ee127aaa,Adolescent and adult risk-taking in virtual social contexts,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8d6344658fa9673b1f4ac0d0bad53617ee127aaa,Adolescent and adult risk-taking in virtual social contexts,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8d6344658fa9673b1f4ac0d0bad53617ee127aaa,Adolescent and adult risk-taking in virtual social contexts,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8d6344658fa9673b1f4ac0d0bad53617ee127aaa,Adolescent and adult risk-taking in virtual social contexts,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8d6344658fa9673b1f4ac0d0bad53617ee127aaa,Adolescent and adult risk-taking in virtual social contexts,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+8d7d02bdd3a6dfc01982468ed3eb4e66d99a302f,Data Curation APIs,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+8d7d02bdd3a6dfc01982468ed3eb4e66d99a302f,Data Curation APIs,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+8d8d333eb194bce847a4bbfc85fe332643622a34,Learning Hand Articulations by Hallucinating Heat Distribution,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+8d03e982bac627dfea7a785a597d5946c6b2c4bb,"Landmark localization, feature matching and biomarker discovery from magnetic resonance images",Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+8d03e982bac627dfea7a785a597d5946c6b2c4bb,"Landmark localization, feature matching and biomarker discovery from magnetic resonance images",Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+8d955b025495522e67e8cb6e29436001ebbd0abb,Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
+8d955b025495522e67e8cb6e29436001ebbd0abb,Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+8dbb08fdd8827383ce74dde937b74cf21b687cbb,Rediction and U Nsupervised L Earning,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+8d1253f315c821bd2b354550ae9ea6d3d7be1d31,Improved Low Resolution Heterogeneous Face Recognition Using Re-ranking,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+8dcc1e0f0215dd5fcb6d698c35180d40dadc8dac,VirtualWorlds as Proxy for Multi-object Tracking Analysis,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
8d4f12ed7b5a0eb3aa55c10154d9f1197a0d84f3,Cascaded pose regression,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+8d1b3fff760c2574a78a849f9b710f8880c94dd2,Improving Multi-Person Pose Estimation using Label Correction,Keio University,Keio University,"綱島市民の森, けつわり坂, 港北区, 横浜市, 神奈川県, 関東地方, 223-0053, 日本",35.54169690,139.63471840,edu,
+8da1b0834688edb311a803532e33939e9ecf8292,CornerNet: Detecting Objects as Paired Keypoints,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+8dea22172bd3008ec3c8008bc6edfdfe1e33e439,CityPersons: A Diverse Dataset for Pedestrian Detection,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
8de6deefb90fb9b3f7d451b9d8a1a3264b768482,Multibiometric Systems : Fusion Strategies and Template Security,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
8d2c0c9155a1ed49ba576ac0446ec67725468d87,A Study of Two Image Representations for Head Pose Estimation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+8d203e9f7aa88ee167f5eb620a63dcf2dc64fb2e,A Knowledge-Grounded Multimodal Search-Based Conversational Agent,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
8d0243b8b663ca0ab7cbe613e3b886a5d1c8c152,Development of Optical Computer Recognition (OCR) for Monitoring Stress and Emotions in Space,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
8d6c4af9d4c01ff47fe0be48155174158a9a5e08,"Labeling, discovering, and detecting objects in images",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+8d09e7c3c6b714574b2a4a7993ac94beb9d4f50d,Human eye localization using edge projections,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+8d09e7c3c6b714574b2a4a7993ac94beb9d4f50d,Human eye localization using edge projections,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
8dcc95debd07ebab1721c53fa50d846fef265022,MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Frontal Face Images,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+8d879f4aa3284aca8d671d8360c6b6f2f0f07a23,Non-local RoIs for Instance Segmentation,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+8d879f4aa3284aca8d671d8360c6b6f2f0f07a23,Non-local RoIs for Instance Segmentation,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+8d44aa6745ec0b30f1402531b3419f3310587dc7,Kernel Latent SVM for Visual Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+8d44aa6745ec0b30f1402531b3419f3310587dc7,Kernel Latent SVM for Visual Recognition,University of Manitoba,University of Manitoba,"University of Manitoba, Gillson Street, Normand Park, Saint Vital, Winnipeg, Manitoba, R3T 2N2, Canada",49.80915360,-97.13304179,edu,
+8d44aa6745ec0b30f1402531b3419f3310587dc7,Kernel Latent SVM for Visual Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+8d44aa6745ec0b30f1402531b3419f3310587dc7,Kernel Latent SVM for Visual Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+8dd9eafab9498d495f0f6bf487d6a9c3aa7f3c57,StNet: Local and Global Spatial-Temporal Modeling for Action Recognition,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+8dd9eafab9498d495f0f6bf487d6a9c3aa7f3c57,StNet: Local and Global Spatial-Temporal Modeling for Action Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+8d0dffcf36e76ebbb5ff9389750264d9fb77265f,Comparison of Visual Datasets for Machine Learning,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+8d0dffcf36e76ebbb5ff9389750264d9fb77265f,Comparison of Visual Datasets for Machine Learning,University of Miami,University of Miami,"University of Miami, Theo Dickenson Drive, Coral Gables, Miami-Dade County, Florida, 33124, USA",25.71733390,-80.27866887,edu,
+8d0dffcf36e76ebbb5ff9389750264d9fb77265f,Comparison of Visual Datasets for Machine Learning,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
+8df05de407b829abb357e230bead5407cabe7305,U Can Touch This: How Tablets Can Be Used to Study Cognitive Development,Ruhr-University Bochum,Ruhr-University Bochum,"RUB, 150, Universitätsstraße, Ruhr-Universität, Querenburg, Bochum-Süd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland",51.44415765,7.26096541,edu,
+8dce6fa7a13cc94954cbc6be9a709a4ce696ead3,Vision and Language Integration: Moving beyond Objects,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
8d91f06af4ef65193f3943005922f25dbb483ee4,Facial Expression Classification Using Rotation Slepian-based Moment Invariants,University of Macau,University of Macau,"研究生宿舍 Residência de Estudantes de Pós-Graduação da Universidade de Macau, 澳門大學 Universidade de Macau, 嘉模堂區 Nossa Senhora do Carmo, 氹仔 Taipa, Universidade de Macau em Ilha de Montanha 澳門大學橫琴校區, 中国",22.12401870,113.54510901,edu,
+8d007d8d75cb84e3350889ad5e1cc6520688e65e,Optimizing Nondecomposable Loss Functions in Structured Prediction,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+8d007d8d75cb84e3350889ad5e1cc6520688e65e,Optimizing Nondecomposable Loss Functions in Structured Prediction,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+8d007d8d75cb84e3350889ad5e1cc6520688e65e,Optimizing Nondecomposable Loss Functions in Structured Prediction,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
8dc9de0c7324d098b537639c8214543f55392a6b,Pose-Invariant 3D Object Recognition Using Linear Combination of 2D Views and Evolutionary Optimisation,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+8dc10cb0c8f6e449c22bb11399aa886d850fc701,A Projected Gradient Descent Method for CRF Inference Allowing End-to-End Training of Arbitrary Pairwise Potentials,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8dc10cb0c8f6e449c22bb11399aa886d850fc701,A Projected Gradient Descent Method for CRF Inference Allowing End-to-End Training of Arbitrary Pairwise Potentials,Lund University,Lund University,"TEM at Lund University, 9, Klostergatan, Stadskärnan, Centrum, Lund, Skåne, Götaland, 22222, Sverige",55.70395710,13.19020110,edu,
+8d228b4c0787d9e29b0c1fff05f15198bda911c9,Scalable and Effective Deep CCA via Soft Decorrelation,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+8d9ffe9f7bf1ff3ecc320afe50a92a867a12aeb7,Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8d9ffe9f7bf1ff3ecc320afe50a92a867a12aeb7,Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8d9ffe9f7bf1ff3ecc320afe50a92a867a12aeb7,Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8d44ac33d768fdc436c1b8ce995e2a6dbc4ad74b,Face recognition across large pose variations via Boosted Tied Factor Analysis,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+8d95317d0e366cecae1dd3f7c1ba69fe3fc4a8e0,Riesz-based Volume Local Binary Pattern and A Novel Group Expression Model for Group Happiness Intensity Analysis,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+8d95317d0e366cecae1dd3f7c1ba69fe3fc4a8e0,Riesz-based Volume Local Binary Pattern and A Novel Group Expression Model for Group Happiness Intensity Analysis,University of Canberra,University of Canberra,"University of Canberra, University Drive, Bruce, Belconnen, Australian Capital Territory, 2617, Australia",-35.23656905,149.08446994,edu,
+8d95317d0e366cecae1dd3f7c1ba69fe3fc4a8e0,Riesz-based Volume Local Binary Pattern and A Novel Group Expression Model for Group Happiness Intensity Analysis,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+8d94e72ebcbc8f93dc60eb42ac7058d6a94e8683,D-LinkNet : LinkNet with Pretrained Encoder and Dilated Convolution for High Resolution Satellite Imagery Road Extraction,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+15fbe139cbfd19513763db06b8ffa2e21168ca4e,GestureGAN for Hand Gesture-to-Gesture Translation in the Wild,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+15fbe139cbfd19513763db06b8ffa2e21168ca4e,GestureGAN for Hand Gesture-to-Gesture Translation in the Wild,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+15638d4611867b8f105fb541dbb61669fde6ab2a,Object Detection via Aspect Ratio and Context Aware Region-based Convolutional Networks,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
+15638d4611867b8f105fb541dbb61669fde6ab2a,Object Detection via Aspect Ratio and Context Aware Region-based Convolutional Networks,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+159afb7fb0740f0b48b812ed5183c2229089044d,A Comparative Study on Multi-person Tracking Using Overlapping Cameras,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+150855fdaca2ff3ae5a51da4f82f120a92cac104,SmartSketcher: sketch-based image retrieval with dynamic semantic re-ranking,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+1505e0aea7f82488dad1448e79b22c3b0ebc65cf,"Fast, Approximate 3D Face Reconstruction from Multiple Views",University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+15b0e598d9692d77aa33370dd3a1a47ba5f99aa6,Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
155199d7f10218e29ddaee36ebe611c95cae68c4,Towards Scalable Visual Navigation of Micro Aerial Vehicles,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
155199d7f10218e29ddaee36ebe611c95cae68c4,Towards Scalable Visual Navigation of Micro Aerial Vehicles,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+158452a25143013e4c406ee2d41a7399c34df3db,Detecting Snap Points in Egocentric Video with a Web Photo Prior,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+15db3bb041ee06a369f0cd478369c75618a35387,Pathological game use in adults with and without Autism Spectrum Disorder,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+15db3bb041ee06a369f0cd478369c75618a35387,Pathological game use in adults with and without Autism Spectrum Disorder,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
+15db3bb041ee06a369f0cd478369c75618a35387,Pathological game use in adults with and without Autism Spectrum Disorder,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+158974dc6503cb4939b87a1fffe17871e8a48c91,Local Sparse Discriminant Analysis for Robust Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
15affdcef4bb9d78b2d3de23c9459ee5b7a43fcb,Semi-Supervised Classification Using Linear Neighborhood Propagation,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
15affdcef4bb9d78b2d3de23c9459ee5b7a43fcb,Semi-Supervised Classification Using Linear Neighborhood Propagation,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
15d653972d176963ef0ad2cc582d3b35ca542673,CSVideoNet: A Real-Time End-to-End Learning Framework for High-Frame-Rate Video Compressive Sensing,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
159e792096756b1ec02ec7a980d5ef26b434ff78,Signed Laplacian Embedding for Supervised Dimension Reduction,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
159e792096756b1ec02ec7a980d5ef26b434ff78,Signed Laplacian Embedding for Supervised Dimension Reduction,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+155959429a6f44e7b980ff00f2d5c0343d71c4dd,Patch-Based Segmentation without Registration: Application to Knee MRI,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
1586871a1ddfe031b885b94efdbff647cf03eff1,A Century of Portraits: A Visual Historical Record of American High School Yearbooks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
1586871a1ddfe031b885b94efdbff647cf03eff1,A Century of Portraits: A Visual Historical Record of American High School Yearbooks,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
1586871a1ddfe031b885b94efdbff647cf03eff1,A Century of Portraits: A Visual Historical Record of American High School Yearbooks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+1582c29d0f752f95a12f5a8ce08d5e5c752f6822,Developmental changes in infants' categorization of anger and disgust facial expressions.,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
15cf7bdc36ec901596c56d04c934596cf7b43115,Face Extraction from Image based on K-Means Clustering Algorithms,Islamic Azad University,Islamic Azad University,"دانشگاه آزاد اسلامی, همدان, بخش مرکزی شهرستان همدان, شهرستان همدان, استان همدان, ایران",34.84529990,48.55962120,edu,
1576ed0f3926c6ce65e0ca770475bca6adcfdbb4,Keep it accurate and diverse: Enhancing action recognition performance by ensemble learning,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
156cd2a0e2c378e4c3649a1d046cd080d3338bca,Exemplar based approaches on Face Fiducial Detection and Frontalization,International Institute of Information Technology,International Institute of Information Technology,"International Institute of Information Technology, Hyderabad, Campus Road, Ward 105 Gachibowli, Greater Hyderabad Municipal Corporation West Zone, Hyderabad, Rangareddy District, Telangana, 500032, India",17.44549570,78.34854698,edu,
+1574abc94d22b03f8c9630f0eb7ad1f8ed67880e,Cross-View Image Synthesis using Conditional GANs,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+15e1af79939dbf90790b03d8aa02477783fb1d0f,Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in Vitro,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+15a0546ee32ac391f342a6188446dd6699a1d7b8,Person re-ID while Crossing Different Cameras: Combination of Salient-Gaussian Weighted BossaNova and Fisher Vector Encodings,"University of Sfax, Tunisia","REGIM-Labo: REsearch Groups in Intelligent Machines, University of Sfax, ENIS, BP 1173, Sfax, 3038, Tunisia","Université de Route de l'Aéroport Km 0.5 BP 1169 .3029 Sfax, Sfax, Tunisia",34.73610660,10.74272750,edu,"University of Sfax, Tunisia"
151481703aa8352dc78e2577f0601782b8c41b34,Appearance Manifold of Facial Expression,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+15037913b5d3f299da509218f0b914227d10b929,Towards the use of social interaction conventions as prior for gaze model adaptation,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+15037913b5d3f299da509218f0b914227d10b929,Towards the use of social interaction conventions as prior for gaze model adaptation,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+15037913b5d3f299da509218f0b914227d10b929,Towards the use of social interaction conventions as prior for gaze model adaptation,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
1565721ebdbd2518224f54388ed4f6b21ebd26f3,Face and landmark detection by using cascade of classifiers,Eskisehir Osmangazi University,Eskisehir Osmangazi University,"Eskişehir Osmangazi Üniversitesi Meşelik Yerleşkesi, Kütahya-Eskişehir yolu, Sazova Mahallesi, Karagözler, Tepebaşı, Eskişehir, İç Anadolu Bölgesi, 26160, Türkiye",39.74875160,30.47653071,edu,
1565721ebdbd2518224f54388ed4f6b21ebd26f3,Face and landmark detection by using cascade of classifiers,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+15d2703ac86652aaa8182ff60da19fc1bccb22ce,"Measurement, Modeling, and Synthesis of Time-Varying Appearance of Natural Phenomena",Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+15d1582c8b65dbab5ca027467718a2c286ddce7a,"On robust face recognition via sparse coding: the good, the bad and the ugly",National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+15d1582c8b65dbab5ca027467718a2c286ddce7a,"On robust face recognition via sparse coding: the good, the bad and the ugly",University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+15d1582c8b65dbab5ca027467718a2c286ddce7a,"On robust face recognition via sparse coding: the good, the bad and the ugly",Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
15252b7af081761bb00535aac6bd1987391f9b79,Estimation of eye gaze direction angles based on active appearance models,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
+1504eae5487e1e062fef96e1e424de5d3a5a3858,MSRC: multimodal spatial regression with semantic context for phrase grounding,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+1504eae5487e1e062fef96e1e424de5d3a5a3858,MSRC: multimodal spatial regression with semantic context for phrase grounding,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+1504eae5487e1e062fef96e1e424de5d3a5a3858,MSRC: multimodal spatial regression with semantic context for phrase grounding,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+1504eae5487e1e062fef96e1e424de5d3a5a3858,MSRC: multimodal spatial regression with semantic context for phrase grounding,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+152ca42d6701db43dbd8a37901d56a52e4a9e6f9,Social negative bootstrapping for visual categorization,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
15ee80e86e75bf1413dc38f521b9142b28fe02d1,Towards a deep learning framework for unconstrained face detection,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+15912abb1fe1457bb358d2d2b0e586c1987b6e25,Evaluation of the Pain Level from Speech: Introducing a Novel Pain Database and Benchmarks,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
15e27f968458bf99dd34e402b900ac7b34b1d575,Ranking 2DLDA features based on fisher discriminance,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
15f70a0ad8903017250927595ae2096d8b263090,Learning Robust Deep Face Representation,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
1564bf0a268662df752b68bee5addc4b08868739,With whom do I interact? Detecting social interactions in egocentric photo-streams,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
1564bf0a268662df752b68bee5addc4b08868739,With whom do I interact? Detecting social interactions in egocentric photo-streams,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
1564bf0a268662df752b68bee5addc4b08868739,With whom do I interact? Detecting social interactions in egocentric photo-streams,University of Barcelona,University of Barcelona,"Universitat de Barcelona, Carrer de la Diputació, l'Antiga Esquerra de l'Eixample, Eixample, Barcelona, BCN, CAT, 08013, España",41.38689130,2.16352385,edu,
158e32579e38c29b26dfd33bf93e772e6211e188,Automated Real Time Emotion Recognition using Facial Expression Analysis,Carleton University,Carleton University,"Carleton University, 1125, Colonel By Drive, Billings Bridge, Capital, Ottawa, Ontario, K1S 5B7, Canada",45.38608430,-75.69539267,edu,
+12044354032fdee40405cb12e8bbebb6d073a768,Women Are Seen More than Heard in Online Newspapers,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+12044354032fdee40405cb12e8bbebb6d073a768,Women Are Seen More than Heard in Online Newspapers,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
122f51cee489ba4da5ab65064457fbe104713526,Long Short Term Memory Recurrent Neural Network based Multimodal Dimensional Emotion Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
122f51cee489ba4da5ab65064457fbe104713526,Long Short Term Memory Recurrent Neural Network based Multimodal Dimensional Emotion Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
122f51cee489ba4da5ab65064457fbe104713526,Long Short Term Memory Recurrent Neural Network based Multimodal Dimensional Emotion Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
122f51cee489ba4da5ab65064457fbe104713526,Long Short Term Memory Recurrent Neural Network based Multimodal Dimensional Emotion Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
121503705689f46546cade78ff62963574b4750b,We Don’t Need No Bounding-Boxes: Training Object Class Detectors Using Only Human Verification,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
+12c6f3ae8f20a1473a89b9cbb82d0f02275ea62b,Hand detection using multiple proposals,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+12c6f3ae8f20a1473a89b9cbb82d0f02275ea62b,Hand detection using multiple proposals,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
+12811f1dc14c9377903d4c814e112071118071a5,I Have Seen Enough: Transferring Parts Across Categories,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
125d82fee1b9fbcc616622b0977f3d06771fc152,Hierarchical face parsing via deep learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
125d82fee1b9fbcc616622b0977f3d06771fc152,Hierarchical face parsing via deep learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
125d82fee1b9fbcc616622b0977f3d06771fc152,Hierarchical face parsing via deep learning,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
1255afbf86423c171349e874b3ac297de19f00cd,Robust Face Recognition by Computing Distances From Multiple Histograms of Oriented Gradients,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
1275d6a800f8cf93c092603175fdad362b69c191,Deep Face Recognition: A Survey,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+12dcb25f10d42ad2b4352ba9fe7a6a32ee2635a6,The Automatic Scientist will be a Data System,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+12c2f7cee1f6abff0d4de9b4b90caa3b5c6084a0,Adult Content Recognition from Images Using a Mixture of Convolutional Neural Networks,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+12e5ff3d6771d725f09bb0b2f14d17a64d4c1c25,The fear gasping face as a threat display in a Melanesian society.,Boston College,Boston College,"Boston College, 140, Commonwealth Avenue, Chestnut Hill, Newton, Middlesex County, Massachusetts, 02467, USA",42.33544810,-71.16813864,edu,
+12e5ff3d6771d725f09bb0b2f14d17a64d4c1c25,The fear gasping face as a threat display in a Melanesian society.,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+1235dd37312cb20aced0e97d953f6379d8a0c7d4,Grounded Textual Entailment,University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
126535430845361cd7a3a6f317797fe6e53f5a3b,Robust Photometric Stereo via Low-Rank Matrix Completion and Recovery,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
126535430845361cd7a3a6f317797fe6e53f5a3b,Robust Photometric Stereo via Low-Rank Matrix Completion and Recovery,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+12c68afcd77584f3db55b42f38c3ac0e19389b60,Discriminative tag learning on YouTube videos with latent sub-tags,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+129d0e22d6b847c8002fd2c70bb508cdf3286fb8,"Investigating Audio, Visual, and Text Fusion Methods for End-to-End Automatic Personality Prediction",Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+12679cdcb4bc5e9c60a795c2418b40b5e1681652,Volterrafaces: Discriminant analysis using Volterra kernels,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
121fe33daf55758219e53249cf8bcb0eb2b4db4b,An Empirical Camera Model for Internet Color Vision,Middlebury College,Middlebury College,"Middlebury College, Old Chapel Road, Middlebury, Addison County, Vermont, 05753, USA",44.00907770,-73.17679460,edu,
12408baf69419409d228d96c6f88b6bcde303505,Temporal Tessellation: A Unified Approach for Video Analysis,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
12408baf69419409d228d96c6f88b6bcde303505,Temporal Tessellation: A Unified Approach for Video Analysis,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
@@ -4091,6 +11405,16 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 120bcc9879d953de7b2ecfbcd301f72f3a96fb87,Report on the FG 2015 Video Person Recognition Evaluation,National Institute of Standards and Technology,National Institute of Standards and Technology,"National Institute of Standards and Technology, Summer Walk Drive, Diamond Farms, Gaithersburg, Montgomery County, Maryland, 20878, USA",39.12549380,-77.22293475,edu,
12095f9b35ee88272dd5abc2d942a4f55804b31e,DenseReg : Fully Convolutional Dense Shape Regression Inthe-Wild Rıza,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
12095f9b35ee88272dd5abc2d942a4f55804b31e,DenseReg : Fully Convolutional Dense Shape Regression Inthe-Wild Rıza,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+12fa75f90b0dcf254c33145fe08e7ce0f099066a,Active Learning with Cross-Class Knowledge Transfer,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+124d60fae338b1f87455d1fc4ede5fcfd806da1a,Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+124d60fae338b1f87455d1fc4ede5fcfd806da1a,Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+124d60fae338b1f87455d1fc4ede5fcfd806da1a,Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification,Charles Sturt University,Charles Sturt University,"Charles Sturt University, Wagga Wagga, NSW, 2678, Australia",-35.06360710,147.35522340,edu,
+12441a74e709ddab53f9039cf507491df7b3840a,SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+12441a74e709ddab53f9039cf507491df7b3840a,SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+12441a74e709ddab53f9039cf507491df7b3840a,SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+12441a74e709ddab53f9039cf507491df7b3840a,SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+12441a74e709ddab53f9039cf507491df7b3840a,SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+12441a74e709ddab53f9039cf507491df7b3840a,SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
1297ee7a41aa4e8499c7ddb3b1fed783eba19056,Effects of emotional expressions on persuasion,University of Nebraska - Lincoln,University of Nebraska - Lincoln,"Sheldon Museum of Art, North 12th Street, West Lincoln, Lincoln, Lancaster County, Nebraska, 68588-0300, USA",40.81747230,-96.70444680,edu,
1297ee7a41aa4e8499c7ddb3b1fed783eba19056,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
1297ee7a41aa4e8499c7ddb3b1fed783eba19056,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
@@ -4098,13 +11422,23 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 1297ee7a41aa4e8499c7ddb3b1fed783eba19056,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
1297ee7a41aa4e8499c7ddb3b1fed783eba19056,Effects of emotional expressions on persuasion,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
126214ef0dcef2b456cb413905fa13160c73ec8e,Modelling human perception of static facial expressions,University of Siena,University of Siena,"大學 University, 澤祥街 Chak Cheung Street, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.41338620,114.21005800,edu,
+126250d6077a6a68ae06277352eb42c4fa4c8b10,Learning Patch-based Structural Element Models with Hierarchical Palettes Abstract Learning Patch-based Structural Element Models with Hierarchical Palettes,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+12bce6e2db10faa4f370f9e40a6084296080b5cb,Learning to rank in person re-identification with metric ensembles,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
12692fbe915e6bb1c80733519371bbb90ae07539,Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
12692fbe915e6bb1c80733519371bbb90ae07539,Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+12169ff906633e486599660ebf77dd73060640b9,Multi-stage Contextual Deep Learning for Pedestrian Detection,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+12f2325789febc95c9b453d12194bf4a778e60bd,Semantic Video Segmentation: A Review on Recent Approaches,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
1251deae1b4a722a2155d932bdfb6fe4ae28dd22,A Large-scale Attribute Dataset for Zero-shot Learning,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
1251deae1b4a722a2155d932bdfb6fe4ae28dd22,A Large-scale Attribute Dataset for Zero-shot Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
12ccfc188de0b40c84d6a427999239c6a379cd66,Sparse Adversarial Perturbations for Videos,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+12169222eeee058578629e5097f250c3992530b1,Boosting relative spaces for categorizing objects with large intra-class variation,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+127b17fdd8860605680cfd053398fa95d12ccc03,Visual Question Generation as Dual Task of Visual Question Answering,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+127b17fdd8860605680cfd053398fa95d12ccc03,Visual Question Generation as Dual Task of Visual Question Answering,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+127b17fdd8860605680cfd053398fa95d12ccc03,Visual Question Generation as Dual Task of Visual Question Answering,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+127b17fdd8860605680cfd053398fa95d12ccc03,Visual Question Generation as Dual Task of Visual Question Answering,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
1270044a3fa1a469ec2f4f3bd364754f58a1cb56,Video-Based Face Recognition Using Probabilistic Appearance Manifolds,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
12003a7d65c4f98fb57587fd0e764b44d0d10125,Face recognition in the wild with the Probabilistic Gabor-Fisher Classifier,University of Ljubljana,University of Ljubljana,"UL Fakulteta za računalništvo in informatiko, 113, Večna pot, Vrtača, Rožna dolina, Ljubljana, Upravna Enota Ljubljana, Osrednjeslovenska, 1000, Slovenija",46.05015580,14.46907327,edu,
+12336e7d5d2ca4e1fdd2a52d50b2a5c987c08b0b,Assessing tracking assessment measures,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
124538b3db791e30e1b62f81d4101be435ee12ef,"Basic level scene understanding: categories, attributes and structures",Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
124538b3db791e30e1b62f81d4101be435ee12ef,"Basic level scene understanding: categories, attributes and structures",Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
124538b3db791e30e1b62f81d4101be435ee12ef,"Basic level scene understanding: categories, attributes and structures",University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
@@ -4112,129 +11446,473 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 124538b3db791e30e1b62f81d4101be435ee12ef,"Basic level scene understanding: categories, attributes and structures",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
124538b3db791e30e1b62f81d4101be435ee12ef,"Basic level scene understanding: categories, attributes and structures",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
124538b3db791e30e1b62f81d4101be435ee12ef,"Basic level scene understanding: categories, attributes and structures",Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+120c85cf69ea656b02262b4bc5761117fe35674e,Learning Exemplar-Represented Manifolds in Latent Space for Classification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+124d43c5f76e70ec1f9eac62ef48f1dc2b547c04,Optimal Dimensionality Discriminant Analysis and Its Application to Image Recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
8c8525e626c8857a4c6c385de34ffea31e7e41d1,Cross-Domain Image Retrieval with a Dual Attribute-Aware Ranking Network,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
8c8525e626c8857a4c6c385de34ffea31e7e41d1,Cross-Domain Image Retrieval with a Dual Attribute-Aware Ranking Network,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+8c04688425fa3e03c24d08b09faad49e33f2cc30,Adversarial Dropout Regularization,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
8c66378df977606d332fc3b0047989e890a6ac76,Hierarchical-PEP model for real-world face recognition,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
+8c8a61fc2c0e426aa64e50756b777475f3beb49b,Robust Marker-Based Tracking for Measuring Crowd Dynamics,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
8c9c8111e18f8798a612e7386e88536dfe26455e,Comparing Bayesian Networks to Classify Facial Expressions,Institute of Systems and Robotics,Institute of Systems and Robotics,"Institut für Robotik und Kognitive Systeme, 160, Ratzeburger Allee, Strecknitz, Sankt Jürgen, Strecknitz, Lübeck, Schleswig-Holstein, 23562, Deutschland",53.83383710,10.70359390,edu,
8c9c8111e18f8798a612e7386e88536dfe26455e,Comparing Bayesian Networks to Classify Facial Expressions,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
8c9c8111e18f8798a612e7386e88536dfe26455e,Comparing Bayesian Networks to Classify Facial Expressions,Institute of Systems and Robotics,Institute of Systems and Robotics,"Institut für Robotik und Kognitive Systeme, 160, Ratzeburger Allee, Strecknitz, Sankt Jürgen, Strecknitz, Lübeck, Schleswig-Holstein, 23562, Deutschland",53.83383710,10.70359390,edu,
8c9c8111e18f8798a612e7386e88536dfe26455e,Comparing Bayesian Networks to Classify Facial Expressions,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
8c9c8111e18f8798a612e7386e88536dfe26455e,Comparing Bayesian Networks to Classify Facial Expressions,Institute of Systems and Robotics,Institute of Systems and Robotics,"Institut für Robotik und Kognitive Systeme, 160, Ratzeburger Allee, Strecknitz, Sankt Jürgen, Strecknitz, Lübeck, Schleswig-Holstein, 23562, Deutschland",53.83383710,10.70359390,edu,
8c9c8111e18f8798a612e7386e88536dfe26455e,Comparing Bayesian Networks to Classify Facial Expressions,University of Coimbra,University of Coimbra,"Reitoria da Universidade de Coimbra, Rua de Entre-Colégios, Almedina, Alta, Almedina, Sé Nova, Santa Cruz, Almedina e São Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal",40.20759510,-8.42566148,edu,
+8c357c8716e7a0606587cc67b209276b08483f3e,Care about you: towards large-scale human-centric visual relationship detection,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+8ccd6aaf1ee4b66c13fffbf560e3920f9bdf5f10,A multitask deep learning model for real-time deployment in embedded systems,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+8c618c038c60a385d220193f87b8b0759aab0fd7,A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+8c618c038c60a385d220193f87b8b0759aab0fd7,A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos,Vrije Universiteit Brussel,Vrije Universiteit Brussel,"Vrije Universiteit Brussel, 170, Quai de l'Industrie - Nijverheidskaai, Anderlecht, Brussel-Hoofdstad - Bruxelles-Capitale, Région de Bruxelles-Capitale - Brussels Hoofdstedelijk Gewest, 1070, België / Belgique / Belgien",50.84110070,4.32377555,edu,
+8c99f35d6c3851513adb2c2d5c385c989879e05b,The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+8c99f35d6c3851513adb2c2d5c385c989879e05b,The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+8c99f35d6c3851513adb2c2d5c385c989879e05b,The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+8c99f35d6c3851513adb2c2d5c385c989879e05b,The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
+8c99f35d6c3851513adb2c2d5c385c989879e05b,The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring,University of Florida,University of Florida,"University of Florida, Southwest 16th Avenue, Diamond Village Apartments, City of Gainesville Municipal Boundaries, Alachua County, Florida, 32611, USA",29.63287840,-82.34901330,edu,
8c81705e5e4a1e2068a5bd518adc6955d49ae434,3D Object Recognition with Enhanced Grassmann Discriminant Analysis,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+8c269412a8c9e646641750dce2a1b2ee7b9c6b2e,On MultiView Face Recognition Using Lytro Images,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+8c269412a8c9e646641750dce2a1b2ee7b9c6b2e,On MultiView Face Recognition Using Lytro Images,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+8c192cd39f90eb8ff2969f8916ef8967607c5298,"See, Hear, and Read: Deep Aligned Representations",MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+8ca0a7f2e5a7b1676f9a409c3ed5749c8a569b83,A new approach for pedestrian density estimation using moving sensors and computer vision,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+8ca0a7f2e5a7b1676f9a409c3ed5749c8a569b83,A new approach for pedestrian density estimation using moving sensors and computer vision,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
8cb403c733a5f23aefa6f583a17cf9b972e35c90,Learning the semantic structure of objects from Web supervision,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8c1e828a4826a1fb3eb47ee432f5333b974fa141,Spatial Graph for Image Classification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+8c522c293ffbb4d8f451789e3f05f5815bf40b92,An Efficient LBP-Based Descriptor for Facial Depth Images Applied to Gender Recognition Using RGB-D Face Data,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+8c6c743e21592304ee28ec073657bf128376ff8c,Power Normalizing Second-order Similarity Network for Few-shot Learning,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+8c6c743e21592304ee28ec073657bf128376ff8c,Power Normalizing Second-order Similarity Network for Few-shot Learning,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
8ccde9d80706a59e606f6e6d48d4260b60ccc736,RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
8ccde9d80706a59e606f6e6d48d4260b60ccc736,RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
8c6b9c9c26ead75ce549a57c4fd0a12b46142848,Facial expression recognition using shape and texture information,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+8c7284a0958c31f57b0558d3951d4486379ffacc,The role of napping on memory consolidation in preschool children,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+8c71e28a4ffb283a9cf3c5549e2fc64e9b0ecd5c,Metric Learning with Dynamically Generated Pairwise Constraints for Ear Recognition,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
8c4ea76e67a2a99339a8c4decd877fe0aa2d8e82,Gated Convolutional Neural Network for Semantic Segmentation in High-Resolution Images,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
8c4ea76e67a2a99339a8c4decd877fe0aa2d8e82,Gated Convolutional Neural Network for Semantic Segmentation in High-Resolution Images,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+8c5d1a334e7a88dc5e54383df1eef13188c2b6b5,Multi-Cue Correlation Filters for Robust Visual Tracking,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+8ce5425f20f2c9e27d954a7d86503b9a0a33c34c,A poselet based key frame searching approach in sports training videos,Beijing University of Technology,Beijing University of Technology,"北京工业大学, 银杏大道, 大郊亭村, 朝阳区 / Chaoyang, 北京市, 3208, 中国",39.87391435,116.47722285,edu,
+8ce9949b88726e117552ce3aa6901a5178db3bb2,Liberating the Biometric Menagerie Through Score Normalization Improvements,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+8c3cf0c579a28890e21428fcad7f09175e65e43d,Adding object detection skills to visual dialogue agents,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
+8c7811c029905f4f3e9f31e925634a42e413f6d8,Face Matching Between Near Infrared and Visible Light Images,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+8c4bcbaee18aaae417e2f2da7a7b95bd8edaf063,Learning Convolutional Networks for Content-weighted Image Compression,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+8c4bcbaee18aaae417e2f2da7a7b95bd8edaf063,Learning Convolutional Networks for Content-weighted Image Compression,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+8c4bcbaee18aaae417e2f2da7a7b95bd8edaf063,Learning Convolutional Networks for Content-weighted Image Compression,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+8c4bcbaee18aaae417e2f2da7a7b95bd8edaf063,Learning Convolutional Networks for Content-weighted Image Compression,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+8c4bcbaee18aaae417e2f2da7a7b95bd8edaf063,Learning Convolutional Networks for Content-weighted Image Compression,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+8c5dcd5a0b3c9940e544993327eab6425ce645d5,nsemble perception of emotions in autistic and typical children and dolescents,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+8c5dcd5a0b3c9940e544993327eab6425ce645d5,nsemble perception of emotions in autistic and typical children and dolescents,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
+8c5dcd5a0b3c9940e544993327eab6425ce645d5,nsemble perception of emotions in autistic and typical children and dolescents,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8c5dcd5a0b3c9940e544993327eab6425ce645d5,nsemble perception of emotions in autistic and typical children and dolescents,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
+8c5dcd5a0b3c9940e544993327eab6425ce645d5,nsemble perception of emotions in autistic and typical children and dolescents,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+8c5dcd5a0b3c9940e544993327eab6425ce645d5,nsemble perception of emotions in autistic and typical children and dolescents,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+8c5dcd5a0b3c9940e544993327eab6425ce645d5,nsemble perception of emotions in autistic and typical children and dolescents,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
8cb55413f1c5b6bda943697bba1dc0f8fc880d28,Video-based Face Recognition on Real-World Data,University of Karlsruhe,University of Karlsruhe,"Karlshochschule International University, 36-38, Karlstraße, Innenstadt-West Westlicher Teil, Innenstadt-West, Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76133, Deutschland",49.00664235,8.39405152,edu,
+8552f6e3f73db564a2e625cceb1d1348d70b598c,Learning Compact Appearance Representation for Video-based Person Re-Identification,Shandong University,Shandong University,"山东大学, 泰安街, 鳌山卫街道, 即墨区, 青岛市, 山东省, 266200, 中国",36.36934730,120.67381800,edu,
+85304f24f5a1800e66de20ad05e20c8c032b7d03,Understanding and Discovering Deliberate Self-harm Content in Social Media,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+85faaad8eddebc960865e351c0e3ea81e25d42eb,Deep Group-shuffling Random Walk for Person Re-identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+85192977775e1f1001334a13de5d32736fbfd24c,Pedestrian Parsing via Deep Decompositional Network,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+85192977775e1f1001334a13de5d32736fbfd24c,Pedestrian Parsing via Deep Decompositional Network,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+85192977775e1f1001334a13de5d32736fbfd24c,Pedestrian Parsing via Deep Decompositional Network,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
85041e48b51a2c498f22850ce7228df4e2263372,Subspace Regression: Predicting a Subspace from One Sample,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+85c2de95080c1e8d955ac57f64a6b51ac186af32,Imputing human descriptions in semantic biometrics,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+85678d8aef7188bd59f18829de5b3980af7404b6,Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental States,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+85678d8aef7188bd59f18829de5b3980af7404b6,Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental States,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+85678d8aef7188bd59f18829de5b3980af7404b6,Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental States,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
857ad04fca2740b016f0066b152bd1fa1171483f,Sample Images can be Independently Restored from Face Recognition Templates,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
+8520da50e5e234c14272921868ff36d55e6c7837,Unsupervised Feature Selection on Data Streams,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+8598e603438360884073fcf7b843ac489fad43b2,Emotion Recognition from Arbitrary View Facial Images,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
+8598e603438360884073fcf7b843ac489fad43b2,Emotion Recognition from Arbitrary View Facial Images,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+85f14bb2ed4b9d680ae4062cbd571752a1ff1dfa,Efficient 3D Face Recognition with Gabor Patched Spectral Regression,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
+85f14bb2ed4b9d680ae4062cbd571752a1ff1dfa,Efficient 3D Face Recognition with Gabor Patched Spectral Regression,Beijing Jiaotong University,Beijing Jiaotong University,"北京交通大学, 银杏大道, 稻香园南社区, 海淀区, 北京市, 100044, 中国",39.94976005,116.33629046,edu,
+85af6c005df806b57b306a732dcb98e096d15bfb,Getting to Know Low-light Images with The Exclusively Dark Dataset,University of Malaya,University of Malaya,"UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia",3.12267405,101.65356103,edu,
+8546885e83f7901340c7893fdfc017cef86d910a,Convolutional Long Short-Term Memory Networks for Recognizing First Person Interactions,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+85c7aab0f58f17816064699865cd0836bfbf2e82,A New Representation for Human Gait Recognition: Motion Silhouettes Image (MSI),Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+858adc1499e556dd4d2c65705dc62d2e3592b3bf,Semantic Feature Augmentation in Few-shot Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+85b32c201ef787e9e28538f1bcbefe30ad785535,Recognition of Vehicles as Changes in Satellite Imagery,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+85b32c201ef787e9e28538f1bcbefe30ad785535,Recognition of Vehicles as Changes in Satellite Imagery,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+85b32c201ef787e9e28538f1bcbefe30ad785535,Recognition of Vehicles as Changes in Satellite Imagery,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+850d84e4c73a8f0762c8c798b2b7fd6f2787263a,The Discovery of Perceptual Structure from Visual Co - occurrences in Space and Time,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+850d84e4c73a8f0762c8c798b2b7fd6f2787263a,The Discovery of Perceptual Structure from Visual Co - occurrences in Space and Time,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+853416c2a96ad46bdf3ef044f7a11e19d86fe073,Head Pose Classification in Crowded Scenes,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+85957b49896246bb416c0a182e52b355a8fa40b4,Feature Pyramid Network for Multi-Class Land Segmentation,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+85ac4459daedecf04c46c0fd90adf57238a5993a,MSRA-MM 2.0: A Large-Scale Web Multimedia Dataset,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+85ac4459daedecf04c46c0fd90adf57238a5993a,MSRA-MM 2.0: A Large-Scale Web Multimedia Dataset,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
856317f27248cdb20226eaae599e46de628fb696,A Method Based on Convex Cone Model for Image-Set Classification with CNN Features,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+852bdbcd091f48e07e9b989cb326e631e2932d7f,Visual scanning patterns and executive function in relation to facial emotion recognition in aging.,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+852bdbcd091f48e07e9b989cb326e631e2932d7f,Visual scanning patterns and executive function in relation to facial emotion recognition in aging.,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+852bdbcd091f48e07e9b989cb326e631e2932d7f,Visual scanning patterns and executive function in relation to facial emotion recognition in aging.,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
855184c789bca7a56bb223089516d1358823db0b,Automatic Procedure to Fix Closed-Eyes Image,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+85d8c16ccd76e2eec303f98f2d1ab239dc3947a2,Self Adversarial Training for Human Pose Estimation,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+85476331edc9a9e3393f736f14aa80ad95f3c105,"""Wealth Makes Many Friends"": Children Expect More Giving From Resource-Rich Than Resource-Poor Individuals.",Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+85476331edc9a9e3393f736f14aa80ad95f3c105,"""Wealth Makes Many Friends"": Children Expect More Giving From Resource-Rich Than Resource-Poor Individuals.",Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
85639cefb8f8deab7017ce92717674d6178d43cc,Automatic Analysis of Spontaneous Facial Behavior: A Final Project Report,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
85674b1b6007634f362cbe9b921912b697c0a32c,Optimizing Facial Landmark Detection by Facial Attribute Learning,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+856c09ab10efbc8c61a84a951746654d947370f3,Human action recognition by learning bases of action attributes and parts,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+856c09ab10efbc8c61a84a951746654d947370f3,Human action recognition by learning bases of action attributes and parts,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+856c09ab10efbc8c61a84a951746654d947370f3,Human action recognition by learning bases of action attributes and parts,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+855cf31504da69daf03766b1357030dd07e485f7,Residual Dense Network for Image Super-Resolution,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+855cf31504da69daf03766b1357030dd07e485f7,Residual Dense Network for Image Super-Resolution,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+855cf31504da69daf03766b1357030dd07e485f7,Residual Dense Network for Image Super-Resolution,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+85dc159dd1eec52147b24f32f8ddab135abeb8ad,Visual Aesthetic Quality Assessment with Multi-task Deep Learning,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+851136b1d3f345d0d00c4ea36c66114444d04305,Sampling Representative Examples for Dimensionality Reduction and Recognition - Bootstrap Bumping LDA,Ohio State University,The Ohio State University,"The Ohio State University, Woody Hayes Drive, Columbus, Franklin County, Ohio, 43210, USA",40.00471095,-83.02859368,edu,
1d21e5beef23eecff6fff7d4edc16247f0fd984a,Face Recognition from Video Using the Generic Shape-Illumination Manifold,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+1d2dab7790303bbe7894d0ff08ecf87d57b1fbca,A codebook-free and annotation-free approach for fine-grained image categorization,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1d187e1d0e9eb874f85e3ecdb75ca0a7bd98d8bc,Aggression in young children with concurrent callous–unemotional traits: can the neurosciences,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+1da7d851c8d6761b4e1ab3e037596969a295ae50,Fast search in Hamming space with multi-index hashing,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+1da2431a799f68888b7e035fe49fe47a4735b71b,Leveraging Video Descriptions to Learn Video Question Answering,National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+1da2431a799f68888b7e035fe49fe47a4735b71b,Leveraging Video Descriptions to Learn Video Question Answering,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1dddfa634589e347648e79ae4e261af23553981e,Learning feed-forward one-shot learners,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1dddfa634589e347648e79ae4e261af23553981e,Learning feed-forward one-shot learners,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1dddfa634589e347648e79ae4e261af23553981e,Learning feed-forward one-shot learners,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1dddfa634589e347648e79ae4e261af23553981e,Learning feed-forward one-shot learners,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1dddfa634589e347648e79ae4e261af23553981e,Learning feed-forward one-shot learners,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1d0ee1069bd433b5f754d70517d2e0fcc519515c,Propagative Hough Voting for Human Activity Recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+1d1603a1ec73a9a0ff972f3898c94eed2c741e51,Pose Guided Person Image Generation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+1d82e7736268917cc3d87a2ee0896b03e02a5ff6,The Promise of Premise: Harnessing Question Premises in Visual Question Answering,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
+1dc35905a1deff8bc74688f2d7e2f48fd2273275,Pedestrian detection: A benchmark,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+1d3d05e294bb522b653bc6d11cb92d5c4140e41b,"AI Oriented Large-Scale Video Management for Smart City: Technologies, Standards and Beyond",Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+1d3d05e294bb522b653bc6d11cb92d5c4140e41b,"AI Oriented Large-Scale Video Management for Smart City: Technologies, Standards and Beyond",Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+1d3d05e294bb522b653bc6d11cb92d5c4140e41b,"AI Oriented Large-Scale Video Management for Smart City: Technologies, Standards and Beyond",City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
1d19c6857e798943cd0ecd110a7a0d514c671fec,Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
1d1a7ef193b958f9074f4f236060a5f5e7642fc1,Ensemble of Patterns of Oriented Edge Magnitudes Descriptors For Face Recognition,University of Bologna,Università di Bologna,"Via Zamboni, 33, 40126 Bologna BO, Italy",44.49623180,11.35415700,edu,
+1dede3e0f2e0ed2984aca8cd98631b43c3f887b9,A vote of confidence based interest point detector,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+1da09ba7340c77b3f943c15f80ff40f6f9d14eeb,MRF-Based Background Initialisation for Improved Foreground Detection in Cluttered Surveillance Videos,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
1d696a1beb42515ab16f3a9f6f72584a41492a03,"Deeply learned face representations are sparse, selective, and robust",Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1d696a1beb42515ab16f3a9f6f72584a41492a03,"Deeply learned face representations are sparse, selective, and robust",Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1d696a1beb42515ab16f3a9f6f72584a41492a03,"Deeply learned face representations are sparse, selective, and robust",Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
1d1caaa2312390260f7d20ad5f1736099818d358,Resource-Allocating Codebook for patch-based face recognition,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+1df1aa9179506554744bf16b238d05ebd1e2d4d5,Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+1df1aa9179506554744bf16b238d05ebd1e2d4d5,Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.,University of Delaware,University of Delaware,"University of Delaware, South College Avenue, Newark, New Castle County, Delaware, 19713, USA",39.68103280,-75.75401840,edu,
+1df1aa9179506554744bf16b238d05ebd1e2d4d5,Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+1df1aa9179506554744bf16b238d05ebd1e2d4d5,Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+1df1aa9179506554744bf16b238d05ebd1e2d4d5,Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+1df1aa9179506554744bf16b238d05ebd1e2d4d5,Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+1df1aa9179506554744bf16b238d05ebd1e2d4d5,Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
1dc241ee162db246882f366644171c11f7aed96d,Deep Action- and Context-Aware Sequence Learning for Activity Recognition and Anticipation,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
1d0128b9f96f4c11c034d41581f23eb4b4dd7780,Automatic construction Of robust spherical harmonic subspaces,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+1dbcf2181cb9890397c88c7cba20941af9019a20,Interpreting CNN Models for Apparent Personality Trait Regression,Universitat Oberta de Catalunya,Universitat Oberta de Catalunya,"Universitat Oberta de Catalunya, 156, Rambla del Poblenou, Provençals del Poblenou, Sant Martí, Barcelona, BCN, CAT, 08018, España",41.40657415,2.19453410,edu,
+1daf148a6d5d86e8cbe76a13311514f1338bdb0d,Image Inpainting via Generative Multi-column Convolutional Neural Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+1d5b030747bd836aebf7a00ed061a2f7bdf0a84c,Discriminative Pose-Free Descriptors for Face and Object Matching,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
1d3dd9aba79a53390317ec1e0b7cd742cba43132,A maximum entropy feature descriptor for age invariant face recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
1d3dd9aba79a53390317ec1e0b7cd742cba43132,A maximum entropy feature descriptor for age invariant face recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1d3dd9aba79a53390317ec1e0b7cd742cba43132,A maximum entropy feature descriptor for age invariant face recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+1d0dcb458aa4d30b51f7c74b159be687f39120a0,Pose-Driven Deep Convolutional Model for Person Re-identification,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+1d0dcb458aa4d30b51f7c74b159be687f39120a0,Pose-Driven Deep Convolutional Model for Person Re-identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+1d0dcb458aa4d30b51f7c74b159be687f39120a0,Pose-Driven Deep Convolutional Model for Person Re-identification,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
1d5aad4f7fae6d414ffb212cec1f7ac876de48bf,Face retriever: Pre-filtering the gallery via deep neural net,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
1db23a0547700ca233aef9cfae2081cd8c5a04d7,Comparative study and evaluation of various data classification techniques in data mining,Raipur Institute of Technology,Raipur Institute of Technology,"Raipur Institute of Technology, NH53, Raipur, Chhattisgarh, 492101, India",21.22622430,81.80136640,edu,
1db23a0547700ca233aef9cfae2081cd8c5a04d7,Comparative study and evaluation of various data classification techniques in data mining,Raipur Institute of Technology,Raipur Institute of Technology,"Raipur Institute of Technology, NH53, Raipur, Chhattisgarh, 492101, India",21.22622430,81.80136640,edu,
+1d93f7de9f6d2daa77d844dd928aaa1e699ed312,Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+1dfa8cce7b8dfd4b954d3fd90bef7bf569c87fb8,Robust Object Tracking in Crowd Dynamic Scenes Using Explicit Stereo Depth,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+1dfa8cce7b8dfd4b954d3fd90bef7bf569c87fb8,Robust Object Tracking in Crowd Dynamic Scenes Using Explicit Stereo Depth,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
+1dea4f56c04d12abbc9e1ed7c48c7ccc09e7f5bb,How magic changes our expectations about autism.,Cardiff University,Cardiff University,"Cardiff University, Park Place, Castle, Cardiff, Wales, CF, UK",51.48799610,-3.17969747,edu,
1d97735bb0f0434dde552a96e1844b064af08f62,Weber binary pattern and Weber ternary pattern for illumination-robust face recognition,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+1d81fe4a386a7d96b256eac41b99604cd132e019,Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1d630cc482f7a261738eb8b3b2021cf27c38370e,Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+1d630cc482f7a261738eb8b3b2021cf27c38370e,Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+1d8c720c95096981edcdfe57941123dca515eb34,Video-Based Person Re-identification by Deep Feature Guided Pooling,Beijing University of Technology,Beijing University of Technology,"北京工业大学, 银杏大道, 大郊亭村, 朝阳区 / Chaoyang, 北京市, 3208, 中国",39.87391435,116.47722285,edu,
+1d8c720c95096981edcdfe57941123dca515eb34,Video-Based Person Re-identification by Deep Feature Guided Pooling,University of Texas at San Antonio,University of Texas at San Antonio,"UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA",29.58333105,-98.61944505,edu,
+1dcf08c37fe2e8e78d3f1857547a965a0ac29526,2D ear classification based on unsupervised clustering,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+1d730a452a5c03cc23f90d4fde71c08864f31c35,Using Machine Learning for Identification of Art Paintings,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1d730a452a5c03cc23f90d4fde71c08864f31c35,Using Machine Learning for Identification of Art Paintings,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1ddacefa549de21f734f43016115ce7d54ab3d94,Supervised hashing with latent factor models,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+1ddacefa549de21f734f43016115ce7d54ab3d94,Supervised hashing with latent factor models,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+1ddacefa549de21f734f43016115ce7d54ab3d94,Supervised hashing with latent factor models,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+1ddacefa549de21f734f43016115ce7d54ab3d94,Supervised hashing with latent factor models,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+1d9b6745c0fd793db6dda8975b498ca517961d25,Visual Reasoning with Natural Language,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+1df84bf495d15569258513f229325d922b91e045,Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+1df84bf495d15569258513f229325d922b91e045,Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+1df84bf495d15569258513f229325d922b91e045,Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
1dacc2f4890431d867a038fd81c111d639cf4d7e,Using social outcomes to inform decision-making in schizophrenia: Relationships with symptoms and functioning.,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+1d911007a6f2832e006773f247fad1f729d1c6ae,Parametric T-Spline Face Morphable Model for Detailed Fitting in Shape Subspace,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
1de690714f143a8eb0d6be35d98390257a3f4a47,Face detection using spectral histograms and SVMs,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+1d5f22e73aa0d8115af0be61fc8832de501f4a1b,Comparison of 3D Scanning Versus 2D Photography for the Identification of Facial Soft-Tissue Landmarks,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+1de800d988f32380c54e430636ebf8913eadcc98,Predicting Images using Convolutional Networks: Visual Scene Understanding with Pixel Maps,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
1d7df3df839a6aa8f5392310d46b2a89080a3c25,Large-Margin Softmax Loss for Convolutional Neural Networks,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
1d7df3df839a6aa8f5392310d46b2a89080a3c25,Large-Margin Softmax Loss for Convolutional Neural Networks,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
1d6c09019149be2dc84b0c067595f782a5d17316,Encoding Video and Label Priors for Multi-label Video Classification on YouTube-8M dataset,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
1d6c09019149be2dc84b0c067595f782a5d17316,Encoding Video and Label Priors for Multi-label Video Classification on YouTube-8M dataset,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
1d6c09019149be2dc84b0c067595f782a5d17316,Encoding Video and Label Priors for Multi-label Video Classification on YouTube-8M dataset,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
1d6c09019149be2dc84b0c067595f782a5d17316,Encoding Video and Label Priors for Multi-label Video Classification on YouTube-8M dataset,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+719969807953d7ea8bda0397b1aadbaa6e205718,Automatic Dataset Augmentation,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+719969807953d7ea8bda0397b1aadbaa6e205718,Automatic Dataset Augmentation,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+71b973c87965e4086e75fd2379dd1bd8e3f8231e,Progressive Attention Networks for Visual Attribute Prediction,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
71b07c537a9e188b850192131bfe31ef206a39a0,300 Faces In-The-Wild Challenge: database and results,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
71b07c537a9e188b850192131bfe31ef206a39a0,300 Faces In-The-Wild Challenge: database and results,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
71b07c537a9e188b850192131bfe31ef206a39a0,300 Faces In-The-Wild Challenge: database and results,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+7180cb0c2773be3c15cc2737fed0fe19b08e1538,Mapping the emotional face. How individual face parts contribute to successful emotion recognition,Bielefeld University,Bielefeld University,"Fachhochschule Bielefeld FB Gestaltung, 3, Lampingstraße, Mitte, Bielefeld, Regierungsbezirk Detmold, Nordrhein-Westfalen, 33615, Deutschland",52.02804210,8.51148270,edu,
+7180cb0c2773be3c15cc2737fed0fe19b08e1538,Mapping the emotional face. How individual face parts contribute to successful emotion recognition,Bielefeld University,Bielefeld University,"Fachhochschule Bielefeld FB Gestaltung, 3, Lampingstraße, Mitte, Bielefeld, Regierungsbezirk Detmold, Nordrhein-Westfalen, 33615, Deutschland",52.02804210,8.51148270,edu,
+71899cbc5b4b25b2e834919f58d7620484d7e848,Predicting Geo-informative Attributes in Large-Scale Image Collections Using Convolutional Neural Networks,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
7142ac9e4d5498037aeb0f459f278fd28dae8048,Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
71f36c8e17a5c080fab31fce1ffea9551fc49e47,Predicting Failures of Vision Systems,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+71559cae0bc89398e75a2f24674d61cb51909390,Relighting Humans : Occlusion-Aware Inverse Rendering for Full-Body Human Images,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+71559cae0bc89398e75a2f24674d61cb51909390,Relighting Humans : Occlusion-Aware Inverse Rendering for Full-Body Human Images,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
7117ed0be436c0291bc6fb6ea6db18de74e2464a,Spatial Transformations,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+71797806fb9685a9a743c84c9e859948f7c6a77b,Learning to Describe Differences Between Pairs of Similar Images,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+71bf455415f283dc70a2f0343fa8387acbf00fb2,Multimodal Generative Models for Scalable Weakly-Supervised Learning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+71bf455415f283dc70a2f0343fa8387acbf00fb2,Multimodal Generative Models for Scalable Weakly-Supervised Learning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+71644fab2275cfd6a8f770a26aba4e6228e85dec,Multi-View Discriminant Analysis,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
71e6a46b32a8163c9eda69e1badcee6348f1f56a,Visually Interpreting Names as Demographic Attributes by Exploiting Click-Through Data,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
713594c18978b965be87651bb553c28f8501df0a,Fast Proximal Linearized Alternating Direction Method of Multiplier with Parallel Splitting,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
713594c18978b965be87651bb553c28f8501df0a,Fast Proximal Linearized Alternating Direction Method of Multiplier with Parallel Splitting,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+714a420173f328999c3b81fb70ce85be925b725f,Accelerating Dynamic Programs via Nested Benders Decomposition with Application to Multi-Person Pose Estimation,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
718824256b4461d62d192ab9399cfc477d3660b4,Selecting Training Data for Cross-Corpus Speech Emotion Recognition: Prototypicality vs. Generalization,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+719b741280607f258707d102feeb53dacf00ff8b,RAID: a relation-augmented image descriptor,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+719b741280607f258707d102feeb53dacf00ff8b,RAID: a relation-augmented image descriptor,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
718d3137adba9e3078fa1f698020b666449f3336,Accuracy Based Feature Ranking Metric for Multi-Label Text Classification,University of Gujrat,University of Gujrat,"University of Gujrat, University Road, Chandhar, Gujrāt District, پنجاب, 50700, پاکستان",32.63744845,74.16174558,edu,
718d3137adba9e3078fa1f698020b666449f3336,Accuracy Based Feature Ranking Metric for Multi-Label Text Classification,University of Gujrat,University of Gujrat,"University of Gujrat, University Road, Chandhar, Gujrāt District, پنجاب, 50700, پاکستان",32.63744845,74.16174558,edu,
+71354f47df241ad2e8b6c065f89f1c5afe077530,Eyemotion: Classifying facial expressions in VR using eye-tracking cameras,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
716d6c2eb8a0d8089baf2087ce9fcd668cd0d4c0,Pose-Robust 3D Facial Landmark Estimation from a Single 2D Image,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
7143518f847b0ec57a0ff80e0304c89d7e924d9a,Speeding-Up Age Estimation in Intelligent Demographics System via Network Optimization,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
7143518f847b0ec57a0ff80e0304c89d7e924d9a,Speeding-Up Age Estimation in Intelligent Demographics System via Network Optimization,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+71de9b3b8f482863d544da0f26ac2876b4fc210a,Who Are Raising Their Hands ? Hand-Raiser Seeking Based on Object Detection and Pose Estimation,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+71912976a7a4a5321b7e7ea20163fe3928cc5b71,Predicting When Saliency Maps are Accurate and Eye Fixations Consistent,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+71912976a7a4a5321b7e7ea20163fe3928cc5b71,Predicting When Saliency Maps are Accurate and Eye Fixations Consistent,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
713db3874b77212492d75fb100a345949f3d3235,Deep Semantic Face Deblurring,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+7150323712cb700a68e7365a9c627b55c2c262dc,SlideNet: Fast and Accurate Slide Quality Assessment Based on Deep Neural Networks,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+71969ee27916d545c63fe852946dd6dcc015d1a8,Who are the Devils Wearing Prada in New York City?,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+71969ee27916d545c63fe852946dd6dcc015d1a8,Who are the Devils Wearing Prada in New York City?,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+71969ee27916d545c63fe852946dd6dcc015d1a8,Who are the Devils Wearing Prada in New York City?,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+71969ee27916d545c63fe852946dd6dcc015d1a8,Who are the Devils Wearing Prada in New York City?,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+71969ee27916d545c63fe852946dd6dcc015d1a8,Who are the Devils Wearing Prada in New York City?,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
715b69575dadd7804b4f8ccb419a3ad8b7b7ca89,Testing Separability and Independence of Perceptual Dimensions with General Recognition Theory: A Tutorial and New R Package (grtools),Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
715b69575dadd7804b4f8ccb419a3ad8b7b7ca89,Testing Separability and Independence of Perceptual Dimensions with General Recognition Theory: A Tutorial and New R Package (grtools),Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
+715c7187b27b452424379254f5dc55909913b339,The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives,"University of Colorado, Boulder","University of Colorado, Boulder","Naropa University, Arapahoe Avenue, The Hill, Boulder, Boulder County, Colorado, 80309, USA",40.01407945,-105.26695944,edu,
+715c7187b27b452424379254f5dc55909913b339,The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+71167cf519940a7373adc221401c396198763ab0,"Scenes-Objects-Actions: A Multi-task, Multi-label Video Dataset",Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
71e56f2aebeb3c4bb3687b104815e09bb4364102,Video Co-segmentation for Meaningful Action Extraction,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+710c30c6c05ad1c9c0858f42364e9ca3f8e70bb4,"Classification of Land Use on Sand-Dune Topography by Object-Based Analysis, Digital Photogrammetry, and GIS Analysis in the Horqin Sandy Land, China",University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+710c30c6c05ad1c9c0858f42364e9ca3f8e70bb4,"Classification of Land Use on Sand-Dune Topography by Object-Based Analysis, Digital Photogrammetry, and GIS Analysis in the Horqin Sandy Land, China",Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+710c30c6c05ad1c9c0858f42364e9ca3f8e70bb4,"Classification of Land Use on Sand-Dune Topography by Object-Based Analysis, Digital Photogrammetry, and GIS Analysis in the Horqin Sandy Land, China",University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+7127f9e9a51236f213c5b7805be8714a3bcbfc28,Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+71b038958df0b7855fc7b8b8e7dcde8537a7c1ad,Kernel Methods for Unsupervised Domain Adaptation by Boqing Gong,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+71ed20748c919cd261024b146992ced4c9c2157b,Learning Semantic Patterns with Discriminant Localized Binary Projections,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+71ed20748c919cd261024b146992ced4c9c2157b,Learning Semantic Patterns with Discriminant Localized Binary Projections,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+71ed20748c919cd261024b146992ced4c9c2157b,Learning Semantic Patterns with Discriminant Localized Binary Projections,Beckman Institute,Beckman Institute,"Beckman Institute, The Presidents' Walk, Urbana, Champaign County, Illinois, 61801-2341, USA",40.11571585,-88.22750772,edu,
+71f9bed14188d861f248fb426a26a3a0b400843a,Robot-Centric Activity Prediction from First-Person Videos: What Will They Do to Me',California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+71f9bed14188d861f248fb426a26a3a0b400843a,Robot-Centric Activity Prediction from First-Person Videos: What Will They Do to Me',University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+71392858b6af5b50b1cd7c740560697101f60e46,Classifiers Combination for Improved Motion Segmentation,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+71cbe1b52e2fdb8fa8a8278eb590f8065d3e7fcb,’ Actions dans des Vidéos Réalistes Structured Models for Action Recognition in Real-world Videos,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+719e58a8b256cdcc88f7980e4798fe8e6aa1a808,Confidence Intervals for Tracking Performance Scores,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+767936728b07238bbf38661fc3c2000d0c17b598,An Own-Age Bias in Recognizing Faces with Horizontal Information,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+76f7664511917bb575081ad3555e383de54562f1,'Lighter' Can Still Be Dark: Modeling Comparative Color Descriptions,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+76f7664511917bb575081ad3555e383de54562f1,'Lighter' Can Still Be Dark: Modeling Comparative Color Descriptions,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+760a8a46089ca9fc7d06ea44b207b948569237ba,Learning a Deep Embedding Model for Zero-Shot Learning,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+76b6577f47d6782bf75aca04e361a7b7381b4a84,Measuring and Modifying the Intrinsic Memorability of Images,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+76b5ce50ab603a6d175fd21f4b1404dff3c897c2,Adult Image and Video Recognition by a Deep Multicontext Network and Fine-to-Coarse Strategy,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+76b5ce50ab603a6d175fd21f4b1404dff3c897c2,Adult Image and Video Recognition by a Deep Multicontext Network and Fine-to-Coarse Strategy,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+76a2846d17521149a118fd54083f8a51646e2804,Context-aware Deep Feature Compression for High-speed Visual Tracking,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+76a2846d17521149a118fd54083f8a51646e2804,Context-aware Deep Feature Compression for High-speed Visual Tracking,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+76a2846d17521149a118fd54083f8a51646e2804,Context-aware Deep Feature Compression for High-speed Visual Tracking,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
7643861bb492bf303b25d0306462f8fb7dc29878,Speeding up 2D-warping for pose-invariant face recognition,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+76229d9e68bca10f3876f351856d6911857be827,Robust features for facial action recognition,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+76229d9e68bca10f3876f351856d6911857be827,Robust features for facial action recognition,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+76cd878c37bcdb8b3ae678e96c9b7700184ddb46,Athlete Pose Estimation from Monocular TV Sports Footage,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+76cd878c37bcdb8b3ae678e96c9b7700184ddb46,Athlete Pose Estimation from Monocular TV Sports Footage,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+76cd878c37bcdb8b3ae678e96c9b7700184ddb46,Athlete Pose Estimation from Monocular TV Sports Footage,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+76b227facbcd75cda35cb5bb8063d8d5cfcec4d0,Expression Recognition Using the Periocular Region: A Feasibility Study,Halmstad University,Halmstad University,"Högskolan i Halmstad, 3, Kristian IV:s väg, Larsfrid, Nyhem, Halmstad, Hallands län, Götaland, 301 18, Sverige",56.66340325,12.87929727,edu,
+76b227facbcd75cda35cb5bb8063d8d5cfcec4d0,Expression Recognition Using the Periocular Region: A Feasibility Study,Halmstad University,Halmstad University,"Högskolan i Halmstad, 3, Kristian IV:s väg, Larsfrid, Nyhem, Halmstad, Hallands län, Götaland, 301 18, Sverige",56.66340325,12.87929727,edu,
+76ad6daa899a8657c9c17480e5fc440fda53acec,A Multi-Task Deep Network for Person Re-Identification,University of Dundee,University of Dundee,"University of Dundee, Park Wynd, Law, Dundee, Dundee City, Scotland, DD1 4HN, UK",56.45796755,-2.98214831,edu,
+7697c8a0eea8b4f7e9b5c3378879cf34ba6d79b3,On Decomposing an Unseen 3D Face into Neutral Face and Expression Deformations,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
76ce3d35d9370f0e2e27cfd29ea0941f1462895f,Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+76616a2709c03ade176db31fa99c7c61970eba28,Learning Heterogeneous Dictionary Pair with Feature Projection Matrix for Pedestrian Video Retrieval via Single Query Image,Wuhan University of Technology,Wuhan University of Technology,"武汉理工大学-余家头校区, 交通二路, 杨园街道, 武昌区 (Wuchang), 武汉市, 湖北省, 430062, 中国",30.60903415,114.35142840,edu,
+76616a2709c03ade176db31fa99c7c61970eba28,Learning Heterogeneous Dictionary Pair with Feature Projection Matrix for Pedestrian Video Retrieval via Single Query Image,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+76616a2709c03ade176db31fa99c7c61970eba28,Learning Heterogeneous Dictionary Pair with Feature Projection Matrix for Pedestrian Video Retrieval via Single Query Image,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+76616a2709c03ade176db31fa99c7c61970eba28,Learning Heterogeneous Dictionary Pair with Feature Projection Matrix for Pedestrian Video Retrieval via Single Query Image,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
768c332650a44dee02f3d1d2be1debfa90a3946c,Bayesian face recognition using support vector machine and face clustering,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
769461ff717d987482b28b32b1e2a6e46570e3ff,MIC-TJU in MediaEval 2017 Emotional Impact of Movies Task,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+7605857f551d128e7c3babfc019950250f81bca9,Reciprocal Attention Fusion for Visual Question Answering,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+765094fa3cd745bed29c20dad92dbed8c4cfebea,Applying Biometric Principles to Avatar Recognition,University of Calgary,University of Calgary,"University of Calgary, Service Tunnel, University Heights, Calgary, Alberta, T2N 1N7, Canada",51.07840380,-114.12870770,edu,
+765094fa3cd745bed29c20dad92dbed8c4cfebea,Applying Biometric Principles to Avatar Recognition,University of Louisville,University of Louisville,"University of Louisville, South Brook Street, Louisville, Jefferson County, Kentucky, 40208, USA",38.21675650,-85.75725023,edu,
+76e48cd3b4b25cdb6c094ff660ed8e43be1e2f34,What-and-Where to Match: Deep Spatially Multiplicative Integration Networks for Person Re-identification,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+76d955e83b1d64de95f37336322cbbca0019e3b2,Robust and Efficient Subspace Segmentation via Least Squares Regression,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+76d955e83b1d64de95f37336322cbbca0019e3b2,Robust and Efficient Subspace Segmentation via Least Squares Regression,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+76d955e83b1d64de95f37336322cbbca0019e3b2,Robust and Efficient Subspace Segmentation via Least Squares Regression,Hefei University of Technology,Hefei University of Technology,"合肥工业大学（屯溪路校区）, 193号, 南一环路, 航运南村, 包公街道, 合肥市区, 合肥市, 安徽省, 230009, 中国",31.84691800,117.29053367,edu,
+76d955e83b1d64de95f37336322cbbca0019e3b2,Robust and Efficient Subspace Segmentation via Least Squares Regression,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+765263556ce90c5c0d86d3e6d8a21e04a307b60d,Comparing Visual Feature Coding for Learning Disjoint Camera Dependencies,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
764882e6779fbee29c3d87e00302befc52d2ea8d,Deep Approximately Orthogonal Nonnegative Matrix Factorization for Clustering,Guangdong University of Technology,Guangdong University of Technology,"广东工业大学, 东风东路, 黄花岗街道, 越秀区 (Yuexiu), 广州市, 广东省, 510080, 中国",23.13538360,113.29470496,edu,
764882e6779fbee29c3d87e00302befc52d2ea8d,Deep Approximately Orthogonal Nonnegative Matrix Factorization for Clustering,Guangdong University of Technology,Guangdong University of Technology,"广东工业大学, 东风东路, 黄花岗街道, 越秀区 (Yuexiu), 广州市, 广东省, 510080, 中国",23.13538360,113.29470496,edu,
764882e6779fbee29c3d87e00302befc52d2ea8d,Deep Approximately Orthogonal Nonnegative Matrix Factorization for Clustering,Guangdong University of Technology,Guangdong University of Technology,"广东工业大学, 东风东路, 黄花岗街道, 越秀区 (Yuexiu), 广州市, 广东省, 510080, 中国",23.13538360,113.29470496,edu,
76d939f73a327bf1087d91daa6a7824681d76ea1,A Thermal Facial Emotion Database and Its Analysis,Japan Advanced Institute of Science and Technology,Japan Advanced Institute of Science and Technology,"JAIST (北陸先端科学技術大学院大学), 石川県道55号小松辰口線, Ishikawa Science Park, 能美市, 石川県, 中部地方, 923-1206, 日本",36.44429490,136.59285870,edu,
+7673d5fa77770629d040fae54c214c60ba69574c,Moving Object Detection from Mobile Platforms Using Stereo Data Registration,University of the Basque Country,University of the Basque Country,"Euskal Herriko Unibertsitatea, Ibaeta Campusa, Paseo Arriola pasealekua, Ibaeta, Donostia/San Sebastián, Donostialdea, Gipuzkoa, Euskadi, 20008, España",43.30927695,-2.01066785,edu,
+76fd59062e563353097694d38855e94efbd53143,3D Face Reconstruction from Light Field Images: A Model-Free Approach,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+76fd59062e563353097694d38855e94efbd53143,3D Face Reconstruction from Light Field Images: A Model-Free Approach,Hunan University,Hunan University,"Yejin University for Employees, 冶金西路, 和平乡, 珠晖区, 衡阳市 / Hengyang, 湖南省, 中国",26.88111275,112.62850666,edu,
+766039c203f76009c5efabe7b24914cc66fe117f,"""BAM!"" Depth-Based Body Analysis in Critical Care",Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+76615d7bc69ef0e50338a8c3e59c75d361ef0db4,Learning a compact latent representation of the Bag-of-Parts model,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+7688187b1ce5cbb1413d075f435ff294ba09cadc,Robust Precise Eye Location by Adaboost and SVM Techniques,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
+1c9a61c8ec255d033201fb9b394b283a6b6acacc,Structured Feature Learning for Pose Estimation,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+1cf53b650c4a3e212bd6f25e3c9fe8c757862a7d,Human Pose Estimation via Convolutional Part Heatmap Regression,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
+1cc902dc999103c8ed27559affa5cdaed6fc2c38,Analysing comparative soft biometrics from crowdsourced annotations,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+1c6e067098fa86ee3f96365f28669b06f9ce0c7a,Object Detection from Video Tubelets with Convolutional Neural Networks,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+1c05dc0f73f424561c488a282c711827047459c4,Supervised trace lasso for robust face recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+1c6690ab404b23d5026dd3ad0c7a49ce2875c1b3,Anchors: High-Precision Model-Agnostic Explanations,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+1c6690ab404b23d5026dd3ad0c7a49ce2875c1b3,Anchors: High-Precision Model-Agnostic Explanations,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+1c6690ab404b23d5026dd3ad0c7a49ce2875c1b3,Anchors: High-Precision Model-Agnostic Explanations,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
1c9efb6c895917174ac6ccc3bae191152f90c625,Unifying Identification and Context Learning for Person Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1c2724243b27a18a2302f12dea79d9a1d4460e35,Fisher+Kernel criterion for discriminant analysis,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
1c2724243b27a18a2302f12dea79d9a1d4460e35,Fisher+Kernel criterion for discriminant analysis,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1c2724243b27a18a2302f12dea79d9a1d4460e35,Fisher+Kernel criterion for discriminant analysis,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
1ca8c09abb73a02519d8db77e4fe107acfc589b6,Automatic Understanding of Image and Video Advertisements,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+1cf4abbd052c94e63557b7922f7a5fc7e22c6e3f,Multimodal Similarity-Preserving Hashing,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
1c4ceae745fe812d8251fda7aad03210448ae25e,Optimization of Color Conversion for Face Recognition,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
1c4ceae745fe812d8251fda7aad03210448ae25e,Optimization of Color Conversion for Face Recognition,Virginia Polytechnic Institute and State University,Virginia Polytechnic Institute and State University,"Virginia Polytechnic Institute and State University, Duck Pond Drive, Blacksburg, Montgomery County, Virginia, 24061-9517, USA",37.21872455,-80.42542519,edu,
+1c1aa29b709370f78cc485b14c18b89a53229b62,Topological Data Mapping for Improved Generalization Capabilities using Counter Propagation Networks,Akita Prefectural University,Akita Prefectural University,"秋田県立大学, 秋田天王線, 潟上市, 秋田県, 東北地方, 011-0946, 日本",39.80114990,140.04591160,edu,
+1c408790a7bc5cc8b0c2e23668ad326d0ccbebd4,Automatic detection of pain intensity,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1c408790a7bc5cc8b0c2e23668ad326d0ccbebd4,Automatic detection of pain intensity,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
1cee993dc42626caf5dbc26c0a7790ca6571d01a,Optimal illumination for image and video relighting,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+1c71e653f86b06eb7d5b1d92694f34e6f57173de,Enhanced Attacks on Defensively Distilled Deep Neural Networks,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
1c147261f5ab1b8ee0a54021a3168fa191096df8,Face Recognition across Time Lapse Using Convolutional Neural Networks,George Mason University,George Mason University,"George Mason University, Aquia Creek Lane, Country Club View, Blue Oaks, Fairfax County, Virginia, 22030-9998, USA",38.83133325,-77.30798839,edu,
1c17450c4d616e1e1eece248c42eba4f87de9e0d,Automatic Age Estimation from Face Images via Deep Ranking,Institute of Information Science,Institute of Information Science,"資訊科學研究所, 數理大道, 中研里, 南港子, 南港區, 臺北市, 11574, 臺灣",25.04107280,121.61475620,edu,
+1c686359a30e68183d1b23e069c56a7c0b1fdae3,3D Human Pose Estimation from Monocular Images with Deep Convolutional Neural Network,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
1c41965c5e1f97b1504c1bdde8037b5e0417da5e,Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+1c1f21bf136fe2eec412e5f70fd918c27c5ccb0a,Object Detection and Viewpoint Estimation with Auto-masking Neural Network,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+1c1f21bf136fe2eec412e5f70fd918c27c5ccb0a,Object Detection and Viewpoint Estimation with Auto-masking Neural Network,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
1cbd3f96524ca2258fd2d5c504c7ea8da7fb1d16,Fusion of Audio-visual Features using Hierarchical Classifier Systems for the Recognition of Affective States and the State of Depression,Ulm University,Ulm University,"HNU, John-F.-Kennedy-Straße, Vorfeld, Wiley, Neu-Ulm, Landkreis Neu-Ulm, Schwaben, Bayern, 89231, Deutschland",48.38044335,10.01010115,edu,
1cad5d682393ffbb00fd26231532d36132582bb4,"ZHENHENG YANG, JIYANG GAO, RAM NEVATIA: SPATIO-TEMPORAL ACTION DETECTION WITH CASCADE PROPOSAL AND LOCATION ANTICIPATION1 Spatio-Temporal Action Detection with Cascade Proposal and Location Anticipation",University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+1c2802c2199b6d15ecefe7ba0c39bfe44363de38,Personalizing Human Video Pose Estimation,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
+1c2802c2199b6d15ecefe7ba0c39bfe44363de38,Personalizing Human Video Pose Estimation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1c2802c2199b6d15ecefe7ba0c39bfe44363de38,Personalizing Human Video Pose Estimation,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
+1c2802c2199b6d15ecefe7ba0c39bfe44363de38,Personalizing Human Video Pose Estimation,University of Leeds,University of Leeds,"University of Leeds, Inner Ring Road, Woodhouse, Leeds, Yorkshire and the Humber, England, LS2 9NS, UK",53.80387185,-1.55245712,edu,
+1c2802c2199b6d15ecefe7ba0c39bfe44363de38,Personalizing Human Video Pose Estimation,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1c42f8ab39e22225ffd3222baeba4863435220a0,Differentiable Learning-to-Normalize via Switchable Normalization,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1c1a98df3d0d5e2034ea723994bdc85af45934db,Guided Unsupervised Learning of Mode Specific Models for Facial Point Detection in the Wild,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
1ca815327e62c70f4ee619a836e05183ef629567,Global supervised descent method,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+1c8d585fb7e82abf43f45014494018a843774d2b,Consistent Iterative Multi-view Transfer Learning for Person Re-identification,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+1c8d585fb7e82abf43f45014494018a843774d2b,Consistent Iterative Multi-view Transfer Learning for Person Re-identification,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+1c8d585fb7e82abf43f45014494018a843774d2b,Consistent Iterative Multi-view Transfer Learning for Person Re-identification,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+1c028833faf11dd565c749741eb97ce811b490de,Person re-identification by probabilistic relative distance comparison,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+1c028833faf11dd565c749741eb97ce811b490de,Person re-identification by probabilistic relative distance comparison,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+1c7a050394371bcb064868dfe681ff4c29ce2101,Expressive Models and Comprehensive Benchmark for 2D Human Pose Estimation,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+1c7a050394371bcb064868dfe681ff4c29ce2101,Expressive Models and Comprehensive Benchmark for 2D Human Pose Estimation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1cfca6b71b0ead87bbb79a8614ddec3a10100faa,Are screening methods useful in feature selection? An empirical study,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+1c2db743b37306e50c4234da53510c113f50f9ff,Exploring Weak Stabilization for Motion Feature Extraction,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+1c2db743b37306e50c4234da53510c113f50f9ff,Exploring Weak Stabilization for Motion Feature Extraction,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+1caac27548cc7f98380e4e95ccbc8e6e164489c8,Human Pose Estimation Using Deep Consensus Voting,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
+1cea72fb523432d80b77224433d57828da44828c,Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior,National Institutes of Health,National Institutes of Health,"NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA",39.00041165,-77.10327775,edu,
+1cea72fb523432d80b77224433d57828da44828c,Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+1cea72fb523432d80b77224433d57828da44828c,Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+1cea72fb523432d80b77224433d57828da44828c,Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+1cea72fb523432d80b77224433d57828da44828c,Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+1cea72fb523432d80b77224433d57828da44828c,Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+1c99e412666d63e46e1c6606841837d3c18f48e6,Unsupervised object learning from dense equivariant image labelling,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1cd3250280a0703ba57bbc357287a7213f901b7e,Learning spatio-temporal models of facial expressions,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
1c530de1a94ac70bf9086e39af1712ea8d2d2781,Sparsity Conditional Energy Label Distribution Learning for Age Estimation,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
82f8652c2059187b944ce65e87bacb6b765521f6,Discriminative Object Categorization with External Semantic Knowledge,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+823db29d4c2a79e309ad2b394a4aaa83d9e15284,Online Multi-Object Tracking by Quadratic Pseudo-Boolean Optimization,"National University of Defense Technology, China","National University of Defence Technology, Changsha 410000, China","国防科学技术大学, 三一大道, 开福区, 开福区 (Kaifu), 长沙市 / Changsha, 湖南省, 410073, 中国",28.22902090,112.99483204,edu,
+823db29d4c2a79e309ad2b394a4aaa83d9e15284,Online Multi-Object Tracking by Quadratic Pseudo-Boolean Optimization,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+82d446206a3e9afba7e5b8c112227df681ef422a,Super-resolution from internet-scale scene matching,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+82d446206a3e9afba7e5b8c112227df681ef422a,Super-resolution from internet-scale scene matching,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+82729f984c514bd0a5157c28b75ff0236d609384,Deep Feature Flow for Video Recognition,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+82729f984c514bd0a5157c28b75ff0236d609384,Deep Feature Flow for Video Recognition,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+828cfe547a2c9719dea68698dfa168b0bdd22aed,Max-margin transforms for visual domain adaptation,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+8233c1d79ddad9d969b995d4ef2c6f8ea9acc646,Hamiltonian Streamline Guided Feature Extraction with Applications to Face Detection,University at Buffalo,State University of New York at Buffalo,"Buffalo, NY 14260, USA",43.00080930,-78.78896970,edu,
+8233c1d79ddad9d969b995d4ef2c6f8ea9acc646,Hamiltonian Streamline Guided Feature Extraction with Applications to Face Detection,University at Buffalo,State University of New York at Buffalo,"Buffalo, NY 14260, USA",43.00080930,-78.78896970,edu,
824d1db06e1c25f7681e46199fd02cb5fc343784,Representing Relative Visual Attributes with a Reference-Point-Based Decision Model,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
824d1db06e1c25f7681e46199fd02cb5fc343784,Representing Relative Visual Attributes with a Reference-Point-Based Decision Model,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
82ccd62f70e669ec770daf11d9611cab0a13047e,Sparse Variation Pattern for Texture Classification,Tafresh University,Tafresh University,"دانشگاه تفرش, پاسداران, خرازان, بخش مرکزی, شهرستان تفرش, استان مرکزی, ایران",34.68092465,50.05341352,edu,
82ccd62f70e669ec770daf11d9611cab0a13047e,Sparse Variation Pattern for Texture Classification,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
82ccd62f70e669ec770daf11d9611cab0a13047e,Sparse Variation Pattern for Texture Classification,Azad University,Azad University,"پل دانشگاه آزاد, باراجین, پونک ۳, قزوین, بخش مرکزی, شهرستان قزوین, استان قزوین, ایران",36.31734320,50.03672860,edu,
+82d9296eb2edc12f6cb830fba78d5bf9469a94b9,Pedestrian Detection Based on Sparse and Low-Rank Matrix Decomposition,Jiangsu University,Jiangsu University,"江苏大学, 301, 学府路, 京口区, 象山街道, 京口区 (Jingkou), 镇江市 / Zhenjiang, 江苏省, 212013, 中国",32.20302965,119.50968362,edu,
+829ddf932d7164ebc915095a4a94471049825410,Towards Around-Device Interaction using Corneal Imaging,Coburg University,Coburg University,"Hochschule für angewandte Wissenschaften Coburg, 2, Friedrich-Streib-Straße, Callenberg, Coburg, Oberfranken, Bayern, 96450, Deutschland",50.26506145,10.95196483,edu,
+829ddf932d7164ebc915095a4a94471049825410,Towards Around-Device Interaction using Corneal Imaging,Coburg University,Coburg University,"Hochschule für angewandte Wissenschaften Coburg, 2, Friedrich-Streib-Straße, Callenberg, Coburg, Oberfranken, Bayern, 96450, Deutschland",50.26506145,10.95196483,edu,
+82766851c790a5225f3b932239e831e1b60f5ee7,Combining motion and appearance for gender classification from video sequences,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+826f9e286eb0c9165c04bc5811aa7793050c7666,Joint regularized nearest points for image set based face recognition,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+826f9e286eb0c9165c04bc5811aa7793050c7666,Joint regularized nearest points for image set based face recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+828a7b3122ebd5b8b0c617902bc04ac5a6c60240,"Show, Adapt and Tell: Adversarial Training of Cross-Domain Image Captioner",National Tsing Hua University,National Tsing Hua University,"國立清華大學, 101, 克恭橋, 光明里, 赤土崎, 東區, 新竹市, 30013, 臺灣",24.79254840,120.99511830,edu,
+828a7b3122ebd5b8b0c617902bc04ac5a6c60240,"Show, Adapt and Tell: Adversarial Training of Cross-Domain Image Captioner",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+82d82272b365028294662ede914caf64e73495fb,Real-time Driver Drowsiness Detection for Android Application Using Deep Neural Networks Techniques,Qatar University,Qatar University,"Qatar University, Roindabout 3, Al Tarfa (68), أم صلال, 24685, قطر",25.37461295,51.48980354,edu,
+82d82272b365028294662ede914caf64e73495fb,Real-time Driver Drowsiness Detection for Android Application Using Deep Neural Networks Techniques,State University of New Jersey,The State University of New Jersey,"Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA",40.51865195,-74.44099801,edu,
+826f1ac8ef16abd893062fdf5058a09881aed516,Identity-Preserving Face Recovery from Portraits,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+821864bf264f924ac7d63c02ad3fdfff3cefd990,Guide Me: Interacting with Deep Networks,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+823a47273e0e6101be67858f5c5f08e235f2d58a,Access to Awareness for Faces during Continuous Flash Suppression Is Not Modulated by Affective Knowledge.,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+823a47273e0e6101be67858f5c5f08e235f2d58a,Access to Awareness for Faces during Continuous Flash Suppression Is Not Modulated by Affective Knowledge.,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+82a7bdc2ca2ba706446fb1b1c8696e0d0d7cc8d0,AUTOMATIC DETECTION AND INTENSITY ESTIMATION OF SPONTANEOUS SMILES by,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+82a7bdc2ca2ba706446fb1b1c8696e0d0d7cc8d0,AUTOMATIC DETECTION AND INTENSITY ESTIMATION OF SPONTANEOUS SMILES by,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+822c7bfebcc456e3598304f69eb8f4a2aee46f02,Robust Degraded Face Recognition Using Enhanced Local Frequency Descriptor and Multi-scale Competition,Shanghai University,Shanghai University,"上海大学, 锦秋路, 大场镇, 宝山区 (Baoshan), 上海市, 201906, 中国",31.32235655,121.38400941,edu,
+820e4727827646c79a9a5d862c510d26be5356f1,"Gaze Behaviour , Motivational Factors , and Knowledge Sharing Completed Research Paper",Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
+820e4727827646c79a9a5d862c510d26be5356f1,"Gaze Behaviour , Motivational Factors , and Knowledge Sharing Completed Research Paper",Monash University,Monash University,"Monash University, Mile Lane, Parkville, City of Melbourne, Victoria, 3000, Australia",-37.78397455,144.95867433,edu,
82b43bc9213230af9db17322301cbdf81e2ce8cc,Attention-Set based Metric Learning for Video Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
82e66c4832386cafcec16b92ac88088ffd1a1bc9,OpenFace: A general-purpose face recognition library with mobile applications,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
82e66c4832386cafcec16b92ac88088ffd1a1bc9,OpenFace: A general-purpose face recognition library with mobile applications,Poznan University of Technology,Poznan University of Technology,"Dom Studencki nr 3, 3, Kórnicka, Święty Roch, Rataje, Poznań, wielkopolskie, 61-141, RP",52.40048370,16.95158083,edu,
+8241008f9d3d5e866f648eb454db2054202121ef,Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+8241008f9d3d5e866f648eb454db2054202121ef,Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+8241008f9d3d5e866f648eb454db2054202121ef,Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
82eb267b8e86be0b444e841b4b4ed4814b6f1942,Single Image 3D Interpreter Network,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
82eb267b8e86be0b444e841b4b4ed4814b6f1942,Single Image 3D Interpreter Network,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+823e57c126124254cf96c723fe1bace505271220,Dorsal stream: from algorithm to neuroscience,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+4996e64c24cef33d0f7e5a2b1c3baf00e51493e6,Deep Relative Distance Learning: Tell the Difference between Similar Vehicles,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
499f1d647d938235e9186d968b7bb2ab20f2726d,Face Recognition via Archetype Hull Ranking,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
499f1d647d938235e9186d968b7bb2ab20f2726d,Face Recognition via Archetype Hull Ranking,IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
+49ecf784afddf7d5cf31c90340eef9380c261f04,FACSCaps : Pose-Independent Facial Action Coding with Capsules,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+49ecf784afddf7d5cf31c90340eef9380c261f04,FACSCaps : Pose-Independent Facial Action Coding with Capsules,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4910c4d7eea372034339f21141550f6d7cb28665,Look Deeper into Depth: Monocular Depth Estimation with Semantic Booster and Attention-Driven Loss,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+4910c4d7eea372034339f21141550f6d7cb28665,Look Deeper into Depth: Monocular Depth Estimation with Semantic Booster and Attention-Driven Loss,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+49ac9738b551d0f8d9c64d5b6e8b08c69e3b0421,3D Pictorial Structures for Multiple View Articulated Pose Estimation,"KTH Royal Institute of Technology, Stockholm","KTH Royal Institute of Technology, Stockholm","KTH, Teknikringen, Lärkstaden, Norra Djurgården, Östermalms stadsdelsområde, Sthlm, Stockholm, Stockholms län, Svealand, 114 28, Sverige",59.34986645,18.07063213,edu,
+497d46649af7dab664cdb9d47242df6dc06b1a48,Integral Channel Features,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+497d46649af7dab664cdb9d47242df6dc06b1a48,Integral Channel Features,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
+495fa8f7d9d0e4d472c49de34a9d17343668f4a4,Automatic Event Detection for Signal-based Surveillance,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
+4990824c5ff6c993e0697e272026438c4a05c3d5,Innovative Sparse Representation Algorithms for Robust Face Recognition,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+4990824c5ff6c993e0697e272026438c4a05c3d5,Innovative Sparse Representation Algorithms for Robust Face Recognition,Curtin University,Curtin University,"Curtin University, Brand Drive, Waterford, Perth, Western Australia, 6102, Australia",-32.00686365,115.89691775,edu,
+49dcfbcb88139e4432cc0d3cfdd91af30f4d53dc,Multi-camera multi-object tracking by robust hough-based homography projections,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
49f70f707c2e030fe16059635df85c7625b5dc7e,Face recognition under illumination variations based on eight local directional patterns,Utah State University,Utah State University,"Utah State University, Champ Drive, Logan, Cache County, Utah, 84322, USA",41.74115040,-111.81223090,edu,
+4931562044a691fe41b638550b54a0a689674e83,Incorporating On-demand Stereo for Real Time Recognition,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+4934fd234db9a095e51d36e738e706886d1dfa0a,Robust Clustering as Ensembles of Affinity Relations,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+4934fd234db9a095e51d36e738e706886d1dfa0a,Robust Clustering as Ensembles of Affinity Relations,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+49512d11c468dc2fe3fe832d8c4dc8e0a01b0a4b,The Long-Short Story of Movie Description,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
49820ae612b3c0590a8a78a725f4f378cb605cd1,Evaluation of Smile Detection Methods with Images in Real-World Scenarios,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
-49e975a4c60d99bcc42c921d73f8d89ec7130916,Human and computer recognition of facial expressions of emotion.,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+4948c1791412cf13b770d922399c625527b51a6f,Face Recognition Techniques and Approaches: a Survey,"COMSATS Institute of Information Technology, Lahore",COMSATS Institute of Information Technology,"COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, بحریہ ٹاؤن, Lahore District, پنجاب, 54700, پاکستان",31.40063320,74.21372960,edu,
+49e975a4c60d99bcc42c921d73f8d89ec7130916,Human and computer recognition of facial expressions of emotion,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+4960ab1cef23e5ccd60173725ea280f462164a0e,Video Object Segmentation by Learning Location-Sensitive Embeddings,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+4960ab1cef23e5ccd60173725ea280f462164a0e,Video Object Segmentation by Learning Location-Sensitive Embeddings,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+4950ae0e837657b611113e219bf848f0c657dcf9,Efficient Unsupervised Learning for Localization and Detection in Object Categories,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+4950ae0e837657b611113e219bf848f0c657dcf9,Efficient Unsupervised Learning for Localization and Detection in Object Categories,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+49e541e0bbc7a082e5c952fc70716e66e5713080,Group expression intensity estimation in videos via Gaussian Processes,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
4934d44aa89b6d871eb6709dd1d1eebf16f3aaf1,A Deep Sum-Product Architecture for Robust Facial Attributes Analysis,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
4934d44aa89b6d871eb6709dd1d1eebf16f3aaf1,A Deep Sum-Product Architecture for Robust Facial Attributes Analysis,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
4934d44aa89b6d871eb6709dd1d1eebf16f3aaf1,A Deep Sum-Product Architecture for Robust Facial Attributes Analysis,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+49a2f3262958465c8cfd5a59bc0f9f4effd1936b,Global Semantic Consistency for Zero-Shot Learning,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+49a2f3262958465c8cfd5a59bc0f9f4effd1936b,Global Semantic Consistency for Zero-Shot Learning,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+49396502143e920f7208bfd27202d6fead39992f,Dense Semantic and Topological Correspondence of 3D Faces without Landmarks,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+49396502143e920f7208bfd27202d6fead39992f,Dense Semantic and Topological Correspondence of 3D Faces without Landmarks,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+49ead21ec51e7df53583ef5ade06606c8a75dfb8,Hallucinating Very Low-Resolution Unaligned and Noisy Face Images by Transformative Discriminative Autoencoders,Australian National University,Australian National University,"Canberra ACT 0200, Australia",-35.27769990,149.11852700,edu,
+497243ed80033921c3c82c278780381a7d9d783e,Think Visually: Question Answering through Virtual Imagery,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+49ae4afe91239a8259dc0c390179d47bc395beda,Saliency Based Opportunistic Search for Object Part Extraction and Labeling,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+495015d21c26eac9a6bd64c836ee3370283641ec,VisKE: Visual knowledge extraction and question answering by visual verification of relation phrases,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
499f2b005e960a145619305814a4e9aa6a1bba6a,Robust human face recognition based on locality preserving sparse over complete block approximation,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+49e2c1bae80e6b75233348102dc44671ee52b548,Age and gender recognition using informative features of various types,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
497bf2df484906e5430aa3045cf04a40c9225f94,Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems,Kyung Hee University,Kyung Hee University,"Kyung Hee Tae Kwon Do, Vons 2370 Truck Service Ramp, University City, San Diego, San Diego County, California, 92122, USA",32.85363330,-117.20352860,edu,
497bf2df484906e5430aa3045cf04a40c9225f94,Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems,Ajou University,Ajou University,"아주대학교, 성호대교, 이의동, 영통구, 수원시, 경기, 16499, 대한민국",37.28300030,127.04548469,edu,
492f41e800c52614c5519f830e72561db205e86c,A Deep Regression Architecture with Two-Stage Re-initialization for High Performance Facial Landmark Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
492f41e800c52614c5519f830e72561db205e86c,A Deep Regression Architecture with Two-Stage Re-initialization for High Performance Facial Landmark Detection,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
492f41e800c52614c5519f830e72561db205e86c,A Deep Regression Architecture with Two-Stage Re-initialization for High Performance Facial Landmark Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+4953da81a1a93ab3a30152d4403c5e8fa79edc09,Fast obstacle detection using targeted optical flow,Carleton University,Carleton University,"Carleton University, 1125, Colonel By Drive, Billings Bridge, Capital, Ottawa, Ontario, K1S 5B7, Canada",45.38608430,-75.69539267,edu,
+4953da81a1a93ab3a30152d4403c5e8fa79edc09,Fast obstacle detection using targeted optical flow,Carleton University,Carleton University,"Carleton University, 1125, Colonel By Drive, Billings Bridge, Capital, Ottawa, Ontario, K1S 5B7, Canada",45.38608430,-75.69539267,edu,
+49435aab7cdf259335725acc96691f755e436f55,A database for fine grained activity detection of cooking activities,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
493ec9e567c5587c4cbeb5f08ca47408ca2d6571,Combining graph embedding and sparse regression with structure low-rank representation for semi-supervised learning,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
49570b41bd9574bd9c600e24b269d945c645b7bd,A Framework for Performance Evaluation of Face Recognition Algorithms,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+49f01ad8e60882d0f3c450345251b6c6b499c3a2,Cryptic Emotions and the Emergence of a Metatheory of Mind in Popular Filmmaking,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+4946ba10a4d5a7d0a38372f23e6622bd347ae273,RONCHI AND PERONA: DESCRIBING COMMON HUMAN VISUAL ACTIONS IN IMAGES 1 Describing Common Human Visual Actions in Images,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+40883844c1ceab95cb92498a92bfdf45beaa288e,Improving Heterogeneous Face Recognition with Conditional Adversarial Networks,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+40b2652cf3bdee159dacb6e18c761003c31f4205,Database Learning: Toward a Database that Becomes Smarter Every Time,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+403ecc19291f21db6084db5c12f428e2af91ed3d,Semi-Supervised Classification Based on Mixture Graph,Southwest University,Southwest University,"西南大学, 天生路, 北碚区 (Beibei), 北碚区, 北碚区 (Beibei), 重庆市, 400711, 中国",29.82366295,106.42050016,edu,
+403ecc19291f21db6084db5c12f428e2af91ed3d,Semi-Supervised Classification Based on Mixture Graph,Jilin University,Jilin University,"吉林大学珠海校区, 丹桂路, 圣堂村, 金湾区, 珠海市, 广东省, 中国",22.05356500,113.39913285,edu,
40a74eea514b389b480d6fe8b359cb6ad31b644a,Discrete Deep Feature Extraction: A Theory and New Architectures,University of Vienna,University of Vienna,"Uni Wien, 1, Universitätsring, Schottenviertel, KG Innere Stadt, Innere Stadt, Wien, 1010, Österreich",48.21313020,16.36068653,edu,
403a108dec92363fd1f465340bd54dbfe65af870,Local Higher-Order Statistics (LHS) describing images with statistics of local non-binarized pixel patterns,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
40ee38d7ff2871761663d8634c3a4970ed1dc058,Three-Dimensional Face Recognition: A Fishersurface Approach,University of York,University of York,"University of York, Lakeside Way, Heslington, York, Yorkshire and the Humber, England, YO10 5FN, UK",53.94540365,-1.03138878,edu,
404042a1dcfde338cf24bc2742c57c0fb1f48359,A Survey on Facial Features Localization,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+40757d94d6ef33555fc940d556ebfb0d32410fbb,Warmth and competence in your face! Visual encoding of stereotype content,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+40757d94d6ef33555fc940d556ebfb0d32410fbb,Warmth and competence in your face! Visual encoding of stereotype content,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+403d6a09c17268fb4bb0ae953107bf5f78ca9d05,Staining Pattern Classification of Antinuclear Autoantibodies Based on Block Segmentation in Indirect Immunofluorescence Images,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
4015e8195db6edb0ef8520709ca9cb2c46f29be7,Smile Detector Based on the Motion of Face Reference Points,University of Tartu,UNIVERSITY OF TARTU,"Paabel, University of Tartu, 17, Ülikooli, Kesklinn, Tartu linn, Tartu, Tartu linn, Tartu maakond, 53007, Eesti",58.38131405,26.72078081,edu,
407bb798ab153bf6156ba2956f8cf93256b6910a,Fisher Pruning of Deep Nets for Facial Trait Classification,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+403530d1c418de29cbc595775ec45e16183950e5,Pioneer Networks: Progressively Growing Generative Autoencoder,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+40fa315150ddcaa1e0996046d140b8882f375f7d,Generative Image Inpainting with Contextual Attention,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+4091b6a3ab33e2aa923ee23c8db7e33d167ff67a,Transductive Multi-class and Multi-label Zero-shot Learning,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
407de9da58871cae7a6ded2f3a6162b9dc371f38,TraMNet - Transition Matrix Network for Efficient Action Tube Proposals,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
405526dfc79de98f5bf3c97bf4aa9a287700f15d,MegaFace: A Million Faces for Recognition at Scale,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
40b7e590dfd1cdfa1e0276e9ca592e02c1bd2b5b,Beyond Trade-off: Accelerate FCN-based Face Detector with Higher Accuracy,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
@@ -4242,27 +11920,81 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 40a9f3d73c622cceee5e3d6ca8faa56ed6ebef60,Automatic Lip Tracking and Action Units Classification using Two-Step Active Contours and Probabilistic Neural Networks,University of Tabriz,University of Tabriz,"دانشگاه تبریز, شهید ایرج خلوتی, کوی انقلاب, تبریز, بخش مرکزی, شهرستان تبریز, استان آذربایجان شرقی, 5166616471, ایران",38.06125530,46.32984840,edu,
40a9f3d73c622cceee5e3d6ca8faa56ed6ebef60,Automatic Lip Tracking and Action Units Classification using Two-Step Active Contours and Probabilistic Neural Networks,University of Ottawa,University of Ottawa,"University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada",45.42580475,-75.68740118,edu,
40a9f3d73c622cceee5e3d6ca8faa56ed6ebef60,Automatic Lip Tracking and Action Units Classification using Two-Step Active Contours and Probabilistic Neural Networks,University of Tabriz,University of Tabriz,"دانشگاه تبریز, شهید ایرج خلوتی, کوی انقلاب, تبریز, بخش مرکزی, شهرستان تبریز, استان آذربایجان شرقی, 5166616471, ایران",38.06125530,46.32984840,edu,
+40e30ba448a079152ccd13f9ba670aa272df66b3,Cross - Pose Facial Expression Recognition,Bilkent University,Bilkent University,"Bilkent Üniversitesi, 3. Cadde, Üniversiteler Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87204890,32.75395155,edu,
+4078c37c39dc5c7c65a5494651ba6dd443cf9269,Empirical Performance Upper Bounds for Im- Age and Video Captioning,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
40e1743332523b2ab5614bae5e10f7a7799161f4,Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
40e1743332523b2ab5614bae5e10f7a7799161f4,Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks,Jiangnan University,Jiangnan University,"江南大学站, 蠡湖大道, 滨湖区, 南场村, 滨湖区 (Binhu), 无锡市 / Wuxi, 江苏省, 214121, 中国",31.48542550,120.27395810,edu,
40c8cffd5aac68f59324733416b6b2959cb668fd,Pooling Facial Segments to Face: The Shallow and Deep Ends,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+4065d038ecbda579a0791aaf46fc62bbcba5b1f3,Real-time Factored ConvNets: Extracting the X Factor in Human Parsing,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
+40bb3ef2b4e556a3646a8cd77364a89b8773e4a4,First-Person Animal Activity Recognition from Egocentric Videos,Kyushu University,Kyushu University,"伊都ゲストハウス, 桜井太郎丸線, 西区, 福岡市, 福岡県, 九州地方, 819−0395, 日本",33.59914655,130.22359848,edu,
+40bb3ef2b4e556a3646a8cd77364a89b8773e4a4,First-Person Animal Activity Recognition from Egocentric Videos,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+4061524d5867325aab871ecf25ba58acd7872192,Aspect-based Question Generation,University of Illinois at Chicago,University of Illinois at Chicago,"University of Illinois at Chicago, West Taylor Street, Greektown, Chicago, Cook County, Illinois, 60607, USA",41.86898915,-87.64856256,edu,
+4061524d5867325aab871ecf25ba58acd7872192,Aspect-based Question Generation,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
40273657e6919455373455bd9a5355bb46a7d614,Anonymizing k Facial Attributes via Adversarial Perturbations,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+40629398c85c12432979379800c267d2a8c62bf8,Timing-Based Local Descriptor for Dynamic Surfaces,Kyoto University,Kyoto University,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
+4066f186ff58d300090c652925ed0aed3355efec,Solving Visual Madlibs with Multiple Cues,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+40559bd43d5480000e34e4fef3e8fe3782d1a688,Active query-driven visual search using probabilistic bisection and convolutional neural networks,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
40bb090a4e303f11168dce33ed992f51afe02ff7,Marginal Loss for Deep Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
40bb090a4e303f11168dce33ed992f51afe02ff7,Marginal Loss for Deep Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
40bb090a4e303f11168dce33ed992f51afe02ff7,Marginal Loss for Deep Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+40e7536f43c8a2623ce27e182a0e66028b58de89,Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation,"University of California, Santa Barbara","University of California, Santa Barbara","UCSB, Santa Barbara County, California, 93106, USA",34.41459370,-119.84581950,edu,
+401a8272c60216d1ce8be58edc13b42b1bfdf912,Semi-Supervised Learning in Gigantic Image Collections,Courant Institute of Mathematical Sciences,Courant Institute of Mathematical Sciences,"Courant Institute of Mathematical Sciences, 251, Mercer Street, Washington Square Village, Greenwich Village, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72864840,-73.99568630,edu,
406431d2286a50205a71f04e0b311ba858fc7b6c,3D facial expression classification using a statistical model of surface normals and a modular approach,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
406431d2286a50205a71f04e0b311ba858fc7b6c,3D facial expression classification using a statistical model of surface normals and a modular approach,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
40217a8c60e0a7d1735d4f631171aa6ed146e719,Part-Pair Representation for Part Localization,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+2e0bd693d12c43c2e86c7a4d8809445f380c5556,Webcam classification using simple features,Purdue University,Purdue University,"Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA",40.43197220,-86.92389368,edu,
+2e58ec57d71b2b2a3e71086234dd7037559cc17e,A Gender Recognition System from Facial Image,Institute of Information Technology,Institute of Information Technology,"Institute of Information Technology, Sir Sayed Road, ফকিরাপুল, সিদ্দিক বাজার, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.72898990,90.39826820,edu,
+2e58ec57d71b2b2a3e71086234dd7037559cc17e,A Gender Recognition System from Facial Image,Institute of Information Technology,Institute of Information Technology,"Institute of Information Technology, Sir Sayed Road, ফকিরাপুল, সিদ্দিক বাজার, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.72898990,90.39826820,edu,
+2e58ec57d71b2b2a3e71086234dd7037559cc17e,A Gender Recognition System from Facial Image,University of Dhaka,University of Dhaka,"World War Memorial, Shahid Minar Rd, Jagannath Hall, DU, জিগাতলা, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.73169570,90.39652750,edu,
+2e58ec57d71b2b2a3e71086234dd7037559cc17e,A Gender Recognition System from Facial Image,University of Dhaka,University of Dhaka,"World War Memorial, Shahid Minar Rd, Jagannath Hall, DU, জিগাতলা, ঢাকা, ঢাকা বিভাগ, 1000, বাংলাদেশ",23.73169570,90.39652750,edu,
+2e68f29f26f91985e0ad12b3229e46edefe1e871,Discovering Shades of Attribute Meaning with the Crowd,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+2ecb3e485b4935d3f7d25ebe8179724b9228bbec,Temporal-Coherency-Aware Human Pose Estimation in Video via Pre-trained Res-net and Flow-CNN,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+2ecb3e485b4935d3f7d25ebe8179724b9228bbec,Temporal-Coherency-Aware Human Pose Estimation in Video via Pre-trained Res-net and Flow-CNN,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+2e942d19333651bf6012374ea9e78d6937fd33ac,Detecting Faces Using Region-based Fully Convolutional Networks,Tencent,"Tencent AI Lab, China","Ke Ji Zhong Yi Lu, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057",22.54471540,113.93571640,company,"Keji Middle 1st Rd, Nanshan Qu, Shenzhen Shi, Guangdong Sheng, China, 518057"
+2e5ebb2ed819b97c6c54570d684576387dc55e93,Reasoning about Object Affordances in a Knowledge Base Representation,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+2e079604c7a00c43f06e214280cea18a89dcecef,Bayesian Optimization and Semiparametric Models with Applications to Assistive Technology,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
2e0addeffba4be98a6ad0460453fbab52616b139,Face View Synthesis Using A Single Image,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
2e0addeffba4be98a6ad0460453fbab52616b139,Face View Synthesis Using A Single Image,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
2e8a0cc071017845ee6f67bd0633b8167a47abed,Spatio-temporal covariance descriptors for action and gesture recognition,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+2e9739056c9d1fe7b37046328f00cae603f59441,A Video-Based Method for Automatically Rating Ataxia,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+2e9739056c9d1fe7b37046328f00cae603f59441,A Video-Based Method for Automatically Rating Ataxia,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+2e9739056c9d1fe7b37046328f00cae603f59441,A Video-Based Method for Automatically Rating Ataxia,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+2e9739056c9d1fe7b37046328f00cae603f59441,A Video-Based Method for Automatically Rating Ataxia,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+2e9739056c9d1fe7b37046328f00cae603f59441,A Video-Based Method for Automatically Rating Ataxia,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+2e9739056c9d1fe7b37046328f00cae603f59441,A Video-Based Method for Automatically Rating Ataxia,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+2e9dc528c023a6634a51d5a74e95e5f432da9aaa,Eye movements while judging faces for trustworthiness and dominance,University of Lincoln,University of Lincoln,"University of Lincoln, Brayford Way, Whitton Park, New Boultham, Lincoln, Lincolnshire, East Midlands, England, LN6 7TS, UK",53.22853665,-0.54873472,edu,
+2e9dc528c023a6634a51d5a74e95e5f432da9aaa,Eye movements while judging faces for trustworthiness and dominance,University of Aberdeen,University of Aberdeen,"University of Aberdeen, High Street, Old Aberdeen, Aberdeen, Aberdeen City, Scotland, AB24 3EJ, UK",57.16461430,-2.10186013,edu,
+2e105974d58cdefcc866c5f6ca73ea033881ddd7,Question Type Guided Attention in Visual Question Answering,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+2e105974d58cdefcc866c5f6ca73ea033881ddd7,Question Type Guided Attention in Visual Question Answering,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+2e105974d58cdefcc866c5f6ca73ea033881ddd7,Question Type Guided Attention in Visual Question Answering,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+2e222383bd75d3c3961ac073e8aabd3557946601,Unsupervised Video Adaptation for Parsing Human Motion,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+2e222383bd75d3c3961ac073e8aabd3557946601,Unsupervised Video Adaptation for Parsing Human Motion,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2e222383bd75d3c3961ac073e8aabd3557946601,Unsupervised Video Adaptation for Parsing Human Motion,University of Queensland,University of Queensland,"University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia",-27.49741805,153.01316956,edu,
+2e02597b9a8239700703920d5b74f765576d6f43,A model of the neural basis of predecisional processes : the fronto-limbic information acquisition network,University of Iowa,University of Iowa,"University of Iowa, Hawkeye Court, Iowa City, Johnson County, Iowa, 52246, USA",41.66590000,-91.57310307,edu,
+2e02597b9a8239700703920d5b74f765576d6f43,A model of the neural basis of predecisional processes : the fronto-limbic information acquisition network,University of Iowa,University of Iowa,"University of Iowa, Hawkeye Court, Iowa City, Johnson County, Iowa, 52246, USA",41.66590000,-91.57310307,edu,
+2e02597b9a8239700703920d5b74f765576d6f43,A model of the neural basis of predecisional processes : the fronto-limbic information acquisition network,University of Iowa,University of Iowa,"University of Iowa, Hawkeye Court, Iowa City, Johnson County, Iowa, 52246, USA",41.66590000,-91.57310307,edu,
+2e355890915492ddd46063828f8534b734b8f58f,Dynamic Label Graph Matching for Unsupervised Video Re-identification,Hong Kong Baptist University,Hong Kong Baptist University,"香港浸會大學 Hong Kong Baptist University, 安明街 On Ming Street, 石門 Shek Mun, 石古壟 Shek Kwu Lung, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1132, 中国",22.38742010,114.20822220,edu,
+2e355890915492ddd46063828f8534b734b8f58f,Dynamic Label Graph Matching for Unsupervised Video Re-identification,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
2e231f1e7e641dd3619bec59e14d02e91360ac01,Fusion Network for Face-Based Age Estimation,University of Bath,University of Bath,"University of Bath, Convocation Avenue, Claverton Down, Bath, Bath and North East Somerset, South West England, England, BA2 7PA, UK",51.37914420,-2.32523320,edu,
2e231f1e7e641dd3619bec59e14d02e91360ac01,Fusion Network for Face-Based Age Estimation,Charles Sturt University,Charles Sturt University,"Charles Sturt University, Wagga Wagga, NSW, 2678, Australia",-35.06360710,147.35522340,edu,
2e6cfeba49d327de21ae3186532e56cadeb57c02,Real Time Eye Gaze Tracking with 3D Deformable Eye-Face Model,Rensselaer Polytechnic Institute,Rensselaer Polytechnic Institute,"Rensselaer Polytechnic Institute, Sage Avenue, Downtown, City of Troy, Rensselaer County, New York, 12180, USA",42.72984590,-73.67950216,edu,
+2e480b3ef788512d647129509ea2e7d20464bf45,Scene image classification with biased spatial block and pLSA,Tianjin University,Tianjin University,"泰山航空港/天津大厦, 枣行路, 枣行 高王寺, 长城路, 大河, 岱岳区 (Daiyue), 泰安市, 山东省, 271000, 中国",36.20304395,117.05842113,edu,
+2e6e9d117b626e34ce0167f9d69cec6698b0eb05,Labeling of Human Motion Based on CBGA,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+2e55a287328b234db16fb538eddbbc185d51582a,UTS-CMU-D 2 DCRC Submission at TRECVID 2016 Video Localization,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+2e55a287328b234db16fb538eddbbc185d51582a,UTS-CMU-D 2 DCRC Submission at TRECVID 2016 Video Localization,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
2ee817981e02c4709d65870c140665ed25b005cc,Sparse representations and Random Projections for robust and cancelable biometrics,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
2ee817981e02c4709d65870c140665ed25b005cc,Sparse representations and Random Projections for robust and cancelable biometrics,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
2e98329fdec27d4b3b9b894687e7d1352d828b1d,Using Affect Awareness to Modulate Task Experience: A Study Amongst Pre-elementary School Kids,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2e59865aa2ddcecaf9275abcad9b134558c686c2,Joint Learning of Single-Image and Cross-Image Representations for Person Re-identification,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+2e59865aa2ddcecaf9275abcad9b134558c686c2,Joint Learning of Single-Image and Cross-Image Representations for Person Re-identification,Hong Kong Polytechnic University,Hong Kong Polytechnic University,"hong kong, 11, 育才道 Yuk Choi Road, 尖沙咀 Tsim Sha Tsui, 油尖旺區 Yau Tsim Mong District, 九龍 Kowloon, HK, 00000, 中国",22.30457200,114.17976285,edu,
+2e59865aa2ddcecaf9275abcad9b134558c686c2,Joint Learning of Single-Image and Cross-Image Representations for Person Re-identification,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+2eb1dc9d1cf571462f7bc616b0dc52c8e402e331,"Towards Speech Emotion Recognition ""in the wild"" using Aggregated Corpora and Deep Multi-Task Learning",University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+2e9d33cba9f547a2e3febe088bae443f1d74d594,PipeLayer: A Pipelined ReRAM-Based Accelerator for Deep Learning,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+2e9d33cba9f547a2e3febe088bae443f1d74d594,PipeLayer: A Pipelined ReRAM-Based Accelerator for Deep Learning,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
2e8eb9dc07deb5142a99bc861e0b6295574d1fbd,Analysis by Synthesis: 3D Object Recognition by Object Reconstruction,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
2e8eb9dc07deb5142a99bc861e0b6295574d1fbd,Analysis by Synthesis: 3D Object Recognition by Object Reconstruction,"University of California, Irvine","University of California, Irvine","University of California, Irvine, East Peltason Drive, Turtle Rock, Irvine, Orange County, California, 92612, USA",33.64319010,-117.84016494,edu,
+2ec55c3fb5fa493ebfacc58115cf28f283a50a02,How to Transfer? Zero-Shot Object Recognition via Hierarchical Transfer of Semantic Attributes,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+2e17cf6a339fd071ad222062f868e882ef4120a4,Inferring and Executing Programs for Visual Reasoning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
2e3c893ac11e1a566971f64ae30ac4a1f36f5bb5,Simultaneous Object Detection and Ranking with Weak Supervision,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
2ed3ce5cf9e262bcc48a6bd998e7fb70cf8a971c,Active AU Based Patch Weighting for Facial Expression Recognition,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
2edc6df161f6aadbef9c12408bdb367e72c3c967,Improved Spatiotemporal Local Monogenic Binary Pattern for Emotion Recognition in The Wild,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
@@ -4270,42 +12002,98 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 2edc6df161f6aadbef9c12408bdb367e72c3c967,Improved Spatiotemporal Local Monogenic Binary Pattern for Emotion Recognition in The Wild,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
2edc6df161f6aadbef9c12408bdb367e72c3c967,Improved Spatiotemporal Local Monogenic Binary Pattern for Emotion Recognition in The Wild,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
2edc6df161f6aadbef9c12408bdb367e72c3c967,Improved Spatiotemporal Local Monogenic Binary Pattern for Emotion Recognition in The Wild,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+2e67d919815a073d1dbc6db3153697578257a28d,Understanding how image quality affects deep neural networks,Arizona State University,Arizona State University,"Arizona State University Polytechnic campus, East Texas Avenue, Mesa, Maricopa County, Arizona, 85212, USA",33.30715065,-111.67653157,edu,
+2e38ff75a80ec92111261bf368781c7eef89eb14,Face hallucination VIA sparse coding,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
+2e38ff75a80ec92111261bf368781c7eef89eb14,Face hallucination VIA sparse coding,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
2e1fd8d57425b727fd850d7710d38194fa6e2654,Learning Structured Appearance Models from Captioned Images of Cluttered Scenes,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
2e1fd8d57425b727fd850d7710d38194fa6e2654,Learning Structured Appearance Models from Captioned Images of Cluttered Scenes,Bielefeld University,Bielefeld University,"Fachhochschule Bielefeld FB Gestaltung, 3, Lampingstraße, Mitte, Bielefeld, Regierungsbezirk Detmold, Nordrhein-Westfalen, 33615, Deutschland",52.02804210,8.51148270,edu,
+2e786f3353667b537636fc1912118961e512be88,Visual Tracking of Multiple Humans with Machine Learning based Robustness Enhancement applied to Real-World Robotic Systems,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+2eb96e784d2b34ba56654ebd0f357f0b121f73cb,A study of impaired judgment of eye-gaze direction and related face-processing deficits in autism spectrum disorders.,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+2eb96e784d2b34ba56654ebd0f357f0b121f73cb,A study of impaired judgment of eye-gaze direction and related face-processing deficits in autism spectrum disorders.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+2eb96e784d2b34ba56654ebd0f357f0b121f73cb,A study of impaired judgment of eye-gaze direction and related face-processing deficits in autism spectrum disorders.,University of Sheffield,The University of Sheffield,"University of Sheffield, Portobello, Port Mahon, Saint George's, Sheffield, Yorkshire and the Humber, England, S1 4DP, UK",53.38152480,-1.48068143,edu,
+2e243d59184f781755339f6b415fff87f63c5ca2,Fixation and Saccade Based Face Recognition from Single Image per Person with Various Occlusions and Expressions,University of Warwick,University of Warwick,"University of Warwick, University Road, Kirby Corner, Cannon Park, Coventry, West Midlands Combined Authority, West Midlands, England, CV4 7AL, UK",52.37931310,-1.56042520,edu,
+2b4512097cb0056886f2d4d2ca7f5b034a647237,3D Facial Expression Recognition Based on Primitive Surface Feature Distribution,SUNY Binghamton,State University of New York at Binghamton,"State University of New York at Binghamton, East Drive, Hinman, Willow Point, Vestal Town, Broome County, New York, 13790, USA",42.08779975,-75.97066066,edu,
2be0ab87dc8f4005c37c523f712dd033c0685827,Relaxed local ternary pattern for face recognition,Institute of Media Innovation,Institute of Media Innovation,"Institute for Media Innovation, 50, Nanyang Drive, Pioneer, Southwest, 637553, Singapore",1.34339370,103.67933030,edu,
2be0ab87dc8f4005c37c523f712dd033c0685827,Relaxed local ternary pattern for face recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
2be0ab87dc8f4005c37c523f712dd033c0685827,Relaxed local ternary pattern for face recognition,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
2bb2ba7c96d40e269fc6a2d5384c739ff9fa16eb,Image-Based Recommendations on Styles and Substitutes,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
2bb2ba7c96d40e269fc6a2d5384c739ff9fa16eb,Image-Based Recommendations on Styles and Substitutes,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+2bdba44420e400eceab79f02a8552ee97e940225,Pornography detection using BossaNova video descriptor,University of Campinas,University of Campinas,"USJ, 97, Rua Sílvia Maria Fabro, Kobrasol, Campinas, São José, Microrregião de Florianópolis, Mesorregião da Grande Florianópolis, SC, Região Sul, 88102-130, Brasil",-27.59539950,-48.61542180,edu,
+2b10b0f309546878ec418ae6e6f0a993fd7f3293,Human Perambulation as a Self Calibrating Biometric,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
2b339ece73e3787f445c5b92078e8f82c9b1c522,"Human Re-identification in Crowd Videos Using Personal, Social and Environmental Constraints",University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+2b64a72d53f13417c6352d3e89fd27df91b5d697,Learning Human Interaction by Interactive Phrases,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
2bb53e66aa9417b6560e588b6235e7b8ebbc294c,Semantic embedding space for zero-shot action recognition,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
2be8e06bc3a4662d0e4f5bcfea45631b8beca4d0,Watch and learn: Semi-supervised learning of object detectors from videos,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+2b0e1a62d7168df5f29e2e9c7fc72ae43c39fdb2,Emotion expression modulates perception of animacy from faces,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
2bcec23ac1486f4106a3aa588b6589e9299aba70,An Uncertain Future: Forecasting from Static Images Using Variational Autoencoders,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
2b773fe8f0246536c9c40671dfa307e98bf365ad,Fast Discriminative Stochastic Neighbor Embedding Analysis,Zhejiang University of Technology,Zhejiang University of Technology,"浙江工业大学, 潮王路, 朝晖街道, 杭州市 Hangzhou, 浙江省, 310014, 中国",30.29315340,120.16204580,edu,
+2bcd59835528c583bb5b310522a5ba6e99c58b15,Multi-class Open Set Recognition Using Probability of Inclusion,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+2b9410889dc6870cc6e0476dbc681049b28ccacb,Learning to Detect Carried Objects with Minimal Supervision,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
2bab44d3a4c5ca79fb8f87abfef4456d326a0445,Player identification in soccer videos,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
2b0102d77d3d3f9bc55420d862075934f5c85bec,Slicing Convolutional Neural Network for Crowd Video Understanding,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
2b0102d77d3d3f9bc55420d862075934f5c85bec,Slicing Convolutional Neural Network for Crowd Video Understanding,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2bce7f8a53fb8ec93dd218dbdf55b48ac54ae8b3,Predicting the Category and Attributes of Mental Pictures Using Deep Gaze Pooling,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+2b73e3d541b0208ae54b3920fef4bfd9fd0c84a7,Feature-based face representations and image reconstruction from behavioral and neural data.,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+2b73e3d541b0208ae54b3920fef4bfd9fd0c84a7,Feature-based face representations and image reconstruction from behavioral and neural data.,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2b73e3d541b0208ae54b3920fef4bfd9fd0c84a7,Feature-based face representations and image reconstruction from behavioral and neural data.,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
2b435ee691718d0b55d057d9be4c3dbb8a81526e,SURF-Face: Face Recognition Under Viewpoint Consistency Constraints,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
+2b4bed0fadee29a84a272d7c52adc4a70e1a2b52,Human Motion Detection Using Fuzzy Rule-base Classification Of Moving Blob Regions,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+2b4bed0fadee29a84a272d7c52adc4a70e1a2b52,Human Motion Detection Using Fuzzy Rule-base Classification Of Moving Blob Regions,Multimedia University,Multimedia University,"Universiti Multimedia, Persiaran Neuron, Bandar Nusaputra, Cyberjaya, Selangor, 63000, Malaysia",2.92749755,101.64185301,edu,
+2b79da19774861621b6a9d0c769f95d33e5b6eb6,Maximum Classifier Discrepancy for Unsupervised Domain Adaptation,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+2bb2abecb4fa7071bc2760784c6f7661e7e725da,StarMap for Category-Agnostic Keypoint and Viewpoint Estimation,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
2b5cb5466eecb131f06a8100dcaf0c7a0e30d391,A comparative study of active appearance model annotation schemes for the face,"UNCW, USA","UNCW, USA","601 S College Rd, Wilmington, NC 28403, USA",34.22398690,-77.87013250,edu,
2b5cb5466eecb131f06a8100dcaf0c7a0e30d391,A comparative study of active appearance model annotation schemes for the face,"UNCW, USA","UNCW, USA","601 S College Rd, Wilmington, NC 28403, USA",34.22398690,-77.87013250,edu,
2b5cb5466eecb131f06a8100dcaf0c7a0e30d391,A comparative study of active appearance model annotation schemes for the face,"UNCW, USA","UNCW, USA","601 S College Rd, Wilmington, NC 28403, USA",34.22398690,-77.87013250,edu,
2b64a8c1f584389b611198d47a750f5d74234426,Deblurring Face Images with Exemplars,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
2b64a8c1f584389b611198d47a750f5d74234426,Deblurring Face Images with Exemplars,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+2b6c031c61b78a9f9ee958d291d29c8ab359404e,Vision of a Visipedia,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
2b10a07c35c453144f22e8c539bf9a23695e85fc,Standardization of Face Image Sample Quality,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
2b10a07c35c453144f22e8c539bf9a23695e85fc,Standardization of Face Image Sample Quality,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+2bc16bf87ceec85822912ef612385e519a6f98b5,"Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+2bc16bf87ceec85822912ef612385e519a6f98b5,"Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+2ba23d9b46027e47b4483243871760e315213ffe,Energy-based Generative Adversarial Network,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
2b84630680e2c906f8d7ac528e2eb32c99ef203a,We are not All Equal: Personalizing Models for Facial Expression Analysis with Transductive Parameter Transfer,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
2b84630680e2c906f8d7ac528e2eb32c99ef203a,We are not All Equal: Personalizing Models for Facial Expression Analysis with Transductive Parameter Transfer,University of Perugia,University of Perugia,"Caffe Perugia, 2350, Health Sciences Mall, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.26224210,-123.24500520,edu,
+2bf8541199728262f78d4dced6fb91479b39b738,Clothing Co-parsing by Joint Image Segmentation and Labeling,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+2bf8541199728262f78d4dced6fb91479b39b738,Clothing Co-parsing by Joint Image Segmentation and Labeling,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2b514d32318bb01ab04f75ef19ad1af63bce7943,ad-heap: an Efficient Heap Data Structure for Asymmetric Multicore Processors,University of Copenhagen,University of Copenhagen,"Københavns Universitet, Krystalgade, Kødbyen, Vesterbro, København, Københavns Kommune, Region Hovedstaden, 1165, Danmark",55.68015020,12.57232700,edu,
2b7ef95822a4d577021df16607bf7b4a4514eb4b,Emergence of Object-Selective Features in Unsupervised Feature Learning,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
2b869d5551b10f13bf6fcdb8d13f0aa4d1f59fc4,Ring loss: Convex Feature Normalization for Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
2b42f83a720bd4156113ba5350add2df2673daf0,Action Recognition and Detection by Combining Motion and Appearance Features,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
2b42f83a720bd4156113ba5350add2df2673daf0,Action Recognition and Detection by Combining Motion and Appearance Features,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
2b42f83a720bd4156113ba5350add2df2673daf0,Action Recognition and Detection by Combining Motion and Appearance Features,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+2b86919eb8073d9b0e137b23cc9a14fab8bc601b,Joint Intensity and Spatial Metric Learning for Robust Gait Recognition,Osaka University,Osaka University,"大阪大学清明寮, 服部西町四丁目, 豊中市, 大阪府, 近畿地方, 日本",34.80809035,135.45785218,edu,
+2b2ba4857991c40fb854080dc5f9e48e60c35e68,"Data Hallucination , Falsification and Validation using Generative Models and Formal Methods by","University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
+2b88c583cd62130f1e2c6921db9703a0c5746a90,Multicamera tracking of multiple humans based on colored visual hulls,University of Crete,University of Crete,"House of Europe, Μακεδονίας, Ρέθυμνο, Δήμος Ρεθύμνης, Περιφερειακή Ενότητα Ρεθύμνου, Περιφέρεια Κρήτης, Κρήτη, 930100, Ελλάδα",35.37130240,24.47544080,edu,
+2b852a4e5026ab962050a0ef23a6892e06abb152,EmojiGAN: learning emojis distributions with a generative model,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+2b852a4e5026ab962050a0ef23a6892e06abb152,EmojiGAN: learning emojis distributions with a generative model,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+2b852a4e5026ab962050a0ef23a6892e06abb152,EmojiGAN: learning emojis distributions with a generative model,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+472500bb0fc49354445b25f851905dda621a42d0,Understanding and Predicting Interestingness of Videos,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+4706d61276b953eadeac572bd449cfa70d2e0b82,Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
47fdbd64edd7d348713253cf362a9c21f98e4296,Facial point detection based on a convolutional neural network with optimal mini-batch procedure,Chubu University,Chubu University,"中部大学, 国道19号, 春日井市, 愛知県, 中部地方, 487-8501, 日本",35.27426550,137.01327841,edu,
47382cb7f501188a81bb2e10cfd7aed20285f376,Articulated Pose Estimation Using Hierarchical Exemplar-Based Models,Columbia University ,Columbia University in the City of New York,"Columbia University In The City Of New York, College Walk, Morningside Heights, Manhattan, Manhattan Community Board 9, New York County, NYC, New York, 10027, USA",40.80717720,-73.96252798,edu,
473366f025c4a6e0783e6174ca914f9cb328fe70,Review of Action Recognition and Detection Methods,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+478cab795c8bc62cb68d3ffa9b0dfc290201416c,Kernel Sharing With Joint Boosting For Multi-Class Concept Detection,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+478cab795c8bc62cb68d3ffa9b0dfc290201416c,Kernel Sharing With Joint Boosting For Multi-Class Concept Detection,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+4764257e844f11e57ff72159bdcfb3dbfe17816a,Towards Instance Segmentation with Object Priority: Prominent Object Detection and Recognition,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+4764257e844f11e57ff72159bdcfb3dbfe17816a,Towards Instance Segmentation with Object Priority: Prominent Object Detection and Recognition,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+47ecc0924c2a17a6664d9ff6c31e2b9b6e490294,An SVM Confidence-Based Approach to Medical Image Annotation,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
4793f11fbca4a7dba898b9fff68f70d868e2497c,Kinship Verification through Transfer Learning,SUNY Buffalo,SUNY Buffalo,"SUNY College at Buffalo, Academic Drive, Elmwood Village, Buffalo, Erie County, New York, 14222, USA",42.93362780,-78.88394479,edu,
+4745baf6c4ae7a088f03340fcc05ad7d18a0aca2,Multi-label Image Classification with A Probabilistic Label Enhancement Model,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+4774b9853968b12156287bd42bb425d79f99e313,Online Multi-object Tracking Based on Hierarchical Association Framework,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+472c8606e68b34f4cc796a11963155fe3c6bfaec,Evolution of Images with Diversity and Constraints Using a Generator Network,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+472c8606e68b34f4cc796a11963155fe3c6bfaec,Evolution of Images with Diversity and Constraints Using a Generator Network,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+472c8606e68b34f4cc796a11963155fe3c6bfaec,Evolution of Images with Diversity and Constraints Using a Generator Network,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
473031328c58b7461753e81251379331467f7a69,Exploring Fisher vector and deep networks for action spotting,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
473031328c58b7461753e81251379331467f7a69,Exploring Fisher vector and deep networks for action spotting,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+47788b7a4700d1bbc972178f3680a028874afdb5,Adaptive Scheduling for Systems with Asymmetric Memory Hierarchies,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+47f84928dd6e40797255fa1e1bbb3c12b2659a7c,Input selection for fast feature engineering,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+47f84928dd6e40797255fa1e1bbb3c12b2659a7c,Input selection for fast feature engineering,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+47dfddafed43bc5afef93ac90ea3376a02046151,Max Margin AND/OR Graph learning for parsing the human body,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+47dfddafed43bc5afef93ac90ea3376a02046151,Max Margin AND/OR Graph learning for parsing the human body,University of Science and Technology of China,University of Science and Technology of China,"中国科学技术大学 东校区, 96号, 金寨路, 江淮化肥厂小区, 芜湖路街道, 合肥市区, 合肥市, 安徽省, 230026, 中国",31.83907195,117.26420748,edu,
+47dfddafed43bc5afef93ac90ea3376a02046151,Max Margin AND/OR Graph learning for parsing the human body,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+47dfddafed43bc5afef93ac90ea3376a02046151,Max Margin AND/OR Graph learning for parsing the human body,"University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+47de0569259e6a420c3eda69cdebf01bf85a1acd,An Integrated Development Environment for Faster Feature Engineering,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
47638197d83a8f8174cdddc44a2c7101fa8301b7,Object-Centric Anomaly Detection by Attribute-Based Reasoning,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
47638197d83a8f8174cdddc44a2c7101fa8301b7,Object-Centric Anomaly Detection by Attribute-Based Reasoning,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
47638197d83a8f8174cdddc44a2c7101fa8301b7,Object-Centric Anomaly Detection by Attribute-Based Reasoning,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
@@ -4314,20 +12102,67 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 472ba8dd4ec72b34e85e733bccebb115811fd726,Cosine Similarity Metric Learning for Face Verification,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
47eba2f95679e106e463e8296c1f61f6ddfe815b,Deep Co-occurrence Feature Learning for Visual Object Recognition,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
47eba2f95679e106e463e8296c1f61f6ddfe815b,Deep Co-occurrence Feature Learning for Visual Object Recognition,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+472541ccd941b9b4c52e1f088cc1152de9b3430f,Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+477ca04e9c6b9fd8326af7e11c6d60b6ada2f42a,Adapting Models to Signal Degradation using Distillation,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+4767a0c9f7261a4265db650d3908c6dd1d10a076,Joint tracking and segmentation of multiple targets,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+47203943c86e4d9355ffd99cd3d75f37211fd805,Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+47203943c86e4d9355ffd99cd3d75f37211fd805,Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
47190d213caef85e8b9dd0d271dbadc29ed0a953,The Devil of Face Recognition is in the Noise,"University of California, San Diego","University of California, San Diego","UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA",32.87935255,-117.23110049,edu,
47190d213caef85e8b9dd0d271dbadc29ed0a953,The Devil of Face Recognition is in the Noise,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+47b6cd69c0746688f6e17b37d73fa12422826dbc,Self corrective Perturbations for Semantic Segmentation and Classification,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+47b6cd69c0746688f6e17b37d73fa12422826dbc,Self corrective Perturbations for Semantic Segmentation and Classification,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+47b6cd69c0746688f6e17b37d73fa12422826dbc,Self corrective Perturbations for Semantic Segmentation and Classification,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+47b6cd69c0746688f6e17b37d73fa12422826dbc,Self corrective Perturbations for Semantic Segmentation and Classification,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+479eb6579194d4d944671dfe5e90b122ca4b58fd,Structural inference embedded adversarial networks for scene parsing,Harbin Engineering University,Harbin Engineering University,"哈尔滨工程大学, 文庙街 - Wenmiao Street, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.77445695,126.67684917,edu,
+479eb6579194d4d944671dfe5e90b122ca4b58fd,Structural inference embedded adversarial networks for scene parsing,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+47d8d8ead70e26eb791c4dea5fe1a4d666ee2462,Single Image 3D without a Single 3D Image,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+47662d1a368daf70ba70ef2d59eb6209f98b675d,The CMU Face In Action (FIA) Database,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+47662d1a368daf70ba70ef2d59eb6209f98b675d,The CMU Face In Action (FIA) Database,GE Global Research Center,GE Global Research Center,"GE Global Research Center, Aqueduct, Niskayuna, Schenectady County, New York, USA",42.82982480,-73.87719385,edu,
+471635c61fffa75cd09121b14e4da155c667c5bf,Exploring the Design Space of Deep Convolutional Neural Networks at Large Scale,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
47dabb566f2bdd6b3e4fa7efc941824d8b923a13,Probabilistic Temporal Head Pose Estimation Using a Hierarchical Graphical Model,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+4747d169a5d6b48febfa111a8b28680159eb3bb2,Detecting People in Artwork with CNNs,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+4780cece6d4adeb0b070fbefbd587b89f4acf3f7,Shared and idiosyncratic cortical activation patterns in autism revealed under continuous real-life viewing conditions.,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+4780cece6d4adeb0b070fbefbd587b89f4acf3f7,Shared and idiosyncratic cortical activation patterns in autism revealed under continuous real-life viewing conditions.,Weizmann Institute of Science,Weizmann Institute of Science,"מכון ויצמן למדע, שדרת מרכוס זיו, מעונות שיין, אחוזות הנשיא, רחובות, מחוז המרכז, NO, ישראל",31.90784990,34.81334092,edu,
+4780cece6d4adeb0b070fbefbd587b89f4acf3f7,Shared and idiosyncratic cortical activation patterns in autism revealed under continuous real-life viewing conditions.,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+4780cece6d4adeb0b070fbefbd587b89f4acf3f7,Shared and idiosyncratic cortical activation patterns in autism revealed under continuous real-life viewing conditions.,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+4780cece6d4adeb0b070fbefbd587b89f4acf3f7,Shared and idiosyncratic cortical activation patterns in autism revealed under continuous real-life viewing conditions.,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+4771af2eeb920bde146c74ee0f56bd421793cd33,ste-GAN-ography: Generating Steganographic Images via Adversarial Training,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+4771af2eeb920bde146c74ee0f56bd421793cd33,ste-GAN-ography: Generating Steganographic Images via Adversarial Training,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+479cd0af9f345bd44cd180a5e26f3e799391e31d,Supervised local subspace learning for continuous head pose estimation,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+479cd0af9f345bd44cd180a5e26f3e799391e31d,Supervised local subspace learning for continuous head pose estimation,Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
+479cd0af9f345bd44cd180a5e26f3e799391e31d,Supervised local subspace learning for continuous head pose estimation,University of Electronic Science and Technology of China,University of Electronic Science and Technology of China,"Columbus, OH 43210, USA",40.01419050,-83.03091430,edu,
+47493ad6e6d5591086c8a2b812bfae85aae50193,On gradient regularizers for MMD GANs,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+47493ad6e6d5591086c8a2b812bfae85aae50193,On gradient regularizers for MMD GANs,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
+47493ad6e6d5591086c8a2b812bfae85aae50193,On gradient regularizers for MMD GANs,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+47493ad6e6d5591086c8a2b812bfae85aae50193,On gradient regularizers for MMD GANs,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
473cbc5ec2609175041e1410bc6602b187d03b23,Semantic Audio-Visual Data Fusion for Automatic Emotion Recognition,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
+47e388dcd33feda1dadac82cd60fd7f7fb599594,"Attributed Grammars for Joint Estimation of Human Attributes, Part and Pose","University of California, Los Angeles","University of California, Los Angeles","200 UCLA, Medical Plaza Driveway Suite 540, Los Angeles, CA 90095, USA",34.06877880,-118.44500940,edu,
+784731961819abc5a5a199be1573abd828bd9af1,Recognizing Emily and Latisha: Inconsistent Effects of Name Stereotypicality on the Other-Race Effect,Universität Hamburg,Universität Hamburg,"Informatikum, 30, Vogt-Kölln-Straße, Stellingen, Eimsbüttel, Hamburg, 22527, Deutschland",53.59948200,9.93353436,edu,
+786f2e480cb81c9df8d213ac156a5333946a2b8f,Violations of Personal Space by Individuals with Autism Spectrum Disorder,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+786f2e480cb81c9df8d213ac156a5333946a2b8f,Violations of Personal Space by Individuals with Autism Spectrum Disorder,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+7811fd02bb77e2f6644f34c0f445d096199c3c2f,Model-Free Head Pose Estimation Based on Shape Factorisation and Particle Filtering,University of Malta,University of Malta,"University of Malta, Ring Road, Japanese Garden, L-Imsida, Malta, MSD 9027, Malta",35.90232260,14.48341890,edu,
+7803281f4b94cb25ed17786fd63807d223cf7af4,Input Reconstruction Side and top down view Part Segmentation Input Reconstruction Side and top down view Part Segmentation,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
78f08cc9f845dc112f892a67e279a8366663e26d,Semi-Autonomous Data Enrichment and Optimisation for Intelligent Speech Analysis,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
78d645d5b426247e9c8f359694080186681f57db,Gender Classification by LUT Based Boosting of Overlapping Block Patterns,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
78d645d5b426247e9c8f359694080186681f57db,Gender Classification by LUT Based Boosting of Overlapping Block Patterns,IDIAP Research Institute,IDIAP Research Institute,"Idiap Research Institute, Parking Centre du parc, Martigny, Valais/Wallis, 1920, Schweiz/Suisse/Svizzera/Svizra",46.10923700,7.08453549,edu,
+78560fc9c224c1b605b3ed30cc3345863c5988e2,Boosted multiple kernel learning for first-person activity recognition,Middle East Technical University,Middle East Technical University,"ODTÜ, 1, 1591.sk(315.sk), Çiğdem Mahallesi, Ankara, Çankaya, Ankara, İç Anadolu Bölgesi, 06800, Türkiye",39.87549675,32.78553506,edu,
+78560fc9c224c1b605b3ed30cc3345863c5988e2,Boosted multiple kernel learning for first-person activity recognition,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
7862d40da0d4e33cd6f5c71bbdb47377e4c6b95a,Demography-based facial retouching detection using subclass supervised sparse autoencoder,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+78569509e61269f5d2276b80f4fd41c22617ccc4,Localization Guided Learning for Pedestrian Attribute Recognition,City University of Hong Kong,City University of Hong Kong,"香港城市大學 City University of Hong Kong, 達康路 Tat Hong Avenue, 大窩坪 Tai Wo Ping, 深水埗區 Sham Shui Po District, 九龍 Kowloon, HK, KIL 3348, 中国",22.34000115,114.16970291,edu,
+78569509e61269f5d2276b80f4fd41c22617ccc4,Localization Guided Learning for Pedestrian Attribute Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+78569509e61269f5d2276b80f4fd41c22617ccc4,Localization Guided Learning for Pedestrian Attribute Recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
7859667ed6c05a467dfc8a322ecd0f5e2337db56,Web-Scale Transfer Learning for Unconstrained 1:N Face Identification,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
78c1ad33772237bf138084220d1ffab800e1200d,Decorrelated Batch Normalization,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
78c1ad33772237bf138084220d1ffab800e1200d,Decorrelated Batch Normalization,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
78436256ff8f2e448b28e854ebec5e8d8306cf21,Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
78436256ff8f2e448b28e854ebec5e8d8306cf21,Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
78436256ff8f2e448b28e854ebec5e8d8306cf21,Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+78990bd69e12f7d123b6a0ce6b1674ea801f2319,Learning Joint Representations of Videos and Sentences with Web Image Search,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+78102141a1b78101515f93385e7b71a4aa1955c5,An Adaptation Framework for Head-Pose Classification in Dynamic Multi-view Scenarios,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+78102141a1b78101515f93385e7b71a4aa1955c5,An Adaptation Framework for Head-Pose Classification in Dynamic Multi-view Scenarios,University of Perugia,University of Perugia,"Caffe Perugia, 2350, Health Sciences Mall, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada",49.26224210,-123.24500520,edu,
+78bdba66b1a5fb19824be37c4f5c2d20e0e3b34f,2 . Dilated Residual Networks,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+78bdba66b1a5fb19824be37c4f5c2d20e0e3b34f,2 . Dilated Residual Networks,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+78f62042bfb3bb49ba10e142d118a9bb058b2a19,WebSeg: Learning Semantic Segmentation from Web Searches,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
78f79c83b50ff94d3e922bed392737b47f93aa06,The computer expression recognition toolbox (CERT),University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
78f79c83b50ff94d3e922bed392737b47f93aa06,The computer expression recognition toolbox (CERT),University of Buffalo,University of Buffalo,"University of Nebraska at Kearney, 2504, 9th Avenue, Kearney, Buffalo County, Nebraska, 68849, USA",40.70217660,-99.09850612,edu,
78fede85d6595e7a0939095821121f8bfae05da6,Discriminant Metric Learning Approach for Face Verification,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
@@ -4336,52 +12171,118 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 78598e7005f7c96d64cc47ff47e6f13ae52245b8,Hand2Face: Automatic synthesis and recognition of hand over face occlusions,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
78598e7005f7c96d64cc47ff47e6f13ae52245b8,Hand2Face: Automatic synthesis and recognition of hand over face occlusions,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
7862f646d640cbf9f88e5ba94a7d642e2a552ec9,Being John Malkovich,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+78bfa428adb237c5ba85eda35e6a304b679c5c8c,Deep Micro-Dictionary Learning and Coding Network,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+78bfa428adb237c5ba85eda35e6a304b679c5c8c,Deep Micro-Dictionary Learning and Coding Network,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+78bdaca41440f03b4d18a4caf9f0dace9afa08b0,The University of Passau Open Emotion Recognition System for the Multimodal Emotion Challenge,University of Passau,"Chair of Complex & Intelligent Systems, University of Passau, Passau, Germany","Innstraße 41, 94032 Passau, Germany",48.56704660,13.45178350,edu,
+78bdaca41440f03b4d18a4caf9f0dace9afa08b0,The University of Passau Open Emotion Recognition System for the Multimodal Emotion Challenge,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+78bdaca41440f03b4d18a4caf9f0dace9afa08b0,The University of Passau Open Emotion Recognition System for the Multimodal Emotion Challenge,Northwestern Polytechnical University,Northwestern Polytechnical University,"西北工业大学 友谊校区, 127号, 友谊西路, 长安路, 碑林区 (Beilin), 西安市, 陕西省, 710072, 中国",34.24691520,108.91061982,edu,
+7869d8b9899226132d410ad6d409746bafe58f77,Biases Associated with Vulnerability to Bipolar Disorder,University of North Texas,University of North Texas,"University of North Texas, West Highland Street, Denton, Denton County, Texas, 76201, USA",33.20988790,-97.15147488,edu,
+78f08685d44b6c6f82983d9b0f9c6ac2f7203a5e,An Adaptive Ensemble Approach to Ambient Intelligence Assisted People Search,Tongji University,Tongji University,"同济大学, 1239, 四平路, 江湾, 虹口区, 上海市, 200092, 中国",31.28473925,121.49694909,edu,
+787fe79e880ecb78ec6df797add20a8f93878b68,Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns,South China University of Technology,South China University of Technology,"华南理工大学, 大学城中环东路, 广州大学城, 新造, 番禺区 (Panyu), 广州市, 广东省, 510006, 中国",23.05020420,113.39880323,edu,
+784ee59ea98a0878f1ba709f4385bffcdb4911d7,The iterative nature of person construal: Evidence from event-related potentials,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+784ee59ea98a0878f1ba709f4385bffcdb4911d7,The iterative nature of person construal: Evidence from event-related potentials,University of Missouri,University of Missouri,"L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA",38.92676100,-92.29193783,edu,
+78a7b042dfdc8c062a1ae9b4b93195b434e91aca,Face Recognition Using a Time-of-Flight Camera,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
78a4eb59ec98994bebcf3a5edf9e1d34970c45f6,Conveying shape and features with image-based relighting,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
78a4eb59ec98994bebcf3a5edf9e1d34970c45f6,Conveying shape and features with image-based relighting,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
78a4eb59ec98994bebcf3a5edf9e1d34970c45f6,Conveying shape and features with image-based relighting,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
78a4eb59ec98994bebcf3a5edf9e1d34970c45f6,Conveying shape and features with image-based relighting,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
78a4eb59ec98994bebcf3a5edf9e1d34970c45f6,Conveying shape and features with image-based relighting,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
78a4eb59ec98994bebcf3a5edf9e1d34970c45f6,Conveying shape and features with image-based relighting,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+78f4e29fafad7a0156cff6d14e9b92c8b8533d4c,Multiple Target Tracking Based on Undirected Hierarchical Relation Hypergraph,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
78174c2be084e67f48f3e8ea5cb6c9968615a42c,Periocular Recognition Using CNN Features Off-the-Shelf,Halmstad University,Halmstad University,"Högskolan i Halmstad, 3, Kristian IV:s väg, Larsfrid, Nyhem, Halmstad, Hallands län, Götaland, 301 18, Sverige",56.66340325,12.87929727,edu,
+78e9abfcee29491ffa53e7a988401ea06fbbe719,Deep Structured Learning for Visual Relationship Detection,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+78e9abfcee29491ffa53e7a988401ea06fbbe719,Deep Structured Learning for Visual Relationship Detection,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
780557daaa39a445b24c41f637d5fc9b216a0621,"Large Video Event Ontology Browsing, Search and Tagging (EventNet Demo)",Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
8ba67f45fbb1ce47a90df38f21834db37c840079,People search and activity mining in large-scale community-contributed photos,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
-8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion Recognition in the Wild using Deep Neural Networks and Bayesian Classifiers,University of Calabria,"Modeling, Electronics, and Systems, University of Calabria, Rende, Italy","Via Pietro Bucci, 87036 Arcavacata, Rende CS, Italy",39.36502160,16.22571770,edu,
-8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion Recognition in the Wild using Deep Neural Networks and Bayesian Classifiers,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
-8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion Recognition in the Wild using Deep Neural Networks and Bayesian Classifiers,University of Calabria,"Modeling, Electronics, and Systems, University of Calabria, Rende, Italy","Via Pietro Bucci, 87036 Arcavacata, Rende CS, Italy",39.36502160,16.22571770,edu,
-8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion Recognition in the Wild using Deep Neural Networks and Bayesian Classifiers,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
+8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion recognition in the wild using deep neural networks and Bayesian classifiers,University of Calabria,"Modeling, Electronics, and Systems, University of Calabria, Rende, Italy","Via Pietro Bucci, 87036 Arcavacata, Rende CS, Italy",39.36502160,16.22571770,edu,
+8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion recognition in the wild using deep neural networks and Bayesian classifiers,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
+8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion recognition in the wild using deep neural networks and Bayesian classifiers,University of Calabria,"Modeling, Electronics, and Systems, University of Calabria, Rende, Italy","Via Pietro Bucci, 87036 Arcavacata, Rende CS, Italy",39.36502160,16.22571770,edu,
+8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion recognition in the wild using deep neural networks and Bayesian classifiers,Plymouth University,Plymouth University,"Plymouth University, Portland Square, Barbican, Plymouth, South West England, England, PL4 6AP, UK",50.37552690,-4.13937687,edu,
8b7191a2b8ab3ba97423b979da6ffc39cb53f46b,Search pruning in video surveillance systems: Efficiency-reliability tradeoff,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+8b2dd5c61b23ead5ae5508bb8ce808b5ea266730,The intrinsic memorability of face photographs.,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
8bf243817112ac0aa1348b40a065bb0b735cdb9c,Learning a Repression Network for Precise Vehicle Search,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
8bfada57140aa1aa22a575e960c2a71140083293,Can we match Ultraviolet Face Images against their Visible Counterparts?,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
+8b0a4d41ee469547163ea154ad2b522d6d335671,The unique contributions of perceiver and target characteristics in person perception.,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
+8b0a4d41ee469547163ea154ad2b522d6d335671,The unique contributions of perceiver and target characteristics in person perception.,York University,York University,"York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada",43.77439110,-79.50481085,edu,
+8b0a4d41ee469547163ea154ad2b522d6d335671,The unique contributions of perceiver and target characteristics in person perception.,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+8b0a4d41ee469547163ea154ad2b522d6d335671,The unique contributions of perceiver and target characteristics in person perception.,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+8b0a4d41ee469547163ea154ad2b522d6d335671,The unique contributions of perceiver and target characteristics in person perception.,Ryerson University,Ryerson University,"Ryerson University, Gould Street, Downtown Yonge, Old Toronto, Toronto, Ontario, M5B 2G9, Canada",43.65815275,-79.37908010,edu,
8befcd91c24038e5c26df0238d26e2311b21719a,A Joint Sequence Fusion Model for Video Question Answering and Retrieval,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
+8bf05e179d50def46b008147fd3cce6c582a542f,Marginalizing Corrupted Features,Delft University of Technology,Delft University of Technology,"TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland",51.99882735,4.37396037,edu,
8bbbdff11e88327816cad3c565f4ab1bb3ee20db,Automatic Semantic Face Recognition,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+8b46df5e851e819473a726503a543a95e130e33d,The Role of Supervision and Geometry in Categorization1),Graz University of Technology,Graz University of Technology,"TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, Österreich",47.05821000,15.46019568,edu,
8bdf6f03bde08c424c214188b35be8b2dec7cdea,Inference Attacks Against Collaborative Learning,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
8b10383ef569ea0029a2c4a60cc2d8c87391b4db,Age classification using Radon transform and entropy based scaling SVM,University of Dundee,University of Dundee,"University of Dundee, Park Wynd, Law, Dundee, Dundee City, Scotland, DD1 4HN, UK",56.45796755,-2.98214831,edu,
8b30259a8ab07394d4dac971f3d3bd633beac811,Representing Sets of Instances for Visual Recognition,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
8b61fdc47b5eeae6bc0a52523f519eaeaadbc8c8,Temporal Perceptive Network for Skeleton-Based Action Recognition,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
8b61fdc47b5eeae6bc0a52523f519eaeaadbc8c8,Temporal Perceptive Network for Skeleton-Based Action Recognition,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+8b302c0edefa8f6a2ce6a41c32fab0f1ef36e523,"Large-scale, Cross-lingual Trend Mining and Summarisation of Real-time Media Streams D3.1.2 Regression models of trends Tools for Mining Non-stationary Data: functional prototype",University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+8b302c0edefa8f6a2ce6a41c32fab0f1ef36e523,"Large-scale, Cross-lingual Trend Mining and Summarisation of Real-time Media Streams D3.1.2 Regression models of trends Tools for Mining Non-stationary Data: functional prototype",University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+8b302c0edefa8f6a2ce6a41c32fab0f1ef36e523,"Large-scale, Cross-lingual Trend Mining and Summarisation of Real-time Media Streams D3.1.2 Regression models of trends Tools for Mining Non-stationary Data: functional prototype",University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+8b2d224c8b69191c02dce750257c39d46b1c4a7b,A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
+8b2d224c8b69191c02dce750257c39d46b1c4a7b,A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators,Fudan University,Fudan University,"复旦大学, 220, 邯郸路, 五角场街道, 杨浦区, 上海市, 200433, 中国",31.30104395,121.50045497,edu,
8b19efa16a9e73125ab973429eb769d0ad5a8208,SCAR: Dynamic Adaptation for Person Detection and Persistence Analysis in Unconstrained Videos,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
8b6fded4d08bf0b7c56966b60562ee096af1f0c4,A Neural Network based Facial Expression Recognition using Fisherface,Semarang State University,Semarang State University,"Mandiri University, Jalan Tambora, RW 10, Tegalsari, Candisari, Semarang, Jawa Tengah, 50252, Indonesia",-7.00349485,110.41774949,edu,
8b2704a5218a6ef70e553eaf0a463bd55129b69d,Geometric Feature-Based Facial Expression Recognition in Image Sequences Using Multi-Class AdaBoost and Support Vector Machines,Chonbuk National University,Chonbuk National University,"전북대학교, 567, 백제대로, 금암동, 덕진구, 전주시, 전북, 54896, 대한민국",35.84658875,127.13501330,edu,
+8b162c2a15bc7aa56cdc1be9773611bc21536782,On Automating Basic Data Curation Tasks,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+8b162c2a15bc7aa56cdc1be9773611bc21536782,On Automating Basic Data Curation Tasks,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+8b162c2a15bc7aa56cdc1be9773611bc21536782,On Automating Basic Data Curation Tasks,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+8b162c2a15bc7aa56cdc1be9773611bc21536782,On Automating Basic Data Curation Tasks,University of New South Wales,University of New South Wales,"UNSW, International Square, UNSW, Kensington, Bay Gardens, Sydney, Randwick, NSW, 2033, Australia",-33.91758275,151.23124025,edu,
+8b68db1af010f36f7e9d174d6ca0fcb24c1049ee,Part I : Computation of Invariant Representations in Visual Cortex and in Deep Convolutional Architectures,McGovern Institute for Brain Research,McGovern Institute for Brain Research,"McGovern Institute for Brain Research (MIT), Main Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.36262950,-71.09144810,edu,
+8b68db1af010f36f7e9d174d6ca0fcb24c1049ee,Part I : Computation of Invariant Representations in Visual Cortex and in Deep Convolutional Architectures,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+8b266e68cc71f98ee42b04dc8f3e336c47f199cb,Learning Face Age Progression: A Pyramid Architecture of GANs,Beihang University,Beihang University,"北京航空航天大学, 37, 学院路, 五道口, 后八家, 海淀区, 100083, 中国",39.98083330,116.34101249,edu,
+8b266e68cc71f98ee42b04dc8f3e336c47f199cb,Learning Face Age Progression: A Pyramid Architecture of GANs,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
8b2e3805b37c18618b74b243e7a6098018556559,Ariational a Utoencoder with D Eep F Eature C Onsistent and G Enerative a Dversar - Ial T Raining,University of Nottingham,University of Nottingham,"University of Nottingham, Lenton Abbey, Wollaton, City of Nottingham, East Midlands, England, UK",52.93874280,-1.20029569,edu,
8b2e3805b37c18618b74b243e7a6098018556559,Ariational a Utoencoder with D Eep F Eature C Onsistent and G Enerative a Dversar - Ial T Raining,Shenzhen University,Shenzhen University,"深圳大学, 3688, 南海大道, 蛇口, 同乐村, 南山区, 深圳市, 广东省, 518060, 中国",22.53521465,113.93159110,edu,
+8b4a10cfa107f3c6546caa32e5012d342d02212a,Learning and Exploiting Camera Geometry for Computer Vision,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
8b74252625c91375f55cbdd2e6415e752a281d10,Using Convolutional 3D Neural Networks for User-independent continuous gesture recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
8b74252625c91375f55cbdd2e6415e752a281d10,Using Convolutional 3D Neural Networks for User-independent continuous gesture recognition,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
8b74252625c91375f55cbdd2e6415e752a281d10,Using Convolutional 3D Neural Networks for User-independent continuous gesture recognition,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+8b5122ea59d8d7f70e344ffb2553537b5ad07dd5,Image Translation by Domain-Adversarial Training,Zhejiang University of Technology,Zhejiang University of Technology,"浙江工业大学, 潮王路, 朝晖街道, 杭州市 Hangzhou, 浙江省, 310014, 中国",30.29315340,120.16204580,edu,
+8b0af7d056e7e8a5ef2bf1278fa0740771e23401,Correntropy Induced L2 Graph for Robust Subspace Clustering,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+8b0af7d056e7e8a5ef2bf1278fa0740771e23401,Correntropy Induced L2 Graph for Robust Subspace Clustering,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+8b0af7d056e7e8a5ef2bf1278fa0740771e23401,Correntropy Induced L2 Graph for Robust Subspace Clustering,Sun Yat-Sen University,Sun Yat-Sen University,"中大, 新港西路, 龙船滘, 康乐, 海珠区 (Haizhu), 广州市, 广东省, 510105, 中国",23.09461185,113.28788994,edu,
+8b0af7d056e7e8a5ef2bf1278fa0740771e23401,Correntropy Induced L2 Graph for Robust Subspace Clustering,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+8bad9d970664d4a9874ea71de9cc7b4360ba04ab,Person Independent Facial Expression Recognition Using 3D Facial Feature Positions,Eastern Mediterranean University,Eastern Mediterranean University,"Eastern Mediterranean University (EMU) - Stadium, Nehir Caddesi, Gazimağusa, Αμμόχωστος - Mağusa, Kuzey Kıbrıs, 99450, Κύπρος - Kıbrıs",35.14479945,33.90492318,edu,
+8b2064a6a535cd2b49e348560c4f9e2c3a8f4748,A Method Based on Convex Cone Model for Image-Set Classification With CNN Features,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
8b38124ff02a9cf8ad00de5521a7f8a9fa4d7259,Real-time 3 D Face Fitting and Texture Fusion on Inthe-wild Videos,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
8b38124ff02a9cf8ad00de5521a7f8a9fa4d7259,Real-time 3 D Face Fitting and Texture Fusion on Inthe-wild Videos,Reutlingen University,Reutlingen University,"Campus Hohbuch, Campus Hochschule Reutlingen, Reutlingen, Landkreis Reutlingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72762, Deutschland",48.48187645,9.18682404,edu,
-134f1cee8408cca648d8b4ca44b38b0a7023af71,Partially Shared Multi-Task Convolutional Neural Network with Local Constraint for Face Attribute Learning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+8ba606d7667c50054d74083867230abbed755574,"ReXCam: Resource-Efficient, Cross-Camera Video Analytics at Enterprise Scale",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+8ba606d7667c50054d74083867230abbed755574,"ReXCam: Resource-Efficient, Cross-Camera Video Analytics at Enterprise Scale",Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+8bc814c9653ef7fe248986788dd2a53375317a3a,Trace Ratio Criterion for Feature Selection,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+8bc814c9653ef7fe248986788dd2a53375317a3a,Trace Ratio Criterion for Feature Selection,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+13f74a94d492919a1ff13af16e2df2ab1bedf04a,Selecting the Best Performing Rotation Invariant Patterns in Local Binary/Ternary Patterns,University of Bologna,Università di Bologna,"Via Zamboni, 33, 40126 Bologna BO, Italy",44.49623180,11.35415700,edu,
+13af83892724343cfdf88debbf00ea1343a10db1,Impact of involuntary subject movement on 3D face scans,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+13af83892724343cfdf88debbf00ea1343a10db1,Impact of involuntary subject movement on 3D face scans,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+13a94d8f5eafbbf411c9a70e1b30937a532664ef,Non-rigid registration of 3D surfaces by deformable 2D triangular meshes,Bogazici University,Bogazici University,"Boğaziçi Üniversitesi Kuzey Yerleşkesi, Okulaltı 1. Sokak, Rumelihisarı, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34467, Türkiye",41.08688410,29.04413167,edu,
+134f1cee8408cca648d8b4ca44b38b0a7023af71,Partially Shared MultiTask Convolutional Neural Network with Local Constraint for Face Attribute Learning,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+13d53896f0ee30121c8dc75dcbfd5ff6c722199b,Building Context-Aware Object Detectors: Tying Objects and Context in a loop,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+13d6dde8767ac7176dcd6d4367974292bc627863,Multi-attribute Queries: To Merge or Not to Merge?,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+13d6dde8767ac7176dcd6d4367974292bc627863,Multi-attribute Queries: To Merge or Not to Merge?,Sharif University of Technology,Sharif University of Technology,"دانشگاه صنعتی شریف, خیابان آزادی, زنجان, منطقه ۹ شهر تهران, تهران, بخش مرکزی شهرستان تهران, شهرستان تهران, استان تهران, 14588, ایران",35.70362270,51.35125097,edu,
+13d6dde8767ac7176dcd6d4367974292bc627863,Multi-attribute Queries: To Merge or Not to Merge?,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
13719bbb4bb8bbe0cbcdad009243a926d93be433,Deep LDA-Pruned Nets for Efficient Facial Gender Classification,McGill University,McGill University,"McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montréal, Agglomération de Montréal, Montréal (06), Québec, H3A 3P8, Canada",45.50397610,-73.57496870,edu,
+1328c0a8a357b303f6e853581360370ef2975612,Obtaining MPEG-4 compliant animatable 3D face models by using TPS method,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+133b0d480a8fac7c7e0c7511b5bdb0dc7d387d42,This Hand Is My Hand: A Probabilistic Approach to Hand Disambiguation in Egocentric Video,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+133b0d480a8fac7c7e0c7511b5bdb0dc7d387d42,This Hand Is My Hand: A Probabilistic Approach to Hand Disambiguation in Egocentric Video,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
1329206dbdb0a2b9e23102e1340c17bd2b2adcf5,Part-Based R-CNNs for Fine-Grained Category Detection,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
13bda03fc8984d5943ed8d02e49a779d27c84114,Efficient object detection using cascades of nearest convex model classifiers,Eskisehir Osmangazi University,Eskisehir Osmangazi University,"Eskişehir Osmangazi Üniversitesi Meşelik Yerleşkesi, Kütahya-Eskişehir yolu, Sazova Mahallesi, Karagözler, Tepebaşı, Eskişehir, İç Anadolu Bölgesi, 26160, Türkiye",39.74875160,30.47653071,edu,
+1337acf12805a24968c0518e695ca94f103e630f,"VARADARAJAN ET AL.,: A TOPIC MODEL APPROACH TO CLASSIFY FOOTBALL PLAYS 1 A Topic Model Approach to Represent and Classify American Football Plays","University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
13a994d489c15d440c1238fc1ac37dad06dd928c,Learning Discriminant Face Descriptor for Face Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+13c0c418df650ad94ac368c81e2133ec9e166381,Mid-level deep pattern mining,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+131125a5aadb48ec3eceb404cedbff713c401feb,Building a Large-scale Multimodal Knowledge Base for Visual Question Answering,University of Wisconsin Madison,University of Wisconsin Madison,"University of Wisconsin-Madison, Marsh Lane, Madison, Dane County, Wisconsin, 53705-2221, USA",43.07982815,-89.43066425,edu,
+131125a5aadb48ec3eceb404cedbff713c401feb,Building a Large-scale Multimodal Knowledge Base for Visual Question Answering,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
131178dad3c056458e0400bed7ee1a36de1b2918,Visual Reranking through Weakly Supervised Multi-graph Learning,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
131178dad3c056458e0400bed7ee1a36de1b2918,Visual Reranking through Weakly Supervised Multi-graph Learning,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
131178dad3c056458e0400bed7ee1a36de1b2918,Visual Reranking through Weakly Supervised Multi-graph Learning,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
132527383890565d18f1b7ad50d76dfad2f14972,Facial Expression Classification Using PCA and Hierarchical Radial Basis Function Network,National Taipei University,National Taipei University,"國立臺北大學, 151, 大學路, 龍恩里, 隆恩埔, 三峽區, 新北市, 23741, 臺灣",24.94314825,121.36862979,edu,
13604bbdb6f04a71dea4bd093794e46730b0a488,Robust Loss Functions under Label Noise for Deep Neural Networks,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
13604bbdb6f04a71dea4bd093794e46730b0a488,Robust Loss Functions under Label Noise for Deep Neural Networks,Indian Institute of Science Bangalore,Indian Institute of Science Bangalore,"IISc, Gulmohar Marg, RMV Stage II - 1st Block, Aramane Nagara Ward, West Zone, Bengaluru, Bangalore Urban, Karnataka, 560012, India",13.02223470,77.56718325,edu,
+1362b43a76412ed9ac67fd182a72b9457cae5aed,Delving into egocentric actions,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
137aa2f891d474fce1e7a1d1e9b3aefe21e22b34,Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
13b1b18b9cfa6c8c44addb9a81fe10b0e89db32a,A Hierarchical Deep Temporal Model for Group Activity Recognition,Simon Fraser University,Simon Fraser University,"SFU Burnaby, South Campus Road, Barnet, Burnaby, Metro Vancouver, British Columbia, V5A 4X6, Canada",49.27674540,-122.91777375,edu,
+133477ccff666305d183cf1c35dcee40d0f2955a,Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+133477ccff666305d183cf1c35dcee40d0f2955a,Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+133477ccff666305d183cf1c35dcee40d0f2955a,Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation,National Chiao Tung University,National Chiao Tung University,"NCTU;交大;交通大學;交大光復校區;交通大學光復校區, 1001, 大學路, 光明里, 赤土崎, 東區, 新竹市, 30010, 臺灣",24.78676765,120.99724412,edu,
1329bcac5ebd0b08ce33ae1af384bd3e7a0deaca,Dataset Issues in Object Recognition,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
1329bcac5ebd0b08ce33ae1af384bd3e7a0deaca,Dataset Issues in Object Recognition,Oxford University,Oxford University,"University College, Logic Lane, Grandpont, Oxford, Oxon, South East, England, OX1 4EX, UK",51.75208490,-1.25166460,edu,
1329bcac5ebd0b08ce33ae1af384bd3e7a0deaca,Dataset Issues in Object Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
@@ -4389,12 +12290,27 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 13c250fb740cb5616aeb474869db6ab11560e2a6,A thesis submitted in conformity with the requirements,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
13940d0cc90dbf854a58f92d533ce7053aac024a,Local learning by partitioning,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
13940d0cc90dbf854a58f92d533ce7053aac024a,Local learning by partitioning,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+13ac93950986fc023d45e9647197d80b86fa4867,Subspace clustering applied to face images,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
131bfa2ae6a04fd3b921ccb82b1c3f18a400a9c1,Elastic Graph Matching versus Linear Subspace Methods for Frontal Face Verification,Aristotle University of Thessaloniki,Aristotle University of Thessaloniki,"Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Εγνατία, Σαράντα Εκκλησίες, Ευαγγελίστρια, Θεσσαλονίκη, Δήμος Θεσσαλονίκης, Περιφερειακή Ενότητα Θεσσαλονίκης, Περιφέρεια Κεντρικής Μακεδονίας, Μακεδονία - Θράκη, 54124, Ελλάδα",40.62984145,22.95889350,edu,
+137239cd29634465f35ce261718efece57cfc617,Video Surveillance Classification-based Multiple Instance Object Retrieval: Evaluation and Dataset,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
1389ba6c3ff34cdf452ede130c738f37dca7e8cb,A Convolution Tree with Deconvolution Branches: Exploiting Geometric Relationships for Single Shot Keypoint Detection,University of Maryland College Park,University of Maryland College Park,"University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA",38.99203005,-76.94610290,edu,
+131e9edbe4b0322a467b7e8c35f6b0c0ca750e21,Contextual Action Recognition with R*CNN,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+1395f0561db13cad21a519e18be111cbe1e6d818,Semantic segmentation using regions and parts,Facebook,Facebook,"250 Bryant St, Mountain View, CA 94041, USA",37.39367170,-122.08072620,company,"Facebook, Mountain View, CA"
13aef395f426ca8bd93640c9c3f848398b189874,1 Image Preprocessing and Complete 2 DPCA with Feature Extraction for Gender Recognition NSF REU 2017 : Statistical Learning and Data Mining,University of North Carolina Wilmington,University of North Carolina Wilmington,"Kenan House, 1705, Market Street, Wilmington, New Hanover County, North Carolina, 28403, USA",34.23755810,-77.92701290,edu,
+133f1f2679892d408420d8092283539010723359,What Makes for Effective Detection Proposals?,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
13be4f13dac6c9a93f969f823c4b8c88f607a8c4,Families in the Wild (FIW): Large-Scale Kinship Image Database and Benchmarks,Northeastern University,Northeastern University,"Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA",42.33836680,-71.08793524,edu,
+136112d29f8abfd8804f9b9c0e15d00f7c013c6c,Space-time tree ensemble for action recognition,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+136112d29f8abfd8804f9b9c0e15d00f7c013c6c,Space-time tree ensemble for action recognition,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
+135c957f6a80f250507c7707479e584c288f430f,Image-Based Synthesis and Re-synthesis of Viewpoints Guided by 3D Models,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+1343f43e231d793a0bb45eb13ae2560e99aff6e1,Measuring Image Distances via Embedding in a Semantic Manifold,Dartmouth College,Dartmouth College,"Dartmouth College, Tuck Mall, Hanover, Grafton County, New Hampshire, 03755, USA",43.70479270,-72.29259090,edu,
+13ea9a2ed134a9e238d33024fba34d3dd6a010e0,SVDNet for Pedestrian Retrieval,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+13ea9a2ed134a9e238d33024fba34d3dd6a010e0,SVDNet for Pedestrian Retrieval,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+131e00d1296a952ed236bc264dc16f7e486c6e79,Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+131e00d1296a952ed236bc264dc16f7e486c6e79,Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
1316296fae6485c1510f00b1b57fb171b9320ac2,FaceID-GAN: Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
1316296fae6485c1510f00b1b57fb171b9320ac2,FaceID-GAN: Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+132045bbf158060cbbb20f86f212ce89c4358eda,Role of Color in Face Recognition A Comparison Study Using Traditional and New Face Recognition Algorithms,Concordia University,Concordia University,"Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA",45.57022705,-122.63709346,edu,
+139ee1b1d98e7ac9d659a5d1bbe8c75588539b29,Identification of EFHC2 as a quantitative trait locus for fear recognition in Turner syndrome.,University College London,University College London,"UCL Institute of Education, 20, Bedford Way, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1H 0AL, UK",51.52316070,-0.12820370,edu,
7f57e9939560562727344c1c987416285ef76cda,Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
7f57e9939560562727344c1c987416285ef76cda,Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
7f57e9939560562727344c1c987416285ef76cda,Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
@@ -4402,44 +12318,90 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 7fc5b6130e9d474dfb49d9612b6aa0297d481c8e,Dimensionality Reduction on Grassmannian via Riemannian Optimization: A Generalized Perspective,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
7fc5b6130e9d474dfb49d9612b6aa0297d481c8e,Dimensionality Reduction on Grassmannian via Riemannian Optimization: A Generalized Perspective,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
7f21a7441c6ded38008c1fd0b91bdd54425d3f80,Real Time System for Facial Analysis,Tampere University of Technology,Tampere University of Technology,"TTY, 10, Korkeakoulunkatu, Finninmäki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, Länsi- ja Sisä-Suomen aluehallintovirasto, Länsi-Suomi, Manner-Suomi, 33720, Suomi",61.44964205,23.85877462,edu,
+7fbdb1d05a34d28b7f93544248edf7a2e0b8cd15,POL-LWIR Vehicle Detection: Convolutional Neural Networks Meet Polarised Infrared Sensors,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+7ffef9f26c39377ee937d29b8990580266a7a8a5,Deep Metric Learning with Hierarchical Triplet Loss,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
7fce5769a7d9c69248178989a99d1231daa4fce9,Towards Face Recognition Using Eigenface,King Faisal University,King Faisal University,"University of Dammam, King Faisal Rd, العقربية, الخبر, المنطقة الشرقية, ٣١٩٥٢, السعودية",26.39777800,50.18305600,edu,
7fa2605676c589a7d1a90d759f8d7832940118b5,A new approach to clothing classification using mid-level layers,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
7fb5006b6522436ece5bedf509e79bdb7b79c9a7,Multi-Task Convolutional Neural Network for Face Recognition,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+7fac20f3908c69bd336ea252e28c79f5abaa6dbe,Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+7f05df12dff3defee495507abd4870a0a30c3590,Placing Images with Refined Language Models and Similarity Search with PCA-reduced VGG Features,Information Technologies Institute,Information Technologies Institute,"公益財団法人九州先端科学技術研究所, Fukuoka SRP Center Building 7F, 百道ランプ下り入り口, 早良区, 福岡市, 福岡県, 九州地方, 814-0001, 日本",33.59345390,130.35578370,edu,
+7f44f2d7b4a84b6d87dd6f7089ce3ee1e6359272,What's in the Chinese Babyface? Cultural Differences in Understanding the Babyface,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+7f44f2d7b4a84b6d87dd6f7089ce3ee1e6359272,What's in the Chinese Babyface? Cultural Differences in Understanding the Babyface,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+7f44f2d7b4a84b6d87dd6f7089ce3ee1e6359272,What's in the Chinese Babyface? Cultural Differences in Understanding the Babyface,Kobe University,Kobe University,"神戸大学, 灘三田線, 灘区, 神戸市, 兵庫県, 近畿地方, 657-00027, 日本",34.72757140,135.23710000,edu,
7fa3d4be12e692a47b991c0b3d3eba3a31de4d05,Efficient Online Spatio-Temporal Filtering for Video Event Detection,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
7fa3d4be12e692a47b991c0b3d3eba3a31de4d05,Efficient Online Spatio-Temporal Filtering for Video Event Detection,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
7fa3d4be12e692a47b991c0b3d3eba3a31de4d05,Efficient Online Spatio-Temporal Filtering for Video Event Detection,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+7fda1edac608bc67e55ac3d7c9dc5a542d8f8aee,Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
7f445191fa0475ff0113577d95502a96dc702ef9,Towards an Unequivocal Representation of Actions,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
7f445191fa0475ff0113577d95502a96dc702ef9,Towards an Unequivocal Representation of Actions,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
7f445191fa0475ff0113577d95502a96dc702ef9,Towards an Unequivocal Representation of Actions,University of Bristol,University of Bristol,"Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK",51.45848370,-2.60977520,edu,
+7fa5ede4a34dbe604ce317d529eed78db6642bc0,Soft Proposal Networks for Weakly Supervised Object Localization,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+7fa5ede4a34dbe604ce317d529eed78db6642bc0,Soft Proposal Networks for Weakly Supervised Object Localization,Duke University,Duke University,"Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA",35.99905220,-78.92906290,edu,
7f82f8a416170e259b217186c9e38a9b05cb3eb4,Multi-Attribute Robust Component Analysis for Facial UV Maps,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
7f82f8a416170e259b217186c9e38a9b05cb3eb4,Multi-Attribute Robust Component Analysis for Facial UV Maps,Middlesex University,Middlesex University,"Middlesex University, Greyhound Hill, Hendon, The Hyde, London Borough of Barnet, London, Greater London, England, NW4 4JP, UK",51.59029705,-0.22963221,edu,
7f82f8a416170e259b217186c9e38a9b05cb3eb4,Multi-Attribute Robust Component Analysis for Facial UV Maps,University of London,University of London,"Birkbeck College, Malet Street, Holborn, Bloomsbury, London Borough of Camden, London, Greater London, England, WC1E 7HX, UK",51.52176680,-0.13019072,edu,
+7fd4e67938d02452e256c69822285778f95eb045,Genetic and Evolutionary Feature Extraction via X-TOOLSS,Clemson University,Clemson University,"Clemson University, Old Stadium Road, Clemson Heights, Pickens County, South Carolina, 29631, USA",34.66869155,-82.83743476,edu,
7fab17ef7e25626643f1d55257a3e13348e435bd,Age Progression/Regression by Conditional Adversarial Autoencoder,University of Tennessee,University of Tennessee,"University of Tennessee, Melrose Avenue, Fort Sanders, Knoxville, Knox County, Tennessee, 37916, USA",35.95424930,-83.93073950,edu,
7f6599e674a33ed64549cd512ad75bdbd28c7f6c,Kernel Alignment Inspired Linear Discriminant Analysis,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+7f33a5fcc5db4625c66972f0e6f06540b64d4f1e,Image Surveillance Assistant Architecture: Status and Planned Extensions,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+7f33a5fcc5db4625c66972f0e6f06540b64d4f1e,Image Surveillance Assistant Architecture: Status and Planned Extensions,Naval Research Laboratory,Naval Research Laboratory,"Naval Research Laboratory Post Office, 4555, Overlook Avenue Southwest, Washington, D.C., 20375, USA",38.82313810,-77.01789020,mil,
7f9260c00a86a0d53df14469f1fa10e318ee2a3c,How iris recognition works,University of Cambridge,University of Cambridge,"Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK",52.17638955,0.14308882,edu,
7f2a4cd506fe84dee26c0fb41848cb219305173f,Face Detection and Pose Estimation Based on Evaluating Facial Feature Selection,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+7f836c047bc86d52e3a28098b53311cb2186acaa,Deep Compositional Question Answering with Neural Module Networks,"University of California, Berkeley","University of California, Berkeley","Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA",37.86871260,-122.25586815,edu,
7fd700f4a010d765c506841de9884df394c1de1c,Correlational spectral clustering,Max Planck Institute for Biological Cybernetics,Max Planck Institute for Biological Cybernetics,"Max-Planck-Institut für Biologische Kybernetik, 8, Max-Planck-Ring, Max-Planck-Institut, Wanne, Tübingen, Landkreis Tübingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72076, Deutschland",48.53691250,9.05922533,edu,
+7f201b4226d62bf449a68ebcc159acf8b95289be,PinterNet: A thematic label curation tool for large image datasets,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
7f59657c883f77dc26393c2f9ed3d19bdf51137b,Facial expression recognition for multiplayer online games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
7f59657c883f77dc26393c2f9ed3d19bdf51137b,Facial expression recognition for multiplayer online games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
7f59657c883f77dc26393c2f9ed3d19bdf51137b,Facial expression recognition for multiplayer online games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
7f59657c883f77dc26393c2f9ed3d19bdf51137b,Facial expression recognition for multiplayer online games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
7f59657c883f77dc26393c2f9ed3d19bdf51137b,Facial expression recognition for multiplayer online games,University of Wollongong,University of Wollongong,"University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia",-34.40505545,150.87834655,edu,
+7fb74f5abab4830e3cdaf477230e5571d9e3ca57,Polyhedral Conic Classifiers for Visual Object Detection and Classification,Eskisehir Osmangazi University,Eskisehir Osmangazi University,"Eskişehir Osmangazi Üniversitesi Meşelik Yerleşkesi, Kütahya-Eskişehir yolu, Sazova Mahallesi, Karagözler, Tepebaşı, Eskişehir, İç Anadolu Bölgesi, 26160, Türkiye",39.74875160,30.47653071,edu,
7f23a4bb0c777dd72cca7665a5f370ac7980217e,Improving Person Re-identification by Attribute and Identity Learning,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+7ff18900bf1d8acbcb81e2f6d8e77fe95e1ddbd0,CoDraw: Visual Dialog for Collaborative Drawing,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
7fc3442c8b4c96300ad3e860ee0310edb086de94,Similarity Scores Based on Background Samples,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
7fc3442c8b4c96300ad3e860ee0310edb086de94,Similarity Scores Based on Background Samples,Open University of Israel,Open University of Israel,"האוניברסיטה הפתוחה, 15, אבא חושי, חיפה, גבעת דאונס, חיפה, מחוז חיפה, NO, ישראל",32.77824165,34.99565673,edu,
7f8d44e7fd2605d580683e47bb185de7f9ea9e28,Predicting Personal Traits from Facial Images Using Convolutional Neural Networks Augmented with Facial Landmark Information,Hebrew University of Jerusalem,The Hebrew University of Jerusalem,"האוניברסיטה העברית בירושלים, Reagan Plaza, קרית מנחם בגין, הר הצופים, ירושלים, מחוז ירושלים, NO, ישראל",31.79185550,35.24472300,edu,
7f8d44e7fd2605d580683e47bb185de7f9ea9e28,Predicting Personal Traits from Facial Images Using Convolutional Neural Networks Augmented with Facial Landmark Information,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
7f8d44e7fd2605d580683e47bb185de7f9ea9e28,Predicting Personal Traits from Facial Images Using Convolutional Neural Networks Augmented with Facial Landmark Information,Cambridge University,Cambridge University,"University, Cambridge Road, Old Portsmouth, Portsmouth, South East, England, PO1 2HB, UK",50.79440260,-1.09717480,edu,
+7fd73c91462153e16d207faa8ec0e3f507c72ae5,Multi-Sample Fusion with Template Protection,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+7fbf1885f27fb72d5e553c4a2147375f928465ee,Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+7fbf1885f27fb72d5e553c4a2147375f928465ee,Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
+7fad07a6cf4c0985c7146e12d8e6639234e447fd,Graph Distillation for Action Detection with Privileged Modalities,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
7f1f3d7b1a4e7fc895b77cb23b1119a6f13e4d3a,Multi-subregion based probabilistic approach toward pose-invariant face recognition,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
7fcfd72ba6bc14bbb90b31fe14c2c77a8b220ab2,Robust FEC-CNN: A High Accuracy Facial Landmark Detection System,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
7fcfd72ba6bc14bbb90b31fe14c2c77a8b220ab2,Robust FEC-CNN: A High Accuracy Facial Landmark Detection System,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+7fb8d9c36c23f274f2dd84945dd32ec2cc143de1,Semantic Segmentation with Second-Order Pooling,Institute of Systems and Robotics,Institute of Systems and Robotics,"Institut für Robotik und Kognitive Systeme, 160, Ratzeburger Allee, Strecknitz, Sankt Jürgen, Strecknitz, Lübeck, Schleswig-Holstein, 23562, Deutschland",53.83383710,10.70359390,edu,
+7fb8d9c36c23f274f2dd84945dd32ec2cc143de1,Semantic Segmentation with Second-Order Pooling,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
+7fa4e972da46735971aad52413d17c4014c49e6e,How to Train Triplet Networks with 100K Identities?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+7fa4e972da46735971aad52413d17c4014c49e6e,How to Train Triplet Networks with 100K Identities?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+7fa4e972da46735971aad52413d17c4014c49e6e,How to Train Triplet Networks with 100K Identities?,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+7f310839e62c2623f6267b533047b323f61d2b27,Learning to Combine Kernels for Object Categorization,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+7f310839e62c2623f6267b533047b323f61d2b27,Learning to Combine Kernels for Object Categorization,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+7f310839e62c2623f6267b533047b323f61d2b27,Learning to Combine Kernels for Object Categorization,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
+7f310839e62c2623f6267b533047b323f61d2b27,Learning to Combine Kernels for Object Categorization,Harbin Institute of Technology,Harbin Institute of Technology,"哈尔滨工业大学, 司令街, 南岗区, 哈尔滨市 / Harbin, 黑龙江省, 150000, 中国",45.74139210,126.62552755,edu,
7f205b9fca7e66ac80758c4d6caabe148deb8581,A A Survey on Mobile Social Signal Processing,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
7f205b9fca7e66ac80758c4d6caabe148deb8581,A A Survey on Mobile Social Signal Processing,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
7f205b9fca7e66ac80758c4d6caabe148deb8581,A A Survey on Mobile Social Signal Processing,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
7f205b9fca7e66ac80758c4d6caabe148deb8581,A A Survey on Mobile Social Signal Processing,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
7fc76446d2b11fc0479df6e285723ceb4244d4ef,Laplacian MinMax Discriminant Projection and its Applications,Zhejiang Normal University,Zhejiang Normal University,"浙江师范大学, 688, 迎宾大道, 柳湖花园, 金华市, 婺城区 (Wucheng), 金华市 / Jinhua, 浙江省, 321004, 中国",29.13646725,119.63768652,edu,
7fc76446d2b11fc0479df6e285723ceb4244d4ef,Laplacian MinMax Discriminant Projection and its Applications,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+7a04b5db3f589ac857b51effa1be3eae7fa8dd4e,Abnormal spatiotemporal processing of emotional facial expressions in childhood autism: dipole source analysis of event-related potentials.,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+7a04b5db3f589ac857b51effa1be3eae7fa8dd4e,Abnormal spatiotemporal processing of emotional facial expressions in childhood autism: dipole source analysis of event-related potentials.,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+7a04b5db3f589ac857b51effa1be3eae7fa8dd4e,Abnormal spatiotemporal processing of emotional facial expressions in childhood autism: dipole source analysis of event-related potentials.,University of Hong Kong,University of Hong Kong,"海洋科學研究所 The Swire Institute of Marine Science, 鶴咀道 Cape D'Aguilar Road, 鶴咀低電台 Cape D'Aguilar Low-Level Radio Station, 石澳 Shek O, 芽菜坑村 Nga Choy Hang Tsuen, 南區 Southern District, 香港島 Hong Kong Island, HK, 中国",22.20814690,114.25964115,edu,
+7a4ea124a971bdda4acea4b539092d4d22c0e169,Anticipating Traffic Accidents with Adaptive Loss and Large-scale Incident DB,Keio University,Keio University,"綱島市民の森, けつわり坂, 港北区, 横浜市, 神奈川県, 関東地方, 223-0053, 日本",35.54169690,139.63471840,edu,
+7ab02556d18d116228a964e38b7f454cf9f2b189,Findings of the E2E NLG Challenge,Heriot-Watt University,Heriot-Watt University,"Heriot-Watt University - Edinburgh Campus, Third Gait, Currie, Gogarbank, City of Edinburgh, Scotland, EH14 4AS, UK",55.91029135,-3.32345777,edu,
+7a7b386385ec5a458c6d45f58c399941c2f054d6,3D Model-Based Face Recognition in Video,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+7ab90189c9c66298c900fde3de4c8d77fd035d80,Long-Term On-Board Prediction of Pedestrians in Traffic Scenes,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+7a7b84b8d8c1edb07f16180ef2c243ef30d85e1d,TrustFA: TrustZone-Assisted Facial Authentication on Smartphone,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
+7a2cee9a210e7b418fa6169f8cf027f7993a3ee5,LETTER TO THE EDITOR Spontaneous versus deliberate vicarious representations: different routes to empathy in psychopathy and autism,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
+7a2cee9a210e7b418fa6169f8cf027f7993a3ee5,LETTER TO THE EDITOR Spontaneous versus deliberate vicarious representations: different routes to empathy in psychopathy and autism,University of Birmingham,University of Birmingham,"University of Birmingham Edgbaston Campus, Ring Road North, Bournbrook, Birmingham, West Midlands Combined Authority, West Midlands, England, B15 2TP, UK",52.45044325,-1.93196134,edu,
7a9c317734acaf4b9bd8e07dd99221c457b94171,Lorentzian Discriminant Projection and Its Applications,Dalian University of Technology,Dalian University of Technology,"大连理工大学, 红凌路, 甘井子区, 凌水镇, 甘井子区 / Ganjingzi, 大连市 / Dalian, 辽宁省, 116023, 中国",38.88140235,121.52281098,edu,
+7a39a3ca168dfebb2e2d55b3fca0f750b32896da,BiSeNet: Bilateral Segmentation Network for Real-Time Semantic Segmentation,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+7a693500b5ac96f2f439989baf250e3305f69fa5,Bi-Sparsity Pursuit: A Paradigm for RobustSubspace Recovery,North Carolina State University,North Carolina State University,"North Carolina State University, Oval Drive, West Raleigh, Raleigh, Wake County, North Carolina, 27695, USA",35.77184965,-78.67408695,edu,
+7acbc7edfeee7c3a19b6f204e1c290172150db5c,On the Effects of Illumination Normalization with LBP-Based Watchlist Screening,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+7a6bacdbc04d06842dd68d27b9f065f472b5aa1f,Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning,Bar-Ilan University,Bar-Ilan University,"אוניברסיטת בר אילן, כביש גהה, גבעת שמואל, קריית מטלון, גבעת שמואל, מחוז תל אביב, NO, ישראל",32.06932925,34.84334339,edu,
+7af8fa8897c6f1ec1e7f9eadb01f74b48c185588,Improving Global Multi-target Tracking with Local Updates,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+7af8fa8897c6f1ec1e7f9eadb01f74b48c185588,Improving Global Multi-target Tracking with Local Updates,Aalborg University,Aalborg University,"AAU, Pontoppidanstræde, Sønder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark",57.01590275,9.97532827,edu,
7a3d46f32f680144fd2ba261681b43b86b702b85,Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification,Xiamen University,Xiamen University,"厦门大学, 思明南路 Siming South Road, 思明区, 思明区 (Siming), 厦门市 / Xiamen, 福建省, 361005, 中国",24.43994190,118.09301781,edu,
7a3d46f32f680144fd2ba261681b43b86b702b85,Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
7a7f2403e3cc7207e76475e8f27a501c21320a44,Emotion recognition from multi-modal information,National Cheng Kung University,National Cheng Kung University,"成大, 1, 大學路, 大學里, 前甲, 東區, 臺南市, 70101, 臺灣",22.99919160,120.21625134,edu,
@@ -4447,91 +12409,291 @@ e0dc6f1b740479098c1d397a7bc0962991b5e294,Face Detection: a Survey,Chinese Academ 7aafeb9aab48fb2c34bed4b86755ac71e3f00338,Real Time 3D Facial Movement Tracking Using a Monocular Camera,Kumamoto University,Kumamoto University,"熊本大学黒髪キャンパス, 熊本菊陽線, 中央区, 熊本市, 熊本県, 九州地方, 860-0863, 日本",32.81641780,130.72703969,edu,
7a84368ebb1a20cc0882237a4947efc81c56c0c0,Robust and efficient parametric face alignment,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
7a84368ebb1a20cc0882237a4947efc81c56c0c0,Robust and efficient parametric face alignment,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+7a72ac1c77110d03dc0482f2556e9bdb36582fcb,Following Gaze: Gaze-Following Behavior as a Window into Social Cognition,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+7a72ac1c77110d03dc0482f2556e9bdb36582fcb,Following Gaze: Gaze-Following Behavior as a Window into Social Cognition,Yale University,Yale University,"Yale University, West Campus Drive, West Haven, New Haven County, Connecticut, 06516, USA",41.25713055,-72.98966960,edu,
+7a9890cdbb62a60ba88a515655535151b568bc44,TAEF: A cross-distance/environment face recognition method,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+7a76c45fdaaa2756233d00b4b1f2e3a580df9870,Multi-view Gender Classification Using Local Binary Patterns and Support Vector Machines,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
+7a0b78879a13bd42c63cd947f583129137b16830,A Multiresolution 3D Morphable Face Model and Fitting Framework,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+7a0b78879a13bd42c63cd947f583129137b16830,A Multiresolution 3D Morphable Face Model and Fitting Framework,Reutlingen University,Reutlingen University,"Campus Hohbuch, Campus Hochschule Reutlingen, Reutlingen, Landkreis Reutlingen, Regierungsbezirk Tübingen, Baden-Württemberg, 72762, Deutschland",48.48187645,9.18682404,edu,
+7a8e54033d166bb5bcb2acfc89c2659b45baa6e6,Creativity: Generating Diverse Questions Using Variational Autoencoders,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+7ae8bca039d0d3de01001c3cd587f1961c4bbe22,Learning Visual Symbols for Parsing Human Poses in Images,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
7a65fc9e78eff3ab6062707deaadde024d2fad40,A Study on Apparent Age Estimation,West Virginia University,West Virginia University,"88, Windsor Avenue, The Flatts, Morgantown, Monongalia County, West Virginia, 26505, USA",39.65404635,-79.96475355,edu,
7ac9aaafe4d74542832c273acf9d631cb8ea6193,Deep Micro-Dictionary Learning and Coding Network,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
7ac9aaafe4d74542832c273acf9d631cb8ea6193,Deep Micro-Dictionary Learning and Coding Network,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
7a1ce696e260899688cb705f243adf73c679f0d9,Predicting Missing Demographic Information in Biometric Records Using Label Propagation Techniques,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
7a1ce696e260899688cb705f243adf73c679f0d9,Predicting Missing Demographic Information in Biometric Records Using Label Propagation Techniques,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+7a7d9cf8a6e28da11b71057948975fd179ef34be,Multicanonical Stochastic Variational Inference,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+7a7d9cf8a6e28da11b71057948975fd179ef34be,Multicanonical Stochastic Variational Inference,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+7a7d9cf8a6e28da11b71057948975fd179ef34be,Multicanonical Stochastic Variational Inference,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+7a7d9cf8a6e28da11b71057948975fd179ef34be,Multicanonical Stochastic Variational Inference,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+7a7d9cf8a6e28da11b71057948975fd179ef34be,Multicanonical Stochastic Variational Inference,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+7a923514c02872e9118b49f81d52f750a2c209a6,End-to-End Learning of Energy-Constrained Deep Neural Networks,University of Rochester,University of Rochester,"Memorial Art Gallery, 500, University Avenue, East End, Rochester, Monroe County, New York, 14607, USA",43.15769690,-77.58829158,edu,
+7a00365f9c7bced9ce47246794932f60564cb662,Converging evidence of configural processing of faces in high-functioning adults with autism spectrum disorders,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
+7add83ab4ec0e856d88f6e76ea4f585e80def1fa,People re-identification in camera networks based on probabilistic color histograms,EURECOM,EURECOM,"Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France",43.61438600,7.07112500,edu,
+7ade8aade0d464ea9a677c7c22a51d1f81edb6e9,Learning Behavior Patterns from Video: A Data-driven Framework for Agent-based Crowd Modeling,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+7ade8aade0d464ea9a677c7c22a51d1f81edb6e9,Learning Behavior Patterns from Video: A Data-driven Framework for Agent-based Crowd Modeling,Xidian University,Xidian University,"Xidian University (New Campus), 266号, 银杏大道, 南雷村, 长安区 (Chang'an), 西安市, 陕西省, 710126, 中国",34.12358250,108.83546000,edu,
+7af15295224c3ad69d56f17ff635763dd008a8a4,Learning Support Vectors for Face Authentication: Sensitivity to Mis-Registrations,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+7af15295224c3ad69d56f17ff635763dd008a8a4,Learning Support Vectors for Face Authentication: Sensitivity to Mis-Registrations,Czech Technical University,Czech Technical University,"České vysoké učení technické v Praze, Resslova, Nové Město, Praha, okres Hlavní město Praha, Hlavní město Praha, Praha, 11121, Česko",50.07642960,14.41802312,edu,
+7a0cd36d02ad962f628d9d504d02a850e27d5bfb,PoseTrack: A Benchmark for Human Pose Estimation and Tracking,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
7a131fafa7058fb75fdca32d0529bc7cb50429bd,Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+14d5bd23667db4413a7f362565be21d462d3fc93,An Online Learned Elementary Grouping Model for Multi-target Tracking,"University of California, Riverside","University of California, Riverside","University of California, Riverside, Linden Street, Riverside, Riverside County, California, 92521, USA",33.98071305,-117.33261035,edu,
+1486f2e32deac2b61d37b52e48d07fcd5208a164,Occlusion Patterns for Object Class Detection,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+14f55f333c29871867b48e1a9084132542d88083,Human centric object detection in highly crowded scenes,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+14151238780bedb19c585ab3374b3240d61899b9,Appearance-Based Classification and Recognition Using Spectral Histogram Representations and Hierarchical Learning for Oca,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+14151238780bedb19c585ab3374b3240d61899b9,Appearance-Based Classification and Recognition Using Spectral Histogram Representations and Hierarchical Learning for Oca,Florida State University,Florida State University,"Florida State University, 600, West College Avenue, Tallahassee, Leon County, Florida, 32306-1058, USA",30.44235995,-84.29747867,edu,
+14f0bce6645f39a44f5b0e695b5f28ea55fd9625,A-CCNN: Adaptive CCNN for Density Estimation and Crowd Counting,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+14f0bce6645f39a44f5b0e695b5f28ea55fd9625,A-CCNN: Adaptive CCNN for Density Estimation and Crowd Counting,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+14629c6989721e452fd9a49b5c20b8e849bce82a,Batch Algorithm with Additional Shape Constraints for Non-Rigid Factorization,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+141ee531d03fb6626043e33dd8f269a6f1f63a4b,How Robust is 3D Human Pose Estimation to Occlusion?,RWTH Aachen University,RWTH Aachen University,"RWTH Aachen, Mies-van-der-Rohe-Straße, Königshügel, Aachen-Mitte, Aachen, Städteregion Aachen, Regierungsbezirk Köln, Nordrhein-Westfalen, 52074, Deutschland",50.77917030,6.06728733,edu,
14b87359f6874ff9b8ee234b18b418e57e75b762,Face Alignment Using a Ranking Model based on Regression Trees,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
14b87359f6874ff9b8ee234b18b418e57e75b762,Face Alignment Using a Ranking Model based on Regression Trees,Istanbul Technical University,Istanbul Technical University,"Istanbul Technical University, walking path from main road to Simit restaurant, İstanbul Teknik Üniversitesi, Maslak, F.S.M Mahallesi, Sarıyer, İstanbul, Marmara Bölgesi, 34469, Türkiye",41.10427915,29.02231159,edu,
142e5b4492bc83b36191be4445ef0b8b770bf4b0,Discriminative Analysis of Brain Function at Resting-State for Attention-Deficit/Hyperactivity Disorder,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
142e5b4492bc83b36191be4445ef0b8b770bf4b0,Discriminative Analysis of Brain Function at Resting-State for Attention-Deficit/Hyperactivity Disorder,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+14401d4aae737a3ed118eca071f27f11dac7eda6,iVQA: Inverse Visual Question Answering,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+14401d4aae737a3ed118eca071f27f11dac7eda6,iVQA: Inverse Visual Question Answering,Southeast University,Southeast University,"SEU, 体育馆路, 新街口, 月季园, 玄武区, 南京市, 江苏省, 210008, 中国",32.05752790,118.78682252,edu,
14b016c7a87d142f4b9a0e6dc470dcfc073af517,Modest proposals for improving biometric recognition papers,San Jose State University,San Jose State University,"SJSU, El Paseo de Cesar E. Chavez, Downtown Historic District, Japantown, San José, Santa Clara County, California, 95113, USA",37.33519080,-121.88126008,edu,
+1423037dd56f85453cd4257861821aeeb7478bc1,"Universal representations: The missing link between faces, text, planktons, and cat breeds",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+1423037dd56f85453cd4257861821aeeb7478bc1,"Universal representations: The missing link between faces, text, planktons, and cat breeds",University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+14df5bbb6fc34819f4ef43bb2b8cb1ada35613fe,RED: Reinforced Encoder-Decoder Networks for Action Anticipation,University of Southern California,University of Southern California,"University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA",34.02241490,-118.28634407,edu,
+14abfe2c7a94bd882efb78da387d8973ace54c0b,Modularity Matters: Learning Invariant Relational Reasoning Tasks,Aalto University,Aalto University,"Aalto, 24, Otakaari, Otaniemi, Suur-Tapiola, Espoo, Helsingin seutukunta, Uusimaa, Etelä-Suomi, Manner-Suomi, 02150, Suomi",60.18558755,24.82427330,edu,
+147e699946e8c54d2176b4d868db03dd1c7bdb8f,Emotion and False Memory,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+147e699946e8c54d2176b4d868db03dd1c7bdb8f,Emotion and False Memory,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+1491c73713ff0b931e5bc1e990b9e762bfe7b60b,Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+14a3194bb454f1f2e3fc1452045ac18c69959368,Fast Object Detection Using Multistage Particle Window Deformable Part Model,National Chung Cheng University,National Chung Cheng University,"國立中正大學, 168, 鳳凰大道, 民雄鄉, 嘉義縣, 62102, 臺灣",23.56306355,120.47510531,edu,
+14a3194bb454f1f2e3fc1452045ac18c69959368,Fast Object Detection Using Multistage Particle Window Deformable Part Model,National Chung Cheng University,National Chung Cheng University,"國立中正大學, 168, 鳳凰大道, 民雄鄉, 嘉義縣, 62102, 臺灣",23.56306355,120.47510531,edu,
14b66748d7c8f3752dca23991254fca81b6ee86c,A BoW-equivalent Recurrent Neural Network for Action Recognition,University of Bonn,University of Bonn,"Rheinische Friedrich-Wilhelms-Universität Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk Köln, Nordrhein-Westfalen, 53113, Deutschland",50.73381240,7.10224650,edu,
14e8dbc0db89ef722c3c198ae19bde58138e88bf,HapFACS: An Open Source API/Software to Generate FACS-Based Expressions for ECAs Animation and for Corpus Generation,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
14e8dbc0db89ef722c3c198ae19bde58138e88bf,HapFACS: An Open Source API/Software to Generate FACS-Based Expressions for ECAs Animation and for Corpus Generation,Florida International University,Florida International University,"FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA",25.75533775,-80.37628897,edu,
+14a7e7290f81e313804a000b125bcd1c341bf9b4,A Survey on Recent Advances of Computer Vision Algorithms for Egocentric Video,Indiana University,Indiana University,"Indiana University East, West Cart Road, Richmond, Wayne County, Indiana, 47374, USA",39.86948105,-84.87956905,edu,
+14e38bafe584fa0f3cf5899027c61247ff14204c,An overview of recent progress in volumetric semantic 3D reconstruction,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
146bbf00298ee1caecde3d74e59a2b8773d2c0fc,University of Groningen 4 D Unconstrained Real - time Face Recognition Using a Commodity Depthh Camera,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
14e9158daf17985ccbb15c9cd31cf457e5551990,ConvNets with Smooth Adaptive Activation Functions for Regression,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
14e9158daf17985ccbb15c9cd31cf457e5551990,ConvNets with Smooth Adaptive Activation Functions for Regression,Oak Ridge National Laboratory,Oak Ridge National Laboratory,"Oak Ridge National Laboratory, Oak Ridge, Roane County, Tennessee, USA",35.93006535,-84.31240032,edu,
14e9158daf17985ccbb15c9cd31cf457e5551990,ConvNets with Smooth Adaptive Activation Functions for Regression,Stony Brook University Hospital,Stony Brook University Hospital,"Stony Brook University Hospital, 101, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.90826665,-73.11520891,edu,
14ce7635ff18318e7094417d0f92acbec6669f1c,DeepFace: Closing the Gap to Human-Level Performance in Face Verification,Tel Aviv University,Tel Aviv University,"אוניברסיטת תל אביב, כיכר מנדל, תל אביב - יפו, אפקה, תל אביב-יפו, מחוז תל אביב, NO, ישראל",32.11198890,34.80459702,edu,
+14de80b1b86ea342ba44c584e9e39b9089472658,M-PACT: An Open Source Platform for Repeatable Activity Classification Research,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+14de80b1b86ea342ba44c584e9e39b9089472658,M-PACT: An Open Source Platform for Repeatable Activity Classification Research,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+14de80b1b86ea342ba44c584e9e39b9089472658,M-PACT: An Open Source Platform for Repeatable Activity Classification Research,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
140438a77a771a8fb656b39a78ff488066eb6b50,Localizing Parts of Faces Using a Consensus of Exemplars,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
140438a77a771a8fb656b39a78ff488066eb6b50,Localizing Parts of Faces Using a Consensus of Exemplars,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+14d6ddb48d1b8a593665576d7e25f17be1447b2e,Recognizing human actions using multiple features,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+14d6ddb48d1b8a593665576d7e25f17be1447b2e,Recognizing human actions using multiple features,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+14d6ddb48d1b8a593665576d7e25f17be1447b2e,Recognizing human actions using multiple features,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
143bee9120bcd7df29a0f2ad6f0f0abfb23977b8,Shared Gaussian Process Latent Variable Model for Multi-view Facial Expression Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
143bee9120bcd7df29a0f2ad6f0f0abfb23977b8,Shared Gaussian Process Latent Variable Model for Multi-view Facial Expression Recognition,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
14d72dc9f78d65534c68c3ed57305f14bd4b5753,Exploiting Multi-grain Ranking Constraints for Precisely Searching Visually-similar Vehicles,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+1450b9f2e69e2a4d0400bffaa535712b5fbab562,Different Visual Preference Patterns in Response to Simple and Complex Dynamic Social Stimuli in Preschool-Aged Children with Autism Spectrum Disorders,Soochow University,Soochow University,"苏州大学（天赐庄校区）, 清荫路, 钟楼社区, 双塔街道, 姑苏区, 苏州市, 江苏省, 215001, 中国",31.30709510,120.63573987,edu,
14b162c2581aea1c0ffe84e7e9273ab075820f52,Training Object Class Detectors from Eye Tracking Data,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
14ff9c89f00dacc8e0c13c94f9fadcd90e4e604d,Correlation filter cascade for facial landmark localization,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+1462fea6c71be9c442f443488fc7c45e1840e9ed,Learning a perceptual manifold for image set classification,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+14421119527aa5882e1552a651fbd2d73bc94637,Searching for objects driven by context,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+14421119527aa5882e1552a651fbd2d73bc94637,Searching for objects driven by context,University of Edinburgh,University of Edinburgh,"New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK",55.94951105,-3.19534913,edu,
14b69626b64106bff20e17cf8681790254d1e81c,Hybrid Super Vector with Improved Dense Trajectories for Action Recognition,Shenzhen Institutes of Advanced Technology,Shenzhen Institutes of Advanced Technology,"中国科学院深圳先进技术研究院, 1068, 科研路, 深圳大学城, 三坑村, 南山区, 深圳市, 广东省, 518000, 中国",22.59805605,113.98533784,edu,
14b69626b64106bff20e17cf8681790254d1e81c,Hybrid Super Vector with Improved Dense Trajectories for Action Recognition,Southwest Jiaotong University,Southwest Jiaotong University,"西南交通大学 - Xinan Jiaotong University, 二环高架路, 沁园小区, 金牛区, 金牛区 (Jinniu), 成都市 / Chengdu, 四川省, 610084, 中国",30.69784700,104.05208110,edu,
14b69626b64106bff20e17cf8681790254d1e81c,Hybrid Super Vector with Improved Dense Trajectories for Action Recognition,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
14070478b8f0d84e5597c3e67c30af91b5c3a917,Detecting Social Actions of Fruit Flies,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
14fb3283d4e37760b7dc044a1e2906e3cbf4d23a,Weak attributes for large-scale image retrieval,Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+14c37ea85ba8d74d053a34aedd7e484659fd54d4,Beyond trees: MRF inference via outer-planar decomposition,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+148316962e1ebb7086837e25cbee9ecbd71e5940,Efficient Multi-Person Pose Estimation with Provable Guarantees,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+148316962e1ebb7086837e25cbee9ecbd71e5940,Efficient Multi-Person Pose Estimation with Provable Guarantees,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
14811696e75ce09fd84b75fdd0569c241ae02f12,Margin-based discriminant dimensionality reduction for visual recognition,Eskisehir Osmangazi University,Eskisehir Osmangazi University,"Eskişehir Osmangazi Üniversitesi Meşelik Yerleşkesi, Kütahya-Eskişehir yolu, Sazova Mahallesi, Karagözler, Tepebaşı, Eskişehir, İç Anadolu Bölgesi, 26160, Türkiye",39.74875160,30.47653071,edu,
14811696e75ce09fd84b75fdd0569c241ae02f12,Margin-based discriminant dimensionality reduction for visual recognition,University of Caen,University of Caen,"京都大学, 今出川通, 吉田泉殿町, 左京区, 京都市, 京都府, 近畿地方, 606-8501, 日本",35.02749960,135.78154513,edu,
14811696e75ce09fd84b75fdd0569c241ae02f12,Margin-based discriminant dimensionality reduction for visual recognition,Rowan University,Rowan University,"Rowan University, Esbjornson Walk, Glassboro, Gloucester County, New Jersey, 08028, USA",39.71035260,-75.11932666,edu,
14e759cb019aaf812d6ac049fde54f40c4ed1468,Subspace Methods,University of Tsukuba,University of Tsukuba,"University of Tsukuba, つばき通り, Kananemoto-satsukabe village, つくば市, 茨城県, 関東地方, 305-8377, 日本",36.11120580,140.10551760,edu,
+149c21e5f1c52429fb1585d30b50bc850a16edcd,A 3D Audio-visual Corpus for Speech Recognition,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+149c21e5f1c52429fb1585d30b50bc850a16edcd,A 3D Audio-visual Corpus for Speech Recognition,University of Western Australia,University of Western Australia,"UWA, 35, Underwood Avenue, Daglish, Perth, Western Australia, 6009, Australia",-31.95040445,115.79790037,edu,
+14f936e4eca8382ad835bf18b4a11d2e6682fd71,Simultaneous Children Recognition and Tracking for Childcare Assisting System by Using Kinect Sensors,University of Electro-Communications,The University of Electro-Communications,"電気通信大学, 甲州街道, 調布市, 東京都, 関東地方, 182-0026, 日本",35.65729570,139.54255868,edu,
146a7ecc7e34b85276dd0275c337eff6ba6ef8c0,AFFACT: Alignment-free facial attribute classification technique,"University of Colorado, Colorado Springs",University of Colorado Colorado Springs,"Main Hall, The Spine, Colorado Springs, El Paso County, Colorado, 80907, USA",38.89207560,-104.79716389,edu,
+1432654a204391b6e2ec197138be0f7c8cb83ae5,Coreset-Based Neural Network Compression,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+1432654a204391b6e2ec197138be0f7c8cb83ae5,Coreset-Based Neural Network Compression,"University of Illinois, Urbana-Champaign","University of Illinois, Urbana-Champaign","B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA",40.11116745,-88.22587665,edu,
148eb413bede35487198ce7851997bf8721ea2d6,People Search in Surveillance Videos,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
148eb413bede35487198ce7851997bf8721ea2d6,People Search in Surveillance Videos,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
148eb413bede35487198ce7851997bf8721ea2d6,People Search in Surveillance Videos,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+147951fa2e0df54c5ddda0ff82dec057dcc61f66,Transforming neutral visual speech into expressive visual speech,University of East Anglia,University of East Anglia,"Arts (Lower Walkway Level), The Square, Westfield View, Earlham, Norwich, Norfolk, East of England, England, NR4 7TJ, UK",52.62215710,1.24091360,edu,
14014a1bdeb5d63563b68b52593e3ac1e3ce7312,Expression-Invariant Age Estimation,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
14418ae9a6a8de2b428acb2c00064da129632f3e,Discovering the Spatial Extent of Relative Attributes,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
14ba910c46d659871843b31d5be6cba59843a8b8,Face Recognition in Movie Trailers via Mean Sequence Sparse Representation-Based Classification,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+14d0afea52c4e9b7a488f6398e4a92bd4f4b93c7,Rethinking the Faster R-CNN Architecture for Temporal Action Localization,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
14318d2b5f2cf731134a6964d8193ad761d86942,FaceDNA: Intelligent Face Recognition System with Intel RealSense 3D Camera,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
+14effecdf4e99a6ef3bb590582ca07e642d49632,Multiple-Gaze Geometry: Inferring Novel 3D Locations from Gazes Observed in Monocular Video,University of Arizona,University of Arizona,"University of Arizona, North Highland Avenue, Rincon Heights, Barrio Viejo, Tucson, Pima County, Arizona, 85721, USA",32.23517260,-110.95095832,edu,
+146f989d2cea0e6825543d45c073f90dd8ae9939,Zero-Shot Learning via Semantic Similarity Embedding,Boston University,Boston University,"BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA",42.35042530,-71.10056114,edu,
14c0f9dc9373bea1e27b11fa0594c86c9e632c8d,Adaptive Exponential Smoothing for Online Filtering of Pixel Prediction Maps,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
1439bf9ba7ff97df9a2da6dae4784e68794da184,LGE-KSVD: Flexible Dictionary Learning for Optimized Sparse Representation Classification,Rochester Institute of Technology,Rochester Institute of Technology,"Rochester Institute of Technology (RIT), 1, Lomb Memorial Drive, Bailey, Henrietta Town, Monroe County, New York, 14623, USA",43.08250655,-77.67121663,edu,
+14819d286c9b46c8e57c7e809db879f9e1451226,Shape Anchors for Data-Driven Multi-view Reconstruction,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+14819d286c9b46c8e57c7e809db879f9e1451226,Shape Anchors for Data-Driven Multi-view Reconstruction,Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+14819d286c9b46c8e57c7e809db879f9e1451226,Shape Anchors for Data-Driven Multi-view Reconstruction,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
+14819d286c9b46c8e57c7e809db879f9e1451226,Shape Anchors for Data-Driven Multi-view Reconstruction,MIT CSAIL,MIT CSAIL,"32 Vassar St, Cambridge, MA 02139, USA",42.36194070,-71.09043780,edu,
141768ab49a5a9f5adcf0cf7e43a23471a7e5d82,Relative facial action unit detection,McMaster University,McMaster University,"McMaster University, Westdale, Hamilton, Ontario, Canada",43.26336945,-79.91809684,edu,
14bca107bb25c4dce89210049bf39ecd55f18568,Emotion recognition from facial images with arbitrary views,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+1412f4024babbc01b671f7ee4a22d86db1545268,Proximity and gaze influences facial temperature: a thermal infrared imaging study,University of Portsmouth,University of Portsmouth,"University of Portsmouth - North Zone, Portland Street, Portsea, Portsmouth, South East, England, PO1 3DE, UK",50.79805775,-1.09834911,edu,
+147f31b603931c688687c6d64d330c9be2ab2f2f,Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification,Huazhong University of Science and Technology,Huazhong University of Science and Technology,"华中大, 珞喻路, 东湖新技术开发区, 关东街道, 东湖新技术开发区（托管）, 洪山区 (Hongshan), 武汉市, 湖北省, 430074, 中国",30.50975370,114.40628810,edu,
+147f31b603931c688687c6d64d330c9be2ab2f2f,Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification,"IBM Research, North Carolina",IBM Research,"IBM, East Cornwallis Road, Research Triangle Park, Nelson, Durham County, North Carolina, 27709, USA",35.90422720,-78.85565763,company,
+147f31b603931c688687c6d64d330c9be2ab2f2f,Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification,Northwestern University,Northwestern University,"Northwestern University, Northwestern Place, Downtown, Evanston, Cook County, Illinois, 60208, USA",42.05511640,-87.67581113,edu,
+8eae6ed5fa66b5eb63bdb6cc23d3b385a7fee37c,A 3D Dynamic Database for Unconstrained Face Recognition,University of Florence,University of Florence,"Piazza di San Marco, 4, 50121 Firenze FI, Italy",43.77764260,11.25976500,edu,
8ec82da82416bb8da8cdf2140c740e1574eaf84f,Lip Reading in Profile,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
8e0ede53dc94a4bfcf1238869bf1113f2a37b667,Joint patch and multi-label learning for facial action unit detection,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
8e0ede53dc94a4bfcf1238869bf1113f2a37b667,Joint patch and multi-label learning for facial action unit detection,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
8e3c97e420e0112c043929087d6456d8ab61e95c,Robust Global Motion Compensation in Presence of Predominant Foreground,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
8e0ab1b08964393e4f9f42ca037220fe98aad7ac,UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+8e63715d458ff79170a010c283c79427ce81ff0c,Demography-based facial retouching detection using subclass supervised sparse autoencoder,University of Notre Dame,University of Notre Dame,"University of Notre Dame du Lac, Holy Cross Drive, Notre Dame, Maple Lane, Saint Joseph County, Indiana, 46556, USA",41.70456775,-86.23822026,edu,
+8e610860a0a273d5a2676e9d53328820f2f59a85,Diversity in Fashion Recommendation Using Semantic Parsing,"IIIT Delhi, India","IIIT Delhi, India","Okhla Industrial Estate, Phase III, Near Govind Puri Metro Station, New Delhi, Delhi 110020, India",28.54562820,77.27315050,edu,
+8e8c141e06d52cee1917b7268abca315bf3af714,Random-Profiles-Based 3D Face Recognition System,Yonsei University,Yonsei University,"연세대, 연세로, 신촌동, 창천동, 서대문구, 서울특별시, 03789, 대한민국",37.56004060,126.93692480,edu,
+8e54329a35b11e48d398dd3df3b27c72f48f5b2b,SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+8e54329a35b11e48d398dd3df3b27c72f48f5b2b,SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+8eda955303623b68ab207abb233fac17b92c6632,Homographic Class Template for Logo Localization and Recognition,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
8e4808e71c9b9f852dc9558d7ef41566639137f3,Adversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
8e4808e71c9b9f852dc9558d7ef41566639137f3,Adversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition,University of North Carolina at Chapel Hill,University of North Carolina at Chapel Hill,"University of North Carolina at Chapel Hill, East Cameron Avenue, Chapel Hill, Orange County, North Carolina, 27514, USA",35.91139710,-79.05045290,edu,
+8e4355225f0db7945952fbdf29e234e71313d30b,3D Human Pose Estimation with Relational Networks,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
8e0ad1ccddc7ec73916eddd2b7bbc0019d8a7958,Segment-based SVMs for Time Series Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
8e0ad1ccddc7ec73916eddd2b7bbc0019d8a7958,Segment-based SVMs for Time Series Analysis,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8e457222d6f38847489d63557ec2e0de7356e2a5,Super-resolution pipeline for fast adjudication in watchlist screening,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
+8eeac4ca19ddc919423c42447c28ce546a25c4f8,Image composition for object pop-out,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+8e861a7809905a003fffa821574e68ae0c0788e7,Dictionary Learning with Iterative Laplacian Regularisation for Unsupervised Person Re-identification,Queen Mary University of London,Queen Mary University of London,"Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK",51.52472720,-0.03931035,edu,
+8e7c647d8e8ba726b03f7e7c5cc395f86b9de9be,Parsing Pose of People with Interaction,California Institute of Technology,California Institute of Technology,"California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA",34.13710185,-118.12527487,edu,
+8e74244e220a1c9e89417caa1ad22f649884d311,ArtTrack: Articulated Multi-Person Tracking in the Wild,Max Planck Institute for Informatics,Max Planck Institute for Informatics,"MPII, E1 4, Campus, Universität, Sankt Johann, Bezirk Mitte, Saarbrücken, Regionalverband Saarbrücken, Saarland, 66123, Deutschland",49.25795660,7.04577417,edu,
+8e69534ae2f00025226c3a46dc6efb4faa3d396a,Object Class Detection Using Local Image Features and Point Pattern Matching Constellation Search,University of Surrey,University of Surrey,"University of Surrey, Spine Road, Guildford Park, Guildford, Surrey, South East, England, GU2 7XH, UK",51.24303255,-0.59001382,edu,
+8e36255da222c01a880c9b88d61f139f7bdba62f,Graph filtering for data reduction and reconstruction,University of Texas at Arlington,University of Texas at Arlington,"University of Texas at Arlington, South Nedderman Drive, Arlington, Tarrant County, Texas, 76010, USA",32.72836830,-97.11201835,edu,
+8e0a86634b286567433736a667e3a0bb7902470e,Dense Semantic Image Segmentation with Objects and Attributes,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+8e0a86634b286567433736a667e3a0bb7902470e,Dense Semantic Image Segmentation with Objects and Attributes,Oxford Brookes University,Oxford Brookes University,"Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK",51.75552050,-1.22615970,edu,
8ed33184fccde677ec8413ae06f28ea9f2ca70f3,Multimodal Visual Concept Learning with Weakly Supervised Techniques,National Technical University of Athens,National Technical University of Athens,"Εθνικό Μετσόβιο Πολυτεχνείο, Στουρνάρη, Μουσείο, Αθήνα, Δήμος Αθηναίων, Π.Ε. Κεντρικού Τομέα Αθηνών, Περιφέρεια Αττικής, Αττική, 11250, Ελλάδα",37.98782705,23.73179733,edu,
+8e59851a9b59d818f2c0beaf23760e9326439a86,Graph Based Image Segmentation,Hong Kong University of Science and Technology,Hong Kong University of Science and Technology,"香港科技大學 Hong Kong University of Science and Technology, 大學道 University Road, 大埔仔 Tai Po Tsai, 大埔仔村 Tai Po Tsai Village, 新界 New Territories, HK, DD253 1209, 中国",22.33863040,114.26203370,edu,
+8e4ff1aa78f8997b683f873c46999f384db4de18,Renewing the respect for similarity,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+8e4ff1aa78f8997b683f873c46999f384db4de18,Renewing the respect for similarity,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
8ee5b1c9fb0bded3578113c738060290403ed472,Extending explicit shape regression with mixed feature channels and pose priors,Karlsruhe Institute of Technology,Karlsruhe Institute of Technology,"KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-Württemberg, 76351, Deutschland",49.10184375,8.43312560,edu,
+8e88a97e09a853cf768ca1c732ba5f008fff77ca,Regularized Residual Quantization: a multi-layer sparse dictionary learning approach,University of Geneva,University of Geneva,"University of Chicago-Yerkes Observatory, 373, West Geneva Street, Williams Bay, Walworth County, Wisconsin, 53191, USA",42.57054745,-88.55578627,edu,
+8e7548911c41b6f3a6ccbda6d3ab913eaa41e721,Feature Learning with Rank-Based Candidate Selection for Product Search,National Taiwan University,National Taiwan University,"臺大;台大, 1, 羅斯福路四段, 學府里, 大安區, 臺北市, 10617, 臺灣",25.01682835,121.53846924,edu,
8efda5708bbcf658d4f567e3866e3549fe045bbb,Pre-trained Deep Convolutional Neural Networks for Face Recognition,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
8efda5708bbcf658d4f567e3866e3549fe045bbb,Pre-trained Deep Convolutional Neural Networks for Face Recognition,University of Groningen,University of Groningen,"Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland",53.21967825,6.56251482,edu,
+8e956117b2e22470814778fed6f4641e475efb44,Learning Attribute Representations with Localization for Flexible Fashion Search,National University of Singapore,National University of Singapore,"NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore",1.29620180,103.77689944,edu,
+8e956117b2e22470814778fed6f4641e475efb44,Learning Attribute Representations with Localization for Flexible Fashion Search,"A*STAR, Singapore","Institute for Infocomm Research, A*STAR, Singapore","1 Fusionopolis Way, #21-01 Connexis, Singapore 138632",1.29889260,103.78731070,edu,
+8e64d872a419f122f870026179ccbc5daa1645fd,Modified Local Binary Pattern (MLBP) for Robust Face Recognition,Old Dominion University,Old Dominion University,"Old Dominion University, Elkhorn Avenue, Lamberts Point, Norfolk, Virginia, 23508, USA",36.88568200,-76.30768579,edu,
+8e64d872a419f122f870026179ccbc5daa1645fd,Modified Local Binary Pattern (MLBP) for Robust Face Recognition,University of Dayton,University of Dayton,"University of Dayton, Caldwell Street, South Park Historic District, Dayton, Montgomery, Ohio, 45409, USA",39.73844400,-84.17918747,edu,
+22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b,A Database for Person Re-Identification in Multi-Camera Surveillance Networks,Queensland University of Technology,Queensland University of Technology,"Queensland University of Technology, Macgregor Lane, Merthyr, South Brisbane, Brisbane, QLD, 4000, Australia",-27.47715625,153.02841004,edu,
2227f978f084ebb18cb594c0cfaf124b0df6bf95,Pillar Networks for action recognition,Imperial College London,Imperial College London,"Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK",51.49887085,-0.17560797,edu,
+228db5326a10cd67605ce103a7948207a65feeb1,Stacked Attention Networks for Image Question Answering,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
22e2066acfb795ac4db3f97d2ac176d6ca41836c,Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
22e2066acfb795ac4db3f97d2ac176d6ca41836c,Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment,University of Chinese Academy of Sciences,University of Chinese Academy of Sciences,"University of Chinese Academy of Sciences, UCAS, Yuquanlu, 玉泉路, 田村, 海淀区, 100049, 中国",39.90828040,116.24585270,edu,
+22dff8fa7cc57f7b4f2903c6fbf6ffa7f1bea0d7,3D Human Pose Estimation Using Convolutional Neural Networks with 2D Pose Information,Seoul National University,Seoul National University,"서울대학교, 서호동로, 서둔동, 권선구, 수원시, 경기, 16614, 대한민국",37.26728000,126.98411510,edu,
22717ad3ad1dfcbb0fd2f866da63abbde9af0b09,A Learning-based Control Architecture for Socially Assistive Robots Providing Cognitive Interventions,University of Toronto,University of Toronto,"University of Toronto, St. George Street, Bloor Street Culture Corridor, Old Toronto, Toronto, Ontario, M5S 1A5, Canada",43.66333345,-79.39769975,edu,
+22bc3624a1e6d46f5b7c9208751d4f14fc87e946,"Book chapter for Artificial Intelligence for Maximizing Content Based Image Retrieval Event detection, query, and retrieval for video surveillance",IBM Thomas J. Watson Research Center,IBM Thomas J. Watson Research Center,"IBM Yorktown research lab, Adams Road, Millwood, Town of New Castle, Westchester County, New York, 10562, USA",41.21002475,-73.80407056,company,
2288696b6558b7397bdebe3aed77bedec7b9c0a9,Action Recognition with Joint Attention on Multi-Level Deep Features,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
2288696b6558b7397bdebe3aed77bedec7b9c0a9,Action Recognition with Joint Attention on Multi-Level Deep Features,"Beijing, China","Beijing, China","北京市, 东城区, 北京市, 100010, 中国",39.90621700,116.39127570,edu,
+22bc12fb82db4c5a5f52bd1ba70e25ffac94f428,Transfer learning for object category detection,University of Oxford,University of Oxford,"Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK",51.75345380,-1.25400997,edu,
+22f1b026bd78fdc2e945bcf88a6d69d44b484ec6,The emperor's new masks: On demographic differences and disguises,University of Pennsylvania,University of Pennsylvania,"Penn Museum, 3260, South Street, University City, Philadelphia, Philadelphia County, Pennsylvania, 19104, USA",39.94923440,-75.19198985,edu,
+22493d8d4d7b4604cae23638dce4981b36e30147,Learning an Image-Based Motion Context for Multiple People Tracking,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+221c9fff1c25368a6b72ca679c67a3d6b35e2c00,Memory-Based Face Recognition for Visitor Identification,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+22dc91889312e796ad36b363bc5ed959714e4694,Deep Di erential Recurrent Neural Networks,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+22dc91889312e796ad36b363bc5ed959714e4694,Deep Di erential Recurrent Neural Networks,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+22dc91889312e796ad36b363bc5ed959714e4694,Deep Di erential Recurrent Neural Networks,University of Central Florida,University of Central Florida,"University of Central Florida, Libra Drive, University Park, Orange County, Florida, 32816, USA",28.59899755,-81.19712501,edu,
+22954dd92a795d7f381465d1b353bcc41901430d,Learning Visual Storylines with Skipping Recurrent Neural Networks,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+22259622612a839d97133d4809f80447dfeb5d56,Incremental Machine Learning Approach for Component-based Recognition,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+22a12ec4258f223b43761e5c4729787d1aaa623b,Optimal Bloom Filters and Adaptive Merging for LSM-Trees,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+22a12ec4258f223b43761e5c4729787d1aaa623b,Optimal Bloom Filters and Adaptive Merging for LSM-Trees,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+22a12ec4258f223b43761e5c4729787d1aaa623b,Optimal Bloom Filters and Adaptive Merging for LSM-Trees,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+22a12ec4258f223b43761e5c4729787d1aaa623b,Optimal Bloom Filters and Adaptive Merging for LSM-Trees,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+22a12ec4258f223b43761e5c4729787d1aaa623b,Optimal Bloom Filters and Adaptive Merging for LSM-Trees,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+22f21a5b230d6bcc2c4ab4e4d5ae57a20f09f348,How do we use our hands? Discovering a diverse set of common grasps,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2296d79753118cfcd0fecefece301557f4cb66e2,Exploring Disentangled Feature Representation Beyond Face Identification,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+2296d79753118cfcd0fecefece301557f4cb66e2,Exploring Disentangled Feature Representation Beyond Face Identification,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
221252be5d5be3b3e53b3bbbe7a9930d9d8cad69,Do We Need More Training Data or Better Models for Object Detection?,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+22db07c472b2d7bc7704b8c2bbd8f620e2e68ca9,MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation,New York University,New York University,"NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA",40.72925325,-73.99625394,edu,
+22f44121a6de3ff942c5fbf4ab1d6734315baf66,Sensor-assisted facial recognition: an enhanced biometric authentication system for smartphones,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+22f44121a6de3ff942c5fbf4ab1d6734315baf66,Sensor-assisted facial recognition: an enhanced biometric authentication system for smartphones,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
+22f44121a6de3ff942c5fbf4ab1d6734315baf66,Sensor-assisted facial recognition: an enhanced biometric authentication system for smartphones,"University of California, Davis","University of California, Davis","University of California, Davis, Apiary Drive, Yolo County, California, 95616-5270, USA",38.53363490,-121.79077264,edu,
22df6b6c87d26f51c0ccf3d4dddad07ce839deb0,Fast action proposals for human action detection and search,Nanyang Technological University,Nanyang Technological University,"NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore",1.34841040,103.68297965,edu,
+22f21d58c6aecdb4f57c50fa9eb4952643eec0e9,Domain Transfer Support Vector Ranking for Person Re-identification without Target Camera Label Information,Hong Kong Baptist University,Hong Kong Baptist University,"香港浸會大學 Hong Kong Baptist University, 安明街 On Ming Street, 石門 Shek Mun, 石古壟 Shek Kwu Lung, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1132, 中国",22.38742010,114.20822220,edu,
+22f2f77120cd28e9b2516179239380adef46b1be,Discovering Object Functionality,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+221c18238b829c12b911706947ab38fd017acef7,A Richly Annotated Dataset for Pedestrian Attribute Recognition,Chinese Academy of Sciences,Chinese Academy of Sciences,"中国科学院心理研究所, 16, 林萃路, 朝阳区 / Chaoyang, 北京市, 100101, 中国",40.00447950,116.37023800,edu,
+221c18238b829c12b911706947ab38fd017acef7,A Richly Annotated Dataset for Pedestrian Attribute Recognition,Temple University,Temple University,"Temple University School of Podiatric Medicine, Race Street, Chinatown, Philadelphia, Philadelphia County, Pennsylvania, 19103, USA",39.95472495,-75.15346905,edu,
+22344ddcae83e732ba0c2116d7ee9016aebb12be,Model-Based Feature Extraction for Gait Analysis and Recognition,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+22fe619996b59c09cb73be40103a123d2e328111,The German Traffic Sign Recognition Benchmark: A multi-class classification competition,University of Copenhagen,University of Copenhagen,"Københavns Universitet, Krystalgade, Kødbyen, Vesterbro, København, Københavns Kommune, Region Hovedstaden, 1165, Danmark",55.68015020,12.57232700,edu,
+227de3327012e8141cc58068fe9bc197773254b8,Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations,Keio University,Keio University,"綱島市民の森, けつわり坂, 港北区, 横浜市, 神奈川県, 関東地方, 223-0053, 日本",35.54169690,139.63471840,edu,
+227de3327012e8141cc58068fe9bc197773254b8,Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations,"National Institute of Informatics, Japan","National Institute of Informatics, Japan","2 Chome-1-２ Hitotsubashi, Chiyoda, Tokyo 100-0003, Japan",35.69248530,139.75825330,edu,
22e678d3e915218a7c09af0d1602e73080658bb7,Adventures in archiving and using three years of webcam images,Washington University,Washington University,"Dero, Wallace Drive, St. Louis County, Missouri, MO 63130, USA",38.64804450,-90.30996670,edu,
+22b5bcd590f6d4c04b8de28217b001da9667ec33,Write a Classifier: Zero-Shot Learning Using Purely Textual Descriptions,Rutgers University,Rutgers University,"Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA",40.47913175,-74.43168868,edu,
2201f187a7483982c2e8e2585ad9907c5e66671d,Joint Face Alignment and 3D Face Reconstruction,"Sichuan University, Chengdu","Sichuan Univ., Chengdu","四川大学（华西校区）, 校东路, 武侯区, 武侯区 (Wuhou), 成都市 / Chengdu, 四川省, 610014, 中国",30.64276900,104.06751175,edu,
2201f187a7483982c2e8e2585ad9907c5e66671d,Joint Face Alignment and 3D Face Reconstruction,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+22a5c5b366e56339b34a66ce2a4a106592656e40,A model of dynamic compilation for heterogeneous compute platforms,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
2241eda10b76efd84f3c05bdd836619b4a3df97e,One-to-many face recognition with bilinear CNNs,University of Massachusetts,University of Massachusetts,"University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA",42.38897850,-72.52869870,edu,
+22267d537cbaed08c2005c42f251bb6097aa1505,Hierarchical Grid-based People Tracking with Multi-camera Setup,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+228408c76823355010bb13e5b3f32823b35a176c,Daily Living Activities Recognition via Efficient High and Low Level Cues Combination and Fisher Kernel Representation,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+228408c76823355010bb13e5b3f32823b35a176c,Daily Living Activities Recognition via Efficient High and Low Level Cues Combination and Fisher Kernel Representation,University Politehnica of Bucharest,University Politehnica of Bucharest,"Universitatea Politehnica din București, Novum Invest, București, Militari, Sector 6, Municipiul București, 060042, România",44.43918115,26.05044565,edu,
22646cf884cc7093b0db2c1731bd52f43682eaa8,Human Action Adverb Recognition: ADHA Dataset and A Three-Stream Hybrid Model,Shanghai Jiao Tong University,Shanghai Jiao Tong University,"上海交通大学（徐汇校区）, 淮海西路, 番禺小区, 平阴桥, 徐汇区, 上海市, 200052, 中国",31.20081505,121.42840681,edu,
22f94c43dd8b203f073f782d91e701108909690b,MovieScope: Movie trailer classification using Deep Neural Networks,University of Virginia,University of Virginia,"University of Virginia, Rotunda Alley, Carr's Hill, Albemarle County, Virginia, 22904-4119, USA",38.03536820,-78.50353220,edu,
+2297ead8a0000dab33ebc73b7d5781b3258322b6,Classifying and Visualizing Emotions with Emotional DAN,Warsaw University of Technology,Warsaw University of Technology,"Politechnika Warszawska, 1, Plac Politechniki, VIII, Śródmieście, Warszawa, mazowieckie, 00-661, RP",52.22165395,21.00735776,edu,
+220377caca34bed8a0081d48d153aecc11c211e1,Spectral-Pruning: Compressing deep neural network via spectral analysis,University of Tokyo,University of Tokyo,"東京大学 柏キャンパス, 学融合の道, 柏市, 千葉県, 関東地方, 277-8583, 日本",35.90204480,139.93622009,edu,
+2231f44be9a8472a46d8e8a628b4e52b9a8f44e0,Visual Dialog,Georgia Institute of Technology,Georgia Institute of Technology,"Georgia Tech, Atlantic Drive Northwest, Bellwood, Rockdale, Atlanta, Fulton County, Georgia, 30318, USA",33.77603300,-84.39884086,edu,
22143664860c6356d3de3556ddebe3652f9c912a,Facial Expression Recognition for Human-Robot Interaction - A Prototype,Electrical and Computer Engineering,Electrical and Computer Engineering,"Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA",33.58667840,-101.87539204,edu,
2271d554787fdad561fafc6e9f742eea94d35518,Multimodale Mensch-Roboter-Interaktion für Ambient Assisted Living,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+22f71559c88fe32b405a6fedf7ee099c32d9377e,Causal and compositional generative models in online perception,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+22f71559c88fe32b405a6fedf7ee099c32d9377e,Causal and compositional generative models in online perception,Korea University,Korea University,"고려대, 안암로, 제기동, 동대문구, 서울특별시, 02796, 대한민국",37.59014110,127.03623180,edu,
+224e78cc643e38c2cdcdaaa5123ecd7cf7a08674,Learning non-redundant codebooks for classifying complex objects,Oregon State University,Oregon State University,"OSU Beaver Store, 538, Southwest 6th Avenue, Portland Downtown, Portland, Multnomah County, Oregon, 97204, USA",45.51982890,-122.67797964,edu,
+22c169fa05a0d5710bc111e451161e9d9141c29d,A Novel Inference of a Restricted Boltzmann Machine,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+22c169fa05a0d5710bc111e451161e9d9141c29d,A Novel Inference of a Restricted Boltzmann Machine,Tokyo Institute of Technology,Tokyo Institute of Technology,"東京工業大学, 厚木街道, 緑区, 町田市, 神奈川県, 関東地方, 226-0026, 日本",35.51675380,139.48342251,edu,
+227cef669b362a7756564519be22c7d060348f66,Factors in Finetuning Deep Model for Object Detection with Long-Tail Distribution,Chinese University of Hong Kong,The Chinese University of Hong Kong,"中大 CUHK, NA梯 New Asia Stairs, 馬料水 Ma Liu Shui, 九肚村 Kau To Village, 沙田區 Sha Tin District, 新界 New Territories, HK, DD193 1191, 中国",22.42031295,114.20788644,edu,
+222db9e290b34ae30c39486697d8e8dac3175770,Stabilizing Training of Generative Adversarial Networks through Regularization,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+222db9e290b34ae30c39486697d8e8dac3175770,Stabilizing Training of Generative Adversarial Networks through Regularization,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+222db9e290b34ae30c39486697d8e8dac3175770,Stabilizing Training of Generative Adversarial Networks through Regularization,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+222db9e290b34ae30c39486697d8e8dac3175770,Stabilizing Training of Generative Adversarial Networks through Regularization,ETH Zürich,ETH Zürich,"ETH Zürich, 101, Rämistrasse, Hochschulen, Altstadt, Zürich, Bezirk Zürich, Zürich, 8092, Schweiz/Suisse/Svizzera/Svizra",47.37645340,8.54770931,edu,
+228c28bd18a2d58cd771a75e8718b14dc32051e0,An effective neutrosophic set-based preprocessing method for face recognition,Utah State University,Utah State University,"Utah State University, Champ Drive, Logan, Cache County, Utah, 84322, USA",41.74115040,-111.81223090,edu,
+220f6ef6f4bf4729871822e08080142359012e10,Implementation of Automatic Multiple Person Tracking System with Open Cv on Beagle Board,Anna University,Anna University,"Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India",13.01058380,80.23537360,edu,
+2520c3d5d114974167561591a57f80e89650f862,Direct Pose Estimation and Refinement,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2520c3d5d114974167561591a57f80e89650f862,Direct Pose Estimation and Refinement,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
25ff865460c2b5481fa4161749d5da8501010aa0,Seeing What is Not There: Learning Context to Determine Where Objects are Missing,University of Maryland,University of Maryland,"The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA",39.28996850,-76.62196103,edu,
+25d474ff23515eeccbc071897c144957edfbd7a5,Dual Swap Disentangling,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+25d474ff23515eeccbc071897c144957edfbd7a5,Dual Swap Disentangling,Stevens Institute of Technology,Stevens Institute of Technology,"Stevens Institute of Technology, River Terrace, Hoboken, Hudson County, New Jersey, 07030, USA",40.74225200,-74.02709490,edu,
+25d474ff23515eeccbc071897c144957edfbd7a5,Dual Swap Disentangling,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+25d474ff23515eeccbc071897c144957edfbd7a5,Dual Swap Disentangling,University of Sydney,University of Sydney,"USyd, Fisher Road, Camperdown, Sydney, NSW, 2006, Australia",-33.88890695,151.18943366,edu,
+25d474ff23515eeccbc071897c144957edfbd7a5,Dual Swap Disentangling,Zhejiang University,Zhejiang University,"浙江大学之江校区, 之江路, 转塘街道, 西湖区 (Xihu), 杭州市 Hangzhou, 浙江省, 310008, 中国",30.19331415,120.11930822,edu,
+25e9a2ec45c34d4610359196dc505a72c3833336,Benchmarking KAZE and MCM for Multiclass Classification,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
25d514d26ecbc147becf4117512523412e1f060b,Annotated crowd video face database,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
+2534997443c7e183c9f8e370ea1e82989ecc940d,Skeleton Search: Category-Specific Object Recognition and Segmentation Using a Skeletal Shape Model,Brown University,Brown University,"Brown University, Waterman Street, College Hill, Providence, Bristol, Rhode Island, 02912, USA",41.82686820,-71.40123146,edu,
+2525483e2d899c435437bd874208071183223b46,Autism as an Infantile Post-trauma Stress Disorder : A Hypothesis,Peking University,Peking University,"北京大学, 5号, 颐和园路, 稻香园南社区, 海淀区, 北京市, 100871, 中国",39.99223790,116.30393816,edu,
+25b1a031a0559a0bc4079e9011bdf527e1a39d19,Modelling the Time-Variant Covariates for Gait Recognition,University of Southampton,University of Southampton,"Waterfront Campus, European Way, Port of Southampton, St Mary's, Southampton, South East, England, SO14 3JW, UK",50.89273635,-1.39464295,edu,
+25bdcfdcdd9a944ce5adb8d2663856f242c580a1,Goal-Oriented Visual Question Generation via Intermediate Rewards,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+25bdcfdcdd9a944ce5adb8d2663856f242c580a1,Goal-Oriented Visual Question Generation via Intermediate Rewards,University of Technology Sydney,University of Technology Sydney,"University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia",-33.88096510,151.20107299,edu,
+25bdcfdcdd9a944ce5adb8d2663856f242c580a1,Goal-Oriented Visual Question Generation via Intermediate Rewards,Nanjing University,Nanjing University,"NJU, 三江路, 鼓楼区, 南京市, 江苏省, 210093, 中国",32.05659570,118.77408833,edu,
+25642be46de0f2e74e0da81a14646f8bfcc9000a,"What Does Classifying More Than 10, 000 Image Categories Tell Us?",Princeton University,Princeton University,"Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA",40.34829285,-74.66308325,edu,
+25642be46de0f2e74e0da81a14646f8bfcc9000a,"What Does Classifying More Than 10, 000 Image Categories Tell Us?",Columbia University,Columbia University,"Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA",40.84198360,-73.94368971,edu,
+25642be46de0f2e74e0da81a14646f8bfcc9000a,"What Does Classifying More Than 10, 000 Image Categories Tell Us?",Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
25c3cdbde7054fbc647d8be0d746373e7b64d150,ForgetMeNot: Memory-Aware Forensic Facial Sketch Matching,Beijing University of Posts and Telecommunications,Beijing University of Posts and Telecommunications,"北京邮电大学, 西土城路, 海淀区, 北京市, 100082, 中国",39.96014880,116.35193921,edu,
+252e48be0fd63d3a786021efa8733f8891101a82,Unsupervised Feature Learning With Winner-Takes-All Based STDP,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
25bf288b2d896f3c9dab7e7c3e9f9302e7d6806b,Neural Networks with Smooth Adaptive Activation Functions for Regression,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
25bf288b2d896f3c9dab7e7c3e9f9302e7d6806b,Neural Networks with Smooth Adaptive Activation Functions for Regression,Stony Brook University,Stony Brook University,"Stony Brook University, 100, Nicolls Road, Stony Brook, Suffolk County, New York, 11794, USA",40.91531960,-73.12706260,edu,
25bf288b2d896f3c9dab7e7c3e9f9302e7d6806b,Neural Networks with Smooth Adaptive Activation Functions for Regression,Oak Ridge National Laboratory,Oak Ridge National Laboratory,"Oak Ridge National Laboratory, Oak Ridge, Roane County, Tennessee, USA",35.93006535,-84.31240032,edu,
+255bb1a38169c7b78fb4da747cde18a961755d7a,A Bayesian generative model for learning semantic hierarchies,University of Michigan,University of Michigan,"University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA",42.29421420,-83.71003894,edu,
+255bb1a38169c7b78fb4da747cde18a961755d7a,A Bayesian generative model for learning semantic hierarchies,University of Washington,University of Washington,"University of Washington, Rainier Vista, Montlake, University District, Seattle, King County, Washington, 98195, USA",47.65432380,-122.30800894,edu,
+255bb1a38169c7b78fb4da747cde18a961755d7a,A Bayesian generative model for learning semantic hierarchies,Stanford University,Stanford University,"Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA",37.43131385,-122.16936535,edu,
+255bb1a38169c7b78fb4da747cde18a961755d7a,A Bayesian generative model for learning semantic hierarchies,MIT,Massachusetts Institute,"MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA",42.35839610,-71.09567788,edu,
+25f5df29342a04936ba0d308b4d1b8245a7e8f5c,Convolutional Pose Machines,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+25f5df29342a04936ba0d308b4d1b8245a7e8f5c,Convolutional Pose Machines,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+253b9b36565b83d0196c3bd9bf05089d9aafa242,Human Body Part Classification in Monocular Soccer Images,Technical University Munich,Technical University Munich,"TUM, 21, Arcisstraße, Bezirksteil Königsplatz, Stadtbezirk 03 Maxvorstadt, München, Obb, Bayern, 80333, Deutschland",48.14955455,11.56775314,edu,
+25e979e3c2d4fde4f297bf845796664424ab4c29,Whitening and Coloring transform for GANs,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+25e979e3c2d4fde4f297bf845796664424ab4c29,Whitening and Coloring transform for GANs,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
+25e979e3c2d4fde4f297bf845796664424ab4c29,Whitening and Coloring transform for GANs,University of Trento,University of Trento,"University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia",46.06588360,11.11598940,edu,
2588acc7a730d864f84d4e1a050070ff873b03d5,Action Recognition by an Attention-Aware Temporal Weighted Convolutional Neural Network,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
25c108a56e4cb757b62911639a40e9caf07f1b4f,Recurrent Scale Approximation for Object Detection in CNN,SenseTime,SenseTime,"China, Beijing Shi, Haidian Qu, WuDaoKou, Zhongguancun E Rd, 1号-7",39.99300800,116.32988200,company,"1 Zhongguancun E Rd, Haidian Qu, China"
2594a77a3f0dd5073f79ba620e2f287804cec630,Regularizing face verification nets for pain intensity regression,Johns Hopkins University,"Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA","3400 N Charles St, Baltimore, MD 21218, USA",39.32905300,-76.61942500,edu,
2594a77a3f0dd5073f79ba620e2f287804cec630,Regularizing face verification nets for pain intensity regression,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+2581a12189eb1a0b5b27a7fd1c2cbe44c88fcc20,Analyzing Classifiers: Fisher Vectors and Deep Neural Networks,TU Berlin,TU Berlin,"Franklinstraße 28-29, 10587 Berlin, Germany",52.51806410,13.32504250,edu,"Franklinstr. 28/29, 10587, Germany"
+2581a12189eb1a0b5b27a7fd1c2cbe44c88fcc20,Analyzing Classifiers: Fisher Vectors and Deep Neural Networks,TU Berlin,TU Berlin,"Franklinstraße 28-29, 10587 Berlin, Germany",52.51806410,13.32504250,edu,"Franklinstr. 28/29, 10587, Germany"
+256f09fe3163564958381d7f3727b5c27c19144c,Image2Emoji: Zero-shot Emoji Prediction for Visual Media,University of Amsterdam,University of Amsterdam,"Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland",52.35536550,4.95016440,edu,
25e2d3122d4926edaab56a576925ae7a88d68a77,Communicative-Pragmatic Treatment in Schizophrenia: A Pilot Study,University of Oulu,University of Oulu,"Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi",65.05921570,25.46632601,edu,
25e2d3122d4926edaab56a576925ae7a88d68a77,Communicative-Pragmatic Treatment in Schizophrenia: A Pilot Study,Harvard University,Harvard University,"Harvard University, Soldiers Field Road, Allston, Boston, Suffolk County, Massachusetts, 02163, USA",42.36782045,-71.12666653,edu,
+2550df6b33260cbe6fd60331ca6c7a8c0b48e80d,Human detection using depth information by Kinect,University of Texas at Austin,University of Texas at Austin,"University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA",30.28415100,-97.73195598,edu,
+2563b2adba98788a217565ba5a648f83cb75eeeb,Weight-Optimal Local Binary Patterns,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+250252b9693778e0af653efebfe17f68d649c8a7,3D Face Recognition,University of Houston,University of Houston,"UH, 4800, Calhoun Road, Houston, Harris County, Texas, 77004, USA",29.72079020,-95.34406271,edu,
+25c56f52c528112da99d0ae7e559500ef7532d3a,Towards Literate Artificial Intelligence,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+25dba68e4db0ce361032126b91f734f9252cae7c,DeepSetNet: Predicting Sets with Deep Neural Networks,University of Adelaide,University of Adelaide,"University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia",-34.91892260,138.60423668,edu,
+257e008c01a32b9b642553f3f1e59e61efcac4a6,Gender discrimination of eyes and mouths by individuals with autism.,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+257e008c01a32b9b642553f3f1e59e61efcac4a6,Gender discrimination of eyes and mouths by individuals with autism.,University of Pittsburgh,University of Pittsburgh,"University of Pittsburgh, Sutherland Drive, West Oakland, PGH, Allegheny County, Pennsylvania, 15240, USA",40.44415295,-79.96243993,edu,
+2599445b0990979483db54c707c9a33b18231910,Binary Biometric Representation through Pairwise Polar Quantization,University of Twente,University of Twente,"University of Twente, De Achterhorst;Hallenweg, Enschede, Regio Twente, Overijssel, Nederland, 7522NH, Nederland",52.23801390,6.85667610,edu,
+25ee08db14dca641d085584909b551042618b8bf,Learning to Segment Instances in Videos with Spatial Propagation Network,Tsinghua University,Tsinghua University,"清华大学, 30, 双清路, 五道口, 后八家, 海淀区, 100084, 中国",40.00229045,116.32098908,edu,
+25ee08db14dca641d085584909b551042618b8bf,Learning to Segment Instances in Videos with Spatial Propagation Network,"University of California, Merced","University of California, Merced","University of California, Merced, Ansel Adams Road, Merced County, California, USA",37.36566745,-120.42158888,edu,
+2577211aeaaa1f2245ddc379564813bee3d46c06,Seeing through the Human Reporting Bias: Visual Classifiers from Noisy Human-Centric Labels,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2577211aeaaa1f2245ddc379564813bee3d46c06,Seeing through the Human Reporting Bias: Visual Classifiers from Noisy Human-Centric Labels,Microsoft Research Asia,"Microsoft Live Labs Research, China",Microsoft Research Asia,35.86166000,104.19539700,company,
+25c3068e7964d3b894916a82b1fa93c9d6792886,Face Recognition with Histograms of Oriented Gradients,Robotics Institute,Robotics Institute,"Institute for Field Robotics, ประชาอุทิศ, กรุงเทพมหานคร, เขตราษฎร์บูรณะ, กรุงเทพมหานคร, 10140, ประเทศไทย",13.65450525,100.49423171,edu,
+25afe234435ede5fd95e47c3b58ed2c1da318f46,Towards Measuring and Inferring User Interest from Gaze,Cornell University,Cornell University,"Cornell University, Forest Home Drive, Forest Home, Tompkins County, New York, 14853, USA",42.45055070,-76.47835130,edu,
+258dda85eadcd2081d1e0131826aceac7f1e2415,Supervision Beyond Manual Annotations for Learning Visual Representations,Carnegie Mellon University,Carnegie Mellon University,"Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA",37.41021930,-122.05965487,edu,
+2544249e92b324a7f79da6eb556c387a4fa5226e,Monocular Video-Based Trailer Coupler Detection Using Multiplexer Convolutional Neural Network,Michigan State University,Michigan State University,"Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA",42.71856800,-84.47791571,edu,
+255971561c250d1ccee1402397586d2c7d0cd545,SmartBox : Benchmarking Adversarial Detection and Mitigation Algorithms for Face Recognition,Indian Institute of Technology Delhi,"IIIT-Delhi, India","IIIT-Delhi, Mathura Road, Friends Colony, South East Delhi, Delhi, 110020, India",28.54632595,77.27325504,edu,
diff --git a/scraper/reports/stats/no_separator_papers.csv b/scraper/reports/stats/no_separator_papers.csv index ee3cef0d..53e82bdd 100644 --- a/scraper/reports/stats/no_separator_papers.csv +++ b/scraper/reports/stats/no_separator_papers.csv @@ -1,344 +1,1264 @@ +614a547cb976fae955e276feb2ccc9a33f1c7806,Classifier-as-a-Service: Online Query of Cascades and Operating Points,,2012
+610c341985633b2d31368f8642519953c39ff7e8,Computational Load Balancing on the Edge in Absence of Cloud and Fog,Unknown,2018
+617a6935643615f09ef2b479609baa0d5f87cd67,To Be Taken At Face Value? Computerised Identification,,2002
+61acd4e07657094c2720bb60299dba0014ec89a6,Image annotation by kNN-sparse graph-based label propagation over noisily tagged web images,ACM TIST,2011
+0da2a7ee04092645867614db3574cb261f33b6e2,Watching Unlabeled Video Helps Learn New Human Actions from Very Few Labeled Snapshots,2013 IEEE Conference on Computer Vision and Pattern Recognition,2013
+0d30a662061a495e4b5aeb92a2edfac868b225ea,Quantification of Emotions for Facial Expression: Generation of Emotional Feature Space Using Self-Mapping,,2012
+0dd151d003ac9b7f3d6936ccdd5ff38fce76c29f,A Review and Comparison of Measures for Automatic Video Surveillance Systems,EURASIP J. Image and Video Processing,2008
+0dc34e186e8680336e88c3b5e73cde911a8774b8,Image Classification Using Naive Bayes Classifier With Pairwise Local Observations,J. Inf. Sci. Eng.,2017
+0d2e29f07275fe05a44b04f16cd3edd0c3f448f0,Development of the Korean Facial Emotion Stimuli: Korea University Facial Expression Collection 2nd Edition,,2017
0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2,Effects of emotional expressions on persuasion,,2016
+0dd72a3522b99aedea83b47c5d7b33a1df058fd0,A Set of Selected SIFT Features for 3D Facial Expression Recognition,2010 20th International Conference on Pattern Recognition,2010
0da4c3d898ca2fff9e549d18f513f4898e960aca,The Headscarf Effect Revisited: Further Evidence for a Culture-Based Internal Face Processing Advantage.,Perception,2015
+95f990600abb9c8879e4f5f7cd03f3d696fcdec4,An Online Algorithm for Constrained Face Clustering in Videos,Unknown,2018
+9501db000474dbd182579d311dfb1b1ab8fa871f,Supplementary of Multi-scale Deep Learning Architectures for Person Re-identification,,2017
+954af3d46d023d73c7ee97f2264451080f542084,The Interplay between Emotion and Cognition in Autism Spectrum Disorder: Implications for Developmental Theory,,2012
+5955bb0325ec4dd3b56759aeb96cc9c18b09bf3e,Self-Supervised Depth Learning Improves Semantic Segmentation,Unknown,2017
+59d10820e0a04d2d1acc43bb18a76c52e9946721,Attention to eyes and mouth in high-functioning children with autism.,Journal of autism and developmental disorders,2006
+592bbab1e073908c75584879bc00911e7246aebf,Exploiting feature Representations Through Similarity Learning and Ranking Aggregation for Person Re-identification,2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017),2017
92c2dd6b3ac9227fce0a960093ca30678bceb364,On Color Texture Normalization for Active Appearance Models,IEEE Transactions on Image Processing,2009
927ba64123bd4a8a31163956b3d1765eb61e4426,Customer satisfaction measuring based on the most significant facial emotion,Unknown,2018
+92f0e02c9f4e95098452d0fd78ba46cd6e7b1f6d,Dynamic machine learning for supervised and unsupervised classification. (Apprentissage automatique dynamique pour la classification supervisée et non supervisée),Unknown,2016
927ad0dceacce2bb482b96f42f2fe2ad1873f37a,Interest-Point based Face Recognition System,,2012
+0c3c83b7f030fe661548d362ddf33f37bb44043d,Crowd Motion Analysis Based on Social Force Graph with Streak Flow Attribute,J. Electrical and Computer Engineering,2015
+0c553e57cb6fe7bdf3212fbf86bcc869958db27f,Straight until proven gay: A systematic bias toward straight categorizations in sexual orientation judgments.,Journal of personality and social psychology,2016
0c3f7272a68c8e0aa6b92d132d1bf8541c062141,Kruskal-Wallis-Based Computationally Efficient Feature Selection for Face Recognition,,2014
+0ce4110d4c3d8b19ca0f7f75bc680aa9ba8d239a,Genetic Algorithms for Classifiers’ Training Sets Optimisation Applied to Human Face Recognition,,2007
+0cc5804c5f113c60ee5894f25ab7078364eef986,Epitomize Your Photos,Int. J. Computer Games Technology,2011
+0c1d5801f2b86afa969524dc74708a78450300d9,12 : Conditional Random Fields,,2014
+0c5b03a6083950aacd9aee2d276a232e6ce3213c,The Main Memory System: Challenges and Opportunities,,2015
+6603e7de5b155c86407edc43099b46b974b7f0bb,Local Feature Based Face Recognition,Unknown,2018
+66cc90ea586c914e6a3b50fe703f4379d530fad7,Automatic integration of social information in emotion recognition.,Journal of experimental psychology. General,2015
66533107f9abdc7d1cb8f8795025fc7e78eb1122,Visual Servoing for a User's Mouth with Effective Intention Reading in a Wheelchair-based Robotic Arm,,2001
+6681ec516067747a4576f737f10f8d9bbca2d8d1,Perturbative Neural Networks ( Supplementary Material ),Unknown,2018
661da40b838806a7effcb42d63a9624fcd684976,An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients,CIT,2010
+660c8a9fa166c1d81e65192e011eacfec208ec00,Discrimination of visual pedestrians data by combining projection and prediction learning,Unknown,2014
+3e56cbce67d312af2b3a7d0981e9cb33d2236bea,Boosting attribute recognition with latent topics by matrix factorization,JASIST,2017
3e4b38b0574e740dcbd8f8c5dfe05dbfb2a92c07,Facial Expression Recognition with Local Binary Patterns and Linear Programming,,2004
+3e0415f0e8c36f20042d6a1f8b7c216fb5543c3a,RGB-D Segmentation of Poultry Entrails,Unknown,2016
+3e42e336d67dad79ab6355c02f1f045f8a71a18f,Autism spectrum traits in normal individuals: a preliminary VBM analysis,,2015
3e04feb0b6392f94554f6d18e24fadba1a28b65f,Subspace Image Representation for Facial Expression Analysis and Face Recognition and its Relation to the Human Visual System,,2007
+3ed60f021fe469f2423d04917e69864251d23e08,Metadata of the chapter that will be visualized in SpringerLink,Unknown,2012
+5087d9bdde0ba5440eb8658be7183bf5074a2a94,Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model,2015 IEEE International Conference on Computer Vision (ICCV),2015
+50a8dc4c1d40967a95b684eb421edd03415fb7ab,Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance,CoRR,2016
+50894e607cd5eb616913b520c4e238a73f432b86,Neural correlates of eye gaze processing in the infant broader autism phenotype.,Biological psychiatry,2009
50eb2ee977f0f53ab4b39edc4be6b760a2b05f96,Emotion recognition based on texture analysis of facial expression,2011 International Conference on Image Information Processing,2011
50e45e9c55c9e79aaae43aff7d9e2f079a2d787b,Unbiased Feature Selection in Learning Random Forests for High-Dimensional Data,,2015
+50af3b6f7192951b42c2531ee931c8244e505a5c,Weakly Supervised Learning for Attribute Localization in Outdoor Scenes,2013 IEEE Conference on Computer Vision and Pattern Recognition,2013
+5047cae1b6f47ac1715479abfa3daf1c1a063977,Predictor Combination at Test Time — Supplemental Document,,2017
+50984f8345a3120d0e6c0a75adc2ac1a13e37961,Impaired face processing in autism: fact or artifact?,Journal of autism and developmental disorders,2006
+50bf19a06915778a0bcbdef700f91b56258a4e1f,Common and distinct neural features of social and non-social reward processing in autism and social anxiety disorder.,Social cognitive and affective neuroscience,2014
+507af6591900a7165c529eca9fd370008c1ac87c,"For Black men, being tall increases threat stereotyping and police stops.",Proceedings of the National Academy of Sciences of the United States of America,2018
50c0de2cccf7084a81debad5fdb34a9139496da0,"The Influence of Annotation, Corpus Design, and Evaluation on the Outcome of Automatic Classification of Human Emotions",Front. ICT,2016
+68ae4db6acf5361486f153ee0c0d540e0823682a,FlashReport Memory conformity for con fi dently recognized items : The power of social in fl uence on memory reports,Unknown,2012
+68e4ed4daa2ae94c789443ed222601a4a47f9a45,Building Extraction from Polarimetric Interferometric Sar Data Using Bayesian Network,,2009
688754568623f62032820546ae3b9ca458ed0870,Resting high frequency heart rate variability is not associated with the recognition of emotional facial expressions in healthy human adults,,2016
+68249064f7d5046abef785ada541244fa67b4346,"Contribution of Developmental Psychology to the Study of Social Interactions: Some Factors in Play, Joint Attention and Joint Action and Implications for Robotics",,2018
+68c279d4fcc02710056e73a3b0d0d564a7615cad,Unified framework for fast exact and approximate search in dissimilarity spaces,ACM Trans. Database Syst.,2007
68c17aa1ecbff0787709be74d1d98d9efd78f410,Gender Classification from Face Images Using Mutual Information and Feature Fusion,,2012
68f61154a0080c4aae9322110c8827978f01ac2e,"Recognizing blurred , non-frontal , illumination and expression variant partially occluded faces",Unknown,2016
6821113166b030d2123c3cd793dd63d2c909a110,Acquisition and Indexing of Rgb-d Recordings for Facial Expressions and Emotion Recognition1,,2015
57bf9888f0dfcc41c5ed5d4b1c2787afab72145a,Robust Facial Expression Recognition Based on Local Directional Pattern,,
+57522ff758642e054d7c50753ec1c3fe598533f0,Information-Based Boundary Equilibrium Generative Adversarial Networks with Interpretable Representation Learning,,2018
+5740a5f9cbfe790afc0ba9a425cfb71197927470,Supplementary Material for Superpixel Sampling Networks,Unknown,2018
57f8e1f461ab25614f5fe51a83601710142f8e88,Region Selection for Robust Face Verification using UMACE Filters,,2007
57a1466c5985fe7594a91d46588d969007210581,A taxonomy of face-models for system evaluation,2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops,2010
+5727ac51ad6fb67d81cc3ef2c04440c179bd53ab,Oxytocin attenuates amygdala responses to emotional faces regardless of valence.,Biological psychiatry,2007
+577c1d59e43f04a4bfda95b0b9e3b41d893bc0a2,Faster Evaluation of Labor-Intensive Features,Unknown,2015
+5700291077b509b11fb227f84ee9fc2de8f2df99,Line search and trust region strategies for canonical decomposition of semi-nonnegative semi-symmetric 3rd order tensors,,2017
57a14a65e8ae15176c9afae874854e8b0f23dca7,Seeing Mixed Emotions: The Specificity of Emotion Perception From Static and Dynamic Facial Expressions Across Cultures,,2018
+3b152bdeedb97d68dd69bbb806c60c205e6fa696,Patch-Based Principal Component Analysis for Face Recognition,,2017
+3b6602e64e62e5703151d17475d4728bd2095256,Brief Communication Oxytocin Modulates Neural Circuitry for Social Cognition and Fear in Humans,,2005
3b7f6035a113b560760c5e8000540fc46f91fed5,Coupling Alignments with Recognition for Still-to-Video Face Recognition,2013 IEEE International Conference on Computer Vision,2013
3bd1d41a656c8159305ba2aa395f68f41ab84f31,Entity-Based Opinion Mining from Text and Multimedia,,2015
+3b466bb66ee79c8e9bcdb6cf9acb54b864dda735,"Joint inference of groups, events and human roles in aerial videos",2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2015
+3b6310052026fc641d3fa639647342c45d8f5bd5,Eye Contact Modulates Cognitive Processing Differently in Children With Autism,,2015
+3b2f78a4edf5da876e52513d0e3960da7d3a253f,Qualitative Evaluation of Detection and Tracking Performance,2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance,2012
+3b23c39f21156f9ea86ad8bb2ca53b2cf56b4181,Predictable Performance and Fairness Through Accurate Slowdown Estimation in Shared Main Memory Systems,CoRR,2018
+6f5d57460e0e156497c4667a875cc5fa83154e3a,Retinal Verification Using a Feature Points-Based Biometric Pattern,EURASIP J. Adv. Sig. Proc.,2009
6f957df9a7d3fc4eeba53086d3d154fc61ae88df,Modélisation et suivi des déformations faciales : applications à la description des expressions du visage dans le contexte de la langue des signes,,2007
+6fee701352f0f5c4abea3e918ddcf078243253cc,Alcohol and Remembering Sexual,,
+6ff9b66aec16d84b1133850e7e8ce188a5a9a7f4,Do-gooder derogation in children: the social costs of generosity,,2015
+6f813ccf106360cc9c3d6df849cc04d881d0a6e8,"360◦ User Profiling: Past, Future, and Applications",,2016
6f5151c7446552fd6a611bf6263f14e729805ec7,Facial Action Unit Recognition using Filtered Local Binary Pattern Features with Bootstrapped and Weighted ECOC Classi ers,,2010
+0344f29da9641edc36bc4952e1f7a4bfd8dd9bb3,Facial expression at retrieval affects recognition of facial identity,,2015
03167776e17bde31b50f294403f97ee068515578,Chapter 11. Facial Expression Analysis,,2004
+032c1e19a59cdbeb3fb741a812980f52c1461ce1,"Mining textural knowledge in biological images: Applications, methods and trends",,2017
030ef31b51bd4c8d0d8f4a9a32b80b9192fe4c3f,Inhibition-Induced Forgetting Results from Resource Competition between Response Inhibition and Memory Encoding Processes.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2015
+033e3fe75da26d8d3dd3cb0f99640181655e6746,From generic to specific deep representations for visual recognition,2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),2015
03fc466fdbc8a2efb6e3046fcc80e7cb7e86dc20,A real time system for model-based interpretation of the dynamics of facial expressions,2008 8th IEEE International Conference on Automatic Face & Gesture Recognition,2008
+035886f58b550be140b1d4dbba0ea0479030589f,Trajectory bundle estimation For perception-driven planning,Unknown,2013
03f14159718cb495ca50786f278f8518c0d8c8c9,Performance evaluation of HOG and Gabor features for vision-based vehicle detection,"2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE)",2015
03ac1c694bc84a27621da6bfe73ea9f7210c6d45,Chapter 1 Introduction to information security foundations and applications,Unknown,2018
+0324a22f71927bee2a448f800287cde562dc2726,People detection in crowded scenes by context-driven label propagation,2016 IEEE Winter Conference on Applications of Computer Vision (WACV),2016
03bd58a96f635059d4bf1a3c0755213a51478f12,Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization,IEEE Transactions on Image Processing,2015
+034f7fcf5a393ac3307ac3609c2b971df6efaff6,Can Synthetic Data Handle Unconstrained Gaze Estimation?,Unknown,2017
+03d10c88aebd7aabe603d455c7bafa9231c7cf51,Hyperconnectivity of the Right Posterior Temporo-parietal Junction Predicts Social Difficulties in Boys with Autism Spectrum Disorder.,Autism research : official journal of the International Society for Autism Research,2015
03fe3d031afdcddf38e5cc0d908b734884542eeb,Engagement with Artificial Intelligence through Natural Interaction Models,Unknown,2017
+9b9b6d34deebb534de66017381be7578e13b761d,"Submitted to the Alfred P . Sloan School of Management in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY IN MANAGEMENT at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February , 2007",,2007
+9bd9050c53d90dfa86cb22501812afe6fc897406,Fine-Grained and Layered Object Recognition,IJPRAI,2012
9b474d6e81e3b94e0c7881210e249689139b3e04,VG-RAM Weightless Neural Networks for Face Recognition,,2009
+9bfe2732a905cb0aab370d1146a29b9d4129321d,Social Judgments Are Influenced by Both Facial Expression and Direction of Eye Gaze,,2011
+9bfda2f5144867d5712a8fcbea9dd5fa69d3312b,Image Super-Resolution Using VDSR-ResNeXt and SRCGAN,CoRR,2018
+9e594ae4f549e0d838f497de31a5b597a6826d55,Recognition of Emotion from Facial Expressions with Direct or Averted Eye Gaze and Varying Expression Intensities in Children with Autism Disorder and Typically Developing Children,,2014
+9e1a21c9af589fc2148ce96aa93c9df4a9e5ae02,Undoing the Damage of Dataset Bias,,2012
+9e384187941e939453fc0c7585c1a8e76d535c02,A Robust Approach to Automatic Iris Localization,,2009
+9ed3e04586f311b1e2b5ded9c9c4bfeeecf27f0c,Understanding rapid category detection via multiply degraded images.,Journal of vision,2009
+9ef9046cc26946acedda3f515d9149a76e19cd6e,A Unified Multi-Faceted Video Summarization System,CoRR,2017
+9e8dd40aea9204ad670b312a46ba807bfc0c61ce,Distribution-sensitive learning for imbalanced datasets Citation,Unknown,2013
+9e1712ac91c7a882070a8e2740ed476d59d6d5d4,Expressive image manipulations for a variety of visual representations. (Manipulations d'image expressives pour une variété de représentations visuelles),Unknown,2009
+9e263d429c3b87aae2653b6fb925b32b63c172cd,Enhanced image and video representation for visual recognition,Unknown,2014
+048eb50c398fa01bd15329945113341102d96454,Addressing perceptual insensitivity to facial affect in violent offenders: first evidence for the efficacy of a novel implicit training approach.,Psychological medicine,2014
+044da4715e439b4f91cee8eec55299e30a615c56,Inducing a Concurrent Motor Load Reduces Categorization Precision for Facial Expressions,,2016
+040eb316cec08b36ae0b57fede86043ee0526686,Learning Reliable and Scalable Representations Using Multimodal Multitask Deep Learning,Unknown,2018
047d7cf4301cae3d318468fe03a1c4ce43b086ed,Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression,"IEEE/ACM Transactions on Audio, Speech, and Language Processing",2015
04317e63c08e7888cef480fe79f12d3c255c5b00,Face Recognition Using a Unified 3D Morphable Model,Unknown,2016
+0419726a00e16ea89868792ca94f5b1b262c5597,An analytical formulation of global occlusion reasoning for multi-target tracking,2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops),2011
+04df36ea27f14f96bb1b33d76103d1dee7c6e0ca,Blur invariant pattern recognition and registration in the Fourier domain,,2009
0470b0ab569fac5bbe385fa5565036739d4c37f8,Automatic face naming with caption-based supervision,2008 IEEE Conference on Computer Vision and Pattern Recognition,2008
+6af35225cfd744b79577c126e553f549e5b5cdcc,Title Discriminative Hessian Eigenmaps for face recognition,Unknown,2010
6a657995b02bc9dee130701138ea45183c18f4ae,The Timing of Facial Motion in posed and Spontaneous Smiles,IJWMIP,2004
+6af98f9843ba629ae1b0347e8b8d81a263f8d7f2,Does this recession make me look black? The effect of resource scarcity on the categorization of biracial faces.,Psychological science,2012
+6ad5a38df8dd4cdddd74f31996ce096d41219f72,Multi-cue onboard pedestrian detection,2009 IEEE Conference on Computer Vision and Pattern Recognition,2009
+6a9c460952a96a04e12caa7bae07ae2f7df1238e,Exploiting scene context for on-line object tracking in unconstrained environments. (Exploitation du contexte de scène pour le suivi d'objet en ligne dans des environnements non contraints),Unknown,2016
324f39fb5673ec2296d90142cf9a909e595d82cf,Relationship Matrix Nonnegative Decomposition for Clustering,,2014
32575ffa69d85bbc6aef5b21d73e809b37bf376d,Measuring Biometric Sample Quality in Terms of Biometric Information,2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference,2006
+32d6ee09bd8f1a7c42708d6dd8a5fb85ac4e08bc,Non-Interfering Effects of Active Post-Encoding Tasks on Episodic Memory Consolidation in Humans,,2017
+3535ba0cba9bf03443d52cbfc9a87090ca2e5d49,Supplementary Material : Synthesized Classifiers for Zero-Shot Learning,Unknown,2016
+35d7b5738350a1bbfd8d7a591433d1664f909009,VisemeNet: Audio-Driven Animator-Centric Speech Animation,ACM Trans. Graph.,2018
+35410a58514cd5fd66d9c43d42e8222526170c1b,Shared mechanism for emotion processing in adolescents with and without autism,,2017
35f084ddee49072fdb6e0e2e6344ce50c02457ef,A bilinear illumination model for robust face recognition,Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1,2005
+690f5d35489c63ec7309b9e4d77c929815065257,Complementary effects of gaze direction and early saliency in guiding fixations during free viewing.,Journal of vision,2014
+69dc87575b56ba7f60fa24bdd4fceabeeaf39a80,Decoding of nonverbal language in alcoholism: A perception or a labeling problem?,Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors,2016
69c2ac04693d53251500557316c854a625af84ee,"50 years of biometric research: Accomplishments, challenges, and opportunities",Pattern Recognition Letters,2016
3cb2841302af1fb9656f144abc79d4f3d0b27380,When 3 D-Aided 2 D Face Recognition Meets Deep Learning : An extended UR 2 D for Pose-Invariant Face Recognition,Unknown,2017
3cc3cf57326eceb5f20a02aefae17108e8c8ab57,Benchmark for Evaluating Biological Image Analysis Tools,,2007
+3caf02979d7cd83d2f3894574c86babf3e201bf3,Seeing to hear? Patterns of gaze to speaking faces in children with autism spectrum disorders,,2014
+3c917f071bfc1244c75fca3ceed0a8c46bb975cc,Reduced acetylcholinesterase activity in the fusiform gyrus in adults with autism spectrum disorders.,Archives of general psychiatry,2011
3c374cb8e730b64dacb9fbf6eb67f5987c7de3c8,Measuring Gaze Orientation for Human-Robot Interaction,,2009
+3c68763caa67dee55bca76f0f71dd4530f3fd57c,Ranking to Learn and Learning to Rank: On the Role of Ranking in Pattern Recognition Applications,CoRR,2017
+3c9f2444b1de1bf960664d8c3109f8b8d5dee44b,Automatic Facial Feature Extraction for Face Recognition,,2007
3c8da376576938160cbed956ece838682fa50e9f,Aiding face recognition with social context association rule based re-ranking,IEEE International Joint Conference on Biometrics,2014
+3c90f2603ef99222697b76d7ab123f513a1f4baa,The Effects of Alcohol Intoxication on Accuracy and the Confidence–Accuracy Relationship in Photographic Simultaneous Line‐ups,,2017
+568067d7232c753e182dbc1d7075364560ffc363,Scope of physiological and behavioural pain assessment techniques in children – a review,,2018
+56c701467da819088c3f734f3ba36a793d645992,Title Underconnectivity of the Superior Temporal Sulcus Predicts Emotion Recognition Deficits in Autism Social Cognitive and Affective Neuroscience Advance Access Published Number of Words,,2013
+560b46547720b3a892f90a337835875f74f4f4ec,Discriminating Color Faces for Recognition,,2008
+56852a56dd830a6ee3882773c453025ddec652e2,Emotion recognition through static faces and moving bodies: a comparison between typically developed adults and individuals with high level of autistic traits,,2015
+56c5d08103c5bf4b263a81da73135455136bbe6d,Kernel MBPLS for a Scalable and Multi-Camera Person Re-Identification System,Unknown,2018
+56bb321e0e180f72be9c4e9eb791b251073750e2,Labeling and modeling large databases of videos,,2012
512befa10b9b704c9368c2fbffe0dc3efb1ba1bf,Evidence and a computational explanation of cultural differences in facial expression recognition.,Emotion,2010
51a8dabe4dae157aeffa5e1790702d31368b9161,Face recognition under generic illumination based on harmonic relighting,IJPRAI,2005
+51b70582fb0d536d4a235f91bf6ad382f29e2601,Detection of emotions from video in non-controlled environment. (Détection des émotions à partir de vidéos dans un environnement non contrôlé),Unknown,2013
511a8cdf2127ef8aa07cbdf9660fe9e0e2dfbde7,A Community Detection Approach to Cleaning Extremely Large Face Database,,2018
+3d3fdeb8792859543d791e34af4005a80f348eed,Children's racial bias in perceptions of others' pain.,The British journal of developmental psychology,2014
+3d741315108b95cdb56d312648f5ad1c002c9718,Image-based face recognition under illumination and pose variations.,"Journal of the Optical Society of America. A, Optics, image science, and vision",2005
+3d67e97227846f579d1825e00d395d30e17f5d0e,Face and ECG Based Multi-Modal Biometric Authentication,,2012
+3d33f16ffb3f56e63b8b5c51147b1a07840d734a,Developing Cognitions about Race: White 5- to 10-Year-Olds’ Perceptions of Hardship and Pain Running head: DEVELOPING COGNITIONS ABOUT RACE,,2017
+3d67aa108e65e636158abc0f31b703af3d31baa6,Decorrelating Semantic Visual Attributes by Resisting the Urge to Share,,2013
3d9db1cacf9c3bb7af57b8112787b59f45927355,Improving Medical Students’ Awareness of Their Non-Verbal Communication through Automated Non-Verbal Behavior Feedback,Front. ICT,2016
+58cbd5a31e92cff29e29e8b25ee79f30ff4e6d4b,Culture shapes spatial frequency tuning for face identification.,Journal of experimental psychology. Human perception and performance,2017
587c48ec417be8b0334fa39075b3bfd66cc29dbe,Serial dependence in the perception of attractiveness,,2015
+6775c818b26263c885b0ce85c224dfd942c9652e,Pedestrian and Object Detection Using Learned Convolutional Filters,,2015
67c3c1194ee72c54bc011b5768e153a035068c43,Street Scenes: towards scene understanding in still images,,2006
+67a3cc056a539d17f00b0be550a2fc7cb2118dc5,Scalable Image Retrieval by Sparse Product Quantization,IEEE Transactions on Multimedia,2017
+6757254d27b761ada5dbd88642bd0112fcb962cf,Gait Recognition Using Wearable Motion Recording Sensors,EURASIP J. Adv. Sig. Proc.,2009
+0b0eb6363a0c5b80c544aff091d547122986131b,Remembering faces with emotional expressions,,2014
+0b937abb3b356a2932d804f9fc4b463485f63d0e,Visual word disambiguation by semantic contexts,2011 International Conference on Computer Vision,2011
+0b24cca96ca61248a3fa3973525a967f94292835,Two Novel Face Recognition Approaches,Unknown,2018
0b85b50b6ff03a7886c702ceabad9ab8c8748fdc,Is there a dynamic advantage for facial expressions?,Journal of vision,2011
+0b19177107a102ee81e5ef1bb9fb2f2881441503,Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition,EURASIP J. Adv. Sig. Proc.,2008
+0b8ef6f5ec5dfc3eded5241fd3d636a596b94d26,Stereological analysis of amygdala neuron number in autism.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2006
0be80da851a17dd33f1e6ffdd7d90a1dc7475b96,Weighted Feature Gaussian Kernel SVM for Emotion Recognition,,2016
+0be8b12f194fb604be69c139a195799e8ab53fd3,Talking Heads: Detecting Humans and Recognizing Their Interactions,2014 IEEE Conference on Computer Vision and Pattern Recognition,2014
+0b6c10ea6bf8a6c254e00fcc2163c4b6fc0f1c3a,"Anti-Spoofing for Text-Independent Speaker Verification: An Initial Database, Comparison of Countermeasures, and Human Performance","IEEE/ACM Transactions on Audio, Speech, and Language Processing",2016
+93a66d470c1840d11eaa96ead3b600450b3cc9f8,Gaze aversion as a cognitive load management strategy in autism spectrum disorder and Williams syndrome,,2012
93747de3d40376761d1ef83ffa72ec38cd385833,Team members' emotional displays as indicators of team functioning.,Cognition & emotion,2016
+93610676003ef1dcda3864b236bca3852cb05388,RECOGNIZING ACTIVITIES WITH CLUSTER-TREES OF TRACKLETS 1 Recognizing activities with cluster-trees of tracklets,Unknown,2015
+93a4c7ac0b09671db8cd3adbe62851d7befc4658,Machine Analysis of Facial Expressions,Unknown,2018
+94d5ebe936c101699e678f6f0cddd8a732986814,What you see is what you get: contextual modulation of face scanning in typical and atypical development,,2014
+949079cc466e875df1ee6bd6590052ba382a35cf,0 Large-Scale Face Image Retrieval :,Unknown,2012
+940865fc3f7ee5b386c4188c231eb6590db874e9,Security and Surveillance System for Drivers Based on User Profile and learning systems for Face Recognition,Network Protocols & Algorithms,2015
+0ee59e5baed4271ab85c85332550ca1539733a19,Atypical Modulations of N170 Component during Emotional Processing and Their Links to Social Behaviors in Ex-combatants,,2017
+0ec17d929f62660fb3d1bcdd791f9639034f5344,How Do We Evaluate Facial Emotion Recognition?,,2016
0e73d2b0f943cf8559da7f5002414ccc26bc77cd,Similarity Comparisons for Interactive Fine-Grained Categorization,2014 IEEE Conference on Computer Vision and Pattern Recognition,2014
0e1983e9d0e8cb4cbffef7af06f6bc8e3f191a64,Estimating illumination parameters in real space with application to image relighting,,2005
+607bfdbf583c4dfa29491eedc3934f2293e1fa96,A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function.,Proceedings of the National Academy of Sciences of the United States of America,2010
+609ff585468ad0faba704dde1a69edb9f847c201,LogDet Rank Minimization with Application to Subspace Clustering,,2015
+60189e2b592056d43a28b6ffa491867f793ebe1e,Bağlamın Hiyerarşik Doğası,,2016
60040e4eae81ab6974ce12f1c789e0c05be00303,Graphical Facial Expression Analysis and Design Method: An Approach to Determine Humanoid Skin Deformation,,2012
60bffecd79193d05742e5ab8550a5f89accd8488,Proposal Classification using sparse representation and applications to skin lesion diagnosis,,
346dbc7484a1d930e7cc44276c29d134ad76dc3f,Artists portray human faces with the Fourier statistics of complex natural scenes.,Network,2007
+34cd99528d873e842083abec429457233fdb3226,Person Re-identification using group context,Unknown,2018
34d484b47af705e303fc6987413dc0180f5f04a9,RI:Medium: Unsupervised and Weakly-Supervised Discovery of Facial Events,,2010
+349668b75c4398c075fc681f563a80ad7cf6b4f2,Real-time face pose estimation from single range images,2008 IEEE Conference on Computer Vision and Pattern Recognition,2008
+341de07abfb89bf78f3a72513c8bce40d654e0a3,Sparse and Deep Generalizations of the FRAME Model,,2017
+5ab2c97ada652ff8f641e1b30cc27050c0ffa7e0,Comparing Emotion Recognition Skills among Children with and without Jailed Parents,,2016
+5a15eedcd836337b50a2bfab82ded7a9b939aca5,Perception of temporal asymmetries in dynamic facial expressions,,2015
+5aa7f33cdc00787284b609aa63f5eb5c0a3212f6,Multiplicative mixing of object identity and image attributes in single inferior temporal neurons,,2018
+5a226afa04f03086e402b22ee2c43089b68fa3ba,Multiview RGB-D Dataset for Object Instance Detection,2016 Fourth International Conference on 3D Vision (3DV),2016
+5ac8edd62fe23911e19d639287135f91e22421cc,Gender and 3D facial symmetry: What's the relationship?,2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG),2013
+5f02e49aa0fe467bbeb9de950e4abb6c99133feb,"Enhancing person re-identification by late fusion of low-, mid- and high-level features",IET Biometrics,2018
+5f39d07dd39e5d7cfba535ada3a0ab9d5d0efb5b,Perceptual dehumanization of faces is activated by norm violations and facilitates norm enforcement.,Journal of experimental psychology. General,2016
5fea26746f3140b12317fcf3bc1680f2746e172e,Semantic Jitter: Dense Supervision for Visual Comparisons via Synthetic Images,2017 IEEE International Conference on Computer Vision (ICCV),2017
+5fc371760fd4c8abe94b91ae2ca03d428ac05faa,Fear-specific amygdala function in children and adolescents on the fragile x spectrum: a dosage response of the FMR1 gene.,Cerebral cortex,2014
+3394168ff0719b03ff65bcea35336a76b21fe5e4,Object Detection Combining Recognition and Segmentation,,2007
+334e559e8decadcedbe8e495b3f5430536cff32c,"The Attentional Suppressive Surround: Eccentricity, Location-Based and Feature-Based Effects and Interactions",,2018
+3369692338841f14ce032fc5d0b5b4fe7cc79f1a,Visualising mental representations: A primer on noise-based reverse correlation in social psychology,,2017
+05904c87cb1d0b1f17fcb018fa0344c020694f36,Modulation of the composite face effect by unintended emotion cues,,2017
050fdbd2e1aa8b1a09ed42b2e5cc24d4fe8c7371,Spatio-Temporal Scale Selection in Video Data,Journal of Mathematical Imaging and Vision,2017
+05ef5efd9e42f49dbb9e50ec3fe367f275a94931,Biologically Inspired Processing for Lighting Robust Face Recognition,Unknown,2018
+05b6c32304dd1673c14f1e1efce4e4d5c4402275,What are the Visual Features Underlying Rapid Object Recognition?,,2011
+05fcbe4009543ec8943bdc418ee81e9594b899a4,Social perception in autism spectrum disorders: impaired category selectivity for dynamic but not static images in ventral temporal cortex.,Cerebral cortex,2014
05e3acc8afabc86109d8da4594f3c059cf5d561f,Actor-Action Semantic Segmentation with Grouping Process Models,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
0559fb9f5e8627fecc026c8ee6f7ad30e54ee929,Facial Expression Recognition,,2011
+0549dc0290fe988ede74c4e030ae485c13eaa54a,Development of Vision Based Multiview Gait Recognition System with MMUGait Database,,2014
+05f3f8f6f97db00bafa2efd2ac9aac570603c0c6,TGIF: A New Dataset and Benchmark on Animated GIF Description,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
9d8ff782f68547cf72b7f3f3beda9dc3e8ecfce6,Improved Pseudoinverse Linear Discriminant Analysis Method for Dimensionality Reduction,IJPRAI,2012
+9d2ad0b408bddc9c5a713e250b52aa48f1786a46,Visual Recognition Using Local Quantized Patterns,Unknown,2012
+9d0bf3b351fb4d80cee5168af8367c5f6c8b2f3a,"The Tromso Infant Faces Database (TIF): Development, Validation and Application to Assess Parenting Experience on Clarity and Intensity Ratings",,2017
+9dc70aa3d51a9403e1894a7fa535ace99b527861,3 Bayesian Tracking by Online Co-Training and Sequential Evolutionary Importance Resampling,Unknown,2012
+9dd47158cd7ee3725be3aa7a2ce9b25a7d4aed74,Clustering-driven Deep Embedding with Pairwise Constraints,CoRR,2018
+9cf69de9e06e39f7f7ce643b3327bf69be8b9678,SHREC ’ 18 track : Recognition of geometric patterns over 3 D models,Unknown,2018
+9cf6d66a0b4e5a3347466a60caea411d67c4b5b7,Joint transfer component analysis and metric learning for person re-identification,Unknown,2018
+9cd8e1ccc5a410c7f31c7e404588597c0bb1952b,Whats Your Type ? Personalized Prediction of Facial Attractiveness,,
9ce0d64125fbaf625c466d86221505ad2aced7b1,Recognizing expressions of children in real life scenarios View project PhD ( Doctor of Philosophy ) View project,Unknown,2017
+9cf07922cf91c4aea66c8d72606ca444f4607cc6,Distinct neural activation patterns underlie economic decisions in high and low psychopathy scorers.,Social cognitive and affective neuroscience,2014
023ed32ac3ea6029f09b8c582efbe3866de7d00a,Discriminative learning from partially annotated examples,,2016
+02e05ad42dbe99257eee1bff3e28feaa005e5924,Remembering Who Was Where: A Happy Expression Advantage for Face Identity-Location Binding in Working Memory,,2018
+0252256fa23eceb54d9eea50c9fb5c775338d9ea,Application-driven Advances in Multi-biometric Fusion,Unknown,2018
+02a2fa826a348cc3bc46a1a31a49dce8d06ca366,Individual differences in the spontaneous recruitment of brain regions supporting mental state understanding when viewing natural social scenes.,Cerebral cortex,2011
+02b72a5a4389cb32a7dd784b1c9084e8412e2e78,Hierarchical Bayesian Image Models,Unknown,2018
+a45ec771ca2db81088c52c173eed9ec2022a8a70,Impaired recognition of negative basic emotions in autism: a test of the amygdala theory.,Social neuroscience,2006
a4c430b7d849a8f23713dc283794d8c1782198b2,Video Concept Embedding,,2016
+a48c71153265d6da7fbc4b16327320a5cbfa6cba,Unite the People: Closing the loop between 3D and 2D Human Representations Supplementary Material,,2017
+a32f28156b47fd262e04426806037d138bb3ed0b,Fisher’s linear discriminant (FLD) and support vector machine (SVM) in non-negative matrix factorization (NMF) residual space for face recognition,,2010
+a361e820a85fa91f23091068f8177c58489304b1,Hard to “tune in”: neural mechanisms of live face-to-face interaction with high-functioning autistic spectrum disorder,,2012
a3f684930c5c45fcb56a2b407d26b63879120cbf,LPM for Fast Action Recognition with Large Number of Classes,,2013
+a3177f82ea8391d9d733be47e4a0656a7b56e64c,The Roles of Emotions in the Law,,2016
+a36aa784e00d479bb0e6cb8aa6b6cd2dfeadfe1b,Evaluation of different features for face recognition in video,Unknown,2014
+a3fa023d7355662d066882df8dead0cac6a8321e,Supplementary Material for “Adversarial Inverse Graphics Networks: Learning 2D-to-3D Lifting and Image-to-Image Translation from Unpaired Supervision”,,2017
a32d4195f7752a715469ad99cb1e6ebc1a099de6,The Potential of Using Brain Images for Authentication,,2014
a308077e98a611a977e1e85b5a6073f1a9bae6f0,Intelligent Screening Systems for Cervical Cancer,,2014
+a3be57fc74460463f03c2a14e81e7e62c05c692e,Object Detection,,2014
a35d3ba191137224576f312353e1e0267e6699a1,Increasing security in DRM systems through biometric authentication,,2001
+a3b70bf7e676f92ebb6dec3e2889c9131634f8b9,Use of 3D faces facilitates facial expression recognition in children,,2017
+b55489547790f7fb2c8b4689530b5660fbc8ee64,Face Scanning in Autism Spectrum Disorder and Attention Deficit/Hyperactivity Disorder: Human Versus Dog Face Scanning,,2015
+b5e3beb791cc17cdaf131d5cca6ceb796226d832,Novel Dataset for Fine-Grained Image Categorization: Stanford Dogs,,2012
b55d0c9a022874fb78653a0004998a66f8242cad,Hybrid Facial Representations for Emotion Recognition Woo,,2013
b5930275813a7e7a1510035a58dd7ba7612943bc,Face Recognition Using L-Fisherfaces,J. Inf. Sci. Eng.,2010
+b2b28eeeaa2b613bf30b5bfee5ec4272ce184bf3,Measuring Collectiveness via Refined Topological Similarity,TOMCCAP,2016
b216040f110d2549f61e3f5a7261cab128cab361,Weighted Voting of Discriminative Regions for Face Recognition,IEICE Transactions,2017
+b255474d62f082fa97f50ea1174bf339522f6c99,Facial mimicry in its social setting,,2015
+b239b39c08a08d9c3b1da68a7bce162b580a746e,Gaze selection in complex social scenes,Unknown,2008
+b29fa452d737e2b6aa16d6f82a9a8daaea655287,Spontaneous Facial Actions Map onto Emotional Experiences in a Non-social Context: Toward a Component-Based Approach,,2017
+d9df2ed64494f54c0e2529f2c05a16423a57235c,A Novel Approach for Facial Expression Analysis in real time applications using SIFT flow and SVM,,2015
+d90026a9ca2489707aff2807617f3782f78097be,"Survey on audiovisual emotion recognition: databases, features, and data fusion strategies",,2014
ac1d97a465b7cc56204af5f2df0d54f819eef8a6,A Look at Eye Detection for Unconstrained Environments,,2010
+ac5d9753a53b0d69308596908032f85b416c0056,Selectivity of Face Distortion Aftereffects for Differences in Expression or Gender,,2012
accbd6cd5dd649137a7c57ad6ef99232759f7544,Facial Expression Recognition with Local Binary Patterns and Linear Programming,Unknown,2004
ac51d9ddbd462d023ec60818bac6cdae83b66992,An Efficient Robust Eye Localization by Learning the Convolution Distribution Using Eye Template,,2015
acc548285f362e6b08c2b876b628efceceeb813e,Objectifying Facial Expressivity Assessment of Parkinson's Patients: Preliminary Study,,2014
+ac56b4d6f9775211dfc966e9151862fd508d3142,Three-dimensional information in face recognition: an eye-tracking study.,Journal of vision,2011
+ac5b3e24a7dd2970c323ca7679625a7d29602480,Warsaw set of emotional facial expression pictures: a validation study of facial display photographs,,2014
ac9dfbeb58d591b5aea13d13a83b1e23e7ef1fea,From Gabor Magnitude to Gabor Phase Features: Tackling the Problem of Face Recognition under Severe Illumination Changes,,2009
+ac559888f996923c06b1cf90db6b57b12e582289,Benchmarking neuromorphic vision: lessons learnt from computer vision,,2015
+acfecef9e56ff36455aed13f8e6be1a79b42f20f,Hit or Run: Exploring Aggressive and Avoidant Reactions to Interpersonal Provocation Using a Novel Fight-or-Escape Paradigm (FOE),,2017
+adc0b5d9f010f8b7d9900fcb1703c3882e340d65,Nasal Oxytocin Treatment Biases Dogs’ Visual Attention and Emotional Response toward Positive Human Facial Expressions,,2017
+ad9ecacca5c28b098096ad0cbd81fe84405924e3,1 Face Recognition by Sparse Representation,,2011
+ada1a5f2d2a3fb471de4a561ed13c52d0904b578,InverseFaceNet : Deep Monocular Inverse Face Rendering — Supplemental Material —,Unknown,2018
+addbddc42462975a02f4933d36f430b874b3d52b,"Social attention and real-world scenes: the roles of action, competition and social content.",Quarterly journal of experimental psychology,2008
ad08c97a511091e0f59fc6a383615c0cc704f44a,Towards the improvement of self-service systems via emotional virtual agents,,2012
adf62dfa00748381ac21634ae97710bb80fc2922,ViFaI : A trained video face indexing scheme Harsh,Unknown,2011
+bb1f4c8e4f310047e50b7dc41d87292025d42eb7,Intersubject Differences in False Nonmatch Rates for a Fingerprint-Based Authentication System,EURASIP J. Adv. Sig. Proc.,2009
bb22104d2128e323051fb58a6fe1b3d24a9e9a46,Analyzing Facial Expression by Fusing Manifolds,,2007
+bbab2c3d0ebc0957c5e962298ffd8c6d4bc25c5a,Have we met before? Neural correlates of emotional learning in women with social phobia.,Journal of psychiatry & neuroscience : JPN,2014
+bbcf6f54d3e991f85a949544abf20b781d5ba2ed,Weighted principal component extraction with genetic algorithms,Appl. Soft Comput.,2012
+d74e14de664be4b784813d93e260abe379e2602d,Supplementary Material for : Video Prediction with Appearance and Motion Conditions,Unknown,2018
d73d2c9a6cef79052f9236e825058d5d9cdc1321,Cutting the visual world into bigger slices for improved video concept detection. (Amélioration de la détection des concepts dans les vidéos en coupant de plus grandes tranches du monde visuel),,2014
+d7f7eb0fbe3339d13f5a6a23df0fd27fdb357d48,Intention-Aware Multi-Human Tracking for Human-Robot Interaction via Particle Filtering over Sets,,2014
d708ce7103a992634b1b4e87612815f03ba3ab24,FCVID: Fudan-Columbia Video Dataset,,2016
+d787f691af05a56eb0e91437fc6b1dfe5fbccbb9,The Effect of Affective Context on Visuocortical Processing of Neutral Faces in Social Anxiety,,2015
d79f9ada35e4410cd255db39d7cc557017f8111a,Evaluation of accurate eye corner detection methods for gaze estimation,,2014
d06c8e3c266fbae4026d122ec9bd6c911fcdf51d,Role for 2D image generated 3D face models in the rehabilitation of facial palsy,,2017
d074b33afd95074d90360095b6ecd8bc4e5bb6a2,Human-Robot Collaboration: a Survey,I. J. Humanoid Robotics,2008
+d0137881f6c791997337b9cc7f1efbd61977270d,"University of Dundee An automated pattern recognition system for classifying indirect immunofluorescence images for HEp-2 cells and specimens Manivannan,",,2016
+d0a9bbd3bd9dcb62f9874fc1378a7f1a17f44563,Prototype Generation Using Self-Organizing Maps for Informativeness-Based Classifier,,2017
+be48780eb72d9624a16dd211d6309227c79efd43,Interactive Visual and Semantic Image Retrieval,,2013
be4a20113bc204019ea79c6557a0bece23da1121,DeepCache: Principled Cache for Mobile Deep Vision,Unknown,2017
+be6f29e129a99529f7ed854384d1f4da04c4ca1f,Spatially Consistent Nearest Neighbor Representations for Fine-Grained Classification. (Représentations d'images basées sur un principe de voisins partagés pour la classification fine),Unknown,2016
+be75a0ff3999754f20e63fde90f4c68b4af22d60,R4-A.1: Dynamics-Based Video Analytics,Unknown,2016
+b370eb9839be558e7db8390ce342312bd4835be9,Object Localization Does Not Imply Awareness of Object Category at the Break of Continuous Flash Suppression,,2017
b37f57edab685dba5c23de00e4fa032a3a6e8841,Towards social interaction detection in egocentric photo-streams,,2015
+b3adc7617dff08d7427142837a326b95d2e83969,A Panoramic View of Performance,,2009
+b3f0a87043f7843b79744ec19dc0b93324d055d5,Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network,Unknown,2017
b32cf547a764a4efa475e9c99a72a5db36eeced6,Mimicry of ingroup and outgroup emotional expressions,Unknown,2018
+dfbf49ed66a9e48671964872c84f75d7f916c131,Supplementary Material for Sparsity Invariant CNNs,Unknown,2017
+dfbf941adeea19f5dff4a70a466ddd1b77f3b727,Models for supervised learning in sequence data,Unknown,2018
+df28cd627afe6d20eb198b8406ff25ece340653d,The Acquisition of Sign Language by Deaf Children with Autism Spectrum Disorder,Unknown,2013
dff838ba0567ef0a6c8fbfff9837ea484314efc6,"Progress Report, MSc. Dissertation: On-line Random Forest for Face Detection",,2014
+df969647a0ee9ea25b23589f44be5240b5097236,How robust is familiar face recognition? A repeat detection study of more than 1000 faces,,2018
+da288fca6b3bcaee87a034529da5621bb90123d1,Aesthetics and Emotions in Images,IEEE Signal Processing Magazine,2011
+da1049ae56eaca2e7d65946cf87b1e504d9fcb70,VisDA : A Synthetic-to-Real Benchmark for Visual Domain Adaptation,Unknown,
+daef6fa60c7d79930ad0a341aab69f1f4fa80442,Supplement for BIER,,2017
+b4b1b39f8902208bbd37febfb68e08809098036d,TRECVid Semantic Indexing of Video : A 6-year Retrospective,Unknown,2016
+b47dae9d6499c6a777847a26297a647f0de49214,Aberrant Social Attention and Its Underlying Neural Correlates in Adults with Autism Spectrum Disorder,,2015
+a2e29b757f4021ed5b9eb7eebf78a0bddb460790,Visual scenes are categorized by function.,Journal of experimental psychology. General,2016
+a2a42aa37641490213b2de9eb8e83f3dab75f5ed,Multilinear Supervised Neighborhood Preserving Embedding Analysis of Local Descriptor Tensor,Unknown,2018
+a2183537ccf24eb95e8e7520b33f9aa8f190e80e,Subspace-Based Holistic Registration for Low-Resolution Facial Images,EURASIP J. Adv. Sig. Proc.,2010
+a2dd13729206a7434ef1f0cd016275c0d6f3bb6d,SFV: Reinforcement Learning of Physical Skills from Videos,CoRR,2018
a59cdc49185689f3f9efdf7ee261c78f9c180789,A New Approach for Learning Discriminative Dictionary for Pattern Classification,J. Inf. Sci. Eng.,2016
a57ee5a8fb7618004dd1def8e14ef97aadaaeef5,Fringe Projection Techniques: Whither we are?,,2009
-bdbba95e5abc543981fb557f21e3e6551a563b45,Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks,CoRR,2018
+a50099f5364d3d4e82991418647c727f0f9c297c,A Generic Bi-Layer Data-Driven Crowd Behaviors Modeling Approach,IEICE Transactions,2017
+bd96c3af9c433b4eaf95c8a28f072e1b0fc2de1a,A Study on Facial Expression Recognition Model using an Adaptive Learning Capability,Unknown,2012
+bdb74f1b633b2c48d5e9d101e09bad2db8d68be6,Chapter 1 . Medical Image Annotation (,,
+bdbba95e5abc543981fb557f21e3e6551a563b45,Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks,International Journal of Computational Intelligence and Applications,2018
+d16968e5baac6d26b9cef5034f9d84bcc3ec627c,"Children Facial Expression Production: Influence of Age, Gender, Emotion Subtype, Elicitation Condition and Culture",,2018
+d1295a93346411bb833305acc0e092c9e3b2eff1,The eMPaThy iMBalance hyPoThesis oF aUTisM : a TheoReTical aPPRoach To cogniTiVe and eMoTional eMPaThy in aUTisTic deVeloPMenT,Unknown,2009
+d1d9e6027288cdd64509ea62f88a3cbd9320c180,Automated Markerless Analysis of Human Gait Motion for Recognition and Classification,,2011
d68dbb71b34dfe98dee0680198a23d3b53056394,VIVA Face-off Challenge: Dataset Creation and Balancing Privacy,,2015
+bcab55f8bf0623df71623e673c767eed2159f05a,Deep Hybrid Scattering Image Learning,CoRR,2018
+bce36092b1910ff3d492f86aa3a39ed8faaf72d2,Chapter 17 Face Recognition Using 3 D Images,,2011
bcf19b964e7d1134d00332cf1acf1ee6184aff00,Trajectory-Set Feature for Action Recognition,IEICE Transactions,2017
+bc99f98b5f1fd158cc31d693061c402a36222dbb,Recent advances in understanding the neural bases of autism spectrum disorder.,Current opinion in pediatrics,2011
+bc4537bc5834b41a631d9a807500d199b438fb27,Perceptual Integration Deficits in Autism Spectrum Disorders Are Associated with Reduced Interhemispheric Gamma-Band Coherence.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2015
+bc8e1c2284008319ee325ff7ea19916726235f55,Autonomic responses to social and nonsocial pictures in adolescents with autism spectrum disorder.,Autism research : official journal of the International Society for Autism Research,2014
+aef59def2a65901de9d520d0442b42bb4a448f06,Facial Expression Recognition,,2009
ae89b7748d25878c4dc17bdaa39dd63e9d442a0d,On evaluating face tracks in movies,2013 IEEE International Conference on Image Processing,2013
+ae60fccb686272d12e909c9de99efb652e0934ec,The impact of internalizing symptoms on autistic traits in adolescents with restrictive anorexia nervosa,,2015
ae2c71080b0e17dee4e5a019d87585f2987f0508,Emotional Face Recognition in Children With Attention Deficit/Hyperactivity Disorder: Evidence From Event Related Gamma Oscillation,,2017
ae71f69f1db840e0aa17f8c814316f0bd0f6fbbf,That personal profile image might jeopardize your rental opportunity! On the relative impact of the seller's facial expressions upon buying behavior on Airbnb™,Computers in Human Behavior,2017
+d82681348489f4f04690e65b9ffe21b68c89b5ff,Cross-Subject EEG Feature Selection for Emotion Recognition Using Transfer Recursive Feature Elimination,,2017
+ab87ab1cf522995510561cd9f494223704f1de91,Human Centric Facial Expression Recognition,Unknown,2018
aba770a7c45e82b2f9de6ea2a12738722566a149,Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels,IEEE Transactions on Information Forensics and Security,2016
+ab1728e84ac682ca0c53435f712a512ac139e9c8,University of Groningen Comparative Study Between Deep Learning and Bag of Visual Words for Wild-Animal,Unknown,2017
ab2b09b65fdc91a711e424524e666fc75aae7a51,Multi-modal Biomarkers to Discriminate Cognitive State *,Unknown,2015
+ab567ca60fc3f72f27746b4d9e505042ab282ca3,Guidelines for studying developmental prosopagnosia in adults and children.,Wiley interdisciplinary reviews. Cognitive science,2016
+ab1f98b59fa98216f052ae19adce6fd94ebb800d,"Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos",CoRR,2018
+e597aca96ea1c928f13d15b7c4b46e3d41861afe,Mitigation of Effects of Occlusion on Object Recognition with Deep Neural Networks through Low-Level Image Completion,,2016
+e5d13afe956d8581a69e9dc2d1f43a43f1e2f311,Automatic Facial Feature Extraction for Face Recognition,Unknown,2018
+e2e920dfcaab27528c6fa65b6613d9af24793cb0,A comprehensive evaluation of multiband-accelerated sequences and their effects on statistical outcome measures in fMRI,,2016
+e2b615e3b78aa18c293e7f03eb96591ccb721b55,Recurrent Segmentation for Variable Computational Budgets,CoRR,2017
+e2e8db754b1ab4cd8aa07f5c5940f6921a1b7187,Interpretable visual models for human perception-based object retrieval,,2011
+e2af85dc41269bc7c50fcf2fb35bfeb75e3d6ee4,xytocin Improves “ Mind-Reading ” in Humans,Unknown,2007
+e20abf7143f4a224824c3db7213049dee2573b4e,An investigation of the relationship between activation of a social cognitive neural network and social functioning.,Schizophrenia bulletin,2008
f412d9d7bc7534e7daafa43f8f5eab811e7e4148,Running Head : Anxiety and Emotional Faces in WS 2,Unknown,2014
f43eeb578e0ca48abfd43397bbd15825f94302e4,Optical computer recognition of facial expressions associated with stress induced by performance demands.,"Aviation, space, and environmental medicine",2005
+f4b729d218139f1e93cc9d4df05fbf699d2e9d07,Introduction to the Special Issue on Recent Advances in Biometric Systems [Guest Editorial],"IEEE Trans. Systems, Man, and Cybernetics, Part B",2007
+f38ad869023c43b59431a3bb55f2fe8fb6ff0f05,A systematic review and meta-analysis of the fMRI investigation of autism spectrum disorders.,Neuroscience and biobehavioral reviews,2012
+f36647e63a11486ef9cf7a5a1c86a40fda5d408a,CS 229 Final Report: Artistic Style Transfer for Face Portraits,,2016
f3cf10c84c4665a0b28734f5233d423a65ef1f23,Title Temporal Exemplar-based Bayesian Networks for facialexpression recognition,Unknown,2008
+f397b8c835425e4b18cc7d9088b7f810c6cf2563,Yimo Guo IMAGE AND VIDEO ANALYSIS BY LOCAL DESCRIPTORS AND DEFORMABLE IMAGE REGISTRATION,Unknown,2013
+eb1208a7f535de6c6180e4dbeb6eef2a27500c52,"To be or Not to be Threatening, but What was the Question? Biased Face Evaluation in Social Anxiety and Depression Depends on How You Frame the Query",,2013
+ebe44c125f6d5c893df73d20b602e479a38e5b23,Algorithmic Identification of Looted Archaeological Sites from Space,Front. ICT,2017
+c757f6ee46208c1c26572265803068f8d837c384,Thermal imaging systems for real-time applications in smart cities,IJCAT,2016
+c72ac3dec0d0b2d5ca4945b07bd6b72c365bdc13,Shorter spontaneous fixation durations in infants with later emerging autism,,2015
+c784d4918ad33f4dd2991155ea583b4789ba3c11,Bimodal Vein Recognition Based on Task-Specific Transfer Learning,IEICE Transactions,2017
+c7dd846c0abc896e5fd0940ac07927553cc55734,Neurofunctional Underpinnings of Audiovisual Emotion Processing in Teens with Autism Spectrum Disorders,,2013
+c7d7cf88d2e9f3194aec2121eb19dbfed170dba8,Unconstrained Gaze Estimation Using Random Forest Regression Voting,,2016
+c793a38c3d16b093c12ba8a9d12dfa88159ecd38,Neurons in the fusiform gyrus are fewer and smaller in autism.,Brain : a journal of neurology,2008
+c719a718073128a985c957cdfa3f298706a180e6,Comparative Evaluations of Selected Tracking-by-Detection Approaches,Unknown,2018
+c02cc6af3cc93e86e86fb66412212babda8fb858,Interocularly merged face percepts eliminate binocular rivalry,,2017
+c08420b1bfa093e89e35e3b8d3a9e3e881f4f563,A Classification Framework for Large-Scale Face Recognition Systems,Unknown,2009
+c0de99c5f15898e2d28f9946436fec2b831d4eae,ClothCap: seamless 4D clothing capture and retargeting,ACM Trans. Graph.,2017
c02847a04a99a5a6e784ab580907278ee3c12653,Fine Grained Video Classification for Endangered Bird Species Protection,,2017
+c0ead9bada2fb7cdebf7dadbc8548d08387966ae,Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing,,2018
+c0e0b878ec8c56679faccb3c3f5e2ae968182da5,A Multifactor Extension of Linear Discriminant Analysis for Face Recognition under Varying Pose and Illumination,EURASIP J. Adv. Sig. Proc.,2010
eee8a37a12506ff5df72c402ccc3d59216321346,Volume C,,2008
eeb6d084f9906c53ec8da8c34583105ab5ab8284,Generation of Facial Expression Map using Supervised and Unsupervised Learning,,2012
eed7920682789a9afd0de4efd726cd9a706940c8,Computers to Help with Conversations : Affective Framework to Enhance Human Nonverbal Skills,Unknown,2013
+ee3a905ec8cd2e62dc642fad33d6f5f8516968a8,It depends: Approach and avoidance reactions to emotional expressions are influenced by the contrast emotions presented in the task.,Journal of experimental psychology. Human perception and performance,2016
+eedf9480de99e3373d2321f61ee5b71ea3ebf493,Altered Social Reward and Attention in Anorexia Nervosa,,2010
+c94ae3d1c029a70cabdab906fe1460d84fd42acd,"Comparison of wavelet, Gabor and curvelet transform for face recognition",,2011
+fc857cebd4150e3fe3aee212f128241b178f0d0a,Amygdala damage impairs eye contact during conversations with real people.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2007
+fc7627e57269e7035e4d56105358211076fe4f04,The Association of Quantitative Facial Color Features with Cold Pattern in Traditional East Asian Medicine,,2017
fcbec158e6a4ace3d4311b26195482b8388f0ee9,Face Recognition from Still Images and Videos,,2004
+fc950b230a0189cc63b2e2295b2dc761d5b2270c,Health care providers' judgments in chronic pain: the influence of gender and trustworthiness.,Pain,2016
+fc64f43cdcf4898b15ddce8b441d2ab9daa324f0,Gabor Filter-based Face Recognition Technique,,2010
fdb33141005ca1b208a725796732ab10a9c37d75,A connectionist computational method for face recognition,Applied Mathematics and Computer Science,2016
fdbacf2ff0fc21e021c830cdcff7d347f2fddd8e,Recognizing Frustration of Drivers From Face Video Recordings and Brain Activation Measurements With Functional Near-Infrared Spectroscopy,,2018
f24e379e942e134d41c4acec444ecf02b9d0d3a9,Analysis of Facial Images across Age Progression by Humans,,2011
+f27bdc4f7ec2006425f999055df071d64640836e,Preserved Crossmodal Integration of Emotional Signals in Binge Drinking,,2017
+f26b3a916aaa50fe6ef554fff744559815ccf954,Serotonin transporter genotype impacts amygdala habituation in youth with autism spectrum disorders.,Social cognitive and affective neuroscience,2014
+f2e9616577a0eb866e78e6fd68c67809e4fce11c,Digital innovations in L 2 motivation : Harnessing the power of the Ideal L 2 Self,Unknown,2018
f231046d5f5d87e2ca5fae88f41e8d74964e8f4f,Perceived Age Estimation from Face Images,Unknown,2018
f28b7d62208fdaaa658716403106a2b0b527e763,Clustering-driven Deep Embedding with Pairwise Constraints,CoRR,2018
+f524b1aac4f2a29dab45d7e8726517798dbc9782,Anger superiority effect: The importance of dynamic emotional facial expressions,,2013
+f5c83679b73ab59c2ada2b72610acdd63669b226,2d-3d Pose Invariant Face Recognition System for Multimedia Applications,,2009
+f558a3812106764fb1af854a02da080cc42c197f,Amygdala volume and nonverbal social impairment in adolescent and adult males with autism.,Archives of general psychiatry,2006
e379e73e11868abb1728c3acdc77e2c51673eb0d,Face Databases,,2005
+e3660a13fcd75cf876a6ce355c2c1a578cfb57cb,2DHMM-Based Face Recognition Method,,2015
+cff0e53006c6145d96322e6401e840f405b6ed02,Guest Editorial: Apparent Personality Analysis,IEEE Trans. Affective Computing,2018
cf875336d5a196ce0981e2e2ae9602580f3f6243,"7 What 1 S It Mean for a Computer to ""have"" Emotions?",,
cf5a0115d3f4dcf95bea4d549ec2b6bdd7c69150,Detection of emotions from video in non-controlled environment. (Détection des émotions à partir de vidéos dans un environnement non contrôlé),Unknown,2013
+cffc94574c8796cbd8234422a979e57e67eca7b5,Multiracial Children's and Adults' Categorizations of Multiracial Individuals.,Journal of cognition and development : official journal of the Cognitive Development Society,2017
+cf814b618fcbc9a556cdce225e74a8806867ba84,Facial Expression Recognition Using 3D Facial Feature Distances,,2007
+ca11dc3a8064583aaf79061866bbcf04caece162,Disentangled Representations in Neural Models,CoRR,2016
e4df83b7424842ff5864c10fa55d38eae1c45fac,Locally Linear Discriminate Embedding for Face Recognition,,2010
+e443cb55dcc54de848e9f0c11a6194568a875011,From passive to interactive object learning and recognition through self-identification on a humanoid robot,Auton. Robots,2016
e48e94959c4ce799fc61f3f4aa8a209c00be8d7f,Design of an Efficient Real-Time Algorithm Using Reduced Feature Dimension for Recognition of Speed Limit Signs,,2013
+fef3efeffade0e39f2c279653b4785b372be410e,Near infrared face recognition: A literature survey,Computer Science Review,2016
fe464b2b54154d231671750053861f5fd14454f5,Multi Joint Action in CoTeSys-Setup and Challenges-Technical report CoTeSys-TR-1001,Unknown,2010
feb6e267923868bff6e2108603d00fdfd65251ca,Unsupervised Discovery of Visual Face Categories,International Journal on Artificial Intelligence Tools,2013
+feb5b8bf315a6b6222f62dd9533b1e0f891a27bd,The Nature and Consequences of Essentialist Beliefs About Race in Early Childhood.,Child development,2018
+feaedb6766f42e867aab7f1a33ba4d7ddacfc7aa,UvA-DARE ( Digital Academic Repository ) Tag-based Video Retrieval by Embedding Semantic Content in a Continuous Word,Unknown,2016
+fe95b902eb362ad39f91e2325300d3f7a9119c48,Modeling invariant object processing based on tight integration of simulated and empirical data in a Common Brain Space,,2012
+c8a5c5c8e1293b7e877a848b7a9e5426c5400651,FaceShop: Deep Sketch-based Face Image Editing,ACM Trans. Graph.,2018
c87f7ee391d6000aef2eadb49f03fc237f4d1170,A real-time and unsupervised face Re-Identification system for Human-Robot Interaction,CoRR,2017
c87d5036d3a374c66ec4f5870df47df7176ce8b9,Temporal Dynamics of Natural Static Emotional Facial Expressions Decoding: A Study Using Event- and Eye Fixation-Related Potentials,,2018
+c8a22550297a25dadd283089f009015bc0df5eed,Neural circuits in the brain that are activated when mitigating criminal sentences,,2012
c8e84cdff569dd09f8d31e9f9ba3218dee65e961,Dictionaries for image and video-based face recognition [Invited].,"Journal of the Optical Society of America. A, Optics, image science, and vision",2014
+c81326a1ecb7e71ae38a665779b8d959d3938d1a,A Novel Neural Network Model Specified for Representing Logical Relations,CoRR,2017
+c8fc81a54ccef6d8111e7253283fc55e7e0f8ebd,High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks,CoRR,2018
+c8e32484bbbc63908080284790edafc4b66008d2,Suivi par ré-identification dans un réseau de caméras à champs disjoints,Traitement du Signal,2012
+fbd047862ea869973ecf8fc35ae090ca00ff06d8,Literature review of fingerprint quality assessment and its evaluation,IET Biometrics,2016
+fbd17af24e86fe487e28f99ba3e402dd6cfcd16a,Towards Detailed Recognition of Visual Categories,,2013
edf98a925bb24e39a6e6094b0db839e780a77b08,Simplex Representation for Subspace Clustering,CoRR,2018
+c18d80d00f2a7107bfe780eeec21b51a634ea925,Computational perspectives on the other-race effect,,2013
+c175f1666f3444e407660c5935a05b2a53f346f0,Modifying the Memorability of Face,Unknown,2013
c1dd69df9dfbd7b526cc89a5749f7f7fabc1e290,Unconstrained face identification with multi-scale block-based correlation,Unknown,2017
+c69ea9367e1244bfa5d3fc290b8a33be3abd8c24,"Many faces, one rule: the role of perceptual expertise in infants’ sequential rule learning",,2015
+c6e99ff40ccae0d7ce8e32666ed7f75e3a381d9b,How does the topic of conversation affect verbal exchange and eye gaze? A comparison between typical development and high-functioning autism.,Neuropsychologia,2010
+c6657c1263bac59b006d1da1174ec4bcea0dff3d,Global-local visual processing in high functioning children with autism: structural vs. implicit task biases.,Journal of autism and developmental disorders,2006
+c694b397a3a0950cd20699a687fe6c8a3173b107,Explaining autism spectrum disorders: central coherence vs. predictive coding theories.,Journal of neurophysiology,2014
c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8,Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.,Scientific reports,2016
+c6dab0aba7045f078313a4186cd507ff8eb8ce32,Atypical disengagement from faces and its modulation by the control of eye fixation in children with autism spectrum disorder.,Journal of autism and developmental disorders,2011
+ec0177cfdee435c6522ca4ee8a5f97ac0412472e,Reconstruction of images from Gabor graphs with applications in facial image processing,IJWMIP,2015
+ecdf8e5393eead0b63c5bc4fbe426db5a70574eb,Linear Subspace Learning for Facial Expression Analysis,Unknown,2012
+ec6855acd0871d3e000872a5dd89db97c1554e18,Contrasting emotion processing and executive functioning in attention-deficit/hyperactivity disorder and bipolar disorder.,Behavioral neuroscience,2016
+ec5f89e822d9fcbc7b7422dc401478fc29f9c02d,Those Virtual People all Look the Same to me: Computer-Rendered Faces Elicit a Higher False Alarm Rate Than Real Human Faces in a Recognition Memory Task,,2018
4e5dc3b397484326a4348ccceb88acf309960e86,Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection,,2014
+4ed4143034fc6303737c7ad5118a72d9a5d12cf2,Web Survey Gamification - Increasing Data Quality in Web Surveys by using Game Design Elements,,2017
+4efaa2a1a14ba6e8bea779eae49d6220fc771f2a,"Individual Differences in the Speed of Facial Emotion Recognition Show Little Specificity but Are Strongly Related with General Mental Speed: Psychometric, Neural and Genetic Evidence",,2017
+4e613c9342d6e90f7af5fd3f246c6d82a33fe98d,Estimating Human Pose in Images,,2009
2004afb2276a169cdb1f33b2610c5218a1e47332,Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition,,2018
20a16efb03c366fa4180659c2b2a0c5024c679da,Screening Rules for Overlapping Group Lasso,CoRR,2014
+20c59a55795eaa4f2629cc83fb556dc8c5bcfc1f,Modeling and visual recognition of human actions and interactions,Unknown,2013
208a2c50edb5271a050fa9f29d3870f891daa4dc,The resolution of facial expressions of emotion.,Journal of vision,2011
+2031b062f4c41f43a32835430b1d55a422baa564,VNect: real-time 3D human pose estimation with a single RGB camera,ACM Trans. Graph.,2017
+20eaa3ebe2b6e1aff7c4585733c9fb0cfc941919,Image similarity using Deep CNN and Curriculum Learning,CoRR,2017
+20388099cc415c772926e47bcbbe554e133343d1,The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults,,2014
+182496e9533ad3a5eef6a06b815a276c18eaea2e,High autistic trait individuals do not modulate gaze behaviour in response to social presence but look away more when actively engaged in an interaction,,2017
+18f70d8e1697bc0b85753db2d4d64aeb696b052a,Evolutionary Discriminant Feature Extraction with Application to Face Recognition,EURASIP J. Adv. Sig. Proc.,2009
+183c8da12a07e2002fd71edbabeca5b3bfb45d66,Grounding Natural Language Instructions with Unknown Object References using Learned Visual Attributes,,2017
+18804d8e981fa66135c0ffa6fdb2b8b3fec6d753,Predicting human gaze beyond pixels.,Journal of vision,2014
+1875b2325b3efcb49dec51c6416f40862db4fe74,Functional abnormalities of the default network during self- and other-reflection in autism.,Social cognitive and affective neuroscience,2008
27a0a7837f9114143717fc63294a6500565294c2,Face Recognition in Unconstrained Environments: A Comparative Study,,2015
+27421586a04584d38dd961b37d0ca85408acfe59,Large brains in autism: the challenge of pervasive abnormality.,"The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry",2005
+27eb092a9adbfcb3aea1b13bde580f1fd5c7b8f0,xytocin Increases Gaze to the Eye Region f Human Faces dam,,2007
270733d986a1eb72efda847b4b55bc6ba9686df4,Recognizing Facial Expressions Using Model-Based Image Interpretation,Unknown,2008
+272c6b6ccf144954a154b83bf5789341ee3f9ed2,A brain-computer interface for potential non-verbal facial communication based on EEG signals related to specific emotions,,2014
27169761aeab311a428a9dd964c7e34950a62a6b,Face Recognition Using 3D Head Scan Data Based on Procrustes Distance,2008 International Conference on Intelligent Engineering Systems,2008
27a299b834a18e45d73e0bf784bbb5b304c197b3,Social Role Discovery in Human Events,2013 IEEE Conference on Computer Vision and Pattern Recognition,2013
4b7c110987c1d89109355b04f8597ce427a7cd72,Feature- and Face-Exchange illusions: new insights and applications for the study of the binding problem,,2014
+4b86e711658003a600666d3ccfa4a9905463df1c,Fusion of Appearance Image and Passive Stereo Depth Map for Face Recognition Based on the Bilateral 2DLDA,EURASIP J. Image and Video Processing,2007
+4ba3f9792954ee3ba894e1e330cd77da4668fa22,Nearest Neighbor Discriminant Analysis,IJPRAI,2006
4b71d1ff7e589b94e0f97271c052699157e6dc4a,Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image,EURASIP J. Adv. Sig. Proc.,2008
+11943efec248fcac57ff6913424e230d0a02e977,Auxiliary Tasks in Multi-task Learning,CoRR,2018
11aa527c01e61ec3a7a67eef8d7ffe9d9ce63f1d,"Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.",Proceedings of the National Academy of Sciences of the United States of America,2015
+116888b8f08419f027f5047f0ff1557b16f69d5a,Fearful contextual expression impairs the encoding and recognition of target faces: an ERP study,,2015
+7dce05b7765541b3fb49a144fb39db331c14fdd1,Modélisation et suivi des déformations faciales : applications à la description des expressions du visage dans le contexte de la langue des signes,Unknown,2007
+7d1ac241fb603a4237cb681dbcf163a9f89e906a,Supplementary Material : Switching Convolutional Neural Network for Crowd Counting,,2017
+7d621ec871a03a01f5aa65253e9ae6c8aadaf798,Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades,,2015
29ce6b54a87432dc8371f3761a9568eb3c5593b0,Age Sensitivity of Face Recognition Algorithms,2013 Fourth International Conference on Emerging Security Technologies,2013
+295266d09fde8f85e6e577b5181cbc73a1594b6b,Parallel effects of processing fluency and positive affect on familiarity-based recognition decisions for faces,,2014
+2933da06df9e47da8e855266f5ff50e03c0ccd27,Combination of RGB-D Features for Head and Upper Body Orientation Classification,Unknown,2016
29c7dfbbba7a74e9aafb6a6919629b0a7f576530,Automatic Facial Expression Analysis and Emotional Classification,,2004
+29230bbb447b39b7fc3de7cb34b313cc3afe0504,Face Detection and Recognition Using Maximum Likelihood Classifiers on Gabor Graphs,IJPRAI,2009
+29a606ba5b9ae9bc16d05a832d4e54d769c63dae,Activation of mGluR2/3 underlies the effects of N-acetylcystein on amygdala-associated autism-like phenotypes in a valproate-induced rat model of autism,,2014
+2939169aed69aa2626c5774d9b20e62c905e479b,Fast Exact HyperGraph Matching with Dynamic Programming for Spatio-Temporal Data,Unknown,2017
+29c6b06ac98dbdaf25e4cc9a05b4ab314923cccd,Assessment of the communicative and coordination skills of children with Autism Spectrum Disorders and typically developing children using social signal processing,,2013
2983efadb1f2980ab5ef20175f488f77b6f059d7,Emotion in Human–computer Interaction,,2011
29f0414c5d566716a229ab4c5794eaf9304d78b6,Biometric Template Security,EURASIP J. Adv. Sig. Proc.,2008
+7c79d3a40c1a1f5b9692ed23396b0f13453c225c,The influence of vocal training and acting experience on measures of voice quality and emotional genuineness,,2014
7c825562b3ff4683ed049a372cb6807abb09af2a,Finding Tiny Faces Supplementary Materials,Unknown,2017
+7cf8440b1c02c021f6ba8543ad490b4788bbe280,"Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations",Frontiers in human neuroscience,2016
+1696f6861c208b6a7cac95fbeba524867ad3e8d6,Using deep learning to quantify the beauty of outdoor places,,2017
+16f76f040f08448cf0a3984168d69197ea4af039,"Now you see race, now you don’t: Verbal cues influence children’s racial stability judgments",,2017
16c884be18016cc07aec0ef7e914622a1a9fb59d,Exploiting Multimodal Data for Image Understanding,,2010
16e95a907b016951da7c9327927bb039534151da,3D Face Recognition Using Spherical Vector Norms Map,J. Inf. Sci. Eng.,2017
+164f3b9740d9ceb14658237fddede0f86b5e0c47,CASENet: Deep Category-Aware Semantic Edge Detection,2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017
167736556bea7fd57cfabc692ec4ae40c445f144,Improved Motion Description for Action Classification,Front. ICT,2016
+4213502d0f226b9845b00c2882851ba4c57742ab,Does Rabbit Antithymocyte Globulin (Thymoglobuline®) Have a Role in Avoiding Delayed Graft Function in the Modern Era of Kidney Transplantation?,,2018
+426b47af132293e9ffe6071a3ede59cfdc1aa3fb,Promoting social behavior with oxytocin in high-functioning autism spectrum disorders.,Proceedings of the National Academy of Sciences of the United States of America,2010
42765c170c14bd58e7200b09b2e1e17911eed42b,Feature Extraction Based on Wavelet Moments and Moment Invariants in Machine Vision Systems,,2012
+42e793b1dd6669b74ad106071c432aa5015b8631,How do people think about interdependence? A multidimensional model of subjective outcome interdependence.,Journal of personality and social psychology,2018
42dc36550912bc40f7faa195c60ff6ffc04e7cd6,Visible and Infrared Face Identification via Sparse Representation,,2013
+425833b5fe892b00dcbeb6e3975008e9a73a5a72,A Review of Performance Evaluation for Biometrics Systems,Int. J. Image Graphics,2005
4276eb27e2e4fc3e0ceb769eca75e3c73b7f2e99,Face Recognition From Video,,2008
+421b3a33ec70af2d733310f6c83ad713a314951d,Using nasal curves matching for expression robust 3D nose recognition,"2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)",2013
89c84628b6f63554eec13830851a5d03d740261a,Image Enhancement and Automated Target Recognition Techniques for Underwater Electro-Optic Imagery,,2010
+8973910c8acfd296922d9691a533b3c5061ec815,Supplementary Material for Efficient Online Local Metric Adaptation via Negative Samples for Person Re-Identification,,2017
893239f17dc2d17183410d8a98b0440d98fa2679,UvA-DARE ( Digital Academic Repository ) Expression-Invariant Age Estimation,Unknown,2017
+89e4f5a1eb6a97459bb748f4f7bc5c2696354aad,Semantics from Sound: Modeling Audio and Text Thesis Proposal,,2006
+89c45ace90d377502dc84825e5039290927ae9e2,"Changes in vegetation persistence across global savanna landscapes , 1982 – 2010",Unknown,2016
+45483f17551d9c6b550474dc7168ec31302e5d7b,Face recognition via collaborative representation based multiple one-dimensional embedding,IJWMIP,2016
4541c9b4b7e6f7a232bdd62ae653ba5ec0f8bbf6,The role of structural facial asymmetry in asymmetry of peak facial expressions.,Laterality,2006
+45518c2350b9e727adf59f1626610917f71aea1e,Cross-Layer Design Space Exploration of Heterogeneous Multicore Processors With Predictive Models,,2014
+451d777ee33833a3b5eb6ba5292fae162c6d265f,Exploiting Feature Correlations by Brownian Statistics for People Detection and Recognition,"IEEE Transactions on Systems, Man, and Cybernetics: Systems",2017
+453e311c6de1285cd5ea6d93fd78a636eac0ba82,Multi patches 3D facial representation for person authentication using AdaBoost,2010 5th International Symposium On I/V Communications and Mobile Network,2010
+45ca696076e9c073e6cf699766f808899589bc88,Aalborg Universitet Thermal Tracking of Sports Players,Unknown,2017
1f89439524e87a6514f4fbe7ed34bda4fd1ce286,Devising Face Authentication System and Performance Evaluation Based on Statistical Models,,2015
+1fa9c5af78b3ca04476f4ee6910684dc19008f5e,Supplementary Material : Cross-Dataset Adaptation for Visual Question Answering,Unknown,2018
+1fb2082d3f772933b586cca65af2099512b9c68b,Comparison of Spectral-Only and Spectral/Spatial Face Recognition for Personal Identity Verification,EURASIP J. Adv. Sig. Proc.,2009
1fe990ca6df273de10583860933d106298655ec8,A Wavelet-Based Image Preprocessing Method or Illumination Insensitive Face Recognition,J. Inf. Sci. Eng.,2015
+73bbbfac7b144f835840fe7f7b5139283bf4f3f1,Do we spontaneously form stable trustworthiness impressions from facial appearance?,Journal of personality and social psychology,2016
+73c13ba142588f45aaa92805fe75ca2691ac981b,A Comparative Study of Social Scene Parsing Strategies between Children with and without Autism Spectrum Disorder,,2016
+7372c1e9cb87dad88bc160536263e461bb7ab04c,Trajectory Energy Minimisation for Cell Growth Tracking and Genealogy Analysis,,2017
+735c38361d77e707ac48f0d040493c65ca559d3c,Machine Learning for Simplifying the Use of Cardiac Image Databases. (Apprentissage automatique pour simplifier l'utilisation de banques d'images cardiaques),Unknown,2015
7373c4a23684e2613f441f2236ed02e3f9942dd4,Feature extraction through Binary Pattern of Phase Congruency for facial expression recognition,2012 12th International Conference on Control Automation Robotics & Vision (ICARCV),2012
+73599349402bf8f0d97f51862d11d128cdba44ef,Affective analysis of videos: detecting emotional content in real-life scenarios,Unknown,2017
+738fadaf40249146f33da5b9efbb72a1fdf8767d,Unsupervised Learning of Invariant Representations in Hierarchical Architectures,CoRR,2013
+8797c870c0881cd30fda186affee4bdec54aeecd,Binary Biometric Representation through Pairwise Adaptive Phase Quantization,EURASIP J. Information Security,2011
+8722ab37a03336f832e4098224cb63cd02cdfe0a,Face recognition with 3 D face asymmetry,Unknown,2016
+87bdafbcf3569c06eef4a397beffc451f5101f94,Facial expression: An under-utilised tool for the assessment of welfare in mammals.,ALTEX,2017
+8732d702aeb08e9c604b36dcaa5933aea91a228d,Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models,,2015
+806f466034e0c3e609e672559e23d5d8bea6fe3d,Adaptive memory: The mnemonic value of contamination,,2017
+80265d7c9fe6a948dd8c975bd4d696fb7ba099c9,Face Recognition Based on Human Visual Perception Theories and Unsupervised ANN,,2009
+801b0ae343a11a15fd7abc5720831afea6f0a61d,Similarity Learning with Listwise Ranking for Person Re-Identification,Unknown,2018
74de03923a069ffc0fb79e492ee447299401001f,On Film Character Retrieval in Feature-Length Films,,2005
744fa8062d0ae1a11b79592f0cd3fef133807a03,Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification.,IEEE transactions on cybernetics,2017
+74113bb67eef4cfa28ebfa8bd38a614c82bdfdea,Neural responses to facial expressions support the role of the amygdala in processing threat.,Social cognitive and affective neuroscience,2014
+743c7e1aef6461d6582cf8deeb5d518e45215f89,Looking you in the mouth: abnormal gaze in autism resulting from impaired top-down modulation of visual attention.,Social cognitive and affective neuroscience,2006
+1a229f1d21abe442520cba31a6e08663b3d31777,The heterogeneous block architecture,2014 IEEE 32nd International Conference on Computer Design (ICCD),2014
1a41e5d93f1ef5b23b95b7163f5f9aedbe661394,Alignment-Free and High-Frequency Compensation in Face Hallucination,,2014
+1ac20a7a76f7b83ccd8ea0aab64e2b24ecd23915,Impaired social brain network for processing dynamic facial expressions in autism spectrum disorders,,2012
+1a9e0bf9f7a9495bcdf1aeb214ccc9df9f2a9030,Challenges and Opportunities The Main Memory System : Challenges and Opportunities,Unknown,2015
+1a515f0b852c2e93272677dbf6ecb05c7be0ea2e,Reduced serotonin receptor subtypes in a limbic and a neocortical region in autism.,Autism research : official journal of the International Society for Autism Research,2013
+1ad823bf77c691f1d2b572799f8a8c572d941118,Précis of “Towards The Deep Model : Understanding Visual Recognition Through Computational Models”,,
+1a5a79b4937b89420049bc279a7b7f765d143881,Are Rich People Perceived as More Trustworthy? Perceived Socioeconomic Status Modulates Judgments of Trustworthiness and Trust Behavior Based on Facial Appearance,,2018
1afd481036d57320bf52d784a22dcb07b1ca95e2,Automated Content Metadata Extraction Services Based on MPEG Standards,Comput. J.,2013
1a4b6ee6cd846ef5e3030a6ae59f026e5f50eda6,Deep Learning for Video Classification and Captioning,CoRR,2016
+1a2431e3b35a4a4794dc38ef16e9eec2996114a1,Automated Face Recognition: Challenges and Solutions,Unknown,2018
+1a51bc5f9f12f6794297a426739350ae57c87731,Image classification with CNN-based Fisher vector coding,2016 Visual Communications and Image Processing (VCIP),2016
+284bf12324805f23b920bec0174be003c248cc9b,Lower Sensitivity to Happy and Angry Facial Emotions in Young Adults with Psychiatric Problems,,2016
28b26597a7237f9ea6a9255cde4e17ee18122904,Network Interactions Explain Sensitivity to Dynamic Faces in the Superior Temporal Sulcus,,2015
28c9198d30447ffe9c96176805c1cd81615d98c8,No evidence that a range of artificial monitoring cues influence online donations to charity in an MTurk sample,,2016
+28ce99940265407517faf7c45755675054ef78c4,Distinct facial expressions represent pain and pleasure across cultures,,2018
+28858a6e956d712331986b31d1646d6b497ff1a9,Independent Neural Computation of Value from Other People's Confidence.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2017
17a85799c59c13f07d4b4d7cf9d7c7986475d01c,Extending Procrustes Analysis: Building Multi-view 2-D Models from 3-D Human Shape Samples,,2015
176bd61cc843d0ed6aa5af83c22e3feb13b89fe1,Investigating Spontaneous Facial Action Recognition through AAM Representations of the Face,,2007
+17dea513763c57dcd0e62085045fb5be6770c600,"Dynamic thread mapping for high-performance, power-efficient heterogeneous many-core systems",2013 IEEE 31st International Conference on Computer Design (ICCD),2013
+175e9bb50cc062c6c1742a5d90c8dfe31d2e4e22,Where to Look: Focus Regions for Visual Question Answering,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
+17db741725b9f8406f69b27a117e99bee1a9a323,Person Re-identification with a Body Orientation-Specific Convolutional Neural Network,Unknown,2018
+17e769ef3d86e74c21f2616c7f7a6f20a4e2fbaa,Bag of Machine Learning Concepts for Visual Concept Recognition in Images,,2013
+7b4e0a98dcb4ba34afcc5901f51384ba727473a0,Introduction to Emotion Recognition,Unknown,2014
+7b3231245a3d518085c8e747e2c2232963f49bc5,Tracking millions of humans in crowded space in crowded spaces,,2017
+7b4d985d03ebf8465757877f0eeaea00fa77676b,Dyadic Dynamics: The Impact of Emotional Responses to Facial Expressions on the Perception of Power,,2018
+7bc8d81a38899b60704681125ec4fc584a3e7ba4,Look me in the eyes: constraining gaze in the eye-region provokes abnormally high subcortical activation in autism,,2017
+7bdab6e725ab1bbf8fcd6d7c451f6c4cc215ada9,Complex Wavelet Transform-Based Face Recognition,EURASIP J. Adv. Sig. Proc.,2008
+7b45aa509184b05064eafb362f80ba5778566a4e,High-Level Interpretation of Urban Road Maps Fusing Deep Learning-Based Pixelwise Scene Segmentation and Digital Navigation Maps,Unknown,2018
+7b9ebcc8b9c05ef661182fe73438b7725584817d,Restoring effects of oxytocin on the attentional preference for faces in autism,,2017
8f6d05b8f9860c33c7b1a5d704694ed628db66c7,Non-linear dimensionality reduction and sparse representation models for facial analysis. (Réduction de la dimension non-linéaire et modèles de la représentations parcimonieuse pour l'analyse du visage),Unknown,2014
+8f5a2750f7ed015efa85887db3f6c6d2c0cb7b11,Social perception in synaesthesia Social perception in synaesthesia for colour,Unknown,2018
8f08b2101d43b1c0829678d6a824f0f045d57da5,Supplementary Material for: Active Pictorial Structures,,2015
+8f81eb82cd046891c88163bc7b472dcc779f5f08,TokyoTechCanon at TRECVID 2012,,2012
+8f5566fa00f8c79f4720e14084489e784688ab0b,The role of the amygdala in atypical gaze on emotional faces in autism spectrum disorders.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2012
+8f48b2da711417d1f1f39069501577c84abb8d37,Elevated amygdala response to faces and gaze aversion in autism spectrum disorder.,Social cognitive and affective neuroscience,2014
+8fa290b5d92c1f427edb62d29988056383e02047,Absence of preferential unconscious processing of eye contact in adolescents with autism spectrum disorder.,Autism research : official journal of the International Society for Autism Research,2014
+8a91cb96dd520ba3e1f883aa6d57d4d716c5d1c8,Low Cost Eye Tracking: The Current Panorama,,2016
+8a7bd4202e49fcdb947d71c9f2da0e7a953c7021,Privacy and security assessment of biometric template protection,,2012
+8a7726e58c2e24b0a738b48ae35185aaaacb8fe9,PILOT ASSESSMENT OF NONVERBAL PRAGMATIC ABILITY IN PEOPLE WITH ASPERGER SYNDROME Introduction,,2014
8a54f8fcaeeede72641d4b3701bab1fe3c2f730a,What do you think of my picture? Investigating factors of influence in profile images context perception,,2015
+8aff946f5d678f689cc9476e48d8b122671205ae,"Neuron numbers increase in the human amygdala from birth to adulthood, but not in autism",,2018
+8a722c17e6bda2df13f03ca522119f4c8b5bfff8,Connecting Missing Links: Object Discovery from Sparse Observations Using 5 Million Product Images,,2012
+8aa5f1b2639da73c2579ea9037a4ebf4579fdc4f,A Steerable multitouch Display for Surface Computing and its Evaluation,International Journal on Artificial Intelligence Tools,2013
+8aef5b3cfc80fafdcefc24c72a4796ca40f4bc8b,Person Re-Identification by Support Vector Ranking,,2010
7ed2c84fdfc7d658968221d78e745dfd1def6332,Evaluation of linear combination of views for object recognition on real and synthetic datasets,,2007
7ef0cc4f3f7566f96f168123bac1e07053a939b2,Triangular Similarity Metric Learning: a Siamese Architecture Approach. ( L'apprentissage de similarité triangulaire en utilisant des réseaux siamois),Unknown,2016
7e18b5f5b678aebc8df6246716bf63ea5d8d714e,Increased Loss Aversion in Unmedicated Patients with Obsessive–Compulsive Disorder,,2017
7ec7163ec1bc237c4c2f2841c386f2dbfd0cc922,Skiing and Thinking About It: Moment-to-Moment and Retrospective Analysis of Emotions in an Extreme Sport,,2018
7ef44b7c2b5533d00001ae81f9293bdb592f1146,Détection des émotions à partir de vidéos dans un environnement non contrôlé Detection of emotions from video in non-controlled environment,Unknown,2003
+7e51a42049193726e9ac547b76e929d803e441f3,Holistic processing of the mouth but not the eyes in developmental prosopagnosia.,Cognitive neuropsychology,2012
+101d1cff1aa5590a1f79bc485cbfec094a995f74,Persuasive Faces: Generating Faces in Advertisements (Supplementary Material),Unknown,2018
+10ffdfdbc0aafb89d94528f359425de0c7a81986,Interacting HiddenMarkovModels for Video Understanding,Unknown,2018
10ce3a4724557d47df8f768670bfdd5cd5738f95,Fisher Light-Fields for Face Recognition across Pose and Illumination,,2002
+1037664753b281543ce300fed0852a64d24334ba,Binary - Feature Based Recognition and Cryptographic Key Generation from Face Biometrics,,2007
190d8bd39c50b37b27b17ac1213e6dde105b21b8,Mining Weakly Labeled Web Facial Images for Search-Based Face Annotation,IEEE Transactions on Knowledge and Data Engineering,2011
+19a30ad283f2ab2d84f1c666d17492da14056d75,Visuomotor Coordination in Reach-To-Grasp Tasks: From Humans to Humanoids and Vice Versa,,2015
19da9f3532c2e525bf92668198b8afec14f9efea,Challenge: Face verification across age progression using real-world data,,2011
+4c293a98e929edaff6ed70c22a844c04e604e9fc,Clustering by fast search and merge of local density peaks for gene expression microarray data,,2017
+4cf17bca0e19070fbe9bb25644787f65fa6ebe1a,Human Pose Estimation,,2014
+4c56f119ebf7c71f2a83e4d79e8d88314b8e6044,An other-race effect for face recognition algorithms,TAP,2011
+4cfa2fe87c250534fd2f285c2300e7ca2cd9e325,"Visual, Auditory, and Cross Modal Sensory Processing in Adults with Autism: An EEG Power and BOLD fMRI Investigation",Frontiers in human neuroscience,2016
+269248eb8a44da5248cef840f7079b1294dbf237,The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments,PACMHCI,2017
+2677a79b6381f3e7787c5dca884fa53d0b28dfe2,Supplementary Document : Single-Shot Multi-Person 3 D Pose Estimation From Monocular RGB 1,Unknown,2018
+268e91262c85ff1ce99dfc5751e2b6e44c808325,Frequency Domain Face Recognition,,2007
+265644f1b6740ca34bfbe9762b90b33021adde62,Deep Learning in Medical Imaging: General Overview.,Korean journal of radiology,2017
+269c1f9df4a36b361d32bfdc81457b0a32b60966,Dimensionality Reduction of Visual Features for Efficient Retrieval and Classification,,2016
+2670c4b556264605c32326f49ab4a8b4e83ab57f,Looking ahead: Anticipatory cueing of attention to objects others will look at.,Cognitive neuroscience,2016
+2663fa2f1777dc779a73d678c7919cce37b5fb61,Relevance - Weighted ( 2 D ) 2 LDA Image Projection Technique for Face Recognition,,
26c884829897b3035702800937d4d15fef7010e4,Facial Expression Recognition by Supervised Independent Component Analysis Using MAP Estimation,IEICE Transactions,2008
+26919156cec1cc5bec03f63f566c934b55b682cd,From Pictorial Structures to deformable structures,2012 IEEE Conference on Computer Vision and Pattern Recognition,2012
+21679eb7e953bd132803703c27dcd56484d497e6,"utism , oxytocin and interoception",Unknown,2014
21a2f67b21905ff6e0afa762937427e92dc5aa0b,Extra Facial Landmark Localization via Global Shape Reconstruction,,2017
+21f5652d4f88ac039c58aa530328e65a39eb7b38,Neural Processing of Facial Identity and Emotion in Infants at High-Risk for Autism Spectrum Disorders,,2013
+2155739f578e33449546f45a0b4cf64dbd614025,what is facereader ?,,
+21bebef8ced5d1e77667c667b54287782556eebc,Image processing and recognition for biological images,,2013
+4dade6faf6d5d6db53d5bcb2e107311da1ad48ac,Facial Expression Biometrics Using Statistical Shape Models,EURASIP J. Adv. Sig. Proc.,2009
+4d6e7d73f5226142ffc42b4e8380882d5071e187,Discretion Within Constraint: Homophily and Structure in a Formal Organization,Organization Science,2013
+4d803109f3d9cca7c514db21a0494972d5681faa,Attribute Adaptation for Personalized Image Search,2013 IEEE International Conference on Computer Vision,2013
+4d231311cdfe3aba13766bd0b358d4db0a9af3d3,Processing and Recognising Faces in 3D Images,Unknown,2018
+75aef130afb8c862575d457db6e168e8d77ae4f0,Content-based search and browsing in semantic multimedia retrieval,,2006
7574f999d2325803f88c4915ba8f304cccc232d1,Transfer Learning for Cross-Dataset Recognition: A Survey,Unknown,2017
+758572c5779a47e898caff7232af76eda253163b,Csr: Medium: Collaborative Research: Architecture and System Support for Power-agile Computing,,2015
+7538ad235caf4dbc64a8b94a6146e1212d4de1ff,Amygdala dysfunction in men with the fragile X premutation.,Brain : a journal of neurology,2007
+75b20672a6290a8e2769ba0226d9187c0ccd5843,Development of response inhibition in the context of relevant versus irrelevant emotions,,2013
+812725dc3968aaff6429ec7c3f44ba1ca2116013,Acoplamiento de micro multitudes para el desarrollo de videojuegos controlados por movimiento,Research in Computing Science,2014
+8145ff6adab3397a5ac52cc62a7c53dae59763db,ERP responses differentiate inverted but not upright face processing in adults with ASD.,Social cognitive and affective neuroscience,2012
+81c03eda1d175fbe351980ac4cffe42c5dec47b0,User observation & dataset collection for robot training,,2011
816eff5e92a6326a8ab50c4c50450a6d02047b5e,fLRR: Fast Low-Rank Representation Using Frobenius Norm,,2014
86c5478f21c4a9f9de71b5ffa90f2a483ba5c497,"Kernel Selection using Multiple Kernel Learning and Domain Adaptation in Reproducing Kernel Hilbert Space, for Face Recognition under Surveillance Scenario",CoRR,2016
+86e5f81bde496549e9df2b1abdef0879a3135adb,The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR,CoRR,2018
+86cdc6ae46f53ac86b9e0ace2763c5fe15633055,Experimental Force-Torque Dataset for Robot Learning of Multi-Shape Insertion,CoRR,2018
+861f4aac1178bf1c4dd1373dbf2794be54c195d4,Survey of Image Processing Techniques for Brain Pathology Diagnosis: Challenges and Opportunities,Unknown,2018
72a87f509817b3369f2accd7024b2e4b30a1f588,Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints,Pattern Analysis and Applications,2011
+72903a6b9894f13facf46a81bd7b659740b488e5,Worldwide AI,,2012
+72b34e9536665f776b0f282ddb63120afa21c84e,An experimental examination of catastrophizing-related interpretation bias for ambiguous facial expressions of pain using an incidental learning task,,2014
+7249b263d0a84d2d9d03f2f7b378778d129f9af9,Research Statement Research Focus,Unknown,2012
+72edfb91e4b3d42547591be9e8c6eb07e7190499,Do Children See in Black and White? Children's and Adults' Categorizations of Multiracial Individuals.,Child development,2015
+72944b4266523effe97708bff89e1d57d6aebf50,"A Multi-Sensory, Automated and Accelerated Sensory Integration Program",,2016
+7240aad3fa4adf65e401345c877ee58a01b76fb1,A new theoretical approach to improving face recognition in disorders of central vision: face caricaturing.,Journal of vision,2014
+44054c64ae7ee16a8a8348bb57345aae95a8ddae,Social Orienting and Attention Is Influenced by the Presence of Competing Nonsocial Information in Adolescents with Autism,,2016
+44442a26062c20dab7db4a9862349b598efca119,Modelling errors in a biometric re-identification system,IET Biometrics,2015
+449b87347fe7f9c3f17e969fab1617fbfd9ccb1b,Flat vs. Expressive Storytelling: Young Children’s Learning and Retention of a Social Robot’s Narrative,,2017
+44fbbd3def64d52c956277628a89aba77b24686b,Context Modulates Congruency Effects in Selective Attention to Social Cues,,2018
+2a218c17944d72bfdc7f078f0337cab67536e501,Detection bank: an object detection based video representation for multimedia event recognition,,2012
+2a12c72b0328a23b0d7ea63db1f93abf3054beec,Extended Feature Descriptor and Vehicle Motion Model with Tracking-by-Detection for Pedestrian Active Safety,IEICE Transactions,2014
+2a3768ac4f6b3bfbcce4001c0c2fd35cfcc7679d,Face Recognition with Variation in Pose Angle Using Face Graphs,,2009
+2af9ee8ee3ab4a89ae0098a1f9caa1aa9dad4e8a,2D and 3D Pose Recovery from a Single Uncalibrated Video - A View and Activity Independent Framework,,2011
2a5903bdb3fdfb4d51f70b77f16852df3b8e5f83,The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments,PACMHCI,2017
+2a87f95e36938ca823b33c72a633d8d902d5cb86,xytocin Improves “Mind-Reading” in Humans,,2006
+2aa06417fd361832df384cf7c003ed1d3c5ee8df,Learning people detection models from few training samples,CVPR 2011,2011
+2a6327a8bdbd31e2c08863b96c4f09245db8cab7,Targets ' facial width-to-height ratio biases pain judgments ☆,Unknown,2017
+2f23f7d08c7b8670289cfedd1e571f44a3bace8b,Contextual Information and Covariance Descriptors for People Surveillance: An Application for Safety of Construction Workers,EURASIP J. Image and Video Processing,2011
+2f3f4e0c8a9c63e714a10a6711c67f5e84e4c7c1,IoT Based Embedded Smart Lock Control System,Unknown,2016
+2fa04fc0bcbc92886902a62dbf538c490084efa4,Visual field bias in hearing and deaf adults during judgments of facial expression and identity,,2013
+43694e7d5861a8bc8aa5884dba3efe2d387511c6,Supplementary Material: Annotating Object Instances with a Polygon-RNN,,2017
+432be99dde7d93001044048501c72c70e4ea2927,People and Mobile Robot Classification Through Spatio-Temporal Analysis of Optical Flow,IJPRAI,2015
+431f013143de3159c0c0033fee2fb4840d213b6f,Preferential attention to animals and people is independent of the amygdala.,Social cognitive and affective neuroscience,2015
+43d4927f5113c5e376ab05d41e33063a6d06d727,Pedestrian Detection: Exploring Virtual Worlds,,2012
+886fc74b943011ce5ce192ff98d6ea9dcac7ef11,Atypical scanpaths in schizophrenia: evidence of a trait- or state-dependent phenomenon?,Journal of psychiatry & neuroscience : JPN,2011
+88dc2b2f6d033b290ed56b844c98c3ee6efde80b,Experimental manipulation of face-evoked activity in the fusiform gyrus of individuals with autism.,Social neuroscience,2011
88e2574af83db7281c2064e5194c7d5dfa649846,A Robust Shape Reconstruction Method for Facial Feature Point Detection,,2017
+88a0ff6b180703a2d90bc86b40520e35a08fe02c,The Normalized Distance Preserving Binary Codes and Distance Table,J. Inf. Sci. Eng.,2017
+8856fbf333b2aba7b9f1f746e16a2b7f083ee5b8,Analyzing animal behavior via classifying each video frame using convolutional neural networks,,2015
+887cd2271ca5a58501786d49afa53139f48c66f3,"Visual orienting in children with autism: Hyper‐responsiveness to human eyes presented after a brief alerting audio‐signal, but hyporesponsiveness to eyes presented without sound",,2017
+88132a786442ab8a5038d81164384c1c1f7231c8,Limited attentional bias for faces in toddlers with autism spectrum disorders.,Archives of general psychiatry,2010
+9f22e0749405dfc3e3211474b933aa7514722e4b,Theory of mind - not emotion recognition - mediates the relationship between executive functions and social functioning in patients with schizophrenia.,Psychiatria Danubina,2018
9f6d04ce617d24c8001a9a31f11a594bd6fe3510,Attentional bias towards angry faces in trait-reappraisal,,2011
+9f61362052e7675b3053a9d1b682ad917ce0e3d1,Social relevance drives viewing behavior independent of low-level salience in rhesus macaques,,2014
+9fb1bd7d98a2fa79e1b9cb21b865ec7af0c1283f,Not All Distraction Is Bad: Working Memory Vulnerability to Implicit Socioemotional Distraction Correlates with Negative Symptoms and Functional Impairment in Psychosis,,2014
9fdfe1695adac2380f99d3d5cb6879f0ac7f2bfd,Active Tracking and Cloning of Facial Expressions Using Spatio-Temporal Information,Unknown,2002
6b7f7817b2e5a7e7d409af2254a903fc0d6e02b6,Feature Extraction through Cross-Phase Congruency for Facial Expression Analysis,IJPRAI,2009
6b17b219bd1a718b5cd63427032d93c603fcf24f,Videos from the 2013 Boston Marathon: An Event Reconstruction Dataset for Synchronization and Localization,,2017
+07d49098ada2d8e1ca0608c70e559dd517ca3432,Modélisation de contextes pour l'annotation sémantique de vidéos. (Context based modeling for video semantic annotation),Unknown,2013
+073c9ec4ff069218f358b9dd8451a040cf1a4a82,Object Classification and Detection in High Dimensional Feature Space,,2013
+38eb71578f82477f4b032481bd401f19f14eaf25,Efficient Resource-constrained Retrospective Analysis of Long Video Sequences,,2009
+3885cfd634c025c6e27c4db8211d72f54f864f90,Implications of holistic face processing in autism and schizophrenia,,2013
+381d15951b5beb2456ac016ac7f15fd27aa07d1c,"The prodrome of autism: early behavioral and biological signs, regression, peri- and post-natal development and genetics.","Journal of child psychology and psychiatry, and allied disciplines",2010
+3859d584d3fb794c2b74b42f0f195d16ce8e3820,Combining Recognition and Geometry for Data - Driven 3 D Reconstruction,,2013
3896c62af5b65d7ba9e52f87505841341bb3e8df,Face Recognition from Still Images and Video,,2011
+38ea19546355e41ee1d57febc07613e7d3122607,Dynamic Functional Brain Connectivity for Face Perception,,2015
+00c4325c669c52db182390b2ab4a2b9c20f06b8d,A False Trail to Follow: Differential Effects of the Facial Feedback Signals From the Upper and Lower Face on the Recognition of Micro-Expressions,,2018
009cd18ff06ff91c8c9a08a91d2516b264eee48e,Face and Automatic Target Recognition Based on Super-Resolved Discriminant Subspace,,2012
+00d14af37bc75b6477b4846f6ab561cdc89c96a2,"UvA-DARE ( Digital Academic Repository ) Infants ’ Temperament and Mothers ’ , and Fathers ’ Depression Predict Infants ’ Attention to Objects Paired with Emotional",Unknown,2018
+00e39fad9846084eb435b6cddd675ee11f2dfb90,Person Re-identification Using Haar-based and DCD-based Signature,2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance,2010
+000cd8d20d91ded078949dfcde76817221ea96c8,Learning Visual Attributes from Image and Text,,2015
+002d1619748a99aa683b5c30b7eafebdfe6adfc4,Nearest feature line embedding for face hallucination,,2013
+00796052277d41e2bb3a1284d445c1747aed295f,Performance and Energy Consumption Characterization and Modeling of Video Decoding on Multi-core Heterogenous SoC and their Applications,,2015
6ed738ff03fd9042965abdfaa3ed8322de15c116,K-MEAP: Generating Specified K Clusters with Multiple Exemplars by Efficient Affinity Propagation,2014 IEEE International Conference on Data Mining,2014
+6ee1f57cbf7daa37576efca7e7d24040a5c94ee2,Multimodal Neural Network for Overhead Person Re-Identification,2017 International Conference of the Biometrics Special Interest Group (BIOSIG),2017
+6eb8e193687c16f0edc3742d3549ad175ef648d1,Working memory load disrupts gaze-cued orienting of attention,,2015
+6e209d7d33c0be8afae863f4e4e9c3e86826711f,Weakly-supervised segmentation by combining CNN feature maps and object saliency maps,2016 23rd International Conference on Pattern Recognition (ICPR),2016
+6e7d799497b94954dc4232d840628c3a00263e42,Deep Multimodal Pain Recognition: A Database and Comparision of Spatio-Temporal Visual Modalities,,2018
6ee64c19efa89f955011531cde03822c2d1787b8,Table S1: Review of Existing Facial Expression Databases That Are Often Used in Social Psycholgy,,
6eece104e430829741677cadc1dfacd0e058d60f,Use of Automated Facial Image Analysis for Measurement of Emotion Expression,,2004
6e93fd7400585f5df57b5343699cb7cda20cfcc2,Comparing a novel model based on the transferable belief model with humans during the recognition of partially occluded facial expressions.,Journal of vision,2009
+6e80ad43c5f383c1d87b1ced2a336fe5cd44e044,Faster R-CNN for Robust Pedestrian Detection Using Semantic Segmentation Network,,2018
+6eb5db8e6a79ad59bf4f4a5fccdd5b10237408d7,Cross Talk: The Microbiota and Neurodevelopmental Disorders,,2017
9ac82909d76b4c902e5dde5838130de6ce838c16,Recognizing Facial Expressions Automatically from Video,,2010
9a3535cabf5d0f662bff1d897fb5b777a412d82e,Large-scale geo-facial image analysis,EURASIP J. Image and Video Processing,2015
+9a7b7d61481e3a5bca1ef809358d46ac87405f67,Neural circuitry of emotional face processing in autism spectrum disorders.,Journal of psychiatry & neuroscience : JPN,2010
+9a88d23234ee41965ac17fc5774348563448a94d,3021977 GI P_212 Cover.indd,,2013
+9a08459b0cb133f0f4352c58225446f9dc95ecc4,Metadata of the chapter that will be visualized in SpringerLink,Unknown,2015
+9a5a1763e0342d41cb1d1eef18a007be6e8dba89,Image Annotation with Discriminative Model and Annotation Refinement by Visual Similarity Matching,,2011
+9adbbd9dadaf7b15bb585555e7a2e2223e711296,Identity information content depends on the type of facial movement,,2016
+36d8cc038db71a473d0c94c21f2b68a840dff21c,Unsupervised Detector Adaptation by Joint Dataset Feature Learning,,2014
36fe39ed69a5c7ff9650fd5f4fe950b5880760b0,Tracking von Gesichtsmimik mit Hilfe von Gitterstrukturen zur Klassifikation von schmerzrelevanten Action Units,,2010
+36d487129fd0b828255e417e0d10cf13d7f525cf,Reduced functional integration and segregation of distributed neural systems underlying social and emotional information processing in autism spectrum disorders.,Cerebral cortex,2012
3674f3597bbca3ce05e4423611d871d09882043b,Facial Expression Spacial Charts for Describing Dynamic Diversity of Facial Expressions,Journal of Multimedia,2012
+36f039e39efde3558531b99d85cd9e3ab7d396b3,Efficiency of Recognition Methods for Single Sample per Person Based Face Recognition,,2011
+365b72a225a18a930b96e7c0b215b9fede8a0968,Storyline Reconstruction for Unordered Images,,2016
361d6345919c2edc5c3ce49bb4915ed2b4ee49be,Models for supervised learning in sequence data,Unknown,2018
+5cc9fdd3a588f6e62e46d7884c1dbeef92a782f2,Spontaneous attention to faces in Asperger syndrome using ecologically valid static stimuli.,Autism : the international journal of research and practice,2013
+5c7db2907c586f4f2d6ae5937b0dc0f4d1bc834a,Deliverable D2.1 Audio-visual Algorithms for Person Tracking and Characterization (baseline),,2017
+5c81048593a6729b2d0b948a1129a97bdbf82f11,Moving Object Localization Using Optical Flow for Pedestrian Detection from a Moving Vehicle,,2014
5c8672c0d2f28fd5d2d2c4b9818fcff43fb01a48,Robust Face Detection by Simple Means,,2012
+5c48f97a8a8217025abafeababaef6288fd7ded6,Model syndromes for investigating social cognitive and affective neuroscience: a comparison of Autism and Williams syndrome.,Social cognitive and affective neuroscience,2006
+5ce40105e002f9cb428a029e8dec6efe8fad380e,Co-design of architectures and algorithms for mobile robot localization and model-based detection of obstacles. (Co-conception d'architectures et d'algorithmes pour la localisation de robots mobiles et la détection d'obstacles basée sur des modèles),Unknown,2017
+09d03b792923695deb0492d8fc3582a50e5f1a1e,Band-Sifting Decomposition for Image-Based Material Editing,ACM Trans. Graph.,2015
+0947c7c46943ebbb6a4b5c795c9b54552c8e0b5a,"QMAS: Querying, Mining and Summarization of Multi-modal Databases",2010 IEEE International Conference on Data Mining,2010
+090b3189391f3e1917649b3a62696febbf0429e1,Taking the Perfect Selfie: Investigating the Impact of Perspective on the Perception of Higher Cognitive Variables,,2017
+09e3967a34cca8dc0f00c9ee7a476a96812a55e0,1 Machine Learning Methods for Social Signal Processing,,2014
+098a0bd7c948e9c94704ac5e8c768c8d430e1842,Cascaded Models for Articulated Pose Estimation,,2010
+5d1608e03ab9c529d0b05631f9d2a3afcbf1c3e3,Sparsity and Robustness in Face Recognition,CoRR,2011
5d09d5257139b563bd3149cfd5e6f9eae3c34776,Pattern recognition with composite correlation filters designed with multi-objective combinatorial optimization,,2014
+5d5533b8b95f25f63e07786cf3e063c8db356f1f,Human Observers and Automated Assessment of Dynamic Emotional Facial Expressions: KDEF-dyn Database Validation,,2018
+31e0303d98fd1bb6a1074d4fe0b14228e91b388b,基於稀疏表示之語者識別 (Sparse Representation Based Speaker Identification) [In Chinese],,2014
+31786e6d5187d7bc41678cbd2d1bf8edf1ddfed9,Capture de mouvements humains par capteurs RGB-D. (Capture human motions by RGB-D sensor ),Unknown,2015
3152e89963b8a4028c4abf6e1dc19e91c4c5a8f4,Exploring Stereotypes and Biased Data with the Crowd,CoRR,2018
+910da5e0afef96c8acca3c6a4314a9ab5121b1e4,Détection d'obstacles multi-capteurs supervisée par stéréovision. (Multi-sensor road obstacle deetection controled by stereovision),Unknown,2008
65b737e5cc4a565011a895c460ed8fd07b333600,Transfer Learning for Cross-Dataset Recognition: A Survey,,2017
+65683bd97720bc18a022b23755b32c8c988e8d5c,Discovering social groups via latent structure learning.,Journal of experimental psychology. General,2018
+656a5d4d84c450792402b3c69eecbdbca4cad4cb,2.1. Imagenet and Related Datasets,,
+656b6133fd671f129fce0091a8dab39c97e604f2,Multiview Discriminative Geometry Preserving Projection for Image Classification,,2014
628a3f027b7646f398c68a680add48c7969ab1d9,Plan for Final Year Project : HKU-Face : A Large Scale Dataset for Deep Face Recognition,Unknown,2017
6226f2ea345f5f4716ac4ddca6715a47162d5b92,Object Detection: Current and Future Directions,Front. Robotics and AI,2015
+629722342f719ee413e9bb07072a2fc2b4f09a26,Gender Classification by Information Fusion of Hair and Face,,2008
+62dd66f9f4995cfdaafb479de50363ce0255b1bd,2 Feature Extraction Based on Wavelet Moments and Moment Invariants in Machine Vision Systems,Unknown,2012
968b983fa9967ff82e0798a5967920188a3590a8,Children's recognition of disgust in others.,Psychological bulletin,2013
+968ab65077c4be1c1071120052b2e4b4f3d3c59a,"""Seeing is believing: the quest for multimodal knowledge"" by Gerard de Melo and Niket Tandon, with Martin Vesely as coordinator",SIGWEB Newsletter,2016
+96eacc464c0177efc4f802f220888c7f675f24af,Deep Semantic Face Deblurring Supplementary Material,Unknown,2018
+96723b42451c42ec396381596490143aac8f85cd,A Computer Vision Approach for the Eye Accessing Cue Model Used in Neuro-linguistic Programming,Unknown,2013
966e36f15b05ef8436afecf57a97b73d6dcada94,Dimensionality Reduction using Relative Attributes,,2014
+96094b030013ca2d9b6d5a14b6f1fbbc57eb8a89,What is in that picture ? Visual Question Answering System,,2017
+3a53bad58f8467092477857ff9c2ae904d7108d2,Simultaneous perceptual and response biases on sequential face attractiveness judgments.,Journal of experimental psychology. General,2015
+3a1c3307f57ef09577ac0dc8cd8b090a4fe8091f,Thermal-to-visible face recognition using partial least squares.,"Journal of the Optical Society of America. A, Optics, image science, and vision",2015
3acb6b3e3f09f528c88d5dd765fee6131de931ea,Novel representation for driver emotion recognition in motor vehicle videos,2017 IEEE International Conference on Image Processing (ICIP),2017
+3a27bdb9925d5b247868950a9575823b3194ac8b,Adaptation across the cortical hierarchy: low-level curve adaptation affects high-level facial-expression judgments.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2008
+3af0400c011700f3958062edfdfed001e592391c,The Intense World Theory – A Unifying Theory of the Neurobiology of Autism,,2010
+3af28e9e9e883c235b6418a68bda519b08f9ae26,Implications of Adult Facial Aging on Biometrics,Unknown,2018
+5432392d916e730c53962be202c115133e6d7777,Face processing in a case of high functioning autism with developmental prosopagnosia.,Acta neurobiologiae experimentalis,2018
+54568bdce3405ffbe2a6f5820711f966e2d2faf3,How Do We Update Faces? Effects of Gaze Direction and Facial Expressions on Working Memory Updating,,2012
+545dc167a4879ce2d61836cb300479c305f8e096,Event-Centric Twitter Photo Summarization,,2014
5495e224ac7b45b9edc5cfeabbb754d8a40a879b,Feature Reconstruction Disentangling for Pose-invariant Face Recognition Supplementary Material,,2017
54756f824befa3f0c2af404db0122f5b5bbf16e0,Computer Vision — Visual Recognition,,2009
9820920d4544173e97228cb4ab8b71ecf4548475,Automated facial coding software outperforms people in recognizing neutral faces as neutral from standardized datasets,,2015
+987dd3dd6079e5fa8a10a1c53b2580fd71e27ede,Concept-Based Video Retrieval By Cees,Unknown,2009
+9802885e39e0847374a2efae801b8b719c09c64c,"An Effective Two-Finger, Two-Stage Biometric Strategy for the US-VISIT Program",Operations Research,2009
+9899eb0ae24aa8c992244afe5f4455e9f96c1f18,"Characteristics of Brains in Autism Spectrum Disorder: Structure, Function and Connectivity across the Lifespan.",Experimental neurobiology,2015
+98960be5ae51d30118f091f7091299a49f2f34bb,Global and Feature Based Gender Classification of Faces: a Comparison of Human Performance and Computational Models,,2004
+98582edd6029c94844f5a40d246eaa86f74d8512,Learning Visual Scene Attributes,,2013
+98126d18be648640fc3cfeb7ffc640a2ec1d5f6f,Supplemental Material: Discovering Groups of People in Images,,2014
+98a60b218ff8addaf213e97e2f4b54d39e45f5b9,Benchmarking Real World Object Recognition,,2005
+984ecfbda7249e67eca8d9b1697e81f80e2e483d,Visual object categorization with new keypoint-based adaBoost features,2009 IEEE Intelligent Vehicles Symposium,2009
+5388638c7801b11958d937c89ece764bc769e298,Identity processing in multiple-face tracking.,Journal of vision,2009
+3fee5c6343c969f33a7db4c7f7da1e152effd911,Patterns of fixation during face recognition: Differences in autism across age.,Autism : the international journal of research and practice,2018
+3f600008dd9745e8357f5b7b3c1a69b8be6b7767,Atypical reflexive gaze patterns on emotional faces in autism spectrum disorders.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2010
+3f4377109a92cf4e422b7e2ae95ef3144323ea72,Bridging the Gap Between Synthetic and Real Data,,2015
+303be881f6cd4907c5e357bc1bb5547d8ea1da5a,Individual Differences in the Recognition of Enjoyment Smiles: No Role for Perceptual–Attentional Factors and Autistic-Like Traits,,2011
+30e18a16d4c7092694d55743ff92965e5dec2692,"Hormonal contraceptives, menstrual cycle and brain response to faces.",Social cognitive and affective neuroscience,2014
+30256c10cb7ec139b4245855850998c39b297975,Functional magnetic resonance imaging of autism spectrum disorders,,2012
+30d21b5baf9514d26da749c6683c49b4fa55f2b5,Towards a unified account of face (and maybe object) processing,,2012
307a810d1bf6f747b1bd697a8a642afbd649613d,An affordable contactless security system access for restricted area,,2016
+3073eff17368262d7c605bbcaf3b2fb015754d39,Voice conversion versus speaker verification: an overview,,2014
+301662c2a6ed86e48f21c1d24bfc67b403201b0c,Repetition Suppression in Ventral Visual Cortex Is Diminished as a Function of Increasing Autistic Traits,,2015
+30f84c48bdf2f6152075dd9651a761a84b2f2166,"No fear, no panic: probing negation as a means for emotion regulation.",Social cognitive and affective neuroscience,2013
3083d2c6d4f456e01cbb72930dc2207af98a6244,Perceived Age Estimation from Face Images,,2011
+30f49d6595359a4a18c728ec83f99346d1e16348,Intact Reflexive but Deficient Voluntary Social Orienting in Autism Spectrum Disorder,,2015
+5eee9c417157916ee66689718af65965c423b2b7,Autism and Asperger’s Syndrome: A Cognitive Neuroscience Perspective,,2009
+5e74d92d841d1bc1c9c2d80219f98bf892f239c4,Developmental changes in face visual scanning in autism spectrum disorder as assessed by data-based analysis,,2015
+5eae1a3e0dfd0834be6a003b979bf5b3dc923453,"Far-Field, Multi-Camera, Video-to-Video Face Recognition",,2007
+5eefe98aafffe665b19de515e3ba90c9c0b7219c,Trimmed Event Recognition Submission to ActivityNet Challenge 2018,Unknown,
5e0e516226413ea1e973f1a24e2fdedde98e7ec0,The Invariance Hypothesis and the Ventral Stream,,2013
+5be6340c55d4a45e96e811bdeac3972328ca9247,People Identification and Tracking Through Fusion of Facial and Gait Features,,2014
+5b6bdf478860b1e3f797858e71abd14f98684b61,Distributed neural computation for the visual perception of motion. (Calcul neuronal distribué pour la perception visuelle du mouvement),,2011
+5b94093939ac42aba54ab41eb1725aeba1bd5c34,RGB-D Segmentation of Poultry Entrails,,2016
5bc0a89f4f73523967050374ed34d7bc89e4d9e1,The role of emotion transition for the perception of social dominance and affiliation.,Cognition & emotion,2016
+3765df816dc5a061bc261e190acc8bdd9d47bec0,Presentation and validation of the Radboud Faces Database,Unknown,2010
+37a23e76674e606ce779131d2c93496e8a53bb2f,The discrete cosine transform (DCT) plus local normalization: a novel two-stage method for de-illumination in face recognition,,2012
081189493ca339ca49b1913a12122af8bb431984,Supplemental Material for Photorealistic Facial Texture Inference Using Deep Neural Networks,,2017
+0834dff6e1d37ecb36137e019f8e2c933d5e74f6,Building Part-Based Object Detectors via 3D Geometry,2013 IEEE International Conference on Computer Vision,2013
+08e3a0f80f10fc40cc1c043cbc4c873a76a6f6e8,Enhanced Pavlovian aversive conditioning to positive emotional stimuli.,Journal of experimental psychology. General,2018
081286ede247c5789081502a700b378b6223f94b,Neural Correlates of Facial Mimicry: Simultaneous Measurements of EMG and BOLD Responses during Perception of Dynamic Compared to Static Facial Expressions,,2018
+083ac08287af7df220d88dca2fbf5b1812e35ee8,Abnormal functional connectivity in autism spectrum disorders during face processing.,Brain : a journal of neurology,2008
+6d84d92d9ed6c226f0cc6401bc425a23432c9f96,Autism spectrum disorders: clinical and research frontiers.,Archives of disease in childhood,2008
+6d432962055a8c521e6b388d5a0a2140a0019a5e,Sensor network reconfiguration and big multimedia data fusion for situational awareness in smart environments,,2014
+6d8612f7856f569f5635ff07a6b94480a9c7c284,Ensemble perception of emotions in autistic and typical children and adolescents,,2017
+6d7ba173121edd5defadfde04f7c1e7bc72859c2,The study of autism as a distributed disorder.,Mental retardation and developmental disabilities research reviews,2007
01cc8a712e67384f9ef9f30580b7415bfd71e980,Failing to ignore: paradoxical neural effects of perceptual load on early attentional selection in normal aging.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2010
+01ababc0985143ad57320b0599fb2f581d79d3c2,Unobtrusive Low Cost Pupil Size Measurements using Web cameras,CoRR,2013
+01018a509f32601e1bbf7f0159aad1a513e23f92,Computers in the Human Interaction Loop,,2009
+06b4522433beca98aea99f924fbaeb8f861df8cd,Selection and combination of local Gabor classifiers for robust face verification,"2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS)",2012
06f8aa1f436a33014e9883153b93581eea8c5c70,Leaving Some Stones Unturned: Dynamic Feature Prioritization for Activity Detection in Streaming Video,,2016
+06e768d74f076b251d53b0c86fc9910d7243bdc6,Effective and efficient visual description based on local binary patterns and gradient distribution for object recognition,Unknown,2016
066d71fcd997033dce4ca58df924397dfe0b5fd1,Iranian Face Database and Evaluation with a New Detection Algorithm,,2007
+06f7e0aee7fc5807ab862432a4e5ade2cda73c4b,Flowing ConvNets for Human Pose Estimation in Videos,2015 IEEE International Conference on Computer Vision (ICCV),2015
+0630b3677323c8c987f16f37545ac6073293de8d,Enhancement and stylization of photographs by Vladimir Leonid,,2013
+066476a38f8751696f5f7b47c0fb7f1d8ecdac1a,Automatic adaptation of a generic pedestrian detector to a specific traffic scene,CVPR 2011,2011
+06f2df0ec9ab6968411e34f581dd8f5d40500d7f,The fusiform face area: a cortical region specialized for the perception of faces.,"Philosophical transactions of the Royal Society of London. Series B, Biological sciences",2006
+06680961e99aadb366968e5f515da58864ecd784,ENabler for Design Specifications FP 6 - IST - 2005 - 27916,,2006
+06c8fcb0429afd3aee153ba42e1fd8aa93f7214f,Social roles in hierarchical models for human activity recognition,2012 IEEE Conference on Computer Vision and Pattern Recognition,2012
+06f969d3858b6d14425fcbe7ff12b72e213ee240,Recognizing Cardiac Magnetic Resonance Acquisition Planes,,2014
+6c4e173fdafa89ac7b40e1dddf953dcc833db92d,Photometric Normalization for Face Recognition using Local discrete cosine Transform,IJPRAI,2013
+6c9ed3378dd53a5ad9e30613ba2e1ef363bd1f9d,Atoms of recognition in human and computer vision.,Proceedings of the National Academy of Sciences of the United States of America,2016
6cfc337069868568148f65732c52cbcef963f79d,Audio-Visual Speaker Localization via Weighted Clustering Israel -,Unknown,2018
+6c70cad229cf3f02d3d490b42c7bd92c6eade1d1,Towards Good Practices on Building Effective CNN Baseline Model for Person Re-identification,CoRR,2018
+39db629b96eda72a23a49d54f32689e0651ca4ae,Applying artificial vision models to human scene understanding,,2015
+39bce1d5e4b31a555f12f0a44e92abcad73aab4f,"Explorer "" Here ' s looking at you , kid """,Unknown,2017
+39742f9b3a9f7adefbe936de68249148576b90da,Alcohol and remembering a hypothetical sexual assault: Can people who were under the influence of alcohol during the event provide accurate testimony?,Memory,2016
+39bbe9885ad1e12e79bc620d83f7768d2fc04994,Autism is characterized by dorsal anterior cingulate hyperactivation during social target detection.,Social cognitive and affective neuroscience,2009
+39b0bce87eec467adfe5bebcfe628ff5bd397fc7,"R4-A.2: Rapid Similarity Prediction, Forensic Search & Retrieval in Video",,2015
+397349476582198639abc7a8b933e350cbc24c37,2D&3D-ComFusFace: 2D and 3D Face Recognition by Scalable Fusion of Common Features,,2012
+992eca71ee8314ede9bf680b6966730f6bb77bc5,Likability’s Effect on Interpersonal Motor Coordination: Exploring Natural Gaze Direction,,2017
+99b41df501f25f4aee9c1f94a75510b2fbcc6bed,Title Impaired social brain network for processing dynamic facialexpressions in autism spectrum disorders,Unknown,2017
+9947687ffe0bd2d6cd4fe717e534cfcb59302a4e,Data-driven photographic style using local transfer,,2015
992ebd81eb448d1eef846bfc416fc929beb7d28b,Exemplar-Based Face Parsing Supplementary Material,,2013
+9963af1199679e176f0836e6d63572b3a69fa7da,23 Generating Facial Expressions with Deep Belief Nets,Unknown,2008
+52f71cc9c312aa845867ad1695c25a6d1d94ba0e,The invariance assumption in process-dissociation models: an evaluation across three domains.,Journal of experimental psychology. General,2015
+52884a0c7913be319c1a2395f009cea47b03f128,Explorer Learning Grounded Meaning Representations with Autoencoders,Unknown,2015
+52b6df1fe810d36fd615eb7c47aa1fd29376e769,Graph Mining for Object Tracking in Videos,Unknown,2012
+52417b0406886154f0b4e2343ad6ac18c0484ec4,Ecological legacies of civil war: 35-year increase in savanna tree cover following wholesale large-mammal declines,,2015
+526ce5c72af5e1f93b8029a26e2eed7d1ac009f5,0 Constructing Kernel Machines in the Empirical Kernel Feature Space,Unknown,2018
+527dd9647c474490ac33ac5b0a19aa76b226610d,Intact perception but abnormal orientation towards face-like objects in young children with ASD,,2016
+52049fb96156729ce0ad88f86fa617ecf7d237e1,Book chapter for Machine Learning for Human Motion Analysis: Theory and Practice,,2011
+55ba5e4c07f6ecf827bfee04e96de35a170f7485,This Dissertation entitled MODELING THE HUMAN FACE THROUGH MULTIPLE VIEW THREE-DIMENSIONAL STEREOPSIS: A SURVEY AND COMPARATIVE ANALYSIS OF FACIAL RECOGNITION OVER MULTIPLE MODALITIES,,2006
+5592574c82eec9367e9173b7820ff329a27b6c21,Image Enhancement and Automated Target Recognition Techniques for Underwater Electro-Optic Imagery,Unknown,2007
+97bcf007516cb70d8cb17b7de6452aa06c4b9c76,GABAergic neurotransmission alterations in autism spectrum disorders,,2015
978a219e07daa046244821b341631c41f91daccd,Emotional Intelligence: Giving Computers Effective Emotional Skills to Aid Interaction,,2008
+970e723404885e94e77780766b39ee951dd7abb3,Multimodal Learning of Geometry-Preserving Binary Codes for Semantic Image Retrieval,IEICE Transactions,2017
+630af2eb466fac956f9a43bf877be0eae6d80027,CariGANs: Unpaired Photo-to-Caricature Translation,Unknown,2018
+63344dee49a1ab7e27ac34eefc30fb948a0bf9bb,Geometry and Illumination Modelling for Scene Understanding,,2011
+0fd53d7e1ab8f42c710cb77b5ec4cc2b22158a4c,Combined Data Association and Evolving Particle Filter for Tracking of Multiple Articulated Objects,EURASIP J. Image and Video Processing,2011
+0f5e10cfca126682e1bad1a07848919489df6a65,Facial emotion processing in patients with social anxiety disorder and Williams-Beuren syndrome: an fMRI study.,Journal of psychiatry & neuroscience : JPN,2016
+0f5bf2a208d262aa0469bd3185f6e2e56acada81,Pose Estimation and Segmentation of People in 3D Movies,2013 IEEE International Conference on Computer Vision,2013
0f829fee12e86f980a581480a9e0cefccb59e2c5,Bird Part Localization Using Exemplar-Based Models with Enforced Pose and Subcategory Consistency,2013 IEEE International Conference on Computer Vision,2013
0f395a49ff6cbc7e796656040dbf446a40e300aa,The Change of Expression Configuration Affects Identity-Dependent Expression Aftereffect but Not Identity-Independent Expression Aftereffect,,2015
+0f42c64a74bc6e3e83821aa8ab5dd8e3a4b797cd,Controlled scanpath variation alters fusiform face activation.,Social cognitive and affective neuroscience,2007
0f21a39fa4c0a19c4a5b4733579e393cb1d04f71,Evaluation of optimization components of a 3D to 2D landmark fitting algorithm for head pose estimation,Unknown,2018
+0f2ffd582674bd856247bc5482d85e6db3b49b8f,A neural signature of the creation of social evaluation.,Social cognitive and affective neuroscience,2014
+0a55e4191c90ec1edb8d872237a2dacd5f6eda90,"Intentional Minds: A Philosophical Analysis of Intention Tested through fMRI Experiments Involving People with Schizophrenia, People with Autism, and Healthy Individuals",,2011
+0a60e76e6983e1647469172a50907023913b0c9f,Longitudinal study of amygdala volume and joint attention in 2- to 4-year-old children with autism.,Archives of general psychiatry,2009
+0a814669f4a0198e46a3a0d91a1bbb81bb089216,"Deficits in facial, body movement and vocal emotional processing in autism spectrum disorders.",Psychological medicine,2010
+0a3a33b872c84dac88bcd6f5bd460ef03584e0f7,Abnormal Neural Activation to Faces in the Parents of Children with Autism.,Cerebral cortex,2015
0a4fc9016aacae9cdf40663a75045b71e64a70c9,Illumination Normalization Based on Homomorphic Wavelet Filtering for Face Recognition,J. Inf. Sci. Eng.,2013
0a85afebaa19c80fddb660110a4352fd22eb2801,Neural Animation and Reenactment of Human Actor Videos,CoRR,2018
0ac664519b2b8abfb8966dafe60d093037275573,Facial action unit detection using kernel partial least squares,2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops),2011
0acf23485ded5cb9cd249d1e4972119239227ddb,Dual coordinate solvers for large-scale structural SVMs,CoRR,2013
641f0989b87bf7db67a64900dcc9568767b7b50f,Reconstructing faces from their signatures using RBF regression,Unknown,2013
+64753fe167a46208e28237fa98db8daedbef83e4,Normal social cognition in developmental prosopagnosia.,Cognitive neuropsychology,2009
+645766177de2ef61619572bc09ce239c232d7d5c,Is the left hemisphere androcentric? Evidence of the learned categorical perception of gender,,2015
64782a2bc5da11b1b18ca20cecf7bdc26a538d68,Facial Expression Recognition using Spectral Supervised Canonical Correlation Analysis,J. Inf. Sci. Eng.,2013
+90ce227ec08053ea6acf9f9f9f53d8b7169574f2,An Introduction to Evaluating Biometric Systems,IEEE Computer,2000
+903210406f14a12b481524d543b14f16114797e2,Pretest of images for the beauty dimension,Unknown,2015
+90fbcea84f621ee5d73482c5cb02479778aecccd,Pose-Invariant Face Recognition via RGB-D Images,,2016
90a754f597958a2717862fbaa313f67b25083bf9,A Review of Human Activity Recognition Methods,Front. Robotics and AI,2015
bf961e4a57a8f7e9d792e6c2513ee1fb293658e9,Robust Face Image Matching under Illumination Variations,EURASIP J. Adv. Sig. Proc.,2004
+bf96a0f037e7472e4b6cb1dae192a5fedbbbd88a,Visual Listening In: Extracting Brand Image Portrayed on Social Media,Unknown,2018
+bffe37791ee7aa277ba6d7c5ff2cb9bddddea09f,Neural correlates of emotion processing during observed self-face recognition in individuals with autism spectrum disorders,Unknown,2017
+bfffcd2818a1679ac7494af63f864652d87ef8fa,Neural Importance Sampling,CoRR,2018
bffbd04ee5c837cd919b946fecf01897b2d2d432,Facial Feature Tracking and Occlusion Recovery in American Sign Language,,2006
d3e04963ff42284c721f2bc6a90b7a9e20f0242f,On Forensic Use of Biometrics,,2014
d3faed04712b4634b47e1de0340070653546deb2,Neural Best-Buddies: Sparse Cross-Domain Correspondence,ACM Trans. Graph.,2018
+d37013e4ce0f5dd6b61a4ffadecc401274966602,Reading affect in the face and voice: neural correlates of interpreting communicative intent in children and adolescents with autism spectrum disorders.,Archives of general psychiatry,2007
d41c11ebcb06c82b7055e2964914b9af417abfb2,CDI-Type I: Unsupervised and Weakly-Supervised Discovery of Facial Events,,2011
d4001826cc6171c821281e2771af3a36dd01ffc0,Modélisation de contextes pour l'annotation sémantique de vidéos. (Context based modeling for video semantic annotation),,2013
+d4e4369babdba158bfdce1b605f92d6b1b665be4,The amygdala and the relevance detection theory of autism: an evolutionary perspective,,2013
+d4f8168242f688af29bcbbe1cc5aec7cd12a601c,Edinburgh Research Explorer Visually Grounded Meaning Representations,Unknown,2017
+d46a5bba21f897f1c4b3366dcb663820ef1c282d,Cerebral Hemodynamic Response to Faces,,2012
+d409d8978034de5e5e8f9ee341d4a00441e3d05f,Annual research review: re-thinking the classification of autism spectrum disorders.,"Journal of child psychology and psychiatry, and allied disciplines",2012
+bad7254ae08f8bf1305e70c7de28374f67f151fd,Ré-identification de personnes à partir des séquences vidéo. (Person re-identification from video sequence),Unknown,2014
+ba25c219b52d675b579941364ce6ee6700cea8e8,8D-THERMO CAM: Combination of Geometry with Physiological Information for Face Recognition,,2005
ba8a99d35aee2c4e5e8a40abfdd37813bfdd0906,Uporaba emotivno pogojenega računalništva v priporočilnih sistemih,,2011
+bab47c7bf80c9310f947cbdaf71b3c983c497b68,Systematic Parameter Optimization and Application of Automated Tracking in Pedestrian Dominant Situations Date of submission : 2014-0801,Unknown,2014
a022eff5470c3446aca683eae9c18319fd2406d5,Deep learning for semantic description of visual human traits. (Apprentissage profond pour la description sémantique des traits visuels humains),Unknown,2017
a0f193c86e3dd7e0020c0de3ec1e24eaff343ce4,A New Classification Approach using Discriminant Functions,J. Inf. Sci. Eng.,2005
a0e7f8771c7d83e502d52c276748a33bae3d5f81,Ensemble Nyström,,2012
a0061dae94d916f60a5a5373088f665a1b54f673,Lensless computational imaging through deep learning,CoRR,2017
a758b744a6d6962f1ddce6f0d04292a0b5cf8e07,"Study on Human Face Recognition under Invariant Pose, Illumination and Expression using LBP, LoG and SVM",Unknown,2017
+a7e5c01e3dca9284f8acffad750cdbb29689d3fb,Introduction to the special issue on learning semantics,Machine Learning,2013
+a760ce8baddf2da7946d2ed6f02ac3927f39a9da,Face Recognition Using a Unified 3D Morphable Model,Unknown,2016
+a77008329c785c0d5d4dcb3d9c79073df85a9b4e,Neural codes of seeing architectural styles,,2017
+b8b46df1b013c30d791972ee109425a94e3adc06,"Automaticity, Control, and the Social Brain",,2014
+b8471908880c916ebc70ac900e9446705ed258f4,Transitional and translational studies of risk for anxiety.,Depression and anxiety,2011
+b13b6e3dfdf6d708a923c547113d99047f1a0374,Neural activation to emotional faces in adolescents with autism spectrum disorders.,"Journal of child psychology and psychiatry, and allied disciplines",2011
+b13254c2c9ca90f57e385d34abc7fe78d74e5222,Real-Time Multi-object Tracking with Occlusion and Stationary Objects Handling for Conveying Systems,Unknown,2016
b18858ad6ec88d8b443dffd3e944e653178bc28b,Trojaning Attack on Neural Networks,,2017
b1df214e0f1c5065f53054195cd15012e660490a,Supplementary Material to Sparse Coding and Dictionary Learning with Linear Dynamical Systems,,2016
+b19e8bce7a3180456f8748caabade89dd802ea84,Inferring and Executing Programs for Visual Reasoning Supplementary Material,,2017
+dd609e4bd83cfcdbf64fc794da73a36398076890,Recurrent Human Pose Estimation,,2016
+dca12da787c023c97058cdb7d56e18ef287084f7,Zebrafish tracking using convolutional neural networks,,2017
+dcba9cd587be2ed5437370e12e3591bdde86dc3c,Template for Regular Entry,,2008
+dc23beb1e5c7402b1a9d5a7c854e62a253d0815e,Microscopic crowd simulation : evaluation and development of algorithms. (Simulation microscopique de foules : évaluation et développement d'algorithmes),Unknown,2016
+dc22de0ed56958013234cf7128952390fb47345a,Towards dense object tracking in a 2D honeybee hive,CoRR,2017
+b6bf15f123a814538fff5db757a474be6fc0c72f,Event-Centric Twitter Photo Summarization,Unknown,2014
+b69fbf046faf685655b5fa52fef07fb77e75eff4,Modeling guidance and recognition in categorical search: bridging human and computer object detection.,Journal of vision,2013
+b62486261104d5136aea782ee8596425b5f228da,Modelling perceptions of criminality and remorse from faces using a data-driven computational approach.,Cognition & emotion,2017
b64cfb39840969b1c769e336a05a30e7f9efcd61,CRF-Based Context Modeling for Person Identification in Broadcast Videos,Front. ICT,2016
b689d344502419f656d482bd186a5ee6b0140891,Structural resemblance to emotional expressions predicts evaluation of emotionally neutral faces.,Emotion,2009
+a96b6e645a8d3eb8efc7358a852cbfbaa32ae245,Small Group Detection in Crowds using Interaction Information,IEICE Transactions,2017
+a94b832facb57ea37b18927b13d2dd4c5fa3a9ea,Domain transfer convolutional attribute embedding,J. Exp. Theor. Artif. Intell.,2018
+a9e0e667537c9059b3050a64d22b8fe86787d913,"Detecting and Tracking Vehicles , Pedestrians , and Bicyclists at Intersections with a Stationary Lidar",Unknown,2018
+a975f1aea5dbb748955da0e17eef8d2270a49f25,Object Recognition,,
+a951f9b3aa95fe53cd9b19e15ebfdbde3fd5af62,Facial electromyographic responses to emotional information from faces and voices in individuals with pervasive developmental disorder.,"Journal of child psychology and psychiatry, and allied disciplines",2007
+d5813a4a0cca115b05e03d8d8c1ac8bf07176e96,Supplementary Material: Reinforced Video Captioning with Entailment Rewards,,2017
+d5440779ca69a2f010e57250f53a9be0116305e3,Emotional face expression modulates occipital-frontal effective connectivity during memory formation in a bottom-up fashion,,2015
+d5fe9c84710b71a754676b2ee67cec63e8cd184b,FPGA Implementation of a HOG-based Pedestrian Recognition System,,2010
+d2044b92486248f87bafe937779cd2167efe170c,"Connecting Deep Neural Networks to Physical, Perceptual, and Electrophysiological Auditory Signals",,2018
+d2b86b6dc93631990e21a12278e77f002fb4b116,Aalborg Universitet Attention in Multimodal Neural Networks for Person Re-identification,Unknown,2018
+aa420d32c48a3fd526a91285673cd55ca9fe2447,R 4-A . 1 : Dynamics-Based Video Analytics,Unknown,2015
+aaf4d938f2e66d158d5e635a9c1d279cdc7639c0,Toward visual understanding of everyday object,,2015
aa94f214bb3e14842e4056fdef834a51aecef39c,Reconhecimento de padrões faciais: Um estudo,,2015
afa57e50570a6599508ee2d50a7b8ca6be04834a,Motion in action : optical flow estimation and action localization in videos. (Le mouvement en action : estimation du flot optique et localisation d'actions dans les vidéos),Unknown,2016
+af370cbe392b7fb2b9f26476a7e063e0f4c46815,Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2016
+af8f59ceed0392159c3475c58af5b7ca8e4f6412,Facial Expression Recognition,Unknown,2018
+af8cd04bbe4902123d7042985159a6a5da9d9fb9,Représenter pour suivre : Exploitation de représentations parcimonieuses pour le suivi multi-objets. (Representing to follow: Exploitation of parsimonious representations for multi-object tracking),Unknown,2017
+af1a6c35f5d75122756d37faed062d5b5cd6bc71,Emotion Modelling and Facial Affect Recognition in Human-Computer and Human-Robot Interaction,,2009
+afb51f0e173cd9ab1d41075862945ae6bc593cde,Large databases of real and synthetic images for feature evaluation and prediction,,2012
b7426836ca364603ccab0e533891d8ac54cf2429,A Review on Human Activity Recognition Using Vision-Based Method,,2017
+b73ba189d0d1a3e2502716fee60c6865a7964d6e,Towards Open-Universe Image Parsing with Broad Coverage,,2013
b7774c096dc18bb0be2acef07ff5887a22c2a848,Distance metric learning for image and webpage comparison. (Apprentissage de distance pour la comparaison d'images et de pages Web),Unknown,2015
+b78e611c32dc0daf762cfa93044558cdb545d857,Temporal Action Detection with Structured Segment Networks Supplementary Materials,,2017
a8638a07465fe388ae5da0e8a68e62a4ee322d68,How to predict the global instantaneous feeling induced by a facial picture?,,2017
-dec0c26855da90876c405e9fd42830c3051c2f5f,Supplementary Material: Learning Compositional Visual Concepts with Mutual Consistency,Unknown,2018
+a84f80ca4e29b49cab1035ed8c7877caf2dbe914,Effects of Facial Symmetry and Gaze Direction on Perception of Social Attributes: A Study in Experimental Art History,,2016
+de46cbf18c7da9efc9368241463919e22230b0b0,What We Have Learned about Autism Spectrum Disorder from Valproic Acid,,2013
+de95fa1dd69a2d0d2b76539357062062f8b1e7b8,Face to Age,,2016
+decc4de8b6964ba473744741c3a46ac37f2d6e3e,A Pose Invariant 3 D Face Recognition Method,Unknown,2005
+dec0c26855da90876c405e9fd42830c3051c2f5f,Supplementary Material : Learning Compositional Visual Concepts with Mutual Consistency,Unknown,2018
+b05633a18a48d9c18735fd0a186a2654297ae543,Development of holistic vs. featural processing in face recognition,,2014
+b05ac3b2286c30fcab385f682b3519a823857112,UvA-DARE ( Digital Academic Repository ) Spatial frequency information modulates response inhibition and decision-making processes,Unknown,2017
+b0fafe26b03243a22e12b021266872afdb96572c,Factors of Transferability for a Generic ConvNet Representation,IEEE Transactions on Pattern Analysis and Machine Intelligence,2016
b018fa5cb9793e260b8844ae155bd06380988584,Project STAR IST - 2000 - 28764 Deliverable D 6 . 3 Enhanced face and arm / hand detector,,
+a67d54cf585c9491ab8a3e2d58d9c4b223359602,Spatial information and end-to-end learning for visual recognition. (Informations spatiales et apprentissage bout-en-bout pour la reconnaissance visuelle),Unknown,2014
+a68c07cb446f63fa6b48eda04c93392219c09700,Averted eye-gaze disrupts configural face encoding,,2014
a6b1d79bc334c74cde199e26a7ef4c189e9acd46,Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.,Human brain mapping,2018
+b97a155bdd86491c8d32f02d6dfe5b73aaef4549,Eliminating the mere exposure effect through changes in context between exposure and test.,Cognition & emotion,2013
b93bf0a7e449cfd0db91a83284d9eba25a6094d8,Supplementary Material for : Active Pictorial Structures,Unknown,2015
b9c9c7ef82f31614c4b9226e92ab45de4394c5f6,Face Recognition under Varying Illumination,,
+b941d4a85be783a6883b7d41c1afa7a9db451831,Radiofrequency ablation planning for cardiac arrhythmia treatment using modeling and machine learning approaches,Unknown,2017
+a13a4e4cc8f4744b40668fe7cca660ae0e88537d,Explorer Multi 30 K : Multilingual English-German Image Descriptions,Unknown,2017
+a165619977bc69a910a771e1096551073122775b,Computational Crowd Camera : Enabling Remote - Vision via Sparse Collective Plenoptic Sampling,,2013
a15c728d008801f5ffc7898568097bbeac8270a4,ForgetIT Deliverable Template,,2016
a1132e2638a8abd08bdf7fc4884804dd6654fa63,Real-Time Video Face Recognition for Embedded Devices,Unknown,2012
-ef940b76e40e18f329c43a3f545dc41080f68748,A Face Recognition and Spoofing Detection Adapted to Visually- Impaired People,Unknown,2017
+a1e1e7e976c22af9de26d9b74c2ece282e20218c,Looking at My Own Face: Visual Processing Strategies in Self–Other Face Recognition,,2018
+a1af05502eac70296ee22e5ab7e066420f5fe447,A Probabilistic Approach for Breast Boundary Extraction in Mammograms,,2013
+a18c8f76f2599d6d61f26cb1d4025ea386919dfe,Video Event Detection: From Subvolume Localization To Spatio-Temporal Path Search.,IEEE transactions on pattern analysis and machine intelligence,2013
+ef940b76e40e18f329c43a3f545dc41080f68748,A Face Recognition and Spoofing Detection Adapted to Visually-Impaired People,Unknown,2017
+ef2084979a3191403c1b8b48f503d06f346afb8f,Une méthode de reconnaissance des expressions du visage basée sur la perception,Unknown,2017
+ef75007cd6e5b990d09e7f3c4ba119be6c2546fb,Lecture 20: Object Recognition 20.1 Introduction 20.2.1 Neocognitron,,
+c3a1a3d13bf1cb2b9c054857b857c3fb9d7176f6,Détection de marqueurs affectifs et attentionnels de personnes âgées en interaction avec un robot. (Audio-visual detection of emotional (laugh and smile) and attentional markers for elderly people in social interaction with a robot),Unknown,2015
+c3dc704790e1a170919087baab0ad10d7df6c24e,Oxytocin in the socioemotional brain: implications for psychiatric disorders,,2015
c317181fa1de2260e956f05cd655642607520a4f,Objective Classes for Micro-Facial Expression Recognition,CoRR,2017
c32c8bfadda8f44d40c6cd9058a4016ab1c27499,Unconstrained Face Recognition From a Single Image,,2008
+c46bcb02f92612cf525fd84c6cc79b0638c2eac9,New Fuzzy LBP Features for Face Recognition,CoRR,2015
c42a8969cd76e9f54d43f7f4dd8f9b08da566c5f,Towards Unconstrained Face Recognition Using 3D Face Model,,2012
+c433ef13220c2ed4d2558283f8515b0e6e09bcad,A Public Video Dataset for Road Transportation Applications,Unknown,2013
+c4be56287fd666f9cfff257018a42e00dc56499d,The role of the fusiform-amygdala system in the pathophysiology of autism.,Archives of general psychiatry,2010
+c48ee576130473efe6dc3ee47f552bc581aa68b2,Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases,IEEE Computational Intelligence Magazine,2014
+ea923da826b9e6f89159cc960db7aac91b5ecbd6,Approved by Major Professor(s): Approved by Head of Graduate Program: Date of Graduate Program Head's Approval: Abhilasha Bhargav-Spantzel Protocols and Systems for Privacy Preserving Protection of Digital Identity Doctor of Philosophy,Unknown,2007
eafda8a94e410f1ad53b3e193ec124e80d57d095,Observer-Based Measurement of Facial Expression With the Facial Action Coding System,Unknown,2006
ea890846912f16a0f3a860fce289596a7dac575f,Benefits of social vs. non-social feedback on learning and generosity. Results from the Tipping Game,,2014
+ea5eaaadb8bc928fb7543d6fa24f9f4a229ff979,Mirror Neuron Forum.,Perspectives on psychological science : a journal of the Association for Psychological Science,2011
+e1e5d64318ec0a493995fb83ef4f433ddde82e77,Affects the Gaze-cueing Effect,,2013
+e1e6a4146c082e5465cde38e9511de3d150b4ede,Targeting static and dynamic workloads with a reconfigurable VLIW processor,Unknown,2018
+e10662a59b5f8e1f5684409023f11ca727647320,Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images,CoRR,2018
+cd0f7b3f545cc4bfa5e2d7185789e8ead7e3cee2,"Children’s and Adults’ Predictions of Black, White, and Multiracial Friendship Patterns",,2017
cd596a2682d74bdfa7b7160dd070b598975e89d9,Mood Detection: Implementing a facial expression recognition system,,2009
+ccd5bd5ce40640ebc6665b97a86ba3d28e457d11,Contributions to a fast and robust object recognition in images. (Contributions à une reconnaissance d'objet rapide et robuste en images),Unknown,2011
+cc5a1cf7ad9d644f21a5df799ffbcb8d1e24abe1,MonoPerfCap: Human Performance Capture from Monocular Video,,2017
ccdea57234d38c7831f1e9231efcb6352c801c55,Illumination Processing in Face Recognition,IJPRAI,2014
+ccc65463198ee0a0db9b303a3dc903c762dbccaa,Adaptive Selection of Deep Learning Models on Embedded Systems,CoRR,2018
+e6d4c0ac2352f108a078a4fd3f908a03b8571f2b,Racial Bias in Judgments of Physical Size and Formidability,,2017
+e6868f172df3736e052fec4c00b63780b3d739fe,Effects of a Common Variant in the CD38 Gene on Social Processing in an Oxytocin Challenge Study: Possible Links to Autism,Neuropsychopharmacology,2012
+f9f08511f77c29ff948e146434dfb23608d3deb5,Question Answering Using Match-LSTM and Answer Pointer,,2017
+f942739b7f9bc3c0b84f760bb2fd4895e1363ec0,Students Wearing Police Uniforms Exhibit Biased Attention toward Individuals Wearing Hoodies,,2017
+f9028b47a4755a7349108b1dc281f13add5c6c12,Atypical gaze patterns in children and adults with autism spectrum disorders dissociated from developmental changes in gaze behaviour,,2010
+f91388f87e10674226f4def4cda411adc01da496,Failure to Affect Decision Criteria During Recognition Memory With Continuous Theta Burst Stimulation,,2018
f935225e7811858fe9ef6b5fd3fdd59aec9abd1a,Spatiotemporal dynamics and connectivity pattern differences between centrally and peripherally presented faces.,NeuroImage,2006
+f9b90d3c1e2c3d0f3d9a94e6a0aea5e3047bca78,Analysis of photometric factors based on photometric linearization.,"Journal of the Optical Society of America. A, Optics, image science, and vision",2007
f93606d362fcbe62550d0bf1b3edeb7be684b000,Nearest Neighbor Classifier Based on Nearest Feature Decisions,Comput. J.,2012
+f006161327d3ea3484064c1a86e4c87c729fd7b8,Rough Sets Methods in Feature Reduction and Classification,,2001
f0f501e1e8726148d18e70c8e9f6feea9360d119,Jukka Komulainen SOFTWARE - BASED COUNTERMEASURES TO 2 D FACIAL,,2015
+f76a04bdc43f1e440b274b299b07ce2e423431e6,Face Recognition from Video: a Review,IJPRAI,2012
f78fe101b21be36e98cd3da010051bb9b9829a1e,Unsupervised Domain Adaptation for Facial Expression Recognition Using Generative Adversarial Networks,,2018
f79c97e7c3f9a98cf6f4a5d2431f149ffacae48f,Title On color texture normalization for active appearance models,Unknown,2017
+f76808d6811cb3790e7fc3ddb08c733febbdefba,Robust Object Categorization and Segmentation Motivated by Visual Contexts in the Human Visual System,EURASIP J. Adv. Sig. Proc.,2011
+e8304700fd89461ec9ecf471179ad87f08f3c2f7,Chapter 1 . Learning to Learn New Models of Human Activities in Indoor Settings (,,2013
e8fdacbd708feb60fd6e7843b048bf3c4387c6db,Deep Learning,Unknown,2014
+e810ddd9642db98492bd6a28b08a8655396c1555,Facing facts: neuronal mechanisms of face perception.,Acta neurobiologiae experimentalis,2008
+e8dda897372e6b4cf903234c7a9c40117711d8d8,What do you think of my picture? Investigating factors of influence in profile images context perception,Unknown,2015
e8c6c3fc9b52dffb15fe115702c6f159d955d308,Linear Subspace Learning for Facial Expression Analysis,Unknown,2012
+e8867f819f39c1838bba7d446934258035d4101c,Face recognition performance with superresolution.,Applied optics,2012
fab83bf8d7cab8fe069796b33d2a6bd70c8cefc6,Draft: Evaluation Guidelines for Gender Classification and Age Estimation,,2011
faeefc5da67421ecd71d400f1505cfacb990119c,PastVision+: Thermovisual Inference of Recent Medicine Intake by Detecting Heated Objects and Cooled Lips,Front. Robotics and AI,2017
fa08a4da5f2fa39632d90ce3a2e1688d147ece61,Supplementary material for “ Unsupervised Creation of Parameterized Avatars ” 1 Summary of Notations,,
+fab04dfcb35a29a46504d2ad3acbc642c602c7e8,Trajectory-based 3 D Convolutional Descriptors for Action Recognition in Videos,Unknown,2018
+faf40ce28857aedf183e193486f5b4b0a8c478a2,Automated Human Identification Using Ear Imaging,Unknown,2015
fac8cff9052fc5fab7d5ef114d1342daba5e4b82,Modeling Phase Spectra Using Gaussian Mixture Models for Human Face Identification,Unknown,2005
+fa5aca45965e312362d2d75a69312a0678fdf5d7,Fast and Accurate Head Pose Estimation via Random Projection Forests: Supplementary Material,,2015
+fa4e709a7008248869584feca81250a8da8291e4,Biometric Quantization through Detection Rate Optimized Bit Allocation,EURASIP J. Adv. Sig. Proc.,2009
+fac0151ed0494caf10c7d778059f176ba374e29c,Recognising Complex Mental States from Naturalistic Human-Computer Interactions,Unknown,2014
+fff32fd598e41ec6dd6903082d77f43f16908cfd,Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition,EURASIP J. Adv. Sig. Proc.,2008
+ff2e25cb67209de8ae922abdfc31f922b130276e,Information Granulation and Pattern Recognition,,2004
+ff70cfaf3e085a6c32bfa7ebedb98adfb7658210,TABULA RASA Trusted Biometrics under Spoofing Attacks,,2011
ff9195f99a1a28ced431362f5363c9a5da47a37b,Serial dependence in the perception of attractiveness,,2016
+ff825a46f0a4e9f6ad748aeefd18f34f6b4addfb,"The ""reading the mind in films"" task: complex emotion recognition in adults with and without autism spectrum conditions.",Social neuroscience,2006
+c51fbd2574e488e486483e39702a3d7754cc769b,Face Recognition from Still Images to Video Sequences: A Local-Feature-Based Framework,EURASIP J. Image and Video Processing,2011
+c28745625f048d86f2ad0f38a41ddc0683d36a96,"Looking, seeing and believing in autism: Eye movements reveal how subtle cognitive processing differences impact in the social domain.",Autism research : official journal of the International Society for Autism Research,2016
+c2adfc55e0ab9be6e8f5e4ebeb20770dca307cef,"The effect of diagnosis, age, and symptom severity on cortical surface area in the cingulate cortex and insula in autism spectrum disorders.",Journal of child neurology,2013
+c2d065bc8067384c40b3e8146cadc9a0c4c1d633,SLC25A12 expression is associated with neurite outgrowth and is upregulated in the prefrontal cortex of autistic subjects,Molecular Psychiatry,2008
+c2c058afe227f2099aae4f204688b22239d6837a,Threatening faces fail to guide attention for adults with autistic-like traits.,Autism research : official journal of the International Society for Autism Research,2017
+c223b2b7d38dc4e0ad418c404b2d3c43c62213bc,Trade-off Between GPGPU based Implementations of Multi Object Tracking Particle Filter,Unknown,2017
+c2b1007824fa7ce3a7a94209f0be0902a3454bae,Project Description 1 Introduction,,
+c2eed73654b544a705b194ade58cd82488c6c5b9,"Scene Understanding by Labeling Pixels Key Insights ˽ Recent Progress on Image Understanding, a Long-standing Challenge of Ai, Is Enabling Numerous New Applications in Robot Perception, Surveillance and Environmental Monitoring, Content- Based Image Search, and Social-media Summarization",,2014
+f68263a6f541429a8645ca2f4b0658cdbbd66638,Setting a world record in 3D Face Recognition,,2015
+f663ad5467721159263c1cde261231312893f45d,UvA-DARE ( Digital Academic Repository ) Gaze Embeddings for Zero-Shot Image Classification,Unknown,
+f69a289a3bc6b61c612ba6ff4033f122100daccb,Morphing between expressions dissociates continuous from categorical representations of facial expression in the human brain.,Proceedings of the National Academy of Sciences of the United States of America,2012
f66f3d1e6e33cb9e9b3315d3374cd5f121144213,Top-down control of visual responses to fear by the amygdala.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2013
+f6c7f1cbfa412fb6244992b7fb2eda0a9e0d933e,Expertise Moderates Incidentally Learned Associations Between Words and Images,,2018
+f6328f02ab64c992d76967dbfd1a66d325173723,Mel- and Mellin-cepstral Feature Extraction Algorithms for Face Recognition,Comput. J.,2011
+f6f12e0fbfce067d02445abde76be0522e4db329,Online Multiple targets Detection and Tracking from Mobile robot in Cluttered indoor Environments with Depth Camera,IJPRAI,2014
f68f20868a6c46c2150ca70f412dc4b53e6a03c2,Differential Evolution to Optimize Hidden Markov Models Training: Application to Facial Expression Recognition,CIT,2015
+e97d824b8e80670d49d53c402f99e0fbeaafacdb,Neural Best-Buddies: Sparse Cross-Domain Correspondence,ACM Trans. Graph.,2018
+e9ccd438d6d55ba0d11a63eb95c773d63b3ea4e5,Will you remember me ? Cultural differences in own-group face recognition biases ☆,Unknown,2016
+e9e39e31419d9a22790b327bc1d6107fa832bdab,Face recognition using adaptively weighted patch PZM array from a single exemplar image per person,Pattern Recognition,2008
+e9bbe558c73de60e40ce2bd8c7cb7a47dacfe594,Can White children grow up to be Black? Children's reasoning about the stability of emotion and race.,Developmental psychology,2016
+e93a65ff1c7c29736cef5701f079f75ecfb76f5f,From image statistics to scene gist: evoked neural activity reveals transition from low-level natural image structure to scene category.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2013
+f193ca76a878af87603ae8ac823a3e6d1c2e3c7e,Recurrent Multi-frame Single Shot Detector for Video Object Detection,Unknown,2018
+f179f7888934b11dc5a2d8ff9205d1ca8b8a1599,Illuminant direction estimation for a single image based on local region complexity analysis and average gray value.,Applied optics,2014
+f153cbec29d86a58b5f15231fd14e7037a210682,Lost in the categorical shuffle: evidence for the social non-prototypicality of black women.,Cultural diversity & ethnic minority psychology,2014
+f16921c1c6e8bce89bce7679cbd824d65b494e4d,The face of love: spontaneous accommodation as social emotion regulation.,Personality & social psychology bulletin,2011
+e7f00f6e5994c5177ec114ee353cc7064d40a78f,Back to Basic: Do Children with Autism Spontaneously Look at Screen Displaying a Face or an Object?,,2013
e726174d516605f80ff359e71f68b6e8e6ec6d5d,3D Face Recognition Using Patched Locality Preserving Projections,J. Inf. Sci. Eng.,2010
e78394213ae07b682ce40dc600352f674aa4cb05,Expression-invariant three-dimensional face recognition,,2005
+e7f4951c1106bff0460665ef67d11fb9c2d07c41,Machine Vision-Based Analysis of Gaze and Visual Context: an Application to Visual Behavior of Children with Autism Spectrum Disorders,,2011
+e7a922049a9bf54a0b13cd1d475a58e36c7c9b3e,The conceptual structure of face impressions.,Proceedings of the National Academy of Sciences of the United States of America,2018
+cb4fc4d49783f2049c48a062169f04eb744443ec,Paying More Attention to Saliency: Image Captioning with Saliency and Context Attention,TOMCCAP,2018
+cb1e34d7fcb7fae914fcb65cb9cf25199d49cec9,SLAQ: quality-driven scheduling for distributed machine learning,Unknown,2017
+cb310356d1c5f567b2a8796b708f6e1e10fa1917,Serotonin and the neural processing of facial emotions in adults with autism: an fMRI study using acute tryptophan depletion.,Archives of general psychiatry,2012
+cb3ba84146d1324e1cdbde3764ca3b354ee09a2a,"On the Interplay Between Throughput, Fairness and Energy Efficiency on Asymmetric Multicore Processors",Comput. J.,2018
+cb2e10d1a6792354bc0ce24ee99ecf2142d16f9b,Enhancing Real-Time Human Detection Based on Histograms of Oriented Gradients,,2008
+f8eedcca6263062b6bab11ead255f719452f1c81,Motion in action : optical flow estimation and action localization in videos. (Le mouvement en action : estimation du flot optique et localisation d'actions dans les vidéos),Unknown,2016
+f8b26b2ec62cf76f58f95938233bc22ae1902144,UvA-DARE ( Digital Academic Repository ) Visual Tracking : An Experimental Survey Smeulders,Unknown,2018
f8a5bc2bd26790d474a1f6cc246b2ba0bcde9464,"KDEF-PT: Valence, Emotional Intensity, Familiarity and Attractiveness Ratings of Angry, Neutral, and Happy Faces",,2017
+f89e5b1f61b221c7b00db55b64239a28f8ba9fe0,Ensemble Learning-Based Person Re-identification with Multiple Feature Representations,Complexity,2018
+ce57cc478421adf85a9058a0cc8fad8ebfd81c52,Multimodal Attribute Extraction,CoRR,2017
cefd9936e91885ba7af9364d50470f6cb54315a4,Expectation and surprise determine neural population responses in the ventral visual stream.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2010
+ceca60c4bf1a5c4e5893ae6685e7a9f80ca47f27,Visual Question: Predicting If a Crowd Will Agree on the Answer,CoRR,2016
+ceb4040acf7f27b4ca55da61651a14e3a1ef26a8,Angry Crowds: Detecting Violent Events in Videos,Unknown,2016
+ced73382d686dee6232c313f014bc21ca7536db0,Detection of Tongue Protrusion Gestures from Video,IEICE Transactions,2011
+ce83369da319607fe2832485913b0f30c00920aa,Human Detection Based on Large Feature Sets Using Graphics Processing Units,Informatica (Slovenia),2011
e03bda45248b4169e2a20cb9124ae60440cad2de,"Learning a Dictionary of Shape-Components in Visual Cortex : Comparison with Neurons , Humans and Machines by Thomas Serre",Unknown,2006
e0dedb6fc4d370f4399bf7d67e234dc44deb4333,Supplementary Material: Multi-Task Video Captioning with Video and Entailment Generation,,2017
+e043d79f4dc41c9decaf637d8ffdd11f8ed59f2b,Distance metric learning for image and webpage comparison. (Apprentissage de distance pour la comparaison d'images et de pages Web),Unknown,2015
+e030697c19dd1919dbdd889b69df7ab002a8af19,The expectancy bias : Expectancy-violating faces evoke earlier pupillary dilation than neutral or negative faces,Unknown,2017
+e042c4d038373a68cca109336598c0323e7a9b60,Culture moderates the relationship between interdependence and face recognition,,2015
+e096db52fc8316e66273b456c58b073f9b689074,Harnessing Repetitive Behaviours to Engage Attention and Learning in a Novel Therapy for Autism: An Exploratory Analysis,,2012
e00d391d7943561f5c7b772ab68e2bb6a85e64c4,Robust continuous clustering.,Proceedings of the National Academy of Sciences of the United States of America,2017
e0244a8356b57a5721c101ead351924bcfb2eef4,Power as an emotional liability: Implications for perceived authenticity and trust after a transgression.,Journal of experimental psychology. General,2017
+e059650472dd7bfd6907b02de491e312a0cb6d4e,Parallel Genetic Algorithms and Machine Learning,,1996
+e0515dc0157a89de48e1120662afdd7fe606b544,Perception Science in the Age of Deep Neural Networks,,2017
+46d7f41189c5e262df9ad1165d5a40d2b685bb0f,Discriminative Multiple Target Tracking,,2010
+46a01565e6afe7c074affb752e7069ee3bf2e4ef,Local Descriptors Encoded by Fisher Vectors for Person Re-identification,,2012
+46282f10271875647219b641dac2cc01c7dc8ab2,Psychopathic traits are associated with reduced fixations to the eye region of fearful faces.,Journal of abnormal psychology,2018
+46b031a3e368f25dd1e42f70f21165fef7b16de2,"Faces in the mirror, from the neuroscience of mimicry to the emergence of mentalizing.",Journal of anthropological sciences = Rivista di antropologia : JASS,2016
+46c3e8c2b2042b193659c0a613adc72100a2f301,Vision for Robotics By Danica Kragic and Markus Vincze,,2009
+4679f4a7da1cf45323c1c458b30d95dbed9c8896,Recognizing Facial Expressions Using Model-Based Image Interpretation,Unknown,2008
+2cdb8df791cb15eef805443293319ec8690ff88f,An Effective Approach to Pose Invariant 3D Face Recognition,,2011
2cc4ae2e864321cdab13c90144d4810464b24275,Face Recognition Using Optimized 3D Information from Stereo Images,,2005
2c883977e4292806739041cf8409b2f6df171aee,Are Haar-Like Rectangular Features for Biometric Recognition Reducible?,,2013
2cdd9e445e7259117b995516025fcfc02fa7eebb,Temporal Exemplar-Based Bayesian Networks for Facial Expression Recognition,2008 Seventh International Conference on Machine Learning and Applications,2008
+2c07d9a383e0bb7e1c8ba07084ba8bcf71af2aad,Robust Ear Recognition via Nonnegative Sparse Representation of Gabor Orientation Information,,2014
2cac70f9c8140a12b6a55cef834a3d7504200b62,Reconstructing High Quality Face-Surfaces using Model Based Stereo,2007 IEEE 11th International Conference on Computer Vision,2007
+2c7946d5d2f1572c20e9843eb2033b8eb9771bf3,THEORETICAL REVIEW Mechanisms for Widespread Hippocampal Involvement in Cognition,,2013
+2c7934a2f1671286370cd9adebc2872c6dd318f5,Visual Scene Understanding through Semantic Segmentation,,2015
+794f76c111ba1a4ca718e84ae74ee8d2a67c4173,Ventromedial prefrontal cortex mediates visual attention during facial emotion recognition.,Brain : a journal of neurology,2014
+79a36b19ea363c14af27a1f4112a9eccdd582837,The scope of social attention deficits in autism: prioritized orienting to people and animals in static natural scenes.,Neuropsychologia,2010
+793e896c2f66fb66bfc6c834f2678cf349af4e20,Incorporating Computation Time Measures During Heterogeneous Features Selection in a Boosted Cascade People Detector,IJPRAI,2016
+79335495e54446541a3655d145911beba7c29d7d,The face inversion effect in opponent-stimulus rivalry,,2014
2dced31a14401d465cd115902bf8f508d79de076,Can a Humanoid Face be Expressive? A Psychophysiological Investigation,,2015
2dfe0e7e81f65716b09c590652a4dd8452c10294,Incongruence Between Observers’ and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli,,2018
2dd5f1d69e0e8a95a10f3f07f2c0c7fa172994b3,Machine Analysis of Facial Expressions,,2007
+2dc7d439e99f15a499cd2dcbdfbc1c0c7648964d,Computational Understanding of Image Memorability by Zoya Bylinskii,Unknown,2015
+2d6d4899c892346a9bc8902481212d7553f1bda4,Neural Face Editing with Intrinsic Image Disentangling SUPPLEMENTARY MATERIAL,,2017
+4129e1075c7856d8bebbf0655ae00a4843109429,A Tale of Two Losses : Discriminative Deep Feature Learning for Person Re-Identification,Unknown,2017
+41ddd29d9e56bb87b9f988afc75cd597657b2600,R4-A.3: Human Detection & Re-Identification for Mass Transit Environments,,2017
+413160257096b9efcd26d8de0d1fa53133b57a3d,Customer satisfaction measuring based on the most significant facial emotion,Unknown,2018
+412b3ef02c85087e5f1721176114672c722b17a4,A Taxonomy of Deep Convolutional Neural Nets for Computer Vision,Front. Robotics and AI,2016
+41ed93fd97aa76b4abfda7a09168ad1799f34664,Video Event Detection: From Subvolume Localization to Spatiotemporal Path Search,IEEE Transactions on Pattern Analysis and Machine Intelligence,2013
+41612c66beaad320af9b7d34407c7d0f4ca7bfea,Inhibition or Ideology ? The Neural Mechanisms of Evaluating Race-Targeted Government Assistance,Unknown,2017
+41e1084e74564ced3e1fa845250162d6d0f2b9c3,A Texture-based Approach to Face Detection,,2004
+41fafb5392ad5e33e5169d870812ab5edca301a1,Tree-Structured Stick Breaking Processes for Hierarchical Data,Unknown,2010
+4189862b2ce9c71e1b451deb58dd42f50c7d04a1,Autistic trait interactions underlie sex-dependent facial recognition abilities in the normal population,,2013
+41c87d3342a85712a3591b6d49d99be8fc8d35d9,Face-trait inferences show robust child – adult agreement : Evidence from three types of faces,Unknown,2015
+4156f9fc5983b09eb97ad3d9abc248b15440b955,"2 Subspace Methods for Face Recognition : Singularity , Regularization , and Robustness",,2012
83fd2d2d5ad6e4e153672c9b6d1a3785f754b60e,Quantifying naturalistic social gaze in fragile X syndrome using a novel eye tracking paradigm.,"American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics",2015
+8387c58a5a3fd847f9b03760842dd49fec7cbb0e,Two-year-olds with autism orient to nonsocial contingencies rather than biological motion,,2009
831226405bb255527e9127b84e8eaedd7eb8e9f9,A Motion-Based Feature for Event-Based Pattern Recognition,,2016
+832aae00e16c647716f1be38de233c9c15af9a28,Feature fusion for facial landmark detection,Pattern Recognition,2014
+83e7c51c4d6f04049f5a3dbf4ac9e129ed96caee,Spatio-temporal Pain Recognition in CNN-Based Super-Resolved Facial Images,Unknown,2016
+83b700f0777a408eb36eef4b1660beb3f6dc1982,Violent behaviour detection using local trajectory response,,2016
1b02b9413b730b96b91d16dcd61b2420aef97414,Détection de marqueurs affectifs et attentionnels de personnes âgées en interaction avec un robot. (Audio-visual detection of emotional (laugh and smile) and attentional markers for elderly people in social interaction with a robot),Unknown,2015
+1bb14ddc0326a8e5b44eafd915738c2b1342f392,Title On color texture normalization for active appearance models,Unknown,2017
1b6394178dbc31d0867f0b44686d224a19d61cf4,EPML: Expanded Parts Based Metric Learning for Occlusion Robust Face Verification,,2014
1bbec7190ac3ba34ca91d28f145e356a11418b67,Explorer Action Recognition with Dynamic Image Networks,Unknown,2017
+1be9ee50f4d4f59b9761a366bba9127213dc4f33,You cannot gamble on others: Dissociable systems for strategic uncertainty and risk in the brain,,2013
+1b2ad281ef74e366ec58221b13edc6eefdb170f8,Use and Usefulness of Dynamic Face Stimuli for Face Perception Studies—a Review of Behavioral Findings and Methodology,,2018
+1bca1a09e2ef62b1960c23ff6653ae2d5aef5718,Comparison of human face matching behavior and computational image similarity measure,Science in China Series F: Information Sciences,2009
+771431afa9b5c936dc970db8d02ae06f49d68638,TabletGaze : Dataset and Algorithm for Unconstrained Appearance-based Gaze Estimation in Mobile Tablets,Unknown,2015
+77dc158a979731d2ed01145b1d3ead34a6c33487,Preference for geometric patterns early in life as a risk factor for autism.,Archives of general psychiatry,2011
+77052654a37b88719c014c5afd3db89cb2288aeb,Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features,,2015
77d31d2ec25df44781d999d6ff980183093fb3de,The Multiverse Loss for Robust Transfer Learning,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
+77d4843a177031b2b5721824280033e2e601334c,Comparative Evaluation of 3D versus 2D Modality for Automatic Detection of Facial Action Units,,2011
+48b4f49ec708677fc9f70edc74fd0f92ef986406,CS168: The Modern Algorithmic Toolbox Lecture #6: Stochastic Gradient Descent and Regularization,,2016
48a5b6ee60475b18411a910c6084b3a32147b8cd,Pedestrian Attribute Recognition with Part-based CNN and Combined Feature Representations,Unknown,2018
+482e8a9323fca1e27fccf03d2a58a36873d0ae10,Assessing Social Cognition of Persons with Schizophrenia in a Chinese Population: A Pilot Study,,2017
+48cdb6a640b4259c61c476fb529d7c176e8345a9,Eyelid-openness and mouth curvature influence perceived intelligence beyond attractiveness.,Journal of experimental psychology. General,2016
+4813d9332a1f3ef2bf5846e81005895322310bed,3D Face Recognition,,2007
48319e611f0daaa758ed5dcf5a6496b4c6ef45f2,Non Binary Local Gradient Contours for Face Recognition,CoRR,2014
+70990e1b13cec2b3e4831a00c6ac901dae76b27a,"Mareckova , Klara ( 2013 ) Sex differences and the role of sex hormones in face development and face processing",Unknown,2016
+7031d7fde9f184b72416759f8a9be4155616f456,Benchmarking Face Detection in a Mobile/Tablet Environment,,2011
+70b42bbd76e6312d39ea06b8a0c24beb4a93e022,Solving Multiple People Tracking in a Minimum Cost Arborescence,2015 IEEE Winter Applications and Computer Vision Workshops,2015
+1e2087908e6ce34032c821c7fb6629f2d0733086,Affective Embodied Conversational Agents for Natural Interaction,Unknown,2008
+1e3a9b0cfdeca614c5689a3419016c89bf9fbdfa,Facial color is an efficient mechanism to visually transmit emotion,,2018
1ecb56e7c06a380b3ce582af3a629f6ef0104457,"A New Way of Discovery of Belief, Desire and Intention in the BDI Agent-Based Software Modeling",JACIII,2004
1ee27c66fabde8ffe90bd2f4ccee5835f8dedbb9,9 Entropy Regularization,,
+1e0dd12f2bff234a4df71641bc95068733506858,Handwritten Word Spotting with Corrected Attributes,2013 IEEE International Conference on Computer Vision,2013
+84fd7c00243dc4f0df8ab1a8c497313ca4f8bd7b,Perceived Age Estimation from Face Images,Unknown,2018
+84d665608c7c005d38290df392b0ba0157ba32ee,Social Cognitive Training Improves Emotional Processing and Reduces Aggressive Attitudes in Ex-combatants,,2017
+84efa16406c8838550cbbed48f0355b936bbe845,Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking,,2016
+4af997701ce14ba689f7f964a72bcae0a2432435,The role of gaze direction in face memory in autism spectrum disorder.,Autism research : official journal of the International Society for Autism Research,2013
+4a8085987032e85ac8017d9977a4b76b0d8fa4ac,Object Recognition using Template Matching,,2008
+4ad51a99e489939755f1d4f5d1f5bc509c49e96d,Preferences for facially communicated big five personality traits and their relation to self-reported big five personality,Unknown,2018
+4a9086cf2637b7ea54855187b978af7a89bfceff,Atypical neural specialization for social percepts in autism spectrum disorder.,Social neuroscience,2011
+24b6d839662e5d56f17fc26eab4d2901f6835ddf,Real Time Lip Motion Analysis for a Person Authentication System using Near Infrared Illumination,2006 International Conference on Image Processing,2006
+247df1d4fca00bc68e64af338b84baaecc34690b,Evaluation of Gender Classification Methods with Automatically Detected and Aligned Faces,IEEE Transactions on Pattern Analysis and Machine Intelligence,2008
+2475ad865b2102cef83a87adfe0d2e71d4791e53,A Supervised Clustering Algorithm for the Initialization of RBF Neural Network Classifiers,2007 IEEE 15th Signal Processing and Communications Applications,2007
+248291285074203eb9ee8e0b8b517ac4ce7dc4aa,The Way Dogs (Canis familiaris) Look at Human Emotional Faces Is Modulated by Oxytocin. An Eye-Tracking Study,,2017
+24585f90bdf30583733841f70430d36948f16ae2,An efficient method for human face recognition using nonsubsampled contourlet transform and support vector machine,,2009
+231e545fdb1a516e29604fbd740e207b6f25c7dc,Perception of dynamic changes in facial affect and identity in autism.,Social cognitive and affective neuroscience,2007
+23fc6c6e1cd52a77215a285a462840cbb96aec39,"Cortical patterns of category-selective activation for faces, places and objects in adults with autism.",Autism research : official journal of the International Society for Autism Research,2008
23ba9e462151a4bf9dfc3be5d8b12dbcfb7fe4c3,Determining Mood from Facial Expressions,,2014
+23ca7c4367f7317c61ebb0574e3d04cfd9bc3893,Aberrant brain activation during gaze processing in boys with fragile X syndrome.,Archives of general psychiatry,2008
+2312bc2d48a0f68bd5ab1b024d5726786455da3a,Learning Deep Context-Aware Features over Body and Latent Parts for Person Re-identification,2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017
+23b93f3b237481bd1d36941ca3312bb16f4beb58,Reconnaissance d'événements et d'actions à partir de la profondeur thermique 3D. (Event and action recognition from thermal and 3D depth Sensing),Unknown,2016
23120f9b39e59bbac4438bf4a8a7889431ae8adb,Improved RGB-D-T based face recognition,IET Biometrics,2016
-23dd8d17ce09c22d367e4d62c1ccf507bcbc64da,Deep Density Clustering of Unconstrained Faces (Supplementary Material),Unknown,2018
+23dd8d17ce09c22d367e4d62c1ccf507bcbc64da,Deep Density Clustering of Unconstrained Faces ( Supplementary Material ),Unknown,2018
+4f922f6602f39baae94f63954005776e1da05671,Peer-Mediated Theatrical Engagement for Improving Reciprocal Social Interaction in Autism Spectrum Disorder,,2014
+4f8bd3519a6e8a05db9e35b027c0c65c91d2ff62,Brain Oxytocin is a Main Regulator of Prosocial Behaviour - Link to Psychopathology,Unknown,2018
+4f1a74cfa7c8383a5dea97cb48c197da5b4f5ee0,LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images,NeuroImage,2014
+4f15b1e750007465024181dd002dfc6d1baa48c9,Face Recognition and Computer Graphics for Modelling,,2014
+4fde52cd3af5c698f0807bc3b821ebb3a270a986,Impaired fixation to eyes during facial emotion labelling in children with bipolar disorder or severe mood dysregulation.,Journal of psychiatry & neuroscience : JPN,2013
+8d6344658fa9673b1f4ac0d0bad53617ee127aaa,Adolescent and adult risk-taking in virtual social contexts,,2014
8de2dbe2b03be8a99628ffa000ac78f8b66a1028,Action Recognition in Videos,,2008
8d3fbdb9783716c1832a0b7ab1da6390c2869c14,Discriminant Subspace Analysis for Uncertain Situation in Facial Recognition,,2008
+8d09c8c6b636ef70633a3f1bb8ff6b4d4136b5cf,3D Twins Expression Challenge,,2011
8d6c4af9d4c01ff47fe0be48155174158a9a5e08,"Labeling, discovering, and detecting objects in images",,2008
+8df05de407b829abb357e230bead5407cabe7305,U Can Touch This: How Tablets Can Be Used to Study Cognitive Development,,2016
+8d007d8d75cb84e3350889ad5e1cc6520688e65e,Optimizing Nondecomposable Loss Functions in Structured Prediction,IEEE Transactions on Pattern Analysis and Machine Intelligence,2013
8dffbb6d75877d7d9b4dcde7665888b5675deee1,Emotion Recognition with Deep-Belief Networks,,2010
15affdcef4bb9d78b2d3de23c9459ee5b7a43fcb,Semi-Supervised Classification Using Linear Neighborhood Propagation,2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06),2006
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+1582c29d0f752f95a12f5a8ce08d5e5c752f6822,Developmental changes in infants' categorization of anger and disgust facial expressions.,Developmental psychology,2017
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+120b22e7a47923e42a123b9b68a93ccac5aaea6d,Paper on Ear Biometric Authentication,Unknown,2016
+1297ee7a41aa4e8499c7ddb3b1fed783eba19056,Effects of emotional expressions on persuasion,Unknown,2016
124538b3db791e30e1b62f81d4101be435ee12ef,"Basic level scene understanding: categories, attributes and structures",,2013
+8ca0a7f2e5a7b1676f9a409c3ed5749c8a569b83,A new approach for pedestrian density estimation using moving sensors and computer vision,Unknown,2018
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+8c244417db2082f4d5897548e72ef304ae886e52,Tree Based Space Partition of Trajectory Pattern Mining For Frequent Item Sets,,2016
8c6b9c9c26ead75ce549a57c4fd0a12b46142848,Facial expression recognition using shape and texture information,,2006
+8c5dcd5a0b3c9940e544993327eab6425ce645d5,nsemble perception of emotions in autistic and typical children and dolescents,Unknown,2017
+850d84e4c73a8f0762c8c798b2b7fd6f2787263a,The Discovery of Perceptual Structure from Visual Co - occurrences in Space and Time,,2016
+852bdbcd091f48e07e9b989cb326e631e2932d7f,Visual scanning patterns and executive function in relation to facial emotion recognition in aging.,"Neuropsychology, development, and cognition. Section B, Aging, neuropsychology and cognition",2013
+85476331edc9a9e3393f736f14aa80ad95f3c105,"""Wealth Makes Many Friends"": Children Expect More Giving From Resource-Rich Than Resource-Poor Individuals.",Child development,2017
+1d187e1d0e9eb874f85e3ecdb75ca0a7bd98d8bc,Aggression in young children with concurrent callous–unemotional traits: can the neurosciences,,2008
+1d0a6759de0d55d15439b0367f0aa49c1e248c5c,"Networking in Autism: Leveraging Genetic, Biomarker and Model System Findings in the Search for New Treatments",Neuropsychopharmacology,2012
+1d9497450f60b874eb6ecbf82e3d0808a6fe236c,Nonconvex proximal splitting with computational errors∗,,2016
+1df1aa9179506554744bf16b238d05ebd1e2d4d5,Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.,Journal of vision,2013
+1dea4f56c04d12abbc9e1ed7c48c7ccc09e7f5bb,How magic changes our expectations about autism.,Psychological science,2010
1dff919e51c262c22630955972968f38ba385d8a,Toward an Affect-Sensitive Multimodal Human–Computer Interaction,,2001
+1dc07322715e093c560b30fdf1e168e58e9a9409,DRBF and IRBF Based Face Recognition and Extraction of Facial Expressions from the Blur Image,,2014
1dacc2f4890431d867a038fd81c111d639cf4d7e,Using social outcomes to inform decision-making in schizophrenia: Relationships with symptoms and functioning.,Journal of abnormal psychology,2016
1d729693a888a460ee855040f62bdde39ae273af,Photorealistic Face De-Identification by Aggregating Donors' Face Components,Unknown,2014
71b07c537a9e188b850192131bfe31ef206a39a0,300 Faces In-The-Wild Challenge: database and results,Image Vision Comput.,2016
+71559cae0bc89398e75a2f24674d61cb51909390,Relighting Humans : Occlusion-Aware Inverse Rendering for Full-Body Human Images,Unknown,2018
+71f1e72670e676b6902cce0d6fc0b4f63b46ca28,Survey paper: Face Detection and Face Recognition,,2004
+710ce8cf25f31df8547b888519b414187e989257,Amygdala activation predicts gaze toward fearful eyes.,The Journal of neuroscience : the official journal of the Society for Neuroscience,2009
+71cbe1b52e2fdb8fa8a8278eb590f8065d3e7fcb,’ Actions dans des Vidéos Réalistes Structured Models for Action Recognition in Real-world Videos,Unknown,2012
+767936728b07238bbf38661fc3c2000d0c17b598,An Own-Age Bias in Recognizing Faces with Horizontal Information,,2016
+76b6577f47d6782bf75aca04e361a7b7381b4a84,Measuring and Modifying the Intrinsic Memorability of Images,,2015
76ce3d35d9370f0e2e27cfd29ea0941f1462895f,Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU,,2014
+7606a74de57f67257c77a8bb0295ff4593566040,Content-based Image Retrieval Using Constrained Independent Component Analysis : Facial Image Retrieval Based on Compound Queries,Unknown,2012
760ba44792a383acd9ca8bef45765d11c55b48d4,Class-specific classifier: avoiding the curse of dimensionality,IEEE Aerospace and Electronic Systems Magazine,2004
+1ca9ab2c1b5e8521cba20f78dcf1895b3e1c36ac,"Explorer "" Here ' s looking at you , kid",,2017
1ce4587e27e2cf8ba5947d3be7a37b4d1317fbee,Deep fusion of visual signatures for client-server facial analysis,,2016
1c4ceae745fe812d8251fda7aad03210448ae25e,Optimization of Color Conversion for Face Recognition,EURASIP J. Adv. Sig. Proc.,2004
1cee993dc42626caf5dbc26c0a7790ca6571d01a,Optimal illumination for image and video relighting,,2005
+1c51aeece7a3c30302ebd83bdcaa65df0bfc48fe,Unsupervised Video Indexing based on Audiovisual Characterization of Persons. (Indexation vidéo non-supervisée basée sur la caractérisation des personnes),,2010
+1c7a050394371bcb064868dfe681ff4c29ce2101,Expressive Models and Comprehensive Benchmark for 2D Human Pose Estimation,,2014
+1ca40e1d0ae377296ac6804c81c1e5bcbc5475c8,RVM-Based Human Action Classification in Crowd through Projection and Star Skeletonization,EURASIP J. Image and Video Processing,2009
+1c0e8c3fb143eb5eb5af3026eae7257255fcf814,Weakly Supervised Deep Detection Networks,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
+8239e4a37825979f66ff0419ccd50a08aebfbadf,Tracing the Colors of Clothing in Paintings with Image Analysis,,2016
+82a922e775ec3a83d2d5637030860f587697ae42,Dense Multiperson Tracking with Robust Hierarchical Linear Assignment,IEEE Transactions on Cybernetics,2015
82d781b7b6b7c8c992e0cb13f7ec3989c8eafb3d,Robust Facial Expression Recognition Using a State-based Model of Spatially-localized Facial,,
+49a038852b9e51af658405231045559d728e0970,DeepCache: Principled Cache for Mobile Deep Vision,Unknown,2018
+40757d94d6ef33555fc940d556ebfb0d32410fbb,Warmth and competence in your face! Visual encoding of stereotype content,,2013
+4091b6a3ab33e2aa923ee23c8db7e33d167ff67a,Transductive Multi-class and Multi-label Zero-shot Learning,CoRR,2014
40389b941a6901c190fb74e95dc170166fd7639d,Automatic Facial Expression Recognition,,2014
+40377a1bc15a9ec28ea54cc53d5cf0699365634f,Некооперативная Биометрическая Идентификация По 3d- Моделям Лица С Использованием Видеокамер Высокого Разрешения,,
+40f2b3af6b55efae7992996bd0c474a9c1574008,xytocin Increases Retention of Social Cognition n Autism,,2006
+403e7fed4fa1785af8309b1c4c736d98fa75be5b,Social status gates social attention in monkeys,Current Biology,2006
+40f6c9355dbf01a240b4c26b0fd00b5cfbd5f67d,An eye-tracking method to reveal the link between gazing patterns and pragmatic abilities in high functioning autism spectrum disorders,,2014
2eb37a3f362cffdcf5882a94a20a1212dfed25d9,Local Feature Based Face Recognition,,2012
+2ea8029283e6bbb03c023070d042cb19647f06af,Neurobiological mechanisms associated with facial affect recognition deficits after traumatic brain injury,Brain Imaging and Behavior,2015
+2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e,3DPeS: 3D people dataset for surveillance and forensics,,2011
+2e708431df3e7a9585a338e1571f078ddbe93a71,Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification.,IEEE transactions on cybernetics,2017
+2ba64deeb3e170e4776e2d2704771019cf9c8639,Differences between Old and Young Adults’ Ability to Recognize Human Faces Underlie Processing of Horizontal Information,,2012
2b4d092d70efc13790d0c737c916b89952d4d8c7,Robust Facial Expression Recognition using Local Haar Mean Binary Pattern,,2017
+2b0e1a62d7168df5f29e2e9c7fc72ae43c39fdb2,Emotion expression modulates perception of animacy from faces,,2017
2b773fe8f0246536c9c40671dfa307e98bf365ad,Fast Discriminative Stochastic Neighbor Embedding Analysis,,2013
+2b73e3d541b0208ae54b3920fef4bfd9fd0c84a7,Feature-based face representations and image reconstruction from behavioral and neural data.,Proceedings of the National Academy of Sciences of the United States of America,2016
+2b8a61184b6423e3d5285803eb1908ff955db1a8,Processing and analysis of 2 . 5 D face models for non-rigid mapping based face recognition using differential geometry tools,Unknown,2012
+2b8667df1a0332386d8d799fbac0327496ce02c9,Stranger danger: Parenthood increases the envisioned bodily formidability of menacing men,,2014
+470b89e2c5248eb58e09129aa9b4d8bc77497e7e,Neurobiology of Disease Cortical Folding Abnormalities in Autism Revealed by Surface-Based Morphometry,,2007
+4780cece6d4adeb0b070fbefbd587b89f4acf3f7,Shared and idiosyncratic cortical activation patterns in autism revealed under continuous real-life viewing conditions.,Autism research : official journal of the International Society for Autism Research,2009
+47440f514318b438ebf04d9932f5dafdb488a536,Emotion Recognition from Facial Images Using Binary Face Relevance Maps,,2016
+784731961819abc5a5a199be1573abd828bd9af1,Recognizing Emily and Latisha: Inconsistent Effects of Name Stereotypicality on the Other-Race Effect,,2018
+789c76749a15614d97ac8f4ec18b3ce7d80a2d28,Explorer Multiplicative LSTM for sequence modelling,Unknown,2017
783f3fccde99931bb900dce91357a6268afecc52,Adapted Active Appearance Models,EURASIP J. Image and Video Processing,2009
+8bdbb685174d6023e63c55fdf9ad9b2ac78e79bd,Learning Human Poses from Actions-Supplementary Material,Unknown,2018
+8b0a4d41ee469547163ea154ad2b522d6d335671,The unique contributions of perceiver and target characteristics in person perception.,Journal of personality and social psychology,2017
+8b8b3375bc51ae357528a1f015c4d094418c9f71,"An Efficient Feature Extraction Method, Global Between Maximum and Local Within Minimum, and Its Applications",,2014
8bb21b1f8d6952d77cae95b4e0b8964c9e0201b0,Multimodal Interaction on a Social Robotic Platform,,2013
+8b5122ea59d8d7f70e344ffb2553537b5ad07dd5,Image Translation by Domain-Adversarial Training,,2018
+13f03aab62fc29748114a0219426613cf3ba76ae,MORPH-II: Feature Vector Documentation,Unknown,2018
+13ec6666b8b722ad9eb68a21a302e3f2f1ab4df7,Biometric Human Identification of Hand Geometry Features Using Discrete Wavelet Transform,,2011
132527383890565d18f1b7ad50d76dfad2f14972,Facial Expression Classification Using PCA and Hierarchical Radial Basis Function Network,J. Inf. Sci. Eng.,2006
1394ca71fc52db972366602a6643dc3e65ee8726,EmoReact: a multimodal approach and dataset for recognizing emotional responses in children,,2016
+138778d75fc4e2fd490897ac064b9ac84b6b9f04,Generation and visualization of emotional states in virtual characters,Journal of Visualization and Computer Animation,2008
+13e348264fe1077caa44e1b59c71e67a8e4b5ad9,Effect of Eyes Detection and Position Estimation Methods on the Accuracy of Comparative Testing of Face Detection Algorithms,,2011
+139ee1b1d98e7ac9d659a5d1bbe8c75588539b29,Identification of EFHC2 as a quantitative trait locus for fear recognition in Turner syndrome.,Human molecular genetics,2007
7f21a7441c6ded38008c1fd0b91bdd54425d3f80,Real Time System for Facial Analysis,CoRR,2018
+7f44f2d7b4a84b6d87dd6f7089ce3ee1e6359272,What's in the Chinese Babyface? Cultural Differences in Understanding the Babyface,,2016
+7f0fadae16cc74b6176ba940aa2f8b5a0a67e09e,An Expert Local Mesh Correlation Histograms for Biomedical Image Indexing and Retrieval,,2015
+7f3c6bf191a8633d10fad32e23fa06a3c925ffee,The benefits of simply observing: mindful attention modulates the link between motivation and behavior.,Journal of personality and social psychology,2015
7fc76446d2b11fc0479df6e285723ceb4244d4ef,Laplacian MinMax Discriminant Projection and its Applications,Journal of Research and Practice in Information Technology,2010
+7a2cee9a210e7b418fa6169f8cf027f7993a3ee5,LETTER TO THE EDITOR Spontaneous versus deliberate vicarious representations: different routes to empathy in psychopathy and autism,,2014
+7a72ac1c77110d03dc0482f2556e9bdb36582fcb,Following Gaze: Gaze-Following Behavior as a Window into Social Cognition,,2010
+7a00365f9c7bced9ce47246794932f60564cb662,Converging evidence of configural processing of faces in high-functioning adults with autism spectrum disorders,,2008
+143e3ec5a5a11547da2d77a17d0ca7b1940280b5,"People detection, tracking and re-identification through a video camera network. (Détection, suivi et ré-identification de personnes à travers un réseau de caméra vidéo)",Unknown,2013
+147e699946e8c54d2176b4d868db03dd1c7bdb8f,Emotion and False Memory,,2016
146bbf00298ee1caecde3d74e59a2b8773d2c0fc,University of Groningen 4 D Unconstrained Real - time Face Recognition Using a Commodity Depthh Camera,,2017
14e759cb019aaf812d6ac049fde54f40c4ed1468,Subspace Methods,,2014
14418ae9a6a8de2b428acb2c00064da129632f3e,Discovering the Spatial Extent of Relative Attributes,2015 IEEE International Conference on Computer Vision (ICCV),2015
+1412f4024babbc01b671f7ee4a22d86db1545268,Proximity and gaze influences facial temperature: a thermal infrared imaging study,,2014
8e33183a0ed7141aa4fa9d87ef3be334727c76c0,Robustness of Face Recognition to Image Manipulations,,2018
+8edb2219370a86c4277549813d36a6c139503fb4,Facial feature units’ localization using horizontal information of most significant bit planes,,2011
+8eb2e7c9017b4a110978a1bb504accbc7b9ba211,Marching into battle: synchronized walking diminishes the conceptualized formidability of an antagonist in men.,Biology letters,2014
+8e8c511ebc12a093d3f73a4717ec71c32e4dbd49,The use of visual information in the recognition of posed and spontaneous facial expressions.,Journal of vision,2018
+8e4ff1aa78f8997b683f873c46999f384db4de18,Renewing the respect for similarity,,2012
+8e88a97e09a853cf768ca1c732ba5f008fff77ca,Regularized Residual Quantization: a multi-layer sparse dictionary learning approach,CoRR,2017
+2258e01865367018ed6f4262c880df85b94959f8,Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics,EURASIP J. Image and Video Processing,2008
+2270c94d3f9d9451b3d337aa5ba2d5681cb98497,Evaluation of GIST descriptors for web-scale image search,,2009
+22f21d58c6aecdb4f57c50fa9eb4952643eec0e9,Domain Transfer Support Vector Ranking for Person Re-identification without Target Camera Label Information,2013 IEEE International Conference on Computer Vision,2013
+22532c6e38ded690dc1420f05c18e23f6f24804d,Chapter 5 Genetic & Evolutionary Biometrics,Unknown,2017
+2251a1efad0cef802fd64fc79cc1b7007b64f425,Estimating 3D Pose via Stochastic Search and Expectation Maximization,,2010
+2534997443c7e183c9f8e370ea1e82989ecc940d,Skeleton Search: Category-Specific Object Recognition and Segmentation Using a Skeletal Shape Model,International Journal of Computer Vision,2009
+25474c21613607f6bb7687a281d5f9d4ffa1f9f3,Recognizing disguised faces,,2012
+252e48be0fd63d3a786021efa8733f8891101a82,Unsupervised Feature Learning With Winner-Takes-All Based STDP,,2018
+253d2fd2891a97d4caa49d87094dac1ec18c7752,Bio-authentication for Layered Remote Health Monitor Framework,Unknown,2014
25e2d3122d4926edaab56a576925ae7a88d68a77,Communicative-Pragmatic Treatment in Schizophrenia: A Pilot Study,,2016
+257e008c01a32b9b642553f3f1e59e61efcac4a6,Gender discrimination of eyes and mouths by individuals with autism.,Autism research : official journal of the International Society for Autism Research,2010
diff --git a/scraper/reports/stats/unknown_papers.csv b/scraper/reports/stats/unknown_papers.csv index 92a64dac..2e064804 100644 --- a/scraper/reports/stats/unknown_papers.csv +++ b/scraper/reports/stats/unknown_papers.csv @@ -1,3 +1,39 @@ +6163381244823241373f6741a282f2c4a868b59c,Multimodal biometrics for identity documents (MBioID).,"Multimodal Biometrics for Identity +Documents 1 +State-of-the-Art +Research Report +PFS 341-08.05 +(Version 2.0) +Damien Dessimoz +Prof. Christophe Champod +Jonas Richiardi +Dr. Andrzej Drygajlo +{damien.dessimoz, +{jonas.richiardi, +June 2006 +This project was sponsored by the Foundation Banque Cantonale Vaudoise."
+610e0bee525a6573932e077f091505f54a5c4ede,"The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA","Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA +The Wisdom of MaSSeS: +Shailza Jolly∗ +SAP SE, Berlin +TU Kaiserslautern +Sandro Pezzelle∗ +SAP SE, Berlin +CIMeC - University of Trento +Tassilo Klein +SAP SE, Berlin +Andreas Dengel +DFKI, Kaiserslautern +CS Department, TU Kaiserslautern +Moin Nabi +SAP SE, Berlin"
+61c4969c78cff37357ac794af5ac8e439751b39f,Midrange Geometric Interactions for Semantic Segmentation,"Int J Comput Vis +DOI 10.1007/s11263-015-0828-7 +Midrange Geometric Interactions for Semantic Segmentation +Constraints for Continuous Multi-label Optimization +Julia Diebold1 · Claudia Nieuwenhuis2 · Daniel Cremers1 +Received: 1 June 2014 / Accepted: 15 May 2015 +© Springer Science+Business Media New York 2015"
610a4451423ad7f82916c736cd8adb86a5a64c59,A Survey on Search Based Face Annotation Using Weakly Labelled Facial Images,"Volume 4, Issue 11, November 2014 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering @@ -8,6 +44,89 @@ Labelled Facial Images Shital A. Shinde*, Prof. Archana Chaugule Department of Computer Engg, DYPIET Pimpri, Savitri Bai Phule Pune University, Maharashtra India"
+61366c2eed49519e3adef44e8b7146db1fcc2113,Convex NMF on Non-Convex Massiv Data,"Convex NMF on Non-Convex Massiv Data +Kristian Kersting1 and Mirwaes Wahabzada1 and Christian Thurau2 and Christian Bauckhage2 +Knowledge Discovery Department, 2Vision and Social Media Group +Fraunhofer IAIS, Schloss Birlinghoven, 53754 Sankt Augustin, Germany"
+617c4e23fc7ca51d98dacb28779214b3e79e9720,Open-Ended Visual Question-Answering,"Open-Ended Visual +Question-Answering +Escola T`ecnica Superior d’Enginyeria de Telecomunicaci´o de Barcelona +Submitted to the Faculty of the +A Degree Thesis +In partial fulfilment +of the requirements for the degree in +SCIENCE AND TELECOMMUNICATION TECHNOLOGIES +ENGINEERING +Author: +Advisors: Xavier Gir´o i Nieto, Santiago Pascual de la Puente +Issey Masuda Mora +Universitat Polit`ecnica de Catalunya (UPC) +June 2016"
+61e97d8440627bdc9772b3b2083c65f44a51107d,Oxytocin and vasopressin in the human brain: social neuropeptides for translational medicine,"R E V I E W S +Oxytocin and vasopressin in the +human brain: social neuropeptides +for translational medicine +Andreas Meyer‑Lindenberg*, Gregor Domes‡, Peter Kirsch* and Markus Heinrichs‡"
+618c13f1e13cc5346ed5c069a77acaa720b6a1a8,Learning More Universal Representations for Transfer-Learning,"SUBMISSION TO PAMI, SEPTEMBER 2018 +Learning More Universal Representations +for Transfer-Learning +Youssef Tamaazousti, Hervé Le Borgne, Céline Hudelot, Mohamed-El-Amine Seddik +nd Mohamed Tamaazousti"
+619eaaa60f0194d456591983a6f26b04cd9e9a52,"Munafo, M. (2017). Impaired Recognition of Basic Emotions from Facial Expressions in Young People with Autism Spectrum Disorder: Assessing the Importance of Expression","Griffiths, S. L., Jarrold, C., Penton-Voak, I., Woods, A., Skinner, A., & +Munafo, M. (2017). Impaired Recognition of Basic Emotions from Facial +Expressions in Young People with Autism Spectrum Disorder: Assessing the +Importance of Expression Intensity. Journal of Autism and Developmental +Disorders. DOI: 10.1007/s10803-017-3091-7 +Publisher's PDF, also known as Version of record +Link to published version (if available): +0.1007/s10803-017-3091-7 +Link to publication record in Explore Bristol Research +PDF-document +This is the final published version of the article (version of record). It first appeared online via Springer at +http://link.springer.com/article/10.1007%2Fs10803-017-3091-7. Please refer to any applicable terms of use of +the publisher. +University of Bristol - Explore Bristol Research +General rights +This document is made available in accordance with publisher policies. Please cite only the published +version using the reference above. Full terms of use are available: +http://www.bristol.ac.uk/pure/about/ebr-terms"
+61f4e08b938986ea80f711c73cadbc84e1811181,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+61764c068ad7d2ec988e6ec315d6ed2ed7489c2e,PhD Forum: Dynamic Camera Positioning and Reconfiguration for Multi Camera Networks,"Dynamic Camera Positioning and +Reconfiguration for Multi Camera +Networks +Krishna Reddy Konda +Advisor: Dr Nicola Conci +February 2015"
+610c341985633b2d31368f8642519953c39ff7e8,Computational Load Balancing on the Edge in Absence of Cloud and Fog,"Computational Load Balancing on the Edge in Absence of Cloud +nd Fog +Citation for published version: +Sthapit, S, Thompson, J, Robertson, NM & Hopgood, J 2018, 'Computational Load Balancing on the Edge +in Absence of Cloud and Fog' IEEE Transactions on Mobile Computing. DOI: 10.1109/TMC.2018.2863301 +Digital Object Identifier (DOI): +0.1109/TMC.2018.2863301 +Link: +Link to publication record in Edinburgh Research Explorer +Document Version: +Peer reviewed version +Published In: +IEEE Transactions on Mobile Computing +General rights +Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +nd / or other copyright owners and it is a condition of accessing these publications that users recognise and +bide by the legal requirements associated with these rights. +Take down policy +The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer +ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please"
6180bc0816b1776ca4b32ced8ea45c3c9ce56b47,Fast Randomized Algorithms for Convex Optimization and Statistical Estimation,"Fast Randomized Algorithms for Convex Optimization and Statistical Estimation Mert Pilanci @@ -20,9 +139,145 @@ August 14, 2016" Localization Xiang Yu, Feng Zhou and Manmohan Chandraker NEC Laboratories America, Department of Media Analytics"
+61c4b35443b152679c923d5db6c26daaec304172,Fast and stable human detection using multiple classifiers based on subtraction stereo with HOG features,"Fast and Stable Human Detection Using Multiple Classifiers +Based on Subtraction Stereo with HOG Features +Makoto Arie, Alessandro Moro, Yuma Hoshikawa, Toru Ubukata, Kenji Terabayashi, Kazunori Umeda"
+6106028c73d22570a01212814e1e4f4edb4abed6,Counting moving people in crowds using motion statistics of feature-points,"Multimed Tools Appl +DOI 10.1007/s11042-013-1367-2 +Counting moving people in crowds using motion +statistics of feature-points +Mahdi Hashemzadeh· Gang Pan· Min Yao +© Springer Science+Business Media New York 2013"
+617a6935643615f09ef2b479609baa0d5f87cd67,To Be Taken At Face Value? Computerised Identification,"Information and Communications Technology Law +To Be Taken At Face Value? +Computerised Identification +Michael Bromby +Joseph Bell Centre for Forensic Statistics and Legal Reasoning +Glasgow Caledonian University and University of Edinburgh +Scientific evidence such as fingerprints, blood, hair and DNA samples are often +presented during legal proceedings. Without such evidence, a description provided by +the victim or any eyewitnesses is often the only means to identify a suspect. With the +dvent of closed circuit television (CCTV), many crimes are now recorded by +ameras in the public or private domain, leading to a new form of forensic +identification – facial biometrics. Decisions on how to view and interpret biometric +evidence are important for both prosecution and defence, not least for the judge and +jury who must decide the case. A jury may accept eyewitnesses as reliable sources of +evidence more readily +False +eyewitness accounts appear reliable when confidently presented to a mock jury. The +decision-making process of the judge and jury may be seriously flawed if an +eyewitness has made a genuine mistake. Using computerised recognition, the judicial +decision of whether to accept an alibi or whether to accept the eyewitness account"
614a7c42aae8946c7ad4c36b53290860f6256441,Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks,"Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li, Senior Member, IEEE, and Yu Qiao, Senior Member, IEEE"
+617b719e6c31cdfe7c5c485a755435b95f0c4991,Visual Classification of Images by Learning Geometric Appearances Through Boosting,"Visual Classification of Images by Learning +Geometric Appearances through Boosting +Martin Antenreiter, Christian Savu-Krohn, and Peter Auer +Chair of Information Technology (CiT) +University of Leoben, Austria"
+6155d504d59c52dc3a6b8ad6aeae8bf249afd5ac,Analysis of Feature Fusion Based on HIK SVM and Its Application for Pedestrian Detection,Hindawi Publishing Corporation
+61c07d7387dcbfb8fa697f15316e3b265d78a2fa,Multi-modal Approach for Affective Computing,"Multi-modal Approach for Affective Computing +Siddharth1,2, Tzyy-Ping Jung2 and Terrence J. Sejnowski2"
+619f9c1552f8f4f7c5927a7369c79e34d6294083,A Volumetric / Iconic Frequency DomainRepresentation,"AVolumetric/IconicFrequencyDomain +RepresentationforObjects +withapplicationfor +PoseInvariantFaceRecognition +AppearedinIEEETrans.onPatternAnalysisandMachineIntelligence +Vol. +JezekielBen-ArieandDibyenduNandy +DepartmentofElectricalEngineeringandComputerScience +TheUniversityofIllinoisatChicago +ContactAddress: +Dr.JezekielBen-Arie +TheUniversityofIllinoisatChicago +DepartmentofElectricalEngineeringandComputerScience(M/C) +SouthMorganStreetChicago,IL +Phone:() - +Fax:() - +ThisworkwassupportedbytheNationalScienceFoundationunderGrantNo.IRI- +ndGrantNo.IRI- ."
+61b0cfd75f5bce59cf79abb7b602e404fa5584e7,Person Re-Identification by Semantic Region Representation and Topology Constraint,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY +Person Re-Identification by Semantic Region +Representation and Topology Constraint +Jianjun Lei, Senior Member, IEEE, Lijie Niu, Huazhu Fu, Senior Member, IEEE, Bo Peng, +Qingming Huang, Fellow, IEEE, and Chunping Hou"
+614f4f8fe47e7c0bcf64aa0ad39dc371e4b4ab7b,promoting access to White Rose research papers,"promoting access to White Rose research papers +Universities of Leeds, Sheffield and York +http://eprints.whiterose.ac.uk/ +This is an author produced version of a paper published in Journal of Autism +nd Developmental Disorders. +White Rose Research Online URL for this paper: +http://eprints.whiterose.ac.uk/10325 +Published paper +Freeth, M., Chapman, P., Ropar, D., Mitchell, P. (2010) Do gaze cues in complex +scenes capture and direct the attention of high functioning adolescents with ASD? +evidence from eye-tracking, Journal of Autism and Developmental Disorders (In +Press) +http://dx.doi.org/10.1007/s10803-009-0893-2 +White Rose Research Online"
+617253f275f14490c61dc9d8cb23ceb9c9d4ba35,A coarse-to-fine curvature analysis-based rotation invariant 3D face landmarking,"A coarse-to-fine curvature analysis-based rotation invariant 3D face +landmarking +Przemyslaw Szeptycki, Mohsen Ardabilian and Liming Chen"
+61f0cb2e3fdc6a5d0719184e51d2dc483a945ac1,Bilinear Attention Networks,"Bilinear Attention Networks +Jin-Hwa Kim1∗, Jaehyun Jun2, Byoung-Tak Zhang2,3 +SK T-Brain, 2Seoul National University, 3Surromind Robotics"
+61b17f719bab899dd50bcc3be9d55673255fe102,Detecting Sarcasm in Multimodal Social Platforms,"Detecting Sarcasm in Multimodal Social Platforms +Rossano Schifanella +University of Turin +Corso Svizzera 185 +0149, Turin, Italy +Paloma de Juan +Yahoo +29 West 43rd Street +New York, NY 10036 +Joel Tetreault +Yahoo +29 West 43rd Street +New York, NY 10036 +Liangliang Cao +Yahoo +29 West 43rd Street +New York, NY 10036 +inc.com"
+61bab86023de164bca3e35fc22944a7262970e1d,Child Facial Expression Detection,"CHILD FACIAL EXPRESSION +DETECTION +Eden Benhamou +Deborah Wolhandler +Supervisors: +Alon Zvirin +Michal Zivan +Spring 2018"
+61dfebbb02dad16b56cd9e6c54b5da3ab41caf1c,Exploiting Local Class Information in Extreme Learning Machine,"Iosifidis, A., Tefas, A., & Pitas, I. (2014). Exploiting Local Class Information +in Extreme Learning Machine. Paper presented at International Joint +Conference on Computational Intelligence (IJCCI), Rome, Italy. +Peer reviewed version +Link to publication record in Explore Bristol Research +PDF-document +University of Bristol - Explore Bristol Research +General rights +This document is made available in accordance with publisher policies. Please cite only the published +version using the reference above. Full terms of use are available: +http://www.bristol.ac.uk/pure/about/ebr-terms"
+611f9faa6f3aeff3ccd674d779d52c4f9245376c,Multiresolution Models for Object Detection,"Multiresolution models for object detection +Dennis Park, Deva Ramanan, and Charless Fowlkes +UC Irvine, Irvine CA 92697, USA,"
+0d1a87dad1e4538cc7bd3c923767c8bf1a9b779f,The Riemannian Geometry of Deep Generative Models,"The Riemannian Geometry of Deep Generative Models +Hang Shao +University of Utah +Salt Lake City, UT +Abhishek Kumar +IBM Research AI +Yorktown Heights, NY +P. Thomas Fletcher +University of Utah +Salt Lake City, UT"
+0db787317ba0d63ec8f9918905e7db181a489026,Automatic Eye Localization in Color Images,"Automatic Eye Localization in Color Images +José Gilvan Rodrigues Maia1, Fernando de Carvalho Gomes1, Osvaldo de Souza2 +Departamento de Computação – Universidade Federal do Ceará (UFC) +Depto de Engenharia de Teleinformática – Universidade Federal do Ceará (UFC) +60455-760 – Fortaleza – CE – Brasil +{gilvan,"
0d88ab0250748410a1bc990b67ab2efb370ade5d,Error handling in multimodal biometric systems using reliability measures,"Author(s) : ERROR HANDLING IN MULTIMODAL BIOMETRIC SYSTEMS USING RELIABILITY MEASURES (ThuPmOR6) @@ -34,6 +289,8 @@ Krzysztof Kryszczuk Jonas Richiardi Plamen Prodanov Andrzej Drygajlo"
+0d82013cbe9f65ddb34e5d99eab730fce4f0effe,A system based on sequence learning for event detection in surveillance video,"978-1-4799-2341-0/13/$31.00 ©2013 IEEE +ICIP 2013"
0d538084f664b4b7c0e11899d08da31aead87c32,Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction,"Deformable Part Descriptors for Fine-grained Recognition and Attribute Prediction Ning Zhang1 @@ -41,6 +298,10 @@ Ryan Farrell1,2 Forrest Iandola1 ICSI / UC Berkeley 2Brigham Young University Trevor Darrell1"
+0dcdef6b8d97483f4d4dab461e1cb5b3c4d1fe1a,Probabilistic Semantic Inpainting with Pixel Constrained CNNs,"Probabilistic Semantic Inpainting with Pixel Constrained CNNs +Emilien Dupont +Suhas Suresha +Schlumberger Software Technology Innovation Center"
0dccc881cb9b474186a01fd60eb3a3e061fa6546,Effective face frontalization in unconstrained images,"Effective Face Frontalization in Unconstrained Images Tal Hassner1, Shai Harel1 †, Eran Paz1 † and Roee Enbar2 The open University of Israel. 2Adience. @@ -61,11 +322,66 @@ ll input faces. We show that this leads to a straightforward, efficient and easy to implement method for frontalization. More importantly, it produces esthetic new frontal views and is surprisingly effective when used for face recognition and gender estimation."
+0d96c9d14f079b7b8b6b56b4fa86f611a4ff237f,Semi-supervised low-rank mapping learning for multi-label classification,"Semi-supervised Low-Rank Mapping Learning for Multi-label Classification +Liping Jing1, Liu Yang1, Jian Yu1, Michael K. Ng2 +Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University. 2Department of Mathematics, Hong Kong Baptist University. +With the rapid growth of online content such as images, videos, web pages, +it is crucial to design a scalable and effective classification system to au- +tomatically organize, store, and search the content. In conventional clas- +sification, each instance is assumed to belong to exactly one class among +finite number of candidate classes. However, in modern applications, an +instance can have multiple labels. For example, an image can be annotated +y many conceptual tags in semantic scene classification. Multi-label data +have ubiquitously occurred in many application domains: multimedia infor- +mation retrieval, tag recommendation, query categorization, gene function +prediction, medical diagnosis, drug discovery and marketing. An important +nd challenging research problem [1, 4] in multi-label learning is how to +exploit and make use of label correlations. +In this paper, we develop a novel method for multi-label learning when +there is only a small number of labeled data. Our main idea is to design +Semi-supervised Low-Rank Mapping (SLRM) from a feature space to a +label space based on given multi-label data. More specifically, the SLRM +model can be formularized as"
0d6b28691e1aa2a17ffaa98b9b38ac3140fb3306,Review of Perceptual Resemblance of Local Plastic Surgery Facial Images using Near Sets,"Review of Perceptual Resemblance of Local Plastic Surgery Facial Images using Near Sets Prachi V. Wagde1, Roshni Khedgaonkar2 ,2 Department of Computer Technology, YCCE Nagpur, India"
+0dc2fdf1b97c76de1e7380e8126f8acc7d87e23a,Robust PCA Via Nonconvex Rank Approximation,"Robust PCA via Nonconvex Rank Approximation +Department of Computer Science, Southern Illinois University, Carbondale, IL 62901, USA +Zhao Kang, Chong Peng, Qiang Cheng +{zhao.kang, pchong,"
+0d2a9f3357717e0a44eb82d5eabfc047cc4d46f1,Classifier Ensembles with Trajectory Under-Sampling for Face Re-Identification,"Classifier Ensembles with Trajectory Under-Sampling +for Face Re-Identification +Roghayeh Soleymani1, Eric Granger1 and Giorgio Fumera2 +Laboratoire d’imagerie, de vision et d’intelligence artificielle, École de technologie supérieure, +Pattern Recognition and Applications Group, Dept. of Electrical and Electronic Engineering, University of +Université du Québec, Montreal, Canada +Cagliari,Cagliari, Italy +Keywords: +Person Re-Identification, Class Imbalance, Ensemble Methods."
+0dab1ab19a44b73ce0fdd15014b635eb7362af3c,Reinforcement Cutting-Agent Learning for Video Object Segmentation,"Reinforcement Cutting-Agent Learning for Video Object Segmentation +Junwei Han1, Le Yang1, Dingwen Zhang1 +, Xiaojun Chang3, Xiaodan Liang3 +Northwestern Polytechincal University, 2Xidian University, 3Carnegie Mellon University"
+0d7ddcf97b1341d8d4bbc4718f4ca3094e994a1f,Homographic Active Shape Models for View-Independent Facial Analysis,"Homographic Active Shape Models for View-Independent +Facial Analysis +Federico M. Sukno12 and Jos´e J. Guerrero32 and Alejandro F. Frangi1 +Department of Technology, Pompeu Fabra University, Barcelona, Spain; +Aragon Institute of Engineering Research, University of Zaragoza, Spain; +Computer Science and System Engineering Department, University of Zaragoza, Spain"
+0dd74bbda5dd3d9305636d4b6f0dad85d6e19572,Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach,"Heterogeneous Face Attribute Estimation: +A Deep Multi-Task Learning Approach +Hu Han, Member, IEEE, Anil K. Jain, Fellow, IEEE, Fang Wang, +Shiguang Shan, Senior Member, IEEE and Xilin Chen, Fellow, IEEE"
+0d07db3510c7f9c2ceab65444cb8fc8ec49197b2,Learning-based Composite Metrics for Improved Caption Evaluation,"Learning-based Composite Metrics for Improved Caption Evaluation +Naeha Sharif, Lyndon White, Mohammed Bennamoun and Syed Afaq Ali Shah, +{naeha.sharif, +nd {mohammed.bennamoun, +The University of Western Australia. +5 Stirling Highway, Crawley, Western Australia"
+0d130b5536bb1b909ff9a62737d768d4b4fab2f6,Semantic Segmentation with Scarce Data,"Semantic Segmentation with Scarce Data +Isay Katsman * 1 Rohun Tripathi * 1 Andreas Veit 1 Serge Belongie 1"
0d3882b22da23497e5de8b7750b71f3a4b0aac6b,Context is routinely encoded during emotion perception.,"Research Article Context Is Routinely Encoded During Emotion Perception @@ -78,6 +394,19 @@ http://pss.sagepub.com Lisa Feldman Barrett1,2,3 and Elizabeth A. Kensinger1,3 Boston College; 2Psychiatric Neuroimaging Program, Massachusetts General Hospital, Harvard Medical School; and 3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School"
+0d185e6de595bd3844909d3606e9218a498a9bd8,Trace optimization and eigenproblems in dimension reduction methods,"TRACE OPTIMIZATION AND EIGENPROBLEMS IN DIMENSION +REDUCTION METHODS +E. KOKIOPOULOU∗, J. CHEN†, AND Y. SAAD†"
+0d90d046db16d3d5ce70590e6dab32cdd58928f6,A robust feature extraction algorithm based on class-Modular Image Principal Component Analysis for face verification,"978-1-4577-0539-7/11/$26.00 ©2011 IEEE +ICASSP 2011"
+0d52f1ae438a395fadebf04990d0d1750cdd0218,Face Recognition in Various Illuminations,"Saurabh D. Parmar et al Int. Journal of Engineering Research and Applications www.ijera.com +ISSN : 2248-9622, Vol. 4, Issue 5( Version 5), May 2014, pp.98-102 +RESEARCH ARTICLE +Face Recognition in Various Illuminations +Saurabh D. Parmar, Vaishali J. Kalariya +Research Scholar, CE/IT Department-School of Engineering, R.K. University, Rajkot +Professor, CE/IT Department-School of Engineering, R.K. University, Rajkot +OPEN ACCESS"
0d760e7d762fa449737ad51431f3ff938d6803fe,LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems,"LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems Subarna Tripathi @@ -90,10 +419,147 @@ Vasudev Bhaskaran Qualcomm Inc. Truong Nguyen UC San Diego"
+0d30a662061a495e4b5aeb92a2edfac868b225ea,Quantification of Emotions for Facial Expression: Generation of Emotional Feature Space Using Self-Mapping,"Chapter 7 +Quantification of Emotions for Facial Expression: +Generation of Emotional Feature Space Using Self- +Mapping +Masaki Ishii, Toshio Shimodate, Yoichi Kageyama, +Tsuyoshi Takahashi and Makoto Nishida +Additional information is available at the end of the chapter +http://dx.doi.org/10.5772/51136 +. Introduction +Facial expression recognition for the purpose of emotional communication between humans +nd machines has been investigated in recent studies [1-7]. +The shape (static diversity) and motion (dynamic diversity) of facial components, such as +the eyebrows, eyes, nose, and mouth, manifest expression. From the viewpoint of static di‐ +versity, owing to the individual variation in facial configurations, it is presumed that a facial +expression pattern due to the manifestation of a facial expression includes subject-specific +features. In addition, from the viewpoint of dynamic diversity, because the dynamic +hanges in facial expressions originate from subject-specific facial expression patterns, it is +presumed that the displacement vector of facial components has subject-specific features. +On the other hand, although an emotionally generated facial expression pattern of an indi‐ +vidual is unique, internal emotions expressed and recognized by humans via facial expres‐"
+0d48c282737793b234c56382053cc69cdddeccb0,A Poodle or a Dog? Evaluating Automatic Image Annotation Using Human Descriptions at Different Levels of Granularity,"Proceedings of the 25th International Conference on Computational Linguistics, pages 38–45, +Dublin, Ireland, August 23-29 2014."
+0dd151d003ac9b7f3d6936ccdd5ff38fce76c29f,A Review and Comparison of Measures for Automatic Video Surveillance Systems,"Hindawi Publishing Corporation +EURASIP Journal on Image and Video Processing +Volume 2008, Article ID 824726, 30 pages +doi:10.1155/2008/824726 +Research Article +A Review and Comparison of Measures for +Automatic Video Surveillance Systems +Axel Baumann, Marco Boltz, Julia Ebling, Matthias Koenig, Hartmut S. Loos, Marcel Merkel, +Wolfgang Niem, Jan Karl Warzelhan, and Jie Yu +Corporate Research, Robert Bosch GmbH, D-70049 Stuttgart, Germany +Correspondence should be addressed to Julia Ebling, +Received 30 October 2007; Revised 28 February 2008; Accepted 12 June 2008 +Recommended by Andrea Cavallaro +Today’s video surveillance systems are increasingly equipped with video content analysis for a great variety of applications. +However, reliability and robustness of video content analysis algorithms remain an issue. They have to be measured against +ground truth data in order to quantify the performance and advancements of new algorithms. Therefore, a variety of measures +have been proposed in the literature, but there has neither been a systematic overview nor an evaluation of measures for +specific video analysis tasks yet. This paper provides a systematic review of measures and compares their effectiveness for specific +spects, such as segmentation, tracking, and event detection. Focus is drawn on details like normalization issues, robustness, and +representativeness. A software framework is introduced for continuously evaluating and documenting the performance of video"
+0d0cee830772c3b2b274bfb5c3ad0ee42d8a0a57,Multimodal Convolutional Neural Networks for Matching Image and Sentence,"Multimodal Convolutional Neural Networks for Matching Image and Sentence +Lin Ma +Zhengdong Lu +Lifeng Shang +Hang Li +{Lu.Zhengdong, Shang.Lifeng, +Noah’s Ark Lab, Huawei Technologies"
0dd72887465046b0f8fc655793c6eaaac9c03a3d,Real-Time Head Orientation from a Monocular Camera Using Deep Neural Network,"Real-time Head Orientation from a Monocular Camera using Deep Neural Network Byungtae Ahn, Jaesik Park, and In So Kweon KAIST, Republic of Korea"
+0dc34e186e8680336e88c3b5e73cde911a8774b8,Image Classification Using Naive Bayes Classifier With Pairwise Local Observations,"JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 32, XXXX-XXXX (2017) +Image Classification Using Naive Bayes Classifier With +Pairwise Local Observations +SHIH-CHUNG HSU1, I-CHIEH CHEN1 AND CHUNG-LIN HUANG2 +Department of Electrical Engineering, National Tsing-Hua University, Hsin-Chu, Taiwan +Department of M-Commerce and Multimedia Applications, Asia Univ., Tai-Chung, Taiwan +E-mail: +We propose a pairwise local observation-based Naive Bayes (NBPLO) classifier for +image classification. First, we find the salient regions (SRs) and the Keypoints (KPs) as +the local observations. Second, we describe the discriminative pairwise local observations +using Bag-of-features (BoF) histogram. Third, we train the object class models by using +random forest to develop the NBPLO classifier for image classification. The two major +ontributions in this paper are multiple pairwise local observations and regression object +lass model training for NBPLO classifier. In the experiments, we test our method using +Scene-15 and Caltech-101 database and compare the results with the other methods. +Keywords: Local observation-based Naive Bayes classifier (NBPLO), Salient Region(SR), +Keypoint(KP), Bag-of-feature(BoF). +. INTRODUCTION +Image classification has been a challenging unsolved problem due to the complexity of +image contents. It has been a popular research subject of many recently published re-"
+0d0199e48d22ff4b80c983e3b28532f908467da7,Linear regression motion analysis for unsupervised temporal segmentation of human actions,"Linear Regression Motion Analysis for Unsupervised Temporal +Segmentation of Human Actions +Simon Jones, Ling Shao +Department of Electronic and Electrical Engineering +The University of Sheffield, Mappin St, Sheffield, S1 3JD, UK"
+0d30066576c029cd888d7c759349379bdb0e88c2,"How Much Information Kinect Facial Depth Data Can Reveal About Identity, Gender and Ethnicity?","How Much Information Kinect Facial Depth +Data Can Reveal about Identity, Gender and +Ethnicity? +Elhocine Boutellaaa;b, Messaoud Bengherabia, Samy Ait-Aoudiab, Abdenour +Hadidc +Centre de D(cid:19)eveloppement des Technologies Avanc(cid:19)ees (DZ), +Ecole Nationale Sup(cid:18)erieure d’Informatique (DZ), +University of Oulu (FI)"
+0d076edd62e258316bc310fafcec88db3ab85434,Automatic detection and tracking of pedestrians from a moving stereo rig,"Automatic detection and tracking of pedestrians from a +moving stereo rig +Konrad Schindlera, Andreas Essb, Bastian Leibec, Luc Van Goolb,d +Photogrammetry and Remote Sensing, ETH Z¨urich, Switzerland +Computer Vision Lab, ETH Z¨urich, Switzerland +UMIC research centre, RWTH Aachen, Germany +dESAT/PSI–VISICS, IBBT, KU Leuven, Belgium"
+0da611ca979327840161df87564fd07299c268b5,Bodyprint: Biometric User Identification on Mobile Devices Using the Capacitive Touchscreen to Scan Body Parts,"Bodyprint +Biometric User Identification on Mobile Devices +Using the Capacitive Touchscreen to Scan Body Parts +Christian Holz +Senaka Buthpitiya +Marius Knaust"
+0d82ac80275283c3dd26aca9e629ee6a9ca8a07a,An object-based semantic world model for long-term change detection and semantic querying,"An Object-Based Semantic World Model for +Long-Term Change Detection and Semantic Querying +Julian Mason and Bhaskara Marthi"
+0dfb47e206c762d2f4caeb99fd9019ade78c2c98,Custom Pictorial Structures for Re-identification,"CHENG et al.: CUSTOM PICTORIAL STRUCTURES FOR RE-IDENTIFICATION +Custom Pictorial Structures for +Re-identification +Dong Seon Cheng1 +Marco Cristani1,2 +Michele Stoppa2 +Loris Bazzani1 +Vittorio Murino1,2 +http://profs.sci.univr.it/~swan +Dipartimento di Informatica +University of Verona +Italy +Istituto Italiano di Tecnologia +Via Morego, 30 +6163 Genova, Italy"
+0d8e7cda7d8a2ff737c0ad72f31dfd4d80d3a09a,Network Structure & Information Advantage,"A research and education initiative at the MIT +Sloan School of Management +Network Structure & Information Advantage +Paper 235 +Sinan Aral +Marshall Van Alstyne +July 2007 +For more information, +please visit our website at http://digital.mit.edu +or contact the Center directly at +or 617-253-7054"
+0d21472dbf20d4c1bd48a15267b4a59eff80e309,Multi-component Models for Object Detection,"Multi-component Models for Object Detection +Chunhui Gu1, Pablo Arbel´aez2, Yuanqing Lin3, Kai Yu4, and Jitendra Malik2 +Google Inc., Mountain View, CA, USA +UC Berkeley, Berkeley, CA, USA +NEC Labs America, Cupertino, CA, USA +Baidu Inc., Beijing, China"
+0d0041aefb16c5f7b1e593b440bb3df7b05b411c,Secure JPEG scrambling enabling privacy in photo sharing,"Secure JPEG Scrambling Enabling +Privacy in Photo Sharing +Lin Yuan, Pavel Korshunov, Touradj Ebrahimi +Multimedia Signal Processing Group, EPFL +De-ID workshop, Ljubljana, Slovenia +8/14/2015 +Workshop on De-identification for Privacy Protection in Multimedia"
0d33b6c8b4d1a3cb6d669b4b8c11c2a54c203d1a,Detection and Tracking of Faces in Videos: A Review of Related Work,"Detection and Tracking of Faces in Videos: A Review © 2016 IJEDR | Volume 4, Issue 2 | ISSN: 2321-9939 of Related Work @@ -101,6 +567,37 @@ Seema Saini, 2 Parminder Sandal Student, 2Assistant Professor , 2Dept. of Electronics & Comm., S S I E T, Punjab, India ________________________________________________________________________________________________________"
+0d8a2034bbdefa214d8debecc704cadc5b9ec6e8,Submitted for the Degree of Doctor of Philosophy at the University of Sussex,"A University of Sussex DPhil thesis +Available online via Sussex Research Online: +http://sro.sussex.ac.uk/ +This thesis is protected by copyright which belongs to the author. +This thesis cannot be reproduced or quoted extensively from without first +obtaining permission in writing from the Author +The content must not be changed in any way or sold commercially in any +format or medium without the formal permission of the Author +When referring to this work, full bibliographic details including the +uthor, title, awarding institution and date of the thesis must be given +Please visit Sussex Research Online for more information and further details"
+0dd72a3522b99aedea83b47c5d7b33a1df058fd0,A Set of Selected SIFT Features for 3D Facial Expression Recognition,"A Set of Selected SIFT Features for 3D Facial +Expression Recognition +Stefano Berretti, Alberto Del Bimbo, Pietro Pala, Boulbaba Ben Amor, +Daoudi Mohamed +To cite this version: +Stefano Berretti, Alberto Del Bimbo, Pietro Pala, Boulbaba Ben Amor, Daoudi Mohamed. A Set +of Selected SIFT Features for 3D Facial Expression Recognition. 20th International Conference on +Pattern Recognition, Aug 2010, Istanbul, Turkey. pp.4125 - 4128, 2010. <hal-00829354> +HAL Id: hal-00829354 +https://hal.archives-ouvertes.fr/hal-00829354 +Submitted on 3 Jun 2013 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non,"
0da4c3d898ca2fff9e549d18f513f4898e960aca,The Headscarf Effect Revisited: Further Evidence for a Culture-Based Internal Face Processing Advantage.,"Wang, Y., Thomas, J., Weissgerber, S. C., Kazemini, S., Ul-Haq, I., & Quadflieg, S. (2015). The Headscarf Effect Revisited: Further Evidence for a 36. 10.1068/p7940 @@ -121,6 +618,31 @@ nd include the following information in your message: • Your contact details • Bibliographic details for the item, including a URL • An outline of the nature of the complaint"
+95ace502ba23a8a5543b882937de23b892112cca,Facial Dynamics Interpreter Network: What Are the Important Relations Between Local Dynamics for Facial Trait Estimation?,"Facial Dynamics Interpreter Network: What are +the Important Relations between Local +Dynamics for Facial Trait Estimation? +Seong Tae Kim and Yong Man Ro* +School of Electrical Engineering, KAIST, Daejeon, Republic of Korea"
+95f990600abb9c8879e4f5f7cd03f3d696fcdec4,An Online Algorithm for Constrained Face Clustering in Videos,"Manuscript version: Author’s Accepted Manuscript +The version presented in WRAP is the author’s accepted manuscript and may differ from the +published version or Version of Record. +Persistent WRAP URL: +http://wrap.warwick.ac.uk/109574 +How to cite: +Please refer to published version for the most recent bibliographic citation information. +If a published version is known of, the repository item page linked to above, will contain +details on accessing it. +Copyright and reuse: +The Warwick Research Archive Portal (WRAP) makes this work by researchers of the +University of Warwick available open access under the following conditions. +Copyright © and all moral rights to the version of the paper presented here belong to the +individual author(s) and/or other copyright owners. To the extent reasonable and +practicable the material made available in WRAP has been checked for eligibility before +eing made available. +Copies of full items can be used for personal research or study, educational, or not-for-profit +purposes without prior permission or charge. Provided that the authors, title and full +ibliographic details are credited, a hyperlink and/or URL is given for the original metadata +page and the content is not changed in any way."
956317de62bd3024d4ea5a62effe8d6623a64e53,Lighting Analysis and Texture Modification of 3D Human Face Scans,"Lighting Analysis and Texture Modification of 3D Human Face Scans Author @@ -140,6 +662,33 @@ Link to published version http://www.ieee.org/ Griffith Research Online https://research-repository.griffith.edu.au"
+9501db000474dbd182579d311dfb1b1ab8fa871f,Supplementary of Multi-scale Deep Learning Architectures for Person Re-identification,"Supplementary of Multi-scale Deep Learning Architectures for Person +Re-identification +Xuelin Qian1 Yanwei Fu2,5,* Yu-Gang Jiang1,3 Tao Xiang4 Xiangyang Xue1,2 +Shanghai Key Lab of Intelligent Info. Processing, School of Computer Science, Fudan University; +School of Data Science, Fudan University; 3Tencent AI Lab; +Queen Mary University of London; 5University of Technology Sydney; +. Multi-scale stream layers +Multi-scale-A layer (Fig. 1), analyses the data stream with +the size 1 × 1, 3 × 3 and 5 × 5 of receptive field. Further- +more, in order to increase both depth and width of this layer, +we split the filter size of 5 × 5 into two 3 × 3 streams cas- +aded (i.e. stream-4 and stream-3 in Tab 1 and Fig. 1). The +weights of each stream are also tied with the corresponding +stream in another branch. Such a design art is, in general, +inspired by, and yet different from the inception architec- +tures [11, 12, 10]. The key difference lies in the weights +which are not tied between any two streams from the same +ranch, but are tied between the two corresponding streams +of different branches. +Reduction layer (Fig. 2) further passes the data stream"
+95296302a7fc82edf782cece082d7319cfa584b7,Detection-free Bayesian Multi-object Tracking via Spatio-Temporal Video Bundles Grouping,"Detection-free Bayesian Multi-object Tracking +via Spatio-Temporal Video Bundles Grouping +Technical Report, November 2013 +Yongyi Lu, Liang Lin, Yuanlu Xu, Zefeng Lai"
+9595a267de2b0ecf7e4e2962a606c8854551e203,On the Relation between Color Image Denoising and Classification,"On the Relation between Color Image Denoising +nd Classification +Jiqing Wu, Radu Timofte, Member, IEEE, Zhiwu Huang, Member, IEEE, and Luc Van Gool, Member, IEEE"
959bcb16afdf303c34a8bfc11e9fcc9d40d76b1c,Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks,"Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks @@ -147,6 +696,13 @@ Prateep Bhattacharjee1, Sukhendu Das2 Visualization and Perception Laboratory Department of Computer Science and Engineering Indian Institute of Technology Madras, Chennai, India"
+95be490aef44da67ca1cef76b16df14b6e40c421,Learning Cross-View Binary Identities for Fast Person Re-Identification,"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16) +Learning Cross-View Binary Identities +for Fast Person Re-Identification +Feng Zheng1, Ling Shao2 +Department of Electronic and Electrical Engineering, The University of Sheffield. +Department of Computer Science and Digital Technologies, Northumbria University."
+95593fb20df8ce1273cebe0690cf2cdab054b9b5,Robust Multi-image HDR Reconstruction for the Modulo Camera,
951f21a5671a4cd14b1ef1728dfe305bda72366f,Use of l2/3-norm Sparse Representation for Facial Expression Recognition,"International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Impact Factor (2012): 3.358 @@ -158,6 +714,24 @@ MATS University, MATS School of Engineering and Technology, Arang, Raipur, India three to discriminate represents emotion,"
+95aef5184b89daebd0c820c8102f331ea7cae1ad,Recognising facial expressions in video sequences,"Recognising facial expressions in video sequences +Jos´e M. Buenaposada1, Enrique Mu˜noz2⋆, Luis Baumela2 +ESCET, Universidad Rey Juan Carlos +C/Tulip´an s/n, 28933 M´ostoles, Spain +Facultad Inform´atica, Universidad Polit´ecnica de Madrid +Campus Montegancedo s/n, 28660 Boadilla del Monte, Spain +http://www.dia.fi.upm.es/~pcr +Received: 7 Jan 2007 / Accepted: 10 July 2007/ Online: 18 Oct 2007"
+95225bab187483e37823daab5c503f6b327fb008,Improved MinMax Cut Graph Clustering with Nonnegative Relaxation,"Improved MinMax Cut Graph Clustering with +Nonnegative Relaxation +Feiping Nie, Chris Ding, Dijun Luo, and Heng Huang +Department of Computer Science and Engineering, +University of Texas, Arlington, America"
+9588a42bff63fb36015e10fac9f3121154c3ab1d,Explaining Potential Risks in Traffic Scenes by Combining Logical Inference and Physical Simulation,"International Journal of Machine Learning and Computing, Vol. 6, No. 5, October 2016 +Explaining Potential Risks in Traffic Scenes by Combining +Logical Inference and Physical Simulation +Ryo Takahashi, Naoya Inoue, Yasutaka Kuriya, Sosuke Kobayashi, and Kentaro Inui +from observation and"
9547a7bce2b85ef159b2d7c1b73dea82827a449f,Facial expression recognition using Gabor motion energy filters,"Facial Expression Recognition Using Gabor Motion Energy Filters Tingfan Wu Dept. Computer Science Engineering @@ -166,21 +740,59 @@ Marian S. Bartlett Javier R. Movellan Institute for Neural Computation UC San Diego"
+95a9e256c8f8bbce0d86199cacea92b15004dd45,Using Semantic Similarity for Multi-Label Zero-Shot Classification of Text Documents,"Using Semantic Similarity for Multi-Label Zero-Shot +Classification of Text Documents +Jinseok Nam2,3 +Sappadla Prateek Veeranna1 +Johannes F¨urnkranz2 ∗ +Eneldo Loza Menc´ıa2 +- Birla Institute of Technology and Science - Pilani - India +- Knowledge Engineering Group - TU Darmstadt - Germany +- Knowledge Discovery in Scientific Literature - DIPF - Germany"
9513503867b29b10223f17c86e47034371b6eb4f,Comparison of Optimisation Algorithms for Deformable Template Matching,"Comparison of optimisation algorithms for deformable template matching Vasileios Zografos Link¨oping University, Computer Vision Laboratory ISY, SE-581 83 Link¨oping, SWEDEN"
+95ed2269c4a13771cc8dfe0ff2d4d6a7f4d73033,Deep Learning for Domain Adaption: Engagement Recognition,"Engagement Recognition using Deep Learning and Facial Expression +Omid Mohamad Nezami , Len Hamey , Deborah Richards , and Mark Dras +Macquarie University, Sydney, NSW, Australia"
956c634343e49319a5e3cba4f2bd2360bdcbc075,A novel incremental principal component analysis and its application for face recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 4, AUGUST 2006 A Novel Incremental Principal Component Analysis nd Its Application for Face Recognition Haitao Zhao, Pong Chi Yuen, Member, IEEE, and James T. Kwok, Member, IEEE"
+95a835cdb5dc46e4de071865f9dccdaf9ec944ad,Euclidean and geodesic distance between a facial feature points in two-dimensional face recognition system,"The International Arab Journal of Information Technology, Vol. 14, No. 4A, Special Issue 2017 565 +Euclidean and Geodesic Distance between a Facial +Feature Points in Two-Dimensional Face +Recognition System +Rachid Ahdid1,2, Said Safi1, and Bouzid Manaut2 +Department of Mathematics and Informatics, Sultan Moulay Slimane University, Morocco +Poladisciplinary Faculty, Sultan Moulay Slimane University, Morocco"
+95deb62b82ede5c6732c5c498d3f9452866eaba7,Unsupervised Video Understanding by Reconciliation of Posture Similarities,"Unsupervised Video Understanding by Reconciliation of Posture Similarities +Timo Milbich, Miguel Bautista, Ekaterina Sutter, Bj¨orn Ommer +Heidelberg Collaboratory for Image Processing +IWR, Heidelberg University, Germany +{timo.milbich, miguel.bautista, ekaterina.sutter,"
+951af0494e8812fdb7d578b68c342ab876acb27e,THÈSE DE DOCTORAT DE L’ÉCOLE NORMALE SUPÉRIEURE DE CACHAN présentée par JULIEN MAIRAL pour obtenir le grade de DOCTEUR DE L’ÉCOLE NORMALE,"THÈSEDEDOCTORATDEL’ÉCOLENORMALESUPÉRIEUREDECACHANprésentéeparJULIENMAIRALpourobtenirlegradedeDOCTEURDEL’ÉCOLENORMALESUPÉRIEUREDECACHANDomaine:MATHÉMATIQUESAPPLIQUÉESSujetdelathèse:Représentationsparcimonieusesenapprentissagestatistique,traitementd’imageetvisionparordinateur—Sparsecodingformachinelearning,imageprocessingandcomputervisionThèseprésentéeetsoutenueàCachanle30novembre2010devantlejurycomposéde:FrancisBACHDirecteurderecherche,INRIAParis-RocquencourtDirecteurdethèseStéphaneMALLATProfesseur,EcolePolytechnique,New-YorkUniversityRapporteurEricMOULINESProfesseur,Télécom-ParisTechExaminateurBrunoOLSHAUSENProfesseur,UniversityofCalifornia,BerkeleyRapporteurJeanPONCEProfesseur,EcoleNormaleSupérieure,ParisDirecteurdethèseGuillermoSAPIROProfesseur,UniversityofMinnesotaExaminateurJean-PhilippeVERTDirecteurderecherche,EcolesdesMines-ParisTechExaminateurThèsepréparéeauseindel’équipeWillowdulaboratored’informatiquedel’ÉcoleNormaleSupérieure,Paris.(INRIA/ENS/CNRSUMR8548).23avenued’Italie,75214Paris."
95ea564bd983129ddb5535a6741e72bb1162c779,Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection,"Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection Ludovic Trottier Philippe Giguère Brahim Chaib-draa Laval University, Québec, Canada"
+9561c7ef4f89019eb7fb779a7b18ef810964b491,Real-Time Object Segmentation Using a Bag of Features Approach,"Real-Time Object Segmentation Using a +Bag of Features Approach +David ALDAVERT a,1, Arnau RAMISA c,b, Ramon LOPEZ DE MANTARAS b and +Ricardo TOLEDO a +Computer Vision Center, Dept. Ciencies de la Computació, Universitat Autonòma de +Barcelona, Catalunya, Spain +Institut d’Investigació d’Inteligencia Artificial (IIIA-CSIC), Campus UAB, Catalunya, +Spain +INRIA-Grenoble, LEAR Team, France"
+95029b1041a169e5b4e1ad79f60bfedb7a6844d0,Learning Superpixels with Segmentation-Aware Affinity Loss,"Learning Superpixels with Segmentation-Aware Affinity Loss +Wei-Chih Tu1 Ming-Yu Liu2 Varun Jampani2 Deqing Sun2 Shao-Yi Chien1 Ming-Hsuan Yang2 +Jan Kautz2 +National Taiwan University 2NVIDIA 3UC Merced"
958c599a6f01678513849637bec5dc5dba592394,Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data,"Noname manuscript No. (will be inserted by the editor) Generalized Zero-Shot Learning for Action @@ -188,6 +800,27 @@ Recognition with Web-Scale Video Data Kun Liu · Wu Liu · Huadong Ma · Wenbing Huang · Xiongxiong Dong Received: date / Accepted: date"
+950cfcbaafad1e2aaae43728fe499d8a4c90f6ec,Object Instance Detection and Dynamics Modeling in a Long-Term Mobile Robot Context,"Object Instance Detection and Dynamics Modeling in +Long-Term Mobile Robot Context +NILS BORE +Doctoral Thesis +Stockholm, Sweden 2017"
+955dc25def91eff6bfa5698249bb189ccfa83367,Geometric Model for Human Body Orientation Classification,"CommIT (Communication and Information Technology) Journal, Vol. 9 No. 1, pp. 29–33 +GEOMETRIC MODEL FOR HUMAN +BODY ORIENTATION CLASSIFICATION +Igi Ardiyanto +Department of Electrical Engineering and Information Technology, +Faculty of Engineering, Gadjah Mada University +Yogyakarta 55281, Indonesia +Email:"
+95aa80cf672771730393e1d7d263ab6f6d6e535d,Learning articulated body models for people re-identification,"Learning Articulated Body Models +for People Re-identification +Davide Baltieri, Roberto Vezzani, Rita Cucchiara +University of Modena and Reggio Emilia +Via Vignolese 905, 41125 Modena - Italy +{davide.baltieri, roberto.vezzani,"
+59b11427853b7892a9f0d8ab6683d96ce59c2ff2,A Multi-Face Challenging Dataset for Robust Face Recognition,"A Multi-Face Challenging Dataset for Robust Face Recognition +Shiv Ram Dubey and Snehasis Mukherjee"
59fc69b3bc4759eef1347161e1248e886702f8f7,Final Report of Final Year Project HKU-Face : A Large Scale Dataset for Deep Face Recognition,"Final Report of Final Year Project HKU-Face: A Large Scale Dataset for Deep Face Recognition @@ -195,6 +828,26 @@ Haoyu Li 035141841 COMP4801 Final Year Project Project Code: 17007"
+59bdd317abe8d87fb525eb4e3197a9311e2766e7,Demystifying Unsupervised Feature Learning a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"DEMYSTIFYING UNSUPERVISED FEATURE LEARNING +A DISSERTATION +SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE +AND THE COMMITTEE ON GRADUATE STUDIES +OF STANFORD UNIVERSITY +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +DOCTOR OF PHILOSOPHY +Adam Coates +September 2012"
+59ef1efb9239a101c2782fab8adc09b7af07d336,Cross-Domain Image Matching with Deep Feature Maps,"Cross-Domain Image Matching with Deep Feature Maps +Bailey Kong · James Supan˘ci˘c, III · Deva Ramanan · Charless C. +Fowlkes +Received: date / Accepted: date"
+59b71e19819c1c6aee98020b34bf92e605f33819,Max-min convolutional neural networks for image classification,"MAX-MIN CONVOLUTIONAL NEURAL NETWORKS FOR IMAGE CLASSIFICATION +Michael Blot, Matthieu Cord, Nicolas Thome +Sorbonne Universit´es, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 4 place Jussieu 75005 Paris"
+59cca46a0442fc6bd0525e5f13cef5b5a9747d34,Cross-Domain Shoe Retrieval With a Semantic Hierarchy of Attribute Classification Network,"Cross-Domain Shoe Retrieval With a Semantic +Hierarchy of Attribute Classification Network +Huijing Zhan, Student Member, IEEE, Boxin Shi, Member, IEEE, and Alex C. Kot, Fellow, IEEE"
59bfeac0635d3f1f4891106ae0262b81841b06e4,Face Verification Using the LARK Face Representation,"Face Verification Using the LARK Face Representation Hae Jong Seo, Student Member, IEEE, Peyman Milanfar, Fellow, IEEE,"
@@ -204,11 +857,76 @@ Devendra Pratap Yadav Indian Institute of Technology Ropar Abhinav Dhall Indian Institute of Technology Ropar"
+59b21f61ac46e1f982cbd9f49cb855ba5fcd3c45,CCNY at TRECVID 2014: Surveillance Event Detection,"CCNY at TRECVID 2014: Surveillance Event Detection +Yang Xian, Xuejian Rong, Xiaodong Yang, and Yingli Tian +Graduate Center and City College +City University of New York +{xrong, xyang02,"
+59f8d0e79eb02c30a5f872038129c4b5dd9bc73a,Design of a Face Recognition System for Security Control,"International Conference on African Development Issues (CU-ICADI) 2015: Information and Communication Teclmology Track +Design of a Face Recognition System for Security +Control +Ambrose A. Azeta, Nicholas A. Omoregbe, Adewole Adewumi, Dolapo Oguntade +Department of Computer and Information Sciences, +Covenant University, +Ota, Ogun-State, Nigeria"
+598f330fc061852162f2aaaf59ea9a3a55d3f6f7,A new strategy based on spatiogram similarity association for multi-pedestrian tracking,"A NEW STRATEGY BASED ON SPATIOGRAM +SIMILARITY ASSOCIATION FOR +MULTI-PEDESTRIAN TRACKING +Nabila MANSOURI1 5, Yousra BEN JEMAA2, Cina MOTAMED 3, Antonio PINTI 4 and Eric WATELAIN1 6 +University of Lille North of France, UVHC, LAMIH laboratory +e-mail: +University of Sfax-Tunisie, U2S laboratory +e-mail: +University of Lille North of France, ULCO, LISIC laboratory +e-mail: +University of Orleans -France, I3MTO laboratory +e-mail: +5 University of Sfax-Tunisie, ReDCAD laboratory +6 University of south Toulon-Var, HandiBio laboratory"
+595d0fe1c259c02069075d8c687210211908c3ed,A Survey on Learning to Hash,"A Survey on Learning to Hash +Jingdong Wang, Ting Zhang, Jingkuan Song, Nicu Sebe, and Heng Tao Shen"
+5921d9a8e143b6d82a2722d9ee27bafa363475f0,Driving Policy Transfer via Modularity and Abstraction,
+599b7e1b4460c8ad77def2330ec76a2e0dfedb84,Robust Subspace Clustering via Smoothed Rank Approximation,"Robust Subspace Clustering via Smoothed Rank +Approximation +Zhao Kang, Chong Peng, and Qiang Cheng∗"
59eefa01c067a33a0b9bad31c882e2710748ea24,Fast Landmark Localization with 3D Component Reconstruction and CNN for Cross-Pose Recognition,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY Fast Landmark Localization with 3D Component Reconstruction and CNN for Cross-Pose Recognition Gee-Sern (Jison) Hsu, Hung-Cheng Shie, Cheng-Hua Hsieh"
+59e266adc3525b4325156f0cc0052c1d76b1c9ae,Contextual Spatial Analysis and Processing for Visual Surveillance Applications,"Contextual Spatial Analysis and Processing +for Visual Surveillance Applications +Vikas Reddy +A thesis submitted for the degree of Doctor of Philosophy at +The University of Queensland in September 2011 +(revised in March 2012) +School of Information Technology and Electrical Engineering"
+5911dcef05ffec02cc1dd88ec6feb1f1e0e8bdcb,Happy Companion: A System of Multimodal Human-Computer Affective Interaction,"Happy Companion: A System of Multimodal Human-Computer +Affective Interaction +Jia Jia1,2,3, Lianhong Cai1,2,3, Sirui Wang4, Xiaolan Fu4 +State Key Laboratory on Intelligent Technology and Systems"
+5955bb0325ec4dd3b56759aeb96cc9c18b09bf3e,Self-Supervised Depth Learning Improves Semantic Segmentation,"Self-Supervised Depth Learning Improves Semantic Segmentation +Huaizu Jiang, Erik Learned-Miller +Univ. of Massachusetts, Amherst +Amherst MA 01003 +. Introduction +How does a newborn agent learn about the world? +When an animal (or robot) moves, its visual system is +exposed to a shower of information. Usually, the speed +with which something moves in the image is inversely +proportional to its depth.1 As an agent continues to +experience visual stimuli under its own motion, it is +natural for it to form associations between the appear- +nce of objects and their relative motion in the image. +For example, an agent may learn that objects that look +like mountains typically don’t move in the image (or +hange appearance much) as the agent moves. Objects +like nearby cars and people, however, appear to move +rapidly in the image as the agent changes position rel- +tive to them. This continuous pairing of images with +motion acts as a kind of “automatic” supervision that"
+591bd78a06814e75cae7cdef50ad91cf22e66c23,3D face recognition based on evolution of iso-geodesic distance curves,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE +ICASSP 2010"
59d225486161b43b7bf6919b4a4b4113eb50f039,Complex Event Recognition from Images with Few Training Examples,"Complex Event Recognition from Images with Few Training Examples Unaiza Ahsan∗ Chen Sun∗∗ @@ -216,6 +934,17 @@ James Hays∗ Irfan Essa∗ *Georgia Institute of Technology **University of Southern California1"
+59945763707557baace208253c029265b4b6e0a9,Face Recognition under Partial Occlusion and Small Dense Noise a Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Technology,"FACE RECOGNITION UNDER PARTIAL +OCCLUSION AND SMALL DENSE NOISE +A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE +REQUIREMENTS FOR THE DEGREE OF +MASTER OF TECHNOLOGY +ELECTRONIC SYSTEMS AND COMMUNICATIONS +ROHIT KUMAR +ROLL NO. -212EE1210 +Department of Electrical Engineering +National Institute of Technology, Rourkela-769008 +| P a g e"
5945464d47549e8dcaec37ad41471aa70001907f,Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos,"Noname manuscript No. (will be inserted by the editor) Every Moment Counts: Dense Detailed Labeling of Actions in Complex @@ -243,19 +972,72 @@ Composites to Mugshots Scott J. Klum, Student Member, IEEE, Hu Han, Member, IEEE, Brendan F. Klare, Member, IEEE, nd Anil K. Jain, Fellow, IEEE tedious, and may not"
+598ccf73ba504a31d65b50c7ede8982c3b1d9192,Learning a Family of Detectors,"LEARNING A FAMILY OF DETECTORS +QUAN YUAN +Dissertation submitted in partial fulfillment +of the requirements for the degree of +Doctor of Philosophy +BOSTON +UNIVERSITY"
59f325e63f21b95d2b4e2700c461f0136aecc171,Kernel sparse representation with local patterns for face recognition,"978-1-4577-1302-6/11/$26.00 ©2011 IEEE FOR FACE RECOGNITION . INTRODUCTION"
+59b202ccc01bae85a88ad0699da7a8ae6aa50fef,"Looking at Vehicles on the Road: A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis","Looking at Vehicles on the Road: A Survey of +Vision-Based Vehicle Detection, Tracking, +nd Behavior Analysis +Sayanan Sivaraman, Member, IEEE, and Mohan Manubhai Trivedi, Fellow, IEEE"
+590065c40574dc797e5aeb380d6e6dab79fad6e5,Face Detection Using Boosted Jaccard Distance-based Regression,"FACE DETECTION USING BOOSTED +JACCARD DISTANCE-BASED REGRESSION +Cosmin Atanasoaei Chris McCool +Sébastien Marcel +Idiap-RR-02-2012 +JANUARY 2012 +Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny +T +41 27 721 77 11 F +41 27 721 77 12 www.idiap.ch"
+590a52702bdf7f9522cff02f477de1fa98fc2ff3,"Visual tracking of hands, faces and facial features of multiple persons","DOI 10.1007/s00138-012-0409-5 +ORIGINAL PAPER +Visual tracking of hands, faces and facial features +of multiple persons +Haris Baltzakis · Maria Pateraki · Panos Trahanias +Received: 17 November 2010 / Revised: 9 December 2011 / Accepted: 18 January 2012 +© Springer-Verlag 2012"
+590c277e8ca10f2c2d7e32eb4a9dc61078a67b96,Statistical Approaches to Face Recognition a Qualifying Examination Report,"StatisticalApproachesTo +FaceRecognition +AQualifyingExaminationReport +AraV.Ne(cid:12)an +PresentedtotheQualifyingExaminationCommittee +InPartialFul(cid:12)llmentoftheRequirementsforthe +DegreeofDoctorofPhilosophyinElectricalEngineering +Dr.AlbinJ.Gasiewski +Dr.Je(cid:11)Geronimo +Dr.MonsonH.HayesIII +Dr.RussellM.Mersereau +Dr.RonaldW.Schafer +GeorgiaInstituteofTechnology +SchoolofElectricalEngineering +December, "
59031a35b0727925f8c47c3b2194224323489d68,Sparse Variation Dictionary Learning for Face Recognition with a Single Training Sample per Person,"Sparse Variation Dictionary Learning for Face Recognition with A Single Training Sample Per Person Meng Yang, Luc Van Gool ETH Zurich Switzerland"
+59ee327192c270fc727c5f6d2ef90058ed072b14,Motion Models for People Tracking,"Motion Models for People Tracking +David J. Fleet"
926c67a611824bc5ba67db11db9c05626e79de96,Enhancing Bilinear Subspace Learning by Element Rearrangement,"Enhancing Bilinear Subspace Learning y Element Rearrangement Dong Xu, Shuicheng Yan, Stephen Lin, Thomas S. Huang, and Shih-Fu Chang"
+923412acb90ed2acbb29290147a567f39d2dfc95,FACSGen: A Tool to Synthesize Emotional Facial Expressions Through Systematic Manipulation of Facial Action Units,"J Nonverbal Behav +DOI 10.1007/s10919-010-0095-9 +O R I G I N A L P A P E R +FACSGen: A Tool to Synthesize Emotional Facial +Expressions Through Systematic Manipulation of Facial +Action Units +Etienne B. Roesch • Lucas Tamarit • +Lionel Reveret • Didier Grandjean • +David Sander • Klaus R. Scherer +Ó Springer Science+Business Media, LLC 2010"
923ede53b0842619831e94c7150e0fc4104e62f7,Masked correlation filters for partially occluded face recognition,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE ICASSP 2016"
92b61b09d2eed4937058d0f9494d9efeddc39002,BoxCars: Improving Vehicle Fine-Grained Recognition using 3D Bounding Boxes in Traffic Surveillance,"Under review in IJCV manuscript No. @@ -264,6 +1046,34 @@ BoxCars: Improving Vehicle Fine-Grained Recognition using D Bounding Boxes in Traffic Surveillance Jakub Sochor · Jakub ˇSpaˇnhel · Adam Herout Received: date / Accepted: date"
+923e9b437a55853120f1778f55fcd956d81260f8,Zoom Out-and-In Network with Map Attention Decision for Region Proposal and Object Detection,"Noname manuscript No. +(will be inserted by the editor) +Zoom Out-and-In Network with Map Attention Decision +for Region Proposal and Object Detection +Hongyang Li · Yu Liu · Wanli Ouyang · Xiaogang Wang +Received: date / Accepted: date"
+92020e6540fe9feb38616334645a0ba28dcac69d,Face Recognition Based on Local Derivative Tetra Pattern,"ISSN: 0976-9102 (ONLINE) +ICTACT JOURNAL ON IMAGE AND VIDEO PROCESSING, FEBRUARY 2017, VOLUME: 07, ISSUE: 03 +FACE RECOGNITION BASED ON LOCAL DERIVATIVE TETRA PATTERN +A. Geetha1, M. Mohamed Sathik2 and Y. Jacob Vetharaj3 +Department of Computer Applications, Nesamony Memorial Christian College, India +Department of Computer Science, Sadakathullah Appa College, India +Department of Computer Science, Nesamony Memorial Christian College, India"
+92b748f2629b3227a9c56bc9e580f45eb5bdfba5,Novel Adaptive Eye Detection and Tracking for Challenging Lighting Conditions,"Version +This is the Accepted Manuscript version. This version is defined in the NISO +recommended practice RP-8-2008 http://www.niso.org/publications/rp/ +Suggested Reference +Rezaei, M., & Klette, R. (2013). Novel Adaptive Eye Detection and Tracking for +Challenging Lighting Conditions. In Lecture Notes in Computer Science Vol. 7729 +(pp. 427-440). Daejeon, Korea: Springer Berlin Heidelberg. +The final publication is available at Springer via http://dx.doi.org/10.1007/978-3- +642-37484-5_35 +Copyright +Items in ResearchSpace are protected by copyright, with all rights reserved, unless +otherwise indicated. Previously published items are made available in accordance +with the copyright policy of the publisher. +http://www.sherpa.ac.uk/romeo/issn/0302-9743/ +https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"
920a92900fbff22fdaaef4b128ca3ca8e8d54c3e,Learning Pattern Transformation Manifolds with Parametric Atom Selection,"LEARNING PATTERN TRANSFORMATION MANIFOLDS WITH PARAMETRIC ATOM SELECTION Elif Vural and Pascal Frossard @@ -286,6 +1096,11 @@ Benjamin Drayer and Thomas Brox Department of Computer Science, Centre of Biological Signalling Studies (BIOSS), University of Freiburg, Germany"
+927ac98da38db528b780f14996bb02b05009c9cc,Hand pose estimation through semi-supervised and weakly-supervised learning,"Hand Pose Estimation through Semi-Supervised and Weakly-Supervised Learning +Natalia Neverovaa,∗, Christian Wolfa, Florian Neboutb, Graham W. Taylorc +Universit´e de Lyon, INSA-Lyon, CNRS, LIRIS, F-69621, France +Awabot SAS, France +School of Engineering, University of Guelph, Canada"
92c2dd6b3ac9227fce0a960093ca30678bceb364,On Color Texture Normalization for Active Appearance Models,"Provided by the author(s) and NUI Galway in accordance with publisher policies. Please cite the published version when available. Title @@ -306,6 +1121,30 @@ version http://dx.doi.org/10.1109/TIP.2009.2017163 Item record http://hdl.handle.net/10379/1350"
+92679c8cff92442f39de3405c21c8028162fe56a,Temporal 3 D ConvNets using Temporal Transition Layer,"Temporal 3D ConvNets using Temporal Transition Layer +Ali Diba1 +, Mohsen Fayyaz2, Vivek Sharma3, A.Hossein Karami4, M.Mahdi Arzani4, +Rahman Yousefzadeh4, Luc Van Gool1 +ESAT-PSI, KU Leuven, 2University of Bonn, 3CV:HCI, KIT, Karlsruhe, 4Sensifai"
+92373095869f1b9e93823f0bd16bb8527c1665dc,How face blurring affects body language processing of static gestures in women and men,"Social Cognitive and Affective Neuroscience, 2018, 590–603 +doi: 10.1093/scan/nsy033 +Advance Access Publication Date: 14 May 2018 +Original article +How face blurring affects body language processing +of static gestures in women and men +Alice Mado Proverbio, Laura Ornaghi, and Veronica Gabaro +Department of Psychology, Neuro-MI Center for Neuroscience, University of Milano-Bicocca, Milano, Italy +Correspondence should be addressed to Alice Mado Proverbio, Department of Psychology, University of Milano-Bicocca, piazza dell’Ateneo Nuovo 1, U6 +Building, Milano, Italy. E-mail:"
+92a93693f43a49a7b320d5771c6afaff98b27864,Audio-visual signal processing in a multimodal assisted living environment,"INTERSPEECH 2014 +Audio-Visual Signal Processing in a Multimodal Assisted Living Environment +Alexey Karpov 1,5, Lale Akarun 2, Hülya Yalçın 3, Alexander Ronzhin 1, Barış Evrim Demiröz 2, +Aysun Çoban 2 and Miloš Železný 4 +St. Petersburg Institute for Informatics and Automation of Russian Academy of Sciences, Russia +Boğaziçi University, İstanbul, Turkey +İstanbul Technical University, İstanbul, Turkey +University of West Bohemia, Pilsen, Czech Republic +5 University ITMO, St. Petersburg, Russia"
927ba64123bd4a8a31163956b3d1765eb61e4426,Customer satisfaction measuring based on the most significant facial emotion,"Customer satisfaction measuring based on the most significant facial emotion Mariem Slim, Rostom Kachouri, Ahmed Atitallah @@ -326,6 +1165,29 @@ L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de"
+92f0e02c9f4e95098452d0fd78ba46cd6e7b1f6d,Dynamic machine learning for supervised and unsupervised classification. (Apprentissage automatique dynamique pour la classification supervisée et non supervisée),"Dynamic machine learning for supervised and +unsupervised classification +Adela-Maria Sîrbu +To cite this version: +Adela-Maria Sîrbu. Dynamic machine learning for supervised and unsupervised classification. Machine +Learning [cs.LG]. INSA de Rouen, 2016. English. <NNT : 2016ISAM0002>. <tel-01402052> +HAL Id: tel-01402052 +https://tel.archives-ouvertes.fr/tel-01402052 +Submitted on 24 Nov 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de +recherche français ou étrangers, des laboratoires"
+9263ca6211ec39469f0daa8790ccaecbd5898423,Exploring Models and Data for Remote Sensing Image Caption Generation,"Exploring Models and Data for +Remote Sensing Image Caption Generation +Xiaoqiang Lu, Senior Member, IEEE, Binqiang Wang, Xiangtao Zheng, and Xuelong Li, Fellow, IEEE"
927ad0dceacce2bb482b96f42f2fe2ad1873f37a,Interest-Point based Face Recognition System,"Interest-Point based Face Recognition System Interest-Point based Face Recognition System Cesar Fernandez and Maria Asuncion Vicente @@ -346,6 +1208,17 @@ database of known criminals. The ideal behaviour of an automatic system performi task would be to get a 100% correct identification rate, but this behaviour is far from the apabilities of current face recognition algorithms. Assuming that there will be false identifications, supervised surveillance systems seem to be the most realistic option: the"
+92a044df6c37571aac25756252dda27676492bb5,Implementation of Real-time System on Fpga Board for Human's Face Detection and Tracking Author Mohd,"IMPLEMENTATION OF REAL-TIME SYSTEM ON FPGA BOARD FOR HUMAN'S +FACE DETECTION AND TRACKING AUTHOR +MOHD NORHAFIZ HASHIM +A project report submitted in partial +Fulfillment of the requirement for the award of the +Degree of Master Electrical Engineering +Fakulti Kejuruteraan Elektrik dan Elektronik +Universiti Tun Hussein Onn Malaysia +JANUARY 2014"
+921aaac9b33ec6a417bfc8bb0e21e11e743342c2,Image enhancement for improving face detection under non-uniform lighting conditions,"978-1-4244-1764-3/08/$25.00 ©2008 IEEE +ICIP 2008"
929bd1d11d4f9cbc638779fbaf958f0efb82e603,"Improving the Performance of Facial Expression Recognition Using Dynamic, Subtle and Regional Features","This is the author’s version of a work that was submitted/accepted for pub- lication in the following source: Zhang, Ligang & Tjondronegoro, Dian W. (2010) Improving the perfor- @@ -362,12 +1235,73 @@ Notice: Changes introduced as a result of publishing processes such as opy-editing and formatting may not be reflected in this document. For a definitive version of this work, please refer to the published source: http://dx.doi.org/10.1007/978-3-642-17534-3_72"
+92980965514210b4f6dd074d122078d54684f724,Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition,"Track Everything: Limiting Prior Knowledge in +Online Multi-Object Recognition +Sebastien C. Wong∗, Senior Member, IEEE, Victor Stamatescu†, Member, IEEE, Adam Gatt‡, Member, IEEE, +David Kearney†, Ivan Lee† Senior Member, IEEE and Mark D. McDonnell†, Senior Member, IEEE ∗ Defence +Science and Technology Group, Edinburgh, SA, Australia † Computational Learning Systems Laboratory, School +of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA, +Australia ‡ Australian Defence Force, Edinburgh, SA, Australia +An important practical consideration in the design of online +object recognition systems is the finite amount of labeled and +nnotated data available for training. When scarce, this can de- +grade classification performance due to overfitting and reduce +the detection probability of highly tuned object detectors. Even +when larger data sets are available, these may be biased in such +way that their image statistics do not accurately reflect the +data encountered by the system at run time [2]. In the case +of classifier-based object recognition [3] and detection [4], the +use of features, which are higher-level representations of an +object than the raw image, can mitigate these problems by +providing a degree of invariance across different data sets. +In the case of tracking and object detection algorithms, the"
+926ca7ce14332f9f848c28565d0f2f9a2d1e35a8,Impaired facial and vocal emotion decoding in schizophrenia is underpinned by basic perceptivo-motor deficits,"Cognitive Neuropsychiatry +ISSN: 1354-6805 (Print) 1464-0619 (Online) Journal homepage: http://www.tandfonline.com/loi/pcnp20 +Impaired facial and vocal emotion decoding in +schizophrenia is underpinned by basic perceptivo- +motor deficits +C. Mangelinckx, J. B. Belge, P. Maurage & E. Constant +To cite this article: C. Mangelinckx, J. B. Belge, P. Maurage & E. Constant (2017): Impaired facial +nd vocal emotion decoding in schizophrenia is underpinned by basic perceptivo-motor deficits, +Cognitive Neuropsychiatry, DOI: 10.1080/13546805.2017.1382342 +To link to this article: http://dx.doi.org/10.1080/13546805.2017.1382342 +Published online: 03 Oct 2017. +Submit your article to this journal +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pcnp20 +Download by: [University of Virginia, Charlottesville] +Date: 06 October 2017, At: 09:26"
0cb7e4c2f6355c73bfc8e6d5cdfad26f3fde0baf,F Acial E Xpression R Ecognition Based on Wapa and Oepa F Ast Ica,"International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 5, No. 3, May 2014 FACIAL EXPRESSION RECOGNITION BASED ON WAPA AND OEPA FASTICA Humayra Binte Ali1 and David M W Powers2 Computer Science, Engineering and Mathematics School, Flinders University, Australia Computer Science, Engineering and Mathematics School, Flinders University, Australia"
+0c5a2bb5d1a1e9bb332207be61e13d0afb8f278c,A Supervised Learning Methodology for Real-Time Disguised Face Recognition in the Wild,"A Supervised Learning Methodology for Real-Time Disguised Face +Recognition in the Wild +Saumya Kumaar3, Abhinandan Dogra4, Abrar Majeedi4, Hanan Gani4, Ravi M. Vishwanath2 and S N Omkar1"
+0c24ccc6d6c386a8d555a81166eaf6e8d4dfccc3,Person count localization in videos from noisy foreground and detections,"Person Count Localization in Videos from Noisy Foreground and Detections +Sheng Chen1, Alan Fern1, Sinisa Todorovic1 +Oregon State University. +In this paper, we introduce a new problem, person count localization from +noisy foreground and person detections. Our formulation strikes a middle- +ground between person detection and frame-level counting. Given a video, +our goal is to output for each frame a set of: +. Detections optimally covering both isolated individuals and crowds +of people in the video; and +. Counts assigned to each detection indicating the number of people +inside. +The problem of detecting people in videos of crowded scenes, where +people frequently appear under severe occlusion by other people in the +rowd is an important line of research, since detecting people in video frames +has become the standard initial step of many approaches to activity recogni- +tion [1, 3, 4], and multi-object tracking by detection [6, 8, 9]. They typically +use as input human appearance, pose, and orientation, and thus critically +depend on robust person detections. In many domains, however, such as +videos of American football or public spaces crowded with pedestrians, de- +tecting every individual person is highly unreliable, and remains an open"
0c8a0a81481ceb304bd7796e12f5d5fa869ee448,A Spatial Regularization of LDA for Face Recognition,"International Journal of Fuzzy Logic and Intelligent Systems, vol. 10, no. 2, June 2010, pp. 95-100 A Spatial Regularization of LDA for Face Recognition Lae-Jeong Park @@ -385,12 +1319,89 @@ Figure1.Face detection results of FDNet1.0" Mixtures and Cascaded Deformable Model Xiang Yu, Member, IEEE, Junzhou Huang, Member, IEEE, Shaoting Zhang, Senior Member, IEEE, and Dimitris N. Metaxas, Fellow, IEEE"
+0c769c19d894e0dbd6eb314781dc1db3c626df57,Joint Detection and Identification Feature Learning for Person Search,"Joint Detection and Identification Feature Learning for Person Search +Tong Xiao1∗ Shuang Li1∗ Bochao Wang2 Liang Lin2 Xiaogang Wang1 +The Chinese University of Hong Kong 2Sun Yat-Sen University"
+0cdac46ec42be2d81f64ec4ee53d88be43290d52,Temporal Poselets for Collective Activity Detection and Recognition,"Temporal Poselets for Collective Activity Detection and Recognition +Moin Nabi +Alessio Del Bue +Vittorio Murino +Pattern Analysis and Computer Vision (PAVIS) +Istituto Italiano di Tecnologia (IIT) +Via Morego 30, Genova, Italy"
+0c3c469e46668ea2c38a6de610d675975f337522,Self-tuned Visual Subclass Learning with Shared Samples An Incremental Approach,"Self-tuned Visual Subclass Learning with Shared Samples +An Incremental Approach +Updated ICCV 2013 Submission +Hossein Azizpour +Royal Insitute of Technology(KTH) +Stefan Carlsson +Royal Insitute of Technology(KTH)"
+0c95ff762bdf6a20609f49f1eb5248de3f748866,Fine-Grained Walking Activity Recognition via Driving Recorder Dataset,"Fine-grained Walking Activity Recognition +via Driving Recorder Dataset +Hirokatsu Kataoka (AIST), Yoshimitsu Aoki (Keio Univ.), Yutaka Satoh (AIST) +Shoko Oikawa (NTSEL), Yasuhiro Matsui (NTSEL) +Email: +http://hirokatsukataoka.net/"
+0ca96dc1557032ff9259562a5b8fc026334997a6,Spectral Graph-Based Method of Multimodal Word Embedding,"Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing, ACL 2017, pages 39–44, +Vancouver, Canada, August 3, 2017. c(cid:13)2017 Association for Computational Linguistics"
+0c049cc7320f9b92f91210ab6961aa6644c867cd,Delving Deep Into Coarse-to-Fine Framework for Facial Landmark Localization,"Delving Deep into Coarse-to-fine Framework +for Facial Landmark Localization +Xi Chen, Erjin Zhou, Yuchen Mo, Jiancheng Liu, Zhimin Cao +Megvii Research +{chenxi, zej, moyuchen, liujiancheng,"
0ca36ecaf4015ca4095e07f0302d28a5d9424254,Improving Bag-of-Visual-Words Towards Effective Facial Expressive Image Classification,"Improving Bag-of-Visual-Words Towards Effective Facial Expressive Image Classification Dawood Al Chanti1 and Alice Caplier1 Univ. Grenoble Alpes, CNRS, Grenoble INP∗ , GIPSA-lab, 38000 Grenoble, France Keywords: BoVW, k-means++, Relative Conjunction Matrix, SIFT, Spatial Pyramids, TF.IDF."
+0cc2fc148eef46c1141edd276d903853052fc19d,Estado del arte en reconocimiento facial,"Estado del arte en reconocimiento facial +Martín Adrián Garduño Santana, L. E. Díaz-Sánchez, Israel Tabarez Paz, +Marcelo Romero Huertas +Universidad Autónoma del Estado de México, Toluca, México +Resumen. En este trabajo se resumen los métodos más utilizados para el +reconocimiento facial, incluyendo las ventajas y desventajas de los sistemas +desarrollados hasta ahora. También se describen las futuras líneas de +investigación y se discute el rumbo del reconocimiento facial en los próximos +ños. Esta revisión es relevante pues se busca la implementación de un novedoso +sistema de reconocimiento facial. +Palabras clave: reconocimiento facial, sistemas biométricos, ciudades +inteligentes, imágenes 2D y 3D. +Face Recognition: a Survey"
+0c8d675bcd4489e886f35bee2a347c948ffee270,Semantic bottleneck for computer vision tasks,"Semantic bottleneck for computer vision tasks +Maxime Bucher1,2, St´ephane Herbin1, and Fr´ed´eric Jurie2 +ONERA, Universit´e Paris-Saclay, FR-91123 Palaiseau, France +Normandie Univ, UNICAEN, ENSICAEN, CNRS"
+0c3c83b7f030fe661548d362ddf33f37bb44043d,Crowd Motion Analysis Based on Social Force Graph with Streak Flow Attribute,"Hindawi Publishing Corporation +Journal of Electrical and Computer Engineering +Volume 2015, Article ID 492051, 12 pages +http://dx.doi.org/10.1155/2015/492051 +Research Article +Crowd Motion Analysis Based on Social Force Graph with +Streak Flow Attribute +Shaonian Huang,1,2 Dongjun Huang,1 and Mansoor Ahmed Khuhro1 +School of Information Science and Engineering, Central South University, Changsha 410083, China +School of Computer and Information Engineering, Hunan University of Commerce, Changsha 420005, China +Correspondence should be addressed to Shaonian Huang; +Received 28 July 2015; Accepted 27 September 2015 +Academic Editor: Stefano Basagni +Copyright © 2015 Shaonian Huang et al. This is an open access article distributed under the Creative Commons Attribution +License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly +ited. +Over the past decades, crowd management has attracted a great deal of attention in the area of video surveillance. Among various +tasks of video surveillance analysis, crowd motion analysis is the basis of numerous subsequent applications of surveillance video. +In this paper, a novel social force graph with streak flow attribute is proposed to capture the global spatiotemporal changes and +the local motion of crowd video. Crowd motion analysis is hereby implemented based on the characteristics of social force graph."
+0c17c42d71eacd2244e43fa55a8ed96607337cca,Automatic Face Reenactment,"Automatic Face Reenactment +Pablo Garrido1 +Thorsten Thorm¨ahlen2 +Levi Valgaerts1 +Patrick P´erez3 +Ole Rehmsen1 +Christian Theobalt1 +Philipps-Universit¨at Marburg +Technicolor +MPI for Informatics"
0cfca73806f443188632266513bac6aaf6923fa8,Predictive Uncertainty in Large Scale Classification using Dropout - Stochastic Gradient Hamiltonian Monte Carlo,"Predictive Uncertainty in Large Scale Classification using Dropout - Stochastic Gradient Hamiltonian Monte Carlo. @@ -398,6 +1409,29 @@ Vergara, Diego∗1, Hern´andez, Sergio∗2, Valdenegro-Toro, Mat´ıas∗∗3 a Laboratorio de Procesamiento de Informaci´on Geoespacial, Universidad Cat´olica del Maule, Chile. German Research Centre for Artificial Intelligence, Bremen, Germany. Email:"
+0cd032a93890d61b9bd187119abee0d6aeb899f7,Iterative Quantization: A Procrustean Approach to Learning Binary Codes for Large-Scale Image Retrieval,"IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +Iterative Quantization: +A Procrustean Approach to Learning Binary +Codes for Large-scale Image Retrieval +Yunchao Gong, Svetlana Lazebnik, Albert Gordo, Florent Perronnin"
+0c5f9f5083b9fca4dcdbc4b122099ac1f630728b,Visual Semantic Role Labeling,"Visual Semantic Role Labeling +Saurabh Gupta +UC Berkeley +Jitendra Malik +UC Berkeley"
+0cec42a1593a02ce3f4a44d375e3b95f5797aa21,Recognizing Scene Categories of Historical Postcards,"Recognizing Scene Categories of Historical +Postcards +Rene Grzeszick, Gernot A. Fink +{rene.grzeszick, +Department of Computer Science, TU Dortmund"
+0cff123a31dcc115377ecca6ba137bebca909ff8,Anxiety dissociates the adaptive functions of sensory and motor response enhancements to social threats,"RESEARCH ARTICLE +Anxiety dissociates the adaptive functions +of sensory and motor response +enhancements to social threats +Marwa El Zein1,2*, Valentin Wyart1†, Julie Gre` zes1† +Laboratoire de Neurosciences Cognitives, De´ partement d’Etudes Cognitives, Ecole +Normale Supe´ rieure, PSL Research University, Paris, France; 2Universite´ Pierre et +Marie Curie, Paris, France"
0c3f7272a68c8e0aa6b92d132d1bf8541c062141,Kruskal-Wallis-Based Computationally Efficient Feature Selection for Face Recognition,"Hindawi Publishing Corporation e Scientific World Journal Volume 2014, Article ID 672630, 6 pages @@ -418,14 +1452,119 @@ which permits unrestricted use, distribution, and reproduction in any medium, pr Face recognition in today’s technological world, and face recognition applications attain much more importance. Most of the existing work used frontal face images to classify face image. However these techniques fail when applied on real world face images. The proposed technique effectively extracts the prominent facial features. Most of the features are redundant and do not contribute"
+0c87f5a6deba422c0db261c4497b9b013b4ef5b8,Robust Face Detection using Convolutional Neural Network,"International Journal of Computer Applications (0975 – 8887) +Volume 170 – No.6, July 2017 +Robust Face Detection using Convolutional +Robert Yao Aaronson +Sch. of Comp. Sci.& Tech +Jiangsu Univ. of Sci. & Tech. +No. 2 Mengxi Road Jingkou +District Zhenjiang Prov. 212003 +Neural Network +Wu Chen +Sch. of Comp. Sci. & Tech +Jiangsu Univ. of Sci. & Tech. +No. 2 Mengxi Road Jingkou +District Zhenjiang Prov. 212003 +Ben-Bright Benuwa +Sch. of Comp. Sci. & Comm. +Eng. Jiangsu Univ. Xuefu Road +01 Jingkou District Zhenjiang +Prov. 212003 +supported by"
+0ceda9dae8b9f322df65ca2ef02caca9758aec6f,Context-Aware CNNs for Person Head Detection,"Context-aware CNNs for person head detection +Tuan-Hung Vu∗ +Anton Osokin† +INRIA/ENS +Ivan Laptev∗"
+0c990e779067c563a79ae17c9d36094a745d7ed8,Model interpolation for eye localization using the Discriminative Generalized Hough Transform,"Model Interpolation for Eye Localization Using the +Discriminative Generalized Hough Transform +Ferdinand Hahmann, Heike Ruppertshofen, Gordon B¨oer, Hauke Schramm +Institute of Applied Computer Science +University of Applied Sciences Kiel +Grenzstraße 3 +4149 Kiel"
+0cfcc1cd8bae5f5899cef0995debd7b38c46e817,Discrete texture traces: Topological representation of geometric context,"Discrete Texture Traces: Topological Representation of Geometric Context +Jan Ernst∗ and Maneesh K. Singh +Siemens Corporation, Corporate Research and Technology, Princeton, NJ, USA +Department of Computer Science and Mathematics, Goethe University, Frankfurt am Main, Germany +Visvanathan Ramesh†"
+0cbefba0f41982bdff091d0e5f0d5ef93185a55c,"Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias, and Rolling Shutter Effect","Challenges in Monocular Visual Odometry: +Photometric Calibration, Motion Bias and +Rolling Shutter Effect +Nan Yang1,2,∗, Rui Wang1,2,∗, Xiang Gao1 and Daniel Cremers1,2"
+0ce4110d4c3d8b19ca0f7f75bc680aa9ba8d239a,Genetic Algorithms for Classifiers’ Training Sets Optimisation Applied to Human Face Recognition,"JOURNAL OF MEDICAL INFORMATICS & TECHNOLOGIES Vol. 11/2007, ISSN 1642-6037 +Michał KAWULOK* +GENETIC ALGORITHMS FOR CLASSIFIERS’ TRAINING SETS +OPTIMISATION APPLIED TO HUMAN FACE RECOGNITION +support vector machines, +genetic algorithms, +human face recognition +Human face recognition is a multi-stage process within which many classification problems must be +solved. This is performed by learning machines which elaborate classification rules based on a given training set. +Therefore, one of the most important issues is selection of a training set which would properly represent the data +that will be further classified. This paper presents an approach which utilizes genetic algorithms for selecting +lassifiers’ training sets. This approach was implemented for the Support Vector Machines which is applied in +two areas of automatic human face recognition: face verification and feature vectors comparison. Effectiveness +of the presented concept was confirmed with appropriate experiments which results are described in this paper. +. INTRODUCTION +Face recognition [7, 13, 14] is among the most popular biometric techniques which are +eing developed nowadays and it is worth noticing that this is the method which is the most +frequently used naturally by humans. Automatic face recognition is characterized by a low +level of required interaction with a person who is being recognized, but offers relatively low +effectiveness comparing to other biometric methods [4, 9]. A face recognition system"
+0c1d5801f2b86afa969524dc74708a78450300d9,12 : Conditional Random Fields,"0-708: Probabilistic Graphical Models 10-708, Spring 2014 +2 : Conditional Random Fields +Lecturer: Eric P. Xing +Scribes: Qin Gao, Siheng Chen +Hidden Markov Model +.1 General parametric form +In hidden Markov model (HMM), we have three sets of parameters, +t = 1|yi +transition probability matrix A : p(yj +initialprobabilities : p(y1) ∼ Multinomial(π1, π2, ..., πM ), +emission probabilities : p(xt|yi +t) ∼ Multinomial(bi,1, bi,2, ..., bi,K). +t−1 = 1) = ai,j, +.2 Inference +The inference can be done with forward algorithm which computes αk +) recursively by +t ≡ µt−1→t(k) = P (x1, ..., xt−1, xt, yk +nd the backward algorithm which computes βk +t = 1) recursively by +(cid:88)"
0c5afb209b647456e99ce42a6d9d177764f9a0dd,Recognizing Action Units for Facial Expression Analysis,"Recognizing Action Units for Facial Expression Analysis Ying-li Tian, Member, IEEE, Takeo Kanade, Fellow, IEEE, and Jeffrey F. Cohn, Member, IEEE"
+0c98defb5a83ea5dc5d90538d1cc8c4b6267a1cb,Perception of Dynamic Facial Expressions of Emotion: Electrophysiological Evidence,"Humboldt-Universität zu Berlin +Dissertation +Perception of Dynamic Facial Expressions +of Emotion: Electrophysiological Evidence +zur Erlangung des akademischen Grades Doctor rerum naturalium im Fach Psychologie +Mathematisch-Naturwisseschafttlichen Fakultät II +Guillermo Recio +Dekan: Prof. Dr. Dr. Elmar Kulke +Gutachter/in: 1. Prof. Dr. Werner Sommer +2. Prof. Dr. Annekathrin Schacht +3. Prof. Dr. Birgit Stürmer +Datum der Einreichung: +7.09.2012 +Datum der Promotion: +07.03.2013"
0c377fcbc3bbd35386b6ed4768beda7b5111eec6,A Unified Probabilistic Framework for Spontaneous Facial Action Modeling and Understanding,"A Unified Probabilistic Framework for Spontaneous Facial Action Modeling nd Understanding Yan Tong, Member, IEEE, Jixu Chen, Student Member, IEEE, and Qiang Ji, Senior Member, IEEE"
0cb2dd5f178e3a297a0c33068961018659d0f443,IARPA Janus Benchmark-B Face Dataset,"© 2017 Noblis, Inc. IARPA Janus Benchmark-B Face Dataset Cameron Whitelam, Emma Taborsky*, Austin Blanton, Brianna Maze*, Jocelyn Adams*, Tim Miller*, Nathan Kalka*, Anil K. Jain**, James A. Duncan*, Kristen Allen, Jordan Cheney*, Patrick Grother*** Noblis* Michigan State University** NIST*** 21 July 2017"
+0c1d40de56698e672d3906b96f47ae1361fc3912,Face recognition using kernel principal component analysis,"Advances in Vision Computing: An International Journal (AVC) Vol.1, No.1, March 2014 +Face Recognition Using Kernel +PrincipalComponent Analysis +Jayanthi T and 2Dr. Aji S +Assistant Professor,Department of Computer Applications, +Mohandas College of Engineering and Technology, Anad, Nedumangad +Thiruvananthapuram, India +Assistant Professor,Department of Computer Science,University of Kerala +Kariyavattom,Thiruvananthapuram, India"
0cd8895b4a8f16618686f622522726991ca2a324,Discrete Choice Models for Static Facial Expression Recognition,"Discrete Choice Models for Static Facial Expression Recognition Gianluca Antonini1, Matteo Sorci1, Michel Bierlaire2, and Jean-Philippe Thiran1 @@ -445,6 +1584,84 @@ Massachusetts Institute of Technology (MIT) Chalmers University of Technology, SAFER"
0c4659b35ec2518914da924e692deb37e96d6206,Registering a MultiSensor Ensemble of Images,"Registering a MultiSensor Ensemble of Images Jeff Orchard, Member, IEEE, and Richard Mann"
+0c53b45321131e61d1266cb960fc47c401f856f1,Space-Time Body Pose Estimation in Uncontrolled Environments,"Space-time Body Pose Estimation in Uncontrolled Environments +Marcel Germann +ETH Zurich +Switzerland +Tiberiu Popa +ETH Zurich +Switzerland +Remo Ziegler +LiberoVision AG +Switzerland +Richard Keiser +LiberoVision AG +Switzerland +Markus Gross +ETH Zurich +Switzerland"
+0cd8fabfc8e22be8275c317e7ccd37e640711c62,Experiments on an RGB-D Wearable Vision System for Egocentric Activity Recognition,"Experiments on an RGB-D Wearable Vision System +for Egocentric Activity Recognition +Mohammad Moghimi1, Pablo Azagra2, Luis Montesano2, Ana C. Murillo1,2 and Serge Belongie3 +UC San Diego +La Jolla, CA +DIIS - I3A +University of Zaragoza, Spain +{montesano, +Cornell Tech +New York, NY +tech.cornell.edu"
+0cdf238fd44684b49302c22b062772e7c66ea182,Autonomous Decision Making Robots,"International Journal of Artificial Intelligence and Applications (IJAIA), Vol.9, No.2, March 2018 +UNSUPERVISED ROBOTIC SORTING: TOWARDS +AUTONOMOUS DECISION MAKING ROBOTS +Joris Gu´Erin, St´Ephane Thiery, Eric Nyiri And Olivier Gibaru +Arts et M´etiers ParisTech, Lille, FRANCE"
+0ca475433d74abb3c0f38fbe9d212058dc771570,Learning pairwise feature dissimilarities for person re-identification,"Learning Pairwise Feature Dissimilarities +for Person Re-Identification +Niki Martinel +University of Udine +Udine, Italy +Christian Micheloni +University of Udine +Udine, Italy +Claudio Piciarelli +University of Udine +Udine, Italy"
+0c03bb741972c99b71d8d733b92e5fa9430cbede,Learning rank reduced interpolation with principal component analysis,"Learning Rank Reduced Interpolation +with Principal Component Analysis +Matthias Ochs1, Henry Bradler1 and Rudolf Mester1,2"
+0c2c53d71942ad3171b693f565812f1db43215e0,Descriptive visual words and visual phrases for image applications,"Descriptive Visual Words and Visual Phrases for Image +Shiliang Zhang1, Qi Tian2, Gang Hua3, Qingming Huang4, Shipeng Li2 +Applications +Key Lab of Intelli. Info. +Process., Inst. of Comput. +Tech., CAS, Beijing 100080, +China +Microsoft Research Asia, +Beijing 100080, China +Microsoft Live Labs +Research, Redmond, WA +78052, U.S.A. +Graduate University of +Chinese Academy of +Sciences, Beijing 100049, +China +{slzhang, {qitian, ganghua,"
+0c30850067c296a01b72cf4803c9712926ae5a95,Text-Dependent Audiovisual Synchrony Detection for Spoofing Detection in Mobile Person Recognition,"INTERSPEECH 2016 +September 8–12, 2016, San Francisco, USA +Text-Dependent Audiovisual Synchrony Detection for Spoofing Detection in +Mobile Person Recognition +Amit Aides1,2, Hagai Aronowitz1 +Dept of Electrical Engineering,Technion - Israel Institute of Technology, Haifa, Israel +IBM Research - Haifa, Israel +{amitaid,"
+0cf333cab1a9ccf671cebf31b78180f863c1caa7,Automated Evaluation of Semantic Segmentation Robustness for Autonomous Driving,"Automated Evaluation of Semantic Segmentation +Robustness for Autonomous Driving +Wei Zhou, Member, IEEE, Julie Stephany Berrio, Member, IEEE, +Stewart Worrall, Member, IEEE, and Eduardo Nebot, Member, IEEE"
+0c25a4636ebde18e229f7e459f1adaab1e9a2db9,Multi - class Classification and Clustering based Multi - object Tracking,"Multi-class Classification and Clustering based +Multi-object Tracking +Nii Longdon Sowah, Qingbo Wu, Fanman Meng"
0ced7b814ec3bb9aebe0fcf0cac3d78f36361eae,Central Local Directional Pattern Value Flooding Co-occurrence Matrix based Features for Face Recognition,"Dr. P Chandra Sekhar Reddy, International Journal of Computer Science and Mobile Computing, Vol.6 Issue.1, January- 2017, pg. 221-227 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing @@ -457,6 +1674,37 @@ Flooding Co-occurrence Matrix based Features for Face Recognition Dr. P Chandra Sekhar Reddy Professor, CSE Department, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad"
+0ccd410b6ae977a945a84bad1c2785cef4c73214,Pseudo two-dimensional Hidden Markov Models for face detection in colour images,"Pseudo two-dimensional Hidden Markov Models +for face detection in colour images +ephane Marchand-Maillet +Bernard M +erialdo +Department of Multimedia Communications +EURECOM Institute + +http:www.eurecom.fr~marchand +To be presented in the +nd Int. Conf. on Audio- and Video-based Biometric Person Authentication"
+0c9d9ebecfce885f3b1e7bd82ec1b74e9f17b9de,Attribute expansion with sequential learning for object classification,"ATTRIBUTE EXPANSION WITH SEQUENTIAL LEARNING FOR OBJECT +CLASSIFICATION +Biao Niuy, Bin Liz, Peng Liy, Xi Zhangy, Jian Chengy, Hanqing Luy +National Laboratory of Pattern Recognition, CASIA, Beijing, China 100190 +ShiJiaZhuang Vocational Technology Institute, Hebei, China 050000 +{bniu, pli, xi.zhang, jcheng,"
+0c922f8be9f0368c1abd53b8d9554f06b73a56cf,High-Level Fusion of Depth and Intensity for Pedestrian Classification,"High-Level Fusion of Depth and +Intensity for Pedestrian Classification +Marcus Rohrbach1,3,(cid:2), Markus Enzweiler2,(cid:2), and Dariu M. Gavrila1,4 +Environment Perception, Group Research, Daimler AG, Ulm, Germany +Image & Pattern Analysis Group, Dept. of Math. +nd Computer Science, Univ. of Heidelberg, Germany +Dept. of Computer Science, TU Darmstadt, Germany +Intelligent Systems Lab, Fac. of Science, Univ. of Amsterdam, The Netherlands"
+0c79485f64733bd128ef8c395034b6bc77abf94d,Fully automatic expression-invariant face correspondence,"Fully Automatic Expression-Invariant Face Correspondence +Augusto Salazar∗† +Stefanie Wuhrer†‡ +Chang Shu‡ +Flavio Prieto § +February 1, 2013"
0c53ef79bb8e5ba4e6a8ebad6d453ecf3672926d,Weakly Supervised PatchNets: Describing and Aggregating Local Patches for Scene Recognition,"SUBMITTED TO JOURNAL Weakly Supervised PatchNets: Describing and Aggregating Local Patches for Scene Recognition @@ -472,16 +1720,46 @@ LEARNING NON-LINEAR TRANSFORM WITH DISCRIM- INATIVE AND MINIMUM INFORMATION LOSS PRIORS Anonymous authors Paper under double-blind review"
+661be86559295d3b2cbabcd31cc90848f601f55c,Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks,"Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks +The Chinese University of Hong Kong 2SenseTime Group Limited 3Nanyang Technological University +Yuenan Hou1, Zheng Ma2, Chunxiao Liu2, and Chen Change Loy3 +{mazheng,"
+661c16658db873efeee3621603fe6bd53eaffac1,LLE Score: A New Filter-Based Unsupervised Feature Selection Method Based on Nonlinear Manifold Embedding and Its Application to Image Recognition,"LLE score: a new filter-based unsupervised feature +selection method based on nonlinear manifold +embedding and its application to image recognition +Chao Yao, Ya-Feng Liu, Member, IEEE, Bo Jiang, Jungong Han, and Junwei Han, Senior Member, IEEE."
6643a7feebd0479916d94fb9186e403a4e5f7cbf,Chapter 8 3 D Face Recognition,"Chapter 8 D Face Recognition Ajmal Mian and Nick Pears"
+66c792b7e9946f8cb92fac185267d03371437451,Adaptive Affinity Fields for Semantic Segmentation,"Adaptive Affinity Fields for Semantic Segmentation +Tsung-Wei Ke*, Jyh-Jing Hwang*, Ziwei Liu, and Stella X. Yu +UC Berkeley / ICSI"
661ca4bbb49bb496f56311e9d4263dfac8eb96e9,Datasheets for Datasets,"Datasheets for Datasets Timnit Gebru 1 Jamie Morgenstern 2 Briana Vecchione 3 Jennifer Wortman Vaughan 1 Hanna Wallach 1 Hal Daumé III 1 4 Kate Crawford 1 5"
+6668ca5ab57d68070f90671a4f92a6bc25f80470,Measuring cues for stand-off deception detection based on full-body non-verbal features in body-worn cameras,"Measuring cues for stand-off deception detection based on full-body +non-verbal features in body-worn cameras +Henri Bouma 1, Gertjan Burghouts, Richard den Hollander, Sophie Van Der Zee, Jan Baan, +Johan-Martijn ten Hove, Sjaak van Diepen, Paul van den Haak, Jeroen van Rest +TNO, Oude Waalsdorperweg 63, 2597 AK The Hague, The Netherlands"
+66b37797286952e7735901e152b4cdea171e8567,Recovering 3D Planes from a Single Image via Convolutional Neural Networks,"Recovering 3D Planes from a Single Image via +Convolutional Neural Networks +Fengting Yang and Zihan Zhou +The Pennsylvania State University +{fuy34,"
+66f55dc04aaf4eefdecef202211ad7563f7a703b,Synthesizing Programs for Images using Reinforced Adversarial Learning,"Synthesizing Programs for Images using Reinforced Adversarial Learning +Yaroslav Ganin 1 Tejas Kulkarni 2 Igor Babuschkin 2 S. M. Ali Eslami 2 Oriol Vinyals 2"
66d087f3dd2e19ffe340c26ef17efe0062a59290,Dog Breed Identification,"Dog Breed Identification Whitney LaRow Brian Mittl Vijay Singh"
+66660f5e8b2a4a695abe0f9e1df32d230126f773,Applying Deep Learning to Improve Maritime Situational Awareness,"Applying Deep Learning to Improve +Maritime Situational Awareness +Kathy Tang +Stottler Henke Associates, Inc. +650 S. Amphlett Blvd. Ste. 300 +San Mateo, CA 94402 +Intelligence"
6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c,Ordinal Regression with Multiple Output CNN for Age Estimation,"Ordinal Regression with Multiple Output CNN for Age Estimation Zhenxing Niu1 Gang Hua3 @@ -489,6 +1767,43 @@ Xidian University 2Xi’an Jiaotong University 3Microsoft Research Asia Xinbo Gao1 Mo Zhou1 Le Wang2"
+66719918aa6562d14ea53286bf248d6f1a7d6b14,Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks,"Perceive Your Users in Depth: Learning Universal User +Representations from Multiple E-commerce Tasks +Yabo Ni∗, Dan Ou∗, Shichen Liu, Xiang Li, Wenwu Ou, Anxiang Zeng, Luo Si +Search Algorithm Team, Alibaba Group, Seattle & Hangzhou, China"
+66b9e9d488ef2bad9bf0d2fb98f73f38fec2bff8,Context-aware Cascade Attention-based RNN for Video Emotion Recognition,"Context-aware Cascade Attention-based RNN for +Video Emotion Recognition +Man-Chin Sun +Emotibot Inc. +Taipei, Taiwan +Shih-Huan Hsu +Emotibot Inc. +Taipei, Taiwan +Min-Chun Yang +Emotibot Inc. +Taipei, Taiwan +Jen-Hsien Chien +Emotibot Inc. +Taipei, Taiwan"
+669727b3258bb3edc38709147f348dc67e3fcac4,A Lightweight approach for biometric template protection,"A Lightweight approach for biometric template protection* +Hisham Al-Assam, Harin Sellahewa, & Sabah Jassim +University of Buckingham, Buckingham MK18 1EG, U.K. +{hisham.al-assam , harin.sellahewa,"
+66837b29270f3e03df64941a081d70c687c7955c,ActionXPose: A Novel 2D Multi-view Pose-based Algorithm for Real-time Human Action Recognition,"ActionXPose: A Novel 2D Multi-view Pose-based +Algorithm for Real-time Human Action Recognition +Federico Angelini, Student Member, IEEE, Zeyu Fu, Student Member, IEEE, Yang Long, Senior Member, IEEE, +Ling Shao, Senior Member, IEEE, and Syed Mohsen Naqvi, Senior Member, IEEE"
+66c92c9145c2b6a304eb1b3a58e2a717884fe064,Emotions in Pervasive Computing Environments,"IJCSI International Journal of Computer Science Issues, Vol. 6, No. 1, 2009 +ISSN (Online): 1694-0784 +ISSN (Print): 1694-0814 +Emotions in Pervasive Computing Environments +Nevin VUNKA JUNGUM1 and Éric LAURENT2 +1 Computer Science and Engineering Department, +University of Mauritius +Réduit, Mauritius +Laboratoire de Psychologie, ENACT-MCA, +University of Franche-Comté +Besançon, France"
66a2c229ac82e38f1b7c77a786d8cf0d7e369598,A Probabilistic Adaptive Search System for Exploring the Face Space,"Proceedings of the 2016 Industrial and Systems Engineering Research Conference H. Yang, Z. Kong, and MD Sarder, eds. A Probabilistic Adaptive Search System @@ -496,6 +1811,34 @@ for Exploring the Face Space Andres G. Abad and Luis I. Reyes Castro Escuela Superior Politecnica del Litoral (ESPOL) Guayaquil-Ecuador"
+669ae4a3a21b5800829ac9ee7e780fa42f9bc5ad,LDADEEP+: Latent aspect discovery with deep representations,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE +ICASSP 2016"
+6603e7de5b155c86407edc43099b46b974b7f0bb,Local Feature Based Face Recognition,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+66ee33bf0064eee159f3563e32b15c5bbd4140a0,Face Recognition Under Varying Viewing Conditions with Subspace Distance,"Face Recognition Under Varying Viewing Conditions with Subspace Distance +Jen-Mei Chang +Department of Mathematics and Statistics +California State University, Long Beach +250 Bellflower Blvd. +Long Beach, California 90840-1001"
66a9935e958a779a3a2267c85ecb69fbbb75b8dc,Fast and Robust Fixed-Rank Matrix Recovery,"FAST AND ROBUST FIXED-RANK MATRIX RECOVERY Fast and Robust Fixed-Rank Matrix Recovery @@ -527,6 +1870,31 @@ Filter Xu Yi Department of Information Engineering, Hunan Industry Polytechnic, Changsha, China images will be tested to project"
+668e93e89835ec662d21cf695b7347339ce74c78,Likelihood Ratio Fusion within Scores of Independent Component Analysis Features Based Face Biometrics Verification Systems,"June. 2015. Vol. 6, No.3 +ISSN 2305-1493 +International Journal of Scientific Knowledge +Computing and Information Technology +© 2012 - 2015 IJSK & K.A.J. All rights reserved +www.ijsk.org/ijsk +LIKELIHOOD RATIO FUSION WITHIN SCORES OF +INDEPENDENT COMPONENT ANALYSIS FEATURES BASED +FACE BIOMETRICS VERIFICATION SYSTEMS +SOLTANE MOHAMED +Electrical Engineering & Computing Department, Faculty of Sciences & Technology, +DOCTOR YAHIA FARES UNIVERSITY OF MEDEA, 26000 MEDEA, ALGERIA +Laboratoire des Systèmes Électroniques Avancées (LSEA)"
+66c0fcf637bede76a6ea61b58655c5fc7e890630,Improving the Generalization of Neural Networks by Changing the Structure of Artificial Neuron,"Improving the Generalization of Neural Networks by Changing the Structure of Artificial Neuron. pp 195-204 +IMPROVING THE GENERALIZATION OF NEURAL NETWORKS BY CHANGING THE STRUCTURE OF +ARTIFICIAL NEURON +Mohammad Reza Daliri1, Mehdi Fatan2 +Biomedical Engineering Department and Iran Neural Technology Center, +Faculty of Electrical Engineering, Iran University of Science and Technology (IUST), +Narmak, 16846-13114 Tehran, Iran (Email: +Mechatronics Group, Faculty of Electrical Engineering, +Qazvin Islamic Azad University, Qazvin, Iran (Email: +Corresponding author: M.R. Daliri, Email:"
+66e2c3d23af8ed76b116121827b9bc5e99cf4acc,Video Prediction with Appearance and Motion Conditions,"Video Prediction with Appearance and Motion Conditions +Yunseok Jang 1 2 Gunhee Kim 2 Yale Song 3"
66af2afd4c598c2841dbfd1053bf0c386579234e,Context-assisted face clustering framework with human-in-the-loop,"Noname manuscript No. (will be inserted by the editor) Context Assisted Face Clustering Framework with @@ -542,6 +1910,10 @@ Genevieve Patterson · Chen Xu · Hang Su · James Hays Received: 27 February 2013 / Accepted: 28 December 2013 / Published online: 18 January 2014 © Springer Science+Business Media New York 2014"
+665e6aa652b99350a08090faaf9d4bcc7800186e,Detection-Free Multiobject Tracking by Reconfigurable Inference With Bundle Representations,"Detection-Free Multiobject Tracking by +Reconfigurable Inference With +Bundle Representations +Liang Lin, Yongyi Lu, Chenglong Li, Hui Cheng, and Wangmeng Zuo, Senior Member, IEEE"
661da40b838806a7effcb42d63a9624fcd684976,An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients,"An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients @@ -570,6 +1942,60 @@ Takumi Kobayashi National Institute of Advanced Industrial Science and Technology Tsukuba, Japan"
+664ccdcc614a8ecfbfedadc7b42b9537fe43d3f1,Probabilistic integration of sparse audio-visual cues for identity tracking,"Probabilistic Integration of Sparse Audio-Visual Cues for +Identity Tracking +Keni Bernardin +Universität Karlsruhe, ITI +Am Fasanengarten 5 +76131, Karlsruhe, Germany +Rainer Stiefelhagen +Universität Karlsruhe, ITI +Am Fasanengarten 5 +76131, Karlsruhe, Germany +Alex Waibel +Universität Karlsruhe, ITI +Am Fasanengarten 5 +76131, Karlsruhe, Germany"
+660c8a9fa166c1d81e65192e011eacfec208ec00,Discrimination of visual pedestrians data by combining projection and prediction learning,"Discrimination of visual pedestrians data by combining +projection and prediction learning +Mathieu Lefort, Alexander Gepperth +To cite this version: +Mathieu Lefort, Alexander Gepperth. Discrimination of visual pedestrians data by combining +projection and prediction learning. ESANN - European Symposium on Artificial Neural Net- +works, Computational Intelligence and Machine Learning, Apr 2014, Bruges, Belgium. 2014. +<hal-01061654> +HAL Id: hal-01061654 +https://hal.inria.fr/hal-01061654 +Submitted on 8 Sep 2014 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
+66f8115136a11684e3b95c5aaa1476a871d58a66,Face recognition using multiple image view line segments,"JAMESCOOKUNIVERSITY +FaceRecognitionusingMultiple +ImageViewLineSegments +StefanAeberhardandOlivierdeVel +TR / +DEPARTMENTOFCOMPUTERSCIENCETOWNSVILLE +QUEENSLAND +AUSTRALIA"
+66b955311ab6841c4644414d8ce2faf6ca721602,RoboCupRescue 2009 - Robot League Team Darmstadt Rescue Robot,"RoboCupRescue 2009 - Robot League Team +Darmstadt Rescue Robot Team (Germany) +Micha Andriluka1, Martin Friedmann1, Stefan Kohlbrecher1, Johannes Meyer2, +Karen Petersen1, Christian Reinl1, Peter Schauß1, Paul Schnitzspan1, Armin +Strobel2, Dirk Thomas1, Anguelina Vatcheva1, Oskar von Stryk1(cid:63) +Department of Computer Science (1) and Department of Mechanical Engineering (2), +Technische Universit¨at Darmstadt, +Karolinenplatz 5, D-64289 Darmstadt, Germany +E-Mail: +Web: www.gkmm.tu-darmstadt.de/rescue"
+66860100a3355f26ffcb9dcbf27e27e4757d641d,Feature Selection in Supervised Saliency Prediction,"Feature Selection in Supervised Saliency Prediction +Ming Liang, Student Member, IEEE, and Xiaolin Hu, Senior Member, IEEE"
3edb0fa2d6b0f1984e8e2c523c558cb026b2a983,Automatic Age Estimation Based on Facial Aging Patterns,"Automatic Age Estimation Based on Facial Aging Patterns Xin Geng, Zhi-Hua Zhou, Senior Member, IEEE, @@ -594,18 +2020,97 @@ than from image sequences because less information for expression actions vailable. However, information in a single image is sometimes enough for"
+3e6b70e5be3dbe688866d8dd4382ce05b201fd28,Evaluation of Face Recognition Techniques,"PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, edited by Honghua Tan, Qi Luo, +Proc. of SPIE Vol. 7489, 74890M · © 2009 SPIE · CCC code: 0277-786X/09/$18 · doi: 10.1117/12.836686 +Proc. of SPIE Vol. 7489 74890M-1 +Downloaded from SPIE Digital Library on 24 Jan 2010 to 130.194.78.137. Terms of Use: http://spiedl.org/terms"
+3e6fa6cf1fe2e23fdf7716f89b160333c7a93b26,A Performance Evaluation of Single and Multi-feature People Detection,"A Performance Evaluation of Single and +Multi-Feature People Detection +Christian Wojek, Bernt Schiele +{wojek, +Computer Science Department +TU Darmstadt"
3e4acf3f2d112fc6516abcdddbe9e17d839f5d9b,Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs,"Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs Michael Gygli 1 * Mohammad Norouzi 2 Anelia Angelova 2"
+3e0415f0e8c36f20042d6a1f8b7c216fb5543c3a,RGB-D Segmentation of Poultry Entrails,"Aalborg Universitet +RGB-D Segmentation of Poultry Entrails +Philipsen, Mark Philip; Jørgensen, Anders; Guerrero, Sergio Escalera; Moeslund, Thomas B. +Published in: +IX International Conference on Articulated Motion and Deformable Objects +DOI (link to publication from Publisher): +0.1007/978-3-319-41778-3_17 +Publication date: +Document Version +Accepted author manuscript, peer reviewed version +Link to publication from Aalborg University +Citation for published version (APA): +Philipsen, M. P., Jørgensen, A., Guerrero, S. E., & Moeslund, T. B. (2016). RGB-D Segmentation of Poultry +Entrails. In IX International Conference on Articulated Motion and Deformable Objects (pp. 168-174). Springer. +Lecture Notes in Computer Science, Vol.. 9756, DOI: 10.1007/978-3-319-41778-3_17 +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. +? You may not further distribute the material or use it for any profit-making activity or commercial gain"
+3efea06ad6398f9db07acf34479c81a99479e80b,Localizing Moments in Video with Natural Language,"Localizing Moments in Video with Natural Language +Lisa Anne Hendricks1 +, Oliver Wang2, Eli Shechtman2, Josef Sivic2 +, Trevor Darrell1, Bryan Russell2 +UC Berkeley, 2Adobe Research, 3INRIA +https://people.eecs.berkeley.edu/˜lisa_anne/didemo.html +Figure 1: We consider localizing moments in video with natural language and demonstrate that incorporating local and +global video features is important for this task. To train and evaluate our model, we collect the Distinct Describable Moments +(DiDeMo) dataset which consists of over 40,000 pairs of localized video moments and corresponding natural language."
+3e0a12352fe3e9fb9246ee0f81ff7fbf0600f818,Facial Surface Analysis using Iso-Geodesic Curves in Three Dimensional Face Recognition System,"Facial Surface Analysis using Iso-Geodesic Curves +in Three Dimensional Face Recognition System +Rachid AHDID, El Mahdi BARRAH, Said SAFI and Bouzid MANAUT"
3e3f305dac4fbb813e60ac778d6929012b4b745a,Feature sampling and partitioning for visual vocabulary generation on large action classification datasets,"Feature sampling and partitioning for visual vocabulary generation on large action classification datasets. Michael Sapienza1, Fabio Cuzzolin1, and Philip H.S. Torr2 Department of Computing and Communications Technology, Oxford Brookes University. Department of Engineering Science, University of Oxford."
3ea8a6dc79d79319f7ad90d663558c664cf298d4,Automatic Facial Expression Recognition from Video Sequences,"(cid:13) Copyright by Ira Cohen, 2000"
+3e8de2f904dea8368477daebab0c0dc97e0229f4,Detection and Classification of Vehicles from Omnidirectional Videos using Temporal Average of Silhouettes,"Detection and Classification of Vehicles from Omnidirectional Videos +using Temporal Average of Silhouettes +Computer Vision Research Group, Department of Computer Engineering, Izmir Institute of Technology, 35430, +Hakki Can Karaimer and Yalin Bastanlar +Izmir, Turkey +{cankaraimer, +Keywords: +Omnidirectional Camera, Omnidirectional Video, Object Detection, Vehicle Detection, Vehicle +Classification."
+3eff18934f5870b27f80c8b1d7104967460e3035,Driver hand localization and grasp analysis: A vision-based real-time approach,
3e4f84ce00027723bdfdb21156c9003168bc1c80,A co-training approach to automatic face recognition,"© EURASIP, 2011 - ISSN 2076-1465 9th European Signal Processing Conference (EUSIPCO 2011) INTRODUCTION"
+3e56a9b6c6aced2cb14f9cd7f89d145851c44113,Zero and Few Shot Learning with Semantic Feature Synthesis and Competitive Learning,"Zero and Few Shot Learning with Semantic +Feature Synthesis and Competitive Learning +Zhiwu Lu, Jiechao Guan, Aoxue Li, Tao Xiang, An Zhao, and Ji-Rong Wen"
+3e08d000ba3dd382c16e4295435ef8264235ccbc,Multiple People Tracking in Smart Camera Networks by Greedy Joint-Likelihood Maximization,
+3e2588aaa719c63e48fe599a7f0dbea10a41b4eb,Using Sparse Semantic Embeddings Learned from Multimodal Text and Image Data to Model Human Conceptual Knowledge,"Using sparse semantic embeddings learned from multimodal text and +image data to model human conceptual knowledge +Steven Derby1 +Paul Miller1 +Brian Murphy1,2 +Barry Devereux1 +Queen’s University Belfast, Belfast, United Kingdom +{sderby02, p.miller, brian.murphy, +BrainWaveBank Ltd., Belfast, United Kingdom"
+3edf3a996790fef8957e21c68ddf48b52238e662,Product of tracking experts for visual tracking of surgical tools,"Product of Tracking Experts for Visual Tracking of Surgical Tools +Suren Kumar, Madusudanan Sathia Narayanan, Pankaj Singhal, Jason J. Corso and Venkat Krovi +State University of New York (SUNY) at Buffalo"
+3eec9e8d5051e84624ea7e009a8947403dee99d1,"Material Recognition Meets 3D Reconstruction: Novel Tools for Efficient, Automatic Acquisition Systems","Material Recognition Meets 3D +Reconstruction: Novel Tools for Efficient, +Automatic Acquisition Systems +Dissertation +Erlangung des Doktorgrades (Dr. rer. nat.) +Mathematisch-Naturwissenschaftlichen Fakultät +der Rheinischen Friedrich-Wilhelms-Universität Bonn +vorgelegt von +Dipl.-Ing. Michael Weinmann +us Karlsruhe +Bonn, Dezember 2015"
3e04feb0b6392f94554f6d18e24fadba1a28b65f,Subspace Image Representation for Facial Expression Analysis and Face Recognition and its Relation to the Human Visual System,"Subspace Image Representation for Facial Expression Analysis and Face Recognition nd its Relation to the Human Visual System @@ -626,14 +2131,108 @@ goal. According to neuropsychological experiments, it seems that encoding for fa recognition, relies on holistic image representation, while a sparse image represen- tation is used for facial expression analysis and classification. From the computer vision perspective, the techniques developed for automatic face and facial expres-"
+3ed186b4337f48e263ef60acffb49f16d5a85511,Discriminatively learned filter bank for acoustic features,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE +ICASSP 2016"
+3eebe8a5adaa49e54ea909b4e2aeb436025c84d5,3D Face Recognition Using Radon Transform and Symbolic Factorial Discriminant Analysis,"Proc. of Int. Conf. onMultimedia Processing, Communication and Info. Tech., MPCIT +D Face Recognition Using Radon Transform and +Symbolic Factorial Discriminant Analysis +P. S. Hiremath, Manjunath Hiremath +Department of Computer Science Gulbarga University, Gulbarga 585106 Karnataka, India +Email:"
+3ede3ed28329bf48fbd06438a69c4f855bef003f,Large-scale geo-facial image analysis,"Islam et al. EURASIP Journal on Image and Video Processing (2015) 2015:17 +DOI 10.1186/s13640-015-0070-9 +RESEARCH +Open Access +Large-scale geo-facial image analysis +Mohammad T. Islam1, Connor Greenwell1, Richard Souvenir2 and Nathan Jacobs1*"
3e685704b140180d48142d1727080d2fb9e52163,Single Image Action Recognition by Predicting Space-Time Saliency,"Single Image Action Recognition by Predicting Space-Time Saliency Marjaneh Safaei and Hassan Foroosh"
+3efb04937f6d87ab9540700e04d8133102c67bc0,Ask Your Neurons: A Deep Learning Approach to Visual Question Answering,"myjournal +Ask Your Neurons: +A Deep Learning Approach to Visual Question Answering +Mateusz Malinowski · Marcus Rohrbach · Mario Fritz +Received: date / Accepted: date"
+3ee522805e16bf7816ec4abfaf0c7648b5cb5c95,From Numerical Sensor Data to Semantic Representations :,"From Numerical Sensor Data to Semantic Representations: +A Data-driven Approach for Generating Linguistic Descriptions +Hadi Banaee +Akademisk avhandling +Avhandling för filosofie doktorsexamen i datavetenskap, +som kommer att försvaras offentligt +fredag den 20 april 2018 kl. 13.15, +Hörsal T, Örebro universitet, Örebro +Opponent: Prof. Antonio Chella +University of Palermo +Italy +Örebro universitet +Institutionen för Naturvetenskap och Teknik +701 82 Örebro"
+3e67058c6ddd0afae692b7665f82124945ea2c5a,On the Learning of Deep Local Features for Robust Face Spoofing Detection,"On the Learning of Deep Local Features for +Robust Face Spoofing Detection +Gustavo Botelho de Souza1, Jo˜ao Paulo Papa2 and Aparecido Nilceu Marana2 - in Proc. of SIBGRAPI 2018 +UFSCar - Federal University of S˜ao Carlos. Rod. Washington Lu´ıs, Km 235. S˜ao Carlos (SP), Brazil. 13565-905. +UNESP - S˜ao Paulo State University. Av. Eng. Luiz Edmundo Carrijo Coube, 14-01. Bauru (SP), Brazil. 17033-360. +E-mail: {papa,"
+3e4ec7bdd279573d328a26b720854894e68230ed,Efficient Relative Attribute Learning Using Graph Neural Networks,"Efficient Relative Attribute Learning using +Graph Neural Networks +Zihang Meng1, Nagesh Adluru1, Hyunwoo J. Kim1⋆, +Glenn Fung2, and Vikas Singh1 +University of Wisconsin – Madison +American Family Insurance"
+3e3ba138edbcf594cd0479ac2cddd5a8e3ee6a18,Edge detection for facial expression recognition,"Edge Detection for Facial Expression Recognition +Jesús García-Ramírez, Ivan Olmos-Pineda, J. Arturo Olvera-López, Manuel Martín +Ortíz +Faculty of Computer Science, Benemérita Universidad Autónoma de Puebla, Av. San Claudio +olvera, +y 14 sur. Puebla, Pue. C.P. 72570, México"
+3e309126c78261f242d21826bfac37412f5437cd,Attribute CNNs for Word Spotting in Handwritten,"International Journal on Document Analysis and Recognition manuscript No. +(will be inserted by the editor) +Attribute CNNs for Word Spotting in Handwritten +Documents +Sebastian Sudholt · Gernot A. Fink +Received: date / Accepted: date"
3e687d5ace90c407186602de1a7727167461194a,Photo Tagging by Collection-Aware People Recognition,"Photo Tagging by Collection-Aware People Recognition Cristina Nader Vasconcelos Vinicius Jardim Asla S´a Paulo Cezar Carvalho"
+3e0db33884ca8c756b26dc0df85c498c18d5f2ec,Exploiting Pedestrian Interaction via Global Optimization and Social Behaviors,"Exploiting pedestrian interaction via global optimization +nd social behaviors +Laura Leal-Taix´e, Gerard Pons-Moll, and Bodo Rosenhahn +Leibniz Universit¨at Hannover, Appelstr. 9A, Hannover, Germany"
+3e18b439a6fff09a0e4c245eb1298531cc766a72,"Semi-automatic Face Image Finding Method , Which Uses the 3 D Model of the Head for Recognising an Unknown Face","Technologies of Computer Control +doi: 10.7250/tcc.2015.001 +______________________________________________________________________________________________ 2015 / 16 +Semi-automatic Face Image Finding Method, Which +Uses the 3D Model of the Head for Recognising an +Olga Krutikova1, Aleksandrs Glazs2 +, 2 Riga Technical University"
+3e159084e12ece3664a17bf4dd0eed8c5f06a33f,Deep Neural Networks with Inexact Matching for Person Re-Identification,"Deep Neural Networks with Inexact Matching for +Person Re-Identification +Arulkumar Subramaniam +Indian Institute of Technology Madras +Chennai, India 600036 +Moitreya Chatterjee +Indian Institute of Technology Madras +Chennai, India 600036 +Anurag Mittal +Indian Institute of Technology Madras +Chennai, India 600036"
+3e7b5b07da3465103929b4347852d456c0f0ed58,Video Processing From Electro-Optical Sensors for Object Detection and Tracking in a Maritime Environment: A Survey,"Video Processing from Electro-optical Sensors for +Object Detection and Tracking in Maritime +Environment: A Survey +Dilip K. Prasad1,∗, Deepu Rajan2, Lily Rachmawati3, Eshan Rajabally4, and Chai Quek2"
+3e4bd583795875c6550026fc02fb111daee763b4,Convolutional Sketch Inversion,"Convolutional Sketch Inversion +Ya˘gmur G¨u¸cl¨ut¨urk∗, Umut G¨u¸cl¨u∗, Rob van Lier, and Marcel A. J. +van Gerven +Radboud University, Donders Institute for Brain, Cognition and +Behaviour, Nijmegen, the Netherlands +Figure 1: Example results of our convolutional sketch inversion models. Our models +invert face sketches to synthesize photorealistic face images. Each row shows the sketch +inversion / photo synthesis pipeline that transforms a different sketch of the same face +to a different image of the same face via a different deep neural network. Each deep +neural network layer is represented by the top three principal components of its feature +maps."
50f0c495a214b8d57892d43110728e54e413d47d,Pairwise support vector machines and their application to large scale problems,"Submitted 8/11; Revised 3/12; Published 8/12 Pairwise Support Vector Machines and their Application to Large Scale Problems @@ -648,15 +2247,84 @@ Cognitec Systems GmbH Grossenhainer Str. 101 01127 Dresden, Germany Editor: Corinna Cortes"
+506f744801c97f005fa04a09e4a4ae5fdabe94d7,MARCOnI—ConvNet-Based MARker-Less Motion Capture in Outdoor and Indoor Scenes,"Local Submodularization +for Binary Pairwise Energies +Lena Gorelick, Yuri Boykov, Olga Veksler, Ismail Ben Ayed, and Andrew Delong"
501096cca4d0b3d1ef407844642e39cd2ff86b37,Illumination Invariant Face Image Representation Using Quaternions,"Illumination Invariant Face Image Representation using Quaternions Dayron Rizo-Rodr´ıguez, Heydi M´endez-V´azquez, and Edel Garc´ıa-Reyes Advanced Technologies Application Center. 7a # 21812 b/ 218 and 222, Rpto. Siboney, Playa, P.C. 12200, La Habana, Cuba."
501eda2d04b1db717b7834800d74dacb7df58f91,Discriminative Sparse Representation for Expression Recognition,"Pedro Miguel Neves Marques Discriminative Sparse Representation for Expression Recognition Master Thesis in Electrical and Computer Engineering September, 2014"
+50da9965104d944a8ae648c9aaec43be8ea1c501,Improving the Correspondence Establishment Based on Interactive Homography Estimation,"Improving the Correspondence Establishment +Based on Interactive Homography Estimation* +Xavier Cortés, Carlos Moreno, and Francesc Serratosa +Universitat Rovira i Virgili, Departament d’Enginyeria Informàtica i Matemàtiques, Spain"
5083c6be0f8c85815ead5368882b584e4dfab4d1,Automated Face Analysis for Affective Computing Jeffrey,"Please do not quote. In press, Handbook of affective computing. New York, NY: Oxford Automated Face Analysis for Affective Computing Jeffrey F. Cohn & Fernando De la Torre"
+5080655990fe0e0446bcb038b3e0adad0218bd29,Quantum Cuts A Quantum Mechanical Spectral Graph Partitioning Method for Salient Object Detection Julkaisu,"Çağlar Aytekin +Quantum Cuts +A Quantum Mechanical Spectral Graph Partitioning Method for Salient +Object Detection +Julkaisu 1440 • Publication 1440 +Tampere 2016"
+50c5a552c191bff34ca74e0f8dbac159e3814533,"Overview of the ImageCLEF 2015 Scalable Image Annotation, Localization and Sentence Generation task","Overview of the ImageCLEF 2015 Scalable +Image Annotation, Localization and Sentence +Generation task +Andrew Gilbert, Luca Piras, Josiah Wang, Fei Yan, Emmanuel Dellandrea, +Robert Gaizauskas, Mauricio Villegas and Krystian Mikolajczyk"
+5056186a5001921d0a24587e26167a7ee9d88cf9,Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition,"World Academy of Science, Engineering and Technology +International Journal of Computer and Information Engineering +Vol:12, No:10, 2018 +Optimizing the Capacity of a Convolutional Neural +Network for Image Segmentation and Pattern +Recognition +Yalong Jiang, Zheru Chi"
+5087d9bdde0ba5440eb8658be7183bf5074a2a94,Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model,"Object detection via a multi-region +semantic segmentation-aware CNN model +Spyros Gidaris, Nikos Komodakis +To cite this version: +Spyros Gidaris, Nikos Komodakis. Object detection via a multi-region +semantic segmentation-aware CNN model. ICCV 2015, Dec 2015, Santiago, Chile. ICCV 2015, 2016, +<10.1109/ICCV.2015.135>. <hal-01245664> +HAL Id: hal-01245664 +https://hal.archives-ouvertes.fr/hal-01245664 +Submitted on 17 Dec 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+50b6d2db19fb71ff5cfde8e2bfa484b10fbb39fe,Perception of Suicide Risk in Mental Health Professionals.,"RESEARCH ARTICLE +Perception of Suicide Risk in Mental Health +Professionals +Tim M. Gale1,2*, Christopher J. Hawley3, John Butler4, Adrian Morton5, Ankush Singhal6 +Department of Research, Hertfordshire Partnership University NHS Foundation Trust, Hatfield, United +Kingdom, 2 Department of Psychology, University of Hertfordshire, Hatfield, United Kingdom, 3 Department +of Post-graduate Medicine, University of Hertfordshire, Hatfield, United Kingdom, 4 School of Health, +University of Central Lancaster, Preston, United Kingdom, 5 Reigate Psychology Service, Reigate, Surrey, +United Kingdom, 6 Psychological Medicine Service, The Royal Oldham Hospital, Oldham, United Kingdom +11111"
+5090e374a0d505040ca6fe957936a12026f5347a,Human Emotion Classification From Videos,"Human Emotion Classification From Videos +Maria Soledad Elli (mselli) - Dhvani Kotak (dkotak)"
+50bc8a4e7e6ab9837c6244b29ff800f523494d65,Learning to Answer Questions from Image Using Convolutional Neural Network,"Learning to Answer Questions From Image Using Convolutional Neural Network +Noah’s Ark Lab, Huawei Technologies +Lin Ma +Zhengdong Lu +Hang Li"
+506e2850a564b6085d8f0af4834a97ddd301d423,Alexandra Teynor Visual Object Class Recognition using Local Descriptions,"Alexandra Teynor +Visual Object Class Recognition +using Local Descriptions +Dissertation zur Erlangung des Doktorgrades +der Fakultät für Angewandte Wissenschaften +der Albert-Ludwigs-Universität Freiburg im Breisgau +August 2008"
5058a7ec68c32984c33f357ebaee96c59e269425,A Comparative Evaluation of Regression Learning Algorithms for Facial Age Estimation,"A Comparative Evaluation of Regression Learning Algorithms for Facial Age Estimation Carles Fern´andez1, Ivan Huerta2, and Andrea Prati2 @@ -693,6 +2361,21 @@ Marie-Francine Moens Dept. of Computer Science K.U.Leuven, Belgium"
50a0930cb8cc353e15a5cb4d2f41b365675b5ebf,Robust Facial Landmark Detection and Face Tracking in Thermal Infrared Images using Active Appearance Models,
+507660f778fe913f6e1957fe39a87cbf50a52b2e,Sparse Camera Network for Visual Surveillance -- A Comprehensive Survey,"Sparse Camera Network for Visual +Surveillance – A Comprehensive Survey +Mingli Song, Member, IEEE, Dacheng Tao, Senior Member, IEEE, +nd Stephen J. Maybank, Fellow, IEEE"
+50fb5e2f0c2fe8679c218ff88d4906e5a0812d34,"Sketch-editing games: human-machine communication, game theory and applications","Sketch-Editing Games: Human-Machine Communication, +Game Theory and Applications +Andre Ribeiro +Takeo Igarashi +JST, Erato, Igarashi +Design Interface Project, +-28-1-7F, Koishikawa +JST, Erato, Igarashi +Design Interface Project, +-28-1-7F, Koishikawa +sketches). We argue"
50eb2ee977f0f53ab4b39edc4be6b760a2b05f96,Emotion recognition based on texture analysis of facial expression,"Australian Journal of Basic and Applied Sciences, 11(5) April 2017, Pages: 1-11 AUSTRALIAN JOURNAL OF BASIC AND APPLIED SCIENCES @@ -716,6 +2399,21 @@ Template Based Methods, Texture" 50d15cb17144344bb1879c0a5de7207471b9ff74,"Divide, Share, and Conquer: Multi-task Attribute Learning with Selective Sharing","Divide, Share, and Conquer: Multi-task Attribute Learning with Selective Sharing Chao-Yeh Chen*, Dinesh Jayaraman*, Fei Sha, and Kristen Grauman"
+505942c5f9b5779bda2859e22e9ed0b1c0c7b54a,Towards 3D Face Recognition in the Real: A Registration-Free Approach Using Fine-Grained Matching of 3D Keypoint Descriptors,"Int J Comput Vis +DOI 10.1007/s11263-014-0785-6 +Towards 3D Face Recognition in the Real: A Registration-Free +Approach Using Fine-Grained Matching of 3D Keypoint +Descriptors +Huibin Li · Di Huang · Jean-Marie Morvan · +Yunhong Wang · Liming Chen +Received: 26 April 2013 / Accepted: 27 October 2014 +© Springer Science+Business Media New York 2014"
+503c16d9cb1560f13a7d6baedf8c9f889b22459d,Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation,"Encoder-Decoder with Atrous Separable +Convolution for Semantic Image Segmentation +Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and +Hartwig Adam +{lcchen, yukun, gpapan, fschroff, +Google Inc."
50d961508ec192197f78b898ff5d44dc004ef26d,A Low Indexed Content Based Neural Network Approach for Natural Objects Recognition,"International Journal of Computer science & Information Technology (IJCSIT), Vol 1, No 2, November 2009 A LOW INDEXED CONTENT BASED NEURAL NETWORK APPROACH FOR @@ -736,6 +2434,36 @@ Signal Processing Laboratory (LTS5), ´Ecole Polytechnique F´ed´erale de Lausa REVISITING CLASSIFIER TWO-SAMPLE TESTS David Lopez-Paz1, Maxime Oquab1,2 Facebook AI Research, 2WILLOW project team, Inria / ENS / CNRS"
+500993a8852f766d4bac7b5039b9072b587e4d09,HARRISON: A Benchmark on HAshtag Recommendation for Real-world Images in Social Networks,"PARK, LI, KIM: HARRISON: A BENCHMARK FOR IMAGE HASHTAG RECOMMENDATION1 +HARRISON: A Benchmark on HAshtag +Recommendation for Real-world Images in +SOcial Networks +School of Electrical Engineering +KAIST +South Korea +Minseok Park +Hanxiang Li +Junmo Kim"
+50984f8345a3120d0e6c0a75adc2ac1a13e37961,Impaired face processing in autism: fact or artifact?,"DOI 10.1007/s10803-005-0050-5 +Published Online: February 14, 2006 +Impaired Face Processing in Autism: Fact or Artifact? +Boutheina Jemel,1,3–5 Laurent Mottron,2–4 and Michelle Dawson2 +Within the last 10 years, there has been an upsurge of interest in face processing abilities in +utism which has generated a proliferation of new empirical demonstrations employing a +variety of measuring techniques. Observably atypical social behaviors early in the develop- +ment of children with autism have led to the contention that autism is a condition where the +processing of social +is impaired. While several empirical +sources of evidence lend support to this hypothesis, others suggest that there are conditions +under which autistic individuals do not differ from typically developing persons. The present +paper reviews this bulk of empirical evidence, and concludes that the versatility and abilities of +face processing in persons with autism have been underestimated. +information, particularly faces, +KEY WORDS: Autism; face processing; FFA; configural; local bias. +Impaired face processing is one of the most +the social cognition +ommonly cited aspects of +deficits observed among persons with autism spec-"
505e55d0be8e48b30067fb132f05a91650666c41,A Model of Illumination Variation for Robust Face Recognition,"A Model of Illumination Variation for Robust Face Recognition Florent Perronnin and Jean-Luc Dugelay Institut Eur´ecom @@ -757,12 +2485,89 @@ Dipl.-Inform. Tobias Gehrig MARCH 2011 KIT – University of the State of Baden-Württemberg and National Laboratory of the Helmholtz Association www.kit.edu"
+5020a75c45416073d0b07b1deb7382bc80de1779,Human Detection Using Learned Part Alphabet and Pose Dictionary,"Human Detection using Learned Part Alphabet +nd Pose Dictionary +Anonymous ECCV submission +Paper ID 895"
+50e5dd45a94a56cb973e51dc3347e621266db7e4,3D Face Recognition Using Concurrent Neural Modules,"D Face Recognition Using Concurrent Neural Modules +VICTOR-EMIL NEAGOE , IONUT MITRACHE, AND DANIEL CARAUSU +Depart. Electronics, Telecommunications & Information Technology +Polytechnic University of Bucharest +Splaiul Independentei No. 313, Sector 6, Bucharest +ROMANIA +Email:"
+684c8acd49148020e9bf9c4f4aefc03708a6dac0,Video-Based Person Re-Identification With Accumulative Motion Context,"Video-based Person Re-identification with +Accumulative Motion Context +Hao Liu, Zequn Jie, Karlekar Jayashree, Meibin Qi, Jianguo Jiang and Shuicheng Yan, Fellow, IEEE, Jiashi Feng"
+68df1f746a3434ee8bcc8918d46809ddaad38b12,Subspace learning in minimax detection,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) +978-1-4799-2893-4/14/$31.00 ©2014 IEEE +Email: {raja.fazliza, david.mary, +SUBSPACE LEARNING IN MINIMAX DETECTION +Raja Fazliza R. Suleiman, David Mary and Andr´e Ferrari +Campus Valrose, 06108 Nice Cedex 02, FRANCE +Laboratoire J.-L. Lagrange, UMR7293, +. INTRODUCTION AND PRIOR WORKS +(cid:26) H0"
680d662c30739521f5c4b76845cb341dce010735,Part and Attribute Discovery from Relative Annotations,"Int J Comput Vis (2014) 108:82–96 DOI 10.1007/s11263-014-0716-6 Part and Attribute Discovery from Relative Annotations Subhransu Maji · Gregory Shakhnarovich Received: 25 February 2013 / Accepted: 14 March 2014 / Published online: 26 April 2014 © Springer Science+Business Media New York 2014"
+68ae4db6acf5361486f153ee0c0d540e0823682a,FlashReport Memory conformity for con fi dently recognized items : The power of social in fl uence on memory reports,"Journal of Experimental Social Psychology 48 (2012) 783–786 +Contents lists available at SciVerse ScienceDirect +Journal of Experimental Social Psychology +j o u r n a l h o m e pa ge : w ww . e l s e v i e r . c o m/ l o c a t e / j e s p +FlashReport +Memory conformity for confidently recognized items: The power of social influence +on memory reports +Ruth Horry ⁎, Matthew A. Palmer 1, Michelle L. Sexton, Neil Brewer +Flinders University, Australia +r t i c l e +i n f o +b s t r a c t +Article history: +Received 14 September 2011 +Revised 9 December 2011 +Available online 22 December 2011 +Keywords: +Memory conformity +Confidence +Face recognition"
+68e4ed4daa2ae94c789443ed222601a4a47f9a45,Building Extraction from Polarimetric Interferometric Sar Data Using Bayesian Network,"BUILDING EXTRACTION FROM POLARIMETRIC INTERFEROMETRIC SAR DATA +USING BAYESIAN NETWORK +Wenju He and Olaf Hellwich +Berlin University of Technology +{wenjuhe, +. INTRODUCTION +Many researches have been done to extract buildings from high resolution Synthetic Aperture Radar (SAR) data. The extraction +problem is far from solved due to many constraints, e.g. SAR side-look imaging, speckle, and lack of object extent in SAR +images. Building detection algorithms usually use intensity information or textures. Layovers and shadows can be discriminated +from other objects since they have distinct appearances. The detection is hindered by the small geometric extent of buildings +in SAR images and the orientation dependency of reflections. Many buildings are occluded with surrounding environments. +The interactions between radar and various buildings are hard to model. Polarimetric SAR data can resolve some ambiguities +ecause polarimetry can be used to analyze physical scattering properties. Scatterers formed by buildings have strong double- +ounce reflections. Polarimetric SAR data also allow us to extract rich features for object detection. Polarimetric interferometric +SAR (PolinSAR) data are more promising since they are able to provide object height information. Furthermore, coherent +scatterer and permanent scatterer analysis using interferometric SAR (InSAR) data are powerful in urban change detection +pplications. As to building localization, a height map retrieved from PolinSAR data is very advantageous. PolinSAR data are +expected to further resolve ambiguities in building detection problems. +For meter-resolution PolinSAR data, however, it is hard to retrieve phases of building roofs from interferometric phase +ecause of complex scattering mechanisms and building geometries. Building height image was derived from InSAR digital"
+683260bf133c282439b91ac4427d42d73a5988b5,"Optimizing Program Performance via Similarity, Using Feature-aware and Feature-agnostic Characterization Approaches","UNIVERSITY OF CALIFORNIA, +IRVINE +Optimizing Program Performance via Similarity, +Using Feature-aware and Feature-agnostic Characterization Approaches +DISSERTATION +submitted in partial satisfaction of the requirements +for the degree of +DOCTOR OF PHILOSOPHY +in Information and Computer Science +Rosario Cammarota +Dissertation Committee: +Professor Alexander V. Veidenbaum, Chair +Professor Alexandru Nicolau +Professor Nikil Dutt"
68a2ee5c5b76b6feeb3170aaff09b1566ec2cdf5,Age Classification Based on Simple Lbp Transitions,"AGE CLASSIFICATION BASED ON SIMPLE LBP TRANSITIONS Research Scholar & Assoc Professor, Aditya institute of Technology and Management, Tekkalli-532 201, A.P., @@ -772,8 +2577,48 @@ Dr. V.Vijaya Kumar A. Obulesu Dean-Computer Sciences (CSE & IT), Anurag Group of Institutions, Hyderabad – 500088, A.P., India., 3Asst. Professor, Dept. Of CSE, Anurag Group of Institutions, Hyderabad – 500088, A.P., India."
+6821a3fa67d9d58655c26e24b568fda1229ac5be,Fast and robust object segmentation with the Integral Linear Classifier,"Fast and Robust Object Segmentation with the Integral Linear Classifier +David Aldavert +Computer Vision Center +Dept. Computer Science +Arnau Ramisa +INRIA-Grenoble +Artificial Intelligence Research +Univ. Aut`onoma de Barcelona +Institute (IIIA-CSIC) +Ramon Lopez de Mantaras +Artificial Intelligence Research +Institute (IIIA-CSIC) +Campus UAB +Ricardo Toledo +Computer Vision Center +Dept. Computer Science +Univ. Aut`onoma de Barcelona"
68d2afd8c5c1c3a9bbda3dd209184e368e4376b9,Representation Learning by Rotating Your Faces,"Representation Learning by Rotating Your Faces Luan Tran, Xi Yin, and Xiaoming Liu, Member, IEEE"
+688cb9fd33769b152806c04ef6fc276629a9f300,LocNet: Improving Localization Accuracy for Object Detection,"LocNet: Improving Localization Accuracy for Object Detection +Spyros Gidaris +Universite Paris Est, Ecole des Ponts ParisTech +Nikos Komodakis +Universite Paris Est, Ecole des Ponts ParisTech"
+68eb5404a22fcca595cc6360e9a77a4b09156eb2,Appearance-based person reidentification in camera networks: problem overview and current approaches,"J Ambient Intell Human Comput (2011) 2:127–151 +DOI 10.1007/s12652-010-0034-y +O R I G I N A L R E S E A R C H +Appearance-based person reidentification in camera networks: +problem overview and current approaches +Gianfranco Doretto • Thomas Sebastian • +Peter Tu • Jens Rittscher +Received: 30 January 2010 / Accepted: 4 October 2010 / Published online: 14 January 2011 +Ó Springer-Verlag 2011"
+6872615b0298aa01affa3b8d71e4d5547244278f,Weighted Fourier Image Analysis and Modeling,"WEIGHTED FOURIER IMAGE ANALYSIS +AND MODELING +Shubing Wang +A dissertation submitted in partial fulfillment of the +requirements for the degree of +Doctor of Philosophy +(Statistics) +t the +UNIVERSITY OF WISCONSIN – MADISON"
6859b891a079a30ef16f01ba8b85dc45bd22c352,"2D Face Recognition Based on PCA & Comparison of Manhattan Distance, Euclidean Distance & Chebychev Distance","International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 10, October 2014) D Face Recognition Based on PCA & Comparison of @@ -809,6 +2654,41 @@ Veracruz, M´exico" Discriminative Block-Diagonal Representation Learning for Image Recognition Zheng Zhang, Yong Xu, Senior Member, IEEE, Ling Shao, Senior Member, IEEE, Jian Yang, Member, IEEE"
+683fbd7593cf5c22ef54004bb89c469eab2f656e,URJC&UNED at ImageCLEF 2013 Photo Annotation Task,"URJCyUNED at ImageCLEF 2012 Photo +Annotation task⋆ +Jes´us S´anchez-Oro1, Soto Montalvo1, Antonio S. Montemayor1, Ra´ul Cabido1, +Juan J. Pantrigo1, Abraham Duarte1, V´ıctor Fresno2, and Raquel Mart´ınez2 +Universidad Rey Juan Carlos, M(cid:19)ostoles, Spain +Universidad Nacional de Educaci(cid:19)on a Distancia, Madrid, Spain"
+68333b73613c59914bfe1264a440b3cf854dc15c,Mugeetion: Musical Interface Using Facial Gesture and Emotion,"Mugeetion: Musical Interface Using Facial Gesture and Emotion +Eunjeong Stella Koh +Music Department +UC San Diego"
+6864b089c8586b0e3f6bd6736cabea96b1c4a28a,Robust classification for occluded ear via Gabor scale feature-based non-negative sparse representation,"Robust classification for occluded ear via +Gabor scale feature-based non-negative +sparse representation +Baoqing Zhang +Zhichun Mu +Chen Li +Hui Zeng +Downloaded From: http://opticalengineering.spiedigitallibrary.org/ on 01/02/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx"
+68becbe61cf30ef93b2679866d3a511e919ffb2f,"Motor, emotional, and cognitive empathy in children and adolescents with autism spectrum disorder and conduct disorder.","J Abnorm Child Psychol (2013) 41:425–443 +DOI 10.1007/s10802-012-9689-5 +Motor, Emotional, and Cognitive Empathy in Children +nd Adolescents with Autism Spectrum Disorder +nd Conduct Disorder +Danielle Bons & Egon van den Broek & Floor Scheepers & +Pierre Herpers & Nanda Rommelse & Jan K. Buitelaaar +Published online: 25 October 2012 +# Springer Science+Business Media New York 2012"
+688680d9902f688b9ac2d47c399ceebd1014d785,GIS-supported people tracking re-acquisition in a multi-camera environment,"GIS-supported People Tracking Re-Acquisition in a Multi-Camera +Environment +Anastasios Dimou1, Vasileios Lovatsis1, Andreas Papadakis2, Stelios Pantelopoulos2 and Petros +Daras1 +CERTH-ITI, 6th kilometer Harilaou-Thermi, Thessaloniki, Greece +SingularLogic, Athens, Greece +Keywords: +GIS, Re-Identification, Multi-camera."
685f8df14776457c1c324b0619c39b3872df617b,Face Recognition with Preprocessing and Neural Networks,"Master of Science Thesis in Electrical Engineering Department of Electrical Engineering, Linköping University, 2016 Face Recognition with @@ -840,8 +2720,57 @@ This study explores whether the myelinated vagal connection between the heart an is involved in emotion recognition. The Polyvagal theory postulates that the activity of the myelinated vagus nerve underlies socio-emotional skills. It has been proposed that the perception of emotions could be one of this skills dependent on heart-brain interactions. However, this"
+688ae87c5e40583ecf9ec6d06d4d15a3e62f5556,A New Angle on L2 Regularization,"A New Angle on L2 Regularization +(interactive version available at https://thomas-tanay.github.io/post--L2-regularization/) +Thomas Tanay +Lewis D Griffin +CoMPLEX, UCL +CoMPLEX, UCL +Deep neural networks have been shown to be vulnerable to the +dversarial example phenomenon: all models tested so far can have their +lassifications dramatically altered by small image perturbations [1, 2]. +The following predictions were for instance made by a state-of-the-art +network trained to recognize celebrities [3]:"
+68b44eb4c7440046783146064ae9e715a72766dc,An Investigation of Physiological Arousal in Children with Autism and Co-morbid Challenging Behaviour,"An Investigation of Physiological Arousal in Children with +Autism and Co-morbid Challenging Behaviour +Sinéad Lydon +A thesis submitted to Trinity College Dublin, the University of Dublin, +in partial fulfillment of the requirements for the Degree of Doctor of +Philosophy (PhD) in Psychology +Supervisors: Dr. Olive Healy (Trinity College Dublin) and +Professor Brian Hughes (National University of Ireland, Galway)."
+688f5cb02dc6c779fa9fd18f44b792f9626bdcd0,Visual pattern discovery in image and video data: a brief survey,"Visual Pattern Discovery in Image and Video Data: +A Brief Survey +Hongxing Wang, Gangqiang Zhao and Junsong Yuan"
68f9cb5ee129e2b9477faf01181cd7e3099d1824,ALDA Algorithms for Online Feature Extraction,"ALDA Algorithms for Online Feature Extraction Youness Aliyari Ghassabeh, Hamid Abrishami Moghaddam"
+68b01afed57ed7130d993dffc03dcbfa36d4e038,Adversarial Learning with Local Coordinate Coding,"Adversarial Learning with Local Coordinate Coding +Jiezhang Cao * 1 Yong Guo * 1 Qingyao Wu * 1 Chunhua Shen 2 Junzhou Huang 3 Mingkui Tan 1"
+687ef116d7115498f12dff1b3338d959f164ef6b,Using Thought-Provoking Children's Questions to Drive Artificial Intelligence Research,"Using Thought-Provoking Children’s Questions +to Drive Artificial Intelligence Research +Erik T. Mueller and Henry Minsky +Minsky Institute for Artificial Intelligence +http://minskyinstitute.org/ +September 14, 2015 00:09"
+68ba19afe924699b4a0c84af91c05deb5b03e3bd,Do Characteristics of Faces That Convey Trustworthiness and Dominance Underlie Perceptions of Criminality?,"Do Characteristics of Faces That Convey Trustworthiness +nd Dominance Underlie Perceptions of Criminality? +Heather D. Flowe* +College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, United Kingdom"
+68415682aa3e25178c9504866f64cf4b2a32273e,Capturing Complex 3D Human Motions with Kernelized Low-Rank Representation from Monocular RGB Camera,"Article +Capturing Complex 3D Human Motions with +Kernelized Low-Rank Representation from +Monocular RGB Camera +Xuan Wang 1,2,3,4, Fei Wang 1,2,3,4,* and Yanan Chen 1,2,3,4 +The Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, No.28 Xianning West Road, +Xi’an 710048, China; (X.W.); (Y.C.) +The School of Software Engineering, Xi’an Jiaotong University, No.28 Xianning West Road, +Xi’an 710048, China +National Engineering Laboratory for Visual Information Processing and Application, Xi’an Jiaotong +University, No.28 Xianning West Road, Xi’an 710048, China +Shaanxi Digital Technology and Intelligent System Key Laboratory, Xi’an Jiaotong University, No.28 +Xianning West Road, Xi’an 710048, China +* Correspondence: +Received: 5 July 2017; Accepted: 24 August 2017; Published: 3 September 2017"
68d40176e878ebffbc01ffb0556e8cb2756dd9e9,Locality Repulsion Projection and Minutia Extraction Based Similarity Measure for Face Recognition,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 International Conference on Humming Bird ( 01st March 2014) RESEARCH ARTICLE @@ -853,9 +2782,47 @@ AgnelAnushya P. is currently pursuing M.E (Computer Science and engineering) at Ramya P. is currently working as an Asst. Professor in the dept. of Information Technology at Vins Christian Engineering. ollege of Engineering."
+68c279d4fcc02710056e73a3b0d0d564a7615cad,Unified framework for fast exact and approximate search in dissimilarity spaces,"Unified Framework for Fast Exact and +Approximate Search in Dissimilarity Spaces +TOM´AˇS SKOPAL +Charles University in Prague +In multimedia systems we usually need to retrieve DB objects based on their similarity to a query +object, while the similarity assessment is provided by a measure which defines a (dis)similarity +score for every pair of DB objects. In most existing applications, the similarity measure is required +to be a metric, where the triangle inequality is utilized to speedup the search for relevant objects +y use of metric access methods (MAMs), e.g. the M-tree. A recent research has shown, however, +that non-metric measures are more appropriate for similarity modeling due to their robustness and +ease to model a made-to-measure similarity. Unfortunately, due to the lack of triangle inequality, +the non-metric measures cannot be directly utilized by MAMs. From another point of view, some +sophisticated similarity measures could be available in a black-box non-analytic form (e.g. as an +lgorithm or even a hardware device), where no information about their topological properties is +provided, so we have to consider them as non-metric measures as well. From yet another point +of view, the concept of similarity measuring itself is inherently imprecise and we often prefer fast +ut approximate retrieval over an exact but slower one. +To date, the mentioned aspects of similarity retrieval have been solved separately, i.e. exact +vs. approximate search or metric vs. non-metric search. In this paper we introduce a similarity +retrieval framework which incorporates both of the aspects into a single unified model. Based on"
6889d649c6bbd9c0042fadec6c813f8e894ac6cc,Analysis of Robust Soft Learning Vector Quantization and an application to Facial Expression Recognition,"Analysis of Robust Soft Learning Vector Quantization and an application to Facial Expression Recognition"
+680402e42c874c14a32146865d985588985744a4,Detection and Tracking of Multiple Humans in High-density Crowds,"DETECTION AND TRACKING OF MULTIPLE HUMANS IN +HIGH-DENSITY CROWDS +Irshad Ali +A research study submitted in partial fulfillment of the requirements for the +degree of Master of Engineering in +Computer Science +Examination Committee: Dr. Matthew N. Dailey (Chairperson) +Dr. Manukid Parnichkun (Member) +Dr. Nitin V. Afzulpurkar (Member) +Nationality: Pakistani +Previous Degree: Bachelor of Science in Computer Engineering +Samara State Technical University, Russia +Scholarship Donor: Higher Education Commission (HEC), Pakistan - AIT +Fellowship +Asian Institute of Technology +School of Engineering and Technology +Thailand +May 2009"
68c17aa1ecbff0787709be74d1d98d9efd78f410,Gender Classification from Face Images Using Mutual Information and Feature Fusion,"International Journal of Optomechatronics, 6: 92–119, 2012 Copyright # Taylor & Francis Group, LLC ISSN: 1559-9612 print=1559-9620 online @@ -896,11 +2863,55 @@ probe as a linear combination of nine blurred illumination basis images in the s pose, plus a sparse occlusion. We also advocate a recognition metric that capitalizes on the sparsity of the occluded pixels. The performance of our method is extensively validated on synthetic as well as real face data. © 2016 Optical Society of America"
+6844a700aee36bd809d1188f6f9e81707c513f19,Interactive model-based reconstruction of the human head using an RGB-D sensor,"Interactive Model-based Reconstruction of the +Human Head using an RGB-D Sensor +M. Zollh¨ofer, J. Thies, M. Colaianni, M. Stamminger, G. Greiner +Computer Graphics Group, University Erlangen-Nuremberg, Germany"
+682f735ef796370f510218eb7afb4d2a36cd1256,On Offline Evaluation of Vision-Based Driving Models,
6888f3402039a36028d0a7e2c3df6db94f5cb9bb,Classifier-to-generator Attack: Estimation,"Under review as a conference paper at ICLR 2018 CLASSIFIER-TO-GENERATOR ATTACK: ESTIMATION OF TRAINING DATA DISTRIBUTION FROM CLASSIFIER Anonymous authors Paper under double-blind review"
+68b6ec13d06facacf5637f90828ab5b6e352be60,Neural Proximal Gradient Descent for Compressive Imaging,"Neural Proximal Gradient Descent for Compressive +Imaging +Morteza Mardani1,2, Qingyun Sun4, Shreyas Vasawanala2, Vardan Papyan3, +Hatef Monajemi3, John Pauly1, and David Donoho3 +Depts. of Electrical Eng., Radiology, Statistics, and Mathematics; Stanford University"
+6898b0934d2bc34acc61a3c63fbb20337d7b9a95,Learning Styles and Emotion Recognition in a Fuzzy Expert System,"Learning Styles and Emotion Recognition in a Fuzzy +Expert System +Ramón Zatarain-Cabada, M. Lucía Barrón-Estrada, Rosalío Zatarain-Cabada +Instituto Tecnológico de Culiacán, Juan de Dios Bátiz s/n, Col. Guadalupe, Culiacán Sinaloa, +80220, Mexico +{rzatarain,"
+5782d17ad87262739d69dcbe76cadfa881179a91,Data Analysis Project: What Makes Paris Look like Paris?,"Data Analysis Project: What Makes Paris Look like +Paris? +Machine Learning Department +Carnegie-Mellon University +Pittsburgh, PA 15213 +Carl Doersch⇤"
+57235f22abcd6bb928007287b17e235dbef83347,Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency,"EXEMPLAR GUIDED UNSUPERVISED +IMAGE-TO- +IMAGE TRANSLATION WITH SEMANTIC CONSISTENCY +Liqian Ma1 Xu Jia2 +KU-Leuven/PSI, TRACE (Toyota Res in Europe) +{liqian.ma, xu.jia, tinne.tuytelaars, +{georgous, +Stamatios Georgoulis1,3 Tinne Tuytelaars2 Luc Van Gool1,3 +KU-Leuven/PSI, IMEC 3ETH Zurich"
+57165586f65f25edd9d14f0173c4c35dab8c2e66,Aligning plot synopses to videos for story-based retrieval,"Noname manuscript No. +(will be inserted by the editor) +Aligning Plot Synopses to Videos for Story-based Retrieval +Makarand Tapaswi · Martin B¨auml · Rainer Stiefelhagen +Received: date / Accepted: date"
+572785b5d6f6fa4b174d79725f82c056b0fb4565,"Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art","Computer Vision for Autonomous Vehicles: +Problems, Datasets and State-of-the-Art +Joel Janaia,∗, Fatma G¨uneya,∗, Aseem Behla,∗, Andreas Geigera,b +Autonomous Vision Group, Max Planck Institute for Intelligent Systems, Spemannstr. 41, D-72076 T¨ubingen, Germany +Computer Vision and Geometry Group, ETH Z¨urich, Universit¨atstrasse 6, CH-8092 Z¨urich, Switzerland"
+576372383bfd6ce6944d885e60b19151efdffc99,Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?,"Can we unify monocular detectors for autonomous driving +y using the pixel-wise semantic segmentation of CNNs? +Eduardo Romera, Luis M. Bergasa, Roberto Arroyo"
57fd229097e4822292d19329a17ceb013b2cb648,Fast Structural Binary Coding,"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16) Fast Structural Binary Coding ⇤Department of Electrical and Computer Engineering,University of California, San Diego @@ -912,6 +2923,40 @@ La Jolla, USA, 92093-0112. Email:" 57c59011614c43f51a509e10717e47505c776389,Unsupervised Human Action Detection by Action Matching,"Unsupervised Human Action Detection by Action Matching Basura Fernando∗ Sareh Shirazi† Stephen Gould∗ The Australian National University †Queensland University of Technology"
+5725c06b406b5291915a6bef8b5c3d20b2873aa0,Face Recognition Using Principal Component Analysis Based Feature Space by Incorporating with Probabilistic Neural Network,"International Journal of Computer Science Trends and Technology (IJCST) – Volume 4 Issue 2, Mar - Apr 2016 +RESEARCH ARTICLE +OPEN ACCESS +Face Recognition Using Principal Component Analysis +Based Feature Space By Incorporating With Probabilistic +Muhammad Tahir, Shahid Akbar, Shahzad, Maqsood Hayat, Nazia Azim +Neural Network +Department of Computer Science +Abdul Wali Khan University +Mardan - Pakistan"
+5740a5f9cbfe790afc0ba9a425cfb71197927470,Supplementary Material for Superpixel Sampling Networks,"Supplementary Material for +Superpixel Sampling Networks +Varun Jampani1, Deqing Sun1, Ming-Yu Liu1, +Ming-Hsuan Yang1,2, Jan Kautz1 +NVIDIA +UC Merced +In Section 1, we formally define the Acheivable Segmentation Accuracy (ASA) +used for evaluating superpixels. Then, in Section 2, we report F-measure and +Compactness scores with more visual results on different datasets. We also in- +lude a supplementary video1 that gives an overview of Superpixel Sampling +Networks (SSN) with a glimpse of experimental results. +Evaluation Metrics +Here, we formally define the Achievable Segmentation Accuracy (ASA) met- +ric that is used in the main paper. Given an image I with n pixels, let H ∈ +{0, 1,··· , m}n×1 denotes the superpixel segmentation with m superpixels. H is +j=1 H j, where jth segment is repre- +sented as H j. Similarly, let G ∈ {0, 1,··· , w}n×1 denotes ground-truth (GT) +l=1 Gl, where Gl denotes lth GT segment. +ASA Score. The ASA score between a given superpixel segmentation H and +the GT segmentation G is defined as"
+573c11e7e00389a033787984223ced536e15c904,Pictorial structures revisited: People detection and articulated pose estimation,"Pictorial Structures Revisited: People Detection and Articulated Pose Estimation +Mykhaylo Andriluka, Stefan Roth, and Bernt Schiele +Department of Computer Science, TU Darmstadt"
+5720784b7e45693109b867992e3f93e4c747e536,Sparse Methods for Robust and Efficient Visual Recognition,
57f8e1f461ab25614f5fe51a83601710142f8e88,Region Selection for Robust Face Verification using UMACE Filters,"Region Selection for Robust Face Verification using UMACE Filters Salina Abdul Samad*, Dzati Athiar Ramli, Aini Hussain Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering, @@ -958,6 +3003,32 @@ Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-resolution Network Ataer-Cansizoglu, E.; Jones, M.J.; Zhang, Z.; Sullivan, A. TR2018-116 August 24, 2018"
+57680f0d53392178bb3c431e03bcd8626c12f620,Semantic Image Segmentation,"Workshop track - ICLR 2017 +ADVERSARIAL EXAMPLES FOR +SEMANTIC IMAGE SEGMENTATION +Volker Fischer1, Mummadi Chaithanya Kumar2, Jan Hendrik Metzen1 & Thomas Brox2 +Bosch Center for Artificial Intelligence, Robert Bosch GmbH +University of Freiburg +{volker.fischer,"
+57ff1222a78a230c46fc81f22daa57981b0fa306,Face recognition in multi-camera surveillance videos using Dynamic Bayesian Network,"Face Recognition +in Multi-Camera +Surveillance +Videos using Dynamic Bayesian Network +Center for Research +Le An, Mehran Kafai, Bir +Bhanu +in Intelligent +Systems, +University +of California, +Riverside +.edu, mkafai bhanu"
+57e9b0d3ab6295e914d5a30cfaa3b2c81189abc1,Self-Learning Scene-Specific Pedestrian Detectors Using a Progressive Latent Model,"Self-learning Scene-specific Pedestrian Detectors +using a Progressive Latent Model +Qixiang Ye1,4, Tianliang Zhang 1, Qiang Qiu4, Baochang Zhang2, Jie Chen3, and Guillermo Sapiro4 +EECE, University of Chinese Academy of Sciences. +ASEE, Beihang University. 3CMV, Oulu University. 4ECE, Duke University."
+57b55a7a1adc8ec06285ebaf93995d67cf80c719,External Data Overcomplete Dictionary Similarity Graph ≈ + Probeimage Gallery Compressed Dictionary With Coefficient Design Phase : Operational Phase : CD Compressed Dictionary,
574705812f7c0e776ad5006ae5e61d9b071eebdb,A Novel Approach for Face Recognition Using PCA and Artificial Neural Network,"Karthik G et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.5, May- 2014, pg. 780-787 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing @@ -971,6 +3042,21 @@ Karthik G1, Sateesh Kumar H C2 ¹Deptartment of Telecommunication Engg., Dayananda Sagar College of Engg., India ²Department of Telecommunication Engg., Dayananda Sagar College of Engg., India email : 2 email :"
+57e8e226e605fe6491111c5dc9461527c5fce56c,Articulated Object Detection,"Articulated Object Detection +Maciej Halber +MEng Computer Science +Submission Date: 26th April 2013 +Supervisors +Niloy J. Mitra +Simon Julier +This report is submitted as part requirement for the MEng Degree in Computer +Science at UCL. It is substantially the result of my own work except where ex- +plicitly indicated in the text. The report may be freely copied and distributed +provided the source is explicitly acknowledged."
+5712cfc11c561c453da6a31d515f4340dacc91a4,3D Facial Expression Reconstruction using Cascaded Regression,"SUBMITTED TO PATTERN RECOGNITION LETTERS +Cascaded Regression using Landmark +Displacement for 3D Face Reconstruction +Fanzi Wu, Songnan Li, Tianhao Zhao, and King Ngi Ngan,Lv Sheng"
571b83f7fc01163383e6ca6a9791aea79cafa7dd,SeqFace: Make full use of sequence information for face recognition,"SeqFace: Make full use of sequence information for face recognition Wei Hu1 ∗ Yangyu Huang2 @@ -981,6 +3067,26 @@ Wei Li1 College of Information Science and Technology, Beijing University of Chemical Technology, China YUNSHITU Corp., China"
+5700291077b509b11fb227f84ee9fc2de8f2df99,Line search and trust region strategies for canonical decomposition of semi-nonnegative semi-symmetric 3rd order tensors,"Line search and trust region strategies for canonical +decomposition of semi-nonnegative semi-symmetric 3rd +Julie Coloigner, Ahmad Karfoul, Laurent Albera, Pierre Comon +order tensors +To cite this version: +Julie Coloigner, Ahmad Karfoul, Laurent Albera, Pierre Comon. Line search and trust region +strategies for canonical decomposition of semi-nonnegative semi-symmetric 3rd order tensors. +Linear Algebra and Applications, Elsevier - Academic Press, 2014, 450, pp.334-374. +HAL Id: hal-00945606 +https://hal.archives-ouvertes.fr/hal-00945606 +Submitted on 12 Feb 2014 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
57a14a65e8ae15176c9afae874854e8b0f23dca7,Seeing Mixed Emotions: The Specificity of Emotion Perception From Static and Dynamic Facial Expressions Across Cultures,"UvA-DARE (Digital Academic Repository) Seeing mixed emotions: The specificity of emotion perception from static and dynamic facial expressions across cultures @@ -1001,6 +3107,22 @@ If you believe that digital publication of certain material infringes any of you your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible."
+573b687ad970e1931debbf366004c0983de28718,A Corpus for Investigating the Multimodal Nature of Multi-Speaker Spontaneous Conversations – EVA Corpus,"A Corpus for Investigating the Multimodal Nature of Multi-Speaker +Spontaneous Conversations – EVA Corpus +IZIDOR MLAKAR, ZDRAVKO KAČIČ, MATEJ ROJC +Faculty of Electrical Engineering and Computer Science, University of Maribor +SLOVENIA"
+57126589b3fe62c35a36a2646dac3045d095ecf5,Adversarial Defense based on Structure-to-Signal Autoencoders,"Adversarial Defense based on +Structure-to-Signal Autoencoders +Joachim Folz(cid:63), Sebastian Palacio(cid:63), Joern Hees, Damian Borth, and Andreas +Dengel +German Research Center for Artificial Intelligence (DFKI) +TU Kaiserslautern"
+57fd8bafa4526b9a56fe43fac22dd62b2ab94563,Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering,"Under review as a conference paper at ICLR 2018 +BEYOND SHARED HIERARCHIES: DEEP MULTITASK +LEARNING THROUGH SOFT LAYER ORDERING +Anonymous authors +Paper under double-blind review"
57d37ad025b5796457eee7392d2038910988655a,Aeaeêêìáîî Áåèääååaeììáçae Çç Àááêêêàáááä Aeçîîäìì Ììììçê,"GEERATVEEETATF DagaEha @@ -1012,9 +3134,77 @@ Re ieefheDegeef TheSch Decebe2009"
+57e562cf99b3dfbb6baa5bbf665aa6fd97ffe8ca,Expression-Compensated 3D Face Recognition with Geodesically Aligned Bilinear Models,"Expression-Compensated 3D Face Recognition with Geodesically +Aligned Bilinear Models +Iordanis Mpiperis1,2,Sotiris Malassiotis1 and Michael G. Strintzis1,2"
+3b319645bfdc67da7d02db766e17a3e0a37be47b,On the relationship between visual attributes and convolutional networks,"On the Relationship between Visual Attributes and Convolutional Networks +Victor Escorcia1,2, Juan Carlos Niebles2, Bernard Ghanem1 +King Abdullah University of Science and Technology (KAUST), Saudi Arabia. 2Universidad del Norte, Colombia. +The seminal work of Krizhevsky et al. [3] that trained a large convo- +lutional network (conv-net) for image-level object recognition on the Ima- +geNet challenge is considered a major stepping stone for subsequent work in +onv-net based visual recognition. Such a network is able to automatically +learn a hierarchy of nonlinear features that richly describe image content as +well as discriminate between object classes. Recent work [4] has shown that +features extracted from a conv-net trained on ImageNet are general purpose +(or black-box) enough to achieve state-of-the-art results in various other +recognition tasks, including scene, fine-grained, and even action recogni- +tion. However, unlike hand-crafted features, those learned by a conv-net +re usually not visually intuitive and straightforward to interpret. Despite +their excellent recognition performance, understanding and interpreting the +inner workings of conv-nets remains mostly elusive to the community. It +is this lack of deep understanding that is currently motivating researchers +to look under the hood and comprehend how and why these deep networks +work so well in practice. Inspired by recent observations on the analysis of +onv-nets [1], this paper takes another step in a similar direction, namely"
3b1aaac41fc7847dd8a6a66d29d8881f75c91ad5,Sparse Representation-Based Open Set Recognition,"Sparse Representation-based Open Set Recognition He Zhang, Student Member, IEEE and Vishal M. Patel, Senior Member, IEEE"
+3b311a1ce30f9c0f3dc1d9c0cf25f13127a5e48c,A Coarse-to-fine Pyramidal Model for Person Re-identification via Multi-Loss Dynamic Training,"A Coarse-to-fine Pyramidal Model for Person Re-identification via Multi-Loss +Dynamic Training +Feng Zheng, Xing Sun, Xinyang Jiang, Xiaowei Guo, Zongqiao Yu, Feiyue Huang +{winfredsun, sevjiang, scorpioguo, quentinyu, +YouTu Lab, Tencent +Shanghai, China"
+3b4177556f1c9f5a8f8e1b2e8d824dee20e388e4,Spatial Weighting for Bag-of-Features,"Spatial Weighting for Bag-of-Features +Marcin Marsza(cid:7)ek +Cordelia Schmid +INRIA Rh(cid:136)one-Alpes, LEAR - GRAVIR +665 av de l’Europe, 38330 Montbonnot, France"
+3ba3ef6d8394055d43bf4fe62227fbae8ab9b195,Finding images of difficult entities in the long tail,"Finding Images of Difficult Entities in the Long Tail +Bilyana Taneva +Max-Planck Institute for +Informatics +Saarbrücken, Germany +Mouna Kacimi +Free University of +Bozen-Bolzano +Italy +Gerhard Weikum +Max-Planck Institute for +Informatics +Saarbrücken, Germany"
3bc776eb1f4e2776f98189e17f0d5a78bb755ef4,View Synthesis from Image and Video for Object Recognition Applications,
+3bfa75238e15e869b902ceb62b31ffddbe8ccb0d,Describing Images using Inferred Visual Dependency Representations,"Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics +nd the 7th International Joint Conference on Natural Language Processing, pages 42–52, +Beijing, China, July 26-31, 2015. c(cid:13)2015 Association for Computational Linguistics"
+3b14bdb0b1a7353d94973ef4c1578e1bd4a4e35e,Three dimensional binary edge feature representation for pain expression analysis,"Three Dimensional Binary Edge +Feature Representation for Pain +Expression Analysis +Xing Zhang1, Lijun Yin1, Jeffrey F. Cohn2 +State University of New York at Binghamton; 2University of Pittsburgh"
+3beb94f61b5909fca8917b0475983ea2c66f1df2,Shape model fitting algorithm without point correspondence,"0th European Signal Processing Conference (EUSIPCO 2012) +© EURASIP, 2012 - ISSN 2076-1465 +. INTRODUCTION"
+3b1b94441010615195a5c404409ce2416860508c,Image Captioning and Visual Question Answering Based on Attributes and External Knowledge,"MANUSCRIPT, 2016 +Image Captioning and Visual Question +Answering Based on Attributes +nd External Knowledge +Qi Wu, Chunhua Shen, Peng Wang, Anthony Dick, Anton van den Hengel"
+3b304585d5af0afe98a85d6e0559315fbf3a7807,An Improved Labelling for the INRIA Person Data Set for Pedestrian Detection,"An Improved Labelling for the INRIA Person +Data Set for Pedestrian Detection +Matteo Taiana, Jacinto Nascimento, and Alexandre Bernardino(cid:63) +Institute for Systems and Robotics, IST, Lisboa, Portugal, +WWW home page: http://users.isr.ist.utl.pt/~mtaiana"
3b15a48ffe3c6b3f2518a7c395280a11a5f58ab0,On knowledge transfer in object class recognition,"On Knowledge Transfer in Object Class Recognition A dissertation approved by @@ -1032,15 +3222,89 @@ Prof. Dr. Bernt Schiele, co-examiner Date of Submission: 12th of August, 2010 Date of Defense: 23rd of September, 2010 Darmstadt, 2010"
-3baa3d5325f00c7edc1f1427fcd5bdc6a420a63f,Enhancing Convolutional Neural Networks for Face Recognition with Occlusion Maps and Batch Triplet Loss,"Enhancing Convolutional Neural Networks for Face Recognition with +3bbdfa097a4c39012cb322b23051e360c2f7f023,Learning Race from Face: A Survey,"Learning Race from Face: A Survey +Siyao Fu, Member, IEEE, Haibo He, Senior Member, IEEE, and Zeng-Guang Hou, Senior Member, IEEE"
+3baa3d5325f00c7edc1f1427fcd5bdc6a420a63f,Enhancing convolutional neural networks for face recognition with occlusion maps and batch triplet loss,"Enhancing Convolutional Neural Networks for Face Recognition with Occlusion Maps and Batch Triplet Loss Daniel S´aez Triguerosa,b, Li Menga,∗, Margaret Hartnettb School of Engineering and Technology, University of Hertfordshire, Hatfield AL10 9AB, UK IDscan Biometrics (a GBG company), London E14 9QD, UK"
+3b1ba9818e2ee6a54e7ec033c5b2ec8bdbe2935f,Social Signaling Descriptor for Group Behaviour Analysis,"Social Signaling Descriptor for Group +Behaviour Analysis +Eduardo M. Pereira1,2(B), Lucian Ciobanu1, and Jaime S. Cardoso1,2 +Faculty of Engineering of the University of Porto, Rua Dr. Roberto Frias, 378, +INESC TEC, Porto, Portugal +200 - 465 Porto, Portugal"
+3b996a2e641be7bd395620d30364a27d1558cbad,Tracking Related Multiple Targets in Videos,"Tracking Related Multiple Targets +in Videos +DISSERTATION +zur Erlangung des akademischen Grades +Doktor/in der technischen Wissenschaften +eingereicht von +Nicole M. Artner +Matrikelnummer 0727746 +n der +Fakultät für Informatik der Technischen Universität Wien +Betreuung: O.Univ.Prof. Dipl.Ing. Dr.techn. Walter G. Kropatsch +Diese Dissertation haben begutachtet: +(O.Univ.Prof. Dipl.Ing. Dr.techn. +(Prof. Em. Dr. Horst Bunke) +Walter G. Kropatsch) +Wien, 10.10.2013 +(Nicole M. Artner) +A-1040 Wien (cid:2) Karlsplatz 13 (cid:2) Tel. +43-1-58801-0 (cid:2) www.tuwien.ac.at +Technische Universität Wien"
+3b6310052026fc641d3fa639647342c45d8f5bd5,Eye Contact Modulates Cognitive Processing Differently in Children With Autism,"Child Development, xxxx 2014, Volume 00, Number 0, Pages 1–11 +Eye Contact Modulates Cognitive Processing Differently in +Children With Autism +Terje Falck-Ytter +Karolinska Institutet and Uppsala University +Christoffer Carlstr€om and Martin Johansson +Uppsala University +In humans, effortful cognitive processing frequently takes place during social interaction, with eye contact +eing an important component. This study shows that the effect of eye contact on memory for nonsocial infor- +mation is different in children with typical development than in children with autism, a disorder of social +ommunication. Direct gaze facilitated memory performance in children with typical development (n = 25, +6 years old), but no such facilitation was seen in the clinical group (n = 10, 6 years old). Eye tracking con- +ducted during the cognitive test revealed strikingly similar patterns of eye movements, indicating that the +results cannot be explained by differences in overt attention. Collectively, these findings have theoretical sig- +nificance and practical implications for testing practices in children. +Being looked at is a strong signal, indicating that +the other person is attending to you and processing +information about you. In many nonhuman species, +direct gaze functions as an aversive stimulus, likely +ecause of the threat value associated with eye con-"
+3b92916dd9d772cf1d167461a548115013a954a8,Unsupervised Framework for Interactions Modeling between Multiple Objects,
3ba8f8b6bfb36465018430ffaef10d2caf3cfa7e,Local Directional Number Pattern for Face Analysis: Face and Expression Recognition,"Local Directional Number Pattern for Face Analysis: Face and Expression Recognition Adin Ramirez Rivera, Student Member, IEEE, Jorge Rojas Castillo, Student Member, IEEE, nd Oksam Chae, Member, IEEE"
+3b38dc6d4f676ace52672f6788b66c9abb10d702,Ph.D. Showcase: Measuring Terrain Distances Through Extracted Channel Networks,"Ph.D. Showcase: Measuring Terrain Distances Through +Extracted Channel Networks +PhD Student: +Christopher Stuetzle +Dept. Computer Science +PhD Superviser: +W. Randolph Franklin +Dept. Electrical Engineering +PhD Superviser: +Barbara Cutler +Dept. Computer Science +Mehrad Kamalzare +Dept. Civil Engineering +Zhongxian Chen +Dept. Computer Science +Thomas Zimmie +Dept. Civil Engineering"
+3b9ee03255eb5a0040676eead1767db431e83562,Conference on Computer Vision and Pattern Recognition,"013 IEEE Conference on Computer Vision and Pattern Recognition +013 IEEE Conference on Computer Vision and Pattern Recognition +013 IEEE Conference on Computer Vision and Pattern Recognition +063-6919/13 $26.00 © 2013 IEEE +063-6919/13 $26.00 © 2013 IEEE +063-6919/13 $26.00 © 2013 IEEE +DOI 10.1109/CVPR.2013.236 +DOI 10.1109/CVPR.2013.236 +DOI 10.1109/CVPR.2013.236"
3b9d94752f8488106b2c007e11c193f35d941e92,"Appearance, Visual and Social Ensembles for Face Recognition in Personal Photo Collections","#2052 CVPR 2013 Submission #2052. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. #2052 @@ -1048,6 +3312,12 @@ Appearance, Visual and Social Ensembles for Face Recognition in Personal Photo Collections Anonymous CVPR submission Paper ID 2052"
+3bd63bea64c770df5049879f4398e65f958ebd23,Predicting an Object Location Using a Global Image Representation,"Predicting an Object Location using a Global Image Representation +Jose A. Rodriguez-Serrano and Diane Larlus +Computer Vision Group, Xerox Research Centre Europe"
+3b47e618c5ceb1c16db7f709dd1cfe53d7417b54,Discrimination on the Grassmann Manifold: Fundamental Limits of Subspace Classifiers,"Discrimination on the Grassmann Manifold: +Fundamental Limits of Subspace Classifiers +Matthew Nokleby, Member, IEEE, Miguel Rodrigues, Member, IEEE, and Robert Calderbank, Fellow,"
3b557c4fd6775afc80c2cf7c8b16edde125b270e,Face recognition: Perspectives from the real world,"Face Recognition: Perspectives from the Real-World Bappaditya Mandal @@ -1055,6 +3325,52 @@ Institute for Infocomm Research, A*STAR, Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632. Phone: +65 6408 2071; Fax: +65 6776 1378; E-mail:"
+3b2f78a4edf5da876e52513d0e3960da7d3a253f,Qualitative Evaluation of Detection and Tracking Performance,"Qualitative Evaluation of Detection and Tracking +Performance +Swaminathan Sankaranarayanan, Francois Bremond, David Tax +To cite this version: +Swaminathan Sankaranarayanan, Francois Bremond, David Tax. Qualitative Evaluation of Detection +nd Tracking Performance. 9th IEEE International Conference On Advanced Video and Signal Based +Surveillance (AVSS 12), Sep 2012, Beijing, China. IEEE, pp.362-367, 2012, 2012 IEEE Ninth Inter- +national Conference on Advanced Video and Signal-Based Surveillance. <10.1109/AVSS.2012.57>. +<hal-00763587> +HAL Id: hal-00763587 +https://hal.inria.fr/hal-00763587 +Submitted on 14 Dec 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents"
+3b2697d76f035304bfeb57f6a682224c87645065,ImageNet Large Scale Visual Recognition Challenge,"Noname manuscript No. +(will be inserted by the editor) +ImageNet Large Scale Visual Recognition Challenge +Olga Russakovsky* · Jia Deng* · Hao Su · Jonathan Krause · +Sanjeev Satheesh · Sean Ma · Zhiheng Huang · Andrej Karpathy · +Aditya Khosla · Michael Bernstein · Alexander C. Berg · Li Fei-Fei +Received: date / Accepted: date"
+3b8ad690f8d43d189ea2f2559c41b6eebac8dcc8,Mobile 3D object detection in clutter,"Mobile 3D Object Detection in Clutter +David Meger and James J. Little"
+3bf66814817f582510e0f0a717112b78aca075a0,UNIVERSITY OF CALIFORNIA RIVERSIDE Bio-Image Analysis for Understanding Plant Development and Mosquito Behaviors A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy,"UNIVERSITY OF CALIFORNIA +RIVERSIDE +Bio-Image Analysis for Understanding Plant Development and Mosquito Behaviors +A Dissertation submitted in partial satisfaction +of the requirements for the degree of +Doctor of Philosophy +Computer Science +Katya Mkrtchyan +March 2017 +Dissertation Committee: +Professor Amit Roy-Chowdhury, Chairperson +Professor Eamonn Keogh +Professor Stefano Lonardi +Professor Tamar Shinar"
+3b2df7d70ecbe3d0d65d27801d159ddaa150bf42,Doubly Sparse Relevance Vector Machine for Continuous Facial Behavior Estimation,"Doubly Sparse Relevance Vector Machine for +Continuous Facial Behavior Estimation +Sebastian Kaltwang, Sinisa Todorovic, Member, IEEE and Maja Pantic, Fellow, IEEE"
3b410ae97e4564bc19d6c37bc44ada2dcd608552,Scalability Analysis of Audio-Visual Person Identity Verification,"Scalability Analysis of Audio-Visual Person Identity Verification Jacek Czyz1, Samy Bengio2, Christine Marcel2, and Luc Vandendorpe1 @@ -1062,14 +3378,74 @@ Communications Laboratory, Universit´e catholique de Louvain, B-1348 Belgium, IDIAP, CH-1920 Martigny, Switzerland"
+6f42cb23262066b4034aba99bf674783ed6cac8b,An Empirical Evaluation of various Deep Learning Architectures for Bi-Sequence Classification Tasks,"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, +pages 2762–2773, Osaka, Japan, December 11-17 2016."
+6f5d57460e0e156497c4667a875cc5fa83154e3a,Retinal Verification Using a Feature Points-Based Biometric Pattern,"Hindawi Publishing Corporation +EURASIP Journal on Advances in Signal Processing +Volume 2009, Article ID 235746, 13 pages +doi:10.1155/2009/235746 +Research Article +Retinal Verification Using a Feature Points-Based +Biometric Pattern +M. Ortega,1 M. G. Penedo,1 J. Rouco,1 N. Barreira,1 and M. J. Carreira2 +VARPA Group, Faculty of Informatics, Department of Computer Science, University of Coru˜na, 15071 A Coru˜na, Spain +Department of Electronics and Computer Science, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain +Correspondence should be addressed to M. Ortega, +Received 14 October 2008; Accepted 12 February 2009 +Recommended by Natalia A. Schmid +Biometrics refer to identity verification of individuals based on some physiologic or behavioural characteristics. The typical +uthentication process of a person consists in extracting a biometric pattern of him/her and matching it with the stored pattern +for the authorised user obtaining a similarity value between patterns. In this work an efficient method for persons authentication +is showed. The biometric pattern of the system is a set of feature points representing landmarks in the retinal vessel tree. The +pattern extraction and matching is described. Also, a deep analysis of similarity metrics performance is presented for the biometric +system. A database with samples of retina images from users on different moments of time is used, thus simulating a hard and real +environment of verification. Even in this scenario, the system allows to establish a wide confidence band for the metric threshold"
+6fc129d384431d17eb7aa22afd6ab68f1084f038,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
6f5ce5570dc2960b8b0e4a0a50eab84b7f6af5cb,Low Resolution Face Recognition Using a Two-Branch Deep Convolutional Neural Network Architecture,"Low Resolution Face Recognition Using a Two-Branch Deep Convolutional Neural Network Architecture Erfan Zangeneh, Mohammad Rahmati, and Yalda Mohsenzadeh"
+6fd3bafa25bf6d376bc9d1cc1311eb260d10d024,Facial Recognition Utilizing Patch Based Game Theory,"International Journal of Machine Learning and Computing, Vol. 5, No. 4, August 2015 +Facial Recognition Utilizing Patch Based Game Theory +Foysal Ahmad, Kaushik Roy, Brian O‟Connor, Joseph Shelton, Pablo Arias, Albert Esterline, and Gerry +Dozier +theory. Texture based"
+6f8fa219ea82ded79757de59250b7213f9f5a104,OriNet: A Fully Convolutional Network for 3D Human Pose Estimation,"Chenxu Luo1 +Xiao Chu2 +Alan Yuille1 +Department of Computer Science +The Johns Hopkins University +Baltimore, MD 21218, USA +Baidu Research (USA) +Sunnyvale, CA 94089, USA +LUO ET AL.: ORINET: A FULLY CONVOLUTIONAL NETWORK FOR 3D HUMAN POSE +OriNet: A Fully Convolutional Network for 3D +Human Pose Estimation"
6f288a12033fa895fb0e9ec3219f3115904f24de,Learning Expressionlets via Universal Manifold Model for Dynamic Facial Expression Recognition,"Learning Expressionlets via Universal Manifold Model for Dynamic Facial Expression Recognition Mengyi Liu, Student Member, IEEE, Shiguang Shan, Senior Member, IEEE, Ruiping Wang, Member, IEEE, Xilin Chen, Senior Member, IEEE"
+6feb0d42232c31eecee5d90290287afe803e88a5,Recognizing Challenging Handwritten Annotations with Fully Convolutional Networks,"Recognizing Challenging Handwritten Annotations +with Fully Convolutional Networks +Andreas K¨olsch∗†, Ashutosh Mishra∗, Saurabh Varshneya∗†, Muhammad Zeshan Afzal∗†, Marcus Liwicki∗†‡§ +{a koelsch12, a ashutosh16, s +MindGarage, University of Kaiserslautern, Germany +Insiders Technologies GmbH, Kaiserslautern, Germany +University of Fribourg, Switzerland +§Lule˚a, University of Technology, Sweden"
+6f41b528abc34c249038f612a6c1033790ace628,Discriminant Subspace Analysis: An Adaptive Approach for Image Classification,"Discriminant Subspace Analysis: An Adaptive +Approach for Image Classification +Yijuan Lu, Member, IEEE, and Qi Tian, Senior Member, IEEE"
6f957df9a7d3fc4eeba53086d3d154fc61ae88df,Modélisation et suivi des déformations faciales : applications à la description des expressions du visage dans le contexte de la langue des signes,"Mod´elisation et suivi des d´eformations faciales : pplications `a la description des expressions du visage dans le contexte de la langue des signes @@ -1090,8 +3466,40 @@ broad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destin´ee au d´epˆot et `a la diffusion de documents scientifiques de niveau recherche, publi´es ou non,"
+6f3a8528841ea323d965d558195710fd8f916ffd,Knowledge Factorization,"Knowledge Factorization +Anubhav Ashok +Khushi Gupta +Nishant Agrawal"
+6f089f9959cc711e16f1ebe0c6251aaf8a65959a,Improvement in object detection using Super Pixels,"International Journal of Engineering Research in Electronic and Communication +Engineering (IJERECE) Vol 3, Issue 5, May 2016 +Improvement in object detection using Super Pixels +[1] Shruti D Kadam [2] H.Mallika +Dept. of Electronics and communication +M. S. Ramaiah Institute of Technology, Bangalore, Karnataka +[1] [2]"
+6f5a3c34360caad4644aea897b8fe7dd72076d0f,Self-calibrating Marker Tracking in 3D with Event-Based Vision Sensors,"Self-Calibrating Marker Tracking in 3D +with Event-Based Vision Sensors +Georg R. Müller, Jörg Conradt +Technische Universität München, Arcisstr. 21, +80290 München, Germany"
+6f1a784ebb8df0689361afe26a2e5f7a1f4c66ca,A unified probabilistic framework for measuring the intensity of spontaneous facial action units,"A Unified Probabilistic Framework For Measuring The Intensity of +Spontaneous Facial Action Units +Yongqiang Li1, S. Mohammad Mavadati2, Mohammad H. Mahoor and Qiang Ji +(AU),"
6f7d06ced04ead3b9a5da86b37e7c27bfcedbbdd,Multi-Scale Fully Convolutional Network for Fast Face Detection,"Pages 51.1-51.12 DOI: https://dx.doi.org/10.5244/C.30.51"
+6f9873e2a7bc279c4f0a45c1a6e831ef3ba78ae7,Improving GAN Training via Binarized Representation Entropy (BRE) Regularization,"Published as a conference paper at ICLR 2018 +IMPROVING GAN TRAINING VIA +BINARIZED REPRESENTATION ENTROPY (BRE) +REGULARIZATION +Yanshuai Cao, Gavin Weiguang Ding, Kry Yik-Chau Lui, Ruitong Huang +Borealis AI +Canada"
+6fa9bae381274518d3972294d81e460f0c63900b,Personalized Recommendations in Police Photo Lineup Assembling Task,"S. Krajˇci (ed.): ITAT 2018 Proceedings, pp. 157–160 +CEUR Workshop Proceedings Vol. 2203, ISSN 1613-0073, c(cid:13) 2018 Ladislav Peška and Hana Trojanová"
+6f1be86c77492af422e936028858c9180b52b698,Indoor Scene Understanding in 2.5/3D: A Survey,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JULY 2015 +Indoor Scene Understanding in 2.5/3D: A Survey +Muzammal Naseer, Salman H Khan, Fatih Porikli"
6f6b4e2885ea1d9bea1bb2ed388b099a5a6d9b81,"Structured Output SVM Prediction of Apparent Age, Gender and Smile from Deep Features","Structured Output SVM Prediction of Apparent Age, Gender and Smile From Deep Features Michal Uˇriˇc´aˇr @@ -1109,6 +3517,15 @@ CVL, D-ITET, ETH Zurich Jiˇr´ı Matas CMP, Dept. of Cybernetics FEE, CTU in Prague"
+6f3391fda6b25796b5e051f822f91243f69276cb,Performance Comparison of Various Face Detection Techniques,"International Journal of Scientific Research Engineering & Technology (IJSRET) +Volume 2 Issue1 pp 019-0027 April 2013 +ISSN 2278 - 0882 +www.ijsret.org +Performance Comparison of Various Face Detection Techniques +Mohammed Javed, 2Bhaskar Gupta +M.Tech. Student, Jamia Hamdard, New Delhi +Associate Professor,ECE,BBDIT,Ghaziabad,UP +Corresponding Author"
6f08885b980049be95a991f6213ee49bbf05c48d,Author's Personal Copy Multi-kernel Appearance Model ☆,"This article appeared in a journal published by Elsevier. The attached opy is furnished to the author for internal non-commercial research nd education use, including for instruction at the authors institution @@ -1122,6 +3539,41 @@ institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/authorsrights"
+6fc8c988dd841c6c4f5e96b1b1458b6aa564b2de,Crowd Counting via Scale-Adaptive Convolutional Neural Network,"Crowd counting via scale-adaptive convolutional neural network +Lu Zhang∗† +Tencent Youtu +Miaojing Shi∗ +Qiaobo Chen† +Inria Rennes & Tencent Youtu +Shanghai Jiaotong University"
+6fa39c0221c8bcae9146d31646cd9f70aba7190c,Review on Histopathological Slide Analysis using Digital Microscopy,"International Journal of Advanced Science and Technology +Vol.62, (2014), pp.65-96 +http://dx.doi.org/10.14257/ijast.2014.62.06 +Review on Histopathological Slide Analysis using Digital Microscopy +Sangita Bhattacharjee1, Jashojit Mukherjee1, Sanjay Nag1, Indra Kanta Maitra2 and +Samir K. Bandyopadhyay1 +Department of Computer Science and Engineering, University of Calcutta, India +B. P. Poddar Institute of Management and Technology, Kolkata, India"
+6f41e2ba877ec690bd1c9e5e8742c4088f95c346,Clockwork Convnets for Video Semantic Segmentation,"Clockwork Convnets for Video Semantic Segmentation +Evan Shelhamer(cid:63) +Kate Rakelly(cid:63) +Judy Hoffman(cid:63) +Trevor Darrell +UC Berkeley"
+6f8fc12004fa068c424369793fd39426e772b07d,Demystifying Core Ranking in Pinterest Image Search,"Demystifying Core Ranking in Pinterest Image Search +Linhong Zhu +Pinterest & USC/ISI"
+6fe149e588a5bf15bf89edfedb1a29cc31384ddc,Fully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Multicenter Water-Fat MRI,"Fully Convolutional Networks for Automated Segmentation +of Abdominal Adipose Tissue Depots in Multicenter +Water-Fat MRI +Taro Langner1*, Anders Hedstr¨om2, Katharina Paulmichl3,4, Daniel Weghuber3,4, +Anders Forslund5, Peter Bergsten5,6, H˚akan Ahlstr¨om1,2, Joel Kullberg1,2 +Dept. of Radiology, Uppsala University, Uppsala, Sweden +Antaros Medical, BioVenture Hub, M¨olndal, Sweden +Dept. of Pediatrics, Paracelsus Medical University, 5020 Salzburg, Austria +Obesity Research Unit, Paracelsus Medical University, 5020 Salzburg, Austria +5Dept. of Women’s and Children’s Health, Uppsala University, Uppsala, SE 751 05, Sweden +6Dept. of Medical Cell Biology, Uppsala University, Uppsala, SE 751 23, Sweden"
6f35b6e2fa54a3e7aaff8eaf37019244a2d39ed3,Learning probabilistic classifiers for human–computer interaction applications,"DOI 10.1007/s00530-005-0177-4 R E G U L A R PA P E R Nicu Sebe · Ira Cohen · Fabio G. Cozman · @@ -1141,10 +3593,23 @@ Seoul 100-715, Korea; (J.S.K.); (C.S.K.); (Y.W.L.); (S.W.C.) * Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 Received: 9 March 2018; Accepted: 10 April 2018; Published: 13 April 2018"
+6f53466b17a2f9da4dbd1d870e822a1f8e837044,Image Aesthetic Assessment: An experimental survey,"Image Aesthetic Assessment: +An Experimental Survey +Yubin Deng, Chen Change Loy, Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
6fa3857faba887ed048a9e355b3b8642c6aab1d8,Face Recognition in Challenging Environments: An Experimental and Reproducible Research Survey,"Face Recognition in Challenging Environments: An Experimental and Reproducible Research Survey Manuel G¨unther and Laurent El Shafey and S´ebastien Marcel"
+6f8ea33c29de7ef94f674c4c847185a127c6ea2f,Cue Integration by Similarity Rank List Coding - Application to Invariant Object Recognition,"nd IEEE International Workshops on Foundations and Applications of Self* Systems +nd IEEE International Workshops on Foundations and Applications of Self* Systems +Cue Integration by Similarity Rank List Coding — +Application to Invariant Object Recognition +Raul Grieben and Rolf P. W¨urtz +Institut f¨ur Neuroinformatik, Ruhr-Universit¨at Bochum,44780 Bochum, Germany"
+6f79c4b82f9ccdee918659a8f7091b8ab99fe889,Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering,"Mono-Camera 3D Multi-Object Tracking Using +Deep Learning Detections and PMBM Filtering +Samuel Scheidegger∗†, Joachim Benjaminsson∗†, Emil Rosenberg†, Amrit Krishnan∗, Karl Granstr¨om† +Zenuity, †Department of Electrical Engineering, Chalmers University of Technology"
6f7ce89aa3e01045fcd7f1c1635af7a09811a1fe,A novel rank order LoG filter for interest point detection,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE ICASSP 2012"
6fe2efbcb860767f6bb271edbb48640adbd806c3,Soft Biometrics; Human Identification Using Comparative Descriptions,"SOFT BIOMETRICS: HUMAN IDENTIFICATION USING COMPARATIVE DESCRIPTIONS @@ -1177,9 +3642,23 @@ JAH *2 BA=JKHAI JDA IAA?JEC BH JDAIA KIEC B=IJ ?HHA=JE =HA MA IDM JD=J >JD JDAIA IKH?AI B AHHH ?= >A HA >O AD=?EC -++ JDHKCD JDA =FFE?=JE B >JIJH=FFEC ?=IIIAF=H=>EEJO MAECDJEC"
+03e83659f0fc98dd03c354a2cc7a90d585ff9cf5,Face Recognition Using Holistic Features and Within Class Scatter-Based PCA,"GSTF JOURNAL ON COMPUTING, VOL. 3, NO. 2, JUNE 2013 +(cid:2)(cid:3)(cid:4)(cid:5)(cid:1)(cid:6)(cid:7)(cid:8)(cid:9)(cid:10)(cid:7)(cid:11)(cid:8)(cid:12)(cid:13)(cid:7)(cid:11)(cid:14)(cid:1)(cid:15)(cid:13)(cid:16)(cid:10)(cid:7)(cid:11)(cid:14)(cid:1)(cid:13)(cid:7)(cid:1)(cid:17)(cid:13)(cid:18)(cid:19)(cid:16)(cid:8)(cid:12)(cid:7)(cid:20)(cid:1)(cid:21)(cid:15)(cid:13)(cid:17)(cid:22)(cid:23)(cid:1)(cid:24)(cid:13)(cid:14)(cid:25)(cid:1)(cid:26)(cid:1)(cid:27)(cid:13)(cid:25)(cid:1)(cid:28)(cid:23)(cid:1)(cid:15)(cid:16)(cid:14)(cid:29)(cid:1)(cid:28)(cid:30)(cid:31)(cid:26) +DOI 10.7603/s40601-013-0002-4 +Face Recognition Using Holistic Features and +Within Class Scatter-Based PCA +I Gede Pasek Suta Wijaya, Non-Member, IEEE, Keiichi Uchimura, Non-Member, IEEE, +Gou Koutaki, Non-Member, IEEE"
+034050422f90938a43e9cfd292187aef124fef61,Race recognition from face images using Weber local descriptor,"Paper 1569528513 +IWSSIP 2012, 11-13 April 2012, Vienna, Austria +. INTRODUCTION"
03c56c176ec6377dddb6a96c7b2e95408db65a7a,A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding,"A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding Anis Kacem, Mohamed Daoudi, Boulbaba Ben Amor, Stefano Berretti, and Juan Carlos Alvarez-Paiva"
+031d22b08d9e8235f46679b89e273ab8723d3e67,Zero-Aliasing Correlation Filters for Object Recognition,"Zero-Aliasing Correlation Filters for Object +Recognition +Joseph A. Fernandez, Student Member, IEEE, Vishnu Naresh Boddeti, Member, IEEE, Andres Rodriguez, +Member, IEEE, B. V. K. Vijaya Kumar, Fellow, IEEE"
0322e69172f54b95ae6a90eb3af91d3daa5e36ea,Face Classification using Adjusted Histogram in Grayscale,"Face Classification using Adjusted Histogram in Grayscale Weenakorn Ieosanurak, and Watcharin Klongdee"
@@ -1189,6 +3668,14 @@ Charles Otto, Student Member, IEEE, Dayong Wang, Member, IEEE, and Anil K. Jain, Models with Application to Real-time Facial Feature Detection and Tracking on Low-power Devices Shuai Zheng, Paul Sturgess and Philip H. S. Torr"
+03df507b31691baeb7343d3eb70d048943e2d4f4,Exploring the Use of Local Descriptors for Fish Recognition in LifeCLEF 2015,"Exploring the use of local descriptors for fish +recognition in LifeCLEF 2015 +Jorge Cabrera-G´amez, Modesto Castrill´on-Santana, Antonio Dom´ınguez-Brito, +Daniel Hern´andez-Sosa, Josep Isern-Gonz´alez, and Javier Lorenzo-Navarro +Universidad de Las Palmas de Gran Canaria +SIANI +Spain +http://berlioz.dis.ulpgc.es/roc-siani"
03c1fc9c3339813ed81ad0de540132f9f695a0f8,Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification,"Proceedings of Machine Learning Research 81:1–15, 2018 Conference on Fairness, Accountability, and Transparency Gender Shades: Intersectional Accuracy Disparities in @@ -1198,10 +3685,71 @@ MIT Media Lab 75 Amherst St. Cambridge, MA 02139 Timnit Gebru Microsoft Research 641 Avenue of the Americas, New York, NY 10011 Editors: Sorelle A. Friedler and Christo Wilson"
+032c1e19a59cdbeb3fb741a812980f52c1461ce1,"Mining textural knowledge in biological images: Applications, methods and trends","Computational and Structural Biotechnology Journal 15 (2017) 56–67 +j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c s b j +Mining textural knowledge in biological images: Applications, methods +nd trends +Santa Di Cataldo*, Elisa Ficarra +Dept. of Computer and Control Engineering, Politecnico di Torino, Cso Duca degli Abruzzi 24, Torino 10129, Italy +A R T I C L E +I N F O +A B S T R A C T +Article history: +Received 25 August 2016 +Received in revised form 14 November 2016 +Accepted 15 November 2016 +Available online 24 November 2016 +Keywords: +Textural analysis +Bioimaging +Textural features extraction +Texture classification +Feature encoding"
+035c606bc6a05e2018e57859737877043673b7b9,Fine-Grained Image Classification by Exploring Bipartite-Graph Labels,"Fine-grained Image Classification by Exploring Bipartite-Graph Labels +Feng Zhou +NEC Labs +Yuanqing Lin +NEC Labs +www.f-zhou.com"
0339459a5b5439d38acd9c40a0c5fea178ba52fb,Multimodal recognition of emotions in car environments,"D|C|I&I 2009 Prague Multimodal recognition of emotions in car environments Dragoş DatcuA and Léon J.M. RothkrantzB"
+0393723dff4c00262c1daf34c26d27fa6fc52ab6,Pedestrian detection in outdoor images using color and gradients,"Pedestrian Detection in Outdoor Images using Color and Gradients +Marcel H¨aselich +Michael Klostermann +Dietrich Paulus +Active Vision Group, University of Koblenz-Landau, 56070 Koblenz, Germany +{mhaeselich, michaelk,"
+030ff7012b92b805a60976f8dbd6a08c1cecebe6,DCAN: Dual Channel-Wise Alignment Networks for Unsupervised Scene Adaptation,
+0315c68902edca77d2c15cfc1f1335d55343c715,Towards optimal distortion-based visual privacy filters,"TOWARDS OPTIMAL DISTORTION-BASED VISUAL PRIVACY FILTERS +Pavel Korshunov and Touradj Ebrahimi +Multimedia Signal Processing Group, EPFL, Lausanne, Switzerland"
+03889b0e8063532ae56d36dd9c54c3784a69e4d4,Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence,"Learning to Play Guess Who? and Inventing a +Grounded Language as a Consequence +Emilio Jorge1, Mikael Kågebäck2, and Emil Gustavsson1 +Fraunhofer-Chalmers Centre , Göteborg, Sweden , +Computer Science & Engineering , Chalmers University of Technology , Göteborg, Sweden ,"
+033e3fe75da26d8d3dd3cb0f99640181655e6746,From generic to specific deep representations for visual recognition,"Factors of Transferability for a Generic ConvNet Representation +Hossein Azizpour, Ali Sharif Razavian, Josephine Sullivan, Atsuto Maki, Stefan Carlsson +{azizpour, razavian, sullivan, atsuto, +Computer Vision and Active Perception (CVAP), Royal Institute of Technology (KTH), Stockholm, SE-10044 Sweden +Evidence is mounting that Convolutional Networks (ConvNets) are the most effective representation learning method for visual +recognition tasks. In the common scenario, a ConvNet is trained on a large labeled dataset (source) and the feed-forward units +ctivation of the trained network, at a certain layer of the network, is used as a generic representation of an input image for a +task with relatively smaller training set (target). Recent studies have shown this form of representation transfer to be suitable for a +wide range of target visual recognition tasks. This paper introduces and investigates several factors affecting the transferability of +such representations. It includes parameters for training of the source ConvNet such as its architecture, distribution of the training +data, etc. and also the parameters of feature extraction such as layer of the trained ConvNet, dimensionality reduction, etc. Then, +y optimizing these factors, we show that significant improvements can be achieved on various (17) visual recognition tasks. We +further show that these visual recognition tasks can be categorically ordered based on their distance from the source task such that +correlation between the performance of tasks and their distance from the source task w.r.t. the proposed factors is observed. +Index Terms—Convolutional Neural Networks, Transfer Learning, Representation Learning, Deep Learning, Visual Recognition +I. INTRODUCTION +C ONVOLUTIONAL NETWORKS (ConvNets) trace back +to the early works on digit and character recognition +[11], [23]. Prior to 2012, though, in computer vision field, +neural networks were more renowned for their propensity to"
032825000c03b8ab4c207e1af4daeb1f225eb025,A Novel Approach for Human Face Detection in Color Images Using Skin Color and Golden Ratio,"J. Appl. Environ. Biol. Sci., 7(10)159-164, 2017 ISSN: 2090-4274 © 2017, TextRoad Publication @@ -1220,8 +3768,74 @@ Subhransu Maji and Alexander C. Berg Sam Hare VGG Reading Group October 30, 2009"
+034f7d5b3878f8b2db92a7cb7f12edcd5681eca7,FAST Pre-Filtering-Based Real Time Road Sign Detection for Low-Cost Vehicle Localization,"Article +FAST Pre-Filtering-Based Real Time Road Sign +Detection for Low-Cost Vehicle Localization +Kyoungtaek Choi 1, Jae Kyu Suhr 2 +Department of Electronic Engineering, Korea National University of Transportation, 50 Daehak-ro, +nd Ho Gi Jung 1,* +Chungju-si 27469, Korea; +School of Intelligent Mechatronics Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, +Seoul 05006, Korea; +* Correspondence: Tel. +82-43-841-5366 +Received: 11 September 2018; Accepted: 16 October 2018; Published: 22 October 2018"
+0313924b600ebb8f608705d96c06b133b3b9627a,Deciphering the Crowd: Modeling and Identification of Pedestrian Group Motion,"Sensors 2013, 13, 875-897; doi:10.3390/s130100875 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +Deciphering the Crowd: Modeling and Identification of +Pedestrian Group Motion +Zeynep Y¨ucel *, Francesco Zanlungo, Tetsushi Ikeda, Takahiro Miyashita and Norihiro Hagita +Intelligent Robotics and Communication Laboratories, Advanced Telecommunications Research +Institute International, Kyoto 619-0288, Japan; E-Mails: (F.Z.); (T.I.); +(T.M.); (N.H.) +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +81-774-95-1405. +Received: 14 December 2012; in revised form: 20 December 2012 / Accepted: 4 January 2013 / +Published: 14 January 2013"
03b98b4a2c0b7cc7dae7724b5fe623a43eaf877b,Acume: A Novel Visualization Tool for Understanding Facial Expression and Gesture Data,"Acume: A Novel Visualization Tool for Understanding Facial Expression and Gesture Data"
+0306a275e80d11d65c4261b8f3d45317a49c1bf7,Optimal Architecture for Deep Neural Networks with Heterogeneous Sensitivity,"Optimal Architecture for Deep Neural Networks +with Heterogeneous Sensitivity +Hyunjoong Cho, Jinhyeok Jang, Chanhyeok Lee, and Seungjoon Yang"
+035ef7b25991b0f7ea841a2270ed053198aab09e,"Retrieval of Images with Objects of Specific Size, Location, and Spatial Configuration","Retrieval of images with objects of specific size, location and spatial configuration +Niloufar Pourian +B.S. Manjunath +Department of Electrical and Computer Engineering +University of California, Santa Barbara, United States"
+036fac2b87cf04c3d93e8a59da618d56a483a97d,Query Adaptive Late Fusion for Image Retrieval,"MANUSCRIPT +Query Adaptive Late Fusion for Image Retrieval +Zhongdao Wang, Liang Zheng, Shengjin Wang"
+038b8b2b629a8ba1e2ad6f9319e16b68e83e518a,Assessing Water Stress of Desert Tamarugo Trees Using in situ Data and Very High Spatial Resolution Remote Sensing,"Remote Sens. 2013, 5, 5064-5088; doi:10.3390/rs5105064 +OPEN ACCESS +ISSN 2072-4292 +www.mdpi.com/journal/remotesensing +Article +Assessing Water Stress of Desert Tamarugo Trees Using in situ +Roberto O. Chávez 1,*, Jan G. P. W. Clevers 1, Martin Herold 1, Edmundo Acevedo 2 +nd Mauricio Ortiz 2,3 +6700 AA Wageningen, The Netherlands; E-Mails: (J.G.P.W.C.); +(M.H.) +Laboratorio de Relación Suelo-Agua-Planta, Facultad de Ciencias Agronómicas, +Universidad de Chile, Casilla 1004, Santiago, Chile; E-Mail: (E.A.); +(M.O.) +Centro de Estudios Avanzados en Fruticultura (CEAF), Conicyt-Regional R08I1001, +Av. Salamanca s/n, Rengo, Chile +* Author to whom correspondence should be addressed; E-Mails: or +Tel.: +31-317-481-552; Fax: +31-317-419-000. +Received: 24 July 2013; in revised form: 12 September 2013 / Accepted: 9 October 2013 / +Published: 15 October 2013"
+03f6d738f9b916f80ce22c3ba605a0fa4d7830c1,Automated Reconstruction of Evolving Curvilinear Tree Structures,"POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCESacceptée sur proposition du jury:Prof. P. Dillenbourg, président du juryProf. P. Fua, directeur de thèseDr F. Moreno-Noguer, rapporteurDr R. Sznitman, rapporteurProf. S. Süsstrunk, rapporteuseAutomated Reconstruction of Evolving Curvilinear Tree StructuresTHÈSE NO 6930 (2016)ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNEPRÉSENTÉE LE 18 MARS 2016À LA FACULTÉ INFORMATIQUE ET COMMUNICATIONSLABORATOIRE DE VISION PAR ORDINATEURPROGRAMME DOCTORAL EN INFORMATIQUE ET COMMUNICATIONS Suisse2016PAR(cid:51)(cid:85)(cid:93)(cid:72)(cid:80)(cid:92)(cid:86)(cid:227)(cid:68)(cid:90)(cid:3)(cid:53)(cid:68)(cid:73)(cid:68)(cid:227)(cid:3)(cid:42)(cid:226)(cid:50)(cid:58)(cid:36)(cid:38)(cid:46)(cid:44)"
+034516f37171e7e6cffb8afa84c1f5d6d12d887f,Comparative Analysis of Content Based Image Retrieval using Texture Features for Plant Leaf Diseases,"International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 9 (2016) pp6244-6249 +© Research India Publications. http://www.ripublication.com +Comparative Analysis of Content Based Image Retrieval using Texture +Features for Plant Leaf Diseases +Ph.D. Scholar, Bharati Vidyapeeth Deemed University College of Engineering Pune, Maharashtra, India +Jayamala K.Patil +Professor, Defense Institute of Advanced Tech., Deemed University, Girinagar +Raj Kumar"
03adcf58d947a412f3904a79f2ab51cfdf0e838a,Video-based face recognition: a survey,"World Journal of Science and Technology 2012, 2(4):136-139 ISSN: 2231 – 2587 Available Online: www.worldjournalofscience.com @@ -1232,6 +3846,26 @@ April 21, 2012 Video-based face recognition: a survey Shailaja A Patil1 and Pramod J Deore2 Department of Electronics and Telecommunication, R.C.Patel Institute of Technology,Shirpur,Dist.Dhule.Maharashtra,India."
+03ae36b2ed0215b15c5bc7d42fbe20b1491e551a,Learning scene-specific pedestrian detectors without real data,"Learning Scene-Specific Pedestrian Detectors without Real Data +Hironori Hattori1, Vishnu Naresh Boddeti2, Kris Kitani2, Takeo Kanade2 +Sony Corporation. 2Carnegie Mellon University. +Figure 1: Overview: For every grid location, geometrically correct renderings of pedestrian are synthetically generated using known scene information +such as camera calibration parameters, obstacles (red), walls (blue) and walkable areas (green). All location-specific pedestrian detectors are trained +jointly to learn a smoothly varying appearance model. Multiple scene-and-location-specific detectors are run in parallel at every grid location. +Consider the scenario in which a new surveillance system is installed +in a novel location and an image-based pedestrian detector must be trained +without access to real scene-specific pedestrian data. A similar situation +may arise when a new imaging system (i.e., a custom camera with unique +lens distortion) has been designed and must be able to detect pedestrians +without the expensive process of collecting data with the new imaging de- +vice. One can use a generic pedestrian detection algorithm trained over co- +pious amounts of real data to work robustly across many scenes. However, +generic models are not always best-suited for detection in specific scenes. +In many surveillance scenarios, it is more important to have a customized +pedestrian detection model that is optimized for a single scene. Optimiz- +ing for a single scene however often requires a labor intensive process of +ollecting labeled data – drawing bounding boxes of pedestrians taken with +particular camera in a specific scene. The process also takes time, as"
03f14159718cb495ca50786f278f8518c0d8c8c9,Performance evaluation of HOG and Gabor features for vision-based vehicle detection,"015 IEEE International Conference on Control System, Computing and Engineering, Nov 27 – Nov 29, 2015 Penang, Malaysia 015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE2015) @@ -1256,6 +3890,55 @@ Performance Evaluation of HOG and Gabor Features for Vision-based" Entropy Estimation in Manifold Learning Jose A. Costa and Alfred O. Hero III December 16, 2003"
+03f3bde03f83c3ff4f346d761fde4ce031dd4c69,Deep Models Calibration with Bayesian Neural Networks,"Under review as a conference paper at ICLR 2019 +DEEP MODELS CALIBRATION WITH BAYESIAN NEURAL +NETWORKS +Anonymous authors +Paper under double-blind review"
+0365ea467c169134e858bb668a8e19bd251019e7,Orthogonal Neighborhood Preserving Projections: A Projection-Based Dimensionality Reduction Technique,"Orthogonal Neighborhood Preserving Projections: A +projection-based dimensionality reduction technique ∗ +E. Kokiopoulou † +Y. Saad‡ +March 21, 2006"
+03161081b47eba967fd3e663c57ec2f99f66eebd,Face and Facial Feature Localization,"Face and facial feature localization +Paola Campadelli?, Raffaella Lanzarotti??, Giuseppe Lipori, and Eleonora Salvi +Dipartimento di Scienze dell’Informazione +Universit(cid:30)a degli Studi di Milano +Via Comelico, 39/41 - 20135 Milano, Italy +fcampadelli, lanzarotti, +http://homes.dsi.unimi.it/(cid:24)campadel/LAIV/"
+031532cc5c4e64e02e796360a16f89580a0ba552,Nonnegative Decompositions for Dynamic Visual Data Analysis,"Nonnegative Decompositions for +Dynamic Visual Data Analysis +Lazaros Zafeiriou, Member, IEEE, Yannis Panagakis, Member, IEEE, +Maja Pantic, Fellow, IEEE, and Stefanos Zafeiriou, Member, IEEE"
+03ea398fcefc53a1bd041346c895aadcffed0261,Learning an Alphabet of Shape and Appearance for Multi-Class Object Detection,"Int J Comput Vis +DOI 10.1007/s11263-008-0139-3 +Learning an Alphabet of Shape and Appearance for Multi-Class +Object Detection +Andreas Opelt · Axel Pinz · Andrew Zisserman +Received: 28 February 2007 / Accepted: 4 April 2008 +© The Author(s) 2008"
+03ed6f09a29fe5d0dbf6d59798f88a5311c966d3,Re-identification with RGB-D Sensors,"Re-identi(cid:12)cation with RGB-D sensors +Igor Barros Barbosa1;3, Marco Cristani1;2, Alessio Del Bue1, +Loris Bazzani1, and Vittorio Murino1 +Pattern Analysis and Computer Vision (PAVIS) - Istituto Italiano di Tecnologia +(IIT), Via Morego 30, 16163 Genova, Italy +Dipartimento di Informatica, University of Verona, +Strada Le Grazie 15, 37134 Verona, Italy +Universit(cid:19)e de Bourgogne, 720 Avenue de lEurope, 71200 Le Creusot, France"
+036a8cb922a30d766b0fc0ba5954098a1d2a09f5,Learning Similarities for Rigid and Non-rigid Object Detection,"Learning Similarities for Rigid and Non-Rigid Object Detection +Asako Kanezaki +The Univ. of Tokyo +Emanuele Rodol`a +TU Munich +Daniel Cremers +TU Munich +Tatsuya Harada +The Univ. of Tokyo"
+037e17ac0272b4db0d4761067dbf0ee56d91e6dd,A New Multi-modal Dataset for Human Affect Analysis,"A New Multi-Modal Dataset for Human Affect +Analysis +nonymous for review +nonymous for review"
03ac1c694bc84a27621da6bfe73ea9f7210c6d45,Chapter 1 Introduction to information security foundations and applications,"Chapter 1 Introduction to information security foundations and applications @@ -1276,6 +3959,11 @@ has extended further to cover not only technical security problems but also soci organizational security challenges [4,5]. Traditional systems’ development approaches were focusing on the system’s usability where security was left to the last stage with less priority. However, the"
+03c53fb96a9acd2ec6ba52a2497410f980793bfa,Trainable Convolution Filters and Their Application to Face Recognition,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +Trainable Convolution Filters and their +Application to Face Recognition +Ritwik Kumar, Member, IEEE, Arunava Banerjee, Member, IEEE, +Baba C. Vemuri, Fellow, IEEE, and Hanspeter Pfister, Senior Member, IEEE"
0394e684bd0a94fc2ff09d2baef8059c2652ffb0,Median Robust Extended Local Binary Pattern for Texture Classification,"Median Robust Extended Local Binary Pattern for Texture Classification Li Liu, Songyang Lao, Paul W. Fieguth, Member, IEEE, Yulan Guo, @@ -1296,6 +3984,14 @@ greed that the extraction of powerful texture features plays a relatively more important role, since if poor features are used even the best classifier will fail to achieve good recognition results. Consequently, most research in texture classification"
+038277dbfcd767b0a0899de42d3277b5b253cc8e,Review and Implementation of High-Dimensional Local Binary Patterns and Its Application to Face Recognition,"TR-IIS-14-003 +Review and Implementation of +High-Dimensional Local Binary +Patterns and Its Application to +Face Recognition +Bor-Chun Chen, Chu-Song Chen, Winston Hsu +July. 24, 2014 || Technical Report No. TR-IIS-14-003 +http://www.iis.sinica.edu.tw/page/library/TechReport/tr2014/tr14.html"
03f4c0fe190e5e451d51310bca61c704b39dcac8,CHEAVD: a Chinese natural emotional audio-visual database,"J Ambient Intell Human Comput DOI 10.1007/s12652-016-0406-z O R I G I N A L R E S E A R C H @@ -1307,6 +4003,22 @@ Ya Li1 • Yazhu Liu1,4 Received: 30 March 2016 / Accepted: 22 August 2016 Ó Springer-Verlag Berlin Heidelberg 2016"
+03de6b2a3c81b26eecbec2705173da3dba25ecbb,FineTag: Multi-attribute Classification at Fine-grained Level in Images,"FineTag: Multi-attribute Classification at +Fine-grained Level in Images +Roshanak Zakizadeh, Michele Sasdelli, Yu Qian and Eduard Vazquez +Cortexica Vision Systems, London, UK"
+033fde43e6ff235fd560435bc060d5ffd14fb827,Pose Estimation and Tracking of Eating Persons in Real-life Settings,"ASCI { IPA { SIKS tracks, ICT.OPEN, Veldhoven, November 14{15, 2011 +Pose Estimation and Tracking of Eating Persons in Real-life Settings +Lu Zhang +EWI-TUDelft +Laurens van der Maaten +EWI-TUDelft +Nicole Koenderink +Wageningen UR, FBR +Franck Golbach +Wageningen UR, FBR +Emile Hendriks +EWI-TUDelft"
031055c241b92d66b6984643eb9e05fd605f24e2,Multi-fold MIL Training for Weakly Supervised Object Localization,"Multi-fold MIL Training for Weakly Supervised Object Localization Ramazan Gokberk Cinbis Jakob Verbeek Cordelia Schmid @@ -1319,17 +4031,70 @@ Stefanos Zafeiriou1 · Anastasios Roussos1,3 · Allan Ponniah2 · David Dunaway2 · Received: 15 March 2016 / Accepted: 24 March 2017 © The Author(s) 2017. This article is an open access publication"
+03650399cbf53d916d10a507852c9e94a02ee13f,3D faces in motion: Fully automatic registration and statistical analysis,"D Faces in Motion: Fully Automatic Registration and Statistical Analysis +Timo Bolkarta,∗, Stefanie Wuhrera +Saarland University, Saarbr¨ucken, Germany"
+034f7fcf5a393ac3307ac3609c2b971df6efaff6,Can Synthetic Data Handle Unconstrained Gaze Estimation?,"Can Synthetic Data Handle Unconstrained Gaze +Estimation ? +Amine Kacete, Renaud Séguier, Michel Collobert, Jérôme Royan +To cite this version: +Amine Kacete, Renaud Séguier, Michel Collobert, Jérôme Royan. Can Synthetic Data Handle Uncon- +strained Gaze Estimation ?. Conférence Nationale sur les Applications Pratiques de l’Intelligence Ar- +tificielle, Jul 2017, Caen, France. Conférence Nationale sur les Applications Pratiques de l’Intelligence +Artificielle. <hal-01561526> +HAL Id: hal-01561526 +https://hal.archives-ouvertes.fr/hal-01561526 +Submitted on 12 Jul 2017 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non,"
034addac4637121e953511301ef3a3226a9e75fd,Implied Feedback: Learning Nuances of User Behavior in Image Search,"Implied Feedback: Learning Nuances of User Behavior in Image Search Devi Parikh Virginia Tech"
03701e66eda54d5ab1dc36a3a6d165389be0ce79,Improved Principal Component Regression for Face Recognition Under Illumination Variations,"Improved Principal Component Regression for Face Recognition Under Illumination Variations Shih-Ming Huang and Jar-Ferr Yang, Fellow, IEEE"
+9b5b2fd938a9337475cb90a143cf7568f8f63709,Illumination Processing in Face Recognition,"Illumination Processing in Face Recognition187Illumination Processing in Face RecognitionYongping Li, Chao Wang and Xinyu AoX Illumination Processing in Face Recognition Yongping Li, Chao Wang and Xinyu Ao Shanghai Institute of Applied Physics, Chinese Academy of Sciences China 1. Introduction Driven by the demanding of public security, face recognition has emerged as a viable solution and achieved comparable accuracies to fingerprint system under controlled lightning environment. In recent years, with wide installing of camera in open area, the automatic face recognition in watch-list application is facing a serious problem. Under the open environment, lightning changes is unpredictable, and the performance of face recognition degrades seriously. Illumination processing is a necessary step for face recognition to be useful in the uncontrolled environment. NIST has started a test called FRGC to boost the research in improving the performance under changing illumination. In this chapter, we will focus on the research effort made in this direction and the influence on face recognition caused by illumination. First of all, we will discuss the quest on the image formation mechanism under various illumination situations, and the corresponding mathematical modelling. The Lambertian lighting model, bilinear illuminating model and some recent model are reviewed. Secondly, under different state of face, like various head pose and different facial expression, how illumination influences the recognition result, where the different pose and illuminating will be examined carefully. Thirdly, the current methods researcher employ to counter the change of illumination to maintain good performance on face recognition are assessed briefly. The processing technique in video and how it will improve face recognition on video, where Wang’s (Wang & Li, 2009) work will be discussed to give an example on the related advancement in the fourth part. And finally, the current state-of-art of illumination processing and its future trends will be discussed. 2. The formation of camera imaging and its difference from the human visual system With the camera invented in 1814 by Joseph N, recording of human face began its new era. Since we do not need to hire a painter to draw our figures, as the nobles did in the middle age. And the machine recorded our image as it is, if the camera is in good condition. Currently, the imaging system is mostly to be digital format. The central part is CCD (charge-coupled device) or CMOS (complimentary metal-oxide semiconductor). The CCD/CMOS operates just like the human eyes. Both CCD and CMOS image sensors operate 11www.intechopen.com"
9b318098f3660b453fbdb7a579778ab5e9118c4c,Joint Patch and Multi-label Learning for Facial Action Unit and Holistic Expression Recognition,"Joint Patch and Multi-label Learning for Facial Action Unit and Holistic Expression Recognition Kaili Zhao, Wen-Sheng Chu, Student Member, IEEE, Fernando De la Torre, Jeffrey F. Cohn, and Honggang Zhang, Senior Member, IEEE lassifiers without"
+9b69ea8034a24db2bb1a1eef73ec11b6367d2f2e,Face Recognition System Using PCA and DCT in HMM,"International Journal of Advanced Research in Computer and Communication Engineering +Vol. 4, Issue 1, January 2015 +Face Recognition System Using PCA and DCT +ISSN (Online) : 2278-1021 +ISSN (Print) : 2319-5940 +in HMM +SamerKais Jameel +Lecturer, Computer Science, University of Raparin, Sulaimaniya, Iraq"
+9b74de11c62ce16d0b4509554556e6b6b0d4f5c0,Bayesian Probabilistic Co-Subspace Addition,"Bayesian Probabilistic Co-Subspace Addition +Lei Shi +Baidu.com, Inc"
+9b3ed8190d99b107837de142324e4aa2be8b7eb2,An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition,"An Efficient Multimodal 2D-3D Hybrid +Approach to Automatic Face Recognition +Ajmal S. Mian, Mohammed Bennamoun, and Robyn Owens"
+9b19be86280c8dbb3fdccc24297449290bd2b6aa,Robust Compressive Phase Retrieval via Deep Generative Priors,"Robust Compressive Phase Retrieval via Deep Generative +Priors +Fahad Shamshad, Ali Ahmed +Dept. of Electrical Engg., Information Technology University, Lahore, Pakistan. +{fahad.shamshad,"
+9bcfa6d23ea628ccfabf6900ef05437e7cecb1c6,A Hybrid Approach for Secure Biometric Authentication Using Fusion of Iris and Ear,"Volume 5, Issue 8, August 2015 ISSN: 2277 128X +International Journal of Advanced Research in +Computer Science and Software Engineering +Research Paper +Available online at: www.ijarcsse.com +A Hybrid Approach for Secure Biometric Authentication Using +Fusion of Iris and Ear +Pamalpreet Kaur*, Er. Nirvair Neeru +CSE Deptt. Punjabi University, +Patiala, India"
9b474d6e81e3b94e0c7881210e249689139b3e04,VG-RAM Weightless Neural Networks for Face Recognition,"VG-RAM Weightless Neural Networks for Face Recognition Alberto F. De Souza, Claudine Badue, Felipe Pedroni, Stiven Schwanz Dias, @@ -1350,9 +4115,77 @@ lows: given an image of a scene, (i) identify or (ii) verify one or more persons using a database of faces. In identification problems, given a face as input, the system reports ack the identity of an individual based on a database of known individuals; whereas in veri- fication problems, the system confirms or rejects the claimed identity of the input face. In both"
+9bf6fbccfdf013cfd076f9357a05fb00b50735ee,JAR-Aibo: A Multi-view Dataset for Evaluation of Model-Free Action Recognition Systems,"JAR-Aibo: A Multi-View Dataset for Evaluation +of Model-Free Action Recognition Systems +Marco K¨orner and Joachim Denzler +Friedrich Schiller University of Jena +Computer Vision Group +Ernst-Abbe-Platz 3, 07743 Jena, Germany +http://www.inf-cv.uni-jena.de"
+9be5129fec3b6f1efc22e19dae3ae684961f5efb,Probability based Extended Direct Attribute Prediction,"Probability based Extended Direct Attribute Prediction +International Journal of Computer Applications (0975 – 8887) +Volume 155 – No 5, December 2016 +Manju +Research Scholar, +Department of computer science, +Baba Mastnath University, Rohtak"
+9b95153e4d3972d59fabef0fddce9b7207836b1b,Nonlinear Discrete Hashing,"Nonlinear Discrete Hashing +Zhixiang Chen, Jiwen Lu, Senior Member, IEEE, Jianjiang Feng, Member, IEEE, and Jie Zhou, Senior Member, IEEE"
9bcfadd22b2c84a717c56a2725971b6d49d3a804,How to Detect a Loss of Attention in a Tutoring System using Facial Expressions and Gaze Direction,"How to Detect a Loss of Attention in a Tutoring System using Facial Expressions and Gaze Direction Mark ter Maat"
+9bdd3ce1879f8fd32d2a3f2c4cedcadcf292a1a5,Geometric Active Learning via Enclosing Ball Boundary,"IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING +Geometric Active Learning via Enclosing Ball +Boundary +Xiaofeng Cao, Ivor W. Tsang, Jianliang Xu, Zenglin Shi, Guandong Xu"
+9bd973e64750a94dcf528da402b39e3a53118312,An FPGA-Accelerated Design for Deep Learning Pedestrian Detection in Self-Driving Vehicles,"An FPGA-Accelerated Design for Deep +Learning Pedestrian Detection in Self-Driving +Vehicles +Abdallah Moussawi, Kamal Haddad, and Anthony Chahine +Department of Electrical and Computer Engineering +American University of Beirut +Beirut, Lebanon +Email:"
+9b30771968b577ea1b71c0cfaee31f3824bfa027,Capturing Form of Non-verbal Conversational Behavior for Recreation on Synthetic Conversational Agent EVA,"Capturing Form of Non-verbal Conversational Behavior for Recreation +on Synthetic Conversational Agent EVA +IZIDOR MLAKAR, 2MATEJ ROJC +Roboti c.s. d.o.o, 2Faculty of Electrical Engineering and Computer Science, University of Maribor +Tržaška cesta 23, 2Smetanova ulica 17 +SLOVENIA"
+9badcba793a54dd90383a55d7dfee1281c510f75,Local Gradients Smoothing: Defense against localized adversarial attacks,"Local Gradients Smoothing: Defense against localized adversarial attacks +Muzammal Naseer +Australian National University (ANU) +Salman H. Khan +Data61, CSIRO +Fatih Porikli +Australian National University (ANU)"
+9b6d61491120bdd579f53e8c5f7cbe1e05cbc91e,Modeling Multimodal Behaviors from Speech Prosody,"Modeling Multimodal Behaviors From Speech +Prosody +Yu Ding1, Catherine Pelachaud1, and Thierry Arti`eres2 +CNRS-LTCI, Institut Mines-TELECOM, TELECOM ParisTech, Paris, France +{yu.ding, +Universit´e Pierre et Marie Curie (LIP6), Paris, France"
+9b555d8c8f518d907fa273d8691b008d55aedd92,Reasoning with shapes: profiting cognitive susceptibilities to infer linear mapping transformations between shapes,"REASONING WITH SHAPES +Reasoning with shapes: profiting cognitive +susceptibilities to infer linear mapping +transformations between shapes +Vahid Jalili"
+9be0de78bb69e7b243e92ab7530f9fd5a08c62cc,Spontaneous Trait Inferences on Social Media,"Article +Spontaneous Trait Inferences +on Social Media +Ana Levordashka1 and Sonja Utz1 +Social Psychological and +Personality Science +017, Vol. 8(1) 93-101 +ª The Author(s) 2016 +Reprints and permission: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/1948550616663803 +journals.sagepub.com/home/spp"
+9b678aa28facf4f90081d41c2c484c6addddb86d,Fully Convolutional Attention Networks for Fine-Grained Recognition,"Fully Convolutional Attention Networks for Fine-Grained Recognition +Xiao Liu, Tian Xia, Jiang Wang, Yi Yang, Feng Zhou and Yuanqing Lin +Baidu Research +{liuxiao12,xiatian,wangjiang03,yangyi05, zhoufeng09,"
9b164cef4b4ad93e89f7c1aada81ae7af802f3a4,A Fully Automatic and Haar like Feature Extraction-Based Method for Lip Contour Detection,"Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502 Vol. 2(1), 17-20, January (2013) Res.J.Recent Sci. @@ -1365,6 +4198,14 @@ Available online at: www.isca.in" 9bac481dc4171aa2d847feac546c9f7299cc5aa0,Matrix Product State for Higher-Order Tensor Compression and Classification,"Matrix Product State for Higher-Order Tensor Compression and Classification Johann A. Bengua1, Ho N. Phien1, Hoang D. Tuan1 and Minh N. Do2"
+9b7c6ef333c6e64f2dfa97a1a3614d0775d81a8a,A New Evaluation Protocol and Benchmarking Results for Extendable Cross-media Retrieval,"A New Evaluation Protocol and Benchmarking +Results for Extendable Cross-media Retrieval +Ruoyu Liu, Yao Zhao, Liang Zheng, Shikui Wei, and Yi Yang"
+9b4e90866c1f096a57383fb7320ac9d516a2f88d,Towards lightweight convolutional neural networks for object detection,"TOWARDS LIGHTWEIGHT CONVOLUTIONAL NEURAL +NETWORKS FOR OBJECT DETECTION +Dmitriy Anisimov, Tatiana Khanova +Intel +Nizhny Novgorod, Russia"
9b7974d9ad19bb4ba1ea147c55e629ad7927c5d7,Faical Expression Recognition by Combining Texture and Geometrical Features,"Faical Expression Recognition by Combining Texture and Geometrical Features Renjie Liu, Ruofei Du, Bao-Liang Lu*"
@@ -1379,6 +4220,16 @@ University of Applied Sciences Darmstadt - CASED, Haardtring 100, 64295 Darmstadt, Germany http://www.h-da.de"
+9ebe5d78163a91239f10c453d76082dfa329851d,Teacher's Perception in the Classroom,"Teachers’ Perception in the Classroom +¨Omer S¨umer1 +Patricia Goldberg1 +Kathleen St¨urmer1 +Tina Seidel3 +Peter Gerjets2 Ulrich Trautwein1 +Enkelejda Kasneci1 +University of T¨ubingen, Germany +Leibniz-Institut f¨ur Wissensmedien, Germany +Technical University of Munich, Germany"
9e4b052844d154c3431120ec27e78813b637b4fc,Local gradient pattern - A novel feature representation for facial expression recognition,"Journal of AI and Data Mining Vol. 2, No .1, 2014, 33-38. Local gradient pattern - A novel feature representation for facial @@ -1387,6 +4238,34 @@ M. Shahidul Islam Department of Computer Science, School of Applied Statistics, National Institute of Development Administration, Bangkok, Thailand. Received 23 April 2013; accepted 16 June 2013 *Corresponding author: (M.Shahidul Islam)"
+9e6c15150179ce848402e89bd245831d9935f4f9,Bi-modal Face Recognition - How combining 2D and 3D Clues Can Increase the Precision,"Bi-modal face recognition +How combining 2D and 3D clues can increase the precision +Amel Aissaoui1, Jean Martinet2 +USTHB, Algeria +Lille 1 University, France +issaoui +Keywords: +Face recognition, multimodal, 2D, 3D, LBP, RGB-depth."
+9e594ae4f549e0d838f497de31a5b597a6826d55,Recognition of Emotion from Facial Expressions with Direct or Averted Eye Gaze and Varying Expression Intensities in Children with Autism Disorder and Typically Developing Children,"Hindawi Publishing Corporation +Autism Research and Treatment +Volume 2014, Article ID 816137, 11 pages +http://dx.doi.org/10.1155/2014/816137 +Research Article +Recognition of Emotion from Facial Expressions with Direct or +Averted Eye Gaze and Varying Expression Intensities in Children +with Autism Disorder and Typically Developing Children +Dina Tell,1 Denise Davidson,2 and Linda A. Camras3 +Department of Health Promotion, Loyola University Chicago, Marcella Niehoff School of Nursing, 2160 S. First Avenue, +Maywood, IL 60153, USA +Department of Psychology, Loyola University Chicago, 1032 W. Sheridan Road, Chicago, IL 60660, USA +Department of Psychology, DePaul University, 2219 N. Kenmore Avenue, Chicago, IL 60614, USA +Correspondence should be addressed to Denise Davidson; +Received 8 November 2013; Revised 7 February 2014; Accepted 12 February 2014; Published 3 April 2014 +Academic Editor: Geraldine Dawson +Copyright © 2014 Dina Tell et al. This is an open access article distributed under the Creative Commons Attribution License, which +permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +Eye gaze direction and expression intensity effects on emotion recognition in children with autism disorder and typically developing +hildren were investigated. Children with autism disorder and typically developing children identified happy and angry expressions"
9ea73660fccc4da51c7bc6eb6eedabcce7b5cead,Talking head detection by likelihood-ratio test,"Talking Head Detection by Likelihood-Ratio Test† Carl Quillen, Kara Greenfield, and William Campbell MIT Lincoln Laboratory, @@ -1421,20 +4300,162 @@ DEPARTMENT OF COMPUTER SCIENCES UNIVERSITY OF TAMPERE D‐2008‐9 TAMPERE 2008"
+9e9c600919332dcabbd32bbe81a00d1e47449193,Automatic 3D face verification from range data,"- 1330-7803-7663-3/03/$17.00 ©2003 IEEEThis paper was originally published in the Proceedings of the 2003 IEEEInternational Conference on Acoustics, Speech, & Signal Processing,April 6-10, 2003, Hong Kong (cancelled). Reprinted with permission.(cid:224)"
9e0285debd4b0ba7769b389181bd3e0fd7a02af6,From Face Images and Attributes to Attributes,"From face images and attributes to attributes Robert Torfason, Eirikur Agustsson, Rasmus Rothe, Radu Timofte Computer Vision Laboratory, ETH Zurich, Switzerland"
+9ed3e04586f311b1e2b5ded9c9c4bfeeecf27f0c,Understanding rapid category detection via multiply degraded images.,"http://journalofvision.org/9/6/19/ +Understanding rapid category detection via multiply +degraded images +Chetan Nandakumar +Vision Science Graduate Program, +University of California, Berkeley, Berkeley, CA, USA +Jitendra Malik +Department of Electrical Engineering and +Computer Science, University of California, +Berkeley, Berkeley, CA, USA +Rapid category detection, as discovered by S. Thorpe, D. Fize, and C. Marlot (1996), demonstrated that the human visual +system can detect object categories in natural images in as little as 150 ms. To gain insight into this phenomenon and to +determine its relevance to naturally occurring conditions, we degrade the stimulus set along various image dimensions and +investigate the effects on perception. To investigate how well modern-day computer vision algorithms cope with +degradations, we conduct an analog of this same experiment with state-of-the-art object recognition algorithms. We +discover that rapid category detection in humans is quite robust to naturally occurring degradations and is mediated by a +non-linear interaction of visual features. In contrast, modern-day object recognition algorithms are not as robust. +Keywords: rapid category detection, degraded images, object recognition, eye tracking +Citation: Nandakumar, C., & Malik, J. (2009). Understanding rapid category detection via multiply degraded images. Journal +of Vision, 9(6):19, 1–8, http://journalofvision.org/9/6/19/, doi:10.1167/9.6.19."
+9e6ecc12794f1d3215f93376a32b350a0492ceb0,Modeling and Predicting Face Recognition System Performance Based on Analysis of Similarity Scores,"Modeling and Predicting Face +Recognition System Performance +Based on Analysis of Similarity Scores +Peng Wang, Member, IEEE, +Qiang Ji, Sr. Member, IEEE, and +James L. Wayman, Sr. Member, IEEE"
+9edd7c738171b0f36b65ae771711c38ed1dc38ad,Long-Term Multi-Cue Tracking of Hands in Vehicles,"Long-Term Multi-Cue Tracking of Hands in Vehicles +Akshay Rangesh, Eshed Ohn-Bar, and Mohan Manubhai Trivedi, Fellow, IEEE"
+9e759860762d40505f25d6fc5c4f4c1f6500d68b,Elastic Net Hypergraph Learning for Image Clustering and Semi-Supervised Classification,"Elastic Net Hypergraph Learning for Image +Clustering and Semi-supervised Classification +Qingshan Liu, Seninor Member, IEEE, Yubao Sun, Cantian Wang, Tongliang Liu and Dacheng Tao, Fellow, IEEE"
+9ef73533507b46278d0d27c41e16af2b8ecf23ef,A comparative assessment of appearance based feature extraction techniques and their susceptibility to image degradations in face recognition systems,"A comparative assessment of appearance based +feature extraction techniques and their susceptibility +to image degradations in face recognition systems +Vitomir ˇStruc and Nikola Paveˇsi´c, Member, IEEE"
+9eb111f6990d1494a3904f22be9836c202efd7d1,Exploiting workload similarities for efficient scheduling in diverse asymmetric chip multiprocessing Research,Exploiting workload similarities for efficient scheduling in diverse asymmetric chip multiprocessing Dani Shaket
+9e8dd40aea9204ad670b312a46ba807bfc0c61ce,Distribution-sensitive learning for imbalanced datasets Citation,"Distribution-sensitive learning for imbalanced datasets +The MIT Faculty has made this article openly available. Please share +how this access benefits you. Your story matters. +Citation +As Published +Publisher +Version +Accessed +Citable Link +Terms of Use +Detailed Terms +Song, Yale, Louis-Philippe Morency, and Randall Davis. +“Distribution-Sensitive Learning for Imbalanced Datasets.” 2013 +0th IEEE International Conference and Workshops on +Automatic Face and Gesture Recognition (FG) (n.d.). +http://dx.doi.org/10.1109/FG.2013.6553715 +Institute of Electrical and Electronics Engineers (IEEE) +Author's final manuscript +Fri Jan 08 19:33:51 EST 2016 +http://hdl.handle.net/1721.1/86107"
+9ee5218a2a74fafbc4227f6c7c587b72e141bd33,Iris Compression and Recognition using Spherical Geometry Image,"(IJARAI) International Journal of Advanced Research in Artificial Intelligence, +Vol. 4, No.6, 2015 +Iris Compression and Recognition using Spherical +Geometry Image +College of Computers and Information Technology University of Tabuk Tabuk, KSA +Rabab M. Ramadan +in 3D domain to test"
+9e2120e48d497b373c53563275c3786c11749883,Topological and metric robot localization through computer vision techniques,"Topological and metric robot localization through computer vision +techniques +A. C. Murillo, J. J. Guerrero and C. Sag¨u´es +DIIS - I3A, University of Zaragoza, Spain"
+9ee4d3c173c41ffb6f5aa3c40951aefe3da11d5b,Forming A Random Field via Stochastic Cliques: From Random Graphs to Fully Connected Random Fields,"Forming A Random Field via Stochastic +Cliques: From Random Graphs to Fully +Connected Random Fields +M. J. Shafiee, A. Wong and P. Fieguth"
+9e1712ac91c7a882070a8e2740ed476d59d6d5d4,Expressive image manipulations for a variety of visual representations. (Manipulations d'image expressives pour une variété de représentations visuelles),"Expressive image manipulations for a variety of visual +representations +Adrien Bousseau +To cite this version: +Adrien Bousseau. Expressive image manipulations for a variety of visual representations. Human- +Computer Interaction [cs.HC]. Université Joseph-Fourier - Grenoble I, 2009. English. <tel-00429151> +HAL Id: tel-00429151 +https://tel.archives-ouvertes.fr/tel-00429151 +Submitted on 31 Oct 2009 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de +recherche français ou étrangers, des laboratoires"
+9e263d429c3b87aae2653b6fb925b32b63c172cd,Enhanced image and video representation for visual recognition,"Enhanced image and video representation for visual +recognition +Mihir Jain +To cite this version: +Mihir Jain. Enhanced image and video representation for visual recognition. Computer Vision +nd Pattern Recognition [cs.CV]. Universit´e Rennes 1, 2014. English. <tel-00996793> +HAL Id: tel-00996793 +https://tel.archives-ouvertes.fr/tel-00996793 +Submitted on 27 May 2014 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de +recherche fran¸cais ou ´etrangers, des laboratoires"
040dc119d5ca9ea3d5fc39953a91ec507ed8cc5d,Large-scale Bisample Learning on ID vs. Spot Face Recognition,"Noname manuscript No. (will be inserted by the editor) Large-scale Bisample Learning on ID vs. Spot Face Recognition Xiangyu Zhu∗ · Hao Liu∗ · Zhen Lei · Hailin Shi · Fan Yang · Dong Yi · Stan Z. Li Received: date / Accepted: date"
+0422a9bc1bde71d3b4fc4f52b4a62b15f2fb101f,A Customized Vision System for Tracking Humans Wearing Reflective Safety Clothing from Industrial Vehicles and Machinery,"Sensors 2014, 14, 17952-17980; doi:10.3390/s141017952 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +A Customized Vision System for Tracking Humans +Wearing Reflective Safety Clothing from Industrial +Vehicles and Machinery +Rafael Mosberger *, Henrik Andreasson and Achim J. Lilienthal +AASS Research Centre, Örebro University, 70182 Örebro, Sweden; +E-Mails: (H.A.); (A.J.L.) +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +46-1930-1113; Fax: +46-1930-3463. +External Editor: Vittorio M.N. Passaro +Received: 8 July 2014; in revised form: 5 September 2014 / Accepted: 9 September 2014 / +Published: 26 September 2014"
+04adf2e51df06a03b6decf520b0952a54a538a18,Randomized Robust Subspace Recovery and Outlier Detection for High Dimensional Data Matrices,"Randomized Robust Subspace Recovery for High Dimensional +Data Matrices +Mostafa Rahmani, Student Member, IEEE and George K. Atia, Member, IEEE"
047f6afa87f48de7e32e14229844d1587185ce45,An Improvement of Energy-Transfer Features Using DCT for Face Detection,"An Improvement of Energy-Transfer Features Using DCT for Face Detection Radovan Fusek, Eduard Sojka, Karel Mozdˇreˇn, and Milan ˇSurkala Technical University of Ostrava, FEECS, Department of Computer Science, 7. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic"
+0485e96bb0c1276fe2a27271b939b6e67997acfc,Active Learning for Structured Probabilistic Models,"Active Learning for Structured Probabilistic Models +Qing Sun +Virginia Tech +Ankit Laddha ∗ +Virginia Tech +Dhruv Batra +Virginia Tech"
+04afb510e11e963fb18e3271ac966164db806120,Harvesting Social Images for Bi-Concept Search,"Harvesting Social Images for Bi-Concept Search +Xirong Li, Cees G. M. Snoek, Senior Member, IEEE, Marcel Worring, Member, IEEE, and +Arnold W. M. Smeulders, Member, IEEE"
04b851f25d6d49e61a528606953e11cfac7df2b2,Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition,"Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition Shuyang Sun1,2, Zhanghui Kuang2, Lu Sheng3, Wanli Ouyang1, Wei Zhang2 @@ -1444,6 +4465,9 @@ The University of Sydney 2SenseTime Research 3The Chinese University of Hong Kon 0447bdb71490c24dd9c865e187824dee5813a676,Manifold Estimation in View-based Feature Space for Face Synthesis Across Pose,"Manifold Estimation in View-based Feature Space for Face Synthesis Across Pose Paper 27"
+04bb0a1ccca86a4c1084fc7472ea07189c110aa7,Tracking Interacting Objects Using Intertwined Flows,"Tracking Interacting Objects Using +Intertwined Flows +Xinchao Wang∗ , Engin T¨uretken∗, Franc¸ois Fleuret, and Pascal Fua, Fellow, IEEE"
0435a34e93b8dda459de49b499dd71dbb478dc18,"VEGAC: Visual Saliency-based Age, Gender, and Facial Expression Classification Using Convolutional Neural Networks","VEGAC: Visual Saliency-based Age, Gender, and Facial Expression Classification Using Convolutional Neural Networks Ayesha Gurnani£1, Vandit Gajjar£1, Viraj Mavani£1, Yash Khandhediya£1 @@ -1464,10 +4488,94 @@ tasks. It is still an open problem when considering the MIT Saliency Benchmark [24]. In previous five years, considering age estimation, gender classification and facial expression classification"
+041ac91c85276f61bec3f0f3c42782e4f9a31f88,Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform,"Detailed Dense Inference with Convolutional Neural Networks +via Discrete Wavelet Transform +Lingni Ma1, J¨org St¨uckler2, Tao Wu1 and Daniel Cremers1"
+04f7eab5d03ac6ad678f2fc8adf29bc1a84a2084,Tree based object matching using multi-scale covariance descriptor,"Tree based object matching using multi-scale covariance +descriptor +Walid AYEDI1,2, Hichem SNOUSSI1, Fethi SMACH2 and Mohamed ABID2 +Charles Delaunay Institute (FRE CNRS 2848), University of Technology of Troyes, 10010 Troyes, France +Sfax University, National Engineering School of Sfax, 3052 Sfax, Tunisia"
044ba70e6744e80c6a09fa63ed6822ae241386f2,Early Prediction for Physical Human Robot Collaboration in the Operating Room,"TO APPEAR IN AUTONOMOUS ROBOTS, SPECIAL ISSUE IN LEARNING FOR HUMAN-ROBOT COLLABORATION Early Prediction for Physical Human Robot Collaboration in the Operating Room Tian Zhou, Student Member, IEEE, and Juan Wachs, Member, IEEE"
+0462aa8b7120a34f111e81f77acd1cc7d81680a6,Color Emotions in Large Scale Content Based Image Indexing,"Link¨oping Studies in Science and Technology +Dissertations, No. 1362 +Color Emotions in Large Scale Content Based +Image Indexing +Martin Solli +Department of Science and Technology +Link¨oping University, SE-601 74 Norrk¨oping, Sweden +Norrk¨oping, March 2011"
+04741341e26bdcd9ed1de18e5a95c31d7b64fa36,Adversarial Action Prediction Networks,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, FEBRUARY 2018 +Adversarial Action Prediction Networks +Yu Kong, Member, IEEE, Zhiqiang Tao, Student Member, IEEE and Yun Fu, Senior Member, IEEE"
+045b45adbcb83a34d087c917b79274858a878937,A Methodology for Extracting Standing Human Bodies From Single Images,"Invention Journal of Research Technology in Engineering & Management (IJRTEM) ISSN: 2455-3689 +www.ijrtem.com ǁ Volume 1 ǁ Issue 8 ǁ +A Methodology for Extracting Standing Human Bodies from Single Images +Dr. Y. Raghavender Rao1, N. Devadas Naik2 +Head ECE JNTUHCEJ Jagtityal +Asst professor Sri Chaitanya engineering college"
+04dca7c7f85d607cba64ca56de3364a4085effa1,ExprGAN: Facial Expression Editing with Controllable Expression Intensity,"ExprGAN: Facial Expression Editing with Controllable Expression Intensity +Hui Ding,1 Kumar Sricharan2, Rama Chellappa3 +,3University of Maryland, College Park +PARC, Palo Alto"
+048eb50c398fa01bd15329945113341102d96454,Addressing perceptual insensitivity to facial affect in violent offenders: first evidence for the efficacy of a novel implicit training approach.,"doi:10.1017/S0033291713001517 +O R I G I N A L A R T I C L E +Addressing perceptual insensitivity to facial affect +in violent offenders: first evidence for the efficacy +of a novel implicit training approach +M. Schönenberg*, S. Christian, A.-K. Gaußer, S. V. Mayer, M. Hautzinger and A. Jusyte +Department of Clinical Psychology and Psychotherapy, University of Tübingen, Germany +Background. Although impaired recognition of affective facial expressions has been conclusively linked to antisocial +ehavior, little is known about the modifiability of this deficit. This study investigated whether and under which circum- +stances the proposed perceptual insensitivity can be addressed with a brief implicit training approach. +Method. Facial affect recognition was assessed with an animated morph task, in which the participants (44 male incar- +erated violent offenders and 43 matched controls) identified the onset of emotional expressions in animated morph clips +that gradually changed from neutral to one of the six basic emotions. Half of the offenders were then implicitly trained to +direct attention to salient face regions (attention training, AT) using a modified dot-probe task. The other half underwent +the same protocol but the intensity level of the presented expressions was additionally manipulated over the course of +training sessions (sensitivity to emotional expressions training, SEE training). Subsequently, participants were reassessed +with the animated morph task. +Results. Facial affect recognition was significantly impaired in violent offenders as compared with controls. Further, our +results indicate that only the SEE training group exhibited a pronounced improvement in emotion recognition. +Conclusions. We demonstrated for the first time that perceptual insensitivity to facial affect can be addressed by an"
+040601d28b683c3c8b48b29e93b6aa3c26dbdf5f,"Facial Expression Recognition for Color Images using Gabor, Log Gabor Filters and PCA","International Journal of Computer Applications (0975 – 8887) +Volume 113 – No. 4, March 2015 +Facial Expression Recognition for Color Images using +Gabor, Log Gabor Filters and PCA +Shail Kumari Shah +PG Scholar, +Computer Engg. Dept. +Vineet Khanna +Assistant Professor, +Computer Engg. Dept. +Rajasthan College of Engineering for Women +Rajasthan Technical University, Jaipur, India +Rajasthan College of Engineering for Women +Rajasthan Technical University, Jaipur, India"
+04bf170753cee3d1da1b9ab41a5b0874685142fa,Casualty Detection for Mobile Rescue Robots via Ground-Projected Point Clouds,"TAROS2018, 037, v5 (final): ’Casualty Detection for Mobile Rescue Robots via Ground- . . ."
+0480b458439069687ec41c90178ba7e9a056bcca,Gender Classification Using Gradient Direction Pattern,"Sci.Int(Lahore),25(4),797-799,2013 +ISSN 1013-5316; CODEN: SINTE 8 +GENDER CLASSIFICATION USING GRADIENT DIRECTION PATTERN +Department of Computer Science, School of Applied Statistics, +National Institute of Development Administration, Bangkok, Thailand. +Mohammad Shahidul Islam"
+0449b56b6b19a3c42766962782bfb88576b5bd62,Spontaneous and cued gaze-following in autism and Williams syndrome,"Spontaneous and cued gaze-following in autism +nd Williams syndrome +Riby et al. +Riby et al. Journal of Neurodevelopmental Disorders 2013, 5:13 +http://www.jneurodevdisorders.com/content/5/1/13"
+04b29b6f1210f4309f3d5ab9e6bd2c8a026ce244,Face Recognition in the Presence of Expressions,"Journal of Software Engineering and Applications, 2012, 5, 321-329 +http://dx.doi.org/10.4236/jsea.2012.55038 Published Online May 2012 (http://www.SciRP.org/journal/jsea) +Face Recognition in the Presence of Expressions +Xia Han1*, Moi Hoon Yap2, Ian Palmer3 +Centre for Visual Computing, University of Bradford, Bradford, UK; 2School of Computing, Mathematics, and Digital Technology, +Manchester Metropolitan University (MMU), Manchester, UK; 3School of Computing, Informatics and Media, University of +Bradford, Bradford, UK. +Email: +Received February 21st, 2012; revised March 25th, 2012; accepted April 27th, 2012"
04dcdb7cb0d3c462bdefdd05508edfcff5a6d315,Assisting the training of deep neural networks with applications to computer vision,"Assisting the training of deep neural networks with applications to computer vision Adriana Romero @@ -1482,10 +4590,60 @@ llicència Reconeixement- NoComercial –" 044fdb693a8d96a61a9b2622dd1737ce8e5ff4fa,Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions,"Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions Guoying Zhao and Matti Pietik¨ainen, Senior Member, IEEE"
+0410659b6a311b281d10e0e44abce9b1c06be462,"A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning","A Gift from Knowledge Distillation: +Fast Optimization, Network Minimization and Transfer Learning +Junho Yim1 +Donggyu Joo1 +Jihoon Bae2 +Junmo Kim1 +School of Electrical Engineering, KAIST, South Korea +Electronics and Telecommunications Research Institute +{junho.yim, jdg105,"
+04b08a2735eff524f17d3f1a63eb7fc6484d4f83,Facial emotion detection using deep learning,IT 16 040Examensarbete 30 hpJuni 2016Facial emotion detection using deep learning Daniel Llatas SpiersInstitutionen för informationsteknologiDepartment of Information Technology
+04cdc847f3b10d894582969feee0f37fbd3745e5,Compressed Sensing with Deep Image Prior and Learned Regularization,"Compressed Sensing with Deep Image Prior +nd Learned Regularization +David Van Veen∗† +Ajil Jalal∗† +Eric Price ‡ +Sriram Vishwanath † +Alexandros G. Dimakis † +June 19, 2018"
+04ff060369c86ccb07414935bd3e3b85e4896261,Object detection can be improved using human-derived contextual expectations,"Object detection can be improved using +human-derived contextual expectations +Harish Katti, Marius V. Peelen, and S. P. Arun"
04f55f81bbd879773e2b8df9c6b7c1d324bc72d8,Multi-view Face Analysis Based on Gabor Features,"Multi-view Face Analysis Based on Gabor Features Hongli Liu， Weifeng Liu， Yanjiang Wang College of Information and Control Engineering in China University of Petroleum, Qingdao 266580, China"
+046f1c194a09fc84f535c27a3373622223a80c67,Memory-efficient groupby-aggregate using compressed buffer trees,"Memory-Efficient GroupBy-Aggregate using +Compressed Buffer Trees +Hrishikesh Amur†, Wolfgang Richter(cid:63), David G. Andersen(cid:63), +Michael Kaminsky‡, Karsten Schwan†, Athula Balachandran(cid:63), Erik Zawadzki(cid:63) +(cid:63)Carnegie Mellon University, †Georgia Institute of Technology, ‡Intel Labs Pittsburgh"
+04f6a747cba48be1cabbf5efe6ce3eb85e061395,Discriminative Detection and Alignment in Volumetric Data,"Discriminative Detection +nd Alignment in Volumetric Data +Dominic Mai1,2, Philipp Fischer1, Thomas Blein4, Jasmin D¨urr3, +Klaus Palme2,3, Thomas Brox1,2, and Olaf Ronneberger1,2 +Lehrstuhl f¨ur Mustererkennung und Bildverabeitung, Institut f¨ur Informatik +BIOSS Centre of Biological Signalling Studies +Institut f¨ur Biologie II, Albert-Ludwigs-Universit¨at Freiburg +INRA Versailles"
+04d9abdae728f09e1d1f78e36a5de551c3a690f5,Color Local Texture Features Based Face Recognition,"International Journal of Innovations in Engineering and Technology (IJIET) +Color Local Texture Features Based Face +Recognition +Priyanka V. Bankar +Department of Electronics and Communication Engineering +SKN Sinhgad College of Engineering, Korti, Pandharpur, Maharashtra, India +Department of Electronics and Communication Engineering +SKN Singhgad College of Engineering, Korti, Pandharpur, Maharashtra, India +Anjali C. Pise"
+04743c503620baffd75f93f8e4583fcba369ac9d,Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction,"Proceedings of the The 8th International Joint Conference on Natural Language Processing, pages 436–441, +Taipei, Taiwan, November 27 – December 1, 2017 c(cid:13)2017 AFNLP"
+04f4679765d2f71576dd77c1b00a2fd92e5c6da4,Part Detector Discovery in Deep Convolutional Neural Networks,"Part Detector Discovery in Deep Convolutional +Neural Networks +Marcel Simon, Erik Rodner, and Joachim Denzler +Computer Vision Group, Friedrich Schiller University of Jena, Germany +www.inf-cv.uni-jena.de"
0431e8a01bae556c0d8b2b431e334f7395dd803a,Learning Localized Perceptual Similarity Metrics for Interactive Categorization,"Learning Localized Perceptual Similarity Metrics for Interactive Categorization Catherine Wah ∗ Google Inc. @@ -1498,7 +4656,64 @@ Beijing Institution of Technology, Beijing, China Jianguo Li School of Information and Electronics, Beijing Institution of Technology, Beijing, China"
+044da4715e439b4f91cee8eec55299e30a615c56,Inducing a Concurrent Motor Load Reduces Categorization Precision for Facial Expressions,"Journal of Experimental Psychology: +Human Perception and Performance +016, Vol. 42, No. 5, 706 –718 +0096-1523/16/$12.00 +© 2015 The Author(s) +http://dx.doi.org/10.1037/xhp0000177 +Inducing a Concurrent Motor Load Reduces Categorization Precision for +Facial Expressions +Alberta Ipser and Richard Cook +City University London +Motor theories of expression perception posit that observers simulate facial expressions within their own +motor system, aiding perception and interpretation. Consistent with this view, reports have suggested that +locking facial mimicry induces expression labeling errors and alters patterns of ratings. Crucially, +however, it is unclear whether changes in labeling and rating behavior reflect genuine perceptual +phenomena (e.g., greater internal noise associated with expression perception or interpretation) or are +products of response bias. In an effort to advance this literature, the present study introduces a new +psychophysical paradigm for investigating motor contributions to expression perception that overcomes +some of the limitations inherent in simple labeling and rating tasks. Observers were asked to judge +whether smiles drawn from a morph continuum were sincere or insincere, in the presence or absence of +motor load induced by the concurrent production of vowel sounds. Having confirmed that smile"
04616814f1aabe3799f8ab67101fbaf9fd115ae4,UNIVERSITÉ DE CAEN BASSE NORMANDIE U . F . R . de Sciences,"UNIVERSIT´EDECAENBASSENORMANDIEU.F.R.deSciences´ECOLEDOCTORALESIMEMTH`ESEPr´esent´eeparM.GauravSHARMAsoutenuele17D´ecembre2012envuedel’obtentionduDOCTORATdel’UNIVERSIT´EdeCAENSp´ecialit´e:InformatiqueetapplicationsArrˆet´edu07aoˆut2006Titre:DescriptionS´emantiquedesHumainsPr´esentsdansdesImagesVid´eo(SemanticDescriptionofHumansinImages)TheworkpresentedinthisthesiswascarriedoutatGREYC-UniversityofCaenandLEAR–INRIAGrenobleJuryM.PatrickPEREZDirecteurdeRechercheINRIA/Technicolor,RennesRapporteurM.FlorentPERRONNINPrincipalScientistXeroxRCE,GrenobleRapporteurM.JeanPONCEProfesseurdesUniversit´esENS,ParisExaminateurMme.CordeliaSCHMIDDirectricedeRechercheINRIA,GrenobleDirectricedeth`eseM.Fr´ed´ericJURIEProfesseurdesUniversit´esUniversit´edeCaenDirecteurdeth`ese"
+045fbe21ea8e501d443fa2d297c1292264712c62,Links between multisensory processing and autism,"Exp Brain Res +DOI 10.1007/s00221-012-3223-4 +R E S E A R C H A R T I C L E +Links between multisensory processing and autism +Sarah E. Donohue • Elise F. Darling • +Stephen R. Mitroff +Received: 1 June 2012 / Accepted: 7 August 2012 +Ó Springer-Verlag 2012"
+04241ba56d4499a00beb6991d2460d571a218d85,Learning appearance in virtual scenarios for pedestrian detection,"Learning Appearance in Virtual Scenarios for Pedestrian Detection +Javier Mar´ın, David V´azquez, David Ger´onimo and Antonio M. L´opez +Computer Vision Center and Computer Science Dpt. UAB, 08193 Bellaterra, Barcelona, Spain +{jmarin, dvazquez, dgeronimo,"
+041d3eedf5e45ce5c5229f0181c5c576ed1fafd6,How to Take a Good Selfie?,"How to Take a Good Selfie? +Mahdi M. Kalayeh(cid:63) Misrak Seifu◦ Wesna LaLanne(cid:5) Mubarak Shah(cid:63) +(cid:63)Center for Research in Computer Vision at University of Central Florida +◦Jackson State University +(cid:5)University of Central Florida"
+040eb316cec08b36ae0b57fede86043ee0526686,Learning Reliable and Scalable Representations Using Multimodal Multitask Deep Learning,"Learning Reliable and Scalable Representations +Using Multimodal Multitask Deep Learning +Abhinav Valada, and Wolfram Burgard +Department of Computer Science, University of Freiburg, Germany +I. INTRODUCTION +Modality 1 +Modality 2 +Unimodal Seg. +Multimodal Seg. +Fifties - in 5 years robots would be everywhere. +Sixties - in 10 years robots would be everywhere. +Seventies - in 20 years robots would be everywhere. +Eighties - in 40 years robots would be everywhere. +-Marvin Minsky +Those were the words from one of the pioneers of AI +when asked to comment on the progress of robotics in the +twentieth century. This shows the high expectations and +unforeseen challenges that we are faced with for deploying +robots in complex real-world environments. One of the primary +impediments has been the robustness of scene understanding"
047d7cf4301cae3d318468fe03a1c4ce43b086ed,Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression,"Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression Antoine Deleforge, Radu Horaud, Yoav Y. Schechner, Laurent Girin @@ -1539,6 +4754,36 @@ opyright owners and it is a condition of accessing these publications that users with these rights. Take down policy The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to"
+047f8d5d5134dd12c67038623417f05ab9885056,Motion Synthesis In : Static Scan + Expression Out : Best Fitting Sequence + Angry Out : Animated Sequence Statistical Analysis Expression Recognition,"D Faces in Motion: Fully Automatic Registration and Statistical Analysis +Timo Bolkarta,∗, Stefanie Wuhrera +Saarland University, Saarbr¨ucken, Germany"
+0464b56c5beee717b074ed950abcc959372256a6,Fast and Robust Optimization Approaches for Pedestrian Detection,"Fast and Robust Optimization Approaches for +Pedestrian Detection +Victor Hugo Cunha de Melo∗, David Menotti (Co-advisor)†, William Robson Schwartz (Advisor)∗ +Computer Science Department, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil +Computer Science Department, Universidade Federal de Ouro Preto, Ouro Preto, Brazil +Email:"
+040806bc41c0dd50273921d8d839fda58d20b01e,Socio-affective touch expression database,"RESEARCH ARTICLE +Socio-affective touch expression database +Haemy Lee Masson*, Hans Op de Beeck* +Department of Brain and Cognition, KU Leuven, Leuven, Belgium +* (HLM); (HOB)"
+040033d73d1efe316c8f0a8ed702b833a0550d83,Generating Expressions that Refer to Visible Objects,"Atlanta, Georgia, 9–14 June 2013. c(cid:13)2013 Association for Computational Linguistics +Proceedings of NAACL-HLT 2013, pages 1174–1184,"
+04379f40d2a26dd769c53488b7b08a5123f89347,3D Facial Expression Recognition Based on Histograms of Surface Differential Quantities,"D Facial Expression Recognition Based on +Histograms of Surface Differential Quantities +Huibin Li1,2, Jean-Marie Morvan1,3,4, and Liming Chen1,2 +Universit´e de Lyon, CNRS +Ecole Centrale de Lyon, LIRIS UMR5205, F-69134, Lyon, France +Universit´e Lyon 1, Institut Camille Jordan, +3 blvd du 11 Novembre 1918, F-69622 Villeurbanne - Cedex, France +King Abdullah University of Science and Technology, GMSV Research Center, +Bldg 1, Thuwal 23955-6900, Saudi Arabia"
+04bd29ec1ae0b64367ec37ddde51a0d8f8b7f670,Few-shot Object Detection,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2017. +Few-shot Object Detection +Xuanyi Dong, Liang Zheng, Fan Ma, Yi Yang, Deyu Meng"
+042510b39c6cdb463610fdda2081b36ff469a353,Human Pose Estimation from Video and IMUs,"Human Pose Estimation from Video and IMUs +Timo von Marcard, Gerard Pons-Moll, and Bodo Rosenhahn"
0470b0ab569fac5bbe385fa5565036739d4c37f8,Automatic face naming with caption-based supervision,"Automatic Face Naming with Caption-based Supervision Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek, Cordelia Schmid To cite this version: @@ -1559,6 +4804,13 @@ Submitted on 11 Apr 2011 HAL is a multi-disciplinary open access rchive for the deposit and dissemination of sci- entific research documents, whether they are pub-"
+6a3cbe2bb27b2a7d32c358e0be4ed268f7d4455c,Shape Tracking with Occlusions via Coarse-to-Fine Region-Based Sobolev Descent,"Modeling Shape, Appearance and Self-Occlusions +for Articulated Object Tracking +Yanchao Yang and Ganesh Sundaramoorthi"
+6a951df76a56fc89e5df3fbba2e5699ccad4f199,Relative Pairwise Relationship Constrained Non-negative Matrix Factorisation,"IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING +Relative Pairwise Relationship Constrained +Non-negative Matrix Factorisation +Shuai Jiang, Kan Li, and Richard Yida Xu"
6a3a07deadcaaab42a0689fbe5879b5dfc3ede52,Learning to Estimate Pose by Watching Videos,"Learning to Estimate Pose by Watching Videos Prabuddha Chakraborty and Vinay P. Namboodiri Department of Computer Science and Engineering @@ -1571,10 +4823,71 @@ Max Planck Institute f¨ur biologische Kybernetik Spemannstr. 38, D-72076 T¨ubingen, Germany {kimki, mof, http://www.kyb.tuebingen.mpg.de/"
+6a951a47aa545e08508b0b2c6a2bef45e154a3a9,DeepCoder: Semi-Parametric Variational Autoencoders for Automatic Facial Action Coding,"DeepCoder: Semi-parametric Variational Autoencoders +for Automatic Facial Action Coding +Dieu Linh Tran∗, Robert Walecki, Ognjen (Oggi) Rudovic*, Stefanos Eleftheriadis, +Bj¨orn Schuller and Maja Pantic +{linh.tran, r.walecki14, bjoern.schuller,"
+6ad32b70ee21b6fc16ff4caf7b4ada2aaf13cabc,Efficient Subwindow Search: A Branch and Bound Framework for Object Localization,"Efficient Subwindow Search: A Branch and Bound +Framework for Object Localization +Christoph H. Lampert, Matthew B. Blaschko, and Thomas Hofmann +n image of as low resolution as 320×240 contains more than +one billion rectangular subimages. In general, the number of +subimages grows quadratically with the number of image pix- +els, which makes it computationally too expensive to evaluate +the quality function exhaustively for all of these. Instead, one +typically uses heuristics to speed up the search that introduce +the risk of mispredicting the location of an object or even +missing it."
6a16b91b2db0a3164f62bfd956530a4206b23fea,A Method for Real-Time Eye Blink Detection and Its Application,"A Method for Real-Time Eye Blink Detection and Its Application Chinnawat Devahasdin Na Ayudhya Mahidol Wittayanusorn School Puttamonton, Nakornpatom 73170, Thailand"
+6a41ba9db0affa701ea125e09a2fe7eb583e3ac9,Frontal imgelerden otomatik yüz tanıma Automatic face recognition from frontal images,"Frontal imgelerden otomatik yüz tanıma +Automatic face recognition from frontal images +Hasan Serhan Yavuz, Hakan Çevikalp, Rıfat Edizkan +Elektrik ve Elektronik Mühendisliği Bölümü +Eskişehir Osmangazi Üniversitesi +Eskişehir, Türkiye +fotoğraflanan +laboratuarımızda +Özetçe—Yüz tanıma basitçe kişilere ait olan yüz imgelerinden +kimlik tespit edilmesi olarak tanımlanabilir. Bu çalışmada, +sayısal kamera +frontal +imgeler kullanılarak yüz tanıma yapılmıştır. Otomatik yüz +tanıma süreci sırasıyla yüz sezme, göz sezme, sezilen gözlerin orta +noktalarını kullanarak belirlenen standart bir yüz şablonuna +uyacak biçimde haritalama yapma ve sonrasında hizalanan yüz +imgelerini sınıflandırma basamaklarından oluşur. Literatürde +yüz imgesi hazırlama süreci genellikle elle yapılmaktadır. Yüz +imgelerinin tamamı birebir aynı biçimde kesildiği için çok +yüksek tanıma oranları elde edilir ancak bir otomatik yüz tanıma"
+6ada03f390f92704f3df1556846697c54c00f7da,Human-Machine Cooperation in Large-Scale Multimedia Retrieval: A Survey,"Human-Machine Cooperation in Large-Scale +Multimedia Retrieval: A Survey +Kimiaki Shirahama,1 Marcin Grzegorzek,1 and Bipin Indurkhya2 +University of Siegen, 2AGH University of Science and Technology +Correspondence: +Correspondence concerning this +rticle should be addressed to Kimiaki +Shirahama, Pattern Recognition Group, +University of Siegen, Hoelderlinstrasse 3, +57076 Siegen, Germany, or via email to +Keywords: +large-scale multimedia retrieval, human- +machine cooperation, machine-based +methods, human-based methods +Large-Scale Multimedia Retrieval (LSMR) is the task to fast analyze a large amount of multi- +media data like images or videos and accurately find the ones relevant to a certain semantic +meaning. Although LSMR has been investigated for more than two decades in the fields +of multimedia processing and computer vision, a more interdisciplinary approach is neces- +sary to develop an LSMR system that is really meaningful for humans. To this end, this paper +ims to stimulate attention to the LSMR problem from diverse research fields. By explaining"
+6a1e5f4dbabf451122bf35228c8b25c79c7d235f,Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation,"Learning to See the Invisible: End-to-End +Trainable Amodal Instance Segmentation +Patrick Follmann, Rebecca K¨onig, Philipp H¨artinger, Michael Klostermann +MVTec Software GmbH, +www.mvtec.com,"
6a806978ca5cd593d0ccd8b3711b6ef2a163d810,Facial Feature Tracking for Emotional Dynamic Analysis,"Facial feature tracking for Emotional Dynamic Analysis Thibaud Senechal1, Vincent Rapp1, and Lionel Prevost2 @@ -1583,19 +4896,227 @@ Univ. Pierre et Marie Curie, Paris {rapp, LAMIA, EA 4540 Univ. of Fr. West Indies & Guyana"
+6a27ffd788a0db64fef74e673786763c82902a26,Discriminative deep transfer metric learning for cross-scenario person re-identification,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/13/2018 +Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +Discriminativedeeptransfermetriclearningforcross-scenariopersonre-identificationTongguangNiXiaoqingGuHongyuanWangZhongbaoZhangShoubingChenCuiJinTongguangNi,XiaoqingGu,HongyuanWang,ZhongbaoZhang,ShoubingChen,CuiJin,“Discriminativedeeptransfermetriclearningforcross-scenariopersonre-identification,”J.Electron.Imaging27(4),043026(2018),doi:10.1117/1.JEI.27.4.043026."
6a8a3c604591e7dd4346611c14dbef0c8ce9ba54,An Affect-Responsive Interactive Photo Frame,"ENTERFACE’10, JULY 12TH - AUGUST 6TH, AMSTERDAM, THE NETHERLANDS. An Affect-Responsive Interactive Photo Frame Hamdi Dibeklio˘glu, Ilkka Kosunen, Marcos Ortega Hortas, Albert Ali Salah, Petr Zuz´anek"
+6a1fd51107770edbdd832a1934ff5461e891f2e1,A Robust and Dominant Local Binary Pattern and Its Application,"IJSRD - International Journal for Scientific Research & Development| Vol. 2, Issue 10, 2014 | ISSN (online): 2321-0613 +A Robust and Dominant Local Binary Pattern and Its Application +Keerthana A.V1 Ashwin M2 +Student of M.E 2Associate Professor +,2Department of Computer Science & Engineering +,2Adhiyamaan College of Engineering, Krishnagiri, Tamilnadu, India +Local +ternary +Pattern, modified"
+6a0b70abb9a81a96d4baa9b396deb9da4cc20f8f,Clustering through ranking on manifolds,"Clustering Through Ranking On Manifolds +Markus Breitenbach +Dept. of Computer Science; University of Colorado, Boulder, USA +Gregory Z. Grudic +Dept. of Computer Science; University of Colorado, Boulder, USA"
6a52e6fce541126ff429f3c6d573bc774f5b8d89,Role of Facial Emotion in Social Correlation,"Role of Facial Emotion in Social Correlation Pankaj Mishra, Rafik Hadfi, and Takayuki Ito Department of Computer Science and Engineering Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, 466-8555 Japan {pankaj.mishra,"
+6a14652508138fcf0aa8c518109165f65c88fd3f,Programming a humanoid robot in natural language: an experiment with description logics,"Programming a humanoid robot in natural language: +n experiment with description logics +Nicola Vitucci , Alessio Mauro Franchi, Giuseppina Gini +DEIB, Politecnico di Milano +Milano, Italy"
+6ae13c7dcd1d10d2dfe58546a49da09b0b471d68,Person-independent facial expression recognition based on compound local binary pattern (CLBP),"The International Arab Journal of Information Technology, Vol. 11, No. 2, March 2014 195 +Person-Independent Facial Expression Recognition +Based on Compound Local Binary Pattern (CLBP) +Department of Computer Science and Engineering, Islamic University of Technology, Bangladesh +Faisal Ahmed1, Hossain Bari2, and Emam Hossain3 +2Samsung Bangladesh R & D Center Ltd, Bangladesh +3Department of Computer Science and Engineering, Ahsanullah University of Science and Technology, +Bangladesh"
+6af35225cfd744b79577c126e553f549e5b5cdcc,Title Discriminative Hessian Eigenmaps for face recognition,"Title +Discriminative Hessian Eigenmaps for face recognition +Author(s) +Si, S; Tao, D; Chan, KP +Citation +The 2010 IEEE International Conference on Acoustics, Speech +nd Signal Processing (ICASSP), Dallas, TX., 14-19 March 2010. +In IEEE International Conference on Acoustics, Speech and +Signal Processing Proceedings, 2010, p. 5586-5589 +Issued Date +http://hdl.handle.net/10722/125723 +Rights +IEEE International Conference on Acoustics, Speech and Signal +Processing Proceedings. Copyright © IEEE.; ©2010 IEEE. +Personal use of this material is permitted. However, permission +to reprint/republish this material for advertising or promotional +purposes or for creating new collective works for resale or +redistribution to servers or lists, or to reuse any copyrighted +omponent of this work in other works must be obtained from +the IEEE.; This work is licensed under a Creative Commons"
+6a553f7ef42000001f407e95f4955e7ddde46a83,A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation,"IJCARS manuscript No. +(will be inserted by the editor) +A Dataset of Laryngeal Endoscopic Images with +Comparative Study on Convolution Neural Network +Based Semantic Segmentation +Max-Heinrich Laves · Jens Bicker · Lüder +A. Kahrs · Tobias Ortmaier +Received: date / Accepted: date"
+6a6280189ead63b2eec733b8e8ac507e830928fd,Face localization in color images with complex background,"Face localization in color images with complex +ackground +Paola Campadelli, Raffaella Lanzarotti, Giuseppe Lipori +Dipartimento di Scienze dell’Informazione +Universit(cid:30)a degli Studi di Milano +Via Comelico, 39/41 20135 Milano, Italy +fcampadelli, lanzarotti,"
+6ac7fe3a292dc5e0f7d27e11b85ed8277905e9ba,Detecting Traffic Lights by Single Shot Detection,"Detecting Traffic Lights by Single Shot Detection +Julian M¨uller1 and Klaus Dietmayer1"
+6a55d6db1b31f44c9bb37b070fbf7c8f64a31f13,Aging and Emotion Recognition : An Examination of Stimulus and Attentional Mechanisms,"Cleveland State University +ETD Archive +Aging and Emotion Recognition: An Examination +of Stimulus and Attentional Mechanisms +Stephanie Nicole Sedall +Follow this and additional works at: http://engagedscholarship.csuohio.edu/etdarchive +Part of the Experimental Analysis of Behavior Commons +How does access to this work benefit you? Let us know! +Recommended Citation +Sedall, Stephanie Nicole, ""Aging and Emotion Recognition: An Examination of Stimulus and Attentional Mechanisms"" (2016). ETD +Archive. 903. +http://engagedscholarship.csuohio.edu/etdarchive/903 +This Thesis is brought to you for free and open access by It has been accepted for inclusion in ETD Archive by an +uthorized administrator of For more information, please contact"
+6aa21d78af359853ee07288cfc8d047e914ce458,Facial Expression Recognition using Log-Euclidean Statistical Shape Models,"FACIAL EXPRESSION RECOGNITION USING +LOG-EUCLIDEAN STATISTICAL SHAPE MODELS +Bartlomiej W. Papiez, Bogdan J. Matuszewski, Lik-Kwan Shark and Wei Quan +Applied Digital Signal and Image Processing Research Centre, University of Central Lancashire, PR1 2HE Preston, U.K. +Keywords: +Facial expression representation, Facial expression recognition, Vectorial log-Euclidean statistics, Statistical +shape modelling."
+6a75ef6b36489cb59c61f21f3cd09c50ad5b2995,MVTec D2S: Densely Segmented Supermarket Dataset,"MVTec D2S: Densely Segmented Supermarket +Dataset +Patrick Follmann1,2[0000−0001−5400−2384], Tobias B¨ottger1,2[0000−0002−5404−8662], +Philipp H¨artinger1[0000−0002−7093−6280], Rebecca K¨onig1[0000−0002−4169−6759], +nd Markus Ulrich1[0000−0001−8457−5554] +MVTec Software GmbH, 80634 Munich, Germany +https://www.mvtec.com/research +Technical University of Munich, 80333 Munich, Germany"
+6ac1dc59e823d924e797afaf5c4a960ed7106f2a,Deep Facial Expression Recognition: A Survey,"Deep Facial Expression Recognition: A Survey +Shan Li and Weihong Deng∗, Member, IEEE"
+6ae47c7793e2f0f684ae07357335c7cf338d66ef,Optimistic and pessimistic neural networks for object recognition,"published in: International Conference on Image Processing (ICIP) 2017 +OPTIMISTIC AND PESSIMISTIC NEURAL NETWORKS FOR OBJECT RECOGNITION +Rene Grzeszick +Sebastian Sudholt +Gernot A. Fink +email: +TU Dortmund University, Germany"
+6acc92f30c7a141384b9b1bbec8dffe16b08a438,Improving Bag-of-Visual-Words Towards Effective Facial Expressive Image Classification,"Improving Bag-of-Visual-Words Towards Effective Facial Expressive +Image Classification +Dawood Al Chanti1 and Alice Caplier1 +Univ. Grenoble Alpes, CNRS, Grenoble INP∗ , GIPSA-lab, 38000 Grenoble, France +Keywords: +BoVW, k-means++, Relative Conjunction Matrix, SIFT, Spatial Pyramids, TF.IDF."
+6af98f9843ba629ae1b0347e8b8d81a263f8d7f2,Does this recession make me look black? The effect of resource scarcity on the categorization of biracial faces.,"Short Report +Does This Recession Make Me Look Black? +The Effect of Resource Scarcity on the +Categorization of Biracial Faces +3(12) 1476 –1478 +© The Author(s) 2012 +Reprints and permission: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0956797612450892 +http://pss.sagepub.com +Christopher D. Rodeheffer, Sarah E. Hill, and Charles G. Lord +Texas Christian University +Received 2/27/12; Revision accepted 5/10/12 +Prosperity makes friends; adversity tries them. +—Publilius Syrus (Lyman, 1856, p. 73) +In-group biases are a ubiquitous feature of human social life +(e.g., Brewer, 1979; Halevy, Bornstein, & Sagiv, 2008; Mullen, +Dovidio, Johnson, & Copper, 1992; Tajfel, 1982). One explana- +tion offered for these biases is that they arise from resource +ompetition between groups (e.g., Kurzban & Neuberg, 2005;"
6aefe7460e1540438ffa63f7757c4750c844764d,Non-rigid Segmentation Using Sparse Low Dimensional Manifolds and Deep Belief Networks,"Non-rigid Segmentation using Sparse Low Dimensional Manifolds and Deep Belief Networks ∗ Jacinto C. Nascimento Instituto de Sistemas e Rob´otica Instituto Superior T´ecnico, Portugal"
+6ad5a38df8dd4cdddd74f31996ce096d41219f72,Multi-cue onboard pedestrian detection,"Objectives +Implementation details +Experiments on TUD-Brussels +Conclusion +{wojek, walk, +Multi-Cue Onboard Pedestrian Detection +Christian Wojek, Stefan Walk, Bernt Schiele +Computer Science Department, TU Darmstadt, Germany +Detect pedestrians from a moving platform +• Exploit motion information +• Leverage complementarity of features +• Evaluate different classifiers +• New datasets with image pairs +Features +• HOG [1] +8× 8 pixel cells, 2× 2 blocks +9-bin histograms, unsigned gradients +• Haar wavelets [2] +2 and 16 pixel masks +horizontal, vertical and diagonal re-"
+6a1da83440c7685f5a03e7bda17be9025e0892e3,Semantic Match Consistency for Long-Term Visual Localization,"Semantic Match Consistency for Long-Term +Visual Localization +Carl Toft1, Erik Stenborg1, Lars Hammarstrand1, Lucas Brynte1, Marc +Pollefeys2,3, Torsten Sattler2, Fredrik Kahl1 +Department of Electrical Engineering, Chalmers University of Technology, Sweden +Department of Computer Science, ETH Z¨urich, Switzerland +Microsoft, Switzerland"
+6a7ec333ccabd41b9d20f05c145b3377f6045f43,Face Recognition under Varying,(cid:13) 2010 Zihan Zhou
+6a9c460952a96a04e12caa7bae07ae2f7df1238e,Exploiting scene context for on-line object tracking in unconstrained environments. (Exploitation du contexte de scène pour le suivi d'objet en ligne dans des environnements non contraints),"Exploiting scene context for on-line object tracking in +unconstrained environments +Salma Moujtahid +To cite this version: +Salma Moujtahid. Exploiting scene context for on-line object tracking in unconstrained environments. +Modeling and Simulation. Université de Lyon, 2016. English. <NNT : 2016LYSEI110>. <tel- +01783935> +HAL Id: tel-01783935 +https://tel.archives-ouvertes.fr/tel-01783935 +Submitted on 2 May 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+6ade1e0d4744d2eb5bf7bab97289ffd7eeb5a661,Simulated+unsupervised Learning with Adaptive Data Generation and Bidirectional Mappings,"Published as a conference paper at ICLR 2018 +SIMULATED+UNSUPERVISED LEARNING WITH +ADAPTIVE DATA GENERATION AND +BIDIRECTIONAL MAPPINGS +Kangwook Lee∗, Hoon Kim∗& Changho Suh +School of Electrical Engineering +KAIST +Daejeon, South Korea"
+6a536aa4ecd6359d54a34aca7eff828e4df02730,Multimodal Observation and Interpretation of Subjects Engaged in Problem Solving,"Multimodal Observation and Interpretation of Subjects Engaged +in Problem Solving +Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP*, LIG, +Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP*, LIG, +(cid:140)omas Guntz +F-38000 Grenoble, France +Dominique Vaufreydaz +F-38000 Grenoble, France +Ra(cid:130)aella Balzarini +F-38000 Grenoble, France +James Crowley +F-38000 Grenoble, France +Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP*, LIG, +Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP*, LIG,"
+6a69b790a7ec5a396607eb717da2b271a750faaa,Stacked Latent Attention for Multimodal Reasoning,"Stacked Latent Attention for Multimodal Reasoning +Haoqi Fan +Jiatong Zhou +Facebook Research +Facebook Research +Hacker Way +Hacker Way"
6a7e464464f70afea78552c8386f4d2763ea1d9c,Facial Landmark Localization – A Literature Survey,"Review Article International Journal of Current Engineering and Technology E-ISSN 2277 – 4106, P-ISSN 2347 - 5161 @@ -1618,17 +5139,78 @@ LIAMA Sino-French IT Lab." Improving Image Classification using Semantic Attributes Yu Su · Fr´ed´eric Jurie Received: date / Accepted: date"
+320e2c950d5b31cb371208a6b752a94585ac6665,Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning,"Context-Patch Face Hallucination Based on +Thresholding Locality-constrained Representation +nd Reproducing Learning +Junjun Jiang, Member, IEEE, Yi Yu, Suhua Tang, Member, IEEE, Jiayi Ma, Member, IEEE, Akiko Aizawa, and +Kiyoharu Aizawa, Fellow, IEEE"
+329c06c00c627c0b041d330f3c0142a88b7cb1e5,Bayesian Sparsification of Gated Recurrent Neural Networks,"Bayesian Sparsification of Gated Recurrent Neural +Networks +Ekaterina Lobacheva1∗, Nadezhda Chirkova1∗, Dmitry Vetrov1,2 +Samsung-HSE Laboratory, National Research University Higher School of Economics +Samsung AI Center +Moscow, Russia +{elobacheva, nchirkova,"
+32bd968e6cf31e69ee5fca14d3eadeec7f4187c6,Monocular Pedestrian Detection: Survey and Experiments,"Monocular Pedestrian Detection: +Survey and Experiments +Markus Enzweiler, Student Member, IEEE, and Dariu M. Gavrila"
325b048ecd5b4d14dce32f92bff093cd744aa7f8,Multi-Image Graph Cut Clothing Segmentation for Recognizing People,"#2670 CVPR 2008 Submission #2670. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. #2670 Multi-Image Graph Cut Clothing Segmentation for Recognizing People Anonymous CVPR submission Paper ID 2670"
+327f3d65a380f70bc39fe99c7ad55d76a5f7fff4,A data-synthesis-driven method for detecting and extracting vague cognitive regions,"International Journal of Geographical Information +Science +ISSN: 1365-8816 (Print) 1362-3087 (Online) Journal homepage: http://www.tandfonline.com/loi/tgis20 +A data-synthesis-driven method for detecting and +extracting vague cognitive regions +Song Gao, Krzysztof Janowicz, Daniel R. Montello, Yingjie Hu, Jiue-An Yang, +Grant McKenzie, Yiting Ju, Li Gong, Benjamin Adams & Bo Yan +To cite this article: Song Gao, Krzysztof Janowicz, Daniel R. Montello, Yingjie Hu, Jiue-An +Yang, Grant McKenzie, Yiting Ju, Li Gong, Benjamin Adams & Bo Yan (2017): A data-synthesis- +driven method for detecting and extracting vague cognitive regions, International Journal of +Geographical Information Science, DOI: 10.1080/13658816.2016.1273357 +To link to this article: http://dx.doi.org/10.1080/13658816.2016.1273357 +Published online: 08 Jan 2017. +Submit your article to this journal +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=tgis20 +Download by: [UC Santa Barbara Library] +Date: 09 January 2017, At: 09:44"
32f7e1d7fa62b48bedc3fcfc9d18fccc4074d347,Hierarchical Sparse and Collaborative Low-Rank representation for emotion recognition,"HIERARCHICAL SPARSE AND COLLABORATIVE LOW-RANK REPRESENTATION FOR EMOTION RECOGNITION Xiang Xiang, Minh Dao, Gregory D. Hager, Trac D. Tran Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA {xxiang, minh.dao, ghager1,"
+32743e72cdb481b7a30a3d81a96569dcbea4e409,Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for Mobile and Embedded Applications,"Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for +Mobile and Embedded Applications +Baohua Sun, +Lin Yang, +Patrick Dong, Wenhan Zhang, +Gyrfalcon Technology Inc. +Jason Dong, Charles Young +900 McCarthy Blvd. Milpitas, CA 95035"
+32a6f6aa50ce2a631bf4de7432f830b29b6b05f2,Through the eyes of a child: preschoolers' identification of emotional expressions from the child affective facial expression (CAFE) set.,"Cognition and Emotion +ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20 +Through the eyes of a child: preschoolers’ +identification of emotional expressions from the +hild affective facial expression (CAFE) set +Vanessa LoBue, Lewis Baker & Cat Thrasher +To cite this article: Vanessa LoBue, Lewis Baker & Cat Thrasher (2017): Through the eyes of a +hild: preschoolers’ identification of emotional expressions from the child affective facial expression +(CAFE) set, Cognition and Emotion, DOI: 10.1080/02699931.2017.1365046 +To link to this article: http://dx.doi.org/10.1080/02699931.2017.1365046 +Published online: 10 Aug 2017. +Submit your article to this journal +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pcem20 +Download by: [173.56.101.121] +Date: 10 August 2017, At: 05:46"
324f39fb5673ec2296d90142cf9a909e595d82cf,Relationship Matrix Nonnegative Decomposition for Clustering,"Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2011, Article ID 864540, 15 pages @@ -1649,6 +5231,72 @@ Nonnegative matrix factorization (cid:2)NMF(cid:3) is a popular tool for analyzi negative data. For a positive pairwise similarity matrix, symmetric NMF (cid:2)SNMF(cid:3) and weighted NMF (cid:2)WNMF(cid:3) can be used to cluster the data. However, both of them are not very efficient for the ill-structured pairwise similarity matrix. In this paper, a novel model, called relationship"
+32cde90437ab5a70cf003ea36f66f2de0e24b3ab,The Cityscapes Dataset for Semantic Urban Scene Understanding,"The Cityscapes Dataset for Semantic Urban Scene Understanding +Marius Cordts1,2 +Markus Enzweiler1 +Mohamed Omran3 +Rodrigo Benenson3 +Sebastian Ramos1,4 +Timo Rehfeld1,2 +Uwe Franke1 +Stefan Roth2 +Bernt Schiele3 +Daimler AG R&D, 2TU Darmstadt, 3MPI Informatics, 4TU Dresden +www.cityscapes-dataset.net +train/val – fine annotation – 3475 images +train – coarse annotation – 20 000 images +test – fine annotation – 1525 images"
+323d6d93b059372bbe26a86bad1b9d94b076f50e,(A) Vision for 2050 - Context-Based Image Understanding for a Human-Robot Soccer Match,"Electronic Communications of the EASST +Volume 62 (2013) +Specification, Transformation, Navigation +Special Issue dedicated to Bernd Krieg-Br¨uckner +on the Occasion of his 60th Birthday +(A) Vision for 2050 – Context-Based Image Understanding for a +Human-Robot Soccer Match +Udo Frese, Tim Laue, Oliver Birbach, and Thomas R¨ofer +9 pages +Guest Editors: Till Mossakowski, Markus Roggenbach, Lutz Schr¨oder +Managing Editors: Tiziana Margaria, Julia Padberg, Gabriele Taentzer +ISSN 1863-2122"
+3274a13562029f36e2f0fad3270e3ecb9ca013bd,Real-time UAV Target Tracking System Based on Optical Flow and Particle Filter Integration,"Real-time UAV Target Tracking System Based on Optical Flow and +Particle Filter Integration +WESAM ASKAR +Electrical Engineering +Military Tech. College +EGYPT +OSAMA ELMOWAFY +Computer Engineering +New Cairo Academy +ALIAA YOUSSIF +Computer Engineering +Helwan University +GAMAL ELNASHAR +Electrical Engineering +Military Tech. College +EGYPT +EGYPT +EGYPT"
+325c9f6f848407a22b86e3253cb7f29fac19e40c,Change Detection in Crowded Underwater Scenes - Via an Extended Gaussian Switch Model Combined with a Flux Tensor Pre-segmentation,"Change Detection in Crowded Underwater Scenes +via an Extended Gaussian Switch Model combined with a Flux Tensor +Pre-Segmentation +Martin Radolko1,2, Fahimeh Farhadifard1,2 and Uwe von Lukas1,2 +Institute for Computer Science, University Rostock, Rostock, Germany +Fraunhofer Institute for Computer Fraphics Research IGD , Rostock, Germany +{Martin.Radolko, +Keywords: +Change Detection, Background Subtraction, Video Segmentation, Video Segregation, Underwater Segmenta- +tion, Flux Tensor"
+32d8194269faf6ae505a8d7937a3423e4830187e,Big Five Personality Recognition from Multiple Text Genres,"Big Five Personality Recognition from +Multiple Text Genres +Vitor Garcia dos Santos, Ivandr´e Paraboni, and Barbara Barbosa Claudino Silva +University of S˜ao Paulo, School of Arts, Sciences and Humanities, S˜ao Paulo, Brazil"
+324cf94743359df3ada2f86ee8cd3bb6dccae695,FERA 2015 - Second Facial Expression Recognition and Analysis Challenge,"FG 2015 +FG 2015 Submission. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. +FG 2015 +FERA 2015 - Second Facial Expression Recognition and Analysis +Challenge +Anonymous FG 2015 submission +– DO NOT DISTRIBUTE –"
321bd4d5d80abb1bae675a48583f872af3919172,Entropy-weighted feature-fusion method for head-pose estimation,"Wang et al. EURASIP Journal on Image and Video Processing (2016) 2016:44 DOI 10.1186/s13640-016-0152-3 EURASIP Journal on Image @@ -1678,6 +5326,66 @@ BA=JKHA p 6DA >EAJHE? EBH=JE BH = IOI JA EI JDA A= D(p(cid:107)q) BH = FAHII E JDA FFK=JE 1 J FH=?JE?=O A=IKHA D(p(cid:107)q) MEJD I= FAI MA = =CHEJD MDE?D HACK=HEAI = /=KIIE="
+320ea4748b1f7e808eabedbedb75cce660122d26,"Detecting Avocados to Zucchinis: What Have We Done, and Where Are We Going?","Detecting avocados to zucchinis: what have we done, and where are we going? +Olga Russakovsky1, Jia Deng1, Zhiheng Huang1, Alexander C. Berg2, Li Fei-Fei1 +Stanford University1 , UNC Chapel Hill2"
+325000c2ebe4fcfd08946aef91aee8bec22026a5,Multi-Label Learning With Fused Multimodal Bi-Relational Graph,"Multi-Label Learning With Fused +Multimodal Bi-Relational Graph +Jiejun Xu, Vignesh Jagadeesh, and B. S. Manjunath, Fellow, IEEE"
+32b9be86de4f82c5a43da2a1a0a892515da8910d,Robust False Positive Detection for Real-Time Multi-target Tracking,"Robust False Positive Detection for Real-Time +Multi-Target Tracking +Henrik Brauer, Christos Grecos, and Kai von Luck +University of the West of Scotland +University of Applied Sciences Hamburg"
+3265c7799f9d14e29de37b1e37aec4330cd1d747,Class-Specific Binary Correlograms for Object Recognition,"Class-Specific Binary Correlograms for Object +Recognition +Jaume Amores1, Nicu Sebe2, Petia Radeva3 +IMEDIA Research Group, INRIA, France +Univ. of Amsterdam, The Netherlands +Computer Vision Center, UAB, Spain"
+323fabb6cb4e74518fd4c7ad6ea5a1b2674e63d3,Object recognition based on radial basis function neural networks: Experiments with RGB-D camera embedded on mobile robots,"Object Recognition Based on Radial Basis Function +Neural Networks: experiments with RGB-D camera +embedded on mobile robots +Saeed Gholami Shahbandi +LISA - University of Angers +Philippe Lucidarme +LISA - University of Angers +62 av. Notre Dame du Lac, 49000 Angers, France +62 av. Notre Dame du Lac, 49000 Angers, France"
+3214ce1c8c86c0c4670e3f8b8f4351d8fa44434d,Deep Semantic Pyramids for Human Attributes and Action Recognition,"Deep Semantic Pyramids for Human Attributes +nd Action Recognition +Fahad Shahbaz Khan1(B), Rao Muhammad Anwer2, Joost van de Weijer3, +Michael Felsberg1, and Jorma Laaksonen2 +Computer Vision Laboratory, Link¨oping University, Link¨oping, Sweden +Department of Information and Computer Science, +Aalto University School of Science, Aalto, Finland +Computer Vision Center, CS Department, Universitat Autonoma de Barcelona, +Barcelona, Spain"
+32d6ee09bd8f1a7c42708d6dd8a5fb85ac4e08bc,Non-Interfering Effects of Active Post-Encoding Tasks on Episodic Memory Consolidation in Humans,"ORIGINAL RESEARCH +published: 29 March 2017 +doi: 10.3389/fnbeh.2017.00054 +Non-Interfering Effects of Active +Post-Encoding Tasks on Episodic +Memory Consolidation in Humans +Samarth Varma 1*, Atsuko Takashima 1,2, Sander Krewinkel 1, Maaike van Kooten 1, +Lily Fu 1, W. Pieter Medendorp 1, Roy P. C. Kessels 1 and Sander M. Daselaar 1 +Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, 2Department of +Neurobiology of Language, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands +So far, studies that investigated interference effects of post-learning processes on +episodic memory consolidation in humans have used tasks involving only complex and +meaningful information. Such tasks require reallocation of general or encoding-specific +resources away from consolidation-relevant activities. The possibility that interference +an be elicited using a task that heavily taxes our limited brain resources, but has +low semantic and hippocampal related long-term memory processing demands, has +never been tested. We address this question by investigating whether consolidation +ould persist in parallel with an active, encoding-irrelevant, minimally semantic task, +regardless of its high resource demands for cognitive processing. We distinguish the +impact of such a task on consolidation based on whether it engages resources that"
+32f0c95cee39eba143452d6a0fe93283575257e6,Generative Adversarial Networks for Extreme Learned Image Compression,"GENERATIVE ADVERSARIAL NETWORKS FOR +EXTREME LEARNED IMAGE COMPRESSION +Eirikur Agustsson∗, Michael Tschannen∗, Fabian Mentzer∗, Radu Timofte & Luc Van Gool +{aeirikur, mentzerf, radu.timofte, +ETH Zurich"
32728e1eb1da13686b69cc0bd7cce55a5c963cdd,Automatic Facial Emotion Recognition Method Based on Eye Region Changes,"Automatic Facial Emotion Recognition Method Based on Eye Region Changes Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran @@ -1687,12 +5395,93 @@ Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehr Muharram Mansoorizadeh Faculty of Electrical and Computer Engineering, Bu-Ali Sina University, Hamadan, Iran Received: 19/Apr/2015 Revised: 19/Mar/2016 Accepted: 19/Apr/2016"
+32ef19e90e7834ec09ef19fcef7cd2aa6eff85a9,Modeling Natural Images Using Gated MRFs,"JOURNAL OF PAMI, VOL. ?, NO. ?, JANUARY 20?? +Modeling Natural Images Using Gated MRFs +Marc’Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton"
+326df1b94624b7958cff0f7e3d16e612ea9d7e4d,Similarity Rank Correlation for Face Recognition Under Unenrolled Pose,"Similarity Rank Correlation for Face +Recognition Under Unenrolled Pose +Marco K. M¨uller, Alexander Heinrichs, Andreas H.J. Tewes, +Achim Sch¨afer, and Rolf P. W¨urtz +Institut f¨ur Neuroinformatik, Ruhr-Universit¨at, D–44780 Bochum, Germany"
+323cd51bc18c700fa88044dd24ae663a7eabaa68,Utilizing student activity patterns to predict performance,"Casey and Azcona International Journal of Educational Technology +in Higher Education (2017) 14:4 +DOI 10.1186/s41239-017-0044-3 +R ES EAR CH A R T I C LE +Utilizing student activity patterns to predict +performance +Kevin Casey1* and David Azcona2 +Open Access +* Correspondence: +Maynooth University, Maynooth, +Ireland +Full list of author information is +vailable at the end of the article"
+32c6086b1605698c8b775b6920741981e85b217d,Designing and sharing activity recognition systems across platforms: methods from wearable computing,"IEEE RAM - SPECIAL ISSUE TOWARDS A WWW FOR ROBOTS +Designing and sharing activity recognition systems +cross platforms: methods from wearable computing +Daniel Roggen, Member, IEEE, and St´ephane Magnenat, Member, IEEE, and Markus Waibel, Member, IEEE, +nd Gerhard Tr¨oster, Senior Member, IEEE"
+321fbbe7da848b602f376219ed9aed6a7f4b7f57,Effective Use of Frequent Itemset Mining for Image Classification,"Effective Use of Frequent Itemset Mining for +Image Classification +Basura Fernando1, Elisa Fromont2, and Tinne Tuytelaars1 +KU Leuven, ESAT-PSI, IBBT (Belgium) +University of Saint-Etienne(France)"
+324d82129642f84838be71bd7401f38c80fb87d7,Adaptive Mixtures of Factor Analyzers,"Adaptive Mixtures of Factor Analyzers +Heysem Kayaa,∗, Albert Ali Salaha +Department of Computer Engineering +Bo˘gazi¸ci University, 34342, Bebek, ˙Istanbul"
324b9369a1457213ec7a5a12fe77c0ee9aef1ad4,Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network,"Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network Jinwei Gu Xiaodong Yang Shalini De Mello Jan Kautz NVIDIA"
+3295ec2e52cd83cec75fc7c7064a843756b4d1ee,An Efficient Pedestrian Detection Approach Using a Novel Split Function of Hough Forests,"Regular Paper +Journal of Computing Science and Engineering, +Vol. 8, No. 4, December 2014, pp. 207-214 +An Efficient Pedestrian Detection Approach Using a Novel Split +Function of Hough Forests +Trung Dung Do, Thi Ly Vu, Van Huan Nguyen, Hakil Kim*, and Chongho Lee +School of Information and Communication Engineering, Inha University, Incheon, Korea +{dotrungdung, vuthily, {hikim,"
32df63d395b5462a8a4a3c3574ae7916b0cd4d1d,Facial expression recognition using ensemble of classifiers,"978-1-4577-0539-7/11/$26.00 ©2011 IEEE ICASSP 2011"
+35570297681daa3973498eabead361d0be961672,Configuration Estimates Improve Pedestrian Finding,"Configuration Estimates Improve Pedestrian Finding +Duan Tran∗ +U.Illinois at Urbana-Champaign +Urbana, IL 61801 USA +D.A. Forsyth +U.Illinois at Urbana-Champaign +Urbana, IL 61801 USA"
+35af45f799c65d21bbb3cd24f666de861bad33b0,Multi-Target Tracking by Discrete-Continuous Energy Minimization,"Multi-Target Tracking by +Discrete-Continuous Energy Minimization +Anton Milan, Member, IEEE, Konrad Schindler, Senior Member, IEEE and +Stefan Roth, Member, IEEE,"
35308a3fd49d4f33bdbd35fefee39e39fe6b30b7,Efficient and effective human action recognition in video through motion boundary description with a compact set of trajectories,"biblio.ugent.be The UGent Institutional Repository is the electronic archiving and dissemination platform for allUGent research publications. Ghent University has implemented a mandate stipulating that allacademic publications of UGent researchers should be deposited and archived in this repository.Except for items where current copyright restrictions apply, these papers are available in OpenAccess. This item is the archived peer-reviewed author-version of: Efficient and effective human action recognition in video through motion boundary description witha compact set of trajectories Jeong-Jik Seo, Jisoo Son, Hyung-Il Kim, Wesley De Neve, and Yong Man Ro In: 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition,1, 1-6, 2015. To refer to or to cite this work, please use the citation to the published version: Seo, J., Son, J., Kim, H., De Neve, W., and Ro, Y. M. (2015). Efficient and effective human actionrecognition in video through motion boundary description with a compact set of trajectories. 11thIEEE International Conference and Workshops on Automatic Face and Gesture Recognition 1 1-6.http://dx.doi.org/10.1109/FG.2015.7163123"
+3535ba0cba9bf03443d52cbfc9a87090ca2e5d49,Supplementary Material : Synthesized Classifiers for Zero-Shot Learning,"Supplementary Material: +Synthesized Classifiers for Zero-Shot Learning +Soravit Changpinyo∗, Wei-Lun Chao∗ +U. of Southern California +Los Angeles, CA +Boqing Gong +U. of Central Florida +Orlando, FL +schangpi, +Fei Sha +U. of California +Los Angeles, CA +In this Supplementary Material, we provide details +omitted in the main text. +• Section 1: cross-validation strategies (Section 3.2 +of the main paper). +• Section 2: learning metrics for semantic similarity +(Section 3.1 of the main paper). +• Section 3: details on experimental setup (Sec- +tion 4.1 of the main paper)."
+35c0220ab8a8281129a00ac32ef2f488fb562eb7,Part Annotations via Pairwise Correspondence,"Part Annotations via Pairwise Correspondence +Subhransu Maji Gregory Shakhnarovich +{smaji, +Toyota Technological Institute at Chicago, Chicago, IL"
+3514140d9c2e692abed0aebe0531f78c250f5806,Discriminative Transformation Learning for Fuzzy Sparse Subspace Clustering,"Discriminative Transformation Learning for Fuzzy +Sparse Subspace Clustering +Zaidao Wen, Biao Hou, Member, IEEE, Qian Wu and Licheng Jiao, Senior Member, IEEE"
352d61eb66b053ae5689bd194840fd5d33f0e9c0,Analysis Dictionary Learning based Classification: Structure for Robustness,"Analysis Dictionary Learning based Classification: Structure for Robustness Wen Tang, Ashkan Panahi, Hamid Krim, and Liyi Dai"
@@ -1719,19 +5508,136 @@ Kumar∗ · Ching-Hui Chen∗ · Vishal M. Patel · Carlos D. Castillo · Rama Chellappa · Rajeev Ranjan∗ · Swami Sankaranarayanan∗ · Amit Received: date / Accepted: date"
+35692e80fa2fc17a1d37a40b3d4ffca28a1bcc7b,Appearance-based people recognition by local dissimilarity representations,"Appearance-based People Recognition by Local +Dissimilarity Representations +Riccardo Satta, Giorgio Fumera, Fabio Roli +Dept. of Electrical and Electronic Engineering, University of Cagliari +Piazza d’Armi, 09123 Cagliari, Italy +riccardo.satta, fumera,"
+35fe83665c61adb513781c7208b92706ae2a1578,Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions,
35b1c1f2851e9ac4381ef41b4d980f398f1aad68,Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning,"Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning Chuang Gan1, Boqing Gong2, Kun Liu3, Hao Su 4, Leonidas J. Guibas 5 MIT-IBM Watson AI Lab , 2 Tencent AI Lab, 3 BUPT, 4 UCSD, 5 Stanford University"
+359a4142f6a55a58a3e18628e3ee52c76744fcb0,Prevalence of face recognition deficits in middle childhood.,"ISSN: 1747-0218 (Print) 1747-0226 (Online) Journal homepage: http://www.tandfonline.com/loi/pqje20 +Prevalence of face recognition deficits in middle +hildhood +Rachel J Bennetts, Ebony Murray, Tian Boyce & Sarah Bate +To cite this article: Rachel J Bennetts, Ebony Murray, Tian Boyce & Sarah Bate (2016): +Prevalence of face recognition deficits in middle childhood, The Quarterly Journal of +Experimental Psychology, DOI: 10.1080/17470218.2016.1167924 +To link to this article: http://dx.doi.org/10.1080/17470218.2016.1167924 +View supplementary material +Accepted author version posted online: 21 +Mar 2016. +Submit your article to this journal +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pqje20 +Download by: [Rachel Bennetts] +Date: 22 March 2016, At: 07:06"
+35058a8166a8fa4479167ba33b3010cc8c839f44,A Study on Gait-Based Gender Classification,"A Study on Gait-Based Gender Classification +Shiqi Yu, Member, IEEE, Tieniu Tan, Fellow, IEEE, +Kaiqi Huang, Member, IEEE, Kui Jia, and Xinyu Wu"
351c02d4775ae95e04ab1e5dd0c758d2d80c3ddd,ActionSnapping: Motion-Based Video Synchronization,"ActionSnapping: Motion-based Video Synchronization Jean-Charles Bazin and Alexander Sorkine-Hornung Disney Research"
+35c0954acde9c86df8bbcb6edccbcd702796f5eb,"Multimodal Database of Emotional Speech , Video and Gestures","World Academy of Science, Engineering and Technology +International Journal of Computer and Information Engineering +Vol:12, No:10, 2018 +Multimodal Database of Emotional Speech, Video +nd Gestures +Tomasz Sapi´nski, Dorota Kami´nska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari"
35e4b6c20756cd6388a3c0012b58acee14ffa604,Gender Classification in Large Databases,"Gender Classification in Large Databases E. Ram´on-Balmaseda, J. Lorenzo-Navarro, and M. Castrill´on-Santana (cid:63) Universidad de Las Palmas de Gran Canaria SIANI Spain"
+357df3ee0f0c30d5c8abc5a1bdf70122322d6fbd,Object Detectors Emerge in Deep Scene CNNs,"Under review as a conference paper at ICLR 2015 +OBJECT DETECTORS EMERGE IN DEEP SCENE CNNS +Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba +Department of Computer Science and Artificial Intelligence, MIT"
+35be5bea87c465c97127c64919d115e235d62e82,"The automatic detection of chronic pain-related expression : requirements , challenges and a multimodal dataset","IEEE TRANSACTIONS ON JOURNAL NAME, MANUSCRIPT ID +The automatic detection of chronic pain- +related expression: requirements, challenges +nd a multimodal dataset +Min S. H. Aung, Sebastian Kaltwang, Bernardino Romera-Paredes, Brais Martinez, Aneesha +Singh, Matteo Cella, Michel Valstar, Hongying Meng, Andrew Kemp, Moshen Shafizadeh, Aaron +C. Elkins, Natalie Kanakam, Amschel de Rothschild, Nick Tyler, Paul J. Watson, Amanda C. de C. +Williams, Maja Pantic, and Nadia Bianchi-Berthouze* +face videos, head mounted and room audio signals,"
+35f3c4012e802332faf0a1426e9acf8365601551,Bidirectional Conditional Generative Adversarial Networks,"Bidirectional Conditional +Generative Adversarial Networks +Ayush Jaiswal, Wael AbdAlmageed, Yue Wu, and Premkumar Natarajan +USC Information Sciences Institute, Marina del Rey, CA, USA +{ajaiswal, wamageed, yue wu,"
+355de7460120ddc1150d9ce3756f9848983f7ff4,Midge: Generating Image Descriptions From Computer Vision Detections,"Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics, pages 747–756, +Avignon, France, April 23 - 27 2012. c(cid:13)2012 Association for Computational Linguistics"
+35e808424317cf03b51516df7d083f45791311ae,A Survey for Action Recognition Research,"A Survey for Action Recognition Research +Yuancheng Ye"
+355c8c0dbd80de9d23affb37ac102179b6b2a908,“A Distorted Skull Lies in the Bottom Center...” Identifying Paintings from Text Descriptions,"Anupam Guha, Mohit Iyyer, and Jordan Boyd-Graber. A Distorted Skull Lies in the Bottom Center: +Identifying Paintings from Text Descriptions. NAACL Human-Computer Question Answering Workshop, 2016. +Title = {A Distorted Skull Lies in the Bottom Center: Identifying Paintings from Text Descriptions}, +Author = {Anupam Guha and Mohit Iyyer and Jordan Boyd-Graber}, +Booktitle = {NAACL Human-Computer Question Answering Workshop}, +Year = {2016}, +Location = {San Diego, CA}, +Url = {docs/2016_naacl_paintings.pdf}, +Links: +• Data [http://www.cs.umd.edu/~aguha/data/paintdata.rar] +Downloaded from http://cs.colorado.edu/~jbg/docs/2016_naacl_paintings.pdf"
+35035f79256a3f19a111fff34df6d14876d83fab,Satyam: Democratizing Groundtruth for Machine Vision,"SATYAM: DEMOCRATIZING GROUNDTRUTH FOR MACHINE VISION +Hang Qiu?, Krishna Chintalapudi†, Ramesh Govindan?"
+35457de70ea13415b8abd3898a4a83021946501f,Learning Robust and Discriminative Subspace With Low-Rank Constraints,"Calhoun: The NPS Institutional Archive +Faculty and Researcher Publications +Funded by Naval Postgraduate School +Learning Robust and Discriminative Subspace +With Low-Rank Constraints +Sheng Li +http://hdl.handle.net/10945/52406"
+3506ef7168e07840187ec978b47f3a05a753101d,Robust 3D Face Landmark Localization Based on Local Coordinate Coding,"Robust 3D Face Landmark Localization based on +Local Coordinate Coding +Mingli Song, Senior Member, IEEE, Dacheng Tao, Senior Member, IEEE, Shengpeng Sun, Chun Chen, and +Stephen J. Maybank Fellow, IEEE,"
+3575d74eb548c3187ec5b0d27383ac966b9d7110,Feature Extraction and Face Recognition through Neural Network,"International Journal of Advanced Computer Technology (IJACT) +ISSN:2319-7900 +Feature Extraction and Face Recognition through Neural +Network +Sanjay Kumar Dekate,Research scholar, Dr. C. V. Raman University, Bilaspur, India +Dr. Anupam Shukla,Professor, ABV-IIITM, Gwalior, India"
+353480b21d5745590db5f70b016a27e25f5b9aec,Cross-Modal and Hierarchical Modeling of Video and Text,"Cross-Modal and Hierarchical Modeling of Video +nd Text +Bowen Zhang(cid:63)1, Hexiang Hu(cid:63)1, and Fei Sha2 +Dept. of Computer Science, U. of Southern California, Los Angeles, CA 90089 +Netflix, 5808 Sunset Blvd, Los Angeles, CA 90028"
+35410a58514cd5fd66d9c43d42e8222526170c1b,Shared mechanism for emotion processing in adolescents with and without autism,"Received: 04 August 2016 +Accepted: 05 January 2017 +Published: 20 February 2017 +Shared mechanism for emotion +processing in adolescents with and +without autism +Christina Ioannou1, Marwa El Zein1, Valentin Wyart1, Isabelle Scheid2,3, +Frédérique Amsellem3,4, Richard Delorme3,4, Coralie Chevallier1,* & Julie Grèzes1,* +Although, the quest to understand emotional processing in individuals with Autism Spectrum Disorders +(ASD) has led to an impressive number of studies, the picture that emerges from this research remains +inconsistent. Some studies find that Typically Developing (TD) individuals outperform those with +ASD in emotion recognition tasks, others find no such difference. In this paper, we move beyond +focusing on potential group differences in behaviour to answer what we believe is a more pressing +question: do individuals with ASD use the same mechanisms to process emotional cues? To this end, +we rely on model-based analyses of participants’ accuracy during an emotion categorisation task in +which displays of anger and fear are paired with direct vs. averted gaze. Behavioural data of 20 ASD +nd 20 TD adolescents revealed that the ASD group displayed lower overall performance. Yet, gaze +direction had a similar impact on emotion categorisation in both groups, i.e. improved accuracy for +salient combinations (anger-direct, fear-averted). Critically, computational modelling of participants’ +ehaviour reveals that the same mechanism, i.e. increased perceptual sensitivity, underlies the"
+3596c23a0f13c36d2c71c4cba4351363954dd02a,PathFinder: An autonomous mobile robot guided by Computer Vision,"PathFinder: An autonomous mobile robot guided by Computer +Vision +Andre R. de Geus1,2, Marcelo H. Stoppa1, Sergio F. da Silva1,2 +Modeling and Optimization Program, Federal University of Goias, Catalao, Goias, Brazil +Biotechnology Institute, Federal University of Goias, Catalao, Goias, Brazil +Email:"
35f084ddee49072fdb6e0e2e6344ce50c02457ef,A bilinear illumination model for robust face recognition,"A Bilinear Illumination Model for Robust Face Recognition The Harvard community has made this @@ -1752,12 +5658,42 @@ This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions pplicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-"
+3533a7714b19396bba8297e0ca22f85ac68ca18a,Dense Captioning with Joint Inference and Visual Context,"Dense Captioning with Joint Inference and Visual Context +Linjie Yang +Kevin Tang +Jianchao Yang +Li-Jia Li +{linjie.yang, kevin.tang, +Snap Inc."
+35e730f7967155b9394f9e5d3cadf2b955ce9a7b,Deep Affinity Network for Multiple Object Tracking,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2017 +Deep Affinity Network +for Multiple Object Tracking +ShiJie Sun, Naveed Akhtar, HuanSheng Song, Ajmal Mian, Mubarak Shah"
+3521904cced380b849325d6fda2a4d855edbe405,Finding Images of Rare and Ambiguous Entities,"Finding Images of Rare and +Ambiguous Entities +Bilyana Taneva +Mouna Kacimi +Gerhard Weikum +MPI–I–2011–5–002 +May 2011"
353a89c277cca3e3e4e8c6a199ae3442cdad59b5,Learning from Multiple Views of Data,
35e0256b33212ddad2db548484c595334f15b4da,Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification,"Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification Wenguan Wang∗1,2, Yuanlu Xu∗2, Jianbing Shen†1, and Song-Chun Zhu2 Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, China Department of Computer Science and Statistics, University of California, Los Angeles, USA"
+35d94887e4eb075f2603b2c69b19d31471351ff7,People detection and tracking from aerial thermal views,
+3555d849b85e9416e9496c9976084b0e692b63cd,Towards Effective Gans,"Under review as a conference paper at ICLR 2018 +TOWARDS EFFECTIVE GANS +FOR DATA DISTRIBUTIONS WITH DIVERSE MODES +Anonymous authors +Paper under double-blind review"
+3597ca03bded3717f5c88273e4b7dbf24545ff83,Mouse Pose Estimation From Depth Images,"Mouse Pose Estimation From Depth Images +Ashwin Nanjappa1, Li Cheng∗1, Wei Gao1, Chi Xu1, Adam Claridge-Chang2, and +Zoe Bichler3 +Bioinformatics Institute, A*STAR, Singapore +Institute of Molecular and Cell Biology, A*STAR, Singapore +National Neuroscience Institute, Singapore"
35e6f6e5f4f780508e5f58e87f9efe2b07d8a864,Summarization of User-Generated Sports Video by Using Deep Action Recognition Features,"This paper is a preprint (IEEE accepted status). IEEE copyright notice. 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for @@ -1770,6 +5706,8 @@ keywords: Cameras; Feature extraction; Games; Hidden Markov models; Semantics; Three-dimensional displays; 3D convolutional neural networks; Sports video summarization; ction recognition; deep learning; long short-term memory; user-generated video, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8259321&isnumber=4456689"
+35800a537017803dd08274710388734db66b54f0,Sliced Wasserstein Generative Models,"Sliced Wasserstein Generative Models +Jiqing Wu * 1 Zhiwu Huang * 1 Wen Li 1 Janine Thoma 1 Luc Van Gool 1 2"
35e87e06cf19908855a16ede8c79a0d3d7687b5c,Strategies for Multi-View Face Recognition for Identification of Human Faces: A Review,"Strategies for Multi-View Face Recognition for Identification of Human Faces: A Review Pritesh G. Shah @@ -1785,6 +5723,66 @@ Aurangabad." Matrix Completion for Weakly-supervised Multi-label Image Classification Ricardo Cabral, Fernando De la Torre, João P. Costeira, Alexandre Bernardino"
+354ddc8976a762ee03fb78b73adc3b5312e5f2a5,Accurate Eye Center Location through Invariant Isocentric Patterns,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +Accurate Eye Center Location through Invariant +Isocentric Patterns +Roberto Valenti, Student Member, IEEE, and Theo Gevers, Member, IEEE,"
+351de1f7862bd13a82fcfcaa698b4efd53bc2c35,Automatic 3D face verification from range data,- 1930-7803-7663-3/03/$17.00 ©2003 IEEEICASSP 2003(cid:224)
+35b9ded80ce2b30ee115b8198d146890b9028d51,Regularizing max-margin exemplars by reconstruction and generative models,"Regularizing Max-Margin Exemplars by Reconstruction and Generative Models +Jose C. Rubio and Bj¨orn Ommer +Heidelberg Collaboratory for Image Processing +IWR, Heidelberg University, Germany"
+694dda2a9f6d86c4bf3f57d85dfd376e2067ec62,How Much Face Information Is Needed?,"HOW MUCH FACE INFORMATION IS NEEDED? +P2CA: +Davide Onofrio*, Antonio Rama+, Francesc Tarres+, Stefano Tubaro* +*Dipartimento di Elettronica e Informazione - Politecnico di Milano ++Department Teoria del Senyal i Comunicacions de la Universitat Politècnica de Catalunya"
+69c8b0ec77d3164df2069a5133780a36ec8e91ad,Unsupervised 3D Reconstruction from a Single Image via Adversarial Learning,"Unsupervised 3D Reconstruction from a Single Image via Adversarial Learning +Lingjing Wang +NYU Multimedia and Visual Computing Lab +Courant Institute of Mathematical Science +NYU Tandon School of Engineering, USA +Yi Fang ∗ +NYU Multimedia and Visual Computing Lab +Dept. of ECE, NYU Abu Dhabi, UAE +Dept. of ECE, NYU Tandon School of Engineering, USA"
+693905c29feb7f9be3517308c8a9c2dc68aa8682,Self-supervised CNN for Unconstrained 3D Facial Performance Capture from an RGB-D Camera,"Self-supervised CNN for Unconstrained 3D Facial +Performance Capture from an RGB-D Camera +Yudong Guo, Juyong Zhang†, Lin Cai, Jianfei Cai and Jianmin Zheng"
+699a7c88a6d226f59c7a5619b3cfad714415c31a,"Incorporating Luminance, Depth and Color Information by Fusion-based Networks for Semantic Segmentation","Incorporating Luminance, Depth and Color Information by +Fusion-based Networks for Semantic Segmentation +Shao-Yuan Lo +Shang-Wei Hung +National Chiao Ting University, UC San Diego +National Chiao Ting University +Figure 1: Flowchart of the proposed semantic segmentation +system. Y: luminance information. +omplexity. Lately, DenseNet [11] designs the invention of +dding dense connections between each layer, which +enhances the information flow in networks, and thus it +previously +outperforms many +network +rchitectures including ResNet [12]. +proposed +With the help of depth sensors such as Kinect, depth +maps can be obtained along with RGB images. Since the +depth channel provides complementary information to the +RGB channels, containing the depth information is believed"
+6911686f00c99c51c21f057c45d561c88027f676,Articulated pose estimation with parts connectivity using discriminative local oriented contours,"Articulated Pose Estimation with Parts Connectivity +using Discriminative Local Oriented Contours +Norimichi Ukita +Nara Institute of Science and Technology"
+6937fe93e6238ee21904c172809bea0086da4570,Contour Grouping Based on Contour-Skeleton Duality,"Int J Comput Vis (2009) 83: 12–29 +DOI 10.1007/s11263-009-0208-2 +Contour Grouping Based on Contour-Skeleton Duality +Nagesh Adluru · Longin Jan Latecki +Received: 30 May 2008 / Accepted: 6 January 2009 / Published online: 27 January 2009 +© Springer Science+Business Media, LLC 2009"
+6903496ee5d4c24ca5f3f18211f406e0ba8442d6,Multi-Mapping Image-to-Image Translation with Central Biasing Normalization,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2018 +Multi-Mapping Image-to-Image Translation with +Central Biasing Normalization +Xiaoming Yu, Zhenqiang Ying, Student Member, IEEE, Thomas Li, Shan Liu, and Ge Li, Member, IEEE,"
69ff40fd5ce7c3e6db95a2b63d763edd8db3a102,Human Age Estimation via Geometric and Textural Features,"HUMAN AGE ESTIMATION VIA GEOMETRIC AND TEXTURAL FEATURES Merve KILINC1 and Yusuf Sinan AKGUL2 @@ -1793,6 +5791,34 @@ GIT Vision Lab, http://vision.gyte.edu.tr/, Department of Computer Engineering, Kocaeli, Turkey Keywords: Age estimation:age classification:geometric features:LBP:Gabor:LGBP:cross ratio:FGNET:MORPH"
+6900bb437679dd0b0c5cea0acdaa9429d0127d38,Self-Erasing Network for Integral Object Attention,"Self-Erasing Network for Integral Object Attention +Qibin Hou +Peng-Tao Jiang +Colledge of Computer Science, Nankai University +Yunchao Wei +Urbana-Champaign, IL, USA +Colledge of Computer Science, Nankai University +Ming-Ming Cheng ∗"
+69447482c6d7d0fde4001231ca84c31f866a2d5d,Survey of Advanced Facial Feature Tracking and Facial Expression Recognition,"ISSN (Print) : 2319-5940 +ISSN (Online) : 2278-1021 +International Journal of Advanced Research in Computer and Communication Engineering +Vol. 2, Issue 10, October 2013 +Survey of Advanced Facial Feature Tracking and +Facial Expression Recognition +Karthick.K1, J.Jasmine2 +PG Scholar, Department of Computer science and Technology, Kalaignar Karunanidhi Institute of Technology, +Coimbatore, Tamilnadu, India1 +Assistant Professor, Department of Computer science and Technology, Kalaignar Karunanidhi Institute of Technology, +Coimbatore, Tamilnadu, India2"
+6957baa0db5576997aef9de43b93fe8fd4d07632,Identifica\c{c}\~ao autom\'atica de picha\c{c}\~ao a partir de imagens urbanas,"Identificac¸˜ao autom´atica de pichac¸˜ao a partir de +imagens urbanas +Eric K. Tokuda and Roberto M. Cesar-Jr. +Institute of Mathematics and Statistics +University of S˜ao Paulo (USP) +Brazil +Claudio Silva +Tandon School of Engineering +New York University (NYU)"
69a55c30c085ad1b72dd2789b3f699b2f4d3169f,Automatic Happiness Strength Analysis of a Group of People using Facial Expressions,"International Journal of Computer Trends and Technology (IJCTT) – Volume 34 Number 3 - April 2016 Automatic Happiness Strength Analysis of a Group of People using Facial Expressions @@ -1800,6 +5826,39 @@ Sagiri Prasanthi#1, Maddali M.V.M. Kumar*2, #1PG Student, #2Assistant Professor #1, #2Department of MCA, St. Ann’s College of Engineering & Technology, Andhra Pradesh, India is a collective concern"
+695e4c975740d2aedcfc42d7ec445b4b2b56cbeb,Principal Component Analysis: An Efficient Facial Feature Extraction Technique,"SSRG International Journal of Electronics and Communication Engineering - (ICRTESTM) - Special Issue – April 2017 +Principal Component Analysis: An Efficient +Facial Feature Extraction Technique +Research scholar, ECE Dept, JJTU, Rajasthan, India, 333001(Associate Professor, SVIT, Secunderabad-500 +Drakshayani Desai, 2Dr. Ramakrishna Seemakurti. +Research Guide (Pricipal,, SVIT, Secunderabd, India, 500003) (Approved Research Guide, JJTU, Jhunjhunu- +33001, Rajasthan, India)"
+69aef3ce50967a00c568849fed630c573f6cd1eb,3-D Face Analysis and Identification Based on Statistical Shape Modelling,"-D Face Analysis and Identification Based on Statistical Shape +Modelling +Wei Quan*, Charlie Frowd † +*School of Computing, Engineering and Physical Sciences +University of Central Lancashire, Preston PR1 2HE, UK. +Department of Psychology +University of Winchester, Winchester SO22 4NR, UK. +Keywords: shape modelling, face analysis, identification."
+69d9b79757d76b73ed940754f4d05288b76eb8c3,Preschool Externalizing Behavior Predicts Gender-Specific Variation in Adolescent Neural Structure,"RESEARCH ARTICLE +Preschool Externalizing Behavior Predicts +Gender-Specific Variation in Adolescent +Neural Structure +Jessica Z. K. Caldwell1*¤, Jeffrey M. Armstrong2, Jamie L. Hanson1, Matthew J. Sutterer1, +Diane E. Stodola1, Michael Koenigs2, Ned H. Kalin2, Marilyn J. Essex2☯, Richard +J. Davidson1,2,3☯ +Department of Psychology, University of Wisconsin–Madison, Madison, Wisconsin, United States of +America, 2 Department of Psychiatry, University of Wisconsin–Madison, Madison, Wisconsin, United States +of America, 3 Center for Investigating Healthy Minds, University of Wisconsin–Madison, Madison, +Wisconsin, United States of America +☯ These authors contributed equally to this work. +¤. Current address: Marquette General Hospital/Michigan State University, Marquette, MI, United States of +America"
+6953911c6756ca70de1555df14a06f13305e1926,Author Profiling based on Text and Images: Notebook for PAN at CLEF 2018,"Author Profiling based on Text and Images +Notebook for PAN at CLEF 2018 +Luka Stout, Robert Musters, and Chris Pool +Anchormen, The Netherlands"
69526cdf6abbfc4bcd39616acde544568326d856,Face Verification Using Template Matching,"[17] B. Moghaddam, T. Jebara, and A. Pentland, “Bayesian face recogni- tion,” Pattern Recognit., vol. 33, no. 11, pp. 1771–1782, Nov. 2000. [18] A. Nefian, “A hidden Markov model-based approach for face detection @@ -1820,6 +5879,45 @@ tion: A literature survey,” ACM Comput. Surveys, vol. 35, no. 44, pp. [24] W. Zhao, R. Chellappa, and P. J. Phillips, “Subspace linear discrimi- nant analysis for face recognition,” UMD TR4009, 1999. Face Verification Using Template Matching"
+6971bdac5119c4cc1b6d92adac605e13f1bcd80f,Limiting the reconstruction capability of generative neural network using negative learning,"LIMITING THE RECONSTRUCTION CAPABILITY OF GENERATIVE NEURAL NETWORK +USING NEGATIVE LEARNING +Asim Munawar, Phongtharin Vinayavekhin and Giovanni De Magistris +IBM Research - Tokyo"
+69dc87575b56ba7f60fa24bdd4fceabeeaf39a80,Decoding of nonverbal language in alcoholism: A perception or a labeling problem?,"tapraid5/ze6-adb/ze6-adb/ze600216/ze62965d15z +xppws S⫽1 +/8/16 +6:36 Art: 2015-0668 +APA NLM +Psychology of Addictive Behaviors +016, Vol. 30, No. 2, 175–183 +0893-164X/16/$12.00 +© 2016 American Psychological Association +http://dx.doi.org/10.1037/adb0000147 +Decoding of Nonverbal Language in Alcoholism: +A Perception or a Labeling Problem? +Université Libre de Bruxelles and Centre Hospitalier +Charles Kornreich +Universitaire Brugmann +Géraldine Petit and Heidi Rolin +Université Libre de Bruxelles +Elsa Ermer +University of Maryland Baltimore +Salvatore Campanella and Paul Verbanck"
+69ee78388e0f40941496ab92efe3e0fa065ad22e,Person Re-Identification with RGB-D Camera in Top-View Configuration through Multiple Nearest Neighbor Classifiers and Neighborhood Component Features Selection,"Article +Person Re-Identification with RGB-D Camera in +Top-View Configuration through Multiple Nearest +Neighbor Classifiers and Neighborhood Component +Features Selection +Marina Paolanti * +Emanuele Frontoni +, Luca Romeo, Daniele Liciotti +, Rocco Pietrini, Annalisa Cenci, +nd Primo Zingaretti +Department of Information Engineering, Universitá Politecnica delle Marche, I-60131 Ancona, Italy; +(L.R.); (D.L.); (R.P.); +(A.C.); (E.F.); (P.Z.) +* Correspondence: +Received: 30 August 2018 ; Accepted: 11 October 2018 ; Published: 15 October 2018"
690d669115ad6fabd53e0562de95e35f1078dfbb,"Progressive versus Random Projections for Compressive Capture of Images, Lightfields and Higher Dimensional Visual Signals","Progressive versus Random Projections for Compressive Capture of Images, Lightfields and Higher Dimensional Visual Signals Rohit Pandharkar @@ -1830,11 +5928,111 @@ Ashok Veeraraghavan Ramesh Raskar MIT Media Lab 75 Amherst St, Cambridge, MA"
+695f6dc7165aa3fca15d1b1deb4c496fc093ac19,Learning Discriminative Visual N-grams from Mid-level Image Features,"GUPTA, PANDEY, CHIA: VISUAL N-GRAMS +Learning Discriminative Visual N-grams +from Mid-level Image Features +Raj Kumar Gupta +Megha Pandey +Alex YS Chia +Institute of High Performance +Computing (A*STAR) +Singapore +Institute of Infocomm Research +(A*STAR) +Singapore +Rakuten Institute of Technology +Singapore"
+698812f7d37e148c0a99e768f0a7d24e7b9605ab,Image Classification and Retrieval from User-Supplied Tags,"Image Classification and Retrieval from User-Supplied Tags +Hamid Izadinia +Univ. of Washington +Ali Farhadi +Univ. of Washington +Aaron Hertzmann +Adobe Research +Matthew D. Hoffman +Adobe Research"
+699b6cbd72ee0274699b939863813499c377ea00,Enlightening Deep Neural Networks with Knowledge of Confounding Factors,"Enlightening Deep Neural Networks +with Knowledge of Confounding Factors +Yu Zhong +Gil Ettinger +{yu.zhong, +Systems & Technology Research"
+69d1b055807ef35a8f9490775348cce899421841,An Improved ABC Algorithm Approach Using SURF for Face Identification,"An Improved ABC Algorithm Approach Using +SURF for Face Identification +Chidambaram Chidambaram1,2, Marlon Subtil Mar¸cal2, Leyza Baldo Dorini2, +Hugo Vieira Neto2, and Heitor Silv´erio Lopes2 +State University of Santa Catarina-UDESC, Brazil +Federal University of Technology - Paran´a - UTFPR, Brazil +http://www.sbs.udesc.br +http://www.utfpr.edu.br"
+6960bfc668aad1b537fbf3f1b48328e7d440b80b,Fully Automatic Recognition of the Temporal Phases of Facial Actions,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 1, FEBRUARY 2012 +Fully Automatic Recognition of the +Temporal Phases of Facial Actions +Michel F. Valstar, Member, IEEE, and Maja Pantic, Senior Member, IEEE"
69063f7e0a60ad6ce16a877bc8f11b59e5f7348e,Class-Specific Image Deblurring,"Class-Specific Image Deblurring Saeed Anwar1, Cong Phuoc Huynh1 , Fatih Porikli1 The Australian National University∗ Canberra ACT 2601, Australia NICTA, Locked Bag 8001, Canberra ACT 2601, Australia"
+691eb8eb9f5d5fbf5d76349098b78e5d6fc25ccc,Deep Learning of Part-Based Representation of Data Using Sparse Autoencoders With Nonnegativity Constraints,"Deep Learning of Part-based Representation of Data +Using Sparse Autoencoders with Nonnegativity +Constraints +Ehsan Hosseini-Asl, Member, IEEE, Jacek M. Zurada, Life Fellow, IEEE, Olfa Nasraoui, Senior Member, IEEE"
+69f27ca2f1280587004c8fae6b3b0021305e52eb,Title of dissertation : Scene and Video Understanding,
+695b040a9550a46b5ffe31e4a6abbadfac02c1ad,Face recognition with illumination distinction description,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-1-6 ©2012 IAPR"
+69f49bae5b1c15adc644b47e6c3b6c3f7aa84171,Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers,"Variational Bayesian Inference for Audio-Visual +Tracking of Multiple Speakers +Yutong Ban, Xavier Alameda-Pineda, Laurent Girin and Radu Horaud"
+692aecba13add2b8c1d82db303f5b2ec743ceb44,FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces,"FaceForensics: A Large-scale Video Dataset for Forgery +Detection in Human Faces +Andreas R¨ossler1 Davide Cozzolino2 Luisa Verdoliva2 Christian Riess3 +Justus Thies1 +Matthias Nießner1 +Technical University of Munich +University Federico II of Naples +University of Erlangen-Nuremberg"
+6997039127d9b262d4a9aa9467c4f4fa3d596085,Classification of Vehicle Types in Car Parks using Computer Vision Techniques,"Classification of Vehicle Types in Car Parks using +Computer Vision Techniques +Chadly Marouane +Research & Development +VIRALITY GmbH +Rauchstraße 7 +81679 Munich, Germany +Lorenz Schauer +Ludwig-Maximilians- +Universität +München +Philipp Bauer +Ludwig-Maximilians- +Universität +München +Oettingenstraße 67 +80538 München, Germany +Oettingenstraße 67 +80538 München, Germany"
+6946acb595095407871992da62298254658f8d84,An Efficient Method for Face Recognition System In Various Assorted Conditions,"An Efficient Method for Face Recognition System +In Various Assorted Conditions +V.Karthikeyan +K.Vijayalakshmi +P.Jeyakumar +finding"
+69a605b2ef38c59e0c8da284d6f27d33e3573620,Automated Multi - Modal Search and Rescue Using Boosted Histogram of Oriented Gradients,"AUTOMATED MULTI-MODAL SEARCH AND RESCUE USING BOOSTED +HISTOGRAM OF ORIENTED GRADIENTS +A Thesis +presented to +the Faculty of California Polytechnic State University, +San Luis Obispo +In Partial Fulfillment +of the Requirements for the Degree +Master of Science in Electrical Engineering +Matthew Lienemann +December 2015"
+3c3eb65a936296d6ae5058b564f6d0e0c07772cf,A metric for sets of trajectories that is practical and mathematically consistent,"A metric for sets of trajectories that is +practical and mathematically consistent +Jos´e Bento +Jia Jie Zhu"
3cb2841302af1fb9656f144abc79d4f3d0b27380,When 3 D-Aided 2 D Face Recognition Meets Deep Learning : An extended UR 2 D for Pose-Invariant Face Recognition,"See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/319928941 When 3D-Aided 2D Face Recognition Meets Deep Learning: An extended UR2D for Pose-Invariant @@ -1875,12 +6073,139 @@ image analysis tools and evaluation methods to compare and validate analysis too microbiological structures whose scales range from a subcellular level (nm) to a tissue level (µm), inheriting intrinsic challenges in the domain of biomedical image analysis (Fig. 1). The dataset is acquired through two of the main microscopic imaging techniques: transmitted light microscopy and confocal laser scanning microscopy. The analysis tools1in the benchmark are"
+3cec488a0910b69f50811cebe8c655dca22078d5,Evidence Extraction for Machine Reading Comprehension with Deep Probabilistic Logic,"Confidential TACL submission. DO NOT DISTRIBUTE. +Evidence Extraction for Machine Reading Comprehension +with Deep Probabilistic Logic +Anonymous TACL submission"
+3c1c8e171450a9b279df939d4c9209d8dbf6b2fe,Large scale mining and retrieval of visual data in a multimodal context,"Diss. ETH No. 18190 +Large-Scale Mining and Retrieval of Visual Data in +Multimodal Context +A dissertation submitted to the +SWISS FEDERAL INSTITUTE OF TECHNOLOGY ZURICH +for the degree of +Doctor of Technical Sciences +presented by +Till Quack +MSc. ETH Zuerich +orn 15. September 1978 +itizen of Germany +ccepted on the recommendation of +Prof. Dr. Luc Van Gool, examiner +Prof. Dr. Andrew Zisserman, co-examiner +September 2008"
3cfbe1f100619a932ba7e2f068cd4c41505c9f58,A Realistic Simulation Tool for Testing Face Recognition Systems under Real-World Conditions,"A Realistic Simulation Tool for Testing Face Recognition Systems under Real-World Conditions∗ M. Correa, J. Ruiz-del-Solar, S. Parra-Tsunekawa, R. Verschae Department of Electrical Engineering, Universidad de Chile Advanced Mining Technology Center, Universidad de Chile"
+3caebf3075e52483c7a7179b3491882af0aaaa37,Lateralization of Cognitive Functions: The Visual Half-Field Task Revisited,"Lateralization of Cognitive Functions: The Visual Half-Field +Task Revisited +Ark Verma +Promotor: Prof. Dr. Marc Brysbaert +Proefschrift ingediend tot het behalen van de academische graad +van Doctor in de Psychologie"
+3ca983d40b9de7dc12b989fce213b4abee652c9e,Will the Pedestrian Cross? A Study on Pedestrian Path Prediction,"Will the Pedestrian Cross? +A Study on Pedestrian Path Prediction +Christoph G. Keller and Dariu M. Gavrila"
+3caf02979d7cd83d2f3894574c86babf3e201bf3,Seeing to hear? Patterns of gaze to speaking faces in children with autism spectrum disorders,"ORIGINAL RESEARCH ARTICLE +published: 08 May 2014 +doi: 10.3389/fpsyg.2014.00397 +Seeing to hear? Patterns of gaze to speaking faces in +hildren with autism spectrum disorders +Julia R. Irwin1,2* and Lawrence Brancazio1,2 +Haskins Laboratories, New Haven, CT, USA +Department of Psychology, Southern Connecticut State University, New Haven, CT, USA +Edited by: +Jean-Luc Schwartz, National Centre +for Scientific Research, France +Reviewed by: +Satu Saalasti, Brain and Mind +Laboratory, Aalto University School of +Science, Finland +David House, Royal Institute of +Technology, Sweden +*Correspondence: +Julia R. Irwin, Haskins Laboratories, +00 George Street, New Haven,"
3cd7b15f5647e650db66fbe2ce1852e00c05b2e4,"ACTIVE, an Extensible Cataloging Platform for Automatic Indexing of Audiovisual Content",
+3ceef6572b00bef961c0246a220edcc48553ed2d,Descriptor Learning for Omnidirectional Image Matching,"Descriptor learning for omnidirectional image matching +Jonathan Masci1,2,3 +Davide Migliore1,4 +Michael M. Bronstein2 +J¨urgen Schmidhuber1,2,3 +Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Manno, Switzerland +Faculty of Informatics, Universit`a della Svizzera Italiana (USI), Lugano, Switzerland +Scuola Universitaria Professionale della Svizzera Italiana (SUPSI), Lugano, Switzerland +Evidence Srl, Pisa, Italy"
+3c70360a4ba30b860d337308633842acbb908ee4,Multi-aspect object detection with Boosted Hough Forest,"REDONDO-CABRERA ET AL.: OBJECT DETECTION WITH BOOSTED HOUGH FOREST +Because better detections are still possible: +Multi-aspect Object Detection with Boosted +Hough Forest +Carolina Redondo-Cabrera +Roberto López-Sastre +University of Alcalá +Alcalá de Henares, ES"
+3c5f390f99272c59fcf822ab78c90ee6bfa7926a,iCub : Learning Emotion Expressions using Human Reward,"iCub: Learning Emotion Expressions using Human Reward +Nikhil Churamani, Francisco Cruz, Sascha Griffiths and Pablo Barros"
+3c77e4ce48d1bbcdb682cdc790806e2d5f2d2e1a,Recognition of Genuine Smiles,"Recognition of Genuine Smiles +Hamdi Dibeklioğlu, Member, IEEE, Albert Ali Salah, Member, IEEE, and Theo Gevers, Member, IEEE"
+3ca4ce8ab704b44701bf7ef8dda01c8dbb226fac,On-the-fly hand detection training with application in egocentric action recognition,"On-the-Fly Hand Detection Training with Application in Egocentric Action +Recognition +Jayant Kumar∗, Qun Li∗, Survi Kyal, Edgar A. Bernal, and Raja Bala +{Jayant.Kumar, Qun.Li, Survi.Kyal, Edgar.Bernal, +PARC, A Xerox Company +800 Phillips Road, Webster, NY 14580"
+3c917f071bfc1244c75fca3ceed0a8c46bb975cc,Reduced acetylcholinesterase activity in the fusiform gyrus in adults with autism spectrum disorders.,"ORIGINAL ARTICLE +Reduced Acetylcholinesterase Activity +in the Fusiform Gyrus in Adults With Autism +Spectrum Disorders +Katsuaki Suzuki, MD, PhD; Genichi Sugihara, MD, PhD; Yasuomi Ouchi, MD, PhD; Kazuhiko Nakamura, MD, PhD; +Masatsugu Tsujii, MA; Masami Futatsubashi, BS; Yasuhide Iwata, MD, PhD; Kenji J. Tsuchiya, MD, PhD; +Kaori Matsumoto, MA; Kiyokazu Takebayashi, MD, PhD; Tomoyasu Wakuda, MD, PhD; Yujiro Yoshihara, MD, PhD; +Shiro Suda, MD, PhD; Mitsuru Kikuchi, MD, PhD; Nori Takei, MD, PhD, MSc; Toshirou Sugiyama, MD, PhD; +Toshiaki Irie, PhD; Norio Mori, MD, PhD +Context: Both neuropsychological and functional mag- +netic resonance imaging studies have shown deficien- +ies in face perception in subjects with autism spectrum +disorders (ASD). The fusiform gyrus has been regarded +s the key structure in face perception. The cholinergic +system is known to regulate the function of the visual +pathway, including the fusiform gyrus. +Objectives: To determine whether central acetylcho- +linesterase activity, a marker for the cholinergic system, +is altered in ASD and whether the alteration in acetyl- +holinesterase activity, if any, is correlated with their so-"
+3c9ad25e91cace6ac93069480745d4578b7f29f5,Automatic Article Commenting: the Task and Dataset,"Automatic Article Commenting: the Task and Dataset +Lianhui Qin1∗, Lemao Liu2, Victoria Bi2, Yan Wang2, +Xiaojiang Liu2, Zhiting Hu, Hai Zhao1, Shuming Shi2 +Department of Computer Science and Engineering, Shanghai Jiao Tong University1, Tencent AI Lab2,"
+3ce8a74b47f81ec66046f2486afa1a89e3165dfd,LSH banding for large-scale retrieval with memory and recall constraints,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE +ICASSP 2009"
+3cb8128b41b419a1fdc7a95bf8e65a37aff79676,Shifting the Baseline: Single Modality Performance on Visual Navigation&QA,"Single Modality Performance on Visual Navigation & QA +Shifting the Baseline: +Jesse Thomason +Yonatan Bisk +Paul G. Allen School of Computer Science and Engineering +Daniel Gordan"
+3c2819dae899559f1c61b3b34aeb5d41a6398440,A Stable and Invariant Three-polar Surface Representation: Application to 3D Face Description,"A Stable and Invariant Three-polar Surface Representation: +Application to 3D Face Description +Majdi Jribi +Faouzi Ghorbel +CRISTAL Laboratory, +GRIFT research group +ENSI,La Manouba +University +010, La manouba, +Tunisia +CRISTAL Laboratory, +GRIFT research group +ENSI,La Manouba +University +010, La manouba, +Tunisia"
+3c793fa4d7f673f1e9f6799729ec266ce573ec60,Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification,"Margin Sample Mining Loss: A Deep Learning Based Method for Person +Re-identification +Qiqi Xiao , Hao Luo , Chi Zhang"
3c374cb8e730b64dacb9fbf6eb67f5987c7de3c8,Measuring Gaze Orientation for Human-Robot Interaction,"Measuring Gaze Orientation for Human-Robot Interaction R. Brochard∗, B. Burger∗, A. Herbulot∗†, F. Lerasle∗† @@ -1915,6 +6240,48 @@ Sharat Pankanti, Arun Hampapur, Andrew Senior, Ruud Bolle IBM T.J. Watson Research Center 9 Skyline Drive, Hawthorne, NY 10532 USA { yltian,lisabr,jconnell,sharat,arunh,aws,bolle"
+3cc0d9c1f690addd2c82e60f2a460e3c557ff242,Sort Story: Sorting Jumbled Images and Captions into Stories,"Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 925–931, +Austin, Texas, November 1-5, 2016. c(cid:13)2016 Association for Computational Linguistics"
+3c0420a0dd90d0900613ac1f1a1174b626df26d9,Learning Discriminative Chamfer Regularization,"YARLAGADDA ∗, EIGENSTETTER ∗, OMMER: CHAMFER REGULARIZATION +Learning Discriminative Chamfer +Regularization +Pradeep Yarlagadda ∗ +Angela Eigenstetter ∗ +Björn Ommer +Interdisciplinary Center for Scientific +Computing (IWR) +University of Heidelberg +Germany"
+3c68763caa67dee55bca76f0f71dd4530f3fd57c,Ranking to Learn and Learning to Rank: On the Role of Ranking in Pattern Recognition Applications,"Ranking to Learn and Learning to Rank: +On the Role of Ranking in Pattern Recognition Applications +Giorgio Roffo +Submitted to the Department of Computer Science +in partial fulfillment of the requirements for the degree of +European Doctor of Philosophy +S.S.D. ING-INF05 +Cycle XXIX/2014 +t the +Universit`a degli Studi di Verona +May 2017 +(cid:13) Universit`a degli Studi di Verona 2017. All rights reserved. +Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . +Department of Computer Science +May 25, 2017 +Certified by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . +Prof. Marco Cristani +Associate Professor +Thesis Tutor +Accepted by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ."
+3c49dafc82ee24e70e338b896868cd9f82f0edd7,Biologically Motivated 3 D Face Recognition,"BIOLOGICALLY MOTIVATED 3D FACE RECOGNITION +Albert Ali Salah +B.S, in Computer Engineering, Bo˘gazi¸ci University, 1998 +M.S, in Computer Engineering, Bo˘gazi¸ci University, 2000 +Submitted to the Institute for Graduate Studies in +Science and Engineering in partial fulfillment of +the requirements for the degree of +Doctor of Philosophy +Graduate Program in +Bo˘gazi¸ci University"
3c56acaa819f4e2263638b67cea1ec37a226691d,Body Joint Guided 3-D Deep Convolutional Descriptors for Action Recognition,"Body Joint guided 3D Deep Convolutional Descriptors for Action Recognition Congqi Cao, Yifan Zhang, Member, IEEE, Chunjie Zhang, Member, IEEE, and Hanqing Lu, Senior Member, IEEE"
@@ -1938,6 +6305,27 @@ Face recognition capabilities of humans have inspired several researchers to und the science behind it and use it in developing automated algorithms. Recently, it is also rgued that encoding social context among individuals can be leveraged for improved utomatic face recognition [175]. As shown in Figure 4.1, often times a person’s identity"
+3ca1e06dfbaeed0f8dc49bf345369fb8e43da53d,Cross-View Asymmetric Metric Learning for Unsupervised Person Re-Identification,"Cross-view Asymmetric Metric Learning for +Unsupervised Person Re-identification +Hong-Xing Yu, Ancong Wu, Wei-Shi Zheng +Code is available at the project page: +https://github.com/KovenYu/CAMEL +For reference of this work, please cite: +Hong-Xing Yu, Ancong Wu, Wei-Shi Zheng. “Cross-view Asymmetric +Metric Learning for Unsupervised Person Re-identification.” Proceedings +of the IEEE International Conference on Computer Vision. 2017. +title={Cross-view Asymmetric Metric Learning for Unsupervised Person +Re-identification}, +uthor={Yu, Hong-Xing and Wu, Ancong and Zheng, Wei-Shi}, +ooktitle={Proceedings of the IEEE International Conference on Computer +Vision}, +year={2017}"
+56e95fa26fb417776824e5adf6d6d511e5b30110,Object and Action Classification with Latent Window Parameters,"Int J Comput Vis +DOI 10.1007/s11263-013-0646-8 +Object and Action Classification with Latent Window Parameters +Hakan Bilen · Vinay P. Namboodiri · Luc J. Van Gool +Received: 1 October 2012 / Accepted: 18 July 2013 +© Springer Science+Business Media New York 2013"
56e4dead93a63490e6c8402a3c7adc493c230da5,Face Recognition Techniques: A Survey,"World Journal of Computer Application and Technology 1(2): 41-50, 2013 DOI: 10.13189/wjcat.2013.010204 http://www.hrpub.org @@ -1946,10 +6334,89 @@ V.Vijayakumari Department of Electronics and Communication, Sri krishna College of Technology, Coimbatore, India *Corresponding Author: Copyright © 2013 Horizon Research Publishing All rights reserved."
+56b9c6efe0322f0087d2f82b52129cc6b41ab356,"Acquire, Augment, Segment & Enjoy: Weakly Supervised Instance Segmentation of Supermarket Products","Acquire, Augment, Segment & Enjoy: +Weakly Supervised Instance Segmentation of +Supermarket Products +Patrick Follmann+*, Bertram Drost+, and Tobias B¨ottger+* ++MVTec Software GmbH, Munich, Germany +Technical University of Munich (TUM) +July 9, 2018"
+56bc524d7cc1ff2fad8f27c0414cac437fc2b4f0,Protest Activity Detection and Perceived Violence Estimation from Social Media Images,"To appear in Proceedings of the 25th ACM International Conference on Multimedia 2017 +Protest Activity Detection and Perceived Violence Estimation +from Social Media Images +Donghyeon Won +Zachary C. Steinert-Threlkeld +Jungseock Joo"
56e885b9094391f7d55023a71a09822b38b26447,Face Retrieval using Frequency Decoded Local Descriptor,"FREQUENCY DECODED LOCAL BINARY PATTERN Face Retrieval using Frequency Decoded Local Descriptor Shiv Ram Dubey, Member, IEEE"
+568727a76dc1242e3d48392f9c19678a27c63482,High Entropy Ensembles for Holistic Figure-ground Segmentation,"GALLO et al.: HEE FOR HOLISTIC FIGURE-GROUND SEGMENTATION +High Entropy Ensembles for Holistic +Figure-ground Segmentation +Ignazio Gallo +Alessandro Zamberletti +Simone Albertini +Lucia Noce +Applied Recognition Technology +Laboratory +Department of Theoretical and Applied +Science +University of Insubria +Varese, Italy"
+56d4eeb7fcdfd4f3156b9bdd20a9f35c995ebcac,Local Similarity Based Linear Discriminant Analysis for Face Recognition with Single Sample per Person,"Local Similarity based Linear Discriminant +Analysis for Face Recognition with Single +Sample per Person +Fan Liu1, Ye Bi1, Yan Cui2, Zhenmin Tang1 +School of Computer Science and Engineering, Nanjing University of Science and +Key Laboratory of Broadband Wireless Communication and Sensor Network +Technology, Nanjing University of Posts and Telecommunications, China +Technology, China"
+56fcc0ef7c10ff322626fec29f532af1860ff2f7,Occlusion and Abandoned Object Detection for Surveillance Applications,"International Journal of Computer Applications Technology and Research +Volume 2– Issue 6, 708 - 713, 2013, ISSN: 2319–8656 +Occlusion and Abandoned Object Detection for +Surveillance Applications +M. Chitra +RVS college of Engineering +nd Technology +Karaikal, India +M.Kalaiselvi Geetha +Annamalai University +Chidambaram, India +L.Menaka +RVS college of Engineering +nd Technology +Karaikal, India +is challenging and"
+568067d7232c753e182dbc1d7075364560ffc363,Scope of physiological and behavioural pain assessment techniques in children – a review,"Scope of physiological and behavioural pain assessment techniques +in children – a review +Saranya Devi Subramaniam1, Brindha Doss1 ✉, Lakshmi Deepika Chanderasekar2, Aswini Madhavan1, +Antony Merlin Rosary2 +Department of Biomedical Engineering, PSG College of Technology, Coimbatore 641004, India +Department of Electronics & Communication Engineering, PSG College of Technology, Coimbatore, 641004, India +✉ E-mail: +Published in Healthcare Technology Letters; Received on 7th February 2018; Accepted on 10th May 2018 +Pain is an unpleasant subjective experience. At present, clinicians are using self-report or pain scales to recognise and monitor pain in children. +However, these techniques are not efficient to observe the pain in children having cognitive disorder and also require highly skilled observers +to measure pain. Using these techniques it is also difficult to choose the analgesic drug dosages to the patients after surgery. Thus, this +onceptual work explains the demand for automatic coding techniques to evaluate pain and also it documents some evidence of +techniques that act as an alternative approach for objectively determining pain in children. In this review, some good indicators of pain in +hildren are explained in detail; they are facial expressions from an RGB image, thermal image and also feature from well proven +physiological signals such as electrocardiogram, skin conductance, body temperature, surgical pleth index, pupillary reflex dilation, +nalgesia nociception index, photoplethysmography, perfusion index etc. +. Introduction: The children will encounter pain resulting from +injuries, disease, after surgery and other health problems. The +‘International Association for the Study of Pain (IASP)’, an +interdisciplinary organisation created in 1973 to study pain and"
+564babec16b895d385d06d38545febd66ef02f35,Robust Statistics for Feature-based Active Appearance Models,
+562f35a662545d839876deeb605ca2c864507a82,Revealing Variations in Perception of Mental States from Dynamic Facial Expressions: A Cautionary Note,"Revealing Variations in Perception of Mental States from +Dynamic Facial Expressions: A Cautionary Note +Elisa Back1*, Timothy R. Jordan2 +Department of Psychology, Kingston University London, Kingston upon Thames, United Kingdom, 2 Department of Psychology, Zayed University, Dubai, United Arab +Emirates"
+564d4ee76c0511bc395dfc8ef8e3b3867fc34a6d,Robust group sparse representation via half-quadratic optimization for face recognition,"Robust Group Sparse Representation via Half-Quadratic Optimization +for Face Recognition +Yong Peng and Bao-Liang Lu(cid:3), Senior Member, IEEE"
56a653fea5c2a7e45246613049fb16b1d204fc96,Quaternion Collaborative and Sparse Representation With Application to Color Face Recognition,"Quaternion Collaborative and Sparse Representation With Application to Color Face Recognition Cuiming Zou, Kit Ian Kou, Member, IEEE, and Yulong Wang, Student Member, IEEE @@ -1963,19 +6430,117 @@ Relatively-Paired Space Analysis: Learning a Latent Common Space from Relatively-Paired Observations Zhanghui Kuang · Kwan-Yee K. Wong Received: date / Accepted: date"
+564555b7fdc45938d813650de7a7b1cd40005aa8,Implementation of SIFT In Various Applications,"International Journal of Engineering Research and Development +e-ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com +Volume 7, Issue 4 (May 2013), PP. 59-64 +Implementation of SIFT In Various Applications +,2,3Deen Bandhu Chotu Ram University of Science and Technology Murthal, Haryana, India. +Ritu Rani1, S. K. Grewal 2, Indiwar 3"
5615d6045301ecbc5be35e46cab711f676aadf3a,Discriminatively Learned Hierarchical Rank Pooling Networks,"Discriminatively Learned Hierarchical Rank Pooling Networks Basura Fernando · Stephen Gould Received: date / Accepted: date"
+56cf859363f1b5231418b40b957a9132a78ea546,VLASE: Vehicle Localization by Aggregating Semantic Edges,"VLASE: Vehicle Localization by Aggregating Semantic Edges +Xin Yu1∗, Sagar Chaturvedi1∗, Chen Feng2, Yuichi Taguchi2, Teng-Yok Lee2, Clinton Fernandes1, Srikumar Ramalingam1"
+56f5a94047966eac4b2f97ded4b50513f9a09951,Is the Kidney Donor Risk Index a Useful Tool in Non-US Patients?,"791148 CJKXXX10.1177/2054358118791148Canadian Journal of Kidney Health and DiseaseYoung et al +research-article20182018 +Original Research Article +Is the Kidney Donor Risk Index a +Useful Tool in Non-US Patients? +Ann Young1, Greg A. Knoll2,3, Eric McArthur2, +Stephanie N. Dixon2,4, Amit X. Garg2,5, +Charmaine E. Lok1,2,6, Ngan N. Lam7, and S. Joseph Kim1,2,6,8 +Canadian Journal of Kidney Health +nd Disease +Volume 5: 1 –10 +© The Author(s) 2018 +Reprints and permissions: +sagepub.com/journals-permissions +DOI: 10.1177/2054358118791148 +https://doi.org/10.1177/2054358118791148 +journals.sagepub.com/home/cjk"
+56852a56dd830a6ee3882773c453025ddec652e2,Emotion recognition through static faces and moving bodies: a comparison between typically developed adults and individuals with high level of autistic traits,"ORIGINAL RESEARCH +published: 23 October 2015 +doi: 10.3389/fpsyg.2015.01570 +Emotion recognition through static +faces and moving bodies: a +omparison between typically +developed adults and individuals +with high level of autistic traits† +Rossana Actis-Grosso1,2*, Francesco Bossi1 and Paola Ricciardelli1,2 +Department of Psychology, University of Milano-Bicocca, Milano, Italy, 2 Milan Centre for Neuroscience, Milano, Italy +We investigated whether the type of stimulus (pictures of static faces vs. body motion) +ontributes differently to the recognition of emotions. The performance (accuracy and +response times) of 25 Low Autistic Traits (LAT group) young adults (21 males) and 20 +young adults (16 males) with either High Autistic Traits or with High Functioning Autism +Spectrum Disorder (HAT group) was compared in the recognition of four emotions +(Happiness, Anger, Fear, and Sadness) either shown in static faces or conveyed by +moving body patch-light displays (PLDs). Overall, HAT individuals were as accurate as +LAT ones in perceiving emotions both with faces and with PLDs. Moreover, they correctly +described non-emotional actions depicted by PLDs, indicating that they perceived the +motion conveyed by the PLDs per se. For LAT participants, happiness proved to be"
+56a0ead811a1bf15e42be8a9a007b0299636f213,Talk the Walk: Navigating New York City through Grounded Dialogue,"Talk the Walk: Navigating New York City through +Grounded Dialogue +Harm de Vries1, Kurt Shuster3, Dhruv Batra3,2, Devi Parikh3,2, Jason Weston3 & Douwe Kiela3 +MILA, Université de Montréal; 2Georgia Institute of Technology; 3Facebook AI Research"
566038a3c2867894a08125efe41ef0a40824a090,Face recognition and gender classification in personal memories,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE ICASSP 2009"
56dca23481de9119aa21f9044efd7db09f618704,Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices,"Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices Anoop Cherian Suvrit Sra"
+560447750f45ea18cb21f202e30344c4fe12c52e,Removal Of Blurred And Illuminated Face Image With Different Poses,"International Journal of Scientific & Engineering Research, Volume 5, Issue 3, March-2014 33 +ISSN 2229-5518 +Removal Of Blurred And Illuminated +Face Image With Different Poses +C.Indhumathi, C.Dhanamani"
+56c5d08103c5bf4b263a81da73135455136bbe6d,Kernel MBPLS for a Scalable and Multi-Camera Person Re-Identification System,"Kernel MBPLS for a Scalable and Multi-Camera Person +Re-Identification System +Raphael Pratesa,*, William Robson Schwartza +Smart Surveillance Interest Group, Computer Science Department, Universidade Federal de Minas Gerais, Minas +Gerais, Brazil +Person re-identification aims at establishing global identities for individuals as they move +cross a camera network. +It is a challenging task due to the drastic appearance changes that +occur between cameras as consequence of different pose and illumination conditions. Pairwise +matching models yield state-of-the-art results in most of the person re-identification datasets by +apturing nuances that are robust and discriminative for a specific pair of cameras. Nonetheless, +pairwise models are not scalable with the number of surveillance cameras. Therefore, elegant solu- +tions combining scalability with high matching rates are crucial for the person re-identification in +real-world scenarios. In this work, we tackle this problem proposing a multi-camera nonlinear re- +gression model called Kernel Multiblock Partial Least Squares (Kernel MBPLS), a single subspace +model for the entire camera network that uses all the labeled information. In this subspace, probe +nd gallery individual can be successfully matched. Experimental results in three multi-camera +person re-identification datasets (WARD, RAID and SAIVT-SoftBIO) demonstrate that the Ker- +nel MBPLS presents favorable aspects such as the scalability and robustness with respect to the +number of cameras combined with the high matching rates."
+5665d98136cc39322d47cb782b8e49d141c5a29e,An Agile Framework for Real-time Visual Tracking in Videos,"REPORT DOCUMENTATION PAGE +Form Approved OMB NO. 0704-0188 +this collection of +information +is estimated +instructions, +The public reporting burden +Send comments +searching existing data sources, gathering and maintaining +to Washington +regarding +this burden estimate or any other aspect of +Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA, 22202-4302. +Headquarters Services, Directorate +Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any oenalty for failing to comply with a collection of +information if it does not display a currently valid OMB control number. +PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. +. REPORT DATE (DD-MM-YYYY) +the data needed, and completing and reviewing +this collection of"
516a27d5dd06622f872f5ef334313350745eadc3,Fine-Grained Facial Expression Analysis Using Dimensional Emotion Model,"> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < Fine-Grained Facial Expression Analysis Us- ing Dimensional Emotion Model ǂFeng Zhou, ǂShu Kong, Charless C. Fowlkes, Tao Chen, *Baiying Lei, Member, IEEE"
+513d9d0fdc9efa0f042ed1a3c8eab1fbb564f67b,Efficient Processing of Deep Neural Networks: A Tutorial and Survey,"Efficient Processing of Deep Neural Networks: +A Tutorial and Survey +Vivienne Sze, Senior Member, IEEE, Yu-Hsin Chen, Student Member, IEEE, Tien-Ju Yang, Student +Member, IEEE, Joel Emer, Fellow, IEEE"
51c3050fb509ca685de3d9ac2e965f0de1fb21cc,Fantope Regularization in Metric Learning,"Fantope Regularization in Metric Learning Marc T. Law Nicolas Thome @@ -1983,14 +6548,53 @@ Matthieu Cord Sorbonne Universit´es, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France"
51c7c5dfda47647aef2797ac3103cf0e108fdfb4,Cs 395t: Celebrity Look-alikes *,"CS 395T: Celebrity Look-Alikes ∗ Adrian Quark"
+511dda02d39dc8107ac385ea8a572970e2eb9b7b,"Face recognition using distributed, mobile computing","014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) +978-1-4799-2893-4/14/$31.00 ©2014 IEEE +Klipsch School of Electrical and Computer Engineering +Gregorio Hinojos and Phillip L. De Leon +Las Cruces, New Mexico, U.S.A. +New Mexico State University +. INTRODUCTION"
519f4eb5fe15a25a46f1a49e2632b12a3b18c94d,Non-Lambertian Reflectance Modeling and Shape Recovery of Faces Using Tensor Splines,"Non-Lambertian Reflectance Modeling and Shape Recovery of Faces using Tensor Splines Ritwik Kumar, Student Member, IEEE, Angelos Barmpoutis, Member, IEEE, Arunava Banerjee, Member, IEEE, and Baba C. Vemuri, Fellow, IEEE"
+5171157c2c09a85ad6558c5c03da6b75b0cf5fe6,Dynamic Coattention Networks For Question Answering,"Published as a conference paper at ICLR 2017 +DYNAMIC COATTENTION NETWORKS +FOR QUESTION ANSWERING +Caiming Xiong∗, Victor Zhong∗, Richard Socher +Salesforce Research +Palo Alto, CA 94301, USA +{cxiong, vzhong,"
+518439ba2895c84ba686db5b83674c440e637c0b,The Price of Fair PCA: One Extra Dimension,"The Price of Fair PCA: One Extra Dimension +Samira Samadi +Georgia Tech +Uthaipon Tantipongpipat +Georgia Tech +Jamie Morgenstern +Georgia Tech +Mohit Singh +Georgia Tech +Santosh Vempala +Georgia Tech"
+519db7bb7d1778bddfbe3725220756627373d69a,A Comparative Study of Local Matching Approach for Face Recognition,"A Comparative Study of Local Matching +Approach for Face Recognition +Jie Zou, Member, IEEE, Qiang Ji, Senior Member, IEEE, and George Nagy, Fellow, IEEE +to holistic methods,"
+516a014f4654c90a22ae3d363b6e80bda68a084d,Adaptive human-centered representation for activity recognition of multiple individuals from 3D point cloud sequences,"Adaptive Human-Centered Representation for Activity Recognition of +Multiple Individuals from 3D Point Cloud Sequences +Hao Zhang1, Christopher Reardon2, Chi Zhang2, and Lynne E. Parker2"
+51c7236feaa2ae23cef78c7bca75c69d7081e24a,Deep multi-frame face super-resolution,"Deep multi-frame face super-resolution +Evgeniya Ustinova, Victor Lempitsky +October 17, 2017"
51cc78bc719d7ff2956b645e2fb61bab59843d2b,Face and Facial Expression Recognition with an Embedded System for Human-Robot Interaction,"Face and Facial Expression Recognition with an Embedded System for Human-Robot Interaction Yang-Bok Lee1, Seung-Bin Moon1, and Yong-Guk Kim 1* School of Computer Engineering, Sejong University, Seoul, Korea"
+517cc1084952133b6d2ecd0a535cdc3ddf8955d7,A Graphical Social Topology Model for Multi-Object Tracking,"A Graphical Social Topology Model for +Multi-Object Tracking +Shan Gao, Xiaogang Chen, Qixiang Ye, Senior Member, IEEE, Arjan Kuijper, Member, IEEE, +Xiangyang Ji, Member, IEEE,"
511b06c26b0628175c66ab70dd4c1a4c0c19aee9,Face Recognition using Laplace Beltrami Operator by Optimal Linear Approximations,"International Journal of Engineering Research and General ScienceVolume 2, Issue 5, August – September 2014 ISSN 2091-2730 Face Recognition using Laplace Beltrami Operator by Optimal Linear @@ -1998,6 +6602,75 @@ Approximations Tapasya Sinsinwar1, P.K.Dwivedi2 Professor and Director Academics, Institute of Engineering and Technology, Alwar, Rajasthan Technical University, Kota(Raj.) Research Scholar (M.Tech, IT), Institute of Engineering and Technology"
+5122a5d4bdf58b4f413d4de1fb250d4ab5e0608a,Gender Classification from Pose-Based GEIs,"Gender Classification from Pose-Based GEIs(cid:2) +Ra´ul Mart´ın-F´elez, Ram´on A. Mollineda, and J. Salvador S´anchez +Institute of New Imaging Technologies (INIT) +Universitat Jaume I. Av. Sos Baynat s/n, 12071, Castell´o de la Plana, Spain"
+5146832515ba8b4ad48372967d9fb7dcdea61869,CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks,"Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers, pages 646–654, +Berlin, Germany, August 11-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
+51a81a17328ad36f1bbc15e240076b68d3271c0c,Laplacian object: One-shot object detection by locality preserving projection,"LAPLACIAN OBJECT: ONE-SHOT OBJECT DETECTION BY LOCALITY PRESERVING +PROJECTION +Sujoy Kumar Biswas and Peyman Milanfar +Electrical Engineering Department +University of California, Santa Cruz +156 High Street, Santa Cruz, CA, 95064"
+5193328862366e114781cb6b196ae958c1553357,Incremental Learning in Person Re-Identification,"Incremental Learning in Person Re-Identification +Prajjwal Bhargava +SRM University +Chennai"
+511662e02373433c8c9e27d1425707069e3695b7,Effects of image compression on ear biometrics,"Engineering and Technology Copyright. The copy of record is available at IET Digital Library. +Research Article +Effects of image compression on ear +iometrics +ISSN 2047-4938 +Received on 23rd October 2015 +Revised on 27th January 2016 +Accepted on 15th February 2016 +doi: 10.1049/iet-bmt.2015.0098 +www.ietdl.org +Christian Rathgeb1 ✉, Anika Pflug2, Johannes Wagner1, Christoph Busch1 +da/sec – Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany +Media Security and IT Forensics – Fraunhofer Institute for Secure Information Technology, Germany +✉ E-mail:"
+5120fb7db8eadb26118847d0553fca1c22ed6f07,Deep Extreme Tracker Based on Bootstrap Particle Filter,"Journal of Theoretical and Applied Information Technology +31st August 2014. Vol. 66 No.3 +© 2005 - 2014 JATIT & LLS. All rights reserved. +ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 +DEEP EXTREME TRACKER BASED ON +BOOTSTRAP PARTICLE FILTER +ALEXANDER A S GUNAWAN, +2 MOHAMAD IVAN FANANY, +WISNU JATMIKO +Bina Nusantara University, Mathematics Department, School of Computer Science, Jakarta, Indonesia +, 3 Universitas Indonesia, Faculty of Computer Science, Depok, Indonesia +E-mail: 1 2 3"
+51b70582fb0d536d4a235f91bf6ad382f29e2601,Detection of emotions from video in non-controlled environment. (Détection des émotions à partir de vidéos dans un environnement non contrôlé),"Detection of emotions from video in non-controlled +environment +Rizwan Ahmed Khan +To cite this version: +Rizwan Ahmed Khan. Detection of emotions from video in non-controlled environment. Image +Processing. Universit´e Claude Bernard - Lyon I, 2013. English. <NNT : 2013LYO10227>. +<tel-01166539v2> +HAL Id: tel-01166539 +https://tel.archives-ouvertes.fr/tel-01166539v2 +Submitted on 23 Jun 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de"
+51319bb12c67fb5b11cbf2012a7e2059718b52eb,Local Fisher Discriminant Analysis for Pedestrian Re-identification,"Local Fisher Discriminant Analysis for Pedestrian Re-identification +Sateesh Pedagadi, James Orwell +Kingston University London +Sergio Velastin +Universidad de Santiago de Chile +Boghos Boghossian +Ipsotek Ltd, UK"
5161e38e4ea716dcfb554ccb88901b3d97778f64,SSPP-DAN: Deep domain adaptation network for face recognition with single sample per person,"SSPP-DAN: DEEP DOMAIN ADAPTATION NETWORK FOR FACE RECOGNITION WITH SINGLE SAMPLE PER PERSON Sungeun Hong, Woobin Im, Jongbin Ryu, Hyun S. Yang @@ -2006,14 +6679,98 @@ School of Computing, KAIST, Republic of Korea" EMBEDDINGS Charles F. Jekel and Raphael T. Haftka Department of Mechanical & Aerospace Engineering - University of Florida - Gainesville, FL 32611"
+51cf3fa26b7c31c10427317fb5d72a6712023279,What Shape Is Your Conjugate? A Survey of Computational Convex Analysis and Its Applications,"A SURVEY OF COMPUTATIONAL CONVEX ANALYSIS AND ITS APPLICATIONS +WHAT SHAPE IS YOUR CONJUGATE? +YVES LUCET"
51d1a6e15936727e8dd487ac7b7fd39bd2baf5ee,"A Fast and Accurate System for Face Detection, Identification, and Verification","JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 A Fast and Accurate System for Face Detection, Identification, and Verification Rajeev Ranjan, Ankan Bansal, Jingxiao Zheng, Hongyu Xu, Joshua Gleason, Boyu Lu, Anirudh Nanduri, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa"
+5194a8acc87dd05a92a21f94fea966a2815f9b38,Noise aware analysis operator learning for approximately cosparse signals,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE +ICASSP 2012"
+51e43578ad761c7c4d58cb159eee0f8e6cf0f7a4,Incremental indexing and distributed image search using shared randomized vocabularies,"Introduction +Method +Results +Incremental Indexing and Distributed Image Search +using Shared Randomized Vocabularies +Rapha¨el Mar´ee, Philippe Denis, Louis Wehenkel, Pierre Geurts +GIGA Bioinformatics +GIGA Research ; Dept. EE & CS (Montefiore Institute) +University of Li`ege, Belgium +MIR 2010 +March 29–31, 2010 +Philadelphia, Pennsylvania, USA +Mar´ee et al. +Shared Randomized Vocabularies +(1 / 44)"
+51d97f4e4385a3da78bf9277a5426216198698c3,Improving the Accuracy of Face Detection for Damaged Video and Distant Targets,"Improving the Accuracy of Face Detection for Damaged Video and +Distant Targets +Department of Communication Engineering, Oriental Institute of Technology, New Taiepi City, Taiwan +Jun-Horng Chen +Keywords: +Error Concealment, Face Detection, Super-resolution."
+514fdf2152dda3a39fc05eb6e1c80314837d96a2,Detailed 3D Representations for Object Recognition and Modeling,"Detailed 3D Representations for +Object Recognition and Modeling +M. Zeeshan Zia, Student Member, IEEE, Michael Stark, Member, IEEE, +Bernt Schiele, Member, IEEE, and Konrad Schindler, Member, IEEE"
+51bfc693d170b4171f5bd9f9aed51f1fe8b5304d,Zero-Shot Recognition via Direct Classifier Learning with Transferred Samples and Pseudo Labels,"Zero-shot Recognition via Direct Classifier Learning +with Transferred Samples and Pseudo Labels +AAAI Anonymous Submission 182"
5157dde17a69f12c51186ffc20a0a6c6847f1a29,Evolutionary Cost-Sensitive Extreme Learning Machine,"Evolutionary Cost-sensitive Extreme Learning Machine Lei Zhang, Member, IEEE, and David Zhang, Fellow, IEEE"
+3dec830b2514e82c714162622b3077966660112f,Statistical Evaluation of Face Recognition Techniques under Variable Environmental Constraints,"International Journal of Statistics and Probability; Vol. 4, No. 4; 2015 +ISSN 1927-7032 E-ISSN 1927-7040 +Published by Canadian Center of Science and Education +Statistical Evaluation of Face Recognition Techniques under Variable +Environmental Constraints +Louis Asiedu1, Atinuke O. Adebanji2, Francis Oduro3 +& Felix O. Mettle4 +Department of Statistics, University of Ghana, Legon-Accra, Ghana +Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana +Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana +Department of Statistics, University of Ghana, Legon-Accra, Ghana +Correspondence: Louis Asiedu, Department of Statistics, University of Ghana, Legon-Accra, Ghana. Tel: +33-543-426-707. E-mail: +Received: August 1, 2015 Accepted: August 19, 2015 Online Published: October 9, 2015 +doi:10.5539/ijsp.v4n4p93 URL: http://dx.doi.org/10.5539/ijsp.v4n4p93"
+3d74d4177f5c1444b73221c12f359e858625a691,Composite-ISA Cores : Enabling Multi-ISA Heterogeneity Using a Single ISA,"ISCA 2018 Submission #283 +Confidential Draft: DO NOT DISTRIBUTE +Composite-ISA Cores: Enabling Multi-ISA Heterogeneity +Using a Single ISA"
+3d6229044f6605604818f39f08c5270a5a132a03,Projective Nonnegative Matrix Factorization based on α-Divergence,"Projective Nonnegative Matrix Factorization based on +-Divergence +Zhirong Yang and Erkki Oja +Department of Information and Computer Science∗ +Aalto University School of Science and Technology +P.O.Box 15400, FI-00076, Aalto, Finland"
+3dbb2ca6942eb49538d92823fe22c7475e866ca1,Institutionen För Systemteknik Department of Electrical Engineering Examensarbete Autonomous Morphometrics Using Depth Cameras for Object Classification and Identification Autonomous Morphometrics Using Depth Cameras for Object Classification and Identification Examensarbete Utfört I Datorseende Vid Tekniska Högskolan Vid Linköpings Universitet Av,"Institutionen för systemteknik +Department of Electrical Engineering +Examensarbete +Autonomous Morphometrics using Depth Cameras for +Object Classification and Identification +Examensarbete utfört i Datorseende +vid Tekniska högskolan vid Linköpings universitet +Felix Björkeson +LiTH-ISY-EX--13/4680--SE +Linköping 2013 +Department of Electrical Engineering +Linköpings universitet +SE-581 83 Linköping, Sweden +Linköpings tekniska högskola +Linköpings universitet +581 83 Linköping"
+3da97d97b12fcf22208c36f471119f33a08d9b6f,Multi-modal Biometric system using ear and face(2D+3D) Modalities,"Multi-modal Biometric system using ear and +face(2D+3D) Modalities +M.Pujitha Raj +Computer Science and engineering +Amrita University +Coimbatore, India +B.Achyut Sarma +Computer Science and engineering +Amrita University +Coimbatore, India"
3daafe6389d877fe15d8823cdf5ac15fd919676f,Human Action Localization with Sparse Spatial Supervision,"Human Action Localization with Sparse Spatial Supervision Philippe Weinzaepfel, Xavier Martin, and Cordelia Schmid, Fellow, IEEE"
@@ -2022,16 +6779,44 @@ Technology? A Literature Review Muhammad Shoaib Jaliawala∗, Rizwan Ahmed Khan∗† Faculty of Information Technology, Barrett Hodgson University, Karachi, Pakistan Universit´e Claude Bernard Lyon 1, France"
+3dcc51a37f2e5e91d77ff00f18178484c4e938cb,Excitation Dropout: Encouraging Plasticity,"Under review as a conference paper at ICLR 2019 +EXCITATION DROPOUT: ENCOURAGING PLASTICITY +IN DEEP NEURAL NETWORKS +Anonymous authors +Paper under double-blind review"
3d36f941d8ec613bb25e80fb8f4c160c1a2848df,Out-of-Sample Generalizations for Supervised Manifold Learning for Classification,"Out-of-sample generalizations for supervised manifold learning for classification Elif Vural and Christine Guillemot"
+3d7a5d1fbec861542631fcb10f58e38f4f51a04c,Face Recognition Application of Blur-Robust,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Impact Factor (2012): 3.358 +Face Recognition Application of Blur-Robust +Pitta Santhosh Kumar1, Ankush Jain2 +M.Tech student, Department of CSE, Anurag Group of Institutions, Hyderabad, India +Assistant professor, Department of CSE, Anurag Group of Institutions, Hyderabad, India"
3d5a1be4c1595b4805a35414dfb55716e3bf80d8,Hidden Two-Stream Convolutional Networks for Action Recognition,"Hidden Two-Stream Convolutional Networks for Action Recognition Yi Zhu, Zhenzhong Lan, Shawn Newsam, Alexander G. Hauptmann"
+3de3c479164312ab3a1795ee84f20c16632c04c4,Scalable Deep Learning Logo Detection,"Scalable Deep Learning Logo Detection +Hang Su∗, Shaogang Gong†, Xiatian Zhu‡ +† Queen Mary University of London ‡ Vision Semantics Ltd."
3d62b2f9cef997fc37099305dabff356d39ed477,Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition,"Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition Feng Liu, Qijun Zhao, Member, IEEE, Xiaoming Liu, Member, IEEE and Dan Zeng"
+3d97f739ae76c8db1146da4aaeb0dc1ef3d31c33,Données multimodales pour l ’ analyse d ’ image,"UNIVERSITÉDEGRENOBLENoattribuéparlabibliothèqueTHÈSEpourobtenirlegradedeDOCTEURDEL’UNIVERSITÉDEGRENOBLESpécialité:MathématiquesetInformatiquepréparéeauLaboratoireJeanKuntzmanndanslecadredel’ÉcoleDoctoraleMathématiques,SciencesetTechnologiesdel’Information,InformatiqueprésentéeetsoutenuepubliquementparMatthieuGuillauminle27septembre2010ExploitingMultimodalDataforImageUnderstandingDonnéesmultimodalespourl’analysed’imageDirecteursdethèse:CordeliaSchmidetJakobVerbeekJURYM.ÉricGaussierUniversitéJosephFourierPrésidentM.AntonioTorralbaMassachusettsInstituteofTechnologyRapporteurMmeTinneTuytelaarsKatholiekeUniversiteitLeuvenRapporteurM.MarkEveringhamUniversityofLeedsExaminateurMmeCordeliaSchmidINRIAGrenobleExaminatriceM.JakobVerbeekINRIAGrenobleExaminateur"
+3d91ba69bfbb2ba018419342d279f2d7571530f6,Qualitative Tracking Performance Evaluation without Ground-Truth,"Qualitative Tracking Performance Evaluation without Ground-Truth∗ +Dept. of Computer Science and Engineering +Dept. of Computer Science and Engineering +Jihun Hamm +Bohyung Han +POSTECH, Korea"
+3da4fa2365c01f53180050c7d332107089d913c0,Face Recognition Using Parzenfaces,"Face Recognition Using Parzenfaces +Zhirong Yang and Jorma Laaksonen +Laboratory of Computer and Information Science ⋆ +Helsinki University of Technology +P.O. Box 5400, FI-02015 TKK, Espoo, Finland +{zhirong.yang,"
3dd4d719b2185f7c7f92cc97f3b5a65990fcd5dd,Ensemble of Hankel Matrices for Face Emotion Recognition,"Ensemble of Hankel Matrices for Face Emotion Recognition Liliana Lo Presti and Marco La Cascia @@ -2039,6 +6824,45 @@ DICGIM, Universit´a degli Studi di Palermo, V.le delle Scienze, Ed. 6, 90128 Palermo, Italy, DRAFT To appear in ICIAP 2015"
+3da12b99cd8040bb374eed160f8016b3fe492967,Multiperson Tracking by Online Learned Grouping Model With Nonlinear Motion Context,"Multi-person Tracking by Online Learned Grouping +Model with Non-linear Motion Context +Xiaojing Chen, Zhen Qin, Le An, Member, IEEE, and Bir Bhanu, Fellow, IEEE"
+3d1b0c7e9ef0e31dd635041539e795dc07ebee86,Tracking people in 3D using a bottom-up top-down detector,"Tracking People in 3D Using a Bottom-Up Top-Down Detector +Luciano Spinello, Matthias Luber and Kai O. Arras +Social Robotics Lab, University of Freiburg, Germany +{spinello, luber,"
+3d88180732d63a4babf3a4b1a82dd7fdf27a7520,"Facial expression, size, and clutter: Inferences from movie structure to emotion judgments and back.","23Attention, Perception, &Psychophysics ISSN 1943-3921Volume 78Number 3 Atten Percept Psychophys (2016)78:891-901DOI 10.3758/s13414-015-1003-5Facial expression, size, and clutter:Inferences from movie structure to emotionjudgments and backJames E. Cutting & Kacie L. Armstrong"
+3db123d094c7ba33bbd3c4ccbea77e2093ad6174,Online Visual Multi-Object Tracking via Labeled Random Finite Set Filtering,"JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, X XXXX +A Labeled Random Finite Set Online +Multi-Object Tracker for Video Data +Du Yong Kim, Ba-Ngu Vo, Member, IEEE, and Ba-Tuong Vo, Member, IEEE"
+3dc3f0b64ef80f573e3a5f96e456e52ee980b877,Maximum Likelihood Training of the Embedded HMM for Face Detection and Recognition,"AXU E +DETECT AD RECGT +Aa V. e(cid:12)a ad +Cee f Siga +Sch +Gegia i e f Tech +faa"
+3d67e97227846f579d1825e00d395d30e17f5d0e,Face and ECG Based Multi-Modal Biometric Authentication,"Face and ECG Based Multi-Modal +Biometric Authentication +Ognian Boumbarov1, Yuliyan Velchev1, Krasimir Tonchev1 +nd Igor Paliy2 +Technical University of Sofia +Ternopil National Economic University +Bulgaria +Ukraine +. Introduction +A biometric system is essentially a pattern recognition system. This system measures +nd analyses human body physiological characteristics, such as face and facial features, +fingerprints, eye, retinas, irises, voice patterns or behavioral characteristic for enrollment, +verification or identification (Bolle & Pankanti, 1998). Uni-modal biometric systems have +poor performance and accuracy, and over last few decades the multi-modal biometric systems +have become very popular. The main objective of multi biometrics is to reduce one or more +false accept rate, false reject rate and failure to enroll rate. Face Recognition (FR) is still +onsidered as one of the most challenging problems in pattern recognition. The FR systems +try to recognize the human face in video sequences as 3D object (Chang et al., 2003; 2005), in +unconstrained conditions, in comparison to the early attempts of 2D frontal faces in controlled +onditions. Despite the effort spent on research today there is not a single, clearly defined,"
3dcebd4a1d66313dcd043f71162d677761b07a0d,Local binary pattern domain local appearance face recognition,"Yerel Đkili Örüntü Ortamında Yerel Görünüme Dayalı Yüz Tanıma Local Binary Pattern Domain Local Appearance Face Recognition Hazım K. Ekenel1, Mika Fischer1, Erkin Tekeli2, Rainer Stiefelhagen1, Aytül Erçil2 @@ -2059,6 +6883,14 @@ irbirleri ile örtüşmeyen bloklara ayrılmış ve her blok dönüşümü uygulanmıştır. Çıkartımı yapılan yerel öznitelikler daha sonra arka arkaya eklenerek global öznitelik vektörü oluşturulmuştur. Önerilen algoritma, CMU PIE ve FRGC"
+3d7fce66c1880f4b29171e415cfad57d8b96ced2,Exploiting Ambiguities in the Analysis of Cumulative Matching Curves for Person Re-identification,
+3df5e17e87144b1e84b5ab9467bc2c2f233b66c7,Convolutional Architecture Exploration for Action Recognition and Image Classification,"Convolutional Architecture Exploration for +Action Recognition and Image Classification +JT Turner∗1,2, David Aha1, Leslie Smith1, and Kalyan Moy Gupta2 +Knexus Research Corporation; +74 Waterfront Street Suite 310; National Harbor, MD 20745 +Navy Center for Applied Research in Artificial Intelligence; +Naval Research Laboratory (Code 5514); Washington, DC 20375"
3d42e17266475e5d34a32103d879b13de2366561,The Global Dimensionality of Face Space,"Proc.4thIEEEInt’lConf.AutomaticFace&GestureRecognition,Grenoble,France,pp264–270 The Global Dimensionality of Face Space (cid:3) @@ -2072,22 +6904,203 @@ Mount Sinai School of Medicine (cid:13) IEEE2000 230 York Avenue, New York, NY 10021 One Gustave L. Levy Place, New York, NY 10029"
+3d8c8acb8c59e9f23f048f44a23f36ffd791cdf5,Visual tracking over multiple temporal scales,"Khan, Muhammad Haris (2015) Visual tracking over +multiple temporal scales. PhD thesis, University of +Nottingham. +Access from the University of Nottingham repository: +http://eprints.nottingham.ac.uk/33056/1/Thesis.pdf +Copyright and reuse: +The Nottingham ePrints service makes this work by researchers of the University of +Nottingham available open access under the following conditions. +This article is made available under the University of Nottingham End User licence and may +e reused according to the conditions of the licence. For more details see: +http://eprints.nottingham.ac.uk/end_user_agreement.pdf +For more information, please contact"
+3dba6c86541aad3ec8f54c55d57eca9aa98f4ed2,PAC-Bayesian Majority Vote for Late Classifier Fusion,"PAC-Bayesian Majority Vote for Late Classifier Fusion∗ +Aix-Marseille Univ., LIF-QARMA, CNRS, UMR 7279, F-13013, Marseille, France +Emilie Morvant +St´ephane Ayache +Amaury Habrard +Univ. of St-Etienne, Lab. Hubert Curien, CNRS, UMR 5516, F-42000, St-Etienne, France +May 2, 2014"
3df7401906ae315e6aef3b4f13126de64b894a54,Robust learning of discriminative projection for multicategory classification on the Stiefel manifold,"Robust Learning of Discriminative Projection for Multicategory Classification on the Stiefel Manifold Duc-Son Pham and Svetha Venkatesh Dept. of Computing, Curtin University of Technology GPO Box U1987, Perth, WA 6845, Australia"
+3dd1338a5d0aa47fa2aef31654ee1392b8089991,Crowdsourcing the construction of a 3D object recognition database for robotic grasping,"014 IEEE International Conference on Robotics & Automation (ICRA) +Hong Kong Convention and Exhibition Center +May 31 - June 7, 2014. Hong Kong, China +978-1-4799-3685-4/14/$31.00 ©2014 IEEE"
+3d1382fa43c31e594ed2d84dda9984b1db047b0e,Compositional Memory for Visual Question Answering,"Compositional Memory for Visual Question Answering +Aiwen Jiang1,2 +Fang Wang2 +Fatih Porikli2 +Yi Li∗ 2,3 +NICTA and ANU +{fang.wang, +Toyota Research Institute North America +feature as the first word to initialize the sequential learning. +While the use of holistic approach is straightforward and +onvenient, it is, however, debatably problematic. For ex- +mple, in the VQA problems many answers are directly re- +lated to the contents of some image regions. Therefore, it +is dubious if the holistic features are rich enough to provide +the information only available at regions. Also, it may hin- +der the exploration of finer-grained local features for VQA. +In this paper we propose a Compositional Memory for +n end-to-end training framework. Our approach takes the +dvantage of the recent progresses in image captioning [3, +], natural language processing [5], and computer vision to"
+3d21b7b4f48e614bc2f2b87eb110aa329b7d66d8,Recognizing Human Actions by Using Effective Codebooks and Tracking,"Recognizing Human Actions by using Effective +Codebooks and Tracking +Lamberto Ballan, Lorenzo Seidenari, Giuseppe Serra, Marco Bertini and Alberto +Del Bimbo"
3d1af6c531ebcb4321607bcef8d9dc6aa9f0dc5a,Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs,"Random Multispace Quantization as n Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs Andrew B.J. Teoh, Member, IEEE, Alwyn Goh, and David C.L. Ngo, Member, IEEE"
+3dffacda086689c1bcb01a8dad4557a4e92b8205,Multiple Object Tracking: A Literature Review,"Multiple Object Tracking: A Literature Review +Wenhan Luo, Junliang Xing, Anton Milan, Xiaoqin Zhang, Wei Liu, Xiaowei Zhao and Tae-Kyun Kim"
+3d67aa108e65e636158abc0f31b703af3d31baa6,Decorrelating Semantic Visual Attributes by Resisting the Urge to Share,"Decorrelating Semantic Visual Attributes by Resisting the Urge +Supplementary material for CVPR 2014 submission ID 0824 +to Share +In this document, we provide supplementary material for our CVPR 2014 submission “Decorrelating Semantic +Visual Attributes by Resisting the Urge to Share”(Paper ID 0824). Sec 1 gives additional details for our experi- +mental setup (Sec 4 of the paper). Sec 1.1 lists the groups used in all three datasets in our experiments. Sec 1.2 +discusses the details of the image descriptors used for each dataset. Sec 2 discusses how attributes are localized +for our experiments in Sec 4.1 in the paper. Sec 3 discusses how it is posible to set parameters that generalize well +to novel test sets, using only training data. Sec 4 discusses the details of the optimization of our formulation (Eq 4 +in the paper). +Datasets +.1 Groups +(see para on Semantic groups in Sec 4 in the paper) +Fig 1, 2 and 3 show the attribute groups used in our experiments on the CUB, AwA and aPY datasets +respectively. The 28 CUB groups come pre-specified with the dataset [6]. The groups on AwA match exactly the +groups specified in [5]. Those on aPY also match the groups outlined in [5] on the 25 attributes (see paper) used +in our experiments (aPY-25). In each figure, attribute groups are enclosed in shaded boxes, and phrases in larger +font labeling the boxes indicate the rationale for the grouping. +.2 Features +(see also Sec 3.2 and para on Features in Sec 4 in the paper)"
+3dc78b41ed926b88c9cc4d40c6c5250bfafad74a,A pilot study for mood-based classification of TV programmes,"Research & Development +White Paper +WHP 231 +September 2012 +A Pilot Study for +Mood-based Classification of TV Programmes +Jana Eggink, Penelope Allen, Denise Bland +BRITISH BROADCASTING CORPORATION"
3d94f81cf4c3a7307e1a976dc6cb7bf38068a381,Data-Dependent Label Distribution Learning for Age Estimation,"Data-Dependent Label Distribution Learning for Age Estimation Zhouzhou He, Xi Li, Zhongfei Zhang, Fei Wu, Xin Geng, Yaqing Zhang, Ming-Hsuan Yang, and Yueting Zhuang"
+3d5187a957cc90f4143e6302786d65dbedf7d9bb,Stacking With Auxiliary Features for Visual Question Answering,"To Appear In Proceedings of the 16th Annual Conference of the North American +Chapter of the Association for Computational Linguistics: Human Language +Technologies 2018."
+3d9d1f8075ebdd03f86b4e40b9a5d08447ade8d3,Comparison of Illumination Normalization Methods for Face Recognition∗,"COMPARISON OF ILLUMINATION NORMALIZATION METHODS FOR +FACE RECOGNITION(cid:3) +Mauricio Villegas Santamar·(cid:17)a and Roberto Paredes Palacios +Instituto Tecnol·ogico de Inform·atica +Universidad Polit·ecnica de Valencia +Camino de Vera s/n, 46022 Valencia (Spain)"
+3d5b8127ce57279f9fd77d3a24d8034b485163a4,System ( tm ) for Image and Vision Computing Manuscript Draft Manuscript Number : IMAVIS-D16-00270 R 2 Title : Extended three-dimensional rotation invariant local binary patterns,"Elsevier Editorial System(tm) for Image and +Vision Computing +Manuscript Draft +Manuscript Number: IMAVIS-D-16-00270R2 +Title: Extended three-dimensional rotation invariant local binary +patterns +Article Type: Full Length Article +Keywords: Local binary patterns (LBP); Three-dimensions; Rotation +invariance; Texture classification +Corresponding Author: Mr. Leonardo Citraro, MSc. +Corresponding Author's Institution: University of Southampton +First Author: Leonardo Citraro, MSc. +Order of Authors: Leonardo Citraro, MSc.; Sasan Mahmoodi, Professor, Phd; +Angela Darekar, Phd; Brigitte Vollmer, Professor, Phd"
+3db588f1e58c1207685771d8015fa9427d731a53,An automatic 3D expression recognition framework based on sparse representation of conformal images,"An Automatic 3D Expression Recognition Framework based on Sparse +Representation of Conformal Images +Wei Zeng, Huibin Li, Liming Chen, Jean-Marie Morvan, Xianfeng David Gu"
+3d740c4f2246ce8e63d0eacc2cc1a5c31259e9ee,Discovering Attribute Shades of Meaning with the Crowd,"http://dx.doi.org/10.1007/s11263-014-0798-1 +Discovering Attribute Shades of Meaning with the Crowd +Adriana Kovashka · Kristen Grauman +Received: date / Accepted: date"
+3da9a9091cfa8f4bf625829faf7a4c35a8fe91e0,Working memory network alterations in high-functioning adolescents with an autism spectrum disorder.,"PDF hosted at the Radboud Repository of the Radboud University +Nijmegen +The following full text is a publisher's version. +For additional information about this publication click this link. +http://hdl.handle.net/2066/183247 +Please be advised that this information was generated on 2018-05-20 and may be subject to +hange."
+3d42aedd347f927a6bce28d0fa509c6d2132c11f,3D Hand Pose Detection in Egocentric RGB-D Images,"International Journal of Computer Vision manuscript No. +(will be inserted by the editor) +D Hand Pose Detection in Egocentric RGB-D Images +Gr´egory Rogez · J. S. Supanˇciˇc III · Maryam Khademi · +J. M. M. Montiel · Deva Ramanan +Received: date / Accepted: date"
+58b80f0e484d32c9fe5b57648848e048270d435b,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+58cbd5a31e92cff29e29e8b25ee79f30ff4e6d4b,Culture shapes spatial frequency tuning for face identification.,"Journal of Experimental Psychology: +Human Perception and Performance +017, Vol. 43, No. 2, 294 –306 +0096-1523/17/$12.00 +© 2016 American Psychological Association +http://dx.doi.org/10.1037/xhp0000288 +Culture Shapes Spatial Frequency Tuning for Face Identification +Université de Montréal and Université du Québec en Outaouais +Jessica Tardif +Daniel Fiset +Université du Québec en Outaouais +Ye Zhang +Hangzhou Normal University +Amanda Estéphan +Université du Québec en Outaouais +Qiuju Cai, Canhuang Luo, and Dan Sun +Hangzhou Normal University +Frédéric Gosselin +Université de Montréal +Caroline Blais"
+58d16e23e1192be4acaf6a29c1f5995817146554,Bringing back simplicity and lightliness into neural image captioning,"Bringing back simplicity and lightliness into neural image captioning +Jean-Benoit Delbrouck and St´ephane Dupont +{jean-benoit.delbrouck, +TCTS Lab, University of Mons, Belgium"
+5834555d239c27369e7a4167bb0c0fed725d761e,Improved illumination invariant homomorphic filtering using the dual tree complex wavelet transform,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE +ICASSP 2016"
+5801690199c1917fa58c35c3dead177c0b8f9f2d,Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis,"Remote Sens. 2010, 2, 2748-2772; doi:10.3390/rs2122748 +OPEN ACCESS +Article +Application of Object Based Classification and High Resolution +Satellite Imagery for Savanna Ecosystem Analysis +ISSN 2072-4292 +www.mdpi.com/journal/remotesensing +Cerian Gibbes *, Sanchayeeta Adhikari, Luke Rostant, Jane Southworth, and Youliang Qiu +Department of Geography & Land Use and Environmental Change Institute (LUECI), University of +Florida, 3141 Turlington Hall, P. O. Box 117315, Gainesville, FL 32611, USA; +E-Mails: (S.A.); (L.R.); (J.S.); +(Y.Q.) +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +1-352-392-0494; Fax: +1-352-392-8855. +Received: 16 October 2010; in revised form: 7 December 2010 / Accepted: 8 December 2010 / +Published: 10 December 2010"
+58a6eb3584b2f5df2f25d39a218904d510cae516,The UAVid Dataset for Video Semantic Segmentation,"The UAVid Dataset for Video Semantic Segmentation +Ye Lyu1, George Vosselman1, Guisong Xia2, Alper Yilmaz3, Michael Ying Yang1∗"
5892f8367639e9c1e3cf27fdf6c09bb3247651ed,Estimating Missing Features to Improve Multimedia Information Retrieval,"Estimating Missing Features to Improve Multimedia Information Retrieval Abraham Bagherjeiran Nicole S. Love Chandrika Kamath (cid:3)"
+58cb6677b77d5a79fc5b8058829693ca30b36ac5,Learning Similarity Metrics by Factorising Adjacency Matrices,"Learning Similarity Metrics by Factorising Adjacency Matrices +Henry Gouk† +Bernhard Pfahringer† +Michael Cree‡ +Department of Computer Science, University of Waikato, Hamilton, New Zealand +School of Engineering, University of Waikato, Hamilton, New Zealand"
587f81ae87b42c18c565694c694439c65557d6d5,DeepFace: Face Generation using Deep Learning,"DeepFace: Face Generation using Deep Learning Hardie Cate Fahim Dalvi @@ -2095,6 +7108,16 @@ Zeshan Hussain" 580054294ca761500ada71f7d5a78acb0e622f19,A Subspace Model-Based Approach to Face Relighting Under Unknown Lighting and Poses,"A Subspace Model-Based Approach to Face Relighting Under Unknown Lighting and Poses Hyunjung Shim, Student Member, IEEE, Jiebo Luo, Senior Member, IEEE, and Tsuhan Chen, Fellow, IEEE"
+58abb5001087f51dd2e9ab17b9fb8fb3567988e8,Array of Multilayer Perceptrons with No-class Resampling Training for Face Recognition,"Inteligencia Artificial 44(2009), 5-13 +doi: 10.4114/ia.v13i44.1041 +INTELIGENCIA ARTIFICIAL +http://erevista.aepia.org/ +Array of Multilayer Perceptrons with No-class +Resampling Training for Face Recognition +D. Capello1, C. Mart´ınez2,3, D. Milone2 and G. Stegmayer1 +CIDISI-UTN-FRSF, CONICET, Lavaise 610 - Santa Fe (Argentina) +Sinc(i)-FICH-UNL, CONICET, Ciudad Universitaria UNL - Santa Fe (Argentina) +Laboratorio de Cibern´etica-FI-UNER, C.C. 47 Suc. 3-3100, Entre R´ıos (Argentina)"
587c48ec417be8b0334fa39075b3bfd66cc29dbe,Serial dependence in the perception of attractiveness,"Journal of Vision (2016) 16(15):28, 1–8 Serial dependence in the perception of attractiveness Ye Xia @@ -2123,6 +7146,11 @@ Dojun Yang Joon-Ho Kim Samsung Research, Samsung Electronics {hyun0772.lee, joody.kim, dojun.yang,"
+58a5c2f9f60bdc6ab640767cb21fd6ba04eef5d7,Towards a Unified 3D Affective Model,"Towards a Unified 3D Affective Model +Kuderna-Iulian Benţa1, Hannelore-Inge Lisei2, Marcel Cremene1 +Technical University of Cluj-Napoca, 400016 Cluj-Napoca, România, +“Babeş-Bolyai“ University, 400084 Cluj-Napoca, România, +{Iulian.Benta, Marcel.Cremene,"
581e920ddb6ecfc2a313a3aa6fed3d933b917ab0,Automatic Mapping of Remote Crowd Gaze to Stimuli in the Classroom,"Automatic Mapping of Remote Crowd Gaze to Stimuli in the Classroom Thiago Santini1, Thomas K¨ubler1, Lucas Draghetti1, Peter Gerjets2, Wolfgang @@ -2133,6 +7161,9 @@ Hector Research Institute of Education Sciences and Psychology, T¨ubingen, Germany"
58fa85ed57e661df93ca4cdb27d210afe5d2cdcd,Facial expression recognition by re-ranking with global and local generic features,"Cancún Center, Cancún, México, December 4-8, 2016 978-1-5090-4847-2/16/$31.00 ©2016 IEEE"
+58888b30e9123c1b1709be1efa92898e090d7bd2,Person Re-Identification by Discriminative Selection in Video Ranking,"Person Re-Identification by Discriminative +Selection in Video Ranking +Taiqing Wang, Shaogang Gong, Xiatian Zhu, and Shengjin Wang"
5860cf0f24f2ec3f8cbc39292976eed52ba2eafd,COMPUTATION EvaBio: A TOOL FOR PERFORMANCE EVALUATION IN BIOMETRICS,"International Journal of Automated Identification Technology, 3(2), July-December 2011, pp. 51-60 COMPUTATION EvaBio: A TOOL FOR PERFORMANCE EVALUATION IN BIOMETRICS @@ -2140,6 +7171,24 @@ Julien Mahier, Baptiste Hemery, Mohamad El-Abed*, Mohamed T. El-Allam, Mohamed Y Bouhaddaoui and Christophe Rosenberger GREYC Laboratory, ENSICAEN - University of Caen Basse Normandie - CNRS, 6 Boulevard Maréchal Juin, 14000 Caen Cedex - France"
+5882e62866fe1fcf7f8458e0bd0bcb39057afce3,Attention to Head Locations for Crowd Counting,"Attention to Head Locations for Crowd Counting +Youmei Zhang, Chunluan Zhou, Faliang Chang, and Alex C. Kot, Fellow Member, IEEE"
+5872a8ae1879c3f20d94e7cc5a4fcef47b654c7e,Sparse Matching of Salient Facial Curves for Recognizing 3 D Faces,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2015): 78.96 | Impact Factor (2015): 6.391 +Sparse Matching of Salient Facial Curves for +Recognizing 3D Faces +Madhura Patil1, L. J. Sankpal2 +Pune University, Sinhgad Academy of Engineering, Kondhwa, Pune 411048, India +Professor, Pune University, Sinhgad Academy of Engineering, Kondhwa, Pune 411048 +cknowledgment +unique mark +cknowledgment. +increase acquisition commotion +furthermore"
+589b30ebdb76659ce5d3a19cd9fa0e7a3466d85d,Very Low Resolution Face Recognition Problem,"Very Low Resolution Face Recognition Problem +Wilman ZOU +Pong C. Yuen"
58bf72750a8f5100e0c01e55fd1b959b31e7dbce,PyramidBox: A Context-assisted Single Shot Face Detector,"PyramidBox: A Context-assisted Single Shot Face Detector. Xu Tang∗, Daniel K. Du∗, Zeqiang He, and Jingtuo Liu† @@ -2164,6 +7213,26 @@ Cambridge CB3 0FD United Kingdom phone +44 1223 763500 http://www.cl.cam.ac.uk/"
+58f7b9ebdb9b380cdfbef12b8abefceee0160a58,Public Document Document Evolution Executive Summary,"Project N° IST-2002-507634 - BioSecure +D7.2.2 – Revision: b3 +Contract Number: +Project Acronym: +Project Title: +Instrument: +Start Date of Project: +Duration: +Deliverable Number: +Title of Deliverable: +8 April 2005 +IST-2002-507634 +BioSecure +Biometrics for Secure Authentication +Network of Excellence +01 June, 2004 +6 months +D7.2.2 +Report on the face state of the art +Contractual Due Date:"
5865e824e3d8560e07840dd5f75cfe9bf68f9d96,Embodied conversational agents for multimodal automated social skills training in people with autism spectrum disorders,"RESEARCH ARTICLE Embodied conversational agents for multimodal automated social skills training in @@ -2176,6 +7245,7 @@ Japan, 3 Developmental Center for Child and Adult, Shigisan Hospital, Ikoma-gun, Features Extracting from Active Facial Patches Yanpeng Liua, Yuwen Caoa, Yibin Lia, Ming Liu, Rui Songa Yafang Wang, Zhigang Xu , Xin Maa†"
+585efe3c8efd1a4fa2ed8221c278997521668bc1,Recognizing Face Images with Disguise Variations,
58db008b204d0c3c6744f280e8367b4057173259,Facial Expression Recognition,"International Journal of Current Engineering and Technology ISSN 2277 - 4106 © 2012 INPRESSCO. All Rights Reserved. @@ -2191,9 +7261,72 @@ Guilhem Chéron∗ 1 2 Jean-Baptiste Alayrac∗ 1 Ivan Laptev1 Cordelia Schmid2"
+67a6bd37e91f2c334b1092fd9e9b16be93f82377,Data Driven Visual Recognition,"Data Driven Visual Recognition +OMID AGHAZADEH +Doctoral Thesis +Stockholm, Sweden, 2014"
+6720edcea05b31a9b9a6db98ee71e8ed31efdc38,Practices in source code sharing in astrophysics,"Practices +source +sharing +astrophysics +Shamir1, +Wallin2, +Alice +Allen3, +Bruce +Berriman4, +Peter +Teuben5, +Robert +Nemiroff6, +Jessica +Mink7, +Robert +Hanisch8, +Kimberly +DuPrie3"
+6768b558cc58e113096540c123ef3b2c2d2469a1,Maximum Margin Linear Classifiers in Unions of Subspaces,"LYU, ZEPEDA, PÉREZ: US-SVM +Maximum Margin Linear Classifiers in +Unions of Subspaces +Xinrui Lyu1,2 +Joaquin Zepeda1 +Patrick Pérez1 +Technicolor +5576, Cesson-Sevigne, France +École Polytechnique Fédérale de +Lausanne (EPFL) +CH-1015, Lausanne, Switzerland"
+67bf0b6bc7d09b0fe7a97469f786e26f359910ef,Abnormal use of facial information in high-functioning autism.,"J Autism Dev Disord +DOI 10.1007/s10803-006-0232-9 +O R I G I N A L P A P E R +Abnormal Use of Facial Information in High-Functioning +Autism +Michael L. Spezio Æ Ralph Adolphs Æ +Robert S. E. Hurley Æ Joseph Piven +Ó Springer Science+Business Media, LLC 2006"
6789bddbabf234f31df992a3356b36a47451efc7,Unsupervised Generation of Free-Form and Parameterized Avatars.,"Unsupervised Generation of Free-Form and Parameterized Avatars Adam Polyak, Yaniv Taigman, and Lior Wolf, Member, IEEE"
+6733adb12458678c606759233f6f55782bace372,Photogenic Facial Expression Discrimination,"PHOTOGENIC FACIAL EXPRESSION DISCRIMINATION +Luana Bezerra Batista and Herman Martins Gomes +Departamento de Sistemas e Computação +João Marques de Carvalho +Departamento de Engenharia Elétrica +Universidade Federal de Campina Grande +Campina Grande, Paraíba, Brasil, 58.109-970 +Keywords: +Facial Expression Recognition, Photogeny, Principal Component Analysis, Multi-Layer Perceptron."
+67490b6f34c827f107b046adeef0f5476132d4f8,"How good are detection proposals, really?","J. HOSANG ET AL.: HOW GOOD ARE DETECTION PROPOSALS, REALLY? +How good are detection proposals, really? +Jan Hosang +http://mpi-inf.mpg.de/~jhosang +Rodrigo Benenson +http://mpi-inf.mpg.de/~benenson +Bernt Schiele +http://mpi-inf.mpg.de/~schiele +MPI Informatics +Saarbrücken, Germany"
+674fcadf1b895e3a79380d3ac5afb43d406fd31a,Facial Asymmetry Assessment from 3D Shape Sequences: The Clinical Case of Facial Paralysis,
675b2caee111cb6aa7404b4d6aa371314bf0e647,AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions,"AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions Chunhui Gu∗ Yeqing Li∗ @@ -2207,8 +7340,35 @@ Susanna Ricco∗ Rahul Sukthankar∗ Cordelia Schmid† ∗ Jitendra Malik‡ ∗"
+67dca0d4b87ab2a4f18b5a1ef76f6ba17b599245,Top-Down Regularization of Deep Belief Networks,"Top-Down Regularization of Deep Belief Networks +Hanlin Goh∗, Nicolas Thome, Matthieu Cord +Laboratoire d’Informatique de Paris 6 +UPMC – Sorbonne Universit´es, Paris, France +Joo-Hwee Lim† +Institute for Infocomm Research +A*STAR, Singapore"
+67a56dd94906a5460c263e1a1b87fa3a52c4b453,Face Analysis by Local Directional Number Pattern,"International Journal of Engineering Research and General Science Volume 3, Issue 1, January-February, 2015 +ISSN 2091-2730 +FACE ANALYSIS BY LOCAL DIRECTIONAL NUMBER PATTERN +Manjunatha S B, Guruprasad A M, Vineesh P +Coorg Institute of Technology, Ponnampet, Coorg-District, Karnataka, 9611962024"
+67f88f37e4853b870debef2bd29b257b5b19f255,EgoSampling: Wide View Hyperlapse from Single and Multiple Egocentric Videos,"EgoSampling: Wide View Hyperlapse from +Single and Multiple Egocentric Videos +Tavi Halperin Yair Poleg Chetan Arora Shmuel Peleg"
67484723e0c2cbeb936b2e863710385bdc7d5368,Anchor Cascade for Efficient Face Detection,"Anchor Cascade for Efficient Face Detection Baosheng Yu and Dacheng Tao, Fellow, IEEE"
+678b367b2d5250f278c994238bbf816098252d9d,IrisDenseNet: Robust Iris Segmentation Using Densely Connected Fully Convolutional Networks in the Images by Visible Light and Near-Infrared Light Camera Sensors,"Article +IrisDenseNet: Robust Iris Segmentation Using +Densely Connected Fully Convolutional Networks in +the Images by Visible Light and Near-Infrared Light +Camera Sensors +Muhammad Arsalan, Rizwan Ali Naqvi, Dong Seop Kim, Phong Ha Nguyen, Muhammad Owais +nd Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (M.A.); (R.A.N.); +(D.S.K.); (P.H.N.); (M.O.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 2 April 2018; Accepted: 8 May 2018; Published: 10 May 2018"
670637d0303a863c1548d5b19f705860a23e285c,Face swapping: automatically replacing faces in photographs,"Face Swapping: Automatically Replacing Faces in Photographs Dmitri Bitouk Neeraj Kumar @@ -2233,6 +7393,28 @@ important of" What does 2D geometric information really tell us about 3D face shape? Anil Bas and William A. P. Smith, Member, IEEE"
+6775c818b26263c885b0ce85c224dfd942c9652e,Pedestrian and Object Detection Using Learned Convolutional Filters,"U.P.B. Sci. Bull., Series C, Vol. 77, Iss. 2, 2015 +ISSN 2286-3540 +PEDESTRIAN AND OBJECT DETECTION USING LEARNED +CONVOLUTIONAL FILTERS +Anamaria R ˘ADOI1 , Dan Alexandru STOICHESCU2 +Object detection is still a very active field in Computer Vision. Until now, part +ased models proved to be one of the most interesting and successful approaches +in object and pedestrian detection. The method applies a machine learning ap- +proach not to the input images themselves, but to histograms of gradients. How- +ever, its performances are still limited when compared to what humans can do. +The purpose of the present paper is to show that sparse representations can be +successfully used in object detection. The main advantage of using this method is +related to the possibility of learning only those filters that are able to express the +most frequent patterns that appear in the analyzed images. The experiments are +arried out on two widely used datasets, namely VOC2007 and INRIA Person. +Keywords: learned filterbanks, stochastic gradient descent, pedestrian detection, +object detection, Histogram of Oriented Gradients. +. Introduction +Object detection is a major challenge for many areas of research, starting +from medicine and going to applications such as street surveillance or video appli-"
+67bee729d046662c6ebd9d3d695823c9d820343a,Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus,"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pages 588–598, +Berlin, Germany, August 7-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
67c703a864aab47eba80b94d1935e6d244e00bcb,Face Retrieval Based On Local Binary Pattern and Its Variants: A Comprehensive Study,"(IJACSA) International Journal of Advanced Computer Science and Applications Vol. 7, No. 6, 2016 Face Retrieval Based On Local Binary Pattern and Its @@ -2240,10 +7422,77 @@ Variants: A Comprehensive Study Department of Computer Vision and Robotics, University of Science, VNU-HCM, Viet Nam Phan Khoi, Lam Huu Thien, Vo Hoai Viet face searching,"
+6752b59da83c03e64c73f9248a67304713b6efa9,Chapter 3 Re - identification by Covariance Descriptors,"Chapter 3 +Re-identification by Covariance Descriptors +Sławomir B ˛ak and François Brémond"
+67c30688bd46d305c610a83a0b28e86e10ef5cc4,Ship Detection in Harbour Surveillance based on Large-Scale Data and CNNs,
+67e00f7e928e6eab0faf1917252778b36bf64e39,Sparse radial sampling LBP for writer identification,"Sparse Radial Sampling LBP for Writer +Identification +Anguelos Nicolaou∗, Andrew D. Bagdanov∗, Marcus Liwicki†, and Dimosthenis Karatzas∗ +Computer Vision Center, Edifici O, Universitad Autonoma de Barcelona,Bellaterra, Spain +DIVA research group, Department of Informatics, University of Fribourg, Switzerland +Email:"
+6737a429dd615a0d9ac78d836c6b65bfd9ec36e8,Image Classification by Transfer Learning Based on the Predictive Ability of Each Attribute,"Image Classification by Transfer Learning Based +on the Predictive Ability of Each Attribute +Masahiro Suzuki, Haruhiko Sato, Satoshi Oyama, and Masahito Kurihara"
+6757254d27b761ada5dbd88642bd0112fcb962cf,Gait Recognition Using Wearable Motion Recording Sensors,"Hindawi Publishing Corporation +EURASIP Journal on Advances in Signal Processing +Volume 2009, Article ID 415817, 16 pages +doi:10.1155/2009/415817 +Research Article +Gait Recognition Using Wearable Motion Recording Sensors +Davrondzhon Gafurov and Einar Snekkenes +Norwegian Information Security Laboratory, Gjøvik University College, P.O. Box 191, 2802 Gjøvik, Norway +Correspondence should be addressed to Davrondzhon Gafurov, +Received 1 October 2008; Revised 26 January 2009; Accepted 26 April 2009 +Recommended by Natalia A. Schmid +This paper presents an alternative approach, where gait is collected by the sensors attached to the person’s body. Such wearable +sensors record motion (e.g. acceleration) of the body parts during walking. The recorded motion signals are then investigated for +person recognition purposes. We analyzed acceleration signals from the foot, hip, pocket and arm. Applying various methods, +the best EER obtained for foot-, pocket-, arm- and hip- based user authentication were 5%, 7%, 10% and 13%, respectively. +Furthermore, we present the results of our analysis on security assessment of gait. Studying gait-based user authentication (in case +of hip motion) under three attack scenarios, we revealed that a minimal effort mimicking does not help to improve the acceptance +hances of impostors. However, impostors who know their closest person in the database or the genders of the users can be a +threat to gait-based authentication. We also provide some new insights toward the uniqueness of gait in case of foot motion. In +particular, we revealed the following: a sideway motion of the foot provides the most discrimination, compared to an up-down or"
+67fd4f209aa6e8359fc86bdc12c62bbdb0529077,Scalable Nearest Neighbor Algorithms for High Dimensional Data,"Scalable Nearest Neighbor Algorithms +for High Dimensional Data +Marius Muja, Member, IEEE and David G. Lowe, Member, IEEE"
67ba3524e135c1375c74fe53ebb03684754aae56,A compact pairwise trajectory representation for action recognition,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE ICASSP 2017"
+679136c2844eeddca34e98e483aca1ff6ef5e902,Scene-Specific Pedestrian Detection Based on Parallel Vision,"Scene-Specific Pedestrian Detection Based on +Parallel Vision +Wenwen Zhang, Kunfeng Wang, Member, IEEE, Hua Qu, Jihong Zhao, and Fei-Yue Wang, Fellow, IEEE"
+676c76c4e3ac2f91a2209ecdae8d20be4de7c9c0,Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System,"International Journal of Computer Applications (0975 – 8887) +Volume 168 – No.12, June 2017 +Performance of Gabor mean Feature Extraction +Techniques for Ear Biometrics Recognition System +Bhanu Vadhwani +Rajasthan College of Engg. +for Women, India +Vineet Khanna +JaipuRajasthan College of +Engg. for Women +Shubhlakshmi Agarwal +The ICFAI University, Jaipur, India +Sandeep Kumar Gupta +Machine Learning Research +Lab, Jaipur, India"
+67751b7ce7f934ffadcf095f4189b31f890e9fdc,Pilot Comparative Study of Different Deep Features for Palmprint Identification in Low-Quality Images,"Ninth Hungarian Conference on Computer Graphics and Geometry, Budapest, 2018 +Pilot Comparative Study of Different Deep Features +for Palmprint Identification in Low-Quality Images +A.S. Tarawneh1, D. Chetverikov1,2 and A.B. Hassanat3 +Eötvös Loránd University, Budapest, Hungary +Institute for Computer Science and Control, Budapest, Hungary +Mutah University, Karak, Jordan"
6769cfbd85329e4815bb1332b118b01119975a95,Tied factor analysis for face recognition across large pose changes,"Tied factor analysis for face recognition across large pose changes"
+0b4189d874ee67f259a1a366ac93740d500064a5,Single-Shot Multi-person 3D Pose Estimation from Monocular RGB,"Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB +Dushyant Mehta[1,2], Oleksandr Sotnychenko[1,2], Franziska Mueller[1,2], +Weipeng Xu[1,2], Srinath Sridhar[3], Gerard Pons-Moll[1,2], Christian Theobalt[1,2] +[1] MPI For Informatics +[2] Saarland Informatics Campus +[3] Stanford University"
0be43cf4299ce2067a0435798ef4ca2fbd255901,Title A temporal latent topic model for facial expression recognition,"Title A temporal latent topic model for facial expression recognition Author(s) @@ -2256,10 +7505,41 @@ Issued Date http://hdl.handle.net/10722/142604 Rights Creative Commons: Attribution 3.0 Hong Kong License"
+0b6bd0a6f396e1479dc30318102bf49c12959783,Face Recognition Using Local Binary Decisions,"Face recognition using local binary decisions +Author +James, Alex, Dimitrijev, Sima +Published +Journal Title +https://doi.org/10.1109/LSP.2008.2006339 +Copyright Statement +© 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be +obtained for all other uses, in any current or future media, including reprinting/republishing this +material for advertising or promotional purposes, creating new collective works, for resale or +redistribution to servers or lists, or reuse of any copyrighted component of this work in other +works. +Downloaded from +http://hdl.handle.net/10072/23556 +Griffith Research Online +https://research-repository.griffith.edu.au"
0b2277a0609565c30a8ee3e7e193ce7f79ab48b0,Cost-Sensitive Semi-Supervised Discriminant Analysis for Face Recognition,"Cost-Sensitive Semi-Supervised Discriminant Analysis for Face Recognition Jiwen Lu, Member, IEEE, Xiuzhuang Zhou, Member, IEEE, Yap-Peng Tan, Senior Member, IEEE, Yuanyuan Shang, Member, IEEE, and Jie Zhou, Senior Member, IEEE"
+0b2c543e0c47454c4512569175094e6cb6ae02a9,The VizWiz Grand Challenge: A Large Visual Question Answering Dataset from Blind People,"#1687 +CVPR 2016 Submission #1687. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. +The VizWiz Grand Challenge: +A Large Visual Question Answering Dataset from Blind People +Anonymous CVPR submission +Paper ID 1687"
+0b57eb772ad9129ea4011c7fcb16c57967409018,“A Distorted Skull Lies in the Bottom Center...” Identifying Paintings from Text Descriptions,"Proceedings of 2016 NAACL Human-Computer Question Answering Workshop, pages 43–47, +San Diego, California, June 12-17, 2016. c(cid:13)2016 Association for Computational Linguistics"
+0b0b0d9b15613a6e3c4f9a4dd1c17c0313ca4303,Evaluation of 3D Face Recognition in the presence of facial expressions: an Annotated Deformable Model approach,"D face recognition +in the presence of facial expressions: +An annotated deformable model approach +I.A. Kakadiaris, Member, IEEE, G. Passalis, G. Toderici, N. Murtuza, Y. Lu, +N. Karampatziakis, and T. Theoharis +August 15, 2006 +DRAFT"
0b9ce839b3c77762fff947e60a0eb7ebbf261e84,Logarithmic Fourier Pca: a New Approach to Face Recognition,"Proceedings of the IASTED International Conference Computer Vision (CV 2011) June 1 - 3, 2011 Vancouver, BC, Canada @@ -2274,6 +7554,26 @@ Central Mechanical Engineering Research Institute Mahatma Gandhi Avenue, Durgapur - 713209, West Bengal, India. email: 1 n prabha 2 3"
+0bcd89b356dc78aaf3573086f13e94b8e7b5bee6,Comparative Testing of Face Detection Algorithms,"Comparative Testing of Face Detection +Algorithms⋆ +Nikolay Degtyarev and Oleg Seredin +Tula State University +http://lda.tsu.tula.ru"
+0bf26d2fd1b375f50c0a6bef086f09f7698c3156,Predicting Entry-Level Categories,"Noname manuscript No. +(will be inserted by the editor) +Predicting Entry-Level Categories +Vicente Ordonez · Wei Liu · Jia Deng · Yejin Choi · +Alexander C. Berg · Tamara L. Berg +Received: date / Accepted: date"
+0b278c9dc9b16b46ed602eab884ad7a37a988031,Robust Face-Name Graph Matching for Movie Character Identification,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2015): 78.96 | Impact Factor (2015): 6.391 +Robust Face-Name Graph Matching for Movie +Character Identification +Jonnadula Narasimha1, S Nishanth Kumar2, Chiluka Shiva Kumar3, D Vamshi Krishna Rao4 +Associate Professor, Department of Computer Science and Engineering, CMR Technical Campus, +Medchal, Hyderabad, Telangana, India +, 3, 4Department of Computer Science and Engineering, CMR Technical Campus, Medchal, Hyderabad, Telangana, India"
0b6a5200c33434cbfa9bf24ba482f6e06bf5fff7,"The use of deep learning in image segmentation, classification and detection","The Use of Deep Learning in Image Segmentation, Classification and Detection Mihai-Sorin Badea, Iulian-Ionuț Felea, Laura Maria Florea, Constantin Vertan @@ -2282,6 +7582,16 @@ The Image Processing and Analysis Lab (LAPI), Politehnica University of Buchares Zeynep Akataa,b, Florent Perronnina, Zaid Harchaouib and Cordelia Schmidb Computer Vision Group∗, XRCE, France LEAR†, INRIA, France"
+0b61cad6ae6e7ab99f2e3c187bd8530da71f10ae,Gameplay Genre Video Classification by Using Mid-Level Video Representation,"Gameplay genre video classification by using +mid-level video representation +Renato Augusto de Souza‡, Raquel Pereira de Almeida‡, Arghir-Nicolae Moldovan∗, +Zenilton Kleber G. do Patrocínio Jr.‡, Silvio Jamil F. Guimarães‡ +Audio-Visual Information Proc. Lab. (VIPLAB) +Computer Science Department – ICEI – PUC Minas +School of Computing, National College of Ireland, Dublin, Ireland +named GameGenre, consists of 700 videos (more than 116 +hours), classified into 7 game genres."
+0b0535fbdc468d1fd6ff32545a717a8af14f634f,The Discriminative Generalized Hough Transform as a Proposal Generator for a Deep Network in Automatic Pedestrian Localization,
0b0eb562d7341231c3f82a65cf51943194add0bb,Line with Your Paper Identification Number ( Double - Click Here to Edit,"> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < Facial Image Analysis Based on Local Binary Patterns: A Survey @@ -2291,6 +7601,43 @@ Tamara L. Berg, Alexander C. Berg, Jaety Edwards and D.A. Forsyth Berkeley, CA 94720 Computer Science Division U.C. Berkeley"
+0b937abb3b356a2932d804f9fc4b463485f63d0e,Visual word disambiguation by semantic contexts,"Visual word disambiguation by semantic contexts +Yu Su, Frédéric Jurie +To cite this version: +Yu Su, Frédéric Jurie. Visual word disambiguation by semantic contexts. IEEE Intenational Confer- +ence on Computer Vision (ICCV), 2011, Spain. pp.311-318, 2011, <10.1109/ICCV.2011.6126257>. +<hal-00808655> +HAL Id: hal-00808655 +https://hal.archives-ouvertes.fr/hal-00808655 +Submitted on 5 Apr 2013 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de +recherche français ou étrangers, des laboratoires"
+0b6f810f287561ff694a9406c7b319fd8549ca68,Face Recognition Based on Texture Features using Local Ternary Patterns,"I.J. Image, Graphics and Signal Processing, 2015, 10, 37-46 +Published Online September 2015 in MECS (http://www.mecs-press.org/) +DOI: 10.5815/ijigsp.2015.10.05 +Face Recognition Based on Texture Features +using Local Ternary Patterns +Associate Professor, Dept. of CSE, BVRIT Hyderabad College of Engineering for Women, Hyderabad, T.S., India. +K. Srinivasa Reddy +Director-CACR, Dean-Computer Sciences (CSE & IT), Anurag Group of Institutions, Hyderabad, T.S., India. +Email: +V. Vijaya Kumar +Email: +B. Eswara Reddy +Professor, Dept. of CSE, JNTUA, Ananthapuram, A.P., India. +Email:"
+0bb574ad77f55f395450b4a9f863ecfdd4880bcd,Learning the Base Distribution in Implicit Generative Models,"Learning the Base Distribution in Implicit Generative Models +Y. Cem Subakan(cid:91), Oluwasanmi Koyejo(cid:91), Paris Smaragdis(cid:91),(cid:93) +(cid:91)UIUC, (cid:93)Adobe Inc."
0b0958493e43ca9c131315bcfb9a171d52ecbb8a,A Unified Neural Based Model for Structured Output Problems,"A Unified Neural Based Model for Structured Output Problems Soufiane Belharbi∗1, Cl´ement Chatelain∗1, Romain H´erault∗1, and S´ebastien Adam∗2 LITIS EA 4108, INSA de Rouen, Saint ´Etienne du Rouvray 76800, France @@ -2304,6 +7651,11 @@ Luan Tran, and Xiaoming Liu, Member, IEEE" 0b174d4a67805b8796bfe86cd69a967d357ba9b6,A Survey on Face Detection and Recognition Approaches,"Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502 Vol. 3(4), 56-62, April (2014) Res.J.Recent Sci."
+0ba6f4fb548d8289fb42d68ac64d55f9e3a274ca,Auto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation,"Auto-context and Its Application to High-level Vision Tasks +nd 3D Brain Image Segmentation +Lab of Neuro Imaging, University of California, Los Angeles +Zhuowen Tu and Xiang Bai +July 9, 2009"
0b87d91fbda61cdea79a4b4dcdcb6d579f063884,Research on Theory and Method for Facial Expression Recognition Sys- tem Based on Dynamic Image Sequence,"The Open Automation and Control Systems Journal, 2015, 7, 569-579 Open Access Research on Theory and Method for Facial Expression Recognition Sys- @@ -2313,6 +7665,39 @@ Yang Xinfeng1,* and Jiang Shan2 School of Computer & Information Engineering, Nanyang Institute of Technology, Henan, Nanyang, 473000, P.R. China Henan University of Traditional Chinese Medicine, Henan, Zhengzhou, 450000, P.R. China"
+0b24cca96ca61248a3fa3973525a967f94292835,Two Novel Face Recognition Approaches,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+0b70facac4d10c7c73e7fdf3a85848ce429d98ab,"Segmentation features, visibility modeling and shared parts for object detection","Segmentation Features, Visibility Modeling and +Shared Parts for Object Detection +Patrick Ott +Submitted in accordance with the requirements +for the degree of Doctor of Philosophy. +The University of Leeds +School of Computing +February 2012 +The candidate confirms that the work submitted is his own and that the appropriate +redit has been given where reference has been made to the work of others. +This copy has been supplied on the understanding that it is copyright material +nd that no quotation from the thesis may be published without proper +cknowledgment."
0b79356e58a0df1d0efcf428d0c7c4651afa140d,Bayesian Modeling of Facial Similarity,"Appears In: Advances in Neural Information Processing Systems , MIT Press, . Bayesian Modeling of Facial Similarity Baback Moghaddam @@ -2326,11 +7711,33 @@ Cambridge, MA 0b572a2b7052b15c8599dbb17d59ff4f02838ff7,Automatic Subspace Learning via Principal Coefficients Embedding,"Automatic Subspace Learning via Principal Coefficients Embedding Xi Peng, Jiwen Lu, Senior Member, IEEE, Zhang Yi, Fellow, IEEE and Rui Yan, Member, IEEE,"
+0bc9f1749e23b37ea5b5588c5bfe23879174d343,Pythia v0.1: the Winning Entry to the VQA Challenge 2018,"Pythia v0.1: the Winning Entry to the VQA Challenge 2018 +Yu Jiang∗, Vivek Natarajan∗, Xinlei Chen∗, Marcus Rohrbach, Dhruv Batra, Devi Parikh +Facebook AI Research"
+0b888196dda951287dddb60bd44798aab16d6fca,Learning Common Sense through Visual Abstraction,
+0ba544ff0d837ba5279b03eb91246d00f2c78817,Direct Prediction of 3D Body Poses from Motion Compensated Sequences,"Direct Prediction of 3D Body Poses from Motion Compensated Sequences +Bugra Tekin1 +Artem Rozantsev1 +Vincent Lepetit1,2 +Pascal Fua1 +CVLab, EPFL, Lausanne, Switzerland, +TU Graz, Graz, Austria,"
+0bc7d8e269a8c8018a7cb120ff25adf02d45c7ed,Exploiting Dissimilarity Representations for Person Re-identification,"Exploiting Dissimilarity Representations for +Person Re-Identification +Riccardo Satta, Giorgio Fumera, and Fabio Roli +Dept. of Electrical and Electronic Engineering, University of Cagliari +Piazza d’Armi, 09123 Cagliari, Italy"
0b02bfa5f3a238716a83aebceb0e75d22c549975,Learning Probabilistic Models for Recognizing Faces under Pose Variations,"Learning Probabilistic Models for Recognizing Faces under Pose Variations M. Saquib Sarfraz and Olaf Hellwich Computer vision and Remote Sensing, Berlin university of Technology Sekr. FR-3-1, Franklinstr. 28/29, Berlin, Germany"
+0beaf17d42b1171dd245131825d2de67000f45ac,Expert Gate: Lifelong Learning with a Network of Experts,"Expert Gate: Lifelong Learning with a Network of Experts +Rahaf Aljundi +Punarjay Chakravarty +Tinne Tuytelaars +KU Leuven, ESAT-PSI, iMinds, Belgium +{rahaf.aljundi, Punarjay.Chakravarty,"
0bce54bfbd8119c73eb431559fc6ffbba741e6aa,Recurrent Neural Networks,"Published as a conference paper at ICLR 2018 SKIP RNN: LEARNING TO SKIP STATE UPDATES IN RECURRENT NEURAL NETWORKS @@ -2338,6 +7745,72 @@ V´ıctor Campos∗†, Brendan Jou‡, Xavier Gir´o-i-Nieto§, Jordi Torres† Barcelona Supercomputing Center, ‡Google Inc, §Universitat Polit`ecnica de Catalunya, ΓColumbia University {victor.campos,"
+0b19177107a102ee81e5ef1bb9fb2f2881441503,Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition,"Hindawi Publishing Corporation +EURASIP Journal on Advances in Signal Processing +Volume 2008, Article ID 468693, 7 pages +doi:10.1155/2008/468693 +Research Article +Comparing Robustness of Pairwise and Multiclass +Neural-Network Systems for Face Recognition +J. Uglov, L. Jakaite, V. Schetinin, and C. Maple +Computing and Information System Department, University of Bedfordshire, Luton LU1 3JU, UK +Correspondence should be addressed to V. Schetinin, +Received 16 June 2007; Revised 28 August 2007; Accepted 19 November 2007 +Recommended by Konstantinos N. Plataniotis +Noise, corruptions, and variations in face images can seriously hurt the performance of face-recognition systems. To make these +systems robust to noise and corruptions in image data, multiclass neural networks capable of learning from noisy data have been +suggested. However on large face datasets such systems cannot provide the robustness at a high level. In this paper, we explore a +pairwise neural-network system as an alternative approach to improve the robustness of face recognition. In our experiments, the +pairwise recognition system is shown to outperform the multiclass-recognition system in terms of the predictive accuracy on the +test face images. +Copyright © 2008 J. Uglov et al. This is an open access article distributed under the Creative Commons Attribution License, which +permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited."
+0b1cf351a4a6758606bea32d29c7d529e79ab7ce,Fake Face Detection System Using Pupil Reflection 양재준,"한국지능시스템학회 논문지 2010, Vol. 20, No. 5, pp. 645-651 +동공의 반사특징을 이용한 얼굴위조판별 시스템 +Fake Face Detection System Using Pupil Reflection +양재준*․조성원*․정선태** +JaeJun Yang, Seongwon Cho and Sun-Tae Chung +* 홍익대학교 전기정보제어공학과 +**숭실대학교 정보통신전자공학부 +최근 지능형 범죄가 늘면서 첨단 보안 기술에 대한 요구가 점차 늘어나고 있다. 현재까지 보고된 위조영상검출방법은 실용 +화를 위하여 정확도 개선이 요구된다. 본 논문에서는 사람의 얼굴에 대하여 동공의 반사광을 이용한 얼굴위조판별 시스템 +을 제안한다. 제안된 시스템은 먼저 다중 스케일 가버특징 벡터를 기반으로 눈의 위치를 찾은 후 2단계의 템플릿 매칭을 +통해서 설정된 적용범위를 벗어나는 눈에 대하여 위조판별을 고려하지 않음으로써 정확도를 높이는 방법을 사용한다. 신뢰 +도가 확보된 눈의 위치를 기반으로 적외선 조명에 반사되는 동공의 특징을 이용하여 눈위치 근처에서의 +화소값을 계산하 +여 위조 여부를 판단한다. 실험을 통하여 본 논문에서 제안한 방법이 더욱 신뢰성 높은 위조판별시스템임을 확인하였다. +키워드 : 변조영상 검출, 얼굴 검출, EBGM, 템플릿 매칭, 얼굴 식별"
+0b8ef6f5ec5dfc3eded5241fd3d636a596b94d26,Stereological analysis of amygdala neuron number in autism.,"7674 • The Journal of Neuroscience, July 19, 2006 • 26(29):7674 –7679 +Neurobiology of Disease +Stereological Analysis of Amygdala Neuron Number +in Autism +Cynthia Mills Schumann and David G. Amaral +Department of Psychiatry and Behavioral Sciences and The M.I.N.D. Institute, University of California, Davis, Sacramento, California 95817 +The amygdala is one of several brain regions suspected to be pathological in autism. Previously, we found that young children with autism +have a larger amygdala than typically developing children. Past qualitative observations of the autistic brain suggest increased cell density +in some nuclei of the postmortem autistic amygdala. In this first, quantitative stereological study of the autistic brain, we counted and +measured neurons in several amygdala subdivisions of 9 autism male brains and 10 age-matched male control brains. Cases with +omorbid seizure disorder were excluded from the study. The amygdaloid complex was outlined on coronal sections then partitioned into +five reliably defined subdivisions: (1) lateral nucleus, (2) basal nucleus, (3) accessory basal nucleus, (4) central nucleus, and (5) remaining +nuclei. There is no difference in overall volume of the amygdala or in individual subdivisions. There are also no changes in cell size. +However, there are significantly fewer neurons in the autistic amygdala overall and in its lateral nucleus. In conjunction with the findings +from previous magnetic resonance imaging studies, the autistic amygdala appears to undergo an abnormal pattern of postnatal devel- +opment that includes early enlargement and ultimately a reduced number of neurons. It will be important to determine in future studies +whether neuron loss in the amygdala is a consistent characteristic of autism and whether cell loss occurs in other brain regions as well. +Key words: autism; neuropathology; stereology; neuronal density; medial temporal lobe; neuroanatomy; amygdaloid complex +Introduction +Autism is a lifelong neurodevelopmental disorder characterized"
+0bdd8f824fa4d4e770e34268a78dca12fb6a135b,Compact Hash Codes for Efficient Visual Descriptors Retrieval in Large Scale Databases,"Compact Hash Codes for Efficient Visual Descriptors +Retrieval in Large Scale Databases +Simone Ercoli, Marco Bertini and Alberto Del Bimbo +Media Integration and Communication Center, Università degli Studi di Firenze +Viale Morgagni 65 - 50134 Firenze, Italy"
+0bdfc21178347ed4f137d4c7d0ba14c996c66b6e,Automated X-Ray Object Recognition Using an Efficient Search Algorithm in Multiple Views,"Automated X-ray object recognition using +n efficient search algorithm in multiple views +Domingo Mery, Vladimir Riffo, Irene Zuccar, Christian Pieringer +Department of Computer Science – Pontificia Universidad Cat´olica de Chile +Av. Vicu˜na Mackenna 4860(143) – Santiago de Chile +http://dmery.ing.puc.cl"
0b4c4ea4a133b9eab46b217e22bda4d9d13559e6,MORF: Multi-Objective Random Forests for face characteristic estimation,"MORF: Multi-Objective Random Forests for Face Characteristic Estimation Dario Di Fina1 MICC - University of Florence @@ -2347,6 +7820,51 @@ Andrew D. Bagdanov2 CVC - Universitat Autonoma de Barcelona Alberto Del Bimbo1 DVMM Lab - Columbia University"
+0b9db62b26b811e8c24eb9edc37901a4b79a897f,Structured Face Hallucination,"Structured Face Hallucination +Chih-Yuan Yang Sifei Liu Ming-Hsuan Yang +Electrical Engineering and Computer Science +University of California at Merced +{cyang35, sliu32,"
+0b6c10ea6bf8a6c254e00fcc2163c4b6fc0f1c3a,"Anti-Spoofing for Text-Independent Speaker Verification: An Initial Database, Comparison of Countermeasures, and Human Performance","Anti-Spoofing for Text-Independent Speaker Verification: An +Initial Database, Comparison of Countermeasures, and Human +Performance +Citation for published version: +Wu, Z, De Leon, P, Demiroglu, C, Khodabakhsh, A, King, S, Ling, Z, Saito, D, Stewart, B, Toda, T, Wester, +M & Yamagishi, J 2016, 'Anti-Spoofing for Text-Independent Speaker Verification: An Initial Database, +Comparison of Countermeasures, and Human Performance' IEEE/ACM Transactions on Audio, Speech, +nd Language Processing, vol. 24, no. 4, pp. 768 - 783. DOI: 10.1109/TASLP.2016.2526653 +Digital Object Identifier (DOI): +0.1109/TASLP.2016.2526653 +Link: +Link to publication record in Edinburgh Research Explorer +Document Version: +Peer reviewed version +Published In: +General rights +Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +nd / or other copyright owners and it is a condition of accessing these publications that users recognise and +bide by the legal requirements associated with these rights. +Take down policy"
+0b4d3e59a0107f0dad22e74054bab1cf1ad9c32e,Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations,"Int J Comput Vis +DOI 10.1007/s11263-016-0981-7 +Visual Genome: Connecting Language and Vision Using +Crowdsourced Dense Image Annotations +· Yuke Zhu1 · Oliver Groth2 · Justin Johnson1 · Kenji Hata1 · +Ranjay Krishna1 +Joshua Kravitz1 · Stephanie Chen1 · Yannis Kalantidis3 · Li-Jia Li4 · +David A. Shamma5 · Michael S. Bernstein1 · Li Fei-Fei1 +Received: 23 February 2016 / Accepted: 12 September 2016 +© The Author(s) 2017. This article is published with open access at Springerlink.com"
+0b2d49cb2d2de06b022e2c636e337d294171dc22,New features and insights for pedestrian detection,"New Features and Insights for Pedestrian Detection +Stefan Walk1 Nikodem Majer1 Konrad Schindler1 Bernt Schiele1,2 +Computer Science Department, TU Darmstadt +MPI Informatics, Saarbr¨ucken"
+0bf2765d431c16de7b8f9c644684e69fa52598eb,Integrating Remote PPG in Facial Expression Analysis Framework,"Integrating Remote PPG in Facial Expression Analysis +Framework +H. Emrah Tasli +Marten den Uyl +Vicarious Perception Technologies, Amsterdam, The Netherlands +Amogh Gudi"
0b8c92463f8f5087696681fb62dad003c308ebe2,On matching sketches with digital face images,"On Matching Sketches with Digital Face Images Himanshu S. Bhatt, Samarth Bharadwaj, Richa Singh, and Mayank Vatsa in local"
@@ -2355,6 +7873,53 @@ Belief Networks CS 229 Project Advisor: Prof. Andrew Ng Adithya Rao Narendran Thiagarajan"
+0babc4af06d210cf38bdf8324c339b6cf3f424fa,A Predictive Model of Patient Readmission Using Combined ICD-9 Codes as Engineered Features,"A Predictive Model of Patient Readmission Using Combined ICD-9 +Codes as Engineered Features"
+0b5c3cf7c8c643cb09d55a08b15de22e134081be,Online Tracking and Offline Recognition Using Scale Invariant Feature Transform,"IJMTES | International Journal of Modern Trends in Engineering and Science ISSN: 2348-3121 +Online Tracking and Offline Recognition Using Scale +Invariant Feature Transform +A. Bahmidha Banu1; Dr. V. Venkatesa kumar2 +PG Scholar, Department of CSE, Anna University Regional Centre, Tamilnadu, +Assistant Professor, Department of CSE, Anna University Regional Centre, , Tamilnadu, +________________________________________________________________________________________________________"
+0bfabcf5c74cc17fe8b5777093699789411868b9,Predictive Tagging of Social Media Images using Unsupervised Learning,"International Journal of Computer Applications (0975 – 8887) +Volume 65– No.24, March 2013 +Predictive Tagging of Social Media Images using +Unsupervised Learning +Nishchol Mishra +Asstt. Professor +School of IT +RGPV, Bhopal +India +Sanjay Silakari, PhD. +Professor, Deptt. Of CSE +UIT- RGPV +Bhopal +India"
+0bc82ec532228427a497ac47391d524e3b4537ae,Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation,"Fluid Annotation: A Human-Machine Collaboration Interface +for Full Image Annotation +Mykhaylo Andriluka∗ +Jasper R. R. Uijlings∗ +Google Research +Z¨urich, Switzerland +Vi(cid:138)orio Ferrari"
+0b4453df81091bcdafedc07b64bea946bf3441b2,Fast and Accurate 3D Face Recognition Using Registration to an Intrinsic Coordinate System and Fusion of Multiple Region Classifiers,"Int J Comput Vis +DOI 10.1007/s11263-011-0426-2 +Fast and Accurate 3D Face Recognition +Using Registration to an Intrinsic Coordinate System and Fusion of Multiple Region +Classifiers +Luuk Spreeuwers +Received: 20 September 2010 / Accepted: 7 February 2011 +© The Author(s) 2011. This article is published with open access at Springerlink.com"
+0b4b6932d5df74b366d9235b40334bc40d719c72,Temporal Ensembling for Semi-Supervised Learning,"Temporal Ensembling for Semi-Supervised Learning +Samuli Laine +NVIDIA +Timo Aila +NVIDIA"
+93cfc6fd29d50fe6589f9506b503f32f6d0372f4,A Face-to-Face Neural Conversation Model,"A Face-to-Face Neural Conversation Model +Hang Chu1,2 Daiqing Li1 Sanja Fidler1,2 +University of Toronto 2Vector Institute +{chuhang1122, daiqing,"
9391618c09a51f72a1c30b2e890f4fac1f595ebd,Globally Tuned Cascade Pose Regression via Back Propagation with Application in 2D Face Pose Estimation and Heart Segmentation in 3D CT Images,"Globally Tuned Cascade Pose Regression via Back Propagation with Application in 2D Face Pose Estimation and Heart Segmentation in 3D @@ -2367,13 +7932,120 @@ April 1, 2015 This work was submitted to ICML 2015 but got rejected. We put the initial submission ”as is” in Page 2 - 11 and add updated contents at the tail. The ode of this work is available at https://github.com/pengsun/bpcpr5."
+93498110032a458fddebfae80d7a93991e11673d,Brownian descriptor: A rich meta-feature for appearance matching,"Brownian descriptor: a Rich Meta-Feature for Appearance Matching +Sławomir B ˛ak +Ratnesh Kumar +François Brémond +INRIA Sophia Antipolis, STARS group +004, route des Lucioles, BP93 +06902 Sophia Antipolis Cedex - France"
93675f86d03256f9a010033d3c4c842a732bf661,Localized Growth and Characterization of Silicon Nanowires,Universit´edesSciencesetTechnologiesdeLilleEcoleDoctoraleSciencesPourl’ing´enieurUniversit´eLilleNord-de-FranceTHESEPr´esent´ee`al’Universit´edesSciencesetTechnologiesdeLillePourobtenirletitredeDOCTEURDEL’UNIVERSIT´ESp´ecialit´e:MicroetNanotechnologieParTaoXULocalizedgrowthandcharacterizationofsiliconnanowiresSoutenuele25Septembre2009Compositiondujury:Pr´esident:TuamiLASRIRapporteurs:ThierryBARONHenriMARIETTEExaminateurs:EricBAKKERSXavierWALLARTDirecteurdeth`ese:BrunoGRANDIDIER
+938566dc8ee83a12d07e4d26bbb75e65ca7963cd,Multi-Scale Singularity Trees (MSSTs),"Multi-Scale Singularity Trees +(MSSTs) +Kerawit Somchaipeng"
936c7406de1dfdd22493785fc5d1e5614c6c2882,Detecting Visual Text,"012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 762–772, Montr´eal, Canada, June 3-8, 2012. c(cid:13)2012 Association for Computational Linguistics"
+93d3f2e546314305e8102538c4714e30e9146858,Image categorization combining neighborhood methods and boosting,"Image Categorization Combining Neighborhood Methods +nd Boosting +Matthew Cooper +FX Palo Alto Laboratory +Palo Alto, CA 94304 USA"
+93610676003ef1dcda3864b236bca3852cb05388,RECOGNIZING ACTIVITIES WITH CLUSTER-TREES OF TRACKLETS 1 Recognizing activities with cluster-trees of tracklets,"Recognizing activities with cluster-trees of tracklets +Adrien Gaidon, Zaid Harchaoui, Cordelia Schmid +To cite this version: +Adrien Gaidon, Zaid Harchaoui, Cordelia Schmid. Recognizing activities with cluster-trees of +tracklets. Richard Bowden and John P. Collomosse and Krystian Mikolajczyk. BMVC 2012 +- British Machine Vision Conference, Sep 2012, Guildford, United Kingdom. BMVA Press, +pp.30.1-30.13, 2012, <10.5244/C.26.30>. <hal-00722955v2> +HAL Id: hal-00722955 +https://hal.inria.fr/hal-00722955v2 +Submitted on 7 Aug 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de"
93cbb3b3e40321c4990c36f89a63534b506b6daf,Learning from examples in the small sample case: face expression recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 35, NO. 3, JUNE 2005 Learning From Examples in the Small Sample Case: Face Expression Recognition Guodong Guo and Charles R. Dyer, Fellow, IEEE"
+93a4c7ac0b09671db8cd3adbe62851d7befc4658,Machine Analysis of Facial Expressions,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+93ed1c9274906f1916d58cd618a9a82858448a3f,Deep Learning for Accurate Population Counting in Aerial Imagery,"Deep Learning for Accurate Population Counting in +Aerial Imagery +Matt Epperson, James Rotenberg, Eric Lo, Sebastian Afshari & Brian Kim"
+931a70ec0bfc1d86894ff37a6f702a033e0129e3,ParlAI: A Dialog Research Software Platform,"ParlAI: A Dialog Research Software Platform +Alexander H. Miller, Will Feng, Adam Fisch, Jiasen Lu, +Dhruv Batra, Antoine Bordes, Devi Parikh and Jason Weston +Facebook AI Research"
+93dce341666b6a57f8888dddb25a3fd37df69b02,Deep Layer Aggregation,"Deep Layer Aggregation +Fisher Yu Dequan Wang +Evan Shelhamer +Trevor Darrell +UC Berkeley"
+934a77d099a38374ef1babe02d95952c089cce5f,Set of texture descriptors for music genre classification,"Set of texture descriptors for music genre classification +Loris Nanni +Yandre Costa +Department of +Information Engineering +University of Padua +viale Gradenigo 6 +5131, Padua, Italy +State University of +Maringa (UEM) +Av. Colombo, 5790 +87020-900, Maringa, +Parana, Brazil"
+93e962f8886eae13b02ad2aa98bdedfbd7e68709,Dual Conditional GANs for Face Aging and Rejuvenation,"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18) +Source： datasets(b)Target: our outputs are a series of images belonging to the same person010Input FaceOutputs2 78x/Age groupy/Personality 2178Non-sequential facial imagesSequential facial imagesFigure1:Anillustrationofourfaceagingandrejuvenationpro-cess.As(a)shows,ourtrainingexamplesarenon-sequentialandun-paired,andweaimtosimultaneouslyrenderaseriesofage-changedfacialimagesofapersonandpreservepersonality,asshownin(b).specificallydescribethechangesoffacesindifferentages.Thesemethodsparametricallymodelshapeandtexturepa-rametersfordifferentfeaturesofeachagegroup,e.g.,mus-cles[Suoetal.,2012],wrinkles[RamanathanandChellappa,2008;Suoetal.,2010]andfacialstructure[RamanathanandChellappa,2006;Lanitisetal.,2002].Ontheotherhand,prototype-basedmethods[KemelmacherShlizermanetal.,2014;Tiddemanetal.,2001]dividefacesintogroupsbyage,andthenconstructanaveragefaceasitsprototypeforeachagegroup.Afterthat,thesemethodscantransferthetexturedifferencebetweentheprototypestotheinputfacialimage.Morerecently,thedeeplearning-basedmethod[Wangetal.,2016;Liuetal.,2017]achievedthestate-of-the-artper-formance.In[Wangetal.,2016],RNNisappliedonthecoefficientsofeigenfacesforagepatterntransition.Itper-formsthegroup-basedlearningwhichrequiresthetrueageoftestingfacestolocalizethetransitionstatewhichmightnotbeconvenient.Inaddition,theseapproachesonlypro-videageprogressionfromyoungerfacetoolderones.Toachieveflexiblebidirectionalagechanges,itmayneedtoretrainthemodelinversely.GenerativeAdversarialNet-"
+935ce31268232b25c9f685128ae0ae9e5c3a0e8e,Implementation of Human detection system using DM 3730,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Impact Factor (2012): 3.358 +Implementation of Human detection system using +DM3730 +Amaraneni Srilaxmi1, Shaik Khaddar Sharif2 +VNR Vignana Jyothi Institute of Engineering & Technology, Bachupally, Hyderabad, India +VNR Vignana Jyothi Institute of Engineering & Technology, Bachupally, Hyderabad, India +digital +ontent management,"
+93798ead90afe86636ca582a92cadd846905a95d,Learning Visual Classifiers From Limited Labeled Images,
+930663a0812a7a53963563b647c5957807d3d97d,A unified view of non-monotonic core selection and application steering in heterogeneous chip multiprocessors,"A Unified View of Non-monotonic Core Selection +nd Application Steering in Heterogeneous +Chip Multiprocessors +Sandeep Navada*, Niket K. Choudhary*, +Salil V. Wadhavkar* +CPU Design Center +Qualcomm +Raleigh, NC, USA +{snavada, niketc,"
+930a6ea926d1f39dc6a0d90799d18d7995110862,Privacy-preserving photo sharing based on a secure JPEG,"Privacy-Preserving Photo Sharing +ased on a Secure JPEG +Lin Yuan, Pavel Korshunov, and Touradj Ebrahimi +Multimedia Signal Processing Group, EPFL, Lausanne, Switzerland +Email: {lin.yuan, pavel.korshunov,"
94b9c0a6515913bad345f0940ee233cdf82fffe1,Face Recognition using Local Ternary Pattern for Low Resolution Image,"International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Impact Factor (2012): 3.358 @@ -2382,6 +8054,19 @@ Low Resolution Image Vikas1, Amanpreet Kaur2 Research Scholar, CGC Group of Colleges, Gharuan, Punjab, India Assistant Professor, Department of Computer Science Engineering, Chandigarh University, Gharuan, Punjab, India"
+94826cb68980e3b89118569c93cfd36f3945fa99,Computer face-matching technology using two-dimensional photographs accurately matches the facial gestalt of unrelated individuals with the same syndromic form of intellectual disability,"Dudding-Byth et al. BMC Biotechnology (2017) 17:90 +DOI 10.1186/s12896-017-0410-1 +Open Access +R ES EAR CH A R T I C LE +Computer face-matching technology using +two-dimensional photographs accurately +matches the facial gestalt of unrelated +individuals with the same syndromic form +of intellectual disability +Tracy Dudding-Byth1,2,3,11*† +Susan M. White5,6, John Attia3,4, Han Brunner7, Bert de Vries7, David Koolen7, Tjitske Kleefstra7, Seshika Ratwatte4,8, +Carlos Riveros3, Steve Brain9 and Brian C. Lovell9,10 +, Anne Baxter1†, Elizabeth G. Holliday3,4, Anna Hackett1,4,11, Sheridan O’Donnell1,"
94eeae23786e128c0635f305ba7eebbb89af0023,On the Emergence of Invariance and Disentangling in Deep Representations,"Journal of Machine Learning Research 18 (2018) 1-34 Submitted 01/17; Revised 4/18; Published 6/18 Emergence of Invariance and Disentanglement @@ -2395,6 +8080,29 @@ Department of Computer Science University of California Los Angeles, CA 90095, USA Editor: Yoshua Bengio"
+940ab36a8b2cdf6cb6a08093bd382ad375717942,Human violence recognition and detection in surveillance videos,"Human Violence Recognition and Detection in Surveillance Videos +Piotr Bilinski +nd Francois Bremond +INRIA Sophia Antipolis, STARS team +004 Route des Lucioles, BP93, 06902 Sophia Antipolis, France"
+9499b8367a84fccb3651a95e4391d6e17fd92ec5,Face Recognition Issues in a Border Control Environment,"Face Recognition Issues in a Border Control +Environment +Marijana Kosmerlj, Tom Fladsrud, Erik Hjelm˚as, and Einar Snekkenes +Department of Computer Science and Media Technology +NISlab +Gjøvik University College +P. O. Box 191, N-2802 Gjøvik, Norway"
+942bb63e78d9edfe3b8d0a4bf9a3511c736a6930,"Implementing Efficient, Portable Computations for Machine Learning","Implementing Efficient, Portable Computations for Machine +Learning +Matthew Walter Moskewicz +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2017-37 +http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-37.html +May 9, 2017"
+9432e1157f252ee626511b2270126436b0e80b73,A set theoretic approach to object-based image restoration,"Image Processing: Algorithms and Systems IV, edited by Edward R. Dougherty, +Jaakko T. Astola, Karen O. Egiazarian, Proc. of SPIE-IS&T Electronic Imaging, +SPIE Vol. 5672 © 2005 SPIE and IS&T · 0277-786X/05/$15"
944faf7f14f1bead911aeec30cc80c861442b610,Action Tubelet Detector for Spatio-Temporal Action Localization,"Action Tubelet Detector for Spatio-Temporal Action Localization Vicky Kalogeiton1,2 Philippe Weinzaepfel3 @@ -2407,6 +8115,11 @@ Zhiwu Huang, Student Member, IEEE, Shiguang Shan, Senior Member, IEEE, Ruiping Wang, Member, IEEE, Haihong Zhang, Member, IEEE, Shihong Lao, Member, IEEE, Alifu Kuerban, nd Xilin Chen, Senior Member, IEEE"
+940a675de8a48b54bac6b420f551529d2bc53b99,"Advances , Challenges , and Opportunities in Automatic Facial Expression Recognition","Advances, Challenges, and Opportunities in +Automatic Facial Expression Recognition +Brais Martinez and Michel F. Valstar"
+9434524669777d281a8a7358f20181c9e157942e,VSEM: An open library for visual semantics representation,"Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pages 187–192, +Sofia, Bulgaria, August 4-9 2013. c(cid:13)2013 Association for Computational Linguistics"
948af4b04b4a9ae4bff2777ffbcb29d5bfeeb494,Face Recognition From Single Sample Per Person by Learning of Generic Discriminant Vectors,"Available online at www.sciencedirect.com Procedia Engineering 41 ( 2012 ) 465 – 472 International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012) @@ -2415,6 +8128,70 @@ Generic Discriminant Vectors Fadhlan Hafiza*, Amir A. Shafieb, Yasir Mohd Mustafahb Faculty of Electrical Engineering, University of Technology MARA, Shah Alam, 40450 Selangor, Malaysia Faculty of Engineering, International Islamic University, Jalan Gombak, 53100 Kuala Lumpur, Malaysia"
+947399fef66bd8c536c6f784a0501b34e4e094bf,Towards Recovery of Conditional Vectors from Conditional Generative Adversarial Networks,"Towards Recovery of Conditional Vectors from +Conditional Generative Adversarial Networks +Sihao Ding +Andreas Wallin +{sihao.ding,"
+9458642e7645bfd865911140ee8413e2f5f9fcd6,Efficient Multiple People Tracking Using Minimum Cost Arborescences,"Efficient Multiple People Tracking Using +Minimum Cost Arborescences +Roberto Henschel1, Laura Leal-Taix´e2, Bodo Rosenhahn1 +Institut f¨ur Informationsverarbeitung, Leibniz Universit¨at Hannover, +Institute of Geodesy and Photogrammetry, ETH Zurich,"
+949079cc466e875df1ee6bd6590052ba382a35cf,0 Large-Scale Face Image Retrieval :,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+94686d5df14875ed800a9f710bfa43ba4eb19b75,Occlusion Handling for Pedestrian Tracking Using Partial Object Template-based Component Particle Filter,"IADIS International Journal on Computer Science and Information Systems +Vol. 8, No. 2, pp. 40-50 +ISSN: 1646-3692 +OCCLUSION HANDLING FOR PEDESTRIAN +TRACKING USING PARTIAL OBJECT +TEMPLATE-BASED COMPONENT PARTICLE +FILTER +Daw-Tung Lin. Department of Computer Science and Information Engineering, National Taipei +University, Taiwan. +Yen-Hsiang Chang. Department of Computer Science and Information Engineering, National Taipei +University, Taiwan."
+941166547968081463398c9eb041f00eb04304f7,Structure-Preserving Sparse Decomposition for Facial Expression Analysis,"Structure-Preserving Sparse Decomposition for +Facial Expression Analysis +Sima Taheri, Student Member, IEEE, Qiang Qiu, Student Member, IEEE, and Rama Chellappa, Fellow, IEEE"
+940865fc3f7ee5b386c4188c231eb6590db874e9,Security and Surveillance System for Drivers Based on User Profile and learning systems for Face Recognition,"Network Protocols and Algorithms +ISSN 1943-3581 +015, Vol. 7, No. 1 +Security and Surveillance System for Drivers based on +User Profile and Learning Systems for Face +Recognition +Loubna Cherrat +Mathematic and Application Laboratory, FSTT of Tangier +Tangier (Morocco) +Tel: 06-64-43-39-18 E-mail: +Mostafa Ezziyyani +Mathematic and Application Laboratory, FSTT of Tangier +Tangier (Morocco) +Tel: 06-61-63-03-01 E-mail: +Annas EL Mouden +Mathematic and Application Laboratory, FSTT of Tangier +Tangier (Morocco) +Tel: 06-66-63-73-63 E-mail: +Mohammed Hassar +Mathematic and Application Laboratory, FSTT of Tangier"
9441253b638373a0027a5b4324b4ee5f0dffd670,A Novel Scheme for Generating Secure Face Templates Using BDA,"A Novel Scheme for Generating Secure Face Templates Using BDA Shraddha S. Shinde @@ -2424,19 +8201,111 @@ Associate Professor, Department of Computer MCERC, Nashik (M.S.), India e-mail:"
+948853c269cf97251ba5082db0481ce6f96cf886,Efficient Distributed Training of Vehicle Vision Systems,"Efficient Distributed Training of Vehicle Vision Systems +Sung-Li Chiang +Xinlei Pan +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2016-195 +http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-195.html +December 11, 2016"
94a11b601af77f0ad46338afd0fa4ccbab909e82,"Title of dissertation : EFFICIENT SENSING , SUMMARIZATION AND CLASSIFICATION OF VIDEOS",
+0e23229289b1fbea14bc425718bc0a227d100b8e,Survey of Recent Advances in Visual Question Answering,"Survey of Recent Advances in Visual Question Answering +Supriya Pandhre∗ +Indian Institute of Technology Hyderabad +Hyderabad, India +Shagun Sodhani +Adobe Systems +Noida, India"
0efdd82a4753a8309ff0a3c22106c570d8a84c20,Lda with Subgroup Pca Method for Facial Image Retrieval,"LDA WITH SUBGROUP PCA METHOD FOR FACIAL IMAGE RETRIEVAL Wonjun Hwang, Tae-Kyun Kim, Seokcheol Kee Human Computer Interaction Lab., Samsung Advanced Institute of Technology, Korea."
+0ed78b9562661c550e382ed30de252d877a04cdc,An Evaluation of Video-to-Video Face Verification,"An Evaluation of Video-to-Video Face Verification +Norman Poh, Member, IEEE, Chi Ho Chan, Josef Kittler, Sébastien Marcel, Christopher Mc Cool, +Enrique Argones Rúa, José Luis Alba Castro, Mauricio Villegas, Student Member, IEEE, Roberto Paredes, +Vitomir ˇStruc, Member, IEEE, Nikola Paveˇsic´, Albert Ali Salah, Hui Fang, and Nicholas Costen +features,"
+0ec17d929f62660fb3d1bcdd791f9639034f5344,How Do We Evaluate Facial Emotion Recognition?,"Psychology & Neuroscience +016, Vol. 9, No. 2, 153–175 +983-3288/16/$12.00 +© 2016 American Psychological Association +http://dx.doi.org/10.1037/pne0000047 +How Do We Evaluate Facial Emotion Recognition? +Ana Idalina de Paiva-Silva +Universidade de Brasília and Universidade Federal +de Goiás +Marta Kerr Pontes, +Juliana Silva Rocha Aguiar, and +Wânia Cristina de Souza +Universidade de Brasília +The adequate interpretation of facial expressions of emotion is crucial for social +functioning and human interaction. New methods are being applied, and a review of the +methods that are used to evaluate facial emotion recognition is timely for the field. An +extensive review was conducted using the Web of Science, PsycINFO, and PubMed +databases. The following keywords were used to identify articles that were published +within the past 20 years: emotion recognition, face, expression, and assessment. The +initial search yielded 291 articles. After applying the exclusion criteria, 115 articles"
+0e9f7d8554e065a586163845dd2bfba26e55cefb,Registration of 3D Face Scans with Average Face Models,"Registration of 3D Face Scans with Average Face Models +Albert Ali Salah1,2, Ne¸se Aly¨uz1, Lale Akarun1 +{salah, nese.alyuz, +Bo˘gazi¸ci University, +4342 Bebek, ˙Istanbul, Turkey +Phone: +90 212 359 4523-24 +Fax: +90 212 287 2461 +Centrum voor Wiskunde en Informatica, +Kruislaan 413, 1098 SJ, 94079, The Netherlands +Phone: +31 020 592 4214 +Fax: +31 020 592 4199"
+0ef40a21edf2b48c73fd51c21d213ee69ca30a4b,Hidden Markov model as a framework for situational awareness,
0eac652139f7ab44ff1051584b59f2dc1757f53b,Efficient Branching Cascaded Regression for Face Alignment under Significant Head Rotation,"Efficient Branching Cascaded Regression for Face Alignment under Significant Head Rotation Brandon M. Smith Charles R. Dyer University of Wisconsin–Madison"
+0ee1916a0cb2dc7d3add086b5f1092c3d4beb38a,The Pascal Visual Object Classes (VOC) Challenge,"Int J Comput Vis (2010) 88: 303–338 +DOI 10.1007/s11263-009-0275-4 +The PASCAL Visual Object Classes (VOC) Challenge +Mark Everingham · Luc Van Gool · +Christopher K. I. Williams · John Winn · +Andrew Zisserman +Received: 30 July 2008 / Accepted: 16 July 2009 / Published online: 9 September 2009 +© Springer Science+Business Media, LLC 2009"
+0e13f7fc698cbe78ddbf3412b13ca27a4d878fa8,Greater need to belong predicts a stronger preference for extraverted faces,"See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/306357929 +Greater need to belong predicts a stronger +preference for extraverted faces ☆ +Article in Personality and Individual Differences · January 2017 +DOI: 10.1016/j.paid.2016.08.012 +CITATION +authors, including: +READS +Mitch Brown +University of Southern Mississippi +6 PUBLICATIONS 5 CITATIONS +SEE PROFILE +Some of the authors of this publication are also working on these related projects: +Metaphor and Disease View project +Limbal Rings View project +All content following this page was uploaded by Mitch Brown on 10 November 2016. +The user has requested enhancement of the downloaded file."
+0e031312cb6e1634e3115e428505e2be9ef46b75,Explicit Knowledge-based Reasoning for Visual Question Answering,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +giraffe people people Attributes: glass house room standing walking wall zoo Scenes: museum indoor Visual Question: How many giraffes are there in the image? Answer: Two. Common-Sense Question: Is this image related to zoology? Answer: Yes. Reason: Object/Giraffe --> Herbivorous animals --> Animal --> Zoology; Attribute/Zoo --> Zoology. KB-Knowledge Question: What are the common properties between the animal in this image and zebra? Answer: Herbivorous animals; Animals; Megafauna of Africa. Figure1:ArealexampleoftheproposedKB-VQAdatasetandtheresultsgivenbyAhab,theproposedVQAapproach.Ourapproachanswersquestionsbyextractingseveraltypesofvisualconceptsfromanimageandaligningthemtolarge-scalestructuredknowl-edgebases.Apartfromanswers,ourapproachcanalsoproviderea-sonsandexplanationsforcertaintypesofquestions.itisansweringthequestionbasedonimageinformation,orjusttheprevalenceofaparticularanswerinthetrainingset.Thesecondproblemisthatbecausethemodelistrainedonindividualquestion/answerpairs,therangeofquestionsthatcanbeaccuratelyansweredislimited.Answeringgeneralquestionsposedbyhumansaboutimagesinevitablyrequiresreferencetoadiversevarietyofinformationnotcontainedintheimageitself.CapturingsuchlargeamountofinformationwouldrequireanimplausiblylargeLSTM,andacompletelyimpracticalamountoftrainingdata.Thethird,andmajor,problemwiththeLSTMapproachisthatitisincapableofex-plicitreasoningexceptinverylimitedsituations[Rockt¨ascheletal.,2016].OurmaincontributionisamethodwecallAhab1foran-sweringawidevarietyofquestionsaboutimagesthatrequire1Ahab,thecaptaininthenovelMobyDick,iseitherabrilliantvisionary,oradeludedfanatic,dependingonyourperspective."
+0eb45876359473156c0d4309f548da63470d30ee,A Deeply-Initialized Coarse-to-fine Ensemble of Regression Trees for Face Alignment,"A Deeply-initialized Coarse-to-fine Ensemble of +Regression Trees for Face Alignment +Roberto Valle1[0000−0003−1423−1478], Jos´e M. +Buenaposada2[0000−0002−4308−9653], Antonio Vald´es3, and Luis Baumela1 +Univ. Polit´ecnica de Madrid, Spain. +Univ. Rey Juan Carlos, Spain. +Univ. Complutense de Madrid, Spain."
0e50fe28229fea45527000b876eb4068abd6ed8c,Angle Principal Component Analysis,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
0eff410cd6a93d0e37048e236f62e209bc4383d1,Learning discriminative MspLBP features based on Ada-LDA for multi-class pattern classification,"Anchorage Convention District May 3-8, 2010, Anchorage, Alaska, USA 978-1-4244-5040-4/10/$26.00 ©2010 IEEE"
+0ecaabbf846bbc78c91bf7ff71b998b61c0082d8,Automated Visual Fin Identification of Individual Great White Sharks,"Noname manuscript No. +(will be inserted by the editor) +Automated Visual Fin Identification +of Individual Great White Sharks +Benjamin Hughes and Tilo Burghardt +Received: date / Accepted: date"
0ee737085af468f264f57f052ea9b9b1f58d7222,SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination,"SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination Chih-Chung Hsu, Member, IEEE, Chia-Wen Lin, Fellow, IEEE, Weng-Tai Su, Student Member, IEEE, @@ -2448,11 +8317,35 @@ Massimo Tistarelli, Senior Member, IEEE, Yunlian Sun, and Norman Poh, Member, IE 0e986f51fe45b00633de9fd0c94d082d2be51406,"Face detection, pose estimation, and landmark localization in the wild","Face Detection, Pose Estimation, and Landmark Localization in the Wild Xiangxin Zhu Deva Ramanan Dept. of Computer Science, University of California, Irvine"
+0e36bf238d2db6c970ade0b5f68811ed6debc4e8,Recognizing Partial Biometric Patterns,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 4, AUGUST 2018 +Recognizing Partial Biometric Patterns +Lingxiao He, Student Member, IEEE, Zhenan Sun, Member, IEEE, Yuhao Zhu and Yunbo Wang"
0e49a23fafa4b2e2ac097292acf00298458932b4,Unsupervised Detection of Outlier Images Using Multi-Order Image Transforms,"Theory and Applications of Mathematics & Computer Science 3 (1) (2013) 13–31 Unsupervised Detection of Outlier Images Using Multi-Order Image Transforms Lior Shamira,∗ Lawrence Technological University, 21000 W Ten Mile Rd., Southfield, MI 48075, United States."
+0e95f68171b27621a39e393afb7c74ef1506fe85,Content Based Image Retrieval Using Enhanced Local Tetra Patterns,"CONTENT BASED IMAGE RETRIEVAL USING +ENHANCED LOCAL TETRA PATTERNS +Divya Gupta1, Anjali Jindal2 +Assistant Professor, Computer Science Department +SRM University, Delhi NCR Campus, India +M.Tech Student (Computer Science and Engineering) +SRM University, Delhi NCR Campus, India"
+0ed91520390ebdee13a0ac13d028f65d959bdc10,Hard Example Mining with Auxiliary Embeddings,"Hard Example Mining with Auxiliary Embeddings +Evgeny Smirnov +Speech Technology Center +Aleksandr Melnikov +ITMO University +Andrei Oleinik +ITMO University +melnikov +Elizaveta Ivanova +Ilya Kalinovskiy +Speech Technology Center +Speech Technology Center +Eugene Luckyanets +ITMO University"
0e78af9bd0f9a0ce4ceb5f09f24bc4e4823bd698,Spontaneous Subtle Expression Recognition: Imbalanced Databases & Solutions,"Spontaneous Subtle Expression Recognition: Imbalanced Databases & Solutions (cid:63) Anh Cat Le Ngo1, Raphael Chung-Wei Phan1, John See2 @@ -2461,6 +8354,13 @@ Multimedia University (MMU), Cyberjaya, Malaysia Faculty of Computing & Informatics, Multimedia University (MMU), Cyberjaya, Malaysia"
0e2ea7af369dbcaeb5e334b02dd9ba5271b10265,Multi-Level Feature Abstraction from Convolutional Neural Networks for Multimodal Biometric Identification,
+0e7fdc0b03a1481b2fa1b5d592125f41b6cb7ad7,Dual CNN Models for Unsupervised Monocular Depth Estimation,"Dual CNN Models for Unsupervised Monocular Depth Estimation +Computer Vision Group, +Indian Institute of Information Technology, Sri City, +Vamshi Krishna Repala +Shiv Ram Dubey +Andhra Pradesh-517646, India +vamshi.r14,"
0e7c70321462694757511a1776f53d629a1b38f3,2012 Proceedings of the Performance Metrics for Intelligent Systems (PerMI'12) Workshop,"NIST Special Publication 1136 012 Proceedings of the Performance Metrics for Intelligent @@ -2469,6 +8369,44 @@ Rajmohan Madhavan Elena R. Messina Brian A. Weiss http://dx.doi.org/10.6028/NIST.SP.1136"
+0e5640677feb2e1d78639b516f7977e80d9d394f,Volume-based Human Re-identification with RGB-D Cameras,"Cosar, S., Coppola, C. and Bellotto, N. +Volume-based Human Re-identification with RGB-D Cameras. +In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP, pages +89-397 +ISBN: 978-989-758-225-7 +Copyright c(cid:13) 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved"
+0efb7d1413ada560ab1aee1ea4cc94d80737e662,Performance Analysis of Eye localization Methods for Real Time Vision Interface using Low Grade Video Camera,"International Journal of Computer Applications (0975 – 8887) +Volume 114 – No. 2, March 2015 +Performance Analysis of Eye localization Methods for +Real Time Vision Interface using Low Grade Video +Krupa Jariwala +Assistant Professor +Computer Engineering Department +SVNIT, Surat +Camera +Upena Dalal, Ph.D. +Associate Professor +Electronics Engineering Department +SVNIT, Surat"
+0edd3517579a110da989405309e4235e47dd8937,Performance and security analysis of Gait-based user authentication,"Performance and Security Analysis +of Gait-based User Authentication +Doctoral Dissertation by +Davrondzhon Gafurov +Submitted to the Faculty of Mathematics and Natural Sciences at the +University of Oslo in partial fulfillment of the requirements for the degree +Philosophiae Doctor (PhD) in Computer Science"
+607850dc8e640c25f027f2eee202dee5605cf27c,A Survey on Face Detection and Recognition Techniques in Different Application Domain,"I.J. Modern Education and Computer Science, 2014, 8, 34-44 +Published Online August 2014 in MECS (http://www.mecs-press.org/) +DOI: 10.5815/ijmecs.2014.08.05 +A Survey on Face Detection and Recognition +Techniques in Different Application Domain +Subrat Kumar Rath, Siddharth Swarup Rautaray +School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India +related +technology +recognition, +to biometric science +the popularity and"
600025c9a13ff09c6d8b606a286a79c823d89db8,A Review on Linear and Non-linear Dimensionality Reduction Techniques,"Machine Learning and Applications: An International Journal (MLAIJ) Vol.1, No.1, September 2014 A REVIEW ON LINEAR AND NON-LINEAR DIMENSIONALITY REDUCTION @@ -2480,9 +8418,64 @@ Ultra College of Engineering and Technology for Women,India. Assistant Professor Department of Computer Science and Engineering Vickram College of Engineering, Enathi, Tamil Nadu, India."
+602ff4fd0f5bd10c9fb971ecd2317e542f070883,Object Detection from the Satellite Images using Divide and Conquer Model,"SSRG International Journal of Computer Science and Engineering (SSRG-IJCSE) – volume1 issue10 Dec 2014 +Object Detection from the Satellite Images +using Divide and Conquer Model +Lakhwinder Kaur, Guru Kashi University +Er.Vinod Kumar Sharma (Assistant professor), Guru Kashi University"
+60fb007eef153fdf9c3d6620c419bef1c657c555,A soft-biometrics dataset for person tracking and re-identification,"A Soft-Biometrics Dataset for Person Tracking and Re-Identification +Arne Schumann, Eduardo Monari +Fraunhofer Institute for Optronics, System Technologies and Image Exploitation +{arne.schumann,"
+60f7de07de4d090990120483bd5407369b29a120,ℓ₁-Norm Heteroscedastic Discriminant Analysis Under Mixture of Gaussian Distributions.,"L1-Norm Heteroscedastic Discriminant Analysis +under Mixture of Gaussian Distributions +Wenming Zheng, Member, IEEE, Cheng Lu, Zhouchen Lin, Fellow, IEEE, Tong Zhang, Zhen Cui, Wankou Yang"
+60ec284f67c1012419e5dea508d1bae4bc144bb2,Curvelet Based Multiresolution Analysis of Face Images for Recognition using Robust Local Binary Pattern Descriptor,"Proc. of Int. Conf. on Recent Trends in Signal Processing, Image Processing and VLSI, ICrtSIV +Curvelet Based Multiresolution Analysis of Face +Images for Recognition using Robust Local Binary +Pattern Descriptor +Nagaraja S. and Prabhakar C.J +Department of P.G. Studies and Research in Computer Science, +Kuvempu University, Karnataka, India +Email: { nagarajas27, psajjan"
+604a4f7c0958c5cac017b853a7d0f5f5b4a4c509,Can We Teach Empathy ? Techniques Using Standardized Patients to Assist Learners with Empathy ( Submission # 1039 ) Gayle,
+60ea05df719973ac4d9d70d3141e671131a55db5,A Practical Subspace Approach To Landmarking,"A Practical Subspace Approach To Landmarking +Signals and systems group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of +G. M. Beumer, and R.N.J. Veldhuis +Twente, Enschede, The Netherlands +Email:"
60e2b9b2e0db3089237d0208f57b22a3aac932c1,Frankenstein: Learning Deep Face Representations Using Small Data,"Frankenstein: Learning Deep Face Representations using Small Data Guosheng Hu, Member, IEEE, Xiaojiang Peng, Yongxin Yang, Timothy M. Hospedales, and Jakob Verbeek"
+6097c33a382c62a44379926ee96b23b51dba49c4,From Depth Data to Head Pose Estimation: a Siamese approach,"From Depth Data to Head Pose Estimation: a Siamese approach +Marco Venturelli, Guido Borghi, Roberto Vezzani, Rita Cucchiara +University of Modena and Reggio Emilia, DIEF +{marco.venturelli, guido.borghi, roberto.vezzani, +Via Vivarelli 10, Modena, Italy +Keywords: +Head Pose Estimation, Deep Learning, Depth Maps, Automotive"
+6025f0761024006e0ea5782a7cea29ed69231fbf,Neural Mechanisms of Qigong Sensory Training Massage for Children With Autism Spectrum Disorder: A Feasibility Study,"Original Article +Neural Mechanisms of Qigong Sensory +Training Massage for Children With Autism +Spectrum Disorder: A Feasibility Study +Global Advances in Health and Medicine +Volume 7: 1–10 +! The Author(s) 2018 +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/2164956118769006 +journals.sagepub.com/home/gam +Kristin K Jerger, MD, LMBT1, Laura Lundegard2, Aaron Piepmeier, PhD1, +Keturah Faurot, PA, MPH, PhD1, Amanda Ruffino, BA1, +Margaret A Jerger, PhD, CCC-SLP1, and Aysenil Belger, PhD3"
+60ab5c64375c4f5f8949a184fd9bfb68778ae6ea,Understanding and Verifying Kin Relationships in a Photo,"N. S. Syed et al Int. Journal of Engineering Research and Applications www.ijera.com +ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.1225-1229 +RESEARCH ARTICLE OPEN ACCESS +Understanding and Verifying Kin Relationships in a Photo +Ms.N.S.Syed, 2mr.B.K.Patil, 3mr.Zafar Ul Hasan +(Department of Computer Science, Everest College of Engg. & Tech., Aurangabad, M.S., India ) +(Department of Computer Science, Everest College of Engg. & Tech., Aurangabad, M.S., India ) +(Department of Computer Science, Sandip Institute of Technology and Research Centre, Nashik, M.S,India)"
60ce4a9602c27ad17a1366165033fe5e0cf68078,Combination of Face Regions in Forensic Scenarios.,"TECHNICAL NOTE DIGITAL & MULTIMEDIA SCIENCES J Forensic Sci, 2015 @@ -2492,6 +8485,26 @@ Pedro Tome,1 Ph.D.; Julian Fierrez,1 Ph.D.; Ruben Vera-Rodriguez,1 Ph.D.; and Ja Ph.D. Combination of Face Regions in Forensic Scenarios*"
+609ff585468ad0faba704dde1a69edb9f847c201,LogDet Rank Minimization with Application to Subspace Clustering,"Hindawi Publishing Corporation +Computational Intelligence and Neuroscience +Volume 2015, Article ID 824289, 10 pages +http://dx.doi.org/10.1155/2015/824289 +Research Article +LogDet Rank Minimization with Application to +Subspace Clustering +Zhao Kang,1 Chong Peng,1 Jie Cheng,2 and Qiang Cheng1 +Computer Science Department, Southern Illinois University, Carbondale, IL 62901, USA +Department of Computer Science and Engineering, University of Hawaii at Hilo, Hilo, HI 96720, USA +Correspondence should be addressed to Qiang Cheng; +Received 25 March 2015; Revised 15 June 2015; Accepted 18 June 2015 +Academic Editor: Jos´e Alfredo Hernandez +Copyright © 2015 Zhao Kang et al. This is an open access article distributed under the Creative Commons Attribution License, +which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +Low-rank matrix is desired in many machine learning and computer vision problems. Most of the recent studies use the nuclear +norm as a convex surrogate of the rank operator. However, all singular values are simply added together by the nuclear norm, and +thus the rank may not be well approximated in practical problems. In this paper, we propose using a log-determinant (LogDet) +function as a smooth and closer, though nonconvex, approximation to rank for obtaining a low-rank representation in subspace +lustering. Augmented Lagrange multipliers strategy is applied to iteratively optimize the LogDet-based nonconvex objective"
60efdb2e204b2be6701a8e168983fa666feac1be,Transferring Deep Object and Scene Representations for Event Recognition in Still Images,"Int J Comput Vis DOI 10.1007/s11263-017-1043-5 Transferring Deep Object and Scene Representations for Event @@ -2500,14 +8513,101 @@ Limin Wang1 · Zhe Wang2 · Yu Qiao3 · Luc Van Gool1 Received: 31 March 2016 / Accepted: 1 September 2017 © Springer Science+Business Media, LLC 2017"
+60189e2b592056d43a28b6ffa491867f793ebe1e,Bağlamın Hiyerarşik Doğası,"Ba˘glamın Hiyerar¸sik Do˘gası +Fethiye Irmak Do˘gan, Sinan Kalkan +Bilgisayar Mühendisli˘gi Bölümü +Orta Do˘gu Teknik Üniversitesi +Ankara, Türkiye +Email: +Özetçe —Ba˘glam, insan bili¸si için oldukça elzemdir ve du- +ru¸s, davranı¸s, konu¸sma biçimi gibi gündelik insan hayatı için +önemli pek çok sürece etki etmektedir. Yakın zamanda hay- +tımızda yer edinmesini bekledi˘gimiz robotların da i¸slevlerini +yerine do˘gru ve verimli bir biçimde getirebilmesi için, ba˘glamı +lgılama ve kullanma yetene˘gine sahip olması beklenmektedir. +Ancak ba˘glam, yapay veya do˘gal bili¸s için ne kadar elzem +olsa da, ba˘glamın yapısı yeterince çalı¸sılmı¸s ve çözümlenebilmi¸s +de˘gildir. Bu çalı¸smada, ba˘glamın çözümlenememi¸s ö˘gelerinden +ir tanesine, ba˘glamın yapısının hiyerar¸sik olup olmadı˘gına +odaklanılmaktadır. Yaptı˘gımız irdelemeye göre, ba˘glama ait +muhtelif sosyal, uzamsal ve zamansal özellikler ve olgular, +a˘glamın hiyerar¸sik bir yapıya sahip oldu˘gunu önermektedir. Bu +konudaki sinirbilim, psikoloji bulguları ve bili¸simsel modelleme"
60824ee635777b4ee30fcc2485ef1e103b8e7af9,Cascaded Collaborative Regression for Robust Facial Landmark Detection Trained Using a Mixture of Synthetic and Real Images With Dynamic Weighting,"Cascaded Collaborative Regression for Robust Facial Landmark Detection Trained using a Mixture of Synthetic and Real Images with Dynamic Weighting Zhen-Hua Feng, Student Member, IEEE, Guosheng Hu, Student Member, IEEE, Josef Kittler, Life Member, IEEE, William Christmas, and Xiao-Jun Wu"
+60c06e5884a672e0ba3bf1d3488307489583b7e5,Audiovisual speech perception and eye gaze behavior of adults with asperger syndrome.,"J Autism Dev Disord +DOI 10.1007/s10803-011-1400-0 +O R I G I N A L P A P E R +Audiovisual Speech Perception and Eye Gaze Behavior of Adults +with Asperger Syndrome +Satu Saalasti • Jari Ka¨tsyri • Kaisa Tiippana • +Mari Laine-Hernandez • Lennart von Wendt • +Mikko Sams +Ó Springer Science+Business Media, LLC 2011"
+60c12b3a1bfd547f5a165c95774a1a17d18a5941,People recognition by mobile robots,"People Recognition by Mobile Robots +Grzegorz Cielniak and Tom Duckett +Centre for Applied Autonomous Sensor Systems +Dept. of Technology, ¨Orebro University +SE-70182 ¨Orebro, Sweden +Phone: +46 19 30 11 13, +46 19 30 34 83 +Email: +Telefax: +46 19 30 34 63"
+60bc358296ae11ac8f11286bba0a49ac7e797d26,Diverse Image-to-Image Translation via Disentangled Representations,"Diverse Image-to-Image Translation via +Disentangled Representations +Hsin-Ying Lee(cid:63)1, Hung-Yu Tseng(cid:63)1, Jia-Bin Huang2, Maneesh Singh3, +Ming-Hsuan Yang1,4 +University of California, Merced 2Virginia Tech 3Verisk Analytics 4Google Cloud +Photo to van Gogh +Content +Attribute Generated +Winter to summer +Photograph to portrait +Input +Output +Input +Output +Fig. 1: Unpaired diverse image-to-image translation. (Lef t) Our model +learns to perform diverse translation between two collections of images without +ligned training pairs. (Right) Example-guided translation."
+60d75d32d345c519fa5c0d8d6b6eb62e633a8d13,Person reidentification by semisupervised dictionary rectification learning with retraining module,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/13/2018 +Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +PersonreidentificationbysemisuperviseddictionaryrectificationlearningwithretrainingmoduleHongyuanWangZongyuanDingJiZhangSuolanLiuTongguangNiFuhuaChenHongyuanWang,ZongyuanDing,JiZhang,SuolanLiu,TongguangNi,FuhuaChen,“Personreidentificationbysemisuperviseddictionaryrectificationlearningwithretrainingmodule,”J.Electron.Imaging27(4),043043(2018),doi:10.1117/1.JEI.27.4.043043."
+60ffc8db53b02e95d852f5a06f97686486f72195,Video Matching Using DC-image and Local Features,"Video Matching Using DC-image and Local +Features +Saddam Bekhet, Amr Ahmed and Andrew Hunter"
+6084cac63fe6fcc1436610f1db4a3764ec2e3692,TST/BTD: An End-to-End Visual Recognition System,"TST/BTD: An End-to-End Visual Recognition System +Taehee Lee +Stefano Soatto +Technical Report UCLA-CSD100008 +February 8, 2010, Revised March 18, 2010"
+60161c712a491764b6f227d72e9d01e956caa873,"Wrong Today, Right Tomorrow: Experience-Based Classification for Robot Perception","Wrong Today, Right Tomorrow: +Experience-Based Classification for +Robot Perception +Jeffrey Hawke†, Corina Gur˘au†, Chi Hay Tong and Ingmar Posner"
+60cc2e8abc20c145727e7089c55bdba5722436d0,Higher Order Matching for Consistent Multiple Target Tracking,"Higher Order Matching for Consistent Multiple Target Tracking +Chetan Arora +Amir Globerson +School of Computer Science and Engineering +The Hebrew University +http://www.cs.huji.ac.il/˜chetan/"
+604d7533bdcfb06f4ae217a2cd9fd2e1467192f8,Gender Recognition using Hog with Maximized Inter-Class Difference,
60cdcf75e97e88638ec973f468598ae7f75c59b4,Face Annotation Using Transductive Kernel Fisher Discriminant,"Face Annotation Using Transductive Kernel Fisher Discriminant Jianke Zhu, Steven C.H. Hoi, and Michael R. Lyu"
+60a33bcfe4b40cf46772e6aa1ead10489e924847,Bayesian representation learning with oracle constraints,"When crowds hold privileges: Bayesian unsupervised +representation learning with oracle constraints +Theofanis Karaletsos +Computational Biology Program, Sloan Kettering Institute +275 York Avenue, New York, USA +Serge Belongie +Cornell Tech +11 Eighth Avenue #302, New York, USA +Gunnar R¨atsch +Computational Biology Program, Sloan Kettering Institute +275 York Avenue, New York, USA"
60040e4eae81ab6974ce12f1c789e0c05be00303,Graphical Facial Expression Analysis and Design Method: An Approach to Determine Humanoid Skin Deformation,"Yonas Tadesse1,2 e-mail: Shashank Priya @@ -2532,6 +8632,36 @@ sion on humanoid face by utilizing discrete actuators, the first and foremost s Binary Gradient Correlation Patterns for Robust Face Recognition Weilin Huang, Student Member, IEEE, and Hujun Yin, Senior Member, IEEE"
+60bd1d33d74619f08baf0d7477b3f8cb8fc711e5,Amygdala Connectivity during Involuntary Attention to Emotional Faces in Typical Development and Autism Spectrum Disorders,"AMYGDALA CONNECTIVITY DURING INVOLUNTARY ATTENTION TO EMOTIONAL FACES +IN TYPICAL DEVELOPMENT AND AUTISM SPECTRUM DISORDERS +A Dissertation +Submitted to the Faculty of the +Graduate School of Arts and Sciences +of Georgetown University +in partial fulfillment of the requirement for the +degree of +Doctor of Philosophy +in Psychology +Eric R. Murphy, M.A. +Washington, DC +August 27th, 2013"
+60b66ec51ddadd132453f700d1781e8e7a8f78c8,Self-Validated Labeling of Markov Random Fields for Image Segmentation,"Self-Validated Labeling of Markov Random +Fields for Image Segmentation +Wei Feng, Jiaya Jia, Member, IEEE, and Zhi-Qiang Liu"
+60c7711bf9a00f697fff61474433da01f8550bf4,A Hybrid Approach of Facial Emotion Detection using Genetic Algorithm along with Artificial Neural Network,"A Hybrid Approach of Facial Emotion Detection using Genetic Algorithm along with Artificial Neural Network +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 175 +Number 4 +Year of Publication: 2017 +Authors: +Amrendra Sharan, Sunil Kumar Chhillar +10.5120/ijca2017915494 +{bibtex}2017915494.bib{/bibtex}"
+6047e9af00dcffbd2effbfa600735eb111f7de65,A Discriminative Representation of Convolutional Features for Indoor Scene Recognition,"A Discriminative Representation of Convolutional +Features for Indoor Scene Recognition +S. H. Khan, M. Hayat, M. Bennamoun, Member, IEEE, R. Togneri, and F. Sohel, Senior Member, IEEE"
60bffecd79193d05742e5ab8550a5f89accd8488,Proposal Classification using sparse representation and applications to skin lesion diagnosis,"PhD Thesis Proposal Classification using sparse representation and applications to skin lesion diagnosis @@ -2552,6 +8682,11 @@ from multiple classes. Sparse representation has become a powerful technique in pplications, including texture classification [16], face recognition [12], object detection [10], and segmentation of medical images [17], [18]. In conventional Sparse Representation Classification (SRC) schemes, learned dictionaries and sparse representation are involved to classify image pixels"
+60e065dbb795cc0d76ec187116eb87d1f42b5485,A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy,"IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, MANUSCRIPT ID +A General Framework for Density Based +Time Series Clustering Exploiting a Novel +Admissible Pruning Strategy +Nurjahan Begum1, Liudmila Ulanova1, Hoang Anh Dau1, Jun Wang2, and Eamonn Keogh1"
601834a4150e9af028df90535ab61d812c45082c,A short review and primer on using video for psychophysiological observations in human-computer interaction applications,"A short review and primer on using video for psychophysiological observations in human-computer interaction applications @@ -2559,6 +8694,10 @@ Teppo Valtonen1 Quantified Employee unit, Finnish Institute of Occupational Health, teppo. valtonen fi, POBox 40, 00250, Helsinki, Finland"
+60978f66eac568ae65d3acdc6559273fc30bc8c4,GReTA-A Novel Global and Recursive Tracking Algorithm in Three Dimensions,"GReTA – a novel Global and Recursive +Tracking Algorithm in three dimensions +Alessandro Attanasi, Andrea Cavagna, Lorenzo Del Castello, Irene Giardina, Asja Jeli´c, +Stefania Melillo, Leonardo Parisi, Fabio Pellacini, Edward Shen, Edmondo Silvestri, Massimiliano Viale"
346dbc7484a1d930e7cc44276c29d134ad76dc3f,Artists portray human faces with the Fourier statistics of complex natural scenes.,"This article was downloaded by:[University of Toronto] On: 21 November 2007 Access Details: [subscription number 785020433] @@ -2579,6 +8718,49 @@ To cite this Article: Redies, Christoph, Hänisch, Jan, Blickhan, Marko and Denz Joachim (2007) 'Artists portray human faces with the Fourier statistics of complex To link to this article: DOI: 10.1080/09548980701574496 URL: http://dx.doi.org/10.1080/09548980701574496"
+34b124ecdc3471167cea1675a74a0232a881bc69,Infrared face recognition based on LBP co-occurrence matrix,"Int. J. Wireless and Mobile Computing, Vol. 8, No. 1, 2015 +Infrared face recognition based on LBP +o-occurrence matrix and partial least squares +Zhihua Xie and Guodong Liu* +Key Lab of Optic-Electronic and Communication, +Jiangxi Sciences and Technology Normal University, +Nanchang, China +Email: +Email: +*Corresponding author"
+343d21ae54b45ef219ac4ba024265eeabf4d6edd,Where Will They Go? Predicting Fine-Grained Adversarial Multi-agent Motion Using Conditional Variational Autoencoders,"Where Will They Go? Predicting Fine-Grained +Adversarial Multi-Agent Motion using +Conditional Variational Autoencoders +Panna Felsen1,2, Patrick Lucey2, and Sujoy Ganguly2 +BAIR, UC Berkeley +STATS +{plucey,"
+34d53d2a418051c56cad9e0c90ea793af6cbb729,Structured Multi-class Feature Selection for Effective Face Recognition,"Structured multi-class feature selection for +effective face recognition +Giovanni Fusco, Luca Zini, Nicoletta Noceti, and Francesca Odone +DIBRIS - Universit`a di Genova +via Dodecaneso, 35 +6146-IT, Italy"
+34c7254d2f420df6309260b2bb461a9c107dfd5a,Semi-supervised image classification based on a multi-feature image query language,"University of Huddersfield Repository +Pein, Raoul Pascal +Semi-Supervised Image Classification based on a Multi-Feature Image Query Language +Original Citation +Pein, Raoul Pascal (2010) Semi-Supervised Image Classification based on a Multi-Feature Image +Query Language. Doctoral thesis, University of Huddersfield. +This version is available at http://eprints.hud.ac.uk/9244/ +The University Repository is a digital collection of the research output of the +University, available on Open Access. Copyright and Moral Rights for the items +on this site are retained by the individual author and/or other copyright owners. +Users may access full items free of charge; copies of full text items generally +an be reproduced, displayed or performed and given to third parties in any +format or medium for personal research or study, educational or not-for-profit +purposes without prior permission or charge, provided: +• The authors, title and full bibliographic details is credited in any copy; +• A hyperlink and/or URL is included for the original metadata page; and +• The content is not changed in any way. +For more information, including our policy and submission procedure, please +ontact the Repository Team at: +http://eprints.hud.ac.uk/"
34b3b14b4b7bfd149a0bd63749f416e1f2fc0c4c,The AXES submissions at TrecVid 2013,"The AXES submissions at TrecVid 2013 Robin Aly1, Relja Arandjelovi´c3, Ken Chatfield3, Matthijs Douze6, Basura Fernando4, Zaid Harchaoui6, Kevin McGuinness2, Noel E. O’Conner2, Dan Oneata6, Omkar M. Parkhi3, Danila Potapov6, Jérôme Revaud6, @@ -2586,6 +8768,34 @@ Cordelia Schmid6, Jochen Schwenninger5, David Scott2, Tinne Tuytelaars4, Jakob V Andrew Zisserman3 University of Twente 2Dublin City University 3Oxford University KU Leuven 5Fraunhofer Sankt Augustin 6INRIA Grenoble"
+34cd99528d873e842083abec429457233fdb3226,Person Re-identification using group context,"Person Re-identification using group context +Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla +Baskurt +To cite this version: +Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla Baskurt. Person Re- +identification using group context. Advanced Concepts for Intelligent Vision systems, Sep 2018, +Poitiers, France. <hal-01895373> +HAL Id: hal-01895373 +https://hal.archives-ouvertes.fr/hal-01895373 +Submitted on 15 Oct 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+344f647463ef160956143ebc8ce370cca144961a,Confidence-Aware Probability Hypothesis Density Filter for Visual Multi-Object Tracking,
+3413af6c689eedb4fe3e7d6c5dc626647976307a,Horizontally Scalable Submodular Maximization,"Horizontally Scalable Submodular Maximization +Mario Lucic1 +Olivier Bachem1 +Morteza Zadimoghaddam2 +Andreas Krause1 +Department of Computer Science, ETH Zurich, Switzerland +Google Research, New York"
34d484b47af705e303fc6987413dc0180f5f04a9,RI:Medium: Unsupervised and Weakly-Supervised Discovery of Facial Events,"RI:Medium: Unsupervised and Weakly-Supervised Discovery of Facial Events Introduction @@ -2606,14 +8816,34 @@ descriptive power, FACS has become the state of the art in manual measurement of widely used in studies of spontaneous facial behavior. The FACS taxonomy was develop by manually ob- serving graylevel variation between expressions in images and to a lesser extent by recording the electrical ctivity of underlying facial muscles [9]. Because of its importance to human social dynamics, person per-"
+3402b5e354eebcf443789f3c8d3c97eccd3ae55e,Multimodal Machine Learning: A Survey and Taxonomy,"Multimodal Machine Learning: +A Survey and Taxonomy +Tadas Baltruˇsaitis, Chaitanya Ahuja, and Louis-Philippe Morency"
341002fac5ae6c193b78018a164d3c7295a495e4,von Mises-Fisher Mixture Model-based Deep learning: Application to Face Verification,"von Mises-Fisher Mixture Model-based Deep learning: Application to Face Verification Md. Abul Hasnat, Julien Bohn´e, Jonathan Milgram, St´ephane Gentric and Liming Chen"
+34ae449ae64cd2c6bfc2f102eac82bd606cd12f7,A Unified Model with Structured Output for Fashion Images Classification,"A Unified Model with Structured Output for Fashion Images +Classification +Beatriz Quintino Ferreira +ISR, Instituto Superior Técnico, Universidade de Lisboa, +Portugal +João Faria +Farfetch"
34ec83c8ff214128e7a4a4763059eebac59268a6,Action Anticipation By Predicting Future Dynamic Images,"Action Anticipation By Predicting Future Dynamic Images Cristian Rodriguez, Basura Fernando and Hongdong Li Australian Centre for Robotic Vision, ANU, Canberra, Australia {cristian.rodriguez, basura.fernando,"
+34128e93f4af820cea65477526645cdc82e0e59b,Decomposed Learning for Joint Object Segmentation and Categorization,"TSAI et al.: DECOMPOSED LEARNING FOR OBJECT RECOGNITION +Decomposed Learning for Joint Object +Segmentation and Categorization +Yi-Hsuan Tsai +Jimei Yang +Ming-Hsuan Yang +Electrical Engineering and Computer +Science +University of California +Merced, USA"
34c594abba9bb7e5813cfae830e2c4db78cf138c,Transport-based single frame super resolution of very low resolution face images,"Transport-Based Single Frame Super Resolution of Very Low Resolution Face Images Soheil Kolouri1, Gustavo K. Rohde1,2 Department of Biomedical Engineering, Carnegie Mellon University. 2Department of Electrical and Computer Engineering, Carnegie Mellon University. @@ -2634,6 +8864,35 @@ Ih is a high-res image or a high-res image patch, w’s are weight coefficients nd ψ’s are high-res images (or image patches), which are learned from the training images using a specific model. Here we propose a fundamentally different approach toward modeling high-res images. In our approach the"
+3412d9f3c620155bf3eb203f5817a310000f0c63,Biomarkers in autism spectrum disorder: the old and the new,"DOI 10.1007/s00213-013-3290-7 +REVIEW +Biomarkers in autism spectrum disorder: the old and the new +Barbara Ruggeri & Ugis Sarkans & Gunter Schumann & +Antonio M. Persico +Received: 15 April 2013 /Accepted: 7 September 2013 +# Springer-Verlag Berlin Heidelberg 2013"
+3490683560ca18d19884949dccca0ad7c98d4749,Content-Based Filtering for Video Sharing Social Networks,"Content-Based Filtering for Video Sharing Social Networks +Eduardo Valle1, Sandra Avila2, Fillipe de Souza2, +Marcelo Coelho2,3, Arnaldo de A. Araújo2 +RECOD Lab — DCA / FEEC / UNICAMP, Campinas, SP, Brazil +NPDI Lab — DCC / UFMG, Belo Horizonte, MG, Brazil +Preparatory School of Air Cadets — EPCAR, Barbacena, MG, Brazil +{sandra, fdms, mcoelho,"
+340798e6b7a9863005863f38c1bbfda5cf85d201,"Image Retrieval, Object Recognition, and Discriminative Models","Image Retrieval, Object Recognition, +nd Discriminative Models +Von der Fakult¨at f¨ur Mathematik, Informatik und Naturwissenschaften der +RWTH Aachen University zur Erlangung des akademischen Grades eines +Doktors der Naturwissenschaften genehmigte Dissertation +vorgelegt von +Diplom-Informatiker Thomas Deselaers +us Aachen +Berichter: +Universit¨atsprofessor Dr.-Ing. Hermann Ney +Universit¨atsprofessor Dr. Bernt Schiele +Tag der m¨undlichen Pr¨ufung: 2. Dezember 2008 +Diese Dissertation ist auf den Internetseiten der Hochschulbibliothek online verf¨ugbar."
+348035720dba98ff54f2ff8c375ace09287c89f6,3D Human Pose Estimation in RGBD Images for Robotic Task Learning,"D Human Pose Estimation in RGBD Images for Robotic Task Learning +Christian Zimmermann*, Tim Welschehold*, Christian Dornhege, Wolfram Burgard and Thomas Brox"
341ed69a6e5d7a89ff897c72c1456f50cfb23c96,"DAGER: Deep Age, Gender and Emotion Recognition Using Convolutional Neural Network","DAGER: Deep Age, Gender and Emotion Recognition Using Convolutional Neural Networks @@ -2643,9 +8902,138 @@ Guang Shu Syed Zain Masood {afshindehghan, egortiz, guangshu, Computer Vision Lab, Sighthound Inc., Winter Park, FL"
+3493b2232449635aff50fc17e03163cb4b66f1b5,Visual exploration of machine learning results using data cube analysis,"Visual Exploration of Machine Learning Results +using Data Cube Analysis +Minsuk Kahng +Georgia Tech +Atlanta, GA, USA +Dezhi Fang +Georgia Tech +Atlanta, GA, USA +Duen Horng (Polo) Chau +Georgia Tech +Atlanta, GA, USA"
+341de07abfb89bf78f3a72513c8bce40d654e0a3,Sparse and Deep Generalizations of the FRAME Model,"Annals of Mathematical Sciences and Applications +Volume 3, Number 1, 211–254, 2018 +Sparse and deep generalizations of the +FRAME model +Ying Nian Wu, Jianwen Xie, Yang Lu, and Song-Chun Zhu +In the pattern theoretical framework developed by Grenander and +dvocated by Mumford for computer vision and pattern recog- +nition, different patterns are represented by statistical generative +models. The FRAME (Filters, Random fields, And Maximum En- +tropy) model is such a generative model for texture patterns. It +is a Markov random field model (or a Gibbs distribution, or an +energy-based model) of stationary spatial processes. The log prob- +bility density function of the model (or the energy function of the +Gibbs distribution) is the sum of translation-invariant potential +functions that are one-dimensional non-linear transformations of +linear filter responses. In this paper, we review two generalizations +of this model. One is a sparse FRAME model for non-stationary +patterns such as objects, where the potential functions are loca- +tion specific, and they are non-zero only at a selected collection of +locations. The other generalization is a deep FRAME model where"
+341633ccce0f8c055dfc633765d905c269e28f82,Collaborative Representation for Face Recognition based on Bilateral Filtering,"Collaborative Representation for Face +Recognition based on Bilateral Filtering +Rokan Khaji1, Hong Li2, Ramadan Abdo Musleh3, Hongfeng Li4, Qabas Ali5 +School of Mathematics and Statistics, +Huazhong University of Science & Technology , Wuhan, 430074, China +Department of Mathematics, College of Science, Diyala University, Diyala, 32001 ,Iraq +,3,4School of Mathematics and Statistics, +Huazhong University of Science & Technology , Wuhan, 430074, China +5Department of Electronics and Information Engineering, +Huazhong University of Science & Technology , Wuhan, 430074, China."
+34b6466e3e69547f6d464ad6b5660b1e629a5c35,Similar and Class Based Image Retrieval Using Hash Code,"IJCSNS International Journal of Computer Science and Network Security, VOL.15 No.3, March 2015 +Similar and Class Based Image Retrieval Using Hash Code +B.Bharathi 1, Nagarjuna Reddy Akkim2 +Faculty of computing, Sathyabama University, Chennai, India +Introduction"
+34f8086eb67eb2cd332cd2d6bca0dd8f1e8f1062,Face Recognition and Growth Prediction using a 3D Morphable Face Model,"Saarland University +Faculty of Natural Sciences and Technology I +Department of Computer Science +Master’s Program in Computer Science +Master’s Thesis +Face Recognition and +Growth Prediction using +3D Morphable Face Model +submitted by Kristina Scherbaum +on October 30, 2007 +Supervisor +Prof. Dr. Hans-Peter Seidel +Saarland University – Computer Science Department +Advisor +Prof. Dr. Volker Blanz +Universit¨at Siegen – Dekanat FB 12 +Reviewers +Prof. Dr. Hans-Peter Seidel +Prof. Dr. Volker Blanz"
+34e23b934794a5abff251698df09cbac5ad2dd56,Towards Engineering a Web-Scale Multimedia Service: A Case Study Using Spark,"Towards Engineering a Web-Scale Multimedia Service: +A Case Study Using Spark∗ +Gylfi Þór Guðmundsson +Reykjavik University +Reykjavík, Iceland +Björn Þór Jónsson +Reykjavik University, Iceland +IT University of Copenhagen, Denmark +Laurent Amsaleg +IRISA–CNRS +Rennes, France +Michael J. Franklin +University of Chicago +Chicago, IL, USA"
+3423f3dcb0edee1c5c6a5505b9e8c0bbdcffbd51,Nurses' Reactions to Patient Weight: Effects on Clinical Decisions,"University of Wisconsin Milwaukee +UWM Digital Commons +Theses and Dissertations +May 2017 +Nurses' Reactions to Patient Weight: Effects on +Clinical Decisions +Heidi M. Pfeiffer +University of Wisconsin-Milwaukee +Follow this and additional works at: http://dc.uwm.edu/etd +Part of the Psychology Commons +Recommended Citation +Pfeiffer, Heidi M., ""Nurses' Reactions to Patient Weight: Effects on Clinical Decisions"" (2017). Theses and Dissertations. 1524. +http://dc.uwm.edu/etd/1524 +This Dissertation is brought to you for free and open access by UWM Digital Commons. It has been accepted for inclusion in Theses and Dissertations +y an authorized administrator of UWM Digital Commons. For more information, please contact"
+344682f69dd9bec68d89a79b0b7f28a3891ab857,Perception of Social Cues of Danger in Autism Spectrum Disorders,"Perception of Social Cues of Danger in Autism Spectrum +Disorders +Nicole R. Zu¨ rcher1,2, Ophe´ lie Rogier1, Jasmine Boshyan2, Loyse Hippolyte1, Britt Russo1, Nanna Gillberg3, +Adam Helles3, Torsten Ruest1, Eric Lemonnier4, Christopher Gillberg3, Nouchine Hadjikhani1,2,3* +Brain Mind Institute, EPFL, Lausanne, Switzerland, 2 Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, +Charlestown, Massachusetts, United States of America, 3 Gillberg Centrum, University of Gothenburg, Gothenburg, Sweden, 4 Laboratoire de Neurosciences, Universite´ de +Brest, Brest, France"
340d1a9852747b03061e5358a8d12055136599b0,Audio-Visual Recognition System Insusceptible to Illumination Variation over Internet Protocol _ICIE_28_,"Audio-Visual Recognition System Insusceptible to Illumination Variation over Internet Protocol Yee Wan Wong, Kah Phooi Seng, and Li-Minn Ang"
+3468740e4a9fc72a269f4f0ca8470ccd60925f92,Robustness Analysis of Visual QA Models by Basic Questions,"Robustness Analysis of Visual QA Models by Basic Questions +Jia-Hong Huang +Bernard Ghanem +Cuong Duc Dao* Modar Alfadly* +C. Huck Yang +King Abdullah University of Science and Technology ; Georgia Institute of Technology +{jiahong.huang, dao.cuong, modar.alfadly, ;"
+34b4f264578fc674dd2bf8d478ec1314739a5629,3D Novel Face Sample Modeling for Face Recognition,"D Novel Face Sample Modeling for Face +Recognition +Yun Ge, Yanfeng Sun, Baocai Yin, Hengliang Tang +Beijing Key Laboratory of Multimedia and Intelligent Software Technology +College of Computer Science and Technology, BJUT, Beijing, China +Email:"
+34df09a9445089c8f23eff5b2a43a822c9713f6e,Boosting Chamfer Matching by Learning Chamfer Distance Normalization,"Boosting Chamfer Matching by Learning +Chamfer Distance Normalization +Tianyang Ma, Xingwei Yang, and Longin Jan Latecki +Dept. of Computer and Information Sciences,Temple Unviersity, Philadelphia. +{tianyang.ma,xingwei,latecki}.temple.edu"
+3410136b86b813b075a258842450835906d58600,A facial expression image database and norm for Asian population: A preliminary report,"Image Quality and System Performance VI, edited by Susan P. Farnand, Frans Gaykema, +Proc. of SPIE-IS&T Electronic Imaging, SPIE Vol. 7242, 72421D · © 2009 SPIE-IS&T +CCC code: 0277-786X/09/$18 · doi: 10.1117/12.806130 +SPIE-IS&T/ Vol. 7242 72421D-1 +Downloaded from SPIE Digital Library on 07 Oct 2009 to 140.112.113.225. Terms of Use: http://spiedl.org/terms"
+5a9126f4478384f6615bf57b6da7299dc17b9a6b,3-D Facial Landmark Localization With Asymmetry Patterns and Shape Regression from Incomplete Local Features,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012 +D Facial Landmark Localization with Asymmetry +Patterns and Shape Regression from Incomplete +Local Features +Federico M. Sukno, John L. Waddington, and Paul F. Whelan"
5a3da29970d0c3c75ef4cb372b336fc8b10381d7,CNN-based Real-time Dense Face Reconstruction with Inverse-rendered Photo-realistic Face Images.,"CNN-based Real-time Dense Face Reconstruction with Inverse-rendered Photo-realistic Face Images Yudong Guo, Juyong Zhang†, Jianfei Cai, Boyi Jiang and Jianmin Zheng"
@@ -2658,9 +9046,107 @@ Fréderic Jurie GREYC — CNRS UMR 6072, University of Caen Basse-Normandie, Caen, France"
+5ad65c6474c135a6c15e7127d8bb91de8c8a55a1,Designing Empathetic Animated Agents for a B-Learning Training Environment within the Electrical Domain,"Hernández, Y., Pérez-Ramírez, M., Zatarain-Cabada, R., Barrón-Estrada, L., & Alor-Hernández, G. (2016). Designing +Empathetic Animated Agents for a B-Learning Training Environment within the Electrical Domain. Educational Technology & +Society, 19 (2), 116–131. +Designing Empathetic Animated Agents for a B-Learning Training +Environment within the Electrical Domain +Yasmín Hernández1*, Miguel Pérez-Ramírez1, Ramón Zatarain-Cabada2, Lucía Barrón- +Estrada2 and Giner Alor-Hernández3 +Instituto de Investigaciones Eléctricas, Gerencia de Tecnologías de la Información, Cuernavaca, México // 2Instituto +Tecnológico de Culiacán, Departamento de Posgrado, Culiacán, México // 3Instituto Tecnológico de Orizaba, +División de Estudios de Posgrado e Investigación, Orizaba, México // // // +// // +*Corresponding author"
+5a14209a5241877f92743d04282598f41fd3e50f,From BoW to CNN: Two Decades of Texture Representation for Texture Classification,"From BoW to CNN: Two Decades of Texture Representation for Texture +Classification +Li Liu 1,2 · Jie Chen 2 · Paul Fieguth 3 · +Guoying Zhao 2 · Rama Chellappa 4 · Matti Pietik¨ainen 2 +Received: date / Accepted: date"
+5afd6c5eb5cc1e8496bb78b8f7b3a00b2900deb3,Self-Supervised Learning of Pose Embeddings from Spatiotemporal Relations in Videos,"Self-supervised Learning of Pose Embeddings +from Spatiotemporal Relations in Videos +¨Omer S¨umer∗ +Tobias Dencker∗ +Bj¨orn Ommer +Heidelberg Collaboratory for Image Processing +IWR, Heidelberg University, Germany"
+5ac18d505ed6d10e8692cbb7d33f6852e6782692,"The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale","IJCV submission in review +The Open Images Dataset V4 +Unified image classification, object detection, and visual relationship detection at scale +Alina Kuznetsova Hassan Rom Neil Alldrin +Shahab Kamali +Stefan Popov Matteo Malloci Tom Duerig Vittorio Ferrari +Jasper Uijlings +Ivan Krasin +Jordi Pont-Tuset"
+5ad4e9f947c1653c247d418f05dad758a3f9277b,WLFDB: Weakly Labeled Face Databases,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (TPAMI) +WLFDB: Weakly Labeled Face Databases +Dayong Wang†, Steven C.H. Hoi∗, and Jianke Zhu‡"
+5ac707ab88c565b1ed34fac89939f0cd2451eb22,Automated Object Recognition in Baggage Screening using Multiple X-ray Views,"Automated Object Recognition in Baggage Screening +using Multiple X-ray Views +Domingo Mery and Vladimir Riffo +Department of Computer Science – Pontificia Universidad Cat´olica de Chile +Av. Vicu˜na Mackenna 4860(143) – Santiago de Chile +http://dmery.ing.puc.cl"
+5aeaee0e3a324970c02ae8463e1b358597457d03,Towards a Types-As-Classifiers Approach to Dialogue Processing in Human-Robot Interaction,"Towards a Types-As-Classifiers Approach to Dialogue Processing in +Human-Robot Interaction +HOUGH, J; JAMONE, L; Schlangen, D; Walck, G; Haschke, R; Workshop on Dialogue and +Perception (DaP 2018) +© The Author(s) 2018 +For additional information about this publication click this link. +http://qmro.qmul.ac.uk/xmlui/handle/123456789/45947 +Information about this research object was correct at the time of download; we occasionally +make corrections to records, please therefore check the published record when citing. For +more information contact"
5a34a9bb264a2594c02b5f46b038aa1ec3389072,Label-Embedding for Image Classification,"Label-Embedding for Image Classification Zeynep Akata, Member, IEEE, Florent Perronnin, Member, IEEE, Zaid Harchaoui, Member, IEEE, nd Cordelia Schmid, Fellow, IEEE"
+5af5802cc6128bafbde1ae12e0ab41612aee9e3b,An object tracking method using extreme learning machine with online learning,"An Object Tracking Method Using Extreme +Learning Machine with Online Learning +Yuanlong Yu, Liyan Xie, and Zhiyong Huang +College of Mathematics and Computer Science +Fuzhou University +Fuzhou, Fujian, 350116, China +Emails: hzy"
+5ade87a54c8baec555c37d59071c6fb4a9a55cf7,Deep Learning For Video Saliency Detection,"Deep Learning For Video Saliency Detection +Wenguan Wang, and Jianbing Shen, Senior Member, IEEE, and Ling Shao, Senior Member,"
+5a6b2f3a542322be153fc9104f3064f2a1bc76eb,"A French-Spanish Multimodal Speech Communication Corpus Incorporating Acoustic Data, Facial, Hands and Arms Gestures Information","Interspeech 2018 +-6 September 2018, Hyderabad +0.21437/Interspeech.2018-2212"
+5a0209515ab62e008efeca31f80fa0a97031cd9d,Dataset fingerprints: Exploring image collections through data mining,"Dataset Fingerprints: Exploring Image Collections Through Data Mining +Konstantinos Rematas1, Basura Fernando1, Frank Dellaert2, and Tinne Tuytelaars1 +KU Leuven, ESAT-PSI, iMinds +Georgia Tech +Figure 1: Given an image collection, our system extracts patterns of discriminative mid level features and uses the connection +etween them to enable structure specific browsing."
+5a1669abdc4f958c589843cff2f4d83a11fe8007,Robust Recognition via ` 1-Minimization April,"Robust Recognition via ‘1-Minimization +April 13, 2007"
+5a8d20ecd92d22bf077208a5e7b1bb008a9b7dbc,A new manifold distance measure for visual object categorization,"A New Manifold Distance Measure for Visual Object +Categorization +Fengfu Li, Xiayuan Huang, Hong Qiao and Bo Zhang +index. The proposed distance is more robust"
+5aaa84090c50da903ea1d61495c0fe96a5470909,Image-embodied Knowledge Representation Learning,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +of armourhas partFigure1:Examplesofentityimages.Fig.1demonstratessomeexamplesofentityimages.Eachentityhasmultipleimageswhichcanprovidesignificantvisu-alinformationthatintuitivelydescribestheappearancesandbehavioursofthisentity.Toutilizetherichinformationinimages,weproposetheImage-embodiedKnowledgeRepre-sentationLearningmodel(IKRL).Morespecifically,wefirstproposeanimageencoderwhichconsistsofaneuralrep-resentationmoduleandaprojectionmoduletogeneratetheimage-basedrepresentationforeachimageinstance.Second,weconstructtheaggregatedimage-basedrepresentationforeachentityjointlyconsideringallitsimageinstanceswithanattention-basedmethod.Finally,wejointlylearntheknowl-edgerepresentationswithtranslation-basedmethods.WeevaluatetheIKRLmodelonknowledgegraphcom-pletionandtripleclassification.Experimentalresultsdemon-stratethatourmodelachievesthestate-of-the-artperfor-mancesonbothtasks,whichconfirmsthesignificanceofvi-sualinformationinknowledgerepresentationlearning.ItalsoindicatesthatourIKRLmodeliscapableofencodingimageinformationwellintoknowledgerepresentations.Wedemon-stratethemaincontributionsofthisworkasfollows:(cid:15)WeproposeanovelIKRLmodelconsideringvisualin-formationinentityimagesforknowledgerepresentationlearning.Tothebestofourknowledge,thisisthefirstattempttocombineimageswithknowledgegraphsforknowledgerepresentationlearning.(cid:15)Weevaluateourmodelsonareal-worlddatasetandre-ceivepromisingperformancesonbothknowledgegraph"
+5af1e8a38b64c6694b9a34cd0b1596f2c905d3ff,Context-based trajectory descriptor for human activity profiling,"Context-based Trajectory Descriptor for Human +Activity Profiling +Eduardo M. Pereira +INESC TEC and +Faculty of Engineering +of the University of Porto +Rua Dr. Roberto Frias, 378 +Porto, Portugal 4200 - 465 +Email: +Lucian Ciobanu +INESC TEC +Rua Dr. Roberto Frias, 378 +Porto, Portugal 4200 - 465 +Email: +Jaime S. Cardoso +INESC TEC and +Faculty of Engineering +of the University of Porto +Rua Dr. Roberto Frias, 378 +Porto, Portugal 4200 - 465"
5a4c6246758c522f68e75491eb65eafda375b701,Contourlet structural similarity for facial expression recognition,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE ICASSP 2010"
5aad5e7390211267f3511ffa75c69febe3b84cc7,Driver Gaze Region Estimation Without Using Eye Movement,"Driver Gaze Estimation @@ -2674,6 +9160,39 @@ Method Anchal Garg , Dr. Rohit Bajaj Deptt. of CSE, Chandigarh Engg. College, Mohali, Punjab, India. 07696449500"
+5ad88a16e2efe9bb67c20cdbd9b003ffb79c12ef,Real-time video event detection in crowded scenes using MPEG derived features: A multiple instance learning approach,"Manuscript Draft +Manuscript Number: PRLETTERS-D-13-00222R2 +Title: Real-Time Video Event Detection in Crowded Scenes using MPEG Derived Features: a Multiple +Instance Learning Approach +Article Type: Special Issue: SIPRCA +Keywords: Event Detection; Crowded Scene; Multiple Instance Learning; +MPEG domain; Sparse Approximation; Random Matrix; Traffic +Surveillance; Naive Bayes Model +Corresponding Author: Mr. Jingxin Xu, M.D +Corresponding Author's Institution: Queensland University of Technology +First Author: Jingxin Xu, M.D +Order of Authors: Jingxin Xu, M.D; Simon Denman, PhD; Vikas Reddy, PhD; Clinton Fookes, PhD; +Sridha Sridhran, PhD"
+5ac8edd62fe23911e19d639287135f91e22421cc,Gender and 3D facial symmetry: What's the relationship?,"Gender and 3D Facial Symmetry: What’s the +Relationship? +Baiqiang Xia, Boulbaba Ben Amor, Hassen Drira, Mohamed Daoudi, +Lahoucine Ballihi +To cite this version: +Baiqiang Xia, Boulbaba Ben Amor, Hassen Drira, Mohamed Daoudi, Lahoucine Ballihi. Gender +nd 3D Facial Symmetry: What’s the Relationship?. 10th IEEE Conference on Automatic Face and +Gesture Recognition (FG 2013), Apr 2013, shanghai, China. 2013. <hal-00771988> +HAL Id: hal-00771988 +https://hal.archives-ouvertes.fr/hal-00771988 +Submitted on 9 Jan 2013 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non,"
5a4ec5c79f3699ba037a5f06d8ad309fb4ee682c,Automatic age and gender classification using supervised appearance model,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 12/17/2017 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use AutomaticageandgenderclassificationusingsupervisedappearancemodelAliMainaBukarHassanUgailDavidConnahAliMainaBukar,HassanUgail,DavidConnah,“Automaticageandgenderclassificationusingsupervisedappearancemodel,”J.Electron.Imaging25(6),061605(2016),doi:10.1117/1.JEI.25.6.061605."
5aed0f26549c6e64c5199048c4fd5fdb3c5e69d6,Human Expression Recognition using Facial Features,"International Journal of Computer Applications® (IJCA) (0975 – 8887) @@ -2689,6 +9208,20 @@ recognition can be used" Database for Emotion Recognition S L Happy, Student Member, IEEE, Priyadarshi Patnaik, Aurobinda Routray, Member, IEEE, nd Rajlakshmi Guha"
+5f4a873118e033e5e168ee99d64474b4cc4d94a3,Lessons Learned from Crime Caught on Camera,"Article +Lessons Learned +from Crime Caught +on Camera +Marie Rosenkrantz Lindegaard1,2 +nd Wim Bernasco1,3 +Journal of Research in Crime and +Delinquency +018, Vol. 55(1) 155-186 +ª The Author(s) 2018 +Reprints and permission: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0022427817727830 +journals.sagepub.com/home/jrc"
5fff61302adc65d554d5db3722b8a604e62a8377,Additive Margin Softmax for Face Verification,"Additive Margin Softmax for Face Verification Feng Wang UESTC @@ -2699,6 +9232,14 @@ UESTC Jian Cheng UESTC haijun"
+5f943f9bfe3154fbd368034903ea11620d2946eb,Cascade Category-Aware Visual Search,"MiniManuscript.com +The one stop shop for academic literature. +07:00am 8 Dec, 2018 +Cascade Category-Aware Visual Search. +Authors Zhang S, Tian Q, Huang Q, Gao W, Rui Y +Volume +Issue +Pages"
5fa6e4a23da0b39e4b35ac73a15d55cee8608736,RED-Net: A Recurrent Encoder–Decoder Network for Video-Based Face Alignment,"IJCV special issue (Best papers of ECCV 2016) manuscript No. (will be inserted by the editor) RED-Net: @@ -2708,7 +9249,103 @@ Submitted: April 19 2017 / Revised: December 12 2017" 5f871838710a6b408cf647aacb3b198983719c31,Locally Linear Regression for Pose-Invariant Face Recognition,"Locally Linear Regression for Pose-Invariant Face Recognition Xiujuan Chai, Shiguang Shan, Member, IEEE, Xilin Chen, Member, IEEE, and Wen Gao, Senior Member, IEEE"
+5fc621cdef59c38ef898a2adc2b4472a8396119a,Synthesizing Samples for Zero-shot Learning,"Synthesizing Samples for Zero-shot Learning +IJCAI Anonymous Submission 2625"
+5f34c96ddcf992e1b8660b5cb01e3c311b05023c,Towards Online Iris and Periocular Recognition Under Relaxed Imaging Constraints,"IEEE Trans. Image Processing, 2013 +Towards Online Iris and Periocular Recognition under +Relaxed Imaging Constraints +Chun-Wei Tan, Ajay Kumar"
+5f58bf2c25826cb6ee927a1461aa72bd623157ff,Tasting Families of Features for Image Classification,"ICCV 2011 Submission #549. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. +Tasting Families of Features for Image Classification +Anonymous ICCV submission +Paper ID 549"
+5f92de3683b4fee28ad3f431c889e7c8bff604f8,"Performance study of Face Recognition systems using LBP and ICA descriptors with sparse representation-MRLSR and KNN Classifiers , respectively","International Journal of Computer Trends and Technology (IJCTT) – Volume 42 Number 1 – December 2016 +Performance study of Face Recognition +systems using LBP and ICA descriptors +with sparse representation - MRLSR and +KNN Classifiers, respectively +K Sarath1 and G. Sreenivasulu2 +PG scholar, Department of Electronics and Communication Engineering, SVU College of Engineering, +Professor, Department of Electronics and Communication Engineering, SVU College of Engineering, +Tirupathi, India +Tirupathi, India +sparse +representation"
5f344a4ef7edfd87c5c4bc531833774c3ed23542,Semisupervised Learning of Classifiers with Application to Human-computer Interaction," +5f02e49aa0fe467bbeb9de950e4abb6c99133feb,"Enhancing person re-identification by late fusion of low-, mid- and high-level features","Aalborg Universitet +Enhancing Person Re-identification by Late Fusion of Low-, Mid-, and High-Level +Features +Lejbølle, Aske Rasch; Nasrollahi, Kamal; Moeslund, Thomas B. +Published in: +DOI (link to publication from Publisher): +0.1049/iet-bmt.2016.0200 +Publication date: +Document Version +Accepted author manuscript, peer reviewed version +Link to publication from Aalborg University +Citation for published version (APA): +Lejbølle, A. R., Nasrollahi, K., & Moeslund, T. B. (2018). Enhancing Person Re-identification by Late Fusion of +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. +? You may not further distribute the material or use it for any profit-making activity or commercial gain +? You may freely distribute the URL identifying the publication in the public portal ? +Take down policy"
+5f19b98e5cd22198d25660d609cbd3f4a69c94e7,Combining Head Pose and Eye Location Information for Gaze Estimation,"Combining Head Pose and Eye Location Information +for Gaze Estimation +Roberto Valenti, Member, IEEE, Nicu Sebe, Member, IEEE, and Theo Gevers, Member, IEEE"
+5fc15baee1383d502775fab8ee91d56f4875429c,Factorial Discriminant Analysis for 3 D Face Recognition System using SVM Classifier,"International Journal of Computer Applications (0975 – 8887) +International Conference on Information and Communication Technologies (ICICT-2014) +Factorial Discriminant Analysis for +D Face Recognition System using SVM Classifier +P. S. Hiremath +Department of P. G. Studies and Research in +Computer Science, +Gulbarga University, Gulbarga-585106 +Karnataka, India +turned"
+5f6116b6e5f21da66a304e9f59f3e224e188caef,Behavior Is Everything: Towards Representing Concepts with Sensorimotor Contingencies,"Behavior is Everything – Towards Representing Concepts +with Sensorimotor Contingencies +Nicholas Hay, Michael Stark, Alexander Schlegel, Carter Wendelken, +Dennis Park, Eric Purdy, Tom Silver, D. Scott Phoenix, and Dileep George +Vicarious AI, San Francisco, CA, USA"
+5f0b7245bedfc984b327b8e144c3cba9d9b2a807,Morphological Primitive Patterns with Grain Components on LDP for Child and Adult Age Classification,"International Journal of Computer Applications (0975 – 8887) +Volume 21– No.3, May 2011 +Morphological Primitive Patterns with Grain Components +on LDP for Child and Adult Age Classification +B.Sujatha +Dr.V.Vijaya Kumar +Associate Professor +G.I.E.T, Rajahmundry +Dean, Dept. of Comp. Sciences +Head, SRRF-G.I.E.T +JNTUK,Kakinada +Andhra Pradesh, India +Rajahmundry +Andhra Pradesh, India +M.Rama Bai +Associate Professor +M.G.I.T, JNTUH +Hyderabad +Andhra Pradesh, India"
+5f7354634e13c9fad64163d53beb0a8eb5df30e1,Sketch-Based Image Retrieval: Benchmark and Bag-of-Features Descriptors,"Sketch-Based Image Retrieval: Benchmark +nd Bag-of-Features Descriptors +Mathias Eitz, Kristian Hildebrand, Tamy Boubekeur and Marc Alexa"
+5ffd74d2873b7cba2cbc5fd295cc7fbdedca22a2,The Cityscapes Dataset,"The Cityscapes Dataset +Marius Cordts1,2 +Mohamed Omran3 +Rodrigo Benenson3 +Sebastian Ramos1,4 +Uwe Franke1 +Timo Scharw¨achter1,2 +Markus Enzweiler1 +Stefan Roth2 +Bernt Schiele3 +Daimler AG R&D, 2TU Darmstadt, 3MPI Informatics, 4TU Dresden +www.cityscapes-dataset.net"
+5f534bacc658f620a15b5647adecb0ea813286c8,Reliable object detection and segmentation using inpainting,"Reliable Object Detection and Segmentation using Inpainting +Ji Hoon Joung, M. S. Ryoo, Sunglok Choi, and Sung-Rak Kim"
5f5906168235613c81ad2129e2431a0e5ef2b6e4,A Unified Framework for Compositional Fitting of Active Appearance Models,"Noname manuscript No. (will be inserted by the editor) A Unified Framework for Compositional Fitting of @@ -2725,9 +9362,88 @@ T. Ogata** Y.Yamauchi* H.Fujiyoshi* -1-20, Toranomon, Minato-ku, Aichi, Japan Tokyo, Japan"
+5f769ba95ffea0ce76ac9d8e7cd47e2d1c91e1bf,Using Geometry to Detect Grasps in 3D Point Clouds,"Localizing antipodal grasps in point clouds +Andreas ten Pas and Robert Platt"
+5f0e9cc18374a670dfea4698424c9d48494f3093,Online Domain Adaptation for Multi-Object Tracking,"GAIDON & VIG: ONLINE DOMAIN ADAPTATION FOR MULTI-OBJECT TRACKING +Online Domain Adaptation for Multi-Object Tracking +Computer Vision Group +Xerox Research Centre Europe +Meylan, France +Adrien Gaidon +Eleonora Vig"
+5fc371760fd4c8abe94b91ae2ca03d428ac05faa,Fear-specific amygdala function in children and adolescents on the fragile x spectrum: a dosage response of the FMR1 gene.,"doi:10.1093/cercor/bhs341 +Fear-Specific Amygdala Function in Children and Adolescents on the Fragile X Spectrum: +A Dosage Response of the FMR1 Gene +So-Yeon Kim1, Jessica Burris1, Frederick Bassal1, Kami Koldewyn5, Sumantra Chattarji6, Flora Tassone2, David Hessl2,3 and +Susan M. Rivera1,2,4 +Center for Mind and Brain, University of California, Davis, CA 95618, USA, 2MIND Institute, University of California, Davis, CA +95817, USA, 3Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA 95817, USA, 4Department of +Psychology, University of California, Davis, CA 95616, USA, 5McGovern Institute for Brain Research, MIT, MA 02139, USA and +6National Center for Biological Sciences, Bangalore 560065, India +Address correspondence to Susan M. Rivera, Center for Mind and Brain, University of California, Davis, 267 Cousteau Place, Davis, CA 95618, +USA. Email: +Mutations of the fragile X mental retardation 1 (FMR1) gene are the +genetic cause of fragile X syndrome (FXS). The presence of signifi- +ant socioemotional problems has been well documented in FXS +lthough the brain basis of those deficits remains unspecified. Here, +we investigated amygdala dysfunction and its relation to socioemo- +tional deficits and FMR1 gene expression in children and adoles- +ents on the FX spectrum (i.e., individuals whose trinucleotide CGG +repeat expansion from 55 to over 200 places them somewhere +within the fragile X diagnostic range from premutation to full"
+5f107c92dd1c3f294b53627a5de1c7c46d996994,Complex Eye Movement Pattern Biometrics: The Effects of Environment and Stimulus,"Complex Eye Movement Pattern Biometrics: +The Effects of Environment and Stimulus +Corey D. Holland, Student Member, IEEE and Oleg V. Komogortsev, Member, IEEE"
+5fd147f57fc087b35650f7f3891d457e4c745d48,Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields,"Published as a conference paper at ICLR 2018 +COULOMB GANS: PROVABLY OPTIMAL NASH EQUI- +LIBRIA VIA POTENTIAL FIELDS +Thomas Unterthiner1 +Bernhard Nessler1 +Calvin Seward1,2 +Günter Klambauer1 +Martin Heusel1 +Hubert Ramsauer1 +Sepp Hochreiter1 +LIT AI Lab & Institute of Bioinformatics, Johannes Kepler University Linz, Austria +Zalando Research, Mühlenstraße 25, 10243 Berlin, Germany"
5fc664202208aaf01c9b62da5dfdcd71fdadab29,Automatic Face Recognition from Video,rXiv:1504.05308v1 [cs.CV] 21 Apr 2015
+5fcde9236d654a0f92a76c1a3f07c0cad954985c,Personality-Dependent Referring Expression Generation,"Personality-dependent Referring Expression Generation +Ivandr´e Paraboni, Danielle Sampaio Monteiro, and Alex Gwo Jen Lan +University of S˜ao Paulo, School of Arts, Sciences and Humanities, S˜ao Paulo, Brazil"
+5f5164cf998a10d2bef37741adb562ab07fac413,A Comprehensive Study on Cross-View Gait Based Human Identification with Deep CNNs,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2016.2545669, IEEE +Transactions on Pattern Analysis and Machine Intelligence +A Comprehensive Study on Cross-View Gait Based +Human Identification with Deep CNNs +Zifeng Wu, Yongzhen Huang, Liang Wang, Xiaogang Wang, and Tieniu Tan"
+5f0f8c9acc3e8eb50ca6e7d9c33cf3d9a8a54985,Structured Inhomogeneous Density Map Learning for Crowd Counting,"Structured Inhomogeneous Density Map Learning +for Crowd Counting +Hanhui Li, Xiangjian He, Hefeng Wu, Saeed Amirgholipour Kasmani, Ruomei Wang, Xiaonan Luo, Liang Lin"
5fa1724a79a9f7090c54925f6ac52f1697d6b570,The Development of Multimodal Lexical Resources,"Proceedings of the Workshop on Grammar and Lexicon: Interactions and Interfaces, pages 41–47, Osaka, Japan, December 11 2016."
+5ff64afd70434b12e043ff39a91271eab6391124,Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters,"Article +Building Extraction in Very High Resolution +nd Guided Filters +Yongyang Xu 1 ID , Liang Wu 1,2, Zhong Xie 1,2,* and Zhanlong Chen 1 +Department of Information Engineering, China University of Geosciences, Wuhan 430074, China; +(Y.X.); (L.W.); (Z.C.) +National Engineering Research Center of Geographic Information System, Wuhan 430074, China +* Correspondence: +Received: 19 December 2017; Accepted: 16 January 2018; Published: 19 January 2018"
+33919313bb3cf09b00f9fa2253b30af33a52bc51,Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs,"Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs +Anton Osokin∗,1 Jean-Baptiste Alayrac∗,1 +Isabella Lukasewitz1 Puneet K. Dokania2 Simon Lacoste-Julien1 +INRIA – ´Ecole Normale Sup´erieure, Paris, France +Both authors contributed equally. +INRIA – CentraleSup´elec, Chˆatenay-Malabry, France"
+33236cd0b9454ab88ec9deddfb8ce8e492056770,Salient social cues are prioritized in autism spectrum disorders despite overall decrease in social attention.,"J Autism Dev Disord +DOI 10.1007/s10803-012-1710-x +O R I G I N A L P A P E R +Salient Social Cues are Prioritized in Autism Spectrum Disorders +Despite Overall Decrease in Social Attention +Coralie Chevallier • Pascal Huguet • +Francesca Happe´ • Nathalie George • +Laurence Conty +Ó Springer Science+Business Media New York 2012"
33a1a049d15e22befc7ddefdd3ae719ced8394bf,An Efficient Approach to Facial Feature Detection for Expression Recognition,"FULL PAPER International Journal of Recent Trends in Engineering, Vol 2, No. 1, November 2009 An Efficient Approach to Facial Feature Detection @@ -2735,12 +9451,39 @@ for Expression Recognition S.P. Khandait1, P.D. Khandait2 and Dr.R.C.Thool2 Deptt. of Info.Tech., K.D.K.C.E., Nagpur, India 2Deptt.of Electronics Engg., K.D.K.C.E., Nagpur, India, 2Deptt. of Info.Tech., SGGSIET, Nanded"
+33d045b39bc4645ff2a8bffd83a49697631ff968,Learning Discrete Representations via Information Maximizing Self-Augmented Training,"Learning Discrete Representations via Information Maximizing +Self Augmented Training +Weihua Hu 1 Takeru Miyato 2 3 Seiya Tokui 2 1 Eiichi Matsumoto 2 1 Masashi Sugiyama 4 1"
+332339c32d41cc8176d360082b4d9faa90dadffa,"UberNet: Training a Universal Convolutional Neural Network for Low-, Mid-, and High-Level Vision Using Diverse Datasets and Limited Memory","UberNet : Training a ‘Universal’ Convolutional Neural Network for Low-, Mid-, +nd High-Level Vision using Diverse Datasets and Limited Memory +Iasonas Kokkinos +CentraleSup´elec - INRIA"
333aa36e80f1a7fa29cf069d81d4d2e12679bc67,Suggesting Sounds for Images from Video Collections,"Suggesting Sounds for Images from Video Collections Matthias Sol`er1, Jean-Charles Bazin2, Oliver Wang2, Andreas Krause1 and Alexander Sorkine-Hornung2 Computer Science Department, ETH Z¨urich, Switzerland Disney Research, Switzerland"
+33ea400ca2105b9a3cd0e3c7c147e06c2d3c6d79,Vision based Decision-Support and Safety Systems for Robotic Surgery,"Vision based Decision-Support and Safety Systems for +Robotic Surgery +Suren Kumar +PhD Candidate +Madusudanan Sathia +Narayanan* +PhD Candidate +Sukumar Misra +Surgical Intern +Sudha Garimella +Assistant Professor +Pankaj Singhal +Director of Robotic Surgery +Jason J. Corso +Assistant Professor"
+33891ca0f8fab0eab503f4b4bcee009a1cf3b880,A video database of human faces under near Infra-Red illumination for human computer interaction applications,"A Video Database of Human Faces under Near Infra-Red +Illumination for Human Computer Interaction Aplications +S L Happy, Anirban Dasgupta, Anjith George, and Aurobinda Routray +Department of Electrical Engineering +Indian Institute of Technology Kharagpur"
33792bb27ef392973e951ca5a5a3be4a22a0d0c6,Two-Dimensional Whitening Reconstruction for Enhancing Robustness of Principal Component Analysis,"Two-dimensional Whitening Reconstruction for Enhancing Robustness of Principal Component Analysis @@ -2749,17 +9492,73 @@ Xiaoshuang Shi, Zhenhua Guo, Feiping Nie, Lin Yang, Jane You, and Dacheng Tao" A Face and Palmprint Recognition Approach Based on Discriminant DCT Feature Extraction Xiao-Yuan Jing and David Zhang"
+3355aff37b5e4ba40fc689119fb48d403be288be,Deep Private-Feature Extraction,"Deep Private-Feature Extraction +Seyed Ali Osia, Ali Taheri, Ali Shahin Shamsabadi, Kleomenis Katevas, Hamed Haddadi, Hamid R. Rabiee"
339937141ffb547af8e746718fbf2365cc1570c8,Facial Emotion Recognition in Real Time,"Facial Emotion Recognition in Real Time Dan Duncan Gautam Shine Chris English"
33ae696546eed070717192d393f75a1583cd8e2c,Subspace selection to suppress confounding source domain information in AAM transfer learning,
+33c485b59249af2d763d6951cd11e4080f3bbb3d,Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation,"Fusing 2D Uncertainty and 3D Cues for Monocular Body Pose Estimation +Bugra Tekin +Pablo M´arquez-Neila +Mathieu Salzmann +Pascal Fua +EPFL, Switzerland"
+3316521a5527c7700af8ae6aef32a79a8b83672c,People-tracking-by-detection and people-detection-by-tracking,"People-Tracking-by-Detection and People-Detection-by-Tracking +Mykhaylo Andriluka +Stefan Roth +Bernt Schiele +Computer Science Department +TU Darmstadt, Germany +{andriluka, sroth,"
3393459600368be2c4c9878a3f65a57dcc0c2cfa,Eigen-PEP for Video Face Recognition,"Eigen-PEP for Video Face Recognition Haoxiang Li†, Gang Hua†, Xiaohui Shen‡, Zhe Lin‡, Jonathan Brandt‡ Stevens Institute of Technology ‡Adobe Systems Inc."
+330bcf952a5a20aac0e334aad1de4cd6ba6ed6eb,Pedestrian Detection at Day/Night Time with Visible and FIR Cameras: A Comparison,"Article +Pedestrian Detection at Day/Night Time with Visible +nd FIR Cameras: A Comparison +Alejandro González 1,2,*, Zhijie Fang 1,2, Yainuvis Socarras 1,2, Joan Serrat 1,2, David Vázquez 1,2, +Jiaolong Xu 1,2 and Antonio M. López 1,2 +Autonomous University of Barcelona, Cerdanyola, Barcelona 08193, Spain; (Z.F.); +(Y.S.); (J.S.); (D.V.); (J.X.); +(A.M.L.) +Computer Vision Center, Cerdanyola, Barcelona 08193, Spain +* Correspondence: Tel.: +34-622-605-455 +Academic Editor: Vittorio M. N. Passaro +Received: 17 March 2016; Accepted: 30 May 2016; Published: 4 June 2016"
+3323a905a3960a663a9884540e8c3586cf362ba9,Face Hallucination Using Sparse Representation Algorithm,"International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) +Volume 4 Issue 9, September 2015 +Face Hallucination Using Sparse Representation +Algorithm +Sudhir Kumar Vikram Mutneja"
+336b2ae3e4db996538f930b754f7d233af56a628,Learning local descriptors by optimizing the keypoint-correspondence criterion,"Learning Local Descriptors by Optimizing the +Keypoint-Correspondence Criterion: Applications to +Face Matching, Learning from Unlabeled Videos +nd 3D-Shape Retrieval +Nenad Markuˇs†, Igor S. Pandˇzi´c†, and J¨orgen Ahlberg‡ +University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia +Computer Vision Laboratory, Dept. of Electrical Engineering, Link¨oping University, SE-581 83 Link¨oping, Sweden"
3352426a67eabe3516812cb66a77aeb8b4df4d1b,Joint Multi-view Face Alignment in the Wild,"JOURNAL OF LATEX CLASS FILES, VOL. 4, NO. 5, APRIL 2015 Joint Multi-view Face Alignment in the Wild Jiankang Deng, Student Member, IEEE, George Trigeorgis, Yuxiang Zhou, and Stefanos Zafeiriou, Member, IEEE"
+333be4858994e6d9364341aeb520f7800a0f6a07,Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks,"Unsupervised Pixel–Level Domain Adaptation +with Generative Adversarial Networks +Konstantinos Bousmalis +Google Brain +San Francisco, CA +Nathan Silberman +Google Research +New York, NY +David Dohan +Google Brain +Mountain View, CA +Dumitru Erhan +Google Brain +San Francisco, CA +Dilip Krishnan +Google Research +Cambridge, MA"
334d6c71b6bce8dfbd376c4203004bd4464c2099,Biconvex Relaxation for Semidefinite Programming in Computer Vision,"BICONVEX RELAXATION FOR SEMIDEFINITE PROGRAMMING IN COMPUTER VISION SOHIL SHAH*, ABHAY KUMAR*, DAVID JACOBS, @@ -2784,6 +9583,9 @@ mannian manifold M, and x ∈ M be a query point on the manifold. We define a general Riemannian coding formulation as More specifically, let D = {di}N (cid:93)N"
+330dda431e0343a96f9d630a0b4ee526bd93ad11,Domain Adaptation for Visual Applications: A Comprehensive Survey,"Domain Adaptation for Visual Applications: A Comprehensive +Survey +Gabriela Csurka"
33e20449aa40488c6d4b430a48edf5c4b43afdab,The Faces of Engagement: Automatic Recognition of Student Engagementfrom Facial Expressions,"TRANSACTIONS ON AFFECTIVE COMPUTING The Faces of Engagement: Automatic Recognition of Student Engagement from Facial @@ -2802,21 +9604,136 @@ Hemanth Singh1, Raman Patel2 ,2 M.Tech Student, SSG Engineering College, Odisha, India ---------------------------------------------------------------------***--------------------------------------------------------------------- examination structures need to analyse the facial exercises"
+335486cb9bb326e2b33fb03a74d0f9d671490ae7,Real-time pedestrian detection with deformable part models,"Real-time Pedestrian Detection with Deformable Part Models +Hyunggi Cho, Paul E. Rybski, Aharon Bar-Hillel and Wende Zhang"
+3369692338841f14ce032fc5d0b5b4fe7cc79f1a,Visualising mental representations: A primer on noise-based reverse correlation in social psychology,"European Review of Social Psychology +ISSN: 1046-3283 (Print) 1479-277X (Online) Journal homepage: http://www.tandfonline.com/loi/pers20 +Visualising mental representations: A primer +on noise-based reverse correlation in social +psychology +L. Brinkman, A. Todorov & R. Dotsch +To cite this article: L. Brinkman, A. Todorov & R. Dotsch (2017) Visualising mental +representations: A primer on noise-based reverse correlation in social psychology, European +Review of Social Psychology, 28:1, 333-361, DOI: 10.1080/10463283.2017.1381469 +To link to this article: http://dx.doi.org/10.1080/10463283.2017.1381469 +© 2017 The Author(s). Published by Informa +UK Limited, trading as Taylor & Francis +Group. +Published online: 16 Oct 2017. +Submit your article to this journal +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pers20 +Download by: [Princeton University]"
+3347d3e9f8a2da66e1c00f6a1e56bb37d27145ae,devant le jury composé de:,"Spécialité: Informatique et Télécommunications Ecole doctorale: Informatique, Télécommunications et Electronique de Paris Présentée par Raluca-Diana ŞAMBRA-PETRE Pour obtenir le grade de DOCTEUR DE TELECOM SUDPARIS MODELISATION ET INFERENCE 2D/3D DE CONNAISSANCES POUR L'ACCES INTELLIGENT AUX CONTENUS VISUELS ENRICHIS Soutenue le 18 Juin 2013 à Paris devant le jury composé de : Président de jury: Madame le Maître de Conférences, HDR Catherine ACHARD Rapporteur: Monsieur le Professeur Marc ANTONINI Rapporteur: Monsieur le Professeur Constantin VERTAN Examinateur: Monsieur le Professeur Miroslaw BOBER Examinateur: Monsieur le Docteur Olivier MARTINOT Directeur de thèse: Monsieur le Professeur Titus ZAHARIA Thèse n°: 2013TELE0012 THESE DE DOCTORAT CONJOINT TELECOM SUDPARIS et L'UNIVERSITE PIERRE ET MARIE CURIE"
+3389fa2f292b72320f4554261eae34d57e2db7b6,Morphable Reflectance Fields for enhancing face recognition,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES +http://www.merl.com +Morphable Reflectance Fields for Enhancing +Face Recognition +Ritwik Kumar, Michael Jones, Tim Marks +TR2010-039 +July 2010"
+330126c9dd71b3b0319d6429737186f1f20057a7,Deep Ordinal Regression Based on Data Relationship for Small Datasets,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+33e5d1c93e4195a1bfd303a94f0fc3f1c5e233bd,3D Face Recognition Under Expression Variations using Similarity Metrics Fusion,"(cid:176)2007 IEEE. Personal use of this material is permitted. +However, permission to reprint/republish this material for ad- +vertising or promotional purposes or for creating new collec- +tive works for resale or redistribution to servers or lists, or to +reuse any copyrighted component of this work in other works +must be obtained from the IEEE."
+3387805b752dadfa34cb8eb63d9dc86aff49934a,"UNIVERSITY OF CALIFORNIA RIVERSIDE Exploration of Contextual Relationships for Robust Video Analysis: Applications in Camera Networks, Bio-image Analysis and Activity Forecasting A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Electrical Engineering","UNIVERSITY OF CALIFORNIA +RIVERSIDE +Exploration of Contextual Relationships for Robust Video Analysis: +Applications in Camera Networks, Bio-image Analysis and Activity Forecasting +A Dissertation submitted in partial satisfaction +of the requirements for the degree of +Doctor of Philosophy +Electrical Engineering +Anirban Chakraborty +August 2014 +Dissertation Committee: +Dr. Amit K. Roy-Chowdhury, Chairperson +Dr. Ertem Tuncel +Dr. Stefano Lonardi"
+33e7bc26047de3c1b607f04a644c2c03920201fd,Learning to Navigate Autonomously in Outdoor Environments : MAVNet,"Learning to Navigate Autonomously in Outdoor Environments : +MAVNet +Saumya Kumaar2, Arpit Sangotra3, Sudakshin Kumar3, Mayank Gupta3, Navaneethkrishnan B2 and S N Omkar1"
+05ce0e4e9ae2c7b2320decb3bb29e066f1dd96d3,Patch-wise low-dimensional probabilistic linear discriminant analysis for Face Recognition,"PATCH-WISE LOW-DIMENSIONAL PROBABILISTIC LINEAR DISCRIMINANT ANALYSIS +FOR FACE RECOGNITION +Vitomir ˇStruc, Nikola Paveˇsi´c +Jerneja ˇZganec-Gros, Boˇstjan Vesnicer +Faculty of Electrical Engineering UL +Trˇzaˇska cesta 25, 1000 Ljubljana, Slovenia +Alpineon Ltd., Ulica Iga Grudna 15 +000 Ljubljana, Slovenia"
05b8673d810fadf888c62b7e6c7185355ffa4121,A Comprehensive Survey to Face Hallucination,"(will be inserted by the editor) A Comprehensive Survey to Face Hallucination Nannan Wang · Dacheng Tao · Xinbo Gao · Xuelong Li · Jie Li Received: date / Accepted: date"
05e658fed4a1ce877199a4ce1a8f8cf6f449a890,Domain Transfer Learning for Object and Action Recognition,
+0569d7d3d8f96140adc8ec5a6016fdc97e7ef8aa,Random tree walk toward instantaneous 3D human pose estimation,"Random Tree Walk toward Instantaneous 3D Human Pose Estimation +Ho Yub Jung1, Soochahn Lee2, Yong Seok Heo3, Il Dong Yun1 +Div. of Comp. & Elect. Sys. Eng., Hankuk University of Foreign Studies. 2Dept. of Elect. Eng., Soonchunghyang University. 3Dept. of Elect. & Comp. Eng., +Ajou University. +Figure 1: The red lines represents the random tree walks trained to find +the head position. The random walk starts from the body center in (a). In +(b), the head position is found with fewer steps by starting from the chest, +which is much closer than the body center. (c) illustrates the kinematic tree +implemented along with RTW. The adjacent joint positions can be used as +the starting positions for new RTW. (d) shows the RTW path examples. +Figure 2: Example results of the RTW from EVAL db [1]. Proposed ap- +proach achieves the state-of-the-art accuracy without using the temporal +prior. 64 RTW steps are taken for each joint to estimate human pose from +single depth image. The RTW paths are drawn, and the expectations of +RTW steps are used to find the joint positions. The pose estimation from a +single frame takes less than 1 millisecond. +The availability of accurate depth cameras have made real-time human +pose estimation possible; however, there are still demands for faster algo- +rithms on low power processors. This paper introduces 1000 frames per +second pose estimation method on a single core 3.20 GHz CPU with no"
+05e3167206bc440d5aacf2256fd2e2e421b0808c,People Detection and Re-identification for Multi Surveillance Cameras,"People detection and re-identification for multi surveillance cameras +Etienne Corvee, Slawomir Bak and Francois Bremond +INRIA, Sophia Antipolis, Pulsar Team +{etienne.corvee, slawomir.bak, +Keywords: +people detection, people tracking, people re-identification, local binary pattern, mean Riemannian covariance"
05ad478ca69b935c1bba755ac1a2a90be6679129,Attribute Dominance: What Pops Out?,"Attribute Dominance: What Pops Out? Naman Turakhia Georgia Tech"
+050e7e32fdc48150f66cb5edf166790c69652b8b,Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network,"Article +Land Cover Segmentation of Airborne LiDAR Data +Using Stochastic Atrous Network +Hasan Asy’ari Arief 1,* ID , Geir-Harald Strand 1,2 ID , Håvard Tveite 1 ID and Ulf Geir Indahl 1 +Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway; +(G.H.S.); (H.T.); (U.G.I.) +Division of Survey and Statistics, Norwegian Institute of Bioeconomy Research, 1431 Ås, Norway +* Correspondence: Tel.: +47-453-91-706 +Received: 30 April 2018; Accepted: 17 June 2018; Published: 19 June 2018"
+051d8bbf12877c46ae9a598a386c5b72d1b103ac,Object Detection using Geometrical Context Feedback,"Int J Comput Vis (2012) 100:154–169 +DOI 10.1007/s11263-012-0547-2 +Object Detection using Geometrical Context Feedback +Min Sun · Sid Yingze Bao · Silvio Savarese +Received: 17 December 2010 / Accepted: 16 July 2012 / Published online: 2 August 2012 +© Springer Science+Business Media, LLC 2012"
054738ce39920975b8dcc97e01b3b6cc0d0bdf32,Towards the design of an end-to-end automated system for image and video-based recognition,"Towards the Design of an End-to-End Automated System for Image and Video-based Recognition Rama Chellappa1, Jun-Cheng Chen3, Rajeev Ranjan1, Swami Sankaranarayanan1, Amit Kumar1, Vishal M. Patel2 and Carlos D. Castillo4"
+05a22ebec697cfa5e8e2883d68e6f4762bbdebd7,Few-Example Object Detection with Model Communication.,"Few-Example Object Detection +with Model Communication +Xuanyi Dong, Liang Zheng, Fan Ma, Yi Yang, Deyu Meng"
05e03c48f32bd89c8a15ba82891f40f1cfdc7562,Scalable Robust Principal Component Analysis Using Grassmann Averages,"Scalable Robust Principal Component Analysis using Grassmann Averages Søren Hauberg, Aasa Feragen, Raffi Enficiaud, and Michael J. Black"
+05ce73c39368aca1d10ab48dbe0dee80ee084bdb,Multi-label Learning with the Rnns for Fashion Search,"Under review as a conference paper at ICLR 2017 +MULTI-LABEL LEARNING WITH THE RNNS +FOR FASHION SEARCH +Se-Yeoung Kim, Sang-Il Na, Ha-Yoon Kim, Moon-Ki Kim, Byoung-Ki Jeon +Machine Intelligence Lab., SK Planet +Seongnam City, South Korea +Taewan Kim ∗ +Naver Labs, Naver Corp. +Seongnam City, South Korea"
056ba488898a1a1b32daec7a45e0d550e0c51ae4,Cascaded Continuous Regression for Real-Time Incremental Face Tracking,"Cascaded Continuous Regression for Real-time Incremental Face Tracking Enrique S´anchez-Lozano, Brais Martinez, @@ -2842,8 +9759,29 @@ Laurent Hoeltgen, Isaac Harris, Michael Breuß, and Andreas Kleefeld Combining Contrast Invariant L1 Data Fidelities with Nonlinear Spectral Image Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Leonie Zeune, Stephan A. van Gils, Leon W.M.M. Terstappen,"
+05a6a40c840c069631a825509f3095697592e1c4,IAN: The Individual Aggregation Network for Person Search,"IAN: The Individual Aggregation Network for +Person Search +Jimin XIAO, Member, IEEE, Yanchun XIE, Tammam TILLO, Senior Member, IEEE, Kaizhu HUANG, Senior +Member, IEEE, Yunchao WEI, Member, IEEE, Jiashi FENG"
052880031be0a760a5b606b2ad3d22f237e8af70,Datasets on object manipulation and interaction: a survey,"Datasets on object manipulation and interaction: a survey Yongqiang Huang and Yu Sun"
+05bba1f1626f02ef4ca497090b4a04d47f36ebb6,Social projection increases for positive targets: ascertaining the effect and exploring its antecedents.,"545039 PSPXXX10.1177/0146167214545039Personality and Social Psychology BulletinMachunsky et al. +research-article2014 +Article +Social Projection Increases for +Positive Targets: Ascertaining the +Effect and Exploring Its Antecedents +Maya Machunsky1, Claudia Toma2, Vincent Yzerbyt3, +nd Olivier Corneille3 +Personality and Social +Psychology Bulletin +014, Vol. 40(10) 1373 –1388 +© 2014 by the Society for Personality +nd Social Psychology, Inc +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0146167214545039 +pspb.sagepub.com"
053c2f592a7f153e5f3746aa5ab58b62f2cf1d21,Performance Evaluation of Illumination Normalization Techniques for Face Recognition,"International Journal of Research in Engineering & Technology (IJRET) ISSN 2321-8843 @@ -2853,15 +9791,96 @@ PERFORMANCE EVALUATION OF ILLUMINATION NORMALIZATION TECHNIQUES FOR FACE RECOGNITION A. P. C. SARATHA DEVI & V. MAHESH Department of Information Technology, PSG College of Technology, Coimbatore, Tamil Nadu, India"
+05ef5efd9e42f49dbb9e50ec3fe367f275a94931,Biologically Inspired Processing for Lighting Robust Face Recognition,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+05487784c1c94e17c26862e342c1b81acfe11258,Spontaneous facial expression analysis based on temperature changes and head motions,"Spontaneous Facial Expression Analysis +Based on Temperature +Changes and Head Motions +Peng Liu and Lijun Yin +State University of New York-at Binghamton"
+051830b0ea58d1568f19ec3297e301d9789c9a76,Bringing Semantics into Focus Using Visual Abstraction,
05ea7930ae26165e7e51ff11b91c7aa8d7722002,Learning And-Or Model to Represent Context and Occlusion for Car Detection and Viewpoint Estimation,"Learning And-Or Model to Represent Context and Occlusion for Car Detection and Viewpoint Estimation Tianfu Wu∗, Bo Li∗ and Song-Chun Zhu"
+05384ac77be3211fb7d221802bc79eb3c9fa2873,A Novel Image Classification System Based on Evidence Probabilistic Transformation,"International Journal of Research in Computer and +Communication Technology, Vol 4,Issue 2 ,February -2015 +ISSN (Online) 2278- 5841 +ISSN (Print) 2320- 5156 +A Novel Image Classification System Based on Evidence +Probabilistic Transformation +Department of Computer Science, Mansoura University, Mansoura 35516, Egypt +A.E. Amin +information +different +identity +paper +evidence"
+056892b7e573608e64c3c9130e8ce33353a94de2,Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform,"Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs +nd a Discriminatively Trained Domain Transform +Liang-Chieh Chen∗ +Jonathan T. Barron, George Papandreou, Kevin Murphy +{barron, gpapan, +Alan L. Yuille"
+056e2c82db905b93f7762a2ee7778d3aacc5a1f0,Bag of Attributes for Video Event Retrieval,"Bag of Attributes for Video Event Retrieval +Leonardo A. Duarte1, Ot´avio A. B. Penatti2, and Jurandy Almeida1 +Institute of Science and Technology +Federal University of S˜ao Paulo – UNIFESP +2247-014, S˜ao Jos´e dos Campos, SP – Brazil +Email: {leonardo.assuane, +Advanced Technologies +SAMSUNG Research Institute +3097-160, Campinas, SP – Brazil +Email:"
+05fcbe4009543ec8943bdc418ee81e9594b899a4,Social perception in autism spectrum disorders: impaired category selectivity for dynamic but not static images in ventral temporal cortex.,"doi:10.1093/cercor/bhs276 +Social Perception in Autism Spectrum Disorders: Impaired Category Selectivity +for Dynamic but not Static Images in Ventral Temporal Cortex +Jill Weisberg1, Shawn C. Milleville1, Lauren Kenworthy1,2, Gregory L. Wallace1, Stephen J. Gotts1, +Michael S. Beauchamp3 and Alex Martin1 +NIMH, Laboratory of Brain and Cognition, Bethesda, MD 20850, 2Children’s National Medical Center, Center for Autism +Spectrum Disorders, Rockville, MD 20850 and 3Department of Neurobiology and Anatomy, University of Texas Medical School +t Houston, Houston, TX 77030, USA +Address correspondence to Jill Weisberg, San Diego State University Research Foundation, Laboratory for Language and Cognitive Neuroscience, +6495 Alvarado Rd, Suite 200, San Diego, CA 92120, USA. Email: +Studies of autism spectrum disorders (ASDs) reveal dysfunction in +the neural systems mediating object processing (particularly faces) +nd social cognition, but few investigations have systematically as- +sessed the specificity of the dysfunction. We compared cortical +responses in typically developing adolescents and those with ASD +to stimuli from distinct conceptual domains known to elicit cat- +egory-related activity in separate neural systems. In Experiment 1, +subjects made category decisions to photographs, videos, and +point-light displays of people and tools. In Experiment 2, subjects +interpreted displays of simple, geometric shapes in motion depicting"
051a84f0e39126c1ebeeb379a405816d5d06604d,Biometric Recognition Performing in a Bioinspired System,"Cogn Comput (2009) 1:257–267 DOI 10.1007/s12559-009-9018-7 Biometric Recognition Performing in a Bioinspired System Joan Fa`bregas Æ Marcos Faundez-Zanuy Published online: 20 May 2009 Ó Springer Science+Business Media, LLC 2009"
+053ff27aba868c64823dbbe2167a762dd3f33b53,Probabilistic Slow Features for Behavior Analysis,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +Probabilistic Slow Features for Behavior Analysis +Lazaros Zafeiriou, Student Member, IEEE, Mihalis A. Nicolaou, Member, IEEE, +Stefanos Zafeiriou, Member, IEEE, Symeon Nikitidis, +nd Maja Pantic, Fellow, IEEE +feature"
0559fb9f5e8627fecc026c8ee6f7ad30e54ee929,Facial Expression Recognition,"Facial Expression Recognition Bogdan J. Matuszewski, Wei Quan and Lik-Kwan Shark ADSIP Research Centre, University of Central Lancashire @@ -2887,9 +9906,67 @@ for Video Classification Xiaodong Yang Pavlo Molchanov Jan Kautz {xiaodongy, pmolchanov, NVIDIA"
+057d879fe2d6c40ef79fe901cc62625a3b2ea8ba,EgoSampling: Fast-forward and stereo for egocentric videos,"EgoSampling: Fast-Forward and Stereo for Egocentric Videos +Yair Poleg +Tavi Halperin +The Hebrew University +The Hebrew University +Jerusalem, Israel +Jerusalem, Israel +Chetan Arora +Delhi, India +Shmuel Peleg +The Hebrew University +Jerusalem, Israel"
+056be8a896f71be4a1dee67b01f4d59e3e982304,Generative Models of Visually Grounded Imagination,"Published as a conference paper at ICLR 2018 +GENERATIVE MODELS OF VISUALLY GROUNDED +IMAGINATION +Ramakrishna Vedantam∗ +Georgia Tech +Ian Fischer +Google Inc. +Jonathan Huang +Google Inc. +Kevin Murphy +Google Inc."
050a149051a5d268fcc5539e8b654c2240070c82,Magisterské a doktorské studijnı́ programy,MAGISTERSKÉ A DOKTORSKÉSTUDIJNÍ PROGRAMY31. 5. 2018SBORNÍKSTUDENTSKÁ VĚDECKÁ KONFERENCE
+05fd17673f1500d46196b0e38857eb3eaf09296e,Fourier Descriptors Based on the Structure of the Human Primary Visual Cortex with Applications to Object Recognition,"(will be inserted by the editor) +Fourier descriptors based on the structure of the human +primary visual cortex with applications to object recognition +Amine Bohi · Dario Prandi · Vincente Guis · Fr´ed´eric Bouchara · +Jean-Paul Gauthier +Received: date / Accepted: date"
0580edbd7865414c62a36da9504d1169dea78d6f,Baseline CNN structure analysis for facial expression recognition,"Baseline CNN structure analysis for facial expression recognition Minchul Shin1, Munsang Kim2 and Dong-Soo Kwon1"
+05a2547d976420f7d1de19907e16280d15199008,Semantic Road Layout Understanding by Generative Adversarial Inpainting,"Road layout understanding by generative +dversarial inpainting +Lorenzo Berlincioni, Federico Becattini, Leonardo Galteri, Lorenzo Seidenari, +Alberto Del Bimbo"
+0534304bc09e92b2cfa0a8da59cfcf0be84d70a4,Towards reliable real-time person detection,"Towards Reliable Real-Time Person Detection +Silviu-Tudor SERBAN1, Srinidhi MUKANAHALLIPATNA SIMHA1, Vasanth +BATHRINARAYANAN1, Etienne CORVEE1 and Francois BREMOND1 +INRIA Sophia Antipolis - Mediterranee, 2004 route des Lucioles, Sophia Antipolis, France +{silviu-tudor.serban,srinidhi.mukanahallipatna +Keywords: +Random sampling, Adaboost, Soft cascade, LBP channel features"
+0582d338a5e5b325c282e2ff13bfd62cf4d08108,Affordance Research in Developmental Robotics: A Survey,"Affordance Research in Developmental +Robotics: A Survey +Huaqing Min, Chang’an Yi, Ronghua Luo, Jinhui Zhu, and Sheng Bi +apture"
+051aa14e0b7dd4231636db39398c0c15b2687682,Robust Subspace Clustering via Thresholding,"Robust Subspace Clustering via Thresholding +Reinhard Heckel and Helmut B¨olcskei +Dept. of IT & EE, ETH Zurich, Switzerland +July 2013; last revised August 2015"
+054953d915f65b66485b653cd2ffbf61568b2849,Face Description with Local Invariant Features: Application to Face Recognition,"Face Description with Local Invariant Features: Application to Face Recognition +{tag} {/tag} +International Journal of Computer Applications +© 2010 by IJCA Journal +Number 24 - Article 12 +Year of Publication: 2010 +Authors: +Sanjay A. Pardeshi +Dr. S.N. Talbar +10.5120/555-726"
9d58e8ab656772d2c8a99a9fb876d5611fe2fe20,Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video,"Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video Lionel Pigou, A¨aron van den Oord∗ , Sander Dieleman∗ , @@ -2907,17 +9984,87 @@ Krishnapriya P S M.Tech Dept of CSE NSS College of Engineering Palakkad, Kerala"
+9d4c05c7c9284c8e303641b95e997f11df2dd1a7,Misalignment-robust Face Recognition via Efficient Locality-constrained Representation,"Misalignment-robust Face Recognition via Effi- +ient Locality-constrained Representation +Yandong Wen, Weiyang Liu, Meng Yang, Member, IEEE, Yuli Fu, Zhifeng Li, Senior Member, IEEE"
9d8fd639a7aeab0dd1bc6eef9d11540199fd6fe2,L Earning to C Luster,"Workshop track - ICLR 2018 LEARNING TO CLUSTER Benjamin B. Meier, Thilo Stadelmann & Oliver D¨urr ZHAW Datalab, Zurich University of Applied Sciences Winterthur, Switzerland"
+9d2ad0b408bddc9c5a713e250b52aa48f1786a46,Visual Recognition Using Local Quantized Patterns,"Visual Recognition using Local Quantized Patterns +Sibt Ul Hussain, Bill Triggs +To cite this version: +Sibt Ul Hussain, Bill Triggs. Visual Recognition using Local Quantized Patterns. Andrew Fitzgibbon, +Svetlana Lazebnik, Pietro Perona, Yoichi Sato, and Cordelia Schmid. ECCV 2012 - 12th European +Conference on Computer Vision, Oct 2012, Florence, Italy. Springer, 7573, pp.716-729, 2012, Lecture +Notes in Computer Science. <10.1007/978-3-642-33709-3_51>. <hal-00695627> +HAL Id: hal-00695627 +https://hal.archives-ouvertes.fr/hal-00695627 +Submitted on 9 May 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
9d357bbf014289fb5f64183c32aa64dc0bd9f454,Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions,"Face Identification by Fitting a 3D Morphable Model using Linear Shape and Texture Error Functions Sami Romdhani, Volker Blanz, and Thomas Vetter University of Freiburg, Instit¨ut f¨ur Informatik, Georges-K¨ohler-Allee 52, 79110 Freiburg, Germany, fromdhani, volker,"
+9d0bf3b351fb4d80cee5168af8367c5f6c8b2f3a,"The Tromso Infant Faces Database (TIF): Development, Validation and Application to Assess Parenting Experience on Clarity and Intensity Ratings","METHODS +published: 24 March 2017 +doi: 10.3389/fpsyg.2017.00409 +The Tromso Infant Faces Database +(TIF): Development, Validation and +Application to Assess Parenting +Experience on Clarity and Intensity +Ratings +Jana K. Maack†, Agnes Bohne†, Dag Nordahl, Lina Livsdatter, Åsne A. W. Lindahl, +Morten Øvervoll, Catharina E. A. Wang and Gerit Pfuhl* +Department of Psychology, UiT – The Arctic University of Norway, Tromsø, Norway +Newborns and infants are highly depending on successfully communicating their needs; +e.g., through crying and facial expressions. Although there is a growing interest in +the mechanisms of and possible influences on the recognition of facial expressions in +infants, heretofore there exists no validated database of emotional infant faces. In the +present article we introduce a standardized and freely available face database containing +Caucasian infant face images from 18 infants 4 to 12 months old. The development +nd validation of the Tromsø Infant Faces (TIF) database is presented in Study 1. Over +700 adults categorized the photographs by seven emotion categories (happy, sad, +disgusted, angry, afraid, surprised, neutral) and rated intensity, clarity and their valance."
+9d6a2180a5f452356526edd8b4833180fa09cb3f,Photo Aesthetics Analysis via DCNN Feature Encoding,"Photo Aesthetics Analysis +via DCNN Feature Encoding +Hui-Jin Lee, Ki-Sang Hong, Henry Kang, and Seungyong Lee"
+9d67af2158807aa815b5a4485b076f7a18ce6ab4,Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understanding,"Model Adaptation with Synthetic and Real Data +for Semantic Dense Foggy Scene Understanding +Christos Sakaridis1( +ETH Z¨urich, Z¨urich, Switzerland +KU Leuven, Leuven, Belgium"
+9df7ea3eed6b0c9c067521119698cfa79cc1f91d,Representations and Matching Techniques for 3D Free-form Object and Face Recognition,"Representations and Matching +Techniques for 3D Free-form Object and +Face Recognition +Ajmal Saeed Mian +This thesis is presented for the degree of +Doctor of Philosophy +of The University of Western Australia +School of Computer Science and Software Engineering. +March 2006"
+9dc263210770e7e836040c8e9d0edff40814254b,A track before detect approach for sequential Bayesian tracking of multiple speech sources,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE +ICASSP 2010"
+9da9ee38d5845d39497b10b0ab442580e75ee4d3,Dynamic Video Segmentation Network,"Dynamic Video Segmentation Network +Yu-Syuan Xu, Tsu-Jui Fu∗, Hsuan-Kung Yang∗, Student Member, IEEE and Chun-Yi Lee, Member, IEEE +Elsa Lab, Department of Computer Science, National Tsing Hua Uiversity +{yusean0118, rayfu1996ozig,"
+9d8978ee319d671283a90761aaed150c7cc9154b,Fader Networks: Manipulating Images by Sliding Attributes,"Fader Networks: +Manipulating Images by Sliding Attributes +Guillaume Lample1,2, Neil Zeghidour1,3, Nicolas Usunier1, +Antoine Bordes1, Ludovic Denoyer2, Marc’Aurelio Ranzato1"
9d839dfc9b6a274e7c193039dfa7166d3c07040b,Augmented faces,"Augmented Faces Matthias Dantone1 Lukas Bossard1 @@ -2926,6 +10073,19 @@ Luc van Gool1,3 ETH Z¨urich Kooaba AG K.U. Leuven"
+9d1940f843c448cc378214ff6bad3c1279b1911a,Shape-aware Instance Segmentation,"Shape-aware Instance Segmentation +Zeeshan Hayder1,2, Xuming He2,1 +Australian National University & 2Data61/CSIRO ∗ +Mathieu Salzmann2,3 +CVLab, EPFL, Switzerland"
+9da2abae3072fd9fcff0e13b8f00fc21f22d0085,NOKMeans: Non-Orthogonal K-means Hashing,"NOKMeans: Non-Orthogonal K-means Hashing +Xiping Fu, Brendan McCane, Steven Mills, and Michael Albert +Dep. of Computer Science, University of Otago, Dunedin, NZ"
+9d3ac3d29164c2665c371a3c71de75bea753eb47,Skeleton-Aided Articulated Motion Generation,"Skeleton-aided Articulated Motion Generation +Yichao Yan, Jingwei Xu, Bingbing Ni, Xiaokang Yang"
+9d35d4fba9217404a7aab84a7d09e53c324710be,Biometrics Project: Bayesian Face Recognition,"Biometrics Project: Bayesian Face Recognition +Jinwei Gu +Computer Science Department"
9d36c81b27e67c515df661913a54a797cd1260bb,3d Face Recognition Techniques - a Review,"Preeti.B.Sharma, Mahesh M. Goyani / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 1,Jan-Feb 2012, pp.787-793 @@ -2934,6 +10094,32 @@ Preeti B. Sharma*, Mahesh M. Goyani** *(Department of Information Technology, Gujarat Technological University, India) **( Department of Computer Engineering, Gujarat Technological University, India) security at many places"
+9d743bbef448e7c145aeb11e55cc05fdbafe9d6d,Person tracking and gesture recognition in challenging visibility conditions using 3D thermal sensing,"Person Tracking and Gesture Recognition +in Challenging Visibility Conditions +Using 3D Thermal Sensing +Ariel Kapusta and Patrick Beeson +IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) +August, 30, 2016"
+9dc70aa3d51a9403e1894a7fa535ace99b527861,3 Bayesian Tracking by Online Co-Training and Sequential Evolutionary Importance Resampling,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,700 +08,500 +.7 M +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact"
9d757c0fede931b1c6ac344f67767533043cba14,Search Based Face Annotation Using PCA and Unsupervised Label Refinement Algorithms,"Search Based Face Annotation Using PCA and Unsupervised Label Refinement Algorithms Shital Shinde1, Archana Chaugule2 @@ -2943,6 +10129,10 @@ Mahatma Phulenagar, 120/2 Mahaganpati soc, Chinchwad, Pune-19, MH, India D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18 Computer Department, D.Y.PIET, Pimpri, Pune-18, MH, India presents"
+9d1e32f6af50354b64ca8f004746073473559056,A visual surveillance system for person re-identification,"International Conference on Quality Control by Artificial Vision 2017, edited by Hajime Nagahara,Kazunori Umeda, Atsushi Yamashita, Proc. of SPIE Vol. 10338, 103380D · © 2017 SPIECCC code: 0277-786X/17/$18 · doi: 10.1117/12.2266509Proc. of SPIE Vol. 10338 103380D-1"
+9d5db7427b44d83bf036ff4cff382c23c6c7b6d8,Video redaction: a survey and comparison of enabling technologies,"Downloaded From: https://biomedicaloptics.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 10/14/2018 +Terms of Use: https://biomedicaloptics.spiedigitallibrary.org/terms-of-use +Videoredaction:asurveyandcomparisonofenablingtechnologiesShaganSahAmeyaShringiRaymondPtuchaAaronBurryRobertLoceShaganSah,AmeyaShringi,RaymondPtucha,AaronBurry,RobertLoce,“Videoredaction:asurveyandcomparisonofenablingtechnologies,”J.Electron.Imaging26(5),051406(2017),doi:10.1117/1.JEI.26.5.051406."
9d60ad72bde7b62be3be0c30c09b7d03f9710c5f,A Survey: Face Recognition Techniques,"A Survey: Face Recognition Techniques Arun Agrawal Assistant Professor, ITM GOI @@ -2951,6 +10141,7 @@ M Tech, ITM GOI video (Eigen passport-verification,"
+9d138bc60593c2770d968ba56172332773e02fa5,GPLAC: Generalizing Vision-Based Robotic Skills Using Weakly Labeled Images,
9d24179aa33a94c8c61f314203bf9e906d6b64de,Searching for People through Textual and Visual Attributes,"Searching for People through Textual and Visual Attributes Junior Fabian, Ramon Pires, Anderson Rocha @@ -2960,11 +10151,53 @@ Campinas-SP, Brazil Fig. 1. The proposed approach aims at searching for people using textual and visual attributes. Given an image database of faces, we extract the points of interest (PoIs) to construct a visual dictionary that allow us to obtain the feature vectors by a quantization process (top). Then we train attribute classifiers to generate a score for each image (middle). Finally, given a textual query (e.g., male), we fusion obtained scores to return a unique final rank (bottom)."
+9d9166e1d9e80bbe772423384af53a3d5da898ae,Object Geolocation Using MRF Based Multi-Sensor Fusion,"OBJECT GEOLOCATION USING MRF BASED MULTI-SENSOR FUSION +Vladimir A. Krylov and Rozenn Dahyot +ADAPT Centre, School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland"
+9d518344d5c7d889f9c90c6193be4757fa584770,3 D registration based on a multi-references local parametrisation : Application to 3 D faces,"D registration based on a multi-references local parametrisation: +Application to 3D faces +Wieme Gadacha1, Faouzi Ghorbel1 +CRISTAL laboratory, GRIFT research group +National School of Computer Sciences (NSCS), La Manouba 2010, Tunisia"
+9da2b79c6942852e8076cdaa4d4c93eb1ae363f1,Constraint-Based Visual Generation,"Constraint-Based Visual Generation +Giuseppe Marra +Francesco Giannini +Marco Gori +Michelangelo Diligenti +Department of Information Engineering and Mathematical Sciences +http://sailab.diism.unisi.it/ +October 9, 2018"
+9cabbb686883635d8755706ee4f1349d812d7ccb,Detection and Tracking of General Movable Objects in Large 3D Maps,"Detection and Tracking of General +Movable Objects in Large 3D Maps +Nils Bore, Johan Ekekrantz, Patric Jensfelt and John Folkesson +Robotics, Perception and Learning Lab +Royal Institute of Technology (KTH) +Stockholm, SE-100 44, Sweden +Email: {nbore, ekz, patric,"
+9cb152758ee57f2abcc0b59348752e528a2ed2f7,Full Video Processing for Mobile Audio-Visual Identity Verification,
+9cdb83ed96f5aa74bc4e2e9edacfbb5263e8fc37,Learning Mutual Visibility Relationship for Pedestrian Detection with a Deep Model,"Manuscript +Click here to download Manuscript: Mutual-DBN-J2.pdf +Click here to view linked References +Noname manuscript No. +(will be inserted by the editor) +Learning Mutual Visibility Relationship for Pedestrian Detection with a +Deep Model +Wanli Ouyang · Xingyu Zeng · Xiaogang Wang +Received: date / Accepted: date"
9c1305383ce2c108421e9f5e75f092eaa4a5aa3c,Speaker Retrieval for Tv Show Videos by Associating Audio Speaker Recognition Result to Visual Faces∗,"SPEAKER RETRIEVAL FOR TV SHOW VIDEOS BY ASSOCIATING AUDIO SPEAKER RECOGNITION RESULT TO VISUAL FACES∗ Yina Han*’, Joseph Razik’, Gerard Chollet’, and Guizhong Liu* *School of Electrical and Information Engineering, Xi’an Jiaotong University, Xi’an, China ’CNRS-LTCI, TELECOM-ParisTech, Paris, France"
+9cd7487e0eed11dabc94dd867178204c53eb2270,Self-Organizing Traffic Lights : A Pedestrian Oriented Approach,"Self-Organizing Traffic Lights: A Pedestrian +Oriented Approach +Jessica S. Souza1, Cesar A. M. Ferreira2, Cassio E. dos Santos Jr3, Victor H. C. Melo4, William Robson Schwartz4 +Computer Science Department, Federal University of Minas Gerais, Belo Horizonte, Brazil +the vehicular and pedestrian traffic. One of"
+9ca82f5936723a773fb44336cd66c315f2024d34,Latent-Class Hough Forests for 3D Object Detection and Pose Estimation,"Latent-Class Hough Forests for 3D Object Detection +nd Pose Estimation +Alykhan Tejani, Danhang Tang, Rigas Kouskouridas, and Tae-Kyun Kim +Imperial Collge London"
9c1860de6d6e991a45325c997bf9651c8a9d716f,3D reconstruction and face recognition using kernel-based ICA and neural networks,"D Reconstruction and Face Recognition Using Kernel-Based ICA and Neural Networks Cheng-Jian Lin Ya-Tzu Huang @@ -2973,6 +10206,55 @@ Dept. of Electrical Dept. of CSIE Dept. of CSI Engineering Chaoyang University Nankai Institute of National University of Technology Technology of Kaohsiung"
+9c341221e19fac7a5e38b9fe5c62361f780a7f08,Productivity Effects of Information Diffusion in Networks Paper 234,"A research and education initiative at the MIT +Sloan School of Management +Productivity Effects of Information +Diffusion in Networks +Paper 234 +July 2007 +Sinan Aral +Erik Brynjolfsson +Marshall Van Alstyne +For more information, +please visit our website at http://digital.mit.edu +or contact the Center directly at +or 617-253-7054"
+9c2f3e9c223153b70f37ee84224d67b5a577bd58,Towards unlocking web video: Automatic people tracking and clustering,"Towards Unlocking Web Video: Automatic People Tracking and Clustering +Alex Holub*, Pierre Moreels*, Atiq Islam*, Andrei Makhanov*, Rui Yang* +Ooyala Inc, 800 W. El Camino Real, Suite 350, Mountain View, CA 94040 +*All authors contributed equally to this work"
+9cc4abd2ec10e5fa94ff846c5ee27377caf17cf0,Improved Techniques for GAN based Facial Inpainting,"Improved Techniques for GAN based Facial +Inpainting +Avisek Lahiri*, Arnav Jain*, Divyasri Nadendla and Prabir Kumar Biswas, Senior Member, IEEE"
+9cf69de9e06e39f7f7ce643b3327bf69be8b9678,SHREC ’ 18 track : Recognition of geometric patterns over 3 D models,"SHREC’18 track: Recognition of geometric patterns +over 3D models +S Biasotti, E. Moscoso Thompson, L Bathe, S Berretti, A. Giachetti, T +Lejemble, N Mellado, K Moustakas, Iason Manolas, Dimitrios Dimou, et al. +To cite this version: +S Biasotti, E. Moscoso Thompson, L Bathe, S Berretti, A. Giachetti, et al.. SHREC’18 track: Recog- +nition of geometric patterns over 3D models. Eurographics Workshop on 3D Object Retrieval, 2018. +<hal-01774423> +https://hal-mines-paristech.archives-ouvertes.fr/hal-01774423 +HAL Id: hal-01774423 +Submitted on 30 Apr 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non,"
+9c576520ed9c960270715f790a62b9337ce88bd2,Beyond Pixels: Leveraging Geometry and Shape Cues for Online Multi-Object Tracking,"Beyond Pixels: Leveraging Geometry and Shape Cues for Online +Multi-Object Tracking +Sarthak Sharma1∗, Junaid Ahmed Ansari1∗, J. Krishna Murthy2, K. Mahdava Krishna1 +Robotics Research Center, KCIS, IIIT Hyderabad, India +Mila, Universite de Montreal, Canada +denotes equal contribution +Fig. 1. An illustration of the proposed method. The first two rows show objects tracks in frames t and t + 1. The bottom row depicts how 3D position +nd orientation information is propagated from frame t to frame t + 1. This information is used to specify search areas for each object in the subsequent +frame, and this greatly reduces the number of pairwise costs that are to be computed."
9ca7899338129f4ba6744f801e722d53a44e4622,Deep neural networks regularization for structured output prediction,"Deep Neural Networks Regularization for Structured Output Prediction Soufiane Belharbi∗ @@ -2991,6 +10273,74 @@ Normandie Univ, UNIROUEN, UNIHAVRE, Normandie Univ, UNIROUEN, UNIHAVRE, Normandie Univ, UNIROUEN, UNIHAVRE, Normandie Univ, UNIROUEN, UNIHAVRE,"
+9c3b9dee9da817134325357afbebbd1a0d67cab2,Deep Learning for Saliency Prediction in Natural Video,"Deep Learning for Saliency Prediction in Natural Video +Souad CHAABOUNIa,b, Jenny BENOIS-PINEAUa, Ofer HADARc, Chokri +BEN AMARb +Universit´e de Bordeaux, Laboratoire Bordelais de Recherche en Informatique, Bˆatiment +Sfax university, Research Groups in Intelligent Machines, National Engineering School of +A30, F-33405 Talence cedex, France +Communication Systems Engineering department, Ben Gurion University of the Nagev +Sfax (ENIS), Tunisia"
+9c731b820c495904a6f7d255d7e6a3bf9e5fc365,Geometric inpainting of 3D structures,"Geometric inpainting of 3D structures +Pratyush Sahay, A.N. Rajagopalan +Indian Institute of Technology Madras +Chennai, India"
+9c889616034adce2af05d74eac44cf43a8106468,Binary Quadratic Programing for Online Tracking of Hundreds of People in Extremely Crowded Scenes,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Binary Quadratic Programing for Online Tracking +of Hundreds of People in Extremely Crowded +Scenes +Afshin Dehghan, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
+9cf6d66a0b4e5a3347466a60caea411d67c4b5b7,Joint transfer component analysis and metric learning for person re-identification,"Joint transfer component analysis and +metric learning for person re-identification +Yixiu Liu, Yunzhou Zhang✉, Sonya Coleman and +Jianning Chi +nd efficient metric +A novel +learning strategy for person +re-identification is proposed. Person re-identification is formulated as +multi-domain learning problem. The assumption that the feature dis- +tributions from different camera views are the same is overthrown in +this Letter. ID-based transfer component analysis (IDB-TCA) is pro- +posed to learn a shared subspace, in which the differences in the +feature distribution between source domain and target domain are sig- +nificantly reduced. Experimental evaluation on the CUHK01 dataset +demonstrates that metric learning with IDB-TCA embedded outper- +forms state-of-art metric methods for person re-identification. +Introduction: Person re-identification, aiming to finding the images that +match the target person in a large-scale image library, greatly reduces the +time cost of human search. Due to its great significance to visual super- +vision, it has rapidly become a research hotspot in the field of computer"
+9c93512df188d7dbab63ebe47586a930559e6279,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+9cd8e1ccc5a410c7f31c7e404588597c0bb1952b,Whats Your Type ? Personalized Prediction of Facial Attractiveness,"Whats Your Type? Personalized Prediction of +Facial Attractiveness +Sam Crognale, Computer Science, Danish Shabbir Electrical Engineering +INTRODUCTION +Attempts to obtain a universal model of facial beauty by +the way of symmetry, golden ratios, and measured +placement of various facial features fall short in explaining +the varied attraction that is actually witnessed in the world. +In this investigation, we devise an application to give a user +some insight about their ‘type’ as users swipe yes or no on a +large dataset of images +There is a wealth of interesting literature attempting to +map the psychophysics of attraction. For example, Johnston +nd Franklin (1993) use a genetic algorithm which evolves a +“most beautiful” female face according to interactive user +selections. They sought to mimic the way humans filter for +features they find the most attractive. +Our approach builds on Kagian et. al (2007), where it was +shown that feature selection and training procedure with the +original geometric features instead of the eigenfeatures fails"
9c1664f69d0d832e05759e8f2f001774fad354d6,Action Representations in Robotics: A Taxonomy and Systematic Classification,"Action representations in robotics: A taxonomy and systematic classification Journal Title @@ -3001,6 +10351,41 @@ sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/ToBeAssigned www.sagepub.com/ Philipp Zech, Erwan Renaudo, Simon Haller, Xiang Zhang and Justus Piater"
+9caa7f125d3e861450bc3685699fceeaebea04d8,Designing Video Surveillance Systems as Services,"Designing Video Surveillance Systems as +Services +R. Cucchiara and A. Prati and R. Vezzani"
+9c2039d036c01e421176d33c1436633d03be4678,Review of person re-identification techniques,"Received on 21st February 2013 +Revised on 14th November 2013 +Accepted on 18th December 2013 +doi: 10.1049/iet-cvi.2013.0180 +www.ietdl.org +ISSN 1751-9632 +Review of person re-identification techniques +Mohammad Ali Saghafi1, Aini Hussain1, Halimah Badioze Zaman2, +Mohamad Hanif Md. Saad1 +Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM), Bangi, Malaysia +Institute of Visual Informatics, Universiti Kebangsaan Malaysia (UKM), Bangi, Malaysia +E-mail:"
+9c07704226e536834c4a8c01e1eb428584bacec6,Benchmarking Single-Image Dehazing and Beyond,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Benchmarking Single Image Dehazing and Beyond +Boyi Li*, Wenqi Ren*, Member, IEEE, Dengpan Fu*, Dacheng Tao, Fellow, IEEE, Dan Feng, Member, IEEE, +Wenjun Zeng, Fellow, IEEE and Zhangyang Wang†, Member, IEEE."
+9cc3172efb42d2f9fa1b9ae7b7eef9cc349cdef9,Imbalanced Deep Learning by Minority Class Incremental Rectification,"Imbalanced Deep Learning by Minority Class +Incremental Rectification +Qi Dong, Shaogang Gong, and Xiatian Zhu"
+9c59304a619b7d503be95bd560f90be976a5309a,DenseASPP for Semantic Segmentation in Street Scenes,"DenseASPP for Semantic Segmentation in Street Scenes +Maoke Yang +Kun Yu +Chi Zhang +DeepMotion +Zhiwei Li +Kuiyuan Yang +{maokeyang, kunyu, chizhang, zhiweili,"
+9cd3ea5cbbe0716fe19ff750940222cdedb22fc8,Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Scientific Question Answering,"Learning to Attend On Essential Terms: An Enhanced Retriever-Reader +Model for Scientific Question Answering +Jianmo Ni1,2∗, Chenguang Zhu1, Weizhu Chen1, Julian McAuley2 +Microsoft Business Applications Group AI Research +Department of Computer Science, UC San Diego"
9c065dfb26ce280610a492c887b7f6beccf27319,Learning from Video and Text via Large-Scale Discriminative Clustering,"Learning from Video and Text via Large-Scale Discriminative Clustering Antoine Miech1,2 Jean-Baptiste Alayrac1,2 @@ -3016,6 +10401,35 @@ Attribute Based Face Classification Using Support Vector Machine Brindha.M1, Amsaveni.R2 Research Scholar, Dept. of Computer Science, PSGR Krishnammal College for Women, Coimbatore Assistant Professor, Dept. of Information Technology, PSGR Krishnammal College for Women, Coimbatore."
+9c8da385750db215dc0728dc310251b320d319af,Deep embodiment: grounding semantics in perceptual modalities,"Technical Report +UCAM-CL-TR-899 +ISSN 1476-2986 +Number 899 +Computer Laboratory +Deep embodiment: +grounding semantics +in perceptual modalities +Douwe Kiela +February 2017 +5 JJ Thomson Avenue +Cambridge CB3 0FD +United Kingdom +phone +44 1223 763500 +http://www.cl.cam.ac.uk/"
+9c8a2d66b8fd6973751b8ee2fe6738327968cfcb,Exploring a model of far-from-equilibrium computation,"Exploring a model of far-from-equilibrium +omputation +R˘azvan V. Florian +Center for Cognitive and Neural Studies (Coneural) +Str. Saturn 24, 400504 Cluj-Napoca, Romania +July 10, 2005"
+9c49e4ba8ad0ba4634fe9306fb612695ed2b8cae,Satellite Imagery Feature Detection using Deep Convolutional Neural Network: A Kaggle Competition,"Satellite Imagery Feature Detection using +Deep Convolutional Neural Network: A Kaggle Competition +Vladimir Iglovikov +True Accord +Sergey Mushinskiy +Open Data Science +Vladimir Osin +AeroState"
9ce0d64125fbaf625c466d86221505ad2aced7b1,Recognizing expressions of children in real life scenarios View project PhD ( Doctor of Philosophy ) View project,"Saliency Based Framework for Facial Expression Recognition Rizwan Ahmed Khan, Alexandre Meyer, Hubert Konik, Saïda Bouakaz @@ -3036,9 +10450,54 @@ L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de"
+9c6d92f3d796242332ebf419a4f9b584864cfa15,Genetic Model Optimization for Hausdorff Distance-Based Face Localization,"(cid:176) In Proc. International ECCV 2002 Workshop on Biometric Authentication, +Springer, Lecture Notes in Computer Science, LNCS-2359, pp. 103{111, +Copenhagen, Denmark, June 2002. +Genetic Model Optimization +for Hausdorfi Distance-Based Face Localization +Klaus J. Kirchberg, Oliver Jesorsky, and Robert W. Frischholz +BioID AG, Germany +WWW home page: http://www.bioid.com"
+9ca2dfe8a6265c4f6ea12bae0e7ff6ffc9128226,Dialog-based Interactive Image Retrieval,"Dialog-based Interactive Image Retrieval +Xiaoxiao Guo† +IBM Research AI +Hui Wu† +IBM Research AI +Steven Rennie +Fusemachines Inc. +Gerald Tesauro +IBM Research AI"
+9cf07922cf91c4aea66c8d72606ca444f4607cc6,Distinct neural activation patterns underlie economic decisions in high and low psychopathy scorers.,"doi:10.1093/scan/nst093 +SCAN (2014) 9,1099^1107 +Distinct neural activation patterns underlie economic +decisions in high and low psychopathy scorers +Joana B. Vieira,1,2,3 Pedro R. Almeida,1,4 Fernando Ferreira-Santos,1 Fernando Barbosa,1 Joa˜o Marques-Teixeira,1 +nd Abigail A. Marsh3 +Laboratory of Neuropsychophysiology, Faculty of Psychology and Educational Sciences, 2Faculty of Medicine, University of Porto, 4200-135 +Porto, Portugal, 3Department of Psychology, Georgetown University, Washington, DC 20057, USA, and 4School of Criminology, Faculty of Law, +University of Porto, 4200-135 Porto, Portugal +Psychopathic traits affect social functioning and the ability to make adaptive decisions in social interactions. This study investigated how psychopathy +ffects the neural mechanisms that are recruited to make decisions in the ultimatum game. Thirty-five adult participants recruited from the community +underwent functional magnetic resonance imaging scanning while they performed the ultimatum game under high and low cognitive load. Across load +onditions, high psychopathy scorers rejected unfair offers in the same proportion as low scorers, but perceived them as less unfair. Among low +scorers, the perceived fairness of offers predicted acceptance rates, whereas in high scorers no association was found. Imaging results revealed +that responses in each group were associated with distinct patterns of brain activation, indicating divergent decision mechanisms. Acceptance of +unfair offers was associated with dorsolateral prefrontal cortex activity in low scorers and ventromedial prefrontal cortex activity in high scorers. Overall, +our findings point to distinct motivations for rejecting unfair offers in individuals who vary in psychopathic traits, with rejections in high psychopathy +scorers being probably induced by frustration. Implications of these results for models of ventromedial prefrontal cortex dysfunction in psychopathy +re discussed. +Keywords: psychopathy; functional magnetic resonance imaging; ultimatum game; ventromedial prefrontal cortex"
+022edc074693c52d4e689947bd2def8b2117fa8b,A super-resolution method for low-quality face image through RBF-PLS regression and neighbor embedding,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE +ICASSP 2012"
+022d74ae2f8680e780b18e0cbb041d5c5a57c7a5,Video Salient Object Detection via Fully Convolutional Networks,"Video Salient Object Detection via +Fully Convolutional Networks +Wenguan Wang, Jianbing Shen, Senior Member, IEEE, and Ling Shao, Senior Member, IEEE"
02601d184d79742c7cd0c0ed80e846d95def052e,Graphical Representation for Heterogeneous Face Recognition,"Graphical Representation for Heterogeneous Face Recognition Chunlei Peng, Xinbo Gao, Senior Member, IEEE, Nannan Wang, Member, IEEE, and Jie Li"
+02fbf86b975c3f45b04de8288d1565cce8b53f62,A real-time pedestrian detection system based on structure and appearance classification,"Anchorage Convention District +May 3-8, 2010, Anchorage, Alaska, USA +978-1-4244-5040-4/10/$26.00 ©2010 IEEE"
02e43d9ca736802d72824892c864e8cfde13718e,Transferring a semantic representation for person re-identification and search,"Transferring a Semantic Representation for Person Re-Identification and Search Shi, Z; Yang, Y; Hospedales, T; XIANG, T; IEEE Conference on Computer Vision and @@ -3056,6 +10515,16 @@ more information contact" 02fda07735bdf84554c193811ba4267c24fe2e4a,Illumination Invariant Face Recognition Using Near-Infrared Images,"Illumination Invariant Face Recognition Using Near-Infrared Images Stan Z. Li, Senior Member, IEEE, RuFeng Chu, ShengCai Liao, and Lun Zhang"
+02ccd5f0eb9a48a6af088197b950fb30a8e3abcc,Scaling for Multimodal 3D Object Detection,"Scaling for Multimodal 3D Object Detection +Andrej Karpathy +Stanford"
+02a99a43670ab83e77de9d935eb8d3d164e1972c,Joint Segmentation and Pose Tracking of Human in Natural Videos,"Joint Segmentation and Pose Tracking of Human in Natural Videos∗ +Taegyu Lim1,2 +Seunghoon Hong2 +Bohyung Han2 +Joon Hee Han2 +DMC R&D Center, Samsung Electronics, Korea +Department of Computer Science and Engineering, POSTECH, Korea"
0241513eeb4320d7848364e9a7ef134a69cbfd55,Supervised translation-invariant sparse coding,"Supervised Translation-Invariant Sparse Coding ¹Jianchao Yang, ²Kai Yu, and ¹Thomas Huang @@ -3066,6 +10535,77 @@ Yilin Wang1 Suhang Wang1 Jiliang Tang2 Huan Liu1 Baoxin Li1 Department of Computer Science, Arizona State Univerity Yahoo Research"
+026ca771bd3995748b477e100ed4283a9bf8215a,Predicting performance of a face recognition system based on image quality,"Predicting Performance of a Face +Recognition System Based on +Image Quality +Abhishek Dutta"
+023da8828f9c039c20ac9267a6b37813b74d4824,Free supervision from video games,"Free supervision from video games +Philipp Kr¨ahenb¨uhl +UT Austin"
+02086be014c4a276663e66ffde4d14f9c4cebe7e,BiggerPicture: data-driven image extrapolation using graph matching,"This is an Open Access document downloaded from ORCA, Cardiff University's institutional +repository: http://orca.cf.ac.uk/67868/ +This is the author’s version of a work that was submitted to / accepted for publication. +Citation for final published version: +Wang, Miao, Lai, Yukun, Liang, Yuan, Martin, Ralph Robert and Hu, Shi-Min 2014. Biggerpicture: +data-driven image extrapolation using graph matching. ACM Transactions on Graphics 33 (6) , 173. +0.1145/2661229.2661278 file +Publishers page: http://dx.doi.org/10.1145/2661229.2661278 +<http://dx.doi.org/10.1145/2661229.2661278> +Changes made as a result of publishing processes such as copy-editing, formatting and page +numbers may not be reflected in this version. For the definitive version of this publication, please +refer to the published source. You are advised to consult the publisher’s version if you wish to cite +Please note: +this paper. +This version is being made available in accordance with publisher policies. See +http://orca.cf.ac.uk/policies.html for usage policies. Copyright and moral rights for publications +made available in ORCA are retained by the copyright holders."
+02b0bf28f34c3c403abecd2fb4fb7d4969c0e0db,Learning Disentangled Joint Continuous and Discrete Representations,"Learning Disentangled Joint Continuous and Discrete +Representations +Schlumberger Software Technology Innovation Center +Emilien Dupont +Menlo Park, CA, USA"
+0252256fa23eceb54d9eea50c9fb5c775338d9ea,Application-driven Advances in Multi-biometric Fusion,"Application-driven Advances +in Multi-biometric Fusion +dem Fachbereich Informatik +der Technischen Universität Darmstadt +vorzulegende +DISSERTATION +zur Erlangung des akademischen Grades eines +Doktor-Ingenieurs (Dr.-Ing.) +M.Sc. Naser Damer +geboren in Amman, Jordanien +Referenten der Arbeit: +Prof. Dr. Arjan Kuijper +Technische Universität Darmstadt +Prof. Dr. Dieter W. Fellner +Technische Universität Darmstadt +Prof. Dr. Raghavendra Ramachandra +Norwegian University of Science and Technology +Tag der Einreichung: +Tag der mündlichen Prüfung: +2/01/2018"
+020d97ca2bf617b7ffed5a31aa8a27ffa5efadbb,An Efficient and Flexible FPGA Implementation of a Face Detection System,"Fekih, H. B., Elhossini, A., & Juurlink, B. +An Efficient and Flexible FPGA +Implementation of a Face Detection +System. +Chapter in book | +This version is available at https://doi.org/10.14279/depositonce-6778 +Accepted manuscript (Postprint) +This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer +Science. The final authenticated version is available online at: +http://dx.doi.org/10.1007/978-3-319-16214-0_20. +Fekih, H. B., Elhossini, A., & Juurlink, B. (2015). An Efficient and Flexible FPGA Implementation of a Face +Detection System. In Lecture Notes in Computer Science (pp. 243–254). Springer International +Publishing. https://doi.org/10.1007/978-3-319-16214-0_20 +Terms of Use +Copyright applies. A non-exclusive, non-transferable and +limited right to use is granted. This document is intended +solely for personal, non-commercial use."
+028dc6a134f1204bd9ae28213e2e6665e82ddcb0,Integral Normalized Gradient Image A Novel Illumination Insensitive Representation,"Integral Normalized Gradient Image +A Novel Illumination Insensitive +Representation +Samsung Advanced Institute of Technology +E-mail:"
029317f260b3303c20dd58e8404a665c7c5e7339,Character Identification in Feature-Length Films Using Global Face-Name Matching,"Character Identification in Feature-Length Films Using Global Face-Name Matching Yi-Fan Zhang, Student Member, IEEE, Changsheng Xu, Senior Member, IEEE, Hanqing Lu, Senior Member, IEEE, @@ -3078,17 +10618,278 @@ Crystal Lee§ Shiry Ginosar¶ Jake Williams(cid:107) December 1, 2016"
+02aff7faf2f6b775844809805424417eed30f440,"A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models","QUARTERLY OF APPLIED MATHEMATICS +VOLUME , NUMBER 0 +XXXX XXXX, PAGES 000–000 +A TALE OF THREE PROBABILISTIC FAMILIES: DISCRIMINATIVE, +DESCRIPTIVE AND GENERATIVE MODELS +YING NIAN WU (Department of Statistics, University of California, Los Angeles), +RUIQI GAO (Department of Statistics, University of California, Los Angeles), +TIAN HAN (Department of Statistics, University of California, Los Angeles), +SONG-CHUN ZHU (Department of Statistics, University of California, Los Angeles)"
02e133aacde6d0977bca01ffe971c79097097b7f,Convolutional Neural Fabrics,
02567fd428a675ca91a0c6786f47f3e35881bcbd,Deep Label Distribution Learning With Label Ambiguity,"ACCEPTED BY IEEE TIP Deep Label Distribution Learning With Label Ambiguity Bin-Bin Gao, Chao Xing, Chen-Wei Xie, Jianxin Wu, Member, IEEE, and Xin Geng, Member, IEEE"
+0296fc4d042ca8657a7d9dd02df7eb7c0a0017ad,Subspace Learning from Image Gradient Orientations,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +Subspace Learning from Image Gradient +Orientations +Georgios Tzimiropoulos, Member, IEEE, Stefanos Zafeiriou Member, IEEE, and Maja Pantic Fellow, IEEE"
+02bee2cef6b04e6b57cfa3fd54cabc756f0c2e8d,Data-driven methods for interactive visual content creation and manipulation,"Data-driven Methods for +Interactive Visual Content Creation +nd Manipulation +Dissertation zur Erlangung des Grades des +Doktors der Ingenieurwissenschaften der +Naturwissenschaftlich-Technischen Fakultäten der +Universität des Saarlandes +Vorgelegt durch +Arjun Jain +Max-Planck-Institut Informatik +Campus E1 4 +66123 Saarbrücken +Germany +m 4. February 2013 in Saarbrücken"
+02e9f1bb203a5ade98308eaff4f6a5c96a2c11e0,Self-Supervised Relative Depth Learning for Urban Scene Understanding,"Self-Supervised Relative Depth Learning for +Urban Scene Understanding +Huaizu Jiang1, +Erik Learned-Miller1 +Gustav Larsson2, Michael Maire3, Greg Shakhnarovich3 +UMass Amherst +University of Chicago +TTI-Chicago"
+02af5e40653b5a545b62aa6aebfaca6557f4173d,Sensor fusion for human safety in industrial workcells,"Sensor Fusion for Human Safety in Industrial Workcells* +Paul Rybski1, Peter Anderson-Sprecher1, Daniel Huber1, Chris Niessl1, Reid Simmons1 +Figure 1: An example of our approach. (a) The workcell as seen +y one of the 3D sensors. The red region indicates the adaptive +danger zone surrounding the moving robot arm. (b) As the person +enters the workcell, the green region indicates the adaptive safety +zone surrounding the person. (c) When the person gets too close +to the robot, the safety zone and danger zones intersect (shown +with a red circle), and the robot automatically halts. LIGHTEN THE +CONTRAST ON THESE FIGURES TO MAKE THEM EASIER TO SEE"
+029fa43a49a2f5df4bee8aa6a9574f8da5098f98,"Learning event representation: As sparse as possible, but not sparser","Learning event representation: As sparse as possible, but not sparser +Tuan Do and James Pustejovsky +Department of Computer Science +Brandeis University +Waltham, MA 02453 USA"
+027beed800f7d5e20194caf6d689345045e8d0d4,Smoothed Dilated Convolutions for Improved Dense Prediction,"Smoothed Dilated Convolutions for Improved Dense Prediction +Zhengyang Wang +Washington State University +Pullman, Washington, USA +Shuiwang Ji +Washington State University +Pullman, Washington, USA"
+02a2c5b332d883d726929474060a7e62411c010a,Totally Corrective Multiclass Boosting with Binary Weak Learners,"SEPTEMBER 2010 +with Binary Weak Learners +Zhihui Hao, Chunhua Shen, Nick Barnes, and Bo Wang"
+02f038ed453de0551813159284746126168f5e15,Multi Channel-Kernel Canonical Correlation Analysis for Cross-View Person Re-Identification,"This is a pre-print version, the final version of the manuscript with more experiments can be found at: +https://doi.org/10.1145/3038916 +Multi Channel-Kernel Canonical Correlation +Analysis for Cross-View Person Re-Identification +Giuseppe Lisanti, Svebor Karaman, Iacopo Masi"
+02e4025fd63f168810724156fb6b20b0b14dccdc,Local inter-session variability modelling for object classification,"This is the author’s version of a work that was submitted/accepted for pub- +lication in the following source: +Anantharajah, Kaneswaran, Ge, ZongYuan, McCool, Christopher, Den- +man, Simon, Fookes, Clinton B., Corke, Peter, Tjondronegoro, Dian W., & +Sridharan, Sridha +(2014) +Local inter-session variability modelling for object classification. In +014), 24-26 March 2014, Steamboat Springs, CO. +This file was downloaded from: https://eprints.qut.edu.au/67786/ +(cid:13) Copyright 2014 [please consult the author] +Notice: Changes introduced as a result of publishing processes such as +opy-editing and formatting may not be reflected in this document. For a +definitive version of this work, please refer to the published source:"
+02b72a5a4389cb32a7dd784b1c9084e8412e2e78,Hierarchical Bayesian Image Models,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,700 +08,500 +.7 M +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact"
+02e97e65fd0ec9a6d98a255d0396eb796a5e444a,Online Multiple View Tracking: Targets Association Across Cameras,"Q.LE, D.CONTE, M.HIDANE: COLLABORATIVE TRACKING +Online Multiple View Tracking: +Targets Association Across Cameras +Quoc Cuong LE1 +Donatello CONTE1 +Moncef HIDANE2 +LIFAT +University of Tours, +Tours, France +Computer Science Department +INSA Centre Val de Loire, +Blois, France"
0278acdc8632f463232e961563e177aa8c6d6833,Selective Transfer Machine for Personalized Facial Expression Analysis,"Selective Transfer Machine for Personalized Facial Expression Analysis Wen-Sheng Chu, Fernando De la Torre, and Jeffrey F. Cohn INTRODUCTION Index Terms—Facial expression analysis, personalization, domain adaptation, transfer learning, support vector machine (SVM) A UTOMATIC facial AU detection confronts a number of"
+0291b43490e02303c9414f03980e606950ec7261,Pose-conditioned joint angle limits for 3D human pose reconstruction,"Pose-Conditioned Joint Angle Limits for 3D Human Pose Reconstruction +Ijaz Akhter, Michael J. Black +Max Planck Institute for Intelligent Systems, Tübingen, Germany +Figure 1: Joint-limit dataset. We captured a new dataset for learning pose- +dependent joint angle limits. This includes an extensive variety of stretching +poses. A few sample images are shown here. We use this dataset to learn +pose-conditioned joint-angle limits. The dataset and the learned joint-angle +model will be made publicly available. +Figure 2: We use our joint-angle-limit prior for 3D pose estimation given +D joint locations in an image. The proposed prior helps in reducing the +space of possible solutions to only valid 3D human poses. Our prior can +e also used for many other problems where estimating 3D human pose is +mbiguous. +Accurate modeling of priors over 3D human pose is fundamental to many +problems in computer vision. Most previous priors are either not general +enough for the diverse nature of human poses or not restrictive enough to +void invalid 3D poses. We propose a physically-motivated prior that only +llows anthropometrically valid poses and restricts the ones that are invalid. +One can use joint-angle limits to evaluate whether two connected bones +re valid or not. However, it is established in biomechanics that there are"
+02bee6bf61566cfc3963fe42b320a740a9458920,Efficient Pedestrian Detection via Rectangular Features Based on a Statistical Shape Model,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +Efficient Pedestrian Detection via Rectangular +Features Based on a Statistical Shape Model +Shanshan Zhang, Student Member, IEEE, Christian Bauckhage, Member, IEEE, and Armin B. Cremers"
+02a88a2f2765b17c9ea76fe13148b4b8a9050b95,DeepPose: Human Pose Estimation via Deep Neural Networks,"DeepPose: Human Pose Estimation via Deep Neural Networks +Alexander Toshev +Christian Szegedy +Google +600 Amphitheatre Pkwy +Mountain View, CA 94043 +mainly by the first challenge, the need to search in the large +space of all possible articulated poses. Part-based models +lend themselves naturally to model articulations ([16, 8]) +nd in the recent years a variety of models with efficient +inference have been proposed ([6, 19]). +The above efficiency, however, is achieved at the cost of +limited expressiveness – the use of local detectors, which +reason in many cases about a single part, and most impor- +tantly by modeling only a small subset of all interactions +etween body parts. These limitations, as exemplified in +Fig. 1, have been recognized and methods reasoning about +pose in a holistic manner have been proposed [15, 21] but +with limited success in real-world problems. +In this work we ascribe to this holistic view of human"
+02d6df5060281cf13fbef68a8f1ddc29983fe8b3,An Enhanced Default Approach Bias Following Amygdala Lesions in Humans.,"583804 PSSXXX10.1177/0956797615583804Harrison et al.Default Approach Bias Following Amygdala Lesions +research-article2015 +Research Article +An Enhanced Default Approach Bias +Following Amygdala Lesions in Humans +1 –13 +© The Author(s) 2015 +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0956797615583804 +pss.sagepub.com +Laura A. Harrison1, Rene Hurlemann2, and Ralph Adolphs1 +California Institute of Technology and 2University of Bonn"
+02cce8b08e4839d16f2142c5723fc009ccb4e3e1,Improving spatial codification in semantic segmentation,"IMPROVING SPATIAL CODIFICATION IN SEMANTIC SEGMENTATION +Carles Ventura(cid:63) +Kevin McGuinness† +Xavier Gir´o-i-Nieto(cid:63) +Ferran Marqu´es(cid:63) +Ver´onica Vilaplana(cid:63) +Noel E. O’Connor† +(cid:63) Universitat Polit`ecnica de Catalunya (UPC), Barcelona, Spain +Insight Centre for Data Analytics, Dublin City University (DCU), Ireland"
+026050f71175d235f3f91ca0e99e994c00f9b5a6,Supervised Discrete Hashing,"Supervised Discrete Hashing +Fumin Shen1, Chunhua Shen2, Wei Liu3, Heng Tao Shen4 +University of Electronic Science and Technology of China. 2 University of Adelaide; and Australian Centre for Robotic Vision. 3IBM Research. +The University of Queensland. +Recently, learning based hashing techniques have attracted broad research +interests due to the resulting efficient storage and retrieval of images, videos, +documents, etc. However, a major difficulty of learning to hash lies in han- +dling the discrete constraints imposed on the needed hash codes. In general, +the discrete constraints imposed on the binary codes that the target hash +functions generate lead to mixed-integer optimization problems—which is +generally NP hard. To simplify the optimization involved in a binary code +learning procedure, most of the aforementioned methods choose to first +solve a relaxed problem through directly discarding the discrete constraints, +nd then threshold the continuous outputs to be binary. This greatly simpli- +fies the optimization but, unfortunately, the approximated solution is typi- +ally of low quality and often makes the final hash functions less effective, +possibly due to the accumulated quantization errors. This is especially the +ase when long-length codes are needed. +Directly learning the binary codes without relaxations would be pre- +ferred if (and only if) a tractable and scalable solver is available. The impor-"
+026509ad687f9cdaba8f2dac0fe5720e0553a8bd,Integrated pedestrian classification and orientation estimation,"Integrated Pedestrian Classification +nd Orientation Estimation +Markus Enzweiler1 +Dariu M. Gavrila2,3 +Image & Pattern Analysis Group, Univ. of Heidelberg, Germany +Environment Perception, Group Research, Daimler AG, Ulm, Germany +Intelligent Autonomous Systems Group, Univ. of Amsterdam, The Netherlands"
+02f1d5c896ced7f6f002eb7514ba49eca940b75c,A Comparison of Efficient Global Image Features for Localizing Small Mobile Robots,"A Comparison of Efficient Global Image Features +for Localizing Small Mobile Robots +Marius Hofmeister, Philipp Vorst and Andreas Zell +Computer Science Department, University of Tübingen, Tübingen, Germany"
+a49b661e42aea6f205e543a80106fc9c6ff0f9d4,Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry,"Deep Virtual Stereo Odometry: +Leveraging Deep Depth Prediction for +Monocular Direct Sparse Odometry +Nan Yang1,2, Rui Wang1,2, J¨org St¨uckler1, and Daniel Cremers1,2 +Technical University of Munich +Artisense"
+a45450824c6e8e6b42fd9bbf52871104b6c6ce8b,Optimizing the Latent Space of Generative Networks,"Optimizing the Latent Space of Generative Networks +Piotr Bojanowski, Armand Joulin, David Lopez-Paz, Arthur Szlam +{bojanowski, ajoulin, dlp, +Facebook AI Research"
+a46f285b928aa547df8d8d8d63d2f9256a73aae7,Networked Decision Making for Poisson Processes With Applications to Nuclear Detection,"[16] E. D. Sontag, “Input-to-state stability: Basic concepts and results,” in +Nonlinear and Optimal Control Theory, P. Nistri and G. Stefani, Eds. +Berlin, Germany: Springer–Verlag, 2006, pp. 163–220. +[17] Z.-P. Jiang, A. R. Teel, and L. Praly, “Small-gain theorem for ISS sys- +tems and applications,” Mathem. of Control, Signals, and Syst., vol. 7, +pp. 95–120, 1994. +[18] A. R. Teel, “A nonlinear small gain theorem for the analysis of control +systems with saturation,” IEEE Trans. Autom. Control, vol. AC-41, no. +9, pp. 1256–1270, Sep. 1996. +[19] Z.-P. Jiang and I. M. Y. Mareels, “A small-gain control method for +nonlinear cascaded systems with dynamic uncertainties,” IEEE Trans. +Autom. Control, vol. 42, no. 3, pp. 292–308, Mar. 1997. +[20] S. Dashkovskiy, Z.-P. Jiang, and B. Rüffer, “Special issue on robust sta- +ility and control of large-scale nonlinear systems,” Mathem. of Con- +trol, Signals, and Syst., vol. 24, no. 1, pp. 1–2, 2012. +[21] H. K. Khalil, Nonlinear Systems, third ed. Upper Saddle River, NJ: +Prentice–Hall, 2002. +[22] R. A. Horn and C. R. Johnson, Matrix Analysis. Cambridge, U.K.: +Cambridge University Press, 1985. +[23] W. Ren and R. W. Beard, “Consensus seeking in multiagent systems"
+a49acd70550c209965a6d39d7ff92d11f0a5b1b6,"YouTube Scale, Large Vocabulary Video Annotation","YouTube Scale, Large Vocabulary +Video Annotation +Nicholas Morsillo, Gideon Mann and Christopher Pal"
+a427ee25ef515ddd9cf50b4cc3a7376f57d58926,Human-Drone-Interaction: A Case Study to Investigate the Relation Between Autonomy and User Experience,"Human-Drone-Interaction: A Case Study to +Investigate the Relation between Autonomy and +User Experience +Patrick Ferdinand Christ1,3(cid:63), Florian Lachner2,3(cid:63), Axel H¨osl3, Bjoern Menze1, +Klaus Diepold3, and Andreas Butz2 +Image-based Biomedical Modeling Group, +Technical University of Munich (TUM) +{patrick.christ, +Chair for Human-Computer-Interaction, +University of Munich (LMU) +{florian.lachner, axel.hoesl, +Center for Digital and Technology Management, +TUM and LMU +Chair for Data Processing, +Technical University of Munich (TUM)"
+a4a90a2db209db2d5c49adfd2091ede2d4130f60,Interactive Grounded Language Acquisition and Generalization in a 2D World,"Published as a conference paper at ICLR 2018 +INTERACTIVE GROUNDED LANGUAGE ACQUISITION +AND GENERALIZATION IN A 2D WORLD +Haonan Yu1, Haichao Zhang1 & Wei Xu1,2 +Baidu Research, Sunnyvale USA +National Engineering Laboratory for Deep Learning Technology and Applications, Beijing China"
a4a5ad6f1cc489427ac1021da7d7b70fa9a770f2,Gated spatio and temporal convolutional neural network for activity recognition: towards gated multimodal deep learning,"Yudistira and Kurita EURASIP Journal on Image and Video Processing (2017) 2017:85 DOI 10.1186/s13640-017-0235-9 @@ -3100,6 +10901,53 @@ Gated spatio and temporal convolutional neural network for activity recognition: towards gated multimodal deep learning Novanto Yudistira1* and Takio Kurita2"
+a4f38e32c23fd1f5a1e1157a4e62b38731f2e5d8,Online Learning for Ship Detection in Maritime Surveillance,"Online Learning for Ship Detection +in Maritime Surveillance +Rob Wijnhoven1 +ViNotion1 +, Kris van Rens1, Egbert G. T. Jaspers1, Peter H. N. de With2 +University of Technol. Eindhoven2 CycloMedia Technol.3 +P.O. Box 2346 +5600 CH Eindhoven +The Netherlands +P.O. Box 513 +5600 MB Eindhoven +The Netherlands"
+a416513aaf97060287bf3e64ccdc1ccf85106c07,Seasonal Separation of African Savanna Components Using Worldview-2 Imagery: A Comparison of Pixel- and Object-Based Approaches and Selected Classification Algorithms,"Article +Seasonal Separation of African Savanna Components +Using Worldview-2 Imagery: A Comparison of Pixel- +nd Object-Based Approaches and Selected +Classification Algorithms +˙Zaneta Kaszta 1,2,*, Ruben Van De Kerchove 1,3, Abel Ramoelo 4, Moses Azong Cho 4, +Sabelo Madonsela 4, Renaud Mathieu 4,5 and Eléonore Wolff 1 +Institut de Gestion de l’Environnement et d’Aménagement de Territoire (IGEAT), +Université Libre de Bruxelles, Brussels 1050, Belgium; +School of Applied Environmental Sciences, Pietermaritzburg 3209, South Africa +Mol 2400, Belgium; +Council for Scientific and Industrial Research, Pretoria 0001, South Africa; (A.R.); +(M.A.C.); (S.M.); (R.M.) +5 Department of Geography, Geoinformatics and Meteorology, University of Pretoria, +Pretoria 0028, South Africa +* Correspondence: Tel.: +32-02-650-68-20 +Academic Editors: Giles M. Foody, Magaly Koch, Clement Atzberger and Prasad S. Thenkabail +Received: 15 May 2016; Accepted: 8 September 2016; Published: 16 September 2016"
+a4bab165158b9627280fb3052b1c731210f2a901,"Pedestrian Localization, Tracking and Behavior Analysis from Multiple Cameras","Pedestrian Localization, Tracking and Behavior Analysis +from Multiple Cameras +THÈSE NO 4629 (2010) +PRÉSENTÉE LE 9 AVRIL 2010 +À LA FACULTÉ INFORMATIQUE ET COMMUNICATIONS +LABORATOIRE DE VISION PAR ORDINATEUR +PROGRAMME DOCTORAL EN INFORMATIQUE, COMMUNICATIONS ET INFORMATION +ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE +POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES +Jérôme BERCLAZ +cceptée sur proposition du jury: +Prof. P. Thiran, président du jury +Prof. P. Fua, Dr F. Fleuret, directeurs de thèse +Prof. M. Bierlaire, rapporteur +Prof. H. Bischof, rapporteur +Dr J. Ferryman, rapporteur +Suisse"
a40f8881a36bc01f3ae356b3e57eac84e989eef0,"End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks","End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks @@ -3124,10 +10972,50 @@ Dr. Julian Urbano Merino Dr. Silvia-Laura Pintea Dr. Ildiko Suveg (Bosch) Dr. Gonzalez Adrlana (Bosch)"
+a4ee9f089ab9a48a6517a6967281247339a51747,Resembled Generative Adversarial Networks: Two Domains with Similar Attributes,"DUHYEON BANG, HYUNJUNG SHIM: RESEMBLED GAN +Resembled Generative Adversarial Networks: +Two Domains with Similar Attributes +School of Integrated Technology, Yonsei +University, South Korea +Duhyeon Bang +Hyunjung Shim"
+a47e51dd3f73817679ff0e987a0064d43db25060,Grad-CAM: Why did you say that? Visual Explanations from Deep Networks via Gradient-based Localization,"Visual Explanations from Deep Networks via Gradient-based Localization +Grad-CAM: Why did you say that? +Ramprasaath R. Selvaraju +Abhishek Das +Devi Parikh +Ramakrishna Vedantam +Dhruv Batra +Virginia Tech +Michael Cogswell +{ram21, abhshkdz, vrama91, cogswell, parikh, +(a) Original Image +(b) Guided Backprop ‘Cat’ +(c) Grad-CAM for ‘Cat’ +(d) Guided Grad-CAM ‘Cat’ +(e) Occlusion Map ‘Cat’ +(f) ResNet Grad-CAM ‘Cat’ +(g) Original Image +(h) Guided Backprop ‘Dog’ +(i) Grad-CAM for ‘Dog’ +(l) ResNet Grad-CAM ‘Dog’"
+a44b91f46ba66c8279b93caab6842444de0c9343,Frequency-domain Tracking Spatial-domain Detection Generic Object Proposal Histogram based Representation Detection Result Tracking State Estimation Spatial Regressor Correlation Model IFFT Search Space Feature Extraction Correlation Map Correlation Model FFT,"Monocular Long-term Target Following on UAVs +Rui Li ∗ +Minjian Pang† +Cong Zhao ‡ +Guyue Zhou ‡ +Lu Fang †§"
+a493a731dadababb6f2ae0b4b6233d861206345b,Studio2Shop: from studio photo shoots to fashion articles,"Studio2Shop: from studio photo shoots to fashion articles +Julia Lasserre1, Katharina Rasch1 and Roland Vollgraf +Zalando Research, Muehlenstr. 25, 10243 Berlin, Germany +Keywords: +omputer vision, deep learning, fashion, item recognition, street-to-shop"
a44590528b18059b00d24ece4670668e86378a79,Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization,"Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization Jinshi Yu, Guoxu Zhou, Andrzej Cichocki IEEE Fellow, and Shengli Xie IEEE Senior Member"
+a453863082a7fb42c9b402023294390eb4167fbe,Identifying Where to Focus in Reading Comprehension for Neural Question Generation,"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2067–2073 +Copenhagen, Denmark, September 7–11, 2017. c(cid:13)2017 Association for Computational Linguistics"
a472d59cff9d822f15f326a874e666be09b70cfd,Visual Learning with Weakly Labeled Video a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"VISUAL LEARNING WITH WEAKLY LABELED VIDEO A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE @@ -3138,6 +11026,8 @@ FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Kevin Tang May 2015"
+a47ac8569ab1970740cff9f1643f77e9143a62d4,Associative Compression Networks for Representation Learning,"Associative Compression Networks for Representation Learning +Alex Graves 1 Jacob Menick 1 A¨aron van den Oord 1"
a4c430b7d849a8f23713dc283794d8c1782198b2,Video Concept Embedding,"Video Concept Embedding Anirudh Vemula Rahul Nallamothu @@ -3158,10 +11048,53 @@ In the computer vision domain, video understanding is a very important topic. It is made hard due to the large mount of high dimensional data in videos. One strategy"
+a48c71153265d6da7fbc4b16327320a5cbfa6cba,Unite the People: Closing the loop between 3D and 2D Human Representations Supplementary Material,"Unite the People: Closing the loop between 3D and 2D Human Representations +Supplementary Material +Christoph Lassner1,2 +Javier Romero2 +Martin Kiefel2 +Federica Bogo2,3 +Michael J. Black2 +Peter V. Gehler1,2 +Bernstein Center for Comp. Neuroscience1 +Max-Planck Institute for Intelligent Systems2 +Microsoft3 +Otfried-M¨uller-Str. 25, T¨ubingen +Spemannstr. 41, T¨ubingen +1 Station Rd., Cambridge +. Introduction +We have obtained human segmentation labels to inte- +grate shape information into the SMPLify 3D fitting pro- +edure and for the evaluation of methods introduced in the +main paper. The labels consist of foreground segmentation +for multiple human pose datasets and six body part segmen-"
a4f37cfdde3af723336205b361aefc9eca688f5c,Recent Advances in Face Recognition,"Recent Advances in Face Recognition"
+a32ebfa79097fdf5c9d44d2f74e33b7c8343425c,A Deeper Look at Dataset Bias,"Chapter 2 +A Deeper Look at Dataset Bias +Tatiana Tommasi, Novi Patricia, Barbara Caputo and Tinne Tuytelaars"
a30869c5d4052ed1da8675128651e17f97b87918,Fine-Grained Comparisons with Attributes,"Fine-Grained Comparisons with Attributes Aron Yu and Kristen Grauman"
+a32f28156b47fd262e04426806037d138bb3ed0b,Fisher’s linear discriminant (FLD) and support vector machine (SVM) in non-negative matrix factorization (NMF) residual space for face recognition,"Optica Applicata, Vol. XL, No. 3, 2010 +Fisher’s linear discriminant (FLD) +nd support vector machine (SVM) +in non-negative matrix factorization (NMF) +residual space for face recognition +CHANGJUN ZHOU, XIAOPENG WEI*, QIANG ZHANG, XIAOYONG FANG +Key Laboratory of Advanced Design and Intelligent Computing, Dalian University, +Ministry of Education, Dalian, 116622, China +*Corresponding author: +A novel method of Fisher’s linear discriminant (FLD) in the residual space is put forward for +the representation of face images for face recognition, which is robust to the slight local +feature changes. The residual images are computed by subtracting the reconstructed images from +the original face images, and the reconstructed images are obtained by performing non-negative +matrix factorization (NMF) on original images. FLD is applied to the residual images for extracting +FLD subspace and the corresponding coefficient matrices. Furthermore, features are obtained by +mapping the residual image to FLD subspace. Finally, the features are utilized to train and test +support vector machines (SVMs) for face recognition. The computer simulation illustrates that +this method is effective on the ORL database and the extended Yale face database B. +Keywords: face recognition, Fisher linear discriminant (FLD), non-negative matrix factorization (NMF), +residual image."
a3ebacd8bcbc7ddbd5753935496e22a0f74dcf7b,"First International Workshop on Adaptive Shot Learning for Gesture Understanding and Production ASL4GUP 2017 Held in conjunction with IEEE FG 2017, in May 30, 2017, Washington DC, USA","First International Workshop on Adaptive Shot Learning for Gesture Understanding and Production ASL4GUP 2017 @@ -3174,6 +11107,9 @@ Anoop Namboodiri (cid:63) Manohar Paluri † Facebook AI Research C. V. Jawahar (cid:63)"
+a3fdba7975494c34552b33cf839f21d62734e6f0,Excavate Condition-invariant Space by Intrinsic Encoder,"Excavate Condition-invariant Space by Intrinsic Encoder +Jian Xu, Chunheng Wang, Cunzhao Shi, and Baihua Xiao +Institute of Automation, Chinese Academy of Sciences (CASIA)"
a3017bb14a507abcf8446b56243cfddd6cdb542b,Face Localization and Recognition in Varied Expressions and Illumination,"Face Localization and Recognition in Varied Expressions and Illumination Hui-Yu Huang, Shih-Hang Hsu"
@@ -3183,11 +11119,21 @@ nd Probability Maps Henrique Morimitsu1(B), Roberto M. Cesar Jr.1, and Isabelle Bloch2 University of S˜ao Paulo, S˜ao Paulo, Brazil Institut Mines T´el´ecom, T´el´ecom ParisTech, CNRS LTCI, Paris, France"
+a3ccf7fa5c130c8bcd20cbcd356ad7a47cdd4296,SymNMF: nonnegative low-rank approximation of a similarity matrix for graph clustering,"Journal of Global Optimization manuscript No. +(will be inserted by the editor) +SymNMF: Nonnegative Low-Rank Approximation of +Similarity Matrix for Graph Clustering +Da Kuang · Sangwoon Yun · Haesun Park +The final publication is available at Springer via http://dx.doi.org/10.1007/s10898-014-0247-2."
a378fc39128107815a9a68b0b07cffaa1ed32d1f,Determining a Suitable Metric when Using Non-Negative Matrix Factorization,"Determining a Suitable Metric When using Non-negative Matrix Factorization∗ David Guillamet and Jordi Vitri`a Computer Vision Center, Dept. Inform`atica Universitat Aut`onoma de Barcelona 08193 Bellaterra, Barcelona, Spain"
+a32dadf343f811e6837b8ac5bab873674fa626b3,Moving Object Detection and Tracking in Forward Looking Infra-Red Aerial Imagery,"Moving Object Detection and Tracking +in Forward Looking Infra-Red Aerial Imagery +Subhabrata Bhattacharya, Haroon Idrees, Imran Saleemi, Saad Ali +nd Mubarak Shah"
a34d75da87525d1192bda240b7675349ee85c123,Naive-Deep Face Recognition: Touching the Limit of LFW Benchmark or Not?,"Naive-Deep Face Recognition: Touching the Limit of LFW Benchmark or Not? Erjin Zhou Face++, Megvii Inc. @@ -3226,18 +11172,140 @@ Dissertations, Professional Papers, and Capstones. 366. http://digitalscholarship.unlv.edu/thesesdissertations/366 This Thesis is brought to you for free and open access by Digital It has been accepted for inclusion in UNLV Theses, Dissertations, Professional Papers, and Capstones by an authorized administrator of Digital For more information, please contact"
+a357bc79b1ac6f2474ff6b9f001419745a8bc21c,Toward More Realistic Face Recognition Evaluation Protocols for the YouTube Faces Database,"Toward More Realistic Face Recognition Evaluation Protocols +for the YouTube Faces Database +Yoanna Mart´ınez-D´ıaz, Heydi M´endez-V´azquez, Leyanis L´opez-Avila +Advanced Technologies Application Center (CENATAV) +7A ♯21406 Siboney, Playa, P.C. 12200, Havana, Cuba +Leonardo Chang +L. Enrique Sucar +Massimo Tistarelli +Tecnol´ogico de Monterrey, +Estado de Mexico, Mexico +INAOE, +University of Sassari, +Puebla, Mexico +Sassari, Italy"
a3f78cc944ac189632f25925ba807a0e0678c4d5,Action Recognition in Realistic Sports Videos,"Action Recognition in Realistic Sports Videos Khurram Soomro and Amir Roshan Zamir"
+a3177f82ea8391d9d733be47e4a0656a7b56e64c,The Roles of Emotions in the Law,"Emotion Researcher | ISRE's Sourcebook for Research on Emotion and Affect +Emotion Researcher +ISRE's Sourcebook for Research on Emotion and Affect +Interviews +Articles +Spotlight +Contact +How To Cite ER +Table of Contents +New Editor Search +THE ROLES OF EMOTIONS IN THE LAW +Time for new blood at the helm of Emotion +Researcher! ISRE is seeking one or more new +editors, who should take over in April 2017. It +is a fun and highly rewarding job. Nominations +of suitable candidates are also encouraged. +Editor’s Column +In this issue of Emotion Researcher, we focus on the roles emotions play in the law. We will explore +the emotions of jurors, judges, defendants, attorneys and other legal actors. +Call for Papers"
+a3fd234763844663f72a8fa22a076eeadce7245c,DelugeNets: Deep Networks with Efficient and Flexible Cross-Layer Information Inflows,"DelugeNets: Deep Networks with Efficient and Flexible Cross-layer Information +Inflows +Jason Kuen1 +Xiangfei Kong1 +Gang Wang2 +Yap-Peng Tan1 +Nanyang Technological University1 Alibaba Group2"
+a30e987e9909a4e307c35809275cf80431211f22,Automatic Sapstain Detection in Processed Timber Through Image Feature Analysis,"Automatic Sapstain Detection in Processed +Timber Through Image Feature Analysis +Jeremiah Deng +The Information Science +Discussion Paper Series +Number 2009/04 +April 2009 +ISSN 1177-455X"
+a3fe284b029269ad5f071dd37bb137593c67dfc2,Feature Learning for the Image Retrieval Task,"Feature Learning for the Image Retrieval Task +Aakanksha Rana, Joaquin Zepeda, Patrick Perez +Technicolor R&I, 975 avenue des Champs Blancs, CS 17616, 35576 Cesson Sevigne, France"
+a3a6e3cadfed3c0a520e4417fc27da561324fbc6,Facing the challenge of teaching emotions to individuals with low- and high-functioning autism using a new Serious game: a pilot study,"Serret et al. Molecular Autism 2014, 5:37 +http://www.molecularautism.com/content/5/1/37 +R ES EAR CH +Facing the challenge of teaching emotions to +individuals with low- and high-functioning autism +using a new Serious game: a pilot study +Sylvie Serret1*, Stephanie Hun1, Galina Iakimova2, Jose Lozada3, Margarita Anastassova3, Andreia Santos1, +Stephanie Vesperini1 and Florence Askenazy4 +Open Access"
+a32f693e98ae35da5508c8eee245a876b6e130a1,Small Sample Scene Categorization from Perceptual Relations Ilan Kadar and,"Small Sample Scene Categorization from Perceptual Relations +Ilan Kadar and Ohad Ben-Shahar +Dept. of Computer Science, Ben-Gurion University +Beer-Sheva, Israel"
+a3fcf3d32a5a4fcc83027e3d367ecc0df3ec4f64,Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength,"Iris Recognition: On the Segmentation +of Degraded Images Acquired +in the Visible Wavelength +Hugo Proenc¸ a"
+a3ed080262f130051d2a02e846f5d227a440b294,ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time,"ContextNet: Exploring Context and Detail +for Semantic Segmentation in Real-time +Rudra P K Poudel, Ujwal Bonde, Stephan Liwicki, and Christopher Zach +Toshiba Research, Cambridge, UK"
+a35d85c2efd1fb090267980ebb3fd7b6381e3b74,Very Low Resolution Image Classification,"Very Low Resolution Image Classification +Adam Vest1 +Muhammadabdullah Jamal2 +Boqing Gong2 +University of Louisville 2 University of Central Florida"
a3a6a6a2eb1d32b4dead9e702824375ee76e3ce7,Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition,"Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition Anıl Y¨uce, Nuri Murat Arar and Jean-Philippe Thiran Signal Processing Laboratory (LTS5), ´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland"
+a33262933df8534de571027d78ccd936bb9ec263,Real-Time Deep Learning Method for Abandoned Luggage Detection in Video,"Real-Time Deep Learning Method for Abandoned Luggage Detection in Video +University of Bucharest, 14 Academiei, Bucharest, Romania +Sorina Smeureanu∗‡, Radu Tudor Ionescu∗‡ +SecurifAI, 24 Mircea Vod˘a, Bucharest, Romania +E-mails:"
a32c5138c6a0b3d3aff69bcab1015d8b043c91fb,Video redaction: a survey and comparison of enabling technologies,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/19/2018 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use Videoredaction:asurveyandcomparisonofenablingtechnologiesShaganSahAmeyaShringiRaymondPtuchaAaronBurryRobertLoceShaganSah,AmeyaShringi,RaymondPtucha,AaronBurry,RobertLoce,“Videoredaction:asurveyandcomparisonofenablingtechnologies,”J.Electron.Imaging26(5),051406(2017),doi:10.1117/1.JEI.26.5.051406."
+a3bf7248e38ed6f9456f0f309b36470c5c0dabd0,Predicting the Driver's Focus of Attention: the DR(eye)VE Project,"Predicting the Driver’s Focus of Attention: +the DR(eye)VE Project +Andrea Palazzi∗, Davide Abati∗, Simone Calderara, Francesco Solera, and Rita Cucchiara"
a3eab933e1b3db1a7377a119573ff38e780ea6a3,Sparse Representation for accurate classification of corrupted and occluded facial expressions,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE ICASSP 2010"
+a308ad39f3cc25096f493280319621a25c2c7f46,Monocular 3D Scene Modeling and Inference: Understanding Multi-Object Traffic Scenes,"Monocular 3D Scene Modeling and Inference: +Understanding Multi-Object Traffic Scenes +Christian Wojek1,2, Stefan Roth1, Konrad Schindler1,3, and Bernt Schiele1,2 +Computer Science Department, TU Darmstadt +MPI Informatics, Saarbr¨ucken +Photogrammetry and Remote Sensing Group, ETH Z¨urich"
+a3be57fc74460463f03c2a14e81e7e62c05c692e,Object Detection,"Object Detection +Yali Amit and Pedro Felzenszwalb, University of Chicago +Related Concepts +– Object Recognition +– Image Classification +Definition +Object detection involves detecting instances of objects from a particular +lass in an image. +Background +The goal of object detection is to detect all instances of objects from a known +lass, such as people, cars or faces in an image. Typically only a small number +of instances of the object are present in the image, but there is a very large +number of possible locations and scales at which they can occur and that need +to somehow be explored. +Each detection is reported with some form of pose information. This could +e as simple as the location of the object, a location and scale, or the extent +of the object defined in terms of a bounding box. In other situations the pose +information is more detailed and contains the parameters of a linear or non-linear +transformation. For example a face detector may compute the locations of the +eyes, nose and mouth, in addition to the bounding box of the face. An example"
+a3b87364aa68b371ca9831d333b934402fbc3713,Which neural mechanisms mediate the effects of a parenting intervention program on parenting behavior: design of a randomized controlled trial,"Kolijn et al. BMC Psychology (2017) 5:9 +DOI 10.1186/s40359-017-0177-0 +Open Access +ST UD Y P R O T O C O L +Which neural mechanisms mediate the +effects of a parenting intervention program +on parenting behavior: design of a +randomized controlled trial +Laura Kolijn1,2,3, Saskia Euser1,2,3, Bianca G. van den Bulk1,2,3, Renske Huffmeijer1,2,3, +Marinus H. van IJzendoorn1,2,3 and Marian J. Bakermans-Kranenburg1,2,3*"
a3a34c1b876002e0393038fcf2bcb00821737105,Face Identification across Different Poses and Illuminations with a 3D Morphable Model,"Face Identification across Different Poses and Illuminations with a 3D Morphable Model V. Blanz, S. Romdhani, and T. Vetter @@ -3252,6 +11320,11 @@ University of California at Berkeley Technical Report No. UCB/EECS-2012-52 http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-52.html May 1, 2012"
+a3d071d2a5c11329aa324b2cae6b7b6ca7800213,C-VQA: A Compositional Split of the Visual Question Answering (VQA) v1.0 Dataset,"C-VQA: A Compositional Split of the +Visual Question Answering (VQA) v1.0 Dataset +Aishwarya Agrawal∗, Aniruddha Kembhavi†, Dhruv Batra‡, Devi Parikh‡ +Virginia Tech, †Allen Institute for Artificial Intelligence, ‡Georgia Institute of Technology +{dbatra,"
a3a97bb5131e7e67316b649bbc2432aaa1a6556e,Role of the hippocampus and orbitofrontal cortex during the disambiguation of social cues in working memory.,"Cogn Affect Behav Neurosci DOI 10.3758/s13415-013-0170-x Role of the hippocampus and orbitofrontal cortex @@ -3279,11 +11352,86 @@ ontent will be available anytime, anywhere. In such DRM systems, encryption algorithms, access control, key management strategies, identification and tracing of contents, or copy control will play a prominent role"
+a3d8887625040d3c07f779ac5353452fd48058e4,A Study of Activity Recognition and Questionable Observer Detection,"International Journal of Computer Applications (0975 – 8887) +Volume 182 – No. 15, September 2018 +A Study of Activity Recognition and Questionable +Observer Detection +D. M. Anisuzzaman +Department of Computer Science and Engineering, +Ahsanullah University of Science and Technology, +Dhaka, Bangladesh"
+b55489547790f7fb2c8b4689530b5660fbc8ee64,Face Scanning in Autism Spectrum Disorder and Attention Deficit/Hyperactivity Disorder: Human Versus Dog Face Scanning,"ORIGINAL RESEARCH +published: 23 October 2015 +doi: 10.3389/fpsyt.2015.00150 +Face scanning in autism spectrum +disorder and attention deficit/ +hyperactivity disorder: human +versus dog face scanning +Mauro Muszkat 1, Claudia Berlim de Mello 2, Patricia de Oliveira Lima Muñoz 3, +Tania Kiehl Lucci 3, Vinicius Frayze David 3, José de Oliveira Siqueira 3 and Emma Otta 3* +Departamento de Psicobiologia, Universidade Federal de São Paulo, São Paulo, Brazil, 2 Programa de Pós Graduação em +Educação e Saúde, Universidade Federal de São Paulo, São Paulo, Brazil, 3 Departamento de Psicologia Experimental, +Instituto de Psicologia, Universidade de São Paulo, São Paulo, Brazil +This study used eye tracking to explore attention allocation to human and dog faces in chil- +dren and adolescents with autism spectrum disorder (ASD), attention deficit/hyperactivity +disorder (ADHD), and typical development (TD). Significant differences were found among +the three groups. TD participants looked longer at the eyes than ASD and ADHD ones, +irrespective of the faces presented. In spite of this difference, groups were similar in that +they looked more to the eyes than to the mouth areas of interest. The ADHD group gazed +longer at the mouth region than the other groups. Furthermore, groups were also similar +in that they looked more to the dog than to the human faces. The eye-tracking tech-"
+b50f2ad8d7f08f99d4ba198120120f599f98095e,Spatiotemporal data fusion for precipitation nowcasting,"Spatiotemporal data fusion for precipitation +nowcasting +Vladimir Ivashkin +Yandex, Moscow, Russia +Vadim Lebedev +Yandex, Moscow, Russia"
+b5f5781cba3c3da807359a6f600aa19c666a3f81,Comparing Attention to Socially-Relevant Stimuli in Autism Spectrum Disorder and Developmental Coordination Disorder,"Journal of Abnormal Child Psychology +https://doi.org/10.1007/s10802-017-0393-3 +Comparing Attention to Socially-Relevant Stimuli in Autism +Spectrum Disorder and Developmental Coordination Disorder +Emma Sumner 1 +& Hayley C. Leonard 2 & Elisabeth L. Hill 3 +# The Author(s) 2018. This article is an open access publication"
+b58672881dd8112cd3e6dedebcf8367ce2c9d78b,Mechanistic Analytical Modeling of Superscalar In-Order Processor Performance,"Mechanistic Analytical Modeling of Superscalar In-Order +Processor Performance +MAXIMILIEN B. BREUGHE, STIJN EYERMAN, and LIEVEN EECKHOUT, +Ghent University, Belgium +Superscalar in-order processors form an interesting alternative to out-of-order processors because of their +energy efficiency and lower design complexity. However, despite the reduced design complexity, it is nontrivial +to get performance estimates or insight in the application–microarchitecture interaction without running +slow, detailed cycle-level simulations, because performance highly depends on the order of instructions within +the application’s dynamic instruction stream, as in-order processors stall on interinstruction dependences +nd functional unit contention. To limit the number of detailed cycle-level simulations needed during design +space exploration, we propose a mechanistic analytical performance model that is built from understanding +the internal mechanisms of the processor. +The mechanistic performance model for superscalar in-order processors is shown to be accurate with an +verage performance prediction error of 3.2% compared to detailed cycle-accurate simulation using gem5. We +lso validate the model against hardware, using the ARM Cortex-A8 processor and show that it is accurate +within 10% on average. We further demonstrate the usefulness of the model through three case studies: +(1) design space exploration, identifying the optimum number of functional units for achieving a given +performance target; (2) program–machine interactions, providing insight into microarchitecture bottlenecks; +nd (3) compiler–architecture interactions, visualizing the impact of compiler optimizations on performance. +Categories and Subject Descriptors: C.0 [Computer Systems Organization]: General—Modeling of com-"
+b569f22ce779d221ec008c0baa354796d71e3d80,Image Classification for Arabic: Assessing the Accuracy of Direct English to Arabic Translations,"Image Classification for Arabic: Assessing the Accuracy of +Direct English to Arabic Translations +Information Systems Department, Prince Sattam Bin Abdulaziz university, Al Kharj, Saudi Arabia +Abdulkareem Alsudais"
b558be7e182809f5404ea0fcf8a1d1d9498dc01a,Bottom-up and top-down reasoning with convolutional latent-variable models,"Bottom-up and top-down reasoning with convolutional latent-variable models Peiyun Hu UC Irvine Deva Ramanan UC Irvine"
+b5fffbc0e590ce67d485f1602c8158befcef9fa8,The use of hidden Markov models to verify the identity based on facial asymmetry,"Kubanek and Bobulski EURASIP Journal on Image and Video +Processing (2017) 2017:45 +DOI 10.1186/s13640-017-0193-2 +EURASIP Journal on Image +nd Video Processing +RESEARCH +Open Access +The use of hidden Markov models to +verify the identity based on facial asymmetry +Mariusz Kubanek and Janusz Bobulski*"
b5cd8151f9354ee38b73be1d1457d28e39d3c2c6,Finding Celebrities in Video,"Finding Celebrities in Video Nazli Ikizler Jai Vasanth @@ -3294,6 +11442,12 @@ University of California at Berkeley Technical Report No. UCB/EECS-2006-77 http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-77.html May 23, 2006"
+b5476afccf97fc498f51170e65ac9cd9665fd2ce,Wide Range Face Pose Estimation by Modelling the 3D Arrangement of Robustly Detectable Sub-parts,"Wide Range Face Pose Estimation +y Modelling the 3D Arrangement +of Robustly Detectable Sub-Parts +Thiemo Wiedemeyer1, Martin Stommel2 and Otthein Herzog3 +TZI Center for Computing and Communication Technologies, +University Bremen, Am Fallturm 1, 28359 Bremen, Germany"
b5fc4f9ad751c3784eaf740880a1db14843a85ba,Significance of image representation for face verification,"SIViP (2007) 1:225–237 DOI 10.1007/s11760-007-0016-5 ORIGINAL PAPER @@ -3302,6 +11456,41 @@ Anil Kumar Sao · B. Yegnanarayana · B. V. K. Vijaya Kumar Received: 29 August 2006 / Revised: 28 March 2007 / Accepted: 28 March 2007 / Published online: 1 May 2007 © Springer-Verlag London Limited 2007"
+b525a863eab597055e02351acfeab64754d22690,Pictorial Structures Revisited : Multiple Human Pose Estimation,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +D Pictorial Structures Revisited: +Multiple Human Pose Estimation +Vasileios Belagiannis, Sikandar Amin, Mykhaylo Andriluka, +Bernt Schiele, Nassir Navab, and Slobodan Ilic"
+b5af4b9d68f1b9b2c2999a726f6d2fbb2a49a3bf,Modulating early visual processing by language,"Modulating early visual processing by language +Harm de Vries∗ +University of Montreal +Florian Strub∗ +Univ. Lille, CNRS, Centrale Lille, +Jérémie Mary† +Univ. Lille, CNRS, Centrale Lille, +Inria, UMR 9189 CRIStAL +Inria, UMR 9189 CRIStAL +Hugo Larochelle +Google Brain +Olivier Pietquin +DeepMind +Aaron Courville +University of Montreal, CIFAR Fellow"
+b5f9c5af707f55d96b1d3d65d970270d35a60987,Comparison of face Recognition Algorithms on Dummy Faces,"The International Journal of Multimedia & Its Applications (IJMA) Vol.4, No.4, August 2012 +Comparison of face Recognition Algorithms on +Dummy Faces +Aruni Singh, Sanjay Kumar Singh, Shrikant Tiwari +Department of Computer Engineering, IT-BHU, Varanasi-India"
+b5ba0c50cfe2559f4197bb35cf50441118b768c8,audEERING's approach to the One-Minute-Gradual Emotion Challenge,"udEERING’s approach to the One-Minute-Gradual Emotion Challenge +Andreas Triantafyllopoulos, Hesam Sagha, Florian Eyben, Bj¨orn Schuller +udEERING GmbH, Gilching, Germany"
+b5cf931cf0bd606575bc793c0c8ec6d913d08bc6,"Geometric primitive feature extraction - concepts, algorithms, and applications","GEOMETRIC PRIMITIVE FEATURE EXTRACTION – +CONCEPTS, ALGORITHMS, AND APPLICATIONS +DILIP KUMAR PRASAD +School of Computer Engineering +A Thesis submitted to the Nanyang Technological University +in fulfillment of the requirement for the degree of +Doctor of Philosophy"
b506aa23949b6d1f0c868ad03aaaeb5e5f7f6b57,Modeling Social and Temporal Context for Video Analysis,"UNIVERSITY OF CALIFORNIA RIVERSIDE Modeling Social and Temporal Context for Video Analysis @@ -3327,17 +11516,74 @@ t the University of Central Florida Orlando, Florida Spring Term Major Professor: Gita R. Sukthankar"
+b55853483873d3947e8c962f1152128059369d93,DoShiCo challenge: Domain shift in control prediction,"DoShiCo challenge: +Domain Shift in Control prediction +Klaas Kelchtermans∗ and Tinne Tuytelaars∗"
+b58e71a3336193bed5785b2818a4fec85dd5f5ff,Object Detection and Tracking for Autonomous Navigation in Dynamic Environments,"Object detection and tracking for autonomous navigation +in dynamic environments +Andreas Ess · Konrad Schindler · Bastian Leibe · Luc Van Gool"
b5160e95192340c848370f5092602cad8a4050cd,Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, TO APPEAR Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor Aaron Chadha, Alhabib Abbas and Yiannis Andreopoulos, Senior Member, IEEE"
+b501361ad3ad4f78a3966830a40d2b4f68466c80,Night-time Vehicle Detection for Automatic Headlight Beam Control,"International Journal of Computer Applications (0975 – 8887) +Volume 157 – No 7, January 2017 +Night-time Vehicle Detection for Automatic Headlight +Beam Control +Pushkar Sevekar +Student, Department of +Electronics Engineering +A.I.S.S.M.S. Institute of +Information Technology, +Pune, India"
+b58417561ea400b60bd976104e43b1361e1314ba,Target Tracking In Real Time Surveillance Cameras and Videos,"Target Tracking In Real Time Surveillance +Cameras and Videos +Nayyab Naseem Mehreen Sirshar +Department of Software Engineering Department of Software Engineering +Fatima Jinnah Women University Fatima Jinnah Women University"
b52886610eda6265a2c1aaf04ce209c047432b6d,Microexpression Identification and Categorization Using a Facial Dynamics Map,"Microexpression Identification and Categorization using a Facial Dynamics Map Feng Xu, Junping Zhang, James Z. Wang"
+b5790f1bc586a77ff2cbea002b7ad2646e32af6b,Person Re-Identification Ranking Optimisation by Discriminant Context Information Analysis,"Person Re-Identification Ranking Optimisation by +Discriminant Context Information Analysis +Jorge Garc´ıa1, Niki Martinel2, Christian Micheloni2 and Alfredo Gardel1 +Department of Electronics, University of Alcala, Alcal´a de Henares, Spain +Department of Mathematics and Computer Science, University of Udine, Udine, Italy"
+b573a57b3da678631bd78f25ecdeac7cd36fa617,A Multi-view RGB-D Approach for Human Pose Estimation in Operating Rooms,"A Multi-view RGB-D Approach for Human Pose Estimation in Operating Rooms +Abdolrahim Kadkhodamohammadi1, Afshin Gangi1,2, Michel de Mathelin1, Nicolas Padoy1 +ICube, University of Strasbourg, CNRS, IHU Strasbourg, France +Radiology Department, University Hospital of Strasbourg, France +{kadkhodamohammad, gangi, demathelin,"
+b5f9d5be7561bb6eacee9012275b17c75696c388,A Teacher Student Network for Faster Video Classification,"Under review as a conference paper at ICLR 2019 +A TEACHER STUDENT NETWORK FOR FASTER VIDEO +CLASSIFICATION +Anonymous authors +Paper under double-blind review"
+b5793958cd1654b4817ebb57f5484dfd8861f916,Recurrent Image Captioner: Describing Images with Spatial-Invariant Transformation and Attention Filtering,"Recurrent Image Captioner: Describing Images with Spatial-Invariant +Transformation and Attention Filtering +Hao Liu +UESTC, China +Yang Yang +UESTC, China +Fumin Shen +UESTC, China +Lixin Duan +UESTC, China +Heng Tao Shen +UESTC, China"
+b5c5a57f5ecd8e11cd47814d584daba53aa14d3c,SOSVR Team Description Paper Robocup 2017 Rescue Virtual Robot League,"SOSVR Team Description Paper +Robocup 2017 Rescue Virtual Robot League +Mahdi Taherahmadi, Sajjad Azami, MohammadHossein GohariNejad, Mostafa +Ahmadi, and Saeed Shiry Ghidary +Cognitive Robotics Lab, Amirkabir University of Technology (Tehran Polytechnic), +No. 424, Hafez Ave., Tehran, Iran. P. O. Box"
b5857b5bd6cb72508a166304f909ddc94afe53e3,SSIG and IRISA at Multimodal Person Discovery,"SSIG and IRISA at Multimodal Person Discovery Cassio E. dos Santos Jr1, Guillaume Gravier2, William Robson Schwartz1 Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil IRISA & Inria Rennes , CNRS, Rennes, France"
+b5050d74dd8f0384506bcd365b31044c80d476c0,Discriminative Multimetric Learning for Kinship Verification,"Discriminative Multimetric Learning +for Kinship Verification +Haibin Yan, Jiwen Lu, Member, IEEE, Weihong Deng, and Xiuzhuang Zhou, Member, IEEE"
b51e3d59d1bcbc023f39cec233f38510819a2cf9,"Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines?","CBMM Memo No. 003 March 27, 2014 Can a biologically-plausible hierarchy effectively @@ -3373,6 +11619,49 @@ ased descriptor. The block-based descriptor represents the micro-orientation and micro-geometric structure information. The pixel-based descriptor represents texture information. We validate our descriptors on two public"
+b5f7b17b0feb3a1f3af60dce61fd9a9c6b067368,The Benefits of Dense Stereo for Pedestrian Detection,"The Benefits of Dense Stereo +for Pedestrian Detection +Christoph G. Keller, Markus Enzweiler, Marcus Rohrbach, David Fernández Llorca, +Christoph Schnörr, and Dariu M. Gavrila"
+b22b4817757778bdca5b792277128a7db8206d08,SCAN: Learning Hierarchical Compositional Visual Concepts,"Published as a conference paper at ICLR 2018 +SCAN: LEARNING HIERARCHICAL +COMPOSITIONAL VISUAL CONCEPTS +Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, +Christopher P Burgess, Matko Bošnjak, Murray Shanahan, +Matthew Botvinick, Demis Hassabis, Alexander Lerchner +DeepMind, London, UK +{irinah,sonnerat,lmatthey,arkap,cpburgess,"
+b26f6e3cad2b3d129c0e70e9307ce9197cad2123,Robust Wearable Camera Localization as a Target Tracking Problem on SE(3),"G.BOURMAUD ET AL.: ROBUST WEARABLE CAMERA LOCALIZATION +Robust Wearable Camera Localization as a +Target Tracking Problem on SE(3) +Guillaume Bourmaud +Audrey Giremus +IMS Laboratory CNRS UMR 5218 +University of Bordeaux +France"
+b266be4d9fab8bf307ee2e6fdd6180ac7f6ef893,Look into Person: Joint Body Parsing&Pose Estimation Network and A New Benchmark,"Look into Person: Joint Body Parsing & Pose +Estimation Network and A New Benchmark +Xiaodan Liang, Ke Gong, Xiaohui Shen, and Liang Lin"
+b2e2260b8d811948e71898d3adfa8aa6b64fe125,Learning Arbitrary Potentials in CRFs with Gradient Descent,"Learning Arbitrary Potentials in CRFs with Gradient Descent +M˚ans Larsson1 +Fredrik Kahl1,2 +Chalmers Univ. of Technology 2Lund Univ. +Shuai Zheng3 Anurag Arnab3 +Oxford Univ. +Philip Torr3 Richard Hartley4 +Australian National Univ."
+b2444e837095706998b03fa5fed223411b9d4d55,Color Based Tracing in Real-Life Surveillance Data,"Color Based Tracing in Real-life Surveillance +Michael J. Metternich, Marcel Worring, and Arnold W.M. Smeulders +ISLA-University of Amsterdam, +Science Park 107, 1098 XG Amsterdam, The Netherlands +http://www.science.uva.nl/research/isla/"
+b2046c78d4e2f00a72ee9a76875746d2d3f47e1c,Variational Infinite Hidden Conditional Random Fields,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI +IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +Variational Infinite +Hidden Conditional Random Fields +Konstantinos Bousmalis, Student Member, IEEE, Stefanos Zafeiriou, Member, IEEE, +Louis-Philippe Morency, Member, IEEE, Maja Pantic, Fellow, IEEE, +nd Zoubin Ghahramani, Member, IEEE"
b216040f110d2549f61e3f5a7261cab128cab361,Weighted Voting of Discriminative Regions for Face Recognition,"IEICE TRANS. INF. & SYST., VOL.E100–D, NO.11 NOVEMBER 2017 LETTER Weighted Voting of Discriminative Regions for Face Recognition∗ @@ -3393,6 +11682,7 @@ extensive experiments show that our method outperforms the baseline and some representative algorithms. key words: discriminative regions, small sample size, occlusion, weighted strategy, face recognition"
+b28e142376a2dd639f58935f2f63a9dc7651131e,Investigation of Gait Representations in Lower Knee Gait Recognition,
b261439b5cde39ec52d932a222450df085eb5a91,Facial Expression Recognition using Analytical Hierarchy Process,"International Journal of Computer Trends and Technology (IJCTT) – volume 24 Number 2 – June 2015 Facial Expression Recognition using Analytical Hierarchy Process @@ -3400,6 +11690,19 @@ MTech Student 1 , Assistant Professor 2 , Department of Computer Science and En Management and Technology, Raipur Chhattisgarh, India1, 2 Vinita Phatnani1, Akash Wanjari2, its significant contribution"
+b29e60ddcabff5002c3ddec135ec94dd991d8d5a,Compressing deep convolutional neural networks in visual emotion recognition,"Compressing deep convolutional neural networks in visual emotion +recognition +A.G. Rassadin1, A.V. Savchenko1 +National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis, 25/12 Bolshaya Pecherskaya +Street, 603155, Nizhny Novgorod, Russia"
+b277bde51641d6b08693c171aea761beb14af800,Face Kernel Extraction from Local Features,"FACE KERNEL EXTRACTION FROM +LOCAL FEATURES +A thesis submitted to the University of Manchester +for the degree of Doctor of Philosophy +in the Faculty of Engineering and Physical Sciences +Maria Pavlou +School of Electrical Engineering and Electronics"
+b2e67e67e5bbb19a02524afcc217929b0a76a9a7,Chapter 12 Using Ocular Data for Unconstrained Biometric Recognition,"Face Recognition in Adverse ConditionsMaria De MarsicoSapienza University of Rome, ItalyMichele NappiUniversity of Salerno, ItalyMassimo TistarelliUniversity of Sassari, ItalyA volume in the Advances in Computational Intelligence and Robotics (ACIR) Book Series"
b2b535118c5c4dfcc96f547274cdc05dde629976,Automatic Recognition of Facial Displays of Unfelt Emotions,"JOURNAL OF IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. XX, NO. X, XXX 2017 Automatic Recognition of Facial Displays of Unfelt Emotions @@ -3412,17 +11715,64 @@ Rongcheng Lin(cid:117) , Huayu Li(cid:117) , Xiaojun Quan† , Richang Hong(cid: (cid:63) Hefei University of Technology. Email: Institute for Infocomm Research. Email: ∓ Nanjing University of Finance and Economics. Email:"
+b20a5427d79c660fe55282da2533071629bfc533,Deep Learning Advances on Different 3D Data Representations: A Survey,"Deep Learning Advances on Different 3D Data +Representations: A Survey +Eman Ahmed, Alexandre Saint, Abd El Rahman Shabayek, Kseniya Cherenkova, Rig Das, Gleb Gusev, +Djamila Aouada and Bj¨orn Ottersten"
+b2504b0b2a7e06eab02a3584dd46d94a3f05ffdf,Conditional Neural Processes,"Conditional Neural Processes +Marta Garnelo 1 Dan Rosenbaum 1 Chris J. Maddison 1 Tiago Ramalho 1 David Saxton 1 Murray Shanahan 1 2 +Yee Whye Teh 1 Danilo J. Rezende 1 S. M. Ali Eslami 1"
+b285e50220fb6c09cf3c724c7e48093373df3c58,Semisupervised Classifier Evaluation and Recalibration,"Semisupervised Classifier Evaluation +nd Recalibration +Peter Welinder∗, Max Welling†, and Pietro Perona‡ +October 7, 2012"
b2c25af8a8e191c000f6a55d5f85cf60794c2709,A novel dimensionality reduction technique based on kernel optimization through graph embedding,"Noname manuscript No. (will be inserted by the editor) A Novel Dimensionality Reduction Technique based on Kernel Optimization Through Graph Embedding N. Vretos, A. Tefas and I. Pitas the date of receipt and acceptance should be inserted later"
+b2f4871cf9f61c44b16c733369d8730e90d9cc0d,The role of emotion in problem solving: first results from observing chess,"The Role of Emotion in Problem Solving: First Results +from Observing Chess +Thomas Guntz1, James L. Crowley1, Dominique Vaufreydaz1, Raffaella Balzarini1, +Philippe Dessus1,2 +Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LIG, 38000 Grenoble, France +Univ. Grenoble Alpes, LaRAC, 38000 Grenoble, France +Author version"
+b2624c3cb508bf053e620a090332abce904099a1,Dynamic Memory Networks for Visual and Textual Question Answering,"Dynamic Memory Networks for Visual and Textual Question Answering +Caiming Xiong*, Stephen Merity*, Richard Socher +MetaMind, Palo Alto, CA USA +{CMXIONG,SMERITY,RICHARD}METAMIND.IO +*indicates equal contribution."
+b2abaffc4d68ebf910dd85c0f7a367895ab90e2a,Iris recognition using scattering transform and textural features,"IRIS RECOGNITION USING SCATTERING TRANSFORM AND TEXTURAL FEATURES +Shervin Minaee, AmirAli Abdolrashidi and Yao Wang +ECE Department, NYU Polytechnic School of Engineering, USA +{shervin.minaee, abdolrashidi,"
d904f945c1506e7b51b19c99c632ef13f340ef4c,0 ° 15 ° 30 ° 45 ° 60 ° 75 ° 90 °,"A scalable 3D HOG model for fast object detection and viewpoint estimation Marco Pedersoli Tinne Tuytelaars KU Leuven, ESAT/PSI - iMinds Kasteelpark Arenberg 10 B-3001 Leuven, Belgium"
+d914c53cdf26acc64259d381fbd45c4e150633ee,Pedestrian Tracking in the Compressed Domain Using Thermal Images,"Pedestrian Tracking in the Compressed Domain +Using Thermal Images +Ichraf Lahouli1,2,3, Robby Haelterman1, Zied Chtourou2, Geert De Cubber1, +nd Rabah Attia3 +Royal Military Academy, +Brussels, Belgium +VRIT Lab, Military Academy of Tunisia, +Nabeul, Tunisia +SERCOM Lab, Tunisia Polytechnic School, +La Marsa, Tunisia"
+d9f0640716ec25278e6f1a4fdda5596660504c54,A Correlated Parts Model for Object Detection in Large 3D Scans,"EUROGRAPHICS 2013 / I. Navazo, P. Poulin +(Guest Editors) +Volume 32 (2013), Number 2 +A Correlated Parts Model for Object Detection in Large 3D +Scans +M. Sunkel1, S. Jansen1, M. Wand1,2, H.-P. Seidel1 +MPI Informatik +Saarland University +Figure 1: Based on sparse user annotations a shape model is learned. The detected instances are transformed into descriptors +for the second hierarchy level. Hierarchical detections shown on the right are obtained using only the example marked red."
d9810786fccee5f5affaef59bc58d2282718af9b,Adaptive Frame Selection for Enhanced Face Recognition in Low-Resolution Videos,"Adaptive Frame Selection for Enhanced Face Recognition in Low-Resolution Videos @@ -3443,6 +11793,8 @@ Keywords: Face Biometrics, Super-Resolution, Optical Flow, Super-Resolution usin Optical Flow, Adaptive Frame Selection, Inter-Frame Motion Parameter, Image Quality, Image-Level Fusion, Score-Level Fusion Copyright 2008 Raghavender Reddy Jillela"
+d929534024614e3153c986e55d758ea7471d3fff,How Not to Evaluate a Developmental System,"How Not to Evaluate a Developmental System +Frederick Shic and Brian Scassellati"
d94d7ff6f46ad5cab5c20e6ac14c1de333711a0c,Face Album: Towards automatic photo management based on person identity on mobile phones,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE ICASSP 2017"
d930ec59b87004fd172721f6684963e00137745f,Face Pose Estimation using a Tree of Boosted Classifiers,"Face Pose Estimation using a @@ -3453,8 +11805,41 @@ Professor: Jean-Philippe Thiran Signal Processing Institute, ´Ecole Polytechnique F´ed´erale de Lausanne (EPFL) September 11, 2006"
+d951ff5f378b2a5f878423029123ad6b3491b444,Foveal Vision for Instance Segmentation of Road Images,"Foveal Vision for Instance Segmentation of Road Images +Benedikt Ortelt1, Christian Herrmann2,3, Dieter Willersinn2, J¨urgen Beyerer2,3 +Robert Bosch GmbH, Leonberg, Germany +Fraunhofer IOSB, Karlsruhe, Germany +Karlsruhe Institute of Technology KIT, Vision and Fusion Lab, Karlsruhe, Germany +Keywords: +Instance Segmentation, Multi-Scale Analysis, Foveated Imaging, Cityscapes."
+d9fe0b257ec50a12ba1af749fad56a6f705d16a4,High Frequency Regions for Face Recognition,"The International Journal of Multimedia & Its Applications (IJMA) Vol.4, No.1, February 2012 +FEATURE IMAGE GENERATION USING LOW, MID +AND HIGH FREQUENCY REGIONS FOR FACE +RECOGNITION +Vikas Maheshkar1, Sushila Kamble2, Suneeta Agarwal3 and Vinay Kumar +Srivastava4 +-3Department of Computer Science and Engineering, MNNIT, Allahabad +Department of Electronics & Communication Engineering, MNNIT, Allahabad"
d9318c7259e394b3060b424eb6feca0f71219179,Face Matching and Retrieval Using Soft Biometrics,"Face Matching and Retrieval Using Soft Biometrics Unsang Park, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+d9ee64038aea3a60120e9f7de16eb4130940a103,Message Passing Multi-Agent GANs,"Message Passing Multi-Agent GANs +Arnab Ghosh∗, Viveka Kulharia∗, Vinay Namboodiri +IIT Kanpur"
+d97e7799142e2c66b63fe63bc52632fdf305f313,Lanczos Vectors versus Singular Vectors for Effective Dimension Reduction,"Lanczos Vectors versus Singular Vectors for +Effective Dimension Reduction +Jie Chen and Yousef Saad"
+d9fda0030ca349da7b1dafca015bea95a6aabea0,ISA2: Intelligent Speed Adaptation from Appearance,"ISA2: Intelligent Speed Adaptation from Appearance +Carlos Herranz-Perdiguero1 and Roberto J. L´opez-Sastre1"
+d950af49c44bc5d9f4a5cc1634e606004790b1e5,Divide and Fuse: A Re-ranking Approach for Person Re-identification,"YU ET AL.: DIVIDE AND FUSE: A RE-RANKING APPROACH FOR PERSON RE-ID +Divide and Fuse: A Re-ranking Approach for +Person Re-identification +Huazhong University of Science and +Technology +Wuhan, China +Rui Yu +Zhichao Zhou +Song Bai +Xiang Bai ∗"
d9ef1a80738bbdd35655c320761f95ee609b8f49,A Research - Face Recognition by Using Near Set Theory,"Volume 5, Issue 4, 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering @@ -3464,7 +11849,59 @@ A Research - Face Recognition by Using Near Set Theory Manisha V. Borkar, Bhakti Kurhade Department of Computer Science and Engineering Abha Gaikwad -Patil College of Engineering, Nagpur, Maharashtra, India"
+d930d20ba42a5d868dd78dd73bac0f72110e0bc5,Multivariate Shape Modeling and Its Application to Characterizing Abnormal Amygdala Shape in Autism,"Multivariate Shape Modeling and Its Application to +Characterizing Abnormal Amygdala Shape in Autism +Moo K. Chunga,b∗,Keith J. Worsleyd, Brendon, M. Nacewiczb, +Kim M. Daltonb, Richard J. Davidsonb,c +Department of Biostatistics and Medical Informatics +Waisman Laboratory for Brain Imaging and Behavior +Department of Psychology and Psychiatry +University of Wisconsin, Madison, WI 53706, USA +dDepartment of Statistics +University of Chicago, Chicago, IL 60637, USA +September 22, 2009"
+d94b37958657aa703d8a3d02a66ee251b4c3f597,Learning deep features from body and parts for person re-identification in camera networks,"Zhang and Si EURASIP Journal on Wireless Communications and +Networking (2018) 2018:52 +https://doi.org/10.1186/s13638-018-1060-2 +RESEARCH +Open Access +Learning deep features from body and +parts for person re-identification in camera +networks +Zhong Zhang1,2* and Tongzhen Si1,2"
+d9df2ed64494f54c0e2529f2c05a16423a57235c,A Novel Approach for Facial Expression Analysis in real time applications using SIFT flow and SVM,"Australian Journal of Basic and Applied Sciences, 9(21) Special 2015, Pages: 1-6 +ISSN:1991-8178 +Australian Journal of Basic and Applied Sciences +Journal home page: www.ajbasweb.com +A Novel Approach for Facial Expression Analysis in real time applications using SIFT +flow and SVM +K. Suganya Devi and 2P. Srinivasan +Department of Computer Science and Engineering, University college of Engg Panruti, Panruti 607106, Tamilnadu, India +Department of Physics, University college of Engg Panruti, Panruti 607106, Tamilnadu, India +A R T I C L E I N F O +Article history: +Article Received : 12 January 2015 +Revised: 1 May 2015 +Accepted: 8 May 2015 +Keywords: +Expression recognition, Facial region +selection, Facial expression, Sparse +learning technique, Scale Invariant +Feature Transform flow, SVM +A B S T R A C T"
d9c4b1ca997583047a8721b7dfd9f0ea2efdc42c,Learning Inference Models for Computer Vision,Learning Inference Models for Computer Vision
+d94c7a89adf6f568bbe1510910850d5083a58b4f,Deep Cross Modal Learning for Caricature Verification and Identification (CaVINet),"Deep Cross Modal Learning for Caricature Verification and +Identification(CaVINet) +https://lsaiml.github.io/CaVINet/ +Jatin Garg∗ +Indian Institute of Technology Ropar +Himanshu Tolani∗ +Indian Institute of Technology Ropar +Skand Vishwanath Peri∗ +Indian Institute of Technology Ropar +Narayanan C Krishnan +Indian Institute of Technology Ropar"
+d9bc16dcbc13502389704e4a0bdd8ee7af618069,Learning pullback HMM distances for action recognition,Learning pullback HMM distances for action recognition
d9bad7c3c874169e3e0b66a031c8199ec0bc2c1f,"It All Matters: Reporting Accuracy, Inference Time and Power Consumption for Face Emotion Recognition on Embedded Systems","It All Matters: Reporting Accuracy, Inference Time and Power Consumption for Face Emotion Recognition on Embedded Systems @@ -3489,16 +11926,52 @@ GU SuiCheng, TAN Ying Key Laboratory of Machine Perception (MOE); Department of Machine Intelligence, School of Electronics Engineering and Computer Science; Peking University, Beijing 100871, China Received March 16, 2009; accepted April 1, 2010"
+d92581c452e780710938cfbfa0f1ca2ffccc5d5e,Facial Feature Extraction Based on Local Color and Texture for Face Recognition using Neural Network,"International Journal of Science and Engineering Applications +Volume 2 Issue 4, 2013, ISSN-2319-7560 (Online) +Facial Feature Extraction Based on Local Color and Texture +for Face Recognition using Neural Network +S.Cynthia Christabel +M.Annalakshmi +Sethu Institute of Technology. +Sethu Institute of Technology. +Kariapatti. +Kariapatti. +Mr.D.Prince Winston +Aruppukottai."
aca232de87c4c61537c730ee59a8f7ebf5ecb14f,Ebgm Vs Subspace Projection for Face Recognition,"EBGM VS SUBSPACE PROJECTION FOR FACE RECOGNITION Andreas Stergiou, Aristodemos Pnevmatikakis, Lazaros Polymenakos 9.5 Km Markopoulou Avenue, P.O. Box 68, Peania, Athens, Greece Athens Information Technology Keywords: Human-Machine Interfaces, Computer Vision, Face Recognition."
+ac7f898ff5789914d423526c392ee61b979fdd8e,"Target Tracking with Kalman Filtering, KNN and LSTMs","Target Tracking with Kalman Filtering, KNN and LSTMs +Dan Iter +Jonathan Kuck +Philip Zhuang +December 17, 2016"
ac6a9f80d850b544a2cbfdde7002ad5e25c05ac6,Privacy-Protected Facial Biometric Verification Using Fuzzy Forest Learning,"Privacy-Protected Facial Biometric Verification Using Fuzzy Forest Learning Richard Jiang, Ahmed Bouridane, Senior Member, IEEE, Danny Crookes, Senior Member, IEEE, M. Emre Celebi, Senior Member, IEEE, and Hua-Liang Wei"
+aca8c4a62ed6e590889f1e859d7bc79311fa6f4d,Beyond Universal Saliency: Personalized Saliency Prediction with Multi-task CNN,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +Semantic labels Observer A Observer B Observer C Figure1:AnillustrationofPSMdataset.Ourdatasetprovidesbotheyefixationsofdifferentsubjectsandsemanticlabels.Duetothelargeamountofobjectsinourdataset,foreachimage,wedidn’tful-lysegmentitandonlylabelledobjectsthatcoveratleastthreegazepointsfromeachindividual.AnotabledifferencebetweenPSManditspredecessorsisthateachsubjectslooks4timesonPSMdatatoderivesolidfixationgroundtruthmaps.Bothcommonalityanddis-tinctivenessexistforPSMsviewedbydifferentparticipant.ThismotivatesustomodelPSMbasedonUSM.recognizingheterogeneityacrossindividuals.ExamplesinFig.1illustratethatwhilemultipleobjectsaredeemedhigh-lysalientwithinthesameimage(eg,humanface(firstrow),text(lasttowrows)andobjectof(highcolorcontrast),differ-entindividualshaveverydifferentfixationpreferenceswhenviewingtheimage.Fortherestofthepaper,weusetermuniversalsaliencytodescribesalientregionsthatincurhighfixationsacrossallsubjectsandtermpersonalizedsaliencytodescribetheheterogeneousones.Motivation.Infact,heterogeneityinsaliencypreferencehasbeenwidelyrecognizedinpsychology:”Interestingnessishighlysubjectiveandthereareindividualswhodidnotconsideranyimageinterestinginsomesequences”[Gyglietal.,2013].Therefore,onceweknowaperson’spersonal-izedinterestingnessovereachimage(personalizedsaliency),weshalldesigntailoredalgorithmstocatertohim/herneed-s.Forexample,intheapplicationofimageretargeting,thetextsonthetableinthefourthrowinFig.1shouldbepre-"
+ac83b9ad20ecf63c7818ff1e43a99b4c626fac12,Accuracy and Security Evaluation of Multi-Factor Biometric Authentication,"Accuracy and Security Evaluation of Multi-Factor Biometric Authentication +Hisham Al-Assam, Harin Sellahewa, Sabah Jassim +Department of Applied Computing +University of Buckingham +Buckingham, MK18 1EG, United Kingdom +{hisham.al-assam, harin.sellahewa,"
+ac57b04359818c17d416ee53ae05a5f126eca4db,Detection and classification of the behavior of people in an intelligent building by camera,"Detection and classification of the behavior of people in an +intelligent building by camera +Henni Sid Ahmed1, Belbachir Mohamed Faouzi2, Jean Caelen3 +Universite of sciences and technology USTO in Oran Algeria, laboratory LSSD, Faculty genie +electrique, department electronique, BP 1505 el menouar Oran 31000 Algeria +Universite of sciences and technology USTO in Oran Algeria, laboratory LSSD, Faculty genie +electrique, department electronique, BP 1505 el menouar Oran 31000 Algeria +Universite Joseph Fourier, Grenoble, F , LIG Grenoble computer laboratory ,domaine +universitaire BP 53, 220 rue de la chimie 38041 Grenoble cedex 9 France +Emails: 1 +Submitted: Apr. 10, 2013 Accepted: July 30, 2013 Published: Sep. 3, 2013"
accbd6cd5dd649137a7c57ad6ef99232759f7544,Facial Expression Recognition with Local Binary Patterns and Linear Programming,"FACIAL EXPRESSION RECOGNITION WITH LOCAL BINARY PATTERNS AND LINEAR PROGRAMMING Xiaoyi Feng1, 2, Matti Pietikäinen1, Abdenour Hadid1 @@ -3519,6 +11992,34 @@ than from image sequences because less information for expression actions vailable. However, information in a single image is sometimes enough for"
+ac88405d34b7b6fa701e25d9fbdb56126cc9a8c3,On the Diversity of Realistic Image Synthesis,"On the Diversity of Realistic Image Synthesis +Zichen Yang, Haifeng Liu, Member, IEEE and Deng Cai, Member, IEEE"
+ac4c19e52a58aea27593b99f0ebe5316339b9646,A Probabilistic Approach for Image Retrieval Using Descriptive Textual Queries,"A Probabilistic Approach for Image Retrieval Using +Descriptive Textual Queries +Yashaswi Verma +CVIT, IIIT Hyderabad, India +C. V. Jawahar +CVIT, IIIT Hyderabad, India"
+ac479607e6b44c69022a56b5847a055535ae63ed,Cross-domain fashion image retrieval,"Cross-domain fashion image retrieval +Bojana Gaji´c, Ramon Baldrich +Computer Vision Center +Universitat Autnoma de Barcelona +Edifici O. UAB. Bellaterra, Spain. +{bgajic,"
+ac968bf321f1dfa2d216dccc22fa5315de63d7bd,Face Template Protection using Deep Convolutional Neural Network,"Face Template Protection using Deep Convolutional Neural Network +Arun Kumar Jindal, Srinivas Chalamala, Santosh Kumar Jami +TCS Research, Tata Consultancy Services, India +{jindal.arun, chalamala.srao,"
+acaa89fb6263aef7ad58a37d9cac79c8fcaa29ca,Person Re-identification in Identity Regression Space,"Noname manuscript No. +(will be inserted by the editor) +Person Re-Identification in Identity Regression Space +Hanxiao Wang · Xiatian Zhu · Shaogang Gong · Tao Xiang +Received: date / Accepted: date"
+acee1e7700e9f084ff64805a2c67d16fe69e63a8,250 years Lambert surface: does it really exist?,"50 years Lambert surface: does it really +exist? +Institut f¨ur Lasertechnologien in der Medizin und Meßtechnik, Helmholtzstr.12, D-89081 Ulm, +Alwin Kienle∗ and Florian Foschum +Germany"
ac26166857e55fd5c64ae7194a169ff4e473eb8b,Personalized Age Progression with Bi-Level Aging Dictionary Learning,"Personalized Age Progression with Bi-level Aging Dictionary Learning Xiangbo Shu, Jinhui Tang, Senior Member, IEEE, Zechao Li, Hanjiang Lai, Liyan Zhang @@ -3532,11 +12033,44 @@ Piek Vossen, Selene Baez, Lenka Baj˘ceti´c, and Bram Kraaijeveld VU University Amsterdam, Computational Lexicology and Terminology Lab, De Boelelaan 1105, 1081HV Amsterdam, The Netherlands www.cltl.nl"
+acc5318592303852feba755a1202fb3c683b3b53,Correction of AI systems by linear discriminants: Probabilistic foundations,"Correction of AI systems by linear discriminants: Probabilistic foundations +A.N. Gorbana,b,∗, A. Golubkovc, B. Grechuka, E.M. Mirkesa,b, I.Y. Tyukina,b +Department of Mathematics, University of Leicester, Leicester, LE1 7RH, UK +Lobachevsky University, Nizhni Novgorod, Russia +Saint-Petersburg State Electrotechnical University, Saint-Petersburg, Russia"
+ac9feef881ed00a5a5e53bddb88f135a9cffe048,A General Method for Appearance-Based People Search Based on Textual Queries,"A general method for appearance-based people +search based on textual queries +Riccardo Satta, Giorgio Fumera, and Fabio Roli +Dept. of Electrical and Electronic Engineering, University of Cagliari +Piazza d’Armi, 09123 Cagliari, Italy"
ac8441e30833a8e2a96a57c5e6fede5df81794af,Hierarchical Representation Learning for Kinship Verification,"IEEE TRANSACTIONS ON IMAGE PROCESSING Hierarchical Representation Learning for Kinship Verification Naman Kohli, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE, Richa Singh, Senior Member, IEEE, Afzel Noore, Senior Member, IEEE, and Angshul Majumdar, Senior Member, IEEE"
+acc37d228f6cb2205497df81532c582ed71dd9fe,Deep Ordinal Ranking for Multi-Category Diagnosis of Alzheimer's Disease using Hippocampal MRI data,"Deep Ordinal Ranking for Multi-Category Diagnosis of Alzheimer’s +Disease using Hippocampal MRI data +Hongming Li, Mohamad Habes, Yong Fan +nd for the Alzheimer's Disease Neuroimaging Initiative* +Section for Biomedical Image Analysis (SBIA), Center for Biomedical Image Computing and +Analytics (CBICA), Department of Radiology, Perelman School of Medicine, University of +Pennsylvania, Philadelphia, PA, 19104, USA +*Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database +(adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or +provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found +t: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf"
+acf13c52c86a3b38642ba0c6cbcd1b771778965c,NAACL HLT 2018 Generalization in the Age of Deep Learning Proceedings of the Workshop,"NAACLHLT2018GeneralizationintheAgeofDeepLearningProceedingsoftheWorkshopJune5,2018NewOrleans,Louisiana"
+ac5c93b789bdd557b90ce77221f1c01ead63041f,Robust People Detection using Computer Vision Spring Term 2013,"Autonomous Systems Lab +Prof. Roland Siegwart +Master-Thesis +Robust People Detection +using Computer Vision +Spring Term 2013 +Supervised by: +Jerome Maye +Paul Beardsley +Author: +Endri Dibra"
ac12ba5bf81de83991210b4cd95b4ad048317681,Combining Deep Facial and Ambient Features for First Impression Estimation,"Combining Deep Facial and Ambient Features for First Impression Estimation Furkan G¨urpınar1, Heysem Kaya2, Albert Ali Salah3 @@ -3546,6 +12080,8 @@ Department of Computer Engineering, Namık Kemal University, C¸ orlu, Tekirda˘g, Turkey Department of Computer Engineering, Bo˘gazi¸ci University, Bebek, Istanbul, Turkey"
+ac0d88ca5f75a4a80da90365c28fa26f1a26d4c4,MOT16: A Benchmark for Multi-Object Tracking,"MOT16: A Benchmark for Multi-Object Tracking +Anton Milan∗, Laura Leal-Taix´e∗, Ian Reid, Stefan Roth, and Konrad Schindler"
acb83d68345fe9a6eb9840c6e1ff0e41fa373229,"Kernel methods in computer vision: object localization, clustering, and taxonomy discovery","Kernel Methods in Computer Vision: Object Localization, Clustering, nd Taxonomy Discovery @@ -3585,9 +12121,72 @@ Basé sur l’exploitation de contraintes qui impliquent des quadruplets d’ima vise à modéliser des relations sémantiques de similarités riches ou complexes. Nous étudions omment ce schéma peut être utilisé dans des contextes tels que la détection de régions impor- tantes dans des pages Web ou la reconnaissance à partir d’attributs relatifs."
+ad3caae50feee550b047e17699cfe7bb9e243cf5,Sparse similarity-preserving hashing,"Sparse similarity-preserving hashing +Jonathan Masci +Alex M. Bronstein +Michael M. Bronstein +Pablo Sprechmann +Guillermo Sapiro"
+ad7a7f70e460d4067d7170bcc0f1ea62eedd7234,CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams,"CBinfer: Exploiting Frame-to-Frame Locality for Faster +Convolutional Network Inference on Video Streams +Lukas Cavigelli, Luca Benini"
+adb2d1e241933ef363bcf03d865a9219d2911780,Classification of Age from Facial Features of Humans,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 +Classification of Age from Facial Features of +Poonam Shirode1, S. M. Handore2 +, 2Department of E&TC, K.J’s Educational Institute’s TCOER, Pune, Maharashtra, India +Humans"
+ade18cf978e4b00fb74352a7eba90b4f4509d645,Articulated Multi-body Tracking under Egomotion,"Articulated Multi-body Tracking Under Egomotion +S. Gammeter1, A. Ess1, T. J¨aggli1, K. Schindler1, B. Leibe1,2, and L. Van Gool1,3 +ETH Z¨urich +RWTH Aachen +KU Leuven, IBBT"
+ad30152944a42975f16a53cf0e0666e9937e9d73,Dyadic Interaction Detection from Pose and Flow,"Dyadic interaction detection from pose and flow +Anonymous ECCV submission +Paper ID 17"
ada73060c0813d957576be471756fa7190d1e72d,VRPBench: A Vehicle Routing Benchmark Tool,"VRPBench: A Vehicle Routing Benchmark Tool October 19, 2016 Guilherme A. Zeni1 , Mauro Menzori1, P. S. Martins1, Luis A. A. Meira1"
+adaff7ff015b4be77e8c0bdb9d002b614d6e2851,A Hybrid Method for Face Recognition using LLS CLAHE Method,"International Journal of Computer Applications (0975 – 8887) +Volume 152 – No.7, October 2016 +A Hybrid Method for Face Recognition using LLS +CLAHE Method +Mohandas College of Engineering and +A. Thamizharasi +Assistant Professor, +Department of Computer +Science & Engineering, +Technology, +Anad, Nedumangad P.O., +Trivandrum, Kerala, India"
+adca02d4b34a9851d1c9c0a7c1bb8d5178b59b85,Modeling the dynamics of individual behaviors for group detection in crowds using low-level features,"Modeling the dynamics of individual behaviors for group +detection in crowds using low-level features +Omar Adair Islas Ram´ırez +Giovanna Varni +Mihai Andries +Mohamed Chetouani +Raja Chatila"
+ad01c5761c89fdf523565cc0dec77b9a6ec8e694,Global and Local Consistent Wavelet-domain Age Synthesis,"Global and Local Consistent Wavelet-domain Age +Synthesis +Peipei Li†, Yibo Hu†, Ran He Member, IEEE and Zhenan Sun Member, IEEE"
+ada4901e0022b4fdeb9ec3ae26b986199f7ae3be,Human Face Recognition based on Improved PCA Algorithm,"Human Face Recognition based on Improved +PCA Algorithm +Xu Yue +College of art and design, LanZhou JiaoTong University, Lanzhou, China +Email: +Linhao Li +AT&T Labs, 200 South Laurel Ave, #D4-3C05, NJ, USA +Email:"
+ad9937ff6c5bff4dae72ca90eddc4dd77751b3fa,FusionNet and AugmentedFlowNet: Selective Proxy Ground Truth for Training on Unlabeled Images,"FusionNet and AugmentedFlowNet: +Selective Proxy Ground Truth +for Training on Unlabeled Images +Osama Makansi*, Eddy Ilg*, and Thomas Brox +University of Freiburg, Germany"
+ad2afeb4c1975c637291bc3f7087d665c3f501c8,WebVision Challenge: Visual Learning and Understanding With Web Data,"WebVision Challenge: Visual Learning and +Understanding With Web Data +Wen Li, Limin Wang, Wei Li, Eirikur Agustsson, Jesse Berent, Abhinav Gupta, Rahul Sukthankar, +nd Luc Van Gool"
adfaf01773c8af859faa5a9f40fb3aa9770a8aa7,Large Scale Visual Recognition,"LARGE SCALE VISUAL RECOGNITION JIA DENG A DISSERTATION @@ -3610,6 +12209,28 @@ William A. P. Smith Submitted for the degree of Doctor of Philosophy Department of Computer Science 0th February 2007"
+adf1b20cffb0ab12d20f878d07373efc4c1bc6c4,Image Retagging Using Collaborative Tag Propagation,"Image Retagging Using Collaborative +Tag Propagation +Dong Liu, Shuicheng Yan, Senior Member, IEEE, Xian-Sheng Hua, Member, IEEE, and +Hong-Jiang Zhang, Fellow, IEEE"
+ad88fcfd12b62d607259db8d98e2a1a0a9642ca0,Real-time tracking-with-detection for coping with viewpoint change,"Real-Time Tracking-with-Detection for Coping With Viewpoint Change +Shaul Oron · Aharon Bar-Hillel · Shai Avidan +Received: 11 May 2014 / Revised: 02 Nov 2014 / Accepted: 09 Mar 2015"
+ad75879082132a73fe173a890a0f414f2c279739,A comparison of CNN-based face and head detectors for real-time video surveillance applications,"A Comparison of CNN-based Face and Head Detectors for +Real-Time Video Surveillance Applications +Le Thanh Nguyen-Meidine1, Eric Granger 1, Madhu Kiran1 and Louis-Antoine Blais-Morin2 +´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montreal, Canada +Genetec Inc., Montreal, Canada"
+adefabe194863b4f764ec982e3120554165c841c,Radius based Block Local Binary Pattern on T-Zone Face Area for Face Recognition,"Journal of Computer Science 11 (1): 96-108, 2015 +ISSN: 1549-3636 +© 2015 Science Publications +RADIUS BASED BLOCK LOCAL BINARY PATTERN ON T- +ZONE FACE AREA FOR FACE RECOGNITION +Md. Jan Nordin, 2Abdul Aziz K. Abdul Hamid, +Sumazly Ulaiman and 2R.U. Gobithaasan +Center for Artificial Intelligent Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia +School of Informatics and App. Maths, Universiti Malaysia Terengganu, Terengganu, Malaysia +Received 2014-02-20; Revised 2014-04-29; Accepted 2014-08-04"
adf62dfa00748381ac21634ae97710bb80fc2922,ViFaI : A trained video face indexing scheme Harsh,"ViFaI: A trained video face indexing scheme Harsh Nayyar Audrey Wei @@ -3630,6 +12251,35 @@ Facebook profile. Such a set of of tagged images of one’s self, family, friends, and colleagues represents n extremely valuable potential training set. In this work, we explore how to leverage the afore-"
+add85ee833e2a1c5cdbcd206d5423d63f20cda24,International Journal of Advanced Robotic Systems Embedded Face Detection and Recognition Regular Paper,"International Journal of Advanced Robotic Systems +Embedded Face Detection +nd Recognition +Regular Paper +Göksel Günlü +Department of Electrical and Electronics Engineering Turgut Özal University, Ankara, Turkey +* Corresponding author E-mail: +Received 07 May 2012; Accepted 28 Jun 2012 +DOI: 10.5772/51132 +© 2012 Günlü; licensee InTech. This is an open access article distributed under the terms of the Creative +Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, +distribution, and reproduction in any medium, provided the original work is properly cited."
+bb2944569a2b3d3b8340b36d4903c8cddf20047f,Improving Regression Performance with Distributional Losses,"Improving Regression Performance with Distributional Losses +Ehsan Imani 1 Martha White 1"
+bb06c12e83255b2c3afca1e3e115e721c53b46b3,Beyond Local Appearance: Category Recognition from Pairwise Interactions of Simple Features,"Beyond Local Appearance: Category Recognition from Pairwise Interactions of +Simple Features +Marius Leordeanu1 +Martial Hebert1 +Rahul Sukthankar2,1 +Carnegie Mellon University 2Intel Research Pittsburgh"
+bb7c5a521607a02e7a291dca7fc33b595c3b7bff,Texture Classification using Local Binary Patterns and Modular PCA,"ISSN: 2278 – 1323 +International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) +Volume 5, Issue 5, May 2016 +Texture Classification using Local Binary +Patterns and Modular PCA +Sayanshree Ghosh, Srimanta Kundu and Sayantari Ghosh +www.ijarcet.org"
+bb35ef89addbbc28d960bc0cab70d8a29fdf6eee,A Survey on Multi-Task Learning,"A Survey on Multi-Task Learning +Yu Zhang and Qiang Yang"
bb489e4de6f9b835d70ab46217f11e32887931a2,Everything You Wanted to Know about Deep Learning for Computer Vision but Were Afraid to Ask,"Everything you wanted to know about Deep Learning for Computer Vision but were fraid to ask Moacir A. Ponti, Leonardo S. F. Ribeiro, Tiago S. Nazare @@ -3641,6 +12291,11 @@ Guildford, GU2 7XH, UK Email: [ponti, leonardo.sampaio.ribeiro, Email: [t.bui, tools,"
+bb97664df153ac563e46ec2233346129cafe601b,A study on the use of Boundary Equilibrium GAN for Approximate Frontalization of Unconstrained Faces to aid in Surveillance,"A study on the use of Boundary Equilibrium GAN for Approximate +Frontalization of Unconstrained Faces to aid in Surveillance +Wazeer Zulfikar, Sebastin Santy, Sahith Dambekodi and Tirtharaj Dash +BITS Pilani - KK Birla Goa Campus, Goa, India +{f20150003, f20150357, f20150192,"
bba281fe9c309afe4e5cc7d61d7cff1413b29558,An unpleasant emotional state reduces working memory capacity: electrophysiological evidence,"Social Cognitive and Affective Neuroscience, 2017, 984–992 doi: 10.1093/scan/nsx030 Advance Access Publication Date: 11 April 2017 @@ -3655,6 +12310,48 @@ Pontifıcia Universidade Catolica do Rio de Janeiro, Rio de Janeiro, Brazil, a Pulmonar, Programa de Engenharia Biome´dica, COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil Correspondence should be addressed to Isabel A. David, Departamento de Fisiologia e Farmacologia, Instituto Biome´dico, Universidade Federal Fluminense, Rua Hernani Pires de Mello, 101, Niteroi, RJ 24210-130, Brazil. E-mail:"
+bb79bb04e569f9319fbc9d8e1f275bbb2cf8d32e,NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning,"NMT-Keras: a Very Flexible Toolkit with a Focus +on Interactive NMT and Online Learning +Álvaro Peris, Francisco Casacuberta +Pattern Recognition and Human Language Technology Research Center, Universitat Politècnica de València, Spain"
+bbc76f0e50ab96e7318816e24c65fd3459d0497c,Survey of Pedestrian Detection for Advanced Driver Assistance Systems,"JULY 2010 +Survey of Pedestrian Detection for +Advanced Driver Assistance Systems +David Gero´ nimo, Antonio M. Lo´ pez, Angel D. Sappa, Member, IEEE, and Thorsten Graf"
+bb131650627cf2d1da570589f6c540041df1ae92,Improving the Intra Class Distance using RBSQI Technique for Facial Images with Illumination Variations,"Volume 2 Special Issue ISSN 2079-8407 +Journal of Emerging Trends in Computing and Information Sciences +©2010-11 CIS Journal. All rights reserved. +http://www.cisjournal.org +Improving the Intra Class Distance using RBSQI Technique for Facial +Images with Illumination Variations +K. R. Singh1, M. A. Zaveri2, M.M. Raghuwanshi3 +,2Computer Engineering Department, S.V.National Institute of Technology, Surat, 329507, India. +NYSS College of Engineering and Research, Nagpur, 441 110, India."
+bb1f4c8e4f310047e50b7dc41d87292025d42eb7,Intersubject Differences in False Nonmatch Rates for a Fingerprint-Based Authentication System,"Hindawi Publishing Corporation +EURASIP Journal on Advances in Signal Processing +Volume 2009, Article ID 896383, 9 pages +doi:10.1155/2009/896383 +Research Article +Intersubject Differences in False Nonmatch Rates for +Fingerprint-Based Authentication System +Jeroen Breebaart, Ton Akkermans, and Emile Kelkboom +Philips Research, HTC 34 MS61, 5656 AE Eindhoven, The Netherlands +Correspondence should be addressed to Jeroen Breebaart, +Received 4 September 2008; Accepted 7 July 2009 +Recommended by Jonathon Phillips +The intersubject dependencies of false nonmatch rates were investigated for a minutiae-based biometric authentication process +using single enrollment and verification measurements. A large number of genuine comparison scores were subjected to statistical +inference tests that indicated that the number of false nonmatches depends on the subject and finger under test. This result was also +observed if subjects associated with failures to enroll were excluded from the test set. The majority of the population (about 90%) +showed a false nonmatch rate that was considerably smaller than the average false nonmatch rate of the complete population. +The remaining 10% could be characterized as “goats” due to their relatively high probability for a false nonmatch. The image +quality reported by the template extraction module only weakly correlated with the genuine comparison scores. When multiple +verification attempts were investigated, only a limited benefit was observed for “goats,” since the conditional probability for a false"
+bba22e04fbe124bf58330e5d911d873a80afa0eb,Probabilistic Global Scale Estimation for MonoSLAM Based on Generic Object Detection,"Probabilistic Global Scale Estimation for MonoSLAM +Based on Generic Object Detection +Centro de Investigaci´on en Matem´aticas - Universidad de Guanajuato +Jalisco S/N, Col. Valenciana CP: 36023 Guanajuato, Gto, Mxico +Edgar Sucar, Jean-Bernard Hayet"
bb22104d2128e323051fb58a6fe1b3d24a9e9a46,Analyzing Facial Expression by Fusing Manifolds,")=OEC .=?E= -NFHAIIE >O .KIEC 9A;= +D=C1,2 +DK5C +DA1,3 ;E2EC 0KC1,2,3 1IJEJKJA B 1BH=JE 5?EA?A 5EE?= 6=EM= @@ -3675,9 +12372,71 @@ ABBA?JELAO = BKIE ?=IIEAH EI MDE?D ?= DAF J AFO IKEJ=>A IELA ?F=HEII B=?E= ANFHAIIE HA?CEJE =HA J JDA ABBA?JELAAII B KH =CHEJD A=EEC DK= AJEI F=OI = EFHJ=J HA E DK= ?KE?=JE 6"
+bbab2c3d0ebc0957c5e962298ffd8c6d4bc25c5a,Have we met before? Neural correlates of emotional learning in women with social phobia.,"Research Paper +Have we met before? Neural correlates of emotional +learning in women with social phobia +Inga Laeger, MA; Kati Keuper, MA; Carina Heitmann, MA; Harald Kugel, PhD; +Christian Dobel, PhD; Annuschka Eden, MA; Volker Arolt, MD; Pienie Zwitserlood, PhD; +Udo Dannlowski, MD, PhD*; Peter Zwanzger, MD* +Laeger, Heitmann, Arolt, Dannlowski, Zwanzger — Department of Psychiatry, University of Muenster, Germany; Keuper, +Dobel, Eden — Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Germany; Kugel — Department of +Clinical Radiology, University of Muenster, Germany; Zwitserlood — Institute for Psychology, University of Muenster, Ger- +many; Dannlowski — Department of Psychiatry, University of Marburg, Germany +Background: Altered memory processes are thought to be a key mechanism in the etiology of anxiety disorders, but little is known about +the neural correlates of fear learning and memory biases in patients with social phobia. The present study therefore examined whether pa- +tients with social phobia exhibit different patterns of neural activation when confronted with recently acquired emotional stimuli. Methods: +Patients with social phobia and a group of healthy controls learned to associate pseudonames with pictures of persons displaying either a +fearful or a neutral expression. The next day, participants read the pseudonames in the magnetic resonance imaging scanner. Afterwards, +memory tests were carried out. Results: We enrolled 21 patients and 21 controls in our study. There were no group differences for +learning performance, and results of the memory tests were mixed. On a neural level, patients showed weaker amygdala activation than +ontrols for the contrast of names previously associated with fearful versus neutral faces. Social phobia severity was negatively related to +mygdala activation. Moreover, a detailed psychophysiological interaction analysis revealed an inverse correlation between disorder +severity and frontolimbic connectivity for the emotional > neutral pseudonames contrast. Limitations: Our sample included only women."
+bbf534b8ee9455b8e492a252bef26f9293d4f91a,Effects of cannabis use and subclinical depression on the P3 event-related potential in an emotion processing task,"Observational Study +Medicine® +Effects of cannabis use and subclinical +depression on the P3 event-related potential +in an emotion processing task +Lucy J. Troup, PhD +, Robert D. Torrence, MS, Jeremy A. Andrzejewski, BSc, Jacob T. Braunwalder, BSc"
bb7f2c5d84797742f1d819ea34d1f4b4f8d7c197,From Images to 3D Shape Attributes.,"TO APPEAR IN TPAMI From Images to 3D Shape Attributes David F. Fouhey, Abhinav Gupta, Andrew Zisserman"
+bb893fac40eb901229567abb507a8cb82553d198,Will the Pedestrian Cross? Probabilistic Path Prediction Based on Learned Motion Features,"Will the Pedestrian Cross? +Probabilistic Path Prediction Based on Learned Motion Features +Christoph G. Keller1, Christoph Hermes2, and Dariu M. Gavrila3,4 +Image & Pattern Analysis Group, Univ. of Heidelberg, Germany +Applied Informatics Group, Univ. of Bielefeld, Germany +Environment Perception, Group Research, Daimler AG, Ulm, Germany +Intelligent Systems Lab, Fac. of Science, Univ. of Amsterdam, The Netherlands"
+bb7c093c41fcec269b6a7a950902cc95429bb289,Robust video object tracking via Bayesian model averaging based feature fusion,"Robust video object tracking via Bayesian model +veraging based feature fusion +Yi Dai, Bin Liu, Member, IEEE"
+bbf5575f0d20b79b61c8c0d8b7c2a57224c359de,Emotion Recognition from Decision Level Fusion of Visual and Acoustic Features using Hausdorff Classifier,"Emotion Recognition from Decision Level Fusion +of Visual and Acoustic Features using Hausdorff +Classifier +H.D.Vankayallapati1, K.R.Anne2, and K. Kyamakya1 +Institute of Smart System Technologies, Transportation Informatics Group +University of Klagenfurt, Klagenfurt, Austria. +Department of Information Technology, TIFAC-CORE in Telematics +VR Siddhartha Engineering College, Vijayawada, India."
+bb667cbbf050040fa39cd9e756cd5bf485fccf32,Effective Deterministic Initialization for $k$-Means-Like Methods via Local Density Peaks Searching,"Effective Deterministic Initialization for +k-Means-Like Methods via Local Density Peaks +Searching +Fengfu Li, Hong Qiao, and Bo Zhang"
+bb021f58f8822d12f5747d583a46005ade4a0b10,Breaking Microsoft’s CAPTCHA,"Breaking Microsoft’s CAPTCHA +Colin Hong Bokil Lopez-Pineda Karthik Rajendran Adri`a Recasens +May 2015"
+bb6ac4e26499dea5bdedb05b269f40f56247b4c6,An Action Unit based Hierarchical Random Forest Model to Facial Expression Recognition,
+bbc4bbf7aa80a8108d62644fea24e6f70a805df9,Inducing Wavelets into Random Fields via Generative Boosting,"Inducing Wavelets into Random Fields via Generative +Boosting +Jianwen Xie, Yang Lu, Song-Chun Zhu, and Ying Nian Wu∗ +Department of Statistics, University of California, Los Angeles, USA"
+bb980dd94463b03c6584513bcccf780e43f089b2,Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities,"Prediction Error Meta Classification in Semantic +Segmentation: Detection via Aggregated Dispersion +Measures of Softmax Probabilities +Matthias Rottmann∗, Pascal Colling∗, Thomas Paul Hack†, +Fabian H¨uger‡, Peter Schlicht‡ and Hanno Gottschalk∗"
bb451dc2420e1a090c4796c19716f93a9ef867c9,A Review on: Automatic Movie Character Annotation by Robust Face-Name Graph Matching,"International Journal of Computer Applications (0975 – 8887) Volume 104 – No.5, October 2014 A Review on: Automatic Movie Character Annotation @@ -3699,12 +12458,116 @@ Pandharpur, Solapur, INDIA Bhise Avdhut S. HOD, Department of"
bbd1eb87c0686fddb838421050007e934b2d74ab,Look at Boundary: A Boundary-Aware Face Alignment Algorithm,"(68 points) COFW (29 points) AFLW (19 points) Figure1:Thefirstcolumnshowsthefaceimagesfromdifferentdatasetswithdifferentnumberoflandmarks.Thesecondcolumnillustratestheuniversallydefinedfacialboundariesestimatedbyourmethods.Withthehelpofboundaryinformation,ourapproachachieveshighaccuracylocalisationresultsacrossmultipledatasetsandannotationprotocols,asshowninthethirdcolumn.Differenttofacedetection[45]andrecognition[75],facealignmentidentifiesgeometrystructureofhumanfacewhichcanbeviewedasmodelinghighlystructuredout-put.Eachfaciallandmarkisstronglyassociatedwithawell-definedfacialboundary,e.g.,eyelidandnosebridge.However,comparedtoboundaries,faciallandmarksarenotsowell-defined.Faciallandmarksotherthancornerscanhardlyremainthesamesemanticallocationswithlargeposevariationandocclusion.Besides,differentannotationschemesofexistingdatasetsleadtoadifferentnumberoflandmarks[28,5,66,30](19/29/68/194points)andanno-tationschemeoffuturefacealignmentdatasetscanhardlybedetermined.Webelievethereasoningofauniquefacial"
+d745cf8c51032996b5fee6b19e1b5321c14797eb,Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features,"Viewpoint Invariant Pedestrian Recognition +with an Ensemble of Localized Features +Douglas Gray and Hai Tao +University of California, Santa Cruz +{dgray, +http://vision.soe.ucsc.edu/"
+d79121a03584123fad02c4f2607f0e63d08ff7c2,Tracking Occluded Objects and Recovering Incomplete Trajectories by Reasoning About Containment Relations and Human Actions,"Tracking Occluded Objects and Recovering Incomplete Trajectories +y Reasoning about Containment Relations and Human Actions +Wei Liang1,2 +Yixin Zhu2 +Song-Chun Zhu2 +Beijing Laboratory of Intelligent Information Technology, Beijing Institute of Technology, China +Center for Vision, Cognition, Learning, and Autonomy, University of California, Los Angeles, USA"
+d7ed878c08c90186e3bf607c20ff943834ad0d68,Semantic Data Integration,"Semantic Data Integration +Michelle Cheatham and Catia Pesquita"
+d78dde04ac4215ed0ed6f2bd5d85094b389d7f5e,A Warping Window Approach to Real-time Vision-based Pedestrian Detection in a Truck's Blind Spot Zone,"A warping window approach to real-time vision-based pedestrian +detection in a truck’s blind spot zone +Kristof Van Beeck1, Toon Goedem´e1;2 and Tinne Tuytelaars2 +IIW/EAVISE, Lessius Mechelen - Campus De Nayer, J. De Nayerlaan 5, 2860, Sint-Katelijne-Waver, Belgium +ESAT/PSI-VISICS, KU Leuven, IBBT, Kasteelpark Arenberg 10, 3100, Heverlee, Belgium +fkristof.vanbeeck, +Keywords: +Computer vision: Pedestrian tracking: Real-time: Active safety systems"
+d74c6e6fbd8952cbad96013e227374c903797162,With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning,"With Great Training Comes Great Vulnerability: +Practical Attacks against Transfer Learning +Bolun Wang +Yuanshun Yao +Bimal Viswanath +Haitao Zheng +UC Santa Barbara +University of Chicago +Virginia Tech +University of Chicago +Ben Y. Zhao +University of Chicago"
+d7c6e4348542fd2b5e64a73d9c1fd0172e2b1774,Grounding language acquisition by training semantic parsers using captioned videos,"Grounding language acquisition by training semantic parsers +using captioned videos +Candace Ross +CSAIL, MIT +Andrei Barbu +CSAIL, MIT +Yevgeni Berzak +BCS, MIT +Battushig Myanganbayar +CSAIL, MIT"
+d7f7eb0fbe3339d13f5a6a23df0fd27fdb357d48,Intention-Aware Multi-Human Tracking for Human-Robot Interaction via Particle Filtering over Sets,"Intention-Aware Multi-Human Tracking for +Human-Robot Interaction via Particle Filtering over Sets +Aijun Bai +Univ. of Sci. & Tech. of China +Reid Simmons +Carnegie Mellon Univ. +Manuela Veloso +Carnegie Mellon Univ. +The Approach +The ability for an autonomous robot to track and identify +multiple humans and understand their intentions is crucial +for socialized human-robot interactions in dynamic envi- +ronments (Michalowski and Simmons 2006). Take CoBot +(Rosenthal, Biswas, and Veloso 2010) trying to enter an ele- +vator as an example. When the elevator door opens, suppose +there are multiple humans occupied, CoBot needs to track +each human’s state and intention in terms of whether he/she +is going to exit the elevator or not. For the purposes of safely +nd friendly interacting with humans, CoBot can only make +the decision to enter the elevator when any human who in-"
+d7731565ec4cb1b910290ccb580405cb55224286,Robust Face Recognition via Adaptive Sparse Representation,"Robust Face Recognition via Adaptive Sparse +Representation +Jing Wang, Canyi Lu, Meng Wang, Member, IEEE, Peipei Li, +Shuicheng Yan, Senior Member, IEEE, Xuegang Hu"
+d7eae9f76dcfa978b99eef430feb9420eac702eb,A Multi-Layer K-means Approach for Multi-Sensor Data Pattern Recognition in Multi-Target Localization,"A Multi-Layer K-means Approach for Multi-Sensor Data Pattern +Recognition in Multi-Target Localization +Samuel Silva, Rengan Suresh, Feng Tao, Johnathan Votion, Yongcan Cao"
d7fe2a52d0ad915b78330340a8111e0b5a66513a,Photo-to-Caricature Translation on Faces in the Wild,"Unpaired Photo-to-Caricature Translation on Faces in the Wild Ziqiang Zhenga, Chao Wanga, Zhibin Yua, Nan Wanga, Haiyong Zhenga,∗, Bing Zhenga No. 238 Songling Road, Department of Electronic Engineering, Ocean University of China, Qingdao, China"
+d7f19812ee77e508b314d0ac6ab49d05ac81e0d1,Active Visual-Based Detection and Tracking of Moving Objects from Clustering and Classification Methods,"Active Visual-based Detection and Tracking of Moving +Objects from Clustering and Classification methods +David Márquez-Gámez Michel Devy +CNRS; LAAS; Université de Toulouse +7 avenue du Colonel Roche, F-31077 Toulouse Cedex, France"
+d7c659ce0442bf1047e7d2e942837b18105f6f47,Depth-Adaptive Deep Neural Network for Semantic Segmentation,"Depth Adaptive Deep Neural Network +for Semantic Segmentation +Byeongkeun Kang, Yeejin Lee, and Truong Q. Nguyen, Fellow, IEEE"
+d76f68c2d0a45ab224065d57836bf3da360c82f2,Learning to Segment Human by Watching YouTube,"Learning to Segment Human by Watching +YouTube +Xiaodan Liang, Yunchao Wei, Liang Lin, Yunpeng Chen, Xiaohui Shen, Jianchao Yang, +Shuicheng Yan"
+d7a0f9ab321e728b981e12775b4906f55d3aab15,3D Object Reconstruction using Computer Vision: Reconstruction and Characterization Applications for External Human Anatomical Structures,"D Object Reconstruction using +Computer Vision: Reconstruction +nd Characterization Applications for +External Human Anatomical Structures +Teresa Cristina de Sousa Azevedo +BSc in Electrical and Computer Engineering by +Faculdade de Engenharia da Universidade do Porto (2002) +MSc in Biomedical Engineering by +Faculdade de Engenharia da Universidade do Porto (2007) +Thesis submitted for the fulfilment of the requirements for the +PhD degree in Informatics Engineering by +Faculdade de Engenharia da Universidade do Porto +Supervisor: +João Manuel R. S. Tavares +Associate Professor of the Department of Mechanical Engineering +Faculdade de Engenharia da Universidade do Porto +Co-supervisor: +Mário A. P. Vaz +Associate Professor of the Department of Mechanical Engineering +Faculdade de Engenharia da Universidade do Porto"
d708ce7103a992634b1b4e87612815f03ba3ab24,FCVID: Fudan-Columbia Video Dataset,"FCVID: Fudan-Columbia Video Dataset Yu-Gang Jiang, Zuxuan Wu, Jun Wang, Xiangyang Xue, Shih-Fu Chang Available at: http://bigvid.fudan.edu.cn/FCVID/ @@ -3725,6 +12588,21 @@ important problem. COLLECTION AND ANNOTATION The categories in FCVID cover a wide range of topics like social events (e.g., “tailgate party”), procedural"
+d7da0f595d135474cc2193d382b22458b313cdbf,Multi-View Constraint Propagation with Consensus Prior Knowledge,Multi-View Constraint Propagation with Consensus Prior Knowledge
+d78b190f98f9630cab261eabc399733af052f05c,Unsupervised Deep Domain Adaptation for Pedestrian Detection,
+d73221adda13a99e8dd8dab101abcfeae6b7b706,The ApolloScape Dataset for Autonomous Driving,"The ApolloScape Dataset for Autonomous Driving +Xinyu Huang, Xinjing Cheng, Qichuan Geng, Binbin Cao, +Dingfu Zhou, Peng Wang, Yuanqing Lin, and Ruigang Yang +Baidu Research, Beijing, China +National Engineering Laboratory of Deep Learning Technology and Application, China"
+d7612e01c10f351a3e2ff1a57465c3d17ddbb193,Rain Streaks Removal in an Image by using Image Decomposition,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2013): 6.14 | Impact Factor (2015): 6.391 +Rain Streaks Removal in an Image by using Image +Decomposition +Priyanka A. Chougule1, J. A. Shaikh2 +Research Student, Electronics Dept., PVPIT, Budhgaon +Associate Professor, Electronics Dept. PVPIT, Budhgaon"
d7b6bbb94ac20f5e75893f140ef7e207db7cd483,griffith . edu . au Face Recognition across Pose : A Review,"Griffith Research Online https://research-repository.griffith.edu.au Face Recognition across Pose: A @@ -3741,10 +12619,46 @@ with the copyright policy of the publisher. Please refer to the journal's websit definitive, published version. Downloaded from http://hdl.handle.net/10072/30193"
+d7144bc7d91841963b037f210f9356d28f76e70e,A comparison of features for regression-based driver head pose estimation under varying illumination conditions,"A COMPARISON OF FEATURES FOR REGRESSION-BASED DRIVER HEAD POSE +ESTIMATION UNDER VARYING ILLUMINATION CONDITIONS +Dimitri J. Walger1, Toby P. Breckon2, Anna Gaszczak3, Thomas Popham3 +Cranfield University, Bedfordshire, UK 2Durham University, Durham, UK +Jaguar Land Rover, Warwickshire, UK"
+d7d6200e41d574e2f3ddd9ded299613683519c7c,Accurate Iris Recognition at a Distance Using Stabilized Iris Encoding and Zernike Moments Phase Features,"IEEE Trans. Image Processing, 2014 +Accurate Iris Recognition at a Distance Using +Stabilized Iris Encoding and Zernike Moments Phase Features +Chun-Wei Tan, Ajay Kumar"
+d75d074c11a62780b836376249391da39660cad6,Task Scheduling Frameworks for Heterogeneous Computing Toward Exascale,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 9, No. 10, 2018 +Task Scheduling Frameworks for Heterogeneous +Computing Toward Exascale +Suhelah Sandokji1, Fathy Eassa2 +Faculty of Computing and Information Technology, KAU +Jeddah ,Saudi Arabia +studies consider partitioning"
+d7e8672caecc7e4b17e8d9d3cbd673d402c7e7af,Robust Stereo-Based Person Detection and Tracking for a Person Following Robot,"Robust Stereo-Based Person Detection and Tracking +for a Person Following Robot +Junji Satake and Jun Miura +Department of Information and Computer Sciences +Toyohashi University of Technology"
+d7d9fa9a5a57f9f3da7ab2c87ca58127665774cc,Improving Shadow Suppression for Illumination Robust Face Recognition,"Improving Shadow Suppression for Illumination +Robust Face Recognition +Wuming Zhang, Xi Zhao, Jean-Marie Morvan and Liming Chen, Senior Member, IEEE"
d7d166aee5369b79ea2d71a6edd73b7599597aaa,Fast Subspace Clustering Based on the Kronecker Product,"Fast Subspace Clustering Based on the Kronecker Product Lei Zhou1, Xiao Bai1, Xianglong Liu1, Jun Zhou2, and Hancock Edwin3 Beihang University 2Griffith University 3University of York, UK"
+d7e8c6da1a95f41d8097b7b713890ccde13ef1d8,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
d79f9ada35e4410cd255db39d7cc557017f8111a,Evaluation of accurate eye corner detection methods for gaze estimation,"Journal of Eye Movement Research 7(3):3, 1-8 Evaluation of accurate eye corner detection methods for gaze @@ -3765,6 +12679,17 @@ pproaches are suggested. All these methods are exhaustively tested on a realisti dataset containing images of subjects gazing at different points on a screen. We have demonstrated that a method based on a neural network presents the est performance even in light changing scenarios."
+d7f3836f2d28adf15fc809bd4f90afb1f61ba8e0,Segment-before-Detect: Vehicle Detection and Classification through Semantic Segmentation of Aerial Images,"Article +Segment-before-Detect: Vehicle Detection and +Classification through Semantic Segmentation of +Aerial Images +Nicolas Audebert 1,2,*, Bertrand Le Saux 1 and Sébastien Lefèvre 2 +ONERA, The French Aerospace Lab, F-91761 Palaiseau, France; +Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), University Bretagne Sud, UMR 6074, +F-56000 Vannes, France; +* Correspondence: +Academic Editors: Norman Kerle, Markus Gerke and Prasad S. Thenkabail +Received: 28 December 2016; Accepted: 7 April 2017; Published: 13 April 2017"
d03265ea9200a993af857b473c6bf12a095ca178,Multiple deep convolutional neural networks averaging for face alignment,"Multiple deep convolutional neural networks averaging for face lignment @@ -3772,6 +12697,82 @@ Shaohua Zhang Hua Yang Zhouping Yin Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/28/2015 Terms of Use: http://spiedl.org/terms"
+d0462aa7754ffdf39962e2003344937258a0e42e,You Can’t Gamble on Others: Dissociable Systems for Strategic Uncertainty and Risk in the Brain,"You Can’t Gamble on Others: Dissociable Systems for +Strategic Uncertainty and Risk in the Brain +W. Gavin Ekins1, Ricardo Caceda, C. Monica Capra1, and Gregory S. Berns1* +1Center for Neuropolicy and Economics Department, Emory University, Atlanta, GA 30322 USA +*Correspondance:"
+d096bdd5743cbb33f0cd0ae984d188b2c302f054,Extractive and Abstractive Caption Generation Model for News Images,"ISSN:2321-1156 +International Journal of Innovative Research in Technology & Science(IJIRTS)"
+d00f6ec074bbe777ba2e419b39729283a28101c5,Hashtag Recommendation for Multimodal Microblog Using Co-Attention Network,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+d0d186779ae4a4e53101a26dc741254e822e07ab,Multi Camera for Surveillance System Ground Detection and 3D Reconstruction,"Multi Camera for Surveillance System Ground Detection and +International Journal of Smart Home +Vol. 9, No. 1 (2015), pp. 103-110 +http://dx.doi.org/10.14257/ijsh.2015.9.1.11 +D Reconstruction +Xu Yongzhe1 and Byungsoo Lee1 +Department of Computer Engineering, University of Incheon, Korea"
+d0ad7324fab174609f26c617869fa328960617e2,Person Identification From Text Independent Lip Movement Using the Longest Matching Segment Method,"Person Identification From Text Independent Lip Movement +Using the Longest Matching Segment Method +Paul C. Brown, Ji Ming, Daryl Stewart +Institute of ECIT, Electronics and Computer Engineering Cluster, Queen(cid:48)s University Belfast, +Belfast BT7 1NN, UK"
+d0a6a700779ac8cb70d7bb95f9a5afdda60152d9,Pyramid Mean Representation of Image Sequences for Fast Face Retrieval in Unconstrained Video Data,"Pyramid Mean Representation of Image Sequences for +Fast Face Retrieval in Unconstrained Video Data +Christian Herrmann1,2 and J¨urgen Beyerer1,2 +Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Karlsruhe, Germany +Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, +Karlsruhe, Germany"
+d04631e40b237ae29cb8d2bd187b04033580e63b,Multi-cue Based Multi-target Tracking with Boosted MHT,"Multi-cue Based Multi-target Tracking +with Boosted MHT +Long Ying1,2, Tianzhu Zhang1,2, Shengsheng Qian1,2, and Changsheng Xu1,2 +Institute of Automation, Chinese Academy of Science, Beijing, China +China-Singapore Institute of Digital Media, Singapore"
+d07e9b04c1480d65e37e44bec3be95fc3206c17b,Combining classifiers for face recognition,- 130-7803-7965-9/03/$17.00 ©2003 IEEEICME 2003(cid:224)
+d0f709ab39e280467d854064132570c1d5316de5,Multi-Object Tracking and Identification over Sets,"Multi-Object Tracking and Identification over Sets +Aijun Bai +UC Berkeley"
+d04d53038d4267cf25badc5d6acccd2fc910a8a7,Online Multi-Object Tracking with Structural Invariance Constraint,"ZHOU, JIANG, WEI, DONG, WANG: ONLINE MULTI-OBJECT TRACKING WITH SIC +Online Multi-Object Tracking +with Structural Invariance Constraint +Xiao Zhou +Peilin Jiang +Zhao Wei +Hang Dong +Fei Wang +National Engineering +Laboratory for Visual Information +Processing and Application, +XJTU, 99 Yanxiang Road, +Xi’an, Shaanxi 710054, China +School of Software Engineering, +XJTU, 28 West Xianning Road, +Xi’an, Shaanxi 710049, China"
+d0de92865a53576af3dd118f4d1fa73be12aee9b,PCANet-II: When PCANet Meets the Second Order Pooling,"PCANet-II:WhenPCANetMeetstheSecondOrderPoolingLeiTian,XiaopengHong"
+d014011b24c62d5b689c782c09b89c52970f46e7,"SRDA: Generating Instance Segmentation Annotation via Scanning, Reasoning and Domain Adaptation","SRDA: Generating Instance Segmentation +Annotation Via Scanning, Reasoning And +Domain Adaptation +Wenqiang Xu(cid:63), Yonglu Li(cid:63), Cewu Lu +Department of Computer Science and Engineering, +Shanghai Jiaotong University +{vinjohn,yonglu"
+d05825a394f11a391c8815f6b0d394cdb4cfaa95,I2T2I: Learning text to image synthesis with textual data augmentation,
+d0e1ad4f3f608124cd3efc2d5bd01b421ffc3274,Running head: SUPPRESSING BEHAVIOUR DOES NOT INFLUENCE WORKING MEMORY CAPACITY DEPARTMENT OF PSYCHOLOGY Suppressing behaviour related to discomfort induced with a cold pressure task does not influence working memory capacity in a 2-back task,"Running +head: +SUPPRESSING +BEHAVIOUR +INFLUENCE +WORKING +MEMORY +CAPACITY +DEPARTMENT OF PSYCHOLOGY +Suppressing behaviour related to discomfort +induced with a cold pressure task does not +influence working memory capacity in a 2-back +task. +Erik Danielski +Master thesis spring 2013 +Supervisors: Martin Wolgast & Emelie Stiernströmer"
d00c335fbb542bc628642c1db36791eae24e02b7,Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor,"Article Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor @@ -3782,8 +12783,51 @@ Seoul 100-715, Korea; (R.A.N.); (M.A.); (G.B.); (H.S.Y.) * Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 Received: 5 January 2018; Accepted: 1 February 2018; Published: 3 February 2018"
+d03f1257066ce5dd843c6977858a1daef0671f3d,Stories for Images-in-Sequence by using Visual and Narrative Components,"Stories for Images-in-Sequence by using Visual +nd Narrative Components (cid:63) +Marko Smilevski1,2, Ilija Lalkovski2, and Gjorgji Madjarov1,3 +Ss. Cyril and Methodius University, Skopje, Macedonia +Pendulibrium, Skopje, Macedonia +Elevate Global, Skopje, Macedonia"
+d0631ba22add59684fff926d80d2e6948dfb7d7e,MUTT: Metric Unit TesTing for Language Generation Tasks,"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pages 1935–1943, +Berlin, Germany, August 7-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
+d01e65591745fc46a3f69a6c9387be17caf55c16,State-Driven Particle Filter for Multi-person Tracking,"State-Driven Particle Filter +for Multi-Person Tracking +David Gerónimo1, Frédéric Lerasle2,3, and Antonio M. López1 +Computer Vision Center and Department of Computer Science +Edifici O, 08193 Campus Universitat Autònoma de Barcelona, Bellaterra, Spain. +CNRS-LAAS, 7 avenue du Colonel Roche, F-31077 Toulouse, France +Université de Toulouse (UPS), F-31077 Toulouse, France"
+d0a9bbd3bd9dcb62f9874fc1378a7f1a17f44563,Prototype Generation Using Self-Organizing Maps for Informativeness-Based Classifier,"Hindawi +Computational Intelligence and Neuroscience +Volume 2017, Article ID 4263064, 15 pages +https://doi.org/10.1155/2017/4263064 +Research Article +Prototype Generation Using Self-Organizing Maps for +Informativeness-Based Classifier +Leandro Juvêncio Moreira1 and Leandro A. Silva2 +Graduate Program in Electrical Engineering and Computing, Mackenzie Presbyterian University, Sao Paulo, SP, Brazil +Computing and Informatics Faculty & Graduate Program in Electrical Engineering and Computing, +Mackenzie Presbyterian University, Sao Paulo, SP, Brazil +Correspondence should be addressed to Leandro A. Silva; +Received 31 January 2017; Revised 13 June 2017; Accepted 15 June 2017; Published 25 July 2017 +Academic Editor: Toshihisa Tanaka +Copyright © 2017 Leandro Juvˆencio Moreira and Leandro A. Silva. This is an open access article distributed under the Creative +Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the +original work is properly cited. +The 𝑘 nearest neighbor is one of the most important and simple procedures for data classification task. The 𝑘NN, as it is called, +requires only two parameters: the number of𝑘 and a similarity measure. However, the algorithm has some weaknesses that make it +nalysis and all training dataset is necessary. Another weakness is the optimal choice of 𝑘 parameter when the object analyzed"
d0144d76b8b926d22411d388e7a26506519372eb,Improving Regression Performance with Distributional Losses,"Improving Regression Performance with Distributional Losses Ehsan Imani 1 Martha White 1"
+d0e20aa3d61b77d17f005a1d24d7cf47600836ef,Rethinking Atrous Convolution for Semantic Image Segmentation,"Rethinking Atrous Convolution for Semantic Image Segmentation +Liang-Chieh Chen George Papandreou Florian Schroff Hartwig Adam +{lcchen, gpapan, fschroff, +Google Inc."
+d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae,A 3-D Audio-Visual Corpus of Affective Communication,"A 3-D Audio-Visual Corpus +of Affective Communication +Gabriele Fanelli, Juergen Gall, Harald Romsdorfer, Member, IEEE, Thibaut Weise, and +Luc Van Gool, Member, IEEE"
d0a21f94de312a0ff31657fd103d6b29db823caa,Facial Expression Analysis,"Facial Expression Analysis Fernando De la Torre and Jeffrey F. Cohn"
d03e4e938bcbc25aa0feb83d8a0830f9cd3eb3ea,Face Recognition with Patterns of Oriented Edge Magnitudes,"Face Recognition with Patterns of Oriented @@ -3822,11 +12866,46 @@ Amity School of Engineering Technology, 580, Bijwasan, New Delhi-110061, India Email: illumination normalization. The lighting conditions. Most of the"
+bee609ea6e71aba9b449731242efdb136d556222,Multi-Target Tracking in Multiple Non-Overlapping Cameras using Constrained Dominant Sets,"Multi-Target Tracking in Multiple +Non-Overlapping Cameras using Constrained +Dominant Sets +Yonatan Tariku Tesfaye*, Student Member, IEEE, Eyasu Zemene*, Student Member, IEEE, +Andrea Prati, Senior member, IEEE, Marcello Pelillo, Fellow, IEEE, and Mubarak Shah, Fellow, IEEE"
be48b5dcd10ab834cd68d5b2a24187180e2b408f,Constrained Low-Rank Learning Using Least Squares-Based Regularization,"FOR PERSONAL USE ONLY Constrained Low-rank Learning Using Least Squares Based Regularization Ping Li, Member, IEEE, Jun Yu, Member, IEEE, Meng Wang, Member, IEEE, Luming Zhang, Member, IEEE, Deng Cai, Member, IEEE, and Xuelong Li, Fellow, IEEE,"
+be9dde86ebd10ecb05808e034e3cadd210fe0bfb,SLAMIT: A Sub-map based SLAM system On-line creation of multi-leveled map,"Master of Science Thesis in Electrical Engineering +Department of Electrical Engineering, Linköping University, 2016 +SLAMIT: A Sub-map based +SLAM system +On-line creation of multi-leveled map +Karl Holmquist"
+be48780eb72d9624a16dd211d6309227c79efd43,Interactive Visual and Semantic Image Retrieval,"Interactive Visual and Semantic Image Retrieval +Joost van de Weijer, Fahad Khan and Marc Masana Castrillo +Introduction +One direct consequence of recent advances in digital visual data generation and +the direct availability of this information through the World-Wide Web, is a urgent +demand for efficient image retrieval systems. The disclosure of the content of these +millions of photos available on the internet is of great importance. The objective +of image retrieval is to allow users to efficiently browse through this abundance +of images. Due to the non-expert nature of the majority of the internet users, such +systems should be user friendly, and therefore avoid complex user interfaces. +Traditionally, two sources of information are exploited in the description of im- +ges on the web. The first approach, called text-based image retrieval, describes +images by a set of labels or keywords [1]. These labels can be automatically ex- +tracted from for example the image name (e.g. ’car.jpg’ would provide information +bout the presence of a car in the image), or alternatively from the webpage text +surrounding the image. Another, more expensive way would be to manually label +images with a set of keywords. Shortcomings of the text-based approach to image +retrieval are obvious: many objects in the scene will not be labeled, words suffer +from the confusions in case of synonyms or homonyms, and words often fall short +in describing the esthetics, composition and color scheme of a scene. However, un-"
+bea2c35ef78eb40df52e27cf4098f28a79bcbad5,TabletGaze: A Dataset and Baseline Algorithms for Unconstrained Appearance-based Gaze Estimation in Mobile Tablets,"TabletGaze: Unconstrained Appearance-based Gaze +Estimation in Mobile Tablets +Qiong Huang, Student Member, IEEE,, Ashok Veeraraghavan, Member, IEEE,, +nd Ashutosh Sabharwal, Fellow, IEEE"
be437b53a376085b01ebd0f4c7c6c9e40a4b1a75,Face Recognition and Retrieval Using Cross Age Reference Coding,"ISSN (Online) 2321 – 2004 ISSN (Print) 2321 – 5526 INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN ELECTRICAL, ELECTRONICS, INSTRUMENTATION AND CONTROL ENGINEERING @@ -3837,6 +12916,22 @@ Age Reference Coding Sricharan H S1, Srinidhi K S1, Rajath D N1, Tejas J N1, Chandrakala B M2 BE, DSCE, Bangalore1 Assistant Professor, DSCE, Bangalore2"
+bea5780d621e669e8069f05d0f2fc0db9df4b50f,Convolutional Deep Belief Networks on CIFAR-10,"Convolutional Deep Belief Networks on CIFAR-10 +Alex Krizhevsky +Introduction +We describe how to train a two-layer convolutional Deep Belief Network (DBN) on the 1.6 million tiny images +dataset. +When training a convolutional DBN, one must decide what to do with the edge pixels of teh images. As +the pixels near the edge of an image contribute to the fewest convolutional lter outputs, the model may +see it t to tailor its few convolutional lters to better model the edge pixels. This is undesirable becaue it +usually comes at the expense of a good model for the interior parts of the image. We investigate several ways +of dealing with the edge pixels when training a convolutional DBN. Using a combination of locally-connected +onvolutional units and globally-connected units, as well as a few tricks to reduce the eects of over tting, +we achieve state-of-the-art performance in the classi cation task of the CIFAR-10 subset of the tiny images +dataset. +The dataset +Throughout this paper we employ two subsets of the 80 million tiny images dataset [2]. The 80 million +tiny images dataset is a collection of 32 × 32 color images obtained by searching various online image search"
be07f2950771d318a78d2b64de340394f7d6b717,3D HMM-based Facial Expression Recognition using Histogram of Oriented Optical Flow,"See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/290192867 D HMM-based Facial Expression Recognition using Histogram of Oriented Optical Flow @@ -3856,17 +12951,136 @@ All in-text references underlined in blue are linked to publications on Research letting you access and read them immediately. Available from: Djamel Bouchaffra Retrieved on: 11 February 2016"
+be313072e9706df300d86bfac54079acfb9c1ef0,Descripteurs à divers niveaux de concepts pour la classification d ’ images multi-objets,"Descripteurs à divers niveaux de concepts pour la classification +d’images multi-objets +Y. Tamaazousti1 3 +H. Le Borgne1 +C. Hudelot2 3 +CentraleSupélec, Laboratoire de Mathématiques et Informatique pour la Complexité et les Systèmes +CEA LIST, Laboratoire Vision et Ingénierie des Contenus +Université Paris-Saclay, Laboratoire MICS +{Youssef.tamaazousti, +Résumé +La classification d’images au moyen de descripteurs sé- +mantiques repose sur des caractéristiques formées par +les sorties de classifieurs binaires, chacun détectant un +oncept visuel dans l’image. Les approches existantes +onsidèrent souvent +les concepts visuels indépendam- +ment les uns des autres, alors qu’ils sont souvent liés. +Ces relations sont parfois prises en compte, au moyen +d’un schéma ascendant dépendant fortement de descrip- +teurs bas-niveaux, induisant des relations non-pertinentes"
+bea185a15d5df7bbfce83bc684c316412703efbb,Pixelnn: Example-based Image Synthesis,"Under review as a conference paper at ICLR 2018 +PIXELNN: EXAMPLE-BASED IMAGE SYNTHESIS +Anonymous authors +Paper under double-blind review"
+be24e5fd1ec27d444c66183e89b5033db9155de9,"A Continuous, Full-scope, Spatio-temporal Tracking Metric based on KL-divergence","A Continuous, Full-scope, Spatio-temporal Tracking +Metric based on KL-divergence +Terry Adams +U.S. Government +Suite 6587 +Ft. Meade, MD 20755 +Email:"
+be21529c47b79b688b420c5e296086698ba11350,CNN-Based Multimodal Human Recognition in Surveillance Environments,"Article +CNN-Based Multimodal Human Recognition in +Surveillance Environments +Ja Hyung Koo, Se Woon Cho, Na Rae Baek, Min Cheol Kim and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pil-dong-ro, 1-gil, Jung-gu, +Seoul 100-715, Korea; (J.H.K.); (S.W.C.); +(N.R.B.); (M.C.K.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 7 August 2018; Accepted: 8 September 2018; Published: 11 September 2018"
+be6f29e129a99529f7ed854384d1f4da04c4ca1f,Spatially Consistent Nearest Neighbor Representations for Fine-Grained Classification. (Représentations d'images basées sur un principe de voisins partagés pour la classification fine),"Spatially Consistent Nearest Neighbor Representations +for Fine-Grained Classification +Valentin Leveau +To cite this version: +Valentin Leveau. Spatially Consistent Nearest Neighbor Representations for Fine-Grained Classifica- +tion. Computer Science [cs]. Université Montpellier, 2016. English. <tel-01410137> +HAL Id: tel-01410137 +https://hal.archives-ouvertes.fr/tel-01410137 +Submitted on 6 Dec 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de +recherche français ou étrangers, des laboratoires"
beb4546ae95f79235c5f3c0e9cc301b5d6fc9374,A Modular Approach to Facial Expression Recognition,"A Modular Approach to Facial Expression Recognition Michal Sindlar Cognitive Artificial Intelligence, Utrecht University, Heidelberglaan 6, 3584 CD, Utrecht Marco Wiering Intelligent Systems Group, Utrecht University, Padualaan 14, 3508 TB, Utrecht"
+befd21f74248ca5f22f608043d64cdea67829737,Decoupled Access-Execute on ARM big.LITTLE,"Decoupled Access-Execute on ARM big.LITTLE +Anton Weber +Uppsala University +nton.weber.0295 +Kim-Anh Tran +Uppsala University +kim-anh.tran +Stefanos Kaxiras +Uppsala University +stefanos.kaxiras +Alexandra Jimborean +lexandra.jimborean +Uppsala University"
+be0bd420b78be8dfc0aad65dddae10ff1ec30a94,People Orientation Recognition by Mixtures of Wrapped Distributions on Random Trees,"People Orientation Recognition by Mixtures +of Wrapped Distributions on Random Trees +Davide Baltieri, Roberto Vezzani, and Rita Cucchiara +DIEF - University of Modena and Reggio Emilia +Via Vignolese 905, 41125 - Modena, Italy +http://imagelab.ing.unimore.it"
+be707bf7c7096df0fcf5bb07ef0fa53494d6a781,Effective Classifiers for Detecting Objects,"Effective Classifiers for Detecting Objects +Michael Mayo +Dept. of Computer Science +University of Waikato +Private Bag 3105, Hamilton, New Zealand +in the +literature: +Introduction +image. Many image databases such as Caltech-101 [1] +onsist of images with the objects of interest in a +dominant foreground position, occupying most of the +image."
bebea83479a8e1988a7da32584e37bfc463d32d4,Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning,"Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning Supasorn Suwajanakorn∗ Noah Snavely Jonathan Tompson Mohammad Norouzi {supasorn, snavely, tompson, Google AI"
+beeeade98988e55afe81faaedf06dc00848ec751,ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the Wild,"Int J Comput Vis manuscript No. +(will be inserted by the editor) +ARBEE: Towards Automated Recognition of Bodily +Expression of Emotion In the Wild +Yu Luo · Jianbo Ye · Reginald B. Adams, Jr. · Jia Li · +Michelle G. Newman · James Z. Wang +Received: date / Accepted: date"
+beb7a0329c3042c2ce63b5789e2581bb8e2dbbea,Generating Visual Representations for Zero-Shot Classification,"Generating Visual Representations for Zero-Shot Classification +Maxime Bucher, St´ephane Herbin +ONERA - The French Aerospace Lab +Palaiseau, France +Normandie Univ, UNICAEN, ENSICAEN, CNRS +Fr´ed´eric Jurie +Caen, France"
+bed7834ae7d371171977a590872f60d137c2f951,GuessWhat?! Visual Object Discovery through Multi-modal Dialogue,"GuessWhat?! Visual object discovery through multi-modal dialogue +Harm de Vries +University of Montreal +Florian Strub +Univ. Lille, CNRS, Centrale Lille, +Inria, UMR 9189 CRIStAL +Sarath Chandar +University of Montreal +Olivier Pietquin +DeepMind +Hugo Larochelle +Twitter +Aaron Courville +University of Montreal"
bed06e7ff0b510b4a1762283640b4233de4c18e0,Face Interpretation Problems on Low Quality Images,"Bachelor Project Czech Technical @@ -3879,6 +13093,80 @@ Quality Images Adéla Šubrtová Supervisor: Ing. Jan Čech, Ph.D May 2018"
+beec0138d21271379bdfa89317a0a1d648733bad,Model-Free Multiple Object Tracking with Shared Proposals,"Model-Free Multiple Object Tracking with +Shared Proposals +Gao Zhu1, Fatih Porikli1,2,3, Hongdong Li1,3 +Australian National University1, Data61/CSIRO2, +ARC Centre of Excellence for Robotic Vision3"
+befa14324bb71e5d0f30808e54abc970d52f758c,A Convex Approach for Image Hallucination,"OAGM/AAPR Workshop 2013 (arXiv:1304.1876) +A Convex Approach for Image Hallucination +Institute for Computer Graphics and Vision, University of Technology Graz +Peter Innerhofer, Thomas Pock"
+be25d7bff3b5928adf6c0a7f5495d47113f80997,Learning to Drive: Perception for Autonomous Cars a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"LEARNING TO DRIVE: +PERCEPTION FOR AUTONOMOUS CARS +A DISSERTATION +SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE +AND THE COMMITTEE ON GRADUATE STUDIES +OF STANFORD UNIVERSITY +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +DOCTOR OF PHILOSOPHY +David Michael Stavens +May 2011"
+be4c2b6fdde83179dd601541f57ee5d14fe1e98a,Graphical Generative Adversarial Networks,"Graphical Generative Adversarial Networks +Chongxuan Li 1 Max Welling 2 Jun Zhu 1 Bo Zhang 1"
+becb704450c6b2f7f57f03955036a5b66380b816,A Software Architecture for RGB-D People Tracking Based on ROS Framework for a Mobile Robot,"A software architecture for RGB-D +people tracking based on ROS +framework for a mobile robot +Matteo Munaro, Filippo Basso, Stefano Michieletto, Enrico Pagello, and +Emanuele Menegatti"
+be993d793e393127e3fb34d27fda255894edaedc,UnFlow: Unsupervised Learning of Optical Flow With a Bidirectional Census Loss,"UnFlow: Unsupervised Learning of Optical Flow +with a Bidirectional Census Loss +Simon Meister, Junhwa Hur, Stefan Roth +Department of Computer Science +TU Darmstadt, Germany"
+be72b20247fb4dc4072d962ced77ed89aa40372f,"Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN","Efficient Facial Representations for Age, Gender +nd Identity Recognition in Organizing Photo +Albums using Multi-output CNN +Andrey V. Savchenko +Samsung-PDMI Joint AI Center, St. Petersburg Department of Steklov Institute of +Mathematics +National Research University Higher School of Economics +Nizhny Novgorod, Russia"
+be75a0ff3999754f20e63fde90f4c68b4af22d60,R4-A.1: Dynamics-Based Video Analytics,"R4-A.1: Dynamics-Based Video Analytics +PARTICIPANTS +Octavia Camps +Mario Sznaier +Title +Co-PI +Co-PI +Faculty/Staff +Institution +Graduate, Undergraduate and REU Students +Oliver Lehmann +Mengran Gou +Yongfang Cheng +Yin Wang +Sadjad Asghari-Esfeden +Angels Rates +Degree Pursued +Institution +Email +Month/Year of Graduation"
+be5b455abd379240460d022a0e246615b0b86c14,"The MR2: A multi-racial, mega-resolution database of facial stimuli.","Behav Res +DOI 10.3758/s13428-015-0641-9 +The MR2: A multi-racial, mega-resolution database of facial +stimuli +Nina Strohminger1,6 · Kurt Gray2 · Vladimir Chituc3 · Joseph Heffner4 · +Chelsea Schein2 · Titus Brooks Heagins5 +© Psychonomic Society, Inc. 2015"
+be62019734554152c4feef62ba3092894b402efb,ARISTA - image search to annotation on billions of web photos,"The Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition +Poster Spotlights +Session: Thursday Poster Session, Thurs 17 June 2010, 10:30 - 12:10 am +ARISTA - Image Search to Annotation +on Billions of Web Photos +Xin-Jing Wang, Lei Zhang, Ming Liu, Yi Li, +Wei-Ying Ma"
beab10d1bdb0c95b2f880a81a747f6dd17caa9c2,DeepDeblur: Fast one-step blurry face images restoration,"DeepDeblur: Fast one-step blurry face images restoration Lingxiao Wang, Yali Li, Shengjin Wang Tsinghua Unversity"
@@ -3912,11 +13200,58 @@ to the fact that the camera is worn as part of clothing (see Fig. 1). Inspired by the theory of F-formation which is a pattern that people tend to follow when interacting [5], our proposed approach consists of three steps: multi-faces as-"
+b33b88a5fa5d4f20c24dd0e5f3b3529b7545c9e6,Object Detection in Real Images,"SCHOOL OF COMPUTER ENGINEERING +PhD Confirmation Report +Object Detection in Real Images +Submitted by: Dilip Kumar Prasad +Research Student (PhD) +School of Computer Engineering +E-mail: +Supervisor: Dr. Maylor K. H. Leung +Associate Professor, +School of Computer Engineering +E-mail: +August 2010"
+b3d8705d46a1d63b40a76bbcf8822b2e90b3b9ad,Efficient Labelling of Pedestrian Supervisions,"Electronic Letters on Computer Vision and Image Analysis 15(1):77-99, 2016 +Efficient Labelling of Pedestrian Supervisions +Kyaw Kyaw Htike +School of Information Technology, UCSI University, Kuala Lumpur, Malaysia +Received 7th Mar 2016; accepted 26th Jun 2016"
+b30bdbad88c72938c476f1ea6827d8b10c300da4,Supervised Mixed Norm Autoencoder for Kinship Verification in Unconstrained Videos,"Supervised Mixed Norm Autoencoder for Kinship +Verification in Unconstrained Videos +Naman Kohli, Student Member, IEEE, Daksha Yadav, Student Member, IEEE, Mayank Vatsa, +Senior Member, IEEE, Richa Singh, Senior Member, IEEE, and Afzel Noore, Senior Member, IEEE."
+b3adc7617dff08d7427142837a326b95d2e83969,A Panoramic View of Performance,"Comp. by: BVijayalakshmi Stage: Galleys ChapterID: 0000883562 Date:27/1/09 Time:17:57:10 +Evaluation of Gait Recognition +, ZONGYI LIU +SUDEEP SARKAR +Computer Science and Engineering, University of +South Florida, Tampa, FL, USA +Amazon.com, Seattle, WA, USA +Synonyms +Gait recognition; Progress in gait recognition +Definition +Gait recognition refers to automated vision methods +that use video of human gait to recognize or to identify +person. Evaluation of gait recognition refers to the +enchmarking of progress in the design of gait recog- +nition algorithms on standard, common, datasets. +Introduction +Design of biometric algorithms and evaluation of per- +formance goes hand in hand. It is important to con- +stantly evaluate and analyze progress being at various +levels of biometrics design. This evaluation can be of"
b3cb91a08be4117d6efe57251061b62417867de9,Label propagation approach for predicting missing biographic labels in face-based biometric records,"T. Swearingen and A. Ross. ""A label propagation approach for predicting missing biographic labels in A Label Propagation Approach for Predicting Missing Biographic Labels in Face-Based Biometric Records Thomas Swearingen and Arun Ross"
+b336f946d34cb427452517f503ada4bbe0181d3c,Diagnosing Error in Temporal Action Detectors,"Diagnosing Error in Temporal Action Detectors +Humam Alwassel, Fabian Caba Heilbron, Victor Escorcia, and Bernard +Ghanem +King Abdullah University of Science and Technology (KAUST), Saudi Arabia +http://www.humamalwassel.com/publication/detad/ +{humam.alwassel, fabian.caba, victor.escorcia,"
b340f275518aa5dd2c3663eed951045a5b8b0ab1,Visual inference of human emotion and behaviour,"Visual Inference of Human Emotion and Behaviour Shaogang Gong Caifeng Shan @@ -3930,13 +13265,91 @@ Queen Mary College, London England, UK England, UK England, UK"
+b38e5da11281be44c82d184079d762c9d526ba2e,Understanding Grounded Language Learning Agents,"Under review as a conference paper at ICLR 2018 +UNDERSTANDING GROUNDED LANGUAGE LEARNING +AGENTS +Anonymous authors +Paper under double-blind review"
+b34487edb8d47c0101d514b8cb63148d80deee54,Utility of Satellite and Aerial Images for Quantification of Canopy Cover and Infilling Rates of the Invasive Woody Species Honey Mesquite (Prosopis Glandulosa) on Rangeland,"Remote Sens. 2012, 4, 1947-1962; doi:10.3390/rs4071947 +OPEN ACCESS +ISSN 2072-4292 +www.mdpi.com/journal/remotesensing +Article +Utility of Satellite and Aerial Images for Quantification of +Canopy Cover and Infilling Rates of the Invasive Woody Species +Honey Mesquite (Prosopis Glandulosa) on Rangeland +Mustafa Mirik * and R. James Ansley +Texas AgriLife Research, P.O. Box 1658, 11708 Hwy 70 South, Vernon, TX 76385, USA; +E-Mail: +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +1-940-552-9941; Fax: +1-940-552-2317. +Received: 9 May 2012; in revised form: 5 June 2012 / Accepted: 25 June 2012 / +Published: 29 June 2012"
+b3655bcc6f491ae995c652c7f51e1b9b3a36d39c,User authentication based on foot motion,"Noname manuscript No. +(will be inserted by the editor) +User Authentication Based on Foot Motion +Davrondzhon Gafurov, Patrick Bours and Einar Snekkenes +Received: date / Accepted: date"
+b3d936c0d82f9b2032949af685a10708c6856d2c,Deep Learning from Noisy Image Labels with Quality Embedding,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Deep Learning from Noisy Image Labels with +Quality Embedding +Jiangchao Yao, Jiajie Wang, +Ivor Tsang, Ya Zhang, Jun Sun, Chengqi Zhang, Rui Zhang"
+b3f0a87043f7843b79744ec19dc0b93324d055d5,Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network,"Western University +Electronic Thesis and Dissertation Repository +August 2016 +Improvements to Tracking Pedestrians in Video +Streams Using a Pre-trained Convolutional Neural +Network +Marjan Ramin +The University of Western Ontario +Supervisor +Dr. Jagath Samarabandu +The University of Western Ontario +Graduate Program in Electrical and Computer Engineering +A thesis submitted in partial fulfillment of the requirements for the degree in Master of Engineering Science +© Marjan Ramin 2016 +Follow this and additional works at: https://ir.lib.uwo.ca/etd +Part of the Computer Engineering Commons +Recommended Citation +Ramin, Marjan, ""Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network"" (2016). +Electronic Thesis and Dissertation Repository. 3886. +https://ir.lib.uwo.ca/etd/3886"
b375db63742f8a67c2a7d663f23774aedccc84e5,Brain-Inspired Classroom Occupancy Monitoring on a Low-Power Mobile Platform,"Brain-inspired Classroom Occupancy Monitoring on a Low-Power Mobile Platform Department of Electrical, Electronic and Information Engineering, University of Bologna, Italy Francesco Conti∗, Antonio Pullini† and Luca Benini∗† Integrated Systems Laboratory, ETH Zurich, Switzerland"
+b3e2bd3f89e49833d45c30af7d5c923489b4d5fc,Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection,"Fast Approximate kNN Graph Construction for High +Dimensional Data via Recursive Lanczos Bisection∗ +Jie Chen† +Haw-ren Fang† +Yousef Saad† +October 2, 2008"
+b3ca58539e1407e0fb6b308194234279f78eb1d7,Structure Aligning Discriminative Latent Embedding for Zero-Shot Learning,"GUNE ET AL: STRUCTURE ALIGNING DISCRIMINATIVE LATENT EMBEDDING FOR ZSL 1 +Structure Aligning Discriminative Latent +Embedding for Zero-Shot Learning +Omkar Gune +Biplab Banerjee +Subhasis Chaudhuri +Indian Institute of Technology Bombay, +Mumbai, India +Indian Institute of Technology Bombay, +Mumbai, India +Indian Institute of Technology Bombay, +Mumbai, India"
b3c60b642a1c64699ed069e3740a0edeabf1922c,Max-Margin Object Detection,"Max-Margin Object Detection Davis E. King"
+b362b812ececef21100d7a702447fcf5ab6d4715,Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer,"Understanding and Improving Interpolation in +Autoencoders via an Adversarial Regularizer +David Berthelot∗ +Google Brain +Colin Raffel∗ +Google Brain +Aurko Roy +Google Brain +Ian Goodfellow +Google Brain"
b3f7c772acc8bc42291e09f7a2b081024a172564,"A novel approach for performance parameter estimation of face recognition based on clustering , shape and corner detection","www.ijmer.com Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3225-3230 ISSN: 2249-6645 International Journal of Modern Engineering Research (IJMER) A novel approach for performance parameter estimation of face @@ -3969,7 +13382,32 @@ your reasons. In case of a legitimate complaint, the Library will make the mater the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Download date: 08 Aug 2018"
+b34e7a2218abd5894525a60ed4f106cb9c3dc1e8,Understanding Grounded Language Learning Agents,"Under review as a conference paper at ICLR 2018 +UNDERSTANDING GROUNDED LANGUAGE LEARNING +AGENTS +Anonymous authors +Paper under double-blind review"
b32631f456397462b3530757f3a73a2ccc362342,Discriminant Tensor Dictionary Learning with Neighbor Uncorrelation for Image Set Based Classification,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+b348d5c7ac93d1148265284d71234e200c9c5f02,GibbsNet: Iterative Adversarial Inference for Deep Graphical Models,"GibbsNet: Iterative Adversarial Inference for Deep +Graphical Models +Alex Lamb +MILA, Universite de Montreal +Yaroslav Ganin +MILA, Universite de Montreal +R Devon Hjelm +MILA, Universite de Montreal +Joseph Paul Cohen +MILA, Universite de Montreal +Institute for Reproducible Research +Aaron Courville +MILA, Universite de Montreal +CIFAR +Yoshua Bengio +MILA, Universite de Montreal +CIFAR"
+dfd18b71f5c53ec2a95fcbe327cf7710da3b4851,Robust Submodular Maximization: A Non-Uniform Partitioning Approach,"Robust Submodular Maximization: +A Non-Uniform Partitioning Approach +Ilija Bogunovic 1 Slobodan Mitrovi´c 2 Jonathan Scarlett 1 Volkan Cevher 1"
df90850f1c153bfab691b985bfe536a5544e438b,"Face Tracking Algorithm Robust to Pose , Illumination and Face Expression Changes : a 3 D Parametric Model Approach","FACE TRACKING ALGORITHM ROBUST TO POSE, ILLUMINATION AND FACE EXPRESSION CHANGES: A 3D PARAMETRIC MODEL APPROACH @@ -3994,6 +13432,30 @@ df577a89830be69c1bfb196e925df3055cafc0ed,"Shift: A Zero FLOP, Zero Parameter Alt Bichen Wu, Alvin Wan∗, Xiangyu Yue∗, Peter Jin, Sicheng Zhao, Noah Golmant, Amir Gholaminejad, Joseph Gonzalez, Kurt Keutzer UC Berkeley"
+df353e3a46cca8c1ef274994f5a6dcb580231726,Data-driven fundamental models for pedestrian movements,"POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCESacceptée sur proposition du jury:Prof. P. Frossard, président du juryProf. M. Bierlaire, directeur de thèseProf. H. Mahmassani, rapporteurProf. S. Hoogendoorn, rapporteurProf. N. Geroliminis, rapporteurData-driven fundamental models for pedestrian movementsTHÈSE NO 7613 (2017)ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNEPRÉSENTÉE LE 5 MAI 2017À LA FACULTÉ DE L'ENVIRONNEMENT NATUREL, ARCHITECTURAL ET CONSTRUITLABORATOIRE TRANSPORT ET MOBILITÉPROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUE Suisse2017PARMarija NIKOLIĆ"
+df50e6e2ad60825167c6b3e641eb5cda0f3dc505,Theoretical vs. empirical discriminability: the application of ROC methods to eyewitness identification,"Wixted and Mickes Cognitive Research: Principles and Implications (2018) 3:9 +https://doi.org/10.1186/s41235-018-0093-8 +Cognitive Research: Principles +nd Implications +TU T O R I A L R E V I EW +Theoretical vs. empirical discriminability: +the application of ROC methods to +eyewitness identification +John T. Wixted1* and Laura Mickes2 +Open Access"
+dfb342327c5e883d21a1f91cd283b36dbc2a3661,Game of Sketches: Deep Recurrent Models of Pictionary-style Word Guessing,"Deep Recurrent Models of Pictionary-style Word +Guessing +Ravi Kiran Sarvadevabhatla, Member, IEEE, Shiv Surya, Trisha Mittal and R. Venkatesh Babu Senior +Member, IEEE"
+dff612c198dc50a7bef5a9cd48da5da1f893fa72,A fast stereo-based multi-person tracking using an approximated likelihood map for overlapping silhouette templates,"A Fast Stereo-Based Multi-Person Tracking +using an Approximated Likelihood Map +for Overlapping Silhouette Templates +Junji Satake +Jun Miura +Department of Computer Science and Engineering +Toyohashi University of Technology +Email: {satake, +Toyohashi, Japan"
df51dfe55912d30fc2f792561e9e0c2b43179089,Face Hallucination Using Linear Models of Coupled Sparse Support,"Face Hallucination using Linear Models of Coupled Sparse Support Reuben A. Farrugia, Member, IEEE, and Christine Guillemot, Fellow, IEEE @@ -4013,14 +13475,119 @@ German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germ {mohamed.selim, alain.pagani, s Keywords: Gender, Face, Deep Neural Networks, Quality, In the Wild"
+df4525d7d99f7237c864adbcb2dab30d8f7447e0,Kernel Cross-View Collaborative Representation based Classification for Person Re-Identification,"Kernel Cross-View Collaborative Representation based Classification for Person +Re-Identification +Raphael Prates and William Robson Schwartz +Universidade Federal de Minas Gerais, Brazil +6627, Av. Pres. Antˆonio Carlos - Pampulha, Belo Horizonte - MG, 31270-901"
df80fed59ffdf751a20af317f265848fe6bfb9c9,Learning Deep Sharable and Structural Detectors for Face Alignment,"Learning Deep Sharable and Structural Detectors for Face Alignment Hao Liu, Jiwen Lu, Senior Member, IEEE, Jianjiang Feng, Member, IEEE, and Jie Zhou, Senior Member, IEEE"
+df3b560a5d6c8cc5fa1477d3a89245a0d3b60715,Human tracking with multiple parallel metrics,"Human tracking with multiple parallel metrics +P. M. Birch*, W. Hassan, R. C. D. Young, C.R. Chatwin +Dept. of Engineering and Design, University of Sussex, Falmer, UK, BN1 9QT +Keywords: HOG, Correlation, Tracking"
+dfe2d36ca249876e5ab5500f155e3a5094dbc170,Application of common sense computing for the development of a novel knowledge-based opinion mining engine,"Application of Common Sense Computing for +the Development of a Novel Knowledge-Based +Opinion Mining Engine +A thesis submitted in accordance with the requirements of +the University of Stirling for the degree of Doctor of Philosophy +Erik Cambria +Principal Supervisor: Amir Hussain (University of Stirling, UK) +Additional Supervisor: Catherine Havasi (MIT Media Laboratory, USA) +Industrial Supervisor: Chris Eckl (Sitekit Solutions Ltd, UK) +Department of Computing Science & Mathematics +University of Stirling, Scotland, UK +December 2011"
+df310591dfba9672252d693bc87da73c246749c9,Fusion of Holistic and Part Based Features for Gender Classification in the Wild,"Fusion of Holistic and Part Based Features +for Gender Classification in the Wild +Modesto Castrill´on-Santana(B), Javier Lorenzo-Navarro, +nd Enrique Ram´on-Balmaseda +Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain +http://berlioz.dis.ulpgc.es/roc-siani"
+dfcb4773543ee6fbc7d5319b646e0d6168ffa116,Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks,"Unifying Variational Autoencoders and Generative Adversarial Networks +Adversarial Variational Bayes: +Lars Mescheder 1 +Sebastian Nowozin 2 +Andreas Geiger 1 3"
+dfbf49ed66a9e48671964872c84f75d7f916c131,Supplementary Material for Sparsity Invariant CNNs,"Supplementary Material for +Sparsity Invariant CNNs +Jonas Uhrig(cid:63),1,2 Nick Schneider(cid:63),1,3 +Lukas Schneider1,4 +Uwe Franke1 +Thomas Brox2 Andreas Geiger4,5 +Daimler R&D Sindelfingen +University of Freiburg +KIT Karlsruhe +ETH Z¨urich +5MPI T¨ubingen +. Convergence Analysis +We find that Sparse Convolutions converge much faster than standard convolutions for most input-output-combinations, +especially for those on Synthia with irregularly sparse depth input, as considered in Section 5.1 of the main paper. In Figure +, we show the mean average error in meters on our validation subset of Synthia over the process of training with identical +solver settings (Adam with momentum terms of β1 = 0.9, β2 = 0.999 and delta 1e−8). We chose for each variant the +maximal learning rate which still causes the network to converge (which turned out to be 1e−3 for all three variants). We +find that Sparse Convolutions indeed train much faster and much smoother compared to both ConvNet variants, most likely +aused by the explicit ignoring of invalid regions in the update step. Interestingly, the ConvNet variant with concatenated +visibility mask in the input converges smoother than the variant with only sparse depth in the input, however, additionally"
+dfbc3a6a629433f24f4e06fdfe8389f83afa7094,Learning OpenCV,"Learning OpenCV +Gary Bradski and Adrian Kaehler +Beijing · Cambridge · Farnham · Köln · Sebastopol · Taipei · Tokyo"
+df999184b1bb5691cd260b2b77df7ef00c0fe7b1,On Latent Distributions Without Finite Mean in Generative Models,"On Latent Distributions Without Finite Mean in +Generative Models +Damian Le´sniak∗ +Igor Sieradzki∗ +Jagiellonian University +Igor Podolak"
+df28cd627afe6d20eb198b8406ff25ece340653d,The Acquisition of Sign Language by Deaf Children with Autism Spectrum Disorder,"The Acquisition of Sign +Language by Deaf Children +with Autism Spectrum +Disorder +Aaron Shield and Richard P. Meier +Introduction +Autism spectrum disorder (ASD) consists of a set of neurobiological +developmental disorders characterized by communicative and social deficits +s well as repetitive, stereotyped behaviors.1 In this chapter, we use the +terms ‘ASD’ and ‘autism’ interchangeably; although ‘autism’ is not a clinical +term, it is the term popularly used to refer to the range of disorders found +in ASD. +The language deficits of hearing children with autism are well docu- +mented, and can range from the very mild in highly fluent speakers to the +very severe in children with a total absence of productive spoken language. +For those children who do acquire speech, the most common characteristics +of autistic language include echolalia (echoing the utterances of others), +pronoun reversal, idiosyncratic language use and neologisms (the creation +of new words), difficulty with pragmatics (problems interpreting the use +of language in context and the non-literal use of language), and abnormal"
+dfaa547451aae219cd2ca7a761e6c16c1e1d0add,Representation Learning by Rotating Your Faces,"Representation Learning by Rotating Your Faces +Luan Tran, Xi Yin, and Xiaoming Liu, Member, IEEE"
dfa80e52b0489bc2585339ad3351626dee1a8395,Human Action Forecasting by Learning Task Grammars,"Human Action Forecasting by Learning Task Grammars Tengda Han Jue Wang Anoop Cherian Stephen Gould"
+dfe7700ed053d4788ecea4a18431806581e03291,Grammatical facial expression recognition using customized deep neural network architecture,"Grammatical facial expression recognition using customized +deep neural network architecture +Devesh Walawalkar"
+dffb64ac066bbcfe6aea6b11408b5ea62a40e9fb,"A New Face Recognition Scheme for Faces with Expressions , Glasses and Rotation","International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), +INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & +ISSN 0976 - 6375(Online), Volume 5, Issue 4, April (2014), pp. 11-23 © IAEME +TECHNOLOGY (IJCET) +ISSN 0976 – 6367(Print) +ISSN 0976 – 6375(Online) +Volume 5, Issue 4, April (2014), pp. 11-23 +© IAEME: www.iaeme.com/ijcet.asp +Journal Impact Factor (2014): 8.5328 (Calculated by GISI) +www.jifactor.com +IJCET +© I A E M E +A NEW FACE RECOGNITION SCHEME FOR FACES WITH EXPRESSIONS, +GLASSES AND ROTATION +Walaa M Abdel-Hafiez1, Mohamed Heshmat2, Moheb Girgis3, Seham Elaw4 +, 2, 4Faculty of Science, Mathematical and Computer Science Department, +Sohag University, 82524, Sohag, Egypt +3Faculty of Science, Department of Computer Science, +Minia University, El-Minia, Egypt"
dfecaedeaf618041a5498cd3f0942c15302e75c3,A recursive framework for expression recognition: from web images to deep models to game dataset,"Noname manuscript No. (will be inserted by the editor) A Recursive Framework for Expression Recognition: From @@ -4030,6 +13597,10 @@ Received: date / Accepted: date" df5fe0c195eea34ddc8d80efedb25f1b9034d07d,Robust modified Active Shape Model for automatic facial landmark annotation of frontal faces,"Robust Modified Active Shape Model for Automatic Facial Landmark Annotation of Frontal Faces Keshav Seshadri and Marios Savvides"
+dfc784c860795f4f9aa704b7655f6d1321018980,Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain,"Unsupervised Co-activity Detection from +Multiple Videos using Absorbing Markov Chain +Donghun Yeo, Bohyung Han, Joon Hee Han +Department of Computer Science and Engineering, POSTECH, Korea"
df2494da8efa44d70c27abf23f73387318cf1ca8,Supervised Filter Learning for Representation Based Face Recognition,"RESEARCH ARTICLE Supervised Filter Learning for Representation Based Face Recognition @@ -4049,35 +13620,270 @@ Prediction Based on Facial Features 1.Ms.Dhanashri Shirkey , 2Prof.Dr.S.R.Gupta, M.E(Scholar),Department Computer Science & Engineering, PRMIT & R, Badnera Asstt.Prof. Department Computer Science & Engineering, PRMIT & R, Badnera"
+da7ffe21508ad8d6dd9de7da378e184cb43a56c8,3D Landmark Localisation,"D Landmark Localisation +Luke Gahan, Supervised by Prof. Paul F. Whelan"
+dab6921a578c9ded6904a5a18bdd054aee62d2ad,Learning to Recognize Faces by Successive Meetings,"Learning to recognize faces +y successive meetings +M. Castrill´on-Santana, O. D´eniz-Su´arez, +J. Lorenzo-Navarro and M. Hern´andez-Tejera +IUSIANI +Edif. Ctral. del Parque Cient´ıfico Tecnol´ogico +Universidad de Las Palmas de Gran Canaria +Las Palmas de Gran Canaria, 35017 +Spain"
+dac07680925b6c56b7ddf184dbdaf143a5d4816d,Object Ordering with Bidirectional Matchings for Visual Reasoning,"Object Ordering with Bidirectional Matchings for Visual Reasoning +Hao Tan and Mohit Bansal +UNC Chapel Hill +{haotan,"
dad7b8be074d7ea6c3f970bd18884d496cbb0f91,Super-Sparse Regression for Fast Age Estimation from Faces at Test Time,"Super-Sparse Regression for Fast Age Estimation From Faces at Test Time Ambra Demontis, Battista Biggio, Giorgio Fumera, and Fabio Roli Dept. of Electrical and Electronic Engineering, University of Cagliari Piazza d’Armi, 09123 Cagliari, Italy WWW home page: http://prag.diee.unica.it"
+da523ee3b7e8077713ebb7d903c3dc3bcb78921a,Multi-person Tracking-by-Detection Based on Calibrated Multi-camera Systems,"Multi-Person Tracking-by-Detection based on +Calibrated Multi-Camera Systems +Xiaoyan Jiang, Erik Rodner, and Joachim Denzler +Computer Vision Group Jena +Friedrich Schiller University of Jena +http://www.inf-cv.uni-jena.de"
+da288fca6b3bcaee87a034529da5621bb90123d1,Aesthetics and Emotions in Images,"[ Dhiraj Joshi, +Ritendra Datta, +Elena Fedorovskaya, +Quang-Tuan Luong, +James Z. Wang, +Jia Li, and Jiebo Luo] +PUBLICDOMAINPICTURES.NET & +© BRAND X PICTURES +[ A computational perspective] +In this tutorial, we define and discuss key aspects of the problem of computational inference of aesthetics +nd emotion from images. We begin with a background discussion on philosophy, photography, paintings, +visual arts, and psychology. This is followed by introduction of a set of key computational problems that the +research community has been striving to solve and the computational framework required for solving +them. We also describe data sets available for performing assessment and outline several real-world applica- +tions where research in this domain can be employed. A significant number of papers that have attempted to +solve problems in aesthetics and emotion inference are surveyed in this tutorial. We also discuss future direc- +tions that researchers can pursue and make a strong case for seriously attempting to solve problems in this +research domain. +Digital Object Identifier 10.1109/MSP.2011.941851 +Date of publication: 22 August 2011"
+dadb7ddfde3478238d23a8bacf5eddecc59e84c9,Vocabulary Image Captioning with Constrained Beam Search,"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 947–956 +Copenhagen, Denmark, September 7–11, 2017. c(cid:13)2017 Association for Computational Linguistics +image containing previously unseen object (‘suitcase’)CNN-RNNCaptioning ModelA catsitting insideofa suitcase.cat, suitcase, insideConstrainedBeamSearchBeamSearchA cat sitting on top ofa refrigerator.Image TagsFigure1:Wesuccessfullycaptionimagescontain-ingpreviouslyunseenobjectsbyincorporatingse-manticattributes(i.e.,imagetags)duringRNNde-coding.ActualexamplefromSection4.2.prisingly,modelstrainedonthesedatasetsdonotgeneralizewelltoout-of-domainimagescontain-ingnovelscenesorobjects(Tranetal.,2016).Thislimitationseverelyhinderstheuseofthesemodelsinrealworldapplicationsdealingwithim-agesinthewild.Althoughavailableimage-captiontrainingdataislimited,manyimagecollectionsareaugmentedwithground-truthtextfragmentssuchassemanticattributes(i.e.,imagetags)orobjectannotations.Eveniftheseannotationsdonotexist,theycanbegeneratedusing(potentiallytaskspecific)imagetaggers(Chenetal.,2013;Zhangetal.,2016)orobjectdetectors(Renetal.,2015;Krauseetal.,2016),whichareeasiertoscaletonewconcepts.Inthispaperourgoalistoincorporatetextfrag-mentssuchastheseduringcaptiongeneration,toimprovethequalityofresultingcaptions.Thisgoalposestwokeychallenges.First,RNNsaregenerallyopaque,anddifficulttoinfluenceattesttime.Second,textfragmentsmayincludewords"
+da55917aa3a8a95179bae92c5b01e4c8f2f61b75,What makes a place? Building bespoke place dependent object detectors for robotics,"What Makes a Place? Building Bespoke Place Dependent Object Detectors +for Robotics +Jeffrey Hawke, Alex Bewley, Ingmar Posner"
da4170c862d8ae39861aa193667bfdbdf0ecb363,Multi-Task CNN Model for Attribute Prediction,"Multi-task CNN Model for Attribute Prediction Abrar H. Abdulnabi, Student Member, IEEE, Gang Wang, Member, IEEE, , Jiwen Lu, Member, IEEE nd Kui Jia, Member, IEEE"
+da013b84a93cc89d78f2d9a346fc275e3c159565,Affordable Self Driving Cars and Robots with Semantic Segmentation,"Affordable Self Driving Cars and Robots with Semantic Segmentation +Gaurav Bansal +Jeff Chen +Evan Darke"
+dabf269f516adc6bf87a7ceb455cceda4466917a,Investigation of Facial Artifacts on Face Biometrics using Eigenface based Single and Multiple Neural Networks,"Investigation of Facial Artifacts on Face Biometrics +using Eigenface based Single and Multiple Neural Networks +K. Sundaraj +University Malaysia Perlis (UniMAP) +School of Mechatronics Engineering +02600 Jejawi - Perlis +MALAYSIA"
+da9080d5b433f73444078ac79c3a8a4515ad958e,IIS at ImageCLEF 2015: Multi-label Classification Task,"IIS at ImageCLEF 2015: +Multi-label classification task +Antonio J Rodr´ıguez-S´anchez1, Sabrina Fontanella1,2, +Justus Piater1, and Sandor Szedmak1 +Intelligent and Interactive Systems, Department of Computer Science, +University of Innsbruck, Austria +Department of Computer Science, University of Salerno, Italy +https://iis.uibk.ac.at/"
+da995212c9c8a933307cd893d862f5bf7d99f3ec,Synthesizing Samples for Zero-shot Learning,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +EmbeddingSample EmbeddingElephantLionPandaMonkeyDolphinDog0.140.490.660.721.060.59Figure1:FrameworkofembeddingbasedZSLapproaches.occurfrequentlyenough,andthenewconceptsemergeev-erydayespeciallyintheWeb,whichmakesitdifficultandex-pensivetocollectandlabelasufficientlylargetrainingsetformodellearning[Changpinyoetal.,2016].Howtotraineffec-tiveclassificationmodelsfortheuncommonclasseswithoutusingthelabeledsamplesbecomesanimportantandpracti-calproblemandhasgatheredconsiderableresearchinterestsfromthemachinelearningandcomputervisioncommunities.Itisestimatedthathumanscanrecognizeapproximate30;000basicobjectcategoriesandmanymoresubordinateonesandtheyareabletoidentifynewclassesgivenanat-tributedescription[Lampertetal.,2014].Basedonthisob-servation,manyzero-shotlearning(ZSL)approacheshavebeenproposed[Akataetal.,2015;Romera-ParedesandTorr,2015;ZhangandSaligrama,2016a;Guoetal.,2017a].ThegoalofZSListobuildclassifiersfortargetunseenclassesgivennolabeledsamples,withclassattributesassidein-formationandfullylabeledsourceseenclassesasknowl-edgesource.Differentfrommanysupervisedlearningap-proacheswhichtreateachclassindependently,ZSLasso-ciatesclasseswithanintermediaryattributeorsemantics-paceandthentransfersknowledgefromthesourceseenclassestothetargetunseenclassesbasedontheassocia-tion.Inthisway,onlytheattributevectorofatarget(un-seen)classisrequiredandtheclassificationmodelcanbebuiltevenwithoutanylabeledsamplesforthisclass.Inparticular,anembeddingfunctionislearnedusingthela-beledsamplesofsourceseenclassesthatmapstheimagesandclassesintoacommonembeddingspacewherethedis-tanceorsimilaritybetweenthemcanbemeasured.Becausetheattributesaresharedbybothsourceandtargetclass-es,theembeddingfunctionlearnedbysourceclassescanbedirectlyappliedtotargetclasses[Farhadietal.,2009;Socheretal.,2013].Finally,givenatestimage,wemapit"
+da1ba46027b7236c937d276fb54e99906036c4ef,Using 3D Representations of the Nasal Region for Improved Landmarking and Expression Robust Recognition,"Using 3D Representations of the Nasal +Region for Improved Landmarking and +Expression Robust Recognition +Jiangning Gao1 +Adrian N Evans1 +Department of Electronic and +Electrical Engineering, University +of Bath, Bath, UK, BA2 7AY."
dac2103843adc40191e48ee7f35b6d86a02ef019,Unsupervised Celebrity Face Naming in Web Videos,"Unsupervised Celebrity Face Naming in Web Videos Lei Pang and Chong-Wah Ngo"
dae420b776957e6b8cf5fbbacd7bc0ec226b3e2e,Recognizing Emotions in Spontaneous Facial Expressions,"RECOGNIZING EMOTIONS IN SPONTANEOUS FACIAL EXPRESSIONS Michael Grimm, Dhrubabrata Ghosh Dastidar, and Kristian Kroschel Institut f¨ur Nachrichtentechnik Universit¨at Karlsruhe (TH), Germany"
+da833d8ec9c91d55256effccd370b2e62a896ccb,Front-view Gait Recognition,"Front-view Gait Recognition +Michela Goffredo, John N. Carter and Mark S. Nixon"
daa02cf195818cbf651ef81941a233727f71591f,Face recognition system on Raspberry Pi,"Face recognition system on Raspberry Pi Olegs Nikisins, Rihards Fuksis, Arturs Kadikis, Modris Greitans Institute of Electronics and Computer Science, 4 Dzerbenes Street, Riga, LV 1006, Latvia"
+da8d0855e7760e86fbec47a3cfcf5acd8c700ca8,F 2 ConText : How to Extract Holistic Contexts of Persons of Interest for Enhancing Exploratory Analysis,"Accepted on 15 Sep 2018. To appear in Knowledge and Information Systems. +Under consideration for publication in Knowledge and Information Sys- +F2ConText: How to Extract Holistic +Contexts of Persons of Interest for +Enhancing Exploratory Analysis +Md Abdul Kader1, Arnold P. Boedihardjo2 and M. Shahriar Hossain3 +IBM Innovation Center, Austin, TX 78758 +Radiant Solutions, Herndon, VA 20171 +The University of Texas at El Paso, El Paso, TX 79968"
+da1e0b9e445493d3e6dc0e3c23be194228c5d796,Video Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) Setting,"Video Segmentation using Teacher-Student Adaptation +in a Human Robot Interaction (HRI) Setting +Mennatullah Siam1, Chen Jiang1, Steven Lu1, Laura Petrich1, +Mahmoud Gamal2, Mohamed Elhoseiny3, Martin Jagersand1"
daefac0610fdeff415c2a3f49b47968d84692e87,Multimodal Frame Identification with Multilingual Evaluation,"New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics Proceedings of NAACL-HLT 2018, pages 1481–1491"
+daef6fa60c7d79930ad0a341aab69f1f4fa80442,Supplement for BIER,"Supplement for BIER +. Introduction +In this document we provide further insights into Boost- +ing Independent Embeddings Robustly (BIER). First, in +Section 2 we describe our method for loss functions op- +erating on triplets. Next, in Section 3 we show how our +method behaves when we vary the embedding size and the +number of groups. In Section 4 we summarize the effect of +our boosting based training approach and our initialization +pproach. We provide an experiment evaluating the impact +of end-to-end training in Section 5. Further, in Section 6 we +demonstrate that our method is applicable to generic im- +ge classification problems. Finally, we show a qualitative +omparison of the different embeddings in our ensemble in +Section 7 and some qualitative results in Section 8. +. BIER for Triplets +For loss functions operating on triplets of samples, we +illustrate our training method in Algorithm 1. In contrast +to our tuple based algorithm, we sample triplets x(1), x(2) +nd x(3) which satisfy the constraint that the first pair (x(1),"
+da24f3e196c5345ce08dfcc835574035da197f48,A Global Alignment Kernel based Approach for Group-level Happiness Intensity Estimation,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2017 +A Global Alignment Kernel based Approach for +Group-level Happiness Intensity Estimation +Xiaohua Huang, Abhinav Dhall, Roland Goecke, Member, IEEE, Matti Pietik¨ainen, Fellow, IEEE, and +Guoying Zhao, Senior Member, IEEE"
b49affdff167f5d170da18de3efa6fd6a50262a2,Linking Names and Faces : Seeing the Problem in Different Ways,"Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France (2008)"""
+b4d117e109b3a6762d1b675defd9f2b228613ac1,Financialized methods for market-based multi-sensor fusion,"Congress Center Hamburg +Sept 28 - Oct 2, 2015. Hamburg, Germany +978-1-4799-9993-4/15/$31.00 ©2015 IEEE"
+b498640d8f0ac5a628563ff84dbef8d35d12a7ec,Overcoming catastrophic forgetting with hard attention to the task,"Overcoming Catastrophic Forgetting with Hard Attention to the Task +Joan Serr`a 1 D´ıdac Sur´ıs 1 2 Marius Miron 1 3 Alexandros Karatzoglou 1"
+b4b6a0129bf6a716fca80a4cfc322687a72fa927,Automatic Generation of Planar Marionettes from Frontal Images,"Automatic Generation of Planar Marionettes from Frontal Images +Elad Richardson and Gil Ben-Shachar +Supervised by Anastasia Dubrovina and Aaron Weltzer"
+b4a3f480e2004bdc8106de2f772283101bb290d0,Multi-stage ranking approach for fast person re-identification,"IET Research Journals +A Multi-Stage Ranking Approach for Fast Person Re-Identification +A Multi-Stage Ranking Approach for Fast +Person Re-Identification +Bahram Lavi, Giorgio Fumera , Fabio Roli +Department of Electrical and Electronic Engineering, University of Cagliari +Piazza d’Armi, 09123, Cagliari, Italy +E-mail: +ISSN 1751-8644 +doi: 0000000000 +www.ietdl.org"
+b40881a905cf6c4963658df4f64b860f9b1755fe,Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation,"Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation +Matan Sela +Elad Richardson +Ron Kimmel +Department of Computer Science, Technion - Israel Institute of Technology +Figure 1: Results of the proposed method. Reconstructed geometries are shown next to the corresponding input images."
+b4270de7380d305b4417f662686093c40d842da4,Graphical Models for Wide-Area Activity Analysis in Continuous Videos,"UNIVERSITY OF CALIFORNIA +RIVERSIDE +Graphical Models for Wide-Area Activity Analysis in Continuous Videos +A Dissertation submitted in partial satisfaction +of the requirements for the degree of +Doctor of Philosophy +Computer Science +Nandita M. Nayak +May 2014 +Dissertation Committee: +Professor Amit K. Roy-Chowdhury, Chairperson +Professor Christian Shelton +Professor Eamonn Keogh +Professor Victor Zordan"
+b49aa569ff63d045b7c0ce66d77e1345d4f9745c,Convolutional Neural Networks for Crop Yield Prediction using Satellite Images,"Convolutional Neural Networks for Crop Yield Prediction using Satellite Images +H. Russello"
b41374f4f31906cf1a73c7adda6c50a78b4eb498,Iterative Gaussianization: From ICA to Random Rotations,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. Iterative Gaussianization: From ICA to Random Rotations Valero Laparra, Gustavo Camps-Valls, Senior Member, IEEE, and Jesús Malo"
+b408b939c0f3be9cce0f84871a78a71d1684cd77,Identifying spatial relations in images using convolutional neural networks,"Identifying Spatial Relations in Images using +Convolutional Neural Networks +Mandar Haldekar, Ashwinkumar Ganesan +Dept. Of Computer Science & Engineering, +Tim Oates +Dept. Of Computer Science & Engineering, +UMBC, +Baltimore, MD +mandarh1, +UMBC, +Baltimore, MD"
+b44d8ecac21867c540d9122a150c8d8c0875cbe6,Mixture Density Generative Adversarial Networks,"Mixture Density Generative Adversarial Networks +Hamid Eghbal-zadeh1 ∗ +Werner Zellinger2 +Gerhard Widmer1 +LIT AI Lab & Institute of Computational Perception +Department of Knowledge-Based Mathematical Systems +{hamid.eghbal-zadeh, werner.zellinger, +Johannes Kepler University of Linz, Austria"
+b4b1b39f8902208bbd37febfb68e08809098036d,TRECVid Semantic Indexing of Video : A 6-year Retrospective,"UvA-DARE (Digital Academic Repository) +TRECVid Semantic Indexing of Video: A 6-year Retrospective +Awad, G.; Snoek, C.G.M.; Smeaton, A.F.; Quénot, G. +Published in: +ITE Transactions on Media Technology and Applications +0.3169/mta.4.187 +Link to publication +Citation for published version (APA): +Awad, G., Snoek, C. G. M., Smeaton, A. F., & Quénot, G. (2016). TRECVid Semantic Indexing of Video: A 6- +year Retrospective. ITE Transactions on Media Technology and Applications, 4(3), 187-208. DOI: +0.3169/mta.4.187 +General rights +It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +Disclaimer/Complaints regulations +If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask +the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, +The Netherlands. You will be contacted as soon as possible. +Download date: 02 Nov 2018"
+b4223cc72543656c28b55af1ffdabb1e47a0f2dd,Stacking with Auxiliary Features for Visual Question Answering,"New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics +Proceedings of NAACL-HLT 2018, pages 2217–2226"
+b4fe9594e1de682e7270645ba95ab64727b6632e,Generative Adversarial Positive-Unlabelled Learning,"Generative Adversarial Positive-Unlabelled Learning +Ming Hou1, Brahim Chaib-draa2, Chao Li1, Qibin Zhao1, +Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan +Department of Computer Science and Software Engineering, Laval University, Quebec, Canada"
+b4c02e071432a9a986501b7317b524f216e87ec8,Visual Saliency Prediction using Deep learning Techniques A Degree Thesis,"Visual Saliency Prediction +using Deep learning Techniques +A Degree Thesis +Submitted to the Faculty of the +Escola Tècnica d'Enginyeria de Telecomunicació de +Barcelona +Universitat Politècnica de Catalunya +Junting Pan +In partial fulfilment +of the requirements for the degree in +TELECOMUNICATION ENGINEERING +Advisor: Xavier Giró i Nieto +Barcelona, July 2015"
+b49425f78907fcc447d181eb713abffc74dd85e4,Sampling Matters in Deep Embedding Learning,"Sampling Matters in Deep Embedding Learning +Chao-Yuan Wu∗ +UT Austin +R. Manmatha +A9/Amazon +Alexander J. Smola +Amazon +Philipp Kr¨ahenb¨uhl +UT Austin"
b4ee64022cc3ccd14c7f9d4935c59b16456067d3,Unsupervised Cross-Domain Image Generation,"Unsupervised Cross-Domain Image Generation Xinru Hua, Davis Rempe, and Haotian Zhang"
+b45a9f95980c434582c920bf15a8099ec267c1f7,Robust Kronecker Component Analysis,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Robust Kronecker Component Analysis +Mehdi Bahri, Student Member, IEEE, Yannis Panagakis, and Stefanos Zafeiriou, Member, IEEE"
+b4f6962068c27d10df9016090a0ca14f65f26b70,A Statisitical Shape Model for Deformable Surface Registration,"A STATISITICAL SHAPE MODEL FOR DEFORMABLE +SURFACE REGISTRATION +Wei Quan, Bogdan J. Matuszewski and Lik-Kwan Shark +Applied Digital Signal and Image Processing (ADSIP) Research Centre +University of Central Lancashire, Preston PR1 2HE, United Kingdom +{wquan, bmatuszewski1, +Keywords: +Deformable Registration, Surface Matching, Shape Modelling and Face Articulation."
b40290a694075868e0daef77303f2c4ca1c43269,Combining Local and Global Information for Hair Shape Modeling,"第 40 卷 第 4 期 014 年 4 月 自 动 化 学 报 @@ -4097,6 +13903,40 @@ DOI 10.3724/SP.J.1004.2014.00615 Combining Local and Global Information for Hair Shape Modeling WANG Nan1 AI Hai-Zhou1"
+b4ee2a6b5fdf66f57e94a998cff2acef4af7d256,Monocular Visual Scene Understanding: Understanding Multi-Object Traffic Scenes,"Monocular Visual Scene Understanding: +Understanding Multi-Object Traffic Scenes +Christian Wojek, Stefan Walk, Stefan Roth, Konrad Schindler, Bernt Schiele"
+b419e0e1192d307d536421d811d10657f65eb72b,Face Recognition using DCT based Energy Discriminant Mask,"International Journal of Computer Applications (0975 – 8887) +Volume 170 – No.5, July 2017 +Face Recognition using DCT based Energy +Discriminant Mask +Vikas Maheshkar +Division of Information technology +New Delhi, India"
+b47386e10125462d60d66f8d6d239a69c5966853,Robust Multi Gradient Entropy Method for Face Recognition System for Low Contrast Noisy Images,"International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) +Web Site: www.ijettcs.org Email: +ISSN 2278-6856 +Volume 2, Issue 3, May – June 2013 +ROBUST MULTI GRADIENT ENTROPY +METHOD FOR FACE RECOGNITION +SYSTEM FOR LOW CONTRAST NOISY +IMAGES +C. Naga Raju1, P.Prathap Naidu2, R. Pradeep Kumar Reddy3, G. Sravana Kumari4 +Associate Professor, CSE Dept, YSR Engg College of YVU +Asst. Professor, CSE Dept, RGM Engg College +Asst. Professor, CSE Dept, YSR Engg College. +M.Tech In CSE RGM Engg College +the most +recognition under difficult"
+b47ea4d5b0040d85181925bda74da4ab5303768f,LIFEisGAME:A Facial Character Animation System to Help Recognize Facial Expressions,"LIFEisGAME:A Facial Character Animation System to +Help Recognize Facial Expressions +Tiago Fernandes1,5, Samanta Alves2, José Miranda3,5, Cristina Queirós2, +Verónica Orvalho1,4 +Instituto de Telecomunicações, Lisboa, Portugal, +Faculdade de Psicologia da Universidade do Porto, Porto, Portugal, +Instituto Politécnico da Guarda, Porto, Portugal, +Faculdade de Ciências da Universidade do Porto, Porto, Portugal, +5 Faculdade de Engenharia da Universidade do Porto, Porto, Portugal,"
b4b0bf0cbe1a2c114adde9fac64900b2f8f6fee4,Autonomous Learning Framework Based on Online Hybrid Classifier for Multi-view Object Detection in Video,"Autonomous Learning Framework Based on Online Hybrid Classifier for Multi-view Object Detection in Video Dapeng Luoa*Zhipeng Zenga Longsheng Weib Yongwen Liua Chen Luoc Jun Chenb Nong Sangd @@ -4105,6 +13945,12 @@ School of Automation, China University of Geosciences, Wuhan, Hubei 430074, Chin Huizhou School Affiliated to Beijing Normal University, Huizhou 516002, China dNational Key Laboratory of Science and Technology on Multispectral Information Processing, School of Automation, Huazhong University of Science and Technology, Wuhan, 430074, China"
+b411850a3614fbb06bc77e6f776b2f23af563a90,Size Does Matter: Improving Object Recognition and 3D Reconstruction with Cross-Media Analysis of Image Clusters,"Size does matter: improving object recognition +nd 3D reconstruction with cross-media analysis +of image clusters +Stephan Gammeter1, Till Quack1, David Tingdahl2, and Luc van Gool1,2 +BIWI, ETH Z¨urich1 http://www.vision.ee.ethz.ch +VISICS, K.U. Leuven2 http://www.esat.kuleuven.be/psi/visics"
a285b6edd47f9b8966935878ad4539d270b406d1,Facial Expression Recognition Based on Local Binary Patterns and Kernel Discriminant Isomap,"Sensors 2011, 11, 9573-9588; doi:10.3390/s111009573 OPEN ACCESS sensors @@ -4121,14 +13967,141 @@ E-Mail: Tel.: +86-576-8513-7178; Fax: ++86-576-8513-7178. Received: 31 August 2011; in revised form: 27 September 2011 / Accepted: 9 October 2011 / Published: 11 October 2011"
+a2ad9ae7c5adbbce9ded16ac3ebdfa96505c0f46,Déjà Image-Captions: A Corpus of Expressive Descriptions in Repetition,"Human Language Technologies: The 2015 Annual Conference of the North American Chapter of the ACL, pages 504–514, +Denver, Colorado, May 31 – June 5, 2015. c(cid:13)2015 Association for Computational Linguistics"
a2359c0f81a7eb032cff1fe45e3b80007facaa2a,Towards Structured Analysis of Broadcast Badminton Videos,"Towards Structured Analysis of Broadcast Badminton Videos Anurag Ghosh Suriya Singh C.V.Jawahar {anurag.ghosh, CVIT, KCIS, IIIT Hyderabad"
+a28f831b4014fa75a69f3c56e39d9c40fc0af48f,AAD: Adaptive Anomaly Detection through traffic surveillance videos,"AAD: Adaptive Anomaly Detection through traffic +surveillance videos +Mohammad Farhadi Bajestani +Seyed Soroush Heidari Rahmat Abadi +Seyed Mostafa Derakhshandeh Fard +Roozbeh Khodadadeh"
+a271f83cb1f72e0f9ca077499f51adb086fb449d,Unsupervised and Semi-supervised Methods for Human Action Analysis,"Unsupervised and +Semi-supervised Methods +for Human Action Analysis +Simon Jones +September 22, 2014 +A thesis submitted in partial fulfillment of the +requirements for the degree of +Doctor of Philosophy +Department of Electronic and Electrical Engineering +The University of Sheffield"
+a290019f7125f6ebdc0dcec3b03b771de6905dd0,Heterogeneous AdaBoost with Real-time Constraints - Application to the Detection of Pedestrians by Stereovision,"HETEROGENEOUS ADABOOST WITH REAL-TIME +Application to the Detection of Pedestrians by stereovision +CONSTRAINTS +Lo¨ıc Jourdheuil1, Nicolas Allezard1, Thierry Chateau2 and Thierry Chesnais1 +CEA, LIST, Laboratoire Vision et Ing´enierie des Contenus, Gif-sur-Yvette, France +LASMEA, UMR UBP-CNRS 6602, 24 Avenue des Landais, AUBIERE, France +{loic.jourdheuil, nicolas.allezard, +Keywords: +Adaboost. stereovision. real time."
+a24f84b156bbb1edeb1d0761f5940de318b7ed9d,Copula Eigenfaces - Semiparametric Principal Component Analysis for Facial Appearance Modeling,
+a2db611b6179f3bc4cfe0e891df7b9d4ab58d642,On the usability of deep networks for object-based image analysis,"ON THE USABILITY OF DEEP NETWORKS FOR OBJECT-BASED IMAGE ANALYSIS +Nicolas Audeberta, b, Bertrand Le Sauxa, Sébastien Lefèvreb +ONERA, The French Aerospace Lab, F-91761 Palaiseau, France +Univ. Bretagne-Sud, UMR 6074, IRISA, F-56000 Vannes, France - +KEY WORDS: deep learning, vehicle detection, semantic segmentation, object classification"
+a212be7ec1ff75ecfee52c7c49c73d7244a87eb7,Video Scene-Aware Dialog Track in DSTC 7,"Video Scene-Aware Dialog Track in DSTC7 +Chiori Hori∗, Tim K. Marks∗, Devi Parikh∗∗, and Dhruv Batra∗∗ +Mitsubishi Electric Research Laboratories +Cambridge, MA, USA +{chori, +School of Interactive Computing +Georgia Tech +{parikh,"
+a2a42aa37641490213b2de9eb8e83f3dab75f5ed,Multilinear Supervised Neighborhood Preserving Embedding Analysis of Local Descriptor Tensor,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+a2505774d5654685c6d899760759520b339e6c1e,Ranking Eigenfaces Through Adaboost and Perceptron Ensembles,"Ranking Eigenfaces Through Adaboost and +Perceptron Ensembles +Tiene A. Filisbino, Gilson A. Giraldi +Laborat´orio Nacional de Computac¸˜ao Cient´ıfica - LNCC +Petr´opolis, Brasil +Email: +Carlos Eduardo Thomaz +Departamento de Engenharia El´etrica +Centro Universit´ario da FEI +S˜ao Bernardo do Campo - Brasil +Email:"
+a2bfab80a4b48717aa647cb38069632c5962c6a6,Countering Bias in Tracking Evaluations,
a27735e4cbb108db4a52ef9033e3a19f4dc0e5fa,Intention from Motion,"Intention from Motion Andrea Zunino, Jacopo Cavazza, Atesh Koul, Andrea Cavallo, Cristina Becchio and Vittorio Murino"
+a2aa272b32c356ec9933b32ca5809c09f2d21b9f,Clockwork Convnets for Video Semantic Segmentation,"Clockwork Convnets for Video Semantic Segmentation +Evan Shelhamer(cid:63) +Kate Rakelly(cid:63) +Judy Hoffman(cid:63) +Trevor Darrell +UC Berkeley"
+a2f2996145d3d670608af1cbbda59c1ac28d4f7c,Real-Time Hand Posture Recognition for Human-Robot Interaction Tasks,"Article +Real-Time Hand Posture Recognition for +Human-Robot Interaction Tasks +Uriel Haile Hernandez-Belmonte and Victor Ayala-Ramirez * +Received: 30 October 2015; Accepted: 18 December 2015; Published: 4 January 2016 +Academic Editor: Lianqing Liu +Universidad de Guanajuato DICIS, Carr. Salamanca-Valle Km. 3.5 + 1.8, Palo Blanco, Salamanca, C.P. 36885, +Mexico; +* Correspondence: Tel.: +52-464-647-9940 (ext. 2413); Fax: +52-464-647-9940 (ext. 2311)"
+a27740f8a3834d6bc605a6b383c4d802ced373c9,"Exploiting feature representations through similarity learning, post-ranking and ranking aggregation for person re-identification","Exploiting feature representations through similarity learning, post-ranking and +ranking aggregation for person re-identification +Julio C. S. Jacques Juniora,b,∗, Xavier Bar´oa,b, Sergio Escalerac,b +Faculty of Computer Science, Multimedia and Telecommunication - Universitat Oberta de Catalunya, Spain +Computer Vision Center - Universitat Aut`onoma de Barcelona, Spain +Department of Mathematics and Informatics - University of Barcelona, Spain"
+a27c7afac5a34141ec5415defed6d4d85325230a,Utrecht Multi-Person Motion (UMPM) benchmark,"Utrecht Multi-Person Motion (UMPM) +enchmark +N.P. van der Aa, X. Luo, G.-J. Giezeman +R.T. Tan, R.C. Veltkamp +Technical Report UU-CS-2011-027 +September 2011 +Department of Information and Computing Sciences +Utrecht University, Utrecht, The Netherlands +www.cs.uu.nl"
+a2afaa782be91f5baf9e9f1794d57dd29143cbf4,IGCV$2$: Interleaved Structured Sparse Convolutional Neural Networks,"IGCV2: Interleaved Structured Sparse Convolutional Neural Networks +Guotian Xie1,2,∗ Jingdong Wang3 Ting Zhang3 +Jianhuang Lai1,2 Richang Hong4 Guo-Jun Qi5 +Sun Yat-Sen University 2Guangdong Key Laboratory of Information Security Technology +Microsoft Research 4Hefei University of Technology 5University of Central Florida"
+a2fce1c551a3c3b1cac16a96f86a59cd7fbd4c80,Attachment and Children’s Biased Attentional Processing: Evidence for the Exclusion of Attachment-Related Information,"Attachment and Children’s Biased Attentional +Processing: Evidence for the Exclusion of Attachment- +Related Information +Eva Vandevivere1*, Caroline Braet1, Guy Bosmans2, Sven C. Mueller3, Rudi De Raedt3 +Department of Developmental, Personality and Social Psychology, Ghent University, Gent, Belgium, 2 Parenting and Special Education Research Unit, Leuven, Belgium, +Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium"
+a237e3d89c460e1b2e3f12c5d4275bd0c6eb47a8,Domain Adaptation on Graphs by Learning Aligned Graph Bases,"Domain Adaptation on Graphs by Learning +Aligned Graph Bases +Mehmet Pilancı and Elif Vural"
+a2b9c998264ab1920ea8f2e07c3590ebb3dc6f35,Shopper Analytics: A Customer Activity Recognition System Using a Distributed RGB-D Camera Network,"Shopper Analytics: a customer activity +recognition system using a distributed RGB-D +amera network +Daniele Liciotti, Marco Contigiani, Emanuele Frontoni, Adriano Mancini, +Primo Zingaretti1, and Valerio Placidi2 +Dipartimento di Ingegneria dell’Informazione, Universit`a Politecnica delle Marche, +{d.liciotti, m.contigiani,e.frontoni, a.mancini, +Via Brecce Bianche, 60131 Ancona, Italy, +Grottini Lab srl, +Via S.Maria in Potenza, 62017, Porto Recanati, Italy,"
a2fbaa0b849ecc74f34ebb36d1442d63212b29d2,An Efficient Approach to Face Recognition of Surgically Altered Images,"Volume 5, Issue 6, June 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering @@ -4140,6 +14113,51 @@ Er. Supriya, Er. Sukhpreet Kaur Department of computer science and engineering SUS college of Engineering and Technology, Tangori, District, Mohali, Punjab, India"
+a21b8aadb27cd10d8a228fe1aad27c0c88d67f15,Design and Implementation of PC Operated Flying Robot for Rescue Operation in Coalmines,"ISSN: 2278 – 7798 +International Journal of Science, Engineering and Technology Research (IJSETR) +Volume 2, Issue 1, January 2013 +Design and Implementation of PC Operated +Flying Robot for Rescue Operation in +Coalmines +Aditya Kumar T , Pravin A, M S Madhan mohan, T V Janardhanarao"
+a23e7e71fb92a56c2e7717f6356e8b69fc2f4bfc,"Multimodal fusion of audio, scene, and face features for first impression estimation","Multimodal Fusion of Audio, Scene, and Face +Features for First Impression Estimation +Furkan G¨urpınar +Program of Computational +Science and Engineering +Bo˘gazic¸i University +Bebek, Istanbul, Turkey +Email: +Heysem Kaya +Albert Ali Salah +Department of Computer Engineering +Department of Computer Engineering +Namık Kemal University +C¸ orlu, Tekirda˘g, Turkey +Email: +Bo˘gazic¸i University +Bebek, Istanbul, Turkey +Email:"
+a2dd13729206a7434ef1f0cd016275c0d6f3bb6d,SFV: Reinforcement Learning of Physical Skills from Videos,"SFV: Reinforcement Learning of Physical Skills from Videos +XUE BIN PENG, University of California, Berkeley +ANGJOO KANAZAWA, University of California, Berkeley +JITENDRA MALIK, University of California, Berkeley +PIETER ABBEEL, University of California, Berkeley +SERGEY LEVINE, University of California, Berkeley +Fig. 1. Simulated characters performing highly dynamic skills learned by imitating video clips of human demonstrations. Left: Humanoid performing +artwheel B on irregular terrain. Right: Backflip A retargeted to a simulated Atlas robot. +Data-driven character animation based on motion capture can produce +highly naturalistic behaviors and, when combined with physics simula- +tion, can provide for natural procedural responses to physical perturbations, +environmental changes, and morphological discrepancies. Motion capture +remains the most popular source of motion data, but collecting mocap data +typically requires heavily instrumented environments and actors. In this +paper, we propose a method that enables physically simulated characters +to learn skills from videos (SFV). Our approach, based on deep pose esti- +mation and deep reinforcement learning, allows data-driven animation to +leverage the abundance of publicly available video clips from the web, such +s those from YouTube. This has the potential to enable fast and easy de- +sign of character controllers simply by querying for video recordings of the"
a50b4d404576695be7cd4194a064f0602806f3c4,Efficiently Estimating Facial Expression and Illumination in Appearance-based Tracking,"In Proceedings of BMVC, Edimburgh, UK, September 2006 Efficiently estimating facial expression and illumination in appearance-based tracking @@ -4151,16 +14169,55 @@ Facultad Inform´atica, UPM Campus de Montegancedo s/n 8660 Boadilla del Monte, Spain http://www.dia.fi.upm.es/~pcr"
+a511463a423f842bdb524009f6ce6c6b0ffa0f77,Kernel diff-hash,"Kernel diff-hash +Michael M. Bronstein +Institute of Computational Science +Faculty of Informatics, +Universit`a della Svizzera Italiana +Via G. Buffi 13, Lugano 6900, Switzerland +November 3, 2011"
a5e5094a1e052fa44f539b0d62b54ef03c78bf6a,Detection without Recognition for Redaction,"Detection without Recognition for Redaction Shagan Sah1, Ram Longman1, Ameya Shringi1, Robert Loce2, Majid Rabbani1, and Raymond Ptucha1 Rochester Institute of Technology - 83 Lomb Memorial Drive, Rochester, NY USA, 14623 Conduent, Conduent Labs - US, 800 Phillips Rd, MS128, Webster, NY USA, 14580 Email:"
+a55dea7981ea0f90d1110005b5f5ca68a3175910,"Are 1, 000 Features Worth A Picture? Combining Crowdsourcing and Face Recognition to Identify Civil War Soldiers","Combining Crowdsourcing and Face Recognition to Identify Civil War Soldiers +Are 1,000 Features Worth A Picture? +Vikram Mohanty, David Thames, Kurt Luther +Department of Computer Science and Center for Human-Computer Interaction +Virginia Tech, Arlington, VA, USA"
+a5c63f38e2e6ca7fff48fc5cd1dbdb8f6362c99f,A Neural Approach to Blind Motion Deblurring,"A Neural Approach to Blind Motion Deblurring +Ayan Chakrabarti +Toyota Technological Institute at Chicago"
+a55ec6bade29f23f8cb1337edf417b2da2f48695,Deep Asymmetric Networks with a Set of Node-wise Variant Activation Functions,"Deep Asymmetric Networks with a Set of +Node-wise Variant Activation Functions +Jinhyeok Jang, Hyunjoong Cho, Jaehong Kim, Jaeyeon Lee, and Seungjoon Yang"
+a5be204b71d1daaf6897270f2373d1a5e37c3010,Improving Spatiotemporal Self-supervision by Deep Reinforcement Learning,"Improving Spatiotemporal Self-Supervision +y Deep Reinforcement Learning +Uta B¨uchler(cid:63), Biagio Brattoli(cid:63), and Bj¨orn Ommer +Heidelberg University, HCI / IWR, Germany"
a56c1331750bf3ac33ee07004e083310a1e63ddc,Efficient Point-to-Subspace Query in ℓ1 with Application to Robust Object Instance Recognition,"Vol. xx, pp. x (cid:13) xxxx Society for Industrial and Applied Mathematics Efficient Point-to-Subspace Query in (cid:96)1 with Application to Robust Object Instance Recognition Ju Sun∗, Yuqian Zhang†, and John Wright‡"
+a5006c29b0609296b5c1368ff1113eeb12b119ad,In-flight launch of unmanned aerial vehicles,"In-flight launch of unmanned aerial vehicles +Niels Nauwynck, Haris Balta, Geert De Cubber, and Hichem Sahli"
+a59e338fec32adee012e31cdb0513ec20d6c8232,Phase Retrieval Under a Generative Prior,"Phase Retrieval Under a Generative Prior +Paul Hand∗, Oscar Leong∗, and Vladislav Voroninski† +July 12, 2018"
+a565990d6b176bf9c82eec9354b0936fb141e631,Scheduling on Heterogeneous Multi-core Processors Using Stable Matching Algorithm,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 7, No. 6, 2016 +Scheduling on Heterogeneous Multi-core Processors +Using Stable Matching Algorithm +Muhammad Rehman Zafar +Department of Computer Science +Bahria University +Islamabad, Pakistan +Muhammad Asfand-e-Yar +Department of Computer Science +Bahria University +Islamabad, Pakistan"
a54e0f2983e0b5af6eaafd4d3467b655a3de52f4,Face Recognition Using Convolution Filters and Neural Networks,"Face Recognition Using Convolution Filters and Neural Networks V. Rihani @@ -4174,16 +14231,26 @@ Physics Department, CFSL, Sec-36, Chandigarh - 160036 to: (a) potential method"
+a52d6daf72281521ee99dabd82cd80093e8d6f4a,Person re-identification across different datasets with multi-task learning,"Person re-identification across different datasets +with multi-task learning +Matthieu Ospici, Antoine Cecchi +Atos BDS R&D"
a5625cfe16d72bd00e987857d68eb4d8fc3ce4fb,VFSC: A Very Fast Sparse Clustering to Cluster Faces from Videos,"VFSC: A Very Fast Sparse Clustering to Cluster Faces from Videos Dinh-Luan Nguyen, Minh-Triet Tran University of Science, VNU-HCMC, Ho Chi Minh city, Vietnam"
+a5da6a6d4243a89e974a6467cb5c6df6d914a946,Static and Dynamic Approaches for Pain Intensity Estimation using Facial Expressions,
a546fd229f99d7fe3cf634234e04bae920a2ec33,Fast Fight Detection,"RESEARCH ARTICLE Fast Fight Detection Ismael Serrano Gracia1*, Oscar Deniz Suarez1*, Gloria Bueno Garcia1*, Tae-Kyun Kim2 Department of Systems Engineering and Automation, E.T.S.I. Industriales, Ciudad Real, Castilla-La Mancha, Spain, 2 Department of Electrical and Electronic Engineering, Imperial College, London, UK * (ISG); (ODS); (GBG)"
+a5531b5626c1ee3b6f9aed281a98338439d06d12,Multichannel Attention Network for Analyzing Visual Behavior in Public Speaking,"Multichannel Attention Network for Analyzing +Visual Behavior in Public Speaking +Rahul Sharma, Tanaya Guha and Gaurav Sharma +IIT Kanpur +{rahus, tanaya,"
a5ae7fe2bb268adf0c1cd8e3377f478fca5e4529,Exemplar Hidden Markov Models for classification of facial expressions in videos,"Exemplar Hidden Markov Models for Classification of Facial Expressions in Videos Univ. of California San Diego @@ -4196,6 +14263,9 @@ California, USA National University Australia California, USA"
+a577eefb31ba63baa087f321537b0be2784ec013,Security Event Recognition for Visual Surveillance,"Security Event Recognition for Visual Surveillance +Michael Ying Yang∗, Senior Member, IEEE, Wentong Liao, Chun Yang, Yanpeng Cao, Member, IEEE and Bodo +Rosenhahn Member, IEEE"
a55efc4a6f273c5895b5e4c5009eabf8e5ed0d6a,"Continuous Head Movement Estimator for Driver Assistance: Issues, Algorithms, and On-Road Evaluations","Continuous Head Movement Estimator for Driver Assistance: Issues, Algorithms, nd On-Road Evaluations @@ -4214,6 +14284,8 @@ University of California at Berkeley Technical Report No. UCB/EECS-2016-97 http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-97.html May 13, 2016"
+a52d6c456122007f10c90989a1e81dc8e1c599da,Query-Adaptive Image Search With Hash Codes,"Query-Adaptive Image Search with Hash Codes +Yu-Gang Jiang, Jun Wang, Member, IEEE, Xiangyang Xue, Member, IEEE, Shih-Fu Chang, Fellow, IEEE"
a5a44a32a91474f00a3cda671a802e87c899fbb4,Moments in Time Dataset: one million videos for event understanding,"Moments in Time Dataset: one million videos for event understanding Mathew Monfort, Bolei Zhou, Sarah Adel Bargal, @@ -4227,6 +14299,76 @@ Technical University of Munich, Munich, 2KTH Royal Institute of Technology, Stoc Polytechnic University of Catalonia, Barcelona, 4National Taiwan University, Taipei, 5University of Tokyo, Tokyo, 6National Institute of Informatics, Tokyo"
bd07d1f68486052b7e4429dccecdb8deab1924db,Face representation under different illumination conditions,
+bd96c3af9c433b4eaf95c8a28f072e1b0fc2de1a,A Study on Facial Expression Recognition Model using an Adaptive Learning Capability,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+bdb74f1b633b2c48d5e9d101e09bad2db8d68be6,Chapter 1 . Medical Image Annotation (,"Chapter 1 +Medical image annotation 1 +Thanks to the rapid development of modern medical devices and the use of +digital systems, more and more medical images are being generated. This +has lead to an increase in the demand for automatic methods to index, com- +pare, analyze and annotate them. Until 2005, automatic categorization of +medical images was often restricted to a small number of classes. The Image- +CLEF medical image annotation challenge was born in this scenario, propos- +ing a task reflecting real life constraints of content based image classification +in medical applications. In this chapter we report about our experience first +s participants, then as co-organizers. This research activity started in 2007, +supported by a 1-year IM2 fellowship. By leveraging over the initial IM2 +support, in 2008 a 4-year project started (EMMA, Enhanced Multimodal +Medical data Access), sponsored by the Halser foundation. Since 2009, B. +Caputo has been an ImageCLEF task organizers, respectively for the medi- +al annotation and robot vision tasks. Since 2013, she is main organizer of +ImageCLEF. +Introduction +This chapter presents the algorithms and results of the Idiap team partici- +pation to the ImageCLEFmed annotation task in 2007, 2008 and 2009. The"
+bdbf414a2059d542f501ad9b1d21eacc9831082b,Two-Layer Mixture Network Ensemble for Apparel Attributes Classification,"Two-Layer Mixture Network Ensemble for Apparel +Attributes Classification +Tianqi Han, Zhihui Fu, and Hongyu Li* +AI Lab, ZhongAn Information Technology Service Co., Ltd. +Shanghai, China"
+bdf64dd341925ea7b9b3abbb49cab3cf978f8e21,Probable Etiopathogenesis (samprapti) of Autism in Frame of Ayurveda in Relation to Intense World Theory,"Global J Res. Med. Plants & Indigen. Med. | Volume 2, Issue 6 | June 2013 | 448–459 +ISSN 2277-4289 | www.gjrmi.com | International, Peer reviewed, Open access, Monthly Online Journal +Review article +PROBABLE ETIOPATHOGENESIS (SAMPRAPTI) OF AUTISM IN FRAME +OF AYURVEDA IN RELATION TO INTENSE WORLD THEORY +Yadav Deepmala1*, Behera Banshidhar2, Kumar Abhimanyu3 +Asst.Professor, Dept. of Kaumarbhritya, M.S.M. Institute of Ayurveda, Khanpur kalan, Haryana-131305, +India +Lecturer, Dept. of Dravyaguna, Gaur Brahman Ayurvedic College, Rohtak, Haryana – 124001, India +Director, All India Institute of Ayurveda, Gautampuri, Mathura road, Sarita Vihar, New Delhi-110076, +India +*Corresponding Author: E-mail: Mob +919414893921, +919414458895 +Received: 10/05/2013; Revised: 26/05/2013; Accepted: 30/05/2013"
+bda61e9bcf02d02f61882790dbbdad8e4fed0986,Face Recognition through Combined SVD and LBP Features,"Face Recognition through Combined SVD and LBP +International Journal of Computer Applications (0975 – 8887) +Volume 88 – No.9, February 2014 +Features +Rahul Kumar Mittal +M.Tech. Scholar +BGIET, Sangrur +Punjab (India) +Anupam Garg +Assistant Professor +BGIET, Sangrur +Punjab (India)"
bd13f50b8997d0733169ceba39b6eb1bda3eb1aa,Occlusion Coherence: Detecting and Localizing Occluded Faces,"Occlusion Coherence: Detecting and Localizing Occluded Faces Golnaz Ghiasi, Charless C. Fowlkes University of California at Irvine, Irvine, CA 92697"
@@ -4236,6 +14378,18 @@ Ritesh Bora, V.A.Chakkarvar Computer science and Engineering Department, Government College of Engineering, Aurangabad [Autonomous] Station Road, Aurangabad, Maharashtra, India."
+bd17d6ba5525dec8762dbaacf6cc3e0cc3f5ff90,Necst: Neural Joint Source-channel Coding,"Under review as a conference paper at ICLR 2019 +NECST: NEURAL JOINT SOURCE-CHANNEL CODING +Anonymous authors +Paper under double-blind review"
+bd88bb2e4f351352d88ee7375af834360e223498,A Multi - camera video data set for research on High - Definition surveillance,"HDA dataset - DRAFT +A Multi-camera video data set for research on +High-Definition surveillance +Athira Nambiar, Matteo Taiana, Dario Figueira, +Jacinto Nascimento and Alexandre Bernardino +Computer and Robot Vision Lab, Institute for Systems and Robotics +Instituto Superior Técnico +Lisbon, Portugal"
bd2d7c7f0145028e85c102fe52655c2b6c26aeb5,Attribute-based People Search: Lessons Learnt from a Practical Surveillance System,"Attribute-based People Search: Lessons Learnt from a Practical Surveillance System Rogerio Feris @@ -4247,8 +14401,18 @@ Lisa Brown IBM Watson Sharath Pankanti IBM Watson"
-bdbba95e5abc543981fb557f21e3e6551a563b45,Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks,"International Journal of Computational Intelligence and Applications -Vol. 17, No. 2 (2018) 1850008 (15 pages) +bd0a6bea1985ece3388b1dae47fa76aab3562d6d,One Deep Music Representation to Rule Them All? : A comparative analysis of different representation learning strategies,"Noname manuscript No. +(will be inserted by the editor) +One Deep Music Representation to Rule Them All? +A comparative analysis of different representation learning strategies +Jaehun Kim · Juli´an Urbano · +Cynthia C. S. Liem · Alan Hanjalic +Received: date / Accepted: date"
+bd2752acf6821282655933d1946f43bb4ac5e901,Flexible Network Binarization with Layer-wise Priority,"Flexible Network Binarization with Layer-wise Priority +Lixue Zhuang*, Yi Xu*, Bingbing Ni*, Hongteng Xu† +Shanghai Jiao Tong University*, Duke University† +{qingliang, xuyi,"
+bdbba95e5abc543981fb557f21e3e6551a563b45,Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks,"Vol. 17, No. 2 (2018) 1850008 (15 pages) #.c The Author(s) DOI: 10.1142/S1469026818500086 Speeding up the Hyperparameter Optimization of Deep @@ -4266,7 +14430,8 @@ parameters before the learning process can begin. However, with modern algorithm evaluation of a given hyperparameter setting can take a considerable amount of time and the search space is often very high-dimensional. We suggest using a lower-dimensional represen- tation of the original data to quickly identify promising areas in the hyperparameter space. This -information can then be used to initialize the optimization algorithm for the original, higher-"
+information can then be used to initialize the optimization algorithm for the original, higher- +dimensional data. We compare this approach with the standard procedure of optimizing the"
d1dfdc107fa5f2c4820570e369cda10ab1661b87,Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation,"Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation Huaizu Jiang1 @@ -4277,6 +14442,15 @@ Erik Learned-Miller1 Jan Kautz2 UMass Amherst NVIDIA 3UC Merced"
+d19df82c5ea644937bf182fabdc0e36e78ea6867,Emotional Facial Expression Recognition from Two Different Feature Domains,"EMOTIONAL FACIAL EXPRESSION RECOGNITION FROM TWO +DIFFERENT FEATURE DOMAINS +Jonghwa Kim and Frank Jung +Institute of Computer Science, University of Augsburg, Germany +Keywords:"
+d168c2bd29fcad2083586430dd76f54da69bc8a6,Person Re-Identification by Iterative Re-Weighted Sparse Ranking,"Person Re-Identification by Iterative +Re-Weighted Sparse Ranking +Giuseppe Lisanti, Iacopo Masi, Andrew D. Bagdanov, Member, IEEE, and +Alberto Del Bimbo, Member, IEEE"
d1dae2993bdbb2667d1439ff538ac928c0a593dc,Gamma Correction Technique Based Feature Extraction for Face Recognition System,"International Journal of Computational Intelligence and Informatics, Vol. 3: No. 1, April - June 2013 Gamma Correction Technique Based Feature Extraction for Face Recognition System @@ -4288,6 +14462,72 @@ Electronics and Communication Engineering K S Rangasamy College of Technology Tamilnadu, India Tamilnadu, India"
+d1dd0c714950cbd89f76ec6b039201eadf74cade,Person Re-identification Using Robust Brightness Transfer Functions Based on Multiple Detections,"Person Re-identification Using Robust +Brightness Transfer Functions Based +on Multiple Detections +Amran Bhuiyan(B), Behzad Mirmahboub, Alessandro Perina, +nd Vittorio Murino +Pattern Analysis and Computer Vision (PAVIS), +Istituto Italiano di Tecnologia, Genova, Italy"
+d1503151b39038a87acbd9ecce073ddc211a597d,Efficient Semantic Segmentation using Gradual Grouping,"Efficient Semantic Segmentation using Gradual Grouping +Nikitha Vallurupalli1, Sriharsha Annamaneni1, Girish Varma1, +C V Jawahar1, Manu Mathew2, Soyeb Nagori2 +Center for Visual Information Technology, Kohli Center on Intelligent Systems, IIIT-Hyderabad, India +Texas Instruments, Bangalore, India"
+d1a0425f764ce8847d20d278e4a4267c8258c4dc,3D Human Pose Estimation with Siamese Equivariant Embedding,"D Human Pose Estimation with Siamese Equivariant +Embedding +M´arton V´egesa,∗, Viktor Vargaa, Andr´as L˝orincza +E¨otv¨os Lor´and University, Budapest, Hungary"
+d1295a93346411bb833305acc0e092c9e3b2eff1,The eMPaThy iMBalance hyPoThesis oF aUTisM : a TheoReTical aPPRoach To cogniTiVe and eMoTional eMPaThy in aUTisTic deVeloPMenT,"the Psychological record, 2009, 59, 489-510 +The eMPaThy iMBalance hyPoThesis oF aUTisM: +TheoReTical aPPRoach To cogniTiVe and +eMoTional eMPaThy in aUTisTic deVeloPMenT +Adam Smith +Dundee, Scotland +There has been a widely held belief that people with autism spectrum disorders +lack empathy. This article examines the empathy imbalance hypothesis (EIH) of +utism. According to this account, people with autism have a deficit of cognitive +empathy but a surfeit of emotional empathy. The behavioral characteristics of +utism might be generated by this imbalance and a susceptibility to empathic +overarousal. The EIH builds on the theory of mind account and provides an +lternative to the extreme-male-brain theory of autism. Empathy surfeit is a re- +urrent theme in autistic narratives, and empirical evidence for the EIH is grow- +ing. A modification of the pictorial emotional Stroop paradigm could facilitate +n experimental test of the EIH. +Autism is a pervasive developmental disorder that continues to fascinate +researchers, challenge clinicians, and distress affected families. empathy +is a set of processes and outcomes at the heart of human social behavior. +Fascination with autism is often interwoven with the study of empathy because"
+d1e66107eb084ea0ef5a97f3363f8787b8df91ed,Max-Margin Regularization for Reducing Accidentalness in Chamfer Matching,"Max-margin Regularization for Reducing +Accidentalness in Chamfer Matching +Angela Eigenstetter*, Pradeep Yarlagadda* and Bj¨orn Ommer +Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany"
+d12c343e60f9cc1a0c6c94c138f38e6bffe22001,Diverse Sampling for Self-Supervised Learning of Semantic Segmentation,"Diverse Sampling for Self-Supervised Learning of Semantic Segmentation +Mohammadreza Mostajabi ∗ +Nicholas Kolkin ∗ +Toyota Technological Institute at Chicago +{mostajabi, nick.kolkin, +Gregory Shakhnarovich"
+d1c103c63d930d3ae7397618f486117a48e35f16,Does gaze direction modulate facial expression processing in children with autism spectrum disorder?,"BIROn - Birkbeck Institutional Research Online +Enabling open access to Birkbeck’s published research output +Does gaze direction modulate facial expression +processing in children with autism spectrum disorder? +Journal Article +http://eprints.bbk.ac.uk/2561 +Version: Accepted (Refereed) +Citation: +© 2009 Wiley Blackwell +Publisher version +______________________________________________________________ +All articles available through Birkbeck ePrints are protected by intellectual property law, including +opyright law. Any use made of the contents should comply with the relevant law. +______________________________________________________________ +Akechi, H.; Senju, A.; Kikuchi, Y.; Tojo, Y.; Osanai, H.; Hasegawa, T. +(2009) +Does gaze direction modulate facial expression processing in children +with autism spectrum disorder? +Deposit Guide +Contact:"
d1f58798db460996501f224fff6cceada08f59f9,Transferrable Representations for Visual Recognition,"Transferrable Representations for Visual Recognition Jeffrey Donahue Electrical Engineering and Computer Sciences @@ -4295,7 +14535,47 @@ University of California at Berkeley Technical Report No. UCB/EECS-2017-106 http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-106.html May 14, 2017"
-d1a43737ca8be02d65684cf64ab2331f66947207,IJB–S: IARPA Janus Surveillance Video Benchmark,"IJB–S: IARPA Janus Surveillance Video Benchmark (cid:3) +d16c8ac2d194a6e862be0d1c4edf1ca2cdf5dc18,Robust Subspace Approaches to Visual Learning and Recognition DOCTORAL,"Univerza v Ljubljani +Fakulteta za raˇcunalniˇstvo in informatiko +Danijel Skoˇcaj +Robustni pristopi k vizualnemu uˇcenju +in razpoznavanju na osnovi podprostorov +DOKTORSKA DISERTACIJA +Ljubljana, 2003 +Mentor: prof. dr. Aleˇs Leonardis"
+d1c091bf9402f1caf13892a3fae39326507401be,Speeding up Semantic Segmentation for Autonomous Driving,"Speeding up Semantic Segmentation for Autonomous +Driving +Michael Treml ∗1, José Arjona-Medina∗1, Thomas Unterthiner∗1, +Rupesh Durgesh2, Felix Friedmann2, Peter Schuberth2, +Andreas Mayr1, Martin Heusel1, Markus Hofmarcher1, Michael Widrich1, +Bernhard Nessler1, Sepp Hochreiter1 +Institute of Bioinformatics, Johannes Kepler University Linz, Austria +Audi Electronics Venture GmbH, Germany +{treml, arjona, unterthiner, nessler, +{rupesh.durgesh, felix.friedmann,"
+d102f18d319d9545588075010f5d10b1ff77f967,Effects of Degradations on Deep Neural Network Architectures,"Effects of Degradations on Deep Neural Network +Architectures +Prasun Roy∗, Subhankar Ghosh∗, Saumik Bhattacharya∗ and Umapada Pal +Indian Statistical Institute Kolkata, India - 700108"
+d170adb2c508edaedb731ada8cb995172a839a1f,Cascade of Boolean detector combinations,"Mahkonen et al. EURASIP Journal on Image and Video +Processing (2018) 2018:61 +https://doi.org/10.1186/s13640-018-0303-9 +EURASIP Journal on Image +nd Video Processing +RESEARCH +Open Access +Cascade of Boolean detector +ombinations +Katariina Mahkonen* +, Tuomas Virtanen and Joni Kämäräinen"
+d1d4c49e764a200bc90113b0ba9c34664d0f9462,"Memo No . 082 May 10 , 2018 Scene Graph Parsing as Dependency Parsing","CBMM Memo No. 082 +May 10, 2018 +Scene Graph Parsing as Dependency Parsing +Yu-Siang Wang1, Chenxi Liu2, Xiaohui Zeng3, Alan Yuille2 +: National Taiwan University +: Johns Hopkins University +: Hong Kong University of Science and Technology"
+d1a43737ca8be02d65684cf64ab2331f66947207,IJB – S : IARPA Janus Surveillance Video Benchmark ∗,"IJB–S: IARPA Janus Surveillance Video Benchmark (cid:3) Nathan D. Kalka y Stephen Elliott z Brianna Maze y @@ -4326,10 +14606,92 @@ Optimization of Accuracy-Diversity Trade off S¨ureyya ¨Oz¨o˘g¨ur Aky¨uz · Terry Windeatt · Raymond Smith Received: date / Accepted: date"
+d1bfb6a9182e5712d8aef46b2fe93ef4ad4fe705,Local Color Contrastive Descriptor for Image Classification,"Local Color Contrastive Descriptor for Image +Classification +Sheng Guo, Student Member, IEEE, Weilin Huang, Member, IEEE, and Yu Qiao, Senior Member, IEEE"
+d1c0592f4f9f0ff2e14e0591d87539e5141b7361,Mobile Emotion Recognition Engine,"Mobile Emotion Recognition Engine +Alberto Scicali1"
+d138270d3c06e85fa2c3da6f953818da4b72313a,An Analytical Framework for Estimating Scale-Out and Scale-Up Power Efficiency of Heterogeneous Manycores,"An Analytical Framework for Estimating +Scale-Out and Scale-Up Power Efficiency +of Heterogeneous Manycores +Jun Ma, Guihai Yan, Member, IEEE, Yinhe Han, Member, IEEE, and Xiaowei Li, Senior Member, IEEE"
d1d6f1d64a04af9c2e1bdd74e72bd3ffac329576,Neural Face Editing with Intrinsic Image Disentangling,"Neural Face Editing with Intrinsic Image Disentangling Zhixin Shu1 Ersin Yumer2 Sunil Hadap2 Kalyan Sunkavalli2 Eli Shechtman 2 Dimitris Samaras1,3 Stony Brook University 2Adobe Research 3 CentraleSup´elec, Universit´e Paris-Saclay"
+d1dc5a8b4d13d2c51eec7bcb29d08f471d3b65dc,Adversarially Occluded Samples for Person Re-identification ( Supplementary Material ) 1 . Improvement of Ranking Results,"Adversarially Occluded Samples for Person Re-identification +Houjing Huang 1 +Dangwei Li 1 +Zhang Zhang 1 +Xiaotang Chen 1 +Kaiqi Huang 1 +CRIPAC & NLPR, CASIA 2 University of Chinese Academy of Sciences +CAS Center for Excellence in Brain Science and Intelligence Technology +{houjing.huang, dangwei.li, zzhang, xtchen,"
+d198b5bc5eae22f7a788729c0ea15b6b60b62f36,Transfer Learning for Estimating Causal Effects using Neural Networks,"Transfer Learning for Estimating Causal Effects +using Neural Networks +Sören R. Künzel∗ +UC Berkeley +Varsha Ramakrishnan +UC Berkeley +Bradly C. Stadie∗ +UC Berkeley +Nikita Vemuri +UC Berkeley +Jasjeet S. Sekhon +UC Berkeley +Pieter Abbeel +UC Berkeley"
+d6dab84451254d7fbb5b9e1d40a7d2a92dec13b3,Enhanced Local Binary Patterns for Automatic Face Recognition,"ENHANCED LOCAL BINARY PATTERNS FOR AUTOMATIC FACE RECOGNITION +Pavel Kr´al1 +, Anton´ın Vrba1 +Dept. of Computer Science & Engineering 2New Technologies for the Information Society +Faculty of Applied Sciences +University of West Bohemia +Plzeˇn, Czech Republic +Faculty of Applied Sciences +University of West Bohemia +Plzeˇn, Czech Republic"
+d6255a0db6f8f157c5c901d758c7a5f36416ab51,Face Recognition Using Gabor Wavelet Transform,"FACE RECOGNITION USING GABOR WAVELET TRANSFORM +A THESIS SUBMITTED TO +THE GRADUATE SCHOOL OF NATURAL SCIENCES +THE MIDDLE EAST TECHNICAL UNIVERSITY +BURCU KEPENEKCI +IN PARTIAL FULLFILMENT OF THE REQUIREMENTS FOR THE DEGREE +MASTER OF SCIENCE +THE DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING +SEPTEMBER 2001"
d69df51cff3d6b9b0625acdcbea27cd2bbf4b9c0,Robust Remote Heart Rate Determination for E-Rehabilitation - A Method that Overcomes Motion and Intensity Artefacts,
+d64b24e9b01f4681d92fc29f36e46d94db7b8bb0,Avoiding Extraverts: Pathogen Concern Downregulates Preferences for Extraverted Faces,"See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/305793723 +Avoiding Extraverts: Pathogen Concern +Downregulates Preferences for Extraverted +Faces +Article · August 2016 +DOI: 10.1007/s40806-016-0064-6 +CITATIONS +authors, including: +Mitch Brown +University of Southern Mississippi +6 PUBLICATIONS 5 CITATIONS +SEE PROFILE +READS +Some of the authors of this publication are also working on these related projects: +Limbal Rings View project +Morality and Mate Preferences View project +All content following this page was uploaded by Mitch Brown on 06 December 2016. +The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the original document +nd are linked to publications on ResearchGate, letting you access and read them immediately."
+d660abfbe5f84c1c49f1e7174eb166b8b23e53c4,"AMIGOS: A dataset for Mood, personality and affect research on Individuals and GrOupS","AMIGOS: A dataset for Mood, personality and +ffect research on Individuals and GrOupS +Nicu Sebe, Senior Member, IEEE, and Ioannis Patras, Senior Member, IEEE"
+d689cdb4e535be040316722229e6362de6617f9e,Geometric Deep Particle Filter for Motorcycle Tracking: Development of Intelligent Traffic System in Jakarta,"INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 8, NO. 1, MARCH 2015 +GEOMETRIC DEEP PARTICLE FILTER FOR MOTORCYCLE +TRACKING: DEVELOPMENT OF INTELLIGENT TRAFFIC +SYSTEM IN JAKARTA +Alexander A S Gunawan1, Wisnu Jatmiko2 +Bina Nusantara University, Mathematics Department, +School of Computer Science, Jakarta, Indonesia +Faculty of Computer Science,Universitas Indonesia, Depok, Indonesia +Submitted: Oct. 4, 2014 Accepted: Jan. 20, 2015 Published: Mar. 1, 2015"
d61578468d267c2d50672077918c1cda9b91429b,Face Image Retrieval Using Pose Specific Set Sparse Feature Representation,"Abdul Afeef N et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.9, September- 2014, pg. 314-323 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing @@ -4342,6 +14704,21 @@ Set Sparse Feature Representation Department of Computer Science, Viswajyothi College of Engineering and Technology Kerala, India Assistant Professor of Computer Science, Viswajyothi College of Engineering and Technology Kerala, India Abdul Afeef N1, Sebastian George2"
+d6eda0c16d226976506396653d14044c185eaf3e,Toward Multimodal Image-to-Image Translation,"Toward Multimodal Image-to-Image Translation +Jun-Yan Zhu +UC Berkeley +Richard Zhang +UC Berkeley +Deepak Pathak +UC Berkeley +Trevor Darrell +UC Berkeley +Alexei A. Efros +UC Berkeley +Oliver Wang +Adobe Research +Eli Shechtman +Adobe Research"
d687fa99586a9ad229284229f20a157ba2d41aea,Face Recognition Based on Wavelet Packet Coefficients and Radial Basis Function Neural Networks,"Journal of Intelligent Learning Systems and Applications, 2013, 5, 115-122 http://dx.doi.org/10.4236/jilsa.2013.52013 Published Online May 2013 (http://www.scirp.org/journal/jilsa) Face Recognition Based on Wavelet Packet Coefficients @@ -4354,6 +14731,18 @@ Received December 12th, 2012; revised April 19th, 2013; accepted April 26th, 201 Copyright © 2013 Thangairulappan Kathirvalavakumar, Jeyasingh Jebakumari Beulah Vasanthi. This is an open access article dis- tributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any me- dium, provided the original work is properly cited."
+d69e644016042d1032995bc9f51e2d72a1c1cd93,Beyond Trees: Adopting MITI to Learn Rules and Ensemble Classifiers for Multi-Instance Data,"Beyond Trees: Adopting MITI to Learn Rules +nd Ensemble Classifiers for Multi-instance Data +Luke Bjerring and Eibe Frank +Department of Computer Science, University of Waikato"
+d6efd1b7b39d91b067488e0c4bf800ce3e3704d8,Visual Analysis of Pedestrian Motion,"Visual Analysis of Pedestrian Motion +PRS Transfer Report +Supervised by Dr Ian Reid +David Ellis +St John’s College +Robotics Research Group +Department of Engineering Science +Michaelmas 2009"
d6a9ea9b40a7377c91c705f4c7f206a669a9eea2,Visual Representations for Fine-grained Categorization,"Visual Representations for Fine-grained Categorization Ning Zhang @@ -4371,6 +14760,32 @@ Computer Vision Center Autonomous University of Barcelona Barcelona, Spain Editor: Radeva Petia, Pujol Oriol"
+d665213b59f2460faf171d3b03ecd9c96d606883,A Multimodal Nonverbal Human-robot Communication System,"VI International Conference on Computational Bioengineering +ICCB 2015 +M. Cerrolaza and S.Oller (Eds) +A MULTIMODAL NONVERBAL HUMAN-ROBOT COMMUNICATION +SYSTEM +S. SALEH†*, M. SAHU†, Z. ZAFAR† AND K. BERNS† +Robotics Research Lab. - Dept. of Computer Science +University of Kaiserslautern +Kaiserslautern, Germany +web page: http://agrosy.cs.uni-kl.de +e-mail: {saleh, sahu, zafar, +* Dept. of Computer Science, University of Basrah +Basrah, Iraq +Key words: HRI, Facial Expression Recognition, Nonverbal Communication"
+d6683c74c17d4fcc48ce3d9df9df6aea38fd4923,Learning Instance Weights in Multi-Instance Learning,"Learning Instance Weights in +Multi-Instance Learning +James Foulds +This thesis is submitted in partial fulfillment of +the requirements for the degree of +Master of Science +t the +University of Waikato. +Department of Computer Science +Hamilton, New Zealand +February 2007 - February 2008 +(cid:13) 2008 James Foulds"
d65b82b862cf1dbba3dee6541358f69849004f30,2.5D Elastic graph matching,"Contents lists available at ScienceDirect j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c v i u .5D Elastic graph matching @@ -4397,6 +14812,19 @@ d6bfa9026a563ca109d088bdb0252ccf33b76bc6,Unsupervised Temporal Segmentation of F Abhishek Kar Advisors: Dr. Amitabha Mukerjee & Dr. Prithwijit Guha Department of Computer Science and Engineering, IIT Kanpur"
+d6adb54f5d25dda71d157b5d574c70c732fdd722,Feature Map Filtering: Improving Visual Place Recognition with Convolutional Calibration,"Pre-print of article that will appear in Proceedings of the Australasian Conference on Robotics and Automation +018. +Please cite this paper as: +Stephen Hausler, Adam Jacobson, and Michael Milford. Feature Map Filtering: Improving Visual Place Recognition +with Convolutional Calibration. Proceedings of Australasian Conference on Robotics and Automation, 2018. +ibtex: +uthor = {Hausler, Stephen and Jacobson, Adam and Milford, Michael}, +title = {Feature Map Filtering: Improving Visual Place Recognition with Convolutional Calibration}, +ooktitle = {Proceedings of Australasian Conference on Robotics and Automation (ACRA)}, +year = {2018},"
+d6dfe23018172d29c36746d24f73bf86e1aaa0a6,Searching Scenes by Abstracting Things,
+d65bcbcddec932480c434f0ffa778e429cdd4ee7,Periocular biometrics: When iris recognition fails,"Periocular Biometrics: When Iris Recognition Fails +Samarth Bharadwaj, Himanshu S. Bhatt, Mayank Vatsa and Richa Singh"
d6c7092111a8619ed7a6b01b00c5f75949f137bf,A Novel Feature Extraction Technique for Facial Expression Recognition,"A Novel Feature Extraction Technique for Facial Expression Recognition *Mohammad Shahidul Islam1, Surapong Auwatanamongkol2 @@ -4406,12 +14834,92 @@ Bangkok, 10240, Thailand Department of Computer Science, School of Applied Statistics, National Institute of Development Administration, Bangkok, 10240, Thailand"
+d6ceebb0cde7fb0fbe916472d7b613a2d7d2e1e6,Do faces capture the attention of individuals with Williams syndrome or autism? Evidence from tracking eye movements.,"Do faces capture the attention of individuals with Williams syndrome +or Autism? Evidence from tracking eye movements +Deborah M Riby & Peter J B Hancock +http://dx.doi.org/10.1007/s10803-008-0641-z"
+d65f11b44180d9997ad5ba6e6970fe4874891f4f,Unobtrusive emotion sensing and interpretation in smart environment,"Journal of Ambient Intelligence and Smart Environments 7 (2015) 59–83 +DOI 10.3233/AIS-140298 +IOS Press +Unobtrusive emotion sensing and +interpretation in smart environment +Oleg Starostenko *, Ximena Cortés, J. Afredo Sánchez and Vicente Alarcon-Aquino +Department of Computing, Electronics and Mechatronics, Universidad de las Americas Puebla, Cholula, +Pue. 72810, Mexico"
+d6b514a68abff3ab14af9fc0152cd5b28bd0192c,Instance Segmentation by Deep Coloring,"JULY 2018 +Instance Segmentation by Deep Coloring +Victor Kulikov, Victor Yurchenko, and Victor Lempitsky"
+d64c362b631f0c94b22952e2d0860054f0854358,Offline Handwritten Devanagari Numeral Recognition Using Artificial Neural Network,"International Journals of Advanced Research in +Computer Science and Software Engineering +ISSN: 2277-128X (Volume-7, Issue-8) +Research Article +August +Offline Handwritten Devanagari Numeral Recognition +Using Artificial Neural Network +P E Ajmire +Associate Professor & Head, Department of Computer Science & Application, G. S. Science, Arts & Commerce +College, Khamgaon, Maharashtra, India +DOI: 10.23956/ijarcsse/V7I7/0157"
+d623428f02e80a689eb58d022237daeae2ae7b9c,Guided depth upsampling for precise mapping of urban environments,"Guided Depth Upsampling for Precise Mapping of Urban Environments +Sascha Wirges1, Bj¨orn Roxin2 , Eike Rehder2, Tilman K¨uhner1 and Martin Lauer2"
+d680cfe583fe61e49656cc7b9dbd480c6159cf0b,Pedestrian Detection in Far-Infrared Daytime Images Using a Hierarchical Codebook of SURF,"Sensors 2015, 15, 8570-8594; doi:10.3390/s150408570 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +Pedestrian Detection in Far-Infrared Daytime Images Using a +Hierarchical Codebook of SURF +Bassem Besbes 1, Alexandrina Rogozan 2,*, Adela-Maria Rus 2,3,*, Abdelaziz Bensrhair 2 +nd Alberto Broggi 4 +Diotasoft, 15 Boulevard Emile Baudot, Massy 91300, France; E-Mail: +LITIS Laboratory, National Institute of Applied Sciences, 76801 Saint-Etienne-du-Rouvray Cedex, +France; E-Mail: +Faculty of Computer Science, Babes-Bolyai University, Kogalniceanu no.1, +Cluj-Napoca RO-400084, Romania +Dipartimento di Ingegneria dell’ Informazione, Universita di Parma, Parco Area delle Scienze, +Parma 181/a 43124, Italy; E-Mail: +* Authors to whom correspondence should be addressed; E-Mails: (A.R.); +(A.-M.R.); Tel.: +33-2-3295-6670 (A.R.); +40-2-6440-5300 (A.-M.R.). +Academic Editor: Felipe Jimenez"
+d69b542b3714b5e90c384d39b5ab0c4bf9dd5375,Geometry and Probability for Motion and Action,"IN PARTNERSHIP WITH: +Institut polytechnique de +Grenoble +Université Pierre Mendes-France +(Grenoble) +Université Joseph Fourier +(Grenoble) +Activity Report 2012 +Project-Team E-MOTION +Geometry and Probability for Motion and +Action +IN COLLABORATION WITH: Laboratoire d’Informatique de Grenoble (LIG) +RESEARCH CENTER +Grenoble - Rhône-Alpes +THEME +Robotics"
+d69ef8b5658fabd0ac092fb2bfd0c9c109574dcc,Neural Class-Specific Regression for face verification,"Neural Class-Specific Regression for face +verification +Guanqun Cao, Alexandros Iosifidis, Moncef Gabbouj"
bcee40c25e8819955263b89a433c735f82755a03,Biologically Inspired Vision for Human-Robot Interaction,"Biologically inspired vision for human-robot interaction M. Saleiro, M. Farrajota, K. Terzi´c, S. Krishna, J.M.F. Rodrigues, and J.M.H. du Buf Vision Laboratory, LARSyS, University of the Algarve, 8005-139 Faro, Portugal, {masaleiro, mafarrajota, kterzic, jrodrig,"
+bcf7fb98ab0137d8a8b8a952819f5e13ec4648aa,Face Recognition with Single Sample per Class Using Cs-lbp and Gabor Filter,"Journal of Theoretical and Applied Information Technology +31st October 2014. Vol. 68 No.3 +© 2005 - 2014 JATIT & LLS. All rights reserved. +ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 +FACE RECOGNITION WITH SINGLE SAMPLE PER +CLASS USING CS-LBP AND GABOR FILTER +A.USHA RUBY, +DR.J.GEORGE CHELLIN CHANDRAN +Research Scholar, Department of CSE, Bharath University +Principal, CSI College of Engineering, Ketti +E-mail: ,"
+bc995457cf5f4b2b5ef62106856571588d7d70f2,Comparison of Maximum Likelihood and GAN-based training of Real NVPs,"Comparison of Maximum Likelihood and GAN-based training of Real NVPs +Ivo Danihelka 1 2 Balaji Lakshminarayanan 1 Benigno Uria 1 Daan Wierstra 1 Peter Dayan 3"
bc6de183cd8b2baeebafeefcf40be88468b04b74,Age Group Recognition using Human Facial Images,"Age Group Recognition using Human Facial Images International Journal of Computer Applications (0975 – 8887) Volume 126 – No.13, September 2015 @@ -4419,6 +14927,10 @@ Shailesh S. Kulkarni Dept. of Electronics and Telecommunication Government College of Engineering, Aurangabad, Maharashtra, India"
+bcf73131c2be397fa2105ac45df3ce1a55c07c2f,Automated markerless extraction of walking people using deformable contour models,"This is a preprint of an article published in Computer Animation and Virtual +Worlds, 15(3-4):399-406, 2004. +This journal may be found at: +http://www.interscience.wiley.com"
bcf19b964e7d1134d00332cf1acf1ee6184aff00,Trajectory-Set Feature for Action Recognition,"IEICE TRANS. INF. & SYST., VOL.E100–D, NO.8 AUGUST 2017 LETTER Trajectory-Set Feature for Action Recognition @@ -4439,8 +14951,103 @@ we take a hand-crafted approach that can be fused later with CNN outputs. Introduction Action recognition has been well studied in the computer"
+bc1fa3efa43dfb79f6f8243d29327c8ee06e8a97,Learning object classes with generic knowledge,"ETH Zurich, D-ITET, BIWI +Technical Report No 275 +Learning object classes with generic knowledge +Thomas Deselaers, Bogdan Alexe, and Vittorio Ferrari"
+bc843c35530e38396e8ba55b8891dbe8324054a8,Group Visual Sentiment Analysis,"Group Visual Sentiment Analysis +Zeshan Hussain, Tariq Patanam and Hardie Cate +June 6, 2016"
+bca09d92a25e5cc96df5c8d2eb87e2854cdc02b1,Pose Invariant 3 D Face Authentication based on Gaussian Fields Approach,"To the Graduate Council: +I am submitting herewith a thesis written by Venkat Rao Ayyagari entitled “Pose +Invariant 3D Face Authentication based on Gaussian Fields Approach”. I have examined +the final electronic copy of this thesis for form and content and recommend that it be +ccepted in partial fulfillment of the requirements for the degree of Master of Science, +with a major in Electrical Engineering. +Mongi A. Abidi +Major Professor +We have read this thesis and +recommend its acceptance: +Andreas Koschan +Seong G. Kong +Accepted for the Council: +Anne Mayhew +Vice Chancellor and Dean of +Graduate Studies +(Original signatures are on file with official student records.)"
bcc172a1051be261afacdd5313619881cbe0f676,A fast face clustering method for indexing applications on mobile phones,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE ICASSP 2017"
+bc7f431c4c5cecfc7bf95b2f0704d81469f23580,An Intelligent Apparel Recommendation System for Online Shopping Using Style Classification,"I J A B E R, Vol. 13, No. 2, (2015): 671-686 +AN INTELLIGENT APPAREL RECOMMENDATION +SYSTEM FOR ONLINE SHOPPING USING STYLE +CLASSIFICATION +C. Perkinian* and P. Vikkraman**"
+bc749f0e81eafe9e32d56336750782f45d82609d,Combination of Texture and Geometric Features for Age Estimation in Face Images,
+bc15e0ebe7ff84e090aa2d74d753d87906d497f7,The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments,"The Impact of Preprocessing on Deep +Representations for Iris Recognition on +Unconstrained Environments +Luiz A. Zanlorensi∗, Eduardo Luz†, Rayson Laroca∗, Alceu S. Britto Jr.‡, Luiz S. Oliveira∗, David Menotti∗ +Department of Informatics, Federal University of Paran´a (UFPR), Curitiba, PR, Brazil +Computing Department, Federal University of Ouro Preto (UFOP), Ouro Preto, MG, Brazil +Postgraduate Program in Informatics, Pontifical Catholic University of Paran´a (PUCPR), Curitiba, PR, Brazil"
+bc4e86b6d2d386805466b822a04ea0c015debfff,Robust 3D Face Recognition from Expression Categorisation,"Cook, Jamie A and Cox, Mark and Chandran, Vinod and Sridharan, +Sridha (2007) Robust 3D Face Recognition from Expression +Categorisation. In Proceedings International Conference on Biometrics +642, pages pp. 271-280, Seoul, Korea. +This is the author-manuscript version of this work - accessed from +http://eprints.qut.edu.au +Copyright 2007 Springer"
+bca52740ba679b67a508894e68a0e52f6bf62079,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+bc4537bc5834b41a631d9a807500d199b438fb27,Perceptual Integration Deficits in Autism Spectrum Disorders Are Associated with Reduced Interhemispheric Gamma-Band Coherence.,"6352 • The Journal of Neuroscience, December 16, 2015 • 35(50):16352–16361 +Neurobiology of Disease +Perceptual Integration Deficits in Autism Spectrum +Disorders Are Associated with Reduced Interhemispheric +Gamma-Band Coherence +Ina Peiker,1* Nicole David,1* X Till R. Schneider,1 Guido Nolte,1 Daniel Scho¨ttle,2 and XAndreas K. Engel1 +Departments of 1Neurophysiology and Pathophysiology and 2Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20246 +Hamburg, Germany +The integration of visual details into a holistic percept is essential for object recognition. This integration has been reported as a key deficit +in patients with autism spectrum disorders (ASDs). The weak central coherence account posits an altered disposition to integrate features +into a coherent whole in ASD. Here, we test the hypothesis that such weak perceptual coherence may be reflected in weak neural coherence +cross different cortical sites. We recorded magnetoencephalography from 20 adult human participants with ASD and 20 matched +ontrols, who performed a slit-viewing paradigm, in which objects gradually passed behind a vertical or horizontal slit so that only +fragments of the object were visible at any given moment. Object recognition thus required perceptual integration over time and, in case +of the horizontal slit, also across visual hemifields. ASD participants were selectively impaired in the horizontal slit condition, indicating +specific difficulties in long-range synchronization between the hemispheres. Specifically, the ASD group failed to show condition-related +enhancement of imaginary coherence between the posterior superior temporal sulci in both hemispheres during horizontal slit-viewing +in contrast to controls. Moreover, local synchronization reflected in occipitocerebellar beta-band power was selectively reduced for +horizontal compared with vertical slit-viewing in ASD. Furthermore, we found disturbed connectivity between right posterior superior +temporal sulcus and left cerebellum. Together, our results suggest that perceptual integration deficits co-occur with specific patterns of"
+bc8e1c2284008319ee325ff7ea19916726235f55,Autonomic responses to social and nonsocial pictures in adolescents with autism spectrum disorder.,"RESEARCH ARTICLE +Autonomic Responses to Social and Nonsocial Pictures in +Adolescents With Autism Spectrum Disorder +Anneke Louwerse, Joke H. M. Tulen, Jos N. van der Geest, Jan van der Ende, Frank C. Verhulst, and +Kirstin Greaves-Lord +It remains unclear why individuals with autism spectrum disorder (ASD) tend to respond in an atypical manner in social +situations. Investigating autonomic and subjective responses to social vs. nonsocial stimuli may help to reveal underlying +mechanisms of these atypical responses. This study examined autonomic responses (skin conductance level and heart +rate) and subjective responses to social vs. nonsocial pictures in 37 adolescents with an ASD and 36 typically developing +(TD) adolescents. Thirty-six pictures from the International Affective Picture System were presented, divided into six +ategories based on social content (social vs. nonsocial) and pleasantness (pleasant, neutral, and unpleasant). Both in +dolescents with ASD as well as TD adolescents, pictures with a social content resulted in higher skin conductance +responses (SCRs) for pleasant and unpleasant pictures than for neutral pictures. No differences in SCRs were found for +the three nonsocial picture categories. Unpleasant pictures, both with and without a social content, showed more heart +rate deceleration than neutral pictures. Self-reported arousal ratings were influenced by the social and affective content +of a picture. No differences were found between individuals with ASD and TD individuals in their autonomic and +subjective responses to the picture categories. These results suggest that adolescents with ASD do not show atypical +utonomic or subjective responses to pictures with and without a social content. These findings make it less likely that +impairments in social information processing in individuals with ASD can be explained by atypical autonomic responses +to social stimuli. Autism Res 2013, (cid:129)(cid:129): (cid:129)(cid:129)–(cid:129)(cid:129). © 2013 International Society for Autism Research, Wiley Periodicals, Inc."
bc811a66855aae130ca78cd0016fd820db1603ec,Towards three-dimensional face recognition in the real Huibin,"Towards three-dimensional face recognition in the real Huibin Li To cite this version: @@ -4471,6 +15078,15 @@ Department of Computer Science, VHNSN College, Virudhunagar, India; 2Department Sivakasi, India. Email: Received April 27th, 2012; revised July 19th, 2012; accepted July 26th, 2012"
+bcaa5fab589d95890d539a3119657fa253176f0d,"Evaluating the Efficiency of a Night-Time, Middle-Range Infrared Sensor for Applications in Human Detection and Recognition","THE PROBLEM: MID-RANGE FR AT NIGHT +No Active Illumination +NIR Led Illuminator +Night Time 120 meters +eters +Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIII, edited by Gerald C. Holst, Keith A. Krapels, +Proc. of SPIE Vol. 8355, 83551B · © 2012 SPIE · CCC code: 0277-786X/12/$18 · doi: 10.1117/12.917831 +Proc. of SPIE Vol. 8355 83551B-1 +From: http://proceedings.spiedigitallibrary.org/ on 04/30/2013 Terms of Use: http://spiedl.org/terms"
bc9af4c2c22a82d2c84ef7c7fcc69073c19b30ab,MoCoGAN: Decomposing Motion and Content for Video Generation,"MoCoGAN: Decomposing Motion and Content for Video Generation Sergey Tulyakov, Snap Research @@ -4483,6 +15099,18 @@ CVPR 2013 Submission #1387. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. Structured Face Hallucination Anonymous CVPR submission Paper ID 1387"
+bc4627e1bc3bbe21c46c4011ec4f9bd377ec83a4,Towards recognition of degraded words by probabilistic parsing,"Towards Recognition of Degraded Words by Probabilistic +Parsing +Karthika Mohan +IIIT, Hyderabad +AP, India 500 032 +K. J. Jinesh +IIIT, Hyderabad +AP, India 500 032 +C. V. Jawahar +IIIT, Hyderabad +AP, India 500 032"
+ae419d28ab936cbbc420dcfd1decb16a45afc8a9,Real-time face verification using multiple feature combination and a support vector machine supervisor,
ae8d5be3caea59a21221f02ef04d49a86cb80191,Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks,"Published as a conference paper at ICLR 2018 SKIP RNN: LEARNING TO SKIP STATE UPDATES IN RECURRENT NEURAL NETWORKS @@ -4490,6 +15118,49 @@ V´ıctor Campos∗†, Brendan Jou‡, Xavier Gir´o-i-Nieto§, Jordi Torres† Barcelona Supercomputing Center, ‡Google Inc, §Universitat Polit`ecnica de Catalunya, ΓColumbia University {victor.campos,"
+ae2b2493f35cecf1673eb3913fdce37e037b53a2,Optimal Transport Maps for Distribution Pre- Serving Operations on Latent Spaces of Gener-,"OPTIMAL TRANSPORT MAPS FOR DISTRIBUTION PRE- +SERVING OPERATIONS ON LATENT SPACES OF GENER- +ATIVE MODELS +Eirikur Agustsson +D-ITET, ETH Zurich +Switzerland +Alexander Sage +D-ITET, ETH Zurich +Switzerland +Radu Timofte +D-ITET, ETH Zurich +Merantix GmbH +Luc Van Gool +D-ITET, ETH Zurich +ESAT, KU Leuven"
+aeee98c90799cd44dde4046754cff27c8ed28d44,Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review,"Deep convolutional neural networks for brain image analysis on magnetic +resonance imaging: a review +Jose Bernal∗, Kaisar Kushibar, Daniel S. Asfaw, Sergi Valverde, Arnau Oliver, Robert Mart´ı, Xavier Llad´o +Computer Vision and Robotics Institute +Dept. of Computer Architecture and Technology +University of Girona +Ed. P-IV, Av. Lluis Santal´o s/n, 17003 Girona (Spain)"
+aeee02b8c8bb749a1203fa634407319dd6874667,VIDEO-SURVEILLANCE IN CLOUD Platform and software aaS for people detection and soft-biometry,"VIDEO-SURVEILLANCE IN CLOUD +Platform and software aaS for people detection and soft- +iometry +R. Cucchiara°,*, A. Prati°,+, R. Vezzani°,*, S. Calderara°,*, C. Grana°,* +°SOFTECH-ICT, *Università di Modena e Reggio Emilia, +Università IUAV di Venezia"
+aed5b3b976077ecdcf3f88ffc511f63d9f9e8697,"A Qualitative Comparison of CoQA, SQuAD 2.0 and QuAC","A Qualitative Comparison of CoQA, SQuAD 2.0 and QuAC +Mark Yatskar +Allen Institute for Artificial Intelligence"
+aeabcbdff7ab810b961a9f7e4399b6c0421d00cd,TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents,"TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents +Yuexin Ma1,2, Xinge Zhu3, Sibo Zhang1, Ruigang Yang1, Wenping Wang2, Dinesh Manocha4 +Baidu Research, Baidu Inc.1, The University of Hong Kong2, +The Chinese University of Hong Kong3, University of Maryland at College Park4"
+ae0514be12d200bd9fecf0d834bdcb30288c7a1e,Automatic Opinion Question Generation,"Automatic Opinion Question Generation +Yllias Chali +University of Lethbridge +401 University Drive +Lethbridge, Alberta, T1K 3M4 +Tina Baghaee +University of Lethbridge +401 University Drive +Lethbridge, Alberta, T1K 3M4"
ae2cf545565c157813798910401e1da5dc8a6199,Cascade of Boolean detector combinations,"Mahkonen et al. EURASIP Journal on Image and Video Processing (2018) 2018:61 https://doi.org/10.1186/s13640-018-0303-9 @@ -4501,7 +15172,39 @@ Cascade of Boolean detector ombinations Katariina Mahkonen* , Tuomas Virtanen and Joni Kämäräinen"
+ae818858a88299090748446b8662e68628612c65,Analysis of Expressiveness of Portuguese Sign Language Speakers,"FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO +Analysis of Expressiveness of +Portuguese Sign Language Speakers +Maria Inês Coutinho Vigário Rodrigues +MASTER THESIS +Integrated Master in Bioengineering +Supervisor: Luis Filipe Pinto de Almeida Teixeira (PhD) +Co-supervisor: Eduardo José Marques Pereira (Eng.) +June 2014"
aebb9649bc38e878baef082b518fa68f5cda23a5,A Multi - scale TVQI - based Illumination Normalization Model,
+ae299fad29ba650fbf1e14c7c95ba8ae32e095f0,Person Re-Identification by Robust Canonical Correlation Analysis,"Person Re-Identification by Robust +Canonical Correlation Analysis +Le An, Songfan Yang, Member, IEEE, and Bir Bhanu, Fellow, IEEE"
+ae9ab89c51d264fb7b6b57d37399a7c629836e35,Obtaining Better Image Representations by Combining Complementary Activation Features of Multiple ConvNet Layers for Transfer Learning,"Obtaining Better Image Representations by +Combining Complementary Activation Features of +Multiple ConvNet Layers for Transfer Learning +Jumabek Alikhanov +School of Computer and +Information Engineering +Seunghyun Ko +School of Computer and +Information Engineering +Jo Geun Sik +School of Computer and +Information Engineering +Inha University Incheon, South Korea +Inha University Incheon, South Korea +Inha University Incheon, South Korea +Email: +Email: +Email:"
+ae5195c44ef7bff090bb5a17a9fe5f86a8c3b316,Web Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings,"Web Scale Image Annotation: Learning to Rank with Joint +Word-Image Embeddings"
aeeea6eec2f063c006c13be865cec0c350244e5b,"Induced Disgust, Happiness and Surprise: an Addition to the MMI Facial Expression Database","Induced Disgust, Happiness and Surprise: an Addition to the MMI Facial Expression Database Michel F. Valstar, Maja Pantic @@ -4509,6 +15212,35 @@ Imperial College London / Twente University Department of Computing / EEMCS 80 Queen’s Gate / Drienerlolaan 5 London / Twente"
+ae13485e75f5e7fc9a9659ce960c8b299c7b889b,Sparse Modeling for High - Dimensional Multi - Manifold Data Analysis,"SPARSE MODELING FOR HIGH-DIMENSIONAL +MULTI-MANIFOLD DATA ANALYSIS +Ehsan Elhamifar +A dissertation submitted to The Johns Hopkins University in conformity with the +requirements for the degree of Doctor of Philosophy. +Baltimore, Maryland +October, 2012 +(cid:13) Ehsan Elhamifar 2012 +All rights reserved"
+ae8ed3b0b8043c5af76390751938edfd100fa9cd,An Overview of MultiTask Learning in Deep Neural Networks,"of 21 +9 May 2017 +An Overview of Multi-Task Learning in Deep +Neural Networks +Table of contents: +Introduction +Motivation +Two MTL methods for Deep Learning +Hard parameter sharing +Soft parameter sharing +Why does MTL work? +Implicit data augmentation +Attention focusing +Eavesdropping +Representation bias +Regularization +MTL in non-neural models +Block-sparse regularization +http://sebastianruder.com/multi-task/index.html +5/31/17, 9:38 AM"
ae9257f3be9f815db8d72819332372ac59c1316b,Deciphering the enigmatic face: the importance of facial dynamics in interpreting subtle facial expressions.,"P SY CH O L O GIC AL SC I E NC E Research Article Deciphering the Enigmatic Face @@ -4516,6 +15248,12 @@ The Importance of Facial Dynamics in Interpreting Subtle Facial Expressions Zara Ambadar,1 Jonathan W. Schooler,2 and Jeffrey F. Cohn1 University of Pittsburgh and 2University of British Columbia, Vancouver, British Columbia, Canada"
+ae33dc04adcb83a486517c48078cdd4af7dcc7c7,The adaptative local Hausdorff-distance map as a new dissimilarity measure,"The adaptative local Hausdorff-distance map +s a new dissimilarity measure +´Etienne Baudrier∗, Gilles Millon, Fr´ed´eric Nicolier, Su Ruan +Centre de Recherche en STIC (CReSTIC) +IUT de Troyes, 9, rue de Qu´ebec, 10026 TROYES CEDEX, FRANCE +{e.baudrier, g.millon, f.nicolier,"
ae89b7748d25878c4dc17bdaa39dd63e9d442a0d,On evaluating face tracks in movies,"On evaluating face tracks in movies Alexey Ozerov, Jean-Ronan Vigouroux, Louis Chevallier, Patrick Pérez To cite this version: @@ -4543,14 +15281,99 @@ Zeshan Hussain" ae753fd46a744725424690d22d0d00fb05e53350,Describing Clothing by Semantic Attributes,"Describing Clothing by Semantic Attributes Anonymous ECCV submission Paper ID 727"
+ae0a0ee1c6e2adcddffebf9b0e429a25b7d9c0e1,"A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms","A Review and Analysis of Eye-Gaze Estimation +Systems, Algorithms and Performance +Evaluation Methods in Consumer Platforms +Anuradha Kar, Student Member, IEEE, Peter Corcoran Fellow, IEEE"
+aeec61ef41d55b5c1becfdc00c2e4dbca0e379c0,Automatic Recognition by Gait,"I N V I T E D +P A P E R +Automatic Recognition by Gait +Recognizing people by the way they walk promises to be useful for identifying +individuals from a distance; improved techniques are under development. +By Mark S. Nixon, Member IEEE, and John N. Carter, Member IEEE"
+ae8cc8db9e05c79adad03da64a4a9ba0b00f4eb5,Large Scale Local Online Similarity/Distance Learning Framework based on Passive/Aggressive,"International Journal of Machine Learning and Cybernetics +DOI –x +ORI GI NAL ARTI CLE +Large Scale Local Online Similarity/Distance Learning Framework based on +Passive/Aggressive +Baida Hamdan1, Davood Zabihzadeh*1, Monsefi Reza1 +Computer Department, Engineering Faculty, Ferdowsi University of Mashhad (FUM), Mashhad, IRAN +* Corresponding Author"
ae85c822c6aec8b0f67762c625a73a5d08f5060d,Retrieving Similar Styles to Parse Clothing,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/TPAMI.2014.2353624 IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. M, NO. N, MONTH YEAR Retrieving Similar Styles to Parse Clothing Kota Yamaguchi, Member, IEEE, M. Hadi Kiapour, Student Member, IEEE, Luis E. Ortiz, and Tamara L. Berg, Member, IEEE"
+aed5aecd3f0a07036e570c84c06cd37ab8904acc,The Resiliency of Memorability: A Predictor of Memory Separate from Attention and Priming,"The Resiliency of Memorability: A Predictor of Memory +Separate from Attention and Priming +Wilma A. Bainbridge +Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology. Cambridge, MA. USA. +Keywords: Memorability, top-down attention, bottom-up attention, priming, visual search, +spatial cueing, directed forgetting, depth of encoding"
+ae87896c38f1871457d811a0588487db0155a833,Attentional allocation of ASD individuals : Searching for a Face - in - the - Crowd,"Attentional allocation of ASD individuals: Searching for a Face-in-the-Crowd +David J. Moore, John Reidy and Lisa Heavey +Department of Psychology, Sociology and Politics, +Sheffield Hallam University +Running Header: Attentional allocation of ASD individuals"
+aef3ecc926ed79478f9d1f38c0fec2a29bae9c3b,Counting in High Density Crowd Videos,"Counting in High Density Crowd Videos +Edgar Lopez +University of Texas at El Paso"
+aee90db1f66b77113b0a62701deb01ca96b6d9e6,"Discriminant Saliency, the Detection of Suspicious Coincidences, and Applications to Visual Recognition","JUNE 2009 +Discriminant Saliency, the Detection +of Suspicious Coincidences, +nd Applications to Visual Recognition +Dashan Gao, Member, IEEE, Sunhyoung Han, Student Member, IEEE, and +Nuno Vasconcelos, Senior Member, IEEE"
+d88e3d5ca820cb240de4b662f0a6fd1172a678c7,Image Quality-based Adaptive Illumination Normalisation for Face Recognition,"Harin Sellahewa and Sabah A. Jassim, ""Image quality-based adaptive illumination normalisation for face recognition"", +Proc. SPIE 7306, Optics and Photonics in Global Homeland Security V and Biometric Technology for Human +Identification VI, 73061V (May 05, 2009); doi:10.1117/12.819087; http://dx.doi.org/10.1117/12.819087 +Copyright 2009 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for +personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for +ommercial purposes, or modification of the content of the paper are prohibited.” (http://spie.org/x1125.xml)"
+d84263e22c7535cb1a2a72c88780d5a407bd9673,Stability of Scattering Decoder For Nonlinear Diffractive Imaging,"Stability of Scattering Decoder for Nonlinear Diffractive Imaging +Yu Sun1 and Ulugbek S. Kamilov1,2 +Department of Computer Science & Engineering, Washington University in St Louis. +Department of Electrical & Systems Engineering, Washington University in St. Louis"
+d80564cea654d11b52c0008891a0fd2988112049,Semi-supervised Conditional GANs,"Semi-supervised Conditional GANs +Kumar Sricharan∗1, Raja Bala1, Matthew Shreve1, +Hui Ding1, Kumar Saketh2, and Jin Sun1 +Interactive and Analytics Lab, Palo Alto Research Center, Palo Alto, CA +Verizon Labs, Palo Alto, CA +August 22, 2017"
+d827c72d6c9e35066b40bd205bbd71ce487a1c39,Ensemble of Face/eye Detectors for Accurate Automatic Face Detection,"International Journal of Latest Research in Science +Volume 4, Issue 3: Page No.8-18, May-June 2015 +http://www.mnkjournals.com/ijlrst.htm +nd Technology ISSN (Online):2278-5299 +ENSEMBLE OF FACE/EYE DETECTORS FOR +ACCURATE AUTOMATIC FACE DETECTION +Loris Nanni, 2Alessandra Lumini, 3Sheryl Brahnam +Department of Information Engineering at the University of Padua, Padua, Italy +DISI, University of Bologna, Cesena, Italy +Computer Information Systems, Missouri State University, USA"
d861c658db2fd03558f44c265c328b53e492383a,Automated face extraction and normalization of 3D Mesh Data,"Automated Face Extraction and Normalization of 3D Mesh Data Jia Wu1, Raymond Tse2, Linda G. Shapiro1"
+d833c48334e906537f21757b6f9fa44da66f6c76,MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement,"MEMC-Net: Motion Estimation and Motion +Compensation Driven Neural Network for +Video Interpolation and Enhancement +Wenbo Bao, Wei-Sheng Lai, Xiaoyun Zhang, Zhiyong Gao, and Ming-Hsuan Yang"
+d8d1fb804d1f4760393c6fd70c9072fa1b39f02c,An Efficient Approach to Onboard Stereo Vision System Pose Estimation,"An Efficient Approach to Onboard Stereo +Vision System Pose Estimation +Angel Domingo Sappa, Member, IEEE, Fadi Dornaika, Daniel Ponsa, David Gerónimo, and Antonio López"
+d8abf01fce0d44665949e7a73716fff7731fa6da,Places: An Image Database for Deep Scene Understanding,"Places: An Image Database for Deep Scene +Understanding +Bolei Zhou, Aditya Khosla, Agata Lapedriza, Antonio Torralba and Aude Oliva"
+d8b58c5b403dc28437af8244ec812efdfbc6b2e0,MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose Estimation,"MVOR: A Multi-view RGB-D Operating Room +Dataset for 2D and 3D Human Pose Estimation +Vinkle Srivastav1, Thibaut Issenhuth1, Abdolrahim Kadkhodamohammadi1, +Michel de Mathelin1, Afshin Gangi1,2, and +Nicolas Padoy1 +ICube, University of Strasbourg, CNRS, IHU Strasbourg, France +Radiology Department, University Hospital of Strasbourg, France"
+d813ec3a3442f2885b76ac0133c4c5d76f9f8065,Panoptic Studio: A Massively Multiview System for Social Interaction Capture,"Panoptic Studio: A Massively Multiview System +for Social Interaction Capture +Hanbyul Joo, Tomas Simon, Xulong Li, Hao Liu, Lei Tan, Lin Gui, Sean Banerjee, Timothy Godisart, +Bart Nabbe, Iain Matthews, Takeo Kanade, Shohei Nobuhara, and Yaser Sheikh"
d8f0bda19a345fac81a1d560d7db73f2b4868836,Online Activity Understanding and Labeling in Natural Videos,"UNIVERSITY OF CALIFORNIA RIVERSIDE Online Activity Understanding and Labeling in Natural Videos @@ -4565,6 +15388,15 @@ Dr. Amit K. Roy-Chowdhury, Chairperson Dr. Eamonn Keogh Dr. Evangelos Christidis Dr. Christian Shelton"
+d809c0ab068861c139a544e5d8eeaa73cc8a3f6b,Monocular Semantic Occupancy Grid Mapping with Convolutional Variational Encoder-Decoder Networks,"Monocular Semantic Occupancy Grid Mapping +with Convolutional Variational Encoder-Decoder Networks +Chenyang Lu1, Ren´e van de Molengraft2, and Gijs Dubbelman1"
+d888895cd56d336aa1367fac8072da782bdbc0fb,AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks,"AttnGAN: Fine-Grained Text to Image Generation +with Attentional Generative Adversarial Networks +Tao Xu∗1, Pengchuan Zhang2, Qiuyuan Huang2, +Han Zhang3, Zhe Gan4, Xiaolei Huang1, Xiaodong He2 +Lehigh University 2Microsoft Research 3Rutgers University 4Duke University +{tax313, {penzhan, qihua,"
d82b93f848d5442f82154a6011d26df8a9cd00e7,Neural Network Based Age Classification Using Linear Wavelet Transforms,"NEURAL NETWORK BASED AGE CLASSIFICATION USING LINEAR WAVELET TRANSFORMS NITHYASHRI JAYARAMAN1 & G.KULANTHAIVEL2 @@ -4573,6 +15405,28 @@ Sathyabama University Old Mamallapuram Road, Chennai, India Electronics Engineering, National Institute of Technical Teachers Training & Research, Taramani, Chennai, India E-mail :"
+d881a59d00971c754e02bfaaf4c48ec6dfbc1343,Neighborhood Sensitive Mapping for Zero-Shot Classification using Independently Learned Semantic Embeddings,"Neighborhood Sensitive Mapping for Zero-Shot +Classification using Independently Learned +Semantic Embeddings +Gaurav Singh1, Fabrizio Silvestri2, and John Shawe-Taylor1 +UCL, UK +Yahoo, UK"
+d87ccfc42cf6a72821d357aab0990e946918350b,Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search,"Exploiting the Potential of Standard Convolutional Autoencoders +for Image Restoration by Evolutionary Search +Masanori Suganuma 1 2 Mete Ozay 1 Takayuki Okatani 1 2"
+d84568d42a02b6d365889451f208f423edb1f0f3,Age Synthesis and Estimation From Face Image Ms,"www.ijecs.in +International Journal Of Engineering And Computer Science ISSN:2319-7242 +Volume 3 Issue 4 April, 2014 Page No. 5462-5466 +Age Synthesis and Estimation From Face Image +Ms. Deepali R. gadbail1, Prof. S.S. Dhande2, Prof.Kanchan M. Pimple3 +M s. Deepali R Gadbail, +Computer Science and Engineering Department, +Sipna COET,Amravati. +Prof. S. S. Dhande, +Computer Science and Engineering Department, +Sipna COET,Amravati. +Prof.Kanchan M . Pimple, +IBSS College of engg. & tech.,Amravati"
d83d2fb5403c823287f5889b44c1971f049a1c93,Introducing the sick face,"Motiv Emot DOI 10.1007/s11031-013-9353-6 O R I G I N A L P A P E R @@ -4580,6 +15434,17 @@ Introducing the sick face Sherri C. Widen • Joseph T. Pochedly • Kerrie Pieloch • James A. Russell Ó Springer Science+Business Media New York 2013"
+d8671247f6188620c6e382ffcd15d3e909647c63,Multicamera human detection and tracking supporting natural interaction with large-scale displays,"DOI 10.1007/s00138-012-0408-6 +ORIGINAL PAPER +Multicamera human detection and tracking supporting natural +interaction with large-scale displays +Xenophon Zabulis · Dimitris Grammenos · +Thomas Sarmis · Konstantinos Tzevanidis · +Pashalis Padeleris · Panagiotis Koutlemanis · +Antonis A. Argyros +Received: 8 March 2011 / Revised: 9 January 2012 / Accepted: 17 January 2012 +© Springer-Verlag 2012"
+d8db46f1775641051d8596dad3d37d1d731558f7,Survey on Deep Learning Techniques for Person Re-Identification Task,
d8b568392970b68794a55c090c4dd2d7f90909d2,PDA Face Recognition System Using Advanced Correlation Filters,"PDA Face Recognition System Using Advanced Correlation Filters @@ -4593,12 +15458,88 @@ APPROVED BY SUPERVISING COMMITTEE: Kristen Grauman, Supervisor Peter Stone"
+d8029237cde893218d21ba551fd127d045ae3422,Eye-Strip based Person Identification based on Non-Subsampled Contourlet Transform,"International Journal of Computer Applications (0975 – 8887) +Volume 121 – No.12, July 2015 +Eye-Strip based Person Identification based on +Non-Subsampled Contourlet Transform +Hemprasad Y. Patil +Dept. of ECE +Visvesvaraya National Institute +of Technology, Nagpur, India +Ashwin G. Kothari +Dept. of ECE +Visvesvaraya National Institute +of Technology, Nagpur, India +Kishor M. Bhurchandi +Dept. of ECE +Visvesvaraya National Institute +of Technology, Nagpur, India +transform +sub-band"
+d8af6a45eaea68adda8597ae65f91ece152f7b21,Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation,"Sparse and Dense Data with CNNs: +Depth Completion and Semantic Segmentation +Maximilian Jaritz1, 2, Raoul de Charette1, Emilie Wirbel2, Xavier Perrotton2, Fawzi Nashashibi1 +{maximilian.jaritz, raoul.de-charette, +Inria RITS Team +{emilie.wirbel, +Valeo"
+d806790866ab9bad77f60436fe77232db8e0c1ba,Deep Directional Network for Object Tracking,"Article +Deep Directional Network for Object Tracking +Zhaohua Hu 1,2,* and Xiaoyi Shi 1 +School of Electronic & Information Engineering, Nanjing University of Information Science & Technology, +Nanjing 210044, China; +Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, +Nanjing University of Information Science & Technology, Nanjing 210044, China +* Correspondence: Tel.: +86-025-58731196 +Received: 10 October 2018; Accepted: 1 November 2018; Published: 5 November 2018"
+d82681348489f4f04690e65b9ffe21b68c89b5ff,Cross-Subject EEG Feature Selection for Emotion Recognition Using Transfer Recursive Feature Elimination,"ORIGINAL RESEARCH +published: 10 April 2017 +doi: 10.3389/fnbot.2017.00019 +Cross-Subject EEG Feature Selection +for Emotion Recognition Using +Transfer Recursive Feature +Elimination +Zhong Yin 1*, Yongxiong Wang 1*, Li Liu 1, Wei Zhang 1 and Jianhua Zhang 2 +Shanghai Key Lab of Modern Optical System, Engineering Research Center of Optical Instrument and System, Ministry of +Education, University of Shanghai for Science and Technology, Shanghai, China, 2 Department of Automation, East China +University of Science and Technology, Shanghai, China +Using machine-learning methodologies to analyze EEG signals becomes increasingly +ttractive for recognizing human emotions because of the objectivity of physiological +data and the capability of the learning principles on modeling emotion classifiers from +heterogeneous features. However, the conventional subject-specific classifiers may +induce additional burdens to each subject for preparing multiple-session EEG data +s training sets. To this end, we developed a new EEG feature selection approach, +transfer recursive feature elimination (T-RFE), to determine a set of the most robust EEG +indicators with stable geometrical distribution across a group of training subjects and +specific testing subject. A validating set is introduced to independently determine"
d86fabd4498c8feaed80ec342d254fb877fb92f5,Region-Object Relevance-Guided Visual Relationship Detection,"Y. GOUTSU: REGION-OBJECT RELEVANCE-GUIDED VRD Region-Object Relevance-Guided Visual Relationship Detection Yusuke Goutsu National Institute of Informatics Tokyo, Japan"
+d8e061960423a17748dedbcfe4b6a6918f79c262,Fast Prototyping and Computationally Intensive Experiments,"Armadillo: An Open Source C++ Linear Algebra Library for +Fast Prototyping and Computationally Intensive Experiments +Conrad Sanderson +http://conradsanderson.id.au +Technical Report, NICTA, Australia +http://nicta.com.au +September 2010 +(revised December 2011)"
+d865c5e85191cfc0da714290d8583a2fb1179fd4,"Learning Hierarchical Space Tiling for Scene Modeling, Parsing and Attribute Tagging","Learning Hierarchical Space Tiling for Scene +Modeling, Parsing and Attribute Tagging +Shuo Wang, Yizhou Wang, and Song-Chun Zhu"
+d8f7b26d25a026fe43487b6f77993e11b8b333e0,Photo Indexing and Retrieval based on Content and Context,"PhD Dissertation +International Doctorate School in Information and +Communication Technologies +DISI - University of Trento +Photo Indexing and Retrieval +ased on Content and Context +Mattia Broilo +Advisor: +Prof. Francesco G. B. De Natale +Universit`a degli Studi di Trento +February 2011"
d850aff9d10a01ad5f1d8a1b489fbb3998d0d80e,Recognizing and Segmenting Objects in the Presence of Occlusion and Clutter,"UNIVERSITY OF CALIFORNIA, IRVINE Recognizing and Segmenting Objects in the Presence of Occlusion and Clutter @@ -4612,9 +15553,44 @@ Dissertation Committee: Professor Charless Fowlkes, Chair Professor Deva Ramanan Professor Alexander Ihler"
+d88eb94d7054d2668b1a8dfa311721f37ae1f059,Straight to the Facts: Learning Knowledge Base Retrieval for Factual Visual Question Answering,"Straight to the Facts: Learning Knowledge Base +Retrieval for Factual Visual Question Answering +Medhini Narasimhan, Alexander G. Schwing +University of Illinois Urbana-Champaign"
+d81dbc2960e527e91c066102aabdaf9eb8b15f85,Deep Directed Generative Models with Energy-Based Probability Estimation,"Deep Directed Generative Models +with Energy-Based Probability Estimation +Taesup Kim, Yoshua Bengio∗ +Department of Computer Science and Operations Research +Université de Montréal +Montréal, QC, Canada"
+d8c04365ed0627a5043996cdd26c1a56b5a630b8,Learning Monocular Depth Estimation with Unsupervised Trinocular Assumptions,"Learning monocular depth estimation with unsupervised trinocular assumptions +Matteo Poggi, Fabio Tosi, Stefano Mattoccia +University of Bologna, Department of Computer Science and Engineering +Viale del Risorgimento 2, Bologna, Italy +{m.poggi, fabio.tosi5,"
d89cfed36ce8ffdb2097c2ba2dac3e2b2501100d,Robust Face Recognition via Multimodal Deep Face Representation,"Robust Face Recognition via Multimodal Deep Face Representation Changxing Ding, Student Member, IEEE, Dacheng Tao, Fellow, IEEE"
+ab87ab1cf522995510561cd9f494223704f1de91,Human Centric Facial Expression Recognition,"Human Centric Facial Expression Recognition +K. Clawson 1*, L. S. Delicato, 2** and C. Bowerman, 1*** +Faculty of Computer Science, University of Sunderland, Sunderland, SR1 3SD, UK +. Faculty of Health, Sciences and Wellbeing, University of Sunderland, SR1 3QR, UK +Facial expression recognition (FER) is an area of active research, both in computer science and in +ehavioural science. Across these domains there is evidence to suggest that humans and machines +find it easier to recognise certain emotions, for example happiness, in comparison to others. Recent +ehavioural studies have explored human perceptions of emotion further, by evaluating the relative +ontribution of features in the face when evaluating human sensitivity to emotion. It has been +identified that certain facial regions have more salient features for certain expressions of emotion, +especially when emotions are subtle in nature. For example, it is easier to detect fearful expressions +when the eyes are expressive. Using this observation as a starting point for analysis, we similarly +examine the effectiveness with which knowledge of facial feature saliency may be integrated into +urrent approaches to automated FER. Specifically, we compare and evaluate the accuracy of ‘full- +face’ versus upper and lower facial area convolutional neural network (CNN) modelling for emotion +recognition in static images, and propose a human centric CNN hierarchy which uses regional image +inputs to leverage current understanding of how humans recognise emotions across the face. +Evaluations using the CK+ dataset demonstrate that our hierarchy can enhance classification +ccuracy +individual CNN architectures, achieving overall true positive"
ab8f9a6bd8f582501c6b41c0e7179546e21c5e91,Nonparametric Face Verification Using a Novel Face Representation,"Nonparametric Face Verification Using a Novel Face Representation Hae Jong Seo, Student Member, IEEE, Peyman Milanfar, Fellow, IEEE,"
@@ -4640,20 +15616,73 @@ opyright owners and it is a condition of accessing these publications that users with these rights. Take down policy The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to"
+ab8af4cb5243544e38852bb670aafe5a2fd9b3ec,Real-Time Human Detection Using Relational Depth Similarity Features,"Real-Time Human Detection using Relational +Depth Similarity Features +Sho Ikemura, Hironobu Fujiyoshi +Dept. of Computer Science, Chubu University. +Matsumoto 1200, Kasugai, Aichi, 487-8501 Japan. +http://www.vision.cs.chubu.ac.jp"
+ab302d79e419348499acbda4a627b67dec89936f,Robust Correlated and Individual Component Analysis,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2014 +Robust Correlated and Individual Component +Analysis +Yannis Panagakis, Member, IEEE, Mihalis A. Nicolaou, Member, IEEE, +Stefanos Zafeiriou, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+abfcafaa765433b8f5b8be7eae392a8daec54b8e,Facial EMG Responses to Emotional Expressions Are Related to Emotion Perception Ability,"Facial EMG Responses to Emotional Expressions Are +Related to Emotion Perception Ability +Janina Ku¨ necke1*, Andrea Hildebrandt1, Guillermo Recio1,2, Werner Sommer1, Oliver Wilhelm2 +Department of Psychology, Humboldt Universita¨t zu Berlin, Berlin, Germany, 2 Department of Psychology, University Ulm, Ulm, Germany"
ab0f9bc35b777eaefff735cb0dd0663f0c34ad31,Semi-supervised Learning of Geospatial Objects through Multi-modal Data Integration,"Semi-Supervised Learning of Geospatial Objects Through Multi-Modal Data Integration Yi Yang and Shawn Newsam Electrical Engineering and Computer Science University of California, Merced, CA, 95343 Email:"
+abc4d51d510cd8222484f7f4f11a739e8bce42ff,On Fast Non-metric Similarity Search by Metric Access Methods,"On Fast Non-metric Similarity Search +y Metric Access Methods +Tom´aˇs Skopal +Charles University in Prague, FMP, Department of Software Engineering, +Malostransk´e n´am. 25, 118 00 Prague 1, Czech Republic"
+ab98abfbdfd700c27bee31ca1f8850db72120c5d,Video Event Detection by Exploiting Word Dependencies from Image Captions,"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, +pages 3318–3327, Osaka, Japan, December 11-17 2016."
+ab8778793b0f2f06d9e97b6277f3b1125f31432c,Stochastic Models for Face Image Analysis,"Stochastic Models for Face Image Analysis +St(cid:19)ephane Marchand-Maillet and Bernard M(cid:19)erialdo +Department of Multimedia Communications +Institut EURECOM { B.P. + ab989225a55a2ddcd3b60a99672e78e4373c0df1,"Sample, computation vs storage tradeoffs for classification using tensor subspace models","Sample, Computation vs Storage Tradeoffs for Classification Using Tensor Subspace Models Mohammadhossein Chaghazardi and Shuchin Aeron, Senior Member, IEEE"
+abddbb57258d85b1f3d9789128fd284d30a91e23,A research and education initiative at the MIT Sloan School of Management Network Structure & Information Advantage Paper 235,"A research and education initiative at the MIT +Sloan School of Management +Network Structure & Information Advantage +Paper 235 +Sinan Aral +Marshall Van Alstyne +July 2007 +For more information, +please visit our website at http://digital.mit.edu +or contact the Center directly at +or 617-253-7054"
+abba22ed4713a5ee5fa91fcf7b8dde58a9b621db,Acquisition of a 3D Audio-Visual Corpus of Affective Speech,"BIWI Technical Report n. 270 +Acquisition of a 3D Audio-Visual Corpus of +Affective Speech +Gabriele Fanelli, Juergen Gall, Harald Romsdorfer, Thibaut Weise, +nd Luc Van Gool"
+ab69f49fedb6936ce04b2e9d1f161772b2f24b7d,Architecture-aware optimization of an HEVC decoder on asymmetric multicore processors,"(will be inserted by the editor) +Architecture-Aware Optimization of an HEVC decoder on +Asymmetric Multicore Processors +Rafael Rodr´ıguez-S´anchez · Enrique S. Quintana-Ort´ı +Received: date / Revised: date"
ab6776f500ed1ab23b7789599f3a6153cdac84f7,A Survey on Various Facial Expression Techniques,"International Journal of Scientific & Engineering Research, Volume 6, Issue 4, April-2015 1212 ISSN 2229-5518 A Survey on Various Facial Expression Techniques Md. Sarfaraz Jalil, Joy Bhattacharya"
+ab036048cf90296171ad2bb7265c5a5b7f3252f7,Multimodal Recurrent Neural Networks With Information Transfer Layers for Indoor Scene Labeling,"Multimodal Recurrent Neural Networks with +Information Transfer Layers for Indoor Scene +Labeling +Abrar H. Abdulnabi, Student Member, IEEE, Bing Shuai, Student Member, IEEE, +Zhen Zuo, Student Member, IEEE, Lap-Pui Chau, Fellow, IEEE, and Gang Wang, Senior Member, IEEE"
ab1719f573a6c121d7d7da5053fe5f12de0182e7,Combining visual recognition and computational linguistics : linguistic knowledge for visual recognition and natural language descriptions of visual content,"Combining Visual Recognition nd Computational Linguistics Linguistic Knowledge for Visual Recognition @@ -4667,6 +15696,16 @@ of Saarland University Marcus Rohrbach, M.Sc. Saarbrücken March 2014"
+ab559473a01836e72b9fb9393d6e07c5745528f3,cGANs with Projection Discriminator,"Published as a conference paper at ICLR 2018 +CGANS WITH PROJECTION DISCRIMINATOR +Takeru Miyato1, Masanori Koyama2 +Preferred Networks, Inc. 2Ritsumeikan University"
+abe9f3b91fd26fa1b50cd685c0d20debfb372f73,The Pascal Visual Object Classes Challenge: A Retrospective,"(will be inserted by the editor) +The Pascal Visual Object Classes Challenge – a Retrospective +Mark Everingham, S. M. Ali Eslami, Luc Van Gool, +Christopher K. I. Williams, John Winn, Andrew Zisserman +Received: date / Accepted: date"
+ab969cfae95f62d68c61830128b35786eb6c84a9,Contents 1 Introduction 2,"Contents1Introduction22Tracking:FundamentalNotions22.1Trackingbydetection........................................22.2TrackingusingFlow........................................22.3Flowmodelsfromkinematicmodels................................22.4TrackingwithProbability......................................23Tracking:Relationsbetween3Dand2D23.1KinematicInferencewithMultipleViews.............................23.2Liftingto3D............................................33.3MultipleModes,RandomizedSearchandHumanTracking....................34Tracking:DataAssociationforHumanTracking54.1DetectingHumans.........................................54.2TrackingbyMatchingRevisited..................................64.3Evaluation..............................................75MotionSynthesisandAnimation95.1Motioncapture...........................................95.2Footskate..............................................95.3ResolvingKinematicAmbiguitieswithExamples.........................95.4MotionSignalProcessing......................................95.5MotionGraphs...........................................95.6MotionPrimitives..........................................105.7EnrichingaMotionCollection...................................105.8MotionfromPhysicalConsiderations...............................105.8.1SimplifiedCharacters....................................105.8.2ModifiedPhysics......................................115.8.3ReducedDimensions....................................115.8.4ModifyingExistingMotions................................116DescribingActivities126.1WhatshouldanActivityRepresentationdo?............................126.1.1NecessaryPropertiesofanActivityRepresentation....................136.1.2WhatDataisAvailable?..................................136.2MiscellaneousMethods.......................................146.2.1ActivityRepresentationMethodsbasedaroundTemporalLogics.............146.2.2ActivityRepresentationMethodsbasedonTemplates...................146.3ActivityRepresentationusingHiddenMarkovModelsandFiniteStateRepresentations.....146.4TheSpeechAnalogy........................................146.4.1FiniteStateTransducers..................................156.4.2WhyshouldweCare?...................................156.5ActivityRecognitionMethodsbasedaroundHMM’s.......................166.6SignLanguageRecognition.....................................176.7Morerecentmaterial........................................171"
ab2b09b65fdc91a711e424524e666fc75aae7a51,Multi-modal Biomarkers to Discriminate Cognitive State *,"Multi-modal Biomarkers to Discriminate Cognitive State* Thomas F. Quatieri 1, James R. Williamson1, Christopher J. Smalt1, Joey Perricone, Tejash Patel, Laura Brattain, Brian S. Helfer, Daryush D. Mehta, Jeffrey Palmer @@ -4687,6 +15726,22 @@ seek biomarkers that reflect timing and coordination relations both wit modality and across different modalities. This is based on the hypothesis that neural coordination cross different parts of the brain is essential in cognition (Figure 1). An example of timing and oordination within a modality is the set of finely timed and synchronized physiological"
+abb1289cfdc4c23d72d0680c3ec100eae74d4fdb,PatchMatch: A Fast Randomized Matching Algorithm with Application to Image and Video,"PatchMatch: A Fast Randomized Matching +Algorithm with Application to Image and Video +Connelly Barnes +A Dissertation +Presented to the Faculty +of Princeton University +in Candidacy for the Degree +of Doctor of Philosophy +Recommended for Acceptance +y the Department of +Computer Science +Adviser: Adam Finkelstein +May 2011"
+ab43c43d5eb2c5bee6de1b25c8bcb8068ab8bcd2,Deep Class-Wise Hashing: Semantics-Preserving Hashing via Class-wise Loss,"Deep Class-Wise Hashing: +Semantics-Preserving Hashing via Class-wise Loss +Xuefei Zhe, Shifeng Chen, Member, IEEE, and Hong Yan, Fellow, IEEE"
ab87dfccb1818bdf0b41d732da1f9335b43b74ae,Structured Dictionary Learning for Classification,"SUBMITTED TO IEEE TRANSACTIONS ON SIGNAL PROCESSING Structured Dictionary Learning for Classification Yuanming Suo, Student Member, IEEE, Minh Dao, Student Member, IEEE, Umamahesh Srinivas, Student @@ -4708,7 +15763,58 @@ d’explications possibles d’une image donnée lorsque les connaissances, expr logique de description, comportent des concepts décrivant les objets mais aussi les relations spatiales entre ces objets. La meilleure explication est sélectionnée en exploitant les domaines oncrets pour évaluer le degré de satisfaction des relations spatiales entre les objets."
+abb3df5b61dc7550db96fc112f98fb99a9db8c93,End-to-End Learning of Deep Visual Representations for Image Retrieval,"Noname manuscript No. +(will be inserted by the editor) +End-to-end Learning of Deep Visual Representations +for Image Retrieval +Albert Gordo · Jon Almaz´an · Jerome Revaud · Diane Larlus +Received: date / Accepted: date"
+ab450a7968555532d9ea79f81189c0d52f9c5f11,RGB-D Face Recognition in Surveillance Videos,"RGB-D Face Recognition in Surveillance Videos +Anurag Chowdhury +IIIT-D-MTech-CS-GEN-14-002 +June 23, 2016 +Indraprastha Institute of Information Technology Delhi +New Delhi +Thesis Advisors +Dr. Richa Singh +Dr. Mayank Vatsa +Submitted in partial fulfillment of the requirements +for the Degree of M.Tech. in Computer Science +(cid:13) Chowdhury, 2016 +Keywords : RGB-D, Kinect, Face Detection, Face Recognition, Deep Learning"
abeda55a7be0bbe25a25139fb9a3d823215d7536,Understanding Human-Centric Images: From Geometry to Fashion,"UNIVERSITATPOLITÈCNICADECATALUNYAProgramadeDoctorat:AUTOMÀTICA,ROBÒTICAIVISIÓTesiDoctoralUnderstandingHuman-CentricImages:FromGeometrytoFashionEdgarSimoSerraDirectors:FrancescMorenoNoguerCarmeTorrasMay2015"
+ab1f98b59fa98216f052ae19adce6fd94ebb800d,"Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos","Preprint submitted to International Journal of Computer Vision manuscript No. +(will be inserted by the editor) +Explaining First Impressions: Modeling, +Recognizing, and Explaining Apparent Personality +from Videos +Hugo Jair Escalante∗ · Heysem Kaya∗ · +Albert Ali Salah∗ · Sergio Escalera · +Ya˘gmur G¨u¸cl¨ut¨urk · Umut G¨u¸cl¨u · +Xavier Bar´o · Isabelle Guyon · Julio +Jacques Junior · Meysam Madadi · +Stephane Ayache · Evelyne Viegas · +Furkan G¨urpınar · Achmadnoer Sukma +Wicaksana · Cynthia C. S. Liem · +Marcel A. J. van Gerven · Rob van Lier +Received: date / Accepted: date +Means equal contribution by the authors. +Hugo Jair Escalante +INAOE, Mexico and ChaLearn, USA E-mail: +Heysem Kaya +Namık Kemal University, Department of Computer Engineering, Turkey"
+abf659847660763c94b44c0baaf9198046a11845,Video Image Object Tracking Algorithm based on Improved Principal Component Analysis,"Video Image Object Tracking Algorithm based +on Improved Principal Component Analysis +. Engineering Technology Research Center of Optoelectronic Technology Appliance, AnHui Tongling Anhui 244000, +. Hefei University of Technology, Hefei Anhui 230009, China +China +Wang Liping 1, 2 +dopts +DPCA +lgorithm +to reduce dimension of object"
+ab41364a58b34844b281046c3d8678f7d537a97e,Learning Deep Hierarchical Visual Feature Coding,"Learning Deep Hierarchical Visual Feature Coding +Hanlin Goh, Nicolas Thome, Member, IEEE, Matthieu Cord, Member, IEEE, and Joo-Hwee Lim, Member, IEEE"
ab8fb278db4405f7db08fa59404d9dd22d38bc83,Implicit and Automated Emotional Tagging of Videos,"UNIVERSITÉ DE GENÈVE Département d'Informatique FACULTÉ DES SCIENCES @@ -4723,8 +15829,113 @@ Téhéran (IRAN) Thèse No 4368 GENÈVE Repro-Mail - Université de Genève"
+ab03a1656d9e45c80379512161f6c90dfbb0b6b3,Active Learning for Regression Tasks with Expected Model Output Changes,"KÄDING ET AL.: ACTIVE LEARNING FOR REGRESSION TASKS WITH EMOC +Active Learning for Regression Tasks +with Expected Model Output Changes +Computer Vision Group +Friedrich Schiller University Jena +Jena, Germany +Carl Zeiss AG +Jena, Germany +Christoph Käding1 +Erik Rodner2 +Alexander Freytag2 +Oliver Mothes1 +Björn Barz1 +Joachim Denzler1"
+e5bcbfd346121769b674a7ad35e594758de5553f,A Dataset for Lane Instance Segmentation in Urban Environments,"A Dataset for Lane Instance Segmentation in +Urban Environments +Brook Roberts, Sebastian Kaltwang, Sina Samangooei, +Mark Pender-Bare, Konstantinos Tertikas, and John Redford +FiveAI Ltd., Cambridge CB2 1NS, U.K."
+e592f6dc3bf1d53044cd59ce4a75fdacd0ecc80d,Hand Vein Infrared Image Segmentation for Biometric Recognition,"Hand Vein Infrared Image Segmentation for Biometric +Recognition +Ignacio Irving Morales-Montiel1, J. Arturo Olvera-López1, Manuel Martín-Ortíz1, and +Eber E. Orozco-Guillén2 +Facultad de Ciencias de la Computación +Benemérita Universidad Autónoma de Puebla +Av. San Claudio y 14 sur. Ciudad Universitaria. +Puebla, Pue., Mexico +Mazatlán, Sin., Mexico +Programa de Ingeniería en Informática +Universidad Politécnica de Sinaloa +Carretera Municipal Libre Mazatlán Higueras Km. 3."
+e5c4b75cb79aa5155ffd9498b3fcc790eb794e72,Object Recognition using Discriminative Robust Local Binary Pattern,"WWW.IJITECH.ORG +ISSN 2321-8665 +Vol.03,Issue.05, +July-2015, +Pages:0700-0706 +Object Recognition using Discriminative Robust Local Binary Pattern +T. LAVANYA +, A. SUJATHA +PG Scholar, Dept of DE & CS, Dr.K.V.Subba Reddy Engineering College for Women, AP, India, +Associate Professor, Dept of DE & CS, Dr.K.V.Subba Reddy Engineering College for Women, AP, India, +E-mail: +E-mail:"
+e5320955580401d5a5b2ae8b507e8f0b47e08118,Deep Supervision with Intermediate Concepts,"Deep Supervision with Intermediate Concepts +Chi Li, M. Zeeshan Zia, Quoc-Huy Tran, Xiang Yu, Gregory D. Hager, and Manmohan Chandraker"
+e5563a0d6a2312c614834dc784b5cc7594362bff,Real-Time Demographic Profiling from Face Imagery with Fisher Vectors,"Noname manuscript No. +(will be inserted by the editor) +Real-Time Demographic Profiling from Face Imagery with +Fisher Vectors +Lorenzo Seidenari · Alessandro Rozza · Alberto Del Bimbo +Received: ... / Accepted: ..."
+e524f222a117890126bd9597934d0504adce85ec,Error Correction for Dense Semantic Image Labeling,"Yu-Hui Huang1∗ Xu Jia2∗ Stamatios Georgoulis1 +Tinne Tuytelaars2 +Luc Van Gool1,3 +KU-Leuven/ESAT-PSI, Toyota Motor Europe (TRACE) +ETH/DITET-CVL +KU-Leuven/ESAT-PSI, IMEC"
e5823a9d3e5e33e119576a34cb8aed497af20eea,DocFace+: ID Document to Selfie Matching,"DocFace+: ID Document to Selfie* Matching Yichun Shi, Student Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
+e596a4aedb5cda6f0df35d38549564a0dd5546a7,Public Document Document Evolution Executive Summary,"Project N° IST-2002-507634 - BioSecure +D 9.1.3 – Revision: b2 +09 June 2006 +Contract Number : +Project Acronym : +Project Title : +Instrument : +Start Date of Project : +Duration : +Deliverable Number : +Title of Deliverable : +Contractual Due Date : +Actual Date of Completion : +IST-2002-507634 +BioSecure +Biometrics for Secure Authentication +Network of Excellence +01 June, 2004 +6 months +D 9.1.3"
+e564268a03b21fa092390db0c11ba1c33d2323f9,Multi-view Stereo with Single-View Semantic Mesh Refinement,"Multi-View Stereo with Single-View Semantic Mesh Refinement +Andrea Romanoni Marco Ciccone +Francesco Visin Matteo Matteucci +{andrea.romanoni, marco.ciccone, francesco.visin, +Politecnico di Milano, Italy"
+e5dcec59afdab7c15e3a874e9b602b8fc42b9019,Nonparametric Video Retrieval and Frame Classification using Tiny Videos,"International Conference on Recent Trends in Computational Methods, Communication and Controls (ICON3C 2012) +Proceedings published in International Journal of Computer Applications® (IJCA) +Nonparametric Video Retrieval and Frame Classification +using Tiny Videos +A.K. M. Shanawas Fathima, +PG Student, +Department of CSE +GCE, Tirunelveli. +R. Kanthavel, +Department of CSE, +Government College of Engineering, +Tirunelveli."
+e59a68c328c69c294991f87b741a5d4e952defba,NISTIR 7972 Performance Metrics for Evaluating Object and Human Detection and Tracking Systems,"This publication is available free of charge from http://dx.doi.org/10.6028/NIST.IR.7972 +NISTIR 7972 +Performance Metrics for Evaluating +Object and Human Detection and +Tracking Systems +Afzal Godil +Roger Bostelman +Will Shackleford +Tsai Hong +Michael Shneier +http://dx.doi.org/10.6028/NIST.IR.7972"
e510f2412999399149d8635a83eca89c338a99a1,Face Recognition using Block-Based DCT Feature Extraction,"Journal of Advanced Computer Science and Technology, 1 (4) (2012) 266-283 (cid:13)Science Publishing Corporation www.sciencepubco.com/index.php/JACST @@ -4747,6 +15958,21 @@ Artur Jord˜ao, Antonio C. Nazare Jr., Jessica Sena and William Robson Schwartz Smart Surveillance Interest Group, Computer Science Department Universidade Federal de Minas Gerais, Brazil Email: {arturjordao, antonio.nazare, jessicasena,"
+e5604c3f61eb7e8b80bf423f7828d8c1fa0f1d32,Towards Image Understanding from Deep Compression without Decoding,"Published as a conference paper at ICLR 2018 +TOWARDS IMAGE UNDERSTANDING FROM +DEEP COMPRESSION WITHOUT DECODING +Robert Torfason +ETH Zurich, Merantix +Fabian Mentzer +ETH Zurich +Eirikur Agustsson +ETH Zurich +Michael Tschannen +ETH Zurich +Radu Timofte +ETH Zurich, Merantix +Luc Van Gool +ETH Zurich, KU Leuven"
e5342233141a1d3858ed99ccd8ca0fead519f58b,Finger print and Palm print based Multibiometric Authentication System with GUI Interface,"ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE) Volume 2, Issue 2, February 2013 @@ -4775,6 +16001,44 @@ the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the Univer The Netherlands. You will be contacted as soon as possible. Download date: 12 Sep 2017 UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl)"
+e5d13afe956d8581a69e9dc2d1f43a43f1e2f311,Automatic Facial Feature Extraction for Face Recognition,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,700 +08,500 +.7 M +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact"
+e58434a01c45505995b000f5e631843a2f2ea582,Scale coding bag of deep features for human attribute and action recognition,"Noname manuscript No. +(will be inserted by the editor) +Scale Coding Bag of Deep Features for Human Attribute +nd Action Recognition +Fahad Shahbaz Khan, Joost van de Weijer, Rao Muhammad Anwer, +Andrew D. Bagdanov, Michael Felsberg, Jorma Laaksonen +Received:"
+e58f08ad6e0edd567f217ef08de1701a8c29fcc8,Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing - and Back,"Pseudo-task Augmentation: From Deep Multitask +Learning to Intratask Sharing—and Back +Elliot Meyerson 1 2 Risto Miikkulainen 1 2"
+e577847c36251dc31282ad57ea969ea8297369be,Face scanning and spontaneous emotion preference in Cornelia de Lange syndrome and Rubinstein-Taybi syndrome,"Crawford et al. Journal of Neurodevelopmental Disorders (2015) 7:22 +DOI 10.1186/s11689-015-9119-4 +R ES EAR CH +Face scanning and spontaneous emotion +preference in Cornelia de Lange syndrome +nd Rubinstein-Taybi syndrome +Hayley Crawford1,2*, Joanna Moss2,3, Joseph P. McCleery4, Giles M. Anderson5 and Chris Oliver2 +Open Access"
e5799fd239531644ad9270f49a3961d7540ce358,Kinship classification by modeling facial feature heredity,"KINSHIP CLASSIFICATION BY MODELING FACIAL FEATURE HEREDITY Ruogu Fang1, Andrew C. Gallagher1, Tsuhan Chen1, Alexander Loui2 Dept. of Elec. and Computer Eng., Cornell University 2Eastman Kodak Company"
@@ -4786,12 +16050,203 @@ Department of Computer Science and Engineering Bangladesh University of Engineering and Technology(BUET) Dhaka-1000, Bangladesh Email: {shafin buet, naim sbh2007,"
+e2b8ba13586bb9a96e4813472d1f763d37ead47d,Media Content Access: Image-Based Filtering,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 9, No. 3, 2018 +Media Content Access: Image-Based Filtering +Rehan Ullah Khan1, Ali Alkhalifah2 +Information Technology Department +Qassim University, Al-Qassim, KSA"
+e2059946b69e0854f21919c1cf13c3f618f48d12,Deep Architectures and Ensembles for Semantic Video Classification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2018 +Deep Architectures and Ensembles for Semantic +Video Classification +Eng-Jon Ong, Sameed Husain, Mikel Bober-Irizar, Miroslaw Bober∗"
+e267c813d8804019fbd8e018171dd05255b10fee,Performance Analysis of Pca Based Techniques for Face Authentication,"Canadian Journal of Pure and Applied Sciences +Vol. 9, No. 1, pp. 3299-3306, February 2015 +Online ISSN: 1920-3853; Print ISSN: 1715-9997 +Available online at www.cjpas.net +PERFORMANCE ANALYSIS OF PCA BASED TECHNIQUES +FOR FACE AUTHENTICATION +*Krishna Dharavath, Fazal Ahmed Talukdar, Rabul Hussain Laskar +Speech and Image Processing Research Lab., +Department of Electronics and Communication Engineering +National Institute of Technology Silchar, India"
+e2edc7e7a2832e2f6014945afce4f76643cab02c,Universität Augsburg An annotated data set for pose estimation of swimmers,"Universit¨at Augsburg +An annotated data set for pose +estimation of swimmers +Thomas Greif and Rainer Lienhart +Report 2009-18 +Januar 2010 +Institut f¨ur Informatik +D-86135 Augsburg"
+e260847323b48a79bd88dd95a1499cd3053d3645,Reconstructing perceived faces from brain activations with deep adversarial neural decoding,"PDF hosted at the Radboud Repository of the Radboud University +Nijmegen +The following full text is a publisher's version. +For additional information about this publication click this link. +http://hdl.handle.net/2066/179505 +Please be advised that this information was generated on 2018-07-04 and may be subject to +hange."
+e27ef52c641c2b5100a1b34fd0b819e84a31b4df,SARC3D: A New 3D Body Model for People Tracking and Re-identification,"SARC3D: a new 3D body model for People +Tracking and Re-identification +Davide Baltieri, Roberto Vezzani, and Rita Cucchiara +Dipartimento di Ingegneria dell’Informazione - University of Modena and Reggio +Emilia, Via Vignolese, 905 - 41125 Modena - Italy"
+e23a75430f777e982b0715b6f8a048d4bbfea438,Maximum Margin Metric Learning over Discriminative Nullspace for Person Re-identification,"Maximum Margin Metric Learning Over Discriminative +Nullspace for Person Re-identification +T M Feroz Ali1 and Subhasis Chaudhuri1 +Indian Institute of Technology Bombay, Mumbai, India"
+e2baf990bc60ef0d24b7556d238e40566ad23d2f,Modified Gabor Filter based Vehicle Verification,"International Journal of Computer Applications® (IJCA) (0975 – 8887) +National Conference cum Workshop on Bioinformatics and Computational Biology, NCWBCB- 2014 +Modified Gabor Filter based Vehicle Verification +Amrutha Ramachandran +Mtech,AE&C, +Dept. of EC, +NCERC,Kerala. +towards +ollision +voidance +ccess,potential"
+e21cdb56c23e2a834a611d51abce545d2e8d01a2,Gender and Identity Classification for a Naive and Evolving System,"Gender and Identity Classification for a Naive and Evolving System +M. Castrill´on-Santana, O. D´eniz-Su´arez, J. Lorenzo-Navarro and M. Hern´andez-Tejera +IUSIANI - Edif. Ctral. del Parque Cient´ıfico Tecnol´ogico +Universidad de Las Palmas de Gran Canaria, Spain"
+e295f31df11ec700851c2413b9bba644a91b0629,3D face reconstruction in a binocular passive stereoscopic system using face properties,"D FACE RECONSTRUCTION IN A BINOCULAR PASSIVE STEREOSCOPIC SYSTEM +USING FACE PROPERTIES +Amel AISSAOUI, Jean MARTINET and Chaabane DJERABA +LIFL UMR Lille1-CNRS n 8022, IRCICA, 50 avenue Halley, 59658 Villeneuve d’Ascq, France"
+e27acf161f569aa876e46ffae2058bb275f12a60,Interactive learning of heterogeneous visual concepts with local features,"Interactive Learning of Heterogeneous Visual Concepts +with Local Features +Wajih Ouertani +INRIA − IMEDIA project +nd INRA, France +Michel Crucianu +INRIA − IMEDIA project +nd CEDRIC − CNAM, France +Nozha Boujemaa +INRIA − IMEDIA project +78153 Le Chesnay, France"
+e2e8db754b1ab4cd8aa07f5c5940f6921a1b7187,Interpretable visual models for human perception-based object retrieval,"Interpretable Visual Models for Human +Perception-Based Object Retrieval +Ahmed Rebai, Alexis Joly, Nozha Boujemaa +To cite this version: +Ahmed Rebai, Alexis Joly, Nozha Boujemaa. +Based Object Retrieval. +trieval, Apr 2011, Trento, +<10.1145/1991996.1992017>. <hal-00642232> +Italy. +Interpretable Visual Models for Human Perception- +ICMR’11 - First ACM International Conference on Multimedia Re- +ACM, pp.21:1–21:8, 2011, <http://www.icmr2011.org/>. +HAL Id: hal-00642232 +https://hal.inria.fr/hal-00642232 +Submitted on 17 Nov 2011 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or"
+e2fc290a245d9f5c545e2e92ee8fcaff4908b97f,Picture-to-Identity linking of social network accounts based on Sensor Pattern Noise,"Picture-to-Identity linking of social network accounts based on +Sensor Pattern Noise +Riccardo Satta∗ and Pasquale Stirparo∗+ +Institute for the Protection and Security of the Citizen, +Joint Research Centre (JRC), European Commission, Ispra (VA), Italy ++Royal Institute of Technology (KTH), Stockholm, Sweden +{riccardo.satta, +Keywords: +linking, digital image forensics +social network, Sensor Pattern Noise, identity,"
e2d265f606cd25f1fd72e5ee8b8f4c5127b764df,Real-Time End-to-End Action Detection with Two-Stream Networks,"Real-Time End-to-End Action Detection with Two-Stream Networks Alaaeldin El-Nouby∗†, Graham W. Taylor∗†‡ School of Engineering, University of Guelph Vector Institute for Artificial Intelligence Canadian Institute for Advanced Research"
+e282bf5a679ca4e8b7d9a2ed56d3b40dc440ab53,Referenceless Quality Estimation for Natural Language Generation,"Referenceless Quality Estimation for Natural Language Generation +Ondˇrej Duˇsek 1 Jekaterina Novikova 1 Verena Rieser 1"
+e24294adfcdb0334c310823c591f15e8829dc224,Deep Neural Networks and Regression Models for Object Detection and Pose Estimation,
+e2279676b01e477b5e7333bab276678f4ad34753,Searching Image with Hash Code Generations,"International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 +Volume: 02 Issue: 05 | Aug-2015 www.irjet.net p-ISSN: 2395-0072 +SEARCHING IMAGE WITH HASH CODE GENERATIONS +R.Lawanya,*2Mrs.G.Sangeetha Lakshmi, 3Ms.A.Sivasankari +,*2,3Department of Computer Science,DKM College for Women, Vellore, +Tamil Nadu, India. +----------------------------------------------------------------------------------------------------------------------"
+e2af85dc41269bc7c50fcf2fb35bfeb75e3d6ee4,xytocin Improves “ Mind-Reading ” in Humans,"PRIORITY COMMUNICATION +Oxytocin Improves “Mind-Reading” in Humans +Gregor Domes, Markus Heinrichs, Andre Michel, Christoph Berger, and Sabine C. Herpertz +Background: The ability to “read the mind” of other individuals, that is, to infer their mental state by interpreting subtle social cues, is +indispensable in human social interaction. The neuropeptide oxytocin plays a central role in social approach behavior in nonhuman +mammals. +Methods: In a double-blind, placebo-controlled, within-subject design, 30 healthy male volunteers were tested for their ability to infer +the affective mental state of others using the Reading the Mind in the Eyes Test (RMET) after intranasal administration of 24 IU oxytocin. +Results: Oxytocin improved performance on the RMET compared with placebo. This effect was pronounced for difficult compared with +easy items. +Conclusions: Our data suggest that oxytocin improves the ability to infer the mental state of others from social cues of the eye region. +Oxytocin might play a role in the pathogenesis of autism spectrum disorder, which is characterized by severe social impairment. +Key Words: Emotion, oxytocin, peptide, social cognition, theory of +T he ability to infer the internal state of another person to +dapt one’s own behavior is a cornerstone of all human +social interactions. Humans have to infer internal states +from external cues such as facial expressions in order to make +sense of or predict another person’s behavior, an ability that is +referred to as “mind-reading” (Siegal and Varley 2002; Stone et al +998). In particular, individuals with autism have distinct diffi-"
+e2afea1a84a5bdbcb64d5ceadaa2249195e1fd82,DOOM Level Generation Using Generative Adversarial Networks,"DOOM Level Generation using Generative +Adversarial Networks +Edoardo Giacomello +Dipartimento di Elettronica, +Informazione e Bioinformatica +Politecnico di Milano +Pier Luca Lanzi +Dipartimento di Elettronica, +Informazione e Bioinformatica +Politecnico di Milano +Daniele Loiacono +Dipartimento di Elettronica, +Informazione e Bioinformatica +Politecnico di Milano"
+e23ed8642a719ff1ab08799257d9566ed3bba403,Unsupervised Visual Attribute Transfer with Reconfigurable Generative Adversarial Networks,"Unsupervised Visual Attribute Transfer with +Reconfigurable Generative Adversarial Networks +Taeksoo Kim, Byoungjip Kim, Moonsu Cha, Jiwon Kim +SK T-Brain"
+e21c45b14d75545d40ed07896f26ec6f766f6a4b,Fisher GAN,"Fisher GAN +Youssef Mroueh∗, Tom Sercu∗ +Equal Contribution +AI Foundations, IBM Research AI +IBM T.J Watson Research Center"
+e22cf1ca10c11991c2a43007e37ca652d8f0d814,A Biologically Inspired Visual Working Memory,"Under review as a conference paper at ICLR 2019 +A BIOLOGICALLY INSPIRED VISUAL WORKING +MEMORY FOR DEEP NETWORKS +Anonymous authors +Paper under double-blind review"
+e21b1c10bee6a984971dcba414c22078dcfd21c2,Recent progress in semantic image segmentation,"Artificial Intelligence Review +https://doi.org/10.1007/s10462-018-9641-3 +Recent progress in semantic image segmentation +Xiaolong Liu1 · Zhidong Deng1 · Yuhan Yang2 +© The Author(s) 2018"
+e2a9b3e9001d57483acbb63dc2cfb91a90d3c12d,"Image worth Evaluation for False Biometric Detection: Submission to Iris, Fingerprint and Face Recognition","Volume 5, Issue 2, February 2015 ISSN: 2277 128X +International Journal of Advanced Research in +Computer Science and Software Engineering +Research Paper +Available online at: www.ijarcsse.com +Image worth Evaluation for False Biometric Detection: Submission to +Iris, Fingerprint and Face Recognition +Boggarapu Srinivasulu, 2 Dr. M. Ekambaram Naidu, 3Dr. E. Sreenivasa Reddy +Assistant Professor, Dept of CSE, Mother Theresa Institute of Engineering & Technology +Palamaner, Chittoor Dist, AP, India +Principal & Professor (CSE), TRR Engineering College, Hyderabad, India +Dean& Professor (CSE), Acharya Nagarjuna University, Nagarjunanagar, Guntur, India"
+f496235629c02c98ad83b37d3d054ccfd0de0131,Learning Cross-Modal Deep Embeddings for Multi-Object Image Retrieval using Text and Sketch,"Learning Cross-Modal Deep Embeddings for +Multi-Object Image Retrieval using Text and Sketch +Sounak Dey, Anjan Dutta, Suman K. Ghosh, Ernest Valveny, Josep Llad´os +Computer Vision Center, Computer Science Department +Autonomous University of Barcelona +Email: {sdey, adutta, sghosh, ernest, +Barcelona, Spain +Umapada Pal +CVPR Unit +Indian Statistical Institute +Kolkata, India +Email:"
f412d9d7bc7534e7daafa43f8f5eab811e7e4148,Running Head : Anxiety and Emotional Faces in WS 2,"Durham Research Online Deposited in DRO: 6 December 2014 @@ -4813,8 +16268,24 @@ to this work since it was submitted for publication. A de nitive version was sub Developmental Disabilities, 34, 12, December 2013, 10.1016/j.ridd.2013.09.042. Additional information:"
f442a2f2749f921849e22f37e0480ac04a3c3fec,Critical Features for Face Recognition in Humans and Machines,"Critical Features for Face Recognition in Humans and Machines Naphtali Abudarham1, Lior Shkiller1, Galit Yovel1,2 1School of Psychological Sciences, 2Sagol School of Neuroscience Tel Aviv University, Tel Aviv, Israel Correspondence regarding this manuscript should be addressed to: Galit Yovel School of Psychological Sciences & Sagol School of Neuroscience Tel Aviv University Tel Aviv, 69978, Israel Email:"
+f4b40b3dc27897fdc40f419a42d64fd1ff80cc9d,A Dual-Source Approach for 3D Human Pose Estimation from a Single Image,"SUBMITTED TO COMPUTER VISION AND IMAGE UNDERSTANDING. +A Dual-Source Approach for 3D Human Pose +Estimation from a Single Image +Umar Iqbal*, Andreas Doering*, Hashim Yasin, Björn Krüger, Andreas Weber, and Juergen Gall"
+f44af3b10a67fe62fd26eb82dd228a3cdeb980e1,"Understand, Compose and Respond - Answering Visual Questions by a Composition of Abstract Procedures","Understand, Compose and Respond +Understand, Compose and Respond - Answering Visual"
f4f6fc473effb063b7a29aa221c65f64a791d7f4,Facial expression recognition in the wild based on multimodal texture features,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 4/20/2018 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use FacialexpressionrecognitioninthewildbasedonmultimodaltexturefeaturesBoSunLiandongLiGuoyanZhouJunHeBoSun,LiandongLi,GuoyanZhou,JunHe,“Facialexpressionrecognitioninthewildbasedonmultimodaltexturefeatures,”J.Electron.Imaging25(6),061407(2016),doi:10.1117/1.JEI.25.6.061407."
+f4ce7c36586c27783a1b0e737c2834f39f9d029d,Advanced non linear dimensionality reduction methods for multidimensional time series : applications to human motion analysis,"Advanced Nonlinear +Dimensionality Reduction +Methods for Multidimensional +Time Series: Application to +Human Motion Analysis +Michał Lewandowski +Submitted in partial fulfilment of the requirements of +Kingston University for the degree of +Doctor of Philosophy +June, 2011"
f4373f5631329f77d85182ec2df6730cbd4686a9,Recognizing Gender from Human Facial Regions using Genetic Algorithm,"Soft Computing manuscript No. (will be inserted by the editor) Recognizing Gender from Human Facial Regions using @@ -4823,6 +16294,29 @@ Avirup Bhattacharyya · Rajkumar Saini · Partha Pratim Roy · Debi Prosad Dogra · Samarjit Kar Received: date / Accepted: date"
+f423e2072441925a16d95e7092005abf602b7145,Survey on 2D and 3D Human Pose Recovery,"Survey on 2D and 3D Human Pose +Recovery +Xavier Perez-Sala, Email: a;c, +Sergio Escalera, Email: b;c and +Cecilio Angulo, Email: a +CETpD-UPC Technical Research Center for Dependency Care and +Autonomous Living, Universitat Polit(cid:18)ecnica de Catalunya, Ne(cid:18)apolis, Rambla de +l’Exposici(cid:19)o, 59-69, 08800 Vilanova i la Geltru, Spain +Dept. Mathematics, Universitat de Barcelona, Gran Via de les Corts Catalanes +Computer Vision Center, Campus UAB, Edi(cid:12)ci 0, 08193, Bellaterra, Spain +585, 08007, Barcelona, Spain"
+f43327075c17e71ee713ad727aa473230a432a90,Geometry meets semantics for semi-supervised monocular depth estimation,"Geometry meets semantics for semi-supervised +monocular depth estimation +Pierluigi Zama Ramirez, Matteo Poggi, Fabio Tosi, +Stefano Mattoccia, and Luigi Di Stefano +University of Bologna, +Viale del Risorgimento 2, Bologna, Italy"
+f439f9a0bd535eab00cbb93c1fa7083615a08d1a,Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications,"Procedural Modeling and Physically Based Rendering for Synthetic Data +Generation in Automotive Applications +Apostolia Tsirikoglou1,∗ Joel Kronander1 Magnus Wrenninge2,† Jonas Unger1,‡ +Link¨oping University, Sweden +7D Labs +Figure 1: Example images produced using our method for synthetic data generation."
f47404424270f6a20ba1ba8c2211adfba032f405,Identification of Face Age range Group using Neural Network,"International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 5, May 2012) Identification of Face Age range Group using Neural @@ -4830,24 +16324,180 @@ Network Sneha Thakur1, Ligendra Verma2 1M.Tech scholar, CSE, RITEE Raipur 2 Reader, MCA dept, RITEE Raipur"
+f4b729d218139f1e93cc9d4df05fbf699d2e9d07,Introduction to the Special Issue on Recent Advances in Biometric Systems [Guest Editorial],"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 37, NO. 5, OCTOBER 2007 +Guest Editorial +Introduction to the Special Issue on Recent +Advances in Biometric Systems +W E ARE pleased to present 14 papers in this special +issue devoted to recent advances in biometric systems. +A total of 78 papers were submitted for consideration for the +special issue. Those that appear in this special issue result from +careful review process and consideration of timing for the +special issue. Other papers, which were originally submitted for +onsideration for the special issue, may be undergoing major +revisions and resubmission and appear at a later time in a +regular issue of this journal or possibly in some other journal. +In particular, several submissions in the area of iris biometrics +ould not be considered for this special issue due to their +experimental results being based primarily on the CASIA 1 +iris image dataset [1]. +Papers on a broad variety of topics were submitted to the +special issue. The large active areas of biometrics such as face, +fingerprint, voice, signature, and iris were naturally well repre-"
+f43b60a33c585827bfa354d3d49fb148a1c26c3f,Identifying Well-formed Natural Language Questions,"Identifying Well-formed Natural Language Questions +Manaal Faruqui Dipanjan Das +Google AI Language"
f4ebbeb77249d1136c355f5bae30f02961b9a359,Human Computation for Attribute and Attribute Value Acquisition,"Human Computation for Attribute and Attribute Value Acquisition Edith Law, Burr Settles, Aaron Snook, Harshit Surana, Luis von Ahn, Tom Mitchell School of Computer Science Carnegie Melon University"
+f445493badf53febbaeab340a4fca98d9e4ab7f7,Do CIFAR-10 Classifiers Generalize to CIFAR-10?,"Do CIFAR-10 Classifiers Generalize to CIFAR-10? +Benjamin Recht +UC Berkeley +Rebecca Roelofs +UC Berkeley +Ludwig Schmidt +Vaishaal Shankar +UC Berkeley +June 4, 2018"
+f4808e78bc648f9e1829c83a68a3e8ed4e7cf325,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
f42dca4a4426e5873a981712102aa961be34539a,Next-Flow: Hybrid Multi-Tasking with Next-Frame Prediction to Boost Optical-Flow Estimation in the Wild,"Next-Flow: Hybrid Multi-Tasking with Next-Frame Prediction to Boost Optical-Flow Estimation in the Wild Nima Sedaghat University of Freiburg Germany"
+f49f1028052baa1588376a78a9dc64812748555e,Feature Fusion using Extended Jaccard Graph and Stochastic Gradient Descent for Robot,"JOURNAL OF LATEX CLASS FILES +Feature Fusion using Extended Jaccard Graph and +Stochastic Gradient Descent for Robot +Shenglan Liu, Muxin Sun, Wei Wang, Feilong Wang"
+f31c9328b5b4678388c19a39064a8056313f7cf4,Two-Stream Multi-Rate Recurrent Neural Network for Video-Based Pedestrian Re-Identification,"IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. XX, NO. XX, AUGUST 201X +Two-Stream Multi-Rate Recurrent Neural +Network for Video-Based Pedestrian +Re-Identification +Zhiqiang Zeng, Zhihui Li*, De Cheng, Huaxiang Zhang, Kun Zhan and Yi Yang"
+f3a34525fa7021322f132c80c9517f240cf1e742,Pose and Pathosformel in Aby Warburg's Bilderatlas,"Pose and Pathosformel in Aby Warburg’s +Bilderatlas +Leonardo Impett, Sabine S¨usstrunk +School of Computer and Communication Sciences, +´Ecole F´ed´erale Polytechnique de Lausanne, Switzerland"
+f34c85c24661ba9990146737fd557f7508677263,A New Pedestrian Detection Descriptor Based on the Use of Spatial Recurrences,"A New Pedestrian Detection Descriptor +Based on the Use of Spatial Recurrences +Carlos Serra-Toro and V. Javier Traver +Departamento de Lenguajes y Sistemas Inform´aticos & +Institute of New Imaging Technologies, +Universitat Jaume I, 12071 Castell´on, Spain"
+f375bc91a5f7b1f2d36e41841ccc22f202be2dcf,Unsupervised Learning of Depth and Ego-Motion from Video,"Unsupervised Learning of Depth and Ego-Motion from Video +Tinghui Zhou∗ +UC Berkeley +Matthew Brown +Google +Noah Snavely +Google +David G. Lowe +Google"
+f3b3d2c0d1d84a7f7bbaaaecb58457c15a947544,Understanding Grounded Language Learning Agents,"UNDERSTANDING GROUNDED LANGUAGE LEARNING +AGENTS +Felix Hill, Karl Moritz Hermann, Phil Blunsom & Stephen Clark +Deepmind +London +{felixhill, kmh, pblunsom,"
+f36647e63a11486ef9cf7a5a1c86a40fda5d408a,CS 229 Final Report: Artistic Style Transfer for Face Portraits,"CS 229 Final Report: Artistic Style Transfer for Face Portraits +Daniel Hsu, Marcus Pan, Chen Zhu +{dwhsu, mpanj, +Dec 16, 2016 +Introduction +The goal of our project is to learn the content and style +representations of face portraits, and then to combine +them to produce new pictures. The content features of +face are the features that identify a face, such as the +outline shape. The stylistic features are the artistic char- +cteristics of a certain portrait or painting, such as brush +strokes, or background color. We forward-pass a content +image, and several style images through a CNN to ex- +tract the desired content and style features. Then we +initialize a white noise image, and perform gradient de- +scent on its pixels until it matches the desired style and +ontent features. +vNet. We hope our project can be a supplement to ex- +isting implementations. +Gradient Descent Loss Functions"
+f36c3ddd43ea7c2e803694aad89e5fd903715c81,"Biometric quality: a review of fingerprint, iris, and face","Bharadwaj et al. EURASIP Journal on Image and Video Processing 2014, 2014:34 +http://jivp.eurasipjournals.com/content/2014/1/34 +REVIEW +Open Access +Biometric quality: a review of fingerprint, iris, +nd face +Samarth Bharadwaj, Mayank Vatsa* and Richa Singh"
f3d9e347eadcf0d21cb0e92710bc906b22f2b3e7,"NosePose: a competitive, landmark-free methodology for head pose estimation in the wild","NosePose: a competitive, landmark-free methodology for head pose estimation in the wild Fl´avio H. B. Zavan, Antonio C. P. Nascimento, Olga R. P. Bellon and Luciano Silva IMAGO Research Group - Universidade Federal do Paran´a"
+f34a6c1bc9a7872c8dc4c35b678f87bb966ab0ab,"PHOG-Derived Aesthetic Measures Applied to Color Photographs of Artworks, Natural Scenes and Objects","PHOG-Derived Aesthetic Measures Applied +to Color Photographs of Artworks, +Natural Scenes and Objects +Christoph Redies2, Seyed Ali Amirshahi1,2, +Michael Koch1,2, and Joachim Denzler1 +Computer Vision Group, Friedrich Schiller University Jena, Germany +http://www.inf-cv.uni-jena.de +Institute of Anatomy I, Friedrich Schiller University, +Jena University Hospital, Germany +http://www.anatomie1.uniklinikum-jena.de"
+f33c427dc152c20537d2857bee1dda2287e85860,Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks,
+f39b88ac61264e9a33dcdf47722f0d048a8e490f,Interactive Data Integration and Entity Resolution for Exploratory Visual Data Analytics,"(cid:13)Copyright 2015 +Kristi Morton"
f3ea181507db292b762aa798da30bc307be95344,Covariance Pooling For Facial Expression Recognition,"Covariance Pooling for Facial Expression Recognition Computer Vision Lab, ETH Zurich, Switzerland VISICS, KU Leuven, Belgium Dinesh Acharya†, Zhiwu Huang†, Danda Pani Paudel†, Luc Van Gool†‡ {acharyad, zhiwu.huang, paudel,"
+f3062992cb10107b9d1e3699c8a61d5281886c4b,Foreground Consistent Human Pose Estimation Using Branch and Bound,"Foreground Consistent Human Pose Estimation +Using Branch and Bound(cid:2) +Jens Puwein1, Luca Ballan1, Remo Ziegler2, and Marc Pollefeys1 +Department of Computer Science, ETH Zurich, Switzerland +Vizrt"
+f3b56b873c48929361c1cada7b18177e3f4d2727,"Development of a N-type GM-PHD Filter for Multiple Target, Multiple Type Visual Tracking","Development of a N-type GM-PHD Filter for +Multiple Target, Multiple Type Visual Tracking +Nathanael L. Baisa , Student Member, IEEE, and Andrew Wallace, Fellow, IET +faced challenges not only in the uncertainty caused by data +ssociation but also in algorithmic complexity that increases +exponentially with the number of targets and measurements. +For instance, the MHT has an exponential complexity with +time and cubic with the number of targets. +To address the problems of increasing complexity, a unified +framework which directly extends single to multiple target +tracking by representing multi-target states and observations +s random finite sets (RFS) was developed by Mahler [7]. +This estimates the states and cardinality of an unknown and +time varying number of targets in the scene, and allows for +target birth, death, handling clutter (false alarms), and missing +detections. Mahler [7] proposed to propagate the first-order +moment of the multi-target posterior, called the Probability +Hypothesis Density (PHD), rather than the full multi-target +posterior."
+f3dc67bb4cd3601ae9bdb7df4ed5036f525ff21d,Multimodal 2 DCNN action recognition from RGB-D Data with Video Summarization,"Master’s Thesis +Multimodal 2DCNN action recognition from +RGB-D Data with Video Summarization +Vicent Roig Ripoll +Master +Artificial Intelligence +Advisor: Sergio Escalera Guerrero +Co-advisor: Maryam Asadi-Aghbolaghi +October, 2017"
+f3ca251ac3b05397ea6d72f2a9a6f0cf619a2a32,Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction,"Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label +Prediction +Charles Corbi`ere1, Hedi Ben-Younes1,2, Alexandre Ram´e1, and Charles Ollion1 +Heuritech, Paris, France +UPMC-LIP6, Paris, France"
f3cf10c84c4665a0b28734f5233d423a65ef1f23,Title Temporal Exemplar-based Bayesian Networks for facialexpression recognition,"Title Temporal Exemplar-based Bayesian Networks for facial expression recognition @@ -4868,21 +16518,74 @@ reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted omponent of this work in other works must be obtained from"
+f32db58cbb8319eb8f2cfa2720c810f8410eb569,A software suite for large-scale video- and image-based analytics,"The 8th International Conference on Bioinspired Information and Communications Technologies (BICT2014), pp. 384-385, Boston, December 1-3, 2014 +A software suite for large-scale video- and image-based +nalytics +Jasmin Léveillé +Isao Hayashi +Kansai University"
+f3f65a8113d6a2dcbc690fd47dfee2dff0f41097,Generating 3D Faces Using Convolutional Mesh Autoencoders,"Generating 3D faces using Convolutional Mesh +Autoencoders +Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, and Michael J. Black +Max Planck Institute for Intelligent Systems +{aranjan, tbolkart, ssanyal, +T¨ubingen, Germany"
f3b7938de5f178e25a3cf477107c76286c0ad691,Object Detection with Deep Learning: A Review,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, MARCH 2017 Object Detection with Deep Learning: A Review Zhong-Qiu Zhao, Member, IEEE, Peng Zheng, Shou-tao Xu, and Xindong Wu, Fellow, IEEE"
+ebd36259defde84deb0d4c09695b54befe538ac8,Robust Generalized Low Rank Approximations of Matrices,"RESEARCH ARTICLE +Robust Generalized Low Rank +Approximations of Matrices +Jiarong Shi*, Wei Yang, Xiuyun Zheng +School of Science, Xi'an University of Architecture and Technology, Xi'an, China"
eb526174fa071345ff7b1fad1fad240cd943a6d7,Deeply vulnerable: a study of the robustness of face recognition to presentation attacks,"Deeply Vulnerable – A Study of the Robustness of Face Recognition to Presentation Attacks Amir Mohammadi, Sushil Bhattacharjee, and S´ebastien Marcel ∗†"
+eb6243b1c9506f9450dab2a09db9c17fc2c2d364,3D Face Recognition system Based on Texture Gabor Features using PCA and Support Vector Machine as a Classifier,"ISSN(Online): 2319-8753 +ISSN (Print): 2347-6710 +International Journal of Innovative Research in Science, +Engineering and Technology +(An ISO 3297: 2007 Certified Organization) +Vol. 5, Issue 8, August 2016 +D Face Recognition system Based on Texture +Gabor Features using PCA and Support +Vector Machine as a Classifier +Rajesh Yadav 1, Dr. Chandra kumarJha 2 +Assistant Professor, Department of Computer Science, Gurgaon Institute of Technology &Management, Gurgaon, +Haryana, India1 +Associate Professor, Department of Computer Science &Engineering, AIM & ACT, Banasthali University, Jaipur, +Rajasthan, India2"
eb566490cd1aa9338831de8161c6659984e923fd,From Lifestyle Vlogs to Everyday Interactions,"From Lifestyle Vlogs to Everyday Interactions David F. Fouhey, Wei-cheng Kuo, Alexei A. Efros, Jitendra Malik EECS Department, UC Berkeley"
+eba31ad9871c6dd5c2e7c62a121bbb417dcb1223,Adaptive Ensemble Selection for Face Re-identification under Class Imbalance,"Adaptive Ensemble Selection for Face +Re-Identification Under Class Imbalance(cid:63) +Paulo Radtke1, Eric Granger1, Robert Sabourin1 and Dmitry Gorodnichy2 +. Laboratoire d’imagerie, de vision et d’intelligence artificielle +´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montreal, Canada +{eric.granger, +. Science and Engineering Directorate, Canada Border Services Agency +Ottawa, Canada,"
eb9312458f84a366e98bd0a2265747aaed40b1a6,Facial Expression Sequence Synthesis Based on Shape and Texture Fusion Model,"-4244-1437-7/07/$20.00 ©2007 IEEE IV - 473 ICIP 2007"
eb716dd3dbd0f04e6d89f1703b9975cad62ffb09, Visual Object Category Discovery in Images and Videos,"Copyright Yong Jae Lee"
+ebc2643567b1c614727cd7ecf1d0604972572568,Robust Subspace Estimation Using Low-rank,"ROBUST SUBSPACE ESTIMATION USING LOW-RANK OPTIMIZATION. +THEORY AND APPLICATIONS IN SCENE RECONSTRUCTION, VIDEO +DENOISING, AND ACTIVITY RECOGNITION. +OMAR OREIFEJ +B.S. University of Jordan, 2006 +M.S. University of Central Florida, 2009 +A dissertation submitted in partial fulfillment of the requirements +for the degree of Doctor of Philosophy +in the Department of Electrical Engineering and Computer Science +in the College of Engineering and Computer Science +t the University of Central Florida +Orlando, Florida +Spring Term +Major Professor: Mubarak Shah"
eb4d2ec77fae67141f6cf74b3ed773997c2c0cf6,A new soft biometric approach for keystroke dynamics based on gender recognition,"Int. J. Information Technology and Management, Vol. 11, Nos. 1/2, 2012 A new soft biometric approach for keystroke dynamics based on gender recognition @@ -4894,6 +16597,9 @@ Fax: +33-231538110 E-mail: E-mail: *Corresponding author"
+eb4edbec8cb122de07951e3cf54c33fc30dd1c19,Examining the Effects of Supervision for Transfer from Synthetic to Real Driving Domains,"Examining the Effects of Supervision for Transfer from Synthetic to Real +Driving Domains +Vashisht Madhavan"
ebb7cc67df6d90f1c88817b20e7a3baad5dc29b9,Fast algorithms for Higher-order Singular Value Decomposition from incomplete data,"Journal of Computational Mathematics Vol.xx, No.x, 200x, 1–25. http://www.global-sci.org/jcm @@ -4903,6 +16609,11 @@ from incomplete data* Department of Mathematics, University of Alabama, Tuscaloosa, AL Yangyang Xu Email:"
+ebabf19e66ef1253fda8d39a0569787c65e60a9e,Multi-person Tracking with Sparse Detection and Continuous Segmentation,"Multi-Person Tracking with Sparse Detection and +Continuous Segmentation +Dennis Mitzel1, Esther Horbert1, Andreas Ess2, Bastian Leibe1 +UMIC Research Centre RWTH Aachen University, Germany +Computer Vision Laboratory, ETH Zurich, Switzerland"
ebabd1f7bc0274fec88a3dabaf115d3e226f198f,Driver Drowsiness Detection System Based on Feature Representation Learning Using Various Deep Networks,"Driver drowsiness detection system based on feature representation learning using various deep networks Sanghyuk Park, Fei Pan, Sunghun Kang and Chang D. Yoo @@ -4917,11 +16628,69 @@ Nenad Markuˇs*, Miroslav Frljak*, Igor S. Pandˇzi´c*, J¨orgen Ahlberg†, an * University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia Link¨oping University, Department of Electrical Engineering, SE-581 83 Link¨oping, Sweden March 28, 2014"
+eb33adf3f8eb5c07b58a1433734ab1fee5d77c93,"Singleton, C. J., Ashwin, C. and Brosnan, M. (2014) Physiological Responses to Social and Nonsocial Stimuli in Neurotypical Adults With High and Low Levels of Autistic Traits:Implications for Understanding Nonsocial Drive in Autism Spectrum","Singleton, C. J., Ashwin, C. and Brosnan, M. (2014) Physiological +Responses to Social and Nonsocial Stimuli in Neurotypical +Adults With High and Low Levels of Autistic Traits:Implications +for Understanding Nonsocial Drive in Autism Spectrum +Disorders. Autism Research, 7 (6). pp. 695-703. ISSN 1939-3792 +Link to official URL (if available): http://dx.doi.org/10.1002/aur.1422 +Opus: University of Bath Online Publication Store +http://opus.bath.ac.uk/ +This version is made available in accordance with publisher policies. +Please cite only the published version using the reference above. +See http://opus.bath.ac.uk/ for usage policies. +Please scroll down to view the document."
+eb0e0a40372db32d30ceaefad046b213fac977f4,Scene Understanding Using Back Propagation by Neural Network,"Scene Understanding Using Back Propagation by Neural Network +SCENE UNDERSTANDING USING BACK PROPAGATION BY +NEURAL NETWORK +ARTI TIWARI1 & JAGVIR VERMA2 +,2Department of Elex & Telecomm. Engg.Chouksey Engg. College,Bilaspur +intelligent human-computer"
+eb0e5db282f88d47b65f98df70c2e7c78b8647a6,Image Provenance Analysis at Scale,"Image Provenance Analysis at Scale +Daniel Moreira, Aparna Bharati, Student Member, IEEE, Joel Brogan, Student Member, IEEE, +Allan Pinto, Student Member, IEEE, Michael Parowski, Kevin W. Bowyer, Fellow, IEEE, +Patrick J. Flynn, Fellow, IEEE, Anderson Rocha, Senior Member, IEEE, +nd Walter J. Scheirer, Senior Member, IEEE"
+eb044760b6502431da6b6f3d5ad11aaab851a1ff,Video Storytelling,"A SUBMISSION TO IEEE TRANSACTIONS ON MULTIMEDIA +Video Storytelling +Junnan Li, Yongkang Wong, Member, IEEE, Qi Zhao, Member, IEEE, Mohan S. Kankanhalli, Fellow, IEEE"
ebf204e0a3e137b6c24e271b0d55fa49a6c52b41,Visual Tracking Using Deep Motion Features,"Master of Science Thesis in Electrical Engineering Department of Electrical Engineering, Linköping University, 2016 Visual Tracking Using Deep Motion Features Susanna Gladh"
+c7774fd600630684cc1d6be8313e2935bb198880,Adapting Hausdorff Metrics to Face Detection Systems: A Scale-Normalized Hausdorff Distance Approach,"Adapting Hausdorff metrics to face detection +systems: a scale-normalized Hausdorff distance +pproach +Pablo Suau +Departamento de Ciencia de la Computaci´on e Inteligencia Artificial +Universidad de Alicante, Ap. de correos 99, 03080, Alicante (Spain)"
+c74a42afeae520ff6ab280d17bccf0d082ba8de5,The Concept of Comprehensive Data Analysis from Ultra-Wideband Subsystem for Smart City Positioning Purposes,"Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 25 October 2018 doi:10.20944/preprints201810.0609.v1 +Article +The Concept of Comprehensive Data Analysis from +Ultra-Wideband Subsystem for Smart City +Positioning Purposes +Damian Grzechca *, Krzysztof Hanzel and Krzysztof Paszek +Faculty of Automatic Control, Electronics and Computer Science, +Silesian University of Technology Gliwice, Poland; +* Correspondence: Tel.: +48-32-237-2717"
+c7fff0d0a6312965b269c6180b2112babd40564c,Unsupervised Person Re-identification: Clustering and Fine-tuning,"Unsupervised Person Re-identification: +Clustering and Fine-tuning +Hehe Fan, Liang Zheng and Yi Yang"
+c726ea46544968335f1e51be633f15d0cc0f0311,Generalized feature learning and indexing for object localization and recognition,"Generalized Feature Learning and Indexing for Object Localization and +Recognition +Ning Zhou∗ +UNC, Charlotte +Anelia Angelova∗ +Google Inc +Jianping Fan +UNC, Charlotte"
+c7ea9611446817f7b668882061ab11c7e998296c,Towards a Crowd Analytic Framework For Crowd Management in Majid-al-Haram,"Towards a Crowd Analytic Framework For Crowd +Management in Majid-al-Haram +Sultan Daud Khan1,*, Muhammad Tayyab1, Muhammad Khurram Amin1, Akram Nour1, +Anas Basalamah1, Saleh Basalamah1, and Sohaib Ahmad Khan1,2,* +Technology Innovation Center, Wadi Makkah, Makkah Al Mukarramah, Saudi Arabia +Science and Technology Unit, Umm Al Qura University, Makkah Al Mukarramah, Saudi Arabia"
c7e4c7be0d37013de07b6d829a3bf73e1b95ad4e,Dynemo: a Video Database of Natural Facial Expressions of Emotions,"The International Journal of Multimedia & Its Applications (IJMA) Vol.5, No.5, October 2013 DYNEMO: A VIDEO DATABASE OF NATURAL FACIAL EXPRESSIONS OF EMOTIONS @@ -4929,6 +16698,60 @@ Anna Tcherkassof1, Damien Dupré1, Brigitte Meillon2, Nadine Mandran2, Michel Dubois1 and Jean-Michel Adam2 LIP, Univ. Grenoble Alpes, BP 47 - 38040 Grenoble Cedex 9, France LIG, Univ. Grenoble Alpes, BP 53 - 38041 Grenoble Cedex 9, France"
+c757f6ee46208c1c26572265803068f8d837c384,Thermal imaging systems for real-time applications in smart cities,"Aalborg Universitet +Thermal Imaging Systems for Real-Time Applications in Smart Cities +Gade, Rikke; Moeslund, Thomas B.; Nielsen, Søren Zebitz; Skov-Petersen, Hans; Andersen, +Hans Jørgen; Basselbjerg, Kent; Dam, Hans Thorhauge; Jensen, Ole B.; Jørgensen, Anders; +Lahrmann, Harry Spaabæk; Madsen, Tanja Kidholm Osmann; Skouboe, Esben Bala; Povey, +Bo Ø. +Published in: +International Journal of Computer Applications in Technology +DOI (link to publication from Publisher): +Publication date: +Document Version +Accepted author manuscript, peer reviewed version +Link to publication from Aalborg University +Citation for published version (APA): +Gade, R., Moeslund, T. B., Nielsen, S. Z., Skov-Petersen, H., Andersen, H. J., Basselbjerg, K., ... Povey, B. Ø. +(2016). Thermal Imaging Systems for Real-Time Applications in Smart Cities. International Journal of Computer +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research."
+c76d143b3fa0d25e21580c583d39ab07fc937e71,Institutionen för systemteknik Department of Electrical Engineering Examensarbete 3 D Position Estimation of a Person of Interest in Multiple Video Sequences : People Detection,"Institutionen för systemteknik +Department of Electrical Engineering +Examensarbete +D Position Estimation of a Person of Interest in +Multiple Video Sequences: People Detection +Examensarbete utfört i Datorseende +vid Tekniska högskolan vid Linköpings universitet +Johannes Markström +LiTH-ISY-EX--13/4721--SE +Linköping 2013 +Department of Electrical Engineering +Linköpings universitet +SE-581 83 Linköping, Sweden +Linköpings tekniska högskola +Linköpings universitet +581 83 Linköping"
+c7eb127e9cd67d645b9a7f59c03bc73183faefeb,Human Detection in Indoor Environments Using Multiple Visual Cues and a Mobile Robot,"Human Detection in Indoor Environments Using +Multiple Visual Cues and a Mobile Robot +Stefan Pszcz´o(cid:2)lkowski and Alvaro Soto +Pontificia Universidad Catolica de Chile +Santiago 22, Chile"
+c70ad19c90491e2de8de686b6a49f9bbe44692c0,Seeing with Humans: Gaze-Assisted Neural Image Captioning,"Seeing with Humans: Gaze-Assisted +Neural Image Captioning +Yusuke Sugano and Andreas Bulling"
+c7c405b6fc95ff2ccf2cb5b59942db4343558fc4,Pseudo 2D Hidden Markov Model Based Face Recognition System Using Singular Values Decomposition Coefficients,"Pseudo 2D Hidden Markov Model Based Face Recognition System Using Singular +Values Decomposition Coefficients +Mukundhan Srinivasan +Department of Electronics & Communication Engineering +Alpha College of Engineering +Chennai, TN India +Sabarigirish Vijayakumar +Retail Domain +Tata Consultancy Services (TCS) +Chennai, TN India"
c7de0c85432ad17a284b5b97c4f36c23f506d9d1,RANSAC-Based Training Data Selection for Speaker State Recognition,"INTERSPEECH 2011 RANSAC-based Training Data Selection for Speaker State Recognition Elif Bozkurt1, Engin Erzin1, C¸ i˘gdem Ero˘glu Erdem2, A.Tanju Erdem3 @@ -4936,6 +16759,14 @@ Multimedia, Vision and Graphics Laboratory, Koc¸ University, Istanbul, Turkey Department of Electrical and Electronics Engineering, Bahc¸es¸ehir University, Istanbul, Turkey Department of Electrical and Computer Engineering, ¨Ozye˘gin University, Istanbul, Turkey ebozkurt,"
+c7f63fc2ff20513c6dc233ec3419417b43b39209,Human Detection from Aerial Imagery for Automatic Counting of Shellfish Gatherers,"Human Detection from Aerial Imagery for Automatic Counting of +Shellfish gatherers +Mathieu Laroze, Luc Courtrai and Sébastien Lefèvre +Univ. Bretagne-Sud, UMR 6074 IRISA +{mathieu.laroze, luc.courtrai, +F-56000, Vannes, France +Keywords: +Human Detection, Image Stitching, Aerial Imagery, Image Mosaicing, Patch Classification, Object Detection"
c7f752eea91bf5495a4f6e6a67f14800ec246d08,Exploring the Transfer Learning Aspect of Deep Neural Networks in Facial Information Processing,"EXPLORING THE TRANSFER LEARNING ASPECT OF DEEP NEURAL NETWORKS IN FACIAL @@ -4945,10 +16776,46 @@ FOR THE DEGREE OF MASTER OF SCIENCE IN THE FACULTY OF ENGINEERING AND PHYSICAL SCIENCES Crefeda Faviola Rodrigues School of Computer Science"
+c7391b43bd0216daf697fb77906b76c71f5c50e2,Where Should You Attend While Driving?,"Where Should You Attend While Driving? +Simone Calderara +Stefano Alletto +Andrea Palazzi∗ +Francesco Solera∗ +Rita Cucchiara +University of Modena and Reggio Emilia"
+c7d7cf88d2e9f3194aec2121eb19dbfed170dba8,Unconstrained Gaze Estimation Using Random Forest Regression Voting,"Unconstrained Gaze Estimation Using Random Forest +Regression Voting +Amine Kacete, Renaud Séguier, Michel Collobert, Jérôme Royan +To cite this version: +Amine Kacete, Renaud Séguier, Michel Collobert, Jérôme Royan. Unconstrained Gaze Estimation +Using Random Forest Regression Voting. Springer. ACCV 13th Asian Conference on Computer +Vision, Nov 2016, Taipei, Taiwan. <http://www.accv2016.org/>. <hal-01393591> +HAL Id: hal-01393591 +https://hal.archives-ouvertes.fr/hal-01393591 +Submitted on 7 Nov 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
c758b9c82b603904ba8806e6193c5fefa57e9613,Heterogeneous Face Recognition with CNNs,"Heterogeneous Face Recognition with CNNs Shreyas Saxena Jakob Verbeek INRIA Grenoble, Laboratoire Jean Kuntzmann"
+c7ecb2ca791fe23c182a06e7700c4e41f5ffa79d,A Review of Sentiment Analysis in Spanish Una Revisión Sobre el Análisis de Sentimientos en Español,"DOI: http://dx.doi.org/10.18180/tecciencia.2017.22.5 +A Review of Sentiment Analysis in Spanish +Una Revisión Sobre el Análisis de Sentimientos en Español +Carlos Henríquez Miranda1*, Jaime Guzmán2 +Universidad Autónoma, Barranquilla, Colombia +Universitario Nacional de Colombia, Bogotá, Colombia +Received: 11 Dec 2015 +Accepted: 6 Sep 2016 +Available Online: 7 Dec 2016"
c7c03324833ba262eeaada0349afa1b5990c1ea7,A Wearable Face Recognition System on Google Glass for Assisting Social Interactions,"A Wearable Face Recognition System on Google Glass for Assisting Social Interactions Bappaditya Mandal∗, Chia Shue Ching, Liyuan Li, Vijay Ramaseshan @@ -4956,6 +16823,54 @@ Chandrasekhar, Cheston Tan Yin Chet and Lim Joo Hwee Visual Computing Department, Institute for Infocomm Research, Singapore Email address: (∗Contact author: Bappaditya Mandal); {scchia, lyli, vijay, cheston-tan,"
+c72914e2e999c99753d1d0058c459af69af6662a,CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation,"MACKOWIAK ET AL.: CEREALS +CEREALS – Cost-Effective REgion-based +Active Learning for Semantic Segmentation +Robert Bosch GmbH +Corporate Research - Computer Vision +Robert-Bosch-Straße 200 +1139 Hildesheim, DE +Heidelberg Collaboratory for Image +Processing (HCI) +Berliner Straße 43, +69120 Heidelberg, DE +Radek Mackowiak1 +Philip Lenz1 +Omair Ghori1 +Ferran Diego1 +Oliver Lange1 +Carsten Rother2"
+c719a718073128a985c957cdfa3f298706a180e6,Comparative Evaluations of Selected Tracking-by-Detection Approaches,"Comparative Evaluations of Selected +Tracking-by-Detection Approaches +Alhayat Ali Mekonnen, Frédéric Lerasle +To cite this version: +Alhayat Ali Mekonnen, Frédéric Lerasle. Comparative Evaluations of Selected Tracking-by-Detection +Approaches. IEEE Transactions on Circuits and Systems for Video Technology, Institute of Electrical +nd Electronics Engineers, 2018, <10.1109/TCSVT.2018.2817609>. <hal-01815850> +HAL Id: hal-01815850 +https://hal.laas.fr/hal-01815850 +Submitted on 14 Jun 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+c737e65d7e8696f5a2878ac623c61aeff434f92d,The influences of face inversion and facial expression on sensitivity to eye contact in high-functioning adults with autism spectrum disorders.,"J Autism Dev Disord (2013) 43:2536–2548 +DOI 10.1007/s10803-013-1802-2 +O R I G I N A L P A P E R +The Influences of Face Inversion and Facial Expression +on Sensitivity to Eye Contact in High-Functioning Adults +with Autism Spectrum Disorders +Mark D. Vida • Daphne Maurer • Andrew J. Calder • +Gillian Rhodes • Jennifer A. Walsh • +Matthew V. Pachai • M. D. Rutherford +Published online: 8 March 2013 +Ó Springer Science+Business Media New York 2013"
c7c8d150ece08b12e3abdb6224000c07a6ce7d47,DeMeshNet: Blind Face Inpainting for Deep MeshFace Verification,"DeMeshNet: Blind Face Inpainting for Deep MeshFace Verification National Laboratory of Pattern Recognition, CASIA Center for Research on Intelligent Perception and Computing, CASIA @@ -4969,6 +16884,34 @@ China Nong Sang China Email:"
+c7742e63579cfea8655606ec6bd9047140efe96a,D and Pseudo-2d Hidden Markov Models for Image Analysis. Theoretical Introduction 1d and Pseudo-2d Hidden Markov Models for Image Analysis. Theoretical Introduction,"D and Pseudo-D Hidden Markov Models +for Image Analysis. +Theoretical Introduction +ephane Marchand-Maillet - Multimedia Communications +Email: +Phone: + +Date: November +Technical Report RR- - Part A +Con +ecom’s research is partially supported by its industrial members: +Ascom, Cegetel, France Telecom, Hitachi, IBM France, Motorola, +Swisscom, Texas Instruments, and Thomson CSF. +Multimedia Communications +Institut EURECOM BP . + +T.R. RR- - Part A November +c0e5a471179d2d8c7025febe77a90c3a99c7c9fa,Learning With ℓ1-Graph for Image Analysis,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 19, NO. 4, APRIL 2010 +Learning With `1-Graph for Image Analysis +Bin Cheng, Jianchao Yang, Student Member, IEEE, Shuicheng Yan, Senior Member, IEEE, Yun Fu, Member, IEEE, +nd Thomas S. Huang, Life Fellow, IEEE"
+c0014e048a5d15ddfeffa075a1b819bcb93dd351,Simple and Efficient Visual Gaze Estimation,"Simple and Efficient Visual Gaze Estimation +Roberto Valenti +Nicu Sebe +Intelligent Systems Lab +Amsterdam +Kruislaan 403, 1018SJ +Amsterdam, The Netherlands +Theo Gevers"
c03f48e211ac81c3867c0e787bea3192fcfe323e,Mahalanobis Metric Scoring Learned from Weighted Pairwise Constraints in I-Vector Speaker Recognition System,"INTERSPEECH 2016 September 8–12, 2016, San Francisco, USA Mahalanobis Metric Scoring Learned from Weighted Pairwise Constraints in @@ -4995,6 +16938,80 @@ COLLECTION OF BIOMETRICS Paul C. Clark, Heather S. Gregg, with preface by Cynthia E. Irvine April 2011 Approved for public release; distribution is unlimited"
+c0f17f99c44807762f2a386ac6579c364330e082,A Review on Deep Learning Techniques Applied to Semantic Segmentation,"A Review on Deep Learning Techniques +Applied to Semantic Segmentation +A. Garcia-Garcia, S. Orts-Escolano, S.O. Oprea, V. Villena-Martinez, and J. Garcia-Rodriguez"
+c0a0adb7f02d5509969e6107c914f7cc6e9ec881,Semantic Instance Segmentation via Deep Metric Learning,"Semantic Instance Segmentation via Deep Metric Learning +Alireza Fathi∗ +Zbigniew Wojna∗ +Vivek Rathod∗ +Peng Wang† +Sergio Guadarrama∗ +Kevin P. Murphy∗ +Hyun Oh Song∗"
+c08420b1bfa093e89e35e3b8d3a9e3e881f4f563,A Classification Framework for Large-Scale Face Recognition Systems,"Kent Academic Repository +Full text document (pdf) +Citation for published version +Zhou, Ziheng and Deravi, Farzin (2009) A Classification Framework for Large-Scale Face Recognition +Systems. In: 3rd IAPR/IEEE International Conference on Biometrics, 2-5 June, University of +Sassari, Italy. +https://doi.org/10.1007/978-3-642-01793-3_35 +Link to record in KAR +http://kar.kent.ac.uk/23302/ +Document Version +Author's Accepted Manuscript +Copyright & reuse +Content in the Kent Academic Repository is made available for research purposes. Unless otherwise stated all +ontent is protected by copyright and in the absence of an open licence (eg Creative Commons), permissions +for further reuse of content should be sought from the publisher, author or other copyright holder. +Versions of research +The version in the Kent Academic Repository may differ from the final published version. +Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the +published version of record. +Enquiries"
+c03c16668426d8b069e75cb440686e12a9adbcd7,Deep Unsupervised Similarity Learning Using Partially Ordered Sets,"Deep Unsupervised Similarity Learning using Partially Ordered Sets +Miguel A. Bautista∗ , Artsiom Sanakoyeu∗ , Bj¨orn Ommer +Heidelberg Collaboratory for Image Processing +IWR, Heidelberg University, Germany"
+c0de99c5f15898e2d28f9946436fec2b831d4eae,ClothCap: seamless 4D clothing capture and retargeting,"ClothCap: Seamless 4D Clothing Capture and Retargeting +GERARD PONS-MOLL∗, Max Planck Institute for Intelligent Systems, Tübingen, Germany +SERGI PUJADES∗, Max Planck Institute for Intelligent Systems, Tübingen, Germany +SONNY HU, Body Labs, New York, NY, USA +MICHAEL J. BLACK, Max Planck Institute for Intelligent Systems, Tübingen, Germany +Fig. 1. ClothCap. From left to right: (1) An example 3D textured scan that is part of a 4D sequence. (2) Our multi-part aligned mesh model, layered over the +ody. (3) The estimated minimally clothed shape (MCS) under the clothing. (4) The body made fatter and dressed in the same clothing. Note that the clothing +dapts in a natural way to the new body shape. (5) This new body shape posed in a new, never seen, pose. This illustrates how ClothCap supports a range of +pplications related to clothing capture, modeling, retargeting, reposing, and try-on. +Dressing virtual avatars and animating them with high quality, visu- +lly plausible, results is a challenging task. Highly realistic physical +simulation of clothing on human bodies in motion is complex: cloth- +ing models are laborious to construct, patterns must be graded so +that they can be sized to different characters, and the physical param- +eters of the cloth must be known. Instead, we propose a data-driven +lothing capture (ClothCap) approach; we capture dynamic clothing +on humans from 4D scans and transform it to more easily dress +virtual avatars. +INTRODUCTION +Designing and simulating realistic clothing is challenging. Previous methods"
+c0afa514524a4cf4b1772c1738ceb6989bff1b71,Impact of Tone-mapping Algorithms on Subjective and Objective Face Recognition in HDR Images,"Impact of Tone-mapping Algorithms on Subjective and +Objective Face Recognition in HDR Images +Pavel Korshunov +MMSPG, EPFL +Marco V. Bernardo +Optics Center, UBI +Touradj Ebrahimi +MMSPG, EPFL +António M. G. Pinheiro +Optics Center, UBI"
+c08ef9ebf46e5a88c4ee1aa64dac104ddc07bee2,Classification of vehicles for urban traffic scenes,"Classification of Vehicles +for Urban Traffic Scenes +Norbert Erich Buch +Submitted in partial fulfilment of the requirements of +Kingston University for the degree of +Doctor of Philosophy +June, 2010 +Collaborating partner: +Traffic Directorate at Transport for London"
c0ff7dc0d575658bf402719c12b676a34271dfcd,A New Incremental Optimal Feature Extraction Method for On-Line Applications,"A New Incremental Optimal Feature Extraction Method for On-line Applications Youness Aliyari Ghassabeh, Hamid Abrishami Moghaddam @@ -5020,10 +17037,59 @@ installed near coast and mountain hill where falcons and seagulls will be the ma will classify the minority eagles out of other bird species during the immigration season and protecting them by using the deterrent system. .2 Brief Approach"
+c03ef6e94808185c1080ac9b155ac3b159b4f1ec,Learning to Avoid Errors in GANs by Manipulating Input Spaces,"Learning to Avoid Errors in GANs by Manipulating +Input Spaces +Alexander B. Jung +TU Dortmund"
+c038186138b76a625500ff84c9dadb18aae29f1c,Learning Implicit Transfer for Person Re-identification,"Learning Implicit Transfer +for Person Re-identi(cid:12)cation +Tamar Avraham, Ilya Gurvich, Michael Lindenbaum, and Shaul Markovitch +Computer science department, Technion - I.I.T., Haifa 32000, Israel."
+c02dbf756b9e9e2bed37cb7d295529397cad616a,Semantic Segmentation of RGBD Videos with Recurrent Fully Convolutional Neural Networks,"Semantic Segmentation of RGBD Videos with Recurrent Fully Convolutional +Neural Networks +Ekrem Emre Yurdakul, Y¨ucel Yemez +Computer Engineering Department, Koc¸ University +Istanbul, Turkey"
+c082afd5928165ccaf6d419aff5d0456d8ef78f3,Face recognition by fusing binary edge feature and second-order mutual information,"Face Recognition by Fusing Binary Edge Feature and +Second-order Mutual Information +Jiatao Song, Beijing Chen, Wei Wang, Xiaobo Ren +School of Electronic and Information Engineering, +Ningbo University of Technology +Ningbo, China"
+c0be23ae7f327f9415e583aee1936b9932c9b58b,Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data,"NetworkCNNimageslabelsFakeDatasetimages24132labelsTarget NetworkCNNimageslabelsOriginalDatasetFakeDatasetFig.1:Ontheleft,thetargetnetworkistrainedwithanoriginal(confidential)datasetandisservedpubliclyasanAPI,receivingimagesasinputandprovidingclasslabelsasoutput.Ontheright,itispresentedtheprocesstogetstolenlabelsandtocreateafakedataset:randomnaturalimagesaresenttotheAPIandthelabelsareobtained.Afterthat,thecopycatnetworkistrainedusingthisfakedataset.cloud-basedservicestocustomersallowingthemtooffertheirownmodelsasanAPI.Becauseoftheresourcesandmoneyinvestedincreatingthesemodels,itisinthebestinterestofthesecompaniestoprotectthem,i.e.,toavoidthatsomeoneelsecopythem.Someworkshavealreadyinvestigatedthepossibilityofcopyingmodelsbyqueryingthemasablack-box.In[1],forexample,theauthorsshowedhowtoperformmodelextractionattackstocopyanequivalentornear-equivalentmachinelearningmodel(decisiontree,logisticregression,SVM,andmultilayerperceptron),i.e.,onethatachievescloseto100%agreementonaninputspaceofinterest.In[2],theauthorsevaluatedtheprocessofcopyingaNaiveBayesandSVMclassifierinthecontextoftextclassification.Bothworksfocusedongeneralclassifiersandnotondeepneuralnetworksthatrequirelargeamountsofdatatobetrainedleavingthequestionofwhetherdeepmodelscanbeeasilycopied.Althoughthesecondusesdeeplearningtostealtheclassifiers,itdoesnottrytouseDNNstostealfromdeepmodels.Additionally,theseworksfocusoncopyingbyqueryingwithproblemdomaindata.Inrecentyears,researchershavebeenexploringsomeintriguingpropertiesofdeepneuralnetworks[3],[4].More©2018IEEE.Personaluseofthismaterialispermitted.PermissionfromIEEEmustbeobtainedforallotheruses,inanycurrentorfuturemedia,includingreprinting/republishingthismaterialforadvertisingorpromotionalpurposes,creatingnewcollectiveworks,forresaleorredistributiontoserversorlists,orreuseofanycopyrightedcomponentofthisworkinotherworks."
c0c8d720658374cc1ffd6116554a615e846c74b5,Modeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 Modeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification Yu-Gang Jiang, Zuxuan Wu, Jinhui Tang, Zechao Li, Xiangyang Xue, Shih-Fu Chang"
+c06447df3e50ec451240205cefa0708caee8ab8c,Picture it in your mind: generating high level visual representations from textual descriptions,"Picture It In Your Mind: Generating High Level Visual +Representations From Textual Descriptions +Fabio Carrara +ISTI-CNR +via G. Moruzzi, 1 +56124 Pisa, Italy +Andrea Esuli +ISTI-CNR +via G. Moruzzi, 1 +56124 Pisa, Italy +Tiziano Fagni +ISTI-CNR +via G. Moruzzi, 1 +56124 Pisa, Italy +Fabrizio Falchi +ISTI-CNR +via G. Moruzzi, 1 +56124 Pisa, Italy +Alejandro Moreo +Fernández"
+c0e9d06383442d89426808d723ca04586db91747,Cascaded SR-GAN for Scale-Adaptive Low Resolution Person Re-identification,Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18)
+c04fec95a448f9b01dd4399b3a5a365f67448bdf,From Image Sequence to Frontal Image: Reconstruction of the Unknown Face A Forensic Case,"From Image Sequence to Frontal Image: +Reconstruction of the Unknown Face +A Forensic Case +Christiaan van Dam"
+c0d21722d83c126af4175add38ffc893a33ee01e,Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor,"Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor +Wongun Choi +NEC Laboratories America +0080 N. Wolfe Rd, Cupertino, CA, USA"
eee8a37a12506ff5df72c402ccc3d59216321346,Volume C,"Uredniki: dr. Tomaž Erjavec Odsek za tehnologije znanja @@ -5044,9 +17110,54 @@ Informacijska družba ISSN 1581-9973 CIP - Kataložni zapis o publikaciji Narodna in univerzitetna knjižnica, Ljubljana"
+eea77e2a891e49e65d4bed54c1b24411f33203a3,Exploring Guide Context in City Scenario Using Color and Gradient Features,"The Open Construction and Building Technology Journal, 2015, 9, 177-181 +Open Access +Exploring Guide Context in City Scenario Using Color and Gradient +Features +Send Orders for Reprints to +Zhuo Bian* +Art Academy of Northeast Agriculture University, Harbin 150001, China"
+ee4fd1a1df6a01e7dabe82090b1024e2eb6d78a1,Effective Emotional Classification Combining Facial Classifiers and User Assessment,"Effective Emotional Classification Combining Facial +Classifiers and User Assessment +Isabelle Hupont1, Sandra Baldassarri2, Rafael Del Hoyo1, and Eva Cerezo2 +Instituto Tecnológico de Aragón, Zaragoza (Spain) +Departamento de Informática e Ingeniería de Sistemas, +Instituto de Investigación en Ingeniería de Aragón, Universidad de Zaragoza (Spain)"
+ee87aa52d9642607d86f011c0d7326c4bdc63121,Automatic Detection of Facial Midline as a Guide for Facial Feature Extraction,"Automatic Detection of Facial Midline +s a Guide for Facial Feature Extraction +Nozomi Nakao, Wataru Ohyama, Tetsushi Wakabayashi and Fumitaka Kimura +Graduate School of Engineering, Mie University +577 Kurimamachiya-cho, Tsu-shi, Mie, 5148507, Japan"
+eed25d9b5b5b28e8454a359d54c9de5a05cc4682,Context-aware home monitoring system for Parkinson ' s disease patients : ambient and wearable sensing for freezing of gait detection,"Context-aware Home Monitoring System +for Parkinson’s Disease Patients +Ambient and Wearable Sensing for Freezing of Gait Detection +B(cid:2456)(cid:2459)(cid:2450)(cid:2460) T(cid:2442)(cid:2452)(cid:2442)(cid:20)(cid:2444)"
+eeec69e910430bebe3808773f5a6a155d77059a0,Multi-shot Pedestrian Re-identification via Sequential Decision Making,"Multi-shot Pedestrian Re-identification via Sequential Decision Making +Jianfu Zhang1, Naiyan Wang2 and Liqing Zhang1 +Shanghai Jiao Tong University∗, 2TuSimple"
ee18e29a2b998eddb7f6663bb07891bfc7262248,Local Linear Discriminant Analysis Framework Using Sample Neighbors,"Local Linear Discriminant Analysis Framework Using Sample Neighbors Zizhu Fan, Yong Xu, Member, IEEE, and David Zhang, Fellow, IEEE"
+ee3a905ec8cd2e62dc642fad33d6f5f8516968a8,It depends: Approach and avoidance reactions to emotional expressions are influenced by the contrast emotions presented in the task.,"tapraid5/zfn-xhp/zfn-xhp/zfn00515/zfn3313d15z +xppws S⫽1 +8/4/15 +5:44 Art: 2014-0213 +APA NLM +Journal of Experimental Psychology: +Human Perception and Performance +015, Vol. 41, No. 5, 000 +0096-1523/15/$12.00 +© 2015 American Psychological Association +http://dx.doi.org/10.1037/xhp0000130 +It Depends: Approach and Avoidance Reactions to Emotional Expressions +re Influenced by the Contrast Emotions Presented in the Task +AQ: au +Andrea Paulus and Dirk Wentura +Saarland University +Studies examining approach and avoidance reactions to emotional expressions have yielded conflicting +results. For example, expressions of anger have been reported to elicit approach reactions in some studies +ut avoidance reactions in others. Nonetheless, the results were often explained by the same general +underlying process, namely the influence that the social message signaled by the expression has on"
eefb8768f60c17d76fe156b55b8a00555eb40f4d,Subspace Scores for Feature Selection in Computer Vision,"Subspace Scores for Feature Selection in Computer Vision Cameron Musco Christopher Musco"
@@ -5060,6 +17171,34 @@ Deepak S. Turaga and Tsuhan Chen Video and Display Processing Philips Research USA Briarcliff Manor, NY 10510"
+ee335fb785c332b1ac43565b007461002616f1e0,Processing Large Amounts of Images on Hadoop with OpenCV,"Processing Large Amounts of Images +on Hadoop with OpenCV +Timofei Epanchintsev1,2 and Andrey Sozykin1,2 +IMM UB RAS, Yekaterinburg, Russia, +Ural Federal University, Yekaterinburg, Russia"
+eebe66c4d1a41b3c7830846306044c8f3fe0d350,Domain adaptation networks for noisy image classification,"Faculty of Electrical Engineering, Mathematics and Computer Science +Department of Intelligent Systems +Domain adaptation +networks for noisy image +lassification +Master Thesis +Chengqiu Zhang +Committee: +Supervisors: +Dr. Jan van Gemert +Prof. Martha Larson +Dr. Silvia-Laura Pintea Dr. Jan van Gemert +Dr. Ildiko Suveg +Dr. Marco Loog +Dr. Silvia-Laura Pintea +Dr. Adriana Gonzalez +Eindhoven, Aug 2017"
+ee9385efb66ee0b1bee31c1632141729bb7fb6f5,Numerical simplification for bloat control and analysis of building blocks in genetic programming,"Noname manuscript No. +(will be inserted by the editor) +Numerical Simplification for Bloat Control and Analysis of +Building Blocks in Genetic Programming +David Kinzett · Mark Johnston · Mengjie Zhang +the date of receipt and acceptance should be inserted later"
eedfb384a5e42511013b33104f4cd3149432bd9e,Multimodal probabilistic person tracking and identification in smart spaces,"Multimodal Probabilistic Person Tracking and Identification in Smart Spaces @@ -5076,25 +17215,253 @@ Erster Gutachter: Zweiter Gutachter: Prof. Dr. A. Waibel Prof. Dr. R. Stiefelhagen"
+c9f3a5fe33782dd486cb32d9667fba0514711f04,Face and Expression Recognition Using Local Directional Number Pattern,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Impact Factor (2012): 3.358 +Face and Expression Recognition Using Local +Directional Number Pattern +Gopu Prasoona1, Dasu Vaman Ravi Prasad2 +Computer Science, CVSR College of Engineering, Venkatapur, RR dist, India +Computer Science and Engineering, CVSR College of Engineering, Venkatapur, RR dist, India +refers +to digital"
c91103e6612fa7e664ccbc3ed1b0b5deac865b02,Automatic Facial Expression Recognition Using Statistical-Like Moments,"Automatic facial expression recognition using statistical-like moments Roberto D’Ambrosio, Giulio Iannello, and Paolo Soda {r.dambrosio, g.iannello, Integrated Research Center, Universit`a Campus Bio-Medico di Roma, Via Alvaro del Portillo, 00128 Roma, Italy"
+c92e701c908908bda407f12edf6984b283e8c258,Where Should You Attend While Driving?,"Where Should You Attend While Driving? +Simone Calderara +Stefano Alletto +Andrea Palazzi∗ +Francesco Solera∗ +Rita Cucchiara +University of Modena and Reggio Emilia"
+c90b109301244e59771fec431a8d50a78e395956,Alternative face models for 3D face registration,"Alternative face models for 3D face registration +Albert Ali Salah, Ne¸se Aly¨uz, Lale Akarun +Bo˘gazi¸ci University, 34342 Bebek, ˙Istanbul, Turkey"
+c9876861cc0e33fffe8c3ce7484ae27d3b2eeb75,A Corpus for Analyzing Linguistic and Paralinguistic Features in Multi-Speaker Spontaneous Conversations – EVA Corpus,"A Corpus for Analyzing Linguistic and Paralinguistic Features in +Multi-Speaker Spontaneous Conversations – EVA Corpus +IZIDOR MLAKAR, ZDRAVKO KAČIČ, MATEJ ROJC +Faculty of Electrical Engineering and Computer Science, University of Maribor +SLOVENIA"
+c9c3ba7bebee553490a9ddbc6840292ed5aed90b,SCHOOL OF COMPUTER ENGINEERING PhD Confirmation Report on Object Detection in Real Images,"SCHOOL OF COMPUTER ENGINEERING +PhD Confirmation Report +Object Detection in Real Images +Submitted by: Dilip Kumar Prasad +Research Student (PhD) +School of Computer Engineering +E-mail: +Supervisor: Dr. Maylor K. H. Leung +Associate Professor, +School of Computer Engineering +E-mail: +August 2010"
+c933c4bef57be3585abb13bacb74aca29588a6ac,People Detection in Color and Infrared Video Using HOG and Linear SVM,"People Detection in Color and Infrared Video +using HOG and Linear SVM +Pablo Tribaldos1, Juan Serrano-Cuerda1, Mar´ıa T. L´opez1;2, +Antonio Fern´andez-Caballero1;2, and Roberto J. L´opez-Sastre3 +Instituto de Investigaci(cid:19)on en Inform(cid:19)atica de Albacete (I3A), 02071-Albacete, Spain +Universidad de Castilla-La Mancha, Departamento de Sistemas Inform(cid:19)aticos, +02071-Albacete, Spain +Universidad de Alcal(cid:19)a, Dpto. de Teor(cid:19)(cid:16)a de la se~nal y Comunicaciones, +8805-Alcal(cid:19)a de Henares (Madrid), Spain"
+c9b90cf9cdd901bd3072d6dfd8ddc523c55944b1,Adversarial Generator-Encoder Networks,"Adversarial Generator-Encoder Networks +Dmitry Ulyanov 1 2 Andrea Vedaldi 3 Victor Lempitsky 1"
+c94c2cf52fef0503c09268c7d1faee60465ee08e,BenchIP: Benchmarking Intelligence Processors,"BENCHIP: Benchmarking Intelligence +Processors +Jinhua Tao1, Zidong Du1,2, Qi Guo1,2, Huiying Lan1, Lei Zhang1 +Shengyuan Zhou1, Lingjie Xu3, Cong Liu4, Haifeng Liu5, Shan Tang6 +Allen Rush7,Willian Chen7, Shaoli Liu1,2, Yunji Chen1, Tianshi Chen1,2 +ICT CAS,2Cambricon,3Alibaba Infrastructure Service, Alibaba Group +IFLYTEK,5JD,6RDA Microelectronics,7AMD"
+c9d7219d54eccb9e49b72044d805e103fe17ba80,Towards Information-Seeking Agents,"Under review as a conference paper at ICLR 2017 +TOWARDS INFORMATION-SEEKING AGENTS +Philip Bachman∗ +phil.bachman +Alessandro Sordoni∗ +lessandro.sordoni +Adam Trischler +dam.trischler +Maluuba Research +Montréal, QC, Canada"
+c95c30fb990576704f2ccb3dc3335aaf43208856,CS231A Project report,"CS231A Project report +Cecile Foret +March 19, 2014."
+c95d8b9bddd76b8c83c8745747e8a33feedf3941,Image Ordinal Classification and Understanding: Grid Dropout with Masking Label,"label:(1, 0, 1, 0, 1, 1, 1, 1, 1)Masking label:(0, 1, 1, 1, 0, 1, 1, 1, 1)Entire imageInput imageNeuron dropout’s gradCAMGrid dropout’s gradCAMFig.1.Above:imageordinalclassificationwithrandomlyblackoutpatches.Itiseasyforhumantorecognizetheageregardlessofthemissingpatches.Themaskinglabelisalsousefultoimageclassification.Bottom:griddropout’sgrad-CAMisbetterthanthatofneurondropout.Thatistosay,griddropoutcanhelplearningfeaturerepresentation.problem[1].Withtheproliferationofconvolutionalneuralnetwork(CNN),workshavebeencarriedoutonordinalclas-sificationwithCNN[1][2][3].Thoughgoodperformanceshavebeenloggedwithmoderndeeplearningapproaches,therearetwoproblemsinimageordinalclassification.Ononehand,theamountofordinaltrainingdataisverylim-itedwhichprohibitstrainingcomplexmodelsproperly,andtomakemattersworse,collectinglargetrainingdatasetwithordinallabelisdifficult,evenharderthanlabellinggenericdataset.Therefore,insufficienttrainingdataincreasestheriskofoverfitting.Ontheotherhand,lessstudiesareconductedtounderstandwhatdeepmodelshavelearnedonordinaldata978-1-5386-1737-3/18/$31.00c(cid:13)2018IEEE"
+c924137ca87e8b4e1557465405744f8b639b16fc,Seeding Deep Learning using Wireless Localization,"ADDRESSING TRAINING BIAS VIA AUTOMATED IMAGE ANNOTATION +Zhujun Xiao 1 Yanzi Zhu 2 Yuxin Chen 1 Ben Y. Zhao 1 Junchen Jiang 1 Haitao Zheng 1"
+c936b9a958a67cdd5665b923569d9d786c934029,Software Specification Document For,"Software Specification +Document +Crowd_Count++ +Version 1.0 +November 2015 +Juan Mejia Michael Safdieh Rosario Antunez +Prepared by:"
+c9bbf31afbec278ca735e91cf5e9c70dd3aa41a4,Enhancing 3D Face Recognition By Mimics Segmentation,"Enhancing 3D Face Recognition By Mimics Segmentation +Boulbaba Ben Amor, Mohsen Ardabilian, and Liming Chen +MI Department, LIRIS Laboratory, CNRS 5205 +Ecole Centrale de Lyon, 36 av. Guy de Collongue, 69134 Lyon , France +{Boulbaba.Ben-Amor, Mohsen.Ardabilian,"
+c94ae3d1c029a70cabdab906fe1460d84fd42acd,"Comparison of wavelet, Gabor and curvelet transform for face recognition","Optica Applicata, Vol. XLI, No. 1, 2011 +Comparison of wavelet, Gabor and curvelet +transform for face recognition +JIULONG ZHANG, YINGHUI WANG, ZHIYU ZHANG, CHUNLI XIA +Computer Science and Engineering School, Xian University of Technology, +Xi'an, 710048, P.R. China +There has been much research about using Gabor wavelet for face recognition. Other multiscale +geometrical tools, such as curvelet and contourlet, have also been used for face recognition, thus +it is interesting to know which method performs best, especially under illumination and expression +hanges. In this paper, we make a systematic comparison of wavelet, Gabor and curvelet for +recognition, and find the best subband irrelevant to expression and illumination changes. We +ombine the multiscale analysis with subspace decomposition as our algorithm. Experiments show +that for expression changes, the properties of the coarse layer of curvelet and wavelet are very +good. Whilst for illumination changes, the low frequency parts of the two methods are similarly +influenced, but the detail coefficients of curvelet and the high frequency of wavelet work fine with +PCA, with the former outperforming the latter. When these two factors change simultaneously, +the detail layer of curvelet is better relative to the others. +Keywords: wavelet transform, Gabor wavelet, curvelet transform, face recognition, multiscale analysis. +. Introduction +Among the so many popular methods for face recognition, the wavelet transform is"
+c9311a0c5045d86a617bd05a5cc269f44e81508d,Accurate Eye Centre Localisation by Means of Gradients,"ACCURATE EYE CENTRE LOCALISATION BY MEANS OF +GRADIENTS +Institute for Neuro- and Bioinformatics, University of L¨ubeck, Ratzeburger Allee 160, D-23538 L¨ubeck, Germany +Pattern Recognition Company GmbH, Innovations Campus L¨ubeck, Maria-Goeppert-Strasse 1, D-23562 L¨ubeck, Germany +{timm, +Fabian Timm and Erhardt Barth +Keywords:"
+c99a23a5bb5d5b10098395f59e9f8f79c79a75bd,Prediction Using Audience Chat Reactions,"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 972–978 +Copenhagen, Denmark, September 7–11, 2017. c(cid:13)2017 Association for Computational Linguistics"
+c93996cb126589b30c04bf1256c97a4431c0e8b6,Robustness Analysis of Pedestrian Detectors for Surveillance,"Robustness Analysis of Pedestrian Detectors +for Surveillance +Yuming Fang, Senior Memmber, IEEE, Guanqun Ding, Yuan Yuan, Weisi Lin, Fellow, IEEE, +nd Haiwen Liu, Senior Memmber, IEEE"
+c9b139b78e5337580047138d7fc2dff3b8fcf31f,Offline Face Recognition System Based on Gabor- Fisher Descriptors and Hidden Markov Models,"Offline Face Recognition System Based on Gabor- +Fisher Descriptors and Hidden Markov Models +Zineb Elgarrai1, Othmane Elmeslouhi2, Mustapha Kardouchi3, Hakim Allali1, Sid-Ahmed Selouani4 +FST of Hassan 1st University Settat /LAVETTE Laboratory, +FPO of Ibnou Zohr University /LabSIE Laboratory +Université de Moncton /Département d’Informatique, +Université de Moncton/Département de Gestion de l’Information"
+c97774191be232678a45d343a25fcc0c96c065e7,Co-Training of Audio and Video Representations from Self-Supervised Temporal Synchronization,"Co-Training of Audio and Video Representations from +Self-Supervised Temporal Synchronization +Undergraduate Thesis +written by +Bruno Korbar +under the supervision of Professor Lorenzo Torresani and Du Tran, and +submitted to the Committee as a culminating experience for the degree of +Bachelor of Arts in Computer Science +t Dartmouth College. +Date of the public presentation: Members of the Thesis Committee: +May 29, 2018 +Prof Lorenzo Torresani +Prof Saeed Hassanpour +Prof Venkatramanan Siva Subrahmanian +Dartmouth Computer Science Technical Report TR2018-849"
+fc04a50379e08ddde501816eb1f9560c36d01a39,Image Pre-processing Using OpenCV Library on MORPH-II Face Database,"Image Pre-processing Using OpenCV Library on MORPH-II Face Database +B. Yip, R. Towner, T. Kling, C. Chen, and Y. Wang"
fc1e37fb16006b62848def92a51434fc74a2431a,A Comprehensive Analysis of Deep Regression,"DRAFT A Comprehensive Analysis of Deep Regression St´ephane Lathuili`ere, Pablo Mesejo, Xavier Alameda-Pineda, Member IEEE, and Radu Horaud"
+fc7627e57269e7035e4d56105358211076fe4f04,The Association of Quantitative Facial Color Features with Cold Pattern in Traditional East Asian Medicine,"Hindawi +Evidence-Based Complementary and Alternative Medicine +Volume 2017, Article ID 9284856, 9 pages +https://doi.org/10.1155/2017/9284856 +Research Article +The Association of Quantitative Facial Color Features with +Cold Pattern in Traditional East Asian Medicine +Sujeong Mun, Ilkoo Ahn, and Siwoo Lee +Mibyeong Research Center, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon 305-811, Republic of Korea +Correspondence should be addressed to Siwoo Lee; +Received 30 June 2017; Accepted 13 September 2017; Published 17 October 2017 +Academic Editor: Kenji Watanabe +Copyright © 2017 Sujeong Mun et al. This is an open access article distributed under the Creative Commons Attribution License, +which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +Introduction. Facial diagnosis is a major component of the diagnostic method in traditional East Asian medicine. We investigated +the association of quantitative facial color features with cold pattern using a fully automated facial color parameterization system. +Methods. The facial color parameters of 64 participants were obtained from digital photographs using an automatic color correction +nd color parameter calculation system. Cold pattern severity was evaluated using a questionnaire. Results. The 𝑎∗ values of the +whole face, lower cheek, and chin were negatively associated with cold pattern score (CPS) (whole face: 𝐵 = −1.048, 𝑃 = 0.021; +lower cheek: 𝐵 = −0.494, 𝑃 = 0.007; chin: 𝐵 = −0.640, 𝑃 = 0.031), while 𝑏∗ value of the lower cheek was positively associated"
+fc50c9392fd23b6c88915177c6ae904a498aacea,Scaling Egocentric Vision: The EPIC-KITCHENS Dataset,"Scaling Egocentric Vision: +The EPIC-KITCHENS Dataset +Dima Damen1, Hazel Doughty1, Giovanni Maria Farinella2, Sanja Fidler3, +Antonino Furnari2, Evangelos Kazakos1, Davide Moltisanti1, +Jonathan Munro1, Toby Perrett1, Will Price1, and Michael Wray1 +Uni. of Bristol, UK 2Uni. of Catania, Italy, +Uni. of Toronto, Canada"
+fc30d7dbf4c3cdd377d8cd4e7eeabd5d73814b8f,Multiple Object Tracking by Efficient Graph Partitioning,"Multiple Object Tracking +y Efficient Graph Partitioning +Ratnesh Kumar, Guillaume Charpiat, Monique Thonnat +STARS Team, INRIA, Sophia Antipolis, France"
fcd3d69b418d56ae6800a421c8b89ef363418665,Effects of Aging over Facial Feature Analysis and Face Recognition,"Effects of Aging over Facial Feature Analysis and Face Recognition Bilgin Esme & Bulent Sankur Bogaziçi Un. Electronics Eng. Dept. March 2010"
fcd77f3ca6b40aad6edbd1dab9681d201f85f365,Machine Learning Based Attacks and Defenses in Computer Security: Towards Privacy and Utility Balance in Sensor Environments,"(cid:13)Copyright 2014 Miro Enev"
+fc3e097ea7dd5daa7d314ecebe7faad9af5e62fb,Variational Inference and Model Selection with Generalized Evidence Bounds,"Variational Inference and Model Selection +with Generalized Evidence Bounds +Chenyang Tao * Liqun Chen * Ruiyi Zhang Ricardo Henao Lawrence Carin"
+fc068f7f8a3b2921ec4f3246e9b6c6015165df9a,Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline),"Beyond Part Models: Person Retrieval with Refined Part Pooling +(and A Strong Convolutional Baseline) +Yifan Sun†, Liang Zheng‡, Yi Yang‡, Qi Tian§, Shengjin Wang†∗ +Tsinghua University ‡University of Technology Sydney §University of Texas at San Antonio +{liangzheng06,"
+fcc6fd9b243474cd96d5a7f4a974f0ef85e7ddf7,InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity,"Improving Face Attribute Detection with Race and Gender Diversity +InclusiveFaceNet: +Hee Jung Ryu 1 Hartwig Adam * 1 Margaret Mitchell * 1"
+fc64f43cdcf4898b15ddce8b441d2ab9daa324f0,Gabor Filter-based Face Recognition Technique,"THE PUBLISHING HOUSE +OF THE ROMANIAN ACADEMY +PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, +Volume 11, Number 3/2010, pp. 277–283 +GABOR FILTER-BASED FACE RECOGNITION TECHNIQUE +Tudor BARBU +Institute of Computer Science, Romanian Academy, Iaşi, Romania +E-mail: +We propose a novel human face recognition approach in this paper, based on two-dimensional Gabor +filtering and supervised classification. The feature extraction technique proposed in this article uses +D Gabor filter banks and produces robust 3D face feature vectors. A supervised classifier, using +minimum average distances, is developed for these vectors. The recognition process is completed by a +threshold-based face verification method, also provided. A high facial recognition rate is obtained +using our technique. Some experiments, whose satisfactory results prove the effectiveness of this +recognition approach, are also described in the paper. +Key words: Face recognition; Face identification; Feature vector; 2D Gabor filter; Supervised classification; +Face verification. +. INTRODUCTION +This article approaches an important biometric domain, which is human face recognition. Face +represents a physiological biometric identifier that is widely used in person recognition. During the past"
+fc74e14a3195fdf91157d5ea86d35c576fcf01d6,Detection and Handling of Occlusion in an Object Detection System,"Detection and Handling of Occlusion in an +Object Detection System +R.M.G. Op het Velda, R.G.J. Wijnhovenb, Y. Bondarauc and Peter H.N. de Withd +,bViNotion B.V., Horsten 1, 5612 AX, Eindhoven, The Netherlands; +,c,dEindhoven University of Technology, Den Dolech 2, 5612 AZ, Eindhoven, The Netherlands"
+fc27c2c8a2486f5918451fbef198f46b5bf45d2c,Robust Real-Time Multi-View Eye Tracking,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. XX, NO. XX, 2018 +Robust Real-Time Multi-View Eye Tracking +Nuri Murat Arar, Student Member, IEEE, and Jean-Philippe Thiran, Senior Member, IEEE"
+fc73090889036a0e42ea40827ac835cd5e135b16,Deep Learning based Large Scale Visual Recommendation and Search for E-Commerce,"Deep Learning based Large Scale Visual Recommendation and +Search for E-Commerce +Devashish Shankar, Sujay Narumanchi, Ananya H A, +Pramod Kompalli, Krishnendu Chaudhury +Flipkart Internet Pvt. Ltd., +Bengaluru, India."
+fcb64ef4421cebb80eb33f62c7726f339eb2bb62,Deep View-Aware Metric Learning for Person Re-Identification,Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18)
fcf8bb1bf2b7e3f71fb337ca3fcf3d9cf18daa46,Feature Selection via Sparse Approximation for Face Recognition,"MANUSCRIPT SUBMITTED TO IEEE TRANS. PATTERN ANAL. MACH. INTELL., JULY 2010 Feature Selection via Sparse Approximation for Face Recognition Yixiong Liang, Lei Wang, Yao Xiang, and Beiji Zou"
+fcd9221f8ef306155f59817a3b0bdae05e9e0ae2,GEFeWS: A Hybrid Genetic-Based Feature Weighting and Selection Algorithm for Multi-Biometric Recognition,"GEFeWS: A Hybrid Genetic-Based Feature Weighting and +Selection Algorithm for Multi-Biometric Recognition +Aniesha Alford+, Khary Popplewell#, Gerry Dozier#, Kelvin Bryant#, John Kelly+, +Josh Adams#, Tamirat Abegaz^, and Joseph Shelton# +Center for Advanced Studies in Identity Sciences ++Electrical and Computer Engineering Department, +#Computer Science Department +^Computational Science and Engineering Department +North Carolina A & T State University +601 E Market St., Greensboro, NC 27411"
+fcabf1c0f4a26431d4df95ddeec2b1dff9b3e928,Semantic Segmentation using Adversarial Networks,
fcbf808bdf140442cddf0710defb2766c2d25c30,Unsupervised Semantic Action Discovery from Video Collections,"IJCV manuscript No. (will be inserted by the editor) Unsupervised Semantic Action Discovery from Video @@ -5102,12 +17469,23 @@ Collections Ozan Sener · Amir Roshan Zamir · Chenxia Wu · Silvio Savarese · Ashutosh Saxena Received: date / Accepted: date"
+fd51665efe2520a55aa58b2f1863a3bd9870529f,Understanding Compressive Adversarial Privacy,"Understanding Compressive Adversarial Privacy +Xiao Chen, Peter Kairouz, Ram Rajagopal"
fd4ac1da699885f71970588f84316589b7d8317b,Supervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007 Supervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision Xuehan Xiong, and Fernando De la Torre"
+fde3f34a1accadb73269e4beef487611f682b781,"Before A Computer Can Draw, It Must First Learn To See","Before A Computer Can Draw, It Must First Learn To See +Derrall Heath and Dan Ventura +Computer Science Department +Brigham Young University +Provo, UT 84602 USA"
fdf533eeb1306ba418b09210387833bdf27bb756,Exploiting Unrelated Tasks in Multi-Task Learning,
+fdb956c7705b7f57f56f944a0f3f4ede1d6f77fa,Does Fast Fashion Increase the Demand for Premium Brands ?,"Does Fast Fashion Increase the Demand for Premium Brands? +A Structural Analysis +Zijun (June) Shi1, Param Vir Singh, Dokyun Lee, Kannan Srinivasan +(Preliminary draft. Please do not cite without the authors’ permission.)"
fdda5852f2cffc871fd40b0cb1aa14cea54cd7e3,Im2Flow: Motion Hallucination from Static Images for Action Recognition,"Im2Flow: Motion Hallucination from Static Images for Action Recognition Ruohan Gao UT Austin @@ -5115,9 +17493,49 @@ Bo Xiong UT Austin Kristen Grauman UT Austin"
+fd1b917476b114919de0ae1b6a4b96a52a410c20,A Memory Based Face Recognition Method,"A Memory Based Face Recognition Method +Alex Pappachen James +B. Tech. (Hons), M. Tech. +Griffith School of Engineering +Science, Environment, Engineering and Technology +Griffith University +Submitted in fulfilment of the requirements of the degree of +Doctor of Philosophy +November 2008"
fdfaf46910012c7cdf72bba12e802a318b5bef5a,Computerized Face Recognition in Renaissance Portrait Art,"Computerized Face Recognition in Renaissance Portrait Art Ramya Srinivasan, Conrad Rudolph and Amit Roy-Chowdhury"
+fd4c46bfd3bb00ed93b0bb5b28ef0336f59f0c15,Expressing Emotions through Vibration for Perception and Control,"Expressing Emotions through Vibration +for Perception and Control +Shafiq ur Réhman +Doctoral Thesis, April 2010 +Department of Applied Physics and Electronics +Umeå University, Sweden +UNIVERSITETSSERVICEProfil & CopyshopÖppettider:Måndag - fredag 10-16Tel. 786 52 00 alt 070-640 52 01Universumhuset"
+fd6d2e4f939b8d804a6b5908bded8f1ad2563e38,Stabilizing GAN Training with Multiple Random Projections,"Stabilizing GAN Training with +Multiple Random Projections +Behnam Neyshabur Srinadh Bhojanapalli Ayan Chakrabarti +Toyota Technological Institute at Chicago +6045 S. Kenwood Ave., Chicago, IL 60637"
+fdbe7c520568d9a32048270d2c87113c635dc7e6,Live Stream Oriented Age and Gender Estimation using Boosted LBP Histograms Comparisons,"Live Stream Oriented Age and Gender Estimation using Boosted LBP +Histograms Comparisons +LAMIA, University of the French West Indies and Guiana, Campus de Fouillole, BP 250, 97157 Pointe `a Pitre, France +Lionel Prevost1, Philippe Phothisane2 and Erwan Bigorgne2 +Eikeo, 11 rue L´eon Jouhaux, 75010 Paris, France +Keywords: +Face Analysis, Boosting, Gender Estimation, Age Estimation."
+fd0a1a2ecf69a6c1a6efcb18b8f23e4d5402f601,"ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events","ExtremeWeather: A large-scale climate dataset for +semi-supervised detection, localization, and +understanding of extreme weather events +Evan Racah1,2, Christopher Beckham1,3, Tegan Maharaj1,3, +Samira Ebrahimi Kahou4, Prabhat2, Christopher Pal1,3 +MILA, Université de Montréal, +Lawrence Berkeley National Lab, Berkeley, CA, +École Polytechnique de Montréal, +Microsoft Maluuba,"
+fd67b9812fa4aef6c5dfb633df4406105cdb4e8f,Zero-Shot Learning with Generative Latent Prototype Model,"Zero-Shot Learning with Generative Latent +Prototype Model +Yanan Li, Student Member, IEEE, Donghui Wang, Member, IEEE"
fdca08416bdadda91ae977db7d503e8610dd744f,ICT - 2009 . 7 . 1 KSERA Project 2010 - 248085,"ICT-2009.7.1 KSERA Project 010-248085 @@ -5134,12 +17552,48 @@ under the 7th Framework Programme (FP7) for Research and Technological Developme under the 7th Framework Programme (FP7) for Research and Technological Development under grant under the 7th Framework Programme (FP7) for Research and Technological Development under grant greement n°2010-248085."
+fd4537b92ab9fa7c653e9e5b9c4f815914a498c0,One-Sided Unsupervised Domain Mapping,
+fdf31db5aa8cf8a7f9ac84fcc7b0949e8e000a41,MODELING FASHION Anonymous ICME submission,"MODELING FASHION +Anonymous ICME submission"
+fd8bb112b197e23183feeb6d1f4506d180caa4fc,Fashion Clothes Matching Scheme Learned from Fashionista ’ S Suggestions in Microblog,"FASHION CLOTHES MATCHING SCHEME LEARNED FROM FASHIONISTA’S +SUGGESTIONS IN MICROBLOG +Guangyu Gao1, Yihang Zhang1, Songyang Du2 +School of Software, Beijing Institute of Technology. Beijing 100081, China +Beijing Special Vehicle Research Institute. Beijing 100072, China"
fd96432675911a702b8a4ce857b7c8619498bf9f,Improved Face Detection and Alignment using Cascade Deep Convolutional Network,"Improved Face Detection and Alignment using Cascade Deep Convolutional Network Weilin Cong†, Sanyuan Zhao†, Hui Tian‡, and Jianbing Shen† Beijing Key Laboratory of Intelligent Information Technology, School of Computer Science,Beijing Institute of Technology, Beijing 100081, P.R.China China Mobile Research Institute, Xuanwu Men West Street, Beijing"
+fdd94d77377df6e55d14e41a28141dc241d8b5d6,Current Status and Future Prospects of Clinical Psychology: Toward a Scientifically Principled Approach to Mental and Behavioral Health Care.,"Current Status and Future Prospects of Clinical Psychology: Toward a Scientifically +Principled Approach to Mental and Behavioral Health Care +Author(s): Timothy B. Baker, Richard M. McFall and Varda Shoham +Source: Psychological Science in the Public Interest, Vol. 9, No. 2 (November 2008), pp. 67- +Published by: Sage Publications, Inc. on behalf of the Association for Psychological Science +Stable URL: http://www.jstor.org/stable/20697320 +Accessed: 07-02-2017 15:41 UTC +REFERENCES +Linked references are available on JSTOR for this article: +http://www.jstor.org/stable/20697320?seq=1&cid=pdf-reference#references_tab_contents +You may need to log in to JSTOR to access the linked references. +JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted +digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about +JSTOR, please contact +Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at +http://about.jstor.org/terms +Sage Publications, Inc., Association for Psychological Science are collaborating with JSTOR to +digitize, preserve and extend access to Psychological Science in the Public Interest +This content downloaded from 129.133.179.122 on Tue, 07 Feb 2017 15:41:42 UTC +All use subject to http://about.jstor.org/terms"
+fd0e1fecf7e72318a4c53463fd5650720df40281,End-to-End Comparative Attention Networks for Person Re-Identification,"End-to-End Comparative Attention Networks for +Person Re-identification +Hao Liu, Jiashi Feng, Meibin Qi, Jianguo Jiang and Shuicheng Yan, Fellow, IEEE"
+fd4f9955ec28b63443039cb9d4e15bae796defe4,Predictably Angry - Facial Cues Provide a Credible Signal of Destructive Behavior,"Predictably Angry +Facial cues provide a credible signal of destructive behavior +Boris van Leeuwen1, Charles N. Noussair2, Theo Offerman3, +Sigrid Suetens4, Matthijs van Veelen5, and Jeroen van de Ven6 +November 2016"
fdb33141005ca1b208a725796732ab10a9c37d75,A connectionist computational method for face recognition,"Int.J.Appl. Math. Comput.Sci.,2016,Vol. 26,No. 2,451–465 DOI: 10.1515/amcs-2016-0032 A CONNECTIONIST COMPUTATIONAL METHOD FOR FACE RECOGNITION @@ -5160,6 +17614,42 @@ Keywords: pattern recognition, face recognition, neural networks, self-organizin Introduction libraries, In recent years, there has been intensive research carried"
+fd23502287ae4ca8db63e4e5080c359610398be5,Real-Time Pedestrian Detection with Deep Network Cascades,"ANGELOVA ET AL.: REAL-TIME PEDESTRIAN DETECTION WITH DEEP CASCADES +Real-Time Pedestrian Detection With Deep +Network Cascades +Anelia Angelova1 +Alex Krizhevsky1 +Vincent Vanhoucke1 +Abhijit Ogale2 +Dave Ferguson2 +Google Research +600 Amphitheatre Parkway +Mountain View, CA, USA +Google X +600 Amphitheatre Parkway +Mountain View, CA, USA"
+fd9286f0e465deffad59123f46fa4f66cb15c3e4,Learning Answer Embeddings for Visual Question Answering,"Learning Answer Embeddings for Visual Question Answering +Hexiang Hu∗ +U. of Southern California +Los Angeles, CA +Wei-Lun Chao∗ +Los Angeles, CA +U. of Southern California +U. of Southern California +Fei Sha +Los Angeles, CA"
+fd8b1715ad34858bf8650ac549c4249d86edbb7c,Paper Title (use style: paper title),"International Association of Scientific Innovation and Research (IASIR) +(An Association Unifying the Sciences, Engineering, and Applied Research) +ISSN (Print): 2279-0063 +ISSN (Online): 2279-0071 +International Journal of Software and Web Sciences (IJSWS) +www.iasir.net +A survey of techniques for human segmentation from static images +Ms.Ashwini T. Magar, Prof.J.V.Shinde +Late G.N.Sapkal College of Engineering, +Computer Engineering Department, Nashik, +University of Pune, India. +__________________________________________________________________________________________"
fde0180735699ea31f6c001c71eae507848b190f,Face Detection and Sex Identification from Color Images using AdaBoost with SVM based Component Classifier,"International Journal of Computer Applications (0975 – 8887) Volume 76– No.3, August 2013 Face Detection and Sex Identification from Color Images @@ -5185,6 +17675,23 @@ Shape Models Brandon M. Smith and Li Zhang University of Wisconsin – Madison http://www.cs.wisc.edu/~lizhang/projects/joint-align/"
+fdc60fe4654b5efe0752acabef0ec6258062be0f,Multi-Sensor Fusion Adopted 2-D Laser Rangefinder and Camera for Pedestrian Detection,"2nd ITS World Congress, Bordeaux, France, 5–9 October 2015 +Paper number ITS-1576 +Multi-Sensor Fusion Adopted 2-D Laser Rangefinder and Camera +for Pedestrian Detection +Kuo-Ching Chang*, Chi-Kuo Chen, Pao-Kai Tseng +Automotive Research & Testing Center, Taiwan ++886-4-7811222 Ext. 2323,"
+fd069af1ede370625703f7984e52f282fcd6342e,Guided Feature Transformation (GFT): A Neural Language Grounding Module for Embodied Agents,"Guided Feature Transformation (GFT): A Neural +Language Grounding Module for Embodied Agents +Haonan Yu†, Xiaochen Lian†, Haichao Zhang†, and Wei Xu‡ +Baidu Research, Sunnyvale CA USA +Horizon Robotics, Cupertino CA USA"
+fdee0cf79e9a2695857afeee6526352918c9f315,Quantization for Rapid Deployment of Deep Neural Networks,"Quantization for Rapid Deployment of Deep Neural Networks +Jun Haeng Lee∗, Sangwon Ha∗, Saerom Choi, Won-Jo Lee, Seungwon Lee +Samsung Advanced Institute of Technology +Samsung-ro 130, Suwon-si, Republic of Korea +{junhaeng2.lee,"
fdaf65b314faee97220162980e76dbc8f32db9d6,Face recognition using both visible light image and near-infrared image and a deep network,"Accepted Manuscript Face recognition using both visible light image and near-infrared image and a deep network @@ -5205,12 +17712,126 @@ our customers we are providing this early version of the manuscript. The manuscr opyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain."
+f218df397afb1f070ee093bb9a19616f61b562c4,A Neural Network Model of Face Detection for Active Vision Implementation,"International Journal of Modern Engineering Research (IJMER) +www.ijmer.com Vol. 2, Issue. 5, Sept.-Oct. 2012 pp-2969-2974 ISSN: 2249-6645 +A Neural Network Model of Face Detection for Active Vision +Implementation +Yasuomi D. Sato*, ** Yasutaka Kuriya* +* Department of Brain Science and Engineering, Graduate School for Life Science and Systems Engineering, Kyushu +** Frankfurt Institute for Advanced Studies (FIAS), Goethe University Frankfurt, Germany +Institute of Technology, Japan +impaired"
+f22058a3003cee6b17c6c25c8a635a653e78614c,Multimodal Attention in Recurrent Neural Networks for Visual Question Answering,"Global Journal of Computer Science and Technology: D +Neural & Artificial Intelligence +Volume 17 Issue 1 Version 1.0 Year 2017 +Type: Double Blind Peer Reviewed International Research Journal +Publisher: Global Journals Inc. (USA) +Online ISSN: 0975-4172 & Print ISSN: 0975-4350 +Multimodal Attention in Recurrent Neural Networks for Visual +Question Answering +By Lorena Kodra & Elinda Kajo Meçe +Polytechnic University of Tirana"
+f26d34d8a8d082ce2c81937f61c28f3769c38372,Probability of Seeing Increases Saccadic Readiness,"Probability of Seeing Increases Saccadic Readiness +The´ re` se Collins* +Laboratoire Psychologie de la Perception, Universite´ Paris Descartes & CNRS, Paris, France"
+f2efc85f9e20840c591b4590fd9ed202f727546a,Distributed signature fusion for person re-identification,"Distributed Signature Fusion for +Person Re-Identification +Niki Martinel +University of Udine +Udine, Italy +Christian Micheloni +University of Udine +Udine, Italy +Claudio Piciarelli +University of Udine +Udine, Italy"
+f2889f3ab8e330e1ba6b23d493f8d727f49a9bc8,Recent Advances in Neural Program Synthesis,"Recent Advances in Neural Program Synthesis +Neel Kant +Machine Learning at Berkeley +UC Berkeley"
+f26a8dcfbaf9f46c021c41a3545fcfa845660c47,Human Pose Regression by Combining Indirect Part Detection and Contextual Information,"Human Pose Regression by Combining Indirect Part Detection and Contextual +Information +Diogo C. Luvizon +Hedi Tabia +ETIS Lab., UMR 8051, Universit´e Paris Seine, +Universit´e Cergy-Pontoise, ENSEA, CNRS. +{diogo.luvizon, hedi.tabia, +David Picard"
+f2bccfb12c1546bdf73b11904ac44b1cfa130072,RoarNet: A Robust 3D Object Detection based on RegiOn Approximation Refinement,"RoarNet: A Robust 3D Object Detection based on +RegiOn Approximation Refinement +Kiwoo Shin∗†, Youngwook Paul Kwon∗‡ and Masayoshi Tomizuka†"
+f2b2d50d6ca72666bab34e0f101ae1b18b434925,High-Fidelity Monocular Face Reconstruction based on an Unsupervised Model-based Face Autoencoder.,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +High-Fidelity Monocular Face Reconstruction based on an +Unsupervised Model-based Face Autoencoder +Ayush Tewari, Michael Zollh¨ofer, Florian Bernard, Pablo Garrido, +Hyeongwoo Kim, Patrick P´erez, and Christian Theobalt +(Invited Paper)"
+f29aae30c2cb4c73a3c814408ee5692e22176329,Pairwise Relational Networks using Local Appearance Features for Face Recognition,"Pairwise Relational Networks using Local +Appearance Features for Face Recognition +Bong-Nam Kang +Yonghyun Kim, Daijin Kim +Department of Creative IT Engineering +Department of Computer Science and Engineering +POSTECH, Korea +POSTECH, Korea"
+f2b95f135b95c3df4f6ebe6015098a2e1667711d,Weakly Supervised Object Localization Using Things and Stuff Transfer,"Weakly Supervised Object Localization Using Things and Stuff Transfer +Miaojing Shi1,2 +Holger Caesar1 +University of Edinburgh 2Tencent Youtu Lab +Vittorio Ferrari1"
f2e9494d0dca9fb6b274107032781d435a508de6,Title of Dissertation : UNCONSTRAINED FACE RECOGNITION,
+f2877cdbffb0c9a4de1f562099d2f0597bcfec0b,"COGNIMUSE: a multimodal video database annotated with saliency, events, semantics and emotion with application to summarization","Zlatintsi et al. EURASIP Journal on Image and Video Processing (2017) 2017:54 +DOI 10.1186/s13640-017-0194-1 +EURASIP Journal on Image +nd Video Processing +RESEARCH +Open Access +COGNIMUSE: a multimodal video +database annotated with saliency, events, +semantics and emotion with application to +summarization +Athanasia Zlatintsi1* +Niki Efthymiou1, Katerina Pastra4, Alexandros Potamianos1 and Petros Maragos1 +, Petros Koutras1, Georgios Evangelopoulos2, Nikolaos Malandrakis3,"
+f20f93a5b2291283c0e40bd0418927efb06acb6a,A Tale of Two Encodings : Comparing Bag-of-Words and Word 2 vec for VQA,"A Tale of Two Encodings: Comparing Bag-of-Words and Word2vec for VQA +Berthy Feng +Princeton University ’19 +Divya Thuremella +Princeton University ’18"
f2a7f9bd040aa8ea87672d38606a84c31163e171,Human Action Recognition without Human,"Human Action Recognition without Human Yun He, Soma Shirakabe, Yutaka Satoh, Hirokatsu Kataoka National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba, Ibaraki, Japan {yun.he, shirakabe-s, yu.satou,"
+f2d95a5b29986a6a28746b30adfa43497b27ff02,Global Self-Similarity and Saliency Measures Based on Sparse Representations for Classification of Objects and Spatio-temporal Sequences,"Global Self-Similarity and Saliency Measures Based on +Sparse Representations for Classification of Objects and +Spatio-temporal Sequences. +A DISSERTATION +SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL +OF THE UNIVERSITY OF MINNESOTA +Guruprasad Somasundaram +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +Doctor of Philosophy +Nikolaos Papanikolopoulos +November, 2012"
+f2b79ae191fc03a93ed50eea773279f67c8351e1,Annotating Images with Suggestions - User Study of a Tagging System,"Annotating images with suggestions — user +study of a tagging system +Michal Hradiˇs, Martin Kol´aˇr, Aleˇs L´an´ık, Jiˇr´ı Kr´al, Pavel Zemˇc´ık and Pavel +Smrˇz +Faculty of Information Technology +VUT — Brno University of Technology +Brno Czech Republic"
+f23d4ed760a35fbfaeab47efde3d876c1818d3d1,Dynamicity and Durability in Scalable Visual Instance Search,"Dynamicity and Durability in Scalable Visual Instance Search +Herwig Lejsek∗ +Videntifier Technologies, Iceland +Björn Þór Jónsson† +Reykjavík University, Iceland +ITU Copenhagen, Denmark +Laurent Amsaleg +IRISA–CNRS, France +Friðrik Heiðar Ásmundsson∗ +Videntifier Technologies, Iceland"
f20e0eefd007bc310d2a753ba526d33a8aba812c,Accurate and robust face recognition from RGB-D images with a deep learning approach,"Lee et al.: RGB-D FACE RECOGNITION WITH A DEEP LEARNING APPROACH Accurate and robust face recognition from RGB-D images with a deep learning @@ -5249,8 +17870,124 @@ in Web of Science™ Core Collection (BKCI) Interested in publishing with us? Contact Numbers displayed above are based on latest data collected."
+f22a7a7a8cdd323270d1f8173c0289d61981dc73,Face Recognition System Using Wavelet Normalization,"ISSN(Online): 2319-8753 +ISSN (Print): 2347-6710 +International Journal of Innovative Research in Science, +Engineering and Technology +(An ISO 3297: 2007 Certified Organization) +Vol. 4, Issue 12, December 2015 +Face Recognition System Using +Wavelet Normalization +R.Anitha 1, S.Ramila 2 +Assistant Professor, Dept. of CSE, Sri Krishna College of Technology, Coimbatore, India 1 +Assistant Professor, Dept. of CSE, Sri Krishna College of Technology, Coimbatore, India 2"
+f202c78e58d33a65c19183414ad0ee91be440d61,Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition,"New Research +Sensory and Motor Systems +Investigating the Influence of Biological Sex on +the Behavioral and Neural Basis of Face +Recognition +K. Suzanne Scherf,1,2 Daniel B. Elbich,1 and Natalie V. Motta-Mena1 +DOI:http://dx.doi.org/10.1523/ENEURO.0104-17.2017 +Department of Psychology, Pennsylvania State University, University Park, PA 16802, and 2Department of +Neuroscience, Pennsylvania State University, University Park, PA 16802"
+f2b547b0bbda1478cbecbd5c184c3c42c3db7e3c,Semi-parametric Image Synthesis,
+f565ac8e175e4659fadd3b5b6507ebac2d90a2b7,Interpretable Visual Question Answering by Reasoning on Dependency Trees,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, XXX +Interpretable Visual Question Answering by +Reasoning on Dependency Trees +Qingxing Cao, Xiaodan Liang, Bailin Li and Liang Lin"
+f59ac278349083a50871822ea08172258030265a,Large-Scale Fiber Tracking Through Sparsely Sampled Image Sequences of Composite Materials,"Large-Scale Fiber Tracking Through Sparsely +Sampled Image Sequences of Composite Materials +Youjie Zhou, Student Member, IEEE, Hongkai Yu, Student Member, IEEE, Jeff Simmons, Member, IEEE, +Craig P. Przybyla, and Song Wang, Senior Member, IEEE +nd accurate"
+f5c99652c4c89e56156faf2bed361a15de6162d5,Towards Large-Scale Multimedia Retrieval Enriched by Knowledge about Human Interpretation Retrospective Survey,"Noname manuscript No. +(will be inserted by the editor) +Towards Large-Scale Multimedia Retrieval Enriched +y Knowledge about Human Interpretation +Retrospective Survey +Kimiaki Shirahama · Marcin Grzegorzek +Received: date / Accepted: date"
+f56edb6f2bf4f5bc9d54284289212b8d4a437c1b,Detection and Localization of Texture-less Objects with Deep Neural Networks,"Bachelor Thesis +Czech +Technical +University +in Prague +Faculty of Electrical Engineering +Department of Cybernetics +Detection and Localization of Texture-less +Objects with Deep Neural Networks +Pavel Haluza +Supervisor: Ing. Tomáš Hodaň +May 2017"
+f5050ffebf973d4d848049dcf661891acd950b82,"Face and object discrimination in autism, and relationship to IQ and age.","J Autism Dev Disord +DOI 10.1007/s10803-013-1955-z +O R I G I N A L P A P E R +Face and Object Discrimination in Autism, and Relationship to IQ +nd Age +Pamela M. Pallett • Shereen J. Cohen • +Karen R. Dobkins +Ó Springer Science+Business Media New York 2013 +faces, yet"
+f553f8022b1417bc7420523220924b04e3f27b8e,Finding your Lookalike: Measuring Face Similarity Rather than Face Identity,"Finding your Lookalike: +Measuring Face Similarity Rather than Face Identity +Amir Sadovnik, Wassim Gharbi, Thanh Vu +Lafayette College +Easton, PA +Andrew Gallagher +Google Research +Mountain View, CA"
+f580b0e1020ad67bdbb11e8d99a59c21a8df1e7d,Compressed Sensing using Generative Models,"Compressed Sensing using Generative Models +Ashish Bora∗ +Ajil Jalal† +Eric Price‡ +Alexandros G. Dimakis§"
f5770dd225501ff3764f9023f19a76fad28127d4,Real Time Online Facial Expression Transfer with Single Video Camera,"Real Time Online Facial Expression Transfer with Single Video Camera"
+f51771c6cd9061acc9c468e7b44d5d3b6c552b32,Discriminative Dictionaries and Projections for Visual Classification,
+f5c83679b73ab59c2ada2b72610acdd63669b226,2d-3d Pose Invariant Face Recognition System for Multimedia Applications,"D-3D POSE INVARIANT FACE RECOGNITION +SYSTEM FOR MULTIMEDIA APPLICATIONS +Authors: +Antonio Rama1, Francesc Tarrés1 +Jürgen Rurainsky2 +{tonirama, +Department of Signal Theory and Communications +Universitat Politècnica de Catalunya (UPC) +Image Processing Department +Fraunhofer Institute for Telecommunications +Heinrich-Hertz-Institut (HHI) +Automatic Face recognition of people is a challenging problem which has re- +eived much attention during the recent years due to its potential multimedia ap- +plications in different fields such as 3D videoconference, security applications or +video indexing. However, there is no technique that provides a robust solution to +ll situations and different applications, yet. Face recognition includes a set of +hallenges like expression variations, occlusions of facial parts, similar identities, +resolution of the acquired images, aging of the subjects and many others. Among +ll these challenges, most of the face recognition techniques have evolved in order +to overcome two main problems: illumination and pose variation. Either of these"
+f5a52b69dde106cb69cb7c35dd8ca23071966876,Nonparametric Scene Parsing via Label Transfer,"Nonparametric Scene Parsing +via Label Transfer +Ce Liu, Member, IEEE, Jenny Yuen, Student Member, IEEE, and +Antonio Torralba, Member, IEEE"
+f558a3812106764fb1af854a02da080cc42c197f,Amygdala volume and nonverbal social impairment in adolescent and adult males with autism.,"ORIGINAL ARTICLE +Amygdala Volume and Nonverbal Social Impairment +in Adolescent and Adult Males With Autism +Brendon M. Nacewicz, BS; Kim M. Dalton, PhD; Tom Johnstone, PhD; Micah T. Long, BS; Emelia M. McAuliff, BS; +Terrence R. Oakes, PhD; Andrew L. Alexander, PhD; Richard J. Davidson, PhD +Background: Autism is a syndrome of unknown cause, +marked by abnormal development of social behavior. At- +tempts to link pathological features of the amygdala, which +plays a key role in emotional processing, to autism have +shown little consensus. +Objective: To evaluate amygdala volume in individu- +ls with autism spectrum disorders and its relationship +to laboratory measures of social behavior to examine +whether variations in amygdala structure relate to symp- +tom severity. +Design: We conducted 2 cross-sectional studies of amyg- +dala volume, measured blind to diagnosis on high- +resolution, anatomical magnetic resonance images. Par- +ticipants were 54 males aged 8 to 25 years, including 23 +with autism and 5 with Asperger syndrome or pervasive"
f558af209dd4c48e4b2f551b01065a6435c3ef33,An Enhanced Attribute Reranking Design for Web Image Search,"International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE) ISSN: 0976-1353 Volume 23 Issue 1 –JUNE 2016. AN ENHANCED ATTRIBUTE @@ -5259,6 +17996,22 @@ SEARCH Sai Tejaswi Dasari#1 and G K Kishore Babu*2 #Student,Cse, CIET, Lam,Guntur, India * Assistant Professort,Cse, CIET, Lam,Guntur , India"
+f5083b4e28e42a2da7bafd2a742ab8e21c12559f,Deep Learning for Automated Image Classification of Seismic Damage to Built Infrastructure,"Eleventh U.S. National Conference on Earthquake Engineering +Integrating Science, Engineering & Policy +June 25-29, 2018 +Los Angeles, California +DEEP LEARNING FOR AUTOMATED +IMAGE CLASSIFICATION OF SEISMIC +DAMAGE TO BUILT INFRASTRUCTURE +B. Patterson1 , G. Leone1, M. Pantoja1, and A. Behrouzi2"
+f5adb841e30eb635b91e95c03575f3b8767c9ed5,Learning Optimal Parameters For Multi-target Tracking,"WANG, FOWLKES: LEARNING MULTI-TARGET TRACKING +Learning Optimal Parameters +For Multi-target Tracking +Shaofei Wang +Charless Fowlkes +Dept of Computer Science +University of California +Irvine, CA, USA"
e378ce25579f3676ca50c8f6454e92a886b9e4d7,Robust Video Super-Resolution with Learned Temporal Dynamics,"Robust Video Super-Resolution with Learned Temporal Dynamics Ding Liu1 Zhaowen Wang2 Yuchen Fan1 Xianming Liu3 Zhangyang Wang4 Shiyu Chang5 Thomas Huang1 @@ -5277,11 +18030,68 @@ Bo Sun, Siming Cao, Jun He, Lejun Yu, Liandong Li, “Automatic temporal segment detection via bilateral long short-term memory recurrent neural networks,” J. Electron. Imaging 26(2), 020501 (2017), doi: 10.1117/1.JEI.26.2.020501. Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 03/03/2017 Terms of Use: http://spiedigitallibrary.org/ss/termsofuse.aspx"
+e312e7657cb98cf03d3b2bf8b21b0ff75fbd4613,No 272 2 D Articulated Human Pose Estimation and Retrieval in ( Almost ) Unconstrained Still Images,"ETH Zurich, D-ITET, BIWI +Technical Report No 272 +D Articulated Human Pose Estimation and Retrieval in (Almost) +Unconstrained Still Images +M. Eichner, M. Marin-Jimenez, A. Zisserman, V. Ferrari"
+e3f2e337d4470545398cc6753a54c21debf9c37b,Potential Contrast – A New Image Quality Measure,"Potential Contrast – A New Image Quality Measure +Arie Shaus, Shira Faigenbaum-Golovin, Barak Sober, Eli Turkel, Eli Piasetzky; Tel Aviv University; Tel Aviv, Israel"
+e3b0caa1ff9067665e349a2480b057e2afdbc41f,Interactive Effects of Obvious and Ambiguous Social Categories on Perceptions of Leadership: When Double-Minority Status May Be Beneficial.,"702373 PSPXXX10.1177/0146167217702373Personality and Social Psychology BulletinWilson et al. +research-article2017 +Article +Interactive Effects of Obvious and +Ambiguous Social Categories on +Perceptions of Leadership: When +Double-Minority Status May +Be Beneficial +Personality and Social +Psychology Bulletin +017, Vol. 43(6) 888 –900 +© 2017 by the Society for Personality +nd Social Psychology, Inc +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0146167217702373 +https://doi.org/10.1177/0146167217702373 +journals.sagepub.com/home/pspb +John Paul Wilson1, Jessica D. Remedios2, and Nicholas O. Rule3"
e315959d6e806c8fbfc91f072c322fb26ce0862b,An Efficient Face Recognition System Based on Sub-Window Extraction Algorithm,"An Efficient Face Recognition System Based on Sub-Window International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-1, Issue-6, January 2012 Extraction Algorithm Manish Gupta, Govind sharma"
+e39d1345a5aef8a5ee32c0a774de877b903de50c,Unsupervised Learning of Semantics of Object Detections for Scene Categorization,"Unsupervised Learning of Semantics of Object +Detections for Scene Categorization +Grégoire Mesnil, Salah Rifai, Antoine Bordes, Xavier Glorot, Yoshua Bengio +nd Pascal Vincent"
+e38c93bb8f7ee103eba4b78443d94f55a63bdf08,Extracting Pathlets From Weak Tracking Data ∗,"Extracting Pathlets From Weak Tracking Data∗ +Kevin Streib +James W. Davis +Dept. of Computer Science and Engineering +Ohio State University, Columbus, OH 43210"
+e33b1833b2d0cd7b0450b22b96a567a59c9e4685,Attribute Discovery via Predictable Discriminative Binary Codes,"Attribute Discovery via +Predictable Discriminative Binary Codes +Mohammad Rastegari† +Ali Farhadi‡ +David Forsyth† +University of Illinois at Urbana Champagin +Carnegi Mellon University +http://vision.ri.cmu.edu/projects/dbc/dbc.html"
+e3f63d12be07c743e7590957f4ed38b06cd98aba,A Novel Approach to Face Detection Algorithm,"A Novel Approach to Face Detection Algorithm +{tag} {/tag} +International Journal of Computer Applications +© 2011 by IJCA Journal +Number 2 - Article 4 +Year of Publication: 2011 +Authors: +Pritam Singh +A.S. Thoke +Kesari Verma +10.5120/3537-4836"
+e3c420b29b8590442decd330ef70494c2209f149,Learning a Part-Based Pedestrian Detector in a Virtual World,"Learning a Part-based Pedestrian Detector in Virtual +World +Jiaolong Xu, David V´azquez, Antonio M. L´opez Member, IEEE, Javier Mar´ın and Daniel Ponsa"
e39a0834122e08ba28e7b411db896d0fdbbad9ba,Maximum Likelihood Estimation of Depth Maps Using Photometric Stereo,"Maximum Likelihood Estimation of Depth Maps Using Photometric Stereo Adam P. Harrison, Student Member, IEEE, and Dileepan Joseph, Member, IEEE"
@@ -5294,6 +18104,71 @@ Computational Medicine Laboratory, Institute of Computer Science, Foundation for 70013 Vasilika Vouton, Heraklion, Crete, Greece Keywords: Facial Expression, Stress, Anxiety, Feature Selection, Well-being Evaluation, FACS, FAPS, Classification."
+e3b40ffd57a676aef377ef463849fd6b9a3d3b5d,Morphable hundred-core heterogeneous architecture for energy-aware computation,"Received on 16th April 2014 +Revised on 23rd June 2014 +Accepted on 7th August 2014 +doi: 10.1049/iet-cdt.2014.0078 +www.ietdl.org +ISSN 1751-8601 +Morphable hundred-core heterogeneous architecture +for energy-aware computation +Nuno Neves, Henrique Mendes, Ricardo Jorge Chaves, Pedro Tomás, Nuno Roma +INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Rua Alves Redol, 9, 1000-029 Lisboa, Portugal +E-mail:"
+e3e44385a71a52fd483c58eb3cdf8d03960c0b70,A Hierarchical Graphical Model for Recognizing Human Actions and Interactions in Video,"Copyright +Sangho Park"
+e3582dffe5f3466cc5bc9d736934306c551ab33c,AttGAN: Facial Attribute Editing by Only Changing What You Want,"SUBMITTED MANUSCRIPT TO IEEE TRANSACTIONS ON IMAGE PROCESSING +AttGAN: Facial Attribute Editing by +Only Changing What You Want +Zhenliang He, Wangmeng Zuo, Senior Member, IEEE, Meina Kan, Member, IEEE, +Shiguang Shan, Senior Member, IEEE, and Xilin Chen, Fellow, IEEE +i.e.,"
+e3b92cc14f2c33bfdc07b794292a30384f8d0ad1,Local Segmentation for Pedestrian Tracking in Dense Crowds,"Local Segmentation for Pedestrian Tracking in +Dense Crowds +Clement Creusot +Toshiba RDC, Kawasaki, Japan, +http://clementcreusot.com/pedestrian"
+e3bbdd6efc906f6ae17e5b1d62497420991b977d,Visual Explanation by High-Level Abduction: On Answer-Set Programming Driven Reasoning about Moving Objects,"Visual Explanation by High-Level Abduction +On Answer-Set Programming Driven Reasoning about Moving Objects +Jakob Suchan1, Mehul Bhatt1,2, Przemysław Wał˛ega3, and Carl Schultz4 +Cognitive Vision – www.cognitive-vision.org +EASE CRC – http://ease-crc.org +HCC Lab., University of Bremen, Germany, 2MPI Lab., Örebro University, Sweden +University of Warsaw, Poland, and 4Aarhus University, Denmark"
+e3f0c5a51d6c5085fbcb64d872d7db438da27474,Ubiquitously Supervised Subspace Learning,"Ubiquitously Supervised Subspace Learning +Jianchao Yang, Student Member, IEEE, Shuicheng Yan, Member, IEEE, and Thomas S. Huang, Life Fellow, IEEE"
+e39f9565903a9701657ce3ade94c37d8a12f702e,Audio-Visual Scene Analysis with Self-Supervised Multisensory Features,"Audio-Visual Scene Analysis with +Self-Supervised Multisensory Features +Andrew Owens Alexei A. Efros +UC Berkeley"
+e39af9fb267c9deb81f9c73bbd71f5674b4358c0,Conceptualizing and Measuring Well-Being Using Statistical Semantics and Numerical Rating Scales,"Conceptualizing and Measuring Well-Being Using Statistical Semantics and Numerical +Rating Scales +Kjell, Oscar +Published: 2018-03-01 +Document Version +Publisher's PDF, also known as Version of record +Link to publication +Citation for published version (APA): +Kjell, O. (2018). Conceptualizing and Measuring Well-Being Using Statistical Semantics and Numerical Rating +Scales Lund +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors +nd/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the +legal requirements associated with these rights. +• Users may download and print one copy of any publication from the public portal for the purpose of private +study or research. +• You may not further distribute the material or use it for any profit-making activity or commercial gain +• You may freely distribute the URL identifying the publication in the public portal +LUND UNIVERSITYPO Box 117221 00 Lund+46 46-222 00 00"
+e31f24b92a19aeb9a7611a9ca09223c8f5238ae1,Expression Empowered ResiDen Network for Facial Action Unit Detection,"RESIDEN: RESIDUE FLOW IN DENSENET +Expression Empowered ResiDen Network +for Facial Action Unit Detection +Shreyank Jyoti +Abhinav Dhall +Learning Affect and Semantic Image +nalysIs (LASII) Group, +Indian Institute of Technology Ropar +Punjab, India"
e3917d6935586b90baae18d938295e5b089b5c62,Face localization and authentication using color and depth images,"Face Localization and Authentication Using Color and Depth Images Filareti Tsalakanidou, Sotiris Malassiotis, and Michael G. Strintzis, Fellow, IEEE"
@@ -5302,13 +18177,107 @@ Optical-Flow Estimation in the Wild Nima Sedaghat University of Freiburg Germany"
+e38709a2ec162a6f2a2fa3b4b6463e752267b154,Super-resolution for Face Recognition Based on Correlated Features and Nonlinear Mappings,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE +ICASSP 2010"
+e309632d479b8f59e615d0f3c4bc69938361d187,Deep Learning for Imbalance Data Classification using Class Expert Generative Adversarial Network,"Deep Learning for Imbalance Data Classification using Class Expert +Generative Adversarial Network +Fannya, Tjeng Wawan Cenggoroa,b +Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, Indonesia 11480 +Bioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta, Indonesia 11480"
+e3c5c5623af4b1a1f719cac24850dcaa6a304bd5,Training Effective Node Classifiers for Cascade Classification,"ppearing in Int. J. Comput. Vis.; content may change prior to final publication. +Training Effective Node Classifiers for Cascade +Classification +Chunhua Shen · Peng Wang · Sakrapee Paisitkriangkrai · +Anton van den Hengel +December 2012"
+e3660a13fcd75cf876a6ce355c2c1a578cfb57cb,2DHMM-Based Face Recognition Method,"DHMM-BASED FACE RECOGNITION +METHOD +Janusz Bobulski1 +Czestochowa University of Technology +Institute of Computer and Information Science +Dabrowskiego Street 73, 42-200 Czestochowa, Poland +Summary. So far many methods of recognizing the face arose, each has the merits +nd demerits. Among these methods are methods based on Hidden Markov models, +nd their advantage is the high efficiency. However, the traditional HMM uses one- +dimensional data, which is not a good solution for image processing, because the +images are two-dimensional. Transforming the image in a one-dimensional feature +vector, we remove some of the information that can be used for identification. The +rticle presents the full ergodic 2D-HMM and applied for face identification. +Introduction +Face recognition has great potentials in many applications dealing with unco- +operative subjects, in which the full power of face recognition being a passive +iometric technique can be implemented and utilised. Face recognition has +een an active area of research in image processing and computer vision due +to its extensive range of prospective applications relating to biometrics, infor- +mation security, video surveillance, law enforcement, identity authentication,"
+cf77d2e7411814b30aca203376709b12a0eb3e08,Obtaining Better Image Representations by Combining Complementary Activation Features of Multiple ConvNet Layers for Transfer Learning,"Obtaining Better Image Representations by +Combining Complementary Activation Features of +Multiple ConvNet Layers for Transfer Learning +Jumabek Alikhanov +School of Computer and +Information Engineering +Seunghyun Ko +School of Computer and +Information Engineering +Jo Geun Sik +School of Computer and +Information Engineering +Inha University Incheon, South Korea +Inha University Incheon, South Korea +Inha University Incheon, South Korea +Email: +Email: +Email:"
+cf98c333c8d7d5870c1ce5538bb0c3de3de16657,Panoptic Segmentation,"Panoptic Segmentation +Alexander Kirillov1,2 Kaiming He1 Ross Girshick1 Carsten Rother2 +Piotr Doll´ar1 +Facebook AI Research (FAIR) +HCI/IWR, Heidelberg University, Germany"
+cf40951840bfa9b8721d722e9422c73e3a6fbf59,Real-time Appearance-based Person Re-identification Over Multiple KinectTM Cameras,"Real-time appearance-based person re-identification +over multiple KinectTMcameras +Riccardo Satta, Federico Pala, Giorgio Fumera and Fabio Roli +Department of Electrical and Electronic Engineering, University of Cagliari, Italy +{riccardo.satta, fumera, +Keywords: +Video surveillance, Person Re-identification, Kinect"
+cf280435c471ee099148c4eb9eb2e106ccb2b218,HoME: a Household Multimodal Environment,"HoME: a Household Multimodal Environment +Simon Brodeur1, Ethan Perez2,3∗, Ankesh Anand2∗, Florian Golemo2,4∗, +Luca Celotti1, Florian Strub2,5, Jean Rouat1, Hugo Larochelle6,7, Aaron Courville2,7 +Université de Sherbrooke, 2MILA, Université de Montréal, 3Rice University, 4INRIA Bordeaux, +5Univ. Lille, Inria, UMR 9189 - CRIStAL, 6Google Brain, 7CIFAR Fellow +{simon.brodeur, luca.celotti, +{florian.golemo, +{ankesh.anand,"
+cfc22c35ad191cf9d70f4a3655840748b0e1322c,Real-Time Dense Mapping for Self-driving Vehicles using Fisheye Cameras,"Real-Time Dense Mapping +for Self-Driving Vehicles using Fisheye Cameras +Zhaopeng Cui1, Lionel Heng2, Ye Chuan Yeo2, Andreas Geiger3, Marc Pollefeys1,4, and Torsten Sattler1"
+cfcf66e4b22dc7671a5941e94e9d4afae75ba2f8,The Cramer Distance as a Solution to Biased Wasserstein Gradients,"The Cramer Distance as a Solution to Biased +Wasserstein Gradients +Marc G. Bellemare1, Ivo Danihelka1,3, Will Dabney1, Shakir Mohamed1 +Balaji Lakshminarayanan1, Stephan Hoyer2, Rémi Munos1 +Google DeepMind, London UK, 2Google +CoMPLEX, Computer Science, UCL"
cfffae38fe34e29d47e6deccfd259788176dc213,Training bookcowgrass flower ? ? water sky doggrass water boat water chair road ? cow grass chair grass dog building ?,"TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, DECEMBER 2012 Matrix Completion for Weakly-supervised Multi-label Image Classification Ricardo Cabral, Fernando De la Torre, João P. Costeira, Alexandre Bernardino"
-cfd4004054399f3a5f536df71f9b9987f060f434,Person Recognition in Social Media Photos,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. ??, NO. ??, ?? 20?? -Person Recognition in Personal Photo Collections +cfd4004054399f3a5f536df71f9b9987f060f434,Person Recognition in Social Media Photos,"Person Recognition in Personal Photo Collections Seong Joon Oh,Rodrigo Benenson, Mario Fritz, and Bernt Schiele, Fellow, IEEE"
+cf216fcd4cf537e53b9ed4f46e59c445e845cfc5,Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization,"Noname manuscript No. +(will be inserted by the editor) +Nonnegative Restricted Boltzmann Machines for +Parts-based Representations Discovery and +Predictive Model Stabilization +Tu Dinh Nguyen, Truyen Tran, Dinh +Phung, Svetha Venkatesh +the date of receipt and acceptance should be inserted later"
+cf8f5cad6aa87a6364f6b5dd985116b902050acf,Slack and Margin Rescaling as Convex Extensions of Supermodular Functions,"Slack and Margin Rescaling as Convex Extensions of +Supermodular Functions +Matthew B. Blaschko +Center for Processing Speech & Images +Departement Elektrotechniek, KU Leuven +Kasteelpark Arenberg 10 +001 Leuven, Belgium"
cfd933f71f4a69625390819b7645598867900eab,Person Authentication Using Face And Palm Vein: A Survey Of Recognition And Fusion Techniques,"INTERNATIONAL JOURNAL OF TECHNOLOGY ENHANCEMENTS AND EMERGING ENGINEERING RESEARCH, VOL 3, ISSUE 03 55 ISSN 2347-4289 Person Authentication Using Face And Palm Vein: @@ -5317,6 +18286,26 @@ Preethi M, Dhanashree Vaidya, Dr. S. Kar, Dr. A. M. Sapkal, Dr. Madhuri A. Joshi Dept. of Electronics and Telecommunication, College of Engineering, Pune, India, Image Processing & Machine Vision Section, Electronics & Instrumentation Services Division, BARC Email:"
+cf2a313b039b8adfee2a14ca5e81f2f5da52b0f2,Learning Fashion Traits with Label Uncertainty,"Learning Fashion Traits with Label Uncertainty +Gal Levi +Eli Alshan +Assaf Neuberger +Amazon Lab 126 +Herzliya, Israel 4672560 +Amazon Lab 126 +Herzliya, Israel 4672560 +Amazon Lab 126 +Herzliya, Israel 4672560 +Sharon Alpert +Amazon Lab 126 +Herzliya, Israel 4672560 +Eduard Oks +Amazon Lab 126 +Herzliya, Israel 4672560"
+cf65c5cfa2a2b0370407810479f179f5fbe88fb1,Multi-Modal Biometrics: An Overview,"Multi-Modal Biometrics: An Overview +Kevin W. Bowyer,1 K. I. Chang,1 P. Yan,1 P. J. Flynn,1 E. Hansley,2 S. Sarkar2 +. Computer Science and Engineering / University of Notre Dame / Notre Dame, IN 46556 USA +. Computer Science and Engineering / University of South Florida / Tampa, FL 33620 USA"
cf875336d5a196ce0981e2e2ae9602580f3f6243,"7 What 1 S It Mean for a Computer to ""have"" Emotions?","7 What 1 Rosalind W. Picard It Mean for a Computer to ""Have"" Emotions? @@ -5378,9 +18367,58 @@ L’archive ouverte pluridisciplinaire HAL, est destin´ee au d´epˆot et `a la diffusion de documents scientifiques de niveau recherche, publi´es ou non, ´emanant des ´etablissements d’enseignement et de"
+cffc94574c8796cbd8234422a979e57e67eca7b5,Multiracial Children's and Adults' Categorizations of Multiracial Individuals.,"Journal of Cognition and Development +ISSN: 1524-8372 (Print) 1532-7647 (Online) Journal homepage: http://www.tandfonline.com/loi/hjcd20 +Multiracial Children’s and Adults’ Categorizations +of Multiracial Individuals +Steven O. Roberts & Susan A. Gelman +To cite this article: Steven O. Roberts & Susan A. Gelman (2017) Multiracial Children’s and +Adults’ Categorizations of Multiracial Individuals, Journal of Cognition and Development, 18:1, +-15, DOI: 10.1080/15248372.2015.1086772 +To link to this article: http://dx.doi.org/10.1080/15248372.2015.1086772 +Accepted author version posted online: 23 +Feb 2016. +Published online: 23 Feb 2016. +Submit your article to this journal +Article views: 75 +View related articles +View Crossmark data +Citing articles: 2 View citing articles +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=hjcd20 +Download by: [University of Michigan]"
+cf009a6b02fbef514a4bac9695a928080ceac764,COLUMBUS: Feature Selection on Data Analytics Systems,"COLUMBUS: Feature Selection on Data Analytics Systems +Arun Kumar +Pradap Konda +Christopher R´e +February 28, 2013"
+cf7e6d057e6ef01904770be3dfc9da29f9c1e197,An Adaptive Detection Method of Multiple Faces,"TELKOMNIKA Indonesian Journal of Electrical Engineering +Vol.12, No.4, April 2014, pp. 2743 ~ 2752 +DOI: http://dx.doi.org/10.11591/telkomnika.v12i4.4368 +An Adaptive Detection Method of Multiple Faces + 2743 +China West Normal University, No. 1 Shida Road, Computer School, Nanchong, China +*Corresponding author, e-mail: +Wei Li"
+cf7b4fa0a8b58473b94496f353f3c8d0f9531b71,Recognition of 3 D Frontal Face Images Using Local Ternary Patterns and MLDA Algorithm,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Impact Factor (2012): 3.358 +Recognition of 3D Frontal Face Images Using Local +Ternary Patterns and MLDA Algorithm +Dr. T. Karthikeyan1, T. K. Sumathi2 +Associate Professor, PSG College of Arts & Science, Coimbatore +Research Scholar, Karpagam University, Coimbatore +identification"
+cfc9056155bf32648448b588a752f694b4e8249c,Combining Contrast Information and Local Binary Patterns for Gender Classification,"Combining Contrast Information and Local +Binary Patterns for Gender Classification +Juha Ylioinas, Abdenour Hadid, and Matti Pietik¨ainen +Machine Vision Group, PO Box 4500, +FI-90014 University of Oulu, Finland"
cfdc632adcb799dba14af6a8339ca761725abf0a,Probabilistic Formulations of Regression with Mixed Guidance,"Probabilistic Formulations of Regression with Mixed Guidance Aubrey Gress, Ian Davidson University of California, Davis"
+cfbfcf538c1c9bbf170a524995098fe4aacde374,Symmetric generalized low rank approximations of matrices,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE +ICASSP 2012"
cfc30ce53bfc204b8764ebb764a029a8d0ad01f4,Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization,"Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization Hyeonwoo Noh @@ -5388,6 +18426,21 @@ Tackgeun You Dept. of Computer Science and Engineering, POSTECH, Korea Jonghwan Mun Bohyung Han"
+cf6527d8d42a9958eea7d8d1f90ea4c86d591408,Convolutional Neural Network-Based Classification of Driver’s Emotion during Aggressive and Smooth Driving Using Multi-Modal Camera Sensors,"Article +Convolutional Neural Network-Based Classification +of Driver’s Emotion during Aggressive and Smooth +Driving Using Multi-Modal Camera Sensors +Kwan Woo Lee, Hyo Sik Yoon, Jong Min Song and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (K.W.L.); (H.S.Y.); +(J.M.S.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 20 February 2018; Accepted: 21 March 2018; Published: 23 March 2018"
+cf74dceae075bde213d2aafad115d2afc893c21b,Master's Thesis : Deep Learning for Visual Recognition,"Master’s Thesis +Deep Learning for Visual Recognition +Supervised by Nicolas Thome and Matthieu Cord +Remi Cadene +Wednesday 7th September, 2016"
cf805d478aeb53520c0ab4fcdc9307d093c21e52,Finding Tiny Faces in the Wild with Generative Adversarial Network,"Finding Tiny Faces in the Wild with Generative Adversarial Network Yancheng Bai1 Yongqiang Zhang1 @@ -5400,10 +18453,25 @@ Institute of Software, Chinese Academy of Sciences (CAS) Figure1. The detection results of tiny faces in the wild. (a) is the original low-resolution blurry face, (b) is the result of re-sizing directly by a bi-linear kernel, (c) is the generated image by the super-resolution method, and our result (d) is learned y the super-resolution (×4 upscaling) and refinement network simultaneously. Best viewed in color and zoomed in."
+cf103f2fe5595a55f918ecbd9119800f4747fc8e,Human recognition based on ear shape images using PCA-Wavelets and different classification methods,"Human recognition based on ear shape images using +PCA-Wavelets and different classification methods +Ali Mahmoud Mayya1* and Mariam Mohammad Saii +PhD student, Computer Engineering, Tishreen University, Syria"
cf86616b5a35d5ee777585196736dfafbb9853b5,Learning Multiscale Active Facial Patches for Expression Analysis,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. Learning Multiscale Active Facial Patches for Expression Analysis Lin Zhong, Qingshan Liu, Peng Yang, Junzhou Huang, and Dimitris N. Metaxas, Senior Member, IEEE"
+cabe652bb3b150f35db9db1434cec69f081c4a60,Towards Scene Understanding: Deep and Layered Recognition and Heuristic Parsing of Objects,"Towards Scene Understanding: Deep and Layered Recognition +nd Heuristic Parsing of Objects +Dissertation Submitted to +Xi’an Jiaotong University +In partial fulfillment of the requirement +for the degree of +Doctor of Engineering Science +Yang Wu +(Control Science and Engineering) +Supervisor: Prof. Nanning Zheng +May 2010"
cacd51221c592012bf2d9e4894178c1c1fa307ca,Face and Expression Recognition Techniques: A Review,"ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) @@ -5422,11 +18490,36 @@ Department of Informatics Box 451 54124 Thessaloniki, Greece email:"
+cae87d5a724507e06f6d8178cfbec043db854fe3,Bayesian Nonparametric Latent Feature Models,"Bayesian Nonparametric Latent Feature Models +Kurt Miller +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2011-78 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-78.html +June 28, 2011"
+cac3bf3ceba79e6a6c8e51eb44c6862b81661f85,Learning Data-Driven Representations for Robust Monocular Computer Vision Applications,"Learning Data-Driven Representations for +Robust Monocular Computer Vision +Applications +Dissertation +der Mathematisch-Naturwissenschaftlichen Fakultät +der Eberhard Karls Universität Tübingen +zur Erlangung des Grades eines +Doktors der Naturwissenschaften +(Dr. rer.-nat.) +Dipl.-math. Christian Joachim Herdtweck +vorgelegt von +us Stuttgart +Tübingen"
cad52d74c1a21043f851ae14c924ac689e197d1f,From Ego to Nos-Vision: Detecting Social Relationships in First-Person Views,"From Ego to Nos-vision: Detecting Social Relationships in First-Person Views Stefano Alletto, Giuseppe Serra, Simone Calderara, Francesco Solera and Rita Cucchiara Universit`a degli Studi di Modena e Reggio Emilia Via Vignolese 905, 41125 Modena - Italy"
+ca6b2b75db9ff8444744df9149601a4ef2beefd4,MirBot: A Multimodal Interactive Image Retrieval System,"MirBot: A multimodal interactive +image retrieval system +Antonio Pertusa, Antonio-Javier Gallego, and Marisa Bernabeu +DLSI, University of Alicante +http://www.dlsi.ua.es"
cad24ba99c7b6834faf6f5be820dd65f1a755b29,"Understanding hand-object manipulation by modeling the contextual relationship between actions, grasp types and object attributes","Understanding hand-object manipulation by modeling the ontextual relationship between actions, @@ -5452,12 +18545,62 @@ Dr. C. Piguet, rapporteur Soutenue le 2 juin 2005 INSTITUT DE MICROTECHNIQUE UNIVERSITÉ DE NEUCHÂTEL"
+ca1db9dc493a045e3fadf8d8209eaa4311bbdc70,Effective Image Retrieval via Multilinear Multi-index Fusion,"JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, JUNE 2017 +Effective Image Retrieval via Multilinear +Multi-index Fusion +Zhizhong Zhang, Yuan Xie, Member, IEEE, Wensheng Zhang, Qi Tian, Fellow, IEEE,"
+cab372bc3824780cce20d9dd1c22d4df39ed081a,"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","DeepLab: Semantic Image Segmentation with +Deep Convolutional Nets, Atrous Convolution, +nd Fully Connected CRFs +Liang-Chieh Chen, George Papandreou, Senior Member, IEEE, Iasonas Kokkinos, Member, IEEE, +Kevin Murphy, and Alan L. Yuille, Fellow, IEEE"
ca37eda56b9ee53610c66951ee7ca66a35d0a846,Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection,"Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection Xiaojun Chang1,2, Yi Yang1, Alexander G. Hauptmann2, Eric P. Xing3 and Yao-Liang Yu3∗ Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney. Language Technologies Institute, Carnegie Mellon University. Machine Learning Department, Carnegie Mellon University. {cxj273, {alex, epxing,"
+ca400e0c7a739ce5555b2e3eccccbcea65e71b11,Neural Mechanisms of Emotion Regulation in Autism Spectrum Disorder.,"J Autism Dev Disord +DOI 10.1007/s10803-015-2359-z +S I : E M O T I O N R E G U L A T I O N A N D P S Y C H I A T R I C C O M O R B I D I T Y I N A S D +Neural Mechanisms of Emotion Regulation in Autism Spectrum +Disorder +J. Anthony Richey • Cara R. Damiano • Antoinette Sabatino • Alison Rittenberg • +Chris Petty • Josh Bizzell • James Voyvodic • Aaron S. Heller • Marika C. Coffman • +Moria Smoski • Richard J. Davidson • Gabriel S. Dichter +Ó Springer Science+Business Media New York 2015 +ccount of"
+ca8b529e389381c8b51ddf83788b7a3eafb8f859,Efficient CNN Implementation for Eye-Gaze Estimation on Low-Power/Low-Quality Consumer Imaging Systems,"Efficient CNN Implementation for Eye-Gaze +Estimation on Low-Power/Low-Quality Consumer +Imaging Systems +Joseph Lemley, Student Member, IEEE, Anuradha Kar, Student Member, IEEE, Alexandru +Drimbarean, Member, IEEE, and Peter Corcoran, Fellow, IEEE"
+ca754b826476b3e4083a0a6fbac3ac39b494fd43,Supporting data-driven I/O on GPUs using GPUfs,"Supporting data-driven I/O on GPUs using GPUfs +Sagi Shahar +Mark Silberstein +Technion - Israel Institute of Technology +Technion - Israel Institute of Technology +Computations on large data sets necessarily involve file +ccesses, but current GPUs cannot access a host file system +directly because they lack file system access support. There- +fore, an application developer needs to coordinate GPU ac- +esses to secondary storage via explicit application-level +management code running on a CPU. This code performs +file accesses on GPU’s behalf and manages low level data +transfers to/from GPU memory. Furthermore, all the data +that a GPU may need must be resident in the GPU mem- +ory prior to computations, and it is the responsibility of a +GPU developer to ensure that this is the case. As a result, all +the potential GPU accesses to data must be known before the +GPU execution starts. This requirement impedes the use of +GPUs to run data processing algorithms with irregular data +ccess pattern on large datasets."
+ca581cd5bd0cecf346f2bc47f4b67bfee31b9da1,"Providing Fairness in Heterogeneous Multicores with a Predictive, Adaptive Scheduler","Providing Fairness in Heterogeneous Multicores with a Predictive, Adaptive +Scheduler +Saeid Barati +University of Chicago +Henry Hoffmann +University of Chicago"
ca606186715e84d270fc9052af8500fe23befbda,"Using subclass discriminant analysis, fuzzy integral and symlet decomposition for face recognition","Using Subclass Discriminant Analysis, Fuzzy Integral and Symlet Decomposition for Face Recognition Seyed Mohammad Seyedzade @@ -5475,12 +18618,75 @@ Narmak, Tehran, Iran Email: Narmak, Tehran, Iran Email:"
+ca494a2f20c267210a677ed9c509c4570f420fdf,Learning to Globally Edit Images with Textual Description,"Learning to Globally Edit Images +with Textual Description +Hai Wang † Jason D. Williams ‡ Sing Bing Kang §"
+cad7845e9668884caf4842b14983ec0e45bbbc75,Urban Tracker: Multiple object tracking in urban mixed traffic,"Urban Tracker: Multiple Object Tracking in Urban Mixed Traffic +Jean-Philippe Jodoin, Guillaume-Alexandre Bilodeau +LITIV lab., Dept. of computer & software eng. +´Ecole Polytechnique de Montr´eal +Montr´eal, QC, Canada +Nicolas Saunier +Dept. of civil, geo. and mining eng. +´Ecole Polytechnique de Montr´eal +Montr´eal, QC, Canada"
+e4896772d51a66b743e0d072d53cf26f6b61fc75,Automated Identification of Trampoline Skills Using Computer Vision Extracted Pose Estimation,"Automated Identification of Trampoline Skills +Using Computer Vision Extracted Pose Estimation +Paul W. Connolly, Guenole C. Silvestre and Chris J. Bleakley +School of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland."
e4bf70e818e507b54f7d94856fecc42cc9e0f73d,Face Recognition under Varying Blur in an Unconstrained Environment,"IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 FACE RECOGNITION UNDER VARYING BLUR IN AN UNCONSTRAINED ENVIRONMENT Anubha Pearline.S1, Hemalatha.M2 M.Tech, Information Technology,Madras Institute of Technology, TamilNadu,India, Assistant Professor, Information Technology,Madras Institute of Technology, TamilNadu,India, email:,"
+e4485930357db8248543eb78ce3bc9f32050694e,Drawn to danger: trait anger predicts automatic approach behaviour to angry faces.,"Cognition and Emotion +ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20 +Drawn to danger: trait anger predicts automatic +pproach behaviour to angry faces +Lotte Veenstra, Iris K. Schneider, Brad J. Bushman & Sander L. Koole +To cite this article: Lotte Veenstra, Iris K. Schneider, Brad J. Bushman & Sander L. Koole (2016): +Drawn to danger: trait anger predicts automatic approach behaviour to angry faces, Cognition +nd Emotion, DOI: 10.1080/02699931.2016.1150256 +To link to this article: http://dx.doi.org/10.1080/02699931.2016.1150256 +Published online: 19 Feb 2016. +Submit your article to this journal +Article views: 39 +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pcem20 +Download by: [Vrije Universiteit Amsterdam] +Date: 04 April 2016, At: 13:19"
+e4d2cc8fe567e8e1f2e0c5eb751ff9e9361346c0,ALTERED BRAIN ACTIVITY IN AUTISTIC CHILDREN VERSUS HEALTHY CONTROLS WHILE PERFORMING SIMPLE TASKS USING fMRI,"Copyright Warning & Restrictions +The copyright law of the United States (Title 17, United +States Code) governs the making of photocopies or other +reproductions of copyrighted material. +Under certain conditions specified in the law, libraries and +rchives are authorized to furnish a photocopy or other +reproduction. One of these specified conditions is that the +photocopy or reproduction is not to be “used for any +purpose other than private study, scholarship, or research.” +If a, user makes a request for, or later uses, a photocopy or +reproduction for purposes in excess of “fair use” that user +may be liable for copyright infringement, +This institution reserves the right to refuse to accept a +opying order if, in its judgment, fulfillment of the order +would involve violation of copyright law. +Please Note: The author retains the copyright while the +New Jersey Institute of Technology reserves the right to +distribute this thesis or dissertation +Printing note: If you do not wish to print this page, then select +“Pages from: first page # to: last page #” on the print dialog screen"
+e4d33362b4f99ab77fd6ceaafa183c087c79faea,Design and implementation of a high performance pedestrian detection,"June 23-26, 2013, Gold Coast, Australia +978-1-4673-2754-1/13/$31.00 ©2013 Crown"
+e4a05b1a478a2aeb6c0b1a4a42f8bdb4f97122f6,Quality Fusion Rule for Face Recognition in Video,"Quality Fusion Rule for Face Recognition in Video +Chao Wang, Yongping Li, and Xinyu Ao +The center for Advanced Detection and Instrumentation, Shanghai Institute of Applied Physics, +Chinese Academy of Science, 201800 Shanghai, China"
+e4501da190012623d5048d57b7e650de27643b8d,Learning Actionlet Ensemble for 3D Human Action Recognition,"Chapter 2 +Learning Actionlet Ensemble for 3D Human +Action Recognition"
e4a1b46b5c639d433d21b34b788df8d81b518729,Side Information for Face Completion: a Robust PCA Approach,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 Side Information for Face Completion: a Robust PCA Approach @@ -5488,17 +18694,102 @@ Niannan Xue, Student Member, IEEE, Jiankang Deng, Student Member,IEEE, Shiyang Cheng, Student Member,IEEE, Yannis Panagakis, Member,IEEE, nd Stefanos Zafeiriou, Member, IEEE"
e4c81c56966a763e021938be392718686ba9135e,Bio-Inspired Architecture for Clustering into Natural and Non-Natural Facial Expressions,",100+OPEN ACCESS BOOKS103,000+INTERNATIONALAUTHORS AND EDITORS106+ MILLIONDOWNLOADSBOOKSDELIVERED TO151 COUNTRIESAUTHORS AMONGTOP 1%MOST CITED SCIENTIST12.2%AUTHORS AND EDITORSFROM TOP 500 UNIVERSITIESSelection of our books indexed in theBook Citation Index in Web of Science™Core Collection (BKCI)Chapter from the book Visual Cortex - Current Status and PerspectivesDownloaded from: http://www.intechopen.com/books/visual-cortex-current-status-and-perspectivesPUBLISHED BYWorld's largest Science,Technology & Medicine Open Access book publisherInterested in publishing with InTechOpen?Contact us at"
+e4d08ef1b4350c7e03bdfb716200370c2ea87a6a,A novel approach for face recognition using fused GMDH-based networks,"The International Arab Journal of Information Technology, Vol. 15, No. 3, May 2018 369 +A Novel Approach for Face Recognition Using +Fused GMDH-Based Networks +El-Sayed El-Alfy1, Zubair Baig2, and Radwan Abdel-Aal1 +College of Computer Sciences and Engineering, King Fahd University of Petroleum and Minerals, KSA +School of Science and Security Research Institute, Edith Cowan University, Australia"
e4e95b8bca585a15f13ef1ab4f48a884cd6ecfcc,Face Recognition with Independent Component Based Super-resolution,"Face Recognition with Independent Component Based Super-resolution Osman Gokhan Sezer†,a, Yucel Altunbasakb, Aytul Ercila Faculty of Engineering and Natural Sciences, Sabanci Univ., Istanbul, Turkiye, 34956 School of Elec. and Comp. Eng. , Georgia Inst. of Tech., Atlanta, GA, USA, 30332-0250"
+e4cbe39daed8700a1d6f4a25a3a98645c4f231d0,A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis,"Comput Optim Appl (2018) 70:395–418 +https://doi.org/10.1007/s10589-018-0002-6 +A nonconvex formulation for low rank subspace +lustering: algorithms and convergence analysis +Hao Jiang1 · Daniel P. Robinson1 +René Vidal1 · Chong You1 +Received: 14 July 2017 / Published online: 27 March 2018 +© Springer Science+Business Media, LLC, part of Springer Nature 2018"
+e46732f0c818b059420f68162363c9d1a9dc5395,Geometric and Physical Constraints for Head Plane Crowd Density Estimation in Videos,"Geometric and Physical Constraints for +Head Plane Crowd Density Estimation in Videos +Weizhe Liu(cid:63) Krzysztof Lis Mathieu Salzmann +Pascal Fua +Computer Vision Laboratory, ´Ecole Polytechnique F´ed´erale de Lausanne +{weizhe.liu, krzysztof.lis, mathieu.salzmann, +(EPFL)"
+e42e7735f94a8f498ef0bf790ab43a668f904848,Low-Latency Detec on and Tracking of Aircra in Very High-Resolu on Video Feeds,"Linköping University | Department of Computer and Information Science +Master thesis, 30 ECTS | Datateknik +018 | LIU-IDA/LITH-EX-A--18/022--SE +Low-Latency Detec(cid:415)on and +Tracking of Aircra(cid:332) in Very +High-Resolu(cid:415)on Video Feeds +Låglatent detek(cid:415)on och spårning av flygplan i högupplösta +videokällor +Jarle Mathiesen +Supervisor : Magnus Bång +Examiner : Erik Berglund +Linköpings universitet +SE–581 83 Linköping ++46 13 28 10 00 , www.liu.se"
e43ea078749d1f9b8254e0c3df4c51ba2f4eebd5,Facial Expression Recognition Based on Constrained Local Models and Support Vector Machines,"Facial Expression Recognition Based on Constrained Local Models and Support Vector Machines Nikolay Neshov1, Ivo Draganov2, Agata Manolova3"
+e45bcda905b897513f4cff9e5c0a5bf475674a02,"Domain Stylization: A Strong, Simple Baseline for Synthetic to Real Image Domain Adaptation","Domain Stylization: A Strong, Simple Baseline for +Synthetic to Real Image Domain Adaptation +Aysegul Dundar, Ming-Yu Liu, Ting-Chun Wang, John Zedlewski, Jan Kautz +NVIDIA"
+e48fa574960b23ba65b7ff1a732cc521213b5120,Mining Automatically Estimated Poses from Video Recordings of Top Athletes,"Mining Automatically Estimated Poses from Video Recordings +of Top Athletes +Rainer Lienhart∗ +University of Augsburg +uni-augsburg.de +Moritz Einfalt +University of Augsburg +uni-augsburg.de +Dan Zecha +University of Augsburg"
e4c2f8e4aace8cb851cb74478a63d9111ca550ae,Distributed One-class Learning,"DISTRIBUTED ONE-CLASS LEARNING Ali Shahin Shamsabadi(cid:63), Hamed Haddadi†, Andrea Cavallaro(cid:63) (cid:63)Queen Mary University of London,†Imperial College London"
+e41e1e4d9e578c29bf648e7098c466935b50f1a9,A Generative Model for Simultaneous Estimation of Human Body Shape and Pixel-Level Segmentation,"A Generative Model for Simultaneous +Estimation of Human Body Shape and +Pixel-level Segmentation +Ingmar Rauschert and Robert T. Collins +Pennsylvania State University, +University Park, 16802 PA, USA"
+e443cb55dcc54de848e9f0c11a6194568a875011,From passive to interactive object learning and recognition through self-identification on a humanoid robot,"From passive to interactive object learning and +recognition through self-identification on a humanoid +robot +Natalia Lyubova, Serena Ivaldi, David Filliat +To cite this version: +Natalia Lyubova, Serena Ivaldi, David Filliat. From passive to interactive object learning and +recognition through self-identification on a humanoid robot. Autonomous Robots, Springer +Verlag, 2015, pp.23. . +HAL Id: hal-01166110 +https://hal.archives-ouvertes.fr/hal-01166110 +Submitted on 22 Jun 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
+e44d8409bb5233bd1822555bf85095a80e27fd49,Spatio-temporal interaction model for crowd video analysis,"Spatio-temporal interaction model for crowd video analysis +Indian Institute of Technology Bombay +Indian Institute of Technology Bombay +Neha Bhargava +India +Subhasis Chaudhuri +India"
+e40007540c4813c81bc8b54dda4dd6f6c21deaa8,3d Face Recognition Using Patch Geodesic Derivative Pattern,"International Journal of Smart Electrical Engineering, Vol.2, No.3, Summer 2013 ISSN: 2251-9246 +pp.127:132 +D Face Recognition using Patch Geodesic Derivative Pattern"
e475e857b2f5574eb626e7e01be47b416deff268,Facial Emotion Recognition Using Nonparametric Weighted Feature Extraction and Fuzzy Classifier,"Facial Emotion Recognition Using Nonparametric Weighted Feature Extraction and Fuzzy Classifier Maryam Imani and Gholam Ali Montazer"
@@ -5518,6 +18809,29 @@ Souza e Silva Rosa Maria Meri Le˜ao Rio de Janeiro Janeiro de 2016"
+e467f7e2434ca74bdd4b19808a6b3d78b8c5ba1a,Feature Construction Using Evolution-COnstructed Features for General Object Recognition,"Feature Construction Using Evolution-COnstructed Features +for General Object Recognition +Kirt Dwayne Lillywhite +A dissertation submitted to the faculty of +Brigham Young University +in partial fulfillment of the requirements for the degree of +Doctor of Philosophy +Dah-Jye Lee, Chair +James K Archibald +Bryan S. Morse +Dan A. Ventura +Brent E. Nelson +Department of Electrical and Computer Engineering +Brigham Young University +April 2012 +Copyright c(cid:13) 2012 Kirt Dwayne Lillywhite +All Rights Reserved"
+e4d90019c312ed87a236a11374caeea9cc4e6940,Comparison Comparison PCA Train GMM Feature Reduction Classify GMM Threshold,"COVER SHEET +Cook, Jamie and Chandran, Vinod and Sridharan, Sridha and Fookes, Clinton (2004) Face +Recognition from 3D Data using Iterative Closest Point Algorithm and Gaussian Mixture Models. +In Proceedings 3D Data Processing, Visualisation and Transmission, Thessaloniki, Greece. +Accessed from http://eprints.qut.edu.au +Copyright 2004 the authors."
e4abc40f79f86dbc06f5af1df314c67681dedc51,Head Detection with Depth Images in the Wild,"Head Detection with Depth Images in the Wild Diego Ballotta, Guido Borghi, Roberto Vezzani and Rita Cucchiara Department of Engineering ”Enzo Ferrari” @@ -5527,6 +18841,21 @@ Head Detection, Head Localization, Depth Maps, Convolutional Neural Network" e4d0e87d0bd6ead4ccd39fc5b6c62287560bac5b,Implicit video multi-emotion tagging by exploiting multi-expression relations,"Implicit Video Multi-Emotion Tagging by Exploiting Multi-Expression Relations Zhilei Liu, Shangfei Wang*, Zhaoyu Wang and Qiang Ji"
+e48432872be1e0449f50c6807b274d57c87a641f,Human Body Extraction from Single Images Using Images Processing Techniques,"Human Body Extraction from Single Images Using Images +Processing Techniques +T.Ravichandra Babu +Associate Professor & HOD, +Department of ECE, +Katravath Rajendhar +PG Scholar-SSP, +Department of ECE, +Krishnamurthy Institute of Technology and +Krishnamurthy Institute of Technology and +Engineering. +Engineering. +that can +images +to cope with"
e48e94959c4ce799fc61f3f4aa8a209c00be8d7f,Design of an Efficient Real-Time Algorithm Using Reduced Feature Dimension for Recognition of Speed Limit Signs,"Hindawi Publishing Corporation The Scientific World Journal Volume 2013, Article ID 135614, 6 pages @@ -5585,10 +18914,50 @@ iMinds - Ghent University, Technologiepark 15, B-9052 Ghent, Belgium {toon.depessemier, Keywords: Recommender System, Face Recognition, Face Detection, TV, Emotion Detection."
+fecce467b42856eadb8dd0c08674d9381f52efab,The Role of Shape in Visual Recognition,"The Role of Shape in Visual Recognition +Bj¨orn Ommer"
+fe4986bbb10f3417372a02fed1218acb5162ddec,Classification model of arousal and valence mental states by EEG signals analysis and Brodmann correlations,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 6, No. 6, 2015 +Classification model of arousal and valence mental +states by EEG signals analysis and Brodmann +orrelations +Adrian Rodriguez Aguin˜aga and Miguel Angel Lo´pez Ram´ırez +Instituto Tecnolo´gico de Tijuana +Calzada del Tecnolo´gico S/N, Toma´s Aquino, 22414 +Tijuana, B.C. Me´xico +Mar´ıa del Rosario Baltazar Flores +Instituto Tecnolo´gico de Leo´n +Av. Tecnolo´gico S/N +Industrial Julia´n de Obrego´n, 37290 +Leo´n, Gto. Me´xico"
fe9c460d5ca625402aa4d6dd308d15a40e1010fa,Neural Architecture for Temporal Emotion Classification,"Neural Architecture for Temporal Emotion Classification Roland Schweiger, Pierre Bayerl, and Heiko Neumann Universit¨at Ulm, Neuroinformatik, Germany"
+fec9fb202906e6f136ae92c3a3540b2a84257c4e,Automatic Facial Feature Detection for Facial Expression Recognition,"AUTOMATIC FACIAL FEATURE DETECTION FOR FACIAL +EXPRESSION RECOGNITION +Taner Danisman, Marius Bilasco, Nacim Ihaddadene and Chabane Djeraba +LIFL - UMR CNRS 8022, University of Science and Technology of Lille, Villeneuve d'Ascq, France +Keywords: +Facial Feature Detection, Emotion Recognition, Eye Detection, Mouth Corner Detection."
+fe01e1099dc2ce02158de607be993f9fc8aade57,Aerial LaneNet: Lane Marking Semantic Segmentation in Aerial Imagery using Wavelet-Enhanced Cost-sensitive Symmetric Fully Convolutional Neural Networks,"Aerial LaneNet: Lane Marking Semantic +Segmentation in Aerial Imagery using +Wavelet-Enhanced Cost-sensitive Symmetric Fully +Convolutional Neural Networks +Seyed Majid Azimi, Peter Fischer, Marco Körner, and Peter Reinartz"
+fec5c0100c72d7c1c823a91dc146ecd5e98e77ff,Coherence criterion for region labelling and description,"Coherence criterion for region labelling and +description +Hichem Houissa +INRIA Rocquencourt +Domaine de Voluceau +Nozha Boujemaa +INRIA Rocquencourt +Domaine de Voluceau +Email: +Email:"
+fe7f5c7da203c48aa1a9a2468aae55c6e0053df9,Interactive Text2Pickup Network for Natural Language based Human-Robot Collaboration,"Interactive Text2Pickup Network for Natural Language based +Human-Robot Collaboration +Hyemin Ahn, Sungjoon Choi, Nuri Kim, Geonho Cha, and Songhwai Oh"
fe7e3cc1f3412bbbf37d277eeb3b17b8b21d71d5,Performance Evaluation of Gabor Wavelet Features for Face Representation and Recognition,"IOSR Journal of VLSI and Signal Processing (IOSR-JVSP) Volume 6, Issue 2, Ver. I (Mar. -Apr. 2016), PP 47-53 e-ISSN: 2319 – 4200, p-ISSN No. : 2319 – 4197 @@ -5599,6 +18968,54 @@ M. E. Ashalatha1, Mallikarjun S. Holi2 Dept. of Biomedical Engineering, Bapuji Institute of Engineering & Technology Davanagere, Karnataka,India Dept. of Electronics and Instrumentation Engineering, University B.D.T.College of Engineering, Visvesvaraya Technological University, Davanagere, Karnataka, India"
+fea0895326b663bf72be89151a751362db8ae881,Homocentric Hypersphere Feature Embedding for Person Re-identification,"Homocentric Hypersphere Feature Embedding for +Person Re-identification +Wangmeng Xiang, Jianqiang Huang, Xianbiao Qi, Xiansheng Hua, Fellow, IEEE and Lei Zhang, Fellow, IEEE"
+feb4bcd20de6ce4f9503ef01c87390e662538c15,Monocular Depth Estimation with Augmented Ordinal Depth Relationships,"Monocular Depth Estimation with Augmented +Ordinal Depth Relationships +Yuanzhouhan Cao, Tianqi Zhao, Ke Xian, Chunhua Shen, Zhiguo Cao"
+fef89593599b78db7d133fc6893519b3ee8ff8d2,3D Face recognition by ICP-based shape matching,"D Face recognition by ICP-based shape matching +Boulbaba Ben Amor1, Karima Ouji1, Mohsen Ardabilian1, Liming Chen1 +LIRIS Lab, Lyon Research Center for Images and Intelligent Information Systems, UMR 5205 CNRS +Centrale Lyon, France"
+fe466e84fa2e838adc3c37ee327cd68004ae08fe,MUTAN: Multimodal Tucker Fusion for Visual Question Answering,"MUTAN: Multimodal Tucker Fusion for Visual Question Answering +Hedi Ben-younes 1,2 * +R´emi Cadene 1* +Matthieu Cord 1 +Nicolas Thome 3 +Sorbonne Universit´es, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 4 place Jussieu, 75005 Paris +Heuritech, 248 rue du Faubourg Saint-Antoine, 75012 Paris +Conservatoire National des Arts et M´etiers"
+fe41550ed350df4cd731a5df3dca5b0ea13511db,Compact Generalized Non-local Network,"Compact Generalized Non-local Network +Kaiyu Yue1,3 Ming Sun1 Yuchen Yuan1 Feng Zhou2 Errui Ding1 Fuxin Xu3 +Baidu VIS 2Baidu Research +Central South University +{yuekaiyu, sunming05, yuanyuchen02, zhoufeng09,"
+feaedb6766f42e867aab7f1a33ba4d7ddacfc7aa,UvA-DARE ( Digital Academic Repository ) Tag-based Video Retrieval by Embedding Semantic Content in a Continuous Word,"UvA-DARE (Digital Academic Repository) +Tag-based Video Retrieval by Embedding Semantic Content in a Continuous Word +Space +Agharwal, A.; Kovvuri, R.; Nevatia, R.; Snoek, C.G.M. +Published in: +016 IEEE Winter Conference on Applications of Computer Vision: WACV 2016: Lake Placid, New York, USA, +7-10 March 2016 +0.1109/WACV.2016.7477706 +Link to publication +Citation for published version (APA): +Agharwal, A., Kovvuri, R., Nevatia, R., & Snoek, C. G. M. (2016). Tag-based Video Retrieval by Embedding +Semantic Content in a Continuous Word Space. In 2016 IEEE Winter Conference on Applications of Computer +Vision: WACV 2016: Lake Placid, New York, USA, 7-10 March 2016 (pp. 1354-1361). Piscataway, NJ: Institute +of Electrical and Electronic Engineers. DOI: 10.1109/WACV.2016.7477706 +General rights +It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +Disclaimer/Complaints regulations +If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask"
+fe030b87e3c985c9dedab130949e2868e3e5e7d5,Explaining Neural Networks Semantically,"Under review as a conference paper at ICLR 2019 +EXPLAINING NEURAL NETWORKS SEMANTICALLY +AND QUANTITATIVELY +Anonymous authors +Paper under double-blind review"
fea83550a21f4b41057b031ac338170bacda8805,Learning a Metric Embedding for Face Recognition using the Multibatch Method,"Learning a Metric Embedding for Face Recognition using the Multibatch Method @@ -5608,6 +19025,45 @@ Tal Rosenwein Shai Shalev-Shwartz Amnon Shashua Orcam Ltd., Jerusalem, Israel"
+fe005c5036ad646051cc779aafb63534bda14f06,The Hand Vein Pattern Used as a Biometric Feature,"The Hand Vein Pattern Used as a Biometric Feature +Master Literature Thesis +Annemarie Nadort +Amsterdam - May 2007"
+fe35639349a87808481e64f9cbea065339063154,Understanding deep learning via backtracking and deconvolution,"Fang J Big Data (2017) 4:40 +DOI 10.1186/s40537-017-0101-8 +METHODOLOGY +Understanding deep learning +via backtracking and deconvolution +Open Access +Xing Fang* +*Correspondence: +School of Information +Technology, Illinois State +University, Normal, IL, USA"
+febb6454a3bfbc76f4c7934854d377ac15666215,Improving the Accuracy of Face Annotation in Social Network,"International Journal of Computer Applications (0975 – 8887) +Volume 182 – No. 14, September 2018 +Improving the Accuracy of Face Annotation in Social +Network +C. Jayaramulu +Research Scholar +individual +Dayananda Sagar University, Bangalore +photographs."
+fed9e971e042b40cc659aca6e338d79dc1d4b59c,Grouping-by-id: Guarding against Adversar-,"Under review as a conference paper at ICLR 2018 +GROUPING-BY-ID: GUARDING AGAINST ADVERSAR- +IAL DOMAIN SHIFTS +Anonymous authors +Paper under double-blind review"
+fe8b2b2a2ace6d6af28dc0f1d63400554c8c675d,Random walk distances in data clustering and applications,"Adv Data Anal Classif (2013) 7:83–108 +DOI 10.1007/s11634-013-0125-7 +REGULAR ARTICLE +Random walk distances in data clustering +nd applications +Sijia Liu · Anastasios Matzavinos · +Sunder Sethuraman +Received: 28 September 2011 / Revised: 24 May 2012 / Accepted: 30 September 2012 / +Published online: 6 March 2013 +© Springer-Verlag Berlin Heidelberg 2013"
fe0c51fd41cb2d5afa1bc1900bbbadb38a0de139,Bayesian face recognition using 2D Gaussian-Hermite moments,"Rahman et al. EURASIP Journal on Image and Video Processing (2015) 2015:35 DOI 10.1186/s13640-015-0090-5 RESEARCH @@ -5631,6 +19087,9 @@ Univ.-Prof. Dr.-Ing. Til Aach Tag der m¨undlichen Pr¨ufung: 28. September 2011 Diese Dissertation ist auf den Internetseiten der Hochschulbibliothek online verf¨ugbar."
+c85aa12331bdeaba06d4c3e44b969e6060c3310c,Ensemble of Part Detectors for Simultaneous Classification and Localization,"Ensemble of Part Detectors for Simultaneous +Classification and Localization +Xiaopeng Zhang, Hongkai Xiong, Senior Member, IEEE, Weiyao Lin, Qi Tian, Fellow, IEEE"
c86e6ed734d3aa967deae00df003557b6e937d3d,Generative Adversarial Networks with Decoder-Encoder Output Noise,"Generative Adversarial Networks with Decoder-Encoder Output Noise Guoqiang Zhong, Member, IEEE, Wei Gao, Yongbin Liu, Youzhao Yang @@ -5658,11 +19117,26 @@ Vincent Rapp Mohamed Chetouani Univ. Pierre & Marie Curie, ISIR - CNRS UMR 7222, F-75005, Paris - France {nicolle, bailly, rapp,"
+c84ca95638893700d8f806e844984a5b2c50b5e3,Automatic Facial Expression Recognition Using 3D Faces,"Paper 071, ENG 101 +Automatic Facial Expression Recognition Using 3D Faces +Chao Li, Antonio Soares +Florida A&M University +hao.li,"
+c8f035510b72b84c21430a887ed03c8836eeddc2,Optical-inertial Synchronization of MoCap Suit with Single Camera Setup for Reliable Position Tracking,
+c8f216dbd43dda14783677f44bb336c92211cd46,Synthesis from 3 D Mesh Sequences Driven by Combined Speech Features,"VISUAL SPEECH SYNTHESIS FROM 3D MESH SEQUENCES DRIVEN BY COMBINED +SPEECH FEATURES +Felix Kuhnke and J¨orn Ostermann +Institut f¨ur Informationsverarbeitung, Leibniz Universit¨at Hannover, Germany"
c866a2afc871910e3282fd9498dce4ab20f6a332,Surveillance Face Recognition Challenge,"Noname manuscript No. (will be inserted by the editor) Surveillance Face Recognition Challenge Zhiyi Cheng · Xiatian Zhu · Shaogang Gong Received: date / Accepted: date"
+c8dcb7b3c5ed43e61b90b50fedc76568d8e30675,Guarding against Adversarial Domain Shifts,"Under review as a conference paper at ICLR 2018 +GUARDING AGAINST ADVERSARIAL DOMAIN SHIFTS +WITH COUNTERFACTUAL REGULARIZATION +Anonymous authors +Paper under double-blind review"
c84233f854bbed17c22ba0df6048cbb1dd4d3248,Exploring Locally Rigid Discriminative Patches for Learning Relative Attributes,"Y. VERMA, C. V. JAWAHAR: EXPLORING PATCHES FOR RELATIVE ATTRIBUTES Exploring Locally Rigid Discriminative Patches for Learning Relative Attributes @@ -5672,6 +19146,43 @@ C. V. Jawahar http://www.iiit.ac.in/~jawahar/ IIIT-Hyderabad, India http://cvit.iiit.ac.in"
+c840d85f6dce0fb69fb6113923f17e1e314c6134,Disparity Sliding Window: Object Proposals From Disparity Images,"Disparity Sliding Window: Object Proposals From Disparity Images +Julian M¨uller1, Andreas Fregin2 and Klaus Dietmayer1"
+c8fc65c83473c633e2bf1c13031ccd10617cc8a2,Every Object Tells a Story,"Every Object Tells a Story +James Pustejovsky +Computer Science Department +Brandeis University +Waltham, MA 02453 +Nikhil Krishnaswamy +Computer Science Department +Brandeis University +Waltham, MA 02453"
+c896946612069f162864edfbecf5c1a8a077ed79,The Image Multi Feature Retrieval based on SVM Semantic Classification,"International Journal of Hybrid Information Technology +Vol.9, No.3 (2016), pp. 291-300 +http://dx.doi.org/10.14257/ijhit.2016.9.3.27 +The Image Multi Feature Retrieval based on SVM Semantic +Classification +Che Chang1,2*, Yu Xiaoyang1 and Bai Yamei3 +. Measuring and Control Technology and Instrumentations,Harbin University of +Science and Technology, Harbin, China +. School of Engineering,Harbin University, Harbin, China +. School of Electronic and Information Engineering,Harbin Huade University +Harbin, China +E-mail:"
+c8ebe4c7d884c468d572a1ccf8583ac912215088,Emotion Dysregulation and Anxiety in Adults with ASD: Does Social Motivation Play a Role?,"J Autism Dev Disord +DOI 10.1007/s10803-015-2567-6 +S . I . : A S D I N A D U L T H O O D : C O M O R B I D I T Y A N D I N T E R V E N T I O N +Emotion Dysregulation and Anxiety in Adults with ASD: Does +Social Motivation Play a Role? +Deanna Swain1 +• Angela Scarpa1 +• Susan White1 +• Elizabeth Laugeson2 +Ó Springer Science+Business Media New York 2015"
+c8855bebdaa985dfc4c1a07e5f74a0e29787e47e,Multi-label Object Attribute Classification using a Convolutional Neural Network,"Multi-label Object Attribute Classification using +Convolutional Neural Network +Soubarna Banik, Mikko Lauri, Simone Frintrop +Department of Informatics, Universit¨at Hamburg"
c81ee278d27423fd16c1a114dcae486687ee27ff,Search Based Face Annotation Using Weakly Labeled Facial Images,"Search Based Face Annotation Using Weakly Labeled Facial Images Shital Shinde1, Archana Chaugule2 @@ -5680,6 +19191,49 @@ D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18 Mahatma Phulenagar, 120/2 Mahaganpati soc, Chinchwad, Pune-19, MH, India D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18, Savitribai Phule Pune University DYPIET, Pimpri, Pune-18, MH, India"
+c867caf3f29abb2f3fd5c4c7e98e5f551a70be25,DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map,"DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map +Peng Wang, Ruigang Yang, Binbin Cao, Wei Xu, Yuanqing Lin +Baidu Research +National Engineering Laboratory for Deep Learning Technology and Applications +{wangpeng54, yangruigang, caobinbin, wei.xu,"
+c81326a1ecb7e71ae38a665779b8d959d3938d1a,A Novel Neural Network Model Specified for Representing Logical Relations,"A Novel Neural Network Model Specified for Representing Logical +Relations +Gang Wang +With computers to handle more and more complicated things in variable environments, it becomes an urgent requirement that +the artificial intelligence has the ability of automatic judging and deciding according to numerous specific conditions so as to deal +with the complicated and variable cases. ANNs inspired by brain is a good candidate. However, most of current numeric ANNs are +not good at representing logical relations because these models still try to represent logical relations in the form of ratio based on +functional approximation. On the other hand, researchers have been trying to design novel neural network models to make neural +network model represent logical relations. In this work, a novel neural network model specified for representing logical relations is +proposed and applied. New neurons and multiple kinds of links are defined. Inhibitory links are introduced besides exciting links. +Different from current numeric ANNs, one end of an inhibitory link connects an exciting link rather than a neuron. Inhibitory +model can simulate the operations of Boolean logic gates, and construct complex logical relations with the advantages of simpler +neural network structures than recent works in this area. This work provides some ideas to make neural networks represent logical +relations more directly and efficiently, and the model could be used as the complement to current numeric ANN to deal with logical +issues and expand the application areas of ANN. +Index Terms—Brain-inspired computing, logical representation, neural network structure, inhibitory link. +I. INTRODUCTION +With computers to handle more and more complicated +things in variable environments like driverless car and ad- +vanced medical diagnosis expert system, higher artificial intel-"
+c8ee4812c32b0ad4e26d53b99e1514514bbcaf14,A NEaT Design for Reliable and Scalable Network Stacks,"A NEaT Design for Reliable and Scalable +Network Stacks +Tomas Hruby +Cristiano Giuffrida +Lionel Sambuc +Herbert Bos +Andrew S. Tanenbaum +Vrije Universiteit Amsterdam"
+c8bcd8e0b2ab6cc00a565efbcf904235c33ac2dc,Unsupervised Person Image Synthesis in Arbitrary Poses,"Unsupervised Person Image Synthesis in Arbitrary Poses +Albert Pumarola +Antonio Agudo +Alberto Sanfeliu +Francesc Moreno-Noguer +Institut de Rob`otica i Inform`atica Industrial (CSIC-UPC) +08028, Barcelona, Spain +Figure 1: Given an original image of a person (left) and a desired body pose defined by a 2D skeleton (bottom-row), our +model generates new photo-realistic images of the person under that pose (top-row). The main contribution of our work is to +train this generative model with unlabeled data."
c83a05de1b4b20f7cd7cd872863ba2e66ada4d3f,A Deep Learning Perspective on the Origin of Facial Expressions,"BREUER, KIMMEL: A DEEP LEARNING PERSPECTIVE ON FACIAL EXPRESSIONS A Deep Learning Perspective on the Origin of Facial Expressions @@ -5689,23 +19243,213 @@ Department of Computer Science Technion - Israel Institute of Technology Technion City, Haifa, Israel Figure 1: Demonstration of the filter visualization process."
+c8e32484bbbc63908080284790edafc4b66008d2,Suivi par ré-identification dans un réseau de caméras à champs disjoints,"Suivi par r´e-identification dans un r´eseau de cam´eras `a +hamps disjoints +Boris Meden, Patrick Sayd, Fr´ed´eric Lerasle +To cite this version: +Boris Meden, Patrick Sayd, Fr´ed´eric Lerasle. Suivi par r´e-identification dans un r´eseau de +am´eras `a champs disjoints. RFIA 2012 (Reconnaissance des Formes et Intelligence Artificielle), +Jan 2012, Lyon, France. pp.978-2-9539515-2-3, 2012. +HAL Id: hal-00656507 +https://hal.archives-ouvertes.fr/hal-00656507 +Submitted on 17 Jan 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de"
+c813413fc84be33d7c4ccdd4a1f025ccc73a77bd,Discriminative Bayesian Active Shape Models,"Discriminative Bayesian Active Shape Models +Pedro Martins, Rui Caseiro, Jo˜ao F. Henriques, Jorge Batista +Institute of Systems and Robotics - University of Coimbra, Portugal"
+c81b303005459285a5864ea4de71f77025cd5be5,Norm-Induced Entropies for Decision Forests,"Norm-induced entropies for decision forests +Christoph Lassner +Rainer Lienhart +Multimedia Computing and Computer Vision Lab, University of Augsburg"
c8adbe00b5661ab9b3726d01c6842c0d72c8d997,Deep Architectures for Face Attributes,"Deep Architectures for Face Attributes Tobi Baumgartner, Jack Culpepper Computer Vision and Machine Learning Group, Flickr, Yahoo, {tobi,"
+fb04a8cb4b573d6b565a5b0c369d775e6bfb04f1,Title of dissertation : LOOKING AT PEOPLE USING PARTIAL LEAST SQUARES,
+fb4c3b2f893baa1fbf8d16da2e09aa9868c61a7a,Decoupled Weight Decay Regularization,"Under review as a conference paper at ICLR 2019 +DECOUPLED WEIGHT DECAY REGULARIZATION +Anonymous authors +Paper under double-blind review"
fb4545782d9df65d484009558e1824538030bbb1,"Learning Visual Patterns: Imposing Order on Objects, Trajectories and Networks",
+fbbccf0454c84bea1fd5c5a1dcd9fd7bba301a44,Face Detection Using Gradient Vector Flow,"Proceedings of the Second International Conference on Machine Learning and Cybernetics, Wan, 2-5 November 2003 +FACE DETECTION USING GRADIENT VECTOR FLOW +MAYANK VATSA, RICHA SINCH, P. GUPTA +Department of Computer Science & Engineering Indian Institute of Technology Kanpur +Kanpur INDIA, 208016 +E-MAIL: (mayankv, richas, pg} cse.iitk.ac.in"
fbf196d83a41d57dfe577b3a54b1b7fa06666e3b,Extreme Learning Machine for Large-Scale Action Recognition,"Extreme Learning Machine for Large-Scale Action Recognition G¨ul Varol and Albert Ali Salah Department of Computer Engineering, Bo˘gazi¸ci University, Turkey"
+fbd7d591e6eecb9a947e377d5b1a865a9f86a11f,Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data,"Consensual and Privacy-Preserving Sharing of +Multi-Subject and Interdependent Data +Alexandra-Mihaela Olteanu +EPFL, UNIL–HEC Lausanne +K´evin Huguenin +UNIL–HEC Lausanne +Italo Dacosta +Jean-Pierre Hubaux"
+fb3af250a2ff85145519fea9ece7187452d02a50,The WILDTRACK Multi-Camera Person Dataset,"The WILDTRACK Multi-Camera Person +Dataset +Tatjana Chavdarova1, Pierre Baqu´e2, St´ephane Bouquet2, +Andrii Maksai2, Cijo Jose1, Louis Lettry3, +Pascal Fua2, Luc Van Gool3 and Fran¸cois Fleuret1 +Machine Learning group, Idiap Research Institute & ´Ecole +Polytechnique F´ed´erale de Lausanne +CVLab, ´Ecole Polytechnique F´ed´erale de Lausanne +Computer Vision Lab, ETH Zurich"
+fbd781143a3f4c9d03c227cfbd1f528d658195ce,A Gender Recognition Experiment on the CASIA Gait Database Dealing with Its Imbalanced Nature,"A GENDER RECOGNITION EXPERIMENT ON THE CASIA GAIT +DATABASE DEALING WITH ITS IMBALANCED NATURE +Ra´ul Mart´ın-F´elez, Ram´on A. Mollineda and J. Salvador S´anchez +Institute of New Imaging Technologies (INIT) and Dept. Llenguatges i Sistemes Inform`atics +Universitat Jaume I. Av. Sos Baynat s/n, 12071, Castell´o de la Plana, Spain +{martinr, mollined, +Keywords: +Gender recognition, Gait analysis, Class imbalance problem, Human silhouette, Appearance-based method."
+fbd047862ea869973ecf8fc35ae090ca00ff06d8,Literature review of fingerprint quality assessment and its evaluation,"A Literature Review of Fingerprint Quality Assessment +nd Its Evaluation +Zhigang Yao, Jean-Marie Le Bars, Christophe Charrier, Christophe +Rosenberger +To cite this version: +Zhigang Yao, Jean-Marie Le Bars, Christophe Charrier, Christophe Rosenberger. A Literature Review +of Fingerprint Quality Assessment and Its Evaluation. +IET journal on Biometrics, 2016. <hal- +01269240> +HAL Id: hal-01269240 +https://hal.archives-ouvertes.fr/hal-01269240 +Submitted on 5 Feb 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents"
+fbb6e707c8a5f189d8ad416597e23671b884448b,Altered gaze following during live interaction in infants at risk for autism: an eye tracking study,"Thorup et al. Molecular Autism (2016) 7:12 +DOI 10.1186/s13229-016-0069-9 +R ES EAR CH +Altered gaze following during live +interaction in infants at risk for autism: +n eye tracking study +Emilia Thorup1*, Pär Nyström1, Gustaf Gredebäck1, Sven Bölte3,2, Terje Falck-Ytter3,1 and The EASE Team +Open Access"
+fb95fb1e0bf99347a69f76c9fd65e039024e73b7,Photograph Based Pair-matching Recognition of Human Faces,"World Academy of Science, Engineering and Technology +International Journal of Computer and Information Engineering +Vol:5, No:12, 2011 +Photograph Base +sed Pair-matching Recogn +gnition of +Human Faces +Min Y +n Yao, Kota Aoki, and Hiroshi Nagahashi +(cid:1)"
+fbc93b13b8a6a5e4ed11310ce4da3be0b7541da8,Real-time Pedestrian Detection in a Truck's Blind Spot Camera,"Real-time pedestrian detection in a truck’s blind spot camera +Kristof Van Beeck1,2 and Toon Goedem´e1,2 +EAVISE, Campus De Nayer - KU Leuven, J. De Nayerlaan 5, 2860 Sint-Katelijne-Waver, Belgium +ESAT-PSI, KU Leuven, Kasteel Arenbergpark 10, 3100 Heverlee, Belgium +{kristof.vanbeeck, +Keywords: +Pedestrian detection, Tracking, Real-time, Computer vision, Active safety systems"
+fbf20dc3367864462d7630aad81c436e50d1cd60,Iterative Bayesian Learning for Crowdsourced Regression,"Iterative Bayesian Learning for Crowdsourced Regression +Jungseul Ok∗, Sewoong Oh∗, Yunhun Jang †, Jinwoo Shin†, and Yung Yi† +October 9, 2018"
+fbb304770d33f44006d134906481208ad087ce63,Visual Self-Localization with Tiny Images,"Visual Self-Localization with Tiny Images +Marius Hofmeister, Sara Erhard and Andreas Zell +University of T¨ubingen, Department of Computer Science, Sand 1, 72076 T¨ubingen"
+fbd17af24e86fe487e28f99ba3e402dd6cfcd16a,Towards Detailed Recognition of Visual Categories,"Research Statement: Towards Detailed Recognition of Visual Categories +Subhransu Maji +As humans, we have a remarkable ability to perceive the world around us in minute detail purely +from the light that is reflected off it – we can estimate material and metric properties of objects, localize +people in images, describe what they are doing, and even identify them. Automatic methods for such +detailed recognition of images are essential for most human-centric applications and large scale analysis +of the content of media collections for market research, advertisement, and social studies. For example, +in order to shop for shoes in an on-line catalogue, a system should be able to understand the style of a +shoe, the length of its heels, or the shininess of its material. In order to support visual demographics +nalysis for advertisement, a system should be able to not only identify the people in a scene, but also +to understand what kind (style and brand) of clothes they are wearing, whether they are wearing any +ccessories, and so on. +Despite several successes, such detailed recognition is beyond the current computer vision systems. +This is a challenging task, and to make progress we have to make advances on several fronts. We need +etter representations of visual categories that can enable fine-grained reasoning about their properties, +s well as machine learning methods that can leverage ‘big-data’ to learn such representations. In order +to enable benchmarks for evaluating recognition tasks and to guide learning and inference in models +that solve challenging problems, we need to develop better ways of human-computer interaction. My +research touches upon several such themes in the intersection of computer vision, machine learning, and +human-computer interaction including:"
fba464cb8e3eff455fe80e8fb6d3547768efba2f,Survey Paper on Emotion Recognition,"International Journal of Engineering and Applied Sciences (IJEAS) ISSN: 2394-3661, Volume-3, Issue-2, February 2016 Survey Paper on Emotion Recognition Prachi Shukla, Sandeep Patil"
+fb66546a16751810754430286fe4c636e4411ca4,Complementary feature sets for optimal face recognition,"Singh et al. EURASIP Journal on Image and Video Processing 2014, 2014:35 +http://jivp.eurasipjournals.com/content/2014/1/35 +R ES EAR CH +Complementary feature sets for optimal face +recognition +Chandan Singh1, Neerja Mittal2* and Ekta Walia3 +Open Access"
+fb2379346def4846ac24bc41349e7cac7c1e7243,ClusterNet: 3D Instance Segmentation in RGB-D Images,"ClusterNet: 3D Instance Segmentation in RGB-D Images +Lin Shao, Ye Tian, and Jeannette Bohg"
+fbb9cdd699baf86e9d616b259ada02449c2322ca,Active Testing: An Efficient and Robust Framework for Estimating Accuracy,"Active Testing: An Efficient and Robust Framework for Estimating Accuracy. +Phuc Nguyen 1 Deva Ramanan 2 Charless Fowlkes 1"
+fb748a6953e72ad6d508109f8d809c25570ff07b,"The ""Eye Avoidance"" Hypothesis of Autism Face Processing.","NIH Public Access +Author Manuscript +J Autism Dev Disord. Author manuscript; available in PMC 2015 April 23. +The “eye avoidance” hypothesis of autism face processing +James W. Tanaka1 and Andrew Sung2 +Department of Psychology, University of Victoria, British Columbia +Department of Special Education and Leadership Studies, University of Victoria, British +Columbia"
+fb1732a1476798c42a0123aaf127036bf8daef09,LightDenseYOLO: A Fast and Accurate Marker Tracker for Autonomous UAV Landing by Visible Light Camera Sensor on Drone,"Article +LightDenseYOLO: A Fast and Accurate Marker +Tracker for Autonomous UAV Landing by Visible +Light Camera Sensor on Drone +Phong Ha Nguyen, Muhammad Arsalan, Ja Hyung Koo, Rizwan Ali Naqvi, Noi Quang Truong +nd Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul +00-715, Korea; (P.H.N.); (M.A.); (J.H.K.); +(R.A.N.); (N.Q.T.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 3 May 2018; Accepted: 22 May 2018; Published: 24 May 2018"
fbb2f81fc00ee0f257d4aa79bbef8cad5000ac59,Reading Hidden Emotions: Spontaneous Micro-expression Spotting and Recognition,"Reading Hidden Emotions: Spontaneous Micro-expression Spotting and Recognition Xiaobai Li, Student Member, IEEE, Xiaopeng Hong, Member, IEEE, Antti Moilanen, Xiaohua Huang, Student Member, IEEE, Tomas Pfister, Guoying Zhao, Senior Member, IEEE, and Matti Pietik¨ainen, Fellow, IEEE"
+fb82681ac5d3487bd8e52dbb3d1fa220eeac855e,1 Network Notebook,"CONNECTIONS +VOLUME IV, NUMBER 2 +Summer 1981 +CONTENTS +NETWORK NOTEBOOK +MEETING CALENDAR +RESEARCH REPORTS +Social Networks : +A Beginner's Bookshelf +Linton C . Freeman (California-Irvine) +Summary of Research on Informant Accuracy in Network Data, +nd on the Reverse Small World Problem +H . Russell Bernard (Florida), Peter D . Killworth (Cambridge) +& Lee Sailer (Pittsburgh) +Russell's Paradox (Part II) +Linton C . Freeman (California-Irvine) +Goedel's Spoof : +A Reply to Freeman +Peter D . Killworth (Cambridge) & H . Russell Bernard (Florida) +The Norwegian Connection :"
+fb76adeff0309ff4c8de4d0b413a8e3a637774d0,client2vec: Towards Systematic Baselines for Banking Applications,"lient2vec: Towards Systematic Baselines for Banking +Applications +Leonardo Baldassini +BBVA Data & Analytics +Jose Antonio Rodr´ıguez Serrano +BBVA Data & Analytics"
fb9ad920809669c1b1455cc26dbd900d8e719e61,3 D Gaze Estimation from Remote RGB-D Sensors THÈSE,"D Gaze Estimation from Remote RGB-D Sensors THÈSE NO 6680 (2015) PRÉSENTÉE LE 9 OCTOBRE 2015 @@ -5732,6 +19476,50 @@ Research Scholar, Dept. of Electronics & Communication Engineering, Rayalaseema University Kurnool, Andhra Pradesh. 2 Research Supervisor, Professor, Dept. of Electronics & Communication Engineering, Madanapalle Institute of Technology & Science, Madanapalle, Andhra Pradesh."
+ed732b3a1f8fe733686a35688b090f426d018f9b,Dual-Process Theories in Social Cognitive Neuroscience,"This article was originally published in Brain Mapping: An Encyclopedic +Reference, published by Elsevier, and the attached copy is provided by +Elsevier for the author's benefit and for the benefit of the author's institution, +for non-commercial research and educational use including without limitation +use in instruction at your institution, sending it to specific colleagues who you +know, and providing a copy to your institution’s administrator. +All other uses, reproduction and distribution, including without limitation +ommercial reprints, selling or licensing copies or access, or posting on open +internet sites, your personal or institution’s website or repository, are +prohibited. For exceptions, permission may be sought for such use through +Elsevier's permissions site at: +http://www.elsevier.com/locate/permissionusematerial +Spunt R.P. (2015) Dual-Process Theories in Social Cognitive Neuroscience. In: +Arthur W. Toga, editor. Brain Mapping: An Encyclopedic Reference, vol. 3, pp. +11-215. Academic Press: Elsevier."
+ed6003db58b67f1dfac654868b437efcef6e2ccb,Restricted Isometry Property of Gaussian Random Projection for Finite Set of Subspaces,"Restricted Isometry Property of Gaussian Random Projection +for Finite Set of Subspaces +Gen Li and Yuantao Gu∗ +submitted April 7, 2017, revised August 11, 2017, accepted November 8, 2017"
+ed9967868fcca2ec38402d2bb3e6946b8e554472,Efficient Eye Location for Biomedical Imaging using Two-level Classifier Scheme,"International Journal of Control, Automation, and Systems, vol. 6, no. 6, pp. 828-835, December 2008 +Efficient Eye Location for Biomedical Imaging using Two-level Classifier +Scheme +Mi Young Nam, Xi Wang, and Phill Kyu Rhee*"
+edc5c359ed0fc24a3e85628f57fde59cd9b26dd4,Search Space Optimization and False Alarm Rejection Face Detection Framework,"Journal of Theoretical and Applied Information Technology +30th September 2015. Vol.79. No.3 +© 2005 - 2015 JATIT & LLS. All rights reserved. +ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 +SEARCH SPACE OPTIMIZATION AND FALSE ALARM +REJECTION FACE DETECTION FRAMEWORK +ALI SHARIFARA, 2MOHD SHAFRY MOHD RAHIM, 3 HAMED SAYYADI, +FARHAD NAVABIFAR +,2, Department of Computer Graphics and Multimedia, Faculty of Computing University Technology +Malaysia (UTM).81310 Skudai Johor, Malaysia. +Department of Computer Systems and Communications, Faculty of Computing University Technology +Malaysia (UTM), 81310 Skudai Johor, Malaysia. +Department of Computer Engineering Mobarakeh Branch-Islamic Azad University, Mobarakeh, Esfahan, +E-mail: +Iran."
+ed07fa6df6a8fc27015d25717c9f730dc9eede84,of the 19 th Workshop on the Semantics and Pragmatics of Dialogue,"SEMDIAL 2015 +goDIAL +Proceedings of the 19th Workshop on +the Semantics and Pragmatics of Dialogue +Christine Howes and Staffan Larsson (eds.) +Gothenburg, 24–26 August 2015"
ed08ac6da6f8ead590b390b1d14e8a9b97370794,An Efficient Approach for 3D Face Recognition Using ANN Based Classifiers,"ISSN(Online): 2320-9801 ISSN (Print): 2320-9798 International Journal of Innovative Research in Computer @@ -5744,19 +19532,173 @@ Vaibhav M. Pathak1, Suhas S.Satonkar2, Dr.Prakash B.Khanale3 Assistant Professor, Dept. of C.S., Shri Shivaji College, Parbhani, M.S, India1 Assistant Professor, Dept. of C.S., Arts, Commerce and Science College, Gangakhed, M.S, India2 Associate Professor, Dept. of C.S., Dnyanopasak College Parbhani, M.S, India3"
+ed3c4d2d28faaccbaef876a7daaecc3cccadb48f,3D Human Pose Estimation from a Single Image via Distance Matrix Regression,"D Human Pose Estimation from a Single Image via Distance Matrix Regression +Institut de Rob`otica i Inform`atica Industrial (CSIC-UPC), 08028, Barcelona, Spain +Francesc Moreno-Noguer"
+edf074a5eb3a1f71cc710ccc42849dceb27e3531,Towards real-time unsupervised monocular depth estimation on CPU,"Towards real-time unsupervised monocular depth estimation on CPU +Matteo Poggi1, Filippo Aleotti2, Fabio Tosi1, Stefano Mattoccia1"
+ed6801362ab442097e7f753f163b9e9c0584b257,Learning Based 2D to 3D Conversion with Input Image Denoising,"International Journal of Scientific Research Engineering & Technology (IJSRET), ISSN 2278 – 0882 +Volume 4, Issue 5, May 2015 +Learning Based 2D to 3D Conversion with Input Image Denoising +Divya K.P.1, Sneha K.2, Nafla C.N.3 +(Department of CSE, RCET, Akkikkvu, Thrissur) +(Asst. Professor, Department of CSE, RCET, Akkikkvu, Thrissur) +(Department of CSE, RCET, Akkikkvu, Thrissur)"
edef98d2b021464576d8d28690d29f5431fd5828,Pixel-Level Alignment of Facial Images for High Accuracy Recognition Using Ensemble of Patches,"Pixel-Level Alignment of Facial Images for High Accuracy Recognition Using Ensemble of Patches Hoda Mohammadzade, Amirhossein Sayyafan, Benyamin Ghojogh"
+ed38d22cd5558d1abb40b477027d52ff7b6d09db,Title of thesis : SIMULTANEOUS MULTI - VIEW FACE TRACKING AND RECOGNITION IN VIDEO USING PARTICLE FILTERING,
+edceeaa885f3eb29761580095059f8a34be8408b,SitNet: Discrete Similarity Transfer Network for Zero-shot Hashing,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +ModelSimilar?Figure1:Zero-shothashing.Thehashingmodeltrainedwithseenconceptsshouldgeneralizewellontheunseenconcepts.supervisedhashinglikeSupervisedDiscreteHashing[Shenetal.,2015a].Withthesupervisedinformationlikesemanticsimilaritymatrixorclasslabels,thesupervisedapproachesachievesuperiorretrievalperformancebecausetheintrinsicsemanticpropertyinthedataisbetterexplored.Recentlythedeepconvolutionalneuralnetwork(CN-N)hasachievedgreatsuccessinmanycomputervisiontasks,likeimageclassification[Heetal.,2016]andfacerecognition[Wenetal.,2016].InspiredbyCNN’spower-fulfeatureextractionability,someworkshaveattemptedtobuildhashingmodelsbasedonCNN[Laietal.,2015;Liuetal.,2016;Xiaetal.,2014]haveappeared.Theyre-quirethehashcodesproducedbythelastfullyconnectedlay-ertopreservethesimilaritygivenbythesupervisedinfor-mation.ItisdemonstratedthattheimageretrievalaccuracyissignificantlyimprovedbyCNN-basedhashingapproachescomparedwiththenon-CNNones[Liuetal.,2016].Itshouldbenoticedthattheexistinghashingapproachesmainlyfocusontheclose-setretrieval,i.e.,theconceptsofpossibletestingsamples(bothdatabasesamplesandquerysamples)arewithinthetrainingset.However,theexplosivegrowthofWebimagesviolatesthissettingbecausethenewconceptsabouttheimagesmayemergerapidly.Itisexpen-sivetoannotatesufficienttrainingdataforthenewconcept-stimely,andalso,impracticaltoretrainthehashingmodelwhereastheretrievalsystemmeetsanewconcept.Asillus-tratedinFigure1,theexistingapproachesperformwellontheseenconceptsbecausetheyaregivencorrectguidance,buttheymayeasilyfailontheunseenconceptsthattheynev-ermeetbeforesuchasthe“dicycle”whichisakindofvehicle"
+edcf668846a3aaf55120aef0c806854936208b3d,Human Recognition in RGBD Combining Object Detectors and Conditional Random Fields,
+ed90a9d379f6412a1580e7eda5cb91640000dc42,Highly Efficient 8-bit Low Precision Inference of Convolutional Neural Networks with IntelCaffe,"Highly Efficient 8-bit Low Precision Inference of +Convolutional Neural Networks with IntelCaffe +Jiong Gong, Haihao Shen, Guoming Zhang, Xiaoli Liu, Shane Li, Ge Jin, Niharika Maheshwari, +Evarist Fomenko, Eden Segal +{jiong.gong, haihao.shen, guoming.zhang, xiaoli.liu, li.shane, ge.jin, niharika.maheshwari, evarist.m.fomenko, +Intel Corporation"
+ed5519a03f52e47047079da2e0c480eb8c4a9805,An Evaluation of Trajectory Prediction Approaches and Notes on the TrajNet Benchmark,"An Evaluation of Trajectory Prediction Approaches and +Notes on the TrajNet Benchmark. +Stefan Becker ∗, Ronny Hug ∗, Wolfgang H¨ubner and Michael Arens +Fraunhofer Institute for Optronics, System Technologies, and Image Exploitation IOSB +Gutleuthausstr. 1, 76275 Ettlingen, Germany"
+eda20a2f33d0f6db44a2e7d060efad3caa6621e0,"Classification with Global, Local and Shared Features","Classification with Global, Local and Shared +Features +Hakan Bilen1, Vinay P. Namboodiri2, Luc J. Van Gool1,3 +ESAT-PSI/IBBT,VISICS/KU Leuven, Belgium +Alcatel-Lucent Bell Labs, Antwerp, Belgium +Computer Vision Laboratory, BIWI/ETH Z¨urich, Switzerland"
ed04e161c953d345bcf5b910991d7566f7c486f7,Mirror my emotions! Combining facial expression analysis and synthesis on a robot,"Combining facial expression analysis and synthesis on a Mirror my emotions! robot Stefan Sosnowski1 and Christoph Mayer2 and Kolja K¨uhnlenz3 and Bernd Radig4"
+edbfbcebb14234b438d90d6dcd9b667e9071952d,Learning Fashion Compatibility with Bidirectional LSTMs,"A.B.C.D.?Task 1: Fill in the blankTask 2: Outfit generation given texts or imagesWhat to dress for a biz meeting?(a)(b)Task 3: Compatibility predictionScore: 0.7Figure1:Wefocusonthreetasksoffashionrecommenda-tion.Task1:recommendingafashionitemthatmatchesthestyleofanexistingset.Task2:generatinganoutfitbasedonusers’text/imageinputs.Task3:predictingthecompatibil-ityofanoutfit.conductedonautomaticfashionanalysisinthemultimediacom-munity.However,mostofthemfocusonclothingparsing[9,26],clothingrecognition[12],orclothingretrieval[10].Although,thereareafewworksthatinvestigatedfashionrecommendation[6,8,10],theyeitherfailtoconsiderthecompositionofitemstoformanout-fit[10]oronlysupportoneofthetworecommendationcategoriesdiscussedabove[6,8].Inaddition,itisdesirablethatrecommenda-tionscantakemultimodalinputsfromusers.Forexample,ausercanprovidekeywordslike“business”,oranimageofabusinessshirt,oracombinationofimagesandtext,togenerateacollec-tionoffashionitemsforabusinessoccasion.However,nopriorapproachsupportsmultimodalinputsforrecommendation.Keytofashionrecommendationismodelingthecompatibilityoffashionitems.Wecontendthatacompatibleoutfit(asshowninFigure3)shouldhavetwokeyproperties:(1)itemsintheout-fitshouldbevisuallycompatibleandsharesimilarstyle;(2)these"
+ed2420d0fc7087d61633bd9a5b2907d1c2de1810,Facial symmetry evaluation from high – density scanned data,
+eddb1a126eafecad2cead01c6c3bb4b88120d78a,Applications of a Graph Theoretic Based Clustering Framework in Computer Vision and Pattern Recognition,"DEPARTMENT DESIGN AND PLANNING IN COMPLEX ENVIRONMENTS +DOTTORATO DI RICERCA IN NUOVE TECNOLOGIE, INFORMAZIONE TERRITORIO E +UNIVERSIT‘A IUAV DI VENEZIA +AMBIENTE, XXX CICLO +APPLICATIONS OF A GRAPH THEORETIC BASED +CLUSTERING FRAMEWORK IN COMPUTER VISION AND +PATTERN RECOGNITION +Doctoral Dissertation of: +Yonatan Tariku Tesfaye +Supervisor: +Prof. Andrea Prati +The Chair of the Doctoral Program: +Prof. Fabio Peron"
+ed6a47f0e2e621d8420082ba1d0078189d76352f,3d Facial Expression Intensity Measurement Analysis,"Proceedings of the 6th International Conference on Computing and Informatics, ICOCI 2017 +5-27April, 2017 Kuala Lumpur. Universiti Utara Malaysia (http://www.uum.edu.my ) +Paper No. +How to cite this paper: +Alicia Cheong Chiek Ying, Hamimah Ujir, & Irwandi Hipiny. (2017). 3D facial expression intensity measurement +nalysis in Zulikha, J. & N. H. Zakaria (Eds.), Proceedings of the 6th International Conference of Computing & +Informatics (pp 43-48). Sintok: School of Computing. +D FACIAL EXPRESSION INTENSITY MEASUREMENT +ANALYSIS +Alicia Cheong Chiek Ying1, Hamimah Ujir2and Irwandi Hipiny3 +Sarawak Information Systems Sdn. Bhd. (SAINS), +Universiti Malaysia Sarawak, +Universiti Malaysia Sarawak,"
+ed02b45d05e58803596891d660837c21be70a0af,Entity type modeling for multi-document summarization : generating descriptive summaries of geo-located entities,"Entity Type Modeling for Multi-Document +Summarization: Generating Descriptive Summaries of +Geo-Located Entities +Ahmet Aker +A thesis submitted in fulfilment of requirements for the degree of +Doctor of Philosophy +Department of Computer Science +University of Sheffield +November 2013"
c1d2d12ade031d57f8d6a0333cbe8a772d752e01,Convex optimization techniques for the efficient recovery of a sparsely corrupted low-rank matrix,"Journal of Math-for-Industry, Vol.2(2010B-5), pp.147–156 Convex optimization techniques for the efficient recovery of a sparsely orrupted low-rank matrix Silvia Gandy and Isao Yamada Received on August 10, 2010 / Revised on August 31, 2010"
+c1c34a3ab7815af1b9bcaf2822e4b9da8505f915,Image transmorphing with JPEG,"IMAGE TRANSMORPHING WITH JPEG +Lin Yuan and Touradj Ebrahimi +Multimedia Signal Processing Group, EPFL, Lausanne, Switzerland"
+c158009b33989c6677f1daa3f5926887c9471c5e,Controlling Complex Systems and Developing Dynamic Technology,"Electronic Thesis and Dissertations +Peer Reviewed +Title: +Controlling Complex Systems and Developing Dynamic Technology +Author: +Avizienis, Audrius Victor +Acceptance Date: +Series: +UCLA Electronic Theses and Dissertations +Degree: +Ph.D., Chemistry 0153UCLA +Advisor(s): +Gimzewski, James K +Committee: +Kodambaka, Suneel, Baugh, Delroy A +Permalink: +https://escholarship.org/uc/item/35c10822"
+c18d80d00f2a7107bfe780eeec21b51a634ea925,Computational perspectives on the other-race effect,"This article was downloaded by: [The University of Texas at Dallas], [Alice +O'Toole] +On: 25 July 2013, At: 12:46 +Publisher: Routledge +Informa Ltd Registered in England and Wales Registered Number: 1072954 +Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, +Visual Cognition +Publication details, including instructions for authors +nd subscription information: +http://www.tandfonline.com/loi/pvis20 +Computational perspectives on +the other-race effect +Alice J. O'Toole a & Vaidehi Natu a +School of Behavioural and Brain Sciences , University +of Texas at Dallas , Richardson , TX , USA +Published online: 14 Jun 2013. +To cite this article: Visual Cognition (2013): Computational perspectives on the other- +race effect, Visual Cognition, DOI: 10.1080/13506285.2013.803505 +To link to this article: http://dx.doi.org/10.1080/13506285.2013.803505 +PLEASE SCROLL DOWN FOR ARTICLE"
+c19ed5102ecd953d5c78d5a0b87eaa51658e07d8,Recovering Accurate 3D Human Pose in the Wild Using IMUs and a Moving Camera,"Recovering Accurate 3D Human Pose in The +Wild Using IMUs and a Moving Camera +Timo von Marcard1, Roberto Henschel1, Michael J. Black2, Bodo Rosenhahn1, +nd Gerard Pons-Moll3 +Leibniz Universit¨at Hannover, Germany +MPI for Intelligent Systems, T¨ubingen, Germany +MPI for Informatics, Saarland Informatics Campus, Germany"
+c1b2668186fcd01b3c0e93a9a0a68e3eb88a09ab,Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360 ^\circ ∘ Panoramic Imagery,"Eliminating the Blind Spot: Adapting 3D Object +Detection and Monocular Depth Estimation to +60◦ Panoramic Imagery +Gr´egoire Payen de La Garanderie, Amir Atapour Abarghouei, +nd Toby P. Breckon +Department of Computer Science +Durham University"
+c1c8ea4b2118095bea55cf6b51c36dbf95cc7f2c,Learning 3D Segment Descriptors for Place Recognition,"Learning 3D Segment Descriptors for Place Recognition +Andrei Cramariuc +Renaud Dubé +Hannes Sommer +Roland Siegwart +Igor Gilitschenski∗"
+c160bcbc8f0517a97e46042c84343bf3f0477478,A Dynamic Approach and a New Dataset for Hand-detection in First Person Vision,"A Dynamic Approach and a New Dataset for +Hand-Detection in First Person Vision. +Alejandro Betancourt1,2, Pietro Morerio1, Emilia I. Barakova2, Lucio Marcenaro1, +Matthias Rauterberg2, Carlo S. Regazzoni1 +Department of Naval, Electric, Electronic and Telecommunications Engineering - University +Designed Intelligence Group, Department of Industrial Design - Eindhoven University of +Technology, The Netherlands. +of Genoa, Italy."
+c165003060eeb01e05800a5ee4cd327f1e0bf5e3,SDC-Net: Video Prediction Using Spatially-Displaced Convolution,"SDC-Net: Video prediction using +spatially-displaced convolution +Fitsum A. Reda, Guilin Liu, Kevin J. Shih, Robert Kirby, Jon Barker, +David Tarjan, Andrew Tao, and Bryan Catanzaro +Nvidia Corporation, Santa Clara CA 95051, USA +Fig. 1. Frame prediction on a YouTube video frame featuring a panning camera. Left +to right: Ground-truth, MCNet [34] result, and our SDC-Net result. The SDC-Net +predicted frame is sharper and preserves fine image details, while color distortion and +lurriness is seen in the tree and text in MCNet’s predicted frame."
+c19845c84abc9e3afe17003fdcd545ed020d0624,A face biometric benchmarking review and characterisation,"A Face Biometric +Benchmarking Review and +Characterisation +Sandra Mau +Senior Research Engineer +NICTA Advanced Surveillance +BeFIT workshop – ICCV 2011"
c10a15e52c85654db9c9343ae1dd892a2ac4a279,Learning the Relative Importance of Objects from Tagged Images for Retrieval and Cross-Modal Search,"Int J Comput Vis (2012) 100:134–153 DOI 10.1007/s11263-011-0494-3 Learning the Relative Importance of Objects from Tagged Images @@ -5764,20 +19706,111 @@ for Retrieval and Cross-Modal Search Sung Ju Hwang · Kristen Grauman Received: 16 December 2010 / Accepted: 23 August 2011 / Published online: 18 October 2011 © Springer Science+Business Media, LLC 2011"
+c1059a702f53c44bb26d3313964e811adf01d9b4,Low and mid-level features for target detection in satellite images,"ISSN: 2278 – 1323 +International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) +Volume 2, Issue 2, February 2013 +Low and mid-level features for target detection in satellite images +Rajani.D.C"
+c1bbcdf3b5901e3378a89808b07e53a502c295f0,Allostasis and the human brain: Integrating models of stress from the social and life sciences.,"Psychol Rev. Author manuscript; available in PMC 2011 January 1. +Published in final edited form as: +Psychol Rev. 2010 January; 117(1): 134–174. +doi: 10.1037/a0017773 +Allostasis and the human brain: Integrating models of stress from the social and life sciences +Barbara L. Ganzel, Pamela A. Morris, and Elaine Wethington +Author information ► Copyright and License information ► +The publisher's final edited version of this article is available at Psychol Rev +See other articles in PMC that cite the published article."
c1dfabe36a4db26bf378417985a6aacb0f769735,Describing Visual Scene through EigenMaps,"Journal of Computer Vision and Image Processing, NWPJ-201109-50 Describing Visual Scene through EigenMaps Shizhi Chen, Student Member, IEEE, and YingLi Tian, Senior Member, IEEE"
+c175381a6b84ebd0a920ff44ccdccabd98bdfb94,Paper on Retrieval Magnets for Facial Duplication by Search Based Face Annotation,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Impact Factor (2012): 3.358 +A Review Paper on Retrieval Magnets for Facial +Duplication by Search Based Face Annotation +Deepika B. Patil1, Ayesha Butalia 2 +P.G. Student, Department of Computer Engineering, GMRCEM, Wagholi, Pune, India, +Professor, Department of Computer Engineering, GMRCEM, Wagholi, Pune, India,"
c1ff88493721af1940df0d00bcfeefaa14f1711f,Subspace Regression: Predicting a Subspace from one Sample,"#1369 CVPR 2010 Submission #1369. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. #1369 Subspace Regression: Predicting a Subspace from one Sample Anonymous CVPR submission Paper ID 1369"
+c1100efda7c00d3181a6a065ab1474c2f864e267,Video visual analytics,"Video Visual Analytics +Von der Fakultät Informatik, Elektrotechnik und +Informationstechnik der Universität Stuttgart +genehmigte Abhandlung +zur Erlangung der Würde eines +Doktors der Naturwissenschaften (Dr. rer. nat.) +Vorgelegt von +Markus Johannes Höferlin +us Herrenberg +Hauptberichter: Prof. Dr. Daniel Weiskopf +Mitberichter: +Prof. Dr. Gunther Heidemann +Prof. Min Chen, BSc, PhD, FBCS, FEG, FLSW +Tag der mündlichen Prüfung: 27. Mai 2013 +Visualisierungsinstitut +der Universität Stuttgart"
+c132a6e869cd171e403784c172961471733dce31,In-vehicle Pedestrian Detection Using Stereo Vision Technology,"IN-VEHICLE PEDESTRIAN DETECTION USING STEREO VISION +TECHNOLOGY +Wei Zhang, Ph.D., P.E. +Highway Research Engineer, Office of Safety Research & Development, HRDS-10 +Federal Highway Administration +6300 Georgetown Pike, McLean, VA 22101, USA, e-mail: +Submitted to the 3rd International Conference on Road Safety and Simulation, September 14-16, +011, Indianapolis, USA"
+c16bae6b2e578df2cba8e436e02bdeda281c2743,Tensor Discriminant Color Space for Face Recognition,"Tensor Discriminant Color Space for Face +Recognition +Su-Jing Wang, Jian Yang, Member, IEEE, Na Zhang, and Chun-Guang Zhou*"
c11eb653746afa8148dc9153780a4584ea529d28,Global and Local Consistent Wavelet-domain Age Synthesis,"Global and Local Consistent Wavelet-domain Age Synthesis Peipei Li†, Yibo Hu†, Ran He Member, IEEE and Zhenan Sun Member, IEEE"
+c1b971cd7263e788e114cf8c4aa076a2e170990f,Establishing the fundamentals for an elephant early warning and monitoring system,"Establishing the fundamentals for an elephant +early warning and monitoring system +Zeppelzauer and Stoeger +Zeppelzauer and Stoeger BMC Res Notes (2015) 8:409 +DOI 10.1186/s13104-015-1370-y"
c1ebbdb47cb6a0ed49c4d1cf39d7565060e6a7ee,Robust Facial Landmark Localization Based on Texture and Pose Correlated Initialization,"Robust Facial Landmark Localization Based on Yiyun Pan, Junwei Zhou, Member, IEEE, Yongsheng Gao, Senior Member, IEEE, Shengwu Xiong"
+c175f1666f3444e407660c5935a05b2a53f346f0,Modifying the Memorability of Face,"Modifying the Memorability of Face Photographs +The MIT Faculty has made this article openly available. Please share +how this access benefits you. Your story matters. +Citation +As Published +Publisher +Version +Accessed +Citable Link +Terms of Use +Detailed Terms +Khosla, Aditya, Wilma A. Bainbridge, Antonio Torralba, and Aude +Oliva. “Modifying the Memorability of Face Photographs.” 2013 +IEEE International Conference on Computer Vision (December +013). +http://dx.doi.org/10.1109/ICCV.2013.397 +Institute of Electrical and Electronics Engineers (IEEE) +Author's final manuscript +Mon Nov 05 02:44:57 EST 2018 +http://hdl.handle.net/1721.1/90986"
+c1c3e32ecf6da8e1372fab7d504cb8cd2c86fd93,Face recognition based on artificial immune networks and principal component analysis with single training image per person,"Face recognition based on artificial immune networks and principal +omponent analysis with single training image per person +, Department of Mechanical Engineering, Tatung University, Taiwan, ROC, +Guan-Chun Luh"
+c1087c588960dd7c00a2b5feed57fbdb70d066f1,Quantifying cortical surface asymmetry via logistic discriminant analysis,"Quantifying Cortical Surface Asymmetry +via Logistic Discriminant Analysis +Moo K. Chung1,2, Daniel J. Kelley2, Kim M. Dalton2, Richard J. Davidon2,3 +Department of Biostatistics and Medical Informatics +Waisman Laboratory for Brain Imaging and Behavior +Department of Psychology and Psychiatry +University of Wisconsin, Madison, WI 53706, USA"
+c1130d5c7bb1311e04cffbaf2bf6cbe734adc2ac,DFNet: Semantic Segmentation on Panoramic Images with Dynamic Loss Weights and Residual Fusion Block,"DFNet: Semantic Segmentation on Panoramic Images with Dynamic Loss +Weights and Residual Fusion Block +Wei Jiang, Yan Wu∗ +technique, moreover,"
+c1bd99083098cf8dbfed8d25514755bc5356bc06,Fly Page (This sheet is left blank and not counted) GENERALIZED DISCRIMINANT ANALYSIS IN CONTENT-BASED IMAGE RETRIEVAL APPROVED BY SUPERVISING,"Fly Page +(This sheet is left blank and not counted)"
c1dd69df9dfbd7b526cc89a5749f7f7fabc1e290,Unconstrained face identification with multi-scale block-based correlation,"Unconstrained face identification with multi-scale block-based orrelation Gaston, J., MIng, J., & Crookes, D. (2016). Unconstrained face identification with multi-scale block-based @@ -5828,6 +19861,20 @@ University of Technology, Guangzhou, 510640, P.R.China {ddyang, Motorola China Research Center, Shanghai, 210000, P.R.China {Li-Xin.Zhen,"
+c6d6193c8f611331c8178c3857f9ef92607a4507,A Study on Using Mid-Wave Infrared Images for Face Recognition,"Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and +Biometric Technology for Human Identification IX, edited by Sárka O. Southern, et al., Proc. of SPIE Vol. 8371, 83711K +© 2012 SPIE · CCC code: 0277-786X/12/$18 · doi: 10.1117/12.918899 +Proc. of SPIE Vol. 8371 83711K-1 +From: http://spiedigitallibrary.org/ on 04/30/2013 Terms of Use: http://spiedl.org/terms"
+c610888cadcf2aa45e7367f43e42eaa7a586652e,Fast Convergence for Object Detection by Learning how to Combine Error Functions,"(cid:13) 2018 IEEE. +Personal use of this material is permitted. Permission from +IEEE must be obtained for all other uses, in any current or +future media, including reprinting/republishing this material +for advertising or promotional purposes, creating new +ollective works, for resale or redistribution to servers or +lists, or reuse of any copyrighted component of this work in +other works. +Accepted version."
c614450c9b1d89d5fda23a54dbf6a27a4b821ac0,Face Image Retrieval of Efficient Sparse Code words and Multiple Attribute in Binning Image,"Vol.60: e17160480, January-December 2017 http://dx.doi.org/10.1590/1678-4324-2017160480 ISSN 1678-4324 Online Edition @@ -5839,11 +19886,109 @@ Face Image Retrieval of Efficient Sparse Code words and Multiple Attribute in Binning Image Suchitra S1*. Srm Easwari Engineering College, Ramapuram, Bharathi Salai, Chennai, Tamil Nadu, India."
+c6c3cee8adacff8a63ab84dc847141315e874400,Disentangling by Factorising,"Disentangling by Factorising +Hyunjik Kim 1 2 Andriy Mnih 1"
c6f3399edb73cfba1248aec964630c8d54a9c534,A comparison of CNN-based face and head detectors for real-time video surveillance applications,"A Comparison of CNN-based Face and Head Detectors for Real-Time Video Surveillance Applications Le Thanh Nguyen-Meidine1, Eric Granger 1, Madhu Kiran1 and Louis-Antoine Blais-Morin2 ´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montreal, Canada Genetec Inc., Montreal, Canada"
+c62c4e5d8243da6bc1fde64097b2ab8971e6e51f,"A Unified Approach for Conventional Zero-Shot, Generalized Zero-Shot, and Few-Shot Learning","JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2017 +A Unified approach for Conventional Zero-shot, +Generalized Zero-shot and Few-shot Learning +Shafin Rahman, Salman H. Khan and Fatih Porikli"
+c636cd6eba286357fe807c0ca4b02c3b9b7b5619,Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization,"Training Deep Networks with Synthetic Data: +Bridging the Reality Gap by Domain Randomization +Jonathan Tremblay∗ +Aayush Prakash∗ +David Acuna∗† +Mark Brophy∗ +Varun Jampani +Cem Anil† +Thang To +Eric Cameracci +Shaad Boochoon +Stan Birchfield +NVIDIA +also University of Toronto +{jtremblay,aayushp,dacunamarrer,markb,vjampani,"
+c600e985ae3af9143b41271abd040a1c1e89177e,Nonparametric Video Retrieval and Frame Classification using Tiny Videos,"Nonparametric Video Retrieval and Frame Classification using Tiny Videos +{tag} {/tag} +IJCA Proceedings on International Conference in +Recent trends in Computational Methods, Communication and Controls (ICON3C 2012) +© 2012 by IJCA Journal +ICON3C - Number 3 +Year of Publication: 2012 +Authors: +A. K. M. Shanawas Fathima +R. Kanthavel +{bibtex}icon3c1024.bib{/bibtex}"
+c694b397a3a0950cd20699a687fe6c8a3173b107,Explaining autism spectrum disorders: central coherence vs. predictive coding theories.,"J Neurophysiol 112: 2669 –2671, 2014. +First published May 28, 2014; doi:10.1152/jn.00242.2014. +Neuro Forum +Explaining autism spectrum disorders: central coherence vs. predictive coding +theories +Jason S. Chan and Marcus J. Naumer +Institute of Medical Psychology, Goethe-University, Frankfurt, Germany +Submitted 27 March 2014; accepted in final form 23 May 2014 +Chan JS, Naumer MJ. Explaining autism spectrum disorders: central +oherence vs. predictive coding theories. J Neurophysiol 112: 2669–2671, +014. First published May 28, 2014; doi:10.1152/jn.00242.2014.—In this +rticle, we review a recent paper by Stevenson et al. (J Neurosci 34: +691–697, 2014). This paper illustrates the need to present different forms of +stimuli in order to characterize the perceptual abilities of people with autism +spectrum disorder (ASD). Furthermore, we will discuss their behavioral +results and offer an opposing viewpoint to the suggested neuronal drivers of +utism spectrum disorder; multisensory integration; temporal binding +window +THE DIFFERENCE in propagation time between an auditory and a +visual stimulus can be substantial, depending on the distance"
+c6d5d47513d6a7a1b0b92b33efda3f2a866d34ad,Characterizing International Travel Behavior from Geotagged Photos: A Case Study of Flickr,"RESEARCH ARTICLE +Characterizing International Travel Behavior +from Geotagged Photos: A Case Study of +Flickr +Yihong Yuan*, Monica Medel +Department of Geography, Texas State University, San Marcos, Texas, 78666, United States of America"
+c679fd4e29597c64e5921fad796183ae30db8396,LG ] 5 M ar 2 01 6 A Latent-Variable Grid Model,"A Latent-Variable Grid Model +Rajasekaran Masatran +Computer Science and Engineering, Indian Institute of Technology Madras +FREESHELL · ORG"
+c6638c7c1ec7b8fd5cdba039536fb44d12cff5c2,Towards a Development of Augmented Reality for Jewellery App,"Revati Mukesh Raspayle et al, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.6, June- 2016, pg. 129-137 +Available Online at www.ijcsmc.com +International Journal of Computer Science and Mobile Computing +A Monthly Journal of Computer Science and Information Technology +ISSN 2320–088X +IMPACT FACTOR: 5.258 +IJCSMC, Vol. 5, Issue. 6, June 2016, pg.129 – 137 +Towards a Development of Augmented +Reality for Jewellery App +Er. Revati Mukesh Raspayle1, Prof. Kavita Kelkar2 +¹Student (M.Tech) CSE, Mumbai University, Computer Engineering, K.J SOMAIYA COE Vidyavihar, +²Assistant Professor, Mumbai University, Computer Engineering, K.J SOMAIYA COE Vidyavihar, +Mumbai 400077, India +Mumbai 400077, India"
+c693c578d783323d130d642bd04d391aac7e8f81,Semantic Pyramids for Gender and Action Recognition,"Semantic Pyramids for Gender and Action +Recognition +Fahad Shahbaz Khan, Joost van de Weijer, Rao Muhammad Anwer, Michael Felsberg, Carlo Gatta"
+c6badb2cc1191f9dd5e5bea7df75a76349176d01,Densely tracking sequences of 3D face scans,"Densely tracking sequences of 3D face scans +Huaxiong DING +Ecole Centrale de LYON +Liming Chen +Ecole Centrale de LYON"
+c6c086748474dcda06d773891848aa1472de3560,Activity Recognition Based on a Magnitude-Orientation Stream Network,"Activity Recognition based on a +Magnitude-Orientation Stream Network +Carlos Caetano, Victor H. C. de Melo, Jefersson A. dos Santos, William Robson Schwartz +Smart Surveillance Interest Group, Department of Computer Science +Universidade Federal de Minas Gerais, Belo Horizonte, Brazil"
+c6eb026d3a0081f4cb5cde16d3170f8ecf8ce706,Face Recognition: From Traditional to Deep Learning Methods,"Face Recognition: From Traditional to Deep +Learning Methods +Daniel S´aez Trigueros, Li Meng +School of Engineering and Technology +University of Hertfordshire +Hatfield AL10 9AB, UK +Margaret Hartnett +GBG plc +London E14 9QD, UK"
c6ffa09c4a6cacbbd3c41c8ae7a728b0de6e10b6,Feature extraction using constrained maximum variance mapping,"This article appeared in a journal published by Elsevier. The attached opy is furnished to the author for internal non-commercial research nd education use, including for instruction at the authors institution @@ -5857,7 +20002,38 @@ institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright"
+c6fdbdbbbc7642daae22df0b7812e78d0647afb3,Unsupervised feature learning with C-SVDDNet,"Unsupervised Feature Learning with C-SVDDNet +Dong Wang and Xiaoyang Tan"
+c6dab0aba7045f078313a4186cd507ff8eb8ce32,Atypical disengagement from faces and its modulation by the control of eye fixation in children with autism spectrum disorder.,"BIROn - Birkbeck Institutional Research Online +Enabling open access to Birkbeck’s published research output +Atypical disengagement from faces and its modulation +y the control of eye fixation in children with Autism +Spectrum Disorder +Journal Article +http://eprints.bbk.ac.uk/4677 +Version: Accepted (Refereed) +Citation: +© 2011 Springer +Publisher version +______________________________________________________________ +All articles available through Birkbeck ePrints are protected by intellectual property law, including +opyright law. Any use made of the contents should comply with the relevant law. +______________________________________________________________ +Kikuchi, Y.; Senju, A.; Akechi, H.; Tojo, Y.; Osanai, H.; Hasegawa, T. +(2011) +Atypical disengagement from faces and its modulation by the control of +eye fixation in children with Autism Spectrum Disorder +Deposit Guide"
+c6260f83e86dd4d1ece92e528422ecc6e36c13ef,Siamese networks for generating adversarial examples,"Siamese networks for generating adversarial examples +Mandar Kulkarni +Data Scientist +Schlumberger"
c62c07de196e95eaaf614fb150a4fa4ce49588b4,SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation,Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18)
+c607572fd2594ca83f732c9790fd590da9e69eb1,Comparative Evaluation of Deep Architectures for Face Recognition in Unconstrained Environment ( FRUE ),"Comparative Evaluation of Deep Architectures for Face +Recognition in Unconstrained Environment (FRUE) +Deeksha Gupta +Department of Computer Science and Applications, +MCM DAV College for Women, Chandigarh, (India)"
ec90d333588421764dff55658a73bbd3ea3016d2,Protocol for Systematic Literature Review of Face Recognition in Uncontrolled Environment,"Research Article Protocol for Systematic Literature Review of Face Recognition in Uncontrolled Environment @@ -5868,11 +20044,72 @@ D Reconstruction of “In-the-Wild” Faces in Images and Videos James Booth, Anastasios Roussos, Evangelos Ververas, Epameinondas Anton- kos, Stylianos Ploumpis, Yannis Panagakis, and Stefanos Zafeiriou"
+ec89c5f2f5acce23b0d05736cd9f32d4ca6dc382,Body Actions Change the Appearance of Facial Expressions,"Body Actions Change the Appearance of Facial +Expressions +Carlo Fantoni1,2*, Walter Gerbino1 +Department of Life Sciences, Psychology Unit ‘‘Gaetano Kanizsa’’, University of Trieste, Trieste, Italy, 2 Center for Neuroscience and Cognitive Istituto +Italiano di Tecnologia, Rovereto, Italy"
+ec9e8d69b67bcb2814b538091fa288b6bdbb990f,GURLS: a Toolbox for Regularized Least Squares Learning,"Computer Science and ArtificialIntelligence LaboratoryTechnical Reportmassachusetts institute of technology, cambridge, ma 02139 usa — www.csail.mit.eduMIT-CSAIL-TR-2012-003CBCL-306January 31, 2012GURLS: a Toolbox for Regularized Least Squares LearningAndrea Tacchetti, Pavan S. Mallapragada, Matteo Santoro, and Lorenzo Rosasco"
+ece31d41b4da5457d570c04d22f19fcd026776b6,Learning Deep Disentangled Embeddings with the F-Statistic Loss,"Learning Deep Disentangled Embeddings +With the F-Statistic Loss +Karl Ridgeway +University of Colorado +Boulder, Colorado +Department of Computer Science +Department of Computer Science +Michael C. Mozer +University of Colorado +Boulder, Colorado"
+ec2027c2dd93e4ee8316cc0b3069e8abfdcc2ecf,Latent Variable PixelCNNs for Natural Image Modeling,"Latent Variable PixelCNNs for Natural Image Modeling +Alexander Kolesnikov 1 Christoph H. Lampert 1"
+ec7a545ba99542b2b74340d2e863590e4f450bb7,Sparse Subspace Clustering by Orthogonal Matching Pursuit,"Sparse Subspace Clustering by Orthogonal Matching Pursuit +Center for Imaging Science, Johns Hopkins University, Baltimore, MD, 21218, USA +Chong You +nd Ren´e Vidal"
+ec443db55db1a6721387b2054b94f6df020994ae,Weakly Supervised Visual Dictionary Learning by Harnessing Image Attributes,"Weakly Supervised Visual Dictionary Learning +y Harnessing Image Attributes +Yue Gao, Senior Member, IEEE, Rongrong Ji, Senior Member, IEEE, Wei Liu, Member, IEEE, +Qionghai Dai, Senior Member, IEEE, and Gang Hua, Senior Member, IEEE"
+ec25f39fa6b4ef4529981a1ae051086e93642d27,Deformable Part Models are Convolutional Neural Networks Tech report,"Deformable Part Models are Convolutional Neural Networks +Tech report +Ross Girshick Forrest Iandola Trevor Darrell +Jitendra Malik +UC Berkeley"
ec12f805a48004a90e0057c7b844d8119cb21b4a,Distance-Based Descriptors and Their Application in the Task of Object Detection,"Distance-Based Descriptors and Their Application in the Task of Object Detection Radovan Fusek(B) and Eduard Sojka Department of Computer Science, Technical University of Ostrava, FEECS, 7. Listopadu 15, 708 33 Ostrava-Poruba, Czech Republic"
+eca9b9dd665556423278b85f79e1d589009a7ea7,Person Re-Identi fi cation by Robust Canonical Correlation Analysis,"IEEE SIGNAL PROCESSING LETTERS, VOL. 22, NO. 8, AUGUST 2015 +Person Re-Identification by Robust +Canonical Correlation Analysis +Le An, Songfan Yang, Member, IEEE, and Bir Bhanu, Fellow, IEEE"
+ecf2ba5ea183a6be63b57543a19dd41e8017daaf,Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching,"Cooperative Learning of Energy-Based Model and Latent Variable Model via +MCMC Teaching +Jianwen Xie 1,2, Yang Lu 1,3, Ruiqi Gao 1, Ying Nian Wu 1 +Department of Statistics, University of California, Los Angeles, USA +Hikvision Research America +Amazon RSML (Retail System Machine Learning) Group"
+ec1223c8fc16751dd577d3418f61d44a139c7dc3,Group Influences on Engaging Self-Control: Children Delay Gratification and Value It More When Their In-Group Delays and Their Out-Group Doesn't.,"RUNNING HEAD: GROUP INFLUENCES ON SELF-CONTROL +Group Influences on Engaging Self-control: Children Delay Gratification and Value It More +When Their In-Group Delays and Their Out-Group Doesn’t +Sabine Doebel* and Yuko Munakata +Department of Psychology and Neuroscience, University of Colorado Boulder +*Corresponding author"
+ecd0a2e55f456b69243d1278fee15d8dbfc98c28,Heterogeneous Multicores: When Slower is Faster,"Heterogeneous Multicores: When Slower is Faster +Tomas Hruby +Herbert Bos +The Network Institute, VU University Amsterdam +Andrew S. Tanenbaum"
+ecc09ab9c61dc3a3a15f55332f63bccbf443f291,Cross-Domain Deep Face Matching for Real Banking Security Systems,"Cross-Domain Deep Face Matching for Real +Banking Security Systems +Johnatan S. Oliveira1,∗, Gustavo B. Souza2,∗, Anderson R. Rocha3, Fl´avio E. Deus1 and Aparecido N. Marana4 +Department of Electrical Engineering, University of Bras´ılia (UnB), Bras´ılia, Brazil. +Department of Computing, Federal University of S˜ao Carlos (UFSCar), S˜ao Carlos, Brazil. +Institute of Computing, University of Campinas (Unicamp), Campinas, Brazil. +Department of Computing, S˜ao Paulo State University (Unesp), Bauru, Brazil. +E-mails: {jow, +Equal contributors."
ec54000c6c0e660dd99051bdbd7aed2988e27ab8,Two in One: Joint Pose Estimation and Face Recognition with Pca,"TWO IN ONE: JOINT POSE ESTIMATION AND FACE RECOGNITION WITH P2CA1 Francesc Tarres*, Antonio Rama* {tarres, @@ -5880,11 +20117,102 @@ Davide Onofrio+, Stefano Tubaro+ {d.onofrio, *Dept. Teoria del Senyal i Comunicacions - Universitat Politècnica de Catalunya, Barcelona, Spain +Dipartimento di Elettronica e Informazione - Politecnico di Milano, Meiland, Italy"
+ecf4690ddd3ad26f9cd1749d16ef1aa06d391f92,Does Exposure to Hostile Environments Predict Enhanced Emotion Detection?,"PDF hosted at the Radboud Repository of the Radboud University +Nijmegen +The following full text is a publisher's version. +For additional information about this publication click this link. +http://hdl.handle.net/2066/191999 +Please be advised that this information was generated on 2018-06-28 and may be subject to +hange."
+ecdf8e5393eead0b63c5bc4fbe426db5a70574eb,Linear Subspace Learning for Facial Expression Analysis,"Linear Subspace Learning for +Facial Expression Analysis +Caifeng Shan +Philips Research +The Netherlands +. Introduction +Facial expression, resulting from movements of the facial muscles, is one of the most +powerful, natural, and immediate means for human beings to communicate their emotions +nd intentions. Some examples of facial expressions are shown in Fig. 1. Darwin (1872) was +the first to describe in detail the specific facial expressions associated with emotions in +nimals and humans; he argued that all mammals show emotions reliably in their faces. +Psychological studies (Mehrabian, 1968; Ambady & Rosenthal, 1992) indicate that facial +expressions, with other non-verbal cues, play a major and fundamental role in face-to-face +ommunication. +Fig. 1. Facial expressions of George W. Bush. +Machine analysis of facial expressions, enabling computers to analyze and interpret facial +expressions as humans do, has many important applications including intelligent human- +omputer interaction, computer animation, surveillance and security, medical diagnosis, +law enforcement, and awareness system (Shan, 2007). Driven by its potential applications +nd theoretical interests of cognitive and psychological scientists, automatic facial"
+ec6855acd0871d3e000872a5dd89db97c1554e18,Contrasting emotion processing and executive functioning in attention-deficit/hyperactivity disorder and bipolar disorder.,"016, Vol. 130, No. 5, 531–543 +0735-7044/16/$12.00 +© 2016 American Psychological Association +http://dx.doi.org/10.1037/bne0000158 +Contrasting Emotion Processing and Executive Functioning in +Attention-Deficit/Hyperactivity Disorder and Bipolar Disorder +Stephen Soncin, Donald C. Brien, and Brian C. Coe +Queen’s University +Queen’s University and Hotel Dieu Hospital, Kingston, +Alina Marin +Ontario, Canada +Douglas P. Munoz +Queen’s University +Attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) are highly comorbid and +share executive function and emotion processing deficits, complicating diagnoses despite distinct clinical +features. We compared performance on an oculomotor task that assessed these processes to capture subtle +differences between ADHD and BD. The interaction between emotion processing and executive func- +tioning may be informative because, although these processes overlap anatomically, certain regions that +re compromised in each network are different in ADHD and BD. Adults, aged 18 – 62, with ADHD (n ⫽ +2), BD (n ⫽ 20), and healthy controls (n ⫽ 21) performed an interleaved pro- and antisaccade task"
+ec4af4a6e89d61c05dcdf89f7f5d0a404bed4027,Bodily action penetrates affective perception.,"Bodily action penetrates affective +perception +Carlo Fantoni, Sara Rigutti and Walter Gerbino +Department of Life Sciences, Psychology Unit “Gaetano Kanizsa,” University of Trieste, Trieste, Italy"
ec0104286c96707f57df26b4f0a4f49b774c486b,An Ensemble CNN2ELM for Age Estimation,"An Ensemble CNN2ELM for Age Estimation Mingxing Duan , Kenli Li, Senior Member, IEEE, and Keqin Li, Fellow, IEEE"
+ecbaa92c289f4f5ff9a57b19a2725036a92311f5,Focused Evaluation for Image Description with Binary Forced-Choice Tasks,"Proceedings of the 5th Workshop on Vision and Language, pages 19–28, +Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
+ec91c6d6235f31c751b03489d7b1d472dfc9da26,Face Database Retrieval Using Pseudo 2D Hidden Markov Models,"Face Database Retrieval Using Pseudo 2D Hidden Markov Models +Fraunhofer Institute for Media Communication IMK +Stefan Eickeler +Schloss Birlinghoven +53754 Sankt Augustin, Germany"
+ec3621e900cc50afd067584bb1246a8b4e338fa8,Structured Triplet Learning with POS-Tag Guided Attention for Visual Question Answering,"Structured Triplet Learning with POS-tag Guided Attention +for Visual Question Answering +Zhe Wang1 Xiaoyi Liu2 Liangjian Chen1 Limin Wang3 Yu Qiao4 Xiaohui Xie1 Charless Fowlkes1 +Dept. of CS, UC Irvine +Microsoft +CVL, ETH Zurich +SIAT, CAS"
+ec7d418ddf95d231b2afc70ed8c94d0764abec61,Knowledge Transfer Using Latent Variable Models,"Copyright +Ayan Acharya"
+4edc7f27d4512b69be54abfc6b9876e5b00725ab,Facial Expression Recognition using Convolutional Neural Networks: State of the Art,"Facial Expression Recognition using +Convolutional Neural Networks: State of the Art +Christopher Pramerdorfer, Martin Kampel +Computer Vision Lab, TU Wien +Vienna, Austria +Email:"
+4e1d7bad6cde28e65b12c5824b1016859e1ae704,Enhanced Face Recognition Using Discrete Cosine Transform,"Enhanced Face Recognition Using Discrete +Cosine Transform +Zahraddeen Sufyanu, Member, IAENG, Fatma S. Mohamad, Abdulganiyu A. Yusuf, and Mustafa B. +Mamat"
+4efb08fcd652c60764b6fd278cee132b71c612a1,Pixel Deconvolutional Networks,"PIXEL DECONVOLUTIONAL NETWORKS +Hongyang Gao +Washington State University +Hao Yuan +Washington State University +Zhengyang Wang +Washington State University +Shuiwang Ji +Washington State University"
4e32fbb58154e878dd2fd4b06398f85636fd0cf4,A Hierarchical Matcher using Local Classifier Chains,"A Hierarchical Matcher using Local Classifier Chains L. Zhang and I.A. Kakadiaris Computational Biomedicine Lab, 4849 Calhoun Rd, Rm 373, Houston, TX 77204"
+4eca3e3c4876fc7ec81224d4ec2f159c9e7c72c3,Facial recognition using new LBP representations,
+4ea6954b47baec061fa3f3e1228833eba7be07f9,Multi-pseudo Regularized Label for Generated Data in Person Re-Identification.,"Multi-pseudo Regularized Label for Generated Data +in Person Re-Identification +Yan Huang, Jingsong Xu, Qiang Wu, Member, IEEE Zhedong Zheng, Zhaoxiang Zhang, Senior Member, IEEE +nd Jian Zhang, Senior Member, IEEE"
4ea53e76246afae94758c1528002808374b75cfa,A Review of Scholastic Examination and Models for Face Recognition and Retrieval in Video,"Lasbela, U. J.Sci. Techl., vol.IV , pp. 57-70, 2015 Review ARTICLE A Review of Scholastic Examination and Models for Face Recognition @@ -5898,17 +20226,155 @@ Institute of Biochemistry, University of Balochistan, Quetta" 4e97b53926d997f451139f74ec1601bbef125599,Discriminative Regularization for Generative Models,"Discriminative Regularization for Generative Models Alex Lamb, Vincent Dumoulin and Aaron Courville Montreal Institute for Learning Algorithms, Universit´e de Montr´eal"
+4e5698894946680e4d6e766346355b2dc1959819,Cross-pose Facial Expression Recognition,Cross-pose Facial Expression Recognition
+4ec3c7fa51d823a43b3808c7c6baa2e153104bdf,Neuron Pruning for Compressing Deep Networks using Maxout Architectures,"Neuron Pruning for Compressing Deep +Networks using Maxout Architectures +Fernando Moya Rueda, Rene Grzeszick, Gernot A. Fink +TU Dortmund University +Department of Computer Science"
4e27fec1703408d524d6b7ed805cdb6cba6ca132,SSD-Sface: Single shot multibox detector for small faces,"SSD-Sface: Single shot multibox detector for small faces C. Thuis"
4e6c9be0b646d60390fe3f72ce5aeb0136222a10,Long-Term Temporal Convolutions for Action Recognition,"Long-term Temporal Convolutions for Action Recognition G¨ul Varol, Ivan Laptev, and Cordelia Schmid, Fellow, IEEE"
+4ec4392246a7760d189cd6ea48a81664cd2fe4bf,GPU Accelerated ACF Detector,
+4ebf84c6389e842e90c39850f0152671ba7fa0dc,Adversarial Attribute-Image Person Re-identification,"Adversarial Attribute-Image Person Re-identification +Zhou Yin, Wei-Shi Zheng, Ancong Wu, Hong-Xing Yu, Hai Wan, Xiaowei Guo, Feiyue +Huang, Jianhuang Lai +For reference of this work, please cite: +Adversarial Attribute-Image Person Re-identification +Zhou Yin, Wei-Shi Zheng, Ancong Wu, Hong-Xing Yu, Hai Wan, Xiaowei Guo, Feiyue Huang, Jianhuang +Lai, IJCAI, 2018 +title={Adversarial Attribute-Image Person Re-identification}, +uthor={Zhou Yin, Wei-Shi Zheng, Ancong Wu, Hong-Xing Yu, Hai Wan, Xiaowei Guo, Feiyue Huang, +Jianhuang Lai}, +journal={ International Joint Conference on Artificial Intelligence}, +year={2018}"
+4e82908e6482d973c280deb79c254631a60f1631,Improving Efficiency and Scalability in Visual Surveillance Applications,
+4eaaefc53fd61d27b9ce310c188fe76003a341bd,Assessing Generative Models via Precision and Recall,"Assessing Generative Models via Precision and Recall +Mehdi S. M. Sajjadi∗ +MPI for Intelligent Systems, +Max Planck ETH Center +for Learning Systems +Olivier Bachem +Google Brain +Mario Lucic +Google Brain +Olivier Bousquet +Google Brain +Sylvain Gelly +Google Brain"
+4eb0b82b294f601510cd965adcf0e8c386cbaf22,Face Detection for Augmented Reality Application Using Boosting-based Techniques,"Face Detection for Augmented Reality Application +Using Boosting-based Techniques +Youssef Hbali1, Lahoucine Ballihi2, Mohammed Sadgal1, El Fazziki Abdelaziz1 +Cadi Ayyad University. B.P. 2390, Avenue Prince My Abdellah, Marrakech, Morocco +LRIT-CNRST URAC 29, Mohammed V University In Rabat, Faculty of Sciences Rabat, Morocco"
+4ed0be0b5d67cff63461ba79f2a7928d652cf310,Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey,"JOURNAL OF LATEX CLASS FILES, VOL. PP, AUGUST 2017 +Threat of Adversarial Attacks on Deep Learning +in Computer Vision: A Survey +ACKNOWLEDGEMENTS: The authors thank Nicholas Carlini (UC Berkeley) and Dimitris Tsipras (MIT) for feedback to improve the survey +quality. We also acknowledge X. Huang (Uni. Liverpool), K. R. Reddy (IISC), E. Valle (UNICAMP), Y. Yoo (CLAIR) and others for providing pointers +to make the survey more comprehensive. This research was supported by ARC grant DP160101458. +Naveed Akhtar and Ajmal Mian"
+4e25cd4e40494aa5073fcfbef7506336b84152f4,"Independent Component Analysis, Principal Component Analysis and Rough Sets in Face Recognition","Independent Component Analysis, Principal +Component Analysis and Rough Sets in Face +Recognition +Roman W. ´Swiniarski1 and Andrzej Skowron2 +Department of Mathematical and Computer Sciences +San Diego State University +5500 Campanile Drive San Diego, CA 92182, USA +Institute of Computer Science, Polish Academy of Sciences +Ordona 21, 01-237 Warsaw, Poland +Institute of Mathematics, Warsaw University +Banacha 2, 02-097 Warsaw, Poland"
+4e608c77043f56b0abfb2760fb2fd2516b5412b0,Spectral Face Recognition Using Orthogonal Subspace Bases,
4ef0a6817a7736c5641dc52cbc62737e2e063420,Study of Face Recognition Techniques,"International Journal of Advanced Computer Research (ISSN (Print): 2249-7277 ISSN (Online): 2277-7970) Volume-4 Number-4 Issue-17 December-2014 Study of Face Recognition Techniques Sangeeta Kaushik1*, R. B. Dubey2 and Abhimanyu Madan3 Received: 10-November-2014; Revised: 18-December-2014; Accepted: 23-December-2014 ©2014 ACCENTS"
+4e71e03d4122aad182ad51ab187d4b55b41fc957,Clustering-Based Discriminant Analysis for Eye Detection,"Clustering-Based Discriminant Analysis +for Eye Detection +Shuo Chen and Chengjun Liu +paper +three +proposes"
+4ee380e444063f9b948a2fd82e5c11b97a570ad1,Operating system support to an online hardware-software co-design scheduler for heterogeneous multicore architectures,"Universidade de São Paulo +Biblioteca Digital da Produção Intelectual - BDPI +Departamento de Sistemas de Computação - ICMC/SSC +Comunicações em Eventos - ICMC/SSC +014-08-20 +Operating system support to an online +hardware-software co-design scheduler for +heterogeneous multicore architectures +IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, +0th, 2014, Chongqing. +http://www.producao.usp.br/handle/BDPI/48567 +Downloaded from: Biblioteca Digital da Produção Intelectual - BDPI, Universidade de São Paulo"
+4e33798e364826af1241d28d57977bec9a579709,Active learning with version spaces for object detection,"Active learning with version spaces for object detection 1 +Soumya Roy 2 +Vinay P. Namboodiri 2 +Arijit Biswas 3"
+4eb22856671b9340e5ae532a021be62b9d31c9bc,The Minority Glass Ceiling Hypothesis: Exploring Reasons and Remedies for the Underrepresentation of Racial-ethnic Minorities in Leadership Positions,"THE MINORITY GLASS CEILING HYPOTHESIS: +EXPLORING REASONS AND REMEDIES FOR THE +UNDERREPRESENTATION OF RACIAL-ETHNIC MINORITIES IN +LEADERSHIP POSITIONS +Seval Gündemir"
+4e3c07283334a9b90dac011033fa2403bcf3c473,A novel feature selection method and its application,"J Intell Inf Syst (2013) 41:235–268 +DOI 10.1007/s10844-013-0243-x +A novel feature selection method and its application +Bing Li· Tommy W. S. Chow· Di Huang +Received: 11 April 2012 / Revised: 8 March 2013 / Accepted: 11 March 2013 / +Published online: 4 April 2013 +© Springer Science+Business Media New York 2013"
+4e613c9342d6e90f7af5fd3f246c6d82a33fe98d,Estimating Human Pose in Images,"Estimating Human Pose in Images +Navraj Singh +December 11, 2009 +Introduction +This project attempts to improve the performance of an existing method of estimating the pose of humans in still images. +Tasks such as object detection and classification have received much attention already in the literature. However, sometimes we are +interested in more detailed aspects of objects like pose. This is a challenging task due to the large variety of poses an object can +take in a variety of settings. For human pose estimation, aspects such as clothing, occlusion of body parts, etc. make the task even +harder. +The approaches taken up in the literature to solve this problem focus on either a top-down approach, bottom-up approach, +or a hybrid of the two. The top-down approach involves comparing test images with stored examples of humans in various poses +using some similarity measure. This approach might require a very large set of examples of human poses. The bottom-up approach, +on the other hand, uses low level human body part detectors and in some manner assembles the information to predict the entire +ody pose. This project attempts to build upon a mostly bottom-up approach, called LOOPS (Localizing Object Outlines using +Probabilistic Shape), that was developed in [1] by G. Heitz, et al. in Prof. Daphne Koller's group. Specifically, we investigate the +onstruction and incorporation of a skin detector into the LOOPS pipeline, and a couple of pairwise features in the appearance +model. The overall improvement in the localization is negligible, with some improvement in head localization. Since the +improvements considered are within the framework of LOOPS, a brief overview of the LOOPS method is discussed next. +Brief Overview of the LOOPS method as applied to humans +The main random variables defined in the LOOPS method, described in detail in [1], are the locations of a set of key"
+4ecd459aa4b4590bdc552e07b6d0bbe132fb1fcf,Learning of Graph Compressed Dictionaries for Sparse Representation Classification,"Learning of Graph Compressed Dictionaries for Sparse +Representation Classification +Farshad Nourbakhsh and Eric Granger +Laboratoire d’imagerie de vision et d’intelligence artificielle +´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montr´eal, Canada +Keywords: +Matrix Factorization, Graph Compression, Dictionary Learning, Sparse Representation Classification, +Clustering, Face Recognition, Video Surveillance"
+4ee87ed965e78adb1035a5322350afac9ca901f5,Multi-target tracking of time-varying spatial patterns,"Multi-Target Tracking of Time-varying Spatial Patterns +Jingchen Liu1 +Yanxi Liu1,2 +Department of Computer Science and Engineering +Department of Electrical Engineering +The Pennsylvania State University +University Park, PA 16802, USA +{jingchen,"
+4e4a47e2d285e55f3d0b6d449d6b9893615db5cd,Use of l2/3-norm Sparse Representation for Facial Expression Recognition,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Impact Factor (2012): 3.358 +Use of ℓ2/3-norm Sparse Representation for Facial +Expression Recognition +Sandeep Rangari1, Sandeep Gonnade2 +MATS University, MATS School of Engineering and Technology, Arang, Raipur, India +MATS University, MATS School of Engineering and Technology, Arang, Raipur, India +three +to discriminate +represents emotion,"
4e0e49c280acbff8ae394b2443fcff1afb9bdce6,Automatic Learning of Gait Signatures for People Identification,"Automatic learning of gait signatures for people identification F.M. Castro Univ. of Malaga @@ -5922,6 +20388,38 @@ nguil<at>uma.es N. P´erez de la Blanca Univ. of Granada nicolas<at>ugr.es"
+4e61f3dc6aa7994613a3708e823aadd478c73f5f,Generating Discriminative Object Proposals via Submodular Ranking,"Generating Discriminative Object Proposals via Submodular Ranking +Yangmuzi Zhang∗, Zhuolin Jiang†, Xi Chen∗, and Larry S. Davis∗ +University of Maryland at College Park, MD +Raytheon BBN Technologies, USA +Email:"
+4eb600aa4071b9a73da49e5374d6e22ca46eaba6,Understanding bag-of-words model: a statistical framework,"Noname manuscript No. +(will be inserted by the editor) +Understanding Bag-of-Words Model: A Statistical Framework +Yin Zhang ⋅ Rong Jin ⋅ Zhi-Hua Zhou +Received: date / Accepted: date"
+4e8206dd2e163c6a139bfd0ec3adf410e7b78c4a,A Multi-scale Boosted Detector for Efficient and Robust Gesture Recognition,"A Multi-scale Boosted Detector for Efficient and +Robust Gesture Recognition +Camille Monnier, Stan German, Andrey Ost +Charles River Analytics +Cambridge, MA, USA"
+4e12080616da4b540c8f79db2dd1b654cd8345ce,Pose-Driven Deep Models for Person Re-Identification,"Pose-Driven Deep Models for Person +Re-Identification +Masters thesis of +Andreas Eberle +At the faculty of Computer Science +Institute for Anthropomatics and Robotics +Reviewer: +Second reviewer: +Advisors: +Prof. Dr.-Ing. Rainer Stiefelhagen +Prof. Dr.-Ing. Jürgen Beyerer +Dr.-Ing. Saquib Sarfraz +Dipl.-Inform. Arne Schumann +Duration: 31. August 2017 – +8. February 2018 +KIT – University of the State of Baden-Wuerttemberg and National Laboratory of the Helmholtz Association +www.kit.edu"
20a432a065a06f088d96965f43d0055675f0a6c1,The Effects of Regularization on Learning Facial Expressions with Convolutional Neural Networks,"In: Proc. of the 25th Int. Conference on Artificial Neural Networks (ICANN) Part II, LNCS 9887, pp. 80-87, Barcelona, Spain, September 2016 The final publication is available at Springer via @@ -5940,6 +20438,26 @@ German Research Center for Artificial Intelligence (DFKI), Tripstaddterstr. 122, 67663 Kaiserslautern, Germany Technical University of Kaiserslautern http://www.av.dfki.de"
+2057837e059a1dde8c6c4c0587e652b79c04780a,Learning to Recognize Novel Objects in One Shot through Human-Robot Interactions in Natural Language Dialogues,"Learning to Recognize Novel Objects in One Shot through Human-Robot +Interactions in Natural Language Dialogues +Thomas Williams +Matthias Scheutz +Evan Krause +HRI Laboratory +Tufts University +00 Boston Ave +Medford, MA 02155, USA +Michael Zillich +Inst. for Automation and Control +Technical University Vienna +Gusshausstr 27-29/E376 +040 Vienna, Austria +HRI Laboratory +Tufts University +00 Boston Ave +HRI Laboratory +Tufts University +00 Boston Ave"
2004afb2276a169cdb1f33b2610c5218a1e47332,Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition,"Hindawi Computational Intelligence and Neuroscience Volume 2018, Article ID 3803627, 11 pages @@ -5960,6 +20478,15 @@ Face recognition (FR) with single sample per person (SSPP) is a challenge in com trained, it makes facial variation such as pose, illumination, and disguise difficult to be predicted. To overcome this problem, this paper proposes a scheme combined traditional and deep learning (TDL) method to process the task. First, it proposes an expanding sample method based on traditional approach. Compared with other expanding sample methods, the method can be used easily and"
+2084e54505cfe4fd81005167b1b11d10b5f837d1,Person Re-Identification by Discriminative Selection in Video,"Person Re-Identification by Discriminative Selection in Video Ranking +Wang, T; Gong, S; Zhu, X; Wang, S +•(cid:9)“The final publication is available at http://link.springer.com/chapter/10.1007%2F978-3-319- +0593-2_45” +For additional information about this publication click this link. +http://qmro.qmul.ac.uk/xmlui/handle/123456789/11432 +Information about this research object was correct at the time of download; we occasionally +make corrections to records, please therefore check the published record when citing. For +more information contact"
20e504782951e0c2979d9aec88c76334f7505393,Robust LSTM-Autoencoders for Face De-Occlusion in the Wild,"Robust LSTM-Autoencoders for Face De-Occlusion in the Wild Fang Zhao, Jiashi Feng, Jian Zhao, Wenhan Yang, Shuicheng Yan"
@@ -5974,6 +20501,24 @@ FOR THE DEGREE OF MASTERS OF SCIENCE Ranjay Krishna March 2016"
+20a052963f2c46aff817f34a09c396c44b3e46da,Visually Grounded Meaning Representations,"Visually Grounded Meaning Representations +Carina Silberer, Member, IEEE, Vittorio Ferrari, Member, IEEE, Mirella Lapata, Member, IEEE"
+20e783a2df0486cd1c8b6b59fc76220f5718b304,Stereo-based Pedestrian Detection Using Two-stage Classifiers,"4-26 +MVA2011 IAPR Conference on Machine Vision Applications, June 13-15, 2011, Nara, JAPAN +Stereo-based Pedestrian Detection Using Two-stage Classifiers +Manabu Nishiyama, Akihito Seki, Tomoki Watanabe +Corporate Research and Development Center, Toshiba Corporation +, Komukai-Toshiba-cho, Saiwai-ku, Kawasaki, 212-8582, Japan"
+202cbc83c22a9c7b3d878cc1bed1c5cf152eb6fb,Learning Embeddings for Product Visual Search with Triplet Loss and Online Sampling,"Learning Embeddings for Product Visual Search with +Triplet Loss and Online Sampling +Eric Dodds, Huy Nguyen, Simao Herdade, Jack Culpepper, Andrew Kae, Pierre Garrigues +{eric.mcvoy.dodds, huyng, sherdade, jackcul, andrewkae, +Yahoo Research"
+208e903211ddc62b997afb5a1bd3c2c43e0e69ee,Real-Time Action Detection in Video Surveillance using Sub-Action Descriptor with Multi-CNN,"Real-Time Action Detection in Video Surveillance using Sub-Action +Descriptor with Multi-CNN +Cheng-Bin Jin*, Shengzhe Li†, and Hakil Kim* +*Inha University, Incheon, Korea +Visionin Inc., Incheon, Korea"
20ade100a320cc761c23971d2734388bfe79f7c5,Subspace Clustering via Good Neighbors,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE Subspace Clustering via Good Neighbors Jufeng Yang, Jie Liang, Kai Wang, Ming-Hsuan Yang"
@@ -5988,6 +20533,88 @@ Shenzhen Key Lab. of Information Sci&Tech, ♯Nagaoka University of Technology, Japan RECOGNITION . INTRODUCTION"
+200f68f899f0bf72dd2c49ba2b4a5027e0291531,Efficient Activity Detection in Untrimmed Video with Max-Subgraph Search,"Efficient Activity Detection in Untrimmed Video +with Max-Subgraph Search +Chao Yeh Chen and Kristen Grauman"
+20e64f44ce2977a4dc5099fce6f73842613f0865,"Ridge Regression, Hubness, and Zero-Shot Learning","Ridge Regression, Hubness, and Zero-Shot Learning(cid:63) +Yutaro Shigeto1, Ikumi Suzuki2, Kazuo Hara3, Masashi Shimbo1, and +Yuji Matsumoto1 +Nara Institute of Science and Technology, Ikoma, Nara, Japan +The Institute of Statistical Mathematics, Tachikawa, Tokyo, Japan +National Institute of Genetics, Mishima, Shizuoka, Japan"
+2049ca79ce94ddfe0cc3d39bf770f580a740f3ac,Activity analysis : finding explanations for sets of events,ActivityAnalysis:FindingExplanationsforSetsofEventsbyDimaJamalAlDamenSubmittedinaccordancewiththerequirementsforthedegreeofDoctorofPhilosophy.TheUniversityofLeedsSchoolofComputingSeptember2009Thecandidateconfirmsthattheworksubmittedisherownandthattheappropriatecredithasbeengivenwherereferencehasbeenmadetotheworkofothers.Thiscopyhasbeensuppliedontheunderstandingthatitiscopyrightmaterialandthatnoquotationfromthethesismaybepublishedwithoutproperacknowledgement.
+20a6de85d7d5f445dfaba90ab2e33879142023fc,Autonomous Vehicles that Interact with Pedestrians: A Survey of Theory and Practice,"THIS WORK HAS BEEN SUBMITTED TO THE IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. +Autonomous Vehicles that Interact with Pedestrians: +A Survey of Theory and Practice +Amir Rasouli and John K. Tsotsos"
+20f9a09defe5b02b98c464ca6df36b3b6358f60b,The State-of-the-Art in Visual Object Tracking,Volume 36 Number 3 September 2012
+20c59a55795eaa4f2629cc83fb556dc8c5bcfc1f,Modeling and visual recognition of human actions and interactions,"Modeling and visual recognition of human actions and +interactions +Ivan Laptev +To cite this version: +Ivan Laptev. Modeling and visual recognition of human actions and interactions. Computer Vision and +Pattern Recognition [cs.CV]. Ecole Normale Supérieure de Paris - ENS Paris, 2013. <tel-01064540> +HAL Id: tel-01064540 +https://tel.archives-ouvertes.fr/tel-01064540 +Submitted on 16 Sep 2014 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de +recherche français ou étrangers, des laboratoires"
+20e210bb6b1d3e637e2b2674aeead3fad8c2c70e,Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer,"Published as a conference paper at ICLR 2017 +PAYING MORE ATTENTION TO ATTENTION: +IMPROVING THE PERFORMANCE OF CONVOLUTIONAL +NEURAL NETWORKS VIA ATTENTION TRANSFER +Sergey Zagoruyko, Nikos Komodakis +Universit´e Paris-Est, ´Ecole des Ponts ParisTech +Paris, France"
+20e903faf8e2e656a89d983541b15f2e0d614eeb,Image to Image Translation for Domain Adaptation,"Image to Image Translation for Domain Adaptation +Zak Murez1,2 +Soheil Kolouri2 David Kriegman1 Ravi Ramamoorthi1 Kyungnam Kim2 +University of California, San Diego; 2 HRL Laboratories, LLC;"
+200f1a55c5974c4cac243bed3131ac5a9338840d,Human Computation for Object Detection,"May 09, 2013 +TR Number: UCSC-SOE-15-03 +Human Computation for Object Detection +Rajan Vaish1, Sascha T. Ishikawa1, Sheng Lundquist2, Reid Porter2, James Davis1 +University of California at Santa Cruz1, Los Alamos National Laboratory2 +{rvaish, stishika, {slundquist,"
+204db062f4952ce446cbb28fbc40d4a7f4424b03,Systematic evaluation of super-resolution using classification,"SYSTEMATIC EVALUATION OF +SUPER-RESOLUTION USING CLASSIFICATION +Vinay P. Namboodiri1, Vincent De Smet1 and Luc Van Gool1,2 +ESAT-PSI/IBBT, K.U.Leuven, Belgium +Computer Vision Laboratory, BIWI/ETH Z¨urich, Switzerland"
+203fcd66c043e44fefd783b8f54105f0a577fc25,Analyzing Content and Customer Engagement in Social Media with Deep Learning,"Analyzing Content and Customer Engagement in +Social Media with Deep Learning +(The bulk of this work was done by a student.)"
+20f272f4bdf562aa8b4dae84b67cfafa34a00738,Periocular biometrics: An emerging technology for unconstrained scenarios,"Periocular Biometrics: +An Emerging Technology for Unconstrained +Scenarios +Gil Santos and Hugo Proenc¸a +IT - Instituto de Telecomunicac¸ ˜oes +Universidade da Beira Interior +Covilh˜a, Portugal +Email:"
+20100323ec5c32ae91add8e866d891a78f1a2bbe,Unsupervised Object Discovery and Tracking in Video Collections,"Unsupervised Object Discovery and Tracking in Video Collections +Suha Kwak1,∗ +Minsu Cho1,∗ +Ivan Laptev1,∗ +Jean Ponce2,∗ +Cordelia Schmid1,† +Inria +´Ecole Normale Sup´erieure / PSL Research University"
+20717f1cb12ab208458c0f2505b237d8f061f97a,Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder,"Learning Classifiers from Synthetic Data Using a +Multichannel Autoencoder +Xi Zhang, Yanwei Fu, Andi Zang, Leonid Sigal, Gady Agam"
+2067ab35379381f05acaa7406a30d0ee02c0b8cc,Directional Statistics-based Deep Metric Learning for Image Classification and Retrieval,"Directional Statistics-based Deep Metric Learning +for Image Classification and Retrieval +Xuefei Zhe, Shifeng Chen, and Hong Yan, Fellow, IEEE"
2059d2fecfa61ddc648be61c0cbc9bc1ad8a9f5b,Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression,"TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 23, NO. 4, APRIL 2015 Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression @@ -5995,6 +20622,20 @@ Antoine Deleforge∗ Radu Horaud∗ Yoav Y. Schechner‡ Laurent Girin∗† INRIA Grenoble Rhˆone-Alpes, Montbonnot Saint-Martin, France Univ. Grenoble Alpes, GIPSA-Lab, France Dept. Electrical Eng., Technion-Israel Inst. of Technology, Haifa, Israel"
+20b8a76e988e796f0f225876a69842f6839e4c98,Real-time Gender Recognition for Uncontrolled Environment of Real-life Images,"REAL-TIME GENDER RECOGNITION FOR UNCONTROLLED +ENVIRONMENT OF REAL-LIFE IMAGES +Duan-Yu Chen and Kuan-Yi Lin +Department of Electrical Engineering, Yuan-Ze University, Taiwan +Keywords: +Gender recognition, Uncontrolled environment, Real-life images."
+202a923504ea81e94c06a81581539b893b461ee5,YELP: masking sound-based opportunistic attacks in zero-effort deauthentication,"YELP: Masking Sound-based Opportunistic A(cid:130)acks in +Zero-E(cid:128)ort Deauthentication +University of Alabama at Birmingham +University of Alabama at Birmingham +University of Alabama at Birmingham +Prakash Shrestha +S Abhishek Anand +Nitesh Saxena"
20111924fbf616a13d37823cd8712a9c6b458cd6,Linear Regression Line based Partial Face Recognition,"International Journal of Computer Applications (0975 – 8887) Volume 130 – No.11, November2015 Linear Regression Line based Partial Face Recognition @@ -6014,6 +20655,37 @@ Computer Science, Manasagagothri, Mysore. images. In"
+2056ba48e687d619c0ce69d0be323d48c5b90701,Similarity Mapping with Enhanced Siamese Network for Multi-Object Tracking,"Similarity Mapping with Enhanced Siamese Network +for Multi-Object Tracking +Minyoung Kim +Cupertino, CA +Stefano Alletto +Modena, MO +Panasonic Silicon Valley Laboratory +University of Modena and Reggio Emilia +Panasonic Silicon Valley Laboratory +Luca Rigazio +Cupertino, CA"
+20eaa3ebe2b6e1aff7c4585733c9fb0cfc941919,Image similarity using Deep CNN and Curriculum Learning,"Image similarity using Deep CNN and Curriculum Learning +Srikar Appalaraju +Vineet Chaoji +Amazon Development Centre (India) Pvt. Ltd. +Image similarity involves fetching similar looking images given a reference image. Our solution called SimNet, is a deep +Siamese network which is trained on pairs of positive and negative images using a novel online pair mining strategy inspired +y Curriculum learning. We also created a multi-scale CNN, where the final image embedding is a joint representation of +top as well as lower layer embedding’s. We go on to show that this multi-scale Siamese network is better at capturing fine +grained image similarities than traditional CNN’s. +Keywords — Multi-scale CNN, Siamese network, Curriculum learning, Transfer learning. +I. INTRODUCTION +The ability to find a similar set of images for a given +image has multiple uses-cases from visual search to +duplicate product detection to domain specific image +lustering. Our approach called SimNet, tries to identify +similar images for a new image using multi-scale Siamese +network. Fig. 1 shows examples of image samples from +CIFAR10 [39] on which SimNet is trained on. +Fig. 1 examples of CIFAR 10 images. Task is - given a new image +ut belonging to one of the 10 categories, find similar set of images."
20532b1f80b509f2332b6cfc0126c0f80f438f10,A Deep Matrix Factorization Method for Learning Attribute Representations,"A deep matrix factorization method for learning ttribute representations George Trigeorgis, Konstantinos Bousmalis, Student Member, IEEE, Stefanos Zafeiriou, Member, IEEE @@ -6026,12 +20698,39 @@ interaction Y. Yang · S. S. Ge · T. H. Lee · C. Wang Received: 27 June 2007 / Accepted: 6 December 2007 / Published online: 23 January 2008 © Springer-Verlag 2008"
+20928315086a49e0cdea0ec66f2e78e9c564f794,Person Detection for Indoor Videosurveillance Using Spatio-temporal Integral Features,"Person Detection for Indoor Videosurveillance +using Spatio-Temporal Integral Features +Adrien Descamps1, Cyril Carincotte2, and Bernard Gosselin1 +TCTS Lab, University of Mons, Mons, Belgium +Multitel ASBL, 2 Rue Pierre et Marie Curie, Mons, Belgium"
+203abfcc3df8de6606cf34fa32cf225627f52d00,Learning Robot Vision for Assisted Living,"Robotic Vision: +Technologies for Machine +Learning and Vision Applications +José García-Rodríguez +University of Alicante, Spain +Miguel Cazorla +University of Alicante, Spain"
+20260d36506911e04ad1efed1e60b06bfc178d52,Deep 3D face identification,"Deep 3D Face Identification +Donghyun Kim +Matthias Hernandez +Jongmoo Choi +G´erard Medioni +USC Institute for Robotics and Intelligent Systems (IRIS) +Unversity of Southern California +{kim207, mthernan, jongmooc,"
20a0b23741824a17c577376fdd0cf40101af5880,Learning to Track for Spatio-Temporal Action Localization,"Learning to track for spatio-temporal action localization Philippe Weinzaepfela Zaid Harchaouia,b NYU Inria∗ Cordelia Schmida"
+18bca470bf51f5cc42148cd7e34fa58280be8eb2,Face Expressional Recognition using Geometry and Behavioral Traits,"IJCSNS International Journal of Computer Science and Network Security, VOL.9 No.8, August 2009 +Face Expressional Recognition using Geometry and Behavioral +Traits +J. K. Kani Mozhi, Sr. Lect / Dept. of MCA, K. S. Rangasamy College of Technology, Tiruchengode. India. +J. K. Kani Mozhi 1 and Dr. R. S. D. Wahida Banu 2 +Dr. R. S. D. Wahida Banu, Prof. & Head / Dept. of ECE, Govt. College of Engg., Salem, India. +recognition"
18c72175ddbb7d5956d180b65a96005c100f6014,From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 23, NO. 6, JUNE 2001 From Few to Many: Illumination Cone @@ -6041,6 +20740,12 @@ Athinodoros S. Georghiades, Student Member, IEEE, Peter N. Belhumeur, Member, IE David J. Kriegman, Senior Member, IEEE"
18636347b8741d321980e8f91a44ee054b051574,Facial marks: Soft biometric for face recognition,"978-1-4244-5654-3/09/$26.00 ©2009 IEEE ICIP 2009"
+18ab703c9959fbea7ad253a4062eb705b245552c,Efficient trajectory extraction and parameter learning for data-driven crowd simulation,"Efficient Trajectory Extraction and Parameter Learning for Data-Driven +Crowd Simulation +Aniket Bera∗ +Sujeong Kim† +Dinesh Manocha‡ +The University of North Carolina at Chapel Hill"
181045164df86c72923906aed93d7f2f987bce6c,Rheinisch-westfälische Technische Hochschule Aachen,"RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN KNOWLEDGE-BASED SYSTEMS GROUP @@ -6060,6 +20765,20 @@ STEFAN SCHIFFER, THOMAS DESELAERS" 18d5b0d421332c9321920b07e0e8ac4a240e5f1f,Collaborative Representation Classification Ensemble for Face Recognition,"Collaborative Representation Classification Ensemble for Face Recognition Xiao Chao Qu, Suah Kim, Run Cui and Hyoung Joong Kim"
+18269fcaba9feba85552b039a9052cd67e6d9c8b,Emotional facial sensing and multimodal fusion in a continuous 2D affective space,"J Ambient Intell Human Comput (2012) 3:31–46 +DOI 10.1007/s12652-011-0087-6 +O R I G I N A L R E S E A R C H +Emotional facial sensing and multimodal fusion in a continuous +D affective space +Eva Cerezo • Isabelle Hupont • Sandra Baldassarri • +Sergio Ballano +Received: 3 February 2011 / Accepted: 24 September 2011 / Published online: 30 October 2011 +Ó Springer-Verlag 2011"
+18ccd8bd64b50c1b6a83a71792fd808da7076bc9,Object detection and segmentation from joint embedding of parts and pixels,"Object Detection and Segmentation +from Joint Embedding of Parts and Pixels +Michael Maire1, Stella X. Yu2, Pietro Perona1 +California Institute of Technology - Pasadena, CA 91125 +Boston College - Chestnut Hill, MA 02467"
18d51a366ce2b2068e061721f43cb798177b4bb7,Looking into your eyes: observed pupil size influences approach-avoidance responses.,"Cognition and Emotion ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20 Looking into your eyes: observed pupil size @@ -6076,10 +20795,50 @@ View related articles View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=pcem20"
+18c4a0e82fdddda2530b7281ad567abc0373a89f,Automatic Subspace Learning via Principal Coefficients Embedding,"Automatic Subspace Learning via Principal +Coefficients Embedding +Xi Peng, Jiwen Lu, Senior Member, IEEE, Zhang Yi, Fellow, IEEE and Rui Yan, Member, IEEE,"
+18cc17c06e34baaa3e196db07e20facdbb17026d,Describing Videos by Exploiting Temporal Structure,"Describing Videos by Exploiting Temporal Structure +Li Yao +Universit´e de Montr´eal +Atousa Torabi +Universit´e de Montr´eal +Kyunghyun Cho +Universit´e de Montr´eal +Nicolas Ballas +Universit´e de Montr´eal +Christopher Pal +´Ecole Polytechnique de Montr´eal +Hugo Larochelle +Universit´e de Sherbrooke +Aaron Courville +Universit´e de Montr´eal"
1885acea0d24e7b953485f78ec57b2f04e946eaf,Combining Local and Global Features for 3D Face Tracking,"Combining Local and Global Features for 3D Face Tracking Pengfei Xiong, Guoqing Li, Yuhang Sun Megvii (face++) Research {xiongpengfei, liguoqing,"
+1868aeb7f13e64ebc78869b371ef321572d6167f,Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes,"Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes +David V´azquez1, Jiaolong Xu1, Sebastian Ramos1, Antonio M. L´opez1,2 and Daniel Ponsa1,2 +Computer Vision Center +Dept. of Computer Science +Autonomous University of Barcelona +08193 Bellaterra, Barcelona, Spain +{dvazquez, jiaolong, sramosp, antonio,"
+18d4210a5bb56e92045ef0637208685abaaca6a5,GIANT: geo-informative attributes for location recognition and exploration,"GIANT: Geo-Informative Attributes for +locatioN recogniTion and exploration +National Lab of Pattern Recognition, Institute of Automation, CAS, Beijing 100190, China +China-Singapore Institute of Digital Media, Singapore, 139951, Singapore +Quan Fang1,2, Jitao Sang1,2, Changsheng Xu1,2 +{qfang, jtsang,"
+18de899c853120a1a2cd502ebc3e970b92e1882f,Age Regression from Soft Aligned Face Images Using Low Computational Resources,"Age regression from soft aligned face images +using low computational resources +Juan Bekios-Calfa1, Jos´e M. Buenaposada2, and Luis Baumela3 +Dept. de Ingenier´ıa de Sistemas y Computaci´on, Universidad Cat´olica del Norte +Av. Angamos 0610, Antofagasta, Chile +Dept. de Ciencias de la Computaci´on, Universidad Rey Juan Carlos +Calle Tulip´an s/n, 28933, M´ostoles, Spain +Dept. de Inteligencia Artificial, Universidad Polit´ecnica de Madrid +Campus Montegancedo s/n, 28660 Boadilla del Monte, Spain"
18a849b1f336e3c3b7c0ee311c9ccde582d7214f,"Efficiently Scaling up Crowdsourced Video Annotation A Set of Best Practices for High Quality, Economical Video Labeling","Int J Comput Vis DOI 10.1007/s11263-012-0564-1 Efficiently Scaling up Crowdsourced Video Annotation @@ -6094,11 +20853,90 @@ SYNTHESIS AND RECOGNITION Amit R. Sharma and 2Prakash. R. Devale Student and 2Professor & Head, Department of Information Tech., Bharti Vidyapeeth Deemed University, Pune, India"
+189355bff03076cc5bddaa11239626051931144d,Learning Representations for Automatic Colorization,"Learning Representations for Automatic Colorization +Gustav Larsson1, Michael Maire2, and Gregory Shakhnarovich2 +University of Chicago +Toyota Technological Institute at Chicago"
+18fe745e0840b7b086fb7d14850a95ebbd5ae57b,Evaluation and Acceleration of High-Throughput Fixed-Point Object Detection on FPGAs,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI +Evaluation and Acceleration of High-Throughput +Fixed-Point Object Detection on FPGAs +Xiaoyin Ma, Student Member, IEEE, Walid A. Najjar, Fellow, IEEE, Amit K. Roy-Chowdhury, Sr. Member, IEEE"
+1856e71437886af2366b620bcfe4caf891425f7b,Analyzing the Distribution of a Large-Scale Character Pattern Set Using Relative Neighborhood Graph,"Analyzing the Distribution of +Large-scale Character Pattern Set +Using Relative Neighborhood Graph +Masanori Goto(cid:3), Ryosuke Ishiday, Yaokai Fengy and Seiichi Uchiday +(cid:3)GLORY LTD., Hyogo, Japan +Email: +yKyushu University, Fukuoka, Japan +Email:"
+1883387726897d94b663cc4de4df88e5c31df285,Measures of Effective Video Tracking,"Measures of effective video tracking +Tahir Nawaz, Fabio Poiesi, Andrea Cavallaro"
+18a7edd0bfe5a3d6ceb4d2053081e479cfa1e920,Transductive Kernel Map Learning and its Application to Image Annotation,"TRANSDUCTIVE LEARNING, KERNEL MAP, IMAGE ANNOTATION: BMVC SUBMISSION 1 +Transductive Kernel Map Learning +nd its Application to Image Annotation +Dinh-Phong Vo +Hichem Sahbi +LTCI CNRS Telecom ParisTech +6 rue Barrault, 75013, Paris, France"
1886b6d9c303135c5fbdc33e5f401e7fc4da6da4,Knowledge Guided Disambiguation for Large-Scale Scene Classification With Multi-Resolution CNNs,"Knowledge Guided Disambiguation for Large-Scale Scene Classification with Multi-Resolution CNNs Limin Wang, Sheng Guo, Weilin Huang, Member, IEEE, Yuanjun Xiong, and Yu Qiao, Senior Member, IEEE"
1888bf50fd140767352158c0ad5748b501563833,A Guided Tour of Face Processing,"PA R T 1 THE BASICS"
+18babfe4c7230522527a068654eeea10b1a827fd,Discriminative Label Propagation for Multi-object Tracking with Sporadic Appearance Features,"Discriminative Label Propagation for Multi-Object Tracking with Sporadic +Appearance Features +Amit Kumar K.C. and Christophe De Vleeschouwer +ISPGroup, ELEN Department, ICTEAM Institute +Universit´e catholique de Louvain +Louvain-la-Neuve, B-1348, Belgium +{amit.kc,"
+1819d9a9099dafc987dd236c2174945e7922be13,Eigenfeature Regularization and Extraction in Face Recognition,"Eigenfeature Regularization and Extraction +in Face Recognition +Xudong Jiang, Senior Member, IEEE, Bappaditya Mandal, and Alex Kot, Fellow, IEEE"
+183ad3409a53914247affc599b33af38d94937be,A Latent-Variable Lattice Model,"An Inertial Latent-Variable Sequence Model +Rajasekaran Masatran +Indian Institute of Technology Madras, Chennai, TN, India +MASATRAN AT FREESHELL.ORG"
+18f348d56a2ff1c0904685ce8b6818b84867b7a4,ML-o-scope: a diagnostic visualization system for deep machine learning pipelines,"ML-o-scope: a diagnostic visualization system for +deep machine learning pipelines +Daniel Bruckner +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2014-99 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-99.html +May 16, 2014"
+18d7684c6b96caf51adb519738720eceb1b13050,Hidden Relationships: Bayesian Estimation With Partial Knowledge,"Hidden Relationships: +Bayesian Estimation with Partial Knowledge +Tomer Michaeli and Yonina C. Eldar, Senior Member, IEEE +the joint probability function of"
+18a4399b8afb460cbd4de2225f39ed23a95336d6,HMS-Net: Hierarchical Multi-scale Sparsity-invariant Network for Sparse Depth Completion,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +HMS-Net: Hierarchical Multi-scale +Sparsity-invariant Network for Sparse Depth +Completion +Zixuan Huang, Junming Fan, Shuai Yi, Xiaogang Wang, Senior Member, IEEE, +Hongsheng Li, Member, IEEE"
+18727c3f4ada0cec9e5914340cc672d0554d7784,"3-D Face Detection, Landmark Localization, and Registration Using a Point Distribution Model","D face detection, landmark localization and +registration using a Point Distribution Model +Prathap Nair*, Student Member, IEEE, and Andrea Cavallaro, Member, IEEE"
+18001ed8ce46cf9df5574b1e360550ed9401cd76,Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics,"Sentic Blending: +Scalable Multimodal Fusion for the Continuous +Interpretation of Semantics and Sentics +Erik Cambria, Member, IEEE, Newton Howard, Member, IEEE, +Jane Hsu, Member, IEEE, and Amir Hussain, Senior Member, IEEE"
+18aae0f20fdc6aab093c72c81005247d2cbc8512,Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination,"Bayesian CP Factorization of Incomplete +Tensors with Automatic Rank Determination +Qibin Zhao, Member, IEEE, Liqing Zhang, Member, IEEE, and Andrzej Cichocki Fellow, IEEE"
+18233c55982050292ba7f6a5462c0e7576c3398d,Face Recognition using Eye Distance and PCA Approaches,"Face Recognition using Eye Distance and PCA +Approaches +Ripal Patel , Nidhi Rathod , Ami Shah , Mayur Sevak +Electronics & Telecommunication Department, +BVM Engineering College. +Vallabh Vidyanagar-388120, Gujarat, India"
+180cf5ab4e021e64b9bf08f2ffc4a4712acd9a30,Multi-view anchor graph hashing,"MULTI-VIEW ANCHOR GRAPH HASHING +Saehoon Kim1 and Seungjin Choi1,2 +Department of Computer Science and Engineering, POSTECH, Korea +Division of IT Convergence Engineering, POSTECH, Korea +{kshkawa,"
185360fe1d024a3313042805ee201a75eac50131,Person De-Identification in Videos,"Person De-Identification in Videos Prachi Agrawal and P. J. Narayanan"
1824b1ccace464ba275ccc86619feaa89018c0ad,One millisecond face alignment with an ensemble of regression trees,"One Millisecond Face Alignment with an Ensemble of Regression Trees @@ -6106,6 +20944,52 @@ Vahid Kazemi and Josephine Sullivan KTH, Royal Institute of Technology Computer Vision and Active Perception Lab Teknikringen 14, Stockholm, Sweden"
+18858cc936947fc96b5c06bbe3c6c2faa5614540,Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification,"Proceedings of Machine Learning Research 81:1–15, 2018 +Conference on Fairness, Accountability, and Transparency +Gender Shades: Intersectional Accuracy Disparities in +Commercial Gender Classification∗ +Joy Buolamwini +MIT Media Lab 75 Amherst St. Cambridge, MA 02139 +Timnit Gebru +Microsoft Research 641 Avenue of the Americas, New York, NY 10011 +Editors: Sorelle A. Friedler and Christo Wilson"
+2783efc96a0d59473e4236ccf1db6ed7e958839e,An Overview of Multi-Task Learning in Deep Neural Networks,"An Overview of Multi-Task Learning +in Deep Neural Networks∗ +Sebastian Ruder +Insight Centre for Data Analytics, NUI Galway +Aylien Ltd., Dublin"
+27e97b67a8401def58eb41b4b00d3dfb0e4ad1a8,Knowledge Based Face Detection Using Fusion Features,"International Journal of Computer Engineering and Applications, ICCSTAR-2016, Special Issue, +May.16 +Knowledge Based Face Detection Using Fusion Features. +Savitri Kulkarni +Assistant Professor,Department of CSE +City Engineering College, +2Annapurna N S +UG Student (B.E) Department of CSE +City Engineering College,"
+2704959c75a2e6741867ae18f11fa822fa544c74,Hierarchical Convex NMF for Clustering Massive Data,"JMLR: Workshop and Conference Proceedings 13: 253-268 +nd Asian Conference on Machine Learning (ACML2010), Tokyo, Japan, Nov. 8–10, 2010. +Hierarchical Convex NMF for Clustering Massive Data +Kristian Kersting +Mirwaes Wahabzada +Knowledge Discovery Department +Fraunhofer IAIS, Schloss Birlinghoven +53754 Sankt Augustin, Germany +Christian Thurau +Christian Bauckhage +Vision and Social Media Group +Fraunhofer IAIS, Schloss Birlinghoven +53754 Sankt Augustin, Germany +Editor: Masashi Sugiyama and Qiang Yang"
+275ad26b7e4d7847f7ad4eedda65f327007a9452,Query-by-Example Image Retrieval using Visual Dependency Representations,"Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, +pages 109–120, Dublin, Ireland, August 23-29 2014."
+27fda2c61f3fe1f74e18bd11555df7751d178bca,Real-time 3D head pose and facial landmark estimation from depth images using triangular surface patch features,"Real-time 3D Head Pose and Facial Landmark Estimation from Depth Images +Using Triangular Surface Patch Features +Chavdar Papazov +Tim K. Marks +Michael Jones +Mitsubishi Electric Research Laboratories (MERL) +01 Broadway, Cambridge, MA 02139"
27a0a7837f9114143717fc63294a6500565294c2,Face Recognition in Unconstrained Environments: A Comparative Study,"Face Recognition in Unconstrained Environments: A Comparative Study Rodrigo Verschae, Javier Ruiz-Del-Solar, Mauricio Correa @@ -6126,6 +21010,32 @@ L’archive ouverte pluridisciplinaire HAL, est destin´ee au d´epˆot et `a la diffusion de documents scientifiques de niveau recherche, publi´es ou non, ´emanant des ´etablissements d’enseignement et de"
+27421586a04584d38dd961b37d0ca85408acfe59,Large brains in autism: the challenge of pervasive abnormality.,"Large Brains in Autism: +The Challenge of Pervasive Abnormality +MARTHA R. HERBERT +Pediatric Neurology, Center for Morphometric Analysis +Massachusetts General Hospital +REVIEW I +The most replicated finding in autism neuroanatomy—a tendency to unusually large brains—has seemed +paradoxical in relation to the specificity of the abnormalities in three behavioral domains that define autism. +We now know a range of things about this phenomenon, including that brains in autism have a growth spurt +shortly after birth and then slow in growth a few short years afterward, that only younger but not older +rains are larger in autism than in controls, that white matter contributes disproportionately to this volume +increase and in a nonuniform pattern suggesting postnatal pathology, that functional connectivity among +regions of autistic brains is diminished, and that neuroinflammation (including microgliosis and astrogliosis) +ppears to be present in autistic brain tissue from childhood through adulthood. Alongside these pervasive +rain tissue and functional abnormalities, there have arisen theories of pervasive or widespread neural +information processing or signal coordination abnormalities (such as weak central coherence, impaired +omplex processing, and underconnectivity), which are argued to underlie the specific observable behav- +ioral features of autism. This convergence of findings and models suggests that a systems- and chronic +disease–based reformulation of function and pathophysiology in autism needs to be considered, and +it opens the possibility for new treatment targets. NEUROSCIENTIST 11(5):417–440; 2005. DOI:"
+2792e5d569b94406ca28f86c9999f569a3d60c6d,Illumination Multiplexing within Fundamental Limits,"Illumination Multiplexing within Fundamental Limits +Netanel Ratner +Yoav Y. Schechner +Department of Electrical Engineering +Technion - Israel Institute of Technology +Haifa 32000, ISRAEL"
276dbb667a66c23545534caa80be483222db7769,An Introduction to Image-based 3D Surface Reconstruction and a Survey of Photometric Stereo Methods,"D Res. 2, 03(2011)4 0.1007/3DRes.03(2011)4 DR REVIEW w @@ -6157,6 +21067,26 @@ in Web of Science™ Core Collection (BKCI) Interested in publishing with us? Contact Numbers displayed above are based on latest data collected."
+27a4bbd7bc90ad118f15c61bb30079d6e6bff78e,3D Deformable Super-Resolution for Multi-Camera 3D Face Scanning,"J Math Imaging Vis +DOI 10.1007/s10851-012-0399-y +D Deformable Super-Resolution for Multi-Camera 3D Face +Scanning +Karima Ouji · Mohsen Ardabilian · Liming Chen · +Faouzi Ghorbel +© Springer Science+Business Media New York 2012"
+277096c5e536784da9856ac083a972715ce9f9c3,Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction,"Article +Gender Recognition from Human-Body Images +Using Visible-Light and Thermal Camera Videos +Based on a Convolutional Neural Network for +Image Feature Extraction +Dat Tien Nguyen, Ki Wan Kim, Hyung Gil Hong, Ja Hyung Koo, Min Cheol Kim and +Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (D.T.N.); (K.W.K.); +(H.G.H.); (J.H.K.); (M.C.K.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Academic Editor: Joonki Paik +Received: 31 January 2017; Accepted: 18 March 2017; Published: 20 March 2017"
27169761aeab311a428a9dd964c7e34950a62a6b,Face Recognition Using 3D Head Scan Data Based on Procrustes Distance,"International Journal of the Physical Sciences Vol. 5(13), pp. 2020 -2029, 18 October, 2010 Available online at http://www.academicjournals.org/IJPS ISSN 1992 - 1950 ©2010 Academic Journals @@ -6177,6 +21107,25 @@ translation and rotation invariant signature. The shape signatures for (ROI) are used as feature vectors and authentication is done using them. After extracting feature vectors a comparison analysis is performed utilizing Procrustes distance to differentiate their face pattern from each other. The proposed scheme attains an equal error rate (EER) of 4.563% for the 400"
+272ac22c670fd0c7c3f1b4ca02e925ff22dd4b27,Articulated part-based model for joint object detection and pose estimation,"Articulated Part-based Model for Joint Object Detection and Pose Estimation +Dept. of Electrical and Computer Engineering, University of Michigan at Ann Arbor, USA +Min Sun +Silvio Savarese +COARSE +LEVEL"
+27ae7c8c650ffef74c465640f423d9008014e1ca,Dimensionality Reduction with Adaptive Approximation,"TobepublishedintheProceedingsofIEEEICME2007,Beijing,China +DIMENSIONALITY REDUCTION WITH ADAPTIVE APPROXIMATION +Effrosyni Kokiopoulou and Pascal Frossard +Ecole Polytechnique F´ed´erale de Lausanne (EPFL) +Signal Processing Institute - ITS +CH- 1015 Lausanne, Switzerland"
+27b87bdee46964757b83b5afb4184e438cad6b1b,Sequence searching with deep-learnt depth for condition- and viewpoint-invariant route-based place recognition,"Sequence Searching with Deep-learnt Depth for Condition- and Viewpoint- +invariant Route-based Place Recognition +Michael Milford, Stephanie Lowry, Niko +Sunderhauf, Sareh Shirazi, Edward Pepperell, +Ben Upcroft +Queensland University of Technology Australia +Australian Centre for Robotic Vision"
27173d0b9bb5ce3a75d05e4dbd8f063375f24bb5,Effect of Different Occlusion on Facial Expressions Recognition,"Ankita Vyas Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 10( Part - 3), October 2014, pp.40-44 RESEARCH ARTICLE @@ -6185,6 +21134,26 @@ Effect of Different Occlusion on Facial Expressions Recognition Ankita Vyas*, Ramchand Hablani** *(Department of Computer Science, RGPV University, Indore) ** (Department of Computer Science, RGPV University, Indore)"
+27f1fd71538ba420c63aa4c74704718a0633b22a,Multimodal News Article Analysis,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+2785c5769489825671a6138fdf0537fcd444038a,A Deep Cascade Network for Unaligned Face Attribute Classification,"A Deep Cascade Network for Unaligned Face Attribute Classification +Hui Ding,1 Hao Zhou,2 Shaohua Kevin Zhou,3 Rama Chellappa4 +,2,4University of Maryland, College Park +Siemens Healthineers, New Jersey"
+27187d4c36f71d08898a53dfda0e81df11b25f21,Worst Case Linear Discriminant Analysis as Scalable Semidefinite Feasibility Problems,"MANUSCRIPT +Worst-Case Linear Discriminant Analysis as +Scalable Semidefinite Feasibility Problems +Hui Li, Chunhua Shen, Anton van den Hengel, Qinfeng Shi"
+2725a68be6bc677bd435c19664569ecd45c52d7a,DeepProposal: Hunting Objects by Cascading Deep Convolutional Layers,"DeepProposal: Hunting Objects by Cascading Deep Convolutional Layers +Amir Ghodrati1∗, Ali Diba1∗, Marco Pedersoli2†‡, Tinne Tuytelaars1, Luc Van Gool1,3 +KU Leuven, ESAT-PSI, iMinds +Inria +CVL, ETH Zurich"
+273b973092a4491974d173cc5258c74aede692cc,Monocular Long-Term Target Following on UAVs,"Monocular Long-term Target Following on UAVs +Rui Li ∗ +Minjian Pang† +Cong Zhao ‡ +Guyue Zhou ‡ +Lu Fang †§"
2770b095613d4395045942dc60e6c560e882f887,GridFace: Face Rectification via Learning Local Homography Transformations,"GridFace: Face Rectification via Learning Local Homography Transformations Erjin Zhou, Zhimin Cao, and Jian Sun @@ -6206,6 +21175,13 @@ IshanBhardwaj Student of Ph.D. Electrical Department NIT Raipur, Chhattisgarh India"
+27f9b43737e234cefb3c5cd72324a36cbe61ee3c,Sparse Manifold Clustering and Embedding,"Sparse Manifold Clustering and Embedding +Ehsan Elhamifar +Center for Imaging Science +Johns Hopkins University +Ren´e Vidal +Center for Imaging Science +Johns Hopkins University"
27f8b01e628f20ebfcb58d14ea40573d351bbaad,Events based Multimedia Indexing and Retrieval,"DEPARTMENT OF INFORMATION ENGINEERING AND COMPUTER SCIENCE ICT International Doctoral School Events based Multimedia Indexing @@ -6221,6 +21197,49 @@ Prof. Nicola Conci, Universit`a degli Studi di Trento, Italy Prof. Pietro Zanuttigh, Universit`a degli Studi di Padova, Italy Prof. Giulia Boato, Universit`a degli Studi di Trento, Italy December 2017"
+27c978bdb9de3a5135349976fdbc514ff547dcab,Multi-Objective Stochastic Optimization by Co-Direct Sequential Simulation for History Matching of Oil Reservoirs,"Multi-Objective Stochastic Optimization by Co-Direct Sequential +Simulation for History Matching of Oil Reservoirs +Jo˜ao Daniel Trigo Pereira Carneiro∗ +under the supervision of Am´ılcar de Oliveira Soares† +Dep. Mines, IST, Lisbon, Portugal +December 2010"
+2799d53ca80d67f104bef207a667fa12b4c59d62,Multiple-Person Tracking for a Mobile Robot Using Stereo,"MVA2009 IAPR Conference on Machine Vision Applications, May 20-22, 2009, Yokohama, JAPAN +Multiple-Person Tracking for a Mobile Robot using Stereo +Junji Satake +Jun Miura +Toyohashi University of Technology +-1 Hibarigaoka, Tempaku-cho, Toyohashi, Aichi 441-8580, Japan +{satake,"
+27ae95d9ad6492511296360ba0618f5d0565cf9e,Person re-Identification over distributed spaces and time,"Person re-Identification over distributed spaces and time +Prosser, Bryan James +For additional information about this publication click this link. +http://qmro.qmul.ac.uk/jspui/handle/123456789/2513 +Information about this research object was correct at the time of download; we occasionally +make corrections to records, please therefore check the published record when citing. For +more information contact"
+276d35fef150f61adf53270eb6e50625022d4e7f,The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research,"A Robotic Shelf Picking Benchmark to Foster Reproducible Research +The ACRV Picking Benchmark: +J¨urgen Leitner1,2, Adam W. Tow1,2, Niko S¨underhauf1,2, Jake E. Dean2, Joseph W. Durham3, Matthew +Cooper2, Markus Eich1,2, Christopher Lehnert2, Ruben Mangels2, Christopher McCool2, Peter T. Kujala1,2, +Lachlan Nicholson2, Trung Pham1,4, James Sergeant1,2, Fangyi Zhang1,2, Ben Upcroft1,2, and Peter Corke1,2."
+27183d23f50884a0e06b978acf9ad77dbcbfb112,Autonomous indoor helicopter flight using a single onboard camera,"The 2009 IEEE/RSJ International Conference on +Intelligent Robots and Systems +October 11-15, 2009 St. Louis, USA +978-1-4244-3804-4/09/$25.00 ©2009 IEEE"
+2757ff9bba677e7bceaa4802d85cc6f872618583,From basis components to complex structural patterns,"FROM BASIS COMPONENTS TO COMPLEX STRUCTURAL PATTERNS +Anh Huy Phan‡, Andrzej Cichocki‡∗, Petr Tichavsk´y•†, Rafal Zdunek§ and Sidney Lehky‡⋆ +Brain Science Institute, RIKEN, Wakoshi, Japan +•Institute of Information Theory and Automation, Prague, Czech Republic +§Wroclaw University of Technology, Poland +⋆Computational Neurobiology Lab, The Salk Institute, USA"
+27448716366bed56515c1b32579daf224165861e,Deep Multi-camera People Detection,"Deep Multi-Camera People Detection +Tatjana Chavdarova and Franc¸ois Fleuret +Idiap Research Institute and +´Ecole Polytechnique F´ed´erale de Lausanne +Email:"
+277cadfadc4550fc781be7df8cb4ec89e54b793e,Autonomous Real-time Vehicle Detection from a Medium-Level UAV,"Autonomous Real-time Vehicle Detection from a +Medium-Level UAV +Toby P. Breckon, Stuart E. Barnes, Marcin L. Eichner and Ken Wahren"
27b1670e1b91ab983b7b1ecfe9eb5e6ba951e0ba,Comparison between k-nn and svm method for speech emotion recognition,"Comparison between k-nn and svm method for speech emotion recognition Muzaffar Khan, Tirupati Goskula, Mohmmed Nasiruddin ,Ruhina Quazi @@ -6231,6 +21250,14 @@ Email: {denis.giri, maxime.rosenwald, benjamin.villeneuve, sylvain.legallou, Avenue de la boulaie, BP 81127, 5 511 Cesson-S´evign´e, France Sup´elec, IETR-SCEE Team"
+2734b3a6345396499b2b7c6cc1b43fc7e9b375ee,Full-System Simulation of big.LITTLE Multicore Architecture for Performance and Energy Exploration,"Full-System Simulation of big.LITTLE Multicore +Architecture for Performance and Energy +Exploration +Anastasiia Butko, Florent Bruguier, Abdoulaye Gamati´e, +Gilles Sassatelli, David Novo, Lionel Torres and Michel Robert +LIRMM (CNRS and University of Montpellier) +Montpellier, France +Email:"
4b4106614c1d553365bad75d7866bff0de6056ed,Unconstrained Facial Images: Database for Face Recognition Under Real-World Conditions,"Unconstrained Facial Images: Database for Face Recognition under Real-world Conditions⋆ Ladislav Lenc1,2 and Pavel Kr´al1,2 @@ -6240,10 +21267,103 @@ Plzeˇn, Czech Republic NTIS - New Technologies for the Information Society University of West Bohemia Plzeˇn, Czech Republic"
+4b90f2e4f421dd9198d4c52cd3371643acddf1f9,Detecting planar surface using a light-field camera with application to distinguishing real scenes from printed photos,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) +978-1-4799-2893-4/14/$31.00 ©2014 IEEE +´Ecole Polytechnique F´ed´erale de Lausanne +School of Computer and Communication Sciences +AudioVisual Communications Laboratory +. INTRODUCTION +Alireza Ghasemi +Martin Vetterli"
+4b57456642e1d21f2bda05aea586b7f419d309ce,Disposable Ties and the Urban Poor,"Disposable Ties and the Urban Poor +Author(s): Matthew Desmond +Reviewed work(s): +Source: American Journal of Sociology, Vol. 117, No. 5 (March 2012), pp. 1295-1335 +Published by: The University of Chicago Press +Stable URL: http://www.jstor.org/stable/10.1086/663574 . +Accessed: 17/08/2012 17:34 +Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . +http://www.jstor.org/page/info/about/policies/terms.jsp +JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of +ontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms +of scholarship. For more information about JSTOR, please contact +The University of Chicago Press is collaborating with JSTOR to digitize, preserve and extend access to +American Journal of Sociology. +http://www.jstor.org"
+4bb83b00e7b8eb27ad04d4bb80499e91fc471a07,Emotion related structures in large image databases,"Emotion Related Structures in Large Image Databases +Martin Solli +ITN, Linköping University +SE-60174 Norrköping, Sweden +Reiner Lenz +ITN, Linköping University +SE-60174 Norrköping, Sweden"
+4b37efd3987c1e625b063a6998bd6b282c844915,End-to-end Convolutional Network for Saliency Prediction,"End-to-end Convolutional Network for Saliency Prediction +Junting Pan and Xavier Gir´o-i-Nieto +Universitat Politecnica de Catalunya (UPC) +Barcelona, Catalonia/Spain"
4b89cf7197922ee9418ae93896586c990e0d2867,Unsupervised Discovery of Action Classes,"LATEX Author Guidelines for CVPR Proceedings First Author Institution1 Institution1 address"
+4b69bbb6dc2959ea3d2e911ed45c6298dc531490,Deep Mixture of Experts via Shallow Embedding,"TAFE-Net: Task-Aware Feature Embeddings for +Efficient Learning and Inference +Xin Wang Fisher Yu Ruth Wang Trevor Darrell +EECS Department, UC Berkeley +Joseph E. Gonzalez"
+4b042eb64ddb8991c0e63fff02b1c51c378a8f58,Leveraging Massive User Contributions for Knowledge Extraction,"Chapter 16 +Leveraging Massive User Contributions for +Knowledge Extraction +Spiros Nikolopoulos, Elisavet Chatzilari, Eirini Giannakidou, +Symeon Papadopoulos, Ioannis Kompatsiaris, and Athena Vakali"
+4b5dd0a1b866f928734bc36afd597adca20a7ec1,Detector ensembles for face recognition in video surveillance,"Detector Ensembles for Face Recognition in Video Surveillance +Christophe Pagano, Eric Granger, Robert Sabourin and Dmitry O. Gorodnichy"
+4b6eb9117c1b7833c8c6b95ecad427f8f994f023,Robust Depth-Based Person Re-Identification,"Robust Depth-based Person Re-identification +Ancong Wu, Wei-Shi Zheng, Jian-Huang Lai +Code is available at the project page: +http://isee.sysu.edu.cn/∼wuancong/ProjectDepthReID.htm +For reference of this work, please cite: +Ancong Wu, Wei-Shi Zheng, +Person Re-identification. +(DOI:10.1109/TIP.2017.2675201) +Jian-Huang Lai. Robust Depth-based +title={Robust Depth-based Person Re-identification}, +uthor={Wu, Ancong and Zheng, Wei-Shi and Lai, Jianhuang}, +(DOI:10.1109/TIP.2017.2675201)}, +year={2017}"
+4b8762d7637868b6ba0c97c95b2d4949d103ecdc,The OU-ISIR Gait Database Comprising the Large Population Dataset and Performance Evaluation of Gait Recognition,"The OU-ISIR Gait Database Comprising the Large +Population Dataset and Performance Evaluation of +Gait Recognition +Haruyuki Iwama, Mayu Okumura, Yasushi Makihara, and Yasushi Yagi, Member, IEEE +the world’s"
+4ba1cf65eb86aba729192d2f0fe2cd064ac346cf,One-Shot Person Re-identification with a Consumer Depth Camera,"One-Shot Person Re-Identification with a +Consumer Depth Camera +Matteo Munaro, Andrea Fossati, Alberto Basso, Emanuele Menegatti and Luc Van"
+4b1fc77a54e9daece9f11ec881a2ec40919337b7,Fusion of LBP and HOG using multiple kernel learning for infrared face recognition,"Fusion of LBP and HOG Using Multiple Kernel +Learning for Infrared Face Recognition +Zhihua Xie, Peng Jiang, Shuai Zhang +Key Lab of Optic-Electronic and Communication +Jiangxi Sciences and Technology Normal University +Nanchang, Jiangxi Province, China +limitation +(LBP) has"
+4b6ea82fa73d2137c884ad43f7865d88b24ff01d,How deep should be the depth of convolutional neural networks: a backyard dog case study,"How deep should be the depth of convolutional neural +networks: a backyard dog case study +Alexander N. Gorban, Evgeny M. Mirkes, Ivan Y. Tukin +University of Leicester, Leicester LE1 7RH, UK"
+4b7dc1e99b0b34022aec2bde1a13481f28f62030,Person Re-Identification Based on Weighted Indexing Structures,"Person Re-Identification based on Weighted +Indexing Structures +Cristianne R. S. Dutra, Matheus Castro Rocha, and William Robson Schwartz +Department of Computer Science, Universidade Federal de Minas Gerais +Belo Horizonte, Minas Gerais, Brazil, 31270-901 +rocha"
+4b9b39bbdac95e24773789f1bb543149116cdc37,Region-Of-Interest Retrieval in Brain MR Images,"Technical Note PR-TN 2008/00905 +Issued: 12/2008 +Region-Of-Interest Retrieval in Brain MR +Images +D. Unay; A. Ekin +Philips Research Europe +Unclassified + Koninklijke Philips Electronics N.V. 2008"
4b04247c7f22410681b6aab053d9655cf7f3f888,Robust Face Recognition by Constrained Part-based Alignment,"Robust Face Recognition by Constrained Part-based Alignment Yuting Zhang, Kui Jia, Yueming Wang, Gang Pan, Tsung-Han Chan, Yi Ma"
@@ -6252,6 +21372,8 @@ Yuyin Sun, Liefeng Bo and Dieter Fox" 4b48e912a17c79ac95d6a60afed8238c9ab9e553,Minimum Margin Loss for Deep Face Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 Minimum Margin Loss for Deep Face Recognition Xin Wei, Student Member, IEEE, Hui Wang, Member, IEEE, Bryan Scotney, and Huan Wan"
+4b0893bf71e4e13529cefb286c78b166a9491552,Estimating orientation in tracking individuals of flying swarms,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE +ICASSP 2016"
4b5eeea5dd8bd69331bd4bd4c66098b125888dea,Human Activity Recognition Using Conditional Random Fields and Privileged Information,"Human Activity Recognition Using Conditional Random Fields and Privileged Information DOCTORAL THESIS @@ -6263,19 +21385,167 @@ Michalis Vrigkas in partial fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY February 2016"
+4bde15a51413fafa04193e72c15e132e7716d8a6,Performance Study of Fusion in Multimodal Biometric Verification using Ear and Iris Features,"International Conference on Research Trends in Computer Technologies (ICRTCT - 2013) +Proceedings published in International Journal of Computer Applications® (IJCA) (0975 – 8887) +Performance Study of Fusion in Multimodal Biometric +Verification using Ear and Iris Features +Poornima.S +Department of IT, SSN College of Engineering +Chennai, India."
+4b4763303a15a4c6313bfb386756437f394a0129,Explicit Inductive Bias for Transfer Learning with Convolutional Networks,"Explicit Inductive Bias for Transfer Learning with Convolutional Networks +Xuhong LI 1 Yves GRANDVALET 1 Franck DAVOINE 1"
+4b8ce1bfedb285d8d609d1059dd0183420d63671,Transductive Multi-View Zero-Shot Learning,"Transductive Multi-view Zero-Shot Learning +Yanwei Fu, Timothy M. Hospedales, Tao Xiang and Shaogang Gong"
4be03fd3a76b07125cd39777a6875ee59d9889bd,Content-based analysis for accessing audiovisual archives: Alternatives for concept-based indexing and search,"CONTENT-BASED ANALYSIS FOR ACCESSING AUDIOVISUAL ARCHIVES: ALTERNATIVES FOR CONCEPT-BASED INDEXING AND SEARCH Tinne Tuytelaars ESAT/PSI - IBBT KU Leuven, Belgium"
+4baf3b165489122a1f8b574240c2a7fa9b6a7a14,Composite Statistical Inference for Semantic Segmentation,"Composite Statistical Inference for Semantic Segmentation +Fuxin Li(1), Joao Carreira(2), Guy Lebanon(1), Cristian Sminchisescu(3) +(1) Georgia Institute of Technology. (2) ISR - University of Coimbra. (3) Lund University"
+4bc67489bbe634271f8fde73a851d7a59946ed36,Wide area motion capture using an array of consumer grade structured light depthsensors,"Mälardalen University +School of Innovation, Design and Engineering +Bachelor thesis in Computer science +Wide area motion capture using an array of +onsumer grade structured light depth +sensors +Author: +Karl Arvidsson +Supervisor: +Afshin Ameri +Examiner: +Baran Çürüklü +October 20, 2015"
+4be63e7891180e28085d03bb992abbc5104ac446,Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers,"Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers +Jiaolong Xu1, David V´azquez1, Sebastian Ramos1, Antonio M. L´opez1,2 and Daniel Ponsa1,2 +Computer Vision Center +Dept. of Computer Science +Autonomous University of Barcelona +08193 Bellaterra, Barcelona, Spain +{jiaolong, dvazquez, sramosp, antonio,"
+4b7d5b17c0daa35f682417c32e80022c6645dc7f,Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery,"Fine-Grained Object Recognition and Zero-Shot +Learning in Remote Sensing Imagery +Gencer Sumbul, Ramazan Gokberk Cinbis, and Selim Aksoy, Senior Member, IEEE +learning (ZSL)"
+4bfdbe2ffc6311c8a297355422d914cb666b358a,"On Boosting, Tug of War, and Lexicographic Programming","On Boosting, Tug of War, and Lexicographic +Programming +Shounak Datta, Sayak Nag, and Swagatam Das, Senior Member, IEEE"
+4bfe7037b2d92215aeb5e116988ade7e6733a6b9,Frontal contributions to face processing differences in autism: evidence from fMRI of inverted face processing.,"Journal of the International Neuropsychological Society (2008), 14, 922–932. +Copyright © 2008 INS. Published by Cambridge University Press. Printed in the USA. +doi:10.10170S135561770808140X +SYMPOSIUM +Frontal contributions to face processing differences +in autism: Evidence from fMRI of inverted +face processing +SUSAN Y. BOOKHEIMER,1,2 A. TING WANG,3 ASHLEY SCOTT,1 MARIAN SIGMAN,1,2 +nd MIRELLA DAPRETTO 1 +Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, +Los Angeles, California +Department of Psychology, University of California Los Angeles, Los Angeles, California +Department of Psychiatry, Mount Sinai School of Medicine, New York, New York +(Received January 8, 2008; Final Revision August 9, 2008; Accepted August 11, 2008)"
+4b0111182ace7443f060a64754ca23b2fc7e1d77,Face Recognition by Super-Resolved 3D Models From Consumer Depth Cameras,"Face Recognition by Super-Resolved 3D Models +From Consumer Depth Cameras +Stefano Berretti, Pietro Pala, Senior Member, IEEE, and Alberto del Bimbo, Member, IEEE +the impact of"
+11943efec248fcac57ff6913424e230d0a02e977,Auxiliary Tasks in Multi-task Learning,"Auxiliary Tasks in Multi-task Learning +Lukas Liebel +Marco Körner +Computer Vision Research Group, Chair of Remote Sensing Technology +Technical University of Munich, Germany +{lukas.liebel, +Multi-task convolutional neural networks (CNNs) have shown impressive results for certain combinations of tasks, such +s single-image depth estimation (SIDE) and semantic segmentation. This is achieved by pushing the network towards +learning a robust representation that generalizes well to different atomic tasks. We extend this concept by adding +uxiliary tasks, which are of minor relevance for the application, to the set of learned tasks. As a kind of additional +regularization, they are expected to boost the performance of the ultimately desired main tasks. To study the proposed +pproach, we picked vision-based road scene understanding (RSU) as an exemplary application. Since multi-task +learning requires specialized datasets, particularly when using extensive sets of tasks, we provide a multi-modal dataset +for multi-task RSU, called synMT. More than 2.5 · 105 synthetic images, annotated with 21 different labels, were +cquired from the video game Grand Theft Auto V (GTA V). Our proposed deep multi-task CNN architecture was +trained on various combination of tasks using synMT. The experiments confirmed that auxiliary tasks can indeed boost +network performance, both in terms of final results and training time. +Introduction +Various applications require solving several atomic tasks from +the computer vision domain using a single image as input. Such"
+1178beb48d666d7fc41b2d476f6a92450c0726c0,Challenges in Multi-modal Gesture Recognition,"Journal of Machine Learning Research 17 (2016) 1-54 +Submitted 11/14; Revised 1/16; Published 4/16 +Challenges in multimodal gesture recognition +Sergio Escalera +Computer Vision Center UAB and University of Barcelona +Vassilis Athitsos +University of Texas +Isabelle Guyon +ChaLearn, Berkeley, California +Editors: Zhuowen Tu"
+1152b88194214d4ea0f85b727f4b120915ad8056,Exploiting feature dynamics for active object recognition,"Exploiting Feature Dynamics for Active +Object Recognition +Philipp Robbel and Deb Roy +MIT Media Laboratory +Cambridge, MA 02139, USA"
11f7f939b6fcce51bdd8f3e5ecbcf5b59a0108f5,Rolling Riemannian Manifolds to Solve the Multi-class Classification Problem,"Rolling Riemannian Manifolds to Solve the Multi-class Classification Problem Rui Caseiro1, Pedro Martins1, João F. Henriques1, Fátima Silva Leite1,2, and Jorge Batista1 Institute of Systems and Robotics - University of Coimbra, Portugal Department of Mathematics - University of Coimbra, Portugal , {ruicaseiro, pedromartins, henriques,"
+111ff5420111751454a2f4f55b7bb75d837ed5f4,Automatic Annotation of Structured Facts in Images,"Proceedings of the 5th Workshop on Vision and Language, pages 1–9, +Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
+11b00a4be68e9622d7b4698aca84da85aca3e288,Modeling Social Interactions in Real Work Environments,"Modeling Social Interactions in Real Work Environments +Salvatore Vanini +SUPSI-DTI +via Cantonale +6928 Manno, Switzerland +Silvia Giordano +SUPSI-DTI +via Cantonale +6928 Manno, Switzerland +Dario Gallucci +SUPSI-DTI +via Cantonale +6928 Manno, Switzerland +Kamini Garg +SUPSI-DTI +via Cantonale +6928 Manno, Switzerland +Victoria Mirata +FFHS-IFeL +Überlandstrasse 12"
+115724ce1ce9422dad095b301c7d096498ad50d3,The E2E Dataset: New Challenges For End-to-End Generation,"Saarbr¨ucken, Germany, 15-17 August 2017. c(cid:13)2017 Association for Computational Linguistics +Proceedings of the SIGDIAL 2017 Conference, pages 201–206,"
+11f73583ba373487967225ae4797d723ff367c1c,"End-to-end, sequence-to-sequence probabilistic visual odometry through deep neural networks","Article +End-to-end, sequence-to-sequence +probabilistic visual odometry through +deep neural networks +The International Journal of +Robotics Research +© The Author(s) 2017 +Reprints and permissions: +sagepub.co.uk/journalsPermissions.nav +DOI: 10.1177/0278364917734298 +journals.sagepub.com/home/ijr +Sen Wang1,2, Ronald Clark3, Hongkai Wen4 and Niki Trigoni2"
11691f1e7c9dbcbd6dfd256ba7ac710581552baa,SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos,"SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos Silvio Giancola, Mohieddine Amine, Tarek Dghaily, Bernard Ghanem King Abdullah University of Science and Technology (KAUST), Saudi Arabia"
+11bfc54a64ca69786323551bbf88b85b216ae486,Exploring the Facial Expression Perception-Production Link Using Real-Time Automated Facial Expression Recognition,"Exploring the Facial Expression +Perception-Production Link Using Real-Time +Automated Facial Expression Recognition +David M. Deriso1, Josh Susskind1, Jim Tanaka2, Piotr Winkielman3, +John Herrington4, Robert Schultz4, and Marian Bartlett1 +Machine Perception Laboratory, University of California, San Diego +Department of Psychology, University of Victoria +Department of Psychology, University of California, San Diego +Center for Autism Research, Children’s Hospital of Philadelphia"
+11155ee686bfb675816a2acdf5a8ddf06e67b65f,EmoDetect – Smart Emotion Detection from Facial Expressions,"EmoDetect – Smart Emotion Detection from Facial Expressions +Rishabh Animesh +Skand Hurkat +Abhinandan Majumdar +Aayush Saxena +ra523 +sh953 +m2352 +s2825"
1149c6ac37ae2310fe6be1feb6e7e18336552d95,"Classification of Face Images for Gender, Age, Facial Expression, and Identity","Proc. Int. Conf. on Artificial Neural Networks (ICANN’05), Warsaw, LNCS 3696, vol. I, pp. 569-574, Springer Verlag 2005 Classification of Face Images for Gender, Age, Facial Expression, and Identity1 @@ -6286,12 +21556,56 @@ Ilmenau Technical University, P.O.Box 100565, 98684 Ilmenau, Germany" Human Actions by Multiple Spatio-Temporal Scales Recurrent Neural Networks Haanvid Lee, Minju Jung, and Jun Tani"
+11467733103a3e58ae88cb238f620cf6cafd4420,Learning of Graphical Models and Efficient Inference for Object Class Recognition,"Learning of Graphical Models and Efficient +Inference for Object Class Recognition +Martin Bergtholdt, J¨org Kappes, and Christoph Schn¨orr +Computer Vision, Graphics, and Pattern Recognition Group +Department of Mathematics and Computer Science +University of Mannheim, 68131 Mannheim, Germany"
+11a34bda2daecad5f7c1caa309897cc9cc334480,Person re-identification using view-dependent score-level fusion of gait and color features,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-1-6 ©2012 IAPR"
+1172ce24f6e9242b9c26c84c6aa89a72ed8203d0,Find your own way: Weakly-supervised segmentation of path proposals for urban autonomy,"Find Your Own Way: Weakly-Supervised Segmentation of Path +Proposals for Urban Autonomy +Dan Barnes, Will Maddern and Ingmar Posner"
+11be33019f591214c8f79dbcb24a50d8f7fa5c95,Salgan 360 : Visual Saliency Prediction on 360 Degree Images with Generative Adversarial Networks,"SALGAN360: VISUAL SALIENCY PREDICTION ON 360 DEGREE IMAGES WITH +GENERATIVE ADVERSARIAL NETWORKS +Fang-Yi Chao, Lu Zhang, Wassim Hamidouche, Olivier Deforges +Univ Rennes, INSA Rennes, CNRS, IETR - UMR 6164, F-35000 Rennes, France +{fang-yi.chao, lu.ge, wassim.hamidouche,"
+1169f3386a49daccbe199cccb518238a0130a537,"Analyzing Complex Events and Human Actions in ""in-the-wild"" Videos",
+1151a81118368e7596843b8db2508e4974fd7435,A Testbed for Cross-Dataset Analysis,"A Testbed for Cross-Dataset Analysis +Tatiana Tommasi and Tinne Tuytelaars +ESAT-PSI/VISICS - iMinds, KU Leuven, Belgium"
+1119b4b038fd7d1d337d4aee232dea6c56f20cf1,A Sparse Embedding and Least Variance Encoding Approach to Hashing,"A Sparse Embedding and Least Variance Encoding +Approach to Hashing +Xiaofeng Zhu, Lei Zhang, Member, IEEE, Zi Huang"
+116261c74ad54646f7d1d6be38cb9930f1bf44f6,3D Twins and Expression Challenge,"D Twins and +Expression Challenge +Vipin Vijayan, Kevin W. Bowyer, and Patrick J. Flynn."
1198572784788a6d2c44c149886d4e42858d49e4,Learning Discriminative Features using Encoder-Decoder type Deep Neural Nets,"Learning Discriminative Features using Encoder/Decoder type Deep Neural Nets Vishwajeet Singh1, Killamsetti Ravi Kumar2, K Eswaran3 ALPES, Bolarum, Hyderabad 500010, ALPES, Bolarum, Hyderabad 500010, SNIST, Ghatkesar, Hyderabad 501301,"
+11ed823555aabf7e32df5b09a04111a686f8ebb6,Learning visual dictionaries and decision lists for object recognition,"CONFIDENTIAL. Limited circulation. For review only. +Preprint submitted to 19th International Conference on Pattern Recognition. +Received April 10, 2008."
+1183db5f409e8498d1a0f542703f908275a6dc34,Robust Visual Tracking and Vehicle Classification via Sparse Representation,"Robust Visual Tracking and Vehicle +Classification via Sparse Representation +Xue Mei and Haibin Ling, Member, IEEE"
+111f2f1255fa9e5a82753bf5b3f2f0974e87f86d,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
11fe6d45aa2b33c2ec10d9786a71c15ec4d3dca8,Tied Factor Analysis for Face Recognition across Large Pose Differences,"JUNE 2008 Tied Factor Analysis for Face Recognition cross Large Pose Differences @@ -6303,10 +21617,33 @@ OCCURRENCE MATRIXFEATURES AND K-NN CLASSIFIER Bonagiri C S K Sunil Kumar1, V Bala Shankar2, Pullela S V V S R Kumar3 ,2,3 Department of Computer Science & Engineering, Aditya College of Engineering, Surampalem, East Godavari District, Andhra Pradesh, India"
+11d9bee72759e23f19117fc8cbb60b487e8ac79e,Benchmark Visual Question Answer Models by using Focus Map,"Benchmark Visual Question Answer Models by using Focus Map +Wenda Qiu +Yueyang Xianzang +Zhekai Zhang +Shanghai Jiaotong University"
+1131088237aacddcc078547b4455e8572c61766b,Object Referring in Videos with Language and Human Gaze,"Object Referring in Videos with Language and Human Gaze +Arun Balajee Vasudevan1, Dengxin Dai1, Luc Van Gool1,2 +ETH Zurich1 +KU Leuven 2"
111a9645ad0108ad472b2f3b243ed3d942e7ff16,Facial Expression Classification Using Combined Neural Networks,"Facial Expression Classification Using Combined Neural Networks Rafael V. Santos, Marley M.B.R. Vellasco, Raul Q. Feitosa, Ricardo Tanscheit DEE/PUC-Rio, Marquês de São Vicente 225, Rio de Janeiro – RJ - Brazil"
+11d04269aa147450f37215beb3ae44207daf3511,Using Visual Context and Region Semantics for High-Level Concept Detection,"Using Visual Context and Region Semantics for +High-Level Concept Detection +Phivos Mylonas, Member, IEEE, Evaggelos Spyrou, Student Member, IEEE, Yannis Avrithis, Member, IEEE, and +Stefanos Kollias, Member, IEEE"
+11a7c4aadb47753c8d30cbda4ab347c361e4c66a,How to collect high quality segmentations: use human or computer drawn object boundaries?,"Boston University Computer Science Technical Report No. BUCS-TR-2013-20 +How to Collect High Quality Segmentations: Use Human or Computer Drawn +Object Boundaries? +Danna Gurari, Zheng Wu, Brett Isenberg, Chentian Zhang, Alberto Purwada, Joyce Y. Wong, Margrit Betke"
+11f732fe8f127c393cc8404ee8db2b3e85dd3d59,Disentangling Latent Factors with Whitening,"DISENTANGLING LATENT FACTORS WITH WHITENING +Sangchul Hahn, Heeyoul Choi +School of Information Technology +{schahn21, +Handong Global University +Pohang, South Korea"
111d0b588f3abbbea85d50a28c0506f74161e091,Facial Expression Recognition from Visual Information using Curvelet Transform,"International Journal of Computer Applications (0975 – 8887) Volume 134 – No.10, January 2016 Facial Expression Recognition from Visual Information @@ -6314,15 +21651,134 @@ using Curvelet Transform Pratiksha Singh Surabhi Group of Institution Bhopal systems. Further applications"
+1120e88663a38ed05120af378f57ecf557660160,Generic Object Crowd Tracking by Multi-Task Learning,"LUOETAL.:GENERICOBJECTCROWDTRACKINGBYMULTI-TASKLEARNING +Generic Object Crowd Tracking by +Multi-Task Learning +Wenhan Luo +http://www.iis.ee.ic.ac.uk/~whluo +Tae-Kyun Kim +http://www.iis.ee.ic.ac.uk/~tkkim +Department of Electrical and Electronic +Engineering, Imperial College, +London, UK"
+11feb48d2c4c8f8a5ed9054d49e7a13b0f75f2af,Feature Representation and Extraction for Image Search and Video Retrieval,"Chapter 1 +Feature Representation and Extraction for +Image Search and Video Retrieval +Qingfeng Liu, Yukhe Lavinia, Abhishek Verma, Joyoung Lee, Lazar Spasovic, and +Chengjun Liu"
+7d92d82eae23fe872e8d29116ae22cbd0b15abce,Joint Image Clustering and Labeling by Matrix Factorization,"Joint Image Clustering and Labeling +y Matrix Factorization +Seunghoon Hong, Jonghyun Choi, Jan Feyereisl, Bohyung Han, Larry S. Davis"
7d98dcd15e28bcc57c9c59b7401fa4a5fdaa632b,Face Appearance Factorization for Expression Analysis and Synthesis,"FACE APPEARANCE FACTORIZATION FOR EXPRESSION ANALYSIS AND SYNTHESIS Bouchra Abboud, Franck Davoine Heudiasyc Laboratory, CNRS, University of Technology of Compi`egne. BP 20529, 60205 COMPIEGNE Cedex, FRANCE. E-mail:"
+7dce05b7765541b3fb49a144fb39db331c14fdd1,Modélisation et suivi des déformations faciales : applications à la description des expressions du visage dans le contexte de la langue des signes,"Modélisation et suivi des déformations faciales : +pplications à la description des expressions du visage +dans le contexte de la langue des signes +Hugo Mercier +To cite this version: +Hugo Mercier. Modélisation et suivi des déformations faciales : applications à la description des +expressions du visage dans le contexte de la langue des signes. +Interface homme-machine [cs.HC]. +Université Paul Sabatier - Toulouse III, 2007. Français. <tel-00185084> +HAL Id: tel-00185084 +https://tel.archives-ouvertes.fr/tel-00185084 +Submitted on 5 Nov 2007 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents"
+7da961cb039b1a01cad9b78d93bdfe2a69ed3ccf,Hierarchical Gaussian Descriptors with Application to Person Re-Identification,"Hierarchical Gaussian Descriptors with +Application to Person Re-Identification +Tetsu Matsukawa, Member, IEEE, Takahiro Okabe, Member, IEEE, +Einoshin Suzuki, Non Member, IEEE and Yoichi Sato, Member, IEEE"
+7d7cfc8dc71967f93c2b5ec611747e63c06e1aa1,Crowd Counting and Profiling: Methodology and Evaluation,"Crowd Counting and Profiling: Methodology +nd Evaluation +Chen Change Loy, Ke Chen, Shaogang Gong, and Tao Xiang"
+7d6539d637f919fa20a9261e03aedcf59f92598e,Improving Cross-Resolution Face Matching Using Ensemble-Based Co-Transfer Learning,"Improving Cross-resolution Face Matching using +Ensemble based Co-Transfer Learning +Himanshu S. Bhatt, Student Member, IEEE, Richa Singh, Senior Member, IEEE, Mayank Vatsa, Senior +Member, IEEE, and Nalini K. Ratha, Fellow, IEEE"
+7dfedb083fadb6822c07be82233588c31f37317c,FPGA-based IP cores implementation for face recognition using dynamic partial reconfiguration,"J Real-Time Image Proc (2013) 8:327–340 +DOI 10.1007/s11554-011-0221-x +S P E C I A L I S S U E +FPGA-based IP cores implementation for face +recognition using dynamic partial reconfiguration +Afandi Ahmad • Abbes Amira • Paul Nicholl • +Benjamin Krill +Received: 8 October 2010 / Accepted: 22 August 2011 / Published online: 14 September 2011 +Ó Springer-Verlag 2011"
+7dba0e39bb059103e10fb81bce2fe831f520fb38,Articulated human pose estimation in natural images,"Articulated Human Pose Estimation +in Natural Images +Samuel Alan Johnson +Submitted in accordance with the requirements +for the degree of Doctor of Philosophy. +The University of Leeds +School of Computing +October 2012"
+7db00be42ded44f87f23661c49913f9d64107983,2d Face Recognition: an Experimental and Reproducible Research Survey,"D FACE RECOGNITION: AN +EXPERIMENTAL AND REPRODUCIBLE +RESEARCH SURVEY +Manuel Günther Laurent El Shafey +Sébastien Marcel +Idiap-RR-13-2017 +APRIL 2017 +Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny +T +41 27 721 77 11 F +41 27 721 77 12 www.idiap.ch"
+7d5a83495c4eff62c98c3fd27d0992850611b2bd,Enhanced Performance of Consensus Fault-tolerant Schemes for Decentralized 363 Unmanned Autonomous Vehicle System —,"Proceedings of the Pakistan Academy of Sciences: +A. Physical and Computational Sciences 53 (4): 363–372 (2016) +Copyright © Pakistan Academy of Sciences +ISSN: 2518-4245 (print), 2518-4253 (online) +Pakistan Academy of Sciences +Research Article +Enhanced Performance of Consensus Fault-tolerant Schemes for +Decentralized Unmanned Autonomous Vehicle System +Naeem Khan*, Aitzaz Ali, and Wasi Ullah +Campus, Pakistan +*Electrical Engineering Department, University of Engineering and Technology Peshawar, Bannu"
+7d7f60e41dd9cb84ac5754d59e5a8b418fc7a685,Image Caption Generator Based On Deep Neural Networks,"Image Caption Generator Based On Deep Neural Networks +Jianhui Chen +CPSC 503 +CS Department +Wenqiang Dong +CPSC 503 +CS Department +Minchen Li +CPSC 540 +CS Department"
+7dab6fbf42f82f0f5730fc902f72c3fb628ef2f0,An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks,"An Unsupervised Approach to Solving Inverse +Problems using Generative Adversarial Networks +Rushil Anirudh +Center for Applied Scientific Computing +Lawrence Livermore National Laboratory +Jayaraman J. Thiagarajan +Center for Applied Scientific Computing +Lawrence Livermore National Laboratory +Bhavya Kailkhura +Timo Bremer +Center for Applied Scientific Computing +Lawrence Livermore National Laboratory +Center for Applied Scientific Computing +Lawrence Livermore National Laboratory"
7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22,Labeled Faces in the Wild: A Survey,"Labeled Faces in the Wild: A Survey Erik Learned-Miller, Gary Huang, Aruni RoyChowdhury, Haoxiang Li, Gang Hua"
7d73adcee255469aadc5e926066f71c93f51a1a5,Face alignment by deep convolutional network with adaptive learning rate,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE ICASSP 2016"
+7de028e5c878b56057559bfbd57f1ce6482ec282,An Architecture for Agile Machine Learning in Real-Time Applications,"An Architecture for Agile Machine Learning +in Real-Time Applications +Johann Schleier-Smith +San Francisco, CA 94111 +if(we) Inc. +848 Battery St."
+7d6132a884d2b154059c461e107c7a8c41603ef7,Exploring Multi-Branch and High-Level Semantic Networks for Improving Pedestrian Detection,"Exploring Multi-Branch and High-Level Semantic +Networks for Improving Pedestrian Detection +Jiale Cao, Yanwei Pang, Senior Member, IEEE, and Xuelong Li, Fellow, IEEE"
7d9fe410f24142d2057695ee1d6015fb1d347d4a,Facial Expression Feature Extraction Based on FastLBP,"Facial Expression Feature Extraction Based on FastLBP Computer and Information Engineering Department of Beijing Technology and Business University, Beijing, China @@ -6332,13 +21788,56 @@ Computer and Information Engineering Department of Beijing Technology and Busine Email: Xiuxin Chen, Chongchong Yu and Cheng Gao facial expression"
+7d9dbef9bacf1257e942121f82c3f411f2a78fff,Machine Learning Performance on Face Expression Recognition using Filtered Backprojection in DCT-PCA Domain,"Machine Learning Performance on Face Expression Recognition +using Filtered Backprojection in DCT-PCA Domain. +Ongalo Pheobe1, Huang DongJun2 and Richard Rimiru3 +1 School of Information Science and Engineering, Central South University +Changsha, Hunan, 410083, PR China +School of Information Science and Engineering, Central South University +Changsha, Hunan, 410083, PR China +School of Information Science and Engineering, Central South University +Changsha, Hunan, 410083, PR China"
+7d841607ce29ff4a75734ffbf569431425d8342f,Bimodal 2D-3D face recognition using a two-stage fusion strategy,"Bimodal 2D-3D face recognition using a two-stage fusion +strategy +Amel AISSAOUI1 and Jean MARTINET2 +University of Science and Technologies +Houari Boumediene +Algiers, Algeria +Email: +CRIStAL +Lille 1 University +Villeneuve d’Ascq, France +Email:"
7dffe7498c67e9451db2d04bb8408f376ae86992,LEAR-INRIA submission for the THUMOS workshop,"LEAR-INRIA submission for the THUMOS workshop Heng Wang and Cordelia Schmid LEAR, INRIA, France"
+7d057676c9ba7b313adf0b191f64eb26ac2f9dd6,Variability in postnatal sex hormones due to the use of oral contraception and the phase of menstrual cycle influenced brain,"SEX DIFFERENCES AND THE ROLE OF SEX +HORMONES IN FACE DEVELOPMENT AND FACE +PROCESSING +Klára Marečková, MSc. +Thesis submitted to the University of Nottingham for the degree of +Doctor of Philosophy +JULY 2013"
+7dd654ac5e775fa1fa585e257565455ae8832caf,Deep Pictorial Gaze Estimation,"Deep Pictorial Gaze Estimation +Seonwook Park, Adrian Spurr, and Otmar Hilliges +AIT Lab, Department of Computer Science, ETH Zurich"
+7d3dd33950f4a1be56eb88c0791263b3e3a6deee,Object Counts! Bringing Explicit Detections Back into Image Captioning,"Object Counts! Bringing Explicit Detections Back into Image Captioning +Josiah Wang, Pranava Madhyastha and Lucia Specia +{j.k.wang, p.madhyastha, +Department of Computer Science +University of Sheffield, UK"
7d3f6dd220bec883a44596ddec9b1f0ed4f6aca2,Linear Regression for Face Recognition,"Linear Regression for Face Recognition Imran Naseem, Roberto Togneri, Senior Member, IEEE, and Mohammed Bennamoun"
+7d30939e2d6f8b980910f4eeca5338d072f5ecb6,A Pylon Model for Semantic Segmentation,"A Pylon Model for Semantic Segmentation +Victor Lempitsky +Andrea Vedaldi +Visual Geometry Group, University of Oxford∗ +Andrew Zisserman"
+7df103807902f45824329ab9b2a558b8baf950b2,Precise Localization in High-Definition Road Maps for Urban Regions,"Precise Localization in High-Definition Road Maps for Urban Regions +Fabian Poggenhans1, Niels Ole Salscheider1 and Christoph Stiller2"
+294163a4126b3a886bf62ab896865ce3fc1147a8,Group Sparse Non-negative Matrix Factorization for Multi-Manifold Learning,BMVC 2011 http://dx.doi.org/10.5244/C.25.56
29ce6b54a87432dc8371f3761a9568eb3c5593b0,Age Sensitivity of Face Recognition Algorithms,"Kent Academic Repository Full text document (pdf) Citation for published version @@ -6359,16 +21858,109 @@ Users are advised to check http://kar.kent.ac.uk for the status of the paper. Us published version of record. Enquiries For any further enquiries regarding the licence status of this document, please contact:"
+295266d09fde8f85e6e577b5181cbc73a1594b6b,Parallel effects of processing fluency and positive affect on familiarity-based recognition decisions for faces,"ORIGINAL RESEARCH ARTICLE +published: 22 April 2014 +doi: 10.3389/fpsyg.2014.00328 +Parallel effects of processing fluency and positive affect on +familiarity-based recognition decisions for faces +Devin Duke*, Chris M. Fiacconi and Stefan Köhler* +Department of Psychology, Brain and Mind Institute, Western University, London, ON, Canada +Edited by: +Kevin Bradley Clark, Veterans Affairs +Greater Los Angeles Healthcare +System, USA +Reviewed by: +Bernhard Hommel, Leiden +University, Netherlands +Sascha Topolinski, Universität +Würzburg, Germany +*Correspondence: +Devin Duke and Stefan Köhler, +Department of Psychology, Brain +nd Mind Institute, Western"
+299ca90452aa8a7dd517de3ff3c9bf224d5100c7,Dynamic Scene Classification Using Redundant Spatial Scenelets,"Dynamic Scene Classification Using Redundant +Spatial Scenelets +Liang Du and Haibin Ling, Member, IEEE"
+29a6cbf089a8d916b563e02480a1844909754bcf,"The rules of implicit evaluation by race, religion, and age.","The Rules of Implicit Evaluation by Race, Religion, and Age +Axt JR, Ebersole CR, Nosek BA. +014; 25(9):1804-1815 +ARTICLE IDENTIFIERS +DOI: 10.1177/0956797614543801 +PMID: 25079218 +PMCID: not available +JOURNAL IDENTIFIERS +LCCN: not available +pISSN: 0956-7976 +eISSN: 1467-9280 +OCLC ID: not available +CONS ID: not available +US National Library of Medicine ID: not available +This article was identified from a query of the SafetyLit database. +Powered by TCPDF (www.tcpdf.org)"
+295d978cf47c873936ad774169cac651ea5f3c96,Monocular Depth Prediction using Generative Adversarial Networks,"018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops +Monocular Depth Prediction using Generative Adversarial Networks +Arun CS Kumar +Suchendra M. Bhandarkar +The University of Georgia +Mukta Prasad +Trinity College Dublin"
+2933da06df9e47da8e855266f5ff50e03c0ccd27,Combination of RGB-D Features for Head and Upper Body Orientation Classification,"Combination of RGB-D Features for Head and Upper +Body Orientation Classification +Laurent Fitte-Duval, Alhayat Ali Mekonnen, Frédéric Lerasle +To cite this version: +Laurent Fitte-Duval, Alhayat Ali Mekonnen, Frédéric Lerasle. Combination of RGB-D Features for +Head and Upper Body Orientation Classification. Advanced Concepts for Intelligent Vision Systems +, Oct 2016, Lecce, Italy. 2016. <hal-01763125> +HAL Id: hal-01763125 +https://hal.laas.fr/hal-01763125 +Submitted on 10 Apr 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+292c4bd6fa516393e9c8c5f1dae5afe0bb0ece35,Interacting Multiview Tracker,"Interacting Multiview Tracker +Ju Hong Yoon, Ming-Hsuan Yang, Senior Member, IEEE, and Kuk-Jin Yoon"
292eba47ef77495d2613373642b8372d03f7062b,Deep Secure Encoding: An Application to Face Recognition,"Deep Secure Encoding: An Application to Face Recognition Rohit Pandey Yingbo Zhou Venu Govindaraju"
+296afa5f7e99fc16df47f961c9539347732f7b13,GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks,"GradNorm: Gradient Normalization for Adaptive +Loss Balancing in Deep Multitask Networks +Zhao Chen 1 Vijay Badrinarayanan 1 Chen-Yu Lee 1 Andrew Rabinovich 1"
29e96ec163cb12cd5bd33bdf3d32181c136abaf9,Regularized Locality Preserving Projections with Two-Dimensional Discretized Laplacian Smoothing,"Report No. UIUCDCS-R-2006-2748 UILU-ENG-2006-1788 Regularized Locality Preserving Projections with Two-Dimensional Discretized Laplacian Smoothing Deng Cai, Xiaofei He, and Jiawei Han July 2006"
+29933de38d72a0941d763b7ac5a480e733ef74a2,Open Set Logo Detection and Retrieval,"Open Set Logo Detection and Retrieval +Andras T¨uzk¨o1, Christian Herrmann1,2, Daniel Manger1, J¨urgen Beyerer1,2 +Fraunhofer IOSB, Karlsruhe, Germany +Karlsruhe Institute of Technology KIT, Vision and Fusion Lab, Karlsruhe, Germany +Keywords: +Logo Detection, Logo Retrieval, Logo Dataset, Trademark Retrieval, Open Set Retrieval, Deep Learning."
+290c8196341bbac80efc8c89af5fc60e1b8c80e6,Learning deep representations by mutual information estimation and maximization,"Learning deep representations by mutual information +estimation and maximization +R Devon Hjelm +MSR Montreal, MILA, UdeM, IVADO +Alex Fedorov +MRN, UNM +Samuel Lavoie-Marchildon +MILA, UdeM +Karan Grewal +U Toronto +Phil Bachman +MSR Montreal +Adam Trischler +MSR Montreal +Yoshua Bengio +MILA, UdeM, IVADO, CIFAR"
29e793271370c1f9f5ac03d7b1e70d1efa10577c,Face Recognition Based on Multi-classifierWeighted Optimization and Sparse Representation,"International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.6, No.5 (2013), pp.423-436 http://dx.doi.org/10.14257/ijsip.2013.6.5.37 @@ -6378,6 +21970,18 @@ Deng Nan1, Zhengguang Xu2 and ShengQin Bian3 ,2,3Institute of control science and engineering, University of Science and Technology Beijing ,2,330 Xueyuan Road, Haidian District, Beijing 100083 P. R.China"
+294eef6848403520016bb2c93bfb71b3c75c73fa,Extension of Robust Principal Component Analysis for Incremental Face Recognition,"Extension of Robust Principal Component Analysis for Incremental Face +Recognition +Ha¨ıfa Nakouri and Mohamed Limam +Institut Sup´erieur de Gestion, LARODEC Laboratory +University of Tunis, Tunis, Tunisia +Keywords: +Image alignment, Robust Principal Component Analysis, Incremental RPCA."
+29c23c7d5d70aef54168ba20dccdd14f570901a3,Duplicate Discovery on 2 Billion Internet Images,"Duplicate Discovery on 2 Billion Internet Images +Xin-Jing Wang, Lei Zhang +Microsoft Research Asia +5 Danling Street, Beijing, China +fxjwang,"
29c7dfbbba7a74e9aafb6a6919629b0a7f576530,Automatic Facial Expression Analysis and Emotional Classification,"Automatic Facial Expression Analysis and Emotional Classification Robert Fischer @@ -6405,6 +22009,35 @@ Department of Electrical and Electronic Engineering, Imperial College, South Ken {oscar.deniz, ismael.serrano, Keywords: ction recognition, violence detection, fight detection"
+293ca770a66313c9427dc71cf86bef7e1b94f2d9,Steerable part models,"Steerable Part Models +Hamed Pirsiavash Deva Ramanan +Department of Computer Science, University of California, Irvine"
+29a46aed79df53a1984ee755bed4c8ba2ae94040,Multiple Object Tracking Using K-Shortest Paths Optimization,"Multiple Object Tracking using +K-Shortest Paths Optimization +J´erˆome Berclaz, Franc¸ois Fleuret, Engin T¨uretken, and Pascal Fua, Senior Member, IEEE"
+29cf7937a1c1848c24b294569d50a2f7122de51b,MarioQA: Answering Questions by Watching Gameplay Videos,"MarioQA: Answering Questions by Watching Gameplay Videos +Jonghwan Mun* +Bohyung Han +Paul Hongsuck Seo* +Ilchae Jung +Department of Computer Science and Engineering, POSTECH, Korea +{choco1916, hsseo, chey0313,"
+29b1a44d1e1ffa05c2bf7f4be931c5045f427718,Review on Generic Object Recognition Techniques : Challenges and Opportunities,"International Journal of Advanced Research in Engineering and Technology +(IJARET) +Volume 6, Issue 12, Dec 2015, pp. 104-133, Article ID: IJARET_06_12_010 +Available online at +http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=6&IType=12 +ISSN Print: 0976-6480 and ISSN Online: 0976-6499 +© IAEME Publication +REVIEW ON GENERIC OBJECT +RECOGNITION TECHNIQUES: +CHALLENGES AND OPPORTUNITIES +Prof. Deepika Shukla +Comp. Science and Engineering Department, +Institute of Technology, Nirma University, Ahmedabad, India +Apurva Desai +Department of Computer Science and Information Technology, +VNSGU, Surat India"
294d1fa4e1315e1cf7cc50be2370d24cc6363a41,A modular non-negative matrix factorization for parts-based object recognition using subspace representation,"008 SPIE Digital Library -- Subscriber Archive Copy Processing: Machine Vision Applications, edited by Kurt S. Niel, David Fofi, Proc. of SPIE-IS&T Electronic Imaging, SPIE Vol. 6813, 68130C, © 2008 SPIE-IS&T · 0277-786X/08/$18SPIE-IS&T/ Vol. 6813 68130C-1"
29d414bfde0dfb1478b2bdf67617597dd2d57fc6,Perfect histogram matching PCA for face recognition,"Multidim Syst Sign Process (2010) 21:213–229 @@ -6414,11 +22047,116 @@ Ana-Maria Sevcenco · Wu-Sheng Lu Received: 10 August 2009 / Revised: 21 November 2009 / Accepted: 29 December 2009 / Published online: 14 January 2010 © Springer Science+Business Media, LLC 2010"
+29c5a44e01d1126505471b2ab46163d598c871c7,Improving Landmark Localization with Semi-Supervised Learning,"Improving Landmark Localization with Semi-Supervised Learning +Sina Honari1∗, Pavlo Molchanov2, Stephen Tyree2, Pascal Vincent1,4,5, Christopher Pal1,3, Jan Kautz2 +MILA-University of Montreal, 2NVIDIA, 3Ecole Polytechnique of Montreal, 4CIFAR, 5Facebook AI Research. +{honaris, +{pmolchanov, styree,"
+29230bbb447b39b7fc3de7cb34b313cc3afe0504,Face Detection and Recognition Using Maximum Likelihood Classifiers on Gabor Graphs,"SPI-J068 00721 +International Journal of Pattern Recognition +nd Artificial Intelligence +Vol. 23, No. 3 (2009) 433–461 +(cid:1) World Scientific Publishing Company +FACE DETECTION AND RECOGNITION USING MAXIMUM +LIKELIHOOD CLASSIFIERS ON GABOR GRAPHS +MANUEL G ¨UNTHER and ROLF P. W ¨URTZ +Institut f¨ur Neuroinformatik +Ruhr-Universit¨at Bochum +D–44780 Bochum, Germany +We present an integrated face recognition system that combines a Maximum Likelihood +(ML) estimator with Gabor graphs for face detection under varying scale and in-plane +rotation and matching as well as a Bayesian intrapersonal/extrapersonal classifier (BIC) +on graph similarities for face recognition. We have tested a variety of similarity functions +nd achieved verification rates (at FAR 0.1%) of 90.5% on expression-variation and 95.8% +on size-varying frontal images within the CAS-PEAL database. Performing Experiment 1 +of FRGC ver2.0, the method achieved a verification rate of 72%. +Keywords: Face recognition; Maximum Likelihood estimators; Gabor graphs. +. Introduction"
+2939169aed69aa2626c5774d9b20e62c905e479b,Fast Exact HyperGraph Matching with Dynamic Programming for Spatio-Temporal Data,"Fast Exact Hyper-Graph Matching with Dynamic +Programming for Spatio-Temporal Data +Oya Celiktutan, Christian Wolf, Bülent Sankur, Eric Lombardi +To cite this version: +Oya Celiktutan, Christian Wolf, Bülent Sankur, Eric Lombardi. Fast Exact Hyper-Graph Matching +with Dynamic Programming for Spatio-Temporal Data. Journal of Mathematical Imaging and Vision, +Springer Verlag, 2015, 51, pp.1-21. <hal-01151755> +HAL Id: hal-01151755 +https://hal.archives-ouvertes.fr/hal-01151755 +Submitted on 13 May 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+29107badb19e7c5c89f57f81f50df08422e53304,Automatic localisation and segmentation of the Left Ventricle in Cardiac Ultrasound Images,"MASTER THESIS +Automatic localisation and +segmentation of the Left Ventricle in +Cardiac Ultrasound Images +Presented by: +Esther PUYOL +IG 3A F4B and MR 2A SISEA +013/2014 +Supervisor: +Paolo PIRO +Academic supervisor: +Guy CAZUGUEL +MEDISYS - PHILIPS RESEARCH PARIS +Company: +University: +TELECOM BRETAGNE +7th March - 12th September 2014"
+29113ed00421953e0ddc4fa6784eaba60f05e801,Automatic Track Creation and Deletion Framework for Face Tracking,"IJCSNS International Journal of Computer Science and Network Security, VOL.15 No.2, February 2015 +Automatic Track Creation and Deletion Framework for Face +Tracking +Dept. of Information and Communication, St.Xavier’s Catholic College of Engineering, Nagercoil, Tamilnadu, India. +Renimol T G, Anto Kumar R.P"
290136947fd44879d914085ee51d8a4f433765fa,On a taxonomy of facial features,"On a Taxonomy of Facial Features Brendan Klare and Anil K. Jain"
2957715e96a18dbb5ed5c36b92050ec375214aa6,InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity,"Improving Face Attribute Detection with Race and Gender Diversity InclusiveFaceNet: Hee Jung Ryu 1 Hartwig Adam * 1 Margaret Mitchell * 1"
+29dbb9492292b574f7bfd8629d6801d3136887b7,Towards Autonomous Situation Awareness,"Towards Autonomous Situation Awareness +Nikhil Naikal +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2014-124 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-124.html +May 21, 2014"
+29b3f9f0fb821883a3c3bccbf0337c242c3b8a64,Transfer Learning for Video Recognition with Scarce Training Data,"Transfer Learning for Video Recognition +with Scarce Training Data +for Deep Convolutional Neural Network +Yu-Chuan Su, Tzu-Hsuan Chiu, Chun-Yen Yeh, Hsin-Fu Huang, Winston H. Hsu"
+29a705a5fa76641e0d8963f1fdd67ee4c0d92d3d,SCface – surveillance cameras face database,"Multimed Tools Appl (2011) 51:863–879 +DOI 10.1007/s11042-009-0417-2 +SCface – surveillance cameras face database +Mislav Grgic & Kresimir Delac & Sonja Grgic +Published online: 30 October 2009 +# Springer Science + Business Media, LLC 2009"
+299af7d4fe6da8ac0b390e3ce45c48f7a8b5bb37,"Attribute And-Or Grammar for Joint Parsing of Human Attributes, Part and Pose","Attribute And-Or Grammar for Joint Parsing of +Human Attributes, Part and Pose +Seyoung Park, Bruce Xiaohan Nie and Song-Chun Zhu"
+29633712a36c3efc77ce3a9844a2e9a029daf310,AdaBoost for Parking Lot Occupation Detection,"AdaBoost for Parking Lot Occupation +Detection +Radovan Fusek1, Karel Mozdˇreˇn1, Milan ˇSurkala1 and Eduard Sojka1"
+29619496c688f8400a90fef79b4fa756967ed0f7,Head Gesture Recognition: A Literature Review,"International Conference on Innovative Research in Engineering, Science, Management and Humanities (ICIRESMH-2017) +t (IETE) Institution of Electronics and Telecommunication Engineers, Lodhi Road, Delhi, India +on 19th February 2017 +ISBN: 978-81-932712-5-4 +Head Gesture Recognition: A Literature Review +Er. Rushikesh T. Bankar +Ph. D Scholar, +Department of Electronics Engineering, +G. H. Raisoni College of Engineering, +Nagpur, India. +Dr. Suresh S. Salankar +Dean SAC & Professor, +Department of E&TC Engineering, +G. H. Raisoni College of Engineering, +Nagpur, India."
2965d092ed72822432c547830fa557794ae7e27b,Improving Representation and Classification of Image and Video Data for Surveillance Applications,"Improving Representation and Classification of Image and Video Data for Surveillance Applications Andres Sanin @@ -6426,9 +22164,51 @@ BSc(Biol), MSc(Biol), MSc(CompSc) A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2012 School of Information Technology and Electrical Engineering"
+29bd7de310438c2b9d8b6e7eb7df662079934747,Semantic Scene Mapping with Spatio-temporal Deep Neural Network for Robotic Applications,"Cogn Comput +https://doi.org/10.1007/s12559-017-9526-9 +Semantic Scene Mapping with Spatio-temporal Deep Neural +Network for Robotic Applications +Ruihao Li1 +· Dongbing Gu1 · Qiang Liu1 · Zhiqiang Long2 · Huosheng Hu1 +Received: 25 September 2017 / Accepted: 31 October 2017 +© Springer Science+Business Media, LLC, part of Springer Nature 2017"
+29c6b06ac98dbdaf25e4cc9a05b4ab314923cccd,Assessment of the communicative and coordination skills of children with Autism Spectrum Disorders and typically developing children using social signal processing,"Research in Autism Spectrum Disorders 7 (2013) 741–756 +Contents lists available at SciVerse ScienceDirect +Research in Autism Spectrum Disorders +J o u r n a l h o m e p a g e : h t t p : / / e e s . e l s e v i e r . c o m / R A S D / d e f a u l t . a s p +Assessment of the communicative and coordination skills of +hildren with Autism Spectrum Disorders and typically +developing children using social signal processing +Emilie Delaherche a, Mohamed Chetouani a, Fabienne Bigouret b,c, Jean Xavier c, +Monique Plaza a, David Cohen a,c,* +Institute of Intelligent Systems and Robotics, University Pierre and Marie Curie, 75005 Paris, France +University of Paris 8, 93526 Saint-Denis, France +Department of Child and Adolescent Psychiatry, Hoˆpital de la Pitie´-Salpeˆtrie`re, University Pierre and Marie Curie, 75013 Paris, France +A R T I C L E +I N F O +A B S T R A C T +Article history: +Received 27 November 2012 +Received in revised form 5 February 2013 +Accepted 8 February 2013 +Keywords:"
+29ca8ddf79d4cd1dc20cc8160a6d3326933e943f,Pragmatic descriptions of perceptual stimuli,"Proceedings of the Student Research Workshop at the 15th Conference of the European Chapter of the Association for Computational Linguistics, +pages 1–10, Valencia, Spain, April 3-7 2017. c(cid:13)2017 Association for Computational Linguistics"
2921719b57544cfe5d0a1614d5ae81710ba804fa,Face Recognition Enhancement Based on Image File Formats and Wavelet De - noising,"Face Recognition Enhancement Based on Image File Formats and Wavelet De-noising Isra’a Abdul-Ameer Abdul-Jabbar, Jieqing Tan, and Zhengfeng Hou"
+2914a20df10f3bb55c5d4764ece85101c1a3e5a8,User interest profiling using tracking-free coarse gaze estimation,"User Interest Profiling Using +Tracking-free Coarse Gaze Estimation +Federico Bartoli, Giuseppe Lisanti, Lorenzo Seidenari, Alberto Del Bimbo +Media Integration and Communication Center +Universit`a degli Studi di Firenze +Firenze, Italy"
+291be6e3027575287c24f4363e4bf7a8b415d4c1,MSER-Based Real-Time Text Detection and Tracking,"To appear in the proceedings of the 2014 International Conference on Pattern Recognition. +MSER-based Real-Time Text Detection and Tracking +Llu´ıs G´omez and Dimosthenis Karatzas +Computer Vision Center +Universitat Aut`onoma de Barcelona +Email:"
29a013b2faace976f2c532533bd6ab4178ccd348,Hierarchical Manifold Learning With Applications to Supervised Classification for High-Resolution Remotely Sensed Images,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. Hierarchical Manifold Learning With Applications to Supervised Classification for High-Resolution @@ -6454,6 +22234,9 @@ Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438 Automatic Face Annotation Ashna Shajahan M.Tech Student, Dept. of Computer Science & Engineering, Mount Zion College of Engineering, Pathanamthitta, Kerala, India"
+296502c6370cabd2b7e38e71cfc757d2e5fa2199,Detection of Deep Network Generated Images Using Disparities in Color Components,"Detection of Deep Network Generated Images +Using Disparities in Color Components +Haodong Li, Bin Li, Shunquan Tan, Jiwu Huang"
2988f24908e912259d7a34c84b0edaf7ea50e2b3,A Model of Brightness Variations Due to Illumination Changes and Non-rigid Motion Using Spherical Harmonics,"A Model of Brightness Variations Due to Illumination Changes and Non-rigid Motion Using Spherical Harmonics @@ -6473,6 +22256,29 @@ Dep. de Inteligencia Artificial, U. Polit´ecnica de Madrid, Spain http://www.dia.fi.upm.es/~pcr http://www.dia.fi.upm.es/~pcr"
+29d591806cdc6ef0d580e4a21f32e5ad9d09d148,Large scale image annotation: learning to rank with joint word-image embeddings,"Large Scale Image Annotation: +Learning to Rank with Joint Word-Image +Embeddings +Jason Weston1, Samy Bengio1, and Nicolas Usunier2 +Google, USA +Universit´e Paris 6, LIP6, France"
+29f46586c95af2fa6326724c867aa88b55b5400e,Failure Prediction for Autonomous Driving,"Failure Prediction for Autonomous Driving +Simon Hecker1, Dengxin Dai1, and Luc Van Gool1,2"
+7c9d8593cdf2f8ba9f27906b2b5827b145631a0b,MsCGAN: Multi-scale Conditional Generative Adversarial Networks for Person Image Generation,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, OCTOBER 2018 +MsCGAN: Multi-scale Conditional Generative +Adversarial Networks for Person Image +Generation +Wei Tang∗, Teng Li +† Anhui University, HeFei, China +Hefei University, HeFei, China +§ Hefei University of Technology, HeFei, China"
+7c4864065f4e107cb5be49a8dba8cf7d94b8340f,Multi-target Tracking by Lagrangian Relaxation to Min-cost Network Flow,"Multi-target Tracking by Lagrangian Relaxation to Min-Cost Network Flow +Asad A. Butt and Robert T. Collins +The Pennsylvania State University, University Park, PA. 16802, USA"
+7c1db13ae2c62d1f860fd2664885c9c93a28cab8,Multistage Particle Windows for Fast and Accurate Object Detection,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +Multi-Stage Particle Windows for Fast and +Accurate Object Detection +Giovanni Gualdi, Andrea Prati, Member, IEEE, and Rita Cucchiara, Member, IEEE"
7cee802e083c5e1731ee50e731f23c9b12da7d36,2^B3^C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional Networks,"B3C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional Networks Vandit Gajjar @@ -6489,11 +22295,42 @@ University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent Constantin Vertan Image Processing and Analysis Laboratory University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313"
+7cee2a2bee27657e6599b13f9ed6536d5f46fd0a,A Semantic Labeling Approach for Accurate Weed Mapping of High Resolution UAV Imagery,"Article +A Semantic Labeling Approach for Accurate Weed +Mapping of High Resolution UAV Imagery +Huasheng Huang 1,2,†, Yubin Lan 1,2,†, Jizhong Deng 1,2,*, Aqing Yang 3, Xiaoling Deng 2,3, +Lei Zhang 2,4 and Sheng Wen 2,5 +College of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, China; +(H.H.); (Y.L.) +National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide +Spraying Technology, Wushan Road, Guangzhou 510642, China; (X.D.); +(L.Z.); (S.W.) +College of Electronic Engineering, South China Agricultural University, Wushan Road, Guangzhou 516042, +China; +College of Agriculture, South China Agricultural University, Wushan Road, Guangzhou 516042, China +Engineering Fundamental Teaching and Training Center, South China Agricultural University, +Wushan Road, Guangzhou 510642, China +* Correspondence: Tel.: +86-20-8528-8201 +These authors contributed equally to this work and should be considered as co-first authors. +Received: 13 May 2018; Accepted: 27 June 2018; Published: 1 July 2018"
+7c25a4b2eaa7bf0bc4e0bd239f05d6c0d4cb3431,Fast Appearance-based Person Re-identification and Retrieval Using Dissimilarity Representations,"Fast Appearance-based Person Re-identification +nd Retrieval Using Dissimilarity +Representations +Riccardo Satta, Giorgio Fumera, and Fabio Roli +Dept. of Electrical and Electronic Engineering, University of Cagliari +Piazza d’Armi, 09123 Cagliari, Italy +e-mail: {satta, fumera, +WWW: http://prag.diee.unica.it"
7c45b5824645ba6d96beec17ca8ecfb22dfcdd7f,News Image Annotation on a Large Parallel Text-image Corpus,"News image annotation on a large parallel text-image corpus Pierre Tirilly, Vincent Claveau, Patrick Gros Universit´e de Rennes 1/IRISA, CNRS/IRISA, INRIA Rennes-Bretagne Atlantique Campus de Beaulieu 5042 Rennes Cedex, France"
+7c18965f5573020f32b151a08178ee4906b5bf4c,Recursive Coarse-to-Fine Localization for Fast Object Detection,"Recursive Coarse-to-Fine Localization +for fast Object Detection +Marco Pedersoli, Jordi Gonz`alez, Andrew D. Bagdanov, and Juan J. Villanueva +Dept. Ci`encies de la Computaci´o & Centre de Visi´o per Computador, +Edifici O, Campus UAB 08193 Bellaterra (Cerdanyola) Barcelona, Spain"
7c0a6824b556696ad7bdc6623d742687655852db,MPCA+MDA: A novel approach for face recognition based on tensor objects,"8th Telecommunications forum TELFOR 2010 Serbia, Belgrade, November 23-25, 2010. MPCA+DATER: A Novel Approach for Face @@ -6512,14 +22349,27 @@ https://doi.org/10.1111/bjop.12206 promoting access to White Rose research papers http://eprints.whiterose.ac.uk/"
+7caca02d3c61271d22c43580677acb6d52b23503,What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?,"IJCV VISI manuscript No. +(will be inserted by the editor) +What Makes Good Synthetic Training Data for Learning +Disparity and Optical Flow Estimation? +Nikolaus Mayer · Eddy Ilg · Philipp Fischer · Caner Hazirbas · Daniel +Cremers · Alexey Dosovitskiy · Thomas Brox +Received: date / Accepted: date"
7c3e09e0bd992d3f4670ffacb4ec3a911141c51f,Transferring Object-Scene Convolutional Neural Networks for Event Recognition in Still Images,"Noname manuscript No. (will be inserted by the editor) Transferring Object-Scene Convolutional Neural Networks for Event Recognition in Still Images Limin Wang · Zhe Wang · Yu Qiao · Luc Van Gool Received: date / Accepted: date"
+7c98c27f4be40a7675ba9c85179ce72d12593a7a,Training Bit Fully Convolutional Network for Fast Semantic Segmentation,"Training Bit Fully Convolutional Network for Fast Semantic Segmentation +He Wen and Shuchang Zhou and Zhe Liang and Yuxiang Zhang and Dieqiao Feng and Xinyu Zhou and Cong Yao +{wenhe, zsc, liangzhe, zyx, fdq, zxy, +Megvii Inc."
7c7b0550ec41e97fcfc635feffe2e53624471c59,"Head, Eye, and Hand Patterns for Driver Activity Recognition","051-4651/14 $31.00 © 2014 IEEE DOI 10.1109/ICPR.2014.124"
+7c8d57ca9cbefd1c2b3f4d45ab6791adba2d6bb4,Two-Stage Hashing for Fast Document Retrieval,"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 495–500, +Baltimore, Maryland, USA, June 23-25 2014. c(cid:13)2014 Association for Computational Linguistics"
7c119e6bdada2882baca232da76c35ae9b5277f8,Facial expression recognition using embedded Hidden Markov Model,"Facial Expression Recognition Using Embedded Hidden Markov Model Languang He, Xuan Wang, Member, IEEE, Chenglong Yu, Member, IEEE, Kun Wu @@ -6527,6 +22377,35 @@ Intelligence Computing Research Center HIT Shenzhen Graduate School Shenzhen, China {telent, wangxuan, ycl, wukun}"
+7cd5d849212c294c452be009ff465ca7d3d923c8,A Brief Survey of Face Recognition Techniques,"(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:2)(cid:2)(cid:3)(cid:3)(cid:4)(cid:4)(cid:5)(cid:5)(cid:6)(cid:6)(cid:7)(cid:7)(cid:1)(cid:1)(cid:8)(cid:8)(cid:1)(cid:1)(cid:9)(cid:9)(cid:1)(cid:1)(cid:10)(cid:10)(cid:5)(cid:5)(cid:6)(cid:6)(cid:11)(cid:11)(cid:7)(cid:7)(cid:12)(cid:12)(cid:1)(cid:1)(cid:13)(cid:13)(cid:1)(cid:1)(cid:14)(cid:14)(cid:15)(cid:15)(cid:12)(cid:12)(cid:16)(cid:16)(cid:17)(cid:17)(cid:1)(cid:1)(cid:13)(cid:13)(cid:18)(cid:18)(cid:19)(cid:19)(cid:20)(cid:20)(cid:1)(cid:1)(cid:21)(cid:21)(cid:1)(cid:1)(cid:22)(cid:22)(cid:7)(cid:7)(cid:23)(cid:23)(cid:24)(cid:24)(cid:1)(cid:1)(cid:13)(cid:13)(cid:18)(cid:18)(cid:19)(cid:19)(cid:20)(cid:20)(cid:1)(cid:1)(cid:23)(cid:23)(cid:23)(cid:23)(cid:25)(cid:25)(cid:1)(cid:1)(cid:13)(cid:13)(cid:18)(cid:18)(cid:21)(cid:21)(cid:26)(cid:26)(cid:27)(cid:27)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1) +(cid:15)(cid:15)(cid:28)(cid:28)(cid:15)(cid:15)(cid:29)(cid:29)(cid:4)(cid:4)(cid:15)(cid:15)(cid:11)(cid:11)(cid:4)(cid:4)(cid:7)(cid:7)(cid:1)(cid:1)(cid:3)(cid:3)(cid:30)(cid:30)(cid:4)(cid:4)(cid:29)(cid:29)(cid:30)(cid:30)(cid:7)(cid:7)(cid:1)(cid:1)(cid:15)(cid:15)(cid:24)(cid:24)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:31)(cid:31)(cid:31)(cid:31)(cid:31)(cid:31)(cid:25)(cid:25)(cid:16)(cid:16) !!(cid:3)(cid:3)(cid:5)(cid:5)(cid:12)(cid:12)(cid:30)(cid:30)(cid:15)(cid:15)(cid:4)(cid:4) (cid:25)(cid:25)(cid:16)(cid:16)(cid:3)(cid:3)(cid:6)(cid:6)(cid:1) +(cid:1) +(cid:1) +AA BBrriieeff SSuurrvveeyy ooff FFaaccee RReeccooggnniittiioonn TTeecchhnniiqquueess +Nilam B. Goswami, Pinal Patel, Chirag I. Patel, Parth Parekh +Post Graduation, CE and IT department, Government Engineering College, Gandhinagar, India"
+7c8adb2fa156b119a1f576652c39fb06e4e19675,Ordinal Regression using Noisy Pairwise Comparisons for Body Mass Index Range Estimation,"Ordinal Regression using Noisy Pairwise Comparisons for Body Mass Index +Range Estimation +Luisa F. Polan´ıa +Dongning Wang +Glenn M. Fung +American Family Insurance, Strategic Data & Analytics, Madison, WI +{lpolania, dwang1,"
+7c25ed788da1f5f61d8d1da23dd319dfb4e5ac2d,Human-In-The-Loop Person Re-Identification,"Human-In-The-Loop Person Re-Identification +Hanxiao Wang, Shaogang Gong, Xiatian Zhu, and Tao Xiang"
+7c26559e7269679ef52a85d02c6ff7000c2387d2,Towards a Development of a Learners’ Ratified Acceptance of Multi-biometrics Intentions Model (RAMIM): Initial Empirical Results,"Yair Levy, Michelle M. Ramim +Towards a Development of a Learners’ Ratified +Acceptance of Multi-biometrics Intentions Model +(RAMIM): Initial Empirical Results +Graduate School of Computer and Information +H. Wayne Huizenga School of Business and +Nova Southeastern University, USA +Nova Southeastern University, USA +Yair Levy +Sciences +Michelle M. Ramim +Entrepreneurship +implemented as"
7c9a65f18f7feb473e993077d087d4806578214e,SpringerLink - Zeitschriftenbeitrag,"SpringerLink - Zeitschriftenbeitrag http://www.springerlink.com/content/93hr862660nl1164/?p=abe5352... Deutsch @@ -6547,6 +22426,19 @@ in diesem Heft Diesen Beitrag exportieren Diesen Beitrag exportieren als RIS | Text"
+7c0f7d47da05a41e8671b059ade70dd2df7070db,Face Recognition and Feature Detection Using Artificial Neural Networks and ANFIS,"International Journal of Emerging Technology and Advanced Engineering +Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 7, July 2015) +Face Recognition and Feature Detection Using Artificial +Neural Networks and ANFIS +Sanjay Kumar Dekate1, Dr. Anupam Shukla2 +Research Scholar, Dr. C. V. Raman University, Bilaspur, India +Professor, ABV-IIITM, Gwalior, India"
+7c0ffae3acb0fd0a14ff66b6d474229aa16c53ab,Covariance Descriptor Multiple Object Tracking and Re-identification with Colorspace Evaluation,"Covariance Descriptor Multiple Object Tracking +nd Re-Identification with Colorspace +Evaluation +Andr´es Romero, Mich`ele Gouiff´es and Lionel Lacassagne +Institut d’´El´ectronique Fondamentale, UMR 8622, Universit´e Paris-Sud XI, Bˆatiment +660, rue Noetzlin, Plateau du Moulon, 91400 Orsay"
7c1e1c767f7911a390d49bed4f73952df8445936,Non-Rigid Object Detection with LocalInterleaved Sequential Alignment (LISA),"NON-RIGID OBJECT DETECTION WITH LOCAL INTERLEAVED SEQUENTIAL ALIGNMENT (LISA) Non-Rigid Object Detection with Local Interleaved Sequential Alignment (LISA) @@ -6563,6 +22455,19 @@ Atlanta, GA 30322, USA Emory University Atlanta, GA 30322, USA"
7c349932a3d083466da58ab1674129600b12b81c,Leveraging Multiple Features for Image Retrieval and Matching,
+16e2e9e4741795c004d15e95532b07943d3a3242,CPS: 3D Compositional Part Segmentation through Grasping,"CPS: 3D Compositional Part Segmentation through Grasping +Safoura Rezapour Lakani +University of Innsbruck +Innsbruck, Austria +Mirela Popa +University of Innsbruck +Innsbruck, Austria +Antonio J. Rodr´ıguez-S´anchez +University of Innsbruck +Innsbruck, Austria +Justus Piater +University of Innsbruck +Innsbruck, Austria"
162403e189d1b8463952fa4f18a291241275c354,Action Recognition with Spatio-Temporal Visual Attention on Skeleton Image Sequences,"Action Recognition with Spatio-Temporal Visual Attention on Skeleton Image Sequences Zhengyuan Yang, Student Member, IEEE, Yuncheng Li, Jianchao Yang, Member, IEEE, @@ -6587,10 +22492,27 @@ Furthermore, a two-stream RNN structure [14] is proposed to" Detection Signal Procesing Laboratory (LTS5), ´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland Anıl Y¨uce, Hua Gao and Jean-Philippe Thiran"
+16fdc3829dc8322a26eac46e93703000005f3d6d,An occlusion reasoning scheme for monocular pedestrian tracking in dynamic scenes,"An Occlusion Reasoning Scheme for Monocular +Pedestrian Tracking in Dynamic Scenes +Sourav Garg and Swagat Kumar +Innovation Lab +Tata Consultancy Services +New Delhi, India 201301 +Email: +Rajesh Ratnakaram and Prithwijit Guha +Department of Electronics and Electrical Engineering +Indian Institute of Technology Guwahati +Guwahati, Assam, India 781039 +Email:"
16671b2dc89367ce4ed2a9c241246a0cec9ec10e,Detecting the Number of Clusters in n-Way Probabilistic Clustering,"Detecting the Number of Clusters in n-Way Probabilistic Clustering Zhaoshui He, Andrzej Cichocki, Senior Member, IEEE, Shengli Xie, Senior Member, IEEE, and Kyuwan Choi"
+16bd796687ca17ac7ca28d28d856b324186628ba,Face Recognition and Verification Using Photometric Stereo: The Photoface Database and a Comprehensive Evaluation,"Face Recognition and Verification Using +Photometric Stereo: The Photoface Database +nd a Comprehensive Evaluation +Stefanos Zafeiriou, Member, IEEE, Gary A. Atkinson, Mark F. Hansen, William A. P. Smith, Member, IEEE, +Vasileios Argyriou, Member, IEEE, Maria Petrou, Senior Member, IEEE, Melvyn L. Smith, and Lyndon N. Smith"
16395b40e19cbc6d5b82543039ffff2a06363845,Action Recognition in Video Using Sparse Coding and Relative Features,"Action Recognition in Video Using Sparse Coding and Relative Features Anal´ı Alfaro Domingo Mery @@ -6601,6 +22523,50 @@ P. Universidad Catolica de Chile Santiago, Chile Santiago, Chile Santiago, Chile"
+16e577820999e584c787ec611f55746cf9147518,Cross-Domain Person Reidentification Using Domain Adaptation Ranking SVMs,"Cross-Domain Person Re-Identification Using +Domain Adaptation Ranking SVMs +Andy J Ma, Jiawei Li, Pong C Yuen, Senior Member, IEEE, and Ping Li +label"
+1696f6861c208b6a7cac95fbeba524867ad3e8d6,Using deep learning to quantify the beauty of outdoor places,"Downloaded from +http://rsos.royalsocietypublishing.org/ +on September 4, 2017 +rsos.royalsocietypublishing.org +Research +Cite this article: Seresinhe CI, Preis T, Moat +HS. 2017 Using deep learning to quantify the +eauty of outdoor places. R. Soc. open sci. +: 170170. +http://dx.doi.org/10.1098/rsos.170170 +Received: 23 February 2017 +Accepted: 19 June 2017 +Subject Category: +Computer science +Subject Areas: +environmental science/computer modelling +nd simulation +Keywords: +environmental aesthetics, well-being, +onvolutional neural networks, deep learning,"
+16d1e29b588fd26f5f0ac8038110f7b8500a1ec9,$L_0$ Regularized Stationary-Time Estimation for Crowd Analysis,"L0 Regularized Stationary-Time Estimation +for Crowd Analysis +Shuai Yi, Xiaogang Wang, Member, IEEE, Cewu Lu, Member, IEEE, +Jiaya Jia, Senior Member, IEEE, and Hongsheng Li"
+16da7c95c218e9e97eea7734d6c243e8b825196d,A stable and accurate multi-reference representation for surfaces of R<sup>3</sup>: Application to 3D faces description,"A stable and accurate multi-reference representation for surfaces of +R3: Application to 3D faces description +Wieme Gadacha1, Faouzi Ghorbel1 +CRISTAL laboratory, GRIFT research group +National School of Computer Sciences (NSCS), La Manouba 2010, Tunisia"
+1685ac0f9fedd83a178a2f64f25155fb37998d8f,Human tracking using wearable sensors in the pocket,"Human Tracking using Wearable Sensors in the +Pocket +Wenchao Jiang +Department of Computer Science +Zhaozheng Yin +Department of Computer Science +Missouri University of Science and Technology +Missouri University of Science and Technology"
+166f42f66c5e6dd959548acfb97dc77a36013639,Bilevel Model-Based Discriminative Dictionary Learning for Recognition,"Bilevel Model-Based Discriminative Dictionary +Learning for Recognition +Pan Zhou, Chao Zhang, Member, IEEE, and Zhouchen Lin, Senior Member, IEEE"
16c884be18016cc07aec0ef7e914622a1a9fb59d,Exploiting Multimodal Data for Image Understanding,"UNIVERSITÉ DE GRENOBLE No attribué par la bibliothèque THÈSE @@ -6621,6 +22587,23 @@ M. Antonio Torralba Mme Tinne Tuytelaars Katholieke Universiteit Leuven M. Mark Everingham University of Leeds Mme Cordelia Schmid"
+16aec3ee9a97162b85b1d51c3c5ce73a472e74b8,Application of Selective Search to Pose estimation,"Application of Selective Search to Pose estimation +Ujwal Krothapalli +Department of Electrical and +Computer Engineering +Virginia Tech +Blacksburg, Virginia 24061"
+16c855aea9789e2b7a77f35dc4181efc93dec69c,Exploiting Sum of Submodular Structure for Inference in Very High Order MRF-MAP Problems,"SUBMITTED TO IEEE TPAMI +Exploiting Sum of Submodular Structure for +Inference in Very High Order MRF-MAP +Problems +Ishant Shanu Surbhi Goel Chetan Arora Parag Singla"
+163738c0f74ec82ab670a868a051edb732543b6e,Image alignment with rotation manifolds built on sparse geometric expansions,"Image alignment with rotation manifolds built +on sparse geometric expansions +Effrosyni Kokiopoulou and Pascal Frossard +Ecole Polytechnique F´ed´erale de Lausanne (EPFL) +Signal Processing Institute - ITS +CH- 1015 Lausanne, Switzerland"
1630e839bc23811e340bdadad3c55b6723db361d,Exploiting relationship between attributes for improved face verification,"SONG, TAN, CHEN: EXPLOITING RELATIONSHIP BETWEEN ATTRIBUTES Exploiting Relationship between Attributes for Improved Face Verification @@ -6631,6 +22614,37 @@ Department of Computer Science and Technology, Nanjing University of Aero- nautics and Astronautics, Nanjing 210016, P.R. China"
+160ab0e879f4451fa4df88cd567508150894ba9d,Cross Dataset Person Re-identification,"Cross Dataset Person Re-identification +Yang Hu, Dong Yi, Shengcai Liao, Zhen Lei, Stan Z. Li(cid:63) +Center for Biometrics and Security Research +National Laboratory of Pattern Recognition +Institute of Automation, Chinese Academy of Sciences (CASIA) +95 Zhongguancun East Road, 100190, Beijing, China +{yhu, dong.yi, scliao, zlei,"
+16597862a1df1a983c439e82e0462424f538bb48,Personalized Saliency and its Prediction,
+166b5bdea1f4f850af5b045a953d6de74bc18d1e,Best of both worlds: Human-machine collaboration for object annotation,"Best of both worlds: human-machine collaboration for object annotation +Olga Russakovsky1, Li-Jia Li2, Li Fei-Fei1 +Stanford University. 2Snapchat (this work was done while at Yahoo! Labs). +The long-standing goal of localizing every object in an image remains +elusive. Manually annotating objects is quite expensive despite crowd en- +gineering innovations. Current automatic object detectors can accurately +detect at most a few objects per image. This paper brings together the latest +dvancements in object detection and in crowd engineering into a principled +framework for accurately and efficiently localizing objects in images. +The input to the system is an image to annotate and a set of annotation +onstraints: (1) desired utility of labeling, which is a generalization of the +number of labeled objects, (2) desired precision of the labeling and/or (3) +the budget, which is the human cost of the labeling. Our system automati- +ally solicits feedback from human workers (“users”) to annotate the image +subject to these constraints, as illustrated in Figure 1. The output is a set of +object annotations, informed by humans and computer vision. +One important decision is which questions to pose to the human label- +ers. In computer vision with human-in-the-loop approaches, human inter- +vention has ranged from binary question-and-answer [1] to attribute-based +feedback [4] to free-form object annotation [6]. Binary questions are not"
+161c9ef7114bda7c5a60a29ee4a3161b0a76e676,Low Rank Approximation and Decomposition of Large Matrices Using Error Correcting Codes,"Low rank approximation and decomposition of +large matrices using error correcting codes +Shashanka Ubaru, Arya Mazumdar Senior Member, IEEE, and Yousef Saad"
16286fb0f14f6a7a1acc10fcd28b3ac43f12f3eb,"All Smiles are Not Created Equal: Morphology and Timing of Smiles Perceived as Amused, Polite, and Embarrassed/Nervous.","J Nonverbal Behav DOI 10.1007/s10919-008-0059-5 O R I G I N A L P A P E R @@ -6639,6 +22653,14 @@ nd Timing of Smiles Perceived as Amused, Polite, nd Embarrassed/Nervous Zara Ambadar Æ Jeffrey F. Cohn Æ Lawrence Ian Reed Ó Springer Science+Business Media, LLC 2008"
+165d966940dcccf9c9976ebffcabe72d66996b05,Semi-Supervised Nonlinear Hashing Using Bootstrap Sequential Projection Learning,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +Semi-supervised Nonlinear Hashing Using +Bootstrap Sequential Projection Learning +Chenxia Wu, Jianke Zhu, Deng Cai, Chun Chen, and Jiajun Bu"
+1697a4188b9f75ff5324eb9957b8317f459bbf59,Dual-tree fast exact max-kernel search,"Dual-Tree Fast Exact Max-Kernel Search +Ryan R. Curtin and Parikshit Ram +December 11, 2013"
+16e8d439fbcf8311efea7b0baeb1a5340272b396,Stereo and LIDAR Fusion based Detection of Humans and Other Obstacles in Farming Scenarios,
166186e551b75c9b5adcc9218f0727b73f5de899,Automatic Age and Gender Recognition in Human Face Image Dataset using Convolutional Neural Network System,"Volume 4, Issue 2, February 2016 International Journal of Advance Research in Computer Science and Management Studies @@ -6664,6 +22686,24 @@ Andhra Pradesh - India" Volume 37 (2018), Number 2 GazeDirector: Fully Articulated Eye Gaze Redirection in Video ID: paper1004"
+165abb6fdbadae997135feec447fc825edb31c6c,Dimensionality Reduction with Simultaneous Sparse Approximations,"SCHOOL OF ENGINEERING - STI +SIGNAL PROCESSING INSTITUTE +EffrosyniKokiopoulouandPascalFrossard +CH-1015 LAUSANNE +Telephone: +41216932601 +Telefax: +41216937600 +e-mail: +ÉCOLE POLYTECHNIQUE(cid:13) +FÉDÉRALE DE LAUSANNE +DIMENSIONALITY REDUCTION WITH +SIMULTANEOUS SPARSE APPROXIMATIONS +Effrosyni Kokiopoulou and Pascal Frossard +Swiss Federal Institute of Technology Lausanne (EPFL) +Signal Processing Institute Technical Report +TR-ITS-2006.010 +October 21st, 2006 +Part of this work has been submitted to IEEE TMM. +This work has been supported by the Swiss NSF, under grants PP-002-68737, and NCCR IM2."
162c33a2ec8ece0dc96e42d5a86dc3fedcf8cd5e,Large-Scale Classification by an Approximate Least Squares One-Class Support Vector Machine Ensemble,"Mygdalis, V., Iosifidis, A., Tefas, A., & Pitas, I. (2016). Large-Scale Classification by an Approximate Least Squares One-Class Support Vector of a meeting held 20-22 August 2015, Helsinki, Finland (Vol. 2, pp. 6-10). @@ -6679,9 +22719,51 @@ General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms"
+16e8b0a1e8451d5f697b94c0c2b32a00abee1d52,UMB-DB: A database of partially occluded 3D faces,"UMB-DB +A Database of Partially Occluded 3D Faces +Alessandro Colombo +Claudio Cusano +Raimondo Schettini +Universit`a degli Studi di Milano-Bicocca +3 November 2011"
+16bd481fb66259df9c4c22b54797d8e8adc910fc,Robustifying Descriptor Instability Using Fisher Vectors,"Robustifying Descriptor Instability +using Fisher Vectors +Ivo Everts, Jan C. van Gemert, Thomas Mensink, Theo Gevers, Member, IEEE"
+1654fadee3e70d744a4eb231932b87c41c1e3ae5,Survey on Emotional Body Gesture Recognition,"JOURNAL OF IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. XX, NO. X, XXX 201X +Survey on Emotional Body Gesture Recognition +Fatemeh Noroozi, Ciprian Adrian Corneanu, Dorota Kami´nska, Tomasz Sapi´nski, Sergio Escalera, +nd Gholamreza Anbarjafari,"
+161eb9ecc119952c137959e87a796da0f3c62cd1,Eye tracking in early autism research,"Falck-Ytter et al. Journal of Neurodevelopmental Disorders 2013, 5:28 +http://www.jneurodevdisorders.com/content/5/1/28 +R EV I E W +Eye tracking in early autism research +Terje Falck-Ytter1,2*, Sven Bölte1,3 and Gustaf Gredebäck2 +Open Access"
+16647dc1bc87ba1e7b8bcd7e1ea8ccebcfe20fa5,Psychometric properties of reaction time based experimental paradigms measuring anxiety-related information-processing biases in children,"PDF hosted at the Radboud Repository of the Radboud University +Nijmegen +The following full text is a publisher's version. +For additional information about this publication click this link. +http://repository.ubn.ru.nl/handle/2066/126858 +Please be advised that this information was generated on 2018-10-16 and may be subject to +hange."
+1670729d1edc9bc6103ee823f1137d302be41397,Patch-based Object Recognition Using Discriminatively Trained Gaussian Mixtures,"Patch-based Object Recognition Using +Discriminatively Trained Gaussian Mixtures +Andre Hegerath, Thomas Deselaers, and Hermann Ney +Human Language Technology and Pattern Recognition Group, +RWTH Aachen University – D-52056 Aachen, Germany +{hegerath, deselaers,"
+16bfd904f5a76bb52d5cd8a25721277047a02e89,Blindfold Baselines for Embodied QA,"Blindfold Baselines for Embodied QA +Ankesh Anand1 Eugene Belilovsky1 Kyle Kastner1 Hugo Larochelle2,1 Aaron Courville1,3 +Mila +Google Brain 3CIFAR Fellow"
161eb88031f382e6a1d630cd9a1b9c4bc6b47652,Automatic facial expression recognition using features of salient facial patches,"Automatic Facial Expression Recognition Using Features of Salient Facial Patches S L Happy and Aurobinda Routray"
+16f48e8b7f1f6c03c888e3f4664ce3fa1261296b,Steganographic Generative Adversarial Networks,"Steganographic Generative Adversarial Networks +Denis Volkhonskiy1,2,3, Ivan Nazarov1,2, Boris Borisenko3 and Evgeny Burnaev1,2,3 +Skolkovo Institute of Science and Technology +The Institute for Information Transmission Problems RAS (Kharkevich Institute) +National Research University Higher School of Economics (HSE)"
4209783b0cab1f22341f0600eed4512155b1dee6,Accurate and Efficient Similarity Search for Large Scale Face Recognition,"Accurate and Efficient Similarity Search for Large Scale Face Recognition Ce Qi Zhizhong Liu @@ -6692,6 +22774,116 @@ EECS, UC Berkeley {mano, ranzato, Facebook AI Research {nzhang,"
+422fc05b3ef72e96c87b9aa4190efa7c7fb8c170,Preprocessing Technique for Face Recognition Applications under Varying Illumination Conditions,"Global Journal of Computer Science and Technology +Graphics & Vision +Volume 12 Issue 11 Version 1.0 Year 2012 +Type: Double Blind Peer Reviewed International Research Journal +Publisher: Global Journals Inc. (USA) +Online ISSN: 0975-4172 & Print ISSN: 0975-4350 +Preprocessing Technique for Face Recognition Applications +under Varying Illumination Conditions +By S.Anila & Dr.N.Devarajan +Sri Ramakrishna Institute of Technology, Coimbatore-10, Tamil Nadu, India"
+42c645df49106b68a71abe757ac13245db4be394,A New Method of Illumination Normalization for Robust Face Recognition,"A New Method of Illumination Normalization +for Robust Face Recognition +Young Kyung Park, Bu Cheon Min, and Joong Kyu Kim +School of Information and Communication Engineering, SungKyunKwan University. +00, Chun-Chun-Dong, Chang-An-Ku, Suwon, Korea 440-746 +{multipym,"
+4244d3340304b114e5c00e7b5797d2338a5c2b82,Face Recognition Using Local Texture Feature,"International Journal of Computer Engineering and Applications, +Volume XII, Issue I, Jan. 18, www.ijcea.com ISSN 2321-3469 +FACE RECOGNITION USING LOCAL TEXTURE FEATURE +Pavan.M 1, Sayed Aftab Ahamed 2 +Dept. of Information Science & engineering, J.N.N.C.E +Shimoga, Karnataka, India"
+429b8d5bb05e1a580fad0222b9e9496985465e40,"See No Evil, Say No Evil: Description Generation from Densely Labeled Images","Proceedings of the Third Joint Conference on Lexical and Computational Semantics (*SEM 2014), pages 110–120, +Dublin, Ireland, August 23-24 2014. +(Count:3) Isa: ride, vehicle,… Doing: parking,… Has: steering wheel,… Attrib: black, shiny,… children (Count:2) Isa: kids, children … Doing: biking, riding … Has: pants, bike … Attrib: young, small … bike (Count:1) Isa: bike, bicycle,… Doing: playing,… Has: chain, pedal,… Attrib: silver, white,… women(Count:3) Isa: girls, models,… Doing: smiling,... Has: shorts, bags,… Attrib: young, tan,… purses(Count:3) Isa: accessory,… Doing: containing,… Has: body, straps,… Attrib: black, soft,… sidewalk(Count:1) Isa: sidewalk, street,… Doing: laying,… Has: stone, cracks,… Attrib: flat, wide,… woman(Count:1) Isa: person, female,… Doing: pointing,… Has: nose, legs,… Attrib: tall, skinny,… tree(Count:1) Isa: plant,… Doing: growing,… Has: branches,… Attrib: tall, green,… kids(Count:5) Isa: group, teens,… Doing: walking,… Has: shoes, bags,… Attrib: young,… Fiveyoungpeopleonthestreet,twosharingabicycle.Severalyoungpeoplearewalkingnearparkedvehicles.Threegirlswithlargehandbagswalkingdownthesidewalk.Threewomenwalkdownacitystreet,asseenfromabove.Threeyoungwomanwalkingdownasidewalklookingup.Figure1:Anannotatedimagewithhumangeneratedsen-tencedescriptions.Eachboundingpolygonencompassesoneormoreobjectsandisassociatedwithacountandtextla-bels.Thisimagehas9highlevelobjectsannotatedwithover250textuallabels.tomuchofthevisualcontentneededtogeneratecomplete,human-likesentences.Inthispaper,weinsteadstudygenerationwithmorecompletevisualsupport,asprovidedbyhu-manannotations,allowingustodevelopmorecomprehensivemodelsthanpreviouslyconsid-ered.Suchmodelshavethedualbenefitof(1)providingnewinsightsintohowtoconstructmorehuman-likesentencesand(2)allowingustoper-formexperimentsthatsystematicallystudythecontributionofdifferentvisualcuesingeneration,suggestingwhichautomaticdetectorswouldbemostbeneficialforgeneration.Inanefforttoapproximaterelativelycompletevisualrecognition,wecollectedmanuallylabeledrepresentationsofobjects,parts,attributesandac-tivitiesforabenchmarkcaptiongenerationdatasetthatincludesimagespairedwithhumanauthored"
+421387011b5cdd2cb4a1fdf04728d350741a0ac1,Incidental memory for faces in children with different genetic subtypes of Prader-Willi syndrome,"Social Cognitive and Affective Neuroscience, 2017, 918–927 +doi: 10.1093/scan/nsx013 +Advance Access Publication Date: 17 February 2017 +Original article +Incidental memory for faces in children with different +genetic subtypes of Prader-Willi syndrome +Alexandra P. Key,1,2 and Elisabeth M. Dykens1,3 +Vanderbilt Kennedy Center for Research on Human Development, 2Department of Hearing and Speech +Sciences, Vanderbilt University Medical Center, and 3Department of Psychology and Human Development, +Vanderbilt University, Nashville, TN 37203, USA +Correspondence should be addressed to Alexandra P. Key, Vanderbilt Kennedy Center, Peabody Box 74, Vanderbilt University, Nashville, TN 37203, USA. +E-mail:"
+42f4653f0693f16e087e4b913407d9b0278154c9,3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning,"D Human Action Recognition with Siamese- +LSTM Based Deep Metric Learning +VisLab, Department of Computer Engineering, Gebze Technical University, Kocaeli, Turkey +Seyma Yucer and Yusuf Sinan Akgul +Email: {syucer,"
+42afe5fd3f7b1d286a20e9306c6bc8624265f658,Face Detection Using the 3×3 Block Rank Patterns of Gradient Magnitude Images,"Signal & Image Processing : An International Journal (SIPIJ) Vol.4, No.5, October 2013 +FACE DETECTION USING THE 3×3 BLOCK RANK +PATTERNS OF GRADIENT MAGNITUDE IMAGES +Kang-Seo Park, Young-Gon Kim, and Rae-Hong Park +Department of Electronic Engineering, School of Engineering, Sogang University, +5 Baekbeom-ro (Sinsu-dong), Mapo-gu, Seoul 121-742, Korea"
+4213502d0f226b9845b00c2882851ba4c57742ab,Does Rabbit Antithymocyte Globulin (Thymoglobuline®) Have a Role in Avoiding Delayed Graft Function in the Modern Era of Kidney Transplantation?,"Hindawi +Journal of Transplantation +Volume 2018, Article ID 4524837, 11 pages +https://doi.org/10.1155/2018/4524837 +Review Article +Does Rabbit Antithymocyte Globulin (ThymoglobulineD) +Have a Role in Avoiding Delayed Graft Function in the Modern +Era of Kidney Transplantation? +Lluís Guirado +Department of Renal Transplantation, Fundaci´o Puigvert, Barcelona, Spain +Correspondence should be addressed to Llu´ıs Guirado; +Received 12 April 2018; Accepted 20 June 2018; Published 12 July 2018 +Academic Editor: Andreas Zuckermann +Copyright © 2018 Llu´ıs Guirado. This is an open access article distributed under the Creative Commons Attribution License, which +permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +Delayed graft function (DGF) increases the risk of graft loss by up to 40%, and recent developments in kidney donation have +increased the risk of its occurrence. Lowering the risk of DGF, however, is challenging due to a complicated etiology in which +ischemia-reperfusion injury (IRI) leads to acute tubular necrosis. Among various strategies explored, the choice of induction +therapy is one consideration. Rabbit antithymocyte globulin (rATG [Thymoglobuline]) has complex immunomodulatory effects +that are relevant to DGF. In addition to a rapid and profound T-cell depletion, rATG inhibits leukocyte migration and adhesion."
+4265269bc894caa97efbfcfe5b83da7413f86a30,Asymmetric Tri-training for Unsupervised Domain Adaptation,"Asymmetric Tri-training for Unsupervised Domain Adaptation +Kuniaki Saito 1 Yoshitaka Ushiku 1 Tatsuya Harada 1"
+42f8ef9d5ebf969a7e2b4d1eef4b332db562e5d4,Which Training Methods for GANs do actually Converge?,"Which Training Methods for GANs do actually Converge? +Lars Mescheder 1 Andreas Geiger 1 2 Sebastian Nowozin 3"
+42cc8637a5e7b8203722ba0dca995814f6dfd525,PETS 2016: Dataset and Challenge,"PETS 2016: Dataset and Challenge +Luis Patino*, Tom Cane**, Alain Vallee*** and James Ferryman* +*University of Reading, Computational Vision Group, Reading RG6 6AY, United Kingdom, +{j.l.patinovilchis, +**BMT Group Ltd., Teddington TW11 8LZ. United Kingdom, +***SAGEM, 92659 Boulogne-Billancourt, France,"
+4212a93f011aa47c6344c0cdc3e991740d8c7c04,Zero-Shot Kernel Learning,"Zero-Shot Kernel Learning +Hongguang Zhang∗,2,1 +Piotr Koniusz∗,1,2 +Data61/CSIRO, 2Australian National University +nu.edu.au2}"
+426b47af132293e9ffe6071a3ede59cfdc1aa3fb,Promoting social behavior with oxytocin in high-functioning autism spectrum disorders.,"Promoting social behavior with oxytocin in high- +functioning autism spectrum disorders +Elissar Andaria, Jean-René Duhamela, Tiziana Zallab, Evelyn Herbrechtb, Marion Leboyerb, and Angela Sirigua,1 +Centre de Neuroscience Cognitive, Unité Mixte de Recherche 5229, Centre National de la Recherche Scientifique, 69675 Bron, France; and bInstitut National +de la Santé et de la Recherche Médicale U 841, Department of Psychiatry, Hôpital Chenevier-Mondor, 94000 Créteil, France +Edited by Leslie G. Ungerleider, National Institute of Mental Health, Bethesda, MD, and approved January 7, 2010 (received for review September 8, 2009) +Social adaptation requires specific cognitive and emotional compe- +tences. Individuals with high-functioning autism or with Asperger +syndrome cannot understand or engage in social situations despite +preserved intellectual abilities. Recently, it has been suggested that +oxytocin, a hormone known to promote mother-infant bonds, may +e implicated in the social deficit of autism. We investigated the +ehavioral effects of oxytocin in 13 subjects with autism. +simulated ball game where participants interacted with fictitious +partners, we found that after oxytocin inhalation, patients +exhibited stronger interactions with the most socially cooperative +partner and reported enhanced feelings of trust and preference. +Also, during free viewing of pictures of faces, oxytocin selectively +increased patients’ gazing time on the socially informative region of +the face, namely the eyes. Thus, under oxytocin, patients respond"
+423e8cc1a7501066b7e0e5bb1beb5b9592337023,Accurate eye center localization using Snakuscule,"Accurate Eye Center Localization using Snakuscule +Abhinav Tripathi +Microsoft Research India +Edward Cutrell +Microsoft Research India +Sanyam Garg +Microsoft Research India"
42cc9ea3da1277b1f19dff3d8007c6cbc0bb9830,Coordinated Local Metric Learning,"Coordinated Local Metric Learning Shreyas Saxena Jakob Verbeek @@ -6700,7 +22892,68 @@ Inria∗" for Face Recognition Shuicheng Yan, Member, IEEE, Dong Xu, Qiang Yang, Senior Member, IEEE, Lei Zhang, Member, IEEE, Xiaoou Tang, Senior Member, IEEE, and Hong-Jiang Zhang, Fellow, IEEE"
+42e793b1dd6669b74ad106071c432aa5015b8631,How do people think about interdependence? A multidimensional model of subjective outcome interdependence.,"tapraid5/z2g-perpsy/z2g-perpsy/z2g99917/z2g4623d17z +xppws S⫽1 +8/10/17 +:53 Art: 2016-0710 +APA NLM +017, Vol. 0, No. 999, 000 +0022-3514/17/$12.00 +© 2017 American Psychological Association +http://dx.doi.org/10.1037/pspp0000166 +How Do People Think About Interdependence? A Multidimensional Model +of Subjective Outcome Interdependence +Fabiola H. Gerpott, Daniel Balliet, +Simon Columbus, and Catherine Molho +Vrije Universiteit Amsterdam +Reinout E. de Vries +Vrije Universiteit Amsterdam and University of Twente +Interdependence is a fundamental characteristic of social interactions. Interdependence Theory states that +6 dimensions describe differences between social situations. Here we examine if these 6 dimensions +describe how people think about their interdependence with others in a situation. We find that people (in +situ and ex situ) can reliably differentiate situations according to 5, but not 6, dimensions of interde-"
42e155ea109eae773dadf74d713485be83fca105,Sparse reconstruction of facial expressions with localized gabor moments,
+423aacfe7467961e32f012bc6de10d636ebc0236,Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES +http://www.merl.com +Breaking the Interactive Bottleneck in +Multi-Class Classification with Active +Selection and Binary Feedback +Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoulos +TR2010-037 +July 2010"
+42b56c77e4b154364763d4024baa8129da75151f,Deep Detection of People and their Mobility Aids for a Hospital Robot,"Deep Detection of People and their Mobility Aids for a Hospital Robot +Andres Vasquez +Marina Kollmitz +Andreas Eitel +Wolfram Burgard"
+4297deda7ea77fb90de2509c763738584b2353de,Beyond one billion time series: indexing and mining very large time series collections with $$i$$ SAX2+,"Knowl Inf Syst +DOI 10.1007/s10115-012-0606-6 +REGULAR PAPER +Beyond one billion time series: indexing and mining very +large time series collections with iSAX2+ +Alessandro Camerra · Jin Shieh · Themis Palpanas · +Thanawin Rakthanmanon · Eamonn Keogh +Received: 23 March 2012 / Revised: 23 September 2012 / Accepted: 28 December 2012 +© Springer-Verlag London 2013"
+423e0f595365640b653c1195749e01394cbcd937,Web-Scale Responsive Visual Search at Bing,"Web-Scale Responsive Visual Search at Bing +Houdong Hu, Yan Wang, Linjun Yang, Pavel Komlev, Li Huang, +Xi (Stephen) Chen, Jiapei Huang, Ye Wu, Meenaz Merchant, Arun Sacheti +Microsoft +Redmond, Washington"
+424e918134ed7c70fa73450bd6af1bd982071a27,Final Report : Localized object detection with Convolutional Neural Networks,"Final Report: Localized object detection with Convolutional +Computer Vision +Neural Networks +Bardia Doosti +Vijay Hareesh Avula +May 5, 2016"
+428e42f8d5cbffc068e2e5fe8f697c9c9ee113a9,Deep Multimodal Subspace Clustering Networks,"IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, VOL. X, NO. X, SEPTEMBER 21, 2018 +Deep Multimodal Subspace Clustering Networks +Mahdi Abavisani, Student Member, IEEE and Vishal M. Patel, Senior Member, IEEE"
+42d8a6b1ef5acaaf4640a8974c6f99d60b56090c,Markerless Motion Capture of Multiple Characters Using Multiview Image Segmentation,"SUBMIT TO IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. XX, NO. XX, AUGUST 2012 +Markerless Motion Capture of Multiple Characters +Using Multi-view Image Segmentation +Yebin Liu, Juergen Gall Member, IEEE, Carsten Stoll, Qionghai Dai Senior Member, IEEE, +Hans-Peter Seidel, and Christian Theobalt"
4270460b8bc5299bd6eaf821d5685c6442ea179a,"Partial Similarity of Objects, or How to Compare a Centaur to a Horse","Int J Comput Vis (2009) 84: 163–183 DOI 10.1007/s11263-008-0147-3 Partial Similarity of Objects, or How to Compare a Centaur @@ -6709,11 +22962,37 @@ Alexander M. Bronstein · Michael M. Bronstein · Alfred M. Bruckstein · Ron Kimmel Received: 30 September 2007 / Accepted: 3 June 2008 / Published online: 26 July 2008 © Springer Science+Business Media, LLC 2008"
+426840ccf74bbd8b087cf357efdb80ecc85ea2ab,Reduced Analytic Dependency Modeling: Robust Fusion for Visual Recognition,"Noname manuscript No. +(will be inserted by the editor) +Reduced Analytic Dependency Modeling: Robust Fusion for Visual +Recognition +Andy J Ma · Pong C Yuen +Received: date / Accepted: date"
+422d352a7d26fef692a3cd24466bfb5b4526efea,Pedestrian interaction in tracking: the social force model and global optimization methods,"Pedestrian interaction in tracking: the social +force model and global optimization methods +Laura Leal-Taix´e and Bodo Rosenhahn"
429d4848d03d2243cc6a1b03695406a6de1a7abd,"Face Recognition based on Logarithmic Fusion of SVD and KT Ramachandra A C , Raja K B , Venugopal K R , L M Patnaik","Face Recognition based on Logarithmic Fusion International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-2, Issue-3, July 2012 of SVD and KT Ramachandra A C, Raja K B, Venugopal K R, L M Patnaik"
+42ab6c438bf5a6e0e74cc2dd9192a12f2406ca33,Nonlinear Dimensionality Reduction by Manifold Unfolding,"Nonlinear Dimensionality Reduction +y Manifold Unfolding +Pooyan Khajehpour Tadavani +A thesis +presented to the University of Waterloo +in fulfillment of the +thesis requirement for the degree of +Doctor of Philosophy +Computer Science +Waterloo, Ontario, Canada, 2013 +(cid:13) Pooyan Khajehpour Tadavani 2013"
+4273a9d1605a69ac66440352b92ebeb230fd34f6,Simple Test Procedure for Image-Based Biometric Veri cation Systems,"SimpleTestProcedureforImage-BasedBiometric +Veri(cid:12)cationSystems +C.L.Wilson,R.M.McCabe +InformationTechnologyLaboratory +NationalInstituteofStandardsandTechnology +Gaithersburg,MD 42dc36550912bc40f7faa195c60ff6ffc04e7cd6,Visible and Infrared Face Identification via Sparse Representation,"Hindawi Publishing Corporation ISRN Machine Vision Volume 2013, Article ID 579126, 10 pages @@ -6734,6 +23013,38 @@ ited. We present a facial recognition technique based on facial sparse representation. A dictionary is learned from data, and patches extracted from a face are decomposed in a sparse manner onto this dictionary. We particularly focus on the design of dictionaries that play a crucial role in the final identification rates. Applied to various databases and modalities, we show that this approach"
+42e0d7fe2039b075ac2372d883fa994eb0a68b48,Learning human actions in video,"Learning human actions in video +Alexander Klaser +To cite this version: +Alexander Klaser. Learning human actions in video. Modeling and Simulation. Institut Na- +tional Polytechnique de Grenoble - INPG, 2010. English. <tel-00514814> +HAL Id: tel-00514814 +https://tel.archives-ouvertes.fr/tel-00514814 +Submitted on 3 Sep 2010 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de +recherche fran¸cais ou ´etrangers, des laboratoires +publics ou priv´es."
+424e52158b43e40f356af7eafb35c91a9e13db30,"Impact Factor : 3 . 449 ( ISRA ) , Impact Factor : 2 .","[Randive, 4(1): January, 2015] +ISSN: 2277-9655 +Scientific Journal Impact Factor: 3.449 +(ISRA), Impact Factor: 2.114 +IJESRT +INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH +TECHNOLOGY +AN INNOVATIVE APPROACH FOR PLASTIC SURGERY FACE RECOGNITION-A +Mahendra P. Randive *, Prof. Umesh W. Hore +REVIEW +*Student of M.E. Department of Electronics & Telecommunication Engineering, P. R. Patil College of +Engineering, Amravati Maharashtra – India."
42ecfc3221c2e1377e6ff849afb705ecd056b6ff,Pose Invariant Face Recognition Under Arbitrary Unknown Lighting Using Spherical Harmonics,"Pose Invariant Face Recognition under Arbitrary Unknown Lighting using Spherical Harmonics Lei Zhang and Dimitris Samaras @@ -6745,10 +23056,57 @@ JUNE 2000 Evolutionary Pursuit and Its Application to Face Recognition Chengjun Liu, Member, IEEE, and Harry Wechsler, Fellow, IEEE"
+42832bcb36ee3f69327c38d0d17e6e2a73aaa2a6,SUN Database: Exploring a Large Collection of Scene Categories,"Int J Comput Vis +DOI 10.1007/s11263-014-0748-y +SUN Database: Exploring a Large Collection of Scene Categories +Jianxiong Xiao · Krista A. Ehinger · James Hays · +Antonio Torralba · Aude Oliva +Received: 9 June 2013 / Accepted: 2 July 2014 +© Springer Science+Business Media New York 2014"
+423cfa55a14cd92ada32245b416b587ef9c29308,Visually-Grounded Bayesian Word Learning,"Visually-Grounded Bayesian Word Learning +Yangqing Jia +Joshua Abbott +Joseph Austerweil +Thomas Griffiths +Trevor Darrell +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2012-202 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-202.html +October 17, 2012"
+4263630a35c5ee34ccf9dbd81c0541d92d0c7d5b,Shape Variation-Based Frieze Pattern for Robust Gait Recognition,"Shape Variation-Based Frieze Pattern for Robust Gait Recognition +Seungkyu Lee* Yanxi Liu* Robert Collins +Dept. of Computer Science and Eng. *Dept. of Electrical Eng. +The Penn State University"
42df75080e14d32332b39ee5d91e83da8a914e34,Illumination Compensation Using Oriented Local Histogram Equalization and its Application to Face Recognition,"Illumination Compensation Using Oriented Local Histogram Equalization and Its Application to Face Recognition Ping-Han Lee, Szu-Wei Wu, and Yi-Ping Hung"
+421b3a33ec70af2d733310f6c83ad713a314951d,Using nasal curves matching for expression robust 3D nose recognition,"Emambakhsh, M., Evans, A. and Smith, M. (2013) Using nasal curves +matching for expression robust 3D nose recognition. In: IEEE Con- +ference on Biometrics: Theory, Applications and Systems (BTAS2013), +Washington DC, USA, September 29th - October 2, 2013. Available +from: http://eprints.uwe.ac.uk/20812 +We recommend you cite the published version. +The publisher’s URL is: +http://eprints.uwe.ac.uk/20812/ +Refereed: Yes +(no note) +Disclaimer +UWE has obtained warranties from all depositors as to their title in the material +deposited and as to their right to deposit such material. +UWE makes no representation or warranties of commercial utility, title, or fit- +ness for a particular purpose or any other warranty, express or implied in respect +of any material deposited. +UWE makes no representation that the use of the materials will not infringe +ny patent, copyright, trademark or other property or proprietary rights. +UWE accepts no liability for any infringement of intellectual property rights +in any material deposited but will remove such material from public view pend-"
+896e2776174dcb86d311789ab83a266151d0595b,A Novel Performance Evaluation Methodology for Single-Target Trackers,"A Novel Performance Evaluation Methodology +for Single-Target Trackers +Matej Kristan, Member, IEEE, Jiri Matas, Aleˇs Leonardis, Member, IEEE, Tom´aˇs Voj´ıˇr, +Roman Pflugfelder, Gustavo Fern´andez, Georg Nebehay, Fatih Porikli and +Luka ˇCehovin Member, IEEE,"
89945b7cd614310ebae05b8deed0533a9998d212,Divide-and-Conquer Method for L1 Norm Matrix Factorization in the Presence of Outliers and Missing Data,"Divide-and-Conquer Method for L1 Norm Matrix Factorization in the Presence of Outliers and Missing Data @@ -6816,19 +23174,91 @@ your reasons. In case of a legitimate complaint, the Library will make the mater the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Download date: 04 Aug 2017"
+89f9225a7223133fa687e1c44bb758c3567f4f26,F3-F: A System Theoretic Approach to Robust Detection Of Potential Threats from Video,"F3-F: A System Theoretic Approach to Robust +Detection Of Potential Threats from Video"
+8966af6a8049192556e9c9356886a135595c19b8,Temporally Coherent CRP: A Bayesian Non-Parametric Approach for Clustering Tracklets with applications to Person Discovery in Videos,"Temporally Coherent CRP: A Bayesian Non-Parametric Approach for +Clustering Tracklets with applications to Person Discovery in Videos +Adway Mitra∗ +Soma Biswas† +Chiranjib Bhattacharyya‡"
+8949563597276246f9f480d4b38b3b7851fd5495,Toward Efficient and Robust Large-scale Structure-from-motion Systems,"TOWARD EFFICIENT AND ROBUST LARGE-SCALE +STRUCTURE-FROM-MOTION SYSTEMS +Jared S. Heinly +A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial +fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of +Computer Science. +Chapel Hill +Approved by: +Jan-Michael Frahm +Enrique Dunn +Alexander C. Berg +Marc Niethammer +Sameer Agarwal"
8913a5b7ed91c5f6dec95349fbc6919deee4fc75,BigBIRD: A large-scale 3D database of object instances,"BigBIRD: A Large-Scale 3D Database of Object Instances Arjun Singh, James Sha, Karthik S. Narayan, Tudor Achim, Pieter Abbeel"
89d3a57f663976a9ac5e9cdad01267c1fc1a7e06,Neural Class-Specific Regression for face verification,"Neural Class-Specific Regression for face verification Guanqun Cao, Alexandros Iosifidis, Moncef Gabbouj"
+89a245eae1e7eda7aa8e360c0cdb4bf6a72da225,A Survey of Pedestrian Detection in Video,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 5, No. 10, 2014 +A Survey of Pedestrian Detection in Video +Achmad Solichin +Department of Informatics +Budi Luhur University +Jakarta, Indonesia +Agus Harjoko +Agfianto Eko Putra +Dept. of Computer Science and +Dept. of Computer Science and +Electronics Gadjah Mada University +Electronics Gadjah Mada University +Yogyakarta, Indonesia +Yogyakarta, Indonesia"
+8948e9dce2dfaeb1d93ce146fab5364b6cd342c9,Dual Attention Network for Scene Segmentation,"Dual Attention Network for Scene Segmentation +Jun Fu, Jing Liu, Haijie Tian, Zhiwei Fang, Hanqing Lu +{jun.fu, jliu, zhiwei.fang, +CASIA IVA"
89bc311df99ad0127383a9149d1684dfd8a5aa34,Towards ontology driven learning of visual concept detectors,"Towards ontology driven learning of visual concept detectors Sanchit ARORA, Chuck CHO, Paul FITZPATRICK, Franc¸ois SCHARFFE 1 Dextro Robotics, Inc. 101 Avenue of the Americas, New York, USA"
+8935ffe454758e2e5def0b5190de6e28c350b3b8,Learning to Reconstruct Face Geometries Research,"Learning to Reconstruct Face +Geometries +Elad Richardson +Technion - Computer Science Department - M.Sc. Thesis MSC-2017-11 - 2017"
+8961677300a9ee30ca51e1a3cf9815b4a162265b,Deep Representation Learning with Part Loss for Person Re-Identification,"Deep Representation Learning with Part Loss for Person Re-Identification +Hantao Yao, Shiliang Zhang, Yongdong Zhang, Jintao Li, Qi Tian"
+89f44f756c230e104cdf2ec0152d5f015586399c,Wide-area Based Traffic Situation Detection at an Ungated Level Crossing,"M. Junghans, et al., Int. J. of Safety and Security Eng., Vol. 6, No. 2 (2016) 383–393 +WIDE-AREA BASED TRAFFIC SITUATION DETECTION +AT AN UNGATED LEVEL CROSSING +M. JUNGHANS, A. LEICH, K. KOZEMPEL, H. SAUL & S. KNAKE-LANGHORST +Institute of Transportation Systems, German Aerospace Center (DLR), Berlin, Germany."
+89e324b9c64a800e57ad82eddecc03f2cc0b7cc5,Long-Term Identity-Aware Multi-Person Tracking for Surveillance Video Summarization,"Long-Term Identity-Aware Multi-Person Tracking +for Surveillance Video Summarization +Shoou-I Yu, Yi Yang, Xuanchong Li, and Alexander G. Hauptmann"
+89174737423d87258d3b9d5a660236a0bb66a470,On the usage of Sensor Pattern Noise for Picture-to-Identity linking through social network accounts,"On the usage of Sensor Pattern Noise for Picture-to-Identity linking +through social network accounts +Riccardo Satta1 and Pasquale Stirparo1,2 +Institute for the Protection and Security of the Citizen +Joint Research Centre (JRC), European Commission, Ispra (VA), Italy +Royal Institute of Technology (KTH), Stockholm, Sweden +{riccardo.satta, +Keywords: +social network, account, Sensor Pattern Noise, identity, linking, digital image forensics, multimedia forensics"
+8929e704b6af7f09ad027714b75972cb9df57483,Image Inpainting for Irregular Holes Using Partial Convolutions,
+894f1e924dfb8dfb843c42835fa79e386ac07383,Dimensional emotion recognition using visual and textual cues,"Dimensional emotion recognition using visual and textual cues +Pedro M. Ferreira1, Diogo Pernes2, Kelwin Fernandes1, Ana Rebelo3 and Jaime S. Cardoso1"
898a66979c7e8b53a10fd58ac51fbfdb6e6e6e7c,Dynamic vs. Static Recognition of Facial Expressions,"Dynamic vs. Static Recognition of Facial Expressions No Author Given No Institute Given"
+89d590d7013433304aae1c97debd257b8dd801fa,Outdoor Human Motion Capture by Simultaneous Optimization of Pose and Camera Parameters,"Volume xx (200y), Number z, pp. 1–13 +Outdoor Human Motion Capture by Simultaneous +Optimization of Pose and Camera Parameters +A. Elhayek C. Stoll K. I. Kim and C. Theobalt +Max-Planck-Institute for Informatics, Saarbrücken, Germany +Figure 1: Examples of multi-person tracking with moving cameras. (Left two images) two actors, and two moving and 3 static +ameras (Soccer1). (Right two images) One actor, and three moving and two static cameras (Walk2)."
89d7cc9bbcd2fdc4f4434d153ecb83764242227b,Face-Name Graph Matching For The Personalities In Movie Screen,"Einstein.J, DivyaBaskaran / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 2, March -April 2013, pp.351-355 @@ -6838,6 +23268,34 @@ Screen Einstein.J*, DivyaBaskaran** ** (Final Year Student, M.Tech IT, Vel Tech Dr. RR &Dr. SR Technical University, Chennai.) Chennai.)"
+890103cb8d3d869298421da817d0a181487ec79a,Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization,"Learning the Hierarchical Parts of Objects by Deep +Non-Smooth Nonnegative Matrix Factorization +Jinshi Yu, Guoxu Zhou, Andrzej Cichocki +IEEE Fellow, and Shengli Xie IEEE Senior Member"
+89358e65aec4d6665098c7dbbe3975296cc7a2fc,Discriminative Feature Based Algorithm for Detecting And Classifying Frames In Image Sequences,"M. A. A Victoria et al. Int. Journal of Engineering Research and Applications www.ijera.com +Vol. 3, Issue 5, Sep-Oct 2013, pp.446-450 +RESEARCH ARTICLE OPEN ACCESS +Discriminative Feature Based Algorithm for Detecting And +Classifying Frames In Image Sequences +M. Antony Arockia Victoria, R. Sahaya Jeya Sutha +B.E,M.E. Assistant Professor, Department of MCA, Dr.Sivanthi Aditanar College of Engineering, +MCA,M.Phil. Assistant Professor, Department of MCA, Dr. Sivanthi Aditanar College of Engineering"
+8954d46e1d7a11b20b2c688e5fb8bce4901650d6,Looking at movies and cartoons: eye-tracking evidence from Williams syndrome and autism.,"Looking at Movies and Cartoons: Eye-tracking evidence from Williams syndrome +nd Autism +Deborah M Riby and Peter J B Hancock +Journal of Intellectual Disability Research +http://dx.doi.org/10.1111/j.1365-2788.2008.01142.x"
+89d02ceae9e972eca633ae6ff9da9ee8a85fb171,Using Explanations to Improve Ensembling of Visual Question Answering Systems,"In Proceedings of the IJCAI 2017 Workshop on Explainable Artificial +Intelligence (XAI), pp. 43-47, Melbourne, Australia, August 2017."
+89742f28108330f97df94df98f73b459b02ca33d,Query Specific Semantic Signature for Improved Web Image Re - Ranking,"International Journal of Engineering and Technical Research (IJETR) +ISSN: 2321-0869, Volume-3, Issue-3, March 2015 +Query Specific Semantic Signature for Improved +Web Image Re-Ranking +Joshith.K, S.Krishnamoorthi"
+89475b4d09e541e09becb9aa134c8de117725205,Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories,"Automatic Analysis of Facial Expressions Based on +Deep Covariance Trajectories +Naima Otberdout, Member, IEEE, Anis Kacem, Member, IEEE, Mohamed Daoudi, Senior, IEEE, +Lahoucine Ballihi, Member, IEEE, and Stefano Berretti, Senior, IEEE"
891b10c4b3b92ca30c9b93170ec9abd71f6099c4,2 New Statement for Structured Output Regression Problems,"Facial landmark detection using structured output deep neural networks Soufiane Belharbi ∗1, Cl´ement Chatelain∗1, Romain H´erault∗1, and S´ebastien @@ -6845,12 +23303,89 @@ Adam∗2 LITIS EA 4108, INSA de Rouen, Saint ´Etienne du Rouvray 76800, France LITIS EA 4108, UFR des Sciences, Universit´e de Rouen, France. September 24, 2015"
+455943924a98593655ae7197ee3835b9f6a3b778,Visual SLAM for Automated Driving: Exploring the Applications of Deep Learning,"Visual SLAM for Automated Driving: +Exploring the Applications of Deep Learning +Stefan Milz, Georg Arbeiter, Christian Witt +Valeo Schalter und Sensoren GmbH +Bassam Abdallah +Valeo Vision, Bobigny +stefan.milz, georg.arbeiter, +Senthil Yogamani +Valeo Vision Systems, Ireland"
+45379046c6c1311dfa6d8e1941b3e2c7971ca2bc,An alternating direction and projection algorithm for structure-enforced matrix factorization,"Noname manuscript No. +(will be inserted by the editor) +An Alternating Direction and Projection Algorithm +for Structure-enforced Matrix Factorization +Lijun Xu · Bo Yu · Yin Zhang +Received: date / Accepted: date"
+4572725e98f3e1b6f258c03643d74b69982aa39a,Semantic Cluster Unary Loss for Efficient Deep Hashing,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Semantic Cluster Unary Loss for Efficient Deep +Hashing +Shifeng Zhang, Jianmin Li, and Bo Zhang +hashing [15], [22], [27], [32], [38], [54] and semi-supervised +hashing [43]. Experiments convey that hashcodes learned by +(semi-)supervised hashing methods contain more semantic +information than those learned by the unsupervised ones."
+45ede580b1e402aae6832256586211a47c53afe3,Biometric Application: Texture and Shape Based 3d Face Recognition,"BIOMETRIC APPLICATION: TEXTURE AND SHAPE BASED 3D FACE +RECOGNITION +P.Manju Bala1 +Senior Assistant professor, +A.Kalaiselvi2 +Assistant Professor, +Department of Computer Science and Engineering, +Department of Computer Science and Engineering, +IFET College of Engineering, +Villupuram."
+451bf4124ec8a55b9112cf9cc167d304fa004924,Modelling State of Interaction from Head Poses for Social Human-Robot Interaction,"Modelling State of Interaction from Head Poses +for Social Human-Robot Interaction +Andre Gaschler +fortiss GmbH +Guerickstr. 25 +80805 München, Germany +Ingmar Kessler +fortiss GmbH +Guerickstr. 25 +80805 München, Germany +Kerstin Huth +Universität Bielefeld +Universitätsstr. 25 +3615 Bielefeld, Germany +Jan de Ruiter +Universität Bielefeld +Universitätsstr. 25 +3615 Bielefeld, Germany +ielefeld.de +Manuel Giuliani"
+45aefa11101129862e323958b62505700bc281ae,Unsupervised learning in generative models of occlusion,"Unsupervised Learning in Generative +Models of Occlusion +Dissertation +zur Erlangung des Doktorgrades +der Naturwissenschaften +vorgelegt beim Fachbereich Physik +der Johann Wolfgang Goethe-Universität +in Frankfurt am Main +Marc Henniges +us Frankfurt am Main +Frankfurt (2012) +(D 30)"
45c340c8e79077a5340387cfff8ed7615efa20fd,Assessment of the Emotional States of Students during e-Learning,
+457abee61182a320b301d73ecceff00d055f596e,Face Recognition Using Line Edge Map,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 24, NO. 6, +JUNE 2002 +Face Recognition Using Line Edge Map +Yongsheng Gao, Member, IEEE, and Maylor K.H. Leung, Member, IEEE"
+450e9f80a273df2cdaafd9ae3a9ff149950cc834,Human Pose Estimation using Histograms of Edge Directions,"Human Pose Estimation +using Histograms of Edge Directions +Andrès Koetsier +University of Twente HMI Department"
45e7ddd5248977ba8ec61be111db912a4387d62f,Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization,"CHEN ET AL.: ADVERSARIAL POSENET Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization Yu Chen1, Chunhua Shen2, Hao Chen2, Xiu-Shen Wei3, Lingqiao Liu2 and Jian Yang1"
+45f884c4c3bcdabdca46ee0e3794ce1631b9c558,Vision-based assessment of parkinsonism and levodopa-induced dyskinesia with pose estimation,"Vision-Based Assessment of Parkinsonism and +Levodopa-Induced Dyskinesia with Deep +Learning Pose Estimation +Michael H. Li, Tiago A. Mestre, Susan H. Fox, Babak Taati*"
4526992d4de4da2c5fae7a5ceaad6b65441adf9d,System for Medical Mask Detection in the Operating Room Through Facial Attributes,"System for Medical Mask Detection in the Operating Room Through Facial Attributes @@ -6874,6 +23409,43 @@ Tieniu Tan1,2,3 National Laboratory of Pattern Recognition, CASIA Center for Research on Intelligent Perception and Computing, CASIA Center for Excellence in Brain Science and Intelligence Technology, CAS"
+451d777ee33833a3b5eb6ba5292fae162c6d265f,Exploiting Feature Correlations by Brownian Statistics for People Detection and Recognition,"TRANSACTIONS ON CYBERNETICS +Exploiting Feature Correlations by Brownian +Statistics for People Detection and Recognition +Sławomir B ˛ak1, Marco San Biagio2, Ratnesh Kumar1, Vittorio Murino2 and François Brémond1 +STARS Lab, INRIA Sophia Antipolis Méditerranée, Sophia Antipolis, 06902 Valbonne, France +Pattern Analysis and Computer Vision (PAVIS), IIT IStituto Italiano di Tecnologia, 16163 Genova, Italy +Characterizing an image region by its feature inter-correlations is a modern trend in computer vision. In this paper, we introduce +new image descriptor that can be seen as a natural extension of a covariance descriptor with the advantage of capturing nonlinear +nd non-monotone dependencies. Inspired from the recent advances in mathematical statistics of Brownian motion, we can express +highly complex structural information in a compact and computationally efficient manner. We show that our Brownian covariance +descriptor can capture richer image characteristics than the covariance descriptor. Additionally, a detailed analysis of the Brownian +manifold reveals that in opposite to the classical covariance descriptor, the proposed descriptor lies in a relatively flat manifold, +which can be treated as a Euclidean. This brings significant boost in the efficiency of the descriptor. The effectiveness and the +generality of our approach is validated on two challenging vision tasks, pedestrian classification and person re-identification. The +experiments are carried out on multiple datasets achieving promising results. +Index Terms—brownian descriptor, covariance descriptor, pedestrian detection, re-identification. +I. INTRODUCTION +D ESIGNING proper image descriptors is a crucial step +in computer vision applications, including scene detec- +tion, target tracking and object recognition. A good descrip-"
+45e81d04d01ef1db78a04ef7a9472fd4cd6de84c,Variational learning of finite Beta-Liouville mixture models using component splitting,"Variational Learning of Finite Beta-Liouville Mixture Models Using +Component Splitting +Wentao Fan and Nizar Bouguila"
+4583d7d1d76dfe18e86e91f7438ce1a03cdcf68f,"""3D Face"": Biometric Template Protection for 3D Face Recognition","\3D Face"": Biometric Template Protection for +D Face Recognition +E.J.C. Kelkboom, B. G(cid:127)okberk, T.A.M. Kevenaar, A.H.M. Akkermans, and M. +van der Veen +Philips Research, High-Tech Campus 34, 5656AE, Eindhoven +femile.kelkboom, berk.gokberk, tom.kevenaar, ton.h.akkermans,"
+454ec30d0a491800458a52a5aa655eb76a28f4f5,3-D Object Recognition Using 2-D Views,"-D Object Recognition Using 2-D Views +Wenjing Li, Member, IEEE, George Bebis, Member, IEEE, and Nikolaos G. Bourbakis, Fellow, IEEE"
+45bedfcb562e48a64436ea3131bc91098eb93dab,Incremental update of biometric models in face-based video surveillance,"Incremental Update of Biometric Models in +Face-Based Video Surveillance +Miguel De-la-Torre∗†, Eric Granger∗, Paulo V. W. Radtke∗, Robert Sabourin∗, Dmitry O. Gorodnichy‡ +´Ecole de technologie sup´erieure, Montr´eal, Canada +Centro Universitario de Los Valles, Universidad de Guadalajara, Ameca, M´exico +Science and Engineering Directorate, Canada Border Services Agency, Ottawa, Canada"
4534d78f8beb8aad409f7bfcd857ec7f19247715,Transformation-Based Models of Video Sequences,"Under review as a conference paper at ICLR 2017 TRANSFORMATION-BASED MODELS OF VIDEO SEQUENCES @@ -6881,20 +23453,103 @@ Joost van Amersfoort ∗, Anitha Kannan, Marc’Aurelio Ranzato, Arthur Szlam, Du Tran & Soumith Chintala Facebook AI Research {akannan, ranzato, aszlam, trandu,"
+453e311c6de1285cd5ea6d93fd78a636eac0ba82,Multi patches 3D facial representation for person authentication using AdaBoost,"Multi patches 3D facial representation for Person +Authentication using AdaBoost +Lahoucine Ballihi, Boulbaba Ben Amor, Mohamed Daoudi, Anuj Srivastava +To cite this version: +Lahoucine Ballihi, Boulbaba Ben Amor, Mohamed Daoudi, Anuj Srivastava. Multi patches 3D facial +representation for Person Authentication using AdaBoost. I/V Communications and Mobile Network +(ISVC), 2010 5th International Symposium on, Sep 2010, Rabat, Morocco. pp.1-4, 2010. <hal- +00665904> +HAL Id: hal-00665904 +https://hal.archives-ouvertes.fr/hal-00665904 +Submitted on 3 Feb 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non,"
459e840ec58ef5ffcee60f49a94424eb503e8982,One-shot Face Recognition by Promoting Underrepresented Classes,"One-shot Face Recognition by Promoting Underrepresented Classes Yandong Guo, Lei Zhang Microsoft One Microsoft Way, Redmond, Washington, United States {yandong.guo,"
+45954ed44b99edc5f0d1100a1ea33d856602d78a,Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network Approach,"Retinal Vessel Segmentation under Extreme Low +Annotation: A Generative Adversarial Network +Approach +Avisek Lahiri*, Vineet Jain*, Arnab Mondal*, and Prabir Kumar Biswas, Senior Member, IEEE"
451c42da244edcb1088e3c09d0f14c064ed9077e,Using subclasses in discriminant non-negative subspace learning for facial expression recognition,"© EURASIP, 2011 - ISSN 2076-1465 9th European Signal Processing Conference (EUSIPCO 2011) INTRODUCTION"
+456ccc8bbb538037ff00fabf25afb2aceb39149e,Computational Aspects of the Hausdorff Distance in Unbounded Dimension,"Journal of Computational Geometry +COMPUTATIONAL ASPECTS OF THE HAUSDORFF DISTANCE +IN UNBOUNDED DIMENSION +Stefan K¨onig∗"
4568063b7efb66801e67856b3f572069e774ad33,Correspondence driven adaptation for human profile recognition,"Correspondence Driven Adaptation for Human Profile Recognition Ming Yang1, Shenghuo Zhu1, Fengjun Lv2, Kai Yu1 NEC Laboratories America, Inc. Huawei Technologies (USA) Cupertino, CA 95014 Santa Clara, CA 95050"
+45c4514ca2b7903b4c8f43e396bce73f014b72be,Parallel Feature Extraction through Preserving Global and Discriminative Property for Kernel-Based Image Classification,"Journal of Information Hiding and Multimedia Signal Processing +Ubiquitous International +(cid:13)2015 ISSN 2073-4212 +Volume 6, Number 5, September 2015 +Parallel Feature Extraction through Preserving +Global and Discriminative Property for Kernel-Based +Image Classification +Xun-Fei Liu, and Xiang-Xian Zhu +Department of Electrical Engineering +Suzhou Institute of Industrial Technology +Suzhou, 215104, China +Received May, 2015; revised June, 2015"
+4563cbfbdba1779fc598081071ae40be021cb81d,Adversarial Attacks on Variational Autoencoders,"Adversarial Attacks on Variational Autoencoders +George Gondim-Ribeiro, Pedro Tabacof, and Eduardo Valle +RECOD Lab. — DCA / School of Electrical and Computer Engineering (FEEC) +University of Campinas (Unicamp) +Campinas, SP, Brazil +{gribeiro, tabacof,"
+4541f3ee510b593243ff9a66d3586ef9125c2931,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+458e44d20f7a85a0ce378b48a41febb16383c075,Tracking Interacting Objects in Image Sequences,"Tracking Interacting Objects in Image Sequences +THÈSE NO 6632 (2015) +PRÉSENTÉE LE 3 JUILLET 2015 +À LA FACULTÉ INFORMATIQUE ET COMMUNICATIONS +LABORATOIRE DE VISION PAR ORDINATEUR +PROGRAMME DOCTORAL EN INFORMATIQUE ET COMMUNICATIONS +ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE +POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES +Xinchao WANG +cceptée sur proposition du jury: +Prof. W. Gerstner, président du jury +Prof. P. Fua, directeur de thèse +Prof. J. Sullivan, rapporteuse +Prof. P. Dillenbourg, rapporteur +Prof. S. Roth, rapporteur +Suisse"
+456f00e213e03058a056069fa75c34929cf7d4e9,Detecting ground control points via convolutional neural network for stereo matching,"Noname manuscript No. +(will be inserted by the editor) +Detecting Ground Control Points via Convolutional Neural Network for +Stereo Matching +Zhun Zhong · Songzhi Su · Donglin Cao · Shaozi Li +Received: date / Accepted: date"
+4599b9d9a379385a3d31681696d2523beeb0e9c1,LG ] 8 F eb 2 01 6 A Latent-Variable Grid Model,"A Latent-Variable Grid Model +Rajasekaran Masatran +Computer Science and Engineering, Indian Institute of Technology Madras +FREESHELL · ORG"
45e459462a80af03e1bb51a178648c10c4250925,LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning,"LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning Ernest Cheung1, Tsan Kwong Wong1, Aniket Bera1, Xiaogang Wang2, and @@ -6916,9 +23571,62 @@ Departamento de E.I.O. y Computacion 8271 Universidad de La Laguna, Spain Keywords: Image understanding, Gesture recognition, Hand dataset."
+4562272025a5bcdb321408116c699798a7997847,Leveraging RGB-D Data: Adaptive fusion and domain adaptation for object detection,"Leveraging RGB-D Data: Adaptive Fusion and +Domain Adaptation for Object Detection +Luciano Spinello and Kai O. Arras +Social Robotics Lab, University of Freiburg, Germany +{spinello,"
+457d3ca924afc21719d19175caf285aa575d1c90,Analyzing Structured Scenarios by Tracking People and Their Limbs,
+45e2aa7706fcedcbb2d93304a9824fe762b8b3b0,DAC-SDC Low Power Object Detection Challenge for UAV Applications,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2018 +DAC-SDC Low Power Object Detection +Challenge for UAV Applications +Xiaowei Xu, Member, IEEE, Xinyi Zhang, Student Member, IEEE, Bei Yu, Senior Member, IEEE, Xiaobo +Sharon Hu, Fellow, IEEE, Christopher Rowen, Fellow, IEEE, Jingtong Hu, Member, IEEE, and Yiyu +Shi, Senior Member, IEEE"
+456983805a8781d6429bed1ed66dc9f3902767af,Seeing with Humans: Gaze-Assisted Neural Image Captioning,"Seeing with Humans: Gaze-Assisted +Neural Image Captioning +Yusuke Sugano and Andreas Bulling"
+45ca696076e9c073e6cf699766f808899589bc88,Aalborg Universitet Thermal Tracking of Sports Players,"Aalborg Universitet +Thermal Tracking of Sports Players +Gade, Rikke; Moeslund, Thomas B. +Published in: +Sensors +DOI (link to publication from Publisher): +0.3390/s140813679 +Publication date: +Document Version +Publisher's PDF, also known as Version of record +Link to publication from Aalborg University +Citation for published version (APA): +Gade, R., & Moeslund, T. B. (2014). Thermal Tracking of Sports Players. Sensors, 14(8), 13679-13691. DOI: +0.3390/s140813679 +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. +? You may not further distribute the material or use it for any profit-making activity or commercial gain +? You may freely distribute the URL identifying the publication in the public portal ?"
+458713d5c1dd8ff95865302e51f0f8df22204d91,A Review on Face Recognition Using Different Pre- Processing Methods in Images Captured under Various Illumination and Posing Conditions,
+1f98daf89f9a3dba655f0a4eb4164118ea6226ef,"Parallel k-Means Image Segmentation Using Sort, Scan and Connected Components on a GPU","The original publication is available at: www.springerlink.com +Parallel k-Means Image Segmentation Using +Sort, Scan & Connected Components on a GPU +Michael Backer, Jan T¨unnermann, and B¨arbel Mertsching +GET Lab, University of Paderborn, Pohlweg 47-49, 33098 Paderborn, Germany +{backer, tuennermann, +http://getwww.upb.de"
1ffe20eb32dbc4fa85ac7844178937bba97f4bf0,Face Clustering: Representation and Pairwise Constraints,"Face Clustering: Representation and Pairwise Constraints Yichun Shi, Student Member, IEEE, Charles Otto, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+1ff616ae8b61f8167f2d626b7c1a36e018b23e94,Learning with Parsimony for Large Scale Object Detection and Discovery,"Learning with Parsimony for Large Scale Object +Detection and Discovery +Hyun Oh Song +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2014-148 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-148.html +August 12, 2014"
+1f7cd3343f4b6b0f936c94e3a45c477c014e2b5c,3D Human Pose Estimation on a Configurable Bed from a Pressure Image,"D Human Pose Estimation on a Configurable Bed from a Pressure Image +Henry M. Clever*, Ariel Kapusta, Daehyung Park, Zackory Erickson, Yash Chitalia, Charles C. Kemp"
1f8304f4b51033d2671147b33bb4e51b9a1e16fe,Beyond Trees: MAP Inference in MRFs via Outer-Planar Decomposition,"Noname manuscript No. (will be inserted by the editor) Beyond Trees: @@ -6944,18 +23652,89 @@ the system uses ESR to learn a shape of a human face image. A simple way to iden find out facial landmarks like eyes, nose, mouth and chin. The researchers define a face shape S nd S is composed of Nf p facial landmarks. Therefore, they get S = [x1, y1, ..., xNf p, yNf p]T . The objective of the researchers is to estimate a shape S of a face image. The way to know the accuracy"
+1f2f712253a68cd9f8172de19297e35cec7919dd,Vision System of Facial Robot SHFR- III for Human-robot Interaction,
+1f8eefd6dd2f20fd78a67dfdfe33022c6f9981d6,Unsupervised Features for Facial Expression Intensity Estimation over Time,
+1fef45786e707e6b9b8517b0403e596ecbdea6a5,Sketch-based manga retrieval using manga109 dataset,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012 +Sketch-based Manga Retrieval +using Manga109 Dataset +Yusuke Matsui, Member, IEEE, Kota Ito, Yuji Aramaki, Toshihiko Yamasaki, Member, IEEE, +nd Kiyoharu Aizawa, Senior Member, IEEE,"
1fc249ec69b3e23856b42a4e591c59ac60d77118,Evaluation of a 3D-aided pose invariant 2D face recognition system,"Evaluation of a 3D-aided Pose Invariant 2D Face Recognition System Xiang Xu, Ha A. Le, Pengfei Dou, Yuhang Wu, Ioannis A. Kakadiaris {xxu18, hale4, pdou, ywu35, Computational Biomedicine Lab 800 Calhoun Rd. Houston, TX, USA"
+1f4aa1d14bb99e152dd1c7ac3cfd5afa8f6a012f,Learning Discriminative Part Detectors for Image Classification and Cosegmentation,"Learning Discriminative Part Detectors for Image Classification and +Cosegmentation +Jian Sun +Jean Ponce +Xi’an Jiaotong University, INRIA, ∗ +´Ecole Normale Sup´erieure, * +This is a preliminary version accepted for publication to ICCV 2013"
+1fbb66a9407470e1da332c4ef69cdc34e169a3d7,A Baseline for General Music Object Detection with Deep Learning,"Article +A Baseline for General Music Object Detection with +Deep Learning +Alexander Pacha 1,* +, Jan Hajiˇc, Jr. 2 and Jorge Calvo-Zaragoza 3 +Institute for Visual Computing and Human-Centered Technology, TU Wien, 1040 Wien, Austria +Institute of Formal and Applied Linguistics, Charles University, 116 36 Staré Mˇesto, Czech Republic; +PRHLT Research Center, Universitat Politècnica de València, 46022 València, Spain; +* Correspondence: +Received: 31 July 2018; Accepted: 26 August 2018; Published: 29 August 2018"
1fbde67e87890e5d45864e66edb86136fbdbe20e,The Action Similarity Labeling Challenge,"The Action Similarity Labeling Challenge Orit Kliper-Gross, Tal Hassner, and Lior Wolf, Member, IEEE"
+1ff057f2fb8258bd5359cded950a3627bd8ee1f4,Low-rank embedding for semisupervised face classification,"Low-Rank Embedding for Semisupervised Face Classification +Gaurav Srivastava, Ming Shao and Yun Fu∗"
1f41a96589c5b5cee4a55fc7c2ce33e1854b09d6,Demographic Estimation from Face Images: Human vs. Machine Performance,"Demographic Estimation from Face Images: Human vs. Machine Performance Hu Han, Member, IEEE, Charles Otto, Student Member, IEEE, Xiaoming Liu, Member, IEEE nd Anil K. Jain, Fellow, IEEE"
+1f35f0400d6d112e3b27231d0d9241258efd782d,Learning to Rank Using High-Order Information,"Learning to Rank Using High-Order Information +Puneet Kumar Dokania1, Aseem Behl2, C.V. Jawahar2, and M. Pawan Kumar1 +Ecole Centrale de Paris +INRIA Saclay, France +IIIT Hyderabad, India"
+1fcd7978c6956fd9a0d752ecc9f5ac1a1b2896e9,Impact of Face Registration Errors on Recognition,"Impact of Face Registration Errors on Recognition +E. Rentzeperis, A. Stergiou, A. Pnevmatikakis and L. Polymenakos +Athens Information Technology, Autonomic and Grid Computing, +Markopoulou Ave., 19002 Peania, Greece +{eren, aste, apne, +http://www.ait.edu.gr/research/RG1/overview.asp"
+1f5e47ad5490a63c7bea79000999b711055fbf2a,Aggregated Channels Network for Real-Time Pedestrian Detection,"Aggregated Channels Network for Real-Time Pedestrian Detection +Farzin Ghorban1,2, Javier Marín3, Yu Su2, Alessandro Colombo2, Anton Kummert1 +Universität Wuppertal, 2Delphi Deutschland, 3Massachusetts Institute of Technology"
+1f5c409e9b6aec60003b5d4534373f9b07ff8443,Saliency Weighted Features for Person Re-identification,"Saliency Weighted Features for Person +Re-Identification +Niki Martinel, Christian Micheloni and Gian Luca Foresti +Department of Mathematics and Computer Science +University of Udine - 33100, Udine, Italy"
+1fc952fef09d63c61b9b8828f872b7a018eefac1,QUEST: Quadriletral Senary bit Pattern for Facial Expression Recognition,"ACCEPTED IN SMC IEEE CONFERENCE 2018 (PAPER ID: 13628) +QUEST:Quadriletral Senary bit Pattern for Facial +Expression Recognition +Monu Verma1 +Prafulla Saxena2 +S. K. Vipparthi3 +Gridhari Singh4 +Dept. of Computer Science and Engineering, Malaviya national Institute of Technology, Jaipur, India +improves"
+1f65cbc7894323a85f2964d05ae937070e70e43b,Eliminating Background-bias for Robust Person Re-identification,"Eliminating Background-bias for Robust Person Re-identification +Maoqing Tian1, Shuai Yi1, Hongsheng Li2, Shihua Li3, +Xuesen Zhang1, Jianping Shi1, Junjie Yan1, Xiaogang Wang2 +SenseTime Research, 2 Chinese University of Hong Kong, 3 Shenzhen Municipal Public Security Bureau"
+1f4fff64adef5ec6ae21e8647d5a042bf71d64d9,Human detection in surveillance videos and its applications - a review,"Paul et al. EURASIP Journal on Advances in Signal Processing 2013, 2013:176 +http://asp.eurasipjournals.com/content/2013/1/176 +R EV I E W +Human detection in surveillance videos and its +pplications - a review +Manoranjan Paul*, Shah M E Haque and Subrata Chakraborty +Open Access"
+1f18708439ba1dadd81568e102216731d44340d5,Sparse Quantization for Patch Description,"Sparse Quantization for Patch Description +Xavier Boix +Michael Gygli +Gemma Roig +Luc Van Gool +Computer Vision Lab, ETH Zurich, Switzerland"
1f8e44593eb335c2253d0f22f7f9dc1025af8c0d,Fine-Tuning Regression Forests Votes for Object Alignment in the Wild,"Fine-tuning regression forests votes for object alignment in the wild. Yang, H; Patras, I © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be @@ -6968,6 +23747,78 @@ http://qmro.qmul.ac.uk/xmlui/handle/123456789/22607 Information about this research object was correct at the time of download; we occasionally make corrections to records, please therefore check the published record when citing. For more information contact"
+1f6dd0ff2e8493b81e3699b520193198d4eed4e6,Shaogang Gong Part I Features and Representations 1 Discriminative Image Descriptors for Person Re-identification . . . . . 25 7 One-shot Person Re-identification with a Consumer Depth Camera . 163 List of Contributors the Re-identification Challenge,"Shaogang Gong +Marco Cristani +Shuicheng Yan +Chen Change Loy (Eds.) +PERSON RE-IDENTIFICATION +October 10, 2013 +Springer"
+1fa9c5af78b3ca04476f4ee6910684dc19008f5e,Supplementary Material : Cross-Dataset Adaptation for Visual Question Answering,"Supplementary Material: +Cross-Dataset Adaptation for Visual Question Answering +Wei-Lun Chao∗ +U. of Southern California +Los Angeles, CA +Hexiang Hu∗ +Los Angeles, CA +U. of Southern California +U. of Southern California +Fei Sha +Los Angeles, CA +We provide contents omitted in the main text. +• Section 1: details on Name that dataset! (Sect. 3.2 of +the main text). +• Section 2: details on the proposed domain adaptation +lgorithm (Sect. 4.2 and 4.3 of the main text). +• Section 3: details on the experimental setup (Sect. 5.2 +of the main text). +• Section 4: additional experimental results (Sect. 5.3 +nd 5.4 of the main text)."
+1fed6a571d9f688e18960e560d9441f5c5e3e2bd,Scalable Active Learning for Multiclass Image Classification,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES +http://www.merl.com +Scalable Active Learning for Multi-Class +Image Classification +Joshi, A.J.; Porikli, F.; Papanikolopoulos, N. +TR2012-026 +January 2012"
+1f436aa4e68274037fff44e6cfbcd0a1ee3f60df,Tell and Predict: Kernel Classifier Prediction for Unseen Visual Classes from Unstructured Text Descriptions,"Tell and Predict: Kernel Classifier Prediction for Unseen Visual Classes +from Unstructured Text Descriptions +Mohamed Elhoseiny, Ahmed Elgammal, Babak Saleh"
+1fd8c71a8859da611a8fde1cbb2bba1c7cf00b4c,EYEDIAP: a database for the development and evaluation of gaze estimation algorithms from RGB and RGB-D cameras,"This paper was presented at the 2014 Symposium on Eye Tracking Research & Applications 2014 +EYEDIAP: A Database for the Development and Evaluation of Gaze Estimation +Algorithms from RGB and RGB-D Cameras +Kenneth Alberto Funes Mora1,2, Florent Monay1 and Jean-Marc Odobez1,2 +Idiap Research Institute 2 ´Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Switzerland +{kfunes, monay,"
+1fe74d637bc5e7d95abcd18b6967e51461fd8cdd,On the Dynamic Selection of Biometric Fusion Algorithms,"On the Dynamic Selection of Biometric Fusion +Algorithms +Mayank Vatsa, Member, IEEE, Richa Singh, Member, IEEE, Afzel Noore, Member, IEEE, and +Arun Ross, Member, IEEE"
+1fb2082d3f772933b586cca65af2099512b9c68b,Comparison of Spectral-Only and Spectral/Spatial Face Recognition for Personal Identity Verification,"Hindawi Publishing Corporation +EURASIP Journal on Advances in Signal Processing +Volume 2009, Article ID 943602, 6 pages +doi:10.1155/2009/943602 +Research Article +Comparison of Spectral-Only and Spectral/Spatial Face +Recognition for Personal Identity Verification +Zhihong Pan,1 Glenn Healey,2 and Bruce Tromberg3 +Galileo Group Inc., 100 Rialto Place Suite 737, Melbourne, FL 32901, USA +Department of Electrical Engineering and Computer Science, University of California, Irvine, CA 92697, USA +Beckman Laser Institute, 1002 East Health Sciences Road, Irvine, CA 92612, USA +Correspondence should be addressed to Zhihong Pan, +Received 29 September 2008; Revised 22 February 2009; Accepted 8 April 2009 +Recommended by Kevin Bowyer +Face recognition based on spatial features has been widely used for personal identity verification for security-related applications. +Recently, near-infrared spectral reflectance properties of local facial regions have been shown to be sufficient discriminants for +ccurate face recognition. In this paper, we compare the performance of the spectral method with face recognition using the +eigenface method on single-band images extracted from the same hyperspectral image set. We also consider methods that use +multiple original and PCA-transformed bands. Lastly, an innovative spectral eigenface method which uses both spatial and spectral +features is proposed to improve the quality of the spectral features and to reduce the expense of the computation. The algorithms"
+1f614a97e16671c091b1bcd1a33e1280822b53db,Tracking People's Hands and Feet Using Mixed Network AND/OR Search,"DRAFT FOR TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +Tracking people’s hands and feet using mixed +network AND/OR search +Vlad I. Morariu, Member, IEEE, David Harwood, Member, IEEE, +nd Larry S. Davis, Fellow, IEEE"
1f94734847c15fa1da68d4222973950d6b683c9e,Embedding Label Structures for Fine-Grained Feature Representation,"Embedding Label Structures for Fine-Grained Feature Representation Xiaofan Zhang UNC Charlotte @@ -6981,9 +23832,85 @@ Cupertino, CA 95014 Shaoting Zhang UNC Charlotte Charlotte, NC 28223"
+1ff89bd94d8a21b7ca4bf844e2d366f854822918,Robust Online Multi-object Tracking by Maximum a Posteriori Estimation with Sequential Trajectory Prior,"Robust Online Multi-object Tracking +y Maximum a Posteriori Estimation +with Sequential Trajectory Prior +Min Yang(B), Mingtao Pei, Jiajun Shen, and Yunde Jia +Beijing Laboratory of Intelligent Information Technology, School of Computer +Science, Beijing Institute of Technology, Beijing 100081, People’s Republic of China"
1fff309330f85146134e49e0022ac61ac60506a9,Data-Driven Sparse Sensor Placement for Reconstruction,"Data-Driven Sparse Sensor Placement for Reconstruction Krithika Manohar∗, Bingni W. Brunton, J. Nathan Kutz, and Steven L. Brunton Corresponding author:"
+1f69fa423b076e19dc2ccf6bc9013f09ae39133c,Multimodal Dialogs (MMD): A large-scale dataset for studying multimodal domain-aware conversations,"Towards Building Large Scale Multimodal Domain-Aware Conversation Systems +Amrita Saha1,2 +Mitesh M. Khapra2 +Karthik Sankaranarayanan1 +IBM Research AI +I.I.T. Madras, India"
+1f8f0abfe4689aa93f2f6cc7ec4fd4c6adc2c2d6,Semantic Instance Segmentation with a Discriminative Loss Function,"Semantic Instance Segmentation with a Discriminative Loss Function +Bert De Brabandere∗ +Davy Neven∗ +ESAT-PSI, KU Leuven +Luc Van Gool"
+1fd54172f7388cd83ed78ff9165519296de5cf20,Changing the Image Memorability: From Basic Photo Editing to GANs,"Changing the Image Memorability: From Basic Photo Editing to GANs +Oleksii Sidorov +The Norwegian Colour and Visual Computing Laboratory, NTNU +Gjovik, Norway +Figure 1: Modification of memorability using the proposed algorithm. All the results were generated without any human intervention. +“What” and “how” to change were learned by the model from experimental data."
+1f82eebadc3ffa41820ad1a0f53770247fc96dcd,Using Trajectories derived by Dense Optical Flows as a Spatial Component in Background Subtraction,"Using Trajectories derived by Dense Optical Flows as a +Spatial Component in Background Subtraction +Martin Radolko +University of Rostock +nd Fraunhofer IGD +Joachim-Jungius 11 +Rostock 18059 +r.fraunhofer.de +Fahimeh Farhadifard +University of Rostock +nd Fraunhofer IGD +Joachim-Jungius 11 +Rostock 18059 +r.fraunhofer.de"
+1f3370e2e6381408efe11e69ab12586bd6f74dc8,Feature Selection Library (MATLAB Toolbox),"Feature Selection Techniques for Classification: +A widely applicable code library +Giorgio Roffo +University of Verona, +Department of Computer Science"
+1f2c99bf032868ce520b9c5586a0c20051367b60,A Study of The Illumination Cones Method for Face Recognition Under Variable Illumination T.J. Chin and D. Suter A Study of The Illumination Cones Method for Face Recognition Under Variable Illumination,"Department of Electrical +Computer Systems Engineering +Technical Report +MECSE-7-2004 +A Study of The Illumination Cones Method for Face +Recognition Under Variable Illumination +T.J. Chin and D. Suter"
+1f53ca209f982500069fed73efe2345358eff79e,Pedestrian Detection with Deep Convolutional Neural Network,"Pedestrian Detection with Deep Convolutional +Neural Network +Xiaogang Chen, Pengxu Wei, Wei Ke, Qixiang Ye, Jianbin Jiao +School of Electronic,Electrical and Communication Engineering, University of +Chinese Academy of Science, Beijing, China"
+1f8d539885f78e1a9d1314e952f3099e71676a5b,Audio-Visual Speaker Diarization Based on Spatiotemporal Bayesian Fusion,"Audio-Visual Speaker Diarization Based on +Spatiotemporal Bayesian Fusion +Israel D. Gebru, Sil`eye Ba, Xiaofei Li and Radu Horaud"
+1f7cf2df2fa7719c9db3fe57a0f01d65f08a9a8f,How social exclusion modulates social information processing: A behavioural dissociation between facial expressions and gaze direction,"RESEARCH ARTICLE +How social exclusion modulates social +information processing: A behavioural +dissociation between facial expressions and +gaze direction +Francesco Bossi1,2*, Marcello Gallucci1,2, Paola Ricciardelli1,2 +Department of Psychology, University of Milan – Bicocca, Milan, Italy, 2 NeuroMI: Milan Center for +Neuroscience, Milan, Italy"
+73a7ccf0facccd8943f7e54d19478f2bef9b7dab,Number 16,"Number 16 +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 132 +Number 16 +Year of Publication: 2015 +Authors: +Pronaya Prosun Das, Taskeed Jabid, S.M. Shariar Mahamud +10.5120/ijca2015907690 +{bibtex}2015907690.bib{/bibtex}"
73f467b4358ac1cafb57f58e902c1cab5b15c590,Combination of Dimensionality Reduction Techniques for Face Image Retrieval: A Review,"ISSN 0976 3724 47 Combination of Dimensionality Reduction Techniques for Face Image Retrieval: A Review @@ -6999,18 +23926,144 @@ Boyu Lu, Student Member, IEEE, Jun-Cheng Chen, Member, IEEE, Carlos D Castillo, nd Rama Chellappa, Fellow, IEEE"
732e8d8f5717f8802426e1b9debc18a8361c1782,Unimodal Probability Distributions for Deep Ordinal Classification,"Unimodal Probability Distributions for Deep Ordinal Classification Christopher Beckham 1 Christopher Pal 1"
+73351b313df89572afe1332625044f7e5dd0ce06,High-level Feature Learning by Ensemble Projection for Image Classification with Limited Annotations I,"High-level Feature Learning by Ensemble Projection for Image +Classification with Limited Annotations $ +Dengxin Dai∗, Luc Van Gool +Computer Vision Lab, ETH Z¨urich, CH-8092, Switzerland"
+73c72161969a070b3caa40d4f075ba501a1b994b,Expression-Invariant 3D Face Recognition Using Patched Geodesic Texture Transform,"Expression-Invariant 3D Face Recognition using Patched +Geodesic Texture Transform +Author +Hajati, Farshid, Raie, Abolghasem, Gao, Yongsheng +Published +Conference Title +Proceedings 2010 Digital Image Computing: Techniques and Applications DICTA 2010 +https://doi.org/10.1109/DICTA.2010.52 +Copyright Statement +© 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/ +republish this material for advertising or promotional purposes or for creating new collective +works for resale or redistribution to servers or lists, or to reuse any copyrighted component of +this work in other works must be obtained from the IEEE. +Downloaded from +http://hdl.handle.net/10072/37733 +Link to published version +http://dicta2010.conference.nicta.com.au/ +Griffith Research Online +https://research-repository.griffith.edu.au"
+73764fa9bed84ad2c932dc8089ace7fa8fa7c1d3,"Disparity Statistics for Pedestrian Detection: Combining Appearance, Motion and Stereo","Disparity Statistics for Pedestrian Detection: +Combining Appearance, Motion and Stereo +Stefan Walk1, Konrad Schindler1,2, and Bernt Schiele1,3 +Computer Science Department, TU Darmstadt +Photogrammetry and Remote Sensing Group, ETH Z¨urich +MPI Informatics, Saarbr¨ucken"
73ed64803d6f2c49f01cffef8e6be8fc9b5273b8,Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos,"Noname manuscript No. (will be inserted by the editor) Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos Hilde Kuehne · Juergen Gall · Thomas Serre Received: date / Accepted: date"
+73bbbfac7b144f835840fe7f7b5139283bf4f3f1,Do we spontaneously form stable trustworthiness impressions from facial appearance?,"ATTITUDES AND SOCIAL COGNITION +Do We Spontaneously Form Stable Trustworthiness Impressions From +Facial Appearance? +André Klapper +Radboud University +Ron Dotsch +Utrecht University and Radboud University +Iris van Rooij and Daniël H. J. Wigboldus +Radboud University +It is widely assumed among psychologists that people spontaneously form trustworthiness impressions of +newly encountered people from their facial appearance. However, most existing studies directly or +indirectly induced an impression formation goal, which means that the existing empirical support for +spontaneous facial trustworthiness impressions remains insufficient. In particular, it remains an open +question whether trustworthiness from facial appearance is encoded in memory. Using the ‘who said +what’ paradigm, we indirectly measured to what extent people encoded the trustworthiness of observed +faces. The results of 4 studies demonstrated a reliable tendency toward trustworthiness encoding. This +was shown under conditions of varying context-relevance, and salience of trustworthiness. Moreover, +evidence for this tendency was obtained using both (experimentally controlled) artificial and (naturalistic +varying) real faces. Taken together, these results suggest that there is a spontaneous tendency to form +relatively stable trustworthiness impressions from facial appearance, which is relatively independent of"
+73713880d4d1ec4c8f4608a94f67ea9e9f9a97a5,Visual query attributes suggestion,"Visual Query Attributes Suggestion +Jingwen Bian +National University of +Singapore, Singapore +Zheng-Jun Zha +National University of +Singapore, Singapore +Hanwang Zhang +National University of +Singapore, Singapore +Qi Tian +University of Texas at San +Antonio, USA"
+73fa81d2b01c81c6ede71d046f9101440884e604,Fuzzy Based Texton Binary Shape Matrix (FTBSM) for Texture Classification,"Global Journal of Computer Science and Technology +Graphics & Vision +Volume 12 Issue 15 Version 1.0 Year 2012 +Type: Double Blind Peer Reviewed International Research Journal +Publisher: Global Journals Inc. (USA) +Online ISSN: 0975-4172 & Print ISSN: 0975-4350 +Fuzzy Based Texton Binary Shape Matrix (FTBSM) for Texture +Classification +By P.Chandra Sekhar Reddy & B.Eswara Reddy +Jntua College of Engineering, Anantapur, A.P, India"
+73c13ba142588f45aaa92805fe75ca2691ac981b,A Comparative Study of Social Scene Parsing Strategies between Children with and without Autism Spectrum Disorder,"96 Jul 2016 Vol 9 No.3 North American Journal of Medicine and Science +Original Research +A Comparative Study of Social Scene Parsing +Strategies between Children with and +without Autism Spectrum Disorder +Chen Song;1 Aosen Wang;1 Kathy Ralabate Doody, PhD;2* Michelle Hartley- +McAndrew, MD;3 Jana Mertz, MBA;4 Feng Lin, PhD;1 Wenyao Xu, PhD1 +Computer Science and Engineering, SUNY, University at Buffalo, Buffalo NY +Exceptional Education, SUNY, Buffalo State, Buffalo, NY +Jacobs School of Medicine and Biomedical Sciences, SUNY, University at Buffalo Women and Children's Hospital of Buffalo, Buffalo, NY +Children’s Guild Foundation Autism Spectrum Disorder Center, Women and Children’s Hospital of Buffalo, Buffalo, NY +Autism spectrum disorder (ASD) is a complex developmental disability characterized by deficits in social +interaction. Gaze behavior is of great interest because it reveals the parsing strategy the participant uses to +chieve social content. The legacy features in gaze fixation, such as time and area-of-interest, however, cannot +omprehensively reveal the way the participant may cognize the social scene. In this work, we investigate the +dynamic components within the gaze behavior of children with ASD upon the carefully-selected social scene. +A cohort of child participants (n = 51) were recruited between 2 and 10 years. The results suggest significant +differences in the social scene parsing strategies of children with ASD, giving added insight into the way they +may decode and interpret the social scenarios. +[N A J Med Sci. 2016;9(3):96-103. DOI: 10.7156/najms.2016.0903096]"
+73d8fafee6be9d4fa789ece2192f259199f00e60,3D Face Recognition Using Radon Transform and Factorial Discriminant Analysis (FDA),"Volume 3, Issue 7, July 2013 ISSN: 2277 128X +International Journal of Advanced Research in +Computer Science and Software Engineering +Research Paper +Available online at: www.ijarcsse.com +D Face Recognition Using Radon Transform and Factorial +Discriminant Analysis (FDA) +P. S. Hiremath , Manjunatha Hiremath +Department of Computer Science +Gulbarga University, Gulbarga-585106 +Karnataka, India."
+735c38361d77e707ac48f0d040493c65ca559d3c,Machine Learning for Simplifying the Use of Cardiac Image Databases. (Apprentissage automatique pour simplifier l'utilisation de banques d'images cardiaques),"N°: 2009 ENAM XXXX +École doctorale n° 84 : +Sciences et technologies de l’information et de la communication +Doctorat ParisTech +T H È S E +pour obtenir le grade de docteur délivré par +l’École nationale supérieure des mines de Paris +Spécialité “ Contrôle, optimisation et prospective ” +présentée et soutenue publiquement par +Ján MARGETA +le 14 Décembre 2015 +Apprentissage automatique pour simplifier +l’utilisation de banques d’images cardiaques +Machine Learning for Simplifying +the Use of Cardiac Image Databases +Directeurs de thèse : Nicholas AYACHE et Antonio CRIMINISI +M. Patrick CLARYSSE, DR, Creatis, CNRS, INSA Lyon +M. Bjoern MENZE, Professeur, ImageBioComp Group, TU München +M. Hervé DELINGETTE, DR, Asclepios Research Project, Inria Sophia Antipolis +M. Antonio CRIMINISI, Chercheur principal, MLP Group, Microsoft Research Cambridge"
7306d42ca158d40436cc5167e651d7ebfa6b89c1,Transductive Zero-Shot Action Recognition by Word-Vector Embedding,"Noname manuscript No. (will be inserted by the editor) Transductive Zero-Shot Action Recognition by Word-Vector Embedding Xun Xu · Timothy Hospedales · Shaogang Gong Received: date / Accepted: date"
+73200504c7381c48c900894455995b9188676cd5,Weakly-Supervised Image Annotation and Segmentation with Objects and Attributes,"Weakly-Supervised Image Annotation and +Segmentation with Objects and Attributes +Zhiyuan Shi, Yongxin Yang, Timothy M. Hospedales, Tao Xiang"
734cdda4a4de2a635404e4c6b61f1b2edb3f501d,Automatic landmark point detection and tracking for human facial expressions,"Tie and Guan EURASIP Journal on Image and Video Processing 2013, 2013:8 http://jivp.eurasipjournals.com/content/2013/1/8 R ES EAR CH @@ -7049,9 +24102,121 @@ Second supervisor: dr. Disa Sauter External Supervisor: prof. dr. Monique Volman Research Master’s, Social Psychology Ethics Committee Reference Code: 2016-SP-7084"
+73599349402bf8f0d97f51862d11d128cdba44ef,Affective analysis of videos: detecting emotional content in real-life scenarios,"Affective Analysis of Videos: +Detecting Emotional Content in Real-Life Scenarios +vorgelegt von +Master of Science +Esra Acar Celik +geb. in Afyonkarahisar +Von der Fakultät IV – Elektrotechnik und Informatik – +der Technischen Universität Berlin +zur Erlangung des akademischen Grades +Doktor der Ingenieurwissenschaften +– Dr.-Ing. – +genehmigte Dissertation +Promotionsausschuss: +Vorsitzender: +Berichter: +Berichter: +Berichter: +Prof. Dr. Thomas Wiegand +Prof. Dr. Dr. h.c. Sahin Albayrak +Prof. Dr. Adnan Yazıcı"
+73a4fe5072a30c132e8a0a18384caae4c112f198,What is typical is good: the influence of face typicality on perceived trustworthiness.,"554955 PSSXXX10.1177/0956797614554955Sofer et al.What Is Typical Is Good +research-article2014 +Research Article +What Is Typical Is Good: The Influence +of Face Typicality on Perceived +Trustworthiness +015, Vol. 26(1) 39 –47 +© The Author(s) 2014 +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0956797614554955 +pss.sagepub.com +Carmel Sofer1,2, Ron Dotsch2,3, Daniel H. J. Wigboldus2, and +Alexander Todorov1,2 +Department of Psychology, Princeton University; 2Behavioural Science Institute, Radboud University +Nijmegen; and 3Department of Psychology, Utrecht University"
+73704242a548e8725926762faf7333e5598d0228,Surveillance of Super-Extended Objects : Bimodal Approach,"World Academy of Science, Engineering and Technology +International Journal of Mechanical and Mechatronics Engineering +Vol:8, No:9, 2014 +Surveillance of Super-Extended Objects: Bimodal +Approach +Andrey V. Timofeev, Dmitry Egorov"
+73866bdb723841da93b6ad93afe3d72817e2b377,Dense and Low-Rank Gaussian CRFs Using Deep Embeddings,"Dense and Low-Rank Gaussian CRFs Using Deep Embeddings +Siddhartha Chandra1 +Nicolas Usunier2 +Iasonas Kokkinos2 +INRIA GALEN, CentraleSup´elec +Facebook AI Research, Paris"
73fbdd57270b9f91f2e24989178e264f2d2eb7ae,Kernel linear regression for low resolution face recognition under variable illumination,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE ICASSP 2012"
+738d5a6491ae0fef5d2debc17f951534061cf6f8,Advances in Learning Visual Saliency: From Image Primitives to Semantic Contents,"Chapter 14 +Advances in Learning Visual Saliency: +From Image Primitives to Semantic Contents +Qi Zhao and Christof Koch"
+73d57e2c855c39b4ff06f2d7394ab4ea35f597d4,First Order Generative Adversarial Networks,"First Order Generative Adversarial Networks +Calvin Seward 1 2 Thomas Unterthiner 2 Urs Bergmann 1 Nikolay Jetchev 1 Sepp Hochreiter 2"
+73052a2bf7b41b7be2447fadc13c29be1d994708,Pedestrian tracking using probability fields and a movement feature space 1,"Pedestrian tracking using probability fields and a movement feature space 1 +Pablo Negri a & Damián Garayalde b +Universidad Argentina de la Empresa (UADE). CONICET. Buenos Aires, Argentina. +Instituto Tecnológico de Buenos Aires (ITBA), Buenos Aires, Argentina. +Received: April 18th, 2016. Received in revised form: November 1rd, 2016. Accepted: December 2nd, 2016."
+73ec2d5a6b4bee0f268b793ff646330507497e38,Is an Image Worth More than a Thousand Words? On the Fine-Grain Semantic Differences between Visual and Linguistic Representations,"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, +pages 2807–2817, Osaka, Japan, December 11-17 2016."
+73be334ecc48751269443b0db2629086125e69f5,Robust Face Recognition under Difficult Lighting Conditions,"International Journal of Technological Exploration and Learning (IJTEL) +Volume 1 Issue 1 (August 2012) +Robust Face Recognition under Difficult Lighting +Conditions +S.S. Ghatge1,V.V. Dixit2 +Department of Electronics &Telecomunication1, 2 +Sinhgad College of Engineering1, 2 +University of Pune, India1, 2"
+731840289e35c61c6e21ae18f2da2751bd8e2f20,Event-related potential (ERP) correlates of face processing in verbal children with autism spectrum disorders (ASD) and their first-degree relatives: a family study,"Sysoeva et al. Molecular Autism (2018) 9:41 +https://doi.org/10.1186/s13229-018-0220-x +Open Access +R ES EAR CH +Event-related potential (ERP) correlates of +face processing in verbal children with +utism spectrum disorders (ASD) and their +first-degree relatives: a family study +Olga V. Sysoeva1,2, John N. Constantino1* +nd Andrey P. Anokhin1"
73c9cbbf3f9cea1bc7dce98fce429bf0616a1a8c,Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings,"imagesViewpoint factorizationLearned landmarksFigure1.Wepresentanovelmethodthatcanlearnviewpointin-variantlandmarkswithoutanysupervision.Themethodusesaprocessofviewpointfactorizationwhichlearnsadeeplandmarkdetectorcompatiblewithimagedeformations.Itcanbeappliedtorigidanddeformableobjectsandobjectcategories.terns.Achievingadeeperunderstandingofobjectsrequiresmodelingtheirintrinsicviewpoint-independentstructure.Oftenthisstructureisdefinedmanuallybyspecifyingen-titiessuchaslandmarks,parts,andskeletons.Givensuffi-cientmanualannotations,itispossibletoteachdeepneuralnetworksandothermodelstorecognizesuchstructuresinimages.However,theproblemoflearningsuchstructureswithoutmanualsupervisionremainslargelyopen.Inthispaper,wecontributeanewapproachtolearnviewpoint-independentrepresentationsofobjectsfromim-ageswithoutmanualsupervision(fig.1).Weformulatethistaskasafactorizationproblem,wheretheeffectsofimagedeformations,forexamplearisingfromaviewpointchange,areexplainedbythemotionofareferenceframeattachedtotheobjectandindependentoftheviewpoint.Afterdescribingthegeneralprinciple(sec.3.1),wein-1"
+87cab840df202609bfcfb5a9ee3293e61c7c85db,Vision based victim detection from unmanned aerial vehicles,"Vision Based Victim Detection from Unmanned Aerial Vehicles +Mykhaylo Andriluka1, Paul Schnitzspan1, Johannes Meyer2, Stefan Kohlbrecher1, +Karen Petersen1, Oskar von Stryk1, Stefan Roth1, and Bernt Schiele1,3 +Department of Computer Science, TU Darmstadt +Department of Mechanical Engineering, TU Darmstadt +MPI Informatics, Saarbr¨ucken"
+874082164d9ab9fced08b9890c009b91a2e846f1,Understanding Convolution for Semantic Segmentation,"Understanding Convolution for Semantic Segmentation +Panqu Wang1, Pengfei Chen1, Ye Yuan2, Ding Liu3, Zehua Huang1, Xiaodi Hou1, Garrison Cottrell4 +TuSimple, 2Carnegie Mellon University, 3University of Illinois Urbana-Champaign, 4UC San Diego"
+87c2806f1fd20287f00b43dab07822ab13035169,Verfahren zur Analyse von Ähnlichkeit im Ortsbereich,"Matthias Fiedler +Verfahren zur Analyse von Ähnlichkeit im Ortsbereich"
+87ad56e06d48fa9b30e2915473c488c1b4b7e6ae,Learn from experience: probabilistic prediction of perception performance to avoid failure,"Article +Learn from experience: probabilistic +prediction of perception performance to +void failure +The International Journal of +Robotics Research +© The Author(s) 2017 +Reprints and permissions: +sagepub.co.uk/journalsPermissions.nav +DOI: 10.1177/0278364917730603 +journals.sagepub.com/home/ijr +Corina Gur˘au1, Dushyant Rao1, Chi Hay Tong2, and Ingmar Posner1"
+8765f22fbcdcf610a08b01db01edc4b8cc67d082,Probability Models for Open Set Recognition,"for all other uses, +© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be +obtained +including +reprinting/republishing this material for advertising or promotional purposes, creating +new collective works, for resale or redistribution to servers or lists, or reuse of any +opyrighted component of this work in other works. +in any current or +future media, +Pre-print of article that will appear in T-PAMI."
8796f2d54afb0e5c924101f54d469a1d54d5775d,Illumination Invariant Face Recognition Using Fuzzy LDA and FFNN,"Journal of Signal and Information Processing, 2012, 3, 45-50 http://dx.doi.org/10.4236/jsip.2012.31007 Published Online February 2012 (http://www.SciRP.org/journal/jsip) Illumination Invariant Face Recognition Using Fuzzy LDA @@ -7074,20 +24239,106 @@ Computer Science" Rasmus Rothe1, Marko Ristin1, Matthias Dantone1, and Luc Van Gool1,2 Computer Vision Laboratory, D-ITET, ETH Z¨urich, Switzerland ESAT - PSI / IBBT, K.U. Leuven, Belgium"
+8722ab37a03336f832e4098224cb63cd02cdfe0a,Face recognition with 3 D face asymmetry,"Face recognition with 3D face asymmetry +Janusz Bobulski +Czestochowa University of Technology +Institute of Computer and Information Sciences +Dabrowskiego 73, 42-200, Czestochowa, Poland +Summary. Using of 3D images for the identification was in a field of the interest +of many researchers which developed a few methods offering good results. However, +there are few techniques exploiting the 3D asymmetry amongst these methods. We +propose fast algorithm for rough extraction face asymmetry that is used to 3D +face recognition with hidden Markov models. This paper presents conception of fast +method for determine 3D face asymmetry. The research results indicate that face +recognition with 3D face asymmetry may be used in biometrics systems. +Introduction +Biometrics systems use individual and unique biological features of person +for user identification. The most popular features are: fingerprint, iris, voice, +palm print, face image et al. Most of them are not accepted by users, because +they feel under surveillance or as criminals. Others, in turn, are characterized +y problems with the acquisition of biometric pattern and require closeness +to the reader. Among the biometric methods popular technique is to identify +people on the basis of the face image, the advantage is the ease of obtaining"
87bee0e68dfc86b714f0107860d600fffdaf7996,Automated 3D Face Reconstruction from Multiple Images Using Quality Measures,"Automated 3D Face Reconstruction from Multiple Images using Quality Measures Marcel Piotraschke and Volker Blanz Institute for Vision and Graphics, University of Siegen, Germany"
+878f70f6abb83f5158ca0bacfc2bacd49b1886b1,Aligning Artificial Neural Networks to the Brain Yields Shallow Recurrent Architec- Tures,"Under review as a conference paper at ICLR 2019 +ALIGNING ARTIFICIAL NEURAL NETWORKS TO THE +BRAIN YIELDS SHALLOW RECURRENT ARCHITEC- +TURES +Anonymous authors +Paper under double-blind review"
+87da8bd9eb2fff2d77809c8bee3bed8c93cb5b4b,A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders,"A Generative Model For Zero Shot Learning +Using Conditional Variational Autoencoders +Ashish Mishra1 , Shiva Krishna Reddy1, Anurag Mittal, and Hema A Murthy +Indian Institute of Technology Madras"
878169be6e2c87df2d8a1266e9e37de63b524ae7,Image interpretation above and below the object level.,"CBMM Memo No. 089 May 10, 2018 Image interpretation above and below the object level Guy Ben-Yosef, Shimon Ullman"
+87363751b8e3d51a002dea6d32df553ee5315cb7,Fine-grained sketch-based image retrieval: The role of part-aware attributes,"Fine-Grained Sketch-Based Image Retrieval: The Role of Part-Aware Attributes +Ke Li1&2 +Kaiyue Pang1&2 +Yi-Zhe Song2 +Timothy Hospedales2 +Honggang Zhang1 +School of Electronic Engineering and Computer Science Queen Mary University of London. +Beijing University of Posts and Telecommunications. +Yichuan Hu1"
+877d083b2a3a75cc1bb25f770a9c5684bf5f6f44,Learning to Hash with Binary Reconstructive Embeddings,"Learning to Hash with Binary Reconstructive +Embeddings +Brian Kulis and Trevor Darrell +UC Berkeley EECS and ICSI +Berkeley, CA"
+87bba3f4292727091027b7888b5d8f364425344d,End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners,"End-to-End Learning of Driving Models with +Surround-View Cameras and Route Planners +Simon Hecker1, Dengxin Dai1, and Luc Van Gool1,2 +ETH Zurich, Zurich, Switzerland +KU Leuven, Leuven, Belgium"
+877aff9bd05de7e9d82587b0e6f1cda28fd33171,Long-Term Visual Localization Using Semantically Segmented Images,"Long-term Visual Localization using Semantically Segmented Images +Erik Stenborg1,2 Carl Toft1 and Lars Hammarstrand1"
878301453e3d5cb1a1f7828002ea00f59cbeab06,Faceness-Net: Face Detection through Deep Facial Part Responses,"Faceness-Net: Face Detection through Deep Facial Part Responses Shuo Yang, Ping Luo, Chen Change Loy, Senior Member, IEEE and Xiaoou Tang, Fellow, IEEE"
87e592ee1a7e2d34e6b115da08700a1ae02e9355,Deep Pictorial Gaze Estimation,"Deep Pictorial Gaze Estimation Seonwook Park, Adrian Spurr, and Otmar Hilliges AIT Lab, Department of Computer Science, ETH Zurich"
+87bdafbcf3569c06eef4a397beffc451f5101f94,Facial expression: An under-utilised tool for the assessment of welfare in mammals.,"published February 8, 2017 +Review article +Facial expression: An under-utilised tool for +the assessment of welfare in mammals1 +Kris A. Descovich1,2,3, Jennifer Wathan4, Matthew C. Leach5, Hannah M. Buchanan-Smith1, +Paul Flecknell6, David Farningham7 and Sarah-Jane Vick1 +Psychology, Faculty of Natural Sciences, University of Stirling; 2Environmental and Animal Sciences, Unitec Institute of +Technology; 3Centre for Animal Welfare and Ethics, University of Queensland; 4School of Psychology, University of Sussex, +United Kingdom; 5School of Agriculture, Food & Rural Development, University of Newcastle; 6Comparative Biology +Centre, University of Newcastle; 7Centre for Macaques, Medical Research Council +Summary +Animal welfare is a key issue for industries that use or impact upon animals. The accurate identification of welfare +states is particularly relevant to the field of bioscience, where the 3Rs framework encourages refinement of +experimental procedures involving animal models. The assessment and improvement of welfare states in animals +is reliant on reliable and valid measurement tools. Behavioural measures (activity, attention, posture and +vocalisation) are frequently used because they are immediate and non-invasive, however no single indicator can +yield a complete picture of the internal state of an animal. Facial expressions are extensively studied in humans +s a measure of psychological and emotional experiences but are infrequently used in animal studies, with the +exception of emerging research on pain behaviour. In this review, we discuss current evidence for facial +representations of underlying affective states, and how communicative or functional expressions can be useful"
+8765f312e35bba0650aa769b59da7e8fac9e98aa,A Cognitively-Motivated Framework for Partial Face Recognition in Unconstrained Scenarios,"Sensors 2015, 15, 1903-1924; doi:10.3390/s150101903 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +A Cognitively-Motivated Framework for Partial Face +Recognition in Unconstrained Scenarios +João C. Monteiro * and Jaime S. Cardoso +INESC TEC and Faculdade de Engenharia, Universidade do Porto, Campus da FEUP, +Rua Dr. Roberto Frias, n 378, 4200-465 Porto, Portugal; E-Mail: +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +351-22-209-4299. +Academic Editor: Vittorio M.N. Passaro +Received: 24 November 2014 / Accepted: 7 January 2015 / Published: 16 January 2015"
87dd3fd36bccbe1d5f1484ac05f1848b51c6eab5,Spatio-temporal Maximum Average Correlation Height Templates in Action Recognition and Video Summarization,"SPATIO-TEMPORAL MAXIMUM AVERAGE CORRELATION HEIGHT TEMPLATES IN ACTION RECOGNITION AND VIDEO SUMMARIZATION @@ -7102,9 +24353,73 @@ t the University of Central Florida Orlando, Florida Summer Term Major Professor: Mubarak Shah"
+87c6ba55b0f817de4504e39dbb201842ae102c9f,Three Dimensional Face Recognition Using Iso-Geodesic and Iso-Depth Curves,"Three Dimensional Face Recognition Using Iso-Geodesic and Iso-Depth +Curves +Sina Jahanbin, Hyohoon Choi, Yang Liu, Alan C. Bovik"
87bb183d8be0c2b4cfceb9ee158fee4bbf3e19fd,Craniofacial Image Analysis,"Craniofacial Image Analysis Ezgi Mercan, Indriyati Atmosukarto, Jia Wu, Shu Liang and Linda G. Shapiro"
+87f0a779ce4e060e3e076df3cc651e0f3f01b2ae,Bimodal Biometric Person Identification System Under Perturbations,"Bimodal Biometric Person Identification System +Under Perturbations +Miguel Carrasco1, Luis Pizarro2, and Domingo Mery1 +Pontificia Universidad Cat´olica de Chile +Av. Vicu˜na Mackenna 4860(143), Santiago, Chile +Mathematical Image Analysis Group +Faculty of Mathematics and Computer Science +Saarland University, Bldg. E11, 66041 Saarbr¨ucken, Germany"
+8064d7a28c763ec37a840450d729f23428ad8f8b,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+80265d7c9fe6a948dd8c975bd4d696fb7ba099c9,Face Recognition Based on Human Visual Perception Theories and Unsupervised ANN,"Face Recognition Based on +Human Visual Perception Theories and +Unsupervised ANN +Mario I. Chacon M. and Pablo Rivas P. +Chihuahua Institute of Technology +Mexico +. Introduction +The face recognition problem has been faced for more than 30 years. Although a lot of +research has been done, much more research is and will be required in order to end up with +robust face recognition system with a potential close to human performance. Currently +face recognition systems, FRS, report high performance levels, however achievement of +00% of correct recognition is still a challenge. Even more, if the FRS must work on non- +ooperative environment its performance may decrease dramatically. Non-cooperative +environments are characterized by changes on; pose, illumination, facial expression. +Therefore FRS for non-cooperative environment represents an attractive challenge to +researchers working on the face recognition area. +Most of the work presented in the literature dealing with the face recognition problem +follows an engineering approach that in some cases do not incorporate information from a +psychological or neuroscience perspective. It is our interest in this material, to show how +information from the psychological and neuroscience areas may contribute in the solution of"
+809e25da311366bfd684228e16184737d948eef6,Supplementary material for : Learning Finer-class Networks for Universal Representations,"GIRARD ET AL.: SUPPLEMENTARY FOR FINER-CLASS NETWORKS +Supplementary material for: Learning +Finer-class Networks for Universal +Representations +Julien Girard12 +Youssef Tamaazousti123 +Hervé Le Borgne2 +Céline Hudelot3 +Both authors contributed equally. +CEA LIST +Vision Laboratory, +Gif-sur-Yvette, France. +CentraleSupélec, +MICS Laboratory, +Châtenay-Malabry, France."
8006219efb6ab76754616b0e8b7778dcfb46603d,Contributions to large-scale learning for image classification. (Contributions à l'apprentissage grande échelle pour la classification d'images),"CONTRIBUTIONSTOLARGE-SCALELEARNINGFORIMAGECLASSIFICATIONZeynepAkataPhDThesisl’´EcoleDoctoraleMath´ematiques,SciencesetTechnologiesdel’Information,InformatiquedeGrenoble"
+8010636454316faf1a09202542af040ffd04fefa,"Performance Parameter Analysis of Face Recognition Based On Fuzzy C-Means Clustering , Shape and Corner Detection","Minj Salen Kujur et al Int. Journal of Engineering Research and Applications www.ijera.com +ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.515-520 +RESEARCH ARTICLE OPEN ACCESS +Performance Parameter Analysis of Face Recognition Based On +Fuzzy C-Means Clustering, Shape and Corner Detection +Minj Salen Kujur1, Prof. Prashant Jain2 +Department of Electronics & Communication Engineering college Jabalpur"
804b4c1b553d9d7bae70d55bf8767c603c1a09e3,Subspace clustering with a learned dimensionality reduction projection,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE ICASSP 2016"
800cbbe16be0f7cb921842d54967c9a94eaa2a65,Multimodal Recognition of Emotions Multimodal Recognition of Emotions,"MULTIMODAL RECOGNITION OF @@ -7119,8 +24434,70 @@ the requirements for the degree of Master of Science Graduate Program in Computer Engineering Bo˘gazi¸ci University"
+8032a89ba67e2b35e2789983426842f688c49a93,Matching-Constrained Active Contours,"Matching-Constrained Active Contours +Junyan Wang*, Member, IEEE, Kap Luk Chan, Member, IEEE"
+801a80f7a18fccb2e8068996a73aee2cf04ae460,Optimal transport maps for distribution preserving operations on latent spaces of Generative Models,"OPTIMAL TRANSPORT MAPS FOR DISTRIBUTION PRE- +SERVING OPERATIONS ON LATENT SPACES OF GENER- +ATIVE MODELS +Eirikur Agustsson +D-ITET, ETH Zurich +Switzerland +Alexander Sage +D-ITET, ETH Zurich +Switzerland +Radu Timofte +D-ITET, ETH Zurich +Merantix GmbH +Luc Van Gool +D-ITET, ETH Zurich +ESAT, KU Leuven"
+807913b776bc5039cd3f195841419e55979ec7c7,Recreation of spontaneous non-verbal behavior on a synthetic agent EVA,"Roboti c.s. d.o.o, 2Faculty of Electrical Engineering and Computer Science, University of Maribor +IZIDOR MLAKAR, 2MATEJ ROJC +Recreation of spontaneous non-verbal behavior on a synthetic agent +Tržaška cesta 23, 2Smetanova ulica 17 +SLOVENIA +systematic +sequencing"
+8031dd2c6583d8681fdd85bdae4371c7c745713f,Generative adversarial models for people attribute recognition in surveillance,"Generative Adversarial Models for People Attribute Recognition in Surveillance +Matteo Fabbri +Simone Calderara +Rita Cucchiara +University of Modena and Reggio Emilia +via Vivarelli 10 Modena 41125 Italy"
803c92a3f0815dbf97e30c4ee9450fd005586e1a,Max-Mahalanobis Linear Discriminant Analysis Networks,"Max-Mahalanobis Linear Discriminant Analysis Networks Tianyu Pang 1 Chao Du 1 Jun Zhu 1"
+802ecaabffbece0dc2c31d44b693967c683fc5ff,Faster RER-CNN: application to the detection of vehicles in aerial images,"Faster RER-CNN: application to the detection of +vehicles in aerial images +Jean Ogier du Terrail(1,2), Fr´ed´eric Jurie(1) +(1)Normandie Univ, UNICAEN, ENSICAEN, CNRS +(2)Safran Electronics and Defense +September 21, 2018"
+801b0ae343a11a15fd7abc5720831afea6f0a61d,Similarity Learning with Listwise Ranking for Person Re-Identification,"SIMILARITY LEARNING WITH LISTWISE +RANKING FOR PERSON RE-IDENTIFICATION +Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla +Baskurt +To cite this version: +Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla Baskurt. SIMILARITY +LEARNING WITH LISTWISE RANKING FOR PERSON RE-IDENTIFICATION. International +onference on image processing, Oct 2018, Athenes, Greece. <hal-01895355> +HAL Id: hal-01895355 +https://hal.archives-ouvertes.fr/hal-01895355 +Submitted on 15 Oct 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non,"
+805c77bd351fc98d6acbee68b73af915c5cb6776,Overview of the ImageCLEF 2012 Scalable Web Image Annotation Task,"Overview of the ImageCLEF 2012 Scalable Web +Image Annotation Task +Mauricio Villegas and Roberto Paredes +Institut Tecnol`ogic d’Inform`atica +Universitat Polit`ecnica de Val`encia +Cam´ı de Vera s/n, 46022 Val`encia, Spain"
80c8d143e7f61761f39baec5b6dfb8faeb814be9,Local Directional Pattern based Fuzzy Co- occurrence Matrix Features for Face recognition,"Local Directional Pattern based Fuzzy Co- occurrence Matrix Features for Face recognition Dr. P Chandra Sekhar Reddy @@ -7140,11 +24517,63 @@ Problem in Face Recognition Ching-Ting Huang, Chaur-Chin Chen Department of Computer Science/National Tsing Hua University 01 KwanFu Rd., Sec. 2, Hsinchu, Taiwan"
+80510c47d7fad872b18d865f3957568dc512780c,Occlusion Invariant 3D Face Recognition with UMB – DB and BOSPHORUS Databases,"International Journal of Computer Applications (0975 – 8887) +National Conference on Advances in Computing (NCAC 2015) +Occlusion Invariant 3D Face Recognition with UMB – DB +nd BOSPHORUS Databases +G.E.S. R.H. Sapat College of Engineering, Nashik +G.E.S. R.H. Sapat College of Engineering, Nashik +H. Y. Patil, PhD +Assistant Professor (Dept. of E&TC), +Maharashtra +Charushila R. Singh +M.E. student (Dept. of E&TC), +Maharashtra"
+80c8f02c945c1dbbec31983164c1e4e0b742c44a,Cohort of LSTM and lexicon verification for handwriting recognition with gigantic lexicon,"Cohort of LSTM and lexicon verification for +handwriting recognition with gigantic lexicon +Bruno STUNERa,∗, Cl´ement CHATELAINa, Thierry PAQUETa +Normandie Univ, UNIROUEN, UNIHAVRE, INSA Rouen, LITIS, 76000 Rouen, France"
80097a879fceff2a9a955bf7613b0d3bfa68dc23,Active Self-Paced Learning for Cost-Effective and Progressive Face Identification,"Active Self-Paced Learning for Cost-Effective and Progressive Face Identification Liang Lin, Keze Wang, Deyu Meng, Wangmeng Zuo, and Lei Zhang"
+748260579dc2fb789335a88ae3f63c114795d047,Action and Interaction Recognition in First-Person Videos,"Action and Interaction Recognition in First-person videos +Sanath Narayan +Dept. of Electrical Engg., +IISc, Bangalore +Mohan S. Kankanhalli +School of Computing, +NUS, Singapore +Kalpathi R. Ramakrishnan +Dept. of Electrical Engg., +IISc, Bangalore"
+7484911e00afec5c08e7b83f3a1259d60035d77f,In Your Face: Startle to Emotional Facial Expressions Depends on Face Direction,"Article +In Your Face: Startle to +Emotional Facial Expressions +Depends on Face Direction +i-Perception +January-February 2017, 1–13 +! The Author(s) 2017 +DOI: 10.1177/2041669517694396 +journals.sagepub.com/home/ipe +Ole A˚ sli, Henriette Michalsen and Morten Øvervoll +Department of Psychology, University of Tromsø—The Arctic University +of Norway, Tromsø, Norway"
+747e9b36c5a1b0b8a9572da0ab416ddd1e1d2d33,Data Augmentation for Visual Question Answering,"Proceedings of The 10th International Natural Language Generation conference, pages 198–202, +Santiago de Compostela, Spain, September 4-7 2017. c(cid:13)2017 Association for Computational Linguistics"
74408cfd748ad5553cba8ab64e5f83da14875ae8,Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation and Evaluation,"Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation nd Evaluation"
+74a1e28dd2c03076124282482074e10bb02bc643,Coulomb Gans: Provably Optimal Nash Equi-,"Under review as a conference paper at ICLR 2018 +COULOMB GANS: PROVABLY OPTIMAL NASH EQUI- +LIBRIA VIA POTENTIAL FIELDS +Anonymous authors +Paper under double-blind review"
+74671fd8dd510db4abdcb93864fb5d5f77c878a0,Real-Time Viola-Jones Face Detection in a Web Browser,"Real-Time Viola-Jones +Face Detection in a +Web Browser +Theo Ephraim - Tristan Himmelman - Kaleem Siddiqi +McGill University - School of Computer Science +Centre For Intelligent Machines (CIM) +http://flashfacedetection.com"
74dbe6e0486e417a108923295c80551b6d759dbe,An HMM based Model for Prediction of Emotional Composition of a Facial Expression using both Significant and Insignificant Action Units and Associated Gender Differences,"International Journal of Computer Applications (0975 – 8887) Volume 45– No.11, May 2012 An HMM based Model for Prediction of Emotional @@ -7161,6 +24590,15 @@ Niigata, Japan Systems Science 603-1 Kamitomioka, Nagaoka Niigata, Japan"
+74032e526edb45bc6c79cb5576e69486e72a316d,Animated 3D Human Models for Use in Person Recognition Experiments,"Animated 3D Human Models for Use in Person Recognition Experiments +Jean M. Vettel1,2,3, Justin Kantner1,2, Matthew Jaswa4, Michael Miller2 +U.S. Army Research Laboratory, 2University of California, Santa Barbara, 3University of +Pennsylvania, 4DCS Corporation +Jean M Vettel +U.S. Army Research Laboratory +59 Mulberry Point Road +Aberdeen Proving Ground, MD 21005 +10.278.7431"
747c25bff37b96def96dc039cc13f8a7f42dbbc7,EmoNets: Multimodal deep learning approaches for emotion recognition in video,"EmoNets: Multimodal deep learning approaches for emotion recognition in video Samira Ebrahimi Kahou · Xavier Bouthillier · Pascal Lamblin · Caglar Gulcehre · @@ -7168,6 +24606,13 @@ Vincent Michalski · Kishore Konda · S´ebastien Jean · Pierre Froumenty · Ya Dauphin · Nicolas Boulanger-Lewandowski · Raul Chandias Ferrari · Mehdi Mirza · David Warde-Farley · Aaron Courville · Pascal Vincent · Roland Memisevic · Christopher Pal · Yoshua Bengio"
+74e6110466306f41f703d84bb3d136ba414b1998,Face Recognition System under Varying Lighting Conditions,"IOSR Journal of Computer Engineering (IOSR-JCE) +e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 14, Issue 3 (Sep. - Oct. 2013), PP 79-88 +www.iosrjournals.org +Face Recognition System under Varying Lighting Conditions +P.Kalaiselvi1, S.Nithya2 +(Asst. Professor, Department of ECE, NSN College of Engineering and Technology, Karur, Tamilnadu, India) +(Asst. Professor, Department of ECE, NSN College of Engineering and Technology, Karur, Tamilnadu, India)"
744fa8062d0ae1a11b79592f0cd3fef133807a03,Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification.,"Aalborg Universitet Deep Pain Rodriguez, Pau; Cucurull, Guillem; Gonzàlez, Jordi; M. Gonfaus, Josep ; Nasrollahi, Kamal; @@ -7188,6 +24633,21 @@ General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. ? Users may download and print one copy of any publication from the public portal for the purpose of private study or research."
+74f21f2edfa985280be63f8a01aa00541f3a5625,People Groping by Spatio-Temporal Features of Trajectories,"4-13 +MVA2013 IAPR International Conference on Machine Vision Applications, May 20-23, 2013, Kyoto, JAPAN +People Groping by Spatio-Temporal Features of Trajectories +Asami Okada†, Yusuke Moriguchi†, Norimichi Ukita†, +nd Norihiro Hagita†‡ +Nara Institute od Science and Technology +Advanced Telecommunications Research Institute International +e-mail"
+747b15ecd9a9e28bbd733527c59e5dd0aa5de7a1,Learning Visual Features from Large Weakly Supervised Data,"Learning Visual Features from Large Weakly Supervised Data +Armand Joulin∗ +Laurens van der Maaten∗ +Allan Jabri +Nicolas Vasilache +Facebook AI Research +770 Broadway, New York NY 10003"
743e582c3e70c6ec07094887ce8dae7248b970ad,Face Recognition based on Deep Neural Network,"International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8, No.10 (2015), pp.29-38 http://dx.doi.org/10.14257/ijsip.2015.8.10.04 @@ -7199,6 +24659,18 @@ M%&QRS15 7 5J(1)whereVWXisapowerweightingconstant.2.1.ConvergencetoExtrinsicZ- bei.i.d.randomvectorswithvaluesinacompactsubsetofandLebesgueden-sity\.Let]?_,aVb]anddefineZF]7VHf].Then,withprobability(w.p.)gh""jk<JDCFHmoDJDCp\mFrHtr(2)whereoDJDCisaconstantindependentof\.Furthermore,themeanlengthuv<JDCFHwfmconvergestothesamelimit.Thequantitythatdeterminesthelimit(2)inTheorem1istheex-trinsicR´enyiZ-entropyofthemultivariateLebesguedensity\:yz{mF\H7Zg!pz{\mFrHtr(3)III - 9880-7803-8484-9/04/$20.00 ©2004 IEEEICASSP 2004(cid:224)"
74156a11c2997517061df5629be78428e1f09cbd,"Preparatory coordination of head, eyes and hands: Experimental study at intersections","Cancún Center, Cancún, México, December 4-8, 2016 978-1-5090-4846-5/16/$31.00 ©2016 IEEE"
+74cbb3acfc401a397c9a4e151ff8e3ecf5ea76d0,Egocentric Video Description based on Temporally-Linked Sequences,"Egocentric Video Description based on Temporally-Linked Sequences +Marc Bola˜nosa,b, ´Alvaro Perisc, Francisco Casacubertac, Sergi Solera, Petia Radevaa,b +Universitat de Barcelona, Barcelona, Spain +Computer Vision Center, Bellaterra, Spain +PRHLT Research Center, Universitat Polit`ecnica de Val`encia, Val`encia, Spain"
+74410df341f44f5c915d97725ce396a862d44a7b,Shadow extraction and application in pedestrian detection,"Wang and Yagi EURASIP Journal on Image and Video Processing 2014, 2014:12 +http://jivp.eurasipjournals.com/content/2014/1/12 +RESEARCH +Open Access +Shadow extraction and application in +pedestrian detection +Junqiu Wang1* and Yasushi Yagi2"
749d605dd12a4af58de1fae6f5ef5e65eb06540e,Multi-Task Video Captioning with Video and Entailment Generation,"Multi-Task Video Captioning with Video and Entailment Generation Ramakanth Pasunuru and Mohit Bansal UNC Chapel Hill @@ -7210,7 +24682,7 @@ Fraunhofer Institute for Integrated Circuits IIS Department Electronic Imaging Am Wolfsmantel 33, 91058 Erlangen, Germany {andreas.ernst, tobias.ruf,"
-74c19438c78a136677a7cb9004c53684a4ae56ff,RESOUND: Towards Action Recognition without Representation Bias,"RESOUND: Towards Action Recognition +74c19438c78a136677a7cb9004c53684a4ae56ff,RESOUND: Towards Action Recognition Without Representation Bias,"RESOUND: Towards Action Recognition without Representation Bias Yingwei Li, Yi Li, and Nuno Vasconcelos UC San Diego"
@@ -7234,6 +24706,11 @@ New Zealand stylized nd control on the generated caricature."
+745ec003b7fbeb52aecd00c41ac889fcd4d88bcd,Guiding Intelligent Surveillance System by learning-by-synthesis gaze estimation,"Pattern Recognition Letters +journal homepage: www.elsevier.com +Guiding Intelligent Surveillance System by learning-by-synthesis gaze estimation +Tongtong Zhaoa, Yuxiao Yana, Jinjia Penga, Zetian Mia, Xianping Fua,∗∗ +Information Science and Technology College, Dalian Maritime University, Dalian, China."
74eae724ef197f2822fb7f3029c63014625ce1ca,Feature Extraction based on Local Directional Pattern with SVM Decision-level Fusion for Facial Expression Recognition,"International Journal of Bio-Science and Bio-Technology Vol. 5, No. 2, April, 2013 Feature Extraction based on Local Directional Pattern with SVM @@ -7242,6 +24719,24 @@ Juxiang Zhou1, Tianwei Xu1,2 and Jianhou Gan1 Key Laboratory of Education Informalization for Nationalities, Ministry of Education, Yunnan Normal University, Kunming, China College of Information, Yunnan Normal University, Kunming, China"
+744fe47157477235032f7bb3777800f9f2f45e52,"Progressive Growing of GANs for Improved Quality, Stability, and Variation","Published as a conference paper at ICLR 2018 +PROGRESSIVE GROWING OF GANS FOR IMPROVED +QUALITY, STABILITY, AND VARIATION +Tero Karras +NVIDIA +Samuli Laine +NVIDIA +Timo Aila +NVIDIA +Jaakko Lehtinen +NVIDIA and Aalto University"
+74d4224989b5937ee6c97eec1955e64ab0699f57,Facial Emotional Classifier For Natural Interaction,"Electronic Letters on Computer Vision and Image Analysis 7(4):1-12, 2008 +Facial Emotional Classifier For Natural Interaction +Isabelle Hupont, Eva Cerezo, Sandra Baldassarri +Departamento de Informática e Ingeniería de Sistemas, +Instituto de Investigación en Ingeniería de Aragón, Universidad de Zaragoza (Spain) +Received 29th November 2007, Revised 26th February 2008, Accepted 3rd June 2008 +{478953, ecerezo,"
7480d8739eb7ab97c12c14e75658e5444b852e9f,MLBoost Revisited: A Faster Metric Learning Algorithm for Identity-Based Face Retrieval,"NEGREL ET AL.: REVISITED MLBOOST FOR FACE RETRIEVAL MLBoost Revisited: A Faster Metric Learning Algorithm for Identity-Based Face @@ -7252,6 +24747,18 @@ Frederic Jurie Normandie Univ, UNICAEN, ENSICAEN, CNRS France"
+747ca08cbf258da8d2b89ba31f24bdb17d7132bb,Tall and skinny QR factorizations in MapReduce architectures,"Tall and Skinny QR factorizations +in MapReduce architectures +Paul G. Constantine +Sandia National Laboratories∗ +Albuquerque, NM +David F. Gleich +Sandia National Laboratories∗ +Livermore, CA"
+7411761e789ccb1da80984472f5df5cb084e8ba3,Towards Scene Understanding with Detailed 3D Object Representations,"Towards Scene Understanding with Detailed 3D Object Representations +M. Zeeshan Zia1, Michael Stark2, and Konrad Schindler1 +Photogrammetry and Remote Sensing, ETH Z¨urich, Switzerland +Stanford University and Max Planck Institute for Informatics"
74ba4ab407b90592ffdf884a20e10006d2223015,Partial Face Detection in the Mobile Domain,"Partial Face Detection in the Mobile Domain Upal Mahbub, Student Member, IEEE, Sayantan Sarkar, Student Member, IEEE, nd Rama Chellappa, Fellow, IEEE"
@@ -7271,6 +24778,12 @@ Queensland University of Technology (QUT) Brisbane QLD 4000, Australia Carnegie Mellon University (CMU) Pittsburgh PA 15289, USA"
+7478c2351c75183527f258aecce6931be9c9d624,Periodic Variance Maximization using Generalized Eigenvalue Decomposition applied to Remote Photoplethysmography estimation,"Periodic Variance Maximization using Generalized Eigenvalue +Decomposition applied to Remote Photoplethysmography estimation +Richard Macwan, Serge Bobbia, Yannick Benezeth, Julien Dubois, Alamin Mansouri +LE2I EA7508, Arts et M´etiers +Univ. Bourgogne Franche-Comt´e +{richard.macwan, serge.bobbia, yannick.benezeth, julien.dubois,"
744d23991a2c48d146781405e299e9b3cc14b731,Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIP.2016.2535284, IEEE Transactions on Image Processing Aging Face Recognition: A Hierarchical Learning @@ -7298,6 +24811,29 @@ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing including the URL of the record and the reason for the withdrawal request. https://eprints.whiterose.ac.uk/"
+1ab7d8da096c418c0bf93de14d128eb008a92db4,Towards three-dimensional face recognition in the real Huibin,"Towards three-dimensional face recognition in the real +Huibin Li +To cite this version: +Huibin Li. Towards three-dimensional face recognition in the real. Other. Ecole Centrale de +Lyon, 2013. English. <NNT : 2013ECDL0037>. <tel-00998798> +HAL Id: tel-00998798 +https://tel.archives-ouvertes.fr/tel-00998798 +Submitted on 2 Jun 2014 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de +recherche fran¸cais ou ´etrangers, des laboratoires +publics ou priv´es."
+1a7243913d9b8c6855b1eb3bb6566f2f1041d50a,Articulated clinician detection using 3D pictorial structures on RGB-D data,"Articulated Clinician Detection Using 3D Pictorial +Structures on RGB-D Data +Abdolrahim Kadkhodamohammadi, Afshin Gangi, Michel de Mathelin and Nicolas Padoy"
1a878e4667fe55170252e3f41d38ddf85c87fcaf,Discriminative Machine Learning with Structure,"Discriminative Machine Learning with Structure Simon Lacoste-Julien Electrical Engineering and Computer Sciences @@ -7305,6 +24841,29 @@ University of California at Berkeley Technical Report No. UCB/EECS-2010-4 http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-4.html January 12, 2010"
+1a03716411e72722f853b904a83d9c15a0d737a3,Using color texture sparsity for facial expression recognition,"Using Color Texture Sparsity for Facial Expression +Recognition +Seung Ho Lee, Hyungil Kim, +Korea Advanced +Department +Institute +of Electrical +of Science +of Korea +Republic +Daejeon, +nd Y ong Man Ro +Engineering +nd Technology +Department +Engineering +Konstantinos +of Electrical +University +N. Plataniotis"
+1ae3a26a985fe525b23f080a9e1041ecff0509ad,A Comparative Study of Statistical Conversion of Face to Voice Based on Their Subjective Impressions,"Interspeech 2018 +-6 September 2018, Hyderabad +0.21437/Interspeech.2018-2005"
1a41831a3d7b0e0df688fb6d4f861176cef97136,A Biological Model of Object Recognition with Feature Learning,"massachusetts institute of technology — artificial intelligence laboratory A Biological Model of Object Recognition with Feature Learning @@ -7314,6 +24873,79 @@ CBCL Memo 227 June 2003 © 2 0 0 3 m a s s a c h u s e t t s i n s t i t u t e o f t e c h n o l o g y, c a m b r i d g e , m a 0 2 1 3 9 u s a — w w w. a i . m i t . e d u"
+1a9e0bf9f7a9495bcdf1aeb214ccc9df9f2a9030,Challenges and Opportunities The Main Memory System : Challenges and Opportunities,"특집원고Ⅰ +The Main Memory System: Challenges and Opportunities +Carnegie Mellon University Onur Mutlu･Justin Meza･Lavanya Subramanian +The memory system is a fundamental performance and +energy bottleneck in almost all computing systems. Recent +system design, application, and technology trends that +require more capacity, bandwidth, efficiency, and predictability +out of the memory system make it an even more important +system bottleneck. At the same time, DRAM technology +is experiencing difficult technology scaling challenges +that make the maintenance and enhancement of its capacity, +energy-efficiency, and reliability significantly more costly +with conventional techniques. +In this article, after describing the demands and challenges +faced by the memory system, we examine some promising +research and design directions to overcome challenges posed +y memory scaling. Specifically, we describe three major +new research challenges and solution directions: 1) enabling +new DRAM architectures, functions, interfaces, and better +integration of the DRAM and the rest of the system (an"
+1a6b2972506d7d85100552bee99ce2b267e30d41,Learning Optimal Embedded Cascades,"Learning Optimal Embedded Cascades +Mohammad Javad Saberian and Nuno Vasconcelos, Senior Member, IEEE"
+1a3f7b9fc451b54110aaebae56c65413c620f6e2,Multilevel Linear Dimensionality Reduction for Data Analysis using Nearest-Neighbor Graphs,"Multilevel Linear Dimensionality Reduction for Data +Analysis using Nearest-Neighbor Graphs∗ +Sophia Sakellaridi +Department of Computer +Science and Engineering +University of Minnesota; +Minneapolis, MN 55455 +Haw-ren Fang +Department of Computer +Science and Engineering +University of Minnesota; +Minneapolis, MN 55455 +Yousef Saad +Department of Computer +Science and Engineering +University of Minnesota; +Minneapolis, MN 55455"
+1ae19084d2cd53c70d7e44d419df32560e417fb9,The Canadian experience using the expanded criteria donor classification for allocating deceased donor kidneys for transplantation,"Young et al. Canadian Journal of Kidney Health and Disease (2016) 3:15 +DOI 10.1186/s40697-016-0106-9 +Open Access +O R I G I N AL R ES EA R C H AR TI C L E +The Canadian experience using the +expanded criteria donor classification for +llocating deceased donor kidneys for +transplantation +Ann Young1, Stephanie N. Dixon2, Greg A. Knoll2,3, Amit X. Garg2,4, Charmaine E. Lok1,2,6, Ngan N. Lam5 +nd S. Joseph Kim1,2,6*"
+1a5151b4205ab27b1c76f98964debbfc11b124d5,Self Paced Deep Learning for Weakly Supervised Object Detection,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Self Paced Deep Learning for Weakly +Supervised Object Detection +Enver Sangineto†, Moin Nabi†, Dubravko Culibrk and Nicu Sebe,"
+1a515f0b852c2e93272677dbf6ecb05c7be0ea2e,Reduced serotonin receptor subtypes in a limbic and a neocortical region in autism.,"RESEARCH ARTICLE +Reduced Serotonin Receptor Subtypes in a Limbic and a Neocortical +Region in Autism +Adrian Oblak, Terrell T. Gibbs, and Gene J. Blatt +Autism is a behaviorally defined, neurological disorder with symptom onset before the age of 3. Abnormalities in +social-emotional behaviors are a core deficit in autism, and are characterized by impaired reciprocal–social interaction, +lack of facial expressions, and the inability to recognize familiar faces. The posterior cingulate cortex (PCC) and fusiform +gyrus (FG) are two regions within an extensive limbic-cortical network that contribute to social-emotional behaviors. +Evidence indicates that changes in brains of individuals with autism begin prenatally. Serotonin (5-HT) is one of the +earliest expressed neurotransmitters, and plays an important role in synaptogenesis, neurite outgrowth, and neuronal +migration. Abnormalities in 5-HT systems have been implicated in several psychiatric disorders, including autism, as +evidenced by immunology, imaging, genetics, pharmacotherapy, and neuropathology. Although information is known +regarding peripheral 5-HT in autism, there is emerging evidence that 5-HT systems in the central nervous system, +including various 5-HT receptor subtypes and transporters, are affected in autism. The present study demonstrated +significant reductions in 5-HT1A receptor-binding density in superficial and deep layers of the PCC and FG, and in the +density of 5-HT2A receptors in superficial layers of the PCC and FG. A significant reduction in the density of serotonin +transporters (5-HTT) was also found in the deep layers of the FG, but normal levels were demonstrated in both layers of +the PCC and superficial layers of the FG. This study provides potential substrates for decreased 5-HT modulation/ +innervation in the autism brain, and implicate two 5-HT receptor subtypes as potential neuromarkers for novel or +existing pharmacotherapies. Autism Res 2013, 6: 571–583. © 2013 International Society for Autism Research, Wiley"
1a6c3c37c2e62b21ebc0f3533686dde4d0103b3f,Implementation of Partial Face Recognition using Directional Binary Code,"International Journal of Linguistics and Computational Applications (IJLCA) ISSN 2394-6385 (Print) Volume 4, Issue 1, January – March 2017 ISSN 2394-6393 (Online) Implementation of Partial Face Recognition @@ -7328,6 +24960,36 @@ face alignment and" Valero Laparra, Gustavo Camps-Valls and Jes´us Malo Image Processing Laboratory (IPL), Universitat de Val`encia Catedr´atico A. Escardino - 46980 Paterna, Val`encia, Spain"
+1a382d4e436e3e4f3d735f6e34ba2bc61e30838e,Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection,
+1a8a2539cffba25ed9a7f2b869ebb737276ccee1,Pros and Cons of GAN Evaluation Measures,"Pros and Cons of GAN Evaluation Measures +Ali Borji"
+1ad823bf77c691f1d2b572799f8a8c572d941118,Précis of “Towards The Deep Model : Understanding Visual Recognition Through Computational Models”,"implement +the system. +Précis of “Towards The Deep Model +: Understanding Visual +Recognition Through Computational Models” +Panqu Wang +Introduction +Vision, due to its significance in surviving and socializing, is one of the most important and +extensively studied sensory functions in the human brain. In order to fully understand visual +information processing, or more specifically, visual recognition, David Marr proposed the +Tri-level Hypothesis [29], in that three levels of the system should be studied: the computational +goal of the system, the internal representation or the algorithm the system uses to achieve the +goal, and the neural substrates that +is well-known that visual +recognition in the human brain is implemented by the ventral visual pathway [32], which +receives visual information from the retina and goes through a layered structure including V1 +(also known as the primary visual cortex), V2, V4, before reaching the inferior temporal cortex +(IT). The topographic mapping between the retina and the human visual cortex follows a +log-polar transformation, in which the Cartesian coordinates of the retina are transformed to +polar coordinates (polar angle and eccentricity) in the human visual cortex. From V1 to V4, each"
+1abf6491d1b0f6e8af137869a01843931996a562,ParseNet: Looking Wider to See Better,"ParseNet: Looking Wider to See Better +Wei Liu +UNC Chapel Hill +Andrew Rabinovich +MagicLeap Inc. +Alexander C. Berg +UNC Chapel Hill"
1a031378cf1d2b9088a200d9715d87db8a1bf041,D Eep D Ictionary L Earning : S Ynergizing R E - Construction and C Lassification,"Workshop track - ICLR 2018 DEEP DICTIONARY LEARNING: SYNERGIZING RE- CONSTRUCTION AND CLASSIFICATION @@ -7352,15 +25014,73 @@ Such a capability can enable a range of new services such as content-based perso roadcasts given that the MPEG-7 based data models fit in well with specifications for advanced television services such as TV-Anytime andAlliance for Telecommunications Industry Solutions IPTV Interoperability Forum."
+1a7e385d2aa041ca8931784fb7664e9905194565,Sentiment Analysis Using Social Multimedia,"Chapter 2 +Sentiment Analysis Using Social +Multimedia +Jianbo Yuan, Quanzeng You and Jiebo Luo"
+1ad88221f308bf9f36775650f880f32d91ce929a,Learning a Recurrent Residual Fusion Network for Multimodal Matching,"Learning a Recurrent Residual Fusion Network for Multimodal Matching +Yu Liu +Yanming Guo +Erwin M. Bakker +Michael S. Lew +LIACS Media Lab, Leiden University, Leiden, The Netherlands +{y.liu, y.guo, e.m.bakker,"
+1a0912bb76777469295bb2c059faee907e7f3258,Mask R-CNN,"Mask R-CNN +Kaiming He Georgia Gkioxari +Piotr Doll´ar Ross Girshick +Facebook AI Research (FAIR)"
+1afe9919ddb2b245e21b610fa96037724bcdf648,SceneNet: A Perceptual Ontology for Scene Understanding,"SceneNet: A Perceptual Ontology for Scene +Understanding +Ilan Kadar and Ohad Ben-Shahar +Ben-Gurion University of the Negev"
1a9a192b700c080c7887e5862c1ec578012f9ed1,Discriminant Subspace Analysis for Face Recognition with Small Number of Training Samples,"IEEE TRANSACTIONS ON SYSTEM, MAN AND CYBERNETICS, PART B Discriminant Subspace Analysis for Face Recognition with Small Number of Training Samples Hui Kong, Xuchun Li, Matthew Turk, and Chandra Kambhamettu"
+1abdf07ce2fca11a26222dedd581b68b141af3f2,Face Recognition Aiding Historical Photographs Indexing Using a Two-Stage Training Scheme and an Enhanced Distance Measure,"Face Recognition Aiding Historical Photographs Indexing +Using a Two-stage Training Scheme and an Enhanced Distance Measure +Ana Paula Brand˜ao Lopes1,2, Camillo Jorge Santos Oliveira1,3, Arnaldo de Albuquerque Ara´ujo1 +Computer Science Department – Federal University of Minas Gerais +Av. Antˆonio Carlos, 6627, Pampulha, CEP 31270–901, Belo Horizonte, MG, Brazil +Exact and Technological Sciences Department – State University of Santa Cruz +Rodovia Ilh´eus-Itabuna, km 16 – Pavilh˜ao Jorge Amado, CEP 45600-000, Ilh´eus, BA, Brazil +Informatics Department – Pontifical Catholic University of Minas Gerais +Rua Rio Comprido, 4.580 - CEP 32.010-025, Contagem, MG, Brazil, +{paula, camillo,"
+1a2431e3b35a4a4794dc38ef16e9eec2996114a1,Automated Face Recognition: Challenges and Solutions,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
1a8ccc23ed73db64748e31c61c69fe23c48a2bb1,Extensive Facial Landmark Localization with Coarse-to-Fine Convolutional Network Cascade,"Extensive Facial Landmark Localization with Coarse-to-fine Convolutional Network Cascade Erjin Zhou Haoqiang Fan Zhimin Cao Yuning Jiang Qi Yin Megvii Inc."
+1afe5d933b58b4dd982a559cc6ec1d17959239de,Enhanced canonical correlation analysis with local density for cross-domain visual classification,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE +ICASSP 2017"
+1a86620ea59816564db30fe0ae94cc422c5266e3,Can 3D Pose be Learned from 2D Projections Alone?,"Can 3D Pose be Learned from +D Projections Alone? +Dylan Drover, Rohith MV, Ching-Hang Chen, +Amit Agrawal, Ambrish Tyagi, and Cong Phuoc Huynh +Amazon Lab126 Inc., Sunnyvale, CA, USA +{droverd, kurohith, chinghc, aaagrawa, +mbrisht,"
1ad97cce5fa8e9c2e001f53f6f3202bddcefba22,Grassmann Averages for Scalable Robust PCA,"Grassmann Averages for Scalable Robust PCA Aasa Feragen DIKU and MPIs T¨ubingen∗ @@ -7368,6 +25088,69 @@ Denmark and Germany Søren Hauberg DTU Compute∗ Lyngby, Denmark"
+1a219e7bcd8f30f886a1f24a8c05bc26bef83ff9,Crowd Counting with Density Adaption Networks,"Crowd Counting with Density Adaption Networks +Li Wang, Weiyuan Shao, Yao Lu, Hao Ye, Jian Pu, Yingbin Zheng"
+1a1ed320882c00c94d9f738b7b14eadd941376ed,Extracting Human Face Similarity Judgments: Pairs or Triplets?,"Extracting Human Face Similarity Judgments: Pairs or Triplets? +Linjie Li1, Vicente Malave2, Amanda Song2, and Angela J. Yu2 +Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, USA +Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA"
+1a1955920ee36d58265fe17100ca451d899e8372,A Local Feature based on Lagrangian Measures for Violent Video Classification,"Best Paper Award, IET 6th International Conference on Imaging for Crime Prevention and Detection, 2015 +A Local Feature based on Lagrangian Measures for Violent Video +Classification +Tobias Senst, Volker Eiselein, Thomas Sikora +Communication Systems Group, Technische Universität Berlin, Germany +Keywords: violent video detection, +recognition, lagrangian measures, lagrangian framework +local feature, action"
+1a9997d8421d577a728f6ac119d4b14a3f46402c,Using Tectogrammatical Annotation for Studying Actors and Actions in Sallust ’ s Bellum Catilinae,"The Prague Bulletin of Mathematical Linguistics +NUMBER 111 OCTOBER 2018 5–28 +Using Tectogrammatical Annotation for Studying +Actors and Actions in Sallust’s Bellum Catilinae +Berta González Saavedra,a Marco Passarottib +Dep. de Filología Clásica, Universidad Autónoma de Madrid, Spain +CIRCSE Research Centre. Università Cattolica del Sacro Cuore, Milan, Italy"
+1a6d748365dbf3b17f2db371a30469478ee7b142,DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2016.2587642, IEEE +Transactions on Pattern Analysis and Machine Intelligence +IEEE TRANSACTIONS PATTERN ANALYSIS AND MACHINE INTELLIGENCE +DeepID-Net: Object Detection with Deformable +Part Based Convolutional Neural Networks +Wanli Ouyang*, Member, IEEE, Xingyu Zeng*, Student Member, IEEE, +Xiaogang Wang, Member, IEEE,Shi Qiu Member, IEEE, Ping Luo, Member, IEEE, +Yonglong Tian Student Member, IEEE, Hongsheng Li, Member, IEEE, Shuo Yang Student Member, IEEE, +Zhe Wang, Student Member, IEEE, Hongyang Li, Kun Wang, Junjie Yan, +Chen-Change Loy, Member, IEEE, Xiaoou Tang, Fellow, IEEE"
+1a54a8b0c7b3fc5a21c6d33656690585c46ca08b,Fast Feature Pyramids for Object Detection,"Fast Feature Pyramids for Object Detection +Piotr Doll´ar, Ron Appel, Serge Belongie, and Pietro Perona"
+1a51bc5f9f12f6794297a426739350ae57c87731,Image classification with CNN-based Fisher vector coding,"Kent Academic Repository +Full text document (pdf) +Citation for published version +Song, Yan and Hong, Xinhai and McLoughlin, Ian Vince and Dai, Li-Rong (2017) Image Classification +with CNN-based Fisher Vector Coding. In: IEEE International Conference on Visual Communications +nd Image Processing 2016, 27-30 Nov 2016, Chengdu, Sichuan, China. +https://doi.org/10.1109/VCIP.2016.7805494 +Link to record in KAR +http://kar.kent.ac.uk/57115/ +Document Version +Author's Accepted Manuscript +Copyright & reuse +Content in the Kent Academic Repository is made available for research purposes. Unless otherwise stated all +ontent is protected by copyright and in the absence of an open licence (eg Creative Commons), permissions +for further reuse of content should be sought from the publisher, author or other copyright holder. +Versions of research +The version in the Kent Academic Repository may differ from the final published version. +Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the +published version of record. +Enquiries"
+1aa52a25c2967b8bc228268c9ab5a96a32d2189b,Visual Fashion-Product Search at SK Planet,"Visual Fashion-Product Search at SK Planet +Taewan Kim, Seyeoung Kim, Sangil Na, Hayoon Kim, Moonki Kim, Byoung-Ki Jeon +Machine Intelligence Lab. +SK Planet, SeongNam City, South Korea"
+1a0b09e7e9182a68fc457bb888536b9023f6c9fd,Multi-affinity spectral clustering,"MULTI-AFFINITY SPECTRAL CLUSTERING +Hsin-Chien Huang(cid:63)† +Yung-Yu Chuang(cid:63) +Chu-Song Chen† +(cid:63)National Taiwan University +Academia Sinica"
1a7a2221fed183b6431e29a014539e45d95f0804,Person Identification Using Text and Image Data,"Person Identification Using Text and Image Data David S. Bolme, J. Ross Beveridge and Adele E. Howe Computer Science Department @@ -7377,6 +25160,22 @@ Fort Collins, Colorado 80523" Effectiveness of Crowdsourcing Markus Rokicki, Sergiu Chelaru, Sergej Zerr, Stefan Siersdorfer L3S Research Center, Hannover, Germany"
+28bd795c580ca24f40dc82cd01d9d277749d2661,Site-adaptation methods for face recognition,"Site-adaptation methods for face recognition +Jilin Tu and Xiaoming Liu and Peter Tu"
+28209a6ef1de7c10ec13717eba8bad7c2f4feba7,Deep Representation of Facial Geometric and Photometric Attributes for Automatic 3D Facial Expression Recognition,"Deep Representation of Facial Geometric and +Photometric Attributes for Automatic 3D Facial +Expression Recognition +Huibin Li, Jian Sun∗, Dong Wang, Zongben Xu, and Liming Chen"
+28e9ae07540e3709e7a3a6242f636f893ba557e6,Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework,"Learning to Select Pre-trained Deep Representations with +Bayesian Evidence Framework +Yong-Deok Kim∗1 +Taewoong Jang∗2 Bohyung Han3 +Seungjin Choi3 +Software R&D Center, Device Solutions, Samsung Electronics, Korea +Department of Computer Science and Engineering, POSTECH, Korea +Stradvision Inc., Korea"
+286eb053f55e45ad5d0490c1c18f6d80381dfb4b,Block-Sparse Recovery via Convex Optimization,"Block-Sparse Recovery via Convex Optimization +Ehsan Elhamifar, Student Member, IEEE, and Ren´e Vidal, Senior Member, IEEE"
287795991fad3c61d6058352879c7d7ae1fdd2b6,Biometrics Security: Facial Marks Detection from the Low Quality Images,"International Journal of Computer Applications (0975 – 8887) Volume 66– No.8, March 2013 Biometrics Security: Facial Marks Detection from the @@ -7390,12 +25189,66 @@ Ziaul Haque Choudhury K.M.M B.S.Abdur Rahman University B.S.Abdur Rahman University Dept. Of Information Technology Dept. Of Computer Science & Engineering Chennai, India Chennai, India"
+282578039c767f3d393529565cae6be56fda6242,Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes,"Augmented Reality Meets Computer Vision : Efficient Data Generation for +Urban Driving Scenes +Hassan Abu Alhaija1 +Siva Karthik Mustikovela1 +Lars Mescheder2 Andreas Geiger2,3 Carsten Rother1 +Computer Vision Lab, TU Dresden +Autonomous Vision Group, MPI for Intelligent Systems T¨ubingen +Computer Vision and Geometry Group, ETH Z¨urich"
+285faa4cc54ef9b1834128705e0f96ad17b61e0b,SIFT Flow: Dense Correspondence across Scenes and Its Applications,"SIFT Flow: Dense Correspondence across +Scenes and its Applications +Ce Liu, Member, IEEE, Jenny Yuen, Student Member, IEEE, and Antonio Torralba, Member, IEEE"
28d7029cfb73bcb4ad1997f3779c183972a406b4,Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification,"Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification Zaidao Wen, Biao Hou, Member, IEEE, and Licheng Jiao, Senior Member, IEEE"
280d59fa99ead5929ebcde85407bba34b1fcfb59,Online Nonnegative Matrix Factorization With Outliers,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE ICASSP 2016"
+28126d165f73c2a18600a9b0440f5e80191d52d9,Clock-Modeled Ternary Spatial Relations for Visual Scene Analysis,"Clock-Modeled Ternary Spatial Relations +for Visual Scene Analysis +Joanna Isabelle Olszewska +School of Computing and Engineering, University of Huddersfield +Queensgate, Huddersfield, HD1 3DH, United Kingdom"
+287c5be2610e1c61798851feb32b88c424acfbf9,Hierarchical Co-Attention for Visual Question Answering,"Hierarchical Co-Attention for Visual Question Answering +Jiasen Lu, Jianwei Yang, Dhruv Batra, Devi Parikh +Virginia Tech +{jiasenlu, jw2yang, dbatra,"
+28f9cf85ebbff86207e1f6067880bb23daff0878,Prime Object Proposals with Randomized Prim's Algorithm,"Prime Object Proposals with Randomized Prim’s Algorithm +Santiago Manen1 +Matthieu Guillaumin1 +Luc Van Gool1,2 +Computer Vision Laboratory +ESAT - PSI / IBBT +{smanenfr, guillaumin, +ETH Zurich +K.U. Leuven"
+286ea63b1b5df1b8b67718f25b47357ec3168e97,Human parsing using stochastic and-or grammars and rich appearances,"Human Parsing using Stochastic And-Or +Grammars and Rich Appearances +Brandon Rothrock and Song-Chun Zhu +UCLA Dept. of Computer Science +Thursday, November 17, 11"
+284be8be0c6bedc36dfe43229bc84345ab0aedc2,Faster Training of Mask R-CNN by Focusing on Instance Boundaries,"Faster Training of Mask R-CNN by Focusing on Instance Boundaries$ +Roland S. Zimmermanna,b,1, Julien N. Siemsa,c,2 +BMW Car IT GmbH, Lise-Meitner-Straße 14, 89081 Ulm, Germany +Georg-August University of G¨ottingen, Friedrich-Hund-Platz 1, 37077 G¨ottingen, Germany +Albert Ludwig University of Freiburg, Fahnenbergplatz, 79085 Freiburg im Breisgau, Germany"
+28f53ec7732299fa946ed3fc27bf691a6ab5c60c,Spatial as Deep: Spatial CNN for Traffic Scene Understanding,"Spatial As Deep: Spatial CNN for Traffic Scene Understanding +Xingang Pan1, Jianping Shi2, Ping Luo1, Xiaogang Wang1, and Xiaoou Tang1 +{px117, pluo, +The Chinese University of Hong Kong 2SenseTime Group Limited"
+283550fce0fdc0876db5df533625dffdfcd8d099,Fairness-aware scheduling on single-ISA heterogeneous multi-cores,"Fairness-Aware Scheduling on +Single-ISA Heterogeneous Multi-Cores +Kenzo Van Craeynest†◦ +Ghent University, Belgium +Shoaib Akram† +Wim Heirman†◦ +◦ExaScience Lab, Belgium +Aamer Jaleel‡ +Lieven Eeckhout† +VSSAD, Intel Corporation +(e.g.,"
28cd46a078e8fad370b1aba34762a874374513a5,"cvpaper.challenge in 2016: Futuristic Computer Vision through 1, 600 Papers Survey","CVPAPER.CHALLENGE IN 2016, JULY 2017 vpaper.challenge in 2016: Futuristic Computer Vision through 1,600 Papers Survey @@ -7403,9 +25256,73 @@ Hirokatsu Kataoka, Soma Shirak- be, Yun He, Shunya Ueta, Teppei Suzuki, Kaori Abe, Asako Kanezaki, Shin’ichiro Morita, Toshiyuki Yabe, Yoshihiro Kanehara, Hiroya Yatsuyanagi, Shinya Maruyama, Ryosuke Taka- sawa, Masataka Fuchida, Yudai Miyashita, Kazushige Okayasu, Yuta Matsuzaki"
+28daa489dace2d2f040dcdbbd2d4ab919b046254,2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning,"D/3D Pose Estimation and Action Recognition using Multitask Deep Learning +ETIS UMR 8051, Paris Seine University, ENSEA, CNRS, F-95000, Cergy, France +Sorbonne Universit´e, CNRS, Laboratoire d’Informatique de Paris 6, LIP6, F-75005 Paris, France +Diogo C. Luvizon1, David Picard1,2, Hedi Tabia1 +{diogo.luvizon, picard,"
+2805daf3795e4e153d79dbecfe88b830ddc068d3,Articulated human motion tracking with foreground learning,"ARTICULATED HUMAN MOTION TRACKING WITH FOREGROUND LEARNING +Aichun Zhu1, Hichem Snoussi1, Abel Cherouat2 +ICD - LM2S - Universit´e de Technologie de Troyes (UTT) - UMR STMR CNRS +ICD - GAMMA3 - Universit´e de Technologie de Troyes (UTT) - UMR STMR CNRS +2 rue Marie Curie - CS 42060 - 10004 Troyes cedex - France +E-mail :{aichun.zhu, hichem.snoussi,"
+280d45fb813e75622b7c584ee7fba70066245871,Visual Tracking with Online Incremental Deep Learning and Particle Filter,"International Journal of Signal Processing, Image Processing and Pattern Recognition +Vol.8, No.12 (2015), pp.107-120 +http://dx.doi.org/10.14257/ijsip.2015.8.12.12 +Visual Tracking with Online Incremental Deep Learning and +Particle Filter +Shuai Cheng 1, Yonggang Cao3,1, Junxi Sun2 and Guangwen Liu1* +School of Electronic Information Engineering, Changchun University of Science +School of Computer Science and information Technology, Northeast Normal +nd Technology, Changchun, China +Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of +University, Changchun, China +Sciences, Changchun, China"
+2803a7e8e6057d4e9462b37b258e670df61a742d,The Conference on Empirical Methods in Natural Language Processing Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing,"EMNLP2017TheConferenceonEmpiricalMethodsinNaturalLanguageProcessingProceedingsofthe2ndWorkshoponStructuredPredictionforNaturalLanguageProcessingSeptember9-11,2017Copenhagen,Denmark"
+28795f32b324eb3601e9a8c1ce93335691e120f3,CliqueCNN: Deep Unsupervised Exemplar Learning,"CliqueCNN: Deep Unsupervised Exemplar Learning +Miguel A. Bautista∗, Artsiom Sanakoyeu∗, Ekaterina Sutter, Björn Ommer +Heidelberg Collaboratory for Image Processing +IWR, Heidelberg University, Germany"
+28103f6c09fd64c90a738076b0681400d4d31c9f,Color Invariants for Person Reidentification,"Color Invariants for Person +Re-Identification +Igor Kviatkovsky +Technion - Computer Science Department - M.Sc. Thesis MSC-2012-03 - 2012"
+2891ceceaf586e4ae013d932978074ff0a06801f,Joint statistical analysis of images and keywords with applications in semantic image enhancement,"Joint Statistical Analysis of Images and Keywords with +Applications in Semantic Image Enhancement +Albrecht Lindner +School of Computer and +Communication Sciences +EPFL, Switzerland +Nicolas Bonnier +Océ Print Logic Technologies +Créteil, France +Appu Shaji +School of Computer and +Communication Sciences +EPFL, Switzerland +Sabine Süsstrunk +School of Computer and +Communication Sciences +EPFL, Switzerland"
+28d65e4d72638983fbc723b102d78b10587c06aa,Low Resolution Sparse Binary Face Patterns,
+28b6adbc5ef790413431cdb2f512432862778b3b,Security and Surveillance,"Security and Surveillance +Shaogang Gong and Chen Change Loy and Tao Xiang"
+286c1e0b34ee6d40706ca6a02604420a192204e7,An overview of NuDetective Forensic Tool and its usage to combat child pornography in Brazil,"An overview of NuDetective Forensic Tool and its usage +to combat child pornography in Brazil +Pedro Monteiro da Silva Eleuterio and Mateus de Castro Polastro +Brazilian Federal Police"
28b5b5f20ad584e560cd9fb4d81b0a22279b2e7b,A New Fuzzy Stacked Generalization Technique and Analysis of its Performance,"A New Fuzzy Stacked Generalization Technique nd Analysis of its Performance Mete Ozay, Student Member, IEEE, Fatos T. Yarman Vural, Member, IEEE"
+28c24f16e20c83c747f2aca8232f2cb6614905f5,The Role of Face Parts in Gender Recognition,"The Role of Face Parts in Gender Recognition +Yasmina Andreu and Ram´on A. Mollineda +Dept. Llenguatges i Sistemes Inform`atics +Universitat Jaume I. Castell´o de la Plana, Spain"
+283181a2173b485726664edc6fe73f0465387629,Random Temporal Skipping for Multirate Video Analysis,"Random Temporal Skipping for Multirate Video +Analysis +Yi Zhu1 and Shawn Newsam1 +University of California at Merced, Merced CA 95343, USA"
28bc378a6b76142df8762cd3f80f737ca2b79208,Understanding Objects in Detail with Fine-Grained Attributes,"Understanding Objects in Detail with Fine-grained Attributes Andrea Vedaldi1 Siddharth Mahendran2 @@ -7421,6 +25338,61 @@ Naomi Saphra2 Sammy Mohamed9 Iasonas Kokkinos3 Karen Simonyan1"
+2814d558b4d7425b5dae6b3dbbf5f4a08650fcb1,A joint estimation of head and body orientation cues in surveillance video,"A Joint Estimation of Head and Body Orientation Cues in Surveillance Video +Cheng Chen +Alexandre Heili +Jean-Marc Odobez +Idiap Research Institute – CH-1920, Martigny, Switzerland∗"
+28e77337bcb88e37d36f5660709a53e71377a2a8,5 Discriminative Cluster Analysis,",250+OPEN ACCESS BOOKS106,000+INTERNATIONALAUTHORS AND EDITORS112+ MILLIONDOWNLOADSBOOKSDELIVERED TO151 COUNTRIESAUTHORS AMONGTOP 1%MOST CITED SCIENTIST12.2%AUTHORS AND EDITORSFROM TOP 500 UNIVERSITIESSelection of our books indexed in theBook Citation Index in Web of Science™Core Collection (BKCI)Chapter from the book Theory and Novel Applications of Machine LearningDownloaded from:http://www.intechopen.com/books/theory_and_novel_applications_of_machine_learningPUBLISHED BYWorld's largest Science,Technology & Medicine Open Access book publisherInterested in publishing with InTechOpen?Contact us at"
+2842cebee2793c9b4f503895a32b328b7781b60e,BWIBots: A platform for bridging the gap between AI and human-robot interaction research,"Article +BWIBots: A platform for bridging the +gap between AI and human–robot +interaction research +The International Journal of +Robotics Research +© The Author(s) 2017 +Reprints and permissions: +sagepub.co.uk/journalsPermissions.nav +DOI: 10.1177/0278364916688949 +journals.sagepub.com/home/ijr +Piyush Khandelwal1, Shiqi Zhang1,2, Jivko Sinapov1, Matteo Leonetti1,3, Jesse Thomason1, +Fangkai Yang4, Ilaria Gori5, Maxwell Svetlik1, Priyanka Khante1, Vladimir Lifschitz1, +J. K. Aggarwal5, Raymond Mooney1 and Peter Stone1"
+28af8e1a3cb3a158f8a642c8493fcfb207743d0a,Better Image Segmentation by Exploiting Dense Semantic Predictions,"Better Image Segmentation by Exploiting Dense +Semantic Predictions +Qiyang Zhao, Lewis D Griffin +Beihang University & UCL"
+2864c8df356b1b915e16bb285bda64bfd7396f74,3D Face Reconstruction from Stereo: A Model Based Approach,"-4244-1437-7/07/$20.00 ©2007 IEEE +III - 65 +ICIP 2007"
+2848cde23fe32c30980183f33b6a2c2ce7526726,Three-Dimensional Model-Based Human Detection in Crowded Scenes,"Title +Three-dimensional model-based human detection in crowded +scenes +Author(s) +Wang, L; Yung, NHC +Citation +v. 13 n. 2, p. 691-703 +Issued Date +http://hdl.handle.net/10722/155766 +Rights +Copyright © IEEE.; ©20xx IEEE. Personal use of this material is +permitted. However, permission to reprint/republish this material +for advertising or promotional purposes or for creating new +ollective works for resale or redistribution to servers or lists, or +to reuse any copyrighted component of this work in other works +must be obtained from the IEEE.; This work is licensed under a +Creative Commons Attribution-NonCommercial-NoDerivatives +.0 International License."
+287afb29b5aef6255a5882418b87e6b41cc9b29d,Nude Detection in Video Using Bag-of-Visual-Features,"Nude Detection in Video using Bag-of-Visual-Features +Ana Paula B. Lopes∗†, Sandra E. F. de Avila∗, Anderson N. A. Peixoto∗, +Rodrigo S. Oliveira∗, Marcelo de M. Coelho∗‡ and Arnaldo de A. Ara´ujo∗ +Computer Science Department, Federal University of Minas Gerais – UFMG +Exact and Technological Sciences Department, State University of Santa Cruz – UESC +1270–010, Belo Horizonte, MG, Brazil +5662–000, Ilh´eus, BA, Brazil +Preparatory School of Air Cadets – EPCAR +6205–900, Barbacena, MG, Brazil +{paula, sandra, andenap, rsilva, mcoelho,"
28bcf31f794dc27f73eb248e5a1b2c3294b3ec9d,Improved Combination of LBP plus LFDA for Facial Expression Recognition using SRC,"International Journal of Computer Applications (0975 – 8887) Volume 96– No.13, June 2014 Improved Combination of LBP plus LFDA for Facial @@ -7432,6 +25404,30 @@ human facial expression recognition"
+288bddfabe739b32721df62d821632e3dafed06a,Robust multi-image based blind face hallucination,"Robust Multi-Image Based Blind Face Hallucination +Yonggang Jin, 2Christos-Savvas Bouganis +University of Bristol. 2Imperial College London. +1.56 0.73 +3.15 0.80 +3.61 0.82 +3.32 0.80 +3.98 0.83 +3.63 0.82 +PCA-Init +PCA-Est +PCA-GT +MPPCA-Est MPPCA-GT +Methods +Blurring +Trans. +9.67 +Initial +9.52 +[1, 5]"
+2830fb5282de23d7784b4b4bc37065d27839a412,Poselets: Body part detectors trained using 3D human pose annotations,"Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations ∗ +Lubomir Bourdev1,2 and Jitendra Malik1 +EECS, U.C. Berkeley, Berkeley, CA 94720 +Adobe Systems, Inc., 345 Park Ave, San Jose, CA 95110"
28fe6e785b32afdcd2c366c9240a661091b850cf,Facial Expression Recognition using Patch based Gabor Features,"International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 10 – No.7, March 2016 – www.ijais.org @@ -7447,6 +25443,8 @@ Mumbai, India Anju Chandran Department Mumbai, India"
+28e1c113b1b57e0731c189d28e404cea3bddf260,Template based Mole Detection for Face,"is used +recognition"
28c9198d30447ffe9c96176805c1cd81615d98c8,No evidence that a range of artificial monitoring cues influence online donations to charity in an MTurk sample,"rsos.royalsocietypublishing.org Research Cite this article: Saunders TJ, Taylor AH, @@ -7467,6 +25465,16 @@ reputation, online behaviour Author for correspondence: Quentin D. Atkinson e-mail:"
+284b5dafe6d8d7552794ccd2efb4eabb12dc3512,Efficient and accurate inversion of multiple scattering with deep learning,"Efficient and accurate inversion of multiple scattering with deep learning +Yu Sun1, Zhihao Xia1, and Ulugbek S. Kamilov1,2,∗ +Department of Computer Science and Engineering, Washington University in St. Louis, MO 63130, USA. +Department of Electrical and Systems Engineering, Washington University in St. Louis, MO 63130, USA. +email:"
+28446fa9d9ac0468cc715594a6dcc0ac5d9288a5,Semantic Instance Segmentation for Autonomous Driving Bert,"Semantic Instance Segmentation for Autonomous Driving +Bert De Brabandere +Davy Neven +Luc Van Gool +ESAT-PSI, KU Leuven"
2866cbeb25551257683cf28f33d829932be651fe,A Two-Step Learning Method For Detecting Landmarks on Faces From Different Domains,"In Proceedings of the 2018 IEEE International Conference on Image Processing (ICIP) The final publication is available at: http://dx.doi.org/10.1109/ICIP.2018.8451026 A TWO-STEP LEARNING METHOD FOR DETECTING LANDMARKS @@ -7475,7 +25483,49 @@ Bruna Vieira Frade Erickson R. Nascimento Universidade Federal de Minas Gerais (UFMG), Brazil {brunafrade,"
+28589357a7631581e55ec6db3cde2e24e4789482,Involuntary processing of social dominance cues from bimodal face-voice displays.,"Cognition and Emotion +ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20 +Involuntary processing of social dominance cues +from bimodal face-voice displays +Virginie Peschard, Pierre Philippot & Eva Gilboa-Schechtman +To cite this article: Virginie Peschard, Pierre Philippot & Eva Gilboa-Schechtman (2016): +Involuntary processing of social dominance cues from bimodal face-voice displays, Cognition and +Emotion, DOI: 10.1080/02699931.2016.1266304 +To link to this article: http://dx.doi.org/10.1080/02699931.2016.1266304 +Published online: 21 Dec 2016. +Submit your article to this journal +Article views: 33 +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pcem20 +Download by: [UCL Service Central des Bibliothèques] +Date: 25 April 2017, At: 23:38"
+281be1be2f0ecce173e3678a7e87419f0815e016,Studies of Plain-to-Rolled Fingerprint Matching Using the NIST Algorithmic Test Bed (ATB),"Studies of Plain-to-Rolled Fingerprint +Matching Using the NIST +Algorithmic Test Bed (ATB) +NISTIR 7112 +Stephen S. Wood +Charles L. Wilson +April 2004"
+28eceb438da0b841bbd3d02684dbfa263838ed60,Photographic Image Synthesis with Cascaded Refinement Networks,"Photographic Image Synthesis with Cascaded Refinement Networks +Qifeng Chen† ‡ +Vladlen Koltun† +(a) Input semantic layouts +(b) Synthesized images +Figure 1. Given a pixelwise semantic layout, the presented model synthesizes an image that conforms to this layout. (a) Semantic layouts +from the Cityscapes dataset of urban scenes; semantic classes are coded by color. (b) Images synthesized by our model for these layouts. +The layouts shown here and throughout the paper are from the validation set and depict scenes from new cities that were never seen during +training. Best viewed on the screen."
+28f5f8dc2f2f9f2a4e49024fe6aa7e9a63b23ab0,Vision-based bicycle detection and tracking using a deformable part model and an EKF algorithm,"Vision-based Bicycle Detection and Tracking using a Deformable Part +Model and an EKF Algorithm +Hyunggi Cho, Paul E. Rybski and Wende Zhang"
28aa89b2c827e5dd65969a5930a0520fdd4a3dc7,Characterization and Classification of Faces across Age Progression,
+283b3160f02db64759259b4eb39dd54c4969d6f8,ActivityNet: A large-scale video benchmark for human activity understanding,"ActivityNet: A Large-Scale Video Benchmark for Human Activity +Understanding +Fabian Caba Heilbron1,2, Victor Escorcia1,2, Bernard Ghanem2 and Juan Carlos Niebles1 +King Abdullah University of Science and Technology (KAUST), Saudi Arabia +Universidad del Norte, Colombia"
28b061b5c7f88f48ca5839bc8f1c1bdb1e6adc68,Predicting User Annoyance Using Visual Attributes,"Predicting User Annoyance Using Visual Attributes Gordon Christie Virginia Tech @@ -7485,6 +25535,22 @@ Ujwal Krothapalli Virginia Tech Devi Parikh Virginia Tech"
+28f1f6cbe07b117387e2b07c11e7ac9c4ef8cf95,A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data,"Article +A Machine Learning Approach to Pedestrian +Detection for Autonomous Vehicles Using +High-Definition 3D Range Data +Pedro J. Navarro *,†, Carlos Fernández †, Raúl Borraz † and Diego Alonso † +División de Sistemas en Ingeniería Electrónica (DSIE), Universidad Politécnica de Cartagena, +Campus Muralla del Mar, s/n, Cartagena 30202, Spain; (C.F.); +(R.B.); (D.A.) +* Correspondence: Tel.: +34-968-32-6546 +These authors contributed equally to this work. +Academic Editor: Felipe Jimenez +Received: 31 October 2016; Accepted: 15 December 2016; Published: 23 December 2016"
+1701ee9e9518a055e82e79f6425645c4797c19de,Supervised Hashing Using Graph Cuts and Boosted Decision Trees,"APPEARING IN IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE, FEB. 2015 +Supervised Hashing Using Graph Cuts and +Boosted Decision Trees +Guosheng Lin, Chunhua Shen, Anton van den Hengel"
17a85799c59c13f07d4b4d7cf9d7c7986475d01c,Extending Procrustes Analysis: Building Multi-view 2-D Models from 3-D Human Shape Samples,"ADVERTIMENT. La consulta d’aquesta tesi queda condicionada a l’acceptació de les següents ondicions d'ús: La difusió d’aquesta tesi per mitjà del servei TDX (www.tesisenxarxa.net) ha estat autoritzada pels titulars dels drets de propietat intel·lectual únicament per a usos privats @@ -7505,11 +25571,58 @@ persona autora. WARNING. On having consulted this thesis you’re accepting the following use conditions: Spreading this thesis by the TDX (www.tesisenxarxa.net) service has been authorized by the titular of the intellectual property rights only for private uses placed in investigation and teaching"
+174ddb6379b91a0e799e9988d0e522a5af18f91d,ChatPainter: Improving Text to Image Generation using Dialogue,"ChatPainter: Improving Text to Image Generation using Dialogue +Shikhar Sharma 1 Dendi Suhubdy 2 3 Vincent Michalski 2 3 1 Samira Ebrahimi Kahou 1 Yoshua Bengio 2 3"
+17c62bff70eb0919864f111df4930062aded729a,Encoding Spatial Context in Local Image Descriptors,"Universit¨at des Saarlandes +Max-Planck-Institut f¨ur Informatik +Encoding Spatial Context in +Local Image Descriptors +Masterarbeit im Fach Informatik +Master’s Thesis in Computer Science +von / by +Dushyant Mehta +ngefertigt unter der Leitung von / supervised by +Dr. Roland Angst +etreut von / advised by +Dr. Roland Angst +egutachtet von / reviewers +Dr. Roland Angst +Prof. Dr. Joachim Weickert +Saarbr¨ucken, February 28, 2016"
+17dea513763c57dcd0e62085045fb5be6770c600,"Dynamic thread mapping for high-performance, power-efficient heterogeneous many-core systems","Summary: Dynamic Thread Mapping for High-Performance, Power-Efficient +Heterogeneous Many-core Systems +Guangshuo Liu, Jinpyo Park, Diana Marculescu +I. OVERVIEW +throughput +for maximizing +This paper investigates about the problem of dynamic thread +mapping in heterogeneous many-core systems via an efficient +lgorithm that maximizes performance under power constraints. +The approach is to formulate the mapping problem as a 0-1 +integer linear program (ILP), given any numbers of threads, +ores and type of cores. An iterative O(n2/m) heuristic-based +lgorithm for solving the 0-1 ILP thread mapping is proposed, +thereby providing, a novel scalable approach for effective thread +mapping +on many-core +heterogeneous systems. +The paper considers multi-threaded workloads and assumes that +each core runs at most one thread at a time thereby supporting +single threaded execution, without simultaneous multithreading"
+1748867e04ba16673ec5231f6a2ca0ae03835658,Fast Exact Search in Hamming Space With Multi-Index Hashing,"Fast Exact Search in Hamming Space +with Multi-Index Hashing +Mohammad Norouzi, Ali Punjani, David J. Fleet, +{norouzi, alipunjani,"
17cf838720f7892dbe567129dcf3f7a982e0b56e,Global-Local Face Upsampling Network,"Global-Local Face Upsampling Network Oncel Tuzel Yuichi Taguchi John R. Hershey Mitsubishi Electric Research Labs (MERL), Cambridge, MA, USA"
+17257fc03b611315ae49bd53d229188b889002e6,Hard Negative Mining for Metric Learning Based Zero-Shot Classification,"Hard Negative Mining for +Metric Learning Based Zero-Shot Classification +Maxime Bucher1,2, St´ephane Herbin1, Fr´ed´eric Jurie2 +ONERA - The French Aerospace Lab, Palaiseau, France +Normandie Univ, UNICAEN, ENSICAEN, CNRS, Caen, France"
178a82e3a0541fa75c6a11350be5bded133a59fd,BioHDD: a dataset for studying biometric identification on heavily degraded data,"Techset Composition Ltd, Salisbury {IEE}BMT/Articles/Pagination/BMT20140045.3d www.ietdl.org @@ -7525,12 +25638,117 @@ Department of Computer Science, IT – Instituto de Telecomunicações, Universi Department of Physics, Remote Sensing Unit – Optics, Optometry and Vision Sciences Group, University of Beira Interior, Covilhã, Portugal E-mail:"
+171d7762137725839fe5292901fe90d91b74811d,SLAM Algorithm by using Global Appearance of Omnidirectional Images,
+174cd8e98f17b3f5bda1c8e16cb39e3dec800f74,Multi-scale Context Intertwining for Semantic Segmentation,"Multi-Scale Context Intertwining +for Semantic Segmentation +Di Lin1, Yuanfeng Ji1, Dani Lischinski2, Daniel Cohen-Or1,3, and Hui Huang1(cid:63) +Shenzhen University 2The Hebrew University of Jerusalem 3Tel Aviv University"
+17c0094c68d6efd19b80287c51d228fa50750f46,An efficient partial face detection method using AlexNet CNN,"SSRG International Journal of Electronics and Communication Engineering - (ICRTECITA-2017) - Special Issue - March 2017 +An efficient partial face detection method using +AlexNet CNN +Prof Mr.Sivalingam.T, S.Kabilan , +Dhanabal.M ,Arun.R ,Chandrabhagavan.K +V.S.B Engineering College,Karur"
+177c48590469c62d430cf74fee7b5bd28bfbbc1d,Articulated Motion Learning via Visual and Lingual Signals,"Learning Articulated Motion Models from Visual and Lingual Signals +Zhengyang Wu +Georgia Tech +Atlanta, GA 30332 +Mohit Bansal +TTI-Chicago +Chicago, IL 60637 +Matthew R. Walter +TTI-Chicago +Chicago, IL 60637"
+1740a0732e8e308f5dd395313313cc3289666f13,Preference-Aware View Recommendation System for Cameras Based on Bag of Aesthetics-Preserving Features,"Transactions on Multimedia +Page 22 of 32 +Preference-Aware View Recommendation System +for Cameras Based on Bag of +Aesthetics-Preserving Features +Hsiao-Hang Su, Tse-Wei Chen, Member, IEEE, Chieh-Chi Kao, Winston H. Hsu, Member, IEEE, +nd Shao-Yi Chien*, Member, IEEE"
+17ff59bb388b155f613f7566ba7cd71ec780cdec,Asymmetric Sparse Kernel Approximations for Large-Scale Visual Search,"Asymmetric sparse kernel approximations +for large-scale visual search +Damek Davis +University of California +Los Angeles, CA 90095 +Jonathan Balzer +University of California +Los Angeles, CA 90095 +Stefano Soatto +University of California +Los Angeles, CA 90095"
+17dd242e6d7afb5d7fafcf9f8e8b201573ce4b89,An Extensive Review on Spectral Imaging in Biometric Systems: Challenges and Advancements,"An Extensive Review on Spectral Imaging in Biometric Systems: Challenges & +Advancements +Rumaisah Munira,∗, Rizwan Ahmed Khana,b,∗∗ +Faculty of IT, Barrett Hodgson University, Karachi, Pakistan. +LIRIS, Universite Claude Bernard Lyon1, France."
+17635e22a73da3ff60a72715b7dd8837de6fee89,The ABBA study – approach bias modification in bulimia nervosa and binge eating disorder: study protocol for a randomised controlled trial,"Brockmeyer et al. Trials (2016) 17:466 +DOI 10.1186/s13063-016-1596-6 +ST UD Y P R O T O C O L +Open Access +The ABBA study – approach bias +modification in bulimia nervosa and binge +eating disorder: study protocol for a +randomised controlled trial +Timo Brockmeyer1,2*, Ulrike Schmidt2 and Hans-Christoph Friederich1,3"
+17daa9ddaf524de914e7440157fc0314db171884,Data driven analysis of faces from images,"Data Driven Analysis +of Faces from Images +Dissertation zur Erlangung des Grades „Doktor der Ingenieurwissenschaften (Dr.-Ing.)” +der Naturwissenschaftlich-Technischen Fakultäten der Universität des Saarlandes +Kristina Scherbaum +8.05.2013 +Universität des Saarlandes | Max-Planck-Institut für Informatik +Saarbrücken – Germany"
17a995680482183f3463d2e01dd4c113ebb31608,Structured Label Inference for Visual Understanding,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. Y, MONTH Z Structured Label Inference for Visual Understanding Nelson Nauata, Hexiang Hu, Guang-Tong Zhou, Zhiwei Deng, Zicheng Liao and Greg Mori"
+17a9db524ddbeb5577a94924c2a7cca048dd19f9,Object Recognition with Multi-Scale Pyramidal Pooling Networks,"Object Recognition with Multi-Scale Pyramidal +Pooling Networks +Jonathan Masci1, Ueli Meier1, Gabriel Fricout2, and J¨urgen Schmidhuber1 +IDSIA – USI – SUPSI, Manno – Lugano, Switzerland, +http://idsia.ch/~masci/ +ArcelorMittal, Maizi`eres Research, Measurement and Control Dept., France"
+17db741725b9f8406f69b27a117e99bee1a9a323,Person Re-identification with a Body Orientation-Specific Convolutional Neural Network,"Person Re-identification with a Body +Orientation-Specific Convolutional Neural Network +Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla +Baskurt +To cite this version: +Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla Baskurt. Person Re- +identification with a Body Orientation-Specific Convolutional Neural Network. Advanced Concepts +for Intelligent Vision systems, Sep 2018, Poitiers, France. <hal-01895374> +HAL Id: hal-01895374 +https://hal.archives-ouvertes.fr/hal-01895374 +Submitted on 15 Oct 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non,"
1742ffea0e1051b37f22773613f10f69d2e4ed2c,Interactive Mirror for Smart Home,
+174b6d661b96840e27cd9435c2dbb8e538b2c8a6,Progressive Representation Adaptation for Weakly Supervised Object Localization,"Progressive Representation Adaptation for +Weakly Supervised Object Localization +Dong Li, Jia-Bin Huang, Yali Li, Shengjin Wang(cid:63) and Ming-Hsuan Yang"
+17d84ca10607442a405f3c4c8b4572bdd79801c2,Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities,"EXPRESSION ROBUST 3D FACE RECOGNITION VIA MESH-BASED HISTOGRAMS OF +MULTIPLE ORDER SURFACE DIFFERENTIAL QUANTITIES +Huibin Li1,2, Di Huang1,2, Pierre Lemaire1,2, Jean-Marie Morvan1,3,4, Liming Chen1,2 +Universit´e de Lyon, CNRS +Ecole Centrale de Lyon, LIRIS UMR5205, F-69134, Lyon, France +Universit´e Lyon 1, Institut Camille Jordan, +3 blvd du 11 Novembre 1918, F-69622 Villeurbanne - Cedex, France +King Abdullah University of Science and Technology, GMSV Research Center, +Bldg 1, Thuwal 23955-6900, Saudi Arabia"
+17ad76ef00d4cb584389682ca6b138a8bdc9a2da,Continuous Multimodal Emotion Recognition Approach for AVEC 2017,"Continuous Multimodal Emotion Recognition +Approach for AVEC 2017 +Narotam Singh*, Nittin Singh†, Abhinav Dhall‡ +Department of Computer Science and Engineering, Indian Institute of Technology Ropar +Email: +India"
174930cac7174257515a189cd3ecfdd80ee7dd54,Multi-view Face Detection Using Deep Convolutional Neural Networks,"Multi-view Face Detection Using Deep Convolutional Neural Networks Sachin Sudhakar Farfade @@ -7544,6 +25762,26 @@ Yahoo" Deep Learning Aparna Bharati, Richa Singh, Senior Member, IEEE, Mayank Vatsa, Senior Member, IEEE, Kevin W. Bowyer, Fellow, IEEE"
+17e769ef3d86e74c21f2616c7f7a6f20a4e2fbaa,Bag of Machine Learning Concepts for Visual Concept Recognition in Images,"Bag of Machine Learning Concepts for +Visual Concept Recognition in Images +vorgelegt vom +Diplom-Mathematiker +Alexander Binder +us Berlin +von der Fakult¨at IV – Elektrotechnik und Informatik +der Technischen Universit¨at Berlin +zur Erlangung des akademischen Grades +Doktor der Naturwissenschaften +– Dr. rer. nat. – +genehmigte Dissertation +Promotionsausschuss: +Vorsitzender: +. Gutachter: +. Gutachter: +. Gutachter: +Prof. Dr. Olaf Hellwich +Prof. Dr. Klaus-Robert M¨uller +Prof. Dr. Volker Tresp"
173657da03e3249f4e47457d360ab83b3cefbe63,HKU-Face : A Large Scale Dataset for Deep Face Recognition Final Report,"HKU-Face: A Large Scale Dataset for Deep Face Recognition Final Report @@ -7551,6 +25789,42 @@ Haicheng Wang 035140108 COMP4801 Final Year Project Project Code: 17007"
+177cbeb83c3a0868b9a5c75cd74edf4b972cba80,Exact Primitives for Time Series Data Mining,"UNIVERSITY OF CALIFORNIA +RIVERSIDE +Exact Primitives for Time Series Data Mining +A Dissertation submitted in partial satisfaction +of the requirements for the degree of +Doctor of Philosophy +Computer Science +Abdullah Al Mueen +March 2012 +Dissertation Committee: +Dr. Eamonn Keogh, Chairperson +Dr. Vassilis Tsotras +Dr. Stefano Lonardi"
+7b0e81249159686337ca2cfe81662123906b6b26,An Automatic Eye Detection Method for Gray Intensity Facial Images,"IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 4, No 2, July 2011 +ISSN (Online): 1694-0814 +www.IJCSI.org +An Automatic Eye Detection Method for Gray Intensity Facial +Images +M. Hassaballah1,2 , Kenji Murakami1, Shun Ido1 +Department of Computer Science, Ehime University, 790-8577, Japan +Department of Mathematics, Faculty of Science, South Valley University, Qena, 83523, Egypt"
+7be6fe8c58ca12974c563689b7230b933dfca432,Design of Radial Basis Function Network as Classifier in Face Recognition Using Eigenfaces,"SBRN’98 – Simpósio Brasileiro de Redes Neurais, Belo Horizonte, Minas Gerais, dezembro de 1998. +Design of Radial Basis Function Network as Classifier in Face Recognition Using +Eigenfaces +Carlos Eduardo Thomaz +Raul Queiroz Feitosa +Álvaro Veiga +PUC RJ- Pontifícia Universidade Católica do Rio de Janeiro +Departamento de Engenharia Elétrica +Rua Marquês de São Vicente, 225, 22453-900 Rio de Janeiro, RJ, Brasil"
+7bd6d0bca27ff68621acd10d6d1709f084f97602,Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World,"Learning to Detect and Track Visible and +Occluded Body Joints in a Virtual World +Matteo Fabbri(cid:63), Fabio Lanzi(cid:63), Simone Calderara(cid:63), Andrea Palazzi, Roberto +Vezzani, and Rita Cucchiara +Department of Engineering “Enzo Ferrari” +University of Modena and Reggio Emilia, Italy"
7bbaa09c9e318da4370a83b126bcdb214e7f8428,"FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC","FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC Josef Spillner1, Cristian Mateos2, and David A. Monge3 @@ -7560,10 +25834,39 @@ ISISTAN Research Institute - CONICET - UNICEN Campus Universitario, Paraje Arroyo Seco, Tandil (7000), Buenos Aires, Argentina ITIC Research Institute, National University of Cuyo Padre Jorge Contreras 1300, M5502JMA Mendoza, Argentina"
+7b8aa3ebeae17e5266dac23e87f603a5d5f7b1e3,Open Set Logo Detection and Retrieval,"Open Set Logo Detection and Retrieval +Andras T¨uzk¨o1, Christian Herrmann1,2, Daniel Manger1, J¨urgen Beyerer1,2 +Fraunhofer IOSB, Karlsruhe, Germany +Karlsruhe Institute of Technology KIT, Vision and Fusion Lab, Karlsruhe, Germany +Keywords: +Logo Detection, Logo Retrieval, Logo Dataset, Trademark Retrieval, Open Set Retrieval, Deep Learning."
+7b1af8cc9c2c43fa9d528bcfb05142d714df3700,"Modeling Shape, Appearance and Motion for Human Movement Analysis",
+7b6f0c4b22aee0cb4987cba9df121d4076fac5a5,On Learning 3D Face Morphable Model from In-the-wild Images,"On Learning 3D Face Morphable Model +from In-the-wild Images +Luan Tran, and Xiaoming Liu, Member, IEEE"
+7b9a5d9d7386d47c51cb473f6338988bd6e9f2b1,An Individual-Specific Strategy for Management of Reference Data in Adaptive Ensembles for Person Re-Identification,"An Individual-Specific Strategy for Management of Reference Data +in Adaptive Ensembles for Person Re-Identification +Miguel De-la-Torre*†, Eric Granger*, Robert Sabourin*, Dmitry O. Gorodnichy‡ +* ´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montr´eal, Canada, +Centro Universitario de Los Valles, Universidad de Guadalajara, Ameca, M´exico +Science and Engineering Directorate, Canada Border Services Agency, Ottawa, Canada, +Keywords: Multi-Classifier Systems; Adaptive Biometrics; Face +Recognition; Video Surveillance; Person Re-Identification"
+7ba6ac1b769ad7098037c07a5b7399fe9d97fcc8,Moving Object Detection in Heterogeneous Conditions in Embedded Systems,"Article +Moving Object Detection in Heterogeneous +Conditions in Embedded Systems +Alessandro Garbo and Stefano Quer * +Dipartimento di Automatica ed Informatica, Politecnico di Torino, 10129 Torino, Italy; +* Correspondence: Tel.: +39-011-090-7076 +Received: 25 May 2017; Accepted: 27 June 2017; Published: 1 July 2017"
7b9961094d3e664fc76b12211f06e12c47a7e77d,Bridging biometrics and forensics,"Bridging Biometrics and Forensics Yanjun Yan and Lisa Ann Osadciw EECS, Syracuse University, Syracuse, NY, USA {yayan,"
+7b67c38a6f49e02c03e1cea98146a506f607b0d7,Using Facial Symmetry to Handle Pose Variations in Real-World 3D Face Recognition,"Using Facial Symmetry to Handle Pose +Variations in Real-World 3D Face Recognition +Georgios Passalis1,2, Panagiotis Perakis1,2, Theoharis Theoharis1,2 +nd Ioannis A. Kakadiaris2, Senior Member, IEEE"
7b9b3794f79f87ca8a048d86954e0a72a5f97758,Passing an Enhanced Turing Test - Interacting with Lifelike Computer Representations of Specific Individuals,"DOI 10.1515/jisys-2013-0016 Journal of Intelligent Systems 2013; 22(4): 365–415 Avelino J. Gonzalez*, Jason Leigh, Ronald F. DeMara, Andrew Johnson, Steven Jones, Sangyoon Lee, Victor Hung, Luc @@ -7578,6 +25881,11 @@ Albert Cruz, Bir Bhanu, Songfan Yang, VISLab, EBUII-216, University of California Riverside, Riverside, California, USA, 92521-0425 {acruz, bhanu,"
+7b8e9c50f74ce6ca66a8ab61fb18ca31d26cf13f,Nonlinear Channels Aggregation Networks for Deep Action Recognition,"Under review as a conference paper at ICLR 2019 +Nonlinear Channels Aggregation Networks +for Deep Action Recognition +Anonymous authors +Paper under double-blind review"
7b0f1fc93fb24630eb598330e13f7b839fb46cce,Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings,"Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings Seonwook Park @@ -7590,6 +25898,49 @@ Otmar Hilliges ETH Zurich"
7bdcd85efd1e3ce14b7934ff642b76f017419751,Learning Discriminant Face Descriptor,"Learning Discriminant Face Descriptor Zhen Lei, Member, IEEE, Matti Pietika¨ inen, Fellow, IEEE, and Stan Z. Li, Fellow, IEEE"
+7b47ca13af16bdc1f4b88e9b68dd3ea52d959199,Online nonparametric discriminant analysis for incremental subspace learning and recognition,"Pattern Anal Applic (2008) 11:259–268 +DOI 10.1007/s10044-008-0131-0 +T H E O R E T I C A L A D V A N C E S +Online nonparametric discriminant analysis for incremental +subspace learning and recognition +B. Raducanu Æ J. Vitria` +Received: 15 December 2006 / Accepted: 20 January 2008 / Published online: 24 July 2008 +Ó Springer-Verlag London Limited 2008"
+7bcd98ee2df3d14eae7bbed713208cb7da7b5db0,Unsupervised data association for metric learning in the context of multi-shot person re-identification,"Unsupervised data association for Metric Learning in the context of Multi-shot +Person Re-identification +Furqan M. Khan, Francois Bremond +INRIA Sophia Antipolis-Mediterrannee +004 Route des Lucioles, Sophia Antipolis Cedex, France +{furqan.khan |"
+7b66dababebd800e95d23a1fde299d44a52e98ed,Dual Recurrent Attention Units for Visual Question Answering,"Under review for Computer Vision and Image Understanding +DRAU: Dual Recurrent Attention Units for Visual Question Answering +Ahmed Osmana,, Wojciech Sameka, +Fraunhofer Heinrich Hertz Institute, Einsteinufer 37, Berlin 10587, Germany"
+7b331c80a91acf3616afd88e78801ac55c874f43,Multiple Player Tracking in Sports Video: A Dual-Mode Two-Way Bayesian Inference Approach With Progressive Observation Modeling,"Multiple Player Tracking in Sports Video: A +Dual-Mode Two-Way Bayesian Inference Approach +With Progressive Observation Modeling +Junliang Xing, Student Member, IEEE, Haizhou Ai, Senior Member, IEEE, Liwei Liu, and +Shihong Lao, Member, IEEE"
+7b9ebcc8b9c05ef661182fe73438b7725584817d,Restoring effects of oxytocin on the attentional preference for faces in autism,"Citation: Transl Psychiatry (2017) 7, e1097; doi:10.1038/tp.2017.67 +www.nature.com/tp +ORIGINAL ARTICLE +Restoring effects of oxytocin on the attentional preference +for faces in autism +M Kanat1,2, I Spenthof1,3, A Riedel4, LT van Elst2,4, M Heinrichs1,2 and G Domes1,2,3 +Reduced attentional preference for faces and symptoms of social anxiety are common in autism spectrum disorders (ASDs). The +neuropeptide oxytocin triggers anxiolytic functions and enhances eye gaze, facial emotion recognition and neural correlates of face +processing in ASD. Here we investigated whether a single dose of oxytocin increases attention to faces in ASD. As a secondary +question, we explored the influence of social anxiety on these effects. We tested for oxytocin’s effects on attention to neutral faces +s compared to houses in a sample of 29 autistic individuals and 30 control participants using a dot-probe paradigm with two +different presentation times (100 or 500 ms). A single dose of 24 IU oxytocin was administered in a randomized, double-blind +placebo-controlled, cross-over design. Under placebo, ASD individuals paid less attention to faces presented for 500 ms than did +ontrols. Oxytocin administration increased the allocation of attention toward faces in ASD to a level observed in controls. +Secondary analyses revealed that these oxytocin effects primarily occurred in ASD individuals with high levels of social anxiety who +were characterized by attentional avoidance of faces under placebo. Our results confirm a positive influence of intranasal oxytocin +on social attention processes in ASD. Further, they suggest that oxytocin may in particular restore the attentional preference for +facial information in ASD individuals with high social anxiety. We conclude that oxytocin’s anxiolytic properties may partially +ccount for its positive effects on socio-cognitive functioning in ASD, such as enhanced eye gaze and facial emotion recognition. +Translational Psychiatry (2017) 7, e1097; doi:10.1038/tp.2017.67; published online 18 April 2017"
7b3b7769c3ccbdf7c7e2c73db13a4d32bf93d21f,"On the design and evaluation of robust head pose for visual user interfaces: algorithms, databases, and comparisons","On the Design and Evaluation of Robust Head Pose for Visual User Interfaces: Algorithms, Databases, and Comparisons @@ -7610,6 +25961,48 @@ Laboratory of Intelligent and Safe Automobiles UCSD - La Jolla, CA, USA Mohan Trivedi"
+7b358ed87f39a12d737070dc22b4c547ce378648,Color Features for Boosted Pedestrian Detection,"Institutionen för systemteknik +Department of Electrical Engineering +Examensarbete +Color Features for Boosted Pedestrian Detection +Examensarbete utfört i Datorseende +vid Tekniska högskolan vid Linköpings universitet +Niklas Hansson +LiTH-ISY-EX--15/4899--SE +Linköping 2015 +Department of Electrical Engineering +Linköpings universitet +SE-581 83 Linköping, Sweden +Linköpings tekniska högskola +Linköpings universitet +581 83 Linköping"
+7b2e0c87aece7ff1404ef2034d4c5674770301b2,Discriminative Feature Learning with Foreground Attention for Person Re-Identification,"Discriminative Feature Learning with Foreground +Attention for Person Re-Identification +Sanping Zhou, Jinjun Wang, Deyu Meng, Yudong Liang, Yihong Gong, Nanning Zheng"
+7b522c5d6d2d0699c4183a543b8e65b1a66d9e74,Understanding Critical Factors in Appearance-Based Gender Categorization,"Understanding Critical Factors in +Appearance-based Gender Categorization +Enrico Grosso, Andrea Lagorio, Luca Pulina, and Massimo Tistarelli +POLCOMING – University of Sassari +Viale Mancini, 5 – 07100 Sassari, Italy"
+7b07a87ff71b85f3493d1944034a960917b8482f,Alternating BackPropagation for Generator Network,"Alternating Back-Propagation for Generator Network +Tian Han†, Yang Lu†, Song-Chun Zhu, and Ying Nian Wu +Department of Statistics, University of California, Los Angeles, USA"
+7b95bd44db15f7cf20bfc051c353841f3fcea383,Low-Complexity Face Recognition using a Multilevel DWT and Two States of Continuous HMM to recognize Noisy Images,"Low-Complexity Face Recognition using a +Multilevel DWT and Two States of +Continuous HMM to recognize Noisy +Images +Hameed R. Farhan1, Mahmuod H. Al-Muifraje2, Thamir R. Saeed2 +Department of Electrical and Electronic Engineering, University of Kerbala, Kerbala, Iraq +Department of Electrical Engineering, University of Technology, Baghdad, Iraq"
+7b83867b7f79cbfbfc71996bcf07fe7ee7a7600c,Object detection through search with a foveated visual system,"Object Detection Through Exploration With A +Foveated Visual Field +Emre Akbas, Miguel P. Eckstein"
+8f9fa03690428cde478f1a27d4773f78d857b88f,Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity,"Visual Recognition using Embedded Feature +Selection for Curvature Self-Similarity +Angela Eigenstetter +HCI & IWR, University of Heidelberg +Bj¨orn Ommer +HCI & IWR, University of Heidelberg"
8f6d05b8f9860c33c7b1a5d704694ed628db66c7,Non-linear dimensionality reduction and sparse representation models for facial analysis. (Réduction de la dimension non-linéaire et modèles de la représentations parcimonieuse pour l'analyse du visage),"Non-linear dimensionality reduction and sparse representation models for facial analysis Yuyao Zhang @@ -7630,23 +26023,103 @@ destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires"
+8f05c4c1b3c1ad31ec95ccb87bca24a884b5ad4c,Overhead Detection: Beyond 8-bits and RGB,"Overhead Detection: Beyond 8-bits and RGB +Eliza Mace1 +Keith Manville1 +Monica Barbu-McInnis1 +Michael Laielli2 +Matthew Klaric2 +Samuel Dooley2 +MITRE, +NGA,"
8f772d9ce324b2ef5857d6e0b2a420bc93961196,Facial Landmark Point Localization using Coarse-to-Fine Deep Recurrent Neural Network,"MAHPOD et al.: CFDRNN Facial Landmark Point Localization using Coarse-to-Fine Deep Recurrent Neural Network Shahar Mahpod, Rig Das, Emanuele Maiorana, Yosi Keller, and Patrizio Campisi,"
+8fdfd4c5039cf7d70470a2a3ac52bfd229bcd4e2,Pushing the Limits of Radiology with Joint Modeling of Visual and Textual Information,"Pushing the Limits of Radiology with Joint Modeling of Visual and +Textual Information +Department of Computing, Macquarie University1 +Sonit Singh1,2 +DATA61, CSIRO2 +Sydney, Australia"
8fda2f6b85c7e34d3e23927e501a4b4f7fc15b2a,Feature Selection with Annealing for Big Data Learning,"Feature Selection with Annealing for Big Data Learning Adrian Barbu, Yiyuan She, Liangjing Ding, Gary Gramajo"
+8fbe68810cbc53521395829620060cf9558231cc,Learning Discriminant Person-Specific Facial Models Using Expandable Graphs,"Learning Discriminant Person-Specific +Facial Models Using Expandable Graphs +Stefanos Zafeiriou, Anastasios Tefas, Member, IEEE, and Ioannis Pitas, Fellow, IEEE"
8fa3478aaf8e1f94e849d7ffbd12146946badaba,Attributes for Classifier Feedback,"Attributes for Classifier Feedback Amar Parkash1 and Devi Parikh2 Indraprastha Institute of Information Technology (Delhi, India) Toyota Technological Institute (Chicago, US)"
+8ff3c7b46ab36f1d01e96681baf512859cc80a4d,Dynamics of alpha oscillations elucidate facial affect recognition in schizophrenia.,"Dynamics of alpha oscillations elucidate facial affect +recognition in schizophrenia +Tzvetan G. Popov & Brigitte S. Rockstroh & Petia Popova & +Almut M. Carolus & Gregory A. Miller"
8f9c37f351a91ed416baa8b6cdb4022b231b9085,Generative Adversarial Style Transfer Networks for Face Aging,"Generative Adversarial Style Transfer Networks for Face Aging Sveinn Palsson D-ITET, ETH Zurich Eirikur Agustsson D-ITET, ETH Zurich"
8f8c0243816f16a21dea1c20b5c81bc223088594,Local Directional Number Based Classification and Recognition of Expressions Using Subspace Methods,
+8f98e1e041e7d3e27397c268e85e815065329d2d,Hierarchical feed forward models for robust object recognition,"Hierarchical Feed-Forward Models for +Robust Object Recognition +Ingo Bax +Der Technischen Fakult¨at der Universit¨at Bielefeld vorgelegt zur Erlangung +des akademischen Grades Doktor der Ingenieurwissenschaften"
+8fc21217ee89c505930b540b716b11bab89d3bcd,Memory Efficient Nonuniform Quantization for Deep Convolutional Neural Network,"Memory Efficient Nonuniform Quantization for +Deep Convolutional Neural Network +Fangxuan Sun and Jun Lin"
+8f5566fa00f8c79f4720e14084489e784688ab0b,The role of the amygdala in atypical gaze on emotional faces in autism spectrum disorders.,"The Journal of Neuroscience, July 11, 2012 • 32(28):9469 –9476 • 9469 +Behavioral/Systems/Cognitive +The Role of the Amygdala in Atypical Gaze on Emotional +Faces in Autism Spectrum Disorders +Dorit Kliemann,1,2,3,4 Isabel Dziobek,2,3 Alexander Hatri,1,2,3 Ju¨rgen Baudewig,2,3 and Hauke R. Heekeren1,2,3,4 +Department of Education and Psychology, 2Cluster of Excellence “Languages of Emotion,” and 3Dahlem Institute for Neuroimaging of Emotion (D.I.N.E), +Freie Universita¨t Berlin, 14195 Berlin, Germany, and 4Max Planck Institute for Human Development, 14195 Berlin, Germany +Reduced focus toward the eyes is a characteristic of atypical gaze on emotional faces in autism spectrum disorders (ASD). Along with the +typical gaze, aberrant amygdala activity during face processing compared with neurotypically developed (NT) participants has been +repeatedly reported in ASD. It remains unclear whether the previously reported dysfunctional amygdalar response patterns in ASD +support an active avoidance of direct eye contact or rather a lack of social attention. Using a recently introduced emotion classification +task, we investigated eye movements and changes in blood oxygen level-dependent (BOLD) signal in the amygdala with a 3T MRI scanner +in 16 autistic and 17 control adult human participants. By modulating the initial fixation position on faces, we investigated changes +triggered by the eyes compared with the mouth. Between-group interaction effects revealed different patterns of gaze and amygdalar +BOLD changes in ASD and NT: Individuals with ASD gazed more often away from than toward the eyes, compared with the NT group, +which showed the reversed tendency. An interaction contrast of group and initial fixation position further yielded a significant cluster of +mygdala activity. Extracted parameter estimates showed greater response to eyes fixation in ASD, whereas the NT group showed an +increase for mouth fixation. +The differing patterns of amygdala activity in combination with differing patterns of gaze behavior between groups triggered by direct +eye contact and mouth fixation, suggest a dysfunctional profile of the amygdala in ASD involving an interplay of both eye-avoidance"
+8fb849fe51fbf4b56393cfef26397caef2a22fb0,Public Document Agreed Plans for Open Source Reference Software Document Evolution Executive Summary,"Project N° IST-2002-507634 - BioSecure +D2.2.1 – Revision: b3 +2 March 2005 +Contract Number : +Project Acronym : +Project Title : +Instrument : +Start Date of Project : +Duration : +Deliverable Number : +Title of Deliverable : +Contractual Due Date : +Actual Date of Completion : +IST-2002-507634 +BioSecure +Biometrics for Secure Authentication +Network of Excellence +01 June, 2004 +6 months +D2.2.1"
+8f2e83f6d70b9e161ad714fee79ed6d23ae2a93f,Image Intelligent Detection Based on the Gabor Wavelet and the Neural Network,"Article +Image Intelligent Detection Based on the Gabor +Wavelet and the Neural Network +Yajun Xu 1, Fengmei Liang 1,*, Gang Zhang 1 and Huifang Xu 2 +College of Information Engineering, Taiyuan University of Technology, Taiyuan 030024, China; +(Y.X.); (G.Z.) +Daqin Railway Co. Ltd., Taiyuan Railway Administration, Taiyuan 030013, China; +* Correspondence: Tel.: +86-186-0341-0966 +Academic Editor: Angel Garrido +Received: 21 September 2016; Accepted: 11 November 2016; Published: 15 November 2016"
8f3e3f0f97844d3bfd9e9ec566ac7a54f6931b09,"A Survey on Human Emotion Recognition Approaches, Databases and Applications","Electronic Letters on Computer Vision and Image Analysis 14(2):24-44; 2015 A Survey on Human Emotion Recognition Approaches, Databases and Applications @@ -7654,11 +26127,134 @@ C.Vinola*, K.Vimaladevi† * Department of Computer Science and Engineering, Francis Xavier Engineering College, Tirunelveli,Tamilnadu,India Department of Computer Science and Engineering, P.S.R Engineering College, Sivakasi, Tamilnadu,India Received 7th Aug 2015; accepted 30th Nov 2015"
+8fc730d22f33d08be927e5449f359dc15b5c3503,Measuring and modeling the perception of natural and unconstrained gaze in humans and machines,"CBMM Memo No. 059 +November 28, 2016 +Measuring and modeling the perception of natural +nd unconstrained gaze in humans and machines +Daniel Harari*, Tao Gao*, Nancy Kanwisher, Joshua Tenenbaum, Shimon +Ullman"
8f89aed13cb3555b56fccd715753f9ea72f27f05,Attended End-to-end Architecture for Age Estimation from Facial Expression Videos,"Attended End-to-end Architecture for Age Estimation from Facial Expression Videos Wenjie Pei, Hamdi Dibeklio˘glu, Member, IEEE, Tadas Baltruˇsaitis and David M.J. Tax"
+8fcdeda0c2f4e265e2180eb5ed39f6548ae3ba99,A Generic Middle Layer for Image Understanding,"UNIVERSIT ¨AT HAMBURG +A Generic Middle Layer for Image +Understanding +Kasim Terzi´c +Doktorarbeit +Fakult¨at f¨ur Mathematik, Informatik und Naturwissenschaften +Fachbereich Informatik"
+8fe7354a92b4c74c22dc0a253dfe7320487d22ab,Literature Survey on Sparse Representation for Neural Network Based Face Detection and Recognition,"Circuits and Systems: An International Journal (CSIJ), Vol. 1, No.2, April 2014 +LITERATURE SURVEY ON SPARSE +REPRESENTATION FOR NEURAL +NETWORK BASED FACE DETECTION AND +RECOGNITION +Raviraj Mane,Poorva Agrawal, +Nisha Auti CS Department SIT, Pune"
+8fe43144c0ff36ffefca869eec0a63e71ca02049,1D correlation filter based class-dependence feature analysis for face recognition,"This article appeared in a journal published by Elsevier. The attached +opy is furnished to the author for internal non-commercial research +nd education use, including for instruction at the authors institution +nd sharing with colleagues. +Other uses, including reproduction and distribution, or selling or +licensing copies, or posting to personal, institutional or third party +websites are prohibited. +In most cases authors are permitted to post their version of the +rticle (e.g. in Word or Tex form) to their personal website or +institutional repository. Authors requiring further information +regarding Elsevier’s archiving and manuscript policies are +encouraged to visit: +http://www.elsevier.com/copyright"
+8f4c8a80e94a883356ee4c4425324dac5457661a,Noise Robust Face Image Super-Resolution Through Smooth Sparse Representation,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +Noise Robust Face Image Super-Resolution +Through Smooth Sparse Representation +Junjun Jiang, Member, IEEE, Jiayi Ma, Member, IEEE, Chen Chen, Xinwei Jiang, and Zheng Wang"
8fd9c22b00bd8c0bcdbd182e17694046f245335f,Recognizing Facial Expressions in Videos,"Recognizing Facial Expressions in Videos Lin Su, Matthew Balazsi"
+8f2e594f55ca1b1675d8bfef25922c97109cb599,An evil face? Verbal evaluative multi-CS conditioning enhances face-evoked mid-latency magnetoencephalographic responses,"Social Cognitive and Affective Neuroscience, 2017, 695–705 +doi: 10.1093/scan/nsw179 +Advance Access Publication Date: 22 December 2016 +Original article +An evil face? Verbal evaluative multi-CS conditioning +enhances face-evoked mid-latency magnetoencephalo- +graphic responses +Markus Jungho¨ fer,1,2 Maimu Alissa Rehbein,1,2 Julius Maitzen,1 +Sebastian Schindler,3,4 and Johanna Kissler3,4 +Institute for Biomagnetism and Biosignalanalysis, University Hospital Mu¨ nster, Mu¨ nster D-48149, Germany, +Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Mu¨ nster, Mu¨ nster D-48151, +Germany, 3Department of Psychology, Affective Neuropsychology Unit and 4Center of Excellence Cognitive +Interaction Technology (CITEC), University of Bielefeld, Bielefeld D-33501, Germany +Correspondence should be addressed to Johanna Kissler, Department of Psychology, Affective Neuropsychology Unit, University of Bielefeld, Bielefeld +D-33501, Germany. E-mail:"
+8f0c11a3332c434af11c01ee11ff7c492c7968da,Domain Adaptive Faster R-CNN for Object Detection in the Wild,"Domain Adaptive Faster R-CNN for Object Detection in the Wild +Yuhua Chen1 Wen Li1 Christos Sakaridis1 Dengxin Dai1 +Luc Van Gool1,2 +Computer Vision Lab, ETH Zurich +VISICS, ESAT/PSI, KU Leuven"
+8a12ee3c98b76d99531d5965f15bb77a10ec2569,Holistic Face Recognition through Multivariate Analysis and Genetic Algorithms,"Holistic Face Recognition through Multivariate Analysis and Genetic +Algorithms"
+8a4119c2898f611a6ffa0b4b72acf322d1b455b1,A Diagram is Worth a Dozen Images,"A Diagram Is Worth A Dozen Images +Aniruddha Kembhavi†, Mike Salvato†(cid:63), Eric Kolve†(cid:63), Minjoon Seo§, +Hannaneh Hajishirzi§, Ali Farhadi†§ +Allen Institute for Artificial Intelligence, §University of Washington"
+8a91cb96dd520ba3e1f883aa6d57d4d716c5d1c8,Low Cost Eye Tracking: The Current Panorama,"Hindawi Publishing Corporation +Computational Intelligence and Neuroscience +Volume 2016, Article ID 8680541, 14 pages +http://dx.doi.org/10.1155/2016/8680541 +Review Article +Low Cost Eye Tracking: The Current Panorama +Onur Ferhat1,2 and Fernando Vilariño1,2 +Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra, Spain +Computer Science Department, Universitat Aut`onoma de Barcelona, Edifici Q, Campus UAB, 08193 Bellaterra, Spain +Correspondence should be addressed to Onur Ferhat; +Received 27 November 2015; Accepted 18 February 2016 +Academic Editor: Ying Wei +Copyright © 2016 O. Ferhat and F. Vilari˜no. This is an open access article distributed under the Creative Commons Attribution +License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly +ited. +Despite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze +tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this +field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous +work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration +strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such"
+8a29378973987bdb040f35349d1c5a86a538c0fc,Hierarchical Temporal Memory Using Memristor Networks: A Survey,"Hierarchical Temporal Memory using Memristor +Networks: A Survey +Olga Krestinskaya, Graduate Student Member, IEEE, Irina Dolzhikova, Graduate Student Member, IEEE, and +Alex Pappachen James, Senior Member, IEEE"
+8a14dfe0e11e03505db9c0d84bce96f165223cae,Learning from Demonstration in the Wild,"Learning from Demonstration in the Wild +Feryal Behbahani1, Kyriacos Shiarlis1, Xi Chen1, Vitaly Kurin1,2, Sudhanshu Kasewa1,2, Ciprian Stirbu1,2, +Jo˜ao Gomes1, Supratik Paul1,2, Frans A. Oliehoek1,3, Jo˜ao Messias1, Shimon Whiteson1,2"
+8a382f000f98cdab7f7b79e543c75c6b8f93b6f9,Learning Semantic Image Representations at a Large Scale,"Learning Semantic Image Representations at a Large +Scale +Yangqing Jia +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2014-93 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-93.html +May 16, 2014"
+8ab183883acba0501c3315a914aee755b5e517d8,Synthesis-based Robust Low Resolution Face Recognition,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. X, NO. X, MONTH 20XX +Synthesis-based Robust Low Resolution Face +Recognition +Sumit Shekhar, Student Member, IEEE, Vishal M. Patel, Member, IEEE, and Rama Chellappa, Fellow, IEEE"
+8ad407142de84b66144029845587c77ae94fd240,Multi-class speed-density relationship for pedestrian traffic,"Multi-class speed-density relationship for +pedestrian traffic +Marija Nikoli´c ∗ +Matthieu de Lapparent ∗ +Michel Bierlaire ∗ +Riccardo Scarinci ∗ +January 15, 2017 +Report TRANSP-OR 170115 +Transport and Mobility Laboratory +School of Architecture, Civil and Environmental Engineering +Ecole Polytechnique Fédérale de Lausanne +transp-or.epfl.ch +Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engi- +neering, École Polytechnique Fédérale de Lausanne, Switzerland, +{marija.nikolic, michel.bierlaire, matthieu.delapparent,"
+8aac66d15e0903257ec3abe6f126bf6316779011,Constructive Autoassociative Neural Network for Facial Recognition,"RESEARCH ARTICLE +Constructive Autoassociative Neural +Network for Facial Recognition +Bruno J. T. Fernandes1*, George D. C. Cavalcanti2, Tsang I. Ren2 +. Escola Polite´ cnica, Universidade de Pernambuco, Recife-PE, Brazil, 2. Centro de Informa´ tica, +Universidade Federal de Pernambuco, Recife-PE, Brazil"
8acdc4be8274e5d189fb67b841c25debf5223840,Improving clustering performance using independent component analysis and unsupervised feature learning,"Gultepe and Makrehchi Hum. Cent. Comput. Inf. Sci. (2018) 8:25 https://doi.org/10.1186/s13673-018-0148-3 @@ -7675,6 +26271,40 @@ University of Ontario Institute of Technology, 2000 Simcoe St N, Oshawa, ON L1H 7K4, Canada"
+8ad4742e656c409e5a813c1a6d5f21fd2e3a9225,A Novel Algorithm for Face Recognition From Very Low Resolution Images,"J Electr Eng Technol Vol. 10, No. ?: 742-?, 2015 +http://dx.doi.org/10.5370/JEET.2015.10.1.742 +ISSN(Print) 1975-0102 +ISSN(Online) 2093-7423 +A Novel Algorithm for Face Recognition From Very Low Resolution +Images +C. Senthilsingh† and M. Manikandan*"
+8ac074829b55bb6b4c67f062ca9ec62bb79f865f,Person re-identification based on deep multi-instance learning,"Person Re-identification based on Deep +Multi-instance Learning +Domonkos Varga∗†, Tam´as Szir´anyi∗‡ +MTA SZTAKI, Institute for Computer Science and Control +{varga.domonkos, +Budapest University of Technology and Economics, Department of Networked Systems and Services +Budapest University of Technology and Economics, Department of Material Handling and Logistics Systems"
+8a7726e58c2e24b0a738b48ae35185aaaacb8fe9,PILOT ASSESSMENT OF NONVERBAL PRAGMATIC ABILITY IN PEOPLE WITH ASPERGER SYNDROME Introduction,"Psychology of Language and Communication 2013, Vol. 17, No. 3 +DOI: 10.2478/plc-2013-0018 +FRANCISCO J. RODRÍGUEZ MUÑOZ +University of Almería +PILOT ASSESSMENT OF NONVERBAL PRAGMATIC ABILITY +IN PEOPLE WITH ASPERGER SYNDROME +The purpose of this study is to present a diagnostic tool to assess the nonverbal pragmatic +ehaviors of people with Asperger syndrome, with the intent to give an account of the +severity of symptoms in the area of nonverbal interaction, as well as providing a profile +of nonverbal behaviors that may be targeted for intervention. Through this communica- +tion profile, overall nonverbal ability is calculated in a group of 20 subjects with Asperger +syndrome. The proposed scale also includes the measurement of the following nonverbal +dimensions: (1) eye gaze, (2) facial expression, (3) body language and posture, (4) proxemics, +(5) gestures, and (6) paralanguage. The results of this assessment suggest low nonverbal +pragmatic ability in these subjects, show specific deficits in nonverbal communication, and +apture variability in nonverbal behavior in individuals with AS. +Key words: Asperger syndrome, autism spectrum disorders, communication profile, non- +verbal communication, pragmatic assessment, speech-language pathology +Introduction +Nobody can deny that nonverbal behavior, understood as a communication"
8a54f8fcaeeede72641d4b3701bab1fe3c2f730a,What do you think of my picture? Investigating factors of influence in profile images context perception,"What do you think of my picture? Investigating factors of influence in profile images context perception Filippo Mazza, Matthieu Perreira da Silva, Patrick Le Callet, Ingrid @@ -7705,9 +26335,59 @@ Shigeru Akamatsu -2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02, Japan INRIA, 2004 route des Lucioles, BP 93, F-06902 Sophia-Antipolis Cedex, France e-mail:"
+8aa6c3601924c99ca420c7c37ffcffe00db1eb78,3D facial expression recognition via multiple kernel learning of Multi-Scale Local Normal Patterns,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-0-9 ©2012 ICPR"
8a866bc0d925dfd8bb10769b8b87d7d0ff01774d,WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art,"WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art Saif M. Mohammad and Svetlana Kiritchenko National Research Council Canada"
+8ab16c26678245ef009cbbf87d750cfd18e21572,A Wearable Ultrasonic Obstacle Sensor for Aiding Visually Impaired and Blind Individuals,"A Wearable Ultrasonic Obstacle Sensor for Aiding Visually Impaired and Blind Individuals +{tag} {/tag} +IJCA Proceedings on National Conference on +Growth of Technologies in Electronics, Telecom and Computers - India Perception +© 2014 by IJCA Journal +GTETC-IP +Year of Publication: 2014 +Authors: +V. Diana Earshia +S. M. Kalaivanan +Angel Dayana +{bibtex}gtetc1314.bib{/bibtex}"
+8af0854c652c90d4004e1868bc5fafec3e4ce724,Labelling the Behaviour of Local Descriptors for Selective Video Content Retrieval,"INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET EN AUTOMATIQUE +Labelling the Behaviour of Local Descriptors for +Selective Video Content Retrieval +Julien Law-To — Valerie Gouet-Brunet — Olivier Buisson — Nozha Boujemaa +N° 5821 +January 2006 +Thème COG +p p o r t (cid:13) +(cid:13) d e r e c h e r c h e (cid:13)"
+8aaa97c686c60f611fe5a979d9afbc29dde3d33f,Mastering the Dungeon: Grounded Language Learning by Mechanical Turker Descent,"Published as a conference paper at ICLR 2018 +MASTERING THE DUNGEON: GROUNDED LANGUAGE +LEARNING BY MECHANICAL TURKER DESCENT +Zhilin Yang, Saizheng Zhang, Jack Urbanek, Will Feng, Alexander H. Miller +Arthur Szlam, Douwe Kiela & Jason Weston +Facebook AI Research"
+8a77025bde5479a1366bb93c6f2366b5a6293720,Sharp Attention Network via Adaptive Sampling for Person Re-identification,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. XX, NO. XX, XX 2018 +Sharp Attention Network via Adaptive Sampling +for Person Re-identification +Chen Shen, Guo-Jun Qi, Member, IEEE, Rongxin Jiang, Zhongming Jin, Hongwei Yong, Yaowu Chen, +nd Xian-Sheng Hua, Fellow, IEEE"
+8a2ed61448d9e41295753f5bd0a662ac28373e6f,Domain-Specific Face Synthesis for Video Face Recognition From a Single Sample Per Person,"Domain-Specific Face Synthesis for Video Face +Recognition From a Single Sample Per Person +Fania Mokhayeri +, Student Member, IEEE, Eric Granger +, Member, IEEE, +nd Guillaume-Alexandre Bilodeau , Member, IEEE"
+8ac2736683dac9a467602ee19f5a290096259148,HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection,"HyperNet: Towards Accurate Region Proposal Generation +nd Joint Object Detection +Tao Kong1 +Anbang Yao2 Yurong Chen2 Fuchun Sun1 +State Key Lab. of Intelligent Technology and Systems +Tsinghua National Laboratory for Information Science and Technology (TNList) +Department of Computer Science and Technology, Tsinghua University 2Intel Labs China +{anbang.yao,"
+8aea75940c90fac8c1e5d7ece7d04a61555c3bf6,Divide and Grow: Capturing Huge Diversity in Crowd Images with Incrementally Growing CNN,
8adb2fcab20dab5232099becbd640e9c4b6a905a,Beyond Euclidean Eigenspaces: Bayesian Matching for Visual Recognition,"Beyond Euclidean Eigenspaces: Bayesian Matching for Visual Recognition Baback Moghaddam @@ -7718,9 +26398,53 @@ MIT Media Laboratory Cambridge, MA Cambridge, MA +8a0538eb80b5d41c0e5991aceeef47db01603033,Proposal Flow: Semantic Correspondences from Object Proposals,"Proposal Flow: Semantic Correspondences from +Object Proposals +Bumsub Ham, Member, IEEE, Minsu Cho, Cordelia Schmid, Fellow, IEEE and Jean Ponce, Fellow, IEEE"
+8aa5f1b2639da73c2579ea9037a4ebf4579fdc4f,A Steerable multitouch Display for Surface Computing and its Evaluation,"December +S0218213013600166 +013 14:51 WSPC/INSTRUCTION +st Reading +International Journal on Artificial Intelligence Tools +Vol. 22, No. 6 (2013) 1360016 (29 pages) +(cid:13) World Scientific Publishing Company +DOI: 10.1142/S0218213013600166 +A STEERABLE MULTITOUCH DISPLAY FOR SURFACE +COMPUTING AND ITS EVALUATION +PANAGIOTIS KOUTLEMANIS, ANTONIOS NTELIDAKIS, XENOPHON ZABULIS, +DIMITRIS GRAMMENOS and ILIA ADAMI +Foundation for Research and Technology – Hellas (FORTH ) +Institute of Computer Science, N. Plastira 100 +Vassilika Vouton, GR-700 13 Heraklion, Crete, Greece +{koutle, ntelidak, zabulis, grammenos, +Received 28 January 2013 +Accepted 19 March 2013 +Published 20 December 2013 +In this paper, a steerable, interactive projection display that has the shape of a disk is"
+8abfda3c1e1599bed454661f15ee0bbe7f6b8c12,Who is Mistaken?,"Who is Mistaken? +Benjamin Eysenbach +Carl Vondrick +Antonio Torralba"
+8ae02cef563120be51f8655e199a54af856059b7,Three-Dimensional Anthropometric Database of Attractive Caucasian Women: Standards and Comparisons,"SCIENTIFIC FOUNDATION +Three-Dimensional Anthropometric Database of +Attractive Caucasian Women: Standards +nd Comparisons +Luigi Maria Galantucci, PhD, MSE, +Alberto Laino, PhD, DS, +Eliana Di Gioia, DS, MD,§jj Raoul D’Alessio, DS, MD,ô Fulvio Lavecchia, PhD, MSE,# +Roberto Deli, PhD, DS, +Gianluca Percoco, PhD, MSE,# and Carmela Savastano, DS, MD"
+8afe84f915d3dbc45c57011e62f5dbf9003dfb4c,Adaptive Binary Quantization for Fast Nearest Neighbor Search,"Adaptive Binary Quantization for Fast Nearest Neighbor +Search +Zhujin Li1 and Xianglong Liu∗2 and Junjie Wu3 and Hao Su4"
8a91ad8c46ca8f4310a442d99b98c80fb8f7625f,2D Segmentation Using a Robust Active Shape Model With the EM Algorithm,"D Segmentation Using a Robust Active Shape Model With the EM Algorithm Carlos Santiago, Jacinto C. Nascimento, Member, IEEE, and Jorge S. Marques"
+8a2bd5dbcf0ab0130dfb97e2a035e5722aa9319e,NLP EAC Recognition by Component Separation in the Eye Region,"NLP EAC Recognition by Component +Separation in the Eye Region +Ruxandra Vrˆanceanu, Corneliu Florea, Laura Florea and Constantin Vertan +The Image Processing and Analysis Laboratory (LAPI), Politehnica University of +Bucharest, Romania"
8aed6ec62cfccb4dba0c19ee000e6334ec585d70,Localizing and Visualizing Relative Attributes,"Localizing and Visualizing Relative Attributes Fanyi Xiao and Yong Jae Lee"
8a336e9a4c42384d4c505c53fb8628a040f2468e,Detecting Visually Observable Disease Symptoms from Faces,"Wang and Luo EURASIP Journal on Bioinformatics @@ -7731,6 +26455,44 @@ Detecting Visually Observable Disease Symptoms from Faces Kuan Wang* and Jiebo Luo Open Access"
+8a56adc9605a894c513537f1a2c8d9459573c0a8,Running head: EFFECT OF IDENTITY ON TRUST LEARNING 1 Incidental learning of trust from eye-gaze: Effects of race and facial trustworthiness,"This is an author produced version of Incidental learning of trust from eye-gaze: Effects of +race and facial trustworthiness. +White Rose Research Online URL for this paper: +http://eprints.whiterose.ac.uk/119885/ +Article: +Strachan, James, Kirkham, Alexander James orcid.org/0000-0001-9286-9448, Manssuer, +Luis et al. (2 more authors) (2017) Incidental learning of trust from eye-gaze: Effects of +race and facial trustworthiness. VISUAL COGNITION. pp. 1-13. ISSN 1350-6285 +https://doi.org/10.1080/13506285.2017.1338321 +promoting access to +White Rose research papers +http://eprints.whiterose.ac.uk/"
+7e8edc45fa80cb0f7bc2c20e8eb893dcadde2c8c,Combining Speeded-up Robust Features with Principal Component Analysis in Face Recognition System,"International Journal of Innovative +Computing, Information and Control +Volume 8, Number 12, December 2012 +ICIC International c(cid:13)2012 ISSN 1349-4198 +pp. 8545{8556 +COMBINING SPEEDED-UP ROBUST FEATURES WITH PRINCIPAL +COMPONENT ANALYSIS IN FACE RECOGNITION SYSTEM +Shinfeng D. Lin(cid:3), Bo-Feng Liu and Jia-Hong Lin +Department of Computer Science and Information Engineering +National Dong Hwa University +No. 1, Sec. 2, Da Hsueh Rd., Shoufeng, Hualien 97401, Taiwan +Corresponding author: +(cid:3) +Received October 2011; revised March 2012"
+7ed9913de03dd2990b68751842306c2636852647,VQABQ: Visual Question Answering by Basic Questions,"VQABQ: Visual Question Answering by Basic Questions +Jia-Hong Huang +King Abdullah University of Science and Technology +{jiahong.huang, modar.alfadly, +Modar Alfadly +Bernard Ghanem"
+7e53ab07d0ce28484830329036a1fc018b9644dd,Online multiple people tracking-by-detection in crowded scenes,"Journal of Advances in Computer Engineering and Technology, 1(2) 2015 +Online multiple people tracking-by-detection in +rowded scenes +Sahar Rahmatian1, Reza Safabakhsh2 +Received (2015-01-23) +Accepted (2015-03-19)"
7e3367b9b97f291835cfd0385f45c75ff84f4dc5,Improved local binary pattern based action unit detection using morphological and bilateral filters,"Improved Local Binary Pattern Based Action Unit Detection Using Morphological and Bilateral Filters Anıl Y¨uce1, Matteo Sorci2 and Jean-Philippe Thiran1 @@ -7759,6 +26521,40 @@ L’archive ouverte pluridisciplinaire HAL, est destin´ee au d´epˆot et `a la diffusion de documents scientifiques de niveau recherche, publi´es ou non, ´emanant des ´etablissements d’enseignement et de"
+7e5414277148c8fdf9903068b001887225b69868,Perceptive Parallel Processes Coordinating Geometry and Texture,"Perceptive Parallel Processes Coordinating Geometry and Texture +Marco A. Gutierrez1, Rafael E. Banchs2 and Luis F. D'Haro2"
+7e7e4af2a79288fd2e391020edff8552ea1ece9a,Trimming Prototypes of Handwritten Digit Images with Subset Infinite Relational Model,"Trimming Prototypes of Handwritten Digit +Images with Subset Infinite Relational Model +Tomonari Masada1 and Atsuhiro Takasu2 +Nagasaki University, 1-14 Bunkyo-machi, Nagasaki-shi, Nagasaki, 852-8521 Japan, +National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430 +Japan,"
+7e79c3a92f60c55a6970f89acfa152bcf74823e0,Face Recognition using FSS-DSOP for Small Sample Size Problem with Illumination Variations,"Int. J. Advance. Soft Comput. Appl., Vol. 1, No. 2, November 2009 +ISSN 2074-8523; Copyright © ICSRS Publication, 2009 +www.i-csrs.org +Face Recognition using FSS-DSOP for Small +Sample Size Problem with Illumination +Variations +Ganesh Bhat, K.K. Achary +Canara Engineering College,Department of Electronics, India"
+7ebc96b4b7886b263808c2cd62b21158ebf6297c,"Crowd Motion Analysis: Segmentation, Anomaly Detection, and Behavior Classification","CROWD MOTION ANALYSIS: +SEGMENTATION, ANOMALY +DETECTION, AND BEHAVIOR +CLASSIFICATION +Habib Ullah +Advisor: Nicola Conci, PhD +February 2015"
+7e7b4b4a84c2aa0ee69b5cea3a4da7f62a0a37d5,GraSp: Combining Spatially-aware Mobile Devices and a Display Wall for Graph Visualization and Interaction,"Eurographics Conference on Visualization (EuroVis) 2017 +J. Heer, T. Ropinski and J. van Wijk +(Guest Editors) +Volume 36 (2017), Number 3 +GRASP: Combining Spatially-aware Mobile Devices +nd a Display Wall for Graph Visualization and Interaction +U. Kister1, K. Klamka1, C. Tominski2 and R. Dachselt1 +Interactive Media Lab Dresden, Technische Universität Dresden, Germany +Institute for Computer Science, University of Rostock, Germany +Figure 1: Mobile devices support graph visualization and interaction on wall-sized displays close to the display wall and further away (A). +The GRASP system provides a mobile toolbox with selections, alternative representations, lenses, and filtering close to the user (B)."
7ee53d931668fbed1021839db4210a06e4f33190,What If We Do Not have Multiple Videos of the Same Action? — Video Action Localization Using Web Images,"What if we do not have multiple videos of the same action? — Video Action Localization Using Web Images Center for Research in Computer Vision (CRCV), University of Central Florida (UCF) @@ -7781,9 +26577,101 @@ Sensors Nina Taherimakhsousi, Hausi A. Müller Department of Computer Science University of Victoria, Victoria, Canada"
+7e3693fffef8d83ac109309a77f2545d32c10fc3,The effect of Ramadan fasting on spatial attention through emotional stimuli,"Psychology Research and Behavior Management +Open access Full Text article +Dovepress +open access to scientific and medical research +O Ri g i n a l R e s e aRc h +The effect of Ramadan fasting on spatial attention +through emotional stimuli +Maziyar Molavi +Jasmy Yunus +nugraha P Utama +Department of clinical sciences, +Faculty of Biosciences and Medical +engineering (FBMe), Universiti +Teknologi Malaysia (UTM), Johor +Bahru, Johor, Malaysia +orrespondence: nugraha P Utama +Department of clinical sciences, Faculty +of Biosciences and Medical engineering, +Universiti Teknologi Malaysia (UTM), +81310 Johor Bahru, Johor, Malaysia"
+7e59d2d3416537dd958ff71b7a0bff87e639dad9,Feature-Based Pose Estimation,"Feature-based Pose Estimation +Cristian Sminchisescu1,2, Liefeng Bo3, Catalin Ionescu4, Atul Kanaujia5"
+7ea7c073d13e80ec5015f41f1d57f0674502cc5e,An Implementation of Face Emotion Identification System using Active Contour Model and PCA,"IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 04, 2015 | ISSN (online): 2321-0613 +An Implementation of Face Emotion Identification System using Active +Contour Model and PCA +Namita Rathore1 Mr.Rohit Miri2 +P.G. Student 2Assistant Professor +,2Department of Computer Science and Engineering +,2DR C V Raman Institute of Science and Technology Kota, bilaspur +systems, +surveillance"
+7e463877264e70d53c844cf4b1bf3b15baec8cfb,ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks,"ReNet: A Recurrent Neural Network Based +Alternative to Convolutional Networks +Francesco Visin(cid:63) +Politecnico di Milano +Kyle Kastner(cid:63) +University of Montreal +Kyunghyun Cho(cid:63) +University of Montreal +Matteo Matteucci +Politecnico di Milano +Aaron Courville +University of Montreal +Yoshua Bengio +University of Montreal +CIFAR Senior Fellow"
7ed6ff077422f156932fde320e6b3bd66f8ffbcb,State of 3D Face Biometrics for Homeland Security Applications,"State of 3D Face Biometrics for Homeland Security Applications Anshuman Razdan1, Gerald Farin2, Myung Soo-Bae3 and Mahesh Chaudhari4"
+7e3b5d30b83a20c7cffdacf53b3ffbaf81002b54,People Transitioning Across Places: A Multimethod Investigation of How People Go to Football Games,"12589 EABXXX10.1177/0013916511412589 +© The Author(s) 2011 +Reprints and permission: http://www. +sagepub.com/journalsPermissions.nav +Environment and Behavior +XX(X) 1 –28 +© 2011 SAGE Publications +Reprints and permission: http://www. +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0013916511412589 +http://eab.sagepub.com +People Transitioning +Across Places: A +Multimethod +Investigation of +How People Go to +Football Games +R. Barry Ruback1, Robert T. Collins1, +Sarah Koon-Magnin1, Weina Ge2, +Luke Bonkiewicz1, and Clifford E. Lutz1"
+7e654380bd0d1f4c00e85da71a3081d3ada432ef,Mgan: Training Generative Adversarial Nets,"Under review as a conference paper at ICLR 2018 +MGAN: TRAINING GENERATIVE ADVERSARIAL NETS WITH +MULTIPLE GENERATORS +Anonymous authors +Paper under double-blind review"
+7ed5dca8725d59714d61ef8e1a14cc4b71c56d3f,Face Sketch to Photo Matching Using LFDA and Pre-Processing,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Impact Factor (2012): 3.358 +Face Sketch to Photo Matching Using LFDA and +Pre-Processing +Pushpa Gopal Ambhore1, Lokesh Bijole2 +Research Scholar, 2Assistant professor, Computer Engineering Department, +Padm. Dr. V. B. Kolte College of Engineering, Malkapur, Maharashtra, India"
+7e25544be9ba701c8cf02c841e0bbadb36fa0e29,Zero-Shot Visual Recognition using Semantics-Preserving Adversarial Embedding Network,"Zero-Shot Visual Recognition using Semantics-Preserving +Adversarial Embedding Networks +Long Chen1 Hanwang Zhang2 +Jun Xiao1∗ Wei Liu3 +Shih-Fu Chang4 +Zhejiang University 2Nanyang Technological University 3Tencent AI Lab 4Columbia University +{longc, {wliu, +Figure 1: (a) Attribute variance heat maps of the 312 attributes in CUB birds [60] and the 102 attributes in SUN scenes [47] +(lighter color indicates lower variance, i.e., lower discriminability) and the t-SNE [35] visualizations of the test images +represented by all attributes (left) and only the high-variance ones (right). Some of the low-variance attributes (the lighter +part to the left of the cut-off line) discarded at training are still needed in discriminating unseen test classes. (b) Comparison +of reconstructed images using SAE [25] and our proposed SP-AEN method, which is shown to retain sufficient semantics for +photo-realistic reconstruction."
7e507370124a2ac66fb7a228d75be032ddd083cc,Dynamic Pose-Robust Facial Expression Recognition by Multi-View Pairwise Conditional Random Forests,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2017.2708106, IEEE Transactions on Affective Computing Dynamic Pose-Robust Facial Expression @@ -7792,10 +26680,109 @@ Random Forests Arnaud Dapogny1 and Kevin Bailly1 and S´everine Dubuisson1 Sorbonne Universit´es, UPMC Univ Paris 06 CNRS, UMR 7222, F-75005, Paris, France"
+7ea07b7b27d59300840df17e5881dbe3a4769872,Detection driven adaptive multi-cue integration for multiple human tracking,"Detection Driven Adaptive Multi-cue Integration for Multiple Human Tracking +Ming Yang, Fengjun Lv, Wei Xu, Yihong Gong +NEC Laboratories America, Inc. +0080 North Wolfe Road, SW-350, Cupertino, CA 95014"
+10fb32ef34f815e9056ba71bc4b67a9951b4475b,End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video Features,"End-to-End Audio Visual Scene-Aware Dialog using +Multimodal Attention-Based Video Features +Chiori Hori†, Huda Alamri∗†, Jue Wang†, Gordon Wichern†, +Vincent Cartillier∗, Raphael Gontijo Lopes∗, Abhishek Das∗, +Takaaki Hori†, Anoop Cherian†, Tim K. Marks†, +Irfan Essa∗, Dhruv Batra∗ Devi Parikh∗, +Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA +School of Interactive Computing, Georgia Tech"
+1042683cf5733244238198ff486d3a65e70c9621,End-to-End Instance Segmentation with Recurrent Attention,"End-to-End Instance Segmentation with Recurrent Attention +Mengye Ren1, Richard S. Zemel1,2 +University of Toronto1, Canadian Institute for Advanced Research2"
+1059729bcca57731c81d8a9c866ceb8ed3547d8d,Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles,"Coupled Object Detection and Tracking from +Static Cameras and Moving Vehicles +Bastian Leibe, Konrad Schindler, Nico Cornelis, and Luc Van Gool"
+100f57d2eb737d6cb467bfac6e4bbfa9b39e774f,Mixing Body-Part Sequences for Human Pose Estimation,"Mixing Body-Part Sequences for Human Pose Estimation +Anoop Cherian∗ +Julien Mairal∗ Karteek Alahari∗ Cordelia Schmid∗ +Inria"
+10cdb31a23c3233527ad2f8beebe7803b7a51a8c,Altered Neocortical Microcircuitry in the Valproic Acid Rat Model of Autism,"Altered Neocortical Microcircuitry in the +Valproic Acid Rat Model of Autism +THÈSE N° 3701 (2006) +PRÉSENTÉE LE 20 NOVEMBRE +À LA FACULTÉ DES SCIENCES DE LA VIE +LABORATOIRE DE NEUROSCIENCE DES MICROCIRCUITS +PROGRAMME DOCTORAL EN NEUROSCIENCES +ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE +POUR L’OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES +Tania Rinaldi +ingénieur chimiste diplômée EPF +de nationalité suisse et originaire de Vouvry (VS) +cceptée sur proposition du jury: +Prof. R. Schneggenburger, président du jury +Prof. H. Markram, directeur de thèse +Prof. B. Gähwiler, rapporteur +Prof. A. Lüthi, rapporteur +Prof. C. Petersen, rapporteur +Suisse +(2006) année d’impression"
10e7dd3bbbfbc25661213155e0de1a9f043461a2,Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video,"Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video Zhiwu Huang, Member, IEEE, Ruiping Wang, Member, IEEE, Shiguang Shan, Senior Member, IEEE, Luc Van Gool, Member, IEEE and Xilin Chen, Fellow, IEEE"
+106b54ed74f0fffaf6408a9b847d4ac0aa0ffef9,Block-Diagonal Sparse Representation by Learning a Linear Combination Dictionary for Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2015 +Block-Diagonal Sparse Representation by Learning +Linear Combination Dictionary for Recognition +Xinglin Piao, Yongli Hu, Member, IEEE, Yanfeng Sun, Member, IEEE, Junbin Gao, Baocai Yin, Member, IEEE"
+10c4b2489d7e1ee43a1d19724d3c1e9c33ca3f29,A Question-Answering framework for plots using Deep learning,"A Question-Answering framework for plots using Deep learning +Revanth Reddy1, Rahul Ramesh1, Ameet Deshpande1 and Mitesh M. Khapra1 +Indian Institute of Technology Madras"
+10d39dedfaf34d862e3ca7216521c6290044ff87,Synthesized Classifiers for Zero-Shot Learning,"Synthesized Classifiers for Zero-Shot Learning +Soravit Changpinyo∗, Wei-Lun Chao∗ +U. of Southern California +Los Angeles, CA +Boqing Gong +U. of Central Florida +Orlando, FL +schangpi, +Fei Sha +U. of California +Los Angeles, CA"
+10c077bf2dd1bed928926feb37837862ab786808,"Multiple Target Tracking and Identity Linking under Split, Merge and Occlusion of Targets and Observations","Multiple target tracking and identity linking under split, merge and +occlusion of targets and observations +nonymous submission +Keywords: +Tracking, graphical models, MAP inference, particle tracking, live cell tracking, intelligent headlights."
+101c5b39f4fc4dda1f39bf0c00e196f0a4720af2,Viewpoint Invariant Human Re-Identification in Camera Networks Using Pose Priors and Subject-Discriminative Features,"Viewpoint Invariant Human Re-identification in +Camera Networks Using Pose Priors and +Subject-Discriminative Features +Ziyan Wu, Student Member, IEEE, Yang Li, Student Member, IEEE, and Richard J. Radke, Senior +Member, IEEE"
+10d8a48deae967b627839cc95c98b6c080ba9966,Overview of the ImageCLEF 2013 Scalable Concept Image Annotation Subtask,"Overview of the ImageCLEF 2013 Scalable +Concept Image Annotation Subtask +Mauricio Villegas,† Roberto Paredes† and Bart Thomee‡ +ITI/DSIC, Universitat Polit`ecnica de Val`encia +Cam´ı de Vera s/n, 46022 Val`encia, Spain +Yahoo! Research +Avinguda Diagonal 177, 08018 Barcelona, Spain"
+10ca3d8802ab0cc6ce000682a42fd9f6575a2006,Embedding Semantic Information into the Content of Natural Scenes Images,"http://dx.doi.org/10.5755/j01.eee.18.9.2808 +ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 18, NO. 9, 2012 +Embedding Semantic Information into the +Content of Natural Scenes Images +G. Kazakeviciute-Januskeviciene1, E. Januskevicius2 +Department of Graphical systems, Vilnius Gediminas Technical University, +Saulėtekio av.11, Vilnius, Lithuania, phone: +370 5 2744848 +Department of Building Structures, Vilnius Gediminas Technical University, +Pylimo St. 26/1, Vilnius, Lithuania; phone: +370 5 2745205"
+10b3afc6a10149cd88bc6f4007b41895d661d5fe,SAN: Learning Relationship Between Convolutional Features for Multi-scale Object Detection,"SAN: Learning Relationship between +Convolutional Features +for Multi-Scale Object Detection +Yonghyun Kim1[0000−0003−0038−7850], Bong-Nam Kang2[0000−0002−6818−7532], +nd Daijin Kim1[0000−0002−8046−8521] +Department of Computer Science and Engineering, POSTECH, Korea +Department of Creative IT Engineering, POSTECH, Korea"
+1099d475ee0807fc0e4aec55b636db4abc01dcb6,Perceptual Principles for Video Classification With Slow Feature Analysis,"Perceptual principles for video classification with +Slow Feature Analysis +Christian Th´eriault(1), Nicolas Thome(1), Matthieu Cord(1), Patrick P´erez(2) +(1)UPMC-Sorbonne Universities, Paris, France (2)Technicolor, France"
+10be82098017fc2d60b0572cea8032afabad5d1a,A Dataset for Multimodal Question Answering in the Cultural Heritage Domain,"Proceedings of the Workshop on Language Technology Resources and Tools for Digital Humanities (LT4DH), +pages 10–17, Osaka, Japan, December 11-17 2016."
10ce3a4724557d47df8f768670bfdd5cd5738f95,Fisher Light-Fields for Face Recognition across Pose and Illumination,"Fihe igh Fie Ac e ad Ra @@ -7820,8 +26807,67 @@ The a Prediction of Difficult Endotracheal Intubation Gabriel L. Cuendet, Student Member, IEEE, Patrick Schoettker, Anıl Y¨uce Student Member, IEEE, Matteo Sorci, Hua Gao, Christophe Perruchoud, Jean-Philippe Thiran, Senior Member, IEEE"
+101c7bfc56091b627886636afcf1103c1cecccf6,Rapid Clothing Retrieval via Deep Learning of Binary Codes and Hierarchical Search,"Rapid Clothing Retrieval via Deep Learning of Binary +Codes and Hierarchical Search +Kevin Lin +Academia Sinica, Taiwan +Huei-Fang Yang +Academia Sinica, Taiwan +Kuan-Hsien Liu +Academia Sinica, Taiwan +Jen-Hao Hsiao +Yahoo! Taiwan +Chu-Song Chen +Academia Sinica, Taiwan"
+10114df7ddbb221337cc1e99e1de0eab8e47c95d,Evaluating Feature Importance for Re-identification,"Chapter 9 +Evaluating Feature Importance for +Re-Identification +Chunxiao Liu, Shaogang Gong, Chen Change Loy, and Xinggang Lin"
+1068f6eca07c35426ca67961f00c3cac4866f155,Bilinear Models for 3-D Face and Facial Expression Recognition,"Bilinear Models for 3D Face and Facial +Expression Recognition +Iordanis Mpiperis, Sotiris Malassiotis and Michael G. Strintzis, Fellow,"
+102a2096ba2e2947dc252445f764e7583b557680,Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks,"Precomputed Real-Time Texture Synthesis with +Markovian Generative Adversarial Networks +Chuan Li and Michael Wand +Institut for Informatik, University of Mainz, Germany"
+10261848b16292a5c8c700de6c6c9f692867c9c8,Cleaning Training-Datasets with Noise-Aware Algorithms,"Cleaning Training-Datasets with Noise-Aware Algorithms +Instituto Nacional de Astrof´ısica ´Optica y Electr´onica, +H. Jair Escalante +Computer Science Department +Tonantzintla, Puebla, 72840, M´exico"
100641ed8a5472536dde53c1f50fa2dd2d4e9be9,Visual attributes for enhanced human-machine communication,"Visual Attributes for Enhanced Human-Machine Communication* Devi Parikh1"
+10678172baa93d8318dd1945d09f38721a0c1ffa,A Comparison of Adaptive Appearance Methods for Tracking Faces in Video Surveillance,"A Comparison of Adaptive Appearance Methods for Tracking +Faces in Video Surveillance +M. Ali Akber Dewan*, E. Granger*, F. Roli†, R. Sabourin*, and G. L. Marcialis† +*Laboratoire d’imagerie, de vision et d’intelligence artificielle, École de technologie supérieure, +Université du Québec, Montréal, Canada +Department of Electrical and Electronic Engineering, University of Cagliari, Piazza d'Armi, Cagliari, Italy +Keywords: Biometrics, Face Tracking, Spatiotemporal Face +Recognition, Video Surveillance, On-Line and Incremental +Learning, Adaptive Appearance Methods."
+10916d4eeacbf63a178c229868160189c6ce8850,Extraction of Illumination Invariant Features using Fuzzy Threshold based Approach,"International Conference on Intelligent Systems and Data Processing (ICISD) 2011 +Special Issue published by International Journal of Computer Applications® (IJCA) +Extraction of Illumination Invariant Features using +Fuzzy Threshold based Approach +R. M. Makwana +V. K. Thakar +N.C. Chauhan +Dept. of Computer Engineering +A. D. Patel Inst. of Technology, +S.P. University, New V.V. Nagar +Dept. of Electronics and Commu. +A. D. Patel Inst. of Technology +S.P. University, New V.V. Nagar +Dept. of Information Technology +A. D. Patel Inst. of Technology +S.P. University, New V.V. Nagar +in unconstrained environment"
+105fdf31d14ec55fda91c05059ec83162ba7ce3a,Automatic feature generation and selection in predictive analytics solutions,AutomaticfeaturegenerationandselectioninpredictiveanalyticssolutionsSuzannevandenBosch
+10f641aabdd8bc1eb87fae74c63b814d8ef274a5,Automatic Single-Image People Segmentation and Removal for Cultural Heritage Imaging,"Automatic Single-Image People Segmentation +nd Removal for Cultural Heritage Imaging +Marco Manfredi, Costantino Grana, and Rita Cucchiara +Universit`a degli Studi di Modena e Reggio Emilia, Modena MO 41125, Italy"
101569eeef2cecc576578bd6500f1c2dcc0274e2,Multiaccuracy: Black-Box Post-Processing for Fairness in Classification,"Multiaccuracy: Black-Box Post-Processing for Fairness in Michael P. Kim∗† Classification @@ -7845,6 +26891,26 @@ Republic of China Full list of author information is available at the end of the rticle"
+107010b7f2abe3c0c9df62bcef35eb77f6fc76df,Domain-Adversarial Training of Neural Networks,"Journal of Machine Learning Research 17 (2016) 1-35 +Submitted 5/15; Published 4/16 +Domain-Adversarial Training of Neural Networks +Yaroslav Ganin +Evgeniya Ustinova +Skolkovo Institute of Science and Technology (Skoltech) +Skolkovo, Moscow Region, Russia +Hana Ajakan +Pascal Germain +D´epartement d’informatique et de g´enie logiciel, Universit´e Laval +Qu´ebec, Canada, G1V 0A6 +Hugo Larochelle +D´epartement d’informatique, Universit´e de Sherbrooke +Qu´ebec, Canada, J1K 2R1 +Fran¸cois Laviolette +Mario Marchand +D´epartement d’informatique et de g´enie logiciel, Universit´e Laval +Qu´ebec, Canada, G1V 0A6 +Victor Lempitsky +Skolkovo Institute of Science and Technology (Skoltech)"
10fcbf30723033a5046db791fec2d3d286e34daa,On-Line Cursive Handwriting Recognition: A Survey of Methods and Performances,"On-Line Cursive Handwriting Recognition: A Survey of Methods nd Performances Dzulkifli Mohamad* , 2Muhammad Faisal Zafar*, and 3Razib M. Othman* @@ -7855,14 +26921,61 @@ Geometry for 2D Face Recognition cross Pose Carlos D. Castillo, Student Member, IEEE, and David W. Jacobs, Member, IEEE"
+103590b36d026928a90eae7ade9d7da318202168,Indoor Scene Recognition Using Local Semantic Concepts,"Indoor Scene Recognition Using Local Semantic +Concepts +Elham Seifossadat1, Niloofar Gheissari2 and Ali Fanian3 +Electrical and Computer Department,Isfahan University of Technology +Isfahan, Iran +Electrical and Computer Department,Isfahan University of Technology +Isfahan, Iran +3 Electrical and Computer Department,Isfahan University of Technology +Isfahan, Iran"
+10773e5c1bc8a9a901a8baf4d0b891397975ea9d,Group encoding of local features in image classification,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-1-6 ©2012 IAPR"
10d334a98c1e2a9e96c6c3713aadd42a557abb8b,Scene Text Recognition Using Part-Based Tree-Structured Character Detection,"Scene Text Recognition using Part-based Tree-structured Character Detection Cunzhao Shi, Chunheng Wang, Baihua Xiao, Yang Zhang, Song Gao and Zhong Zhang State Key Laboratory of Management and Control for Complex Systems, CASIA, Beijing, China"
+1038aa6c1f63c1de9045f10e47ed573810cb4a52,A Video-Based Method for Objectively Rating Ataxia,"A Video-Based Method for Objectively Rating Ataxia +Ronnachai Jaroensri∗1, Amy Zhao∗1, Guha Balakrishnan1, Derek Lo2, Jeremy Schmahmann3, +John Guttag1, and Fr´edo Durand1 +MIT CSAIL 2Yale University 3Massachusetts General Hospital"
+1040a32d5bd5e6f4c8bc1932345ef93671e2c019,Real-time RGB-D based template matching pedestrian detection,"Real-Time RGB-D based Template Matching Pedestrian Detection +Omid Hosseini jafari and Michael Ying Yang"
+109df0e8e5969ddf01e073143e83599228a1163f,Scheduling heterogeneous multi-cores through performance impact estimation (PIE),"Scheduling Heterogeneous Multi-Cores through +Performance Impact Estimation (PIE) +Kenzo Van Craeynest•∗ Aamer Jaleel† +Lieven Eeckhout• +Paolo Narvaez† +Joel Emer†‡ +Ghent University• +Ghent, Belgium +{kenzo.vancraeynest, +Intel Corporation, VSSAD† +{aamer.jaleel,paolo.narvaez, +Hudson, MA +Cambridge, MA"
1048c753e9488daa2441c50577fe5fdba5aa5d7c,Recognising faces in unseen modes: A tensor based approach,"Recognising faces in unseen modes: a tensor based approach Santu Rana, Wanquan Liu, Mihai Lazarescu and Svetha Venkatesh {santu.rana, wanquan, m.lazarescu, Dept. of Computing, Curtin University of Technology GPO Box U1987, Perth, WA 6845, Australia."
+191753aa338f24bb41f7bacb4326e0c0a1b90459,"Visual People Detection – Different Models, Comparison and Discussion","Visual People Detection – Different Models, Comparison and Discussion +Bernt Schiele, Mykhaylo Andriluka, Nikodem Majer, Stefan Roth and Christian Wojek +Department of Computer Science, TU Darmstadt"
+199fdc3c0b73d9469d2e732c97e889bfc8bf8bff,"Multi-Class Constrained Normalized Cut With Hard, Soft, Unary and Pairwise Priors and its Applications to Object Segmentation","Multi-Class Constrained Normalized Cut With +Hard, Soft, Unary and Pairwise Priors and Its +Applications to Object Segmentation +Han Hu, Jianjiang Feng, Member, IEEE, Chuan Yu, and Jie Zhou, Senior Member, IEEE"
+199aabb19ea78576a74d573739a7f35cf04fac6e,Fast globally optimal 2D human detection with loopy graph models,"Fast Globally Optimal 2D Human +Detection with Loopy Graph Models +Paper by +T.-P. Tian and S. Sclaroff +Slides by A. Vedaldi"
+19fd089807f8925b9384bae6e66cbfe7e6d318aa,Acume: A new visualization tool for understanding facial expression and gesture data,"Acume: A New Visualization Tool for +Understanding Facial Expression and Gesture +Daniel McDuff - MIT Media Lab +March 24, 2011"
19841b721bfe31899e238982a22257287b9be66a,Recurrent Neural Networks,"Published as a conference paper at ICLR 2018 SKIP RNN: LEARNING TO SKIP STATE UPDATES IN RECURRENT NEURAL NETWORKS @@ -7870,11 +26983,46 @@ V´ıctor Campos∗†, Brendan Jou‡, Xavier Gir´o-i-Nieto§, Jordi Torres† Barcelona Supercomputing Center, ‡Google Inc, §Universitat Polit`ecnica de Catalunya, ΓColumbia University {victor.campos,"
+19cfe13e8196872b81d6f31d2849dc540d146f7c,A Bayesian Framework for Sparse Representation-Based 3-D Human Pose Estimation,"A Bayesian Framework for Sparse +Representation-Based 3D Human Pose Estimation +Behnam Babagholami-Mohamadabadi, Amin Jourabloo, Ali Zarghami, and Shohreh Kasaei Senior Member, IEEE"
+19dc5a1156819230e6ae425e9c9d56e898d6bcb9,Comparing human and machine face recognition,"Comparing human and machine face recognition1 +Face Recognition Algorithms +Surpass Humans Matching Faces Over +Changes in Illumination +Alice J. O’TOOLE, P. Jonathon PHILLIPS, Fang JIANG, Janet AYYAD, Nils PENARD, +nd Hervé ABDI*"
+19fcb95815e4c225b250f7deed9be3e90963933d,Evaluación de la calidad de las imágenes de rostros utilizadas para la identificación de las personas,"ISSN: 1405-5546 +Instituto Politécnico Nacional +México +Méndez-Vázquez, Heydi; Chang, Leonardo; Rizo-Rodríguez, Dayron; Morales-González, Annette +Evaluación de la calidad de las imágenes de rostros utilizadas para la identificación de las personas +Instituto Politécnico Nacional +Distrito Federal, México +Disponible en: http://www.redalyc.org/articulo.oa?id=61523309003 +Cómo citar el artículo +Número completo +Más información del artículo +Página de la revista en redalyc.org +Sistema de Información Científica +Red de Revistas Científicas de América Latina, el Caribe, España y Portugal +Proyecto académico sin fines de lucro, desarrollado bajo la iniciativa de acceso abierto"
+19441b8be551e8134dd9eb33238309bc2de0a42f,Playing for Benchmarks,"Playing for Benchmarks +Stephan R. Richter +TU Darmstadt +Zeeshan Hayder +Vladlen Koltun +Intel Labs +Figure 1. Data for several tasks in our benchmark suite. Clockwise from top left: input video frame, semantic segmentation, semantic +instance segmentation, 3D scene layout, visual odometry, optical flow. Each task is presented on a different image."
192723085945c1d44bdd47e516c716169c06b7c0,Vision and Attention Theory Based Sampling for Continuous Facial Emotion Recognition,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation Vision and Attention Theory Based Sampling for Continuous Facial Emotion Recognition Albert C. Cruz, Student Member, IEEE, Bir Bhanu, Fellow, IEEE, and Ninad S. Thakoor, Member, IEEE"
+197a3c1863c780507798c9550dd6faadeb65caaa,Processing and Recognising Faces in 3D Images,",300+OPEN ACCESS BOOKS107,000+INTERNATIONALAUTHORS AND EDITORS113+ MILLIONDOWNLOADSBOOKSDELIVERED TO151 COUNTRIESAUTHORS AMONGTOP 1%MOST CITED SCIENTIST12.2%AUTHORS AND EDITORSFROM TOP 500 UNIVERSITIESSelection of our books indexed in theBook Citation Index in Web of Science™Core Collection (BKCI)Chapter from the book New Approaches to Characterization and Recognition of FacesDownloaded from: http://www.intechopen.com/books/new-approaches-to-characterization-and-recognition-of-facesPUBLISHED BYWorld's largest Science,Technology & Medicine Open Access book publisherInterested in publishing with InTechOpen?Contact us at"
+19b9e5127155730c618c0e1b41e1c723f143651d,Face Verification for Mobile Personal Devices,"Face Verification for Mobile Personal Devices +Qian Tao"
19fb5e5207b4a964e5ab50d421e2549ce472baa8,Online emotional facial expression dictionary,"International Conference on Computer Systems and Technologies - CompSysTech’14 Online Emotional Facial Expression Dictionary Léon Rothkrantz"
@@ -7888,6 +27036,13 @@ Received: 3 December 2008 / Accepted: 11 March 2011 / Published online: 1 April Ó Springer-Verlag London Limited 2011 supervised manifold the local sub-manifolds."
+19bc52323383732c3c7d73e11726f6232515d2f9,KAIST Multi-Spectral Day/Night Data Set for Autonomous and Assisted Driving,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +KAIST Multi-Spectral Day/Night Data Set for +Autonomous and Assisted Driving +Yukyung Choi +, Namil Kim, Soonmin Hwang, Kibaek Park, Jae Shin Yoon, +Kyounghwan An, Member, IEEE, and In So Kweon, Member, IEEE +i.e., a thermal"
191674c64f89c1b5cba19732869aa48c38698c84,Face Image Retrieval Using Attribute - Enhanced Sparse Codewords,"International Journal of Advanced Technology in Engineering and Science www.ijates.com Volume No.03, Issue No. 03, March 2015 ISSN (online): 2348 – 7550 FACE IMAGE RETRIEVAL USING ATTRIBUTE - @@ -7930,6 +27085,23 @@ Guoxu Zhou, Andrzej Cichocki Fellow, IEEE, Yu Zhang, and Danilo Mandic Fellow, I Recognition Michael Wilber University of Colorado, Colorado Springs"
+197eafb6abb6b7d2813eec0891b143e27fc57386,Smile! Studying expressivity of happiness as a synergic factor in collaborative information seeking,"Smile! Studying expressivity of happiness as a synergic factor in collaborative +information seeking. +Rutgers University has made this article freely available. Please share how this access benefits you. +Your story matters. [https://rucore.libraries.rutgers.edu/rutgers-lib/47408/story/] +This work is the AUTHOR'S ORIGINAL (AO) +This is the author's original version of a work, which may or may not have been subsequently published. The author accepts full +responsibility for the article. Content and layout is as set out by the author. +Citation to this Version: Shah, Chirag, González-Ibáñez, Roberto & Córdova-Rubio, Natalia. (2011). Smile! Studying +expressivity of happiness as a synergic factor in collaborative information seeking.. New Orleans +(La.). Retrieved from doi:10.7282/T3NK3GWF. +Terms of Use: Copyright for scholarly resources published in RUcore is retained by the copyright holder. By virtue of its appearance in this open +ccess medium, you are free to use this resource, with proper attribution, in educational and other non-commercial settings. Other uses, such as +reproduction or republication, may require the permission of the copyright holder. +Article begins on next page +SOAR is a service of RUcore, the Rutgers University Community Repository +RUcore is developed and maintained by Rutgers University Libraries"
+19911c7e66b05d5aa28673608fdfc50ef00591dd,Recognizing Human Faces: Physical Modeling and Pattern Classification,
195d331c958f2da3431f37a344559f9bce09c0f7,Parsing occluded people by flexible compositions,"Parsing Occluded People by Flexible Compositions Xianjie Chen, Alan Yuille University of California, Los Angeles. @@ -7950,9 +27122,68 @@ that, even in presence of occlusion, the visible nodes form a connected sub- tree of the graphical model. We call each connected subtree a flexible com- position of object parts. This involves a novel method for learning occlusion ues. During inference we need to search over a mixture of different flexible"
+19a30ad283f2ab2d84f1c666d17492da14056d75,Visuomotor Coordination in Reach-To-Grasp Tasks: From Humans to Humanoids and Vice Versa,"Visuomotor Coordination in Reach-To-Grasp Tasks: +From Humans to Humanoids and Vice Versa +THÈSE NO 6695 (2015) +PRÉSENTÉE LE 4 JUIN 2015 +À L’ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE +À LA FACULTÉ DES SCIENCES ET TECHNIQUES DE L'INGÉNIEUR +LABORATOIRE D'ALGORITHMES ET SYSTÈMES D'APPRENTISSAGE +À L’INSTITUTO SUPERIOR TÉCNICO (IST) DA UNIVERSIDADE DE LISBOA +INSTITUTO DE SISTEMA E ROBOTICA +PROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUE +DOUTORAMENTO EM ENGENHARIA ELECTROTÉCNICA E DE COMPUTADORES +POUR L’OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES (PhD) +Luka LUKIC +Prof. A. Billard, Prof. J. Santos-Victor, directeurs de thèse +cceptée sur proposition du jury: +Prof. J. Faria, président du jury +Prof. D. Vernon, rapporteur +Prof. E. Bicho, rapporteuse +Prof. A. Bernardino, rapporteur +Prof. G. Sandini, rapporteur"
+19a3374ac2f917b408b4bcdca33fc9e9fd7ff260,Visual Fixation Patterns during Reciprocal Social Interaction Distinguish a Subgroup of 6-Month-Old Infants At-Risk for Autism from Comparison Infants.,"J Autism Dev Disord (2007) 37:108–121 +DOI 10.1007/s10803-006-0342-4 +O R I G I N A L P A P E R +Visual Fixation Patterns during Reciprocal Social Interaction +Distinguish a Subgroup of 6-Month-Old Infants At-Risk +for Autism from Comparison Infants +Noah Merin Æ Gregory S. Young Æ Sally Ozonoff Æ +Sally J. Rogers +Published online: 27 December 2006 +Ó Springer Science+Business Media, LLC 2006"
+19c53302bda8a82ec40d314a85b1713f43058a1a,Deep learning models of biological visual information processing,"Turcsány, Diána (2016) Deep learning models of +iological visual information processing. PhD thesis, +University of Nottingham. +Access from the University of Nottingham repository: +http://eprints.nottingham.ac.uk/35561/1/thesis_DianaTurcsany.pdf +Copyright and reuse: +The Nottingham ePrints service makes this work by researchers of the University of +Nottingham available open access under the following conditions. +This article is made available under the University of Nottingham End User licence and may +e reused according to the conditions of the licence. For more details see: +http://eprints.nottingham.ac.uk/end_user_agreement.pdf +For more information, please contact"
+197f945b66995e4d006497808586f828f8a88a86,Part Discovery from Partial Correspondence,"Part Discovery from Partial Correspondence +Subhransu Maji +Gregory Shakhnarovich +Toyota Technological Institute at Chicago, IL, USA"
19c0c7835dba1a319b59359adaa738f0410263e8,Natural Image Statistics and Low-Complexity Feature Selection,"Natural Image Statistics and Low-Complexity Feature Selection Manuela Vasconcelos and Nuno Vasconcelos, Senior Member, IEEE"
+193c9bd069e9457ac8650a8dfd4319bb3f4afd56,Improving Person Tracking Using an Inexpensive Thermal Infrared Sensor,"Improving Person Tracking Using an Inexpensive Thermal Infrared Sensor +Suren Kumar +Univ. of SUNY-Buffalo +Tim K. Marks +Mitsubishi Electric Research Labs +Michael Jones +Mitsubishi Electric Research Labs"
+19cfec264e863793dd96a5f308a3b603c6b9912e,Attention-Based Ensemble for Deep Metric Learning,"Attention-based Ensemble for +Deep Metric Learning +Wonsik Kim, Bhavya Goyal, Kunal Chawla, Jungmin Lee, Keunjoo Kwon +Samsung Research, +Samsung Electronics +{wonsik16.kim, bhavya.goyal, kunal.chawla, jm411.lee,"
19d583bf8c5533d1261ccdc068fdc3ef53b9ffb9,FaceNet: A unified embedding for face recognition and clustering,"FaceNet: A Unified Embedding for Face Recognition and Clustering Florian Schroff Dmitry Kalenichenko @@ -7970,10 +27201,23 @@ Image Search Amol Darkunde, 2Manoj Jalan, 3Yelmar Mahesh, 4Shivadatta Shinde, 5Dnyanda Patil , 2, 3, 4 B. E. Dept of CSE, 5 Asst. Prof. Dept of CSE , 2, 3, 4, 5 Dr.D.Y.Patil College of Engineering, Pune, Maharashtra, India"
+1936a73920c5a7eb97e8b73cb9a6096aa509e402,Robust Multi-Person Tracking from Moving Platforms,"Robust Multi-Person Tracking from Moving Platforms +Andreas Ess1, Konrad Schindler1, Bastian Leibe1,2 and Luc van Gool1,3 +ETH Z¨urich +KU Leuven, IBBT +RWTH Aachen"
+19f7654f22416e6fdf430c1c873ad3e8c15e64f8,Zero-crossing based image projections encoding for eye localization,"0th European Signal Processing Conference (EUSIPCO 2012) +© EURASIP, 2012 - ISSN 2076-1465 +. INTRODUCTION"
197c64c36e8a9d624a05ee98b740d87f94b4040c,Regularized Greedy Column Subset Selection,"Regularized Greedy Column Subset Selection Bruno Ordozgoiti*a, Alberto Mozoa, Jes´us Garc´ıa L´opez de Lacalleb Department of Computer Systems, Universidad Polit´ecnica de Madrid Department of Applied Mathematics, Universidad Polit´ecnica de Madrid"
+19158dfe2815e7f9eebc5822687e83d0a89ae147,Semantic Regularisation for Recurrent Image Annotation,[cs.CV] 16 Nov 2016
+1957956856dc04ebee5815bd62874687e2af7260,Joint Optical Flow and Temporally Consistent Semantic Segmentation,"Joint Optical Flow and Temporally Consistent +Semantic Segmentation +Junhwa Hur and Stefan Roth +Department of Computer Science, TU Darmstadt"
19d4855f064f0d53cb851e9342025bd8503922e2,Learning SURF Cascade for Fast and Accurate Object Detection,"Learning SURF Cascade for Fast and Accurate Object Detection Jianguo Li, Yimin Zhang Intel Labs China"
@@ -7994,6 +27238,31 @@ Peer reviewed eScholarship.org Powered by the California Digital Library University of California"
+19359fb238888c0eb012a4ab5c6f0fa0e9be493b,Enhanced Facial Expression Recognition using 2DPCA Principal component Analysis and Gabor Wavelets,"Enhanced Facial Expression Recognition +using 2DPCA Principal component Analysis +nd Gabor Wavelets. +(1)Laboratory of Automatic and Signals Annaba (LASA) , Department of electronics, Faculty of Engineering, +Zermi.Narima(1), Saaidia.Mohammed(2), +Badji-Mokhtar University, P.O.Box 12, Annaba-23000, Algeria. +E-Mail : +(2) Département de Génie-électrique, Université M.C.M. Souk-Ahras, Algeria"
+19766585a701749fc297a5ca6b8cdc0c62d4ba1b,A Bottom-Up Approach for Pancreas Segmentation Using Cascaded Superpixels and (Deep) Image Patch Labeling,"A Bottom-up Approach for Pancreas Segmentation using +Cascaded Superpixels and (Deep) Image Patch Labeling +Amal Faraga, Le Lua, Holger R. Rotha, Jiamin Liua, Evrim Turkbeya, Ronald M. Summersa,∗ +Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes +of Health Clinical Center, Building 10 Room 1C224D, MSC 1182, Bethesda, MD 20892-1182, United States"
+4c6d6bb5bafba9e04d8f2ce128be71fba1d1e0e8,Human parsing with a cascade of hierarchical poselet based pruners,"HUMAN PARSING WITH A CASCADE OF HIERARCHICAL POSELET BASED PRUNERS +Duan Tran† +Yang Wang‡ +University of Illinois at Urbana Champaign† +David Forsyth† +University of Manitoba‡"
+4c0ce0ed9cc92115874be4397f6240769d3ed84f,The effect of familiarity on face adaptation.,"doi:10.1068/p6774 +The effect of familiarity on face adaptation +Sarah Laurence, Graham Hole +School of Psychology, University of Sussex, Falmer, Brighton BN1 9QH, Sussex, UK; +e-mail: +Received 14 July 2010, in revised form 30 March 2011"
4c6e1840451e1f86af3ef1cb551259cb259493ba,Hand Posture Dataset Creation for Gesture Recognition,"HAND POSTURE DATASET CREATION FOR GESTURE RECOGNITION Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria @@ -8004,13 +27273,165 @@ Departamento de E.I.O. y Computacion 8271 Universidad de La Laguna, Spain Keywords: Image understanding, Gesture recognition, Hand dataset."
+4c69da79843016d5d934464d3777030741978180,Neuromorphic Atomic Switch Networks,"Neuromorphic Atomic Switch Networks +Audrius V. Avizienis1. +Adam Z. Stieg2,3*, James K. Gimzewski1,2,3 +, Henry O. Sillin1. +, Cristina Martin-Olmos1, Hsien Hang Shieh2, Masakazu Aono3, +Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, California, United States of America, 2 California NanoSystems Institute, +University of California Los Angeles, Los Angeles, California, United States of America, 3 World Premier International Center for Materials Nanoarchitectonics, National +Institute for Materials Science, Tsukuba, Ibaraki, Japan"
+4cc5fb6cf48b2c58b283460b19f3beeb7e5b6a22,Clickage: towards bridging semantic and intent gaps via mining click logs of search engines,"Clickage: Towards Bridging Semantic and Intent Gaps +via Mining Click Logs of Search Engines +Xian-Sheng Hua, Linjun Yang, Jingdong Wang, Jing Wang +Ming Ye, Kuansan Wang, Yong Rui, Jin Li +Microsoft Corporation, One Microsoft Way, Redmond WA 98052, USA +{xshua; linjuny; jingdw; v-wangji; mingye; kuansanw; yongrui;"
+4cf74211e635c73ca5816199ef33d10c3462beae,Review of Facial Expression Recognition System and Used Datasets,"IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 +REVIEW OF FACIAL EXPRESSION RECOGNITION SYSTEM AND +USED DATASETS +Shyna Dutta1, V.B. Baru2, +ME Student, Department of Electronics and Telecommunication, Sinhgad College of Engineering Vadgaon, Pune, +Associate Professor, Department of Electronics and Telecommunication, Sinhgad College of Engineering Vadgaon,"
+4c41b774a6bdf43d980f640880cc49b82ae19b34,3D Facial Landmark Detection under Large Yaw and Expression Variations,"D Facial Landmark Detection under +Large Yaw and Expression Variations +Panagiotis Perakis, Member, IEEE Computer Society, Georgios Passalis, +Theoharis Theoharis, and Ioannis A. Kakadiaris, Senior Member, IEEE"
+4cff5b5099b0227730efa9e9fd724a63dc0c0c2f,Learning Efficient Binary Codes From High-Level Feature Representations for Multilabel Image Retrieval,"Learning Efficient Binary Codes From +High-Level Feature Representations +for Multilabel Image Retrieval +Lei Ma +, Hongliang Li, Senior Member, IEEE, Fanman Meng, Member, IEEE, Qingbo Wu, Member, IEEE, +nd King Ngi Ngan, Fellow, IEEE"
+4cdfef0fec0918dcf5c40b9b53c9e3f48be0462b,Unsupervised robotic sorting: Towards autonomous decision making robots,"Unsupervised robotic sorting: +Towards autonomous decision making +robots +Joris Gu´erin, St´ephane Thiery, Eric Nyiri and Olivier Gibaru +Arts et M´etiers ParisTech, Lille, FRANCE"
+4c4454aa7a2a244c678f507a982fe8827ba419bb,Adversarial Examples for Semantic Image Segmentation,"Workshop track - ICLR 2017 +ADVERSARIAL EXAMPLES FOR +SEMANTIC IMAGE SEGMENTATION +Volker Fischer1, Mummadi Chaithanya Kumar2, Jan Hendrik Metzen1 & Thomas Brox2 +Bosch Center for Artificial Intelligence, Robert Bosch GmbH +University of Freiburg +{volker.fischer,"
+4c797506d610525591288f813621b271ce879452,The automaticity of face perception is influenced by familiarity,"Atten Percept Psychophys (2017) 79:2202–2211 +DOI 10.3758/s13414-017-1362-1 +The automaticity of face perception is influenced by familiarity +Xiaoqian Yan 1 & Andrew W. Young 1 & Timothy J. Andrews 1 +Published online: 5 July 2017 +# The Author(s) 2017. This article is an open access publication"
+4c5041f8b93fd71a851445e84bfca0d7d0c3bb9b,Enhancing Memory-Based Particle Filter with Detection-Based Memory Acquisition for Robustness under Severe Occlusion,"ENHANCING MEMORY-BASED PARTICLE FILTER WITH +DETECTION-BASED MEMORY ACQUISITION FOR ROBUSTNESS +UNDER SEVERE OCCLUSION +Dan Mikami, Kazuhiro Otsuka, Shiro Kumano and Junji Yamato +NTT Communication Science Laboratories, NTT, 3-1 Morinosato-Wakamiya, Atsugi, Kanagawa, 243-0198, Japan +Keywords: +Pose Tracking, Face Pose, Memory-based Prediction, Memory Acquisition."
4c815f367213cc0fb8c61773cd04a5ca8be2c959,Facial expression recognition using curvelet based local binary patterns,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE ICASSP 2010"
+4ca8ff09f24f0838022f1d0b94af4331f6e538cd,Semantic Parsing to Probabilistic Programs for Situated Question Answering,"Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 160–170, +Austin, Texas, November 1-5, 2016. c(cid:13)2016 Association for Computational Linguistics"
+4cf17bca0e19070fbe9bb25644787f65fa6ebe1a,Human Pose Estimation,"Human pose estimation +Leonid Sigal, Disney Research, Pittsburgh +Synonyms +– Articulated pose estimation +– Body configuration recovery +Related Concepts +– Human pose tracking +– People tracking +– Articulated pose tracking +– Body parsing +– People parsing +Definition +Human pose estimation is the process of estimating the configuration of the +ody (pose) from a single, typically monocular, image. +Background +Human pose estimation is one of the key problems in computer vision that +has been studied for well over 15 years. The reason for its importance is the +bundance of applications that can benefit from such a technology. For example, +human pose estimation allows for higher level reasoning in the context of human- +omputer interaction and activity recognition; it is also one of the basic building"
+4ce18536eec7917da848be6b5f783d3ee3d49677,Fast Face Detection in One Line of Code,"Fast Face Detection in One Line of Code +Michael Zucchi, B.E. (Comp. Sys. Eng.) +Una liated, unfunded, personal research."
+4c1ef2a628627798939dccc072d33f9e12b48640,Advanced Hybrid Color Space Normalization for Human Face Extraction and Detection,"IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 4, 2013 | ISSN (online): 2321-0613 +Advanced Hybrid Color Space Normalization for Human Face +Extraction and Detection +Jayakrishna.V1 Akhila G.P.2 Shafeena Basheer3 +, 2Faculty 3PG Student +, 3Amal Jyothi College of Engineering, Kanjirappally +UKF College of Engineering &Technology,Parippally +S.P.B.Patel Engineering College, Mehsana, Gujarat +(CSN) +technique +enhancing +is contained +in Y component, and"
4c4e49033737467e28aa2bb32f6c21000deda2ef,Improving Landmark Localization with Semi-Supervised Learning,"Improving Landmark Localization with Semi-Supervised Learning Sina Honari1∗, Pavlo Molchanov2, Stephen Tyree2, Pascal Vincent1,4,5, Christopher Pal1,3, Jan Kautz2 MILA-University of Montreal, 2NVIDIA, 3Ecole Polytechnique of Montreal, 4CIFAR, 5Facebook AI Research. {honaris, {pmolchanov, styree,"
+4c39000bbd6761dd9e5609fe310af51facb835a9,Kinects and human kinetics: A new approach for studying pedestrian behavior,"This paper might be a pre-copy-editing or a post-print author-produced .pdf of an article accepted for publication. For the +definitive publisher-authenticated version, please refer directly to publishing house’s archive system."
+4c822705edd305d04f2c02ac9b1b73421e857961,Towards fully automated person re-identification,"Towards Fully Automated Person Re-Identification +Matteo Taiana, Dario Figueira, Athira Nambiar, Jacinto Nascimento and Alexandre Bernardino +Institute for Systems and Robotics, IST, Lisboa, Portugal +Re-Identification, Pedestrian Detection, Camera Networks, Video Surveillance +Keywords:"
+4c477ba5513ec9c629ca3442c1fee15612259905,Complex Relations in a Deep Structured Prediction Model for Fine Image Segmentation,"Complex Relations in a Deep Structured Prediction +Model for Fine Image Segmentation +Cristina Mata, Guy Ben-Yosef, Boris Katz +Computer Science and Artificial Intelligence Laboratory +{cfmata, gby, +Center for Brains, Minds and Machines"
+4c55ea9c04d46d60ec5789f4e4c3224c41360768,Dimensionality Reduction Using Similarity-Induced Embeddings,"IEEE Copyright Notice +Copyright c(cid:13)2017 IEEE +Personal use of this material is permitted. Permission from +IEEE must be obtained for all other uses, in any current or fu- +ture media, including reprinting/republishing this material for +dvertising or promotional purposes, creating new collective +works, for resale or redistribution to servers or lists, or reuse +of any copyrighted component of this work in other works. +Published in: IEEE Transactions on Neural Networks and +Learning Systems +URL: http://ieeexplore.ieee.org/document/8004500 +DOI: 10.1109/TNNLS.2017.2728818 +DOI 10.1109/TNNLS.2017.2728818 c(cid:13)2017 IEEE"
+4cc675422395ed7dc7e4772280f7c57cac6fbaee,Efficient person re-identification by hybrid spatiogram and covariance descriptor,"Efficient Person Re-identification by Hybrid Spatiogram and Covariance +Descriptor +Mingyong Zeng, Zemin Wu, Chang Tian, Lei Zhang, and Lei Hu +College of Communications Engineering, PLA University +of Science and Technology, Nanjing 210007, China"
+4c1e47ba68b81d210718f837b197253164decaf0,Evaluation of Quality Factors for the Captured Facial Image,"International Journal of Computer Applications (0975 – 8887) +Volume 142 – No.10, May 2016 +Evaluation of Quality Factors for the Captured Facial +Image +Abhay Goyal +M.Tech. Student +Department of ECE +SBSSTC, Ferozepur, Pujnab"
+4ce68170f85560942ee51465e593b16560f9c580,Practical Matrix Completion and Corruption Recovery Using Proximal Alternating Robust Subspace Minimization,"(will be inserted by the editor) +Practical Matrix Completion and Corruption Recovery using +Proximal Alternating Robust Subspace Minimization +Yu-Xiang Wang · Choon Meng Lee · Loong-Fah Cheong · Kim-Chuan Toh +Introduction +Completing a low-rank matrix from partially observed +entries, also known as matrix completion, is a central +task in many real-life applications. The same abstrac- +tion of this problem has appeared in diverse fields such +s signal processing, communications, information re- +trieval, machine learning and computer vision. For in- +stance, the missing data to be filled in may correspond +to plausible movie recommendations (Koren et al 2009; +Funk 2006), occluded feature trajectories for rigid or +non-rigid structure from motion, namely SfM (Hart- +ley and Schaffalitzky 2003; Buchanan and Fitzgibbon +005) and NRSfM (Paladini et al 2009), relative dis- +tances of wireless sensors (Oh et al 2010), pieces of un- +ollected measurements in DNA micro-array (Friedland +et al 2006), just to name a few."
4c81c76f799c48c33bb63b9369d013f51eaf5ada,Multi-modal Score Fusion and Decision Trees for Explainable Automatic Job Candidate Screening from Video CVs,"Multi-modal Score Fusion and Decision Trees for Explainable Automatic Job Candidate Screening from Video CVs Heysem Kaya1, Furkan G¨urpınar2, and Albert Ali Salah2 @@ -8030,19 +27451,206 @@ University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent Constantin Vertan Image Processing and Analysis Laboratory University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313"
+4cfa2fe87c250534fd2f285c2300e7ca2cd9e325,"Visual, Auditory, and Cross Modal Sensory Processing in Adults with Autism: An EEG Power and BOLD fMRI Investigation","ORIGINAL RESEARCH +published: 19 April 2016 +doi: 10.3389/fnhum.2016.00167 +Visual, Auditory, and Cross Modal +Sensory Processing in Adults with +Autism: An EEG Power and BOLD +fMRI Investigation +Elizabeth’ C. Hames1, Brandi Murphy2, Ravi Rajmohan3, Ronald C. Anderson1, +Mary Baker1*, Stephen Zupancic2, Michael O’Boyle4 and David Richman5 +Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USA, 2 Department of Audiology, +Texas Tech University Health Sciences Center, Lubbock, TX, USA, 3 Department of Pharmacology and Neuroscience, Texas +Tech University Health Sciences Center, Lubbock, TX, USA, 4 College of Human Sciences, Texas Tech University, Lubbock, +TX, USA, 5 Burkhart Center for Autism Education and Research, Texas Tech University, Lubbock, TX, USA +Electroencephalography (EEG) and blood oxygen level dependent functional magnetic +resonance imagining (BOLD fMRI) assessed the neurocorrelates of sensory processing +of visual and auditory stimuli +in 11 adults with autism (ASD) and 10 neurotypical (NT) +ontrols between the ages of 20–28. We hypothesized that ASD performance on +ombined audiovisual trials would be less accurate with observable decreased EEG +power across frontal, temporal, and occipital channels and decreased BOLD fMRI"
+4c88e41424022c7c5f111d34d931fae15f52a551,"CUR Decompositions, Similarity Matrices, and Subspace Clustering","CUR Decompositions, Similarity Matrices, and +Subspace Clustering +Akram Aldroubi, Keaton Hamm, Ahmet Bugra Koku, and Ali Sekmen"
+4cfae149d6acd8cffc12c06ed796f1f84dce0e73,Face Recognition Based on Image Latent Semantic Analysis Model and SVM,"International Journal of Signal Processing, Image Processing and Pattern Recognition +Vol. 6, No. 3, June, 2013 +Face Recognition Based on Image Latent Semantic Analysis Model +nd SVM +Jucheng Yang 1, 2, Min Luo3 and Yanbin Jiao4 +Ahead Software Company Limited, Nanchang, 330041, China +College of Computer Science and Information Engineering, Tianjin University of +Science and Technology, Tianjin, China +Jiangxi Institute of Computing Technology, Nanchang, China +School of Information Technology, Jiangxi University of Finance and Economics, +Nanchang, China"
+4cfdd0c8313ac4f92845dcd658115beb115b97ce,Multi-Task Learning as Multi-Objective Optimization,"Multi-Task Learning as Multi-Objective Optimization +Ozan Sener +Intel Labs +Vladlen Koltun +Intel Labs"
+4c863a15c4da0d0ccd20c5897a4e33fb771fe3eb,The effect of forced choice on facial emotion recognition: a comparison to open verbal classification of emotion labels,"OPEN ACCESS +Research Article +The effect of forced choice on facial emotion recognition: +comparison to open verbal classification of emotion +labels +Der Effekt eines geschlossenen Antwortformats auf die mimische +Emotionserkennung: ein Vergleich mit der freien verbale Zuordnung von +Emotionswörtern +Kerstin +Limbrecht-Ecklundt1 +Andreas Scheck1 +Lucia Jerg-Bretzke1 +Steffen Walter1 +Holger Hoffmann1 +Harald C. Traue1 +University of Ulm, University +Clinic of Psychosomatic +Medicine and Psychotherapy, +Medical Psychology, Ulm, +Germany"
+4c05dc45b82b79e87f7b337ccf9f48d537c0e6e2,Exploring Heterogeneity within a Core for Improved Power Efficiency,"Exploring Heterogeneity within a Core for +Improved Power Efficiency +Sudarshan Srinivasan, Nithesh Kurella, Israel Koren, Fellow, IEEE, and Sandip Kundu, Fellow, IEEE"
+2608a2499819053468f4e6f77a715c2dbfefdfb0,Object Classification using Hybrid Holistic Descriptors: Application to Building Detection in Aerial Orthophotos,"Object Classification using Hybrid Holistic +Descriptors: Application to Building Detection +in Aerial Orthophotos +Fadi Dornaika, Abdelmalik Moujahid, Alireza Bosaghzadeh, Youssef El Merabet, and Yassine Ruichek"
+26172460c2c47886f8b0e141c15de29c9766bfbe,An Iterative Co-Saliency Framework for RGBD Images,"IEEE TRANSACTIONS ON CYBERNETICS, VOL. XX, NO. XX, XXXX 2017 +An Iterative Co-Saliency Framework for RGBD +Images +Runmin Cong, Jianjun Lei, Senior Member, IEEE, Huazhu Fu, Weisi Lin, Fellow, IEEE, +Qingming Huang, Senior Member, IEEE, Xiaochun Cao, Senior Member, IEEE, and Chunping Hou"
+2603efdc673e9c7cfa0c1e1dfda512b6ef54ea2c,On the Use of Simple Geometric Descriptors Provided by RGB-D Sensors for Re-Identification,"Sensors 2013, 13, 8222-8238; doi:10.3390/s130708222 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +On the Use of Simple Geometric Descriptors Provided by +RGB-D Sensors for Re-Identification +Javier Lorenzo-Navarro *, Modesto Castrill´on-Santana and Daniel Hern´andez-Sosa +SIANI, Universidad de Las Palmas de Gran Canaria, Campus de Tafira, +Las Palmas de Gran Canaria 35017, Spain; E-Mails: (M.C.-S.); +(D.H.-S.) +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +34-928-458-747. +Received: 25 March 2013; in revised form: 7 June 2013 / Accepted: 20 June 2013 / +Published: 27 June 2013"
2661f38aaa0ceb424c70a6258f7695c28b97238a,Multilayer Architectures for Facial Action Unit Recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 4, AUGUST 2012 Multilayer Architectures for Facial Action Unit Recognition Tingfan Wu, Nicholas J. Butko, Paul Ruvolo, Jacob Whitehill, Marian S. Bartlett, and Javier R. Movellan"
+2603d8578a6c95a9b9d4cb8a73bc66f18d523f37,Deep Parts Similarity Learning for Person Re-Identification,
264a84f4d27cd4bca94270620907cffcb889075c,Deep motion features for visual tracking,"Deep Motion Features for Visual Tracking Susanna Gladh, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg Computer Vision Laboratory, Department of Electrical Engineering, Link¨oping University, Sweden"
+2677a79b6381f3e7787c5dca884fa53d0b28dfe2,Supplementary Document : Single-Shot Multi-Person 3 D Pose Estimation From Monocular RGB 1,"Supplementary Document: +Single-Shot Multi-Person 3D Pose +Estimation From Monocular RGB +. Read-out Process +An algorithmic description of the read-out process +is provided in Alg. 1. +Algorithm 1 3D Pose Inference +: Given: P 2D, C2D, M +: for all i ∈ (1..m) do +if C2D +[k] > thresh, k ∈ {pelvis, neck} then +Person i is detected +for all joints j ∈ (1..n) do +rloc = P2D +Pi[:, j] = ReadLocMap(j, rloc) +limbs +{arml, armr, legl, legr, head} do +{pelvis, neck}; j = parent(j) do +j = getExtremity(l); j +if isValidReadoutLoc(i, j) then"
+266b5b038750e1ab1311e38554e4c2c8ba6564fd,SLIC Superpixels Compared to State-of-the-Art Superpixel Methods,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, DECEMBER 2011 +SLIC Superpixels Compared to State-of-the-art +Superpixel Methods +Radhakrishna Achanta, Appu Shaji, Kevin Smith, +Aurelien Lucchi, Pascal Fua, and Sabine S¨usstrunk"
+26a6b2051fe7970f94584e9efbfcf7bdcfd1d6d6,Diffeomorphic image registration with applications to deformation modelling between multiple data sets,"Diffeomorphic image registration +with applications to deformation +modelling between multiple data sets +Bartłomiej Władysław Papież +A thesis submitted in partial fulfilment +for the requirements of the degree +of Doctor of Philosophy +The research presented in this thesis was carried out at the +Applied Digital Signal and Image Processing Research Centre, +School of Computing, Engineering and Physical Sciences, +University of Central Lancashire, +October 2012"
+26a32691321574ac1c90c58f47ec73fdfbc8507a,SATURN (Situational awareness tool for urban responder networks),"SATURN +(Situational Awareness Tool for Urban Responder Networks) +Heather Zwahlen +Aaron Yahr +Danielle Berven +Michael T. Chan +Maximilian Merfeld +Christine Russ +Jason Thornton +MIT Lincoln Laboratory +Lexington, MA +{heatherz | ayahr | danielle.berven | mchan | max.merfeld +| christine russ |"
+265644f1b6740ca34bfbe9762b90b33021adde62,Deep Learning in Medical Imaging: General Overview.,"Review Article | Experiment, Engineering, and Physics +https://doi.org/10.3348/kjr.2017.18.4.570 +pISSN 1229-6929 · eISSN 2005-8330 +Korean J Radiol 2017;18(4):570-584 +Deep Learning in Medical Imaging: General Overview +June-Goo Lee, PhD1, Sanghoon Jun, PhD2, 3, Young-Won Cho, MS2, 3, Hyunna Lee, PhD2, 3, +Guk Bae Kim, PhD2, 3, Joon Beom Seo, MD, PhD2*, Namkug Kim, PhD2, 3* +Biomedical Engineering Research Center, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea; 2Department of +Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea; 3Department of +Convergence Medicine, Biomedical Engineering Research Center, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea +The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was +introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing +gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of +sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, +enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. +Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition +tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. +This review article offers perspectives on the history, development, and applications of deep learning technology, particularly +regarding its applications in medical imaging. +Keywords: Artificial intelligence; Machine learning; Convolutional neural network; Recurrent Neural Network; Computer-aided;"
+267bb08aa4eeefa1ef653716ca0ab572748a3a4e,Vision-Based Real-Time Aerial Object Localization and Tracking for UAV Sensing System,"Vision-based Real-Time Aerial Object Localization +nd Tracking for UAV Sensing System +Yuanwei Wu, Student Member, +IEEE, Yao Sui, Member, IEEE, and Guanghui Wang, Member, IEEE"
26a72e9dd444d2861298d9df9df9f7d147186bcd,Collecting and annotating the large continuous action dataset,"DOI 10.1007/s00138-016-0768-4 ORIGINAL PAPER Collecting and annotating the large continuous action dataset Daniel Paul Barrett1 · Ran Xu2 · Haonan Yu1 · Jeffrey Mark Siskind1 Received: 18 June 2015 / Revised: 18 April 2016 / Accepted: 22 April 2016 / Published online: 21 May 2016 © The Author(s) 2016. This article is published with open access at Springerlink.com"
+269c1f9df4a36b361d32bfdc81457b0a32b60966,Dimensionality Reduction of Visual Features for Efficient Retrieval and Classification,"SIP (2016), vol. 5, e14, page 1 of 14 © The Authors, 2016. +This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unre- +stricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. +doi:10.1017/ATSIP.2016.14 +industrial technology advances +Dimensionality reduction of visual features +for efficient retrieval and classification +petros t. boufounos1, hassan mansour1, shantanu rane2 and anthony vetro1 +Visual retrieval and classification are of growing importance for a number of applications, including surveillance, automotive, +s well as web and mobile search. To facilitate these processes, features are often computed from images to extract discriminative +spects of the scene, such as structure, texture or color information. Ideally, these features would be robust to changes in per- +spective, illumination, and other transformations. This paper examines two approaches that employ dimensionality reduction +for fast and accurate matching of visual features while also being bandwidth-efficient, scalable, and parallelizable. We focus on +two classes of techniques to illustrate the benefits of dimensionality reduction in the context of various industrial applications. +The first method is referred to as quantized embeddings, which generates a distance-preserving feature vector with low rate. The +second method is a low-rank matrix factorization applied to a sequence of visual features, which exploits the temporal redun- +dancy among feature vectors associated with each frame in a video. Both methods discussed in this paper are also universal in +that they do not require prior assumptions about the statistical properties of the signals in the database or the query. Further- +more, they enable the system designer to navigate a rate versus performance trade-off similar to the rate-distortion trade-off in +onventional compression."
+26861e41e5b44774a2801e1cd76fd56126bbe257,Personalized Tour Recommendation Based on User Interests and Points of Interest Visit Durations,"Personalized Tour Recommendation based on User Interests and Points of Interest +Visit Durations +Kwan Hui Lim*†, Jeffrey Chan*, Christopher Leckie*† and Shanika Karunasekera* +*Department of Computing and Information Systems, The University of Melbourne, Australia +Victoria Research Laboratory, National ICT Australia, Australia"
266766818dbc5a4ca1161ae2bc14c9e269ddc490,Boosting a Low-Cost Smart Home Environment with Usage and Access Control Rules,"Article Boosting a Low-Cost Smart Home Environment with Usage and Access Control Rules @@ -8053,9 +27661,18 @@ Institute of Information Science and Technologies of CNR (CNR-ISTI)-Italy, 56124 (E.M.); (C.V.) * Correspondence: Tel.: +39-050-315-2965 Received: 27 April 2018; Accepted: 31 May 2018; Published: 8 June 2018"
+2606e6a5759c030e259ebf3f4261b9c04a36a609,Generating Semantically Precise Scene Graphs from Textual Descriptions for Improved Image Retrieval,"Proceedings of the 2015 Workshop on Vision and Language (VL’15), pages 70–80, +Lisbon, Portugal, 18 September 2015. c(cid:13)2015 Association for Computational Linguistics."
265af79627a3d7ccf64e9fe51c10e5268fee2aae,A Mixture of Transformed Hidden Markov Models for Elastic Motion Estimation,"A Mixture of Transformed Hidden Markov Models for Elastic Motion Estimation Huijun Di, Linmi Tao, and Guangyou Xu, Senior Member, IEEE"
+267595dd40cd109c93e67874a1cf49ce79871f3a,A Compromise Principle in Deep Monocular Depth Estimation,"A Compromise Principle in Deep Monocular Depth +Estimation +Huan Fu, Mingming Gong, Chaohui Wang, and Dacheng Tao, Fellow, IEEE"
+26c89f890da91119ffa16d5a23fba963257ef3fc,Tattoo Image Search at Scale: Joint Detection and Compact Representation Learning,"Tattoo Image Search at Scale: Joint Detection +nd Compact Representation Learning +Hu Han, Member, IEEE, Jie Li, Anil K. Jain, Fellow, IEEE, +Shiguang Shan, Senior Member, IEEE and Xilin Chen, Fellow, IEEE"
26af867977f90342c9648ccf7e30f94470d40a73,Joint Gender and Face Recognition System for RGB-D Images with Texture and DCT Features,"IJIRST –International Journal for Innovative Research in Science & Technology| Volume 3 | Issue 04 | September 2016 ISSN (online): 2349-6010 Joint Gender and Face Recognition System for @@ -8070,6 +27687,26 @@ Associate Professor Department of Computer Science & Engineering Federal Institute of Science and Technology, Mookkannoor PO, Angamaly, Ernakulam, Kerala 683577, India"
+2663fa2f1777dc779a73d678c7919cce37b5fb61,Relevance - Weighted ( 2 D ) 2 LDA Image Projection Technique for Face Recognition,"Relevance-Weighted (2D)2LDA +Image Projection Technique for Face Recognition +In this paper, a novel image projection technique for +face recognition application is proposed which is based on +linear discriminant analysis (LDA) combined with the +relevance-weighted (RW) method. The projection is +performed through 2-directional and 2-dimensional LDA, +or (2D)2LDA, which simultaneously works in row and +olumn directions to solve the small sample size problem. +Moreover, a weighted discriminant hyperplane is used in +the between-class scatter matrix, and an RW method is +used in the within-class scatter matrix to weigh the +information to resolve confusable data in these classes. +This technique is called the relevance-weighted (2D)2LDA, +or RW(2D)2LDA, which is used for a more accurate +discriminant decision than that produced by the +onventional LDA or 2DLDA. The proposed technique +has been successfully tested on four face databases. +Experimental results +the proposed"
26c884829897b3035702800937d4d15fef7010e4,Facial Expression Recognition by Supervised Independent Component Analysis Using MAP Estimation,"IEICE TRANS. INF. & SYST., VOL.Exx–??, NO.xx XXXX 200x PAPER Facial Expression Recognition by Supervised Independent @@ -8090,6 +27727,14 @@ selective prior as a supervised ICA (sICA). We formulated the learning rule for sICA by taking a Maximum a Posteriori (MAP) scheme and further derived a fixed point algorithm for learning the de-mixing matrix. We investigate the performance of sICA"
+26cdb9b6d94c1d6c6a01792fee3c176585f594ac,Hybrid Person Detection and Tracking in H.264/AVC Video Streams,"Hybrid Person Detection and Tracking in H.264/AVC Video Streams +Philipp Wojaczek1, Marcus Laumer1,2, Peter Amon2, Andreas Hutter2 and André Kaup1 +Multimedia Communications and Signal Processing, +Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany +Imaging and Computer Vision, Siemens Corporate Technology, Munich, Germany +Keywords: +Object Detection, Person Detection, Tracking, Compressed Domain, Pixel Domain, H.264/AVC, Mac- +roblocks, Compression, Color Histogram, Hue, HSV, Segmentation."
26ad6ceb07a1dc265d405e47a36570cb69b2ace6,Neural Correlates of Cross-Cultural Adaptation,"RESEARCH AND EXPLOR ATORY DEVELOPMENT DEPARTMENT REDD-2015-384 @@ -8106,12 +27751,41 @@ Mike Wolmetz Alice Jackson Prepared for: Office of Naval Research"
+26ad124271c118e207113ae42f0fd3d30f204ea1,State of the Art Report on Video-Based Graphics and Video Visualization,"General Copyright Notice +The documents distributed by this server have been provided by the contributing authors as a means to ensure timely +dissemination of scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the +uthors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that +ll persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works +may not be reposted without the explicit permission of the copyright holder. +R. Borgo, M. Chen, B. Daubney, E. Grundy, G. Heidemann, B. Höferlin, M. Höferlin, H. Leitte, D. +Weiskopf, X. Xie: +State of the Art Report on Video-Based Graphics and Video Visualization, +Computer Graphics Forum, Vol. 31, No. 8, 2450-2477, 2012. +DOI: 10.1111/j.1467-8659.2012.03158.x +This is the author’s personal copy of the final, accepted version of the paper, which slightly differs from +the version published in Computer Graphics Form. +Copyright © 2012 The Eurographics Association and Blackwell Publishing Ltd. +Preprint"
+260081528f19f6f7e8e5ae16a776b62ad8c2ed0d,An Agent Based WCET Analysis for Top-View Person Re-Identification,"An agent-based WCET analysis for Top-View +Person Re-Identification +Marina Paolanti, Valerio Placidi, +Michele Bernardini, Andrea Felicetti, Rocco Pietrini, and +Emanuele Frontoni +Department of Information Engineering, Universit`a Politecnica delle Marche, +Via Brecce Bianche 12, 60131, Ancona, Italy"
+26f5b8a79fac681ffb132c4863c51a55bc2b20e2,Visual speech synthesis from 3D mesh sequences driven by combined speech features,"VISUAL SPEECH SYNTHESIS FROM 3D MESH SEQUENCES DRIVEN BY COMBINED +SPEECH FEATURES +Felix Kuhnke and J¨orn Ostermann +Institut f¨ur Informationsverarbeitung, Leibniz Universit¨at Hannover, Germany"
26437fb289cd7caeb3834361f0cc933a02267766,Innovative Assessment Technologies: Comparing ‘Face-to-Face’ and Game-Based Development of Thinking Skills in Classroom Settings,"012 International Conference on Management and Education Innovation IPEDR vol.37 (2012) © (2012) IACSIT Press, Singapore Innovative Assessment Technologies: Comparing ‘Face-to-Face’ and Game-Based Development of Thinking Skills in Classroom Settings Gyöngyvér Molnár 1 + and András Lőrincz 2 University of Szeged, 2 Eötvös Loránd University"
+2690264001ccd4b682b7b4c0334c80af6f5e9c9c,Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation,"Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation +for Sim-to-Real Domain Adaptation +Alexandra Carlson1, Katherine A. Skinner1, Ram Vasudevan2 and Matthew Johnson-Roberson3"
26e570049aaedcfa420fc8c7b761bc70a195657c,Hybrid Facial Regions Extraction for Micro-expression Recognition System,"J Sign Process Syst DOI 10.1007/s11265-017-1276-0 Hybrid Facial Regions Extraction for Micro-expression @@ -8120,11 +27794,48 @@ Sze-Teng Liong1,2,3 · John See4 · Raphael C.-W. Phan2 · KokSheik Wong5 · Su-Wei Tan2 Received: 2 February 2016 / Revised: 20 October 2016 / Accepted: 10 August 2017 © Springer Science+Business Media, LLC 2017"
+264dcfb5be3f89dc0950472a2a274ef7b641b1af,Dynamic Objects Segmentation for Visual Localization in Urban Environments,"Dynamic Objects Segmentation for Visual +Localization in Urban Environments +G. Zhou1, B. Bescos2, M. Dymczyk1, M. Pfeiffer1, J. Neira2, R. Siegwart1"
+21b0b2f5df87318912d58d3b843da363a4fb91c3,"Distributed and Higher-Order Graphical Models: towards Segmentation, Tracking, Matching and 3D Model Inference Defended by","ECOLECENTRALEPARISPHDTHESIStoobtainthetitleofDoctorofEcoleCentraleParisSpecialty:APPLIEDMATHEMATICSDistributedandHigher-OrderGraphicalModels:towardsSegmentation,Tracking,Matchingand3DModelInferenceDefendedbyChaohuiWANGpreparedatEcoleCentraleParis,MASlaboratorydefendedonSeptember29,2011JURYChairman:Prof.HenriMAITRE-TélécomParisTechReviewers:Prof.MichaelJ.BLACK-MaxPlanckInstituteforIntelligentSystemsProf.PhilipH.S.TORR-OxfordBrookesUniversityAdvisor:Prof.NikosPARAGIOS-EcoleCentraleParisExaminers:Prof.PatrickBOUTHEMY-INRIA-RennesProf.VladimirKOLMOGOROV-InstituteofScienceandTechnologyAustriaProf.DimitrisSAMARAS-StonyBrookUniversity"
21ef129c063bad970b309a24a6a18cbcdfb3aff5,Individual and Inter-related Action Unit Detection in Videos for Affect Recognition,"POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCESacceptée sur proposition du jury:Dr J.-M. Vesin, président du juryProf. J.-Ph. Thiran, Prof. D. Sander, directeurs de thèseProf. M. F. Valstar, rapporteurProf. H. K. Ekenel, rapporteurDr S. Marcel, rapporteurIndividual and Inter-related Action Unit Detection in Videos for Affect RecognitionTHÈSE NO 6837 (2016)ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNEPRÉSENTÉE LE 19 FÉVRIER 2016À LA FACULTÉ DES SCIENCES ET TECHNIQUES DE L'INGÉNIEURLABORATOIRE DE TRAITEMENT DES SIGNAUX 5PROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUE Suisse2016PARAnıl YÜCE"
218b2c5c9d011eb4432be4728b54e39f366354c1,Enhancing Training Collections for Image Annotation: An Instance-Weighted Mixture Modeling Approach,"Enhancing Training Collections for Image Annotation: An Instance-Weighted Mixture Modeling Approach Neela Sawant, Student Member, IEEE, James Z. Wang, Senior Member, IEEE, Jia Li, Senior Member, IEEE."
+21967faefa55857c6a09f9fe52a10a394757d59c,Emotion Recognition Ability Test Using JACFEE Photos: A Validity/Reliability Study of a War Veterans' Sample and Their Offspring,"RESEARCH ARTICLE +Emotion Recognition Ability Test Using +JACFEE Photos: A Validity/Reliability Study of +War Veterans' Sample and Their Offspring +Ivone Castro-Vale1,5*, Milton Severo2,3, Davide Carvalho4,5, Rui Mota-Cardoso1 +Medical Psychology Unit, Department of Clinical Neurosciences and Mental Health, Faculty of Medicine, +University of Porto, Porto, Portugal, 2 Department of Clinical Epidemiology, Predictive Medicine and Public +Health, Faculty of Medicine, University of Porto, Porto, Portugal, 3 Department of Medical Education and +Simulation, Faculty of Medicine, University of Porto, Porto, Portugal, 4 Department of Endocrinology, +Diabetes and Metabolism, Centro Hospitalar Sāo Joāo, Faculty of Medicine, University of Porto, Porto, +Portugal, 5 Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal +11111"
+21262e01039e5994114b4c102fc80e9afa3f1bde,Pedestrian Detection and Tracking in Thermal Images from Aerial MPEG Videos,
+21679eb7e953bd132803703c27dcd56484d497e6,"utism , oxytocin and interoception","Neuroscience and Biobehavioral Reviews 47 (2014) 410–430 +Contents lists available at ScienceDirect +Neuroscience +Biobehavioral +Reviews +j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / n e u b i o r e v +Review +Autism, oxytocin and interoception +E. Quattrocki∗, Karl Friston 1 +The Wellcome Trust Centre for Neuroimaging, UCL, 12 Queen Square, London WC1N 3BG, UK +Article history: +Received 5 February 2014 +Received in revised form 23 July 2014 +Accepted 20 September 2014 +Available online 30 September 2014 +Keywords: +Autism +Oxytocin +Interoception +Bayesian predictive coding"
2162654cb02bcd10794ae7e7d610c011ce0fb51b,Joint gaze-correction and beautification of DIBR-synthesized human face via dual sparse coding,"978-1-4799-5751-4/14/$31.00 ©2014 IEEE http://www.skype.com/ http://www.google.com/hangouts/ @@ -8146,11 +27857,57 @@ NEC Laboratories America, Inc. Dept. of CS, Univ. of Texas at San Antonio Cupertino, CA 95014 San Antonio, TX 78249"
+219b7b157f2a559ecdffe21c2a0edf5285931298,Deep hashing for compact binary codes learning,"Deep Hashing for Compact Binary Codes Learning +Venice Erin Liong1, Jiwen Lu1, Gang Wang1,2, Pierre Moulin1,3, and Jie Zhou4 +ADSC, Singapore, 2NTU, Singapore, 3UIUC, USA, 4Tsinghua University, China +Large scale visual search has attracted great attention in computer vision +due to its wide potential applications [1]. Hashing is a powerful technique +for large-scale visual search and a variety of hashing-based methods have +een proposed in the literature [3, 4, 7]. The basic idea of hashing-based +pproach is to construct a series of hash functions to map each visual object +into a binary feature vector so that visually similar samples are mapped into +similar binary codes. +In this paper, we propose a new deep hashing (DH) method to learn +ompact binary codes for large scale visual search. Figure 1 illustrates the +asic idea of the proposed approach. Different from most existing binary +odes learning methods which usually seek a single linear projection to map +each sample into a binary vector [2, 5, 6], we develop a deep neural network +to seek multiple hierarchical non-linear transformations to learn these bina- +ry codes. For a given sample xn, we obtain a binary vector bn by passing +it to a network which contains multiple stacked layers of nonlinear trans- +formations. Assume we have M + 1 layers, the output for the mth layer is: +n = s(Wmhm−1"
+2129304075990cd2f3317ea67a2acf52b7d7a3e2,Face Recognition and Detection through Similarity Measurements,"International Journal of Computer Applications (0975 – 8887) +Volume 174 – No.3, September 2017 +Face Recognition and Detection through Similarity +Measurements +Irfan Bashir +M.Tech( CSE) Schoral +SMVDU, Kakryal Katra, Jummu"
+21e82350472bf6a12af0f761b8dea91cb16bf42f,Cost-Sensitive Convolution based Neural Networks for Imbalanced Time-Series Classification,"Cost-Sensitive Convolution based Neural +Networks for Imbalanced Time-Series +Classification +Yue Geng* and Xinyu Luo +Mechanical and Electrical Engineering Institute of CUMTB, Beijing, 100083, China +E-mail:"
214ac8196d8061981bef271b37a279526aab5024,Face Recognition Using Smoothed High-Dimensional Representation,"Face Recognition Using Smoothed High-Dimensional Representation Juha Ylioinas, Juho Kannala, Abdenour Hadid, and Matti Pietik¨ainen Center for Machine Vision Research, PO Box 4500, FI-90014 University of Oulu, Finland"
+218595e1979007ccd6b1bc5a30a3484841c0eafa,Discovering Beautiful Attributes for Aesthetic Image Analysis,"Noname manuscript No. +(will be inserted by the editor) +Discovering beautiful attributes for aesthetic image analysis +Luca Marchesotti · Naila Murray · Florent Perronnin +Received: date / Accepted: date"
+21913787b7ed62773926a287b60308d1960e6966,LR-CNN for fine-grained classification with varying resolution,"LR-CNN FOR FINE-GRAINED CLASSIFICATION WITH VARYING RESOLUTION +M. Chevalier(1,2), N. Thome(1), M. Cord(1), J. Fournier(2), G. Henaff(2), E. Dusch(2) +(1) Sorbonne Universit´es, UPMC Univ Paris 06, LIP6, 4 place Jussieu 75005 Paris, France +(2) Thales Optronique S.A.S., 2 avenue Gay-Lussac, 78990 Elancourt, France"
+218603147709344d4ff66625d83603deee2854bf,Learning Deep Embeddings with Histogram Loss,"Learning Deep Embeddings with Histogram Loss +Evgeniya Ustinova and Victor Lempitsky +Skolkovo Institute of Science and Technology (Skoltech) +Moscow, Russia"
213a579af9e4f57f071b884aa872651372b661fd,Automatic and Efficient Human Pose Estimation for Sign Language Videos,"Int J Comput Vis DOI 10.1007/s11263-013-0672-6 Automatic and Efficient Human Pose Estimation for Sign @@ -8159,8 +27916,56 @@ James Charles · Tomas Pfister · Mark Everingham · Andrew Zisserman Received: 4 February 2013 / Accepted: 29 October 2013 © Springer Science+Business Media New York 2013"
+2155739f578e33449546f45a0b4cf64dbd614025,what is facereader ?,"FaceReader +Methodology Note +what is facereader? +FaceReader™ is a program for facial analysis. It can detect +facial expressions. FaceReader has been trained to classify +expressions in one of the following categories: happy, +sad, angry, surprised, scared, disgusted, and neutral. These +emotional categories have been described by Ekman [1] +s the basic or universal emotions. In addition to these +asic emotions, contempt can be classified as expression, +just like the other emotions [2]. Obviously, facial expres- +sions vary in intensity and are often a mixture of emo- +tions. In addition, there is quite a lot of interpersonal +variation. +Figure 1. Analyzing facial expressions with FaceReader. +FaceReader has been trained to classify the expressions +mentioned above. It is not possible to add expressions to +the software yourself. Please contact Noldus Information +Technology if you are interested in the classification of +other expressions."
21626caa46cbf2ae9e43dbc0c8e789b3dbb420f1,Transductive VIS-NIR face matching,"978-1-4673-2533-2/12/$26.00 ©2012 IEEE ICIP 2012"
+2118b1ce0c2551e75d30fb6ba24482e50b319a90,Ensemble Projection for Semi-supervised Image Classification,"Ensemble Projection for Semi-supervised Image Classification +Dengxin Dai +Computer Vision Lab, ETH Zurich +Luc Van Gool +Computer Vision Lab, ETH Zurich"
+216c61796c6ead27b1042046e1d95a2038624d26,Vehicle Re-identification Using Quadruple Directional Deep Learning Features,"Vehicle Re-identification Using Quadruple +Directional Deep Learning Features +Jianqing Zhu, Huanqiang Zeng, Jingchang Huang, Shengcai Liao, Zhen Lei, Canhui Cai and LiXin Zheng"
+21241d07840e3cc30feda59642571a9b459c817b,Biometrics via Oculomotor Plant Characteristics: Impact of Parameters in Oculomotor Plant Model,"This is a pre-print. Final version of the paper will be available at ACM digital library. +Biometrics via Oculomotor Plant Characteristics: +Impact of Parameters in Oculomotor Plant Model +OLEG KOMOGORTSEV, COREY HOLLAND, ALEX KARPOV, AND LARRY R. PRICE Texas State University +This paper proposes and evaluates a novel biometric approach utilizing the internal, non-visible, anatomical structure of the human eye. The +proposed method estimates the anatomical properties of the human oculomotor plant from the measurable properties of human eye movements, +utilizing a two-dimensional linear homeomorphic model of the oculomotor plant. The derived properties are evaluated within a biometric +framework to determine their efficacy in both verification and identification scenarios. The results suggest that the physical properties derived from +the oculomotor plant model are capable of achieving 20.3% equal error rate and 65.7% rank-1 identification rate on high-resolution equipment +involving 32 subjects, with biometric samples taken over four recording sessions; or 22.2% equal error rate and 12.6% rank-1 identification rate on +low-resolution equipment involving 172 subjects, with biometric samples taken over two recording sessions. +Categories and Subject Descriptors: I.2.10 [Artificial Intelligence]: Vision and Scene Understanding—Modeling and recovery of physical +ttributes; I.5.1 [Pattern Recognition]: Models—Structural; I.6.4 [Simulation and Modeling]: Model Validation and Analysis +General Terms: Biometrics +Additional Key Words and Phrases: Human oculomotor system, biological system modeling, mathematical model, security and protection. +ACM Reference Format: +Komogortsev, O., Holland, C., Karpov, A., and Price, L. R. 2014. Oculomotor Plant Characteristics: Biometric Performance Evaluation. ACM +Trans. Appl. Percept. 2, 3, Article 1 (May 2014), 13 pages. +DOI:http://dx.doi.org/10.1145/0000000.0000000 +INTRODUCTION"
21b16df93f0fab4864816f35ccb3207778a51952,Recognition of Static Gestures Applied to Brazilian Sign Language (Libras),"Recognition of Static Gestures applied to Brazilian Sign Language (Libras) Igor L. O. Bastos Math Institute @@ -8170,6 +27975,56 @@ Federal University of Bahia (UFBA), State University of Feira de Santana (UEFS) Salvador, Brazil Feira de Santana, Brazil"
+2170636d5d31eb461618b5da10f4473c67e74e73,Person Re-identification by Multi-Channel Parts-Based CNN with Improved Triplet Loss Function,"Person Re-Identification by Multi-Channel Parts-Based CNN with Improved +Triplet Loss Function +De Cheng, Yihong Gong, Sanping Zhou, Jinjun Wang, Nanning Zheng +Institute of Artificial Intelligence and Robotics +Xi’an Jiaotong University,Xi’an, Shaanxi, P.R. China"
+21ff1d20dd7b3e6b1ea02036c0176d200ec5626d,Loss Max-Pooling for Semantic Image Segmentation,"Loss Max-Pooling for Semantic Image Segmentation +Samuel Rota Bul`o(cid:63),† +Gerhard Neuhold† +Peter Kontschieder† +Mapillary - Graz, Austria - +(cid:63)FBK - Trento, Italy -"
+2168ec12eff5c3d1ff09d0f3c13d6df5b5061164,Face recognition with salient local gradient orientation binary patterns,"978-1-4244-5654-3/09/$26.00 ©2009 IEEE +ICIP 2009"
+21ac5d1c34675bf6056d2670f9fa3dde530b1716,ALB at SemEval-2018 Task 10: A System for Capturing Discriminative Attributes,"Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018), pages 963–967 +New Orleans, Louisiana, June 5–6, 2018. ©2018 Association for Computational Linguistics"
+21a1654b856cf0c64e60e58258669b374cb05539,"You Only Look Once: Unified, Real-Time Object Detection","You Only Look Once: +Unified, Real-Time Object Detection +Joseph Redmon∗, Santosh Divvala∗†, Ross Girshick¶, Ali Farhadi∗† +University of Washington∗, Allen Institute for AI†, Facebook AI Research¶ +http://pjreddie.com/yolo/"
+4dd2744a37bd1e666346a41dcd2a271945c74e2f,Human-Robot Teaming : Approaches from Joint Action and Dynamical Systems,"Human Robot Teaming: Approaches from Joint +Action and Dynamical Systems +Tariq Iqbal and Laurel D. Riek"
+4d510bca00b625f86606cb0096299b993090534a,Small Sample Learning in Big Data Era,"Small Sample Learning in Big Data Era +Jun Shu +Zongben Xu +Deyu Meng +School of Mathematics and Statistics +Ministry of Education Key Lab of Intelligent Networks and Network Security +Xi’an Jiaotong University, Xian, China"
+4dade6faf6d5d6db53d5bcb2e107311da1ad48ac,Facial Expression Biometrics Using Statistical Shape Models,"Hindawi Publishing Corporation +EURASIP Journal on Advances in Signal Processing +Volume 2009, Article ID 261542, 17 pages +doi:10.1155/2009/261542 +Research Article +Facial Expression Biometrics Using Statistical Shape Models +Wei Quan, Bogdan J. Matuszewski (EURASIP Member), Lik-Kwan Shark, +nd Djamel Ait-Boudaoud +Applied Digital Signal and Image Processing Research Centre, University of Central Lancashire, Preston PR1 2HE, UK +Correspondence should be addressed to Bogdan J. Matuszewski, +Received 30 September 2008; Revised 2 April 2009; Accepted 18 August 2009 +Recommended by Jonathon Phillips +This paper describes a novel method for representing different facial expressions based on the shape space vector (SSV) of the +statistical shape model (SSM) built from 3D facial data. The method relies only on the 3D shape, with texture information not +eing used in any part of the algorithm, that makes it inherently invariant to changes in the background, illumination, and to +some extent viewing angle variations. To evaluate the proposed method, two comprehensive 3D facial data sets have been used +for the testing. The experimental results show that the SSV not only controls the shape variations but also captures the expressive +haracteristic of the faces and can be used as a significant feature for facial expression recognition. Finally the paper suggests +improvements of the SSV discriminatory characteristics by using 3D facial sequences rather than 3D stills. +Copyright © 2009 Wei Quan et al. This is an open access article distributed under the Creative Commons Attribution License,"
4d49c6cff198cccb21f4fa35fd75cbe99cfcbf27,Topological principal component analysis for face encoding and recognition,"Topological Principal Component Analysis for face encoding and recognition Albert Pujol , Jordi Vitri(cid:18)a, Felipe Lumbreras, @@ -8178,13 +28033,107 @@ Computer Vision Center and Departament d’Inform(cid:18)atica, Edi(cid:12)ci O, Aut(cid:18)onoma de Barcelona 4da735d2ed0deeb0cae4a9d4394449275e316df2,"The rhythms of head, eyes and hands at intersections","Gothenburg, Sweden, June 19-22, 2016 978-1-5090-1820-8/16/$31.00 ©2016 IEEE"
+4db64fbc3dd2486a74dba3350d44c51e561f515f,An Ecological Visual Exploration Tool to Support the Analysis of Visual Processing Pathways in Children with Autism Spectrum Disorders,"Article +An Ecological Visual Exploration Tool to Support the +Analysis of Visual Processing Pathways in Children +with Autism Spectrum Disorders +Dario Cazzato 1, Marco Leo 2,*, Cosimo Distante 2, Giulia Crifaci 3, +Giuseppe Massimo Bernava 4, Liliana Ruta 4, Giovanni Pioggia 4 and Silvia M. Castro 5 +Interdisciplinary Centre for Security Reliability and Trust (SnT), University of Luxembourg, 29, +Avenue JF Kennedy, L-1855 Luxembourg, Luxembourg; +Institute of Applied Sciences and Intelligence Systems—CNR, 73100 Lecce, Italy; +Department of Clinical Physiology, CNR Pisa, 56124 Pisa, Italy; +Institute of Applied Sciences and Intelligence Systems—CNR, 98164 Messina, Italy; +(G.M.B.); (L.R.); (G.P.) +5 Universidad Nacional del Sur, 8000 Bahía Blanca, Argentina; +* Correspondence: +Received: 6 November 2017; Accepted: 19 December 2017; Published: 29 December 2017"
+4dc6659b5022ecc2c4e1459e9dff16ddece4147e,Transfer Learning for Illustration Classification,"CEIG - Spanish Computer Graphics Conference (2017) +F. J. Melero and N. Pelechano (Editors) +Transfer Learning for Illustration Classification +Manuel Lagunas1 Elena Garces2 +Universidad de Zaragoza, I3A +Technicolor +Figure 1: Comparison of the probabilities of the images that belong to the class pelican using our method and the network VGG19 [SZ14]. +image (a) is a photograph and image (b) is an illustration which has similar colours, gradients and edges than the natural image. On the"
+4d1fc3245b05731a313e61165c1109f42f5b4a0c,Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding,"Zhao and Zhang EURASIP Journal on Advances in Signal Processing 2012, 2012:20 +http://asp.eurasipjournals.com/content/2012/1/20 +RESEARCH +Facial expression recognition using local binary +patterns and discriminant kernel locally linear +embedding +Xiaoming Zhao1 and Shiqing Zhang2* +Open Access"
+4d4b1aa87af8bfd65ac7bc250bba5951aed40986,A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery,"Sensors 2014, 14, 4189-4210; doi:10.3390/s140304189 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Review +A Survey on Model Based Approaches for 2D and 3D Visual +Human Pose Recovery +Xavier Perez-Sala 1 +,*, Sergio Escalera 2, Cecilio Angulo 3 and Jordi Gonz`alez 4 +Fundaci´o Privada Sant Antoni Abat, Vilanova i la Geltr´u, Universitat Polit`ecnica de Catalunya, +Vilanova i la Geltr´u 08800, Catalonia, Spain +Department Mathematics (MAIA), Universitat de Barcelona and Computer Vision Center (CVC), +Barcelona 08007, Catalonia, Spain; E-Mail: +Automatic Control Department (ESAII), Universitat Polit`ecnica de Catalunya, +Vilanova i la Geltr´u 08800, Catalonia, Spain; E-Mail: +Department Computer Science, Universitat Aut`onoma de Barcelona and Computer Vision Center +(CVC), Bellaterra 08193, Catalonia, Spain; E-Mail: +* Author to whom correspondence should be addressed; E-Mail: +Received: 29 November 2013; in revised form: 30 January 2014 / Accepted: 9 February 2014 /"
+4de83b6025526ef7a340ffca30626dac53d7f8cb,SIFT/LBP 3D face recognition,"SIFT/LBP 3D face recognition +Narimen SAAD1 NourEddine DJEDI +Department of Computer Science +LESIA Laboratory +University of Biskra, Algeria"
4d530a4629671939d9ded1f294b0183b56a513ef,Facial Expression Classification Method Based on Pseudo Zernike Moment and Radial Basis Function Network,"International Journal of Machine Learning and Computing, Vol. 2, No. 4, August 2012 Facial Expression Classification Method Based on Pseudo Zernike Moment and Radial Basis Function Network Tran Binh Long, Le Hoang Thai, and Tran Hanh"
+4d87784afdb704d9eca14010212afd5cd74c60ec,Cosine Similarity Search with Multi Index Hashing,"Cosine Similarity Search +with Multi-Index Hashing +Sepehr Eghbali and Ladan Tahvildari"
+4dd72cdafead8a98dbc77a1a74bd66ffb90d3e01,Virtual and Real World Adaptation for Pedestrian Detection,"Virtual and Real World Adaptation for +Pedestrian Detection +David V ´azquez, Antonio M. L ´opez, Member, IEEE, Javier Mar´ın, Daniel Ponsa, David Ger ´onimo"
+4d8347a69e77cc02c1e1aba3a8b6646eac1a0b3d,Re-ID done right: towards good practices for person re-identification,"Re-ID done right: towards good practices for person re-identification +Jon Almaz´an1 Bojana Gaji´c2∗ Naila Murray1 Diane Larlus1 +Computer Vision Group +NAVER LABS Europe +Computer Vision Center +Dept. de Ci`encies de la Computaci´o, UAB"
+4d2022e3db712237b95fe381a75dbeb827551924,Running Head : GENDER CATEGORIZATION IN INFANTS AND CHILDREN 1 Gender Categorization in Infants and Children,"Running Head: GENDER CATEGORIZATION IN INFANTS AND CHILDREN +Gender Categorization in Infants and Children +Hong N. T. Bui +Senior Thesis in Psychology +Advisor: Karen Wynn +April 27, 2018"
4d2975445007405f8cdcd74b7fd1dd547066f9b8,Image and Video Processing for Affective Applications,"Image and Video Processing for Affective Applications Maja Pantic and George Caridakis"
+4d45612c41d3e27a30a5ec64e0d8e2362dcb6b73,Brand > Logo: Visual Analysis of Fashion Brands,"Brand > Logo: Visual Analysis of Fashion +Brands +M. Hadi Kiapour and Robinson Piramuthu +eBay, San Francisco CA 94105, USA"
+4ddd55a9f103001da8dc24d123d9223dbb67f884,Combining Face and Facial Feature Detectors for Face Detection Performance Improvement,"Combining face and facial feature detectors for +face detection performance improvement +M. Castrill´on-Santana, D. Hern´andez-Sosa, and J. Lorenzo-Navarro(cid:63) +SIANI +Universidad de Las Palmas de Gran Canaria, Spain"
+4dba7e19e2958d8ab75261219747aebc675c6f8a,Finding the Topic of a Set of Images,"Finding the Topic of a Set of Images +Gonzalo Vaca-Castano +Univeristy of Central Florida"
+4df54d4758b1a883902c036b2a10ef6d0f2d4af9,An Automatic Face Recognition System Based On Adaptive Wavelet Transforms,"International Journal of Scientific Research and Engineering Studies (IJSRES) +Volume 2 Issue 4, April 2015 +ISSN: 2349-8862 +An Automatic Face Recognition System Based On Adaptive +Wavelet Transforms +Prof. Khaladkar +Nilam Chavan +Apurva Kadam"
4db9e5f19366fe5d6a98ca43c1d113dac823a14d,"Are 1, 000 Features Worth A Picture? Combining Crowdsourcing and Face Recognition to Identify Civil War Soldiers","Combining Crowdsourcing and Face Recognition to Identify Civil War Soldiers Are 1,000 Features Worth A Picture? Vikram Mohanty, David Thames, Kurt Luther @@ -8196,8 +28145,74 @@ Review of Face Recognition Technology Using Feature Fusion Vector Shrutika Shukla, Prof. Anuj Bhargav, Prof. Prashant Badal Department of Electronics and Communication, S.R.C.E.M, Banmore, RGPV, University, Bhopal, Madhya Pradesh, India"
+4d20fbd6dcdb4408dd6268951d86b92e8d96f332,Robust Face Recognition of Variations in Blur and Illumination by Using LDA,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 +International Conference on Humming Bird ( 01st March 2014) +RESEARCH ARTICLE +OPEN ACCESS +Robust Face Recognition of Variations in Blur and Illumination +y Using LDA +Ms. K. Hema +PG Student +Department of AE +University College of Engineering +Nagercoil-629004. +Mr. J. Arun Prem Santh M. E., +Teaching Fellow +Department of ECE +University College of Engineering +Nagercoil-629004 ."
+4d334cfafd11a93394917adcffef6c1d27aa178b,Refined Clustering technique based on boosting and outlier detection,"International Journal of Scientific & Engineering Research, Volume 6, Issue 11, November-2015 472 +ISSN 2229-5518 +Refined Clustering technique based on boosting +nd outlier detection +Ms. Reshma Y. Nagpure, Prof. P. P. Rokade"
+4d6043a25bf48c6fd6aff6a46597fe1902a9c6a7,Long-term tracking of multiple interacting pedestrians using a single camera,"Long-term tracking of multiple interacting +pedestrians using a single camera +Mogomotsi Keaikitse∗, Willie Brink† and Natasha Govender∗ +Modelling and Digital Sciences +Council for Scientific and Industrial Research +Pretoria, South Africa +Department of Mathematical Sciences +Stellenbosch University +Stellenbosch, South Africa"
+4d6e7d73f5226142ffc42b4e8380882d5071e187,Discretion Within Constraint: Homophily and Structure in a Formal Organization,"This article was downloaded by: [128.32.74.70] On: 03 July 2014, At: 15:15 +Publisher: Institute for Operations Research and the Management Sciences (INFORMS) +INFORMS is located in Maryland, USA +Publication details, including instructions for authors and subscription information: +http://pubsonline.informs.org +Discretion Within Constraint: Homophily and Structure in +Formal Organization +Adam M. Kleinbaum, Toby E. Stuart, Michael L. Tushman +To cite this article: +Adam M. Kleinbaum, Toby E. Stuart, Michael L. Tushman (2013) Discretion Within Constraint: Homophily and Structure in a +Full terms and conditions of use: http://pubsonline.informs.org/page/terms-and-conditions +This article may be used only for the purposes of research, teaching, and/or private study. Commercial use +or systematic downloading (by robots or other automatic processes) is prohibited without explicit Publisher +pproval, unless otherwise noted. For more information, contact +The Publisher does not warrant or guarantee the article’s accuracy, completeness, merchantability, fitness +for a particular purpose, or non-infringement. Descriptions of, or references to, products or publications, or +inclusion of an advertisement in this article, neither constitutes nor implies a guarantee, endorsement, or +support of claims made of that product, publication, or service. +Copyright © 2013, INFORMS +Please scroll down for article—it is on subsequent pages"
+4d442ea40635a10fd3e642a7161dfc8f2b15a71e,An Image reranking model based on attributes and visual features eliminating duplication,"© 2016 IJEDR | Volume 4, Issue 2 | ISSN: 2321-9939 +An Image reranking model based on attributes and +visual features eliminating duplication +Ms.Madhuri Mhaske,2Prof.Sachin Patil +PG Scholar at G. H. Raisoni College of Engineering and Management, Chas, Ahmednagar +, 2Professor at G. H. Raisoni College of Engineering and Management, Vagholi, Pune +________________________________________________________________________________________________________"
4d7e1eb5d1afecb4e238ba05d4f7f487dff96c11,Largest center-specific margin for dimension reduction,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE ICASSP 2017"
+4d5c34fb36cf8c74880a62814750760bce0aef16,Boosting descriptors condensed from video sequences for place recognition,"Boosting Descriptors Condensed from Video Sequences for Place Recognition +Tat-Jun Chin, Hanlin Goh and Joo-Hwee Lim +Institute for Infocomm Research +1 Heng Mui Keng Terrace, Singapore 119613. +{tjchin, hlgoh,"
+4df34e0194faa27078832cb5078a2af6c9d0ea9b,Saliency Prediction in the Deep Learning Era: An Empirical Investigation,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +Saliency Prediction in the Deep Learning Era: +An Empirical Investigation +Ali Borji, Member, IEEE"
4d6ad0c7b3cf74adb0507dc886993e603c863e8c,Human Activity Recognition Based on Wearable Sensor Data : A Standardization of the State-ofthe-Art,"Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art @@ -8205,6 +28220,9 @@ Artur Jord˜ao, Antonio C. Nazare Jr., Jessica Sena and William Robson Schwartz Smart Surveillance Interest Group, Computer Science Department Universidade Federal de Minas Gerais, Brazil Email: {arturjordao, antonio.nazare, jessicasena,"
+4d7bbaa2c7e89d5ba6940ee5804cf10a6b24d6ec,Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories,"Multi-target Unsupervised Domain Adaptation +without Exactly Shared Categories +Huanhuan Yu, Menglei Hu and Songcan Chen"
4dca3d6341e1d991c902492952e726dc2a443d1c,Learning towards Minimum Hyperspherical Energy,"Learning towards Minimum Hyperspherical Energy Weiyang Liu1,*, Rongmei Lin2,*, Zhen Liu1,*, Lixin Liu3,*, Zhiding Yu4, Bo Dai1,5, Le Song1,6 Georgia Institute of Technology 2Emory University @@ -8217,9 +28235,64 @@ reuse of any copyrighted component of this work in other works. Pre-print of article that appeared at BTAS 2010. The published article can be accessed from: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5634517"
+4d231311cdfe3aba13766bd0b358d4db0a9af3d3,Processing and Recognising Faces in 3D Images,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+4dea287ad9271d4ac73c58c03b8e6e714dd2db6c,Pyramid Center - symmetric Local 1 Binary / Trinary Patterns for Pedestrian 2 Detection,"Pyramid Center-symmetric Local +Binary/Trinary Patterns for Pedestrian +Detection +Yongbin Zheng, Chunhua Shen, Richard Hartley and Xinsheng Huang +Australian National University and NICTA, Canberra"
4d47261b2f52c361c09f7ab96fcb3f5c22cafb9f,Deep multi-frame face super-resolution,"Deep multi-frame face super-resolution Evgeniya Ustinova, Victor Lempitsky October 17, 2017"
+4dc8b1c193c421f8f570c0a7eac2fc73da06cb51,MODS: Fast and Robust Method for Two-View Matching,"MODS: Fast and Robust Method for Two-View +Matching +Dmytro Mishkin, Jiri Matas, Michal Perdoch +Center for Machine Perception, Faculty of Electrical Engineering, +Czech Technical University in Prague. Karlovo namesti, 13. Prague 2, 12135"
+4d9d25e67ebabbfc0acd63798f1a260cb2c8a9bd,Playing for Data: Ground Truth from Computer Games,"Playing for Data: Ground Truth from Computer Games +Stephan R. Richter∗1 Vibhav Vineet∗2 +Stefan Roth1 Vladlen Koltun2 +TU Darmstadt +Intel Labs"
+4d3a6c2cee0cf06ff6471fad3d65a5835d0552f8,3-D Face Recognition Using Geodesic-Map Representation and Statistical Shape Modelling,"Article +D Face Recognition Using GeodesicMap +Representation and Statistical Shape Modelling +Quan, Wei, Matuszewski, Bogdan and Shark, Lik +Available at http://clok.uclan.ac.uk/13240/ +Quan, Wei, Matuszewski, Bogdan and Shark, Lik (2016) 3D Face Recognition Using Geodesic +Map Representation and Statistical Shape Modelling. Lecture Notes in Computer Science, 9493 . +pp. 199212. ISSN 03029743 +It is advisable to refer to the publisher’s version if you intend to cite from the work. +http://dx.doi.org/10.1007/978-3-319-27677-9_13 +For more information about UCLan’s research in this area go to +http://www.uclan.ac.uk/researchgroups/ and search for <name of research Group>. +For information about Research generally at UCLan please go to +http://www.uclan.ac.uk/research/ +All outputs in CLoK are protected by Intellectual Property Rights law, including +Copyright law. Copyright, IPR and Moral Rights for the works on this site are retained +y the individual authors and/or other copyright owners. Terms and conditions for use +of this material are defined in the http://clok.uclan.ac.uk/policies/ +Central Lancashire online Knowledge +www.clok.uclan.ac.uk"
4df3143922bcdf7db78eb91e6b5359d6ada004d2,The Chicago face database: A free stimulus set of faces and norming data.,"Behav Res (2015) 47:1122–1135 DOI 10.3758/s13428-014-0532-5 The Chicago face database: A free stimulus set of faces @@ -8227,12 +28300,95 @@ nd norming data Debbie S. Ma & Joshua Correll & Bernd Wittenbrink Published online: 13 January 2015 # Psychonomic Society, Inc. 2015"
+75827a2021ac2ad2256144b2a2fe301948d39b51,AI Benchmark: Running Deep Neural Networks on Android Smartphones,"AI Benchmark: Running Deep Neural Networks +on Android Smartphones +Andrey Ignatov +ETH Zurich +Radu Timofte +ETH Zurich +William Chou +Qualcomm, Inc. +Ke Wang +Huawei, Inc. +Max Wu +MediaTek, Inc. +Tim Hartley +Arm, Inc. +Luc Van Gool ∗ +ETH Zurich"
+75cb21fa931e957941c0237a1030aa36209bae36,Gaussian Process for Activity Modeling and Anomaly Detection,"GAUSSIAN PROCESS FOR ACTIVITY MODELING AND ANOMALY DETECTION +Wentong Liaoa, Bodo Rosenhahna, Michael Ying Yangb +Institute for Information Processing, Leibniz University Hannover, Germany +Computer Vision Lab, TU Dresden, Germany +KEY WORDS: Gaussian Process regression, activity modeling, anomaly detection +Commission WG III/3"
75879ab7a77318bbe506cb9df309d99205862f6c,Analysis of emotion recognition from facial expressions using spatial and transform domain methods,"Analysis Of Emotion Recognition From Facial Expressions Using Spatial And Transform Domain Methods Ms. P. Suja* and Dr. Shikha Tripathi"
+75d571d53eb250e222d66461fa2400956b40eaa9,What Makes a Photograph Memorable?,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +What makes a photograph memorable? +Phillip Isola, Jianxiong Xiao, Member, IEEE, Devi Parikh, Member, IEEE, Antonio Torralba, Member, IEEE, +nd Aude Oliva"
+75d59ae0ed3ce51e37b383985cfff310251f591a,Cost-Sensitive Robustness against Adversarial Examples,"Cost-Sensitive Robustness against Adversarial Examples +Xiao Zhang∗ +nd David Evans†"
+75a9d9ea6c1a5ee55fc0ccb347b263785b15ac0a,An Image Search Reranking Model based on attribute assisted hypergraph Miss,"International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 +Volume: 03 Issue: 05 | May-2016 www.irjet.net p-ISSN: 2395-0072 +An Image Search Reranking Model based on +ttribute assisted hypergraph +Miss. Madhuri J.Mhaske1, Prof. Sachin P.Patil2 +PG Scholar Computer Engineering , G. H. Raisoni College of Engineering and Management, +Savitribai Phule Pune University , Chas, Ahmednagar.414001,Maharashtra, India. +Assistant professor, computer engineering, G.H. Raisoni College of engineering and Management, +Savitribai Phule Pune University, Wagholi, Pune 411015, Maharashtra, India. +---------------------------------------------------------------------***--------------------------------------------------------------------- +user wants to search for a red image, the images cannot be"
+758572c5779a47e898caff7232af76eda253163b,Csr: Medium: Collaborative Research: Architecture and System Support for Power-agile Computing,"CSR: MEDIUM: COLLABORATIVE RESEARCH: ARCHITECTURE AND +SYSTEM SUPPORT FOR POWER-AGILE COMPUTING +Co-PI: Geoffrey Challen (University at Buffalo), Co-PI: Mark Hempstead (Drexel University) +NSF PROPOSAL +5 OCT 2013 +As energy management on energy-constrained devices continues to challenge researchers and frustrate +users, device designs are addressing the problem by integrating more hardware components that can trade +off energy and performance. Dynamic voltage-and-frequency scaling (DVFS) allows CPUs and memory +to trade off speed and energy, buffering and polling rates allow radios to trade off latency and energy, +nd screen refresh rates allow displays to trade off quality and energy. And as the Dark Silicon utilization +wall forces systems to choose what parts of the CPU to operate, the already-large configuration space will +explode. This proposal refers to the emerging class of devices integrating multiple energy-proportional +omponents as power-agile, reflecting their potential ability to adaptively reallocate energy usage between +omponents to improve performance and save energy. But as energy-management features proliferate, +new interfaces enabling coordination between applications, the operating system (OS), and hardware are +urgently needed to realize the potential energy and performance benefits. +INTELLECTUAL MERIT: Our proposal describes a new architecture for power-agile systems with both +novel interfaces that cleanly separate energy management responsibilities and a new approach to energy +llocation driven by differences in hardware energy efficiency. Applications use resource requests to allo- +ate energy between hardware components, making their resource needs explicit. The OS manages energy"
+75a92d92ee59555c847973a7422d7356514cde2d,Exploiting Multiple Detections for Person Re-Identification,"Article +Exploiting Multiple Detections for +Person Re-Identification +Amran Bhuiyan *, Alessandro Perina and Vittorio Murino +Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Morego 30, +6163 Genova, Italy; (A.P.); (V.M.) +* Correspondence: Tel.: +39-331-803-7176 +Received: 18 November 2017; Accepted: 11 January 2018; Published: 23 January 2018"
+7557e81c1189f0ef9643519e0664d60baed51721,Robust and Efficient Graph Correspondence Transfer for Person Re-identification,"DRAFT +Transfer for Person Re-identification +Qin Zhou, Heng Fan, Hua Yang, Member, IEEE, Hang Su, Member, IEEE, Shibao Zheng, Member, IEEE, +Shuang Wu, and Haibin Ling, Member, IEEE"
+751e11880b54536a89bfcc4fd904b0989345a601,Hierarchical Adversarially Learned Inference,"HIERARCHICAL ADVERSARIALLY LEARNED +INFERENCE +Mohamed Ishmael Belghazi1, Sai Rajeswar1, Olivier Mastropietro1, +Negar Rostamzadeh2, Jovana Mitrovic2 and Aaron Courville1† +MILA, Université de Montréal, +Element AI, +DeepMind, +CIFAR Fellow."
75503aff70a61ff4810e85838a214be484a674ba,Improved facial expression recognition via uni-hyperplane classification,"Improved Facial Expression Recognition via Uni-Hyperplane Classification S.W. Chew∗, S. Lucey†, P. Lucey‡, S. Sridharan∗, and J.F. Cohn‡"
+754fa133a250d824c50b4c3b9c73975059954f41,Siamese Learning Visual Tracking: A Survey,"Siamese Learning Visual Tracking: A Survey +Roman Pflugfelder, Member, IEEE +(Draft Article)"
75308067ddd3c53721430d7984295838c81d4106,Rapid Facial Reactions in Response to Facial Expressions of Emotion Displayed by Real Versus Virtual Faces,"Article Rapid Facial Reactions in Response to Facial @@ -8246,12 +28402,71 @@ DOI: 10.1177/2041669518786527 journals.sagepub.com/home/ipe Leonor Philip, Jean-Claude Martin and Ce´ line Clavel LIMSI, CNRS, University of Paris-Sud, Orsay, France"
+750e567370fd8c37bab657207195517405727a71,Time Aware Task Delegation in Agent Interactions for Video-Surveillance,"Time aware task delegation in agent interactions +for video-surveillance +Paolo Sernani1, Matteo Biagiola2,3, Nicola Falcionelli1, +Dagmawi Neway Mekuria1, Stefano Cremonini4, Aldo Franco Dragoni1 +Dipartimento di Ingegneria dell’Informazione, +Universit`a Politecnica delle Marche, +Ancona, Italy +{p.sernani, +{n.falcionelli, +Fondazione Bruno Kessler, +Trento, Italy +Universit`a degli Studi di Genova, +Genova, Italy +Site Spa, Bologna, Italy"
+75d8f2da0e9d80eef141c765254d7752445afb53,Violent video detection based on MoSIFT feature and sparse coding,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) +978-1-4799-2893-4/14/$31.00 ©2014 IEEE +Long Xu1, Chen Gong1, Jie Yang1(cid:3), Qiang Wu2, Lixiu Yao1 +. INTRODUCTION"
+75e4efae6de6d1ac787a6ca381fb49381fcb062b,Hierarchical Representation Learning for Kinship Verification,"IEEE TRANSACTIONS ON IMAGE PROCESSING +Hierarchical Representation Learning for Kinship +Verification +Naman Kohli, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE, Richa Singh, Senior Member, IEEE, +Afzel Noore, Senior Member, IEEE, and Angshul Majumdar, Senior Member, IEEE"
+75d5e67e31cefa09ae46044fa1f9f7696e058c99,MRI based Techniques for Detection of Alzheimer: A Survey,"MRI based Techniques for Detection of Alzheimer: A Survey +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 159 +Number 5 +Year of Publication: 2017 +Authors: +Ruaa Adeeb Abdulmunem Al-falluji +10.5120/ijca2017912929 +{bibtex}2017912929.bib{/bibtex}"
759a3b3821d9f0e08e0b0a62c8b693230afc3f8d,Attribute and simile classifiers for face verification,"Attribute and Simile Classifiers for Face Verification Neeraj Kumar Alexander C. Berg Peter N. Belhumeur Columbia University∗ Shree K. Nayar"
+75e9401e70c05c4d080e2d17f83ed2b61b44b3af,A distributed algorithm for partitioned robust submodular maximization,"A Distributed Algorithm for Partitioned +Robust Submodular Maximization +Ilija Bogunovic, Slobodan Mitrovi´c, Jonathan Scarlett, and Volkan Cevher +École Polytechnique Fédérale de Lausanne (EPFL) +{ilija.bogunovic, slobodan.mitrovic, jonathan.scarlett,"
+7538ad235caf4dbc64a8b94a6146e1212d4de1ff,Amygdala dysfunction in men with the fragile X premutation.,"doi:10.1093/brain/awl338 +Brain (2007), 130, 404–416 +Amygdala dysfunction in men with the fragile +X premutation +David Hessl,1,2 Susan Rivera,1,5 Kami Koldewyn,1,6 Lisa Cordeiro,1 John Adams,1 Flora Tassone,1,4 +Paul J. Hagerman1,4 and Randi J. Hagerman1,3 +Medical Investigation of Neurodevelopmental Disorders (MIND) Institute and Departments of 2Psychiatry and Behavioral +Sciences, 3Pediatrics, University of California-Davis, Medical Center, Sacramento, 4Department of Biochemistry and +Molecular Medicine, University of California-Davis, School of Medicine, 5Department of Psychology and 6Center for +Neuroscience, University of California-Davis, Davis, CA, USA +Correspondence to: David Hessl, PhD, Assistant Clinical Professor, MIND Institute, University of California, Davis Medical +Center, 2825 50th Street, Sacramento, CA 95817, USA. +E-mail: +Premutation alleles (55–200 CGG repeats) of the fragile X mental retardation 1 (FMR1) gene are associated +with autism spectrum disorder in childhood, premature ovarian failure, and the neurodegenerative disorder, +fragile X-associated tremor/ataxia syndrome (FXTAS). FXTAS, and perhaps the other clinical presentations +mong carriers, are thought to be due to toxic gain-of-function of elevated levels of the expanded-repeat +FMR1 mRNA. Previous structural MRI studies have implicated the amygdala as a potential site of dysfunction +underlying social deficits and/or risk for FXTAS. As a preliminary investigation of this possible association, adult +males with the premutation, and male controls matched for IQ, age and education, completed three protocols"
75859ac30f5444f0d9acfeff618444ae280d661d,Multibiometric Cryptosystems Based on Feature-Level Fusion,"Multibiometric Cryptosystems based on Feature Level Fusion Abhishek Nagar, Student Member, IEEE, Karthik Nandakumar, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
@@ -8260,6 +28475,16 @@ AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild Ali Mollahosseini, Student Member, IEEE, Behzad Hasani, Student Member, IEEE, nd Mohammad H. Mahoor, Senior Member, IEEE"
+75522dfc1610c8765185c4344d97db33e1af5047,"RASKIN, RUDZSKY, RIVLIN: BODY-PART TRACKING AND ACTION CLASSIFICATION 1 3D Human Body-Part Tracking and Action Classification Using a Hierarchical Body Model","RASKIN, RUDZSKY, RIVLIN: BODY-PART TRACKING AND ACTION CLASSIFICATION +D Human Body-Part Tracking and Action +Classification Using a Hierarchical Body +Model +Leonid Raskin +Michael Rudzsky +Ehud Rivlin +Computer Science Department +Technion -Israel Institute of Technology +Haifa, Israel, 3200"
7553fba5c7f73098524fbb58ca534a65f08e91e7,A Practical Approach for Determination of Human Gender & Age,"Harpreet Kaur Bhatia et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.6, June- 2014, pg. 816-824 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing @@ -8272,10 +28497,45 @@ of Human Gender & Age Harpreet Kaur Bhatia1, Ahsan Hussain2 CSE Dept. & CSVTU University, India CSE Dept. & CSVTU University, India"
+75cf72819b8741777a961157f43d994238219f5e,Crowd Behavior Detection for Abnormal Conditions,"International Journal of Computer Systems (ISSN: 2394-1065), Volume 03– Issue 06, June, 2016 +Available at http://www.ijcsonline.com/ +Crowd Behavior Detection for Abnormal Conditions +Aniket A. Patil, Prof. S. A. Shinde +Department of Computer Engineering, +Savitribai Phule Pune University, Pune, India"
+75b987f86af2bc7f68edc45be240dd30e1ef2699,Sampling Algorithms to Handle Nuisances in Large-Scale Recognition,"UNIVERSITY OF CALIFORNIA +Los Angeles +Sampling Algorithms to Handle Nuisances in Large-Scale Recognition +A dissertation submitted in partial satisfaction +of the requirements for the degree +Doctor of Philosophy in Computer Science +Nikolaos Karianakis"
+75073faadb967823db48794e9cd54b681bb0729b,Thermal-Aware Task Allocation and Scheduling for Heterogeneous Multi-core Cyber-Physical Systems,"Thermal-Aware Task Allocation and Scheduling for +Heterogeneous Multi-core Cyber-Physical Systems +Department of Electrical and Computer Engineering University of Massachusetts Amherst, Amherst, MA, 01003 +Shikang Xu, Israel Koren and C. M. Krishna"
+75c3ba0c7e5b0d4a11e9d2e073ccd02ee688c0c9,"A Multimodal LDA Model integrating Textual, Cognitive and Visual Modalities","Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pages 1146–1157, +Seattle, Washington, USA, 18-21 October 2013. c(cid:13)2013 Association for Computational Linguistics"
+75650bfc20036d99314f7ddae8f2baecde3d57e2,Concave Losses for Robust Dictionary Learning,"CONCAVE LOSSES FOR ROBUST DICTIONARY LEARNING +Rafael Will M. de Araujo, R. Hirata Jr ∗ +Alain Rakotomamonjy † +University of S˜ao Paulo +Institute of Mathematics and Statistics +Rua do Mat˜ao, 1010 – 05508-090 – S˜ao Paulo-SP, Brazil +Universit´e de Rouen Normandie +LITIS EA 4108 +76800 Saint- ´Etienne-du-Rouvray, France"
75249ebb85b74e8932496272f38af274fbcfd696,Face Identification in Large Galleries,"Face Identification in Large Galleries Rafael H. Vareto, Filipe Costa, William Robson Schwartz Smart Surveillance Interest Group, Department of Computer Science Universidade Federal de Minas Gerais, Belo Horizonte, Brazil"
+816c8c8d0f02200f988625d4989a1b4b34d779c6,An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets,
+81eb804756f27d08f2d193d1074e58e1c5d263ca,Monocular 3D Human Pose Estimation Using Transfer Learning and Improved CNN Supervision,"Monocular 3D Human Pose Estimation Using Transfer Learning and Improved +CNN Supervision +Dushyant Mehta*, Helge Rhodin*, Dan Casass, Oleksandr Sotnychenko*, Weipeng Xu*, and Christian +Theobalt* +*Max Planck Institute For Informatics, Saarland Informatics Campus, Germany +sUniversidad Rey Juan Carlos, Spain"
81a142c751bf0b23315fb6717bc467aa4fdfbc92,Pairwise Trajectory Representation for Action Recognition,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE ICASSP 2017"
81bfe562e42f2eab3ae117c46c2e07b3d142dade,A Hajj And Umrah Location Classification System For Video Crowded Scenes,"A Hajj And Umrah Location Classification System For Video @@ -8307,6 +28567,53 @@ Caltech Google Cornell Tech iNaturalist"
+816617fa6801fb2abd3d4475c459bf6e3221954d,3D human detection and tracking on a mobile platform for situation awareness,"D Human Detection and +Tracking on a Mobile Platform +for Situation Awareness +Niklas Beuter"
+81e628a23e434762b1208045919af48dceb6c4d2,Attend and Rectify: A Gated Attention Mechanism for Fine-Grained Recovery,"Attend and Rectify: a Gated Attention +Mechanism for Fine-Grained Recovery +Pau Rodr´ıguez†, Josep M. Gonfaus‡, Guillem Cucurull†, +F. Xavier Roca†, Jordi Gonz`alez† +Computer Vision Center and Universitat Aut`onoma de Barcelona (UAB), +Campus UAB, 08193 Bellaterra, Catalonia Spain +Visual Tagging Services, Parc de Recerca, Campus UAB"
+811dff89b6d4657e5a0b8534e208baefd2204cee,Pseudo-Feature Generation for Imbalanced Data Analysis in Deep Learning,"Pseudo-Feature Generation for Imbalanced Data +Analysis in Deep Learning +Tomohiko Konno∗ and Michiaki Iwazume +AI Science Research and Development Promotion Center +National Institute of Information and Communications Technology, Tokyo Japan +Figure 1: The sketch of proposed method. Left: train deep neural networks. Center: extract features +from a layer, and then obtain multivariate probability distributions of the features, and then generate +pseudo-features of minority classes from the probability distributions, and then re-train the layers +elow the layer. Right: Put the retrained layers back to the original one. (It is the last classifier that is +re-trained and put back in the experiment.)"
+812725dc3968aaff6429ec7c3f44ba1ca2116013,Acoplamiento de micro multitudes para el desarrollo de videojuegos controlados por movimiento,"Acoplamiento de micro multitudes +para el desarrollo de videojuegos +ontrolados por movimiento +Iv´an Rivalcoba1, Krely Rodr´ıguez2, Oriam Degives1, Isaac Rudom´ın3 +Tecnol´ogico de Monterrey, Campus Estado de M´exico, +M´exico +Tecnol´ogico de Minatitl´an, +Minatitl´an, Veracruz, M´exico +Barcelona Supercomputing Center +Barcelona, Espa˜na +Resumen. La simulaci´on de multitudes en tiempo real y los juegos controlados +por movimiento se han vuelto muy populares en los ´ultimos a˜nos. En conjunto +estas dos tecnolog´ıas proporcionan una mejor experiencia de juego en entornos +virtuales logrando escenas m´as realistas y vibrantes. Sin embargo, hasta ahora no +se ha explotado la interacci´on de m´ultiples jugadores con una gran multitud bajo +un entorno virtual. En este trabajo presentamos un sistema no intrusivo capaz +de simular multitudes virtuales acopladas en tiempo real con varios usuarios, +sentando con ello las bases para la creaci´on de juegos donde interact´uen muchos +jugadores con muchas personajes, para ello se realiza una detecci´on de personas +en una secuencia de v´ıdeo, nuestra contribuci´on consiste en utilizar patrones"
+812a6ced985317b3b9429ef0455645a9744af6d1,No need for a social cue! A masked magician can also trick the audience in the vanishing ball illusion.,"Atten Percept Psychophys +DOI 10.3758/s13414-015-1036-9 +No need for a social cue! A masked magician can also trick +the audience in the vanishing ball illusion +Cyril Thomas 1 & André Didierjean 1 +# The Psychonomic Society, Inc. 2015"
81706277ed180a92d2eeb94ac0560f7dc591ee13,Emotion based Contextual Semantic Relevance Feedback in Multimedia Information Retrieval,"International Journal of Computer Applications (0975 – 8887) Volume 55– No.15, October 2012 Emotion based Contextual Semantic Relevance @@ -8321,6 +28628,37 @@ Institute of Technology, Banaras Hindu University,Varanasi, 221005, India find some issued by a user"
+81c03eda1d175fbe351980ac4cffe42c5dec47b0,User observation & dataset collection for robot training,"User Observation & Dataset Collection for Robot Training +Caroline Pantofaru +Willow Garage, Inc. +Menlo Park, CA 94025 +Categories and Subject Descriptors: +I.5.2 [Comput- +ing Methodologies]: Pattern Recognition - Design Method- +ology, H.1.2 [Information Systems]: Models and Principles - +User/Machine Systems +General Terms: Measurement +INTRODUCTION +Personal robots operate in human environments such as +homes and offices, co-habiting with people. To effectively +train robot algorithms for such scenarios, a large amount of +training data containing both people and the environment is +required. Collecting such data involves taking a robot into +new environments, observing and interacting with people. +So far, best practices for robot data collection have been +undefined. Fortunately, the human-robot interaction com- +munity has conducted field studies whose methodology can"
+81a51cd6ecd467abb1ef38c8e35bdf1885f96fe3,Deep Spatio-Temporal Random Fields for Efficient Video Segmentation,"Deep Spatio-Temporal Random Fields for Efficient Video Segmentation +Siddhartha Chandra1 +Camille Couprie2 +INRIA GALEN, Ecole CentraleSup´elec Paris +Iasonas Kokkinos2 +Facebook AI Research, Paris"
+81f30bc57b84a6e5b71983b50bdea32f32bee285,"The more fine-grained, the better for transfer learning","The more fine-grained, the better for transfer learning +Anonymous Author(s) +Affiliation +Address +email"
81b2a541d6c42679e946a5281b4b9dc603bc171c,Semi-supervised learning with committees: exploiting unlabeled data using ensemble learning algorithms,"Universit¨at Ulm | 89069 Ulm | Deutschland Fakult¨at f¨ur Ingenieurwissenschaften und Informatik Institut f¨ur Neuroinformatik @@ -8336,10 +28674,57 @@ vorgelegt von Mohamed Farouk Abdel Hady us Kairo, ¨Agypten Ulm, Deutschland"
+81ff6d7f934f7134d93b2039d788b72f8593693c,Accelerating Convolutional Neural Network Systems,"Accelerating Convolutional +Neural Network Systems +Henry G.R. Gouk +This report is submitted in partial fulfillment of the requirements for the degree of +Bachelor of Computing and Mathematical Sciences with Honours (BCMS(Hons)) +t The University of Waikato. +COMP520-14C (HAM) +© 2014 Henry G.R. Gouk"
+813e9f76fb9e3f007f0bc819eab66b0b5fbd8204,Towards Building Large Scale Multimodal Domain-Aware Conversation Systems,"Towards Building Large Scale Multimodal Domain-Aware Conversation Systems +Amrita Saha1,2 +Mitesh M. Khapra2 +Karthik Sankaranarayanan1 +IBM Research AI +I.I.T. Madras, India"
+81eecb00eeadb5fe36cd840b687439bfdca7ff30,Kernelized Saliency-Based Person Re-Identification Through Multiple Metric Learning,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012 +Kernelized Saliency-based Person Re-Identification +through Multiple Metric Learning +Niki Martinel* Student Member, IEEE, Christian Micheloni, Member, IEEE, and Gian Luca Foresti, Senior +Member, IEEE"
+81d327ec41c67728b15438bca86d10b72de1d88f,Visual Affordance and Function Understanding: A Survey,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JULY 2018 +Visual Affordance and Function Understanding: +A Survey +Mohammed Hassanin, Salman Khan, Murat Tahtali"
+81d5c4b49fe17aaa3af837745cafdedb066a067d,Automatic Adaptive Center of Pupil Detection Using Face Detection and CDF Analysis,"Automatic Adaptive Center of Pupil Detection +Using Face Detection and CDF Analysis +Mansour Asadifard, Jamshid Shanbezadeh"
+819a321975c736e006870e76446d581e195cad2e,Deep Canonical Time Warping for Simultaneous Alignment and Representation Learning of Sequences,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Deep Canonical Time Warping +for simultaneous alignment and representation +learning of sequences +George Trigeorgis, Mihalis A. Nicolaou, Member, IEEE, Bj¨orn W. Schuller, Senior member, IEEE +Stefanos Zafeiriou, Member, IEEE"
+81006fe4c4947d225b9fa17e6b98b8acb36a7692,A Dataset for Grasping and Manipulation using ROS,"A Dataset for Grasping and Manipulation using ROS +Matei Ciocarlie†, Gary Bradski†, Kaijen Hsiao† and Peter Brook†∗"
+810eafc9e854ea9b1d7a9e9f755f8102310d5db6,Dynamic Multimodal Instance Segmentation Guided by Natural Language Queries,"Dynamic Multimodal Instance Segmentation +Guided by Natural Language Queries +Edgar Margffoy-Tuay, Juan C. P´erez, Emilio Botero, and Pablo Arbel´aez +{ea.margffoy10, jc.perez13, e.botero10, +Universidad de los Andes, Colombia"
+816c1925de9e8557fa70ec67d0ff71a5059eb931,Person Re-identification by Articulated Appearance Matching,"Person Re-identification by Articulated +Appearance Matching +Dong Seon Cheng and Marco Cristani"
8160b3b5f07deaa104769a2abb7017e9c031f1c1,Exploiting discriminant information in nonnegative matrix factorization with application to frontal face verification,"Exploiting Discriminant Information in Nonnegative Matrix Factorization With Application to Frontal Face Verification Stefanos Zafeiriou, Anastasios Tefas, Member, IEEE, Ioan Buciu, and Ioannis Pitas, Senior Member, IEEE"
+81fc46dd71121cfafbb11455745ae62f6eca0b25,Joint Camera Pose Estimation and 3D Human Pose Estimation in a Multi-camera Setup,"Joint Camera Pose Estimation and 3D Human +Pose Estimation in a Multi-Camera Setup +Jens Puwein1, Luca Ballan1, Remo Ziegler2 and Marc Pollefeys1 +Department of Computer Science, ETH Zurich, Switzerland +Vizrt"
814d091c973ff6033a83d4e44ab3b6a88cc1cb66,The EU-Emotion Stimulus Set: A validation study.,"Behav Res (2016) 48:567–576 DOI 10.3758/s13428-015-0601-4 The EU-Emotion Stimulus Set: A validation study @@ -8367,6 +28752,27 @@ LRR algorithm. Introduction: Given a data set X ∈ Rm×n(m < n) composed of column vectors, let A be a data set composed of vectors with the same dimension s those in X. Both X and A can be considered as matrices. A linear"
+81ed28ea6cfe71bfc4cfc35c6695fa07dd7cc42e,"Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution","Deep Episodic Memory: Encoding, Recalling, and Predicting +Episodic Experiences for Robot Action Execution +Jonas Rothfuss∗†, Fabio Ferreira∗†, Eren Erdal Aksoy ‡, You Zhou† and Tamim Asfour†"
+81ede08b36f3abd423424804da8ff240606b3a5d,Top-Down Deep Appearance Attention for Action Recognition,"Top-Down Deep Appearance Attention for +Action Recognition +Rao Muhammad Anwer1, Fahad Shahbaz Khan2, Joost van de Weijer3, Jorma +Laaksonen1 +Department of Computer Science, Aalto University School of Science, Finland +Computer Vision Laboratory, Link¨oping University, Sweden +Computer Vision Center, CS Dept. Universitat Autonoma de Barcelona, Spain"
+810d60ff5c0106de53a48fa2731eacf5ca2377b6,MultiQ: single sensor-based multi-quality multi-modal large-scale biometric score database and its performance evaluation,"Uddin et al. IPSJ Transactions on Computer Vision and +Applications (2017) 9:18 +DOI 10.1186/s41074-017-0029-0 +IPSJ Transactions on Computer +Vision and Applications +TECHNICAL NOTE +Open Access +MultiQ: single sensor-based multi-quality +multi-modal large-scale biometric score +database and its performance evaluation +Md. Zasim Uddin*, Daigo Muramatsu, Takuhiro Kimura, Yasushi Makihara and Yasushi Yagi"
8149c30a86e1a7db4b11965fe209fe0b75446a8c,Semi-supervised multiple instance learning based domain adaptation for object detection,"Semi-Supervised Multiple Instance Learning based Domain Adaptation for Object Detection Siemens Corporate Research @@ -8380,6 +28786,91 @@ Bangalore Rahul Thota Bangalore rahul.thota,"
+815069f591122aa7b388615f944c17c7fa1eff14,Constrained Overcomplete Analysis Operator Learning for Cosparse Signal Modelling,"Constrained Overcomplete Analysis Operator +Learning for Cosparse Signal Modelling +Mehrdad Yaghoobi, Sangnam Nam, R´emi Gribonval and Mike E. Davies"
+81b6de17391f44c07b2efe75a529aa200604ee48,Machine à Vecteurs Supports Multi-Noyau pour la détection de points caractéristiques du visage,"Machine à Vecteurs Supports Multi-Noyau pour la détection de points +aractéristiques du visage +Vincent Rapp1, Thibaud Senechal1, Kevin Bailly1, Lionel Prevost2 +ISIR - CNRS UMR 7222 +Université Pierre et Marie Curie, Paris +LAMIA - EA 4540 +Université des Antilles et de la Guyanne +{rapp, senechal, +Résumé +Dans cet article, nous présentons une méthode robuste +et précise pour détecter 17 points caractéristiques du vi- +sage sur des images expressives. Une nouvelle architecture +multi-résolution basée sur les récents algorithmes multi- +noyau est introduite. Les patches de faibles résolutions +odent les informations globales du visage donnant lieu à +une détection grossière mais robuste du point désiré. Les +patches de grandes résolutions quant à eux utilisent les dé- +tails locaux afin d’affiner cette localisation. En combinant +une détection indépendante de points et des informations +priori sur les distributions de points, nous proposons"
+819d1dcea397e6e671acf74adccdef5750550873,Representations for Visually Guided Actions,"Representations for Visually Guided Actions +Saurabh Gupta +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2018-104 +http://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-104.html +August 8, 2018"
+8121824f4598d600e4cdb745cd2715e4655c9e88,A Taxonomy of Emerging Multilinear Discriminant Analysis Solutions for Biometric Signal Recognition,"Contents +A Taxonomy of Emerging Multilinear Discriminant Analysis Solutions +for Biometric Signal Recognition +Haiping Lu, K. N. Plataniotis and A. N. Venetsanopoulos +Introduction +.2 Multilinear basics +.3 Multilinear discriminant analysis +.5 Conclusions +Empirical Comparison of MLDA variants on Face Recognition +Appendix: Multilinear decompositions +References"
+81c3d1be0c69e9d3e13054969e4b67ee69a4e6f0,Dynamical Models for Neonatal Intensive Care Monitoring,"This thesis has been submitted in fulfilment of the requirements for a postgraduate degree +(e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following +terms and conditions of use: +This work is protected by copyright and other intellectual property rights, which are +retained by the thesis author, unless otherwise stated. +A copy can be downloaded for personal non-commercial research or study, without +prior permission or charge. +This thesis cannot be reproduced or quoted extensively from without first obtaining +permission in writing from the author. +The content must not be changed in any way or sold commercially in any format or +medium without the formal permission of the author. +When referring to this work, full bibliographic details including the author, title, +warding institution and date of the thesis must be given."
+81eb9fca9093f58eabb8850512f8f46fe2bb07a2,Sem-GAN: Semantically-Consistent Image-to-Image Translation,"Sem-GAN: Semantically-Consistent Image-to-Image Translation +Anoop Cherian +Alan Sullivan +Mitsubishi Electric Research Labs (MERL), Cambridge, MA +{cherian,"
+818dcb3bac6342c02eebd896cd0a46bcf2192b64,Unified Structured Learning for Simultaneous Human Pose Estimation and Garment Attribute Classification,"Unified Structured Learning for Simultaneous +Human Pose Estimation and Garment Attribute +Classification +Jie Shen, Guangcan Liu, Member, IEEE, Jia Chen, Yuqiang Fang, Jianbin Xie, Member, IEEE, Yong Yu, +nd Shuicheng Yan, Senior Member, IEEE"
+8134b052a9aedd573dd16649a611f68b48e30cb2,InverseFaceNet: Deep Single-Shot Inverse Face Rendering From A Single Image,"InverseFaceNet: Deep Single-Shot Inverse Face Rendering From A Single Image +Hyeongwoo Kim1 +Justus Thies2 +Max-Planck-Institute for Informatics +Michael Zollhöfer1 +Christian Richardt3 +University of Erlangen-Nuremberg 3 University of Bath +Christian Theobalt1 +Ayush Tewari1 +Figure 1. Our single-shot deep inverse face renderer InverseFaceNet obtains a high-quality geometry, reflectance and illumination estimate +from just a single input image. We jointly recover the face pose, shape, expression, reflectance and incident scene illumination. From left to +right: input photo, our estimated face model, its geometry, and the pointwise Euclidean error compared to Garrido et al. [14]."
+862f19f8317971fabc46cf0f994f4a8616f17b78,Human Re-identification through Distance Metric Learning based on Jensen-Shannon Kernel,"HUMAN RE-IDENTIFICATION THROUGH DISTANCE METRIC +LEARNING BASED ON JENSEN-SHANNON KERNEL +Yoshihisa Ijiri1, Shihong Lao2, Tony X. Han3 and Hiroshi Murase4 +Corporate R&D, OMRON Corp., Kizugawa, Kyoto, Japan +OMRON Social Solutions Co. Ltd., Kizugawa, Kyoto, Japan +Electrical & Computer Engineering Dept., Univ. of Missouri, Columbia, MO, U.S.A. +Graduate School of Information Science, Nagoya Univ., Chigusaku, Nagoya, Japan +Keywords: +Human Re-identification, Distance Metric Learning, Jensen-Shannon Kernel."
86614c2d2f6ebcb9c600d4aef85fd6bf6eab6663,Benchmarks for Cloud Robotics,"Benchmarks for Cloud Robotics Arjun Singh Electrical Engineering and Computer Sciences @@ -8393,6 +28884,13 @@ National Library of Medicine, NIH, Bethesda, MD" 86904aee566716d9bef508aa9f0255dc18be3960,Learning Anonymized Representations with Adversarial Neural Networks,"Learning Anonymized Representations with Adversarial Neural Networks Cl´ement Feutry, Pablo Piantanida, Yoshua Bengio, and Pierre Duhamel"
+8602b2ef26a0f851f1f6f2f2ae0ce142eb64300a,Is it a face ? How to find and validate a face on 3D scans,"Is it a face ? How to find and validate a face on 3D scans +Przemyslaw Szeptycki, +Mohsen Ardabilian, +Liming Chen +Ecole Centrale de Lyon, 36 av. Guy de Collongue, 69134 Lyon, France +{przemyslaw.szeptycki, mohsen.ardabilian, +Introduction"
867e709a298024a3c9777145e037e239385c0129,Analytical Representation of Undersampled Face Recognition Approach Based on Dictionary Learning and Sparse Representation,"INTERNATIONAL JOURNAL OF PROFESSIONAL ENGINEERING STUDIES Volume VIII /Issue 2 / FEB 2017 ANALYTICAL REPRESENTATION OF UNDERSAMPLED FACE @@ -8406,6 +28904,54 @@ Devi Parikh1, Adriana Kovashka3, Amar Parkash2, and Kristen Grauman3 Toyota Technological Institute, Chicago Indraprastha Institute of Information Technology, Delhi University of Texas, Austin"
+86b1751b265b289b09de79956e77a01d82e12086,Face recognition in multi-camera surveillance videos,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-1-6 ©2012 IAPR"
+8645fe95f3f503f854b08096c2874a3f7ea6b79b,BoxCars: 3D Boxes as CNN Input for Improved Fine-Grained Vehicle Recognition,"BoxCars: 3D Boxes as CNN Input +for Improved Fine-Grained Vehicle Recognition +Jakub Sochor∗, Adam Herout, Jiˇr´ı Havel +Brno University of Technology +Brno, Czech Republic"
+86e5f81bde496549e9df2b1abdef0879a3135adb,The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR,"The Visual QA Devil in the Details: The Impact +of Early Fusion and Batch Norm on CLEVR +Mateusz Malinowski and Carl Doersch +DeepMind, London, United Kingdom +Introduction +Visual QA is a pivotal challenge for higher-level reasoning [1,2,3,4], requiring +understanding language, vision, and relationships between many objects in a +scene. Although datasets like CLEVR [5] are designed to be unsolvable with- +out such complex relational reasoning, some surprisingly simple feed-forward, +“holistic” models have recently shown strong performance on this dataset [6,7]. +These models lack any kind of explicit iterative, symbolic reasoning procedure, +which are hypothesized to be necessary for counting objects, narrowing down +the set of relevant objects based on several attributes, etc. The reason for this +strong performance is poorly understood. Hence, our work analyzes such mod- +els, and finds that minor architectural elements are crucial to performance. In +particular, we find that early fusion of language and vision provides large per- +formance improvements. This contrasts with the late fusion approaches popular +t the dawn of Visual QA [5,8,9,10]. We propose a simple module we call Mul- +timodal Core (MC), which we hypothesize performs the fundamental operations +for multimodal tasks. We believe that understanding why these elements are so"
+86cdc6ae46f53ac86b9e0ace2763c5fe15633055,Experimental Force-Torque Dataset for Robot Learning of Multi-Shape Insertion,"Experimental Force-Torque Dataset for Robot Learning of Multi-Shape Insertion +Giovanni De Magistris1, Asim Munawar1, Tu-Hoa Pham1, Tadanobu Inoue1, +Phongtharin Vinayavekhin1, Ryuki Tachibana1 +IBM Research - Tokyo, Japan +The accurate modeling of real-world systems and +physical interactions is a common challenge towards the +resolution of robotics tasks. Machine learning approaches +have demonstrated significant results in the modeling of +omplex systems (e.g., articulated robot structures, ca- +le stretch, fluid dynamics), or to learn robotics tasks +(e.g., grasping, reaching) from raw sensor measurements +without explicit programming, using reinforcement learn- +ing. However, a common bottleneck in machine learn- +ing techniques resides in the availability of suitable data. +While many vision-based datasets have been released in +the recent years, ones involving physical interactions, of +particular interest for the robotic community, have been +scarcer. In this paper, we present a public dataset on peg- +in-hole insertion tasks containing force-torque and pose +information for multiple variations of convex-shaped pegs."
86c053c162c08bc3fe093cc10398b9e64367a100,Cascade of forests for face alignment,"Cascade of Forests for Face Alignment Heng Yang, Changqing Zou, Ioannis Patras"
861802ac19653a7831b314cd751fd8e89494ab12,"Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications","Marcin Grzegorzek, Christian Theobalt, Reinhard Koch, @@ -8428,6 +28974,13 @@ lot of attention recently and have een improved considerably over the last few years. The present techniques..."
+8646f22a46b65c2018bc39ad3cbdb939e788a1fc,Learning a Confidence Measure for Optical Flow,"Learning a Confidence Measure +for Optical Flow +Oisin Mac Aodha, Ahmad Humayun, Marc Pollefeys and Gabriel J. Brostow"
+8641593c67d87d81e528448a527e45fc9a5aa145,Complex Urban LiDAR Data Set,"Complex Urban LiDAR Data Set +Jinyong Jeong1, Younggun Cho1, Young-Sik Shin1, Hyunchul Roh1 and Ayoung Kim1 +Fig. 1: This paper provides the complex urban data set including metropolitan area, apartment building complex and +underground parking lot. Sample scenes from the data set can be found in https://youtu.be/IguZjmLf5V0."
861b12f405c464b3ffa2af7408bff0698c6c9bf0,An Effective Technique for Removal of Facial Dupilcation by SBFA,"International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 3 Issue: 5 3337 - 3342 @@ -8441,6 +28994,17 @@ Dr. Ayesha Butalia Computer Department, GHRCEM, Pune, India"
+869df5e8221129850e81e77d4dc36e6c0f854fe6,A metric for sets of trajectories that is practical and mathematically consistent,"A metric for sets of trajectories that is +practical and mathematically consistent +Jos´e Bento +Jia Jie Zhu"
+86c1bf121851aa901e3e7eb11a3b8cc5a08a921b,"Motion, Blur, Illumination based Face Recognition","ISSN: 2455-5797 International Journal of Innovative Works in Engineering and Technology (IJIWET) +Motion, Blur, Illumination based Face Recognition +Anand M.S +PG Student +Department of ECE +Satyam College of Engineering +E-mail :"
86e1bdbfd13b9ed137e4c4b8b459a3980eb257f6,The Kinetics Human Action Video Dataset,"The Kinetics Human Action Video Dataset Will Kay Jo˜ao Carreira @@ -8474,8 +29038,83 @@ Chongqing Key Laboratory of Computational Intelligence College of Computer Science and Technology, Chongqing Chongqing Key Laboratory of Computational Intelligence College of Computer Science and Technology, Chongqing"
+86e87d276b5b01a6b4b09b5487781fab740aca2e,Deep Ranking Model by Large Adaptive Margin Learning for Person Re-identification,"Deep Ranking Model by Large Adaptive Margin Learning for +Person Re-identification +Jiayun Wanga, Sanping Zhoua, Jinjun Wanga,∗, Qiqi Houa +The institute of artificial intelligence and robotic, Xi’an Jiaotong University, Xianning West Road +No.28, Shaanxi, 710049, P.R. China"
+860196a306c9303ddaf323d702dacba68db658d2,Open-Ended Content-Style Recombination Via Leakage Filtering,"OPEN-ENDED CONTENT-STYLE RECOMBINATION +VIA LEAKAGE FILTERING +Karl Ridgeway+∗ & Michael C. Mozer+† ++ Department of Computer Science, University of Colorado, Boulder +Sensory, Inc. +presently at Google Brain, Mountain View"
86b105c3619a433b6f9632adcf9b253ff98aee87,A Mutual Information based Face Clustering Algorithm for Movies,"424403677/06/$20.00 ©2006 IEEE ICME 2006"
+8616ff1d0fd7bcfc5fd81d1e8a9b189c21f3b93d,Visual Reference Resolution using Attention Memory for Visual Dialog,"Visual Reference Resolution using Attention Memory +for Visual Dialog +Paul Hongsuck Seo† +POSTECH +Andreas Lehrmann§ +{hsseo, {andreas.lehrmann, +Bohyung Han† +§Disney Research +Leonid Sigal§"
+8609035f1b9fa5bddfbbffd287a98ba47a1ecba0,Making Bertha See,"Making Bertha See +Uwe Franke, David Pfeiffer, Clemens Rabe, Carsten Knoeppel, +Markus Enzweiler, Fridtjof Stein, and Ralf G. Herrtwich +Daimler AG - Research & Development, 71059 Sindelfingen, Germany"
+86be567bab1293ed847979d2c56a662fcbcbc1d5,Exploiting View-Specific Appearance Similarities Across Classes for Zero-Shot Pose Prediction: A Metric Learning Approach,"Exploiting View-Specific Appearance Similarities Across Classes for +Zero-shot Pose Prediction: A Metric Learning Approach +Alina Kuznetsova +Leibniz University Hannover +Appelstr 9A, 30169 +Hannover, Germany +Sung Ju Hwang +UNIST +50 UNIST-gil, 689798 +Ulsan, Korea +Bodo Rosenhahn +Leibniz University Hannover +Appelstr 9A, 30169 +Hannover, Germany +Leonid Sigal +Disney Research +720 Forbes Avenue, 15213 +Pittsburgh, PA, US"
+8627248c6e3c3e316e3964d12e0a44e23aa969f3,Automated Annotations,"Automated Annotations +Richard Brath and Martin Matusiak* +Uncharted Software Inc."
+72ef0ac03d3043bf664ca7c21abafc4191b24557,Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection,"Towards Safe Autonomous Driving: Capture Uncertainty in the Deep +Neural Network For Lidar 3D Vehicle Detection +Di Feng1, Lars Rosenbaum1, Klaus Dietmayer2"
+7214d9356398aa39923c69650bcf761d4ab6307f,Improving Spatial Saliency Using Affinity Model and Temporal Motion,"Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'15 | +Improving Spatial Saliency Using +Affinity Model and Temporal Motion +Dept. of Computer and Communications Engineering, Kangwon National University +Manbae Kim +Chunchon, Gangwondo, Republic of Korea +E-mail:"
+721fbc63a647239158bf817311d1c084455398e9,Shape-based automatic detection of a large number of 3D facial landmarks,"Shape-based Automatic Detection of a Large Number of 3D Facial Landmarks +Syed Zulqarnain Gilani, Faisal Shafait, Ajmal Mian +School of Computer Science and Software Engineering,The University of Western Australia. +Figure 3: Histogram of mean localization error for 18 landmarks on 4,007 +scans of FRGCv2 dataset (18× 4007 Landmarks). +Mean Localization Error(mm) +Neutral +Non−Neutral +Neutral +Level−1 +Level−2 +Level−3 +Level−4 +Figure 1: Our algorithm automatically detects an arbitrarily large number of +facial landmarks by establishing dense correspondences between 3D faces. +The figure shows 85 landmarks detected (red) on neutral and extreme anger +expression of a subject from BU3DFE database [3]. The ground truth is +represented by blue dots. +2202 +Mean Localization Error(mm)"
72a87f509817b3369f2accd7024b2e4b30a1f588,Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints,"Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints Etienne Côme, Latifa Oukhellou, Thierry Denoeux, Patrice Aknin @@ -8503,6 +29142,13 @@ identification Sinjini Mitra · Nicole A. Lazar · Yanxi Liu Received: May 2005 / Accepted: September 2006 / Published online: 30 January 2007 C(cid:1) Springer Science + Business Media, LLC 2007"
+725597072c76dad5caa92b7baa6e1c761addc300,Deep adversarial neural decoding,"Deep adversarial neural decoding +Ya˘gmur Güçlütürk*, Umut Güçlü*, +Katja Seeliger, Sander Bosch, +Rob van Lier, Marcel van Gerven, +Radboud University, Donders Institute for Brain, Cognition and Behaviour +Nijmegen, the Netherlands +*Equal contribution"
727ecf8c839c9b5f7b6c7afffe219e8b270e7e15,Leveraging Geo-referenced Digital Photographs a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"LEVERAGING GEO-REFERENCED DIGITAL PHOTOGRAPHS A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE @@ -8513,16 +29159,79 @@ FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Mor Naaman July 2005"
+7278f4c361f960b2e54275c5efd98535f9ccaded,Image Based Recognition of Dynamic Traffic Situations by Evaluating the Exterior Surrounding and Interior Space of Vehicles,"IMAGE BASED RECOGNITION OF DYNAMIC TRAFFIC SITUATIONS BY +EVALUATING THE EXTERIOR SURROUNDING AND INTERIOR SPACE OF VEHICLES +Photogrammetry & Remote Sensing, Technische Universitaet Muenchen, Germany - (alexander.hanel, ludwig.hoegner, +BMW Research & Technology, Muenchen, Germany - +A. Hanela, H. Klödenb, L. Hoegnera, U. Stillaa +KEY WORDS: vehicle camera system, crowd sourced data, image analysis, machine learning, object detection, illumination recogni- +tion, traffic situation recognition"
+722221f6c696b4a7cc094748aaad8158990ec41e,3D facial expression recognition: A perspective on promises and challenges,"D Facial Expression Recognition: +A Perspective on Promises and Challenges +T. Fang, X. Zhao, O. Ocegueda, S.K. Shah and I.A. Kakadiaris*"
72ecaff8b57023f9fbf8b5b2588f3c7019010ca7,Facial Keypoints Detection,"Facial Keypoints Detection Shenghao Shi"
+72edc24c67c34b5f2c98086a689bf0f3591e393d,An Introduction to Image Synthesis with Generative Adversarial Nets,"An Introduction to Image Synthesis with +Generative Adversarial Nets +He Huang, Phillip S. Yu and Changhu Wang"
72591a75469321074b072daff80477d8911c3af3,Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction,"Group Component Analysis for Multi-block Data: Common and Individual Feature Extraction Guoxu Zhou, Andrzej Cichocki Fellow, IEEE, Yu Zhang, and Danilo Mandic Fellow, IEEE"
+72a1ecfcd5f0b022fef49cab72bb476e41dea40e,Bag-of-features representations using spatial visual vocabularies for object classification,"BAG-OF-FEATURES REPRESENTATIONS USING SPATIAL VISUAL VOCABULARIES FOR +OBJECT CLASSIFICATION +Rene Grzeszick, Leonard Rothacker, Gernot A. Fink +TU Dortmund +Email: {rene.grzeszick, leonard.rothacker, +Department of Computer Science"
729a9d35bc291cc7117b924219bef89a864ce62c,Recognizing Material Properties from Images,"Recognizing Material Properties from Images Gabriel Schwartz and Ko Nishino, Senior Member, IEEE"
+7249b263d0a84d2d9d03f2f7b378778d129f9af9,Research Statement Research Focus,"RESEARCH STATEMENT +Ryan Farrell +In recent years, the topic of object detection/recognition has rapidly gained in popularity and is now +perhaps the most actively researched topic in computer vision. Object detection algorithms are becoming +prevalent in consumer devices such as digital cameras (real-time face detection) and automobiles (pedestrian +detection systems for collision avoidance are already available and will be a standard feature on new cars +within a few years). Object recognition technology is quickly becoming widespread in smartphone apps; +examples include Google Goggles, Amazon Flow and Leafsnap. I believe we are at a ‘tipping point’ towards +the impending ubiquity of computer vision, specifically object recognition, in our everyday lives. +RESEARCH FOCUS +My research in object recognition focuses specifically on Fine-grained Visual Categorization (sometimes +bbreviated FGVC). For many years, computer vision has focused on classifying an object in several basic- +level categories such as person, car, frog, or piano. At the opposing end of the categorization spectrum +(see Figure ) is biometric identification - recognizing individuals within a population (e.g. face recognition or +recognizing individual whales by unique fluke patterns). Between these two extremes lie what are called entry- +nd subordinate-level categories. Entry-level categories include penguin, owl, etc.; people generally use these +more specific labels instead of simply saying “bird” (the basic-level category). Subordinate-level categories +re highly specific. Continuing with the example of birds, categorizing at the subordinate-level would require +differentiating two quite similar species (such as the Red-breasted and White-breasted Nuthatches). Fine- +grained recognition addresses this situation where categories are distinguised by very subtle differences."
721d9c387ed382988fce6fa864446fed5fb23173,Assessing Facial Expressions in Virtual Reality Environments,
72c0c8deb9ea6f59fde4f5043bff67366b86bd66,Age progression in Human Faces : A Survey,"Age progression in Human Faces : A Survey Narayanan Ramanathan, Rama Chellappa and Soma Biswas"
+727d03100d4a8e12620acd7b1d1972bbee54f0e6,von Mises-Fisher Mixture Model-based Deep learning: Application to Face Verification,"von Mises-Fisher Mixture Model-based Deep +learning: Application to Face Verification +Md. Abul Hasnat, Julien Bohn´e, Jonathan Milgram, St´ephane Gentric and Liming Chen"
+728a8c4ed6b5565a250bd1e0587293a6a97f515b,Arguing Machines: Human Supervision of Black Box AI Systems That Make Life-Critical Decisions,"Arguing Machines: Human Supervision of Black Box +AI Systems That Make Life-Critical Decisions +Lex Fridman* +Li Ding +Massachusetts Institute of Technology (MIT) +Benedikt Jenik +Bryan Reimer +Figure 1: “Arguing machines” framework that adds a secondary system to a primary “black box” AI system that makes life- +ritical decisions and uses disagreement between the two as a signal to seek human supervision. We demonstrate that this can +e a powerful way to reduce overall system error."
+72a6044a0108e0f8f1e68cd70ada46c81a416324,Improved Training of Generative Adversarial Networks Using Representative Features,"Improved Training of Generative Adversarial Networks +using Representative Features +Duhyeon Bang 1 Hyunjung Shim 1"
+72ef87fb1a49f0e386f123a6b4f5566f51a3a47d,Minimizing Latency for Secure Coded Computing Using Secret Sharing via Staircase Codes,"Minimizing Latency for Secure Coded Computing +Using Secret Sharing via Staircase Codes +Rawad Bitar, Parimal Parag, and Salim El Rouayheb"
+7276a3ffa0941524083ac0fa9f0129746bca65d7,Multi-scale Deep Learning Architectures for Person Re-identification,"Multi-scale Deep Learning Architectures for Person Re-identification +Xuelin Qian1 Yanwei Fu2,5,* Yu-Gang Jiang1,3 Tao Xiang4 Xiangyang Xue1,2 +Shanghai Key Lab of Intelligent Info. Processing, School of Computer Science, Fudan University; +School of Data Science, Fudan University; 3Tencent AI Lab; +Queen Mary University of London; 5University of Technology Sydney;"
72f4aaf7e2e3f215cd8762ce283988220f182a5b,Active illumination and appearance model for face alignment,"Turk J Elec Eng & Comp Sci, Vol.18, No.4, 2010, c(cid:2) T ¨UB˙ITAK doi:10.3906/elk-0906-48 Active illumination and appearance model for face @@ -8534,6 +29243,39 @@ DTU Informatics, Technical University of Denmark, DK-2800 Kgs. Lyngby, DENMARK e-mail: e-mail: e-mail: {sda,"
+72944b4266523effe97708bff89e1d57d6aebf50,"A Multi-Sensory, Automated and Accelerated Sensory Integration Program","A Multi-Sensory, Automated and Accelerated +Sensory Integration Program +The Research +Below are several published research reports that document the efficacy of a +singular program such as auditory therapy or visual therapy alone as well as the +use of multi-sensory programs using one or more sensory programs together. +This is only a sample of the volumes of research that has been done. +Multisensory integration of cross-modal stimulus combinations yielded responses +that were significantly greater than those evoked by the best component +stimulus. J Neurophysiol 97: 3193–3205, 2007. doi:10.1152/jn.00018.2007. +Multisensory Versus Unisensory Integration: Contrasting Modes in the Superior +Colliculus, Juan Carlos Alvarado, J. William Vaughan, Terrence R. Stanford, and +Barry E. Stein +Department of Neurobiology and Anatomy, Wake Forest University School of +Medicine, Winston-Salem, North Carolina +When sound and touch were activated simultaneously, the activation of the +uditory cortex was strongest. Auditory information in conjunction with tactile +input assists with making tactile decisions. Tactile and auditory stimulation +simultaneously and individually may positively impact neuroplastic changes in +individuals with neurological deficits or impairments. Used singularly, sound"
+72d067a6e1fd447ef512262248ad5f73823a3842,Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms,"Probabilistic Models for +D Urban Scene Understanding +from Movable Platforms +Dissertation +Dipl.-Inform. Andreas Geiger"
+72f4c415b5f3ecf63380b6985c95c5af2ba72632,Activity Recognition on a Large Scale in Short Videos - Moments in Time Dataset,"ACTIVITY RECOGNITION ON A LARGE SCALE IN +SHORT VIDEOS - MOMENTS IN TIME DATASET +Ankit Parag Shah* ∗ +Harini Kesavamoorthy* +Poorva Rane* +Pramati Kalwad* +Alexander Hauptmann +Florian Metze"
72a55554b816b66a865a1ec1b4a5b17b5d3ba784,Real-Time Face Identification via CNN and Boosted Hashing Forest,"Real-Time Face Identification via CNN nd Boosted Hashing Forest @@ -8541,6 +29283,24 @@ Yury Vizilter, Vladimir Gorbatsevich, Andrey Vorotnikov and Nikita Kostromov State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russia IEEE Computer Society Workshop on Biometrics In conjunction with CVPR 2016, June 26, 2016"
+72c248c8d3bd76e2a31963aad7286b8d06ab7f8e,Looking outside of the Box: Object Detection and Localization with Multi-scale Patterns,"Looking outside of the Box: +Object Detection and Localization with +Multi-scale Patterns +Eshed Ohn-Bar, Student Member, IEEE, and Mohan Manubhai Trivedi, Fellow, IEEE"
+72a79f351d4ae03ff940ff920898e41ce960f58e,Author's Personal Copy Backtracking: Retrospective Multi-target Tracking,"(This is a sample cover image for this issue. The actual cover is not yet available at this time.) +This article appeared in a journal published by Elsevier. The attached +opy is furnished to the author for internal non-commercial research +nd education use, including for instruction at the authors institution +nd sharing with colleagues. +Other uses, including reproduction and distribution, or selling or +licensing copies, or posting to personal, institutional or third party +websites are prohibited. +In most cases authors are permitted to post their version of the +rticle (e.g. in Word or Tex form) to their personal website or +institutional repository. Authors requiring further information +regarding Elsevier’s archiving and manuscript policies are +encouraged to visit: +http://www.elsevier.com/copyright"
72bf9c5787d7ff56a1697a3389f11d14654b4fcf,Robust Face Recognition Using Symmetric Shape-from-Shading,"RobustFaceRecognitionUsing SymmetricShape-from-Shading W.Zhao @@ -8550,9 +29310,86 @@ ElectricalandComputerEngineeringDepartment UniversityofMaryland CollegePark,MD ThesupportoftheO(cid:14)ceofNavalResearchunderGrantN +727c8c696c6acc04e57b6c3541613702c22c6f0f,Optimal discrete wavelet transform (DWT) features for face recognition,"010 Asia Pacific Conference on Circuits and Systems (APCCAS 2010) +6 - 9 December 2010, Kuala Lumpur, Malaysia +Optimal Discrete Wavelet Transform (DWT) +Features for Face Recognition +Paul Nicholl +School of Electronics, Electrical +Engineering & Computer Science +Queen’s Univ., Northern Ireland +Email: +Afandi Ahmad +Abbes Amira +JEC, Faculty of. Elec. and Electronic Eng. +Univ. Tun Hussein Onn Malaysia +NIBEC, Faculty of Comp. and Eng. +Univ. of Ulster, Jordanstown Campus +Johor, Malaysia +Email: +Northern Ireland +Email:"
+725a45ad75caf0112d649253f8a69793b1f00e80,LIFEisGAME : An approach to the utilization of serious games for therapy for children with ASD,"LIFEisGAME: An approach to the utilization of serious +games for therapy for children with ASD +Tiago Fernandes1,5, Samanta Alves2, José Miranda3,5, Cristina Queirós2, Verónica +Instituto de Telecomunicações, Lisboa, Portugal, +Faculdade de Psicologia da Universidade do Porto, Porto, Portugal, +Instituto Politécnico da Guarda, Porto, Portugal, +Faculdade de Ciências da Universidade do Porto, Porto, Portugal, +5 Faculdade de Engenharia da Universidade do Porto, Porto, Portugal, +Orvalho1,4"
+72cebd7d046080899703ed3cd96e3019a9f60f13,Towards Transparent AI Systems: Interpreting Visual Question Answering Models,"Towards Transparent AI Systems: +Interpreting Visual Question Answering Models +Yash Goyal, Akrit Mohapatra, Devi Parikh, Dhruv Batra +{ygoyal, akrit, parikh, +Virginia Tech"
+724a493411b7c5a904445406d3037df4a22b6c89,Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentation,"Training of Convolutional Networks on Multiple Heterogeneous +Datasets for Street Scene Semantic Segmentation +Panagiotis Meletis and Gijs Dubbelman"
4414a328466db1e8ab9651bf4e0f9f1fe1a163e4,Weighted voting of sparse representation classifiers for facial expression recognition,"© EURASIP, 2010 ISSN 2076-1465 8th European Signal Processing Conference (EUSIPCO-2010) INTRODUCTION"
+44736c0c7cfced2c0f06c5ae8dd0111d9ea0dc20,On the Robustness of Speech Emotion Recognition for Human-Robot Interaction with Deep Neural Networks,"On the Robustness of Speech Emotion Recognition for Human-Robot +Interaction with Deep Neural Networks +Egor Lakomkin1, Mohammad Ali Zamani1, Cornelius Weber1, Sven Magg1 and Stefan Wermter1"
+44f4b1b90f8d5515f2486e07e4cb4b9589c27518,Deep Learning and Its Applications to Machine Health Monitoring: A Survey,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Deep Learning and Its Applications to Machine +Health Monitoring: A Survey +Rui Zhao, Ruqiang Yan, Zhenghua Chen, Kezhi Mao, Peng Wang, and Robert X. Gao"
+44b30a1048465cd56904cdcbec8e79dffab693bd,Semantic based Query Approach For Web Image Search Through reranking algorithm,"Scientific Journal of Impact Factor (SJIF): 3.134 +E-ISSN (O): 2348-4470 +P-ISSN (P): 2348-6406 +International Journal of Advance Engineering and Research +Development +Volume 2,Issue 12,December -2015 +Semantic based Query Approach For Web Image Search +Through reranking algorithm +Pushpak Waghmare1, Shubham Katkamwan2, Abhijeet Markand3, Abuj Pratiksha4, Prof. Navale Girish Jaysingh5 +-5Department Of Computer,All India shri Shivaji Memorial Society’s"
+44442a26062c20dab7db4a9862349b598efca119,Modelling errors in a biometric re-identification system,"Modeling Errors in a Biometric Re-Identification System +B. DeCann and A. Ross +We consider the problem of “re-identification” where a biometric system answers the question “Has this person been encountered before?” without actually +deducing the person’s identity. Such a system is vital in biometric surveillance applications and applicable to biometric de-duplication. In such a system, identifiers +re created dynamically as and when the system encounters an input probe. Consequently, multiple probes of the same identity may be mistakenly assigned different +identifiers, while probes from different identities may be mistakenly assigned the same identifier. In this work, we describe a re-identification system and develop +terminology as well as mathematical expressions for prediction of matching errors. Further, we demonstrate that the sequential order in which the probes are +encountered by the system has a great impact on its matching performance. Experimental analysis based on unimodal and multimodal face and fingerprint scores +onfirms the validity of the designed error prediction model, as well as demonstrates that traditional metrics for biometric recognition fail to accurately characterize +the error dynamics of a re-identification system. +Introduction: In a classical biometric system [1], the input probe (query) biometric data is compared against the reference samples (templates) residing +in the reference database (gallery). Each sample in the reference database is assigned a label, which acts as an identifier (e.g., user-id, name, etc.) that +relates the reference sample to a specific individual and therefore, the comparison process enables the system to either determine the individual associated +with the input data (referred to as identification or 1:N matching) or verify whether the input biometric data corresponds to a specific person (referred +to as verification or 1:1 matching). Labels are assigned to a reference sample during an enrollment phase, when the biometric data of an individual is +cquired and stored in the reference database. The identifier may be further associated with additional biographic data (e.g., legal name, ID number) to +link the identifier to an identity.1 Thus, the identification and verification problems address the question: “Who is this person?” or “Is this person who +they claim to be?”, respectively. +In this work, we examine a variant of the classical biometric identification system, wherein probe data is input into the system from sensors at +multiple locations. The objective of the system is to deduce: “Has this person been encountered before?”. A biometric system performing such duties"
+4425df6cc10917644c44a7f4177a5d7cc1c8b7bc,Object Localization based on Structural SVM using Privileged Information,"Object Localization based on Structural SVM +using Privileged Information +Jan Feyereisl, Suha Kwak∗, Jeany Son, Bohyung Han +Dept. of Computer Science and Engineering, POSTECH, Pohang, Korea"
4439746eeb7c7328beba3f3ef47dc67fbb52bcb3,YASAMAN HEYDARZADEH at al: AN EFFICIENT FACE DETECTION METHOD USING ADABOOST,"YASAMAN HEYDARZADEH at al: AN EFFICIENT FACE DETECTION METHOD USING ADABOOST . . . An Efficient Face Detection Method Using Adaboost and Facial Parts Yasaman Heydarzadeh, Abolfazl Toroghi Haghighat @@ -8579,11 +29416,56 @@ F-75010, Paris, France" IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE Learning Multi-modal Latent Attributes Yanwei Fu, Timothy M. Hospedales, Tao Xiang and Shaogang Gong"
+448efcae3b97aa7c01b15c6bc913d4fbb275f644,Style Finder: Fine-Grained Clothing Style Recognition and Retrieval,"Style Finder: Fine-Grained Clothing Style Recognition and Retrieval +Wei Di2, Catherine Wah1, Anurag Bhardwaj2, Robinson Piramuthu2, and Neel Sundaresan2 +Department of Computer Science and Engineering, University of California, San Diego +eBay Research Labs, 2145 Hamilton Ave. San Jose, CA"
+4443ee5eaa56e41acddb62cacbc2f6d8c84ccd59,Multiple Objects Fusion Tracker Using a Matching Network for Adaptively Represented Instance Pairs,"Article +Multiple Objects Fusion Tracker Using a Matching +Network for Adaptively Represented Instance Pairs +Sang-Il Oh and Hang-Bong Kang * +Department of Media Engineering, Catholic University of Korea, 43-1, Yeoggok 2-dong, Wonmmi-gu, +Bucheon-si, Gyeonggi-do 14662, Korea; +* Correspondence: Tel.: +82-2-2164-4598 +Academic Editor: Simon X. Yang +Received: 27 February 2017; Accepted: 14 April 2017; Published: 18 April 2017"
446dc1413e1cfaee0030dc74a3cee49a47386355,Recent Advances in Zero-shot Recognition,"Recent Advances in Zero-shot Recognition Yanwei Fu, Tao Xiang, Yu-Gang Jiang, Xiangyang Xue, Leonid Sigal, and Shaogang Gong"
44a3ec27f92c344a15deb8e5dc3a5b3797505c06,A Taxonomy of Part and Attribute Discovery Techniques,"A Taxonomy of Part and Attribute Discovery Techniques Subhransu Maji"
+44880df54e6caa3e7263db7a4d5cb77838f4698f,Learning Optimal Parameters for Multi-target Tracking with Contextual Interactions,"Learning Optimal Parameters for Multi-target Tracking with Contextual +Interactions +Shaofei Wang · Charless C. Fowlkes"
+44bb6ccb3526bb38364550263bc608116910da32,Model-Driven Simulations for Computer Vision,"017 IEEE Winter Conference on Applications of Computer Vision +Model-driven Simulations for Computer Vision +VSR Veeravasarapu1, Constantin Rothkopf2, Ramesh Visvanathan1 +Center for Cognition and Computation, Dept. of Computer Science, Goethe University, Frankfurt +Center for Cognitive Science & Dept. of Psychology, Technical University Darmstadt. +(a) Lambertian +(Direct-lighting based rendering) +(b) Ray tracing +(appearance-driven rendering) +(c) Monte-Carlo rendering +(physics-driven rendering) +(d) Semantic labels +(e) Day light +(f) Night +Figure 1: Rendering fidelity and Virtual scene diversity. This work aims to quantify the impact of photorealism and physics +fidelity on transfer learning from virtual reality. (a)-(c): Images of same scene state rendered with different rendering engines. +(e)-(g): Same scene under different lighting. (d) and (h) semantic labels. Color coding scheme for labels is same as [5]. +(g) Rain +(h) Semantic labels"
+44993de87bbbce71f14d7917944d055700217696,A late fusion approach to combine multiple pedestrian detectors,"A Late Fusion Approach to Combine Multiple +Pedestrian Detectors +Artur Jord˜ao, Jessica Sena de Souza, William Robson Schwartz +Smart Surveillance Interest Group, Computer Science Department +Universidade Federal de Minas Gerais, Minas Gerais, Brazil"
+44241248f16c172a1c2fb90e48fd728ba26220fc,Expression-invariant Non-rigid 3D Face Recognition: A Robust Approach to Expression-aware Morphing,"Expression-invariant Non-rigid 3D Face Recognition: A Robust Approach to +Expression-aware Morphing +F. R. Al-Osaimi +M. Bennamoun +A. Mian"
44dd150b9020b2253107b4a4af3644f0a51718a3,An Analysis of the Sensitivity of Active Shape Models to Initialization When Applied to Automatic Facial Landmarking,"An Analysis of the Sensitivity of Active Shape Models to Initialization when Applied to Automatic Facial Landmarking @@ -8597,11 +29479,47 @@ under variations in illumination Anil Kumar Sao · B. Yegnanarayana Received: 17 November 2008 / Revised: 20 February 2009 / Accepted: 7 July 2009 © Springer-Verlag London Limited 2009"
+44703dea094eb9558965db9439a07b9a74fd36b5,"Multiculturalism, Colorblindness, and Prejudice: Examining How Diversity Ideologies Impact Intergroup Attitudes","University of Arkansas, Fayetteville +Theses and Dissertations +8-2018 +Multiculturalism, Colorblindness, and Prejudice: +Examining How Diversity Ideologies Impact +Intergroup Attitudes +David Sparkman +University of Arkansas, Fayetteville +Follow this and additional works at: https://scholarworks.uark.edu/etd +Part of the Social Psychology Commons +Recommended Citation +Sparkman, David, ""Multiculturalism, Colorblindness, and Prejudice: Examining How Diversity Ideologies Impact Intergroup +Attitudes"" (2018). Theses and Dissertations. 2923. +https://scholarworks.uark.edu/etd/2923 +This Dissertation is brought to you for free and open access by It has been accepted for inclusion in Theses and Dissertations by +n authorized administrator of For more information, please contact"
+4461a1b70e461ec298d7066ba103deda48d4ba22,Classification via Minimum Incremental Coding Length,"Vol. 2, No. 2, pp. 367–395 +(cid:2) 2009 Society for Industrial and Applied Mathematics +Classification via Minimum Incremental Coding Length +John Wright +, Yi Ma +, Yangyu Tao +, Zhouchen Lin +, and Heung-Yeung Shum"
+442cc39db208a66acf3acc22589b13981bb303fd,Design of Non-Linear Discriminative Dictionaries for Image Classification,"CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. +Design of Non-Linear Discriminative +Dictionaries for Image Classi(cid:12)cation +Anonymous ACCV 2012 submission +Paper ID 662"
447a5e1caf847952d2bb526ab2fb75898466d1bc,Learning Non-linear Transform with Discrim- Inative and Minimum Information Loss Priors,"Under review as a conference paper at ICLR 2018 LEARNING NON-LINEAR TRANSFORM WITH DISCRIM- INATIVE AND MINIMUM INFORMATION LOSS PRIORS Anonymous authors Paper under double-blind review"
+4452c36dc4c5e9f11d041489c8ff2e7006d33c80,"A Computational Analysis of Recent Multi-Object Tracking Methods Based on Particle Filter, HMM and Appearance Information of Objects","International Journal of Emerging Technology and Advanced Engineering +Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 3, Issue 02, February 2013) +A Computational Analysis of Recent Multi-Object Tracking +Methods Based on Particle Filter, HMM and Appearance +Information of Objects +Raksha Shrivastava1, Professor Rajesh Nema 2 +,2Department of Electronics and Communication, NRI Institute of Information Science and Technology, Bhopal (M.P)"
2a7bca56e2539c8cf1ae4e9da521879b7951872d,Exploiting Unrelated Tasks in Multi-Task Learning,"Exploiting Unrelated Tasks in Multi-Task Learning Anonymous Author 1 Unknown Institution 1 @@ -8609,15 +29527,134 @@ Anonymous Author 2 Unknown Institution 2 Anonymous Author 3 Unknown Institution 3"
+2af2aa21538783e46911fb857a23dbb88ed90c2b,A Study on Deep Learning Based Sauvegrain Method for Measurement of Puberty Bone Age,"A Study on Deep Learning Based +Sauvegrain Method for Measurement +of Puberty Bone Age +Keum Gang Cha∗ +Seung Bin Baik∗ +Plani Inc. +Plani Inc. +September 20, 2018"
+2aa08ab3d6c227e3b071dc470a2f36dc5d4a2403,Ensembling Visual Explanations for VQA,"To Appear In Proceedings of the NIPS 2017 workshop on Visually-Grounded +Interaction and Language (ViGIL), December 2017."
+2a2b99fc9583419931681acfd83ac953a3df3270,Estimating the quality of face localization for face verification,"ESTIMATING THE QUALITY OF FACE LOCALIZATION FOR FACE VERIFICATION +Yann Rodriguez +Fabien Cardinaux +Samy Bengio +Johnny Mari´ethoz +IDIAP +CP 592, rue du Simplon 4 +920 Martigny, Switzerland"
+2a93ce4284c7f8605e1d9bc0a8b86036073ebf61,"Tracking, Learning and Detection of Multiple Objects in Video Sequences","Master Thesis +Czech +Technical +University +in Prague +Faculty of Electrical Engineering +Department of Cybernetics +Tracking, Learning and Detection of +Multiple Objects in Video Sequences +Filip Naiser +Supervisor: prof. Ing. Jiří Matas, Ph.D. +January 2017"
+2a218c17944d72bfdc7f078f0337cab67536e501,Detection bank: an object detection based video representation for multimedia event recognition,"Detection Bank: An Object Detection Based Video +Representation for Multimedia Event Recognition +Tim Althoff, Hyun Oh Song, Trevor Darrell +UC Berkeley EECS/ICSI +Multimedia Event Detection +Birthday Party vs Wedding Ceremony +● ObjectBank omits the following steps that are +standard in a detection pipeline: +● Thresholding of score maps +● Non-maximum suppression +● Pooling across all scales +● We compute different detection count statistics to +apture e.g. max number of detections, sum of +detection scores, probablity of detection based on +the detection images from a large number of +windowed object detectors. +Detection Count Statistics +Look for: Balloon, Candle, Birthday Cake vs. +Bride, Groom, Wedding Gown, Wedding Cake +Illustration"
+2a152dae1ba70d0cc605b0f7418392ed1a294a4a,Head Pose Detection Using Fast Robust PCA for Side Active Appearance Models Under Occlusion,"Head Pose Detection Using Fast Robust PCA +for Side Active Appearance Models Under Occlusion +Anıl Yüce1, Matteo Sorci2, and Jean-Philippe Thiran1 +Signal Processing Laboratory (LTS5) +École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland +nViso Sàrl, Lausanne, Switzerland"
+2a12c72b0328a23b0d7ea63db1f93abf3054beec,Extended Feature Descriptor and Vehicle Motion Model with Tracking-by-Detection for Pedestrian Active Safety,"IEICE TRANS. ??, VOL.Exx–??, NO.xx XXXX 200x +PAPER +Extended Feature Descriptor and Vehicle Motion Model with +Tracking-by-detection for Pedestrian Active Safety +Hirokatsu KATAOKAy;yya), Kimimasa TAMURAy, Nonmembers, Kenji IWATAyyy, Yutaka SATOHyyy, Members, +Yasuhiro MATSUIyyyy, Nonmember, and Yoshimitsu AOKIy, Member +SUMMARY +The percentage of pedestrian deaths in traffic accidents is +on the rise in Japan. In recent years, there have been calls for measures +to be introduced to protect vulnerable road users such as pedestrians and +yclists. In this study, a method to detect and track pedestrians using an +in-vehicle camera is presented. We improve the technology of detecting +pedestrians by using the highly accurate images obtained with a monocular +amera. In the detection step, we employ ECoHOG as the feature descrip- +tor; it accumulates the integrated gradient intensities. In the tracking step, +we apply an effective motion model using optical flow and the proposed +feature descriptor ECoHOG in a tracking-by-detection framework. These +techniques were verified using images captured on real roads. +key words: Pedestrian Active Safety, Tracking-by-detection, ECoHOG, +Particle Filter, Vehicle Motion Model"
+2a067874fc1ec318b6d23f34bdb13ea4e95d5ca6,An Evaluation of Image-Based Verb Prediction Models against Human Eye-Tracking Data,"New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics +Proceedings of NAACL-HLT 2018, pages 758–763"
+2ad2af8e3bdeb0302de07defc3fec9b387414a27,Don't Look Back: Post-hoc Category Detection via Sparse Reconstruction,"Don't Look Back: Post-hoc Category Detection via +Sparse Reconstruction +Hyun Oh Song +Mario Fritz +Tim Althoff +Trevor Darrell +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2012-16 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-16.html +January 24, 2012"
+2a86bcdfb1d817ddb76ba202319f8267a36c0f62,PCL: Proposal Cluster Learning for Weakly Supervised Object Detection,"JOURNAL OF LATEX CLASS FILES +PCL: Proposal Cluster Learning for Weakly +Supervised Object Detection +Peng Tang, Xinggang Wang, Member, IEEE, Song Bai, Wei Shen, Xiang Bai, Senior Member, IEEE, +Wenyu Liu, Senior Member, IEEE, and Alan Yuille, Fellow, IEEE"
+2a259fd1b4442a71cd127afac417a650ffc379d9,Human upper body posture recognition and upper limbs motion parameters estimation,"Human Upper Body Posture Recognition and Upper +Limbs Motion Parameters Estimation +Jun-Yang Huang1 Shih-Chung Hsu1and Chung-Lin Huang1,2 +. Department Of Electrical Engineering, National Tsing-Hua University, Hsin-Chu, Taiwan +. Department of Applied Informatics and Multimedia, Asia Univeristy, Tai-Chung, Taiwan. +Email:"
2a0efb1c17fbe78470acf01e4601a75735a805cc,Illumination-Insensitive Face Recognition Using Symmetric Shape-from-Shading,"Illumination-InsensitiveFaceRecognitionUsing SymmetricShape-from-Shading WenYiZhao RamaChellappa CenterforAutomationResearch UniversityofMaryland,CollegePark,MD +2a7e2cda27807d24b845f5b5080fb1296c302bfe,Personal Authentication Using Signature Recognition,"Personal Authentication Using Signature Recognition +Diana Kalenova +Department of Information Technology, Laboratory of Information Processing, +Lappeenranta University of Technology"
+2a08147bf88041c6e0354e26762b4e4d65d5163f,Trimmed Event Recognition ( Moments in Time ) : Submission to ActivityNet Challenge 2018,"Trimmed Event Recognition (Moments in Time): +Submission to ActivityNet Challenge 2018 +Dongyang Cai"
+2a3227f54286d8a36736663781f194167f2b6582,Nonlinear Dimensionality Reduction for Discriminative Analytics of Multiple Datasets,"Nonlinear Dimensionality Reduction for +Discriminative Analytics of Multiple Datasets +Jia Chen, Gang Wang, Member, IEEE, and Georgios B. Giannakis, Fellow, IEEE"
+2ade545f25f5ba66295aeab3a89583e7cf6101b3,A Dataset for Airborne Maritime Surveillance Environments,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2017.2775524, IEEE +Transactions on Circuits and Systems for Video Technology +A Dataset for Airborne Maritime Surveillance +Environments +Ricardo Ribeiro, Member, IEEE, Gonc¸alo Cruz, Jorge Matos, Student, IST, +nd Alexandre Bernardino, Member, IEEE,"
2aec012bb6dcaacd9d7a1e45bc5204fac7b63b3c,Robust Registration and Geometry Estimation from Unstructured Facial Scans,"Robust Registration and Geometry Estimation from Unstructured Facial Scans Maxim Bazik1 and Daniel Crispell2"
+2ac31bc7a4dd0256166208dcc8d5dfa99347117e,A Window-Based Classifier for Automatic Video-Based Reidentification,"A Window-Based Classifier for Automatic +Video-Based Reidentification +Dario Figueira, Matteo Taiana, Jacinto C. Nascimento, Member, IEEE, and Alexandre Bernardino, Member, IEEE"
2ae139b247057c02cda352f6661f46f7feb38e45,Combining modality specific deep neural networks for emotion recognition in video,"Combining Modality Specific Deep Neural Networks for Emotion Recognition in Video Samira Ebrahimi Kahou1, Christopher Pal1, Xavier Bouthillier2, Pierre Froumenty1, @@ -8626,18 +29663,172 @@ Samira Ebrahimi Kahou1, Christopher Pal1, Xavier Bouthillier2, Pierre Froumenty1 Laboratoire d’Informatique des Systèmes Adaptatifs, Université de Montréal, Montréal, Canada {samira.ebrahimi-kahou, christopher.pal, {bouthilx, gulcehrc, memisevr, vincentp, courvila,"
+2a86bc520586f611771c2052b50ac52239414dd2,CrowdHuman: A Benchmark for Detecting Human in a Crowd,"CrowdHuman: A Benchmark for Detecting Human in a Crowd +Shuai Shao∗ Zijian Zhao∗ Boxun Li +Tete Xiao Gang Yu Xiangyu Zhang +Jian Sun +{shaoshuai, zhaozijian, liboxun, xtt, yugang, zhangxiangyu, +Megvii Inc. (Face++)"
+2a1deffc67ccb5f8ca5897ac3f31dac09af70f05,Robust Subspace Clustering via Tighter Rank Approximation,"Robust Subspace Clustering via Tighter Rank +Approximation +Zhao Kang +Computer Science Dept. +Southern Illinois University +Carbondale, IL, USA +Chong Peng +Computer Science Dept. +Southern Illinois University +Carbondale, IL, USA +Qiang Cheng +Computer Science Dept. +Southern Illinois University +Carbondale, IL, USA"
+2a83a51c9596ed796da52bdac49ca30e4eb04345,Eclectic Genetic Algorithm for Holistic Face Recognition in L ∞ Space,"Eclectic Genetic Algorithm for Holistic Face +Recognition in L∞ Space +C. Villegas, J. Climent, C.R. Murillo, A. Otero, C.R. Villegas"
+2a87f95e36938ca823b33c72a633d8d902d5cb86,xytocin Improves “Mind-Reading” in Humans,"PRIORITY COMMUNICATION +Oxytocin Improves “Mind-Reading” in Humans +Gregor Domes, Markus Heinrichs, Andre Michel, Christoph Berger, and Sabine C. Herpertz +Background: The ability to “read the mind” of other individuals, that is, to infer their mental state by interpreting subtle social cues, is +indispensable in human social interaction. The neuropeptide oxytocin plays a central role in social approach behavior in nonhuman +mammals. +Methods: In a double-blind, placebo-controlled, within-subject design, 30 healthy male volunteers were tested for their ability to infer +the affective mental state of others using the Reading the Mind in the Eyes Test (RMET) after intranasal administration of 24 IU oxytocin. +Results: Oxytocin improved performance on the RMET compared with placebo. This effect was pronounced for difficult compared with +easy items. +Conclusions: Our data suggest that oxytocin improves the ability to infer the mental state of others from social cues of the eye region. +Oxytocin might play a role in the pathogenesis of autism spectrum disorder, which is characterized by severe social impairment. +Key Words: Emotion, oxytocin, peptide, social cognition, theory of +T he ability to infer the internal state of another person to +dapt one’s own behavior is a cornerstone of all human +social interactions. Humans have to infer internal states +from external cues such as facial expressions in order to make +sense of or predict another person’s behavior, an ability that is +referred to as “mind-reading” (Siegal and Varley 2002; Stone et al +998). In particular, individuals with autism have distinct diffi-"
+2a6c7d5aa087233ff8a09bdaa34d5f76f3330a4f,A Survey of Efficient Regression of General-Activity Human Poses from Depth Images,"A Survey of Efficient Regression of General-Activity Hu- +man Poses from Depth Images +Wenye He +This paper presents a comprehensive review on regression-based method for human pose es- +timation. The problem of human pose estimation has been intensively studied and enabled +many application from entertainment to training. Traditional methods often rely on color im- +ge only which cannot completely ambiguity of joint’s 3D position, especially in the complex +ontext. With the popularity of depth sensors, the precision of 3D estimation has significant +improvement. In this paper, we give a detailed analysis of state-of-the-art on human pose +estimation, including depth image based and RGB-D based approaches. The experimental +results demonstrate their advantages and limitation for different scenarios. +Introduction +Human pose estimation from images has been studied for decades in computer vision. As recent +development in cameras and sensors, depth images receive a wide spread of notice from researchers +from body pose estimation 1 to 3D reconstruction 2. Girshick et al.1 present an approach to find the +joints position in human body from depth images. They address the problem of general-activity +pose estimation. Their regression-based approach sucessfully computes the joint positions even +with occlusion. Their method can be view as a new combination of two existing works, implicit +shape models3 and Hough forest4. The following sections cover related works, explanation on the +method from testing to training, and result and comparison."
+2a2232f2972191a0606d588aa4f13c9f27d1972d,InstanceCut: From Edges to Instances with MultiCut,"InstanceCut: from Edges to Instances with MultiCut +Alexander Kirillov1 Evgeny Levinkov2 Bjoern Andres2 Bogdan Savchynskyy1 Carsten Rother1 +TU Dresden, Dresden, Germany +MPI for Informatics, Saarbr¨ucken, Germany"
+2a06341b40b3fd27483b2a8d8cbf86fddf45e423,Automatic generation of ground truth for the evaluation of obstacle detection and tracking techniques,"Automatic generation of ground truth for the evaluation of obstacle detection +nd tracking techniques +Hatem Hajri∗, Emmanuel Doucet∗†, Marc Revilloud∗, Lynda Halit∗, Benoit Lusetti∗, +Mohamed-Cherif Rahal∗ +Automated Driving Research Team, Institut VEDECOM, Versailles, France +InnoCoRe Team, Valeo, Bobigny, France"
+2acf319c5eac89cc9e0ed24633e4408dbd4a8a5b,The Effect of Distance Measures on the Recognition Rates of PCA and LDA Based Facial Recognition,"The Effect of Distance Measures on the Recognition Rates of PCA +nd LDA Based Facial Recognition +Philip Miller, Jamie Lyle +Digitial Image Processing +Clemson Universtiy +{pemille,"
+2a40917ef436000b22bc7c6f35400440ef673d36,Learning clustered sub-spaces for sketch-based image retrieval,"Learning Clustered Sub-spaces for Sketch-based Image Retrieval +Koustav Ghosal Ameya Prabhu +Riddhiman Dasgupta +koustav.ghosal∗ +meya.prabhu∗ +riddhiman.dasgupta∗ +Anoop M Namboodiri +noop† +Centre for Visual Information Technology, IIIT-Hyderabad, India"
+2a56a51490f6ccfaf6fcbdf546a5515bef5203a1,"Attention, please!: Comparing Features for Measuring Audience Attention Towards Pervasive Displays","Attention, please! Comparing Features for Measuring +Audience Attention Towards Pervasive Displays +Florian Alta, Andreas Bullingb, Lukas Meckea, Daniel Buscheka +LMU Munich +Munich, Germany"
+2aa362740ac9a2b304a74122da820e3829689842,"Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age","Past, Present, and Future of Simultaneous +Localization And Mapping: Towards the +Robust-Perception Age +Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, +Davide Scaramuzza, Jos´e Neira, Ian Reid, John J. Leonard"
2ad0ee93d029e790ebb50574f403a09854b65b7e,Acquiring linear subspaces for face recognition under variable lighting,"Acquiring Linear Subspaces for Face Recognition under Variable Lighting Kuang-Chih Lee, Student Member, IEEE, Jeffrey Ho, Member, IEEE, and David Kriegman, Senior Member, IEEE"
+2a8aedea2031128868f1c6dd44329c5bb7afc419,A Convex Duality Framework for GANs,"A Convex Duality Framework for GANs +Farzan Farnia∗ +David Tse∗"
+2acf7e58f0a526b957be2099c10aab693f795973,Bosphorus Database for 3D Face Analysis,"Bosphorus Database for 3D Face Analysis +Arman Savran1, Neşe Alyüz2, Hamdi Dibeklioğlu2, Oya Çeliktutan1, Berk Gökberk3, +Bülent Sankur1, and Lale Akarun2 +Boğaziçi University, Electrical and Electronics Engineering Department +Boğaziçi University, Computer Engineering Department +Philips Research, Eindhoven, The Netherlands"
+2ab9c36e19090ed9ac5295b3704708bdce80462d,Zero-Shot Learning via Category-Specific Visual-Semantic Mapping and Label Refinement,"Zero-Shot Learning via Category-Specific +Visual-Semantic Mapping +Li Niu, Jianfei Cai, and Ashok Veeraraghavan"
+2ac986ec18c3572ee4f922ba9a90ae374563491c,A New Approach of Human Segmentation from Photo Images,"International Journal of Scientific and Research Publications, Volume 5, Issue 1, January 2015 +ISSN 2250-3153 +A New Approach of Human Segmentation from Photo +Images +Ashwini Magar*, Prof.J.V.Shinde** +* Computer Department, Late G .N. Sapkal College Of Engineering, Savitribai Phule Pune University +** Computer Department, Late G .N .Sapkal College Of Engineering, Savitribai Phule Pune University"
+2a6327a8bdbd31e2c08863b96c4f09245db8cab7,Targets ' facial width-to-height ratio biases pain judgments ☆,"Journal of Experimental Social Psychology 74 (2018) 56–64 +Contents lists available at ScienceDirect +Journal of Experimental Social Psychology +journal homepage: www.elsevier.com/locate/jesp +Targets' facial width-to-height ratio biases pain judgments☆ +Jason C. Deska⁎, Kurt Hugenberg +Miami University, 501 East High Street, Oxford, OH 45056, United States +A R T I C L E I N F O +A B S T R A C T +Keywords: +Facial width-to-height ratio +Pain judgments +Pain perception +The accurate perception of others' pain is important for both perceivers and targets. Yet, like other person +perception judgments, pain judgments are prone to biases. Although past work has begun detailing character- +istics of targets that can bias pain judgments (e.g., race, gender), the current work examines a novel source of +ias inherent to all targets: structural characteristics of the human face. Specifically, we present four studies +demonstrating that facial width-to-height ratio, a stable feature of all faces, biases pain judgments. Compared to +those with low facial width-to-height ratio, individuals with high facial width-to-height ratio are perceived as +experiencing less pain in otherwise identical situations (Studies 1, 2, & 3), and as needing less pain medication to"
2ff9618ea521df3c916abc88e7c85220d9f0ff06,Facial Tic Detection Using Computer Vision,"Facial Tic Detection Using Computer Vision Christopher D. Leveille Advisor: Prof. Aaron Cass March 20, 2014"
+2f587ab6694fdcfe6bd2977120ebeb758e28d77f,Coupled Generative Adversarial Nets,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES +http://www.merl.com +Coupled Generative Adversarial Nets +Liu, M.-Y.; Tuzel, O. +TR2016-070 +June 2016"
+2f0c30d6970da9ee9cf957350d9fa1025a1becb4,Deformable Convolutional Networks,"Deformable Convolutional Networks +Jifeng Dai∗ Haozhi Qi∗,† Yuwen Xiong∗,† Yi Li∗,† Guodong Zhang∗,† Han Hu Yichen Wei +Microsoft Research Asia"
2fda461869f84a9298a0e93ef280f79b9fb76f94,OpenFace: An open source facial behavior analysis toolkit,"OpenFace: an open source facial behavior analysis toolkit Tadas Baltruˇsaitis Peter Robinson Louis-Philippe Morency"
+2f0d5cd2d25ea2f3add0139cf4b61f358435bab8,A New Effective System for Filtering Pornography Videos,"Tarek Abd El Hafeez / (IJCSE) International Journal on Computer Science and Engineering +Vol. 02, No. 09, 2010, 2847-2852 +A New Effective System for Filtering +Pornography Videos +Tarek Abd El-Hafeez +Department of Computer Science, +Faculty of Science, Minia University +El-Minia, Egypt"
2ffcd35d9b8867a42be23978079f5f24be8d3e35,Satellite based Image Processing using Data mining,"ISSN XXXX XXXX © 2018 IJESC Research Article Volume 8 Issue No.6 Satellite based Image Processing using Data mining @@ -8645,6 +29836,12 @@ E.Malleshwari1, S.Nirmal Kumar2, J.Dhinesh3 Professor1, Assistant Professor2, PG Scholar3 Department of Information Technology1, 2, Master of Computer Applications3 Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College, Avadi, Chennai, India"
+2fa16dc0ee50550c1bf58c410912d48cddbc3554,Search Tracker: Human-Derived Object Tracking in the Wild Through Large-Scale Search and Retrieval,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2016.2555718, IEEE +Transactions on Circuits and Systems for Video Technology +Search Tracker: Human-derived object tracking +in-the-wild through large-scale search and retrieval +Archith John Bency, Student Member, IEEE S. Karthikeyan,, Carter De Leo, Santhoshkumar Sunderrajan, +Member, IEEE and B. S. Manjunath, Fellow, IEEE"
2f7e9b45255c9029d2ae97bbb004d6072e70fa79,cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurvey,"Noname manuscript No. (will be inserted by the editor) vpaper.challenge in 2015 @@ -8654,6 +29851,9 @@ Shirakabe · Shin’ichi Sato · Hironori Hoshino · Ryo Kato · Kaori Abe · Takaaki Imanari · Naomichi Kobayashi · Shinichiro Morita · Akio Nakamura Received: date / Accepted: date"
+2f04c7aaac3a884088be550d1be51b4a0b585a2e,"Robust, Real-Time 3D Tracking of Multiple Objects with Similar Appearances","Robust, Real-Time 3D Tracking of Multiple Objects with Similar Appearances +Taiki Sekii +Panasonic System Networks R&D Lab. Co., Ltd."
2f489bd9bfb61a7d7165a2f05c03377a00072477,Structured Semi-supervised Forest for Facial Landmarks Localization with Face Mask Reasoning,"JIA, YANG: STRUCTURED SEMI-SUPERVISED FOREST Structured Semi-supervised Forest for Facial Landmarks Localization with Face @@ -8667,11 +29867,72 @@ Heng Yang2 Angran Lin1 Kwok-Ping Chan1 Ioannis Patras2"
+2f33884d0612fcc3f7eed66e1a4acc229860d6b5,Survey on Spatio-Temporal View Invariant Human Pose Recovery,"Survey on Spatio-Temporal View +Invariant Human Pose Recovery +Xavier Perez-Sala, Email: a;c, +Sergio Escalera, Email: b;c and +Cecilio Angulo, Email: a +CETpD-UPC Technical Research Center for Dependency Care and Autonomous +Living, Universitat Polit`ecnica de Catalunya, Ne`apolis, Rambla de l’Exposici´o, 59-69, +Dept. Mathematics, Universitat de Barcelona, Gran Via de les Corts Catalanes 585, +08800 Vilanova i la Geltru, Spain +Computer Vision Center, Campus UAB, Edifici 0, 08193, Bellaterra, Spain +08007, Barcelona, Spain"
+2f7452476910a7dbf6231b6b27aed67d9ed455d3,Seam carving for content-aware image resizing,"Seam Carving for Content-Aware Image Resizing +Shai Avidan +Mitsubishi Electric Research Labs +Ariel Shamir +The Interdisciplinary Center & MERL +Figure 1: A seam is a connected path of low energy pixels in an image. On the left is the original image with one horizontal and one vertical +seam. In the middle the energy function used in this example is shown (the magnitude of the gradient), along with the vertical and horizontal +path maps used to calculate the seams. By automatically carving out seams to reduce image size, and inserting seams to extend it, we achieve +ontent-aware resizing. The example on the top right shows our result of extending in one dimension and reducing in the other, compared to +standard scaling on the bottom right."
+2f29b13fcf7a92a3cc438014068f11f9e45d62be,"AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups","AMIGOS: A dataset for Mood, personality and +ffect research on Individuals and GrOupS +Juan Abdon Miranda-Correa, Student Member, IEEE, Mojtaba Khomami Abadi, Student Member, IEEE, +Nicu Sebe, Senior Member, IEEE, and Ioannis Patras, Senior Member, IEEE"
+2fe0555f2b92a81992247519cb8fdc047069e2b0,A Semantic World Model for Urban Search and Rescue Based on Heterogeneous Sensors,"This is a preprint of a paper which appeared in the Proceedings of +RoboCup 2010: Robot Soccer World Cup XIV +A Semantic World Model for Urban Search and +Rescue Based on Heterogeneous Sensors +Johannes Meyer2, Paul Schnitzspan1, Stefan Kohlbrecher1, Karen Petersen1, +Mykhaylo Andriluka1, Oliver Schwahn1, Uwe Klingauf2, Stefan Roth1, +Bernt Schiele1,3, and Oskar von Stryk1 +Department of Computer Science, TU Darmstadt, Germany +Department of Mechanical Engineering, TU Darmstadt, Germany +MPI Informatics, Saarbr¨ucken, Germany"
+2f23f7d08c7b8670289cfedd1e571f44a3bace8b,Contextual Information and Covariance Descriptors for People Surveillance: An Application for Safety of Construction Workers,"Hindawi Publishing Corporation +EURASIP Journal on Image and Video Processing +Volume 2011, Article ID 684819, 16 pages +doi:10.1155/2011/684819 +Research Article +Contextual Information and Covariance Descriptors for People +Surveillance: An Application for Safety of Construction Workers +Giovanni Gualdi,1 Andrea Prati,2 and Rita Cucchiara1 +DII, University of Modena and Reggio Emilia, 41122 Modena, Italy +DISMI, University of Modena and Reggio Emilia, 42122 Reggio Emilia, Italy +Correspondence should be addressed to Andrea Prati, +Received 30 April 2010; Revised 7 October 2010; Accepted 10 December 2010 +Academic Editor: Luigi Di Stefano +Copyright © 2011 Giovanni Gualdi et al. This is an open access article distributed under the Creative Commons Attribution +License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly +ited. +In computer science, contextual information can be used both to reduce computations and to increase accuracy. This paper +discusses how it can be exploited for people surveillance in very cluttered environments in terms of perspective (i.e., weak scene +alibration) and appearance of the objects of interest (i.e., relevance feedback on the training of a classifier). These techniques are +pplied to a pedestrian detector that uses a LogitBoost classifier, appropriately modified to work with covariance descriptors which"
2f59f28a1ca3130d413e8e8b59fb30d50ac020e2,Children Gender Recognition Under Unconstrained Conditions Based on Contextual Information,"Children Gender Recognition Under Unconstrained Conditions Based on Contextual Information Riccardo Satta, Javier Galbally and Laurent Beslay Joint Research Centre, European Commission, Ispra, Italy Email:"
+2f43bfedb8cffc9e44de9f95db80b26395a29cc8,Generalized Hadamard-Product Fusion Operators for Visual Question Answering,"Generalized Hadamard-Product Fusion Operators +for Visual Question Answering +Brendan Duke∗†, Graham W. Taylor∗†‡ +School of Engineering, University of Guelph +Vector Institute for Artificial Intelligence +Canadian Institute for Advanced Research"
2f78e471d2ec66057b7b718fab8bfd8e5183d8f4,An Investigation of a New Social Networks Contact Suggestion Based on Face Recognition Algorithm,"SOFTWARE ENGINEERING VOLUME: 14 | NUMBER: 5 | 2016 | DECEMBER An Investigation of a New Social Networks @@ -8695,6 +29956,64 @@ Berkeley, CA 94720" 2f8ef26bfecaaa102a55b752860dbb92f1a11dc6,A Graph Based Approach to Speaker Retrieval in Talk Show Videos with Transcript-Based Supervision,"A Graph Based Approach to Speaker Retrieval in Talk Show Videos with Transcript-Based Supervision Yina Han 1, Guizhong Liu, Hichem Sahbi, Gérard Chollet"
+2fd9ecb40df6c7cd4f27c047223a1e45aae1bb95,Feature-based affine-invariant localization of faces,"Feature-based affine-invariant localization of +faces +M. Hamouz, J. Kittler, J.-K. Kamarainen, P. Paalanen, H. K¨alvi¨ainen, J. Matas"
+2fdb3576715829aa9bbaf74825236bbb71d06f1a,Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification,"Where-and-When to Look: Deep Siamese Attention +Networks for Video-based Person Re-identification +Lin Wu, Yang Wang, Junbin Gao, Xue Li"
+2f3f4e0c8a9c63e714a10a6711c67f5e84e4c7c1,IoT Based Embedded Smart Lock Control System,"ISSN XXXX XXXX © 2016 IJESC +Research Article Volume 6 Issue No. 11 +IoT Based Embedded Smart Lock Control System +Rohith R1, J. Nageswara Reddy2, K. Ravi Kiran3 +M.Tech, Embedded Systems, CM RCET, Hyderabad, India 1 +Assistant Professor, Depart ment of ECE, CM RCET, Hyderabad, India2 +Assistant Professor, Depart ment, of ECE, CM RCET, Hyderabad, India3 +INTRODUCTION +Abstrac t: +Smart ho me security and re mote monitoring have become vita l and indispensable in recent times, and with the advent of new con cepts +like Internet of Things and development of advanced authentication and security technologies, the need for smarter security s ystems +has only been growing. The design and development of an intelligent web -based door lock control system using face recognition +technology, for authentication, re mote monitoring of visitors and re mote control of s mart door loc k has been reported in th is paper. +This system uses Haar-like features for face detection and Local Binary Pattern Histogram (LBPH) fo r face recognition. The system +lso includes a web-based remote monitoring, an authentication module, and a bare-bones embedded IoT server, which transmits the +live pictures of the visitors via email a long with an SMS notification, and the owner can then remotely control the lock by responding +to the email with predefined security codes to unlock the door. This system finds a wide application in sma rt homes where the +physical presence of the owner at all times is not possible, and where a remote authentication and control is desired. The system has +een imple mented and tested using the Raspberry Pi 2 board, Python along with OpenCV are used to program the various face +recognition and control modules."
+2f000034f040f6a23c756671477f5f573514af8a,Learning Transferable Distance Functions for Human Action Recognition and Detection,"-)41/ 64)5.-4)*- ,156)+- .7+615 +.4 07) )+61 4-+/161 ), +,-6-+61 +9AEC ;=C +*-C 5KJDA=IJ 7ELAHIEJO +DE= % += 6DAIEI E F=HJE= BKBEAJ +B JDA HAGKEHAAJI BH JDA B +=IJAH B 5?EA?A +E JDA 5?D ++FKJEC 5?EA?A +? 9AEC ;=C +51 .4)5-4 718-4516; +5FHEC +) HECDJI 0MALAH E MEJD JDA ++FOHECDJ )?J B JDEI MH =O >A MEJDKJ +=KJDHE=JE JDA BH .=EH ,A=EC 6DAHABHA +B JDEI MH BH JDA FKHFIAI B FHEL=JA +HAIA=H?D ?HEJE?EI HALEAM AMI HAFHJEC EI EAO J +>A E MEJD JDA =M F=HJE?K=HO EB =FFHFHE=JAO"
+2fdc469096f72533726964260c80b4c14ae62fab,A Kernel Maximum uncertainty Discriminant Analysis and its Application to Face Recognition,"A KERNEL MAXIMUM UNCERTAINTY DISCRIMINANT +ANALYSIS AND ITS APPLICATION TO FACE RECOGNITION +Department of Electrical Engineering, Centro Universitario da FEI, FEI, Sao Paulo, Brazil +Carlos Eduardo Thomaz +Gilson Antonio Giraldi +Department of Computer Science, National Laboratory for Scientific Computing, LNCC, Rio de Janeiro, Brazil +Keywords:"
+2fce767ad830e0203d62ce30bbe75213b959d19c,Histogram of Log-Gabor Magnitude Patterns for face recognition,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) +978-1-4799-2893-4/14/$31.00 ©2014 IEEE +School of Information and Communication Engineering, +{yijun, +Jun Yi†, Fei Su†‡ +. INTRODUCTION"
2f17f6c460e02bd105dcbf14c9b73f34c5fb59bd,Robust Face Recognition Using the Deep C2D-CNN Model Based on Decision-Level Fusion,"Article Robust Face Recognition Using the Deep C2D-CNN Model Based on Decision-Level Fusion @@ -8711,11 +30030,76 @@ Received: 20 May 2018; Accepted: 25 June 2018; Published: 28 June 2018" y One-per-Class Compensated Reconstruction Rule Roberto D’Ambrosio and Paolo Soda Integrated Research Centre, Universit´a Campus Bio-Medico of Rome, Rome, Italy"
+2fa1629d75a03b950c56bf9b3430b2983abd7881,Learning geometrical transforms between multi camera views using Canonical Correlation Analysis,"CONRAD, MESTER: LEARNING GEOMETRICAL TRANSFORMS USING CCA +Learning geometrical transforms between +multi camera views using Canonical +Correlation Analysis +Christian Conrad +Rudolf Mester +Visual Sensorics and Information +Processing Lab, Goethe University +Frankfurt am Main, Germany +Computer Vision Laboratory +Electr. Eng. Dept. (ISY) +Linköping University, Sweden"
+2f529605ed776d4fbeac2d73054247b495504ac7,Person Re-identification for Real-world Surveillance Systems,"Person Re-identification for Real-world +Surveillance Systems +Furqan M. Khan and Fran¸cois Br´emond +INRIA Sophia Antipolis - M´editerran´ee +004 Route des Lucioles, Sophia Antipolis +{furqan.khan |"
+2f3125bf303bca19d9cdc9ffe1de2aacf7a23023,In-Bed Pose Estimation: Deep Learning with Shallow Dataset,"JOURNAL OF , VOL. , NO. , MONTH YEAR +In-Bed Pose Estimation: +Deep Learning with Shallow Dataset +Shuangjun Liu, Yu Yin, and Sarah Ostadabbas"
+2f48f1cb1cfef964fa70d7868b87d81455e7be2e,A new image centrality descriptor for wrinkle frame detection in WCE videos,"MVA2013 IAPR International Conference on Machine Vision Applications, May 20-23, 2013, Kyoto, JAPAN +A new image centrality descriptor for wrinkle frame detection in +WCE videos. +Santi Segu´ı1,2, Ekaterina Zaytseva1,2, Michal Drozdzal1,2, Carolina Malagelada3, +Fernando Azpiroz3, Petia Radeva1,2 and Jordi Vitri`a1,2 +Computer Vision Center (CVC), Universitat Aut`onoma de Barcelona, Barcelona, Spain +Dept. Matem`atica Aplicada i An`alisis, Universitat de Barcelona, Barcelona, Spain +Digestive System Research Unit, Hospital Vall dHebron, Barcelona, Spain"
+2fc15f80080b4317cad60ad645300b49afddb19e,Low cognitive load strengthens distractor interference while high load attenuates when cognitive load and distractor possess similar visual characteristics.,"Atten Percept Psychophys +DOI 10.3758/s13414-015-0866-9 +Low cognitive load strengthens distractor interference while high +load attenuates when cognitive load and distractor possess similar +visual characteristics +Takehiro Minamoto & Zach Shipstead & Naoyuki Osaka & +Randall W. Engle +# The Psychonomic Society, Inc. 2015"
+2fc2250d843326f3eefab1941e5a6e54eef239b3,Appearance Based Facial Recognition System Using Dhmm with Linear Discriminant Analysis,"Daffodil International University +Institutional Repository +DIU Journal of Science and Technology +Volume 10, Issue 1-2, July 2015 +016-06-18 +Appearance Based Facial Recognition +System Using Dhmm with Linear +Discriminant Analysis +Islam, Md. Rabiul +http://hdl.handle.net/20.500.11948/1487 +Downloaded from http://dspace.library.daffodilvarsity.edu.bd, Copyright Daffodil International University Library"
2f13dd8c82f8efb25057de1517746373e05b04c4,Evaluation of state-of-the-art algorithms for remote face recognition,"EVALUATION OF STATE-OF-THE-ART ALGORITHMS FOR REMOTE FACE RECOGNITION Jie Ni and Rama Chellappa Department of Electrical and Computer Engineering and Center for Automation Research, University of Maryland, College Park, MD 20742, USA"
+2fa241edb56734539c3b3487eda159e0b3e0f31c,Kinematic Pose Rectification for Performance Analysis and Retrieval in Sports,"Kinematic Pose Rectification for Performance Analysis and Retrieval in Sports +Dan Zecha, Moritz Einfalt, Christian Eggert and Rainer Lienhart +Multimedia Computing and Computer Vision Lab +University of Augsburg"
+2f77c0908716b0febfda19ff6a0e2970c23af440,A face recognition system dealing with expression variant faces,"A face recognition system dealing with expression variant faces +Stefano Arca∗, Paola Campadelli, Raffaella Lanzarotti, Giuseppe Lipori +Dipartimento di Scienze dell’Informazione +Universit`a degli Studi di Milano +Via Comelico, 39/41 20135 Milano, Italy"
+2f02328dc09396e37e159141c5e21bef3e6ff06e,Combining face detection and people tracking in video sequences,"Author manuscript, published in ""The 3rd International Conference on Imaging for Crime Detection and Prevention - ICDP09, +Kingston Upon Thames (London) : Royaume-Uni (2009)"""
+2f3a67394deb32f265bcff9daf2c829d4be36336,Improving Visual Relationship Detection Using Semantic Modeling of Scene Descriptions,"Improving Visual Relationship Detection using +Semantic Modeling of Scene Descriptions +Stephan Baier1, Yunpu Ma1,2, and Volker Tresp1,2 +Ludwig Maximilian University, 80538 Munich, Germany +Siemens AG, Corporate Technology, Munich, Germany"
2fa1fc116731b2b5bb97f06d2ac494cb2b2fe475,A novel approach to personal photo album representation and management,"A novel approach to personal photo album representation nd management Edoardo Ardizzone, Marco La Cascia, and Filippo Vella @@ -8725,12 +30109,22 @@ Viale delle Scienze, 90128, Palermo, Italy" Algorithm for Face Video Enhancement Junwen Wu, Mohan Trivedi, Bhaskar Rao CVRR Lab, UC San Diego, La Jolla, CA 92093, USA"
+2f349ec19443523bc6c1e4b15fb677b1c188e253,Finding Time Series Motifs in Disk-Resident Data,"Finding Time Series Motifs in Disk-Resident Data +Abdullah Mueen, Eamonn Keogh +Nima Bigdely-Shamlo +Department of Computer Science and Engineering +University of California, Riverside, USA +{mueen,"
2f95340b01cfa48b867f336185e89acfedfa4d92,Face expression recognition with a 2-channel Convolutional Neural Network,"Face Expression Recognition with a 2-Channel Convolutional Neural Network Dennis Hamester, Pablo Barros, Stefan Wermter University of Hamburg — Department of Informatics Vogt-K¨olln-Straße 30, 22527 Hamburg, Germany http://www.informatik.uni-hamburg.de/WTM/"
+2fa3ad0329386bf9f55eb2c011e031ca71a11299,Weakly-supervised Semantic Parsing with Abstract Examples,
+2fa4f66a7c3846a189ea1f962592d7c20d9683b1,Object Detection with YOLO on Artwork Dataset,"Object Detection with YOLO on Artwork Dataset +Yihui He∗ +Computer Science Department, Xi’an Jiaotong University"
2faa09413162b0a7629db93fbb27eda5aeac54ca,Quantifying how lighting and focus affect face recognition performance,"NISTIR 7674 Quantifying How Lighting and Focus Affect Face Recognition Performance @@ -8741,6 +30135,25 @@ Bolme, D. Givens, G. H. Lui, Y. M."
433bb1eaa3751519c2e5f17f47f8532322abbe6d,Face Recognition,
+434ad689f9f8bc034fa8489f80f851686b8b449e,Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization,"A.RUIZ, X.BINEFA, J.VAN DE WEIJER: RMC-MIL FACIAL BEHAVIOR CATEGORIZATION 1 +Regularized Multi-Concept MIL for +weakly-supervised facial behavior +ategorization +Adria Ruiz1 +Joost Van de Weijer2 +Xavier Binefa1 +Universitat Pompeu Fabra (DTIC) +Barcelona, Spain +Centre de Visió per Computador +Barcelona, Spain"
+43bf6489abd63992b82f2008b4417a1638955f0c,Principal Angles Separate Subject Illumination Spaces in YDB and CMU-PIE,"Short Papers___________________________________________________________________________________________________ +Principal Angles Separate Subject +Illumination Spaces in YDB and CMU-PIE +J. Ross Beveridge, Member, IEEE, +Bruce A. Draper, Member, IEEE, +Jen-Mei Chang, Michael Kirby, +Holger Kley, and +Chris Peterson"
43bb20ccfda7b111850743a80a5929792cb031f0,Discrimination of Computer Generated versus Natural Human Faces,"PhD Dissertation International Doctorate School in Information and Communication Technologies @@ -8762,14 +30175,77 @@ Face authentication with undercontrolled pose and illumination Maria De Marsico · Michele Nappi · Daniel Riccio Received: 15 September 2010 / Revised: 14 December 2010 / Accepted: 17 February 2011 / Published online: 7 August 2011 © Springer-Verlag London Limited 2011"
+432be99dde7d93001044048501c72c70e4ea2927,People and Mobile Robot Classification Through Spatio-Temporal Analysis of Optical Flow,"June 3, 2015 +3:29 WSPC/INSTRUCTION FILE +People and mobile robot classification through spatio-temporal analysis +of optical flow +Plinio Moreno and Dario Figueira and Alexandre Bernardino and Jos´e Santos-Victor +Institute for Systems and Robotics (ISR/IST) +LARSyS, Instituto Superior T´ecnico +Universidade de Lisboa +{plinio, dfigueira, alex, +Lisboa, Portugal +The goal of this work is to distinguish between humans and robots in a mixed human- +robot environment. We analyze the spatio-temporal patterns of optical flow-based fea- +tures along several frames. We consider the Histogram of Optical Flow (HOF) and the +Motion Boundary Histogram (MBH) features, which have shown good results on people +detection. The spatio-temporal patterns are composed by groups of feature components +that have similar values on previous frames. The groups of features are fed into the +FuzzyBoost algorithm, which at each round selects the spatio-temporal pattern (i.e. +feature set) having the lowest classification error. The search for patterns is guided by +grouping feature dimensions, considering three algorithms: (a) similarity of weights from +dimensionality reduction matrices, (b) Boost Feature Subset Selection (BFSS) and (c)"
43f6953804964037ff91a4f45d5b5d2f8edfe4d5,Multi-feature fusion in advanced robotics applications,"Multi-Feature Fusion in Advanced Robotics Applications Zahid Riaz, Christoph Mayer, Michael Beetz, Bernd Radig Institut für Informatik Technische Universität München D-85748 Garching, Germany"
+430482d92007a3eec7009a2603aa5c1f2e63f661,Synaesthesia: mechanisms and broader traits,"Synaesthesia: mechanisms and broader traits. +Agnieszka Barbara Janik +Department of Psychology +Goldsmiths University of London +PhD in Psychology +I, Agnieszka Barbara Janik, confirm that the work presented in this thesis is my own. +Where information has been derived from other sources, I confirm that this has been +indicated in the thesis."
+43a2c871450ba4d8888e8692aa98cb10e861ea71,Learning Generative ConvNet with Continuous Latent Factors by Alternating Back-Propagation,"Alternating Back-Propagation for Generator Network +Tian Han †, Yang Lu †, Song-Chun Zhu, Ying Nian Wu +Department of Statistics, University of California, Los Angeles, USA"
439ec47725ae4a3660e509d32828599a495559bf,Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation and Evaluation,"Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation nd Evaluation"
+43de246e9cc197623e27ab41a69530a8d121c77e,Developmental disruption of amygdala transcriptome and socioemotional behavior in rats exposed to valproic acid prenatally,"Barrett et al. Molecular Autism (2017) 8:42 +DOI 10.1186/s13229-017-0160-x +R ES EAR CH +Developmental disruption of amygdala +transcriptome and socioemotional behavior +in rats exposed to valproic acid prenatally +Catherine E. Barrett 1,2*, Thomas M. Hennessey1,2, Katelyn M. Gordon1,2, Steve J. Ryan1,2, Morgan L. McNair1,2, +Kerry J. Ressler3 and Donald G. Rainnie1,2 +Open Access"
+43c76cf17767a43a345cd1a8d7c08d18578b53ec,Boosting Color Feature Selection for Color Face Recognition,"Accepted Manuscript for Publication in IEEE Transaction on Image Processing +Boosting Color Feature Selection for Color Face Recognition +Jae Young Choi, Student Member, IEEE, Yong Man Ro, Senior Member, IEEE, and +Konstantinos N. Plataniotis, Senior Member, IEEE"
+43fbe350681185ec9a18991dbcb19d694ce4f245,The Perspective Face Shape Ambiguity,"The Perspective Face Shape Ambiguity +William A. P. Smith"
+432326edbc598774315a0def91d1fc224d732922,Classification of Diseased Arecanut based on Texture Features,"International Journal of Computer Applications (0975 – 8887) +Recent Advances in Information Technology, 2014 +Classification of Diseased Arecanut based on Texture +Suresha M +Department of Computer +Science +Kuvempu University +Karnataka, India +Features +Ajit Danti +Department of MCA +JNN College of Engineering +Karnataka, India +S. K Narasimhamurthy +Department of Mathematics +Kuvempu University +Karnataka, India"
434bf475addfb580707208618f99c8be0c55cf95,DeXpression: Deep Convolutional Neural Network for Expression Recognition,"UNDER CONSIDERATION FOR PUBLICATION IN PATTERN RECOGNITION LETTERS DeXpression: Deep Convolutional Neural Network for Expression Recognition @@ -8787,6 +30263,8 @@ Open Access Effective hyperparameter optimization using Nelder-Mead method in deep learning Yoshihiko Ozaki1,2, Masaki Yano1,2 and Masaki Onishi1,2*"
+43e11904ca961006be79f650025b5d8fbac9913f,Unsupervised Deep Video Hashing with Balanced Rotation,"Unsupervised Deep Video Hashing with Balanced Rotation +IJCAI Anonymous Submission 2367"
4362368dae29cc66a47114d5ffeaf0534bf0159c,"Performance Analysis of FDA Based Face Recognition Using Correlation, ANN and SVM","UACEE International Journal of Artificial Intelligence and Neural Networks ISSN:- 2250-3749 (online) Performance Analysis of FDA Based Face Recognition Using Correlation, ANN and SVM @@ -8813,6 +30291,20 @@ Tensors Amit Agrawal, Ramesh Raskar, Rama Chellappa TR2006-058 June 2006"
+43c1bf9bd7b18c9603324c328f0f2696278c5327,Tracking Multiple Players using a Single Camera,"Noname manuscript No. +(will be inserted by the editor) +Tracking Multiple Players using a Single Camera +Horesh BenShitrit · Mirko Raca · Fran¸cois +Fleuret · Pascal Fua +Received: date / Accepted: date"
+439da29cf857151f386e6af488b2d60c098c4fd8,Person Authentication Using Color Face Recognition,"Kiran Davakhar et al. Int. Journal of Engineering Research and Applications www.ijera.com +Vol. 3, Issue 5, Sep-Oct 2013, pp.178-182 +RESEARCH ARTICLE OPEN ACCESS +Person Authentication Using Color Face Recognition +Kiran Davakhar1, S. B. Mule2, Achala Deshmukh3 +(Department of E&TC, Sinhgad COE, Vadgaon, Pune, Pune University, India) +(Department of E&TC, Sinhgad COE, Vadgaon, Pune, Pune University, India) +(Department of E&TC, Sinhgad COE, Vadgaon, Pune, Pune University, India)"
43476cbf2a109f8381b398e7a1ddd794b29a9a16,A Practical Transfer Learning Algorithm for Face Verification,"A Practical Transfer Learning Algorithm for Face Verification Xudong Cao David Wipf @@ -8824,6 +30316,58 @@ for Facial Expression Recognition Caifeng Shan and Tommaso Gritti Philips Research, High Tech Campus 36, Eindhoven 5656 AE, The Netherlands {caifeng.shan,"
+4335d53e763b2caf20f06928cd420ae09e5041ad,Discrete-continuous optimization for multi-target tracking,"Discrete-Continuous Optimization for Multi-Target Tracking +Anton Andriyenko1 +Konrad Schindler2 +Stefan Roth1 +Department of Computer Science, TU Darmstadt +Photogrammetry and Remote Sensing Group, ETH Z¨urich"
+43d073d3fdc22f0d74793fdac47ff56b66c95990,Online Localization and Prediction of Actions and Interactions,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +Online Localization and Prediction of +Actions and Interactions +Khurram Soomro, Member, IEEE, Haroon Idrees, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
+43d4927f5113c5e376ab05d41e33063a6d06d727,Pedestrian Detection: Exploring Virtual Worlds,"Pedestrian Detection: Exploring Virtual Worlds +Javier Mar´ın +Computer Vision Center, +Universitat Aut`onoma de Barcelona, Spain +David Ger´onimo, David V´azquez, Antonio M. L´opez +Computer Vision Center and Computer Science Department, +Universitat Aut`onoma de Barcelona, Spain +Introduction +The objective of advanced driver assistance systems (ADAS) is to improve traffic safety by assisting the driver +through warnings and by even automatically taking active countermeasures. Two examples of successfully com- +mercialised ADAS are lane departure warnings and adaptive cruise control, which make use of either active +(e.g., radar) or passive (e.g., cameras) sensors to keep the vehicle on the lane and maintain a safe distance from +the preceding vehicle, respectively. One of the most complex safety systems are pedestrian protection systems +(PPSs) (Bishop, 2005; Gandhi & Trivedi, 2007; Enzweiler & Gavrila, 2009; Ger´onimo et al., 2010), which are +specialised in avoiding vehicle-to-pedestrian collisions. In fact, this kind of accidents results in approximately +50000 injuries and 7000 killed pedestrians every year just in the European Union (UN-ECE, 2007). Similar +statistics apply to the United States, while underdeveloped countries are increasing theirs year after year. In the +ase of PPSs, the most promising approaches make use of images as main source of information, as can be seen +in the large amount of proposals exploiting them (Ger´onimo et al., 2010). Hence, the core of a PPS is a forward +facing camera that acquires images and processes them using Computer Vision techniques. In fact, the Computer"
+434627a03d4433b0df03058724524c3ac1c07478,Online Multi-Target Tracking With Unified Handling of Complex Scenarios,"IEEE TRANSANCTIONS ON IMAGE PROCESSING, VOL. XX, NO. XX, NOVEMBER 2014 +Online Multi-Target Tracking +with Unified Handling of Complex Scenarios +Huaizu Jiang, Jinjun Wang, Yihong Gong, Senior Member, IEEE +Na Rong, Zhenhua Chai, and Nanning Zheng, Fellow, IEEE"
+431fc5903ab4853820eac6614073c5b7aec0ac31,Semantic-visual concept relatedness and co-occurrences for image retrieval,"978-1-4673-2533-2/12/$26.00 ©2012 IEEE +ICIP 2012"
+434fe2cca3321c08ef30a0076864298cf608e0d5,Multiple Human Tracking in High-Density Crowds,"Multiple Human Tracking in High-Density Crowds +Irshad Ali1, Matthew N. Dailey 2 +Computer Science and Information Management Program, Asian Institute of Technology +(AIT), Pathumthani, Thailand"
+43cb50f669a0d492256d11c6cc4128ba0ce79a3e,Per-Pixel Feedback for improving Semantic Segmentation,"Indian Institute of Technology Roorkee +Department of Mathematics +Per-Pixel Feedback for improving Semantic +Segmentation +Aditya Ganeshan +Submitted in part fulfilment of the requirements for the degree of +Integrated Masters of Science in Applied Mathematics, May 2017"
+434a0aebf3522638d75614b0de1f0c2dcc1b19f1,Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers,"Visual Analytics in Deep Learning: +An Interrogative Survey for the Next Frontiers +Fred Hohman, Member, IEEE, Minsuk Kahng, Member, IEEE, Robert Pienta, Member, IEEE, +nd Duen Horng Chau, Member, IEEE"
43b8b5eeb4869372ef896ca2d1e6010552cdc4d4,Large-scale Supervised Hierarchical Feature Learning for Face Recognition,"Large-scale Supervised Hierarchical Feature Learning for Face Recognition Jianguo Li, Yurong Chen Intel Labs China"
@@ -8838,6 +30382,11 @@ Computer Science, U.C. Berkeley Computer Science, UMass Amherst Jitendra Malik Computer Science, U.C. Berkeley"
+43e3cd896d4dada4114a8961b98ae9f6d6ff9401,Image2speech: Automatically generating audio descriptions of images,"Image2speech: Automatically generating audio descriptions of images +Mark Hasegawa-Johnson1, Alan Black2, Lucas Ondel3, Odette Scharenborg4, Francesco Ciannella2 +. University of Illinois, Urbana, IL USA 2. Carnegie-Mellon University, Pittsburgh, PA USA +. Brno University of Technology, Brno, Czech Republic +. Centre for Language Studies, Radboud University, Nijmegen, Netherlands"
43fb9efa79178cb6f481387b7c6e9b0ca3761da8,Mixture of parts revisited: Expressive part interactions for Pose Estimation,"Mixture of Parts Revisited: Expressive Part Interactions for Pose Estimation Anoop R Katti IIT Madras @@ -8845,6 +30394,13 @@ Chennai, India Anurag Mittal IIT Madras Chennai, India"
+4332314ac4ab56153f68a9e55e92b3659e93a5b4,Learning Collective Crowd Behaviors with Dynamic Pedestrian-Agents,"Int J Comput Vis +DOI 10.1007/s11263-014-0735-3 +Learning Collective Crowd Behaviors with Dynamic +Pedestrian-Agents +Bolei Zhou · Xiaoou Tang · Xiaogang Wang +Received: 9 September 2013 / Accepted: 24 May 2014 +© Springer Science+Business Media New York 2014"
43ed518e466ff13118385f4e5d039ae4d1c000fb,Classification of Occluded Objects Using Fast Recurrent Processing,"Classification of Occluded Objects using Fast Recurrent Processing Ozgur Yilmaza,∗ @@ -8852,6 +30408,14 @@ Turgut Ozal University, Department of Computer Engineering, Ankara Turkey" 43d7d0d0d0e2d6cf5355e60c4fe5b715f0a1101a,Playlist Generation using Facial Expression Analysis and Task Extraction,"Pobrane z czasopisma Annales AI- Informatica http://ai.annales.umcs.pl Data: 04/05/2018 16:53:32 U M CS"
+88e3aefe454e72388bbbe7dfa0b74fcfc52032f0,Weighted Gradient Feature Extraction Based on Multiscale Sub-Blocks for 3D Facial Recognition in Bimodal Images,"Article +Weighted Gradient Feature Extraction Based on +Multiscale Sub-Blocks for 3D Facial Recognition in +Bimodal Images +Yingchun Guo *, Ruoyu Wei and Yi Liu * +School of Computer Science and Engineering, Hebei University of Technology, Tianjin 300400, China; +* Correspondence: (Y.G.); (Y.L.) +Received: 6 January 2018; Accepted: 19 February 2018; Published: 28 February 2018"
88c6d4b73bd36e7b5a72f3c61536c8c93f8d2320,Image patch modeling in a light field,"Image patch modeling in a light field Zeyu Li Electrical Engineering and Computer Sciences @@ -8862,6 +30426,31 @@ May 15, 2014" 889bc64c7da8e2a85ae6af320ae10e05c4cd6ce7,Using Support Vector Machines to Enhance the Performance of Bayesian Face Recognition,"Using Support Vector Machines to Enhance the Performance of Bayesian Face Recognition Zhifeng Li, Member, IEEE, and Xiaoou Tang, Senior Member, IEEE"
+88dc2b2f6d033b290ed56b844c98c3ee6efde80b,Experimental manipulation of face-evoked activity in the fusiform gyrus of individuals with autism.,"!""#$%&’(#)*+%,&$%-.,/*.&-+-%012%34&*+%5/#6+’$#(17 +8/2%9:%;+<(+=0+’%9>?> +FB0*#$""+’%F$1)"".*.G1%F’+$$ +H/I.’=&%J(-%K+G#$(+’+-%#/%L/G*&/-%&/-%M&*+$%K+G#$(+’+-%NB=0+’2%?>D9COP%K+G#$(+’+-%.II#)+2%Q.’(#=+’%R.B$+S%EDT +P?%Q.’(#=+’%;(’++(S%J./-./%M?!%EURS%5V +;.)#&*%N+B’.$)#+/)+ +FB0*#)&(#./%-+(&#*$S%#/)*B-#/G%#/$(’B)(#./$%I.’%&B("".’$%&/-%$B0$)’#<(#./%#/I.’=&(#./2 +""((<2WW,,,X#/I.’=&,.’*-X).=W$=<<W(#(*+Y)./(+/(Z(DP?DD??PE +L[<+’#=+/(&*%=&/#<B*&(#./%.I%I&)+T+6.\+-%&)(#6#(1%#/%(""+%IB$#I.’=%G1’B$%.I +#/-#6#-B&*$%,#(""%&B(#$= +‘#’$(%<B0*#$""+-%./2%>P%Q&1%9>?> +N+B’.$)#+/)+SS%‘#’$(%<B0*#$""+-%./2%>P%Q&1%9>?>%a#‘#’$(b +5KJ2%""((<2WW-[X-.#X.’GW?>X?>d>W?DPD>C??>>E:dE?dO +PLEASE SCROLL DOWN FOR ARTICLE +Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf +This article may be used for research, teaching and private study purposes. Any substantial or +systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or +distribution in any form to anyone is expressly forbidden. +The publisher does not give any warranty express or implied or make any representation that the contents +will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses"
+88bbedf7f6f0dcc830640c521acece28e67be356,Robust sparse coding for face recognition,"Robust Sparse Coding for +Face Recognition +Meng Yang, Lei Zhang, Jian Yang, David Zhang +Hong Kong Polytechnic Univ. +Presenter : 江振國"
88a898592b4c1dfd707f04f09ca58ec769a257de,MobileFace: 3D Face Reconstruction with Efficient CNN Regression,"MobileFace: 3D Face Reconstruction with Efficient CNN Regression Nikolai Chinaev1, Alexander Chigorin1, and Ivan Laptev1,2 @@ -8876,8 +30465,26 @@ Center for Visual Information Technology, IIIT Hyderabad, India" 8813368c6c14552539137aba2b6f8c55f561b75f,Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition,"Trunk-Branch Ensemble Convolutional Neural Networks for Video-based Face Recognition Changxing Ding, Student Member, IEEE, Dacheng Tao, Fellow, IEEE"
+886dfe069bd0f6bbb0a885e0bf2788007bfb737c,3-D Facial Expression Representation using B-spline Statistical Shape Model,"-D Facial Expression Representation using +B-spline Statistical Shape Model +Wei Quan, Bogdan J. Matuszewski, Lik-Kwan Shark, Djamel Ait-Boudaoud +Applied Digital Signal and Image Processing Research Centre +University of Central Lancashire +Preston PR1 2HE, UK"
883006c0f76cf348a5f8339bfcb649a3e46e2690,Weakly supervised pain localization using multiple instance learning,"Weakly Supervised Pain Localization using Multiple Instance Learning Karan Sikka, Abhinav Dhall and Marian Bartlett"
+88f5f9d92c4fa696457a824c3eec204da05ba6a4,XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings,"XGAN: Unsupervised Image-to-Image +Translation for Many-to-Many Mappings +Am´elie Royer1[0000−0002−8407−0705], Konstantinos Bousmalis2,6, Stephan +Gouws2, Fred Bertsch3, Inbar Mosseri4, Forrester Cole4, and Kevin Murphy5 +IST Austria, 3400 Klosterneuburg, Austria +Work done while at Google Brain London, UK +Google Brain, London, UK +{konstantinos, +Google Brain, Mountain View, USA +Google Research, Cambridge, USA +5 Google Research, Mountain View, USA +6 Currently at Deepmind, London, UK"
88850b73449973a34fefe491f8836293fc208580,XBeats-An Emotion Based Music Player,"www.ijaret.org Vol. 2, Issue I, Jan. 2014 ISSN 2320-6802 INTERNATIONAL JOURNAL FOR ADVANCE RESEARCH IN @@ -8900,6 +30507,32 @@ Vile Parle (W), Mumbai-400056." 88f2952535df5859c8f60026f08b71976f8e19ec,A neural network framework for face recognition by elastic bunch graph matching,"A neural network framework for face recognition by elastic bunch graph matching Francisco A. Pujol López, Higinio Mora Mora*, José A. Girona Selva"
+88c5baffa5522ea62ff5d5c41036b92e30d7e3c9,Who is who at different cameras. People re-identification using Depth Cameras,"Document downloaded from: +This paper must be cited as: +The final publication is available at +Copyright +Additional Information +http://dx.doi.org/10.1049/iet-cvi.2011.0140http://hdl.handle.net/10251/56627Institution of Engineering and Technology (IET)Albiol Colomer, AJ.; Albiol Colomer, A.; Oliver Moll, J.; Mossi García, JM. (2012). Who iswho at different cameras: people re-identification using depth cameras. IET ComputerVision. 6(5):378-387. doi:10.1049/iet-cvi.2011.0140."
+887cd2271ca5a58501786d49afa53139f48c66f3,"Visual orienting in children with autism: Hyper‐responsiveness to human eyes presented after a brief alerting audio‐signal, but hyporesponsiveness to eyes presented without sound","SHORT REPORT +Visual Orienting in Children With Autism: Hyper-Responsiveness +to Human Eyes Presented After a Brief Alerting Audio-Signal, +ut Hyporesponsiveness to Eyes Presented Without Sound +Johan Lundin Kleberg, Emilia Thorup, and Terje Falck-Ytter +Autism Spectrum Disorder (ASD) has been associated with reduced orienting to social stimuli such as eyes, but the +results are inconsistent. It is not known whether atypicalities in phasic alerting could play a role in putative altered +social orienting in ASD. Here, we show that in unisensory (visual) trials, children with ASD are slower to orient to +eyes (among distractors) than controls matched for age, sex, and nonverbal IQ. However, in another condition where +brief spatially nonpredictive sound was presented just before the visual targets, this group effect was reversed. Our +results indicate that orienting to social versus nonsocial stimuli is differently modulated by phasic alerting mecha- +nisms in young children with ASD. Autism Res 2017, 10: 246–250. VC 2016 The Authors Autism Research published +y Wiley Periodicals, Inc. on behalf of International Society for Autism Research. +Keywords: Autism; social orienting; eye tracking; phasic alerting; arousal; face perception +According to social orienting theories of Autism Spec- +trum Disorder (ASD), people with this condition orient +less or slower to socially salient stimuli than people +with typical development (TD; Dawson et al., 2004). +Further, it is assumed that reduced orienting early in +life may have cascading effects on both brain develop-"
887b7676a4efde616d13f38fcbfe322a791d1413,Deep Temporal Appearance-Geometry Network for Facial Expression Recognition,"Deep Temporal Appearance-Geometry Network for Facial Expression Recognition Injae Lee‡ Chunghyun Ahn‡ @@ -8908,18 +30541,152 @@ Heechul Jung† Sihaeng Lee† Sunjeong Park† Korea Advanced Institute of Science and Technology† Electronics and Telecommunications Research Institute‡ {heechul, haeng, sunny0414, {ninja,"
+88909ec19d2c6750f836e8b9c15ee3e1236b37e7,Local Learning with Deep and Handcrafted Features for Facial Expression Recognition,"Local Learning with Deep and Handcrafted Features +for Facial Expression Recognition +Mariana-Iuliana Georgescu1,2 +Radu Tudor Ionescu1,3 +Marius Popescu1,3 +University of Bucharest, 14 Academiei, Bucharest, Romania +Novustech Services, 12B Aleea Ilioara, Bucharest, Romania +SecurifAI, 21D Mircea Vod˘a, Bucharest, Romania +georgescu"
+887b7d34ebac80bbe3fb3792ed579dd82ff7e373,Query-driven iterated neighborhood graph search for scalable visual indexing,"Query-driven iterated neighborhood graph search for scalable +visual indexing∗ +Jingdong Wang† Xian-Sheng Hua‡ Shipeng Li† +Microsoft Corporation +Microsoft Research Asia +August 10, 2012"
8878871ec2763f912102eeaff4b5a2febfc22fbe,Human Action Recognition in Unconstrained Videos by Explicit Motion Modeling,"Human Action Recognition in Unconstrained Videos by Explicit Motion Modeling Yu-Gang Jiang, Qi Dai, Wei Liu, Xiangyang Xue, and Chong-Wah Ngo"
8855d6161d7e5b35f6c59e15b94db9fa5bbf2912,COGNITION IN PREGNANCY AND THE POSTPARTUM PERIOD COGNITIVE REORGANIZATION AND PROTECTIVE MECHANISMS IN PREGNANCY AND THE POSTPARTUM PERIOD By,COGNITION IN PREGNANCY AND THE POSTPARTUM PERIOD
+88132a786442ab8a5038d81164384c1c1f7231c8,Limited attentional bias for faces in toddlers with autism spectrum disorders.,"ORIGINAL ARTICLE +Limited Attentional Bias for Faces in Toddlers +With Autism Spectrum Disorders +Katarzyna Chawarska, PhD; Fred Volkmar, MD; Ami Klin, PhD +Context: Toddlers with autism spectrum disorders (ASD) +exhibit poor face recognition and atypical scanning pat- +terns in response to faces. It is not clear if face-processing +deficits are also expressed on an attentional level. Typical +individuals require more effort to shift their attention from +faces compared with other objects. This increased disen- +gagement cost is thought to reflect deeper processing of these +socially relevant stimuli. +Objective: To examine if attention disengagement from +faces is atypical in the early stages of ASD. +Design: Attention disengagement was tested in a varia- +tion of the cued attention task in which participants were +required to move their visual attention from face or non- +face central fixation stimuli and make a reactive saccade +to a peripheral target. The design involved diagnosis as +between-group factor and central fixation stimuli type"
+88590857138505ee524f3adf6da9c57352d917f2,Random Subspace Two-Dimensional PCA for Face Recognition,"Random Subspace Two-Dimensional PCA for +Face Recognition +Nam Nguyen, Wanquan Liu and Svetha Venkatesh +Department of Computing, Curtin University of Technology, WA 6845, Australia"
+8855755a72c148dfde84bb08ae65d58c260e70d4,Robust image classification: analysis and applications,"POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCESacceptée sur proposition du jury:Prof. P. Vandergheynst, président du juryProf. P. Frossard, directeur de thèseProf. J. Bruna, rapporteurProf. N. Paragios, rapporteurDr F. Fleuret, rapporteurRobust image classification: analysis and applicationsTHÈSE NO 7258 (2016)ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNEPRÉSENTÉE LE 16 DÉCEMBRE 2016 À LA FACULTÉ DES SCIENCES ET TECHNIQUES DE L'INGÉNIEURLABORATOIRE DE TRAITEMENT DES SIGNAUX 4PROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUE Suisse2016PARAlhussein FAWZI"
88bee9733e96958444dc9e6bef191baba4fa6efa,Extending Face Identification to Open-Set Face Recognition,"Extending Face Identification to Open-Set Face Recognition Cassio E. dos Santos Jr., William Robson Schwartz Department of Computer Science Universidade Federal de Minas Gerais Belo Horizonte, Brazil"
+8818dafda0cf230731ac2f962d8591c89a9fac09,xGEMs: Generating Examplars to Explain Black-Box Models,"xGEMs: Generating Examplars to Explain Black-Box +Models +Shalmali Joshi +UT Austin +Oluwasanmi Koyejo +Been Kim +Google Brain +Joydeep Ghosh +UT Austin"
88fd4d1d0f4014f2b2e343c83d8c7e46d198cc79,Joint action recognition and summarization by sub-modular inference,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE ICASSP 2016"
+9f22e0749405dfc3e3211474b933aa7514722e4b,Theory of mind - not emotion recognition - mediates the relationship between executive functions and social functioning in patients with schizophrenia.,"© Medicinska naklada - Zagreb, Croatia +Original paper +THEORY OF MIND - NOT EMOTION RECOGNITION - +MEDIATES THE RELATIONSHIP BETWEEN EXECUTIVE +FUNCTIONS AND SOCIAL FUNCTIONING IN PATIENTS +WITH SCHIZOPHRENIA +Michal Hajdúk1,2, Dana Kraj(cid:254)ovi(cid:254)ová2, Miroslava Zimányiová2, Viera Ko(cid:284)ínková2, +Anton Heretik1 & Ján Pe(cid:254)e(cid:278)ák2 +Department of Psychology, Faculty of Arts, Comenius University, Bratislava, Slovak Republic +Clinic of Psychiatry, Faculty of Medicine, Comenius University, Bratislava, Slovak Republic +received: 9.8.2017; +revised: 15.3.2018; +ccepted: 17.7.2018 +SUMMARY +Background: Dysfunction of social-cognitive abilities is one of the hallmark features of schizophrenia and is associated with +neurocognition and social functioning. The Green and Nuechterlein model proposed that social cognition mediates the relationship +etween neurocognition and functional outcome. We tested this hypothesis in schizophrenia patients in the everyday clinical setting. +Subjects and methods: Social cognition, executive function and social functioning were assessed in a group of 43 patients with +schizophrenia or schizoaffective disorder using a range of measures. +Results: Theory of mind was associated with executive functions and social functioning. Results of our mediation analysis"
+9f889c81bdb1d791e22c5f455baf32829b5b788b,The GRODE metrics: Exploring the performance of group detection approaches,"Exploring the Performance of Group Detection Approaches +The GRODE Metrics: +Francesco Setti +ISTC - CNR +via alla Cascata 56/C, I-38121 Trento"
+9fd5ecc538a9344814dc00b92beb45c54d5dff3e,NIC: A Robust Background Extraction Algorithm for Foreground Detection in Dynamic Scenes,"NIC: A Robust Background Extraction Algorithm +for Foreground Detection in Dynamic Scenes +Thien Huynh-The, Student Member, IEEE, Oresti Banos, Member, IEEE, Sungyoung Lee, Member, IEEE, +Byeong Ho Kang, Eun-Soo Kim, and Thuong Le-Tien, Member, IEEE"
+9f1319162974cb4d6125e8c6c52878ebc48eb8a7,Loss factors for learning Boosting ensembles from imbalanced data,"Loss Factors for Learning Boosting Ensembles +from Imbalanced Data +Roghayeh Soleymani∗, Eric Granger∗, Giorgio Fumera† +Laboratoire d’imagerie, de vision et d’intelligence artificielle, École de technologie supérieure, +Université du Québec, Montreal, Canada, +Dept. of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy, +Email: +Email:"
+9fede7e3fac47a4206a643c4647834e5680f2a8f,Results from a Real-time Stereo-based Pedestrian Detection System on a Moving Vehicle,"Results from a Real-time Stereo-based Pedestrian Detection System on +Moving Vehicle +Max Bajracharya, Baback Moghaddam, Andrew Howard, Shane Brennan, Larry H. Matthies"
+9f91fd3e9621b88769ecc330f362a591876f948f,Bicycle Detection Based On Multi-feature and Multi-frame Fusion in low-resolution traffic videos,"Bicycle Detection Based On Multi-feature and +Multi-frame Fusion in low-resolution traffic videos +Yicheng Zhang, Student Member, IEEE, and Qiang Ling, Senior Member, IEEE +Some other methods like using MSC-HOG method for +detection [12] or detecting tires of bicycles in videos [13] +lso can get good results, but they are either time consuming +or high quality videos required. Some new methods, such the +method based on HOG features with ROI in [14], try to use +more advanced hardware device like GPU to finish the great +mount of computation. +In summary, there are three major defects in the available +icycle detection methods based on image processing. First, +they require fine features for detection, which are hard to +extract, particularly for traffic videos with low-resolution. +Second, the processing time under these methods is usually +long and may not meet +the requirement of the real-time +detection. Last, they make the bicycle detection decision by the +information in a single frame, which may lead to misjudgment, +especially in the case of strong noise or light changing."
+9fc37eccb3d12329f208cb7d3a509024e182a100,Mel-cepstral feature extraction methods for image representation,Downloaded From: https://www.spiedigitallibrary.org/journals/Optical-Engineering on 9/28/2017 Terms of Use: https://spiedigitallibrary.spie.org/ss/TermsOfUse.aspx
+9fb1bd7d98a2fa79e1b9cb21b865ec7af0c1283f,Not All Distraction Is Bad: Working Memory Vulnerability to Implicit Socioemotional Distraction Correlates with Negative Symptoms and Functional Impairment in Psychosis,"Hindawi Publishing Corporation +Schizophrenia Research and Treatment +Volume 2014, Article ID 320948, 6 pages +http://dx.doi.org/10.1155/2014/320948 +Clinical Study +Not All Distraction Is Bad: Working Memory Vulnerability +to Implicit Socioemotional Distraction Correlates with Negative +Symptoms and Functional Impairment in Psychosis +Quintino R. Mano,1,2,3 Gregory G. Brown,1,2,3 Heline Mirzakhanian,1,2,3 +Khalima Bolden,1,2,3 Kristen S. Cadenhead,1,2,3 and Gregory A. Light1,2,3 +San Diego Veterans Affairs Healthcare System, San Diego, CA 92161, USA +VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, +San Diego, CA 92161, USA +Department of Psychiatry, University of California, San Diego, School of Medicine, San Diego, CA, USA +Correspondence should be addressed to Gregory G. Brown; +Received 31 July 2013; Revised 26 November 2013; Accepted 15 December 2013; Published 27 February 2014 +Academic Editor: Steven J. Siegel +Copyright © 2014 Quintino R. Mano et al. This is an open access article distributed under the Creative Commons Attribution +License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly +ited."
+9f483933bcc872771707dcf0acb1382411ffee94,Which Facial Expressions Can Reveal Your Gender? A Study With 3D Faces,"IN SUBMISSION TO IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY +Which Facial Expressions Can Reveal Your +Gender? A Study With 3D Faces +Baiqiang XIA"
9fa1be81d31fba07a1bde0275b9d35c528f4d0b8,Identifying Persons by Pictorial and Contextual Cues,"Identifying Persons by Pictorial and Contextual Cues Nicholas Leonard Pi¨el @@ -8927,12 +30694,38 @@ Thesis submitted for the degree of Master of Science Supervisor: Prof. dr. Theo Gevers April 2009"
+9f7c1b794805be34bc2091e02c382c5461e0bcb4,On-board real-time tracking of pedestrians on a UAV,"On-board real-time tracking of pedestrians on a UAV +Floris De Smedt, Dries Hulens, and Toon Goedem´e +ESAT-PSI-VISICS, KU Leuven, Belgium"
9f094341bea610a10346f072bf865cb550a1f1c1,Recognition and volume estimation of food intake using a mobile device,"Recognition and Volume Estimation of Food Intake using a Mobile Device Manika Puri Zhiwei Zhu Qian Yu Ajay Divakaran Harpreet Sawhney Sarnoff Corporation 01 Washington Rd, Princeton, NJ, 08540 {mpuri, zzhu, qyu, adivakaran,"
+9fbe2611b1e2a49199fdee96c2083da625ba57df,Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain,"J-STSP-PCSPHT-00370-2015.R1 +Leveraging Multi-Modal Sensing for Mobile +Health: a Case Review in Chronic Pain +Min S. H. Aung, Faisal Alquaddoomi, Andy Hsieh, Mashfiqui Rabbi, Longqi Yang, J.P. Pollak, +Tanzeem Choudhury, and Deborah Estrin +(cid:3)"
+9fb1d7cbf1baf5f347d159410d22912fcee1fdb1,Face Detection Using Ferns,"FACE DETECTION USING FERNS +Venkatesh Bala Subburaman Sébastien Marcel +Idiap-Com-01-2011 +DECEMBER 2011 +Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny +T +41 27 721 77 11 F +41 27 721 77 12 www.idiap.ch"
+6b7f27cff688d5305c65fbd90ae18f3c6190f762,Generative networks as inverse problems with Scattering transforms,"Published as a conference paper at ICLR 2018 +GENERATIVE NETWORKS AS INVERSE PROBLEMS +WITH SCATTERING TRANSFORMS +Tom´as Angles & St´ephane Mallat +´Ecole normale sup´erieure, Coll`ege de France, PSL Research University +75005 Paris, France"
+6bd6460ec06adc1bd69d9517d116fd1545c04ac7,Small sample scene categorization from perceptual relations,"In the Proceedings of the IEEE conference on Computer Vision and Pattern Recognition (CVPR), 2012 +Small Sample Scene Categorization from Perceptual Relations +Ilan Kadar and Ohad Ben-Shahar +Dept. of Computer Science, Ben-Gurion University +Beer-Sheva, Israel"
6bcfcc4a0af2bf2729b5bc38f500cfaab2e653f0,Facial Expression Recognition in the Wild Using Improved Dense Trajectories and Fisher Vector Encoding,"Facial expression recognition in the wild using improved dense trajectories and Fisher vector encoding Sadaf Afshar1 @@ -8940,6 +30733,37 @@ Albert Ali Salah2 Computational Science and Engineering Program, Bo˘gazic¸i University, Istanbul, Turkey Department of Computer Engineering, Bo˘gazic¸i University, Istanbul, Turkey {sadaf.afshar,"
+6bee77418af305d632b21eb03872a0d268eeebac,Understanding the Intrinsic Memorability of Images,"Understanding the Intrinsic Memorability of Images +Phillip Isola +Devi Parikh +TTI-Chicago +Antonio Torralba +Aude Oliva"
+6bbcec054017a6fd64af8bf325cb6e3e7244ba55,On the Benefits and the Limits of `p-norm Multiple Kernel Learning In Image Classification,"On the Benefits and the Limits of (cid:96)p-norm Multiple Kernel Learning In Image +Classification +Alexander Binder +Technical University of Berlin +Franklinstr. 28/29, 10587 Berlin, Germany +Shinichi Nakajima +NIKON Corporation +Optical Research Laboratory, Tokyo, Japan +Marius Kloft +Technical University of Berlin +Christina M¨uller +Technical University of Berlin +Wojciech Samek +Technical University of Berlin +Ulf Brefeld +Yahoo! Research +Barcelona, Spain +Klaus-Robert M¨uller +Technical University of Berlin +Motoaki Kawanabe"
+6b4da897dce4d6636670a83b64612f16b7487637,Learning from Simulated and Unsupervised Images through Adversarial Training,"This paper has been submitted for publication on November 15, 2016. +Learning from Simulated and Unsupervised Images through Adversarial +Training +Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Josh Susskind, Wenda Wang, Russ Webb +Apple Inc"
6b089627a4ea24bff193611e68390d1a4c3b3644,Cross-Pollination of Normalization Techniques From Speaker to Face Authentication Using Gaussian Mixture Models,"CROSS-POLLINATION OF NORMALISATION TECHNIQUES FROM SPEAKER TO FACE AUTHENTICATION USING GAUSSIAN @@ -8950,10 +30774,47 @@ Idiap-RR-03-2012 JANUARY 2012 Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny T +41 27 721 77 11 F +41 27 721 77 12 www.idiap.ch"
+6b5850c5a288fd26480ebcbbfc43172597e0d442,PHARMACOLOGICAL EFFECTS ON SOCIAL INTERACTION 1 Effects of Pharmacological Manipulations on Natural Social Interaction in Rhesus Macaques: A Pilot Investigation,"PHARMACOLOGICAL EFFECTS ON SOCIAL INTERACTION +Effects of Pharmacological Manipulations on +Natural Social Interaction in Rhesus Macaques: A Pilot Investigation +Angelica Fuentes +Spring, 2017 +Cognitive Science +Advisor: Steve W. Chang"
6be0ab66c31023762e26d309a4a9d0096f72a7f0,Enhance Visual Recognition under Adverse Conditions via Deep Networks,"Enhance Visual Recognition under Adverse Conditions via Deep Networks Ding Liu, Student Member, IEEE, Bowen Cheng, Zhangyang Wang, Member, IEEE, Haichao Zhang, Member, IEEE, and Thomas S. Huang, Life Fellow, IEEE"
+6b3c9c0e4d47bd960c0adc4d13ae524a5d9b94d1,Visual Multiple-Object Tracking for Unknown Clutter Rate,"THIS PAPER IS A PREPRINT OF A PAPER SUBMITTED TO IET COMPUTER VISION. IF ACCEPTED, THE COPY OF RECORD WILL BE AVAILABLE AT THE IET DIGITAL LIBRARY1 +Visual Multiple-Object Tracking for Unknown +Clutter Rate +Du Yong Kim"
+6bf58047438f54720e03252d50984d1a340a116a,Discriminative Autoencoders for Small Targets Detection,"Discriminative Autoencoders +for Small Targets Detection. +Sebastien Razakarivony +SAGEM D.S. – SAFRAN Group +CNRS UMR 6072 – University of Caen – ENSICAEN +Email: +Fr´ed´eric Jurie +CNRS UMR 6072 – University of Caen – ENSICAEN +Email:"
+6b0b10836197d7934f53080a39787b7d8d2b81f2,Detecting Granger-causal relationships in global spatio-temporal climate data via multitask learning,"Detecting Granger-causal relationships in global +spatio-temporal climate data via multi-task learning +Matthias Demuzere +Christina Papagiannopoulou +Diego G. Miralles +Ghent University +Ghent University +Ghent University +Niko E. C. Verhoest +Ghent University +Willem Waegeman +Ghent University"
+6b78f2ece211c2d1eb6699e1e057b7beb3e0b4a7,GM-PHD-Based Multi-Target Visual Tracking Using Entropy Distribution and Game Theory,"GM-PHD-Based Multi-Target Visual Tracking +Using Entropy Distribution and Game Theory +Xiaolong Zhou, Youfu Li, Senior Member, IEEE, Bingwei He, and Tianxiang Bai"
+6b2db002cbc5312e4796de4d4b14573df2c01648,Learning Hierarchical Features from Deep Generative Models,"Learning Hierarchical Features from Deep Generative Models +Shengjia Zhao 1 Jiaming Song 1 Stefano Ermon 1"
6b18628cc8829c3bf851ea3ee3bcff8543391819,Face recognition based on subset selection via metric learning on manifold,"Hong Shao, Shuang Chen, Jie-yi Zhao, Wen-cheng Cui, Tian-shu Yu, 2015. Face recognition based on subset selection via metric learning on manifold. 058. [doi:10.1631/FITEE.1500085] @@ -8965,12 +30826,93 @@ Contact: Shuang Chen E-mail: ORCID: http://orcid.org/0000-0001-7441-4749 Front Inform Technol & Electron Eng"
+6b02d73f097d745e58bb99a880e559b78c4594a1,Cross-Domain Face Verification: Matching ID Document and Self-Portrait Photographs,"Cross-Domain Face Verification: +Matching ID Document and Self-Portrait Photographs +Guilherme Folego 1,2 ∗ Marcus A. Angeloni 1,2 +Jos´e Augusto Stuchi 2,3 Alan Godoy 1,2 Anderson Rocha 2 +CPqD Foundation, Brazil +University of Campinas (Unicamp), Brazil +Phelcom Technologies, Brazil"
+6bf57ae6c63873253d1b95782f8c6b7bbc91b9ac,Semantic face segmentation from video streams in the wild,"UNIVERSITAT POLITÈCNICA DE CATALUNYA +Universitat de Barcelona +Universitat Rovira i Virgili +MASTER THESIS +Semantic face segmentation from video +streams in the wild +Author: +Deividas SKIPARIS +Academic Supervisor: +Dr. Sergio ESCALERA +Industry Supervisor: +Dr. Pascal LANDRY +A thesis submitted in fulfillment of the requirements +for the degree of Master of Artificial Intelligence +in the +Facultat d’Informàtica de Barcelona (FIB) +Facultat de Matemàtiques (UB) +Escola Tècnica Superior d’Enginyeria (URV) +June 16, 2017"
+6b6946ce943da5ba4bf6471609d3355cadec172e,Improvement of Facial Emotion Recognition Using Skin Color and Face Components,"International journal of Computer Science & Network Solutions April.2014-Volume 2.No4 +http://www.ijcsns.com +ISSN 2345-3397 +Improvement of Facial Emotion Recognition +Using Skin Color and Face Components +Department of Computer Engineering, khouzestan Science and Research Branch, Islamic Azad +kowsar azadmanesh, Reza javidan, S. Enayatolah Alavi +Computer Engineering and IT Department Shiraz University of Technology, Shiraz, Iran, +Department of computer Engineering, shahid chamran university, Ahvaz, Iran, +University, Ahvaz, Iran,"
+6b5438161cfe55d1bd44829db81f396819e9e6b9,Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning,"Wasserstein Dictionary Learning: +Optimal Transport-Based Unsupervised Nonlinear Dictionary Learning +Morgan A. Schmitz∗ , Matthieu Heitz† , Nicolas Bonneel† , Fred Ngol`e‡ , David Coeurjolly† , +Marco Cuturi§ , Gabriel Peyr´e¶, and Jean-Luc Starck∗"
+6b6791c0a3f06c356035747f7e5f87d54bc5a657,A Neuro Fuzzy approach for Facial Expression Recognition using LBP Histograms,"International Journal of Computer Theory and Engineering, Vol. 2, No. 2 April, 2010 +793-8201 +A Neuro Fuzzy approach for Facial Expression +Recognition using LBP Histograms +V. Gomathi, Dr. K. Ramar, and A. Santhiyaku Jeevakumar"
+6b59716a193d3f91f88277e4c8a0f4cd0b6873c4,Detection of Deception in the Mafia Party Game,"Detection of Deception in the Mafia Party Game +Sergey Demyanov +James Bailey +Kotagiri +Ramamohanarao +Christopher Leckie +Department of Computing and Information Systems +The University of Melbourne, Melbourne, VIC, Australia"
+6b55153f8d87bfd0dfb2f24eb2aa61d40e314cae,"Track, Then Decide: Category-Agnostic Vision-Based Multi-Object Tracking","Track, then Decide: Category-Agnostic Vision-based +Multi-Object Tracking +Aljoˇsa Oˇsep, Wolfgang Mehner, Paul Voigtlaender, and Bastian Leibe"
+6bca057c25b48fa7d1607e5701c46392ec906822,An ordered topological representation of 3D triangular mesh facial surface: Concept and applications,"Werghi et al. EURASIP Journal on Advances in Signal Processing 2012, 2012:144 +http://asp.eurasipjournals.com/content/2012/1/144 +RESEARCH +Open Access +An ordered topological representation of 3D +triangular mesh facial surface: concept and +pplications +Naoufel Werghi1*, Mohamed Rahayem2 and Johan Kjellander2"
+6b6943a138938c31b285c1bb11213b87404feddf,Multiple Instance Learning-Based Birdsong Classification Using Unsupervised Recording Segmentation,"Multiple Instance Learning-Based Birdsong Classification +Using Unsupervised Recording Segmentation +J. F. Ruiz-Mu˜noz, Mauricio Orozco-Alzate, G. Castellanos-Dominguez +Universidad Nacional de Colombia - Sede Manizales +{jfruizmu, morozcoa,"
+6b8a5a2d018356b396301b27156fd69dd18b1d82,A Study on the Impact of Wavelet Decomposition on Face Recognition Methods,"International Journal of Computer Applications (0975 – 8887) +Volume 87 – No.3, February 2014 +A Study on the Impact of Wavelet Decomposition on +Face Recognition Methods +M. M. Mohie El-Din1, Neveen. I. Ghali2, Ahmed. A. A. G1 and H. A. El Shenbary 1 +Department of Mathematics and Computer Science, Faculty of Science, Al-Azhar University, Cairo, Egypt +Assoc. Prof Computer Science, Faculty of Science, Al-Azhar University, Cairo. Egypt"
6b6493551017819a3d1f12bbf922a8a8c8cc2a03,Pose Normalization for Local Appearance-Based Face Recognition,"Pose Normalization for Local Appearance-Based Face Recognition Hua Gao, Hazım Kemal Ekenel, and Rainer Stiefelhagen Computer Science Department, Universit¨at Karlsruhe (TH) Am Fasanengarten 5, Karlsruhe 76131, Germany http://isl.ira.uka.de/cvhci"
+6b6e2c2ff6fcc5837523940c69cf2e9e94bc0503,Unsupervised Deep Video Hashing with Balanced Rotation,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+6b95a3dbec92071c8552576930e69455c70e529c,BEGAN: Boundary Equilibrium Generative Adversarial Networks,"BEGAN: Boundary Equilibrium Generative +Adversarial Networks +David Berthelot, Thomas Schumm, Luke Metz +Google"
6b6ff9d55e1df06f8b3e6f257e23557a73b2df96,Survey of Threats to the Biometric Authentication Systems and Solutions,"International Journal of Computer Applications (0975 – 8887) Volume 61– No.17, January 2013 Survey of Threats to the Biometric Authentication @@ -8983,10 +30925,33 @@ Kota University,Kota(INDIA) Khushboo Mantri M.tech.student, Arya College of engineering ,Jaipur(INDIA)"
+6bb55ed3761eb1556acbd1a0d15c2c9099bab0b7,Temporally Coherent Bayesian Models for Entity Discovery in Videos by Tracklet Clustering,"Temporally Coherent Chinese Restaurant Process +for Discovery of Persons and Corresponding +Tracklets from User-generated Videos"
0728f788107122d76dfafa4fb0c45c20dcf523ca,The Best of BothWorlds: Combining Data-Independent and Data-Driven Approaches for Action Recognition,"The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition Zhenzhong Lan, Dezhong Yao, Ming Lin, Shoou-I Yu, Alexander Hauptmann {lanzhzh, minglin, iyu,"
+07d49098ada2d8e1ca0608c70e559dd517ca3432,Modélisation de contextes pour l'annotation sémantique de vidéos. (Context based modeling for video semantic annotation),"Modélisation de contextes pour l’annotation sémantique +de vidéos +Nicolas Ballas +To cite this version: +Nicolas Ballas. Modélisation de contextes pour l’annotation sémantique de vidéos. Autre [cs.OH]. +Ecole Nationale Supérieure des Mines de Paris, 2013. Français. <NNT : 2013ENMP0051>. <pastel- +00958135> +HAL Id: pastel-00958135 +https://pastel.archives-ouvertes.fr/pastel-00958135 +Submitted on 11 Mar 2014 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
07ea3dd22d1ecc013b6649c9846d67f2bf697008,Human-centric Video Understanding with Weak Supervision a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"HUMAN-CENTRIC VIDEO UNDERSTANDING WITH WEAK SUPERVISION A DISSERTATION @@ -9001,6 +30966,12 @@ June 2016" 071099a4c3eed464388c8d1bff7b0538c7322422,Facial expression recognition in the wild using rich deep features,"FACIAL EXPRESSION RECOGNITION IN THE WILD USING RICH DEEP FEATURES Abubakrelsedik Karali, Ahmad Bassiouny and Motaz El-Saban Microsoft Advanced Technology labs, Microsoft Technology and Research, Cairo, Egypt"
+079b6800e3130ca2ef1815a35632ab6998848ef3,Fine-grained Apparel Classification and Retrieval without rich annotations,"Fine-grained Apparel Classification and Retrieval +without rich annotations +Aniket Bhatnagar · Sanchit Aggarwal"
+0760b9375db1505e9b9c182e98bb9579dd9197af,Robust Subspace Discovery through Supervised Low-Rank Constraints,"Robust Subspace Discovery through Supervised Low-Rank Constraints +Sheng Li∗ +Yun Fu∗"
070ab604c3ced2c23cce2259043446c5ee342fd6,An Active Illumination and Appearance (AIA) Model for Face Alignment,"AnActiveIlluminationandAppearance(AIA)ModelforFaceAlignment FatihKahraman,MuhittinGokmen IstanbulTechnicalUniversity, @@ -9009,6 +30980,11 @@ ComputerScienceDept.,Turkey InformaticsandMathematicalModelling,Denmark SuneDarkner,RasmusLarsen TechnicalUniversityofDenmark"
+07a8a4b8f207b2db2a19e519027f70cd1c276294,Pixel Recursive Super Resolution,"Pixel Recursive Super Resolution +Ryan Dahl ∗ +Jonathon Shlens +Mohammad Norouzi +Google Brain"
071135dfb342bff884ddb9a4d8af0e70055c22a1,Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification,"New Architecture and Transfer Learning for Video Classification Temporal 3D ConvNets: Ali Diba1,4,(cid:63), Mohsen Fayyaz2,(cid:63), Vivek Sharma3, Amir Hossein Karami4, Mohammad Mahdi Arzani4, @@ -9017,12 +30993,96 @@ ESAT-PSI, KU Leuven, 2University of Bonn, 3CV:HCI, KIT, Karlsruhe, 4Sensifai" 0754e769eb613fd3968b6e267a301728f52358be,Towards a Watson that sees: Language-guided action recognition for robots,"Towards a Watson That Sees: Language-Guided Action Recognition for Robots Ching L. Teo, Yezhou Yang, Hal Daum´e III, Cornelia Ferm¨uller and Yiannis Aloimonos"
+0725b950792ddbe4edf812a7ee8cef14447236ed,Efficient Large-Scale Multi-Modal Classification,"Efficient Large-Scale Multi-Modal Classification +Douwe Kiela, Edouard Grave, Armand Joulin and Tomas Mikolov +Facebook AI Research"
07c83f544d0604e6bab5d741b0bf9a3621d133da,Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition,"Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba, Ibaraki, Japan {kensho.hara, hirokatsu.kataoka,"
+07adc7429fb22352946b675023df7db11c905701,Active Multitask Learning Using Both Latent and Supervised Shared Topics,"Active Multitask Learning Using Both Latent and Supervised Shared Topics +Ayan Acharya∗ +Raymond J. Mooney∗ +Joydeep Ghosh∗"
+073c9ec4ff069218f358b9dd8451a040cf1a4a82,Object Classification and Detection in High Dimensional Feature Space,"Object Classification and Detection +in High Dimensional Feature Space +THIS IS A TEMPORARY TITLE PAGE +It will be replaced for the final print by a version +provided by the service académique. +Thèse n. 6043 +présentée le 17 Décembre 2013 +à la Faculté Sciences et Techniques de l’Ingénieur +Laboratoire de l’Idiap +Programme doctoral en Informatique, Communications et Infor- +mation +École Polytechnique Fédérale de Lausanne +pour l’obtention du grade de Docteur ès Sciences +Charles Dubout +cceptée sur proposition du jury: +Prof Mark Pauly, président du jury +Dr François Fleuret, directeur de thèse +Prof Pascal Fua, rapporteur +Prof Gilles Blanchard, rapporteur +Prof Frédéric Jurie, rapporteur"
+0726152a1c1a5723ac34d54abec0dc8d4659598e,Realtime Image Matching for Vision Based Car Navigation with Built-in Sensory Data,"ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-3/W2, 2013 +ISA13 - The ISPRS Workshop on Image Sequence Analysis 2013, 11 November 2013, Antalya, Turkey"
+070199a5087590f96c4422b82e4803911bb0652e,What Are We Tracking: A Unified Approach of Tracking and Recognition,"What Are We Tracking: A Unified Approach of +Tracking and Recognition +Jialue Fan, Xiaohui Shen, Student Member, IEEE, and Ying Wu, Senior Member, IEEE"
+07ca211bde38009697c964702a29d0fe3260bf97,Resource Aware Person Re-identification across Multiple Resolutions,"Resource Aware Person Re-identification across Multiple Resolutions +Yan Wang∗ †, Lequn Wang∗ †, Yurong You∗ ‡, Xu Zou§, Vincent Chen† +Serena Li†, Gao Huang†, Bharath Hariharan†, Kilian Q. Weinberger†"
+07dbf04089b015db773fe95e664fa73aef874b36,Fishy Faces: Crafting Adversarial Images to Poison Face Authentication,"Fishy Faces: Crafting Adversarial Images to Poison Face Authentication +Giuseppe Garofalo +Vera Rimmer +Tim Van hamme +imec-DistriNet, KU Leuven +imec-DistriNet, KU Leuven +imec-DistriNet, KU Leuven +Davy Preuveneers +Wouter Joosen +imec-DistriNet, KU Leuven +imec-DistriNet, KU Leuven"
+07d6238d8f8edbfe0fd2887fa0a7939735f21e13,Learning Human Optical Flow,"RANJAN, ROMERO, BLACK: LEARNING HUMAN OPTICAL FLOW +Learning Human Optical Flow +MPI for Intelligent Systems +Tübingen, Germany +Amazon Inc. +Anurag Ranjan1 +Javier Romero∗,2 +Michael J. Black1"
+07ad6bb9b21c065cd92ab2f24a22c1d4a8f205a7,Realtime facial animation with on-the-fly correctives,"Realtime Facial Animation with On-the-fly Correctives +Hao Li⇤ +Jihun Yu† +Yuting Ye‡ +Chris Bregler§ +Industrial Light & Magic +input depth map & 2D features +data-driven tracking +our tracking +data-driven retargeting +our retargeting +Figure 1: Our adaptive tracking model conforms to the input expressions on-the-fly, producing a better fit to the user than state-of-the-art +data driven techniques [Weise et al. 2011] which are confined to learned motion priors and generate plausible but not accurate tracking. +Links: +Introduction +The essence of high quality performance-driven facial animation is +to capture every trait and characteristic of an actor’s facial and ver- +al expression and to reproduce those on a digital double or crea- +ture. Even with the latest 3D scanning and motion capture tech- +nology, the creation of realistic digital faces in film and game pro-"
+072fd0b8d471f183da0ca9880379b3bb29031b6a,Image-to-Image Translation with Conditional Adversarial Networks,"Image-to-Image Translation with Conditional Adversarial Networks +Phillip Isola +Jun-Yan Zhu +Tinghui Zhou +Alexei A. Efros +Berkeley AI Research (BAIR) Laboratory, UC Berkeley +Figure 1: Many problems in image processing, graphics, and vision involve translating an input image into a corresponding output image. +These problems are often treated with application-specific algorithms, even though the setting is always the same: map pixels to pixels. +Conditional adversarial nets are a general-purpose solution that appears to work well on a wide variety of these problems. Here we show +results of the method on several. In each case we use the same architecture and objective, and simply train on different data."
0717b47ab84b848de37dbefd81cf8bf512b544ac,Robust Face Recognition and Tagging in Visual Surveillance System,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 International Conference on Humming Bird ( 01st March 2014) RESEARCH ARTICLE @@ -9032,6 +31092,26 @@ Kavitha MS 1, Siva Pradeepa S2 System Kavitha MS Author is currently pursuing M.E(CSE)in VINS Christian college of Engineering,Nagercoil. Siva pradeepa,Assistant Lecturer in VINS Christian college of Engineering"
+07eaf19eecf4ccdd5f8e3367c1675d9f4addd2df,Learning pullback manifolds of dynamical models,"IEEE TRANSACTIONS ON PAMI, VOL. XX, NO. Y, MONTH 2010 +SubmittedtoIEEETrans.onPatternAnalysisandMachineIntelligence;October27,2010 +Learning pullback manifolds of dynamical +models +Fabio Cuzzolin"
+0779875eff440365184dd8bf44e9f85f78267c5f,An Intelligent Extraversion Analysis Scheme from Crowd Trajectories for Surveillance,"JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. YY, JULY 2017 +An Intelligent Extraversion Analysis Scheme from +Crowd Trajectories for Surveillance +Wenxi Liu, Yuanlong Yu, Chun-Yang Zhang, Genggeng Liu, Naixue Xiong"
+074a12f9187beafe40386f19aa2544df30fa5703,Product Characterisation towards Personalisation: Learning Attributes from Unstructured Data to Recommend Fashion Products,"Product Characterisation towards Personalisation +Learning Attributes from Unstructured Data to Recommend Fashion Products +Ângelo Cardoso∗ +ISR, IST, Universidade de Lisboa +Lisbon, Portugal +Fabio Daolio +ASOS.com +London, UK +Saúl Vargas +ASOS.com +London, UK"
0750a816858b601c0dbf4cfb68066ae7e788f05d,CosFace: Large Margin Cosine Loss for Deep Face Recognition,"CosFace: Large Margin Cosine Loss for Deep Face Recognition Hao Wang, Yitong Wang, Zheng Zhou, Xing Ji, Dihong Gong, Jingchao Zhou, Zhifeng Li∗, and Wei Liu∗ @@ -9051,12 +31131,50 @@ Bangalore" Clustering via Attribute-Based Explanations Shrenik Lad and Devi Parikh Virginia Tech, Blacksburg, VA, USA"
+07c6744e25ed01967e448a397f5d7e9d540345c3,Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval,"Effective Multi-Query Expansions: Collaborative Deep Networks for Robust +Landmark Retrieval +Yang Wang, Xuemin Lin, Lin Wu, Wenjie Zhang"
0726a45eb129eed88915aa5a86df2af16a09bcc1,Introspective perception: Learning to predict failures in vision systems,"Introspective Perception: Learning to Predict Failures in Vision Systems Shreyansh Daftry, Sam Zeng, J. Andrew Bagnell and Martial Hebert"
+07625af8d73142e239b5cdccb1dd226648e4b0d4,Learning Scene-Independent Group Descriptors for Crowd Understanding,"Learning Scene-Independent Group Descriptors for +Crowd Understanding +Jing Shao, Chen Change Loy, Member, IEEE, and Xiaogang Wang, Member, IEEE"
0742d051caebf8a5d452c03c5d55dfb02f84baab,Real-time geometric motion blur for a deforming polygonal mesh,"Real-Time Geometric Motion Blur for a Deforming Polygonal Mesh Nathan Jones Formerly: Texas A&M University Currently: The Software Group"
+079a0a3bf5200994e1f972b1b9197bf2f90e87d4,Component-Based Face Recognition with 3D Morphable Models,"Component-based Face Recognition with 3D +Morphable Models +Jennifer Huang1, Bernd Heisele1;2, and Volker Blanz3 +Center for Biological and Computational Learning, M.I.T., Cambridge, MA, USA +Honda Research Institute US, Boston, MA, USA +Computer Graphics Group, Max-Planck-Institut, Saarbr˜ucken, Germany"
+07faa38d4d0e9d14d72bd049362efa83fae78ee3,Quick Identification of Child Pornography in Digital Videos,"IJoFCS (2012) 2, 21-32 +DOI: 10.5769/J201202002 or http://dx.doi.org/10.5769/J201202002 +Quick Identification of Child Pornography +in Digital Videos +Mateus de Castro Polastro and Pedro Monteiro da Silva Eleuterio +Brazilian Federal Police +Campo Grande/MS +E-mails:"
+073bcb3b1aed5cdf7bff4e9fe46a21175f42c877,"Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly","Zero-Shot Learning - A Comprehensive +Evaluation of the Good, the Bad and the Ugly +Yongqin Xian, Student Member, IEEE, Christoph H. Lampert, +Bernt Schiele, Fellow, IEEE, and Zeynep Akata, Member, IEEE"
+0770f0f8f168c284a63e46b394150a8c429549da,Project-Team Pulsar Perception Understanding Learning Systems for Activity Recognition,"INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET EN AUTOMATIQUE +Project-Team Pulsar +Perception Understanding Learning +Systems for Activity Recognition +Sophia Antipolis - Méditerranée +THEME COG +tivitytepor2008"
+389b2390fd310c9070e72563181547cf23dceea3,Β-vae: Learning Basic Visual Concepts with a Constrained Variational Framework,"Published as a conference paper at ICLR 2017 +β-VAE: LEARNING BASIC VISUAL CONCEPTS WITH A +CONSTRAINED VARIATIONAL FRAMEWORK +Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, +Matthew Botvinick, Shakir Mohamed, Alexander Lerchner +Google DeepMind +{irinah,lmatthey,arkap,cpburgess,glorotx,"
38d56ddcea01ce99902dd75ad162213cbe4eaab7,Sense Beauty by Label Distribution Learning,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
389334e9a0d84bc54bcd5b94b4ce4c5d9d6a2f26,Facial parameter extraction system based on active contours,"FACIAL PARAMETER EXTRACTION SYSTEM BASED ON ACTIVE CONTOURS Montse Pardàs, Marcos Losada @@ -9097,18 +31215,110 @@ promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any opyrighted component of this work in other works must be obtained from the IEEE."
+38998d58a0c1048ad4c08d0022066e22ba6d1201,Re-identification through a Video Camera Network,"UNIVERSIT´EDENICE-SOPHIAANTIPOLIS´ECOLEDOCTORALESTICSCIENCESETTECHNOLOGIESDEL’INFORMATIONETDELACOMMUNICATIONTH`ESEpourl’obtentiondugradedeDocteurenSciencesdel’Universit´edeNice-SophiaAntipolisMention:AUTOMATIQUETRAITEMENTDUSIGNALETDESIMAGESpr´esent´eeetsoutenueparMalikSOUDEDPEOPLEDETECTION,TRACKINGANDRE-IDENTIFICATIONTHROUGHAVIDEOCAMERANETWORKTh`esedirig´eeparFranc¸oisBR´EMONDSoutenancepr´evuele20/12/2013Jury:MoniqueTHONNATDirectrice,INRIASophia-Antipolis,FrancePr´esidenteJamesFERRYMANProfesseur,UniversityofReading,UKRapporteurCarloREGAZZONIProfesseur,UniversityofGenova,ItalyRapporteurPatrickBOUTHEMYDirecteur,INRIARennes,FranceExaminateurFranc¸oisBREMONDDirecteur,INRIASophia-Antipolis,FranceDirecteurdeth`eseMarie-ClaudeFRASSONDirectrice,DigitalBarriers,Sophia-Antipolis,FranceInvit´ee"
+380b8df0f340e5bbc3a953c62f9bc573ce073b92,Joint Image-Text News Topic Detection and Tracking by Multimodal Topic And-Or Graph,"Joint Image-Text News Topic Detection and +Tracking by Multimodal Topic And-Or Graph +Weixin Li, Jungseock Joo, Hang Qi, and Song-Chun Zhu"
+382f1ebe6009e580949d5513bc298cb253a1eeda,Interpreting Complex Regression Models,"Interpreting Complex Regression Models +Noa Avigdor-Elgrabli∗, Alex Libov†, Michael Viderman∗, Ran Wolff∗ +Yahoo Research, Haifa, Israel, +Amazon Research, Haifa, Israel,"
38682c7b19831e5d4f58e9bce9716f9c2c29c4e7,Movie Character Identification Using Graph Matching Algorithm,"International Journal of Computer Trends and Technology (IJCTT) – Volume 18 Number 5 – Dec 2014 Movie Character Identification Using Graph Matching Algorithm Shaik. Kartheek.*1, A.Srinivasa Reddy*2 M.Tech Scholar, Dept of CSE, QISCET, ONGOLE, Dist: Prakasam, AP, India. Associate Professor, Department of CSE, QISCET, ONGOLE, Dist: Prakasam, AP, India"
+383d64b27fb3cdf2beff43f3beb8caac8c21a886,Detecting activities of daily living in first-person camera views,"Detecting Activities of Daily Living in First-person Camera Views +Hamed Pirsiavash Deva Ramanan +Department of Computer Science, University of California, Irvine"
+3851ed2e3c00083f68c2811694736ebdaa9ed8b5,DeepStory: Video Story QA by Deep Embedded Memory Networks,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+38b3cae6ba1b98d6bc6f88d903916dac888cb951,Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classiffication,"Improving Semantic Embedding Consistency by +Metric Learning for Zero-Shot Classification +Maxime Bucher1,2, St´ephane Herbin1, Fr´ed´eric Jurie2 +ONERA - The French Aerospace Lab, Palaiseau, France +Normandie Univ, UNICAEN, ENSICAEN, CNRS"
+3810b6299140bf2c7d6d0cced765c0777d603923,Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?,"Do Deep Features Generalize from Everyday Objects +to Remote Sensing and Aerial Scenes Domains? +Ot´avio A. B. Penatti +Advanced Technologies Group +SAMSUNG Research Institute +Campinas, SP, 13097-160, Brazil +Keiller Nogueira, Jefersson A. dos Santos +Department of Computer Science +Universidade Federal de Minas Gerais +Belo Horizonte, MG, 31270-010, Brazil"
38eea307445a39ee7902c1ecf8cea7e3dcb7c0e7,Multi-distance Support Matrix Machines,"Noname manuscript No. (will be inserted by the editor) Multi-distance Support Matrix Machine Yunfei Ye1 · Dong Han1 Received: date / Accepted: date"
+3885cfd634c025c6e27c4db8211d72f54f864f90,Implications of holistic face processing in autism and schizophrenia,"Implications of holistic face processing in autism and +schizophrenia +Tamara L. Watson* +School of Social Science and Psychology, University of Western Sydney, Sydney, NSW, Australia +REVIEW ARTICLE +published: 05 July 2013 +doi: 10.3389/fpsyg.2013.00414 +People with autism and schizophrenia have been shown to have a local bias in sensory +processing and face recognition difficulties. A global or holistic processing strategy is +known to be important when recognizing faces. Studies investigating face recognition in +these populations are reviewed and show that holistic processing is employed despite +lower overall performance in the tasks used. This implies that holistic processing is +necessary but not sufficient for optimal face recognition and new avenues for research +into face recognition based on network models of autism and schizophrenia are proposed. +Keywords: vision, face recognition, autism, schizophrenia, holistic coding, configurational coding +Edited by: +Rachel A. Robbins, Univeristy of +Western Sydney, Australia +Reviewed by: +Olivia Carter, University of"
+3837f81524286ed5f9142d245743733766aa4017,Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples,"Houdini: Fooling Deep Structured Visual and Speech +Recognition Models with Adversarial Examples +Moustapha Cisse +Facebook AI Research +Natalia Neverova* +Facebook AI Research"
+38192f06ac19172299ab543483d2e0eca2f889c0,Mining Mid-level Features for Image Classification,"(will be inserted by the editor) +Mining Mid-level Features for Image Classification +Basura Fernando · Elisa Fromont · Tinne Tuytelaars +Received: date / Accepted: date"
+3832a6d6b1f78cdadee6968d51c1c7c2922ab3cd,ISIA at the ImageCLEF 2017 Image Caption Task,"ISIA at the ImageCLEF 2017 Image Caption Task +Sisi Liang, Xiangyang Li, Yongqing Zhu, Xue Li, and Shuqiang Jiang +Key Laboratory of Intelligent Information Processing, +Institute of Computing Technology Chinese Academy of Sciences, +No.6 Kexueyuan South Road Zhongguancun, Haidian District, 100190 Beijing, China +{sisi.liang, xiangyang.li, yongqing.zhu, xue.li,"
+384908bfad5b9e81d605344abcb9e99d8b0f4027,Improving Deep Models of Person Re-identification for Cross-Dataset Usage,"Improving Deep Models of Person Re-identification for +Cross-Dataset Usage +Sergey Rodionov1,2, Alexey Potapov1,3, Hugo Latapie4, Enzo Fenoglio4, +Maxim Peterson2,3 +SingularityNET LLC +Novamente LLC, USA +ITMO University, Kronverkskiy pr. 49, 197101 St. Petersburg, Russia +Chief Technology & Architecture Office, Cisco +{pas.aicv, astroseger, {hlatapie,"
+38a169b6e67ef7768f91fa208c9b5544f6f57f16,Object Bank: An Object-Level Image Representation for High-Level Visual Recognition,"Int J Comput Vis +DOI 10.1007/s11263-013-0660-x +Object Bank: An Object-Level Image Representation +for High-Level Visual Recognition +Li-Jia Li · Hao Su · Yongwhan Lim · Li Fei-Fei +Received: 2 January 2012 / Accepted: 11 September 2013 +© Springer Science+Business Media New York 2013"
+38b18585e4bdb78347d44caa561e69a0045ade8d,Differential Attention for Visual Question Answering,"Differential Attention for Visual Question Answering +Badri Patro, Vinay P. Namboodiri +IIT Kanpur +{ badri,vinaypn"
+3805d47da61527137b6f44b92af3017a2dfe7bd5,Greedy column subset selection for large-scale data sets,"(will be inserted by the editor) +Greedy Column Subset Selection for Large-scale +Data Sets +Ahmed K. Farahat · Ahmed Elgohary · +Ali Ghodsi · Mohamed S. Kamel +Received: date / Accepted: date"
+386a5c06d334d20227e8b2daf5433a2bef385648,Cross and Learn: Cross-Modal Self-Supervision,"Cross and Learn: Cross-Modal Self-Supervision +Nawid Sayed1, Biagio Brattoli2, and Bj¨orn Ommer2 +Heidelberg University, HCI / IWR, Germany"
384f972c81c52fe36849600728865ea50a0c4670,"Multi-Fold Gabor, PCA and ICA Filter Convolution Descriptor for Face Recognition","Multi-Fold Gabor, PCA and ICA Filter Convolution Descriptor for Face Recognition Cheng Yaw Low, Andrew Beng Jin Teoh, Senior Member, IEEE, Cong Jie Ng"
@@ -9122,6 +31332,9 @@ L3S Research Center, Leibniz Universit¨at Hannover, Germany" 380d5138cadccc9b5b91c707ba0a9220b0f39271,Deep Imbalanced Learning for Face Recognition and Attribute Prediction,"Deep Imbalanced Learning for Face Recognition nd Attribute Prediction Chen Huang, Yining Li, Chen Change Loy, Senior Member, IEEE and Xiaoou Tang, Fellow, IEEE"
+383a58de852715c8544abe60fa64d29fb7ea5688,Inductive Hashing on Manifolds,"Inductive Hashing on Manifolds +Fumin Shen‡(cid:5)∗ Chunhua Shen(cid:5)† Qinfeng Shi(cid:5) Anton van den Hengel(cid:5) Zhenmin Tang‡ +(cid:5) The University of Adelaide, Australia ‡ Nanjing University of Science and Technology, China"
38215c283ce4bf2c8edd597ab21410f99dc9b094,The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent,"The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent @@ -9142,14 +31355,151 @@ The Research Portal is Queen's institutional repository that provides access to ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the Research Portal that you believe breaches copyright or violates any law, please contact Download date:05. Nov. 2018"
+38b0a67727dea3fe563e8662517bd0fda2fd5e06,Perceiving and expressing feelings through actions in relation to individual differences in empathic traits: the Action and Feelings Questionnaire (AFQ),"Cogn Affect Behav Neurosci (2016) 16:248–260 +DOI 10.3758/s13415-015-0386-z +Perceiving and expressing feelings through actions in relation +to individual differences in empathic traits: the Action +nd Feelings Questionnaire (AFQ) +Justin H. G. Williams 1,4 & Isobel M. Cameron 1 & Emma Ross 2 & Lieke Braadbaart 3 & +Gordon D Waiter 3 +Published online: 20 October 2015 +# The Author(s) 2015. This article is published with open access at Springerlink.com"
+38a3611138388490c2cd60dfbf795932d5e55a79,2D pose estimation in the Restaurant of the Future,"D pose estimation in the Restaurant +of the Future +Frederik (Frank) Evers +supervision by +dr. ir. Nico P. van der Aa +Noldus IT B.V. +Wageningen, NL +dr. Robby T. Tan +University of Utrecht +Utrecht, NL +March 29, 2012"
+383f874ba7975c83b55c694ec0a70f51dc3a0ee5,Towards Automatic Image Understanding and Mining via Social Curation,"Towards Automatic Image Understanding and Mining via Social Curation +Katsuhiko Ishiguro, Akisato Kimura, and Koh Takeuchi +NTT Communication Science Laboratories +NTT Corporation, Kyoto, Japan"
+389363432ee9fcf0e0cfe67b7b4f62618e1f4b59,Performing content-based retrieval of humans using gait biometrics,"Performing Content-Based Retrieval of Humans +Using Gait Biometrics +Sina Samangooei and Mark S. Nixon +School of Electronics and Computer Science, Southampton University, Southampton, +SO17 1BJ, United Kingdom"
+3837f3faa722c91aa21d6f17ea1ac1cb5187bda1,Human Action Attribute Learning From Video Data Using Low-Rank Representations,"Human Action Attribute Learning From Video +Data Using Low-Rank Representations +Tong Wu, Student Member, IEEE, Prudhvi Gurram, Senior Member, IEEE, +Raghuveer M. Rao, Fellow, IEEE, and Waheed U. Bajwa, Senior Member, IEEE"
+3898a9dcb22f87413f08bb44c656f4129e1c42df,On binary representations for biometric template protection,"ON BINARY REPRESENTATIONS FOR +BIOMETRIC TEMPLATE PROTECTION +Chun Chen"
+38cc2896058131e4656443aedfb1b9dae61b99cd,Functional Connectivity Imaging Analysis: Interhemispheric Integration in Autism,"Functional Connectivity Imaging Analysis: +Interhemispheric Integration in Autism +Daniel J. Kelley"
3802da31c6d33d71b839e260f4022ec4fbd88e2d,Deep Attributes for One-Shot Face Recognition,"Deep Attributes for One-Shot Face Recognition Aishwarya Jadhav1,3, Vinay P. Namboodiri2, and K. S. Venkatesh 3 Xerox Research Center India, 2Department of Computer Science, Department of Electrical Engineering, IIT Kanpur"
+38e509fc0d94e954a512128760f7a1f0d6fbc384,A Framework for Application-Guided Task Management on Heterogeneous Embedded Systems,"A Framework for Application Guided Task Management on +Heterogeneous Embedded Systems +FRANCISCO GASPAR, INESC-ID, Instituto Superior T´ecnico, Universidade de Lisboa +LUIS TANIC¸ A, INESC-ID, Instituto Superior T´ecnico, Universidade de Lisboa +PEDRO TOM ´AS, INESC-ID, Instituto Superior T´ecnico, Universidade de Lisboa +ALEKSANDAR ILIC, INESC-ID, Instituto Superior T´ecnico, Universidade de Lisboa +LEONEL SOUSA, INESC-ID, Instituto Superior T´ecnico, Universidade de Lisboa +In this paper, we propose a general framework for fine-grain application-aware task management in hetero- +geneous embedded platforms, which allows integration of different mechanisms for an efficient resource uti- +lization, frequency scaling and task migration. The proposed framework incorporates several components for +ccurate run-time monitoring by relying on the OS facilities and performance self-reporting for parallel and +iterative applications. The framework efficiency is experimentally evaluated on a real hardware platform, +where significant power and energy savings are attained for SPEC CPU2006 and PARSEC benchmarks, by +guiding frequency scaling and inter-cluster migrations according to the run-time application behavior and +predefined performance targets. +CCS Concepts:rComputer systems organization → Multicore architectures; Heterogeneous (hybrid) +systems;rSoftware and its engineering → Process management; +Additional Key Words and Phrases: Heterogeneous multi processor; scheduling; embedded systems; quality +of service; big.LITTLE; task migration; dynamic voltage and frequency control +ACM Reference Format:"
+000a83a533f9c945addce83e466e308df1ae79c5,Efficient max-margin multi-label classification with applications to zero-shot learning,"Mach Learn manuscript No. +(will be inserted by the editor) +Efficient Max-Margin Multi-Label Classification with +Applications to Zero-Shot Learning +Bharath Hariharan · S. V. N. Vishwanathan · +Manik Varma +Received: 30 September 2010 / Accepted: date"
+004dc8de3a6832c8d4764144570dc122b5265ec5,Hyper-dimensional computing for a visual question-answering system that is trainable end-to-end,"Hyper-dimensional computing for a visual +question-answering system that is trainable +end-to-end +Guglielmo Montone +J.Kevin O’Regan +Laboratoire Psychologie de la Perception +Laboratoire Psychologie de la Perception +Université Paris Descartes +75006 Paris, France +Université Paris Descartes +75006 Paris, France +Alexander V. Terekhov +Laboratoire Psychologie de la Perception +Université Paris Descartes +75006 Paris, France"
00fb2836068042c19b5197d0999e8e93b920eb9c,Genetic Algorithm for Weight Optimization in Descriptor based Face Recognition Methods,
+005c996a9059af96454c3d6f83338068d3608585,On Detection of Multiple Object Instances Using Hough Transforms,"On Detection of Multiple Object Instances using Hough Transforms +Olga Barinova +Moscow State University∗ +Victor Lempitsky +University of Oxford∗ +Pushmeet Kohli +Microsoft Research Cambridge"
+0033e0ce8720f913761f9edb9a6c378eed8366a8,Interactive Object Retrieval using Interpretable Visual Models,"UNIVERSIT´EPARIS-SUD11Facult´edessciencesd’OrsayN◦Ordre:2011PA112054PHDTHESISInteractiveObjectRetrievalusingInterpretableVisualModelsSubmittedforthedegreeof“docteurensciences”oftheUniversityParis-Sud11Speciality:ComputerScienceByAhmedRebaiMay2011INRIAParis-Rocquencourt,ImediaTeamThesiscommittee:Reviewers:FredStentiford-Prof.atUniversityCollegeLondon(UK)SylviePhilipp-Foliguet-Prof.atUniversit´eCergy/Pontoise(FR)Director:NozhaBoujemaa-DirectoroftheINRIA-SaclayCenter(FR)Advisor:AlexisJoly-ResearcheratINRIA-Rocquencourt(FR)Examinator:MichelCrucianu-Prof.atCNAM(FR)President:Fran¸coisYvon-Prof.atUniversit´eParis-Sud11(FR)Copyrightc(cid:13)2011AhmedRebaiAllrightsreserved."
+003afe78ec7989371f648fd8957a6ce79083cf11,SeaCLEF 2016: Object Proposal Classification for Fish Detection in Underwater Videos,"SeaCLEF 2016: Object proposal classification for +fish detection in underwater videos +Jonas J¨ager1,2, Erik Rodner2, Joachim Denzler2, Viviane Wolff1, and Klaus +Fricke-Neuderth1 +Department of Electrical Engineering and Information Technology, +Fulda University of Applied Sciences, Germany +Computer Vision Group, Friedrich Schiller University Jena, Germany"
+00dfd58bbaff871603e4a8aa81e67915b0675aeb,Human Sensing Using Computer Vision for Personalized Smart Spaces,"013 IEEE 10th International Conference on Ubiquitous Intelligence & Computing and 2013 IEEE 10th International Conference +on Autonomic & Trusted Computing +Human Sensing using Computer Vision for +Personalized Smart Spaces +Dipak Surie, Saeed Partonia, Helena Lindgren +User Interaction and Knowledge Modeling Group +Dept. of Computing Science +Umeå University, Sweden +{dipak, mcs10spa, +spaces +everyday"
+008dafebbb27eb64a1af8ded8bfe2e7a04c1d703,CANDLE/Supervisor: A Workflow Framework for Machine Learning Applied to Cancer Research,"CANDLE/Supervisor: A Workflow Framework for +Machine Learning Applied to Cancer Research +Justin M. Wozniak, Rajeev Jain, +Prasanna Balaprakash +Mathematics & Computer Science +Argonne National Laboratory +Argonne, IL, USA +Jamaludin Mohd-Yusof, +Cristina Garcia Cardona +Computer, Computational & +Statistical Sciences +Los Alamos National Laboratory +Los Alamos, NM, USA +Jonathan Ozik, +Nicholson Collier +Global Security Sciences +Argonne National Laboratory +Argonne, IL, USA +Brian Van Essen +Lawrence Livermore National"
0077cd8f97cafd2b389783858a6e4ab7887b0b6b,Face Image Reconstruction from Deep Templates,"MAI et al.: ON THE RECONSTRUCTION OF DEEP FACE TEMPLATES On the Reconstruction of Deep Face Templates Guangcan Mai, Kai Cao, Pong C. Yuen, Senior Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
+00b03ee4a7e31a999715d7a0c31d283d646106fa,Multi-level Semantic Feature Augmentation for One-shot Learning,"Multi-level Semantic Feature Augmentation for +One-shot Learning +Zitian Chen, Yanwei Fu*, Yinda Zhang, Leonid Sigal"
+00d8f67ac0ea0bb2c9827b60e1f47c300346cd7a,Face recognition using color local binary pattern from mutually independent color channels,"Anbarjafari EURASIP Journal on Image and Video Processing 2013, 2013:6 +http://jivp.eurasipjournals.com/content/2013/1/6 +R ES EAR CH +Open Access +Face recognition using color local binary pattern +from mutually independent color channels +Gholamreza Anbarjafari"
00214fe1319113e6649435cae386019235474789,Face Recognition using Distortion Models,"Bachelorarbeit im Fach Informatik Face Recognition using Distortion Models @@ -9167,18 +31517,145 @@ Prof. Dr. B. Leibe Betreuer: Dipl.-Inform. Philippe Dreuw September 2009"
+0063b44da282eec78045ab59d2debbf61959a4a4,Improving person re-identification by viewpoint cues,"Improving Person Re-identification by Viewpoint Cues +Sławomir B ˛ak +Sofia Zaidenberg Bernard Boulay +Francois Brémond +INRIA Sophia Antipolis, STARS/Neosensys +004, route des Lucioles, BP93 +06902 Sophia Antipolis Cedex - France"
+003b141fb02078a4b5d02f4f803001ce22d73ba7,Real-time 3d Multiple Human Tracking with Robustness Enhancement through Machine Learning,"REAL-TIME 3D MULTIPLE HUMAN TRACKING WITH +ROBUSTNESS ENHANCEMENT THROUGH MACHINE LEARNING +Keywords: +Visual Tracking"
004e3292885463f97a70e1f511dc476289451ed5,Quadruplet-Wise Image Similarity Learning,"Quadruplet-wise Image Similarity Learning Marc T. Law Nicolas Thome Matthieu Cord LIP6, UPMC - Sorbonne University, Paris, France {Marc.Law, Nicolas.Thome,"
+00d14af37bc75b6477b4846f6ab561cdc89c96a2,"UvA-DARE ( Digital Academic Repository ) Infants ’ Temperament and Mothers ’ , and Fathers ’ Depression Predict Infants ’ Attention to Objects Paired with Emotional","UvA-DARE (Digital Academic Repository) +Infants’ Temperament and Mothers’, and Fathers’ Depression Predict Infants’ Attention +to Objects Paired with Emotional Faces +Aktar, E.; Mandell, D.J.; de Vente, W.; Majdandzic, M.; Raijmakers, M.E.J.; Bögels, S.M. +Published in: +Journal of Abnormal Child Psychology +0.1007/s10802-015-0085-9 +Link to publication +Citation for published version (APA): +Aktar, E., Mandell, D. J., de Vente, W., Majdandži, M., Raijmakers, M. E. J., & Bögels, S. M. (2016). Infants’ +Temperament and Mothers’, and Fathers’ Depression Predict Infants’ Attention to Objects Paired with Emotional +Faces. Journal of Abnormal Child Psychology, 44(5), 975-990. DOI: 10.1007/s10802-015-0085-9 +General rights +It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +Disclaimer/Complaints regulations +If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask +the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, +The Netherlands. You will be contacted as soon as possible."
+00433d2ad90b40bc5ad22a591aac0da68037003e,K-means Based Automatic Pests Detection and Classification for Pesticides Spraying,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 8 No. 11, 2017 +K-means Based Automatic Pests Detection and +Classification for Pesticides Spraying +Muhammad Hafeez Javed +Foundation University Islamabad +M Humair Noor +Babar Yaqoob Khan +Foundation University Islamabad +Foundation University Islamabad +Nazish Noor +Foundation University Islamabad +Tayyaba Arshad +Foundation University Islamabad"
+00cb08dcef72bfaa1aab0664d34168615ac6a5cc,Amygdala Surface Modeling with Weighted Spherical Harmonics,"Amygdala Surface Modeling with +Weighted Spherical Harmonics +Moo K. Chung1,2, Brendon M. Nacewicz2, Shubing Wang1, +Kim M. Dalton2, Seth Pollak3, and Richard J. Davidson2,3 +Department of Statistics, Biostatistics and Medical Informatics +Waisman Laboratory for Brain Imaging and Behavior +Department of Psychology and Psychiatry +University of Wisconsin, Madison, WI 53706, USA"
+0079d56c8e183ef36f876b84327b97ee9454825b,Scene Parsing by Weakly Supervised Learning with Image Descriptions,"Hierarchical Scene Parsing by Weakly +Supervised Learning with Image Descriptions +Ruimao Zhang, Liang Lin, Guangrun Wang, Meng Wang, and Wangmeng Zuo"
+003846e4559fa32699f08ecd09de13ed5a4e92d2,Analysis of Brain Waves in Violent Images - Are Differences in Gender?,
00f0ed04defec19b4843b5b16557d8d0ccc5bb42,Modeling Spatial and Temporal Cues for Multi-label Facial Action Unit Detection,
+005503ccf270890ea2582370feed4506f3785004,Characterizing the temporal dynamics of object recognition by deep neural networks: role of depth,"ioRxiv preprint first posted online Sep. 10, 2017; +peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission. +http://dx.doi.org/10.1101/178541 +The copyright holder for this preprint (which was not +Characterizing the temporal dynamics of object +recognition by deep neural networks : role of depth +Kandan Ramakrishnan1, Iris I.A. Groen2, Arnold W.M. Smeulders1, +H. Steven Scholte*3, Sennay Ghebreab*1 +Institute of Informatics, University of Amsterdam. +Laboratory of Brain and Cognition, National Institute of Health. +Department of Psychology, University of Amsterdam. +Keywords: deep neural network, ERP, architecture, number of layers"
+00d63b30e7e8383ea3dd2993499df70a51295d13,Exploiting structure in man-made environments,"Exploiting structure in man-made environments +ALPER AYDEMIR +Doctoral Thesis +Stockholm, Sweden, 2012"
0037bff7be6d463785d4e5b2671da664cd7ef746,Multiple Instance Metric Learning from Automatically Labeled Bags of Faces,"Author manuscript, published in ""European Conference on Computer Vision (ECCV '10) 6311 (2010) 634--647"" DOI : 10.1007/978-3-642-15549-9_46"
+0014a057ebdeca672b1cdee8104cca4dc928ef3e,Training Deformable Part Models with Decorrelated Features,"Training deformable part models with decorrelated features +Ross Girshick and Jitendra Malik +UC Berkeley +{rbg,"
+00b370765678c44acd5313f3946b2431890721a9,Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis,"Dynamic Scene Classification: Learning Motion Descriptors with Slow Features +Analysis +Christian Th´eriault, Nicolas Thome, Matthieu Cord +UPMC-Sorbonne Universities, Paris, France"
+00e39fad9846084eb435b6cddd675ee11f2dfb90,Person Re-identification Using Haar-based and DCD-based Signature,"Person Re-identification Using Haar-based and +DCD-based Signature +Slawomir Bak, Etienne Corvee, François Bremond, Monique Thonnat +To cite this version: +Slawomir Bak, Etienne Corvee, François Bremond, Monique Thonnat. Person Re-identification Us- +ing Haar-based and DCD-based Signature. 2nd Workshop on Activity Monitoring by Multi-Camera +Surveillance Systems, AMMCSS 2010, in conjunction with 7th IEEE International Conference on Ad- +vanced Video and Signal-Based Surveillance, AVSS - 2010, Aug 2010, Boston, United States. 2010. +<inria-00496051> +HAL Id: inria-00496051 +https://hal.inria.fr/inria-00496051 +Submitted on 29 Jun 2010 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents"
+006a9f68bcf6edca62d8750af55168971cf0890c,Dynamic Programming Bipartite Belief Propagation For Hyper Graph Matching,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+001dc49f7f3348841b4086f966bfe4e9dfadf03e,Automatic image captioning using multitask learning,"Automatic image captioning using multi-task learning +Anna Fariha"
+0029418d56d8fe71d1d45bdaad88e5cc75dc58e7,Pushing the “Speed Limit”: High-Accuracy US Traffic Sign Recognition With Convolutional Neural Networks,"Pushing the “Speed Limit”: High-Accuracy U.S. +Traffic Sign Recognition with Convolutional Neural +Networks +Yuan Li, Andreas Møgelmose, and Mohan M. Trivedi"
00d9d88bb1bdca35663946a76d807fff3dc1c15f,Subjects and Their Objects: Localizing Interactees for a Person-Centric View of Importance,"Subjects and Their Objects: Localizing Interactees for a Person-Centric View of Importance Chao-Yeh Chen · Kristen Grauman"
+00091891790ee77816ebd785d25900254e6986bd,Discriminative Robust Local Binary Pattern based Edge Texture Features for Object Recognition,"International Journal of Scientific Engineering and Research (IJSER) +ISSN (Online): 2347-3878, Impact Factor (2014): 3.05 +www.ijser.in +Discriminative Robust Local Binary Pattern based +Edge Texture Features for Object Recognition +Rasika Raikar1, Shivani Pandita2 +Dhole Patil College of Engineering, Wagholi, Pune, India +Professor, Dhole Patil College of Engineering, Wagholi, Pune, India +round +each point. Various"
+00edd45d8f4fd75fc329d6a6fcc7d87108baa3a9,Distance Measures for Gabor Jets-Based Face Authentication: A Comparative Evaluation,"Distance Measures for Gabor Jets-based Face +Authentication: A Comparative Evaluation +Daniel Gonz´alez-Jim´enez1, Manuele Bicego2, J.W.H. Tangelder3, B.A.M +Schouten3, Onkar Ambekar3, Jos´e Luis Alba-Castro1, Enrico Grosso2, Massimo +Tistarelli4 +TSC Department, University of Vigo, Vigo (Spain) +DEIR - University of Sassari, Sassari (Italy) +CWI, Amsterdam (The Netherlands) +DAP - University of Sassari, Alghero (Italy)"
00a3cfe3ce35a7ffb8214f6db15366f4e79761e3,Using Kinect for real-time emotion recognition via facial expressions,"Qi-rong Mao, Xin-yu Pan, Yong-zhao Zhan, Xiang-jun Shen, 2015. Using Kinect for real-time emotion recognition via facial expressions. Frontiers of Information Technology & Electronic Engineering, 16(4):272-282. @@ -9193,9 +31670,41 @@ ORCID: http://orcid.org/0000-0002-5021-9057 Front Inform Technol & Electron Eng"
004a1bb1a2c93b4f379468cca6b6cfc6d8746cc4,Balanced k-Means and Min-Cut Clustering,"Balanced k-Means and Min-Cut Clustering Xiaojun Chang, Feiping Nie, Zhigang Ma, and Yi Yang"
+0089a590154694e0de340f357a022f6a38d60946,Speeding-up Object Detection Training for Robotics with FALKON,"Speeding-up Object Detection Training for Robotics with FALKON +Elisa Maiettini1,2,3, Giulia Pasquale1,2, Lorenzo Rosasco2,3 and Lorenzo Natale1"
00d94b35ffd6cabfb70b9a1d220b6823ae9154ee,Discriminative Bayesian Dictionary Learning for Classification,"Discriminative Bayesian Dictionary Learning for Classification Naveed Akhtar, Faisal Shafait, and Ajmal Mian"
+002d1619748a99aa683b5c30b7eafebdfe6adfc4,Nearest feature line embedding for face hallucination,"Nearest feature line embedding for face +hallucination +Junjun Jiang, Ruimin Hu, Zhen Han and Tao Lu +A new manifold learning method, called nearest feature line (NFL) +embedding, for face hallucination is proposed. While many manifold +learning based face hallucination algorithms have been proposed in +recent years, most of them apply the conventional nearest neighbour +metric to derive the subspace and may not effectively characterise +the geometrical +information of the samples, especially when the +number of training samples is limited. This reported work proposes +using the NFL metric to define the neighbourhood relations between +face samples to improve the expressing power of the given training +samples for reconstruction. The algorithm preserves the linear relation- +ship in a smaller local space than traditional manifold learning based +methods, which better reflects the nature of manifold learning theory. +Experimental results demonstrate that +the method is effective at +preserving detailed visual information. +Introduction: Face super-resolution (SR), or face hallucination, refers to"
+00f17fca3cf3ab4262edde3626e6230a89ff1a1f,Human Pose Estimation with Iterative Error Feedback,"Human Pose Estimation with Iterative Error +Feedback +Jo˜ao Carreira +UC Berkeley +Pulkit Agrawal +UC Berkeley +Katerina Fragkiadaki +UC Berkeley +Jitendra Malik +UC Berkeley"
006f283a50d325840433f4cf6d15876d475bba77,Preserving Structure in Model-Free Tracking,"Preserving Structure in Model-Free Tracking Lu Zhang and Laurens van der Maaten"
00d931eccab929be33caea207547989ae7c1ef39,The Natural Input Memory Model,"The Natural Input Memory Model @@ -9206,6 +31715,26 @@ Jaap M.J. Murre Department of Computer Science, IKAT, Universiteit Maastricht, St. Jacobsstraat 6, 6211 LB Maastricht, The Netherlands Eric O. Postma H. Jaap van den Herik"
+00796052277d41e2bb3a1284d445c1747aed295f,Performance and Energy Consumption Characterization and Modeling of Video Decoding on Multi-core Heterogenous SoC and their Applications,"Performance and Energy Consumption Characterization +nd Modeling of Video Decoding on Multi-core +Heterogenous SoC and their Applications +Yahia Benmoussa +To cite this version: +Yahia Benmoussa. Performance and Energy Consumption Characterization and Modeling of +Video Decoding on Multi-core Heterogenous SoC and their Applications. Multimedia [cs.MM]. +Universit´e de Bretagne Occidentale, 2015. English. <tel-01313326> +HAL Id: tel-01313326 +https://hal.archives-ouvertes.fr/tel-01313326 +Submitted on 9 May 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
0052de4885916cf6949a6904d02336e59d98544c,Generalized Low Rank Approximations of Matrices,"005 Springer Science + Business Media, Inc. Manufactured in The Netherlands. DOI: 10.1007/s10994-005-3561-6 Generalized Low Rank Approximations of Matrices @@ -9215,10 +31744,83 @@ MN 55455, USA Editor: Peter Flach Published online: 12 August 2005"
+00319cd17cebae5e1095a248260bd7be15781362,A Dataset for Improved RGBD-Based Object Detection and Pose Estimation for Warehouse Pick-and-Place,"A Dataset for Improved RGBD-based Object +Detection and Pose Estimation for Warehouse +Pick-and-Place +Colin Rennie1, Rahul Shome1, Kostas E. Bekris1, and Alberto F. De Souza2"
+0041afaf2b17f1a33bd514db27b17ce34670fdb8,Deep Reinforcement Learning-Based Image Captioning with Embedding Reward,"Deep Reinforcement Learning-based Image Captioning with Embedding Reward +Zhou Ren1 +Xiaoyu Wang1 +Ning Zhang1 +Xutao Lv1 +Li-Jia Li2∗ +{zhou.ren, xiaoyu.wang, ning.zhang, +Snap Inc. +Google Inc."
+006350ae14784bb929b6a749d4e5c265a10168b7,Abstract Eye Detection Using Discriminatory Features and an Efficient Support Vector Machine Eye Detection Using Discriminatory Features and an Efficient Support Vector Machine Eye Detection Using Discriminatory Features and an Efficient Support Vector Machine,"Copyright Warning & Restrictions +The copyright law of the United States (Title 17, United +States Code) governs the making of photocopies or other +reproductions of copyrighted material. +Under certain conditions specified in the law, libraries and +rchives are authorized to furnish a photocopy or other +reproduction. One of these specified conditions is that the +photocopy or reproduction is not to be “used for any +purpose other than private study, scholarship, or research.” +If a, user makes a request for, or later uses, a photocopy or +reproduction for purposes in excess of “fair use” that user +may be liable for copyright infringement, +This institution reserves the right to refuse to accept a +opying order if, in its judgment, fulfillment of the order +would involve violation of copyright law. +Please Note: The author retains the copyright while the +New Jersey Institute of Technology reserves the right to +distribute this thesis or dissertation +Printing note: If you do not wish to print this page, then select +“Pages from: first page # to: last page #” on the print dialog screen"
+6ef0b43cf897f527540c29cae0618aabb7329072,Parallel Algorithms for Nearest Neighbor Search Problems in High Dimensions,"PARALLEL ALGORITHMS FOR NEAREST NEIGHBOR SEARCH +PROBLEMS IN HIGH DIMENSIONS. +BO XIAO∗ AND GEORGE BIROS†"
+6e396401b3950eccdaf8265aeae8a4f0da8965a0,Obstacle Detection Quality as a Problem-Oriented Approach to Stereo Vision Algorithms Estimation in Road Situation Analysis,"Obstacle Detection Quality as a Problem-Oriented +Approach to Stereo Vision Algorithms Estimation +in Road Situation Analysis +A.A. Smagina, D.A. Shepelev, E.I. Ershov, A.S. Grigoryev +Institute for Information Transmission Problems (Kharkevich Institute) –IITP RAS, +Bolshoy Karetny per. 19, build.1, Moscow, Russia, 127051 +E-mail:"
+6e99832e265999194aa88958d892db62afbd7ac9,Is Combinational Strategy Better For Image Memorability Prediction,"Is Combinational Strategy Better For Image +Memorability Prediction +Wenting Zhu"
6e198f6cc4199e1c4173944e3df6f39a302cf787,MORPH-II: Inconsistencies and Cleaning Whitepaper,"MORPH-II: Inconsistencies and Cleaning Whitepaper Participants: G. Bingham, B. Yip, M. Ferguson, and C. Nansalo Mentors: C. Chen, Y. Wang, and T. Kling NSF-REU Site at UNC Wilmington, Summer 2017"
+6e0288b874320b1b6461016fde8b215c3ba46b90,Recognising activities by jointly modelling actions and their effects,"This thesis has been submitted in fulfilment of the requirements for a postgraduate degree +(e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following +terms and conditions of use: +This work is protected by copyright and other intellectual property rights, which are +retained by the thesis author, unless otherwise stated. +A copy can be downloaded for personal non-commercial research or study, without +prior permission or charge. +This thesis cannot be reproduced or quoted extensively from without first obtaining +permission in writing from the author. +The content must not be changed in any way or sold commercially in any format or +medium without the formal permission of the author. +When referring to this work, full bibliographic details including the author, title, +warding institution and date of the thesis must be given."
+6e82ce9897093ce4f5fa795887273992489c380d,Face recognition using Eigensurface on Kinect depth-maps,"Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'16 | +Face recognition using Eigensurface on Kinect depth-maps +Marcelo Romero1, Cesar Flores1, Vianney Muñoz1 and Luis Carlos Altamirano2 +Universidad Autónoma del Estado de México1 and Benemérita Universidad Autónoma de Puebla2"
+6e297f10a02580dfc74595ff8d7db34020002ec4,Correlation Net : spatio temporal multimodal deep learning,"learning +Novanto Yudistira, Takio Kurita, Member, IEEE,"
+6e35585eb37ee8a1de60a10a56a3183af480e214,"The YLI-MED Corpus: Characteristics, Procedures, and Plans",
+6e7cfcefe82471a6aca78b59be0285467ce37b8b,Déjà Vu: an empirical evaluation of the memorization properties of ConvNets,"D´ej`a Vu: an empirical evaluation of the +memorization properties of ConvNets +Alexandre Sablayrolles†,(cid:63), Matthijs Douze†, Cordelia Schmid(cid:63), +nd Herv´e J´egou† +Facebook AI Research +(cid:63)Inria +September 19, 2018"
6eba25166fe461dc388805cc2452d49f5d1cdadd,"ALBANIE, VEDALDI: LEARNING GRIMACES BY WATCHING TV 1 Learning Grimaces by Watching TV","Pages 122.1-122.12 DOI: https://dx.doi.org/10.5244/C.30.122"
6e8a81d452a91f5231443ac83e4c0a0db4579974,Illumination robust face representation based on intrinsic geometrical information,"Illumination robust face representation based on intrinsic geometrical @@ -9252,6 +31854,26 @@ reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any opyrighted component of this work in other works. The"
+6ee1f57cbf7daa37576efca7e7d24040a5c94ee2,Multimodal Neural Network for Overhead Person Re-Identification,"Aalborg Universitet +Multimodal Neural Network for Overhead Person Re-identification +Lejbølle, Aske Rasch; Nasrollahi, Kamal; Krogh, Benjamin; Moeslund, Thomas B. +Published in: +6th International Conference of the Biometrics Special Interest Group +DOI (link to publication from Publisher): +0.23919/BIOSIG.2017.8053514 +Publication date: +Document Version +Accepted author manuscript, peer reviewed version +Link to publication from Aalborg University +Citation for published version (APA): +Lejbølle, A. R., Nasrollahi, K., Krogh, B., & Moeslund, T. B. (2017). Multimodal Neural Network for Overhead +Person Re-identification. In 16th International Conference of the Biometrics Special Interest Group IEEE. +https://doi.org/10.23919/BIOSIG.2017.8053514 +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. +? You may not further distribute the material or use it for any profit-making activity or commercial gain"
6ecd4025b7b5f4894c990614a9a65e3a1ac347b2,Automatic Naming of Character using Video Streaming for Face Recognition with Graph Matching,"International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 2 Issue: 5 @@ -9265,21 +31887,103 @@ PG Student at MET’s IOE Bhujbal Knowledge City, PG Student at MET’s IOE Bhujbal Knowledge City, Nasik, Maharashtra, India, Nasik, Maharashtra, India,"
+6e7b2afb4daf1fe50a62faf75018ff81c24ee526,Submitted to CVPR ' 99 Discriminant Analysis based Feature ExtractionW,"SubmittedtoCVPR' DiscriminantAnalysisbasedFeatureExtraction +W.Zhao +CenterforAutomationResearch +UniversityofMaryland +CollegePark,MD +nantAnalysishaveachievedquiteasuccessinprac-"
6e3a181bf388dd503c83dc324561701b19d37df1,Finding a low-rank basis in a matrix subspace,"Finding a low-rank basis in a matrix subspace Yuji Nakatsukasa · Tasuku Soma · Andr´e Uschmajew"
+6e1b85aabb132ed741381fdf00909475d16cd3ba,"Motor, emotional and cognitive empathic abilities in children with autism and conduct disorder","Motor, Emotional and Cognitive Empathic Abilities +in Children with Autism and Conduct Disorder +Danielle M.A. Bons1,2 ++31 (0)488 – 469 611 +Nanda N.J. Rommelse1,2 ++31 (0)24 351 2222 +Floor E. Scheepers1 +Jan K. Buitelaar1,2 +Karakter child- and adolescent psychiatry +University Centre Nijmegen, Zetten-Tiel +Department of Psychiatry UMC St. Radboud +P.O. Box 9101, 6500HB Nijmegen, The +P.O. Box 104, 6670AC Zetten, The Netherlands +the studies"
6ef1996563835b4dfb7fda1d14abe01c8bd24a05,Nonparametric Part Transfer for Fine-Grained Recognition,"Nonparametric Part Transfer for Fine-grained Recognition Christoph G¨oring, Erik Rodner, Alexander Freytag, and Joachim Denzler∗ Computer Vision Group, Friedrich Schiller University Jena www.inf-cv.uni-jena.de"
+6e75fcf384b31ea2108a81d868fbb886f39cd188,Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences,"Sparse Coding on Symmetric Positive Definite Manifolds +using Bregman Divergences +Mehrtash Harandi, Richard Hartley, Brian Lovell, Conrad Sanderson"
+6e80caed3f2ac86db775bd5e7d64925b00f1a0ca,Social interaction contexts bias the perceived expressions of interactants.,"City Research Online +City, University of London Institutional Repository +Citation: Gray, K., Barber, L., Murphy, J. & Cook, R. (2017). Social interaction contexts +0.1037/emo0000257 +This is the accepted version of the paper. +This version of the publication may differ from the final published +version. +Permanent repository link: http://openaccess.city.ac.uk/16315/ +Link to published version: http://dx.doi.org/10.1037/emo0000257 +Copyright and reuse: City Research Online aims to make research +outputs of City, University of London available to a wider audience. +Copyright and Moral Rights remain with the author(s) and/or copyright +holders. URLs from City Research Online may be freely distributed and +linked to. +City Research Online: http://openaccess.city.ac.uk/"
+6e32c368a6157fb911c9363dc3e967a7fb2ad9f7,Hybrid Stochastic / Deterministic Optimization for Tracking Sports Players and Pedestrians,"Hybrid Stochastic / Deterministic Optimization +for Tracking Sports Players and Pedestrians(cid:2) +Robert T. Collins1 and Peter Carr2 +The Pennsylvania State University, USA +Disney Research Pittsburgh, USA"
+6e44ddb54edbb80d5bb8f2ca3b36e40c486b9daf,Evolutionary 3D Mapping,"Evolutionary 3D Mapping Using the GPU +Calculating the psi similarity function for 2D images +Diana Cristina Albu +May 7, 2007 +Submitted to the School of Engineering and Sciences +in partial fulfillment of the requirements for the degree of +Bachelor of Science in Electrical Engineering and Computer Science +Jacobs University Bremen +Supervisor: Andreas Birk"
6e8c3b7d25e6530a631ea01fbbb93ac1e8b69d2f,"Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution","Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution Jonas Rothfuss∗†, Fabio Ferreira∗†, Eren Erdal Aksoy ‡, You Zhou† and Tamim Asfour†"
+6e7d799497b94954dc4232d840628c3a00263e42,Deep Multimodal Pain Recognition: A Database and Comparision of Spatio-Temporal Visual Modalities,"Aalborg Universitet +Deep Multimodal Pain Recognition: A Database and Comparison of Spatio-Temporal +Visual Modalities +Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.; B. Bautista, Ruben; +Laursen, Christian B.; Escalera, Sergio; Irani, Ramin; Andersen, Ole Kæseler; Spaich, Erika +Geraldina; Kulkarni, Kaustubh; Bellantonio, Marco; Anbarjafari, Gholamreza; Noroozi, +Fatemeh +Published in: +Proc. of the 13th IEEE Conf. on Automatic Face and Gesture Recognition +Publication date: +Link to publication from Aalborg University +Citation for published version (APA): +Haque, M. A., Nasrollahi, K., Moeslund, T. B., B. Bautista, R., Laursen, C. B., Escalera, S., ... Noroozi, F. (2018). +Deep Multimodal Pain Recognition: A Database and Comparison of Spatio-Temporal Visual Modalities. In Proc. +of the 13th IEEE Conf. on Automatic Face and Gesture Recognition (pp. 1). IEEE. +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. +? You may not further distribute the material or use it for any profit-making activity or commercial gain"
6e911227e893d0eecb363015754824bf4366bdb7,Wasserstein Divergence for GANs,"Wasserstein Divergence for GANs Jiqing Wu1, Zhiwu Huang1, Janine Thoma1, Dinesh Acharya1, and Luc Van Gool1,2 Computer Vision Lab, ETH Zurich, Switzerland VISICS, KU Leuven, Belgium"
+6e885d831568520aa95f523f625623e46578efd0,Camera Selection for Adaptive Human-Computer Interface,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012 +Camera Selection for Adaptive +Human-Computer Interface +Niki Martinel Student Member, IEEE, Christian Micheloni, Member, IEEE, +Claudio Piciarelli, Member, IEEE and Gian Luca Foresti, Senior Member, IEEE"
+6eb7ae81554ad4db92ee6b578f47be659c8b9cbd,Audio phrases for audio event recognition,"AUDIO PHRASES FOR AUDIO EVENT RECOGNITION +Huy Phan(cid:63)†, Lars Hertel(cid:63), Marco Maass(cid:63), Radoslaw Mazur(cid:63), and Alfred Mertins(cid:63) +Graduate School for Computing in Medicine and Life Sciences, University of L¨ubeck, Germany +(cid:63)Institute for Signal Processing, University of L¨ubeck, Germany +Email: {phan, hertel, maass, mazur,"
6ee8a94ccba10062172e5b31ee097c846821a822,How to solve classification and regression problems on high-dimensional data with a supervised extension of slow feature analysis,"Submitted 3/13; Revised 10/13; Published 12/13 How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised @@ -9310,6 +32014,21 @@ nger, muse- dmiration, ment,"
+6ed559a0d04e7d4185eeea43f77e372483982e4b,A Review Paper on Player Tracking and Automated Analysis in Sports Videos,"International Journal of Emerging Technology and Advanced Engineering +Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 6, June 2015) +A Review Paper on Player Tracking and Automated Analysis in +Sports Videos +Nikhil M.1, Sreejith S.2 +,2Department of ECE, Government College of Engineering Kannur, kerala, India"
+6ee3fbc4768f578601d42b1596aaf2b0cfa1d40a,Human Detection and Identification by Robots Using Thermal and Visual Information in Domestic Environments,"J Intell Robot Syst (2012) 66:223–243 +DOI 10.1007/s10846-011-9612-2 +Human Detection and Identification by Robots +Using Thermal and Visual Information +in Domestic Environments +Mauricio Correa · Gabriel Hermosilla · +Rodrigo Verschae · Javier Ruiz-del-Solar +Received: 11 December 2010 / Accepted: 30 May 2011 / Published online: 12 July 2011 +© Springer Science+Business Media B.V. 2011"
6e379f2d34e14efd85ae51875a4fa7d7ae63a662,A New Multi-modal Biometric System Based on Fingerprint and Finger Vein Recognition,"A NEW MULTI-MODAL BIOMETRIC SYSTEM BASED ON FINGERPRINT AND FINGER VEIN RECOGNITION @@ -9318,6 +32037,22 @@ Master's Thesis Department of Software Engineering Advisor: Prof. Dr. Asaf VAROL JULY-2014"
+6e74a055a70c69c287a34d86ce8b159456cf4420,Pose Recognition for Tracker Initialization Using 3 D Models,"Institutionen för systemteknik +Department of Electrical Engineering +Examensarbete +Pose Recognition for Tracker Initialization Using +D Models +Examensarbete utfört i Bildbehandling +vid Tekniska högskolan i Linköping +Martin Berg +LiTH-ISY-EX--07/4076--SE +Linköping 2008 +Department of Electrical Engineering +Linköpings universitet +SE-581 83 Linköping, Sweden +Linköpings tekniska högskola +Linköpings universitet +581 83 Linköping"
6e0a05d87b3cc7e16b4b2870ca24cf5e806c0a94,Random Graphs for Structure Discovery in High-dimensional Data,"RANDOM GRAPHS FOR STRUCTURE DISCOVERY IN HIGH-DIMENSIONAL DATA Jos¶e Ant¶onio O. Costa @@ -9341,6 +32076,24 @@ Xiang Yu† NEC Laboratories America Jianchao Yang‡ Wilmot Li§ Snapchat"
+6e261b9e539ecd03d76063f893d59c6eafb6ed43,On the Use of External Face Features for Identity Verification,"On the Use of External Face Features for +Identity Verification +`Agata Lapedriza1, David Masip2 and Jordi Vitri`a1 +Computer Vision Center (CVC), Computer Science Dept. +Universitat Aut`onoma de Barcelona +Bellaterra, Spain, 08193. +{agata, +Department of Applied Mathematics and Analysis (MAiA) +University of Barcelona (UB) +Edifici Hist`oric Gran Via de les Corts Catalanes 585, Barcelona 08007, Spain."
+6ee5205408fc6db03460c05765ae0f21a6eb9552,A literature review on recent multi-object tracking methods based on HMM and particle filter,"IOSR Journal of Computer Engineering (IOSR-JCE) +e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 2, Ver. VII (Mar-Apr. 2014), PP 05-07 +www.iosrjournals.org +A literature review on recent multi-object tracking methods +ased on HMM and particle filter +Kalyani Ahire1, Prof.P.S Mohod2 +Department of Computer Science & Engineering,, G.H.R.I.E.T.W.,RashtrasantTukdojiMaharaj Nagpur +University Nagpur, India"
6e93fd7400585f5df57b5343699cb7cda20cfcc2,Comparing a novel model based on the transferable belief model with humans during the recognition of partially occluded facial expressions.,"http://journalofvision.org/9/2/22/ Comparing a novel model based on the transferable elief model with humans during the recognition of @@ -9361,6 +32114,22 @@ during the M. Smith, G. Cottrell, F. Gosselin, and P. G. Schyns (2005) facial ex stimuli randomly sampled using Gaussian apertures. The modelVwhich we had to significantly modify in order to give the bility to deal with partially occluded stimuliVclassifies the six basic facial expressions (Happiness, Fear, Sadness, Surprise, Anger, and Disgust) plus Neutral from static images based on the permanent facial feature deformations and the"
+6e604946a0a51911db0e887378ba1ae103dcfb9e,Detection and Classification of a Moving Object in a Video Stream,"Proc. of the Intl. Conf. on Advances in Computing and Information Technology-- ACIT 2014 +Copyright © Institute of Research Engineers and Doctors. All rights reserved. +ISBN: 978-981-07-8859-9 doi: 10.3850/ 978-981-07-8859-9_23 +Detection and Classification of a Moving Object +in a Video Stream +Asim R. Aldhaheri and Eran A. Edirisinghe"
+6edb41364802b0fdd1e3e98d644fe78b1ecbbe45,Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task,"Understanding Image and Text Simultaneously: a Dual Vision-Language +Machine Comprehension Task +Nan Ding +Google +Sebastian Goodman +Google +Fei Sha +Google +Radu Soricut +Google"
9ab463d117219ed51f602ff0ddbd3414217e3166,Weighted Transmedia Relevance Feedback for Image Retrieval and Auto-annotation,"Weighted Transmedia Relevance Feedback for Image Retrieval and @@ -9372,6 +32141,12 @@ N° 0415 December 2011 Project-Teams LEAR - INRIA nd TVPA - XRCE"
+9af9fa7727df11b86301a252db8a916c3a516a8d,VIBIKNet: Visual Bidirectional Kernelized Network for Visual Question Answering,"VIBIKNet: Visual Bidirectional Kernelized +Network for Visual Question Answering +Marc Bola˜nos1,2, ´Alvaro Peris3, Francisco Casacuberta3, Petia Radeva1,2 +Universitat de Barcelona, Barcelona, Spain, +Computer Vision Center, Bellaterra, Spain, +PRHLT Research Center, Universitat Polit`ecnica de Val`encia, Val`encia, Spain,"
9ac82909d76b4c902e5dde5838130de6ce838c16,Recognizing Facial Expressions Automatically from Video,"Recognizing Facial Expressions Automatically from Video Caifeng Shan and Ralph Braspenning @@ -9392,6 +32167,9 @@ intelligent human-computer interaction, computer animation, surveillance and se- urity, medical diagnosis, law enforcement, and awareness systems (Shan, 2007). Therefore, it has been an active research topic in multiple disciplines such as psy- hology, cognitive science, human-computer interaction, and pattern recognition."
+9a6b80f8ea7e5f24e3da05a5151ba8b42494962f,Leveraging multiple tasks to regularize fine-grained classification,"Cancún Center, Cancún, México, December 4-8, 2016 +978-1-5090-4847-2/16/$31.00 ©2016 IEEE +KingfisherRingedKingfisherWhite Breasted KingfisherMegaceryleCeryleChloroceryleHalcyonAlcedinidaeHalcyonidaeFig.1.Leveragingthetaxonomicontologyofbirdsforfinegrainedrecogni-tion.Fromtoptobottom,wehavefamily,orderandspeciesforfiveclassesofkingfishersintheCUB-200-2011dataset[6].Observehowidentifyingthefamilyorordercanhelpidentifyingtheclass,e.g.incaseofringedkingfisherandgreenkingfisher.Bestviewedenlarged,incolor.differencesandstrikinginter-classsimilarities.Mostmodernmethodsforfinegrainedrecognitionrelyonacombinationoflocalizingdiscriminativeregionsandlearningcorrespondingdiscriminativefeatures.Thisinturnrequiresstrongsuper-visionsuchaskeypointorattributeannotations,whichareexpensiveanddifficulttoobtainatscale.Ontheotherhand,sincefinegrainedrecognitiondealswithsubordinate-levelclassification,thereexistsanimpliedrelationshipsamonglabels.Theserelationshipsmaybetaxonomical(suchassuperclasses)orsemantic(suchasattributes)innature.Theontol-ogyobtainedinthismannercontainsrichlatentknowledgeaboutfinerdifferencesbetweenclassesthatcanbeexploitedforvisualclassification.Themodelweproposeconsistsofasingledeepconvolutionalneuralnetwork,witheachleveloftheontologygivingrisetoanadditionalsetoflabelsfortheinputimages.Theseadditionallabelsareusedasauxiliarytasksforamulti-tasknetwork,whichcanbetrainedend-to-endusingasimpleweightedobjectivefunction.Wealsoproposeanovelmethodtodynamicallyupdatethelearningrates(hereforthreferredtoasthetaskcoefficients)foreachtaskinthemulti-tasknetwork,basedonitsrelatednesstotheprimarytask.Inthiswork,weanalyzetheutilityofjointlylearningmultiplerelated/auxiliarytasksthatcouldregularizeeachothertopreventover-fitting,whileensuringthatthenetworkretainsitsdiscriminativecapability.Muchlikedropoutisbaggingtakentotheextreme,multi-tasklearningisanalogoustoboosting,ifeachtaskisconsideredaweaklearner.Wenotethatourmodelcanbepluggedintoorusedinconjunctionwithmorecomplexmulti-stagepipelinemethodssuchas[7]–[10]"
9ac15845defcd0d6b611ecd609c740d41f0c341d,Robust Color-based Vision for Mobile Robots,"Copyright Juhyun Lee"
9af1cf562377b307580ca214ecd2c556e20df000,International Journal of Advanced Studies in Computer Science and Engineering,"Feb. 28 @@ -9402,6 +32180,7 @@ Using Local Directional Binary Pattern Sahar Hooshmand, Ali Jamali Avilaq, Amir Hossein Rezaie Electrical Engineering Dept., AmirKabir Univarsity of Technology Tehran, Iran"
+9a9af8a5b6939a1da9936608fbf071f852eca7e1,Deep Part Features Learning by a Normalised Double-Margin-Based Contrastive Loss Function for Person Re-Identification,
9a23a0402ae68cc6ea2fe0092b6ec2d40f667adb,High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs,"High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs Ting-Chun Wang1 Ming-Yu Liu1 Jun-Yan Zhu2 Andrew Tao1 @@ -9413,27 +32192,121 @@ Figure 1: We propose a generative adversarial framework for synthesizing 2048 × hange labels in the original label map to create new scenes, like replacing trees with buildings. (c) Our framework also llows a user to edit the appearance of individual objects in the scene, e.g. changing the color of a car or the texture of a road. Please visit our website for more side-by-side comparisons as well as interactive editing demos."
+9ad27106b8e0cf14e8e2814dc318142138d5527b,Camera Style Adaptation for Person Re-identification,"Camera 6Style Transfer(a) Example images under two cameras from Market-1501(b) Examples of camera-aware style transfer between two camerasrealtransferredrealtransferredFigure1.(a)ExampleimagesfromMarket-1501[42].(b)Exam-plesofcamera-awarestyletransferbetweentwocamerasusingourmethod.Imagesinthesamecolumnrepresentthesameperson.ancepropertyunderdifferentcameras.Examplesintradi-tionalapproachesincludeKISSME[16],XQDA[20],DNS[39],etc.Examplesindeeprepresentationlearningmeth-odsincludeIDE[43],SVDNet[29],TripletNet[11],etc.Comparingtopreviousmethods,thispaperresortstoanexplicitstrategyfromtheviewofcamerastyleadapta-tion.Wearemostlymotivatedbytheneedforlargedatavolumeindeeplearningbasedpersonre-ID.Tolearnrichfeatureswhicharerobusttocameravariations,annotatinglarge-scaledatasetsisusefulbutprohibitivelyexpensive.Nevertheless,ifwecanaddmoresamplestothetrainingsetthatareawareofthestyledifferencesbetweencameras,weareableto1)addressthedatascarcityprobleminpersonre-IDand2)learninvariantfeaturesacrossdifferentcameras.Preferably,thisprocessshouldnotcostanymorehumanla-beling,sothatthebudgetiskeptlow.Basedontheabovediscussions,weproposeacam-erastyle(CamStyle)adaptationmethodtoregularizeCNNtrainingforpersonre-ID.Initsvanillaversion,welearnimage-imagetranslationmodelsforeachcamerapairwithCycleGAN[51].WiththelearnedCycleGANmodel,foratrainingimagecapturedbyacertaincamera,wecangener-"
+9a7784eea6bfa62bf2834ee0b87a3cdda46006f2,Digital Comics Image Indexing Based on Deep Learning,"Article +Digital Comics Image Indexing Based on +Deep Learning +Nhu-Van Nguyen * ID , Christophe Rigaud ID and Jean-Christophe Burie ID +Lab L3I, University of La Rochelle, 17000 La Rochelle, France; (C.R.); +(J.-C.B.) +* Correspondence: +Received: 30 April 2018; Accepted: 27 June 2018; Published: 2 July 2018"
+9a9a888bcce37e582b8a5b5f12f662e487443e5c,Cascaded Pyramid Network for Multi-Person Pose Estimation,"Cascaded Pyramid Network for Multi-Person Pose Estimation +Yilun Chen∗ Zhicheng Wang∗ Yuxiang Peng1 +Zhiqiang Zhang2 Gang Yu +Jian Sun +Megvii Inc. (Face++), {chenyilun, wangzhicheng, pyx, zhangzhiqiang, yugang, +Tsinghua University 2HuaZhong University of Science and Technology"
9a7858eda9b40b16002c6003b6db19828f94a6c6,Mooney face classification and prediction by learning across tone,"MOONEY FACE CLASSIFICATION AND PREDICTION BY LEARNING ACROSS TONE Tsung-Wei Ke(cid:63)† Stella X. Yu(cid:63)† David Whitney(cid:63) (cid:63) UC Berkeley / †ICSI"
+9a2ed8abaa17834cb8f227a9353c8cfed3a367cd,A Method of Detecting Abnormal Crowd Behavior Events Applied in Air Patrol Robot,"A Method of Detecting Abnormal Crowd Behavior Events Applied in Air Patrol Robot +School of Electrical and Electronic Engineering ,Shanghai Institute of Technology, Shanghai, China +Huailin Zhao +School of Electrical and Electronic Engineering ,Shanghai Institute of Technology, Shanghai, China +Shunzhou Wang +School of Electrical and Electronic Engineering ,Shanghai Institute of Technology, Shanghai, China +Shifang Xu +School of Computer Science and Information Engineering ,Shanghai Institute of Technology, Shanghai, China +Yani Zhang +Masanori Sugisaka +Alife Robotics Corporation LTD, Oita, Japan"
+9abc9e3cadbec9139b39dfddb0de6c08b7aaf2d0,Pain Intensity Evaluation through Facial Action Units,"Pain Intensity Evaluation Through Facial Action +Units +Zuhair Zafar +Dept. of Electrical Engineering, SBASSE, +Lahore University of Management Sciences, +Lahore, Pakistan +Nadeem Ahmad Khan +Dept. of Electrical Engineering, SBASSE, +Lahore University of Management Sciences, +Lahore, Pakistan"
+9a88d23234ee41965ac17fc5774348563448a94d,3021977 GI P_212 Cover.indd,"Gesellschaft für Informatik e.V. (GI) +publishes this series in order to make available to a broad public +recent findings in informatics (i.e. computer science and informa- +tion systems), to document conferences that are organized in co- +operation with GI and to publish the annual GI Award dissertation. +Broken down into +• seminars +• proceedings +• dissertations +• thematics +urrent topics are dealt with from the vantage point of research and +development, teaching and further training in theory and practice. +The Editorial Committee uses an intensive review process in order +to ensure high quality contributions. +The volumes are published in German or English. +Information: http://www.gi.de/service/publikationen/lni/ +ISSN 1617-5468 +ISBN 978-3-88579-606-0 +The proceedings of the BIOSIG 2013 include scientific contributions of the annual +onference of the Biometrics Special Interest Group (BIOSIG) of the Gesellschaft"
9a276c72acdb83660557489114a494b86a39f6ff,Emotion Classification through Lower Facial Expressions using Adaptive Support Vector Machines,"Emotion Classification through Lower Facial Expressions using Adaptive Support Vector Machines Porawat Visutsak Department of Information Technology, Faculty of Industrial Technology and Management, King Mongkut’s University of Technology North Bangkok,"
+9ad65c5c5a2b22ef0343831fe0dabc2055d72497,Eyediap Database: Data Description and Gaze Tracking Evaluation Benchmarks,"EYEDIAP DATABASE: DATA DESCRIPTION +AND GAZE TRACKING EVALUATION +BENCHMARKS +Kenneth Alberto Funes Mora Florent Monay +Jean-Marc Odobez +Idiap-RR-08-2014 +Version of SEPTEMBER 18, 2014 +Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny +T +41 27 721 77 11 F +41 27 721 77 12 www.idiap.ch"
9a1a9dd3c471bba17e5ce80a53e52fcaaad4373e,Automatic Recognition of Spontaneous Facial Actions,"Automatic Recognition of Spontaneous Facial Actions Marian Stewart Bartlett1, Gwen C. Littlewort1, Mark G. Frank2, Claudia Lainscsek1, Ian R. Fasel1, Javier R. Movellan1 Institute for Neural Computation, University of California, San Diego. Department of Communication, University at Buffalo, State University of New York."
+9a08459b0cb133f0f4352c58225446f9dc95ecc4,Metadata of the chapter that will be visualized in SpringerLink,"Metadata of the chapter that will be visualized in +SpringerLink +Book Title +Series Title +Chapter Title +Copyright Year +Copyright HolderName +Author +Corresponding Author +Author +Author +Instituto de Investigación en Informática de Albacete +Universidad de Castilla-La Mancha +02071, Albacete, Spain +Ambient Assisted Living. ICT-based Solutions in Real Life Situations +Sokolova +Marina V. +Fernández-Caballero +Experimentation on Emotion Regulation with Single-Colored Images +Springer International Publishing Switzerland"
9a42c519f0aaa68debbe9df00b090ca446d25bc4,Face Recognition via Centralized Coordinate Learning,"Face Recognition via Centralized Coordinate Learning Xianbiao Qi, Lei Zhang"
+9a03b7b71a82fc2c86b3b4cbec802dfc16978486,One-Shot Observation Learning,"One-Shot Observation Learning +Leo Pauly, Wisdom C. Agboh, Mohamed Abdellatif, David C. Hogg, Raul Fuentes"
9aad8e52aff12bd822f0011e6ef85dfc22fe8466,Temporal-Spatial Mapping for Action Recognition,"Temporal-Spatial Mapping for Action Recognition Xiaolin Song, Cuiling Lan, Wenjun Zeng, Junliang Xing, Jingyu Yang, and Xiaoyan Sun"
+9a9019972dece591f502a2f794e81648b9e064fe,Combination of facial landmarks for robust eye localization using the Discriminative Generalized Hough Transform,"Combination of Facial Landmarks +for Robust Eye Localization +Using the Discriminative Generalized Hough Transform +Ferdinand Hahmann, Gordon B¨oer, Hauke Schramm +Institute of Applied Computer Science +University of Applied Sciences Kiel +Grenzstraße 3, 24149 Kiel"
363ca0a3f908859b1b55c2ff77cc900957653748,Local Binary Patterns and Linear Programming using Facial Expression,"International Journal of Computer Trends and Technology (IJCTT) – volume 1 Issue 3 Number 4 – Aug 2011 Local Binary Patterns and Linear Programming using Facial Expression @@ -9443,11 +32316,70 @@ Ms.P.Jennifer Dr. A. Muthu kumaravel #MCA Department, Bharath Institute of Science and Technology +B.Tech (C.S.E), Bharath University , Chennai – 73."
+36d8cc038db71a473d0c94c21f2b68a840dff21c,Unsupervised Detector Adaptation by Joint Dataset Feature Learning," + + + + + + + + + + + + !∀∀ +##!∃%&∋( ) + +∗+, + + #−./ !0!∀ + !!2!342 +,"
+36cbcd70af6f2fd3e700e0a710acd5f1f6abebcf,Matching People across Camera Views using Kernel Canonical Correlation Analysis,"Matching People across Camera Views using +Kernel Canonical Correlation Analysis +Giuseppe Lisanti , Iacopo Masi , Alberto Del Bimbo +Media Integration and Communication Center (MICC), Università degli Studi di Firenze +Viale Morgagni 65 - 50134 Firenze, Italy"
+36358eff7c34de64c0ce8aa42cf7c4da24bf8e93,Deep Metric Learning for Person Re-identification,"Deep Metric Learning for Person Re-Identification +(Invited Paper) +Dong Yi, Zhen Lei, Shengcai Liao and Stan Z. Li +Center for Biometrics and Security Research & National Laboratory of Pattern Recognition +Institute of Automation, Chinese Academy of Sciences (CASIA)"
+367231b80e8201fc9c461fbb42047b20e89ea961,Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets,"MANUEL AMTHOR, ERIK RODNER, AND JOACHIM DENZLER: IMPATIENT DNNS +Impatient DNNs – Deep Neural Networks +with Dynamic Time Budgets +Manuel Amthor +Erik Rodner +Joachim Denzler +Computer Vision Group +Friedrich Schiller University Jena +Germany +www.inf-cv.uni-jena.de"
+36fa002f36e14ab7d24ebcdd99b6589ed726b383,Detecting conversational gaze aversion using unsupervised learning,"Detecting Conversational Gaze Aversion Using +Unsupervised Learning +Matthew Roddy, Naomi Harte +ADAPT Centre, School of Engineering +Trinity College Dublin, Ireland"
+362cfe79a6822f9e317555c5e3469dd038b9053f,Damped Gauss-Newton algorithm for nonnegative Tucker decomposition,"978-1-4577-0568-7/11/$26.00 ©2011 IEEE +DY, An , G (cid:2) (cid:12)Y G A (cid:12)2 +DECOMPOSITION +. INTRODUCTION"
+364584f8313e7601b1f5134d371e98aeb61110e8,An invariant bipolar representation for 3D surfaces,"An invariant bipolar representation for 3D surfaces +M. JRIBI and F. GHORBEL +CRSITAL Laboratory / GRIFT research group, +Ecole Nationale des Sciences de l’Informatique (ENSI), +La Manouba University, 2010 La Manouba, Tunisia"
36939e6a365e9db904d81325212177c9e9e76c54,"Assessing the Accuracy of Four Popular Face Recognition Tools for Inferring Gender, Age, and Race","Assessing the Accuracy of Four Popular Face Recognition Tools for Inferring Gender, Age, and Race Soon-Gyo Jung, Jisun An, Haewoon Kwak, Joni Salminen, Bernard J. Jansen Qatar Computing Research Institute, HBKU HBKU Research Complex, Doha, P.O. Box 34110, Qatar"
+366c14f477bf2ed16b1498d1c56a7e1f2af08e69,Comparative Analysis of Statistical Shape Spaces,"Comparative Analysis of Statistical Shape Spaces +Alan Brunton∗ +Augusto Salazar† +Timo Bolkart† +Stefanie Wuhrer†"
3646b42511a6a0df5470408bc9a7a69bb3c5d742,Detection of Facial Parts based on ABLATA,"International Journal of Computer Applications (0975 – 8887) Applications of Computers and Electronics for the Welfare of Rural Masses (ACEWRM) 2015 Detection of Facial Parts based on ABLATA @@ -9460,6 +32392,19 @@ Technical Campus, Bhilai Abha Choubey Shri Shankaracharya Technical Campus, Bhilai"
+36cd55cdb1b032c8f29e011ed0637923afc46d3f,Strategies to Improve Activity Recognition Based on Skeletal Tracking: Applying Restrictions Regarding Body Parts and Similarity Boundaries †,"Article +Strategies to Improve Activity Recognition Based on +Skeletal Tracking: Applying Restrictions Regarding +Body Parts and Similarity Boundaries † +Carlos Gutiérrez-López-Franca *, Ramón Hervás and Esperanza Johnson +MAmI Research Lab, University of Castilla-La Mancha, Paseo de la Universidad 4, 13071 Ciudad Real, Spain; +(R.H.); (E.J.) +* Correspondence: +This paper is an extended version of our paper published in Gutiérrez López de la Franca, C.; Hervás, R.; +Johnson, E.; Bravo, J. Findings about Selecting Body Parts to Analyze Human Activities through Skeletal +Tracking Joint Oriented Devices. In Proceedings of the 10th International Conference on Ubiquitous +Computing and Ambient Intelligence (UCAMI 2016), Gran Canaria, Spain, 29 November–2 December 2016. +Received: 4 April 2018; Accepted: 17 May 2018; Published: 22 May 2018"
36fe39ed69a5c7ff9650fd5f4fe950b5880760b0,Tracking von Gesichtsmimik mit Hilfe von Gitterstrukturen zur Klassifikation von schmerzrelevanten Action Units,"Tracking von Gesichtsmimik mit Hilfe von Gitterstrukturen zur Klassifikation von schmerzrelevanten Action @@ -9480,6 +32425,16 @@ und ordnet diese Bewegungen bestimmten Gesichtsarealen zu. Mit die- sem Wissen kann aus den Bewegungen auf die zugeh¨origen Action Units geschlossen werden. Einleitung"
+363e5a0e4cd857e98de72a726ad6f80cea9c50ab,Fast Landmark Localization With 3D Component Reconstruction and CNN for Cross-Pose Recognition,"Fast Landmark Localization +with 3D Component Reconstruction and CNN for +Cross-Pose Recognition +Gee-Sern (Jison) Hsu, Hung-Cheng Shie, Cheng-Hua Hsieh"
+36b2aa7248152fdad7bc7f670d0b577c9728d466,Data-dependent Initializations of Convolutional Neural Networks,"Under review as a conference paper at ICLR 2016 +DATA-DEPENDENT INITIALIZATIONS OF +CONVOLUTIONAL NEURAL NETWORKS +Philipp Kr¨ahenb¨uhl1, Carl Doersch1,2, Jeff Donahue1, Trevor Darrell1 +Department of Electrical Engineering and Computer Science, UC Berkeley +Machine Learning Department, Carnegie Mellon"
36fc4120fc0638b97c23f97b53e2184107c52233,Introducing Celebrities in an Images using HAAR Cascade algorithm,"National Conference on Innovative Paradigms in Engineering & Technology (NCIPET-2013) Proceedings published by International Journal of Computer Applications® (IJCA) Introducing Celebrities in an Images using HAAR @@ -9494,6 +32449,13 @@ PES Modern College of Engg. Shivaji Nagar, Pune Shivaji Nagar, Pune Shivaji Nagar, Pune"
+361367838ee5d9d5c9a77c69c1c56b1c309ab236,Salient Object Detection: A Survey,"Salient Object Detection: A Survey +Ali Borji, Ming–Ming Cheng, Huaizu Jiang and Jia Li"
+36ca720185b62e92a7f3cce75418356a5a125d24,Template aging in 3D and 2D face recognition,"Template Aging in 3D and 2D Face Recognition +Ishan Manjani∗ +Hakki Sumerkan† +Patrick J. Flynn† +Kevin W. Bowyer†"
36ce0b68a01b4c96af6ad8c26e55e5a30446f360,Facial expression recognition based on a mlp neural network using constructive training algorithm,"Multimed Tools Appl DOI 10.1007/s11042-014-2322-6 Facial expression recognition based on a mlp neural @@ -9526,6 +32488,8 @@ Facial Expression Spacial Charts for Describing Dynamic Diversity of Facial Expr LEARNING Sujoy Paul, Sourya Roy and Amit K. Roy-Chowdhury Dept. of Electrical and Computer Engineering, University of California, Riverside, CA 92521"
+36918b2ef6b20ffb8cffe458c0067742500c6149,"""Look, some Green Circles!"": Learning to Quantify from Images","Proceedings of the 5th Workshop on Vision and Language, pages 75–79, +Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
365866dc937529c3079a962408bffaa9b87c1f06,Facial Feature Expression Based Approach for Human Face Recognition: A Review,"IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 3, May 2014. www.ijiset.com ISSN 2348 – 7968 @@ -9538,11 +32502,41 @@ required extraction of"
362a70b6e7d55a777feb7b9fc8bc4d40a57cde8c,A partial least squares based ranker for fast and accurate age estimation,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE ICASSP 2016"
+360a590703542f2ba345b432416398b6dad9e3fb,Multimodal Person Reidentification Using RGB-D Cameras,"Multi-modal Person Re-Identification +Using RGB-D Cameras +Federico Pala, Member, IEEE, Riccardo Satta, Giorgio Fumera, Member, IEEE, and Fabio Roli, Fellow, IEEE"
+36c91b1342c1357877e89b4c43f8eadb39755c0b,Recognizing Human-Object Interactions in Still Images by Modeling the Mutual Context of Objects and Human Poses,"Recognizing Human-Object Interactions in +Still Images by Modeling the Mutual Context +of Objects and Human Poses +Bangpeng Yao, Member, IEEE, and Li Fei-Fei, Member, IEEE"
+36c9731f24e5daa42c1e2c6c68258567dfa78a0a,Movement tracking in terrain conditions accelerated with CUDA,"Proceedings of the 2014 Federated Conference on +Computer Science and Information Systems pp. 709–717 +DOI: 10.15439/2014F282 +ACSIS, Vol. 2 +978-83-60810-58-3/$25.00 c(cid:13) 2014, IEEE"
+3678dac7e9998567b92f526046a16e2910ced55d,Talking Robots: grounding a shared lexicon in an unconstrained environment,"Berthouze, L., Prince, C. G., Littman, M., Kozima, H., and Balkenius, C. (2007). +Proceedings of the Seventh International Conference on Epigenetic Robotics: Modeling +Cognitive Development in Robotic Systems. Lund University Cognitive Studies, 135. +Talking Robots: grounding a shared lexicon in an +unconstrained environment +Matthieu Nottale +Jean-Christophe Baillie +ENSTA-UEI cognitive robotics lab."
3630324c2af04fd90f8668f9ee9709604fe980fd,Image Classification With Tailored Fine-Grained Dictionaries,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2016.2607345, IEEE Transactions on Circuits and Systems for Video Technology Image Classification with Tailored Fine-Grained Dictionaries Xiangbo Shu, Jinhui Tang, Guo-Jun Qi, Zechao Li, Yu-Gang Jiang and Shuicheng Yan"
+36513f869e5ba2928369014244dff998ab93728c,Discriminative cluster analysis,"Chapter 1 +Discriminative Cluster Analysis +Fernando De la Torre and Takeo Kanade"
+36973330ae638571484e1f68aaf455e3e6f18ae9,Scale-Aware Fast R-CNN for Pedestrian Detection,"Scale-aware Fast R-CNN for Pedestrian Detection +Jianan Li, Xiaodan Liang, ShengMei Shen, Tingfa Xu, and Shuicheng Yan"
+36b322095bd0953d6076096111e4a020f427793b,Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +Large Displacement Optical Flow: +Descriptor Matching in Variational +Motion Estimation +Thomas Brox, Jitendra Malik, Fellow, IEEE"
36cf96fe11a2c1ea4d999a7f86ffef6eea7b5958,RGB-D Face Recognition With Texture and Attribute Features,"RGB-D Face Recognition with Texture and Attribute Features Gaurav Goswami, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE, and Richa Singh, Senior @@ -9552,6 +32546,86 @@ FEATURES Burcu Kepenekci 1,2, F. Boray Tek 1,2, Gozde Bozdagi Akar 1 Department of Electrical And Electronics Engineering, METU, Ankara, Turkey 7h%ł7$.(cid:3)%ł/7(1(cid:15)(cid:3)$QNDUD(cid:15)(cid:3)7XUNH\"
+36f039e39efde3558531b99d85cd9e3ab7d396b3,Efficiency of Recognition Methods for Single Sample per Person Based Face Recognition,"Efficiency of Recognition Methods for Single +Sample per Person Based Face Recognition +Miloš Oravec, Jarmila Pavlovičová, Ján Mazanec, +Ľuboš Omelina, Matej Féder and Jozef Ban +Faculty of Electrical Engineering and Information Technology +Slovak University of Technology in Bratislava +Slovakia +. Introduction +Even for the present-day computer technology, the biometric recognition of human face is +difficult task and continually evolving concept in the area of biometric recognition. The +rea of face recognition is well-described today in many papers and books, e.g. (Delac et al., +008), (Li & Jain, 2005), (Oravec et al., 2010). The idea that two-dimensional still-image face +recognition in controlled environment is already a solved task is generally accepted and +several benchmarks evaluating recognition results were done in this area (e.g. Face +Recognition Vendor Tests, FRVT 2000, 2002, 2006, http://www.frvt.org/). Nevertheless, +many tasks have to be solved, such as recognition in unconstrained environment, +recognition of non-frontal images, single sample per person problem, etc. +This chapter deals with single sample per person face recognition (also called one sample +per person problem). This topic is related to small sample size problem in pattern +recognition. Although there are also advantages of single sample – fast and easy creation of"
+367b5b814aa991329c2ae7f8793909ad8c0a56f1,Performance evaluation of random set based pedestrian tracking algorithms,"Performance Evaluation of Random Set Based +Pedestrian Tracking Algorithms +Branko Ristic +ISR Division +Australia +Jamie Sherrah +ISR Division +Australia +´Angel F. Garc´ıa-Fern´andez +Department of Signals and Systems +Chalmers University of Technology +Sweden"
+36688a79cc8926f489ccb6e6dadba15afbb4b6a4,Linear discriminant analysis for the small sample size problem: an overview,"Int. J. Mach. Learn. & Cyber. +DOI 10.1007/s13042-013-0226-9 +O R I G I N A L A R T I C L E +Linear discriminant analysis for the small sample size problem: +n overview +Alok Sharma • Kuldip K. Paliwal +Received: 19 March 2013 / Accepted: 26 December 2013 +Ó Springer-Verlag Berlin Heidelberg 2014"
+368132f8dfcbd6e857dfc1b7dce2ab91bd9648ad,"Simultaneous Localization And Mapping: Present, Future, and the Robust-Perception Age","Simultaneous Localization And Mapping: +Present, Future, and the Robust-Perception Age +Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, +Davide Scaramuzza, Jos´e Neira, Ian D. Reid, John J. Leonard"
+367008b91eb57c5ea64ef7520dfcabc0c5c85532,"Person Re-identification: Past, Present and Future","JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Person Re-identification: +Past, Present and Future +Liang Zheng, Yi Yang, and Alexander G. Hauptmann"
+365b72a225a18a930b96e7c0b215b9fede8a0968,Storyline Reconstruction for Unordered Images,"Storyline Reconstruction for Unordered Images +Final Paper +Sameedha Bairagi, Arpit Khandelwal, Venkatesh Raizaday +Introduction: +Storyline reconstruction is a relatively new topic and has not been researched extensively. The +main objective is to take a stream of images as input and re-shuffle them in chronological order. +The recent growth of online multimedia data has generated lots and lots of unstructured data on +the web. Image streams are generated daily on websites like Flicker, Instagram etc. and almost +00 hours of video is uploaded on YouTube on a daily basis. +In this paper, we try and implement an algorithm which uses the property of videos of being +temporally adept to sort a stream of unordered images. The basic process is as follows: +- Generate key frames/video summary of a video from multiple instances of the same +ategory. +- Cluster these key frames on the basis of the action being performed in them. +- Create a graph from these clusters using temporal data from the videos. +- Take an input stream of images and assign each image to its most probable cluster. +- Use the graph to assign ordering to the images. +In the following sections, we will try and go deep into each of the step mentioned above and +discuss multiple approaches we implemented to do the same. +Background and Related work:"
+362250566948f17693b737122fc1434173982da8,Automatic Image Annotation using Weakly Labelled Web Data,"Automatic Image Annotation using +Weakly Labelled Web Data +Pravin Kakar, Xiangyu Wang and Alex Yong-Sang Chia +Social Media and Internet Vision Analytics Lab, +Institute for Infocomm Research, +#21-01, 1 Fusionopolis Way, +{kakarpv, wangx, +Singapore 138632."
+36ab143da8b6f6d49811afaaa7bcbf81c22a210e,Modeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Modeling Multimodal Clues in a Hybrid Deep +Learning Framework for Video Classification +Yu-Gang Jiang, Zuxuan Wu, Jinhui Tang, Zechao Li, Xiangyang Xue, Shih-Fu Chang"
366595171c9f4696ec5eef7c3686114fd3f116ad,Algorithms and Representations for Visual Recognition,"Algorithms and Representations for Visual Recognition Subhransu Maji @@ -9560,6 +32634,47 @@ University of California at Berkeley Technical Report No. UCB/EECS-2012-53 http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-53.html May 1, 2012"
+3607afdb204de9a5a9300ae98aa4635d9effcda2,Face Description with Local Binary Patterns: Application to Face Recognition,"Face Description with Local Binary Patterns: +Application to Face Recognition +Timo Ahonen, Student Member, IEEE, Abdenour Hadid, +nd Matti Pietik¨ainen, Senior Member, IEEE"
+367c571480ac46d48be050dee4e6103a0ebb5db5,Multimedia Content Based Image Retrieval Iii: Local Tetra Pattern,"Manas M N et al Int. Journal of Engineering Research and Applications www.ijera.com +ISSN : 2248-9622, Vol. 4, Issue 6( Version 3), June 2014, pp.104-107 +RESEARCH ARTICLE +OPEN ACCESS +Multimedia Content Based Image Retrieval Iii: Local Tetra +Pattern +Nagaraja G S1, Rajashekara Murthy S2, Manas M N3, Sridhar N H4 +(Department of CSE, RVCE, Visvesvaraya Technological University, Bangalore-59, Karnataka, India) +(Department of ISE, RVCE, Visvesvaraya Technological University, Bangalore-59, Karnataka, India) +(M. Tech, Department of CSE, RVCE, Visvesvaraya Technological University, Bangalore-59, Karnataka, +India) +(Research Scholar, Department of CSE, RVCE, Visvesvaraya Technological University, Bangalore-59, +Karnataka, India)"
+36119c10f75094e0568cae8256400c94546d973b,The CASIA NIR-VIS 2.0 Face Database,"The CASIA NIR-VIS 2.0 Face Database +Stan Z. Li, Dong Yi, Zhen Lei and Shengcai Liao +Center for Biometrics and Security Research & National Laboratory of Pattern Recognition +Institute of Automation, Chinese Academy of Sciences (CASIA) +szli, dyi, zlei,"
+36b9faf0d6c4c6296193b8d5d7833624a181624c,Real-Time Multiple Human Perception With Color-Depth Cameras on a Mobile Robot,"Real-Time Multiple Human Perception +with Color-Depth Cameras on a Mobile Robot +Hao Zhang, Student Member, IEEE, Christopher Reardon, Student Member, IEEE, and Lynne E. Parker, Fellow, IEEE"
+5c6ccca19179fd217a74ccb954a4c4370e4203e2,Correspondences of Persistent Feature Points on Near-Isometric Surfaces,"Correspondences of Persistent Feature Points +on Near-Isometric Surfaces +Ying Yang1,2, David G¨unther1,3, Stefanie Wuhrer3,1, Alan Brunton3,4 +Ioannis Ivrissimtzis2, Hans-Peter Seidel1, Tino Weinkauf1 (cid:63) +MPI Informatik 2Durham University 3Saarland University 4University of Ottawa"
+5cb343e447c7fd933ff8f57fc9c99c5673cad97d,MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild,"MoCap-guided Data Augmentation +for 3D Pose Estimation in the Wild +Grégory Rogez +Cordelia Schmid +Inria Grenoble Rhône-Alpes, Laboratoire Jean Kuntzmann, France"
+5ca2e14f91dffb4784c443fe5cfe7838c3f3713c,Convolutional Recurrent Predictor: Implicit Representation for Multi-target Filtering and Tracking,"Convolutional Recurrent Predictor: +Implicit Representation for Multi-target Filtering and Tracking +Mehryar Emambakhsh, Alessandro Bay and Eduard Vazquez +{mehryar.emambakhsh, alessandro.bay, +Cortexica Vision Systems +London, UK"
5c6de2d9f93b90034f07860ae485a2accf529285,Compensating for pose and illumination in unconstrained periocular biometrics,"Int. J. Biometrics, Vol. X, No. Y, xxxx Compensating for pose and illumination in unconstrained periocular biometrics @@ -9573,8 +32688,135 @@ Fax: +351-275-319899 E-mail: E-mail: *Corresponding author"
+5c5dbca68946434afb201f0df90011104c85e4c4,Robust 3D Patch-Based Face Hallucination,"Robust 3D Patch-Based Face Hallucination +Chengchao Qu1,2 Christian Herrmann1,2 Eduardo Monari2 Tobias Schuchert2 +J¨urgen Beyerer2,1 +Vision and Fusion Laboratory (IES), Karlsruhe Institute of Technology (KIT) +Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (Fraunhofer IOSB)"
+5cc9fdd3a588f6e62e46d7884c1dbeef92a782f2,Spontaneous attention to faces in Asperger syndrome using ecologically valid static stimuli.,"Durham Research Online +Deposited in DRO: +6 December 2014 +Version of attached le: +Accepted Version +Peer-review status of attached le: +Peer-reviewed +Citation for published item: +Hanley, M. and McPhillips, M. and Mulhern, G. and Riby, D. M. (2013) 'Spontaneous attention to faces in +Asperger Syndrome using ecologically valid static stimuli.', Autism., 17 (6). pp. 754-761. +Further information on publisher's website: +http://dx.doi.org/10.1177/1362361312456746 +Publisher's copyright statement: +Use policy +The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for +personal research or study, educational, or not-for-pro t purposes provided that: +• a full bibliographic reference is made to the original source +• a link is made to the metadata record in DRO +• the full-text is not changed in any way +The full-text must not be sold in any format or medium without the formal permission of the copyright holders."
+5c7db2907c586f4f2d6ae5937b0dc0f4d1bc834a,Deliverable D2.1 Audio-visual Algorithms for Person Tracking and Characterization (baseline),"MULTIMODAL MALL ENTERTAINMENT ROBOT +mummer-project.eu +Grant No. 688147. Project started 2016-03-01. Duration 48 months. +DELIVERABLE D2.1 +AUDIO-VISUAL ALGORITHMS FOR PERSON +TRACKING AND CHARACTERIZATION (BASELINE) +Jean-Marc Odobez (Idiap), Natalia Lyubova (SBRE), +Olivier Can´evet (Idiap), Kenneth Funes Mora (Idiap), +Weipeng He (Idiap), Angel Martinez Gonzalez (Idiap), +Jean-Marc Montanier (SBRE), Marc Moreaux (SBRE) +Beneficiaries: +Workpackage: +Idiap Research Institute (lead), SoftBank Robotics Europe +Active Multimodal Sensing and Perception +Version: +Nature: +Dissemination level: +Pages: +017-3-3 +Draft"
+5c0dc4dff1dfb5e27b19bef0713bccd9f85ce3b2,Joint probabilistic pedestrian head and body orientation estimation,"014 IEEE Intelligent Vehicles Symposium (IV) +June 8-11, 2014. Dearborn, Michigan, USA +978-1-4799-3637-3/14/$31.00 ©2014 IEEE"
+5c8ad080ccb3f5e3c999c2948029f0bd005d5635,Engaging Image Captioning,"ENGAGING IMAGE CAPTIONING VIA PERSONALITY +Kurt Shuster, Samuel Humeau, Hexiang Hu, Antoine Bordes, Jason Weston +Facebook AI Research"
+5c81048593a6729b2d0b948a1129a97bdbf82f11,Moving Object Localization Using Optical Flow for Pedestrian Detection from a Moving Vehicle,"Hindawi Publishing Corporation +e Scientific World Journal +Volume 2014, Article ID 196415, 8 pages +http://dx.doi.org/10.1155/2014/196415 +Research Article +Moving Object Localization Using Optical Flow for Pedestrian +Detection from a Moving Vehicle +Joko Hariyono, Van-Dung Hoang, and Kang-Hyun Jo +Graduate School of Electrical Engineering, University of Ulsan, Ulsan 680-749, Republic of Korea +Correspondence should be addressed to Kang-Hyun Jo; +Received 9 April 2014; Revised 7 June 2014; Accepted 8 June 2014; Published 10 July 2014 +Academic Editor: Yu-Bo Yuan +Copyright © 2014 Joko Hariyono et al. This is an open access article distributed under the Creative Commons Attribution License, +which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +This paper presents a pedestrian detection method from a moving vehicle using optical flows and histogram of oriented gradients +(HOG). A moving object is extracted from the relative motion by segmenting the region representing the same optical flows after +ompensating the egomotion of the camera. To obtain the optical flow, two consecutive images are divided into grid cells 14 × 14 +pixels; then each cell is tracked in the current frame to find corresponding cell in the next frame. Using at least three corresponding +ells, affine transformation is performed according to each corresponding cell in the consecutive images, so that conformed optical +flows are extracted. The regions of moving object are detected as transformed objects, which are different from the previously"
+5c271b5f96cfce1b4fdacc728ae8f8ebcbc738f9,A framework for implicit human-centered image tagging inspired by attributed affect,"Vis Comput (2013) +O R I G I NA L A RT I C L E +A framework for implicit human centered image tagging +inspired by attributed affect +Konstantinos C. Apostolakis · Petros Daras +Published online: +© Springer-Verlag Berlin Heidelberg 2013"
+5cfa8d0384bcdf5dfd7501561c748e69f3a2a747,Lip AUs Detection by Boost-SVM and Gabor,"Lip AUs Detection by Boost-SVM and Gabor +Xianmei Wang, Yuyu Liang, Xiujie Zhao and Zhiliang Wang +School of Computer and Communication Engineering, University of Science and Technology, Beijing, China +Email:"
5c2e264d6ac253693469bd190f323622c457ca05,Improving large-scale face image retrieval using multi-level features,"978-1-4799-2341-0/13/$31.00 ©2013 IEEE ICIP 2013"
+5c48f97a8a8217025abafeababaef6288fd7ded6,Model syndromes for investigating social cognitive and affective neuroscience: a comparison of Autism and Williams syndrome.,"doi:10.1093/scan/nsl035 +SCAN (2006) 1of 8 +Model syndromes for investigating social cognitive +nd affective neuroscience: a comparison of +utism and Williams syndrome +Helen Tager-Flusberg, Daniela Plesa Skwerer, and Robert M. Joseph +Boston University School of Medicine, Boston, MA, USA +Autism and Williams syndrome are genetically based neurodevelopmental disorders that present strikingly different social +phenotypes. Autism involves fundamental impairments in social reciprocity and communication, whereas people with Williams +syndrome are highly sociable and engaging. This article reviews the behavioral and neuroimaging literature that has explored the +neurocognitive mechanisms that underlie these contrasting social phenotypes, focusing on studies of face processing. The article +oncludes with a discussion of how the social phenotypes of both syndromes may be characterized by impaired connectivity +etween the amygdala and other critical regions in the ’social brain’. +Keywords: autism; Williams syndrome; face processing; emotion processing; amygdala +INTRODUCTION +For the past two decades autism, (ASD)1 and Williams +syndrome (WMS) have captured the interest and imagina- +tion of cognitive neuroscientists. These neurodevelopmental +disorders present striking phenotypes that hold out the +promise of advancing our understanding of the biological"
+5cdc02ed9f456219369fe3115321564c9955b9ae,Real-time Analysis and Visualization of the YFCC100m Dataset,"Real-time Analysis and Visualization +of the YFCC100m Dataset +Firstname Lastname +Institute +City, Country"
+5ce40105e002f9cb428a029e8dec6efe8fad380e,Co-design of architectures and algorithms for mobile robot localization and model-based detection of obstacles. (Co-conception d'architectures et d'algorithmes pour la localisation de robots mobiles et la détection d'obstacles basée sur des modèles),"Co-design of architectures and algorithms for mobile +robot localization and model-based detection of obstacles +Daniel Törtei +To cite this version: +Daniel Törtei. Co-design of architectures and algorithms for mobile robot localization and model-based +detection of obstacles. Embedded Systems. Université Paul Sabatier - Toulouse III, 2016. English. +<NNT : 2016TOU30294>. <tel-01477662v2> +HAL Id: tel-01477662 +https://tel.archives-ouvertes.fr/tel-01477662v2 +Submitted on 16 Feb 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
5c5e1f367e8768a9fb0f1b2f9dbfa060a22e75c0,Reference Face Graph for Face Recognition,"Reference Face Graph for Face Recognition Mehran Kafai, Member, IEEE, Le An, Student Member, IEEE, and Bir Bhanu, Fellow, IEEE"
5c35ac04260e281141b3aaa7bbb147032c887f0c,Face Detection and Tracking Control with Omni Car,"Face Detection and Tracking Control with Omni Car @@ -9592,14 +32834,163 @@ Research Center and Laboratoire d’Informatique de Grenoble (LIG) 655 avenue de l’Europe 8 334 Saint Ismier Cedex, France"
+5c315aae464602115674716a7f976c4992fcb98e,Teachers’ Perception in the Classroom,"Teachers’ Perception in the Classroom +¨Omer S¨umer1 +Patricia Goldberg1 +Kathleen St¨urmer1 +Tina Seidel3 +Peter Gerjets2 Ulrich Trautwein1 +Enkelejda Kasneci1 +University of T¨ubingen, Germany +Leibniz-Institut f¨ur Wissensmedien, Germany +Technical University of Munich, Germany"
+5c77901df1e0f52a9774b39e730c31afbc1214a7,Learning Social Tag Relevance by Neighbor Voting,"Learning Social Tag Relevance by Neighbor Voting +Xirong Li, Cees G. M. Snoek, Member, IEEE, Marcel Worring, Member, IEEE"
+5cb1277bc7257e7b4cfc1699199c6d8e13ff0b1a,Refining Synthetic Images with Semantic Layouts by Adversarial Training,"Proceedings of Machine Learning Research 95:863-878, 2018 +ACML 2018 +Refining Synthetic Images with Semantic Layouts by +Adversarial Training +Tongtong Zhao +Dalian Maritime University +Dalian 116026, China +Yuxiao Yan +Dalian Maritime University +Dalian 116026, China +JinJia Peng +Dalian Maritime University +Dalian 116026, China +HaoHui Wei +Dalian Maritime University +Dalian 116026, China +Xianping Fu +Dalian Maritime University +Dalian 116026, China +Editors: Jun Zhu and Ichiro Takeuchi"
+5c9c153f705a02e157adcf49dccf4f1eeb70cf93,Learning Appearance Transfer for Person Re-identification,"Learning Appearance Transfer for Person +Re-identification +Tamar Avraham and Michael Lindenbaum"
+5c1e0e94d6cb74448c7b3c1e0db42121be4e9bd6,Saliency Detection using regression trees on hierarchical image segments,"SALIENCY DETECTION USING REGRESSION TREES ON +HIERARCHICAL IMAGE SEGMENTS +G¨okhan Yildirim, Appu Shaji, Sabine S¨usstrunk +School of Computer and Communication Sciences +´Ecole Polytechnique F´ed´erale de Lausanne"
+5c3fd194ba96c5eea41c0772ad0b2292dedcd197,Understanding the Energy Saving Potential of Smart Scale Selection in the Viola and Jones Facial Detection Algorithm,
+5cff58d081a4732b11e6da498196ed6fbb54d15b,Adversarial Examples for Semantic Segmentation and Object Detection,"Adversarial Examples for Semantic Segmentation and Object Detection +Cihang Xie1*, Jianyu Wang2*, Zhishuai Zhang1∗, Yuyin Zhou1, Lingxi Xie1, Alan Yuille1 +Department of Computer Science, The Johns Hopkins University, Baltimore, MD 21218 USA +{cihangxie306, wjyouch, zhshuai.zhang, zhouyuyiner, 198808xc, +Baidu Research USA, Sunnyvale, CA 94089 USA"
+5cd11d6b6cb7a2b8c00fcb535879edbd6b008a01,Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras,"Large-Scale Direct Sparse Visual Odometry with Stereo Cameras +Stereo DSO: +Rui Wang∗, Martin Schw¨orer∗, Daniel Cremers +Technical University of Munich +{wangr, schwoere,"
+5c09d905f6d4f861624821bf9dfe2aae29137e9c,Women Also Snowboard: Overcoming Bias in Captioning Models,"Women also Snowboard: +Overcoming Bias in Captioning Models +Lisa Anne Hendricks * 1 Kaylee Burns * 1 Kate Saenko 2 Trevor Darrell 1 Anna Rohrbach 1"
+5cead7ba087ebe7314f96d875f3d3dbb8dbed1c7,Automatic Food Intake Assessment Using Camera Phones,"Michigan Technological University +Digital Commons Michigan +Dissertations, Master's Theses and Master's Reports +- Open +Dissertations, Master's Theses and Master's Reports +Automatic Food Intake Assessment Using Camera +Phones +Fanyu Kong +Michigan Technological University +Copyright 2012 Fanyu Kong +Recommended Citation +Kong, Fanyu, ""Automatic Food Intake Assessment Using Camera Phones"", Dissertation, Michigan Technological University, 2012. +http://digitalcommons.mtu.edu/etds/494 +Follow this and additional works at: http://digitalcommons.mtu.edu/etds +Part of the Computer Engineering Commons"
+5cebc83001ea0737cc46360850fd294327c82013,MEMORY-BASED GAIT RECOGNITION 1 Memory-based Gait Recognition,"DANLIUet al.:MEMORY-BASEDGAITRECOGNITION +Memory-based Gait Recognition +Dan Liu +Mao Ye∗ +Xudong Li +Feng Zhang +Lan Lin +School of Computer Science and +Engineering, +Center for Robotics, +Key Laboratory for NeuroInformation of +Ministry of Education, +University of Electronic Science and +Technology of China, +Chengdu 611731, P.R. China"
+5cd34abb1e96e0c11f427364e40b1e87d6fc62c2,Greedy Part-Wise Learning of Sum-Product Networks,"Greedy Part-Wise Learning of Sum-Product +Networks +Robert Peharz, Bernhard C. Geiger and Franz Pernkopf +{robert.peharz, geiger, +Signal Processing and Speech Communication Laboratory +Graz, University of Technology"
5c02bd53c0a6eb361972e8a4df60cdb30c6e3930,Multimedia stimuli databases usage patterns: a survey report,"Multimedia stimuli databases usage patterns: a survey report M. Horvat1, S. Popović1 and K. Ćosić1 University of Zagreb, Faculty of Electrical Engineering and Computing Department of Electric Machines, Drives and Automation Zagreb, Croatia"
+5c5304b79ebc2afd28ade6bb88daa80144ae3587,Review of Human-Robot Interactive Modelling and Application for Elders,"COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 408-413 +Han Jing, Xie, Lun Xu Shangmou, Wang Zhiliang +Review of Human-Robot Interactive Modelling and +Application for Elders +Jing Han, Lun Xie*, Shangmou Xu, Zhiliang Wang +School of Computer and Communication Engineering, University of Science and Technology Beijing, No.30 Xueyuan road, Beijing, China +Received 23 November 2014, www.cmnt.lv"
5c717afc5a9a8ccb1767d87b79851de8d3016294,A novel eye region based privacy protection scheme,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE ICASSP 2012"
+5c879f9e2e79d6c6af8d4c821575e73876240a83,DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain,"Journal of Machine Learning Research 66 (2017) 1-16 +Submitted 5/17; Published 08/17 +DeepFaceLIFT: Interpretable Personalized Models +for Automatic Estimation of Self-Reported Pain +Dianbo Liu*2,3 +Fengjiao Peng*1 +Andrew Shea*3 +Ognjen (Oggi) Rudovic1 +Rosalind Picard1 +Media Lab, MIT, Cambridge, MA, USA +Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA +Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA"
+0971a5e835f365b6008177a867cfe4bae76841a5,Supervised Dictionary Learning by a Variational Bayesian Group Sparse Nonnegative Matrix Factorization,"Supervised Dictionary Learning by a +Variational Bayesian Group Sparse +Nonnegative Matrix Factorization +Ivan Ivek"
+09f4e1064afffd8464e9fd558fc8ef7be5e33170,Spatial and Temporal Organization of the Individual Human Cerebellum,"Article +Spatial and Temporal Organization of the Individual +Human Cerebellum"
+098388c08ef7d23ab583819b793b0057c0396dc8,Low Rank Approximation using Error Correcting Coding Matrices,"Low Rank Approximation using Error Correcting Coding Matrices +Shashanka Ubaru +Arya Mazumdar +Yousef Saad +University of Minnesota-Twin Cities, MN USA"
+092f955f701b31f3e58adb57c57e39a4dcab9fcd,Weighted Additive Criterion for Linear Dimension Reduction,"Seventh IEEE International Conference on Data Mining +Seventh IEEE International Conference on Data Mining +Seventh IEEE International Conference on Data Mining +Seventh IEEE International Conference on Data Mining +Seventh IEEE International Conference on Data Mining +Weighted Additive Criterion for Linear Dimension Reduction +Jing Peng & Stefan Robila +Computer Science Department, Montclair State University +Montclair, NJ 07043"
+09e5f2f819a21162d833f356670a140cd555a740,Adaptive Algorithm and Platform Selection for Visual Detection and Tracking,"Adaptive Algorithm and Platform Selection for +Visual Detection and Tracking +Shu Zhang, Qi Zhu, and Amit K. Roy-Chowdhury"
+096e68f8d632f4363056d54a7de9c59d66b806d8,Impaired visuocortical discrimination learning of socially conditioned stimuli in social anxiety.,"Impaired Visuocortical Discrimination Learning of Socially +Conditioned Stimuli in Social Anxiety +Lea M. Ahrens1, Andreas Mühlberger2, Paul Pauli1, & Matthias J. Wieser1 +Department of Psychology I, University of Würzburg, Germany +Department of Clinical Psychology and Psychotherapy, University of Regensburg, Germany +Address for correspondence: +Lea M. Ahrens, University of Würzburg, Department of Psychology, Biological Psychology, Clinical +Psychology, and Psychotherapy, Marcusstr. 9-11, D-97070 Würzburg, Phone.: +49 931 31-81929, +Fax: +49 931 31-82733, +Running title: +Social Conditioning in Social Anxiety +Words: 4995 (+ 8 place marker) +© The Author (2014). Published by Oxford University Press. For Permissions, please email:"
+0969aa7d4557699b7460e4159658828efafed8bd,Con-Text: Text Detection for Fine-Grained Object Classification,"Con-Text: Text Detection for Fine-grained Object +Classification +Sezer Karaoglu, Ran Tao, Jan C. van Gemert and Theo Gevers, Member, IEEE,"
096eb8b4b977aaf274c271058feff14c99d46af3,Multi-observation visual recognition via joint dynamic sparse representation,"REPORT DOCUMENTATION PAGE Form Approved OMB NO. 0704-0188 including @@ -9620,25 +33011,140 @@ regarding this burden estimate or any other aspect of Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA, 22202-4302. Headquarters Services, Directorate"
+09d9d9d153119558e83643f0097ffb87e1037649,Face Recognition and Verification Using Artificial Neural Network,"©2010 International Journal of Computer Applications (0975 – 8887) +Volume 1 – No. 14 +Face Recognition and Verification +Using Artificial Neural Network +Ms. S. S.Ranawade +Maharashtra Institute Technology, Pune 05 +/ nonface +images. We solve"
09137e3c267a3414314d1e7e4b0e3a4cae801f45,Two Birds with One Stone: Transforming and Generating Facial Images with Iterative GAN,"Noname manuscript No. (will be inserted by the editor) Two Birds with One Stone: Transforming and Generating Facial Images with Iterative GAN Dan Ma · Bin Liu · Zhao Kang · Jiayu Zhou · Jianke Zhu · Zenglin Xu Received: date / Accepted: date"
+092d5bc60a21933abf98aa85ace8a9c85df16958,Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments,"Implementing Randomized Matrix Algorithms in Parallel and +Distributed Environments +Jiyan Yang ∗ +Xiangrui Meng † +Michael W. Mahoney ‡"
+09d78009687bec46e70efcf39d4612822e61cb8c,Consistent Re-identification in a Camera Network,"Consistent Re-identification in a Camera +Network +Abir Das(cid:2), Anirban Chakraborty(cid:2), and Amit K. Roy-Chowdhury(cid:2)(cid:2) +Dept. of Electrical Engineering, University of California, Riverside, CA 92521, USA"
09926ed62511c340f4540b5bc53cf2480e8063f8,Tubelet Detector for Spatio-Temporal Action Localization,"Action Tubelet Detector for Spatio-Temporal Action Localization Vicky Kalogeiton1,2 Philippe Weinzaepfel3 Vittorio Ferrari2 Cordelia Schmid1"
+0917de8a3be50f2a813e7b77fc53b81125a58acb,Video based head detection and tracking surveillance system,978-1-4673-0024-7/10/$26.00 ©2012 IEEE 2832
+09fbfb566a8f2af9df4d3a1bf5df00d0693a22eb,Conformal Prediction for Automatic Face Recognition,"Proceedings of Machine Learning Research 60:1–20, 2017 Conformal and Probabilistic Prediction and Applications +Conformal Prediction for Automatic Face Recognition +Charalambos Eliades +Harris Papadopoulos +Computer Science and Engineering Department, Frederick University, +7 Y. Frederickou St., Palouriotisa, Nicosia 1036, Cyprus +Editor: Alex Gammerman, Vladimir Vovk, Zhiyuan Luo, and Harris Papadopoulos"
+0965a62c9c354d2c7175e313ade9e38120f1bd4e,Efficient Face Detection Method using Modified Hausdorff Distance Method with C 4 . 5 Classifier and Canny Edge Detection,"International Journal of Computer Applications (0975 – 8887) +Volume 123 – No.10, August 2015 +Efficient Face Detection Method using Modified +Hausdorff Distance Method with C4.5 Classifier and +Canny Edge Detection +Neelima Singh +Research Scholar +Computer Science and +Engineering Department +Samrat Ashok Technological +Institute, Vidisha, M. P. +Satish Pawar +Assistant Professor +Computer Science and +Engineering Department +Samrat Ashok Technological +Institute, Vidisha, M. P. +Yogendra Kumar Jain +Head of Department +Computer Science and"
+09eaa332ddcd036b0f0950bbdb3624072f105a3b,When appearance does not match accent: neural correlates of ethnicity-related expectancy violations.,"doi: 10.1093/scan/nsw148 +Advance Access Publication Date: 19 October 2016 +Original article +When appearance does not match accent: neural +orrelates of ethnicity-related expectancy violations +Karolina Hansen,1 Melanie C. Steffens,2 Tamara Rakic,3 and Holger Wiese4 +University of Warsaw, Warsaw, Poland, 2University of Koblenz-Landau, Landau, Germany, 3Lancaster +University, Lancaster, UK, and 4Durham University, Durham, UK +Correspondence should be addressed to Karolina Hansen, Faculty of Psychology, University of Warsaw, Stawki 5/7, 00-183 Warszawa, Poland. +E-mail:"
+09c4732280c3b2586e390d818ef0056a8de73e2c,A New Method of Histogram Computation for Efficient Implementation of the HOG Algorithm,"Article +A New Method of Histogram Computation for +Efficient Implementation of the HOG Algorithm † +Mariana-Eugenia Ilas 1,* ID and Constantin Ilas 2 +Department of Electronics, Telecommunications and IT, University Politehnica Bucharest, +Bucharest 060042, Romania +Department of Automatics and Computer Science, University Politehnica Bucharest, +Bucharest 060042, Romania; +* Correspondence: Tel.: +40-21-402-4618 +This paper is an extended version of our paper published in the 9th Computer Science & Electronic +Engineering Conference (CEEC), Colchester, UK, 27–29 September 2017. +Received: 5 January 2018; Accepted: 27 February 2018; Published: 1 March 2018"
+09a6261c3334471bb0bc1a173aff672afe963ae3,Key-Pose Prediction in Cyclic Human Motion,"Key-Pose Prediction in Cyclic Human Motion +Multimedia Computing and Computer Vision Lab, University of Augsburg +Dan Zecha +Rainer Lienhart"
+09c019141b209401b76a35184c86bab6cd1fe6b9,3D Deformable Shape Reconstruction with Diffusion Maps,"TAO, MATUSZEWSKI: 3D RECONSTRUCTION WITH DIFFUSION MAPS +D Deformable Shape Reconstruction with +Diffusion Maps +Lili Tao +Bogdan J. Matuszewski +Applied Digital Signal and Image +Processing Research Centre +University of Central Lancashire, UK"
09718bf335b926907ded5cb4c94784fd20e5ccd8,"Recognizing partially occluded, expression variant faces from single training image per person with SOM and soft k-NN ensemble","Recognizing Partially Occluded, Expression Variant Faces From Single Training Image per Person With SOM and Soft k-NN Ensemble Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Member, IEEE, and Fuyan Zhang"
+09251a324dc4865732e2ead50334bfb906f8ffb4,Beyond Text based sentiment analysis: Towards multi-modal systems,"Springer Cognitive Computation manuscript No. +(will be inserted by the editor) +Beyond Text based sentiment analysis: Towards multi-modal +systems +Soujanya Poria · Amir Hussain · Erik Cambria +the date of receipt and acceptance should be inserted later"
+09ac8added26307b358b83884b55af29de8b5bf9,Learning to grasp objects with multiple contact points,"Learning to grasp objects with multiple contact points +Quoc V. Le, David Kamm, Arda F. Kara, Andrew Y. Ng"
+0949f46d5db3169813ae23acafa345c6b8a37f08,When Slower Is Faster: On Heterogeneous Multicores for Reliable Systems,"When Slower is Faster: On Heterogeneous Multicores for Reliable Systems +Tomas Hruby +The Network Institute, VU University Amsterdam +Herbert Bos +Andrew S. Tanenbaum"
+09222c50d8ffcc74bbb7462400bd021772850bba,Incorporating Network Built-in Priors in Weakly-Supervised Semantic Segmentation,"Incorporating Network Built-in Priors in +Weakly-supervised Semantic Segmentation +Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, +Jose M. Alvarez, and Stephen Gould"
+0994916f67fd15687dd5d7e414becb1cd77129ac,Multi Class Different Problem Solving Using Intelligent Algorithm,"SIVAKUMAR R, Dr.M.SRIDHAR / International Journal of Engineering Research and +Applications (IJERA) ISSN: 2248-9622 www.ijera.com +Vol. 2, Issue4, July-August 2012, pp.1782-1785 +Multi Class Different Problem Solving Using Intelligent +Algorithm +SIVAKUMAR R, 2Dr.M.SRIDHAR +Research Scholar Dept of ECE BHARATH UNIVERSITY India +Dept of ECE BHARATH UNIVERSITY India"
0903bb001c263e3c9a40f430116d1e629eaa616f,An Empirical Study of Context in Object Detection,"CVPR 2009 Submission #987. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. An Empirical Study of Context in Object Detection Anonymous CVPR submission Paper ID 987"
+092597b8e0f31be1671025cea1b9fd28a48e04bc,Supervised Person Re-ID based on Deep Hand-crafted and CNN Features,
+091b4ad74ac5bec206604673506b19838d6a0c52,Person Re-Identification By Saliency Learning,"|| Volume 2 ||Issue 10 ||MAY 2017||ISSN (Online) 2456-0774 +INTERNATIONAL JOURNAL OF ADVANCE SCIENTIFIC RESEARCH +AND ENGINEERING TRENDS +Person Re-Identification By Saliency Learning +Shaihenila +P.G. Student, Computer Science & Engineering, Everest Educational Society's Group of Institutions, Aurangabad, India."
+092b64ce89a7ec652da935758f5c6d59499cde6e,Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments,"Human3.6M: +Large Scale Datasets and Predictive Methods +for 3D Human Sensing in Natural Environments +Catalin Ionescu∗†‡, Dragos Papava∗‡, Vlad Olaru∗, Cristian Sminchisescu§∗"
09df62fd17d3d833ea6b5a52a232fc052d4da3f5,Mejora de Contraste y Compensación en Cambios de la Iluminación,"ISSN: 1405-5546 Instituto Politécnico Nacional México @@ -9655,20 +33161,124 @@ Página de la revista en redalyc.org Sistema de Información Científica Red de Revistas Científicas de América Latina, el Caribe, España y Portugal Proyecto académico sin fines de lucro, desarrollado bajo la iniciativa de acceso abierto"
+093b6af0e5f00f9578088a49822d8d500283cab0,Human visual behaviour for collaborative human-machine interaction,"Human Visual Behaviour for +Collaborative Human-Machine +Interaction +Andreas Bulling +Perceptual User Interfaces +Group +Max Planck Institute for +Informatics +Saarbr¨ucken, Germany +Permission to make digital or hard copies of all or part of this work for +personal or classroom use is granted without fee provided that copies are not +made or distributed for profit or commercial advantage and that copies bear +this notice and the full citation on the first page. Copyrights for components"
+09e3967a34cca8dc0f00c9ee7a476a96812a55e0,1 Machine Learning Methods for Social Signal Processing,"Machine Learning Methods for +Social Signal Processing +Ognjen Rudovic, Mihalis A. Nicolaou and Vladimir Pavlovic +Introduction +In this chapter we focus on systematization, analysis, and discussion of recent +trends in machine learning methods for Social signal processing (SSP)(Pentland +007). Because social signaling is often of central importance to subconscious de- +ision making that affects everyday tasks (e.g., decisions about risks and rewards, +resource utilization, or interpersonal relationships) the need for automated un- +derstanding of social signals by computers is a task of paramount importance. +Machine learning has played a prominent role in the advancement of SSP over +the past decade. This is, in part, due to the exponential increase of data avail- +bility that served as a catalyst for the adoption of a new data-driven direction in +ffective computing. With the difficulty of exact modeling of latent and complex +physical processes that underpin social signals, the data has long emerged as the +means to circumvent or supplement expert- or physics-based models, such as the +deformable musculo-sceletal models of the human body, face or hands and its +movement, neuro-dynamical models of cognitive perception, or the models of the +human vocal production. This trend parallels the role and success of machine +learning in related areas, such as computer vision, c.f., (Poppe 2010, Wright"
+094f5e36dae2602e179f2c1d95a616df3dbe967f,Bilinear classifiers for visual recognition,"Bilinear classifiers for visual recognition +Hamed Pirsiavash +Deva Ramanan +Charless Fowlkes +Department of Computer Science +University of California at Irvine"
+0910a4c470a410fac446f4026f7c8ef512ae7427,Hierarchical Question-Image Co-Attention for Visual Question Answering,"Hierarchical Question-Image Co-Attention +for Visual Question Answering +Jiasen Lu∗, Jianwei Yang∗, Dhruv Batra∗† , Devi Parikh∗† +Virginia Tech, † Georgia Institute of Technology +{jiasenlu, jw2yang, dbatra,"
+09d08e543a9b2fc350cb37e47eb087935c12be16,"A Multimodal, Full-Surround Vehicular Testbed for Naturalistic Studies and Benchmarking: Design, Calibration and Deployment","A Multimodal, Full-Surround Vehicular Testbed for Naturalistic Studies +nd Benchmarking: Design, Calibration and Deployment +Akshay Rangesh1, Kevan Yuen1, Ravi Kumar Satzoda1, Rakesh Nattoji Rajaram1, +Pujitha Gunaratne2, and Mohan M. Trivedi1 +Laboratory for Intelligent and Safe Automobiles (LISA), UC San Diego +Toyota Collaborative Safety Research Center (CSRC) +in autonomous"
09f853ce12f7361c4b50c494df7ce3b9fad1d221,Random Forests for Real Time 3D Face Analysis,"myjournal manuscript No. (will be inserted by the editor) Random forests for real time 3D face analysis Gabriele Fanelli · Matthias Dantone · Juergen Gall · Andrea Fossati · Luc Van Gool Received: date / Accepted: date"
+09ba6b87736fa29aae88c5b4cf30f25188e4c6ef,Gaze Estimation in the 3D Space Using RGB-D Sensors,"The final publication is available at Springer via http://dx.doi.org/10.1007/s11263-015-0863-4 +Gaze Estimation in the 3D Space Using RGB-D sensors +Towards Head-Pose And User Invariance +Kenneth A. Funes-Mora · Jean-Marc Odobez +Received: 19 November 2014 / Accepted: 23 September 2015"
+09edf114f8764c82713f8dd35b1b32ad83ecaa17,Large-Margin Learning of Compact Binary Image Encodings,"MANUSCRIPT +Large-margin Learning of Compact Binary Image +Encodings +Sakrapee Paisitkriangkrai, Chunhua Shen, Anton van den Hengel"
+09b0040ad09d61f3403c57c437c03271f8614add,HUMAN ACTIVITY RECOGNITION AND GYMNASTICS ANALYSIS THROUGH DEPTH IMAGERY by,"HUMAN ACTIVITY RECOGNITION AND +GYMNASTICS ANALYSIS THROUGH +DEPTH IMAGERY +Brian J. Reily"
09750c9bbb074bbc4eb66586b20822d1812cdb20,Estimation of the neutral face shape using Gaussian Mixture Models,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE ICASSP 2012"
+09e15bb266da86d0a9525d2a94ac0b38f0b53b88,Detect What You Can: Detecting and Representing Objects Using Holistic Models and Body Parts,"Detect What You Can: Detecting and Representing Objects using Holistic +Models and Body Parts +Xianjie Chen1, Roozbeh Mottaghi2, Xiaobai Liu1, Sanja Fidler3, Raquel Urtasun3, Alan Yuille1 +University of California, Los Angeles 2Stanford University 3University of Toronto"
+0956a3c628959afcf870f5d7ec581160a4aa5221,LIFEisGAME Prototype: A Serious Game about Emotions for Children with Autism Spectrum Disorders,"Volume 11, Number 3, 191 – 211 +LIFEisGAME Prototype: A Serious Game about Emotions +for Children with Autism Spectrum Disorders +Samanta Alves1, António Marques2, Cristina Queirós∗1 and Verónica Orvalho3 +Psychosocial +Rehabilitation +Laboratory, Faculty of +Psychology and +Educational Sciences, +Porto University +(Portugal) +Psychosocial +Rehabilitation +Laboratory, School of +Allied Health Sciences, +Porto Polytechnic +Institute +(Portugal) +Porto +Interactive"
+09749e7b0ae6bd9ab37671fcc4f0e7a7bcf9ff2e,Perceptual enhancement of emotional mocap head motion: An experimental study,"Perceptual Enhancement of Emotional Mocap Head Motion: An Experimental +Study +Yu Ding +Univeristy of Houston +Houston, TX, USA +Lei Shi +Univeristy of Houston +Houston, TX, USA +Zhigang Deng +Univeristy of Houston +Houston, TX, USA"
097f674aa9e91135151c480734dda54af5bc4240,Face Recognition Based on Multiple Region Features,"Proc. VIIth Digital Image Computing: Techniques and Applications, Sun C., Talbot H., Ourselin S. and Adriaansen T. (Eds.), 10-12 Dec. 2003, Sydney Face Recognition Based on Multiple Region Features Jiaming Li, Geoff Poulton, Ying Guo, Rong-Yu Qiao CSIRO Telecommunications & Industrial Physics Australia Tel: 612 9372 4104, Fax: 612 9372 4411, Email:"
+5d0e11844f1a210f16025e990de938f6732672ab,Distance to Center of Mass Encoding for Instance Segmentation,"Distance to Center of Mass Encoding for Instance Segmentation +Thomio Watanabe +University of Sao Paulo +Denis Wolf +University of Sao Paulo"
5da740682f080a70a30dc46b0fc66616884463ec,Real-Time Head Pose Estimation Using Multi-variate RVM on Faces in the Wild,"Real-Time Head Pose Estimation Using Multi-Variate RVM on Faces in the Wild Mohamed Selim, Alain Pagani, Didier Stricker @@ -9677,9 +33287,57 @@ German Research Center for Artificial Intelligence (DFKI), Tripstaddterstr. 122, 67663 Kaiserslautern, Germany Technical University of Kaiserslautern http://www.av.dfki.de"
+5dc003a75a302761778cb1c15d796e3d90dd9322,Bayesian Fisher's Discriminant for Functional Data,"Bayesian Fisher’s Discriminant for Functional Data +Yao-Hsiang Yang ∗, Lu-Hung Chen†, Chieh-Chih Wang‡, and Chu-Song Chen § +December 10, 2014"
+5d1608e03ab9c529d0b05631f9d2a3afcbf1c3e3,Sparsity and Robustness in Face Recognition,"Sparsity and Robustness in Face Recognition +John Wright, Arvind Ganesh, Allen Yang, Zihan Zhou, and Yi Ma +Background. This note concerns the use of techniques for sparse signal representation and sparse +from the paper [WYG+09], which showed how, under certain technical conditions, one could cast +the face recognition problem as one of seeking a sparse representation of a given input face image +in terms of a “dictionary” of training images and images of individual pixels. To be more precise, +the method of [WYG+09] assumes access to a sufficient number of well-aligned training images of +each of the k subjects. These images are stacked as the columns of matrices A1, . . . , Ak. Given a +new test image y, also well aligned, but possibly subject to illumination variation or occlusion, the +method of [WYG+09] seeks to represent y as a sparse linear combination of the database as whole. +Writing A = [A1 | ··· | Ak], this approach solves +(cid:107)x(cid:107)1 + (cid:107)e(cid:107)1 +subj. to Ax + e = y. +minimize +the identity of the test image y the index whose sparse coefficients minimize the residual: +ˆi = arg min +(cid:107)y − Aixi − e(cid:107)2. +This approach demonstrated successful results in laboratory settings (fixed pose, varying illumi- +nation, moderate occlusion) in [WYG+09], and was extended to more realistic settings (involving +moderate pose and misalignemnt) in [WWG+11]. For the sake of clarity, we repeat the above"
+5d80149e005894ab57f47e667f3e060e247d8e43,Lip reading using CNN and LSTM,"Lip reading using CNN and LSTM +Amit Garg +Jonathan Noyola +Sameep Bagadia"
+5df11c59e3b47189486445f5833675bf08359bfe,Influence of Image Classification Accuracy on Saliency Map Estimation,"IET Research Journals +Brief Paper +Influence of Image Classification Accuracy +on Saliency Map Estimation +Taiki Oyama1 Takao Yamanaka1 +Department of Information & Communication Sciences, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-0094, Japan +* E-mail: +ISSN 1751-8644 +doi: 0000000000 +www.ietdl.org"
5da139fc43216c86d779938d1c219b950dd82a4c,A Generalized Multiple Instance Learning Algorithm for Iterative Distillation and Cross-Granular Propagation of Video Annotations,"-4244-1437-7/07/$20.00 ©2007 IEEE II - 205 ICIP 2007"
+5d04bd7104f08f7fb91967613ffc519c27641e99,Bound to Lose: Physical Incapacitation Increases the Conceptualized Size of an Antagonist in Men,"Bound to Lose: Physical Incapacitation Increases the +Conceptualized Size of an Antagonist in Men +Daniel M. T. Fessler*, Colin Holbrook +Department of Anthropology and Center for Behavior, Evolution, and Culture, University of California Los Angeles, Los Angeles, California, United States of America"
+5d14cc415a93e6f3a625ed7794e1fdcf99ea5713,Predicting Face Recognition Performance Using Image Quality,"Predicting Face Recognition Performance Using +Image Quality +Abhishek Dutta, Raymond Veldhuis, Senior Member, IEEE and Luuk Spreeuwers,"
+5da53a17165fcc64e8fb6e9ca532bfb6d95ff622,RSCM: Region Selection and Concurrency Model for Multi-Class Weather Recognition,"RSCM: Region Selection and Concurrency Model +for Multi-Class Weather Recognition +Di Lin, Cewu Lu, Member, IEEE, Hui Huang, Member, IEEE, and Jiaya Jia, Senior Member, IEEE +ondition"
5d185d82832acd430981ffed3de055db34e3c653,A Fuzzy Reasoning Model for Recognition of Facial Expressions,"A Fuzzy Reasoning Model for Recognition of Facial Expressions Oleg Starostenko1, Renan Contreras1, Vicente Alarcón Aquino1, Leticia Flores Pulido1, @@ -9690,12 +33348,35 @@ Universidad de las Américas, 72820, Puebla, Mexico Engineering Institute, Autonomous University of Baja California, Blvd. Benito Juárez, Insurgentes Este, 21280, Mexicali, Baja California, Mexico Universidad Politécnica de Baja California, Mexicali, Baja California, Mexico"
+5d90f06bb70a0a3dced62413346235c02b1aa086,Learning Multiple Layers of Features from Tiny Images,"Learning Multiple Layers of Features from Tiny Images +Alex Krizhevsky +April 8, 2009"
5d233e6f23b1c306cf62af49ce66faac2078f967,Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions,"RESEARCH ARTICLE Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions Vasanthan Maruthapillai, Murugappan Murugappan* School of Mechatronic Engineering, Universiti Malaysia Perlis, 02600, Ulu Pauh, Arau, Perlis, West Malaysia"
+5da0224590d91defe8c75db0ab5e12d50b6ab6f3,NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation Systems,"NMTPY: A FLEXIBLE TOOLKIT FOR ADVANCED +NEURAL MACHINE TRANSLATION SYSTEMS +Ozan Caglayan, Mercedes García-Martínez, Adrien Bardet, Walid Aransa, +Fethi Bougares, Loïc Barrault +Laboratoire d’Informatique de l’Université du Maine (LIUM) +Language and Speech Technology (LST) Team +Le Mans, France"
+5da43ff9c246ae37d9006bba3406009cb4fb1dcf,Lifelong Machine Learning Lifelong Machine Learning,"Lifelong Machine Learning +November, 2016 +Zhiyuan Chen and Bing Liu +Draft : This is an early draft of the book. +Zhiyuan Chen and Bing Liu. Lifelong Machine Learning. +Morgan & Claypool Publishers, Nov 2016. +LifelongMachineLearningZhiyuan ChenBing Liu"
+5dcfb84ab3f5d5f1dd02f59e45154c9710de97b2,On the Latent Variable Interpretation in Sum-Product Networks,"On the Latent Variable Interpretation in +Sum-Product Networks +Robert Peharz, Robert Gens, Franz Pernkopf, Senior Member, IEEE, and Pedro Domingos"
+5db46dda9f0f08220d49a5db1204f149bd4f6a4a,Engaging Image Captioning Via Personality,"ENGAGING IMAGE CAPTIONING VIA PERSONALITY +Kurt Shuster, Samuel Humeau, Hexiang Hu, Antoine Bordes, Jason Weston +Facebook AI Research"
5db075a308350c083c3fa6722af4c9765c4b8fef,The Novel Method of Moving Target Tracking Eyes Location based on SIFT Feature Matching and Gabor Wavelet Algorithm,"The Novel Method of Moving Target Tracking Eyes Location based on SIFT Feature Matching and Gabor Wavelet Algorithm @@ -9709,6 +33390,12 @@ SSSeeennnsssooorrrsss &&& TTTrrraaannnsssddduuuccceeerrrsss © 2013 by IFSA http://www.sensorsportal.com Received: 28 April 2013 /Accepted: 19 July 2013 /Published: 31 July 2013"
+5d7de2eb2ee99798bfb2e50ed5169e3b8a35469a,Design of a Three-dimensional Face Recognition System,"The Open Automation and Control Systems Journal, 2015, 7, 587-590 +Design of a Three-Dimensional Face Recognition System +Send Orders for Reprints to +Open Access +Wang Xuechun* and Wang Zhaoping +School of Information Engineering, Huanghe Science and Technology College, Zhengzhou, Henan, 450006, P.R. China"
5d7f8eb73b6a84eb1d27d1138965eb7aef7ba5cf,Robust Registration of Dynamic Facial Sequences,"Robust Registration of Dynamic Facial Sequences Evangelos Sariyanidi, Hatice Gunes, and Andrea Cavallaro"
5db4fe0ce9e9227042144758cf6c4c2de2042435,Recognition of Facial Expression Using Haar Wavelet Transform,"INTERNATIONAL JOURNAL OF ELECTRICAL AND ELECTRONIC SYSTEMS RESEARCH, VOL.3, JUNE 2010 @@ -9718,6 +33405,21 @@ M. Satiyan, M.Hariharan, R.Nagarajan paper features investigates"
+5d165ff5b0b389e32809c17838a2afc218a91d62,Object Detectors Emerge in Deep Scene CNNs,"Published as a conference paper at ICLR 2015 +OBJECT DETECTORS EMERGE IN DEEP SCENE CNNS +Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba +Computer Science and Artificial Intelligence Laboratory, MIT"
+5d7f9e1463b596eb5d77865a8b1a0e149215303b,A Hidden Markov Model-based Approach for Face Detection and Recognition a Hidden Markov Model-based Approach for Face Detection and Recognition,"AHiddenMarkovModel-BasedApproach +forFaceDetectionandRecognition +ATHESIS +Presentedto +TheAcademicFaculty +AraNe(cid:12)an +InPartialFul(cid:12)llment +oftheRequirementsfortheDegreeof +DoctorofPhilosophyinElectricalEngineering +GeorgiaInstituteofTechnology +August,"
5d5cd6fa5c41eb9d3d2bab3359b3e5eb60ae194e,Face Recognition Algorithms,"Face Recognition Algorithms Proyecto Fin de Carrera June 16, 2010 @@ -9744,6 +33446,11 @@ Accepted 16 November 2014 Available online 23 October 2014 Keywords: Object recognition"
+5d7395085f2636dd2b6262bc7f3fef14058f4765,Regularizing Deep Networks by Modeling and Predicting Label Structure,"Regularizing Deep Networks by Modeling and Predicting Label Structure +Mohammadreza Mostajabi +Michael Maire +Gregory Shakhnarovich +Toyota Technological Institute at Chicago"
5d197c8cd34473eb6cde6b65ced1be82a3a1ed14,A Face Image Database for Evaluating Out-of-Focus Blur,"0AFaceImageDatabaseforEvaluatingOut-of-FocusBlurQiHan,QiongLiandXiamuNiuHarbinInstituteofTechnologyChina1.IntroductionFacerecognitionisoneofthemostpopularresearchfieldsofcomputervisionandmachinelearning(Tores(2004);Zhaoetal.(2003)).Alongwithinvestigationoffacerecognitionalgorithmsandsystems,manyfaceimagedatabaseshavebeencollected(Gross(2005)).Facedatabasesareimportantfortheadvancementoftheresearchfield.Becauseofthenonrigidityandcomplex3Dstructureofface,manyfactorsinfluencetheperformanceoffacedetectionandrecognitionalgorithmssuchaspose,expression,age,brightness,contrast,noise,blurandetc.Someearlyfacedatabasesgatheredunderstrictlycontrolledenvironment(Belhumeuretal.(1997);Samaria&Harter(1994);Turk&Pentland(1991))onlyallowslightexpressionvariation.Toinvestigatetherelationshipsbetweenalgorithms’performanceandtheabovefactors,morefacedatabaseswithlargerscaleandvariouscharacterswerebuiltinthepastyears(Bailly-Bailliereetal.(2003);Flynnetal.(2003);Gaoetal.(2008);Georghiadesetal.(2001);Hallinan(1995);Phillipsetal.(2000);Simetal.(2003)).Forinstance,The""CAS-PEAL"",""FERET"",""CMUPIE"",and""YaleB""databasesincludevariousposes(Gaoetal.(2008);Georghiadesetal.(2001);Phillipsetal.(2000);Simetal.(2003));The""HarvardRL"",""CMUPIE""and""YaleB""databasesinvolvemorethan40differentconditionsinillumination(Georghiadesetal.(2001);Hallinan(1995);Simetal.(2003));Andthe""BANCA"",and""NDHID""databasescontainover10timesgathering(Bailly-Bailliereetal.(2003);Flynnetal.(2003)).Thesedatabaseshelpresearcherstoevaluateandimprovetheiralgorithmsaboutfacedetection,recognition,andotherpurposes.Blurisnotthemostimportantbutstillanotablefactoraffectingtheperformanceofabiometricsystem(Fronthaleretal.(2006);Zamanietal.(2007)).Themainreasonsleadingblurconsistinout-of-focusofcameraandmotionofobject,andtheout-of-focusblurismoresignificantintheapplicationenvironmentoffacerecognition(Eskicioglu&Fisher(1995);Kimetal.(1998);Tanakaetal.(2007);Yitzhaky&Kopeika(1996)).Toinvestigatetheinfluenceofbluronafacerecognitionsystem,afaceimagedatabasewithdifferentconditionsofclarityandefficientblurevaluatingalgorithmsareneeded.Thischapterintroducesanewfacedatabasebuiltforthepurposeofblurevaluation.Theapplicationenvironmentsoffacerecognitionareanalyzedfirstly,thenaimagegatheringschemeisdesigned.Twotypicalgatheringfacilitiesareusedandthefocusstatusaredividedinto11steps.Further,theblurassessmentalgorithmsaresummarizedandthecomparisonbetweenthemisraisedonthevarious-claritydatabase.The7www.intechopen.com"
5da2ae30e5ee22d00f87ebba8cd44a6d55c6855e,"When facial expressions do and do not signal minds: The role of face inversion, expression dynamism, and emotion type.","This is an Open Access document downloaded from ORCA, Cardiff University's institutional repository: http://orca.cf.ac.uk/111659/ @@ -9764,18 +33471,98 @@ Hirokatsu Kataoka, Yun He, Soma Shirakabe, Yutaka Satoh National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba, Ibaraki, Japan {hirokatsu.kataoka, yun.he, shirakabe-s,"
+3107486fe666a3004b720125bd2b05ff9382fdb8,Generalized two-dimensional linear discriminant analysis with regularization,"JOURNAL OF LATEX CLASS FILES, VOL. +, NO. +Generalized two-dimensional linear discriminant +nalysis with regularization +Chun-Na Li, Yuan-Hai Shao,Wei-Jie Chen, Zhen Wang and Nai-Yang Deng"
318e7e6daa0a799c83a9fdf7dd6bc0b3e89ab24a,Sparsity in Dynamics of Spontaneous Subtle Emotions: Analysis and Application,"Sparsity in Dynamics of Spontaneous Subtle Emotions: Analysis & Application Anh Cat Le Ngo, Member, IEEE, John See, Member, IEEE, Raphael C.-W. Phan, Member, IEEE"
+3137eede6bbada4442e0193dc5918788b7e88aa1,Hyper-class augmented and regularized deep learning for fine-grained image classification,"Hyper-class Augmented and Regularized Deep Learning for Fine-grained Image Classification +Saining Xie1, Tianbao Yang2 Xiaoyu Wang3, Yuanqing Lin4 +University of California, San Diego. 2University of Iowa. 3Snapchat Research. 4NEC Labs America, Inc. +Fine-grained image classification (FGIC) is challenging because (i) fine- +grained labeled data is much more expensive to acquire (usually requir- +ing domain expertise); (ii) there exists large intra-class and small inter- +lass variance. In this paper, we propose a systematic framework of learn- +ing a deep CNN that addresses the challenges from two new perspectives: +(i) identifying easily annotated hyper-classes inherent in the fine-grained +data and acquiring a large number of hyper-class-labeled images from read- +ily available external sources, and formulating the problem into multi-task +learning, to address the data scarcity issue. We use two common types of +hyper-classes to augment our data, with one being the super-type hyper- +lasses that subsume a set of fine-grained classes, and another being named +factor-type hyper-classes (e.g., different view-points of a car) that explain +the large intra-class variance. (ii) a novel learning model by exploiting a reg- +ularization between the fine-grained recognition model and the hyper-class +recognition model to mitigate the issue of large intra-class variance and im- +prove the generalization performance. The proposed approach also closely +relates to attribute-based learning, since one can consider that factor-type"
31c0968fb5f587918f1c49bf7fa51453b3e89cf7,Deep Transfer Learning for Person Re-identification,"Deep Transfer Learning for Person Re-identification Mengyue Geng Yaowei Wang Tao Xiang Yonghong Tian"
+318d7a4bc9c7b1e3a01056815479564ed8ad78a4,University of Oklahoma Graduate College Reinforcement Learning Scheduler for Heterogeneous Multi-core Processors Reinforcement Learning Scheduler for Heterogeneous Multi-core Processors a Thesis Approved for the School of Computer Science,"UNIVERSITY OF OKLAHOMA +GRADUATE COLLEGE +REINFORCEMENT LEARNING SCHEDULER FOR HETEROGENEOUS +MULTI-CORE PROCESSORS +A THESIS +SUBMITTED TO THE GRADUATE FACULTY +in partial fulfillment of the requirements for the +Degree of +MASTER OF SCIENCE +XIAOLEI YAN +Norman, Oklahoma"
+318eb316c0117059dd47978854cfa92baeaac1d2,Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study,"Deterministic CUR for Improved Large-Scale Data Analysis: +An Empirical Study +Christian Thurau, Kristian Kersting, and Christian Bauckhage +Fraunhofer IAIS, Germany"
+3174fceef3cf09ac35e8d1eb4e1b8b73a3b2c713,Unsupervised learning from videos using temporal coherency deep networks,"Computer Vision and Image Understanding +journal homepage: www.elsevier.com +Unsupervised learning from videos using temporal coherency deep networks +Carolina Redondo-Cabreraa,∗∗, Roberto Lopez-Sastrea +GRAM, University of Alcal´a, Alcal´a de Henares, 28805, Spain"
+31f1c4cf34ce0bb35382c35b2f468cf72bffae0b,Are spatial and global constraints really necessary for segmentation?,"Are Spatial and Global Constraints Really Necessary for Segmentation? +Aur´elien Lucchi1 +Yunpeng Li1 +Computer Vision Laboratory, EPFL, Lausanne +Xavier Boix2 +Kevin Smith1 +Pascal Fua1 +BIWI, ETH Zurich"
+3123e97a6b86913d994e44f8d9d5c639e0e2dc96,A Method of Initialization for Nonnegative Matrix Factorization,"A METHOD OF INITIALIZATION FOR NONNEGATIVE MATRIX FACTORIZATION +Yong-Deok Kim and Seungjin Choi +Department of Computer Science, POSTECH, Korea +{karma13,"
+31ea778b6f5c9c2653eb2bed307ac7b02bcc6894,Dense Error Correction via `-Minimization,"IEEE TRANS. ON INFORMATION THEORY, 2009. +Dense Error Correction via (cid:96)1-Minimization +John Wright, Member, and Yi Ma, Senior Member."
316e67550fbf0ba54f103b5924e6537712f06bee,Multimodal semi-supervised learning for image classification,"Multimodal semi-supervised learning for image classification Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmid LEAR team, INRIA Grenoble, France"
+31786e6d5187d7bc41678cbd2d1bf8edf1ddfed9,Capture de mouvements humains par capteurs RGB-D. (Capture human motions by RGB-D sensor ),"Capture de mouvements humains par capteurs RGB-D +Jean-Thomas Masse +To cite this version: +Jean-Thomas Masse. Capture de mouvements humains par capteurs RGB-D. Robotique +[cs.RO]. Universit´e Paul Sabatier - Toulouse III, 2015. Fran¸cais. +¡ NNT : 2015TOU30361 +HAL Id: tel-01280163 +https://tel.archives-ouvertes.fr/tel-01280163v2 +Submitted on 26 Apr 2017 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de +recherche fran¸cais ou ´etrangers, des laboratoires"
31ef5419e026ef57ff20de537d82fe3cfa9ee741,Facial Expression Analysis Based on High Dimensional Binary Features,"Facial Expression Analysis Based on High Dimensional Binary Features Samira Ebrahimi Kahou, Pierre Froumenty, and Christopher Pal @@ -9785,6 +33572,14 @@ Samira Ebrahimi Kahou, Pierre Froumenty, and Christopher Pal Sina Honari1, Jason Yosinski2, Pascal Vincent1,4, Christopher Pal3 University of Montreal, 2Cornell University, 3Ecole Polytechnique of Montreal, 4CIFAR {honaris,"
+310a88a60ffa2d8a0fa7ef9fc77fa842d16eed57,View Invariant Gait Recognition,"View Invariant Gait Recognition +Richard D. Seely, Michela Goffredo, John N. Carter and Mark S. Nixon"
+3151b110ecdcf2105def494bfb0775f21259d7e8,Asymmetric Cuts: Joint Image Labeling and Partitioning,"Asymmetric Cuts : Joint Image Labeling and +Partitioning +Thorben Kroeger1, J¨org H. Kappes2, Thorsten Beier1, Ullrich Koethe1 and +Fred A. Hamprecht1,2 +Multidimensional Image Processing Group, Heidelberg University +Heidelberg Collaboratory for Image Processing, Heidelberg University"
31ace8c9d0e4550a233b904a0e2aabefcc90b0e3,Learning Deep Face Representation,"Learning Deep Face Representation Haoqiang Fan Megvii Inc. @@ -9796,6 +33591,19 @@ Qi Yin Megvii Inc. Chinchilla Doudou Megvii Inc."
+312b807a24b8c30876c1750530b08e4d9627e231,Increasing Trustworthiness of Face Authentication in Mobile Devices by Modeling Gesture Behavior and Location Using Neural Networks,"Article +Increasing Trustworthiness of Face Authentication in +Mobile Devices by Modeling Gesture Behavior and +Location Using Neural Networks +Blerim Rexha 1 ID , Gresa Shala 2,* and Valon Xhafa 3 +Faculty of Electrical and Computer Engineering, University of Prishtina, Kodra e Diellit p.n., +0000 Prishtina, Kosovo; +Department of Computer Science, Freiburg University, Georges-Köhler Alley 101, +79110 Freiburg im Breisgau, Germany +Department of Informatics, Technical University of Munich, Boltzmannstraße 3, +85748 Garching bei München, Germany; +* Correspondence: +Received: 18 January 2018; Accepted: 2 February 2018; Published: 5 February 2018"
31afdb6fa95ded37e5871587df38976fdb8c0d67,Quantized fuzzy LBP for face recognition,"QUANTIZED FUZZY LBP FOR FACE RECOGNITION Jianfeng Xudong Jiang, @@ -9816,9 +33624,153 @@ School of Electrical Engineering Nanyang 50 Nanyang"
+318c4c25d86511690cc5df7b041a6392e8cc4ea8,Fashion-Gen: The Generative Fashion Dataset and Challenge,"Fashion-Gen: The Generative Fashion Dataset and Challenge +Negar Rostamzadeh 1 Seyedarian Hosseini 1 2 Thomas Boquet 1 Wojciech Stokowiec 1 Ying Zhang 1 +Christian Jauvin 1 Chris Pal 3 1"
+316bed02e22aa6742dffcd50c29a7365c5a5a437,Representation Learning for Visual-Relational Knowledge Graphs,"Representation Learning for Visual-Relational +Knowledge Graphs +Daniel Oñoro-Rubio, Mathias Niepert, Alberto García-Durán, Roberto +González-Sánchez and Roberto J. López-Sastre* +NEC Labs Europe, Alcalá de Henares* +{daniel.onoro, mathias.niepert, alberto.duran, +https://github.com/nle-ml/mmkb.git"
+317f5a56519df95884cce81cfba180ee3adaf5a5,Operator-In-The-Loop Deep Sequential Multi-camera Feature Fusion for Person Re-identification,"FusionCam C1Cam C2Classical re-id schemeProposed re-idschemeQueryQueryRanked List: Cam 𝐶1Ranked List: Cam 𝐶2Ranked List: Cam 𝐶1OperatorFeedbackRanked List: Cam 𝐶2Fig.1:(Top)Classicalre-idschemewherequeryimage’sfeaturerepresentationisusedtosearcheachcamerainthenetworkinde-pendently.Theretrievedlistsarereturnedtothehumanoperator.(Bottom)Ourproposedsequentialre-idschemewhereoperatorfeedbackregardingtargetsightingisutilizedtowardsbetterre-idperformanceinanonlinefashion.Inthefigure,cameraC1isqueriedfirstandrankedlistofmatchesisobtained.Thecorrectmatch(pinkbox)inretrievedrankedlistisidentifiedbyoperator.Thecorrectmatchisfusedwithqueryimageatfeaturelevel(orangeblock).ThisfusedrepresentationisusedtoquerycameraC2.NoticethatrankingofquerytargetinC2’slistimprovesinourapproachunliketheclassicalversionwhichcannotexploitoperatorinputstoimprovesubsequentqueries.arXiv:1807.07295v3 [cs.CV] 6 Nov 2018"
+3130eb9bfab5e5a095ab989ba3cc6a2ec62c156d,Generating Facial Ground Truth with Synthetic Faces,"Generating Facial Ground Truth with Synthetic Faces +Rossana Queiroz, Marcelo Cohen, Juliano L. Moreira, Adriana Braun, J´ulio C. Jacques J´unior, Soraia Raupp Musse +Pontif´ıcia Universidade Cat´olica do Rio Grande do Sul - PUCRS +Graduate Programme in Computer Science +Virtual Human Laboratory -www.inf.pucrs.br/∼vhlab +Porto Alegre, Brazil +Figure 1. A sample of 3D faces generated by our prototype."
+31b9251dedce1e10467a0a33f56ac4eb05ed0451,Viewpoint-dependent 3D human body posing for sports legacy recovery from images and video,"VIEWPOINT-DEPENDENT 3D HUMAN BODY POSING FOR SPORTS LEGACY +RECOVERY FROM IMAGES AND VIDEO +Luis Unzueta, Jon Goenetxea, Mikel Rodriguez and Maria Teresa Linaza +Vicomtech-IK4, Paseo Mikeletegi, 57, Parque Tecnológico, 20009, Donostia, Spain"
+31ca0d6488a27a140263291c51ec924b8a49967b,"Show, Ask, Attend, and Answer: A Strong Baseline For Visual Question Answering","Show, Ask, Attend, and Answer: +A Strong Baseline For Visual Question Answering +Vahid Kazemi +Ali Elqursh +Google Research +600 Amphitheater Parkway +{vahid,"
+31ea3186aa7072a9e25218efe229f5ee3cca3316,A ug 2 01 7 Reinforced Video Captioning with Entailment Rewards,"Reinforced Video Captioning with Entailment Rewards +Ramakanth Pasunuru and Mohit Bansal +UNC Chapel Hill +{ram,"
+318f7b59fc22d6326f77b24939860b0137bf8e77,Multiple Classifier Boosting and Tree-Structured Classifiers,"Multiple Classifier Boosting and +Tree-Structured Classifiers +Tae-Kyun Kim and Roberto Cipolla"
+31470cf8fda53c4460de4373e5ac4544236c44af,Biased information processing as an endophenotype for depression,"PDF hosted at the Radboud Repository of the Radboud University +Nijmegen +The following full text is a publisher's version. +For additional information about this publication click this link. +http://repository.ubn.ru.nl/handle/2066/127113 +Please be advised that this information was generated on 2017-04-19 and may be subject to +hange."
+318ee553c61888f2418280cb1d342c698d3444c9,Towards face unlock: on the difficulty of reliably detecting faces on mobile phones,"Towards Face Unlock: On the Difficulty of Reliably +Detecting Faces on Mobile Phones +Rainhard D. Findling +Softwarepark 11 +Hagenberg, Austria +Rene Mayrhofer +Softwarepark 11 +Hagenberg, Austria +Department for Mobile Computing +Upper Austria University of Applied Sciences +Department for Mobile Computing +Upper Austria University of Applied Sciences"
+318985dc2b8d5a1882b709eedeaac4a2e7de1d81,Accelerating Message Passing for MAP with Benders Decomposition,"Accelerating Message Passing for MAP with +Benders Decomposition +Julian Yarkony +Experian Data Lab. +Shaofei Wang +Baidu Inc. +May 15, 2018"
+31fc3b044ec908f7f61386422727ef23784178c0,Enhancing Face Recognition using Average per Region,"International Journal of Computer Applications (0975 – 8887) +Volume 65– No.3, March 2013 +Enhancing Face Recognition using Average per Region +Basheer M. Nasef +Teaching Assistant +Dept of Computer and Systems Engineering, +Zagazig University, Sharkia, Egypt +Ibrahim E. Ziedan +Dept of Computer and Systems Engineering, +Professor +Zagazig University, Sharkia, Egypt"
+31c174f2190889d5792358713e078336926d7ee4,Image Categorization Using Codebooks Built from Scored and Selected Local Features,"Image Categorization using Codebooks Built from +Scored and Selected Local Features +Department of Computer Science, Northern Illinois University DeKalb IL USA 60115 +Bala S. Divakaruni and Jie Zhou +follows +(M&C) process"
+31d30089d00d89715167ca4a130a5d262e1d79d3,"Fawzi, Frossard: Measuring the Effect of Nuisance Variables","FAWZI, FROSSARD: MEASURING THE EFFECT OF NUISANCE VARIABLES +Measuring the effect of nuisance variables +on classifiers +Alhussein Fawzi +Pascal Frossard +Signal Processing Laboratory (LTS4) +Ecole Polytechnique Fédérale de +Lausanne (EPFL) +Lausanne, Switzerland"
+3137870bf1314e25c2246d4a9d77d941aadd5398,Influence of Positive Instances on Multiple Instance Support Vector Machines,"Influence of Positive Instances on +Multiple Instance Support Vector Machines +Nuno Barroso Monteiro1,2, Jo˜ao Pedro Barreto2, and Jos´e Gaspar1 +Institute for Systems and Robotics (ISR/IST), LARSyS, Univ. of Lisbon, Portugal +Institute for Systems and Robotics, Univ. of Coimbra, Portugal"
+9175b123837ecf55a9aae6c40ba245ddacbc37d5,Various Fusion Schemes to Recognize Simulated and Spontaneous Emotions,"Various Fusion Schemes to Recognize Simulated and Spontaneous +Emotions +Sonia Gharsalli1, H´el`ene Laurent2, Bruno Emile1 and Xavier Desquesnes1 +Univ. Orl´eans, INSA CVL, +PRISME EA 4229, Bourges, France +on secondment from INSA CVL, Univ. Orl´eans, +PRISME EA 4229, Bourges, France +to the Rector of the Academy of Strasbourg, Strasbourg, France +Keywords: +Facial Emotion Recognition, Posed Expression, Spontaneous Expression, Early Fusion, Late Fusion, SVM, +FEEDTUM Database, CK+ Database."
91811203c2511e919b047ebc86edad87d985a4fa,Expression Subspace Projection for Face Recognition from Single Sample per Person,"Expression Subspace Projection for Face Recognition from Single Sample per Person Hoda Mohammadzade, Student Member, IEEE, and Dimitrios Hatzinakos, Senior Member, IEEE"
+912f1f57a010194047b6438cc1ea6bec95c6c2b8,ContextVP: Fully Context-Aware Video Prediction,"ContextVP: Fully Context-Aware Video +Prediction +Wonmin Byeon1,2,3,4, Qin Wang2, +Rupesh Kumar Srivastava4, and Petros Koumoutsakos2 +NVIDIA, Santa Clara, CA, USA +ETH Zurich, Zurich, Switzerland +The Swiss AI Lab IDSIA, Manno, Switzerland +NNAISENSE, Lugano, Switzerland"
+91f67f69597a52b905c748a15db427c61f352073,Scale-Aware Pixelwise Object Proposal Networks,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Scale-aware Pixel-wise Object Proposal Networks +Zequn Jie, Xiaodan Liang, Jiashi Feng, Wen Feng Lu, Eng Hock Francis Tay, Shuicheng Yan +essential +proposal"
+91edca64a666c46b0cbca18c3e4938e557eeb21a,Guiding InfoGAN with Semi-supervision,"Guiding InfoGAN with Semi-Supervision +Adrian Spurr, Emre Aksan, and Otmar Hilliges +Advanced Interactive Technologies, ETH Zurich +{adrian.spurr, emre.aksan,"
+912f6a6ac8703e095d21e2049da4871cc6d4d23b,Partitioning Networks with Node Attributes by Compressing Information Flow,"Partitioning Networks with Node Attributes by +Compressing Information Flow +Laura M. Smith +Department of Mathematics +California State University +Fullerton, CA +Kristina Lerman +Information Sciences Institute +U. of Southern California +Marina del Rey, CA 90292 +Linhong Zhu +Information Sciences Institute +U. of Southern California +Marina del Rey, CA 90292 +Allon G. Percus +Claremont Graduate U. +Claremont, CA 91711"
+91dda4183c6118de8195e07a623962dbd22cc34e,Representing local binary descriptors with BossaNova for visual recognition,"Representing Local Binary Descriptors with +BossaNova for Visual Recognition +Carlos Caetano†, Sandra Avila†, Silvio Guimarães‡, Arnaldo de A. Araújo† +Federal University of Minas Gerais, NPDI Lab — DCC/UFMG, Minas Gerais, Brazil +Pontifical Catholic University of Minas Gerais, VIPLAB — ICEI/PUC Minas, Minas Gerais, Brazil +{carlos.caetano,"
9117fd5695582961a456bd72b157d4386ca6a174,Recognition Using Dee Networks,"Facial Expression n Recognition Using Dee ep Neural @@ -9846,12 +33798,23 @@ Karunakara K Professor & Head of Dept. Department of Information Science & Engineering Sri SidarthaInstitute of Technology, Tumkur"
+91b0081a348d182d616f74a0c9fb80d56acf4198,Exploiting photographic style for category-level image classification by generalizing the spatial pyramid,"Exploiting Photographic Style for Category-Level Image +Classification by Generalizing the Spatial Pyramid +Jan C. van Gemert +Puzzual +Oudeschans 18 +011LA, Amsterdam, The Netherlands"
+91a7816609f991c1ac45b791c1cd3c6117194bb0,I Know How You Feel: Emotion Recognition with Facial Landmarks,"I Know How You Feel: Emotion Recognition with Facial Landmarks +Tooploox 2Polish-Japanese Academy of Information Technology 3Warsaw University of Technology +Ivona Tautkute1,2, Tomasz Trzcinski1,3 and Adam Bielski1"
919d3067bce76009ce07b070a13728f549ebba49,Time Based Re-ranking for Web Image Search,"International Journal of Scientific and Research Publications, Volume 4, Issue 6, June 2014 ISSN 2250-3153 Time Based Re-ranking for Web Image Search Ms. A.Udhayabharadhi *, Mr. R.Ramachandran ** * MCA Student, Sri Manakula Vinayagar Engineering College, Pondicherry-605106 ** Assistant Professor dept of MCA, Sri Manakula Vinayagar Engineering College, Pondicherry-605106"
+91f820e2cb6fb5a8adc83e6065cbdf071aca84bd,What makes Federer look so elegant?,"What makes Federer look so elegant? +Kuldeep Kulkarni and Vinay Venkataraman"
91e57667b6fad7a996b24367119f4b22b6892eca,Probabilistic Corner Detection for Facial Feature,"Probabilistic Corner Detection for Facial Feature Extraction Article @@ -9863,6 +33826,13 @@ from the work. Publisher: Springer http://link.springer.com/content/pdf/10.1007%2F978-3- 642-04146-4_50.pdf"
+917611cfc0fee3e834d1a6cc13ad5bc18ae428f3,Geometric models with co-occurrence groups,"Geometric Models with Co-occurrence Groups +Joan Bruna1 +and St´ephane Mallat2 +8/16 rue Paul Vaillant Couturier, 92240, Malakoff - France +- Zoran France +- Ecole Polytechnique - CMAP +Route de Saclay, 91128 Palaiseau - France"
917bea27af1846b649e2bced624e8df1d9b79d6f,Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for Mobile and Embedded Applications,"Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for Mobile and Embedded Applications Baohua Sun, @@ -9889,11 +33859,92 @@ Javier Romero∗,2 Michael J. Black1"
91ead35d1d2ff2ea7cf35d15b14996471404f68d,Combining and Steganography of 3D Face Textures,"Combining and Steganography of 3D Face Textures Mohsen Moradi and Mohammad-Reza Rafsanjani-Sadeghi"
+91c014ff243ea747ea3a84a9efd4a3e38a7217ee,Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-identification,"Reinforced Temporal Attention and Split-Rate +Transfer for Depth-Based Person +Re-Identification +Nikolaos Karianakis1, Zicheng Liu1, Yinpeng Chen1, and Stefano Soatto2 +Microsoft, Redmond, USA +University of California, Los Angeles, USA"
+919e827c449ca77bcff4ce5f2ccbccdab8399ac6,Generative Entity Networks: Disentangling Enti-,"Under review as a conference paper at ICLR 2018 +GENERATIVE ENTITY NETWORKS: DISENTANGLING ENTI- +TIES AND ATTRIBUTES IN VISUAL SCENES USING PARTIAL +NATURAL LANGUAGE DESCRIPTIONS +Anonymous authors +Paper under double-blind review"
+914fd65d29094e434346806bdddeb17d9468610d,Scene Text Recognition in Mobile Applications by Character Descriptor and Structure Configuration,"IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 +SCENE TEXT RECOGNITION IN MOBILE APPLICATIONS BY +CHARACTER DESCRIPTOR AND STRUCTURE CONFIGURATION +Sathish Kumar Penchala1, Pallavi S.Umap2 +Assistant Professor, Dept. of Computer Engineering, Dr. D.Y.Patil SOET., Lohegaon, Pune-47, Maharashtra, India +ME 2nd year, Dept. of Computer Engineering, Dr.D.Y.Patil SOET., Lohegaon, Pune-47, Maharashtra India"
91d513af1f667f64c9afc55ea1f45b0be7ba08d4,Automatic Face Image Quality Prediction,"Automatic Face Image Quality Prediction Lacey Best-Rowden, Student Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
91e58c39608c6eb97b314b0c581ddaf7daac075e,Pixel-wise Ear Detection with Convolutional Encoder-Decoder Networks,"Pixel-wise Ear Detection with Convolutional Encoder-Decoder Networks ˇZiga Emerˇsiˇc 1, Luka Lan Gabriel 2, Vitomir ˇStruc 3 and Peter Peer 1"
+910da5e0afef96c8acca3c6a4314a9ab5121b1e4,Détection d'obstacles multi-capteurs supervisée par stéréovision. (Multi-sensor road obstacle deetection controled by stereovision),"Détection d’obstacles multi-capteurs supervisée par +stéréovision +Mathias Perrollaz +To cite this version: +Mathias Perrollaz. Détection d’obstacles multi-capteurs supervisée par stéréovision. Vision par ordi- +nateur et reconnaissance de formes [cs.CV]. Université Pierre et Marie Curie - Paris VI, 2008. Français. +<tel-00656864> +HAL Id: tel-00656864 +https://tel.archives-ouvertes.fr/tel-00656864 +Submitted on 5 Jan 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+91ee88754cc7a193d51656a3b53e16389bf4aadb,Fast and accurate algorithm for eye localisation for gaze tracking in low-resolution images,"Fast and Accurate Algorithm for Eye Localization +for Gaze Tracking in Low Resolution Images +Anjith George, Member, IEEE, and Aurobinda Routray, Member, IEEE"
+91bdc706ad1d7b246e457870a7eb8caff87ec05a,Face Recognition Using Holistic Based Approach,"International Journal of Emerging Technology and Advanced Engineering +Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 7, July 2014) +Face Recognition Using Holistic Based Approach +1Research Scholar, 2Professor, Department of Information Science and Engineering, SDM CET, Dharwad +Vandana S. Bhat1, Dr. Jagadeesh D. Pujari2"
+9168b36568b8abffab5b9de029be5941f673dca2,Improving 3D Facial Action Unit Detection with Intrinsic Normalization,"YUDIN, ET AL.: IMPROVING 3D AU DETECTION WITH INTRINSIC NORMALIZATION +Improving 3D Facial Action Unit Detection +with Intrinsic Normalization +Geometric Image Processing Lab +Technion - Israel Institute of Technology +Technion City, Haifa, Israel +Eric Yudin +Aaron Wetzler +Matan Sela +Ron Kimmel"
+916ca7000c022fbd97ea15cc0094f0e53c408b56,Spontaneous and Non-Spontaneous 3D Facial Expression Recognition Using a Statistical Model with Global and Local Constraints,"SPONTANEOUS AND NON-SPONTANEOUS 3D FACIAL EXPRESSION RECOGNITION +USING A STATISTICAL MODEL WITH GLOBAL AND LOCAL CONSTRAINTS"
+91eae81dbba3013261292296bb929a18d73b447f,Utilization of Interest Point Detectors in Content Based Image Retrieval,"Ročník 2011 +Číslo II +Utilization of Interest Point Detectors in Content Based Image Retrieval +M. Zukal 1, P. Číka1 +Department of Telecommunications, Faculty of Electrical Engineering, BUT, Brno, +E-mail : +Purkyňova 118, Brno"
+91ddac7d1d63c52cbe30fe27674b9c1e54bc584c,Development of Eye-Blink and Face Corpora for Research in Human Computer Interaction,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 6, No. 5, 2015 +Development of Eye-Blink and Face Corpora for +Research in Human Computer Interaction +Emmanuel Jadesola Adejoke. +Dept. of Computer science +Bingham University +Nassarawa, Nigeria +Ibiyemi Tunji Samuel +Dept. of Electrical Engineering +University of Ilorin +Ilorin, Nigeria +oded +voluntary +eye-blink based +language communication depends"
9131c990fad219726eb38384976868b968ee9d9c,Deep Facial Expression Recognition: A Survey,"Deep Facial Expression Recognition: A Survey Shan Li and Weihong Deng∗, Member, IEEE"
911505a4242da555c6828509d1b47ba7854abb7a,Improved Active Shape Model for Facial Feature Localization,"IMPROVED ACTIVE SHAPE MODEL FOR FACIAL FEATURE LOCALIZATION @@ -9910,11 +33961,37 @@ http://www.atvs.diac.upm.es" Hierarchical Deformable Part Model Golnaz Ghiasi Charless C. Fowlkes Dept. of Computer Science, University of California, Irvine"
+657ae9ecb59cb2a27e57784577a9efb60de81126,The Task Matters: Comparing Image Captioning and Task-Based Dialogical Image Description,"The Task Matters: Comparing Image +Captioning and Task-Based Dialogical Image Description +Nikolai Ilinykh, Sina Zarrieß, David Schlangen +Dialogue Systems Group +University of Bielefeld +Germany"
6582f4ec2815d2106957215ca2fa298396dde274,Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations,"JUNE 2007 Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations Tae-Kyun Kim, Josef Kittler, Member, IEEE, and Roberto Cipolla, Member, IEEE"
+656e7c7739e3f334d4f275c71499485501aabc44,A Two-Step Methodology for Human Pose Estimation Increasing the Accuracy and Reducing the Amount of Learning Samples Dramatically,"A two-step methodology for human pose +estimation increasing the accuracy and reducing +the amount of learning samples dramatically +Samir Azrour, Sébastien Piérard, Pierre Geurts, and Marc Van Droogenbroeck +INTELSIG Laboratory, Department of Electrical Engineering and Computer Science, +University of Liège, Belgium"
+65eff143b099e53dcf39692c2fb542b0ee1fdfb6,Real-time Scale-invariant Object Recognition from Light Field Imaging,
+65639b79576f22b705a601f062bb6905f0a396af,A Preliminary Investigation into the Impact of Training for Example-Based Facial Blendshape Creation,"EUROGRAPHICS 2018/ O. Diamanti and A. Vaxman +Short Paper +A Preliminary Investigation into the Impact of Training for +Example-Based Facial Blendshape Creation +Emma Carrigan1, Ludovic Hoyet2, Rachel McDonnell1 and Quentin Avril3 +Graphics Vision and Visualisation Group, Trinity College Dublin, Ireland +Inria Rennes, France 3 Technicolor"
+65539436abf0eedabeb915a52f787b962722c99a,Satellite Image Classification via Two-Layer Sparse Coding With Biased Image Representation,"Satellite Image Classification via Two-Layer Sparse +Coding With Biased Image Representation +Dengxin Dai and Wen Yang, Member, IEEE"
+658c802890c7133e2ade778b5d88b68bcd0dca9c,Learning to Segment via Cut-and-Paste,"Learning to Segment via Cut-and-Paste +Tal Remez, Jonathan Huang, Matthew Brown +Google"
65b1209d38c259fe9ca17b537f3fb4d1857580ae,Information Constraints on Auto-Encoding Variational Bayes,"Information Constraints on Auto-Encoding Variational Bayes Romain Lopez1, Jeffrey Regier1, Michael I. Jordan1,2, and Nir Yosef1,3,4 {romain_lopez, regier, @@ -9922,6 +33999,14 @@ Department of Electrical Engineering and Computer Sciences, University of Califo Department of Statistics, University of California, Berkeley Ragon Institute of MGH, MIT and Harvard Chan-Zuckerberg Biohub"
+651125ca22947e95e5be6206c3056988b850266a,Swifter: improved online video scrubbing,"Swifter: Improved Online Video Scrubbing +Justin Matejka, Tovi Grossman, and George Fitzmaurice +Autodesk Research, Toronto, Ontario, Canada +Figure 1. Scrubbing behavior of a traditional streaming video player, the Swift interface [16], and our new Swifter +interface, which shows multiple frames around the active timeline location and allows for direct selection of each frame. +Traditional +Swift +Swifter"
655d9ba828eeff47c600240e0327c3102b9aba7c,Kernel pooled local subspaces for classification,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 35, NO. 3, JUNE 2005 Kernel Pooled Local Subspaces for Classification Peng Zhang, Student Member, IEEE, Jing Peng, Member, IEEE, and Carlotta Domeniconi"
@@ -9930,6 +34015,33 @@ for Visual Recognition ALI SHARIF RAZAVIAN Doctoral Thesis Stockholm, Sweden, 2017"
+650f4ccbe7d4aa49ae80e246df394ca6c60894ec,Department of Informatics,"DEPARTMENT OF INFORMATICS +TECHNISCHE UNIVERSITÄT MÜNCHEN +Bachelor’s Thesis in Informatics +Pedestrian detection in urban environments +ased on vision and depth data +Andreas Kreutz"
+652d3f33fd0a99808dd646aed228b45eacdaf34f,A Framework for Binding and Retrieving Class-Specific Information to and from Image Patterns Using Correlation Filters,"A Framework for Binding and Retrieving +Class-Specific Information to and from Image +Patterns using Correlation Filters +Vishnu Naresh Boddeti, Student Member, IEEE, and B.V.K Vijaya Kumar, Fellow, IEEE"
+65edab091e437d3b9d093dcb8be7c5dc4ce0fe0f,DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation,"DeepOrgan: Multi-level Deep Convolutional +Networks for Automated Pancreas Segmentation +Holger R. Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu, +Evrim B. Turkbey, and Ronald M. Summers +Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and +Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD +0892-1182, USA"
+65237b5e96c7492a0e5d01ddea5b1d381da408cd,A human-machine collaborative approach to tracking human movement in multi-camera video,"A Human-Machine Collaborative Approach to Tracking +Human Movement in Multi-Camera Video +Philip DeCamp +MIT Media Lab +0 Ames Street, E15-441 +Cambridge, Massachusetts 02139 +Deb Roy +MIT Media Lab +0 Ames Street, E15-488 +Cambridge, Massachusetts 02139"
656aeb92e4f0e280576cbac57d4abbfe6f9439ea,Use of Image Enhancement Techniques for Improving Real Time Face Recognition Efficiency on Wearable Gadgets,"Journal of Engineering Science and Technology Vol. 12, No. 1 (2017) 155 - 167 © School of Engineering, Taylor’s University @@ -9941,7 +34053,113 @@ AHMAD MOHAMMAD MAHMOOD ALQURNEH3 , 3Asia Pacific University of Technology & Innovation, Kuala Lumpur 57000, Malaysia Staffordshire University, Beaconside Stafford ST18 0AB, United Kingdom *Corresponding Author:"
+65a858ca95dcfa032e812a7f1fc7ee5bdac88f5b,Using Pre-Trained Models for Fine-Grained Image Classification in Fashion Field,"Using Pre-Trained Models for Fine-Grained Image +Classification in Fashion Field +Anna Iliukovich-Strakovskaia +Moscow Institute of Physics and +Technology +Moscow Institute of Physics and +Alexey Dral +Technology +“А” Kerchenskaya st., Moscow, +17303, Russian Federation +“А” Kerchenskaya st., Moscow, +17303, Russian Federation ++7 495 408 45 54 ++7 495 408 45 54 +Emeli Dral +Moscow Institute of Physics and +Technology & Yandex Data Factory +“А” Kerchenskaya st., Moscow, +17303, Russian Federation ++7 495 408 45 54"
+6527cf0b9dbddbd0c6429a35a3cbded3ca336583,MCMC Supervision for People Re-identification in Nonoverlapping Cameras,"MEDEN, LERASLE, SAYD: MCMC TRACKING-BY-REIDENTICATION +MCMC Supervision for People +Reidentification in Nonoverlapping Cameras +Boris Meden1 +Frédéric Lerasle2 +lerasle.laas.fr +Patrick Sayd1 +CEA, LIST, +Laboratoire Vision et Ingénierie des +Contenus, +BP 94, F-91191 Gif-sur-Yvette, France +CNRS ; LAAS ; +Université de Toulouse ; UPS, LAAS ; +F-31077 Toulouse Cedex 4, France"
656f05741c402ba43bb1b9a58bcc5f7ce2403d9a,Supervised Learning Approaches for Automatic Structuring of Videos. (Méthodes d'apprentissage supervisé pour la structuration automatique de vidéos),"THÈSEPour obtenir le grade deDOCTEUR DE L’UNIVERSITÉ GRENOBLE ALPESSpécialité : Mathématiques et InformatiqueArrêté ministériel : 7 août 2006Présentée parDanila POTAPOVThèse dirigée par Cordelia SCHMID et codirigée par Zaid HARCHAOUIpréparée au sein de Inria Grenoble Rhône-Alpesdans l'École Doctorale Mathématiques, Sciences et technologies de l'information, InformatiqueSupervised Learning Approaches for Automatic Structuring of VideosThèse soutenue publiquement le « 22 Juillet 2015 »,devant le jury composé de : Prof. Cordelia SCHMID Inria Grenoble Rhône-Alpes, France, Directeur de thèseDr. Zaid HARCHAOUIInria Grenoble Rhône-Alpes, France, Co-encadrant de thèse Prof. Patrick PEREZTechnicolor Rennes, France, RapporteurProf. Ivan LAPTEVInria Paris Rocquencourt, France, Rapporteur, PrésidentDr. Florent PERRONNINFacebook AI Research, Paris, France, ExaminateurDr. Matthijs DOUZEInria Grenoble Rhône-Alpes, France, Examinateur"
+659fc2a483a97dafb8fb110d08369652bbb759f9,Improving the Fisher Kernel for Large-Scale Image Classification,"Improving the Fisher Kernel +for Large-Scale Image Classification +Florent Perronnin, Jorge S´anchez, and Thomas Mensink +Xerox Research Centre Europe (XRCE)"
+656a5d4d84c450792402b3c69eecbdbca4cad4cb,2.1. Imagenet and Related Datasets,"Figure 4: Percent of clean images at different tree depth levels in +ImageNet. A total of 80 synsets are randomly sampled at every +tree depth of the mammal and vehicle subtrees. An independent +group of subjects verified the correctness of each of the images. +An average of 99.7% precision is achieved for each synset. +ImageNet +TinyImage +LabelMe +LHill +LabelDisam +Clean +DenseHie +FullRes +PublicAvail +Segmented +Table 1: Comparison of some of the properties of ImageNet ver- +sus other existing datasets. +ImageNet offers disambiguated la- +els (LabelDisam), clean annotations (Clean), a dense hierarchy +(DenseHie), full resolution images (FullRes) and is publicly avail-"
+65874dd7220664762b5b25f47460b623a7eb0175,Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis,"Sensors 2014, 14, 22643-22669; doi:10.3390/s141222643 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +Tree Crown Mapping in Managed Woodlands (Parklands) of +Semi-Arid West Africa Using WorldView-2 Imagery and +Geographic Object Based Image Analysis +Martin Karlson 1,*, Heather Reese 2,† and Madelene Ostwald 1,3,† +Centre for Climate Science and Policy Research, Department of Thematic Studies/Environmental +Change, Linköping University, Linköping 58183, Sweden; E-Mail: +Section of Forest Remote Sensing, Department of Forest Resource Management, +Swedish University of Agricultural Sciences, Umeå 901 83, Sweden; E-Mail: +Centre for Environment and Sustainability, GMV, University of Gothenburg and +Chalmers University of Technology, Göteborg 405 30, Sweden +These authors contributed equally to this work. +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +46-1328-2977; Fax: +46-1313-3630. +External Editor: Assefa M. Melesse"
+6574eaab393aa8d674cd785fab16cae06a53151a,A study on polymorphing superscalar processor dynamically to improve power efficiency,"A Study on Polymorphing Superscalar Processor Dynamically +to Improve Power Efficiency +Sudarshan Srinivasan, Rance Rodrigues, Arunachalam Annamalai, Israel Koren and Sandip Kundu +Department of Electrical and Computer Engineering +University of Massachusetts at Amherst, MA, USA +Email: {ssrinivasan, rodrigues, annamalai, koren,"
+65ec52a3e0a0f6a46fd140ff83bb82d7d02a2d45,Learning Hierarchical Features from Generative Models,"Learning Hierarchical Features from Generative Models +Shengjia Zhao 1 Jiaming Song 1 Stefano Ermon 1"
+656b6133fd671f129fce0091a8dab39c97e604f2,Multiview Discriminative Geometry Preserving Projection for Image Classification,"Hindawi Publishing Corporation +e Scientific World Journal +Volume 2014, Article ID 924090, 11 pages +http://dx.doi.org/10.1155/2014/924090 +Research Article +Multiview Discriminative Geometry Preserving +Projection for Image Classification +Ziqiang Wang, Xia Sun, Lijun Sun, and Yuchun Huang +School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China +Correspondence should be addressed to Ziqiang Wang; +Received 19 December 2013; Accepted 22 January 2014; Published 9 March 2014 +Academic Editors: X. Meng, Z. Zhou, and X. Zhu +Copyright © 2014 Ziqiang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, +which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +In many image classification applications, it is common to extract multiple visual features from different views to describe an image. +Since different visual features have their own specific statistical properties and discriminative powers for image classification, the +onventional solution for multiple view data is to concatenate these feature vectors as a new feature vector. However, this simple +oncatenation strategy not only ignores the complementary nature of different views, but also ends up with “curse of dimensionality.” +To address this problem, we propose a novel multiview subspace learning algorithm in this paper, named multiview discriminative +geometry preserving projection (MDGPP) for feature extraction and classification. MDGPP can not only preserve the intraclass"
65817963194702f059bae07eadbf6486f18f4a0a,WhittleSearch: Interactive Image Search with Relative Attribute Feedback,"http://dx.doi.org/10.1007/s11263-015-0814-0 WhittleSearch: Interactive Image Search with Relative Attribute Feedback @@ -9967,6 +34185,15 @@ Prof. Dr. Gerhard Rigoll Technische Universität München KIT – Universität des Landes Baden-Württemberg und nationales Forschungszentrum in der Helmholtz-Gemeinschaft www.kit.edu"
+659fc18b1ec79a7437e6e7b1dce145d423e82199,Real time person detection and tracking by mobile robots using RGB-D images,"Real Time Person Detection and Tracking by Mobile Robots using +RGB-D Images +Duc My Vo, Lixing Jiang and Andreas Zell"
+65d588e2ff7b4f2903efbeded978885f7da5d0e0,UMPM benchmark: A multi-person dataset with synchronized video and motion capture data for evaluation of articulated human motion and interaction,"UMPM benchmark: a multi-person dataset with synchronized video and motion +apture data for evaluation of articulated human motion and interaction +N.P. van der Aa1,2, X. Luo1, G.J. Giezeman1, R.T. Tan1, R.C. Veltkamp1 +{x.luo, g.j.giezeman, r.t.tan, +Utrecht University +Noldus Information Technology"
653d19e64bd75648cdb149f755d59e583b8367e3,"Decoupling ""when to update"" from ""how to update""","Decoupling “when to update” from “how to update” Eran Malach and Shai Shalev-Shwartz @@ -9988,6 +34215,13 @@ Noise-resistant network: a deep-learning method for face recognition under noise Yuanyuan Ding1,2, Yongbo Cheng1,2, Xiaoliu Cheng1, Baoqing Li1*, Xing You1 and Xiaobing Yuan1 Open Access"
+62aeecbe5db3e4ed6b783f4b580157f4f1c8ba45,"Haar like and LBP based features for face, head and people detection in video sequences","Author manuscript, published in ""International Workshop on Behaviour Analysis and Video Understanding (ICVS 2011) (2011)"
+6275aa21331a2712222b7ab2116e9589e21ae82c,Prediction of Manipulation Actions,"Noname manuscript No. +(will be inserted by the editor) +Prediction of Manipulation Actions +Cornelia Ferm¨uller · Fang Wang · Yezhou Yang · Konstantinos Zampogiannis · Yi +Zhang · Francisco Barranco · Michael Pfeiffer +the date of receipt and acceptance should be inserted later"
62694828c716af44c300f9ec0c3236e98770d7cf,Identification of Action Units Related to Affective States in a Tutoring System for Mathematics,"Padrón-Rivera, G., Rebolledo-Mendez, G., Parra, P. P., & Huerta-Pacheco, N. S. (2016). Identification of Action Units Related to Identification of Action Units Related to Affective States in a Tutoring System Gustavo Padrón-Rivera1, Genaro Rebolledo-Mendez1*, Pilar Pozos Parra2 and N. Sofia @@ -9996,12 +34230,61 @@ Tabasco, Mexico // // // // for Mathematics Huerta-Pacheco1 *Corresponding author"
+6225e9c2a9ee47b4d3d58313a839f6e170b48525,Shape Aware Matching of Implicit Surfaces based on Thin Shell Energies,"SHAPE AWARE MATCHING OF IMPLICIT SURFACES BASED ON THIN SHELL +ENERGIES +JOS ´E A. IGLESIAS, MARTIN RUMPF, AND OTMAR SCHERZER"
+62e8010e2ac1523d3a3e7e1c13cb34e63e85ce04,Transfer Learning for Action Unit Recognition,"Transfer Learning for Action Unit Recognition +Yen Khye Lim1, Zukang Liao1, Stavros Petridis1 and Maja Pantic1,2"
+62d5c16760018b08e301a940434c3fc2e862c385,Approach For Palm Vein Blood Vessel Detection Based On Fuzzy Logic,"International Journal of Electronics Engineering Research. +ISSN 0975-6450 Volume 9, Number 4 (2017) pp. 613-619 +© Research India Publications +http://www.ripublication.com +Approach For Palm Vein Blood Vessel Detection +Based On Fuzzy Logic +Praveen Kaundal +Department of E.C.E, PEC, University of Technology +Chandigarh-160012, India +Dr. Sukhwinder Singh +Department of E.C.E, PEC, University of Technology +Chandigarh-160012, India"
+622949b1aacd316c60a7034c44121c698a3fb6a4,Highway Driving Dataset for Semantic Video Segmentation,"KIM, YIM, AND KIM: HIGHWAY DRIVING DATASET +Highway Driving Dataset +for Semantic Video Segmentation +Byungju Kim +Junho Yim +Junmo Kim* +School of Electrical Engineering +Korea Advanced Institute of Science +nd Technology (KAIST), +South Korea"
+6211ba456908d605e85d102d63b106f1acb52186,Visual Interpretability forDeepLearning,"Zhang et al. / Front Inform Technol Electron Eng +in press +Frontiers of Information Technology & Electronic Engineering +www.jzus.zju.edu.cn; engineering.cae.cn; www.springerlink.com +ISSN 2095-9184 (print); ISSN 2095-9230 (online) +E-mail: +Visual Interpretability for Deep Learning∗ +Quanshi Zhang and Song-Chun Zhu +(University of California, Los Angeles) +E-mail:"
62f0d8446adee6a5e8102053a63a61af07ac4098,Facial point detection using convolutional neural network transferred from a heterogeneous task,"FACIAL POINT DETECTION USING CONVOLUTIONAL NEURAL NETWORK TRANSFERRED FROM A HETEROGENEOUS TASK Takayoshi Yamashita* Taro Watasue** Yuji Yamauchi* Hironobu Fujiyoshi* **Tome R&D *Chubu University, 200, Matsumoto-cho, Kasugai, AICHI"
+62cf8c07ca6c4c7817f6a5682eb2d7cde76198ae,Boosted Metric Learning for Efficient Identity-Based Face Retrieval,"NEGREL ET AL.: BOOSTED METRIC LEARNING FOR FACE RETRIEVAL +Boosted Metric Learning for Efficient +Identity-Based Face Retrieval +Romain Negrel +Alexis Lechervy +Frederic Jurie +GREYC, CNRS UMR 6072, ENSICAEN +Université de Caen Basse-Normandie +France"
+6268ad4bc516a41a30db566e2207079fc483212e,LBP-Based Edge-Texture Features for Object Recognition,"LBP-Based Edge-Texture Features for +Object Recognition +Amit Satpathy, Member, IEEE, Xudong Jiang, Senior Member, IEEE, and How-Lung Eng, Member, IEEE"
62374b9e0e814e672db75c2c00f0023f58ef442c,Frontal face authentication using discriminating,"Frontalfaceauthenticationusingdiscriminatinggridswith morphologicalfeaturevectors A.Tefas @@ -10022,11 +34305,137 @@ presented. Correspondingauthor:I.Pitas DRAFT September +6215c5713adeacbb33b9d1c4c739f2b0b50dd17f,Part-based 3d Face Recognition under Pose and Expression Variations,"PART-BASED 3D FACE RECOGNITION UNDER POSE AND EXPRESSION +VARIATIONS +Hamdi Dibeklio˘glu +B.S, in Computer Engineering, Yeditepe University, 2006 +Submitted to the Institute for Graduate Studies in +Science and Engineering in partial fulfillment of +the requirements for the degree of +Master of Science +Graduate Program in Computer Engineering +Bo˘gazi¸ci University"
+6273b3491e94ea4dd1ce42b791d77bdc96ee73a8,"Evaluating Appearance Models for Recognition, Reacquisition, and Tracking","Evaluating Appearance Models for Recognition, Reacquisition, and Tracking +Doug Gray +Shane Brennan +Hai Tao +University of California, Santa Cruz +156 High St., Santa Cruz, CA 95064 +{dgray, shanerb,"
+62d1b32d67e4a4b58a66cba91629aae5f7968962,Recurrent Neural Networks for Semantic Instance Segmentation,"Recurrent Neural Networks +for Semantic Instance Segmentation +Amaia Salvador1, M´ıriam Bellver2, V´ıctor Campos2, Manel Baradad1 +Ferran Marques1 Jordi Torres2 and Xavier Giro-i-Nieto1 +Universitat Polit`ecnica de Catalunya 2Barcelona Supercomputing Center"
626859fe8cafd25da13b19d44d8d9eb6f0918647,Activity Recognition Based on a Magnitude-Orientation Stream Network,"Activity Recognition based on a Magnitude-Orientation Stream Network Carlos Caetano, Victor H. C. de Melo, Jefersson A. dos Santos, William Robson Schwartz Smart Surveillance Interest Group, Department of Computer Science Universidade Federal de Minas Gerais, Belo Horizonte, Brazil"
+6289d2c4c47d7101861153bfe78c92d16cf4581b,A Cross-Core Performance Model for Heterogeneous Many-Core Architectures,"A Cross-Core Performance Model for +Heterogeneous Many-Core Architectures +Rui Pinheiro, Nuno Roma, and Pedro Tom´as (cid:63) +INESC-ID, Instituto Superior T´ecnico, Universidade de Lisboa"
+623da0faea1f98f238936e34f361518829edfdf4,Digital geometry image analysis for medical diagnosis,"Digital Geometry Image Analysis for Medical Diagnosis +Jiandong Fang Shiaofen Fang Jeffrey Huang Mihran Tuceryan +Department of Computer and Information Science +Indiana University Purdue University Indianapolis +723 W. Michigan St., SL 280 +Indianapolis, IN 46202, USA +-317-274-9731"
+624077c8c8c9306c12671870cacc0fb13ff20324,"Smart, Sparse Contours to Represent and Edit Images","Sparse, Smart Contours to Represent and Edit Images +Tali Dekel 1 +Chuang Gan 2 +Dilip Krishnan 1 +Ce Liu 1 William T. Freeman 1,3 +Google Research 2 MIT-Watson AI Lab 3 MIT-CSAIL +Figure 1. Our method produces high quality reconstructions of images from information along a small number of contours: a source +(512×512) image in (a) is reconstructed in (c) from gradient information stored at the set of colored contours in (b)2, which are less than +5% of the pixels. The model synthesizes hair texture, facial lines and shading even in regions where no input information is provided. +Our model allows for semantically intuitive editing in the contour domain. Top-right: a caricature-like result (e) is created by moving and +scaling some contours in (d). Bottom-right: hairs are synthesized by pasting a set of hair contours copied from a reference image. Edited +ontours are marked in green while the original contours in red."
+6236962ce0d627fc23774f0680e77069b9667803,Fitting a Morphable Model to Pose and Shape of a Point Cloud,"Fitting a Morphable Model to Pose and Shape of a Point Cloud +David C. Schneider, Peter Eisert +Fraunhofer Heinrich Hertz Institute, Einsteinufer 37, 10587 Berlin, Germany"
+627107c02c2df1366965f11678dd3c4fb14ac9b3,Connecting Images and Natural Language a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"CONNECTING IMAGES AND NATURAL LANGUAGE +A DISSERTATION +SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE +AND THE COMMITTEE ON GRADUATE STUDIES +OF STANFORD UNIVERSITY +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +DOCTOR OF PHILOSOPHY +Andrej Karpathy +August 2016"
+629722342f719ee413e9bb07072a2fc2b4f09a26,Gender Classification by Information Fusion of Hair and Face,"Gender Classification by Information Fusion +of Hair and Face +Zheng Ji, Xiao-Chen Lian and Bao-Liang Lu +Department of Computer Science and Engineering, Shanghai +Jiao Tong University 800 Dong Chuan Road, +Shanghai 200240, China +. Introduction +Various gender classification methods have been reported in the literature. These existing +methods fall into two categories. The first kind of method is the appearance-based approach. +Golomb et al. [1] used a two-layer neural network with 30 × 30 inputs and directly fed the +scaled image pixels to the network without dimensionality reduction. Their database +ontains only 90 images with half male and half female facial images. Gutta et al. [2] used the +mixture of experts combining the ensembles of radial basis functions (RBF) networks and a +decision tree. Xu et al. [3] applied Adaboost to gender classification problem with the feature +pools composed of a set of linear projections utilizing statistical moments up to second +order. Wu et al. [4] also adopted Adaboost. Instead of using threshold weak classifiers, they +used looking-up table weak classifiers, which are more general and better than simple +threshold ones due to stronger ability to model complex distribution of training samples. +Moghaddam and Yang [5] demonstrated that support vector machines (SVMs) work better +than other classifiers such as ensemble of radial basis function (RBF) networks, classical RBF"
+62e2c431d375bbafd988d53c4d39f240c8b7977b,A Game-Theoretic Probabilistic Approach for Detecting Conversational Groups,"A Game-Theoretic Probabilistic Approach +for Detecting Conversational Groups +Sebastiano Vascon1, Eyasu Zemene Mequanint2, Marco Cristani1,3, Hayley Hung4 (cid:63), +Marcello Pelillo2, and Vittorio Murino1,3 +Dept. of Pattern Analysis & Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Genova, Italy +Dept. of Environmental Sciences, Informatics and Statistics, University Ca’ Foscari of Venice, Italy +Dept. of Computer Science, University of Verona, Italy +Faculty of Electrical Engineering, Mathematics and Computer Science, Technical University of Delft, Netherlands"
+627412bf4cf2706f6dc9530313ecf06bbc532cca,Dissertation Gerard Pons Moll,"Human Pose Estimation from Video and Inertial +Sensors +Von der Fakultät für Elektrotechnik und Informatik +der Gottfried Wilhelm Leibniz Universität Hannover +zur Erlangung des akademischen Grades +Doktor-Ingenieur +(abgekürzt: Dr.-Ing.) +genehmigte +Dissertation +Gerard Pons Moll +geboren am 25. Oktober 1984 in Barcelona."
+62dd66f9f4995cfdaafb479de50363ce0255b1bd,2 Feature Extraction Based on Wavelet Moments and Moment Invariants in Machine Vision Systems,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+621ea1f1e364262348135c803557e7b3454a804e,Generative spatiotemporal modeling of neutrophil behavior,"Accepted to 2018 IEEE International Symposium on Biomedical Imaging +Copyright ©2018 IEEE +Generative Spatiotemporal Modeling Of Neutrophil Behavior +Narita Pandhe(cid:63) +Balazs Rada† +Shannon Quinn(cid:63) +(cid:63) Department of Computer Science +Department of Infectious Diseases +University of Georgia"
62007c30f148334fb4d8975f80afe76e5aef8c7f,Eye In-Painting with Exemplar Generative Adversarial Networks,"Eye In-Painting with Exemplar Generative Adversarial Networks Brian Dolhansky, Cristian Canton Ferrer Facebook Inc. @@ -10035,6 +34444,11 @@ Hacker Way, Menlo Park (CA), USA 62a30f1b149843860938de6dd6d1874954de24b7,Fast Algorithm for Updating the Discriminant Vectors of Dual-Space LDA,"Fast Algorithm for Updating the Discriminant Vectors of Dual-Space LDA Wenming Zheng, Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
+626c12d6ccb1405c97beca496a3456edbf351643,Conditional Variance Penalties and Domain Shift Robustness,"Conditional Variance Penalties and Domain Shift Robustness +Christina Heinze-Deml & Nicolai Meinshausen +Seminar for Statistics +ETH Zurich +Zurich, Switzerland"
62e0380a86e92709fe2c64e6a71ed94d152c6643,Facial emotion recognition with expression energy,"Facial Emotion Recognition With Expression Energy Albert Cruz Center for Research in @@ -10051,6 +34465,29 @@ Intelligent Systems Riverside, CA, 92521-0425, Riverside, CA, 92521-0425, Riverside, CA, 92521-0425,"
+62b90583723174220b26c92bd67f6c422ad75570,Dna-gan: Learning Disentangled Represen-,"Under review as a conference paper at ICLR 2018 +DNA-GAN: LEARNING DISENTANGLED REPRESEN- +TATIONS FROM MULTI-ATTRIBUTE IMAGES +Anonymous authors +Paper under double-blind review"
+62070fbd22b2a4bba830668c2e9720ec4bff4171,Fast human detection using template matching for gradient images and aSC descriptors based on subtraction stereo,"978-1-4799-2341-0/13/$31.00 ©2013 IEEE +ICIP 2013"
+968c62bb2927ca300ef953644e652ba7d2c2e5e6,Learning person-object interactions for action recognition in still images,"Learning person-object interactions for +ction recognition in still images +Vincent Delaitre∗ +´Ecole Normale Sup´erieure +Josef Sivic* +INRIA Paris - Rocquencourt +Ivan Laptev* +INRIA Paris - Rocquencourt"
+96e7142ab905c54c033696ac3692e85692c43bf3,Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment,"Noname manuscript No. +(will be inserted by the editor) +Sparse Illumination Learning and Transfer for +Single-Sample Face Recognition with Image Corruption and +Misalignment +Liansheng Zhuang · Tsung-Han Chan · +Allen Y. Yang · S. Shankar Sastry · Yi Ma +Received: date / Accepted: date"
9626bcb3fc7c7df2c5a423ae8d0a046b2f69180c,A deep learning approach for action classification in American football video sequences,"UPTEC STS 17033 Examensarbete 30 hp November 2017 @@ -10058,19 +34495,119 @@ A deep learning approach for ction classification in American football video sequences Jacob Westerberg"
+96e9bc6b54d1c79406cf37ae45fd35ef04d647c6,A Fully Automated System for Sizing Nasal PAP Masks Using Facial Photographs,"A Fully Automated System for Sizing Nasal PAP Masks Using Facial +Photographs +Benjamin Johnston Student Member, IEEE and Philip de Chazal Senior Member, IEEE"
+9603b3a4649fd217752972909d627bde8e0a5023,Spectral Hashing With Semantically Consistent Graph for Image Indexing,"Spectral Hashing With Semantically +Consistent Graph for Image Indexing +Peng Li, Meng Wang, Member, IEEE, Jian Cheng, Member, IEEE, Changsheng Xu, Senior Member, IEEE, and +Hanqing Lu, Senior Member, IEEE"
+96d6e0bf752c42ede0170e9b332ca390ac75cd1f,Temporal Hierarchical Dictionary with HMM for Fast Gesture Recognition,"018 24th International Conference on Pattern Recognition (ICPR) +Beijing, China, August 20-24, 2018 +978-1-5386-3787-6/18/$31.00 ©2018 European Union"
9696b172d66e402a2e9d0a8d2b3f204ad8b98cc4,Region-Based Facial Expression Recognition in Still Images,"J Inf Process Syst, Vol.9, No.1, March 2013 pISSN 1976-913X eISSN 2092-805X Region-Based Facial Expression Recognition in Still Images Gawed M. Nagi*, Rahmita Rahmat*, Fatimah Khalid* and Muhamad Taufik*"
+9679d15c6699b521740408b2e899c03af89390ac,Dimensionality Reduction for 3d Articulated Body Tracking and Human Action Analysis,"DIMENSIONALITY REDUCTION FOR 3D +ARTICULATED BODY TRACKING AND HUMAN +ACTION ANALYSIS +Leonid Raskin +Research Supervisors: +Prof. Ehud Rivlin, Dr. Michael Rudzsky +Prof. Michael Lindenbaum +Submitted in Partial Fulfillment of the Requirements for the +Degree of Doctor of Philosophy +Technion IIT - Israel Institute of Technology +Haifa, Israel +March 2010 +(cid:176) Copyright by Leonid Raskin, 2010 +Technion - Computer Science Department - Ph.D. Thesis PHD-2010-11 - 2010"
+96390f95a73a6bd495728b6cd2a97554ef187f76,Pan Olympus : Sensor Privacy through Utility Aware,"Proceedings on Privacy Enhancing Technologies ..; .. (..):1–21 +Nisarg Raval, Ashwin Machanavajjhala, and Jerry Pan +Olympus: Sensor Privacy through Utility Aware +Obfuscation"
+9630109529870d142fde01341da05967484e906c,Techniques of Facial Synthesis: A Comprehensive Literature Review,"International Journal of Computer Applications (0975 – 8887) +Volume 61– No.10, January 2013 +Techniques of Facial Synthesis: A +Comprehensive Literature Review +Deepti Chandra +Shri Shankaracharya College +of Engg. & Technology, Bhilai, +Chhattisgarh, India +Sanjeev Karmakar +Bhilai Institute of Technology (BIT) +Chhattisgarh, Durg 491001, India +Rajendra Hegadi +Pragati College of Engg. & +Management +Raipur,Chhattisgarh, India +realism +-the synthesized"
96f4a1dd1146064d1586ebe86293d02e8480d181,Comparative Analysis of Reranking Techniques for Web Image Search,"COMPARATIVE ANALYSIS OF RERANKING TECHNIQUES FOR WEB IMAGE SEARCH Suvarna V. Jadhav1, A.M.Bagade2 ,2Department of Information Technology, Pune Institute of Computer Technology, Pune,( India)"
+96723b42451c42ec396381596490143aac8f85cd,A Computer Vision Approach for the Eye Accessing Cue Model Used in Neuro-linguistic Programming,"U.P.B. Sci. Bull., Series C, Vol. 75, Iss. 4, 2013 ISSN 2286 – 3540 +A COMPUTER VISION APPROACH FOR THE EYE +ACCESSING CUE MODEL USED IN NEURO-LINGUISTIC +PROGRAMMING +Ruxandra VRÂNCEANU1, Laura FLOREA2, Corneliu FLOREA3 +This paper investigates the Eye Accessing Cue (EAC) model used in Neuro- +Linguistic Programming (NLP) and shows how image processing techniques can be +used to improve the interpretation of this model. An experiment was carried out to +validate the model by inducing certain eye cues using a set of questions. A simple +nd efficient method is proposed for automatically locating the eyes and the +orrespondent EAC. The relative position between the iris and the sclera is +determined using a fast mechanism, based on the analysis of integral projections +inside the bounding box of the eye. +Keywords: Neuro-Linguistic Programming, Eye Detection, Eye Gaze +. Introduction +The progress made in image processing and the increase of computational +apabilities of machines over the past decades has led to new opportunities for +human-computer interactions and to the development of systems capable of +utomatically interpreting the facial attributes of a person. Such algorithms are +used in the field of people identification and description, in applications that"
+96a7f2faf4baa09184deb458a03146805d62beed,Passive Three Dimensional Face Recognition Using Iso-Geodesic Contours and Procrustes Analysis,"Int J Comput Vis (2013) 105:87–108 +DOI 10.1007/s11263-013-0631-2 +Passive Three Dimensional Face Recognition Using Iso-Geodesic +Contours and Procrustes Analysis +Sina Jahanbin · Rana Jahanbin · Alan C. Bovik +Received: 11 November 2011 / Accepted: 11 May 2013 / Published online: 19 June 2013 +© Springer Science+Business Media New York 2013"
9606b1c88b891d433927b1f841dce44b8d3af066,Principal Component Analysis with Tensor Train Subspace,"Principal Component Analysis with Tensor Train Subspace Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron"
+96fdc0131dc80ffa6d7b9c526e07f080414c54ec,1 Paying More A ention to Saliency : Image Captioning with Saliency and Context A ention,"Paying More A(cid:130)ention to Saliency: Image Captioning with +Saliency and Context A(cid:130)ention +MARCELLA CORNIA, University of Modena and Reggio Emilia +LORENZO BARALDI, University of Modena and Reggio Emilia +GIUSEPPE SERRA, University of Udine +RITA CUCCHIARA, University of Modena and Reggio Emilia +Image captioning has been recently gaining a lot of a(cid:138)ention thanks to the impressive achievements +shown by deep captioning architectures, which combine Convolutional Neural Networks to extract image +representations, and Recurrent Neural Networks to generate the corresponding captions. At the same time, +signi(cid:128)cant research e(cid:130)ort has been dedicated to the development of saliency prediction models, which +an predict human eye (cid:128)xations. Even though saliency information could be useful to condition an image +aptioning architecture, by providing an indication of what is salient and what is not, research is still struggling +to incorporate these two techniques. In this work, we propose an image captioning approach in which a +generative recurrent neural network can focus on di(cid:130)erent parts of the input image during the generation of +the caption, by exploiting the conditioning given by a saliency prediction model on which parts of the image +re salient and which are contextual. We show, through extensive quantitative and qualitative experiments on +large scale datasets, that our model achieves superior performances with respect to captioning baselines with +nd without saliency, and to di(cid:130)erent state of the art approaches combining saliency and captioning. +CCS Concepts: •Computing methodologies →Scene understanding; Natural language generation; +Additional Key Words and Phrases: saliency, visual saliency prediction, image captioning, deep learning."
+9691055b1fcbe626b5bce9d8d43903094a5c0339,Generating an item pool for translational social cognition research: methodology and initial validation.,"Behav Res (2015) 47:228–234 +DOI 10.3758/s13428-014-0464-0 +Generating an item pool for translational social cognition +research: Methodology and initial validation +Michael K. Keutmann & Samantha L. Moore & +Adam Savitt & Ruben C. Gur +Published online: 10 April 2014 +# Psychonomic Society, Inc. 2014"
96b1000031c53cd4c1c154013bb722ffd87fa7da,ContextVP: Fully Context-Aware Video Prediction,"ContextVP: Fully Context-Aware Video Prediction Wonmin Byeon1,2,3,4, Qin Wang2, @@ -10079,7 +34616,19 @@ NVIDIA, Santa Clara, CA, USA ETH Zurich, Zurich, Switzerland The Swiss AI Lab IDSIA, Manno, Switzerland NNAISENSE, Lugano, Switzerland"
+96f0da034d090a3ecadd0fb92333bb681f23ab14,Temporal-Spatial Mapping for Action Recognition,"Temporal-Spatial Mapping for Action Recognition +Xiaolin Song, Cuiling Lan, Wenjun Zeng, Junliang Xing, Jingyu Yang, and Xiaoyan Sun"
+964e43f4983a42ef3790c265bdce42c1fce56d79,A Virtual Environment Tool for Benchmarking Face Analysis Systems,"A Virtual Environment Tool for Benchmarking Face +Analysis Systems +Mauricio Correa+,*, Javier Ruiz-del-Solar+,*, Rodrigo Verschae* ++Department of Electrical Engineering, Universidad de Chile +*Advanced Mining Technology Center, Universidad de Chile +{macorrea,"
968f472477a8afbadb5d92ff1b9c7fdc89f0c009,Firefly-based Facial Expression Recognition,Firefly-based Facial Expression Recognition
+96fc93175169b788acd98f0a676dffab00651cbc,On Matching Faces with Alterations due to Plastic Surgery and Disguise,"On Matching Faces with Alterations due to Plastic Surgery and Disguise +Saksham Suri1, Anush Sankaran2, Mayank Vatsa1, Richa Singh1 +IIIT - Delhi, India 2IBM Research, Bengaluru, India +{saksham15082, mayank,"
9686dcf40e6fdc4152f38bd12b929bcd4f3bbbcc,Emotion Based Music Player,"International Journal of Engineering Research and General Science Volume 3, Issue 1, January-February, 2015 ISSN 2091-2730 Emotion Based Music Player @@ -10089,10 +34638,78 @@ Department of Computer Science and Engineering Department of Computer Science and Engineering Asst. Professor, Department of Computer Science and Engineering M.H Saboo Siddik College of Engineering, University of Mumbai, India"
+96788880589a514c3ae9de29695c0127d6e76b8f,Attention-Based Multimodal Fusion for Video Description,"Attention-Based Multimodal Fusion for Video Description +Chiori Hori +Takaaki Hori +Teng-Yok Lee +Kazuhiro Sumi∗ +John R. Hershey +Tim K. Marks +Mitsubishi Electric Research Laboratories (MERL) +{chori, thori, tlee, sumi, hershey,"
+3abfab8740ffc66c0c191ce32ce1240062620bea,Continuous Facial Affect Recognition from Videos,"N. Garay, J. Abascal (Eds.): Actas del XII Congreso Internacional Interacción 2011, Lisboa +Continuous Facial Affect Recognition from Videos +Sergio Ballano1, Isabelle Hupont1, Eva Cerezo2 and Sandra Baldassarri2 +Aragon Institute of Technology, Department of R&D and Technology Services, +Zaragoza. 5018, María de Luna 7-8, Spain +University of Zaragoza, Computer Science and Systems Engineering Department, +Zaragoza. 50018, María de Luna 3, Spain +{sballano, {ecerezo,"
+3a7f9b4badc7407273325650763e887ad7b5cc9e,Anthropometric Comparison of Cross-Sectional External Ear between Monozygotic Twin,"Annals of Forensic Research and Analysis +*Corresponding author +Rumiza Abd Rashid, Institute of Forensic Sciences, +Universiti Teknologi MARA, 40450 Shah Alam, Selangor, +Malaysia; Tel: +60196943080; Fax: +603-55444562 ; +Email: +Submitted: 19 November 2014 +Accepted: 20 November 2014 +Published: 22 November 2014 +Copyright +© 2014 Rashid et al. +OPEN ACCESS +Keywords +• External ear +• Monozygotic twin +• Anthropometric measurement +• Forensic anthropology +• Identification +Research Article +Anthropometric Comparison"
+3aad63c3c049eedb1c6da4871faa90e797b933e8,Highway Networks for Visual Question Answering,"Highway Networks for Visual Question Answering +Aaditya Prakash and James Storer +Brandeis University"
3a2fc58222870d8bed62442c00341e8c0a39ec87,Probabilistic Local Variation Segmentation,"Probabilistic Local Variation Segmentation Michael Baltaxe Technion - Computer Science Department - M.Sc. Thesis MSC-2014-02 - 2014"
+3a4ecdf7d73b0fb392763048aa834a537a495537,Contour-based object detection,"SCHLECHT, OMMER: CONTOUR-BASED OBJECT DETECTION +Contour-based Object Detection +Joseph Schlecht +Björn Ommer +Interdisciplinary Center for +Scientific Computing +University of Heidelberg +Germany"
+3aef744dad3982a7ae1ad97b4f126b6772fc3d07,Scene-Centric Joint Parsing of Cross-View Videos,"Scene-centric Joint Parsing of Cross-view Videos +Hang Qi1∗, Yuanlu Xu1∗, Tao Yuan1∗, Tianfu Wu2, Song-Chun Zhu1 +Dept. Computer Science and Statistics, University of California, Los Angeles (UCLA) +{hangqi, tianfu +Dept. Electrical and Computer Engineering, NC State University"
+3a8f16d8f7adae8bd0cdc5cc5114dac0b388a9f6,Interpreting Deep Neural Network: Fast Object Localization via Sensitivity Analysis,"Under review as a conference paper at ICLR 2019 +INTERPRETING DEEP NEURAL NETWORK: +FAST OBJECT LOCALIZATION VIA SENSITIVITY +ANALYSIS +Anonymous authors +Paper under double-blind review"
+3a8023d206613c930cee8e9166fcbbfd743e6634,Enhancing Person Re-identification in a Self-trained Subspace,"Enhancing Person Re-identification in a Self-trained +Subspace +Xun Yang, Meng Wang, Richang Hong, Qi Tian, Yong Rui"
+3acfbc2aee9b2ed246a640930ebc2e350621f990,Progressive Boosting for Class Imbalance,"Progressive Boosting for Class Imbalance +Roghayeh Soleymania,∗, Eric Grangera, Giorgio Fumerab +Laboratoire d’imagerie, de vision et d’intelligence artificielle, ´Ecole de technologie sup´erieure +Pattern Recognition and Applications Group, Dept. of Electrical and Electronic Engineering +Universit´e du Qu´ebec, Montreal, Canada +University of Cagliari, Cagliari, Italy"
3a804cbf004f6d4e0b041873290ac8e07082b61f,A Corpus-Guided Framework for Robotic Visual Perception,"Language-Action Tools for Cognitive Artificial Agents: Papers from the 2011 AAAI Workshop (WS-11-14) A Corpus-Guided Framework for Robotic Visual Perception Ching L. Teo, Yezhou Yang, Hal Daum´e III, Cornelia Ferm¨uller, Yiannis Aloimonos @@ -10106,6 +34723,49 @@ Margaret Mitchell · Kota Yamaguchi · Karl Stratos · Amit Goyal · Jesse Dodge · Alyssa Mensch · Hal Daum´e III · Alexander C. Berg · Yejin Choi · Tamara L. Berg Received: date / Accepted: date"
+3a165f7e22f0667b401cba1b2615048193781b4c,Patch-based Object Recognition,"Diplomarbeit im Fach Informatik +Rheinisch-Westf¨alische Technische Hochschule Aachen +Lehrstuhl f¨ur Informatik 6 +Prof. Dr.-Ing. H. Ney +Patch-Based Object Recognition +vorgelegt von: +Andre Hegerath +Matrikelnummer 228760 +Gutachter: +Prof. Dr.-Ing. H. Ney +Prof. Dr. T. Seidl +Betreuer: +Dipl.-Inform. T. Deselaers"
+3abb51739b90c8bfd665e045b0eeadc87e065b63,Intrinsic 3D Dynamic Surface Tracking based on Dynamic Ricci Flow and Teichmüller Map,"Intrinsic 3D Dynamic Surface Tracking based on Dynamic Ricci Flow and +Teichm ¨uller Map +Xiaokang Yu +Dept of Comp Sci +Qingdao Univ +Na Lei +Dept of Soft and Tech +Dalian Univ of Tech +Qingdao, PR China +Dalian,PR China +Yalin Wang +Comp.Sci.& Engin +Arizona State Univ +Arizona, USA +Xianfeng Gu +Dept of Comp Sci +Stony Brook Univ +Stony Brook, USA"
+3ab13f3ee6d66186c33766ac115d57f8b381468f,Stream Clustering with Dynamic Estimation of Emerging Local Densities,"Stream Clustering with Dynamic Estimation of +Emerging Local Densities +Ziyin Wang +Gavriil Tsechpenakis +Department of Computer and Information Science +Indiana University-Purdue University Indianapolis +Department of Computer and Information Science +Indiana University-Purdue University Indianapolis +Indianapolis, IN 46202, USA +Email: +Indianapolis, IN 46202, USA +Email:"
3acb6b3e3f09f528c88d5dd765fee6131de931ea,Novel representation for driver emotion recognition in motor vehicle videos,"(cid:49)(cid:50)(cid:57)(cid:40)(cid:47)(cid:3)(cid:53)(cid:40)(cid:51)(cid:53)(cid:40)(cid:54)(cid:40)(cid:49)(cid:55)(cid:36)(cid:55)(cid:44)(cid:50)(cid:49)(cid:3)(cid:41)(cid:50)(cid:53)(cid:3)(cid:39)(cid:53)(cid:44)(cid:57)(cid:40)(cid:53)(cid:3)(cid:40)(cid:48)(cid:50)(cid:55)(cid:44)(cid:50)(cid:49)(cid:3)(cid:53)(cid:40)(cid:38)(cid:50)(cid:42)(cid:49)(cid:44)(cid:55)(cid:44)(cid:50)(cid:49)(cid:3)(cid:3) (cid:44)(cid:49)(cid:3)(cid:48)(cid:50)(cid:55)(cid:50)(cid:53)(cid:3)(cid:57)(cid:40)(cid:43)(cid:44)(cid:38)(cid:47)(cid:40)(cid:3)(cid:57)(cid:44)(cid:39)(cid:40)(cid:50)(cid:54)(cid:3) (cid:53)(cid:68)(cid:77)(cid:78)(cid:88)(cid:80)(cid:68)(cid:85)(cid:3)(cid:55)(cid:75)(cid:72)(cid:68)(cid:74)(cid:68)(cid:85)(cid:68)(cid:77)(cid:68)(cid:81)(cid:13)(cid:15)(cid:3)(cid:37)(cid:76)(cid:85)(cid:3)(cid:37)(cid:75)(cid:68)(cid:81)(cid:88)(cid:13)(cid:15)(cid:3)(cid:36)(cid:79)(cid:69)(cid:72)(cid:85)(cid:87)(cid:3)(cid:38)(cid:85)(cid:88)(cid:93)(cid:130)(cid:15)(cid:3)(cid:37)(cid:72)(cid:79)(cid:76)(cid:81)(cid:71)(cid:68)(cid:3)(cid:47)(cid:72)(cid:13)(cid:15)(cid:3)(cid:36)(cid:86)(cid:82)(cid:81)(cid:74)(cid:88)(cid:3)(cid:55)(cid:68)(cid:80)(cid:69)(cid:82)(cid:13)(cid:3) @@ -10126,11 +34786,46 @@ patterns. The emotion recognition system incorporated face detection and registration followed by the proposed feature representation: Local Anisotropic Inhibited Binary Patterns in Three Orthogonal"
+3a13c964cc7adc5f010164ccb91d150457685a78,LIMO: Lidar-Monocular Visual Odometry,"LIMO: Lidar-Monocular Visual Odometry +Johannes Graeter1, Alexander Wilczynski1 and Martin Lauer1"
+3aee6a6285869e6db48ad269eb110b542ad23c93,One-Click Annotation with Guided Hierarchical Object Detection,"One - Click Annotation with Guided Hierarchical Object Detection +Adithya Subramanian, Anbumani Subramanian +Intel +Bangalore, India"
+3ac09c2589178dac0b6a2ea2edf04b7629672d81,Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2017 +Wasserstein CNN: Learning Invariant Features +for NIR-VIS Face Recognition +Ran He, Senior Member, IEEE, Xiang Wu, Zhenan Sun∗, Member, IEEE, and Tieniu Tan, Fellow, IEEE"
+3a772ed83fdc90e10def9d38f59153aee49cd47b,A Camera Network Tracking (CamNeT) Dataset and Performance Baseline,"A Camera Network Tracking (CamNeT) Dataset and Performance Baseline +Shu Zhang1, Elliot Staudt1, Tim Faltemier2, and Amit K. Roy-Chowdhury1 +Department of Electrical and Computer Engineering, University of California, Riverside +Progeny Systems Corporation"
+3a35154f765dcba4e3789a38346bf54bce69e336,Object Hallucination in Image Captioning,"Object Hallucination in Image Captioning +Anna Rohrbach∗1, Lisa Anne Hendricks∗1, +Kaylee Burns1 , Trevor Darrell1, Kate Saenko2 +UC Berkeley, 2 Boston University"
3a60678ad2b862fa7c27b11f04c93c010cc6c430,A Multimodal Database for Affect Recognition and Implicit Tagging,"JANUARY-MARCH 2012 A Multimodal Database for Affect Recognition and Implicit Tagging Mohammad Soleymani, Member, IEEE, Jeroen Lichtenauer, Thierry Pun, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+3a37f57a9b94fff82ffea4e77803ebe5ebf6401b,ER7ST-algorithm for extracting facial expressions,"068 The International Arab Journal of Information Technology Vol. 13, No. 6B, 2016 +ER7ST-Algorithm for Extracting Facial Expressions +Ahmad Tayyar1, Shadi Al-Shehabi2, and Majida AlBakoor3 +Department of Computer Science, Jerash University, Jordan +Department of C omputer Engineeringm, Türk Hava Kurumu Üniversitesi, Turkey +Department of Mathematics, Aleppo University, Syria"
+3acdccd33e518f22dcfe36ee29c332a644afdb25,Automatic Detection of Facial Midline And Its Contributions To Facial Feature Extraction,"Electronic Letters on Computer Vision and Image Analysis 6(3):55-66, 2008 +Automatic Detection of Facial Midline +And Its Contributions To Facial Feature Extraction +Nozomi NAKAO, Wataru OHYAMA, Tetsushi WAKABAYASHI and Fumitaka KIMURA +Graduate School of Engineering, Mie University, 1577 Kurimamachiya–cho, Tsu–shi, Mie 514–8507, Japan +Received 17 April 2007; revised 17 June 2007; accepted 17 September 2007"
+3a92a00b41dc6217f7685148c8a378524fa1a542,Human Pose Estimation Using Exemplars and Part Based Refinement,"Human Pose Estimation +Using Exemplars and Part Based Refinement +Yanchao Su1, Haizhou Ai1, Takayoshi Yamashita2, and Shihong Lao2 +Computer Science and Technology Department, Tsinghua, Beijing 100084, China +Core Technology Center, Omron Corporation, Kyoto 619-0283, Japan"
3a591a9b5c6d4c62963d7374d58c1ae79e3a4039,Driver Cell Phone Usage Detection from HOV/HOT NIR Images,"Driver Cell Phone Usage Detection From HOV/HOT NIR Images Yusuf Artan, Orhan Bulan, Robert P. Loce, and Peter Paul Xerox Research Center Webster @@ -10141,6 +34836,14 @@ Master of Science in Computer Science and Information Systems"
3a0a839012575ba455f2b84c2d043a35133285f9,Corpus-Guided Sentence Generation of Natural Images,"Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 444–454, Edinburgh, Scotland, UK, July 27–31, 2011. c(cid:13)2011 Association for Computational Linguistics"
+3a192e0391c357124cd2ec2287b1706f523ecdfd,An Introduction to the 3rd Workshop on Egocentric (First-Person) Vision,"An Introduction to the 3rd Workshop on Egocentric (First-person) Vision +Steve Mann, Kris M. Kitani, Yong Jae Lee, M. S. Ryoo, Alireza Fathi"
+3aa98c08043558fec09bbf731cd7a8f09cf4eacf,Projective Nonnegative Matrix Factorization with α-Divergence,"Projective Nonnegative Matrix Factorization +with α-Divergence +Zhirong Yang and Erkki Oja +Department of Information and Computer Science(cid:2) +P.O. Box 5400, FI-02015, TKK, Espoo, Finland +Helsinki University of Technology"
3a9681e2e07be7b40b59c32a49a6ff4c40c962a2,"Comparing treatment means : overlapping standard errors , overlapping confidence intervals , and tests of hypothesis","Biometrics & Biostatistics International Journal Comparing treatment means: overlapping standard errors, overlapping confidence intervals, and tests of @@ -10158,9 +34861,97 @@ Pre-print of article that appeared at the IEEE Computer Society Workshop on Biom 010. The published article can be accessed from: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5544597"
+3af0a26ef9a4084703b310eb997ca630d0bae237,Automatic conversion of monoscopic image / video to stereo for 3 D visualization,"________________________________________________________________________________________________ +International Journal of Recent Advances in Engineering & Technology (IJRAET) +Automatic conversion of monoscopic image/ video to stereo for 3D +visualization +R.C.Gokul Nanda Kumar, 2Vijaykumar T +4th sem, M.Tech (Digital Electronics), SJBIT, Bangalore +Assoc Prof, Dept. of ECE, SJBIT, Bangalore +Email: +into a"
+3aa66f2829ef440842c71a52cdaff30398a90ccb,Pointly-Supervised Action Localization,"International Journal of Computer Vision manuscript No. +(will be inserted by the editor) +Pointly-Supervised Action Localization +Pascal Mettes · Cees G. M. Snoek +Received: date / Accepted: date"
+3a0673199699cd51abe0f104ebe080f63d1b6d37,Sparse shape registration for occluded facial feature localization,"Sparse Shape Registration for Occluded Facial Feature Localization +Fei Yang, Junzhou Huang and Dimitris Metaxas"
3a95eea0543cf05670e9ae28092a114e3dc3ab5c,Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering,"Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering Xi Peng, Zhiding Yu, Huajin Tang, Member, IEEE, and Zhang Yi, Senior Member, IEEE"
+3af0400c011700f3958062edfdfed001e592391c,The Intense World Theory – A Unifying Theory of the Neurobiology of Autism,"HUMAN NEUROSCIENCE +The Intense World Theory – a unifying theory of the +neurobiology of autism +Review ARticle +published: 21 December 2010 +doi: 10.3389/fnhum.2010.00224 +Kamila Markram +* and +Henry Markram +Laboratory of Neural Microcircuits, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland +Edited by: +Silvia A. Bunge, University of California +Berkeley, USA +Reviewed by: +Matthew K. Belmonte, Cornell +University, USA; University of +Cambridge, UK +Egidio D’Angelo, University of Pavia, +Italy +*Correspondence:"
+3a24c276368fa63473078723ce4bc99c9ea36019,Stability comparison of dimensionality reduction techniques attending to data and parameter variations,"Eurographics Conference on Visualization (EuroVis) (2013) +M. Hlawitschka and T. Weinkauf (Editors) +Short Papers +Stability comparison of dimensionality reduction techniques +ttending to data and parameter variations +Francisco J. García-Fernández1,2, Michel Verleysen2, John A. Lee2 and Ignacio Díaz1 +University of Oviedo, Spain +Université Catholique de Louvain, Belgium"
+3a0cceb1a10697e3e17738579d27708c9c3303a8,Data-Intensive Multimedia Semantic Concept Modeling using Robust Subspace Bagging and MapReduce,"Data-Intensive Multimedia Semantic Concept Modeling +using Robust Subspace Bagging and MapReduce"
+3af28e9e9e883c235b6418a68bda519b08f9ae26,Implications of Adult Facial Aging on Biometrics,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+3a28fe49e7a856ddd60d134696a891ed7bca5962,Small-scale Pedestrian Detection Based on Somatic Topology Localization and Temporal Feature Aggregation,"Small-scale Pedestrian Detection Based on +Somatic Topology Localization and Temporal +Feature Aggregation +Tao Song, Leiyu Sun, Di Xie, Haiming Sun, Shiliang Pu +Hikvision Research Institute"
+3affe6f9c2244f4b32c1c0f7d7f1d24770d40efe,Evaluating the Resilience of Face Recognition Systems against Malicious Attacks,"OMAR L., IVRISSIMTZIS I.: RESILIENCE OF FACE RECOGNITION SYSTEMS +Evaluating the Resilience of Face +Recognition Systems against Malicious +Attacks +Luma Omar1 +Ioannis Ivrissimtzis1 +School of Engineering and +Computing Sciences +Durham University +Durham, UK"
+3ab7f06cf8e7e7ca34427f81b766b823647ac117,Explaining Eye Movements During Learning as an Active Sampling Process,"Proceedings of the 2004 International +Conference on Development and Learning +Editors: Jochen Triesch and Tony Jebara +Publisher: UCSD Institute for Neural Computation +Location: The Salk Institute for Biological Studies +La Jolla California, USA +ISBN: 0-615-12704-5"
3a4f522fa9d2c37aeaed232b39fcbe1b64495134,Face Recognition and Retrieval Using Cross-Age Reference Coding With Cross-Age Celebrity Dataset,"ISSN (Online) 2321 – 2004 ISSN (Print) 2321 – 5526 INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN ELECTRICAL, ELECTRONICS, INSTRUMENTATION AND CONTROL ENGINEERING @@ -10171,6 +34962,29 @@ Age Reference Coding Sricharan H S1, Srinidhi K S1, Rajath D N1, Tejas J N1, Chandrakala B M2 BE, DSCE, Bangalore1 Assistant Professor, DSCE, Bangalore2"
+54509dbe70cd3015007bbd5fa1fd8793b388319e,Fast Pedestrian Detection by Cascaded Random Forest with Dominant Orientation Templates,"TANG ET AL.: FAST PEDESTRIAN DETECTION BY RANDOM FORESTS WITH DOT +Fast Pedestrian Detection by Cascaded +Random Forest with Dominant Orientation +Templates +Danhang Tang +http://www.iis.ee.ic.ac.uk/~dtang +Yang Liu +http://www.iis.ee.ic.ac.uk/~yliu +Tae-Kyun Kim +http://www.iis.ee.ic.ac.uk/~tkkim +Department of Electrical Engineering, +Imperial College, +London, UK"
+548f94f82bf28efa299a64c2527aad36d76b81af,Adaptive Kernels for Texture Based Analysis of Object Based Classification of Forest Stands,"Adaptive Kernels for Texture Based +Analysis of Object Based Classification +of Forest Stands +Ziab Khan +A thesis submitted in partial fulfilment for the +degree of Master of Philosophy +in the +Department of Geography +University of Leicester +August 26, 2014"
540b39ba1b8ef06293ed793f130e0483e777e278,Biologically Inspired Emotional Expressions for Artificial Agents,"ORIGINAL RESEARCH published: 13 July 2018 doi: 10.3389/fpsyg.2018.01191 @@ -10186,6 +35000,49 @@ nd Media Informatics, Budapest University of Technology and Economics, Budapest, A special area of human-machine interaction, the expression of emotions gains importance with the continuous development of artificial agents such as social robots or"
+54ed052738ca0f4570c74931857b3275fca9993b,Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation,"Knowledge-Guided Deep Fractal Neural Networks +for Human Pose Estimation +Guanghan Ning, Student Member, IEEE, Zhi Zhang, Student Member, IEEE, and Zhihai He, Fellow, IEEE"
+54bb3a17d536c7b88e56d294464f3d54de2ea9b3,Video surveillance online repository (ViSOR): www.openvisor.org,"Video Surveillance Online Repository (ViSOR) +www.openvisor.org +Roberto Vezzani, Rita Cucchiara +Dipartimento di Ingegneria “Enzo Ferrari” +University of Modena and Reggio Emilia, Italy"
+544829d3b2e878c8f28fae5aa0c226e65ba6242a,Human Body Segmentation with Multi-limb Error-Correcting Output Codes Detection and Graph Cuts Optimization,"Human Pose Recovery and Behavior Analysis Group +Human Body Segmentation with +Multi-limb Error-Correcting Output +Codes Detection and Graph Cuts +Optimization +Daniel Sánchez, Juan Carlos Ortega, +Miguel Ángel Bautista & Sergio Escalera +All rights reserved HuBPA©"
+54d78ad2ed30557474fabd1d3a9e5db1c76fbeaa,Deep Person Re-identification for Probabilistic Data Association in Multiple Pedestrian Tracking,"Deep Person Re-identification for Probabilistic Data Association in +Multiple Pedestrian Tracking +Brian H. Wang1, Yan Wang2, Kilian Q. Weinberger2, and Mark Campbell1"
+54983972aafc8e149259d913524581357b0f91c3,ReSEED: social event dEtection dataset,"ReSEED: Social Event dEtection Dataset +Timo Reuter +Universität Bielefeld, CITEC +Bielefeld, Germany +ielefeld.de +Symeon Papadopoulos +CERTH-ITI +Thermi, Greece +Vasilios Mezaris +CERTH-ITI +Thermi, Greece +Philipp Cimiano +Universität Bielefeld, CITEC +Bielefeld, Germany +ielefeld.de"
+541c68e2c65f6dce6179801c9f92dc7803dc71b5,Unsupervised and Transfer Learning under Uncertainty - From Object Detections to Scene Categorization,"Unsupervised and Transfer Learning under Uncertainty: +from Object Detections to Scene Categorization +Gr´egoire Mesnil1,2, Salah Rifai1, Antoine Bordes3, +Xavier Glorot1, Yoshua Bengio1 and Pascal Vincent1 +LISA, Universit´e de Montr´eal, Qu´ebec, Canada +LITIS, Universit´e de Rouen, France +CNRS - Heudiasyc UMR 7253, Universit´e de Technologie de Compi`egne, France +Keywords: +Unsupervised Learning, Transfer Learning, Deep Learning, Scene Categorization, Object Detection"
543f21d81bbea89f901dfcc01f4e332a9af6682d,Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks,"Published as a conference paper at ICLR 2016 UNSUPERVISED AND SEMI-SUPERVISED LEARNING WITH CATEGORICAL GENERATIVE ADVERSARIAL @@ -10193,6 +35050,11 @@ NETWORKS Jost Tobias Springenberg University of Freiburg 79110 Freiburg, Germany"
+54c5e9cded7da1f9dc695f5397d9d1a5ac5350af,Person Re-identification Based on Color Histogram and Spatial Configuration of Dominant Color Regions,"Person Re-identification Based on Color Histogram and Spatial +Configuration of Dominant Color Regions +Kwangchol Jang, Sokmin Han, Insong Kim +College of Computer Science, KIM IL SUNG University, Pyongyang, D.P.R of Korea +illumination, pose and viewpoint, camera parameters. Being related"
54969bcd728b0f2d3285866c86ef0b4797c2a74d,Learning for Video Compression,"IEEE TRANSACTION SUBMISSION Learning for Video Compression Zhibo Chen, Senior Member, IEEE, Tianyu He, Xin Jin, Feng Wu, Fellow, IEEE"
@@ -10203,12 +35065,108 @@ Computer Vision and Active Perception, KTH, Stockholm 10800, Sweden {kobetski, Keywords: Boosting, Image Classification, Algorithm Evaluation, Dataset Pruning, VOC2007."
+543c601f8ebc0995040f4b8de4a339fd4c860cbb,Eye localization: a survey,"Eye localization: a survey +Paola CAMPADELLI, Raffaella LANZAROTTI, Giuseppe LIPORI 1 +Dipartimento di Scienze dell’Informazione. +Università degli Studi di Milano. +Via Comelico, 39/41 - 20135 Milano (Italy)"
+5432392d916e730c53962be202c115133e6d7777,Face processing in a case of high functioning autism with developmental prosopagnosia.,"RESEARCH PAPER +Acta Neurobiol Exp 2018, 78: 114–131 +DOI: 10.21307/ane‑2018‑011 +Face processing in a case of high functioning autism +with developmental prosopagnosia +Hanna B. Cygan1,3*, Hanna Okuniewska2, Katarzyna Jednoróg3, Artur Marchewka4, +Marek Wypych4 and Anna Nowicka3 +Laboratory of Social Psychology, Department of Ergonomics, Central Institute for Labour Protection, National Research Institute, +Warsaw, Poland, 2 Faculty of Psychology, University of Warsaw, Warsaw, Poland, 3 Laboratory of Psychophysiology, Department of +Neurophysiology, Nencki Institute of Experimental Biology, Polish Academy of Science, Warsaw, Poland, 4 Laboratory of Brain Imaging, +Neurobiology Center, Nencki Institute of Experimental Biology, Polish Academy of Science, Warsaw, Poland, +* Email: +The ability to “read” the information about facial identity, expressed emotions, and intentions is crucial for non‑verbal social interaction. +Neuroimaging and clinical studies consequently link face perception with fusiform gyrus (FG) and occipital face area (OFA) activity. Here +we investigated face processing in an adult, patient PK, diagnosed with both high functioning autism spectrum disorder (ASD) and +developmental prosopagnosia (DP). Both disorders have a significant impact on face perception and recognition, thus creating a unique +neurodevelopmental condition. We used eye‑tracking and functional magnetic resonance imaging (fMRI) method. Eye‑tracking and fMRI +results of PK were compared to results of control subjects. Patient PK showed atypical gaze‑fixation strategy during face perception and +typical patterns of brain activations in the FG and OFA. However, a significant difference between PK and control subjects was found in +the left anterior superior temporal sulcus/middle temporal gyrus (aSTS/MTG). In PK the left aSTS/MTG was hypo‑activated in comparison"
+5479da1038a530beb760a38dbb5b08947dfaefbd,Fusing continuous spectral images for face recognition under indoor and outdoor illuminants,"DOI 10.1007/s00138-008-0151-1 +ORIGINAL PAPER +Fusing continuous spectral images for face recognition +under indoor and outdoor illuminants +H. Chang · A. Koschan · B. Abidi · M. Abidi +Received: 4 December 2007 / Accepted: 14 May 2008 / Published online: 17 June 2008 +© Springer-Verlag 2008 +image fusion approaches,"
54aacc196ffe49b3450059fccdf7cd3bb6f6f3c3,A joint learning framework for attribute models and object descriptions,"A Joint Learning Framework for Attribute Models and Object Descriptions Dhruv Mahajan Yahoo! Labs, Bangalore, India Sundararajan Sellamanickam Vinod Nair"
+5478a70badcf4d6da383d86163f0acc2c28b6bd3,Enhancing pedestrian detection using optical flow for surveillance,"Int. J. Computational Vision and Robotics, Vol. 7, Nos. 1/2, 2017 +Enhancing pedestrian detection using optical flow for +surveillance +Redwan A.K. Noaman*, +Mohd Alauddin Mohd Ali and +Nasharuddin Zainal +Department of Electrical, Electronic and Systems Engineering, +Faculty of Engineering and Built Environment, +Universiti Kebangsaan Malaysia, +3600 Bandar Baru Bangi, Selangor, Malaysia +Email: +Email: +Email: +*Corresponding author"
+5454c5900b6b6a0cf36df65d667129fcbd5262dc,Benchmarking asymmetric 3D-2D face recognition systems,"Benchmarking Asymmetric 3D-2D Face Recognition Systems +Xi Zhao, Wuming Zhang, Georgios Evangelopoulos, Di Huang, Shishir K. Shah, Yunhong Wang, +Ioannis A. Kakadiaris and Liming Chen"
541bccf19086755f8b5f57fd15177dc49e77d675,A few days of a robot's life in the human's world: toward incremental individual recognition,"Computer Science and ArtificialIntelligence LaboratoryTechnical Reportmassachusetts institute of technology, cambridge, ma 02139 usa — www.csail.mit.eduMIT-CSAIL-TR-2007-022April 3, 2007A Few Days of A Robot’s Life in the Human’s World: Toward Incremental Individual RecognitionLijin Aryananda"
+54f0fa07dee7bd270d3bd8da9011ca90df78af59,Comparison of Laser-Based Person Tracking at Feet and Upper-Body Height,"Comparison of Laser-based Person Tracking at +Feet and Upper-Body Height +Konrad Schenk, Markus Eisenbach, +Alexander Kolarow, and Horst-Michael Gross (cid:63) +Neuroinformatics and Cognitive Robotics +Ilmenau University of Technologies"
+542289d1acfebb9d79ea7a10c8e1516924e09973,Video Highlight Prediction Using Audience Chat Reactions,"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 972–978 +Copenhagen, Denmark, September 7–11, 2017. c(cid:13)2017 Association for Computational Linguistics"
+54dae5187de3898d8034719bcaa3e0100ae72d76,Probabilistic Attributed Hashing,"Probabilistic Attributed Hashing +Mingdong Ou1, Peng Cui1, Jun Wang2, Fei Wang3, Wenwu Zhu1 +Tsinghua National Laboratory for Information Science and Technology +Department of Computer Science and Technology, Tsinghua University. Beijing, China +Department of Computer Science and Engineering, University of Connecticut. Storrs, CT. USA. +Data Science, Alibaba Group, Seattle, WA, USA."
+5458ccf22bdea7197e28b433ef06d5225fb030a7,Video Description Using Bidirectional Recurrent Neural Networks,"Video Description using Bidirectional Recurrent +Neural Networks +´Alvaro Peris1, Marc Bola˜nos2,3, Petia Radeva2,3, and Francisco Casacuberta1 +PRHLT Research Center, Universitat Polit`ecnica de Val`encia, Valencia (Spain) +Universitat de Barcelona, Barcelona (Spain) +Computer Vision Center, Bellaterra (Spain)"
+546cef6f86fb5a9fd59d40d9df63301c8a9d7d15,PathTrack: Fast Trajectory Annotation with Path Supervision,"PathTrack: Fast Trajectory Annotation with Path Supervision +Santiago Manen1 +Michael Gygli1 +Dengxin Dai1 +Luc Van Gool1,2 +Computer Vision Laboratory +ESAT - PSI / IBBT +{smanenfr, gygli, daid, +ETH Zurich +K.U. Leuven"
+54b309443f53ed960f588f64d6aefe53f87504b6,TVD: A Reproducible and Multiply Aligned TV Series Dataset,"TVD: a reproducible and multiply aligned TV series dataset +Anindya Roy1, Camille Guinaudeau1,2, Herv´e Bredin1, Claude Barras1,2 +Spoken Language Processing Group, CNRS-LIMSI, B.P. 133, Orsay, France. +Universit´e Paris Sud, Orsay, France. +{roy, guinaudeau, bredin,"
+541b13515480c0371bb8bb79cf17120645edccc7,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
54756f824befa3f0c2af404db0122f5b5bbf16e0,Computer Vision — Visual Recognition,"Research Statement Computer Vision — Visual Recognition Alexander C. Berg @@ -10241,6 +35199,32 @@ Xin Pan Google Brain Vincent Vanhoucke Google Brain"
+548bc4203770450c21133bfb72c58f5fae0fbdf2,Visual-Inertial-Semantic Scene Representation for 3D Object Detection,"Visual-Inertial-Semantic Scene Representation for 3D Object Detection +Jingming Dong∗ +Xiaohan Fei∗ +Stefano Soatto +UCLA Vision Lab, University of California, Los Angeles, CA 90095 +{dong, feixh,"
+987dd3dd6079e5fa8a10a1c53b2580fd71e27ede,Concept-Based Video Retrieval By Cees,"Foundations and Trends R(cid:1) in +Information Retrieval +Vol. 2, No. 4 (2008) 215–322 +(cid:1) 2009 C. G. M. Snoek and M. Worring +DOI: 10.1561/1500000014 +Concept-Based Video Retrieval +By Cees G. M. Snoek and Marcel Worring +Contents +Introduction +How to Retrieve Video Content? +Human-Driven Labeling +.3 Machine-Driven Labeling +Aims, Scope, and Organization +Detecting Semantic Concepts in Video +Introduction +Basic Concept Detection +Feature Fusion +Classifier Fusion +.5 Modeling Relations +Best of Selection"
9853136dbd7d5f6a9c57dc66060cab44a86cd662,"Improving the Neural Network Training for Face Recognition using Adaptive Learning Rate , Resilient Back Propagation and Conjugate Gradient Algorithm","International Journal of Computer Applications (0975 – 8887) Volume 34– No.2, November 2011 Improving the Neural Network Training for Face @@ -10261,16 +35245,136 @@ of Surrey, UK Karim Mohammadi Professor Department of Electrical"
+98f1613889657963b102460e4e970fe421c6ed3c,Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks,"Accurate and Robust Neural Networks for +Security Related Applications Exampled by Face +Morphing Attacks +Clemens Seibold1, Wojciech Samek1, Anna Hilsmann1 and Peter Eisert1,2 +Fraunhofer HHI, Einsteinufer 37, 10587 Berlin, Germany +Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany"
+98a6f2145a358cb2e54eddc99dd29911764bce0e,Learning Single-view 3D Reconstruction of Objects and Scenes,"Learning Single-view 3D Reconstruction of Objects and +Scenes +Shubham Tulsiani +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2018-93 +http://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-93.html +July 26, 2018"
+986224bad9684c359db7fac2192b7134b855fbe3,Shopping for emotion,"Shopping for emotion +Evaluating the usefulness of emotion recognition data from a retail perspective +Anton Forsberg +Anton Forsberg +VT 2017 +Examensarbete f¨or civilingenj¨orer, 30hp +Supervisor: Lars-Erik Janlert +Examiner: Anders Broberg +Civilingenj¨orsprogammet i Interaktion & Design"
+987c9a137d638f3d561c52b6dd0f987734ad5460,Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation,"Efficient Dense Modules of Asymmetric Convolution for +Real-Time Semantic Segmentation +Shao-Yuan Lo1 Hsueh-Ming Hang1 Sheng-Wei Chan2 Jing-Jhih Lin2 +National Chiao Tung University 2 Industrial Technology Research Institute +{ShengWeiChan,"
988d1295ec32ce41d06e7cf928f14a3ee079a11e,Semantic Deep Learning,"Semantic Deep Learning Hao Wang September 29, 2015"
+98c7a6210ca7bc81d2f7092ab28451f47039e920,UC Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title What is the Ground ?,"UC Merced +Proceedings of the Annual Meeting of the Cognitive Science +Society +Title +What is the Ground? Continuous Maps for Symbol Grounding +Permalink +https://escholarship.org/uc/item/9p5236j4 +Journal +Proceedings of the Annual Meeting of the Cognitive Science Society, 36(36) +Authors +Perera, Ian +Allen, James +Publication Date +014-01-01 +Peer reviewed +eScholarship.org +Powered by the California Digital Library +University of California"
98c548a4be0d3b62971e75259d7514feab14f884,Deep generative-contrastive networks for facial expression recognition,"Deep generative-contrastive networks for facial expression recognition Youngsung Kim†, ByungIn Yoo‡,†, Youngjun Kwak†, Changkyu Choi†, and Junmo Kim‡ Samsung Advanced Institute of Technology (SAIT), ‡KAIST hangkyu"
+98b98a8413f21a48ee6effd52da8c31ece6a910d,Detecting handwritten signatures in scanned documents,"9th Computer Vision Winter Workshop +Zuzana Kúkelová and Jan Heller (eds.) +Křtiny, Czech Republic, February 3–5, 2014 +Detecting handwritten signatures in scanned documents +İlkhan Cüceloğlu1,2, Hasan Oğul1 +Department of Computer Engineering, Başkent University, Ankara, Turkey +DAS Document Archiving and Management Systems CO., Ankara, Turkey"
+98142e84a3cee08661b31371a2c610183df82c8f,Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees,"Tight Bounds for the Expected Risk of Linear Classifiers and +PAC-Bayes Finite-Sample Guarantees +Jean Honorio +CSAIL, MIT +Cambridge, MA 02139, USA"
981449cdd5b820268c0876477419cba50d5d1316,Learning Deep Features for One-Class Classification,"Learning Deep Features for One-Class Classification Pramuditha Perera, Student Member, IEEE, and Vishal M. Patel, Senior Member , IEEE"
+98960be5ae51d30118f091f7091299a49f2f34bb,Global and Feature Based Gender Classification of Faces: a Comparison of Human Performance and Computational Models,"GLOBAL AND FEATURE BASED GENDER CLASSIFICATION +OF FACES: A COMPARISON OF HUMAN PERFORMANCE +AND COMPUTATIONAL MODELS +SAMARASENA BUCHALAA TIM M.GALEA,B NEIL DAVEYA RAY J.FRANKA +KERRY FOLEYB +A Department of Computer Science, University of Hertfordshire, College Lane, Hatfield, +{S.Buchala, N.Davey, T.Gale, +AL10 9AB, UK +B Department of Psychiatry, QEII Hospital, Welwyn Garden City, AL7 4HQ, UK +Most computational models for gender classification use global information (the full face +image) giving equal weight to the whole face area irrespective of the importance of the +internal features. Here, we use a global and feature based representation of face images +that includes both global and featural information. We use dimensionality reduction +techniques and a support vector machine classifier and show that this method performs +etter than either global or feature based representations alone. +. Introduction +Most computational models of gender classification use whole face images, +giving equal weight to all areas of the face, irrespective of the importance of +internal facial features. In this paper we evaluate the importance of global and +local information in a series of gender recognition experiments. Global"
+98c5b88db35d7ab2d3cc0a63c7ff1414160d2aa6,Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors,"Article +Convolutional Neural Network-Based Finger-Vein +Recognition Using NIR Image Sensors +Hyung Gil Hong, Min Beom Lee and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (H.G.H); (M.B.L.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Academic Editor: Vittorio M. N. Passaro +Received: 11 May 2017; Accepted: 1 June 2017; Published: 6 June 2017"
+98424c79970a80f30db837db84880a4c02e76f1a,Deepagent: An Algorithm Integration Approach for Person Re-Identification,"DEEPAGENT: AN ALGORITHM INTEGRATION APPROACH FOR PERSON +RE-IDENTIFICATION +Fulong Jiao, Bir Bhanu +Center for Research in Intelligent Systems +University of California, Riverside, Riverside, CA 92521, USA"
+98f13ab2845cfe8513a0c05427a8b90d9c0c1b69,Pedestrian Attribute Recognition with Part-based CNN and Combined Feature Representations,
+98220d35ae6a3ba745f7dea1434f000ca60c62c0,Multi-object Tracking using Particle Swarm Optimization on Target Interactions,"Multi-object Tracking using Particle Swarm +Optimization on Target Interactions +Bogdan Kwolek"
+984d5ed1fa80124117fdd0aa9a5be69f269da268,[insert Cover Letter Here],[Insert cover letter here]
+988d5ad8d114f5f21a73b2ae464dca4277f5725f,Persian Viseme Classification Using Interlaced Derivative Patterns and Support Vector Machine,"Journal of Information Assurance and Security. +ISSN 1554-1010 Volume 9 (2014) pp. 148-156 +© MIR Labs, www.mirlabs.net/jias/index.html +Persian Viseme Classification Using Interlaced +Derivative Patterns and Support Vector Machine +Mohammad Mahdi Dehshibi1, Jamshid Shanbehzadeh2 +Digital Signal Processing Lab., Pattern Research Center, +Karaj, Iran +Department of Computer Engineering, Kharazmi University, +Tehran, Iran +is a"
+986be05b286d99d840583578c102af31c56428fd,An Efficient Algorithm for Implementing Traffic Sign Detection on Low Cost Embedded System,"International Journal of Innovative +Computing, Information and Control +Volume 14, Number 1, February 2018 +ICIC International c(cid:13)2018 ISSN 1349-4198 +pp. 1–14 +AN EFFICIENT ALGORITHM FOR IMPLEMENTING TRAFFIC SIGN +DETECTION ON LOW COST EMBEDDED SYSTEM +Aryuanto Soetedjo and I Komang Somawirata +Department of Electrical Engineering +National Institute of Technology +Jalan Raya Karanglo KM 2 Malang 65153, Indonesia +Received May 2017; revised September 2017"
9854145f2f64d52aac23c0301f4bb6657e32e562,An Improved Face Verification Approach Based on Speedup Robust Features and Pairwise Matching,"An Improved Face Verification Approach based on Speedup Robust Features and Pairwise Matching Eduardo Santiago Moura, Herman Martins Gomes and Jo˜ao Marques de Carvalho @@ -10278,6 +35382,10 @@ Center for Electrical Engineering and Informatics (CEEI) Federal University of Campina Grande (UFCG) Campina Grande, Para´ıba, Brazil Email:"
+983534325c649e391fefe87025337187021b9830,Towards Automatic Generation of Question Answer Pairs from Images,"Towards Automatic Generation of Question Answer Pairs from Images +Issey Masuda Mora, Santiago Pascual de la Puente, Xavier Giro-i-Nieto +Universitat Politecnica de Catalunya (UPC) +Barcelona, Catalonia/Spain"
98127346920bdce9773aba6a2ffc8590b9558a4a,Efficient human action recognition using histograms of motion gradients and VLAD with descriptor shape information,"Noname manuscript No. (will be inserted by the editor) Efficient Human Action Recognition using @@ -10287,6 +35395,27 @@ Ionut C. Duta · Jasper R.R. Uijlings · Bogdan Ionescu · Kiyoharu Aizawa · Alexander G. Hauptmann · Nicu Sebe Received: date / Accepted: date"
+98582edd6029c94844f5a40d246eaa86f74d8512,Learning Visual Scene Attributes,"Learning Visual Scene Attributes +Vazheh Moussavi +A Glance at Attribute-Centric Scene Representations +Take a look around you. How would you describe your surroundings to best give an idea of what +everything looks like to someone not there? Maybe you will give a category to the scene, say, +‘bedroom’. You might try to list some of the objects around you, like ‘bed’, ‘lamp’, and ‘desk’. Or +perhaps you’ll describe it with adjectives like ‘indoors’, ‘cozy’, and ‘cluttered’. In computer vision, +(or more specifically, in scene understanding), the most effective way to describe a visual scene is +lso a major question. +Of the these three ways of describing a scene, (commonly referred to as categorization, scene pars- +ing, and attribute-based representation respectively), categories have historically been the method of +hoice. In categorization, an image (scene) is allowed to fall into exactly one of an arbitrary number +of buckets. Attribute representations, however, are typically composed of several sets of buckets +each of which will have a value associated with that scene. For instance, a simple category-based +model would place an image in one of urban/rural/room, whereas a binary attribute-based model +would have as attributes indoors and warm, each of which are marked as either present or not. In +larger models, this leads to high dimensionality for attribute-based models, which has been a large +disincentive for its use. In addition, classifying a scene’s entire attribute set non-trivially falls un- +der multi-label learning, for which there exist very few learning algorithms in popular use. Lastly, +there is scene parsing[5], which involves using object detectors, possibly in conjunction, to build"
+9889596a98824bdf7e7c59b62e732c0b2d356c69,Soft Correspondences in Multimodal Scene Parsing,"Sarah Taghavi Namin, Mohammad Najafi, Mathieu Salzmann, and Lars Petersson"
98a660c15c821ea6d49a61c5061cd88e26c18c65,Face Databases for 2D and 3D Facial Recognition: A Survey,"IOSR Journal of Engineering (IOSRJEN) e-ISSN: 2250-3021, p-ISSN: 2278-8719 Vol. 3, Issue 4 (April. 2013), ||V1 || PP 43-48 @@ -10296,6 +35425,71 @@ Assistant Professor, Department of Electronics and Communication Engineering, I Professor and Dean , Department of Electronics and Communication Engineering, Odaiyappa College of Transport Technology,Erode-638 316. Engineering and Technology,Theni-625 531."
+9817e0d11701e9ce0e31a32338ff3ff0969621ed,Dppnet: Approximating Determinantal Point Processes with Deep Networks,"Under review as a conference paper at ICLR 2019 +DPPNET: APPROXIMATING DETERMINANTAL POINT +PROCESSES WITH DEEP NETWORKS +Anonymous authors +Paper under double-blind review"
+98126d18be648640fc3cfeb7ffc640a2ec1d5f6f,Supplemental Material: Discovering Groups of People in Images,"Supplemental Material: Discovering Groups of People in +Images +Wongun Choi1, Yu-Wei Chao2, Caroline Pantofaru3 and Silvio Savarese4 +. NEC Laboratories 2. University of Michigan, Ann Arbor +. Google, Inc +. Stanford University +Qualitative Examples +In Fig. 1 and 2, we show additional qualitative examples obtained using our model +with poselet [1] and ground truth (GT) detections, respectively. We show the image +onfiguration of groups on the left and corresponding 3D configuration on the right. +Different colors and different line types (solid or dashed) represent different groups, +the type of each structured group is overlayed on the bottom-left of one participant. In +D visualization, squares represent standing people, circles represent people sitting on +n object, and triangles represent people sitting on the ground. The view point of each +individual is shown with a line. The gray triangle is the camera position. The poses are +obtained by using the individual pose classification output for visualization purposes. +The figures show that our algorithm is capable of correctly associating individu- +ls into multiple different groups while estimating the type of each group. Notice that +our algorithm can successfully segment different instances of the same group type that +ppear in proximity. A distance-based clustering method would not be able to differ-"
+98a60b218ff8addaf213e97e2f4b54d39e45f5b9,Benchmarking Real World Object Recognition,"Bonn-Aachen International Center for Information Technology +Master of Science in Autonomous Systems +Bonn-Rhein-Sieg University of Applied Sciences +Date: March 4, 2005 +Student: Adolf, Florian-Michael +Matriculation-No: 9005989 +eMail: +Supervisor: Prassler, Erwin +Institution: UAS Bonn-Rhein-Sieg +eMail: +Benchmarking Real World Object Recognition +Summer Term 2005 +Master Thesis Proposal +Context +Service robotics basically comprise everything that is not industrial robotics, and reflects +the distinction between the manufacturing and service sectors of the economy. Hence +service robots are supposed to operate in our human world as autonomously as possible. +The perception of objects in video images suitable for everyday use (”real-world”) is one +of the key disciplines in developing this key technology. +Recent service robotic projects [16, 13, 19, 20, 2] demand research in machine vision and"
+984ecfbda7249e67eca8d9b1697e81f80e2e483d,Visual object categorization with new keypoint-based adaBoost features,"Visual object categorization with new keypoint-based +daBoost features +Taoufik Bdiri, Fabien Moutarde, Bruno Steux +To cite this version: +Taoufik Bdiri, Fabien Moutarde, Bruno Steux. Visual object categorization with new keypoint-based +daBoost features. IEEE Symposium on Intelligent Vehicles (IV’2009), Jun 2009, XiAn, China. 2009. +<hal-00422580> +HAL Id: hal-00422580 +https://hal.archives-ouvertes.fr/hal-00422580 +Submitted on 7 Oct 2009 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
98519f3f615e7900578bc064a8fb4e5f429f3689,Dictionary-Based Domain Adaptation Methods for the Re-identification of Faces,"Dictionary-based Domain Adaptation Methods for the Re-identification of Faces Qiang Qiu, Jie Ni, and Rama Chellappa"
@@ -10316,6 +35510,60 @@ Snehalata Patil M.Tech (CSE) VKIT, Bangalore- 560040 BANGALORE, INDIA"
+981847c0a3d667aae385276221834edbb8ebd11c,A generalizable approach for multi-view 3D human pose regression,"A generalizable approach for multi-view 3D human pose regression +Abdolrahim Kadkhodamohammadia,∗, Nicolas Padoya +ICube, University of Strasbourg, CNRS, IHU Strasbourg, France"
+982db27f0a092d5c8db88e959a77fae5b4f9cdf6,"A cross-cultural, multimodal, affective corpus for gesture expressivity analysis","J Multimodal User Interfaces +DOI 10.1007/s12193-012-0112-x +ORIGINAL PAPER +A cross-cultural, multimodal, affective corpus for gesture +expressivity analysis +G. Caridakis · J. Wagner · A. Raouzaiou · +F. Lingenfelser · K. Karpouzis · E. Andre +Received: 5 March 2012 / Accepted: 15 September 2012 +© OpenInterface Association 2012"
+53819049f41998a5a1587dfccccc2db8612b45af,Deep Semantic Lane Segmentation for Mapless Driving,"018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) +Madrid, Spain, October 1-5, 2018 +978-1-5386-8093-3/18/$31.00 ©2018 IEEE"
+53079196041fedeb5f1e236b1c76c7108fd8346e,"Multiple Object Detection, Tracking and Long-Term Dynamics Learning in Large 3D Maps","Multiple Object Detection, Tracking +nd Long-Term Dynamics Learning +in Large 3D Maps +Local +D Maps +Object +Posteriors +Learn +Dynamics +Location l1 +Location l3 +Object jump +probability: +pjump = 0.036 +Object spatial +process variance: +q = 0.137 +Measurement +ovariance: + 0.14 −0.03 0.02"
+5357bdaf7c54619016bdb7ebfa991a65a6cc8353,"Infants’ Temperament and Mothers’, and Fathers’ Depression Predict Infants’ Attention to Objects Paired with Emotional Faces","J Abnorm Child Psychol (2016) 44:975–990 +DOI 10.1007/s10802-015-0085-9 +Infants’ Temperament and Mothers’, and Fathers’ Depression +Predict Infants’ Attention to Objects Paired with Emotional Faces +Evin Aktar 1,2 & Dorothy J. Mandell 1 & Wieke de Vente 2 & Mirjana Majdandžić 2 & +Maartje E. J. Raijmakers 1,3 & Susan M. Bögels 2 +Published online: 8 October 2015 +# The Author(s) 2015. This article is published with open access at Springerlink.com"
+53c5f995e76ead002f1b0a78bfd50de3b1faf593,Enhancing the Symmetry and Proportion of 3D Face Geometry,"Enhancing the symmetry and proportion of 3D +face geometry +Qiqi Liao, Xiaogang Jin, Wenting Zeng"
+531b211d4cbe766e0b86c4bb6f24e924494360c5,"SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation","SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation +Sudeep Pillai, Rares, Ambrus,, Adrien Gaidon +Toyota Research Institute (TRI)"
+53bb52eb910c3a0ac5dc7f379b1f3f7c29af529d,Pain recognition using spatiotemporal oriented energy of facial muscles,"Pain Recognition using Spatiotemporal Oriented Energy of Facial Muscles +Ramin Irani, Kamal Nasrollahi, and Thomas B. Moeslund +Visual Analysis of People (VAP) Laboratory +Rendsburggade 14, 9000 Aalborg, Denmark +{ri, kn,"
53e081f5af505374c3b8491e9c4470fe77fe7934,Unconstrained realtime facial performance capture,"Unconstrained Realtime Facial Performance Capture Pei-Lun Hsieh⇤ ⇤ University of Southern California @@ -10324,6 +35572,76 @@ Jihun Yu† Hao Li⇤ Industrial Light & Magic Figure 1: Calibration-free realtime facial performance capture on highly occluded subjects using an RGB-D sensor."
+53f8f1ddd83a9e0e0821aaa883fbf7c1f7f5426e,Face Recognition using Principal Component Analysis and Log-Gabor Filters,"Face Recognition using Principal Component +Analysis and Log-Gabor Filters +Vytautas Perlibakas +Image Processing and Analysis Laboratory, Computational Technologies Centre, +Kaunas University of Technology, Studentu st. 56-305, LT-51424 Kaunas, +Lithuania"
+53ac22fff7ae3ed08565439ac30656846cac2465,Learning 3D Human Pose from Structure and Motion,"Learning 3D Human Pose from Structure and Motion +Rishabh Dabral1, Anurag Mundhada1, Uday Kusupati1, Safeer Afaque1, Abhishek +Sharma2, Arjun Jain1 +{rdabral, safeer, {anuragmundhada, +Indian Institute of Technology Bombay, 2Gobasco AI Labs +kusupatiuday,"
+53b35519e09772fb7ec470fdec51c6edb43c4f13,Word Channel Based Multiscale Pedestrian Detection without Image Resizing and Using Only One Classifier,"Word Channel Based Multiscale Pedestrian Detection +Without Image Resizing and Using Only One Classifier +Arthur Daniel Costea and Sergiu Nedevschi +Image Processing and Pattern Recognition Group (http://cv.utcluj.ro) +Computer Science Department, Technical University of Cluj-Napoca, Romania +{arthur.costea, +pedestrian or non-pedestrian based on image features. The +image features should capture the required information for +lassification, while allowing fast computation. +Previous object detection approaches use a fixed size +sliding window and resize the image [8] or use a fixed size +image and resize the sliding window [29]. When using +multiple sliding window scales, individual classifiers are +trained for different scales. In this paper we propose a +solution to pedestrian detection that does not require image +resizing and uses only one classifier for all sliding window +scales. The proposed approach introduces the use of word +hannels, inspired from codebook based semantic image +nnotation techniques for extracting classification features. +. Related work"
+5357e6e5d5fe06934bfe693d18b9f44bbd98f73b,Landmark Detection for Unconstrained Face Recognition,"Landmark Detection for +Unconstrained Face Recognition +Panagiotis B. Perakis (cid:63) +National and Kapodistrian University of Athens +Department of Informatics and Telecommunications"
+53f981cb6f1cf19b08255c571d62cc1073fd792b,Deconvolutional networks for point-cloud vehicle detection and tracking in driving scenarios,"Deconvolutional Networks for Point-Cloud Vehicle Detection +nd Tracking in Driving Scenarios +V´ıctor Vaquero∗, Ivan del Pino∗, Francesc Moreno-Noguer, Joan Sol`a, Alberto Sanfeliu and Juan Andrade-Cetto"
+538a9230ddc14b8a5d3f5f195aac4ec43e37d16f,Joint Holistic and Partial CNN for Pedestrian Detection,"YUN ZHAO et al.: JOINT HOLISTIC AND PARTIAL CNN FOR PEDESTRIAN DETECTION 1 +Joint Holistic and Partial CNN for Pedestrian +Detection +Yun Zhao1 +Zejian Yuan*1 +Hui Zhang2 +Institute of Artificial Intelligence and +Robotics +Xi’an Jiaotong University +Xi’an, China +Shenzhen Forward Innovation +Digital Technology Co. Ltd. China"
+53881bb35cb98c788f75fbc8c76198ccbc50edbf,Selective experience replay in reinforcement learning for reidentification,"SELECTIVE EXPERIENCE REPLAY IN REINFORCEMENT LEARNING FOR +REIDENTIFICATION +Ninad Thakoor , Bir Bhanu +Center for Research in Intelligent Systems, +University of California, Riverside, Riverside, CA 92521, USA"
+53993c7fabf631cbd8a44ab3e42c6bdf784db456,Understanding and Predicting Image Memorability at a Large Scale,"Understanding and Predicting Image Memorability at a Large Scale +Aditya Khosla +Akhil S. Raju +Antonio Torralba +Aude Oliva"
+537a00082b413b40fbdd02b5584791614f5071d2,Face Recognition Using Principal Component Analysis for Security Based System,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438 +Face Recognition Using Principal Component +Analysis for Security Based System +Madhuri M. Ghodake1, Parul S. Arora2 +Savitribai Phule Pune University, G.H.Raisoni College of Engg & Management, Domkhel Road, Wagholi, Pune +Assistant Professor, G.H.Raisoni College of Engg & Management, Domkhel Road, Wagholi, Pune, Savitribai Phule University, Pune"
53c36186bf0ffbe2f39165a1824c965c6394fe0d,I Know How You Feel: Emotion Recognition with Facial Landmarks,"I Know How You Feel: Emotion Recognition with Facial Landmarks Tooploox 2Polish-Japanese Academy of Information Technology 3Warsaw University of Technology Ivona Tautkute1,2, Tomasz Trzcinski1,3 and Adam Bielski1"
@@ -10336,11 +35654,68 @@ Kumar Krishna Agrawal∗ Pabitra Mitra {arnavkj95, abhinavagarawalla, kumarkrishna, Indian Institute of Technology Kharagpur"
+53822d61e829ef02a95a6c89fea082114fd3e16b,A General Framework for Tracking Multiple People from a Moving Camera,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +A General Framework for Tracking Multiple +People from a Moving Camera +Wongun Choi, Caroline Pantofaru, Silvio Savarese"
+53c8f841cbf2c8f09c6ece9d7f164504fe39409b,Deep Clustering for Unsupervised Learning of Visual Features,"Deep Clustering for Unsupervised Learning +of Visual Features +Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze +Facebook AI Research"
533bfb82c54f261e6a2b7ed7d31a2fd679c56d18,Unconstrained Face Recognition: Identifying a Person of Interest From a Media Collection,"Technical Report MSU-CSE-14-1 Unconstrained Face Recognition: Identifying a Person of Interest from a Media Collection Lacey Best-Rowden, Hu Han, Member, IEEE, Charles Otto, Brendan Klare, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+5383473d1a669beb0089f72a9a5075e943f0270f,Higher-order Occurrence Pooling on Mid- and Low-level Features: Visual Concept Detection,
+5367610430dc0380dfbe8344e08537267875968c,Tracking 3D Surfaces Using Multiple Cameras: A Probabilistic Approach,"Tracking 3D Surfaces Using +Multiple Cameras: A +Probabilistic Approach +Thomas Popham +Thesis +Submitted to the University of Warwick +for the degree of +Doctor of Philosophy +Department of Computer Science +August 2010"
+53facd4da5f1d1f98f876211421957f5fbe8a29a,The Mesh-LBP: A Framework for Extracting Local Binary Patterns From Discrete Manifolds,"The Mesh-LBP: A Framework for Extracting Local +Binary Patterns From Discrete Manifolds +Naoufel Werghi, Member, IEEE, Stefano Berretti, Member, IEEE, and Alberto del Bimbo, Member, IEEE"
+537061f3601965b5aab9f402763d9dcf451e1cef,A Deep Neural Model Of Emotion Appraisal,"Noname manuscript No. +(will be inserted by the editor) +A Deep Neural Model Of Emotion Appraisal +Pablo Barros · Emilia Barakova · Stefan Wermter +Received: date / Accepted: date"
+53492cb14b33a26b10c91102daa2d5a2a3ed069d,Improving Online Multiple Object tracking with Deep Metric Learning,"Improving Online Multiple Object tracking with Deep Metric Learning +Michael Thoreau, Navinda Kottege"
+53bed2d3d75c4320ad5af4a85e31bf92e3c704ef,Reinforced Video Captioning with Entailment Rewards,"Reinforced Video Captioning with Entailment Rewards +Ramakanth Pasunuru and Mohit Bansal +UNC Chapel Hill +{ram,"
+536d1f74c6543afcf2bc711befd82ac7886d1c33,Fusing Shearlets and LBP Feature Sets for Face Recognition,"ISSN 1746-7659, England, UK +Journal of Information and Computing Science +Vol. 10, No. 1, 2015, pp. 029-039 +Fusing Shearlets and LBP Feature Sets for Face Recognition +Zhiyong Zeng 1 +Faculty of Software, Fujian Normal University, Fuzhou, 350108, China +(Received October 07, 2014, accepted December 24, 2014)"
+538f735450463f40c78f60797899fcee47df72bc,Discriminative Dictionary Learning With Motion Weber Local Descriptor for Violence Detection,"© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for +ll other uses, in any current or future media, including reprinting/republishing this material for +dvertising or promotional purposes, creating new collective works, for resale or redistribution to +servers or lists, or reuse of any copyrighted component of this work in other works."
+3f55d26dd638c849745b95e912c28d88445ba5e1,Supervised Learning of Universal Sentence Representations from Natural Language Inference Data,"Supervised Learning of Universal Sentence Representations from +Natural Language Inference Data +Alexis Conneau +Facebook AI Research +Douwe Kiela +Facebook AI Research +Holger Schwenk +Facebook AI Research +Lo¨ıc Barrault +LIUM, Universit´e Le Mans +Antoine Bordes +Facebook AI Research"
3fbd68d1268922ee50c92b28bd23ca6669ff87e5,A shape- and texture-based enhanced Fisher classifier for face recognition,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 10, NO. 4, APRIL 2001 A Shape- and Texture-Based Enhanced Fisher Classifier for Face Recognition @@ -10348,6 +35723,10 @@ Chengjun Liu, Member, IEEE, and Harry Wechsler, Fellow, IEEE" 3f22a4383c55ceaafe7d3cfed1b9ef910559d639,Robust Kronecker Component Analysis,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 Robust Kronecker Component Analysis Mehdi Bahri, Student Member, IEEE, Yannis Panagakis, and Stefanos Zafeiriou, Member, IEEE"
+3f06d445371c252d5a6ba977181987094148d6de,Fast Single Shot Detection and Pose Estimation,"Fast Single Shot Detection and Pose Estimation +Patrick Poirson1, Phil Ammirato1, Cheng-Yang Fu1, Wei Liu1, Jana Koˇseck´a2, Alexander C. Berg1 +UNC Chapel Hill 2George Mason University +201 S. Columbia St., Chapel Hill, NC 27599 24400 University Dr, Fairfax, VA 22030"
3fdcc1e2ebcf236e8bb4a6ce7baf2db817f30001,A Top-Down Approach for a Synthetic Autobiographical Memory System,"A top-down approach for a synthetic utobiographical memory system Andreas Damianou1,2, Carl Henrik Ek3, Luke Boorman1, Neil D. Lawrence2, @@ -10355,6 +35734,69 @@ nd Tony J. Prescott1 Sheffield Centre for Robotics (SCentRo), Univ. of Sheffield, Sheffield, S10 2TN, UK Dept. of Computer Science, Univ. of Sheffield, Sheffield, S1 4DP, UK CVAP Lab, KTH, Stockholm, Sweden"
+3f44352b857f2fc18c18c5ebb2cbf994ee22f44c,Humanist computing for knowledge discovery from ordered datasets,"HumanistComputingforKnowledgeDiscovery +fromOrderedDatasets +JonathanMichaelRossiter +DepartmentofEngineeringMathematics +UniversityofBristol +AdissertationsubmittedtotheUniversityofBristol +inaccordancewiththerequirementsofthedegreeof +DoctorofPhilosophyintheFacultyofEngineering +January +3f9c09e2fbefc9aeba6505f49317f9a2fc03a615,Understanding fundamental design choices in single-ISA heterogeneous multicore architectures,"Understanding Fundamental Design Choices in Single-ISA +Heterogeneous Multicore Architectures +KENZO VAN CRAEYNEST and LIEVEN EECKHOUT, Ghent University +Single-ISA heterogeneous multicore processors have gained substantial interest over the past few years +ecause of their power efficiency, as they offer the potential for high overall chip throughput within a +given power budget. Prior work in heterogeneous architectures has mainly focused on how heterogeneity +an improve overall system throughput. To what extent heterogeneity affects per-program performance +has remained largely unanswered. In this article, we aim at understanding how heterogeneity affects both +hip throughput and per-program performance; how heterogeneous architectures compare to homogeneous +rchitectures under both performance metrics; and how fundamental design choices, such as core type, cache +size, and off-chip bandwidth, affect performance. +We use analytical modeling to explore a large space of single-ISA heterogeneous architectures. The ana- +lytical model has linear-time complexity in the number of core types and programs of interest, and offers a +unique opportunity for exploring the large space of both homogeneous and heterogeneous multicore proces- +sors in limited time. Our analysis provides several interesting insights: While it is true that heterogeneity +an improve system throughput, it fundamentally trades per-program performance for chip throughput; +lthough some heterogeneous configurations yield better throughput and per-program performance than +homogeneous designs, some homogeneous configurations are optimal for particular throughput versus per- +program performance trade-offs. Two core types provide most of the benefits from heterogeneity and a larger +number of core types does not contribute much; job-to-core mapping is both important and challenging for"
+3f5b20c35f55417823f0201862d85af1f31e9348,Salience Biased Loss for Object Detection in Aerial Images,"Salience Biased Loss for Object Detection +in Aerial Images +Peng Sun +Guerdan Luke +Guang Chen +University of Missouri-Columbia +Yi Shang +over regular and dense sampling of object scales, locations, +nd aspect ratios, such as YOLO [8], SSD [11], and RetinaNet +[18]. Each of these demonstrates promising results with faster +speed, a simpler network, and similar accuracy of two-stage +object detectors. RetinaNet [18] even outperforms one of the +est two-stage detectors, Faster R-CNN [5], with a relative 4.0 +mAP improvement in COCO data [17]."
+3faebe9d5c47fc90998811c4ac768706283d605c,Semi-Supervised Detection of Extreme Weather Events in Large Climate Datasets,"Under review as a conference paper at ICLR 2017 +SEMI-SUPERVISED DETECTION OF EXTREME WEATHER +EVENTS IN LARGE CLIMATE DATASETS +Evan Racah1, Christopher Beckham2, Tegan Maharaj2 +Prabhat1, Christopher Pal2 +Lawrence Berkeley National Lab, Berkeley, CA, +´Ecole Polytechnique de Montr´eal,"
+3f0f3c2bc151ef91959b06442b9ad80d405387a5,Evidential combination of pedestrian detectors,"XU ET AL.: EVIDENTIAL COMBINATION OF PEDESTRIAN DETECTORS +Evidential combination of pedestrian +detectors +Philippe Xu1 +https://www.hds.utc.fr/~xuphilip +Franck Davoine12 +Thierry Denœux1 +https://www.hds.utc.fr/~tdenoeux +UMR CNRS 7253, Heudiasyc, +Université de Technologie de +Compiègne, France +CNRS, LIAMA, +Beijing, P. R. China"
3f848d6424f3d666a1b6dd405a48a35a797dd147,Is 2D Information Enough For Viewpoint Estimation?,"GHODRATI et al.: IS 2D INFORMATION ENOUGH FOR VIEWPOINT ESTIMATION? Is 2D Information Enough For Viewpoint Estimation? @@ -10363,6 +35805,21 @@ Marco Pedersoli Tinne Tuytelaars KU Leuven, ESAT - PSI, iMinds Leuven, Belgium"
+3f6a6050609ba205ec94b8af186a9dca60a8f65e,Harmonizing Maximum Likelihood with Gans,"Under review as a conference paper at ICLR 2019 +HARMONIZING MAXIMUM LIKELIHOOD WITH GANS +FOR MULTIMODAL CONDITIONAL GENERATION +Anonymous authors +Paper under double-blind review"
+3f10b9d98a276fb9e21e5742ce88bc7f48629715,Imparare a Quantificare Guardando (Learning to Quantify by Watching),"Imparare a quantificare guardando +Sandro Pezzelle +CIMeC +Ionut Sorodoc +Aurelie Herbelot +CIMeC +EM LCT +Universit`a degli Studi di Trento +Raffaella Bernardi +CIMeC, DISI"
3fa738ab3c79eacdbfafa4c9950ef74f115a3d84,DaMN - Discriminative and Mutually Nearest: Exploiting Pairwise Category Proximity for Video Action Recognition,"DaMN – Discriminative and Mutually Nearest: Exploiting Pairwise Category Proximity for Video Action Recognition @@ -10370,8 +35827,62 @@ Rui Hou1, Amir Roshan Zamir1, Rahul Sukthankar2, and Mubarak Shah1 Center for Research in Computer Vision at UCF, Orlando, USA Google Research, Mountain View, USA http://crcv.ucf.edu/projects/DaMN/"
+3f8e481ea845aa20704d8c93f6a3a72025219f64,Data mapping by probabilistic modular networks and information-theoretic criteria,"IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 46, NO. 12, DECEMBER 1998 +Data Mapping by Probabilistic Modular +Networks and Information-Theoretic Criteria +Yue Wang, Shang-Hung Lin, Huai Li, and Sun-Yuan Kung, Fellow, IEEE"
+3f2270762ff68d6771d93d800683ae6bc76855e7,3D Human Motion Tracking and Pose Estimation using Probabilistic Activity Models,"MANCHESTER METROPOLITAN UNIVERSITY +D Human Motion Tracking and +Pose Estimation using +Probabilistic Activity Models +John Darby +A thesis submitted in partial fulfillment for the +degree of Doctor of Philosophy +Faculty of Science and Engineering +The Department of Computing and Mathematics +October 2010"
3fb98e76ffd8ba79e1c22eda4d640da0c037e98a,Convolutional Neural Networks for Crop Yield Prediction using Satellite Images,"Convolutional Neural Networks for Crop Yield Prediction using Satellite Images H. Russello"
+3fa9bf4649ff5e0d63ee20a546e8814f3a93ca4d,Digital Image Technique using Gabor Filter and SVM in Heterogeneous Face Recognition,"Research Inventy: International Journal of Engineering And Science +Vol.4, Issue 4 (April 2014), PP 45-52 +Issn (e): 2278-4721, Issn (p):2319-6483, www.researchinventy.com +Digital Image Technique using Gabor Filter and SVM in +Heterogeneous Face Recognition +M.Janani#1, K.Nandhini*2, K.Senthilvadivel*3,S.Jothilakshmi*4, +PG Student#1,*2*3, Assistant Professor*4,, Dept of CSE#1,*2,*3,*4 +S.V.S College of Engineering#1,*4,, PPG Institute of Technology*2,*3, +Coimbatore, Tamilnadu"
+3f600008dd9745e8357f5b7b3c1a69b8be6b7767,Atypical reflexive gaze patterns on emotional faces in autism spectrum disorders.,"The Journal of Neuroscience, September 15, 2010 • 30(37):12281–12287 • 12281 +Behavioral/Systems/Cognitive +Atypical Reflexive Gaze Patterns on Emotional Faces in +Autism Spectrum Disorders +Dorit Kliemann,1,2,3 Isabel Dziobek,2 Alexander Hatri,1,2 Rosa Steimke,2,4 and Hauke R. Heekeren1,2,3 +Department of Educational Science and Psychology, and 2Cluster of Excellence, “Languages of Emotion,” Freie Universita¨t Berlin, 14195 Berlin, Germany, +nd 3Max Planck Institute for Human Development, 14195 Berlin, Germany, and 4Department of Psychiatry and Psychotherapy, Charité University +Medicine, 10117 Berlin, Germany +Atypical scan paths on emotional faces and reduced eye contact represent a prominent feature of autism symptomatology, yet the reason +for these abnormalities remains a puzzle. Do individuals with autism spectrum disorders (ASDs) fail to orient toward the eyes or do they +ctively avoid direct eye contact? Here, we used a new task to investigate reflexive eye movements on fearful, happy, and neutral faces. +Participants (ASDs: 12; controls: 11) initially fixated either on the eyes or on the mouth. By analyzing the frequency of participants’ eye +movements away from the eyes and toward the eyes, respectively, we explored both avoidance and orientation reactions. The ASD group +showed a reduced preference for the eyes relative to the control group, primarily characterized by more frequent eye movements away +from the eyes. Eye-tracking data revealed a pronounced influence of active avoidance of direct eye contact on atypical gaze in ASDs. The +ombination of avoidance and reduced orientation into an individual index predicted emotional recognition performance. Crucially, this +result provides evidence for a direct link between individual gaze patterns and associated social symptomatology. These findings thereby +give important insights into the social pathology of ASD, with implications for future research and interventions. +Introduction +Recent reports from the social-cognitive neurosciences have em-"
+3f60b1f800178841f4e0ecb79b64fe60b48ed03b,Video Scene Parsing with Predictive Feature Learning,"Video Scene Parsing with Predictive Feature Learning +Xiaojie Jin1 Xin Li2 Huaxin Xiao2 Xiaohui Shen3 Zhe Lin3 Jimei Yang3 +Yunpeng Chen2 Jian Dong4 Luoqi Liu4 Zequn Jie2 Jiashi Feng2 Shuicheng Yan4,2 +NUS Graduate School for Integrative Science and Engineering, NUS +360 AI Institute +Department of ECE, NUS +Adobe Research"
+3f9210830e31f42103c6550f75cb37fde18e5af1,HeadFusion: 360° Head Pose Tracking Combining 3D Morphable Model and 3D Reconstruction,"PAMI SPECIAL ISSUE +HeadFusion: 360◦Head Pose tracking combining +D Morphable Model and 3D Reconstruction +Yu Yu, Kenneth Alberto Funes Mora, Jean-Marc Odobez"
3f14b504c2b37a0e8119fbda0eff52efb2eb2461,Joint Facial Action Unit Detection and Feature Fusion: A Multi-Conditional Learning Approach,"Joint Facial Action Unit Detection and Feature Fusion: A Multi-Conditional Learning Approach Stefanos Eleftheriadis, Ognjen Rudovic, Member, IEEE, and Maja Pantic, Fellow, IEEE"
@@ -10383,6 +35894,11 @@ nd Masafumi Hashimoto3 Information Systems Design, Doshisha University, Kyoto, Japan Graduate School of Doshisha University, Kyoto, Japan Intelligent Information Engineering and Science, Doshisha University, Kyoto, Japan"
+3f0e00188d751829c4548f9aacb939b982425ebd,Template Protection For 3D Face Recognition,"Template Protection For 3D Face Recognition +Template Protection For 3D Face Recognition +Xuebing Zhou, Arjan Kuijper and Christoph Busch +Fraunhofer Institute for Computer Graphics Research IGD +Germany"
3f9a7d690db82cf5c3940fbb06b827ced59ec01e,VIP: Finding important people in images,"VIP: Finding Important People in Images Clint Solomon Mathialagan Virginia Tech @@ -10397,12 +35913,33 @@ Demo: http://cloudcv.org/vip/" Attribute-Based Classification for Zero-Shot Visual Object Categorization Christoph H. Lampert, Hannes Nickisch and Stefan Harmeling"
+3f5158ea65bb483c6797462faffa16fea9f0b004,"Lie-X: Depth Image Based Articulated Object Pose Estimation, Tracking, and Action Recognition on Lie Groups","Lie-X : Depth Image Based Articulated Object Pose Estimation, +Tracking, and Action Recognition on Lie Groups +Chi Xu1, Lakshmi Narasimhan Govindarajan1, Yu Zhang1, and Li Cheng∗1 +Bioinformatics Institute, A*STAR, Singapore"
+3faff93758fe7fc58b3832055cb15c6ca3f306a7,Evaluation of multi feature fusion at score-level for appearance-based person re-identification,"Evaluation of Multi Feature Fusion at Score-Level +for Appearance-based Person Re-Identification +Markus Eisenbach +Ilmenau University of Technology +98684 Ilmenau, Germany +Alexander Kolarow +Alexander Vorndran +Julia Niebling +Horst-Michael Gross +Ilmenau University of Technology +Ilmenau University of Technology +98684 Ilmenau, Germany +98684 Ilmenau, Germany"
3f7723ab51417b85aa909e739fc4c43c64bf3e84,Improved Performance in Facial Expression Recognition Using 32 Geometric Features,"Improved Performance in Facial Expression Recognition Using 32 Geometric Features Giuseppe Palestra1(B), Adriana Pettinicchio2, Marco Del Coco2, Pierluigi Carcagn`ı2, Marco Leo2, and Cosimo Distante2 Department of Computer Science, University of Bari, Bari, Italy National Institute of Optics, National Research Council, Arnesano, LE, Italy"
+3fb689c0f1db224d53d9fdaee578d3ff8522f807,"Integrating Motion, Illumination, and Structure in Video Sequences with Applications in Illumination-Invariant Tracking","Integrating Motion, Illumination, and Structure +in Video Sequences with Applications in +Illumination-Invariant Tracking +Yilei Xu, Student Member, IEEE, and Amit K. Roy-Chowdhury, Member, IEEE"
3f63f9aaec8ba1fa801d131e3680900680f14139,Facial Expression recognition using Local Binary Patterns and Kullback Leibler divergence,"Facial Expression Recognition using Local Binary Patterns and Kullback Leibler Divergence AnushaVupputuri, SukadevMeher @@ -10415,6 +35952,16 @@ Ali Pazandeh Sharif UTech Luc Van Gool ESAT-KU Leuven, ETH Zurich"
+302fee58f8c9498e8a5e543312e7c11baf7e0827,Robust voting algorithm based on labels of behavior for video copy detection,"Robust Voting Algorithm Based on Labels of Behavior +for Video Copy Detection +Julien Law-To, Olivier Buisson +Valerie Gouet-Brunet, Nozha Boujemaa +INRIA Institut National +de la Recherche et de l’Informatique +Rocquencourt, France +Institut National de l’Audiovisuel +Bry Sur Marne, France +(jlawto,obuisson)"
30b15cdb72760f20f80e04157b57be9029d8a1ab,Face Aging with Identity-Preserved Conditional Generative Adversarial Networks,"Face Aging with Identity-Preserved Conditional Generative Adversarial Networks Zongwei Wang @@ -10424,6 +35971,9 @@ Baidu Weixin Luo, Shenghua Gao∗ Shanghaitech University {luowx,"
+30c8a2b6a505645b9f93dcc4d365eee6f46c4c37,Using Curvilinear Features in Focus for Registering a Single Image to a 3D Object,"Using Curvilinear Features in Focus for Registering +Single Image to a 3D Object +Hatem A. Rashwan, Sylvie Chambon, Pierre Gurdjos, G´eraldine Morin and Vincent Charvillat"
30870ef75aa57e41f54310283c0057451c8c822b,Overcoming catastrophic forgetting with hard attention to the task,"Overcoming Catastrophic Forgetting with Hard Attention to the Task Joan Serr`a 1 D´ıdac Sur´ıs 1 2 Marius Miron 1 3 Alexandros Karatzoglou 1"
305346d01298edeb5c6dc8b55679e8f60ba97efb,Fine-Grained Face Annotation Using Deep Multi-Task CNN,"Article @@ -10436,24 +35986,130 @@ Department of Informatics, Systems and Communication, University of Milano-Bicoc viale Sarca, 336 Milano, Italy; (S.B.); (R.S.) * Correspondence: Received: 3 July 2018; Accepted: 13 August 2018; Published: 14 August 2018"
+306ae56a4fc8f090e58a237749950e1607382ed7,Spatio-Temporal Matching for Human Pose Estimation in Video,"Spatio-temporal Matching for +Human Pose Estimation in Video +Feng Zhou and Fernando De la Torre"
+30ccfd2b4b6d5b30581356ccefcf96fd77c1766a,Overview of the ImageCLEF 2014 Scalable Concept Image Annotation Task,"Overview of the ImageCLEF 2016 Scalable +Concept Image Annotation Task +Andrew Gilbert, Luca Piras, Josiah Wang, Fei Yan, Arnau Ramisa, Emmanuel +Dellandrea, Robert Gaizauskas, Mauricio Villegas and Krystian Mikolajczyk"
+30aac3becead355545b5ab7f0c3158040360021e,ACD: Action Concept Discovery from Image-Sentence Corpora,"ACD: Action Concept Discovery from +Image-Sentence Corpora +Jiyang Gao +Univ. of Southern California +Chen Sun +Univ. of Southern California +Ram Nevatia +Univ. of Southern California"
+30962cf6f47396df88bf1c8827ebda8f0a6ff516,A Convolutional Neural Network Approach for Assisting Avalanche Search and Rescue Operations with UAV Imagery,"Article +A Convolutional Neural Network Approach for +Assisting Avalanche Search and Rescue Operations +with UAV Imagery +Mesay Belete Bejiga 1, Abdallah Zeggada 1, Abdelhamid Nouffidj 2 and Farid Melgani 1,* +Department of Information Engineering and Computer Science University of Trento, 38123 Trento, Italy; +(M.B.B.); (A.Z.) +Département des Télécommunications, Faculté d’Electronique et d’Informatique, USTHB BP 32, El-Alia, +Bab-Ezzouar, 16111 Algiers, Algeria; +* Correspondence: Tel.: +39-046-128-1573 +Academic Editors: Francesco Nex, Xiaofeng Li and Prasad S. Thenkabail +Received: 11 November 2016; Accepted: 14 January 2017; Published: 24 January 2017"
309e17e6223e13b1f76b5b0eaa123b96ef22f51b,Face recognition based on a 3D morphable model,"Face Recognition based on a 3D Morphable Model Volker Blanz University of Siegen H¤olderlinstr. 3 57068 Siegen, Germany"
+30256c10cb7ec139b4245855850998c39b297975,Functional magnetic resonance imaging of autism spectrum disorders,"C l i n i c a l r e s e a r c h +Functional magnetic resonance imaging of +utism spectrum disorders +Gabriel S. Dichter, PhD +Introduction +utism was first described by Leo Kanner1 and +Hans Asperger2 in a series of clinical case studies. Both +linicians suggested that the conditions now referred to +s autism spectrum disorders (ASDs) may have a neu- +robiological basis. With the relatively recent advent of +modern brain imaging techniques, translational psychi- +tric research has embraced the systematic study of +This review presents an overview of functional magnetic resonance imaging findings in autism spectrum disorders +(ASDs). Although there is considerable heterogeneity with respect to results across studies, common themes have +emerged, including: (i) hypoactivation in nodes of the “social brain” during social processing tasks, including regions +within the prefrontal cortex, the posterior superior temporal sulcus, the amygdala, and the fusiform gyrus; (ii) aber- +rant frontostriatal activation during cognitive control tasks relevant to restricted and repetitive behaviors and inter- +ests, including regions within the dorsal prefrontal cortex and the basal ganglia; (iii) differential lateralization and +ctivation of language processing and production regions during communication tasks; (iv) anomalous mesolimbic +responses to social and nonsocial rewards; (v) task-based long-range functional hypoconnectivity and short-range"
3046baea53360a8c5653f09f0a31581da384202e,Deformable Face Alignment via Local Measurements and Global Constraints,"Deformable Face Alignment via Local Measurements and Global Constraints Jason M. Saragih"
+30aff559ad25dd3490712749793547bc89b0f103,Image Latent Semantic Analysis for Face Recognition,"Image Latent Semantic Analysis for Face Recognition +Jucheng Yang 1,2,3 , Yanbin Jiao2, Jinfeng Yang4,Zhijun Fang2 , Congcong Xiong1, +Lei Shu2 +College of Computer Science and Information Engineering, Tianjin University of Science +nd Technology, Tianjin, China. +School of Information Technology, Jiangxi University of Finance and Economics, +Nanchang, China. {ybjiao, zjfang, lshu +Ahead Software Company Limited, Nanchang, 330041, China +Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, +Tianjin, China"
3028690d00bd95f20842d4aec84dc96de1db6e59,Leveraging Union of Subspace Structure to Improve Constrained Clustering,"Leveraging Union of Subspace Structure to Improve Constrained Clustering John Lipor 1 Laura Balzano 1"
+308647f22e3f1c80b7416b3c53fd56f9abfa904f,Robust Real-Time Tracking with Diverse Ensembles and Random Projections,"Robust Real-Time Tracking with Diverse Ensembles and Random Projections +Center for Informatics Science, +Center for Informatics Science, +Sara Maher +Nile University +Giza, Egypt +Mohamed El Helw +Center for Informatics Science, +Nile University +Giza, Egypt +Ahmed Salaheldin +Nile University +Giza, Egypt"
+30f7609d111bb3bc006e3dd38678291528aa14d3,A new approach for extracting and summarizing abnormal activities in surveillance videos,"014 IEEE International +Conference on Multimedia and +Expo Workshops +(ICMEW 2014) +Chengdu, China +4-18 July 2014 +Pages 516-1030 +IEEE Catalog Number: +ISBN: +CFP14IEW-POD +978-1-4799-4716-4"
30c96cc041bafa4f480b7b1eb5c45999701fe066,Discrete Cosine Transform Locality-Sensitive Hashes for Face Retrieval,"Discrete Cosine Transform Locality-Sensitive Hashes for Face Retrieval Mehran Kafai, Member, IEEE, Kave Eshghi, and Bir Bhanu, Fellow, IEEE"
+300fb25626bebfc84cf2f6458784b5cdf5c3ffc2,Cross-Dataset Adaptation for Visual Question Answering,"Cross-Dataset Adaptation for Visual Question Answering +Wei-Lun Chao∗ +Hexiang Hu∗ +Fei Sha +U. of Southern California +U. of Southern California +U. of Southern California +Los Angeles, CA +Los Angeles, CA +Los Angeles, CA"
+30eed14dfdee78279536e680871bed4f128d5f46,A Study of Calorie Estimation in Pictures of Food,
306957285fea4ce11a14641c3497d01b46095989,Face Recognition Under Varying Lighting Based on Derivates of Log Image,"FACE RECOGNITION UNDER VARYING LIGHTING BASED ON DERIVATES OF LOG IMAGE Laiyun Qing1,2, Shiguang Shan2, Wen Gao1,2 ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing 100080, China Graduate School, CAS, Beijing, 100039, China"
+309e5ae1554d2afc3b94eaea66b8f31ba85c434a,"Bian, Xiao. Sparse and Low-rank Modeling on High Dimensional Data: a Geometric Perspective. (under the Direction of Dr. Hamid Krim.) Sparse and Low-rank Modeling on High Dimensional Data: a Geometric Perspective",
+30f113d985d876a3974838b2ead49a069b474e57,Guided Upsampling Network for Real-Time Semantic Segmentation,"MAZZINI: GUN FOR REAL-TIME SEMANTIC SEGMENTATION +Guided Upsampling Network for Real-Time +Semantic Segmentation +Davide Mazzini +Department of Informatics, Systems +nd Communication +University of Milano-Bicocca +viale Sarca 336 Milano, Italy"
+3005a4afddab849d9070788ac0e4e95e0fff2216,"Transfer Metric Learning: Algorithms, Applications and Outlooks","JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, XXXX XXXX +Transfer Metric Learning: Algorithms, +Applications and Outlooks +Yong Luo, Yonggang Wen, Senior Member, IEEE, Ling-Yu Duan, Member, IEEE, +nd Dacheng Tao, Fellow, IEEE"
307a810d1bf6f747b1bd697a8a642afbd649613d,An affordable contactless security system access for restricted area,"An affordable contactless security system access for restricted area Pierre Bonazza1, Johel Mitéran1, Barthélémy Heyrman1, Dominique Ginhac1, @@ -10474,12 +36130,103 @@ tection [2] or human fall detection [3]. The principle of the system, fully thought and designed in our laboratory, is as follows: the allowed user pre- sents a RFID card to the reader based on Odalid system"
+301474a50a39b24917ad79bd2493f1168c4c1227,Eigen-disfigurement model for simulating plausible facial disfigurement after reconstructive surgery,"Lee et al. BMC Medical Imaging (2015) 15:12 +DOI 10.1186/s12880-015-0050-7 +R ES EAR CH A R T I C LE +Open Access +Eigen-disfigurement model for simulating plausible +facial disfigurement after reconstructive surgery +Juhun Lee1,2, Michelle C Fingeret2,3, Alan C Bovik1, Gregory P Reece2, Roman J Skoracki2, +Matthew M Hanasono2 and Mia K Markey4,5*"
+30b32f4a6341b5809428df1271bdb707f2418362,A Sequential Neural Encoder With Latent Structured Description for Modeling Sentences,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +A Sequential Neural Encoder with Latent Structured +Description for Modeling Sentences +Yu-Ping Ruan, Qian Chen, and Zhen-Hua Ling, Member, IEEE"
+30a059872d0fff3442504c24880c93738036e6aa,Calcul Neuronal Distribué Pour La Perception Visuelle Du Mouvement Th`ese,"UFRmath´ematiquesetinformatique´EcoledoctoraleIAEMLorraineD´epartementdeformationdoctoraleeninformatiqueCalculneuronaldistribu´epourlaperceptionvisuelledumouvementTH`ESEpr´esent´eeetsoutenuepubliquementle14Octobre2011pourl’obtentionduDoctoratdel’universit´eNancy2(sp´ecialit´einformatique)parMauricioDavidCerdaVillablancaCompositiondujuryPr´esident:Lepr´esidentRapporteurs:MathiasQUOYProfesseur,Universit´edeCergy-Pontoise,FranceAdrianPALACIOSProfesseur,UniversidaddeValparaiso,ChiliExaminateurs:HeikoNEUMANNProfesseur,UniversityofUlm,AllemagneAnneBOYERProfesseur,Universit´eNancy2,FranceRachidDERICHEDirecteurdeRecherche,INRIA,Sophia-Antipolis,FranceBernardGIRAU(directeur)Professeur,Universit´eHenriPoincar´e,Nancy1LaboratoireLorraindeRechercheenInformatiqueetsesApplications—UMR7503"
+300eb15b819ecc9668be26735e5038efc4e05281,Object-based Place Recognition for Mobile Robots Using Panoramas,"Object-based Place Recognition for +Mobile Robots Using Panoramas +Arturo RIBES a,1, Arnau RAMISA a and Ramon LOPEZ DE MANTARAS a and +Ricardo TOLEDO b +Artificial Intelligence Research Institute (IIIA-CSIC), Campus UAB, 08193 Bellaterra, +Computer Vision Center (CVC), Campus UAB, 08193 Bellaterra, Spain +Spain"
+30bb582c2c09abc7eb9dda7d9f80804eeb89f9d7,Research Problems and Opportunities in Memory Systems,"ResearchProblemsandOpportunitiesinMemorySystemsOnurMutlu1,LavanyaSubramanian1c(cid:13)TheAuthors2014.ThispaperispublishedwithopenaccessatSuperFri.orgThememorysystemisafundamentalperformanceandenergybottleneckinalmostallcom-putingsystems.Recentsystemdesign,application,andtechnologytrendsthatrequiremoreca-pacity,bandwidth,efficiency,andpredictabilityoutofthememorysystemmakeitanevenmoreimportantsystembottleneck.Atthesametime,DRAMtechnologyisexperiencingdifficulttech-nologyscalingchallengesthatmakethemaintenanceandenhancementofitscapacity,energy-efficiency,andreliabilitysignificantlymorecostlywithconventionaltechniques.Inthisarticle,afterdescribingthedemandsandchallengesfacedbythememorysystem,weexaminesomepromisingresearchanddesigndirectionstoovercomechallengesposedbymemoryscaling.Specifically,wedescribethreemajornewresearchchallengesandsolutiondirections:1)enablingnewDRAMarchitectures,functions,interfaces,andbetterintegrationoftheDRAMandtherestofthesystem(anapproachwecallsystem-DRAMco-design),2)designingamemorysystemthatemploysemergingnon-volatilememorytechnologiesandtakesadvantageofmultipledifferenttechnologies(i.e.,hybridmemorysystems),3)providingpredictableperformanceandQoStoapplicationssharingthememorysystem(i.e.,QoS-awarememorysystems).WealsobrieflydescribeourongoingrelatedworkincombatingscalingchallengesofNANDflashmemory.Keywords:memorysystems,scaling,DRAM,flash,non-volatilememory,QoS,reliability.IntroductionMainmemoryisacriticalcomponentofallcomputingsystems,employedinserver,em-bedded,desktop,mobileandsensorenvironments.Memorycapacity,energy,cost,performance,andmanagementalgorithmsmustscaleaswescalethesizeofthecomputingsysteminordertomaintainperformancegrowthandenablenewapplications.Unfortunately,suchscalinghasbe-comedifficultbecauserecenttrendsinsystems,applications,andtechnologygreatlyexacerbatethememorysystembottleneck.1.MemorySystemTrendsInparticular,onthesystems/architecturefront,energyandpowerconsumptionhavebecomekeydesignlimitersasthememorysystemcontinuestoberesponsibleforasignificantfractionofoverallsystemenergy/power[112].Moreandincreasinglyheterogeneousprocessingcoresandagents/clientsaresharingthememorysystem[11,36,39,60,78,79,178,181],leadingtoincreasingdemandformemorycapacityandbandwidthalongwitharelativelynewdemandforpredictableperformanceandqualityofservice(QoS)fromthememorysystem[129,137,176].Ontheapplicationsfront,importantapplicationsareusuallyverydataintensiveandarebecomingincreasinglyso[17],requiringbothreal-timeandofflinemanipulationofgreatamountsofdata.Forexample,next-generationgenomesequencingtechnologiesproducemassiveamountsofsequencedatathatoverwhelmsmemorystorageandbandwidthrequirementsoftoday’shigh-enddesktopandlaptopsystems[9,111,186,196,197]yetresearchershavethegoalofenablinglow-costpersonalizedmedicine,whichrequiresevenlargeramountsofdataandtheireffectiveanalyses.Creationofnewkillerapplicationsandusagemodelsforcomputerslikelydependsonhowwellthememorysystemcansupporttheefficientstorageandmanipulationofdatainsuch1CarnegieMellonUniversityDOI:10.14529/jsfi1403022014,Vol.1,No.319"
+302c2293e36e0704ccfe9af759a8505df588eb07,Face recognition with Multilevel B-Splines and Support Vector Machines,"Face Recognition with Multilevel B-Splines and Support +Vector Machines +Manuele Bicego +Dipartimento di Informatica +University of Verona +Strada Le Grazie 15 +7134 Verona - Italia +Gianluca Iacono +Dipartimento di Informatica +University of Verona +Strada Le Grazie 15 +7134 Verona - Italia +Vittorio Murino +Dipartimento di Informatica +University of Verona +Strada Le Grazie 15 +7134 Verona - Italia"
+30f84c48bdf2f6152075dd9651a761a84b2f2166,"No fear, no panic: probing negation as a means for emotion regulation.","doi:10.1093/scan/nss043 +SCAN (2013) 8, 654 ^661 +No fear, no panic: probing negation as a means for +emotion regulation +Cornelia Herbert,1 Roland Deutsch,2 Petra Platte,1 and Paul Pauli1 +Department of Psychology, Biological Psychology, Clinical Psychology and Psychotherapy, University of Wu¨rzburg, 97070 Wu¨rzburg and +Department of Psychology, Technische Universita¨t Dresden, Dresden, Germany +This electroencephalographic study investigated if negating ones emotion results in paradoxical effects or leads to effective emotional downregulation. +Healthy participants were asked to downregulate their emotions to happy and fearful faces by using negated emotional cue words (e.g. no fun, no fear). +Cue words were congruent with the emotion depicted in the face and presented prior to each face. Stimuli were presented in blocks of happy and fearful +faces. Blocks of passive stimulus viewing served as control condition. Active regulation reduced amplitudes of early event-related brain potentials (early +posterior negativity, but not N170) and the late positive potential for fearful faces. A fronto-central negativity peaking at about 250 ms after target face +onset showed larger amplitude modulations during downregulation of fearful and happy faces. Behaviorally, negating was more associated with +reappraisal than with suppression. Our results suggest that in an emotional context, negation processing could be quite effective for emotional +downregulation but that its effects depend on the type of the negated emotion (pleasant vs unpleasant). Results are discussed in the context of +dual process models of cognition and emotion regulation. +Keywords: emotion regulation; event-related brain potentials; negation; reappraisal; suppression +INTRODUCTION +Emotion regulation is an important aspect of everyday life (Gross and +John, 2003; Nezlek and Kuppens, 2008). Imagine the following situ-"
+300b8caf79783a7eba5608b5819b6fed14273d2d,Unsupervised Joint Mining of Deep Features and Image Labels for Large-Scale Radiology Image Categorization and Scene Recognition,"Unsupervised Joint Mining of Deep Features and Image Labels +for Large-scale Radiology Image Categorization and Scene Recognition +Xiaosong Wang, Le Lu, Hoo-chang Shin, Lauren Kim, Mohammadhadi Bagheri, +Isabella Nogues, Jianhua Yao, Ronald M. Summers +Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, +0 Center Drive, Bethesda, MD 20892"
+300b819bbbe857f5fe89d0895f907073fc288719,"Towards a Robust People Tracking Framework for Service Robots in Crowded, Dynamic Environments","Towards a Robust People Tracking Framework +for Service Robots in Crowded, Dynamic Environments +Timm Linder +Fabian Girrbach +Kai O. Arras"
+305dccd4004560572af2e849a36faf5626990517,Comparative Analysis of Face Recognition Approaches : A Survey,"Comparative Analysis of Face Recognition Approaches: +International Journal of Computer Applications (0975 – 8887) +Volume 57– No.17, November 2012 +A Survey +Ripal Patel, Nidhi Rathod, Ami Shah +Electronics & Telecommunication Department, +BVM Engineering College, +Vallabh Vidyanagar-388120, Gujarat, India."
+30fd7b1f8502b1c1d7a855946d99d2d5323ec973,Big Data Analysis for 2 Media Production,"I N V I T E D +P A P E R +Big Data Analysis for +Media Production +By Josep Blat, Alun Evans, Hansung Kim, Evren Imre, Luka`sˇ Polok, +Viorela Ila, Nikos Nikolaidis, Senior Member IEEE, Pavel Zemcˇı´k, Anastasios Tefas, +Pavel Smrzˇ, Adrian Hilton, Member IEEE, and Ioannis Pitas, Fellow IEEE"
302c9c105d49c1348b8f1d8cc47bead70e2acf08,Unconstrained Face Recognition Using A Set-to-Set Distance Measure,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2017.2710120, IEEE Transactions on Circuits and Systems for Video Technology IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY Unconstrained Face Recognition Using A Set-to-Set Distance Measure Jiaojiao Zhao, Jungong Han, and Ling Shao, Senior Member IEEE"
+30861d747c87e2e838c1c30eed334b17cc93cdb6,Bootstrapping Face Detection with Hard Negative Examples,"Bootstrapping Face Detection with Hard +Negative Examples +Shaohua Wan +Zhijun Chen Tao Zhang Bo Zhang Kong-kat Wong +{wanshaohua, chenzhijun, tao.zhang, zhangbo, +Xiaomi Inc. +August 9, 2016"
301b0da87027d6472b98361729faecf6e1d5e5f6,Head Pose Estimation in Face Recognition Across Pose Scenarios,"HEAD POSE ESTIMATION IN FACE RECOGNITION ACROSS POSE SCENARIOS M. Saquib Sarfraz and Olaf Hellwich @@ -10497,31 +36244,295 @@ Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba, Ibaraki, Japan {kensho.hara, hirokatsu.kataoka,"
+5e5e11e143140cc376db466d5b096a54b900c2ba,Face Recognition in Uncontrolled Environment,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 7, No. 8, 2016 +Face Recognition in Uncontrolled Environment +Radhey Shyam and Yogendra Narain Singh +Department of Computer Science & Engineering +Institute of Engineering and Technology +Lucknow - 226 021, India"
+5eee9c417157916ee66689718af65965c423b2b7,Autism and Asperger’s Syndrome: A Cognitive Neuroscience Perspective,"In Press: Carol Armstrong, Ed., Handbook of Medical Neuropsychology. New York: +Springer Science. +Autism and Asperger’s Syndrome: A Cognitive Neuroscience Perspective +Jeanne Townsend, Ph.D., Marissa Westerfield, Ph.D. +Department of Neurosciences, University of California, San Diego +Table of Contents +History and Background +Biological Underpinnings +Postmortem Studies +MRI Studies +White Matter Connectivity +Neuroanatomy +EEG Abnormalities +Seizures +Diagnosis +Neurocognitive Mechanisms +Screening Guidelines +Clinical & Research Criteria +Increased Prevalence of Autism +It’s not the vaccine"
5e0eb34aeb2b58000726540336771053ecd335fc,Low-Quality Video Face Recognition with Deep Networks and Polygonal Chain Distance,"Low-Quality Video Face Recognition with Deep Networks and Polygonal Chain Distance Christian Herrmann∗†, Dieter Willersinn†, J¨urgen Beyerer†∗ Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Karlsruhe, Germany Fraunhofer IOSB, Karlsruhe, Germany"
+5e0832848fab012b7e59580264257e0a3d05c596,The University of Southampton Multi-Biometric Tunnel and introducing a novel 3D gait dataset,"The University of Southampton Multi-Biometric Tunnel and +introducing a novel 3D gait dataset +Richard D. Seely, Sina Samangooei, Lee Middleton, John N. Carter and Mark S. Nixon"
+5eae1a3e0dfd0834be6a003b979bf5b3dc923453,"Far-Field, Multi-Camera, Video-to-Video Face Recognition","Far-Field, Multi-Camera, Video-to-Video Face +Recognition +Aristodemos Pnevmatikakis and Lazaros Polymenakos +Athens Information Technology +Greece +. Introduction +Face recognition on still images has been extensively studied. Given sufficient training data +(many gallery stills of each person) and/or high resolution images, the 90% recognition +arrier can be exceeded, even for hundreds of different people to be recognized (Phillips et +l., 2006). Face recognition on video streams has only recently begun to receive attention +(Weng et al., 2000; Li et al., 2001; Gorodnichy, 2003; Lee et al., 2003; Liu and Chen, 2003; +Raytchev and Murase, 2003; Aggarval et al., 2004; Xie et al., 2004; Stergiou et al., 2006). +Video-to-video face recognition refers to the problem of training and testing face recognition +systems using video streams. Usually these video streams are near-field, where the person +to be recognized occupies most of the frame. They are also constrained in the sense that the +person looks mainly at the camera. Typical such video streams originate from video-calls +nd news narration, where a person’s head and upper torso is visible. +A much more interesting application domain is that of the far-field unconstrained video +streams. In such streams the people are far from the camera, which is typically mounted on a +room corner near the ceiling. VGA-resolution cameras in such a setup can easily lead to quite"
+5ecf564bc9eab26c96c17304744ff1029215a109,Single-Sample Face Recognition Based on Intra-Class Differences in a Variation Model,"Sensors 2015, 15, 1071-1087; doi:10.3390/s150101071 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +Single-Sample Face Recognition Based on Intra-Class +Differences in a Variation Model +Jun Cai, Jing Chen * and Xing Liang +School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China; +E-Mails: (J.C.); (X.L.) +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +86-136-8151-5195. +External Editor: Valentina Gatteschi +Received: 17 September 2014 / Accepted: 10 December 2014 / Published: 8 January 2015"
+5e0df06d92176f362d52962de866e2d825185afb,Improving Multi-frame Data Association with Sparse Representations for Robust Near-online Multi-object Tracking,"Improving Multi-Frame Data Association with +Sparse Representations for Robust Near-Online +Multi-Object Tracking +Lo¨ıc Fagot-Bouquet1, Romaric Audigier1, Yoann Dhome1, Fr´ed´eric Lerasle2,3 +CEA, LIST, Vision and Content Engineering Laboratory, +Point Courrier 173, F-91191 Gif-sur-Yvette, France +CNRS, LAAS, 7, Avenue du Colonel Roche, F-31400 Toulouse, France +Universit´e de Toulouse, UPS, LAAS, F-31400 Toulouse, France"
+5e16cc5dc7ef8b4fc1320abbfeb838b4fe041905,A Proposal for Common Dataset in Neural-Symbolic Reasoning Studies,"A Proposal for Common Dataset in +Neural-Symbolic Reasoning Studies +Ozgur Yilmaz, Artur d’Avila Garcez, and Daniel Silver +Turgut Ozal University, Computer Science Department, Ankara Turkey +City University London, Department of Computer Science, London UK +Acadia University, Jodrey School of Computer Science, Nova Scotia Canada,"
5e28673a930131b1ee50d11f69573c17db8fff3e,Descriptor Based Methods in the Wild,"Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France (2008)"""
+5ef49174ca2b54c1bb54df828acc52075cf1634b,DAPs: Deep Action Proposals for Action Understanding,"DAPs: Deep Action Proposals for Action +Understanding +Victor Escorcia1, Fabian Caba Heilbron1, +Juan Carlos Niebles2,3, Bernard Ghanem1 +King Abdullah University of Science and Technology (KAUST), Saudi Arabia. +Stanford University. 3 Universidad del Norte, Colombia. +{victor.escorcia, fabian.caba,"
5ea9063b44b56d9c1942b8484572790dff82731e,Multiclass Support Vector Machines and Metric Multidimensional Scaling for Facial Expression Recognition,"MULTICLASS SUPPORT VECTOR MACHINES AND METRIC MULTIDIMENSIONAL SCALING FOR FACIAL EXPRESSION RECOGNITION Irene Kotsiay, Stefanos Zafeiriouy, Nikolaos Nikolaidisy and Ioannis Pitasy yAristotle University of Thessaloniki, Department of Informatics Thessaloniki, Greece email: fekotsia, dralbert, nikolaid,"
+5e9a6357fd7de7271dac77756c3992dce260eb49,On the Convergence of Affective and Persuasive Technologies in Computer-mediated Health-care Systems,"Rebeca I. García-Betances +Life Supporting Technologies (LifeSTech) +Superior Technical School of +Telecommunications Engineers +Polytechnic University of Madrid +Superior Technical School of +Telecommunications Engineers +Polytechnic University of Madrid +Spain +Dario Salvi +Spain +Giuseppe Fico +Life Supporting Technologies (LifeSTech) +Superior Technical School of +Telecommunications Engineers +Polytechnic University of Madrid +Spain +Manuel Ottaviano +Superior Technical School of +Telecommunications Engineers"
+5e8a7a2eef68f568c023f37e41576fa811e5c628,Deep Reinforcement Learning For Sequence to Sequence Models,"Deep Reinforcement Learning for +Sequence-to-Sequence Models +Yaser Keneshloo, Tian Shi, Naren Ramakrishnan, Chandan K. Reddy, Senior Member, IEEE"
+5e1b42d07eb84cddc1ebae607f3041aa2ef8fce8,RAM: Role Representation and Identification from combined Appearance and Activity Maps,"RAM: Role Representation and Identification +from combined Appearance and Activity Maps +Carlos Torres† Archith J. Bency† Je(cid:130)rey C. Fried‡ B. S. Manjunath† +University of California Santa Barbara ‡Santa Barbara Co(cid:138)age Hospital +{carlostorres, archith,"
+5e053cd164b02433c4efc0fc675f6273a8a1c46a,Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling,"Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pages 321–331 +Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pages 321–331 +Vancouver, Canada, July 30 - August 4, 2017. c(cid:13)2017 Association for Computational Linguistics +Vancouver, Canada, July 30 - August 4, 2017. c(cid:13)2017 Association for Computational Linguistics +https://doi.org/10.18653/v1/P17-1030 +https://doi.org/10.18653/v1/P17-1030"
+5e4ad1f19e88b6dc87000f64b984d8f09abe7baf,Invariant Spectral Hashing of Image Saliency Graph,"Invariant Spectral Hashing of Image Saliency Graph +Maxime Taquet, Laurent Jacques, Christophe De Vleeschouwer and Benoˆıt Macq +Information and Communication Technologies, Electronics and Applied Mathematics +Universit´e catholique de Louvain, Belgium. +September 17, 2010"
+5e832ea5328cdcc9b4346458672ad8288a56c0a7,Illumination-robust face recognition with Block-based Local Contrast Patterns,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE +ICASSP 2017"
5e6ba16cddd1797853d8898de52c1f1f44a73279,Face Identification with Second-Order Pooling,"Face Identification with Second-Order Pooling Fumin Shen, Chunhua Shen and Heng Tao Shen"
+5e2b918f2dee17cb79d692e10aa2103ca9129e2c,Rotating your face using multi-task deep neural network,"Rotating Your Face Using Multi-task Deep Neural Network +Junho Yim1 Heechul Jung1 ByungIn Yoo1;2 Changkyu Choi2 Dusik Park2 +Junmo Kim1 +School of Electrical Engineering, KAIST, South Korea +Samsung Advanced Institute of Technology +fjunho.yim, heechul, +fbyungin.yoo, changkyu choi,"
+5e8e3d2a79537a6cd0c138545bce63ddafaa853c,Intent-aware long-term prediction of pedestrian motion,"Intent-Aware Long-Term Prediction of Pedestrian Motion +Vasiliy Karasev +Alper Ayvaci +Bernd Heisele +Stefano Soatto"
+5e2266d4ca1377bdf38ad2c07d0d9e0200813522,Recognizing and Mask Removal in 3D Faces Even In Presence of Occlusions,"ISSN(Online): 2320-9801 +ISSN (Print): 2320-9798 +International Journal of Innovative Research in Computer and Communication Engineering +(An ISO 3297: 2007 Certified Organization) +Vol.2, Special Issue 1, March 2014 +Proceedings of International Conference On Global Innovations In Computing Technology (ICGICT’14) +Organized by +Department of CSE, JayShriram Group of Institutions, Tirupur, Tamilnadu, India on 6th & 7th March 2014 +Recognizing and Mask Removal in 3D Faces Even +In Presence of Occlusions +M.Dhivya1, P.Purushothaman2 +Dept. of Computer Science and Engineering, Muthayammal Engineering College, Rasipuram, Tamilnadu, India1. 2"
+5eefe98aafffe665b19de515e3ba90c9c0b7219c,Trimmed Event Recognition Submission to ActivityNet Challenge 2018,"Trimmed Event Recognition Submission to ActivityNet Challenge 2018 +Jiaqing Lin, Akikazu Takeuchi +STAIR Lab, Chiba Institute of Technology, Japan +{lin, +. Overview +This paper describes STAIR Lab submission to +ActivityNet 2018 Challenge for guest +task C: +Trimmed Event Recognition (Moments in Time) [1]. +Our approach is to utilize three networks, Audio +Net, Spatial-temporal Net, and DenseNet to make +individual predictions, then use MLP to fuses the +results to make an overall prediction. The flow chart +of our approach is shown in figure 1. +. Implementation +.1 Audio network +Our audio dataset training is different from other +methods. Usually, auditory raw waveforms are used +s input and are fed into a model like SoundNet [2]. +In our case, firstly, we converted auditory raw"
+5e6944abfed38fd30d8be45ee0c24dc1c0525ba1,An Algorithm for Face Recognition based on Isolated Image Points with Neural Network,"International Journal of Computer Applications (0975 – 8887) +Volume 150 – No.2, September 2016 +An Algorithm for Face Recognition based on Isolated +Image Points with Neural Network +Hassan Jaleel Hassan, PhD +Computer Engineering Department, +University of Technology +techniques +Pixel-based"
+5e9e3afeea446a2ae19e3a8e0678f08b73b0b36b,Commonsense knowledge acquisition and applications,"Commonsense Knowledge +Acquisition and Applications +Niket Tandon +Max-Planck-Institut f¨ur Informatik +Dissertation +zur Erlangung des Grades +des Doktors der Ingenieurwissenschaften (Dr.-Ing.) +der Naturwissenschaftlich-Technischen Fakult¨aten +der Universit¨at des Saarlandes +Saarbr¨ucken +August, 2016"
+5ece99e52efbd43ac7fed8a7d0d604218cba0337,Towards Deep Representation Learning with Genetic Programming,"Towards Deep Representation Learning with Genetic +Programming(cid:63) +Lino Rodriguez-Coayahuitl, Alicia Morales-Reyes, and Hugo Jair Escalante +Instituto Nacional de Astrofisica, Optica y Electronica, +Luis Enrique Erro No.1, Tonantzintla, 72840, Puebla, Mexico,"
5ec94adc9e0f282597f943ea9f4502a2a34ecfc2,Leveraging the Power of Gabor Phase for Face Identification: A Block Matching Approach,"Leveraging the Power of Gabor Phase for Face Identification: A Block Matching Approach Yang Zhong, Haibo Li KTH, Royal Institute of Technology"
+5ebd9457a3a09889fad8cc86a91b274da5986636,oASIS: Adaptive Column Sampling for Kernel Matrix Approximation,"PATEL et al.: OASIS: ADAPTIVE COLUMN SAMPLING FOR KERNEL MATRIX APPROXIMATION +oASIS: Adaptive Column Sampling +for Kernel Matrix Approximation +Raajen Patel*, Student Member, IEEE, Thomas A. Goldstein, Member, IEEE, Eva L. Dyer, Member, IEEE, +Azalia Mirhoseini, Student Member, IEEE, and Richard G. Baraniuk, Fellow, IEEE"
+5e286a45a4780a142e1420728ab99cb92993ab50,Data-driven image captioning with meta-class based retrieval,"META-SINIF TABANLI GETİRME İLE VERİYE DAYALI İMGE ALTYAZILAMA +DATA-DRIVEN IMAGE CAPTIONING WITH META-CLASS BASED RETRIEVAL +Mert Kılıçkaya1, Erkut Erdem1, Aykut Erdem1, Nazlı İkizler Cinbiş1, Ruket Çakıcı2 +Bilgisayar Mühendisliği Bölümü +Hacettepe Üniversitesi +ÖZETÇE +Otomatik imge altyazılama, bir imgenin açıklamasını yaratma +işlemi, bilgisayarlı görü ve doğal dil işleme topluluklarının +ilgisini daha yeni çeken çok zorlu bir problemdir. Bu +çalışmada, verilen bir imge için; imge-altyazı ikilileri içeren +geniş bir veri kümesinden ona görsel olarak en benzer imgeyi +ulan ve onun altyazısını girdi imgesinin açıklaması olarak +ktaran veriye dayalı özgün bir imge altyazılama stratejisi +önerilmiştir. Özgünlüğümüz, getirme +için girdi +görüntüsünün anlamsal içeriğini daha iyi yakalamak için +meta-sınıg gösterimi olarak adlandırılan yeni önerilmiş yüksek +düzey bir global imge gösterimi kullanılmasında yatmaktadır. +Deneylerimiz meta-sınıf güdümlü yaklaşımımızın dayanak +Im2Text modeline kıyasla daha doğru açıklamalar ürettiğini"
+5ef2be1aadd2f666756b2ab66bc05d146ba0681b,Normalization in Training Deep Convolutional Neural Networks for 2D Bio-medical Semantic Segmentation,"Normalization in Training Deep Convolutional Neural Networks for 2D +Bio-medical Semantic Segmentation +Xiao-Yun Zhou1 and Guang-Zhong Yang1"
+5e39deb4bff7b887c8f3a44dfe1352fbcde8a0bd,Supervised COSMOS Autoencoder: Learning Beyond the Euclidean Loss!,"Supervised COSMOS Autoencoder: Learning Beyond the +Euclidean Loss! +Maneet Singh, Student Member, IEEE, Shruti Nagpal, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE, +Richa Singh, Senior Member, IEEE, and Afzel Noore, Senior Member, IEEE"
+5ee220b6fb70a3d4d99be9d81d2c0e5de06ab3b9,LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics,"Pre-print of article that will appear in Proceedings of Robotics: Science and Systems XIV, 2018.Please cite this paper as:Sourav Garg, Niko Sunderhauf, and Michael Milford. LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics. Proceedings of Robotics: Science and Systems XIV, title={LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics}, author={Garg, Sourav and Suenderhauf, Niko and Milford, Michael}, journal={Proceedings of Robotics: Science and Systems XIV}, year={2018}}"
+5e4a451faf2e47486a5dbeca8a5109b53e22d95a,Statement Arun Kumar,"Research Statement +Arun Kumar +Large-scale data analytics using machine learning (ML), popularly known as advanced analytics or “Big +Data” analytics, is transforming almost every data-powered application in the enterprise, Web, science, +government, and other domains. However, there are still many barriers to broad and successful adoption +of advanced analytics. Designing new ML algorithms and faster ML implementations are important issues +that have been studied by researchers for a long time, but for most data-powered applications, the real +showstopper is a different issue that is often glossed over in research: the end-to-end process of building +ML models given raw data is often too painful even for professional analysts, while developers skilled in +oth general-purpose programming and the latest ML are rare. The goal of my research is to improve the +productivity of the users and developers of advanced analytics systems to enable data-powered applications +to realize the full potential of advanced analytics. To this end, my work focuses on fundamental research +questions at the intersection of data management and ML that address usability, developability, perfor- +mance, and scalability issues. My approach to solving a problem involves the whole spectrum of algorithm +design, theoretical analysis, empirical analysis, building prototype systems, and deploying them in practice. +Research Summary. My dissertation opens up a new problem that I call “learning over joins”, which +illustrates my goal of improving the productivity of analysts. My observation is simple: most ML toolkits +ssume the input data is a single table, but many real-world datasets are multi-table. Thus, analysts join +ll tables to create a single table that might be much larger, which means that managing and maintaining +it is a usability headache. Creating a single table also causes storage and performance issues. To mitigate"
+5be74c6fa7f890ea530e427685dadf0d0a371fc1,Deep Co-attention based Comparators For Relative Representation Learning in Person Re-identification,"Deep Co-attention based Comparators For Relative +Representation Learning in Person Re-identification +Lin Wu, Yang Wang, Junbin Gao, Dacheng Tao, Fellow, IEEE"
+5b25b9053ceafe1cf8258d8daa818a2da80c800f,Assigning affinity-preserving binary hash codes to images,"Assigning affinity-preserving +inary hash codes to images +Jason Filippou +Varun Manjunatha +June 10, 2014"
5bfc32d9457f43d2488583167af4f3175fdcdc03,Local Gray Code Pattern (LGCP): A Robust Feature Descriptor for Facial Expression Recognition,"International Journal of Science and Research (IJSR), India Online ISSN: 2319-7064 Local Gray Code Pattern (LGCP): A Robust Feature Descriptor for Facial Expression Recognition Mohammad Shahidul Islam Atish Dipankar University of Science & Technology, School, Department of Computer Science and Engineering, Dhaka, Bangladesh."
+5bc5cfc2622f6b0a0003d7b115726d075205a2cc,Auto Landing Process for Autonomous Flying Robot by Using Image Processing Based on Edge Detection,"AUTO LANDING PROCESS FOR +AUTONOMOUS FLYING ROBOT BY USING +IMAGE PROCESSING BASED ON EDGE +DETECTION +Bahram Lavi Sefidgari1 and Sahand Pourhassan Shamchi2 +Department of Computer Engineering, EMU, Famagusta, Cyprus +Department of Mechanical Engineering, EMU, Famagusta, Cyprus"
5ba7882700718e996d576b58528f1838e5559225,Predicting Personalized Image Emotion Perceptions in Social Networks,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2016.2628787, IEEE Transactions on Affective Computing IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. X, NO. X, OCTOBER 2016 @@ -10535,10 +36546,72 @@ University of California at Berkeley Technical Report No. UCB/EECS-2010-174 http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-174.html December 20, 2010"
+5b10fa6b4c0921af7b36a58f4fd2d8fca6e3c9b1,Low-Rank Multi-View Learning in Matrix Completion for Multi-Label Image Classification,"Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence +Low-Rank Multi-View Learning +in Matrix Completion for Multi-Label Image Classification +Meng Liu†, Yong Luo†§, Dacheng Tao‡, Chao Xu†, and Yonggang Wen§ +Key Laboratory of Machine Perception (MOE), School of EECS, PKU, Beijing 100871, China +Center for Quantum Computation and Intelligent Systems, UTS, Sydney, NSW 2007, Australia +§Division of Networks and Distributed Systems School of Computer Engineering, NTU, 639798, Singapore +{lemolemac,"
5bb684dfe64171b77df06ba68997fd1e8daffbe1,One-Sided Unsupervised Domain Mapping,
+5bf9493564d1ed173aee4dc701d4e62d5f926fe3,Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics using CNNs,"Bonnet: An Open-Source Training and Deployment Framework +for Semantic Segmentation in Robotics using CNNs +Andres Milioto +Cyrill Stachniss"
+5b0552a8e0ffdf1b6e7f2573640f888815391dec,Part-level fully convolutional networks for pedestrian detection,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE +ICASSP 2017"
+5b14abbea83270282ef94fcf3f3a73e7d8fee023,Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition,"Experiments about the Generalization Ability of +Common Vector based methods for Face +Recognition ? +Marcelo Armengot, Francesc J. Ferri, and Wladimiro D´ıaz +Dept. d’Inform`atica, Universitat de Val`encia +Dr Moliner, 50 46100 Burjassot, Spain"
+5b9c849c2acbdea6e3cfc730def4f083f169521c,A Method for Face Detection based on Wavelet Transform and optimised feature selection using Ant Colony Optimisation in Support Vector Machine,"ISSN (Print) : 2320 – 9798 +ISSN (Online) : 2320 – 9801 +International Journal of Innovative Research in Computer and Communication Engineering +Vol. 1, Issue 2, April 2013 +A Method for Face Detection based on Wavelet +Transform and optimised feature selection using Ant +Colony Optimisation in Support Vector Machine +Sanjay Kumar Pal1, Uday Chourasia 2 and Manish Ahirwar3 +Department of CSE, University Institute of Technology, RGPV, Bhopal, India1,2,3"
+5bf4f97b631937b2176db9c80dee965e2e2286be,From Classical to Generalized Zero-Shot Learning: a Simple Adaptation Process,"From Classical to Generalized Zero-Shot +Learning: a Simple Adaptation Process +Yannick Le Cacheux +Herv´e Le Borgne +CEA LIST +CEA LIST +Michel Crucianu +CEDRIC Lab – CNAM +September 27, 2018"
+5be6340c55d4a45e96e811bdeac3972328ca9247,People Identification and Tracking Through Fusion of Facial and Gait Features,"Original citation: +Guan, Yu (Researcher in Computer Science), Wei, Xingjie, Li, Chang-Tsun and Keller, +Y. (2014) People identification and tracking through fusion of facial and gait features. In: +Cantoni, Virginio and Dimov, Dimo and Tistarell, Massimo, (eds.) Biometric +Authentication : First International Workshop, BIOMET 2014, Sofia, Bulgaria, June 23- +4, 2014. Revised Selected Papers. Lecture Notes in Computer Science . Springer +International Publishing, pp. 209-221. ISBN 9783319133850 +Permanent WRAP url: +http://wrap.warwick.ac.uk/65110 +Copyright and reuse: +The Warwick Research Archive Portal (WRAP) makes this work by researchers of the +University of Warwick available open access under the following conditions. Copyright © +nd all moral rights to the version of the paper presented here belong to the individual +uthor(s) and/or other copyright owners. To the extent reasonable and practicable the +material made available in WRAP has been checked for eligibility before being made +vailable. +Copies of full items can be used for personal research or study, educational, or not-for +profit purposes without prior permission or charge. Provided that the authors, title and +full bibliographic details are credited, a hyperlink and/or URL is given for the original +metadata page and the content is not changed in any way."
5bae9822d703c585a61575dced83fa2f4dea1c6d,MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking,"MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking Laura Leal-Taix´e∗, Anton Milan∗, Ian Reid, Stefan Roth, and Konrad Schindler"
+5bcff482bd9652420f8f6b0e6e58ab59a562046e,Bit-Scalable Deep Hashing With Regularized Similarity Learning for Image Retrieval and Person Re-Identification,"Bit-Scalable Deep Hashing with Regularized +Similarity Learning for Image Retrieval and Person +Re-identification +Ruimao Zhang, Liang Lin, Rui Zhang, Wangmeng Zuo, and Lei Zhang"
5babbad3daac5c26503088782fd5b62067b94fa5,Are You Sure You Want To Do That? Classification with Verification,"Are You Sure You Want To Do That? Classification with Verification Harris Chan∗ @@ -10547,6 +36620,18 @@ Kevin Shen∗" 5bb87c7462c6c1ec5d60bde169c3a785ba5ea48f,Targeting Ultimate Accuracy: Face Recognition via Deep Embedding,"Targeting Ultimate Accuracy: Face Recognition via Deep Embedding Jingtuo Liu Yafeng Deng Tao Bai Zhengping Wei Chang Huang Baidu Research – Institute of Deep Learning"
+5b7870359b8b9934453f8e772ab7c3f9df3a5035,LF Indoor Location and Identification System,"LF Indoor Location and Identification System +Antti Ropponen, Matti Linnavuo, Raimo Sepponen +Helsinki University of Technology +Department of Electronics +PL 3340, 02015 TKK Finland +Emails:"
+5b6c603fba0a66fb3c037632079bdca82ec3bf91,Alternating Co-Quantization for Cross-Modal Hashing,"Alternating Co-Quantization for Cross-modal Hashing +Go Irie +Hiroyuki Arai +Yukinobu Taniguchi +NTT Corporation +{irie.go, arai.hiroyuki,"
5b9d9f5a59c48bc8dd409a1bd5abf1d642463d65,An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks,"Evolving Systems. manuscript No. (will be inserted by the editor) An evolving spatio-temporal approach for gender and age @@ -10578,6 +36663,84 @@ Ryan Sheatsley, Raquel Alvarez Pennsylvania State University Ananthram Swami Army Research Laboratory"
+5b6bdf478860b1e3f797858e71abd14f98684b61,Distributed neural computation for the visual perception of motion. (Calcul neuronal distribué pour la perception visuelle du mouvement),"Distributed neural computation for the visual +perception of motion +Mauricio Cerda +To cite this version: +Mauricio Cerda. Distributed neural computation for the visual perception of motion. Computer +science. Universit´e Nancy II, 2011. English. <tel-00642818> +HAL Id: tel-00642818 +https://tel.archives-ouvertes.fr/tel-00642818 +Submitted on 18 Nov 2011 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de +recherche fran¸cais ou ´etrangers, des laboratoires"
+5b3725c8b5e058ec3a383b621aa9316b90738b2e,Gaussian Conditional Random Field Network for Semantic Segmentation,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES +http://www.merl.com +Gaussian Conditional Random Field Network for Semantic +Segmentation +Vemulapalli, R.; Tuzel, C.O.; Liu, M.-Y.; Chellappa, R. +TR2016-078 +June 2016"
+5b1b90a0a6d491b26f427824985d69d5d0693220,Human gender classification: a review,"IEEE SENSORS JOURNAL, VOL. X, NO. X, XXXXXXX 2015 +Human Gender Classification: A Review +Yingxiao Wu, Member, IEEE, Yan Zhuang, Student Member, IEEE, Xi Long, Member, IEEE, +Feng Lin, Member, IEEE, and Wenyao Xu, Member, IEEE"
+5bb24d1250df62a56cab1445f1d8c5c61269b785,Measuring the Temporal Behavior of Real-World Person Re-Identification,"Measuring the Temporal Behavior of Real-World +Person Re-Identification +Meng Zheng, Student Member, IEEE, Srikrishna Karanam, Member, IEEE, +nd Richard J. Radke, Senior Member, IEEE"
+5bb14bba7510c590164007d7e3aa1bf88cb3faec,Learning to Match Appearances by Correlations in a Covariance Metric Space,"Learning to Match Appearances by Correlations +in a Covariance Metric Space +Sªawomir B¡k, Guillaume Charpiat, Etienne Corvée, François Brémond, +Monique Thonnat +INRIA Sophia Antipolis, STARS group +004, route des Lucioles, BP93 +06902 Sophia Antipolis Cedex - France"
+5ba1db56bccc090ce5eceb13f46f2cd15ba3aa55,Interpretable Counting in Visual Question Answering,"Under review as a conference paper at ICLR 2018 +INTERPRETABLE COUNTING IN VISUAL QUESTION +ANSWERING +Anonymous authors +Paper under double-blind review"
+5b818c73ce5681e523d6fe9ed8603c7afc0a9089,Improving Shape Retrieval by Spectral Matching and Meta Similarity,"Improving Shape retrieval by Spectral +Matching and Meta Similarity +Amir Egozi (BGU), +Yosi Keller (BIU) +nd Hugo Guterman (BGU) +Department of Electrical and Computer Engineering, +Ben-Gurion University of the Negev +/ 21"
+5b1d78b160560db5f581e65289ce5e2f99eb9b1f,Twitter100k: A Real-World Dataset for Weakly Supervised Cross-Media Retrieval,"Twitter100k: A Real-world Dataset for Weakly +Supervised Cross-Media Retrieval +Yuting Hu, Liang Zheng, Yi Yang, and Yongfeng Huang"
+5b94093939ac42aba54ab41eb1725aeba1bd5c34,RGB-D Segmentation of Poultry Entrails,"Aalborg Universitet +RGB-D Segmentation of Poultry Entrails +Philipsen, Mark Philip; Jørgensen, Anders; Guerrero, Sergio Escalera; Moeslund, Thomas B. +Published in: +IX International Conference on Articulated Motion and Deformable Objects +DOI (link to publication from Publisher): +0.1007/978-3-319-41778-3_17 +Publication date: +Document Version +Accepted author manuscript, peer reviewed version +Link to publication from Aalborg University +Citation for published version (APA): +Philipsen, M. P., Jørgensen, A., Guerrero, S. E., & Moeslund, T. B. (2016). RGB-D Segmentation of Poultry +Entrails. In IX International Conference on Articulated Motion and Deformable Objects (pp. 168-174). Springer. +(Lecture Notes in Computer Science, Vol. 9756). DOI: 10.1007/978-3-319-41778-3_17 +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. +? You may not further distribute the material or use it for any profit-making activity or commercial gain"
5be3cc1650c918da1c38690812f74573e66b1d32,Relative Parts: Distinctive Parts for Learning Relative Attributes,"Relative Parts: Distinctive Parts for Learning Relative Attributes Ramachandruni N. Sandeep Yashaswi Verma @@ -10604,6 +36767,14 @@ Irene Kotsiay, Nikolaos Nikolaidisy and Ioannis Pitasy yAristotle University of Thessaloniki Department of Informatics Box 451, 54124 Thessaloniki, Greece"
+37b207d2c4a82a57f80e96353f79ecd71320a854,Person Search with Natural Language Description,"Person Search with Natural Language Description +Shuang Li1 Tong Xiao1 Hongsheng Li1∗ Bolei Zhou2 Dayu Yue3 Xiaogang Wang1 ∗ +The Chinese University of Hong Kong 2Massachuate Institute of Technology 3SenseTime Group Limited"
+37c42f0a0e2e97a74113e1a1e1a79b04e0c64244,Covariance Pooling For Facial Expression Recognition,"Covariance Pooling for Facial Expression Recognition +Computer Vision Lab, ETH Zurich, Switzerland +VISICS, KU Leuven, Belgium +Dinesh Acharya†, Zhiwu Huang†, Danda Pani Paudel†, Luc Van Gool†‡ +{acharyad, zhiwu.huang, paudel,"
372fb32569ced35eaf3740a29890bec2be1869fa,Mu rhythm suppression is associated with the classification of emotion in faces.,"Running head: MU RHYTHM MODULATION BY CLASSIFICATION OF EMOTION 1 Mu rhythm suppression is associated with the classification of emotion in faces Matthew R. Moore1, Elizabeth A. Franz1 @@ -10615,11 +36786,23 @@ Department of Psychology University of Otago PO Box 56 Dunedin, New Zealand"
+376ea595a6ff5b876367654833de1e1778bacd1e,Bilingualism and ambiguous emotional cues 1,"Bilingualism and ambiguous emotional cues 1 +Examensarbete på avancerad nivå +Independent degree project second cycle +Psychology +Major subject +Title +Bilingualism and Children's Attention to Facial Expressions that Conflict with Lexical +Content +Amani Asad"
37f2e03c7cbec9ffc35eac51578e7e8fdfee3d4e,Co-operative Pedestrians Group Tracking in Crowded Scenes Using an MST Approach,"WACV 2015 Submission #394. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. Co-operative Pedestrians Group Tracking in Crowded Scenes using an MST Approach Anonymous WACV submission Paper ID 394"
+3748a828dabc6b5292b53cec6080cef33d78d3e3,On Clustering and Embedding Manifolds using a Low Rank Neighborhood Approach,"On Clustering and Embedding Manifolds using a +Low Rank Neighborhood Approach +Arun M. Saranathan, Student Member, IEEE, and Mario Parente, Member, IEEE"
3795974e24296185d9b64454cde6f796ca235387,Finding your Lookalike: Measuring Face Similarity Rather than Face Identity,"Finding your Lookalike: Measuring Face Similarity Rather than Face Identity Amir Sadovnik, Wassim Gharbi, Thanh Vu @@ -10628,6 +36811,33 @@ Easton, PA Andrew Gallagher Google Research Mountain View, CA"
+37d6cde8be756b70d22262f1acc3442a0c6aa7ea,Kernel learning approaches for image classification,"Kernel Learning Approaches for +Image Classification +Dissertation +zur Erlangung des akademischen Grades +Doctor rerum naturalium (Dr.rer.nat) +n der Naturwissenschaftlich-Technischen Fakult¨at I +der Universit¨at des Saarlandes, Saarbr¨ucken +vorgelegt von Dipl.-Inform. +Peter Vincent Gehler +0. Juni 2009"
+37a4eb74f9c9d6333864dbe1e0803d30c2e4db7c,An Evaluation of Deep CNN Baselines for Scene-Independent Person Re-Identification,"An Evaluation of Deep CNN Baselines for +Scene-Independent Person Re-Identification +Paul Marchwica, Michael Jamieson, Parthipan Siva +Senstar Corporation +Waterloo, Canada +{Paul.Marchwica, Mike.Jamieson, +the art"
+37a95a78bee34bb26a64c7ec30f7bd0496e072f1,The Focus-Aspect-Polarity Model for Predicting Subjective Noun Attributes in Images,"The Focus-Aspect-Polarity Model +for Predicting Subjective Noun Attributes in Images +Tushar Karayil1 +DFKI, Germany +Philipp Blandfort1 +DFKI and TUK, Germany +J¨orn Hees +DFKI, Germany +Andreas Dengel +DFKI, Germany"
37278ffce3a0fe2c2bbf6232e805dd3f5267eba3,Can we still avoid automatic face detection?,"Can we still avoid automatic face detection? Michael J. Wilber1,2 Vitaly Shmatikov1,2 @@ -10644,12 +36854,53 @@ Location: Bourns A265 Time: 11:00am Facial emotion recognition with anisotropic inhibited gabor energy histograms"
+37992120053b50b2f92eaa1949273bf828a54b50,Face Recognition Techniques - An evaluation Study,"Int. J. Advanced Networking and Applications +Volume: 6 Issue: 4 Pages: 2393-2397 (2015) ISSN: 0975-0290 +Face Recognition Techniques - An evaluation +Department of Management Information System, Applied Science University, 166-11391, Jordan +Study +Dr.Asmahan M Altaher +Email: +Keywords"
+3765df816dc5a061bc261e190acc8bdd9d47bec0,Presentation and validation of the Radboud Faces Database,"This article was downloaded by: [Radboud University Nijmegen] +On: 24 November 2010 +Access details: Access Details: [subscription number 907172236] +Publisher Psychology Press +Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37- +1 Mortimer Street, London W1T 3JH, UK +Cognition & Emotion +Publication details, including instructions for authors and subscription information: +http://www.informaworld.com/smpp/title~content=t713682755 +Presentation and validation of the Radboud Faces Database +Oliver Langnera; Ron Dotscha; Gijsbert Bijlstraa; Daniel H. J. Wigboldusa; Skyler T. Hawkb; Ad van +Knippenberga +Radboud University Nijmegen, Nijmegen, The Netherlands b University of Amsterdam, Amsterdam, +The Netherlands +Online publication date: 22 November 2010 +To cite this Article Langner, Oliver , Dotsch, Ron , Bijlstra, Gijsbert , Wigboldus, Daniel H. J. , Hawk, Skyler T. and van +Knippenberg, Ad(2010) 'Presentation and validation of the Radboud Faces Database', Cognition & Emotion, 24: 8, 1377 — +To link to this Article: DOI: 10.1080/02699930903485076 +URL: http://dx.doi.org/10.1080/02699930903485076 +PLEASE SCROLL DOWN FOR ARTICLE"
370e0d9b89518a6b317a9f54f18d5398895a7046,Cross-pollination of normalisation techniques from speaker to face authentication using Gaussian mixture models,"IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. X, NO. X, XXXXXXX 20XX Cross-pollination of normalisation techniques from speaker to face authentication using Gaussian mixture models Roy Wallace, Member, IEEE, Mitchell McLaren, Member, IEEE, Christopher McCool, Member, IEEE, nd S´ebastien Marcel, Member, IEEE"
+372bc106c61e7eb004835e85bbfee997409f176a,Coupled Generative Adversarial Networks,"Coupled Generative Adversarial Networks +Mitsubishi Electric Research Labs (MERL), +Mitsubishi Electric Research Labs (MERL), +Ming-Yu Liu +Oncel Tuzel"
+37838a832838ff3211b358bc51ba5105b9d82e89,The Complete Gabor-Fisher Classifier for Robust Face Recognition,"EURASIP JOURNAL ON ADVANCES IS SIGNAL PROCESSING +The Complete Gabor-Fisher Classifier for Robust +Face Recognition +Vitomir ˇStruc and Nikola Paveˇsi´c"
+37381718559f767fc496cc34ceb98ff18bc7d3e1,Harnessing Synthesized Abstraction Images to Improve Facial Attribute Recognition,Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18)
+372bf2716c53e353be6c3f027493f1a40edb6640,MINE: Mutual Information Neural Estimation,"Mutual Information Neural Estimation +Mohamed Ishmael Belghazi 1 Aristide Baratin 1 2 Sai Rajeswar 1 Sherjil Ozair 1 Yoshua Bengio 1 3 4 +Aaron Courville 1 3 R Devon Hjelm 1 4"
3773e5d195f796b0b7df1fca6e0d1466ad84b5e7,UNIVERSITY OF CALIFORNIA RIVERSIDE Learning from Time Series in the Presence of Noise: Unsupervised and Semi-Supervised Approaches,"UNIVERSITY OF CALIFORNIA RIVERSIDE Learning from Time Series in the Presence of Noise: Unsupervised and Semi-Supervised @@ -10668,22 +36919,127 @@ Dr. Vassilis Tsotras" Age, Gender and Race Estimation from Unconstrained Face Images Hu Han, Member, IEEE and Anil K. Jain, Fellow, IEEE"
+375993fd5f94c7b02169ff0d71a74d1b84262dfc,Parallel Application Library for Object Recognition,"Parallel Application Library for Object Recognition +Bor-Yiing Su +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2012-199 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-199.html +September 27, 2012"
375435fb0da220a65ac9e82275a880e1b9f0a557,From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild Akshay Asthana, Stefanos Zafeiriou, Georgios Tzimiropou- los, Shiyang Cheng and Maja Pantic"
+37a23e76674e606ce779131d2c93496e8a53bb2f,The discrete cosine transform (DCT) plus local normalization: a novel two-stage method for de-illumination in face recognition,"Optica Applicata, Vol. XLI, No. 4, 2011 +The discrete cosine transform (DCT) +plus local normalization: +novel two-stage method +for de-illumination in face recognition +MINGHUA ZHAO*, YINGHUI WANG, ZHENGHAO SHI, JIULONG ZHANG +School of Computer Science and Engineering, Xi’an University of Technology, Xi’an710048, China +*Corresponding author: +To deal with illumination variations in face recognition, a novel two-stage illumination +normalization method is proposed in this paper. Firstly, a discrete cosine transform (DCT) is used +on the original images in logarithm domain. DC coefficient is set based on the average pixel value +of all the within-class training samples and some low frequency AC coefficients are set to zero to +eliminate illumination variations in large areas. Secondly, local normalization method, which can +minimize illumination variations in small areas, is used on the inverse DCT images. This makes +the pixel values on the processed images be close to or equal to that of the normal illumination +ondition. Experimental results, both on Yale B database and Extended Yale B database, show +that the proposed method can eliminate effect of illumination variations effectively and improve +performance of face recognition methods significantly. The present method does not demand +modeling step and can eliminate the effect of illumination variations before face recognition. In +this way, it can be used as a preprocessing step for any existing face recognition method."
+3726b82007512a15a530fd1adad57af58a9abb62,Teaching Compositionality to CNNs,"Teaching Compositionality to CNNs∗ +Austin Stone +Yi Liu +Huayan Wang +D. Scott Phoenix +Michael Stark +Dileep George +Vicarious FPC, San Francisco, CA, USA +{austin, huayan, michael, yi, scott,"
37b6d6577541ed991435eaf899a2f82fdd72c790,Vision-based Human Gender Recognition: A Survey,"Vision-based Human Gender Recognition: A Survey Choon Boon Ng, Yong Haur Tay, Bok Min Goi Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia."
+37b0357d2db89bc4560d4201c3c2478988c87640,Face Recognition Based on Curvelet Transform and LS-SVM,"ISBN 978-952-5726-02-2 (Print), 978-952-5726-03-9 (CD-ROM) +Proceedings of the 2009 International Symposium on Information Processing (ISIP’09) +Huangshan, P. R. China, August 21-23, 2009, pp. 140-143 +Face Recognition Based on Curvelet Transform +nd LS-SVM +School of Electronics, Jiangxi University of Finance and Economics, Nanchang, China +Jianhong Xie +long +reduce +singularities +urves. To"
+37347e4c1b35196761fc1620e451738f880f0392,Exemplar-based human action pose correction and tagging,"Exemplar-Based Human Action Pose Correction and Tagging +Wei Shen +Ke Deng +Xiang Bai +Huazhong Univ. of Sci.&Tech. +Microsoft Corporation +Huazhong Univ. of Sci.&Tech. +Tommer Leyvand +Microsoft Corporation +Baining Guo +Zhuowen Tu +Microsoft Research Asia +Microsoft Research Asia & UCLA"
+3752dc15fada54abc0af866273d03a28f4dc8975,A Variational Framework for Pedestrian Segmentation in Cluttered Scenes Using Bag of Optical Flows and Shape Priors,"A VARIATIONAL FRAMEWORK FOR PEDESTRIAN +SEGMENTATION IN CLUTTERED SCENES USING +BAG OF OPTICAL FLOWS AND SHAPE PRIORS +Gagan Bansal +A thesis submitted to The Johns Hopkins University in conformity with the requirements +for the degree of Master of Science. +Baltimore, Maryland +January, 2009 +(cid:176) Gagan Bansal 2009 +All rights reserved"
+375e478acf62eede1cc69693c54d81aa718df9e7,DFT domain Feature Extraction using Edge-based Scale Normalization for Enhanced Face Recognition,"Journal of Advanced Computer Science and Technology, 1 (3) (2012) 134-166 +(cid:13)Science Publishing Corporation +www.sciencepubco.com/index.php/JACST +DFT domain Feature Extraction using +Edge-based Scale Normalization for +Enhanced Face Recognition +K Manikantan1,∗, S Ramachandran2,† +Department of Electronics and Communication Engineering, +M S Ramaiah Institute of Technology, Bangalore, Karnataka, India 560054 +Department of Electronics and Communication Engineering, +S J B Institute of Technology, Bangalore, Karnataka, India 560060"
372a8bf0ef757c08551d41e40cb7a485527b6cd7,Unsupervised Video Hashing by Exploiting Spatio-Temporal Feature,"Unsupervised Video Hashing by Exploiting Spatio-Temporal Feature Chao Ma, Yun Gu, Wei Liu, and Jie Yang(cid:63) Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China."
+37c4541037b67e8f4c538b285efe80aa251a49b9,Tracking as a Whole: Multi-Target Tracking by Modeling Group Behavior With Sequential Detection,"Tracking as a Whole: Multi-Target Tracking +y Modeling Group Behavior With +Sequential Detection +Yuan Yuan, Senior Member, IEEE, Yuwei Lu, and Qi Wang, Senior Member, IEEE"
+376b73334bd9aebed1fbb69c4ed3848ec0826b6c,Online non-rigid structure-from-motion based on a keyframe representation of history,"Online Non-rigid Structure-from-motion based on a +keyframe representation of history +Simon Donn´e, Ljubomir Jovanov, Bart Goossens, Wilfried Philips, Aleksandra Piˇzurica +Department of Telecommunications and Information Processing (TELIN) +{Simon.Donne, Ljubomir.Jovanov, Bart.Goossens, Wilfried.Philips, +Ghent University +Ghent, Belgium"
+370ed90971eca7ad84c67d8804f97e02ff6fd5b4,"The Socio-Moral Image Database (SMID): A novel stimulus set for the study of social, moral and affective processes","RESEARCH ARTICLE +The Socio-Moral Image Database (SMID): A +novel stimulus set for the study of social, +moral and affective processes +Damien L. Crone1*, Stefan Bode1, Carsten Murawski2, Simon M. Laham1 +Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia, +Department of Finance, University of Melbourne, Melbourne, Australia"
+370277791a0708b7c93deb21da172e025b558643,"Fusing LIDAR, camera and semantic information: A context-based approach for pedestrian detection","Fusing LIDAR, camera and semantic information: +context-based approach for pedestrian detection +Cristiano Premebida and Urbano Nunes +The final version is available at: http://ijr.sagepub.com/content/32/3.toc +This is a pre-print version."
370b5757a5379b15e30d619e4d3fb9e8e13f3256,Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments,"Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller"
+08aedeb74dda306a14c699ffcef4f434a60f34e8,3 D Spatial Layout and Geometric Constraints for Scene Understanding by Varsha Chandrashekhar,(cid:13) 2011 Varsha Chandrashekhar Hedau
08d2f655361335bdd6c1c901642981e650dff5ec,Automatic Cast Listing in Feature-Length Films with Anisotropic Manifold Space,"This is the published version: Arandjelovic, Ognjen and Cipolla, R. 2006, Automatic cast listing in feature‐length films with Anisotropic Manifold Space, in CVPR 2006 : Proceedings of the Computer Vision and Pattern @@ -10692,6 +37048,9 @@ http://hdl.handle.net/10536/DRO/DU:30058435 Reproduced with the kind permission of the copyright owner. Copyright : 2006, IEEE Available from Deakin Research Online:"
+085fce160b0fa279597bf23b518c56c735d9e7ff,Joint detection and recognition of human actions in wireless surveillance camera networks,"Joint Detection and Recognition of Human Actions in Wireless +Surveillance Camera Networks +Nikhil Naikal1, Pedram Lajevardi2 and Shankar. S. Sastry1"
08fbe3187f31b828a38811cc8dc7ca17933b91e9,Statistical Computations on Grassmann and Stiefel Manifolds for Image and Video-Based Recognition,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Statistical Computations on Grassmann and @@ -10709,6 +37068,12 @@ Predicting the Sixteen Personality Factors features Mihai Gavrilescu* and Nicolae Vizireanu Open Access"
+08c6943a17f267ef27316cff9248b3036a7059f3,We are not contortionists: Coupled adaptive learning for head and body orientation estimation in surveillance video,"We are not Contortionists: Coupled Adaptive Learning +for Head and Body Orientation Estimation in Surveillance Video +Cheng Chen +Jean-Marc Odobez +Idiap Research Institute – CH-1920, Martigny, Switzerland +(cid:3)"
08c18b2f57c8e6a3bfe462e599a6e1ce03005876,A Least-Squares Framework for Component Analysis,"A Least-Squares Framework for Component Analysis Fernando De la Torre Member, IEEE,"
@@ -10727,11 +37092,120 @@ General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms"
+08d625158727bd97ba6fc58992158ee55a53011c,HCLAE: High Capacity Locally Aggregating Encodings for Approximate Nearest Neighbor Search,"HCLAE: High Capacity Locally Aggregating Encodings for Approximate Nearest +Neighbor Search +{artheru, yz sjr, Shanghai Jiaotong University +Liu Shicong, Shao Junru, Lu Hongtao"
+08f46d6a91e513edd57a0ef15d5367b5d0545c1b,"How do targets, nontargets, and scene context influence real-world object detection?","Atten Percept Psychophys +DOI 10.3758/s13414-017-1359-9 +How do targets, nontargets, and scene context influence +real-world object detection? +Harish Katti 1 +& Marius V. Peelen 2 & S. P. Arun 1 +# The Psychonomic Society, Inc. 2017"
+0888b6904ef12bc7a3c59fa59c4051d5002de80f,Learning with Shared Information for Image and Video Analysis,"DEPARTMENT OF INFORMATION ENGINEERING AND COMPUTER SCIENCE +ICT International Doctoral School +LEARNING WITH SHARED INFORMATION FOR IMAGE +AND VIDEO ANALYSIS +Gaowen Liu +Advisor +Prof. Nicu Sebe +Universit`a degli Studi di Trento"
+0834dff6e1d37ecb36137e019f8e2c933d5e74f6,Building Part-Based Object Detectors via 3D Geometry,"BUILDING PART-BASED OBJECT DETECTORS VIA 3D GEOMETRY +Experimental Results +Qualitative Results +Input Image +DPM Detection +Test Set: NYU v2 RGB Images +gDPM Detection Predicted Geometry +Bed gDPM Model 3 +Sofa gDPM Model 3 +Table gDPM Model 3 +Discriminative Part-based Models +Supervised Parts +Unsupervised Parts +Key-point/part annotation, e.g., +Heuristic initialization, e.g., gradient +natomical. +magnitudes. +. Overview +. Overview +As input to the system, at training, we use RGB images"
+0816cbac9ea8f4425d9b57fd46174cb35cd5d7cc,People tracking in RGB-D data with on-line boosted target models,"People Tracking in RGB-D Data +With On-line Boosted Target Models +Matthias Luber +Luciano Spinello +Kai O. Arras"
+0856622ce2fcc4e39fd396427abae90cddf78fd0,Abnormal activation of the social brain during face perception in autism.,"Abnormal Activation of the Social Brain During +Face Perception in Autism +Nouchine Hadjikhani,1,2* Robert M. Joseph,3 Josh Snyder,1 +nd Helen Tager-Flusberg3 +Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, +Division of Health Sciences and Technology, Harvard-Massachusetts Institute of Technology, +Harvard Medical School, Charlestown, Massachusetts +Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, +Cambridge, Massachusetts +Massachusetts"
+083a2bc86e0984968b06593ba06654277b252f00,Neural evidence for the contribution of holistic processing but not attention allocation to the other-race effect on face memory.,"Cognitive, Affective, & Behavioral Neuroscience (2018) 18:1015–1033 +https://doi.org/10.3758/s13415-018-0619-z +Neural evidence for the contribution of holistic processing but not +ttention allocation to the other-race effect on face memory +Grit Herzmann 1 & Greta Minor 1 & Tim Curran 2 +Published online: 25 June 2018 +# Psychonomic Society, Inc. 2018"
+085ca7f8935808986ae1c6afbbb62f6804049f26,Monocular 3D human pose estimation by classification,"Universit¨at Augsburg +Monocular 3D Human Pose Estimation +y Classification +T. Greif, D. Sengupta, R. Lienhart +Report 2011-09 +M¨arz 2011 +Institut f¨ur Informatik +D-86135 Augsburg"
+0875af310ab8c850b3232b3f6b84535ffff84e5d,A Novel Technique to Detect Faces in a Group Photo,"International Journal of Computer Applications (0975 – 8887) +Volume 54– No.1, September 2012 +A Novel Technique to Detect Faces in a Group Photo +Saravanan Chandran +Assistant Professor, National Institute of Technology, Durgapur, West Bengal, India."
+081093b0b3195e3f6bfa283b49fee26b606d4f67,Object Co-detection,"Object Co-detection +Sid Yingze Bao, Yu Xiang, Silvio Savarese +University of Michigan at Ann Arbor, USA +{yingze, yuxiang,"
+08bbb59036c4b85a2418f9702ccd37929c5dd154,Understanding and Predicting the Memorability of Natural Scene Images,"Understanding and Predicting the Memorability of +Natural Scene Images +Jiaxin Lu, Mai Xu, Senior Member, IEEE, Ren Yang and Zulin Wang"
+08bdb84d5c66265b3b6d33e8f95c4cc27caf33ad,Detecting Visual Relationships Using Box Attention,"Detecting Visual Relationships Using Box Attention +Alexander Kolesnikov∗ +Google AI +Christoph H. Lampert +IST Austria +Vittorio Ferrari +Google AI"
+084bd219dd239dc4c9a02621a5333d3bc1446566,DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking,"DeepTrack: Learning Discriminative Feature +Representations Online for Robust Visual Tracking +Hanxi Li, Yi Li, Fatih Porikli"
0861f86fb65aa915fbfbe918b28aabf31ffba364,An Efficient Facial Annotation with Machine Learning Approach,"International Journal of Computer Trends and Technology (IJCTT) – volume 22 Number 3–April 2015 An Efficient Facial Annotation with Machine Learning Approach A.Anusha,2R.Srinivas Final M.Tech Student, 2Associate Professor ,2Dept of CSE ,Aditya Institute of Technology And Management, Tekkali, Srikakulam , Andhra Pradesh"
+082a8642455b9a5cfb27c07cf9969106f8a7bf3c,Face recognition is similarly affected by viewpoint in school-aged children and adults,"Face recognition is similarly affected by +viewpoint in school-aged children and +dults +Marisa Nordt and Sarah Weigelt +Department of Developmental Neuropsychology, Institute of Psychology, Ruhr-Universität Bochum, +Bochum, Germany"
+08b76e6923eea74ab0ed149811b3144fa21c7c73,Scalable Laplacian K-modes,"Scalable Laplacian K-modes +Imtiaz Masud Ziko ∗ +ÉTS Montreal +Eric Granger +ÉTS Montreal +Ismail Ben Ayed +ÉTS Montreal"
+08809165154c9c557d368cddfa3ae66ccaceaed9,Taming VAEs,"Taming VAEs +Danilo J. Rezende ∗ +Fabio Viola ∗ +{danilor, +DeepMind, London, UK"
080c204edff49bf85b335d3d416c5e734a861151,CLAD: A Complex and Long Activities Dataset with Rich Crowdsourced Annotations,"CLAD: A Complex and Long Activities Dataset with Rich Crowdsourced Annotations @@ -10756,16 +37230,47 @@ VPCOE Baramati V. U. Deshmukh Assistant Professor VPCOE Baramati"
+081d6ac51bbb7df142e3db6649fb5d663e90d569,Generalized zero-shot learning for action recognition with web-scale video data,"Noname manuscript No. +(will be inserted by the editor) +Generalized Zero-Shot Learning for Action +Recognition with Web-Scale Video Data +Kun Liu · Wu Liu · Huadong Ma · +Wenbing Huang · Xiongxiong Dong +Received: date / Accepted: date"
+082d339e29b1b1a9a800a1d72b401f69b6a157c5,Webly Supervised Joint Embedding for Cross-Modal Image-Text Retrieval,"Webly Supervised Joint Embedding for Cross-Modal +Image-Text Retrieval +Niluthpol Chowdhury Mithun +University of California, Riverside, CA +Evangelos E. Papalexakis +University of California, Riverside, CA +Rameswar Panda +University of California, Riverside, CA +Amit K. Roy-Chowdhury +University of California, Riverside, CA"
08d40ee6e1c0060d3b706b6b627e03d4b123377a,Towards Weakly-Supervised Action Localization,"Human Action Localization with Sparse Spatial Supervision Philippe Weinzaepfel, Xavier Martin, and Cordelia Schmid, Fellow, IEEE"
+08030f9d34cc96384f672d9f9f296914d594335b,Multiple Object Tracking: A Literature Review,"Multiple Object Tracking: A Literature Review +Wenhan Luo, Junliang Xing, Anton Milan, Xiaoqin Zhang, Wei Liu, Xiaowei Zhao and Tae-Kyun Kim"
+085ba9f82e15603f1fe2a29dfa0182d46465a591,Face Recognition In Presence Of Occlusion Using Machine Learning Classifier,"International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 4, April 2014 +Face Recognition In Presence Of Occlusion +Using Machine Learning Classifier +Vandana P, Manjunath C N +chieve"
088aabe3da627432fdccf5077969e3f6402f0a80,Classifier-to-generator Attack: Estimation,"Under review as a conference paper at ICLR 2018 CLASSIFIER-TO-GENERATOR ATTACK: ESTIMATION OF TRAINING DATA DISTRIBUTION FROM CLASSIFIER Anonymous authors Paper under double-blind review"
+084f1a6c62a3464b1a9b745fee40af2895920301,Capitalize on dimensionality increasing techniques for improving face recognition grand challenge performance,"Capitalize on Dimensionality Increasing +Techniques for Improving Face Recognition +Grand Challenge Performance +Chengjun Liu"
08903bf161a1e8dec29250a752ce9e2a508a711c,Joint Dimensionality Reduction and Metric Learning: A Geometric Take,"Joint Dimensionality Reduction and Metric Learning: A Geometric Take Mehrtash Harandi 1 2 Mathieu Salzmann 3 Richard Hartley 2 1"
+08847df8ea5b22c6a2d6d75352ef6270f53611de,Using k-Poselets for Detecting People and Localizing Their Keypoints,"Using k-poselets for detecting people and localizing their keypoints +Georgia Gkioxari∗, Bharath Hariharan∗, Ross Girshick and Jitendra Malik +University of California, Berkeley - Berkeley, CA 94720"
08e24f9df3d55364290d626b23f3d42b4772efb6,Enhancing facial expression classification by information fusion,"ENHANCING FACIAL EXPRESSION CLASSIFICATION BY INFORMATION FUSION I. Buciu1, Z. Hammal 2, A. Caplier2, N. Nikolaidis 1, and I. Pitas 1 @@ -10777,6 +37282,32 @@ phone: + 33(0476)574363, fax: + 33(0476)57 47 90, email: web: http://www.aiia.csd.auth.gr 8031 Grenoble, France web: http://www.lis.inpg.fr"
+08ff22f76a567fcbc1afec6bfbf957a560cfadc7,Exploring Person Context and Local Scene Context for Object Detection,"Exploring Person Context and Local Scene Context for Object Detection +Saurabh Gupta∗ +UC Berkeley +Bharath Hariharan∗ +Facebook AI Research +Jitendra Malik +UC Berkeley"
+08b0664fd37cd434201a1b37c20c0919833a6ff1,Online Multi-Object Tracking with Historical Appearance Matching and Scene Adaptive Detection Filtering,"Online Multi-Object Tracking with Historical Appearance Matching and +Scene Adaptive Detection Filtering +Young-chul Yoon Abhijeet Boragule Young-min Song Kwangjin Yoon Moongu Jeon +Gwangju Institute of Science and Technology +23 Cheomdangwagi-ro, Buk-gu, Gwangju, 61005, South Korea +{zerometal9268, abhijeet, sym, yoon28, +(cid:11)(cid:36)(cid:57)(cid:54)(cid:54)(cid:3)(cid:21)(cid:19)(cid:20)(cid:27)(cid:12) +(cid:20)(cid:17)(cid:3)(cid:44)(cid:81)(cid:87)(cid:85)(cid:82)(cid:71)(cid:88)(cid:70)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:11)(cid:87)(cid:72)(cid:80)(cid:83)(cid:82)(cid:85)(cid:68)(cid:79)(cid:3)(cid:72)(cid:85)(cid:85)(cid:82)(cid:85)(cid:86)(cid:3)(cid:71)(cid:88)(cid:85)(cid:76)(cid:81)(cid:74)(cid:3)(cid:87)(cid:85)(cid:68)(cid:70)(cid:78)(cid:76)(cid:81)(cid:74)(cid:12)"
+08ca2a2a543ee74e2bd6585e0a059b30aae65d30,Semantic Video Segmentation with Using Ensemble of Particular Classifiers and a Deep Neural Network for Systems of Detecting Abnormal Situations,"IT in Industry, vol. 6, 2018 Published online 09-Feb-2018 +Semantic Video Segmentation with Using Ensemble +of Particular Classifiers and a Deep Neural Network +for Systems of Detecting Abnormal Situations +O. Amosov, Y. Ivanov, S. Zhiganov +Department of Industrial Electronics +Komsomolsk-on-Amur State Technical University +Komsomolsk-on-Amur, Russia"
+0874a262c2ec7082658cbfc55892ec6e5ca6a374,CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video,"CATDET: CASCADED TRACKED DETECTOR FOR EFFICIENT OBJECT +DETECTION FROM VIDEO +Huizi Mao 1 Taeyoung Kong 1 William J. Dally 1 2"
0857281a3b6a5faba1405e2c11f4e17191d3824d,Face recognition via edge-based Gabor feature representation for plastic surgery-altered images,"Chude-Olisah et al. EURASIP Journal on Advances in Signal Processing 2014, 2014:102 http://asp.eurasipjournals.com/content/2014/1/102 R ES EAR CH @@ -10784,23 +37315,207 @@ Face recognition via edge-based Gabor feature representation for plastic surgery-altered images Chollette C Chude-Olisah1*, Ghazali Sulong1, Uche A K Chude-Okonkwo2 and Siti Z M Hashim1 Open Access"
+08b70ab782141a2d7003226a0f438a6aea0a0d46,Parametrizing Fully Convolutional Nets,"Under review as a conference paper at ICLR 2019 +PARAMETRIZING FULLY CONVOLUTIONAL NETS +WITH A SINGLE HIGH-ORDER TENSOR +Anonymous authors +Paper under double-blind review"
+081456e22734a2cdef442345f80182e84d1c6124,Approaches for Multi-Class Discriminant Analysis for Ranking Principal Components,"Approaches for Multi-Class Discriminant Analysis +for Ranking Principal Components +Tiene Andre Filisbino +Laborat´orio Nacional +Gilson Antonio Giraldi +Laborat´orio Nacional +Carlos Eduardo Thomaz +Departamento de Engenharia El´etrica +de Computac¸˜ao Cient´ıfica - LNCC +de Computac¸˜ao Cient´ıfica - LNCC +Centro Universit´ario da FEI +Petr´opolis, RJ 25651-075 +Email: +Petr´opolis, RJ 25651-075 +Email: +S˜ao Bernardo do Campo, SP 09850-901 +Email:"
+08f00e5adaba03628144dbc97daefa8ceb6e5322,Machine Vision based Fruit Classification and Grading-A Review,"International Journal of Computer Applications (0975 – 8887) +Volume 170 – No.9, July 2017 +Machine Vision based Fruit Classification and +Grading - A Review +Sapan Naik +Babu Madhav Institute of Information Technology +Uka Tarsadia University, +Bardoli, Surat, Gujarat, India."
+08ff3e9f5ad47e59592ad993348b817003b9c0e4,A Sequential Classifier for Hand Detection in the Framework of Egocentric Vision,"A Sequential Classifier for Hand Detection in the Framework of Egocentric Vision +Alejandro Betancourt1,2 +Miriam M. L´opez1 +Carlo S. Regazzoni1 +Matthias Rauterberg2 +Department of Naval, Electric, Electronic and Telecommunications Engineering - University of Genoa, Italy +Designed Intelligence Group, Department of Industrial Design - Eindhoven University of Technology, The Netherlands"
08f6745bc6c1b0fb68953ea61054bdcdde6d2fc7,Understanding Kin Relationships in a Photo,"Understanding Kin Relationships in a Photo Siyu Xia, Ming Shao, Student Member, IEEE, Jiebo Luo, Fellow, IEEE, and Yun Fu, Senior Member, IEEE"
+6d88fb85fe5c61bd65e0a373cd39fac81a19596a,DC-Image for Real Time Compressed Video Matching,"DC-Image for Real Time Compressed +Video Matching +Saddam Bekhet, Amr Ahmed and Andrew Hunter"
+6d96bf377c96e1dd9b43e9f12e0ee2a66543edbe,Viewpoint invariant 3D landmark model inference from monocular 2D images using higher-order priors,"011 IEEE International Conference on Computer Vision +978-1-4577-1102-2/11/$26.00 c(cid:13)2011 IEEE"
6dd052df6b0e89d394192f7f2af4a3e3b8f89875,A literature survey on Facial Expression Recognition using Global Features,"International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-2, Issue-4, April 2013 A literature survey on Facial Expression Recognition using Global Features Vaibhavkumar J. Mistry, Mahesh M. Goyani"
+6d84d92d9ed6c226f0cc6401bc425a23432c9f96,Autism spectrum disorders: clinical and research frontiers.,"Downloaded from +dc.bmj.com +on 22 May 2008 +Autism spectrum disorders: clinical and research +frontiers +E B Caronna, J M Milunsky and H Tager-Flusberg +Arch. Dis. Child. +doi:10.1136/adc.2006.115337 +2008;93;518-523; originally published online 27 Feb 2008; +Updated information and services can be found at: +http://adc.bmj.com/cgi/content/full/93/6/518 +These include: +References +This article cites 70 articles, 25 of which can be accessed free at: +http://adc.bmj.com/cgi/content/full/93/6/518#BIBL +Rapid responses +You can respond to this article at: +http://adc.bmj.com/cgi/eletter-submit/93/6/518 +Email alerting +service"
6dd5dbb6735846b214be72983e323726ef77c7a9,A Survey on Newer Prospective Biometric Authentication Modalities,"Josai Mathematical Monographs vol. 7 (2014), pp. 25-40 A Survey on Newer Prospective Biometric Authentication Modalities Narishige Abe, Takashi Shinzaki"
6d10beb027fd7213dd4bccf2427e223662e20b7d,User Adaptive and Context-Aware Smart Home Using Pervasive and Semantic Technologies,"Publishing CorporationJournal of Electrical and Computer EngineeringVolume 2016, Article ID 4789803, 20 pageshttp://dx.doi.org/10.1155/2016/4789803"
+6d500b0c342c1cf23efff049ef121bcf5e606ea1,Real-Time Category-Based and General Obstacle Detection for Autonomous Driving,"Real-time category-based and general obstacle detection for autonomous driving +Noa Garnett +Uri Verner +Ariel Ayash +Shai Silberstein +Vlad Goldner +Shaul Oron +Rafi Cohen +Ethan Fetaya +Kobi Horn +Dan Levi +Advanced Technical Center Israel, General Motors R&D +Hamada 7, Herzlyia, Israel"
+6dd007b6e518a3aa96111028c4664f2647e5e81a,3D Face Synthesis Driven by Personality Impression,"D Face Synthesis Driven by Personality Impression +Yining Lang1 Wei Liang1 Yujia Wang1 Lap-Fai Yu2 +Beijing Institute of Technology +University of Massachusetts Boston"
+6d6bb981bc8470de23e30890bd96a76ffd2b7ced,The Eyes Are the Windows to the Mind: Direct Eye Gaze Triggers the Ascription of Others' Minds.,"669124 PSPXXX10.1177/0146167216669124Personality and Social Psychology BulletinKhalid et al. +research-article2016 +Article +The Eyes Are the Windows to +the Mind: Direct Eye Gaze Triggers +the Ascription of Others’ Minds +Saara Khalid1, Jason C. Deska1, and Kurt Hugenberg1 +Personality and Social +Psychology Bulletin +016, Vol. 42(12) 1666 –1677 +© 2016 by the Society for Personality +nd Social Psychology, Inc +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0146167216669124 +pspb.sagepub.com"
+6d432962055a8c521e6b388d5a0a2140a0019a5e,Sensor network reconfiguration and big multimedia data fusion for situational awareness in smart environments,"Sensor network reconfiguration and big multimedia data fusion for situational +wareness in smart environments +Z. Akhtar, C. Drioli, M. Farinosi, G. Ferrin, G.L. Foresti, N. Martinel, C. Micheloni, C. Piciarelli, D. +Salvati, L. Snidaro and M. Vernier +AVIRES Lab - Department of Mathematics and Computer Science, Università degli Studi di Udine +Via delle Scienze, 206, 33100 Udine - Italy +last years, an +INTRODUCTION +increasing number of +environments have been enhanced with smart +sensors and have become more and more smart and +self-organizing [1]. Situational awareness (SA) in +these wide areas covers a huge range of topics and +hallenges [2]. As matter of fact, understanding +ctivities +for situation assessment cannot be +chieved locally but it requires to widen as much as +possible the monitored area. Several different and +new problems must be investigated from the use of +single sensors able to adapt internal or external"
6dddf1440617bf7acda40d4d75c7fb4bf9517dbb,"Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking","JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, MM YY Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking Di Kang, Zheng Ma, Member, IEEE, Antoni B. Chan Senior Member, IEEE,"
+6d902439b736a7546dd8872b307fb760087ca629,SIFT Meets CNN: A Decade Survey of Instance Retrieval,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +SIFT Meets CNN: +A Decade Survey of Instance Retrieval +Liang Zheng, Yi Yang, and Qi Tian, Fellow, IEEE"
+6d5b0f6e5258d370f9af8a2cebf035fe61905db1,Gazefinder as a clinical supplementary tool for discriminating between autism spectrum disorder and typical development in male adolescents and adults,"Fujioka et al. Molecular Autism (2016) 7:19 +DOI 10.1186/s13229-016-0083-y +Open Access +R ES EAR CH +Gazefinder as a clinical supplementary tool +for discriminating between autism +spectrum disorder and typical development +in male adolescents and adults +Toru Fujioka1,2,3, Keisuke Inohara1,4, Yuko Okamoto2,3, Yasuhiro Masuya1, Makoto Ishitobi1,5, Daisuke N. Saito2,3,6, +Minyoung Jung2,3, Sumiyoshi Arai2,3, Yukiko Matsumura1, Takashi X. Fujisawa2,3, Kosuke Narita7, Katsuaki Suzuki3,8,9, +Kenji J. Tsuchiya3,8,9, Norio Mori3,8,9, Taiichi Katayama3, Makoto Sato2,3,10,11, Toshio Munesue3,12, +Hidehiko Okazawa2,3,6, Akemi Tomoda2,3, Yuji Wada1,2,3 and Hirotaka Kosaka1,2,3*"
+6d973fb5f682c491be94aa40a184a1707a8dc24a,Combining Multiple Image Segmentations by Maximizing Expert Agreement,"Combining Multiple Image Segmentations by +Maximizing Expert Agreement +Joni-Kristian Kamarainen, Lasse Lensu, and Tomi Kauppi +Machine Vision and Pattern Recognition Laboratory +Department of Information Technology +Lappeenranta University of Technology +P.O. Box 20, FI-53851 Lappeenranta, Finland +http://www2.it.lut.fi/mvpr/"
+6d79999f8dc0cb9f86a87eaa2eb313a4eaeb2e5a,Instructions for use Title Bregman pooling : feature-space local pooling for imageclassification,"Title +Bregman pooling : feature-space local pooling for image +lassification +Author(s) +Najjar, Alameen; Ogawa, Takahiro; Haseyama, Miki +Citation +International Journal of Multimedia Information Retrieval +Issue Date +015-09-04 +Doc URL +http://hdl.handle.net/2115/62753 +Right +The final publication is available at link.springer.com +rticle (author version) +Additional +Information +Information BP.pdf +Instructions for use +Hokkaido University Collection of Scholarly and Academic Papers : HUSCAP"
+6da06fc70f32454f7841b153c582e65aed7047e9,Deep pipelined one-chip FPGA implementation of a real-time image-based human detection algorithm,"NAOSITE: Nagasaki University's Academic Output SITE +Title +Deep pipelined one-chip FPGA implementation of a real-time image-based +human detection algorithm +Author(s) +Negi, Kazuhiro; Dohi, Keisuke; Shibata, Yuichiro; Oguri, Kiyoshi +Citation +011, Article number6132679; 2011 +Issue Date +011-12 +Right +http://hdl.handle.net/10069/29887 +© 2011 IEEE. Personal use of this material is permitted. Permission from +IEEE must be obtained for all other uses, in any current or future media, +including reprinting/republishing this material for advertising or +promotional purposes, creating new collective works, for resale or +redistribution to servers or lists, or reuse of any copyrighted component of +this work in other works. +This document is downloaded at: 2018-12-08T05:46:10Z +http://naosite.lb.nagasaki-u.ac.jp"
+6dc17e91c0b02ff3b9e5c9283924279c28641db7,A Methodology for Extracting Standing Human Bodies from Single Images,"Invention Journal of Research Technology in Engineering & Management (IJRTEM) ISSN: 2455-3689 +www.ijrtem.com ǁ Volume 1 ǁ Issue 8 ǁ +A Methodology for Extracting Standing Human Bodies from Single Images +Dr. Y. Raghavender Rao1, N. Devadas Naik2 +Head ECE JNTUHCEJ Jagtityal +Asst professor Sri Chaitanya engineering college"
6d4b5444c45880517213a2fdcdb6f17064b3fa91,Harvesting Image Databases from The Web,"Journal of Information Engineering and Applications ISSN 2224-5782 (print) ISSN 2225-0506 (online) Vol 2, No.3, 2012 @@ -10815,6 +37530,75 @@ G.H.Raisoni College of Engg. & Mgmt.,Pune,India" 6d8c9a1759e7204eacb4eeb06567ad0ef4229f93,"Face Alignment Robust to Pose, Expressions and Occlusions","Face Alignment Robust to Pose, Expressions and Occlusions Vishnu Naresh Boddeti†, Myung-Cheol Roh†, Jongju Shin, Takaharu Oguri, Takeo Kanade"
+6dd0597f8513dc100cd0bc1b493768cde45098a9,Learning to parse images of articulated bodies,"Learning to parse images of articulated bodies +Deva Ramanan +Toyota Technological Institute at Chicago +Chicago, IL 60637"
+6db59b031406546682a773baed2caed529aaf37c,Inferring the semantics of direction signs in public places,"Inferring the Semantics of Direction Signs in Public Places +J´erˆome Maye∗, Luciano Spinello∗†, Rudolph Triebel∗, and Roland Siegwart∗ +Autonomous Systems Lab, ETH Zurich, Switzerland +email: {jerome.maye, rudolph.triebel, +Social Robotics Lab, Department of Computer Science, University of Freiburg, Germany +email:"
+6d2b633743178bd5aac1073b60d81ceb41933a4a,Carried Object Detection Based on an Ensemble of Contour Exemplars,"Carried Object Detection based on an Ensemble +of Contour Exemplars +Farnoosh Ghadiri1, Robert Bergevin1, Guillaume-Alexandre Bilodeau2 +LVSN-REPARTI, Universit(cid:19)e Laval +LITIV lab., Polytechnique Montr(cid:19)eal"
+6dfa82f00ec6faee1db319c1e306ae779cfc1c36,"The Role of Methodology and Spatiotemporal Scale in Understanding Environmental Change in Peri-Urban Ouagadougou, Burkina Faso","Remote Sens. 2013, 5, 1465-1483; doi:10.3390/rs5031465 +OPEN ACCESS +ISSN 2072-4292 +www.mdpi.com/journal/remotesensing +Article +The Role of Methodology and Spatiotemporal Scale in +Understanding Environmental Change in Peri-Urban +Ouagadougou, Burkina Faso +Yonatan Kelder 1,*, Thomas Theis Nielsen 1 and Rasmus Fensholt 2 +Roskilde University, Universitetsvej 1, ENSPAC House 0.2, Roskilde 4000, Denmark; +E-Mail: +Copenhagen University, Institute for Geography and Geology, Øster Voldgade 10, +Copenhagen K 1350, Denmark; E-Mail: +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +45-30-49-14-92. +Received: 18 January 2013; in revised form: 24 February 2013 / Accepted: 15 March 2013 / +Published: 19 March 2013"
+6d7ba173121edd5defadfde04f7c1e7bc72859c2,The study of autism as a distributed disorder.,"MENTAL RETARDATION AND DEVELOPMENTAL DISABILITIES +RESEARCH REVIEWS 13: 85 – 95 (2007) +THE STUDY OF AUTISM AS A +DISTRIBUTED DISORDER +Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, California +Department of Cognitive Science, University of California, San Diego, California +Ralph-Axel Mu¨ ller1,2* +Past autism research has often been dedicated to tracing the +auses of the disorder to a localized neurological abnormality, a single +functional network, or a single cognitive-behavioral domain. +In this +review, I argue that autism is a ‘‘distributed disorder’’ on various levels of +study (genetic, neuroanatomical, neurofunctional, behavioral). ‘‘Localizing’’ +models are therefore not promising. The large array of potential genetic +risk factors suggests that multiple (or all) emerging functional brain net- +works are affected during early development. This is supported by wide- +spread growth abnormalities throughout the brain. Interactions during +development between affected functional networks and atypical experi- +ential effects (associated with atypical behavior) in children with autism +further complicate the neurological bases of the disorder, resulting in"
+6dc3b8a5fdceaea4b32df8552cbb5a22ef83c197,Speech-Based Visual Question Answering,"Speech-Based Visual Question Answering +Ted Zhang +KU Leuven +Dengxin Dai +ETH Zurich +Tinne Tuytelaars +KU Leuven +Marie-Francine Moens +KU Leuven"
+6d6a106caef228b3eee1f5765740938a534db828,Density-based clustering: A ‘landscape view’ of multi-channel neural data for inference and dynamic complexity analysis,"RESEARCH ARTICLE +Density-based clustering: A ‘landscape view’ of +multi-channel neural data for inference and +dynamic complexity analysis +Gabriel Baglietto1,2*, Guido Gigante3,4, Paolo Del Giudice1,3 +INFN-Roma1, Italian National Institute for Nuclear Research (INFN), Rome, Italy, 2 IFLYSIB Instituto de +Fı´sica de Lı´quidos y Sistemas Biolo´gicos (UNLP-CONICET), La Plata, Argentina, 3 Italian Institute of Health +(ISS), Rome, Italy, 4 Mperience srl, Rome, Italy"
6d618657fa5a584d805b562302fe1090957194ba,Human Facial Expression Recognition based on Principal Component Analysis and Artificial Neural Network,"Full Paper NNGT Int. J. of Artificial Intelligence , Vol. 1, July 2014 Human Facial Expression Recognition based @@ -10824,6 +37608,24 @@ Laboratory of Automatic and Signals Annaba (LASA) , Department of electronics, F Zermi.Narima, Ramdani.M, Saaidia.M Badji-Mokhtar University, P.O.Box 12, Annaba-23000, Algeria. E-Mail :"
+6d7dabc58f53c0233d6d593a8fee76d1c7f44033,Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches,"Sensors 2012, 12, 15638-15670; doi:10.3390/s121115638 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +Robust Observation Detection for Single Object Tracking: +Deterministic and Probabilistic Patch-Based Approaches +Mohd Asyraf Zulkifley 1,*, David Rawlinson 2 and Bill Moran 2 +Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built +Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Malaysia +Department of Electrical and Electronic Engineering, The University of Melbourne, VIC 3010, +Australia; E-Mails: (D.R.); (B.M.) +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +603-8921-6335. +Received: 18 September 2012; in revised form: 5 November 2012 / Accepted: 5 November 2012 / +Published: 12 November 2012 +the problems of blurring, moderate deformation,"
6d66c98009018ac1512047e6bdfb525c35683b16,Face Recognition Based on Fitting a 3D Morphable Model,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 25, NO. 9, SEPTEMBER 2003 Face Recognition Based on Fitting a 3D Morphable Model @@ -10832,6 +37634,18 @@ Volker Blanz and Thomas Vetter, Member, IEEE" Computer and System Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt A. Abbas, M. I. Khalil, S. Abdel-Hay, H. M. Fahmy Expression and Illumination Invariant Preprocessing"
+013e9e0f712d8caa89dd0881ab8dcf90d687ba50,Face Recognition using LBP and LVQ Classifier,"Face Recognition using LBP and LVQ Classifier +Abdul Quyoom +Department of Computer Science Engineering +Central University of Rajasthan +Ajmer, Rajasthan, India +each human"
+01b5d63b60bcc35aa8bead42ea52a517f879bfc9,Solving Uncalibrated Photometric Stereo Using Total Variation,"Noname manuscript No. +(will be inserted by the editor) +Solving Uncalibrated Photometric Stereo using Total +Variation +Yvain Qu´eau · Fran¸cois Lauze · Jean-Denis Durou +the date of receipt and acceptance should be inserted later"
0145dc4505041bf39efa70ea6d95cf392cfe7f19,Human action segmentation with hierarchical supervoxel consistency,"Human Action Segmentation with Hierarchical Supervoxel Consistency Jiasen Lu1, Ran Xu1 Jason J. Corso2 Department of Computer Science and Engineering, SUNY at Buffalo. 2Department of EECS, University of Michigan. @@ -10872,6 +37686,35 @@ CHILI Laboratory École polytechnique fédérale École polytechnique fédérale École polytechnique fédérale"
+014844a9e6ae39a101fb79f103aa047699f88246,Interpretable Counting for Visual Question Answering,"Under review as a conference paper at ICLR 2018 +INTERPRETABLE COUNTING FOR VISUAL QUESTION +ANSWERING +Anonymous authors +Paper under double-blind review"
+017229c2df23c542b30c59f4a5eeb747e3d34729,Efficient Object Recognition using Convolution Neural Networks Theorem,"International Journal of Computer Applications (0975 – 8887) +Volume 161 – No 2, March 2017 +Efficient Object Recognition using Convolution Neural +Networks Theorem +Aarushi Thakral +VIT University +Vellore +Tamil Nadu +Shaurya Shekhar +VIT University +Vellore +Tamil Nadu +to overcome"
+0183eff3a60f44bc6e4bcade37518f6470af3437,Human Identification Using Temporal Information Preserving Gait Template,"Human Identification Using Temporal +Information Preserving Gait Template +Chen Wang, Junping Zhang, IEEE Member, Liang Wang, IEEE Senior Member, +Jian Pu, and Xiaoru Yuan, IEEE Member"
+01c9f0be6a300f385274b72a5463a650e51e300a,Support Vector Data Description based on PCA features for face detection,"SUPPORT VECTOR DATA DESCRIPTION BASED ON PCA FEATURES FOR FACE +DETECTION +Ver´onica Vilaplana and Ferran Marqu´es +phone: + (34)934011066, fax: + (34)934016447, email: +Jordi Girona, 1-3, 08034 Barcelona, SPAIN +Image Processing Group, Universitat Polit`ecnica de Catalunya +web: gps-tsc.upc.es/imatge"
01c8d7a3460422412fba04e7ee14c4f6cdff9ad7,Rule Based System for Recognizing Emotions Using Multimodal Approach,"(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No. 7, 2013 Rule Based System for Recognizing Emotions Using @@ -10880,6 +37723,16 @@ Preeti Khanna Information System SBM, SVKM’s NMIMS Mumbai, India"
+01d785bb989850019001a418a16202fd7502ac14,Hierarchical object detection and tracking with an Implicit Shape Model,"Hierarchical object detection and tracking with an Implicit Shape +Model +K. Jüngling1, S. Becker1, and M. Arens1 +Object Recognition, Fraunhofer IOSB, Ettlingen, Germany"
+01f5689a4010ae14ca444c36bec81f12ce528912,"Extended Fast Search Clustering Algorithm: Widely Density Clusters, No Density Peaks","EXTENDED FAST SEARCH CLUSTERING +ALGORITHM: WIDELY DENSITY +CLUSTERS, NO DENSITY PEAKS +Zhang WenKai1 and Li Jing2 +,2School of Computer Science and Technology, University of Science and +Technology of China, Hefei, 230026, China"
0163d847307fae508d8f40ad193ee542c1e051b4,Classemes and Other Classifier-Based Features for Efficient Object Categorization,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007 Classemes and Other Classifier-based Features for Efficient Object Categorization @@ -10909,21 +37762,185 @@ Laiyun Qing1,2, Shiguang Shan2, Wen Gao1,2 ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing, China, 100080 Graduate School, CAS, Beijing, China, 100080 Emails: {lyqing, sgshan, wgao}jdl.ac.cn"
+014e1186209e4f942f3b5ba29b6b039c8e99ad88,Social interactions: A first-person perspective,"Social Interactions: A First-Person +Perspective +Alireza Fathi, Jessica K. Hodgins, James M. Rehg +CVPR 2012 +Bora Çelikkale"
+0135747b4d3c9a2d983f7d0d9f4c39e094825149,Embedded wavelet-based face recognition under variable position,"Embedded wavelet-based face recognition under variable +position +Pascal Cotreta, Stéphane Chevobbea and Mehdi Darouicha +CEA, LIST, Laboratoire Adéquation Algorithme Architecture, Gif-sur-Yvette, F-91191 France"
014e3d0fa5248e6f4634dc237e2398160294edce,What does 2D geometric information really tell us about 3D face shape?,"Int J Comput Vis manuscript No. (will be inserted by the editor) What does 2D geometric information really tell us about D face shape? Anil Bas1 · William A. P. Smith1 Received: date / Accepted: date"
+01ababc0985143ad57320b0599fb2f581d79d3c2,Unobtrusive Low Cost Pupil Size Measurements using Web cameras,"Unobtrusive Low Cost Pupil Size Measurements using Web cameras +Sergios Petridis, Theodoros Giannakopoulos and Costantine D. Spyropoulos +National Center for Scientific Research ""Demokritos"" +Unobtrusive every day health monitoring can be of important use for the elderly population. In +particular, pupil size may be a valuable source of information, since, apart from pathological +ases, it can reveal the emotional state, the fatigue and the ageing. To allow for unobtrusive +monitoring to gain acceptance, one should seek for efficient methods of monitoring using com- +mon low-cost hardware. This paper describes a method for monitoring pupil sizes using a +ommon web camera in real time. Our method works by first detecting the face and the eyes +rea. Subsequently, optimal iris and sclera location and radius, modelled as ellipses, are found +using efficient filtering. Finally, the pupil center and radius is estimated by optimal filtering +within the area of the iris. Experimental result show both the efficiency and the effectiveness +of our approach. +Keywords: video analysis, eye tracking, pupil size estimation, physiological measurements +Motivation +Unobtrusive every day health monitoring can be of im- +portant use for the elderly population. +In particular, pupil +size may be a valuable source of information, since, apart +from pathological cases, it can reveal the emotional state, the"
+016473c5b809ff55304a2923c36eaf58f02f02e4,DensePose: Dense Human Pose Estimation In The Wild,"DensePose: Dense Human Pose Estimation In The Wild +Rıza Alp G¨uler∗ +Natalia Neverova +Iasonas Kokkinos +INRIA-CentraleSup´elec +Facebook AI Research +Facebook AI Research +Figure 1: Dense pose estimation aims at mapping all human pixels of an RGB image to the 3D surface of the human body. +spondences for 50K images, and train DensePose-RCNN to densely regress UV coordinates at multiple frames per second. +Right: Partitioning and UV parametrization of the body surface."
+013ae78fc6bd26a13799fe2e07a6ad363aca9ba7,Inspiring Computer Vision System Solutions,"Inspiring Computer Vision System Solutions +Julian Zilly 1 Amit Boyarski 2 Micael Carvalho 3 Amir Atapour Abarghouei 4 Konstantinos Amplianitis 5 +Aleksandr Krasnov 6 Massimiliano Mancini 7 Hernán Gonzalez 8 Riccardo Spezialetti 9 +Carlos Sampedro Pérez 10 Hao Li 11"
+0155c2921f060a95c0eca8c64bf62a1eaac591e4,Spatiotemporal CNNs for Pornography Detection in Videos,"Spatiotemporal CNNs for Pornography +Detection in Videos +Murilo Varges da Silva1,2 and Aparecido Nilceu Marana3 +UFSCar - Federal University of Sao Carlos, Sao Carlos, SP, Brazil +IFSP - Federal Institute of Education of Sao Paulo, Birigui, SP, Brazil +UNESP - Sao Paulo State University, Bauru, SP, Brazil"
011e6146995d5d63c852bd776f782cc6f6e11b7b,Fast Training of Triplet-Based Deep Binary Embedding Networks,"Fast Training of Triplet-based Deep Binary Embedding Networks Bohan Zhuang, Guosheng Lin, Chunhua Shen∗, Ian Reid The University of Adelaide; and Australian Centre for Robotic Vision"
+01350214f850f43d72268df4f98b05901fbbe06c,1 Deep convolutional neural networks for detection of 2 polar mesocyclones from satellite mosaics 3,"Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 19 September 2018 doi:10.20944/preprints201809.0361.v1 +Article +Deep convolutional neural networks for detection of +polar mesocyclones from satellite mosaics +Mikhail Krinitskiy 1,*, Polina Verezemskaya 1,2, Kirill Grashchenkov1,3, Natalia Tilinina1, +Sergey Gulev1 and Matthew Lazzara 4 +Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia; +Research Computing Center of Lomonosov Moscow State University, Moscow, Russia +Moscow Institute of Physics and Technology, Moscow, Russia +University of Wisconsin-Madison and Madison Area Technical College, Madison, Wisconsin, USA +* Correspondence: Tel.: +7-926-141-6200"
+01f42436042ddaa48998c87109cbe46cad6e7e52,Schedtask: a hardware-assisted task scheduler,"SchedTask: A Hardware-Assisted Task Scheduler +Prathmesh Kallurkar∗ +Microarchitecture Research Lab +Intel Corporation +Smruti R. Sarangi +Department of Computer Science +Indian Institute of Technology Delhi"
+014b4335d055679bc680a6ceb6f1a264d8ce8a4a,Are You Sure You Want To Do That? Classification with Verification,"Are You Sure You Want To Do That? +Classification with Verification +Harris Chan∗ +Atef Chaudhury∗ +Kevin Shen∗"
+01959ef569f74c286956024866c1d107099199f7,VQA: Visual Question Answering,"VQA: Visual Question Answering +www.visualqa.org +Stanislaw Antol∗1, Aishwarya Agrawal∗1, Jiasen Lu, Margaret Mitchell, +Dhruv Batra, C. Lawrence Zitnick, Devi Parikh"
+016860404c0926dda53b9bf4745f3eb9708fa1d2,Iterative hypothesis testing for multi-object tracking in presence of features with variable reliability,"Iterative hypothesis testing for multi-object tracking in presence of +features with variable reliability +Amit Kumar K.C.1, Damien Delannay2 and Christophe De Vleeschouwer1 +ISPGroup, ELEN Department, Universit´e catholique de Louvain, Belgium +{amit.kc, +Keemotion, Belgium"
+011c5bb510c9a4c24e2fc07e7464fa8493237058,Accelerating Nearest Neighbor Search on Manycore Systems,"Accelerating Nearest Neighbor Search on Manycore +Systems +Lawrence Cayton +Max Planck Institute +Tübingen, Germany"
+01a152e7ca6accce4fa52e29b27feb76418583fb,Tracking Multiple High-Density Homogeneous Targets,"IEEE TRANSACTION ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. X, NO. X, XXXX +Tracking multiple high-density homogeneous targets +Fabio Poiesi and Andrea Cavallaro"
+0144b29bde2579e0a1b8ab3a38306c5621a5c30b,Top-Down Visual Saliency via Joint CRF and Dictionary Learning,"Top-Down Visual Saliency via Joint CRF and Dictionary Learning +Jimei Yang and Ming-Hsuan Yang +University of California at Merced"
+01915181692c821cc5a0a703047bd5b07c1f9af5,Cross-Caption Coreference Resolution for Automatic Image Understanding,"Proceedings of the Fourteenth Conference on Computational Natural Language Learning, pages 162–171, +Uppsala, Sweden, 15-16 July 2010. c(cid:13)2010 Association for Computational Linguistics"
0181fec8e42d82bfb03dc8b82381bb329de00631,Discriminative Subspace Clustering,"Discriminative Subspace Clustering Vasileios Zografos∗1, Liam Ellis†1, and Rudolf Mester‡1 2 CVL, Dept. of Electrical Engineering, Link¨oping University, Link¨oping, Sweden VSI Lab, Computer Science Department, Goethe University, Frankfurt, Germany"
+01ece1dd9a0a2a7289d791625c6c7446d38584e7,A Comparative Analysis of Classification Algorithms Applied to M5AIE-Extracted Human Poses,"A Comparative Analysis of Classification Algorithms +Applied to M5AIE-Extracted Human Poses +Andr´e Brand˜ao, Leandro A. F. Fernandes, and Esteban Clua +MediaLab-UFF, Instituto de Computac¸˜ao, Universidade Federal Fluminense +Email: +CEP 24210-240 Niter´oi, RJ, Brazil"
+01e812ad00b7743e9b24aa070a24023f05710b8b,A Distributed Representation Based Query Expansion Approach for Image Captioning,"Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics +nd the 7th International Joint Conference on Natural Language Processing (Short Papers), pages 106–111, +Beijing, China, July 26-31, 2015. c(cid:13)2015 Association for Computational Linguistics"
+019a95631c49011330773e953194a0c73c61f3f0,Impairments in monkey and human face recognition in 2-year-old toddlers with Autism Spectrum Disorder and Developmental Delay.,"DOI: 10.1111/j.1467-7687.2006.00543.x +Blackwell Publishing Ltd +Face recognition in ASD +PAPER +Impairments in monkey and human face recognition in +-year-old toddlers with Autism Spectrum Disorder and +Developmental Delay +Katarzyna Chawarska and Fred Volkmar +Child Study Center, Yale University School of Medicine, New Haven, CT, USA"
+013e0fe2d203eaa33a4b42d057688815116cc6bb,Recognizing Car Fluents from Video,"Recognizing Car Fluents from Video +Bo Li1,∗, Tianfu Wu2, Caiming Xiong3,∗ and Song-Chun Zhu2 +Beijing Lab of Intelligent Information Technology, Beijing Institute of Technology +Department of Statistics, University of California, Los Angeles +Metamind Inc. +{tfwu,"
0113b302a49de15a1d41ca4750191979ad756d2f,Matching Faces with Textual Cues in Soccer Videos,"424403677/06/$20.00 ©2006 IEEE ICME 2006"
+014b8df0180f33b9fea98f34ae611c6447d761d2,Facial feature tracking and expression recognition for sign language,"Facial Feature Tracking and Expression Recognition +for Sign Language +˙Ismail Arı +Computer Engineering +Bo˜gazic.i University +˙Istanbul, Turkey +Email: +Asli Uyar +Computer Engineering +Bo˜gazic.i University +˙Istanbul, Turkey +Email: +Lale Akarun +Computer Engineering +Bo˜gazic.i University +˙Istanbul, Turkey +Email:"
+01e5eb25e262afa4289d39b964c837a22a32f5a2,Cricket activity detection,"Cricket Activity Detection +Ashok Kumar(11164) +Javesh Garg(11334) +March 1, 2014"
+0136bf1d3747770a7fb4fcdeaf0b4b195815ed67,Weighted Fourier Series Representation and Its Application to Quantifying the Amount of Gray Matter,"Weighted Fourier Series Representation and +Its Application to Quantifying the Amount +of Gray Matter +Moo K. Chung*, Kim M. Dalton, Li Shen, Alan C. Evans, and Richard J. Davidson"
+069f2092c5d22e6d4c1e27c30e18dc63848fa3c3,A comparison of low-level features for visual attribute recognition,"Görsel Nitelik Ö˘grenmede Alt-Düzey Özniteliklerin +Kar¸sıla¸stırılması +A Comparison of Low-level Features for Visual +Attribute Recognition +Emine Gül DANACI +Bilgisayar Mühendisli˘gi Bölümü +Hacettepe Üniversitesi +Ankara, Türkiye +Nazlı ˙IK˙IZLER C˙INB˙I¸S +Bilgisayar Mühendisli˘gi Bölümü +Hacettepe Üniversitesi +Ankara, Türkiye +Özetçe —Görsel nitelik ö˘grenme ve kullanımı, son yıllarda +ilgisayarlı görü alanında sıklıkla ara¸stırılmaya ba¸slanmı¸s bir +konudur. Bu çalı¸smamızda, görsel nitelik ö˘grenmeye, hangi alt +düzey özniteliklerin daha anlamlı ve verimli sonuçlar verdi˘gini +ra¸stırmayı amaçlamaktayız. Bu kapsamda, renk ve ¸sekil bil- +gisini farklı detaylarda ele alan alt düzey özniteliklerin, nitelik +sınıflandırmaya katkısı ara¸stırılmı¸s, ve deneysel olarak de˘ger- +lendirilmi¸stir. Elde edilen sonuçlar, özellikle renk ve yerel ¸sekil"
0601416ade6707c689b44a5bb67dab58d5c27814,Feature Selection in Face Recognition: A Sparse Representation Perspective,"Feature Selection in Face Recognition: A Sparse Representation Perspective Allan Y. Yang @@ -10935,6 +37952,11 @@ University of California at Berkeley Technical Report No. UCB/EECS-2007-99 http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS-2007-99.html August 14, 2007"
+06e15d0d6f92a11bb5b46b5a3e0250cccc452c92,Diagnostic Features of Emotional Expressions Are Processed Preferentially,"Diagnostic Features of Emotional Expressions Are +Processed Preferentially +Elisa Scheller1, Christian Bu¨ chel2, Matthias Gamer2* +Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg, Germany, 2 Department of Systems Neuroscience, University Medical Center +Hamburg-Eppendorf, Hamburg, Germany"
064b797aa1da2000640e437cacb97256444dee82,Coarse-to-fine Face Alignment with Multi-Scale Local Patch Regression,"Coarse-to-fine Face Alignment with Multi-Scale Local Patch Regression Zhiao Huang Megvii Inc. @@ -10948,14 +37970,74 @@ Bor-Chun Chen, Yan-Ying Chen, Yin-Hsi Kuo, Winston H. Hsu" 0697bd81844d54064d992d3229162fe8afcd82cb,User-driven mobile robot storyboarding: Learning image interest and saliency from pairwise image comparisons,"User-driven mobile robot storyboarding: Learning image interest and saliency from pairwise image comparisons Michael Burke1"
+06cfc431b70ec6a6783284953a668984600e77e2,A Framework for Human Pose Estimation in Videos,"A Framework for Human Pose Estimation in +Videos +Dong Zhang and Mubarak Shah"
06262d6beeccf2784e4e36a995d5ee2ff73c8d11,Recognize Actions by Disentangling Components of Dynamics,"Recognize Actions by Disentangling Components of Dynamics Yue Zhao1, Yuanjun Xiong1,2, and Dahua Lin1 CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong 2Amazon Rekognition"
+0690ba31424310a90028533218d0afd25a829c8d,Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs,"Published as a conference paper at ICLR 2015 +SEMANTIC IMAGE SEGMENTATION WITH DEEP CON- +VOLUTIONAL NETS AND FULLY CONNECTED CRFS +Liang-Chieh Chen +Univ. of California, Los Angeles +George Papandreou ∗ +Google Inc. +Iasonas Kokkinos +CentraleSup´elec and INRIA +Kevin Murphy +Google Inc. +Alan L. Yuille +Univ. of California, Los Angeles"
+063f0e6afe13df9913617dbc2230ad4263a595bc,Loneliness and Hypervigilance to Social Cues in Females: An Eye-Tracking Study,"RESEARCH ARTICLE +Loneliness and Hypervigilance to Social Cues +in Females: An Eye-Tracking Study +Gerine M. A. Lodder1*, Ron H. J. Scholte1¤a, Ivar A. H. Clemens2, Rutger C. M. E. Engels1¤b, +Luc Goossens3, Maaike Verhagen1 +Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands, 2 Donders Institute for +Brain, Cognition, and Behaviour, Radboud University, Nijmegen, The Netherlands, 3 Research Group +School Psychology and Child and Adolescent Development, KU Leuven, Leuven, Belgium +¤a Current address: Praktikon, Nijmegen, The Netherlands +¤b Current address: The Trimbos Institute, Netherlands Institute of Mental Health and Addiction, Utrecht, +The Netherlands"
+06a23ffbd9752ce204197df59812b2ebd1a097ff,Feedforward semantic segmentation with zoom-out features,"Feedforward semantic segmentation with zoom-out features +Mohammadreza Mostajabi, Payman Yadollahpour and Gregory Shakhnarovich +Toyota Technological Institute at Chicago"
+06de3eab314437cc3ed08c3db5171a79c1f684c6,Boosting patch-based scene text script identification with ensembles of conjoined networks,"Boosting patch-based scene text script identification with +ensembles of conjoined networks +Lluis Gomez, Anguelos Nicolaou, Dimosthenis Karatzas +Computer Vision Center, Universitat Autonoma de Barcelona. Edifici O, Campus UAB, 08193 Bellaterra (Cerdanyola) +Barcelona, Spain. E-mail:"
+06774cc8b0ab364866beaf3efda1b2d012a7bcf9,MobileNetV2: Inverted Residuals and Linear Bottlenecks,"MobileNetV2: Inverted Residuals and Linear Bottlenecks +Mark Sandler Andrew Howard Menglong Zhu Andrey Zhmoginov Liang-Chieh Chen +{sandler, howarda, menglong, azhmogin, +Google Inc."
06d93a40365da90f30a624f15bf22a90d9cfe6bb,Learning from Candidate Labeling Sets,"Learning from Candidate Labeling Sets Idiap Research Institute and EPF Lausanne Luo Jie Francesco Orabona DSI, Universit`a degli Studi di Milano"
+06ef2ba33ec911aa0102fb938b53bd3cc36a475f,Introducing FoxFaces: A 3-in-1 Head Dataset,
+06992ca951456bb88523f702f904dfd23eb27c53,Using Mobile Platform to Detect and Alerts Driver Fatigue,"International Journal of Computer Applications (0975 – 8887) +Volume 123 – No.8, August 2015 +Using Mobile Platform to Detect and Alerts +Maysoon F. Abulkhair +Department of Information +Technology, Faculty of +Computing and Information +Technology, King Abdulaziz +University +B.P. 42808 Zip Code 21551- +Girl Section, Jeddah, Saudi +Arabia +Driver Fatigue +Hesham A. Salman +Department of Information +Systems +Faculty of Computing and +Information Technology King +Abdulaziz University +Lamiaa F. Ibrahim"
06e7e99c1fdb1da60bc3ec0e2a5563d05b63fe32,WhittleSearch: Image search with relative attribute feedback,"WhittleSearch: Image Search with Relative Attribute Feedback Adriana Kovashka, Devi Parikh and Kristen Grauman (Supplementary Material) @@ -10976,6 +38058,35 @@ feedback into the scoring function, revealing the two methods’ respective perf while both methods retrieve high-heeled shoes, only our method retrieves images that are as “open” s the target image. This is because using the proposed approach, the user was able to comment explicitly on the desired openness property."
+064aaad2a9ac5044b333714e61955631faee87fd,Face Recognition using Radial Curves and Back Propagation Neural Network for Frontal Faces under Various Challenges,"International Journal of Computer Applications (0975 – 8887) +International Conference on Advances in Science and Technology 2015 (ICAST 2015) +Face Recognition using Radial Curves and Back +Propagation Neural Network for frontal faces under +various challenges +Latasha Keshwani +Electronics and Telecommunication Department +Datta Meghe College of Engineering, Airoli, Mumbai +University, (MS), India"
+06e768d74f076b251d53b0c86fc9910d7243bdc6,Effective and efficient visual description based on local binary patterns and gradient distribution for object recognition,"Effective and efficient visual description based on local +inary patterns and gradient distribution for object +recognition +Chao Zhu +To cite this version: +Chao Zhu. Effective and efficient visual description based on local binary patterns and gradient +distribution for object recognition. Other. Ecole Centrale de Lyon, 2012. English. <NNT : +012ECDL0005>. <tel-00755644> +HAL Id: tel-00755644 +https://tel.archives-ouvertes.fr/tel-00755644 +Submitted on 21 Nov 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
066d71fcd997033dce4ca58df924397dfe0b5fd1,Iranian Face Database and Evaluation with a New Detection Algorithm,"(cid:1)(cid:2)(cid:3)(cid:4)(cid:5)(cid:3)(cid:4)(cid:6)(cid:7)(cid:3)(cid:8)(cid:9)(cid:6)(cid:10)(cid:3)(cid:11)(cid:3)(cid:12)(cid:3)(cid:13)(cid:9) (cid:3)(cid:4)(cid:14)(cid:6)(cid:15)(cid:16)(cid:3)(cid:17)(cid:18)(cid:3)(cid:11)(cid:5)(cid:19)(cid:4) (cid:20)(cid:5)(cid:11)(cid:21)(cid:6)(cid:3)(cid:6)(cid:22)(cid:9)(cid:20)(cid:6)(cid:10)(cid:9)(cid:11)(cid:9)(cid:8)(cid:11)(cid:5)(cid:19)(cid:4)(cid:6)(cid:23)(cid:17)(cid:24)(cid:19)(cid:2)(cid:5)(cid:11)(cid:21)(cid:25) (cid:26)(cid:11)(cid:5)(cid:8)(cid:17)(cid:6)(cid:27)(cid:1)(cid:9)(cid:22)(cid:8)(cid:18)(cid:1)(cid:28)(cid:12)(cid:6)(cid:29)(cid:4)(cid:20)(cid:11)(cid:6)(cid:24)(cid:30)(cid:1)(cid:15)(cid:25)(cid:1)(cid:31)(cid:8)(cid:20)(cid:8) (cid:14)(cid:1)!(cid:8) (cid:8)(cid:6)(cid:4)(cid:1)""(cid:16)(cid:8)(cid:16)(cid:20)(cid:14)(cid:1)(cid:3)(cid:15)(cid:8)(cid:22)(cid:4)(cid:12)(cid:1)(cid:23)(cid:5)(cid:29)(cid:18)(cid:14)(cid:1)(cid:31)(cid:8)(cid:20)(cid:8) (cid:14)(cid:1)(cid:26)!(cid:9)(cid:13)(cid:14)(cid:1)#(cid:17)(cid:8)(cid:6)(cid:5)$(cid:1)(cid:17)(cid:4)(cid:5)%(cid:8)(cid:10)(cid:8)(cid:11)(cid:6)(cid:8)(cid:12)&(cid:30)(cid:8)(cid:16)(cid:15)(cid:15)(cid:21)(cid:27)(cid:15)(cid:17) @@ -11005,6 +38116,45 @@ Department of Automation University of Science and Technology of China Hefei, China"
+066000d44d6691d27202896691f08b27117918b9,Vision-Based Analysis of Small Groups in Pedestrian Crowds,"Vision-based Analysis of Small Groups in +Pedestrian Crowds +Weina Ge, Robert T. Collins, Senior Member, IEEE, and R. Barry Ruback +E-mail:"
+061fb1b627554f52ff8f3ebb531e326767d845ec,Globally-optimal greedy algorithms for tracking a variable number of objects,"Globally-Optimal Greedy Algorithms for Tracking a Variable Number of +Objects +Hamed Pirsiavash Deva Ramanan Charless C. Fowlkes +Department of Computer Science, University of California, Irvine"
+06599d41a3256245aa0cb2e9e56b29459c2e2c69,VisualWord2Vec (Vis-W2V): Learning Visually Grounded Word Embeddings Using Abstract Scenes,Visual Word2Vec (vis-w2v): Learning Visually Grounded
+06dfc1c6f62bffd5f8b8619d8c51db1ec4d25f3f,Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition,"Fusing Local Patterns of Gabor Magnitude +nd Phase for Face Recognition +Shufu Xie, Shiguang Shan, Member, IEEE, Xilin Chen, Senior Member, IEEE, and Jie Chen, Member, IEEE"
+06f7e0aee7fc5807ab862432a4e5ade2cda73c4b,Flowing ConvNets for Human Pose Estimation in Videos,"Flowing ConvNets for Human Pose Estimation in Videos +Tomas Pfister1, James Charles2 and Andrew Zisserman1 +Objective & Contributions +Estimate 2D upper body joint positions (wrist, elbow, shoulder, head) with high accuracy in real-time +- A better ConvNet for general image (x,y) position regression +- Spatial fusion layers that learn an implicit spatial model between predicted positions +- Optical flow for propagating position predictions from neighbouring frames +. Regress a heatmap for each position +Heatmap +ConvNet +(fully convolutional) +56 x 256 x 3 +64 x 64 x N +. Represent positions by Gaussians +k joints +Idea 1: Implicit ConvNet spatial model +. Add fusion layers to learn dependencies between predicted positions +onv1 +5x5x128 +pool 2x2"
+069c40a8ca5305c9a0734c1f6134eb19a678f4ab,LabelMe: A Database and Web-Based Tool for Image Annotation,"Int J Comput Vis (2008) 77: 157–173 +DOI 10.1007/s11263-007-0090-8 +LabelMe: A Database and Web-Based Tool for Image Annotation +Bryan C. Russell · Antonio Torralba · +Kevin P. Murphy · William T. Freeman +Received: 6 September 2005 / Accepted: 11 September 2007 / Published online: 31 October 2007 +© Springer Science+Business Media, LLC 2007"
06fe63b34fcc8ff68b72b5835c4245d3f9b8a016,Learning semantic representations of objects and their parts,"Mach Learn DOI 10.1007/s10994-013-5336-9 Learning semantic representations of objects @@ -11013,6 +38163,15 @@ Grégoire Mesnil · Antoine Bordes · Jason Weston · Gal Chechik · Yoshua Bengio Received: 24 May 2012 / Accepted: 26 February 2013 © The Author(s) 2013"
+069c9b3c7cf82310d3e06831208aea15f6fdfc32,Power management for mobile games on asymmetric multi-cores,"Power Management for Mobile Games +on Asymmetric Multi-Cores +Anuj Pathania, Santiago Pagani, Muhammad Shafique, J¨org Henkel +Chair for Embedded Systems (CES), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany +Corresponding Author:"
+06d89147794d0889b2e031b0c6811423806f5ea0,A 3D Morphable Eye Region Model for Gaze Estimation,"A 3D Morphable Eye Region Model +for Gaze Estimation +Anonymous ECCV submission +Paper ID 93"
06aab105d55c88bd2baa058dc51fa54580746424,Image Set-Based Collaborative Representation for Face Recognition,"Image Set based Collaborative Representation for Face Recognition Pengfei Zhu, Student Member, IEEE, Wangmeng Zuo, Member, IEEE, Lei Zhang, Member, IEEE, Simon C.K. Shiu, @@ -11021,12 +38180,43 @@ Member, IEEE, David Zhang, Fellow, IEEE" Roman Jur´anek, Adam Herout, Mark´eta Dubsk´a, Pavel Zemˇc´ık Brno University of Technology Brno, Czech Republic"
+06e9149b7ef8bff3a4b5a18fe01da9a522f91891,SRLSP: A Face Image Super-Resolution Algorithm Using Smooth Regression With Local Structure Prior,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TMM.2016.2601020, IEEE +Transactions on Multimedia +SRLSP: A Face Image Super-Resolution Algorithm +Using Smooth Regression with Local Structure Prior +Junjun Jiang, Member, IEEE, Chen Chen, Jiayi Ma, Member, IEEE, Zheng Wang, Zhongyuan +Wang, Member, IEEE, and Ruimin Hu, Senior Member, IEEE +traditional"
062c41dad67bb68fefd9ff0c5c4d296e796004dc,Temporal Generative Adversarial Nets with Singular Value Clipping,"Temporal Generative Adversarial Nets with Singular Value Clipping Masaki Saito∗ Eiichi Matsumoto∗ Preferred Networks inc., Japan {msaito, matsumoto, Shunta Saito"
+06cb0939ed5fb2b3398d54a7fcdb865fe53f414a,Bag-of-Words Image Representation: Key Ideas and Further Insight,"Chapter 2 +Bag-of-Words Image Representation: +Key Ideas and Further Insight +Marc T. Law, Nicolas Thome and Matthieu Cord"
+06bd34951305d9f36eb29cf4532b25272da0e677,"A Fast and Accurate System for Face Detection, Identification, and Verification","JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +A Fast and Accurate System for Face Detection, +Identification, and Verification +Rajeev Ranjan, Ankan Bansal, Jingxiao Zheng, Hongyu Xu, Joshua Gleason, Boyu Lu, Anirudh Nanduri, +Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa"
+068a7c7849cb6480def2e124ac5a45564e094b2a,Multi-Scale Learning for Low-Resolution Person Re-Identification,"Multi-scale learning for low-resolution person re-identification +Li, X; Zheng, WS; Wang, X; Xiang, T; Gong, S +© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be +obtained for all other uses, in any current or future media, including reprinting/republishing +this material for advertising or promotional purposes, creating new collective works, for resale +or redistribution to servers or lists, or reuse of any copyrighted component of this work in +other works. +For additional information about this publication click this link. +http://qmro.qmul.ac.uk/xmlui/handle/123456789/19657 +Information about this research object was correct at the time of download; we occasionally +make corrections to records, please therefore check the published record when citing. For +more information contact"
+06687e82ecc94f716d86d3e9f6bfbd30655c6631,CANDECOMP/PARAFAC Decomposition of High-Order Tensors Through Tensor Reshaping,"CANDECOMP/PARAFAC Decomposition of +High-order Tensors Through Tensor Reshaping +Anh Huy Phan∗, Petr Tichavsk´y and Andrzej Cichocki"
0694b05cbc3ef5d1c5069a4bfb932a5a7b4d5ff0,Exploiting Local Class Information in Extreme Learning Machine,"Iosifidis, A., Tefas, A., & Pitas, I. (2014). Exploiting Local Class Information in Extreme Learning Machine. Paper presented at International Joint Conference on Computational Intelligence (IJCCI), Rome, Italy. @@ -11038,6 +38228,28 @@ General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms"
+0612745dbd292fc0a548a16d39cd73e127faedde,Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models,"Noname manuscript No. +(will be inserted by the editor) +Flickr30k Entities: Collecting Region-to-Phrase Correspondences for +Richer Image-to-Sentence Models +Bryan A. Plummer · Liwei Wang · Chris M. Cervantes · Juan C. Caicedo · Julia +Hockenmaier · Svetlana Lazebnik +Received: date / Accepted: date"
+0683be899f3e04b8b55a501e8ffafc0484b44056,Using Deep Learning and Low-Cost RGB and Thermal Cameras to Detect Pedestrians in Aerial Images Captured by Multirotor UAV,"Article +Using Deep Learning and Low-Cost RGB and +Thermal Cameras to Detect Pedestrians in Aerial +Images Captured by Multirotor UAV +Diulhio Candido de Oliveira * ID and Marco Aurelio Wehrmeister ID +Computing Systems Engineering Laboratory (LESC), Federal University of Technology—Parana (UTFPR), +Curitiba 80230-901, Brazil; +* Correspondence: Tel.: +55-41-3310-4646 +Received: 27 April 2018; Accepted: 3 July 2018; Published: 12 July 2018"
+06dee5ff4b41eadf5db5c6841d3441d388f08117,3D Cascade of Classifiers for Open and Closed Eye Detection in Driver Distraction Monitoring,"D Cascade of Classifiers for +Open and Closed Eye Detection +in Driver Distraction Monitoring +Mahdi Rezaei and Reinhard Klette +The .enpeda.. Project, The University of Auckland +Tamaki Innovation Campus, Auckland, New Zealand"
060820f110a72cbf02c14a6d1085bd6e1d994f6a,Fine-grained classification of pedestrians in video: Benchmark and state of the art,"Fine-Grained Classification of Pedestrians in Video: Benchmark and State of the Art David Hall and Pietro Perona California Institute of Technology. @@ -11077,10 +38289,84 @@ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing including the URL of the record and the reason for the withdrawal request. https://eprints.whiterose.ac.uk/"
+060797f33c242b568189be251f9735afdc4c9f22,Robust Deep-Learning-Based Road-Prediction for Augmented Reality Navigation Systems at Night,"Robust Deep-Learning-Based Road-Prediction +for Augmented Reality Navigation Systems +Matthias Limmer1*, Julian Forster1*, Dennis Baudach1, Florian Schüle2, +Roland Schweiger1 and Hendrik P.A. Lensch3"
+069ebb57ccca31ab68983e07044e65ce1a04174f,4D facial expression recognition,"011 IEEE International Conference on Computer Vision Workshops +978-1-4673-0063-6/11/$26.00 c(cid:13)2011 IEEE"
+06680961e99aadb366968e5f515da58864ecd784,ENabler for Design Specifications FP 6 - IST - 2005 - 27916,"Trends Research ENabler for Design Specifications +FP6-IST-2005-27916 +Deliverable +TRENDS META-DELIVERABLE 1 - STATE OF THE ART +Security Classification : PU +Leading partner +SERAM +Issue Date +03/09/2007 +Version +Authors +Approved by +Final draft +Aranzazu BERECIARTUA, Carole BOUCHARD, Marin FERECATU, Guillaume LOGEROT, Loïs RIGOUSTE, Carlotta +VITALE +Carole Bouchard +03/09/2007 +META DELIVERABLE 1 - STATE OF THE ART +This document presents a State Of the Art related to +most popular products, tools and methods"
+069cadd9d8e52ad2715a3551012a06e506191626,Person re-identification using semantic color names and RankBoost,"Person Re-identification using Semantic Color Names and RankBoost +Cheng-Hao Kuo1, Sameh Khamis2∗, and Vinay Shet1 +Imaging and Computer Vision, Siemens Corporation, Corporate Technology1, Princeton, NJ +University of Maryland2, College Park, MD"
+06f969d3858b6d14425fcbe7ff12b72e213ee240,Recognizing Cardiac Magnetic Resonance Acquisition Planes,"Recognizing cardiac magnetic resonance acquisition +planes +Jan Margeta, Antonio Criminisi, Daniel C. Lee, Nicholas Ayache +To cite this version: +Jan Margeta, Antonio Criminisi, Daniel C. Lee, Nicholas Ayache. Recognizing cardiac magnetic +resonance acquisition planes. MIUA - Medical Image Understanding and Analysis Conference +- 2014, Jul 2014, London, United Kingdom. 2014. <hal-01009952> +HAL Id: hal-01009952 +https://hal.inria.fr/hal-01009952 +Submitted on 19 Jun 2014 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de"
+06c333fc146d0a87f591c82a1f22925ccef378b1,Emotional Cues during Simultaneous Face and Voice Processing: Electrophysiological Insights,"Emotional Cues during Simultaneous Face and Voice +Processing: Electrophysiological Insights +Taosheng Liu1,2, Ana Pinheiro2,3, Zhongxin Zhao4*, Paul G. Nestor2,5, Robert W. McCarley2, Margaret A. +Niznikiewicz2* +Department of Psychology, Second Military Medical University, Shanghai, China, 2 Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, +Boston VA Healthcare System, Brockton Division and Harvard Medical School, Brockton, Massachusetts, United States of America, 3 Neuropsychophysiology Laboratory, +CiPsi, School of Psychology, University of Minho, Braga, Portugal, 4 Department of Neurology, Neuroscience Research Center of Changzheng Hospital, Second Military +Medical University, Shanghai, China, 5 University of Massachusetts, Boston, Massachusetts, United States of America"
+0628ffefb911d1446914098d7c38a094c92c8a70,An opportunistic prediction-based thread scheduling to maximize throughput/watt in AMPs,"An Opportunistic Prediction-based Thread +Scheduling to Maximize Throughput/Watt in AMPs +Arunachalam Annamalai, Rance Rodrigues, Israel Koren and Sandip Kundu +Department of Electrical and Computer Engineering, University of Massachusetts at Amherst +Email: {annamalai, rodrigues, koren,"
06ad99f19cf9cb4a40741a789e4acbf4433c19ae,SenTion: A framework for Sensing Facial Expressions,"SenTion: A framework for Sensing Facial Expressions Rahul Islam∗, Karan Ahuja∗, Sandip Karmakar∗, Ferdous Barbhuiya∗ ∗IIIT Guwahati {rahul.islam, karan.ahuja, sandip,"
+06e959c88dcce05847a395dc404725dd0488003d,Articulated clinician detection using 3D pictorial structures on RGB-D data,"D Pictorial Structures on RGB-D Data for +Articulated Human Detection in Operating Rooms +Abdolrahim Kadkhodamohammadi, Afshin Gangi, Michel de Mathelin and Nicolas Padoy"
+06a2a3c6d44ab5572df55ce34d9b1216bc685385,GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks,"GANVO: Unsupervised Deep Monocular Visual Odometry and Depth +Estimation with Generative Adversarial Networks +Yasin Almalioglu1, Muhamad Risqi U. Saputra1, Pedro P. B. de Gusmo1, Andrew Markham1, and Niki Trigoni1"
+6c3c845fe484bdb2b3549054644c7a06bd9b87b8,ENCARA: real-time detection of frontal faces,"ENCARA: REAL-TIME DETECTION OF FRONTAL FACES +M. Castrillón Santana, M. Hernández Tejera, J. Cabrera Gámez +Instituto Universitario Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería +Universidad de Las Palmas de Gran Canaria +5017 Gran Canaria - Spain"
6c27eccf8c4b22510395baf9f0d0acc3ee547862,Using CMU PIE Human Face Database to a Convolutional Neural Network - Neocognitron,"Using CMU PIE Human Face Database to a Convolutional Neural Network - Neocognitron José Hiroki Saito1, Tiago Vieira de Carvalho1, Marcelo Hirakuri1, André Saunite1, @@ -11089,6 +38375,27 @@ Alessandro Noriaki Ide2 and Sandra Abib1 Rodovia Washington Luis, Km 235, São Carlos – SP - Brazil - University of Genoa - Department of Informatics, Systems and Telematics - Neurolab Via Opera Pia, 13 – I-16145 – Genoa - Italy"
+6c0f9acd62ca9f156ca632dad6d666209eae461e,Discriminative vision-based recovery and recognition of human motion,"Discriminative Vision-Based Recovery and +Recognition of Human Motion +9-789036-528108 +CTIT Dissertation Series No. 09-136 +Center for Telematics and Information Technology (CTIT) +P.O. Box 217, 7500 AE Enschede, The Netherlands +Ronald Poppe"
+6cbb3c47010e406de656d13fe289522bb3071bc0,Improved vehicle detection system based on customized HOG,"Improved vehicle detection system based on +ustomized HOG +Haythem AMEUR1, Abdelhamid HELALI1, Hassen MAAREF1, Anis YOUSSEF2 +Laboratory of Micro-Optoelectronic and Nanostructure, University of Monastir +Tunisia, Monastir +2 TELNET Innovation Labs Tunisia, Tunis"
+6ce6da7a6b2d55fac604d986595ba6979580393b,Cross Domain Knowledge Transfer for Person Re-identification,"Cross Domain Knowledge Transfer for Person Re-identification +Qiqi Xiao +Kelei Cao +Haonan Chen +Fangyue Peng +Chi Zhang"
+6cd557019b7775d8647ca31260734c786fdb69ec,Visual Classifier Prediction by Distributional Semantic Embedding of Text Descriptions,"Proceedings of the 2015 Workshop on Vision and Language (VL’15), pages 48–50, +Lisbon, Portugal, 18 September 2015. c(cid:13)2015 Association for Computational Linguistics."
6cefb70f4668ee6c0bf0c18ea36fd49dd60e8365,Privacy-Preserving Deep Inference for Rich User Data on The Cloud,"Privacy-Preserving Deep Inference for Rich User Data on The Cloud Seyed Ali Osia ♯, Ali Shahin Shamsabadi ♯, Ali Taheri ♯, Kleomenis Katevas ⋆, @@ -11096,6 +38403,49 @@ Hamid R. Rabiee ♯, Nicholas D. Lane †, Hamed Haddadi ⋆ ♯ Sharif University of Technology ⋆ Queen Mary University of London Nokia Bell Labs & University of Oxford"
+6cb68c1f7558e01966ad1e1fa81feeeae3dee666,Photo Filter Recommendation by Category-Aware Aesthetic Learning,"IEEE TRANSACTION ON MULTIMEDIA +Photo Filter Recommendation +y Category-Aware Aesthetic Learning +Wei-Tse Sun, Ting-Hsuan Chao, Yin-Hsi Kuo, Winston H. Hsu"
+6c54261f601c8a569149b77d32efe6c58f2e4a2e,Preliminary evidence that the limbal ring influences facial attractiveness.,"Evolutionary Psychology +www.epjournal.net – 2011. 9(2): 137-146 +¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ +Original Article +Preliminary Evidence that the Limbal Ring Influences Facial Attractiveness +Darren Peshek, Department of Cognitive Sciences, University of California Irvine, Irvine, CA, USA. Email: +(Corresponding author). +Negar Semmaknejad, Department of Cognitive Sciences, University of California Irvine, Irvine, CA, USA. +Donald Hoffman, Department of Cognitive Sciences, University of California Irvine, Irvine, CA, USA. +Pete Foley, Innovation Science, Procter & Gamble, Cincinnati, OH, USA."
+6c62330cbd60f2cb6cb80b920104d0df3116cb3f,Robust People Tracking Using A Light Coding Depth Sensor,"Robust People Tracking Using A Light Coding Depth Sensor +Xun Changqing1, Yang Shuqiang2, and Zhang Chunyuan1 +College of Computer, National University of Defence Technology, ChangSha, China +College of Electronic Science and Engineering, National University of Defence Technology, ChangSha, China"
+6c52c12644321d4256306feaf784ccae6ebc4fea,Enhanced vote count circuit based on nor flash memory for fast similarity search,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE +ICASSP 2016"
+6ceacd889559cfcf0009e914d47f915167231846,The impact of visual attributes on online image diffusion,"The Impact of Visual Attributes on Online Image Diffusion +Luam Totti +Federal University of +Minas Gerais (UFMG) +Belo Horizonte, MG, Brazil +Felipe Costa +Federal University of +Minas Gerais (UFMG) +Belo Horizonte, MG, Brazil +Sandra Avila +RECOD Lab., DCA / FEEC / +UNICAMP +Campinas, SP, Brazil +Eduardo Valle +RECOD Lab., DCA / FEEC / +UNICAMP +Campinas, SP, Brazil +Wagner Meira Jr. +Federal University of +Minas Gerais (UFMG)"
+6cad008ad80081dc42752e813ee6924e3c174dc7,Does Facial Resemblance Enhance Cooperation?,"Does Facial Resemblance Enhance Cooperation? +Trang Giang*, Raoul Bell*, Axel Buchner +Department of Experimental Psychology, Heinrich Heine University Du¨ sseldorf, Du¨ sseldorf, Germany"
6c304f3b9c3a711a0cca5c62ce221fb098dccff0,Attentive Semantic Video Generation Using Captions,"Attentive Semantic Video Generation using Captions Tanya Marwah∗ IIT Hyderabad @@ -11113,6 +38463,50 @@ on local and global features Cong Geng · Xudong Jiang Received: 30 May 2011 / Revised: 21 February 2012 / Accepted: 29 February 2012 / Published online: 22 March 2012 © Springer-Verlag 2012"
+6c4d5ac0eed17513e3ceacd396526b8ad6c8fc09,Learning to Learn by Exploiting Prior Knowledge,"Learning to Learn by Exploiting +Prior Knowledge +Thèse n. 5587 +à présenter le 07 November 2012 +à la Faculté des Sciences et Techniques de L'ingénieur +laboratoire de L'Idiap +programme doctoral en Génie Électrique +École Polytechnique Fédérale de Lausanne +pour l'obtention du grade de Docteur ès Sciences +Tatiana Tommasi +cceptée sur proposition du jury : +Prof Dario Floreano, président du jury +Prof Hervé Bourlard, directeur de thèse +Dr Barbara Caputo, co-directeur de thèse +Prof Jean-Philippe Thiran, rapporteur +Prof Jim Little, rapporteur +Dr Vittorio Ferrari, rapporteur +Lausanne, EPFL, 2012"
+6c984bb3243f3b8d0afd8d90cd4ce85eb8f1dd3c,3D Ear Recognition System Using Neural Network Based Self Organizing Maps,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 +International Conference on Humming Bird ( 01st March 2014) +RESEARCH ARTICLE +OPEN ACCESS +D Ear Recognition System Using Neural Network Based Self +Organizing Maps +M.Sathish Babu1, Assistant Professor +Email: +Department of Computer Science and Engineering, Cape Institute of Technology."
+6c38ab65df4a1bf546f1426e8a7f2f5cb5f765d3,Pathological Tremor Detection From Video,"Pathological Tremor Detection From Video +Xilin Li"
+6c518aabdbba2c073eab6a3bb4120023851e524c,Person Recognition System Based on a Combination of Body Images from Visible Light and Thermal Cameras,"Article +Person Recognition System Based on a Combination +of Body Images from Visible Light and +Thermal Cameras +Dat Tien Nguyen, Hyung Gil Hong, Ki Wan Kim and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (D.T.N.); (H.G.H.); +(K.W.K.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Academic Editor: Vittorio M. N. Passaro +Received: 5 January 2017; Accepted: 14 March 2017; Published: 16 March 2017"
+6c514a85b840c461cf6959927e6a34414e1e0f5e,Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI,"Medical Imaging 2014: Computer-Aided Diagnosis, edited by Stephen Aylward, Lubomir M. Hadjiiski, +Proc. of SPIE Vol. 9035, 90352B · © 2014 SPIE · CCC code: 1605-7422/14/$18 · doi: 10.1117/12.2043969 +Proc. of SPIE Vol. 9035 90352B-1 +From: http://proceedings.spiedigitallibrary.org/ on 10/02/2014 Terms of Use: http://spiedl.org/terms"
6cddc7e24c0581c50adef92d01bb3c73d8b80b41,Face Verification Using the LARK Representation,"Face Verification Using the LARK Representation Hae Jong Seo, Student Member, IEEE, Peyman Milanfar, Fellow, IEEE,"
@@ -11136,6 +38530,41 @@ L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de"
+6cadbc0122376be3c249ecfec7de8247ffbc4fb3,Bidirectional Label Propagation over Graphs,"Int J Software Informatics, Volume 7, Issue 3 (2013), pp.419–433 +International Journal of Software and Informatics, ISSN 1673-7288 +(cid:176)2013 by ISCAS. All rights reserved. +Tel: +86-10-62661040 +http://www.ijsi.org +Email: +Bidirectional Label Propagation over Graphs +Wei Liu1 and Tongtao Zhang2 +(IBM T. J. Watson Research Center, Yorktown Heights, NY, USA) +(Columbia University, New York, NY, USA)"
+6c24fed42d9a1ec283d2aa39a2dd768256a1a066,Swift: reducing the effects of latency in online video scrubbing,"Swift: Reducing the Effects of Latency in Online Video Scrubbing +Justin Matejka, Tovi Grossman, George Fitzmaurice +Autodesk Research, Toronto, Ontario, Canada +Traditional Video Scrubbing +Swift Video Scrubbing +Figure 1. An illustration of the scrubbing behavior of a traditional streaming video player and the Swift player. With the +Swift system a quick-to-download low resolution version of the video is displayed while scrubbing. +tasks which +the effects of"
+6c22b549d854845c5d2f17d75417e4469e6d3f83,A robust face recognition algorithm for real-world applications,"A Robust Face Recognition +Algorithm for +Real-World Applications +zur Erlangung des akademischen Grades eines +Doktors der Ingenieurwissenschaften +der Fakult¨at f¨ur Informatik +der Universit¨at Fridericiana zu Karlsruhe (TH) +genehmigte +Dissertation +Hazım Kemal Ekenel +us Samsun, T¨urkei +Tag der m¨undlichen Pr¨ufung: 02.02.2009 +Erster Gutachter: +Prof. Dr. A. Waibel +Zweiter Gutachter: +Prof. Dr. J. Kittler"
6cd96f2b63c6b6f33f15c0ea366e6003f512a951,A New Approach in Solving Illumination and Facial Expression Problems for Face Recognition,"A New Approach in Solving Illumination and Facial Expression Problems for Face Recognition Yee Wan Wong, Kah Phooi Seng, Li-Minn Ang @@ -11157,6 +38586,27 @@ Hong Kong, 99907 CHINA Fu-lai Chung Department of Computing, Hung Hom, Kowloon Hong Kong, 99907 CHINA"
+6cd762e7cb1301abd0ddbb265dd9c7661ffc0458,On optimal low rank Tucker approximation for tensors: the case for an adjustable core size,"On Optimal Low Rank Tucker Approximation for Tensors: +The Case for an Adjustable Core Size +Bilian CHEN ∗ +Zhening LI † +Shuzhong ZHANG ‡ +August 7, 2014"
+6cd7a47bbba11a994cd8e68ee5eae2fcb0033054,Driving in the Matrix: Can virtual worlds replace human-generated annotations for real world tasks?,"Driving in the Matrix: Can Virtual Worlds Replace Human-Generated +Annotations for Real World Tasks? +Matthew Johnson-Roberson1, Charles Barto2, Rounak Mehta3, Sharath Nittur Sridhar2, and Ram Vasudevan4"
+3965d73c9d7c97cdb391bfd86a15bfd3534cbd32,Deep Learning for Visual Question Answering,"Deep Learning for Visual Question Answering +Avi Singh"
+39803a9c075d543e19384d79fb4c36b207892179,Regression Techniques versus Discriminative Methods for Face Recognition,"Regression Techniques versus Discriminative Methods for Face +Recognition +Vitomir ˇStruc, France Miheliˇc, Rok Gajˇsek and Nikola Paveˇsi´c"
+3917bf2cc075ef075d9c879fc9ec3349ea116735,Discriminant Analysis by Locally Linear Transformations,"Discriminant Analysis by Locally Linear +Transformations +Tae-Kyun Kim1,2, Josef Kittler2, Hyun-Chul Kim3, and Seok Cheol Kee1 +: Samsung Advanced Institute of Technology, KOREA +: Center for Vision, Speech and Signal Processing, University of +Surrey,U.K. +: Pohang University of Science and Technology, KOREA"
390f3d7cdf1ce127ecca65afa2e24c563e9db93b,Learning Deep Representation for Face Alignment with Auxiliary Attributes,"Learning Deep Representation for Face Alignment with Auxiliary Attributes Zhanpeng Zhang, Ping Luo, Chen Change Loy, Member, IEEE and Xiaoou Tang, Fellow, IEEE"
@@ -11165,14 +38615,134 @@ Yibo Hu1,2, Xiang Wu1, Bing Yu3, Ran He1,2 ∗, Zhenan Sun1,2 CRIPAC & NLPR & CEBSIT, CASIA 2University of Chinese Academy of Sciences Noah’s Ark Laboratory, Huawei Technologies Co., Ltd. {yibo.hu, {rhe,"
+3918dcfddf2da218a615dd8f008f6fce436e06f7,Learning Sight from Sound: Ambient Sound Provides Supervision for Visual Learning,"Int J Comput Vis manuscript No. +(will be inserted by the editor) +Learning Sight from Sound: +Ambient Sound Provides Supervision for Visual Learning +Andrew Owens · Jiajun Wu · Josh H. McDermott · William T. Freeman · +Antonio Torralba +Received: date / Accepted: date"
3918b425bb9259ddff9eca33e5d47bde46bd40aa,Learning Language from Ambiguous Perceptual Context,"Copyright David Lieh-Chiang Chen"
+39675124e4fe1be08f42bdd2e1e237e5a87839ba,"Adversarial Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation","Adversarial Collaboration: Joint Unsupervised +Learning of Depth, Camera Motion, Optical +Flow and Motion Segmentation +Anurag Ranjan1 +Varun Jampani2 +Kihwan Kim 2 +Deqing Sun 2 +Jonas Wulff 1 +Michael J. Black1 +Max Planck Institute for Intelligent Systems +NVIDIA Research +{aranjan, jwulff, +{vjampani, kihwank,"
+39df6ca15f41e5a674ed8cd1654e699dbc8b8c11,Human tracking over camera networks: a review,"Hou et al. EURASIP Journal on Advances in Signal Processing (2017) 2017:43 +DOI 10.1186/s13634-017-0482-z +EURASIP Journal on Advances +in Signal Processing +R EV I E W +Human tracking over camera networks: a +review +Li Hou1,2,3*, Wanggen Wan1,3, Jenq-Neng Hwang4, Rizwan Muhammad1,3, Mingyang Yang1,3 and Kang Han1,3 +Open Access"
+39d900da87fa2f8987567d22a924fb7674f9be67,Generating Notifications for Missing Actions: Don't Forget to Turn the Lights Off!,"Generating Notifications for Missing Actions: +Don’t forget to turn the lights off! +Bilge Soran*, Ali Farhadi*†, Linda Shapiro* +*University of Washington +Allen Institute for Artificial Intelligence +{bilge, ali, +Figure 1: Our purpose is to issue notifications about missing actions given an unsegmented input stream of egocentric video. +For the latte making sequence above, our system recognizes the actions that happened so far, predicts the ongoing action, +reasons about missing actions and the associated cost, and generates notifications for the costly missing actions. In this figure, +the brackets refer to segmented action boundaries, the blue arrows show the prediction points and the graphs below show the +inter-action dependencies. The most recently completed action is marked in red, the predicted action is marked in blue, and +the missing action is marked in orange. In this example, the actor is about to miss an important action: steam milk, and a +reminder for that is given."
+39d406df1823aad167a429f60ae8f1d3dc4250fa,Scaling for Multimodal 3D Object Detection,"Scaling for Multimodal 3D Object Detection +Andrej Karpathy +Stanford"
+397400dd7c31e47f8dec20a742695abed297a150,An integrated vision-based architecture for home security system,"An Integrated Vision-based Architecture for Home +Security System +John See, Student Member, IEEE, and Sze-Wei Lee, Member, IEEE"
+39b080aea9b342947058884ca25fb5bb1b8f6d66,Fully Automated and Highly Accurate Dense Correspondence for Facial Surfaces,"Fully Automated and Highly Accurate Dense +Correspondence for Facial Surfaces +C. Martin Grewe and Stefan Zachow +Mathematics for Life and Materials Sciences, +Zuse Institute Berlin, Germany +Fig. 1: Two facial expressions (a,b) from our database set into dense correspon- +dence using the proposed framework. High geometric and photometric details are +ccurately morphed between both expressions via a dense corresponding mesh."
+39d08fa8b028217384daeb3e622848451809a422,Variational Approaches for Auto-Encoding Generative Adversarial Networks,"Variational Approaches for Auto-Encoding +Generative Adversarial Networks +Mihaela Rosca∗ Balaji Lakshminarayanan∗ David Warde-Farley +Shakir Mohamed +DeepMind"
3998c5aa6be58cce8cb65a64cb168864093a9a3e,Understanding head and hand activities and coordination in naturalistic driving videos,Intelligent Vehicles Symposium 2014
+39fc0fe46ddf43f13073cbab077d981547889dc1,Using Gradient Features from Scale-invariant Keypoints on Face Recognition,"International Journal of Innovative +Computing, Information and Control +Volume 7, Number 4, April 2011 +ICIC International c⃝2011 ISSN 1349-4198 +pp. 1639{1649 +USING GRADIENT FEATURES FROM SCALE-INVARIANT +KEYPOINTS ON FACE RECOGNITION +Shinfeng D. Lin, Jia-Hong Lin and Cheng-Chin Chiang +Department of Computer Science and Information Engineering +National Dong Hwa University +No. 1, Sec. 2, Da Hsueh Rd., Shoufeng, Hualien 97401, Taiwan +f david; bbmac; +Received November 2009; revised March 2010"
39dc2ce4cce737e78010642048b6ed1b71e8ac2f,Recognition of six basic facial expressions by feature-points tracking using RBF neural network and fuzzy inference system,"Recognition of Six Basic Facial Expressions by Feature-Points Tracking using RBF Neural Network and Fuzzy Inference System Hadi Seyedarabi*, Ali Aghagolzadeh **, Sohrab Khanmohammadi ** *Islamic Azad University of AHAR **Elect. Eng. Faculty, Tabriz University, Tabriz, Iran"
+39a76fdc4b2d4b9e8ef8f69a87d17ae930520acc,Occlusion-Aware Human Pose Estimation with Mixtures of Sub-Trees,"Occlusion-Aware Human Pose Estimation with +Mixtures of Sub-Trees +Ibrahim Radwan∗, Abhinav Dhall and Roland Goecke"
+397fffa6f785762acb3cd3c96c4c6b65058b816f,Modeling mutual context of object and human pose in human-object interaction activities,"Modeling Mutual Context of Object and +Human Pose in Human-object Interaction +Activities +• Bangpeng Yao +• Li Fei-Fei +Presented by Sahil Shah"
+3907d83f14ba9e2b8a93c3f02b04ca0b81901c4b,Semantic segmentation - using Convolutional Neural Networks and Sparse Dictionaries,"Master of Science Thesis in Electrical Engineering +Department of Electrical Engineering, Linköping University, 2017 +Semantic segmentation +- using Convolutional Neural Networks +nd Sparse Dictionaries +Viktor Andersson"
+391e52ac04408d3e6496614ffafd6ac89c1b6c45,Seeing 3D Chairs: Exemplar Part-Based 2D-3D Alignment Using a Large Dataset of CAD Models,"Seeing 3D chairs: exemplar part-based 2D-3D alignment +using a large dataset of CAD models +Mathieu Aubry1,∗ Daniel Maturana2 Alexei A. Efros3,∗ Bryan C. Russell4 +Josef Sivic1,∗ +INRIA 2Carnegie Mellon University +UC Berkeley +Intel Labs"
+390e212d4a874d8d2256e55fe0dee9193e4c376a,Just in Time: Controlling Temporal Performance in Crowdsourcing Competitions,"Just in Time: Controlling Temporal Performance in +Crowdsourcing Competitions +Markus Rokicki +L3S Research Center, +Hannover, Germany +Electronics and Computer +Science, University of +Southampton, Southampton, +Sergej Zerr"
+399ab5652908d99a5be1a664425f6463f67df2aa,Mechanisms of Diminished Attention to Eyes in Autism.,"Mechanisms of diminished attention to eyes in +utism +Jennifer M. Moriuchi, Emory University +Ami Klin, Emory University +Warren R Jones, Emory University +Journal Title: American Journal of Psychiatry +Volume: Volume 174, Number 1 +Publisher: American Psychiatric Publishing | 2017-01-01, Pages 26-35 +Type of Work: Article | Post-print: After Peer Review +Publisher DOI: 10.1176/appi.ajp.2016.15091222 +Permanent URL: https://pid.emory.edu/ark:/25593/s8mpz +Final published version: http://dx.doi.org/10.1176/appi.ajp.2016.15091222 +Copyright information: +018 American Psychiatric Association +Accessed June 11, 2018 8:03 PM EDT"
397085122a5cade71ef6c19f657c609f0a4f7473,Using Segmentation to Predict the Absence of Occluded Parts,"GHIASI, FOWLKES: USING SEGMENTATION TO DETECT OCCLUSION Using Segmentation to Predict the Absence of Occluded Parts @@ -11183,11 +38753,84 @@ University of California Irvine, CA"
39c8b34c1b678235b60b648d0b11d241a34c8e32,Learning to Deblur Images with Exemplars,"Learning to Deblur Images with Exemplars Jinshan Pan∗, Wenqi Ren∗, Zhe Hu∗, and Ming-Hsuan Yang"
+39bce1d5e4b31a555f12f0a44e92abcad73aab4f,"Explorer "" Here ' s looking at you , kid ""","""Here's looking at you, kid"" +Citation for published version: +Marin-Jimenez, M, Zisserman, A & Ferrari, V 2011, ""Here's looking at you, kid"": Detecting people looking at +each other in videos. in Proceedings of the British Machine Vision Conference (BMVC): Dundee, September +011. BMVA Press, pp. 22.1-22.12. DOI: 10.5244/C.25.22 +Digital Object Identifier (DOI): +0.5244/C.25.22 +Link: +Link to publication record in Edinburgh Research Explorer +Document Version: +Peer reviewed version +Published In: +Proceedings of the British Machine Vision Conference (BMVC) +General rights +Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +nd / or other copyright owners and it is a condition of accessing these publications that users recognise and +bide by the legal requirements associated with these rights. +Take down policy +The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer +ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please"
3986161c20c08fb4b9b791b57198b012519ea58b,An Efficient Method for Face Recognition based on Fusion of Global and Local Feature Extraction,"International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-4 Issue-4, September 2014 An Efficient Method for Face Recognition based on Fusion of Global and Local Feature Extraction E. Gomathi, K. Baskaran"
+3988ed2b900af26c07432d0f9f3c2679f3c532ac,Vision Meets Drones: A Challenge,"Vision Meets Drones: A Challenge +Pengfei Zhu, Longyin Wen, Xiao Bian, Haibin Ling and Qinghua Hu"
+398ad0036b899aec04502c243dd129c1f3e4c21e,Object detection using voting spaces trained by few samples,"Downloaded From: https://www.spiedigitallibrary.org/journals/Optical-Engineering on 12/17/2017 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +ObjectdetectionusingvotingspacestrainedbyfewsamplesPeiXuMaoYeXueLiLishenPeiPengweiJiao"
+3910b1cc849f999dc8a2c02a0313be32dd5d2b43,A Systematic Comparison of Deep Learning Architectures in an Autonomous Vehicle,"A Systematic Comparison of Deep Learning Architectures in an +Autonomous Vehicle +Michael Teti1†, William Edward Hahn1, Shawn Martin2, Christopher Teti3, and Elan Barenholtz1 +such tasks, or an attempt +largely due to recent developments"
+395978c1dee9fd75bbcb249e74ad6fb4d3c2b9fc,A Reliable Hybrid Technique for Human Face Detection,"Hakim A., Marsland S. and W. Guesgen H. (2010). +A RELIABLE HYBRID TECHNIQUE FOR HUMAN FACE DETECTION. +In Proceedings of the International Conference on Computer Vision Theory and Applications, pages 241-244 +Copyright c(cid:13) SciTePress"
+395dadff1eab9c8177f843326ec864567342eba5,Vision-Based People Detection System for Heavy Machine Applications,"Article +Vision-Based People Detection System for Heavy +Machine Applications +Vincent Fremont 1,*, Manh Tuan Bui 1, Djamal Boukerroui 1 and Pierrick Letort 2 +Received: 12 October 2015; Accepted: 13 January 2016; Published: 20 January 2016 +Academic Editor: Vittorio M. N. Passaro +Sorbonne Universités, Université de Technologie de Compiègne, CNRS, UMR 7253, +Heudiasyc-CS 60 319, 60 203 Compiègne Cedex, France; (M.T.B.); +(D.B.) +Technical Center for the Mechanical Industry (CETIM), 60300 Senlis, France; +* Correspondence: Tel.: +33-344-237-917; Fax: +33-344-234-477"
+39b0bce87eec467adfe5bebcfe628ff5bd397fc7,"R4-A.2: Rapid Similarity Prediction, Forensic Search & Retrieval in Video","R4-A.2: Rapid Similarity Prediction, Forensic +Search & Retrieval in Video +PARTICIPANTS +Venkatesh Saligrama +David Castañón +Ziming Zhang +Gregory Castañón +Yuting Chen +Marc Eder +Faculty/Staff +Institution +Title +Co-PI +Co-PI +Post-Doc +Graduate, Undergraduate and REU Students +Degree Pursued +Institution +Email +Month/Year of Graduation"
+399a5f7500648462fd8cf1704dfaeaea9d560e7e,Spoof Detection for Finger-Vein Recognition System Using NIR Camera,"Article +Spoof Detection for Finger-Vein Recognition System +Using NIR Camera +Dat Tien Nguyen, Hyo Sik Yoon, Tuyen Danh Pham and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (D.T.N.); (H.S.Y.); +(T.D.P.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 15 August 2017; Accepted: 27 September 2017; Published: 1 October 2017"
392c3cabe516c0108b478152902a9eee94f4c81e,Tiny images,"Computer Science and Artificial Intelligence Laboratory Technical Report MIT-CSAIL-TR-2007-024 @@ -11195,11 +38838,80 @@ April 23, 2007 Tiny images Antonio Torralba, Rob Fergus, and William T. Freeman m a s s a c h u s e t t s i n s t i t u t e o f t e c h n o l o g y, c a m b r i d g e , m a 0 213 9 u s a — w w w. c s a i l . m i t . e d u"
+39e7ac344b17d97267ec80681aeded17e3e6d786,Joint Parsing of Cross-view Scenes with Spatio-temporal Semantic Parse Graphs,"Joint Parsing of Cross-view Scenes with Spatio-temporal Semantic Parse Graphs∗ +Hang Qi1∗, Yuanlu Xu1∗, Tao Yuan1∗, Tianfu Wu2, Song-Chun Zhu1 +Dept. Computer Science and Statistics, University of California, Los Angeles (UCLA) +{hangqi, tianfu +Dept. Electrical and Computer Engineering, NC State University"
+39db2ff704cc30a7e94989de33ff4290ea4a6df1,Low-Cost Visual Feature Representations For Image Retrieval,"Low-Cost Visual Feature Representations For Image +Retrieval +Ramon F. Pessoa, William R. Schwartz, Jefersson A. dos Santos +Department of Computer Science +Universidade Federal de Minas Gerais (UFMG) +Belo Horizonte - Minas Gerais, Brazil, 31270-901 +Email: {ramon.pessoa, william,"
+39a19a687b3182054b30f36f627bc6875b09dbd3,A new boostrapping strategy for the AdaBoost-based face detector T.-J. Chin and D. Suter A new boostrapping strategy for the AdaBoost-based face detector,"Department of Electrical +Computer Systems Engineering +Technical Report +MECSE-13-2005 +A new boostrapping strategy for the AdaBoost-based face +detector +T.-J. Chin and D. Suter"
+39340257d9a478b3c3b736ad31df1c0a6a78c851,Parts-based object recognition seeded by frequency-tuned saliency for child detection in active safety,"Parts-based object recognition seeded by frequency-tuned saliency for +Child Detection in Active Safety +Shinko Y. Cheng, Jose Molineros, Yuri Owechko +HRL Laboratories, LLC +011 Malibu Canyon Road +Malibu CA 90265"
+3964caa0a1d788eb30365972880f83b71df1ab21,Multi-Modal Obstacle Detection in Unstructured Environments with Conditional Random Fields,"Multi-Modal Obstacle Detection in Unstructured +Environments with Conditional Random Fields +Mikkel Kragh1 and James Underwood2"
+39df4f8ad7add3863208a5f7b71e22ed1970ca58,Bayesian Supervised Dictionary learning,"Bayesian Supervised Dictionary learning +B. Babagholami-Mohamadabadi +A. Jourabloo +M. Zolfaghari +M.T. Manzuri-Shalmani +CE Dept. +Sharif University +Tehran, Iran +CE Dept. +Sharif University +Tehran, Iran +CE Dept. +Sharif University +Tehran, Iran +CE Dept. +Sharif University +Tehran, Iran"
+397c395aed9d96aef064b9ceb9f0eae9421eb00a,An Evaluation of the Pedestrian Classification in a Multi-Domain Multi-Modality Setup,"Sensors 2015, 15, 13851-13873; doi:10.3390/s150613851 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +An Evaluation of the Pedestrian Classification in +Multi-Domain Multi-Modality Setup +Alina Miron 1,*, Alexandrina Rogozan 2, Samia Ainouz 2, Abdelaziz Bensrhair 2 +nd Alberto Broggi 3 +ISR Laboratory, University of Reading, Reading RG6 6AY, UK +INSA Rouen/LITIS laboratory - EA4108, Saint-Etienne du Rouvray 76801, France; +E-Mails: (A.R.); (S.A.); +(A.B.) +VisLab, University of Parma, Parco Area delle Scienze 181A, 43100 Parma, Italy; +E-Mail: +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +44-118-378-7631. +Academic Editor: Vittorio M.N. Passaro +Received: 2 April 2015 / Accepted: 8 June 2015 / Published: 12 June 2015"
3933e323653ff27e68c3458d245b47e3e37f52fd,Evaluation of a 3 D-aided Pose Invariant 2 D Face Recognition System,"Evaluation of a 3D-aided Pose Invariant 2D Face Recognition System Xiang Xu, Ha A. Le, Pengfei Dou, Yuhang Wu, Ioannis A. Kakadiaris {xxu18, hale4, pdou, ywu35, Computational Biomedicine Lab 800 Calhoun Rd. Houston, TX, USA"
+3903cbd56446436a4a3b8443c26c90fc1b69f5e0,Event driven software architecture for multi-camera and distributed surveillance research systems,"Event Driven Software Architecture for Multi-camera and Distributed +Surveillance Research Systems +Roberto Vezzani, Rita Cucchiara +University of Modena and Reggio Emilia - Italy"
3958db5769c927cfc2a9e4d1ee33ecfba86fe054,Describable Visual Attributes for Face Verification and Image Search,"Describable Visual Attributes for Face Verification and Image Search Neeraj Kumar, Student Member, IEEE, Alexander C. Berg, Member, IEEE, @@ -11229,10 +38941,15 @@ D-Face Modeling Rik Fransens, Christoph Strecha, Luc Van Gool PSI ESAT-KUL Leuven, Belgium"
+9900be092f81547ad71e4124cd850048e1969063,3D Face Analysis for Facial Expression Recognition,"Author manuscript, published in ""20th International Conference on Pattern Recognition (ICPR 2010), Istanbul : Turquie (2010)"""
9958942a0b7832e0774708a832d8b7d1a5d287ae,The Sparse Matrix Transform for Covariance Estimation and Analysis of High Dimensional Signals,"The Sparse Matrix Transform for Covariance Estimation and Analysis of High Dimensional Signals Guangzhi Cao*, Member, IEEE, Leonardo R. Bachega, and Charles A. Bouman, Fellow, IEEE"
+99582ce8439dce17d9d6f74eb54fc5c89dbe06d9,"Hough Forests for Object Detection, Tracking, and Action Recognition","Hough Forests for Object Detection, Tracking, +nd Action Recognition +Juergen Gall Member, IEEE, Angela Yao, Nima Razavi, Luc Van Gool Member, IEEE, and +Victor Lempitsky"
99726ad232cef837f37914b63de70d8c5101f4e2,Facial Expression Recognition Using PCA & Distance Classifier,"International Journal of Scientific & Engineering Research, Volume 5, Issue 5, May-2014 570 ISSN 2229-5518 Facial Expression Recognition Using PCA & Distance Classifier @@ -11245,6 +38962,57 @@ Reader in Dept. of Electronics & Telecomm. Engg. VEER SURENDRA SAI UNIVERSITY OF TECHNOLOGY BURLA, ODISHA, INDIA"
+998e829cc72080c88a780f322d6bf7ab78dbd743,Towards Real-Time Multiresolution Face/Head Detection,"´AAAAAAAAAAAAAAAAAAAAAAAA +´AAAAAAAAAAAAAAAAAAAAAAAA +ART´ICULO +Towards Real-Time Multiresolution Face/Head +Detection* +M. Castrill´on-Santana, H. Kruppa**, C. Guerra-Artal, M. Hern´andez-Tejera +Universidad de Las Palmas de Gran Canaria +Instituto Universitario de Sistemas Inteligentes +y Aplicaciones Num´ericas en Ingenier´ıa +Edificio Central del Parque Cient´ıfico-Tecnol´ogico +Campus Universitario de Tafira +5017 Las Palmas - Espa˜na"
+99a3a4151abbc2e5d33d4beec88dc55a057df299,Topological analysis of discrete scalar data,"TOPOLOGICAL ANALYSIS OF +DISCRETE SCALAR DATA +DAVID GÜNTHER +DISSERTATION ZUR ERLANGUNG DES GRADES +DES DOKTORS DER INGENIEURWISSENSCHAFTEN +DER NATURWISSENSCHAFTLICH-TECHNISCHEN FAKULTÄTEN +DER UNIVERSITÄT DES SAARLANDES +SAARBRÜCKEN, 2012"
+99e1fd6a378209d48c12a70229e4f6d4d83f4417,Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs,"Modular Vehicle Control for Transferring Semantic +Information Between Weather Conditions Using +Patrick Wenzel1,2∗ +, Qadeer Khan1,2∗ +, Daniel Cremers1,2, and Laura Leal-Taixé1 +Technical University of Munich +Artisense"
+99e1ab1fb08af137cad6efbc0454c6e1e68dca51,3D human action recognition and motion analysis using selective representations,"D HUMAN ACTION RECOGNITION +AND MOTION ANALYSIS USING +SELECTIVE REPRESENTATIONS +D LEIGHTLEY +PhD 2015"
+99f565df31ef710a2d8a1b606e3b7f5f92ab657c,Geometry Score: A Method For Comparing Generative Adversarial Networks,"Geometry Score: A Method For Comparing Generative Adversarial Networks +Valentin Khrulkov 1 Ivan Oseledets 1 2"
+99b7ff97ad54308b816e47d9bbf6704b787b8f52,Causal Flow,"Causal Flow +Yuya Yamashita, Tatsuya Harada, Member, IEEE, and Yasuo Kuniyoshi, Member, IEEE"
+99df887213407f612c1f5df502b637709a29cd6b,Ensembles of exemplar-SVMs for video face recognition from a single sample per person,"Ensembles of Exemplar-SVMs for Video Face Recognition from a +Single Sample Per Person +Saman Bashbaghi, Eric Granger, Robert Sabourin +Guillaume-Alexandre Bilodeau +Laboratoire d’imagerie de vision et d’intelligence artificielle +LITIV Lab +École de technologie supérieure, Université du Québec, Montréal, Canada +Polytechnique Montréal, Montréal, Canada +{eric.granger,"
+99cb716cd7687db8ef3d0403c85b1ab90869800f,Face Recognition under Pose and Expresivity Variation Using Thermal and Visible Images,"FACE RECOGNITION UNDER POSE AND EXPRESIVITY +VARIATION USING THERMAL AND VISIBLE IMAGES +Florin Marius Pop, Mihaela Gordan, Camelia Florea, Aurel Vlaicu +Centre for Multimedia Technologies and Distance Education +Technical University of Cluj-Napoca, Romania +{Mihaela.Gordan, Camelia.Florea,"
9993f1a7cfb5b0078f339b9a6bfa341da76a3168,"A Simple, Fast and Highly-Accurate Algorithm to Recover 3D Shape from 2D Landmarks on a Single Image","JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 A Simple, Fast and Highly-Accurate Algorithm to Recover 3D Shape from 2D Landmarks on a Single @@ -11270,6 +39038,35 @@ hallenges, our algorithm generally performs well on the mouth, with large segmen The scene parsing approach by Liu et al. [2] shares sevaral similarities with our work. Like our approach, they propose a nonparametric system that transfers labels from exemplars in a database to annotate a test image. This begs the question, Why not simply apply the approach from Liu et al. to face images?"
+998b7c8608fb9f80177ce54230761d8c3d82b2da,SHEF-Multimodal: Grounding Machine Translation on Images,"Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers, pages 660–665, +Berlin, Germany, August 11-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
+9941a408ae031d1254bbc0fe7a63fac5f85fe347,Neural Processes,"Neural Processes +Marta Garnelo 1 Jonathan Schwarz 1 Dan Rosenbaum 1 Fabio Viola 1 Danilo J. Rezende 1 S. M. Ali Eslami 1 +Yee Whye Teh 1"
+9963af1199679e176f0836e6d63572b3a69fa7da,23 Generating Facial Expressions with Deep Belief Nets,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,500 +08,000 +.7 M +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact"
+998f2cfb4a3bac6b38d8a4a96a3827e06a0eaadb,Geo-Supervised Visual Depth Prediction,"Geo-Supervised Visual Depth Prediction +Xiaohan Fei +Alex Wong +Stefano Soatto"
99c20eb5433ed27e70881d026d1dbe378a12b342,Semi-Supervised and Unsupervised Data Extraction Targeting Speakers: From Speaker Roles to Fame?,"ISCA Archive http://www.isca-speech.org/archive First Workshop on Speech, Language @@ -11277,6 +39074,9 @@ nd Audio in Multimedia Marseille, France August 22-23, 2013 Proceedings of the First Workshop on Speech, Language and Audio in Multimedia (SLAM), Marseille, France, August 22-23, 2013."
+99d3bc6d62675297693e5e57ff0770e7017f9637,Hierarchical Invariant Feature Learning with Marginalization for Person Re-Identification,"Hierarchical Invariant Feature Learning with +Marginalization for Person Re-Identification +Rahul Rama Varior, Student Member, IEEE, Gang Wang, Member, IEEE"
9990e0b05f34b586ffccdc89de2f8b0e5d427067,Auto - Optimized Multimodal Expression Recognition Framework Using 3 D Kinect Data for ASD Therapeutic Aid,"International Journal of Modeling and Optimization, Vol. 3, No. 2, April 2013 Auto-Optimized Multimodal Expression Recognition Framework Using 3D Kinect Data for ASD Therapeutic @@ -11292,6 +39092,23 @@ Dhruvil Badani† Jake Ryland Williams¶ Crystal Lee‡ November 28, 2017"
+9922a2ec8dfb307bb1fcb334098fd912e23b3bab,Particle-based pedestrian path prediction using LSTM-MDL models,"Particle-based Pedestrian Path Prediction using LSTM-MDL Models +Ronny Hug∗, Stefan Becker∗, Wolfgang H¨ubner∗ and Michael Arens∗"
+99ae92bae7c873432a6a60238b33d494bbae13eb,Recognition of Human Pose from Images Based on Graph Spectra,"RECOGNITION OF HUMAN POSE FROM IMAGES BASED ON GRAPH SPECTRA +A. A. Zakharov a *, A. E. Barinov a, A. L. Zhiznyakov a +Murom Institut Vladimir State University, CAD Department, , 602264, Orlovskaya 23, Murom, Russian Federation, aa- +Commission VI, WG VI/4 +KEY WORDS: Image Recognition, Human Pose, Spectral Graph Matching"
+99227909e5733d76b0d50fc3fab975ab7a43fce3,A Cascaded Inception of Inception Network with Attention Modulated Feature Fusion for Human Pose Estimation,"A Cascaded Inception of Inception Network with Attention Modulated Feature +Fusion for Human Pose Estimation +Submission ID: 2065"
+522fab628aab972f39835521e31564b4b6c64fe5,Vehicle Classification on Low-resolution and Occluded images: A low-cost labeled dataset for augmentation,"Vehicle Classification on Low-resolution and +Occluded images: A low-cost labeled dataset for +ugmentation +Anonymous Author(s) +Affiliation +Address +email"
52012b4ecb78f6b4b9ea496be98bcfe0944353cd,Using Support Vector Machine and Local Binary Pattern for Facial Expression Recognition,"JOURNAL OF COMPUTATION IN BIOSCIENCES AND ENGINEERING Journal homepage: http://scienceq.org/Journals/JCLS.php Research Article @@ -11303,6 +39120,21 @@ Ayeni Olaniyi Abiodun 1, Alese Boniface Kayode1, Dada Olabisi Matemilayo2 . Department of computer science, Kwara state polytechnic Ilorin, Kwara-State, Nigeria. . *Corresponding author: Ayeni Olaniyi Abiodun Mail Id: Received: September 22, 2015, Accepted: December 14, 2015, Published: December 14, 2015."
+5293960de53b0118ef3c8b410d27b23b9cec9bf7,Online Multi-Object Tracking with Dual Matching Attention Networks,"Online Multi-Object Tracking with +Dual Matching Attention Networks +Ji Zhu1,2, Hua Yang1(cid:63), Nian Liu3, Minyoung Kim4, +Wenjun Zhang1, and Ming-Hsuan Yang5,6 +Northwestern Polytechnical University 4Massachusetts Institute of Technology +Shanghai Jiao Tong University 2Visbody Inc +5University of California, Merced 6Google Inc +{jizhu1023,"
+527cc8cd2af06a9ac2e5cded806bab5c3faad9cf,Abnormal Event Detection in Videos Using Spatiotemporal Autoencoder,"Abnormal Event Detection in Videos +using Spatiotemporal Autoencoder +Yong Shean Chong +Yong Haur Tay +Lee Kong Chian Faculty of Engineering Science, +Universiti Tunku Abdul Rahman, 43000 Kajang, Malaysia. +January 9, 2017"
529e2ce6fb362bfce02d6d9a9e5de635bde81191,Normalization of Face Illumination Based on Large-and Small-Scale Features,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. > TIP-05732-2009< Normalization of Face Illumination Based @@ -11313,10 +39145,185 @@ Pong C. Yuen, Member, IEEE, Ching Y. Suen, IEEE Fellow" Attributes and Travel Group Types From Community-Contributed Photos Yan-Ying Chen, An-Jung Cheng, and Winston H. Hsu, Senior Member, IEEE"
+52f71cc9c312aa845867ad1695c25a6d1d94ba0e,The invariance assumption in process-dissociation models: an evaluation across three domains.,"Journal of Experimental Psychology: General +015, Vol. 144, No. 1, 198 –221 +0096-3445/15/$12.00 +© 2014 American Psychological Association +http://dx.doi.org/10.1037/xge0000044 +The Invariance Assumption in Process-Dissociation Models: +An Evaluation Across Three Domains +Karl Christoph Klauer, Kerstin Dittrich, +nd Christine Scholtes +Albert-Ludwigs-Universität Freiburg +Andreas Voss +Universität Heidelberg +The class of process-dissociation models, a subset of the class of multinomial processing-tree models, is +one of the best understood classes of models used in experimental psychology. A number of prominent +debates have addressed fundamental assumptions of process-dissociation models, leading, in many cases, +to conceptual clarifications and extended models that address identified issues. One issue that has so far +defied empirical clarification is how to evaluate the invariance assumption for the dominant process. +Violations of the invariance assumption have, however, the potential to bias conventional process- +dissociation analyses in different ways, and they can cause misleading theoretical interpretations and +onclusions. Based on recent advances in multinomial modeling, we propose new approaches to examine"
+52e0c03dd661d032865dfedd91ca49542ccfc2a3,Improving Human Action Recognition Using Score Distribution and Ranking,"Improving Human Action Recognition +using Score Distribution and Ranking +Minh Hoai1,2 and Andrew Zisserman1 +Visual Geometry Group, Dept. Engineering Science, University of Oxford. +Department of Computer Science, Stony Brook University."
+523abe29cc278f9daf03fe74d1e09d9e2711b73e,Facial Recognition System: A Review,"Debolina S. De, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.10, October- 2015, pg. 7-11 +Available Online at www.ijcsmc.com +International Journal of Computer Science and Mobile Computing +A Monthly Journal of Computer Science and Information Technology +ISSN 2320–088X +IJCSMC, Vol. 4, Issue. 10, October 2015, pg.7 – 11 +REVIEW ARTICLE +Facial Recognition System: A Review +Debolina S. De +Computer Engineering Department, Mukesh Patel School of Technology Management and Engineering, India"
+5251cb5349e37495b3ca29b06e6ed7422f12d126,A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier,"Proceedings of the 2007 IEEE +Intelligent Transportation Systems Conference +Seattle, WA, USA, Sept. 30 - Oct. 3, 2007 +MoD2.2 +-4244-1396-6/07/$25.00 ©2007 IEEE."
+524634e1055637b7c22b29e7e36437f4ba80df04,Thermal to Visible Synthesis of Face Images Using Multiple Regions,"Thermal to Visible Synthesis of Face Images using Multiple Regions +Benjamin S. Riggan1,* +Nathaniel J. Short1,2 +Shuowen Hu1 +U.S. Army Research Laboratory, 2800 Powder Mill Rd., Adelphi, MD 20783 +Booz Allen Hamilton, 8283 Grennsboro Dr., McLean, VA 22102 +*Corresponding author:"
+52884a0c7913be319c1a2395f009cea47b03f128,Explorer Learning Grounded Meaning Representations with Autoencoders,"Learning Grounded Meaning Representations with Autoencoders +Citation for published version: +Silberer, C & Lapata, M 2014, 'Learning Grounded Meaning Representations with Autoencoders'. in +Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long +Papers). Association for Computational Linguistics, Baltimore, Maryland, pp. 721-732. +Link: +Link to publication record in Edinburgh Research Explorer +Document Version: +Publisher final version (usually the publisher pdf) +Published In: +Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long +Papers) +General rights +Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +nd / or other copyright owners and it is a condition of accessing these publications that users recognise and +bide by the legal requirements associated with these rights. +Take down policy +The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer +ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please +ontact providing details, and we will remove access to the work immediately and"
+52b6df1fe810d36fd615eb7c47aa1fd29376e769,Graph Mining for Object Tracking in Videos,"Graph Mining for Object Tracking in Videos +Fabien Diot, Elisa Fromont, Baptiste Jeudy, Emmanuel Marilly, Olivier +Martinot +To cite this version: +Fabien Diot, Elisa Fromont, Baptiste Jeudy, Emmanuel Marilly, Olivier Martinot. Graph +Mining for Object Tracking in Videos. European Conference on Machine Learning and Prin- +iples and Practice of Knowledge Discovery in Databases, Sep 2012, Bristol, United Kingdom. +Springer, LNCS (LNAI 6321), pp.394-409, 2012. <hal-00714705v2> +HAL Id: hal-00714705 +https://hal.archives-ouvertes.fr/hal-00714705v2 +Submitted on 20 Sep 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
+521120c3907677e17708c17c5b6bab9087e61c5b,"l2, 1-Norm Regularized Discriminative Feature Selection for Unsupervised Learning","(cid:2)2,1-Norm Regularized Discriminative Feature +Selection for Unsupervised Learning +Yi Yang1, Heng Tao Shen1, Zhigang Ma2, Zi Huang1, Xiaofang Zhou1 +School of Information Technology & Electrical Engineering, The University of Queensland. +Department of Information Engineering & Computer Science, University of Trento. +yangyi {huang,"
+5223f3485b96bffe7dd4b3aa71e63fd2b049fcf0,Is the Pedestrian going to Cross? Answering by 2D Pose Estimation,"Is the Pedestrian going to Cross? Answering by 2D Pose Estimation +Zhijie Fang and Antonio M. L´opez"
+52417b0406886154f0b4e2343ad6ac18c0484ec4,Ecological legacies of civil war: 35-year increase in savanna tree cover following wholesale large-mammal declines,"Journal of Ecology 2016, 104, 79–89 +doi: 10.1111/1365-2745.12483 +Ecological legacies of civil war: 35-year increase in +savanna tree cover following wholesale large-mammal +declines +Joshua H. Daskin1*, Marc Stalmans2 and Robert M. Pringle1 +Department of Ecology and Evolutionary Biology, 106A Guyot Hall, Princeton University Princeton, NJ 08540, USA; +nd 2Department of Scientific Services, Gorongosa National Park, Sofala Province, Mozambique +Summary +. Large mammalian herbivores (LMH) exert strong effects on plants in tropical savannas, and +many wild LMH populations are declining. However, predicting the impacts of these declines on +vegetation structure remains challenging. +. Experiments suggest that tree cover can increase rapidly following LMH exclusion. Yet it is +unclear whether these results scale up to predict ecosystem-level impacts of LMH declines, which +often alter fire regimes, trigger compensatory responses of other herbivores and accompany anthro- +pogenic land-use changes. Moreover, theory predicts that grazers and browsers should have oppos- +ing effects on tree cover, further complicating efforts to forecast the outcomes of community-wide +declines. +. We used the near-extirpation of grazing and browsing LMH from Gorongosa National Park dur- +ing the Mozambican Civil War (1977–1992) as a natural experiment to test whether megafaunal col-"
+52ed30920f2f96970c4f79d6768436ed855dad42,Active image pair selection for continuous person re-identification,"ACTIVE IMAGE PAIR SELECTION FOR CONTINUOUS PERSON RE-IDENTIFICATION +Abir Das, Rameswar Panda, Amit Roy-Chowdhury +Electrical and Computer Engineering Department, University of California, Riverside, USA"
52258ec5ec73ce30ca8bc215539c017d279517cf,Recognizing Faces with Expressions: Within-class Space and Between-class Space,"Recognizing Faces with Expressions: Within-class Space and Between-class Space Department of Computer Science and Engineering, Zhejang University, Hangzhou 310027,P.R.China Email: Yu Bing Chen Ping Jin Lianfu"
+526ce11a6c80716fca69bdc111f32dfbe045e400,A Survey on Dataset Recognition of 3 D Face with Missing Parts,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 +A Survey on Dataset Recognition of 3D Face with +Missing Parts +Madhura Patil +ME Student, Department of Computer Engineering, Sinhgad Academy of Engg. Pune, Maharashtra, India +possibly +recognition.3D +recognization +methodology"
+52969cdd2c5eaccb534fe1296a61517b7ec42a54,Human Identification based on Ear Recognition,"Human Identification based on Ear Recognition +S. Gangaram1, and S. Viriri1,2"
+526ce5c72af5e1f93b8029a26e2eed7d1ac009f5,0 Constructing Kernel Machines in the Empirical Kernel Feature Space,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+5265be9c7b8b22f4e06a01736bbedf171caee74e,Covariance of Motion and Appearance Featuresfor Spatio Temporal Recognition Tasks,"Covariance of Motion and Appearance Features +for Human Action and Gesture Recognition +Subhabrata Bhattacharya, Nasim Souly and Mubarak Shah"
+524890eef6beaeb2e206c7b1bf51b58298eb55ec,Florian et al_ICMCSSE 2012_3,"Efficient and Effective Gabor Feature +Representation for Face Detection +Yasuomi D. Sato, Yasutaka Kuriya"
+527ed756eba3bc77eb58d22d4cfe27da04d3bbbb,Adaptive skew-sensitive fusion of ensembles and their application to face re-identification,"Adaptive Skew-Sensitive Fusion of Ensembles and +their Application to Face Re-Identification +Miguel De-la-Torre∗†, Eric Granger∗, Robert Sabourin∗ +´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montr´eal, Canada +Centro Universitario de Los Valles, Universidad de Guadalajara, Ameca, M´exico"
+52144c6d20ddea70e59514c2aa9ec7dc801e5c5e,An Investigation of Face Recognition Characteristics Using PCA and ICA,"Yundi Fu et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.2, February- 2014, pg. 110-123 +Available Online at www.ijcsmc.com +International Journal of Computer Science and Mobile Computing +A Monthly Journal of Computer Science and Information Technology +ISSN 2320–088X +IJCSMC, Vol. 3, Issue. 2, February 2014, pg.110 – 123 +RESEARCH ARTICLE +An Investigation of Face Recognition +Characteristics Using PCA and ICA +Yundi Fu1, Yongli Cao1, Arun Kumar Sangaiah2 +Department of Software Engineering, University of Electronic Science and Technology, China +School of Computing Science and Engineering, VIT University, Vellore, India"
+529341eb910ca5125b4aa6aa83bfc5fc8bf44fe3,V&L Net 2014 The 3rd Annual Meeting Of The EPSRC Network On Vision & Language and The 1st Technical Meeting of the European Network on Integrating Vision and Language,"V&LNet2014The3rdAnnualMeetingOfTheEPSRCNetworkOnVision&LanguageandThe1stTechnicalMeetingoftheEuropeanNetworkonIntegratingVisionandLanguageAWorkshopofthe25thInternationalConferenceonComputationalLinguistics(COLING2014)ProceedingsAugust23,2014Dublin,Ireland"
529baf1a79cca813f8c9966ceaa9b3e42748c058,Triangle wise Mapping Technique to Transform one Face Image into Another Face Image,"Triangle Wise Mapping Technique to Transform one Face Image into Another Face Image {tag} {/tag} International Journal of Computer Applications @@ -11328,11 +39335,27 @@ Rustam Ali Ahmed Bhogeswar Borah 10.5120/15209-3714 {bibtex}pxc3893714.bib{/bibtex}"
+527d596a56aa238dfc450c3ebfdae31e82c6c175,Face Detection Methods,"Face Detection Methods +ZYAD SHAABAN +Department of Information Technology +College of Computers and Information Technology +University of Tabuk +Tabuk 71491 +KINGDOM OF SAUDI ARABIA"
5239001571bc64de3e61be0be8985860f08d7e7e,Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, JUNE 2016 Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling Chi Nhan Duong, Student, IEEE, Khoa Luu, Member, IEEE, Kha Gia Quach, Student, IEEE, Tien D. Bui, Senior Member, IEEE"
+558c587373e2ea44898f70de7858da71aa217b8d,Cross-Lingual Image Caption Generation,"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pages 1780–1790, +Berlin, Germany, August 7-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
+555488f1da920bb1a06b4d19ff687805993eb7fb,Finding Speaker Face Region by Audiovisual Correlation,"Author manuscript, published in ""Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 +008, Marseille : France (2008)"""
+554b53f6e5e37d0f8c8eade1a962b39ce591f6ae,"COCO-CN for Cross-Lingual Image Tagging, Captioning and Retrieval","COCO-CN for Cross-Lingual Image Tagging, Captioning and +Retrieval +Xirong Li, Xiaoxu Wang, Chaoxi Xu, Weiyu Lan, Qijie Wei, Gang Yang, Jieping Xu +Key Lab of Data Engineering and Knowledge Engineering, Renmin University of China +Multimedia Computing Lab, Renmin University of China"
55ea0c775b25d9d04b5886e322db852e86a556cd,DOCK: Detecting Objects by transferring Common-sense Knowledge,"DOCK: Detecting Objects y transferring Common-sense Knowledge Santosh Divvala2,3[0000−0003−4042−5874], Ali Farhadi2,3[0000−0001−7249−2380], and @@ -11345,31 +39368,220 @@ Recognition in Large Dataset Sameh MEGRHI1, Marwa JMAL 2, Azeddine BEGHDADI1 and Wided Mseddi1,2 L2TI, Institut Galil´ee, Universit´e Paris 13, France; SERCOM, Ecole Polytechnique de Tunisie"
+5582aafd943f2b67805cdb4aba9e2f288dfe0ca8,"Human Object Sketches: Datasets, Descriptors, Computational Recognition and 3d Shape Retrieval","Human Object Sketches: +Datasets, Descriptors, Computational +Recognition and 3d Shape Retrieval +vorgelegt von +Mathias Eitz, Dipl.-Inf., M.Eng. +us Friedrichshafen +von der Fakultät IV - Elektrotechnik und Informatik +der Technischen Universität Berlin +zur Erlangung des akademischen Grades +Doktor der Ingenieurwissenschaften +– Dr.-Ing. – +genehmigte Dissertation +Promotionsausschuss: +Vorsitzender: Prof. Dr. Oliver Brock +Gutachter: Prof. Dr. Marc Alexa +Gutachter: Prof. Tamy Boubekeur, PhD +Tag der wissenschaftlichen Aussprache: 07.12.2012 +Berlin 2012"
+558613d96d7c125c00eae0c58c56ee6983208fd5,Identification of Unmodeled Objects from Symbolic Descriptions,"Identification of Unmodeled Objects from Symbolic Descriptions* +Andrea Baisero, Stefan Otte, Peter Englert and Marc Toussaint"
+550edcdc27aff4e7ea8807356a265a0031434a49,Fully Convolutional Attention Localization Networks: Efficient Attention Localization for Fine-Grained Recognition,"Fine-Grained Recognition with Automatic and Efficient Part Attention +Xiao Liu, Tian Xia, Jiang Wang, Yi Yang, Feng Zhou and Yuanqing Lin +Baidu Research +{liuxiao12,xiatian,wangjiang03, yangyi05, zhoufeng09,"
55c68c1237166679d2cb65f266f496d1ecd4bec6,Learning to score the figure skating sports videos,"Learning to Score Figure Skating Sport Videos Chengming Xu, Yanwei Fu, Zitian Chen,Bing Zhang, Yu-Gang Jiang, Xiangyang Xue"
+55c22f9c8f76b40793a8473248873f726abd8ce9,Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks,"Unpaired Image-to-Image Translation +using Cycle-Consistent Adversarial Networks +Jun-Yan Zhu∗ +Taesung Park∗ +Berkeley AI Research (BAIR) laboratory, UC Berkeley +Phillip Isola +Alexei A. Efros +Figure 1: Given any two unordered image collections X and Y , our algorithm learns to automatically “translate” an image +from one into the other and vice versa: (left) Monet paintings and landscape photos from Flickr; (center) zebras and horses +from ImageNet; (right) summer and winter Yosemite photos from Flickr. Example application (bottom): using a collection +of paintings of famous artists, our method learns to render natural photographs into the respective styles."
+558c4917dc9a1d34f62c0ab713b1b9a37ad04853,Action Recognition Using Multilevel Features and Latent Structural SVM,"Action Recognition Using Multilevel Features and +Latent Structural SVM +Xinxiao Wu, Dong Xu, Member, IEEE, Lixin Duan, Jiebo Luo, Fellow, IEEE, and Yunde Jia, Member, IEEE"
+55dcaee65936583846e8c4fa36589df066ebadfa,Learning to Relate Literal and Sentimental Descriptions of Visual Properties,"Atlanta, Georgia, 9–14 June 2013. c(cid:13)2013 Association for Computational Linguistics +Proceedings of NAACL-HLT 2013, pages 416–425,"
+555222f2ad6dae447eef04f96fa40c1b8a397150,CaloriNet: From silhouettes to calorie estimation in private environments,"CaloriNet: From silhouettes to calorie estimation in private +environments +Alessandro Masullo∗ +Tilo Burghardt +Victor Ponce-López +Dima Damen +Majid Mirmehdi +Sion Hannuna +June 22, 2018"
5502dfe47ac26e60e0fb25fc0f810cae6f5173c0,Affordance Prediction via Learned Object Attributes,"Affordance Prediction via Learned Object Attributes Tucker Hermans James M. Rehg Aaron Bobick"
+5582bebed97947a41e3ddd9bd1f284b73f1648c2,Grad-CAM: Why did you say that? Visual Explanations from Deep Networks via Gradient-based Localization,"Visual Explanations from Deep Networks via Gradient-based Localization +Grad-CAM: Why did you say that? +Ramprasaath R. Selvaraju +Abhishek Das +Devi Parikh +Ramakrishna Vedantam +Dhruv Batra +Virginia Tech +Michael Cogswell +{ram21, abhshkdz, vrama91, cogswell, parikh, +(a) Original Image +(b) Guided Backprop ‘Cat’ +(c) Grad-CAM for ‘Cat’ +(d) Guided Grad-CAM ‘Cat’ +(e) Occlusion Map ‘Cat’ +(f) ResNet Grad-CAM ‘Cat’ +(g) Original Image +(h) Guided Backprop ‘Dog’ +(i) Grad-CAM for ‘Dog’ +(l) ResNet Grad-CAM ‘Dog’"
+5556234869c36195ffdcd29349e5dcdf695023e9,Minimum Distance between Pattern Transformation Manifolds: Algorithm and Applications,"JULY 2009 +Minimum Distance between +Pattern Transformation Manifolds: +Algorithm and Applications +Effrosyni Kokiopoulou, Student Member, IEEE, and Pascal Frossard, Senior Member, IEEE"
+55ef8c3c28e2afda486d8471205204927127c605,Multiview Alignment Hashing for Efficient Image Search,"Multiview Alignment Hashing for Efficient Image +Search +Li Liu, Mengyang Yu, Student Member, IEEE, and Ling Shao, Senior Member, IEEE"
+5531e728850185b80835a78db2e4fd23e288f359,Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods,"Reading Hidden Emotions: Spontaneous +Micro-expression Spotting and Recognition +Xiaobai Li, Student Member, IEEE, Xiaopeng Hong, Member, IEEE, Antti Moilanen, Xiaohua Huang, Student +Member, IEEE, Tomas Pfister, Guoying Zhao, Senior Member, IEEE, and Matti Pietik¨ainen, Fellow, IEEE"
+5520acfa1f4e678f1abbaab67ec76e903c3d3bdc,SALSA: A Novel Dataset for Multimodal Group Behavior Analysis,"SALSA: A Novel Dataset for Multimodal Group +Behavior Analysis +Xavier Alameda-Pineda, Jacopo Staiano, Ramanathan Subramanian, Member, IEEE, Ligia Batrinca, +Elisa Ricci, Member, IEEE, Bruno Lepri, Oswald Lanz, Member, IEEE, Nicu Sebe, Senior Member, IEEE"
+558719ec858120908ef40b27a5d32904a68f6dd9,Toward an Automatic Evaluation of Retrieval Performance with Large Scale Image Collections,"Towards an Automatic Evaluation of Retrieval Performance +with Large Scale Image Collections +Adrian Popescu1, Eleftherios Spyromitros-Xioufis2, Symeon Papadopoulos2, Hervé Le +Borgne1, Ioannis Kompatsiaris2 +CEA, LIST, 91190 Gif-sur-Yvette, France, +CERTH-ITI, Thermi-Thessaloniki, Greece,"
+559295770dc2e2e3a1348df31ac5c3f3e66f1764,Generating Multiple Hypotheses for Human 3D Pose Consistent with 2D Joint Detections,"Generating Multiple Hypotheses for Human 3D Pose Consistent with 2D Joint Detections +Johns Hopkins University +Johns Hopkins University +Alan L. Yuille +Baltimore, USA +Ehsan Jahangiri +Baltimore, USA"
+551fedfeaf55e3f7a7cf19d2b21f1a56f8cbe9f6,Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems,"Egocentric Vision-based Future Vehicle Localization +for Intelligent Driving Assistance Systems +Yu Yao1∗, Mingze Xu2∗, Chiho Choi3, David J. Crandall2, Ella M. Atkins1, and Behzad Dariush3"
55a158f4e7c38fe281d06ae45eb456e05516af50,Simile Classifiers for Face Classification,"The 22nd International Conference on Computer Graphics and Vision GraphiCon’2012"
+55cad1f4943018459b761f89afd9292d347610f2,Self-supervised Multi-level Face Model Learning for Monocular Reconstruction at over 250 Hz,
+5543224d6f8e22e7eaabfcbc4bed9e8a9451e3f8,Automatische Bildfolgenanalyse mit statistischen Mustererkennungsverfahren,"Automatische Bildfolgenanalyse +mit statistischen +Mustererkennungsverfahren +Vom Fachbereich Elektrotechnik +der Gerhard-Mercator-Universit¨at Duisburg +zur Erlangung des akademischen Grades eines +Doktors der Ingenieurwissenschaften +genehmigte Dissertation +Dipl.-Ing. Stefan Eickeler +us Duisburg +Referent: Prof. Dr. Gerhard Rigoll +Korreferent: Prof. Dr. Martin Reiser +Tag der m¨undlichen Pr¨ufung: 5. November 2001"
5550a6df1b118a80c00a2459bae216a7e8e3966c,A perusal on Facial Emotion Recognition System ( FERS ),"ISSN: 0974-2115 www.jchps.com Journal of Chemical and Pharmaceutical Sciences A perusal on Facial Emotion Recognition System (FERS) School of Information Technology and Engineering, VIT University, Vellore, 632014, India Krithika L.B *Corresponding author: E-Mail:"
+555b332252522fce0f31b0c0b7630cf4f36ba0a5,Face processing in Williams syndrome and Autism,"Face processing in Williams syndrome and Autism +Deborah Michelle Riby +Department of Psychology, +University of Stirling"
+55ba5e4c07f6ecf827bfee04e96de35a170f7485,This Dissertation entitled MODELING THE HUMAN FACE THROUGH MULTIPLE VIEW THREE-DIMENSIONAL STEREOPSIS: A SURVEY AND COMPARATIVE ANALYSIS OF FACIAL RECOGNITION OVER MULTIPLE MODALITIES,"This Dissertation +entitled +MODELING THE HUMAN FACE THROUGH MULTIPLE +VIEW THREE-DIMENSIONAL STEREOPSIS: A SURVEY AND +COMPARATIVE ANALYSIS OF FACIAL RECOGNITION +OVER MULTIPLE MODALITIES +typeset with nddiss2"" v1.0 (2004/06/15) on July 26, 2006 for +Xin Chen +This LATEX 2"" class(cid:12)le conforms to the University of Notre Dame style guide- +lines established in Spring 2004. However it is still possible to generate a non- +onformant document if the published instructions are not followed! Be sure to re- +fer to the published Graduate School guidelines at http://graduateschool.nd.edu +s well. +It is YOUR resposnsibility to ensure that the Chapter titles and Table caption +titles are put in CAPS LETTERS. This class(cid:12)le does NOT do that! This way, +you have total control over how you want the symbols and sub-/superscripts in +titles and captions look like. +This summary page can be disabled by specifying the nosummary option to the class +invocation. (i.e., ndocumentclass[...,nosummary,...]fnddiss2eg) +THIS PAGE IS NOT PART OF THE THESIS, BUT"
+5522073ebd53a6502cec9d716a77bb2c18aca593,Multi-view Body Part Recognition with Random Forests,"KAZEMI, BURENIUS, AZIZPOUR, SULLIVAN: MULTI-VIEW BODY PART RECOGNITION 1 +Multi-view Body Part Recognition with +Random Forests +CVAP / KTH +The Royal Institute of Technology +Stockholm, Sweden +Vahid Kazemi +Magnus Burenius +Hossein Azizpour +Josephine Sullivan"
55079a93b7d1eb789193d7fcdcf614e6829fad0f,Efficient and Robust Inverse Lighting of a Single Face Image Using Compressive Sensing,"Efficient and Robust Inverse Lighting of a Single Face Image using Compressive Sensing Miguel Heredia Conde†, Davoud Shahlaei#, Volker Blanz# and Otmar Loffeld† Center for Sensor Systems† (ZESS) and Institute for Vision and Graphics#, University of Siegen 57076 Siegen, Germany"
+550c369cc3080c03b89d738d82f1ed50145c5aa7,"Information, Technology, and Information Worker Productivity","Information, Technology and Information Worker Productivity +NYU Stern School of Business & MIT, 44 West 4th Street Room: 8-81, New York, NY 10012 +MIT Sloan School of Management, Room: E53-313, 50 Memorial Drive, Cambridge, MA 02142 +Sinan Aral +Erik Brynjolfsson +Marshall Van Alstyne +Boston University & MIT, 595 Commonwealth Avenue, Boston, MA 02215 +We study the fine-grained relationships among information flows, IT use, and individual information-worker produc- +tivity, by analyzing work at a midsize executive recruiting firm. We analyze both project-level and individual-level +performance using: (1) direct observation of over 125,000 e-mail messages over a period of 10 months by individual +workers (2) detailed accounting data on revenues, compensation, project completion rates, and team membership for +over 1300 projects spanning 5 years, and (3) survey data on a matched set of the same workers’ IT skills, IT use and in- +formation sharing. These detailed data permit us to econometrically evaluate a multistage model of production and in- +teraction activities at the firm, and to analyze the relationships among communications flows, key technologies, work +practices, and output. We find that (a) the structure and size of workers’ communication networks are highly correlated +with their performance; (b) IT use is strongly correlated with productivity but mainly by allowing multitasking rather +than by speeding up work; (c) productivity is greatest for small amounts of multitasking but beyond an optimum, mul- +titasking is associated with declining project completion rates and revenue generation; and (d) asynchronous informa- +tion seeking such as email and database use promotes multitasking while synchronous information seeking over the +phone shows a negative correlation. Overall, these data show statistically significant relationships among social net-"
551fa37e8d6d03b89d195a5c00c74cc52ff1c67a,GeThR-Net: A Generalized Temporally Hybrid Recurrent Neural Network for Multimodal Information Fusion,"GeThR-Net: A Generalized Temporally Hybrid Recurrent Neural Network for Multimodal Information Fusion Ankit Gandhi1 ∗, Arjun Sharma1 ∗ , Arijit Biswas2, and Om Deshmukh1 Xerox Research Centre India; 2 Amazon Development Center India (*-equal contribution)"
+5592574c82eec9367e9173b7820ff329a27b6c21,Image Enhancement and Automated Target Recognition Techniques for Underwater Electro-Optic Imagery,"Image Enhancement and Automated Target Recognition +Techniques for Underwater Electro-Optic Imagery +Thomas Giddings (PI), Cetin Savkli and Joseph Shirron +Metron, Inc. +1911 Freedom Dr., Suite 800 +Reston, VA 20190 +phone: (703) 437-2428 fax: (703) 787-3518 email: +Contract Number N00014-07-C-0351 +http:www.metsci.com +LONG TERM GOALS +The long-term goal of this project is to provide a flexible, accurate and extensible automated target +recognition (ATR) system for use with a variety of imaging and non-imaging sensors. Such an ATR +system, once it achieves a high level of performance, can relieve human operators from the tedious +usiness of pouring over vast quantities of mostly mundane data, calling the operator in only when the +omputer assessment involves an unacceptable level of ambiguity. The ATR system will provide most +leading edge algorithms for detection, segmentation, and classification while incorporating many novel +lgorithms that we are developing at Metron. To address one of the most critical challenges in ATR +technology, the system will also provide powerful feature extraction routines designed for specific +pplications of current interest. +OBJECTIVES"
55c40cbcf49a0225e72d911d762c27bb1c2d14aa,Indian Face Age Database : A Database for Face Recognition with Age Variation,"Indian Face Age Database: A Database for Face Recognition with Age Variation {tag} {/tag} International Journal of Computer Applications @@ -11381,6 +39593,39 @@ Authors: Reecha Sharma, M.S. Patterh 10.5120/ijca2015906055 {bibtex}2015906055.bib{/bibtex}"
+55202f10bb1d7640b0b279a4cdc8e9925cd9ef81,ICM: An Intuitive Model Independent and Accurate Certainty Measure for Machine Learning,
+9717bd66ad50aedabaea0f3af784c7ba9643b686,TransFlow: Unsupervised Motion Flow by Joint Geometric and Pixel-level Estimation,"TransFlow: Unsupervised Motion Flow by Joint +Geometric and Pixel-level Estimation +Stefano Alletto*, Davide Abati, Simone Calderara, Rita Cucchiara +University of Modena and Reggio Emilia +Via P. Vivarelli 10, Modena, Italy +Luca Rigazio* +Panasonic Silicon Valley Laboratory +0900 North Tantau Avenue, Suite 200, Cupertino, CA, USA"
+97692960a11d4316880fb229cca699293e133945,An efficient multi-resolution SVM network approach for object detection in aerial images,"015 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, SEPT. 17–20, 2015, BOSTON, USA +AN EFFICIENT MULTI-RESOLUTION SVM NETWORK APPROACH FOR OBJECT +DETECTION IN AERIAL IMAGES +J. Pasquet(cid:63)† +M. Chaumont∗† +G. Subsol † +M. Derras(cid:63) +LIRMM, Universit´e de Montpellier / CNRS, France +(cid:63) Berger Levrault, Lab`ege, France +Universit´e de Nˆımes, France"
+970e571305ed9dde9308e559694044e204d6e2ad,Learning Finer-class Networks for Universal Representations,"GIRARD ET AL.: FINER-CLASS NETWORKS +Learning Finer-class Networks for Universal +Representations +Julien Girard12 +Youssef Tamaazousti123 +Hervé Le Borgne2 +Céline Hudelot3 +Both authors contributed equally. +CEA LIST +Vision Laboratory, +Gif-sur-Yvette, France. +CentraleSupélec, +MICS Laboratory, +Châtenay-Malabry, France."
973e3d9bc0879210c9fad145a902afca07370b86,From Emotion Recognition to Website Customizations,"(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7, No. 7, 2016 From Emotion Recognition to Website @@ -11389,11 +39634,38 @@ O.B. Efremides School of Web Media Bahrain Polytechnic Isa Town, Kingdom of Bahrain"
+97104def2b92b430c02f595d7802f9ba23b74cc7,DispSegNet: Leveraging Semantics for End-to-End Learning of Disparity Estimation from Stereo Imagery,"DispSegNet: Leveraging Semantics for End-to-End Learning of +Disparity Estimation from Stereo Imagery +Junming Zhang1, Katherine A. Skinner2, Ram Vasudevan3 and Matthew Johnson-Roberson4"
97b8249914e6b4f8757d22da51e8347995a40637,"Large-Scale Vehicle Detection, Indexing, and Search in Urban Surveillance Videos","Large-Scale Vehicle Detection, Indexing, nd Search in Urban Surveillance Videos Rogerio Schmidt Feris, Associate Member, IEEE, Behjat Siddiquie, James Petterson, Yun Zhai, Associate Member, IEEE, Ankur Datta, Lisa M. Brown, Senior Member, IEEE, and Sharath Pankanti, Fellow, IEEE"
+9728c3e32f57b54dea94fa9737c8f300de5cc468,Imbalanced Malware Images Classification: a CNN based Approach,"Imbalanced Malware Images Classification: a CNN +ased Approach +Songqing Yue +University of Wisconsin"
+97bcf007516cb70d8cb17b7de6452aa06c4b9c76,GABAergic neurotransmission alterations in autism spectrum disorders,"Neurotransmitter 2015; 2: e1052. doi: 10.14800/nt.1052; © 2015 by Carla V Sesarini +http://www.smartscitech.com/index.php/nt +REVIEW +GABAergic neurotransmission alterations in autism spectrum +disorders +Carla V Sesarini +Instituto de Ciencias Básicas y Medicina Experimental (ICBME), Instituto Universitario del Hospital Italiano de Buenos Aires +(HIBA), Potosi 4240 (C1199ACL), CABA, Argentina +Correspondence: Carla V Sesarini +E-mail: +Received: October 04, 2015 +Published online: November 09, 2015 +Autism spectrum disorders (ASDs) are a group of complex disorders of neurodevelopment characterized by +difficulties in social interaction, verbal and nonverbal communication, and repetitive behaviors. In ASD, deficits +in social cognition and related cognitive functions would be the resultant of reduced synchronization between +rain regions. A possible explanation for ASDs is the disturbance of the delicate balance between excitation and +inhibition in the developing brain which may have profound impact in neurobehavioral phenotypes. At least +some forms of autism would be caused by a disproportionately high level of excitation (or weaker inhibition) in +neural circuits that mediate language and social behavior (local circuits). A more excitable cortex (more weakly +inhibited) is functionally more poorly differentiated and could lead to broad ranging abnormalities in"
972ef9ddd9059079bdec17abc8b33039ed25c99c,A Novel on understanding How IRIS Recognition works,"International Journal of Innovations in Engineering and Technology (IJIET) A Novel on understanding How IRIS Recognition works @@ -11407,6 +39679,17 @@ M.P.M. College, Bhopal, India" Peter Collingbourne, Nakul Durve, Khilan Gudka, Steve Lovegrove, Jiefei Ma, Sadegh Shahrbaf Supervisor: Professor Duncan Gillies January 11, 2006"
+97b54703c267deef8c86ab6240c24d76a59864e7,Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos,"Pixel Objectness: Learning to Segment Generic +Objects Automatically in Images and Videos +Bo Xiong∗, Suyog Dutt Jain∗, and Kristen Grauman, Member, IEEE"
+97a0aba4e9a95db17c3d4367f59aad1f02e04b55,How far did we get in face spoofing detection?,"This manuscript is a preprint version. The final version of this paper is +vailable in Engineering Applications of Artificial Intelligence, vol. 72, +pp. 368-381, 2018. DOI: 10.1016/j.engappai.2018.04.013 +How far did we get in face spoofing detection? +Luiz Souza, Luciano Oliveira, Mauricio Pamplona +IVISION Lab, Federal University of Bahia +Joao Papa +RECOGNA Lab, S˜ao Paulo State University"
97f9c3bdb4668f3e140ded2da33fe704fc81f3ea,An Experimental Comparison of Appearance and Geometric Model Based Recognition,"AnExperimentalComparisonofAppearance ndGeometricModelBasedRecognition J.Mundy,A.Liu,N.Pillow,A.Zisserman,S.Abdallah,S.Utcke, @@ -11415,6 +39698,14 @@ S.NayarandC.Rothwell RoboticsResearchGroup,UniversityofOxford,Oxford,UK Dept.ofComputerScience,ColumbiaUniversity,NY,USA INRIA,SophiaAntipolis,France"
+97d811ae99bcbcf9f63c2f447041ab6d74a20b1e,Face recognition using truncated transform domain feature extraction,"The International Arab Journal of Information Technology, Vol. 12, No. 3, May 2015 211 +Face Recognition using Truncated Transform +Domain Feature Extraction +Rangan Kodandaram, Shashank Mallikarjun, Manikantan Krishnamuthan, and Ramachandran Sivan +Department of Electronics and Communication Engineering, M.S. Ramaiah Institute of Technology, India"
+9729ff547b6882b49898c1f5abb69646edf77e71,Two Kinds of Statistics for Better Face Recognition,"Two Kinds of Statistics for Better Face Recognition +Manuel Günther, Marco K. Müller and Rolf P. Würtz +Institut für Neuroinformatik, Ruhr-Universität, 44780 Bochum, Germany"
97cf04eaf1fc0ac4de0f5ad4a510d57ce12544f5,"Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond","manuscript No. (will be inserted by the editor) Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, @@ -11426,6 +39717,14 @@ Zafeiriou4" A Survey Yun Fu, Member, IEEE, Guodong Guo, Senior Member, IEEE, and Thomas S. Huang, Fellow, IEEE"
+97e7810f21a145caddc7e5168b59f0ab8894f669,Technical Report: Learning to Rank using High-Order Information,"Technical Report: Learning to Rank using +High-Order Information +Puneet K. Dokania1, Aseem Behl2, C. V. Jawahar2, and M. Pawan Kumar1 +Ecole Centrale de Paris1, INRIA Saclay1, IIIT Hyderabad - India2"
+97ee35db6b389a7bcc4b7975d12dbcd165226aad,Structured Learning of Human Interactions in TV Shows,"Structured Learning +of Human Interactions in TV Shows +Alonso Patron-Perez, Member, IEEE, Marcin Marszalek, +Ian Reid, Member, IEEE, and Andrew Zisserman"
97865d31b5e771cf4162bc9eae7de6991ceb8bbf,Face and Gender Classification in Crowd Video,"Face and Gender Classification in Crowd Video Priyanka Verma IIIT-D-MTech-CS-GEN-13-100 @@ -11439,13 +39738,128 @@ Submitted in partial fulfillment of the requirements for the Degree of M.Tech. in Computer Science (cid:13) Verma, 2015 Keywords : Face Recognition, Gender Classification, Crowd database"
+97ede92a6a3579f9fc8ad7c179eaaf37b3966e5a,Bicycle tracking using ellipse extraction,"Bicycle Tracking Using Ellipse Extraction +Tohid Ardeshiri, Fredrik Larsson, Fredrik Gustafsson, Thomas B. Sch¨on, Michael Felsberg +Department of Electrical Engineering +Link¨oping University +Link¨oping, Sweden +e-mail: {tohid, larsson, fredrik, schon,"
+978d9a5251028da5a23fd0aed8234ed22b4918c5,Reduced Eigen Space Dimensionality for Fast Face Recognition,"www.ijemr.net +ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962 +Volume-5, Issue-2, April-2015 +International Journal of Engineering and Management Research +Page Number: 33-39 +Reduced Eigen Space Dimensionality for Fast Face Recognition +Research Scholar, Department of Computer Science and Applications, Panjab University, Chandigarh, INDIA +Professor, Department of Computer Science and Applications, Panjab University, Chandigarh, INDIA +Davoud Aflakian1, M. Syamala Devi2"
+979f63114a30d60c5c06d4c9c18c8249c3a63099,Synthetically Trained Neural Networks for Learning Human-Readable Plans from Real-World Demonstrations,"Synthetically Trained Neural Networks for Learning +Human-Readable Plans from Real-World Demonstrations +Jonathan Tremblay +Thang To +Artem Molchanov† +Stephen Tyree +Jan Kautz +Stan Birchfield"
+9709d362a15414b062efa9cf4a212469af803a7a,Holistic Multi-modal Memory Network for Movie Question Answering,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Holistic Multi-modal Memory Network +for Movie Question Answering +Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar"
+9727c74a09aad74abd67ff1d2dff083cc73d4a2e,Visual Focus of Attention in Non-calibrated Environments using Gaze Estimation,"Int J Comput Vis +DOI 10.1007/s11263-013-0691-3 +Visual Focus of Attention in Non-calibrated Environments using +Gaze Estimation +Stylianos Asteriadis · Kostas Karpouzis · +Stefanos Kollias +Received: 24 May 2012 / Accepted: 2 December 2013 +© Springer Science+Business Media New York 2013"
+970e723404885e94e77780766b39ee951dd7abb3,Multimodal Learning of Geometry-Preserving Binary Codes for Semantic Image Retrieval,"IEICE TRANS. INF. & SYST., VOL.E100–D, NO.4 APRIL 2017 +INVITED PAPER SpecialSectiononAward-winningPapers +Multimodal Learning of Geometry-Preserving Binary Codes for +Semantic Image Retrieval +Go IRIE†a), Hiroyuki ARAI†, Members, and Yukinobu TANIGUCHI††, Senior Member +SUMMARY +This paper presents an unsupervised approach to feature +inary coding for efficient semantic image retrieval. Although the majority +of the existing methods aim to preserve neighborhood structures of the fea- +ture space, semantically similar images are not always in such neighbors +ut are rather distributed in non-linear low-dimensional manifolds. More- +over, images are rarely alone on the Internet and are often surrounded by +text data such as tags, attributes, and captions, which tend to carry rich se- +mantic information about the images. On the basis of these observations, +the approach presented in this paper aims at learning binary codes for se- +mantic image retrieval using multimodal information sources while pre- +serving the essential low-dimensional structures of the data distributions in +the Hamming space. Specifically, after finding the low-dimensional struc- +tures of the data by using an unsupervised sparse coding technique, our +pproach learns a set of linear projections for binary coding by solving an"
+9715aba0688195b2019d510ae3fd8da2e40f6e20,Evaluation of color spaces for person re-identification,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-1-6 ©2012 IAPR"
+97d9c57576a573955c1b21b63f5b5ae44438e973,Discriminative on Multi - Manifolds,
9755554b13103df634f9b1ef50a147dd02eab02f,How Transferable Are CNN-Based Features for Age and Gender Classification?,"How Transferable are CNN-based Features for Age and Gender Classification? Gökhan Özbulak1, Yusuf Aytar2 and Hazım Kemal Ekenel1"
+9794d69194ac772c3e92ee1f322a36feb3c16239,Hausdorff Artmap for Human Face Recognition,"HAUSDORFF ARTMAP FOR HUMAN FACE RECOGNITION +ARIT THAMMANO AND CHONGKOLNEE RUNGRUANG +Faculty of Information Technology +King Mongkut’s Institute of Technology Ladkrabang, +Bangkok, 10520 Thailand +later +received +identification has +encompasses +ll of"
+63ebe80e020d902bc1fdc865c23a9ad7d1eac17a,Exploring the feasibility of subliminal priming on smartphones,"Exploring the Feasibility of Subliminal Priming on +Anonymised for blind review +Smartphones +Affiliation +City, Country +e-mail address"
63cf5fc2ee05eb9c6613043f585dba48c5561192,Prototype Selection for Classification in Standard and Generalized Dissimilarity Spaces Prototype Selection for Classification in Standard and Generalized Dissimilarity Spaces,"Prototype Selection for Classification in Standard nd Generalized Dissimilarity Spaces"
+63db312ec494988e1af0c1db5f9d9ca40ef89237,Vision Based Gesture Recognition : a Comprehensive Study,"REGULAR ISSUE +ARTICLE +VISION BASED GESTURE RECOGNITION: A COMPREHENSIVE +STUDY +A Balasundaram1*, C Chellappan 2 +Research Scholar, Department of CSE, G.K.M. College of Engineering and Technology, Chennai, INDIA +Principal, G.K.M. College of Engineering and Technology, Chennai, INDIA"
+63f2c3e312d07c6452bdad0a8adef1b879950500,Multi-stage Sampling with Boosting Cascades for Pedestrian Detection in Images and Videos,"Multi-stage Sampling with Boosting Cascades +for Pedestrian Detection in Images and Videos +Giovanni Gualdi, Andrea Prati, and Rita Cucchiara +University of Modena and Reggio Emilia(cid:2), Italy"
+63cbfc7bfabd1e234c779f8445ea775b74d8fbe8,Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks,"Adequacy of the Gradient-Descent Method for +Classifier Evasion Attacks +Yi Han +School of Computing and Information Systems +University of Melbourne +Ben Rubinstein +School of Computing and Information Systems +University of Melbourne"
+63dbacac269c29b46b2b0bddbef828db025689dd,Deep Structure Inference Network for Facial Action Unit Recognition,"Deep Structure Inference Network for Facial Action Unit Recognition +Ciprian A. Corneanu1, Meysam Madadi2,3, Sergio Escalera1,2 +Dept. Mathematics and Informatics, Universitat de Barcelona, Catalonia, Spain +Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra (Barcelona), Catalonia, Spain +Dept. of Computer Science, Univ. Aut`onoma de Barcelona (UAB), 08193 Bellaterra, Catalonia, Spain"
+6358b95b1c97df4f10f57a90913f672e44d2094b,Opponent Colors for Human Detection,"Opponent Colors for Human Detection +Rao Muhammad Anwer, David V´azquez, and Antonio M. L´opez +Computer Vision Center and Computer Science Dpt., +Universitat Aut`onoma de Barcelona +-- www.cvc.uab.es/adas +Edifici O, 08193 Bellaterra, Barcelona, Spain"
+631d21e51ca9100f1eca3c80dcf42db81cfc7e2b,Interactive Person Following and Gesture Recognition with a Flying Robot,"Interactive Person Following and +Gesture Recognition with a Flying Robot +Tayyab Naseer*, J¨urgen Sturm†, Wolfram Burgard*, and Daniel Cremers† +*Department of Computer Science, University of Freiburg, Germany +Department of Computer Science, Technical University of Munich, Germany"
+637648198f9e91654ce27eaaa40512f2dc870fc1,Survey of Visual Question Answering: Datasets and Techniques,"Survey of Visual Question Answering: Datasets and Techniques +Akshay Kumar Gupta +Indian Institute of Technology Delhi"
+63b89e654124eb2b8edeeb82c6373bdcf228744e,Single-Image 3D Scene Parsing Using Geometric Commonsense,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +image I3D reconstructed sceneFigure1:Single-view3DscenereconstructionusingGeometriccommonsense.Top:theworldisfullofcommonsenseovergeo-metricdimensions,e.g.,thatasedanisabout4.5meterslong.Bot-tom:exemplarresultoftheproposedmethod,includingsynthesizedimage(left),planarsegmentation(middle),anddepthmap(right).geometriccommonsensefor3Dsceneparsing.Suchapars-ingtaskaimstosegmentbothlow-levelsceneentities(e.g.,straightedges,semanticregions)andobject-levelsceneenti-ties(e.g.,human,vehicles)in2Dimages,andestimatetheirgeometricdimensionsinthe3Dworld[Hoiemetal.,2005;DelPeroetal.,2013;Liuetal.,2014;Wangetal.,2015a;Mottaghietal.,2016].Mostexisting3Dparsingalgo-rithms[Hoiemetal.,2008]aredesignedforaparticu-lartypeofscenecategories,e.g.,urban[Liuetal.,2014;Guptaetal.,2010],indoor[Wangetal.,2015b].Howev-er,apracticalAIsystem,e.g.,autonomousdriving,usuallyneedstodealwithawidevarietyofscenecategories.Oursolutiontotheabovechallengesismotivatedbythefactthatwehumanbeings,unconsciouslysometimes,uti-lizerichpriorknowledgeofthegeometricdimensionsofsceneentitiestounderstandthescenestructuresinimagesorvideos[Davisetal.,1993].Thisknowledgecanberoughlydividedintotwotypes:i)priordistributionsoverasingledi-mensionofobjects,e.g.,theheightofafemaleadultisabout1.75meters,orthatthelengthofasedanisabout4.5meters;ii)pair-wisecomparisonsbetweenthedimensionsofdifferentsceneentitiesatbothobject-level,e.g.,human,windows,ve-hicles,etc.,andpart-level,e.g.,straightedges,planarregions,etc.AsillustratedinFigure1,forexample,thewindowedgesonthesamefacadeareparalleltoeachotherandareorthog-onaltotheedgesontheground,abuildingishigherthanahuman,orthelengthofallsedansareroughlyequal.Theseu-naryandpair-wiseknowledge,onceacquired,arevalidacross"
63c109946ffd401ee1195ed28f2fb87c2159e63d,Robust Facial Feature Localization Using Improved Active Shape Model and Gabor Filter,"MVA2011 IAPR Conference on Machine Vision Applications, June 13-15, 2011, Nara, JAPAN Robust Facial Feature Localization using Improved Active Shape Model and Gabor Filter @@ -11453,6 +39867,21 @@ Hui-Yu Huang Engineering, National Formosa University, Taiwan E-mail:"
+63db76fc3ab23beb921be682d70eb021cb6c4f16,How Polarized Have We Become? A Multimodal Classification of Trump Followers and Clinton Followers,
+634f698c05d640ab355e94a9a0cf9191891b3dcb,Video Face Recognition From A Single Still Image Using an Adaptive Appearance Model Tracker,"Video Face Recognition From A Single Still Image +Using an Adaptive Appearance Model Tracker +M. Ali Akber Dewan +E. Granger, R. Sabourin +G.-L. Marcialis, F. Roli +School of Computing and Information +Systems, Athabasca University +Department of Automated Production +Engineering, École de technologie supé- +Department of Electrical and Electronic +Engineering, University of Cagliari +Edmonton, Canada +rieure, Montreal, Canada +Cagliari, Italy"
631483c15641c3652377f66c8380ff684f3e365c,Sync-DRAW: Automatic GIF Generation using Deep Recurrent Attentive Architectures,"Sync-DRAW: Automatic Video Generation using Deep Recurrent A(cid:130)entive Architectures Gaurav Mi(cid:138)al∗ @@ -11460,6 +39889,20 @@ Tanya Marwah∗ IIT Hyderabad Vineeth N Balasubramanian IIT Hyderabad"
+636027f52ab111b2b22332ab2ec5346d03aac305,Unsupervised learning of foreground object detection,"Unsupervised learning of foreground object detection +Ioana Croitoru · Simion-Vlad Bogolin · Marius Leordeanu"
+63cdf4aa1492c5c8fb109a1bf03af4844982e265,Reconstructing High-Resolution Face Models From Kinect Depth Sequences,"Reconstructing High-Resolution Face Models +From Kinect Depth Sequences +Enrico Bondi, Pietro Pala, Senior Member, IEEE, Stefano Berretti, Member, IEEE, +nd Alberto Del Bimbo, Senior Member, IEEE"
+6372262685162f3f11ef7ac1882c327e98564875,A Survey of Approaches for Curve Based Facial Surface Representations For Three-Dimensional Face Recognition,"A Survey of Approaches for Curve Based Facial Surface Representations +For Three-Dimensional Face Recognition +Aouragh Salima1,3, Sbaa Salim2, Taleb-Ahmed Abdelmalik3 +Department of Electrical engineering, Kasdi Merbah University, Ouargla, Algeria. +Department of Electrical engineering, Mohamed Kheider University, Biskra, Algeria. +LAMIH UMR CNRS 8201 UVHC, University of Valenciennes and Hainaut Cambrésis, France."
+63c65e8584d2c3fb8833af772eb713f438cbdfe0,Exposing seam carving forgery under recompression attacks by hybrid large feature mining,"Cancún Center, Cancún, México, December 4-8, 2016 +978-1-5090-4846-5/16/$31.00 ©2016 IEEE"
632fa986bed53862d83918c2b71ab953fd70d6cc,What Face and Body Shapes Can Tell About Height,"GÜNEL ET AL.: WHAT FACE AND BODY SHAPES CAN TELL ABOUT HEIGHT What Face and Body Shapes Can Tell About Height @@ -11472,6 +39915,47 @@ Lausanne, Switzerland" 63340c00896d76f4b728dbef85674d7ea8d5ab26,Discriminant Subspace Analysis: A Fukunaga-Koontz Approach,"Discriminant Subspace Analysis: A Fukunaga-Koontz Approach Sheng Zhang, Member, IEEE, and Terence Sim, Member, IEEE"
+635bea02dae6d4402b53eb3b31930b53ef00adc0,Unsupervised Feature Learning for Dense Correspondences Across Scenes,"Unsupervised Feature Learning for Dense Correspondences +cross Scenes +Chao Zhang, Chunhua Shen, Tingzhi Shen +v1 July 2014; v2 December 2014; v3 April 2015"
+63c71e317168d5b55dccaf5515ad96c9e87f7d9e,"Part-Based RDF for Direction Classification of Pedestrians, and a Benchmark","Part-based RDF for Direction Classification +of Pedestrians, and a Benchmark +Junli Tao and Reinhard Klette +The .enpeda.. Project, Tamaki Campus +The University of Auckland, Auckland, New Zealand"
+63344dee49a1ab7e27ac34eefc30fb948a0bf9bb,Geometry and Illumination Modelling for Scene Understanding,"Geometry and Illumination Modelling for Scene Understanding +Principal Investigators: Jana Koˇseck´a and Dimitris Samaras +Project Summary The goal this proposal is to develop unified framework for reasoning about +objects, scenes and lighting from single and multiple views of indoors and outdoors environments. +We propose computational models for semantic parsing of scenes which incorporate information +bout the lighting and illumination to resolve the ambiguities of purely appearance based methods +nd develop class of models where partial geometry and semantic information aid the process of +recovery of illumination. The proposed work can be partitioned into three main research topics: +. Supervised approach for semantic parsing of object and non-object categories using photo- +metric, geometric and shadow cues. +. Closing the loop on estimation of Illumination using coarse object models and geometric +ontext. +. Object recognition, change detection, scene matching and 3D reconstruction with dramatic +hanges in illumination. +We propose to study the interactions between appearance, geometry and lighting in the context +of the problems outlined above and develop computational models which jointly consider these +spects. In some cases different models will serve as preprocessing stage for the follow up prob- +lems and in others they will interact jointly or in a feedback loop manner. For joint interactions +final inference for estimation of semantic categories and illumination will be formulated in Markov +Random field or Conditional Markov Random field using both photometric, geometric and illumi-"
+6388c3f3559b61632942856bbede67b724542c9e,Multi-Target Tracking Using Hierarchical Convolutional Features and Motion Cues,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 8, No. 11, 2017 +Multi-Target Tracking Using Hierarchical +Convolutional Features and Motion Cues +Heba Mahgoub, Khaled Mostafa, Khaled T. Wassif, Ibrahim Farag +Faculty of Computers and Information +Cairo University +Cairo, Egypt"
+63f38f60022ab78aa5e47bd84070547409ab3cc8,The Use of Semantic Human Description as a Soft Biometric,"The Use of Semantic Human Description as a Soft Biometric +Sina Samangooei +Baofeng Guo +Mark S. Nixon"
634541661d976c4b82d590ef6d1f3457d2857b19,Advanced Techniques for Face Recognition under Challenging Environments,"AAllmmaa MMaatteerr SSttuuddiioorruumm –– UUnniivveerrssiittàà ddii BBoollooggnnaa in cotutela con Università di Sassari DOTTORATO DI RICERCA IN @@ -11507,6 +39991,62 @@ Department of Electrical and Computer Engineering, 2 School of Computing, Nation {zheng.s, Advanced Digital Sciences Center, Singapore; 4 Facebook"
63c022198cf9f084fe4a94aa6b240687f21d8b41,Consensus Message Passing for Layered Graphical Models,
+63c7c0511e82172b6b60af21e56df68e2c6ab228,Target-based evaluation of face recognition technology for video surveillance applications,"Target-based evaluation of face recognition +technology for video surveillance applications +Dmitry Gorodnichy and Eric Granger"
+0f5e10cfca126682e1bad1a07848919489df6a65,Facial emotion processing in patients with social anxiety disorder and Williams-Beuren syndrome: an fMRI study.,"Research Paper +Facial emotion processing in patients with social +nxiety disorder and Williams–Beuren syndrome: +n fMRI study +Cynthia Binelli, PhD; Armando Muñiz, MD; Susana Subira, MD, PhD; +Ricard Navines, MD, PhD; Laura Blanco-Hinojo, MSc; Debora Perez-Garcia, BSc; +Jose Crippa, MD, PhD; Magi Farré, MD, PhD; Luis Pérez-Jurado, MD, PhD; +Jesus Pujol, MD, PhD; Rocio Martin-Santos, MD, PhD +Background: Social anxiety disorder (SAD) and Williams–Beuren syndrome (WBS) are 2 conditions with major differences in terms of +genetics, development and cognitive profiles. Both conditions are associated with compromised abilities in overlapping areas, including so- +ial approach, processing of social emotional cues and gaze behaviour, and to some extent they are associated with opposite behaviours in +these domains. We examined common and distinct patterns of brain activation during a facial emotion processing paradigm in patients with +SAD and WBS. Methods: We examined patients with SAD and WBS and healthy controls matched by age and laterality using functional +MRI during the processing of happy, fearful and angry faces. Results: We included 20 patients with SAD and 20 with WBS as well as +0 matched controls in our study. Patients with SAD and WBS did not differ in the pattern of limbic activation. We observed differences in +early visual areas of the face processing network in patients with WBS and differences in the cortical prefrontal regions involved in the top– +down regulation of anxiety and in the fusiform gyrus for patients with SAD. Compared with those in the SAD and control groups, participants +in the WBS group did not activate the right lateral inferior occipital cortex. In addition, compared with controls, patients with WBS hypoacti- +vated the posterior primary visual cortex and showed significantly less deactivation in the right temporal operculum. Participants in the SAD +group showed decreased prefrontal activation compared with those in the WBS and control groups. In addition, compared with controls,"
+0f0499989f3331396af94f92c29f2eda9b58d4dc,Object detection methods for robot grasping: Experimental assessment and tuning,"Object detection methods for robot +grasping: Experimental assessment and +tuning +Ferran RIGUAL a,1, Arnau RAMISA a, Guillem ALENYA a and Carme TORRAS a +Institut de Rob`otica i Inform`atica Industrial, CSIC-UPC, Barcelona"
+0f4b902a2e12378e0ac0cb6fff7dd4c5f81e2c0a,Capturing facial videos with Kinect 2.0: A multithreaded open source tool and database,"Capturing Facial Videos with Kinect 2.0: +A Multithreaded Open Source Tool and Database +Daniel Merget +Tobias Eckl +Institute for Human-Machine Communication, TUM, Germany +Philipp Tiefenbacher +Martin Schwoerer +Gerhard Rigoll"
+0f5bf2a208d262aa0469bd3185f6e2e56acada81,Pose Estimation and Segmentation of People in 3D Movies,"Pose Estimation and Segmentation of People in 3D +Movies +Karteek Alahari, Guillaume Seguin, Josef Sivic, Ivan Laptev +To cite this version: +Karteek Alahari, Guillaume Seguin, Josef Sivic, Ivan Laptev. Pose Estimation and Segmentation of +People in 3D Movies. ICCV - IEEE International Conference on Computer Vision, Dec 2013, Sydney, +Australia. IEEE, pp.2112-2119, 2013, <10.1109/ICCV.2013.263>. <hal-00874884> +HAL Id: hal-00874884 +https://hal.inria.fr/hal-00874884 +Submitted on 18 Oct 2013 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
0f65c91d0ed218eaa7137a0f6ad2f2d731cf8dab,Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition,"Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition Changxing Ding, Jonghyun Choi, Dacheng Tao, Senior Member, IEEE, and Larry S. Davis, Fellow, IEEE"
@@ -11514,6 +40054,17 @@ Changxing Ding, Jonghyun Choi, Dacheng Tao, Senior Member, IEEE, and Larry S. Da Unsang Park, Member, IEEE, Yiying Tong, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+0f07dcf92588945eb0d70893cdf0fe4a48552763,Detection- and Trajectory-Level Exclusion in Multiple Object Tracking,"Detection- and Trajectory-Level Exclusion in Multiple Object Tracking +Anton Milan1 +Konrad Schindler2 +Stefan Roth1 +Department of Computer Science, TU Darmstadt +Photogrammetry and Remote Sensing Group, ETH Z¨urich"
+0fbf59328d32e1a9950dfa08c3ec87eb94398651,Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks,"Beyond RGB: Very High Resolution Urban Remote +Sensing With Multimodal Deep Networks +Nicolas Audeberta,b,, Bertrand Le Sauxa, Sébastien Lefèvreb +ONERA, The French Aerospace Lab, F-91761 Palaiseau, France +Univ. Bretagne-Sud, UMR 6074, IRISA, F-56000 Vannes, France"
0f4cfcaca8d61b1f895aa8c508d34ad89456948e,Local appearance based face recognition using discrete cosine transform,"LOCAL APPEARANCE BASED FACE RECOGNITION USING DISCRETE COSINE TRANSFORM (WedPmPO4) Author(s) :"
@@ -11527,6 +40078,35 @@ UT Austin Fei Sha Kristen Grauman UT Austin"
+0f085f389a52e13586fe50f2dae49e105225303f,Distribution-sensitive learning for imbalanced datasets,"Distribution-Sensitive +Learning +for Imbalanced +Datasets +Yale Songl, Louis-Philippe +Morency2, and Randall Davisl +MIT Computer Science and Artificial +Intelligence +Laboratory +USC Institute +for Creative Technology"
+0f708ace6f4829e466a8a549bd23f6fcf719ab9d,Multi-shot person re-identification via relational Stein divergence,"This is the author’s version of a work that was submitted/accepted for pub- +lication in the following source: +Alavi, Azadeh, Yang, Yan, Harandi, Mehrtash, & Sanderson, Conrad +(2013) +Multi-shot person re-identification via relational stein divergence. In +ICIP 2013 Proceedings : 2013 IEEE International Conference on Image +Processing, Institute of Electrical and Electronics Engineers, Inc., Mel- +ourne Convention and Exhibition Centre, Melbourne, pp. 3542-3546. +This file was downloaded from: https://eprints.qut.edu.au/71704/ +(cid:13) c(cid:13) 2013 by the Institute of Electrical and Electronics +Engineers, Inc. +Notice: Changes introduced as a result of publishing processes such as +opy-editing and formatting may not be reflected in this document. For a +definitive version of this work, please refer to the published source: +https://doi.org/10.1109/ICIP.2013.6738731"
+0fe5d8acc77f54d60edc56c012f35517d9c861da,Interactive Stereoscopic Video Conversion,"Interactive Stereoscopic Video Conversion +Zhebin Zhang, Chen Zhou, Yizhou Wang, and Wen Gao, Fellow, IEEE +erial perspective,"
0fd1715da386d454b3d6571cf6d06477479f54fc,A Survey of Autonomous Human Affect Detection Methods for Social Robots Engaged in Natural HRI,"J Intell Robot Syst (2016) 82:101–133 DOI 10.1007/s10846-015-0259-2 A Survey of Autonomous Human Affect Detection Methods @@ -11536,6 +40116,38 @@ Naoaki Hatakeyama · Goldie Nejat · Beno Benhabib Received: 10 December 2014 / Accepted: 11 August 2015 / Published online: 23 August 2015 © Springer Science+Business Media Dordrecht 2015"
+0f08d62e882026ac83ebf26c0bd288c553873814,Multispecies Fruit Flower Detection Using a Refined Semantic Segmentation Network,"Multispecies fruit flower detection using a refined +semantic segmentation network +Philipe A. Dias1, Amy Tabb2, and Henry Medeiros1"
+0f94f4934d0a26dfd243852036468ecc9bf8d22c,Low Resolution Lidar-Based Multi-Object Tracking for Driving Applications,"Low resolution lidar-based multi-object tracking +for driving applications +Iv´an del Pino(cid:63), V´ıctor Vaquero(cid:63), Beatrice Masini, +Joan Sol`a, Francesc Moreno-Noguer, +Alberto Sanfeliu, and Juan Andrade-Cetto +Institut de Rob`otica i Inform`atica Industrial, CSIC-UPC +Llorens Artigas 4-6, 08028 Barcelona, Spain. +http://www.iri.upc.edu"
+0f1392c1180582a45b42e621e1526f03cc6e9ca6,Learning with Hierarchical-Deep Models,"Learning with Hierarchical-Deep Models +Ruslan Salakhutdinov, Joshua B. Tenenbaum, and Antonio Torralba"
+0fb75f5cb12d1e1a909b9f698b7617bb9603002f,Design of Weight-Learning Efficient Convolutional Modules in Deep Convolutional Neural Networks and its Application to Large-Scale Visual Recognition Tasks,"Data Analysis Project +Design of Weight-Learning Efficient Convolutional Modules in Deep +Convolutional Neural Networks and its Application to +Large-Scale Visual Recognition Tasks +Felix Juefei-Xu +May 3, 2017"
+0f366de3ea595932dad06389f6e61fe0dd8cbe74,DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field,"Article +DeepAnomaly: Combining Background Subtraction +nd Deep Learning for Detecting Obstacles and +Anomalies in an Agricultural Field +Peter Christiansen 1,*, Lars N. Nielsen 2, Kim A. Steen 3, Rasmus N. Jørgensen 1 and +Henrik Karstoft 1 +Department of Engineering, Aarhus University, Aarhus 8200, Denmark; +(R.N.J.); (H.K.) +Danske Commodities, Aarhus 8000, Denmark; +AgroIntelli, Aarhus 8200, Denmark; +* Correspondence: Tel.: +45-2759-2953 +Academic Editors: Gabriel Oliver-Codina, Nuno Gracias and Antonio M. López +Received: 15 September 2016; Accepted: 7 November 2016; Published: 11 November 2016"
0f92e9121e9c0addc35eedbbd25d0a1faf3ab529,MORPH-II: A Proposed Subsetting Scheme,"MORPH-II: A Proposed Subsetting Scheme Participants: K. Kempfert, J. Fabish, K. Park, and R. Towner Mentors: Y. Wang, C. Chen, and T. Kling @@ -11546,6 +40158,20 @@ Jonghyun Choi, Hyunjong Cho, Jungsuk Kwak#, Larry S. Davis UMIACS | University of Maryland, College Park #Stanford University"
+0fd2956ef990443f584112fa093f85a90a43c4af,Performance Evaluation of Multi-camera Visual Tracking,"PEOPLE COUNT ESTIMATION IN SMALL CROWDS +Pietro Morerio, Lucio Marcenaro, Carlo S. Regazzoni +Department of Biophysical and Electronic Engineering +University of Genoa, Genoa, Italy"
+0fcda01765c5a0b4cff99b5ed5139a6e1eddb689,Exploiting Long-Term Connectivity and Visual Motion in CRF-Based Multi-Person Tracking,"Exploiting Long-Term Connectivity and Visual +Motion in CRF-Based Multi-Person Tracking +Alexandre Heili, Student Member, IEEE, Adolfo López-Méndez, and Jean-Marc Odobez, Member, IEEE"
+0fcca61391e7ee7718f5d2c05adc658f2978a2e8,Spectral Face Recognition Using Orthogonal Subspace Bases,
+0f9bd0d528603654de2687d3ae2472a522607ee3,Semantics-aware visual localization under challenging perceptual conditions,"Semantics-aware Visual Localization +under Challenging Perceptual Conditions +Tayyab Naseer +Gabriel L. Oliveira +Thomas Brox +Wolfram Burgard"
0f395a49ff6cbc7e796656040dbf446a40e300aa,The Change of Expression Configuration Affects Identity-Dependent Expression Aftereffect but Not Identity-Independent Expression Aftereffect,"ORIGINAL RESEARCH published: 22 December 2015 doi: 10.3389/fpsyg.2015.01937 @@ -11566,9 +40192,140 @@ closed-mouth smile. In the first of two experiments, the expression aftereffect measured using a cross-identity/cross-expression configuration factorial design. The facial identities of test faces were the same or different from the adaptor, while"
+0fb680b5136d80c13e8d15078ef18ca4aac269f6,Optimizing Deep Neural Network Architecture: A Tabu Search Based Approach,"Optimizing Deep Neural Network Architecture: A Tabu +Search Based Approach +Tarun Kumar Gupta and Khalid Raza* +Department of Computer Science, Jamia Millia Islamia, New Delhi-110025"
+0f2a910f98e9955d2fbd4841d31b4943b91ab382,Creating and Annotating Affect Databases from Face and Body Display: A Contemporary Survey,"Creating and Annotating Affect Databases from Face and Body +Display: A Contemporary Survey +Hatice Gunes and Massimo Piccardi"
+0f29710e54f714eeea5233628afc68c680d881bb,Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning,"Tracking indistinguishable translucent objects over time +using weakly supervised structured learning +Luca Fiaschi1, Ferran Diego1, Konstantin Gregor1, Martin Schiegg1, Ullrich Koethe1, Marta Zlatic2 and +Fred A. Hamprecht1 +HCI University of Heidelberg, Germany, http://hci.iwr.uni-heidelberg.de +HHMI Janelia Farm, USA, http://janelia.org/"
+0ffee18b495830d373dbc65f67a452d94938900b,Registration-based moving object detection from a moving camera,"IROS 2008 2nd Workshop on Planning, Perception and Navigation for Intelligent Vehicles +Registration-based moving object detection +from a moving camera +Angel D. Sappa, Fadi Dornaika, David Ger´onimo and Antonio L´opez"
+0f5275b472344dbfc4a26a9ba73dff23844b7e84,Head movements and postures as pain behavior,"RESEARCH ARTICLE +Head movements and postures as pain +ehavior +Philipp Werner1*, Ayoub Al-Hamadi1, Kerstin Limbrecht-Ecklundt2, Steffen Walter3, +Harald C. Traue3 +Neuro-Information Technology group, Institute for Information Technology and Communications, Otto-von- +Guericke University Magdeburg, Magdeburg, Germany, 2 Department of Anesthesiology, University Medical +Center Hamburg-Eppendorf, Hamburg, Germany, 3 Medical Psychology, University Clinic for Psychosomatic +Medicine and Psychotherapy, Ulm, Germany +1111111111 +1111111111 +1111111111 +1111111111 +1111111111"
+0f41f1a4bd5141184ee3ed3cf8874eeb396d7862,Deep Forest: Towards An Alternative to Deep Neural Networks,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
0fd1bffb171699a968c700f206665b2f8837d953,Weakly Supervised Object Localization with Multi-Fold Multiple Instance Learning,"Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning Ramazan Gokberk Cinbis, Jakob Verbeek, and Cordelia Schmid, Fellow, IEEE"
+0f82a869a80b6114bd16437dbf703bcae84da7b9,Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks,"Neural Activation Constellations: Unsupervised Part Model Discovery with +Convolutional Networks +Marcel Simon and Erik Rodner +Computer Vision Group, University of Jena, Germany∗ +http://www.inf-cv.uni-jena.de/constellation_model_revisited"
+0fa42d4478b514b0f961e26bccbaf2b75d42e912,Extending UML for Conceptual Modeling of Annotation of Medical Images,"Extending UML for Conceptual Modeling of Annotation +International Journal of Computer Applications (0975 – 8887) +Volume 72– No.10, June 2013 +of Medical Images +Mouhamed Gaith Ayadi +Riadh Bouslimi +Jalel Akaichi +Department of computer +sciences +ISG university of Tunis +Tunisia +Department of computer +sciences +ISG university of Tunis +Tunisia +Department of computer +sciences +ISG university of Tunis +Tunisia"
+0f25aa473e808de72c6975fdb1e3e65180a38c05,Bag of Soft Biometrics for Person Identification New trends and challenges,"Noname manuscript No. +(will be inserted by the editor) +Bag of Soft Biometrics for Person Identi(cid:12)cation +New trends and challenges. +Antitza Dantcheva (cid:1) Carmelo Velardo (cid:1) +Angela D’Angelo (cid:1) Jean{Luc Dugelay +Received: 01.08.2010 / Accepted: 11.10.2010"
+0ff14ec76e5fe7f17dce102e781ffce2738c8d4b,Real-time pedestrian detection in urban scenarios,"Real-time Pedestrian Detection in Urban Scenarios +VARGA Robert, VESA Andreea Valeria, JEONG Pangyu, NEDEVSCHI Sergiu +{robert.varga, pangyu.jeong, +Technical University of Cluj Napoca +Telephone: (800) 555–1212"
+0f556558853268d86cd05bf8ea42da6d7862a024,Shade Face: Multiple image-based 3D face recognition,"UWA Research Publication +Mian, A. (2009). Shade Face: Multiple Image-based 3D Face Recognition. In R. Cipolla, +M. Hebert, X. Tang, & N. Yokoya (Eds.), Proceedings of the 2009 IEEE International +Workshop on 3-D Digital Imaging and Modeling (3DIM2009). (pp. 1833-1839). USA: +IEEE Computer Society. 10.1109/ICCVW.2009.5457505 +© 2009 IEEE +This is pre-copy-editing, author-produced version of an article accepted for publication, +following peer review. The definitive published version is located at +http://dx.doi.org/10.1109/ICCVW.2009.5457505 +This version was made available in the UWA Research Repository on 4 March 2015, in +ompliance with the publisher’s policies on archiving in institutional repositories. +Use of the article is subject to copyright law."
+0f2ffd582674bd856247bc5482d85e6db3b49b8f,A neural signature of the creation of social evaluation.,"doi:10.1093/scan/nst051 +SCAN (2014) 9, 731^736 +A neural signature of the creation of social evaluation +Roman Osinsky,1 Patrick Mussel,1 Linda O¨ hrlein,1 and Johannes Hewig1,2 +Department of Psychology I, Julius-Maximilians-University Wu¨rzburg, 97070 Wu¨rzburg, Germany and 2Department of Psychology, +Friedrich-Schiller-University Jena, 07743 Jena, Germany +Previous research has shown that receiving an unfair monetary offer in economic bargaining elicits also-called feedback negativity (FN). This scalp- +recorded brain potential probably reflects a bad-vs-good evaluation in the medial frontal cortex and has been linked to fundamental processes of +reinforcement learning. In the present study, we investigated whether the evaluative mechanism indexed by the FN is also involved in learning who is an +unfair vs fair bargaining partner. An electroencephalogram was recorded while participants completed a computerized version of the Ultimatum Game, +repeatedly receiving fair or unfair monetary offers from alleged other participants. Some of these proposers were either always fair or always unfair in +their offers. In each trial, participants first saw a portrait picture of the respective proposer before the monetary offer was presented. Therefore, the faces +ould be used as predictive cues for the fairness of the pending offers. We found that not only unfair offers themselves induced a FN, but also (over the +task) faces of unfair proposers. Thus, when interaction partners repeatedly behave in an unfair way, their faces acquire a negative valence, which +manifests in a basal neural mechanism of bad-vs-good evaluation. +Keywords: social evaluation; feedback negativity; ultimatum game; evaluative conditioning +INTRODUCTION +trading +example, +family, work,"
+0a811063cfd674275f91006d28cb8620c781e817,Image recognition based on hidden Markov eigen-image models using variational Bayesian method,"IMAGE RECOGNITION BASED ON +HIDDEN MARKOV EIGEN-IMAGE MODELS +USING VARIATIONAL BAYESIAN METHOD +Kei Sawada, Kei Hashimoto, +Yoshihiko Nankaku, Keiichi Tokuda +Nagoya Institute of Technology +APSIPA ASC 10/30/2013"
+0a2aca07c9e15de3d5924e156af9a8e1a67b4cab,Person Reidentification With Reference Descriptor,"Person Reidentification With Reference Descriptor +Le An, Member, IEEE, Mehran Kafai, Member, IEEE, Songfan Yang, Member, IEEE, +nd Bir Bhanu, Fellow, IEEE +cross +identification"
+0a1e3d271fefd506b3a601bd1c812a9842385829,Face Recognition Using 3D Directional Corner Points,"Face Recognition using 3D Directional Corner Points +Author +Yu, Xun, Gao, Yongsheng, Zhou, Jun +Published +Conference Title +Pattern Recognition (ICPR), 2014 22nd International Conference on +https://doi.org/10.1109/ICPR.2014.483 +Copyright Statement +© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be +obtained for all other uses, in any current or future media, including reprinting/republishing this +material for advertising or promotional purposes, creating new collective works, for resale or +redistribution to servers or lists, or reuse of any copyrighted component of this work in other +works. +Downloaded from +http://hdl.handle.net/10072/66408 +Link to published version +http://www.icpr2014.org/index.htm +Griffith Research Online +https://research-repository.griffith.edu.au"
0a6d344112b5af7d1abbd712f83c0d70105211d0,Constrained Local Neural Fields for Robust Facial Landmark Detection in the Wild,"Constrained Local Neural Fields for robust facial landmark detection in the wild Tadas Baltruˇsaitis Peter Robinson @@ -11577,6 +40334,52 @@ USC Institute for Creative Technologies 5 JJ Thomson Avenue Louis-Philippe Morency 2015 Waterfront Drive"
+0a55e4191c90ec1edb8d872237a2dacd5f6eda90,"Intentional Minds: A Philosophical Analysis of Intention Tested through fMRI Experiments Involving People with Schizophrenia, People with Autism, and Healthy Individuals","HUMAN NEUROSCIENCE +Intentional minds: a philosophical analysis of intention tested +through fMRI experiments involving people with +schizophrenia, people with autism, and healthy individuals +Review ARticle +published: 02 February 2011 +doi: 10.3389/fnhum.2011.00007 +Bruno G. Bara1,2*, Angela Ciaramidaro1, Henrik Walter 3 and Mauro Adenzato1,2 +Department of Psychology, Center for Cognitive Science, University of Turin, Turin, Italy +Neuroscience Institute of Turin, University of Turin, Turin, Italy +Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany +Edited by: +Ivan Toni, Radboud University, +Netherlands +Reviewed by: +Ivan Toni, Radboud University, +Netherlands +Roel M. Willems, University of +California Berkeley, USA +*Correspondence:"
+0a391c4d7aafa73324549f212cf28640ed471a81,From Caregivers to Peers: Puberty Shapes Human Face Perception.,"663142 PSSXXX10.1177/0956797616663142Picci, ScherfPuberty Shapes Human Face Perception +research-article2016 +Research Article +From Caregivers to Peers: Puberty +Shapes Human Face Perception +Giorgia Picci and K. Suzanne Scherf +Department of Psychology, Pennsylvania State University +1 –13 +© The Author(s) 2016 +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0956797616663142 +pss.sagepub.com"
+0a66015112da542b9b6687e4b3c9ff73565d0844,A k-NN Approach for Scalable Image Annotation Using General Web Data,"A k-NN Approach for Scalable Image Annotation +Using General Web Data +Mauricio Villegas and Roberto Paredes +Institut Tecnol`ogic d’Inform`atica +Universitat Polit`ecnica de Val`encia +Cam´ı de Vera s/n, 46022 Val`encia, Spain"
+0a058caa89d195930224148d3d2897c0c08fc668,Metric Embedding Autoencoders for Unsupervised Cross-Dataset Transfer Learning,"Metric Embedding Autoencoders for +Unsupervised Cross-Dataset Transfer Learning +Alexey Potapov1,3, Sergey Rodionov1,2, Hugo Latapie4, and Enzo Fenoglio4 +SingularityNET Foundation +Novamente LLC +ITMO University, St. Petersburg, Russia +Chief Technology & Architecture Office, Cisco"
0a3863a0915256082aee613ba6dab6ede962cdcd,Early and Reliable Event Detection Using Proximity Space Representation,"Early and Reliable Event Detection Using Proximity Space Representation Maxime Sangnier LTCI, CNRS, T´el´ecom ParisTech, Universit´e Paris-Saclay, 75013, Paris, France @@ -11584,6 +40387,71 @@ J´erˆome Gauthier LADIS, CEA, LIST, 91191, Gif-sur-Yvette, France Alain Rakotomamonjy Normandie Universit´e, UR, LITIS EA 4108, Avenue de l’universit´e, 76801, Saint-Etienne-du-Rouvray, France"
+0ad4a9fad873e9c4914fd2464404b211f295d7b6,New insights into Laplacian similarity search,"New Insights into Laplacian Similarity Search +Xiao-Ming Wu1, Zhenguo Li2, Shih-Fu Chang1 +Department of Electrical Engineering, Columbia University. 2Huawei Noah’s Ark Lab, Hong Kong. +(a) Λ = I, AP = 0.14 +(b) Λ = D, AP = 0.67 +(c) Λ = H, AP = 0.67 +(a) Λ = I, AP = 0.27 +(b) Λ = D, AP = 0.17 +(c) Λ = H, AP = 0.27 +Figure 1: Top 40 retrieved images on extended YaleB, with false images +highlighted in blue box (query on top left comes from the sparsest cluster). +Figure 2: Top 40 retrieved images on CIFAR-10, with positive images high- +lighted in magenta box (query on top left comes from the densest cluster). +Similarity metrics are important building blocks of many visual applica- +tions such as image retrieval, image segmentation, and manifold learning. +Well-known similarity metrics include personalized PageRank, hitting and +ommute times, and the pseudo-inverse of graph Laplacian. Despite their +popularity, the understanding of their behaviors is far from complete, and +their use in practice is mostly guided by empirical trials and error analy- +sis. This paper bridges this gap by investigating the fundamental design of"
+0a6a173a1d1d36285bae97f98f4b901067d40097,Similarity learning on an explicit polynomial kernel feature map for person re-identification,"Similarity Learning on an Explicit Polynomial Kernel Feature Map for Person +Re-Identification +Dapeng Chen y, Zejian Yuan y, Gang Huaz, Nanning Zhengy, Jingdong Wang x +y Xi’an Jiaotong University +zStevens Institute of Technology +xMicrosoft Research"
+0a60e76e6983e1647469172a50907023913b0c9f,Longitudinal study of amygdala volume and joint attention in 2- to 4-year-old children with autism.,"ORIGINAL ARTICLE +Longitudinal Study of Amygdala Volume and Joint +Attention in 2- to 4-Year-Old Children With Autism +Matthew W. Mosconi, PhD; Heather Cody-Hazlett, PhD; Michele D. Poe, PhD; +Guido Gerig, PhD; Rachel Gimpel-Smith, BA; Joseph Piven, MD +Context: Cerebral cortical volume enlargement has been +reported in 2- to 4-year-olds with autism. Little is known +bout the volume of subregions during this period of de- +velopment. The amygdala is hypothesized to be abnormal +in volume and related to core clinical features in autism. +Objectives: To examine amygdala volume at 2 years with +follow-up at 4 years of age in children with autism and +to explore the relationship between amygdala volume and +selected behavioral features of autism. +Design: Longitudinal magnetic resonance imaging study. +Setting: University medical setting. +Participants: Fifty autistic and 33 control (11 devel- +opmentally delayed, 22 typically developing) children be- +tween 18 and 35 months (2 years) of age followed up at +2 to 59 months (4 years) of age."
+0a81810af97e8ab5b8c483209b4d0ff7210436f9,Human Joint Angle Estimation and Gesture Recognition for Assistive Robotic Vision,"Human Joint Angle Estimation and Gesture Recognition +for Assistive Robotic Vision +Alp Guler1, Nikolaos Kardaris2, Siddhartha Chandra1, Vassilis Pitsikalis2, Christian +Werner3, Klaus Hauer3, Costas Tzafestas2, Petros Maragos2, Iasonas Kokkinos1 +(1) INRIA GALEN & Centrale Sup´elec Paris, +(2) National Technical University of Athens, (3) University of Heidelberg"
+0adffd02029363c204a561092e1e0cc05cacfee7,A New Method for Static Video Summarization Using Local Descriptors and Video Temporal Segmentation,"A New Method for Static Video Summarization +Using Local Descriptors and Video Temporal +Segmentation +Edward J. Y. Cayllahua Cahuina +Computer Research Center +San Pablo Catholic University +Arequipa, Peru +Email: +Guillermo Camara Chavez +Department of Computer Science +Federal university of Ouro Preto +Ouro Preto, Brazil +Email:"
0a60d9d62620e4f9bb3596ab7bb37afef0a90a4f,Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates,"Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates. GCPR 2016 (cid:13) Copyright by Springer. The final publication will be available at link.springer.com A. Freytag, E. Rodner, M. Simon, A. Loos, H. K¨uhl and J. Denzler @@ -11597,6 +40465,15 @@ Michael Stifel Center Jena, Germany Fraunhofer Institute for Digital Media Technology, Germany Max Planck Institute for Evolutionary Anthropology, Germany 5German Centre for Integrative Biodiversity Research (iDiv), Germany"
+0a773ed20a5920897788dd6f0d63c20defca8ab0,ConceptLearner: Discovering visual concepts from weakly labeled image collections,"ConceptLearner: Discovering Visual Concepts from Weakly Labeled Image +Collections +Bolei Zhou†, Vignesh Jagadeesh‡, Robinson Piramuthu‡ +MIT ‡eBay Research Labs"
+0ad0a1293f80c838c843726eeddf5a97f33f0c89,Understanding image virality,"Understanding Image Virality +Arturo Deza +UC Santa Barbara +Devi Parikh +Virginia Tech"
0aa9872daf2876db8d8e5d6197c1ce0f8efee4b7,Timing is everything : a spatio-temporal approach to the analysis of facial actions,"Imperial College of Science, Technology and Medicine Department of Computing Timing is everything @@ -11605,16 +40482,66 @@ ctions Michel Fran¸cois Valstar Submitted in part fulfilment of the requirements for the degree of Doctor of Philosophy in Computing of Imperial College, February 2008"
+0adb5923fb1955f7ca0a85454afe17e5d25425df,Crowd motion monitoring using tracklet-based commotion measure,"CROWD MOTION MONITORING USING TRACKLET-BASED COMMOTION MEASURE +Hossein Mousavi* +Moin Nabi* Hamed Kiani +Alessandro Perina +Vittorio Murino +Pattern Analysis and Computer Vision Department (PAVIS) +Istituto Italiano di Tecnologia +Genova, Italy"
0a87d781fe2ae2e700237ddd00314dbc10b1429c,Multi-scale HOG Prescreening Algorithm for Detection of Buried Explosive Hazards in FL-IR and FL-GPR Data,"Distribution Statement A: Approved for public release; distribution unlimited. Multi-scale HOG Prescreening Algorithm for Detection of Buried Explosive Hazards in FL-IR and FL-GPR Data *University of Missouri, Electrical and Computer Engineering Department, Columbia, MO K. Stone*, J. M. Keller*, D. Shaw*"
+0ae07f24251946b2086fb992031c298ada2805de,Exemplar-AMMs: Recognizing Crowd Movements From Pedestrian Trajectories,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014 +Exemplar-AMMs: Recognizing Crowd Movements +from Pedestrian Trajectories +Wenxi Liu, Rynson W.H. Lau, Xiaogang Wang, Dinesh Manocha"
+0af65df112db18248ed24a1c0fb5fe8524015336,Contour Segment Analysis for Human Silhouette Pre-segmentation,"Author manuscript, published in ""5th International Conference on Computer Vision Theory and Applications (VISAPP 2010), +Angers : France (2010)"""
+0ae3182836b1b962902d664ddd524e8554b742cf,Integrating Context and Occlusion for Car Detection by Hierarchical And-Or Model,"Integrating Context and Occlusion for Car +Detection by Hierarchical And-Or Model +Bo Li1,2, Tianfu Wu2,(cid:2), and Song-Chun Zhu2 +Beijing Lab of Intelligent Information Technology, Beijing Institute of Technology +Department of Statistics, University of California, Los Angeles"
+0a7a7b3f05918fb4fc33f04cb7e31232fa197f76,Fitting a Morphable Model to 3D Scans of Faces,"Fitting a Morphable Model to 3D Scans of Faces +Volker Blanz +Universit¤at Siegen, +Siegen, Germany +Kristina Scherbaum +MPI Informatik, +Saarbr¤ucken, Germany +Hans-Peter Seidel +MPI Informatik, +Saarbr¤ucken, Germany"
+0a3051c8dde80975640d42dca21fac17ed60f987,A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring,
+0a8ab703839ae585c2f27099616c40974cbeeda2,"Fast, Exact and Multi-scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs","Fast, Exact and Multi-Scale Inference for Semantic +Image Segmentation with Deep Gaussian CRFs +Siddhartha Chandra +Iasonas Kokkinos +INRIA GALEN & Centrale Sup´elec, Paris, France"
+0a2d2b79ba39e2140c93543b8ce873f106c08e3d,Semi-Supervised Sparse Representation Based Classification for Face Recognition With Insufficient Labeled Samples,"Semi-Supervised Sparse Representation Based +Classification for Face Recognition with Insufficient +Labeled Samples +Yuan Gao, Jiayi Ma, and Alan L. Yuille Fellow, IEEE"
0af48a45e723f99b712a8ce97d7826002fe4d5a5,Toward Wide-Angle Microvision Sensors,"Toward Wide-Angle Microvision Sensors Sanjeev J. Koppal, Member, IEEE, Ioannis Gkioulekas, Student Member, IEEE, Travis Young, Member, IEEE, Hyunsung Park, Student Member, IEEE, Kenneth B. Crozier, Member, IEEE, Geoffrey L. Barrows, Member, IEEE, and Todd Zickler, Member, IEEE"
+0a4ba4d5bd6e07a31fa4586322fd5e07d9f9975e,Online Bayesian Nonparametrics for Group Detection,"ZANOTTO, BAZZANI, CRISTANI, MURINO: ONLINE BNP FOR GROUP DETECTION +Online Bayesian Nonparametrics for Group +Detection +Matteo Zanotto +Loris Bazzani +Marco Cristani +Vittorio Murino +Pattern Analysis & Computer Vision +Istituto Italiano di Tecnologia +Via Morego 30 - 16163 +Genova, Italy"
0aa8a0203e5f406feb1815f9b3dd49907f5fd05b,Mixture Subclass Discriminant Analysis,"Mixture subclass discriminant analysis Nikolaos Gkalelis, Vasileios Mezaris, Ioannis Kompatsiaris"
0a7309147d777c2f20f780a696efe743520aa2db,Stories for Images-in-Sequence by using Visual and Narrative Components,"Stories for Images-in-Sequence by using Visual @@ -11623,11 +40550,25 @@ Marko Smilevski1,2, Ilija Lalkovski2, and Gjorgji Madjarov1,3 Ss. Cyril and Methodius University, Skopje, Macedonia Pendulibrium, Skopje, Macedonia Elevate Global, Skopje, Macedonia"
+0a40415bdfe4bc9ef7e019e4f1442a9fb61f58b2,Automatic Discovery and Geotagging of Objects from Street View Imagery,"Automatic Discovery and Geotagging of Objects from Street View Imagery +Vladimir A. Krylov +Eamonn Kenny +Rozenn Dahyot +ADAPT Centre, School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland"
+0ad90ad5d2050ebaba5b5cddeb474c7d889bec3e,A Unified Semantic Embedding: Relating Taxonomies and Attributes,"A Unified Semantic Embedding: +Relating Taxonomies and Attributes +Sung Ju Hwang∗ +Disney Research +Pittsburgh, PA"
+0a8c6b40d6ca75bc1995083825e362137b130624,Nonparametric Method for Data-driven Image Captioning,"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 592–598, +Baltimore, Maryland, USA, June 23-25 2014. c(cid:13)2014 Association for Computational Linguistics"
0a1138276c52c734b67b30de0bf3f76b0351f097,Discriminant Incoherent Component Analysis,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/TIP.2016.2539502 Discriminant Incoherent Component Analysis Christos Georgakis, Student Member, IEEE, Yannis Panagakis, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+0a572c16e635312f118d1a53f0ff6446402d3c32,Learning with proxy supervision for end-to-end visual learning,"Learning with Proxy Supervision for End-To-End Visual Learning +Jiˇr´ı ˇCerm´ak1∗ Anelia Angelova2"
0a6a25ee84fc0bf7284f41eaa6fefaa58b5b329a,Neural Networks Regularization Through Representation Learning,"THÈSEPour obtenir le diplôme de doctorat Spécialité Informatique Préparée au sein de « l'INSA Rouen Normandie » Présentée et soutenue parSoufiane BELHARBIThèse dirigée par Sébastien ADAM, laboratoire LITIS Neural Networks Regularization Through Representation LearningThèse soutenue publiquement le 06 Juillet 2018 devant le jury composé deSébastien ADAMProfesseur à l'Université de Rouen NormandieDirecteur de thèseClément CHATELAINMaître de conférence à l'INSA Rouen NormandieEncadrant de thèseRomain HÉRAULTMaître de conférence à l'INSA Rouen NormandieEncadrant de thèseElisa FROMONTProfesseur à l'Université de Rennes 1Rapporteur de thèseThierry ARTIÈRESProfesseur à l'École Centrale MarseilleRapporteur de thèseJohn LEEProfesseur à l'Université Catholique de LouvainExaminateur de thèseDavid PICARDMaître de conférences à l'École Nationale Supérieure de l'Électronique et de ses ApplicationsExaminateur de thèseFrédéric JURIEProfesseur à l' Université de Caen NormandieInvité"
0ae9cc6a06cfd03d95eee4eca9ed77b818b59cb7,"Multi-task, multi-label and multi-domain learning with residual convolutional networks for emotion recognition","Noname manuscript No. (will be inserted by the editor) @@ -11655,6 +40596,42 @@ This writeup describes the solver in detail. Approach: Our approach is closely based on data-subsampling algorithms for collecting hard exam- ples [9, 10, 6], combined with the dual coordinate quadratic programming (QP) solver described in liblinear [8]. The latter appears to be current fastest method for learning linear SVMs. We make two extensions (1)"
+0aaa66501298c3df27293eca7906e93d8013b729,Fast HOG based person detection devoted to a mobile robot with a spherical camera,"Fast HOG based Person Detection devoted to a Mobile Robot with a +Spherical Camera +A. A. Mekonnen1, C. Briand1, F. Lerasle1, A. Herbulot1"
+0a20e2fbe52efdb794b7566ce5233c41f4c5efc9,Monocular visual scene understanding from mobile platforms,"Monocular Visual Scene +Understanding +from Mobile Platforms +A dissertation for the degree of +Doktor-Ingenieur (Dr.-Ing.) +pproved by +TECHNISCHE UNIVERSITÄT DARMSTADT +Fachbereich Informatik +presented by +CHRISTIAN ALEXANDER WOJEK +Dipl.-Inform. +orn in Schillingsfürst, Germany +Examiner: +Prof. Dr. Bernt Schiele +Co-examiner: Prof. Dr. Luc Van Gool +Date of Submission: 14th of May, 2010 +0th of June, 2010 +Date of Defense: +Darmstadt, 2010"
+64a6c30ca95e85427c56acb4c1c20f62c6ec0709,PersonNet: Person Re-identification with Deep Convolutional Neural Networks,"PersonNet: Person Re-identification with Deep +Convolutional Neural Networks +Lin Wu, Chunhua Shen, Anton van den Hengel"
+64c9cc92ea496b9053fa5326567487b5f08bb13f,3D Human Face Recognition Using Summation Invariants,"(cid:176)2006 IEEE. Personal use of this material is permitted. +However, permission to reprint/republish this material for ad- +vertising or promotional purposes or for creating new collec- +tive works for resale or redistribution to servers or lists, or to +reuse any copyrighted component of this work in other works +must be obtained from the IEEE."
+647c6ac5e0bfee0241d583650f18c6314f28aaee,Segmentation Driven Object Detection with Fisher Vectors,"Segmentation Driven Object Detection with Fisher Vectors +Ramazan Gokberk Cinbis +Jakob Verbeek Cordelia Schmid +LEAR, INRIA Grenoble - Rhˆone-Alpes, France +Laboratoire Jean Kuntzmann"
6412d8bbcc01f595a2982d6141e4b93e7e982d0f,"Deep Convolutional Neural Network Using Triplets of Faces, Deep Ensemble, and Score-Level Fusion for Face Recognition","Deep Convolutional Neural Network using Triplets of Faces, Deep Ensemble, and Score-level Fusion for Face Recognition Bong-Nam Kang, Student Member, IEEE1, Yonghyun Kim, Student Member, IEEE2, and @@ -11682,15 +40659,145 @@ L’archive ouverte pluridisciplinaire HAL, est destin´ee au d´epˆot et `a la diffusion de documents scientifiques de niveau recherche, publi´es ou non, ´emanant des ´etablissements d’enseignement et de"
+64fb6c31033e38eaaa10c0f7c2b7995f8fa84de3,Visualizing Video Sounds through Sound Word Animation,"VISUALIZING VIDEO SOUNDS THROUGH +SOUND WORD ANIMATION +擬音語アニメーションによる動画音響の可視化手法 +Fangzhou Wang +A Master Thesis +Submitted to +the Graduate School of the University of Tokyo +on February 20, 2014 +in Partial Ful(cid:12)llment of the Requirements +for the Degree of Master of Information Science and +Technology +in Computer Science +Thesis Supervisor: Takeo Igarashi 五十嵐健夫 +Professor of Computer Science"
+6483ebbb9c28024431c8ada03354217453ca1b3b,Statement in Lieu of an Oath,"Universit¨at des Saarlandes +Max-Planck-Institut f¨ur Informatik +Learning to Track Humans in Videos +Master’s Thesis in Computer Science +Mihai Fieraru +supervised by +Prof. Dr. Bernt Schiele +dvised by +MSc Anna Khoreva +MSc Eldar Insafutdinov +reviewers +Prof. Dr. Bernt Schiele +Dr. Mario Fritz +Saarbr¨ucken, December 2017"
+64be271fd50fce1cf8434020145a1b6e16f75c1a,Intrinsic Divergence for Face Recognition,"Centre for Theoretical Neuroscience +Technical Report +UW-CTN-TR-20090204-001 +February 4, 2009 +Intrinsic Divergence for Face +Recognition +Yichuan Tang and Xuan Choo +Centre for Theoretical Neuroscience, Waterloo, ON. http://compneuro.uwaterloo.ca/cnrglab"
+646fa86edc22ccc452a44ac7a5953ba62fc0929b,Recognizing jumbled images: The role of local and global information in image classification,"The Role of Local and Global Information in Image Classification +Recognizing Jumbled Images: +Toyota Technological Institute, Chicago (TTIC) +Devi Parikh"
+6475c1e95da0a3bd36786a32d00a893d85460e9e,Combined image- and world-space tracking in traffic scenes,"Combined Image- and World-Space Tracking in Traffic Scenes +Aljoˇsa Oˇsep, Wolfgang Mehner, Markus Mathias, and Bastian Leibe"
+643abe6001946ebb7e262465edcf78d600c38f4f,The COST292 experimental framework for TRECVID 2007,"The COST292 experimental framework for TRECVID 2007 +Q. Zhang1, K. Chandramouli1, U. Damnjanovic1, T. Piatrik1, E. Izquierdo1, +M. Corvaglia2, N. Adami2, R. Leonardi2, G. Yakın3, S. Aksoy3, U. Naci4, +A. Hanjalic4, S. Vrochidis5, A. Moumtzidou5, S. Nikolopoulos5, V. Mezaris5, +L. Makris5, I. Kompatsiaris5, E. Esen6, A. Alatan6, E. Spyrou7, +P. Kapsalas7, G. Tolias7, P. Mylonas7, Y. Avrithis7, B. Reljin8, G. Zajic8, +R. Jarina9, M. Kuba9, N. Aginamo10, J. Goya10, B. Mansencal11, +J. Benois-Pineau11, A. M. G. Pinheiro12, L. A. Alexandre12, P. Almeida12 +October 22, 2007"
64153df77fe137b7c6f820a58f0bdb4b3b1a879b,Shape Invariant Recognition of Segmented Human Faces using Eigenfaces,"Shape Invariant Recognition of Segmented Human Faces using Eigenfaces Zahid Riaz, Michael Beetz, Bernd Radig Department of Informatics Technical University of Munich, Germany"
+64c78c8bf779a27e819fd9d5dba91247ab5a902b,Tracking with multi-level features,"Tracking with multi-level features +Roberto Henschel, Laura Leal-Taix´e, Bodo Rosenhahn, Konrad Schindler"
+64e0bd1210f180e0610b2a1faa188051a1de29bf,Combining Detectors for Robust Head Detection,"Combining Detectors for Robust Head Detection +Henrik Brauer, Christos Grecos and Kai von Luck +Living Place - HAW Hamburg +Berliner Tor 11 +0099 Hamburg, Germany"
649eb674fc963ce25e4e8ce53ac7ee20500fb0e3,Toward correlating and solving abstract tasks using convolutional neural networks,
+64f6f1cd23bbac1983ad4115475e4ef26ab86ba4,Person re-identification by unsupervised video matching,"Person Re-Identification by Unsupervised Video Matching +Xiaolong Ma1,4, Xiatian Zhu2, Shaogang Gong2, Xudong Xie1, Jianming Hu1, Kin-Man Lam3, Yisheng Zhong1"
+6434b95401aea9ece22b2b29950118afc163c2db,Localized anomaly detection via hierarchical integrated activity discovery,"THIS PAPER APPEARED IN IEEE INT. CONF. ON ADVANCED VIDEO AND SIGNAL-BASED PROCESSING (AVSS), KRAKOW, 2013 +Localized Anomaly Detection via Hierarchical Integrated Activity Discovery +Thiyagarajan Chockalingam1 +R´emi Emonet2 +http://home.heeere.com +Jean-Marc Odobez2,3 +: Colorado State University – Fort Collins, CO 80523, United States +: Idiap Research Institute – CH-1920, Martigny, Switzerland +: ´Ecole Polytechnique F´ed´eral de Lausanne – CH-1015, Lausanne, Switzerland"
+6497eb53fd7d3ff09190566be8099016fb49f801,Biometric Sensor Interoperability: A Case Study in 3D Face Recognition,
+64cac22210861d4e9afb00b781da90cf99f9d19c,Facial Landmark Detection for Manga Images,"Noname manuscript No. +(will be inserted by the editor) +Facial Landmark Detection for Manga Images +Marco Stricker · Olivier Augereau · +Koichi Kise · Motoi Iwata +Received: date / Accepted: date"
+64d1fcc26c2af47c8ed7436fe91546ba5bfc7a1f,Disentangling Multiple Conditional Inputs in GANs,"Disentangling Multiple Conditional Inputs in GANs +Gökhan Yildirim +Urs Bergmann +Zalando Research +Zalando Research +Berlin, Germany +Berlin, Germany +Calvin Seward∗ +Zalando Research +Berlin, Germany +process. Researchers have achieved control of image generation by +using GANs that are conditioned on a categorical input [12, 13]. +In this paper, we employ conditional GANs to control the visual +ttributes, such as color, texture, and shape, of a generated apparel. +One of the main challenges of the conditional image generation +GANs is to isolate the effects of input attributes on the final image. +For example, we want the color of an article to stay constant, when +we tune its texture and/or shape. One possibility would be to employ +Adversarial Autoencoders [11] or DNA-GAN [17] to disentangle +the inputs. However, this requires an exhaustive dataset, in other"
+641fd2edcf93fa29181952356e93a83a26012aa2,Following are some examples from CIFAR dataset : Goal : To alter the training criteria to obtain ‘ objectness ’ in the synthesis of images,"Published as a conference paper at ICLR 2017 +IMPROVING GENERATIVE ADVERSARIAL NETWORKS +WITH DENOISING FEATURE MATCHING +David Warde-Farley & Yoshua Bengio(cid:63) +Montreal Institute for Learning Algorithms, (cid:63) CIFAR Senior Fellow +Universit´e de Montr´eal +Montreal, Quebec, Canada"
+6472df86bed51909f7b8aa0631f910db5a627c84,Minimax and Adaptive Estimation of Covariance Operator for Random Variables Observed on a Lattice Graph,"Minimax and Adaptive Estimation of Covariance Operator for +Random Variables Observed on a Lattice Graph +T. Tony Cai∗ and Ming Yuan† +University of Pennsylvania and Georgia Institute of Technology +November 3, 2012"
+6403117f9c005ae81f1e8e6d1302f4a045e3d99d,"A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.","A Systematic Evaluation and Benchmark for +Person Re-Identification: Features, Metrics, and +Datasets +Srikrishna Karanam∗, Student Member, IEEE, Mengran Gou∗, Student Member, IEEE, +Ziyan Wu, Member, IEEE, Angels Rates-Borras, Octavia Camps, Member, IEEE, +nd Richard J. Radke, Senior Member, IEEE"
+641f9c87356c0829e690272b010848242058b8bc,Object Co-detection via Efficient Inference in a Fully-Connected CRF,"Object Co-detection via Efficient Inference +in a Fully-Connected CRF(cid:2) +Zeeshan Hayder, Mathieu Salzmann, and Xuming He +Australian National University (ANU) +NICTA, Canberra, Australia"
+6446089a2a383ad9e4315aea0199084dc61490f9,Computational analysis of human-robot interactions through first-person vision: Personality and interaction experience,"Proceedings of the 24th IEEE International +Symposium on Robot and Human Interactive Communication +Kobe, Japan, Aug 31 - Sept 4, 2015 +978-1-4673-6704-2/15/$31.00 ©2015 IEEE"
645de797f936cb19c1b8dba3b862543645510544,Deep Temporal Linear Encoding Networks,"Deep Temporal Linear Encoding Networks Ali Diba1,(cid:63), Vivek Sharma1,(cid:63), and Luc Van Gool1,2 ESAT-PSI, KU Leuven, 2CVL, ETH Z¨urich"
+64bd5878170bfab423bc3fc38d693202ef4ba6b6,Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision,"Monocular 3D Human Pose Estimation In The Wild +Using Improved CNN Supervision +Dushyant Mehta1, Helge Rhodin2, Dan Casas3, Pascal Fua2, +Oleksandr Sotnychenko1, Weipeng Xu1, and Christian Theobalt1 +MPI for Informatics, Germany +EPFL, Switzerland +Universidad Rey Juan Carlos, Spain"
90d735cffd84e8f2ae4d0c9493590f3a7d99daf1,Recognition of Faces using Efficient Multiscale Local Binary Pattern and Kernel Discriminant Analysis in Varying Environment,"Original Research Paper American Journal of Engineering and Applied Sciences Recognition of Faces using Efficient Multiscale Local Binary @@ -11710,6 +40817,93 @@ Department of Electronics Engg, Priyadarshini College of Engg, Nagpur, India Email:"
+904c53ea063d7d1e13b99d55257801d69d073775,Combined Object Detection and Segmentation,"International Journal of Machine Learning and Computing, Vol. 3, No. 1, February 2013 +Combined Object Detection and Segmentation +Jarich Vansteenberge, Masayuki Mukunoki, and Michihiko Minoh"
+9070045c1a9564a5f25b42f3facc7edf4c302483,Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker,"Everybody needs somebody: Modeling social and grouping behavior on a linear +programming multiple people tracker +Laura Leal-Taix´e, Gerard Pons-Moll and Bodo Rosenhahn +Institute for Information Processing (TNT) +Leibniz University Hannover, Germany"
+90d8bf2199e7fd972dab3bd3dc6fb67536fa509b,Performance and Energy Modeling of Heterogeneous Many-core Architectures,"PERFORMANCE AND ENERGY MODELING OF HETEROGENEOUS MANY-CORE ARCHITECTURES +Performance and Energy Modeling of +Heterogeneous Many-core Architectures +Rui Pedro Gaspar Pinheiro"
+904a8241ef400bd85b1ad10267a1177bbde1c048,Image-Text Dataset Generation for Image Annotation and Retrieval,"II Congreso Español de Recuperación de la Información +CERI 2012 +Image-Text Dataset Generation for Image +Annotation and Retrieval⋆ +Mauricio Villegas and Roberto Paredes +Institut Tecnol`ogic d’Inform`atica +Universitat Polit`ecnica de Val`encia +Cam´ı de Vera s/n, 46022 Val`encia (Spain)"
+902d1b14b076120cb21029b51ed8e63529fe686d,Performance Analysis for Facial Expression Recognition under Salt and Pepper Noise with Median Filter Approach,"PERFORMANCE ANALYSIS FOR FACIAL EXPRESSION +RECOGNITION UNDER SALT AND PEPPER NOISE WITH +MEDIAN FILTER APPROACH +AZRINI BINTI IDRIS +A project report submitted in partial +fulfillment of the requirement for the award of the +Degree of Master of Electrical Engineering +Facultyof Electrical and Electronic Engineering +UniversitiTun Hussein Onn Malaysia +JULY 2013"
+90915cc93248174c4729be65159fb946d2ad5f72,"Relative Dense Tracklets for Human Action Recognition Piotr Bilinski Etienne Corvee Slawomir Bak Francois Bremond INRIA Sophia Antipolis , STARS team 2004 Route des Lucioles , BP 93 , 06902 Sophia Antipolis , France","Relative Dense Tracklets for Human Action Recognition +Piotr Bilinski +Etienne Corvee +Slawomir Bak +Francois Bremond +INRIA Sophia Antipolis, STARS team +004 Route des Lucioles, BP93, 06902 Sophia Antipolis, France"
+907fbe706ec14101978a63c6252e0d75e657e8dd,The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution,"The Unreasonable Effectiveness of Texture Transfer +for Single Image Super-resolution +Muhammad Waleed Gondal +Max Planck Institute for Intelligent Systems. +Bernhard Schölkopf +Max Planck Institute for Intelligent Systems. +Michael Hirsch +Amazon Research."
+9095f633a153c0e3a5503c0373c9c1dfeeefb0cc,Fast 3D face reconstruction based on uncalibrated photometric stereo,"Multimed Tools Appl +DOI 10.1007/s11042-013-1791-3 +Fast 3D face reconstruction based on uncalibrated +photometric stereo +Yujuan Sun & Junyu Dong & Muwei Jian & Lin Qi +# Springer Science+Business Media New York 2013"
+90eb9f6a1b7e3dae24e438b201e6b1f671a87eb5,Single-Camera Automatic Landmarking for People Recognition with an Ensemble of Regression Trees,"Single-Camera Automatic Landmarking for People Recognition +with an Ensemble of Regression Trees +Karla Trejo, Cecilio Angulo +Universitat Polit`ecnica de Catalunya, Barcelona, +Spain +(AAM) +Active Appearance Model"
+90dd771829094dad1230e32b8bc4385bfe86c4e5,A Comparison of Word Embeddings for the Biomedical Natural Language Processing,[cs.IR] 18 Jul 2018
+90e994a802a0038f24c8e3735d7619ebb40e6e93,Semantic Foggy Scene Understanding with Synthetic Data,"Noname manuscript No. +(will be inserted by the editor) +Semantic Foggy Scene Understanding with Synthetic Data +Christos Sakaridis · Dengxin Dai · Luc Van Gool +Received: date / Accepted: date"
+90ce227ec08053ea6acf9f9f9f53d8b7169574f2,An Introduction to Evaluating Biometric Systems,"C O V E R F E A T U R E +An Introduction to +Evaluating +Biometric +Systems +O n the basis of media hype alone, you might +onclude that biometric passwords will soon +replace their alphanumeric counterparts +with versions that cannot be stolen, forgot- +ten, lost, or given to another person. But +what if the performance estimates of these systems are +far more impressive than their actual performance? +P. Jonathon +Phillips +Alvin Martin +C.L. Wilson +Przybocki +National +Institute of +Standards and"
+90e56a8515c8c2ff16f5c79c69811e283be852c7,Boosting face recognition via neural Super-Resolution,"Boosting face recognition via neural Super-Resolution +Guillaume Berger, Cl´ement Peyrard and Moez Baccouche +Orange Labs - 4 rue du Clos Courtel, 35510 Cesson-S´evign´e - France"
90fb58eeb32f15f795030c112f5a9b1655ba3624,Face and Iris Recognition in a Video Sequence Using Dbpnn and Adaptive Hamming Distance,"INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND ROBOTICS www.ijrcar.com Vol.4 Issue 6, Pg.: 12-27 @@ -11725,6 +40919,23 @@ S. Revathy, 2Mr. L. Ramasethu PG Scholar, Hindusthan College of Engineering and Technology, Coimbatore, India. Assistant Professor, Hindusthan College of Engineering and Technology, Coimbatore, India. Email id:"
+9043df1de4f6e181875011c1379d1a7f68a28d6c,People Detection from Overhead Cameras,"People Detection from Overhead +Cameras +A study of impact of occlusion on +performance +Lu Liu +in partial fulfillment of the requirements for the degree of +Master of Science +t the Delft University of Technology, +to be defended publicly on Friday August 31, 2018 at 01:00 PM. +Student number: +Thesis committee: Dr. Hayley Hung (supervisor) +621832 +EEMCS +Laura Cabrera-Quiros (mentor) EEMCS +EEMCS +Prof. Marcel Reinders, +Dr. Julian Kooij,"
902114feaf33deac209225c210bbdecbd9ef33b1,Side-Information based Linear Discriminant Analysis for Face Recognition,"KAN et al.: SIDE-INFORMATION BASED LDA FOR FACE RECOGNITION Side-Information based Linear Discriminant Analysis for Face @@ -11743,6 +40954,51 @@ China School of Computer Engineering, Nanyang Technological University, Singapore"
+90a70b38c5a1b40ac16e18628a7772923cdc5cb5,Exact Subspace Segmentation and Outlier Detection by Low-Rank Representation,"Exact Subspace Segmentation and Outlier Detection by +Low-Rank Representation +Anonymous Author 1 +Unknown Institution 1 +Anonymous Author 2 +Unknown Institution 2 +Anonymous Author 3 +Unknown Institution 3"
+900175d24928921600d09985211b6b9bfea44ce0,Person re-identification by pose priors,"Person re-identification by pose priors +Sławomir Bąk +Filipe Martins +Francois Brémond +INRIA Sophia Antipolis, STARS team, 2004, route des Lucioles, BP93 +06902 Sophia Antipolis Cedex - France"
+909f91c1957ce2bf9d76ee2109a865e87bf17057,GMCP-Tracker: Global Multi-object Tracking Using Generalized Minimum Clique Graphs,"GMCP-Tracker: Global Multi-object Tracking +Using Generalized Minimum Clique Graphs +Amir Roshan Zamir, Afshin Dehghan, and Mubarak Shah +UCF Computer Vision Lab, Orlando, FL 32816, USA"
+903210406f14a12b481524d543b14f16114797e2,Pretest of images for the beauty dimension,"Análise Psicológica (2015), 4 (XXXIII): 453-466 +doi: 10.14417/ap.1052 +Pretest of images for the beauty dimension +Joana Mello* / Filipe Loureiro* +* ISPA – Instituto Universitário +In this work, we present norms concerning the perceived association of two sets of image stimuli with +the concept of “beauty”: 40 objects (Study 1) and 40 photos of human faces (Study 2)1. Participants +were presented with a set of words associated with the construct of “beauty” and were subsequently +sked to judge each image on how much they considered them to be related with this construct on a +7-point scale (1 – Not at all related; 7 – Very related). The interpretation of means’ confidence intervals +distinguish between 40 images, evaluated as “ugly” – with low scores on the beauty dimension – (20 +objects and 20 faces), and 28 images evaluated as “beautiful” – with high scores on the beauty +dimension – (12 objects and 16 faces). Results are summarized and photos made available to support +future research requiring beauty and/or ugly stimulus. +Key words: Norms, Beauty, Ugly, People, Objects. +Introduction +The objective of this work consists on the presentation of beauty norms of a set of images from +two categories (people and objects) for further use in different contexts and experimental settings. +Our main purpose was to present norms of a set of updated to present-days photos of faces and +objects regarding its level of activation of the “beauty” construct, i.e., of the perceived association"
+9015fd773526e21e352037663de3f586ccf4e907,Fused Deep Neural Networks for Efficient Pedestrian Detection,"Fused Deep Neural Networks for Efficient +Pedestrian Detection +Xianzhi Du, Mostafa El-Khamy, Vlad I. Morariu, Jungwon Lee, and Larry Davis"
+90f0646c0801f1dad43d2374d1145be8e005bdbf,Raised Middle-Finger: Electrocortical Correlates of Social Conditioning with Nonverbal Affective Gestures,"Raised Middle-Finger: Electrocortical Correlates of Social +Conditioning with Nonverbal Affective Gestures +Matthias J. Wieser1*, Tobias Flaisch2, Paul Pauli1 +Department of Psychology, University of Wu¨ rzburg, Wu¨ rzburg, Germany, 2 Department of Psychology, University of Konstanz, Konstanz, Germany"
90cb074a19c5e7d92a1c0d328a1ade1295f4f311,Fully Automatic Upper Facial Action Recognition,"MIT. Media Laboratory Affective Computing Technical Report #571 Appears in IEEE International Workshop on Analysis and Modeling of Faces and Gestures , Oct 2003 Fully Automatic Upper Facial Action Recognition @@ -11754,6 +41010,13 @@ Bouchra Abboud, Franck Davoine, Mˆo Dang Heudiasyc Laboratory, CNRS, University of Technology of Compi`egne. BP 20529, 60205 COMPIEGNE Cedex, FRANCE. E-mail:"
+90d8dbaa799430d7384425061317e0fa55bf5cbb,Representation Models and Machine Learning Techniques for Scene Classificatio,"Representation Models and +Machine Learning Techniques +for Scene Classificatio +Giovanni Maria Farinella and Sebastiano Battiato +Image Processing Lab, Dipartimento di Matematica e Informatica, +Universit`a degli Studi di Catania, Viale A. Doria 6, 95125 Catania, Italy; +E-mail: {gfarinella,"
9028fbbd1727215010a5e09bc5758492211dec19,Solving the Uncalibrated Photometric Stereo Problem Using Total Variation,"Solving the Uncalibrated Photometric Stereo Problem using Total Variation Yvain Qu´eau1, Fran¸cois Lauze2, and Jean-Denis Durou1 @@ -11770,6 +41033,22 @@ CHINA Taizhou University Taizhou 318000 CHINA"
+bf4ec5068e6ff0b008a09f0c94bfaac290ae7d3b,Co-attention CNNs for Unsupervised Object Co-segmentation,Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18)
+bf4fcd80083f3145176b64d15bab78456a7e5e43,Title Fast Randomized Algorithms for Convex Optimization and Statistical Estimation Permalink,"Fast Randomized Algorithms for Convex Optimization and +Statistical Estimation +Mert Pilanci +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2016-147 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-147.html +August 14, 2016"
+bfd8bfce7c998a7bf209b7bf2e6c2e1f03c4334e,Discriminative Face Alignment,"Discriminative Face Alignment +Xiaoming Liu, Member, IEEE"
+bf4f76c3da8a46783dfd2b72651e2300901ced25,Robust aggregation of GWAP tracks for local image annotation,"Robust aggregation of GWAP tracks +for local image annotation +C. Bernaschina, P. Fraternali, L. Galli, D. Martinenghi, M. Tagliasacchi +Dipartimento di Elettronica, Informazione e Bioingegneria +Politecnico di Milano, Italy"
bf1e0279a13903e1d43f8562aaf41444afca4fdc,Different Viewpoints of Recognizing Fleeting Facial Expressions with DWT,"International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 04 Issue: 10 | Oct -2017 www.irjet.net p-ISSN: 2395-0072 Different Viewpoints of Recognizing Fleeting Facial Expressions with @@ -11779,6 +41058,45 @@ to get desired information Introduction ---------------------------------------------------------------------***---------------------------------------------------------------------"
+bf96a0f037e7472e4b6cb1dae192a5fedbbbd88a,Visual Listening In: Extracting Brand Image Portrayed on Social Media,"Visual Listening In: Extracting Brand Image +Portrayed on Social Media +Liu Liu +NYU Stern School of Business, +Daria Dzyabura +NYU Stern School of Business, +University of Washington - Foster School of Business, +Natalie Mizik +Marketing academics and practitioners recognize the importance of monitoring consumer online conversations +bout brands. The focus so far has been on user generated content in the form of text. However, images are +on their way to surpassing text as the medium of choice for social conversations. In these images, consumers +often tag brands. We propose a “visual listening in” approach to measuring how brands are portrayed on +social media (Instagram), by mining visual content posted by users. Our approach consists of two stages. We +first use two supervised machine learning methods, traditional support vector machine classifiers and deep +onvolutional neural networks, to measure brand attributes (glamorous, rugged, healthy, fun) from images. +We then apply the classifiers to brand-related images posted on social media to measure what consumers +re visually communicating about brands. We study 56 brands in the apparel and beverages categories, and +ompare their portrayal in consumer-created images with images on the firm’s official Instagram account, as +well as with consumer brand perceptions measured in a national brand survey. Although the three measures +exhibit convergent validity, we find key differences between how consumers and firms portray the brands on"
+bfef76d0e287fc6401d69a9f65ff174e4fbf0970,Nonnegative Matrix Factorization with Outliers,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE +ICASSP 2016"
+bfebba8356c5d20dc6a9b2f72ff66adaf63321b7,End-to-end pedestrian collision warning system based on a convolutional neural network with semantic segmentation,"End-to-End Pedestrian Collision Warning System +ased on a Convolutional Neural Network +with Semantic Segmentation +Heechul Jung +DGIST +Daegu, Republic of Korea +Min-Kook Choi +DGIST +Daegu, Republic of Korea +Kwon Soon +DGIST +Daegu, Republic of Korea +Woo Young Jung +DGIST +Daegu, Republic of Korea"
+bf05e710dae791f82cc639a09dbe5ec66fed2008,Generating Video Description using Sequence-to-sequence Model with Temporal Attention,"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, +pages 44–52, Osaka, Japan, December 11-17 2016."
bf4825474673246ae855979034c8ffdb12c80a98,"UNIVERSITY OF CALIFORNIA RIVERSIDE Active Learning in Multi-Camera Networks, With Applications in Person Re-Identification A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Electrical Engineering","UNIVERSITY OF CALIFORNIA RIVERSIDE Active Learning in Multi-Camera Networks, With Applications in Person @@ -11793,12 +41111,104 @@ Dissertation Committee: Professor Amit K. Roy-Chowdhury, Chairperson Professor Anastasios Mourikis Professor Walid Najjar"
+bfdcd4d5cc10c8c64743fc7be7e7ad6709d93b53,Evaluation of PCA and LDA techniques for Face recognition using ORL face database,"Evaluation of PCA and LDA techniques for Face +recognition using ORL face database +CSE Dept. Faculty of Engineering, Avinashilingam University, Coimbatore, India +M.Saraswathi, Dr. S. Sivakumari"
+bf735bb7557e73bc6f68853cba828b55bd163726,Fusion of Zernike Moments and SIFT Features for Improved Face Recognition,"International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT2012) +Proceedings published in International Journal of Computer Applications® (IJCA) +Fusion of Zernike Moments and SIFT Features for +Improved Face Recognition +Chandan Singh +Professor +Department of Computer +Science, Punjabi University +Patiala, India +Ekta Walia +Asst. Prof., Department of +Computer Science, South +Asian University, New Delhi, +Neerja Mittal +Asst. Prof., Department of +CSE&IT, RBIEBT, Kharar, +Distt. Mohali, India +India"
+bfffcd2818a1679ac7494af63f864652d87ef8fa,Neural Importance Sampling,"Neural Importance Sampling +THOMAS MÜLLER, Disney Research & ETH Zürich +BRIAN MCWILLIAMS, Disney Research +FABRICE ROUSSELLE, Disney Research +MARKUS GROSS, Disney Research & ETH Zürich +JAN NOVÁK, Disney Research +We propose to use deep neural networks for generating samples in Monte +Carlo integration. Our work is based on non-linear independent compo- +nents estimation (NICE), which we extend in numerous ways to improve +performance and enable its application to integration problems. First, we +introduce piecewise-polynomial coupling transforms that greatly increase +the modeling power of individual coupling layers. Second, we propose to +preprocess the inputs of neural networks using one-blob encoding, which +stimulates localization of computation and improves inference. Third, we de- +rive a gradient-descent-based optimization for the KL and the χ 2 divergence +for the specific application of Monte Carlo integration with unnormalized +stochastic estimates of the target distribution. Our approach enables fast and +ccurate inference and efficient sample generation independently of the di- +mensionality of the integration domain. We show its benefits on generating +natural images and in two applications to light-transport simulation: first,"
+bf15ba4db09fd805763738ec2cb48c09481785dd,Training Deep Neural Network in Limited Precision,"Training Deep Neural Network in Limited Precision +Hyunsun Park∗, Jun Haeng Lee∗, Youngmin Oh, Sangwon Ha, Seungwon Lee +Samsung Advanced Institute of Technology +Samsung-ro 130, Suwon-si, Republic of Korea +{h-s.park,"
bf5940d57f97ed20c50278a81e901ae4656f0f2c,Query-Free Clothing Retrieval via Implicit Relevance Feedback,"Query-free Clothing Retrieval via Implicit Relevance Feedback Zhuoxiang Chen, Zhe Xu, Ya Zhang, Member, IEEE, and Xiao Gu"
+bff354d05823c83215183c8824faefbc093de011,A new efficient SVM and its application to real-time accurate eye localization,"Proceedings of International Joint Conference on Neural Networks, San Jose, California, USA, July 31 – August 5, 2011 +A New Efficient SVM and Its Application to +Real-time Accurate Eye Localization +Shuo Chen and Chengjun Liu"
+bfa763e7cec812f855c712895fa48eae89a34a00,Face Retrieval using Frequency Decoded Local Descriptor,"PREPRINT: ACCEPTED IN MULTIMEDIA TOOLS AND APPLICATIONS, SPRINGER +Face Retrieval using Frequency Decoded Local +Descriptor +Shiv Ram Dubey"
bfb98423941e51e3cd067cb085ebfa3087f3bfbe,Sparseness helps: Sparsity Augmented Collaborative Representation for Classification,"Sparseness helps: Sparsity Augmented Collaborative Representation for Classification Naveed Akhtar, Faisal Shafait, and Ajmal Mian"
+bf4e6ec60e5603324f6a40d2a060420322dbdd62,Kinects and Human Kinetics: A New Approach for Studying Crowd Behavior,"Kinects and Human Kinetics: A New Approach for +Studying Crowd Behavior +Stefan Seera,b,∗, Norbert Br¨andlea, Carlo Rattib +Austrian Institute of Technology (AIT), Giefinggasse 2, 1210 Vienna, Austria +MIT Senseable City Lab, Massachusetts Institute of Technology (MIT), 77 +Massachusetts Avenue, 02139 Cambridge, MA, USA"
+bff9d100e99dd6a99ec26ca867694075b1dcac92,Passive Multimodal 2-D+3-D Face Recognition Using Gabor Features and Landmark Distances,"Passive Multimodal 2-D+3-D Face Recognition +Using Gabor Features and Landmark Distances +Sina Jahanbin, Member, IEEE, Hyohoon Choi, Member, IEEE, and Alan C. Bovik, Fellow, IEEE"
+bf8bcda2e4d04b6bd6f5e70622e972baf525a1c7,Three decades of Cognition & Emotion: A brief review of past highlights and future prospects.,"COGNITION AND EMOTION, 2018 +VOL. 32, NO. 1, 1–12 +https://doi.org/10.1080/02699931.2018.1418197 +nd future prospects +Klaus Rothermunda and Sander L. Kooleb +Institute of Psychology, Friedrich-Schiller-Universität Jena, Jena, Germany; bDepartment of Psychology, VU Amsterdam, +Amsterdam, the Netherlands"
+d3e9c5a63215a9c46bc61ec04df5285ac355e42c,Integration of visual and depth information for vehicle detection,pport (cid:13)(cid:13)de recherche(cid:13)ISSN0249-6399ISRNINRIA/RR--7703--FR+ENGRoboticsINSTITUTNATIONALDERECHERCHEENINFORMATIQUEETENAUTOMATIQUEIntegrationofvisualanddepthinformationforvehicledetectionAlexandrosMakris—MathiasPerrollaz—IgorParomtchik—ChristianLaugierN°7703July2011
+d3c1612ae08241dadf6abd650663f4f9351abaf9,Early Start Intention Detection of Cyclists Using Motion History Images and a Deep Residual Network,"Early Start Intention Detection of Cyclists Using Motion History +Images and a Deep Residual Network +Stefan Zernetsch, Viktor Kress, Bernhard Sick and Konrad Doll"
+d33c9fe66bad7a90e34e8bc1332b73147a30d202,Trace alignment algorithms for offline workload analysis of heterogeneous architectures,"Trace Alignment Algorithms for Offline Workload Analysis +of Heterogeneous Architectures +Muhammet Mustafa Ozdal +Intel Corporation +Hillsboro, OR 97124 +Aamer Jaleel +Intel Corporation +Hudson, MA +Paolo Narvaez +Intel Corporation +Hudson, MA +Steven Burns +Intel Corporation +Hillsboro, OR +Ganapati Srinivasa +Intel Corporation +Hillsboro, OR"
d3b73e06d19da6b457924269bb208878160059da,Implementation of an Automated Smart Home Control for Detecting Human Emotions via Facial Detection,"Proceedings of the 5th International Conference on Computing and Informatics, ICOCI 2015 1-13 August, 2015 Istanbul, Turkey. Universiti Utara Malaysia (http://www.uum.edu.my ) Paper No. @@ -11811,10 +41221,22 @@ Universiti Sains Malaysia, Malaysia, Universiti Sains Malaysia, Malaysia, Universiti Sains Malaysia, Malaysia, Universiti Sains Malaysia, Malaysia,"
+d3612bcc772761b611365fe21c42eafb181338ef,Face and Street Detection with Asymmetric Haar Features,"Face and Street Detection with Asymmetric Haar Features +Geovany A. Ramirez +University of Texas at El Paso +500 W University Ave - El Paso TX 79968 +500 W University Ave - El Paso TX 79968 +Olac Fuentes +University of Texas at El Paso"
d3d71a110f26872c69cf25df70043f7615edcf92,Learning Compact Feature Descriptor and Adaptive Matching Framework for Face Recognition,"Learning Compact Feature Descriptor and Adaptive Matching Framework for Face Recognition Zhifeng Li, Senior Member, IEEE, Dihong Gong, Xuelong Li, Fellow, IEEE, and Dacheng Tao, Fellow, IEEE improvements"
+d33beb4f1477374fbcffd8e9df74ca2547eb77ee,Feature Selection for Tracker-Less Human Activity Recognition,"Feature Selection for tracker-less human activity +recognition(cid:63) +Plinio Moreno, Pedro Ribeiro, and Jos´e Santos-Victor +Instituto de Sistemas e Rob´otica & Instituto Superior T´ecnico +Portugal"
d3b18ba0d9b247bfa2fb95543d172ef888dfff95,Learning and Using the Arrow of Time,"Learning and Using the Arrow of Time Donglai Wei1, Joseph Lim2, Andrew Zisserman3 and William T. Freeman4,5 Harvard University 2University of Southern California @@ -11824,6 +41246,39 @@ elow1). Depending on the video, solving the task may require (a) low-level under reasoning (e.g. semantics), or (c) familiarity with very subtle effects or with (d) camera conventions. In this work, we learn nd exploit several types of knowledge to predict the arrow of time automatically with neural network models trained on large-scale video datasets."
+d3e51c0cfd6ae3d3082c2aa27fa1c73fa9662fdf,Isometry-invariant Surface Matching : Numerical Algorithms and Applications,"ISOMETRY-INVARIANT SURFACE +MATCHING: NUMERICAL ALGORITHMS +AND APPLICATIONS +MICHAEL M. BRONSTEIN +Technion - Computer Science Department - Ph.D. Thesis PHD-2007-04 - 2007"
+d3761354b7df1228eabf46032fd01a4109229d43,Selection of optimal narrowband multispectral images for face recognition. (Sélection des bandes spectrales optimales pour la reconnaissance des visages),"UNIVERSITY OF BURGUANDY +SPIM doctoral school +PhD from the University of Burgundy in +Computer Science +Presented by: +Hamdi Bouchech +Defense Date: January 26, 2015 +Selection of optimal narrowband multispectral images for face +recognition +Thesis supervisor: +Dr. Sebti Foufou +Jury: +Frederic Morain-Nicolier, Professeur a I’IUT de Troyes, Rapporteur. +Pierre BONTON, Professeur à l’ Université Blaise Pascal, retraité , Rapporteur. +Saida Bouakaz, Professeur à l’ Université Claude Bernard Lyon 1, Examinatrice. +Pierre Gouton, Professeur à l’ Université de Bourgogne, Examinateur. +Yassine Ruichek, Professeur à l’ Université de Technologie de Belfort-Montbéliard, +Examinateur. +Sebti Foufou, Professeur à l’ Université de Bourgogne, directeur de thèse."
+d348197e47a8e081bd3f12a22bc52b055ecd8302,Unified Framework for Automated Person Re-identification and Camera Network Topology Inference in Camera Networks,"Unified Framework for Automated Person Re-identification and +Camera Network Topology Inference in Camera Networks +Yeong-Jun Cho, Jae-Han Park*, Su-A Kim*, Kyuewang Lee and Kuk-Jin Yoon +Computer Vision Laboratory, GIST, South Korea +{yjcho, qkrwogks, suakim, kyuewang,"
+d3797366259182070c598e95cef8fff1ddb21f65,Distance-based Camera Network Topology Inference for Person Re-identification,"Distance-based Camera Network Topology Inference for Person Re-identification +Yeong-Jun Cho and Kuk-Jin Yoon +Computer Vision Laboratory, GIST, South Korea +{yjcho,"
d309e414f0d6e56e7ba45736d28ee58ae2bad478,Efficient Two-Stream Motion and Appearance 3 D CNNs for Video Classification,"Efficient Two-Stream Motion and Appearance 3D CNNs for Video Classification Ali Diba @@ -11833,6 +41288,11 @@ Sharif UTech Luc Van Gool ESAT-KU Leuven, ETH Zurich"
d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9,STAIR Actions: A Video Dataset of Everyday Home Actions,
+d3d887aebeeae44cefd5c2bdbb388d9ce109e335,Image Manipulation with Perceptual Discriminators,"Image Manipulation with +Perceptual Discriminators +Diana Sungatullina(cid:63), Egor Zakharov(cid:63), Dmitry Ulyanov, and Victor Lempitsky +Skolkovo Institute of Science and Technology, Moscow, Russia +{d.sungatullina, egor.zakharov, dmitry.ulyanov,"
d3c004125c71942846a9b32ae565c5216c068d1e,Recognizing Age-Separated Face Images: Humans and Machines,"RESEARCH ARTICLE Recognizing Age-Separated Face Images: Humans and Machines @@ -11857,6 +41317,11 @@ Germany Paolo Favaro University of Bern Switzerland"
+d40bd8d44fe78952769a9bb04fe74ce38ef07534,Locally Adaptive Learning Loss for Semantic Image Segmentation,"Locally Adaptive Learning Loss for Semantic Image Segmentation +Jinjiang Guo1,2, Pengyuan Ren1, Aiguo Gu1, Jian Xu1, Weixin Wu1 +Beijing NetPosa Technologies Co., Ltd. Beijing, China +Institut National des Sciences Appliqu´ees de Lyon, Lyon, France +{renpengyuan, guaiguo, xujian,"
d41c11ebcb06c82b7055e2964914b9af417abfb2,CDI-Type I: Unsupervised and Weakly-Supervised Discovery of Facial Events,"CDI-Type I: Unsupervised and Weakly-Supervised Introduction Discovery of Facial Events @@ -11877,8 +41342,34 @@ expression recognition and analysis is slowed. For the most detailed and compreh systems, such as Facial Action Coding System (FACS), three to four months is typically required to train coder (’coding’ refers to the labeling of video using behavioral descriptors). Once trained, each minute of video may require 1 hour or more to code [9]. No wonder relatively few databases are yet available,"
+d497b9e50dc2aacfb1693ca4de6ebf904404d98d,Patch Based Approaches for Visual Object Class Recognition - a Survey,"ALBERT-LUDWIGS-UNIVERSIT ¨AT FREIBURG +INSTITUT F ¨UR INFORMATIK +Lehrstuhl f¨ur Mustererkennung und Bildverarbeitung +Patch Based Approaches for the Recognition of Visual Object +Classes - A Survey +Internal Report 2/06 +Alexandra Teynor +November, 2006"
+d488dad9fa81817c85a284b09ebf198bf6b640f9,FCHD: A fast and accurate head detector,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +FCHD: A fast and accurate head detector +Aditya Vora, Johnson Controls Inc."
d444368421f456baf8c3cb089244e017f8d32c41,CNN for IMU assisted odometry estimation using velodyne LiDAR,"CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR Martin Velas, Michal Spanel, Michal Hradis, and Adam Herout"
+d48bd355d091e7ae75ade4e878fe346741e7da1a,Can You Spot the Semantic Predicate in this Video ?,"Can You Spot the Semantic Predicate in this Video? +Christopher Reale, Claire Bonial, Heesung Kwon and Clare R. Voss +U.S. Army Research Lab, Adelphi, Maryland 20783 +{claire.n.bonial.civ, heesung.kwon.civ,"
+d4ced2086ccd9259ade8fabdba14e0e4d9fc0c40,A Mobile Imaging System for Medical Diagnostics,"A Mobile Imaging System for Medical +Diagnostics +Sami Varjo and Jari Hannuksela +The Center for Machine Vision Research +Department of Computer Science and Engineering +P.O. Box 4500, FI-90014 University of Oulu"
+d40c4e370d35264e324e4e3d5df59e51518c9979,A Transfer Learning based Feature-Weak-Relevant Method for Image Clustering,"A Transfer Learning based Feature-Weak-Relevant Method for +Image Clustering +Bo Dong, Xinnian Wang +Dalian Maritime University +Dalian, China"
d4885ca24189b4414031ca048a8b7eb2c9ac646c,"Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN","Efficient Facial Representations for Age, Gender nd Identity Recognition in Organizing Photo Albums using Multi-output CNN @@ -11887,6 +41378,12 @@ Samsung-PDMI Joint AI Center, St. Petersburg Department of Steklov Institute of Mathematics National Research University Higher School of Economics Nizhny Novgorod, Russia"
+d45dc3546702db7fcef8d4863db319ca84cc8d3d,How emotional are you? Neural Architectures for Emotion Intensity Prediction in Microblogs,"How emotional are you? Neural Architectures for Emotion Intensity +Prediction in Microblogs +Devang Kulshreshtha∗, Pranav Goel∗, and Anil Kumar Singh +Indian Institute of Technology (Banaras Hindu University) Varanasi +{devang.kulshreshtha.cse14, pranav.goel.cse14, +Varanasi, Uttar Pradesh, India"
d4001826cc6171c821281e2771af3a36dd01ffc0,Modélisation de contextes pour l'annotation sémantique de vidéos. (Context based modeling for video semantic annotation),"Modélisation de contextes pour l’annotation sémantique de vidéos Nicolas Ballas @@ -11914,6 +41411,46 @@ DOI: 10.5829/idosi.mejsr.2014.20.01.11434 A Comparative Analysis of Gender Classification Techniques Sajid Ali Khan, Maqsood Ahmad, Muhammad Nazir and Naveed Riaz Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan"
+d4e4369babdba158bfdce1b605f92d6b1b665be4,The amygdala and the relevance detection theory of autism: an evolutionary perspective,"REVIEW ARTICLE +published: 30 December 2013 +doi: 10.3389/fnhum.2013.00894 +The amygdala and the relevance detection theory of autism: +n evolutionary perspective +Tiziana Zalla1* and Marco Sperduti 2,3 +Institut Jean Nicod, Centre National de la Recherche Scientifique, Ecole Normale Supérieure, Paris, France +Laboratoire Mémoire et Cognition, Institut de Psychologie, Université Paris Descartes, Boulogne-Billancourt, France +Inserm U894, Centre de Psychiatrie et Neurosciences, Université Paris Descartes, Paris, France +Edited by: +Corrado Corradi-Dell’Acqua, University +of Geneva, Switzerland +Reviewed by: +Sebastian B. Gaigg, City University +London, UK +Bhismadev Chakrabarti, University of +Reading, UK +Danilo Bzdok, Research Center Jülich, +Germany +*Correspondence:"
+d4f8168242f688af29bcbbe1cc5aec7cd12a601c,Edinburgh Research Explorer Visually Grounded Meaning Representations,"Visually Grounded Meaning Representations +Citation for published version: +Silberer, C, Ferrari, V & Lapata, M 2016, 'Visually Grounded Meaning Representations' IEEE Transactions +on Pattern Analysis and Machine Intelligence. DOI: 10.1109/TPAMI.2016.2635138 +Digital Object Identifier (DOI): +0.1109/TPAMI.2016.2635138 +Link: +Link to publication record in Edinburgh Research Explorer +Document Version: +Peer reviewed version +Published In: +IEEE Transactions on Pattern Analysis and Machine Intelligence +General rights +Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +nd / or other copyright owners and it is a condition of accessing these publications that users recognise and +bide by the legal requirements associated with these rights. +Take down policy +The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer +ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please +ontact providing details, and we will remove access to the work immediately and"
d4e669d5d35fa0ca9f8d9a193c82d4153f5ffc4e,A Lightened CNN for Deep Face Representation,"A Lightened CNN for Deep Face Representation Xiang Wu School of Computer and Communication Engineering @@ -11922,11 +41459,74 @@ Ran He, Zhenan Sun National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences, Beijing, China {rhe,"
+d409d8978034de5e5e8f9ee341d4a00441e3d05f,Annual research review: re-thinking the classification of autism spectrum disorders.,"Journal of Child Psychology and Psychiatry 53:5 (2012), pp 490–509 +doi:10.1111/j.1469-7610.2012.02547.x +Annual Research Review: Re-thinking the +lassification of autism spectrum disorders +Center for Autism and the Developing Brain, Weill-Cornell Medical College and New York Presbyterian Hospital/ +Westchester Division, White Plains, NY, USA +Catherine Lord and Rebecca M. Jones +Background: The nosology of autism spectrum disorders (ASD) is at a critical point in history as the +field seeks to better define dimensions of social-communication deficits and restricted/repetitive +ehaviors on an individual +level for both clinical and neurobiological purposes. These different +dimensions also suggest an increasing need for quantitative measures that accurately map their dif- +ferences, independent of developmental factors such as age, language level and IQ. Method: Psycho- +metric measures, clinical observation as well as genetic, neurobiological and physiological research +from toddlers, children and adults with ASD are reviewed. Results: The question of how to conceptu- +lize ASDs along dimensions versus categories is discussed within the nosology of autism and the +proposed changes to the DSM-5 and ICD-11. Differences across development are incorporated into the +new classification frameworks. Conclusions: It is crucial to balance the needs of clinical practice in +ASD diagnostic systems, with neurobiologically based theories that address the associations between +social-communication and restricted/repetitive dimensions in individuals. Clarifying terminology,"
+d45fbd818f032566e9e8f8bdc0f658cdd6873e8f,Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks,"Full-body High-resolution Anime Generation +with Progressive Structure-conditional +Generative Adversarial Networks +Koichi Hamada, Kentaro Tachibana, Tianqi Li, +Hiroto Honda, and Yusuke Uchida +DeNA Co., Ltd., Tokyo, Japan"
d4b88be6ce77164f5eea1ed2b16b985c0670463a,A Survey of Different 3D Face Reconstruction Methods,"TECHNICAL REPORT JAN.15.2016 A Survey of Different 3D Face Reconstruction Methods Amin Jourabloo Department of Computer Science and Engineering"
+d42142285c46207a16bd4294e437d504e419a9b7,Varying image description tasks : spoken versus written descriptions,"Varying image description tasks: spoken versus written descriptions +Emiel van Miltenburg +Vrije Universiteit Amsterdam +Ruud Koolen +Tilburg University +Emiel Krahmer +Tilburg University"
+d4dd4600e8f4ecfd11fa4a4a702b1f08bc9ec6f7,Combining intention and emotional state inference in a dynamic neural field architecture for human-robot joint action,"Special issue on Grounding Emotions in Robots +Combining intention and emotional +state inference in a dynamic neural +field architecture for human-robot +joint action +Adaptive Behavior +016, Vol. 24(5) 350–372 +Ó The Author(s) 2016 +Reprints and permissions: +sagepub.co.uk/journalsPermissions.nav +DOI: 10.1177/1059712316665451 +db.sagepub.com +Rui Silva1, Luı´s Louro1, Tiago Malheiro1, Wolfram Erlhagen2 and +Estela Bicho1"
+d4712c75a1a51ecbc74e362747926a16a2cd36ed,Automated Human Recognition by Gait using Neural Network,"Image Processing Theory, Tools & Applications +Automated Human Recognition by Gait using Neural Network +Jang-Hee Yoo +Information Security +Research Division, ETRI +S. Korea +Ki-Young Moon +Information Security +Research Division, ETRI +S. Korea"
+d4c657ce3b7e47237201393aa6bba0e19442bfd2,Interpolation Based Tracking for Fast Object Detection in Videos,"Interpolation Based Tracking for Fast Object +Detection In Videos +Rahul Jain, Pramod Sankar K.*, C. V. Jawahar +Center for Visual Information Technology +pramod +IIIT-Hyderabad, INDIA"
d44ca9e7690b88e813021e67b855d871cdb5022f,"Selecting, Optimizing and Fusing 'Salient' Gabor Features for Facial Expression Recognition","QUT Digital Repository: http://eprints.qut.edu.au/ Zhang, Ligang and Tjondronegoro, Dian W. (2009) Selecting, optimizing and @@ -11934,8 +41534,42 @@ fusing ‘salient’ Gabor features for facial expression recognition. In: Neura Information Processing (Lecture Notes in Computer Science), 1-5 December 009, Hotel Windsor Suites Bangkok, Bangkok. © Copyright 2009 Springer-Verlag GmbH Berlin Heidelberg"
+d4901683e2c2552fc2d62d4eb3b1f5d5fa60a5ff,ScaleNet: Scale Invariant Network for Semantic Segmentation in Urban Driving Scenes,
+ba0d84d97eeec7774534b91da78b10c5d924fdc8,Classification with Repulsion Tensors: A Case Study on Face Recognition,"Classification with Repulsion Tensors: A Case Study on Face +Recognition +Hawren Fang∗ +March 16, 2016"
+bad7254ae08f8bf1305e70c7de28374f67f151fd,Ré-identification de personnes à partir des séquences vidéo. (Person re-identification from video sequence),"Ré-identification de personnes à partir des séquences +vidéo +Mohamed Ibn Khedher +To cite this version: +Mohamed Ibn Khedher. Ré-identification de personnes à partir des séquences vidéo. Réseaux et +télécommunications [cs.NI]. Institut National des Télécommunications, 2014. Français. <NNT : +014TELE0018>. <tel-01149691> +HAL Id: tel-01149691 +https://tel.archives-ouvertes.fr/tel-01149691 +Submitted on 7 May 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
bafb8812817db7445fe0e1362410a372578ec1fc,Image-Quality-Based Adaptive Face Recognition,"Image-Quality-Based Adaptive Face Recognition Harin Sellahewa and Sabah A. Jassim"
+bac5906adc227e390f2f70705e990a3e1ec369df,Active Control of Camera Parameters for Object Detection Algorithms,"Active Control of Camera Parameters for Object +Detection Algorithms +Yulong Wu, John Tsotsos +Department of Electrical Engineering and Computer Science +York Univeristy +Toronto, ON M3J 1P3 +Email: {yulong,"
+ba8e0bda11af08b6037666b67cf54ae1f780822d,Spatial Pyramid Matching,"Author manuscript, published in ""Object Categorization: Computer and Human Vision Perspectives Cambridge University Press (Ed.) +(2009) 401--415"""
ba99c37a9220e08e1186f21cab11956d3f4fccc2,A Fast Factorization-Based Approach to Robust PCA,"A Fast Factorization-based Approach to Robust PCA Department of Computer Science, Southern Illinois University,Carbondale, IL 62901 USA Chong Peng, Zhao Kang, and Qiang Cheng @@ -11950,6 +41584,29 @@ MindLAB Research Group Bogot´a, Colombia Bogot´a, Colombia Bogot´a, Colombia"
+ba051292ca6e8c689542831479e436be7035c147,Superpixel Sampling Networks,"Superpixel Sampling Networks +Varun Jampani1, Deqing Sun1, Ming-Yu Liu1, +Ming-Hsuan Yang1,2, Jan Kautz1 +NVIDIA +UC Merced"
+baf0af0ac2f2fbbf0c04141e12886ff850d77413,Feature-based 3d Slam,"KERNEL{BASED CLASSIFIERS WITH +APPLICATIONS TO FACE DETECTION +TH(cid:18)ESE No 3141 (2004) +PR(cid:19)ESENT(cid:19)EE (cid:18)A LA FACULT(cid:19)E SCIENCES ET TECHNIQUES DE L’ING(cid:19)ENIEUR +INSTITUT DE TRAITEMENT DES SIGNAUX +SECTION DE G(cid:19)ENIE (cid:19)ELECTRIQUE ET (cid:19)ELECTRONIQUE +(cid:19)ECOLE POLYTECHNIQUE F(cid:19)ED(cid:19)ERALE DE LAUSANNE +POUR L’OBTENTION DU GRADE DE DOCTEUR (cid:18)ES SCIENCES +Vlad POPOVICI +DEA de sciences des syst(cid:18)emes et des calculateurs, Universit(cid:19)e Technique de Cluj-Napoca, Roumanie +et de nationalit(cid:19)e roumaine +ccept(cid:19)ee sur proposition du jury: +Prof. J.-P. Thiran, directeur de th(cid:18)ese +Dr. S. Bengio, rapporteur +Prof. J. Kittler, rapporteur +Prof. M. Kunt, rapporteur +Lausanne, EPFL +D(cid:19)ecembre 2004"
badcd992266c6813063c153c41b87babc0ba36a3,Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks,"Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks Shivang Agarwal(∗ @@ -11979,6 +41636,33 @@ emocije Uporaba emotivnega raˇcunalniˇstva v priporoˇcilnih sistemih In this paper we present the results of three investigations of"
+baeb207ea6f4b52eea129b9d8597d4b7a0891ad6,"Sparse , Smart Contours to Represent and Edit Images","Sparse, Smart Contours to Represent and Edit Images +Tali Dekel 1 +Chuang Gan 2 +Dilip Krishnan 1 +Ce Liu 1 William T. Freeman 1,3 +Google Research 2 MIT-Watson AI Lab 3 MIT-CSAIL +Reconstruction from Sparse Contour Represenation +Editing in the Contour Domain +.4% px +.5% px +(a) Source +(b) Contours +(c) Source Reconstuction +(d) Edited/blended Contours +(e) Recon. from Edit +Reference +Figure 1. Our method produces high quality reconstructions of images from information along a small number of contours: a source +(512×512) image in (a) is reconstructed in (c) from gradient information stored at the set of colored contours in (b)2, which are less than +5% of the pixels. The model synthesizes hair texture, facial lines and shading even in regions where no input information is provided. +Our model allows for semantically intuitive editing in the contour domain. Top-right: a caricature-like result (e) is created by moving and"
+ba1cf2d0493f25da61bd816f92712291999c0ef6,Simple online and realtime tracking with a deep association metric,"SIMPLE ONLINE AND REALTIME TRACKING WITH A DEEP ASSOCIATION METRIC +Nicolai Wojke†, Alex Bewley(cid:5), Dietrich Paulus† +University of Koblenz-Landau†, Queensland University of Technology(cid:5)"
+bade9b38c45afd4f988e246974427685f3ff599f,Pairwise Rotation Hashing for High-dimensional Features,"Pairwise Rotation Hashing for High-dimensional +Features +Kohta Ishikawa, Ikuro Sato, and Mitsuru Ambai +Denso IT Laboratory, Inc."
badd371a49d2c4126df95120902a34f4bee01b00,Parallel Separable 3D Convolution for Video and Volumetric Data Understanding,"GONDA, WEI, PARAG, PFISTER: PARALLEL SEPARABLE 3D CONVOLUTION Parallel Separable 3D Convolution for Video nd Volumetric Data Understanding @@ -11989,6 +41673,48 @@ Felix Gonda Donglai Wei Toufiq Parag Hanspeter Pfister"
+ba87bcf4bf799001641b7afd7d1025600f57c4a1,A Hybrid Architecture for Tracking People in Real-time Using a Video Surveillance Camera: Application for Behavioural Marketing,"Signal & Image Processing : An International Journal (SIPIJ) Vol.6, No.6, December 2015 +A HYBRID ARCHITECTURE FOR TRACKING +PEOPLE IN REAL-TIME USING A VIDEO +SURVEILLANCE CAMERA: APPLICATION FOR +BEHAVIOURAL MARKETING +Kheireddine AZIZ1, Djamal MERAD2, Jean-Luc DAMOISEAUX3 and +Pierre DRAP2 +SeaTech Toulon, Toulon University, La Gardes, France +LSIS Lab, Aix-Marseille University, Marseille, France +IUT R&T, Aix-Marseille University, Marseille, France"
+bab47c7bf80c9310f947cbdaf71b3c983c497b68,Systematic Parameter Optimization and Application of Automated Tracking in Pedestrian Dominant Situations Date of submission : 2014-0801,"Systematic Parameter Optimization and Application of Automated +Tracking in Pedestrian Dominant Situations +Date of submission: 2014-08-01 +Dariush Ettehadieh* +M.Sc. Student, +Polytechnique Montréal, +500, Chemin de Polytechnique, Montreal +phone : 1-514-266-5544 +Bilal Farooq +Assistant Professor, +Polytechnique Montréal +500, Chemin de Polytechnique, Montreal +phone : 1-514-340-4711 ext. 4802 +Nicolas Saunier +Associate Professor, +Polytechnique Montréal +500, Chemin de Polytechnique, Montreal +phone : 1-514-340-4711 ext. 4962 +5029 Words + 4 Figures + 3 Tables = 6779 +Submitted for presentation to the 94th Annual Meeting of the Transportation Research Board and publication in"
+ba7c01e1432bffc2fcde824d0b0ebd25ad7238c3,Face Recognition Techniques : A Review,"International Journal of Engineering Research and Development +e-ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com +Volume 4, Issue 7 (November 2012), PP. 70-78 +Face Recognition Techniques: A Review +Rajeshwar Dass, 2Ritu Rani, 3Dharmender Kumar +,2,3 Deen Bandhu Chotu Ram University of Science & Technology Murthal, Haryana, India"
+a079309d28b6f8753ca26a789bd0bc43de9bd9f8,Interpretable Counting for Visual Question Answering,"Published as a conference paper at ICLR 2018 +INTERPRETABLE COUNTING FOR VISUAL QUESTION +ANSWERING +Alexander Trott, Caiming Xiong∗, & Richard Socher +Salesforce Research +Palo Alto, CA"
a0f94e9400938cbd05c4b60b06d9ed58c3458303,Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes,"Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes @@ -12013,7 +41739,67 @@ M. Christian WOLF, MC/HDR, INSA de Lyon M. Patrick PEREZ, Chercheur/HDR, Technicolor Rennes M. Moez BACCOUCHE, Chercheur/Docteur, Orange Labs Rennes M. Jean-Luc DUGELAY, PRU, Eurecom Sophia Antipolis"
+a06ef8ef4838c048b814563f7cca479c7d4513f2,Multi-module Singular Value Decomposition for Face Recognition,"ORIENTAL JOURNAL OF +COMPUTER SCIENCE & TECHNOLOGY +An International Open Free Access, Peer Reviewed Research Journal +Published By: Oriental Scientific Publishing Co., India. +www.computerscijournal.org +ISSN: 0974-6471 +April 2014, +Vol. 7, No. (1): +Pgs. 09-14 +Multi-module Singular Value Decomposition +for Face Recognition +A. NAMACHIVAYAM and KALIYAPERUMAL KARTHIKEYAN +Eritrea Institute of Technology, Asmara, Eritrea, North East Africa. +(Received: March 20, 2014; Accepted: March 30, 2014)"
a0c37f07710184597befaa7e6cf2f0893ff440e9,Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning,
+a010835842ac0e49eade395f056e1e33d45b6ea5,Four Way Local Binary Pattern for Gender Classification Using Periocular Images,"Four Way Local Binary Pattern for +Gender Classification Using Periocular +Images +Md. Siyam Sajeeb Khan +(2014-1-60-024) +Rifat Mehreen Amin +(2014-1-60-003) +Department of Computer Science and Engineering +East West University +Aftabnagar, Dhaka-1212, Bangladesh +August, 2017"
+a0a950f513b4fd58cee54bccc49b852943ffd02c,Image Inpainting using Block-wise Procedural Training with Annealed Adversarial Counterpart,"Image Inpainting using Block-wise Procedural Training with Annealed +Adversarial Counterpart +Chao Yang1, Yuhang Song1, Xiaofeng Liu2, Qingming Tang3, and C.-C. Jay Kuo1 +USC, 2Carnegie Mellon University, 3Toyota Technological Institute at Chicago,"
+a012b41fc54060e11744db20ef6d191b290f1879,Unconstrained Face Recognition From Blurred and Illumination with Pose Variant Face Image Using SVM,"ISSN(Online): 2320-9801 +ISSN (Print): 2320-9798 +International Journal of Innovative Research in Computer and Communication Engineering +(An ISO 3297: 2007 Certified Organization) +Vol.2, Special Issue 1, March 2014 +Proceedings of International Conference On Global Innovations In Computing Technology (ICGICT’14) +Department of CSE, JayShriram Group of Institutions, Tirupur, Tamilnadu, India on 6th & 7th March 2014 +Organized by +Unconstrained Face Recognition From Blurred and +Illumination with Pose Variant Face Image Using +Dept. of CSE, PG Student (SE), Sri Krishna College of Engineering and Technology, Coimbatore, Tamilnadu, India1 +C.Indhumathi1"
+a0e3775fd5d5df951ac7f65d3a9165bf4b96fbd8,Towards Automatic Image Editing: Learning to See another You,"Towards Automatic Image Editing: Learning to See another You +Amir Ghodrati1∗, Xu Jia1∗, Marco Pedersoli2†, Tinne Tuytelaars1 +KU Leuven, ESAT-PSI, iMinds +INRIA"
+a0b2df8f72ff672cb0760c5221657a5f48f0ec5d,Searching Image Databases Using Appearance Models,"Searching Image Databases +Using Appearance Models +A thesis submitted to the University of Manchester for the degree of +Doctor of Philosophy in the Faculty of Medicine, Dentistry, Nursing +nd Pharmacy +Ian M. Scott +Division of Imaging Science and Biomedical Engineering"
+a01ba008252d2ce32f326f50c208c9ad9d5c78a6,Detecting Sudden Pedestrian Crossings and Avoiding Accidents Using Arm 11,"K. Sri Krishna Aditya et al Int. Journal of Engineering Research and Applications www.ijera.com +ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1213-1216 +RESEARCH ARTICLE OPEN ACCESS +Detecting Sudden Pedestrian Crossings and Avoiding Accidents +Using Arm 11 +K. Sri Krishna Aditya1, T. Surya Kavita2, U. Yedukondalu3 +Assistant Professor, 2Associate Professor, 3Head of the Department E.C.E. +Aditya Engineering College, 2Aditya Engineering College, 3Aditya Engineering College"
a0fd85b3400c7b3e11122f44dc5870ae2de9009a,Learning Deep Representation for Face Alignment with Auxiliary Attributes,"Learning Deep Representation for Face Alignment with Auxiliary Attributes Zhanpeng Zhang, Ping Luo, Chen Change Loy, Member, IEEE and Xiaoou Tang, Fellow, IEEE"
@@ -12052,6 +41838,40 @@ Beijing Lab of Intelligent Information Technology, School of Computer Science, Youdong Zhao, Xi Song, Yunde Jia Beijing Institute of Technology, Beijing 100081, PR China {zyd458, songxi,"
+a05a770bb2b7778e195a578006482926dfc1af82,Learning to Recognize Pedestrian Attribute,"Learning to Recognize Pedestrian Attribute +Yubin Deng, Ping Luo, Chen Change Loy, Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
+a016fbe8d09402316c7b38946ccd502d76aa8c74,Using a Single RGB Frame for Real Time 3D Hand Pose Estimation in the Wild,"Using a single RGB frame for real time 3D hand pose estimation in the wild +Paschalis Panteleris1 +Iason Oikonomidis1 +Institute of Computer Science, FORTH +Computer Science Department, UOC +Antonis Argyros1,2"
+a0798a0a422520241cc02282946882dd1ef853cd,Full Quantification of Left Ventricle via Deep Multitask Learning Network Respecting Intra- and Inter-Task Relatedness,"Full Quantification of Left Ventricle via Deep +Multitask Learning Network Respecting +Intra- and Inter-Task Relatedness +Wufeng Xue, Andrea Lum, Ashley Mercado, Mark Landis, James Warrington, +nd Shuo Li* +Department of Medical Imaging, Western University, ON, Canada +Digital Imaging Group of London, ON, Canada"
+a0541d4a28d90a17cd3eaa9d1797882eacc8ccf0,Improving Person Re-identification via Pose-Aware Multi-shot Matching,"Improving Person Re-identification via Pose-aware Multi-shot Matching +Yeong-Jun Cho and Kuk-Jin Yoon +Computer Vision Laboratory, GIST, South Korea +{yjcho,"
+a0e5afb1237d47f7a8ac66e7b5ada24cec5222cb,Semantic pooling for image categorization using multiple kernel learning,"SEMANTIC POOLING FOR IMAGE CATEGORIZATION USING MULTIPLE KERNEL +LEARNING +Thibaut Durand(1,2), David Picard(1), Nicolas Thome(2), Matthieu Cord(2) +(1) ETIS, UMR 8051 / ENSEA, Universit´e Cergy-Pontoise, CNRS, F-95000, Cergy, +(2) Sorbonne Universit´es, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France"
+a06761b3181a003c2297d8e86c7afc20e17fd2c6,Convolutional Neural Network-Based Human Detection in Nighttime Images Using Visible Light Camera Sensors,"Article +Convolutional Neural Network-Based Human +Detection in Nighttime Images Using Visible Light +Camera Sensors +Jong Hyun Kim, Hyung Gil Hong and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (J.H.K.); (H.G.H.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Academic Editor: Vittorio M. N. Passaro +Received: 31 March 2017; Accepted: 4 May 2017; Published: 8 May 2017"
a000149e83b09d17e18ed9184155be140ae1266e,Action Recognition in Realistic Sports Videos,"Chapter 9 Action Recognition in Realistic Sports Videos @@ -12061,17 +41881,34 @@ nd local appearance Descriptors Ivan Huerta1, Carles Fern´andez2, and Andrea Prati1 DPDCE, University IUAV, Santa Croce 1957, 30135 Venice, Italy Herta Security, Pau Claris 165 4-B, 08037 Barcelona, Spain"
+a0e03c5b647438299c79c71458e6b1776082a37b,Areas of Attention for Image Captioning,"transformerFigure1.Weproposeanattentionmechanismthatjointlypredictsthenextcaptionwordandthecorrespondingregionateachtime-stepgiventheRNNstate(top).BesidesimplementingourmodelusingattentionareasdefinedoverCNNactivationgridsorobjectproposals,asusedinpreviouswork,wealsopresentaend-to-endtrainableconvolutionalspatialtransformerapproachtocomputeimagespecificattentionareas(bottom).typeorlocation,objectproperties,andtheirinteractions.Neuralencoder-decoderbasedapproaches,similartothoseusedinmachinetranslation[30],havebeenfoundveryeffectiveforthistask,seee.g.[19,23,32].Thesemethodsuseaconvolutionalneuralnetwork(CNN)toen-codetheinputimageintoacompactrepresentation.Are-currentneuralnetwork(RNN)isusedtodecodethisrepre-sentationword-by-wordintoanaturallanguagedescriptionoftheimage.Whileeffective,thesemodelsarelimitedinthattheimageanalysisis(i)static,i.e.doesnotchangeovertimeasthedescriptionisproduced,and(ii)notspatiallylo-calized,i.e.describesthesceneasawholeinsteadoffo-cousingonlocalaspectsrelevanttopartsofthedescription.Attentionmechanismscanaddresstheselimitationsbydy-namicallyfocusingondifferentpartsoftheinputastheout-putsequenceisgenerated.Suchmechanismsareeffectiveforavarietyofsequentialpredictiontasks,includingma-1"
+a759570e6ef674cd93068020c2e6bd036961f7c6,SPEECH-COCO: 600k Visually Grounded Spoken Captions Aligned to MSCOCO Data Set,"SPEECH-COCO: 600k Visually Grounded Spoken Captions Aligned to +MSCOCO Data Set +William N. Havard1, Laurent Besacier1, Olivier Rosec2 +Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG, F-38000 Grenoble, France +Voxygen, France"
a702fc36f0644a958c08de169b763b9927c175eb,Facial expression recognition using Hough forest,"FACIAL EXPRESSION RECOGNITION USING HOUGH FOREST Chi-Ting Hsu1, Shih-Chung Hsu1, and Chung-Lin Huang1,2 . Department of Electrical Engineering, National Tsing-Hua University, Hsin-Chu, Taiwan Email: . Department of Applied Informatics and Multimedia, Asia University, Taichung, Taiwan"
+a7790555c65be0fc5b5de9bcb1dc550f4919ce3f,Literature Survey for Face Detection under Illumination Variation,"International Journal of Scientific Research Engineering & Technology (IJSRET) +Volume 2 Issue 10 pp 659-664 January 2014 +www.ijsret.org ISSN 2278 – 0882 +Literature Survey for Face Detection under Illumination Variation +J.SHYNU, P.KANNAN +PG Scholar Department of ECE, PET Engineering College, India +Professor Department of ECE, PET Engineering College, India"
a7267bc781a4e3e79213bb9c4925dd551ea1f5c4,Proceedings of eNTERFACE 2015 Workshop on Intelligent Interfaces,"Proceedings of eNTERFACE’15 The 11th Summer Workshop on Multimodal Interfaces August 10th - September 4th, 2015 Numediart Institute, University of Mons Mons, Belgium"
+a7a1d3036c542824f2c681c3bf08f5b85f05d9e9,A Fast and Precise HOG-Adaboost Based Visual Support System Capable to Recognize Pedestrian and Estimate Their Distance,"A fast and precise HOG-Adaboost based based visual support +system capable to recognize Pedestrian and estimate their distance. +Yokohama City University, Graduate School of Nanobioscience, 22-2 Seto Kanazawa-ku, 236-0027 Yokohama, Japan +Takahisa Kishino1, Sun Zhe1,Ruggero Micheletto1"
a784a0d1cea26f18626682ab108ce2c9221d1e53,Anchored Regression Networks Applied to Age Estimation and Super Resolution,"Anchored Regression Networks applied to Age Estimation and Super Resolution Eirikur Agustsson D-ITET, ETH Zurich @@ -12093,13 +41930,35 @@ A Summary of literature review : Face Recognition Kittikhun Meethongjan & Dzulkifli Mohamad Faculty of Computer Science & Information System, University Technology of Malaysia, 81310 Skudai, Johor, Malaysia."
+a77e0db38ed7ad95a3bca95fea72048985c54508,DART: Distribution Aware Retinal Transform for Event-based Cameras,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +DART: Distribution Aware Retinal Transform for +Event-based Cameras +Bharath Ramesh*, Hong Yang, Garrick Orchard, Ngoc Anh Le Thi, and Cheng Xiang, Member, IEEE"
+a7fe834a0af614ce6b50dc093132b031dd9a856b,Orientation Driven Bag of Appearances for Person Re-identification,"Orientation Driven Bag of Appearances for Person +Re-identification +Liqian Ma, Hong Liu†, Member, IEEE, Liang Hu, Can Wang, Qianru Sun"
a7664247a37a89c74d0e1a1606a99119cffc41d4,Modal Consistency based Pre-Trained Multi-Model Reuse,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+a7bfb6426359140a0bc0c84741ad9a3ac83eff04,Object-Level Context Modeling For Scene Classification with Context-CNN,"Object-Level Context Modeling For Scene Classification with Context-CNN +Syed Ashar Javed1 and Anil Kumar Nelakanti2 +IIIT Hyderabad, 2Amazon"
+a71e3cf566de457336aab9dd6a5f5d6282b4a6af,Visual Abstraction for Zero-Shot Learning,
+a73bc57fb0aa429ba5f7f12b6d02e2c6274cabdd,A Superior Tracking Approach: Building a Strong Tracker through Fusion,"A Superior Tracking Approach: +Building a Strong Tracker through Fusion +Christian Bailer1, Alain Pagani1, and Didier Stricker1,2 +German Research Center for Artificial Intelligence, Kaiserslautern, Germany +University of Kaiserslautern, Germany"
+a7152589980ec27375023d719eec6acc04b7d4fd,Generating Facial Expressions,"Generating Facial Expressions +Jonathan Suit +Georgia Tech"
a7a6eb53bee5e2224f2ecd56a14e3a5a717e55b9,Face Recognition Using Multi-viewpoint Patterns for Robot Vision,"1th International Symposium of Robotics Research (ISRR2003), pp.192-201, 2003 Face Recognition Using Multi-viewpoint Patterns for Robot Vision Kazuhiro Fukui and Osamu Yamaguchi Corporate Research and Development Center, TOSHIBA Corporation , KomukaiToshiba-cho, Saiwai-ku, Kawasaki 212-8582 Japan"
+a7e274db8f1389b95469588995f18c1c42b62534,VideoStory Embeddings Recognize Events when Examples are Scarce,
+a7e78f80e0e37d0c17bc09058c27996e32e4454e,UNAM at SemEval-2018 Task 10: Unsupervised Semantic Discriminative Attribute Identification in Neural Word Embedding Cones,"Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018), pages 977–984 +New Orleans, Louisiana, June 5–6, 2018. ©2018 Association for Computational Linguistics"
a758b744a6d6962f1ddce6f0d04292a0b5cf8e07,"Study on Human Face Recognition under Invariant Pose, Illumination and Expression using LBP, LoG and SVM","ISSN XXXX XXXX © 2017 IJESC Research Article Volume 7 Issue No.4 Study on Human Face Recognition under Invariant Pose, Illumination @@ -12120,12 +41979,90 @@ Support Vector Machine classifier (SVM ) is used to classify t he image. The a like illu mination, e xp ression and pose variation Ke ywor ds: Face Recognition, Local Binary Pattern, Laplac ian of Gaussian, histogram, illu mination, pose angle, exp ression variations, SVM ."
+a73a16203b644353a287a4759bc951450e67d700,BodyNet: Volumetric Inference of 3D Human Body Shapes,"BodyNet: Volumetric Inference of +D Human Body Shapes +G¨ul Varol1,* +Ersin Yumer2,‡ +Duygu Ceylan2 +Bryan Russell2 +Jimei Yang2 +Ivan Laptev1,* +Cordelia Schmid1,† +Inria, France +Adobe Research, USA"
+a764cba765648c6e36782b02393ea2eed5cd69c7,Contributions to large-scale learning for image classification. (Contributions à l'apprentissage grande échelle pour la classification d'images),"CONTRIBUTIONSTOLARGE-SCALELEARNINGFORIMAGECLASSIFICATIONZeynepAkataPhDThesisl’´EcoleDoctoraleMath´ematiques,SciencesetTechnologiesdel’Information,InformatiquedeGrenoble"
+a7663528eb6c9b79a68b94800e30da952c0b6bb2,IFQ-Net : Integrated Fixed-point Quantization Networks for Embedded Vision,"IFQ-Net: Integrated Fixed-point Quantization Networks for Embedded Vision +Hongxing Gao, Wei Tao, Dongchao Wen +Canon Information Technology (Beijing) Co., LTD +Tse-Wei Chen, Kinya Osa, Masami Kato +Device Technology Development Headquarters, Canon Inc."
+a7e8ce268c16ea8c10e4c5ccd8d6e53702423faa,The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment,"The Ciona17 Dataset for Semantic Segmentation +of Invasive Species in a Marine Aquaculture Environment +Angus Galloway∗, Graham W. Taylor∗, Aaron Ramsay†, Medhat Moussa∗ +School of Engineering +University of Guelph +Guelph, ON, Canada +{gallowaa, gwtaylor, +Department of Agriculture and Fisheries +Government of PEI +Montague, PEI, Canada"
a75ee7f4c4130ef36d21582d5758f953dba03a01,Human face attributes prediction with Deep Learning,"DD2427 Final Project Report Mohamed Abdulaziz Ali Haseeb DD2427 Final Project Report Human face attributes prediction with Deep Learning Mohamed Abdulaziz Ali Haseeb"
+a726858df7c9503116504206577a938df1a67815,Unsupervised Vehicle Re-Identification using Triplet Networks,"Unsupervised Vehicle Re-Identification using Triplet Networks +Pedro Antonio Mar´ın-Reyes +Andrea Palazzi +University of Las Palmas de Gran Canaria +University of Modena and Reggio Emilia +Luca Bergamini +Simone Calderara +University of Modena and Reggio Emilia +University of Modena and Reggio Emilia +Javier Lorenzo-Navarro +Rita Cucchiara +University of Las Palmas de Gran Canaria +University of Modena and Reggio Emilia"
+a760ce8baddf2da7946d2ed6f02ac3927f39a9da,Face Recognition Using a Unified 3D Morphable Model,"Face Recognition Using a Unified 3D Morphable Model +Hu, G., Yan, F., Chan, C-H., Deng, W., Christmas, W., Kittler, J., & Robertson, N. M. (2016). Face Recognition +Using a Unified 3D Morphable Model. In Computer Vision – ECCV 2016: 14th European Conference, +Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII (pp. 73-89). (Lecture Notes in +Computer Science; Vol. 9912). Springer Verlag. DOI: 10.1007/978-3-319-46484-8_5 +Published in: +Computer Vision – ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, +016, Proceedings, Part VIII +Document Version: +Peer reviewed version +Queen's University Belfast - Research Portal: +Link to publication record in Queen's University Belfast Research Portal +Publisher rights +The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46484-8_5 +General rights +Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other +opyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated +with these rights. +Take down policy +The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to"
+a71106ef95103276fac010c10291f6dd6fd9d9f5,Social status level and dimension interactively influence person evaluations indexed by P300s.,"ISSN: 1747-0919 (Print) 1747-0927 (Online) Journal homepage: http://www.tandfonline.com/loi/psns20 +Social status level and dimension interactively +influence person evaluations indexed by P300s +Ivo Gyurovski, Jennifer Kubota, Carlos Cardenas-Iniguez & Jasmin Cloutier +To cite this article: Ivo Gyurovski, Jennifer Kubota, Carlos Cardenas-Iniguez & Jasmin Cloutier +(2017): Social status level and dimension interactively influence person evaluations indexed by +To link to this article: http://dx.doi.org/10.1080/17470919.2017.1326400 +Accepted author version posted online: 02 +May 2017. +Published online: 15 May 2017. +Submit your article to this journal +Article views: 11 +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=psns20 +Download by: [University of Chicago Library] +Date: 22 May 2017, At: 09:19"
a775da3e6e6ea64bffab7f9baf665528644c7ed3,Human Face Pose Estimation based on Feature Extraction Points,"International Journal of Computer Applications (0975 – 8887) Volume 142 – No.9, May 2016 Human Face Pose Estimation based on Feature @@ -12144,12 +42081,60 @@ Div. of EE, Dept. of EECS, KAIST Kwang-Hyun Park Human-friendly Welfare Robotic System Engineering Research Center, KAIST 73-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea"
+a70fa8af52e4cc32dae09e6e753f1dd3ec198327,Neural Task Representations as Weak Supervision for Model Agnostic Cross-Lingual Transfer,"Neural Task Representations as Weak Supervision for Model Agnostic +Cross-Lingual Transfer +Sujay Kumar Jauhar +Microsoft Research AI +Redmond, WA, USA +Michael Gamon +Microsoft Research AI +Redmond, WA, USA +Patrick Pantel∗ +Facebook Inc. +Seattle, WA, USA"
+a7eee3222623778294461102d0dc770d4e09a7c5,A novel fusion-based method for expression-invariant gender classification,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE +ICASSP 2009"
+b878518814fee31ce8cb61040301e7a921892156,A Gaussian Feature Adaptive Integrated PCA-ICA Approach for Facial Recognition,"Vaishali et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.5, May- 2015, pg. 401-406 +Available Online at www.ijcsmc.com +International Journal of Computer Science and Mobile Computing +A Monthly Journal of Computer Science and Information Technology +IJCSMC, Vol. 4, Issue. 5, May 2015, pg.401 – 406 +RESEARCH ARTICLE +ISSN 2320–088X +A Gaussian Feature Adaptive Integrated PCA-ICA +Approach for Facial Recognition +Student, Dept. of ECE, ITM University Gurgaon Haryana +Vaishali +Dr. Rekha Vig +Asstt. Prof, Dept. of ECE, ITM University Gurgaon Haryana"
b871d1b8495025ff8a6255514ed39f7765415935,Application of Completed Local Binary Pattern for Facial Expression Recognition on Gabor Filtered Facial Images,"Application of Completed Local Binary Pattern for Facial Expression Recognition on Gabor Filtered Facial Images Tanveer Ahsan, 2Rifat Shahriar, *3Uipil Chong Dept. of Electrical and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea"
+b85901174fa83c76ae994603228ba5b4f299a1af,"Sos, Lost in a High Dimensional Space","SOS, LOST IN A HIGH DIMENSIONAL SPACE +Anne Hendrikse"
b8dba0504d6b4b557d51a6cf4de5507141db60cf,Comparing Performances of Big Data Stream Processing Platforms with RAM3S,"Comparing Performances of Big Data Stream Processing Platforms with RAM3S"
+b8b46df1b013c30d791972ee109425a94e3adc06,"Automaticity, Control, and the Social Brain","C H A P T E R 1 9 +Automaticity, Control, +nd the Social Brain +Robert P. Spunt and Matthew D. Lieberman +The social world is good at keeping the +human brain busy, posing cognitive chal- +lenges that are complex, frequent, and enor- +mously important to our well-being. In fact, +the computational demands of the social +world may be the principal reason why +the human brain has evolved to its present +form and function relative to other primates +(Dunbar, 1993). Importantly, the human +rain is often able to make sense of the +social world without having to do too much +work. This is because many of its processes +re automatically initiated by the presence +of relevant social stimuli and run to comple- +tion without much, if any, conscious inter- +vention (Bargh & Chartrand, 1999; Gilbert,"
b89862f38fff416d2fcda389f5c59daba56241db,A Web Survey for Facial Expressions Evaluation,"A Web Survey for Facial Expressions Evaluation Matteo Sorci Gianluca Antonini @@ -12161,6 +42146,53 @@ Ecole Polytechnique Federale de Lausanne, Operation Research Group Michel Bierlaire Ecublens, 1015 Lausanne, Switzerland June 9, 2008"
+b8612b5c1aa0970b5d99340ad19d7fcede1b0854,"Fusion of Speech, Faces and Text for Person Identification in TV Broadcast","Fusion of speech, faces and text for +person identification in TV broadcast +Herv´e Bredin1, Johann Poignant2, Makarand Tapaswi3, Guillaume Fortier4, +Viet Bac Le5, Thibault Napoleon6, Hua Gao3, Claude Barras1, Sophie Rosset1, +Laurent Besacier2, Jakob Verbeek4, Georges Qu´enot2, Fr´ed´eric Jurie6, and +Hazim Kemal Ekenel3 +Univ Paris-Sud / CNRS-LIMSI UPR 3251, BP 133, F-91403 Orsay, France +UJF-Grenoble 1 / UPMF-Grenoble 2 / Grenoble INP / CNRS-LIG UMR 5217, +F-38041 Grenoble, France +Karlsruher Institut fur Technologie, Karlsruhe, Germany +INRIA Rhone-Alpes, 655 Avenue de lEurope, F-38330 Montbonnot, France +5 Vocapia Research, 3 rue Jean Rostand, Parc Orsay Universit´e, F-91400 Orsay, +6 Universit´e de Caen / GREYC UMR 6072, F-14050 Caen Cedex, France +France"
+b82a4a0457170258aaf622b81e6f739a220398eb,Probe Strongly Similar Neutral Strongly Dissimilar Quasi-similar Quasi-dissimilar Push Pull,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TMM.2016.2605058, IEEE +Transactions on Multimedia +Person Re-identification via Ranking Aggregation +of Similarity Pulling and Dissimilarity Pushing +Mang Ye, Chao Liang(cid:3), Yi Yu, Zheng Wang, Qingming Leng, +Chunxia Xiao, Member, IEEE, Jun Chen, Ruimin Hu, Senior Member, IEEE"
+b88771387d5c0f09ea9a2ccc743b11471fb257b4,An interactive facial-expression training platform for individuals with autism spectrum disorder,"An Interactive Facial-Expression Training Platform +for Individuals with Autism Spectrum Disorder +Christina Tsangouri*, Wei Li+, Zhigang Zhu* +* Dept. of Comp. Sci.. and +Dept of Electrical Eng.. +City College of New York, New York, USA"
+b8a5839f6b1e051f430f2b89d5a1a7e49a10655a,DCFNet: Deep Neural Network with Decomposed Convolutional Filters,"DCFNet: Deep Neural Network with Decomposed Convolutional Filters +Qiang Qiu 1 Xiuyuan Cheng 1 Robert Calderbank 1 Guillermo Sapiro 1"
+b8969d6e5658b360111f33d3f85eac63afcd7252,WESPE: Weakly Supervised Photo Enhancer for Digital Cameras,"WESPE: Weakly Supervised Photo Enhancer for Digital Cameras +Andrey Ignatov, Nikolay Kobyshev, Kenneth Vanhoey, Radu Timofte, Luc Van Gool +ETH Zurich +{andrey, nk, vanhoey, timofter,"
+b8053da77bf1a5b4c87fddf6140be0a612cfc164,Multi-Pose Face Recognition Using Hybrid Face Features Descriptor,"MULTI-POSE FACE RECOGNITION USING +HYBRID FACE FEATURES DESCRIPTOR +I Gede Pasek Suta WIJAYA[1,2], Keiichi UCHIMURA[2] and Gou KOUTAKI[2]"
+b8b202fa955801da840afc9f523d439d14d87cc1,A Novel Approach for Monocular 3D Object Tracking in Cluttered Environment,"International Journal of Computational Intelligence Research +ISSN 0973-1873 Volume 13, Number 5 (2017), pp. 851-864 +© Research India Publications +http://www.ripublication.com +A Novel Approach for Monocular 3D Object +Tracking in Cluttered Environment +Navneet S. Ghedia +Research scholar, Gujarat Technological University, Gujarat, India. +Dr. C.H. Vithalani +Professor and Head of EC Dept., Government Engineering College, Rajkot, India. +Dr. Ashish Kothari +Associate Professor and Head of EC Dept., Atmiya Institute of Technology and +Science, Rajkot, Gujarat, India."
b8f3f6d8f188f65ca8ea2725b248397c7d1e662d,Selfie Detection by Synergy-Constraint Based Convolutional Neural Network,"Selfie Detection by Synergy-Constriant Based Convolutional Neural Network Yashas Annadani, Vijaykrishna Naganoor, Akshay Kumar Jagadish and Krishnan Chemmangat @@ -12172,14 +42204,154 @@ Tu-Khiem Le, Thanh-An Nguyen, Minh-Triet Tran Faculty of Information Technology University of Science, Vietnam National University-Ho Chi Minh city {nhmtien, cqhuu, nvtu,"
+b8471908880c916ebc70ac900e9446705ed258f4,Transitional and translational studies of risk for anxiety.,"Review +TRANSITIONAL AND TRANSLATIONAL STUDIES +OF RISK FOR ANXIETY +B. J. Casey Ph.D., +Erika J. Ruberry B.S., Victoria Libby B.A., Charles E. Glatt M.D., Ph.D., Todd Hare Ph.D., +Fatima Soliman M.D., Ph.D., Stephanie Duhoux Ph.D., Helena Frielingsdorf M.D., Ph.D., and Nim Tottenham +Ph.D. +Adolescence reflects a period of increased rates of anxiety, depression, and +suicide. Yet most teens emerge from this period with a healthy, positive outcome. +In this article, we identify biological factors that may increase risk for some +individuals during this developmental period by: (1) examining changes in +neural circuitry underlying core phenotypic features of anxiety as healthy +individuals transition into and out of adolescence; (2) examining genetic factors +that may enhance the risk for psychopathology in one individual over another +using translation from mouse models to human neuroimaging and behavior; +nd (3) examining the effects of early experiences on core phenotypic features of +nxiety using human neuroimaging and behavioral approaches. Each of these +pproaches alone provides only limited information on genetic and environ- +mental influences on complex human behavior across development. Together, +they reflect an emerging field of translational developmental neuroscience in"
+b856c493c2e5cbb71791f56763886e5e0d40295c,Unsupervised Domain Adaptive Re-Identification: Theory and Practice,"Unsupervised Domain Adaptive Re-Identification: +Theory and Practice +Liangchen Song12∗ Cheng Wang23∗ Lefei Zhang1 Bo Du1 +Qian Zhang2 Chang Huang2 Xinggang Wang3 +Wuhan University 2Horizon Robotics +Huazhong Univ. of Science and Technology"
+b8e35566129299c3591af0fd4f127e5e0d0b5774,3D Facial Image Comparison using Landmarks,"D Facial Image Comparison using Landmarks +A study to the discriminating value of the characteristics +of 3D facial landmarks and their automated detection. +Alize Scheenstra +Master thesis: INF/SCR-04-54 +Netherlands Forensic Institute +Institute of Information and Computing Sciences +Utrecht University +February 2005"
+b831a08a7098b64485587541485859c9213e6dc2,Applications of 3D morphable models for faces with expressions,"Applications of 3D morphable models for faces with expressions +B. Chu1,2, S. Romdhani1 et L. Chen2 +Morpho, SAFRAN Group +1 boulevard Galliéni 92130 Issy-Les-Moulineaux - France +{baptiste.chu, +Université de Lyon, CNRS +Ecole Centrale de Lyon, LIRIS UMR5205, F-69134 +Lyon, France +{baptiste.chu,"
+b8a53daa97fb917a89c351c47f0b197573e20023,Recognizing Faces---An Approach Based on Gabor Wavelets,"Recognizing Faces --- An Approach Based on Gabor +Wavelets +By LinLin Shen, BSc, MSc +Thesis submitted to the University of Nottingham +for the degree of Doctor of Philosophy +July 2005"
+b8f09ff53e5a1700492100b8cd1b9e9783485376,Clustered Multi-task Feature Learning for Attribute Prediction,"#1105 +CVPR 2016 Submission #1105. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. +#1105 +Clustered Multi-task Feature Learning for Attribute Prediction +Anonymous CVPR submission +Paper ID 1105"
+b8aef59bac4035013bcdaa9b56d665fc8b4e187d,Optimal Bayes Classification of High Dimensional Data in Face Recognition,"Optimal Bayes Classification of High Dimensional Data in Face +Recognition +GRIFT Research Group, CRISTAL Laboratory, National School of Computer Sciences, University of Manouba, +Wissal Drira and Faouzi Ghorbel +Manouba, Tunisia +Keywords: +Face Classification, Bayes, Feature Extraction, Reduction Dimension, L2 Probabilistic Dependence +Measure."
b8a829b30381106b806066d40dd372045d49178d,A Probabilistic Framework for Joint Pedestrian Head and Body Orientation Estimation,"A Probabilistic Framework for Joint Pedestrian Head nd Body Orientation Estimation Fabian Flohr, Madalin Dumitru-Guzu, Julian F. P. Kooij, and Dariu M. Gavrila"
+b8a4e7c21c3163b7595dac0cb00cf518e2dd82b5,Coupling Fall Detection and Tracking in Omnidirectional Cameras,"Coupling Fall Detection and Tracking in +Omnidirectional Cameras +removed for blind review +No Institute Given"
+b88e0c3a6a95e5193085a258cd281802852e5a4a,Progression in large Age-gap face verification,"International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 +Volume: 04 Issue: 09 | Sep -2017 www.irjet.net p-ISSN: 2395-0072 +Progression in large Age-gap face verification +Neha Rahman1, Ankit Chaora2 +,2 Dept. of Electronics and Telecommunication Engineering, Rungta College of Engineering and Technology +M.tech Scholar, Digital Electronics, 2Assistant Professor +Bhilai, India +techniques, database, machine +research projects. +. The +increasing need for surveillance related +pplications due to drug trafficking and terrorist +ctivities etc. +. The availability of real time hardware. +. The re-emergence of neural network classifiers with +emphasis on real time computation and adaptation. +---------------------------------------------------------------------***--------------------------------------------------------------------- +. The increase in emphasis on civilian or commercial"
b1d89015f9b16515735d4140c84b0bacbbef19ac,Too Far to See? Not Really!—Pedestrian Detection With Scale-Aware Localization Policy,"Too Far to See? Not Really! — Pedestrian Detection with Scale-aware Localization Policy Xiaowei Zhang, Li Cheng, Bo Li, and Hai-Miao Hu"
+b12431e61172443c534ea523a4d7407e847b5c5b,Yüz Tanımaya Dayalı Kişi Bazlı Test Otomasyonu,"Y¨uz Tanımaya Dayalı Ki¸si Bazlı Test +Otomasyonu +Alphan C¸ amlı1, Damla G¨ulen1, Nihat ¨Uk1, and Anıl G¨undo˘gdu1 +Siemens A.S., Istanbul 34870, Turkey"
+b1e27fade89e973f4087ed9a243981b0e713b22c,Functional neuroanatomy and the rationale for using EEG biofeedback for clients with Asperger's syndrome.,"Appl Psychophysiol Biofeedback (2010) 35:39–61 +DOI 10.1007/s10484-009-9095-0 +Functional Neuroanatomy and the Rationale for Using EEG +Biofeedback for Clients with Asperger’s Syndrome +Lynda Thompson Æ Michael Thompson Æ +Andrea Reid +Published online: 1 July 2009 +Ó Springer Science+Business Media, LLC 2009 +nd Oberman"
+b18f94c5296a9cebe9e779d50d193fd180f78ed9,Forecasting Interactive Dynamics of Pedestrians with Fictitious Play,"Forecasting Interactive Dynamics of Pedestrians with Fictitious Play +Wei-Chiu Ma1 De-An Huang2 Namhoon Lee3 Kris M. Kitani4 +Stanford +Oxford"
b14b672e09b5b2d984295dfafb05604492bfaec5,Apprentissage de Modèles pour la Classification et la Recherche d ’ Images Learning Image Classification and Retrieval Models,LearningImageClassificationandRetrievalModelsThomasMensink
+b183914d0b16647a41f0bfd4af64bf94a83a2b14,Extensible video surveillance software with simultaneous event detection for low and high density crowd analysis,"Extensible Video Surveillance Software with +Simultaneous Event Detection for Low and High +Density Crowd Analysis +Anuruddha L. Hettiarachchi, Heshani O. Thathsarani, Pamuditha U. Wickramasinghe, +Dilranjan S. Wickramasuriya and Ranga Rodrigo +Department of Electronic and Telecommunication Engineering, University of Moratuwa, Sri Lanka +Email: 090184v, 090518c, 090560v, 090561b,"
+b196f95a4274533b7f931a509eaf5507358945f9,Transformation-Invariant Analysis of Visual Signals with Parametric Models,"POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCESacceptée sur proposition du jury:Prof. P. Vandergheynst, président du juryProf. P. Frossard, directeur de thèseProf. D. Kressner, rapporteur Dr G. Peyré, rapporteur Prof. M. B. Wakin, rapporteurTransformation-Invariant Analysis of Visual Signals with Parametric ModelsTHÈSE NO 5844 (2013)ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNEPRÉSENTÉE LE 4 OCTOBRE 2013 À LA FACULTÉ DES SCIENCES ET TECHNIQUES DE L'INGÉNIEURLABORATOIRE DE TRAITEMENT DES SIGNAUX 4PROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUESuisse2013PARElif VURAL"
+b13254c2c9ca90f57e385d34abc7fe78d74e5222,Real-Time Multi-object Tracking with Occlusion and Stationary Objects Handling for Conveying Systems,"Real-time Multi-Object Tracking with Occlusion and +Stationary Objects Handling for Conveying Systems +Adel Benamara, Serge Miguet, Mihaela Scuturici +To cite this version: +Adel Benamara, Serge Miguet, Mihaela Scuturici. Real-time Multi-Object Tracking with Occlu- +sion and Stationary Objects Handling for Conveying Systems. 12th International Symposium +on Visual Computing (ISVC’16), Dec 2016, Las Vegas, NV, United States. . +HAL Id: hal-01385529 +https://hal.archives-ouvertes.fr/hal-01385529 +Submitted on 26 Oct 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de"
+b11e97d5a12046ded77bc4dc0f762ac3c34e65cb,Blur and Illumination Invariant Robust Face Recognition Using Support Vector Machine (svm),"Vetri--International Journal of Computer Science information and Engg., Technologies ISSN 2277-4408 || 01032014-011 +BLUR AND ILLUMINATION INVARIANT ROBUST +FACE RECOGNITION USING SUPPORT VECTOR +MACHINE (SVM) +A.Vetri Selvi1 , N.Priyalakshmi2, S.Reshmi3 +, G.Nandhini4, +1, 2, 3 UG Scholars, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore, India. +4 Assistant Professor, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore, +India."
b1a3b19700b8738b4510eecf78a35ff38406df22,Automatic Analysis of Facial Actions: A Survey,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2017.2731763, IEEE Transactions on Affective Computing JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014 @@ -12202,6 +42374,17 @@ Received: 04.02.2017 Accepted/Published Online: 01.06.2017 (cid:15) Final Version: 05.10.2017"
+b16ff1331f961b2067c9464c491b7cbe90694758,Automatic plankton image classification combining multiple view features via multiple kernel learning,"Zheng et al. BMC Bioinformatics 2017, 18(Suppl 16):570 +DOI 10.1186/s12859-017-1954-8 +RESEARCH +Open Access +Automatic plankton image classification +ombining multiple view features via multiple +kernel learning +Haiyong Zheng1, Ruchen Wang1, Zhibin Yu1, Nan Wang1, Zhaorui Gu1 and Bing Zheng2* +From 16th International Conference on Bioinformatics (InCoB 2017) +Shenzhen, China. 20-22 September 2017 +including phytoplankton and zooplankton, are the main source of food for organisms in the"
b15a06d701f0a7f508e3355a09d0016de3d92a6d,Facial contrast is a cue for perceiving health from the face.,"Running head: FACIAL CONTRAST LOOKS HEALTHY Facial contrast is a cue for perceiving health from the face Richard Russell1, Aurélie Porcheron2,3, Jennifer R. Sweda1, Alex L. Jones1, Emmanuelle @@ -12219,28 +42402,105 @@ College, Gettysburg, PA 17325, USA. Email: This is a prepublication copy. This article may not exactly replicate the authoritative document published in the APA journal. It is not the copy of record. The authoritative document can be found through this DOI: http://psycnet.apa.org/doi/10.1037/xhp0000219"
+b137480d2ccf3b53433de208815ce891d95af912,Visual Sentences for Pose Retrieval Over Low-Resolution Cross-Media Dance Collections,"Visual Sentences for Pose Retrieval over +Low-resolution Cross-media Dance Collections +Reede Ren, Member, IEEE, John Collomosse, Member, IEEE"
+b17b20c3a3804482a1af3be897758d4f3be26677,Self-calibrating 3D context for retrieving people with luggage,"Self-Calibrating 3D Context for Retrieving People with Luggage +Johannes Schels∗ , Joerg Liebelt∗ +EADS Innovation Works +M¨unchen, Germany +Rainer Lienhart +University of Augsburg +Augsburg, Germany"
+b13499d60e7be1d593ec91fc952b9c32ce62bd57,Gambit: A Robust Chess-Playing Robotic System,"Gambit: A Robust Chess-Playing Robotic System +Cynthia Matuszek, Brian Mayton, Roberto Aimi, Marc Peter Deisenroth, Liefeng Bo, +Robert Chu, Mike Kung, Louis LeGrand, Joshua R. Smith, Dieter Fox"
b1444b3bf15eec84f6d9a2ade7989bb980ea7bd1,Local Directional Relation Pattern for Unconstrained and Robust Face Retrieval,"LOCAL DIRECTIONAL RELATION PATTERN Local Directional Relation Pattern for Unconstrained and Robust Face Retrieval Shiv Ram Dubey, Member, IEEE"
+b1edff56936e5d306e51479142b98cc2414c1a56,Human-Centered Autonomous Vehicle Systems: Principles of Effective Shared Autonomy,"Human-Centered Autonomous Vehicle Systems: +Principles of E(cid:128)ective Shared Autonomy +Massachuse(cid:138)s Institute of Technology (MIT) +Lex Fridman +Figure 1: Principles of shared autonomy used for the design and development of the Human-Centered Autonomous Vehicle."
b1451721864e836069fa299a64595d1655793757,Criteria Sliders: Learning Continuous Database Criteria via Interactive Ranking,"Criteria Sliders: Learning Continuous Database Criteria via Interactive Ranking James Tompkin,1∗ Kwang In Kim,2∗ Hanspeter Pfister,3 and Christian Theobalt4 Brown University 2University of Bath Harvard University 4Max Planck Institute for Informatics"
+b1ec55cbf2e9a6785e1f1f2fc060e4171ec88b4b,Implicit Discrimination of Basic Facial Expressions of Positive/Negative Emotion in Fragile X Syndrome and Autism Spectrum Disorder.,"015, Vol. 120, No. 4, 328–345 +EAAIDD +DOI: 10.1352/1944-7558-120.4.328 +Implicit Discrimination of Basic Facial Expressions of +Positive/Negative Emotion in Fragile X Syndrome and +Autism Spectrum Disorder +Hayley Crawford, Joanna Moss, Giles M. Anderson, Chris Oliver, and Joseph P. McCleery"
+b1ffa7a926e129f8dccdd6f258fea034cbee9160,Minimizing hallucination in histogram of Oriented Gradients,"Minimizing hallucination in Histogram of Oriented Gradients +Sławomir B ˛ak Michał Koperski +INRIA Sophia Antipolis, STARS group +François Brémond +004, route des Lucioles, BP93 +06902 Sophia Antipolis Cedex - France +Javier Ortiz"
+b1bd58bb76ae9e4504622a941e1da21a24b5cfdd,"International conference on Advanced Computing , Communication and Networks ’ 11 1087 Face Recognition Using Incremental Principal Component Analysis","International conference on Advanced Computing, Communication and Networks’11 +Face Recognition Using Incremental Principal Component Analysis +Satish S. Banait1, Vivek Kshirsagar2, Meghana Nagori3, Archana R. Ugale4 +Dept. of Computer Engg. KK Wagh Institute of Engg. Education & Research Centre, Nashik +, 3 Dept. of Computer Science & Engineering, Govt. College Of Engineering, Aurangabad, India +Dept. of Computer Engg. MET’s BKC College of Engg., Nashik +space +- IN +feature"
+b1ffd13e8f68401a603eea9806bc37e396a3c77d,Face Generation with Conditional Generative Adversarial Networks,"Face Generation with Conditional Generative Adversarial Networks +Xuwen Cao, Subramanya Rao Dulloor, Marcella Cindy Prasetio"
+b19f24ec92388513d1516d71292559417c776006,Causalgan: Learning Causal Implicit Gener-,"Under review as a conference paper at ICLR 2018 +CAUSALGAN: LEARNING CAUSAL IMPLICIT GENER- +ATIVE MODELS WITH ADVERSARIAL TRAINING +Anonymous authors +Paper under double-blind review"
b19e83eda4a602abc5a8ef57467c5f47f493848d,Heat Kernel Based Local Binary Pattern for Face Representation,"JOURNAL OF LATEX CLASS FILES Heat Kernel Based Local Binary Pattern for Face Representation Xi Li†, Weiming Hu†, Zhongfei Zhang‡, Hanzi Wang§"
+b18efa91e9893ae5fdfcaf880bae5c569fab4d18,Visual Scanning of Dynamic Affective Stimuli in Autism Spectrum Disorders,"Georgia State University +ScholarWorks Georgia State University +Psychology Dissertations +Department of Psychology +8-1-2012 +Visual Scanning of Dynamic Affective Stimuli in +Autism Spectrum Disorders +Susan M. McManus +Georgia State University +Follow this and additional works at: http://scholarworks.gsu.edu/psych_diss +Recommended Citation +McManus, Susan M., ""Visual Scanning of Dynamic Affective Stimuli in Autism Spectrum Disorders."" Dissertation, Georgia State +University, 2012. +http://scholarworks.gsu.edu/psych_diss/105 +This Dissertation is brought to you for free and open access by the Department of Psychology at ScholarWorks Georgia State University. It has been +ccepted for inclusion in Psychology Dissertations by an authorized administrator of ScholarWorks Georgia State University. For more information, +please contact"
+ddc8f480898a846c2a6ba0dddd7d733ce35f0e19,Dense Pose Transfer,"Dense Pose Transfer +Natalia Neverova1, Rıza Alp G¨uler2, and Iasonas Kokkinos1 +Facebook AI Research, Paris, France, {nneverova, +INRIA-CentraleSup´elec, Paris, France,"
dde5125baefa1141f1ed50479a3fd67c528a965f,Synthesizing Normalized Faces from Facial Identity Features,"Synthesizing Normalized Faces from Facial Identity Features Forrester Cole1 David Belanger1,2 Dilip Krishnan1 Aaron Sarna1 Inbar Mosseri1 William T. Freeman1,3 Google, Inc. 2University of Massachusetts Amherst 3MIT CSAIL {fcole, dbelanger, dilipkay, sarna, inbarm,"
+ddefb92908e6174cf48136ae139efbb4bd198896,Feature-wise Bias Amplification,"Under review as a conference paper at ICLR 2019 +FEATURE-WISE BIAS AMPLIFICATION +Anonymous authors +Paper under double-blind review"
dd8084b2878ca95d8f14bae73e1072922f0cc5da,"Model Distillation with Knowledge Transfer in Face Classification, Alignment and Verification","Model Distillation with Knowledge Transfer from Face Classification to Alignment and Verification Chong Wang∗, Xipeng Lan and Yangang Zhang Beijing Orion Star Technology Co., Ltd. Beijing, China {chongwang.nlpr, xipeng.lan,"
+dd7ed20a65d811dcf863f796d6dcbe873f57e7c4,Object Detection Via Structural Feature Selection and Shape Model,"Object Detection via Structural Feature +Selection and Shape Model +Huigang Zhang, Xiao Bai, Jun Zhou, Senior Member, IEEE, Jian Cheng and +Huijie Zhao"
ddf55fc9cf57dabf4eccbf9daab52108df5b69aa,Methodology and Performance Analysis of 3-D Facial Expression Recognition Using Statistical Shape Representation,"International Journal of Grid and Distributed Computing Vol. 4, No. 3, September, 2011 Methodology and Performance Analysis of 3-D Facial Expression @@ -12250,10 +42510,38 @@ ADSIP Research Centre, University of Central Lancashire {WQuan, BMatuszewski1, Charlie Frowd School of Psychology, University of Central Lancashire"
+dd72ed9a30e4d04703487df29a8762940bd79967,Image Retrieval based on LBP Transitions,"International Journal of Computer Applications (0975 – 8887) +Volume 101– No.16, September 2014 +Image Retrieval based on LBP Transitions +A. Srinivasa Rao +Assoc.Prof in CSE Dept. +MSSISTCE +Mylavaram, Vijayawada +V.Venkata Krishna +Professor in CSE Dept. +GIET, Rajahmundry +Andhra Pradesh, India +A.Obulesu +Asst.Prof in CSE Dept. +AGI (Autonomous), Hyderabad +Telanganastate, India"
ddea3c352f5041fb34433b635399711a90fde0e8,Facial Expression Classification using Visual Cues and Language,"Facial Expression Classification using Visual Cues and Language Abhishek Kar Advisor: Dr. Amitabha Mukerjee Department of Computer Science and Engineering, IIT Kanpur"
+dde24967490f58c8d10b2a00f12bf9103bd9b4a6,Evaluation of Shape Features for Efficient Classification Based on Rotational Invariant Using Texton Model,"Dr. P Chandra Sekhar Reddy, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.8, August- 2016, pg. 282-295 +Available Online at www.ijcsmc.com +International Journal of Computer Science and Mobile Computing +A Monthly Journal of Computer Science and Information Technology +ISSN 2320–088X +IMPACT FACTOR: 5.258 +IJCSMC, Vol. 5, Issue. 8, August 2016, pg.282 – 295 +EVALUATION OF SHAPE FEATURES FOR +EFFICIENT CLASSIFICATION BASED ON +ROTATIONAL INVARIANT USING TEXTON MODEL +Dr. P Chandra Sekhar Reddy +Professor, CSE Dept. +Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad"
ddbd24a73ba3d74028596f393bb07a6b87a469c0,Multi-region Two-Stream R-CNN for Action Detection,"Multi-region two-stream R-CNN for action detection Xiaojiang Peng, Cordelia Schmid @@ -12269,14 +42557,48 @@ University of Valencia. Computing Department, Burjassot. Valencia 46100, Spain, Universidad Cat´olica San Vicente M´artir de Valencia (UCV), Burjassot. Valencia. Spain"
+dda7bb490171a1d3364928fb8143bbe021146c5f,Local Shape Spectrum Analysis for 3D Facial Expression Recognition,"Local Shape Spectrum Analysis for 3D Facial Expression Recognition +Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain +Dmytro Derkach and Federico M. Sukno"
dd8d53e67668067fd290eb500d7dfab5b6f730dd,A Parameter-Free Framework for General Supervised Subspace Learning,"A Parameter-Free Framework for General Supervised Subspace Learning Shuicheng Yan, Member, IEEE, Jianzhuang Liu, Senior Member, IEEE, Xiaoou Tang, Senior Member, IEEE, nd Thomas S. Huang, Life Fellow, IEEE"
+ddcb77d09e4e9e2a948f9ffe7eaa5554dceb8ce3,Revisiting Cross Modal Retrieval,
+ddbfea5302fcb5cbc2ca4c498a592ddb063b9eff,L Ow Supervision Visual Learning through Cooperative Agents,"Low-supervision visual learning through cooperative agents +Ashish Bora +Abhishek Sinha"
ddbb6e0913ac127004be73e2d4097513a8f02d37,Face Detection Using Quantized Skin Color Regions Merging and Wavelet Packet Analysis,"IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 1, NO. 3, SEPTEMBER 1999 Face Detection Using Quantized Skin Color Regions Merging and Wavelet Packet Analysis Christophe Garcia and Georgios Tziritas, Member, IEEE"
+ddfde5d6f4e720aeb770a20e4197db3a0c279958,Learning Convolutional Text Representations for Visual Question Answering,"Learning Convolutional Text Representations for Visual Question Answering +Zhengyang Wang∗ +Shuiwang Ji†"
+dd54255065cf93895661c40073cdd031af7dd7e8,"GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose","GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose +Zhichao Yin and Jianping Shi +SenseTime Research +{yinzhichao,"
+dc53c4bb04e787a0d45dd761ba2101cc51c17b82,Multiple-Person Tracking by Detection,"http://excel.fit.vutbr.cz +Multiple-Person Tracking by Detection +Jakub Vojvoda*"
+dc3cd4e110b526cb59bd7527d540120c5fae77ce,Adversarially Tuned Scene Generation,"Adversarially Tuned Scene Generation +VSR Veeravasarapu1, Constantin Rothkopf2, Ramesh Visvanathan1 +Center for Cognition and Computation, Dept. of Computer Science, Goethe University, Frankfurt +Center for Cognitive Science & Dept. of Psychology, Technical University Darmstadt."
+dcf17cc3b4f8519a6789c1ea086689bcbc1d6f11,Unsupervised Learning of Deep Feature Representation for Clustering Egocentric Actions,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+dceaef5e7cbfc4d0150c2d765cc3df4349b8b2bd,Sentiment Analysis Using Social Multimedia,"Chapter 2 +Sentiment Analysis Using Social +Multimedia +Jianbo Yuan, Quanzeng You and Jiebo Luo"
+dcace6f0611b77177f4aff4bb650afab0a819575,3D Face Recognition,BMVC 2006 doi:10.5244/C.20.89
+dcd88a249b480d2e25326cdd11c5879fa31865cc,A Cross-Modal Distillation Network for Person Re-identification in RGB-Depth,"A Cross-Modal Distillation Network for Person +Re-identification in RGB-Depth +Frank Hafner +, Amran Bhuiyan, +, Julian F. P. Kooij +, Eric Granger +, Member, IEEE"
dc550f361ae82ec6e1a0cf67edf6a0138163382e,Emotion Based Music Player,"ISSN XXXX XXXX © 2018 IJESC Research Article Volume 8 Issue No.3 Vijay Chakole1, Aniket Choudhary2, Kalyani Trivedi3, Kshitija Bhoyar4, Ruchita Bodele5, Sayali Karmore6 @@ -12284,19 +42606,368 @@ Emotion Based Music Player Professor1, UG Student2, 3, 4, 5, 6 Department of Electronics Engineering K.D.K. College of Engineering Nagpur, India"
+dc6263270cd23a51d8fffdfd7e408250442b40f3,"SimpleElastix: A User-Friendly, Multi-lingual Library for Medical Image Registration","SimpleElastix: A user-friendly, multi-lingual library for medical image +registration +Kasper Marstal1, Floris Berendsen2, Marius Staring2 and Stefan Klein1 +Biomedical Imaging Group Rotterdam (BIGR), Department of Radiology & Medical Informatics, +Erasmus Medical Center, PO Box 2040, Rotterdam, 3000 CA, the Netherlands, +Division of Image Processing (LKEB), Department of Radiology, Leiden University Medical Center, +PO Box 9600, 2300 RC Leiden, the Netherlands,"
+dc6c47d15ffc0fd59e51ed03556c3566afe5710b,Robust Object Recognition Through Symbiotic Deep Learning In Mobile Robots *,"CONFIDENTIAL. Limited circulation. For review only. +Preprint submitted to 2018 IEEE/RSJ International Conference +on Intelligent Robots and Systems. Received March 1, 2018."
dcb44fc19c1949b1eda9abe998935d567498467d,Ordinal Zero-Shot Learning,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) labelunseen labelFigure1:Supervisionintensityfordifferentlabels.Greenrepre-sentsseenlabelsandredrepresentsunseenlabels.Thegroundtruthlabelofthisinstanceis“Good”,soithasthestrongestsupervisionintensity.Although“Common”isanunseenlabel,itstillhascertainsupervisioninformationbecauseitiscloselyrelatedto“Good”.classifier;[ZhangandSaligrama,2016]learnsajointlatentspaceusingstructuredlearning.Thedifficultyinobtainingthesideinformationorusingothertechniquestoprocessthesideinformationarethemostseriousissuesformanyexistingzero-shotlearningmethods.Fortheattribute-basedmethods,humanexpertsareneededtolabelattributesandthisisverytime-consumingandnoteasytoobtainthediscriminativecategory-levelattributes.Somemethodsdiscoverattributesinteractively[ParikhandGrau-man,2011][Bransonetal.,2010],butthisalsorequiresla-borioushumanparticipation.Althoughmanyalgorithmscandiscoverattribute-relatedconceptsontheWeb[Rohrbachetal.,2010][Bergetal.,2010],theycanalsobebiasedorlackinformationthatiscriticaltoaparticulartask[ParikhandGrauman,2011].Forthetextcorpora-basedmethods,theyfirstrequirealargelanguagecorpora,suchasWikipedia,andthenneedtolearnwordrepresentation[Socheretal.,2013]orusestandardNaturalLanguageProcessing(NLP)techniquestoproduceclassdescriptions[Elhoseinyetal.,2013].Itishardtoguaranteethecorrectnessofsuchclassdescriptionsforzero-shotlearning.Conclusively,althoughsideinforma-tionishelpfulforzero-shotlearning,ithasmanydisadvan-tages.Generatingthesesideinformationisverytediousandsometimeswecannotknowwhichsideinformationistrulywanted.IfwedependonhumanlabororNLPtechniques,noisysideinformationwillbecomealmostinevitableandin-fluencethefinalperformance.Toavoidtheseproblems,itisimportanttosolvezero-shotlearninginwhateverpossiblecasesthathavesomepropertieswecanutilizetoavoidusingsideinformation."
+dcce157aa2e5db081b36fd16544a038becb408ab,Fast and Accurate Pedestrian Detection in a Truck's Blind Spot Camera,"Fast and Accurate Pedestrian Detection +in a Truck’s Blind Spot Camera +Kristof Van Beeck1,2(B) and Toon Goedem´e1,2 +EAVISE, KU Leuven - Campus De Nayer, J. De Nayerlaan 5, 2860 +ESAT/PSI - VISICS, KU Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium +Sint-katelijne-waver, Belgium"
+dc452f3e531c4057c930f0538d5652ad9034d1aa,Quality metrics for practical face recognition,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-0-9 ©2012 ICPR"
+dc7a4d5ba20ca07d29c360b26e1e72afae9a77be,The ApolloScape Open Dataset for Autonomous Driving and its Application,"The ApolloScape Open Dataset for Autonomous +Driving and its Application +Xinyu Huang*, Peng Wang*, Xinjing Cheng, Dingfu Zhou, Qichuan Geng, Ruigang Yang"
+dc6d518585c18504b2e69223c062cdd691c79bbd,Domain Adaptation Through Synthesis for Unsupervised Person Re-identification,
+dc771cd7780538953811a5b6ae0e901ca68cce3d,Multiple People Tracking Using Hierarchical Deep Tracklet Re-identification,"Multiple People Tracking Using Hierarchical Deep Tracklet Re-identification +Maryam Babaee∗ +Ali Athar∗ +Gerhard Rigoll +Institute for Human-Machine Communication, Technical University of Munich +Arcisstrasse 21, Munich, Germany"
+dcba9cd587be2ed5437370e12e3591bdde86dc3c,Template for Regular Entry,"TEMPLATE FOR REGULAR ENTRY +(ENCYCLOPEDIA OF DATABASE SYSTEMS) +TITLE OF ENTRY +Automatic Image Annotation +BYLINE +Nicolas Hervé and Nozha Boujemaa, INRIA Paris-Rocquencourt, IMEDIA project, France. +http://www-rocq.inria.fr/imedia/ +SYNONYMS +Multimedia Content Enrichment, Image Classification, Object Detection and Recognition, +Auto-annotation +DEFINITION +The widespread search engines, in the professional as well as the personal context, used to work +on the basis of textual information associated or extracted from indexed documents. Nowadays, +most of the exchanged or stored documents have multimedia content. To reduce the technological +gap so that these engines still can work on multimedia content, it is very convenient developing +methods capable to generate automatically textual annotations and metadata. These methods will +then allow to enrich the upcoming new content or to post-annotate the existing content with +dditional information extracted automatically if ever this existing content is partly or not annotated. +A broad diversity in the typology of manual annotation is usually found in image databases. Part of +them is representing contextual information. The author, date, place or technical shooting"
dc2e805d0038f9d1b3d1bc79192f1d90f6091ecb,Face Recognition and Facial Attribute Analysis from Unconstrained Visual Data,
+dc23beb1e5c7402b1a9d5a7c854e62a253d0815e,Microscopic crowd simulation : evaluation and development of algorithms. (Simulation microscopique de foules : évaluation et développement d'algorithmes),"Microscopic crowd simulation : evaluation and +development of algorithms +David Wolinski +To cite this version: +David Wolinski. Microscopic crowd simulation : evaluation and development of algorithms. Data +Structures and Algorithms [cs.DS]. Université Rennes 1, 2016. English. <NNT : 2016REN1S036>. +<tel-01420105> +HAL Id: tel-01420105 +https://tel.archives-ouvertes.fr/tel-01420105 +Submitted on 20 Dec 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+dcc064b8bf7744801ae7dfe4cbfd11b7e5a5b673,Men's physical strength moderates conceptualizations of prospective foes in two disparate societies.,"Hum Nat +DOI 10.1007/s12110-014-9205-4 +Men’s Physical Strength Moderates Conceptualizations +of Prospective Foes in Two Disparate Societies +Daniel M. T. Fessler & Colin Holbrook & +Matthew M. Gervais +# Springer Science+Business Media New York 2014"
+dc041f307d467918ba684d3c425fb23016f3b28e,A Survey of 3D Face Recognition Methods,"A Survey of 3D Face Recognition Methods +Alize Scheenstra1, Arnout Ruifrok2, and Remco C. Veltkamp1 +Utrecht University, Institute of Information and Computing Sciences, +Padualaan 14, 3584 CH Utrecht, The Netherlands +Netherlands Forensic Institute, +Laan van Ypenburg 6, 2497 GB Den Haag, The Netherlands,"
+dc090aea412cef17c7a68ec84c34797806feab24,A mixture of gated experts optimized using simulated annealing for 3D face recognition,"978-1-4577-1302-6/11/$26.00 ©2011 IEEE +D FACE RECOGNITION +. INTRODUCTION"
+dc9f29118e38602c03bb2866f8b12ce478aad52c,Large scale evolution of convolutional neural networks using volunteer computing,"Large Scale Evolution of Convolutional Neural +Networks Using Volunteer Computing +Travis Desell∗ +March 17, 2017"
+dc22de0ed56958013234cf7128952390fb47345a,Towards dense object tracking in a 2D honeybee hive,"Towards dense object tracking in a 2D honeybee hive +Katarzyna Bozek a, Laetitia Hebert a, Alexander S Mikheyev a & Greg J Stephens a,b∗ +Okinawa Institute of Science and Technology, 1919-1 Tancha Onna-son, Kunigami-gun, Okinawa 904-0495, Japan +Department of Physics and Astronomy, VU University Amsterdam, 1081 HV Amsterdam, The Netherlands +From human crowds to cells in tissue, the detection and efficient tracking of multiple objects +in dense configurations is an important and unsolved problem. In the past, limitations of image +nalysis have restricted studies of dense groups to tracking a single or subset of marked individ- +uals, or to coarse-grained group-level dynamics, all of which yield incomplete information. Here, +we combine convolutional neural networks (CNNs) with the model environment of a honeybee hive +to automatically recognize all individuals in a dense group from raw image data. We create new, +dapted individual labeling and use the segmentation architecture U-Net with a loss function depen- +dent on both object identity and orientation. We additionally exploit temporal regularities of the +video recording in a recurrent manner and achieve near human-level performance while reducing +the network size by 94% compared to the original U-Net architecture. Given our novel applica- +tion of CNNs, we generate extensive problem-specific image data in which labeled examples are +produced through a custom interface with Amazon Mechanical Turk. This dataset contains over +75,000 labeled bee instances across 720 video frames at 2 FPS, representing an extensive resource +location error of ∼ 7% of a typical body dimension, and orientation error of 12◦, approximating the +variability of human raters. Our results provide an important step towards efficient image-based +dense object tracking by allowing for the accurate determination of object location and orientation"
+dca246cd06666a331b0203cb09a6ef51727bfdcc,The micro-foundations of email communication networks,"The Micro-Foundations of Email +Communication Networks +Ofer Engel +London School of Economics and Political Science +Department of Management +Information Systems and Innovation Group +Thesis submitted for the degree of +PhilosophiæDoctor (PhD) +013 June"
dc974c31201b6da32f48ef81ae5a9042512705fe,Am I Done? Predicting Action Progress in Videos,"Am I done? Predicting Action Progress in Video Federico Becattini1, Tiberio Uricchio1, Lorenzo Seidenari1, Alberto Del Bimbo1, and Lamberto Ballan2 Media Integration and Communication Center, Univ. of Florence, Italy Department of Mathematics “Tullio Levi-Civita”, Univ. of Padova, Italy"
+b66418ecc37ea0c79da5425e9ceac939ca9075ae,Efficient Gait-based Gender Classification through Feature Selection,"EFFICIENT GAIT-BASED GENDER CLASSIFICATION +THROUGH FEATURE SELECTION∗ +Ra´ul Mart´ın-F´elez, Javier Ortells, Ram´on A. Mollineda and J. Salvador S´anchez +Institute of New Imaging Technologies and Dept. Llenguatges i Sistemes Inform`atics +Universitat Jaume I. Av. Sos Baynat s/n, 12071, Castell´o de la Plana, Spain +{martinr, jortells, mollined, +Keywords: +Gender classification, Gait, ANOVA, Feature selection."
+b6ecc8d34ebc8895378abe2b8f35e3a0691f5d26,Annotation Methodologies for Vision and Language Dataset Creation,"Annotation Methodologies for Vision and Language Dataset Creation +Gitit Kehat +Computer Science Department +Brandeis University +Waltham, MA. 02453 USA +James Pustejovsky +Computer Science Department +Brandeis University +Waltham, MA. 02453 USA"
+b691463de5e30e7efd18b9d02cbf83c805834fe7,Evaluation of Penalty Functions for Semi-global Matching Cost Aggregation,"EVALUATION OF PENALTY FUNCTIONS FOR SEMI-GLOBAL MATCHING +COST AGGREGATION +Christian Banz, Peter Pirsch, and Holger Blume +Institute of Microelectronic Systems +Leibniz Universität Hannover, Hannover, Germany +KEY WORDS: Stereoscopic, Quality, Matching, Vision, Reconstruction, Camera, Disparity Estimation, Semi-Global Matching"
+b6b1b0632eb9d4ab1427278f5e5c46f97753c73d,Generalização cartográfica automatizada para um banco de dados cadastral,"UNIVERSIDADE FEDERAL DE SANTA CATARINA -UFSC +DEPARTAMENTO DE ENGENHARIA CIVIL +PROGRAMA DE PÓS-GRADUAÇÃO EM +ENGENHARIA CIVIL - PPGEC +AREA DE CONCENTRAÇÃO: CADASTRO TÉCNICO E +GESTÃO TERRITORIAL +GENERALIZAÇÃO CARTOGRÁFICA AUTOMATIZADA +PARA UM BANCO DE DADOS CADASTRAL +Tese submetida à Universidade Federal de +Santa Catarina como requisito exigido pelo +Programa de Pós-Graduação em Engenharia +Civil - PPGEC, para a obtenção do Título de +DOUTOR em Engenharia Civil. +Mariane Alves Dal Santo +Orientador: Prof. Dr. Carlos Loch +Florianópolis, dezembro de 2007"
+b63411ed70ba315b87a716e1809faea48e70a982,"A Survey on Object Detect , Track and Identify Using Video Surveillance","IOSR Journal of Engineering (IOSRJEN) +e-ISSN: 2250-3021, p-ISSN: 2278-8719, www.iosrjen.org +Volume 2, Issue 10 (October 2012), PP 71-76 +A Survey on Object Detect, Track and Identify Using Video +Surveillance +Chandrashekhar D.Badgujar1, Dipali P.Sapkal2 +1,2(Computer Science and Engineering G.H.R.E.M, Jalgoan)"
+b651814360e3899cd9206bfd23621aca6551e69c,Improving Feature Level Likelihoods using Cloud Features,"IMPROVING FEATURE LEVEL LIKELIHOODS USING CLOUD +FEATURES +Heydar Maboudi Afkham1, Stefan Carlsson1, Josephine Sullivan1 +Computer Vision and Active Perception Lab., KTH, Stockholm, Sweden +Keywords: +Feature inference, Latent models, Clustering"
+b69badabc3fddc9710faa44c530473397303b0b9,Unsupervised Image-to-Image Translation Networks,"Unsupervised Image-to-Image Translation Networks +Ming-Yu Liu, Thomas Breuel, +Jan Kautz +NVIDIA"
+b6fd905efd5da32bd32047896074a821477cb564,An Human Perceptive Model for Person Re-identification,"An Human Perceptive Model for Person Re-identification +Angelo Cardellicchio1, Tiziana D’Orazio1, Tiziano Politi2 and Vito Ren`o1 +National Research Council, Institute of Intelligent Systems for Automation, Bari, Italia +Politecnico di Bari, Bari, Italia +Keywords: +Color Analysis, Feature Extraction, Histograms."
+b62486261104d5136aea782ee8596425b5f228da,Modelling perceptions of criminality and remorse from faces using a data-driven computational approach.,"Cognition and Emotion +ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20 +Modelling perceptions of criminality and remorse +from faces using a data-driven computational +pproach +Friederike Funk, Mirella Walker & Alexander Todorov +To cite this article: Friederike Funk, Mirella Walker & Alexander Todorov (2017) Modelling +perceptions of criminality and remorse from faces using a data-driven computational approach, +Cognition and Emotion, 31:7, 1431-1443, DOI: 10.1080/02699931.2016.1227305 +To link to this article: http://dx.doi.org/10.1080/02699931.2016.1227305 +View supplementary material +Published online: 07 Sep 2016. +Submit your article to this journal +Article views: 235 +View related articles +View Crossmark data +Citing articles: 1 View citing articles +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pcem20 +Download by: [Princeton University]"
+b63041d05b78a66724fbcb2803508999bf885d6b,Deep Sets,"Deep Sets +Manzil Zaheer 1 2 Satwik Kottur 2 Siamak Ravanbhakhsh 2 Barnabas Poczos 2 Ruslan Ssalakhutdinov 2 +Alexander Smola 1 2"
+b61b4eb2e28b9cf35578498e1bbcc35ec0a07651,Backtracking ScSPM Image Classifier for Weakly Supervised Top-Down Saliency,"Backtracking ScSPM Image Classifier for Weakly Supervised Top-down Saliency +Hisham Cholakkal +Jubin Johnson +Deepu Rajan +Multimedia Lab, School of Computer Science and Engineering +Nanyang Technological University Singapore +{hisham002, jubin001,"
+b6aa94b81b2165e492cc2900e05dd997619bfe7a,Automatic temporal segment detection via bilateral long short-term memory recurrent neural networks,"Automatic temporal segment +detection via bilateral long short- +term memory recurrent neural +networks +Bo Sun +Siming Cao +Jun He +Lejun Yu +Liandong Li +Bo Sun, Siming Cao, Jun He, Lejun Yu, Liandong Li, “Automatic temporal segment +detection via bilateral long short-term memory recurrent neural networks,” J. +Electron. Imaging 26(2), 020501 (2017), doi: 10.1117/1.JEI.26.2.020501. +Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 03/03/2017 Terms of Use: http://spiedigitallibrary.org/ss/termsofuse.aspx"
+b632d47eb7421a3d622b0f1ceb009e4415ccc84d,Deep Perceptual Mapping for Cross-Modal Face Recognition,"(will be inserted by the editor) +Deep Perceptual Mapping for Cross-Modal Face +Recognition +M. Saquib Sarfraz · Rainer Stiefelhagen +the date of receipt and acceptance should be inserted later"
+b6ef46621d8660eb53836202fa58f04fa20adfd7,Disgust and Anger Relate to Different Aggressive Responses to Moral Violations,"692000 PSSXXX10.1177/0956797617692000Molho et al.Moral Emotions and Aggressive Tactics +research-article2017 +Research Article +Disgust and Anger Relate to Different +Aggressive Responses to Moral Violations +Catherine Molho1, Joshua M. Tybur1, Ezgi Güler2, +Daniel Balliet1, and Wilhelm Hofmann3 +Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam; +Department of Political and Social Sciences, European University Institute; and 3Social Cognition +Center Cologne, University of Cologne +Psychological Science +017, Vol. 28(5) 609 –619 +© The Author(s) 2017 +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/0956797617692000 +https://doi.org/10.1177/0956797617692000 +www.psychologicalscience.org/PS"
+b69f7660985be23abda72990cb1f367778960275,Object Recognition based on Principal Component Analysis to Image Patches,"International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June-2013 1096 +ISSN 2229-5518 +Object Recognition based on Principal +Component Analysis to Image Patches +R.Ahilapriyadharsini +Mepco Schlenk Engineering +College, +Sivakasi, India +S.Arivazhagan +M.Gowthami +Mepco Schlenk Engineering +Renganayagi Varatharaj College of +College, +Sivakasi, India +Engineering, Salvarpatti, +Sivakasi, India."
b613b30a7cbe76700855479a8d25164fa7b6b9f1,Identifying User-Specific Facial Affects from Spontaneous Expressions with Minimal Annotation,"Identifying User-Specific Facial Affects from Spontaneous Expressions with Minimal Annotation Michael Xuelin Huang, Grace Ngai, Kien A. Hua, Fellow, IEEE, Stephen C.F. Chan, Member, IEEE nd Hong Va Leong, Member, IEEE Computer Society"
+b640c36acc0e748553f78280fce7a840965c5cec,Text Detection from Natural Image using MSER and BOW,"International Journal of Emerging Engineering Research and Technology +Volume 3, Issue 11, November 2015, PP 152-156 +ISSN 2349-4395 (Print) & ISSN 2349-4409 (Online) +Text Detection from Natural Image using MSER and BOW +K.Sowndarya Lahari, 2M.Haritha, 3P.Prasanna Murali Krishna +(M.Tech), DECS, DR.Sgit, Markapur, India. +Associate Professor, Department of ECE, DR.Sgit, Markapur, India. +.3H.O.D Department of ECE, DR.Sgit, Markapur, India."
+b66a93884f80a243f50da97e33211693a317dc45,Deep Learning for Generic Object Detection: A Survey,"Deep Learning for Generic Object Detection: A Survey +Li Liu 1,2 · Wanli Ouyang 3 · Xiaogang Wang 4 · +Paul Fieguth 5 · Jie Chen 2 · Xinwang Liu 1 · Matti Pietik¨ainen 2 +Received: 12 September 2018"
b6f682648418422e992e3ef78a6965773550d36b,"CBMM Memo No . 061 February 8 , 2017 Full interpretation of minimal images","February 8, 2017"
+b610e52b0a8fa11af3d01944c0383f015cade9c0,Multimodal 2 D - 3 D Face Recognition,"International Journal of Future Computer and Communication, Vol. 2, No. 6, December 2013 +Multimodal 2D-3D Face Recognition +Gawed M. Nagi, Rahmita Rahmat, Muhamad Taufik, and Fatimah Khalid +technology"
+b67e2ccd0f05df5358464b9b38da3bcb9feda1ab,FaceID@home: cycle-sharing for facial recognition,"ycle-sharing for facial recognition +FaceID-BOINC: adapta¸c˜ao de algoritmos de reconhecimento facial (eigenfaces) para execu¸c˜ao +em m´aquinas multicore e GPUs integrado num cliente para plataforma BOINC +Nuno Miguel Abreu Teixeira - 55397 +Instituto Superior T´ecnico"
+b64cc1f0772e9620ecf916019de85b7adb357b7a,Fast Face-Swap Using Convolutional Neural Networks,"Fast Face-swap Using Convolutional Neural Networks +Iryna Korshunova1,2 +Wenzhe Shi1 +{iryna.korshunova, +Twitter +Joni Dambre2 +Lucas Theis1 +IDLab, Ghent University +{wshi,"
+b6aaaf6290ba0ca13be61d122907617f1ea86315,Embedded Face Recognition Using Cascaded Structures PROEFSCHRIFT,"Embedded Face Recognition +Using Cascaded Structures +PROEFSCHRIFT +ter verkrijging van de graad van doctor aan de +Technische Universiteit Eindhoven, op gezag van de +Rector Magnificus, prof.dr.ir. C.J. van Duijn, voor een +ommissie aangewezen door het College voor +Promoties in het openbaar te verdedigen op +dinsdag 3 oktober 2006 om 16.00 uur +Fei Zuo +geboren te Xi’an, China"
+b6dc1cd3cabdfea7363d41773a315a0d241dc836,Local Context Priors for Object Proposal Generation,"Local Context Priors for Object Proposal +Generation +Marko Ristin1, Juergen Gall2, and Luc Van Gool1,3 +ETH Zurich +MPI for Intelligent Systems +KU Leuven"
+b648d73edd1a533decd22eec2e7722b96746ceae,weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming,"weedNet: Dense Semantic Weed Classification Using Multispectral +Images and MAV for Smart Farming +Inkyu Sa1, Zetao Chen2, Marija Popovi´c1, Raghav Khanna1, Frank Liebisch3, Juan Nieto1, Roland Siegwart1"
+b67e0ae9d64ec06b3e1c25c7f7e8b86020612d33,Vocabulary-informed Visual Feature Augmen-,"Under review as a conference paper at ICLR 2018 +VOCABULARY-INFORMED VISUAL FEATURE AUGMEN- +TATION FOR ONE-SHOT LEARNING"
+a93ecf7b9780989c709714dde0f93f4d81eea640,Unconstrained Face Recognition Using SVM Across Blurred And Illuminated Images With Pose Variation,"International Journal of Innovative Research in Computer and Communication Engineering +(An ISO 3297: 2007 Certified Organization) +Vol.2, Special Issue 1, March 2014 +Proceedings of International Conference On Global Innovations In Computing Technology (ICGICT’14) +Department of CSE, JayShriram Group of Institutions, Tirupur, Tamilnadu, India on 6th & 7th March 2014 +Organized by +Unconstrained Face Recognition Using SVM +Across Blurred And Illuminated Images With Pose +Variation +Nadeena M1, S.Sangeetha, M.E, 2 +ISSN(Online): 2320-9801 +ISSN (Print): 2320-9798 +II M.E CSE, Dhanalakshmi Srinivasan College of Engineering, Coimbatore, India1 +Assistant Professor, Dhanalakshmi Srinivasan College of Engineering, Coimbatore, India 2"
+a9d3547ab16a9cc936bf5991bf8fb475eadce931,Face Recognition using DWT with HMM,"Eng. & Tech. Journal, Vol.30, No.1, 2012 +Face Recognition using DWT with HMM +Dr. Eyad I. Abbas +Department of Electrical Engineering, University of Technology/ Baghdad +Hameed R. Farhan +Department of Electrical Engineering, Engineering College, University of Kerbala/ Kerbala +Received on: 19/6/2011 & Accepted on: 3/11/2011"
+a9e28863c7fb963b40a379c5a4e0da00eb031933,A Corpus of Natural Language for Visual Reasoning,"Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 217–223 +Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 217–223 +Vancouver, Canada, July 30 - August 4, 2017. c(cid:13)2017 Association for Computational Linguistics +Vancouver, Canada, July 30 - August 4, 2017. c(cid:13)2017 Association for Computational Linguistics +https://doi.org/10.18653/v1/P17-2034 +https://doi.org/10.18653/v1/P17-2034"
+a91caf771905ddff8cb271f04e7ede1a8b6d529b,Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training,"Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via +Adversarial Training +Department of Biomedical Engineering +Department of Computer Science +Faisal Mahmood1 Richard Chen2 Nicholas J. Durr1 +Johns Hopkins University (JHU) +{faisalm, rchen40,"
a9791544baa14520379d47afd02e2e7353df87e5,The Need for Careful Data Collection for Pattern Recognition in Digital Pathology,"Technical Note The Need for Careful Data Collection for Pattern Recognition in Digital Pathology @@ -12305,6 +42976,11 @@ Department of Electrical Engineering and Computer Science, Montefiore Institute, Received: 08 December 2016 Accepted: 15 March 2017 Published: 10 April 2017"
+a9d6d62f4f3f12ed565e5d75f8c4b7a202a3d809,Action and intention recognition of pedestrians in urban traffic,"Action and intention recognition of pedestrians in urban traffic +Dimitrios Varytimidis1, Fernando Alonso-Fernandez1, Boris Duran2 and Cristofer Englund1,2∗"
+a97f3d2313affd35c889c57f2ebe21e7ba2b5bbb,Real-Time Semantic Mapping for Autonomous Off-Road Navigation,"Real-time Semantic Mapping for Autonomous +Off-Road Navigation +Daniel Maturana, Po-Wei Chou, Masashi Uenoyama and Sebastian Scherer"
a9eb6e436cfcbded5a9f4b82f6b914c7f390adbd,A Model for Facial Emotion Inference Based on Planar Dynamic Emotional Surfaces,"(IJARAI) International Journal of Advanced Research in Artificial Intelligence, Vol. 5, No.6, 2016 A Model for Facial Emotion Inference Based on @@ -12325,6 +43001,25 @@ S˜ao Paulo, Brazil S˜ao Paulo, Brazil S˜ao Paulo, Brazil S˜ao Paulo, Brazil"
+a9ebeca46445b8af728118b05e56d95d4985000c,Restricted Isometry Property of Subspace Projection Matrix Under Random Compression,"Restricted Isometry Property of Subspace Projection +Matrix Under Random Compression +Xinyue Shen, Student Member, IEEE, and Yuantao Gu, Member, IEEE"
+a91fd02ed2231ead51078e3e1f055d8be7828d02,The Robust Manifold Defense: Adversarial Training using Generative Models,"The Robust Manifold Defense: +Adversarial Training using Generative Models +Andrew Ilyas +Ajil Jalal +Eirini Asteri +MIT EECS +UT Austin +UT Austin +Constantinos Daskalakis +Alexandros G. Dimakis +MIT EECS +UT Austin +December 27, 2017 +Problems worthy of attack, +prove their worth by fighting back."
+a9ad8f6c6bf110485921b17f9790241b1548487c,Automatic Skin Tone Extraction for Visagism Applications,
a955033ca6716bf9957b362b77092592461664b4,Video Based Face Recognition Using Artificial Neural Network,"ISSN(Online): 2320-9801 ISSN (Print): 2320-9798 International Journal of Innovative Research in Computer @@ -12341,6 +43036,13 @@ JalilMazloum, Ali Jalali and Javad Amiryan Electrical and Computer Engineering Department ShahidBeheshti University Tehran, Iran"
+a90226c41b79f8b06007609f39f82757073641e2,Β-vae: Learning Basic Visual Concepts with a Constrained Variational Framework,"Under review as a conference paper at ICLR 2017 +β-VAE: LEARNING BASIC VISUAL CONCEPTS WITH A +CONSTRAINED VARIATIONAL FRAMEWORK +Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, +Matthew Botvinick, Shakir Mohamed, Alexander Lerchner +Google DeepMind +{irinah,lmatthey,arkap,cpburgess,glorotx,"
a98316980b126f90514f33214dde51813693fe0d,Collaborations on YouTube: From Unsupervised Detection to the Impact on Video and Channel Popularity,"Collaborations on YouTube: From Unsupervised Detection to the Impact on Video and Channel Popularity Christian Koch, Moritz Lode, Denny Stohr, Amr Rizk, Ralf Steinmetz @@ -12348,6 +43050,27 @@ Multimedia Communications Lab (KOM), Technische Universität Darmstadt, Germany E-Mail: {Christian.Koch | Denny.Stohr | Amr.Rizk |"
a93781e6db8c03668f277676d901905ef44ae49f,Recent Data Sets on Object Manipulation: A Survey.,"Recent Datasets on Object Manipulation: A Survey Yongqiang Huang, Matteo Bianchi, Minas Liarokapis and Yu Sun"
+a969efee78149357ec109c1de2238a0cc670858a,Automatic 2.5-D Facial Landmarking and Emotion Annotation for Social Interaction Assistance,"Automatic 2.5-D Facial Landmarking and Emotion +Annotation for Social Interaction Assistance +Xi Zhao, Member, IEEE, Jianhua Zou, Member, IEEE, Huibin Li, Student Member, IEEE, +Emmanuel Dellandréa, Member, IEEE, Ioannis A. Kakadiaris, Senior Member, IEEE, +nd Liming Chen, Senior Member, IEEE"
+a99cf14afb556187233f772fa9bf561d7cf0c088,A Survey on Sclera Vein Recognition Techniques,"INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN COMPUTER SCIENCE AND APPLICATIONS +ISSN 2321-872X ONLINE ISSN 2321-8932 PRINT +VOLUME 2, ISSUE 12, DECEMBER 2014. +A SURVEY ON SCLERA VEIN RECOGNITION TECHNIQUES +Dr.S.BABU 1 S.SUBA 2 +Associate Professor / CSE, IFET College of Engineering, Viluppuram, Tamilnadu, India +PG Scholar, IFET College of Engineering, Viluppuram, Tamilnadu, India"
+a9d2c96cead937e53e614abb9fd051574a55c77a,Ensembling Visual Explanations for,"In Proceedings of the NIPS 2017 workshop on Visually-Grounded Interaction and +Language (ViGIL), December 2017."
+a94c3091be2090df6144bd121e41e7dfa96ec0e9,Enhanced visual functioning in autism: an ALE meta-analysis.,"Enhanced Visual Functioning in Autism: +An ALE Meta-Analysis +Fabienne Samson,1 Laurent Mottron,1 Isabelle Soulie` res,1,2 +nd Thomas A. Zeffiro2 +Centre d’Excellence en Troubles Envahissants du De´veloppement de l’Universite´ de Montre´al +Neural Systems Group, Massachusetts General Hospital, Boston, Massachusetts +(CETEDUM), Montre´al, QC, Canada"
a9adb6dcccab2d45828e11a6f152530ba8066de6,Aydınlanma Alt-uzaylarına dayalı Gürbüz Yüz Tanıma Illumination Subspaces based Robust Face Recognition,"Aydınlanma Alt-uzaylarına dayalı Gürbüz Yüz Tanıma Illumination Subspaces based Robust Face Recognition D. Kern, H.K. Ekenel, R. Stiefelhagen @@ -12383,8 +43106,158 @@ a949b8700ca6ba96ee40f75dfee1410c5bbdb3db,Instance-Weighted Transfer Learning of Daniel Haase, Erik Rodner, and Joachim Denzler Computer Vision Group, Friedrich Schiller University of Jena, Germany Ernst-Abbe-Platz 2-4, 07743 Jena, Germany"
+a94aac3caccebd82413dd05707ef8bf525dc46b9,Evaluation of the UR3D algorithm using the FRGC v2 data set,"Evaluation of the UR3D algorithm using the FRGC v2 data set +G. Passalis, I.A. Kakadiaris, T. Theoharis, G. Toderici and N. Murtuza +Visual Computing Lab, Dept. of Computer Science, Univ. of Houston, Houston, TX 77204, USA"
a92b5234b8b73e06709dd48ec5f0ec357c1aabed,Disjoint Multi-task Learning Between Heterogeneous Human-Centric Tasks,
+a9453721f35f364e176a5aaa7bdb622f72fbcaec,Learning Articulated Motion Models from Visual and Lingual Signals,"Learning Articulated Motion Models from Visual and Lingual Signals +Zhengyang Wu +Georgia Tech +Atlanta, GA 30332 +Mohit Bansal +TTI-Chicago +Chicago, IL 60637 +Matthew R. Walter +TTI-Chicago +Chicago, IL 60637"
+a94b832facb57ea37b18927b13d2dd4c5fa3a9ea,Domain transfer convolutional attribute embedding,"April 3, 2018 +Journal of Experimental & Theoretical Artificial Intelligence +To appear in the Journal of Experimental & Theoretical Artificial Intelligence +Vol. 00, No. 00, Month 20XX, 1–23 +Domain transfer convolutional attribute embedding +Fang Sua ∗ , Jing-Yan Wangb +School of Economics and Management, Shaanxi University of Science & Technology, Xi’an, +New York University Abu Dhabi, Abu Dhabi, United Arab Emirates +ShaanXi Province, P.R.C, 710021 +(v5.0 released July 2015) +In this paper, we study the problem of transfer learning with the attribute data. In the trans- +fer learning problem, we want to leverage the data of the auxiliary and the target domains +to build an effective model for the classification problem in the target domain. Meanwhile, +the attributes are naturally stable cross different domains. This strongly motives us to learn +effective domain transfer attribute representations. To this end, we proposed to embed the +ttributes of the data to a common space by using the powerful convolutional neural net- +work (CNN) model. The convolutional representations of the data points are mapped to the +orresponding attributes so that they can be effective embedding of the attributes. We also +represent the data of different domains by a domain-independent CNN, ant a domain-specific +CNN, and combine their outputs with the attribute embedding to build the classification"
+a9f5acdcf1fbc9563aaad943cbe1c195b796aa62,Learning Fashion By Simulated Human Supervision,"Learning Fashion By Simulated Human Supervision +Eli Alshan Sharon Alpert Assaf Neuberger Nathaniel Bubis Eduard Oks +{alshan, alperts, neuberg, bubis, +Amazon Lab126"
+a91d0ebc1255d6de1c4588767b3b5e1fc630e56f,eTRIMS Scene Interpretation Datasets,"Universit¨at Hamburg +Technical Report FBI-HH-M-345/10 +eTRIMS Scene Interpretation +Datasets +Johannes Hartz +Patrick Koopmann +Arne Kreutzmann +Kasim Terzi´c +{hartz | koopmann | +informatik.uni-hamburg.de +November 15, 2010"
+a9978df0b4df4d7b04bc4e9464c67f9ff7c31d3d,From Traditional to Interactive Playspaces,"FROM TRADITIONAL TO +FROM TRADITIONAL TO +INTERACTIVE PLAYSPACES +INTERACTIVE PLAYSPACES +Automatic Analysis of Player Behavior in the +Interactive Tag Playground +CTIT Ph.D. Thesis Series No. 16-386 +ISSN: 1381-3617 +Alejandro Moreno"
+a9e53a7533c9c743b57b6668c11be0c73525f188,Enhanced Feature Sets for Face Recognition with varying Lighting Conditions and Noise,"Enhanced Feature Sets for Face Recognition with varying Lighting Conditions and Noise ISSN 2278 – 3806 +Enhanced Feature Sets for Face Recognition with +varying Lighting Conditions and Noise +Final ME (CSE), 2Head of Department of Computer Science and Engineering +S.Vishnupriya1 Dr.k.Lakshmi2 +Periyar Maniammai University, Thanjavur, Tamilnadu, India."
+a975f1aea5dbb748955da0e17eef8d2270a49f25,Object Recognition,"OBJECT RECOGNITION +Object recognition is a subproblem of the more general +problem of perception, and can be defined as follows. Given +scene consisting of one or more objects, can we identify +nd localize those objects that are sufficiently visible to +the sensory system? It is generally assumed that a de- +scription of each object to be recognized is available to the +omputer and can be used to facilitate the task of iden- +tification and localization. These descriptions can either +e model-based or appearance-based, or a combination of +oth. Model-based object representation is based on geo- +metric features, whereas appearance-based representation +uses a large set of images for training but does not require +ny insight into the geometric structure of the objects. Ob- +ject recognition is a key component of many intelligent vi- +sion systems, such as those used in hand-eye coordination +for bin picking, inspection, and mobile robotics. +Various types of object recognition problems can be +stated based on the dimensionality of their spatial descrip- +tion: (1) recognition of a 2-D object from a single 2-D im-"
+a9c120de41679fe336e2779f3e6fe4b04945cb3a,A Robust Multilinear Model Learning Framework for 3D Faces,"A Robust Multilinear Model Learning Framework for 3D Faces∗ +Timo Bolkart +Stefanie Wuhrer +Saarland University, Germany +Inria Grenoble Rhˆone-Alpes, France"
+a9f63dcae167630b0c6ba4131897539151217e2b,Testing a Method for Statistical Image Classification in Image Retrieval,"Testing a Method for Statistical Image +Classification in Image Retrieval +Christoph Rasche, Constantin Vertan +Laboratorul de Analiza si Prelucrarea Imaginilor +Universitatea Politehnica din Bucuresti +Bucuresti 061071, RO"
+a9f03e4bb90addab234423994bfd8c25854484ea,Object Based Image Retrieval Using Lbp and Fuzzy Clustering Method,"Volume1, Issue 3, 15 May- 15 August 2015 +International Journal In Applied Studies And +Production Management +ISSN 2394-840X +OBJECT BASED IMAGE RETRIEVAL USING LBP AND FUZZY +CLUSTERING METHOD +Jiwanjot kaur Bhinder +Department of Computer Science & Engg, RIMT(IET) Mandigobindgarh +Kirti joshi +Department of Computer Science & Engg, RIMT(IET) Mandigobindgarh"
+d55cce6ecbad2c6ecccbaa1cb0d14ae3a46b1454,Multimodal representation learning with neural networks,"Multimodal representation learning with +neural networks +John Edilson Arevalo Ovalle +National University of Colombia +Engineering School, Systems and Industrial Engineering Departament +Bogot´a, Colombia"
+d5813a4a0cca115b05e03d8d8c1ac8bf07176e96,Supplementary Material: Reinforced Video Captioning with Entailment Rewards,"Supplementary Material: Reinforced Video Captioning with Entailment +Rewards +Ramakanth Pasunuru and Mohit Bansal +UNC Chapel Hill +{ram, +Attention-based Baseline Model +(Cross-Entropy) +Reinforcement Learning (Policy +Gradient) +Our attention baseline model is similar to the Bah- +danau et al. (2015) architecture, where we encode +input frame level video features to a bi-directional +LSTM-RNN and then generate the caption using a +single layer LSTM-RNN, with an attention mech- +nism. Let {f1, f2, ..., fn} be the frame-level fea- +tures of a video clip and {w1, w2, ..., wm} be the +sequence of words forming a caption. The distri- +ution of words at time step t given the previously +generated words and input video frame-level fea- +tures is given as follows:"
d50c6d22449cc9170ab868b42f8c72f8d31f9b6c,Dynamic Multi-Task Learning with Convolutional Neural Network,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+d5bef023a7d1032a5c717109a9c1b600ee1e8a71,Autism Spectrum Disorder (ASD) and Fragile X Syndrome (FXS): Two Overlapping Disorders Reviewed through Electroencephalography—What Can be Interpreted from the Available Information?,"Brain Sci. 2015, 5, 92-117; doi:10.3390/brainsci5020092 +OPEN ACCESS +rain sciences +ISSN 2076-3425 +www.mdpi.com/journal/brainsci/ +Review +Autism Spectrum Disorder (ASD) and Fragile X Syndrome +(FXS): Two Overlapping Disorders Reviewed through +Electroencephalography—What Can be Interpreted +from the Available Information? +Niamh Mc Devitt 1,2,*, Louise Gallagher 1,3,4,5,6 and Richard B. Reilly 1,2,3,7 +School of Medicine, Trinity College, the University of Dublin, Dublin, Ireland; +E-Mails: (L.G.); (R.B.R.) +Trinity Centre for Bioengineering, Trinity College Dublin, the University of Dublin, Dublin, Ireland +Trinity College Institute for Neuroscience, Trinity College Dublin, the University of Dublin, +Dublin, Ireland +Department of Psychiatry, Trinity College Dublin, the University of Dublin, Dublin, Ireland +5 Institute of Molecular Medicine, Trinity Centre for Health Sciences, St James’ Hospital, +Dublin, Ireland +6 Linn Dara Child and Adolescent Mental Health Services, Cherry Orchard Hospital Dublin 10,"
d522c162bd03e935b1417f2e564d1357e98826d2,Weakly supervised object extraction with iterative contour prior for remote sensing images,"He et al. EURASIP Journal on Advances in Signal Processing 2013, 2013:19 http://asp.eurasipjournals.com/content/2013/1/19 RESEARCH @@ -12393,6 +43266,14 @@ Weakly supervised object extraction with iterative contour prior for remote sensing images Chu He1,2*, Yu Zhang1, Bo Shi1, Xin Su3, Xin Xu1 and Mingsheng Liao2"
+d5d3c1b299e81b4ab96d052f8a37013305b731d9,Performance Evaluation of Human Detection Systems for Robot Safety,"J Intell Robot Syst +DOI 10.1007/s10846-016-0334-3 +Performance Evaluation of Human Detection Systems +for Robot Safety +William Shackleford · Geraldine Cheok · +Tsai Hong · Kamel Saidi · Michael Shneier +Received: 9 April 2015 / Accepted: 11 January 2016 +© Springer Science+Business Media Dordrecht (outside the USA) 2016"
d59f18fcb07648381aa5232842eabba1db52383e,Robust Facial Expression Recognition Using Spatially Localized Geometric Model,"International Conference on Systemics, Cybernetics and Informatics, February 12–15, 2004 ROBUST FACIAL EXPRESSION RECOGNITION USING SPATIALLY LOCALIZED GEOMETRIC MODEL @@ -12413,18 +43294,49 @@ chieved expression recognition rates of as high as 98% [2], they re computationally inefficient and require considerable apriori training based on 3D information, which is often unavailable. Recognition from 2D images remains a difficult yet important"
+d5579b2708a1c713e1b2feb8646533ce26085a3a,Effective Use of Dilated Convolutions for Segmenting Small Object Instances in Remote Sensing Imagery,"Effective Use of Dilated Convolutions for Segmenting Small Object Instances in +Remote Sensing Imagery +Ryuhei Hamaguchi Aito Fujita Keisuke Nemoto +Tomoyuki Imaizumi Shuhei Hikosaka +PASCO CORPORATION, Japan +{riyhuc2734, aaitti6875, koetio8807, tiommu4352,"
d588dd4f305cdea37add2e9bb3d769df98efe880,Audio - Visual Authentication System over the Internet Protocol,"Audio-Visual Authentication System over the Internet Protocol Yee Wan Wong, Kah Phooi Seng, and Li-Minn Ang bandoned. illumination based is developed with the objective to"
+d5de20cca347d6c5e6f662292e4d52e765ff5cee,Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties,
+d59a9d80e7d8c875d2b73241a8b02078ea6ad0a7,A Deep Learning Perspective on the Origin of Facial Expressions,"BREUER, KIMMEL: A DEEP LEARNING PERSPECTIVE ON FACIAL EXPRESSIONS +A Deep Learning Perspective on the Origin +of Facial Expressions +Ran Breuer +Ron Kimmel +Department of Computer Science +Technion - Israel Institute of Technology +Technion City, Haifa, Israel +Figure 1: Demonstration of the filter visualization process."
+d55d6ccefe797317996805ebf58a74587b158950,Distribution-based Label Space Transformation for Multi-label Learning,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Distribution-based Label Space Transformation for +Multi-label Learning +Zongting Lyu, Yan Yan, and Fei Wu"
d5444f9475253bbcfef85c351ea9dab56793b9ea,BoxCars: Improving Fine-Grained Recognition of Vehicles using 3-D Bounding Boxes in Traffic Surveillance,"IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS BoxCars: Improving Fine-Grained Recognition of Vehicles using 3D Bounding Boxes in Traffic Surveillance Jakub Sochor, Jakub ˇSpaˇnhel, Adam Herout in contrast"
+d53994f28deb2800120fab8a42852813b3b8c081,Does the Left Hair Part Look Better ( or Worse ) Than the Right ?,"Article +Does the Left Hair Part Look Better +(or Worse) Than the Right? +Social Psychological and +Personality Science +ª The Author(s) 2018 +Reprints and permission: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/1948550618762500 +journals.sagepub.com/home/spp +Jeremy A. Frimer1"
d5ab6aa15dad26a6ace5ab83ce62b7467a18a88e,Optimized Structure for Facial Action Unit Relationship Using Bayesian Network,"World Journal of Computer Application and Technology 2(7): 133-138, 2014 DOI: 10.13189/wjcat.2014.020701 http://www.hrpub.org @@ -12435,11 +43347,35 @@ Intelligent Biometric Group, School of Electrical and Electronic Engineering, En *Corresponding Author: Pinang, Malaysia Copyright © 2014 Horizon Research Publishing All rights reserved."
+d5fe9c84710b71a754676b2ee67cec63e8cd184b,FPGA Implementation of a HOG-based Pedestrian Recognition System,"Sebastian Bauer, Ulrich Brunsmann, Stefan Schlotterbeck-Macht +Aschaffenburg University of Applied Sciences, Aschaffenburg, Germany +Faculty of Engineering +FPGA Implementation of a HOG-based +Pedestrian Recognition System +FPGA Implementation of a HOG-based +Pedestrian Recognition System +{sebastian.bauer, ulrich.brunsmann, stefan.schlotterbeck-macht} +terms of +With respect to road crash statistics, on-board +pedestrian detection is a key task for future +dvanced driver assistance systems. +In this +paper, we describe the implementation of a real- +time pedestrian recognition system that combines +FPGA-based extraction of image features with a +CPU-based object localization and classification +framework. +features, we have +implemented"
+d5d6b3959958adb1333fa1a72227378ad3f7c16d,Collaborative Contributions for Better Annotations,
d56fe69cbfd08525f20679ffc50707b738b88031,Training of multiple classifier systems utilizing partially labeled sequential data sets,"Training of multiple classifier systems utilizing partially labelled sequences Martin Schels, Patrick Schillinger, and Friedhelm Schwenker Ulm University - Department of Neural Information Processing 89069 Ulm - Germany"
+d5c6c0fb51947a2df1389f1aab7a635bf687ac1d,A Multiview Approach to Learning Articulated Motion Models,"A Multiview Approach to Learning +Articulated Motion Models +Andrea F. Daniele, Thomas M. Howard, and Matthew R. Walter"
d5de42d37ee84c86b8f9a054f90ddb4566990ec0,Asynchronous Temporal Fields for Action Recognition,"Asynchronous Temporal Fields for Action Recognition Gunnar A. Sigurdsson1∗ Santosh Divvala2,3 Ali Farhadi2,3 Abhinav Gupta1,3 Carnegie Mellon University 2University of Washington 3Allen Institute for Artificial Intelligence @@ -12449,18 +43385,73 @@ STEGANOGRAPHY Atique ur Rehman, Rafia Rahim, Shahroz Nadeem, Sibt ul Hussain National University of Computer & Emerging Sciences (NUCES-FAST), Islamabad, Pakistan. Reveal.ai (Recognition, Vision & Learning) Lab"
+d5cf6a02f8308e948e3bcd1fd1ca660ea8ea8921,G Enerative Networks as Inverse Problems with Scattering Transforms,"Under review as a conference paper at ICLR 2018 +GENERATIVE NETWORKS AS INVERSE PROBLEMS +WITH SCATTERING TRANSFORMS +Anonymous authors +Paper under double-blind review"
d5b5c63c5611d7b911bc1f7e161a0863a34d44ea,Extracting Scene-Dependent Discriminant Features for Enhancing Face Recognition under Severe Conditions,"Extracting Scene-dependent Discriminant Features for Enhancing Face Recognition under Severe Conditions Rui Ishiyama and Nobuyuki Yasukawa Information and Media Processing Research Laboratories, NEC Corporation 753, Shimonumabe, Nakahara-Ku, Kawasaki 211-8666 Japan"
+d53c5a974f9fccf18f3c8f7d73522d6ca7162115,X-GAN : Improving Generative Adversarial Networks with ConveX Combinations,"X-GAN: Improving Generative Adversarial +Networks with ConveX Combinations +Oliver Blum, Biagio Brattoli, and Bj¨orn Ommer +Heidelberg University, HCI / IWR, Germany"
d59404354f84ad98fa809fd1295608bf3d658bdc,Face Synthesis from Visual Attributes via Sketch using Conditional VAEs and GANs,"International Journal of Computer Vision manuscript No. (will be inserted by the editor) Face Synthesis from Visual Attributes via Sketch using Conditional VAEs and GANs Xing Di · Vishal M. Patel Received: date / Accepted: date"
+d56407072eb9847fa44d49969129b5a4d1ef9ceb,Gaussian Process Prior Variational Autoencoders,"Gaussian Process Prior Variational Autoencoders +Francesco Paolo Casale†∗, Adrian V Dalca‡§, Luca Saglietti†¶, +Jennifer Listgarten(cid:93), Nicolo Fusi† +Microsoft Research New England, Cambridge (MA), USA +Computer Science and Artificial Intelligence Lab, MIT, Cambridge (MA), USA +§ Martinos Center for Biomedical Imaging, MGH, HMS, Boston (MA), USA; +¶ Italian Institute for Genomic Medicine, Torino, Italy +(cid:93) EECS Department, University of California, Berkeley (CA), USA."
+d5856f47fe117c114e8bcfbf2abc4e80691a512c,Interpreting Complex Scenes using a Hierarchy of Prototypical Scene Models,"Interpreting Complex Scenes using a +Hierarchy of Prototypical Scene +Models +Dissertation +zur Erlangung des akademischen Grades +Doktor der Ingenieurwissenschaften (Dr.-Ing.) +vorgelegt an +der Technischen Fakult¨at der Universit¨at Bielefeld +Sarah Bonnin +4.10.2014"
+d54f508c943b8415bfdd30d9210869ec93ff3f03,A method of illumination compensation for human face image based on quotient image,"Available online at www.sciencedirect.com +Information Sciences 178 (2008) 2705–2721 +www.elsevier.com/locate/ins +A method of illumination compensation for human face +image based on quotient image q +Wang Ying-hui a,b, Ning Xiao-juan a,*, Yang Chun-xia a, Wang Qiong-fang b +School of Computer Science Engineering, Xi’an University of Technology, Xi’an 710048, China +Department of Computer Science, Shaanxi Normal University, Xi’an 710062, China +Received 23 February 2007; received in revised form 2 December 2007; accepted 14 December 2007"
+d24a30ed78b749f3730e25dcef89472dd5fb439c,Improving Face Recognition Performance Using a Hierarchical Bayesian Model,"Improving Face Recognition +Performance Using a Hierarchical +Bayesian Model +Ashwini Shikaripur Nadig +Submitted to the graduate degree program in +Electrical Engineering & Computer Science and the +Graduate Faculty of the University of Kansas +School of Engineering in partial fulfillment of the +requirements for the degree of Master of Science +Thesis Committee: +Dr. Brian Potetz: Chairperson +Dr. Prasad Kulkarni +Dr. Luke Huan +Date Defended"
+d2f717d1799b5cec5f1f426511527bd7e6e05d9d,Image-Based Synthesis for Deep 3D Human Pose Estimation,"Noname manuscript No. +(will be inserted by the editor) +Image-based Synthesis for Deep 3D Human Pose Estimation +Grégory Rogez · Cordelia Schmid +Received: date / Accepted: date"
d231a81b38fde73bdbf13cfec57d6652f8546c3c,SUPERRESOLUTION TECHNIQUES FOR FACE RECOGNITION FROM VIDEO by Osman,"SUPERRESOLUTION TECHNIQUES FOR FACE RECOGNITION FROM VIDEO Osman Gökhan Sezer @@ -12480,6 +43471,38 @@ Sanghvi Institute of Management & Science Indore (MP), India local INTRODUCTION"
+d28c12e270a06e977b59194cc6564787c87caa7e,Human Action Poselets Estimation via Color G-surf in Still Images,"HUMAN ACTION POSELETS ESTIMATION VIA COLOR G-SURF IN STILL IMAGES +M. Favorskaya *, D. Novikov, Y. Savitskaya +Institute of Informatics and Telecommunications, Siberian State Aerospace University, 31 Krasnoyarsky Rabochy av., Krasnoyarsk, +660014 Russian Federation - (favorskaya, +Commission WG V/5, WG III/3 +KEY WORDS: Human Action, Poselets, Gauge-SURF, Random Forest, Still Image"
+d2df37ecfbf914d5b81e2e5e342e3907c6f55a14,Can Convolution Neural Network ( CNN ) Triumph in Ear Recognition of Uniform Illumination Invariant ?,"Indonesian Journal of Electrical Engineering and Computer Science +Vol. 11, No. 2, August 2018, pp. 558~566 +ISSN: 2502-4752, DOI: 10.11591/ijeecs.v11.i2.pp558-566 + 558 +Can Convolution Neural Network (CNN) Triumph in Ear +Recognition of Uniform Illumination Invariant? +Nursuriati Jamil1, Ali Abd Almisreb2, Syed Mohd Zahid Syed Zainal Ariffin3, N. Md Din4, +Raseeda Hamzah5 +,3,5Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, +40450 Shah Alam, Selangor, Malaysia +,4College of Graduate Studies, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Malaysia +Article Info +Article history: +Received Mar 1, 2018 +Revised Apr 21, 2018 +Accepted May 1, 2018 +Keywords: +Convolution Neural Network +Ear Recognition +Uniform Illumination Invariant"
+d252e10024a22c8274ae67dbf37aa854d75a85f2,Joint Gender Classification and Age Estimation by Nearly Orthogonalizing Their Semantic Spaces,"Joint Gender Classification and Age Estimation +y Nearly Orthogonalizing Their Semantic +Spaces +Qing Tiana, Songcan Chena,∗ +College of Computer Science and Technology, Nanjing University of Aeronautics and +Astronautics, Nanjing 210016, China"
d2eb1079552fb736e3ba5e494543e67620832c52,DeSTNet: Densely Fused Spatial Transformer Networks,"ANNUNZIATA, SAGONAS, CALÌ: DENSELY FUSED SPATIAL TRANSFORMER NETWORKS1 DeSTNet: Densely Fused Spatial Transformer Networks1 @@ -12501,6 +43524,60 @@ Charlotte van Eeuwijk4 • Nexhmedin Morina3 Published online: 25 September 2017 Ó The Author(s) 2017. This article is an open access publication"
+d2860bb05f747e4628e95e4d84018263831bab0d,Learning to Generate Samples from Noise through Infusion Training,"Published as a conference paper at ICLR 2017 +LEARNING TO GENERATE SAMPLES FROM NOISE +THROUGH INFUSION TRAINING +Florian Bordes, Sina Honari, Pascal Vincent∗ +Montreal Institute for Learning Algorithms (MILA) +D´epartement d’Informatique et de Recherche Op´erationnelle +Universit´e de Montr´eal +Montr´eal, Qu´ebec, Canada"
+d2b2b56dd8c1daa61152595caf759a62596a85c9,Revocable and Non-Invertible Multibiometric Template Protection based on Matrix Transformation,"Pertanika J. Sci. & Technol. 26 (1): 133 - 160 (2018) +Revocable and Non-Invertible Multibiometric Template +Protection based on Matrix Transformation +Jegede, A.1,2*, Udzir, N. I.1, Abdullah, A.1 and Mahmod, R.1 +Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM, +Serdang, Selangor, Malaysia +Department of Computer Science, University of Jos, 930001 Nigeria"
+d20e7d7ab8e767dc1c170ca2141d8ba64a4d092b,Mental Concept in Autism,"Psychology, 2014, 5, 1392-1403 +Published Online August 2014 in SciRes. http://www.scirp.org/journal/psych +http://dx.doi.org/10.4236/psych.2014.511150 +“Please Draw Me a Face…” Atypical Face +Mental Concept in Autism +Emilie Meaux1*, David Bakhos2, Frédérique Bonnet-Brilhault1, Patrice Gillet3, +Emmanuel Lescanne4, Catherine Barthélémy1, Magali Batty1 +UMRS Imagerie et Cerveau, Inserm U930 Equipe 1, CNRS ERL 3106, Université François Rabelais de Tours, +CHRU de Tours, Tours, France +Unité Pédiatrique d’ORL et CCF, Centre Hospitalier Régional Universitaire de Tours, Université François +Rabelais de Tours, CHRU de Tours, Tours, France +Université François Rabelais de Tours, CHRU de Tours, Tours, France +Service d’ORL et CCF Pédiatrique, CHU de Tours Gatien-de-Clocheville, Université François Rabelais de Tours, +Tours, France +Email: +Received 16 May 2014; revised 12 June 2014; accepted 5 July 2014 +Copyright © 2014 by authors and Scientific Research Publishing Inc. +This work is licensed under the Creative Commons Attribution International License (CC BY). +http://creativecommons.org/licenses/by/4.0/"
+d259d3652f03c7b80e29c986e9540ab00b1f1133,3D Face Detection and Recognition under Occlusion,"Dr.V.Ramaswamy1, Parashuram Baraki2 +Research Guide, Jain University, Bangalore, +Doctoral Student, Jain University, Bangalore +& Asst.Professor , CS&E, Dept, +GM Institute of Technology, Davanagere +D Face Detection and Recognition under Occlusion +is very vital. Three-dimensional"
+d2f3ba37ef34d5d39f799f8dd3557f1eb795aedd,Learning Unified Embedding for Apparel Recognition,"Learning Unified Embedding for Apparel Recognition +Yang Song +Google +Yuan Li +Google +Xiao Zhang +Google +Bo Wu +Google +Chao-Yeh Chen +Google +Hartwig Adam +Google"
d278e020be85a1ccd90aa366b70c43884dd3f798,Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks,"Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks Vishal Kaushal @@ -12521,11 +43598,176 @@ Seattle, Washington, USA Narsimha Raju IIT Bombay Mumbai, Maharashtra, India"
+d2b86b6dc93631990e21a12278e77f002fb4b116,Aalborg Universitet Attention in Multimodal Neural Networks for Person Re-identification,"Aalborg Universitet +Attention in Multimodal Neural Networks for Person Re-identification +Lejbølle, Aske Rasch; Krogh, Benjamin; Nasrollahi, Kamal; Moeslund, Thomas B. +Published in: +018 IEEE Computer Vision and Pattern Recognition Workshops: Visual Understanding of Humans in Crowd +Scene +Publication date: +Document Version +Accepted author manuscript, peer reviewed version +Link to publication from Aalborg University +Citation for published version (APA): +Lejbølle, A. R., Krogh, B., Nasrollahi, K., & Moeslund, T. B. (2018). Attention in Multimodal Neural Networks for +Person Re-identification. In 2018 IEEE Computer Vision and Pattern Recognition Workshops: Visual +Understanding of Humans in Crowd Scene (pp. 179-187). IEEE. +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. +? You may not further distribute the material or use it for any profit-making activity or commercial gain +? You may freely distribute the URL identifying the publication in the public portal ?"
+d2a5b9b8f02f39f7d9ef48d234ec61f4ddc6c291,Facial surface reconstruction in 3D format,"Journal of Theoretical and Applied Computer Science +ISSN 2299-2634 +Vol. 6, No. 4, 2012, pp. 37-50 +http://www.jtacs.org +Facial surface reconstruction in 3D format +Nadezhda Shchegoleva +Department of Mathematical Computer Software, Saint Petersburg Electrotechnical University (LETI), Russia"
+d2518b01092160cecec2e986935b0129b0bbff45,Looking around the Backyard Helps to Recognize Handwritten Digits,"#2611 +CVPR 2008 Submission #2611. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. +#2611 +Looking around the Backyard Helps to Recognize Handwritten Digits +Anonymous CVPR submission +Paper ID 2611"
+d2cda0dbb8b2e83ce3e70d818f78d2add803c661,Automatic Video Captioning via Multi-channel Sequential Encoding,"Automatic Video Captioning via Multi-channel +Sequential Encoding +Chenyang Zhang and Yingli Tian +Department of Electrical Engineering +The City College of New York +New York, NY 10031"
+d2b8459b41172dc332cf00dc18a309c442347a7d,Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free Approach,"Deep Spatial Feature Reconstruction for Partial Person Re-identification: +Alignment-free Approach +Lingxiao He∗1,2, Jian Liang∗1,2, Haiqing Li1,2, and Zhenan Sun1,2,3 +CRIPAC & NLPR, CASIA 2 University of Chinese Academy of Sciences, Beijing, P.R. China +Center for Excellence in Brain Science and Intelligence Technology, CAS +{lingxiao.he, jian.liang, hqli,"
+aa420d32c48a3fd526a91285673cd55ca9fe2447,R 4-A . 1 : Dynamics-Based Video Analytics,"R4-A.1: Dynamics-Based Video Analytics +PARTICIPANTS +Octavia Camps +Mario Sznaier +Title +Co-PI +Co-PI +Faculty/Staff +Institution +Graduate, Undergraduate and REU Students +Oliver Lehmann +Mengran Gou +Yongfang Cheng +Yin Wang +Sadjad Ashari-Esfeden +Tom Hebble +Rachel Shaff er +Burak Yilmaz +Degree Pursued +MSEE/ PhD"
+aaaeca92457a72ec4e7e538cf6393c4c1dc8e670,Life-long Learning Perception using Cloud Database Technology,"Life-long Learning Perception using Cloud Database Technology +Tim Niemueller +Stefan Schiffer +Gerhard Lakemeyer +Knowledge-based Systems Group +Safoura Rezapour Lakani +Intelligent and Interactive Systems +RWTH Aachen University (Aachen, Germany) +University of Innsbruck (Innsbruck, Austria)"
+aaa021feeec2f84c4a5f3c56b4c0fecb5a85a352,A Riemannian Network for SPD Matrix Learning,"A Riemannian Network for SPD Matrix Learning +Zhiwu Huang and Luc Van Gool +Computer Vision Lab, ETH Zurich, Switzerland +{zhiwu.huang,"
+aad03480c30c0a3d917d171d8d6b914026fe5105,Affordances Provide a Fundamental Categorization Principle for Visual Scenes,"Affordances +Provide +Fundamental +Categorization +Principle +Visual +Scenes +Michelle +Greene +Christopher +Baldassano +Andre +Esteva +Diane +(1) Stanford +University, +Department +Computer +Science +(2) Stanford"
+aaaefba1bd0a9a9ec6c66a822d11fb907a05625c,"On Detection, Data Association and Segmentation for Multi-target Tracking.","This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2018.2849374, IEEE +Transactions on Pattern Analysis and Machine Intelligence +On Detection, Data Association and +Segmentation for Multi-target Tracking +Yicong Tian, Member, IEEE, Afshin Dehghan, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
+aa5c2ac60a288132efeeb85c5af1fd0b39294eed,Directed Markov Stationary Features for visual classification,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE +ICASSP 2009"
+aa5efcc4331da6b1902f2c900b79120226fdcf20,A Robust Class-based Reflectance Rendering for Face Images,A ROBUST CLASS-BASED REFLECTANCE RENDERING FOR FACE IMAGES
+aa2ad3df24d8d8c4a4d2fe85f0d4e635d595f0a2,PedCut: an iterative framework for pedestrian segmentation combining shape models and multiple data cues,"F. FLOHR, D. M. GAVRILA: PEDCUT +PedCut: an iterative framework for +pedestrian segmentation combining +shape models and multiple data cues +Fabian Flohr1,2 +Dariu M. Gavrila1,2 +www.gavrila.net +Environment Perception Department, +Daimler R&D, Ulm, Germany +Intelligent Systems Laboratory, +Univ. of Amsterdam, The Netherlands"
+aa3e1824af497dc16ae27e6818a0e89c78a18371,Local Gray Code Pattern ( LGCP ) : A Robust Feature Descriptor for Facial Expression Recognition,"International Journal of Science and Research (IJSR), India Online ISSN: 2319-7064 +Local Gray Code Pattern (LGCP): A Robust +Feature Descriptor for Facial Expression +Recognition +Mohammad Shahidul Islam +Atish Dipankar University of Science & Technology, School, Department of Computer Science and Engineering, Dhaka, Bangladesh."
+aa23d33983b1abd2d8a677040eb875e93c478a7f,Measuring the Objectness of Image Windows,"Measuring the objectness of image windows +Bogdan Alexe, Thomas Deselaers, and Vittorio Ferrari"
+aad8d2e32f1cc21eedbdd5e8ebff9f367daa6d92,Online Multi-target Tracking by Large Margin Structured Learning,"Online Multi-Target Tracking +y Large Margin Structured Learning +Suna Kim, Suha Kwak, Jan Feyereisl, and Bohyung Han +Department of Computer Science and Engineering +POSTECH, Korea"
+aaa6fe8045e1a071e1762cffe4f59e0bd508daf9,Single-Pedestrian Detection Aided by Two-Pedestrian Detection,"IEEE TRANSACTIONS PATTERN ANALYSIS AND MACHINE INTELLIGENCE +Single-Pedestrian Detection Aided by +-Pedestrian Detection +Wanli Ouyang, Member, IEEE, Xingyu Zeng and Xiaogang Wang, Member, IEEE,"
+aa5fbe092f8a4dcb43c31ab93af0290900b4f0e2,Visual Question Answering using Natural Language Object Retrieval and Saliency Cues,"Visual Question Answering using Natural Language Object Retrieval and +CS381V Final Project Report +Saliency Cues +Aishwarya Padmakumar +Akanksha Saran"
aae742779e8b754da7973949992d258d6ca26216,Robust facial expression classification using shape and appearance features,"Robust Facial Expression Classification Using Shape nd Appearance Features S L Happy and Aurobinda Routray Department of Electrical Engineering, Indian Institute of Technology Kharagpur, India"
+aad7f9eeb10d4f655c3e3d18d3542603ad3071b4,Deep Unsupervised Learning of Visual Similarities,"Deep Unsupervised Learning of Visual Similarities +Artsiom Sanakoyeu∗, Miguel A. Bautista, Björn Ommer +Heidelberg Collaboratory for Image Processing and Interdisciplinary Center for Scientific Computing, Heidelberg University, Germany"
+aa8cec9cec1f15f95bbe0ef4d7809e199de0f30b,Vitamin D hormone regulates serotonin synthesis. Part 1: relevance for autism.,"The FASEB Journal (cid:129) Review +Vitamin D hormone regulates serotonin synthesis. +Part 1: relevance for autism +Rhonda P. Patrick1 and Bruce N. Ames1 +Nutrition and Metabolism Center, Children’s Hospital Oakland Research Institute, Oakland, +California, USA +Serotonin and vitamin D have been pro-"
+aa32f5b0a866b04a89f75cda32e0975a541864ff,Action-Driven Object Detection with Top-Down Visual Attentions,"Action-Driven Object Detection +with Top-Down Visual Attentions +Donggeun Yoo, Student Member, IEEE, Sunggyun Park, Student Member, IEEE, +Kyunghyun Paeng, Student Member, IEEE, Joon-Young Lee, Member, IEEE, +nd In So Kweon, Member, IEEE"
+aaa82dfc7942ae16c1d7155a109582505ccee4ec,Properties of Datasets Predict the Performance of Classifiers,"AGHAZADEH, CARLSSON: PROPERTIES OF DATASETS PREDICT THE PERFORMANCE ... 1 +Properties of Datasets Predict the +Performance of Classifiers +Omid Aghazadeh +http://www.csc.kth.se/~omida +Stefan Carlsson +http://www.csc.kth.se/~stefanc +Computer Vision Group +Computer Vision and Active Perception +Laboratory +KTH, Sweden"
aa52910c8f95e91e9fc96a1aefd406ffa66d797d,Face Recognition System Based on 2dfld and Pca,"FACE RECOGNITION SYSTEM BASED ON 2DFLD AND PCA Dr. Sachin D. Ruikar @@ -12536,6 +43778,12 @@ Mr. Hulle Rohit Rajiv ME E&TC [Digital System] Sinhgad Academy of Engineering Pune, India"
+aa6854612062edff9978b33e0a410f2717bc3027,LPT: Eye Features Localizer in an N-Dimensional Image Space,"LPT: Eye Features Localizer in an N-Dimensional Image +Space +Mohammad Mahdi Dehshibi1, Azam Bastanfard2, and Alireza Abdi3 +Young Researchers Club, Islamic Azad University South Tehran Branch, Tehran, Iran +IT Research Laboratory, Faculty of Engineering, Islamic Azad University Karaj Branch, Karaj, Iran +Faculty of Electrical, Computer and IT, Islamic Azad University Qazvin Branch, Qazvin, Iran"
aafb8dc8fda3b13a64ec3f1ca7911df01707c453,Excitation Backprop for RNNs,"Excitation Backprop for RNNs Sarah Adel Bargal∗1, Andrea Zunino∗ 2, Donghyun Kim1, Jianming Zhang3, Vittorio Murino2,4, Stan Sclaroff1 @@ -12545,14 +43793,45 @@ Figure 1: Our proposed framework spatiotemporally highlights/grounds the evidenc or caption for a given input video. In this example, by using our proposed back-propagation method, the evidence for the activity class CliffDiving is highlighted in a video that contains CliffDiving and HorseRiding. Our model employs a single backward pass to produce saliency maps that highlight the evidence that a given RNN used in generating its outputs."
+aa8c3eb6e821cb44ed5a15a2f09fba332e5561c6,Object Detection in Multi-view X-Ray Images,"Object Detection in Multi-View X-Ray Images +Thorsten Franzel, Uwe Schmidt, and Stefan Roth +Department of Computer Science, TU Darmstadt"
+aaba2a04c025f12f839ac71fb248da0dd6985d58,A Combined Face Recognition Approach Based on Lpd and Lvp,"VOL. 10, NO. 6, APRIL 2015 ISSN 1819-6608 +ARPN Journal of Engineering and Applied Sciences +©2006-2015 Asian Research Publishing Network (ARPN). All rights reserved. +www.arpnjournals.com +A COMBINED FACE RECOGNITION APPROACH BASED ON LPD +AND LVP +Kabilan R.1, Ravi R.2, Rajakumar G.1, Esther Leethiya Rani S.1 and Mini Minar V. C.1 +Department of ECE, Francis Xavier Engineering College, Tirunelveli, Tamilnadu, India +Department of IT, Francis Xavier Engineering College, Tirunelveli, Tamilnadu, India +E-Mail:"
aadfcaf601630bdc2af11c00eb34220da59b7559,Multi-view Hybrid Embedding: A Divide-and-Conquer Approach,"Multi-view Hybrid Embedding: A Divide-and-Conquer Approach Jiamiao Xu∗, Shujian Yu∗, Xinge You†, Senior Member, IEEE, Mengjun Leng, Xiao-Yuan Jing, and C. L. Philip Chen, Fellow, IEEE"
aaa4c625f5f9b65c7f3df5c7bfe8a6595d0195a5,Biometrics in ambient intelligence,"Biometrics in Ambient Intelligence Massimo Tistarelli§ and Ben Schouten§§"
+aa49556ee4f1ee3fcc9f0f713c755da30b0f505c,Exactly Robust Kernel Principal Component Analysis,"Exactly Robust Kernel Principal Component +Analysis +Jicong Fan, Tommy W.S. Chow"
+aa261599d70a9e649501cae5cf46fbc56229fad8,The effect of the Distance in Pedestrian Detection,"Master in Computer Vision and Artificial Intelligence - Universitat Aut`onoma de Barcelona +September 2009 +The effect of the Distance in Pedestrian Detection +David V´azquez Berm´udez +Computer Vision Center +Edifici O, Universitat Aut`onoma de Barcelona +08193, Bellaterra (Spain) +Advisors: Dr. Antonio M. L´opez and David Ger´onimo"
+aa5ed6ee0b2fd53df5cab952aa368f8c4908ffeb,REACH - Realtime crowd tracking using a hybrid motion model,"REACH - Realtime Crowd tracking using a Hybrid motion model +Aniket Bera1 and Dinesh Manocha1 +http://gamma.cs.unc.edu/REACH"
aae0e417bbfba701a1183d3d92cc7ad550ee59c3,A Statistical Method for 2-D Facial Landmarking,"A Statistical Method for 2-D Facial Landmarking Hamdi Dibeklio˘glu, Student Member, IEEE, Albert Ali Salah, Member, IEEE, and Theo Gevers, Member, IEEE"
+aa782f4af587ee68936f0f5361fc1448ef61bdd9,Human Tracking using Wearable Sensors in the Pocket Double blind submission,"Human Tracking using Wearable Sensors in the Pocket +Double blind submission +Address +e-mail address"
aa577652ce4dad3ca3dde44f881972ae6e1acce7,Deep Attribute Networks,"Deep Attribute Networks Junyoung Chung Department of EE, KAIST @@ -12566,6 +43845,12 @@ Daejeon, South Korea Chang D. Yoo Department of EE, KAIST Daejeon, South Korea"
+aa2a4f7cf8866d513053873a410879ab5b34b53a,Improving robot manipulation with data-driven object-centric models of everyday forces,"Noname manuscript No. +(will be inserted by the editor) +Improving Robot Manipulation with Data-Driven +Object-Centric Models of Everyday Forces +Advait Jain · Charles C. Kemp +Received: date / Accepted: date"
aa94f214bb3e14842e4056fdef834a51aecef39c,Reconhecimento de padrões faciais: Um estudo,"Reconhecimento de padrões faciais: Um estudo Alex Lima Silva, Marcos Evandro Cintra Universidade Federal @@ -12596,6 +43881,10 @@ of the requirements for the degree of DOCTOR OF PHILOSOPHY September 2010 Department of Computer Science"
+afaa607aa9ad0e9dad0ce2fe5b031eb4e525cbd8,Towards an automatic face indexing system for actor-based video services in an IPTV environment,"J. Y. Choi et al.: Towards an Automatic Face Indexing System for Actor-based Video Services in an IPTV Environment +Towards an Automatic Face Indexing System for Actor-based +Video Services in an IPTV Environment +Jae Young Choi, Wesley De Neve, and Yong Man Ro, Senior Member, IEEE"
af6e351d58dba0962d6eb1baf4c9a776eb73533f,How to Train Your Deep Neural Network with Dictionary Learning,"How to Train Your Deep Neural Network with Dictionary Learning Vanika Singhal*, Shikha Singh+ and Angshul Majumdar# @@ -12608,6 +43897,12 @@ Okhla Phase 3 Okhla Phase 3 Delhi, 110020, India Delhi, 110020, India"
+af24595c0c8f1b317b6fe2f2b49417cc40094b5c,LSH Softmax : Sub-Linear Learning and Inference of the Softmax Layer in Deep Architectures,"LSH Softmax: Sub-Linear Learning and +Inference of the Softmax Layer in Deep +Daniel Levy∗ +Architectures +Danlu Chen† +January 31, 2018"
af62621816fbbe7582a7d237ebae1a4d68fcf97d,Active Shape Model Based Recognition Of Facial Expression,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 International Conference on Humming Bird ( 01st March 2014) RESEARCH ARTICLE @@ -12638,13 +43933,194 @@ L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de"
+af1fa9d29512fc8f4c07efdf75d3f640567a5262,Sparse Representation for Face Recognition Based on Constraint Sampling and Face Alignment,"TSINGHUA SCIENCE AND TECHNOLOGY +ISSNll1007-0214ll08/12llpp62-67 +Volume 18, Number 1, February 2013 +Sparse Representation for Face Recognition Based on Constraint +Sampling and Face Alignment +Jing Wang, Guangda Su(cid:3), Ying Xiong, Jiansheng Chen, Yan Shang, Jiongxin Liu, and Xiaolong Ren"
+af9d41c598fc5ae57b20948cf664273da4664931,A comparison of crowd commotion measures from generative models,"A Comparison of Crowd Commotion Measures from Generative Models +Sadegh Mohammadi +Hamed Kiani +Alessandro Perina +Vittorio Murino +Pattern Analysis and Computer Vision Department (PAVIS) +Istituto Italiano di Tecnologia +Genova, Italy"
+afb6d1e72d5b5506867a74beeb1e661599b8fff3,Dynamic Feature Learning for Partial Face Recognition,"Dynamic Feature Learning for Partial Face Recognition +Lingxiao He1 +, Haiqing Li1 +, Qi Zhang1 +, and Zhenan Sun1 +CRIPAC & NLPR, CASIA 2 University of Chinese Academy of Sciences, Beijing, P.R. China +Center for Excellence in Brain Science and Intelligence Technology, CAS +{lingxiao.he, hqli, qi.zhang,"
+af9a830f62478c3638880d9a870f0b10535b3f92,Hausdorff distance-based multiresolution maps applied to image similarity measure,"Hausdorff distance-based multiresolution maps +pplied to image similarity measure +E. Baudrier*a, G. Millonb, F. Nicolierb, R. Seulinc and S. Ruanb +LMA – University of La Rochelle, Avenue Cre´peau, 17000 La Rochelle, France +CReSTIC – URCA, IUT, 9, rue de Que´bec, 10026 Troyes Cedex, France +Le2i – CNRS UMR 5158, University of Burgundy – IUT, 12, rue de la fonderie, 71200 Le Creusot, +France"
+af267b44c3ae6c2a0587310021a6180962e835d6,Shape and Symmetry Induction for 3D Objects,"Shape and Symmetry Induction for 3D Objects +Shubham Tulsiani1, Abhishek Kar1, Qixing Huang2, Jo˜ao Carreira1 and Jitendra Malik1 +University of California, Berkeley 2Toyota Technological Institute at Chicago +{shubhtuls, akar, carreira,"
+af8f59ceed0392159c3475c58af5b7ca8e4f6412,Facial Expression Recognition,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+afe3a0d463e2f099305c745ddbf943844583795d,Learning Visual Question Answering by Bootstrapping Hard Attention,"Learning Visual Question Answering by +Bootstrapping Hard Attention +Mateusz Malinowski, Carl Doersch, Adam Santoro, and Peter Battaglia +DeepMind, London, United Kingdom"
+af97b793a61ba6e2b02d0d29503b73b5bdc2150d,Wavelet-Local binary pattern based face recognition,"I S S N 2 2 7 7 - 3 0 6 1 +V o l u m e 1 6 N u m b e r 1 +I N T E R N A T I O N A L J O U R N A L O F C O M P U T E R S & T E C H N O L O G Y +Wavelet-Local binary pattern based face recognition +Azad Abdullah Ameen(1), Hardi M. M-Saleh(2) ,Zrar Kh. Abdul(3) +(1) Charmo University, College of Basic Education, Computer Department,Chamchamal, Raperin, Iraq +(2) Charmo University, College of Basic Education, Computer Department, Chamchamal, Raperin, Iraq +(3)Charmo University, College of Basic Education, Computer Department, Chamchamal, Raperin, Iraq"
+af8cd04bbe4902123d7042985159a6a5da9d9fb9,Représenter pour suivre : Exploitation de représentations parcimonieuses pour le suivi multi-objets. (Representing to follow: Exploitation of parsimonious representations for multi-object tracking),"Représenter pour suivre : exploitation de représentations +parcimonieuses pour le suivi multi-objets +Loïc Pierre Fagot-Bouquet +To cite this version: +Loïc Pierre Fagot-Bouquet. Représenter pour suivre : exploitation de représentations parcimonieuses +pour le suivi multi-objets. Automatique. Université Paul Sabatier - Toulouse III, 2017. Français. +<NNT : 2017TOU30030>. <tel-01516921v2> +HAL Id: tel-01516921 +https://tel.archives-ouvertes.fr/tel-01516921v2 +Submitted on 4 May 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+afa004a8daaa7fc093a798bf97babdb00273e1a0,Experimental Study on Fast 2d Homography Estimation from a Few Point Correspondences,"Tutkimusraportti 111 +Research Report 111 +EXPERIMENTAL STUDY ON FAST 2D +HOMOGRAPHY ESTIMATION FROM A FEW +POINT CORRESPONDENCES +Joni-Kristian Kämäräinen and Pekka Paalanen +Lappeenranta University of Technology +Faculty of Technology Management +Department of Information Technology +Box 20 +FIN-53851 Lappeenranta +ISBN 978-952-214-772-1 (paperback) +ISBN 978-952-214-773-8 (PDF) +ISSN 0783-8069 +Lappeenranta 2009"
+af34388e69800a168876f7446a621f68ca2215c0,Low-cost scene modeling using a density function improves segmentation performance,"Low-Cost Scene Modeling using a Density Function Improves Segmentation +Performance +Vivek Sharma(cid:5)(cid:63), S¸ule Yildirim-Yayilgan(cid:63), and Luc Van Gool(cid:5)∓"
+af053b8cf39612cec0148e14a9c4b7a789d7db11,Paris-Lille-3D: a large and high-quality ground truth urban point cloud dataset for automatic segmentation and classification,"Paris-Lille-3D: a large and high-quality ground truth urban point cloud +dataset for automatic segmentation and classification +Xavier Roynard, Jean-Emmanuel Deschaud and François Goulette +{xavier.roynard ; jean-emmanuel.deschaud ; +Mines ParisTech, PSL Research University, Centre for Robotics"
+afb1bc830febdb9893fd938fbdb20856b4ff3922,Defoiling Foiled Image Captions,"Defoiling Foiled Image Captions +Pranava Madhyastha, Josiah Wang and Lucia Specia +Department of Computer Science +University of Sheffield, UK +{p.madhyastha, j.k.wang,"
+afb51f0e173cd9ab1d41075862945ae6bc593cde,Large databases of real and synthetic images for feature evaluation and prediction,"Large databases of real and synthetic images for +feature evaluation and prediction +Biliana K. Kaneva +B.A., Computer Science and Mathematics, Smith College (2000) +M.S., Computer Science, University of Washington (2005) +Submitted to the Department of Electrical Engineering and Computer Science +in partial fulfillment of the requirements for the degree of +Doctor of Philosophy +in Electrical Engineering and Computer Science +t the Massachusetts Institute of Technology +February 2012 +(cid:13) 2012 Massachusetts Institute of Technology +All Rights Reserved. +Author: +Certified by: +Certified by: +Accepted by: +Department of Electrical Engineering and Computer Science +December 22, 2011 +William T. Freeman, Professor of Computer Science"
+af64854f653f2c1724d04c9657adfcdabe0f8440,Structure propagation for zero-shot learning,"Structure propagation for zero-shot learning +Guangfeng Lina,∗, Yajun Chena, Fan Zhaoa +Information science department, Xian University of Technology, +5 South Jinhua Road, Xi’an, Shaanxi Province 710048, PR China"
+af740db182b541eef80bb0a2dfebd1f07bb0e316,Deformable Kernel Networks for Joint Image Filtering,"Deformable Kernel Networks for Joint Image Filtering +Beomjun Kim, Jean Ponce, Bumsub Ham +To cite this version: +Beomjun Kim, Jean Ponce, Bumsub Ham. Deformable Kernel Networks for Joint Image Filtering. +018. <hal-01857016v2> +HAL Id: hal-01857016 +https://hal.archives-ouvertes.fr/hal-01857016v2 +Submitted on 10 Oct 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de +recherche français ou étrangers, des laboratoires +publics ou privés."
afc7092987f0d05f5685e9332d83c4b27612f964,Person-independent facial expression detection using Constrained Local Models,"Person-Independent Facial Expression Detection using Constrained Local Models Sien. W. Chew, Patrick Lucey, Simon Lucey, Jason Saragih, Jeffrey F. Cohn and Sridha Sridharan"
+b7a09eaadcb21bf9ab234d87c954e329518580c5,Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation,"Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation +Bugra Tekin +Pablo M´arquez-Neila +Mathieu Salzmann +Pascal Fua +EPFL, Switzerland"
b730908bc1f80b711c031f3ea459e4de09a3d324,Active Orientation Models for Face Alignment In-the-Wild,"Active Orientation Models for Face Alignment In-the-Wild Georgios Tzimiropoulos, Joan Alabort-i-Medina, Student Member, IEEE, Stefanos P. Zafeiriou, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+b778c0e5ec6cebbabc77fc56f9b7438f2974a4ea,Altered activity of the primary visual area during gaze processing in individuals with high-functioning autistic spectrum disorder: a magnetoencephalography study.,"Altered Activity of the Primary Visual Area during Gaze Processing in +Individuals with High-Functioning Autistic Spectrum Disorder: A +Magnetoencephalography Study +Naoya Hasegawaa, Hideaki Kitamuraa, Hiroatsu Murakamib, Shigeki Kameyamab, Mutsuo +Sasagawac, Jun Egawaa, Ryu Tamuraa, Tarou Endoa, Toshiyuki Someyaa +Department of Psychiatry, Niigata University Graduate School of Medical and Dental Sciences, +-757 Asahimachi-dori, Chuo-ku, Niigata 951-8510, Japan +Department of Neurosurgery, Epilepsy Center, Nishi-Niigata Chuo National Hospital, 1-14-1 +Masago, Nishi-ku, Niigata 950-2085, Japan +Department of Psychiatry, Epilepsy Center, Nishi-Niigata Chuo National Hospital, 1-14-1 +Masago, Nishi-ku, Niigata 950-2085, Japan +Short title: +Altered activity of the primary visual area of autistic spectrum disorder during gaze processing +Correspondence: Hideaki Kitamura +Department of Psychiatry, Niigata University Graduate School of Medical and Dental Sciences, +-757 Asahimachi-dori, Chuo-ku, Niigata 951-8510, Japan +Tel: +81-25-227-2213; Fax: +81-25-227-0777; +E-mail:"
b7cf7bb574b2369f4d7ebc3866b461634147041a,From NLDA to LDA/GSVD: a modified NLDA algorithm,"Neural Comput & Applic (2012) 21:1575–1583 DOI 10.1007/s00521-011-0728-x O R I G I N A L A R T I C L E @@ -12660,10 +44136,41 @@ feature extraction. Karthikeyan D1*, Balakrishnan G2 Department of ECE, Srinivasan Engineering College, Perambalur, India Department of Computer Science and Engineering, Indra Ganesan College of Engineering, Trichy, India"
+b7a0e7dab11781c252e1145f3526aee388b4136d,Facing humanness: Facial width-to-height ratio predicts ascriptions of humanity.,"Journal of Personality and Social +Psychology +Facing Humanness: Facial Width-to-Height Ratio +Predicts Ascriptions of Humanity +Jason C. Deska, E. Paige Lloyd, and Kurt Hugenberg +Online First Publication, August 28, 2017. http://dx.doi.org/10.1037/pspi0000110 +CITATION +Deska, J. C., Lloyd, E. P., & Hugenberg, K. (2017, August 28). Facing Humanness: Facial Width-to- +Advance online publication. http://dx.doi.org/10.1037/pspi0000110"
b7eead8586ffe069edd190956bd338d82c69f880,A Video Database for Facial Behavior Understanding,"A VIDEO DATABASE FOR FACIAL BEHAVIOR UNDERSTANDING D. Freire-Obreg´on and M. Castrill´on-Santana. SIANI, Universidad de Las Palmas de Gran Canaria, Spain"
+b79f3d9f8de4d1cc6679676146a40d2a8596f32d,Composing Simple Image Descriptions using Web-scale N-grams,"Proceedings of the Fifteenth Conference on Computational Natural Language Learning, pages 220–228, +Portland, Oregon, USA, 23–24 June 2011. c(cid:13)2011 Association for Computational Linguistics"
+b7ac537d97efcb968ca8e353ff5b0563e26b9dbe,Object-Aware Dense Semantic Correspondence,"Object-aware Dense Semantic Correspondence +Fan Yang1, Xin Li1 ∗, Hong Cheng2, Jianping Li1, Leiting Chen1 +School of Computer Science & Engineering, UESTC +Center for Robotics, School of Automation Engineering, UESTC +fanyang xinli"
+b797f3fa4e732d52092f9eb863350440d5de8bb1,Unsupervised Category Discovery via Looped Deep Pseudo-Task Optimization Using a Large Scale Radiology Image Database,"Unsupervised Category Discovery via Looped Deep Pseudo-Task Optimization +Using a Large Scale Radiology Image Database +Xiaosong Wang +Le Lu +Hoo-chang Shin +Lauren Kim Isabella Nogues +Jianhua Yao +Ronald Summers +Imaging Biomarkers and Computer-aided Detection Laboratory +Department of Radiology and Imaging Sciences +National Institutes of Health Clinical Center +0 Center Drive, Bethesda, MD 20892"
+b7c4fe5c89df51ebd1f89a34c66b94cc6019d8e6,Model Cards for Model Reporting,"Model Cards for Model Reporting +Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben +Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru"
b7774c096dc18bb0be2acef07ff5887a22c2a848,Distance metric learning for image and webpage comparison. (Apprentissage de distance pour la comparaison d'images et de pages Web),"Distance metric learning for image and webpage omparison Marc Teva Law @@ -12694,6 +44201,10 @@ FUJI PHOTO FILM CO., LTD. fujifilm.co.jp FUJI PHOTO FILM CO., LTD. fujifilm.co.jp"
+b701f11ecf5d465c7d5c427914db2ad8c97bb8a9,JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets,"JointGAN: Multi-Domain Joint Distribution Learning with +Generative Adversarial Nets +Yunchen Pu 1 Shuyang Dai 2 Zhe Gan 3 Weiyao Wang 2 Guoyin Wang 2 Yizhe Zhang 3 Ricardo Henao 2 +Lawrence Carin 2"
b755505bdd5af078e06427d34b6ac2530ba69b12,NFRAD: Near-Infrared Face Recognition at a Distance,"To appear in the International Joint Conf. Biometrics, Washington D.C., October, 2011 NFRAD: Near-Infrared Face Recognition at a Distance Hyunju Maenga, Hyun-Cheol Choia, Unsang Parkb, Seong-Whan Leea and Anil K. Jaina,b @@ -12713,9 +44224,63 @@ K(cid:2) (cid:2) (cid:3) (cid:4)"
+b732393cd3877f7e6d3cf3ca033a42415bd6db56,Statistical and Geometric Modeling of Spatio-Temporal Patterns for Video Understanding,
b73fdae232270404f96754329a1a18768974d3f6,Local Relation Map : A Novel Illumination Invariant Face Recognition Approach Regular Paper,
b76af8fcf9a3ebc421b075b689defb6dc4282670,Face Mask Extraction in Video Sequence,"Face Mask Extraction in Video Sequence Yujiang Wang 1 · Bingnan Luo 1 · Jie Shen 1 · Maja Pantic 1"
+b75df22c7c52b8d85dd7f155f7b495907ff3561f,Benchmark data and method for real-time people counting in cluttered scenes using depth sensors,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, APRIL 2018 +Benchmark data and method for real-time people +ounting in cluttered scenes using depth sensors +ShiJie Sun, Naveed Akhtar, HuanSheng Song, ChaoYang Zhang, JianXin Li, Ajmal Mian +Computer Vision techniques are well-suited to the problem +of automatic people counting for public transportations. How- +ever, using conventional RGB videos for this purpose is chal- +lenged by multiple issues resulting from real-world conditions +such as clutter, occlusions, illumination variations, handling +shadows etc. In comparison to the conventional video systems, +RGB-D cameras (e.g. Kinect V1 [4], Prime Sense Camera [5]) +an mitigate these issues by providing ‘depth’ information +of the scene in addition to its color video. Nevertheless, +effective people counting in real-world conditions using depth +information still remains a largely unsolved problem due to +noise and occlusion [6]."
+b73a6c7083f3dbc8b355f934aaf84438c10a7963,The 54th Annual Meeting of the Association for Computational Linguistics,"The54thAnnualMeetingoftheAssociationforComputationalLinguisticsProceedingsoftheConference,Vol.2(ShortPapers)August7-12,2016Berlin,Germany"
+b774d7c951b9c444572085e15f6a81a063abf123,Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification,"FeaturesSpatial AttentionTemporal Attention1 2 3 N‘face’‘torso’‘bag’Figure1.SpatiotemporalAttention.Inchallengingvideore-identificationscenarios,apersonisrarelyfullyvisibleinallframes.However,framesinwhichonlypartofthepersonisvis-ibleoftencontainusefulinformation.Forexample,thefaceisclearlyvisibleintheframes1and2,thetorsoinframe2,andthehandbaginframes2,3andN.Insteadofaveragingfullframefeaturesacrosstime,weproposeanewspatiotemporalapproachwhichlearnstodetectasetofKdiversesalientimageregionswithineachframe(superimposedheatmaps).Anaggregaterep-resentationofeachbodypartisthenproducedbycombiningtheextractedper-frameregionsacrosstime(weightsshownaswhitetext).Ourspatiotemporalapproachcreatesacompactencodingofthevideothatexploitsusefulpartialinformationineachframebyleveragingmultiplespatialattentionmodels,andcombiningtheiroutputsusingmultipletemporalattentionmodels.personre-identification,whichisageneralizationofthestandardimage-basedre-identificationtask.InsteadofarXiv:1803.09882v1 [cs.CV] 27 Mar 2018"
+b7f0d1d65763fb57ee9a3624116a42a2fe763707,Predicting psychological attributions from face photographs with a deep neural network,"Predicting psychological attributions from face +photographs with a deep neural network +Edward Grant1∗, Stephan Sahm1∗, Mariam Zabihi1∗, Marcel van Gerven1 +Radboud University, Nijmegen, the Netherlands +Denotes equal contribution"
+b7c4b22d44be82b2e1074c5c40b76461db4b0292,Generating Multiple Diverse Hypotheses for Human 3D Pose Consistent with 2D Joint Detections,"Generating Multiple Diverse Hypotheses for Human 3D Pose Consistent with 2D +Joint Detections +Ehsan Jahangiri, Alan L. Yuille +Johns Hopkins University, Baltimore, USA"
+b705ca751a947e3b761e2305b41891051525d9df,Exploring Context with Deep Structured Models for Semantic Segmentation,"Exploring Context with Deep Structured models +for Semantic Segmentation +Guosheng Lin, Chunhua Shen, Anton van den Hengel, Ian Reid"
+b7207c142b0b9f4def3ae7cd07ce50ca31d930e8,Human Age Group Prediction from Unknown Facial Image,"Volume 7, Issue 5, May 2017 ISSN: 2277 128X +International Journal of Advanced Research in +Computer Science and Software Engineering +Research Paper +Available online at: www.ijarcsse.com +Human Age Group Prediction from Unknown Facial Image +Arumugam P, 2Muthukumar S, 3Selva Kumar S, 4Gayathri +Department of Statistics, 2, 4 Department of CSE, 3Research Scholar +, 3 Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India +, 4 Varuvan Vadivelan Institute of Technology, Dharmapuri, Tamilnadu, India +DOI: 10.23956/ijarcsse/SV7I5/0103"
+b768cb6fc2616f3dbe9ef4e25dedd7d95781ba66,Distribution Matching in Variational Inference,"Distribution Matching in Variational Inference +Mihaela Rosca Balaji Lakshminarayanan +Shakir Mohamed +DeepMind"
+b7b23814948afc5525975ed44f3dd247100e6722,Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images,"Relevant Feature Selection for Human Pose Estimation +nd Localization in Cluttered Images +Ryuzo Okada(cid:2) and Stefano Soatto +Computer Science Department, University of California, Los Angeles"
+b7216846c743d94fcd43e1b543c9d16ae11d3c48,Engaging Image Chat: Modeling Personality in Grounded Dialogue,"Engaging Image Chat: Modeling Personality in Grounded Dialogue +Kurt Shuster Samuel Humeau Antoine Bordes Jason Weston +{kshuster, samuelhumeau, abordes, jase} +Facebook AI Research"
b7f7a4df251ff26aca83d66d6b479f1dc6cd1085,Handling missing weak classifiers in boosted cascade: application to multiview and occluded face detection,"Bouges et al. EURASIP Journal on Image and Video Processing 2013, 2013:55 http://jivp.eurasipjournals.com/content/2013/1/55 RESEARCH @@ -12724,6 +44289,54 @@ Handling missing weak classifiers in boosted ascade: application to multiview and occluded face detection Pierre Bouges1*, Thierry Chateau1*, Christophe Blanc1 and Gaëlle Loosli2"
+b7d425ea6b476c4af208a6b6a9e84ab17921dab4,Heuristic-based Automatic Face Detection,"HEURISTIC-BASED AUTOMATIC FACE DETECTION +Geovany Ramírez1, Vittorio Zanella1,2, Olac Fuentes2 +Universidad Popular Autónoma del Estado de Puebla +1 sur #1103 Col. Santiago Puebla 72160, México +Instituto Nacional de Astrofísica Optica y Electrónica +Luis Enrique Erro #1 Sta. María Tonantzintla Puebla 72840, México +E-mail:"
+b7a827bb393361c309fbba652967dee11d16857c,Comparative Analysis of various Illumination Normalization Techniques for Face Recognition,"International Journal of Computer Applications (0975 – 8887) +Volume 28– No.9, August 2011 +Comparative Analysis of various Illumination +Normalization Techniques for Face Recognition +Tripti Goel +GPMCE, Delhi +Vijay Nehra +BPSMV, Khanpur +Virendra P.Vishwakarma +JIIT, Noida +explained"
+b704f8360c369e65f0826ca23dac2d4e221d8997,A Knowledge Base for Automatic Feature Recognition from Point Clouds in an Urban Scene,"Article +A Knowledge Base for Automatic Feature Recognition +from Point Clouds in an Urban Scene +Xu-Feng Xing 1,2,* ID , Mir-Abolfazl Mostafavi 1,2 ID and Seyed Hossein Chavoshi 1,2 +Department of Geomatics Sciences, Université Laval, Québec, QC G1V 0A6, Canada; +(M.-A.M.); (S.H.C.) +Center for Research in Geomatics, Université Laval, Québec, QC G1V 0A6, Canada +* Correspondence: Tel.: +1-581-888-9786 +Received: 4 October 2017; Accepted: 11 January 2018; Published: 16 January 2018"
+b7c2173668a4c23b79450111887d8b1e4199f89c,Complex event recognition by latent temporal models of concepts,"COMPLEX EVENT RECOGNITION BY LATENT TEMPORAL MODELS OF CONCEPTS +Ehsan Zare Borzeshi1, Afshin Dehghan2, Massimo Piccardi1, and Mubarak Shah2 +School of Computing and Communications, University of Technology, Sydney (UTS)1, +Centre for Research in Computer Vision, University of Central Florida (UCF)2"
+db85195e171f7b75e4e6f99ed3029d31ee557e13,the influence of a verticality metaphor in the processing of happy and sad faces,"RIPS / IRSP, 27 (2), 51-77 © 2014, Presses universitaires de Grenoble +the influence of a verticality metaphor +in the processing of happy and sad faces +L’influence de la métaphore de verticalité sur le traitement +des émotions faciales de gaieté et de tristesse +Timothée Mahieu*,** +Olivier Corneille** +Vincent Y. Yzerbyt** +Key-words +Metaphorical thinking, +grounded cognition, +facial emotions, gender +Mots-clés +Pensée métaphorique, +ognition incarnée, +émotions faciales, +genre"
db227f72bb13a5acca549fab0dc76bce1fb3b948,Characteristic Based Image Search Using Re-Ranking Method,"International Refereed Journal of Engineering and Science (IRJES) ISSN (Online) 2319-183X, (Print) 2319-1821 Volume 4, Issue 6 (June 2015), PP.169-169-174 @@ -12734,13 +44347,93 @@ dbaf89ca98dda2c99157c46abd136ace5bdc33b3,Nonlinear Cross-View Sample Enrichment Action Recognition Ling Wang, Hichem Sahbi Institut Mines-T´el´ecom; T´el´ecom ParisTech; CNRS LTCI"
+dbe101c7c4b5ea5986be38e4d6de70bfc4324683,1 Deep convolutional neural networks capabilities for 2 binary classification of polar mesocyclones in 3 satellite mosaics 4,"Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 29 October 2018 doi:10.20944/preprints201809.0361.v3 +Article +Deep convolutional neural networks capabilities for +inary classification of polar mesocyclones in +satellite mosaics +Mikhail Krinitskiy 1,*, Polina Verezemskaya 1,2, Kirill Grashchenkov1,3, Natalia Tilinina1, +Sergey Gulev1 and Matthew Lazzara 4 +Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia; +Research Computing Center of Lomonosov Moscow State University, Moscow, Russia +Moscow Institute of Physics and Technology, Moscow, Russia +University of Wisconsin-Madison and Madison Area Technical College, Madison, Wisconsin, USA +* Correspondence: Tel.: +7-926-141-6200"
dbe255d3d2a5d960daaaba71cb0da292e0af36a7,Evolutionary Cost-Sensitive Extreme Learning Machine,"Evolutionary Cost-sensitive Extreme Learning Machine Lei Zhang, Member, IEEE, and David Zhang, Fellow, IEEE"
+db480f100004e3ef075f9404041fe4f89fcf4e0c,Human Pose Estimation for RGBD Imagery with Multi-Channel Mixture of Parts and Kinematic Constraints,"Human Pose Estimation for RGBD Imagery with Multi-Channel +Mixture of Parts and Kinematic Constraints +ENRIQUE MARTINEZ-BERTI +Universitat Politecnica de Valencia +Instituto AI2 +Camino de Vera s/n, Valencia +SPAIN +ANTONIO J. SNCHEZ-SALMERN +Universitat Politecnica de Valencia +CARLOS RICOLFE-VIALA +Universitat Politecnica de Valencia +Instituto AI2 +Camino de Vera s/n, Valencia +SPAIN +Instituto AI2 +Camino de Vera s/n, Valencia +SPAIN +Center for Research in Computer Vision +Center for Research in Computer Vision +OLIVER NINA"
+db6d00f9237cce392c08b422662b48baa2ed1b80,A New Framework for Biometric Face Recognition Using Visual,"Annals of DAAAM for 2012 & Proceedings of the 23rd International DAAAM Symposium, Volume 23, No.1, ISSN 2304-1382 +ISBN 978-3-901509-91-9, CDROM version, Ed. B. Katalinic, Published by DAAAM International, Vienna, Austria, EU, 2012 +Make Harmony between Technology and Nature, and Your Mind will Fly Free as a Bird +Annals & Proceedings of DAAAM International 2012 +A NEW FRAMEWORK FOR BIOMETRIC FACE RECOGNITION USING VISUAL +CRYPTOGRAPY +MIHAILESCU, M[arius] I[ulian] & PIRLOAGA, M[arian] D[orin]"
+dba3ec4420a0bcca3264f75f4c975cabdbb1af74,"""Edutainment 2017"" a visual and semantic representation of 3D face model for reshaping face in images","J Vis (2018) 21:649–660 +https://doi.org/10.1007/s12650-018-0476-4 +R E G UL A R P A P E R +Jiang Du • Dan Song • Yanlong Tang • Ruofeng Tong • Min Tang +‘‘Edutainment 2017’’ a visual and semantic +representation of 3D face model for reshaping face +in images +Received: 15 September 2017 / Revised: 20 December 2017 / Accepted: 22 January 2018 / Published online: 16 February 2018 +Ó The Visualization Society of Japan 2018"
+db24a2c27656db88486479b26f99d8754a44f4b8,Age estimation via face images : a survey,"Angulu et al. EURASIP Journal on Image and Video +Processing (2018) 2018:42 +https://doi.org/10.1186/s13640-018-0278-6 +EURASIP Journal on Image +nd Video Processing +REVIEW +Open Access +Age estimation via face images: a survey +Raphael Angulu1*† +, Jules R. Tapamo2 and Aderemi O. Adewumi1"
dbb0a527612c828d43bcb9a9c41f1bf7110b1dc8,Machine Learning Techniques for Face Analysis,"Chapter 7 Machine Learning Techniques for Face Analysis Roberto Valenti, Nicu Sebe, Theo Gevers, and Ira Cohen"
+dbb065aa2a6e6804e0ab8aee27314a6f68c4cde1,Advanced Hypothesis Testing Techniques and Their Application to Image Classification Advanced Hypothesis Testing Techniques and Their Application to Image Classification Title: Advanced Hypothesis Testing Techniques and Their Application to Image Classification Acknowledgements,"Dipartimento di Informatica e +Scienze dell’Informazione +•• •• +Advanced Hypothesis testing techniques and their +pplication to image classification +Emanuele Franceschi +Theses Series +DISI-TH-2005-XX +DISI, Universit`a di Genova +v. Dodecaneso 35, 16146 Genova, Italy +http://www.disi.unige.it/"
+db458242dd526d84579aeee563355ca1a7dea5ea,Face Detection in Nighttime Images Using Visible-Light Camera Sensors with Two-Step Faster Region-Based Convolutional Neural Network,"Article +Face Detection in Nighttime Images Using +Visible-Light Camera Sensors with Two-Step Faster +Region-Based Convolutional Neural Network +Se Woon Cho, Na Rae Baek, Min Cheol Kim, Ja Hyung Koo, Jong Hyun Kim and +Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pil-dong-ro 1-gil, Jung-gu, +Seoul 04620, Korea; (S.W.C.); (N.R.B.); +(M.C.K.); (J.H.K.); (J.H.K.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 31 July 2018; Accepted: 4 September 2018; Published: 7 September 2018"
dbb7f37fb9b41d1aa862aaf2d2e721a470fd2c57,Face image analysis with convolutional neural networks,"Face Image Analysis With Convolutional Neural Networks Dissertation @@ -12748,6 +44441,16 @@ Zur Erlangung des Doktorgrades der Fakult¨at f¨ur Angewandte Wissenschaften n der Albert-Ludwigs-Universit¨at Freiburg im Breisgau Stefan Duffner"
+db625c4c26c7df67c9099e78961d479532628ec7,"All-in Text: Learning Document, Label, and Word Representations Jointly","Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) +All-in Text: Learning Document, Label, and Word Representations Jointly +Jinseok Nam, Eneldo Loza Menc´ıa, Johannes F¨urnkranz +Knowledge Discovery in Scientific Literature, TU Darmstadt +Knowledge Engineering Group, TU Darmstadt +Research Training Group AIPHES, TU Darmstadt"
+dbb7b563e84903dad4953a8e9f23e3c54c6d7e78,Joint Person Re-identification and Camera Network Topology Inference in Multiple Cameras,"Joint Person Re-identification and Camera Network +Topology Inference in Multiple Cameras +Yeong-Jun Cho, Su-A Kim*, Jae-Han Park*, Kyuewang Lee, Student Member, IEEE +nd Kuk-Jin Yoon, Member, IEEE"
dbd5e9691cab2c515b50dda3d0832bea6eef79f2,Image - based Face Recognition : Issues and Methods 1,"Image-basedFaceRecognition:IssuesandMethods WenYiZhao RamaChellappa @@ -12757,30 +44460,97 @@ CenterforAutomationResearch UniversityofMaryland Princeton,NJ CollegePark,MD +db186bd2a276a574b2246e3e4d136f8a07c53ff2,Verisimilar Percept Sequences Tests for Autonomous Driving Intelligent Agent Assessment,"Verisimilar Percept Sequences Tests for +Autonomous Driving Intelligent Agent Assessment +Thomio Watanabe +University of Sao Paulo +Denis Wolf +University of Sao Paulo"
db67edbaeb78e1dd734784cfaaa720ba86ceb6d2,SPECFACE — A dataset of human faces wearing spectacles,"SPECFACE - A Dataset of Human Faces Wearing Spectacles Anirban Dasgupta, Shubhobrata Bhattacharya and Aurobinda Routray Indian Institute of Technology Kharagpur India"
+db0d33590dc15de2d30cf0407b7a26ae79cd51b5,Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition,"Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition +Alexander Kolesnikov +IST Austria, Am Campus 1, Klosterneuburg, 3400 Austria +Christoph H. Lampert +IST Austria, Am Campus 1, Klosterneuburg, 3400 Austria"
a83fc450c124b7e640adc762e95e3bb6b423b310,Deep Face Feature for Face Alignment and Reconstruction,"Deep Face Feature for Face Alignment Boyi Jiang, Juyong Zhang, Bailin Deng, Yudong Guo and Ligang Liu"
+a84032e66db042a57722b4a3bc7301ebe567fb8b,"IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 01, 2015 | ISSN (online): 2321-0613","IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 01, 2015 | ISSN (online): 2321-0613 +Review of Energy Enhancements of Modified LEACH +Kirti Sharma1 +Department of Electronics & Communication Engineering +Maharishi Ved Vyas Engineering College, Jagadhri, India +using +minimized"
a85e9e11db5665c89b057a124547377d3e1c27ef,Dynamics of Driver's Gaze: Explorations in Behavior Modeling and Maneuver Prediction,"Dynamics of Driver’s Gaze: Explorations in Behavior Modeling & Maneuver Prediction Sujitha Martin, Member, IEEE, Sourabh Vora, Kevan Yuen, and Mohan M. Trivedi, Fellow, IEEE"
+a8ed00afc46064b18a6bcc7aa282e554891eacf2,Underwater image restoration: super-resolution and deblurring via sparse representation and denoising by means of marine snow removal,"Underwater Image Restoration: +Super-resolution and Deblurring via Sparse Representation and +Denoising by Means of Marine Snow Removal +Dissertation +Erlangung des akademischen Grades +Doktor-Ingenieur (Dr.-Ing) +der Fakultät für Informatik und Elektrotechnik +der Universität Rostock +vorgelegt von +Fahimeh Farhadifard +geb. am 05.11.1985 in Mashhad/Iran +us Rostock +Rostock, den 27. Oktober 2017"
+a8420e7fa53b81b8069ced8d9c743c141e2fc432,Real-Time Multiple Object Tracking - A Study on the Importance of Speed,"Real-TimeMultipleObjectTrackingAStudyontheImportanceofSpeedSAMUELMURRAYMaster’sProgramme,MachineLearningDate:September28,2017Supervisor:KevinSmithExaminer:HedvigKjellströmPrincipal:HelmutPrendinger,NationalInstituteofInformatics,TokyoSwedishtitle:IdentifieringavrörligaobjektirealtidSchoolofComputerScienceandCommunication"
+a856449c724f958dbb2f0629228d26a322153ba3,Face Mask Extraction in Video Sequence,"Face Mask Extraction in Video Sequence +Yujiang Wang 1 · Bingnan Luo 1 · Jie Shen 1 · Maja Pantic 1"
a8117a4733cce9148c35fb6888962f665ae65b1e,A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion,"IEEE TRANSACTIONS ON XXXX, VOL. XX, NO. XX, XX 201X A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion Lin Xiong1∗†, Jayashree Karlekar1∗, Jian Zhao2∗†, Jiashi Feng2, Member, IEEE, Sugiri Pranata1, and Shengmei Shen1"
+a8788ce65d01018a0e1b4cdaf6466f495e68f7e3,A Probabilistic Retrieval Model for Word Spotting based on Direct Attribute Prediction,"A Probabilistic Retrieval Model +for Word Spotting based on +Direct Attribute Prediction +Eugen Rusakov, Leonard Rothacker, Hyunho Mo, and Gernot A. Fink +Department of Computer Science +TU Dortmund University +4221 Dortmund, Germany +Email:{eugen.rusakov, leonard.rothacker, hyunho.mo,"
+a8d3dc5c68032c60ebbe3b547ac948d7cf8dd1d8,Multi-Label Zero-Shot Learning via Concept Embedding,"Multi-Label Zero-Shot Learning via Concept +Embedding +Ubai Sandouk and Ke Chen"
a87ab836771164adb95d6744027e62e05f47fd96,Understanding human-human interactions: a survey,"Understanding human-human interactions: a survey Alexandros Stergiou Department of Information and Computing Sciences, Utrecht University,Buys Ballotgebouw, Princetonplein 5, Utrecht, 3584CC, Netherlands Department of Information and Computing Sciences, Utrecht University,Buys Ballotgebouw, Princetonplein 5, Utrecht, 3584CC, Netherlands Ronald Poppe1"
+a81d396c9210282d461f9f08b7b9794b096ecdfe,FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising,"FFDNet: Toward a Fast and Flexible Solution for +CNN based Image Denoising +Kai Zhang, Wangmeng Zuo, Senior Member, IEEE, and Lei Zhang, Fellow, IEEE"
+a8e5d204549fcf93c5bea88b0f99a2e4da9648e7,Neuropeptidergic regulation of affiliative behavior and social bonding in animals.,"www.elsevier.com/locate/yhbeh +Neuropeptidergic regulation of affiliative behavior and +social bonding in animals +Miranda M. Lim 1, Larry J. Young ⁎ +Center for Behavioral Neuroscience, Department of Psychiatry and Behavioral Sciences, and 954 Gatewood Road Yerkes National Primate Research Center, +Emory University, Atlanta, GA 30322, USA +Received 16 May 2006; revised 26 June 2006; accepted 27 June 2006 +Available online 4 August 2006"
a88640045d13fc0207ac816b0bb532e42bcccf36,Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction,"ARXIV VERSION Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction Yanwei Pang, Senior Member, IEEE, Bo Zhou, and Feiping Nie, Senior Member, IEEE"
+a8d41c63462da7dbddf4094eddaa0bb6d72d0fdc,A Semantic-based Method for Visualizing Large Image Collections.,"A Semantic-based Method for +Visualizing Large Image Collections +Xiao Xie, Xiwen Cai, Junpei Zhou, Nan Cao, Yingcai Wu"
+a8eebadc262594d1ca86d5520f312c1779d00b33,Improved Minimum Squared Error Algorithm with Applications to Face Recognition,"Improved Minimum Squared Error Algorithm with +Applications to Face Recognition +Qi Zhu1,2,3, Zhengming Li1,3,4, Jinxing Liu5, Zizhu Fan1,6, Lei Yu7, Yan Chen8* +Bio-Computing Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China, 2 School of Optical-Electrical and Computer Engineering, University +of Shanghai for Science and Technology, Shanghai, China, 3 Key Laboratory of Network Oriented Intelligent Computation, Shenzhen, China, 4 Guangdong Industrial +Training Center, Guangdong Polytechnic Normal University, Guangzhou, China, 5 College of Information and Communication Technology, Qufu Normal University, Rizhao, +China, 6 School of Basic Science, East China Jiaotong University, Nanchang, China, 7 School of Urban Planning and Management, Harbin Institute of Technology Shenzhen +Graduate School, Shenzhen, China, 8 Shenzhen Sunwin Intelligent Co., Ltd., Shenzhen, China"
a8a30a8c50d9c4bb8e6d2dd84bc5b8b7f2c84dd8,This is a repository copy of Modelling of Orthogonal Craniofacial Profiles,"This is a repository copy of Modelling of Orthogonal Craniofacial Profiles. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/131767/ @@ -12818,9 +44588,33 @@ L’archive ouverte pluridisciplinaire HAL, est destin´ee au d´epˆot et `a la diffusion de documents scientifiques de niveau recherche, publi´es ou non, ´emanant des ´etablissements d’enseignement et de"
+a8948941f7a24c09cd7c26f3635d8571c7998570,Face recognition of Pose and Illumination changes using Extended ASM and Robust sparse coding,"IOSR Journal of Dental and Medical Sciences (IOSR-JDMS) +e-ISSN: 2279-0853, p-ISSN: 2279-0861.Volume 13, Issue 3 Ver. VI. (Mar. 2014), PP 49-54 +www.iosrjournals.org +Face recognition of Pose and Illumination changes using +Extended ASM and Robust sparse coding +Arulmurugan R1, Laxmi Priya M.R2 +(Information Technology, Bannari Amman Institute of Technology, India) +(Information Technology, Bannari Amman Institute of Technology, India)"
a8e75978a5335fd3deb04572bb6ca43dbfad4738,Sparse Graphical Representation based Discriminant Analysis for Heterogeneous Face Recognition,"Sparse Graphical Representation based Discriminant Analysis for Heterogeneous Face Recognition Chunlei Peng, Xinbo Gao, Senior Member, IEEE, Nannan Wang, Member, IEEE, and Jie Li"
+a8f032b300b99dedb9c0f8362557302696d5ee9a,Intelligent Video Object Classification Scheme using Offline Feature Extraction and Machine Learning based Approach,"Intelligent Video Object Classification Scheme using Offline Feature Extraction and +Machine Learning based Approach +Chandra Mani Sharma1, Alok Kumar Singh Kushwaha2 ,Rakesh Roshan3 , Rabins Porwal4 and Ashish Khare5 +,3,4Department of Information Technology, Institute of Technology and Science +Ghaziabad, U.P., India +Department of Computer Engg. and Application, G.L.A. University, +Mathura, U.P., India +5 Department of Electronics and Communication, University of Allahabad, +U.P., India"
+a8eeace37181dd87d5125c213add6e15fdd9d9f7,Approximate Fisher Kernels of Non-iid Image Models for Image Categorization,"Approximate Fisher Kernels of non-iid Image +Models for Image Categorization +Ramazan Gokberk Cinbis, Jakob Verbeek, and Cordelia Schmid, Fellow, IEEE"
+a81769a36c9ed7b6146a408eb253eb8e0d3ad41e,Super-Fine Attributes with Crowd Prototyping.,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Super-Fine Attributes +with Crowd Prototyping +Daniel Martinho-Corbishley, Mark S. Nixon and John N. Carter"
ded968b97bd59465d5ccda4f1e441f24bac7ede5,Large scale 3 D Morphable Models,"Noname manuscript No. (will be inserted by the editor) Large scale 3D Morphable Models @@ -12832,24 +44626,195 @@ Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification Yi Wang, Jianwu Wan, Jun Guo, Yiu-Ming Cheung, and Pong C Yuen"
+de87a5d5fbae0733806ba965b2d70fd04596f6e9,Predictive control for autonomous driving with experimental evaluation on a heavy-duty construction truck,"Predictive control for autonomous driving +with experimental evaluation on a heavy-duty construction truck +PEDRO F. LIMA +Licenciate Thesis +Stockholm, Sweden 2016"
+de86a9f484addcfee57a6f5a9224aa77bd23345b,Face Recognition Using Elastic Bunch Graph Matching,"International Journal For Technological Research In Engineering +Volume 2, Issue 11, July-2015 +ISSN (Online): 2347 - 4718 +FACE RECOGNITION USING ELASTIC BUNCH GRAPH +MATCHING +Sandeep R1, D Jayakumar2 +Dept. of ECE, Kuppam Engineering College, Chittoor, Andhra Pradesh."
+de6ab8cd9d402c976082b707b1207c3ad49ae204,End-to-end Image Captioning Exploits Distributional Similarity in Multimodal Space,"MADHYASTHA ET AL.: IMAGE CAPTIONING EXPLOITS DISTRIBUTIONAL SIMILARITY 1 +End-to-end Image Captioning Exploits +Multimodal Distributional Similarity +Pranava Madhyastha +Josiah Wang +Lucia Specia +Department of Computer Science +The University of Sheffield +Sheffield, UK"
+de99971e61613f174c9e5aa41a2c600399f59953,Pixel-wise Attentional Gating for Scene Parsing,"Pixel-wise Attentional Gating for Scene Parsing +Department of Computer Science, University of California, Irvine, CA 92697, USA +Shu Kong, Charless Fowlkes +{skong2,"
+de724211683bb92931a5d80193e5dee31ca2e045,Sampling Design For Face Recognition,"Sampling Design For Face Recognition +Yanjun Yan and Lisa A. Osadciw +EECS, Syracuse University, Syracuse, NY, USA +{yayan,"
+de2faaee4f1b2ecf23149995d0146347a13b9257,Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment,"Robust Unsupervised Domain Adaptation for Neural +Networks via Moment Alignment +Werner Zellingera,∗, Bernhard A. Moserb, Thomas Grubingerb, Edwin +Lughofera, Thomas Natschl¨agerb, Susanne Saminger-Platza +Johannes Kepler University, Linz, Austria +Software Competence Center Hagenberg GmbH, Hagenberg, Austria"
+de309a1d10f819d69a4ef2c26d968d3b287c3dd5,Preprocessing and Feature Sets for Robust Face Recognition,"Preprocessing and Feature Sets for Robust Face Recognition +Xiaoyang Tan and Bill Triggs +LJK-INRIA, 655 avenue de l’Europe, Montbonnot 38330, France"
+dea749f087a8c9a9baa9167b4eaff50bd3eb9d16,Physically Grounded Spatio-temporal Object Affordances,"Physically Grounded Spatio-Temporal +Object Affordances +Hema S. Koppula and Ashutosh Saxena +Department of Computer Science, Cornell University."
+de95fa1dd69a2d0d2b76539357062062f8b1e7b8,Face to Age,"Face to Age +Project 1 +CS395T - Deep Learning Seminar +Aishwarya Padmakumar, Ashish Bora, Amir Gholaminejad +October 9, 2016 +A Century of Portraits is a dataset that contains frontal-facing American high school year-book photos +with labels to indicate the years those photos were taken [2]. +In this project we train classifiers to +predict the label, given the image. We used several Deep Neural Network architectures for this task, +ll of which were finetuned with ImageNet pretraining. With VGGNet architecture, we demonstrate +significant improvements in classification accuracy reporting test set accuracy of 67.59% and mean L1 +error, as compared to 11.31 % achieved by Ginosar et al. [2]. Further, we show some visualizations of +the trained model to gain insights into the learned model. The code for this project can be found at +https://github.com/AshishBora/face2year. +Introduction +Deep Neural networks have been central to large improvements in several visual learning tasks. Feature +representations learned by deep convolutional neural networks for image classification on large datasets +such as ImageNet [1] have been repeatedly demonstrated to be useful for other tasks [6]. Several down- +stream applications have also greatly benefited from these representations, either when used directly +[9, 10] or with appropriate finetuning [3, 5]."
+de0aaf8c6b5dea97327e8ef8060d9a708bf564af,A Benchmark for Iris Location and a Deep Learning Detector Evaluation,"A Benchmark for Iris Location and a Deep +Learning Detector Evaluation +Evair Severo∗, Rayson Laroca∗, Cides S. Bezerra∗, Luiz A. Zanlorensi∗, +Daniel Weingaertner∗, Gladston Moreira† and David Menotti∗ +Postgraduate Program in Informatics, Federal University of Paran´a (UFPR), Curitiba, Paran´a, Brazil +Computing Department, Federal University of Ouro Preto (UFOP), Ouro Preto, Minas Gerais, Brazil +Email: {ebsevero, rblsantos, csbezerra, lazjunior, daniel,"
dee406a7aaa0f4c9d64b7550e633d81bc66ff451,Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning,"Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning Dongyu Zhang, Liang Lin, Tianshui Chen, Xian Wu, Wenwei Tan, and Ebroul Izquierdo"
+dedbbb6e588e77969ab87571917d4f84a3b1722d,Multimodal Human-Human-Robot Interactions (MHHRI) Dataset for Studying Personality and Engagement,"JOURNAL OF IEEE TRANS. ON AFFECTIVE COMPUTING +Multimodal Human-Human-Robot Interactions +(MHHRI) Dataset for Studying Personality and +Engagement +Oya Celiktutan, Efstratios Skordos and Hatice Gunes"
+defcfed9c43bdf8a4388daade4899ef9d3345458,Sistema de reconocimiento multimodal de emociones relacionadas al aprendizaje en dispositivos móviles,"Sistema de reconocimiento multimodal de emociones +relacionadas al aprendizaje en dispositivos móviles +María Lucía Barrón-Estrada, Ramón Zatarain-Cabada, +Claudia Guadalupe Aispuro-Gallegos +Instituto Tecnológico de Culiacán, Culiacán, Sinaloa, +México +{lbarron, rzatarain, +Resumen. Gran variedad de sistemas reconocedores de emociones han sido +implementados, pero pocos han logrado aplicarse en el mundo real debido al +elevado costo de la tecnología necesaria y al bajo porcentaje de efectividad del +reconocimiento, cuando no se trabaja con emociones espontáneas. Este artículo +presenta la implementación de un sistema de reconocimiento multimodal de +emociones usando dispositivos móviles y la creación de una base de datos +fectiva por medio de una aplicación móvil. El reconocedor puede ser integrado +fácilmente a una aplicación educativa móvil para identificar las emociones de un +usuario mientras éste interactúa con el dispositivo. Las emociones que el sistema +reconoce son compromiso y aburrimiento. La base de datos afectiva fue creada +on emociones espontáneas de estudiantes que interactuaron con una aplicación +móvil educativa llamada Duolingo y una aplicación móvil recolectora de +información llamada EmoData. El sistema desarrollado tiene un porcentaje de"
dedabf9afe2ae4a1ace1279150e5f1d495e565da,Robust Face Recognition With Structurally Incoherent Low-Rank Matrix Decomposition,"Robust Face Recognition With Structurally Incoherent Low-Rank Matrix Decomposition Chia-Po Wei, Chih-Fan Chen, and Yu-Chiang Frank Wang"
+de7daa206f1dc3d5f83c5342fc08e3e92ddfa126,Index Codes for Multibiometric Pattern Retrieval,"Index Codes for Multibiometric Pattern Retrieval +Aglika Gyaourova, Student Member, IEEE, and Arun Ross, Senior Member, IEEE"
+de7a148970881cbd4e6a12b6a014e3dfeee98cc9,D 4 h : Final report on WP 4,"D4h: Final report on WP4 +Workpackage 4 Deliverable +Date: 30th January 2008"
de398bd8b7b57a3362c0c677ba8bf9f1d8ade583,Hierarchical Bayesian Theme Models for Multipose Facial Expression Recognition,"Hierarchical Bayesian Theme Models for Multi-pose Facial Expression Recognition Qirong Mao, Member, IEEE, Qiyu Rao, Yongbin Yu, and Ming Dong*, Member, IEEE"
+def3b2254caea169c5cbc4b771c44f1773c004fd,Matching Adversarial Networks,"Matching Adversarial Networks +Gell´ert M´attyus and Raquel Urtasun +Uber Advanced Technologies Group and University of Toronto"
defa8774d3c6ad46d4db4959d8510b44751361d8,FEBEI - Face Expression Based Emoticon Identification CS - B657 Computer Vision,"FEBEI - Face Expression Based Emoticon Identification CS - B657 Computer Vision Nethra Chandrasekaran Sashikar - necsashi Prashanth Kumar Murali - prmurali Robert J Henderson - rojahend"
+de48bb3a9974f6f1ed2aa36d066150015f9f8647,Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering,"I.J. Information Technology and Computer Science, 2013, 06, 1-9 +Published Online May 2013 in MECS (http://www.mecs-press.org/) +DOI: 10.5815/ijitcs.2013.06.01 +Ultrasound Image Despeckling using Local +Binary Pattern Weighted Linear Filtering +Digital Image Processing Lab, Dept. of Computer Applications, Cochin University of Science and Technology, Kerala, +Simily Joseph, Kannan Balakrishnan +E-mail: {simily.joseph, +India +M.R. Balachandran Nair +Ernakulam Scan Center, Kerala, India +E-mail: +Reji Rajan Varghese +Dept. of Biomedical Engineering, Co operative Medical College, Kerala, India +E-mail:"
+de26c1560db47f63ef2dc8171d7c2c52369ffede,Mathematically inspired approaches to face recognition in uncontrolled conditions : super resolution and compressive sensing,"MATHEMATICALLY INSPIRED +APPROACHES TO +FACE RECOGNITION IN +UNCONTROLLED CONDITIONS - +SUPER RESOLUTION AND +COMPRESSIVE SENSING +NADIA AL-HASSAN +Applied Computing Department +The University of Buckingham / United Kingdom +A Thesis +Submitted for the Degree of Doctor of Philosophy in Mathematical +Science to the school of Science and Medicine in the University of +Buckingham +September 2014"
+b0c3bc3e3ca143444f5193735f2aad89d1776276,Training Generative Reversible Networks,"Training Generative Reversible Networks +Robin Tibor Schirrmeister 1 2 Patryk Chrab ˛aszcz 2 Frank Hutter 2 Tonio Ball 1"
b08203fca1af7b95fda8aa3d29dcacd182375385,Object and Text-guided Semantics for CNN-based Activity Recognition,"OBJECT AND TEXT-GUIDED SEMANTICS FOR CNN-BASED ACTIVITY RECOGNITION (cid:63)Sungmin Eum †§, (cid:63)Christopher Reale †, Heesung Kwon†, Claire Bonial †, Clare Voss† U.S. Army Research Laboratory, Adelphi, MD, USA §Booz Allen Hamilton Inc., McLean, VA, USA"
+b04d4b1e8b510180726f49a66dbaaf23c9ef64a0,Introspective Generative Modeling: Decide Discriminatively,"Introspective Generative Modeling: Decide Discriminatively +Justin Lazarow ∗ +Dept. of CSE +Long Jin∗ +Dept. of CSE +Zhuowen Tu +Dept. of CogSci"
+b00796447d670f9413e831ffb4ed548a380816a2,Servoing across object instances: Visual servoing for object category,"Servoing Across Object Instances: Visual Servoing for Object Category +Harit Pandya1, K Madhava Krishna1 and C. V. Jawahar1"
+b008d973ee93fd3b13d1148fb7533dbdbc8374d6,New Representations for Analyzing Motion and Applications,"New Representations for Analyzing Motion and Applications +Ce Liu +Submitted to the Department of Electrical Engineering and Computer Science in partial +fulfillment of the requirements for the degree of +Doctor of Philosophy +Electrical Engineering and Computer Science +t the Massachusetts Institute of Technology +June 2009 +(cid:13) 2009 Massachusetts Institute of Technology +All Rights Reserved. +Signature of Author: +Certified by: +Accepted by: +Department of Electrical Engineering and Computer Science +May 1, 2009 +William T. Freeman, Professor of EECS +Thesis Supervisor +Terry P. Orlando, Professor of Electrical Engineering +Chair, Department Committee on Graduate Students"
+b02342a423eef6e19f473eba26b067405b525f16,Co-occurrence matrix analysis-based semi-supervised training for object detection,"CO-OCCURRENCE MATRIX ANALYSIS-BASED SEMI-SUPERVISED TRAINING FOR +OBJECT DETECTION +Min-Kook Choi1, Jaehyeong Park1, Jihun Jung1, Heechul Jung2, Jin-Hee Lee1, +Woong Jae Won1, Woo Young Jung1, Jincheol Kim3, and Soon Kwon1∗ +DGIST, Daegu, Republic of Korea1 +KAIST, Daejeon, Republic of Korea2 +SK Telecom, Seoul, Republic of Korea3"
+b0d607d5e9e79540c9f2673f2224b2d51be3393c,Kernel Truncated Regression Representation for Robust Subspace Clustering,"Kernel Truncated Regression Representation for +Robust Subspace Clustering +Liangli Zhen, Dezhong Peng, Xin Yao"
b09b693708f412823053508578df289b8403100a,Two-Stream SR-CNNs for Action Recognition in Videos,"WANG et al.: TWO-STREAM SR-CNNS FOR ACTION RECOGNITION IN VIDEOS Two-Stream SR-CNNs for Action Recognition in Videos @@ -12864,12 +44829,109 @@ Zurich, Switzerland Computer Vision Lab ETH Zurich Zurich, Switzerland"
+b0a376888a33defd6fcfe396a11e6ea6d4f99f0e,Soft Measure of Visual Token Occurrences for Object Categorization,"Soft Measure of Visual Token Occurrences for +Object Categorization +Yanjie Wang, Xiabi Liu(cid:2), and Yunde Jia +Beijing Laboratory of Intelligent Information Technology, School of Computer +Science, Beijing Institute of Technology +Tel.: +86-10-68913447, Fax: +86-10-86343158"
+b05ac3b2286c30fcab385f682b3519a823857112,UvA-DARE ( Digital Academic Repository ) Spatial frequency information modulates response inhibition and decision-making processes,"UvA-DARE (Digital Academic Repository) +Spatial frequency information modulates response inhibition and decision-making +processes +Jahfari, S.; Ridderinkhof, K.R.; Scholte, H.S. +Published in: +PLoS One +0.1371/journal.pone.0076467 +Link to publication +Citation for published version (APA): +Jahfari, S., Ridderinkhof, K. R., & Scholte, H. S. (2013). Spatial frequency information modulates response +inhibition and decision-making processes. PLoS One, 8(10), e76467. [e76467]. DOI: +0.1371/journal.pone.0076467 +General rights +It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +Disclaimer/Complaints regulations +If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask +the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, +The Netherlands. You will be contacted as soon as possible."
+b0fafe26b03243a22e12b021266872afdb96572c,Factors of Transferability for a Generic ConvNet Representation,"Factors of Transferability for a Generic ConvNet Representation +Hossein Azizpour, Ali Sharif Razavian, Josephine Sullivan, Atsuto Maki, Stefan Carlsson +{azizpour, razavian, sullivan, atsuto, +Computer Vision and Active Perception (CVAP), Royal Institute of Technology (KTH), Stockholm, SE-10044 Sweden +Evidence is mounting that Convolutional Networks (ConvNets) are the most effective representation learning method for visual +recognition tasks. In the common scenario, a ConvNet is trained on a large labeled dataset (source) and the feed-forward units +ctivation of the trained network, at a certain layer of the network, is used as a generic representation of an input image for a +task with relatively smaller training set (target). Recent studies have shown this form of representation transfer to be suitable for a +wide range of target visual recognition tasks. This paper introduces and investigates several factors affecting the transferability of +such representations. It includes parameters for training of the source ConvNet such as its architecture, distribution of the training +data, etc. and also the parameters of feature extraction such as layer of the trained ConvNet, dimensionality reduction, etc. Then, +y optimizing these factors, we show that significant improvements can be achieved on various (17) visual recognition tasks. We +further show that these visual recognition tasks can be categorically ordered based on their distance from the source task such that +correlation between the performance of tasks and their distance from the source task w.r.t. the proposed factors is observed. +Index Terms—Convolutional Neural Networks, Transfer Learning, Representation Learning, Deep Learning, Visual Recognition +I. INTRODUCTION +C ONVOLUTIONAL NETWORKS (ConvNets) trace back +to the early works on digit and character recognition +[11], [23]. Prior to 2012, though, in computer vision field, +neural networks were more renowned for their propensity to"
+b0d6e204c36f029300787f6334cb727325f8983a,Neural networks related to dysfunctional face processing in autism spectrum disorder,"Brain Struct Funct +DOI 10.1007/s00429-014-0791-z +O R I G I N A L A R T I C L E +Neural networks related to dysfunctional face processing +in autism spectrum disorder +Thomas Nickl-Jockschat • Claudia Rottschy • +Johanna Thommes • Frank Schneider • +Angela R. Laird • Peter T. Fox • Simon B. Eickhoff +Received: 6 September 2013 / Accepted: 28 April 2014 +Ó Springer-Verlag Berlin Heidelberg 2014"
b07582d1a59a9c6f029d0d8328414c7bef64dca0,Employing Fusion of Learned and Handcrafted Features for Unconstrained Ear Recognition,"Employing Fusion of Learned and Handcrafted Features for Unconstrained Ear Recognition Maur´ıcio Pamplona Segundo∗† Earnest E. Hansley∗ Sudeep Sarkar∗‡ October 24, 2017"
+b0c651f23516055583060e2197756e1390455de5,Multimodal Verification of Identity for a Realistic Access Control Application,"Multimodal Verification of Identity for a +Realistic Access Control Application +Thesis submitted in partial fulfilment of the requirements for the degree +Doctor Ingeneriae +Mechanical Engineering +Rand Afrikaans University +Supervisor: Professor A.L. Nel +Nele Denys +t the +May 2004"
+b0b628bda8a6c4267eeaf91420b8610400ff398f,Intact emotion facilitation for nonsocial stimuli in autism: is amygdala impairment in autism specific for social information?,"Journal of the International Neuropsychological Society (2008), 14, 42–54. +Copyright © 2008 INS. Published by Cambridge University Press. Printed in the USA. +DOI: 10.10170S1355617708080107 +Intact emotion facilitation for nonsocial stimuli in autism: +Is amygdala impairment in autism specific +for social information? +MIKLE SOUTH,1,2 SALLY OZONOFF,3 YANA SUCHY,1,4 RAYMOND P. KESNER,1,4 +WILLIAM M. McMAHON,2,4 and JANET E. LAINHART2,4 +Department of Psychology, University of Utah, Salt Lake City, Utah +Department of Psychiatry, University of Utah School of Medicine and Utah Autism Research Project, Salt Lake City, Utah +M.I.N.D. Institute, Department of Psychiatry and Behavioral Sciences, University of California–Davis, Sacramento, California +The Brain Institute at the University of Utah, Salt Lake City, Utah +(Received April 25, 2007; Final Revision July 11, 2007; Accepted July 18, 2007)"
+b0c379f740292ad2cad2c990a445f69167e18894,Knowledge distillation using unlabeled mismatched images,"Workshop track - ICLR 2017 +KNOWLEDGE DISTILLATION USING UNLABELED MIS- +MATCHED IMAGES +Mandar Kulkarni(*), Kalpesh Patil(**), Shirish Karande(*) +TCS Innovation Labs, Pune, India (*), IIT Bombay, Mumbai, India(**)"
+b0771b7ca52022b37a563464f823af67c0b36c03,Image Retrieval Technique Using Local Binary Pattern (LBP),"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438 +Image Retrieval Technique Using Local Binary +Pattern (LBP) +Miss. Priyanka Pawar1, P.P.Belagali2 +P.G Student, Department of Electronics Engineering, Shivaji University, Dr.J.J.M.C.O.E Jaysingpur, Kolhapur, India +Associate Professor, Department of Electronics Engineering, Shivaji University, Dr.J.J.M.C.O.E Jaysingpur, Kolhapur, India"
+b07546f26a99b61c5045e313bc024b0fe7de590a,Bilinear CNNs for Fine-grained Visual Recognition,"Bilinear CNNs for Fine-grained Visual +Recognition +Tsung-Yu Lin +Aruni RoyChowdhury +Subhransu Maji"
b0c1615ebcad516b5a26d45be58068673e2ff217,How Image Degradations Affect Deep CNN-Based Face Recognition?,"How Image Degradations Affect Deep CNN-based Face Recognition? S¸amil Karahan1 Merve Kılınc¸ Yıldırım1 Kadir Kırtac¸1 Ferhat S¸ ¨ukr¨u Rende1 @@ -12878,6 +44940,14 @@ b0de0892d2092c8c70aa22500fed31aa7eb4dd3f,A Robust and Efficient Video Representa A robust and efficient video representation for action recognition Heng Wang · Dan Oneata · Jakob Verbeek · Cordelia Schmid Received: date / Accepted: date"
+b0623c1d8493d273d704ba1d0413db0de579ae77,Attributes-Based Re-identification,"Attributes-based Re-Identification +Ryan Layne, Timothy M. Hospedales and Shaogang Gong"
+b0158b26f01d5fa18aac51ece055cad9a12f6d87,Memory-based Gait Recognition,"Pages 82.1-82.12 +DOI: https://dx.doi.org/10.5244/C.30.82"
+b0e7c177084be76fb73df3c4bcf1846676a2d615,Joint action recognition and pose estimation from video,"Joint Action Recognition and Pose Estimation From Video +Bruce Xiaohan Nie, Caiming Xiong and Song-Chun Zhu +Center for Vision, Cognition, Learning and Art +University of California, Los Angeles, USA"
b073313325b6482e22032e259d7311fb9615356c,Robust and accurate cancer classification with gene expression profiling,"Robust and Accurate Cancer Classification with Gene Expression Profiling Haifeng Li Keshu Zhang @@ -12891,16 +44961,108 @@ Motorola, Inc. Tempe, AZ 85282 University of California Riverside, CA 92521"
+b03d5ed5b3f253703fa37d6445fab0e7cdf38ba1,Separate-Group Covariance Estimation With Insufficient Data for Object Recognition,"Separate-Group Covariance Estimation With Insufficient Data for +Object Recognition +Carlos Eduardo Thomaz1, Raul Queiroz Feitosa2, Álvaro Veiga3 +,2,3Catholic University of Rio de Janeiro +Department of Electrical Engineering +Department of Computer Engineering +University of Rio de Janeiro +r. Marquês de São Vicente 225,22453-900, Rio de +r. São Francisco Xavier, 524, 20559-900, Rio de +Janeiro, Brazil +Janeiro, Brazil"
+a6e7513371a49cd7b8b30bb444e8fc448c5326cb,Simple online and realtime tracking,"SIMPLE ONLINE AND REALTIME TRACKING +Alex Bewley†, Zongyuan Ge†, Lionel Ott(cid:5), Fabio Ramos(cid:5), Ben Upcroft† +Queensland University of Technology†, University of Sydney(cid:5)"
+a66373beaad40fb5a8e2e1b42c5a2213b166a55c,Childhood abuse is related to working memory impairment for positive emotion in female university students.,"Childhood abuse is related to working memory impairment for positive +emotion in female university students +Cromheeke S, Herpoel LA, Mueller SC. +014; 19(1):38-48 +ARTICLE IDENTIFIERS +DOI: 10.1177/1077559513511522 +PMID: 24271026 +PMCID: not available +JOURNAL IDENTIFIERS +LCCN: not available +pISSN: 1077-5595 +eISSN: 1552-6119 +OCLC ID: 30832620 +CONS ID: sn 94001296 +US National Library of Medicine ID: 9602869 +This article was identified from a query of the SafetyLit database. +Powered by TCPDF (www.tcpdf.org)"
a66d89357ada66d98d242c124e1e8d96ac9b37a0,Failure Detection for Facial Landmark Detectors,"Failure Detection for Facial Landmark Detectors Andreas Steger, Radu Timofte, and Luc Van Gool Computer Vision Lab, D-ITET, ETH Zurich, Switzerland {radu.timofte,"
+a62ca056821a3179b116662b28338433ba5b5e7d,How far can we go without convolution: Improving fully-connected networks,"Under review as a conference paper at ICLR 2016 +HOW FAR CAN WE GO WITHOUT CONVOLUTION: IM- +PROVING FULLY-CONNECTED NETWORKS +Zhouhan Lin & Roland Memisevic +Universit´e de Montr´eal +Canada +{zhouhan.lin, +Kishore Konda +Goethe University Frankfurt +Germany"
+a649bc66524e5e61e4d34cc00159099b6b58db2f,Large-Scale Image Geolocalization,"Chapter 3 +Large-Scale Image Geolocalization +James Hays and Alexei A. Efros"
+a65c76169bdb8479353806556f61bf94fdec7e10,Online Object Tracking With Sparse Prototypes,"Online Object Tracking With Sparse Prototypes +Dong Wang, Huchuan Lu, Member, IEEE, and Ming-Hsuan Yang, Senior Member, IEEE"
+a6f477f3c1cb2ab230fe8d89c31ae6af0b9c2346,Relevance Subject Machine: A Novel Person Re-identification Framework,"Relevance Subject Machine: A Novel Person +Re-identification Framework +Igor Fedorov, Student Member, IEEE, Ritwik Giri, Student Member, IEEE, Bhaskar D. Rao, Fellow, IEEE, +Truong Q. Nguyen, Fellow, IEEE"
+a63638b26d36bab8db10bd95fb287c727bab33ec,Joint Sparse and Low-Rank Representation for Emotion Recognition,"MAY 2014 +Joint Sparse and Low-Rank Representation for +Emotion Recognition +Xiang Xiang, Fabian Prada, Hao Jiang"
+a60146c458adfe9207f015d7a77cb7dfb54f744f,Understanding Dynamic Social Grouping Behaviors of Pedestrians,"Understanding Dynamic Social Grouping +Behaviors of Pedestrians +Linan Feng, Student Member, IEEE, and Bir Bhanu, Fellow, IEEE"
a608c5f8fd42af6e9bd332ab516c8c2af7063c61,Age Estimation via Grouping and Decision Fusion,"Age Estimation via Grouping and Decision Fusion Kuan-Hsien Liu, Member, IEEE, Shuicheng Yan, Senior Member, IEEE, nd C.-C. Jay Kuo, Fellow, IEEE"
a6eb6ad9142130406fb4ffd4d60e8348c2442c29,"Video Description: A Survey of Methods, Datasets and Evaluation Metrics","Video Description: A Survey of Methods, Datasets and Evaluation Metrics Nayyer Aafaq, Syed Zulqarnain Gilani, Wei Liu, and Ajmal Mian"
+a65e953df1dbc007862f8eaa8c12ceb225d15837,Robust Head-shoulder Detection using Deformable Part-based Models,"Robust Head-shoulder Detection using Deformable Part-based Models +Enes Dayangac, Christian Wiede, Julia Richter and Gangolf Hirtz +Faculty of Electrical Engineering and Information Technology, Technische Universit¨at Chemnitz, +Chemnitz, Germany +Keywords: +Person Detection, Head-shoulder Detection, Ambient Assisted Living, Latent SVM, DPM, ACF-Detector."
+a618cc9c513762d4eb5db2f7f7b686e7e2b758ca,Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction,"Learning Semi-Riemannian Metrics +for Semisupervised Feature Extraction +Wei Zhang, Zhouchen Lin, Senior Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
+a67e7ca0c7e1e3020169b5c59dc492e9f62f0022,3d Face Recognition Performance under Adversarial Conditions,
+a6404e91af8d1644aa7eea307ffceefa715dd7ea,Human Motion Capture Using a Drone,"Human Motion Capture Using a Drone +Xiaowei Zhou, Sikang Liu, Georgios Pavlakos, Vijay Kumar, Kostas Daniilidis"
+a67d54cf585c9491ab8a3e2d58d9c4b223359602,Spatial information and end-to-end learning for visual recognition. (Informations spatiales et apprentissage bout-en-bout pour la reconnaissance visuelle),"Spatial information and end-to-end learning for visual +recognition +Mingyuan Jiu +To cite this version: +Mingyuan Jiu. Spatial information and end-to-end learning for visual recognition. Computer Science +[cs]. INSA de Lyon, 2014. English. <NNT : 2014ISAL0038>. <tel-01127462> +HAL Id: tel-01127462 +https://tel.archives-ouvertes.fr/tel-01127462 +Submitted on 7 Mar 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de +recherche français ou étrangers, des laboratoires"
+a6a6cfae45e8633c01793debf43592b7d515f65d,From ImageNet to Mining: Adapting Visual Object Detection with Minimal Supervision,"From ImageNet to Mining: Adapting Visual +Object Detection with Minimal Supervision +Alex Bewley and Ben Upcroft"
a6590c49e44aa4975b2b0152ee21ac8af3097d80,3D Interpreter Networks for Viewer-Centered Wireframe Modeling,"https://doi.org/10.1007/s11263-018-1074-6 D Interpreter Networks for Viewer-Centered Wireframe Modeling Jiajun Wu1 · Tianfan Xue2 · Joseph J. Lim3 · Yuandong Tian4 · @@ -12914,12 +45076,46 @@ a6ce2f0795839d9c2543d64a08e043695887e0eb,Driver Gaze Region Estimation Without U Without Using Eye Movement Lex Fridman, Philipp Langhans, Joonbum Lee, and Bryan Reimer Massachusetts Institute of Technology (MIT)"
+a6161e53d77d7cbd6e69d1b84e6d03d7041cb93e,Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime,"Dark Model Adaptation: Semantic Image Segmentation from Daytime +to Nighttime +Dengxin Dai1 and Luc Van Gool1,2"
+a6eb8cb1c35d0f53f8d2c9a404e374c01275544b,NovaSearch on Medical ImageCLEF 2013,"NovaSearch on medical ImageCLEF 2013 +Andr´e Mour˜ao, Fl´avio Martins and Jo˜ao Magalh˜aes +Universidade Nova de Lisboa, Faculdade de Ciˆencias e Tecnologia, +Caparica, Portugal,"
a6ebe013b639f0f79def4c219f585b8a012be04f,Facial Expression Recognition Based on Hybrid Approach,"Facial Expression Recognition Based on Hybrid Approach Md. Abdul Mannan, Antony Lam, Yoshinori Kobayashi, and Yoshinori Kuno Graduate School of Science and Engineering, Saitama University, 55 Shimo-Okubo, Sakura-ku, Saitama-shi, Saitama 338-8570, Japan E-mail"
+a6574d111bfb12d6a9988bdbbf24639d3c4534ec,Image denoising: Can plain neural networks compete with BM3D?,"Image denoising: Can plain Neural Networks compete with BM3D? +Harold C. Burger, Christian J. Schuler, and Stefan Harmeling +Max Planck Institute for Intelligent Systems, T¨ubingen, Germany +http://people.tuebingen.mpg.de/burger/neural_denoising/"
+b98aec5bbe7116fa3ae5f9b4d77cb1f1141eaabd,Appearance-Based 3D Upper-Body Pose Estimation and Person Re-identification on Mobile Robots,"Appearance-Based 3D Upper-Body Pose Estimation +nd Person Re-Identification on Mobile Robots +Christoph Weinrich, Michael Volkhardt, Horst-Michael Gross +Neuroinformatics and Cognitive Robotics Lab +Ilmenau University of Technology +Ilmenau, Germany"
+b9bd9cab426f4d4a0b0d0077f6d9dca2ec01ce3c,Propositionalisation of Multi-instance Data Using Random Forests,"Propositionalisation of Multi-instance Data +using Random Forests +Eibe Frank and Bernhard Pfahringer +Department of Computer Science, University of Waikato"
+b9953824b3d4cd2be77ecbc5db3f7dec3dfa031e,Guided Attention for Large Scale Scene Text Verification,"Large Scale Scene Text Verification with Guided +Attention +Dafang He1(cid:63), Yeqing Li2∗, Alexander Gorban2, Derrall Heath2, Julian Ibarz2, +Qian Yu2, Daniel Kifer1, C. Lee Giles1 +The Pennsylvania State University1, Google Inc2."
+b9fb66f09b358a4ce167b54eed8c596772a392d9,Modal Regression based Atomic Representation for Robust Face Recognition,"Modal Regression based Atomic Representation for +Robust Face Recognition +Yulong Wang, Yuan Yan Tang, Life Fellow, IEEE, Luoqing Li, and Hong Chen"
+b9696bdba6e16959258bad17ce26e6a643be5faf,Using Photometric Stereo for Face Recognition,"International Journal of Bio-Science and Bio-Technology +Vol. 3, No. 3, September, 2011 +Using Photometric Stereo for Face Recognition +Gary A. Atkinson and Melvyn L. Smith +University of the West of England, Bristol, BS16 1QY, UK"
b97f694c2a111b5b1724eefd63c8d64c8e19f6c9,Group Affect Prediction Using Multimodal Distributions,"Group Affect Prediction Using Multimodal Distributions Saqib Nizam Shamsi Aspiring Minds @@ -12927,6 +45123,15 @@ Bhanu Pratap Singh Univeristy of Massachusetts, Amherst Manya Wadhwa Johns Hopkins University"
+b94e57ee9278f06c65a96ce1b586cb7a5b2b7fbb,Group Re-identification via Unsupervised Transfer of Sparse Features Encoding,"Group Re-Identification via +Unsupervised Transfer of Sparse Features Encoding +Giuseppe Lisanti∗,1, Niki Martinel∗,2, Alberto Del Bimbo1 and Gian Luca Foresti2 +MICC - University of Firenze, Italy +AViReS Lab - University of Udine, Italy"
+b9305c065b3c95fd0844d16a09fb9cc7c321cf58,Detecting Humans in Dense Crowds Using Locally-Consistent Scale Prior and Global Occlusion Reasoning,"Detecting Humans in Dense Crowds Using +Locally-Consistent Scale Prior and Global +Occlusion Reasoning +Haroon Idrees, Member, IEEE, Khurram Soomro, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
b9d0774b0321a5cfc75471b62c8c5ef6c15527f5,Fishy Faces: Crafting Adversarial Images to Poison Face Authentication,"Fishy Faces: Crafting Adversarial Images to Poison Face Authentication Giuseppe Garofalo Vera Rimmer @@ -12947,14 +45152,76 @@ Boyi Jiang, Juyong Zhang, Bailin Deng, Yudong Guo and Ligang Liu" b9f2a755940353549e55690437eb7e13ea226bbf,Unsupervised Feature Learning from Videos for Discovering and Recognizing Actions,"Unsupervised Feature Learning from Videos for Discovering and Recognizing Actions Carolina Redondo-Cabrera Roberto J. López-Sastre"
+b9e82ee9bb4cf016b5ed44b7acd2b42e1a5a6be2,Face recognition by applying wavelet subband representation and kernel associative memory,"Face Recognition by Applying Wavelet Subband +Representation and Kernel Associative Memory +Bai-Ling Zhang, Haihong Zhang, and Shuzhi Sam Ge, Senior Member, IEEE"
+b941d4a85be783a6883b7d41c1afa7a9db451831,Radiofrequency ablation planning for cardiac arrhythmia treatment using modeling and machine learning approaches,"Radiofrequency ablation planning for cardiac +rrhythmia treatment using modeling and machine +learning approaches +Roc´ıo Cabrera Lozoya +To cite this version: +Roc´ıo Cabrera Lozoya. Radiofrequency ablation planning for cardiac arrhythmia treatment +using modeling and machine learning approaches. Other. Universit´e Nice Sophia Antipolis, +015. English. <NNT : 2015NICE4059>. <tel-01206478v2> +HAL Id: tel-01206478 +https://tel.archives-ouvertes.fr/tel-01206478v2 +Submitted on 15 Dec 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
+b9b7b37d7edf4482a6f440e282c3418ab1913afa,ThiNet: Pruning CNN Filters for a Thinner Net.,"ACCEPTED BY IEEE TRANS. PAMI +ThiNet: Pruning CNN Filters for a Thinner Net +Jian-Hao Luo, Hao Zhang, Hong-Yu Zhou, Chen-Wei Xie, Jianxin Wu, Member, IEEE, +nd Weiyao Lin, Senior Member, IEEE"
+b92a057606a47eb7de6ecc180e4dbf53c4a8d4b7,Face Recognition Based on 2D and 3D Features,"Face Recognition Based on 2D and 3D Features +Stefano Arca, Ra(cid:11)aella Lanzarotti, and Giuseppe Lipori +Dipartimento di Scienze dell’Informazione +Universit(cid:18)a degli Studi di Milano +Via Comelico, 39/41 20135 Milano, Italy +farca, lanzarotti,"
b9cedd1960d5c025be55ade0a0aa81b75a6efa61,Inexact Krylov Subspace Algorithms for Large Matrix Exponential Eigenproblem from Dimensionality Reduction,"INEXACT KRYLOV SUBSPACE ALGORITHMS FOR LARGE MATRIX EXPONENTIAL EIGENPROBLEM FROM DIMENSIONALITY REDUCTION GANG WU∗, TING-TING FENG† , LI-JIA ZHANG‡ , AND MENG YANG§"
+b95acfe00686cc6f6526fcd1f30b6f38061d3a29,Revisiting Multiple-Instance Learning Via Embedded Instance Selection,"Revisiting Multiple-Instance Learning via +Embedded Instance Selection +James Foulds and Eibe Frank +Department of Computer Science, University of Waikato, New Zealand"
b971266b29fcecf1d5efe1c4dcdc2355cb188ab0,On the Reconstruction of Face Images from Deep Face Templates.,"MAI et al.: ON THE RECONSTRUCTION OF FACE IMAGES FROM DEEP FACE TEMPLATES On the Reconstruction of Face Images from Deep Face Templates Guangcan Mai, Kai Cao, Pong C. Yuen∗, Senior Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
+a14260cd8c607afc6a9bd0c4df2ee22162e6d8c0,Discriminative Dictionary Learning With Ranking Metric Embedded for Person Re-Identification,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+a13a4e4cc8f4744b40668fe7cca660ae0e88537d,Explorer Multi 30 K : Multilingual English-German Image Descriptions,"Multi30K: Multilingual English-German Image Descriptions +Citation for published version: +Elliott, D, Frank, S, Sima'an, K & Specia, L 2016, Multi30K: Multilingual English-German Image +Descriptions. in Proceedings of the 5th Workshop on Vision and Language, hosted by the 54th Annual +Meeting of the Association for Computational Linguistics, 2016, August 12, Berlin, Germany. +Association for Computational Linguistics (ACL), pp. 70-74. +Link: +Link to publication record in Edinburgh Research Explorer +Document Version: +Publisher's PDF, also known as Version of record +Published In: +Proceedings of the 5th Workshop on Vision and Language, hosted by the 54th Annual Meeting of the +Association for Computational Linguistics, 2016, August 12, Berlin, Germany +General rights +Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +nd / or other copyright owners and it is a condition of accessing these publications that users recognise and +bide by the legal requirements associated with these rights. +Take down policy +The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer +ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please"
+a11600deb182677f4fe586fcea59f10d032a6c6f,Active Appearance Models with Rotation Invariant Kernels,"Active Appearance Models with Rotation Invariant Kernels +Onur C. Hamsici and Aleix M. Martinez +Department of Electrical and Computer Engineering +Ohio State University, Columbus, OH 43210"
a158c1e2993ac90a90326881dd5cb0996c20d4f3,Symmetry as an Intrinsically Dynamic Feature,"OPEN ACCESS ISSN 2073-8994 Article @@ -12967,6 +45234,17 @@ Deceased on 15 March 2009. * Author to whom correspondence should be addressed; E-Mail: Received: 4 March 2010; in revised form: 23 March 2010 / Accepted: 29 March 2010 / Published: 1 April 2010"
+a1e198454bd0868b4da9bca7a35218dd235cfdda,3d‐facial Expression Synthesis and Its Application to Face Recognition Systems,"D‐Facial Expression Synthesis and its Application to Face Recognition Systems +Leonel Ramírez‐Valdez1, Rogelio Hasimoto‐Beltran2 +,2Centro de Investigación en Matemáticas(CIMAT) +Jalisco s/n, Col. Mineral de Valenciana, Guanajuato, Gto., México 36240"
+a15f4e3adb56dbbdd6f922489efef48fc5efa003,Grounding Semantic Roles in Images,"Grounding Semantic Roles in Images +Carina Silberer†♣ +Manfred Pinkal† +Department of Computational Linguistics +Saarland University, Saarbr¨ucken, Germany +♣Universitat Pompeu Fabra +Barcelona, Spain"
a15d9d2ed035f21e13b688a78412cb7b5a04c469,Object Detection Using Strongly-Supervised Deformable Part Models,"Object Detection Using Strongly-Supervised Deformable Part Models Hossein Azizpour1 and Ivan Laptev2 @@ -12976,6 +45254,31 @@ a1b1442198f29072e907ed8cb02a064493737158,Crowdsourcing Facial Responses to Onlin to Online Videos Daniel McDuff, Student Member, IEEE, Rana El Kaliouby, Member, IEEE, and Rosalind W. Picard, Fellow, IEEE"
+a125bc46fee1bd170a0654b8856d3b78d62e9d29,Learning weighted sparse representation of encoded facial normal information for expression-robust 3D face recognition,"Learning Weighted Sparse Representation of Encoded Facial Normal +Information for Expression-Robust 3D Face Recognition +Huibin Li1,2, Di Huang1,2, Jean-Marie Morvan1,3,4, Liming Chen1,2 +Universit´e de Lyon, CNRS, 2Ecole Centrale de Lyon, LIRIS UMR5205, F-69134, Lyon, France +Universit´e Lyon 1, Institut Camille Jordan, 43 blvd. du 11 Nov. 1918, F-69622 Villeurbanne - Cedex, France +King Abdullah University of Science and Technology, GMSV Research Center, Bldg 1, Thuwal 23955-6900, Saudi Arabia"
+a175f20189f028a1420b76ae42f6dfe99d8d6847,Where and Why Are They Looking ? Jointly Inferring Human Attention and Intentions in Complex Tasks,"Where and Why Are They Looking? Jointly Inferring Human Attention and +Intentions in Complex Tasks +Ping Wei1,2, Yang Liu2, Tianmin Shu2, Nanning Zheng1, and Song-Chun Zhu2 +School of Electronic and Information Engineering, Xi’an Jiaotong University, China +Center for Vision, Cognition, Learning, and Autonomy, University of California, Los Angeles"
+a102edaa9fd458316637ce51a0b7aba2ee651637,Learning Human Poses from Actions,"ADITYA, JAWAHAR, PAWAN: LEARNING HUMAN POSES FROM ACTIONS +Learning Human Poses from Actions +IIIT Hyderabad +University of Oxford & +The Alan Turing Institute +Aditya Arun1 +C.V. Jawahar1 +M. Pawan Kumar2"
+a1aac8e95cd262f974b26374ec8fe35c0f000185,Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot Learning,"IJCV manuscript No. +(will be inserted by the editor) +Transferrable Feature and Projection Learning with Class Hierarchy for +Zero-Shot Learning +Aoxue Li · Zhiwu Lu · Jiechao Guan · Tao Xiang · Liwei Wang · Ji-Rong Wen +Received: date / Accepted: date"
a15c728d008801f5ffc7898568097bbeac8270a4,ForgetIT Deliverable Template,"www.forgetit-project.eu ForgetIT Concise Preservation by Combining Managed Forgetting @@ -12996,6 +45299,36 @@ Information Consolidation and Con- entration D4.4: Information analysis, consolidation"
+a1e1bd4dacddc703a236681e987a09601ee1016d,Embedding Visual Hierarchy With Deep Networks for Large-Scale Visual Recognition,"Embedding Visual Hierarchy with Deep Networks +for Large-Scale Visual Recognition +Tianyi Zhao, Baopeng Zhang, Wei Zhang, Ning Zhou, Jun Yu, Jianping Fan"
+a19f08d7b1ce8b451df67ec125dd9254b5a05d95,3D Face Recognition Using Multiview Keypoint Matching,"009 Advanced Video and Signal Based Surveillance +D Face Recognition Using Multiview Keypoint Matching +Michael Mayo, Edmond Zhang +Department of Computer Science, University of Waikato, New Zealand +{mmayo,"
+a1669fa7d3d8f0c0cafe770c79007949cd32b245,Deep Metric Learning with BIER: Boosting Independent Embeddings Robustly,"TPAMI SUBMISSION +Deep Metric Learning with BIER: +Boosting Independent Embeddings Robustly +Michael Opitz, Georg Waltner, Horst Possegger, and Horst Bischof"
+a147cec1434753777b3651101bdbda1489b09fd4,Individual differences in shifting decision criterion: a recognition memory study.,"Mem Cogn (2012) 40:1016–1030 +DOI 10.3758/s13421-012-0204-6 +Individual differences in shifting decision criterion: +A recognition memory study +Elissa M. Aminoff & David Clewett & Scott Freeman & +Amy Frithsen & Christine Tipper & Arianne Johnson & +Scott T. Grafton & Michael B. Miller +Published online: 4 May 2012 +# Psychonomic Society, Inc. 2012"
+a157ebc849d57ccff00a52a68b24e4ac8eba9536,The Contextual Loss for Image Transformation with Non-aligned Data,"The Contextual Loss for Image Transformation +with Non-Aligned Data +Roey Mechrez(cid:63) , Itamar Talmi(cid:63), Lihi Zelnik-Manor +Technion - Israel Institute of Technology +Fig. 1. Our Contextual loss is effective for many image transformation tasks: It can +make a Trump cartoon imitate Ray Kurzweil, give Obama some of Hillary’s features, +nd, turn women more masculine or men more feminine. Mutual to these tasks is the +bsence of ground-truth targets that can be compared pixel-to-pixel to the generated +images. The Contextual loss provides a simple solution to all of these tasks."
a1132e2638a8abd08bdf7fc4884804dd6654fa63,Real-Time Video Face Recognition for Embedded Devices,"Real-Time Video Face Recognition for Embedded Devices Gabriel Costache, Sathish Mangapuram, Alexandru @@ -13016,6 +45349,22 @@ large community of researchers in that discipline. Many reasons feed t main being the wide range of commercial, law enforcement and security applications that require authentication. The progress made in recent years on the methods and algorithms for data processing as well as the availability of new technologies makes it easier to study"
+a19de85fa1533a1a1929b98b5fc3b1fb618dc668,Towards Improving Abstractive Summarization via Entailment Generation,
+a15663e0c0a2427ac4da5161e4ed75d331a5a2be,Streaming spectral clustering,"Streaming Spectral Clustering +Shinjae Yoo +Computational Science Center +Brookhaven National Laboratory +Upton, New York 11973-5000 +Email: +Hao Huang +Machine Learning Laboratory +General Electric Global Research +San Ramon, CA 94583 +Email: +Shiva Prasad Kasiviswanathan +Samsung Research America +Mountain View, CA 94043 +Email:"
a14ae81609d09fed217aa12a4df9466553db4859,Face Identification Using Large Feature Sets,"REVISED VERSION, JUNE 2011 Face Identification Using Large Feature Sets William Robson Schwartz, Huimin Guo, Jonghyun Choi, and Larry S. Davis, Fellow, IEEE"
@@ -13024,11 +45373,121 @@ Yongqin Xian1, Zeynep Akata1, Gaurav Sharma1,2,∗, Quynh Nguyen3, Matthias Hein MPI for Informatics IIT Kanpur Saarland University"
+a10f734e30d8dcb8506c9ea5b1074e6c668904e2,Learning Features and Parts for Fine-Grained Recognition,"Learning Features and Parts for Fine-Grained +Recognition +(Invited Paper) +Jonathan Krause∗, Timnit Gebru∗, Jia Deng †, Li-Jia Li ‡, Li Fei-Fei∗ +Stanford University: {jkrause, tgebru, +University of Michigan: +Yahoo! Research:"
+a1af05502eac70296ee22e5ab7e066420f5fe447,A Probabilistic Approach for Breast Boundary Extraction in Mammograms,"Hindawi Publishing Corporation +Computational and Mathematical Methods in Medicine +Volume 2013, Article ID 408595, 19 pages +http://dx.doi.org/10.1155/2013/408595 +Research Article +A Probabilistic Approach for Breast Boundary +Extraction in Mammograms +Hamed Habibi Aghdam, Domenec Puig, and Agusti Solanas +Department of Computer Engineering and Mathematics, Rovira i Virgili University, 43007 Tarragona, Spain +Correspondence should be addressed to Domenec Puig; +Received 31 May 2013; Revised 21 August 2013; Accepted 16 September 2013 +Academic Editor: Reinoud Maex +Copyright © 2013 Hamed Habibi Aghdam et al. This is an open access article distributed under the Creative Commons Attribution +License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +The extraction of the breast boundary is crucial to perform further analysis of mammogram. Methods to extract the breast boundary +an be classified into two categories: methods based on image processing techniques and those based on models. The former use +image transformation techniques such as thresholding, morphological operations, and region growing. In the second category, the +oundary is extracted using more advanced techniques, such as the active contour model. The problem with thresholding methods +is that it is a hard to automatically find the optimal threshold value by using histogram information. On the other hand, active +ontour models require defining a starting point close to the actual boundary to be able to successfully extract the boundary. In this"
+a1c6f88330762cc97f26585c124c6b3ac791eb89,Confidence Sets for Fine-Grained Categorization and Plant Species Identification,"Int J Comput Vis +DOI 10.1007/s11263-014-0743-3 +Confidence Sets for Fine-Grained Categorization and Plant +Species Identification +Asma Rejeb Sfar · Nozha Boujemaa · Donald Geman +Received: 1 January 2014 / Accepted: 20 June 2014 +© Springer Science+Business Media New York 2014"
+a18c8f76f2599d6d61f26cb1d4025ea386919dfe,Video Event Detection: From Subvolume Localization To Spatio-Temporal Path Search.,"This document is downloaded from DR-NTU, Nanyang Technological +University Library, Singapore. +Title +Video event detection : from subvolume localization to +spatio-temporal path search +Author(s) +Tran, Du; Yuan, Junsong; Forsyth, David +Citation +Tran, D., Yuan, J., & Forsyth, D. (2014). Video Event +Detection: From Subvolume Localization to +Spatiotemporal Path Search. IEEE Transactions on +Pattern Analysis and Machine Intelligence, 36(2), 404- +http://hdl.handle.net/10220/19322 +Rights +© 2014 IEEE. Personal use of this material is permitted. +Permission from IEEE must be obtained for all other +uses, in any current or future media, including +reprinting/republishing this material for advertising or +promotional purposes, creating new collective works, for +resale or redistribution to servers or lists, or reuse of any"
+a1b7b23bd8f2b2ef37a9113e6b8499f0069aac85,Performance assessment of face recognition using super-resolution,"Performance Assessment of Face Recognition Using +Super-Resolution +Shuowen Hu +Robert Maschal +S. Susan Young +U.S. Army Research Laboratory +U.S. Army Research Laboratory +U.S. Army Research Laboratory +800 Powder Mill Rd. +Adelphi, MD 20783 +(301)394-2526 +800 Powder Mill Rd. +Adelphi, MD 20783 +(301)394-0437 +800 Powder Mill Rd. +Adelphi, MD 20783 +(301)394-0230 +Tsai Hong Hong +Jonathon P. Phillips +National Institute of Standards and"
+a120cac99c85548d0749dd83b0450520949e6474,Unsupervised Eye Pupil Localization through Differential Geometry and Local Self-Similarity Matching,"Unsupervised Eye Pupil Localization through Differential +Geometry and Local Self-Similarity Matching +Marco Leo1*, Dario Cazzato1,2, Tommaso De Marco1, Cosimo Distante1 +National Research Council of Italy, Institute of Optics, Arnesano, Lecce, Italy, 2 Faculty of Engineering, University of Salento, Lecce, Italy"
+a1030e6e0e6995768dbcafedc712a59db090d2b4,Bayesian Sparsification of Recurrent Neural Networks,"Bayesian Sparsification of Recurrent Neural Networks +Ekaterina Lobacheva * 1 2 Nadezhda Chirkova * 1 3 Dmitry Vetrov 1 4"
+a11a63e00c0e587adf4efc1425c0651c242263b7,Two More Strategies to Speed Up Connected Components Labeling Algorithms,"Two More Strategies to Speed Up Connected +Components Labeling Algorithms +Federico Bolelli, Michele Cancilla, Costantino Grana +Dipartimento di Ingegneria “Enzo Ferrari” +Universit`a degli Studi di Modena e Reggio Emilia +Via Vivarelli 10, Modena MO 41125, Italy"
+a11f5e74b13a6353d14e024d06a902b9afa728b3,Yum-me: Personalized Healthy Meal Recommender System,"Yum-me: Personalized Healthy Meal Recommender System +Longqi Yang +Cornell Tech +Nicola Dell +Cornell Tech +Cheng-Kang Hsieh +Serge Belongie +Cornell Tech +Hongjian Yang +Cornell Tech +Deborah Estrin +Cornell Tech"
a1e97c4043d5cc9896dc60ae7ca135782d89e5fc,"Re-identification of Humans in Crowds using Personal, Social and Environmental Constraints","IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE Re-identification of Humans in Crowds using Personal, Social and Environmental Constraints Shayan Modiri Assari, Member, IEEE, Haroon Idrees, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
-ef940b76e40e18f329c43a3f545dc41080f68748,A Face Recognition and Spoofing Detection Adapted to Visually- Impaired People,"Research Article Volume 7 Issue No.3 +ef61e43a1cce95afdc0696879085e834b981d5de,Real time multi-object tracking using multiple cameras Semester Project,"CVLab: Computer Vision Laboratory +School of Computer and Communication Sciences +Ecole Polytechnique Fédérale de Lausanne +http://cvlab.epfl.ch/ +Real time multi-object tracking +using multiple cameras +Semester Project +Michalis Zervos +Supervisor Professor Pascal Fua +Teaching Assistant Horesh Ben Shitrit +Spring Semester +June 2012"
+ef940b76e40e18f329c43a3f545dc41080f68748,A Face Recognition and Spoofing Detection Adapted to Visually-Impaired People,"Research Article Volume 7 Issue No.3 ISSN XXXX XXXX © 2017 IJESC A Face Recognition and Spoofing Detection Adapted to Visually- Impaired People @@ -13052,6 +45511,29 @@ efd308393b573e5410455960fe551160e1525f49,Tracking Persons-of-Interest via Unsupe Unsupervised Representation Adaptation Shun Zhang, Jia-Bin Huang, Jongwoo Lim, Yihong Gong, Jinjun Wang, Narendra Ahuja, and Ming-Hsuan Yang"
+ef48f1d8ec88dabbf7253cb1c8a224cb95f604af,Survey on Video Analysis of Human Walking Motion,"International Journal of Signal Processing, Image Processing and Pattern Recognition +Vol.7, No.3 (2014), pp.99-122 +http://dx.doi.org/10.14257/ijsip.2014.7.3.10 +Survey on Video Analysis of Human Walking Motion +S. Nissi Paul and Y. Jayanta Singh +Dept. Computer Science Engineering and information Technology +Don Boco College of Engineering and Technology, Assam Don Bosco University +Guwahati, Assam - India"
+efa2b259407b5b9171dd085061d05b72b6309eb0,"Egocentric Activity Recognition Using HOG , HOF , MBH and Combined features","International Journal on Future Revolution in Computer Science & Communication Engineering +Volume: 3 Issue: 8 +_______________________________________________________________________________________________ +74 – 79 +ISSN: 2454-4248 +Egocentric Activity Recognition Using HOG, HOF, MBH and +Combined features +K. P. Sanal Kumar +Research Scholar +Dept. of CSE +Annamalai University +R. Bhavani +Professor +Dept. of CSE +Annamalai University"
ef230e3df720abf2983ba6b347c9d46283e4b690,QUIS-CAMPI: an annotated multi-biometrics data feed from surveillance scenarios,"Page 1 of 20 QUIS-CAMPI: An Annotated Multi-biometrics Data Feed From Surveillance Scenarios @@ -13063,6 +45545,72 @@ ef4ecb76413a05c96eac4c743d2c2a3886f2ae07,Modeling the importance of faces in nat Jin B.a, Yildirim G.a, Lau C.a, Shaji A.a, Ortiz Segovia M.b and S¨usstrunk S.a EPFL, Lausanne, Switzerland; Oc´e, Paris, France"
+efef00465e1b2f4003e838e50f9c8fa1c8ffaf3e,SceneNet: A Perceptual Ontology for Scene Understanding,"SceneNet: A Perceptual Ontology for Scene +Understanding +Ilan Kadar and Ohad Ben-Shahar +Ben-Gurion University of the Negev"
+ef2084979a3191403c1b8b48f503d06f346afb8f,Une méthode de reconnaissance des expressions du visage basée sur la perception,"Une m´ethode de reconnaissance des expressions du +visage bas´ee sur la perception +Rizwan Khan, Alexandre Meyer, Hubert Konik, Saida Bouakaz +To cite this version: +Rizwan Khan, Alexandre Meyer, Hubert Konik, Saida Bouakaz. Une m´ethode de reconnais- +sance des expressions du visage bas´ee sur la perception. RFIA 2012 (Reconnaissance des +Formes et Intelligence Artificielle), Jan 2012, Lyon, France. pp.978-2-9539515-2-3, 2012. <hal- +00660976> +HAL Id: hal-00660976 +https://hal.archives-ouvertes.fr/hal-00660976 +Submitted on 19 Jan 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
+ef66ed8d8db41f67048d077fd4b772c8ba748090,Reservoir Computing Hardware with Cellular Automata,"Reservoir Computing Hardware with +Cellular Automata +Alejandro Mor´an, Christiam F. Frasser and Josep L. Rossell´o +Electronic Engineering Group, Physics Department, Universitat de les Illes Balears, +Spain. +E-mail: +June 22, 2018"
+ef75007cd6e5b990d09e7f3c4ba119be6c2546fb,Lecture 20: Object Recognition 20.1 Introduction 20.2.1 Neocognitron,"Chapter 20 +Lecture 20: Object recognition +0.1 Introduction +In its simplest form, the problem of recognition is posed as a binary classification task, namely distin- +guishing between a single object class and background class. Such a classification task can be turned +into a detector by sliding it across the image (or image pyramid), and classifying each local window. +Classifier based methods have defined their own family of object models. Driven by advances in +machine learning, a common practice became to through a bunch of features into the last published +lgorithm. However, soon became clear that such an approach, in which the research gave up into trying +to have a well defined physical model of the object, hold a lot of promise. In many cases, the use of a +specific classifier has driven the choice of the object representation and not the contrary. In classifier- +ased models, the preferred representations are driven by efficiency constraints and by the characteristics +of the classifier (e.g., additive models, SVMs, neural networks, etc.). +0.2 Neural networks +Although neural networks can be trained in other settings than a purely discriminative framework, some +of the first classifier based approaches used neural networks to build the classification function. Many +urrent approaches, despite of having a different inspiration, still follow an architecture motivated by +neural networks. +0.2.1 Neocognitron +The Neocognitron, developed by Fukushima in the 80 [8], consisted on a multilayered network with"
+ef3697668eb643de27995827c630cfd029b10c37,Online self-supervised multi-instance segmentation of dynamic objects,"014 IEEE International Conference on Robotics & Automation (ICRA) +Hong Kong Convention and Exhibition Center +May 31 - June 7, 2014. Hong Kong, China +978-1-4799-3685-4/14/$31.00 ©2014 IEEE"
+ef247c194162f76eb8d44b1f83c25a4002ab69a6,An Effective Profile Based Video Browsing System for e- Learning,"An Effective Profile Based Video Browsing System for e- +Learning +S. C. Premaratne, D. D. Karunaratna and K. P. Hewagamage +University of Colombo School of Computing, Sri Lanka"
+efcedd5750f57f4c7f748783e91918e0f42da61f,Global Haar-Like Features: A New Extension of Classic Haar Features for Efficient Face Detection in Noisy Images,"Global Haar-like Features: +A New Extension of Classic Haar Features for +Efficient Face Detection in Noisy Images +Mahdi Rezaei(cid:63), Hossein Ziaei Nafchi‡, and Sandino Morales† +(cid:63)The University of Auckland, New Zealand +Synchromedia Laboratory, ´Ecole de Technologie Sup´erieure, Canada +The University of Auckland, New Zealand"
ef032afa4bdb18b328ffcc60e2dc5229cc1939bc,Attribute-enhanced metric learning for face retrieval,"Fang and Yuan EURASIP Journal on Image and Video Processing (2018) 2018:44 https://doi.org/10.1186/s13640-018-0282-x @@ -13074,6 +45622,14 @@ Attribute-enhanced metric learning for face retrieval Yuchun Fang* nd Qiulong Yuan"
+ef9081d153f96b96183666a5086c63cecf2f33e6,3D Face Recognition Using Radon Transform and Symbolic PCA,"International Journal of Electronics and Computer Science Engineering 2342 +Available Online at www.ijecse.org ISSN- 2277-1956 +D Face Recognition Using Radon Transform and +Symbolic PCA +P. S. Hiremath 1, Manjunath Hiremath 2 +2Departmentof Computer Science +Gulbarga University, Gulbarga-585106 +Karnataka, India"
ef5531711a69ed687637c48930261769465457f0,Studio2Shop: from studio photo shoots to fashion articles,"Studio2Shop: from studio photo shoots to fashion articles Julia Lasserre1, Katharina Rasch1 and Roland Vollgraf Zalando Research, Muehlenstr. 25, 10243 Berlin, Germany @@ -13095,6 +45651,16 @@ nd Analysis Methods Beijing, 100872, China"
efa08283656714911acff2d5022f26904e451113,Active Object Localization in Visual Situations,"Active Object Localization in Visual Situations Max H. Quinn, Anthony D. Rhodes, and Melanie Mitchell"
+ef52f1e2b52fd84a7e22226ed67132c6ce47b829,Online Eye Status Detection in the Wild with Convolutional Neural Networks,
+efe208a03e2f75ddcebf8bb0f10b1c0bea4824be,A data set for evaluating the performance of multi-class multi-object video tracking,"A data set for evaluating the performance of multi-class multi-object +video tracking +Avishek Chakrabortya, Victor Stamatescua, Sebastien C. Wongb, Grant Wigleya, David Kearneya +Computational Learning Systems Laboratory, School of Information Technology and Mathematical +Sciences, University of South Australia, Mawson Lakes, SA, Australia; bDefence Science and +Technology Group, Edinburgh, SA, Australia"
+efa65394d0ec5a16ecd57075951016502c541c0d,The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers,"The Gap of Semantic Parsing: A Survey on Automatic +Math Word Problem Solvers +Dongxiang Zhang, Lei Wang, Nuo Xu, Bing Tian Dai and Heng Tao Shen"
ef999ab2f7b37f46445a3457bf6c0f5fd7b5689d,Improving face verification in photo albums by combining facial recognition and metadata with cross-matching,"Calhoun: The NPS Institutional Archive DSpace Repository Theses and Dissertations @@ -13107,10 +45673,43 @@ Bouthour, Khoubeib Monterey, California: Naval Postgraduate School http://hdl.handle.net/10945/56868 Downloaded from NPS Archive: Calhoun"
+ef473c96dde98e2015b2d135a17a2d734319649a,Playlist Generation using Facial Expression Analysis and Task Extraction,"Pobrane z czasopisma Annales AI- Informatica http://ai.annales.umcs.pl +Data: 04/05/2018 16:53:32 +U M CS"
+ef4b5bcaad4c36d7baa7bc166bd1712634c7ad71,Towards Spatio-temporal Face Alignment in Unconstrained Conditions,
+efbe52289f71eca9a0aaa8a5362f73334fa6b23c,Face recognition based on LDA in manifold subspace,"EAI Endorsed Transactions +on Context-aware Systems and Applications +Research Article +Face recognition based on LDA in manifold subspace +Hung Phuoc Truong1, Tue-Minh Dinh Vo1 and Thai Hoang Le1, * +Faculty of Information Technology, University of Science – Vietnam National University Ho Chi Minh city, 227 Nguyen +Van Cu street, HCMc, Vietnam"
+c32b5f8d400cdfd4459b0dfdeccf011744df0b4b,Object Tracking Using Local Multiple Features and a Posterior Probability Measure,"Article +Object Tracking Using Local Multiple Features and a +Posterior Probability Measure +Wenhua Guo *, Zuren Feng and Xiaodong Ren +Systems Engineering Institute, State Key Laboratory for Manufacturing Systems Engineering, +Xi’an Jiaotong University, Xi’an 710049, China; (Z.F.); (X.R.) +* Correspondence: Tel.: +86-29-8266-7771 +Academic Editors: Xue-Bo Jin, Shuli Sun, Hong Wei and Feng-Bao Yang +Received: 20 February 2017; Accepted: 28 March 2017; Published: 31 March 2017"
c32fb755856c21a238857b77d7548f18e05f482d,Multimodal Emotion Recognition for Human-Computer Interaction: A Survey,"Multimodal Emotion Recognition for Human- Computer Interaction: A Survey School of Computer and Communication Engineering, University of Science and Technology Beijing, 100083 Beijing, China. Michele Mukeshimana, Xiaojuan Ban, Nelson Karani, Ruoyi Liu"
+c33289788ca69a55c7eefe6e672c82a0cac5a299,Semantic Video CNNs Through Representation Warping,"Semantic Video CNNs through Representation Warping +Raghudeep Gadde1,3, Varun Jampani1,4 and Peter V. Gehler1,2,3 +MPI for Intelligent Systems, +University of W¨urzburg +Bernstein Center for Computational Neuroscience, +NVIDIA"
+c3c73bb626efec988aadbac519c61810710282fe,Saccadic movements using eye-tracking technology in individuals with autism spectrum disorders: pilot study.,"Arq Neuropsiquiatr 2006;64(3-A):559-562 +SACCADIC MOVEMENTS USING EYE-TRACKING +TECHNOLOGY IN INDIVIDUALS WITH AUTISM +SPECTRUM DISORDERS +Pilot study +Marcos T. Mercadante, Elizeu C. Macedo, Patrícia M. Baptista, +Cristiane S. Paula, José S. Schwartzman"
c3beae515f38daf4bd8053a7d72f6d2ed3b05d88,ACL 2014 52nd Annual Meeting of the Association for Computational Linguistics TACL Papers,"ACL201452ndAnnualMeetingoftheAssociationforComputationalLinguisticsTACLPapersJune23-25,2014Baltimore,Maryland,USA"
c3dc4f414f5233df96a9661609557e341b71670d,Utterance independent bimodal emotion recognition in spontaneous communication,"Tao et al. EURASIP Journal on Advances in Signal Processing 2011, 2011:4 http://asp.eurasipjournals.com/content/2011/1/4 @@ -13119,17 +45718,146 @@ Utterance independent bimodal emotion recognition in spontaneous communication Jianhua Tao*, Shifeng Pan, Minghao Yang, Ya Li, Kaihui Mu and Jianfeng Che Open Access"
+c3a1a3d13bf1cb2b9c054857b857c3fb9d7176f6,Détection de marqueurs affectifs et attentionnels de personnes âgées en interaction avec un robot. (Audio-visual detection of emotional (laugh and smile) and attentional markers for elderly people in social interaction with a robot),"Détection de marqueurs affectifs et attentionnels de +personnes âgées en interaction avec un robot +Fan Yang +To cite this version: +Fan Yang. Détection de marqueurs affectifs et attentionnels de personnes âgées en interaction +vec un robot. +Intelligence artificielle [cs.AI]. Université Paris-Saclay, 2015. Français. <NNT : +015SACLS081>. <tel-01280505> +HAL Id: tel-01280505 +https://tel.archives-ouvertes.fr/tel-01280505 +Submitted on 29 Feb 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non,"
+c348118690d2e6544ec1e68f904dbf9e5b6397bd,Video-to-Video Synthesis,"Video-to-Video Synthesis +Ting-Chun Wang1, Ming-Yu Liu1, Jun-Yan Zhu2, Guilin Liu1, +Andrew Tao1, Jan Kautz1, Bryan Catanzaro1 +NVIDIA, 2MIT CSAIL"
+c380aa240ebcdb8bf2cad4f30bcef2390fada091,Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space,"Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space +Berta Bescos1, Jos´e Neira1, Roland Siegwart2 and Cesar Cadena2"
+c3dc704790e1a170919087baab0ad10d7df6c24e,Oxytocin in the socioemotional brain: implications for psychiatric disorders,"C l i n i c a l r e s e a r c h +Oxytocin in the socioemotional brain: +implications for psychiatric disorders +Peter Kirsch, PhD +Introduction +During recent years, the neuropeptide oxytocin +(OXT) has attracted enormous interest in neuroscien- +tific research on social and emotional processes. Given +the generally increased interest in social cognition in +the area of psychiatric research, the number of publi- +ations focusing on OXT in the context of mental dis- +orders has also increased markedly in recent years. The +role of OXT in the context of childbirth and lactation +has long been studied; however, two lines of research +have motivated investigation into the role of OXT in +social behavior. First, animal research initiated by In- +sel and Young1 on the role of OXT in maternal be- +havior and bonding revealed that OXT in the central +nervous system modulates social behavior. Second, +in human research, a startling paper by Kosfeld et al2"
+c3de7c38493cfe67654411d77f47069cfa7b077b,Multiple context mere exposure: Examining the limits of liking.,"ISSN: 1747-0218 (Print) 1747-0226 (Online) Journal homepage: http://www.tandfonline.com/loi/pqje20 +Multiple context mere exposure: Examining the +limits of liking +Daniel de Zilva, Ben R. Newell & Chris J. Mitchell +To cite this article: Daniel de Zilva, Ben R. Newell & Chris J. Mitchell (2015): Multiple context +mere exposure: Examining the limits of liking, The Quarterly Journal of Experimental +Psychology, DOI: 10.1080/17470218.2015.1057188 +To link to this article: http://dx.doi.org/10.1080/17470218.2015.1057188 +Accepted online: 29 Jun 2015.Published +online: 06 Jul 2015. +Submit your article to this journal +Article views: 43 +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pqje20 +Download by: [UNSW Library] +Date: 05 October 2015, At: 22:09"
+c34911e9fefd987470edf8f620d9ce8f0030339d," +Autism, Emotion Recognition and the Mirror +Neuron System: The Case of Music + ","Copyright © 2009 by MJM +MJM 2009 12(2): 87-98 +FoCuS rEViEW +Autism, Emotion Recognition and the Mirror +Neuron System: The Case of Music +Istvan Molnar-Szakacs*, Martha J. Wang, Elizabeth A. Laugeson, +Katie Overy, Wai-Ling Wu, Judith Piggot"
+c3b037fd6fb4542f7ed18c194a03ae328bcca423,Random Binary Mappings for Kernel Learning and Efficient SVM,"Random Decision Stumps for +Kernel Learning and Efficient SVM +Gemma Roig * +Xavier Boix * +Luc Van Gool +Computer Vision Lab, ETH Zurich, Switzerland +* Both first authors contributed equally."
c3b3636080b9931ac802e2dd28b7b684d6cf4f8b,Face Recognition via Local Directional Pattern,"International Journal of Security and Its Applications Vol. 7, No. 2, March, 2013 Face Recognition via Local Directional Pattern Dong-Ju Kim*, Sang-Heon Lee and Myoung-Kyu Sohn Division of IT Convergence, Daegu Gyeongbuk Institute of Science & Technology 50-1, Sang-ri, Hyeonpung-myeon, Dalseong-gun, Daegu, Korea."
+c3341286ece958e6b05df56d788456b61313380b,Estimating Attention of Faces due to its Growing Level of Emotions,"Estimating Attention of Faces due to its Growing Level of Emotions +Ravi Kant Kumar*, Jogendra Garain, Dakshina Ranjan Kisku and Goutam Sanyal +Department of Computer Science and Engineering +National Institute of Technology +Durgapur, India +E-mail: {vit.ravikant, jogs.cse, drkisku, +imperative +nd feeling [2] of a person at that moment. Facial +expression plays an +in non-verbal +ommunication as well as to predicting the behavior of the +person. During a group discussion, our attention +utomatically goes towards those participants who put +more stressed on his words or talk in a sentimental or +emphatic voice. Same phenomenon occurs with the non- +verbal visual communication. The face reflecting the +higher expression of a particular emotion draws more +ttention [3, 4] in the discussion. A particular object (It +lso may be face), which gives us more visualization is +onsider as a salient object and this phenomenon is called"
+c390fb954a07ecee473e0704ac065875121f6137,Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization,"IEEE TRANSACTIONS ON XXXX, VOL. XX, NO. X, APRIL 2015 +Heterogeneous Tensor Decomposition for +Clustering via Manifold Optimization +Yanfeng Sun, Junbin Gao, Xia Hong, Bamdev Mishra and Baocai Yin"
c398684270543e97e3194674d9cce20acaef3db3,Comparative Face Soft Biometrics for Human Identification,"Chapter 2 Comparative Face Soft Biometrics for Human Identification Nawaf Yousef Almudhahka, Mark S. Nixon and Jonathon S. Hare"
c3285a1d6ec6972156fea9e6dc9a8d88cd001617,Extreme 3D Face Reconstruction: Seeing Through Occlusions,
+c3ea346826467f04779e55679679c7c7e549c8a2,Learning Short-Cut Connections for Object Counting,"OÑORO-RUBIO, NIEPERT, LÓPEZ-SASTRE: LEARNING SHORT-CUT CONNECTIONS. . . +Learning Short-Cut Connections for Object +Counting +Daniel Oñoro-Rubio1 +Mathias Niepert1 +Roberto J. López-Sastre2 +SysML, +NEC Lab Europe, +Heidelberg, Germany +GRAM, +University of Alcalá, +Alcalá de Henares, Spain"
+c3b5ec36a29b320a576f6b9e58188b505becb4aa,Practical Gauss-Newton Optimisation for Deep Learning,"Practical Gauss-Newton Optimisation for Deep Learning +Aleksandar Botev 1 Hippolyt Ritter 1 David Barber 1 2"
+c391029d67e5a0c352f9f328b838cb19528336fe,Responding to Other People’s Direct Gaze: Alterations in Gaze Behavior in Infants at Risk for Autism Occur on Very Short Timescales,"J Autism Dev Disord (2017) 47:3498–3509 +DOI 10.1007/s10803-017-3253-7 +ORIGINAL PAPER +Responding to Other People’s Direct Gaze: Alterations in Gaze +Behavior in Infants at Risk for Autism Occur on Very Short +Timescales +Pär Nyström1 +· Sven Bölte2,3 · Terje Falck‑Ytter1,2 · The EASE Team +Published online: 4 September 2017 +© The Author(s) 2017. This article is an open access publication"
c3bcc4ee9e81ce9c5c0845f34e9992872a8defc0,A New Scheme for Image Recognition Using Higher-Order Local Autocorrelation and Factor Analysis,"MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan A New Scheme for Image Recognition Using Higher-Order Local Autocorrelation and Factor Analysis @@ -13139,10 +45867,22 @@ Tokyo, Japan yyyAIST Tukuba, Japan f shiraki, takumi, otsug"
+c324986c8599fee2f6da7b59751e89ed9624afa3,Dual Quaternions as Constraints in 4D-DPM Models for Pose Estimation,"Article +Dual Quaternions as Constraints in 4D-DPM Models +for Pose Estimation +Enrique Martinez-Berti *, Antonio-José Sánchez-Salmerón and Carlos Ricolfe-Viala +Departamento de Ingeniería de Sistemas y Automática, Instituto de Automática e informática Industrial, +Universitat Politècnica de València, València, 46022, Spain ; (A.-J.S.-S.); +(C.R.-V.) +* Correspondence: +Received: 1 June 2017; Accepted: 13 August 2017; Published: 19 August 2017"
c32383330df27625592134edd72d69bb6b5cff5c,Intrinsic Illumination Subspace for Lighting Insensitive Face Recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 2, APRIL 2012 Intrinsic Illumination Subspace for Lighting Insensitive Face Recognition Chia-Ping Chen and Chu-Song Chen, Member, IEEE"
+c3955d74f2a084a8ddcbd7e73952c326e81804b2,Mutual Information Neural Estimation,"Mutual Information Neural Estimation +Mohamed Ishmael Belghazi 1 Aristide Baratin 1 2 Sai Rajeswar 1 Sherjil Ozair 1 Yoshua Bengio 1 3 4 +Aaron Courville 1 3 R Devon Hjelm 1 4"
c32f04ccde4f11f8717189f056209eb091075254,Analysis and Synthesis of Behavioural Specific Facial Motion,"Analysis and Synthesis of Behavioural Specific Facial Motion Lisa Nanette Gralewski @@ -13151,6 +45891,18 @@ for the degree of Doctor of Philosophy in the Faculty of Engineering, Department Computer Science. February 2007 71657 words"
+c338045f80ab3465bdc381f2b1791744b060fbb3,A Diffusion and Clustering-Based Approach for Finding Coherent Motions and Understanding Crowd Scenes,"A Diffusion and Clustering-based Approach for +Finding Coherent Motions and Understanding +Crowd Scenes +Weiyao Lin, Yang Mi, Weiyue Wang, Jianxin Wu, Jingdong Wang, and Tao Mei"
+c34ec5dd51880acf72336e85e4e45da5fcfc75f4,LEGO: Learning Edge with Geometry all at Once by Watching Videos,"LEGO: Learning Edge with Geometry all at Once by Watching Videos +Zhenheng Yang1 Peng Wang2 Yang Wang2 Wei Xu3 Ram Nevatia1 +University of Southern California 2Baidu Research +National Engineering Laboratory for Deep Learning Technology and Applications"
+c3d60c8b1dff411982ccd8875496f1e74d2cefc4,Multi-view X-ray R-CNN,"Multi-view X-ray R-CNN +Jan-Martin O. Steitz[0000−0002−3549−312X], Faraz +Saeedan +Department of Computer Science, TU Darmstadt, Darmstadt, Germany"
c317181fa1de2260e956f05cd655642607520a4f,Objective Classes for Micro-Facial Expression Recognition,"Research Article Research Article for submission to journal @@ -13171,18 +45923,81 @@ Centre for Imaging Sciences, University of Manchester, Manchester, United Kingdom Sudan University of Science and Technology, Khartoum, Sudan"
+c36f933a46e1d1c51785295bb97154df9ceada36,"Optimizing Program Performance via Similarity, Using a Feature-Agnostic Approach","Optimizing Program Performance via Similarity, +Using a Feature-agnostic Approach +Rosario Cammarota, Laleh Aghababaie Beni +Alexandru Nicolau, and Alexander V. Veidenbaum +Department of Computer Science, University of California Irvine, Irvine, USA"
+c33522fc5d2cf92c5a10f32ba9416365944cdb85,Scaling the Scattering Transform: Deep Hybrid Networks,"Scaling the Scattering Transform: Deep Hybrid Networks +Edouard Oyallon +D´epartement Informatique +Ecole Normale Sup´erieure +Eugene Belilovsky +University of Paris-Saclay +INRIA and KU Leuven +Paris, France +Sergey Zagoruyko +Universit´e Paris-Est +´Ecole des Ponts ParisTech +Paris, France"
+c3599c91d0e3473178c1578b731b03e4be5d3ff1,Improving Resource Efficiency in Cloud Computing a Dissertation Submitted to the Department of Electrical Engineering and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"IMPROVING RESOURCE EFFICIENCY IN CLOUD COMPUTING +A DISSERTATION +SUBMITTED TO THE DEPARTMENT OF ELECTRICAL +ENGINEERING +AND THE COMMITTEE ON GRADUATE STUDIES +OF STANFORD UNIVERSITY +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +DOCTOR OF PHILOSOPHY +Christina Delimitrou +August 2015"
c30e4e4994b76605dcb2071954eaaea471307d80,Feature Selection for Emotion Recognition based on Random Forest,
c37a971f7a57f7345fdc479fa329d9b425ee02be,A Novice Guide towards Human Motion Analysis and Understanding,"A Novice Guide towards Human Motion Analysis and Understanding Dr. Ahmed Nabil Mohamed"
+c35724d227eb1e3d680333469fb9b94c677e871f,Multi-view Generative Adversarial Networks,"Under review as a conference paper at ICLR 2017 +MULTI-VIEW GENERATIVE ADVERSARIAL NET- +WORKS +Mickaël Chen +Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France +Ludovic Denoyer +Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France"
c3fb2399eb4bcec22723715556e31c44d086e054,Face recognition based on SIGMA sets of image features,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) 978-1-4799-2893-4/14/$31.00 ©2014 IEEE . INTRODUCTION"
+c3293ef751d3fb041bd3016fbc3fa5cc16f962fa,Inferencing Based on Unsupervised Learning of Disentangled Representations,"Accepted as a conference paper at the European Symposium on Artificial Neural +Networks, Computational Intelligence and Machine Learning (ESANN) 2018 +Inferencing Based on Unsupervised Learning +of Disentangled Representations +Tobias Hinz and Stefan Wermter ∗ +Universit¨at Hamburg, Department of Informatics, Knowledge Technology +Vogt-Koelln-Str. 30, 22527 Hamburg, Germany +http://www.informatik.uni-hamburg.de/WTM/"
c37de914c6e9b743d90e2566723d0062bedc9e6a,Joint and Discriminative Dictionary Learning for Facial Expression Recognition,"©2016 Society for Imaging Science and Technology DOI: 10.2352/ISSN.2470-1173.2016.11.IMAWM-455 Joint and Discriminative Dictionary Learning Expression Recognition for Facial Sriram Kumar, Behnaz Ghoraani, Andreas Savakis"
+c4f632a1b6faa43c217e63c58a4764511104c303,Extracting Pathlets FromWeak Tracking Data,"Extracting Pathlets From Weak Tracking Data∗ +Kevin Streib +James W. Davis +Dept. of Computer Science and Engineering +Ohio State University, Columbus, OH 43210"
+c4a024d73902462275879fa6133bff22134fcc7e,When crowds hold privileges: Bayesian unsupervised representation learning with oracle constraints,"When crowds hold privileges: Bayesian unsupervised +representation learning with oracle constraints +Theofanis Karaletsos +Computational Biology Program, Sloan Kettering Institute +275 York Avenue, New York, USA +Serge Belongie +Cornell Tech +11 Eighth Avenue #302, New York, USA +Gunnar R¨atsch +Computational Biology Program, Sloan Kettering Institute +275 York Avenue, New York, USA"
+c44e2fa02f0b578a2cc92795fe6a4c578f65dc97,A Method for Copyright Protection of Line Drawings,"A Method for Copyright Protection of Line Drawings +Weihan Sun*, Koichi Kise* +* Graduate School of Engineering, Osaka Prefecture University, Osaka +E-mail:"
c4f1fcd0a5cdaad8b920ee8188a8557b6086c1a4,The Ignorant Led by the Blind: A Hybrid Human–Machine Vision System for Fine-Grained Categorization,"Int J Comput Vis (2014) 108:3–29 DOI 10.1007/s11263-014-0698-4 The Ignorant Led by the Blind: A Hybrid Human–Machine Vision @@ -13191,9 +46006,42 @@ Steve Branson · Grant Van Horn · Catherine Wah · Pietro Perona · Serge Belongie Received: 7 March 2013 / Accepted: 8 January 2014 / Published online: 20 February 2014 © Springer Science+Business Media New York 2014"
+c46bcb02f92612cf525fd84c6cc79b0638c2eac9,New Fuzzy LBP Features for Face Recognition,"New Fuzzy LBP Features for Face Recognition +Abdullah Gubbia, Mohammed Fazle Azeemb Zahid Ansaric +Department of Electronics and Communications, P.A. College of Engineering, Mangalore, India, +Contact: +Department of Electrical Engineering, Aligarh Muslim University, Aligarh, India, +Department of Computer Science, P.A. College of Engineering, Mangalore, India, +zahid +Contact: +Contact: +There are many Local texture features each very in way they implement and each of the Algorithm trying +improve the performance. An attempt is made in this paper to represent a theoretically very simple and com- +putationally effective approach for face recognition. In our implementation the face image is divided into 3x3 +sub-regions from which the features are extracted using the Local Binary Pattern (LBP) over a window, fuzzy +membership function and at the central pixel. The LBP features possess the texture discriminative property +nd their computational cost is very low. By utilising the information from LBP, membership function, and +entral pixel, the limitations of traditional LBP is eliminated. The bench mark database like ORL and Sheffield +Databases are used for the evaluation of proposed features with SVM classifier. For the proposed approach K-fold +nd ROC curves are obtained and results are compared. +Keywords : Face Recognition, Fuzzy Logic, Information Set, Local Binary Pattern, SVM. +. INTRODUCTION"
+c4c4e5ff454584ae6a68d25b36bfc860e9a893a0,"Real-Time Facial Recognition System—Design, Implementation and Validation","Journal of Signal Processing Theory and Applications +(2013) 1: 1-18 +doi:10.7726/jspta.2013.1001 +Research Article +Real-Time Facial Recognition System—Design, +Implementation and Validation +M. Meenakshi* +Received 29 August 2012; Published online November 10, 2012 +© The author(s) 2012. Published with open access at uscip.org"
c43862db5eb7e43e3ef45b5eac4ab30e318f2002,Provable Self-Representation Based Outlier Detection in a Union of Subspaces,"Provable Self-Representation Based Outlier Detection in a Union of Subspaces Chong You, Daniel P. Robinson, Ren´e Vidal Johns Hopkins University, Baltimore, MD, 21218, USA"
+c4827fe8002ea61a2748b78369afe3a0747d1a0c,Towards Optimal Naive Bayes Nearest Neighbor,"Towards Optimal Naive Bayes Nearest Neighbor +R´egis Behmo1, Paul Marcombes1,2, Arnak Dalalyan2, and V´eronique Prinet1 +NLPR / LIAMA, Institute of Automation, Chinese Academy of Sciences(cid:2) +IMAGINE, LIGM, Universit´e Paris-Est"
c4dcf41506c23aa45c33a0a5e51b5b9f8990e8ad,Understanding Activity: Learning the Language of Action,"Understanding Activity: Learning the Language of Action Randal Nelson and Yiannis Aloimonos Univ. of Rochester and Maryland @@ -13234,11 +46082,151 @@ machines to learn person dependent traits and interaction behavior to utilize th for tasks manipulation. In such scenarios acquired face images contain large variations which demands an unconstrained face recognition system. Fig. 1. Biometric analysis of past few years has been shown in figure showing the"
+c48bde5b9ff17b708ab3e4f7c62a31a46c77f2f1,Nested Sparse Quantization for Efficient Feature Coding,"Nested Sparse Quantization +for Efficient Feature Coding +Xavier Boix1(cid:63), Gemma Roig1(cid:63), and Luc Van Gool1,2 (cid:63)(cid:63) +Computer Vision Lab, ETH Zurich, Switzerland, +KU Leuven, Belgium"
+c4f3375dab1886f37f542d998e61d8c30a927682,Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering,"Under review as a conference paper at ICLR 2018 +BEYOND SHARED HIERARCHIES: DEEP MULTITASK +LEARNING THROUGH SOFT LAYER ORDERING +Anonymous authors +Paper under double-blind review"
+c4fed8f23bc9ff1ffc27edb12970963ecf2dead9,Statistical Models and Optimization Algorithms for High-Dimensional Computer Vision Problems,
+c4d3033356066ef8133f03f4060bb8cad842918f,Inference of quantized neural networks on heterogeneous all-programmable devices,"Inference of Quantized Neural Networks +on Heterogeneous All-Programmable Devices +Thomas B. Preußer +Marie Skłodowska-Curie Fellow +Xilinx Research Labs +Giulio Gambardella +Xilinx Research Labs +Dublin, Ireland +Nicholas Fraser +Xilinx Research Labs +Dublin, Ireland +Michaela Blott +Xilinx Research Labs +Dublin, Ireland +Dublin, Ireland"
+c4a5932f33e6f4ccbfc7218fac58350a530d0ad6,Face Recognition using Discriminant Face Features Extraction method,"Face Recognition using Discriminant Face Features Extraction method +Miss. Poonam S. Sharma1, Prof. Nitin R. Chopde2 +Student of Master of Engineering in (CSE), G.H. Raisoni college of Engineering and Technology, +2Assistant professor Department of (CSE), G.H. Raisoni College of Engineering and Technology, +Amravati, India +Amravati, India"
+c48c452f26e54f37faaf025ca3c76b33ce3e40f6,Incremental learning of latent structural SVM for weakly supervised image classification,"INCREMENTAL LEARNING OF LATENT STRUCTURAL SVM FOR WEAKLY SUPERVISED +IMAGE CLASSIFICATION +Thibaut Durand (1) +Nicolas Thome (1) +Matthieu Cord (1) +David Picard (2) +(1) Sorbonne Universit´es, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France +(2) ETIS/ENSEA, University of Cergy-Pontoise, CNRS, UMR 8051, France"
+c43490eb0a3ce18fb2326ef1d0828664b60e73e2,Is This Car Looking at You? How Anthropomorphism Predicts Fusiform Face Area Activation when Seeing Cars,"RESEARCH ARTICLE +Is This Car Looking at You? How +Anthropomorphism Predicts Fusiform Face +Area Activation when Seeing Cars +Simone Ku¨ hn1*, Timothy R. Brick1, Barbara C. N. Mu¨ ller2,3, Ju¨ rgen Gallinat4,5 +. Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195, +Berlin, Germany, 2. Behavioural Science Institute, Radboud University of Nijmegen, P. O. Box 9104, 6500 HE, +Nijmegen, Netherlands, 3. Department of Psychology, Ludwig-Maximilian University, Leopoldstrasse 13, +80802, Mu¨ nchen, Germany, 4. Clinic for Psychiatry and Psychotherapy, Charite´ University Medicine, St. +Hedwig-Krankenhaus, Große Hamburger Straße 5–11, 10115, Berlin, Germany, 5. Clinic and Policlinic for +Psychiatry and Psychotherapy, University Clinic Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, +Germany"
+c4b3a1cf8842da8c64f7abf4a352583d5fd9762c,Gait recognition using sub-vector quantisation technique,"Int. J. Machine Intelligence and Sensory Signal Processing, Vol. 1, No. 1, 2013 +Gait recognition using sub-vector quantisation +technique +Neel K. Pandey* +Department of Electrical Engineering and Trades, +Faculty of Engineering and Trades, +Manukau Institute of Technology, +Private Bag 94006, Manukau 2241, Auckland, New Zealand +E-mail: +*Corresponding author +Waleed H. Abdulla and Zoran Salcic +Department of Electrical and Computer Engineering, +The University of Auckland, +Private Bag 92019, Auckland Mail Centre, +Auckland 1142, New Zealand +E-mail: +E-mail:"
+c45183ec95f89aff793a2629a0520006b4153d6a,Entropy-based template analysis in face biometric identification systems,"SIViP (2013) 7:493–505 +DOI 10.1007/s11760-013-0451-4 +ORIGINAL PAPER +Entropy-based template analysis in face biometric identification +systems +Maria De Marsico · Michele Nappi · Daniel Riccio · +Genoveffa Tortora +Received: 19 December 2011 / Revised: 7 June 2012 / Accepted: 10 October 2012 / Published online: 17 March 2013 +© Springer-Verlag London 2013"
+c4baa3d2fe702d3e96c500274f7fd9e63f8b3d6d,Pedestrian Detection Optimization Based on Random Filtering,"Pedestrian Detection Optimization Based on +Random Filtering +Victor Hugo Cunha de Melo, Samir Le˜ao, William Robson Schwartz +Universidade Federal de Minas Gerais +Department of Computer Science +Belo Horizonte, Minas Gerais, Brazil +Email: {victorhcmelo, samirleao,"
+ea9cecb5b619cfa4afef6c70e193c2303696a4f9,Integration of Probabilistic Pose Estimates from Multiple Views,"Integration of Probabilistic Pose Estimates From +Multiple Views +¨Ozg¨ur Erkent, Dadhichi Shukla and Justus Piater +Institute of Computer Science, +University of Innsbruck"
+ea94d834f912f092618d030f080de8395fe39b3f,Joint autoencoders : a flexible meta-learning framework,"Under review as a conference paper at ICLR 2018 +JOINT AUTOENCODERS: A FLEXIBLE META-LEARNING +FRAMEWORK +Anonymous authors +Paper under double-blind review"
+ea3503e9dc74b30b4c98a89843fe2ea0dc9221ab,Human Action Recognition Using LBP-TOP as Sparse Spatio-Temporal Feature Descriptor,"Human Action Recognition Using LBP-TOP as Sparse +Spatio-Temporal Feature Descriptor +Riccardo Mattivi and Ling Shao +Philips Research, Eindhoven, The Netherlands"
+eabdefeb685dd71a39417bf40247d206af4f9b9e,"Of Kith and Kin: Perceptual Enrichment, Expectancy, and Reciprocity in Face Perception.","657250 PSRXXX10.1177/1088868316657250Personality and Social Psychology ReviewCorrell et al. +research-article2016 +Article +Of Kith and Kin: Perceptual Enrichment, +Expectancy, and Reciprocity in Face +Perception +Personality and Social Psychology Review +1 –25 +© 2016 by the Society for Personality +nd Social Psychology, Inc. +Reprints and permissions: +sagepub.com/journalsPermissions.nav +DOI: 10.1177/1088868316657250 +pspr.sagepub.com +Joshua Correll1, Sean M. Hudson1, Steffanie Guillermo1, +nd Holly A. Earls1"
eac6aee477446a67d491ef7c95abb21867cf71fc,A Survey of Sparse Representation: Algorithms and Applications,"JOURNAL A survey of sparse representation: algorithms and pplications Zheng Zhang, Student Member, IEEE, Yong Xu, Senior Member, IEEE, Jian Yang, Member, IEEE, Xuelong Li, Fellow, IEEE, and David Zhang, Fellow, IEEE"
+ead587db6b2b76726e98b17cb1fbf973a34ddf31,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+ea533fac61db537fe1e1f351c98ae28db7272705,Theoretical Informatics and Applications Eye Localization for Face Recognition *,"Theoretical Informatics and Applications +Informatique Th´eorique et Applications +Will be set by the publisher +EYE LOCALIZATION FOR FACE RECOGNITION ∗ +PAOLA CAMPADELLI, RAFFAELLA LANZAROTTI, GIUSEPPE LIPORI 1"
+ea5dd7125c73756d7d81e49fa9826198f533cff7,Appearance tracking by transduction in surveillance scenarios,"8th IEEE International Conference on Advanced Video and Signal-Based Surveillance, 2011 +978-1-4577-0845-9/11/$26.00 c(cid:13)2011 IEEE"
+eabbf37742b79147c3bcf42d376dbceaae869a01,Recurrent Multimodal Interaction for Referring Image Segmentation,"Recurrent Multimodal Interaction for Referring Image Segmentation +Chenxi Liu1 +Zhe Lin2 Xiaohui Shen2 +Jimei Yang2 Xin Lu2 Alan Yuille1 +Johns Hopkins University1 Adobe Research2 +{cxliu, +{zlin, xshen, jimyang,"
ea079334121a0ba89452036e5d7f8e18f6851519,Unsupervised incremental learning of deep descriptors from video streams,"UNSUPERVISED INCREMENTAL LEARNING OF DEEP DESCRIPTORS FROM VIDEO STREAMS Federico Pernici and Alberto Del Bimbo @@ -13248,6 +46236,34 @@ Action Classification and Detection Mohammadreza Zolfaghari , Gabriel L. Oliveira, Nima Sedaghat, and Thomas Brox University of Freiburg Freiburg im Breisgau, Germany"
+eadf6cb8f16c507e4a73db33da201cde3d9b2f5a,PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing,"PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network +for Simultaneous Depth Estimation and Scene Parsing +Dan Xu1, Wanli Ouyang2, Xiaogang Wang3, Nicu Sebe1 +The University of Trento, 2The University of Sydney, 3The Chinese University of Hong Kong +{dan.xu,"
+ea8cb4a79b211fb288f747bdd64b3fc36e11c0fc,Automatic Facial Action Unit Recognition by Modeling Their Semantic And Dynamic Relationships,"Chapter 10 +Automatic Facial Action Unit Recognition +y Modeling Their Semantic And Dynamic +Relationships +Yan Tong, Wenhui Liao, and Qiang Ji"
+ea939d72d55c095e57fedaaf2aa49f596002c196,A Part based Modeling Approach for Invoice Parsing,
+ea638559b6dd6b5520f9abe2674b92c07873a157,Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks,"Semantic Segmentation of Earth Observation +Data Using Multimodal and Multi-scale Deep +Networks +Nicolas Audebert1,2, Bertrand Le Saux1, S´ebastien Lef`evre2 +ONERA, The French Aerospace Lab, F-91761 Palaiseau, France - +{nicolas.audebert,bertrand.le +Univ. Bretagne-Sud, UMR 6074, IRISA, F-56000 Vannes, France -"
+eaaf411826d129c2a31d997dc3f5f708a8186656,SDALF: Modeling Human Appearance with Symmetry-Driven Accumulation of Local Features,"SDALF: Modeling Human Appearance with +Symmetry-Driven Accumulation of Local +Features +Loris Bazzani and Marco Cristani and Vittorio Murino"
+eaaec63bb86ee87d56f5844951143485ce84a4ea,GANtruth – an unpaired image-to-image translation method for driving scenarios,"GANtruth – an unpaired image-to-image translation +method for driving scenarios +Anonymous Author(s) +Affiliation +Address +email"
ea482bf1e2b5b44c520fc77eab288caf8b3f367a,Flexible Orthogonal Neighborhood Preserving Embedding,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
ea6f5c8e12513dbaca6bbdff495ef2975b8001bd,Applying a Set of Gabor Filter to 2D-Retinal Fundus Image to Detect the Optic Nerve Head (ONH),"Applying a Set of Gabor Filter to 2D-Retinal Fundus Image to Detect the Optic Nerve Head (ONH) @@ -13269,6 +46285,20 @@ Electrical Engineering, University of Tunis El-Manar, ENSIT 5, Avenue Taha Hussein, B. P.: 56, Bab Menara, 1008 Tunis, Tunisia,"
+ea8abe31f3cac058cf757f16e1eefa11295322bc,Ensemble of Deep Learned Features for Melanoma Classification,"Ensemble of Deep Learned Features for Melanoma +Classification +Loris Nanni1*, Alessandra Lumini2, Stefano Ghidoni1 +Department of Information Engineering, University of Padua, via Gradenigo 6/B, 35131 +Padova, Italy. +Department of Computer Science and Engineering, University of Bologna, via Sacchi 3, +7521, Cesena (FC), Italy."
+ead2701e883174028a1b1b25472bc83bedc330aa,"Face Recognition Methods Based on Feedforward Neural Networks, Principal Component Analysis and Self-Organizing Map","RADIOENGINEERING, VOL. 16, NO. 1, APRIL 2007 +Face Recognition Methods Based on Feedforward +Neural Networks, Principal Component Analysis +nd Self-Organizing Map +Miloš ORAVEC, Jarmila PAVLOVIČOVÁ +Dept. of Telecommunications, Faculty of Electrical Engineering and Information Technology, Slovak University of +Technology, Ilkovičova 3, 812 19 Bratislava, Slovak Republic"
eafda8a94e410f1ad53b3e193ec124e80d57d095,Observer-Based Measurement of Facial Expression With the Facial Action Coding System,"Jeffrey F. Cohn Zara Ambadar Paul Ekman @@ -13289,6 +46319,11 @@ perception (Ambadar, Schooler, & Cohn, 2005), social pro- esses (Hatfield, Cacioppo, & Rapson, 1992; Hess & Kirouac, 000), and emotion disorder (Kaiser, 2002; Sloan, Straussa, Quirka, & Sajatovic, 1997), to name a few."
+ea0785c2d4ac8f8d6415cffdb83547bfc4e7adba,Spontaneous Facial Expression Recognition using Sparse Representation,"Spontaneous Facial Expression Recognition using Sparse Representation +Univ. Grenoble Alpes, GIPSA-Lab, F-38000 Grenoble, France CNRS, GIPSA-Lab, F-38000 Grenoble, France +Dawood Al Chanti1 and Alice Caplier1 +Keywords: +Dictionary learning, Random projection, Spontaneous facial expression, Sparse representation."
ea85378a6549bb9eb9bcc13e31aa6a61b655a9af,Template Protection for PCA - LDA - based 3 D Face Recognition System,"Diplomarbeit Template Protection for PCA-LDA-based 3D Face Recognition System @@ -13307,6 +46342,147 @@ SIANI Edif. Central del Parque Cient´ıfico Tecnol´ogico Universidad de Las Palmas de Gran Canaria 5017 - Spain"
+eace134548f9be17c243b06f133bfac76a797676,ADNet: A Deep Network for Detecting Adverts,"ADNet: A Deep Network for Detecting Adverts +Murhaf Hossari(cid:63)1, Soumyabrata Dev(cid:63)1, Matthew Nicholson1, Killian McCabe1, +Atul Nautiyal1, Clare Conran1, Jian Tang3, Wei Xu3, and Fran¸cois Piti´e1,2 +The ADAPT SFI Research Centre, Trinity College Dublin +Department of Electronic & Electrical Engineering, Trinity College Dublin +Huawei Ireland Research Center, Dublin"
+ea5eaaadb8bc928fb7543d6fa24f9f4a229ff979,Mirror Neuron Forum.,"Perspectives on Psychological +Science +http://pps.sagepub.com/ +Vittorio Gallese, Morton Ann Gernsbacher, Cecilia Heyes, Gregory Hickok and Marco Iacoboni +Mirror Neuron Forum +Perspectives on Psychological Science +DOI: 10.1177/1745691611413392 +2011 6: 369 +The online version of this article can be found at: +http://pps.sagepub.com/content/6/4/369 +Perspectives on Psychological Science +can be found at: +Additional services and information for +Email Alerts: +Subscriptions: +Reprints: +Permissions: +http://pps.sagepub.com/cgi/alerts +http://pps.sagepub.com/subscriptions +http://www.sagepub.com/journalsReprints.nav"
+ea3353efbe7b856ced106718d04ea7d83e2a2310,A Survey of Video Object Tracking,"International Journal of Control and Automation +Vol. 8, No. 9 (2015), pp. 303-312 +http://dx.doi.org/10.14257/ijca.2015.8.9.29 +A Survey of Video Object Tracking +Meng Li, Zemin Cai1, Chuliang Wei and Ye Yuan +Department of Electronic Engineering, College of Engineering, Shantou +University, China +Guangdong Provicial Key Laboratory of Digital Signal and Image Processing +Techniques, China +Corresponding author,"
+ea572991a75acfc8a8791955f670d2c48db49023,Arbitrary-Shape Object Localization Using Adaptive Image Grids,"Arbitrary-Shape Object Localization using +Adaptive Image Grids +Chunluan Zhou and Junsong Yuan +School of EEE, Nanyang Technology University, Singapore"
+ea099ee1183145131e29009f2af0e4b13ac583f0,Effects of exposure to facial expression variation in face learning and recognition,"Psychological Research (2015) 79:1042–1053 +DOI 10.1007/s00426-014-0627-8 +O R I G I N A L A R T I C L E +Effects of exposure to facial expression variation in face learning +nd recognition +Chang Hong Liu • Wenfeng Chen • James Ward +Received: 25 July 2014 / Accepted: 6 November 2014 / Published online: 15 November 2014 +Ó The Author(s) 2014. This article is published with open access at Springerlink.com"
+eae625274767cb695fa2121ccdcb30828ffc9b66,Social Context Modulates Facial Imitation of Children’s Emotional Expressions,"RESEARCH ARTICLE +Social Context Modulates Facial Imitation of +Children’s Emotional Expressions +Peter A. Bos*, Nadine Jap-Tjong, Hannah Spencer, Dennis Hofman +Department of Experimental Psychology, Utrecht University, Utrecht, The Netherlands"
+ea9857a5e5c72d435054a5a73e50dafb755a2597,Comparative study of histogram distance measures for re-identification,"Comparative study of histogram distance measures for re-identification +Pedro A. Mar´ın-Reyes, Javier Lorenzo-Navarro, Modesto Castrill´on-Santana +Instituto Universitario SIANI +Universidad de Las Palmas de Gran Canaria"
+ea2d43aa2490331cd1406e1432ce706c53139323,Tracked Instance Search,"TRACKED INSTANCE SEARCH +Andreu Girbau† +Ryota Hinami(cid:63) +Shin’ichi Satoh(cid:63) +Universitat Polit`ecnica de Catalunya, Barcelona +(cid:63) National Institute of Informatics, Tokyo"
+ea251fc90da36fdbaf7be76f449a9e0dac1d42ef,Brain mechanisms for processing direct and averted gaze in individuals with autism.,"J Autism Dev Disord +DOI 10.1007/s10803-011-1197-x +O R I G I N A L P A P E R +Brain Mechanisms for Processing Direct and Averted Gaze +in Individuals with Autism +Naomi B. Pitskel • Danielle Z. Bolling • Caitlin M. Hudac • +Stephen D. Lantz • Nancy J. Minshew • Brent C. Vander Wyk • +Kevin A. Pelphrey +Ó Springer Science+Business Media, LLC 2011"
+e1f794bacd01eecb623bead652bdc9f86e17944e,Affective Environment for Java Programming Using Facial and EEG Recognition,"Affective Environment for Java Programming +Using Facial and EEG Recognition +María Lucía Barrón-Estrada, Ramón Zatarain-Cabada, Claudia Guadalupe +Aispuro-Gallegos, Catalina de la Luz Sosa-Ochoa, Mario Lindor-Valdez +Instituto Tecnológico de Culiacán, Culiacán, Sinaloa, +Mexico +{lbarron, rzatarain, m03171007, m07170739,"
+e1e5d64318ec0a493995fb83ef4f433ddde82e77,Affects the Gaze-cueing Effect,"(cid:5)(cid:36)(cid:57)(cid:50)(cid:44)(cid:39)(cid:44)(cid:49)(cid:42)(cid:3)(cid:50)(cid:53)(cid:3)(cid:36)(cid:51)(cid:51)(cid:53)(cid:50)(cid:36)(cid:38)(cid:43)(cid:44)(cid:49)(cid:42)(cid:3)(cid:40)(cid:60)(cid:40)(cid:54)(cid:5)(cid:34)(cid:3)(cid:44)(cid:49)(cid:55)(cid:53)(cid:50)(cid:57)(cid:40)(cid:53)(cid:54)(cid:44)(cid:50)(cid:49)(cid:18)(cid:40)(cid:59)(cid:55)(cid:53)(cid:36)(cid:57)(cid:40)(cid:53)(cid:54)(cid:44)(cid:50)(cid:49) +(cid:36)(cid:41)(cid:41)(cid:40)(cid:38)(cid:55)(cid:54)(cid:3)(cid:55)(cid:43)(cid:40)(cid:3)(cid:42)(cid:36)(cid:61)(cid:40)(cid:16)(cid:38)(cid:56)(cid:40)(cid:44)(cid:49)(cid:42)(cid:3)(cid:40)(cid:41)(cid:41)(cid:40)(cid:38)(cid:55) +(cid:16)(cid:16)(cid:48)(cid:68)(cid:81)(cid:88)(cid:86)(cid:70)(cid:85)(cid:76)(cid:83)(cid:87)(cid:3)(cid:39)(cid:85)(cid:68)(cid:73)(cid:87)(cid:16)(cid:16) +(cid:38)(cid:82)(cid:74)(cid:81)(cid:76)(cid:87)(cid:76)(cid:89)(cid:72)(cid:3)(cid:51)(cid:85)(cid:82)(cid:70)(cid:72)(cid:86)(cid:86)(cid:76)(cid:81)(cid:74) +(cid:3) +(cid:3) +(cid:48)(cid:68)(cid:81)(cid:88)(cid:86)(cid:70)(cid:85)(cid:76)(cid:83)(cid:87)(cid:3)(cid:49)(cid:88)(cid:80)(cid:69)(cid:72)(cid:85)(cid:29) +(cid:41)(cid:88)(cid:79)(cid:79)(cid:3)(cid:55)(cid:76)(cid:87)(cid:79)(cid:72)(cid:29) +(cid:36)(cid:85)(cid:87)(cid:76)(cid:70)(cid:79)(cid:72)(cid:3)(cid:55)(cid:92)(cid:83)(cid:72)(cid:29) +(cid:46)(cid:72)(cid:92)(cid:90)(cid:82)(cid:85)(cid:71)(cid:86)(cid:29) +(cid:38)(cid:82)(cid:85)(cid:85)(cid:72)(cid:86)(cid:83)(cid:82)(cid:81)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:29) +(cid:38)(cid:82)(cid:85)(cid:85)(cid:72)(cid:86)(cid:83)(cid:82)(cid:81)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:3)(cid:54)(cid:72)(cid:70)(cid:82)(cid:81)(cid:71)(cid:68)(cid:85)(cid:92) +(cid:44)(cid:81)(cid:73)(cid:82)(cid:85)(cid:80)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:29) +(cid:38)(cid:82)(cid:85)(cid:85)(cid:72)(cid:86)(cid:83)(cid:82)(cid:81)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:10)(cid:86)(cid:3)(cid:44)(cid:81)(cid:86)(cid:87)(cid:76)(cid:87)(cid:88)(cid:87)(cid:76)(cid:82)(cid:81)(cid:29) +(cid:38)(cid:82)(cid:85)(cid:85)(cid:72)(cid:86)(cid:83)(cid:82)(cid:81)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:10)(cid:86)(cid:3)(cid:54)(cid:72)(cid:70)(cid:82)(cid:81)(cid:71)(cid:68)(cid:85)(cid:92) +(cid:44)(cid:81)(cid:86)(cid:87)(cid:76)(cid:87)(cid:88)(cid:87)(cid:76)(cid:82)(cid:81)(cid:29) +(cid:41)(cid:76)(cid:85)(cid:86)(cid:87)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:29) +(cid:41)(cid:76)(cid:85)(cid:86)(cid:87)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:3)(cid:54)(cid:72)(cid:70)(cid:82)(cid:81)(cid:71)(cid:68)(cid:85)(cid:92)(cid:3)(cid:44)(cid:81)(cid:73)(cid:82)(cid:85)(cid:80)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:29) +(cid:50)(cid:85)(cid:71)(cid:72)(cid:85)(cid:3)(cid:82)(cid:73)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:86)(cid:29) +(cid:50)(cid:85)(cid:71)(cid:72)(cid:85)(cid:3)(cid:82)(cid:73)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:86)(cid:3)(cid:54)(cid:72)(cid:70)(cid:82)(cid:81)(cid:71)(cid:68)(cid:85)(cid:92)(cid:3)(cid:44)(cid:81)(cid:73)(cid:82)(cid:85)(cid:80)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:29)"
+e19b60e5b8083828285a2baa781ceaad27f6353c,The accuracy and value of machine-generated image tags: design and user evaluation of an end-to-end image tagging system,"The Accuracy and Value of Machine-Generated Image Tags +Design and User Evaluation of an End-to-End Image Tagging System +Lexing Xie, Apostol Natsev, Matthew Hill, John R. Smith +IBM Watson Research Center, Hawthorne, NY, USA +{xlx, natsev, mh, +Alex Phillips +IBM Global Business Services, United Kingdom"
+e18cc09c3d3d79df6cd40ea5cf13ad40eacb8a73,Visual Transfer Learning: Informal Introduction and Literature Overview,"Visual Transfer Learning: Informal Introduction +nd Literature Overview +Erik Rodner +University of Jena, Germany +August 2011"
+e151c99b5e55bfc03047a2c6c2118cd9e4ad829b,Perspectives on Deep Multimodel Robot Learning,"Perspectives on Deep Multimodel +Robot Learning +Wolfram Burgard, Abhinav Valada, Noha Radwan, Tayyab Naseer, Jingwei Zhang, +Johan Vertens, Oier Mees, Andreas Eitel and Gabriel Oliveira"
+e1e60501677ae67c6a682bac2c17e4fc904ee380,Performance Analysis of Local Binary Pattern Variants in Texture Classification,"Performance Analysis of Local Binary Pattern +International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) +Volume 06, Issue 05, May 2017, ISSN: 2278 – 1323 +Variants in Texture Classification +Ch. Sudha Sree1, M. V. P Chandra Sekhara Rao2 +,2Department of CA, Department of CSE, R.V.R &J.C College of Engineering +Guntur, India"
+e1371af87f6d5e22ef6d8c5f9977f5e924f176f6,Bidirectional Retrieval Made Simple Jônatas Wehrmann,"Bidirectional Retrieval Made Simple +Jˆonatas Wehrmann +School of Technology +Rodrigo C. Barros +School of Technology +Pontif´ıcia Universidade Cat´olica +Pontif´ıcia Universidade Cat´olica +do Rio Grande do Sul +do Rio Grande do Sul"
+e1725b71f3f127d6a49d24f14bee05aada1e2f96,Part-Based Deep Hashing for Large-Scale Person Re-Identification,"Part-based Deep Hashing for Large-scale +Person Re-identification∗ +Fuqing Zhu, Xiangwei Kong, Member, IEEE, Liang Zheng, Member, IEEE, Haiyan Fu, Member, IEEE, +Qi Tian, Fellow, IEEE,"
+e1660c10ae661cf951602232b36047b19198f599,Web Image Search Using Attribute Assisted Re- Ranking Model,"Vol-2 Issue-1 2016 +IJARIIE-ISSN(O)-2395-4396 +Web Image Search Using Attribute Assisted Re- +Ranking Model +Ganesh R Nagare1, Ashok V Markad 2 +Information Technology, Amrutvahini College of Engineering, Maharashtra, India"
e1f790bbedcba3134277f545e56946bc6ffce48d,Image Retrieval Using Attribute Enhanced Sparse Code Words,"International Journal of Innovative Research in Science, Engineering and Technology (An ISO 3297: 2007 Certified Organization) @@ -13317,9 +46493,59 @@ Image Retrieval Using Attribute Enhanced M.Balaganesh1, N.Arthi2 Associate Professor, Department of Computer Science and Engineering, SRV Engineering College, sembodai, india1 P.G. Student, Department of Computer Science and Engineering, SRV Engineering College, sembodai, India 2"
+e135f8118145b6a2e2a6a2088c04c26ca6d38642,Dynamic Biometrics Fusion at Feature Level for Video-Based Human Recognition,
+e10662a59b5f8e1f5684409023f11ca727647320,Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images,"Performance Evaluation of Deep Learning Networks for +Semantic Segmentation of Traffic Stereo-Pair Images +Vlad Taran, Nikita Gordienko, Yuriy Kochura, Yuri Gordienko, Alexandr Rokovyi, Oleg +Alienin, Sergii Stirenko +National Technical University of Ukraine ""Igor Sikorsky Kyiv Polytechnic Institute"", +Kyiv, Ukraine +Semantic image segmentation is one the most demanding task, especially for analysis of traffic conditions +for self-driving cars. Here the results of application of several deep learning architectures (PSPNet and +ICNet) for semantic image segmentation of traffic stereo-pair images are presented. The images from +Cityscapes dataset and custom urban images were analyzed as to the segmentation accuracy and image +inference time. For the models pre-trained on Cityscapes dataset, the inference time was equal in the limits +of standard deviation, but the segmentation accuracy was different for various cities and stereo channels +even. The distributions of accuracy (mean intersection over union — mIoU) values for each city and channel +re asymmetric, long-tailed, and have many extreme outliers, especially for PSPNet network in comparison +to ICNet network. Some statistical properties of these distributions (skewness, kurtosis) allow us to +distinguish these two networks and open the question about relations between architecture of deep learning +networks and statistical distribution of the predicted results (mIoU here). The results obtained demonstrated +the different sensitivity of these networks to: (1) the local street view peculiarities in different cities that +should be taken into account during the targeted fine tuning the models before their practical applications, +(2) the right and left data channels in stereo-pairs. For both networks, the difference in the predicted results"
+e17783170ecc48253fa16123a041ae298184f4ff,Graph Embedding Algorithms Based on Neighborhood Discriminant Embedding for Face Recognition,"International Journal of Computer Information Systems and Industrial Management Applications. +ISSN 2150-7988 Volume 4 (2012) pp. 374–382 +(cid:13) MIR Labs, www.mirlabs.net/ijcisim/index.html +Graph Embedding Algorithms Based on +Neighborhood Discriminant Embedding for Face +Recognition +Dexing Zhong1,2, Jiuqiang Han1, Yongli Liu1 and Shengbin Li2 +Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi’an Jiaotong University, +8 Xianning West Road, Xian, 710049 P. R. China +State Key Laboratory of Ministry of Health for Forensic Sciences, Xian Jiaotong University, +76 Yanta West Road, Xian, 710061 P. R. China"
+e1e2b6a8944a4e6f195b6f7371ee9e6b0684ae6b,Generating Personalized Virtual Agent in Speech Dialogue System for People with Dementia,"Generating Personalized Virtual Agent +in Speech Dialogue System for People +with Dementia +Shota Nakatani1(B), Sachio Saiki1, Masahide Nakamura1, and Kiyoshi Yasuda2 +Graduate School of System Informatics Kobe University, +-1 Rokkodai, Nada, Kobe, Japan +Chiba Rosai Hospital, 2-16 Tatsumidai-higashi, Ichihara, Japan"
e19ebad4739d59f999d192bac7d596b20b887f78,Learning Gating ConvNet for Two-Stream based Methods in Action Recognition,"Learning Gating ConvNet for Two-Stream based Methods in Action Recognition Jiagang Zhu1,2, Wei Zou1, Zheng Zhu1,2"
+e1cb110c45c4416f7aff490db2674abe1460259e,Hard-Aware Point-to-Set Deep Metric for Person Re-identification,"Hard-AwarePoint-to-SetDeepMetricforPersonRe-identificationRuiYu1,ZhiyongDou1,SongBai1,ZhaoxiangZhang2,YongchaoXu1( ),andXiangBai1("
+e163118b4a5b8016754134215433eee1f2c0065a,3-D Shape Matching for Face Analysis and Recognition,"-D Shape Matching for Face Analysis and Recognition +Wei Quan, Bogdan J. Matuszewski and Lik-Kwan Shark +Robotics and Computer Vision Research Laboratory, Applied Digital Signal and Image Processing (ADSIP) Research +Centre, University of Central Lancashire, Preston PR1 2HE, U.K. +Keywords: +Face Recognition, Shape Matching and Modelling, Isometric Embedding Representation, Non-Rigid +Deformation Registration."
+e1fb8ab53996f06e9a35de6b553333bd6279bcbd,Learning Multilayer Channel Features for Pedestrian Detection,"Learning Multilayer Channel Features for +Pedestrian Detection +Jiale Cao, Yanwei Pang, and Xuelong Li"
e1d726d812554f2b2b92cac3a4d2bec678969368,Human Action Recognition Bases on Local Action Attributes,"J Electr Eng Technol.2015; 10(?): 30-40 http://dx.doi.org/10.5370/JEET.2015.10.2.030 ISSN(Print) @@ -13328,6 +46554,24 @@ ISSN(Online) 2093-7423 Human Action Recognition Bases on Local Action Attributes Jing Zhang*, Hong Liu*, Weizhi Nie† Lekha Chaisorn**, Yongkang Wong** nd Mohan S Kankanhalli**"
+e1140b86c64549cbcd138f868c82ee8aad77d103,Occlusion Handling using Semantic Segmentation and Visibility-Based Rendering for Mixed Reality,"Occlusion Handling using Semantic Segmentation and +Visibility-Based Rendering for Mixed Reality +Menandro Roxas +Tomoki Hori +Taiki Fukiage +Tokyo, Japan +Yasuhide Okamoto +Takeshi Oishi +(cid:140)e University of Tokyo"
+e1f815c50a6c0c6d790c60a1348393264f829e60,Pedestrian Detection and Tracking in Surveillance Video,"PEDESTRIAN DETECTION AND TRACKING IN +SURVEILLANCE VIDEO +PENNY CHONG +A project report submitted in partial fulfilment of the +requirements for the award of Bachelor of Science (Hons.) +Applied Mathematics with Computing +Lee Kong Chian Faculty of Engineering and Science +Universiti Tunku Abdul Rahman +April 2016"
e1e6e6792e92f7110e26e27e80e0c30ec36ac9c2,Ranking with Adaptive Neighbors,"TSINGHUA SCIENCE AND TECHNOLOGY ISSNll1007-0214 0?/?? pp???–??? @@ -13335,10 +46579,35 @@ DOI: 10.26599/TST.2018.9010000 Volume 1, Number 1, Septembelr 2018 Ranking with Adaptive Neighbors Muge Li, Liangyue Li, and Feiping Nie∗"
+e1e1b3683ac278386cf1569e97f9aced0923f4a0,Hyperdrive: A Systolically Scalable Binary-Weight CNN Inference Engine for mW IoT End-Nodes,"Hyperdrive: A Systolically Scalable Binary-Weight +CNN Inference Engine for mW IoT End-Nodes +Renzo Andri∗, Lukas Cavigelli∗, Davide Rossi†, Luca Benini∗† +Integrated Systems Laboratory, ETH Zurich, Zurich, Switzerland +DEI, University of Bologna, Bologna, Italy"
+cd01a0018f2b8f1211e8dfe311c28e32773c58dc,Globally-Optimal Inlier Set Maximisation for Simultaneous Camera Pose and Feature Correspondence,"Globally-Optimal Inlier Set Maximisation for +Simultaneous Camera Pose and Feature Correspondence +Dylan Campbell1,2, Lars Petersson1,2, Laurent Kneip1 and Hongdong Li1 +Australian National University* +Data61 – CSIRO"
cd9666858f6c211e13aa80589d75373fd06f6246,A Novel Time Series Kernel for Sequences Generated by LTI Systems,"A Novel Time Series Kernel for Sequences Generated by LTI Systems Liliana Lo Presti, Marco La Cascia V.le delle Scienze Ed.6, DIID, Universit´a degli studi di Palermo, Italy"
+cd2c1e542ae8c08cfb8baea3dff788d143232de8,Multiview Human Synthesis From a Single View,"Multiview Human Synthesis From a Singleview +Si Wen (06246679), Tiancong Zhou (06247022), Honghao Qiu (06246258) +{wensi, longztc,"
+cd36768795c696c990ff5c89be8d8b3b205858bd,CliCR: A Dataset of Clinical Case Reports for Machine Reading Comprehension,"CliCR: A Dataset of Clinical Case Reports for Machine +Reading Comprehension∗ +Simon ˇSuster and Walter Daelemans +Computational Linguistics & Psycholinguistics Research Center, +University of Antwerp, Belgium"
+cd6978bf6b98794552bd52d166b5e04626fb6d6d,A Review on Face Recognition in various Illuminations,"A Review on Face Recognition in various +Illuminations +Saurabh D. Parmar , Vaishali j. kalariya +CE/IT Department-School of Engineering,R.K. University,Rajkot"
+cd0a04c0af9b6c523884415ba54bff370fd02fab,Generalized Sparselet Models for Real-Time Multiclass Object Recognition,"Generalized Sparselet Models for Real-Time +Multiclass Object Recognition +Hyun Oh Song, Ross Girshick, Stefan Zickler, Christopher Geyer, Pedro Felzenszwalb, and Trevor Darrell"
cd444ee7f165032b97ee76b21b9ff58c10750570,Table of Contents.,"UNIVERSITY OF CALIFORNIA, IRVINE Relational Models for Human-Object Interactions and Object Affordances @@ -13353,6 +46622,26 @@ Professor Deva Ramanan, Chair Professor Charless Fowlkes Professor Padhraic Smyth Professor Serge Belongie"
+cd0f7b3f545cc4bfa5e2d7185789e8ead7e3cee2,"Children’s and Adults’ Predictions of Black, White, and Multiracial Friendship Patterns","Journal of Cognition and Development +ISSN: 1524-8372 (Print) 1532-7647 (Online) Journal homepage: http://www.tandfonline.com/loi/hjcd20 +Children’s and Adults’ Predictions of Black, White, +nd Multiracial Friendship Patterns +Steven O. Roberts, Amber D. Williams & Susan A. Gelman +To cite this article: Steven O. Roberts, Amber D. Williams & Susan A. Gelman (2017) Children’s +nd Adults’ Predictions of Black, White, and Multiracial Friendship Patterns, Journal of Cognition +nd Development, 18:2, 189-208, DOI: 10.1080/15248372.2016.1262374 +To link to this article: http://dx.doi.org/10.1080/15248372.2016.1262374 +Accepted author version posted online: 22 +Nov 2016. +Published online: 22 Nov 2016. +Submit your article to this journal +Article views: 91 +View related articles +View Crossmark data +Citing articles: 1 View citing articles +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=hjcd20 +Download by: [University of Michigan]"
cd596a2682d74bdfa7b7160dd070b598975e89d9,Mood Detection: Implementing a facial expression recognition system,"Mood Detection: Implementing a facial expression recognition system Neeraj Agrawal, Rob Cosgriff and Ritvik Mudur @@ -13373,8 +46662,32 @@ works well with such an approach. Figure 1 – Overview of our system design . Image pre-processing We performed pre-processing on the images used to train and test our algorithms as follows:"
+cd490432e35ed5c5b7d80e1525e2780d7467ffb6,Background Estimation of Lost Values Using Kinect’s Sensor in an Inpainting Technique,"International Journal of Scientific Research Engineering & Technology (IJSRET), ISSN 2278 – 0882 +Vo lu me 3, Issue 8, Nove mber 2014 +BACKGROUND ESTIMATION OF LOST VALUES USING +KINECT’S SENSOR IN AN INPAINTING TECHNIQUE +* PG Schola r, Dept of EEE [Embedded systems technologies], #Assistant Professsor, +Dept of EEE, Kongunadu College Of Engineering & Technology,Trichy, Ta mil Nadu, India +*S.Kavitha, #Ms.S.Hemalatha"
+cd5ef3aeebc231e2c833ef55cf0571aa990c5ff8,Image Quality Assessment Techniques Improve Training,"Under review as a conference paper at ICLR 2018 +IMAGE QUALITY ASSESSMENT TECHNIQUES IMPROVE +TRAINING AND EVALUATION OF ENERGY-BASED +GENERATIVE ADVERSARIAL NETWORKS +Anonymous authors +Paper under double-blind review"
cda4fb9df653b5721ad4fe8b4a88468a410e55ec,Gabor wavelet transform and its application,"Gabor wavelet transform and its application Wei-lun Chao R98942073"
+cd855c776240150f4dba7a5975c7011a9c6737ac,On Accurate and Reliable Anomaly Detection for Gas Turbine Combustors: A Deep Learning Approach,"On Accurate and Reliable Anomaly Detection for Gas Turbine +Combustors: A Deep Learning Approach +Weizhong Yan1 and Lijie Yu2 +General Electric Global Research Center, Niskayuna, New York 12309, USA +General Electric Power & Water Engineering, Atlanta, Georgia 30339, USA"
+cdba015be9db1e047a51b7e06403528b3551587e,SHOG - Spherical HOG Descriptors for Rotation Invariant 3D Object Detection,"SHOG - Spherical HOG Descriptors for +Rotation Invariant 3D Object Detection +Henrik Skibbe1,3, Marco Reisert2 and Hans Burkhardt1,3 +Department of Computer Science, University of Freiburg, Germany +Dept. of Diagnostic Radiology, Medical Physics, University Medical Center, Freiburg +Center for Biological Signalling Studies (BIOSS), University of Freiburg"
cd3005753012409361aba17f3f766e33e3a7320d,Multilinear Biased Discriminant Analysis: A Novel Method for Facial Action Unit Representation,"Multilinear Biased Discriminant Analysis: A Novel Method for Facial Action Unit Representation Mahmoud Khademi†, Mehran Safayani†and Mohammad T. Manzuri-Shalmani† @@ -13385,14 +46698,101 @@ Hemanta Sapkota Daniel Rosser Yusuf Pisan Games Studio, Faculty of Engineering and IT, University of Technology, Sydney"
+cd4252d1f0a124dcc91af28f527ad1fa7be3a195,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
cd7a7be3804fd217e9f10682e0c0bfd9583a08db,Women also Snowboard: Overcoming Bias in Captioning Models,"Women also Snowboard: Overcoming Bias in Captioning Models Lisa Anne Hendricks * 1 Kaylee Burns * 1 Kate Saenko 2 Trevor Darrell 1 Anna Rohrbach 1"
+cca228b47a603a9b9e2a1e3a1b278b35612d078d,Randomized Face Recognition on Partially Occluded Images,"Randomized Face Recognition on Partially +Occluded Images +Ariel Morelli Andres, Sebastian Padovani, Mariano Tepper, Marta Mejail, and +Julio Jacobo +Departamento de Computación, Facultad de Ciencias Exactas y Naturales, +Universidad de Buenos Aires, Argentina."
ccfcbf0eda6df876f0170bdb4d7b4ab4e7676f18,A Dynamic Appearance Descriptor Approach to Facial Actions Temporal Modeling,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JUNE 2011 A Dynamic Appearance Descriptor Approach to Facial Actions Temporal Modelling Bihan Jiang, Student Member, IEEE, Michel Valstar, Member, IEEE, Brais Martinez, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+ccd5bd5ce40640ebc6665b97a86ba3d28e457d11,Contributions to a fast and robust object recognition in images. (Contributions à une reconnaissance d'objet rapide et robuste en images),"Contributions to a fast and robust object recognition in +images +J´erˆome Revaud +To cite this version: +J´erˆome Revaud. Contributions to a fast and robust object recognition in images. Other [cs.OH]. +INSA de Lyon, 2011. English. <NNT : 2011ISAL0042>. <tel-00694442> +HAL Id: tel-00694442 +https://tel.archives-ouvertes.fr/tel-00694442 +Submitted on 4 May 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de +recherche fran¸cais ou ´etrangers, des laboratoires"
+cc5f4d5aa9c3ffa75a335f3305a1caf9cbdeb71f,Learning Hierarchical Representations for Video Analysis Using Deep Learning,"LEARNING HIERARCHICAL REPRESENTATIONS FOR VIDEO ANALYSIS USING DEEP +LEARNING +YANG YANG +B.S. Beijing University of Technology, 2008 +A dissertation submitted in partial fulfilment of the requirements +for the degree of Doctor of Philosophy +in the Department of Electrical Engineering and Computer Science +in the College of Engineering and Computer Science +t the University of Central Florida +Orlando, Florida +Summer Term +Major Professor: Mubarak Shah"
+cc34b0ab84e82a6d8ebce08eff1b7556026b5352,Face Recognition using Gaussian Hermite Moments,"Special Issue of International Journal of Computer Applications (0975 – 8887) +on Software Engineering, Databases and Expert Systems – SEDEXS, September 2012 +D Face Recognition using Gaussian Hermite Moments +Naouar Belghini +Faculty of Technical Sciences +B.P. 2202 – Road of Imouzzer +Fez – Morocco +Arsalane Zarghili +Faculty of Technical Sciences +B.P. 2202 – Road of Imouzzer +Fez – Morocco +Jamal Kharroubi +Faculty of Technical Sciences +B.P. 2202 – Road of Imouzzer +Fez – Morocco"
+ccf5852bfb55e1fa6760f76139ab44dab89f2a17,"Recognize Faces across Multi - View Videos and under Varying Illumination , Facial Expressions","Recognize Faces across Multi-View Videos and +under Varying Illumination, Facial Expressions +Research Scholar, Dept. Electronics & Communication Engineering, +Mr. Steven Lawrence Fernandes1 +Karunya University, +Coimbatore, Tamil Nadu, India +Professor, Dept. Electronics & Communication Engineering, +Dr. G. Josemin Bala2 +Karunya University, +Coimbatore, Tamil Nadu, India"
+cc392ab1cfaee298e05488a4a1d84ece12220880,A new multi-scale fuzzy model for Histogram-Based Descriptors,"A NEW MULTI-SCALE FUZZY MODEL FOR HISTOGRAM-BASED DESCRIPTORS +Lunshao Chaia, Zhen Qinb, Honggang Zhanga, Jun Guoa, Bir Bhanub +Beijing University of Posts and Telecomuunictions, Beijing, 100876, China +University of California at Riverside, Riverside, CA 92521, USA"
+cc3e1a6376928138dff5582b7a56d40cfb3b7367,Cost-Effective Features for Reidentification in Camera Networks,"Cost-effective features for +re-identification in camera networks +Syed Fahad Tahir and Andrea Cavallaro"
+cc2df3a03ee731478ed48838c284ad4548563308,Towards a Better Metric for Evaluating Question Generation Systems,"Towards a Better Metric for Evaluating Question Generation Systems +Preksha Nema†‡ Mitesh M. Khapra†‡ +IIT Madras, India +Robert Bosch Center for Data Science and Artificial Intelligence, IIT Madras"
+ccd2152c77ae65e4d3d0988990f6e243133a5efc,Learning Human Activities and Poses with Interconnected Data,"Copyright +Chao-Yeh Chen"
cc3c273bb213240515147e8be68c50f7ea22777c,Gaining Insight Into Films Via Topic Modeling & Visualization,"Gaining Insight Into Films Via Topic Modeling & Visualization MISHA RABINOVICH, MFA @@ -13420,6 +46820,8 @@ Department of Electrical Engineering, IIT Delhi, New Delhi, India *Corresponding Author: Available online at: www.ijcseonline.org Received: 07/Nov/2017, Revised: 22/Nov/2017, Accepted: 14/Dec/2017, Published: 31/Dec/2017"
+cc5a62bd7c45a9ca479506acb572566331354fa3,Eye localization through multiscale sparse dictionaries,"Eye Localization through Multiscale Sparse Dictionaries +Fei Yang, Junzhou Huang, Peng Yang and Dimitris Metaxas"
ccf43c62e4bf76b6a48ff588ef7ed51e87ddf50b,Nutraceuticals and Cosmeceuticals for Human Beings–An Overview,"American Journal of Food Science and Health Vol. 2, No. 2, 2016, pp. 7-17 http://www.aiscience.org/journal/ajfsh @@ -13428,6 +46830,13 @@ Nutraceuticals and Cosmeceuticals for Human Beings–An Overview R. Ramasubramania Raja* Department of Pharmacognosy, Narayana Pharmacy College, Nellore, India"
+cc622a0ac114821be935ca9c66cc177b93e18876,Anomaly Detection Based on Trajectory Analysis Using Kernel Density Estimation and Information Bottleneck Techniques,"Anomaly Detection Based on Trajectory Analysis +Using Kernel Density Estimation and Information +Bottleneck Techniques +Yuejun Guo, Qing Xu(cid:3), Yu Yang, Sheng Liang, Yu Liu, Mateu Sbert"
+cc09cf5831fcae802ed2905a61ab502956655bbe,Shape-based instance detection under arbitrary viewpoint,"Shape-based instance detection under arbitrary +viewpoint +Edward Hsiao and Martial Hebert"
cc31db984282bb70946f6881bab741aa841d3a7c,Learning Grimaces by Watching TV,"ALBANIE, VEDALDI: LEARNING GRIMACES BY WATCHING TV Learning Grimaces by Watching TV Samuel Albanie @@ -13437,6 +46846,16 @@ http://www.robots.ox.ac.uk/~vedaldi Engineering Science Department Univeristy of Oxford Oxford, UK"
+cc246025ec8e1d32ecfbeefaba0727fdf73cd9cb,Vehicle Tracking by Simultaneous Detection and Viewpoint Estimation,"Vehicle Tracking by Simultaneous Detection and +Viewpoint Estimation +Ricardo Guerrero-G´omez-Olmedo1, Roberto L´opez-Sastre1, Saturnino +Maldonado-Basc´on1, and Antonio Fern´andez-Caballero2 +GRAM, Department of Signal Theory and Communications, UAH, Alcal´a de Henares, Spain. +Department of Computing Systems, UCLM, Albacete, Spain."
+cc9f473584c1a7f224b42d4a3a3ea2864173cc28,Hephaestus: Data Reuse for Accelerating Scientific Discovery,"Hephaestus: Data Reuse for +Accelerating Scientific Discovery +Jennie Duggan +Northwestern EECS"
cc91001f9d299ad70deb6453d55b2c0b967f8c0d,Performance Enhancement of Face Recognition in Smart TV Using Symmetrical Fuzzy-Based Quality Assessment,"OPEN ACCESS ISSN 2073-8994 Article @@ -13453,14 +46872,84 @@ Received: 31 March 2015 / Accepted: 21 August 2015 / Published: 25 August 2015" cc96eab1e55e771e417b758119ce5d7ef1722b43,An Empirical Study of Recent Face Alignment Methods,"An Empirical Study of Recent Face Alignment Methods Heng Yang, Xuhui Jia, Chen Change Loy and Peter Robinson"
+cc4a2cab31ed06d0d8723df0bdf8cd0ece71bbe9,Analysis of Using Metric Access Methods for Visual Search of Objects in Video Databases,"Analysis of Using Metric Access Methods for Visual Search +of Objects in Video Databases +Henrique Batista da Silva 1 +Zenilton Kleber Gonçalves do Patrocínio Júnior 2 +Silvio Jamil Ferzoli Guimarães 2"
+cc2bb4318191a04e3fc82c008c649f5b90151e4d,Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering,"Published as a conference paper at ICLR 2018 +BEYOND SHARED HIERARCHIES: DEEP MULTITASK +LEARNING THROUGH SOFT LAYER ORDERING +Elliot Meyerson & Risto Miikkulainen +The University of Texas at Austin and Sentient Technologies, Inc. +{ekm,"
+cca198ae698e7956992f2fb326c04965b2964a18,Learning Pain from Emotion: Transferred HoT Data Representation for Pain Intensity Estimation,"Learning Pain from Emotion: Transferred HoT +Data Representation for Pain Intensity +Estimation +Corneliu Florea1, Laura Florea1, and Constantin Vertan1 +Image Processing and Applications Laboratory, +{corneliu.florea; laura.florea; constantin.vertan} +University “Politehnica” of Bucharest,"
+e6d50d65a87425e7f0b4ec08c53d200f12f75590,The Neural Dynamics of Facial Identity Processing: Insights from EEG-Based Pattern Analysis and Image Reconstruction,"New Research +Sensory and Motor Systems +The Neural Dynamics of Facial Identity +Processing: Insights from EEG-Based Pattern +Analysis and Image Reconstruction +Dan Nemrodov,1 Matthias Niemeier,1 Ashutosh Patel,1 and Adrian Nestor1 +DOI:http://dx.doi.org/10.1523/ENEURO.0358-17.2018 +Department of Psychology, University of Toronto Scarborough, 1265 Military Trail, Toronto, Ontario M1C1A4, +Canada"
e64b683e32525643a9ddb6b6af8b0472ef5b6a37,Face Recognition and Retrieval in Video,"Face Recognition and Retrieval in Video Caifeng Shan"
+e68b1fdc4e515f947c96f65ec7ac2521edbc06b2,ROS Wrapper for Real-Time Multi-Person Pose Estimation with a Single Camera,"Technical Report +IRI--TR-17-02 +ROS Wrapper +for Real-Time Multi-Person +Pose Estimation +with a Single Camera +Autor +Miguel Arduengo +Sven Jens Jorgensen +Supervisors +Kimberly Hambuchen +Luis Sentis +Francesc Moreno +Guillem Alenyà +July 2017 +Institut de Robòtica i Informàtica Industrial"
+e6d8f332ae26e9983d5b42af4466ff95b55f2341,Pose-Normalized Image Generation for Person Re-identification,"Pose-Normalized Image Generation for Person Re-identification +Xuelin Qian1, Yanwei Fu1, Tao Xiang2, Wenxuan Wang1 +Jie Qiu3, Yang Wu3, Yu-Gang Jiang1, Xiangyang Xue1 +Fudan University; 2Queen Mary University of London; +Nara Institute of Science and Technology;"
+e63f4867c73eff9ff7cdf31246585a6915acef57,Digging Into Self-Supervised Monocular Depth Estimation,"Digging Into Self-Supervised +Monocular Depth Estimation +Cl´ement Godard +Oisin Mac Aodha +Gabriel J. Brostow"
+e6af98d1567dad534262ec0863264bb26157533f,On Multi-scale Differential Features and Their Representations for Image Retrieval and Recognition,"ON MULTI-SCALE DIFFERENTIAL FEATURES AND THEIR +REPRESENTATIONS FOR IMAGE RETRIEVAL AND RECOGNITION +A Dissertation Presented +SRINIVAS S. RAVELA +Submitted to the Graduate School of the +University of Massachusetts Amherst in partial fulfillment +of the requirements for the degree of +DOCTOR OF PHILOSOPHY +February 2003 +Department of Computer Science"
+e624c73e3057a1de75e9d6d7e813771154ff1375,Incorporating Scalability in Unsupervised Spatio- Temporal Feature Learning,"INCORPORATING SCALABILITY IN UNSUPERVISED SPATIO-TEMPORAL FEATURE +LEARNING +Sujoy Paul, Sourya Roy and Amit K. Roy-Chowdhury +Dept. of Electrical and Computer Engineering, University of California, Riverside, CA 92521"
e6b45d5a86092bbfdcd6c3c54cda3d6c3ac6b227,Pairwise Relational Networks for Face Recognition,"Pairwise Relational Networks for Face Recognition Bong-Nam Kang1[0000−0002−6818−7532], Yonghyun Kim2[0000−0003−0038−7850], nd Daijin Kim1,2[0000−0002−8046−8521] Department of Creative IT Engineering, POSTECH, Korea Department of Computer Science and Engineering, POSTECH, Korea"
+e68083909381a8fbd0e4468aa06204ac00a0e6fc,Visual Identification by Signature Tracking,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 25, NO. 2, FEBRUARY 2003 +Visual Identification by Signature Tracking +Mario E. Munich, Member, IEEE, and Pietro Perona, Member, IEEE"
e6865b000cf4d4e84c3fe895b7ddfc65a9c4aaec,"Tobias Siebenlist , Kathrin Knautz Chapter 15 . The critical role of the cold - start problem and incentive systems in emotional Web 2 . 0 services","Tobias Siebenlist, Kathrin Knautz Chapter 15. The critical role of the old-start problem and incentive systems @@ -13469,12 +46958,41 @@ e6d689054e87ad3b8fbbb70714d48712ad84dc1c,Robust Facial Feature Tracking,"Robust Fabrice Bourel, Claude C. Chibelushi, Adrian A. Low School of Computing, Staffordshire University Stafford ST18 0DG"
+e6868f172df3736e052fec4c00b63780b3d739fe,Effects of a Common Variant in the CD38 Gene on Social Processing in an Oxytocin Challenge Study: Possible Links to Autism,"Effects of a Common Variant in the CD38 Gene on Social +Processing in an Oxytocin Challenge Study: Possible Links +to Autism +Carina Sauer*,1, Christian Montag2, Christiane Wo¨ rner1, Peter Kirsch1,3 and Martin Reuter2,3 +Department of Clinical Psychology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; +Department of Differential and Biological Psychology, Rheinische Friedrich-Wilhelms-University, Bonn, Germany +The intranasal application of oxytocin (OT) has been shown to influence behavioral and neural correlates of social processing. These +effects are probably mediated by genetic variations within the OT system. One potential candidate could be the CD38 gene, which codes +for a transmembrane protein engaged in OT secretion processes. A common variation in this gene (rs3796863) was recently found to +e associated with autism spectrum disorders (ASD). Using an imaging genetics approach, we studied differential effects of an intranasal +OT application on neural processing of social stimuli in 55 healthy young men depending on their CD38 gene variant in a double-blind +placebo-controlled crossover design. Genotype had a significant influence on both behavioral and neuronal measures of social processing. +Homozygotic risk allele carriers showed slower reaction times (RT) and higher activation of left fusiform gyrus during visual processing of +social stimuli. Under OT activation differences between genotypes were more evident (though not statistically significantly increased) and +RT were accelerated in homozygotic risk allele carriers. According to our data, rs3796863 mainly influences fusiform gyrus activation, an +rea which has been widely discussed in ASD research. OT seems to modulate this effect by enhancing activation differences between +llele groups, which suggests an interaction between genetic makeup and OT availability on fusiform gyrus activation. These results +support recent approaches to apply OT as a pharmacological treatment of ASD symptoms. +Keywords: oxytocin; CD38; social processing; imaging genetics; autism +INTRODUCTION"
+e63a0ea338dfc7293ddd68074baf250e99d0c6d5,Nonlinear Supervised Dimensionality Reduction via Smooth Regular Embeddings,"Nonlinear Supervised Dimensionality Reduction via +Smooth Regular Embeddings +Department of Electrical and Electronics Engineering, METU, Ankara +Cem ¨Ornek and Elif Vural"
+e6d48d23308a9e0a215f7b5ba6ae30ee5d2f0ef5,Multi-person Tracking by Online Learned Grouping Model with Non-linear Motion Context,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. XX, NO. XX, MONTH YEAR +Multi-person Tracking by Online Learned Grouping +Model with Non-linear Motion Context +Xiaojing Chen, Zhen Qin, Le An, Member, IEEE, and Bir Bhanu, Fellow, IEEE"
+e6ca412a05002b51d358c2e3061913c3dab6b810,MoFA: Model-Based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction,
e6dc1200a31defda100b2e5ddb27fb7ecbbd4acd,Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction,"Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction Feiping Nie, Dong Xu, Member, IEEE, Ivor Wai-Hung Tsang, and Changshui Zhang, Member, IEEE , the linear regression function ("
-e6e5a6090016810fb902b51d5baa2469ae28b8a1,Energy-Efficient Deep In-memory Architecture for NAND Flash Memories,"Title +e6e5a6090016810fb902b51d5baa2469ae28b8a1,Title Energy-Efficient Deep In-memory Architecture for NAND Flash Memories,"Title Energy-Efficient Deep In-memory Architecture for NAND Flash Memories Archived version @@ -13484,11 +47002,135 @@ Published version Published paper Authors (contact) 0.1109/ISCAS.2018.8351458"
+e688a6535dbdd6ce6928bc4eb2978f39628e5302,Hand Drawn Sketch Classification Using Convolutional Neural Networks,"SUPPLEMENT ISSUE +ARTICLE +HAND DRAWN SKETCH CLASSIFICATION USING +CONVOLUTIONAL NEURAL NETWORKS +Habibollah Agh Atabay* +Department of Computer, Gonbad Kavous University, Gonbad Kavous, IRAN"
+e6aadde93aedc06525523415e574507cf5c8cc44,End-to-end optimization of goal-driven and visually grounded dialogue systems,"End-to-end optimization of goal-driven and visually grounded dialogue systems +Florian Strub +Univ. Lille, CNRS, Centrale Lille, Inria, +UMR 9189 - CRIStAL, F-59000 Lille, France +Harm de Vries +University of Montreal +Jeremie Mary +Univ. Lille, CNRS, Centrale Lille, Inria, +UMR 9189 - CRIStAL, F-59000 Lille, France +Bilal Piot +DeepMind"
+e605242319ba495bc5f47abe9f1c08d508d83627,Importance-Aware Semantic Segmentation for Autonomous Driving System,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
e6178de1ef15a6a973aad2791ce5fbabc2cb8ae5,Improving Facial Landmark Detection via a Super-Resolution Inception Network,"Improving Facial Landmark Detection via a Super-Resolution Inception Network Martin Knoche, Daniel Merget, Gerhard Rigoll Institute for Human-Machine Communication Technical University of Munich, Germany"
+e6beb5d95fa262b8717cc264d79a879285db15d4,Towards Transparent AI Systems: Interpreting Visual Question Answering Models,"Towards Transparent AI Systems: +Interpreting Visual Question Answering Models +Yash Goyal, Akrit Mohapatra, Devi Parikh, Dhruv Batra +{ygoyal, akrit, parikh, +Virginia Tech"
+e68ef9597613cd2b6cf76e81c13eb061ee468485,Latent Convolutional Models,"Published as a conference paper at ICLR 2019 +LATENT CONVOLUTIONAL MODELS +ShahRukh Athar +Skolkovo Institute of Science and Technology (Skoltech), Russia +Evgeny Burnaev +Victor Lempitsky∗"
+f9f08511f77c29ff948e146434dfb23608d3deb5,Question Answering Using Match-LSTM and Answer Pointer,"Question Answering Using Match-LSTM and Answer Pointer +Annie Hu, Cindy Wang, and Brandon Yang +{anniehu, ciwang, +CodaLab: anniehu +March 21, 2016 +Introduction +Machine comprehension of text is a significant problem in natural language processing today – +in this project, we tackle machine reading comprehension as applied to question answering. Our +goal is: given a question and a context paragraph, to extract from the paragraph the answer to +the question. +As an oracle, on the dataset we used, humans score over 86.8% accuracy (EM) on the test +set for this task, while the best models only achieve roughly 75%. Existing approaches to this +extractive Question Answering problem typically involve an encoding layer that encodes the +question and paragraph into a sequence, some additional layer that accounts for interaction +etween the question and paragraph, and a final decoding layer that extracts the answer from +the paragraph [2][3][4][7]. In this paper, we will follow a similar structure, using LSTMs in our +encoding and decoding layers, and calculating attention as our interaction layer. +Dataset +The dataset used is the recently released Stanford Question Answering Dataset (SQuAD)[1]. +The context paragraphs are extracted from Wikipedia, while questions and answers are human-"
+f984a9bb5c6e7b8a055b810bff468d7f8d80a7ff,Face identification by using fusing Photographic and Thermal Images,"www.jchps.com Journal of Chemical and Pharmaceutical Sciences +Face identification by using fusing Photographic and Thermal Images +M. Parisa Beham, 2M.R.H. Prasanna, 2SM.Mansoor Roomi and 1H. Jebina +ISSN: 0974-2115 +Vickram College of Engineering, Tamilnadu, India. +Thiagarajar College of Engineering, Tamilnadu, India. +*Corresponding Author:E-Mail"
+f95616b1593467f5b11689582d934da34e6ad1ee,Interactive Language Acquisition with One-shot Visual Concept Learning through a Conversational Game,"Interactive Language Acquisition with One-shot Visual Concept Learning +through a Conversational Game +Haichao Zhang†, Haonan Yu†, and Wei Xu †§ +§ National Engineering Laboratory for Deep Learning Technology and Applications, Beijing China +Baidu Research - Institue of Deep Learning, Sunnyvale USA"
+f96b3122f66c01cb78643d7e1b412e1bae16f2c4,Affective Robots : Evaluation of Automatic Emotion Recognition Approaches on a Humanoid Robot towards Emotionally Intelligent Machines,"World Academy of Science, Engineering and Technology +International Journal of Mechanical and Mechatronics Engineering +Vol:12, No:6, 2018 +Affective Robots: Evaluation of Automatic Emotion +Recognition Approaches on a Humanoid Robot +towards Emotionally Intelligent Machines +Silvia Santano Guill´en, Luigi Lo Iacono, Christian Meder"
+f98cbf32989387733529fa4fc943f0a7e97b5c07,To Know and To Learn - About the Integration of Knowledge Representation and Deep Learning for Fine-Grained Visual Categorization,
+f9129b3858c14b5f6cca1fcbf31c4816d94a5038,A Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation,"A Robust 3D-2D Interactive Tool for Scene +Segmentation and Annotation +Duc Thanh Nguyen, Binh-Son Hua∗, Lap-Fai Yu, Member, IEEE, and Sai-Kit Yeung, Member, IEEE"
+f98a975642972ce24e42e6957f63be556c11dd31,Dynamic Obstacle Detection of Road Scenes using Equi-Height Mosaicking Image,"Electronic Letters on Computer Vision and Image Analysis 13(2):13-14, 2014 +Dynamic Obstacle Detection of Road Scenes +using Equi-Height Mosaicking Image +Min Woo Park and Soon Ki Jung +School of Computer Science and Engineering, Kyungpook National University, +80 Daehak-ro, Bukgu, Daegu, Republic of Korea +Advisor/s: Soon Ki Jung +Date and location of PhD thesis defense: 3 December 2013, Kyungpook National University +Received 30 January 2014; accepted 25 May 2014"
+f95f5e43f34e1bfb425b6491fc09558c44d2973d,Soft Layer-Specific Multi-Task Summarization with Entailment and Question Generation,"Soft Layer-Specific Multi-Task Summarization +with Entailment and Question Generation +Han Guo∗ +Ramakanth Pasunuru∗ +UNC Chapel Hill +{hanguo, ram, +Mohit Bansal"
+f9bee6e61833c0323c9175402b73442d27ab9eb8,D Human Poses Estimation from a Single 2 D Silhouette,
+f9028b47a4755a7349108b1dc281f13add5c6c12,Atypical gaze patterns in children and adults with autism spectrum disorders dissociated from developmental changes in gaze behaviour,"Downloaded from +http://rspb.royalsocietypublishing.org/ +on June 9, 2017 +Proc. R. Soc. B +doi:10.1098/rspb.2010.0587 +Published online +Atypical gaze patterns in children and +dults with autism spectrum disorders +dissociated from developmental changes +in gaze behaviour +Tamami Nakano1,2, Kyoko Tanaka3, Yuuki Endo1, Yui Yamane1, +Takahiro Yamamoto4, Yoshiaki Nakano4, Haruhisa Ohta2,5, +Nobumasa Kato2,5 and Shigeru Kitazawa1,2,* +Department of Neurophysiology, and 3Department of Pediatrics, Juntendo University +School of Medicine, Tokyo, Japan +CREST, JST, Saitama, Japan +Japanese Institute for Education and Treatment, Tokyo, Japan +5Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan +Eye tracking has been used to investigate gaze behaviours in individuals with autism spectrum disorder +(ASD). However, traditional analysis has yet to find behavioural characteristics shared by both children"
+f921e6f5085f1ebbd8289081e499240a89bf6c43,Three-Dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach,"Three-Dimensional Face Recognition +in the Presence of Facial Expressions: +An Annotated Deformable Model Approach +Ioannis A. Kakadiaris, Member, IEEE, Georgios Passalis, George Toderici, +Mohammed N. Murtuza, Yunliang Lu, Nikos Karampatziakis, and Theoharis Theoharis"
+f9fdc63934841a0c4d8d29fdea80e1972ffcfe1e,Pedestrian Using Catadioptric Sensor 12,"Journal of Theoretical and Applied Information Technology +0th April 2018. Vol.96. No 8 +© 2005 – ongoing JATIT & LLS +ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 +PEDESTRIAN USING CATADIOPTRIC SENSOR +2BOUI MAROUANE, 2HADJ-ABDELKADER HICHAM, 2ABABSA FAKHR-EDDINE, +ABOUYAKHF EL HOUSSINE +LIMIARF University Mohammed V-Rabat +IBISC, University of Evry, France +E-mail:"
f9784db8ff805439f0a6b6e15aeaf892dba47ca0,"Comparing the performance of Emotion-Recognition Implementations in OpenCV, Cognitive Services, and Google Vision APIs","Comparing the performance of Emotion-Recognition Implementations in OpenCV, Cognitive Services, and Google Vision APIs LUIS ANTONIO BELTRÁN PRIETO, ZUZANA KOMÍNKOVÁ OPLATKOVÁ @@ -13516,6 +47158,12 @@ statistical parametric mapping analyses, we identified occipitotemporal reas activated by face stimuli more than by control conditions. V1/V2 ctivity was significantly stronger for lower than central and upper visual field presentation. Fusiform activity, however, was significantly"
+f95ba7673789d1b4118d30e360a5a37fd75d3961,Face Recognition using Modified Generalized Hough Transform and Gradient Distance Descriptor,"Face Recognition using Modified Generalized Hough Transform +nd Gradient Distance Descriptor +Marian Moise, Xue Dong Yang and Richard Dosselmann +Department of Computer Science, University of Regina, 3737 Wascana Parkway, Regina, Saskatchewan, Canada +Keywords: +Face Recognition, Generalized Hough Transform, Image Descriptors."
f93606d362fcbe62550d0bf1b3edeb7be684b000,Nearest Neighbor Classifier Based on Nearest Feature Decisions,"The Computer Journal Advance Access published February 1, 2012 © The Author 2012. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved. For Permissions, please email: @@ -13536,6 +47184,12 @@ lassification datasets show average improvements of 6 and 3.5% in recognition a rea under curve performance measures, respectively. The statistical significance of the observed performance improvements is verified by the Friedman test and by the post hoc Bonferroni–Dunn test. In addition, the application of the classifier is demonstrated on face recognition databases, a"
+f94feceb5b725c6b303b758a0e5e90215b0174d3,Learning Non-maximum Suppression,"Learning non-maximum suppression +Jan Hosang +Rodrigo Benenson +Bernt Schiele +Max Planck Institut für Informatik +Saarbrücken, Germany"
f997a71f1e54d044184240b38d9dc680b3bbbbc0,Deep Cross Modal Learning for Caricature Verification and Identification(CaVINet),"Deep Cross Modal Learning for Caricature Verification and Identification(CaVINet) https://lsaiml.github.io/CaVINet/ @@ -13547,6 +47201,7 @@ Skand Vishwanath Peri∗ Indian Institute of Technology Ropar Narayanan C Krishnan Indian Institute of Technology Ropar"
+f96970f75b0f37787a47073bf7d02111f45abe83,3 D Face Recognition Performance under Adversarial Conditions,
f9d1f12070e5267afc60828002137af949ff1544,Maximum Entropy Binary Encoding for Face Template Protection,"Maximum Entropy Binary Encoding for Face Template Protection Rohit Kumar Pandey Yingbo Zhou @@ -13554,12 +47209,75 @@ Bhargava Urala Kota Venu Govindaraju University at Buffalo, SUNY {rpandey, yingbozh, buralako,"
+f0f876b5bf3d442ef9eb017a6fa873bc5d5830c8,"LOH and Behold: Web-Scale Visual Search, Recommendation and Clustering Using Locally Optimized Hashing","LOH and Behold: Web-scale visual search, +recommendation and clustering using Locally +Optimized Hashing +Yannis Kalantidis:, Lyndon Kennedy;‹, Huy Nguyen:, +Clayton Mellina: and David A. Shamma§‹ +:Computer Vision and Machine Learning Group, Flickr, Yahoo +;Futurewei Technologies Inc. +§CWI: Centrum Wiskunde & Informatica, Amsterdam"
+f00e51ec0e3894bdb2977a01824f37b15bb82c6e,A Gaussian Approximation of Feature Space for Fast Image Similarity,"Computer Science and ArtificialIntelligence LaboratoryTechnical Reportmassachusetts institute of technology, cambridge, ma 02139 usa — www.csail.mit.eduMIT-CSAIL-TR-2012-032October 1, 2012A Gaussian Approximation of Feature Space for Fast Image Similarity Michael Gharbi, Tomasz Malisiewicz, Sylvain Paris, and FrØdo Durand"
+f0ca04fe6de04a46f44dabd8744b4163e8e0b4d3,Low-Resolution and Low-Quality Face Super-Resolution in Monitoring Scene via Support-Driven Sparse Coding,"J Sign Process Syst (2014) 75:245–256 +DOI 10.1007/s11265-013-0804-9 +Low-Resolution and Low-Quality Face Super-Resolution +in Monitoring Scene via Support-Driven Sparse Coding +Junjun Jiang & Ruimin Hu & Zhen Han & Zhongyuan Wang +Received: 25 April 2013 / Revised: 2 June 2013 / Accepted: 4 June 2013 / Published online: 26 June 2013 +# Springer Science+Business Media New York 2013"
+f006161327d3ea3484064c1a86e4c87c729fd7b8,Rough Sets Methods in Feature Reduction and Classification,"Int. J. Appl. Math. Comput. Sci., 2001, Vol.11, No.3, 565{582 +ROUGH SETS METHODS IN FEATURE REDUCTION +AND CLASSIFICATION +Roman W. (cid:145)WINIARSKI(cid:3) +The paper presents an application of rough sets and statistical methods to fea- +ture reduction and pattern recognition. The presented description of rough sets +theory emphasizes the role of rough sets reducts in feature selection and data +reduction in pattern recognition. The overview of methods of feature selection +emphasizes feature selection criteria, including rough set-based methods. The +paper also contains a description of the algorithm for feature selection and re- +duction based on the rough sets method proposed jointly with Principal Compo- +nent Analysis. Finally, the paper presents numerical results of face recognition +experiments using the learning vector quantization neural network, with feature +selection based on the proposed principal components analysis and rough sets +methods. +Keywords: rough sets, feature selection, classi(cid:12)cation +. Introduction +One of the fundamental steps in classi(cid:12)er design is reduction of pattern dimensional- +ity through feature extraction and feature selection (Cios et al., 1998; Kittler, 1986; +Langley and Sage, 1994; Liu and Motoda, 1999). Feature selection is often isolated as"
+f08266cea120e8aa091983da5269ee5e35febe75,Semantic Diversity versus Visual Diversity in Visual Dictionaries,"Semantic Diversity versus Visual Diversity +in Visual Dictionaries +Ot´avio A. B. Penatti, Sandra Avila, Member, IEEE, Eduardo Valle, Ricardo da S. Torres, Member, IEEE"
+f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4,The EuroCity Persons Dataset: A Novel Benchmark for Object Detection,"The EuroCity Persons Dataset: +A Novel Benchmark for Object Detection +Markus Braun, Sebastian Krebs, Fabian Flohr, and Dariu M. Gavrila"
+f0865d11131a84ef1d91e1c8b5718692f153267d,Explaining Autism Spectrum Disorders,"Articles in PresS. J Neurophysiol (May 28, 2014). doi:10.1152/jn.00242.2014 +EXPLAINING AUTISM SPECTRUM DISORDERS +Explaining autism spectrum disorders: central coherence versus predictive coding theories. +Target Article: Stevenson, R. A., Siemann, J. K., Schneider, B. C., Eberly, H. E., Woynaroski, T. G., +Camarata, S. M., & Wallace, M. T. (2014). Multisensory Temporal Integration in Autism Spectrum +Disorders. The Journal of Neuroscience, 34(3), 691-697. doi: 10.1523/jneurosci.3615-13.2014 +Jason S. Chan* & Marcus J. Naumer +Institute of Medical Psychology +Goethe-University, Frankfurt +KEYWORDS: Autism Spectrum Disorder, Multisensory Integration, Temporal Binding Window +Acknowledgements: This was funded by the Hessian initiative for the development of scientific and +economic excellence (LOEWE) Neuronal Coordination Research Focus Frankfurt (NeFF). +*Corresponding author: +Jason Chan +Copyright © 2014 by the American Physiological Society."
f0cee87e9ecedeb927664b8da44b8649050e1c86,Image Ordinal Classification and Understanding: Grid Dropout with Masking Label,"label:(1, 0, 1, 0, 1, 1, 1, 1, 1)Masking label:(0, 1, 1, 1, 0, 1, 1, 1, 1)Entire imageInput imageNeuron dropout’s gradCAMGrid dropout’s gradCAMFig.1.Above:imageordinalclassificationwithrandomlyblackoutpatches.Itiseasyforhumantorecognizetheageregardlessofthemissingpatches.Themaskinglabelisalsousefultoimageclassification.Bottom:griddropout’sgrad-CAMisbetterthanthatofneurondropout.Thatistosay,griddropoutcanhelplearningfeaturerepresentation.problem[1].Withtheproliferationofconvolutionalneuralnetwork(CNN),workshavebeencarriedoutonordinalclas-sificationwithCNN[1][2][3].Thoughgoodperformanceshavebeenloggedwithmoderndeeplearningapproaches,therearetwoproblemsinimageordinalclassification.Ononehand,theamountofordinaltrainingdataisverylim-itedwhichprohibitstrainingcomplexmodelsproperly,andtomakemattersworse,collectinglargetrainingdatasetwithordinallabelisdifficult,evenharderthanlabellinggenericdataset.Therefore,insufficienttrainingdataincreasestheriskofoverfitting.Ontheotherhand,lessstudiesareconductedtounderstandwhatdeepmodelshavelearnedonordinaldata978-1-5386-1737-3/18/$31.00c(cid:13)2018IEEE"
f0f4f16d5b5f9efe304369120651fa688a03d495,Temporal Generative Adversarial Nets,"Temporal Generative Adversarial Nets Masaki Saito∗ Eiichi Matsumoto∗ Preferred Networks inc., Japan {msaito,"
+f0d29be1a93158d320bef285442f63bb090f6c31,An Online and Flexible Multi-Object Tracking Framework using Long Short-Term Memory,"An Online and Flexible Multi-Object Tracking Framework using Long +Short-Term Memory +Xingyu Wan, Jinjun Wang, Sanping Zhou +Xi’an Jiaotong University +Institute of Artificial Intelligence and Robotics +8 West Xianning Road, Xi’an, Shaanxi, China, 710049"
f0ae807627f81acb63eb5837c75a1e895a92c376,Facial Landmark Detection using Ensemble of Cascaded Regressions,"International Journal of Emerging Engineering Research and Technology Volume 3, Issue 12, December 2015, PP 128-133 ISSN 2349-4395 (Print) & ISSN 2349-4409 (Online) @@ -13568,6 +47286,116 @@ Regressions Martin Penev1*, Ognian Boumbarov2 Faculty of Telecommunications, Technical University, Sofia, Bulgaria Faculty of Telecommunications, Technical University, Sofia, Bulgaria"
+f06f3e1cef2d04af915a932e83b22e46a45f3b73,Action understanding and social learning in Autism: a developmental perspective,"Life Span and Disability / XIV, 1 (2011), 7-29 +Action understanding and social learning in Autism: +developmental perspective +Giacomo Vivanti1 & Sally J. Rogers2"
+f0dd265dfbe9ffe86ca56ba053335626720059a3,CNN Fixations: An unraveling approach to visualize the discriminative image regions,"CNN Fixations: An unraveling approach to +visualize the discriminative image regions +Konda Reddy Mopuri*, Utsav Garg*, R. Venkatesh Babu, Senior Member, IEEE"
+f0aac566e3d2c06759b8f4f45a270d5af93b9705,Ear Structure Feature Extraction Based on Multi-scale Hessian Matrix,"International Journal of Signal Processing, Image Processing and Pattern Recognition +Vol.9, No.5 (2016), pp.159-172 +http://dx.doi.org/10.14257/ijsip.2016.9.5.14 +Ear Structure Feature Extraction Based on Multi-scale Hessian +Matrix +,Ban Xiaojuan*1, Wang Guosheng3 and Tian Ying2 +Ma Chi1,2,3 +School of Computer & Communication Engineering, University of Science and +College of Software, University of Science and Technology LiaoNing, Anshan, +Technology Beijing, Beijing, China +Beihai Yinhe Industry Investment Co.,Ltd., Beihai, China +China"
+f0d18a5d205c23d1309387dfbd4ecfbcf3b1687e,Atypical neural modulation in the right prefrontal cortex during an inhibitory task with eye gaze in autism spectrum disorder as revealed by functional near-infrared spectroscopy.,"Terms of Use: https://journals.spiedigitallibrary.org/terms-of-use +Atypicalneuralmodulationintherightprefrontalcortexduringaninhibitorytaskwitheyegazeinautismspectrumdisorderasrevealedbyfunctionalnear-infraredspectroscopyTakahiroIkedaMasahiroHiraiTakeshiSakuradaYukifumiMondenTatsuyaTokudaMasakoNagashimaHideoShimoizumiIppeitaDanTakanoriYamagataTakahiroIkeda,MasahiroHirai,TakeshiSakurada,YukifumiMonden,TatsuyaTokuda,MasakoNagashima,HideoShimoizumi,IppeitaDan,TakanoriYamagata,“Atypicalneuralmodulationintherightprefrontalcortexduringaninhibitorytaskwitheyegazeinautismspectrumdisorderasrevealedbyfunctionalnear-infraredspectroscopy,”Neurophoton.5(3),035008(2018),doi:10.1117/1.NPh.5.3.035008."
+f09432b7f470268c28d3d4ebd17a44773b678900,Structured Attentions for Visual Question Answering,"Structured Attentions for Visual Question Answering +Chen Zhu, Yanpeng Zhao, Shuaiyi Huang, Kewei Tu, Yi Ma +{zhuchen, zhaoyp1, huangsy, tukw, +ShanghaiTech University"
+f07956d0031ff046c5c719296f7916d7897fdd21,A Flexible Real-Time Control System for Autonomous Vehicles,"A Flexible Real-Time Control System for Autonomous Vehicles. +Johannes Meyer, Armin Strobel +Institute of Flight Systems and Automatic Control, Technische Universität Darmstadt, Germany 1"
+f0b77702c8f2249ee1f48e51ff9b86faffe177c9,Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation,"Reformulating Level Sets as Deep Recurrent Neural Network Approach +to Semantic Segmentation +Ngan Le 1 Kha Gia Quach 1 2 Khoa Luu 1 Marios Savvides 1 Chenchen Zhu 1"
+f040e4fcedca0c07788ecb6e92ad246b9c1697a9,Real-time Multiple Head Tracking Using Texture and Colour Cues,"REAL-TIME MULTIPLE HEAD TRACKING +USING TEXTURE AND COLOUR CUES +Vasil Khalidov Jean-Marc Odobez +Idiap-RR-02-2017 +FEBRUARY 2017 +Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny +T +41 27 721 77 11 F +41 27 721 77 12 www.idiap.ch"
+f0a0f341fa1f91ee58a5020297bea02f8863cb26,Learning Deep Semantic Embeddings for Cross-Modal Retrieval,"Proceedings of Machine Learning Research 77:471–486, 2017 +ACML 2017 +Learning Deep Semantic Embeddings for Cross-Modal +Retrieval +Cuicui Kang +No.89A Minzhuang Road, Beijing, China +Shengcai Liao∗ +No.95 Zhuangguancun East Road, Beijing, China +Zhen Li, Zigang Cao, Gang Xiong +No.89A Minzhuang Road, Beijing, China +Editors: Yung-Kyun Noh and Min-Ling Zhang"
+f0cc615b14c97482faa9c47eb855303c71ff03a7,Tracklet clustering for robust multiple object tracking using distance dependent Chinese restaurant processes,"SIViP +DOI 10.1007/s11760-015-0817-x +ORIGINAL PAPER +Tracklet clustering for robust multiple object tracking +using distance dependent Chinese restaurant processes +Ibrahim Saygin Topkaya1 · Hakan Erdogan1 · Fatih Porikli2,3 +Received: 4 June 2015 / Revised: 19 August 2015 / Accepted: 10 September 2015 +© Springer-Verlag London 2015"
+f0483ebab9da2ba4ae6549b681cf31aef2bb6562,3c-gan: an Condition-context-composite Generative Adversarial Networks for Gen-,"Under review as a conference paper at ICLR 2018 +C-GAN: AN +CONDITION-CONTEXT-COMPOSITE +GENERATIVE ADVERSARIAL NETWORKS FOR GEN- +ERATING IMAGES SEPARATELY +Anonymous authors +Paper under double-blind review"
+f04cffcd0cc68e28cf05827ab998cf84b1ab0f3d,Crowdsourced Data Preprocessing with R and Amazon Mechanical Turk,"CONTRIBUTED RESEARCH ARTICLES +Crowdsourced Data Preprocessing with R +nd Amazon Mechanical Turk +y Thomas J. Leeper"
+f0b30a9bb9740c2886d96fc44d6f35b8eacab4f3,Are You Sure You Want To Do That ? Classification with Interpretable Queries,"Are You Sure You Want To Do That? +Classification with Interpretable Queries +Anonymous Author(s) +Affiliation +Address +email"
+f736b7cf8388f20bfe9619d63d9c4ce070091863,Automated Crowd Detection in Stadium Arenas,"AUTOMATED CROWD DETECTION IN STADIUM ARENAS +Loris Nanni, 1 Sheryl Brahnam, 2 Stefano Ghidoni, 1 Emanuele Menegatti1 +DIE, University of Padua, Via Gradenigo, 6 - 35131- Padova – Italy e-mail: {loris.nanni, ghidoni, +CIS, Missouri State University, 901 S. National, Springfield, MO 65804, USA e-mail:"
+f73b15d33b9dcf329cf605815be7493b162b1fab,SLMotion - An extensible sign language oriented video analysis tool,"SLMotion – An extensible sign language oriented video analysis tool +Matti Karppa∗, Ville Viitaniemi∗, Marcos Luzardo∗, Jorma Laaksonen∗, Tommi Jantunen† +Department of Information and Computer Science, +Aalto University School of Science, Espoo, Finland, +Sign Language Centre, Department of Languages, +University of Jyv¨askyl¨a, Finland, +We present a software toolkit called SLMotion which provides a framework for automatic and semiautomatic analysis, feature extraction +nd annotation of individual sign language videos, and which can easily be adapted to batch processing of entire sign language corpora. +The program follows a modular design, and exposes a Numpy-compatible Python application programming interface that makes it easy +nd convenient to extend its functionality through scripting. The program includes support for exporting the annotations in ELAN +format. The program is released as free software, and is available for GNU/Linux and MacOS platforms."
+f79267b0f4c0110051c93f9faabe436215e4fc28,Selective Feature Connection Mechanism: Concatenating Multi-layer CNN Features with a Feature Selector,"Selective Feature Connection Mechanism: +Concatenating Multi-layer CNN Features with a Feature Selector +Chen Du1,2, Chunheng Wang1, Cunzhao Shi1, Baihua Xiao1 +Institute of Automation, Chinese Academy of Sciences(CASIA) +University of Chinese Academy of Sciences(UCAS) +{duchen2016, chunheng.wang, cunzhao.shi,"
+f74dbf3481fc3228ea821da232128b98ad5f7a60,Using low-level motion for high-level vision,"Using Low-Level Motion for +High-Level Vision +Ben Daubney +A dissertation submitted to the University of Bristol in accordance with the +requirements for the degree of Doctor of Philosophy in the Faculty of Engineering, +Department of Computer Science. +July 2009"
+f79c4bf83371627ba139b61eb427463b93cd687b,Learning from Few Examples for Visual Recognition Problems,"Learning from Few Examples for Visual +Recognition Problems +Erik Rodner +Dissertation +zur Erlangung des akademischen Grades +doctor rerum naturalium (Dr. rer. nat.) +vorgelegt dem Rat der Fakultät für Mathematik und Informatik +der Friedrich-Schiller-Universität Jena"
f740bac1484f2f2c70777db6d2a11cf4280081d6,Soft Locality Preserving Map (SLPM) for Facial Expression Recognition,"Soft Locality Preserving Map (SLPM) for Facial Expression Recognition Cigdem Turana,*, Kin-Man Lama, Xiangjian Heb @@ -13597,6 +47425,42 @@ version http://dx.doi.org/10.1109/TIP.2009.2017163 Item record http://hdl.handle.net/10379/1350"
+f7db1a670a99fd68dc3c6478eb9aeadc2838a897,Based Pose Invariant Face Recognition,"FEATURE BASED POSE INVARIANT FACE RECOGNITION +Berk G¨okberk +BS. in Computer Engineering, Bo˘gazi¸ci University, 1999 +Submitted to the Institute for Graduate Studies in +Science and Engineering in partial fulfillment of +the requirements for the degree of +Master of Science +Computer Engineering +Bo˘gazi¸ci University"
+f7580def2dd84a6a083188aadd9c66c99925860b,Effective Use of Synthetic Data for Urban Scene Semantic Segmentation,"Effective Use of Synthetic Data for +Urban Scene Semantic Segmentation(cid:63) +Fatemeh Sadat Saleh1,2[0000−0002−3695−9876], Mohammad Sadegh +Aliakbarian1,2,3[0000−0003−3948−6418], Mathieu Salzmann4[0000−0002−8347−8637], +Lars Petersson2[0000−0002−0103−1904], and Jose M. Alvarez5[0000−0002−7535−6322] +ANU, 2 Data61-CSIRO, 3 ACRV, 4 CVLab, EPFL, 5 NVIDIA"
+f7514435495cd76552a4de01652a08ff8c2863c7,Recognition of Emotions From Facial Expression and Situational Cues in Children with Autism,"Dissertations +Loyola University Chicago +Loyola eCommons +Theses and Dissertations +Recognition of Emotions From Facial Expression +nd Situational Cues in Children with Autism +Dina Tell +Loyola University Chicago +Recommended Citation +Tell, Dina, ""Recognition of Emotions From Facial Expression and Situational Cues in Children with Autism"" (2009). Dissertations. +Paper 234. +http://ecommons.luc.edu/luc_diss/234 +This Dissertation is brought to you for free and open access by the Theses and Dissertations at Loyola eCommons. It has been accepted for inclusion in +Dissertations by an authorized administrator of Loyola eCommons. For more information, please contact +This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. +Copyright © 2009 Dina Tell"
+f755d9b2b7ef66ffdf7504b34167b95d0685c18d,Efficient Online Subspace Learning With an Indefinite Kernel for Visual Tracking and Recognition,"Efficient Online Subspace Learning With +n Indefinite Kernel for Visual +Tracking and Recognition +Stephan Liwicki, Student Member, IEEE, Stefanos Zafeiriou, Member, IEEE, +Georgios Tzimiropoulos, Member, IEEE, and Maja Pantic, Fellow, IEEE"
f7dcadc5288653ec6764600c7c1e2b49c305dfaa,Interactive Image Search with Attributes by,"Copyright Adriana Ivanova Kovashka"
f7de943aa75406fe5568fdbb08133ce0f9a765d4,Biometric Identification and Surveillance1,"Project 1.5: Human Identification at a Distance - Hornak, Adjeroh, Cukic, Gautum, & Ross @@ -13632,14 +47496,86 @@ Face Recognition. The performances of these algorithms were compared on the CMU- Illumination dataset [13], by using the entire face as the input to the algorithms. Then, a model of dividing the face into four regions is proposed and the performance of the lgorithms on these new features is analyzed."
+f79ab9baccd466d86460214c5cee9f3be0af4064,Image Segmentation of Medical Images using Automatic Fuzzy C-Mean Clustering,"IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613 +Image Segmentation of Medical Images using Automatic Fuzzy C-Mean +Clustering +Padmini Umorya1 Rajesh Singh2 +Research Scholar 2Assistant Professor +,2Department of Computer Science and Engineering +,2NITM College Gwalior, India"
+f7c9bafc66dc8d8002cbb2ea926378bce2b3b251,Emotion Detection Using EEG Signal Analysis,"International Journal of Electronics Communication and Computer Technology (IJECCT) +Volume 5 Issue 2 (March 2015) +Emotion Detection Using EEG Signal Analysis +‘Review’ +K.S. Bhagat +Assistant Professor, +Dr. P.M. Mahajan +Assistant Professo, +Gunjal P. Waghulade +M.E. IVth Semester, +J.T. Mahajan College of ngineering, +J.T. Mahajan College of ngineering, +J.T. Mahajan College of ngineering, +Faizpur, India +Faizpur, India +Faizpur, India"
+f7a37cf724aef23d0e714a35d54352243e5b52ee,Entire Reflective Object Surface Structure Understanding,"Q.LU ET AL.: ENTIRE REFLECTIVE OBJECT SURFACE STRUCTURE UNDERSTANDING 1 +Entire Reflective Object Surface Structure +Understanding +Qinglin Lu1 +Olivier Laligant1 +Eric Fauvet1 +Anastasia Zakharova2 +University of Burgundy +Le2i UMR 6306 CNRS +2,Rue de la Fonderie,71200,France +INSA Rouen LMI EA3226 +Avenue de l’Université,76800,France"
f77c9bf5beec7c975584e8087aae8d679664a1eb,Local Deep Neural Networks for Age and Gender Classification,"Local Deep Neural Networks for Age and Gender Classification Zukang Liao, Stavros Petridis, Maja Pantic March 27, 2017"
+f727b12c905ac585de60811048c9f9dd4188b498,R4-A.2: Rapid Forensic Search & Retrieval in Video Archives,"R4-A.2: Rapid Forensic Search & Retrieval in Video +Archives"
f7ba77d23a0eea5a3034a1833b2d2552cb42fb7a,LOTS about attacking deep features,"This is a pre-print of the original paper accepted at the International Joint Conference on Biometrics (IJCB) 2017. LOTS about Attacking Deep Features Andras Rozsa, Manuel G¨unther, and Terrance E. Boult Vision and Security Technology (VAST) Lab University of Colorado, Colorado Springs, USA"
+f727837e03a039d9bcec6d02cd87256f5a5854a4,"Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning","Deep Convolutional Neural Networks for +Computer-Aided Detection: CNN Architectures, +Dataset Characteristics and Transfer Learning +Hoo-Chang Shin, Member, IEEE, Holger R. Roth, Mingchen Gao, Le Lu, Senior Member, IEEE, Ziyue Xu, +Isabella Nogues, Jianhua Yao, Daniel Mollura, Ronald M. Summers*"
+f77b3e6b6eb4bc6d6bfeed290a1bc533bb97968a,Real Time Violence Detection in Video with ViF and Horn-Schunck,"Real Time Violence Detection in Video with ViF and +Horn-Schunck +Vicente Machaca Arceda Universidad Nacional de San Agustín Arequipa, Perú +Karla Fernández Fabián Universidad Nacional de San Agustín Arequipa, Perú +Juan Carlos Gutíerrez Universidad Nacional de San Agustín Arequipa, Perú"
+f724cbf5035e2df0dbe9a4992a0100465f5c6db5,Scalable Multicore k-NN Search via Subspace Clustering for Filtering,"Parallel Graph Partitioning for Complex Networks +Henning Meyerhenke, Peter Sanders, and Christian Schulz"
+f77563386ac293620ce2b90b5d7250ab5d8f9f50,Regression-based Hypergraph Learning for Image Clustering and Classification,"IEEE TRANSACTIONS ON +Regression-based Hypergraph Learning for Image +Clustering and Classification +Sheng Huang Student Member, IEEE, Dan Yang, Bo Liu, Xiaohong Zhang"
+f774f80fa4b5a8760084921f093730da519c6681,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+e819d8ec94ff9b07f81bcfcf6eb66301aa271805,Optimised Blurred Object Tracking Using Anfis,"VOL. 11, NO. 13, JULY 2016 ISSN 1819-6608 +ARPN Journal of Engineering and Applied Sciences +©2006-2016 Asian Research Publishing Network (ARPN). All rights reserved. +www.arpnjournals.com +OPTIMISED BLURRED OBJECT TRACKING USING ANFIS +Department of Electronics and Communication, Sathyabama University, Chennai, India +S. Rajaprabha and M. Sugadev +E-Mail:"
e8686663aec64f4414eba6a0f821ab9eb9f93e38,Improving shape-based face recognition by means of a supervised discriminant Hausdorff distance,"IMPROVING SHAPE-BASED FACE RECOGNITION BY MEANS OF A SUPERVISED DISCRIMINANT HAUSDORFF DISTANCE J.L. Alba @@ -13649,6 +47585,50 @@ nd J.J. Villanueva Signal Theory and Communications Department, University of Vigo, Spain Centre de Visio per Computador, Universitat Autonoma de Barcelona, Spain Digital Pointer MVT"
+e80635b9b48df5ad263c51ecec62d7d4bd7327fd,"Keepon A Playful Robot for Research , Therapy , and Entertainment","Int J Soc Robot (2009) 1: 3–18 +DOI 10.1007/s12369-008-0009-8 +O R I G I N A L PA P E R +Keepon +A Playful Robot for Research, Therapy, and Entertainment +Hideki Kozima · Marek P. Michalowski · +Cocoro Nakagawa +Accepted: 28 October 2008 / Published online: 19 November 2008 +© Springer 2008"
+e8304700fd89461ec9ecf471179ad87f08f3c2f7,Chapter 1 . Learning to Learn New Models of Human Activities in Indoor Settings (,"Chapter 1 +Learning to learn new +models of human activities in +indoor settings1 +Introduction +Biological cognitive systems have the great capability to recognize and in- +terpret unknown situations. Equally, they can integrate new observations +easily within their existing knowledge base. Autonomous artificial agents to +large extent still lack such capacities. In this paper, we work towards this +direction, as we do not only detect abnormal situations, but are also able to +learn new concepts during runtime. +We aim at the interpretation of human behavior in indoor environments. +Possible applications go from the main IM2 scenario, i.e. analysis and un- +derstanding of meetings, to monitoring of elderly or handicapped people in +their homes in order to ensure their well-being. The indoor setting triggers +interesting issues, such as the adaptation of pre-trained knowledge to a par- +ticular room scene filmed with a different camera or to an unknown person +with an individual behavior style, whereas real abnormalities must still be +detected. +One main limitation of automated surveillance approaches is their need"
+e8d898a6adcd526874e0a41840b69760506a98a1,Computer Vision Methods as an Aid to Visually Impaired Users Title: Computer Vision Methods as an Aid to Visually Impaired Users,"Dipartimento di Informatica, Bioingegneria, +Robotica ed Ingegneria dei Sistemi +Computer Vision methods as an aid to visually impaired users +Giovanni Fusco +Theses Series +DIBRIS-TH-2013-03 +DIBRIS, Universit`a di Genova +Via Opera Pia, 13 16145 Genova, Italy +http://www.dibris.unige.it/"
+e8e8d8a619eea66c41a1a2bdc0a921a3b6d74836,"Restoring Degraded Face Images: A Case Study in Matching Faxed, Printed, and Scanned Photos","Restoring Degraded Face Images: A Case Study in +Matching Faxed, Printed, and Scanned Photos +Thirimachos Bourlai, Member, IEEE, Arun Ross, Senior Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+e8d1d2a61c5a259440ef9fcd301093b43e87efa1,Periocular Biometrics in the Visible Spectrum,"Periocular Biometrics in the Visible Spectrum +Unsang Park, Member, IEEE, Raghavender Reddy Jillela, Student Member, IEEE, Arun Ross, Senior Member, IEEE, +nd Anil K. Jain, Fellow, IEEE"
e8fdacbd708feb60fd6e7843b048bf3c4387c6db,Deep Learning,"Deep Learning Andreas Eilschou Hinnerup Net A/S @@ -13669,16 +47649,155 @@ that are of interest to the general public. In July 2012 Google trained a deep l network on YouTube videos with the remarkable result that the network learned to recognize humans as well as cats [6], and in January this year Google successfully used deep learning on Street View images to automatically recognize house numbers with"
+e8632e5bf43f7c59f4e1978833db8aa405c76c58,Saliency and Gist Features for Target Detection in Satellite Images,"Saliency and Gist Features for Target +Detection in Satellite Images +Zhicheng Li and Laurent Itti"
+e849b9b3e65130712e23afb872ac925e1e9a6b73,"Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and with bounds","Journal of Machine Learning Research x (2012) xxx +Submitted xx/xx; Published xx/xx +Image denoising with multi-layer perceptrons, part 1: +omparison with existing algorithms and with bounds +Harold Christopher Burger +Christian J. Schuler +Stefan Harmeling +Max Planck Institute for Intelligent Systems +Spemannstr. 38 +72076 T¨ubingen, Germany +Editor:"
+e810ddd9642db98492bd6a28b08a8655396c1555,Facing facts: neuronal mechanisms of face perception.,"Review +Acta Neurobiol Exp 2008, 68: 229–252 +Facing facts: Neuronal mechanisms of face perception +Monika Dekowska1, Michał Kuniecki2, and Piotr Jaśkowski3* +Kazimierz Wielki University of Bydgoszcz, Poland; 2Department of Psychophysiology, Jagiellonian University, +Kraków, Poland; 3Department of Cognitive Psychology, University of Finance and Management, Warszawa, Poland, +*Email: +The face is one of the most important stimuli carrying social meaning. Thanks to the fast analysis of faces, we are able to +judge physical attractiveness and features of their owners’ personality, intentions, and mood. From one’s facial expression +we can gain information about danger present in the environment. It is obvious that the ability to process efficiently one’s +face is crucial for survival. Therefore, it seems natural that in the human brain there exist structures specialized for face +processing. In this article, we present recent findings from studies on the neuronal mechanisms of face perception and +recognition in the light of current theoretical models. Results from brain imaging (fMRI, PET) and electrophysiology (ERP, +MEG) show that in face perception particular regions (i.e. FFA, STS, IOA, AMTG, prefrontal and orbitofrontal cortex) are +involved. These results are confirmed by behavioral data and clinical observations as well as by animal studies. The +developmental findings reviewed in this article lead us to suppose that the ability to analyze face-like stimuli is hard-wired +nd improves during development. Still, experience with faces is not sufficient for an individual to become an expert in face +perception. This thesis is supported by the investigation of individuals with developmental disabilities, especially with +utistic spectrum disorders (ASD). +Key words: face perception, emotion perception"
e8b2a98f87b7b2593b4a046464c1ec63bfd13b51,CMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection,"CMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection Chenchen Zhu*, Student, IEEE, Yutong Zheng*, Student, IEEE, Khoa Luu, Member, IEEE, Marios Savvides, Senior Member, IEEE"
+e8ff87c9072d67dcbcd5491b1e5a0cecc2ee309d,A Survey on Gaze Estimation Techniques in Smartphone,"International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 +Volume: 04 Issue: 04 | Apr -2017 www.irjet.net p-ISSN: 2395-0072 +A Survey on Gaze Estimation Techniques in Smartphone +Akshay A Gawande1, Prof.Gangotri Nathaney2 +M.Tech Scholar, CSE Department, WCOEM, Nagpur, India1 +Assistant Professor, CSE Department, WCOEM, Nagpur, India2 +image dataset +interest. Many of +field mobile technology and digital +The goal of this system to get correct gaze point with +minimum of error rate and allow handicap people to +operate mobile easily by eyes .The proposed system +onsist of collecting some steps as: Collecting people +different position eye +,preprocessing, +feature extraction, regression. This paper is organized as +follows: Section 2 comprises Previous Work; section 3 +omprises Methodology and Conclusion is in section 4. +---------------------------------------------------------------------***--------------------------------------------------------------------- +use eye trackers to identify what customer's gaze is"
+e8dda897372e6b4cf903234c7a9c40117711d8d8,What do you think of my picture? Investigating factors of influence in profile images context perception,"What do you think of my picture? Investigating factors +of influence in profile images context perception +Filippo Mazza, Matthieu Perreira da Silva, Patrick Le Callet, Ingrid +Heynderickx +To cite this version: +Filippo Mazza, Matthieu Perreira da Silva, Patrick Le Callet, Ingrid Heynderickx. What do you +think of my picture? Investigating factors of influence in profile images context perception. Human +Vision and Electronic Imaging XX, Mar 2015, San Francisco, United States. Proc. SPIE 9394, Hu- +man Vision and Electronic Imaging XX, 9394, <http://spie.org/EI/conferencedetails/human-vision- +electronic-imaging>. <10.1117/12.2082817>. <hal-01149535> +HAL Id: hal-01149535 +https://hal.archives-ouvertes.fr/hal-01149535 +Submitted on 7 May 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est"
+e8d2d991dcfb12b287ab06d282a86802e565780c,Inducing Behavior Change in Children with Autism Spectrum Disorders by Monitoring their Attention,"Inducing behavior change in children with autism spectrum disorders by +monitoring their attention +Margarida Lucas da Silva12, Hugo Silva3 and Daniel Gonc¸alves12 +Instituto Superior T´ecnico, Av. Rovisco Pais, 1, 1049-001, Lisboa, Portugal +INESC-ID, R. Alves Redol, 9, 1000-029 Lisboa, Portugal +Instituto de Telecomunicac¸ ˜oes, Instituto Superior T´ecnico, Av. Rovisco Pais, 1, Torre Norte - Piso 10, 1049-001, Lisboa, +Portugal +Keywords: +Human Behavior Analysis, Autism Spectrum Disorders, Inducing Behavior Change."
+e84e49c9530897fad7927a06ac4a48ddaf0adf0f,Searching for Efficient Multi-Scale Architectures for Dense Image Prediction,"Searching for Efficient Multi-Scale +Architectures for Dense Image Prediction +Liang-Chieh Chen Maxwell D. Collins +Barret Zoph +Florian Schroff +Yukun Zhu +Hartwig Adam +George Papandreou +Jonathon Shlens +Google Inc."
+e8af37ac6e0a5b7f04b6824bb1f74e4f363b99b5,On the replication of CycleGAN,"Bachelor thesis +Computer Science +Radboud University +On the replication of CycleGAN +Author: +Robin Elbers +s4225678 +First supervisor/assessor: +MSc. Jacopo Acquarelli +Second assessor: +Prof. Tom Heskes +August 10, 2018"
+e8e8f40ceff8b71d5dafa6b680d40690dfae940c,title : Guidelines for studying developmental prosopagnosia in adults and children,"Article type: Focus Article +Article title: Guidelines for studying developmental prosopagnosia in adults +nd children +First author: Full name and affiliation; plus email address if +orresponding author +Kirsten A. Dalrymple* +Institute of Child Development, University of Minnesota, Minneapolis, USA +Second author: Full name and affiliation; plus email address if +orresponding author +Romina Palermo* +School of Psychology, and ARC Centre of Excellence in Cognition and its Disorders +University of Western Australia, Crawley, Australia +Please note that both authors would like to be listed as “corresponding authors”."
+e819a577c57c83a133a0a0e81180d14dc13b82e9,Pyramid Histogram of Oriented Gradients based Human Ear Identification,"Pyramid Histogram of Oriented Gradients based Human Ear Identification +Pyramid Histogram of Oriented Gradients based Human +Ear Identification +Partha Pratim Sarangi1, B.S.P. Mishra1 and Sachidanada Dehuri2 +School of Computer Engineering KIIT University, Bhubaneswar , Emails: +Department of ICT FM University, Balasore, Email:"
e8d1b134d48eb0928bc999923a4e092537e106f6,Weighted Multi-region Convolutional Neural Network for Action Recognition with Low-latency Online Prediction,"WEIGHTED MULTI-REGION CONVOLUTIONAL NEURAL NETWORK FOR ACTION RECOGNITION WITH LOW-LATENCY ONLINE PREDICTION Yunfeng Wang(cid:63), Wengang Zhou(cid:63), Qilin Zhang†, Xiaotian Zhu(cid:63), Houqiang Li(cid:63) (cid:63)University of Science and Technology of China, Hefei, Anhui, China HERE Technologies, Chicago, Illinois, USA"
+e855856d4b61b6a732005418f543c49195cb1542,Novel Method for Eyeglasses Detection in Frontal Face Images,"Novel Method for Eyeglasses Detection in Frontal +Face Images +R. L. Parente, L. V. Batista +Centro de Inform´atica - CI +Universidade Federal da Para´ıba - UFPB +Jo˜ao Pessoa, Brazil +I. Andreza, E. Borges, R. Marques +VSoft Research Group +VSoft Technology +Jo˜ao Pessoa, Brazil +{igorlpa90, erickvagnerr,"
+e8039e1531dd86da960be26d59718d2452f9943b,Scene Parsing and Fusion-Based Continuous Traversable Region Formation,"Scene parsing and fusion-based continuous +traversable region formation +Xuhong Xiao, Gee Wah Ng, Yuan Sin Tan, Yeo Ye Chuan +0 Science Park Drive, DSO national Laboratories, Singapore 118230"
e8c6c3fc9b52dffb15fe115702c6f159d955d308,Linear Subspace Learning for Facial Expression Analysis,"Linear Subspace Learning for Facial Expression Analysis Caifeng Shan @@ -13699,6 +47818,102 @@ expressions as humans do, has many important applications including int omputer interaction, computer animation, surveillance and security, medical diagnosis, law enforcement, and awareness system (Shan, 2007). Driven by its potential applications nd theoretical interests of cognitive and psychological scientists, automatic facial"
+e8691980eeb827b10cdfb4cc402b3f43f020bc6a,Segmentation Guided Attention Networks for Visual Question Answering,"Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics- Student Research Workshop, pages 43–48 +Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics- Student Research Workshop, pages 43–48 +Vancouver, Canada, July 30 - August 4, 2017. c(cid:13)2017 Association for Computational Linguistics +Vancouver, Canada, July 30 - August 4, 2017. c(cid:13)2017 Association for Computational Linguistics +https://doi.org/10.18653/v1/P17-3008 +https://doi.org/10.18653/v1/P17-3008"
+e8baf6ddd2e651350b843fedfe58f761848d3524,Design And Implementation Of Multiposes Face Recognization System,"Pritika V.Mamankar et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.4, April- 2015, pg. 387-394 +Available Online at www.ijcsmc.com +International Journal of Computer Science and Mobile Computing +A Monthly Journal of Computer Science and Information Technology +IJCSMC, Vol. 4, Issue. 4, April 2015, pg.387 – 394 +RESEARCH ARTICLE +ISSN 2320–088X +Design And Implementation Of Multiposes Face +Recognization System +Ms. Pritika V.Mamankar +Master of Engineering Scholar, Information Technology Department, Sipna College of Engg. and Technology, Amravati, India +Assistant Professor of CSE Department, Computer Science and Engineering Department, Sipna College of Engg. and +Prof. H R. Vyawahare +Technology, Amravati, India"
+e8867f819f39c1838bba7d446934258035d4101c,Face recognition performance with superresolution.,"Face recognition performance with superresolution +Shuowen Hu,1,* Robert Maschal,1 S. Susan Young,1 Tsai Hong Hong,2 +nd P. Jonathon Phillips2 +United States Army Research Laboratory, 2800 Powder Mill Road, Adelphi, Maryland 20783, USA +NIST, 100 Bureau Drive, Gaithersburg, Maryland 20899, USA +*Corresponding author: +Received 29 September 2011; revised 19 April 2012; accepted 24 April 2012; +posted 30 April 2012 (Doc. ID 155384); published 20 June 2012 +With the prevalence of surveillance systems, face recognition is crucial to aiding the law enforcement com- +munity and homeland security in identifying suspects and suspicious individuals on watch lists. However, +face recognition performance is severely affected by the low face resolution of individuals in typical sur- +veillance footage, oftentimes due to the distance of individuals from the cameras as well as the small pixel +ount of low-cost surveillance systems. Superresolution image reconstruction has the potential to improve +face recognition performance by using a sequence of low-resolution images of an individual’s face in the +same pose to reconstruct a more detailed high-resolution facial image. This work conducts an extensive +performance evaluation of superresolution for a face recognition algorithm using a methodology and ex- +perimental setup consistent with real world settings at multiple subject-to-camera distances. Results show +that superresolution image reconstruction improves face recognition performance considerably at the +examined midrange and close range. +OCIS codes:"
+e8f753208fc354fa9aeb3fa9c6acb3d45e7eac7b,Definite Description Lexical Choice: taking Speaker's Personality into account,"Definite Description Lexical Choice: +taking Speaker’s Personality into account +Alex Gwo Jen Lan, Ivandr´e Paraboni +University of S˜ao Paulo, School of Arts, Sciences and Humanities +S˜ao Paulo, Brazil"
+facdb71e8175c33ec54c2248fa6cfc319e27cfa5,Accelerating Machine Learning Research with MI-Prometheus,"Accelerating Machine Learning Research with +MI-Prometheus +Tomasz Kornuta Vincent Marois Ryan L. McAvoy Younes Bouhadjar +Alexis Asseman +Vincent Albouy +IBM Research AI, Almaden Research Center, San Jose, USA +T.S. Jayram Ahmet S. Ozcan +{tkornut, vmarois, mcavoy, byounes, jayram, +{alexis.asseman,"
+fab7f1af3d67c7b7cf76ec1d8dfcb265da61a572,Towards Recommender Systems for Police Photo Lineup,"Towards Recommender Systems for Police Photo Lineup +Ladislav Peska +Department of Software Engineering +Hana Trojanova +Department of Psychology +Faculty of Mathematics and Physics, Charles University, Prague +Faculty of Arts, Charles University, Prague +Czech Republic +Czech Republic"
+facf25e1880d23eb993d4ad507256ebbc7e0d82d,CURE-OR: Challenging Unreal and Real Environments for Object Recognition,"Citation D. Temel, J. Lee, and G. AlRegib, “CURE-OR: Challenging unreal and real environments +for object recognition,” 2018 17th IEEE International Conference on Machine Learning +nd Applications (ICMLA), Orlando, Florida, USA, 2018. +Dataset +https://ghassanalregib.com/cure-or/ +ICMLA, +uthor={D. Temel and J. Lee and G. AlRegib}, +ooktitle={2018 17th IEEE International Conference on Machine Learning and Applications +(ICMLA)}, +title={CURE-OR: Challenging unreal and real environments for object recognition}, +year=2018,} +Copyright c(cid:13)2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be +obtained for all other uses, in any current or future media, including reprinting/republishing +this material for advertising or promotional purposes, creating new collective works, for +resale or redistribution to servers or lists, or reuse of any copyrighted component of this +work in other works. +Contact +https://ghassanalregib.com/ +http://cantemel.com/"
+fa1b849697115ceede0a08ac552ea25ce2bf33a1,A N Approach to F Ace R Ecognition of 2 - D Images Using E Igen F Aces and Pca,"Signal & Image Processing : An International Journal (SIPIJ) Vol.3, No.2, April 2012 +AN APPROACH TO FACE RECOGNITION OF 2-D +IMAGES USING EIGEN FACES AND PCA +Annapurna Mishra1, Monorama Swain2 and Bodhisattva Dash3 +Department of Electronics & Telecommunication Engineering +Silicon Institute of Technology, Bhubaneswar, India"
+fa11590fea86049fff1eb412642753422738c584,Depression-related difficulties disengaging from negative faces are associated with sustained attention to negative feedback during social evaluation and predict stress recovery,"RESEARCH ARTICLE +Depression-related difficulties disengaging +from negative faces are associated with +sustained attention to negative feedback +during social evaluation and predict stress +recovery +Alvaro Sanchez*, Nuria Romero, Rudi De Raedt +Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium"
fab83bf8d7cab8fe069796b33d2a6bd70c8cefc6,Draft: Evaluation Guidelines for Gender Classification and Age Estimation,"Draft: Evaluation Guidelines for Gender Classification and Age Estimation Tobias Gehrig, Matthias Steiner, Hazım Kemal Ekenel @@ -13719,6 +47934,14 @@ File lists for the folds corresponding to the individual benchmarking proto- ols will be provided over our website at http://face.cs.kit.edu/befit. We will provide two kinds of folds for each of the tasks and conditions: one set of folds using the whole dataset and one set of folds using a reduced dataset, which"
+fa23122db319440fb5a7253e19709f992b4571b9,Human Age Estimation via Geometric and Textural Features,"HUMAN AGE ESTIMATION VIA GEOMETRIC +AND TEXTURAL FEATURES +Merve Kilinc1 and Yusuf Sinan Akgul2 +TUBITAK BILGEM UEKAE, Anibal Street, 41470, Gebze, Kocaeli, Turkey +GIT Vision Lab∗, Department of Computer Engineering, Gebze Institute of Technology, 41400, Kocaeli, Turkey +Keywords: +Age Estimation, Age Classification, Geometric Features, LBP, Gabor, LGBP, Cross Ratio, FGNET, MORPH."
+fa4ff855ca125b986bcb2bc6b71bef2ae8fde1cf,"3d Integral Invariant Signatures and Their Application on Face Recognition Dedication I Am Grateful for the Support and Guidance I Have Received from Dr. Irina A. Kogan, and I Also Express My Gratitude To",
fa08a4da5f2fa39632d90ce3a2e1688d147ece61,Supplementary material for “ Unsupervised Creation of Parameterized Avatars ” 1 Summary of Notations,"Supplementary material for “Unsupervised Creation of Parameterized Avatars” Summary of Notations @@ -13739,6 +47962,41 @@ Fig. 2 depicts the results obtained by this selection method on sample images fo the same image. Detailed Architecture of the Various Networks In this section we describe the architectures of the networks used in for the emoji and avatar experiments."
+fa83597bf71dbeb606bca6593bcef8ecd51e8661,Michael Kamaraj and G. Balakrishnan: Multiple Target Tracking Using Cost Minimization Techniques,"MICHAEL KAMARAJ AND G. BALAKRISHNAN: MULTIPLE TARGET TRACKING USING COST MINIMIZATION TECHNIQUES +MULTIPLE TARGET TRACKING USING COST MINIMIZATION TECHNIQUES +Department of Computer Applications, Pavendar Bharathidasan College of Engineering and Technology, India +Department of Computer Science and Engineering, Indra Ganesan College of Engineering, India +Michael Kamaraj1 and G. Balakrishnan2"
+fa2603efaf717974c77162c93d800defae61a129,Face recognition/detection by probabilistic decision-based neural network,"Face Recognition/Detection by Probabilistic +Decision-Based Neural Network +Shang-Hung Lin, Sun-Yuan Kung, Fellow, IEEE, and Long-Ji Lin"
+fac36fa1b809b71756c259f2c5db20add0cb0da0,Transferring GANs: Generating Images from Limited Data,"Transferring GANs: generating images from +limited data +Yaxing Wang, Chenshen Wu, Luis Herranz, Joost van de Weijer, +Abel Gonzalez-Garcia, Bogdan Raducanu +{yaxing, chenshen, lherranz, joost, agonzgarc, +Computer Vision Center +Universitat Aut`onoma de Barcelona, Spain"
+faf40ce28857aedf183e193486f5b4b0a8c478a2,Automated Human Identification Using Ear Imaging,"Imperial Journal of Interdisciplinary Research (IJIR) +Vol.2, Issue-1 , 2016 +ISSN : 2454-1362 , www.onlinejournal.in +Automated Human Identification Using Ear Imaging +Priya Thakare +SITS.Narhe +Abhijit Patil +SITS, Narhe. +Priya More +SITS, Narhe. +Vivek Patil +SITS, Narhe. +Akshay Shende +SITS, Narhe. +Reliability +in human authentication +from airport surveillance +important aspect for the security requirements in various +pplications ranging +electronic banking. Many physical characteristics of"
fa24bf887d3b3f6f58f8305dcd076f0ccc30272a,Interval Insensitive Loss for Ordinal Classification,"JMLR: Workshop and Conference Proceedings 39:189–204, 2014 ACML 2014 Interval Insensitive Loss for Ordinal Classification @@ -13748,6 +48006,15 @@ V´aclav Hlav´aˇc Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technick´a 2, 166 27 Prague 6 Czech Republic Editor: Dinh Phung and Hang Li"
+fa8c73899c22b461cc062a10b6df20fccb18800c,A Novel Framework for Face Recognition in Real-Time Environments,"International Journal of Scientific and Research Publications, Volume 3, Issue 8, August 2013 +ISSN 2250-3153 +A Novel Framework for Face Recognition in Real-Time +Environments +Tmt.Maithili Easwaran*, Dr.B.Poorna** +*Department of Computer Applications, S.A.Engineering College, TN, INDIA +** Department of Computer applications, Shankarlal Sundarbai Shasun Jain College for Women, TN, INDIA +i.e., +(PCA)-based"
fafe69a00565895c7d57ad09ef44ce9ddd5a6caa,Gaussian Mixture Models for Human Face Recognition under Illumination Variations,"Applied Mathematics, 2012, 3, 2071-2079 http://dx.doi.org/10.4236/am.2012.312A286 Published Online December 2012 (http://www.SciRP.org/journal/am) Gaussian Mixture Models for Human Face Recognition @@ -13757,6 +48024,27 @@ California State University, Fullerton, USA Email: Sinjini Mitra Received August 18, 2012; revised September 18, 2012; accepted September 25, 2012"
+fab6e12a913223b69e1b9f0672df6c89275b1ed0,Initial Development of a Learners’ Ratified Acceptance of Multibiometrics Intentions Model (RAMIM),"Interdisciplinary Journal of E-Learning and Learning Objects +IJELLO special series of Chais Conference 2009 best papers +Volume 5, 2009 +Initial Development of a Learners’ Ratified +Acceptance of Multibiometrics Intentions Model +(RAMIM) +Yair Levy +GSCIS, +Nova Southeastern University, +Ft. Lauderdale, FL, USA +Michelle M. Ramim +Nova Southeastern University, +Huizenga School of Business, +Ft. Lauderdale, FL, USA"
+fab0d19c58815eccb0db7215fe45d6a32066ca1c,Inferring Human Attention by Learning Latent Intentions,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +the mug's statuschecking the book's statuslocating the dispenserFigure1:Humanattentionandintentionsina3Dscene.thedispenser,hisattentionsweepsfromthetabletothedis-penser;whilefetchingwaterfromthedispenser,hisintentionistocheckifthemugisfullandhisattentionsteadilyfocusesonthemug.Thedrivingrulesofintentionsactingonattentioncanbeindependentofactivitycategories.Forexample,inFigure1,theattentiondrivenbytheintentioncheckingstatusalwayspresentsassteadilyfocusing,evenindifferentactivities.Thisphenomenonmakesitpossibletoinfertheattentionwiththesamerulesacrossdifferentactivities.However,thesedrivingrulesarehiddenandshouldbelearnedfromdata.Thispaperproposesaprobabilisticmethodtoinfer3Dhu-manattentionbyjointlymodelingattention,intentions,andtheirinteractions.Theattentionandintentionarerepresent-edwithfeaturesextractedfromhumanskeletonsandscenevoxels.Humanintentionsaretakenaslatentvariableswhichguidethemotionsandformsofhumanattention.Conversely,thehumanattentionrevealstheintentionfeatures.Attentioninferenceismodeledasajointoptimizationwithlatenthu-manintentions.WeadoptanEM-based[Bishop,2006]approachtolearnthemodelparametersandminethelatentintentions.Giv-enanRGB-DvideowithhumanskeletonscapturedbytheKinectcamera,ajoint-statedynamicprogrammingalgorithm"
+faa111d749eb228c686643e4667dd1bc21c724f2,Condensed from Video Sequences for Place Recognition,"Boosting Descriptors Condensed from Video Sequences for Place Recognition +Tat-Jun Chin, Hanlin Goh and Joo-Hwee Lim +Institute for Infocomm Research +1 Heng Mui Keng Terrace, Singapore 119613. +{tjchin, hlgoh,"
faca1c97ac2df9d972c0766a296efcf101aaf969,Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition,"Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition C´esar Roberto de Souza1,2, Adrien Gaidon1, Eleonora Vig3, Antonio Manuel L´opez2 @@ -13764,6 +48052,27 @@ Computer Vision Group, Xerox Research Center Europe, Meylan, France Centre de Visi´o per Computador, Universitat Aut`onoma de Barcelona, Bellaterra, Spain German Aerospace Center, Wessling, Germany {cesar.desouza,"
+fa60521dabd2b64137392b4885e4d989f4b86430,Physics-Based Generative Adversarial Models for Image Restoration and Beyond,"Physics-Based Generative Adversarial Models +for Image Restoration and Beyond +Jinshan Pan, Yang Liu, Jiangxin Dong, Jiawei Zhang, +Jimmy Ren, Jinhui Tang, Yu-Wing Tai and Ming-Hsuan Yang"
+fabbc7f921d77b5aa9157310df29ad81367fe92d,Title of Dissertation : EFFICIENT IMAGE AND VIDEO REPRESENTATIONS FOR RETRIEVAL,
+fa9f1b236d0a252d4a56e26e8a9a41d496803413,Face Recognition Method with Two-Dimensional HMM,"FACE RECOGNITION METHOD WITH +TWO-DIMENSIONAL HMM +Janusz Bobulski1 +Czestochowa University of Technology +Institute of Computer and Information Science +Dabrowskiego Street 73, 42-200 Czestochowa, Poland."
+fa24a04f1e8095d47e2d2ce0076bf47bdd6f997a,Wavelet Based Face Recognition for Low Quality Images,"International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering +Vol. 2, Issue 1, January 2013 +Wavelet Based Face Recognition for Low +ISSN: 2278 – 8875 +Quality Images +M.Karthika, 2K.Shanmugapriya, 3Dr.S.Valarmathy, 4M.Arunkumar +PG Scholar, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu,India +PG Scholar, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu,India +Professor and Head, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India +Assistant Professor, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India"
fab60b3db164327be8588bce6ce5e45d5b882db6,Maximum A Posteriori Estimation of Distances Between Deep Features in Still-to-Video Face Recognition,"Maximum A Posteriori Estimation of Distances Between Deep Features in Still-to-Video Face Recognition @@ -13784,10 +48093,51 @@ vorgelegt von Ahmad Rabie n der Technischen Fakultät der Universität Bielefeld 5. März 2010"
+fac0151ed0494caf10c7d778059f176ba374e29c,Recognising Complex Mental States from Naturalistic Human-Computer Interactions,"Copyright and use of this thesis +This thesis must be used in accordance with the +provisions of the Copyright Act 1968. +Reproduction of material protected by copyright +may be an infringement of copyright and +opyright owners may be entitled to take +legal action against persons who infringe their +opyright. +Section 51 (2) of the Copyright Act permits +n authorized officer of a university library or +rchives to provide a copy (by communication +or otherwise) of an unpublished thesis kept in +the library or archives, to a person who satisfies +the authorized officer that he or she requires +the reproduction for the purposes of research +or study. +The Copyright Act grants the creator of a work +number of moral rights, specifically the right of +ttribution, the right against false attribution and +the right of integrity."
+fae4185a5fc540b057ea9e0402223e653327d0f9,Structured Edge Detection for Improved Object Localization using the Discriminative Generalized Hough Transform,
ff8315c1a0587563510195356c9153729b533c5b,Zapping Index:Using Smile to Measure Advertisement Zapping Likelihood,"Zapping Index:Using Smile to Measure Advertisement Zapping Likelihood Songfan Yang, Member, IEEE, Mehran Kafai, Member, IEEE, Le An, Student Member, IEEE, and Bir Bhanu, Fellow, IEEE"
+ff2e25cb67209de8ae922abdfc31f922b130276e,Information Granulation and Pattern Recognition,"Chapter 25 +Information Granulation and Pattern Recognition +Andrzej Skowron,1 Roman W. Swiniarski2 +Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warsaw, Poland +San Diego State University, Department of Mathematical and Computer Sciences, 5500 +Campanile Drive, San Diego, CA 92182, USA +Summary. We discuss information granulation applications in pattern recognition. The chap- +ter consists of two parts. In the first part, we present applications of rough set methods for +feature selection in pattern recognition. We emphasize the role of different forms of reducts +that are the basic constructs of the rough set approach in feature selection. In the overview +of methods for feature selection, we discuss feature selection criteria based on the rough set +pproach and the relationships between them and other existing criteria. Our algorithm for +feature selection used in the application reported is based on an application of the rough set +method to the result of principal component analysis used for feature projection and reduc- +tion. Finally, the first part presents numerical results of face recognition experiments using a +neural network, with feature selection based on proposed principal component analysis and +rough set methods. The second part consists of an outline of an approach to pattern recog- +nition with the application of background knowledge specified in natural language. The ap- +proach is based on constructing approximations of reasoning schemes. Such approximations +re called approximate reasoning schemes and rough neural networks."
ff44d8938c52cfdca48c80f8e1618bbcbf91cb2a,Towards Video Captioning with Naming: A Novel Dataset and a Multi-modal Approach,"Towards Video Captioning with Naming: a Novel Dataset and a Multi-Modal Approach Stefano Pini, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara @@ -13798,6 +48148,26 @@ Attention LSTM Networks Ke Zhang, Member, IEEE, Na Liu, Xingfang Yuan, Student Member, IEEE, Xinyao Guo, Ce Gao, nd Zhenbing Zhao Member, IEEE,"
ff398e7b6584d9a692e70c2170b4eecaddd78357,Title of dissertation : FACE RECOGNITION AND VERIFICATION IN UNCONSTRAINED ENVIRIONMENTS,
+ff70cfaf3e085a6c32bfa7ebedb98adfb7658210,TABULA RASA Trusted Biometrics under Spoofing Attacks,"TABULA RASA +Trusted Biometrics under Spoofing Attacks +http://www.tabularasa-euproject.org/ +Funded under the 7th FP (Seventh Framework Programme) +[Trustworthy Information and Communication Technologies] +Theme ICT-2009.1.4 +D3.2: Evaluation of baseline non-ICAO +iometric systems +Due date: 30/09/2011 +Project start date: 01/11/2010 Duration: 42 months +WP Manager: Abdenour Hadid Revision: 0 +Submission date: 30/09/2011 +Author(s): Federico Alegre, Xuran Zhao, Nick Evans (EURECOM); +John Bustard, Mark Nixon (USOU); Abdenour Hadid (UOULU); William +Ketchantang, Sylvaine Picard, St´ephane Revelin (MORPHO); Ale- +jandro Riera, Aureli Soria-Frisch (STARLAB); Gian Luca Marcialis +(UNICA) +Project funded by the European Commission +in the 7th Framework Programme (2008-2010) +Dissemination Level"
ffd81d784549ee51a9b0b7b8aaf20d5581031b74,Performance Analysis of Retina and DoG Filtering Applied to Face Images for Training Correlation Filters,"Performance Analysis of Retina and DoG Filtering Applied to Face Images for Training Correlation Filters @@ -13810,6 +48180,24 @@ Ensenada, Baja California, C.P. 22860 Facultad de Ingenier(cid:19)(cid:16)a, Arquitectura y Dise~no, Universidad Aut(cid:19)onoma de Baja California, Carretera Transpeninsular Tijuana-Ensenada, N(cid:19)um. 3917, Colonia Playitas, Ensenada, Baja California, C.P. 22860"
+fff854b3d8f8e916162dc5451cf6f46caf50002b,Multi-task Learning for Universal Sentence Embeddings: A Thorough Evaluation using Transfer and Auxiliary Tasks,"Multi-task Learning for Universal Sentence Embeddings: A Thorough +Evaluation using Transfer and Auxiliary Tasks +Wasi Uddin Ahmad†, Xueying Bai∗, Zhechao Huang§, Chao Jiang∗, Nanyun Peng(cid:63), Kai-Wei Chang† +§Fudan University, ∗University of Virginia +(cid:63)University of Southern California, †University of California, Los Angeles"
+ffdaa12d37c720561f74d23fc3b5d47afa268000,Pose Proposal Networks,"Pose Proposal Networks +Taiki Sekii[0000−0002−1895−3075] +Konica Minolta, Inc."
+ff4e8a8333e4ef506318160248c068250963806d,Gender recognition from face images using texture descriptors for human computer interaction,"www.jchps.com Journal of Chemical and Pharmaceutical Sciences +Gender recognition from face images using texture descriptors +ISSN: 0974-2115 +for human computer interaction +M.Annalakshmi1*, S.M.M.Roomi2, and S.S.Priya1 +&3Department of Electronics and Communication Engineering, Sethu Institute of Technology, Pulloor, Kariapatti +Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai 625 +– 626 115, Virudhunagar – District, Tamilnadu, India. +*Corresponding author: E-Mail: +015, Tamilnadu, India"
ff01bc3f49130d436fca24b987b7e3beedfa404d,Fuzzy System-Based Face Detection Robust to In-Plane Rotation Based on Symmetrical Characteristics of a Face,"Article Fuzzy System-Based Face Detection Robust to In-Plane Rotation Based on Symmetrical @@ -13822,12 +48210,66 @@ Seoul 100-715, Korea; (H.G.H.); (W.O.L.); (Y.G.K.); * Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 Academic Editor: Angel Garrido Received: 15 June 2016; Accepted: 29 July 2016; Published: 3 August 2016"
+ffd73d1956163a4160ec2c96b3ab256f79fc92e8,Attributes as Semantic Units between Natural Language and Visual Recognition,"Attributes as Semantic Units between +Natural Language and Visual Recognition +Marcus Rohrbach"
+ffc06713436afc4e08bf4afa401ac52db674c5da,Neural Adaptive Content-aware Internet Video Delivery,"Neural Adaptive Content-aware +Internet Video Delivery +Hyunho Yeo, Youngmok Jung, Jaehong Kim, Jinwoo Shin, and Dongsu Han, KAIST +https://www.usenix.org/conference/osdi18/presentation/yeo +This paper is included in the Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI ’18).October 8–10, 2018 • Carlsbad, CA, USAISBN 978-1-931971-47-8Open access to the Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation is sponsored by USENIX."
+ff269353b4e49274ff85dfb98b531888c98da365,Master : a Mobile Autonomous Scientist for Terretrial and Extra-terrestrial Research,"MASTER: A MOBILE AUTONOMOUS SCIENTIST FOR TERRETRIAL AND EXTRA- +TERRESTRIAL RESEARCH +Iain Wallace (1), Mark Woods (2) +(1) SCISYS, 23 Clothier Road, Bristol, BS4 5SS, UK, Email: +(2) SCISYS, 23 Clothier Road, Bristol, BS4 5SS, UK, Email: +paper +includes +utonomy. The +INTRODUCTION"
+ff3fa31882bb9c7573a38c7d0883503a464522a6,Imcube @ MediaEval 2015 Placing Task: Hierarchical Approach for Geo-referencing Large-Scale Datasets,"Imcube MediaEval 2015 Placing Task: A Hierarchical +Approach for Geo-referencing Large-Scale Datasets +Pascal Kelm, Sebastian Schmiedeke, and Lutz Goldmann +{kelm, schmiedeke, +Imcube Labs GmbH +Berlin, Germany"
+fff12919cf912347776b70aa76af7635280dc401,Are object detection assessment criteria ready for maritime computer vision?,"Are object detection assessment criteria ready +for maritime computer vision? +Dilip K. Prasad1,∗, Deepu Rajan2, and Chai Quek2"
+ffcb92719dcd993dda292ca82d4585950ea22ac9,Handwritten Digit Recognition Using Convolutional Neural Networks,"ISSN(Online): 2320-9801 +ISSN (Print): 2320-9798 +International Journal of Innovative Research in Computer +nd Communication Engineering +(An ISO 3297: 2007 Certified Organization) +Vol. 4, Issue 2, February 2016 +Handwritten Digit Recognition Using +Convolutional Neural Networks +Haider A. Alwzwazy1, Hayder M. Albehadili2, Younes S. Alwan3, Naz E. Islam4 +M.E Student, Dept. of Electrical and Computer Eng. University of Missouri-Columbia, MO, USA1,2,3 +Professor, Dept. of Electrical and Computer Eng. University of Missouri-Columbia, MO, USA4"
+ff7de2ea4d21e7d32d7f07e07fd278bebf6b5d66,Comparative survey of visual object classifiers,"Comparative survey of visual object classifiers +Laboratory Le2i, Universite Bourgogne - Franche-Comte, +Hiliwi Leake Kidane +1000 Dijon, France,"
+ffae2fe85d3c93610ac6270db2ddf1f2f6779ea8,Learning pullback HMM distances for action recognition,"#**** +ICCV 2011 Submission #****. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. +Learning pullback HMM distances for action recognition +Anonymous ICCV submission +Paper ID ****"
ffc9d6a5f353e5aec3116a10cf685294979c63d9,Eigenphase-based face recognition: a comparison of phase- information extraction methods,"Eigenphase-based face recognition: a comparison of phase- information extraction methods Slobodan Ribarić, Marijo Maračić Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10 000 Zagreb E-mail:"
+ff25c6602305ac46e9c35ffa4e30b14d679a5413,Face Templates Creation for Surveillance Face Recognition System,"Face Templates Creation for Surveillance Face Recognition System +Department of Radio Electronics, Brno University of Technology, Brno, Czech Republic +Department of Telecommunications, Brno University of Technology, Brno, Czech Republic +Tobias Malach1,2 and Jiri Prinosil3 +EBIS, spol. s r.o., Brno, Czech Republic +Keywords: +Face Templates, Template Database Creation, Face Recognition System Application, Real-world +Conditons."
ff8ef43168b9c8dd467208a0b1b02e223b731254,BreakingNews: Article Annotation by Image and Text Processing,"BreakingNews: Article Annotation by Image and Text Processing Arnau Ramisa*, Fei Yan*, Francesc Moreno-Noguer, @@ -13852,6 +48294,25 @@ of food, object, and mate preference. Like perception of other visual features, perception of attractiveness is stable despite constant changes of image properties due to factors like occlusion, visual noise, and eye"
+ff3ec3607b77a1dbb685cf90dd23a273d622dda5,Visual Attribute Extraction Using Human Pose Estimation,"Visual Attribute Extraction using Human Pose +Estimation +Angelo Nodari, Marco Vanetti, and Ignazio Gallo +Universit`a dell’Insubria, Dipartimento di Scienze Teoriche e Applicate +via Mazzini 5, 21100 Varese, Italy"
+ff4dec12d0ba0bb1d2c6bbc194545819bc9c1e5a,Face Recognition at a Distance: System Issues,"Chapter 6 +Face Recognition at a Distance: +System Issues +Meng Ao, Dong Yi, Zhen Lei, and Stan Z. Li"
+ffc8f9fe66a14aa0657e59e219364b5a852ecb8f,On the Utility of Context (or the Lack Thereof) for Object Detection,"On the Utility of Context (or the Lack Thereof) for Object Detection +Ehud Barnea and Ohad Ben-Shahar +Dept. of Computer Science, Ben-Gurion University +Beer-Sheva, Israel +{barneaeh,"
+ff83aade985b981fbf2233efbbd749600e97454c,Towards Understanding Adversarial Learning for Joint Distribution Matching,"ALICE: Towards Understanding Adversarial +Learning for Joint Distribution Matching +Chunyuan Li1, Hao Liu2, Changyou Chen3, Yunchen Pu1, Liqun Chen1, +Ricardo Henao1 and Lawrence Carin1 +Duke University 2Nanjing University 3University at Buffalo"
ffcbedb92e76fbab083bb2c57d846a2a96b5ae30,Sparse Dictionary Learning and Domain Adaptation for Face and Action Recognition,
ff7bc7a6d493e01ec8fa2b889bcaf6349101676e,Facial expression recognition with spatiotemporal local descriptors_v3.rtf,"Facial expression recognition with spatiotemporal local descriptors @@ -13866,6 +48327,16 @@ Facial Expression Recognition M. Dharmateja Purna, 1 N. Praveen2 M.Tech, Sri Sunflower College of Engineering & Technology, Lankapalli Asst. Professor, Dept. of ECE, Sri Sunflower College of Engineering & Technology, Lankapalli"
+ffb2d596c22be7b0ed8f809fdfbeaa95bd4db835,"The BDD-Nexar Collective: A Large-Scale, Crowsourced, Dataset of Driving Scenes","The BDD-Nexar Collective: A Large-Scale, Crowsourced, +Dataset of Driving Scenes +Vashisht Madhavan +Trevor Darrell +Fisher Yu, Ed. +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2017-113 +http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-113.html +May 29, 2017"
ff5dd6f96e108d8233220cc262bc282229c1a582,Robust Facial Marks Detection Method Using AAM And SURF,"Ziaul Haque Choudhury, K.M. Mehata / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.708-715 @@ -13873,10 +48344,51 @@ Robust Facial Marks Detection Method Using AAM And SURF Ziaul Haque Choudhury, K.M. Mehata Dept. of Information Technology, B.S. Abdur Rahman University, Chennai-48, India Dept. of Computer Science & Engineering, B.S. Abdur Rahman University, Chennai-48, India"
+ffe8a4cef9dec30ddd2c956c2f63b128a4568f84,Intensity Video Guided 4D Fusion for Improved Highly Dynamic 3D Reconstruction,"Intensity Video Guided 4D Fusion for +Improved Highly Dynamic 3D Reconstruction +Jie Zhang, Christos Maniatis, Luis Horna and Robert B. Fisher"
+c5af99522e324b72c8a563a5d6b7c9a0101efb65,Exploring Human Vision Driven Features for Pedestrian Detection,"(cid:13) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any +urrent or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new +ollective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other +works."
+c54e8c7a4f9c2ebd8787aecafa4cfdb35bfd49e0,Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition,"Effective Use of Bidirectional Language Modeling for +Medical Named Entity Recognition +Devendra Singh Sachan1,*, Pengtao Xie1, and Eric P Xing1 +Petuum Inc, Pittsburgh, 15222, USA"
c588c89a72f89eed29d42f34bfa5d4cffa530732,Attributes2Classname: A Discriminative Model for Attribute-Based Unsupervised Zero-Shot Learning,"Attributes2Classname: A discriminative model for attribute-based unsupervised zero-shot learning Berkan Demirel1,3, Ramazan Gokberk Cinbis2, Nazli Ikizler-Cinbis3 HAVELSAN Inc., 2Bilkent University, 3Hacettepe University"
+c52aa6b9c7b89782f2316ce8ef2156fa06a3696d,Learning Semantic Part-Based Models from Google Images,"Learning Semantic Part-Based Models +from Google Images +Davide Modolo and Vittorio Ferrari"
+c5420ef59d7508d82e53671b0d623027eb58e6ed,Learning to Reweight Examples for Robust Deep Learning,"Learning to Reweight Examples for Robust Deep Learning +Mengye Ren 1 2 Wenyuan Zeng 1 2 Bin Yang 1 2 Raquel Urtasun 1 2"
+c5318c79bc1b880e8356211b837b684f1ee6e5c4,Acquiring Common Sense Spatial Knowledge Through Implicit Spatial Templates,"Acquiring Common Sense Spatial Knowledge through Implicit Spatial Templates +Department of Computer Science +Computer Vision Laboratory +Guillem Collell +KU Leuven +Luc Van Gool +ETH Zurich +Marie-Francine Moens +Department of Computer Science +KU Leuven"
+c55a6c98887b3079647d0edb4778d81bab6708f6,Self-Similarity Representation of Faces for Kin Relationships,"HCTL Open International Journal of Technology Innovations and Research (IJTIR) +http://ijtir.hctl.org +Volume 16, July 2015 +e-ISSN: 2321-1814, ISBN (Print): 978-1-943730-43-8 +Self-Similarity Representation +of Faces for Kin +Relationships +Pratibha Chaskar1, Dr. Manjusha Deshmukh2"
+c5decf0a3906c85b6540e96c9c7003957c6d395b,Optimizing the Trade-off between Single-Stage and Two-Stage Object Detectors using Image Difficulty Prediction,"Optimizing the Trade-off between +Single-Stage and Two-Stage Deep Object Detectors +using Image Difficulty Prediction +Petru Soviany, Radu Tudor Ionescu +Department of Computer Science +University of Bucharest, Romania +E-mails:"
c574c72b5ef1759b7fd41cf19a9dcd67e5473739,"COGNIMUSE: a multimodal video database annotated with saliency, events, semantics and emotion with application to summarization","Zlatintsi et al. EURASIP Journal on Image and Video Processing (2017) 2017:54 DOI 10.1186/s13640-017-0194-1 EURASIP Journal on Image @@ -13890,10 +48402,71 @@ summarization Athanasia Zlatintsi1* Niki Efthymiou1, Katerina Pastra4, Alexandros Potamianos1 and Petros Maragos1 , Petros Koutras1, Georgios Evangelopoulos2, Nikolaos Malandrakis3,"
+c5b05718963f4edff80456c441796e4199ad8d41,Sampling and Ontologically Pooling Web Images for Visual Concept Learning,"Sampling and Ontologically Pooling Web Images for +Visual Concept Learning +Shiai Zhu, Chong-Wah Ngo, and Yu-Gang Jiang"
c5a561c662fc2b195ff80d2655cc5a13a44ffd2d,Using Language to Learn Structured Appearance Models for Image Annotation,"Using Language to Learn Structured Appearance Models for Image Annotation Michael Jamieson, Student Member, IEEE, Afsaneh Fazly, Suzanne Stevenson, Sven Dickinson, Member, IEEE, Sven Wachsmuth, Member, IEEE"
+c5e4467b5830d7dad4e940f0766ae728f22e38fc,Object recognition and localization,"Object recognition and localization +Badri Narayana Patro +Dept. of Electrical Engineering +Ganesh Boddupally +Dept. of Electrical Engineering"
+c5637543e80f97c9ddab8b54a635cf71941e2786,Self-Calibrating View-Invariant Gait Biometrics,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS +Self-Calibrating View-Invariant Gait Biometrics +Michela Goffredo, Member, IEEE, Imed Bouchrika, Member, IEEE, John N. Carter, Member, IEEE, and +Mark S. Nixon, Associate Member, IEEE"
+c528e6285ed170c9a838446c062c8dfbe31c546e,Real Time 3 D Head Pose Estimation : Recent Achievements and Future Challenges,"REAL TIME 3D HEAD POSE ESTIMATION: +RECENT ACHIEVEMENTS AND FUTURE CHALLENGES +Gabriele Fanelli, Juergen Gall, Luc Van Gool +Computer Vision Laboratory - ETH Zurich"
+c542fa8c4cfaff6a8d8efa9678e42e1b9ead8aa9,griffith . edu . au Face Recognition using Ensemble String Matching,"Griffith Research Online +https://research-repository.griffith.edu.au +Face Recognition using Ensemble String +Matching +Author +Chen, Weiping, Gao, Yongsheng +Published +Journal Title +IEEE Transactions on Image Processing +https://doi.org/10.1109/TIP.2013.2277920 +Copyright Statement +Copyright 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be +obtained for all other uses, in any current or future media, including reprinting/republishing this material +for advertising or promotional purposes, creating new collective works, for resale or redistribution to +servers or lists, or reuse of any copyrighted component of this work in other works. +Downloaded from +http://hdl.handle.net/10072/54416"
+c53a512b4d7dee0d8d0f3e5bf2c6ace7a00cbbae,"Content-Based Video Indexing and Retrieval using Key frames Texture, Edge and Motion Features","International Journal of Current Engineering and Technology +©2016 INPRESSCO®, All Rights Reserved +Research Article +Content-Based Video Indexing and Retrieval using Key frames Texture, +Edge and Motion Features +M.Ravinder†* and T.Venugopal‡ +E-ISSN 2277 – 4106, P-ISSN 2347 – 5161 +Available at http://inpressco.com/category/ijcet +(R.Hamid et al., 2007; G. Lavee et al., 2009; J. Tang et al., +009; X. Chen et al., 2009). +JNTUK, Kakinada, Andhra Pradesh, India +Department of CSE, JNTUHCES, Sultanpur, Medak, Telangana, India +Accepted 25 April 2016, Available online 30 April 2016, Vol.6, No.2 (April 2016)"
+c593c6080c75133191a27381a58cd07c97aa935b,Gender Classification Using a Min-Max Modular Support Vector Machine with Incorporating Prior Knowledge,"SUBMITTED TO IEEE TRANSACTIONS ON NEURAL NETWORKS +Gender Classification Using a Min-Max Modular +Support Vector Machine with Incorporating +Prior Knowledge +Hui-Cheng Lian and ∗Bao-Liang Lu, Senior Member, IEEE"
+c5d9ac2f52c9fc229890798b9d6e4d899b72c525,Image Enhancement Technique using Adaptive Multiscale Retinex for Face Recognition Systems,"Image Enhancement Technique using Adaptive +Multiscale Retinex for Face Recognition Systems +Khairul Anuar Ishak1, Salina Abdul Samad1 +M. A. Hannan1 and Maizura Mohd Sani2 +Dept. of Electrical, Electronics and Systems Engineering +Faculty of Engineering and Built Environment, University Kebangsaan Malaysia +3600, UKM Bangi, Selangor, Malaysia +Institute of Microengineering and Nanoelectronics, University Kebangsaan Malaysia +3600, UKM Bangi, Selangor, Malaysia"
c5c379a807e02cab2e57de45699ababe8d13fb6d,Facial Expression Recognition Using Sparse Representation,"Facial Expression Recognition Using Sparse Representation SHIQING ZHANG 1, XIAOMING ZHAO 2, BICHENG LEI 1 School of Physics and Electronic Engineering @@ -13912,6 +48485,21 @@ for the degree of Doctor of Philosophy The University of Leeds School of Computing September 2016"
+c5c0cda46a77a7ea8c1f6d4d762b189ef424ffa4,Semantic 3 D Reconstruction of Heads,"Semantic 3D Reconstruction of Heads +Fabio Maninchedda1, Christian H¨ane2,(cid:63), Bastien Jacquet3,(cid:63), +Ama¨el Delaunoy(cid:63), Marc Pollefeys1,4 +ETH Zurich +UC Berkeley +Kitware SAS +Microsoft"
+c52f2a00fdbfb7fb10252796dbede6403e780da6,Input Convex Neural Networks,"Input Convex Neural Networks +Brandon Amos 1 Lei Xu 2 * J. Zico Kolter 1"
+c50c034d264083757eadeee5d0b94d933fe78544,Query by string word spotting based on character bi-gram indexing,"Query by String word spotting based on character +i-gram indexing +Computer Vision Center, Dept. Ci`encies de la Computaci´o +Universitat Aut`onoma de Barcelona, 08193 Bellaterra (Barcelona), Spain +Suman K. Ghosh and Ernest Valveny +Email:"
c5844de3fdf5e0069d08e235514863c8ef900eb7,A Study on Similarity Computations in Template Matching Technique for Identity Verification,"Lam S K et al. / (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 08, 2010, 2659-2665 A Study on Similarity Computations in Template @@ -13928,6 +48516,29 @@ Eun-Hye Jang, 2Byoung-Jun Park, 3Sang-Hyeob Kim, 4Jin-Hun Sohn Research Institute, 138 Gajeongno, Yuseong-gu, Daejeon, 305-700, Republic of Korea, *4Department of Psychology/Brain Research Institute, Chungnam National University 220, Gung-dong, Yuseong-gu, Daejeon, 305-765, Republic of Korea,"
+c591cb28d12b7ee53af4e5c2050b74071527c248,The face of fear and anger: Facial width-to-height ratio biases recognition of angry and fearful expressions.,"The Face of Fear and Anger: Facial Width-to-Height +Ratio Biases Recognition of Angry and Fearful +Expressions +Jason C. Deska, E. Paige Lloyd, and Kurt Hugenberg +Online First Publication, May 11, 2017. http://dx.doi.org/10.1037/emo0000328 +CITATION +Deska, J. C., Lloyd, E. P., & Hugenberg, K. (2017, May 11). The Face of Fear and Anger: Facial +online publication. http://dx.doi.org/10.1037/emo0000328"
+c55dcc587a53ff82cf3f79d84e7df67f4c8f77ed,TabletGaze: A Dataset and Baseline Algorithms for Unconstrained Appearance-based Gaze Estimation in Mobile Tablets,"TabletGaze: A Dataset and Baseline Algorithms +for Unconstrained Appearance-based Gaze +Estimation in Mobile Tablets +Qiong Huang, Student Member, IEEE, Ashok Veeraraghavan, Member, IEEE, +nd Ashutosh Sabharwal, Fellow, IEEE"
+c50630e485d3c7785ea9e1f3bff35ea00e926a56,Deep Image Retrieval: Learning Global Representations for Image Search,"Deep Image Retrieval: +Learning global representations for image search +Albert Gordo, Jon Almaz´an, Jerome Revaud, and Diane Larlus +Computer Vision Group, Xerox Research Center Europe"
+c5c6ec48ae98d86171360b19e3ec03738c712f53,Infinite Hidden Conditional Random Fields for Human Behavior Analysis,"Infinite Hidden Conditional Random Fields for +Human Behavior Analysis +Konstantinos Bousmalis, Student Member, IEEE, +Stefanos Zafeiriou, Member, IEEE, +Louis-Philippe Morency, Member, IEEE, +nd Maja Pantic, Fellow, IEEE"
c2c3ff1778ed9c33c6e613417832505d33513c55,"Multimodal Biometric Person Authentication Using Fingerprint, Face Features","Multimodal Biometric Person Authentication Using Fingerprint, Face Features Tran Binh Long1, Le Hoang Thai2, and Tran Hanh1 @@ -13935,6 +48546,32 @@ Department of Computer Science, University of Lac Hong 10 Huynh Van Nghe, DongNai 71000, Viet Nam Department of Computer Science, Ho Chi Minh City University of Science 27 Nguyen Van Cu, HoChiMinh 70000, Viet Nam"
+c21db705a33212768c63be11747d075371c7307f,A Content-Based Late Fusion Approach Applied to Pedestrian Detection,"A Content-Based Late Fusion Approach Applied to +Pedestrian Detection +Jessica Sena, Artur Jord˜ao, William Robson Schwartz +Smart Surveillance Interest Group +Department of Computer Science, Universidade Federal de Minas Gerais +Av. Presidente Antˆonio Carlos, 6627 - Pampulha, Belo Horizonte, Brazil"
+c2adfc55e0ab9be6e8f5e4ebeb20770dca307cef,"The effect of diagnosis, age, and symptom severity on cortical surface area in the cingulate cortex and insula in autism spectrum disorders.","http://jcn.sagepub.com/ +The Effect of Diagnosis, Age, and Symptom Severity on Cortical Surface Area in the Cingulate Cortex +nd Insula in Autism Spectrum Disorders +Krissy A.R. Doyle-Thomas, Azadeh Kushki, Emma G. Duerden, Margot J. Taylor, Jason P. Lerch, Latha V. Soorya, A. +Ting Wang, Jin Fan and Evdokia Anagnostou +J Child Neurol +2013 28: 729 originally published online 25 July 2012 +DOI: 10.1177/0883073812451496 +The online version of this article can be found at: +http://jcn.sagepub.com/content/28/6/729 +Published by: +http://www.sagepublications.com +Additional services and information for +can be found at: +Email Alerts: +http://jcn.sagepub.com/cgi/alerts +Subscriptions: +http://jcn.sagepub.com/subscriptions +Reprints: +http://www.sagepub.com/journalsReprints.nav"
c27f64eaf48e88758f650e38fa4e043c16580d26,Title of the proposed research project: Subspace analysis using Locality Preserving Projection and its applications for image recognition,"Title of the proposed research project: Subspace analysis using Locality Preserving Projection and its applications for image recognition Research area: Data manifold learning for pattern recognition @@ -13943,21 +48580,185 @@ Name: Gitam C Shikkenawis Email Address: University: Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT), Gandhinagar."
+c2d065bc8067384c40b3e8146cadc9a0c4c1d633,SLC25A12 expression is associated with neurite outgrowth and is upregulated in the prefrontal cortex of autistic subjects,"& 2008 Nature Publishing Group All rights reserved 1359-4184/08 $30.00 +www.nature.com/mp +ORIGINAL ARTICLE +SLC25A12 expression is associated with neurite +outgrowth and is upregulated in the prefrontal cortex +of autistic subjects +A-M Lepagnol-Bestel1, G Maussion1, B Boda2, A Cardona3, Y Iwayama4, A-L Delezoide5, J-M Moalic1, +D Muller2, B Dean6, T Yoshikawa4,7, P Gorwood1, JD Buxbaum8,9, N Ramoz1 and M Simonneau1 +INSERM U675, IFR2, Faculte´ de Me´ decine Xavier Bichat, Paris, France; 2Department of Basic Neuroscience, Centre Medical +Universitaire, Geneva, Switzerland; 3Histotechnology and Pathology Unit, Institut Pasteur, Paris, France; 4Laboratory for +AP-HP, Paris, France; 6The Rebecca L Cooper Research Laboratories, Mental Health Research Institute of Victoria, Parkville, +VIC, Australia; 7CREST, Japan Science and Technology Agency, Saitama, Japan; 8Department of Psychiatry, Mount Sinai +School of Medicine, New York, NY, USA and 9Department of Neuroscience, Mount Sinai School of Medicine, New York, +NY, USA +in the BA46 prefrontal cortex but not +Autism is a neurodevelopmental disorder with a strong genetic component, probably involving +several genes. Genome screens have provided evidence of linkage to chromosome 2q31–q33, +which includes the SLC25A12 gene. Association between autism and single-nucleotide +polymorphisms in SLC25A12 has been reported in various studies. SLC25A12 encodes the +mitochondrial aspartate/glutamate carrier functionally important"
+c231d8638e8b5292c479d20f7dd387c53e581a1a,Multi-View Data Generation Without View Supervision,"MULTI-VIEW DATA GENERATION WITHOUT VIEW +SUPERVISION +Micka¨el Chen, Ludovic Denoyer +Sorbonne Universit´es, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France +Thierry Arti`eres +Ecole Centrale Marseille - Laboratoire d’Informatique Fondamentale (Aix-Marseille Univ.), France."
+c223b2b7d38dc4e0ad418c404b2d3c43c62213bc,Trade-off Between GPGPU based Implementations of Multi Object Tracking Particle Filter,"Trade-off between GPGPU based implementations of +multi object tracking particle filter +Petr Jecmen, Frédéric Lerasle, Alhayat Ali Mekonnen +To cite this version: +Petr Jecmen, Frédéric Lerasle, Alhayat Ali Mekonnen. Trade-off between GPGPU based implemen- +tations of multi object tracking particle filter. International Conference on Computer Vision Theory +nd Applications, Feb 2017, Porto, Portugal. 10p., 2017. <hal-01763095> +HAL Id: hal-01763095 +https://hal.laas.fr/hal-01763095 +Submitted on 10 Apr 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+c2fb2cb5487ad404b8e66daf74198496c40bef32,Learning to Transfer Privileged Information,"Learning to Transfer Privileged Information +Viktoriia Sharmanska1∗, Novi Quadrianto2, and Christoph Lampert1, +Institute of Science and Technology Austria, Austria +SMiLe CLiNiC, University of Sussex, UK"
c220f457ad0b28886f8b3ef41f012dd0236cd91a,Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition Rajeev Ranjan, Member, IEEE, Ankan Bansal, Hongyu Xu, Member, IEEE, Swami Sankaranarayanan, Member, IEEE, Jun-Cheng Chen, Member, IEEE, Carlos D Castillo, Member, IEEE, and Rama Chellappa, Fellow, IEEE"
+c28f57d0a22e54fdd3c4a57ecb1785dda49f0e5e,From Scores to Face Templates: A Model-Based Approach,"From Scores to Face Templates: +A Model-Based Approach +Pranab Mohanty, Student Member, IEEE, Sudeep Sarkar, Senior Member, IEEE, and +Rangachar Kasturi, Fellow, IEEE"
c254b4c0f6d5a5a45680eb3742907ec93c3a222b,A Fusion-based Gender Recognition Method Using Facial Images,"A Fusion-based Gender Recognition Method Using Facial Images Benyamin Ghojogh, Saeed Bagheri Shouraki, Hoda Mohammadzade*, Ensieh Iranmehr"
+c259693737ce52e2e37972e15334cbe78b653e69,Image Processing Supports HCI in Museum Application,"Image Processing Supports HCI in Museum Application +Niki Martinel, Marco Vernier, Gian Luca Foresti and Elisabetta Lamedica +Department of Mathematics and Computer Science, University of Udine, Via Delle Scienze 206, Udine, Italy +{niki.martinel, marco.vernier, +Keywords: +Augmented Reality: Information Visualization: User Interface Design: Mobile HCI."
+c29487c5eb0cdb67d92af1bc0ecbcf825e2abec3,3-D Face Recognition With the Geodesic Polar Representation,"-D Face Recognition With the +Geodesic Polar Representation +Iordanis Mpiperis, Sotiris Malassiotis, and Michael G. Strintzis, Fellow, IEEE +therefore,"
+c2b1007824fa7ce3a7a94209f0be0902a3454bae,Project Description 1 Introduction,"Project Description +Introduction +Recognizing human action is a key component in many vision applications, such as video surveil- +lance, 3D human pose estimation and video indexing. From the human-centered computing (HCC) +point of view, an automatic action recognition system can provide an interface between artificial +gents and human users accounting for perception and action in a novel interaction paradigm. +Although significant progress has been made in action recognition [1], the problem remains inher- +ently challenging due to significant intra-class variations, viewpoint change, partial occlusion and +ackground dynamic variations. A key limitation of many action-recognition approaches is that +their models are learned from single 2D view video features on individual datasets and thus un- +ble to handle arbitrary view change or scale and background variations. Also, since they are not +generalizable across different datasets, retraining is necessary for any new dataset. +Our research is motivated by the requirement of view-invariant action recognition and the fact that +the existing human motion capture data provides useful knowledge to understand the intrinsic motion +structure (Fig. 2). In particular, we address the problem of modeling and analyzing human motion +in the joint-trajectories space. Our view-invariant recognition system has the following functions +(Fig. 1), +(1) Given a labeled Mocap sequences with M markers in 3D, which is a 3M -dimensional sequential +data, the low dimensional manifold structure (i.e., geodesics distance, intrinsic dimensionality, etc) +is learnt by using Tensor Voting. This is an offline process, as shown in Fig. 1."
+c2f2c89d7615df07b540748d6c53485c4cbfa9c0,An Experience Report on Requirements-Driven Model-Based Synthetic Vision Testing,"An Experience Report on Requirements-Driven +Model-Based Synthetic Vision Testing +Markus Murschitz and Oliver Zendel and Martin Humenberger +nd Christoph Sulzbachner and Gustavo Fern´andez Dom´ınguez 1"
+c2b9d6742e504491800cee44adb05d2d706fc209,Semantic-Based Web Mining For Image Retrieval Using Enhanced Support Vector Machine,"International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 5 (2016) pp 3276-3281 +© Research India Publications. http://www.ripublication.com +Semantic-Based Web Mining For Image Retrieval Using Enhanced Support +Vector Machine +Ph.D Research Scholar, Research Department of Computer Science, +NGM College, Pollachi, Coimbatore, Tamil Nadu, India. +P. Sumathi +R. Manickachezian +Associate Professor, Research Department of Computer Science, +NGM College, Pollachi, Coimbatore, Tamil Nadu, India."
+c2eed73654b544a705b194ade58cd82488c6c5b9,"Scene Understanding by Labeling Pixels Key Insights ˽ Recent Progress on Image Understanding, a Long-standing Challenge of Ai, Is Enabling Numerous New Applications in Robot Perception, Surveillance and Environmental Monitoring, Content- Based Image Search, and Social-media Summarization","ontributed articles +DOI:10.1145/2629637 +Pixels labeled with a scene’s semantics and +geometry let computers describe what they see. +BY STEPHEN GOULD AND XUMING HE +Scene +Understanding +y Labeling +Pixels +PROGRAMMING COMPUTERS TO automatically interpret +the content of an image is a long-standing challenge in +rtificial intelligence and computer vision. That difficulty +is echoed in a well-known anecdote from the early years +of computer-vision research in which an undergraduate +student at MIT was asked to spend his summer getting a +omputer to describe what it “saw” in images obtained +from a video camera.35 Almost 50 years later researchers +re still grappling with the same problem. +A scene can be described in many ways and include +details about objects, regions, geometry, location,"
+c2b8b49526e3dd537b641a6495e49a3d1a0ebbf2,Extended Feature-Fusion Guidelines to Improve Image-Based Multi-Modal Biometrics,"Extended Feature-Fusion Guidelines to Improve +Image-Based Multi-Modal Biometrics +Dane Brown +Council for Scientific and Industrial Research +Information Security +Pretoria, South Africa"
+c238f871c029d8c33949f8410f8cf3bf79ffc102,No Blind Spots: Full-Surround Multi-Object Tracking for Autonomous Vehicles using Cameras & LiDARs,"No Blind Spots: Full-Surround Multi-Object +Tracking for Autonomous Vehicles using +Cameras & LiDARs +Akshay Rangesh, Member, IEEE, and Mohan M. Trivedi, Fellow, IEEE"
+c2d35b387518496d8100f70e82597b002eba600e,Online Multi-player Tracking in Monocular Soccer Videos,"Available online at www.sciencedirect.com +AASRI Procedia 00 (2014) 000–000 +014 AASRI Conference on Sports Engineering and Computer Science (SECS 2014) +Online Multi-player Tracking in Monocular Soccer Videos +Michael Herrmanna,*, Martin Hoerniga, Bernd Radiga +Technische Universität München, Image Understanding and Knowledge-Based Systems, Boltzmannstr. 3, D-85748 Garching, Germany"
+c20b2ec72ebf798e9567a145465e37a755fc34d8,Fully Automatic Multi-person Human Motion Capture for VR Applications,"Fully Automatic Multi-person Human Motion Capture +for VR Applications +Ahmed Elhayek1,2, Onorina Kovalenko1, Pramod Murthy1,2, Jameel Malik1,2, and +Didier Stricker1,2 +German Research Centre for Artificial Intelligence (DFKI), Kaiserslautern, Germany +University of Kaiserslautern, Germany +{ahmed.elhayek, onorina.kovalenko, pramod.murthy, +jameel.malik,"
+c2e9300b0e72dca0b95ccd4181fc2a7a5178dea7,Improving Bilayer Product Quantization for Billion-Scale Approximate Nearest Neighbors in High Dimensions,"Improving Bilayer Product Quantization +for Billion-Scale Approximate Nearest Neighbors in High +Dimensions +Artem Babenko +Yandex +Moscow Institute of Physics and Technology +Victor Lempitsky +Skolkovo Institute of Science and Technology"
+c2cb38fc68b877a96be99b814e8ee437e585f5b2,Mining on Manifolds: Metric Learning without Labels,"Mining on Manifolds: Metric Learning without Labels +Ahmet Iscen1 Giorgos Tolias1 Yannis Avrithis2 Ondˇrej Chum1 +VRG, FEE, CTU in Prague +Inria Rennes"
c2e6daebb95c9dfc741af67464c98f1039127627,Efficient Measuring of Facial Action Unit Activation Intensities using Active Appearance Models,"MVA2013 IAPR International Conference on Machine Vision Applications, May 20-23, 2013, Kyoto, JAPAN Efficient Measuring of Facial Action Unit Activation Intensities using Active Appearance Models Daniel Haase1, Michael Kemmler1, Orlando Guntinas-Lichius2, Joachim Denzler1 Computer Vision Group, Friedrich Schiller University of Jena, Germany Department of Otolaryngology, University Hospital Jena, Germany"
+f65896855e5df3db5422b57ab360287efa213066,Detection of Uncontrolled Motion Behavior in Human Crowds,"IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 +DETECTION OF UNCONTROLLED MOTION BEHAVIOR IN HUMAN +CROWDS +Vijitha V. A1 +Student of M. Tech., Computer Science & Engineering, Sahyadri College of Engineering & Management, Karnataka, +India"
+f6ba16aee3c40b69dc88c947ae59811104b1bd49,Skeletal Tracking using Microsoft Kinect,"Skeletal Tracking using Microsoft Kinect +Abhishek Kar +Advisors: Dr. Amitabha Mukerjee & Dr. Prithwijit Guha +Department of Computer Science and Engineering, IIT Kanpur"
f6f06be05981689b94809130e251f9e4bf932660,An Approach to Illumination and Expression Invariant Multiple Classifier Face Recognition,"An Approach to Illumination and Expression Invariant International Journal of Computer Applications (0975 – 8887) Volume 91 – No.15, April 2014 @@ -13987,6 +48788,23 @@ ISSN: 2249 – 8958, Volume-2, Issue-4, April 2013 Algorithm for Face Matching Using Normalized Cross-Correlation C. Saravanan, M. Surender"
+f614f9ba33554cfd1a474be03520319b51651a35,Cardiac interoceptive learning is modulated by emotional valence perceived from facial expressions,"Social Cognitive and Affective Neuroscience, 2018, 677–686 +doi: 10.1093/scan/nsy042 +Advance Access Publication Date: 6 April 2018 +Original article +Cardiac interoceptive learning is modulated by +emotional valence perceived from facial expressions +Amanda C. Marshall, Antje Gentsch, Lena Schro¨ der, and +Simone Schu¨ tz-Bosbach +General and Experimental Psychology Unit, Department of Psychology, Ludwig-Maximilians University +Munich, D-80802 Munich, Germany +Correspondence should be addressed to Amanda C. Marshall, General and Experimental Psychology Unit, Department of Psychology, Ludwig- +Maximilians-University Munich, Leopoldstr. 13, D-80802 Munich, Germany. E-mail:"
+f6684367e7925cd90fb8974640d41823191c7cff,CNN-based Pore Detection and Description for High-Resolution Fingerprint Recognition,"Automatic Dataset Annotation to Learn CNN Pore +Description for Fingerprint Recognition +Gabriel Dahia +Maur´ıcio Pamplona Segundo +Department of Computer Science, Federal University of Bahia"
f67a73c9dd1e05bfc51219e70536dbb49158f7bc,A Gaussian Mixture Model for Classifying the Human Age using DWT and Sammon Map,"Journal of Computer Science 10 (11): 2292-2298, 2014 ISSN: 1549-3636 © 2014 Nithyashri and Kulanthaivel, This open access article is distributed under a Creative Commons Attribution @@ -13997,11 +48815,67 @@ J. Nithyashri and 2G. Kulanthaivel Department of Computer Science and Engineering, Sathyabama University, Chennai, India Department of Electronics Engineering, NITTTR, Chennai, India Received 2014-05-08; Revised 2014-05-23; Accepted 2014-11-28"
+f663ad5467721159263c1cde261231312893f45d,UvA-DARE ( Digital Academic Repository ) Gaze Embeddings for Zero-Shot Image Classification,"UvA-DARE (Digital Academic Repository) +Gaze Embeddings for Zero-Shot Image Classification +Karessli, N.; Akata, Z.; Schiele, B.; Bulling, A. +Published in: +0th IEEE Conference on Computer Vision and Pattern Recognition +0.1109/CVPR.2017.679 +Link to publication +Citation for published version (APA): +Karessli, N., Akata, Z., Schiele, B., & Bulling, A. (2017). Gaze Embeddings for Zero-Shot Image Classification. In +0th IEEE Conference on Computer Vision and Pattern Recognition: CVPR 2017 : 21-26 July 2016, Honolulu, +Hawaii : proceedings (pp. 6412-6421). Piscataway, NJ: IEEE. DOI: 10.1109/CVPR.2017.679 +General rights +It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +Disclaimer/Complaints regulations +If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask +the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, +The Netherlands. You will be contacted as soon as possible. +Download date: 18 Nov 2018"
+f672d6352a5864caab5a5a286fbc1ce042b55c16,Stabilizing GAN Training with Multiple Random Projections,"Under review as a conference paper at ICLR 2018 +Stabilizing GAN Training with +Multiple Random Projections +Anonymous authors +Paper under double-blind review"
+f66bc143d85d2b1d9aafec20f598a21d2b90b0c0,Seeing 3 D Objects in a Single 2 D Image,"Accepted for publication in the Proceedings of the 12th International Conference of Computer Vision, 2009 +Seeing 3D Objects in a Single 2D Image +Diego Rother +Johns Hopkins University"
+f6785ffe6fe2c30887637a61061a64f4d6725979,BAR: Bayesian Activity Recognition using variational inference,"BAR: Bayesian Activity Recognition using variational +inference +Ranganath Krishnan +Mahesh Subedar +Omesh Tickoo +Intel Labs +Hillsboro, OR (USA)"
f6c70635241968a6d5fd5e03cde6907022091d64,Measuring Deformations and Illumination Changes in Images with Applications to Face Recognition,
+f636c087091847bd4ccd6d196ada6c0894b52d88,Rate-Accuracy Trade-Off in Video Classification with Deep Convolutional Neural Networks,"Rate-Accuracy Trade-Off In Video Classification +With Deep Convolutional Neural Networks +Mohammad Jubran, Alhabib Abbas, Aaron Chadha and Yiannis Andreopoulos, Senior Member, IEEE"
f6ce34d6e4e445cc2c8a9b8ba624e971dd4144ca,Cross-Label Suppression: A Discriminative and Fast Dictionary Learning With Group Regularization,"Cross-label Suppression: A Discriminative and Fast Dictionary Learning with Group Regularization Xiudong Wang and Yuantao Gu∗ April 24, 2017"
+f67afec4226aba674e786698b39b85b124945ddd,Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions,"Spatial Variational Auto-Encoding via Matrix-Variate +Normal Distributions +Zhengyang Wang +School of Electrical Engineering +nd Computer Science +Washington State University +Pullman, WA 99163 +Hao Yuan +School of Electrical Engineering +nd Computer Science +Washington State University +Pullman, WA 99163 +Shuiwang Ji +School of Electrical Engineering +nd Computer Science +Washington State University +Pullman, WA 99163"
f6fa97fbfa07691bc9ff28caf93d0998a767a5c1,K2-means for Fast and Accurate Large Scale Clustering,"k2-means for fast and accurate large scale clustering Eirikur Agustsson Computer Vision Lab @@ -14018,6 +48892,11 @@ f6cf2108ec9d0f59124454d88045173aa328bd2e,Robust User Identification Based on Fac unaffected by users’ emotions Ricardo Buettner Aalen University, Germany"
+f614b449ee2fd45974214014c109d993aab73343,A Mathematical Motivation for Complex-Valued Convolutional Networks,"A Mathematical Motivation for +Complex-valued Convolutional Networks +Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert +Facebook Artificial Intelligence Research, 1 Facebook Way, Menlo Park, California 94025 +Keywords: deep learning, neural networks, harmonic analysis"
f68f20868a6c46c2150ca70f412dc4b53e6a03c2,Differential Evolution to Optimize Hidden Markov Models Training: Application to Facial Expression Recognition,"Differential Evolution to Optimize Hidden Markov Models Training: Application to Facial Expression @@ -14038,6 +48917,22 @@ most pertinent information and give a meaningful repre- sentation to humans. The main problem of the use of HMMs is that the training is generally trapped in local minima, so we used the Differential Evolution (DE)"
+f6cf220b8ef17e0a4bef0ff5aadc40eec9653159,Automated System for interpreting Non-verbal Communication in Video Conferencing,"Chetana Gavankar et al / International Journal on Computer Science and Engineering Vol.2(1), 2010, 22-27 +Automated System for interpreting Non-verbal +Communication in Video Conferencing +Chetana Gavankar +Senior Lecturer, +Department of Information Technology +Cummins College of Engineering for Women +Karve Nagar, Pune - 411052 +for more effective"
+e909b9e0bbfc37d0b99acad5014e977daac7e2bd,Adversarial Training of Variational Auto-Encoders for High Fidelity Image Generation,"Adversarial Training of Variational Auto-encoders for +High Fidelity Image Generation +Salman H. Khan†, Munawar Hayat ‡, Nick Barnes † +Data61 - CSIRO and ANU, Australia, ‡University of Canberra, Australia,"
+e9ac109c395ededb23dfc78fe85d76eeb772ee7e,A Multilevel Mixture-of-Experts Framework for Pedestrian Classification,"A Multilevel Mixture-of-Experts Framework for +Pedestrian Classification +Markus Enzweiler and Dariu M. Gavrila"
e9ed17fd8bf1f3d343198e206a4a7e0561ad7e66,Cognitive Learning for Social Robot through Facial Expression from Video Input,"International Journal of Enhanced Research in Science Technology & Engineering, ISSN: 2319-7463 Vol. 3 Issue 1, January-2014, pp: (362-365), Impact Factor: 1.252, Available online at: www.erpublications.com Cognitive Learning for Social Robot through @@ -14052,6 +48947,72 @@ e9d43231a403b4409633594fa6ccc518f035a135,Deformable Part Models with CNN Feature Pierre-Andr´e Savalle1, Stavros Tsogkas1,2, George Papandreou3, Iasonas Kokkinos1,2 Ecole Centrale Paris,2 INRIA, 3TTI-Chicago (cid:63)"
+e96a3d4df7f6956ba185107747c3d7c16d1ed845,Unite the People: Closing the Loop Between 3D and 2D Human Representations,"Unite the People: Closing the Loop Between 3D and 2D Human Representations +Christoph Lassner1,2 +Javier Romero3,* +Martin Kiefel2 +Federica Bogo4,* +Michael J. Black2 +Peter V. Gehler5,* +Bernstein Center for Computational Neuroscience, T¨ubingen, Germany +MPI for Intelligent Systems, T¨ubingen, Germany +Body Labs Inc., New York, United States +Microsoft, Cambridge, UK +5University of W¨urzburg, Germany"
+e941ee2d584938e6509c0676466023f8b43b9486,Appearance based tracking with background subtraction,"The 8th International +Computer Science +April 26-28, 2013. Colombo, +Sri Lanka +& Education (ICCSE 2013) +Conference on +SuD1.4 +Appearance Based Tracking with Background +Dileepa Joseph Jayamanne +Subtraction +Jayathu Samarawickrama +Ranga Rodrigo +Electronic +Engineering +Telecommunication +Electronic +Engineering +Telecommunication +Telecommunication +Electronic"
+e91c7dbd33a3047c70d550e201ebdf4353cbe929,Re-identification for Online Person Tracking by Modeling Space-Time Continuum,"Re-identification for Online Person Tracking by Modeling Space-Time +Continuum +Neeti Narayan, Nishant Sankaran, Srirangaraj Setlur and Venu Govindaraju +University at Buffalo, SUNY +{neetinar, n6, setlur,"
+e9dc096762f503cfe0d56066c02d27082665b3cf,Face Sketch to Photo Matching Using LFDA,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Face Sketch to Photo Matching Using LFDA +Pushpa Gopal Ambhore1, Lokesh Bijole2 +Research Scholor of Amravati University, +Computer Engineering Department Padm. Dr. V. B. Kolte Coe Malkapur Maharashtra, India +Assistant Professor, Computer Engineering Department Padm. Dr.V.B. Kolte coe Malkapur Maharashtra, India"
+e917bb1f7efdfc448b8b63c52e8f643e68630a11,3D information is valuable for the detection of humans in video streams,"D information is valuable for the detection of humans +in video streams +Sébastien Piérard +Antoine Lejeune +Marc Van Droogenbroeck +INTELSIG Laboratory +Montefiore Institute +University of Liège, Belgium +INTELSIG Laboratory +Montefiore Institute +University of Liège, Belgium +INTELSIG Laboratory +Montefiore Institute +University of Liège, Belgium +Email : +Email : +Email :"
+e9ae8bbfec913300eedede3ec48acb56c15ebdea,DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild,"DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild +Skand Vishwanath Peri +Abhinav Dhall +Learning Affect and Semantic Image AnalysIs (LASII) Group, +Indian Institute of Technology Ropar, India"
e9fcd15bcb0f65565138dda292e0c71ef25ea8bb,Analysing Facial Regions for Face Recognition Using Forensic Protocols,"Repositorio Institucional de la Universidad Autónoma de Madrid https://repositorio.uam.es Esta es la versión de autor de la comunicación de congreso publicada en: @@ -14063,6 +49024,22 @@ DOI: http://dx.doi.org/10.1007/978-3-642-38061-7_22 Copyright: © 2013 Springer-Verlag El acceso a la versión del editor puede requerir la suscripción del recurso Access to the published version may require subscription"
+e939fb6b762de242b22e295940e0d9d7d259e442,Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos,"Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised +Learning from Monocular Videos +Vincent Casser∗1 +Soeren Pirk +Reza Mahjourian2 +Anelia Angelova +Institute for Applied Computational Science, Harvard University; Google Brain +Google Brain +University of Texas at Austin; Google Brain +{pirk, rezama,"
+e94804b7f2515740671a678239eccdb79a050272,Generating a Fusion Image: One's Identity and Another's Shape,"Generating a Fusion Image: One’s Identity and Another’s Shape +Donggyu Joo∗ +School of Electrical Engineering, KAIST, South Korea +Doyeon Kim∗ +{jdg105, doyeon kim, +Junmo Kim"
e9363f4368b04aeaa6d6617db0a574844fc59338,BenchIP: Benchmarking Intelligence Processors,"BENCHIP: Benchmarking Intelligence Processors Jinhua Tao1, Zidong Du1,2, Qi Guo1,2, Huiying Lan1, Lei Zhang1 @@ -14070,6 +49047,41 @@ Shengyuan Zhou1, Lingjie Xu3, Cong Liu4, Haifeng Liu5, Shan Tang6 Allen Rush7,Willian Chen7, Shaoli Liu1,2, Yunji Chen1, Tianshi Chen1,2 ICT CAS,2Cambricon,3Alibaba Infrastructure Service, Alibaba Group IFLYTEK,5JD,6RDA Microelectronics,7AMD"
+f17d6db4844f26a023f92b8771a1c33cea91b9e4,1 Million Captioned Dutch Newspaper Images,"Million Captioned Dutch Newspaper Images +Desmond Elliott∗† and Martijn Kleppe‡ +ILLC, University of Amsterdam; †CWI; ‡Erasmus University Rotterdam"
+f13552e2e2843716e7a1c7c2492cfcc6e86aa03c,Reinforced Pipeline Optimization: Behaving Optimally,"Under review as a conference paper at ICLR 2019 +REINFORCED PIPELINE OPTIMIZATION: BEHAVING +OPTIMALLY WITH NON-DIFFERENTIABILITIES +Anonymous authors +Paper under double-blind review"
+f1ec3752535e0aa6aafe3930974a22250e652ca1,Gender and emotion recognition with implicit user signals,"Gender and Emotion Recognition with Implicit User Signals +Maneesh Bilalpur +International Institute of Information +Technology +Hyderabad, India +Seyed Mostafa Kia +Donders Institute, Radboud +University +Nijmegen, Netherlands +Manisha Chawla +Centre for Cognitive Science, Indian +Institute of Technology +Gandhinagar, India +Tat-Seng Chua +School of Computing, National +University of Singapore +Singapore +Ramanathan Subramanian +University of Glasgow & Advanced +Digital Sciences Center"
+f18c34458460b9b62b51213b9165b37c057c5837,Unsupervised Object Discovery and Co-Localization by Deep Descriptor Transforming,"Noname manuscript No. +(will be inserted by the editor) +Unsupervised Object Discovery and Co-Localization +y Deep Descriptor Transforming +Xiu-Shen Wei · Chen-Lin Zhang · Jianxin Wu · Chunhua Shen · +Zhi-Hua Zhou +Received: date / Accepted: date"
f16a605abb5857c39a10709bd9f9d14cdaa7918f,Fast greyscale road sign model matching and recognition,"Fast greyscale road sign model matching nd recognition Sergio Escalera and Petia Radeva @@ -14087,6 +49099,11 @@ Ayush Tewari1 Figure 1. Our single-shot deep inverse face renderer InverseFaceNet obtains a high-quality geometry, reflectance and illumination estimate from just a single input image. We jointly recover the face pose, shape, expression, reflectance and incident scene illumination. From left to right: input photo, our estimated face model, its geometry, and the pointwise Euclidean error compared to Garrido et al. [14]."
+f1a05136c8b8f9334a4b3d9de2a4b192d2c762c2,Scene Classification via Hypergraph-Based Semantic Attributes Subnetworks Identification,"Scene Classification via Hypergraph-Based +Semantic Attributes Subnetworks Identification +Sun-Wook Choi, Chong Ho Lee, and In Kyu Park +Department of Information and Communication Engineering +Inha University, Incheon 402-751, Korea"
f1ba2fe3491c715ded9677862fea966b32ca81f0,Face Tracking and Recognition in Videos : HMM Vs KNN,"ISSN: 2321-7782 (Online) Volume 1, Issue 7, December 2013 International Journal of Advance Research in @@ -14100,6 +49117,27 @@ Assistant Professor Department of Computer Engineering MIT College of Engineering (Pune University) Pune - India"
+f1471a408369689e2fc956b417dce24e47557a38,A Novel Face Template Protection Algorithm Based on the Fusion of Chaos Theory and RSA Encryption,"International Journal of Security and Its Applications +Vol. 10, No. 6 (2016) pp.315-330 +http://dx.doi.org/10.14257/ijsia.2016.10.6.30 +A Novel Face Template Protection Algorithm Based on the Fusion +of Chaos Theory and RSA Encryption +Liu Yunan1, Zhao Fudong2, Xu Yanli3 and Cao Yu2* +.School of Foreign Languages, Harbin University of Science and Technology, +Harbin, 150080, China +.School of Automation, Harbin University of Science and Technology, Harbin, +50080, China +.School of Foreign Languages, Northeast Forestry University, Harbin, 150040, +China"
+f1c2ba8c7797c4844fa61068b3ce9d319e6ced3f,Human Head Tracking Based on Inheritance and Evolution Concept,"MVA2009 IAPR Conference on Machine Vision Applications, May 20-22, 2009, Yokohama, JAPAN +Human Head Tracking Based on Inheritance and Evolution Concept +Yi Hu, Tetsuya Takamori +Fujifilm Corporation, Japan +798, Miyanodai, Kaisei-machi, Ashigarakami-gun, Kanagawa, 258-8538 JAPAN +{yi_hu,"
+f19527b2ceabf50831e78ac04161107c936efb2b,Discriminative Sparse Neighbor Approximation for Imbalanced Learning,"Discriminative Sparse Neighbor Approximation +for Imbalanced Learning +Chen Huang, Chen Change Loy, Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
f1d090fcea63d9f9e835c49352a3cd576ec899c1,Single-hidden Layer Feedforward Neual network training using class geometric information,"Iosifidis, A., Tefas, A., & Pitas, I. (2015). Single-Hidden Layer Feedforward Neual Network Training Using Class Geometric Information. In . J. J. Merelo, A. Rosa, J. M. Cadenas, A. Dourado, K. Madani, & J. Filipe (Eds.), @@ -14117,6 +49155,13 @@ General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms.html"
+f157daaffa1754aae5963d9c49247142b07c8d4a,Dct-based Reduced Face for Face Recognition,"International Journal of Information Technology and Knowledge Management +January-June 2012, Volume 5, No. 1, pp. 97-100 +DCT-BASED REDUCED FACE FOR FACE RECOGNITION +Vikas Maheshkar1, Sushila Kamble2, Suneeta Agarwal3, and Vinay Kumar Srivastava4"
+f174b24860b4cacbe047d3a5650cf8866d2244d9,Monocular Depth Estimation by Learning from Heterogeneous Datasets,"Monocular Depth Estimation by Learning from Heterogeneous +Datasets +Akhil Gurram1,2, Onay Urfalioglu2, Ibrahim Halfaoui2, Fahd Bouzaraa2 and Antonio M. L´opez1"
f113aed343bcac1021dc3e57ba6cc0647a8f5ce1,A Survey on Mining of Weakly Labeled Web Facial Images and Annotation,"International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 @@ -14126,6 +49171,12 @@ Tarang Boharupi1, Pranjali Joshi2 Pune Institute of Computer Technology, Pune, India Professor, Pune Institute of Computer Technology, Pune, India the proposed system which"
+f1052df3e311b7caa563685e741e0a1bb6b288df,A Hierarchical Fusion Strategy based Multimodal Biometric System,"The International Arab Conference on Information Technology (ACIT’2013) +A Hierarchical Fusion Strategy based Multimodal +Biometric System +Youssef Elmir, 2Zakaria Elberrichi and 2Réda Adjoudj +Faculty of Sciences and Technology, University of Adrar, Algeria +Faculty of Technology, Djillali Liabès University of Sidi Bel Abbès, Algeria"
f19777e37321f79e34462fc4c416bd56772031bf,Literature Review of Image Compression Algorithm,"International Journal of Scientific & Engineering Research, Volume 3, Issue 6, June-2012 1 ISSN 2229-5518 Literature Review of Image Compression Algorithm @@ -14133,6 +49184,28 @@ Dr. B. Chandrasekhar Padmaja.V.K email: email:: Jawaharlal Technological University, Anantapur"
+f16921c1c6e8bce89bce7679cbd824d65b494e4d,The face of love: spontaneous accommodation as social emotion regulation.,"Personality and Social Psychology +Bulletin +http://psp.sagepub.com/ +The Face of Love : Spontaneous Accommodation as Social Emotion Regulation +Pers Soc Psychol Bull +Michael Häfner and Hans IJzerman +2011 37: 1551 originally published online 21 July 2011 +DOI: 10.1177/0146167211415629 +The online version of this article can be found at: +http://psp.sagepub.com/content/37/12/1551 +Published by: +http://www.sagepublications.com +On behalf of: +Society for Personality and Social Psychology +Additional services and information for +Personality and Social Psychology Bulletin +can be found at: +Email Alerts: +http://psp.sagepub.com/cgi/alerts +Subscriptions:"
+f11d070cdc9ee12b201757ca4a50a3682967ba0c,Spatial Language Understanding with Multimodal Graphs using Declarative Learning based Programming,"Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing, pages 33–43 +Copenhagen, Denmark, September 7–11, 2017. c(cid:13)2017 Association for Computational Linguistics"
f19ab817dd1ef64ee94e94689b0daae0f686e849,Blickrichtungsunabhängige Erkennung von Personen in Bild- und Tiefendaten,"TECHNISCHE UNIVERSIT¨AT M ¨UNCHEN Lehrstuhl f¨ur Mensch-Maschine-Kommunikation Blickrichtungsunabh¨angige Erkennung von @@ -14151,7 +49224,66 @@ Technische Universit¨at Ilmenau Die Dissertation wurde am 16.06.2009 bei der Technischen Universit¨at M¨unchen einge- reicht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik am 30.10.2009 ngenommen."
+f196a79c5e4b570013e4aa031cdd0fc0c98fc07d,Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions,"Interactively Picking Real-World Objects with +Unconstrained Spoken Language Instructions +Jun Hatori∗, Yuta Kikuchi∗, Sosuke Kobayashi∗, Kuniyuki Takahashi∗, +Yuta Tsuboi∗, Yuya Unno∗, Wilson Ko, Jethro Tan†"
+f1c76d97caa6f882764c1382c622a2dfb6aade43,CoreRank: Redeeming “Sick Silicon” by Dynamically Quantifying Core-Level Healthy Condition,"CoreRank: Redeeming “Sick Silicon” +y Dynamically Quantifying Core-Level +Healthy Condition +Guihai Yan, Member, IEEE, Faqiang Sun, Huawei Li, Senior Member, IEEE, and +Xiaowei Li, Senior Member, IEEE"
+f1bb2c95dc270ffa9c2f88e29ae5d2178b4459cb,A Generative Model of People in Clothing,"A Generative Model of People in Clothing +Christoph Lassner1, 2 +Gerard Pons-Moll2 +Peter V. Gehler3,* +BCCN, Tübingen +MPI for Intelligent Systems, Tübingen 3University of Würzburg +Figure 1: Random examples of people generated with our model. For each row, sampling is conditioned on the silhouette +displayed on the left. Our proposed framework also supports unconditioned sampling as well as conditioning on local +ppearance cues, such as color."
+f131a654bbf4c8de0679d3c6054c10bba4a919d4,Vision-based Driver Assistance Systems,"Vision-based Driver Assistance Systems +.enpeda.. (Environment Perception and Driver Assistance) Project +CITR, Auckland, New Zealand +Reinhard Klette +5 February 2015"
+e79847c3bf3ffefe9304e212d8dda7aaa29eaada,From Deterministic to Generative: Multi-Modal Stochastic RNNs for Video Captioning,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +From Deterministic to Generative: Multi-Modal +Stochastic RNNs for Video Captioning +Jingkuan Song, Yuyu Guo, Lianli Gao, Xuelong Li, IEEE Fellow Alan Hanjalic, IEEE Fellow Heng Tao Shen"
+e7906370eae8655fb69844ae1a3d986c9f37c902,Face recognition using Deep Learning,"POLYTECHNIC UNIVERSITY OF CATALONIA +MASTER THESIS +Face recognition using Deep +Learning +Author: +Xavier SERRA +Advisor: +Javier CASTÁN +Tutor: +Sergio ESCALERA +This master thesis has been developed at GoldenSpear LLC +January 2017"
e76798bddd0f12ae03de26b7c7743c008d505215,Joint Max Margin and Semantic Features for Continuous Event Detection in Complex Scenes,
+e75cd1379b07d77358e5a2f4a042f624066603b6,Weakly-Supervised Learning of Visual Relations,"Weakly-supervised learning of visual relations +Julia Peyre1,2 +Ivan Laptev1,2 +Cordelia Schmid2,4 +Josef Sivic1,2,3"
+e778e618862ea1c9a97e89e942228c4de98c9a86,Automated Pruning for Deep Neural Network Compression,"Automated Pruning for Deep Neural Network Compression +Franco Manessi1†, Alessandro Rozza1†, Simone Bianco2, Paolo Napoletano2, Raimondo Schettini2 +lastminute.com group — Strategic Analytics +{first name.last +Universit`a degli Studi di Milano Bicocca — DISCo {first name.last"
+e74bddccc40e65b31081a1599cbe7385d5d3e1c0,Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering,"Bottom-Up and Top-Down Attention for Image Captioning +nd Visual Question Answering +Peter Anderson1∗ +Xiaodong He2 +Chris Buehler3 +Damien Teney4 +Mark Johnson5 +Stephen Gould1 +Lei Zhang3 +Australian National University 2JD AI Research 3Microsoft Research 4University of Adelaide 5Macquarie University"
e7cac91da51b78eb4a28e194d3f599f95742e2a2,"Positive Feeling, Negative Meaning: Visualizing the Mental Representations of In-Group and Out-Group Smiles","RESEARCH ARTICLE Positive Feeling, Negative Meaning: Visualizing the Mental Representations of In- @@ -14160,6 +49292,31 @@ Andrea Paulus1☯*, Michaela Rohr1☯, Ron Dotsch2,3, Dirk Wentura1 Saarland University, Saarbrücken, Germany, 2 Utrecht University, Utrecht, the Netherlands, Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands ☯ These authors contributed equally to this work."
+e7dc0d5545e6e028b03a82d2f5bb3bccc995a0d7,A New Fast and Efficient HMM-Based Face Recognition System Using a 7-State HMM Along With SVD Coefficients,"Archive of SID +A New Fast and Efficient HMM-Based Face Recognition +System Using a 7-State HMM Along With SVD Coefficients +H. Miar-Naimi* and P. Davari*"
+e7f00f6e5994c5177ec114ee353cc7064d40a78f,Back to Basic: Do Children with Autism Spontaneously Look at Screen Displaying a Face or an Object?,"Hindawi Publishing Corporation +Autism Research and Treatment +Volume 2013, Article ID 835247, 7 pages +http://dx.doi.org/10.1155/2013/835247 +Research Article +Back to Basic: Do Children with Autism Spontaneously Look at +Screen Displaying a Face or an Object? +Marie Guimard-Brunault,1,2,3,4 Nadia Hernandez,3 Laetitia Roché,3 Sylvie Roux,3 +Catherine Barthélémy,1,2,3 Joëlle Martineau,2,3 and Frédérique Bonnet-Brilhault1,2,3 +CHRU de Tours, Centre Universitaire de P´edopsychiatrie, 2 Boulevard Tonnell´e, 37044 Tours Cedex 9, France +Universit´e Franc¸ois Rabelais de Tours, 60 rue du Plat D’Etain, 37020 Tours Cedex 1, France +UMR Inserm U 930, ´Equipe 1: Imagerie et Cerveau, Universit´e Franc¸ois Rabelais de Tours, Tours, France +UMR Inserm U 930, ´Equipe 1: Imagerie et Cerveau, CHRU de Tours-Hˆopital Bretonneau, 2 boulevard Tonnell´e, +Bˆat B1A, 1er Etage, 37044 Tours Cedex 9, France +Correspondence should be addressed to Marie Guimard-Brunault; +Received 29 June 2013; Revised 29 September 2013; Accepted 21 October 2013 +Academic Editor: Elizabeth Aylward +Copyright © 2013 Marie Guimard-Brunault et al. This is an open access article distributed under the Creative Commons +Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is +properly cited."
+e72e852dca333d66559dbcfb050140fac5affe4f,Anatomical Landmark Tracking by One-shot Learned Priors for Augmented Active Appearance Models,"DataωLDAFull AAMAUGMENTED AAMSubset AAMLocal TrackingextractionlearnmodelOne-shotDetectortraintrainLower LegContraintsEipolar ConstraintsDistance ConstraintsTorso ConstraintsFigure1:BasedonfewannotatedbiplanarrecordedtrainingimagesanAugmentedAAM(HaaseandDenzler,2013)istrained,consistingofanatomicalknowledge,afullmulti-viewAAMmodel,anAAMmodelofthetorsoland-marksubset,epipolarconstraintsandalocaltracking-by-detectionpriorintroducedinthispaper.In(HaaseandDenzler,2013)ActiveAppearanceModels(AAM)(Cootesetal.,2001)havebeenap-pliedtoseveralbipedalbirdlocomotiondatasets.OnecrucialconclusionofthisworkisthatAAMsneedsubstantialconstraintsfromvarioussources.Withthesupportofadditionalanatomicalknowledge,i.e.re-gionsegmentation,multi-viewacquisition,andlocallandmarktracking,fortheanimalslowerlimbsys-tem,theresultingAugmentedAAM(HaaseandDen-zler,2013)providesrobustresultsforthemajorityoftheprocesseddatasets.However,theappliedonlinetrackingapproach(Amthoretal.,2012)suffersfrom246MothesO.andDenzlerJ.AnatomicalLandmarkTrackingbyOne-shotLearnedPriorsforAugmentedActiveAppearanceModels.DOI:10.5220/0006133302460254InProceedingsofthe12thInternationalJointConferenceonComputerVision,ImagingandComputerGraphicsTheoryandApplications(VISIGRAPP2017),pages246-254ISBN:978-989-758-227-1Copyrightc(cid:13)2017bySCITEPRESS–ScienceandTechnologyPublications,Lda.Allrightsreserved"
e78394213ae07b682ce40dc600352f674aa4cb05,Expression-invariant three-dimensional face recognition,"Expression-invariant three-dimensional face recognition Alexander M. Bronstein Email: @@ -14180,8 +49337,102 @@ near-isometric model assumption, the difficult problem of face recognition expressions can be solved in a relatively simple way. 0.1 Introduction It is well-known that some characteristics or behavior patterns of the human body are strictly"
+e79a34f9942172ad97c5fadca3701db3e29d32e2,Fusiform Correlates of Facial Memory in Autism,"NIH Public Access +Author Manuscript +Behav Sci (Basel). Author manuscript; available in PMC 2014 April 21. +Published in final edited form as: +Behav Sci (Basel). ; 3(3): 348–371. doi:10.3390/bs3030348. +Fusiform Correlates of Facial Memory in Autism +Haley G. Trontel1, Tyler C. Duffield2, Erin D. Bigler2,3,4,*, Alyson Froehlich5, Molly B.D. +Prigge5, Jared A. Nielsen5, Jason R. Cooperrider5, Annahir N. Cariello5, Brittany G. +Travers6, Jeffrey S. Anderson7, Brandon A. Zielinski8, Andrew Alexander6,11, Nicholas +Lange9,10, and Janet E. Lainhart11,12 +Department of Psychology, University of Montana, Missoula, MT 59812, USA; +Department of Psychology, Brigham Young University, Provo, UT 84604, +USA; (T.C.D.); (E.D.B.) 3Neuroscience Center, +Brigham Young University, Provo, UT 84604, USA 4The Brain Institute of Utah, University of +Utah, Salt Lake City, UT 84112, USA 5Department of Psychiatry, University of Utah, Salt Lake +City, UT 84112, USA; (A.F.); +(M.B.D.P); (J.A.N.); (J.R.C.); +(A.N.C.) 6Department of Medical Physics, University of Wisconsin, +Madison, WI 53706, USA; (B.G.T.); (A.A.) +7Department of Radiology, University of Utah, Salt Lake City, UT 84112, USA;"
+e7f4951c1106bff0460665ef67d11fb9c2d07c41,Machine Vision-Based Analysis of Gaze and Visual Context: an Application to Visual Behavior of Children with Autism Spectrum Disorders,"Machine Vision-Based Analysis of Gaze and +Visual Context: an Application to Visual +Behavior of Children with Autism Spectrum +Disorders +Basilio Noris +MSc/BSc in Computer Science, Université de Lausanne, 2005 +Dissertation +Submitted to the School of Engineering +in partial fulfillment of the requirements for the degree of +Doctor of Philosophy +Ecole Polytechnique Fédérale de Lausanne (EPFL) +t the +(Swiss Federal Insitute of Technology Lausanne) +Supervisor: +Prof. Aude Billard +Examiners: +Prof. Thierry Pun +Prof. Jacqueline Nadel +Prof. Nouchine Hadjikhani +President of the jury:"
+e719e1ed86bf2214512d5631e31716effe2e23d2,Learning to Estimate 3D Human Pose and Shape from a Single Color Image,"Learning to Estimate 3D Human Pose and Shape from a Single Color Image +Georgios Pavlakos1, Luyang Zhu2, Xiaowei Zhou3, Kostas Daniilidis1 +University of Pennsylvania 2 Peking University 3 Zhejiang University"
e7b6887cd06d0c1aa4902335f7893d7640aef823,Modelling of Facial Aging and Kinship: A Survey,"Modelling of Facial Aging and Kinship: A Survey Markos Georgopoulos, Yannis Panagakis, and Maja Pantic,"
+e746447afc4898713a0bcf2bb560286eb4d20019,Leveraging Virtual and Real Person for Unsupervised Person Re-identification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, NOVEMBER 2018 +Leveraging Virtual and Real Person for +Unsupervised Person Re-identification +Fengxiang Yang, Zhun Zhong, Zhiming Luo, Sheng Lian, and Shaozi Li"
+e72c5fb54c3d14404ebd1bf993e51d0056f6c429,Tempered Adversarial Networks,
+e72d35ae7c1f477ce4341a5fb3a15bcfe0481a0e,Behavioral Consistency Extraction for Face Verification,"Behavioral Consistency Extraction for Face +Verification +Hui Fang and Nicholas Costen +Manchester Metropolitan University +Department of Computing and Mathematics, +Manchester, U.K."
+e7721f40fed05aae4d49d84e9ebc94ced7015aac,Design and Implementation of Resampling Techniques for Face Recognition using Classical LDA Algorithm in MATLAB,"International Journal of Computer Applications (0975 – 8887) +Volume 152 – No.6, October 2016 +Design and Implementation of Resampling Techniques +for Face Recognition using Classical LDA Algorithm in +MATLAB +S. R Bichwe +Dept. of Electronics & +Communication +Kavikulguru Institute of +Technology & Science, +Ramtek, Maharashtra +Sugandha Satija +Dept. of Information +Technology +Kavikulguru Institute of +Technology & Science, +Ramtek, Maharashtra +Madhavi R. Bichwe +Dept of Computer Science & +Technology"
+cb4fc4d49783f2049c48a062169f04eb744443ec,Paying More Attention to Saliency: Image Captioning with Saliency and Context Attention,"Paying More Attention to Saliency: Image Captioning with +Saliency and Context Attention +MARCELLA CORNIA, University of Modena and Reggio Emilia +LORENZO BARALDI, University of Modena and Reggio Emilia +GIUSEPPE SERRA, University of Udine +RITA CUCCHIARA, University of Modena and Reggio Emilia +Image captioning has been recently gaining a lot of attention thanks to the impressive achievements shown by +deep captioning architectures, which combine Convolutional Neural Networks to extract image representations, +nd Recurrent Neural Networks to generate the corresponding captions. At the same time, a significant research +effort has been dedicated to the development of saliency prediction models, which can predict human eye +fixations. Even though saliency information could be useful to condition an image captioning architecture, by +providing an indication of what is salient and what is not, research is still struggling to incorporate these two +techniques. In this work, we propose an image captioning approach in which a generative recurrent neural +network can focus on different parts of the input image during the generation of the caption, by exploiting +the conditioning given by a saliency prediction model on which parts of the image are salient and which are +ontextual. We show, through extensive quantitative and qualitative experiments on large scale datasets, that +our model achieves superior performances with respect to captioning baselines with and without saliency, +nd to different state of the art approaches combining saliency and captioning. +CCS Concepts: • Computing methodologies → Scene understanding; Natural language generation; +Additional Key Words and Phrases: saliency, visual saliency prediction, image captioning, deep learning."
cbca355c5467f501d37b919d8b2a17dcb39d3ef9,Super-resolution of Very Low Resolution Faces from Videos,"CANSIZOGLU, JONES: SUPER-RESOLUTION OF VERY LR FACES FROM VIDEOS Super-resolution of Very Low-Resolution Faces from Videos @@ -14190,6 +49441,73 @@ Michael Jones Mitsubishi Electric Research Labs (MERL) Cambridge, MA, USA"
+cb3d38cd18c99aca9c2a228aeb4998f394c7b1b3,Impairments in facial affect recognition associated with autism spectrum disorders: a meta-analysis.,"# Cambridge University Press 2014 +doi:10.1017/S0954579414000479 +Impairments in facial affect recognition associated with autism +spectrum disorders: A meta-analysis +LEAH M. LOZIER, JOHN W. VANMETER, AND ABIGAIL A. MARSH +Georgetown University"
+cba90ec61155a233fee33b529401e65d9481213a,Houdini: Fooling Deep Structured Prediction Models,"Houdini: Fooling Deep Structured Prediction Models +Moustapha Cisse +Facebook AI Research +Natalia Neverova* +Facebook AI Research"
+cb4418b5bddaaceb92caea9e72c8cc528ce4e3cc,Generative Semantic Manipulation with Contrasting GAN,"Generative Semantic Manipulation with Contrasting +Xiaodan Liang, Hao Zhang, Eric P. Xing +Carnegie Mellon University and Petuum Inc. +{xiaodan1, hao,"
+cb658e9e0823dc7afe66b593307b230cc2747790,Nouveau modèle pour la datation automatique de photographies à partir de caractéristiques visuelles,"Nouveau modèle pour la datation +utomatique de photographies +à partir de caractéristiques visuelles1 +Paul MARTIN* — Antoine DOUCET** — Frédéric JURIE* +* Laboratoire GREYC [UMR 6072], Université de Caen Normandie, FRANCE 14032 +{paul.martin ; +** Laboratoire L3i, Université de La Rochelle, FRANCE 17042 +RÉSUMÉ. Nous présentons, dans cet article, une méthode de datation de photographies par +l’usage du contenu visuel de celles-ci. Nous nous sommes inspirés de travaux récents de la +vision par ordinateur. Nous avons amélioré la méthode de classification utilisée dans ces tra- +vaux en dépassant une limite intrinsèque de leur approche. En effet, ils considèrent la datation +d’images comme un problème de classification multi-classes, pour lequel une classe repré- +sente un ensemble d’années, mais ignorant l’ordre relatif sous-jacent à l’information tempo- +relle. Dans leur approche soit une prédiction est bonne (période valide) soit elle est mauvaise +(période invalide) mais aucune différence n’est faite entre se tromper d’une décennie ou de +plusieurs. Nos travaux, s’appuient sur des avancées récentes en classification ordinale. Nous +onsidérons les dates comme des attributs à la fois ordonnés et relatifs et nous proposons un +adre spécifique pour les manipuler."
+cb1214e42fa81977bc21f4b3c8e194a9b68278f5,Visually Aligned Word Embeddings for Improving Zero-shot Learning,"Qiao et al.: Visually Aligned Word Embeddings. Appearing in Proc. British Mach. Vis. Conf. 2017 +Visually Aligned Word Embeddings for Improving +Zero-shot Learning +School of Computer Science, University of +Adelaide, Australia +Ruizhi Qiao +Lingqiao Liu +Chunhua Shen +Anton van den Hengel"
+cb310356d1c5f567b2a8796b708f6e1e10fa1917,Serotonin and the neural processing of facial emotions in adults with autism: an fMRI study using acute tryptophan depletion.,"ORIGINAL ARTICLE +Serotonin and the Neural Processing +of Facial Emotions in Adults With Autism +An fMRI Study Using Acute Tryptophan Depletion +Eileen M. Daly, BA; Quinton Deeley, PhD; Christine Ecker, MSc, PhD; Michael Craig, PhD; Brian Hallahan, MRCPsych; +Clodagh Murphy, MRCPsych; Patrick Johnston, PhD; Debbie Spain, MSc; Nicola Gillan, MSc; Michael Brammer, PhD; +Vincent Giampietro, PhD; Melissa Lamar, PhD; Lisa Page, MRCPsych; Fiona Toal, MRCPsych; Anthony Cleare, PhD; +Simon Surguladze, MD, PhD; Declan G. M. Murphy, FRCPsych +Context: People with autism spectrum disorders (ASDs) +have lifelong deficits in social behavior and differences +in behavioral as well as neural responses to facial expres- +sions of emotion. The biological basis to this is incom- +pletely understood, but it may include differences in the +role of neurotransmitters such as serotonin, which modu- +late facial emotion processing in health. While some in- +dividuals with ASD have significant differences in the sero- +tonin system, to our knowledge, no one has investigated +its role during facial emotion processing in adults with +ASD and control subjects using acute tryptophan deple- +tion (ATD) and functional magnetic resonance imaging."
+cb8b2db657cd6b6ccac13b56e2ca62b7d88eda68,Log Hyperbolic Cosine Loss Improves Varia-,"Under review as a conference paper at ICLR 2019 +LOG HYPERBOLIC COSINE LOSS IMPROVES VARIA- +TIONAL AUTO-ENCODER +Anonymous authors +Paper under double-blind review"
cbcf5da9f09b12f53d656446fd43bc6df4b2fa48,Face Recognition using Gray level Co-occurrence Matrix and Snap Shot Method of the Eigen Face,"ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) @@ -14203,13 +49521,106 @@ cb004e9706f12d1de83b88c209ac948b137caae0,Face Aging Effect Simulation Using Hidd Analysis Joint Sparse Representation Hongyu Yang, Student Member, IEEE, Di Huang, Member, IEEE, Yunhong Wang, Member, IEEE, Heng Wang, nd Yuanyan Tang, Fellow, IEEE"
+cb11a150fc245958799e763069a6ae3080814d40,3d Face Recognition from Range Image,
+cb3ba84146d1324e1cdbde3764ca3b354ee09a2a,"On the Interplay Between Throughput, Fairness and Energy Efficiency on Asymmetric Multicore Processors","On the interplay between throughput, +fairness and energy efficiency on +symmetric multicore processors +J. C. Saez1, A. Pousa2, A. E. de Giusti2, M. Prieto-Matias1 +ArTeCS Group, Facultad de Inform´atica, Complutense University of Madrid +III-LIDI, Facultad de Inform´atica, National University of La Plata +Email: +Asymmetric single-ISA multicore processors (AMPs), which integrate high- +performance big cores and low-power small cores, were shown to deliver +higher performance per watt than symmetric multicores. Previous work has +highlighted that this potential of AMP systems can be realizable by scheduling +the various applications in a workload on the most appropriate core type. A +number of scheduling schemes have been proposed to accomplish different goals, +such as system throughput optimization, enforcing fairness or reducing energy +onsumption. While the interrelationship between throughput and fairness on +AMPs has been comprehensively studied, the impact that optimizing energy +efficiency has on the other two aspects is still unclear. To fill this gap, we carry out +comprehensive analytical and experimental study that illustrates the interplay +etween throughput, fairness and energy efficiency on AMPs. Our analytical +study allowed us to define the energy-efficiency factor (EEF) metric, which aids"
+cb7bbede1c2eae831dd73440f439955c4310837f,Cross-Cultural and Cultural-Specific Production and Perception of Facial Expressions of Emotion in the Wild,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Cross-Cultural and Cultural-Specific Production +nd Perception of Facial Expressions of Emotion +in the Wild +Ramprakash Srinivasan, Aleix M. Martinez"
+cbd20c2199062724eee841016f1575cb7d5309b4,Dropout training for SVMs with data augmentation,"JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, MAY 2015 +Dropout Training for SVMs with +Data Augmentation +Ning Chen and Jun Zhu, Member, IEEE, Jianfei Chen and Ting Chen"
+cb2e10d1a6792354bc0ce24ee99ecf2142d16f9b,Enhancing Real-Time Human Detection Based on Histograms of Oriented Gradients,"Enhancing Real-time Human Detection based +on Histograms of Oriented Gradients +Marco Pedersoli1, Jordi Gonz`alez2, Bhaskar Chakraborty1, and Juan J. +Villanueva1 +Computer Vision Center and Departament d’Inform`atica. Universitat Aut`onoma +de Barcelona, 08193 Bellaterra, Spain +Institut de Rob`otica i Inform`atica Industrial(UPC-CSIC), Edifici U Parc +Tecnol`ogic de Barcelona. 08028, Spain. +Summary. In this paper we propose a human detection framework based on an +enhanced version of Histogram of Oriented Gradients (HOG) features. These feature +descriptors are computed with the help of a precalculated histogram of square-blocks. +This novel method outperforms the integral of oriented histograms allowing the +alculation of a single feature four times faster. Using Adaboost for HOG feature +selection and Support Vector Machine as weak classifier, we build up a real-time +human classifier with an excellent detection rate. +Introduction +Human detection is the task of finding presence and position of human beings +in images. Many applications take advantage of it, mainly in the videosurvel- +liance and human-computer iteration domains. Thus, human detection is the +first step of the full process of Human Sequence Evaluation [5]."
+cbdca5e0f1fd3fd745430497d372a2a30b7bb0c5,Towards Distributed Coevolutionary GANs,"Towards Distributed Coevolutionary GANs +Abdullah Al-Dujaili, Tom Schmiedlechner, Erik Hemberg and Una-May O’Reilly +CSAIL, MIT, USA"
+cb30c1370885033bc833bc7ef90a25ee0900c461,FaceOff: Anonymizing Videos in the Operating Rooms,"FaceOff: Anonymizing Videos in the Operating +Rooms +Evangello Flouty1, Odysseas Zisimopoulos1, and Danail Stoyanov1,2 +Wellcome / ESPRC Centre for Interventional and Surgical Sciences, London, +Digital Surgery, London, United Kingdom +United Kingdom"
+cb6be69c67b0b15ebbda89a126f4dd62a4d32958,Igure Qa : a N a Nnotated F Igure D Ataset for V Isual R Easoning,"Workshop track - ICLR 2018 +FIGUREQA: AN ANNOTATED FIGURE DATASET FOR +VISUAL REASONING +Samira Ebrahimi Kahou1∗, Vincent Michalski2∗†, Adam Atkinson1, +Ákos Kádár3†, Adam Trischler1, Yoshua Bengio3 +Microsoft Research Montréal +Université de Montréal, MILA +Tilburg University"
+cb38b4a5e517b4bcb00efbb361f4bdcbcf1dca2c,Learning towards Minimum Hyperspherical Energy,"Learning towards Minimum Hyperspherical Energy +Weiyang Liu1,*, Rongmei Lin2,*, Zhen Liu1,*, Lixin Liu3,*, Zhiding Yu4, Bo Dai1,5, Le Song1,6 +Georgia Institute of Technology 2Emory University +South China University of Technology 4NVIDIA 5Google Brain 6Ant Financial"
+cb53c8a85d58ccb2635be5b7ff978ea6e8b78cde,Face Recognition Based on Wavelet Transform and Regional Directional Weighted Local Binary Pattern,"Face Recognition Based on Wavelet Transform +nd Regional Directional Weighted Local Binary +Pattern +Wu Fengxiang +North China Career Academy of Water Resources, Henan Zhengzhou, China +Email: +independent application technology area"
cb08f679f2cb29c7aa972d66fe9e9996c8dfae00,Action Understanding with Multiple Classes of Actors,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014 Action Understanding with Multiple Classes of Actors Chenliang Xu, Member, IEEE, Caiming Xiong, and Jason J. Corso, Senior Member, IEEE"
+cbae3eaf926aede9bec7ce2e28c35c1c50b1b43f,Fast RGB-D people tracking for service robots,"Noname manuscript No. +(will be inserted by the editor) +Fast RGB-D People Tracking for Service Robots +Matteo Munaro · Emanuele Menegatti +Received: date / Accepted: date"
cb84229e005645e8623a866d3d7956c197f85e11,Disambiguating Visual Verbs,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, MONTH 201X Disambiguating Visual Verbs Spandana Gella, Frank Keller, and Mirella Lapata"
+cb94ea16f12bde2de91d3cf3fac03a20b02611b1,Element-wise Bilinear Interaction for Sentence Matching,"Proceedings of the 7th Joint Conference on Lexical and Computational Semantics (*SEM), pages 107–112 +New Orleans, June 5-6, 2018. c(cid:13)2018 Association for Computational Linguistics"
+cb96c819f20f05ad0d85bba91f86795162f63445,Noisy Ocular Recognition Based on Three Convolutional Neural Networks,"Article +Noisy Ocular Recognition Based on Three +Convolutional Neural Networks +Min Beom Lee, Hyung Gil Hong and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (M.B.L.); (H.G.H.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 18 October 2017; Accepted: 14 December 2017; Published: 17 December 2017"
cbe859d151466315a050a6925d54a8d3dbad591f,Gaze shifts as dynamical random sampling,"GAZE SHIFTS AS DYNAMICAL RANDOM SAMPLING Giuseppe Boccignone Mario Ferraro @@ -14217,6 +49628,58 @@ Dipartimento di Scienze dell’Informazione Universit´a di Milano Via Comelico 39/41 0135 Milano, Italy"
+cb8567f074573a0d66d50e75b5a91df283ccd503,Large Margin Learning in Set-to-Set Similarity Comparison for Person Reidentification,"Large Margin Learning in Set to Set Similarity +Comparison for Person Re-identification +Sanping Zhou, Jinjun Wang, Rui Shi, Qiqi Hou, Yihong Gong, Nanning Zheng"
+cb4f0656ce177161667759b46e20aec5488550fa, Learning with single view . . . ,"Washington University in St. Louis +School of Engineering and Applied Science +Department of Computer Science and Engineering +Dissertation Examination Committee: +Kilian Q. Weinberger, Chair +John Blitzer +John Cunningham +Tao Ju +Robert Pless +Bill Smart +Learning with Single View Co-training and Marginalized Dropout +Minmin Chen +A dissertation presented to the Graduate School of Arts and Sciences +of Washington University in partial fulfillment of the +requirements for the degree of +Doctor of Philosophy +May 2013 +Saint Louis, Missouri"
+cb34481714bc7194ac108a1568d34e120f256405,Audio Visual Scene-Aware Dialog (AVSD) Challenge at DSTC7,"Audio Visual Scene-Aware Dialog (AVSD) Challenge at DSTC7 +Huda Alamri∗†, Vincent Cartillier∗, Raphael Gontijo Lopes∗, Abhishek Das∗, Jue Wang†, +Irfan Essa∗, Dhruv Batra∗, Devi Parikh∗, +Anoop Cherian†, Tim K. Marks†, Chiori Hori† +School of Interactive Computing, Georgia Tech +Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"
+f881d2a04de838c8950a279e1ed8c0f9886452af,Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation,"Multi-Stage Variational Auto-Encoders for +Coarse-to-Fine Image Generation +Lei Cai +Hongyang Gao +Washington State University +Washington State University +Pullman, WA 99164 +Pullman, WA 99164 +Shuiwang Ji +Washington State University +Pullman, WA 99164"
+f81f5da2a1e4eb80b465b8dffca4c9e583a8a8a6,"Rapid Object Detection Systems , Utilising Deep Learning and Unmanned Aerial Systems ( Uas ) for Civil Engineering Applications","RAPID OBJECT DETECTION SYSTEMS, UTILISING DEEP LEARNING AND +UNMANNED AERIAL SYSTEMS (UAS) FOR CIVIL ENGINEERING APPLICATIONS +UCL Department of Civil, Environmental & Geomatic Engineering, Gower Street, London, WC1E 6BT – (david.griffiths.16, +David Griffiths*, Jan Boehm +Commission II, WG II/6 +KEY WORDS: Object detection, Deep Learning, Unmanned Aerial Systems, Railway, Rapid"
+f86c65bc2753ae71826a0dafbf46a75d22fb5b5b,Fearful Faces do Not Lead to Faster Attentional Deployment in Individuals with Elevated Psychopathic Traits,"J Psychopathol Behav Assess (2017) 39:596–604 +DOI 10.1007/s10862-017-9614-x +Fearful Faces do Not Lead to Faster Attentional Deployment +in Individuals with Elevated Psychopathic Traits +Sylco S. Hoppenbrouwers 1 & Jaap Munneke 2,3 & Karen A. Kooiman 4 & Bethany Little 4 & +Craig S. Neumann 5 & Jan Theeuwes 4 +Published online: 30 June 2017 +# The Author(s) 2017. This article is an open access publication"
f842b13bd494be1bbc1161dc6df244340b28a47f,An Improved Face Recognition Technique Based on Modular Multi-directional Two-dimensional Principle Component Analysis Approach,"An Improved Face Recognition Technique Based on Modular Multi-directional Two-dimensional Principle Component Analysis Approach @@ -14226,6 +49689,33 @@ Department of Physics and Electronic Engineering, Hanshan Normal University, Email: Hongcai Chen Email:"
+f86d8385a6170b98e434a121fb7d12facb2c8426,Frank-Wolfe Algorithm for Exemplar Selection,"Frank-Wolfe Algorithm for Exemplar Selection +Gary Cheng +UC Berkeley +Armin Askari +UC Berkeley +Laurent El Ghaoui +Kannan Ramchandran +UC Berkeley +UC Berkeley"
+f884a67187929e7dda66091c13867ed0a8a36d01,Weighted-Fusion-Based Representation Classifiers for Hyperspectral Imagery,"Remote Sens. 2015, 7, 14806-14826; doi:10.3390/rs71114806 +OPEN ACCESS +ISSN 2072-4292 +www.mdpi.com/journal/remotesensing +Article +Weighted-Fusion-Based Representation Classifiers for +Hyperspectral Imagery +Bing Peng 1, Wei Li 1,*, Xiaoming Xie 1,*, Qian Du 2 and Kui Liu 3 +College of Information Science and Technology, Beijing University of Chemical Technology, +Beijing 100029, China; E-Mail: +Department of Electrical and Computer Engineering, Mississippi State University, Starkville, +MS 39762, USA; E-Mail: +Intelligent Fusion Technology, Germantown, MD 20876, USA; E-Mail: +* Authors to whom correspondence should be addressed; E-Mails: (W.L.); +(X.X.); Tel.: +86-010-6443-3717 (W.L.); +86-010-6441-3467 (X.X.). +Academic Editors: Magaly Koch and Prasad S. Thenkabail +Received: 17 June 2015 / Accepted: 30 October 2015 / Published: 6 November 2015"
+f8ea0f76f2044168040fcd0a9e81072c88cde4a4,Nonlinear Feature Extraction using Multilayer Perceptron based Alternating Regression for Classification and Multiple-output Regression Problems,
f8c94afd478821681a1565d463fc305337b02779,Design and Implementation of Robust Face Recognition System for Uncontrolled Pose and Illumination Changes,"www.semargroup.org, www.ijsetr.com ISSN 2319-8885 @@ -14238,17 +49728,95 @@ VIJAYA BHASKAR TALARI , VENKATESWARLU PRATTI PG Scholar, Dept of ECE, LITAM, JNTUK, Andhrapradesh, India, Email: Assistant Professor, Dept of ECE, LITAM, JNTUK, Andhrapradesh, India, Email:"
+f8eedcca6263062b6bab11ead255f719452f1c81,Motion in action : optical flow estimation and action localization in videos. (Le mouvement en action : estimation du flot optique et localisation d'actions dans les vidéos),"Motion in action : optical flow estimation and action +localization in videos +Philippe Weinzaepfel +To cite this version: +Philippe Weinzaepfel. Motion in action : optical flow estimation and action localization in videos. +Computer Vision and Pattern Recognition [cs.CV]. Université Grenoble Alpes, 2016. English. <NNT : +016GREAM013>. <tel-01407258> +HAL Id: tel-01407258 +https://tel.archives-ouvertes.fr/tel-01407258 +Submitted on 1 Dec 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+f8cfabecbe587c611de2696a37f96e3f77ac8555,NEMGAN: Noise Engineered Mode-matching GAN,"NEMGAN: Noise Engineered Mode-matching GAN +Deepak Mishra∗, Prathosh AP∗, Aravind J, Prashant Pandey +& Santanu Chaudhury +Department of Electrical Engineering +Indian Institute of Technology Delhi +New Delhi, India"
+f8106b414d81df11ef2e9c26dd83f812711eec35,Inferring Analogous Attributes: Large-Scale Transfer of Category-Specific Attribute Classifiers,"Inferring Analogous Attributes: +Large-Scale Transfer of Category-Specific Attribute Classifiers +Chao-Yeh Chen and Kristen Grauman"
+f827b596b4099b0490ab46a9dd2922db2b708963,Pathologies of Neural Models Make Interpretation Difficult,"Pathologies of Neural Models Make Interpretations Difficult +Shi Feng1 Eric Wallace1 Alvin Grissom II2 Mohit Iyyer3,4 +Pedro Rodriguez1 Jordan Boyd-Graber1 +University of Maryland 2Ursinus College +UMass Amherst 4Allen Institute for Artificial Intelligence"
+f879556115284946637992191563849e840789d1,Geometry Guided Adversarial Facial Expression Synthesis,"Geometry Guided Adversarial Facial Expression Synthesis +Lingxiao Song1,2 +Zhihe Lu1,3 Ran He1,2,3 +Zhenan Sun1,2 +Tieniu Tan1,2,3 +National Laboratory of Pattern Recognition, CASIA +Center for Research on Intelligent Perception and Computing, CASIA +Center for Excellence in Brain Science and Intelligence Technology, CAS"
f8ec92f6d009b588ddfbb47a518dd5e73855547d,Extreme Learning Machine Ensemble Using Bagging for Facial Expression Recognition,"J Inf Process Syst, Vol.10, No.3, pp.443~458, September 2014 ISSN 1976-913X (Print) ISSN 2092-805X (Electronic) Extreme Learning Machine Ensemble Using Bagging for Facial Expression Recognition Deepak Ghimire* and Joonwhoan Lee*"
+f8796b8e8246ce41efb2904c053fe0ea2868e373,A Variational U-Net for Conditional Appearance and Shape Generation,"A Variational U-Net for Conditional Appearance and Shape Generation +Patrick Esser∗, Ekaterina Sutter∗, Bj¨orn Ommer +Heidelberg Collaboratory for Image Processing +IWR, Heidelberg University, Germany"
+f8b26b2ec62cf76f58f95938233bc22ae1902144,UvA-DARE ( Digital Academic Repository ) Visual Tracking : An Experimental Survey Smeulders,"UvA-DARE (Digital Academic Repository) +Visual Tracking: An Experimental Survey +Smeulders, A.W.M.; Chu, D.M.; Cucchiara, R.; Calderara, S.; Dehghan, A.; Shah, M. +Published in: +IEEE Transactions on Pattern Analysis and Machine Intelligence +0.1109/TPAMI.2013.230 +Link to publication +Citation for published version (APA): +Smeulders, A. W. M., Chu, D. M., Cucchiara, R., Calderara, S., Dehghan, A., & Shah, M. (2014). Visual +Tracking: An Experimental Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(7), +442-1468. DOI: 10.1109/TPAMI.2013.230 +General rights +It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +Disclaimer/Complaints regulations +If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask +the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, +The Netherlands. You will be contacted as soon as possible. +Download date: 26 Apr 2018"
+f89e5a8800b318fa03289b5cc67df54b956875b4,Do GANs actually learn the distribution? An empirical study,"Do GANs actually learn the distribution? An empirical study +Sanjeev Arora +Yi Zhang +July 4, 2017"
f8ed5f2c71e1a647a82677df24e70cc46d2f12a8,Artificial Neural Network Design and Parameter Optimization for Facial Expressions Recognition,"International Journal of Scientific & Engineering Research, Volume 2, Issue 12, December-2011 1 ISSN 2229-5518 Artificial Neural Network Design and Parameter Optimization for Facial Expressions Recognition Ammar A. Alzaydi"
+f8ec2079838520fcb9394574bdd956ac9d3d5832,Visual Dynamics: Stochastic Future Generation via Layered Cross Convolutional Networks,"Visual Dynamics: Stochastic Future Generation +via Layered Cross Convolutional Networks +Tianfan Xue*, Jiajun Wu*, Katherine L. Bouman, and William T. Freeman"
+f809f9e5a03817d238718723a7b4ac04abcd3f12,Highly Efficient 8-bit Low Precision Inference,"Under review as a conference paper at ICLR 2019 +HIGHLY EFFICIENT 8-BIT LOW PRECISION INFERENCE +OF CONVOLUTIONAL NEURAL NETWORKS +Anonymous authors +Paper under double-blind review"
f8f872044be2918de442ba26a30336d80d200c42,Facial Emotion Recognition Techniques : A Survey,"IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613 Facial Emotion Recognition Techniques: A Survey Namita Rathore1 Rohit Miri2 @@ -14257,6 +49825,10 @@ Namita Rathore1 Rohit Miri2 defense systems, surveillance"
+f8a2a6b821a092ac43acd4e7366fe7c1e9285317,Attribute-controlled face photo synthesis from simple line drawing,"ATTRIBUTE-CONTROLLED FACE PHOTO SYNTHESIS FROM SIMPLE LINE DRAWING +Qi Guo Ce Zhu Zhiqiang Xia Zhengtao Wang Yipeng Liu +School of Electronic Engineering / Center for Robotics +University of Electronic Science and Technology of China (UESTC), Chengdu, China"
f8a5bc2bd26790d474a1f6cc246b2ba0bcde9464,"KDEF-PT: Valence, Emotional Intensity, Familiarity and Attractiveness Ratings of Angry, Neutral, and Happy Faces","ORIGINAL RESEARCH published: 19 December 2017 doi: 10.3389/fpsyg.2017.02181 @@ -14277,10 +49849,164 @@ students, M = 23.73 years old, SD = 7.24) and to extend the number of subjective dimensions used to evaluate each image. Specifically, participants reported emotional labeling (forced-choice task) and evaluated the emotional intensity and valence of the expression, as well as the attractiveness and familiarity of the model (7-points rating"
+f8ddeb23343cde8e2a9fdd87e877f0ce5461b42b,Illumination and Pose Invariant Face Recognition: A Technical Review,"International Journal of Computer Information Systems and Industrial Management Applications (IJCISIM) +ISSN: 2150-7988 Vol.2 (2010), pp.029-038 +http://www.mirlabs.org/ijcisim +Illumination and Pose Invariant Face Recognition: A Technical Review +Kavita. R. Singh +Department of Computer +Technology, YCCE, Nagpur(M.S), +41 110, India +Mukesh. A. Zaveri +Computer Engineering +Department, S.V.National Institute +of Technology, Surat(Gujarat), +29507, India +Mukesh. M. Raghuwanshi +NYSS College of Engineering and +Research, Nagpur(M.S), 441 110, +India"
+f8d68084931f296abfb5a1c4cd971f0b0294eaa4,Unconditional Generative Models,"Published as a conference paper at ICLR 2018 +LATENT CONSTRAINTS: +LEARNING TO GENERATE CONDITIONALLY FROM +UNCONDITIONAL GENERATIVE MODELS +Jesse Engel +Google Brain +San Francisco, CA, USA +Matthew D. Hoffman +Google Inc. +San Francisco, CA, USA +Adam Roberts +Google Brain +San Francisco, CA, USA"
+ce54dd2b0c6c75208ac77420233419066dd0117f,Issn 2348-375x Ear Segmentation Using Differential Box Counting Approach,"Geetha et al. UJEAS 2014, 02 (01): Page 77-78 +ISSN 2348-375X +Unique Journal of Engineering and Advanced Sciences +Available online: www.ujconline.net +Research Article +EAR SEGMENTATION USING DIFFERENTIAL BOX COUNTING APPROACH +Geetha Prem P1*, Manikandaprabu N2, Dhivya P3, Deepa A4 +PG Scholar, AVS Engineering College, TN, India +Lecturer, Senthur Polytechnic College, TN, India +Asso. Prof/ECE, AVS Engineering College, Salem +ME (Communication Systems), Sona College of Technology, Salem +Received: 28-12-2013; Revised: 24-01-2014; Accepted: 20-02-2014 +*Corresponding Author: P. Prem Geetha, PG Scholar, AVS Engineering College, TN, India Email:"
+ceac97de889ed2f65af62f61a007651d03b36b6c,Diagnostic Accuracy of Content Based Dermatoscopic Image Retrieval with Deep Classification Features,"Diagnostic Accuracy of Content Based Dermatoscopic Image Retrieval with +Deep Classification Features +Tschandl P, Argenziano G, Razmara M, Yap J +Final version available at https://doi.org/10.1111/bjd.17189 +Citation: +tschandl cbir2018, +Author=”Tschandl, P. and Argenziano, G. and Razmara, M. and Yap, J. ”, +Title=”Diagnostic Accuracy of Content Based Dermatoscopic Image Retrieval with Deep Classification Features”, +Journal=”Br J Dermatol”, +Year=”2018”"
+cefd107b19201cd9f403e2f9332c690e81f770b5,A Survey on Databases for Facial Expression Analysis,
+cef2b5ab841568755233994b12cf046c408f881e,Techniques for Statistical Shape Model Building and Fusion,"TECHNIQUES +STATISTICAL SHAPE MODEL +BUILDING AND FUSION +Constantine Butakoff +(Kostantyn Butakov)"
+ce57cc478421adf85a9058a0cc8fad8ebfd81c52,Multimodal Attribute Extraction,"Multimodal Attribute Extraction +Robert L. Logan IV +University of California +Irvine, CA +Samuel Humeau +Diffbot +Mountain View, CA +Sameer Singh +University of California +Irvine, CA +Introduction +Given the large collections of unstructured and semi-structured data available on the web, there is a +rucial need to enable quick and efficient access to the knowledge content within them. Traditionally, +the field of information extraction has focused on extracting such knowledge from unstructured text +documents, such as job postings, scientific papers, news articles, and emails. However, the content +on the web increasingly contains more varied types of data, including semi-structured web pages, +tables that do not adhere to any schema, photographs, videos, and audio. Given a query by a user, +the appropriate information may appear in any of these different modes, and thus there’s a crucial +need for methods to construct knowledge bases from different types of data, and more importantly, +Motivated by this goal, we introduce the task of multimodal attribute extraction. Provided contextual"
+ce391bcdb64f7659ddc5a0c2e5c73854c1e8031c,Zur Erlangung Des Grades Des,"FILTERING AND OPTIMIZATION +STRATEGIES FOR MARKERLESS +HUMAN MOTION CAPTURE WITH +SKELETON-BASED SHAPE MODELS. +DISSERTATION +ZUR ERLANGUNG DES GRADES DES +DOKTORS DER INGENIEURWISSENSCHAFTEN (DR.-ING.) +DER NATURWISSENSCHAFTLICH-TECHNISCHEN FAKULT ¨ATEN +DER UNIVERSIT ¨AT DES SAARLANDES +VORGELEGT VON +JUERGEN GALL +SAARBR ¨UCKEN"
+ce316d2366ec1b95ee91a98b4f426e6c00cdcdc4,Hierarchical Energy-transfer Features,"Hierarchical Energy-Transfer Features +Radovan Fusek, Eduard Sojka, Karel Mozdˇreˇn and Milan ˇSurkala +Technical University of Ostrava, FEECS, Department of Computer Science +7. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic +{radovan.fusek, eduard.sojka, karel.mozdren, +Keywords: +Object Detection, Recognition, SVM, Image Descriptors, Feature Selection."
+ceb02a8f874c84ece88fcc7be1530a581b1cd1b0,A Novel Geometry-based Algorithm for Robust Grasping in Extreme Clutter Environment,"A Novel Geometry-based Algorithm for Robust Grasping in Extreme Clutter +Environment +Olyvia Kundua, Swagat Kumara,∗ +TATA Consultancy Services, Bangalore, India 560066"
ce85d953086294d989c09ae5c41af795d098d5b2,Bilinear Analysis for Kernel Selection and Nonlinear Feature Extraction,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. Bilinear Analysis for Kernel Selection and Nonlinear Feature Extraction Shu Yang, Shuicheng Yan, Member, IEEE, Chao Zhang, and Xiaoou Tang, Senior Member, IEEE"
+ceb4040acf7f27b4ca55da61651a14e3a1ef26a8,Angry Crowds: Detecting Violent Events in Videos,"Angry Crowds: +Detecting Violent Events in Videos +Sadegh Mohammadi1, Alessandro Perina1,2, Hamed Kiani1, Vittorio Murino1,3 +Pattern Analysis and Computer Vision (PAVIS), +Istituto Italiano di Tecnologia, Genova, Italy +Microsoft Corp, +WDG Core Data Science, Redmond +Dept. of Computer Science, +University of Verona, Italy +As supplementary material, we selected a few testing video clips from Vio- +lence in crowds (VIC) [1] dataset to illustrate the effectiveness of the proposed +Aggression Force compared to the Interaction Force (SFM) [2] and Optical Flow +for the task of violent detection in video sequences. The scenarios depicted in +the attached video are captured under very challenging situations including low +image quality, cluttered background, densely crowded scenes, camera motion, +occlusions, large scale/illumination variations. +The qualitative results in video format can be seen in ”video.avi”, highlight- +ing two major advantages of Aggression Force compared to Social Force and +Optical Flowing. +Firstly, the SFM and Optical Flow are very sensitive to footages captured"
+cee700093d6672df48d169ef194861026fe31e8e,Hashing on Nonlinear Manifolds,"Hashing on Nonlinear Manifolds +Fumin Shen, Chunhua Shen, Qinfeng Shi, Anton van den Hengel, Zhenmin Tang, Heng Tao Shen +in the Hamming space. This means that many algorithms +which are based on such pairwise comparisons can be made +more efficient, and applied to much larger datasets. Due to the +flexibility of hash codes, hashing techniques can be applied +in many ways. one can, for example, efficiently perform +similarity search by exploring only those data points falling +into the close-by buckets to the query by the Hamming +distance, or use the binary representations for other tasks like +image classification."
+ceedb191328ac4d968853b948a32b5689c2ac2a2,Semisupervised Dimensionality Reduction and Classification Through Virtual Label Regression,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 41, NO. 3, JUNE 2011 +Semisupervised Dimensionality Reduction and +Classification Through Virtual Label Regression +Feiping Nie, Dong Xu, Xuelong Li, Senior Member, IEEE, and Shiming Xiang"
+ce0cc5f078c5224b9599caf518d74ae3023be0a6,Review on computer vision techniques in emergency situations,"(will be inserted by the editor) +Review on Computer Vision Techniques in Emergency Situations +Laura Lopez-Fuentes · Joost van de Weijer · Manuel Gonz´alez-Hidalgo · Harald +Skinnemoen · Andrew D. Bagdanov +Received: date / Accepted: date"
+ce4853f2214ee1f4c47a97ff45d4e53f6ffd5087,Models and Methods for Bayesian Object Matching,"Helsinki University of Technology Laboratory of Computational Engineering Publications +Teknillisen korkeakoulun Laskennallisen tekniikan laboratorion julkaisuja +Espoo 2005 +REPORT B52 +MODELS AND METHODS FOR BAYESIAN OBJECT +MATCHING +Toni Tamminen +AB TEKNILLINEN KORKEAKOULU +TEKNISKA H(cid:214)GSKOLAN +HELSINKI UNIVERSITY OF TECHNOLOGY +TECHNISCHE UNIVERSIT˜T HELSINKI +UNIVERSITE DE TECHNOLOGIE D’HELSINKI"
ceaa5eb51f761b5f84bd88b58c8f484fcd2a22d6,UC San Diego UC San Diego Electronic Theses and Dissertations Title Interactive learning and prediction algorithms for computer vision applications,"UC San Diego UC San Diego Electronic Theses and Dissertations Title @@ -14295,6 +50021,16 @@ Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California"
+cef092bf9beed65e379ab48ef2b43498d4aaea92,Process Monitoring in the Intensive Care Unit: Assessing Patient Mobility Through Activity Analysis with a Non-Invasive Mobility Sensor,"Process Monitoring in the Intensive Care Unit: +Assessing Patient Mobility Through Activity +Analysis with a Non-Invasive Mobility Sensor +Austin Reiter1(B), Andy Ma1, Nishi Rawat2, Christine Shrock2, +nd Suchi Saria1 +The Johns Hopkins University, Baltimore, MD, USA +Johns Hopkins Medical Institutions, Baltimore, MD, USA"
+ce12bbb8ce974df4b64f18e478d7fa99b722de03,A Hybrid Data Association Framework for Robust Online Multi-Object Tracking,"A Hybrid Data Association Framework for Robust +Online Multi-Object Tracking +Min Yang, Yuwei Wu∗, and Yunde Jia Member, IEEE,"
ce9a61bcba6decba72f91497085807bface02daf,Eigen-harmonics faces: face recognition under generic lighting,"Eigen-Harmonics Faces: Face Recognition under Generic Lighting Laiyun Qing1,2, Shiguang Shan2, Wen Gao1,2 Graduate School, CAS, Beijing, China, 100080 @@ -14304,10 +50040,26 @@ cef6cffd7ad15e7fa5632269ef154d32eaf057af,Emotion Detection Through Facial Featur Recognition James Pao through consistent"
+ce3ee08f4d937a6dcb2d6dd0a1ca100920f312e6,Literature Survey On Contactless Palm Vein Recognition,"International Journal of Computer Science Trends and Technology (IJCST) – Volume 3 Issue 5, Sep-Oct 2015 +RESEARCH ARTICLE +Literature Survey On Contactless Palm Vein Recognition +Roshni C Rahul [1], Merin Cherian [2], Manu Mohan C M [3] +Department of Computer Science [1], Department of Science [2], Department of Electronics [3] +OPEN ACCESS +Mahatma Gandhi University +Kerala - India"
cebfafea92ed51b74a8d27c730efdacd65572c40,Matching 2.5D face scans to 3D models,"JANUARY 2006 Matching 2.5D Face Scans to 3D Models Xiaoguang Lu, Student Member, IEEE, Anil K. Jain, Fellow, IEEE, and Dirk Colbry, Student Member, IEEE"
+ce0dbe6b1abecb54dcc98dbe652aa63d190dbc94,Part-Based Models for Finding People and Estimating Their Pose,"Part-based models for finding people and +estimating their pose +Deva Ramanan"
+ced4853617ba6af27f5447f9c4de07c3e05e8c3b,Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations,"Real-Time Joint Semantic Segmentation and Depth Estimation Using +Asymmetric Annotations +Vladimir Nekrasov1, Thanuja Dharmasiri2, Andrew Spek2, Tom Drummond2, Chunhua Shen1 and Ian Reid1"
+cea85314294f9731661a419f627cb99331ad9c50,Race recognition using local descriptors,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE +ICASSP 2012"
ce54e891e956d5b502a834ad131616786897dc91,Face Recognition Using LTP Algorithm,"International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 @@ -14324,6 +50076,23 @@ to variation in the luminance the representation get varied from the original image. The person with same poses expression and seen from same viewpoint can be appear very different due to variation in lightening."
+ce6d23894f88349443e7c9fe512ca81291bb2e00,VIENA2: A Driving Anticipation Dataset,"VIENA2: A Driving Anticipation Dataset +Mohammad Sadegh Aliakbarian1,2,4, Fatemeh Sadat Saleh1,4, Mathieu +Salzmann3, Basura Fernando2, Lars Petersson1,4, and Lars Andersson4 +ANU, 2ACRV, 3CVLab, EPFL, 4Data61-CSIRO"
+ce06015fc0eb2add064ef93c9b97ad063c03aef4,Person Re-identification in Surveillance Videos using Multi-part Color Descriptor,"International Journal of Computer Applications (0975 – 8887) +Volume 121 – No.16, July 2015 +Person Re-identification in Surveillance Videos +using Multi-part Color Descriptor +P.K. Sathish +S. Balaji +Computer Science and Engineering Dept. +Centre for Emerging Technologies, Jain University +Christ University +Bengaluru- 560074"
+ce073cb70eec80d87c9e07a4ec2d4162d91e23a6,Positive Definite Matrices: Data Representation and Applications to Computer Vision,"Positive Definite Matrices: Data Representation +nd Applications to Computer Vision +Anoop Cherian and Suvrit Sra"
ce6f459462ea9419ca5adcc549d1d10e616c0213,A Survey on Face Identification Methodologies in Videos,"A Survey on Face Identification Methodologies in Videos Student, M.Tech CSE ,Department of Computer Science @@ -14334,6 +50103,29 @@ ce933821661a0139a329e6c8243e335bfa1022b1,Temporal Modeling Approaches for Large- Youtube-8M Video Understanding Fu Li, Chuang Gan, Xiao Liu, Yunlong Bian, Xiang Long, Yandong Li, Zhichao Li, Jie Zhou, Shilei Wen Baidu IDL & Tsinghua University"
+cea50611ba73b5775cc2fe1e9c27990a0bb20cf8,Gabor Feature Based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary,"Gabor Feature based Sparse Representation for +Face Recognition with Gabor Occlusion +Dictionary +Meng Yang, Lei Zhang ⋆ +Biometric Research Center, Dept. of Computing, The Hong Kong Polytechnic +University, Hong Kong,"
+e0d2a28bdcb1996f9659ce2d5fcdace3d369cff6,Fusion Scheme for Semantic and Instance-level Segmentation,"Fusion Scheme for Semantic and Instance-level Segmentation +Arthur Daniel Costea ∗, Andra Petrovai ∗ and Sergiu Nedevschi +Image Processing and Pattern Recognition Research Center +Technical University of Cluj-Napoca, Romania +{arthur.costea, andra.petrovai,"
+e000dd1aec1c7b1e9e781ec7ea66f2bde72faa5e,Ear Recognition: A Complete System,"Ear Recognition: A Complete System +Ayman Abazaa,b and MaryAnn F. Harrisona +West Virginia High Tech Foundation, 1000 Technology Drive, Fairmont, USA; +Cairo University, Cairo, Egypt"
+e0e8c7145c9b389dad2f4e1982f2b9c31b766503,Augmenting Crowd-Sourced 3 D Reconstructions using Semantic Detections,"Augmenting Crowd-Sourced 3D Reconstructions using Semantic Detections +True Price1 +Department of Computer Science, UNC Chapel Hill +Johannes L. Sch¨onberger2 +Zhen Wei1 Marc Pollefeys2 +Department of Computer Science, ETH Z¨urich +Jan-Michael Frahm1 +Microsoft"
e0dedb6fc4d370f4399bf7d67e234dc44deb4333,Supplementary Material: Multi-Task Video Captioning with Video and Entailment Generation,"Supplementary Material: Multi-Task Video Captioning with Video and Entailment Generation Ramakanth Pasunuru and Mohit Bansal @@ -14361,6 +50153,49 @@ Deep Convolutional Layers Amir Ghodrati · Ali Diba · Marco Pedersoli · Tinne Tuytelaars · Luc Van Gool Received: date / Accepted: date"
+e0aa9ab8f00b2bf0dd1b6ffd5c00e5a15b6a67e1,Robust Visual Tracking via Hierarchical Convolutional Features,"Robust Visual Tracking +via Hierarchical Convolutional Features +Chao Ma, Jia-Bin Huang, Xiaokang Yang, and Ming-Hsuan Yang"
+e0eb1d66f244456063409264ed795d9893565011,Inhibited Softmax for Uncertainty Estimation in Neural Networks,"Electronic Preprint +INHIBITED SOFTMAX FOR UNCERTAINTY ESTIMATION +IN NEURAL NETWORKS +Marcin Mo˙zejko, Mateusz Susik & Rafał Karczewski +Sigmoidal"
+e043d79f4dc41c9decaf637d8ffdd11f8ed59f2b,Distance metric learning for image and webpage comparison. (Apprentissage de distance pour la comparaison d'images et de pages Web),"Distance metric learning for image and webpage +omparison +Marc Teva Law +To cite this version: +Marc Teva Law. Distance metric learning for image and webpage comparison. Image Processing. Uni- +versité Pierre et Marie Curie - Paris VI, 2015. English. <NNT : 2015PA066019>. <tel-01135698v2> +HAL Id: tel-01135698 +https://tel.archives-ouvertes.fr/tel-01135698v2 +Submitted on 18 Mar 2015 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de +recherche français ou étrangers, des laboratoires"
+e0cac58f3855cd84b9d28f508b2f7711e0d7e44a,3a: a Person Re-identification System via Attribute Augmentation and Aggregation,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE +ICASSP 2017"
+e0181f7596b475f7c7d31fd1eccad8e9b7379180,Facial Expression Recognition for Traumatic Brain Injured Patients,
+e00bdb0b046c4d21517ca808a4233a6fd5f3faee,Efficient Retina-like Resampling from Cartesian Images,"VII Workshop de Vis˜ao Computacional – WVC 2011 +Efficient Retina-like Resampling from Cartesian Images +Hugo Vieira Neto, Diogo Rosa Kuiaski and Gustavo Benvenutti Borba +Graduate School of Electrical Engineering and Applied Computer Science +Federal University of Technology - Paran´a, Brazil"
+e09c7bbf1bef602018928acb395f09448a0366b8,Learning beautiful (and ugly) attributes,"MARCHESOTTI, PERRONNIN: LEARNING BEAUTIFUL (AND UGLY) ATTRIBUTES +Learning beautiful (and ugly) attributes +Luca Marchesotti +Florent Perronnin +Xerox Research Centre Europe +Meylan, France"
+e05444e51d292bda871388c22b97400ed4cf73a8,An Overview of Recent Approaches in Person Re-Identification,An Overview of Recent Approaches in Person Re-Identification
e0939b4518a5ad649ba04194f74f3413c793f28e,Mind-reading machines : automated inference of complex mental states Rana,"Technical Report UCAM-CL-TR-636 ISSN 1476-2986 @@ -14376,10 +50211,35 @@ Cambridge CB3 0FD United Kingdom phone +44 1223 763500 http://www.cl.cam.ac.uk/"
+e01ac06aa1f0b193a620bf70c5dad91128a1bc90,CAPTAIN: Comprehensive Composition Assistance for Photo Taking,"International Journal on Computer Vision manuscript No. +(will be inserted by the editor) +CAPTAIN: Comprehensive Composition Assistance for Photo +Taking +Farshid Farhat · Mohammad Mahdi Kamani · James Z. Wang +Received: date / Accepted: date"
+e0e71b59a34c97d15e5ff148fb9a43b892d45bd5,Facial Expression Emotion Detection for Real-Time Embedded Systems,"Article +Facial Expression Emotion Detection for Real-Time +Embedded Systems † +Saeed Turabzadeh 1, Hongying Meng 1,* ID , Rafiq M. Swash 1 ID , Matus Pleva 2 ID and Jozef Juhar 2 ID +Department of Electronic and Computer Engineering, Brunel University London, Uxbridge UB8 3PH, UK; +(S.T.); (R.M.S.) +Department of Electronics and Multimedia Telecommunications, Technical University of Kosice, Letna 9, +04001 Kosice, Slovakia; (M.P.); (J.J.) +* Correspondence: Tel.: +44-1895-265496 +This paper is an extended version of our paper in Proceedings of Innovative Computing Technology +(INTECH 2017), Luton, UK, 16–18 August 2017; with permission from IEEE. +Received: 15 December 2017; Accepted: 22 January 2018; Published: 26 January 2018"
e0ed0e2d189ff73701ec72e167d44df4eb6e864d,Recognition of static and dynamic facial expressions: a study review,"Recognition of static and dynamic facial expressions: a study review Estudos de Psicologia, 18(1), janeiro-março/2013, 125-130 Nelson Torro Alves Federal University of Paraíba"
+e018c7f468a9b61cd6e7dcbc40b332a8a25808ae,Face Recognition by Face Bunch Graph Method,"Face Recognition by Face Bunch Graph Method +JIRI STASTNY*, VLADISLAV SKORPIL** +* Department of Automation and Computer Science, +** Department of Telekommunications, +Brno University of Technology, +Purkynova 118, 612 00 Brno, +CZECH REPUBLIC,"
e065a2cb4534492ccf46d0afc81b9ad8b420c5ec,SFace: An Efficient Network for Face Detection in Large Scale Variations,"SFace: An Efficient Network for Face Detection in Large Scale Variations Jianfeng Wang12∗, Ye Yuan 1†, Boxun Li†, Gang Yu† and Sun Jian† @@ -14388,6 +50248,63 @@ Megvii Inc. (Face++)†" e013c650c7c6b480a1b692bedb663947cd9d260f,Robust Image Analysis With Sparse Representation on Quantized Visual Features,"Robust Image Analysis With Sparse Representation on Quantized Visual Features Bing-Kun Bao, Guangyu Zhu, Jialie Shen, and Shuicheng Yan, Senior Member, IEEE"
+e01058388d139e027482a7d89a2997606f7ef4fd,Global-residual and Local-boundary Refinement Networks for Rectifying Scene Parsing Predictions,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +Input (b) FCN Based Model (c) GRN (d) Input (f) LRN (e) FCN Based Model Figure1:ResultofFCNbasedmodel(b)hasinconsistentlabelsinwall,curtainandbedsidetable,whichcanberefinedbytheproposedGRN(c).ResultofFCNbasedmodel(e)hasimpreciseanddiscon-tinuousobjectboundariesofcabinet,tableandchairs,whichcanberefinedbytheproposedLRN(f).stepinmanypracticalframeworks.Forexample,inobjectdetection,bounding-boxrefinement[GidarisandKomodakis,2015]iswidelyusedin[Heetal.,2016][Belletal.,2016][Shrivastavaetal.,2016],bringingsignificantimprovementofbounding-boxlocalizationandscoring.Inspiredbyitssuccess,wedesigntwonewrefinementnetworksparticularlyforrectifyingtheparsingpredictions,frombothglobalandlocalviewsrespectively.Eachofthetwonetworkscanbeemployedaftertheexistingparsingframeworksindividually.Moreover,cascadingthemtogetherforrefinementcangainmorepreciseparsingresults.Firstly,weconsiderperformingrefinementfromtheglobalview.Inconsistentparsingresultsareverycommoninpre-dictionsofexistingsceneparsingframeworks,asshowninFigure1(b).Toaddressthisproblem,wedesigntheGlobal-residualRefinementNetwork(GRN)throughexploit-ingglobalcontextualinformationandspatiallayoutrelation-shipsduringrefining.ThisnetworktakestheoriginalimagesandtheKconfidencemaps(i.e.,theoutputofthelastlayerbeforeSoftMaxlayer,eachforoneoftheKsemanticclasses)asinput.Thenoutputstheglobalparsingresidual,whichwillbeaddedtotheinputconfidencemapstoobtaintheglobalrectifyingresults.Thisnetworkeffectivelycapturesglobalcontextualinformationbyiterativelyusingadeepneuralnet-workwithlargereceptivefields.AfterglobalrefinementbyGRN,somemislabelingcanbecorrectedandsomeinconsis-"
+e00526ff149bd61f6811ba2f2145ed22d9306319,Personal Space Regulation in Childhood Autism Spectrum Disorders,"Personal Space Regulation in Childhood Autism +Spectrum Disorders +Erica Gessaroli1,2, Erica Santelli3, Giuseppe di Pellegrino1,4*, Francesca Frassinetti1,2* +Department of Psychology, University of Bologna, Bologna, Italy, 2 Fondazione Salvatore Maugeri, Clinica del Lavoro e della Riabilitazione, Istituto di Ricovero +e Cura a Carattere Scientifico, Mantova, Castel Goffredo, Italy, 3 Centro Autismo, Reggio Emilia, Italy, 4 Center for Studies and Research in Cognitive +Neuroscience, Cesena, Italy"
+e0739088d578b2abf583e30953ffa000620cca98,Efficient Pedestrian Detection in Urban Traffic Scenes,"Efficient Pedestrian Detection in Urban Traffic Scenes +Dissertation +Erlangung des Doktorgrades (Dr. rer. nat.) +Mathematisch-Naturwissenschaftlichen Fakult¨at +Rheinischen Friedrich-Wilhelms-Universit¨at Bonn +vorgelegt von +Shanshan Zhang +Jiangxi, V.R. China +Bonn, 2014"
+e0082ae9e466f7c855fb2c2300215ced08f61432,Generative Temporal Models with Spatial Memory for Partially Observed Environments,"Generative Temporal Models with Spatial Memory +for Partially Observed Environments +Marco Fraccaro 1 * Danilo Jimenez Rezende 2 Yori Zwols 2 Alexander Pritzel 2 S. M. Ali Eslami 2 Fabio Viola 2"
+e076f818b090e42036821c69727cfa3b7da49373,Social Groups Detection in Crowd through Shape-Augmented Structured Learning,"Social Groups Detection in Crowd Through +Shape-Augmented Structured Learning +Francesco Solera and Simone Calderara +DIEF University of Modena and Reggio Emilia, Italy"
+e0515dc0157a89de48e1120662afdd7fe606b544,Perception Science in the Age of Deep Neural Networks,"SPECIALTY GRAND CHALLENGE +published: 02 February 2017 +doi: 10.3389/fpsyg.2017.00142 +Perception Science in the Age of +Deep Neural Networks +Rufin VanRullen 1, 2* +Centre National de la Recherche Scientifique, UMR 5549, Faculté de Médecine Purpan, Toulouse, France, 2 Université de +Toulouse, Centre de Recherche Cerveau et Cognition, Université Paul Sabatier, Toulouse, France +Keywords: perception, neuroscience, psychology, neural networks, deep learning, artificial intelligence +For decades, perception was considered a unique ability of biological systems, little understood in +its inner workings, and virtually impossible to match in artificial systems. But this status quo was +upturned in recent years, with dramatic improvements in computer models of perception brought +bout by “deep learning” approaches. What does all the ruckus about a “new dawn of artificial +intelligence” imply for the neuroscientific and psychological study of perception? Is it a threat, an +opportunity, or maybe a little of both? +WHILE WE WERE SLEEPING... +My personal journey in the field of perception science started about 20 years ago. For as long as +I can remember, we perception scientists have exploited in our papers and grant proposals the +lack of human-level artificial perception systems, both as a justification for scientific inquiry, and +s a convenient excuse for using a cautious, methodical approach—i.e., “baby steps.” Visual object"
+e0e511a5d58a8d090ad169be4fcfdbeaef097a70,Leveraging Cognitive Computing for Gender and Emotion Detection,"Leveraging Cognitive Computing for Gender and +Emotion Detection +Andrea Corriga1, Simone Cusimano1, Francesca M. Malloci1, Lodovica +Marchesi1 and Diego Reforgiato Recupero1 +Department of Mathematics and Computer Science, +University of Cagliari, Via Ospedale 72, 09124, Cagliari"
+4640dfc0bfe7923c08d0c762a9c33b52b9029409,Head Movement and Facial Expression Transfer from 2D Video to a 3D Model,"Head Movement and Facial Expression Transfer +from 2D Video to a 3D Model +Mairead Grogan +A dissertation submitted to the University of Dublin, Trinity College, +in partial fulfilment of the requirements for the degree of +Master of Science in Computer Science (Interactive Entertainment Technology) +University of Dublin, Trinity College"
46a4551a6d53a3cd10474ef3945f546f45ef76ee,Robust and continuous estimation of driver gaze zone by dynamic analysis of multiple face videos,"014 IEEE Intelligent Vehicles Symposium (IV) June 8-11, 2014. Dearborn, Michigan, USA 978-1-4799-3637-3/14/$31.00 ©2014 IEEE"
@@ -14405,13 +50322,122 @@ Yuzuko Utsumi*†, Tomoya Mizuno†, Masakazu Iwamura and Koichi Kise" Sound Joseph Roth Student Member, IEEE,, Xiaoming Liu, Member, IEEE, Arun Ross, Senior Member, IEEE, nd Dimitris Metaxas, Member, IEEE"
+46d0a519da10160a20a3070cc53e5b9401066526,Incremental Learning of Random Forests for Large-Scale Image Classification,"Incremental Learning of Random Forests for +Large-Scale Image Classification +Marko Ristin, Matthieu Guillaumin, Juergen Gall, Member, IEEE and Luc Van Gool, Member, IEEE"
46f2611dc4a9302e0ac00a79456fa162461a8c80,Spatio-Temporal Channel Correlation Networks for Action Classification,"for Action Classification Ali Diba1,4,(cid:63), Mohsen Fayyaz3,(cid:63), Vivek Sharma2, M.Mahdi Arzani4, Rahman Yousefzadeh4, Juergen Gall3, Luc Van Gool1,4 ESAT-PSI, KU Leuven, 2CV:HCI, KIT, Karlsruhe, 3University of Bonn, 4Sensifai"
+46c52f92e10fd2f2dddda162ad7995a1658e1245,Finding Socio-Textual Associations Among Locations,"Series ISSN: 2367-2005 +0.5441/002/edbt.2017.12"
+46a01565e6afe7c074affb752e7069ee3bf2e4ef,Local Descriptors Encoded by Fisher Vectors for Person Re-identification,"Local Descriptors Encoded by Fisher Vectors for Person +Re-identification +Bingpeng Ma, Yu Su, Fr´ed´eric Jurie +To cite this version: +Bingpeng Ma, Yu Su, Fr´ed´eric Jurie. Local Descriptors Encoded by Fisher Vectors for Person +Re-identification. 12th European Conference on Computer Vision (ECCV) Workshops, 2012, +Italy. pp.413-422, 2012, <10.1007/978-3-642-33863-2 41>. <hal-00806066> +HAL Id: hal-00806066 +https://hal.archives-ouvertes.fr/hal-00806066 +Submitted on 29 Mar 2013 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de"
+46994b489f7c673d031f6ef644e84ebe5d843d93,A learning-based visual saliency prediction model for stereoscopic 3D video (LBVS-3D),"A Learning-Based Visual Saliency Prediction +Model for Stereoscopic 3D Video (LBVS-3D) +Amin Banitalebi-Dehkordi, Mahsa T. Pourazad, and Panos Nasiopoulos"
+46386d4aa6a2b96106ab1d18658103622b24f9d8,Google Street View images support the development of vision-based driver assistance systems,"Google Street View Images Support the Development of +Vision-Based Driver Assistance Systems +Jan Salmen∗, Sebastian Houben∗, and Marc Schlipsing∗"
+462e4d0b35bf571bfc35dcd8e9bd589dca07a464,"Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation","Inverted Residuals and Linear Bottlenecks: Mobile Networks for +Classification, Detection and Segmentation +Mark Sandler Andrew Howard Menglong Zhu Andrey Zhmoginov Liang-Chieh Chen +{sandler, howarda, menglong, azhmogin, +Google Inc."
+46282f10271875647219b641dac2cc01c7dc8ab2,Psychopathic traits are associated with reduced fixations to the eye region of fearful faces.,"018, Vol. 127, No. 1, 43–50 +0021-843X/18/$12.00 +© 2018 American Psychological Association +http://dx.doi.org/10.1037/abn0000322 +Psychopathic Traits Are Associated With Reduced Fixations to the Eye +Region of Fearful Faces +Monika Dargis, Richard C. Wolf, and Michael Koenigs +University of Wisconsin–Madison +Impairments in processing fearful faces have been documented in both children and adults with +psychopathic traits, suggesting a potential mechanism by which psychopathic individuals develop callous +nd manipulative interpersonal and affective traits. Recently, research has demonstrated that psycho- +pathic traits are associated with reduced fixations to the eye regions of faces in samples of children and +ommunity-dwelling adults, however this relationship has not yet been established in an offender sample +with high levels of psychopathy. In the current study, we employed eye-tracking with paradigms +involving the identification and passive viewing of facial expressions of emotion, respectively, in a +sample of adult male criminal offenders (n ⫽ 108) to elucidate the relationship between visual processing +of fearful facial expressions and interpersonal and affective psychopathic traits. We found that the +interpersonal-affective traits of psychopathy were significantly related to fewer fixations to the eyes of +fear faces during the emotion recognition task. This association was driven particularly by the interper- +sonal psychopathic traits (e.g., egocentricity, deceitfulness), whereas fear recognition accuracy was"
+4669b079c3ca15aba08130c36ead597014f7341a,GrabCut-Based Human Segmentation in Video Sequences,"Sensors 2012, 12, 15376-15393; doi:10.3390/s121115376 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +GrabCut-Based Human Segmentation in Video Sequences +Antonio Hern´andez-Vela 1,2,⋆, Miguel Reyes 1,2, V´ıctor Ponce 1,2 and Sergio Escalera 1,2 +Departamento MAIA, Universitat de Barcelona, Gran Via 585, 08007 Barcelona, Spain; +E-Mails: (M.R.); (V.P.); (S.E.) +Centre de Visi´o per Computador, Campus UAB, Edifici O, 08193 Bellaterra, Barcelona, Spain +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +34-93-402-1897; Fax: +34-93-402-1601. +Received: 4 September 2012; in revised form: 1 November 2012 / Accepted: 6 November 2012 / +Published: 9 November 2012"
+463bfb0b55c085cda77c2c6e1583abb64baa5d0a,Learning Arbitrary Potentials in CRFs with Gradient Descent,"Learning Arbitrary Potentials in CRFs with Gradient Descent +M˚ans Larsson1 +Fredrik Kahl1,2 +Chalmers Univ. of Technology 2Lund Univ. +Shuai Zheng3 Anurag Arnab3 +Oxford Univ. +Philip Torr3 Richard Hartley4 +Australian National Univ."
+46f5bb35ea99c62320199b1f0924a4e7c0b001d3,Perspective-Aware CNN For Crowd Counting,"Perspective-Aware CNN For Crowd Counting +Miaojing Shi, Zhaohui Yang, Chao Xu, Member, IEEE, and Qijun Chen, Senior Member, IEEE"
+465b75fa4b84948e19d8bf2ebf4fe4459c3c87ae,A deformation model to reduce the effect of expressions in 3D face recognition,"Vis Comput (2011) 27: 333–345 +DOI 10.1007/s00371-010-0530-2 +O R I G I NA L A RT I C L E +A deformation model to reduce the effect of expressions in 3D face +recognition +Yueming Wang · Gang Pan · Jianzhuang Liu +Published online: 5 November 2010 +© Springer-Verlag 2010"
466a5add15bb5f91e0cfd29a55f5fb159a7980e5,Video Repeat Recognition and Mining by Visual Features,"Video Repeat Recognition and Mining by Visual Features Xianfeng Yang1and Qi Tian"
+46b031a3e368f25dd1e42f70f21165fef7b16de2,"Faces in the mirror, from the neuroscience of mimicry to the emergence of mentalizing.","doi 10.4436/jass.94037 +Vol. 94 (2016), pp. 113-126 +Faces in the mirror, from the neuroscience of mimicry +to the emergence of mentalizing +Antonella Tramacere & Pier Francesco Ferrari +University of Parma, Dep. of Neuroscience, via Volturno 39, 43100, Parma, Italy +e-mail: +Summary - In the current opinion paper, we provide a comparative perspective on specific aspects +of primate empathic abilities, with particular emphasis on the mirror neuron system associated with +mouth/face actions and expression. Mouth and faces can be very salient communicative classes of stimuli +that allow an observer access to the emotional and physiological content of other individuals. We thus +describe patterns of activations of neural populations related to observation and execution of specific +mouth actions and emotional facial expressions in some species of monkeys and in humans. Particular +ttention is given to dynamics of face-to-face interactions in the early phases of development and to +the differences in the anatomy of facial muscles among different species of primates. We hypothesize +that increased complexity in social environments and patterns of social development have promoted +specializations of facial musculature, behavioral repertoires related to production and recognition of +facial emotional expression, and their neural correlates. In several primates, mirror circuits involving +parietal-frontal regions, insular regions, cingulate cortices, and amygdala seem to support automatic +forms of embodied empathy, which probably contribute to facial mimicry and behavioural synchrony."
46f3b113838e4680caa5fc8bda6e9ae0d35a038c,Automated Dermoscopy Image Analysis of Pigmented Skin Lesions,"Cancers 2010, 2, 262-273; doi:10.3390/cancers2020262 OPEN ACCESS ancers @@ -14430,6 +50456,57 @@ ACS, Advanced Computer Systems, Via della Bufalotta 378, 00139 Rome, Italy Fax: +390815569693. Received: 23 February 2010; in revised form: 15 March 2010 / Accepted: 25 March 2010 / Published: 26 March 2010"
+4602bbec65b0c718d5887fdf2381fb7cee77a64d,Explicit Occlusion Modeling for 3D Object Class Representations,"Explicit Occlusion Modeling for 3D Object Class Representations +M. Zeeshan Zia1, Michael Stark2, and Konrad Schindler1 +Photogrammetry and Remote Sensing, ETH Z¨urich, Switzerland +Stanford University and Max Planck Institute for Informatics"
+46471a285b1d13530f1885622d4551b48c19fc67,Generating Artificial Data for Private Deep Learning,"Generating Artificial Data for Private Deep Learning +Ecole Polytechnique Fédérale de Lausanne +Ecole Polytechnique Fédérale de Lausanne +Aleksei Triastcyn +Artificial Intelligence Laboratory +Lausanne, Switzerland +Boi Faltings +Artificial Intelligence Laboratory +Lausanne, Switzerland"
+46d728356b5090bc28461b30cb21a08c3a690195,"Deep Multi-patch Aggregation Network for Image Style, Aesthetics, and Quality Estimation","Deep Multi-Patch Aggregation Network +for Image Style, Aesthetics, and Quality Estimation +Xin Lu(cid:63) +James Z. Wang(cid:63) +(cid:63)The Pennsylvania State University, University Park, Pennsylvania +Zhe Lin† Xiaohui Shen† Radom´ır Mˇech† +Adobe Research, San Jose, California +{xinlu, {zlin, xshen,"
+46a553e670027e838716e5a1a39577d7cd7a4893,Face Recognition using TSF Model and DWT based Multilevel Illumination Normalization,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 +Face Recognition using TSF Model and DWT based +Multilevel Illumination Normalization +Midhun Madhusoodanan1, Jini Cheriyan2 +M.Tech Scholar (Signal Processing), Department of Electronics and Communication, TKM Institute of Technology, +MusaliarHills, Karuvelil P.O, Ezhukone, Kollam-691505, Kerala, India +Assistant Professor, Department of Electronics and Communication, TKM Institute of Technology, +Musaliar Hills, Karuvelil P.O, Ezhukone, Kollam-691505, Kerala, India +recognition +is a"
+4684c487758df6b6bf4b69f3fe22e1aad874378a,A Discriminative Voting Scheme for Object Detection using Hough Forests,"VIJAY KUMAR B G, IOANNIS PATRAS: +A Discriminative Voting Scheme for Object +Detection using Hough Forests +Vijay Kumar.B.G +Dr Ioannis Patras +Multimedia Vision Research Group +Queen Mary, UoL +London, UK"
+46df854f57b6553b4b3238779e46bf2a3a3fffcf,3D Face Recognition using ICP and Geodesic Computation Coupled Approach,"D Face Recognition using ICP and Geodesic +Computation Coupled Approach +Karima Ouji‡, Boulbaba Ben Amor§, Mohsen Ardabilian§, +Faouzi Ghorbel‡, and Liming Chen§ +§LIRIS, Laboratoire d’InfoRmatique en Image et Systmes d’information, +6, av. Guy de Collongue, 69134 Ecully, France. +GRIFT, Groupe de Recherche en Images et Formes de Tunisie, +Ecole Nationale des Sciences de l’Informatique, Tunisie. +Key words: 3D face recognition, Iterative Closest Point, Geodesics computa- +tion, biometric evaluation"
46538b0d841654a0934e4c75ccd659f6c5309b72,A Novel Approach to Generate Face Biometric Template Using Binary Discriminating Analysis,"Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.1, February 2014 A NOVEL APPROACH TO GENERATE FACE BIOMETRIC TEMPLATE USING BINARY @@ -14457,15 +50534,129 @@ Moradabad, U.P., INDIA E-mail: E-mail: E-mail:"
+468aaa87ccdba65f3115bd0864f7772b6706c00e,A Survey on Heterogeneous Face Matching : NIR Images to VIS Images,"International Journal of Computer Applications (0975 – 8887) +Emerging Trends In Computing 2016 +Heterogeneous Face Matching: NIR images to VIS +Images +Sandhya R.Waddhavane +M.E Student +Department of Computer Engineering +KKWIEER, Nashik, India. +Savitribai Phule Pune University,Pune +S.M.Kamalapur, PhD +Associate Professor +Department of Computer Engineering +KKWIEER, Nashik, India. +Savitribai Phule Pune University,Pune"
+46c3e8c2b2042b193659c0a613adc72100a2f301,Vision for Robotics By Danica Kragic and Markus Vincze,"Foundations and Trends R(cid:1) in +Robotics +Vol. 1, No. 1 (2010) 1–78 +(cid:1) 2009 D. Kragic and M. Vincze +DOI: 10.1561/2300000001 +Vision for Robotics +By Danica Kragic and Markus Vincze +Contents +Introduction +.1 Scope and Outline +Historical Perspective +.1 Early Start and Industrial Applications +.2 Biological Influences and Affordances +.3 Vision Systems +What Works +.1 Object Tracking and Pose Estimation +.2 Visual Servoing–Arms and Platforms +.3 Reconstruction, Localization, Navigation, and +Visual SLAM +.4 Object Recognition"
+4679f4a7da1cf45323c1c458b30d95dbed9c8896,Recognizing Facial Expressions Using Model-Based Image Interpretation,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
4682fee7dc045aea7177d7f3bfe344aabf153bd5,Tabula rasa: Model transfer for object category detection,"Tabula Rasa: Model Transfer for Object Category Detection Yusuf Aytar & Andrew Zisserman, Department of Engineering Science Oxford (Presented by Elad Liebman)"
+460845e06ca99f292fa2265beb4e535d20ba16f8,Object Detection for Comics using Manga109 Annotations,"Object Detection for Comics using Manga109 +Annotations +Toru Ogawa · Atsushi Otsubo · Rei +Narita · Yusuke Matsui · Toshihiko +Yamasaki · Kiyoharu Aizawa"
+46106d9f9d9b90401b7984794536e2f45fff1dbe,Learning Distance Functions for Automatic Annotation of Images,"Learning Distance Functions for +Automatic Annotation of Images +Josip Krapac and Fr´ed´eric Jurie +INRIA Rhˆone-Alpes, 655, Avenue de l’Europe, 38334 Saint Ismier Cedex, France"
+463a1ca5f819af35e71ae47ea0e57293691507d3,Soft Biometrics Classification Using Denoising Convolutional Autoencoders and Support Vector Machines,"Soft Biometrics Classification Using Denoising +Convolutional Autoencoders and Support Vector +Machines +Nelson Marcelo Romero Aquino1, Matheus Gutoski2 +Leandro Takeshi Hattori3 and Heitor Silv´erio Lopes4 +Federal University of Technology - Paran´a +Av. Sete de Setembro, 3165 - Rebou¸cas CEP 80230-901"
+4634bf44a0c994e2bed89686225f8cef601a0224,NLM at ImageCLEF 2018 Visual Question Answering in the Medical Domain,"NLM at ImageCLEF 2018 Visual Question +Answering in the Medical Domain +Asma Ben Abacha, Soumya Gayen, Jason J Lau, Sivaramakrishnan +Rajaraman, and Dina Demner-Fushman +Lister Hill National Center for Biomedical Communications, +National Library of Medicine, Bethesda, MD, USA."
+469d249a40639d4ffb62abfb2c25f5aab0812fa4,Image Inspired Poetry Generation in XiaoIce,"Image Inspired Poetry Generation in XiaoIce∗ +Wen-Feng Cheng1,2, Chao-Chung Wu2, Ruihua Song1, Jianlong Fu1, Xing Xie1, Jian-Yun Nie3 +{wencheng, rsong, jianf, +Microsoft, 2National Taiwan University, 3University of Montreal"
+466212a84d5b60f4517e8ab3e4473c3c9e081897,Thermal-Visible Registration of Human Silhouettes: a Similarity Measure Performance Evaluation,"Thermal-Visible Registration of Human Silhouettes: a +Similarity Measure Performance Evaluation +Guillaume-Alexandre Bilodeaua,∗, Atousa Torabib, Pierre-Luc St-Charlesa, +Dorra Riahia +LITIV Lab., Department of Computer and Software Engineering, +´EcolePolytechnique de Montr´eal, +P.O. Box 6079, Station Centre-ville, Montr´eal +Qu´ebec, Canada, H3C 3A7 +LISA, Dept. IRO, +Universit´e de Montr´eal, +Montr´eal, Qu´ebec, Canada, H2C 3J7"
+2c9179fec33f69a5c1a453034dc7d3d3302839d3,Exploiting Hierarchical Dense Structures on Hypergraphs for Multi-Object Tracking,"Exploiting Hierarchical Dense Structures +on Hypergraphs for Multi-Object Tracking +Longyin Wen, Zhen Lei, Siwei Lyu, Stan Z. Li, Fellow, IEEE, and Ming-Hsuan Yang"
+2cdc1b728c90d4da31f924879a39d00008d52daa,A Side of Data with My Robot: Three Datasets for Mobile Manipulation in Human Environments,"A Side of Data with My Robot: Three Datasets for Mobile Manipulation in Human Environments +Matei Ciocarlie, Member, IEEE, Caroline Pantofaru, Member, IEEE, Kaijen Hsiao, Member, IEEE, +Gary Bradski, Member, IEEE, Peter Brook, and Ethan Dreyfuss"
+2ce2560cf59db59ce313bbeb004e8ce55c5ce928,Anthropometric 3D Face Recognition,"Int J Comput Vis +DOI 10.1007/s11263-010-0360-8 +Anthropometric 3D Face Recognition +Shalini Gupta · Mia K. Markey · Alan C. Bovik +Received: 3 July 2009 / Accepted: 20 May 2010 +© Springer Science+Business Media, LLC 2010"
+2cc0e431d7cc0bcb926b9a19e7be8a3592d670d4,NovaMedSearch: a multimodal search engine for medical case-based retrieval,"NovaMedSearch: A multimodal search engine for medical +ase-based retrieval +André Mourão +Flávio Martins +Faculdade de Ciências e Tecnologia +Universidade Nova de Lisboa +Departamento de Informática +Caparica, Portugal"
2c8743089d9c7df04883405a31b5fbe494f175b4,Real-time full-body human gender recognition in (RGB)-D data,"Washington State Convention Center Seattle, Washington, May 26-30, 2015 978-1-4799-6922-7/15/$31.00 ©2015 IEEE"
+2c5ff99e7e9769677df3eeab9f198e3ead016c35,Registration of 3D facial surfaces using covariance matrix pyramids,"Anchorage Convention District +May 3-8, 2010, Anchorage, Alaska, USA +978-1-4244-5040-4/10/$26.00 ©2010 IEEE"
2c93c8da5dfe5c50119949881f90ac5a0a4f39fe,Advanced local motion patterns for macro and micro facial expression recognition,"Advanced local motion patterns for macro and micro facial expression recognition B. Allaerta,∗, IM. Bilascoa, C. Djerabaa @@ -14520,6 +50711,12 @@ Email: Email: Department of Electrical Engineering - EESC/USP Email:"
+2cd03c6e78d09bb98872bb34bb70e08c32dc5f7e,Pedestrian Alignment Network for Large-scale Person Re-identification,"Noname manuscript No. +(will be inserted by the editor) +Pedestrian Alignment Network for +Large-scale Person Re-identification +Zhedong Zheng · Liang Zheng · Yi Yang +Received: date / Accepted: date"
2c883977e4292806739041cf8409b2f6df171aee,Are Haar-Like Rectangular Features for Biometric Recognition Reducible?,"Aalborg Universitet Are Haar-like Rectangular Features for Biometric Recognition Reducible? Nasrollahi, Kamal; Moeslund, Thomas B. @@ -14560,12 +50757,64 @@ reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted omponent of this work in other works must be obtained from"
+2c98165dd72bac574ed463b00f1dd4c276808cb4,Efficient Object Pixel-Level Categorization Using Bag of Features,"Efficient Object Pixel-Level Categorization using +Bag of Features +David Aldavert1, Arnau Ramisa2, Ricardo Toledo1, and Ramon Lopez de +Mantaras2 +Computer Vision Center (CVC) +Dept. Ci`encies de la Computaci´o +Universitat Aut`onoma de Barcelona (UAB), 08193, Bellaterra, Spain +Artificial Intelligence Research Institute (IIIA-CSIC) +Campus de la UAB, 08193, Bellaterra, Spain"
+2c07d9a383e0bb7e1c8ba07084ba8bcf71af2aad,Robust Ear Recognition via Nonnegative Sparse Representation of Gabor Orientation Information,"Hindawi Publishing Corporation +e Scientific World Journal +Volume 2014, Article ID 131605, 11 pages +http://dx.doi.org/10.1155/2014/131605 +Research Article +Robust Ear Recognition via Nonnegative Sparse Representation +of Gabor Orientation Information +Baoqing Zhang, Zhichun Mu, Hui Zeng, and Shuang Luo +School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China +Correspondence should be addressed to Zhichun Mu; muzc +Received 21 December 2013; Accepted 18 January 2014; Published 24 February 2014 +Academic Editors: S. Kobashi and A. Materka +Copyright © 2014 Baoqing Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, +which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +Orientation information is critical to the accuracy of ear recognition systems. In this paper, a new feature extraction approach is +investigated for ear recognition by using orientation information of Gabor wavelets. The proposed Gabor orientation feature can +not only avoid too much redundancy in conventional Gabor feature but also tend to extract more precise orientation information of +the ear shape contours. Then, Gabor orientation feature based nonnegative sparse representation classification (Gabor orientation ++ NSRC) is proposed for ear recognition. Compared with SRC in which the sparse coding coefficients can be negative, the +nonnegativity of NSRC conforms to the intuitive notion of combining parts to form a whole and therefore is more consistent"
2c5d1e0719f3ad7f66e1763685ae536806f0c23b,AENet: Learning Deep Audio Features for Video Analysis,"AENet: Learning Deep Audio Features for Video Analysis Naoya Takahashi, Member, IEEE, Michael Gygli, Member, IEEE, and Luc Van Gool, Member, IEEE"
2c8f24f859bbbc4193d4d83645ef467bcf25adc2,Classification in the Presence of Label Noise: A Survey,"Classification in the Presence of Label Noise: a Survey Benoît Frénay and Michel Verleysen, Member, IEEE"
+2c564f5241b0905baafc3677e7ca15c27fd2c6e7,An Integrated Approach to Contextual Face Detection,"AN INTEGRATED APPROACH TO CONTEXTUAL FACE +DETECTION. +Santi Segu´ı1, Michal Drozdzal1,2, Petia Radeva1,2 and Jordi Vitri`a1,2 +Computer Vision Center, Universitat Aut`onoma de Barcelona, Bellaterra, Spain +Dept. Matem`atica Aplicada i An`alisi, Universitat de Barcelona, Barcelona, Spain +{ssegui, michal, petia, +Keywords: +face detection, object detection."
+2c7932c2096669113328a75d1ad1d1bfb8f86ad0,Multi30K: Multilingual English-German Image Descriptions,"Proceedings of the 5th Workshop on Vision and Language, pages 70–74, +Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
+2c786b32a621a52fc7d00499e4b056f149a4fba7,Face Recognition with Decision Tree-Based Local Binary Patterns,"Face Recognition with Decision Tree-based Local +Binary Patterns +Daniel Maturana, Domingo Mery and ´Alvaro Soto +Department of Computer Science, Pontificia Universidad Cat´olica de Chile"
+2cf7383e238fe37516e2607c4741f79a230834bf,A new Sparse Coding Approach for Human Face and Action Recognition,"A new Sparse Coding Approach for Human Face and Action +Recognition +Mohsen Nikpour* +Department of Electrical and Computer Engineering, Babol Noushirvani University of Technology, Babol, Iran +Mohammad Reza Karami Molaei +Department of Electrical and Computer Engineering, Babol Noushirvani University of Technology, Babol, Iran +Reza Ghaderi +Department of nuclear Engineering, Shahid Beheshti University of Tehran, Tehran, Iran +Received: 27/Jul/2016 Revised: 07/Jan/2017 Accepted: 14/Jan/2017"
2cdd5b50a67e4615cb0892beaac12664ec53b81f,Mirror mirror: crowdsourcing better portraits,"To appear in ACM TOG 33(6). Mirror Mirror: Crowdsourcing Better Portraits Jun-Yan Zhu1 @@ -14577,13 +50826,46 @@ University of California, Berkeley1 Adobe2 Figure 1: We collect thousands of portraits by capturing video of a subject while they watch movie clips designed to elicit a range of positive emotions. We use crowdsourcing and machine learning to train models that can predict attractiveness scores of different expressions. These models can be used to select a subject’s best expressions across a range of emotions, from more serious professional portraits to big smiles."
+2c5b5a5e4b8cd001e535118c2fa90bff95d51648,Combining Facial Dynamics With Appearance for Age Estimation,"Combining Facial Dynamics With Appearance +for Age Estimation +Hamdi Dibeklio˘glu, Member, IEEE, Fares Alnajar, Student Member, IEEE, +Albert Ali Salah, Member, IEEE, and Theo Gevers, Member, IEEE"
2cdde47c27a8ecd391cbb6b2dea64b73282c7491,Order-aware Convolutional Pooling for Video Based Action Recognition,"ORDER-AWARE CONVOLUTIONAL POOLING FOR VIDEO BASED ACTION RECOGNITION Order-aware Convolutional Pooling for Video Based Action Recognition Peng Wang, Lingqiao Liu, Chunhua Shen, and Heng Tao Shen"
+2cc8371c483f76fff65a5fb1c9cc89e974ce83ea,Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks,"Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural +Networks +Michael Gygli +gifs.com +Zurich, Switzerland"
+2cad358676854505517307314728e8920fe53d77,Mixture of Ridge Regressors for Human Pose Estimation,"#1754 +CVPR 2012 Submission #1754. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. +#1754 +Mixture of Ridge Regressors +for Human Pose Estimation +Anonymous CVPR submission +Paper ID 1754"
2cf5f2091f9c2d9ab97086756c47cd11522a6ef3,MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation,"MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation Xucong Zhang, Yusuke Sugano∗, Mario Fritz, Andreas Bulling"
+2c72096bbecd70000f919b1cec3f31a649c94fd5,Neural Network Interpretation via Fine Grained Textual Summarization,"Neural Network Interpretation via Fine-Grained Textual Summarization +Pei Guo, Connor Anderson, Kolton Pearson, Ryan Farrell +Brigham Young University"
+2c2bf22e2f0a1817475aefb37e0c4e0404e8d479,Structured Prediction of 3D Human Pose with Deep Neural Networks,"TEKIN ET AL.: STRUCTURED PREDICTION OF 3D HUMAN POSE +Structured Prediction of 3D Human Pose +with Deep Neural Networks +Bugra Tekin∗1 +Isinsu Katircioglu∗1 +Mathieu Salzmann1 +Vincent Lepetit2 +Pascal Fua1 +CVLab +EPFL, +Lausanne, Switzerland +CVARLab +TU Graz, +Graz, Austria"
2c4b96f6c1a520e75eb37c6ee8b844332bc0435c,Automatic Emotion Recognition in Robot-Children Interaction for ASD Treatment,"Automatic Emotion Recognition in Robot-Children Interaction for ASD Treatment Marco Leo, Marco Del Coco, Pierluigi Carcagn`ı, Cosimo Distante @@ -14595,6 +50877,28 @@ Giuseppe Palestra Univerisita’ di Bari Marine Institute, via Torre Bianca, 98164 Messina Italy Via Orabona 4, 70126 Bari, Italy"
+2cc17e1ccb5f1f67f8ce882e683d8c66475330be,Multitarget tracking with the von Mises-Fisher filter and probabilistic data association,"JOURNAL OF ADVANCES IN INFORMATION FUSION +Multitarget tracking with the von Mises-Fisher filter +nd probabilistic data association +Ivan Markovi´c, Mario Bukal, Josip ´Cesi´c and Ivan Petrovi´c"
+2c0a71b5e111d2c7d99c3f23989d317a0d845adc,N-best maximal decoders for part models,"N-best maximal decoders for part models +Dennis Park Deva Ramanan +UC Irvine"
+795cea6b95af22238600aa129b1975e83c531858,Sentence Directed Video Object Codetection,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +Sentence Directed Video Object Codetection +Haonan Yu, Student Member, IEEE and Jeffrey Mark Siskind, Senior Member, IEEE"
+7950d67f7104e9bd82d957f0ed80f11982802397,Coupled Action Recognition and Pose Estimation from Multiple Views,"Noname manuscript No. +(will be inserted by the editor) +Coupled Action Recognition and Pose Estimation from +Multiple Views +Angela Yao (cid:1) Juergen Gall (cid:1) Luc Van Gool +Received: date / Accepted: date"
+79d3e7321e50be745bef92ba1405b486bd1f133d,Emotion Recognition in Simulated Social Interactions,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2018.2799593, IEEE +> TAFFC-2017-04-0117.R1 < +Transactions on Affective Computing +Emotion Recognition in Simulated Social +Interactions +C. Mumenthaler, D. Sander, and A. S. R. Manstead"
790aa543151312aef3f7102d64ea699a1d15cb29,Confidence-Weighted Local Expression Predictions for Occlusion Handling in Expression Recognition and Action Unit Detection,"Confidence-Weighted Local Expression Predictions for Occlusion Handling in Expression Recognition and Action Unit detection @@ -14603,8 +50907,66 @@ Kevin Bailly1 Séverine Dubuisson1 Sorbonne Universités, UPMC Univ Paris 06, CNRS, ISIR UMR 7222 place Jussieu 75005 Paris"
+791eb376d4db96376eba3ef804657c5f0ba7229a,SAFE: Secure authentication with Face and Eyes,"SAFE: Secure Authentication with Face and Eyes +Arman Boehm(cid:91), Dongqu Chen§, Mario Frank(cid:91), Ling Huang†, +Cynthia Kuo(cid:93), Tihomir Lolic(cid:91), Ivan Martinovic(cid:63), Dawn Song(cid:91) +(cid:91) University of California, Berkeley; † Intel Labs; (cid:93) Nokia Research; (cid:63) Oxford University; § Yale University"
+796d5d1f6052cd600e183471a2354751883d8d5d,Feature Extraction Techniques Implementation Review and Case Study,"ISSN: 2278 – 909X +International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE) +Volume 4, Issue 12, December 2015 +Feature Extraction Techniques +Implementation Review and Case Study +Uma Bhati +Department of Computer Science & Engineering +JSS Academy of Technical Education +Noida-201301 +Krishna Nand Chaturvedi +Department of Computer Science & Engineering +JSS Academy of Technical Education +Noida-201301 +utilizing +recognition"
+7954a1bd6e693da8f2ae69ad01233e937d600e9b,The Lov\'asz-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks,"Accepted as a conference paper at CVPR 2018 +The Lov´asz-Softmax loss: A tractable surrogate for the optimization of the +intersection-over-union measure in neural networks +Maxim Berman Amal Rannen Triki Matthew B. Blaschko +Dept. ESAT, Center for Processing Speech and Images +KU Leuven, Belgium"
+792e656d2297d3b00da73c7a606eb6f539311c25,Force from Motion: Decoding Control Force of Activity in a First Person Video,"Force from Motion: Decoding Control Force of +Activity in a First Person Video +Hyun Soo Park and Jianbo Shi"
79f6a8f777a11fd626185ab549079236629431ac,Pradeep RavikumarDiscriminative Object Categorization with External Semantic Knowledge,"Copyright Sung Ju Hwang"
+7910d3a86e03f4c41fbbe8029fab115547be151b,Taming Adversarial Domain Transfer with Structural Constraints for Image Enhancement,"Taming Adversarial Domain Transfer +with Structural Constraints for Image Enhancement +Elias Vansteenkiste and Patrick Kern +Brighter.AI +Torstrasse 177, Berlin +{elias, +Figure 1: Our domain transfer techniques applied to the night-to-day, removing rain and removing fog applications"
+79fc892abaf44a84a758268efd4d1b9e6b64ecf5,Leveraging Random Label Memorization for Unsupervised Pre-Training,"Leveraging Random Label Memorization for Unsupervised Pre-Training +Vinaychandran Pondenkandath * 1 Michele Alberti * 1 Sammer Puran 1 Rolf Ingold 1 Marcus Liwicki 1 2"
+79e39f3d0577b9c5a47b93eb6d75bec04d14c07a,Person tracking and following with 2D laser scanners,"Person Tracking and Following with 2D Laser Scanners +Angus Leigh1, Joelle Pineau1, Nicolas Olmedo2, and Hong Zhang2"
+794cf037dac115755cd15295d8c5fc1c00242548,The City Infant Faces Database: A validated set of infant facial expressions,"Behav Res (2018) 50:151–159 +DOI 10.3758/s13428-017-0859-9 +The City Infant Faces Database: A validated set of infant +facial expressions +Rebecca Webb 1 & Susan Ayers 1 & Ansgar Endress 2 +Published online: 15 February 2017 +# The Author(s) 2017. This article is published with open access at Springerlink.com"
+79b50cd468fcdba8f3c841c9d28d84ff66fd97fd,What do Deep Networks Like to See?,"What do Deep Networks Like to See? +Sebastian Palacio∗ +Federico Raue Damian Borth Andreas Dengel +Joachim Folz∗ +German Research Center for Artificial Intelligence (DFKI) +J¨orn Hees +TU Kaiserslautern"
+79bd7fd2b40aadea84bced07f813ffc28c88bc85,Low Rank Matrix Recovery with Simultaneous Presence of Outliers and Sparse Corruption,"Low Rank Matrix Recovery with Simultaneous +Mostafa Rahmani, Student Member, IEEE and George K. Atia, Member, IEEE"
+79c959833ff49f860e20b6654dbf4d6acdee0230,Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond,"Hide-and-Seek: A Data Augmentation Technique +for Weakly-Supervised Localization and Beyond +Krishna Kumar Singh, Hao Yu, Aron Sarmasi, Gautam Pradeep, and Yong Jae Lee, Member, IEEE"
79b669abf65c2ca323098cf3f19fa7bdd837ff31,Efficient tensor based face recognition,"Deakin Research Online This is the published version: Rana, Santu, Liu, Wanquan, Lazarescu, Mihai and Venkatesh, Svetha 2008, Efficient tensor @@ -14618,12 +50980,248 @@ material for advertising or promotional purposes or for creating new collective resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Copyright : 2008, IEEE"
+790bce6cbe30ef9bc4431c988d0d747da1c6bb1d,Salient Object Detection Using Window Mask Transferring with Multi-layer Background Contrast,"Salient Object Detection using Window Mask +Transferring with Multi-layer Background +Contrast +Quan Zhou1, Shu Cai1, Shaojun Zhu2, and Baoyu Zheng1 +College of Telecom & Inf Eng, Nanjing Univ of Posts & Telecom, P.R. China +Dept. of Comput & Inf Sci, University of Pennsylvania Philadelphia, PA, USA"
+79f02a006c77f2d7fece8302bf54d851269a515a,A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor,"Article +A Study of Deep CNN-Based Classification of Open +nd Closed Eyes Using a Visible Light Camera Sensor +Ki Wan Kim, Hyung Gil Hong, Gi Pyo Nam and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (K.W.K.); (H.G.H.); (G.P.N.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 2 June 2017; Accepted: 28 June 2017; Published: 30 June 2017"
+79fc3c10ce0d0f48b25c8cf460048087c97e2e90,Variational Bi-domain Triplet Autoencoder,"Variational learning across domains with triplet +information +Rita Kuznetsova1,2, Oleg Bakhteev1,2 and Alexandr Ogaltsov2,3 +Moscow Institute of Physics and Technology +National Research University Higher School of Economics +{rita.kuznetsova, +Antiplagiat Company"
79dd787b2877cf9ce08762d702589543bda373be,Face detection using SURF cascade,"Face Detection Using SURF Cascade Jianguo Li, Tao Wang, Yimin Zhang Intel Labs China"
+7917a7549f00306db8775d2d559460fc93dbde5a,DaP 2018 Proceedings of the Workshop on Dialogue and Perception,"DaP 2018 +Proceedings of the Workshop on +Dialogue and Perception +Christine Howes, Simon Dobnik and Ellen Breitholtz (eds.) +Gothenburg, 14–15 June 2018"
+7985ac55e170273dd0ffa6bd756e588bab301d57,Mind's eye: A recurrent visual representation for image caption generation,"Mind’s Eye: A Recurrent Visual Representation for Image Caption Generation +Xinlei Chen1, C. Lawrence Zitnick2 +Carnegie Mellon University. 2Microsoft Research Redmond. +A good image description is often said to “paint a picture in your mind’s +eye.” The creation of a mental image may play a significant role in sentence +omprehension in humans [3]. In fact, it is often this mental image that is +remembered long after the exact sentence is forgotten [5, 7]. As an illus- +trative example, Figure 1 shows how a mental image may vary and increase +in richness as a description is read. Could computer vision algorithms that +omprehend and generate image captions take advantage of similar evolving +visual representations? +Recently, several papers have explored learning joint feature spaces for +images and their descriptions [2, 4, 9]. These approaches project image +features and sentence features into a common space, which may be used +for image search or for ranking image captions. Various approaches were +used to learn the projection, including Kernel Canonical Correlation Anal- +ysis (KCCA) [2], recursive neural networks [9], or deep neural networks +[4]. While these approaches project both semantics and visual features to +common embedding, they are not able to perform the inverse projection. +That is, they cannot generate novel sentences or visual depictions from the"
+79d13b74952449667c769be76dac9065db1acc22,"Fine-grained Recognition: Data, Recognition, and Application a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy","FINE-GRAINED RECOGNITION: +DATA, RECOGNITION, AND APPLICATION +A DISSERTATION +SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE +AND THE COMMITTEE ON GRADUATE STUDIES +OF STANFORD UNIVERSITY +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +DOCTOR OF PHILOSOPHY +Jonathan Krause +October 2016"
+796e333796024acf662fe76c4761607eaaa98a5d,Nested multi-instance image classification,"Nested multi-instance image classification +Anonymous Authors"
+794fd0fb684f90704e108677edb40d3ff6a85f8c,"EyeLad: Remote Eye Tracking Image Labeling Tool - Supportive Eye, Eyelid and Pupil Labeling Tool for Remote Eye Tracking Videos","EyeLad:Remote Eye Tracking Image Labeling Tool +Supportive eye, eyelid and pupil labeling tool for remote eye tracking videos. +Wolfgang Fuhl1, Thiago Santini1, David Geisler1, Thomas K¨ubler1, and Enkelejda Kasneci1 +{wolfgang.fuhl, thiago.santini, david.geisler, thomas.kuebler, +Perception Engineering, University of Tbingen, Tbingen, Germany +Keywords: +data labeling, image processing, feature tracking, object detection, eye tracking data, remote eye tracking"
+793e896c2f66fb66bfc6c834f2678cf349af4e20,Incorporating Computation Time Measures During Heterogeneous Features Selection in a Boosted Cascade People Detector,"Incorporating Computation Time Measures during +Heterogeneous Features Selection in a Boosted Cascade +People Detector +Alhayat Ali Mekonnen, Frédéric Lerasle, Ariane Herbulot, Cyril Briand +To cite this version: +Alhayat Ali Mekonnen, Frédéric Lerasle, Ariane Herbulot, Cyril Briand. Incorporating Computation +Time Measures during Heterogeneous Features Selection in a Boosted Cascade People Detector. Inter- +national Journal of Pattern Recognition and Artificial Intelligence, World Scientific Publishing, 2016, +0 (8), pp.1655022. <10.1142/S0218001416550223>. <hal-01300472> +HAL Id: hal-01300472 +https://hal.archives-ouvertes.fr/hal-01300472 +Submitted on 11 Apr 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents"
+7960336aed2aa701c147ccfe36d153046f1500bc,Occlusion Reasoning for Multiple Object Visual Tracking,"OCCLUSION REASONING +FOR MULTIPLE OBJECT VISUAL TRACKING +ZHENG WU +Dissertation submitted in partial fulfillment +of the requirements for the degree of +Doctor of Philosophy +BOSTON +UNIVERSITY"
+79f12f28b060221f3b80ea1b7b16779ef9362ca8,Investigations of face expertise in the social developmental disorders.,"Jason J.S. Barton, +MD, PhD, FRCPC +Rebecca L. Hefter, BSc +Mariya V. +Cherkasova, BSc +Dara S. Manoach, +Address correspondence and +reprint requests to Dr. Jason +J.S. Barton, Neuro- +ophthalmology Section D, VGH +Eye Care Center, 2550 Willow +Street, Vancouver, BC Canada +V5Z 3N9 +Investigations of face expertise in the +social developmental disorders"
+79e7f1e13e8aafee6558729804cf1284134815b3,Deep Representation Learning for Domain Adaptation of Semantic Image Segmentation,"BENBIHI, GEIST, PRADALIER: DEEP REPRESENTATION LEARNING +Deep Representation Learning for Domain +Adaptation of Semantic Image Segmentation +Assia Benbihi1 +Matthieu Geist2 +Cedric Pradalier1 +UMI 2958 GT-CNRS – GeorgiaTech +Lorraine +Metz, France +Université de Lorraine +CNRS LIEC UNR 7360, +Metz, France"
+79335495e54446541a3655d145911beba7c29d7d,The face inversion effect in opponent-stimulus rivalry,"ORIGINAL RESEARCH ARTICLE +published: 15 May 2014 +doi: 10.3389/fnhum.2014.00295 +The face inversion effect in opponent-stimulus rivalry +Malte Persike*, Bozana Meinhardt-Injac and Günter Meinhardt +Research Methods and Statistics, Department of Psychology, Institute of Psychology, Johannes Gutenberg University Mainz, Mainz, Germany +Edited by: +Davide Rivolta, University of East +London, UK +Reviewed by: +Guillaume A. Rousselet, University +of Glasgow, UK +Timo Stein, Charité +Universitätsmedizin Berlin, Germany +*Correspondence: +Malte Persike, Research Methods +nd Statistics, Department of +Psychology, Institute of Psychology, +Johannes Gutenberg University +Mainz, Mainz, Rheinland-Pfalz,"
+7918698ffa86cdd6123bc2f1f613be1ab38c0d2f,Learning to Recognize Faces in Realistic Conditions,"Learning to Recognize Faces in Realistic Conditions +Anonymous Author(s) +Affiliation +Address +email"
+79ade61f677dcadfc2b46444d2e0275d25ca1f06,Nonnegative Tucker decomposition with alpha-divergence,"NONNEGATIVE TUCKER DECOMPOSITION WITH ALPHA-DIVERGENCE +Yong-Deok Kim §, Andrzej Cichocki †, Seungjin Choi § +§ Department of Computer Science, POSTECH, Korea +Brain Science Institute, RIKEN, Japan"
+795bd86fc22ec544e7cd9b3d3c2ccabe72de54ec,Max Margin AND / OR Graph Learning for Efficient Articulated Object,"Noname manuscript No. +(will be inserted by the editor) +Max Margin AND/OR Graph Learning for Efficient Articulated Object +Parsing +Long (Leo) Zhu · Yuanhao Chen · Chenxi Lin · Alan Yuille +the date of receipt and acceptance should be inserted later"
+79815f31f42708fd59da345f8fa79f635a070730,Autoregressive Quantile Networks for Generative Modeling,"Autoregressive Quantile Networks for Generative Modeling +Georg Ostrovski * 1 Will Dabney * 1 R´emi Munos 1"
+2d919473cf43e2522b2366271b778ce6ce7dc75c,Appearance-Based Re-identification of Humans in Low-Resolution Videos Using Means of Covariance Descriptors,"Appearance-based Re-Identification of Humans in Low-Resolution Videos +using Means of Covariance Descriptors +Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB +J¨urgen Metzler +76131 Karlsruhe, Germany"
+2d8ffa4a27b3e3b792b2d2516bbcb1a47c114846,Multi-view Laplacian Eigenmaps Based on Bag-of-Neighbors For RGBD Human Emotion Recognition,"JOURNAL OF LATEX CLASS FILES +Multi-view Laplacian Eigenmaps +Based on Bag-of-Neighbors +For RGBD Human Emotion Recognition +Shenglan Liu, Member, IEEE, Shuai Guo, Hong Qiao, Senior Member, IEEE, Yang Wang, Bin Wang, +Wenbo Luo, Mingming Zhang, Keye Zhang, and Bixuan Du"
+2dfc48168c0de9e6c7135293c95b7d794fcfbbbf,Query-Driven Locally Adaptive Fisher Faces and Expert-Model for Face Recognition,"-4244-1437-7/07/$20.00 ©2007 IEEE +I - 141 +ICIP 2007"
+2d27e2d8188743c4e3ca30fda5c25e70775f03e8,FollowMe: Person following and gesture recognition with a quadrocopter,"FollowMe: Person Following and +Gesture Recognition with a Quadrocopter +Tayyab Naseer*, J¨urgen Sturm†, and Daniel Cremers† +*Department of Computer Science, University of Freiburg, Germany +Department of Computer Science, Technical University of Munich, Germany"
+2db0d42192618d0c7419321fac06b887d96dea53,Image Set Classification for Low Resolution Surveillance,"Image Set Classification +for Low Resolution Surveillance +Uzair Nadeem, Syed Afaq Ali Shah, Mohammed Bennamoun, Roberto Togneri +nd Ferdous Sohel"
+2d532fd0636fd49dd893c9dff7fe615f974ec826,Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality,"Causal Inference in Nonverbal Dyadic Communication with Relevant +Interval Selection and Granger Causality +Lea M¨uller1, Maha Shadaydeh1∗, Martin Th¨ummel1, Thomas Kessler2, Dana Schneider2 and Joachim +Denzler1,3 +Computer Vision Group, Friedrich Schiller University of Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany +Department of Social Psychology, Friedrich Schiller University of Jena, Humboldtstrasse 26, 07743 Jena, Germany +Michael Stifel Center, Ernst-Abbe-Platz 2, 07743 Jena, Germany +Keywords: +Nonverbal emotional communication, Granger causality, maximally coherent intervals"
+2d54dc50bbc1a0a63b6f1000bc255f88d57a7a63,It's All Fun and Games until Someone Annotates: Video Games with a Purpose for Linguistic Annotation,"Transactions of the Association for Computational Linguistics, 2 (2014) 449–463. Action Editor: Mirella Lapata. +Submitted 10/2013; Revised 03/2014; Revised 08/2014; Published 10/2014. c(cid:13)2014 Association for Computational Linguistics."
2d294c58b2afb529b26c49d3c92293431f5f98d0,Maximum Margin Projection Subspace Learning for Visual Data Analysis,"Maximum Margin Projection Subspace Learning for Visual Data Analysis Symeon Nikitidis, Anastasios Tefas, Member, IEEE, and Ioannis Pitas, Fellow, IEEE"
+2df731a01db3caf45105c40ac266f76fe1871470,Affective issues in adaptive educational environments,"Neapolis University +HEPHAESTUS Repository +School of Information Sciences +http://hephaestus.nup.ac.cy +Book chapters +Affective Issues in Adaptive Educational Environments +Leontidis, Makis +IGI Global +http://hdl.handle.net/11728/6301 +Downloaded from HEPHAESTUS Repository, Neapolis University institutional repository"
+2d51b52b3eeae8877d1a76ca564a35b8e5051c9d,AU recognition on 3D faces based on an extended statistical facial feature model,"AU Recognition on 3D Faces Based On An Extended Statistical Facial +Feature Model +Xi Zhao, Emmanuel Dellandr´ea, Liming Chen and Dimitris Samaras"
+2da845c75bf9ff02bd27b6e2ceb4732e89b05fad,Linear Support Tensor Machine With LSK Channels: Pedestrian Detection in Thermal Infrared Images,"Linear Support Tensor Machine: +Pedestrian Detection in Thermal Infrared Images +Sujoy Kumar Biswas, Student Member, IEEE, Peyman Milanfar, Fellow, IEEE"
+2d690c63b00e68782666ebf86ac0756fad100a18,Multiple-view face hallucination by a novel regression analysis in tensor space,"The International Arab Journal of Information Technology, Vol. 13, No. 6, November 2016 +Multiple-View Face Hallucination by a Novel +Regression Analysis in Tensor Space +Faculty of Engineering and Technology, Panyapiwat Institute of Management, Thailand +Parinya Sanguansat"
+2d6130f043e69849fc0443bb489c5d21f933eddd,Convolutional LSTM Networks for Video-based Person Re-identification,"Noname manuscript No. +(will be inserted by the editor) +Deep Recurrent Convolutional Networks for Video-based Person +Re-identification: An End-to-End Approach +Lin Wu · Chunhua Shen · Anton van den Hengel"
+2d1f710ba593833cdb0b63880f60146504cf1dc5,Linguistically-driven Framework for Computationally Efficient and Scalable Sign Recognition,"Linguistically-driven Framework for Computationally +Efficient and Scalable Sign Recognition +Dimitris Metaxas*, Mark Dilsizian*, Carol Neidle** +*Rutgers University, **Boston University +*Rutgers University, CBIM, Department of Computer Science, 617 Bowser Road, Piscataway, NJ 08854 +**Boston University Linguistics, 621 Commonwealth Ave., Boston, MA 02215"
+2dc62458979dfc00ec195258ea8809077c5de442,Robust Painting Recognition and Registration for Mobile Augmented Reality,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007 +Robust Painting Recognition and Registration +for Mobile Augmented Reality +Niki Martinel*, Student Member, IEEE, Christian Micheloni, Member, IEEE, +nd Gian Luca Foresti, Senior Member, IEEE"
+2d120c8c74bc029a14fb0726ef103c873a5090eb,Real-Time Gender Classification by Face,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 7, No. 3, 2016 +Real-Time Gender Classification by Face +Eman Fares Al Mashagba +Computer Sciences Department +Zarqa University +Zarqa, Jordan"
2d88e7922d9f046ace0234f9f96f570ee848a5b5,Detection under Privileged Information,"Building Better Detection with Privileged Information Z. Berkay Celik Department of CSE @@ -14644,6 +51242,43 @@ University Ananthram Swami Army Research Laboratory"
+2d0dfa8779aefa1a9a89a1b400188fa9114b4c0a,Functional Map of the World,"Functional Map of the World +Gordon Christie1 +Neil Fendley1 +The Johns Hopkins University Applied Physics Laboratory +James Wilson2 +Ryan Mukherjee1 +DigitalGlobe"
+2dbb4b45b6a392268ce45d16fb944a652d434bd2,Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning,"Maximal Cliques that Satisfy Hard Constraints with +Application to Deformable Object Model Learning +Xinggang Wang1∗ Xiang Bai1 Xingwei Yang2† Wenyu Liu1 Longin Jan Latecki3 +Dept. of Electronics and Information Engineering, Huazhong Univ. of Science and Technology, China +Image Analytics Lab, GE Research, One Research Circle, Niskayuna, NY 12309, USA +Dept. of Computer and Information Sciences, Temple Univ., USA"
+2d3d4883350a48708cdc0c260479110e5eed965a,Leveraging Visual Question Answering for Image-Caption Ranking,"Leveraging Visual Question Answering for +Image-Caption Ranking +Xiao Lin Devi Parikh +Virginia Tech"
+2d12efd5aef4c180ecfaf65184eb7b56e5a40329,3D Object Recognition Based on Image Features: A Survey,"D Object Recognition Based on Image Features: A +International Journal of Computer and Information Technology (ISSN: 2279 – 0764) +Volume 03 – Issue 03, May 2014 +Survey +Dept. of Information Systems, Faculty of Computers and +Khaled Alhamzi +Information, Mansoura University +Mansoura, Egypt +Kalhamzi {at} yahoo.com +Mohammed Elmogy +Dept. of Information Technology, Faculty of Computers and +Information, Mansoura University +Mansoura, Egypt +Dept. of Information Systems, Faculty of Computers and +Sherif Barakat +Information, Mansoura University +Mansoura, Egypt"
+2d1b8f60f2724efd6c9344870fb60e8525157d70,Parallel Multiscale Autoregressive Density Estimation,"Parallel Multiscale Autoregressive Density Estimation +Scott Reed 1 A¨aron van den Oord 1 Nal Kalchbrenner 1 Sergio G´omez Colmenarejo 1 Ziyu Wang 1 +Yutian Chen 1 Dan Belov 1 Nando de Freitas 1"
2d05e768c64628c034db858b7154c6cbd580b2d5,FACIAL EXPRESSION RECOGNITION : Machine Learning using C #,"Neda Firoz et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.8, August- 2015, pg. 431-446 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing @@ -14655,6 +51290,22 @@ FACIAL EXPRESSION RECOGNITION: Machine Learning using C# Author: Neda Firoz Advisor: Dr. Prashant Ankur Jain"
+2d95cf1df9701de410792997205c71208bde98d9,Visual-Inertial based autonomous navigation of an Unmanned Aerial Vehicle in GPS-Denied environments,"FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO +Visual-Inertial based autonomous +navigation of an Unmanned Aerial +Vehicle in GPS-Denied environments +Francisco de Babo Martins +EEC0035 - PREPARAÇÃO DA DISSERTAÇÃO +Mestrado Integrado em Engenharia Electrotécnica e de Computadores +Supervisor: Luís Teixeira +February 18, 2015"
+2d42b5915ca18fdc5fa3542bad48981c65f0452b,Generalization and Equilibrium in Generative Adversarial Nets (GANs),"Generalization and Equilibrium in Generative Adversarial Nets +(GANs) +Sanjeev Arora∗ +Rong Ge † +Yingyu Liang‡ +Tengyu Ma§ +Yi Zhang¶"
2d072cd43de8d17ce3198fae4469c498f97c6277,Random Cascaded-Regression Copse for Robust Facial Landmark Detection,"Random Cascaded-Regression Copse for Robust Facial Landmark Detection Zhen-Hua Feng, Student Member, IEEE, Patrik Huber, Josef Kittler, Life Member, IEEE, William Christmas, @@ -14695,6 +51346,15 @@ Professor Conrad Rudolph Professor Tamar Shinar"
2d8d089d368f2982748fde93a959cf5944873673,Visually Guided Spatial Relation Extraction from Text,"Proceedings of NAACL-HLT 2018, pages 788–794 New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics"
+2d8eff4b085b57788e2f4485c81eb80910f94da0,The impact of organizational performance on the emergence of Asian American leaders.,"Journal of Applied Psychology +The Impact of Organizational Performance on the +Emergence of Asian American Leaders +Seval Gündemir, Andrew M. Carton, and Astrid C. Homan +Online First Publication, September 24, 2018. http://dx.doi.org/10.1037/apl0000347 +CITATION +Gündemir, S., Carton, A. M., & Homan, A. C. (2018, September 24). The Impact of Organizational +Performance on the Emergence of Asian American Leaders. Journal of Applied Psychology. +Advance online publication. http://dx.doi.org/10.1037/apl0000347"
2df4d05119fe3fbf1f8112b3ad901c33728b498a,Multi-task Learning for Structured Output Prediction,"Facial landmark detection using structured output deep neural networks Soufiane Belharbi ∗1, Cl´ement Chatelain∗1, Romain H´erault∗1, and S´ebastien @@ -14702,6 +51362,45 @@ Adam∗2 LITIS EA 4108, INSA de Rouen, Saint ´Etienne du Rouvray 76800, France LITIS EA 4108, UFR des Sciences, Universit´e de Rouen, France. September 24, 2015"
+2d7d8c468bdf123b50ea473fe78a178bfc50724c,Evaluating multi-modal deep learning systems with microworlds,"Research proposal: Evaluating multi-modal deep +learning systems with micro-worlds +Alexander Kuhnle +University of Cambridge (United Kingdom) +6th November 2016"
+2d9a49666bd72e7ba06579d9411ceb2df5205466,3D Face Mesh Modeling from Range Images for 3D Face Recognition,"-4244-1437-7/07/$20.00 ©2007 IEEE +IV - 509 +ICIP 2007"
+2d22a60e69ebdb3fde056adcf4f6a08ccdb6106f,Robust Facial Expression Recognition,"IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 2, Issue 2, Apr-May, 2014 +ISSN: 2320 – 8791 (Impact Factor: 1.479) +www.ijreat.org +Robust Facial Expression Recognition +Mr. Mukund Kumar1, Ms. D. Udaya2 +, 2Computer Science and Engineering, Dr. Pauls Engineering College,Villupuram"
+2d6d4899c892346a9bc8902481212d7553f1bda4,Neural Face Editing with Intrinsic Image Disentangling SUPPLEMENTARY MATERIAL,"Neural Face Editing with Intrinsic Image Disentangling +SUPPLEMENTARY MATERIAL +Zhixin Shu1 Ersin Yumer2 Sunil Hadap2 Kalyan Sunkavalli2 Eli Shechtman 2 Dimitris Samaras1,3 +Stony Brook University 2Adobe Research 3 CentraleSup´elec, Universit´e Paris-Saclay +. Implementation: more details +In this section, we provide more details regarding +the implementation of the rendering layers fshading and +fimage-formation as described in the paper. +.1. Shading Layer +The shading layer is rendered with a spherical harmonics +illumination representation [6, 2, 7, 1]. +where += c3n2 +z − c5 += 2c1nxnz += c1n2 +x − c1n2 +The forward process is described by equations (3),(4), +nd (5) in the main paper. We now provide the backward +process, i.e., the partial derivatives ∂Si"
+41308edf82ae645923efea2d6979d076b975ee25,Convolutional Scale Invariance for Semantic Segmentation,"Convolutional Scale Invariance +for Semantic Segmentation +Ivan Kre(cid:20)so, Denis (cid:20)Cau(cid:20)sevi(cid:19)c, Josip Krapac and Sini(cid:20)sa (cid:20)Segvi(cid:19)c +Faculty of Electrical Engineering and Computing +University of Zagreb, Croatia"
4188bd3ef976ea0dec24a2512b44d7673fd4ad26,Nonlinear Non-Negative Component Analysis Algorithms,"Nonlinear Non-Negative Component Analysis Algorithms Stefanos Zafeiriou, Member, IEEE, and Maria Petrou, Senior Member, IEEE"
@@ -14711,12 +51410,83 @@ Shraddha S. Shinde1 and Prof. Anagha P. Khedkar2 P.G. Student, Department of Computer Engineering, MCERC, Nashik (M.S.), India. Associate Professor, Department of Computer Engineering, MCERC, Nashik (M.S.), India"
+418b468b804379e8a600bca0395e01bffb7e08de,Class-specific kernel linear regression classification for face recognition under low-resolution and illumination variation conditions,"Chou et al. EURASIP Journal on Advances in Signal Processing (2016) 2016:28 +DOI 10.1186/s13634-016-0328-0 +Open Access +R ES EAR CH +Class-specific kernel linear regression +lassification for face recognition under +low-resolution and illumination variation +onditions +Yang-Ting Chou, Shih-Ming Huang and Jar-Ferr Yang*"
+416c647cd9f8c1d77db8676195dff7ae5dfc1fd8,Grammatical Facial Expressions Recognition with Machine Learning,"Grammatical Facial Expressions Recognition with Machine Learning +Fernando de Almeida Freitas +Incluir Tecnologia +Itajub´a, MG, Brazil +Universidade de S˜ao Paulo +S˜ao Paulo, SP, Brazil +Clodoaldo Aparecido de Moraes Lima +Sarajane Marques Peres +Felipe Venˆancio Barbosa +Universidade de S˜ao Paulo +S˜ao Paulo, SP, Brazil"
+414722ddd809b460d5b397eaf454fbb697cfb881,Dimensionality Reduction and Classification through PCA and LDA,"International Journal of Computer Applications (0975 – 8887) +Volume 122 – No.17, July 2015 +Dimensionality Reduction and Classification +through PCA and LDA +Telgaonkar Archana H. +PG Student +Department of CS and IT +Dr. BAMU, Aurangabad"
+41f6368bc4ec5e334c81a9d16185205b3acecee3,Machine Learning Methods from Group to Crowd Behaviour Analysis,"Machine learning methods from group to crowd +ehaviour analysis +Luis Felipe Borja-Borja1, Marcelo Saval-Calvo2, and Jorge Azorin-Lopez2 +Universidad Central del Ecuador, +Ciudadela Universitaria Av. Am´erica, Quito, Ecuador +Computer Technology Department, University of Alicante, +Carretera San Vicente s/n, 03690, San Vicente del Raspeig (Spain)"
+41dd2ca8929bfdae49a4bf85de74df4723ef9c3b,Correction by Projection: Denoising Images with Generative Adversarial Networks,"CORRECTION BY PROJECTION: DENOISING IMAGES +WITH GENERATIVE ADVERSARIAL NETWORKS +Subarna Tripathi +Zachary C. Lipton +Truong Q. Nguyen +UC San Diego +UC San Diego +UC San Diego"
+4129e1075c7856d8bebbf0655ae00a4843109429,A Tale of Two Losses : Discriminative Deep Feature Learning for Person Re-Identification,"A Tale of Two Losses: Discriminative Deep Feature Learning for +Person Re-Identification +Borgia, A., Hua, Y., & Robertson, N. (2017). A Tale of Two Losses: Discriminative Deep Feature Learning for +Person Re-Identification. In Irish Machine Vision and Image Processing Conference 2017: Proceedings +Published in: +Irish Machine Vision and Image Processing Conference 2017: Proceedings +Document Version: +Peer reviewed version +Queen's University Belfast - Research Portal: +Link to publication record in Queen's University Belfast Research Portal +Publisher rights +© 2017 National University of Ireland Maynooth. +This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher. +General rights +Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other +opyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated +with these rights. +Take down policy +The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to +ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the"
414715421e01e8c8b5743c5330e6d2553a08c16d,PoTion : Pose MoTion Representation for Action Recognition,"PoTion: Pose MoTion Representation for Action Recognition Philippe Weinzaepfel2 Inria∗ NAVER LABS Europe J´erˆome Revaud2 Cordelia Schmid1 Vasileios Choutas1,2"
+41f7c03519a2b108c064a2126daf627edde14c1e,Generic Object Detection using AdaBoost,"Generic Object Detection using AdaBoost +Ben Weber +Department of Computer Science +University of California, Santa Cruz +Santa Cruz, CA 95064"
+4196e0b77f88ea01cd868c535befb52c2722454f,3D Facial similarity: Automatic assessment versus perceptual judgments,"D Facial Similarity: Automatic Assessment versus Perceptual +Judgments +Anush K. Moorthy, Anish Mittal, Sina Jahanbin, Kristen Grauman and Alan C. Bovik"
41ab4939db641fa4d327071ae9bb0df4a612dc89,Interpreting Face Images by Fitting a Fast Illumination-Based 3D Active Appearance Model,"Interpreting Face Images by Fitting a Fast Illumination-Based 3D Active Appearance Model @@ -14725,6 +51495,12 @@ Instituto Nacional de Astrof´ısica, ´Optica y Electr´onica, Luis Enrique Erro #1, 72840 Sta Ma. Tonantzintla. Pue., M´exico Coordinaci´on de Ciencias Computacionales {saraggi, robles,"
+41a5e043d499967f405e823b959e2ac4fdf9ff71,Extending Recognition in a Changing Environment,"Extending Recognition in a Changing Environment +Department of Computer Science and Applied Mathematics, The Weizmann Institue of Science, Rehovot, Israel +Daniel Harari and Shimon Ullman +{danny.harari, +Keywords: +Object Recognition, Video Analysis, Dynamic Model Update, Unsupervised Learning, Bayesian Model."
41a6196f88beced105d8bc48dd54d5494cc156fb,Using facial images for the diagnosis of genetic syndromes: A survey,"015 International Conference on Communications, Signal Processing, and their Applications @@ -14735,6 +51511,51 @@ IEEE Catalog Number: ISBN: CFP1574T-POD 978-1-4799-6533-5"
+41ddd29d9e56bb87b9f988afc75cd597657b2600,R4-A.3: Human Detection & Re-Identification for Mass Transit Environments,"R4-A.3: Human Detection & Re-Identification for +Mass Transit Environments +PARTICIPANTS +Rich Radke +Title +Faculty/Staff +Institution +Graduate, Undergraduate and REU Students +Srikrishna Karanam +Eric Lam +Degree Pursued +Institution +Email +Month/Year of Graduation +5/2017 +5/2017 +PROJECT DESCRIPTION +Project Overview +The computer vision research problem of human re-identification or “re-id” is generally posed as follows: +Given a cropped rectangle of pixels representing a human in one view, a re-id algorithm produces a similarity"
+41decbe12a8aa7996163636e09d1ce1372c271cd,Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification,"Attentive Fashion Grammar Network for +Fashion Landmark Detection and Clothing Category Classification +Wenguan Wang∗1,2, Yuanlu Xu∗2, Jianbing Shen†1, and Song-Chun Zhu2 +Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, China +Department of Computer Science and Statistics, University of California, Los Angeles, USA"
+413160257096b9efcd26d8de0d1fa53133b57a3d,Customer satisfaction measuring based on the most significant facial emotion,"Customer satisfaction measuring based on the most +significant facial emotion +Mariem Slim, Rostom Kachouri, Ahmed Atitallah +To cite this version: +Mariem Slim, Rostom Kachouri, Ahmed Atitallah. Customer satisfaction measuring based on the +most significant facial emotion. 15th IEEE International Multi-Conference on Systems, Signals +Devices (SSD 2018), Mar 2018, Hammamet, Tunisia. <hal-01790317> +HAL Id: hal-01790317 +https://hal-upec-upem.archives-ouvertes.fr/hal-01790317 +Submitted on 11 May 2018 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
41de109bca9343691f1d5720df864cdbeeecd9d0,Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality,"Article Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality @@ -14743,6 +51564,26 @@ EECS Department, The University of Toledo, Toledo, OH 43606, USA; (D.M.); (M.F.H.S.) * Correspondence: Tel.: +1-419-530-8260 Received: 10 December 2017; Accepted: 26 January 2018; Published: 1 Febuary 2018"
+41ed93fd97aa76b4abfda7a09168ad1799f34664,Video Event Detection: From Subvolume Localization to Spatiotemporal Path Search,"This document is downloaded from DR-NTU, Nanyang Technological +University Library, Singapore. +Title +Video event detection : from subvolume localization to +spatio-temporal path search +Author(s) +Tran, Du; Yuan, Junsong; Forsyth, David +Citation +Tran, D., Yuan, J., & Forsyth, D. (2014). Video Event +Detection: From Subvolume Localization to +Spatiotemporal Path Search. IEEE Transactions on +Pattern Analysis and Machine Intelligence, 36(2), 404- +http://hdl.handle.net/10220/19322 +Rights +© 2014 IEEE. Personal use of this material is permitted. +Permission from IEEE must be obtained for all other +uses, in any current or future media, including +reprinting/republishing this material for advertising or +promotional purposes, creating new collective works, for +resale or redistribution to servers or lists, or reuse of any"
41d9a240b711ff76c5448d4bf4df840cc5dad5fc,Image Similarity Using Sparse Representation and Compression Distance,"JOURNAL DRAFT, VOL. X, NO. X, APR 2013 Image Similarity Using Sparse Representation nd Compression Distance @@ -14750,14 +51591,115 @@ Tanaya Guha, Student Member, IEEE, and Rabab K Ward, Fellow, IEEE" 419a6fca4c8d73a1e43003edc3f6b610174c41d2,A component based approach improves classification of discrete facial expressions over a holistic approach,"A Component Based Approach Improves Classification of Discrete Facial Expressions Over a Holistic Approach Kenny Hong, and Stephan K. Chalup, Senior Member, IEEE and Robert A.R. King"
+41a174c27f0b431d62d0f50051bce7f5b3b4ce64,A System for Object Class Detection,"A system for object class detection +Daniela Hall +INRIA Rh^one-Alpes, 655, ave de l’Europe, +8320 St. Ismier, France"
+4131aa28d640d17e1d63ca82e55cc0b280db0737,Coulomb Gans: Provably Optimal Nash Equi-,"Under review as a conference paper at ICLR 2018 +COULOMB GANS: PROVABLY OPTIMAL NASH EQUI- +LIBRIA VIA POTENTIAL FIELDS +Anonymous authors +Paper under double-blind review"
4180978dbcd09162d166f7449136cb0b320adf1f,Real-time head pose classification in uncontrolled environments with Spatio-Temporal Active Appearance Models,"Real-time head pose classification in uncontrolled environments with Spatio-Temporal Active Appearance Models Miguel Reyes∗ and Sergio Escalera+ and Petia Radeva + Matematica Aplicada i Analisi ,Universitat de Barcelona, Barcelona, Spain + Matematica Aplicada i Analisi, Universitat de Barcelona, Barcelona, Spain + Matematica Aplicada i Analisi, Universitat de Barcelona, Barcelona, Spain"
+41ea92251c668a99d2b9a31935fc71e6b6d82b6d,Canonical Correlation Analysis of Datasets With a Common Source Graph,"Canonical Correlation Analysis of Datasets +with a Common Source Graph +Jia Chen, Gang Wang, Student Member, IEEE, +Yanning Shen, Student Member, IEEE, and Georgios B. Giannakis, Fellow, IEEE"
+4106c49eb96b506ea1125c27e2b2f32ad79f8c48,"Markovian Tracking-by-Detection from a Single, Uncalibrated Camera","Markovian Tracking-by-Detection from a Single, Uncalibrated Camera +Michael D. Breitenstein1 Fabian Reichlin1 Bastian Leibe1,2 Esther Koller-Meier1 Luc Van Gool1,3 +ETH Zurich +RWTH Aachen +KU Leuven"
+413a1a00f0eab2fcc3dcc0d821fb2f34e85f5d7a,Pedestrian detection by scene dependent classifiers with generative learning,"June 23-26, 2013, Gold Coast, Australia +978-1-4673-2754-1/13/$31.00 ©2013 IEEE"
+413c960e57ec3fe713e7b3e070cb6072726874bd,A Search Space Strategy for Pedestrian Detection and Localization in World Coordinates,
+41fafb5392ad5e33e5169d870812ab5edca301a1,Tree-Structured Stick Breaking Processes for Hierarchical Data,"TREE-STRUCTURED STICK BREAKING PROCESSES +FOR HIERARCHICAL DATA +By Ryan P. Adams, Zoubin Ghahramani and Michael I. Jordan +Many data are naturally modeled by an unobserved hierarchical +structure. In this paper we propose a flexible nonparametric prior over +processes to allow for trees of unbounded width and depth, where data +an live at any node and are infinitely exchangeable. One can view +our model as providing infinite mixtures where the components have a +dependency structure corresponding to an evolutionary diffusion down +tree. By using a stick-breaking approach, we can apply Markov chain +Monte Carlo methods based on slice sampling to perform Bayesian +inference and simulate from the posterior distribution on trees. We +pply our method to hierarchical clustering of images and topic +modeling of text data. +. Introduction. Structural aspects of models are often critical to ob- +taining flexible, expressive model families. In many cases, however, the +structure is unobserved and must be inferred, either as an end in itself or +to assist in other estimation and prediction tasks. This paper addresses an +important instance of the structure learning problem: the case when the +data arise from a latent hierarchy. We take a direct nonparametric Bayesian"
+4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06,Nighttime Face Recognition at Long Distance: Cross-Distance and Cross-Spectral Matching,"Nighttime Face Recognition at Long Distance: +Cross-distance and Cross-spectral Matching +Hyunju Maenga, Shengcai Liaob, Dongoh Kanga, Seong-Whan Leea, +Anil K. Jaina;b +Dept. of Brain and Cognitive Eng. Korea Univ., Seoul, Korea +Dept. of Comp. Sci. & Eng. Michigan State Univ., E. Lansing, MI, USA 48824"
+41690be86b39c55a26ea056261513ddd726d6601,Heterogeneous microarchitectures trump voltage scaling for low-power cores,"Heterogeneous Microarchitectures Trump Voltage Scaling +for Low-Power Cores +Andrew Lukefahr, Shruti Padmanabha, Reetuparna Das, Ronald Dreslinski Jr., +Thomas F. Wenisch, and Scott Mahlke +Advanced Computer Architecture Laboratory +Ann Arbor, MI, USA +{lukefahr, shrupad, reetudas, rdreslin, twenisch,"
+4189aa74550c1761dd5927442d0a98ff3d3d1134,Residual Conv-Deconv Grid Network for Semantic Segmentation,"FOURURE ET AL.: RESIDUAL CONV-DECONV GRIDNET +Residual Conv-Deconv Grid Network for +Semantic Segmentation +Univ Lyon, UJM Saint-Etienne, +CNRS UMR 5516, +Hubert Curien Lab, F-42023 +Saint-Etienne, France +INSA-Lyon, +LIRIS UMR CNRS 5205, +F-69621, +France +Damien Fourure1 +Rémi Emonet1 +Elisa Fromont1 +Damien Muselet1 +Alain Tremeau1 +Christian Wolf2"
413a184b584dc2b669fbe731ace1e48b22945443,Human Pose Co-Estimation and Applications,"Human Pose Co-Estimation and Applications Marcin Eichner and Vittorio Ferrari"
+410017a1810308564dc54cb986b12f079428f966,A functional pipeline framework for landmark identification on 3D surface extracted from volumetric data,"RESEARCH ARTICLE +A functional pipeline framework for landmark +identification on 3D surface extracted from +volumetric data +Pan Zheng1,2*, Bahari Belaton2*, Iman Yi Liao3, Zainul Ahmad Rajion4,5 +Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, +Kuching, Malaysia, 2 School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia, 3 School of +Computer Science, The University of Nottingham Malaysia Campus, Semenyih, Malaysia, 4 School of Dental +Sciences, Universiti Sains Malaysia, Kubang Kerian, Malaysia, 5 College of Dentistry, King Saud bin +Abdulaziz University for Health Sciences, Riyadh, Kingdom of Saudi Arabia +* (PZ); (BB)"
+4183d1b79d54f5638063e6c59a2a873ee2cd1bed,Multi-cue pedestrian classification with partial occlusion handling,"Multi-Cue Pedestrian Classification With Partial Occlusion Handling +Markus Enzweiler1 +Angela Eigenstetter2 +Bernt Schiele2,3 +Dariu M. Gavrila4,5 +Image & Pattern Analysis Group, Univ. of Heidelberg, Germany +Computer Science Department, TU Darmstadt, Germany +MPI Informatics, Saarbr¨ucken, Germany +Environment Perception, Group Research, Daimler AG, Ulm, Germany +5 Intelligent Autonomous Systems Group, Univ. of Amsterdam, The Netherlands"
+41c1b8f319e27be0c77c3b33cf877c29b1676501,"3D Face Recognition based on Radon Transform, PCA, LDA using KNN and SVM","I.J. Computer Network and Information Security, 2014, 7, 36-43 +Published Online June 2014 in MECS (http://www.mecs-press.org/) +DOI: 10.5815/ijcnis.2014.07.05 +D Face Recognition based on Radon Transform, +PCA, LDA using KNN and SVM +P. S. Hiremath and Manjunatha Hiremath +Department of Computer Science, Gulbarga University, Gulbarga – 585106 +e-mail: and +Karnataka, India"
83b7578e2d9fa60d33d9336be334f6f2cc4f218f,The S-HOCK dataset: Analyzing crowds at the stadium,"The S-HOCK Dataset: Analyzing Crowds at the Stadium Davide Conigliaro1,3, Paolo Rota2, Francesco Setti3, Chiara Bassetti3, Nicola Conci4, Nicu Sebe4, Marco Cristani1, University of Verona. 2Vienna Institute of Technology. 3ISTC–CNR (Trento). 4University of Trento. @@ -14778,11 +51720,47 @@ ported team and what has been the best action in the match; all of this has een obtained by interviews at the stadium. At a medium level, spectators re localized, and information regarding the pose of their heads and body is given. Finally, at a lowest level, a fine grained specification of all the actions"
+83b20fdd3eafd21a6971dacc73d85c484a093bfc,Interleaved Structured Sparse Convolutional Neural Networks,"Interleaved Structured Sparse Convolutional Neural Networks +Guotian Xie1,2,∗ Jingdong Wang3† Ting Zhang3 +Jianhuang Lai1,2 Richang Hong4 Guo-Jun Qi5 +Sun Yat-Sen University 2Guangdong Key Laboratory of Information Security Technology +Microsoft Research 4Hefei University of Technology 5University of Central Florida"
83ca4cca9b28ae58f461b5a192e08dffdc1c76f3,Detecting emotional stress from facial expressions for driving safety,"DETECTING EMOTIONAL STRESS FROM FACIAL EXPRESSIONS FOR DRIVING SAFETY Hua Gao, Anil Y¨uce, Jean-Philippe Thiran Signal Processing Laboratory (LTS5), ´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland"
+83c19722450e8f7dcb89dabb38265f19efafba27,A framework with updateable joint images re-ranking for Person Re-identification,"A framework with updateable joint images re-ranking for Person +Re-identification +Yuan Mingyue1,2 Yin Dong1,2* Ding Jingwen1,3* Luo Yuhao1,2 Zhou Zhipeng1,2 +Zhu Chengfeng1,2 Zhang Rui1,2 +School of Information Science Technology, USTC, Hefei, Anhui 230027, China +Key Laboratory of Electromagnetic Space Information of CAS, Hefei, Anhui 230027, China"
+8380b8f4e36c993eef23af42ccb382ae60aceabf,"URBAN-i: From urban scenes to mapping slums, transport modes, and pedestrians in cities using deep learning and computer vision","URBAN-i: From urban scenes to mapping slums, transport modes, and pedestrians +in cities using deep learning and computer vision +Mohamed R. Ibrahim1, James Haworth2 and Tao Cheng3 +Department of Civil, Environmental and Geomatic Engineering, University College London (UCL)"
831fbef657cc5e1bbf298ce6aad6b62f00a5b5d9,Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning,
+830b48f210f3905117b335e305166df4ec092b8b,Pixel-Level Encoding and Depth Layering for Instance-Level Semantic Labeling,"Pixel-level Encoding and Depth Layering for +Instance-level Semantic Labeling +Jonas Uhrig1,2, Marius Cordts1,3, Uwe Franke1, Thomas Brox2 +Daimler AG R&D, 2University of Freiburg, 3TU Darmstadt"
+8322ed1a3db7c63af40280a782e39fb01bfe96dd,Class label autoencoder for zero-shot learning,"Class label autoencoder for zero-shot learning +Guangfeng Lina,∗, Caixia Fana, Wanjun Chena, Yajun Chena, Fan Zhaoa +Information Science Department, Xian University of Technology, +5 South Jinhua Road, Xi’an, Shaanxi Province 710048, PR China"
+833a2c168849697aae3589bbeef0cbca22808fe8,"Quantity, Contrast, and Convention in Cross-Situated Language Comprehension","Proceedings of the 19th Conference on Computational Language Learning, pages 226–236, +Beijing, China, July 30-31, 2015. c(cid:13)2015 Association for Computational Linguistics"
+8306e384e7ca48445843bc025b08236cd181d7c6,Histogram of Oriented Gradients with Cell Average Brightness for Human Detection,"Metrol. Meas. Syst., Vol. XXIII (2016), No. 1, pp. 27–36. +METROLOGY AND MEASUREMENT SYSTEMS +Index 330930, ISSN 0860-8229 +www.metrology.pg.gda.pl +HISTOGRAM OF ORIENTED GRADIENTS WITH CELL AVERAGE +BRIGHTNESS FOR HUMAN DETECTION +Marek Wójcikowski +Gdańsk University of Technology, Faculty of Electronics, Telecommunications and Informatics, G. Narutowicza 11/12, 80-233 Gdańsk, Poland +((cid:1) +48 58 347 1974)"
+83c00537e0c3e226d999a5abf02464e138867e96,Pedestrians and their phones - detecting phone-based activities of pedestrians for autonomous vehicles,"Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016 +978-1-5090-1889-5/16/$31.00 ©2016 IEEE"
832e1d128059dd5ed5fa5a0b0f021a025903f9d5,Pairwise Conditional Random Forests for Facial Expression Recognition,"Pairwise Conditional Random Forests for Facial Expression Recognition Arnaud Dapogny1 Kevin Bailly1 @@ -14795,9 +51773,67 @@ Karsten Vogt, Oliver M¨uller and J¨orn Ostermann Institut f¨ur Informationsverarbeitung (tnt) Leibniz Universit¨at Hannover, Germany {vogt, omueller,"
+8326d3e57796dad294ab1c14a0688221550098b6,ABC-GAN: Adaptive Blur and Control for improved training stability of Generative Adversarial Networks,"Adaptive Blur and Control for improved training stability of +Generative Adversarial Networks +ABC-GAN: +Igor Susmelj 3 Eirikur Agustsson 3 Radu Timofte 3"
+8377ac1b2dffb11cf48f456be2531c95d14aa6e5,Improving the Annotation of DeepFashion Images for Fine-grained Attribute Recognition,"Improving the Annotation of DeepFashion +Images for Fine-grained Attribute Recognition +Roshanak Zakizadeh, Michele Sasdelli, Yu Qian and Eduard Vazquez +Cortexica Vision Systems, London, UK"
+838a4bcfeb36dc7bdb4a38f776fc0a70ce8ae9f0,Face Presentation Attack Detection using Biologically-inspired Features,
+83ef7de2669bb2827208fd3a64ac910e276fbdb4,Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery,"Fully Convolutional Networks for Dense Semantic Labelling of +High-Resolution Aerial Imagery +Jamie Sherrah +Defence Science & Technology Group +Edinburgh, South Australia +email: +https://au.linkedin.com/jsherrah +June 9, 2016"
+8397956c7ad3bd24c6c6c0b38866e165367327c0,Social Relation Trait Discovery from Visual LifeLog Data with Facial Multi-Attribute Framework,
83b4899d2899dd6a8d956eda3c4b89f27f1cd308,A Robust Approach for Eye Localization Under Variable Illuminations,"-4244-1437-7/07/$20.00 ©2007 IEEE I - 377 ICIP 2007"
+8387c58a5a3fd847f9b03760842dd49fec7cbb0e,Two-year-olds with autism orient to nonsocial contingencies rather than biological motion,"Vol 459 | 14 May 2009 | doi:10.1038/nature07868 +LETTERS +Two-year-olds with autism orient to non-social +ontingencies rather than biological motion +Ami Klin1, David J. Lin1{, Phillip Gorrindo1{, Gordon Ramsay1,2 & Warren Jones1,3 +Typically developing human infants preferentially attend to bio- +logical motion within the first days of life1. This ability is highly +onserved across species2,3 and is believed to be critical for filial +ttachment and for detection of predators4. The neural under- +pinnings of biological motion perception are overlapping with +rain regions involved in perception of basic social signals such +s facial expression and gaze direction5, and preferential attention +to biological motion is seen as a precursor to the capacity for +ttributing intentions to others6. However, in a serendipitous +observation7, we recently found that an infant with autism failed +to recognize point-light displays of biological motion, but was +instead highly sensitive to the presence of a non-social, physical +ontingency that occurred within the stimuli by chance. This +observation raised the possibility that perception of biological +motion may be altered in children with autism from a very early"
+833fbf0e4be3ba82e7a1efdbc16813ee849d9942,Restricted Deformable Convolution based Road Scene Semantic Segmentation Using Surround View Cameras,"SUBMITTED TO IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS +Restricted Deformable Convolution based +Road Scene Semantic Segmentation +Using Surround View Cameras +Liuyuan Deng, Ming Yang, Hao Li, Tianyi Li, Bing Hu, Chunxiang Wang"
+83d1617092b34804c3825fdf4292120c382fe043,Appearance-Based Multimodal Human Tracking and Identification for Healthcare in the Digital Home,"Sensors 2014, 14, 14253-14277; doi:10.3390/s140814253 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +Appearance-Based Multimodal Human Tracking and +Identification for Healthcare in the Digital Home +Mau-Tsuen Yang * and Shen-Yen Huang +Department of Computer Science & Information Engineering, National Dong-Hwa University, No. 1, +Sec. 2, Da-Hsueh Rd., Shoufeng, Hualien 974, Taiwan; E-Mail: +* Author to whom correspondence should be addressed; E-Mail: +Tel.: +886-3-863-4028; Fax: +886-3-863-4010. +Received: 2 April 2014; in revised form: 3 July 2014 / Accepted: 8 July 2014 / +Published: 5 August 2014"
8323af714efe9a3cadb31b309fcc2c36c8acba8f,Automatic Real-Time Facial Expression Recognition for Signed Language Translation,"Automatic Real-Time Facial Expression Recognition for Signed Language Translation @@ -14811,6 +51847,10 @@ Images Orhan Bulan, Safwan Wshah, Ramesh Palghat, Vladimir Kozitsky and Aaron Burry Palo Alto Research Center (PARC) 800 Phillips Rd. Webster NY 14580"
+83ce2c969ea323784b9098b9b170e015d559a1df,Detecting domestic objects with ensembles of view-tuned support vector machine cascades trained on Web images,"Detecting Domestic Objects with Ensembles of +View-tuned Support Vector Machine Cascades Trained +on Web Images +Marco Kortkamp"
8395cf3535a6628c3bdc9b8d0171568d551f5ff0,Entropy Non-increasing Games for the Improvement of Dataflow Programming,"Entropy Non-increasing Games for the Improvement of Dataflow Programming Norbert B´atfai, Ren´at´o Besenczi, Gerg˝o Bogacsovics, @@ -14821,22 +51861,163 @@ Zhiwu Huang†, Bernhard Kratzwald†, Danda Pani Paudel†, Jiqing Wu†, Luc V Computer Vision Lab, ETH Zurich, Switzerland VISICS, KU Leuven, Belgium {zhiwu.huang, paudel, jwu,"
+83df0ec6071dfda29da831860fdb2a1f19a6b3bc,3D Face Recognition Using Joint Differential Invariants,"D Face Recognition Using Joint Differential +Invariants +Marinella Cadoni1, Manuele Bicego1,2, and Enrico Grosso1 +Computer Vision Laboratory, DEIR, University of Sassari, Italy +Computer Science Dept., University of Verona, Italy"
+832aae00e16c647716f1be38de233c9c15af9a28,Feature fusion for facial landmark detection,"Author's Accepted Manuscript +Feature fusion for facial landmark detection +Panagiotis Perakis, Theoharis Theoharis, Ioan- +nis A. Kakadiaris +Reference: +S0031-3203(14)00105-8 +http://dx.doi.org/10.1016/j.patcog.2014.03.007 +PR5053 +www.elsevier.com/locate/pr +To appear in: +Received date: 10 March 2013 +Revised date: 18 September 2013 +Accepted date: 8 March 2014 +Cite this article as: Panagiotis Perakis, Theoharis Theoharis, +http://dx.doi.org/10.1016/j.patcog.2014.03.007 +Ioannis A. +This is a PDF file of an unedited manuscript that has been accepted for +publication. As a service to our customers we are providing this early version of +the manuscript. The manuscript will undergo copyediting, typesetting, and +review of the resulting galley proof before it is published in its final citable form."
8320dbdd3e4712cca813451cd94a909527652d63,Ear Biometrics,"EAR BIOMETRICS Mark Burge nd Wilhelm Burger Johannes Kepler University(cid:1) Institute of Systems Science(cid:1) A(cid:2) urge(cid:1)cast(cid:2)uni(cid:3)linz(cid:2)ac(cid:2)at"
+83d0b7100ddce32e37af72585f9aa4181e6447e3,Online Social Behavior Modeling for Multi-target Tracking,"Online Social Behavior Modeling for Multi-Target Tracking +Shu Zhang1 Abir Das1 Chong Ding2 Amit K. Roy-Chowdhury1 +University of California, Riverside, CA 92521 USA"
+833cd4265bd8162d3cfb483ce8f31eaef28e7a2e,Towards Effective Gans,"Under review as a conference paper at ICLR 2018 +TOWARDS EFFECTIVE GANS +FOR DATA DISTRIBUTIONS WITH DIVERSE MODES +Anonymous authors +Paper under double-blind review"
+83968f81f23a34e18e850fe2cf68bab51e22e35c,Attention-Driven Parts-Based Object Detection,"Attention-Driven Parts-Based Object Detection +Ilkka Autio & J.T. Lindgren +Department of Computer Science +University of Helsinki +Finland"
+83e71455ee2070617ea35c02f03b7451187985d1,Faces Recognition with Image Feature Weights and Least Mean Square Learning Approach,"Faces Recognition with Image Feature Weights and Least Mean Square +Learning Approach +Dept. of Electrical Engineering, National Taiwan Uni. of Sci. & Technology, Taipei, Taiwan +Wei-Li Fang, Ying-Kuei Yang and Jung-Kuei Pan +Email:"
+833bdee366f1e6250dea59bdebdcad271c7cfddd,Bayesian non-parametrics for multi-modal segmentation,"Bayesian Non-Parametrics for +Multi-Modal Segmentation +Thesis for obtaining the title of +Doctor of Engineering Science +(Dr.-Ing.) +of the Faculty of Natural Science and Technology I +of Saarland University +Wei-Chen Chiu, M.Sc. +Saarbrücken +September 2016"
837e99301e00c2244023a8a48ff98d7b521c93ac,Local Feature Evaluation for a Constrained Local Model Framework,"Local Feature Evaluation for a Constrained Local Model Framework Maiya Hori(B), Shogo Kawai, Hiroki Yoshimura, and Yoshio Iwai Graduate School of Engineering, Tottori University, 01 Minami 4-chome, Koyama-cho, Tottori 680-8550, Japan"
+83e7254431486d24715d4170680c6cbc8bdb2328,Image retrieval using visual attention,"IMAGE RETRIEVAL USING VISUAL ATTENTION +Liam M. Mayron +A Dissertation Submitted to the Faculty of +The College of Engineering and Computer Science +in Partial Fulfillment of the Requirements for the Degree of +Doctor of Philosophy +Florida Atlantic University +Boca Raton, Florida +May 2008"
+83c332971c4534907afc4865179c2de30f2792c4,Sparse and Dense Hybrid Representation via Dictionary Decomposition for Face Recognition,"Sparse And Dense Hybrid Representation +via Dictionary Decomposition +for Face Recognition +Xudong Jiang, Senior Member, IEEE, and Jian Lai, Student Member, IEEE"
+8326b11dd0b81dcc169ce21fc12e0c9d632db6bd,Tracking and Recognition: A Unified Approach on Tracking and Recognition,"ISSN: 2321-8169 +International Journal on Recent and Innovation Trends in Computing and Communication +Volume: 2 Issue: 11 +3532 – 3539 +_______________________________________________________________________________________________ +Tracking and Recognition: A Unified Approach on Tracking and Recognition +Ms. Anuja V. Vaidya +Dr. Mrs. S.B. Patil +Dept. of Electronics & Communication +Dept of Electronics & Communication +Dr. J.J. Magdum College of Engg. Jaysingpur, +Dr. J.J. Magdum College of Engg. Jaysingpur, +Maharashtra, India +Maharashtra, India"
834b15762f97b4da11a2d851840123dbeee51d33,Landmark-free smile intensity estimation,"Landmark-free smile intensity estimation J´ulio C´esar Batista, Olga R. P. Bellon and Luciano Silva IMAGO Research Group - Universidade Federal do Paran´a Fig. 1. Overview of our method for smile intensity estimation"
+83e7c51c4d6f04049f5a3dbf4ac9e129ed96caee,Spatio-temporal Pain Recognition in CNN-Based Super-Resolved Facial Images,"Aalborg Universitet +Spatio-Temporal Pain Recognition in CNN-based Super-Resolved Facial Images +Bellantonio, Marco; Haque, Mohammad Ahsanul; Rodriguez, Pau; Nasrollahi, Kamal; Telve, +Taisi; Guerrero, Sergio Escalera; Gonzàlez, Jordi; Moeslund, Thomas B.; Rasti, Pejman; +Anbarjafari, Gholamreza +Published in: +Video Analytics +DOI (link to publication from Publisher): +0.1007/978-3-319-56687-0_13 +Publication date: +Document Version +Accepted author manuscript, peer reviewed version +Link to publication from Aalborg University +Citation for published version (APA): +Bellantonio, M., Haque, M. A., Rodriguez, P., Nasrollahi, K., Telve, T., Guerrero, S. E., ... Anbarjafari, G. (2017). +Spatio-Temporal Pain Recognition in CNN-based Super-Resolved Facial Images. In Video Analytics: Face and +Facial Expression Recognition and Audience Measurement Springer. Lecture Notes in Computer Science, Vol.. +0165 https://doi.org/10.1007/978-3-319-56687-0_13 +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners"
+83b700f0777a408eb36eef4b1660beb3f6dc1982,Violent behaviour detection using local trajectory response,"See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/317628106 +Violent behaviour detection using local +trajectory response +Conference Paper · January 2016 +DOI: 10.1049/ic.2016.0082 +CITATIONS +authors, including: +Paul L. Rosin +Cardiff University +READS +David Marshall +Cardiff University +31 PUBLICATIONS 7,739 CITATIONS +98 PUBLICATIONS 2,855 CITATIONS +SEE PROFILE +SEE PROFILE +Simon Christopher Moore +University of Wales +08 PUBLICATIONS 1,069 CITATIONS +SEE PROFILE"
+83a4b9c9ae3f75bf7e4a3222c46d99be7b7998ab,A random forest approach to segmenting and classifying gestures,"A Random Forest Approach to Segmenting and Classifying Gestures +Ajjen Joshi1, Camille Monnier2, Margrit Betke1 and Stan Sclaroff1 +Department of Computer Science, Boston Univeristy, Boston, MA 02215 USA +Charles River Analytics, Cambridge, MA 02138 USA"
833f6ab858f26b848f0d747de502127406f06417,Learning weighted similarity measurements for unconstrained face recognition,"978-1-4244-5654-3/09/$26.00 ©2009 IEEE ICIP 2009"
+832a9584e85af1675d49ee35fd13283b21ce3a3f,Generating Photo-Realistic Training Data to Improve Face Recognition Accuracy,"Generating Photo-Realistic Training Data to Improve +Face Recognition Accuracy +Daniel S´aez Trigueros, Li Meng +School of Engineering and Technology +University of Hertfordshire +Hatfield AL10 9AB, UK +Margaret Hartnett +GBG plc +London E14 9QD, UK"
+8399c71abc9a820bacd9c4e21c85c461c0b830b3,"Adaboost with ""Keypoint Presence Features"" for Real-Time Vehicle Visual Detection","Author manuscript, published in ""16th World Congress on Intelligent Transport Systems (ITSwc'2009), Sweden (2009)"""
+83963d1454e66d9cc82e28ff4efc562f5fe6b7d3,"Automated detection of feeding strikes by larval fish using continuous high-speed digital video: a novel method to extract quantitative data from fast, sparse kinematic events.","© 2016. Published by The Company of Biologists Ltd | Journal of Experimental Biology (2016) 219, 1608-1617 doi:10.1242/jeb.133751 +METHODS & TECHNIQUES +Automated detection of feeding strikes by larval fish using +ontinuous high-speed digital video: a novel method to extract +quantitative data from fast, sparse kinematic events +Eyal Shamur1,‡, Miri Zilka2,*,‡, Tal Hassner1, Victor China3,4, Alex Liberzon5 and Roi Holzman3,4,§ +the observer and subject"
8309e8f27f3fb6f2ac1b4343a4ad7db09fb8f0ff,Generic versus Salient Region-Based Partitioning for Local Appearance Face Recognition,"Generic versus Salient Region-based Partitioning for Local Appearance Face Recognition Hazım Kemal Ekenel and Rainer Stiefelhagen @@ -14863,6 +52044,68 @@ broad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non,"
+1bed38bc216f80a50617afa5c6d9cc4b2db72519,Face recognition using early biologically inspired features,"Face Recognition Using Early Biologically Inspired Features +Min Li, Shenghua Bao, Weihong Qian, and Zhong Su +IBM China Research Lab, PRC +fminliml,baoshhua,qianwh, +Nalini K. Ratha +IBM Watson Research Center, USA"
+1b55a0ad1d4738a7d46ed787542991d4a05ae27e,Accurate Object Detection and Semantic Segmentation using Gaussian Mixture Model and CNN,"IJARCCE +ISSN (Online) 2278-1021 +ISSN (Print) 2319 5940 +International Journal of Advanced Research in Computer and Communication Engineering +Vol. 4, Issue 11, November 2015 +Accurate Object Detection and Semantic +Segmentation using Gaussian Mixture Model and +Sakshi Jain1, Satish Dehriya2, Yogendra Kumar Jain3 +Research Scholar, Computer Science & Engg, Samrat Ashok Technological Institute, Vidisha (M.P.), India1 +Assist. Professor, Computer Science & Engg, Samrat Ashok Technological Institute, Vidisha (M.P.), India 2 +Head of the Department, Computer Science & Engg, Samrat Ashok Technological Institute, Vidisha (M.P.), India3"
+1b2183c2b9608b7f815551c9ba602f22205126b1,Facial Reenactment Project Plan,"Facial Reenactment +Project Plan +Student: +Li Wing Yee +Supervisor: +Dr. Dirk Scheiders"
+1b1d9b528c69e082dc5685089090bd2d849d887d,MixedPeds: Pedestrian Detection in Unannotated Videos using Synthetically-Generated Human-agents for Training,"MixedPeds: Pedestrian Detection in Unannotated Videos using Synthetically +Generated Human-agents for Training +Ernest Cheung, Anson Wong, Aniket Bera, Dinesh Manocha +Department of Computer Science +Project Webpage: http://gamma.cs.unc.edu/MixedPeds +The University of North Carolina at Chapel Hill +Email: {ernestc, ahtsans, ab,"
+1bb14ddc0326a8e5b44eafd915738c2b1342f392,Title On color texture normalization for active appearance models,"Provided by the author(s) and NUI Galway in accordance with publisher policies. Please cite the published +version when available. +Title +On color texture normalization for active appearance models +Author(s) +Ionita, Mircea C.; Corcoran, Peter M.; Buzuloiu, Vasile +Publication +009-05-12 +Publication +Information +Ionita, M. C., Corcoran, P., & Buzuloiu, V. (2009). On Color +Texture Normalization for Active Appearance Models. Image +Processing, IEEE Transactions on, 18(6), 1372-1378. +Publisher +Link to +publisher's +version +http://dx.doi.org/10.1109/TIP.2009.2017163 +Item record +http://hdl.handle.net/10379/1350"
+1b7a7d291235e4b6e5f97722124070feb26f3cc1,Learning Two-Branch Neural Networks for Image-Text Matching Tasks,"Learning Two-Branch Neural Networks for +Image-Text Matching Tasks +Liwei Wang, Yin Li, Jing Huang, Svetlana Lazebnik"
+1ba55051d3957895d77257cc9a5885068fb2e43a,High-Resolution Face Verification Using Pore-Scale Facial Features,"High-Resolution Face Verification Using +Pore-Scale Facial Features +Dong Li, Huiling Zhou, and Kin-Man Lam"
+1b8508c6e341dcc803e52ed02968ae944c744f68,Face detection evaluation: a new approach based on the golden ratio $${\Phi}$$,"SIViP manuscript No. +(will be inserted by the editor) +Face Detection Evaluation: A New Approach Based on +the Golden Ratio (cid:8) +M. Hassaballah (cid:1) Kenji Murakami (cid:1) Shun Ido +Received: 1 Jan. 2011 /Revised: 9 March 2011/ Accepted: date"
1b55c4e804d1298cbbb9c507497177014a923d22,Incremental Class Representation Learning for Face Recognition,"Incremental Class Representation Learning for Face Recognition Degree’s Thesis @@ -14897,6 +52140,11 @@ Lewis J. Baker Vanessa LoBue Elizabeth Bonawitz & Patrick Shafto Department of Mathematics and Computer Science, 2Department of Psychology Rutgers University – Newark, 101 Warren St., Newark, NJ, 07102 USA"
+1b2e50412ec151486912f0bfd01703c8ec46b5a7,A Geometric Approach to Face Detector Combining,"A Geometric Approach to Face Detector +Combining⋆ +Nikolay Degtyarev and Oleg Seredin +Tula State University +http://lda.tsu.tula.ru"
1b150248d856f95da8316da868532a4286b9d58e,Analyzing 3D Objects in Cluttered Images,"Analyzing 3D Objects in Cluttered Images Mohsen Hejrati UC Irvine @@ -14904,6 +52152,18 @@ Deva Ramanan UC Irvine"
1be498d4bbc30c3bfd0029114c784bc2114d67c0,Age and Gender Estimation of Unfiltered Faces,"Age and Gender Estimation of Unfiltered Faces Eran Eidinger, Roee Enbar, Tal Hassner*"
+1b3505018e39a794eab032e7e313784b21be42e9,Saliency based Person Re-Identification in Video using Colour Features,"GRD Journals- Global Research and Development Journal for Engineering | Volume 1 | Issue 10 | September 2016 +ISSN: 2455-5703 +Saliency based Person Re-Identification in Video +using Colour Features +Srujy Krishna A U +PG Student +Shimy Joseph +Assistant Professor +Department of Computer Science and Engineering +Department of Computer Science and Engineering +Federal Institute Of Science and Technology +Federal Institute Of Science and Technology"
1bbec7190ac3ba34ca91d28f145e356a11418b67,Explorer Action Recognition with Dynamic Image Networks,"Action Recognition with Dynamic Image Networks Citation for published version: Bilen, H, Fernando, B, Gravves, E & Vedaldi, A 2017, 'Action Recognition with Dynamic Image Networks' @@ -14932,17 +52192,89 @@ Language Technology Lab, University of Duisburg-Essen (cid:52) Ubiquitous Knowledge Processing Lab (UKP) and Research Training Group AIPHES Department of Computer Science, Technische Universit¨at Darmstadt www.ukp.tu-darmstadt.de"
+1ba61a4fedc217f7bd052d1b2904567c9985dc44,Person Re-identification for Improved Multi-person Multi-camera Tracking by Continuous Entity Association,"Person Re-identification for Improved +Multi-person Multi-camera Tracking by +Continuous Entity Association +Neeti Narayan, Nishant Sankaran, Devansh Arpit, Karthik +Dantu, Srirangaraj Setlur, Venu Govindaraju +University at Buffalo"
+1b3d5d95e1fcded017f193f5cf9772bf8a1ed108,Using Keystroke Analytics to Improve Pass – Fail Classifiers,"(2017). Using +nalytics +http://dx.doi.org/10.18608/jla.2017.42.14 +keystrokes +improve +pass-fail +lassifiers. +Journal +Learning Analytics, +(2), +89–211. +Using Keystroke Analytics to Improve Pass–Fail Classifiers +Kevin Casey +Maynooth University, Ireland"
+1b74479f6e597a33703a63161527d55cc5d3096f,Self-Supervised Model Adaptation for Multimodal Semantic Segmentation,"Self-Supervised Model Adaptation for Multimodal +Semantic Segmentation +Abhinav Valada · Rohit Mohan · Wolfram Burgard"
+1b92973843c3a791bb5ca5a68405c3ecb3473ded,Building Deep Networks on Grassmann Manifolds,"Building Deep Networks on Grassmann Manifolds +Zhiwu Huang†, Jiqing Wu†, Luc Van Gool†‡ +Computer Vision Lab, ETH Zurich, Switzerland +VISICS, KU Leuven, Belgium +{zhiwu.huang, jiqing.wu,"
1b300a7858ab7870d36622a51b0549b1936572d4,Dynamic Facial Expression Recognition With Atlas Construction and Sparse Representation,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIP.2016.2537215, IEEE Transactions on Image Processing Dynamic Facial Expression Recognition with Atlas Construction and Sparse Representation Yimo Guo, Guoying Zhao, Senior Member, IEEE, and Matti Pietik¨ainen, Fellow, IEEE"
+1bea531e8271202462c7907f60a8458fa5aec00d,"Ein generisches System zur automatischen Detektion, Verfolgung und Wiedererkennung von Personen in Videodaten","Ein generisches System zur automatischen +Detektion, Verfolgung und Wiedererkennung von +Personen in Videodaten +Zur Erlangung des akademischen Grades eines +Doktor-Ingenieurs +von der Fakult¨at f¨ur +Bauingenieur-, Geo- und Umweltwissenschaften +des Karlsruher Instituts f¨ur Technologie (KIT) +(Institut f¨ur Photogrammetrie und Fernerkundung) +genehmigte +Dissertation +Dipl.-Inform. Kai J¨ungling +us Adenau +Tag der m¨undlichen Pr¨ufung: 24.01.2011 +Referent: Prof. Dr.-Ing. Stefan Hinz +Korreferent: Prof. Dr. rer. nat. Maurus Tacke +Korreferent: Prof. Dr.-Ing. Christoph Stiller +Karlsruhe 2011"
+1b6d2f8f9cbbf5e20e445a60cb7840a30975f297,Learning from Noisy Web Data with Category-level Supervision,"Learning from Noisy Web Data with Category-level +Supervision +Li Niu, Qingtao Tang, Ashok Veeraraghavan, and Ashu Sabharwal"
1b90507f02967ff143fce993a5abbfba173b1ed0,Gradient-DCT (G-DCT) descriptors,"Image Processing Theory, Tools and Applications Gradient-DCT (G-DCT) Descriptors Radovan Fusek, Eduard Sojka Technical University of Ostrava, FEECS, Department of Computer Science, 7. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic e-mail:"
+1b7b95ee13d91e9c768de6417a8919f2a3384599,A Probabilistic U-Net for Segmentation of Ambiguous Images,"A Probabilistic U-Net for Segmentation of Ambiguous +Images +Simon A. A. Kohl1∗,2,, Bernardino Romera-Paredes1, Clemens Meyer1, Jeffrey De Fauw1, +Joseph R. Ledsam1, Klaus H. Maier-Hein2, S. M. Ali Eslami1, Danilo Jimenez Rezende1, and +Olaf Ronneberger1 +Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany +DeepMind, London, UK"
+1bd80812c58de8cb0127aea915a45ebbff42dc3b,Twins 3D face recognition challenge,"Twins 3D Face Recognition Challenge +Vipin Vijayan 1, Kevin W. Bowyer 1, Patrick J. Flynn 1, Di Huang 2, Liming Chen 2, +Mark Hansen 3, Omar Ocegueda 4, Shishir K. Shah 4, Ioannis A. Kakadiaris 4"
+1ba20398e3b0154730590217a0988fbbab19e927,Doubly weighted nonnegative matrix factorization for imbalanced face recognition,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE +ICASSP 2009"
+1b6afc2cdf931a02df46d5052b4409c770ef8660,An Approach to Analyse Facial Expression from Videos using Pyramid Histogram of Orientation Gradients,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 +International Conference on Industrial Automation and Computing (ICIAC- 12-13th April 2014) +RESEARCH ARTICLE +OPEN ACCESS +An Approach to Analyse Facial Expression from Videos using +Pyramid Histogram of Orientation Gradients +Ashish D. Lonare1, Shweta V. Jain2 +Department of Computer Science and Engineering, Shri Ramdeobaba College of Engineering and +Management Nagpur, India +Department of Computer Science and Engineering, Shri Ramdeobaba College of Engineering and +Management Nagpur, India"
1b1173a3fb33f9dfaf8d8cc36eb0bf35e364913d,Registration Invariant Representations for Expression Detection,"DICTA DICTA 2010 Submission #147. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. Registration Invariant Representations for Expression Detection @@ -14950,15 +52282,33 @@ Anonymous DICTA submission Paper ID 147"
1b0a071450c419138432c033f722027ec88846ea,Looking at faces in a vehicle: A deep CNN based approach and evaluation,"Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016 978-1-5090-1889-5/16/$31.00 ©2016 IEEE"
+1b224ad99c42e696b6d98c05a87f1738e28c6c5e,A Markov Random Field Groupwise Registration Framework for Face Recognition,"A Markov Random Field Groupwise Registration +Framework for Face Recognition +Shu Liao, Dinggang Shen, and Albert C.S. Chung"
1b3b01513f99d13973e631c87ffa43904cd8a821,HMM recognition of expressions in unrestrained video intervals,"HMM RECOGNITION OF EXPRESSIONS IN UNRESTRAINED VIDEO INTERVALS José Luis Landabaso, Montse Pardàs, Antonio Bonafonte Universitat Politècnica de Catalunya, Barcelona, Spain"
+1b71e4b59358ed7ecf6117e19fc944307e58a7af,3 D Spectral Nonrigid Registration of Facial Expression Scans,"IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS +D Spectral Nonrigid Registration of +Facial Expression Scans +Gabriel L. Cuendet, Student member, IEEE, Christophe Ecabert, Marina Zimmermann, Student +member, IEEE, Hazım K. Ekenel, and Jean-Philippe Thiran, Senior Member, IEEE"
+1b2568de7363a9f46094b9cac82f4fe2ec1a4f56,Detection of Fragmented Rectangular Enclosures in Very High Resolution Remote Sensing Images,"Detection of Fragmented Rectangular Enclosures in +Very High Resolution Remote Sensing Images +Igor Zingman, Dietmar Saupe, Otávio A. B. Penatti, and Karsten Lambers"
+1b2297ba37fece76568c8b53369e6fd34d63175a,High-Resolution 3D Layout from a Single View,"High-Resolution 3D Layout from a Single View +M. Zeeshan Zia1, Michael Stark2, and Konrad Schindler1 +Photogrammetry and Remote Sensing, ETH Z¨urich, Switzerland +Stanford University and Max Planck Institute for Informatics"
1be18a701d5af2d8088db3e6aaa5b9b1d54b6fd3,Enhancement of Fast Face Detection Algorithm Based on a Cascade of Decision Trees,"ENHANCEMENT OF FAST FACE DETECTION ALGORITHM BASED ON A CASCADE OF DECISION TREES V. V. Khryashchev a, *, A. A. Lebedev a, A. L. Priorov a YSU, Yaroslavl, Russia - (vhr, Commission II, WG II/5 KEY WORDS: Face Detection, Cascade Algorithm, Decision Trees."
+1bb73d8f1224a846473d0a2ddc4289ae3e21b61c,A joint particle filter to track the position and head orientation of people using audio visual cues,"© EURASIP, 2010 ISSN 2076-1465 +8th European Signal Processing Conference (EUSIPCO-2010) +INTRODUCTION"
1b70bbf7cdfc692873ce98dd3c0e191580a1b041,Enhancing Performance of Face Recognition System Using Independent Component Analysis,"International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 03 Issue: 10 | Oct -2016 www.irjet.net p-ISSN: 2395-0072 Enhancing Performance of Face Recognition @@ -14969,16 +52319,33 @@ Guide, HOD, Computer Science, Shah and Anchor Kuttchi Engineering College, Mumba Co-Guide, Assistant Prof., Computer Science, Shah and Anchor Kuttchi Engineering College, Mumbai, India 3 ---------------------------------------------------------------------***--------------------------------------------------------------------- ards, tokens and keys. Biometric based methods examine"
+1b2dd300a43d0553f1deb578d9aea45d99472136,TABIA et al.: FAST APPROXIMATION OF DISTANCE BETWEEN ELASTIC CURVES USING KERNELS,
+1b4424e06ac29b72535727b92f261f39d065e858,3D Pictorial Structures Revisited: Multiple Human Pose Estimation,"D Pictorial Structures Revisited: +Multiple Human Pose Estimation +Vasileios Belagiannis, Sikandar Amin, Mykhaylo Andriluka, +Bernt Schiele, Nassir Navab, and Slobodan Ilic"
+1bf0b5186af083117af136dfcb08ed28828664d0,"Deep Filter Banks for Texture Recognition, Description, and Segmentation","Int J Comput Vis +DOI 10.1007/s11263-015-0872-3 +Deep Filter Banks for Texture Recognition, Description, +nd Segmentation +Mircea Cimpoi1 · Subhransu Maji2 · Iasonas Kokkinos3 · Andrea Vedaldi1 +Received: 4 June 2015 / Accepted: 20 November 2015 +© The Author(s) 2015. This article is published with open access at Springerlink.com"
1b71d3f30238cb6621021a95543cce3aab96a21b,Fine-grained Video Classification and Captioning,"Fine-grained Video Classification and Captioning Farzaneh Mahdisoltani1,2, Guillaume Berger2, Waseem Gharbieh2 David Fleet1, Roland Memisevic2 {farzaneh, University of Toronto1, Twenty Billion Neurons2"
+1b807b6abaeef68edfbdc4200e198bf4e9613198,Image Processing Pipeline for Facial Expression Recognition under Variable Lighting,"Image Processing Pipeline for Facial Expression Recognition under Variable +Lighting +Ralph Ma, Amr Mohamed"
1b4f6f73c70353869026e5eec1dd903f9e26d43f,Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels,"Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Jiechao Xiong, Shaogang Gong, Yizhou Wang, and Yuan Yao"
1bc23c771688109bed9fd295ce82d7e702726327,Sparse Modeling of High - Dimensional Data for Learning and Vision,(cid:13) 2011 Jianchao Yang
+1b0548e52a1ffc7ebffe5200e2111525c9f7fd4a,Novel Views of Objects from a Single Image,"Novel Views of Objects from a Single Image +Konstantinos Rematas, Chuong Nguyen, Tobias Ritschel, Mario Fritz, and Tinne Tuytelaars"
1b4bc7447f500af2601c5233879afc057a5876d8,Facial Action Unit Classification with Hidden Knowledge under Incomplete Annotation,"Facial Action Unit Classification with Hidden Knowledge under Incomplete Annotation Jun Wang @@ -14996,11 +52363,38 @@ Troy, NY P.R.China, 230027 P.R.China, 230027 USA, 12180"
+1b7a0fffb5ee96adece2f6079f5e9ab79c3bc50e,Spigan: Privileged Adversarial Learning,"Under review as a conference paper at ICLR 2019 +SPIGAN: PRIVILEGED ADVERSARIAL LEARNING +FROM SIMULATION +Anonymous authors +Paper under double-blind review"
7711a7404f1f1ac3a0107203936e6332f50ac30c,Action Classification and Highlighting in Videos,"Action Classification and Highlighting in Videos Atousa Torabi Disney Research Pittsburgh Leonid Sigal Disney Research Pittsburgh"
+77ad2727065cb3dc5c91975604af01c82ec5c9f6,Convolutional Neural Networks for Disaster Images Retrieval,"Convolutional Neural Networks for Disaster Images Retrieval +Sheharyar Ahmad1,Kashif Ahmad2, Nasir Ahmad1, Nicola Conci2 +DCSE, UET Peshawar, Pakistan +DISI-University of Trento, Trento"
+776c5e37eecd26049ae31f56b3249c390e25e4e9,Angry and Beautiful: The Interactive Effect of Facial Expression and Attractiveness on Time Perception,"Psihologijske teme, 25, 2016 (2), 299-315 +Izvorni znanstveni rad – UDK –159.925.072 +59.937.072:115 +Angry and Beautiful: The Interactive Effect of Facial +Expression and Attractiveness on Time Perception +Jasmina Tomas +Department of Psychology, Faculty of Humanities and Social Sciences, +University of Zagreb, Croatia +Ana Marija Španić +Child Protection Center of Zagreb, Zagreb, Croatia"
+770b3855cdd15b49c89e4053b6cedafe53cecd6f,Improved Face Recognition Using Pseudo 2 - DHidden,"ImprovedFaceRecognitionUsingPseudo-D +HiddenMarkovModels +StefanEickeler,StefanM(cid:127)uller,GerhardRigoll +Gerhard-Mercator-UniversityDuisburg +DepartmentofComputerScience +FacultyofElectricalEngineering + +-ti.uni-duisburg.de"
778c9f88839eb26129427e1b8633caa4bd4d275e,Pose pooling kernels for sub-category recognition,"Pose Pooling Kernels for Sub-category Recognition Ning Zhang ICSI & UC Berkeley @@ -15012,11 +52406,76 @@ ICSI & UC Berkeley" Model Zhen-Hua Feng, Member, IEEE, Josef Kittler, Life Member, IEEE, William Christmas, and Xiao-Jun Wu, Member, IEEE"
+779f67f2fe406828bbe7a19e8736cb5fd309e321,Fine-Grained Recognition in the Wild: A Multi-task Domain Adaptation Approach,"Fine-grained Recognition in the Wild: +A Multi-Task Domain Adaptation Approach +Timnit Gebru +Judy Hoffman +Li Fei-Fei +CS Department Stanford University +{tgebru, jhoffman,"
+771a9e7dc747fa2282815a4863502183f4e887c8,Efficient Bootsrapping and Query Adaptive Ranking for Image Search,"The International Journal Of Science & Technoledge (ISSN 2321 – 919X) +www.theijst.com +THE INTERNATIONAL JOURNAL OF +SCIENCE & TECHNOLEDGE +Efficient Bootsrapping and Query Adaptive Ranking for Image Search +A. A. R. Senthilkumar +Head of the Department, Department of Master of Computer Application +PGP College of Engineering and Technology, Namakkal +P. Mayuri +Department of Computer Science and Engineering +PGP College of Engineering and Technology, Namakkal"
+774c8945ccf0f5315482abb8cf84ac5d37c60aa0,A Comparative Study of Feature Extraction Methods in Images Classification,"I.J. Image, Graphics and Signal Processing, 2015, 3, 16-23 +Published Online February 2015 in MECS (http://www.mecs-press.org/) +DOI: 10.5815/ijigsp.2015.03.03 +A Comparative Study of Feature Extraction +Methods in Images Classification +University of Sciences and Technology Mohamed Boudiaf USTO-MB, Faculty of Mathematics and Computer Science, +Seyyid Ahmed Medjahed +Oran, 31000, Algeria +Email:"
+778952cc94d5baa5132ffbe2cf342f80032f5f73,Comparative Analysis of Techniques for the Recognition of Stabbed Wound and Accidental Wound Patterns,"International Journal of Computer Applications (0975 – 8887) +Volume 182 – No. 13, September 2018 +Comparative Analysis of Techniques for the Recognition +of Stabbed Wound and Accidental Wound Patterns +Dayanand G. Savakar +Department of Computer Science +Rani Channamma University, Belagavi +INDIA +schemas of"
+7711330fb88e2522a5779a09c1622b75557f9254,Real-time detection and tracking of pedestrians in CCTV images using a deep convolutional neural network,"Real-time detection and tracking of pedestrians in +CCTV images using a deep convolutional neural network +Debaditya Acharya +Kourosh Khoshelham +Stephan Winter +Infrastructure Engineering, The University of Melbourne"
+77882930692d41db107430a5a524ff5e4bb2ee5c,Hyperbolic Attention Networks,"Hyperbolic Attention Networks +Caglar Gulcehre Misha Denil Mateusz Malinowski Ali Razavi +Razvan Pascanu Karl Moritz Hermann +Peter Battaglia Victor Bapst +David Raposo Adam Santoro Nando de Freitas +Deepmind"
+77e69753fc7cf007a136b12f102e1e11a93f87f5,Head and Body Orientation Estimation Using Convolutional Random Projection Forests.,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2017.2784424, IEEE +Transactions on Pattern Analysis and Machine Intelligence +Head and Body Orientation Estimation Using +Convolutional Random Projection Forests +Donghoon Lee, Ming-Hsuan Yang, and Songhwai Oh∗"
+7730fd15ff14dd84d71f965bfeab8e4d790d91d8,SpaRTA - Tracking across occlusions via global partitioning of 3D clouds of points,"SpaRTA +Tracking across occlusions via global +partitioning of 3D clouds of points +Andrea Cavagna, Stefania Melillo, Leonardo Parisi, Federico Ricci-Tersenghi"
778bff335ae1b77fd7ec67404f71a1446624331b,Hough Forest-Based Facial Expression Recognition from Video Sequences,"Hough Forest-based Facial Expression Recognition from Video Sequences Gabriele Fanelli, Angela Yao, Pierre-Luc Noel, Juergen Gall, and Luc Van Gool BIWI, ETH Zurich http://www.vision.ee.ethz.ch VISICS, K.U. Leuven http://www.esat.kuleuven.be/psi/visics"
+776b77306bdb852c89a22ba142fb57c8e8bb7bb5,Efficient On-Board Stereo Vision Pose Estimation,"Efficient On-Board Stereo Vision +Pose Estimation(cid:2) +Angel D. Sappa1, Fadi Dornaika2, David Ger´onimo1, and Antonio L´opez1 +Computer Vision Center, Edifici O Campus UAB +08193 Bellaterra, Barcelona, Spain +{asappa, dgeronimo, +Institut G´eographique National +94165 Saint Mand´e, France"
7726a6ab26a1654d34ec04c0b7b3dd80c5f84e0d,Content-aware compression using saliency-driven image retargeting,"CONTENT-AWARE COMPRESSION USING SALIENCY-DRIVEN IMAGE RETARGETING Fabio Z¨und*†, Yael Pritch*, Alexander Sorkine-Hornung*, Stefan Mangold*, Thomas Gross† *Disney Research Zurich @@ -15035,6 +52494,14 @@ Ahmad Poursaberi1*, Hossein Ahmadi Noubari2, Marina Gavrilova1 and Svetlana N Ya 77037a22c9b8169930d74d2ce6f50f1a999c1221,Robust Face Recognition With Kernelized Locality-Sensitive Group Sparsity Representation,"Robust Face Recognition With Kernelized Locality-Sensitive Group Sparsity Representation Shoubiao Tan, Xi Sun, Wentao Chan, Lei Qu, and Ling Shao"
+7714a5aa27ab5ad4d06a81fbb3e973d3b1002ac1,SSD-Sface : Single shot multibox detector for small faces,"SSD-Sface: Single shot multibox detector for small faces +C. Thuis"
+77cb6ea4feff6f44e9977cc7572185d24e48ce40,On the Complementarity of Face Parts for Gender Recognition,"On the Complementarity of Face Parts for +Gender Recognition +Yasmina Andreu and Ram´on A. Mollineda +Dept. Llenguatges i Sistemes Inform`atics +Universitat Jaume I. Castell´o de la Plana, Spain"
+775c15a5dfca426d53c634668e58dd5d3314ea89,Image Quality-aware Deep Networks Ensemble for Efficient Gender Recognition in the Wild,
779ad364cae60ca57af593c83851360c0f52c7bf,Steerable Pyramids Feature Based Classification Using Fisher Linear Discriminant for Face Recognition,"Steerable Pyramids Feature Based Classification Using Fisher Linear Discriminant for Face Recognition EL AROUSSI MOHAMED1 @@ -15045,6 +52512,86 @@ ABOUTAJDINE DRISS1 GSCM-LRIT, Faculty of Sciences, Mohammed V University-Agdal, Rabat, Morocco DESTEC, FLSHR Mohammed V University-Agdal, Rabat, Morocco PO.Box 1014, Rabat, Morocco"
+77b11260154e13e33c84599feba4cdc4f781bf71,Building User Profiles from Shared Photos,Building User Profiles from Shared Photos
+7793c7431f3ddce74fe2d444df614d8d8fd9af4a,A Review of Neural Network based Semantic Segmentation for Scene Understanding in Context of the self driving Car,"A Review of Neural Network based Semantic Segmentation for +Scene Understanding in Context of the self driving Car +J. Niemeijer1, P. Pekezou Fouopi2, S. Knake-Langhorst2, and E. Barth3 +Medizinische Informatik, Universität zu Lübeck, +German Aerospace Center, Braunschweig, +Institute of Neuro- and Bioinformatics, Universität zu Lübeck,"
+77dc158a979731d2ed01145b1d3ead34a6c33487,Preference for geometric patterns early in life as a risk factor for autism.,"ORIGINAL ARTICLE +ONLINE FIRST +Preference for Geometric Patterns Early in Life +s a Risk Factor for Autism +Karen Pierce, PhD; David Conant; Roxana Hazin, BS; Richard Stoner, PhD; Jamie Desmond, MPH +Context: Early identification efforts are essential for the +early treatment of the symptoms of autism but can only oc- +ur if robust risk factors are found. Children with autism +often engage in repetitive behaviors and anecdotally pre- +fertovisuallyexaminegeometricrepetition,suchasthemov- +ing blade of a fan or the spinning of a car wheel. The ex- +tent to which a preference for looking at geometric repeti- +tion is an early risk factor for autism has yet to be examined. +Objectives: To determine if toddlers with an autism spec- +trum disorder (ASD) aged 14 to 42 months prefer to vi- +sually examine dynamic geometric images more than so- +ial images and to determine if visual fixation patterns +an correctly classify a toddler as having an ASD. +Design: Toddlers were presented with a 1-minute movie +depicting moving geometric patterns on 1 side of a video"
+77851ca35105ebe007d99e5d78ceb3473491071c,Spatiotemporal Stacked Sequential Learning for Pedestrian Detection,"Spatiotemporal Stacked Sequential Learning for Pedestrian Detection +Alejandro Gonz´alez1 +Sebastian Ramos1 +David V´azquez1 +Antonio M. L´opez1 +Jaume Amores1 +Computer Vision Center, Barcelona +Universitat Aut`onoma de Barcelona +United Technologies Research Center"
+77351eaeb65e374a4d1e54acc28fea426670e364,Compression Based Face Recognition Using Transform Domain Features Fused at Matching Level,"Signal & Image Processing : An International Journal (SIPIJ) Vol.8, No.4, August 2017 +COMPRESSION BASED FACE RECOGNITION +USING TRANSFORM DOMAIN FEATURES +FUSED AT MATCHING LEVEL +Srinivas Halvia, Nayina Ramapurb , K B Rajac and Shanti Prasadd +Dayananda Sagar College of Engineering, Bangalore, India. +Sai-Tektronix Pvt. Ltd., Bangalore, India. +University Visvesvaraya College of Engineering, Bangalore, India. +dK.S. Institute of Technology, Bangalore, India."
+77052654a37b88719c014c5afd3db89cb2288aeb,Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features,"Hindawi Publishing Corporation +e Scientific World Journal +Volume 2015, Article ID 786013, 17 pages +http://dx.doi.org/10.1155/2015/786013 +Research Article +Lung Cancer Prediction Using Neural Network Ensemble with +Histogram of Oriented Gradient Genomic Features +Emmanuel Adetiba and Oludayo O. Olugbara +ICT and Society Research Group, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa +Correspondence should be addressed to Oludayo O. Olugbara; +Received 12 December 2014; Accepted 29 January 2015 +Academic Editor: Alexander Schonhuth +Copyright © 2015 E. Adetiba and O. O. Olugbara. This is an open access article distributed under the Creative Commons +Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is +properly cited. +This paper reports an experimental comparison of artificial neural network (ANN) and support vector machine (SVM) ensembles +nd their “nonensemble” variants for lung cancer prediction. These machine learning classifiers were trained to predict lung cancer +using samples of patient nucleotides with mutations in the epidermal growth factor receptor, Kirsten rat sarcoma viral oncogene, +nd tumor suppressor p53 genomes collected as biomarkers from the IGDB.NSCLC corpus. The Voss DNA encoding was used to +map the nucleotide sequences of mutated and normal genomes to obtain the equivalent numerical genomic sequences for training"
+77c81c13a110a341c140995bedb98101b9e84f7f,WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection,"WILDTRACK: A Multi-camera HD Dataset for +Dense Unscripted Pedestrian Detection +Tatjana Chavdarova1, Pierre Baqu´e2, St´ephane Bouquet2, +Andrii Maksai2, Cijo Jose1, Timur Bagautdinov2, Louis Lettry3, +Pascal Fua2, Luc Van Gool3, and Franc¸ois Fleuret1 +Machine Learning group, Idiap Research Institute & ´Ecole Polytechnique F´ed´erale de Lausanne +CVLab, ´Ecole Polytechnique F´ed´erale de Lausanne +Computer Vision Lab, ETH Zurich"
+771b7d76df1ed476dea859034a276f14ad1e49f1,Multi-scale elastic graph matching for face detection,"Sato and Kuriya EURASIP Journal on Advances in Signal Processing 2013, 2013:175 +http://asp.eurasipjournals.com/content/2013/1/175 +REVIEW +Open Access +Multi-scale elastic graph matching for face +detection +Yasuomi D Sato1,2,3* and Yasutaka Kuriya1"
77d31d2ec25df44781d999d6ff980183093fb3de,The Multiverse Loss for Robust Transfer Learning,"The Multiverse Loss for Robust Transfer Learning Supplementary . Omitted proofs @@ -15065,6 +52612,46 @@ Lemma 1. The minimizers F ∗, b∗ of L are not unique, and it holds that for any vector v ∈ Rc and scalar s, the solu- tions F ∗ + v1(cid:62) Proof. denoting V = v1(cid:62)"
+77d4843a177031b2b5721824280033e2e601334c,Comparative Evaluation of 3D versus 2D Modality for Automatic Detection of Facial Action Units,"Author’s Accepted Manuscript +Comparative Evaluation of 3D versus 2D Modality +for Automatic Detection of Facial Action Units +Arman Savran, Bülent Sankur, M. Taha Bilge +Reference: +S0031-3203(11)00310-4 +doi:10.1016/j.patcog.2011.07.022 +PR 4228 +To appear in: +Pattern Recognition +Received date: +Revised date: +Accepted date: +3 November 2010 +5 July 2011 +9 July 2011 +www.elsevier.com/locate/pr +Cite this article as: Arman Savran, Bülent Sankur and M. Taha Bilge, Comparative Eval- +uation of 3D versus 2D Modality for Automatic Detection of Facial Action Units, Pattern +Recognition, doi:10.1016/j.patcog.2011.07.022"
+77fb0266b354d33f3725629c2ddce3d2342b318a,Is Attribute-Based Zero-Shot Learning an Ill-Posed Strategy?,"Is Attribute-Based Zero-Shot Learning +n Ill-Posed Strategy? +Ibrahim Alabdulmohsin1, Moustapha Cisse2, and Xiangliang Zhang1(B) +Computer, Electrical and Mathematical Sciences and Engineering Division, +King Abdullah University of Science and Technology (KAUST), +Thuwal 23955-6900, Saudi Arabia +Facebook Artificial Intelligence Research (FAIR), Menlo Park, USA +http://mine.kaust.edu.sa"
+77c7f5c5852c189b59c34ebbbbec03e5e4060428,Talking to Robots: Learning to Ground Human Language in Perception and Execution,"(cid:13)Copyright 2014 +Cynthia Matuszek"
+482769e4c4cf832128b52f1bdff873af1eee8ba8,Robust Face Detection using Fusion of Haar and Daubechies Orthogonal Wavelet Template,"International Journal of Computer Applications (0975 – 8887) +Volume 46– No.6, May 2012 +Robust Face Detection using Fusion of Haar and +Daubechies Orthogonal Wavelet Template +Chirag I Patel +Sanjay Garg +Research scholar, Institute of Technology, +Professor, Institute of Technology, +Nirma University, Ahmedabad, Gujarat, India +Nirma University, Ahmedabad, Gujarat, India"
48186494fc7c0cc664edec16ce582b3fcb5249c0,P-CNN: Pose-Based CNN Features for Action Recognition,"P-CNN: Pose-based CNN Features for Action Recognition Guilhem Ch´eron∗ † Ivan Laptev∗ @@ -15082,10 +52669,94 @@ Project Code: 17007" 486a82f50835ea888fbc5c6babf3cf8e8b9807bc,Face Search at Scale: 80 Million Gallery,"MSU TECHNICAL REPORT MSU-CSE-15-11, JULY 24, 2015 Face Search at Scale: 80 Million Gallery Dayong Wang, Member, IEEE, Charles Otto, Student Member, IEEE, Anil K. Jain, Fellow, IEEE"
+48fb35946641351f7480a5b88567aae59e526d82,Generating faces for affect analysis,"Noname manuscript No. +(will be inserted by the editor) +Generating faces for affect analysis +Dimitrios Kollias (cid:63) · Shiyang Cheng † · Evangelos Ververas ∗ · Irene +Kotsia1 · Stefanos Zafeiriou2 +Received: Sept 30th 2018 / Accepted: date"
+48b38d157272f03f6b44c0df61130534d11d8569,Natural Language Guided Visual Relationship Detection,"oard)(person-behind-kid)(skate board-on-street)(person-sit on-street)...ImageVisual relationshipsFigure1:Visualrelationshipsrepresenttheinteractionsbe-tweenobservedobjects.Eachrelationshiphasthreeele-ments:subject,predicateandobject.HereisanexampleimagefromVisualGenome[17].Ourproposedmethodisabletoeffectivelydetectnumerouskindsofdifferentrela-tionshipsfromsuchimage.objectsinimages.Therelationshipscanberepresentedinatripletformofhsubject-predicate-objecti,e.g.,hkid-on-skateboardi,asshowninFig.1.Anaturalapproachforthistaskistotreatitasaclassificationproblem:eachkindofrelationships/phraseisarelationcategory[32],asshowninFig.2.Totrainsuchreliableandrobustmodel,suffi-cienttrainingsamplesforeachpossiblehsubject-predicate-objecticombinationareessential.ConsidertheVisualRe-lationshipDataset(VRD)[24],withN=100objectcate-goriesandK=70predicates,thenthereareN2K=700kcombinationsintotal.However,itcontainsonly38kre-lationships,whichmeansthateachcombinationhaslessthan1sampleonaverage.Thepreviousclassification-basedworkscanonlydetectthemostcommonrelationships,e.g.,[32]studiedonly13frequentrelationships.Anotherpopularstrategyistodetecttherelationshippredicatesandtheobjectcategoriesindependently.Al-thoughthenumberofcategoriesdecreasesdramatically,thesemanticrelationshipbetweentheobjectsandthepredi-catesareignored.Consequently,thephrasewhichhasthesamepredicatebutdifferentagentsisconsideredasthesametypeofrelationship.Forinstance,the”clock-on-1"
+485e0d178bafa959ac956aa8de6556a2439c6663,Learning from Examples to Generalize over Pose and Illumination,"Learning from Examples to Generalize over Pose +nd Illumination +Marco K. M¨uller and Rolf P. W¨urtz +Institute f¨ur Neural Computation, Ruhr-University, 44780 Bochum, Germany"
+483ca50670c5f7d33f7c722dd71105327a30ea60,Improving object classification using semantic attributes,"SU, ALLAN, JURIE: SEMANTIC ATTRIBUTES +Improving object classification +using semantic attributes +Yu Su +http://users.info.unicaen.fr/~ysu/ +Moray Allan +http://users.info.unicaen.fr/~mallan/ +Frédéric Jurie +http://users.info.unicaen.fr/~jurie/ +GREYC +Université de Caen +4032 Caen Cedex +France"
+4839f861709e6ae6d4d032228473ce1764acbdcc,Finding Egocentric Image Topics through Convolutional Neural Network Based Representations,"Finding Egocentric Image Topics through Convolutional Neural Network Based Representations +Kai Zhen, David Crandall +School of Informatics and Computing, Indiana University. +Life-logging cameras create huge collections of photos, even for a single +person on a single day [1, 6], which makes it difficult for users to browse +or organize their photos effectively. Unlike text corpora in which words +reate intermediate representations that carry semantic meaning for higher- +level concepts such as topics, images have no such obvious intermediate +representation to connect raw pixels and semantics. Egocentric photos are +particularly challenging because they were taken opportunistically, so they +re often blurry and poorly-composed compared to consumer-style images. +This paper applies topic modeling on deep features to extract visual +“concept clusters” from egocentric datasets. We discretize features to form +better analogy to the word-document model, which we find yields faster +onvergence during inference. We also find that removing frequent, less in- +formative features helps to prevent outliers and improve the semantic mean- +ing of extracted topics, analogous to removing stop words in the text mining +domain. In a generative process similar to that proposed in LDA [2], we +model an image as being generated by first choosing topics, and then sam- +pling features (visual words) from selected topics,"
4850af6b54391fc33c8028a0b7fafe05855a96ff,Discovering useful parts for pose estimation in sparsely annotated datasets,"Discovering Useful Parts for Pose Estimation in Sparsely Annotated Datasets Mikhail Breslav1, Tyson L. Hedrick2, Stan Sclaroff1, and Margrit Betke1 Department of Computer Science and 2Department of Biology Boston University and 2University of North Carolina"
+485eb41be3ce1600e9934167808b0319a6c3ec2f,A Novel Structural-Description Approach for Image Retrieval,"A Novel Structural-Description Approach For +Image Retrieval +Christoph Rasche, Constantin Vertan +Laboratorul de Analiza si Prelucrarea Imaginilor +Universitatea Politehnica din Bucuresti +Bucuresti 061071, RO"
+48c0059feb14ca3deedfa7e3b53fbc34bd6d8efb,Facial Expression Retrieval Using 3-Dimensional Mesh Sequences,"Facial Expression Retrieval Using +-Dimensional Mesh Sequences +Danelakis E. Antonios* +National and Kapodistrian University of Athens +Department of Informatics and Telecommunications"
+48b4f49ec708677fc9f70edc74fd0f92ef986406,CS168: The Modern Algorithmic Toolbox Lecture #6: Stochastic Gradient Descent and Regularization,"CS168: The Modern Algorithmic Toolbox +Lecture #6: Stochastic Gradient Descent and +Regularization +Tim Roughgarden & Gregory Valiant∗ +April 13, 2016 +Context +Last lecture we covered the basics of gradient descent, with an emphasis on the intuition +ehind and geometry underlying the method, plus a concrete instantiation of it for the +problem of linear regression (fitting the best hyperplane to a set of data points). This basic +method is already interesting and useful in its own right (see Homework #3). +This lecture we’ll cover two extensions that, while simple, will bring your knowledge a step +loser to the state-of-the-art in modern machine learning. The two extensions have different +haracters. The first concerns how to actually solve (computationally) a given unconstrained +minimization problem, and gives a modification of basic gradient descent — “stochastic +gradient descent” — that scales to much larger data sets. The second extension concerns +problem formulation rather than implementation, namely the choice of the unconstrained +optimization problem to solve (i.e., the objective function f ). Here, we introduce the idea +of “regularization,” with the goal of avoiding overfitting the function learned to the data set +t hand, even for very high-dimensional data. +Recap"
+4871300f1e5a58ce920e6b5be14e89c5da4aa4c4,Manifold Learning for Video-to-Video Face Recognition,"Manifold Learning for Video-to-Video Face +Recognition"
+48d299fe3303c80f840816fc76971a42b4a8b624,Predicting Important Objects for Egocentric Video Summarization,"http://dx.doi.org/10.1007/s11263-014-0794-5 +Predicting Important Objects for Egocentric Video Summarization +Yong Jae Lee · Kristen Grauman +Received: date / Accepted: date"
+488676e61fcf7b79d83c25fb103c8d8a854d8987,Leveraging Convolutional Pose Machines for Fast and Accurate Head Pose Estimation,"Leveraging Convolutional Pose Machines +for Fast and Accurate Head Pose Estimation +Yuanzhouhan Cao1, Olivier Can´evet 1 and Jean-Marc Odobez1,2"
48a5b6ee60475b18411a910c6084b3a32147b8cd,Pedestrian Attribute Recognition with Part-based CNN and Combined Feature Representations,"Pedestrian attribute recognition with part-based CNN nd combined feature representations Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla @@ -15106,15 +52777,70 @@ broad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non,"
+486e5c2996726ec0f7c37077a2752dc4bd8c1413,Linearized Smooth Additive Classifiers,"Linearized Smooth Additive Classifiers +Subhransu Maji +Toyota Technological Institute at Chicago, +Chicago, IL 60637, USA"
+480810001ed845ec04a20b00461a8a82fcffbb52,Autistic Traits and Brain Activation during Face-to-Face Conversations in Typically Developed Adults,"Autistic Traits and Brain Activation during Face-to-Face +Conversations in Typically Developed Adults +Masashi Suda, Yuichi Takei, Yoshiyuki Aoyama, Kosuke Narita, Noriko Sakurai, Masato Fukuda*, +Masahiko Mikuni +Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan"
+488493dc29c844b36660395266d8d347c7cfa9ce,Towards Flexible Classification: Cost-Aware Online Query of Cascades and Operating Points,"Towards Flexible Classification: Cost-Aware +Online Query of Cascades and Operating Points +Brandyn White, Andrew Miller, Tom Yeh, and Larry S. Davis +University of Maryland: College Park"
+48a42303559ea518ba06f54a8cfce4226bb0e77e,Urban tribes: Analyzing group photos from a social perspective,"Urban Tribes: Analyzing Group Photos from a Social Perspective +Ana C. Murillo†, +Iljung S. Kwak‡, Lubomir Bourdev§∗, David Kriegman‡, Serge Belongie‡ +DIIS - Instituto de Ingenier´ıa de Arag´on. Universidad de Zaragoza, Spain +§Facebook. 1601 Willow Road, Menlo Park, CA 94025, USA +Computer Science and Engineering Department. University of California, San Diego, USA"
+483f85e1ebef9d10a951b3c01751892aca92a2c2,Adaptive Classification for Person Re-identification Driven by Change Detection,"Adaptive Classification for Person Re-Identification Driven by Change +Detection +C. Pagano1, E. Granger1, R. Sabourin1, G. L. Marcialis2 and F. Roli2 +Lab. d’imagerie, de vision et d’intelligence artificielle, +´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montreal, Canada +Pattern Recognition and Applications Group, Dept. of Electrical and Electronic Engineering, +{eric.granger, +University of Cagliari, Cagliari, Italy +Keywords: +Multi-Classifier Systems, Incremental Learning, Adaptive Biometrics, Change Detection, Face Recognition, +Video Surveillance."
+484c2617471fd742c4806f9281e5add45c6831a7,LSTM Self-Supervision for Detailed Behavior Analysis,"LSTM Self-Supervision for Detailed Behavior Analysis +Biagio Brattoli1∗, Uta B¨uchler1∗, Anna-Sophia Wahl2, Martin E. Schwab2, Bj¨orn Ommer1 +HCI / IWR, Heidelberg University, Germany +Department of HST, ETH Zurich, Switzerland"
+486f08c875e88b3f1f157e7de1ae2cf5176f5431,Structure-from-motion for Calibration of a Vehicle Camera System with Non-overlapping Fields-of-view in an Urban Environment,"STRUCTURE-FROM-MOTION FOR CALIBRATION OF A VEHICLE CAMERA SYSTEM +WITH NON-OVERLAPPING FIELDS-OF-VIEW IN AN URBAN ENVIRONMENT +Photogrammetry & Remote Sensing, Technische Universitaet Muenchen, Germany - (alexander.hanel, +A. Hanela, U. Stillaa +Commission I, WG 9 +KEY WORDS: vehicle cameras, camera calibration, structure from motion, bundle adjustment"
488e475eeb3bb39a145f23ede197cd3620f1d98a,Pedestrian Attribute Classification in Surveillance: Database and Evaluation,"Pedestrian Attribute Classification in Surveillance: Database and Evaluation Jianqing Zhu, Shengcai Liao, Zhen Lei, Dong Yi, Stan Z. Li∗ Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences (CASIA) 95 Zhongguancun East Road, 100190, Beijing, China {jqzhu, scliao, zlei, dyi,"
+48bf7357723abf7770400d68f914d6a7ca5a1a5f,Real-Time Head Pose Tracking with Online Face Template Reconstruction,"Real-Time Head Pose Tracking with Online +Face Template Reconstruction +Songnan Li, Member, IEEE, +King Ngi Ngan, Fellow, IEEE, +Raveendran Paramesran, Senior Member, IEEE, +nd Lu Sheng"
+48f45accce6a4a22e4ead41fe292a915f3531f5b,Active Learning for Visual Question Answering: An Empirical Study,"Active Learning for Visual Question Answering: +An Empirical Study +Xiao Lin +Virginia Tech +Devi Parikh +Georgia Tech"
487df616e981557c8e1201829a1d0ec1ecb7d275,Acoustic Echo Cancellation Using a Vector-Space-Based Adaptive Filtering Algorithm,"Acoustic Echo Cancellation Using a Vector-Space-Based Adaptive Filtering Algorithm Yu Tsao, Member IEEE, Shih-Hau Fang*, Senior Member IEEE, and Yao Shiao"
+486a0044b9c86c6f648f153f3d3f2e534342b754,Trajectories and Maneuvers of Surrounding Vehicles With Panoramic Camera Arrays,"Trajectories and Maneuvers of Surrounding Vehicles +with Panoramic Camera Arrays +Jacob V. Dueholm, Miklas S. Kristoffersen, Ravi K. Satzoda, Thomas B. Moeslund, and Mohan M. Trivedi"
48319e611f0daaa758ed5dcf5a6496b4c6ef45f2,Non Binary Local Gradient Contours for Face Recognition,"Non Binary Local Gradient Contours for Face Recognition Abdullah Gubbia, Mohammad Fazle Azeemb, M Sharmila Kumaric Department of Electronics and Communication, P.A. College of Engnineering, Mangalore, @@ -15135,12 +52861,24 @@ Vector Machine, KNN, Face Recognition. . INTRODUCTION In face recognition, the major issue to be ad- dressed is the extraction of features which are"
+4875bed500321dec353959a556541715da5c9d18,A Domain Agnostic Normalization Layer for Unsupervised Adversarial Domain Adaptation,"A Domain Agnostic Normalization Layer +for Unsupervised Adversarial Domain Adaptation +R. Romijnders +Eindhoven, University of Technology +P. Meletis +G. Dubbelman"
48cfc5789c246c6ad88ff841701204fc9d6577ed,Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis,"J Inf Process Syst, Vol.12, No.3, pp.392~409, September 2016 ISSN 1976-913X (Print) ISSN 2092-805X (Electronic) Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis Leila Boussaad*, Mohamed Benmohammed**, and Redha Benzid***"
+484c4eec34e985d8ca0c20bf83efc56881180709,Efficient semantic image segmentation with superpixel pooling,"Efficient semantic image segmentation with superpixel pooling +Mathijs Schuurmans Maxim Berman Matthew B. Blaschko +Dept. ESAT, Center for Processing Speech and Images +KU Leuven, Belgium +{maxim.berman, +June 8, 2018"
70f189798c8b9f2b31c8b5566a5cf3107050b349,The challenge of face recognition from digital point-and-shoot cameras,"The Challenge of Face Recognition from Digital Point-and-Shoot Cameras J. Ross Beveridge∗ Geof H. Givens§ @@ -15154,11 +52892,45 @@ Patrick J. Flynn(cid:107) Bruce A. Draper∗, Hao Zhang∗ Su Cheng†"
+70671018d4597b6d2d0c99b38b1f1a3f1271eaec,Learning Representations Specialized in Spatial Knowledge: Leveraging Language and Vision,"Transactions of the Association for Computational Linguistics, vol. 6, pp. 133–144, 2018. Action Editor: Stefan Riezler. +Submission batch: 6/2017; Revision batch: 9/2017; Published 2/2018. +(cid:13)2018 Association for Computational Linguistics. Distributed under a CC-BY 4.0 license."
+70f0636b14b9e3916a780d70a5c712e8fea739da,"ANDRE MOUTON On Artefact Reduction , Segmentation and Classification of 3 D Computed Tomography Imagery in Baggage Security Screening","CRANFIELD UNIVERSITY +SCHOOL OF ENGINEERING +PhD THESIS +Academic Year 2013-2014 +ANDRE MOUTON +On Artefact Reduction, Segmentation and Classification of +D Computed Tomography Imagery in Baggage Security +Screening +Supervised by: Dr Toby Breckon and Dr Carol Armitage +March 2014 +This thesis is submitted in partial fulfilment of the requirements for +the Degree of Doctor of Philosophy +©Cranfield University, 2014. All rights reserved. No part of this +publication may be reproduced without the written permission of +the copyright holder."
+70ec156f7e6de0275c7e4e95e35f1bc1e92e29b3,Deep learning ensembles for melanoma recognition in dermoscopy images,"Deep learning ensembles for melanoma recognition in dermoscopy images1 +N. C. F. Codella, Q. B. Nguyen, S. Pankanti, D. Gutman, B. Helba, A. Halpern, J. R. Smith"
70109c670471db2e0ede3842cbb58ba6be804561,Zero-Shot Visual Recognition via Bidirectional Latent Embedding,"Noname manuscript No. (will be inserted by the editor) Zero-Shot Visual Recognition via Bidirectional Latent Embedding Qian Wang · Ke Chen Received: date / Accepted: date"
+706600aa77ffb165097e4aeccb2b214dabdb8092,Combining Graph-based Dependency Features with Convolutional Neural Network for Answer Triggering,"Combining Graph-based Dependency Features with +Convolutional Neural Network for Answer Triggering +Deepak Gupta∗, Sarah Kohail†, Pushpak Bhattacharyya∗ +Indian Institute of Technology Patna, India +Universit¨at Hamburg, Germany +{deepak.pcs16,"
+708a55d65568faf8158417ddfb79e728b2b28f86,3D Body Model Construction and Matching for Real Time People Re-Identification,"Eurographics Italian Chapter Conference (2010) +E. Puppo, A. Brogni, and L. De Floriani (Editors) +D Body Model Construction and Matching for Real Time +People Re-Identification +D. Baltieri, R. Vezzani and R. Cucchiara +Dipartimento di Ingegneria dell’Informazione +University of Modena and Reggio Emilia +Via Vignolese, 905 - 41100 Modena - Italy"
706236308e1c8d8b8ba7749869c6b9c25fa9f957,Crowdsourced data collection of facial responses,"Crowdsourced Data Collection of Facial Responses Daniel McDuff MIT Media Lab @@ -15172,6 +52944,10 @@ Rana el Kaliouby MIT Media Lab Cambridge 02139, USA"
+70f3d3d9a7402a0f62a5646a16583c6c58e3b07a,"An Architecture for Deep, Hierarchical Generative Models","An Architecture for Deep, Hierarchical Generative +Models +Philip Bachman +Maluuba Research"
706b9767a444de4fe153b2f3bff29df7674c3161,Fast Metric Learning For Deep Neural Networks,"Fast Metric Learning For Deep Neural Networks Henry Gouk1, Bernhard Pfahringer1, and Michael Cree2 Department of Computer Science, University of Waikato, Hamilton, New Zealand @@ -15180,11 +52956,56 @@ School of Engineering, University of Waikato, Hamilton, New Zealand" LEARNING Sujoy Paul, Sourya Roy and Amit K. Roy-Chowdhury Dept. of Electrical and Computer Engineering, University of California, Riverside, CA 92521"
+708355d319a88485fdbbea3524104982b8cf37c2,2D/3D Sensor Exploitation and Fusion for Enhanced Object Detection,"D/3D Sensor Exploitation and Fusion for Enhanced Object Detection +Jiejun Xu +HRL Laboratories LLC +Kyungnam Kim +HRL Laboratories LLC +Zhiqi Zhang +HRL Laboratories LLC +Hai-wen Chen +HRL Laboratories LLC +Yuri Owechko +HRL Laboratories LLC"
+70990e1b13cec2b3e4831a00c6ac901dae76b27a,"Mareckova , Klara ( 2013 ) Sex differences and the role of sex hormones in face development and face processing","Mareckova, Klara (2013) Sex differences and the role of +sex hormones in face development and face processing. +PhD thesis, University of Nottingham. +Access from the University of Nottingham repository: +http://eprints.nottingham.ac.uk/13333/1/KlaraMareckova_PhDThesis_finalversion1.pdf +Copyright and reuse: +The Nottingham ePrints service makes this work by researchers of the University of +Nottingham available open access under the following conditions. +· Copyright and all moral rights to the version of the paper presented here belong to +the individual author(s) and/or other copyright owners. +To the extent reasonable and practicable the material made available in Nottingham +ePrints has been checked for eligibility before being made available. +· Copies of full items can be used for personal research or study, educational, or not- +for-profit purposes without prior permission or charge provided that the authors, title +nd full bibliographic details are credited, a hyperlink and/or URL is given for the +original metadata page and the content is not changed in any way. +· Quotations or similar reproductions must be sufficiently acknowledged. +Please see our full end user licence at: +http://eprints.nottingham.ac.uk/end_user_agreement.pdf +A note on versions:"
+70eb48e06d9d5edf84246b772673b6d44af4b3c6,Robust Ldp Based Face Descriptor,"International Journal of Advances in Engineering & Technology, Mar. 2013. +©IJAET ISSN: 2231-1963 +ROBUST LDP BASED FACE DESCRIPTOR +Mahadeo D. Narlawar and Jaideep G. Rana +Department of Electronics Engineering, Jawaharlal Nehru College of Engineering, +Aurangabad-431004, Maharashtra, India"
70e79d7b64f5540d309465620b0dab19d9520df1,Facial Expression Recognition System Using Extreme Learning Machine,"International Journal of Scientific & Engineering Research, Volume 8, Issue 3, March-2017 ISSN 2229-5518 Facial Expression Recognition System Using Extreme Learning Machine Firoz Mahmud, Dr. Md. Al Mamun"
+70bfe8dfd9c9b05c8854a5d4aca9c3ee3a3b7eff,3D Object Reconstruction using Multiple Views,"!, >A?J 4A?IJHK?JE KIEC KJEFA 8EAMI +,CD E +,AF=HJAJ B +FKJAH 5?EA?A 5J=JEIJE?I +7ELAHIEJO B ,K>E 6HEEJO +ACA +) JDAIEI J JDA 7ELAHIEJO B ,K>E 6HEEJO +ACA E BKAJ B +JDA HAGKEHAAJI BH JDA B +,?JH B 2DEIFDO +5AFJA>AH"
7003d903d5e88351d649b90d378f3fc5f211282b,Facial Expression Recognition using Gabor Wavelet,"International Journal of Computer Applications (0975 – 8887) Volume 68– No.23, April 2013 Facial Expression Recognition using Gabor Wavelet @@ -15200,11 +53021,116 @@ Ashish Jadhav ENTC SVERI’S COE (Poly), Pandharpur, Solapur, India"
+70e3c02575e4041519434e0dacb291bbb8791380,Generative 2D and 3D Human Pose Estimation with Vote Distributions,"Generative 2D and 3D +Human Pose Estimation +with Vote Distributions +J¨urgen Brauer, Wolfgang H¨ubner, Michael Arens +Fraunhofer Institute of Optronics, System Technologies and Image Exploitation +{juergen.brauer, wolfgang.huebner, +Gutleuthausstr. 1, 76275 Ettlingen, Germany"
+70920447b8300fd65745c0a884523e4d52d000ef,Automated Crowd Detection in Stadium Arenas,"AUTOMATED CROWD DETECTION IN STADIUM ARENAS +Loris Nanni, 1 Sheryl Brahnam, 2 Stefano Ghidoni, 1 Emanuele Menegatti1 +DIE, University of Padua, Via Gradenigo, 6 - 35131- Padova – Italy e-mail: {loris.nanni, ghidoni, +CIS, Missouri State University, 901 S. National, Springfield, MO 65804, USA e-mail:"
+70af8e4ff3c029aea788bc28b45c56932b50c056,Robust Facial Landmark Detection Using a Mixture of Synthetic and Real Images with Dynamic Weighting: A Survey,"Om Prakash Gupta et al. 2016, Volume 4 Issue 1 +ISSN (Online): 2348-4098 +ISSN (Print): 2395-4752"
+70ce1a17f257320fc718d61964b21e7aeabd8cd5,Person re-identification with fusion of hand-crafted and deep pose-based body region features,"Person re-identification with fusion of hand-crafted and deep pose-based body +region features +Jubin Johnson1 +Shunsuke Yasugi2 +Yoichi Sugino2 +Sugiri Pranata1 +Panasonic R&D Center +Singapore +Shengmei Shen1 +Panasonic Corporation +Core Element Technology Development Center +Japan +http://www.prdcsg.panasonic.com.sg/"
+70b0538af40672e3be4b72f97cec486693d5204f,Mixture Component Identification and Learning for Visual Recognition,"Mixture Component Identification and Learning +for Visual Recognition +Omid Aghazadeh, Hossein Azizpour, Josephine Sullivan, and Stefan Carlsson +Computer Vision and Active Perception laboratory (CVAP), KTH, Sweden"
+70e90b9df5b8617ef6636c5492db727f9d48d0ec,People Search with Textual Queries About Clothing Appearance Attributes,"People search with textual queries about +lothing appearance attributes +Riccardo Satta, Federico Pala, Giorgio Fumera, and Fabio Roli"
+7056a051e0589ab6aa299c7d2a31588800b8c93e,Facial expression recognition and histograms of oriented gradients: a comprehensive study,"Carcagnì et al. SpringerPlus (2015) 4:645 +DOI 10.1186/s40064-015-1427-3 +RESEARCH +Facial expression recognition +nd histograms of oriented gradients: a +omprehensive study +Pierluigi Carcagnì*†, Marco Del Coco†, Marco Leo† and Cosimo Distante† +Open Access +*Correspondence: +Pierluigi Carcagnì, Marco Del +Coco, Marco Leo and Cosimo +Distante contributed equally +to this work +National Research Council +of Italy, Institute of Applied +Sciences and Intelligent +Systems, Via della Libertà, 3, +73010 Arnesano , LE, Italy"
70bf1769d2d5737fc82de72c24adbb7882d2effd,Face Detection in Intelligent Ambiences with Colored Illumination,"Face detection in intelligent ambiences with colored illumination Christina Katsimerou, Judith A. Redi, Ingrid Heynderickx Department of Intelligent Systems TU Delft Delft, The Netherlands"
+70560383cbf7c0dc5e9be1f2fd9efba905377095,Accelerating Online CP Decompositions for Higher Order Tensors,"Accelerating Online CP Decompositions for +Higher Order Tensors +Shuo Zhou1, Nguyen Xuan Vinh1, James Bailey1, Yunzhe Jia1, Ian Davidson2 +Dept. of Computing and Information Systems, The University of Melbourne, Australia +Dept. of Computer Science, University of California, Davis, USA"
+70480ee0e636a77f6289be98ae39300a584808f6,Iterative Robust Registration Approach based on Feature Descriptors Correspondence - Application to 3D Faces Description,"Iterative Robust Registration Approach based on Feature Descriptors +Correspondence +Application to 3D Faces Description +Cristal lab.Grift research group, National School of Computer Science, La Mannouba, Tunisia +Wieme Gadacha and Faouzi Ghorbel +Keywords: +D Rigid Registration, Hausdorff Distance in Shape Space, 3D Parametrisation, Matching, Face Description, +Shannon Theorem."
+70bb5c2570673eae86a3f9ced55c7ef00e0be8b5,Combinaison de Descripteurs Hétérogènes pour la Reconnaissance de Micro-Mouvements Faciaux,"Combinaison de Descripteurs Hétérogènes pour la Reconnaissance de +Micro-Mouvements Faciaux. +Vincent Rapp1, Thibaud Senechal1, Hanan Salam2, Lionel Prevost3, Renaud Seguier2, Kevin Bailly1 +ISIR - CNRS UMR 7222 +Université Pierre et Marie Curie, Paris +{rapp, senechal, +Supelec - ETR (UMR 6164) +Avenue de la Boulaie, 35511, +Cesson-Sevigne +{salam, +LAMIA - EA 4540 +Université des Antilles et de la Guyanne +Résumé +Dans cet article, nous présentons notre réponse au premier +hallenge international sur la reconnaissance et l’analyse +d’émotions faciales (Facial Emotion Recognition and Ana- +lysis Challenge). Nous proposons une combinaison de dif- +férents types de descripteurs dans le but de détecter de ma- +nière automatique, les micro-mouvements faciaux d’un vi- +sage. Ce système utilise une Machine à Vecteurs Supports"
+70b42bbd76e6312d39ea06b8a0c24beb4a93e022,Solving Multiple People Tracking in a Minimum Cost Arborescence,"Solving Multiple People Tracking In A Minimum Cost Arborescence +Institut f¨ur Informationsverarbeitung +Institute of Geodesy and Photogrammetry +Laura Leal-Taix´e +ETH Z¨urich +Roberto Henschel +Universit¨at Hannover +Bodo Rosenhahn +Institut f¨ur Informationsverarbeitung +Universit¨at Hannover +. Introduction +For many applications of computer vision, it is neces- +sary to localize and track humans that appear in a video +sequence. Multiple people tracking has thus evolved as an +ongoing research topic in the computer vision domain. +A commonly used approach to solve the data associa- +tion problem within the tracking task is to apply a hierarchi- +al tracklet framework [5]. Although there has been great +progress in such a model, mainly due to its good bootstrap- +ping capabilities, so far little attention has been drawn to"
1e058b3af90d475bf53b3f977bab6f4d9269e6e8,Manifold Relevance Determination,"Manifold Relevance Determination Andreas C. Damianou Dept. of Computer Science & Sheffield Institute for Translational Neuroscience, University of Sheffield, UK @@ -15214,6 +53140,46 @@ Michalis K. Titsias Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, UK Neil D. Lawrence Dept. of Computer Science & Sheffield Institute for Translational Neuroscience, University of Sheffield, UK"
+1e1e35284591b6a69569c48b3677b6f4409c5edc,Optimal Feature Extraction and Classification of Tensors via Matrix Product State Decomposition,"Matrix Product State for Feature Extraction of +Higher-Order Tensors +Johann A. Bengua1, Ho N. Phien1, Hoang D. Tuan1 and Minh N. Do2 +een applied in neuroscience, pattern analysis, image classifi- +ation and signal processing [7], [8], [9]. The central concept +of using the TD is to decompose a large multidimensional +tensor into a set of common factor matrices and a single core +tensor which is considered as reduced features of the original +tensor in spite of its lower dimension [7]. In practice, the +TD is often performed in conjunction with some constraints, +e.g. nonnegativity, orthogonality, etc., imposed on the common +factors in order to obtain a better feature core tensor [7]. +However, constraints like orthogonality often leads to an NP- +hard computational problem [10]. Practical application of the +TD is normally limited to small-order tensors. This is due +to the fact +the TD core tensor preserves the higher- +order structure of the original tensor, with its dimensionality +remaining fairly large in order to capture relevant interactions +etween components of the tensor [2]."
+1e2087908e6ce34032c821c7fb6629f2d0733086,Affective Embodied Conversational Agents for Natural Interaction,"Affective Embodied Conversational Agents for +Natural Interaction +Eva Cerezo, Sandra Baldassarri, Isabelle Hupont and Francisco J. Seron +Advanced Computer Graphics Group (GIGA) +Computer Science Department, Engineering Research Institute of Aragon(I3A), +University of Zaragoza, +Spain +. Introduction +Human computer intelligent interaction is an emerging field aimed at providing natural +ways for humans to use computers as aids. It is argued that for a computer to be able to +interact with humans it needs to have the communication skills of humans. One of these +skills is the affective aspect of communication, which is recognized to be a crucial part of +human intelligence and has been argued to be more fundamental in human behaviour and +success in social life than intellect (Vesterinen, 2001; Pantic, 2005). +Embodied conversational agents, ECAs (Casell et al., 2000), are graphical interfaces capable +of using verbal and non-verbal modes of communication to interact with users in computer- +ased environments. These agents are sometimes just as an animated talking face, may be +displaying simple facial expressions and, when using speech synthesis, with some kind of +lip synchronization, and sometimes they have sophisticated 3D graphical representation, +with complex body movements and facial expressions."
1e799047e294267087ec1e2c385fac67074ee5c8,Automatic Classification of Single Facial Images,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 21, NO. 12, DECEMBER 1999 Short Papers___________________________________________________________________________________________________ Automatic Classification of @@ -15239,6 +53205,16 @@ Received: 6 December 2017; Accepted: 25 January 2018; Published: 30 January 2018 Transactions on Pattern Analysis and Machine Intelligence Face Search at Scale Dayong Wang, Member, IEEE, Charles Otto, Student Member, IEEE, Anil K. Jain, Fellow, IEEE"
+1e02dfeb93e8fd8753d2e69baf705baf8996cb81,"Online Object Tracking, Learning and Parsing with And-Or Graphs","ARXIV VERSION +Online Object Tracking, Learning and Parsing +with And-Or Graphs +Tianfu Wu, Yang Lu and Song-Chun Zhu"
+1ea2a53a6cb9c08312276a2f0646935d5fab5ed3,Real-time Crowd Tracking using Parameter Optimized Mixture of Motion Models,"Noname manuscript No. +(will be inserted by the editor) +Real-time Crowd Tracking using Parameter Optimized +Mixture of Motion Models +Aniket Bera · David Wolinski · Julien Pettr´e · Dinesh Manocha +Received: date / Accepted: date"
1eec03527703114d15e98ef9e55bee5d6eeba736,Automatic identification of persons in TV series,"UNIVERSITÄT KARLSRUHE (TH) FAKULTÄT FÜR INFORMATIK INTERACTIVE SYSTEMS LABS @@ -15252,6 +53228,27 @@ MAY 2008 ADVISORS M.Sc. Hazım Kemal Ekenel Dr.-Ing. Rainer Stiefelhagen"
+1e4c717a8a5eed5c3385b77641ebe3d8c4ceb3ac,An efficient algorithm for maximal margin clustering,"J Glob Optim +DOI 10.1007/s10898-011-9691-4 +An efficient algorithm for maximal margin clustering +Jiming Peng · Lopamudra Mukherjee · Vikas Singh · +Dale Schuurmans · Linli Xu +Received: 29 April 2009 / Accepted: 5 February 2011 +© Springer Science+Business Media, LLC. 2011"
+1e2d965df330a72b3426279f9327f77330c2ee64,Simultaneous Detection and Segmentation of Pedestrians using Top-down and Bottom-up Processing,"Simultaneous Detection and Segmentation of Pedestrians +using Top-down and Bottom-up Processing ∗ +Vinay Sharma +James W. Davis +Dept. of Computer Science and Engineering +Ohio State University +Columbus OH 43210 USA"
+1ebf201b34d9687fa17e336a608ab43e466ca13f,Detecting Parts for Action Localization,"Nicolas Chesneau +Grégory Rogez +Karteek Alahari +Cordelia Schmid +CHESNEAU ET AL.: DETECTING PARTS FOR ACTION LOCALIZATION +Detecting Parts for Action Localization +Inria∗"
1ef1f33c48bc159881c5c8536cbbd533d31b0e9a,Identity-based Adversarial Training of Deep CNNs for Facial Action Unit Recognition,"Z. ZHANG ET AL.: ADVERSARIAL TRAINING FOR ACTION UNIT RECOGNITION Identity-based Adversarial Training of Deep CNNs for Facial Action Unit Recognition @@ -15262,10 +53259,61 @@ Department of Computer Science State University of New York at Binghamton NY, USA."
+1ebcf5dbb37fcd369530b0ee4df5d4a60f756f3e,High-level Feature Learning by Ensemble Projection for Image Classification with Limited Annotations,"High-level Feature Learning by Ensemble Projection for Image +Classification with Limited Annotations $ +Dengxin Dai∗, Luc Van Gool +Computer Vision Lab, ETH Z¨urich, CH-8092, Switzerland"
+1e1334f76177ddf3ddc35f7359a1e04b65438dc4,What is the Most EfficientWay to Select Nearest Neighbor Candidates for Fast Approximate Nearest Neighbor Search?,"What Is the Most Efficient Way to Select Nearest Neighbor Candidates for Fast +Approximate Nearest Neighbor Search? +Masakazu Iwamura, Tomokazu Sato and Koichi Kise +Graduate School of Engineering, Osaka Prefecture University +{masa,"
+1e1a3ee9626c740be78f9c5f75f9c4d7edc45666,Estimating the Natural Illumination Conditions from a Single Outdoor Image,E-mail:
+1e8a265ec741584e851b83b5efc00351048bbe3f,Real Time Human Detection and Localization Using Consumer Grade Camera and Commercial UAV,"Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 7 November 2018 doi:10.20944/preprints201811.0156.v1 +Article +Real Time Human Detection and Localization Using +Consumer Grade Camera and Commercial UAV +Nemi Bhattarai 1,*, Tai Nakamura 1 and Chitrini Mozumder 1,* +Remote Sensing and Geographic Information Systems, School of Engineering and Technology, Asian +Institute of Technology, Thailand; (T.N.) +* Correspondence: (N.B); (C.M); Tel.: +66-099-421-7492"
+1e5c6c9fa9ba089931cfb2bc81e4368a4db5dd2d,Multi- View Fusion for Action Recognition in Child-Robot Interaction,"978-1-4799-7061-2/18/$31.00 ©2018 IEEE +ICIP 2018 +#2Kinect #1Kinect #3Multi-view action recognition systemSenseActDecisionSpeakRec.ActionActFig.1:Multi-viewactionrecognitionsystemforchild-robotinteraction.presentspontaneousbehaviorandaninformalwayofcommunica-tion.Inaddition,thesameactionscanbeperformedinavarietyofwaysandawidespectrum,furthercomplicatingtherecognitionofactions.Althoughhumanactionrecognitionisapopularproblemwithmanyproposedmethods[8–13],therequirementsofmulti-viewac-tionrecognitiondiffersignificantlyasithastotakeintoaccountbothactionrecognitionthatresultsfromsingleviewsandalsothefusionamongtheresultinginformationfromthedifferentstreams[14,15].Incross-viewactionrecognitionworksitisattemptedtoshareknowledgefortheactionamongthedifferentsetupviews.Forexample,in[16]aspecificviewistreatedasthetargetdomainandtheotherviewsassourcedomainsinordertoformulateacross-viewlearningframework.Inotherapproaches,theknowledgeofactionsistransferredfromthedifferentviewsinasinglecanoni-calview[17].In[18]itisproposedtolearnview-invariantfeaturesrobusttoviewvariationsusingdeepmodels.Inthefieldofmulti-viewactionrecognition,anewglobalrepresentationthatiscalledmulti-viewsupervectorhasalsobeenproposedinordertoenhancerecognitionperformance[19].Finally,anotherinterestingapproachispresentedin[20]whereitisattemptedtotransferthelow-levelfeaturesintoahigh-levelsemanticspaceandamulti-tasklearningapproachforjointactionmodelingisexamined.Inthispaperwedevelopamulti-viewactionrecognitionsystemsuitableforCRI.Themaincontributionsofthispapercanbesum-marizedasfollows:1)Single-viewmethodsareexploredinordertocreaterobustactionrecognitionmodelsforparticularusers,i.e.children,underdifficulttaskswithfewtrainingdata.2)Methodsforthefusionofinformationfromdifferentstreamsinamulti-viewsys-temareproposedtoenhanceactionrecognitionduringCRI.3)Themulti-viewactionrecognitionsystemisintegratedinroboticplat-"
+1ed6a05a226cb0d09afd76ff9b7560c404d8eb49,D4g: Pre-completion report on exemplar,"D4g: Pre-completion report on exemplar +Workpackage 4 Deliverable +Date: 31th August 2007"
+1ecf4055831ca23c9f6026ef866dac95c8b8f9de,Eye Gaze Tracking With a Web Camera in a Desktop Environment,"Eye Gaze Tracking With a Web Camera +in a Desktop Environment +Yiu-ming Cheung, Senior Member, IEEE, and Qinmu Peng, Member, IEEE"
+1eadafc27372b33a73eca062438a58d4280fd3a1,DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images,"DeepSkeleton: Learning Multi-task Scale-associated +Deep Side Outputs for Object Skeleton Extraction +in Natural Images +Wei Shen, Kai Zhao, Yuan Jiang, Yan Wang, Xiang Bai and Alan Yuille"
+1e21078efc0aa7a3881d0e87cb5dd5918523f525,Network Consistent Data Association,"Network Consistent Data Association +Anirban Chakraborty, Member, IEEE, Abir Das, Student Member, IEEE, +nd Amit K. Roy-Chowdhury, Senior Member, IEEE"
1e8394cc9fe7c2392aa36fb4878faf7e78bbf2de,Zero-Shot Object Recognition System Based on Topic Model,"TO APPEAR IN IEEE THMS Zero-Shot Object Recognition System ased on Topic Model Wai Lam Hoo and Chee Seng Chan"
+1e2b8778cfe44de4bbe4a099ee7cdff5c2ca5f38,Attention to Scale: Scale-Aware Semantic Image Segmentation,"Attention to Scale: Scale-aware Semantic Image Segmentation +Liang-Chieh Chen∗ +{yangyi05, wangjiang03, +Yi Yang, Jiang Wang, Wei Xu +Alan L. Yuille"
+1e93ec0f5c29069beedbe7d617f5167b82b70730,Filtering SVM frame-by-frame binary classification in a detection framework,"FILTERING SVM FRAME-BY-FRAME BINARY CLASSIFICATION IN A DETECTION +FRAMEWORK +Alejandro Betancourt1,2, Pietro Morerio1, Lucio Marcenaro1, Matthias Rauterberg2, Carlo Regazzoni1 +Information and Signal Processing for Cognitive +University of Genoa, Italy +Telecommunications Group. +Department of Naval, Electric, Electronic +nd Telecommunications Engineering. +Designed Intelligence Group. +Department of Industrial Design. +Eindhoven University of Technology. +Eindhoven, Netherlands."
1ecb56e7c06a380b3ce582af3a629f6ef0104457,"A New Way of Discovery of Belief, Desire and Intention in the BDI Agent-Based Software Modeling","List of Contents Vol.8 Contents of Journal of Advanced Computational @@ -15295,6 +53343,8 @@ CLASSIFICATION Christer Loob, Pejman Rasti, Iiris Lusi, Julio C. S. Jacques Junior, Xavier Baro, Sergio Escalera, Tomasz Sapinski, Dorota Kaminska and Gholamreza Anbarjafari"
+1e82a8965f08e8d38b16f39412e6e3c456f6f22e,Social force model aided robust particle PHD filter for multiple human tracking,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE +ICASSP 2016"
1e21b925b65303ef0299af65e018ec1e1b9b8d60,Unsupervised Cross-Domain Image Generation,"Under review as a conference paper at ICLR 2017 UNSUPERVISED CROSS-DOMAIN IMAGE GENERATION Yaniv Taigman, Adam Polyak & Lior Wolf @@ -15320,6 +53370,63 @@ A series of experiments illustrates the good behavior of the algorithm in terms performance and robustness with respect to the violation of the postulated low den- sity separation assumption. The minimum entropy solution bene(cid:12)ts from unlabeled data and is able to challenge mixture models and manifold learning in a number of"
+1e0ba1a61ed0c6d4a76697de1e185ed5def60fb4,Learning to Parse Video into Stable Spatiotemporal Volumes1,"Learning to Parse Video into Stable Spatiotemporal Volumes1 +Thomas Dean +Google Inc. +We are interested in learning how to exploit continuity, motion and context to account for stable, recov- +erable, spatiotemporal phenomena embedded in video. While most humans can make sense of still images, +for the most part, we need continuity and motion to make sense of the world around us. Humans are also +ided by strong priors that allow us to make confident predictions despite ambiguity, noise and occlusion. +The idea of combining top-down prior knowledge and bottom-up cues derived from motion and other +low-level features has been around almost as long as research in computer vision, e.g., [10], and has recently +seen renewed interest, e.g., [3, 2, 6, 11]. Rather than the traditional tasks of object recognition or image +ategorization, here we focus on the task of explaining each new frame in a video in terms of a continuously +evolving representation of spatiotemporal volumes that account for the complete visual field. For the purpose"
+1e1dc91c2ac3ad0ae44941e711aed193231c3335,Universal Adversarial Perturbations Against Semantic Image Segmentation,"Universal Adversarial Perturbations Against Semantic Image Segmentation +Bosch Center for Artificial Intelligence, Robert Bosch GmbH +Jan Hendrik Metzen +Mummadi Chaithanya Kumar +University of Freiburg +Thomas Brox +University of Freiburg +Bosch Center for Artificial Intelligence, Robert Bosch GmbH +Volker Fischer"
+1e1a67a78badc619b2f9938e4a03922dcbee0fb6,Food/Non-food Image Classification and Food Categorization using Pre-Trained GoogLeNet Model,"Food/Non-food Image Classification and Food +Categorization using Pre-Trained GoogLeNet Model +Ashutosh Singla +Lin Yuan +Touradj Ebrahimi +Multimedia Signal Processing Group +Ecole Polytechnique Fédérale de Lausanne +Station 11, 1015 Lausanne, Switzerland"
+1e15c5cba95cbb475ddb67157fdd480f5253502e,Face Recognition under Varying Lighting Conditions: A Combination of Weber-face and Local Directional Pattern for Feature Extraction and Support Vector Machines for Classification,"Journal of Information Hiding and Multimedia Signal Processing +Ubiquitous International +©2017 ISSN 2073-4212 +Volume 8, Number 5, September 2017 +Face Recognition under Varying Lighting Conditions: +A Combination of Weber-face and Local Directional +Pattern for Feature Extraction and Support Vector +Machines for Classification +Chin-Shiuh Shieh1,5, Liyun Chang4,∗, and Tsair-Fwu Lee1,3,5,∗ +Chi-Kien Tran1,2, Chin-Dar Tseng1, Pei-Ju Chao1,3 +Medical Physics and Informatics Laboratory of Electronics Engineering, +National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan, ROC +Center for Information Technology, Hanoi University of Industry, Hanoi, Vietnam +Department of Radiation Oncology, Kaohsiung Chang Gung Memorial Hospital, +Department of Medical Imaging and Radiological Sciences, I-Shou University, +Kaohsiung 83305,Taiwan, ROC +Kaohsiung 82445,Taiwan, ROC +5 Graduate Institute of Clinical Medicine, Kaohsiung Medical University, +Corresponding authors: +Kaohsiung 807,Taiwan, ROC"
+1e9c3d0d87e09ea359ce1e31114b677d627bf9e7,Correction: Rapid Stress System Drives Chemical Transfer of Fear from Sender to Receiver,"RESEARCH ARTICLE +Rapid Stress System Drives Chemical Transfer +of Fear from Sender to Receiver +Jasper H. B. de Groot1*, Monique A. M. Smeets1, Gün R. Semin1,2,3 +Department of Social and Organizational Psychology, Faculty of Social and Behavioral Sciences, Utrecht +University, Utrecht, the Netherlands, 2 Department of Psychology, Koç University, Istanbul, Turkey, +Instituto Superior de Psicologia Aplicada (ISPA), Instituto Universitário, Lisbon, Portugal +11111"
1ee3b4ba04e54bfbacba94d54bf8d05fd202931d,Celebrity Face Recognition using Deep Learning,"Indonesian Journal of Electrical Engineering and Computer Science Vol. 12, No. 2, November 2018, pp. 476~481 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v12.i2.pp476-481 @@ -15340,20 +53447,76 @@ Keywords: AlexNet Convolutional neural network Deep learning"
+1eda03469d860ac725122bd27faaae6b2cb47d0d,Image Question Answering Using Convolutional Neural Network with Dynamic Parameter Prediction,"Image Question Answering using Convolutional Neural Network +with Dynamic Parameter Prediction +Hyeonwoo Noh +Paul Hongsuck Seo +Bohyung Han +{shgusdngogo, hsseo, +Department of Computer Science and Engineering, POSTECH, Korea"
1e41a3fdaac9f306c0ef0a978ae050d884d77d2a,Robust Object Recognition with Cortex-Like Mechanisms,"Robust Object Recognition with Cortex-Like Mechanisms Thomas Serre, Lior Wolf, Stanley Bileschi, Maximilian Riesenhuber, and Tomaso Poggio, Member, IEEE"
+1e8711d2fc4b05eac0699c82f4698154c2b057d3,The unreasonable effectiveness of small neural ensembles in high-dimensional brain,"The unreasonable effectiveness of small neural ensembles +in high-dimensional brain +A.N. Gorbana,b,∗, V.A. Makarovb,c, I.Y. Tyukina,b,d +Instituto de Matem´atica Interdisciplinar, Faculty of Mathematics, Universidad Complutense de Madrid, Avda Complutense s/n, 28040 Madrid, +Department of Mathematics, University of Leicester, Leicester, LE1 7RH, UK +Lobachevsky University, Nizhni Novgorod, Russia +dSaint-Petersburg State Electrotechnical University, Saint-Petersburg, Russia +Spain"
+1e83e2abcb258cd62b160e3f31a490a6bc042e83,Metric Learning in Codebook Generation of Bag-of-Words for Person Re-identification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Metric Learning in Codebook Generation of +Bag-of-Words for Person Re-identification +Lu Tian, Student Member, IEEE, and Shengjin Wang, Member, IEEE"
1e1e66783f51a206509b0a427e68b3f6e40a27c8,Semi-supervised Estimation of Perceived Age from Face Images,"SEMI-SUPERVISED ESTIMATION OF PERCEIVED AGE FROM FACE IMAGES VALWAY Technology Center, NEC Soft, Ltd., Tokyo, Japan Kazuya Ueki Masashi Sugiyama Keywords:"
+1ef46f7bb7463ead4369a796435106da63578733,Shamann: Shared Memory Augmented Neural Networks,"Under review as a conference paper at ICLR 2019 +SHAMANN: SHARED MEMORY AUGMENTED +NEURAL NETWORKS +Anonymous authors +Paper under double-blind review"
1efaa128378f988965841eb3f49d1319a102dc36,Hierarchical binary CNNs for landmark localization with limited resources,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 Hierarchical binary CNNs for landmark localization with limited resources Adrian Bulat and Georgios Tzimiropoulos"
+8408f4b1193e8db25fec818a989d9fe3194d5ea6,3D Face Recognition using Radon Transform and Symbolic LDA,"International Journal of Computer Applications (0975 - 8887) +Volume 67 - No. 4, April 2013 +D Face Recognition using Radon Transform and +Symbolic LDA +P. S. Hiremath +Department of Computer Science +Gulbarga University, Gulbarga-585106 +Karnataka, India +Manjunatha Hiremath +Department of Computer Science +Gulbarga University, Gulbarga-585106 +Karnataka, India"
+84a69f6357b137028e3aa51376ce2dffad5e0179,Studies of Typically and Atypically Developing Children,"Digital Comprehensive Summaries of Uppsala Dissertations +from the Faculty of Social Sciences 152 +Visual Attention to Faces, Eyes and +Objects +Studies of Typically and Atypically Developing +Children +JOHAN L. KLEBERG +ISSN 1652-9030 +ISBN 978-91-513-0244-7 +urn:nbn:se:uu:diva-342578 +UNIVERSITATIS +UPSALIENSIS +UPPSALA"
+84af83ff6412a756df58b6436f0d2e3c049e1f12,Abnormality Detection with Improved Histogram of Oriented Tracklets,"Abnormality Detection with Improved +Histogram of Oriented Tracklets +Hossein Mousavi1, Moin Nabi1 , Hamed Kiani Galoogahi1 +Alessandro Perina1 and Vittorio Murino1,2 +Pattern Analysis and Computer Vision Department (PAVIS) +Istituto Italiano di Tecnologia (IIT) Genova, Italy +Dipartimento di Informatica,University of Verona, Italy"
8451bf3dd6bcd946be14b1a75af8bbb65a42d4b2,Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data,"Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data Alexandra-Mihaela Olteanu @@ -15362,6 +53525,29 @@ K´evin Huguenin UNIL–HEC Lausanne Italo Dacosta Jean-Pierre Hubaux"
+842e42d30dc31de1833047c268f0a5cdff16f2ce,3D Face Compression and Recognition using Spherical Wavelet Parametrization,"(IJACSA) International Journal of Advanced Computer Science and Applications, +Vol. 3, No.9, 2012 +D Face Compression and Recognition using +Spherical Wavelet Parametrization +Rabab M. Ramadan +College of Computers and Information Technology +University of Tabuk +Tabuk, KSA +into multi-resolution sub"
+845c03910c7cfd02de7df9622a9973e8b085c0d8,Interactive Generation of Realistic Facial Wrinkles from Sketchy Drawings,"EUROGRAPHICS 2015 / O. Sorkine-Hornung and M. Wimmer +(Guest Editors) +Volume 34 (2015), Number 2 +Interactive Generation of Realistic Facial Wrinkles from +Sketchy Drawings +Hyeon-Joong Kim 1,3, A. Cengiz Öztireli2, Il-Kyu Shin1, Markus Gross2, Soo-Mi Choi†1 +Sejong University, Korea 2 ETH Zurich, Switzerland 3 3D Systems, Korea +Figure 1: We use statistics extracted from example faces to augment interactively drawn concept sketches for synthesizing +realistic facial wrinkles."
+84c35fc21db3bcd407a4ffb009912b6ac5a47e3c,Mgan: Training Generative Adversarial Nets,"Under review as a conference paper at ICLR 2018 +MGAN: TRAINING GENERATIVE ADVERSARIAL NETS WITH +MULTIPLE GENERATORS +Anonymous authors +Paper under double-blind review"
84e4b7469f9c4b6c9e73733fa28788730fd30379,Projective complex matrix factorization for facial expression recognition,"Duong et al. EURASIP Journal on Advances in Signal Processing (2018) 2018:10 DOI 10.1186/s13634-017-0521-9 EURASIP Journal on Advances @@ -15372,6 +53558,46 @@ facial expression recognition Viet-Hang Duong1, Yuan-Shan Lee1, Jian-Jiun Ding2, Bach-Tung Pham1, Manh-Quan Bui1, Pham The Bao2 nd Jia-Ching Wang1,3* Open Access"
+84968d6488e87c99b8560ab33110a5bf85aa5761,Object category learning and retrieval with weak supervision,"Object category learning and retrieval with +weak supervision +Steven Hickson, Anelia Angelova, Irfan Essa, Rahul Sukthankar +Google Brain / Google Research +(shickson, anelia, irfanessa,"
+84be05dd82a7208a6e7b3d238df27b123cc917ce,Revisiting Visual Question Answering Baselines,"Revisiting Visual Question Answering Baselines +Allan Jabri, Armand Joulin, and Laurens van der Maaten +Facebook AI Research"
+84c8b29103480cf6f2b93e2fd4225b0d9d535ed6,Playing hide and seek with a mobile companion robot,"Playing Hide and Seek with a Mobile +Companion Robot +Michael Volkhardt, Steffen Mueller, Christof Schroeter, Horst-Michael Gross +Neuroinformatics and Cognitive Robotics Lab +Ilmenau University of Technology +98684 Ilmenau, Germany +Email:"
+846f3857976ba437e0592a848e47f6a3370880a3,3D Face Recognition Based on Depth and Intensity Gabor Features using Symbolic PCA and AdaBoost,"International Journal of Signal Processing, Image Processing and Pattern Recognition +Vol.6, No.5 (2013), pp.1-12 +http://dx.doi.org/10.14257/ijsip.2013.6.5.01 +D Face Recognition Based on Depth and Intensity Gabor +Features using Symbolic PCA and AdaBoost +P. S. Hiremath and Manjunatha Hiremath +Department of Computer Science +Gulbarga University, Gulbarga – 585106 +Karnataka, India,"
+844568d9e49ec34536502bb8c66d5578c962abd6,From Virtual to Real World Visual Perception Using Domain Adaptation - The DPM as Example,"Invited book chapter to appear in Domain Adaptation in Computer Vision Applications, Springer Series: Advances +in Computer Vision and Pattern Recognition, Edited by Gabriela Csurka. Written during Summer 2016. +From Virtual to Real World Visual Perception using Domain +Adaptation – The DPM as Example +Computer Vision Center (CVC) and Dpt. Ci`encies de la Computaci´o (DCC), +Antonio M. L´opez +Universitat Aut`onoma de Barcelona (UAB) +Jiaolong Xu +Jos´e L. G´omez +David V´azquez +CVC and DCC, UAB +CVC and DCC, UAB +CVC and DCC, UAB +Germ´an Ros +CVC and DCC, UAB +December 30, 2016"
84fa126cb19d569d2f0147bf6f9e26b54c9ad4f1,Improved Boosting Performance by Explicit Handling of Ambiguous Positive Examples,"Improved Boosting Performance by Explicit Handling of Ambiguous Positive Examples Miroslav Kobetski and Josephine Sullivan"
@@ -15382,10 +53608,36 @@ Department of Computer Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai, Songkhla, 90112 Thailand Telephone: (66)080-7045015, (66)074-287-357 E-mail:"
+84c8eb2db35f7fd38c906ced741e2c5470ba7544,Deep Control - a simple automatic gain control for memory efficient and high performance training of deep convolutional neural networks,"Deep Control - a simple automatic gain control for memory +efficient and high performance training of deep +onvolutional neural networks +Brendan Ruff +Submitted to BMVC 2017, 2nd May 2017 +Patent application GB1619779.0, 23rd Nov 2016"
841a5de1d71a0b51957d9be9d9bebed33fb5d9fa,PCANet: A Simple Deep Learning Baseline for Image Classification?,"PCANet: A Simple Deep Learning Baseline for Image Classification? Tsung-Han Chan, Member, IEEE, Kui Jia, Shenghua Gao, Jiwen Lu, Senior Member, IEEE, Zinan Zeng, and Yi Ma, Fellow, IEEE"
+84fd7c00243dc4f0df8ab1a8c497313ca4f8bd7b,Perceived Age Estimation from Face Images,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
8411fe1142935a86b819f065cd1f879f16e77401,Facial Recognition using Modified Local Binary Pattern and Random Forest,"International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 4, No. 6, November 2013 Facial Recognition using Modified Local Binary Pattern and Random Forest @@ -15393,8 +53645,80 @@ Brian O’Connor and Kaushik Roy Department of Computer Science, North Carolina A&T State University, Greensboro, NC 27411"
+84187adc5e6412123405102bb3c2f0428713593c,Quad-Tree based Image Encoding Methods for Data-Adaptive Visual Feature Learning,"IPSJ SIG Technical Report +Quad-Tree based Image Encoding Methods for +Data-Adaptive Visual Feature Learning +Cuicui Zhang1,a) Xuefeng Liang1,b) Takashi Matsuyama1,c)"
+84a20d0a47c0d826b77f73075530d618ba7573d2,Look at Boundary: A Boundary-Aware Face Alignment Algorithm,"(68 points) COFW (29 points) AFLW (19 points) Figure1:Thefirstcolumnshowsthefaceimagesfromdifferentdatasetswithdifferentnumberoflandmarks.Thesecondcolumnillustratestheuniversallydefinedfacialboundariesestimatedbyourmethods.Withthehelpofboundaryinformation,ourapproachachieveshighaccuracylocalisationresultsacrossmultipledatasetsandannotationprotocols,asshowninthethirdcolumn.Differenttofacedetection[45]andrecognition[75],facealignmentidentifiesgeometrystructureofhumanfacewhichcanbeviewedasmodelinghighlystructuredout-put.Eachfaciallandmarkisstronglyassociatedwithawell-definedfacialboundary,e.g.,eyelidandnosebridge.However,comparedtoboundaries,faciallandmarksarenotsowell-defined.Faciallandmarksotherthancornerscanhardlyremainthesamesemanticallocationswithlargeposevariationandocclusion.Besides,differentannotationschemesofexistingdatasetsleadtoadifferentnumberoflandmarks[28,5,66,30](19/29/68/194points)andanno-tationschemeoffuturefacealignmentdatasetscanhardlybedetermined.Webelievethereasoningofauniquefacial"
+84124eba5ccd5a25d2275c3dd6d2f15e30225ef7,People counting with image retrieval using compressed sensing,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) +978-1-4799-2893-4/14/$31.00 ©2014 Crown +Homa Foroughi, Nilanjan Ray, Hong Zhang +Index Terms— compressed sensing, people counting, +. INTRODUCTION"
+84f6f20496fadb975922b47528fd94c71e872950,Dissimilarity-based people re-identification and search for intelligent video surveillance,"Ph.D. in Electronic and Computer Engineering +Dept. of Electrical and Electronic Engineering +University of Cagliari +Dissimilarity-based people +re-identification and search for +intelligent video surveillance +Riccardo Satta +Advisor: Prof. Fabio Roli +Co-advisor: Prof. Giorgio Fumera +Curriculum: ING-INF/05 - Sistemi di Elaborazione delle Informazioni +XXV Cycle +April 2013"
4adca62f888226d3a16654ca499bf2a7d3d11b71,Models of Semantic Representation with Visual Attributes,"Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pages 572–582, Sofia, Bulgaria, August 4-9 2013. c(cid:13)2013 Association for Computational Linguistics"
+4a45b8f8decc178305af06d758ac7428a9070fad,Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data,"Augmented CycleGAN: Learning Many-to-Many Mappings +from Unpaired Data +Amjad Almahairi 1 † Sai Rajeswar 1 Alessandro Sordoni 2 Philip Bachman 2 Aaron Courville 1 3"
+4a70c6e14bcd7a44838fdabdcdb33bc026c907b4,Allocentric Pose Estimation,"Allocentric Pose Estimation +Jos´e Oramas M. +Luc De Raedt +Tinne Tuytelaars +KU Leuven, ESAT-PSI, iMinds +KU Leuven, CS-DTAI +KU Leuven, ESAT-PSI, iMinds"
+4a9831e5fec549edee454709048a51997ef60fb7,Did the Model Understand the Question?,"Did the Model Understand the Question? +Pramod K. Mudrakarta +University of Chicago +Ankur Taly +Google Brain +Mukund Sundararajan +Kedar Dhamdhere +Google +Google"
+4af25075729aa4d0fa4ecf6c948f59ec15bf9565,ii DOCUMENT EVOLUTION Version Date,"Project N° IST-2002-507634 - BioSecure +D 9.1.2 - Revision: b3 +4 June 2005 +Contract Number : +Project Acronym : +Project Title : +Instrument : +Start Date of Project : +Duration : +Deliverable Number : +Title of Deliverable : +Contractual Due Date : +Actual Date of Completion : +IST-2002-507634 +BioSecure +Biometrics for Secure Authentication +Network of Excellence +01 June, 2004 +6 months +D 9.1.2"
+4af133c49d39c8b7aa9d82c17f1fd2c70e36233f,Recognition of Facial Gestures using Gabor Filter,"Recognition of Facial Gestures using Gabor Filter +{tag} {/tag} +International Journal of Computer Applications +© 2011 by IJCA Journal +Number 8 - Article 2 +Year of Publication: 2011 +Authors: +Subhashini Ramalingam +Dr Ilango Paramasivam +Mangayarkarasi Ramiah +10.5120/3153-3990"
4a2d54ea1da851151d43b38652b7ea30cdb6dfb2,Direct recognition of motion-blurred faces,"Direct Recognition of Motion Blurred Faces Kaushik Mitra, Priyanka Vageeswaran and Rama Chellappa"
4ab84f203b0e752be83f7f213d7495b04b1c4c79,Concave Losses for Robust Dictionary Learning,"CONCAVE LOSSES FOR ROBUST DICTIONARY LEARNING @@ -15406,12 +53730,61 @@ Rua do Mat˜ao, 1010 – 05508-090 – S˜ao Paulo-SP, Brazil Universit´e de Rouen Normandie LITIS EA 4108 76800 Saint- ´Etienne-du-Rouvray, France"
+4a75d59c9c57da420441190071ba545eb4a75e1e,Deep Mixture of Diverse Experts for Large-Scale Visual Recognition,"Deep Mixture of Diverse Experts for Large-Scale +Visual Recognition +Tianyi Zhao, Jun Yu, Zhenzhong Kuang, Wei Zhang, Jianping Fan"
+4a1b67d1f30abeeecb270666605025d9d78971ff,Energy-based adaptive skin segmentation for hand and head detection,"Noname manuscript No. +(will be inserted by the editor) +Energy-based adaptive skin segmentation for hand and +head detection +Michal Kawulok +Received: date / Accepted: date"
4a3758f283b7c484d3f164528d73bc8667eb1591,Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial Networks,"Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial Networks Yunfan Liu, Qi Li, and Zhenan Sun∗ Center for Research on Intelligent Perception and Computing, CASIA National Laboratory of Pattern Recognition, CASIA {qli,"
+4a19f6545473363b16d4a10ed13fef29b38856d3,What is a Salient Object? A Dataset and a Baseline Model for Salient Object Detection,"What is a salient object? A dataset and +baseline model for salient object detection +Ali Borji, Member, IEEE"
+4af997701ce14ba689f7f964a72bcae0a2432435,The role of gaze direction in face memory in autism spectrum disorder.,"RESEARCH ARTICLE +The Role of Gaze Direction in Face Memory in Autism +Spectrum Disorder +Safa R. Zaki and Shannon A. Johnson +We tested the hypothesis that the direction of gaze of target faces may play a role in reported face recognition deficits +in those with an autism spectrum disorder (ASD). In previous studies, typically developing children and adults better +remembered faces in which the eyes were gazing directly at them compared with faces in which the eyes were averted. +In the current study, high-functioning children and adolescents with an ASD and age- and IQ-matched typically +developing controls were shown a series of pictures of faces in a study phase. These pictures were of individuals whose +gaze was either directed straight ahead or whose gaze was averted to one side. We tested the memory for these study faces +in a recognition task in which the faces were shown with their eyes closed. The typically developing group better +remembered the direct-gaze faces, whereas the ASD participants did not show this effect. These results imply that there +may be an important link between gaze direction and face recognition abilities in ASD. Autism Res 2013, (cid:129)(cid:129): (cid:129)(cid:129)–(cid:129)(cid:129). +© 2013 International Society for Autism Research, Wiley Periodicals, Inc. +Keywords: autism spectrum disorder; face recognition; eye-contact; face-processing; gaze +Face processing is a pivotal component of human +ommunication and interaction. There is evidence that +people with an autism spectrum disorder (ASD), a disor- +der characterized by impairments in social interaction +nd communication as well as restricted range of interests"
+4ac4b0a2d06ff5df1cc4941f8ae47843b4593bba,American Sign Language fingerspelling recognition from video: Methods for unrestricted recognition and signer-independence,"American Sign Language fingerspelling recognition +from video: Methods for unrestricted recognition +nd signer-independence +Taehwan Kim +A thesis submitted +in partial fulfillment of the requirements for +the degree of +Doctor of Philosophy in Computer Science +t the +Toyota Technological Institute at Chicago +Chicago, Illionois +August 2016 +Thesis Committee: +Vassilis Athitsos +Karen Livescu (Thesis Advisor) +Greg Shakhnarovich +Yisong Yue"
4a4da3d1bbf10f15b448577e75112bac4861620a,"Face , Expression , and Iris Recognition","FACE, EXPRESSION, AND IRIS RECOGNITION USING LEARNING-BASED APPROACHES Guodong Guo @@ -15428,6 +53801,10 @@ Sikandar Amin · Mykhaylo Andriluka · Manfred Pinkal · Bernt Schiele" 4a0f98d7dbc31497106d4f652968c708f7da6692,Real-time eye gaze direction classification using convolutional neural network,"Real-time Eye Gaze Direction Classification Using Convolutional Neural Network Anjith George, Member, IEEE, and Aurobinda Routray, Member, IEEE"
+4af36d3ce93f7ed82a7dc321fca926d540691b33,ADVISE: Symbolism and External Knowledge for Decoding Advertisements,[cs.CV] 29 Jul 2018
+4a95dacb1d38a07e73007082b8ed7651a4b5277c,Region labelling using a Point-Based Coherence Criterion,"Region labelling using a Point-Based Coherence Criterion +Hichem Houissa(cid:2) and Nozha Boujemaa(cid:2) +(cid:2)INRIA Rocquencourt, BP 105,78153, Le Chesnay Cedex-France"
4a5592ae1f5e9fa83d9fa17451c8ab49608421e4,Multi-modal social signal analysis for predicting agreement in conversation settings,"Multi-modal Social Signal Analysis for Predicting Agreement in Conversation Settings Víctor Ponce-López @@ -15448,6 +53825,15 @@ Computer Vision Center, UAB, Xavier Baró EIMT, Open University of Catalonia, Rbla. Poblenou,"
+4a56d5e483ddea93f14bfbe350a3063b2b9126cb,Iterative Action and Pose Recognition Using Global-and-Pose Features and Action-Specific Models,"Iterative Action and Pose Recognition +using Global-and-Pose Features and Action-specific Models +Norimichi Ukita +Nara Institute of Science and Technology"
+4a53ac7f99a42da17a7f1ba04f5c6d6831e31151,Beyond Bilinear: Generalized Multi-modal Factorized High-order Pooling for Visual Question Answering,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Beyond Bilinear: Generalized Multi-modal +Factorized High-order Pooling +for Visual Question Answering +Zhou Yu, Jun Yu Member, IEEE, Chenchao Xiang, Jianping Fan, Dacheng Tao Fellow, IEEE"
4a1a5316e85528f4ff7a5f76699dfa8c70f6cc5c,Face Recognition using Local Features based on Two-layer Block Model,"MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan Face Recognition using Local Features based on Two-layer Block M odel W onjun Hwang1 Ji-Yeun Kim Seokcheol Kee @@ -15474,16 +53860,129 @@ Hilal Ergun and Mustafa SertB Department of Computer Engineering Bas¸kent University 06810 Ankara, TURKEY"
+4a8085987032e85ac8017d9977a4b76b0d8fa4ac,Object Recognition using Template Matching,"Object Recognition using Template Matching +Nikhil Gupta, Rahul Gupta, Amardeep Singh, Matt Wytock +December 12, 2008 +Introduction +Building 3D models +Object Recognition is inherently a hard problem in +omputer vision. Current standard object recogni- +tion techniques require small training data sets of +images and apply sophisticated algorithms. These +methods tend to perform poorly because the small +data set does not reflect the true distribution (selec- +tion bias). +Recently, Torralba et al [1] have proposed to de- +velop a large data set of images (80 million images) +nd apply simple algorithms for object recognition. +Their method performs relatively well for some cer- +tain classes of objects. Nevertheless, their data sets +require very large storage and are noisy. +In this project, we develop precise 3D models of +objects and use these to apply simple learning al-"
4ac3cd8b6c50f7a26f27eefc64855134932b39be,Robust Facial Landmark Detection via a Fully-Convolutional Local-Global Context Network,"Robust Facial Landmark Detection via a Fully-Convolutional Local-Global Context Network Daniel Merget Matthias Rock Gerhard Rigoll Technical University of Munich"
+4a0f152a07a9becb986b516a1281a4482b38db81,Video Compression for Object Detection Algorithms,"CONFIDENTIAL. Limited circulation. For review only. +Preprint submitted to 24th International Conference on Pattern Recognition. +Received January 22, 2018."
+4ad51a99e489939755f1d4f5d1f5bc509c49e96d,Preferences for facially communicated big five personality traits and their relation to self-reported big five personality,"Personality and Individual Differences 134 (2018) 195–200 +Contents lists available at ScienceDirect +Personality and Individual Differences +journal homepage: www.elsevier.com/locate/paid +Preferences for facially communicated big five personality traits and their +relation to self-reported big five personality +Donald F. Sacco⁎, Mitch Brown +The University of Southern Mississippi, United States of America +A R T I C L E I N F O +A B S T R A C T +Keywords: +Personality +Face perception +Big five +Similarity +Complementarity +A growing body of research has begun to document that core personality traits are associated with specific facial +structures, and that individuals are sensitive to these facial cues, as indexed by preferences for faces commu- +nicating higher or lower levels of specific traits. We explored how self-reported Big Five personality traits in- +fluence preferences for facially-communicated Big Five personality in targets. Participants selected among pairs"
+4a31ca27b987606ae353b300488068b5240633ee,WSABIE: Scaling Up to Large Vocabulary Image Annotation,"WSABIE: Scaling Up To Large Vocabulary Image Annotation +Jason Weston1 and Samy Bengio1 and Nicolas Usunier2 +Google, USA +Universit´e Paris 6, LIP6, France"
4abaebe5137d40c9fcb72711cdefdf13d9fc3e62,Dimension Reduction for Regression with Bottleneck Neural Networks,"Dimension Reduction for Regression with Bottleneck Neural Networks Elina Parviainen BECS, Aalto University School of Science and Technology, Finland"
+4a64b020c72db15a729939a2c041ef4f5830f0f7,Challenges of Ground Truth Evaluation of Multi-target Tracking,"Challenges of Ground Truth Evaluation of Multi-Target Tracking +Anton Milan1 +Konrad Schindler2 +Stefan Roth1 +Department of Computer Science, TU Darmstadt +Photogrammetry and Remote Sensing Group, ETH Z¨urich"
+4abaf7d4b9577131cb2f93e913f8bd83f924da4c,Towards learning through robotic interaction alone: the joint guided search task,"Towards learning through robotic interaction alone: +the joint guided search task +Nick DePalma and Cynthia Breazeal +0 Ames Str. Cambridge MA +Personal Robots Group +MIT Media Lab"
+4a3a9d02999fcf0895db31d644f40c98254ac4b1,Vision-based 3D bicycle tracking using deformable part model and Interacting Multiple Model filter,"Vision-based 3D Bicycle Tracking using Deformable Part Model +nd Interacting Multiple Model Filter +Hyunggi Cho, Paul E. Rybski and Wende Zhang"
+4a4a3effdfffb51a0f82d3b0904c017086996ac6,Conceptual and methodological challenges for neuroimaging studies of autistic spectrum disorders,"Mazzone and Curatolo Behavioral and Brain Functions 2010, 6:17 +http://www.behavioralandbrainfunctions.com/content/6/1/17 +REVIEW +Conceptual and methodological challenges for +neuroimaging studies of autistic spectrum +disorders +Luigi Mazzone1*, Paolo Curatolo2 +Open Access"
+4a9afcc6ba45c0ff05ea93d306ff73ede32f7ed4,Multiple-shot People Re-identify based on Feature Selection with Sparsity,"International Journal of Hybrid Information Technology +Vol.8, No.1 (2015), pp.27-34 +http://dx.doi.org/10.14257/ijhit.2015.8.1.03 +Multiple-shot People Re-identify based on Feature Selection with +Sparsity +Dongping Zhang, Yanjie Li, Jiao Xu and Ye Shen +College of Information Engineering, China Jiliang University, Hangzhou 310018, +China"
+4a88237199595feaa3f0e3289cbdd201a3ce28ff,Multi-Domain Pose Network for Multi-Person Pose Estimation and Tracking,"Multi-Domain Pose Network for Multi-Person +Pose Estimation and Tracking +Hengkai Guo1(cid:63), Tang Tang1, Guozhong Luo1, Riwei Chen1, Yongchen Lu1, +nd Linfu Wen1 +ByteDance AI Lab"
+4a227881f5763d2bda2e545eac346389b2b2017a,Model based image interpretation with application to facial expression recognition,"d d d +d d d d +ddd ddd ddd ddd +Institut für Informatik +der Technischen Universität München +Model-based Image Interpretation with +Application to Facial Expression +Recognition +Dissertation +Matthias Wimmer"
+4a869781d074f6be7a5001c59e41b25145bdd830,DeltaPhish: Detecting Phishing Webpages in Compromised Websites,"DeltaPhish: Detecting Phishing Webpages +in Compromised Websites∗ +Igino Corona1,2, Battista Biggio1,2, Matteo Contini2, Luca Piras1,2, Roberto Corda2, Mauro +Mereu2, Guido Mureddu2, Davide Ariu1,2, and Fabio Roli1,2 +Pluribus One, via Bellini 9, 09123 Cagliari, Italy +DIEE, University of Cagliari, Piazza d’Armi 09123, Cagliari, Italy"
+4a303369828d9334022a0f5e8ad2b1a715d1c0c9,Deep Metric Learning by Online Soft Mining and Class-Aware Attention,"Deep Metric Learning by Online Soft Mining and Class-Aware Attention +Xinshao Wang1,2, Yang Hua1,2, Elyor Kodirov2, Guosheng Hu1,2, Neil M. Robertson1,2 +School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, UK +{xwang39, y.hua, {elyor, +Anyvision Research Team, UK"
+4ae3cdba121dec886a84eff146e438a55513002c,Interactive Hausdorff distance computation for general polygonal models,"Interactive Hausdorff Distance Computation for General Polygonal Models +Min Tang∗ +Minkyoung Lee† +Ewha Womans University, Seoul, Korea +Young J. Kim‡ +http://graphics.ewha.ac.kr/HDIST +Figure 1: Interactive Hausdorff Distance Computation. Our algorithm can compute Hausdorff distance between complicated models at +interactive rates (the first three figures). Here, the green line denotes the Hausdorff distance. This algorithm can also be used to find +penetration depth (PD) for physically-based animation (the last two figures). It takes only a few milli-seconds to run on average."
4aeb87c11fb3a8ad603311c4650040fd3c088832,Self-paced Mixture of Regressions,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) SamplesSelected SamplesOutliersMoRSPMoR (ours)6361242024Figure1:Inter-componentimbalanceandintra-componentoutliersinMixtureofRegression(MoR)approaches.StandardMoRcannotlearnaccurateregressors(denotedbythedashedlines).Byintroduc-inganovelself-pacedscheme,ourSPMoRapproach(denotedbythesolidlines)selectsbalancedandconfidenttrainingsamplesfromeachcomponent,whilepreventlearningfromtheoutliersthroughoutthetrainingprocedure.theywillbeinevitablybiasedbydatadistribution:lowre-gressionerrorindenselysampledspacewhilehigherrorineverywhereelse.Foraddressingtheissuesofthedatadiscontinuityandheterogeneity,thedivide-and-conquerapproacheswerepro-posedlately.Thecoreideaistolearntocombinemultiplelocalregressors.Forinstance,thehierarchical-based[Hanetal.,2015]andtree-basedregression[HaraandChellappa,2014]makehardpartitionsrecursively,andthesubsetsofsam-plesmaynotbehomogeneousforlearninglocalregressors.WhileMixtureofRegressions(MoR)[Jacobsetal.,1991;JordanandXu,1995]distributesregressionerroramonglocalregressorsbymaximizinglikelihoodinthejointinput-outputspace.Theseapproachesreduceoverallerrorbyfittingre-gressionlocallyandreliefsthebiasbydiscontinuousdatadistribution.Unfortunately,theaforementionedapproachesstillcannotachievesatisfactoryperformancewhenapplyinginsomereal-worldapplications.Themainreasonisthattheseapproachestendtobesensitivetotheintra-componentoutliers(i.e.,thenoisytrainingdataresidingincertaincomponents)andtheinter-componentimbalance(i.e.,thedifferentamountsoftrain-"
4a3d96b2a53114da4be3880f652a6eef3f3cc035,A Dictionary Learning-Based 3D Morphable Shape Model,"A Dictionary Learning-Based @@ -15491,9 +53990,33 @@ D Morphable Shape Model Claudio Ferrari , Giuseppe Lisanti, Stefano Berretti , Senior Member, IEEE, and Alberto Del Bimbo"
+4aa18f3a1c85f7a09d3b0d6b28c0339199892d60,The Application of Neural Networks for Facial Landmarking on Mobile Devices,
4a6fcf714f663618657effc341ae5961784504c7,Scaling Up Class-Specific Kernel Discriminant Analysis for Large-Scale Face Verification,"Scaling up Class-Specific Kernel Discriminant Analysis for large-scale Face Verification Alexandros Iosifidis, Senior Member, IEEE, and Moncef Gabbouj, Fellow, IEEE"
+4a855d86574c9bd0a8cfc522bc1c77164819c0bc,PixelCNN Models with Auxiliary Variables for Natural Image Modeling,"PixelCNN Models with Auxiliary Variables for Natural Image Modeling +Alexander Kolesnikov 1 Christoph H. Lampert 1"
+2409557812a3d26258949ba73a05031591f42bdc,Exact Discovery of Time Series Motifs,"Abdullah Mueen +Exact Discovery of Time Series Motifs +Eamonn Keogh +Qiang Zhu +Sydney Cash1,2 Brandon Westover1,3 +Massachusetts General Hospital, 2Harvard Medical School, 3Brigham and Women's Hospital +University of California – Riverside +{mueen, eamonn,"
+24ec4cd704d07865ce31fe539d00cd2597b5dfc9,Face Localization in the Neural Abstraction Pyramid,Face Localization
+24e98b70dc6982af2dd3a5bb4e501cc1b61f7d2b,LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2018 +LCR-Net++: Multi-person 2D and 3D Pose +Detection in Natural Images +Gr´egory Rogez, Philippe Weinzaepfel, and Cordelia Schmid, Fellow, IEEE"
+24c7554823bb8c1c0729c4ece5f3e50965aea74e,Robust Computation of Linear Models by Convex Relaxation,"ROBUST COMPUTATION OF LINEAR MODELS, +OR HOW TO FIND A NEEDLE IN A HAYSTACK +GILAD LERMAN∗, MICHAEL MCCOY†, JOEL A. TROPP†, AND TENG ZHANG◦"
+245130ac792531ca9981f9c5907190eac19ebb50,Detecting Objects using Unsupervised Parts-based Attributes∗,"Detecting Objects using Unsupervised Parts-based Attributes∗ +Santosh K. Divvala1, Larry Zitnick2, Ashish Kapoor2 , Simon Baker2 +Carnegie Mellon University. +Microsoft Research. +{larryz, ashishk,"
24115d209e0733e319e39badc5411bbfd82c5133,Long-Term Recurrent Convolutional Networks for Visual Recognition and Description,"Long-term Recurrent Convolutional Networks for Visual Recognition and Description Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, Subhashini Venugopalan, Sergio Guadarrama, @@ -15504,6 +54027,45 @@ Joaquin Zepeda Technicolor, Cesson-S´evign´e, France Franc¸ois Le Clerc Patrick P´erez"
+245922e5251c103c2021577cc0f99791d748ac64,Fusion of Intraoperative 3D B-mode and Contrast-Enhanced Ultrasound Data for Automatic Identification of Residual Brain Tumors,"Article +Fusion of Intraoperative 3D B-mode and +Contrast-Enhanced Ultrasound Data for Automatic +Identification of Residual Brain Tumors +Elisee Ilunga-Mbuyamba 1,3, Dirk Lindner 2, Juan Gabriel Avina-Cervantes 1,∗, Felix Arlt 2, +Horacio Rostro-Gonzalez 1, Ivan Cruz-Aceves 4 and Claire Chalopin 3 +Telematics (CA), Engineering Division (DICIS), University of Guanajuato, Campus Irapuato-Salamanca, +Carr. Salamanca-Valle km 3.5 + 1.8, Comunidad de Palo Blanco, Salamanca, Gto. 36885, Mexico; +(E.I.-M.); (H.R.-G.) +Department of Neurosurgery, University Hospital Leipzig, Leipzig 04103, Germany; +(D.L.); (F.A.) +Innovation Center Computer Assisted Surgery (ICCAS), University of Leipzig, Leipzig 04103, Germany; +Centro de Investigacion en Matematicas (CIMAT), A.C., Jalisco S/N, Col. Valenciana, +Guanajuato, Gto. 36000, Mexico; +* Correspondence: Tel.: +52-46-4647-9940 (ext. 2400) +Academic Editor: Hideyuki Hasegawa +Received: 15 February 2017; Accepted: 17 April 2017; Published: 19 April 2017"
+244a6d4f5f745f8c2a58a6a70d7ba2b91300c118,RADON Transform and PCA based 3 D Face Recognition using KNN and SVM,"International Journal of Computer Applications (0975 – 8887) +Recent Advances in Information Technology, 2014 +RADON Transform and PCA based 3D Face Recognition +using KNN and SVM +P. S. Hiremath +Department of Computer Science +Gulbarga University +Gulbarga, KA, India +Manjunatha Hiremath +Department of Computer Science +Gulbarga University +Gulbarga, KA, India +integral +researches +society.Many"
+247b14570940601f5c7a2da1db532ecf1c302288,Dual Attention Networks for Multimodal Reasoning and Matching,"Dual Attention Networks for Multimodal Reasoning and Matching +Hyeonseob Nam +Naver Search Solutions +Jung-Woo Ha +Naver Labs +Jeonghee Kim +Naver Labs"
245f8ec4373e0a6c1cae36cd6fed5a2babed1386,Lucas Kanade Optical Flow Computation from Superpixel based Intensity Region for Facial Expression Feature Extraction,"J. Appl. Environ. Biol. Sci., 7(3S)1-10, 2017 © 2017, TextRoad Publication ISSN: 2090-4274 @@ -15519,6 +54081,50 @@ Engineering Campus, 14300 Nibong Tebal, Pulau Pinang, Malaysia Kulim Hi-Tech Park, Kedah, Malaysia Received: February 21, 2017 Accepted: May 14, 2017"
+2484a34597a40d846c084e827fda299fd0927008,Image Matching Algorithm based on SURF Feature-point and DAISY Descriptor,"Image Matching Algorithm based on +Feature-point and DAISY Descriptor +School of Business, Sichuan Agricultural University, Sichuan Dujianyan 611830, China +Li Li +is the research"
+24b6d839662e5d56f17fc26eab4d2901f6835ddf,Real Time Lip Motion Analysis for a Person Authentication System using Near Infrared Illumination,"REAL TIME LIP MOTION ANALYSIS FOR A +PERSON AUTHENTICATION SYSTEM USING NEAR +INFRARED ILLUMINATION +Faisal Shafait, Ralph Kricke, Islam Shdaifat, Rolf-Rainer Grigat +TUHH Vision Systems (4-08/1) +Harburger Schloßstr. 20, 21079 Hamburg, Germany +Tel: +49 40 42878-3125, Fax: +49 40 42878-2911 +http://www.ti1.tu-harburg.de +in: 2006 IEEE International Conference on Image Processing. See also BIBTEX entry below. +BIBTEX: +uthor = {Faisal Shafait and Ralph Kricke and Islam Shdaifat and Rolf-Rainer Grigat}, +title = {REAL TIME LIP MOTION ANALYSIS FOR A PERSON AUTHENTICATION SYSTEM +USING NEAR INFRARED ILLUMINATION}, +ooktitle = {2006 IEEE International Conference on Image Processing}, +year = {2006}, +pages = {1957-1960}, +month = {oct}, +url = {http://www.ti1.tu-harburg.de/Publikationen} +scheduled for October 8-11, 2006 in Atlanta, Georgia, USA. Personal use of this material is permitted. +However, permission to reprint/republish this material for advertising or promotional purposes or for cre-"
+246218fd60d47975990908c48274341b47255292,Marker-less motion capture in general scenes with sparse multi-camera setups,"Marker-less Motion Capture in General +Scenes with Sparse Multi-camera Setups +Ahmed Elhayek +Saarbr¨ucken, Germany +Dissertation +zur Erlangung des Grades des +Doktors der Ingenieurswissenschaften (Dr.-Ing.) +der Naturwissenschaftlich-Technischen Fakult¨aten +der Universit¨at des Saarlandes +March 2015"
+2491203e3b268235ea0269f41dbebd113d2a1b0a,"Optimal multiplexed sensing: bounds, conditions and a graph theory link.","Optimal multiplexed sensing: bounds, +onditions and a graph theory link +Netanel Ratner,1 Yoav Y. Schechner,1,∗ +nd Felix Goldberg2 +Dept. Electrical Engineering, Technion - Israel Inst. Technology +Haifa 32000, Israel +Dept. Mathematics, Technion - Israel Inst. Technology +Haifa 32000, Israel +Corresponding author:"
24e099e77ae7bae3df2bebdc0ee4e00acca71250,Robust Face Alignment Under Occlusion via Regional Predictive Power Estimation,"Robust face alignment under occlusion via regional predictive power estimation. Heng Yang; Xuming He; Xuhui Jia; Patras, I @@ -15528,6 +54134,20 @@ http://qmro.qmul.ac.uk/xmlui/handle/123456789/22467 Information about this research object was correct at the time of download; we occasionally make corrections to records, please therefore check the published record when citing. For more information contact"
+24e79933d8d71dd9e72e289d9d89a061ccbb01c3,Analysis of Principal Component Analysis (PCA) Face Recognition: Effects of Similarity Measure,"Analysis of Principal Component Analysis (PCA) +Face Recognition: Effects of Similarity Measure +Arjun V Mane#1, Ramesh R Manza#2, Karbhari V Kale#3 +#Department of Computer Science & Information Technology, +Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MS) India"
+2431eeb2df8877d78901fa37a091a23dc207c2b2,Rotation-Invariant HOG Descriptors Using Fourier Analysis in Polar and Spherical Coordinates,"Int J Comput Vis +DOI 10.1007/s11263-013-0634-z +Rotation-Invariant HOG Descriptors Using Fourier Analysis +in Polar and Spherical Coordinates +Kun Liu · Henrik Skibbe · Thorsten Schmidt · +Thomas Blein · Klaus Palme · Thomas Brox · +Olaf Ronneberger +Received: 30 September 2012 / Accepted: 21 May 2013 +© Springer Science+Business Media New York 2013"
2450c618cca4cbd9b8cdbdb05bb57d67e63069b1,A connexionist approach for robust and precise facial feature detection in complex scenes,"A Connexionist Approach for Robust and Precise Facial Feature Detection in Complex Scenes Stefan Duffner and Christophe Garcia @@ -15535,9 +54155,124 @@ France Telecom Research & Development , rue du Clos Courtel 5512 Cesson-S´evign´e, France fstefan.duffner,"
+246fa412f26d5bf5b151a7c3f5287141bd08ae0b,Deep Metric Learning for the Target Cost in Unit-Selection Speech Synthesizer,"Interspeech 2018 +-6 September 2018, Hyderabad +0.21437/Interspeech.2018-1305"
+24041477d6e412e4afc441992f4b170831f725c7,International Journal of Advance Research in Computer Science and Management Studies,"Volume 3, Issue 10, October 2015 +International Journal of Advance Research in +Computer Science and Management Studies +Research Article / Survey Paper / Case Study +Available online at: www.ijarcsms.com +ISSN: 2321-7782 (Online) +Automatic Face Naming by Using Fused Affinity Matrix +Kadam Vaibhav Bharat1 +B.E. Computer Science +Deshpande Supriya Ajay2 +B.E. Computer Science +Alarm College of Engineering, Pune, India +Alarm College of Engineering, Pune, India +Malpure Sagar3 +B.E. Computer Science +Choudhary Jitendra4 +B.E. Computer Science +Alarm College of Engineering, Pune, India +Alarm College of Engineering, Pune, India"
244b57cc4a00076efd5f913cc2833138087e1258,Warped Convolutions: Efficient Invariance to Spatial Transformations,"Warped Convolutions: Efficient Invariance to Spatial Transformations Jo˜ao F. Henriques 1 Andrea Vedaldi 1"
+242ae7b1b1c3e1aafcbe9cef3cb23918c6f94f2c,Performance Evaluation of Biometric Template Update,"Performance Evaluation +of Biometric Template Update +Romain Giot and Christophe Rosenberger +Université de Caen, UMR 6072 GREYC +ENSICAEN, UMR 6072 GREYC +CNRS, UMR 6072 GREYC +Email: +Email: +Bernadette Dorizzi +Institut Télécom; Télécom SudParis +UMR 5157 SAMOVAR +Email:"
+2475d216fd52994ac69ef922f4daf73e47f9535d,Joint Albedo Estimation and Pose Tracking from Video,"Joint Albedo Estimation and Pose Tracking +from Video +Sima Taheri, Student Member, IEEE, Aswin Sankaranarayanan, Member, IEEE, +nd Rama Chellappa, Fellow, IEEE"
24869258fef8f47623b5ef43bd978a525f0af60e,Données multimodales pour l ’ analyse d ’ image,"UNIVERSITÉDEGRENOBLENoattribuéparlabibliothèqueTHÈSEpourobtenirlegradedeDOCTEURDEL’UNIVERSITÉDEGRENOBLESpécialité:MathématiquesetInformatiquepréparéeauLaboratoireJeanKuntzmanndanslecadredel’ÉcoleDoctoraleMathématiques,SciencesetTechnologiesdel’Information,InformatiqueprésentéeetsoutenuepubliquementparMatthieuGuillauminle27septembre2010ExploitingMultimodalDataforImageUnderstandingDonnéesmultimodalespourl’analysed’imageDirecteursdethèse:CordeliaSchmidetJakobVerbeekJURYM.ÉricGaussierUniversitéJosephFourierPrésidentM.AntonioTorralbaMassachusettsInstituteofTechnologyRapporteurMmeTinneTuytelaarsKatholiekeUniversiteitLeuvenRapporteurM.MarkEveringhamUniversityofLeedsExaminateurMmeCordeliaSchmidINRIAGrenobleExaminatriceM.JakobVerbeekINRIAGrenobleExaminateur"
+246ec873db261257833231d657ec8995d686cc3e,Facing the implications: Dangerous world beliefs differentially predict men and Women's aversion to facially communicated..,"See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/315831650 +Facing the implications: Dangerous world +eliefs differentially predict men and Women's +version to facially communicated... +Article in Personality and Individual Differences · October 2017 +READS +DOI: 10.1016/j.paid.2017.04.018 +CITATIONS +authors, including: +Mitch Brown +University of Southern Mississippi +9 PUBLICATIONS 14 CITATIONS +SEE PROFILE +Some of the authors of this publication are also working on these related projects: +Facially Communicated Extraversion and Social Motives View project +Grip Strength and Perceptions View project +All content following this page was uploaded by Mitch Brown on 09 April 2017. +The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the original document +nd are linked to publications on ResearchGate, letting you access and read them immediately."
+247df1d4fca00bc68e64af338b84baaecc34690b,Evaluation of Gender Classification Methods with Automatically Detected and Aligned Faces,"Review +Procedure +009/6/12 +Paper + “Evaluation of Gender Classification Methods +with Automatically Detected and Aligned +Faces” + Erno Makinen & Roope Raisamo + 2008 +Decision +resizing +lignment +face detection +resizing +lassification +resizing +lignment +lignment +resizing +face detection"
+24da9c1eb30ed5ef0052f760d5d847bf5cd1d2ba,A Machine-Learning Approach to Keypoint Detection and Landmarking on 3D Meshes,"Int J Comput Vis +DOI 10.1007/s11263-012-0605-9 +A Machine-Learning Approach to Keypoint Detection +nd Landmarking on 3D Meshes +Clement Creusot · Nick Pears · Jim Austin +Received: 14 October 2011 / Accepted: 17 December 2012 +© Springer Science+Business Media New York 2013"
+2475ad865b2102cef83a87adfe0d2e71d4791e53,A Supervised Clustering Algorithm for the Initialization of RBF Neural Network Classifiers,"A Supervised Clustering Algorithm for the Initialization +of RBF Neural Network Classifiers +Hakan Cevikalp, Diane Larlus, Frédéric Jurie +To cite this version: +Hakan Cevikalp, Diane Larlus, Frédéric Jurie. A Supervised Clustering Algorithm for the Ini- +SIU ’07 - 15th Signal Processing and Com- +tialization of RBF Neural Network Classifiers. +munications Applications, Jun 2007, Eskisehir, Turkey. +IEEE Computer society, pp.1-4, 2007, +<10.1109/SIU.2007.4298803>. <hal-00203762> +HAL Id: hal-00203762 +https://hal.archives-ouvertes.fr/hal-00203762 +Submitted on 14 Jan 2008 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est"
+2472d6e4459dd65cd77b5fce99220d3b30854408,Towards 3D object recognition via classification of arbitrary object tracks,"Towards 3D Object Recognition +via Classification of Arbitrary Object Tracks +Alex Teichman, Jesse Levinson, Sebastian Thrun +Stanford Artificial Intelligence Laboratory +{teichman, jessel,"
+243778aefb3c23d6774309c70217cb83f7204915,"The Mutex Watershed: Efficient, Parameter-Free Image Partitioning","The Mutex Watershed: +Efficient, Parameter-Free Image Partitioning +Steffen Wolf1⋆, Constantin Pape1,2⋆, Alberto Bailoni1, Nasim Rahaman1, Anna +Kreshuk1,2, Ullrich K¨othe1, and Fred A. Hamprecht1 +HCI/IWR, University of Heidelberg, Germany +EMBL Heidelberg, Germany"
2465fc22e03faf030e5a319479a95ef1dfc46e14,Influence of different feature selection approaches on the performance of emotion recognition methods based on SVM,"______________________________________________________PROCEEDING OF THE 20TH CONFERENCE OF FRUCT ASSOCIATION Influence of Different Feature Selection Approaches on the Performance of Emotion Recognition @@ -15546,12 +54281,43 @@ Daniil Belkov, Konstantin Purtov, Vladimir Kublanov Ural Federal University (UrFU) Yekaterinburg, Russia d.d.belkov,"
+2452dfb2c5a4578ac9497cc4dc3c6d5d03997210,On designing an unconstrained tri-band pupil detection system for human identification,"DOI 10.1007/s00138-015-0700-3 +ORIGINAL PAPER +On designing an unconstrained tri-band pupil detection system +for human identification +Cameron Whitelam1 · Thirimachos Bourlai1 +Received: 30 September 2014 / Revised: 11 February 2015 / Accepted: 15 June 2015 +© Springer-Verlag Berlin Heidelberg 2015 +facial"
24ff832171cb774087a614152c21f54589bf7523,Beat-Event Detection in Action Movie Franchises,"Beat-Event Detection in Action Movie Franchises Danila Potapov Matthijs Douze Jerome Revaud Zaid Harchaoui Cordelia Schmid"
+247232ab9eabb4f2480dd70557a1ee89afed4f20,Dominant men are faster in decision-making situations and exhibit a distinct neural signal for promptness,"Cerebral Cortex, October 2018;28: 3740–3751 +doi: 10.1093/cercor/bhy195 +Advance Access Publication Date: 15 August 2018 +Original Article +O R I G I N A L A R T I C L E +Dominant men are faster in decision-making situations +nd exhibit a distinct neural signal for promptness +Janir da Cruz1,2, João Rodrigues3, John C. Thoresen3, Vitaly Chicherov1, +Patrícia Figueiredo2, Michael H. Herzog1 and Carmen Sandi +Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, Swiss Federal Institute of +Technology Lausanne (EPFL), CH-1015 Lausanne, Switzerland, 2Institute for Systems and Robotics – Lisboa, +Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal +nd 3Laboratory of Behavioral Genetics, Brain Mind Institute, School of Life Sciences, Swiss Federal Institute of +Technology Lausanne (EPFL), CH-1015 Lausanne, Switzerland +Address correspondence to Carmen Sandi, Laboratory of Behavioral Genetics, Brain Mind Institute, School of Life Sciences, Swiss Federal Institute of +Technology Lausanne (EPFL), CH-1015 Lausanne, Switzerland. Email: +orcid.org/0000-0001-7713-8321 +Janir da Cruz, João Rodrigues, and John C. Thoresen contributed equally to this work +Michael H. Herzog and Carmen Sandi contributed equally to this work"
+244377600b1474e1da3b86a08683e629990d1417,Embedded Vision System for Atmospheric Turbulence Mitigation,"Embedded Vision System for Atmospheric Turbulence Mitigation +Ajinkya Deshmukh1, Gaurav Bhosale, Swarup Medasani2, Karthik Reddy, +Hemanthakumar P, Chandrasekhar A, Kirankumar P, Vijayasagar K +Uurmi Systems Pvt. Ltd., Hyderabad, India"
247a6b0e97b9447850780fe8dbc4f94252251133,Facial action unit detection: 3D versus 2D modality,"Facial Action Unit Detection: 3D versus 2D Modality Arman Savran Electrical and Electronics Engineering @@ -15562,11 +54328,114 @@ Bo˘gazic¸i University, Istanbul, Turkey M. Taha Bilge Department of Psychology Bo˘gazic¸i University, Istanbul, Turkey"
+2485c98aa44131d1a2f7d1355b1e372f2bb148ad,The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 38, NO. 1, JANUARY 2008 +The CAS-PEAL Large-Scale Chinese Face +Database and Baseline Evaluations +Wen Gao, Senior Member, IEEE, Bo Cao, Shiguang Shan, Member, IEEE, +Xilin Chen, Member, IEEE, Delong Zhou, Xiaohua Zhang, and Debin Zhao"
+24d3e695af619e88613aba7dc0e7492c12fa4d0e,Sparsest Matrix based Random Projection for Classification,"Sparse Matrix-based Random Projection for +Classification +Weizhi Lu, Weiyu Li, Kidiyo Kpalma and Joseph Ronsin"
+24585f90bdf30583733841f70430d36948f16ae2,An efficient method for human face recognition using nonsubsampled contourlet transform and support vector machine,"Optica Applicata, Vol. XXXIX, No. 3, 2009 +An efficient method for human face recognition +using nonsubsampled contourlet transform +nd support vector machine +XUEBIN XU, DEYUN ZHANG, XINMAN ZHANG* +School of Electronics and Information Engineering, Xi’an Jiaotong University, +8 Xianning West Road, Xi’an 710049, P.R. China +*Corresponding author: +To improve the recognition rate in different conditions, a multiscale face recognition method +ased on nonsubsampled contourlet transform and support vector machine is proposed in this +paper. Firstly, all face images are decomposed by using nonsubsampled contourlet transform. +The contourlet coefficients of low frequency and high frequency in different scales and various +ngles will be obtained. Most significant information of faces is contained in coefficients, which +is important for face recognition. Then, the combinations of coefficients are applied as study +samples to the support vector machine classifiers. Finally, the decomposed coefficients of testing +face image are used to test classifiers, then face recognition results are obtained. The experiments +re performed on the YaleB database and the Cambridge University ORL database. The results +indicate that the method proposed has performs better than the wavelet-based method. Compared +with the wavelet-based method, the proposed method can make the best recognition rates increase +y 2.85% for YaleB database and 1.87% for ORL database, respectively. Our method is also"
230527d37421c28b7387c54e203deda64564e1b7,Person Re-identification: System Design and Evaluation Overview,"Person Re-identification: System Design and Evaluation Overview Xiaogang Wang and Rui Zhao"
+236942bb64f1711b4763424b2f795fb518c9d8d4,Optimizing LBP Structure For Visual Recognition Using Binary Quadratic Programming,"Optimizing LBP Structure For Visual Recognition +Using Binary Quadratic Programming +Jianfeng Ren, Student Member, IEEE, Xudong Jiang, Senior Member, IEEE, Junsong Yuan, Senior Member, IEEE, +nd Gang Wang, Member, IEEE"
+2315371408e02cdff6f54359f159f192009d1600,Effective Pedestrian Detection Using Center-symmetric Local Binary/Trinary Patterns,"SEPTEMBER 2010 +Effective Pedestrian Detection Using +Center-symmetric Local Binary/Trinary Patterns +Yongbin Zheng, Chunhua Shen, Richard Hartley, Fellow, IEEE, and Xinsheng Huang"
+237316762470d72a02795a7f57de9279e9cda16a,Dimensionality-reduced subspace clustering,"Dimensionality-reduced subspace clustering +Reinhard Heckel, Michael Tschannen, and Helmut B¨olcskei +December 15, 2015"
+239c06cd437832faa55a8e7292c50e45229a3d7c,Generating analytic insights on human behavior using image processing,"Generating Analytic Insights on Human behavior +using Image Processing +Namit Juneja, Rajesh Kumar M, Senior Member, IEEE +School of Electronics Engineering +VIT University +Vellore, India"
+2396ff03c41c498ff20e3a0e5419afa45e4a9d41,MIT Autonomous Vehicle Technology Study: Large-Scale Deep Learning Based Analysis of Driver Behavior and Interaction with Automation,"MIT Autonomous Vehicle Technology Study: +Large-Scale Deep Learning Based Analysis of +Driver Behavior and Interaction with Automation +Lex Fridman∗, Daniel E. Brown, Michael Glazer, William Angell, Spencer Dodd, Benedikt Jenik, +Andrew Sipperley, Anthony Pettinato, Bobbie Seppelt, Linda Angell, Bruce Mehler, Bryan Reimer∗ +Jack Terwilliger, Julia Kindelsberger, Li Ding, Sean Seaman, Hillary Abraham, Alea Mehler,"
+23e1746c449e675a4ffa3833b0ac5c5a7b743f7f,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+2349eab05cd0c6f94ba5314c037d198aa12c2f0f,Eigen-profiles of spatio-temporal fragments for adaptive region-based tracking,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE +ICASSP 2012"
+237734e3fd3abab005b0b97d61416ee16105f902,Consensus Maximization for Semantic Region Correspondences,"Consensus Maximization for Semantic Region Correspondences +Pablo Speciale1, Danda P. Paudel2, Martin R. Oswald1, +Hayko Riemenschneider2, Luc V. Gool2,4, and Marc Pollefeys1,3 +Department of Computer Science, ETH Z¨urich. +Microsoft, Redmond, USA +{pablo, moswald, +Computer Vision Laboratory, D-ITET, ETH Z¨urich +VISICS, ESAT/PSI, KU Leuven, Belgium +{paudel, hayko, +Day / Night +Registration +Outdoor / Indoor +Registration +Scan / CAD +Registration +Figure 1: Example registration results. Our approach solves challenging registration problems by maximizing the number of corre- +sponding semantic regions – such as windows, doors or balconies – for datasets from different modalities, with large amounts of noise and +outliers, little data overlap, or significantly different data statistics."
+239df42479c69cf95e7194cc0ec3d8cf7d4a98e8,Face Detection and Extraction from Low Resolution Surveillance Video Using Motion Segmentation,"Face Detection and Extraction from Low +Resolution Surveillance Video Using +Motion Segmentation +Vikram Mutneja1 +I.K. Gujral Punjab Technical University, Kapurthala, Punjab (India) +Ph.D. Research Scholar, +I.K. Gujral Punjab Technical University Main Campus, Kapurthala, Punjab (India) +Dr. Satvir Singh2, +Associate Professor,"
+23fa51635c646aa621bb18ff76f31d5e48ac969b,MFSC: A new shape descriptor with robustness to deformations,"MFSC: A NEW SHAPE DESCRIPTOR WITH ROBUSTNESS TO DEFORMATIONS +Lunshao Chaia, Zhen Qinb, Honggang Zhanga, Jun Guoa, Bir Bhanub +Beijing University of Posts and Telecomuunictions, Beijing, 100876, China +University of California at Riverside, Riverside, CA 92521, USA"
23172f9a397f13ae1ecb5793efd81b6aba9b4537,Defining Visually Descriptive Language,"Proceedings of the 2015 Workshop on Vision and Language (VL’15), pages 10–17, Lisbon, Portugal, 18 September 2015. c(cid:13)2015 Association for Computational Linguistics."
+23fd82c04852b74d655015ff0876e6c5defc6e61,Deep-based Ingredient Recognition for Cooking Recipe Retrieval,"Deep-based Ingredient Recognition for +Cooking Recipe Retrieval +Jingjing Chen +City University of HongKong +Kowloon, HongKong +Chong-Wah Ngo +City University of HongKong +Kowloon, HongKong"
236a4f38f79a4dcc2183e99b568f472cf45d27f4,Randomized Clustering Forests for Image Classification,"Randomized Clustering Forests for Image Classification Frank Moosmann, Student Member, IEEE, Eric Nowak, Student Member, IEEE, and @@ -15578,10 +54447,13 @@ Israel D. Gebru, Xavier Alameda-Pineda, Florence Forbes and Radu Horaud" Bidirectional PCA With Assembled Matrix Distance Metric for Image Recognition Wangmeng Zuo, David Zhang, Senior Member, IEEE, and Kuanquan Wang, Member, IEEE"
+237ec7e6d20025c32069e41f8007bb97931a7fc6,Learning real-time object detectors : probabilistic generative approaches,
2331df8ca9f29320dd3a33ce68a539953fa87ff5,Extended Isomap for Pattern Classification,"Extended Isomap for Pattern Classification Ming-Hsuan Yang Honda Fundamental Research Labs Mountain View, CA 94041"
+2333cf918f50ac2ae201a837166d310adf3a00b0,Optimally Training a Cascade Classifier,"Optimally Training a Cascade Classifier +Chunhua Shen, Peng Wang, and Anton van den Hengel"
23ba9e462151a4bf9dfc3be5d8b12dbcfb7fe4c3,Determining Mood from Facial Expressions,"CS 229 Project, Fall 2014 Matthew Wang Spencer Yee @@ -15602,6 +54474,15 @@ large number of pictures for a specific photo, which is becoming increasingly di storing photos digitally has been extremely common in the past decade. The possibilities re endless. II Data and Features"
+2311cdd241c118395a510776ec226aff7725ebc8,Hunting Nessie - Real-time abnormality detection from webcams,"Hunting Nessie – Real-Time Abnormality Detection from Webcams +Michael D. Breitenstein1 Helmut Grabner1 Luc Van Gool1,2 +Computer Vision Laboratory +ETH Zurich +ESAT-PSI / IBBT +KU Leuven"
+2340a8fa6d90741c53e659cd1e7ca86ff900aa55,Body Parts Dependent Joint Regressors for Human Pose Estimation in Still Images,"Body Parts Dependent Joint Regressors for +Human Pose Estimation in Still Images +Matthias Dantone, Juergen Gall, Member, IEEE Christian Leistner, and Luc Van Gool, Member, IEEE"
238fc68b2e0ef9f5ec043d081451902573992a03,Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition,"Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition Chuan-Xian Ren, Zhen Lei, Member, IEEE, Dao-Qing Dai, Member, IEEE, and Stan Z. Li, Fellow, IEEE @@ -15633,6 +54514,67 @@ http://eprints.gla.ac.uk/116592/ Deposited on: 20 April 2016 Enlighten – Research publications by members of the University of Glasgow http://eprints.gla.ac.uk"
+23ea8a34570342855611a78a4ff00ddd902e6123,Gradient-based global features and its application to image retargeting,"Gradient-based Global Features and Its Application +to Image Retargeting +Izumi Ito +Tokyo Institute of Technology Tokyo, 152-8552 Japan ++81-3-5734-2997"
+2312bc2d48a0f68bd5ab1b024d5726786455da3a,Learning Deep Context-Aware Features over Body and Latent Parts for Person Re-identification,"Learning Deep Context-aware Features over Body and Latent Parts +for Person Re-identification +Supplementary Materials +Dangwei Li1,2, Xiaotang Chen1,2, Zhang Zhang1,2, Kaiqi Huang1,2,3 +CRIPAC & NLPR, CASIA 2University of Chinese Academy of Sciences +CAS Center for Excellence in Brain Science and Intelligence Technology +{dangwei.li, xtchen, zzhang, +. Market1501 dataset +To further understand the results on Market1501 [8], we show mean Average Precision (mAP) and Rank-1 identification +rate between camera pairs in Figure 1 and Figure 2. Compared to the BOW methods, the proposed method improves mean +mAP and Rank-1 identification rate between camera pairs by 35.09% and 40.01% respectively. In addition, we show some +searching results with different query images in Figure 3. The dataset is challenging and the returned images have very similar +ppearances and some pedestrians have large backgrounds and occlusions. For the query image in first row of Figure 3, even +though the query person has large occlusions and some groundtruth images have large backgrounds, our proposed method +an still return the right results. This shows the effectiveness of our proposed method. +. CUHK03 dataset +CUHK03 [3] is one of the largest person re-identification datasets. It provides two types of pedestrian bounding boxes, +including detected and manually annotated. In this paragraph, we show the overall Cumulated Matching Characteristics +(CMC) on both detected and labeled datasets in Figure 4. For the GateSCNN [5] in Figure 4(a), we use the singe-query +results to approximate the single-shot results. The DGD [6] is trained using multiple datasets. In this paper, we use the"
+23a2b75c92123b3e7bbaf1d98e434845167fe259,Multimodal Biometrics for Identity Documents,"Forensic Science International 167 (2007) 154–159 +www.elsevier.com/locate/forsciint +Multimodal biometrics for identity documents ( +Damien Dessimoz a,*, Jonas Richiardi b, Christophe Champod a, Andrzej Drygajlo b +Institut de Police Scientifique, E´ cole des Sciences Criminelles, Universite´ de Lausanne, Switzerland +Speech Processing and Biometrics Group, Signal Processing Institute, E´ cole Polytechnique Fe´de´rale de Lausanne, Switzerland +Received 9 June 2006; accepted 14 June 2006 +Available online 4 August 2006"
+23c9fe37fa0474967be4cc6c7a310dcc87b86b72,Spatial Feature Interdependence Matrix (SFIM): A Robust Descriptor for Face Recognition,"Spatial Feature Interdependence Matrix (SFIM): +A Robust Descriptor for Face Recognition +Anbang Yao1 and Shan Yu2 +National Laboratory of Pattern Recognition, Institute of Automation, +Chinese Academy of Science, Beijing, 100090, China +National Institute for Research in Computer Science and Control, France"
+23b93f3b237481bd1d36941ca3312bb16f4beb58,Reconnaissance d'événements et d'actions à partir de la profondeur thermique 3D. (Event and action recognition from thermal and 3D depth Sensing),"Reconnaissance d’événements et d’actions à partir de la +profondeur thermique 3D +Adnan Al Alwani +To cite this version: +Adnan Al Alwani. Reconnaissance d’événements et d’actions à partir de la profondeur thermique +D. Vision par ordinateur et reconnaissance de formes [cs.CV]. Université de Caen Normandie, 2016. +Français. <tel-01418369> +HAL Id: tel-01418369 +https://hal.archives-ouvertes.fr/tel-01418369 +Submitted on 16 Dec 2016 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+235f4fad10a5d9e043759354a7cb94122a8f10fc,"Multi-perspective vehicle detection and tracking: Challenges, dataset, and metrics","Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016 +978-1-5090-1889-5/16/$31.00 ©2016 IEEE"
23120f9b39e59bbac4438bf4a8a7889431ae8adb,Improved RGB-D-T based face recognition,"Aalborg Universitet Improved RGB-D-T based Face Recognition Oliu Simon, Marc; Corneanu, Ciprian; Nasrollahi, Kamal; Guerrero, Sergio Escalera; @@ -15664,6 +54606,15 @@ Generic and attribute-specific deep representations for maritime vessels Berkan Solmaz*† , Erhan Gundogdu†, Veysel Yucesoy and Aykut Koc"
+23095c6fc92f41a86f93276d446cfc72c7ce7b23,Stereo-based Pedestrian Detection using Multiple Patterns,"HATTORI et al.: STEREO-BASED PEDESTRIAN DETECTION USING MULTI-PATTERNS +Stereo-based Pedestrian Detection using +Multiple Patterns +Research & Development Center, +TOSHIBA Corporation, JAPAN +Hiroshi Hattori +Akihito Seki +Manabu Nishiyama +Tomoki Watanabe"
23a8d02389805854cf41c9e5fa56c66ee4160ce3,Influence of low resolution of images on reliability of face detection and recognition,"Multimed Tools Appl DOI 10.1007/s11042-013-1568-8 Influence of low resolution of images on reliability @@ -15672,6 +54623,11 @@ Tomasz Marciniak· Agata Chmielewska· Radoslaw Weychan· Marianna Parzych· Adam Dabrowski © The Author(s) 2013. This article is published with open access at SpringerLink.com"
+23e881c9b791fd17e248b1fb4fc980710dd005d7,An Unbiased Temporal Representation for Video-Based Person Re-Identification,"AN UNBIASED TEMPORAL REPRESENTATION FOR VIDEO-BASED PERSON +RE-IDENTIFICATION +Xiu Zhang and Bir Bhanu +Center for Research in Intelligent Systems +University of California, Riverside, Riverside, CA 92521, USA"
23b37c2f803a2d4b701e2f39c5f623b2f3e14d8e,Modified Approaches on Face Recognition By using Multisensory Image,"Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology @@ -15683,6 +54639,16 @@ By using Multisensory Image S. Dhanarajan1, G. Michael2 Computer Science Department, Bharath University, India Computer Science Department, Bharath University, India"
+4f892475be26333ddf1b72c21f0c9c4ca129bd80,Mobile Cloud Computing for Biometric Applications,"Singidunum University +Belgrade, Serbia +Mobile Cloud Computing for Biometric Applications +Milos Stojmenovic +Department of Informatics and Computation"
+4f00f5fe9d762009f524fb97555088769b96328c,Eye Gaze Tracking System Using . Net,"IJSART - Volume 3 Issue 5 –MAY 2017 ISSN [ONLINE]: 2395-1052 +Eye Gaze Tracking System Using .Net +Madhu M Nayak1, Usha Rani J2, Anandhi G3 +Department of CSE +, 2, 3Assistant Professor,GSSIETW, Mysuru"
4f051022de100241e5a4ba8a7514db9167eabf6e,Face Parsing via a Fully-Convolutional Continuous CRF Neural Network,"Face Parsing via a Fully-Convolutional Continuous CRF Neural Network Lei Zhou, Zhi Liu, Senior Member, IEEE, Xiangjian He, Senior Member, IEEE"
@@ -15695,6 +54661,23 @@ Department : Computer Engineering Programme: Computer Engineering Supervisor: Prof. Dr. Muhittin GÖKMEN JUNE 2006"
+4f4c067e684252cf5549f60036829a89b2f35fc8,Sentic Avatar: Multimodal Affective Conversational Agent with Common Sense,"Sentic Avatar: Multimodal Affective +Conversational Agent with Common Sense +Erik Cambria1, Isabelle Hupont2, +Amir Hussain1, Eva Cerezo3, and Sandra Baldassarri3 +University of Stirling, Stirling, UK +Aragon Institute of Technology, Zaragoza, Spain +University of Zaragoza, Zaragoza, Spain +http://cs.stir.ac.uk/~eca/sentics"
+4f41f7a2f1f5eb5f26d47aeb168dbeb0f9ed453f,A Graph Transduction Game for Multi-target Tracking,"A Graph Transduction Game for Multi-target +Tracking +Tewodros Mulugeta Dagnew∗, Dalia Coppi†, Marcello Pelillo∗, Rita Cucchiara† +DAIS - Ca´ Foscari University +Venezia, Italy +Email: +DIEF - University of Modena and Reggio Emilia +Email: +Modena, Italy"
4fc936102e2b5247473ea2dd94c514e320375abb,Guess Where? Actor-Supervision for Spatiotemporal Action Localization,"Guess Where? Actor-Supervision for Spatiotemporal Action Localization Victor Escorcia1∗ Cuong D. Dao1 @@ -15702,14 +54685,176 @@ Mihir Jain3 KAUST1, University of Amsterdam2, Qualcomm Technologies, Inc.3 Bernard Ghanem1 Cees Snoek2∗"
+4f0aedbd0b5cb5939449da41579c93b98048fcdc,Robust classification using structured sparse representation,"Robust Classification using Structured Sparse Representation +Center for Imaging Science, Johns Hopkins University, Baltimore MD 21218, USA +Ehsan Elhamifar Ren´e Vidal"
+4f8bd3519a6e8a05db9e35b027c0c65c91d2ff62,Brain Oxytocin is a Main Regulator of Prosocial Behaviour - Link to Psychopathology,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+4ff7f5928f96ddc877b4b8675cc41cc08f4bd561,Recent Advance in Content-based Image Retrieval: A Literature Survey,"Recent Advance in Content-based Image +Retrieval: A Literature Survey +Wengang Zhou, Houqiang Li, and Qi Tian Fellow, IEEE"
4f6adc53798d9da26369bea5a0d91ed5e1314df2,Online Nonnegative Matrix Factorization with General Divergences,"IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. , NO. , 2016 Online Nonnegative Matrix Factorization with General Divergences Renbo Zhao, Member, IEEE, Vincent Y. F. Tan, Senior Member, IEEE, Huan Xu"
+4f46dba09e075b2e7dfae1ba2a71e8e21b46e88d,Genetic CNN,"Genetic CNN +Center for Imaging Science, The Johns Hopkins University, Baltimore, MD, USA +Lingxi Xie, Alan Yuille"
+4fc609df4e17b5854e3b7f4371e5f4192608eda5,3D Face Recognition Benchmarks on the Bosphorus Database with Focus on Facial Expressions,"D Face Recognition Benchmarks on the +Bosphorus Database with Focus on Facial +Expressions +Nes¸e Aly¨uz1, Berk G¨okberk2, Hamdi Dibeklio˘glu1, Arman Savran3, Albert Ali +Salah4, Lale Akarun1, B¨ulent Sankur3"
4f591e243a8f38ee3152300bbf42899ac5aae0a5,Understanding Higher-Order Shape via 3D Shape Attributes,"SUBMITTED TO TPAMI Understanding Higher-Order Shape via 3D Shape Attributes David F. Fouhey, Abhinav Gupta, Andrew Zisserman"
+4fec382efed4e08a36fafa3710b97f0b20de1ebe,Binarized Representation Entropy (bre) Regularization,"Published as a conference paper at ICLR 2018 +IMPROVING GAN TRAINING VIA +BINARIZED REPRESENTATION ENTROPY (BRE) +REGULARIZATION +Yanshuai Cao, Gavin Weiguang Ding, Kry Yik-Chau Lui, Ruitong Huang +Borealis AI +Canada"
+4fdeb5d59b218ecba0f72dc3c42f38a086417c0f,InformatIon theoretIc combInatIon of classIfIers wIth applIcatIon to face DetectIon,"InformatIon theoretIc combInatIon +of classIfIers wIth applIcatIon to face DetectIon +THÈSE NO 3951 (2007) +PRÉSENTÉE LE 23 NOvEMBRE 2007 +À LA FACULTÉ DES SCIENCES ET TECHNIQUES DE L'INGÉNIEUR +LABORATOIRE DE TRAITEMENT DES SIGNAUX 5 +PROGRAMME DOCTORAL EN INFORMATIQUE, COMMUNICATIONS ET INFORMATION +ÉCOLE POLyTECHNIQUE FÉDÉRALE DE LAUSANNE +POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES +Julien MEyNET +DEA signal, image, parole, télécoms, Institut national polytechnique de Grenoble, France +et de nationalité française +cceptée sur proposition du jury: +Prof. H. Bourlard, président du jury +Prof. J.-Ph. Thiran, directeur de thèse +Prof. A. Billard, rapporteur +Prof. H. Bunke, rapporteur +Prof. J. Kittler, rapporteur +Suisse"
+4f15b1e750007465024181dd002dfc6d1baa48c9,Face Recognition and Computer Graphics for Modelling,"Face Recognition and Computer Graphics for +Modelling Expressive Faces in 3D +Tufool Al-Nuaimi +Submitted to the Department of Electrical Engineering and Computer Science +in Partial Fulfillment of the Requirements for the Degree of +Master of Engineering in Electrical Engineering and Computer Science +t the Massachusetts Institute of Technology +May 26, 2006 +Copyright 2006 Tufool AI-Nuaimi. All rights reserved. +The author hereby grants to M.I.T. permission to reproduce and +distribute publicly paper and electronic copies of this thesis +nd to grant others the right to do so. +Author +Certified by_ +Accepted by_ _ +Tufool Al-Nuaimi +Department of Electrical Engineering and Computer Science +-Ma 26, 2006 +Judith Barry +Supervisor"
+4fa6a688f350831503d158f8f618c58d1e06bc5d,"Bootstrap, Review, Decode: Using Out-of-Domain Textual Data to Improve Image Captioning","Bootstrap, Review, Decode: Using Out-of-Domain Textual Data +to Improve Image Captioning +Wenhu Chen +RWTH Aachen +Aurelien Lucchi +ETH Zurich +Thomas Hofmann +ETH Zurich"
+4fb569af589d89f11d84d4b828459231345cc301,Exploring Linear Relationship in Feature Map Subspace for ConvNets Compression,"Exploring Linear Relationship in Feature Map +Subspace for ConvNets Compression +Dong Wang1, Lei Zhou1, Xueni Zhang1, Xiao Bai1, and Jun Zhou2 +Beihang University 2Griffith University"
+4f7e4b1b74955b54c434bdf76c47fb1e96db74e0,Naive Bayes Image Classification: Beyond Nearest Neighbors,"Naive Bayes Image Classification: +Beyond Nearest Neighbors +Radu Timofte1, Tinne Tuytelaars1, and Luc Van Gool1,2 +ESAT-VISICS /IBBT, Catholic University of Leuven, Belgium +D-ITET, ETH Zurich, Switzerland"
+4f10b81f822091ce2142e33f0578940da1e25ad3,"Indoor Mobile Robotics at Grima, PUC","Noname manuscript No. +(will be inserted by the editor) +Indoor Mobile Robotics at Grima, PUC +L. Caro · J. Correa · P. Espinace · D. +Maturana · R. Mitnik · S. Montabone · S. +Pszcz´o(cid:32)lkowski · D. Langdon · A. Araneda · +D. Mery · M. Torres · A. Soto +Received: date / Accepted: date"
+4f863543407143a62e1bb053d435a947886ba619,Distributed deep learning on edge-devices: Feasibility via adaptive compression,"Distributed deep learning on edge-devices: +feasibility via adaptive compression +Corentin Hardy +Technicolor, Inria +Rennes, France +Erwan Le Merrer +Technicolor +Rennes, France +Bruno Sericola +Inria +Rennes, France"
+4f5e5fea12c44a5be7107748320e6d66192b7acb,Automatic approach-avoidance tendencies as a candidate intermediate phenotype for depression: Associations with childhood trauma and the 5-HTTLPR transporter polymorphism,"RESEARCH ARTICLE +Automatic approach-avoidance tendencies as +candidate intermediate phenotype for +depression: Associations with childhood +trauma and the 5-HTTLPR transporter +polymorphism +Pascal Fleurkens1*, Agnes van Minnen1,2, Eni S. Becker1, Iris van Oostrom3, +Anne Speckens3, Mike Rinck1, Janna N. Vrijsen3,4 +Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands, +Psychotrauma Expertise Centrum (PSYTREC), Bilthoven, The Netherlands, 3 Department of Psychiatry, +Radboud University Medical Centre, Nijmegen, The Netherlands, 4 Pro Persona: Institution for Integrated +Mental Health Care, Nijmegen, The Netherlands"
+4fe0c6c83d998a0660bc5280c8ab6e61df9df887,Face Image Normalization and Expression/pose Validation for the Analysis of Machine Readable Travel Documents,"FACE IMAGE NORMALIZATION AND +EXPRESSION/POSE VALIDATION FOR THE +ANALYSIS OF MACHINE READABLE TRAVEL +DOCUMENTS +Markus Storer1, Martin Urschler1, Horst Bischof1, +Josef A. Birchbauer2"
+4f618cbf19917ce5b8703adbc14e15b0bf0d35cc,Multi-View Dynamic Facial Action Unit Detection,"Multi-View Dynamic Facial Action Unit Detection +Andr´es Romero +Juan Le´on +Pablo Arbel´aez +Universidad de los Andes"
+4fb11a58d5a3ffc0bb6d4ade334a366b4a431b02,The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings,
+4f606761ce65399ef4ff24cd503ec09cf53562e9,"A System View of the Recognition and Interpretation of Observed Human Shape, Pose and Action","Copyright © 2015 David W. Arathorn +A System View of the Recognition and Interpretation of +Observed Human Shape, Pose and Action +David W. Arathorn +Dept of Electrical and Computer Engineering +(formerly of Center for Computational Biology) +Montana State University-Bozeman +General Intelligence Corporation +Bozeman, MT"
+4fdbe95edb967bfc0b44f0fa291cd86b178fca2e,"Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation","Competitive Collaboration: Joint Unsupervised +Learning of Depth, Camera Motion, Optical +Flow and Motion Segmentation +Anurag Ranjan1 +Varun Jampani2 +Kihwan Kim 2 +Deqing Sun 2 +Jonas Wulff 1 +Michael J. Black1 +Max Planck Institute for Intelligent Systems +NVIDIA Research +{aranjan, jwulff, +{vjampani, kihwank,"
4f4f920eb43399d8d05b42808e45b56bdd36a929,A Novel Method for 3 D Image Segmentation with Fusion of Two Images using Color K-means Algorithm,"International Journal of Computer Applications (0975 – 8887) Volume 123 – No.4, August 2015 A Novel Method for 3D Image Segmentation with Fusion @@ -15728,11 +54873,48 @@ Md. Kamrul Hasan1, Christopher Pal1 and Sharon Moalem2 ´Ecole Polytechnique de Montr´eal, Universit´e de Montr´eal University of Toronto and Recognyz Systems Technologies lso focused on emotion recognition in the wild [9]."
+4f77c682f133d5010762556ebf512533524da071,Deep Learning of Appearance Models for Online Object Tracking,"Deep Learning of Appearance Models for Online +Object Tracking +Mengyao Zhai, Mehrsan Javan Roshtkhari, Greg Mori"
+4fec8a97d6d87713c5c00f369fc1373fba4377e3,Training Sources 3 D Normalized Pose Space 2 D Normalized Pose Space KD-Tree Input Image 2 D Pose Estimation 3 D Pose Reconstruction Retrieved 3 D Nearest Neighbours Motion Capture Dataset Annotated 2,"SUBMITTED TO COMPUTER VISION AND IMAGE UNDERSTANDING. +A Dual-Source Approach for 3D Human Pose +Estimation from a Single Image +Umar Iqbal*, Andreas Doering*, Hashim Yasin, Björn Krüger, Andreas Weber, and Juergen Gall"
+8d40150c7ec59daba7d1a34eba291ff2eac6388c,Overcoming Dataset Bias: An Unsupervised Domain Adaptation Approach,"Overcoming Dataset Bias: +An Unsupervised Domain Adaptation Approach +Boqing Gong +Dept. of Computer Science +U. of Southern California +Los Angeles, CA 90089 +Fei Sha +Dept. of Computer Science +U. of Southern California +Los Angeles, CA 90089 +Kristen Grauman +Dept. of Computer Science +U. of Texas at Austin +Austin, TX 78701"
8de06a584955f04f399c10f09f2eed77722f6b1c,Facial Landmarks Localization Estimation by Cascaded Boosted Regression,"Author manuscript, published in ""International Conference on Computer Vision Theory and Applications (VISAPP 2013) (2013)"""
8d4f0517eae232913bf27f516101a75da3249d15,Event-based Dynamic Face Detection and Tracking Based on Activity,"ARXIV SUBMISSION, MARCH 2018 Event-based Dynamic Face Detection and Tracking Based on Activity Gregor Lenz, Sio-Hoi Ieng and Ryad Benosman"
+8d19cfe643582fae03ce024efaf117d1efef5e58,A Robust Likelihood Function for 3D Human Pose Tracking,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. +The final version of record is available at http://dx.doi.org/10.1109/TIP.2014.2364113 +A Robust Likelihood Function for 3D Human Pose +Tracking +Weichen Zhang, Student Member, IEEE, Lifeng Shang, Member, IEEE, Antoni B. Chan, Member, IEEE,"
+8d97e0102b5d89c62e5c6697eeaaefc82b36c809,Bottom-up attention orienting in young children with autism.,"J Autism Dev Disord (2014) 44:664–673 +DOI 10.1007/s10803-013-1925-5 +O R I G I N A L P A P E R +Bottom-Up Attention Orienting in Young Children with Autism +Dima Amso • Sara Haas • Elena Tenenbaum • +Julie Markant • Stephen J. Sheinkopf +Published online: 1 September 2013 +Ó Springer Science+Business Media New York 2013"
+8d8afef13a8f6195d3b874231e5e767cf62f3c50,Deep Ranking for Person Re-Identification via Joint Representation Learning,"Deep Ranking for Person Re-identification via +Joint Representation Learning +Shi-Zhe Chen, Chun-Chao Guo, Student Member, IEEE, and Jian-Huang Lai, Senior Member, IEEE"
8de2dbe2b03be8a99628ffa000ac78f8b66a1028,Action Recognition in Videos,"´Ecole Nationale Sup´erieure dInformatique et de Math´ematiques Appliqu´ees de Grenoble INP Grenoble – ENSIMAG UFR Informatique et Math´ematiques Appliqu´ees de Grenoble @@ -15753,6 +54935,8 @@ Mme. Cordelia Schmid Tuteur ´ecole M. Augustin Lux M. Roger Mohr"
+8db9f32b0de29cfb7fd8e3d225be47b801cc9848,Vision-based deep execution monitoring,"Vision-based deep execution monitoring +Francesco Puja, Simone Grazioso, Antonio Tammaro, Valsmis Ntouskos, Marta Sanzari, Fiora Pirri"
8d3fbdb9783716c1832a0b7ab1da6390c2869c14,Discriminant Subspace Analysis for Uncertain Situation in Facial Recognition,"Discriminant Subspace Analysis for Uncertain Situation in Facial Recognition Pohsiang Tsai, Tich Phuoc Tran, Tom Hintz and Tony Jan @@ -15773,6 +54957,26 @@ features of the input data that make distinct pattern classes separable (Jan, 20 there exist a number of different feature extraction methods. The most common feature extraction methods are subspace analysis methods such as principle component analysis (PCA) (Kirby & Sirovich, 1990) (Jolliffe, 1986) (Turk & Pentland, 1991b), kernel principle"
+8d09c8c6b636ef70633a3f1bb8ff6b4d4136b5cf,3D Twins Expression Challenge,"D Twins Expression Challenge +Vipin Vijayan, Kevin Bowyer, Patrick Flynn +Department of Computer Science and Engineering, +University of Notre Dame. +84 Fitzpatrick Hall, +Notre Dame, IN 46556, USA. +{vvijayan, kwb, +. Introduction +We describe the 3D Twins Expression Challenge (“3D +TEC”) problem in the area of 3D face recognition. The +supporting dataset contains 3D scans of pairs of identical +twins taken with two different facial expressions, neutral +nd smiling. The dataset is smaller than the FRGC v2 [1] +dataset by approximately a factor of ten, but is still more +hallenging than the FRGC v2 dataset due to it containing +twins with different expressions. This challenge problem +will help to push the frontiers of 3D face recognition. +Three dimensional face recognition is an active research +topic in biometrics [2, 3]. While 2D pictures can be cap- +tured quickly, non-intrusively, and easily by widely avail-"
8d42a24d570ad8f1e869a665da855628fcb1378f,An Empirical Study of Context in Object Detection,"CVPR 2009 Submission #987. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. An Empirical Study of Context in Object Detection Anonymous CVPR submission @@ -15782,11 +54986,62 @@ Network Sneha Thakur, Ligendra Verma CSE Department,CSVTU RIT, Raipur, Chhattisgarh , INDIA"
+8de7c496c1dac3be5fa55de72867325153b119bd,Robust Face Recognition using Key-point Descriptors,"Robust Face Recognition using Key-point Descriptors +Soeren Klemm, Yasmina Andreu, Pedro Henriquez and Bogdan J. Matuszewski +Robotics and Computer Vision Research Laboratory, School of Computing Engineering and Physical Sciences, +University of Central Lancashire, Preston, U.K. +Keywords: +Face Recognition, SIFT, SURF, ORB, Feature Matching, Face Occlusions."
8d384e8c45a429f5c5f6628e8ba0d73c60a51a89,Temporal Dynamic Graph LSTM for Action-Driven Video Object Detection,"Temporal Dynamic Graph LSTM for Action-driven Video Object Detection Yuan Yuan1 Xiaodan Liang2 Xiaolong Wang2 Dit-Yan Yeung1 Abhinav Gupta2 The Hong Kong University of Science and Technology 2 Carneige Mellon University"
+8d9067da4ba5c57643ee7a84cd5c5d5674384937,Sorting out Lipschitz function approximation,"SORTING OUT LIPSCHITZ FUNCTION APPROXIMATION +Cem Anil ∗ +James Lucas∗ +Roger Grosse +University of Toronto; Vector Institute +{cemanil, jlucas,"
+8d559aeefb291d5b017c263a49f38e8a28439344,Visually-Driven Semantic Augmentation for Zero-Shot Learning,"VDSA: VISUALLY-DRIVEN SEMANTIC AUGMENTATION FOR ZSL +Visually-Driven Semantic Augmentation for +Zero-Shot Learning +Abhinaba Roy1,2 +Jacopo Cavazza1 +Vittorio Murino1,3 +Pattern Analysis and Computer Vision +Istituto Italiano di Tecnologia +Genova, Italy +Department of Naval, Electrical, +Electronic and Telecommunications +Engineering +University of Genova, Italy +Department of Computer Science +University of Verona, Italy"
+8d6d0fdf4811bc9572326d12a7edbbba59d2a4cc,SchiNet: Automatic Estimation of Symptoms of Schizophrenia from Facial Behaviour Analysis,"SchiNet: Automatic Estimation of Symptoms of +Schizophrenia from Facial Behaviour Analysis +Mina Bishay, Petar Palasek, Stefan Priebe, and Ioannis Patras"
+8d4f2339fcadc2d1ef2126a11dce08ce7cb75bdd,Subspace Clustering via Optimal Direction Search,"Subspace Clustering via Optimal Direction Search +Mostafa Rahmani, Student Member, IEEE and George K. Atia, Member, IEEE"
+8d3114a3236ec9adabcf0c40613a23f00c272a1c,From 3D Point Clouds to Pose-Normalised Depth Maps,"Int J Comput Vis (2010) 89: 152–176 +DOI 10.1007/s11263-009-0297-y +From 3D Point Clouds to Pose-Normalised Depth Maps +Nick Pears · Tom Heseltine · Marcelo Romero +Received: 30 September 2008 / Accepted: 14 September 2009 / Published online: 25 September 2009 +© Springer Science+Business Media, LLC 2009"
8d1adf0ac74e901a94f05eca2f684528129a630a,Facial Expression Recognition Using Facial Movement Features,"Facial Expression Recognition Using Facial Movement Features"
+8db43d306a70e23e2a0e6eb2fda60f14b73f65d0,Multi-Commodity Network Flow for Tracking Multiple People,"Multi-Commodity Network Flow +for Tracking Multiple People +Horesh Ben Shitrit, J´erˆome Berclaz, Franc¸ois Fleuret, and Pascal Fua, Fellow, IEEE"
+8dfdfcc3f34263779871d023fad973f4a1966ec0,Internet of vehicles in big data era,"Internet of Vehicles in Big Data Era +Wenchao Xu, Haibo Zhou, Member, IEEE, Nan Cheng, Member, IEEE, Feng Lyu, Weisen Shi, Jiayin Chen, +Xuemin (Sherman) Shen, Fellow, IEEE"
+8def62fd86b5ea0a41fd9f892bd95b01bf072e88,A hybrid approach to content based image retrieval using visual features and textual queries,"Proceedings of the 2013 International Conference on Information, Operations Management and Statistics (ICIOMS2013), +Kuala Lumpur, Malaysia, September 1-3, 2013 +A Hybrid Approach to Content-based Image Retrieval +Smarajit Bosea, Amita Pala*, Jhimli Mallickb , Sunil Kumarc +Applied Statistics Division, Indian Statistical Institute, Kolkata, India +TechBLA Solutions, Kolkata, India +ETH, Zurich, Switzerland"
8d646ac6e5473398d668c1e35e3daa964d9eb0f6,Memory-Efficient Global Refinement of Decision-Tree Ensembles and its Application to Face Alignment,"MEMORY-EFFICIENT GLOBAL REFINEMENT OF DECISION-TREE ENSEMBLES AND ITS APPLICATION TO FACE ALIGNMENT Nenad Markuˇs† @@ -15834,9 +55089,56 @@ Sylvain Meignier7, Jean-Marc Odobez1 Idiap Research Institute & EPFL, 2 LIMSI, CNRS, Univ. Paris-Sud, Université Paris-Saclay, CNRS, Irisa & Inria Rennes, 4 PUC de Minas Gerais, Belo Horizonte, 5 Universitat Politècnica de Catalunya, 6 University of Vigo, 7 LIUM, University of Maine"
+8d7a55d184659ac97d02061a660ae4e30604185b,Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation,"Penalizing Top Performers: Conservative Loss +for Semantic Segmentation Adaptation +Xinge Zhu1, Hui Zhou2, Ceyuan Yang1, Jianping Shi2, Dahua Lin1 +CUHK-SenseTime Joint Lab, CUHK +SenseTime Research"
+8df3bef321cd1b259cf6fb1ef264a2e885610044,Interactively Learning Visually Grounded Word Meanings from a Human Tutor,"Proceedings of the 5th Workshop on Vision and Language, pages 48–53, +Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
+8d156f3b4f1ad5d041ae9f50a0b879e25c80749e,A New Approach for Face Recognition and Age Classification using LDP,"International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June 2013 +ISSN 2229-5518 +A New Approach for Face Recognition and Age +Classification using LDP +M Rama Bai +Professor, Dept of CSE, M.G.I.T, JNTUH, Hyderabad, Andhra Pradesh, INDIA"
153f5ad54dd101f7f9c2ae17e96c69fe84aa9de4,Overview of algorithms for face detection and tracking,"Overview of algorithms for face detection and tracking Nenad Markuˇs"
+15b44a1c3602385b6cf3eeb049cb2d6c12bb7d74,Automatic semantic annotation of images based on Web data,"010 Sixth International +Conference +on Information +Assurance +nd Security +Automatic +semantic annotation +of images based on Web data +Guiguang Ding +School of Software +University +of Tsinghua +Beijing, +China +edu.cn +School of Software +University +Beijing, +China +of Tsinghua"
+155ce5d596c7b525110ca24db11e47d521b487ce,STC: A Simple to Complex Framework for Weakly-Supervised Semantic Segmentation,"STC: A Simple to Complex Framework for +Weakly-supervised Semantic Segmentation +Yunchao Wei, Xiaodan Liang, Yunpeng Chen, Xiaohui Shen, Ming-Ming Cheng, Jiashi Feng, Yao Zhao, +Senior Member, IEEE and Shuicheng Yan Senior Member, IEEE"
+15c8443f8d9f1f6537fa8ff470ac407bf2185b0e,Learning Binary Code Representations for Effective and Efficient Image Retrieval,
+1550c3835822843a02b2144cef8abc534441f5d4,Human Pose Classification within the Context of Near-IR Imagery Tracking,"Human Pose Classification within the Context of Near-IR +Imagery Tracking +Jiwan Han, Anna Gaszczak, Ryszard Maciol, Stuart E. Barnes, Toby P. Breckon +School of Engineering, Cranfield University, Bedfordshire, UK"
+15696370ff33b6e5a81bf5131d80065d6e59804f,Semantically guided location recognition for outdoors scenes,"Semantically Guided Location Recognition for Outdoors Scenes +Arsalan Mousavian and Jana Koˇseck´a and Jyh-Ming Lien"
+15cf11ddfc046b2ed2766c375e8ad067baaf8347,Active Pedestrian Safety by Automatic Braking and Evasive Steering,"Active Pedestrian Safety +y Automatic Braking and Evasive Steering +C. Keller, T. Dang, H. Fritz, A. Joos, C. Rabe and D. M. Gavrila"
15cd05baa849ab058b99a966c54d2f0bf82e7885,Structured Sparse Subspace Clustering: A unified optimization framework,"Structured Sparse Subspace Clustering: A Unified Optimization Framework Chun-Guang Li1, René Vidal2 SICE, Beijing University of Posts and Telecommunications. 2Center for Imaging Science, Johns Hopkins University. @@ -15860,10 +55162,168 @@ hand, appealing because the first step can be solved using convex optimiza-" 15136c2f94fd29fc1cb6bedc8c1831b7002930a6,Deep Learning Architectures for Face Recognition in Video Surveillance,"Deep Learning Architectures for Face Recognition in Video Surveillance Saman Bashbaghi, Eric Granger, Robert Sabourin and Mostafa Parchami"
+15623fe8875a36cac5283ff2f08cd50998599725,Semantic Instance Segmentation for Autonomous Driving,"Semantic Instance Segmentation for Autonomous Driving +Bert De Brabandere +Davy Neven +ESAT-PSI, KU Leuven +Luc Van Gool"
+159b52158512481df7684c341401efbdbc5d8f02,Object Detection with Active Sample Harvesting,"Object Detection +with Active Sample Harvesting +Thèse no 7312 +présentée le 5 Octobre 2016 +à la Faculté des Sciences et Techniques de l'Ingénieur +Laboratoire LIDIAP (Idiap Research Institute) +École Polytechnique Fédérale de Lausanne +pour l'obtention du grade de Docteur ès Sciences +Olivier Canévet +devant le jury composé de : +Prof. Pascal Frossard, président du jury +Prof. Gilles Blanchard, rapporteur +Prof. Raphael Sznitman, rapporteur +Dr Mathieu Salzmann, rapporteur +Dr François Fleuret, directeur de thèse +Lausanne, EPFL, 2016"
+15e024d8f5625ec03c8ac592fbc093687cfb5f02,The Visual Object Tracking VOT2013 Challenge Results,"The Visual Object Tracking VOT2013 challenge results +Matej Kristan a +Luka ˇCehovin a +Roman Pflugfelder b +Georg Nebehay b +Aleˇs Leonardis c +Gustavo Fernandez b +Jiri Matas d +Tom´aˇs Voj´ıˇr d +Fatih Porikli e +Adam Gatt f +Ahmad Khajenezhad g +Alfredo Petrosino i +Chee Seng Chan m +Dorothy Monekosso n +Jin Gao q +Ahmed Salahledin h +Anthony Milton j +CherKeng Heng l +Jingjing Xiao c"
+15605634feb1a5770182a8f2c3515daf102ed463,Real-time human pose recognition in parts from single depth images,"Real-Time Human Pose Recognition in Parts from Single Depth Images +Mark Finocchio +Jamie Shotton +Andrew Fitzgibbon +Toby Sharp +Andrew Blake +Richard Moore +Mat Cook +Alex Kipman +Microsoft Research Cambridge & Xbox Incubation"
+15f57134b42638cbd57d0d8c4437e8b6b6a8bac4,Learning Visual Reasoning Without Strong Priors,"Learning Visual Reasoning Without Strong Priors +Ethan Perez12, Harm de Vries1, Florian Strub3, +Vincent Dumoulin1, Aaron Courville14 +MILA, Universit´e of Montr´eal, Canada; 2Rice University, U.S.A. +Univ. Lille, CNRS, Centrale Lille, Inria, UMR 9189 CRIStAL France +CIFAR Fellow, Canada"
153e5cddb79ac31154737b3e025b4fb639b3c9e7,Active Dictionary Learning in Sparse Representation Based Classification,"PREPRINT SUBMITTED TO IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Active Dictionary Learning in Sparse Representation Based Classification Jin Xu, Haibo He, Senior Member, IEEE, and Hong Man, Senior Member, IEEE"
+15e6c983e74dcf70d8a557b75bdc172e36692191,VSO: Visual Semantic Odometry,"VSO: Visual Semantic Odometry +Konstantinos-Nektarios Lianos 1,⋆, +Johannes L. Sch¨onberger 2, +Marc Pollefeys 2,3, Torsten Sattler 2 +Geomagical Labs, Inc., USA 3 Microsoft, Switzerland +Department of Computer Science, ETH Z¨urich, Switzerland"
+15df73918e084a146cd215b839a3eec1cc813a78,Projection Peak Analysis for Rapid Eye Localization,"PROJECTION PEAK ANALYSIS FOR RAPID EYE LOCALIZATION +Research Center of Intelligent Robotics, Shanghai Jiaotong University, Shanghai, 200240, China +Jingwen Dai, Dan Liu and Jianbo Su +Keywords: +Eye localization, Threshold, Segmentation, Projection peak."
+1542b8a1805d73a755d4b2eb402c5c861e6acd02,PMCTrack: Delivering Performance Monitoring Counter Support to the OS Scheduler,"PMCTrack: Delivering performance +monitoring counter support to the OS +scheduler +J. C. Saez1, A. Pousa2, R. Rodr´ıguez-Rodr´ıguez1, F. Castro1, +M. Prieto-Matias1 +ArTeCS Group, Facultad de Inform´atica, Complutense University of Madrid +III-LIDI, Facultad de Inform´atica, National University of La Plata +Email: +Hardware performance monitoring counters (PMCs) have proven effective in +haracterizing application performance. Because PMCs can only be accessed +directly at the OS privilege level, kernel-level tools must be developed to enable +the end user and userspace programs to access PMCs. A large body of work +has demonstrated that the OS can perform effective runtime optimizations in +multicore systems by leveraging performance-counter data. Special attention has +een paid to optimizations in the OS scheduler. While existing performance +monitoring tools greatly simplify the collection of PMC application data from +userspace, they do not provide an architecture-agnostic kernel-level mechanism +that is capable of exposing high-level PMC metrics to OS components, such as +the scheduler. As a result, the implementation of PMC-based OS scheduling +schemes is typically tied to specific processor models."
+1548cea1fa9be7a23d4d1e38086336913d501e44,Semantic 3D Reconstruction of Heads Supplementary Material,"Semantic 3D Reconstruction of Heads +Supplementary Material +Fabio Maninchedda1, Christian H¨ane2,(cid:63), Bastien Jacquet3,(cid:63), +Ama¨el Delaunoy(cid:63), Marc Pollefeys1,4 +ETH Zurich +UC Berkeley +Kitware SAS +Microsoft +Fig. 1: From left to right: Input image; Input labels and depth; Depth map fusion +(TV-Flux fusion from [9]); Statistical model of [7] fitted into our raw input data; +Our semantic reconstruction; Our result skin class only; Our model textured. +(cid:63) Work done while authors were at the Department of Computer Science, ETH Z¨urich"
+15d1326f054f4fadea463f217ce54bad6908705a,Sensor fusion in smart camera networks for Ambient Intelligence - Report on PhD Thesis and Defense,"Sensor fusion in smart camera networks for ambient +intelligence +Maatta, T.T. +0.6100/IR755363 +Published: 01/01/2013 +Document Version +Publisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers) +Please check the document version of this publication: +• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences +etween the submitted version and the official published version of record. People interested in the research are advised to contact the +uthor for the final version of the publication, or visit the DOI to the publisher's website. +• The final author version and the galley proof are versions of the publication after peer review. +• The final published version features the final layout of the paper including the volume, issue and page numbers. +Link to publication +Citation for published version (APA): +Maatta, T. T. (2013). Sensor fusion in smart camera networks for ambient intelligence Eindhoven: Technische +Universiteit Eindhoven DOI: 10.6100/IR755363 +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights."
+159b87e6e68b18f4daa3505bfc415be9b21a7db6,Tracking The Invisible Man - Hidden-object Detection for Complex Visual Scene Understanding,
+15ec1faddbd61a9d50925c7b9b0c76642abe94e7,Efficient Techniques for Recovering 2d Human Body Poses from Images Dissertation Efficient Techniques for Recovering 2d Human Body Poses from Images Second Reader,"EFFICIENT TECHNIQUES FOR RECOVERING 2D +HUMAN BODY POSES FROM IMAGES +TAI-PENG TIAN +Dissertation submitted in partial fulfillment +of the requirements for the degree of +Doctor of Philosophy +BOSTON +UNIVERSITY"
+150326137da214210b46e0b7f22e30f7e6529006,Pedestrian Detection at Warp Speed: Exceeding 500 Detections per Second,"Pedestrian Detection at Warp Speed: Exceeding 500 Detections per Second +Floris De Smedt∗, Kristof Van Beeck∗, Tinne Tuytelaars and Toon Goedem´e +EAVISE, ESAT-PSI-VISICS, KU Leuven, Belgium"
+15ebec3796a2e23d31c8c8ddf6d21555be6eadc6,Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks,"Recent Advances in Object Detection in the Age +of Deep Convolutional Neural Networks +Shivang Agarwal(∗ +,1), Jean Ogier du Terrail(∗ +,1,2), Fr´ed´eric Jurie(1) +(∗) equal contribution +(1)Normandie Univ, UNICAEN, ENSICAEN, CNRS +(2)Safran Electronics and Defense +September 11, 2018"
+156b194d0cee545337524bd993ae640ed227b79e,Radon Transform and Symbolic Linear Discriminant Analysis Based 3 D Face Recognition Using Knn and Svm,"ISSN 2320 - 2602 +Volume 2, No.12, December 2013 +P. S. Hiremath et al., International Journal of Advances in Computer Science and Technology, 2(12), December 2013, 267-274 +International Journal of Advances in Computer Science and Technology +Available Online at http://warse.org/pdfs/2013/ijacst022122013.pdf +RADON TRANSFORM AND SYMBOLIC LINEAR DISCRIMINANT +ANALYSIS BASED 3D FACE RECOGNITION USING KNN AND SVM +P. S. Hiremath, Manjunatha Hiremath1 +Department of Computer Science, +Gulbarga University, Gulbarga, Karnataka, India"
+1565bf91f8fdfe5f5168a5050b1418debc662151,One-pass Person Re-identification by Sketch Online Discriminant Analysis,"One-pass Person Re-identification by +Sketch Online Discriminant Analysis +Wei-Hong Li, Zhuowei Zhong, and Wei-Shi Zheng∗"
+1546b65e5e95543cf2dc0ead92b758fb31a5f4d6,An inexpensive monocular vision system for tracking humans in industrial environments,"An Inexpensive Monocular Vision System for +Tracking Humans in Industrial Environments +Centre for Applied Autonomous Sensor Systems (AASS), ¨Orebro University, Sweden +Rafael Mosberger and Henrik Andreasson"
157eb982da8fe1da4c9e07b4d89f2e806ae4ceb6,Connecting the dots in multi-class classification: From nearest subspace to collaborative representation,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Connecting the Dots in Multi-Class Classification: From @@ -15871,6 +55331,10 @@ Nearest Subspace to Collaborative Representation Chi, Y.; Porikli, F. TR2012-043 June 2012"
+15f51d51c05c22e1dca3a40fb1af46941d91f598,Modeling Visual Compatibility through Hierarchical Mid-level Elements,"Modeling Visual Compatibility through +Hierarchical Mid-level Elements +Jose Oramas M., Tinne Tuytelaars +KU Leuven, ESAT-PSI, iMinds"
15e0b9ba3389a7394c6a1d267b6e06f8758ab82b,The OU-ISIR Gait Database comprising the Large Population Dataset with Age and performance evaluation of age estimation,"Xu et al. IPSJ Transactions on Computer Vision and Applications (2017) 9:24 DOI 10.1186/s41074-017-0035-2 @@ -15882,7 +55346,25 @@ The OU-ISIR Gait Database comprising the Large Population Dataset with Age and performance evaluation of age estimation Chi Xu1,2, Yasushi Makihara2*, Gakuto Ogi2, Xiang Li1,2, Yasushi Yagi2 and Jianfeng Lu1"
+155033f2f096934042d659d10912ef29aa1cdbd1,Visual classification of coarse vehicle orientation using Histogram of Oriented Gradients features,"Visual Classification of Coarse Vehicle Orientation +using Histogram of Oriented Gradients Features +Paul E. Rybski and Daniel Huber and Daniel D. Morris and Regis Hoffman"
+158a8037ce1c577620550da385d2275a31b9ccaa,Combining motion detection and hierarchical particle filter tracking in a multi-player sports environment,"Combining motion detection and hierarchical particle filter tracking +in a multi-player sports environment +Robbie Vos, Willie Brink +Department of Mathematical Sciences +University of Stellenbosch, South Africa"
+157d2c6dd8c9999b251099ef4211cff8030ae486,Invariance properties of Gabor filter-based features-overview and applications,"Invariance Properties of Gabor Filter Based +Features – Overview and Applications +Joni-Kristian Kamarainen∗, Ville Kyrki, Member, IEEE, Heikki K¨alvi¨ainen, Member, IEEE"
15aa6c457678e25f6bc0e818e5fc39e42dd8e533,Conditional Image Generation for Learning the Structure of Visual Objects,
+15c7fe9c9154113f9824f68ca1870564600b66d6,"EICHNER, FERRARI: BETTER APPEARANCE MODELS FOR PICTORIAL STRUCTURES 1 Better appearance models for pictorial structures","EICHNER, FERRARI: BETTER APPEARANCE MODELS FOR PICTORIAL STRUCTURES +Better appearance models +for pictorial structures +Marcin Eichner +Vittorio Ferrari +Computer Vision Laboratory +Zürich, Switzerland"
15cf1f17aeba62cd834116b770f173b0aa614bf4,Facial Expression Recognition using Neural Network with Regularized Backpropagation Algorithm,"International Journal of Computer Applications (0975 – 8887) Volume 77 – No.5, September 2013 Facial Expression Recognition using Neural Network with @@ -15909,7 +55391,115 @@ Anonymous Anonymous Anonymous"
15728d6fd5c9fc20b40364b733228caf63558c31,Expanding the Breadth and Detail of Object Recognition By,(cid:13) 2013 Ian N. Endres
+15667845de2531b59736d866531728a771500d34,3-D Face Recognition Using Local Appearance-Based Models,"[4] L. Lee and W. E. L. Grimson, “Gait analysis for recognition and classi- +fication,” in Proc. IEEE Int. Conf. Automatic Face and Gesture Recog- +nition, Washington, DC, May 2002, pp. 734–742. +[5] L. Wang, H. Ning, W. Hu, and T. Tan, “Gait recognition based on pro- +rustes shape analysis,” in Proc. Int. Conf. Image Processing, 2002, pp. +33–436. +[6] L. Wang, H. Ning, T. Tan, and W. Hu, “Fusion of static and dynamic +ody biometrics for gait recognition,” IEEE Trans. Circuits Syst. Video +Technol., vol. 14, no. 2, pp. 149–158, Feb. 2004. +[7] D. Cunado, M. S. Nixon, and J. N. Carter, “Automatic extraction and +description of human gait models for recognition purposes,” in Comput. +Vis. Image Understand., Apr. 2003, vol. 90, pp. 1–41. +[8] P. J. Phillips, S. Sarkar, I. R. Vega, P. Grother, and K. W. Bowyer, +“The gait identification challenge problem: Data sets and baseline al- +gorithm,” in Proc. Int. Conf. Pattern Recognition, Quebec City, QC, +Canada, Aug. 2002, vol. 1, pp. 385–388. +[9] S. Sarkar, P. J. Phillips, Z. Liu, I. R. Vega, P. Grother, and K. W. +Bowyer, “The human ID gait challenge problem: Data sets, perfor- +mance, and analysis,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, +no. 2, pp. 162–177, Feb. 2005."
+15e6e1551ce9a4094c57db70985e420e57c6997a,Asymmetric cross-view dictionary learning for person re-identification,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE +ICASSP 2017"
+155448563c354b01d12610b5864b511644cfeb27,Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets,"Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets +Takuya Narihira +Sony / ICSI +Damian Borth +DFKI / ICSI +Stella X. Yu +UC Berkeley / ICSI +Karl Ni +In-Q-Tel +Trevor Darrell +UC Berkeley / ICSI"
+15292f380f5996f539f4d5e93dba3082d53338fb,Feature Space Optimization for Semantic Video Segmentation,"Feature Space Optimization for Semantic Video Segmentation +Abhijit Kundu∗ +Georgia Tech +Vibhav Vineet∗ +Vladlen Koltun +Intel Labs +Intel Labs +Figure 1. Semantic video segmentation on the Cityscapes dataset [6]. Input frame on the left, semantic segmentation computed by our +pproach on the right."
+157ee7498320119f6f5da2d9c592448986edea7e,Learning Multiple Non-linear Sub-spaces Using K-RBMs,"Learning Multiple Non-Linear Sub-Spaces using K-RBMs +Siddhartha Chandra1, Shailesh Kumar2 & C. V. Jawahar3 +CVIT, IIIT Hyderabad, 2Google, Hyderabad"
153c8715f491272b06dc93add038fae62846f498,On Clustering Images of Objects,"(cid:13) Copyright by Jongwoo Lim, 2005"
+12dfc8d4062b83a0b824b1676533482f14e4978c,Cutting Edge: Soft Correspondences in Multimodal Scene Parsing,"Cutting Edge: Soft Correspondences in Multimodal Scene Parsing +Sarah Taghavi Namin1,2 Mohammad Najafi1,2 Mathieu Salzmann2,3 +Australian National University (ANU) +Lars Petersson1,2 +CVLab, EPFL, Switzerland +NICTA∗ +{sarah.namin, mohammad.najafi,"
+12919f98aecdd74c1e0db56cba13d107553e421b,Temporal Model Adaptation for Person Re-Identification: Supplementary Material,"Temporal Model Adaptation for +Person Re-Identification: +Supplementary Material +Niki Martinel1,3, Abir Das2, +Christian Micheloni1, and Amit K. Roy-Chowdhury3 +University of Udine, 33100 Udine, Italy +University of Massatchussets Lowell, 01852 Lowell, MA, USA +University of California Riverside, 92507 Riverside, CA, USA"
+123bc74a006a75fefcdd9995cbdc1c6c64c8bed6,Socially Constrained Structural Learning for Groups Detection in Crowd,"Socially Constrained Structural Learning for +Groups Detection in Crowd +Francesco Solera, Simone Calderara, Member, IEEE, and Rita Cucchiara, Fellow, IEEE"
+124476c2815bbfb523c77943c74356f94f79b580,Recognition of Faces in Unconstrained Environments: A Comparative Study,"Hindawi Publishing Corporation +EURASIP Journal on Advances in Signal Processing +Volume 2009, Article ID 184617, 19 pages +doi:10.1155/2009/184617 +Research Article +Recognition of Faces in Unconstrained Environments: +A Comparative Study +Javier Ruiz-del-Solar, Rodrigo Verschae, and Mauricio Correa +Department of Electrical Engineering, Universidad de Chile, Avenida Tupper 2007, 837-0451 Santiago, Chile +Correspondence should be addressed to Javier Ruiz-del-Solar, +Received 10 October 2008; Revised 31 January 2009; Accepted 13 March 2009 +Recommended by Kevin Bowyer +The aim of this work is to carry out a comparative study of face recognition methods that are suitable to work in unconstrained +environments. The analyzed methods are selected by considering their performance in former comparative studies, in addition to +e real-time, to require just one image per person, and to be fully online. In the study two local-matching methods, histograms +of LBP features and Gabor Jet descriptors, one holistic method, generalized PCA, and two image-matching methods, SIFT- +ased and ERCF-based, are analyzed. The methods are compared using the FERET, LFW, UCHFaceHRI, and FRGC databases, +which allows evaluating them in real-world conditions that include variations in scale, pose, lighting, focus, resolution, facial +expression, accessories, makeup, occlusions, background and photographic quality. Main conclusions of this study are: there is +large dependence of the methods on the amount of face and background information that is included in the face’s images,"
+12c7ecbfd714c160d2a6bb9cf03fa8b88e8da62b,Impaired Recognition of Basic Emotions from Facial Expressions in Young People with Autism Spectrum Disorder: Assessing the Importance of Expression Intensity.,"Griffiths, S. L., Jarrold, C., Penton-Voak, I., Woods, A., Skinner, A., & +Munafo, M. (2017). Impaired Recognition of Basic Emotions from Facial +Expressions in Young People with Autism Spectrum Disorder: Assessing the +Importance of Expression Intensity. Journal of Autism and Developmental +Disorders. DOI: 10.1007/s10803-017-3091-7 +Publisher's PDF, also known as Version of record +License (if available): +CC BY +Link to published version (if available): +0.1007/s10803-017-3091-7 +Link to publication record in Explore Bristol Research +PDF-document +This is the final published version of the article (version of record). It first appeared online via Springer at +http://link.springer.com/article/10.1007%2Fs10803-017-3091-7. Please refer to any applicable terms of use of +the publisher. +University of Bristol - Explore Bristol Research +General rights +This document is made available in accordance with publisher policies. Please cite only the published +version using the reference above. Full terms of use are available: +http://www.bristol.ac.uk/pure/about/ebr-terms.html"
+12d62f1360587fdecee728e6c509acc378f38dc9,Feature Affinity based Pseudo Labeling for Semi-supervised Person Re-identification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Feature Affinity based Pseudo Labeling for +Semi-supervised Person Re-identification +Guodong Ding, Shanshan Zhang, Salman Khan, Zhenmin Tang, Jian Zhang, Senior Member, IEEE and Fatih +Porikli, Fellow, IEEE"
122ee00cc25c0137cab2c510494cee98bd504e9f,The Application of Active Appearance Models to Comprehensive Face Analysis Technical Report,"The Application of Active Appearance Models to Comprehensive Face Analysis @@ -15917,24 +55507,130 @@ Technical Report Simon Kriegel TU M¨unchen April 5, 2007"
+12ebb51d50f704b5d0a8d821e90dd336175ec8aa,TUHOI: Trento Universal Human Object Interaction Dataset,"Proceedings of the 25th International Conference on Computational Linguistics, pages 17–24, +Dublin, Ireland, August 23-29 2014."
+127759fc41d62b516298fff2706dfcc754ff1ee8,Fabrik: An Online Collaborative Neural Network Editor,"FABRIK: AN ONLINE COLLABORATIVE NEURAL NETWORK EDITOR +Utsav Garg 1 Viraj Prabhu 2 Deshraj Yadav 2 Ram Ramrakhya 3 Harsh Agrawal 2 Dhruv Batra 2 4 +fabrik.cloudcv.org"
+12417ed7ae81fb4e6c07f501ace9ea463349481b,Pairwise Augmented GANs with Adversarial Reconstruction Loss,"PAIRWISE AUGMENTED GANS WITH +ADVERSARIAL RECONSTRUCTION LOSS +Aibek Alanov1,2,3∗, Max Kochurov1,2∗, Daniil Yashkov5, Dmitry Vetrov1,3,4 +Samsung AI Center in Moscow +Skolkovo Institute of Science and Technology +National Research University Higher School of Economics +Joint Samsung-HSE lab +5Federal Research Center ""Informatics and Management"" of the Russian Academy of Sciences"
+129a6daa54a7334930b6413875b6154acef3922a,Data-Driven Synthesis of Cartoon Faces Using Different Styles,"Data-Driven Synthesis of Cartoon +Faces Using Different Styles +Yong Zhang, Weiming Dong, Member, IEEE, Chongyang Ma, Xing Mei, Member, IEEE, Ke Li, +Feiyue Huang, Bao-Gang Hu, Senior Member, IEEE, and Oliver Deussen"
+124fddbb5cbe4e5e6ea69be1467437aad01eb5d9,A Unified Algorithmic Framework for Multi-Dimensional Scaling,"A Unified Algorithmic Framework for Multi-Dimensional Scaling +Arvind Agarwal +Jeff M. Phillips† +Suresh Venkatasubramanian‡"
+12d0c11d546d91e776a170898ebf3a38c010695c,Semi-Supervised Hashing for Large-Scale Search,"Semi-Supervised Hashing for Large Scale +Search +Jun Wang, Member, IEEE, Sanjiv Kumar, Member, IEEE, and Shih-Fu Chang, Fellow, IEEE"
+12727bb8a4a1462553a13a253a97c2569cbcba0a,Study on Different Representation Methods for Subspace Segmentation,"International Journal of Grid Distribution Computing +Vol.8, No.1 (2015), pp.259-268 +http://dx.doi.org/10.14257/ijgdc.2015.8.1.24 +Study on Different Representation Methods for Subspace +Segmentation +Jiangshu Wei, Mantao Wang and Qianqian Wu +College of Information and Engineering, Sichuan Agricultural University, Ya’an, +625014, China"
+12149fc431d2b3ec4d1f194e92e74c765e51ee67,Concentration in unbounded metric spaces and algorithmic stability,"Concentration in unbounded metric spaces and algorithmic stability +Aryeh Kontorovich +Department of Computer Science, Ben-Gurion University, Beer Sheva 84105, ISRAEL"
+120b22e7a47923e42a123b9b68a93ccac5aaea6d,Paper on Ear Biometric Authentication,"Research Article Volume 6 Issue No.10 +ISSN XXXX XXXX © 2016 IJESC +Review Paper on Ear Biometric Authentication +Shubham Mohurle 1, See ma Khutwad 2, Pratiksha Kunjir3, Anjali Bhosle4 +Assistant Professor4 +KJCOEM R, Pune, India +Abstrac t: +In this paper we have studied about ear bio metric authentication. Powe rful bio metrics likes fingerprint, face and iris are used while +omparing the new biometric technology that is human ear recognition. We are studied different methods like 2D ear reco gnition, +Pattern extract ion method, robust algorithm, Pixe l based feature extraction. Genetic algorith m is the solution to all proble ms faced by +these methods. Recognition Rate for t ime series modeling is 99% obtained.AR model is used for time series modeling. All methods +re discussed later. +Ke ywor ds: Ear, Recognition Rate, 2D image, AR model +During crime investigation, in the absence of (valid) fingerprints +nd footprints ear ma rks are used for identification. Just like +fingerprints, use of ear shapes recommends its use for human +identification. An ear recognition system is simila r to face +recognition system and which has five components: image +cquisition, preprocessing, feature extraction, model training and +template matching. Du ring image gaining, an image of the ear is"
12cb3bf6abf63d190f849880b1703ccc183692fe,Guess Who?: A game to crowdsource the labeling of affective facial expressions is comparable to expert ratings,"Guess Who?: A game to crowdsource the labeling of affective facial expressions is comparable to expert ratings. Barry Borsboom Graduation research project, june 2012 Supervised by: Dr. Joost Broekens Leiden University Media Technology Department,"
+1222705b626a33974e85985ddabfcea135e9ddce,k-fold Subsampling based Sequential Backward Feature Elimination,
+127c229a3306bfc8170b84b12316f4a8024cc7ab,"A derived transformation of emotional functions using self-reports, implicit association tests, and frontal alpha asymmetries.","Learn Behav +DOI 10.3758/s13420-015-0198-6 +A derived transformation of emotional functions +using self-reports, implicit association tests, and frontal +lpha asymmetries +Micah Amd 1 & Bryan Roche 1 +# Psychonomic Society, Inc. 2015"
12cd96a419b1bd14cc40942b94d9c4dffe5094d2,Leveraging Captions in the Wild to Improve Object Detection,"Proceedings of the 5th Workshop on Vision and Language, pages 29–38, Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
+12c548d99fdc59bd702910af2c3daa17ed43e5d7,Performance analysis of different matrix decomposition methods on face recognition,"016 International Conference on Computer Communication and Informatics (ICCCI -2016), Jan. 07 – 09, 2016, Coimbatore, INDIA +Performance analysis of different Matrix +decomposition methods on Face Recognition +Dept. of Electronics and Communication Engineering +Dept. of Electronics and Communication Engineering +Suresh Babu K and K B Raja +UVCE, Bengaluru, India +the recognition accuracy +image and known stored images in terms of dimension +reduced images is made to declare identity of a person. It is +proved +improved by +onverting the images with variation in expression to neutral +images [5] and using image fusion with light field camera for +image capturing [6]. Maintaining robustness in recognition +ccuracy is elusive for key factors such as pose [7], back view +illumination variation [9] and others. Developing +illumination invariant image representation with textures is a +difficult task and pre-processing methods for mitigating the +illumination effect are discussed in future sections of this"
1275852f2e78ed9afd189e8b845fdb5393413614,A Transfer Learning based Feature-Weak-Relevant Method for Image Clustering,"A Transfer Learning based Feature-Weak-Relevant Method for Image Clustering Bo Dong, Xinnian Wang Dalian Maritime University Dalian, China"
+126b98473cc25e604abd58eb6bcf720354ac7e7a,An experimental illustration of 3D facial shape analysis under facial expressions,"Author manuscript, published in ""Annals of Telecommunications 64, 5-6 (2009) 369-379"""
12055b8f82d5411f9ad196b60698d76fbd07ac1e,Multiview Facial Landmark Localization in RGB-D Images via Hierarchical Regression With Binary Patterns,"Multiview Facial Landmark Localization in RGB-D Images via Hierarchical Regression With Binary Patterns Zhanpeng Zhang, Student Member, IEEE, Wei Zhang, Member, IEEE, Jianzhuang Liu, Senior Member, IEEE, nd Xiaoou Tang, Fellow, IEEE"
+12d813f14166578dea8aa6aacc945102dddfd05d,Fog Computing in 5G Networks: An Application Perspective,"“fog˙5g˙full” +016/5/4 +page 1 +Chapter 1 +Fog Computing in 5G Networks: An Application +Perspective +Harshit Gupta1, Sandip Chakraborty1, Soumya K. Ghosh1, +nd Rajkumar Buyya2 +Department of Computer Science and Engineering, IIT +CLOUDS Laboratory, University of Melbourne, Australia +Kharagpur, India"
+12e80b3a89bc021a6352840fb4552df842a6fe7d,Fast sparse representation with prototypes,"Fast Sparse Representation with Prototypes +Jia-Bin Huang and Ming-Hsuan Yang +University of California at Merced"
+1272d526614e40ce859e73de7e39a54baffd28cc,A unified approach to learning task-specific bit vector representations for fast nearest neighbor search,"A Unified Approach to Learning Task-Specific Bit Vector +Representations for Fast Nearest Neighbor Search +Vinod Nair +Yahoo! Labs Bangalore +Dhruv Mahajan +Yahoo! Labs Bangalore +S. Sundararajan +Yahoo! Labs Bangalore"
120785f9b4952734818245cc305148676563a99b,Diagnostic automatique de l'état dépressif(Classification of depressive moods),"Diagnostic automatique de l’état dépressif S. Cholet H. Paugam-Moisy @@ -15955,6 +55651,50 @@ temps réel, au moyen d’une simple webcam. A partir de vidéos du challenge AVEC’2014, nous avons entraîné un lassifieur neuronal à extraire des prototypes de visages selon différentes valeurs du score de dépression de Beck"
+12c5cd899d5ed85741197baed191f3b8b7fac495,Altered intrinsic functional connectivity of anterior and posterior insula regions in high-functioning participants with autism spectrum disorder.,"Altered Intrinsic Functional Connectivity of +Anterior and Posterior Insula Regions in +High-Functioning Participants With +Autism Spectrum Disorder +Sjoerd J.H. Ebisch,1,2* Vittorio Gallese,3,4 Roel M. Willems,5 +Dante Mantini,1,2,6 Wouter B. Groen,7 Gian Luca Romani,1,2 +Jan K. Buitelaar,7 and Harold Bekkering8 +Department of Clinical Sciences and Bioimaging, G. d’Annunzio University Chieti-Pescara, +Institute for Advanced Biomedical Technologies (ITAB), G. d’Annunzio Foundation, Chieti, Italy +Department of Neuroscience, Section of Physiology, Parma University, Parma, Italy +Chieti, Italy +Italian Institute of Technology (IIT), Section of Parma, Italy +5Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, +6Laboratory for Neuro-Psychophysiology, K.U. Leuven Medical School, Leuven, Belgium +7Department of Psychiatry, Radboud University Medical Centre and Karakter University Centre for +Radboud University, Nijmegen, The Netherlands +Child and Adolescent Psychiatry, Nijmegen, The Netherlands +8Donders Institute for Brain, Cognition and Behavior, Centre for Cognition, +Radboud University, Nijmegen, The Netherlands"
+122c674f264c53d762af841669209e131b49b3f2,Non-Rigid Structure from Motion for Building 3D Face Model,"Faculty of Informatics +Institute for Anthropomatics +Chair Prof. Dr.-Ing. R. Stiefelhagen +Facial Image Processing and Analysis Group +Non-Rigid Structure from Motion +for Building 3D Face Model +DIPLOMA THESIS OF +Chengchao Qu +ADVISORS +Dipl.-Inform. Hua Gao +Dr.-Ing. Hazım Kemal Ekenel +MARCH 2011 +KIT – University of the State of Baden-Württemberg and National Laboratory of the Helmholtz Association +www.kit.edu"
+127316fbe268c78c519ceb23d41100e86639418a,CNN Features Off-the-Shelf: An Astounding Baseline for Recognition,"CNN Features off-the-shelf: an Astounding Baseline for Recognition +Ali Sharif Razavian Hossein Azizpour +Josephine Sullivan Stefan Carlsson +CVAP, KTH (Royal Institute of Technology) +Stockholm, Sweden"
+123a9768700433c405bd7266f4c57ca8222e7fe1,Expanded Parts Model for Human Attribute and Action Recognition in Still Images,"Expanded Parts Model for Human Attribute and Action +Recognition in Still Images +Gaurav Sharma1,2, Fr´ed´eric Jurie1, Cordelia Schmid2 +GREYC, CNRS UMR 6072, University of Caen Basse-Normandie +LEAR, INRIA Grenoble Rhˆone-Alpes +inria}.fr"
12ebeb2176a5043ad57bc5f3218e48a96254e3e9,Traffic Road Sign Detection and Recognition for Automotive Vehicles,"International Journal of Computer Applications (0975 – 8887) Volume 120 – No.24, June 2015 Traffic Road Sign Detection and Recognition for @@ -15972,10 +55712,15 @@ Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri Presented by: Ahmed Osman Ahmed Osman"
+12ba7c6f559a69fbfaacf61bfb2f8431505b09a0,DocFace+: ID Document to Selfie Matching,"DocFace+: ID Document to Selfie* Matching +Yichun Shi, Student Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
12d8730da5aab242795bdff17b30b6e0bac82998,Persistent Evidence of Local Image Properties in Generic ConvNets,"Persistent Evidence of Local Image Properties in Generic ConvNets Ali Sharif Razavian, Hossein Azizpour, Atsuto Maki, Josephine Sullivan, Carl Henrik Ek, and Stefan Carlsson CVAP, KTH (Royal Institute of Technology), Stockholm, SE-10044"
+12831caca9674e0ab3fe2fc02a447ddb5a372994,Deep Aesthetic Quality Assessment With Semantic Information,"Deep Aesthetic Quality Assessment with Semantic +Information +Yueying Kao, Ran He, Kaiqi Huang"
8c13f2900264b5cf65591e65f11e3f4a35408b48,A Generic Face Representation Approach for Local Appearance Based Face Verification,"A GENERIC FACE REPRESENTATION APPROACH FOR LOCAL APPEARANCE BASED FACE VERIFICATION Hazim Kemal Ekenel, Rainer Stiefelhagen @@ -15983,6 +55728,18 @@ Interactive Systems Labs, Universität Karlsruhe (TH) 76131 Karlsruhe, Germany {ekenel, web: http://isl.ira.uka.de/face_recognition/"
+8ca29760334b7bdeaa7ad7ae4ff54c3b24420dd2,Analysis of Dynamic Characteristics of Spontaneous Facial Expressions,"Analysis of Dynamic Characteristics of Spontaneous Facial Expressions +Masashi Komori Yoshitaro Onishi +Division of Information and Computer Sciences, Osaka Electro-Communication University, +8-8 Hatsucho, Neyagawa, Osaka, 572-8530, JAPAN"
+8c5fa29c9bcab3d518fdf355e9da62fb0b58905e,Exploiting Semantics in Adversarial Training for Image-Level Domain Adaptation,"Exploiting Semantics in Adversarial Training for +Image-Level Domain Adaptation +st Pierluigi Zama Ramirez +University of Bologna +nd Alessio Tonioni +University of Bologna +rd Luigi Di Stefano +University of Bologna"
8c955f3827a27e92b6858497284a9559d2d0623a,Facial Expression Recognition under Noisy Environment Using Gabor Filters,"Buletinul Ştiinţific al Universităţii ""Politehnica"" din Timişoara Seria ELECTRONICĂ şi TELECOMUNICAŢII TRANSACTIONS on ELECTRONICS and COMMUNICATIONS @@ -15990,11 +55747,91 @@ Tom 53(67), Fascicola 1-2, 2008 Facial Expression Recognition under Noisy Environment Using Gabor Filters Ioan Buciu1, I. Nafornita2, I. Pitas3"
+8cd61bb3469aa253d4411ef2295b50683a031d17,Random Occlusion-recovery for Person Re-identification,"Random Occlusion-recovery for Person Re-identification +Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji +Di Wu1, Kun Zhang1 and De-Shuang Huang1 +University, Caoan Road 4800, Shanghai 201804, China"
+8c30b154811453b6a1017bb27e3becefde44f689,Bibliometric profile of the global scientific research on autism spectrum disorders,"Sweileh et al. SpringerPlus (2016) 5:1480 +DOI 10.1186/s40064-016-3165-6 +RESEARCH +Bibliometric profile of the global +scientific research on autism +spectrum disorders +Waleed M. Sweileh1*, Samah W. Al‑Jabi2, Ansam F. Sawalha1 and Sa’ed H. Zyoud2 +Open Access"
8c7f4c11b0c9e8edf62a0f5e6cf0dd9d2da431fa,Dataset Augmentation for Pose and Lighting Invariant Face Recognition,"Dataset Augmentation for Pose and Lighting Invariant Face Recognition Daniel Crispell∗, Octavian Biris∗, Nate Crosswhite†, Jeffrey Byrne†, Joseph L. Mundy∗ Vision Systems, Inc. Systems and Technology Research"
+8cf679ef0ea28557acb86546e4b1b1a617d1c698,Long Term Multi-Target Tracking based on Detection and Data Association,"International Journal of Electronics and Electrical Engineering Vol. 1, No. 3, September, 2013 +Long Term Multi-Target Tracking based on +Detection and Data Association +Ai Min Li +Shandong Polytechnic University, Jinan, China +Email: +Pil Seong Park +University of Suwon, Suwon, Korea +Email:"
+8c0f38c7c07c631d0b5414a84dda2992bdc4514f,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
+8cc23e554d98522b377d227dc78e9382a0ed35e5,"Bootstrap, Review, Decode: Using Out-of-Domain Textual Data to Improve Image Captioning","Bootstrap, Review, Decode: Using Out-of-Domain Textual Data +to Improve Image Captioning +Wenhu Chen +RWTH Aachen +Aurelien Lucchi +ETH Zurich +Thomas Hofmann +ETH Zurich"
+8c5852530abaefcdce805d1e339677351c6ec7fe,Lernen situationsunabhängiger Personenerkennung,"{ HAUPTBEITRAG / SITUATIONSUNABHÄNGIGE PERSONENERKENNUNG +Lernen situationsunabhängiger +Personenerkennung +Marco K. Müller · Michael Tremer +Christian Bodenstein · Rolf P. Würtz +Einleitung +In den vergangenen 25 Jahren hat sich automati- +sche Gesichtserkennung von einem akademischen +Projekt zu einer reifen Technik entwickelt. Bei der +Frage, ob es sich auf zwei Fotos um die gleiche Per- +son handelt, sind kommerzielle Systeme inzwischen +sogar Menschen überlegen [6]. Dies ist nicht mit der +Erkennung von bekannten Personen zu verwech- +seln, die der Mensch in sehr vielen verschiedenen +Situationen auch nach vielen Jahren wiedererkennen +kann. +Es ist eine zentrale Aufgabe des Computersehens, +ekannte Objekte in Bildern wiederzuerkennen. Dies +ist schwierig, weil dasselbe Objekt in verschiede- +nen Situationen sehr verschiedene Bilder erzeugt."
+8c244417db2082f4d5897548e72ef304ae886e52,Tree Based Space Partition of Trajectory Pattern Mining For Frequent Item Sets,"Australian Journal of Basic and Applied Sciences, 10(2) Special 2016, Pages: 250-261 +Australian Journal of Basic and Applied Sciences +AUSTRALIAN JOURNAL OF BASIC AND +AUSTRALIAN JOURNAL OF BASIC AND +APPLIED SCIENCES +ISSN:1991-8178 EISSN: 2309-8414 +Journal home page: www.ajbasweb.com +Tree Based Space Partition of Trajectory Pattern Mining For Frequent +Tree Based Space Partition of Trajectory Pattern Mining For Frequent +Tree Based Space Partition of Trajectory Pattern Mining For Frequent +Item Sets +nd Engineering , Alagappa University, Tamil Nadu, India. +P.Geetha and 2 E. Ramaraj +Ph.D scholar, Alagappa University. +Department of Computer Science and Engineering +Address For Correspondence: +P.Geetha, Ph.D scholar, Alagappa University. +Ph.D scholar, Alagappa University. +A R T I C L E I N F O +Article history:"
8ce9b7b52d05701d5ef4a573095db66ce60a7e1c,Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework,"Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework @@ -16003,6 +55840,14 @@ Chun-Guang Li, Chong You, and Ren´e Vidal" via Learning Temporal Driving Models Ashesh Jain, Hema S Koppula, Bharad Raghavan, Shane Soh, Ashutosh Saxena Cornell University and Stanford University"
+8cb4349f7d4b04a2e98b727524d3699bad50de1c,SOCIAL GAME EPITOME VERSUS AUTOMATIC VISUAL ANALYSIS Paper ID ***,"SOCIAL GAME EPITOME VERSUS AUTOMATIC VISUAL ANALYSIS +Paper ID ***"
+8c6427cc1f4e1bbe5d6da34a4511842361f4fbb6,Hypothesis Only Baselines in Natural Language Inference,"Hypothesis Only Baselines in Natural Language Inference +Adam Poliak1 Jason Naradowsky1 Aparajita Haldar1,2 +Rachel Rudinger1 Benjamin Van Durme1 +Johns Hopkins University 2BITS Pilani, Goa Campus, India"
+8c3c699f568ee825eefc4dc44b71c8b0bc592cca,Binary Multi-View Clustering.,"Binary Multi-View Clustering +Zheng Zhang†, Li Liu†, Fumin Shen, Heng Tao Shen, Ling Shao*"
8c6c0783d90e4591a407a239bf6684960b72f34e,SESSION KNOWLEDGE ENGINEERING AND MANAGEMENT + KNOWLEDGE ACQUISITION Chair(s),"SESSION KNOWLEDGE ENGINEERING AND MANAGEMENT + KNOWLEDGE ACQUISITION @@ -16018,13 +55863,38 @@ Department of Engineering, Aarhus University, Finlandsgade 22 8200 Aarhus N, Den These authors contributed equally to this work. Academic Editors: Francisco Rovira-Más and Gonzalo Pajares Martinsanz Received: 18 December 2015; Accepted: 2 February 2016; Published: 15 February 2016"
+8599560c50a55e75928dba6bbcbb98ef180a0798,Vocabulary Length Experiments for Binary Image Classification Using Bov Approach,"Signal & Image Processing : An International Journal (SIPIJ) Vol.4, No.6, December 2013 +VOCABULARY LENGTH EXPERIMENTS FOR BINARY +IMAGE CLASSIFICATION USING BOV APPROACH +S.P.Vimal1, Eshaan Puri2 and P.K.Thiruvikiraman3 +,2Department of Computer Science and Information Systems +Birla Institute of Technology and Science, Pilani, Rajasthan, India +Department of Physics, Birla Institute of Technology and Science, +Hyderabad Campus, Andra Pradesh, India"
8509abbde2f4b42dc26a45cafddcccb2d370712f,A way to improve precision of face recognition in SIPP without retrain of the deep neural network model,"Improving precision and recall of face recognition in SIPP with combination of modified mean search and LSH Xihua.Li"
+8529c0b98ab4f6eb21715a54395420988dd69633,Adapting Semantic Segmentation Models for Changes in Illumination and Camera Perspective,"Adapting Semantic Segmentation Models for Changes +in Illumination and Camera Perspective +Wei Zhou, Alex Zyner, Stewart Worrall, and Eduardo Nebot"
858ddff549ae0a3094c747fb1f26aa72821374ec,"Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications","Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-related Applications Ciprian A. Corneanu, Marc Oliu, Jeffrey F. Cohn, and Sergio Escalera"
+851f3dcfde59313dc2c8b87314f5a191d82194f4,Multiview Graphical Models for Tracking Occluded Objects,"Volume 3, Issue 10, October 2013 ISSN: 2277 128X +International Journal of Advanced Research in +Computer Science and Software Engineering +Research Paper +Available online at: www.ijarcsse.com +Multiview Graphical Models for Tracking Occluded Objects +Bharath +Student, +Dept.of CSE, +Jntuk, Kakinada, India +Smt. D.Neelima +Asst.Professor, +Dept.of CSE, +Jntuk, Kakinada, India"
85fd2bda5eb3afe68a5a78c30297064aec1361f6,"Are You Smiling, or Have I Seen You Before? Familiarity Makes Faces Look Happier.","702003 PSSXXX10.1177/0956797617702003Carr et al.Are You Smiling, or Have I Seen You Before? research-article2017 Research Article @@ -16042,11 +55912,106 @@ Evan W. Carr1, Timothy F. Brady2, and Piotr Winkielman2,3,4 Columbia Business School, Columbia University; 2Psychology Department, University of California, San Diego; Behavioural Science Group, Warwick Business School, University of Warwick; and 4Faculty of Psychology, SWPS University of Social Sciences and Humanities"
+856b8576999517c0cb7d95aef0159432604a8447,Weighted Heterogeneous Learning for Deep Convolutional Neural Network Based Facial Image Analysis,The 19th Meeting on Image Recognition and Understanding
+85955fe6cdf4f9f35fc9eab6cc4fccbb819e68a1,3D Face Reconstruction by Learning from Synthetic Data,"D Face Reconstruction by Learning from Synthetic Data +Elad Richardson* +Matan Sela* +Ron Kimmel +Department of Computer Science, Technion - Israel Institute of Technology"
+8558ea46c8f7e56c57073b27408c6638e81293f0,Morphable crowds,
858901405086056361f8f1839c2f3d65fc86a748,On Tensor Tucker Decomposition: the Case for an Adjustable Core Size,"ON TENSOR TUCKER DECOMPOSITION: THE CASE FOR AN ADJUSTABLE CORE SIZE BILIAN CHEN ∗, ZHENING LI † , AND SHUZHONG ZHANG ‡"
+851e78906e1307773b664953bf2830f32b28511f,Lie Algebra-Based Kinematic Prior for 3D Human Pose Tracking,"Lie Algebra-Based Kinematic Prior for 3D Human Pose Tracking +Edgar Simo-Serra, Carme Torras, and Francesc Moreno-Noguer +Institut de Rob`otica i Inform`atica Industrial (CSIC-UPC). Barcelona, Spain"
+8562ca7f86e7cc144aa2d34a9cce41431b9e13e9,Master Thesis Report: Face Recognition for Cognitive Robots,"Face Recognition for Cognitive +Robots +F. Gaisser +BioMechanical Enginering"
+85401b669a989da15bb3d2b37d4598c21d9d061b,"The effect of intranasal oxytocin versus placebo treatment on the autonomic responses to human sounds in autism: a single-blind, randomized, placebo-controlled, crossover design study","Lin et al. Molecular Autism 2014, 5:20 +http://www.molecularautism.com/content/5/1/20 +Open Access +R ES EAR CH +The effect of intranasal oxytocin versus placebo +treatment on the autonomic responses to human +sounds in autism: a single-blind, randomized, +placebo-controlled, crossover design study +I-Fan Lin1*, Makio Kashino1,2, Haruhisa Ohta3, Takashi Yamada3, Masayuki Tani3, Hiromi Watanabe3, Chieko Kanai3, +Taisei Ohno3, Yuko Takayama3, Akira Iwanami3 and Nobumasa Kato3,4"
+8575adafc04a7915bd71c3733e379577da0c4406,Sistema tutor afectivo para la enseñanza de lógica algorítmica y programación,"Sistema tutor afectivo para la enseñanza de lógica +lgorítmica y programación +Ramón Zatarain-Cabada1, María Lucia Barrón-Estrada1, +José Mario Ríos-Félix1, Giner Alor-Hernandez2 +Instituto Tecnológico de Culiacán, Culiacán Sinaloa, +México +Instituto Tecnológico de Orizaba, +División de Estudios de Posgrado e Investigación, Orizaba, Veracruz, +México +{rzatarain, lbarron, +Resumen. La creciente demanda de herramientas de software que motiven y +poyen a los estudiantes en el aprendizaje de diseño e implementación de +lgoritmos y programas, ha motivado la creación de este tipo de sistemas de +software. En este artículo presentamos un nuevo e innovador sistema tutor +fectivo de lógica algorítmica y programación, basado en la técnica de bloques. +Nuestro enfoque combina la interfaz de Google Blockly con técnicas de +gamificación y ejercicios que son monitoreados para obtener el estado afectivo +del estudiante. Dependiendo de la emoción manifestada (aburrido, enganchado, +frustrado y neutral), el sistema evalúa una serie de variables, para determinar si +el estudiante requiere asistencia. En base a las pruebas preliminares con varios"
+850c5d1f97eee47a1fdaefc0894b52e51a3145fc,Improved Semantic Stixels via Multimodal Sensor Fusion,"Improved Semantic Stixels via +Multimodal Sensor Fusion +Florian Piewak(cid:63)1,2, Peter Pinggera1, Markus Enzweiler1, +David Pfeiffer(cid:63)(cid:63)1, and Marius Z¨ollner2,3 +Daimler AG, R&D, Stuttgart, Germany +Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany +Forschungszentrum Informatik (FZI), Karlsruhe, Germany"
85188c77f3b2de3a45f7d4f709b6ea79e36bd0d9,"Combined model for detecting, localizing, interpreting and recognizing faces","Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France (2008)"""
+8582d5307793643e5b6a5e4354ee1ba32eff3809,Techniques for Face Detection & Recognition System-,"IOSR Journal of Computer Engineering (IOSR-JCE) +e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 15, Issue 5 (Nov. - Dec. 2013), PP 01-12 +www.iosrjournals.org +Techniques for Face Detection & Recognition System- +Comprehensive Review +Vandana S.Bhat1, Dr. J. D. Pujari2 +Department of Information Science & Engineering, SDMCET, Dharwad, INDIA +Department of Information Science & Engineering, SDMCET, Dharwad, INDIA"
+853d6cfe9c08c971979d1dd138bb21c25ff750bf,Comparison of MultiView Face Recognition using DCT and Hybrid DWT of Score Fusion under Uncontrolled Illumination Variation,"International Journal of Computer Applications (0975 – 8887) +Volume 96– No.4, June 20143 +Comparison of Multi-View Face Recognition using DCT +nd Hybrid DWT of Score Fusion under Uncontrolled +Illumination Variation +Manisha J Kasar +M.Tech Student (CE) +Computer Department, MPSTME +NMIMS, Shirpur, Dist :Dhule, Maharashtra, +India +Nitin S.Choubey +P.hd (Computer) +Computer Department, MPSTME +NMIMS, Shirpur, Dist :Dhule, Maharashtra, +India +is one of +for matching. First,"
+853feff8674f4a856e6568c9ddce5eace014de8c,NISTIR 8045 Performance Evaluation Methods for Human Detection and Tracking Systems for Robotic Applications,"NISTIR 8045 +Performance Evaluation Methods for +Human Detection and Tracking +Systems for Robotic Applications +Michael Shneier +Tsai Hong +Geraldine Cheok +Kamel Saidi +Will Shackleford +This publication is available free of charge from: +http://dx.doi.org/10.6028/NIST.IR.8045"
+85489639f395608174f686d634d6e27ef44c9d77,Social ‘wanting’ dysfunction in autism: neurobiological underpinnings and treatment implications,"Kohls et al. Journal of Neurodevelopmental Disorders 2012, 4:10 +http://www.jneurodevdisorders.com/content/4/1/10 +RE VI E W +Open Access +Social ‘wanting’ dysfunction in autism: +neurobiological underpinnings and +treatment implications +Gregor Kohls*, Coralie Chevallier, Vanessa Troiani and Robert T Schultz"
858b51a8a8aa082732e9c7fbbd1ea9df9c76b013,Can Computer Vision Problems Benefit from Structured Hierarchical Classification?,"Can Computer Vision Problems Benefit from Structured Hierarchical Classification? Thomas Hoyoux1, Antonio J. Rodr´ıguez-S´anchez2, Justus H. Piater2, and @@ -16054,23 +56019,225 @@ Sandor Szedmak2 INTELSIG, Montefiore Institute, University of Li`ege, Belgium Intelligent and Interactive Systems, Institute of Computer Science, University of Innsbruck, Austria"
+854890f35fc7955d94777395f6a66da433426d98,Human Gaze Following for Human-Robot Interaction,"Human Gaze Following for Human-Robot Interaction +Akanksha Saran1, Srinjoy Majumdar2, Elaine Schaertl Short2, Andrea Thomaz2 and Scott Niekum1"
+854f9fb21853d1e50302dddcc1fd5c2e933ed8f4,Information Constraints on Auto-Encoding Variational Bayes,"Information Constraints on Auto-Encoding Variational Bayes +Romain Lopez1, Jeffrey Regier1, Michael I. Jordan1,2, and Nir Yosef1,3,4 +{romain_lopez, regier, +Department of Electrical Engineering and Computer Sciences, University of California, Berkeley +Department of Statistics, University of California, Berkeley +Ragon Institute of MGH, MIT and Harvard +Chan-Zuckerberg Biohub"
+8566231abd7e5bc71ee0bc0da84b8d76ce07a501,On The Stability of Video Detection and Tracking,"On The Stability of Video Detection and Tracking +Hong Zhang +Chinese University of Hong Kong +Naiyan Wang +TuSimple LLC"
8518b501425f2975ea6dcbf1e693d41e73d0b0af,Relative Hidden Markov Models for Evaluating Motion Skill,"Relative Hidden Markov Models for Evaluating Motion Skills Qiang Zhang and Baoxin Li Computer Science and Engineering Arizona State Univerisity, Tempe, AZ 85281"
+85c1926ea23ff4f472774fec8c6a993bb499e4f4,Eigenbands fusion for frontal face recognition,"EIGENBANDS FUSION FOR FRONTAL FACE RECOGNITION +George D. C. Cavalcanti1s2 and Edson C. B. Cawalho Filho’ +’ UFPE-Universidade Federal de Pemambuco, 50732-970, Recife, PE, Brad +FIR-Faculdade Integrada do Recife 50720-635 Recife, PE, Brad"
853bd61bc48a431b9b1c7cab10c603830c488e39,Learning Face Representation from Scratch,"Learning Face Representation from Scratch Dong Yi, Zhen Lei, Shengcai Liao and Stan Z. Li Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences (CASIA) dong.yi, zlei, scliao,"
+857fface5ccd0fd4f30d6b1b3d2cd25a2b471501,Head pose estimation via probabilistic high-dimensional regression,"Head Pose Estimation Via Probabilistic +High-Dimensional Regression +Vincent Drouard 1 Sil`eye Ba 1 Georgios Evangelidis 1 +Antoine Deleforge 2 Radu Horaud 1 +Team Perception - Inria Grenoble Rhˆone-Alpes, France +Friedrich-Alexander-Universit¨at, Erlangen, Germany +September 28, 2015, Qu´ebec, Canada +Work supported by EU-FP7 ERC Advanced Grant VHIA (#340113) and STREP project EARS (#609645)"
854dbb4a0048007a49df84e3f56124d387588d99,Spatial-Temporal Recurrent Neural Network for Emotion Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014 Spatial-Temporal Recurrent Neural Network for Emotion Recognition Tong Zhang, Wenming Zheng*, Member, IEEE, Zhen Cui*, Yuan Zong and Yang Li"
+8569fc88a3d1ac8b873872becb2ee8bc01dc73bc,Deep-Person: Learning Discriminative Deep Features for Person Re-Identification,"Deep-Person: Learning Discriminative Deep Features +for Person Re-Identification +Xiang Bai, Mingkun Yang, Tengteng Huang, +Zhiyong Dou, Rui Yu, Yongchao Xu∗ +School of Electronic Information and Communications, Huazhong University of Science and +Technology (HUST), Wuhan, 430074, China"
+85387549277d6131dc8596ffacc7a21aeee0c6d1,Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial Networks,"Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial +Networks +Yunfan Liu, Qi Li, and Zhenan Sun∗ +Center for Research on Intelligent Perception and Computing, CASIA +National Laboratory of Pattern Recognition, CASIA +{qli,"
+85cad2b23e2ed7098841285bae74aafbff921659,Pa-gan: Improving Gan Training by Progressive Augmentation,"Under review as a conference paper at ICLR 2019 +PA-GAN: IMPROVING GAN TRAINING BY +PROGRESSIVE AUGMENTATION +Anonymous authors +Paper under double-blind review"
+1d7df7000a3e8fafa21679db4efe2ffedcfe0335,And the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"SEMANTIC IMAGE UNDERSTANDING: FROM THE WEB, IN +LARGE SCALE, WITH REAL-WORLD CHALLENGING DATA +A DISSERTATION +SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE +AND THE COMMITTEE ON GRADUATE STUDIES +OF STANFORD UNIVERSITY +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +DOCTOR OF PHILOSOPHY +Jia Li +November 2011"
+1d4c2dd3996cb3d87da6c35d72572637d3175ea5,Toward Storytelling From Visual Lifelogging: An Overview,"JOURNAL OF TRANSACTIONS ON HUMAN-MACHINE SYSTEMS JULY 2015 +Towards Storytelling from +Visual Lifelogging: An Overview +Marc Bola˜nos∗, Mariella Dimiccoli∗, and Petia Radeva"
+1d5901662dc4fa5be2375f35be07b4116fd450ea,The Effects of Prediction on the Perception for Own-Race and Other-Race Faces,"RESEARCH ARTICLE +The Effects of Prediction on the Perception +for Own-Race and Other-Race Faces +Guangming Ran1,2, Qi Zhang3, Xu Chen1,2*, Yangu Pan1,2 +. Faculty of Psychology, Southwest University (SWU), Chongqing, 400715, China, 2. Research Center of +Mental Health Education, Southwest University (SWU), Chongqing, 400715, China, 3. School of Education +Science, Guizhou Normal University (GNU), Guizhou, 550001, China"
+1d524c57214384ad6a003c54b1918130744b69d2,Identifying Human-Object Interactions in Motionless Images by Modeling the Mutual Context of Objects and Human Poses,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Impact Factor (2012): 3.358 +Identifying Human-Object Interactions in +Motionless Images by Modeling the Mutual Context +of Objects and Human Poses +A. N. Bhagat1, N. B. Pokale2 +Department of Computer Engineering, TSSM,s Bhivrabai Sawant College Of Engineering and Research, Narhe, Pune, Maharashtra, India. +Associate Professor, Department of Computer Engineering, TSSM,s Bhivrabai Sawant College Of Engineering and Research, Narhe, Pune, +Maharashtra, India."
+1dc45403839d6aefe65c6e7f2179d5ea697dfeac,DCT-based features for categorisation of social media in compressed domain,"DCT-based Features for Categorisation of Social +Media in Compressed Domain +Sebastian Schmiedeke, Pascal Kelm, Thomas Sikora +Communication Systems Group +Technische Universit¨at Berlin +Germany"
+1d0a6759de0d55d15439b0367f0aa49c1e248c5c,"Networking in Autism: Leveraging Genetic, Biomarker and Model System Findings in the Search for New Treatments","............................................................................................................................................................... +REVIEW +Networking in Autism: Leveraging Genetic, Biomarker +nd Model System Findings in the Search for New +Treatments +Jeremy Veenstra-VanderWeele1,2,3,4 and Randy D Blakely*,1,3,4 +Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA; 2Department of Pediatrics, +Vanderbilt University School of Medicine, Nashville, TN, USA; 3Department of Pharmacology, Vanderbilt University School of +Medicine, Nashville, TN, USA; 4Center for Molecular Neuroscience, Vanderbilt University School of Medicine, Nashville, +TN, USA +Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder affecting approximately 1% of children. ASD is +defined by core symptoms in two domains: negative symptoms of impairment in social and communication function, and +positive symptoms of restricted and repetitive behaviors. Available treatments are inadequate for treating both core +symptoms and associated conditions. Twin studies indicate that ASD susceptibility has a large heritable component. Genetic +studies have identified promising leads, with converging insights emerging from single-gene disorders that bear ASD +features, with particular interest in mammalian target of rapamycin (mTOR)-linked synaptic plasticity mechanisms. Mouse +models of these disorders are revealing not only opportunities to model behavioral perturbations across species, but also +evidence of postnatal rescue of brain and behavioral phenotypes. An intense search for ASD biomarkers has consistently +pointed to elevated platelet serotonin (5-HT) levels and a surge in brain growth in the first 2 years of life. Following a review of +the diversity of ASD phenotypes and its genetic origins and biomarkers, we discuss opportunities for translation of these"
+1d5d68bee741d81771e9224fe53806e85ed469aa,RATM: Recurrent Attentive Tracking Model,"RATM: Recurrent Attentive Tracking Model +Samira Ebrahimi Kahou, Vincent Michalski, and Roland Memisevic"
+1d03698a46ff12fdfaf4811528b3e7961dfd2fe6,Fast Exact Max-Kernel Search,"Fast Exact Max-kernel Search +Ryan R. Curtin +Parikshit Ram +Alexander G. Gray"
1d7ecdcb63b20efb68bcc6fd99b1c24aa6508de9,The Hidden Sides of Names—Face Modeling with First Name Attributes,"The Hidden Sides of Names—Face Modeling with First Name Attributes Huizhong Chen, Student Member, IEEE, Andrew C. Gallagher, Senior Member, IEEE, and Bernd Girod, Fellow, IEEE"
+1d9497450f60b874eb6ecbf82e3d0808a6fe236c,Nonconvex proximal splitting with computational errors∗,"Nonconvex proximal splitting with computational errors∗ +Suvrit Sra +Max Planck Institute, T¨ubingen, Germany +Introduction +We study in this chapter large-scale nonconvex optimization problems with composite objective functions +that are composed of a differentiable possibly nonconvex cost and a nonsmooth but convex regularizer. +More precisely, we consider optimization problems of the form +minimize Φ(x) := f (x) + r(x), +where X ⊂ Rn is a compact convex set, f : Rn → R is a differentiable cost function and r : Rn → R is a +losed convex function. Further, we assume that the gradient ∇ f is Lipschitz continuous on X (denoted +f ∈ C1 +L(X )), i.e., +x ∈ X , +∃L > 0 s.t. (cid:107)∇ f (x) − ∇ f (y)(cid:107) ≤ L(cid:107)x − y(cid:107) +for all +x, y ∈ X . +Throughout this chapter, (cid:107)·(cid:107) denotes the standard Euclidean norm. +Problem (1) generalizes the more thoroughly studied class of composite convex optimization prob- +lems [30], a class that has witnessed huge interest in machine learning, signal processing, statistics, +nd other related areas. We refer the interested reader to [2, 3, 21, 37] for several convex examples"
+1df554e992baf60f2d0b7c1b563250ba19b8f8ff,3D Face Recognition Based on 3D Ridge Lines in Range Data,"-4244-1437-7/07/$20.00 ©2007 IEEE +I - 137 +ICIP 2007"
+1d251acc459931d927f5befdfb5b9cdf643cd8bc,Bayesian Compression for Natural Language Processing,"Bayesian Compression for Natural Language Processing +Nadezhda Chirkova1∗, Ekaterina Lobacheva1∗, Dmitry Vetrov1,2 +Samsung-HSE Laboratory, National Research University Higher School of Economics +Samsung AI Center +Moscow, Russia"
+1dca6a54d201dd56b41a5475aaf498a207083b0e,Ego-surfing first person videos,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +Ego-Surfing First-Person Videos +Ryo Yonetani, Member, IEEE, Kris M. Kitani, Member, IEEE, and Yoichi Sato, Member, IEEE"
+1dd3a58ab363cb396bf36223fadc8d2341bfdb83,Picture: A probabilistic programming language for scene perception,"Picture: a probabilistic programming language for scene perception +Tejas D Kulkarni1, Pushmeet Kohli2, Joshua B Tenenbaum1, Vikash Mansinghka1 +Brain and Cognitive Science, Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology. 2Microsoft Research Cambridge. +Probabilistic scene understanding systems aim to produce high-probability +descriptions of scenes conditioned on observed images or videos, typically ei- +ther via discriminatively trained models or generative models in an “analysis +y synthesis” framework. Discriminative approaches lend themselves to fast, +ottom-up inference methods and relatively knowledge-free, data-intensive +training regimes, and have been remarkably successful on many recognition +problems. Generative approaches hold out the promise of analyzing complex +scenes more richly and flexibly, but have been less widely embraced for two +main reasons: Inference typically depends on slower forms of approximate +inference, and both model-building and inference can involve considerable +problem-specific engineering to obtain robust and reliable results. These +factors make it difficult to develop simple variations on state-of-the-art mod- +els, to thoroughly explore the many possible combinations of modeling, +representation, and inference strategies, or to richly integrate complemen- +tary discriminative and generative modeling approaches to the same problem. +More generally, to handle increasingly realistic scenes, generative approaches +will have to scale not just with respect to data size but also with respect to"
+1dc94886ca1d4893208d38b18cb7ad1541a74b82,Weakly Supervised Training of Speaker Identification Models,"Weakly Supervised Training of Speaker Identification Models +Martin Karu, Tanel Alum¨ae +Department of Software Science +Tallinn University of Technology, Estonia"
+1d9bd24e65345258259ee24332141e371c6e4868,Learning Image Descriptors with Boosting,"Learning Image Descriptors with Boosting +Tomasz Trzcinski, Mario Christoudias, and Vincent Lepetit"
+1d1e78bb93590a86ecfd2516f4e5789cc05d76f5,Local Features and Generative Models,"FACE AUTHENTICATION BASED ON +LOCAL FEATURES AND +GENERATIVE MODELS +Fabien Cardinaux (a) +IDIAP–RR 05-85 +JANUARY 2006 +ESEARCHREPRORTIDIAPRue du Simplon 4IDIAP Research Institute1920 Martigny − Switzerlandwww.idiap.chTel: +41 27 721 77 11Email: Box 592Fax: +41 27 721 77 12"
+1d692f37c2594ddb30518da27bfc0f5044690d09,Learning Depth From Single Images With Deep Neural Network Embedding Focal Length,"Learning Depth from Single Images with Deep +Neural Network Embedding Focal Length +Lei He, Guanghui Wang (Senior Member, IEEE) and Zhanyi Hu"
+1d6905e88f64ac826344d89c51ad8daea3b95e0e,Monocular Object Orientation Estimation using Riemannian Regression and Classification Networks,"Noname manuscript No. +(will be inserted by the editor) +Monocular Object Orientation Estimation using +Riemannian Regression and Classification Networks +Siddharth Mahendran · Ming Yang Lu · Haider Ali · Ren´e Vidal +the date of receipt and acceptance should be inserted later"
+1d59ffad091a5bffa5fe935b79f5bfc08d2e802d,Intensity Video Guided 4D Fusion for Improved Highly Dynamic 3D Reconstruction,"Intensity Video Guided 4D Fusion for +Improved Highly Dynamic 3D Reconstruction +Jie Zhang, Christos Maniatis, Luis Horna and Robert B. Fisher"
+1d53aebe67d0e088e2da587fd6b08c8e8ed7f45c,A Selection Module for Large-Scale Face Recognition Systems,"A Selection module for large-scale face +recognition systems +Giuliano Grossi, Raffaella Lanzarotti, and Jianyi Lin +Dipartimento di Informatica, Universit`a degli Studi di Milano +Via Comelico 39/41, Milano, Italy"
+1d4e1b4f37caf40dc70d211c6b2745195dfa6c3f,Facial Expression Recognition Using Interpolation Features,"Facial Expression Recognition Using Interpolation +Features +Jesús García-Ramírez, Ivan Olmos-Pineda, J. Arturo Olvera-López, and +Manuel Martín-Ortíz +Benemérita Universidad Autónoma de Puebla, Faculty of Computer Science, Puebla, México"
+1df314a1e4dce42fd9fab094b79a0f2a10ad0b03,People Detection in Fish-eye Top-views,
+1dca96fdcab180133644442df4ad78eeec1aa00b,Learning from Synthetic Humans,"Learning from Synthetic Humans +G¨ul Varol∗† +Javier Romero‡ +Xavier Martin† +Naureen Mahmood‡ +Michael Black‡ +Ivan Laptev∗ +Cordelia Schmid†"
1d0dd20b9220d5c2e697888e23a8d9163c7c814b,Boosted Metric Learning for Efficient Identity-Based Face Retrieval,"NEGREL ET AL.: BOOSTED METRIC LEARNING FOR FACE RETRIEVAL Boosted Metric Learning for Efficient Identity-Based Face Retrieval @@ -16080,11 +56247,56 @@ Frederic Jurie GREYC, CNRS UMR 6072, ENSICAEN Université de Caen Basse-Normandie France"
+1d4f56a9bb093c52569917537a93c7671db28e6f,Real-time Tracking of Player Identities in Team Sports,"Real-time Tracking of Player +Identities in Team Sports +Dissertation +Nicolai Baron von Hoyningen-Huene"
+1dc4b5e93233fc632b070c8ff282ef0fe9141f64,2-D Structure-Based Gait Recognition in Video Using Incremental GMM-HMM,"-D Structure-Based Gait Recognition in Video +Using incremental GMM-HMM +Rui Pu1, Yunhong Wang1 +Laboratory of Intelligence Recognition and Image Processing, Beijing Key +Laboratory of Digital Media, School of Computer Science and Engineering, Beihang +University, Beijing 100191, China"
1d776bfe627f1a051099997114ba04678c45f0f5,Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras,"Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras Pratik Dubal(cid:63), Rohan Mahadev(cid:63), Suraj Kothawade(cid:63), Kunal Dargan, and Rishabh Iyer AitoeLabs (www.aitoelabs.com)"
+1d9306ea0f0239c88aecbcf0a48a11c964a0fcd4,3D facial expression recognition using maximum relevance minimum redundancy geometrical features,"Rabiu et al. EURASIP Journal on Advances in Signal Processing 2012, 2012:213 +http://asp.eurasipjournals.com/content/2012/1/213 +RESEARCH +Open Access +D facial expression recognition using +maximum relevance minimum redundancy +geometrical features +Habibu Rabiu*, M. Iqbal Saripan, Syamsiah Mashohor and Mohd Hamiruce Marhaban"
+1da57510321fb8b25dc4d21844fb9afa4e40571e,Activity representation with motion hierarchies,"Int J Comput Vis +DOI 10.1007/s11263-013-0677-1 +Activity representation with motion hierarchies +Adrien Gaidon · Zaid Harchaoui · Cordelia Schmid +Received: 17 May 2013 / Accepted: 20 November 2013 +© Springer Science+Business Media New York 2013"
+1dd3faf5488751c9de10977528ab96be24616138,Detecting Anomalous Faces with 'No Peeking' Autoencoders,"Detecting Anomalous Faces with ‘No Peeking’ Autoencoders +Anand Bhattad 1 Jason Rock 1 David Forsyth 1"
+1d4e0427dffec6ac75b96a564986046ea2b00980,Eye Controlled Robotic Motion Using Video Tracking In Real Time,"ISSN(Online): 2319-8753 +ISSN (Print): 2347-6710 +International Journal of Innovative Research in Science, +Engineering and Technology +(An ISO 3297: 2007 Certified Organization) +Website: www.ijirset.com +Vol. 6, Issue 7, July 2017 +Eye Controlled Robotic Motion Using Video +Tracking In Real Time +Kriti Bhattacharjee 1, Dr. Manoj Soni 2 +P.G. Student, Department of Mechanical and Automation Engineering, IGDTUW, New Delhi, India1 +Associate Professor, Department of Mechanical and Automation Engineering, IGDTUW, New Delhi, India2"
+1d1f83023686d43fd4e8805c8e517dffb02d118c,Compiler Enhanced Scheduling for OpenMP for Heterogeneous Multiprocessors,"Compiler Enhanced Scheduling for OpenMP for +Heterogeneous Multiprocessors +Jyothi Krishna V S +IIT Madras"
+1d81293bc17a135cfd35912146c538cd81830381,Single camera multi-person tracking based on crowd simulation,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-1-6 ©2012 IAPR"
1dff919e51c262c22630955972968f38ba385d8a,Toward an Affect-Sensitive Multimodal Human–Computer Interaction,"Toward an Affect-Sensitive Multimodal Human–Computer Interaction MAJA PANTIC, MEMBER, IEEE, AND LEON J. M. ROTHKRANTZ @@ -16114,10 +56326,62 @@ Jeffrey F. Cohn1,2 · Daniel S. Messinger3 · Fernando De la Torre1 · Received: 3 June 2016 / Accepted: 12 January 2017 © Springer Science+Business Media New York 2017"
+1d2af64416882b2ae8fe4de51b85fdd7d561cfee,Headgear Accessories Classification Using an Overhead Depth Sensor,"Article +Headgear Accessories Classification Using an +Overhead Depth Sensor +Carlos A. Luna, Javier Macias-Guarasa ID , Cristina Losada-Gutierrez * ID , Marta Marron-Romera, +Manuel Mazo, Sara Luengo-Sanchez and Roberto Macho-Pedroso +Department of Electronics, University of Alcala, Ctra. Madrid-Barcelona, km.33,600, 28805 Alcalá de Henares, +Spain; (C.A.L.); (J.M.-G.); (M.M.-R.); +(M.M.); (S.L.-S.); (R.M.-P.) +* Correspondence: Tel.: +34-918-856-906; Fax: +34-918-856-591 +Received: 22 June 2017; Accepted: 8 August 2017; Published: 10 August 2017"
+1dc07322715e093c560b30fdf1e168e58e9a9409,DRBF and IRBF Based Face Recognition and Extraction of Facial Expressions from the Blur Image,"Australian Journal of Basic and Applied Sciences, 8(3) March 2014, Pages: 61-68 +AENSI Journals +Australian Journal of Basic and Applied Sciences +ISSN:1991-8178 +Journal home page: www.ajbasweb.com +DRBF and IRBF Based Face Recognition and Extraction of Facial Expressions from the +Blur Image +M. Jayashree, 2Dr. D. Deepa, 3M. Rubhashree +PG Scholar, Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, TamilNadu, India. +2Associate Professor, Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, TamilNadu, +India. +Assistant Professor, Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, +TamilNadu, India. +A R T I C L E I N F O +Article history: +Received 12 January 2014 +Received in revised form 22 +March 2014 +Accepted 27 March 2014 +Available online 2 April 2014"
1da83903c8d476c64c14d6851c85060411830129,Iterated Support Vector Machines for Distance Metric Learning,"Iterated Support Vector Machines for Distance Metric Learning Wangmeng Zuo, Member, IEEE, Faqiang Wang, David Zhang, Fellow, IEEE, Liang Lin, Member, IEEE, Yuchi Huang, Member, IEEE, Deyu Meng, and Lei Zhang, Senior Member, IEEE"
+1d93a1af770040cb8a64e96215884ee363a8f53a,Improved face recognition at a distance using light field camera & super resolution schemes,"Improved Face Recognition At A Distance Using Light +Field Camera & Super Resolution Schemes +R. Raghavendra* Kiran B. Raja*† Bian Yang* Christoph Busch*† +{raghavendra.ramachandra, kiran.raja, bian.yang, +*Norwegian Biometrics Laboratory +Hochschule Darmstadt - CASED +Gjøvik University College +802 Gjøvik, Norway +Haardtring 100, +64295 Darmstadt, Germany"
+1d5fe82303712a70c1d231ead2ee03f042d8ad70,ImageNet pre-trained models with batch normalization,"ImageNet pre-trained models with batch normalization +Marcel Simon, Erik Rodner, Joachim Denzler +Computer Vision Group +Friedrich-Schiller-Universit¨at Jena, Germany +{marcel.simon, erik.rodner,"
+1d455f918062f66e86ed53cf258284abd6abd8fc,SMSnet: Semantic motion segmentation using deep convolutional neural networks,"SMSnet: Semantic Motion Segmentation +using Deep Convolutional Neural Networks +Johan Vertens∗ +Abhinav Valada∗ +Wolfram Burgard"
+1d99282d00f7cf3e4d912428313848add8de8220,Comparing Attribute Classifiers for Interactive Language Grounding,"Proceedings of the 2015 Workshop on Vision and Language (VL’15), pages 60–69, +Lisbon, Portugal, 18 September 2015. c(cid:13)2015 Association for Computational Linguistics."
1d58d83ee4f57351b6f3624ac7e727c944c0eb8d,Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions,"Enhanced Local Texture Feature Sets for Face Recognition under Difficult @@ -16126,6 +56390,8 @@ Xiaoyang Tan and Bill Triggs INRIA & Laboratoire Jean Kuntzmann, 655 avenue de l'Europe, Montbonnot 38330, France"
+1d679b371c9dfd833cee0925de483562d2bc7d88,Face Recognition using 3D Summation Invariant Features,"424403677/06/$20.00 ©2006 IEEE +ICME 2006"
1d729693a888a460ee855040f62bdde39ae273af,Photorealistic Face De-Identification by Aggregating Donors' Face Components,"Photorealistic Face de-Identification by Aggregating Donors’ Face Components Saleh Mosaddegh, Lo¨ıc Simon, Fr´ed´eric Jurie @@ -16156,22 +56422,195 @@ Student of M.E., Department of Electronics & Telecommunication Engineering, P. R. Patil College of Engineering, Amravati Maharashtra – India Assistant Professor, Department of Electronics & Telecommunication Engineering, P. R. Patil College of Engineering, Amravati Maharashtra – India"
+714794c74941e45798d9c405a4fec1138cff2df3,Iris Segmentation: State of the Art and Innovative Methods,"Iris segmentation: state of the art and innovative +methods +Ruggero Donida Labati, Angelo Genovese, Vincenzo Piuri, and Fabio Scotti"
+71ab53b0b3635411d5985f71cc56bb1784023834,RoboCupRescue 2012 - Robot League Team,"RoboCupRescue 2012 - Robot League Team +Hector Darmstadt (Germany) +Thorsten Graber2, Stefan Kohlbrecher1, Johannes Meyer2, Karen Petersen1, +Oskar von Stryk1, Uwe Klingauf2(cid:63) +Department of Computer Science (1) and Department of Mechanical Engineering (2), +Technische Universit¨at Darmstadt, +Karolinenplatz 5, D-64289 Darmstadt, Germany +E-Mail: +Web: www.gkmm.tu-darmstadt.de/rescue"
71b376dbfa43a62d19ae614c87dd0b5f1312c966,The temporal connection between smiles and blinks,"The Temporal Connection Between Smiles and Blinks Laura C. Trutoiu, Jessica K. Hodgins, and Jeffrey F. Cohn"
+713345804a00c6c0083e4155b904956bb95949da,Scalable Normalized Cut with Improved Spectral Rotation,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
71fd29c2ae9cc9e4f959268674b6b563c06d9480,End-to-end 3D shape inverse rendering of different classes of objects from a single input image,"End-to-end 3D shape inverse rendering of different classes of objects from a single input image Shima Kamyab1 and S. Zohreh Azimifar1 Computer Science and Engineering and Information Technology, Shiraz university, Shiraz, Iran November 17, 2017"
+712609494dd049b44ebfd82698b9305ef07f027b,Biometric bits extraction through phase quantization based on feature level fusion,"Telecommun Syst (2011) 47:255–273 +DOI 10.1007/s11235-010-9317-z +Biometric bits extraction through phase quantization based +on feature level fusion +Hyunggu Lee · Andrew Beng Jin Teoh · Jaihie Kim +Published online: 4 June 2010 +© Springer Science+Business Media, LLC 2010"
+71dcf25a3ea3801f09d6cc446dbf78e22481d609,Face recognition with the continuous n-tuple classifier,"FaceRecognitionwiththecontinuous +n-tupleclassi(cid:12)er +S.M.Lucas +DepartmentofElectronicSystemsEngineering +UniversityofEssex +ColchesterCOSQ,UK"
+7174e77f8e26aef3105996512b787b336320d46f,People Counting in High Density Crowds from Still Images,"People Counting in High Density Crowds from Still +Images +Ankan Bansal, and K S Venkatesh"
+71f1e72670e676b6902cce0d6fc0b4f63b46ca28,Survey paper: Face Detection and Face Recognition,"Survey paper: +Face Detection and Face Recognition +By Hyun Hoi James Kim +. Introduction +Face recognition is one of biometric methods identifying individuals by the features of face. Research in this +rea has been conducted for more than 30 years; as a result, the current status of face recognition technology +is well advanced. Many commercial applications of face recognition are also available such as criminal +identification, security system, image and film processing. +From the sequence of images captured by camera, the goal is to find best match with given image. Using a +pre-stored image database, the face recognition system should be able to identify or verify one or more +persons in the scene. Before face recognition is performed, the system should determine whether or not there +is a face in a given image or given video, a sequence of images. This process is called face detection. Once a +face is detected, face region should be isolated from the scene for the face recognition. The face detection and +face extraction are often performed simultaneously. The overall process is depicted in Fig 1. +Identification +or Verification +Feature Extraction +Face Detection +Face Recognition +Input"
+71f969fdc6990b21536c5662c52110d7fdb29028,Driver Gaze Tracking and Eyes Off the Road Detection System Using a Depth Camera,"X Encontro de Alunos e Docentes do DCA/FEEC/UNICAMP (EADCA) +X DCA/FEEC/University of Campinas (UNICAMP) Workshop (EADCA) +Campinas, 26 e 27 de outubro de 2017 +Campinas, Brazil, October 26-27, 2017 +Driver Gaze Tracking and Eyes Off the Road Detection System +Using a Depth Camera +Ribeiro, Rafael F. , Costa, P. D. P (Orientador) +Dept. of Computer Engineering and Industrial Automation (DCA) +School of Electrical and Computer Engineering (FEEC) +University of Campinas (Unicamp) +Postal Code 6101, 13083-970 – Campinas, SP, Brazil"
+71c549df77b0fc2ebe0dc20d39d0a629a563bd7a,Texture Classification based on Local Features Using Dual Neighborhood Approach,"I.J. Image, Graphics and Signal Processing, 2017, 9, 59-67 +Published Online September 2017 in MECS (http://www.mecs-press.org/) +DOI: 10.5815/ijigsp.2017.09.07 +Texture Classification based on Local Features +Using Dual Neighborhood Approach +Associate Professor, Dept. of C.S.E, Sri Vasavi Institute of Engineering & Technology, pedana, Andhrapradesh, India +M. Srinivasa Rao +Email: +V.Vijaya Kumar +Professor, Anurag Group of Institutions (Autonomous), Hyderabad,Telanagana, India +Email: +MHM KrishnaPrasad +Professor of the Department of Computer Science and Engineering, University College of Engineering, Kakinada +(Autonomous), JNTUK, Andhra Pradesh, India +Email: +Received: 11 March 2017; Accepted: 05 July 2017; Published: 08 September 2017"
+71406b7358812400d0626e8d62e7eb38cea99bbe,On Improving Face Detection Performance by Modelling Contextual Information,"ON IMPROVING FACE DETECTION +PERFORMANCE BY MODELLING +CONTEXTUAL INFORMATION +Cosmin Atanasoaei Chris McCool +Sébastien Marcel +Idiap-RR-43-2010 +DECEMBER 2010 +Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny +T +41 27 721 77 11 F +41 27 721 77 12 www.idiap.ch"
+71403805e67eeb6ec336e0cb83646fdb7c819757,Visual Strategies for Sparse Spike Coding,"Visual Strategies for Sparse Spike Coding +Laurent Perrinet +Manuel Samuelides +ONERA/DTIM, +, av. Belin, +1055 Toulouse, France"
714d487571ca0d676bad75c8fa622d6f50df953b,eBear: An expressive Bear-Like robot,"eBear: An Expressive Bear-Like Robot Xiao Zhang, Ali Mollahosseini, Amir H. Kargar B., Evan Boucher, Richard M. Voyles, Rodney Nielsen and Mohammd H. Mahoor"
+710ce8cf25f31df8547b888519b414187e989257,Amygdala activation predicts gaze toward fearful eyes.,"The Journal of Neuroscience, July 15, 2009 • 29(28):9123–9126 • 9123 +Brief Communications +Amygdala Activation Predicts Gaze toward Fearful Eyes +Matthias Gamer and Christian Bu¨chel +Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, D-20246 Hamburg, Germany +The human amygdala can be robustly activated by presenting fearful faces, and it has been speculated that this activation has functional +relevance for redirecting the gaze toward the eye region. To clarify this relationship between amygdala activation and gaze-orienting behavior, +functional magnetic resonance imaging data and eye movements were simultaneously acquired in the current study during the evaluation of +facial expressions. Fearful, angry, happy, and neutral faces were briefly presented to healthy volunteers in an event-related manner. We con- +trolled for the initial fixation by unpredictably shifting the faces downward or upward on each trial, such that the eyes or the mouth were +presentedatfixation.Acrossemotionalexpressions,participantsshowedabiastoshifttheirgazetowardtheeyes,butthemagnitudeofthiseffect +followed the distribution of diagnostically relevant regions in the face. Amygdala activity was specifically enhanced for fearful faces with the +mouth aligned to fixation, and this differential activation predicted gazing behavior preferentially targeting the eye region. These results reveal +direct role of the amygdala in reflexive gaze initiation toward fearfully widened eyes. They mirror deficits observed in patients with amygdala +lesions and open a window for future studies on patients with autism spectrum disorder, in which deficits in emotion recognition, probably +related to atypical gaze patterns and abnormal amygdala activation, have been observed. +Introduction +The human amygdala is known to be robustly activated by the +presentation of fearful faces (Morris et al., 1996; Hariri et al., +002; Gla¨scher et al., 2004; Reinders et al., 2005), which seems to"
+7128f1239cbd1007ef19d8fd8cdab083d33a6984,"Aligned to the Object, not to the Image: A Unified Pose-aligned Representation for Fine-grained Recognition","Aligned to the Object, not to the Image: +A Unified Pose-aligned Representation for Fine-grained Recognition +Pei Guo, Ryan Farrell +Computer Science Department +Brigham Young University"
710011644006c18291ad512456b7580095d628a2,Learning Residual Images for Face Attribute Manipulation,"Learning Residual Images for Face Attribute Manipulation Wei Shen Rujie Liu Fujitsu Research & Development Center, Beijing, China. {shenwei,"
+71529e3e51f2967e338124652e93a3d34eb6c5e1,Deep triplet-group network by exploiting symmetric and asymmetric information for person reidentification,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/6/2018 +Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +Deeptriplet-groupnetworkbyexploitingsymmetricandasymmetricinformationforpersonreidentificationBenzhiYuNingXuBenzhiYu,NingXu,“Deeptriplet-groupnetworkbyexploitingsymmetricandasymmetricinformationforpersonreidentification,”J.Electron.Imaging27(3),033033(2018),doi:10.1117/1.JEI.27.3.033033."
+714947e4d7f79f753c5c44eac701185e37086276,An Exponential Representation in the API Algorithm for Hidden Markov Models Training,"An Exponential Representation in the API +Algorithm for Hidden Markov Models Training +S´ebastien Aupetit1, Nicolas Monmarch´e1, Mohamed Slimane1, and +Pierre Liardet2 +Universit´e Fran¸cois-Rabelais de Tours, Laboratoire d’Informatique +Polytech’Tours, 64, Av Jean Portalis, 37200 Tours, France +Universit´e de Provence, CMI +Laboratoire ATP, UMR-CNRS 6632 +9 rue F. Joliot-Curie, 13453 Marseille cedex 13, France"
+71f98c3f7a5b02ab193110d5ae9f9d48a1c5ec38,Deep Human Parsing with Active Template Regression,"Deep Human Parsing with Active Template +Regression +Xiaodan Liang, Si Liu, Xiaohui Shen, Jianchao Yang, Luoqi Liu, Jian Dong, Liang Lin, Shuicheng +Yan, Senior Member, IEEE"
+71286a2b3d564daf171cdef54ff8972159152729,Combinatorial Resampling Particle Filter: An Effective and Efficient Method for Articulated Object Tracking,"Noname manuscript No. +(will be inserted by the editor) +Combinatorial Resampling Particle Filter: an Effective and Efficient +Method for Articulated Object Tracking +Christophe Gonzales · S´everine Dubuisson +Received: date / Accepted: date"
+71d3ed17c0642234a921bb45fcadd86520794941,Learning by Tracking: Siamese CNN for Robust Target Association,"Learning by tracking: Siamese CNN for robust target association +Laura Leal-Taix´e +TU M¨unchen +Munich, Germany +Cristian Canton-Ferrer +Microsoft +Redmond (WA), USA +Konrad Schindler +ETH Zurich +Zurich, Switzerland"
+71766bf224d5c74a0be6996b38d8885c2eed5a2c,Fooling Vision and Language Models Despite Localization and Attention Mechanism,
+71d8fae870ea78a89e231247afb3259267e09799,Probabilistic multi-class segmentation for the Amazon Picking Challenge,"Probabilistic Multi-Class Segmentation +for the Amazon Picking Challenge +Rico Jonschkowski +Clemens Eppner∗ +Sebastian H¨ofer∗ +Roberto Mart´ın-Mart´ın∗ Oliver Brock"
+71dcbca34d71bda0bc41c33c04d2c1a740274feb,An Innovative Mean Approach for Plastic Surgery Face Recognition,"International Journal of Science and Research (IJSR) +ISSN (Online): 2319-7064 +Index Copernicus Value (2014): 6.14 | Impact Factor (2014): 4.438 +An Innovative Mean Approach for Plastic Surgery +Face Recognition +Mahendra P. Randive1, Umesh W. Hore2 +Student of M.E., Department of Electronics & Telecommunication Engineering, +P. R. Patil College of Engineering, Amravati Maharashtra – India +Assistant Professor, Department of Electronics & Telecommunication Engineering, +P. R. Patil College of Engineering, Amravati Maharashtra – India"
+7189d5584416ef2a39d6ab16929dfecdddc10081,A Review of Face Sketch Recognition Systems,"Journal of Theoretical and Applied Information Technology +20th November 2015. Vol.81. No.2 +© 2005 - 2015 JATIT & LLS. All rights reserved. +ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 +A REVIEW OF FACE SKETCH RECOGNITION SYSTEMS +SALAH EDDINE LAHLALI, 2ABDELALIM SADIQ, 3 SAMIR MBARKI +23Department of Computing, Faculty of sciences, IbnTofail University, Kenitra, Morocco +E-mail:"
711bb5f63139ee7a9b9aef21533f959671a7d80e,Objects extraction and recognition for camera-based interaction : heuristic and statistical approaches,"Helsinki University of Technology Laboratory of Computational Engineering Publications Teknillisen korkeakoulun Laskennallisen tekniikan laboratorion julkaisuja Espoo 2007 @@ -16190,6 +56629,38 @@ TECHNISCHE UNIVERSITÄT HELSINKI TECHNISCHE UNIVERSITÄT HELSINKI UNIVERSITE DE TECHNOLOGIE D'HELSINKI UNIVERSITE DE TECHNOLOGIE D'HELSINKI"
+7173871866fc7e555e9123d1d7133d20577054e8,Simultaneous Adversarial Training - Learn from Others Mistakes,"Simultaneous Adversarial Training - Learn from +Others’ Mistakes +Zukang Liao +Lite-On Singapore Pte. Ltd, 2Imperial College London"
+71edcfe5e3a4e1678698a0659a7e51555291d242,Who's that Actor? Automatic Labelling of Actors in TV Series Starting from IMDB Images,"Who’s that Actor? Automatic Labelling of +Actors in TV series starting from IMDB Images +Rahaf Aljundi(cid:63), Punarjay Chakravarty(cid:63) and Tinne Tuytelaars +KU Leuven, ESAT-PSI, iMinds, Belgium"
+715216a92c338a3c35319026d38ed0da0c57d013,Integrated Pedestrian and Direction Classification Using a Random Decision Forest,"Integrated Pedestrian and Direction Classification +using a Random Decision Forest +Junli Tao and Reinhard Klette +University of Auckland, Auckland, New Zealand"
+711801297f23df9ac8ca1c2d3c9d7dfa2ed12043,Enhancing Energy Efficiency of Multimedia Applications in Heterogeneous Mobile Multi-Core Processors,"Contention-Aware Fair Scheduling for +Asymmetric Single-ISA Multicore Systems +Adrian Garcia-Garcia , Juan Carlos Saez , and Manuel Prieto-Matias"
+76ec5c774bb3fd04f9e68864a411286536a544c5,Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models,"LATENT CONSTRAINTS: +LEARNING TO GENERATE CONDITIONALLY FROM +UNCONDITIONAL GENERATIVE MODELS +Jesse Engel +Google Brain +San Francisco, CA, USA +Matthew D. Hoffman +Google Inc. +San Francisco, CA, USA +Adam Roberts +Google Brain +San Francisco, CA, USA"
+7608953ef5c7a882bd2e7e7053a600e543748233,Robust 3D Face Recognition by Local Shape Difference Boosting,"Robust 3D Face Recognition +y Local Shape Difference Boosting +Yueming Wang, Jianzhuang Liu, Senior Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
+76ff6a68d7a8dcc12b6ba68e914294f6720a466d,The red one!: On learning to refer to things based on discriminative properties,"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pages 213–218, +Berlin, Germany, August 7-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
76fd801981fd69ff1b18319c450cb80c4bc78959,Alignment of Eye Movements and Spoken Language for Semantic Image Understanding,"Proceedings of the 11th International Conference on Computational Semantics, pages 76–81, London, UK, April 15-17 2015. c(cid:13)2015 Association for Computational Linguistics"
76dc11b2f141314343d1601635f721fdeef86fdb,Weighted Decoding ECOC for Facial Action Unit Classification,"Weighted Decoding ECOC for Facial @@ -16199,6 +56670,12 @@ Terry Windeatt" Subhransu Maji Toyota Technological Institute at Chicago, Chicago, IL 60637, USA"
+76f73c884e4437a22afcba60193bbd7f35e64aaf,Title of dissertation : RESOURCE ALLOCATION IN COMPUTER VISION,
+768cb0e32de3f1b5aebe04448aaec4c25586680c,Boosting Image Captioning with Attributes,"Under review as a conference paper at ICLR 2017 +BOOSTING IMAGE CAPTIONING WITH ATTRIBUTES +Ting Yao, Yingwei Pan, Yehao Li, Zhaofan Qiu, Tao Mei +Microsoft Research Asia +{tiyao, v-yipan, v-yehl, v-zhqiu,"
76cd5e43df44e389483f23cb578a9015d1483d70,Face Verification from Depth using Privileged Information,"BORGHI ET AL.: FACE VERIFICATION FROM DEPTH Face Verification from Depth using Privileged Information @@ -16212,6 +56689,22 @@ Stefano Pini Filippo Grazioli Roberto Vezzani Rita Cucchiara"
+76b2732a8684babdfd95c655b2e1a1b79c3aeb9b,Face detection from few training examples,"978-1-4244-1764-3/08/$25.00 ©2008 IEEE +ICIP 2008 +Authorized licensed use limited to: UNSW Library. Downloaded on June 12, 2009 at 01:20 from IEEE Xplore. Restrictions apply."
+76c018c6dfc81f61c3912c5ed442d9a72f64e467,Graphical Processing Unit Assisted Image Processing for Accelerated Eye Tracking,"Graphical Processing Unit Assisted Image Processing for +Accelerated Eye Tracking +Dissertation submitted by +Jean-Pierre Louis du Plessis +Student Number: 2006033415 +to the +Department of Computer Science and Informatics +Faculty of Natural and Agricultural Sciences +University of the Free State, South Africa +Submitted in fulfilment of the requirements of the degree +Magister Scientiae +February 2015 +Study Leader: Prof P.J. Blignaut"
76b11c281ac47fe6d95e124673a408ee9eb568e3,Real-time Multi View Face Detection and Pose Estimation Aishwarya,"International Journal of Latest Engineering and Management Research (IJLEMR) ISSN: 2455-4847 www.ijlemr.com || Volume 02 - Issue 03 || March 2017 || PP. 59-71 @@ -16220,6 +56713,27 @@ ESTIMATION AISHWARYA.S1 , RATHNAPRIYA.K1, SUKANYA SARGUNAR.V2 U. G STUDENTS, DEPT OF CSE, ALPHA COLLEGE OF ENGINEERING, CHENNAI, ASST PROF.DEPARTMENT OF CSE, ALPHA COLLEGE OF ENGINEERING, CHENNAI"
+76bfa74a6311db5d84bad2a7a941f30dd750d01c,Evidence That Emotion Mediates Social Attention in Rhesus Macaques,"Evidence That Emotion Mediates Social Attention in +Rhesus Macaques +Emily J. Bethell1*, Amanda Holmes2, Ann MacLarnon1, Stuart Semple1 +Centre for Research in Evolutionary and Environmental Anthropology, University of Roehampton, London, United Kingdom, 2 Department of Psychology, University of +Roehampton, London, United Kingdom"
+7689d23a22682c92bdf9a1df975fa2cdd24f1b87,MMD with Kernel Learning In practice we use finite samples from distributions to estimate,"MMD GAN: Towards Deeper Understanding of Moment Matching +Network +Chun-Liang Li +Committee: Barnab´as P´oczos and Pradeep Ravikumar +Tuesday 28th November, 2017"
+76ebe6d24ee69e3f853740fb75085a2118d40d51,ILLUMINANCE FLOW ( met een samenvatting in het Nederlands ) PROEFSCHRIFT ter verkrijging van de graad van doctor,"ILLUMINANCE FLOW +(met een samenvatting in het Nederlands) +PROEFSCHRIFT +ter verkrijging van de graad van doctor aan de Universiteit Utrecht op +gezag van de rector magnificus, prof.dr. J.C. Stoof, ingevolge het besluit +van het college voor promoties +in het openbaar te verdedigen op vrijdag 15 januari 2010 +des middags te 4.15 uur +(Dan) Stefan Mikael Karlsson +geboren op 3 september 1978 te Stafsinge, Zweden"
+76f3450e50c20fca00dd6319df38503c5d7ebad0,THÈSE DE DOCTORAT présentée par OLIVIER DUCHENNE pour obtenir le grade de DOCTEUR DE L ’ ÉCOLE NORMALE SUPÉRIEURE,"THÈSEDEDOCTORATprésentéeparOLIVIERDUCHENNEpourobtenirlegradedeDOCTEURDEL’ÉCOLENORMALESUPÉRIEUREDomaine:MATHÉMATIQUESAPPLIQUÉESSujetdelathèse:Alignementélastiqued’imagespourlareconnaissanced’objet—Non-rigidimagealignmentforobjectrecognitionThèseprésentéeetsoutenueàl’ENSUlmle29Novembre2012devantlejurycomposéde:JeanPonceProfesseur,DirecteurduDI,ENSUlmDirecteurdethèsePedroFelzenszwalbProfesseur,BrownUniversityRapporteurMartialHebertProfesseur,CarnegieMellonUniversityRapporteurFrancisBachDirecteurderecherche,ENSUlmÉxaminateurJitendraMalikProfesseur,UniversityofBerkeleyÉxaminateurCordeliaSchmidProfesseur,INPGrenobleÉxaminateurAndrewZissermanProfesseur,UniversityofOxfordÉxaminateurThèsepréparéeauseindel’équipeWILLOWdudépartementd’informatiquedel’ÉcoleNormaleSupérieure,Ulm.(INRIA/ENS/CNRSUMR8548)."
76d9f5623d3a478677d3f519c6e061813e58e833,Fast Algorithms for the Generalized Foley-Sammon Discriminant Analysis,"FAST ALGORITHMS FOR THE GENERALIZED FOLEY-SAMMON DISCRIMINANT ANALYSIS LEI-HONG ZHANG∗, LI-ZHI LIAO† , AND MICHAEL K. NG‡"
@@ -16246,6 +56760,31 @@ Thesis submitted for the degree of Alon Zweig Submitted to the Senate of the Hebrew University August / 2013"
+7606a74de57f67257c77a8bb0295ff4593566040,Content-based Image Retrieval Using Constrained Independent Component Analysis : Facial Image Retrieval Based on Compound Queries,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,800 +16,000 +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact +Numbers displayed above are based on latest data collected."
+76cb2ecc96f02b1d8a7a0d1681fbb55367a4b765,Learning Object States from Videos,"Learning Object States from Videos +Liang-Kang Huang +Katerina Fragkiadaki"
+7671234c3726fda01b2842f85327624f0dda8ead,The data deluge: Challenges and opportunities of unlimited data in statistical signal processing,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE +ICASSP 2009"
760ba44792a383acd9ca8bef45765d11c55b48d4,Class-specific classifier: avoiding the curse of dimensionality,"INTRODUCTION AND BACKGROUND The purpose of this article is to introduce the reader to the basic principles of classification with @@ -16266,6 +56805,18 @@ which attempt to determine the decision boundaries in a highdimensional featue space. In contrast, in CSM, it is possible to build classifiers without a ” n o n feature space. Separate Law-dimensional features seta may be de6ned for each class, while"
+76d8b370d0a8fc63ead6ba657dd438d7155d659f,Modular Sensor Fusion for Semantic Segmentation,"(cid:13)2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any +urrent or future media, including reprinting/republishing this material for advertising or promotional purposes, creating +new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in +other works. +Please cite this paper as: +title +uthor +ooktitle = ""2018 {IEEE/RSJ} International Conference on Intelligent Robots += ""Modular Sensor Fusion for Semantic Segmentation"", += ""Blum, Hermann and Gawel, Abel and Siegwart, Roland and Cadena, Cesar"", +nd Systems ({IROS})"", += 2018;"
766728bac030b169fcbc2fbafe24c6e22a58ef3c,A survey of deep facial landmark detection,"A survey of deep facial landmark detection Yongzhe Yan1,2 Xavier Naturel2 @@ -16290,6 +56841,20 @@ dans ce domaine, y compris sur les corpus non contraints Georgia Gkioxari Ross Girshick Piotr Doll´ar Kaiming He Facebook AI Research (FAIR)"
+76a0016ce19363ef8f7ba5c3964c4a0c29b608ca,ModaNet: A Large-scale Street Fashion Dataset with Polygon Annotations,"ModaNet: A Large-scale Street Fashion Dataset with Polygon +Annotations +Shuai Zheng +eBay Inc. +San Jose, California +M. Hadi Kiapour +eBay Inc. +San Francisco, California +Fan Yang +eBay Inc. +San Jose, California +Robinson Piramuthu +eBay Inc. +San Francisco, California"
7636f94ddce79f3dea375c56fbdaaa0f4d9854aa,Robust Facial Expression Recognition Using a Smartphone Working against Illumination Variation,"Appl. Math. Inf. Sci. 6 No. 2S pp. 403S-408S (2012) An International Journal © 2012 NSP @@ -16303,6 +56868,30 @@ Department of Computer Engineering, Sejong University, 98 Kunja-Dong, Kwangjin-G Corresponding author: Email: Received June 22, 2010; Revised March 21, 2011; Accepted 11 June 2011 Published online: 1 January 2012"
+7638cb16631fbcdf621aaf392fec5108e6fa9f47,On Nonrigid Shape Similarity and Correspondence,"Alon Shtern and Ron Kimmel +November 25, 2013 +trinsically symmetric halves of a human face were found by mapping the shape (left) to itself. +Textures from two faces (middle) were transferred to each half (right)."
+1ca9ab2c1b5e8521cba20f78dcf1895b3e1c36ac,"Explorer "" Here ' s looking at you , kid","""Here's looking at you, kid"" +Citation for published version: +Marin-Jimenez, M, Zisserman, A & Ferrari, V 2011, ""Here's looking at you, kid"": Detecting people looking at +each other in videos. in Proceedings of the British Machine Vision Conference (BMVC): Dundee, September +011. BMVA Press, pp. 22.1-22.12. DOI: 10.5244/C.25.22 +Digital Object Identifier (DOI): +0.5244/C.25.22 +Link: +Link to publication record in Edinburgh Research Explorer +Document Version: +Peer reviewed version +Published In: +Proceedings of the British Machine Vision Conference (BMVC) +General rights +Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +nd / or other copyright owners and it is a condition of accessing these publications that users recognise and +bide by the legal requirements associated with these rights. +Take down policy +The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer +ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please"
1c80bc91c74d4984e6422e7b0856cf3cf28df1fb,Hierarchical Adaptive Structural SVM for Domain Adaptation,"Noname manuscript No. (will be inserted by the editor) Hierarchical Adaptive Structural SVM for Domain Adaptation @@ -16316,6 +56905,48 @@ Steven M. Seitz1,3 University of Washington∗ Adobe Systems† Google Inc."
+1cd9dba357e05c9be0407dc5d477fd528cfeb79b,Model-driven Simulations for Deep Convolutional Neural Networks,"Model-driven Simulations for Deep Convolutional +Neural Networks +V S R Veeravasarapu1, Constantin Rothkopf2, Visvanathan Ramesh1 +Center for Cognition and Computing, Goethe University, Frankfurt. +Cognitive Science Center, Technical University, Darmstadt."
+1cb68fa98a0d9871a394cd0035488df167b9c2cf,RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation,"RedNet: Residual Encoder-Decoder Network for +indoor RGB-D Semantic Segmentation +Jindong Jiang, Lunan Zheng, Fei Luo, and Zhijun Zhang +The School of Automation Science and Engineering, South China University of +Technology, Guangzhou 510640, China"
+1cf6bc0866226c1f8e282463adc8b75d92fba9bb,"Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering","Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for +Visual Question Answering +Huijuan Xu +UMass Lowell +Kate Saenko +UMass Lowell"
+1c9333bcf523388d75f852e0689b0e7f5a04faa4,Person Part Segmentation based on Weak Supervision,"JIANG, CHI: PERSON PART SEGMENTATION BASED ON WEAK SUPERVISION 1 +Person Part Segmentation based on Weak +Supervision +Yalong Jiang1 1Department of Electronic and Information +Engineering +Zheru Chi1 The Hong Kong Polytechnic University, HK"
+1c26e415c7eae2f3b0f49e0519f0d985ec661c63,Intersection of Longest Paths in Graph Theory and Predicting Performance in Facial Recognition,"Georgia State University +ScholarWorks Georgia State University +Mathematics Dissertations +Department of Mathematics and Statistics +-6-2017 +Intersection of Longest Paths in Graph Theory and +Predicting Performance in Facial Recognition +Amy Yates +Follow this and additional works at: http://scholarworks.gsu.edu/math_diss +Recommended Citation +Yates, Amy, ""Intersection of Longest Paths in Graph Theory and Predicting Performance in Facial Recognition."" Dissertation, Georgia +State University, 2017. +http://scholarworks.gsu.edu/math_diss/34 +This Dissertation is brought to you for free and open access by the Department of Mathematics and Statistics at ScholarWorks Georgia State +University. It has been accepted for inclusion in Mathematics Dissertations by an authorized administrator of ScholarWorks Georgia State +University. For more information, please contact"
+1cb95f013ec3e78acdda6ac6cfdb362ae6a5ceac,Nonnegative matrix factorization for segmentation analysis,"Nonnegative matrix factorization for +segmentation analysis +Roman Sandler +Technion - Computer Science Department - Ph.D. Thesis PHD-2010-09 - 2010"
1cfe3533759bf95be1fce8ce1d1aa2aeb5bfb4cc,Recognition of Facial Gestures Based on Support Vector Machines,"Recognition of Facial Gestures based on Support Vector Machines Attila Fazekas and Istv(cid:19)an S(cid:19)anta @@ -16341,42 +56972,289 @@ sends back various information describing the face e.g. is the person male or female, is she/he bald, does he have a mus- tache, etc. We assume that a client can compute one (or a ombination) of visual features; from very simple and effi-"
+1cd0bc067e66bc1f66a73b401a4a470e43e4bb9e,Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples,"Houdini: Fooling Deep Structured Visual and Speech +Recognition Models with Adversarial Examples +Moustapha Cisse +Facebook AI Research +Natalia Neverova* +Facebook AI Research"
+1cee733ee31e245dac4655a870fd9226163a52b5,Bidirectional Beam Search: Forward-Backward Inference in Neural Sequence Models for Fill-in-the-Blank Image Captioning,"Bidirectional Beam Search: Forward-Backward Inference in +Neural Sequence Models for Fill-in-the-Blank Image Captioning +Qing Sun +Virginia Tech +Stefan Lee +Virginia Tech +Dhruv Batra +Georgia Tech"
+1cd584f519d9cd730aeef1b1d87f7e2e82b4de59,A fully automatic face recognition system using a combined audio - visual approach ∗,"A fully automatic face recognition system using a combined +udio-visual approach ∗ +Alberto Albiol†, Luis Torres†, and Edward J. Delp? † +Communications Department +Technical University of Valencia, Valencia, Spain +Department of Signal Theory & Communications +Technical University of Catalonia, Barcelona, Spain +?School of Electrical and Computer Engineering +Purdue University West Lafayette, IN 47907-1285 +Corresponding Author: +Dr. Alberto Albiol +Communications Department +Technical University of Valencia, Valencia, Spain +6022 Valencia (Spain) +Telephone: +34 96 387 97 38 +Fax: +34 96 387 73 09 +Email:"
1c30bb689a40a895bd089e55e0cad746e343d1e2,Learning Spatiotemporal Features with 3D Convolutional Networks,"Learning Spatiotemporal Features with 3D Convolutional Networks Du Tran1 , Lubomir Bourdev1, Rob Fergus1, Lorenzo Torresani2, Manohar Paluri1 Facebook AI Research, 2Dartmouth College"
+1c521ac6e68436f6c6aad3c0eb7ffa557fe25b0d,Modeling Image Patches with a Generic Dictionary of Mini-epitomes,"Modeling Image Patches with a Generic Dictionary of Mini-Epitomes +George Papandreou +TTI Chicago +Liang-Chieh Chen +UC Los Angeles +Alan L. Yuille +UC Los Angeles"
+1cc3c5f242d885738e9349a91d4beba82ae106a6,Scalable nonconvex inexact proximal splitting,"Scalable nonconvex inexact proximal splitting +Suvrit Sra +Max Planck Institute for Intelligent Systems +72076 T¨ubigen, Germany"
+1cf01968594ae59d28b12c9a35fc43d944563071,Low-Level Features for Image Retrieval Based on Extraction of Directional Binary Patterns and Its Oriented Gradients Histogram,"Computer Applications: An International Journal (CAIJ), Vol.2, No.1, February 2015 +LOW-LEVEL FEATURES FOR IMAGE RETRIEVAL BASED +ON EXTRACTION OF DIRECTIONAL BINARY PATTERNS +AND ITS ORIENTED GRADIENTS HISTOGRAM +Nagaraja S. and Prabhakar C.J. +Department of P.G. Studies and Research in Computer Science +Kuvempu University, India"
1c3073b57000f9b6dbf1c5681c52d17c55d60fd7,Direction de thèse:,"THÈSEprésentéepourl’obtentiondutitredeDOCTEURDEL’ÉCOLENATIONALEDESPONTSETCHAUSSÉESSpécialité:InformatiqueparCharlotteGHYSAnalyse,Reconstruction3D,&AnimationduVisageAnalysis,3DReconstruction,&AnimationofFacesSoutenancele19mai2010devantlejurycomposéde:Rapporteurs:MajaPANTICDimitrisSAMARASExaminateurs:MichelBARLAUDRenaudKERIVENDirectiondethèse:NikosPARAGIOSBénédicteBASCLE"
+1cbc189a4484cd2b1371798bae2ff50c0442ce60,A Hybrid Loss for Multiclass and Structured Prediction,"IEEE TRANSACTIONS ON PATTERN ANALYSIS & MACHINE INTELLIGENCE, FINAL DRAFT, FEB. 2014 +A Hybrid Loss for Multiclass +nd Structured Prediction +Qinfeng Shi, Mark Reid, Tiberio Caetano, Anton van den Hengel and Zhenhua Wang"
+1cf29a0131211079fc73908ecf211ee78f090ad9,Regionlets for Generic Object Detection,"Regionlets for Generic Object Detection +Xiaoyu Wang Ming Yang +Shenghuo Zhu +Yuanqing Lin +NEC Laboratories America, Inc."
+1c1a24169be56e01b0e36e260f49025260a5c7e7,A Deep Compositional Framework for Human-like Language Acquisition in Virtual Environment,"A Deep Compositional Framework for Human-like +Language Acquisition in Virtual Environment +Haonan Yu, Haichao Zhang, and Wei Xu +Baidu Research - Institue of Deep Learning +Sunnyvale, CA 94089"
1c93b48abdd3ef1021599095a1a5ab5e0e020dd5,A Compositional and Dynamic Model for Face Aging,"JOURNAL OF LATEX CLASS FILES, VOL. *, NO. *, JANUARY 2009 A Compositional and Dynamic Model for Face Aging Jinli Suo , Song-Chun Zhu , Shiguang Shan and Xilin Chen"
+1cc0183d8fbef098d29b6b5f621745ff099f6c6c,Joint Discovery of Object States and Manipulation Actions,"Joint Discovery of Object States and Manipulation Actions +Jean-Baptiste Alayrac∗ † +Josef Sivic∗ † ‡ +Ivan Laptev∗ † +Simon Lacoste-Julien§"
+1c90ad1e264c29a8d180de47373257a5f1b5aa57,Generalizing Image Captions for Image-Text Parallel Corpus,"Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pages 790–796, +Sofia, Bulgaria, August 4-9 2013. c(cid:13)2013 Association for Computational Linguistics +house being pulled by a boat.” “I saw her in the light of her reading lamp and sneaked back to her door with the camera.” “Sections of the bridge sitting in the Dyer Construction yard south of Cabelas Driver.” Circumstantial information that is not visually present Visually relevant, but with overly extraneous details Visually truthful, but for an uncommon situation Figure1:Examplesofcaptionsthatarenotreadilyapplicabletoothervisuallysimilarimages.textfromtheretrievedsamplestothequeryim-age(e.g.Farhadietal.(2010),Ordonezetal.(2011),Kuznetsovaetal.(2012)).Otherwork(e.g.FengandLapata(2010a),FengandLapata(2010b))usescomputervisiontobiassummariza-tionoftextassociatedwithimagestoproducede-scriptions.Alloftheseapproachesrelyonex-istingtextthatdescribesvisualcontent,butmanytimesexistingimagedescriptionscontainsignifi-cantamountsofextraneous,non-visual,orother-wisenon-desirablecontent.Thegoalofthispaperistodeveloptechniquestoautomaticallycleanupvisuallydescriptivetexttomakeitmoredirectlyusableforapplicationsexploitingtheconnectionbetweenimagesandlanguage.Asaconcreteexample,considerthefirstimageinFigure1.Thiscaptionwaswrittenbythephotoownerandthereforecontainsinformationrelatedtothecontextofwhenandwherethephotowastaken.Objectssuchas“lamp”,“door”,“camera”arenotvisuallypresentinthephoto.Thesecondimageshowsasimilarbutsomewhatdifferentis-sue.Itscaptiondescribesvisibleobjectssuchas“bridge”and“yard”,but“CabelasDriver”areoverlyspecificandnotvisuallydetectable.The"
+1c51aeece7a3c30302ebd83bdcaa65df0bfc48fe,Unsupervised Video Indexing based on Audiovisual Characterization of Persons. (Indexation vidéo non-supervisée basée sur la caractérisation des personnes),"Unsupervised Video Indexing based on Audiovisual +Characterization of Persons +Elie El Khoury +To cite this version: +Elie El Khoury. Unsupervised Video Indexing based on Audiovisual Characterization of Per- +sons. Human-Computer Interaction [cs.HC]. Universit´e Paul Sabatier - Toulouse III, 2010. +English. <tel-00515424v3> +HAL Id: tel-00515424 +https://tel.archives-ouvertes.fr/tel-00515424v3 +Submitted on 7 Sep 2010 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non, +´emanant des ´etablissements d’enseignement et de"
+1cbf3b90065e8a410668ed914e9d03a94a4d94aa,Visual-Inertial Semantic Scene Representation,"Visual-Inertial Semantic Scene Representation +UCLA TR CSD160005 +Stefano Soatto +May 20, 2016"
+1c7e1248ce254b3a9a0b6fef9e37d37620fc8aa3,Dynamic Image-to-Class Warping for Occluded Face Recognition,"Dynamic Image-to-Class Warping for Occluded +Face Recognition +Xingjie Wei, Chang-Tsun Li, Senior Member, IEEE, Zhen Lei, Member, IEEE, +Dong Yi, and Stan Z. Li, Fellow, IEEE"
+1cdf8790a675037579bbe2ee4f39f731f7672fae,Pivot Correlational Neural Network for Multimodal Video Categorization,"Pivot Correlational Neural Network for +Multimodal Video Categorization +Sunghun Kang1[0000−0003−2632−7522], Junyeong Kim1[0000−0002−7871−9627], +Hyunsoo Choi2, Sungjin Kim2, and Chang D. Yoo1 +KAIST, Daejeon, South Korea +{sunghun.kang, junyeong.kim, +SAMSUNG ELECTRONICS CO.,LTD, Seoul, South Korea +{hsu.choi,"
+1ca40e1d0ae377296ac6804c81c1e5bcbc5475c8,RVM-Based Human Action Classification in Crowd through Projection and Star Skeletonization,"Hindawi Publishing Corporation +EURASIP Journal on Image and Video Processing +Volume 2009, Article ID 164019, 12 pages +doi:10.1155/2009/164019 +Research Article +RVM-Based Human Action Classification in Crowd through +Projection and Star Skeletonization +B. Yogameena, S. Veeralakshmi, E. Komagal, S. Raju, and V. Abhaikumar +Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, +Madurai 625015, Tamil Nadu, India +Correspondence should be addressed to B. Yogameena, +Received 1 February 2009; Revised 17 May 2009; Accepted 26 August 2009 +Recommended by Amit Roy-Chowdhury +Detection of abnormal human actions in the crowd has become a critical problem in video surveillance applications like terrorist +ttacks. This paper proposes a real-time video surveillance system which is capable of classifying normal and abnormal actions of +individuals in a crowd. The abnormal actions of human such as running, jumping, waving hand, bending, walking and fighting +with each other in a crowded environment are considered. In this paper, Relevance Vector Machine (RVM) is used to classify +the abnormal actions of an individual in the crowd based on the results obtained from projection and skeletonization methods. +Experimental results on benchmark datasets demonstrate that the proposed system is robust and efficient. A comparative study of +lassification accuracy between Relevance Vector Machine and Support Vector Machine (SVM) classification is also presented."
+1cdff2cd2e3cf8dbeb8f0a42df0cdc77c953dc81,The Emergence of Visual Crowdsensing: Challenges and Opportunities,"The Emergence of Visual Crowdsensing: +Challenges and Opportunities +Bin Guo, Senior Member, IEEE, Qi Han,Member, IEEE , Huihui Chen, Longfei Shangguan, Member, IEEE, +Zimu Zhou, Member, IEEE, and Zhiwen Yu, Senior Member, IEEE"
+1c1e4415f0acf5d536c9579117d326471f0b678b,Temporal Model Adaptation for Person Re-identification,"Temporal Model Adaptation for +Person Re-Identification +Niki Martinel1,3, Abir Das2, +Christian Micheloni1, and Amit K. Roy-Chowdhury3 +University of Udine, 33100 Udine, Italy +University of Massatchussets Lowell, 01852 Lowell, MA, USA +University of California Riverside, 92507 Riverside, CA, USA"
+1ca155a4b65ae19ccb73df48516e4775770a382c,Action Representations in Robotics: A Taxonomy and Systematic Classification,"Action representations in robotics: A +taxonomy and systematic classification +Journal Title +XX(X):1–32 +(cid:13)The Author(s) 2016 +Reprints and permission: +sagepub.co.uk/journalsPermissions.nav +DOI: 10.1177/ToBeAssigned +www.sagepub.com/ +Philipp Zech, Erwan Renaudo, Simon Haller, Xiang Zhang and Justus Piater"
+1c0e8c3fb143eb5eb5af3026eae7257255fcf814,Weakly Supervised Deep Detection Networks,"GOALS +Goal: Learn object detectors using only image-level labels +Why weakly supervised learning? +• annotations are costly +• CNN training is data-hungry +Hypothesis: Pre-trained CNNs should contain meaningful +representations of data such as objects and object parts. +Thus we can exploit this implicit knowledge to learn localizing +objects. +Classification stream +𝑹𝟏 𝑹𝟐 𝑹𝟑 𝑹𝟒 +0.52 0.47 0.04 0.93 +horse +person 0.48 0.53 0.96 0.07 +Normalize over classes +Detection stream +𝑹𝟏 𝑹𝟐 𝑹𝟑 𝑹𝟒 +horse +0.04 0.01 0.07 0.88 +person 0.02 0.03 0.91 0.04"
+1c400dcd6c3e54498d9a7bd5aa4c456079a9d236,Sketch and Validate for Big Data Clustering,"Sketch and Validate for Big Data Clustering +Panagiotis A. Traganitis, Konstantinos Slavakis, Senior Member, IEEE, and Georgios B. Giannakis, Fellow, IEEE"
1c6e22516ceb5c97c3caf07a9bd5df357988ceda,Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data,"NetworkCNNimageslabelsFakeDatasetimages24132labelsTarget NetworkCNNimageslabelsOriginalDatasetFakeDatasetFig.1:Ontheleft,thetargetnetworkistrainedwithanoriginal(confidential)datasetandisservedpubliclyasanAPI,receivingimagesasinputandprovidingclasslabelsasoutput.Ontheright,itispresentedtheprocesstogetstolenlabelsandtocreateafakedataset:randomnaturalimagesaresenttotheAPIandthelabelsareobtained.Afterthat,thecopycatnetworkistrainedusingthisfakedataset.cloud-basedservicestocustomersallowingthemtooffertheirownmodelsasanAPI.Becauseoftheresourcesandmoneyinvestedincreatingthesemodels,itisinthebestinterestofthesecompaniestoprotectthem,i.e.,toavoidthatsomeoneelsecopythem.Someworkshavealreadyinvestigatedthepossibilityofcopyingmodelsbyqueryingthemasablack-box.In[1],forexample,theauthorsshowedhowtoperformmodelextractionattackstocopyanequivalentornear-equivalentmachinelearningmodel(decisiontree,logisticregression,SVM,andmultilayerperceptron),i.e.,onethatachievescloseto100%agreementonaninputspaceofinterest.In[2],theauthorsevaluatedtheprocessofcopyingaNaiveBayesandSVMclassifierinthecontextoftextclassification.Bothworksfocusedongeneralclassifiersandnotondeepneuralnetworksthatrequirelargeamountsofdatatobetrainedleavingthequestionofwhetherdeepmodelscanbeeasilycopied.Althoughthesecondusesdeeplearningtostealtheclassifiers,itdoesnottrytouseDNNstostealfromdeepmodels.Additionally,theseworksfocusoncopyingbyqueryingwithproblemdomaindata.Inrecentyears,researchershavebeenexploringsomeintriguingpropertiesofdeepneuralnetworks[3],[4].More©2018IEEE.Personaluseofthismaterialispermitted.PermissionfromIEEEmustbeobtainedforallotheruses,inanycurrentorfuturemedia,includingreprinting/republishingthismaterialforadvertisingorpromotionalpurposes,creatingnewcollectiveworks,forresaleorredistributiontoserversorlists,orreuseofanycopyrightedcomponentofthisworkinotherworks."
+82d5656c74362d6c5c5fd889fc48f7816bbb033a,Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias,"Contemplating Visual Emotions: Understanding +nd Overcoming Dataset Bias +Rameswar Panda1, Jianming Zhang2, Haoxiang Li3, Joon-Young Lee2, Xin +Lu2, and Amit K. Roy-Chowdhury1 +Department of ECE, UC Riverside. +Adobe Research. +Aibee."
825f56ff489cdd3bcc41e76426d0070754eab1a8,Making Convolutional Networks Recurrent for Visual Sequence Learning,"Making Convolutional Networks Recurrent for Visual Sequence Learning Xiaodong Yang Pavlo Molchanov Jan Kautz NVIDIA"
+82224858677af47b8c836df701eeea8fffaec924,Paper On Person Identification System Using Multi - Model Biometric Based On Face,"International Journal of Science, Engineering and Technology Research (IJSETR) +Volume 6, Issue 4, April 2017, ISSN: 2278 -7798 +Review Paper On Person Identification System +Using Multi-Model Biometric Based On Face +CHETAN JAMDAR1, AMOL BOKE2 +Chetan Jamdar, M. Tech Student, Dept Of ECE, G.H. Raisoni Academy Of Engg. And Technology, Nagpur, +Maharashtra, India. +Guide details: Amol Boke, Assistant Professor, Dept Of ECE, G.H. Raisoni Academy Of Engg. And Technology, +Nagpur, Maharashtra, India"
82d2af2ffa106160a183371946e466021876870d,A Novel Space-Time Representation on the Positive Semidefinite Con for Facial Expression Recognition,"A Novel Space-Time Representation on the Positive Semidefinite Cone for Facial Expression Recognition Anis Kacem1, Mohamed Daoudi1, Boulbaba Ben Amor1, and Juan Carlos Alvarez-Paiva2 IMT Lille Douai, Univ. Lille, CNRS, UMR 9189 – CRIStAL – Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France Univ. Lille, CNRS, UMR 8524, Laboratoire Paul Painlev´e, F-59000 Lille, France."
+82a2a523c4488c34b486c920046f4ebbf8ea828e,Vision-Based System for Human Detection and Tracking in Indoor Environment,"Author manuscript, published in ""International Journal of Social Robotics 2, 1 (2010) 41-52"" +DOI : 10.1007/s12369-009-0040-4"
82eff71af91df2ca18aebb7f1153a7aed16ae7cc,MSU-AVIS dataset : Fusing Face and Voice Modalities for Biometric Recognition in Indoor Surveillance Videos,"MSU-AVIS dataset: Fusing Face and Voice Modalities for Biometric Recognition in Indoor Surveillance Videos Anurag Chowdhury*, Yousef Atoum+, Luan Tran*, Xiaoming Liu*, Arun Ross* *Michigan State University, USA +Yarmouk University, Jordan"
+82d3dc1dd35e7d2d13bc43614b575dce61b0aba3,Head Pose Estimation from Passive Stereo Images,"Head Pose Estimation +from Passive Stereo Images +M. D. Breitenstein1, J. Jensen2, C. Høilund2, T. B. Moeslund2, L. Van Gool1 +ETH Zurich, Switzerland1 Aalborg University, Denmark2"
+820b1349751d7e932b74c3de94b96557fa2534cf,BAM! The Behance Artistic Media Dataset for Recognition Beyond Photography,"BAM! The Behance Artistic Media Dataset for Recognition Beyond Photography +Michael J. Wilber1,2 +Chen Fang1 +John Collomosse1 +Adobe Research +Aaron Hertzmann1 +Hailin Jin1 +Serge Belongie2 +Cornell Tech"
+82ff25b6e7749e0210b2f8d5a0666f3499745154,Adaptive Multiple Kernels with SIR-Particle Filter Based Multi Human Tracking for Occluded Environment,"International Journal of Computational Intelligence and Informatics, Vol. 3: No. 4, January - March 2014 +Adaptive Multiple Kernels with SIR-Particle Filter +Based Multi Human Tracking for Occluded +Environment +T Karpagavalli +Department of Electronics and Communication +KLN College of Information Technology +Sivagangai, Tamilnadu, India +S Appavu alias Balamurugan +Department of Information Technology +KLN College of Information Technology +Sivagangai, Tamilnadu, India"
82c303cf4852ad18116a2eea31e2291325bc19c3,Fusion Based FastICA Method: Facial Expression Recognition,"Journal of Image and Graphics, Volume 2, No.1, June, 2014 Fusion Based FastICA Method: Facial Expression Recognition Humayra B. Ali and David M W Powers Computer Science, Engineering and Mathematics School, Flinders University, Australia Email: {ali0041,"
+82fae97673a353271b1d4c001afda1af6ef6dc23,Semantic contours from inverse detectors,"Semantic Contours from Inverse Detectors∗ +Bharath Hariharan1, Pablo Arbel´aez1, Lubomir Bourdev1 +, Subhransu Maji1 and Jitendra Malik1 +EECS, U.C. Berkeley, Berkeley, CA 94720 +Adobe Systems, Inc., 345 Park Ave, San Jose, CA 95110 +{bharath2, arbelaez, lbourdev, smaji,"
+82ec2ff0bef7db7e5ea48c42336200fb0e44dbf9,Reconstruction of 3D Human Facial Images Using Partial Differential Equations,"Reconstruction of 3D Human Facial Images +Using Partial Differential Equations +University of Bradford/EIMC Department, Richmond Road, BD7 1DP, Bradford, UK +Email: {E.Elyan, +Eyad Elyan, Hassan Ugail +(PDE). Here"
8210fd10ef1de44265632589f8fc28bc439a57e6,Single Sample Face Recognition via Learning Deep Supervised Autoencoders,"Single Sample Face Recognition via Learning Deep Supervised Auto-Encoders Shenghua Gao, Yuting Zhang, Kui Jia, Jiwen Lu, Yingying Zhang"
+82ab819815c86e85128a2a055a0c0fcd1146b696,Sampled Image Tagging and Retrieval Methods on User Generated Content,[cs.CV] 23 Nov 2016
+82f6dad08432a5f1b737ba91dd002ff1f89170f7,c○2013 The Association for Computational Linguistics Order copies of this and other ACL proceedings from:,"ACL201351stAnnualMeetingoftheAssociationforComputationalLinguisticsProceedingsoftheConferenceSystemDemonstrationsAugust4-9,2013Sofia,Bulgaria"
82a4a35b2bae3e5c51f4d24ea5908c52973bd5be,Real-time emotion recognition for gaming using deep convolutional network features,"Real-time emotion recognition for gaming using deep convolutional network features S´ebastien Ouellet"
+8239e4a37825979f66ff0419ccd50a08aebfbadf,Tracing the Colors of Clothing in Paintings with Image Analysis,"Tracing the Colors of Clothing in Paintings with +Image Analysis +Cihan Sarı1, Albert Ali Salah2, and Alkım Almıla Akda˘g Salah3 +Bo˘gazi¸ci University, Systems and Control Engineering, +Bo˘gazi¸ci University, Computer Engineering, +{cihan.sari, +Istanbul S¸ehir University, College of Communications +Introduction +The history of color is full of instances of how and why certain colors become to +e associated with certain concepts, ideas, politics, status and power. Sometimes +the connotations occur arbitrarily, like in the instance when pink was assigned +to baby girls, and blue started to be associated with baby boys at the turn of +9th Century [Paoletti, 1987]. Sometimes though, color associations have very +tangible reasons, such as in the case of Marian blue and why over the centuries +it was reserved only for painting Virgin Mary. The reason is to be found in the +scarcity of the rock lapis lazuli -even more valuable than gold-, from which the +lue pigments were extracted. Individual colors have convoluted and contested +histories, since they have been attached to many symbols at any given time. +John Gage, an art historian who has devoted 30 years of research on the topic +of color, explains the conundrum of what he terms as “politics of color” in a"
82a610a59c210ff77cfdde7fd10c98067bd142da,Human attention and intent analysis using robust visual cues in a Bayesian framework,"UC San Diego UC San Diego Electronic Theses and Dissertations Title @@ -16391,6 +57269,36 @@ Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California"
+825bfa844e4493f205f66782c6ca68aa69018d9c,In-Place Activated BatchNorm for Memory-Optimized Training of DNNs,"In-Place Activated BatchNorm for Memory-Optimized Training of DNNs +Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder +Mapillary Research"
+82a922e775ec3a83d2d5637030860f587697ae42,Dense Multiperson Tracking with Robust Hierarchical Linear Assignment,"Dense Multiperson Tracking with Robust Hierarchical Linear +Assignment +McLaughlin, N., Martinez-del-Rincon, J., & Miller, P. (2015). Dense Multiperson Tracking with Robust +https://doi.org/10.1109/TCYB.2014.2348314 +Published in: +Document Version: +Peer reviewed version +Queen's University Belfast - Research Portal: +Link to publication record in Queen's University Belfast Research Portal +Publisher rights +Copyright 2014 IEEE. +Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this +material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any +opyrighted components of this work in other works. +General rights +Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other +opyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated +with these rights. +Take down policy +The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to"
+82485c89a6b48077b03b65a774fd5768ea768d4d,Unsupervised Adaptive Re-identification in Open World Dynamic Camera Networks,"Unsupervised Adaptive Re-identification in Open World Dynamic Camera +Networks +Rameswar Panda1,∗ Amran Bhuiyan2,∗,† Vittorio Murino2 Amit K. Roy-Chowdhury1 +Department of ECE +Pattern Analysis and Computer Vision (PAVIS) +UC Riverside +Istituto Italiano di Tecnologia, Italy"
829f390b3f8ad5856e7ba5ae8568f10cee0c7e6a,A Robust Rotation Invariant Multiview Face Detection in Erratic Illumination Condition,"International Journal of Computer Applications (0975 – 8887) Volume 57– No.20, November 2012 A Robust Rotation Invariant Multiview Face Detection in @@ -16402,6 +57310,30 @@ Salem" 82f4e8f053d20be64d9318529af9fadd2e3547ef,Technical Report: Multibiometric Cryptosystems,"Technical Report: Multibiometric Cryptosystems Abhishek Nagar, Student Member, IEEE, Karthik Nandakumar, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+82319857563e7b578bcb66ec4df1c85decd6a624,Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure,"Cooperative Tracking of Cyclists Based on +Smart Devices and Infrastructure +G¨unther Reitberger, Maarten Bieshaar, Stefan Zernetsch, Konrad Doll, Bernhard Sick, and Erich Fuchs"
+828b73e8a4d539eeae82601b5f5a4392818c6430,Long-Term Tracking by Decision Making,"UNIVERSITY OF CALIFORNIA, +IRVINE +Long-Term Tracking by Decision Making +DISSERTATION +submitted in partial satisfaction of the requirements +for the degree of +DOCTOR OF PHILOSOPHY +in Computer Science +James Supanˇciˇc, III +Dissertation Committee: +Deva Ramanan, Chair +Charless Fowlkes +Alexander Ihler"
+821ba3eba1e36a29cc482f5378f4a0d0f6893159,Unsupervised Domain Adaptation for Learning Eye Gaze from a Million Synthetic Images: An Adversarial Approach,"Unsupervised Domain Adaptation for Learning Eye Gaze from a +Million Synthetic Images: An Adversarial Approach +Avisek Lahiri∗ +Abhinav Agarwalla +Prabir Kumar Biswas +Dept. of E&ECE, IIT Kharagpur +Dept. of E&ECE, IIT Kharagpur +Dept. of Mathematics, IIT Kharagpur"
82d781b7b6b7c8c992e0cb13f7ec3989c8eafb3d,Robust Facial Expression Recognition Using a State-based Model of Spatially-localized Facial,"REFERENCES Adler A., Youmaran R. and Loyka S., “Towards a Measure of Biometric Information”, Canadian Conference on Electrical and @@ -16422,17 +57354,117 @@ nd Medical Physics, pp. 1-4, 2005. Avraam Kasapis., “MLPs and Pose, Expression Classification”, Proceedings of UNiS Report, pp. 1-87, 2003. Banikazemi M., Poff D. and Abali B., “Storage-based Intrusion"
+82088af865626e2340db12b2e42f3a258053d593,Learning Generative ConvNets via Multi-grid Modeling and Sampling,"Learning Generative ConvNets via Multi-grid Modeling and Sampling +Ruiqi Gao1∗, Yang Lu2∗, Junpei Zhou3, Song-Chun Zhu1, Ying Nian Wu1 +University of California, Los Angeles, USA, 2 Amazon, 3 Zhejiang University, China +{sczhu,"
82417d8ec8ac6406f2d55774a35af2a1b3f4b66e,Some Faces are More Equal than Others: Hierarchical Organization for Accurate and Efficient Large-Scale Identity-Based Face Retrieval,"Some faces are more equal than others: Hierarchical organization for accurate and efficient large-scale identity-based face retrieval Binod Bhattarai1, Gaurav Sharma2, Fr´ed´eric Jurie1, Patrick P´erez2 GREYC, CNRS UMR 6072, Universit´e de Caen Basse-Normandie, France1 Technicolor, Rennes, France2"
+82a4562d9ef19aec3aeaf9bd9f0ac4e09bdf5c86,Putting Out a HIT: Crowdsourcing Malware Installs,"Putting Out a HIT: Crowdsourcing Malware Installs +Chris Kanich +UC San Diego +Stephen Checkoway +UC San Diego +Keaton Mowery +UC San Diego"
+82f6cc54ddb4df9fae811467bdf25f25985c7e2f,CNN features are also great at unsupervised classification,"CNN features are also great at unsupervised +lassification +Joris Guérin∗ +Arts et Métiers ParisTech +59000, Lille, France +Eric Nyiri∗ +Arts et Métiers ParisTech +59000, Lille, France +Olivier Gibaru∗ +Arts et Métiers ParisTech +59000, Lille, France +Stéphane Thiery∗ +Arts et Métiers ParisTech +59000, Lille, France"
+82752700f496d4575163b2c59a547d24eb916baf,Similarity Search on Spatio-Textual Point Sets,"Series ISSN: 2367-2005 +0.5441/002/edbt.2016.31 +o1, {shop,jeans}u2, o2, {football,match,stadium}u3, o3, {shop,market}u2, o5, {hurry, tube, time}u1, o4, {tube,ride}u3, o6, {thames,bridge}u3, o7, {bus,ride}spatial thresholdu2, o8, {football,derby}Figure1:STPSJoinqueryscenario.Multipleobjectsarespatiallyortextuallysimilar,butonlyusersu1andu3haveobjectswhicharemutuallysimilar.dayfrom100millionactiveusers.Useractivitiesintheseplatformsgeneratecontentthathastextualcomponent,e.g.,statusupdates,shortmessages,ortags,and,followingthewidespreadadoptionofGPSinmobiledevices,ageospatialcomponent,e.g.,geotaggedtweets,photos,andusercheck-ins.Thus,theactionsofusersaredocumentedbytheirmessagesinsocialnetworksandassuchgenerate“traces”,whichconsistofspatio-textualobjects.Efficientindexingandqueryingofspatio-textualdatahasreceivedalotofattentionoverthepastyears,duetothehighimportanceofsuchcontentinlocation-basedservices,suchasnearbysearchandrecommendations.Inparticu-lar,multipletypesofspatio-textualquerieshavebeenex-tensivelystudied,includingbooleanrangequeries,top-kqueries,k-nearestneighborqueries,andmorerecently,spatio-textualsimilarityjoins[11,7].Nevertheless,inexistingworks,spatio-textualentitiesaretypicallytreatedasisolatedobservations.Atypicalexamplequeryistofindnearbyrestaurantsorhotelsmatchingcertaincriteria.Theworkin[7]dealswithfindingpairsofentitiesthatarebothspatiallycloseandtextuallysimilar.Exampleusecasesarede-duplicatingPoints-of-Interestacrossdatasets,orfindingmatchingphotostakenatroughlythesameloca-tionandhavingsimilartags.Nowconsiderlookingforsimilarusersinsocialnetworks.Here,auserischaracterizedbythemessagestheygenerateand,ifavailable,respectivelocationinformation.Assuch,eachmessagecanbeconsideredaspatio-textualobject,e.g.,ageotaggedphotoortweet.Witheachuserbeingcharacter-"
+8263834bbe6e986a703370810f9b963e2d25a7f7,Towards Head Motion Compensation Using Multi-Scale Convolutional Neural Networks,"Towards Head Motion Compensation Using Multi-Scale +Convolutional Neural Networks +O. Rajput1∗, N. Gessert1∗, M. Gromniak1, L. Matth¨aus2, A. Schlaefer1 +Institute of Medical Technology, Hamburg University of Technology, Hamburg, Germany +eemagine Medical Imaging Solutions GmbH, Berlin, Germany +Both authors contributed equally. +Contact:"
+8239a0b4cdb480c9fb913c7476f12825418b0909,People detection in RGB-D data,"People Detection in RGB-D Data +Luciano Spinello +Kai O. Arras"
+8291491723d24fd242a3a93248f6475cb084999c,MobileFace: 3D Face Reconstruction with Efficient CNN Regression,"MobileFace: 3D Face Reconstruction +with Efficient CNN Regression +Nikolai Chinaev1, Alexander Chigorin1, and Ivan Laptev1,2 +VisionLabs, Amsterdam, The Netherlands +{n.chinaev, +Inria, WILLOW, Departement d’Informatique de l’Ecole Normale Superieure, PSL +Research University, ENS/INRIA/CNRS UMR 8548, Paris, France"
+823f4300ddf64a95324db89035946638ecb02aa0,MX-LSTM: mixing tracklets and vislets to jointly forecast trajectories and head poses,"MX-LSTM: mixing tracklets and vislets to jointly forecast +trajectories and head poses +Irtiza Hasan1,2, Francesco Setti1, Theodore Tsesmelis1,2,3, Alessio Del Bue3, +Fabio Galasso2, and Marco Cristani1 +University of Verona (UNIVR) +OSRAM GmbH +Istituto Italiano di Tecnologia (IIT)"
826c66bd182b54fea3617192a242de1e4f16d020,Action-vectors: Unsupervised movement modeling for action recognition,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE ICASSP 2017"
+49b2545b8b9ed81cc547ec974e0b61d01b7bc759,Examplers based image fusion features for face recognition,"Examplers based image fusion features for face +recognition +Alex Pappachen James*1 and Sima Dimitrijev2 +*1 Asst. Professor and Group Lead, Machine Intelligence Group, Indian Institute of +Information Technology and Management-Kerala, India. www.mirgroup.co.cc, +Professor and Deputy Director,Queensland Micro- and Nanotechnology Center, Griffith +University, Australia, www.gu.edu.au/qmnc"
+499842b3df387b81dbb2436c764d22b1a3f42cae,Collaborative feature learning from social media,"Collaborative Feature Learning from Social Media +Chen Fang1, Hailin Jin2, Jianchao Yang3, Zhe Lin2 +Department of Computer Science, Dartmouth College. 2Adobe Research. 3Snapchat. +Image feature representation plays an essential role in image recognition +nd related tasks. The current state-of-the-art feature learning paradigm +is supervised learning from labeled data [3], which surpasses other well- +known hand-crafted feature based methods [4, 5]. However, this paradigm +requires large datasets with category labels to train properly, which limits its +pplicability to new problem domains where labels are hard to obtain. +In this paper, we ask an interesting research question: Are category-level +labels the only way for data driven feature learning? +There is a surge of social media websites in the last ten years. Most +social media websites such as Pinterest have been collecting content data +that the users share as well as behavior data of the users. User behavior +data are the activities of individual users, such as likes, comments, or view +histories and they carry rich information about corresponding content data. +For instance, two photos of a similar style on Pinterest tend to be pinned by +the same user. If we aggregate the user behavior data across many users, we +may recover interesting properties of the content. For instance, the photos +liked by a group of users of similar interests tend to have very similar styles."
+4941f92222d660f9b60791ba95796e51a7157077,Conditional CycleGAN for Attribute Guided Face Image Generation,"Conditional CycleGAN for Attribute Guided +Face Image Generation +Yongyi Lu +HKUST +Yu-Wing Tai +Tencent +Chi-Keung Tang +HKUST"
+49004f22a420e0897f7b811239c1e098b0c655bf,Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering,"Out of the Box: Reasoning with Graph Convolution +Nets for Factual Visual Question Answering +Medhini Narasimhan, Svetlana Lazebnik, Alexander G. Schwing +University of Illinois Urbana-Champaign +{medhini2, slazebni,"
4919663c62174a9bc0cc7f60da8f96974b397ad2,Human age estimation using enhanced bio-inspired features (EBIF),"HUMAN AGE ESTIMATION USING ENHANCED BIO-INSPIRED FEATURES (EBIF) Mohamed Y.El Dib and Motaz El-Saban Faculty of Computers and Information, Cairo University, Cairo, Egypt"
+492f3def325296164cd32b80d19a591b72b480cd,Metric Learning,"Computer Vision Group +Metric Learning +Technical University of Munich +Department of Informatics +Computer Vision Group +June 9, 2017 +M.Sc. John Chiotellis: Metric Learning +/ 46"
4967b0acc50995aa4b28e576c404dc85fefb0601,An Automatic Face Detection and Gender Classification from Color Images using Support Vector Machine,"Vol. 4, No. 1 Jan 2013 ISSN 2079-8407 Journal of Emerging Trends in Computing and Information Sciences ©2009-2013 CIS Journal. All rights reserved. @@ -16442,9 +57474,39 @@ Color Images using Support Vector Machine Md. Hafizur Rahman, 2 Suman Chowdhury, 3 Md. Abul Bashar , 2, 3 Department of Electrical & Electronic Engineering, International University of Business Agriculture and Technology, Dhaka-1230, Bangladesh"
+4913477a16c8354f032546b1444728c592823586,Web Image Retrieval Search Engine based on Semantically Shared Annotation,"Web Image Retrieval Search Engine based on Semantically +Shared Annotation +Alaa Riad1, Hamdy Elminir2 and Sameh Abd-Elghany3 +Vice dean of Students Affair, Faculty of Computers and Information Sciences, Mansoura University +Mansoura, Egypt +Mansoura, Egypt +Mansoura, Egypt +Head of Electronic and Communication Dept, Misr Higher Institute of Engineering and Technology +Faculty of Computers and Information Sciences, Mansoura University"
+4914f51bc2f5a35c0d15924e39a51975c53f9753,A 3D Feature Descriptor Recovered from a Single 2D Palmprint Image,"A 3D Feature Descriptor Recovered from a +Single 2D Palmprint Image +Qian Zheng1,2, Ajay Kumar1, and Gang Pan2"
4972aadcce369a8c0029e6dc2f288dfd0241e144,Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories,"Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories Huanhuan Yu, Menglei Hu and Songcan Chen"
+49d4cb2e1788552a04c7f8fec33fbfabb3882995,Visually-Enabled Active Deep Learning for (Geo) Text and Image Classification: A Review,"Article +Visually-Enabled Active Deep Learning for +(Geo) Text and Image Classification: A Review +Liping Yang 1,*, Alan M. MacEachren 1,* ID , Prasenjit Mitra 2 and Teresa Onorati 3 +Department of Geography and Institute for CyberScience, The Pennsylvania State University, +University Park, PA 16802, USA +College of Information Sciences and Technology, The Pennsylvania State University, University Park, +PA 16802, USA; +Computer Science Department, Universidad Carlos III de Madrid, 28911-Leganés, Madrid, Spain; +* Correspondence: (L.Y.); (A.M.M.) +Received: 29 December 2017; Accepted: 17 February 2018; Published: 20 February 2018"
+494c1630c93e74aca3169ae33734f2f733c95e05,The Iris Challenge Evaluation 2005,"The Iris Challenge Evaluation 2005 +P. Jonathon Phillips, Kevin W. Bowyer, Patrick J. Flynn, Xiaomei Liu, W. Todd Scruggs"
+49f22f29e57f5867b47348555136844ffa6c6603,Beyond Lesion-Based Diabetic Retinopathy: A Direct Approach for Referral,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012 +Beyond Lesion-based Diabetic Retinopathy: +Direct Approach for Referral +Ramon Pires, Member, IEEE, Sandra Avila, Member, IEEE, Herbert F. Jelinek, Member, IEEE, +Jacques Wainer, Eduardo Valle, and Anderson Rocha, Senior Member, IEEE"
49e85869fa2cbb31e2fd761951d0cdfa741d95f3,Adaptive Manifold Learning,"Adaptive Manifold Learning Zhenyue Zhang, Jing Wang, and Hongyuan Zha"
490a217a4e9a30563f3a4442a7d04f0ea34442c8,An SOM-based Automatic Facial Expression Recognition System,"International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), Vol.2, No.4, August 2013 @@ -16456,9 +57518,27 @@ Department of Computer Science &InformationEngineering,National Central University,Taiwan, R.O.C. Cathay General Hospital, Taiwan, R.O.C. E-mail:"
+4987ac5638e1fdb116cc76626465f166998d7536,Polysemous Codes,"Polysemous codes +Matthijs Douze, Herv´e J´egou and Florent Perronnin +Facebook AI Research"
+494e736c05ddf500830e9c51b5fb42be9b9bff1a,Learning Depth from Monocular Videos using Direct Methods,
49a7949fabcdf01bbae1c2eb38946ee99f491857,A concatenating framework of shortcut convolutional neural networks,"A CONCATENATING FRAMEWORK OF SHORTCUT CONVOLUTIONAL NEURAL NETWORKS Yujian Li Ting Zhang, Zhaoying Liu, Haihe Hu"
+49b3f6d8712c01f315686b6b8541eda8c5ee428a,Virtual friend or threat? The effects of facial expression and gaze interaction on psychophysiological responses and emotional experience.,"Copyright r 2009 Society for Psychophysiological Research +DOI: 10.1111/j.1469-8986.2009.00831.x +Virtual friend or threat? The effects of facial expression +nd gaze interaction on psychophysiological responses +nd emotional experience +FRANZISKA SCHRAMMEL,a SEBASTIAN PANNASCH,a SVEN-THOMAS GRAUPNER,a +ANDREAS MOJZISCH,b and BORIS M. VELICHKOVSKYa +Institute for Psychology III, Technische Universitaet Dresden, Germany +Institute for Psychology, Georg-August-University Goettingen, Germany"
+49957368eceaa751c0b9c49251512ca6a8800cff,Accurate Object Localization with Shape Masks,"Accurate Object Localization with Shape Masks +Marcin Marsza(cid:7)ek +Cordelia Schmid +INRIA, LEAR - LJK +665 av de l’Europe, 38330 Montbonnot, France"
499343a2fd9421dca608d206e25e53be84489f44,Face Recognition with Name Using Local Weber‟s Law Descriptor,"Anil Kumar.C, et.al, International Journal of Technology and Engineering Science [IJTES]TM Volume 1[9], pp: 1371-1375, December 2013 Face Recognition with Name Using Local Weber‟s @@ -16467,6 +57547,18 @@ C.Anil kumar,2A.Rajani,3I.Suneetha M.Tech Student,2Assistant Professor,3Associate Professor Department of ECE, Annamacharya Institute of Technology and Sciences, Tirupati, India-517520 on FERET"
+490fa9ee39614e1ef1d74162e698e4a1f0e5f916,In Good Shape: Robust People Detection based on Appearance and Shape,"PISHCHULIN et al.: PEOPLE DETECTION USING APPEARANCE AND SHAPE +In Good Shape: Robust People Detection +ased on Appearance and Shape +Computer Vision and +Multimodal Computing +MPI Informatics +Saarbrücken, Germany +Leonid Pishchulin +Arjun Jain +Christian Wojek +Thorsten Thormählen +Bernt Schiele"
498fd231d7983433dac37f3c97fb1eafcf065268,Linear Disentangled Representation Learning for Facial Actions,"LINEAR DISENTANGLED REPRESENTATION LEARNING FOR FACIAL ACTIONS Xiang Xiang1 and Trac D. Tran2 Dept. of Computer Science @@ -16481,6 +57573,38 @@ Support Vector Machine for age classification Sangeeta Agrawal1, Rohit Raja2, Sonu Agrawal3 Assistant Professor, CSE, RSR RCET, Kohka Bhilai ,3 Sr. Assistant Professor, CSE, SSCET, Junwani Bhilai"
+491cf4d86ed895000a35ba96f46261984c0bdf7c,Facial Expression Recognition for Domestic Service Robots,"Facial Expression Recognition for Domestic +Service Robots +Geovanny Giorgana and Paul G. Ploeger +Bonn-Rhein-Sieg University of Applied Sciences, +Grantham-Allee 20 53757 Sankt Augustin, Germany"
+490a0b6ff5b982e884622bb9c81250f05c069f32,Template Aging in 3 D and 2 D Face Recognition,"Template Aging in 3D and 2D Face Recognition +Ishan Manjani∗ +Hakki Sumerkan† +Patrick J. Flynn† +Kevin W. Bowyer†"
+4991dcef497ddd7ea115663985a9e0635494a95d,Detecting Group Activities With Multi-Camera Context,"Detecting Group Activities With +Multi-Camera Context +Zheng-Jun Zha, Member, IEEE, Hanwang Zhang, Meng Wang, Member, IEEE, Huanbo Luan, and Tat-Seng Chua"
+49d7fd8975413fb2912e111093749733712210dd,Vpliv kakovosti vhodnih slik na zanesljivost samodejnega razpoznavanja obrazov,"Elektrotehniški vestnik 74(3): 145-150, 2007 +Electrotechnical Review: Ljubljana, Slovenija +Vpliv kakovosti vhodnih slik na zanesljivost samodejnega +razpoznavanja obrazov +Vitomir Štruc, Nikola Paveši(cid:29) +Univerza v Ljubljani, Fakulteta za elektrotehniko, Tržaška 25, 1001 Ljubljana, Slovenija +E-pošta: +Povzetek. Zanesljivost samodejnega razpoznavanja obrazov je odvisna od številnih dejavnikov, med katerimi so +najpomembnejši natan(cid:24)nost dolo(cid:24)itve slikovnega obmo(cid:24)ja obraza in njegova odpornost na slabšo kakovost slik, +izbira ustreznega postopka izpeljave obraznih zna(cid:24)ilk ter uporaba primernega algoritma za izra(cid:24)un podobnosti in +sprejetje odlo(cid:24)itve o identiteti osebe. V (cid:24)lanku predstavljamo rezultate vrednotenja napak, ki jih v biometri(cid:24)ni +sistem vnašajo razli(cid:24)ne degradacije vhodnih slik. Njihov vpliv smo prou(cid:24)ili za tri na podro(cid:24)ju razpoznavanja +obrazov pogosteje uporabljene postopke izpeljave zna(cid:24)ilk (analizo glavnih komponent – PCA, analizo linearne +diskriminante – LDA ter analizo neodvisnih komponent – ICA), pri (cid:24)emer smo za dolo(cid:24)itev zanesljivosti +razpoznavanja (verifikacije) uporabili bazo XM2VTS; za ovrednotenje napak, ki jih v biometri(cid:24)ni sistem vnašajo +spremembe v kakovosti slik, pa njene degradirane razli(cid:24)ice. +Klju ne besede: razpoznavanje obrazov, analiza glavnih komponent, analiza linearne diskriminante, analiza +neodvisnih komponent, zanesljivost razpoznavanja, kakovost vhodnih slik +Impact of image degradations on the face recognition accuracy"
49df381ea2a1e7f4059346311f1f9f45dd997164,Client-Specific Anomaly Detection for Face Presentation Attack Detection,"On the Use of Client-Specific Information for Face Presentation Attack Detection Based on Anomaly Detection @@ -16503,6 +57627,25 @@ Facial Communicative Signals Valence Recognition in Task-Oriented Human-Robot Interaction Christian Lang · Sven Wachsmuth · Marc Hanheide · Heiko Wersing Received: date / Accepted: date"
+403b3d0594989629c95e5bc5230d4ccb1691f255,Automatic detection of pain from spontaneous facial expressions,"Meawad, F., Yang, S.-Y. and Loy, F. L. (2017) Automatic Detection of +Pain from Spontaneous Facial Expressions. In: 19th ACM International +Conference on Multimodal Interaction (ICMI 2017), Glasgow, Scotland, +3-17 Nov 2017, pp. 397-401. ISBN 9781450355438 +(doi:10.1145/3136755.3136794) +This is the author’s final accepted version. +There may be differences between this version and the published version. +You are advised to consult the publisher’s version if you wish to cite from +http://eprints.gla.ac.uk/151491/ +Deposited on: 22 December 2017 +Enlighten – Research publications by members of the University of Glasgow +http://eprints.gla.ac.uk"
+40ce2567ccc2552287f8a1c25e9f6086efa6bf8f,Identification and evaluation of children with autism spectrum disorders.,"CLINICAL REPORT +Identification and Evaluation of +Children With Autism Spectrum +Disorders +Chris Plauche´ Johnson, MD, MEd, Scott M. Myers, MD, and the Council on Children With Disabilities +Guidance for the Clinician in Rendering +Pediatric Care"
40b0fced8bc45f548ca7f79922e62478d2043220,Do Convnets Learn Correspondence?,"Do Convnets Learn Correspondence? Trevor Darrell Jonathan Long @@ -16533,6 +57676,33 @@ it resimler daha çok olup, bu resimler birbirine diğerlerine olduğundan daha çok benzeyeceklerdir. Bu nedenle, yüzler rasındaki benzerlikler çizgesel olarak betimlendiğinde , irbirine en çok benzeyen yüzler bu çizgede en yoğun bileşen"
+40a0e080a01094cdb2174e9154540c217d3f9440,Improved Security Aspects on Microsofts Two -layer Captcha,"Vol-2 Issue-5 2017 +IJARIIE-ISSN(O)-2395-4396 +IMPROVED SECURITY ASPECTS ON +MICROSOFTS +TWO -LAYER CAPTCHA +Rachana.B.S, Dhruthi.S, Swarna.R, Chandan.A +Rachana.B.S, Asst.Prof, ISE, APSCE, B’lore, Karnataka, INDIA +Dhruthi S, Student, ISE,, APSCE, Karnataka, India +Swarna R, Student, ISE, APSCE, Karnataka, India +Chandana A, Student, ISE, APSCE, Karnataka, India"
+404c7839afe2fec48a06f83d2a532c05ad8ba0d3,Vehicle Classification using Transferable Deep Neural Network Features,"Vehicle Classification using Transferable Deep +Neural Network Features +Yiren Zhou, Ngai-Man Cheung"
+40041b80cef6dc23946ffa9628b6ac3b8dcc971a,Parallel Separable 3D Convolution for Video and Volumetric Data Understanding,"GONDA, WEI, PARAG, PFISTER: PARALLEL SEPARABLE 3D CONVOLUTION +Parallel Separable 3D Convolution for Video +nd Volumetric Data Understanding +Harvard John A. Paulson School of +Engineering and Applied Sciences +Camabridge MA, USA +Felix Gonda +Donglai Wei +Toufiq Parag +Hanspeter Pfister"
+40f7ea135907d2f4abeae0475d9a88477239d504,Multimodal Explanations: Justifying Decisions and Pointing to the Evidence,"Multimodal Explanations: Justifying Decisions and Pointing to the Evidence +Dong Huk Park1, Lisa Anne Hendricks1, Zeynep Akata2,3, Anna Rohrbach1,3, +Bernt Schiele3, Trevor Darrell1, and Marcus Rohrbach4 +EECS, UC Berkeley, 2University of Amsterdam, 3MPI for Informatics, 4Facebook AI Research"
402f6db00251a15d1d92507887b17e1c50feebca,3D Facial Action Units Recognition for Emotional Expression,"D Facial Action Units Recognition for Emotional Expression Norhaida Hussain1, Hamimah Ujir, Irwandi Hipiny and Jacey-Lynn Minoi2 @@ -16547,12 +57717,72 @@ Then the facial distances are trained using Support Vector Machine (SVM) and Neu using SVM is presented with several different SVM kernels while result using NN is presented for each training, validation nd testing phase. Keywords: Facial action units recognition, 3D AU recognition, facial expression"
+40932ccdd7cda22e90c1e16b4a4dc4930b122a9c,Learning to Look around Objects for Top-View Representations of Outdoor Scenes,"Learning to Look around Objects for Top-View +Representations of Outdoor Scenes +Samuel Schulter1,† Menghua Zhai2,† +Nathan Jacobs2 +Manmohan Chandraker1,3 +NEC-Labs1, Computer Science University of Kentucky2, UC San Diego3"
+4053e3423fb70ad9140ca89351df49675197196a,Robust Face Detection Using the Hausdorff Distance,"(cid:13) In Proc. Third International Conference on Audio- and Video-based +Biometric Person Authentication, Springer, Lecture Notes in Computer +Science, LNCS-2091, pp. 90–95, Halmstad, Sweden, 6–8 June 2001. +Robust Face Detection +Using the Hausdorff Distance +Oliver Jesorsky, Klaus J. Kirchberg, and Robert W. Frischholz +BioID AG, Berlin, Germany +WWW home page: http://www.bioid.com"
+409220cf5137d6dc6c85f440d618e44d244f402e,Randomized Algorithms for Large-scale Strongly Over-determined Linear Regression Problems a Dissertation Submitted to the Institute for Computational and Mathematical Engineering and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree Of,"RANDOMIZED ALGORITHMS FOR LARGE-SCALE STRONGLY +OVER-DETERMINED LINEAR REGRESSION PROBLEMS +A DISSERTATION +SUBMITTED TO THE INSTITUTE FOR +COMPUTATIONAL AND MATHEMATICAL ENGINEERING +AND THE COMMITTEE ON GRADUATE STUDIES +OF STANFORD UNIVERSITY +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +DOCTOR OF PHILOSOPHY +Xiangrui Meng +June 2014"
+406caefc7f51e8a16833402e4757704d5d84a1f8,Dual-Tree Complex Wavelets Transform Based Facial Expression Recognition using Principal Component Analysis ( PCA ) and Local Binary Pattern ( LBP ),"ISSN XXXX XXXX © 2017 IJESC +Research Article Volume 7 Issue No.4 +Dual-Tree Complex Wavelets Transform Based Facial Expression +Recognition using Principal Component Analysis (PCA) and Local +Binary Pattern(LBP) +Fahad Abdu Jibrin1, Abubakar Sadiq Muhammad2 +Department of Electrical Engineering1, Department of Computer Engineering2 +School of Technology, Kano State Polytechnic, Nigeria"
+40d4fab85e2e1557e61d03b92429d64c6efba101,Detection-based multi-human tracking using a CRF model,"Detection-Based Multi-Human Tracking Using a CRF Model +Alexandre Heili1,2 +Jean-Marc Odobez1,2 +Idiap Research Institute – CH-1920 Martigny, Switzerland +Cheng Chen1 +´Ecole Polytechnique F´ed´erale de Lausanne – CH-1015, Lausanne, Switzerland"
+40000b058cf80b7983a2c0f96562368a40a04580,Predicting human mobility through the assimilation of social media traces into mobility models,"Predicting human mobility through the assimilation of social media +traces into mobility models +Mariano G. Beir´o1 +Andr´e Panisson1 +Michele Tizzoni1 +Ciro Cattuto1 +ISI Foundation, Turin, Italy"
40fb4e8932fb6a8fef0dddfdda57a3e142c3e823,A mixed generative-discriminative framework for pedestrian classification,"A Mixed Generative-Discriminative Framework for Pedestrian Classification Markus Enzweiler1 Dariu M. Gavrila2,3 Image & Pattern Analysis Group, Dept. of Math. and Comp. Sc., Univ. of Heidelberg, Germany Environment Perception, Group Research, Daimler AG, Ulm, Germany Intelligent Systems Lab, Faculty of Science, Univ. of Amsterdam, The Netherlands"
+40f5ae73e598114edab3ddaefc38fbdbf5c114b9,Optical Flow Based Face Recognition under Expression Variations,"International Journal of Information Science and Intelligent System, 3(2): 1-12, 2014 +Optical Flow Based Face Recognition under +Expression Variations +Vimala K1,∗, Dr.V.Kalaivani2, V.Anusuya Devi3 +1Assistant Professor, Department of CSE(PG),National Engineering College , Kovilpatti, India +2 Associate Professor(SG) and Head, Department of CSE(PG),National Engineering College India , +Assistant Professor, Department of CSE(PG),National Engineering College, Kovilpatti, India"
+409ff083816d8357fe839e3ea0e62d648a5532aa,SEMDIAL 2016 JerSem Proceedings of the 20th Workshop on the Semantics and Pragmatics of Dialogue,"SEMDIAL 2016 +JerSem +Proceedings of the 20th Workshop on +the Semantics and Pragmatics of Dialogue +Julie Hunter, Mandy Simons, and Matthew Stone (eds.) +New Brunswick, NJ, 16–18 July 2016"
40dd2b9aace337467c6e1e269d0cb813442313d7,Localizing spatially and temporally objects and actions in videos. (Localiser spatio-temporallement des objets et des actions dans des vidéos),"This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following terms and conditions of use: @@ -16566,6 +57796,32 @@ The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the author. When referring to this work, full bibliographic details including the author, title, warding institution and date of the thesis must be given."
+40536b0cc73fda29a335c6ecf9ce891dcb6d04cd,Face Detection Algorithms: A Comparative Study,"Face Detection Algorithms: A Comparative Study +Kapil Kumar Gupta1, M. Rizwan Beg 2 , Jitendra Kumar Niranjan3 +1 Department of Computer Science & Engg., Integral University, +Lucknow, Uttar Pradesh, 226001, India +Department of Computer Science & Engg., Integral University, +Lucknow, Uttar Pradesh, 226001, India +Department of Computer Science & Engg, IMS Engineering College +Ghaziabad, Uttar Pradesh 201009, India"
+405a70c184e00eefcf797a0e842578ea0b51f6cd,Learning a Family of Detectors via Multiplicative Kernels,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +Learning a Family of Detectors +via Multiplicative Kernels +Quan Yuan, Member, IEEE, Ashwin Thangali, Student Member, IEEE, +Vitaly Ablavsky, Student Member, IEEE, and Stan Sclaroff, Senior Member, IEEE"
+40c3b350008ada8f3f53a758e69992b6db8a8f95,Discriminative Decorrelation for Clustering and Classification,"Discriminative Decorrelation for Clustering and +Classification +Bharath Hariharan1, Jitendra Malik1, and Deva Ramanan2 +Univerisity of California at Berkeley, Berkeley, CA, USA +University of California at Irvine, Irvine, CA, USA"
+40b87d3b1e3dbbc82fb7d786004fe202e131c045,Multi-modal Egocentric Activity Recognition using Audio-Visual Features,"Submitted to IEEE Transactions on Human-Machine Systems +Multi-modal Egocentric Activity Recognition +using Audio-Visual Features +Mehmet Ali Arabacı, Fatih Özkan, Elif Surer, Peter Jančovič, Alptekin Temizel"
+40229a034d2fcddc3df32f906ec4ef6a3b3e017e,A semi-automated system for accurate gaze coding in natural dyadic interactions,"A Semi-Automated System for Accurate Gaze Coding +in Natural Dyadic Interactions +Kenneth A. Funes-Mora, Laurent Nguyen, Daniel Gatica-Perez, Jean-Marc Odobez +Idiap Research Institute and École Polytechnique Fédérale de Lausanne (EPFL), Switzerland"
40a34d4eea5e32dfbcef420ffe2ce7c1ee0f23cd,Bridging Heterogeneous Domains With Parallel Transport For Vision and Multimedia Applications,"Bridging Heterogeneous Domains With Parallel Transport For Vision and Multimedia Applications Raghuraman Gopalan @@ -16592,11 +57848,61 @@ sking the patients to fill out a questionnaire, as it is currently done [7]. Fa recognition may enable a new generation of teaching systems to adapt to the expression of their students in the way good teachers do [61]. Expression recognition could be used to assess the fatigue of drivers and air-pilots [58, 59]. Daily-life robots with automatic"
+401f056e1017151018e83d2b13b5eaec573b4dbc,Rapid and accurate face depth estimation in passive stereo systems,"Noname manuscript No. +(will be inserted by the editor) +Rapid and accurate face depth estimation in passive +stereo systems +Amel AISSAOUI · Jean MARTINET · +Chaabane DJERABA +Received: date / Accepted: date"
+40010e1918e1f342b14c8ec74e570101f07471b2,Flower Categorization using Deep Convolutional Neural Networks,"Flower Categorization using Deep Convolutional Neural Networks +Ayesha Gurnani +Viraj Mavani +Vandit Gajjar +Yash Khandhediya +L. D. College of Engineering +L. D. College of Engineering +L. D. College of Engineering +L. D. College of Engineering"
+40a63746a710baf4a694fd5a4dd8b5a3d9fc2846,Invertible Conditional GANs for image editing,"Invertible Conditional GANs for image editing +Guim Perarnau, Joost van de Weijer, Bogdan Raducanu +Computer Vision Center +Barcelona, Spain +Jose M. Álvarez +Data61 CSIRO +Canberra, Australia"
+40377a1bc15a9ec28ea54cc53d5cf0699365634f,Некооперативная Биометрическая Идентификация По 3d- Моделям Лица С Использованием Видеокамер Высокого Разрешения,"НЕКООПЕРАТИВНАЯ БИОМЕТРИЧЕСКАЯ ИДЕНТИФИКАЦИЯ ПО 3D- +МОДЕЛЯМ ЛИЦА С ИСПОЛЬЗОВАНИЕМ ВИДЕОКАМЕР ВЫСОКОГО +РАЗРЕШЕНИЯ +А.И. Манолов, А.Ю. Соколов, О.В. Степаненко, А.C. Тумачек, А.В.Тяхт, А. К. Цискаридзе, +Д.Н. Заварикин, А.А. Кадейшвили, +Компания Vocord +Аннотация +Получены результаты по распознаванию лиц, основанные +на 3D реконструкции без использования какой-либо +структурированной подсветки. 3D реконструкция основана +на использовании камер высокого разрешения. +Вероятность распознавания составляет 92-98%. +Ключевые слова: 3D реконструкция, 3D распознавание +. ВВЕДЕНИЕ +Системам распознавания лиц, основанным на двумерных +изображениях, присущи определенные недостатки. Такие +системы чувствительны к изменениям яркости. Свет, +собранный с лица, является функцией геометрии лица, +отражательной способности лица, свойствами источника +света и свойствами камеры. С учетом этого, сложно создать"
40b10e330a5511a6a45f42c8b86da222504c717f,Implementing the Viola-Jones Face Detection Algorithm,"Implementing the Viola-Jones Face Detection Algorithm Ole Helvig Jensen Kongens Lyngby 2008 IMM-M.Sc.-2008-93"
+400aa5cb2fec558f7827c3638993bae34752ff31,Assessing post-detection filters for a generic pedestrian detector in a tracking-by-detection scheme,"(cid:13)2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including +reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, +or reuse of any copyrighted component of this work in other works. +Assessing Post-Detection Filters for a Generic Pedestrian Detector in a +Tracking-By-Detection Scheme +Volker Eiselein, Erik Bochinski and Thomas Sikora +Communication Systems Group, Technische Universit¨at Berlin"
40ca925befa1f7e039f0cd40d57dbef6007b4416,Sampling Matters in Deep Embedding Learning,"Sampling Matters in Deep Embedding Learning Chao-Yuan Wu∗ UT Austin @@ -16610,6 +57916,26 @@ UT Austin" Recognition and Eye-Gaze Tracking Soo-Mi Choi and Yong-Guk Kim School of Computer Engineering, Sejong University, Seoul, Korea"
+40f2b3af6b55efae7992996bd0c474a9c1574008,xytocin Increases Retention of Social Cognition n Autism,"ARTICLE IN PRESS +Oxytocin Increases Retention of Social Cognition +in Autism +Eric Hollander, Jennifer Bartz, William Chaplin, Ann Phillips, Jennifer Sumner, Latha Soorya, +Evdokia Anagnostou, and Stacey Wasserman +Background: Oxytocin dysfunction might contribute to the development of social deficits in autism, a core symptom domain and +potential target for intervention. This study explored the effect of intravenous oxytocin administration on the retention of social +information in autism. +Methods: Oxytocin and placebo challenges were administered to 15 adult subjects diagnosed with autism or Asperger’s disorder, and +omprehension of affective speech (happy, indifferent, angry, and sad) in neutral content sentences was tested. +Results: All subjects showed improvements in affective speech comprehension from pre- to post-infusion; however, whereas those who +received placebo first tended to revert to baseline after a delay, those who received oxytocin first retained the ability to accurately assign +emotional significance to speech intonation on the speech comprehension task. +Conclusions: These results are consistent with studies linking oxytocin to social recognition in rodents as well as studies linking +oxytocin to prosocial behavior in humans and suggest that oxytocin might facilitate social information processing in those with autism. +These findings also provide preliminary support for the use of oxytocin in the treatment of autism. +Key Words: Autism, oxytocin, neuropeptide, social cognition, +ffective speech +A utism is a developmental disorder characterized by ab- +normalities in speech and communication, impaired so-"
40f127fa4459a69a9a21884ee93d286e99b54c5f,Optimizing Apparent Display Resolution Enhancement for Arbitrary Videos,"Optimizing Apparent Display Resolution Enhancement for Arbitrary Videos Michael Stengel*, Member, IEEE, Martin Eisemann, Stephan Wenger, @@ -16617,11 +57943,74 @@ Benjamin Hell, Marcus Magnor, Member, IEEE" 401e6b9ada571603b67377b336786801f5b54eee,Active Image Clustering: Seeking Constraints from Humans to Complement Algorithms,"Active Image Clustering: Seeking Constraints from Humans to Complement Algorithms November 22, 2011"
+40248cd4a742cb33c14e835fe6b847ad3f8d5b96,Learning View-Specific Deep Networks for Person Re-Identification,"Learning View-Specific Deep Networks for Person +Re-Identification +Zhanxiang Feng, Jianhuang Lai, and Xiaohua Xie"
+403e7fed4fa1785af8309b1c4c736d98fa75be5b,Social status gates social attention in monkeys,"Magazine +Social status +gates social +ttention in +monkeys +Stephen V. Shepherd1, +Robert O. Deaner1 and +Michael L. Platt1,2,3 +Humans rapidly shift attention in +the direction other individuals are +looking, following gaze in a +manner suggestive of an +obligatory social reflex [1–4]. +Monkeys’ attention also follows +gaze, and the similar magnitude +nd time-course of gaze- +following in rhesus macaques and +humans [5] is indicative of shared +neural mechanisms. Here we +show that low-status male rhesus"
+40f6c9355dbf01a240b4c26b0fd00b5cfbd5f67d,An eye-tracking method to reveal the link between gazing patterns and pragmatic abilities in high functioning autism spectrum disorders,"ORIGINAL RESEARCH ARTICLE +published: 14 January 2015 +doi: 10.3389/fnhum.2014.01067 +An eye-tracking method to reveal the link between gazing +patterns and pragmatic abilities in high functioning autism +spectrum disorders +Ouriel Grynszpan 1* and Jacqueline Nadel 2 +Institut des Systèmes Intelligents et de Robotique (ISIR), Université Pierre et Marie Curie, Centre National de la Recherche Scientifique, Paris, France +Centre Emotion, Hôpital de La Salpêtrière, Paris, France +Edited by: +John J. Foxe, Albert Einstein +College of Medicine, USA +Reviewed by: +Hans-Peter Frey, Albert Einstein +College of Medicine, USA +Julia Irwin, Haskins Laboratories, +Karri Gillespie-Smith, University of +West of Scotland, UK +*Correspondence: +Ouriel Grynszpan, Institut des"
+40bd5d4b01c89e84fe2b0f6b1cc22657bf4e8d80,Toward Unconstrained Fingerprint Recognition: A Fully Touchless 3-D System Based on Two Views on the Move,"Toward Unconstrained Fingerprint Recognition: +Fully Touchless 3-D System +Based on Two Views on the Move +Ruggero Donida Labati, Member, IEEE, Angelo Genovese, Member, IEEE, +Vincenzo Piuri, Fellow, IEEE, and Fabio Scotti, Senior Member, IEEE"
+2eef20a11324686099ee6f9b1a7613444b0d2112,Dual-Path Convolutional Image-Text Embedding with Instance Loss,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Dual-Path Convolutional Image-Text Embeddings +with Instance Loss +Zhedong Zheng, Liang Zheng, Michael Garrett, Yi Yang, Yi-Dong Shen"
+2e53a5dbadfd30b834feea80c365ffff3925eb76,The role of alexithymia in reduced eye-fixation in Autism Spectrum Conditions.,"23Journal of Autism andDevelopmental Disorders ISSN 0162-3257Volume 41Number 11 J Autism Dev Disord (2011)41:1556-1564DOI 10.1007/s10803-011-1183-3The Role of Alexithymia in Reduced Eye-Fixation in Autism Spectrum ConditionsGeoffrey Bird, Clare Press & DanielC. Richardson"
2e8e6b835e5a8f55f3b0bdd7a1ff765a0b7e1b87,Pointly-Supervised Action Localization,"International Journal of Computer Vision manuscript No. (will be inserted by the editor) Pointly-Supervised Action Localization Pascal Mettes · Cees G. M. Snoek Received: date / Accepted: date"
+2e10560579f2bdeae0143141f26bd9f0a195b4b7,Mixed Precision Training,"Published as a conference paper at ICLR 2018 +MIXED PRECISION TRAINING +Sharan Narang∗, Gregory Diamos, Erich Elsen† +Baidu Research +{sharan, +Paulius Micikevicius∗, Jonah Alben, David Garcia, Boris Ginsburg, Michael Houston, +Oleksii Kuchaiev, Ganesh Venkatesh, Hao Wu +NVIDIA +{pauliusm, alben, dagarcia, bginsburg, mhouston, +okuchaiev, gavenkatesh,"
2eb37a3f362cffdcf5882a94a20a1212dfed25d9,Local Feature Based Face Recognition,"Local Feature Based Face Recognition Sanjay A. Pardeshi and Sanjay N. Talbar R.I.T., Rajaramnagar and S.G.G.S. COE &T, Nanded @@ -16642,6 +58031,10 @@ living person based on its facial characteristics. In last decade, major advances occurred in face recognition, with many systems capable of chieving recognition rates greater than 90%. However real-world scenarios remain a hallenge, because face acquisition process can undergo to a wide range of variations. Hence"
+2e0481def73dbd3e6dfb447c1c3c8afdfaf9b7ec,UPC System for the 2015 MediaEval Multimodal Person Discovery in Broadcast TV task,"UPC System for the 2015 MediaEval Multimodal Person +Discovery in Broadcast TV task +M. India, D. Varas, V. Vilaplana, J.R. Morros, J. Hernando +Universitat Politecnica de Catalunya, Spain"
2e5cfa97f3ecc10ae8f54c1862433285281e6a7c,Generative Adversarial Networks for Improving Face Classification,"Generative Adversarial Networks for Improving Face Classification JONAS NATTEN SUPERVISOR Morten Goodwin, PhD University of Agder, 2017 Faculty of Engineering and Science Department of ICT"
2e091b311ac48c18aaedbb5117e94213f1dbb529,Collaborative Facial Landmark Localization for Transferring Annotations Across Datasets,"Collaborative Facial Landmark Localization for Transferring Annotations Across Datasets @@ -16656,6 +58049,30 @@ Neeraja K.C.#1, RameshMarivendan E.#2, #1#2ECE Department, Dhanalakshmi Srinivasan College of Engineering, Coimbatore,Tamilnadu,India. Anna University."
+2eefaa9c278346b9e0eb51085cff490b0a43688f,TEMPO: Feature-Endowed Teichmüller Extremal Mappings of Point Clouds,"Vol. 9, No. 4, pp. 1922–1962 +(cid:13) 2016 Society for Industrial and Applied Mathematics +TEMPO: Feature-Endowed Teichm¨uller Extremal Mappings of Point Clouds∗ +Ting Wei Meng† , Gary Pui-Tung Choi‡ , and Lok Ming Lui†"
+2ea8029283e6bbb03c023070d042cb19647f06af,Neurobiological mechanisms associated with facial affect recognition deficits after traumatic brain injury,"Neurobiological mechanisms associated with facial affect recognition deficits after +traumatic brain injury +Dawn Neumann, PhD +Indiana University School of Medicine +Department of Physical Medicine and Rehabilitation +Rehabilitation Hospital of Indiana +141 Shore Drive +Indianapolis, IN 46254 +Email: +Phone: 317-329-2188 +Brenna C. McDonald, PsyD, MBA +Indiana University School of Medicine +Department of Radiology and Imaging Sciences +Indiana University Center for Neuroimaging +55 W. 16th St., GH Suite 4100 +Indianapolis, IN 46202 +Email: +John West, MS +Indiana University School of Medicine +Department of Radiology and Imaging Sciences"
2e68190ebda2db8fb690e378fa213319ca915cf8,Generating Videos with Scene Dynamics,"Generating Videos with Scene Dynamics Carl Vondrick Hamed Pirsiavash @@ -16663,16 +58080,98 @@ Antonio Torralba" 2e0d56794379c436b2d1be63e71a215dd67eb2ca,Improving precision and recall of face recognition in SIPP with combination of modified mean search and LSH,"Improving precision and recall of face recognition in SIPP with combination of modified mean search and LSH Xihua.Li"
+2ed9a69ee6509c0b3fe5a51d1116dccc877653ba,Reconstruction and Analysis of Shapes from 3D Scans,"Reconstruction and Analysis +of Shapes from 3D Scans"
+2e7874ec37df91db1934d61d9e1181de5e4efb36,COCO-Stuff: Thing and Stuff Classes in Context,"COCO-Stuff: Thing and Stuff Classes in Context +Holger Caesar1 +Jasper Uijlings2 Vittorio Ferrari1 2 +University of Edinburgh1 Google AI Perception2"
+2e585adbe1f434396ca6a669dd91914d4d4bf42a,Early Prediction for Physical Human Robot Collaboration in the Operating Room,"TO APPEAR IN AUTONOMOUS ROBOTS, SPECIAL ISSUE IN LEARNING FOR HUMAN-ROBOT COLLABORATION +Early Prediction for Physical Human Robot +Collaboration in the Operating Room +Tian Zhou, Student Member, IEEE, and Juan Wachs, Member, IEEE"
+2edf55ebc88e89c4caff0c49c6b8e79f46407d19,Pruning Deep Neural Networks using Partial Least Squares,"Pruning Deep Neural Networks using Partial Least Squares +Artur Jordao, Ricardo Kloss∗, Fernando Yamada and William Robson Schwartz +Smart Sense Laboratory, Computer Science Department +Universidade Federal de Minas Gerais, Brazil +Email: {arturjordao, rbk, fernandoakio,"
+2e1ff08fb5790e3b5ba7864408628467795a9df4,Human Pose Estimation with Fields of Parts,"Human Pose Estimation +with Fields of Parts +Martin Kiefel and Peter Vincent Gehler +Max Planck Institute for Intelligent Systems, T¨ubingen Germany"
+2e1822bf06d80f5ad07a79a4bfff98c1c18fb573,Knowing who to listen to: Prioritizing experts from a diverse ensemble for attribute personalization,"KNOWING WHO TO LISTEN TO: PRIORITIZING EXPERTS FROM A DIVERSE +ENSEMBLE FOR ATTRIBUTE PERSONALIZATION +Shrenik Lad1, Bernardino Romera Paredes2, Julien Valentin2, Philip Torr2, Devi Parikh1 +. Virginia Tech 2. University of Oxford"
2e475f1d496456831599ce86d8bbbdada8ee57ed,Groupsourcing: Team Competition Designs for Crowdsourcing,"Groupsourcing: Team Competition Designs for Crowdsourcing Markus Rokicki, Sergej Zerr, Stefan Siersdorfer L3S Research Center, Hannover, Germany"
+2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e,3DPeS: 3D people dataset for surveillance and forensics,"DPeS: 3D People Dataset for Surveillance and Forensics +Davide Baltieri, Roberto Vezzani, Rita Cucchiara +{davide.baltieri, roberto.vezzani, rita.cucchiara} +University of Modena and Reggio Emilia, Italy (Dipartimento di Ingegneria dell’Informazione) +A new Dataset for People +Tracking and Reidentification +600 videos, 200 people, 8 cameras +Calibration and 3D scene reconstruction +taken +The dataset contains hundreds of video sequences of +from a multi-camera distributed +00 people +surveillance system over several days, with different light +onditions; each person is detected multiple times and +from different points of view. +The dataset +The starting point of our dataset is a real +surveillance setup, composed by 8 different +surveillance cameras, monitoring a section of the +ampus of the University of Modena and Reggio"
2ef51b57c4a3743ac33e47e0dc6a40b0afcdd522,Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition,"Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition Yaniv Taigman and Lior Wolf face.com {yaniv,"
+2efc4eee3953f6b52e23989bbcc2598a91e18ba0,External Cameras and a Mobile Robot for Enhanced Multi-person Tracking,"RFAntennas2D SICKLaserFirewire Cameraon PTU LaptopCamera 1Flea RGB Camera 2Flea RGBHubFirewireFigure1:Perceptualplatform;staticcameras(withroughpositionsandfieldsofview)andthemobilerobotRackham.Thispaperisstructuredasfollows:architectureofthecooperativesystemispresentedinsection2.Sec-tion3describesthedifferentdetectionmodalitiesthatdrivethemulti-persontracker(presentedinsection4).Evaluationsandresultsarepresentedinsection5fol-lowedbyconcludingremarksinsection6.2ARCHITECTUREOurcooperativeframeworkismadeupofamobilerobotandtwofixedviewwall-mountedRGBflea2cameras(figure1).Thecamerashaveamaximumres-olutionof640x480pixelsandareconnectedtoadual-coreIntelCentrinoLaptopviaafire-wirecable.Therobot,calledRackham,isaniRobotB21rmobileplat-form.Ithasvarioussensors,ofwhichitsSICKLaserRangeFinder(LRF)isutilizedinthiswork.Commu-nicationbetweenthemobilerobotandthecomputer"
+2e956e178fd50ab140f30f9255a83d853c8be210,Robust Facial Expression Recognition via Compressive Sensing,"Sensors 2012, 12, 3747-3761; doi:10.3390/s120303747 +OPEN ACCESS +sensors +ISSN 1424-8220 +www.mdpi.com/journal/sensors +Article +Robust Facial Expression Recognition via Compressive Sensing +Shiqing Zhang 1, Xiaoming Zhao 2,* and Bicheng Lei 1 +School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, China; +E-Mails: (S.Z.); (B.L.) +Department of Computer Science, Taizhou University, Taizhou 318000, China +* Author to whom correspondence should be addressed; E-Mail: +Tel./Fax: +86-576-8513-7178. +Received: 28 December 2011; in revised form: 19 February 2012 / Accepted: 16 March 2012 / +Published: 21 March 2012"
+2e082232eb37c98052e62eec76e674a491082544,Virtual Scenarios: Achievements and Current Work,"Virtual Scenarios: Achievements and Current Work +Javier Mar´ın, David V´azquez and Antonio M. L´opez +ADAS, Computer Vision Center, Universitat Autonoma de Barcelona, Spain +e-mail:{ jmarin, dvazquez, antonio"
+2eae02d59a3f455f3714ce674d85d3f073c9d7a2,All in the first glance: first fixation predicts individual differences in valence bias.,"Cognition and Emotion +ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20 +All in the first glance: first fixation predicts +individual differences in valence bias +Maital Neta, Tien T. Tong, Monica L. Rosen, Alex Enersen, M. Justin Kim & +Michael D. Dodd +To cite this article: Maital Neta, Tien T. Tong, Monica L. Rosen, Alex Enersen, M. Justin Kim & +Michael D. Dodd (2016): All in the first glance: first fixation predicts individual differences in +valence bias, Cognition and Emotion, DOI: 10.1080/02699931.2016.1152231 +To link to this article: http://dx.doi.org/10.1080/02699931.2016.1152231 +View supplementary material +Published online: 10 Mar 2016. +Submit your article to this journal +View related articles +View Crossmark data +Full Terms & Conditions of access and use can be found at +http://www.tandfonline.com/action/journalInformation?journalCode=pcem20 +Download by: [University of Nebraska, Lincoln] +Date: 10 March 2016, At: 09:04"
2ed4973984b254be5cba3129371506275fe8a8eb,Victoria Ovsyannikova THE EFFECTS OF MOOD ON EMOTION RECOGNITION AND ITS RELATIONSHIP WITH THE GLOBAL VS LOCAL INFORMATION PROCESSING,"Victoria Ovsyannikova THE EFFECTS OF MOOD ON EMOTION RECOGNITION AND @@ -16697,6 +58196,26 @@ Towards Wide-angle Micro Vision Sensors Sanjeev J. Koppal* Ioannis Gkioulekas* Travis Young+ Hyunsung Park* Kenneth B. Crozier* Geoffrey L. Barrows+ Todd Zickler*"
+2ea46531f7d837c1e4b9e6a8d8fc084c6e526545,Just Look at the Image: Viewpoint-Specific Surface Normal Prediction for Improved Multi-View Reconstruction,"Just look at the image: viewpoint-specific surface normal prediction +for improved multi-view reconstruction +Silvano Galliani +Konrad Schindler +Photogrammetry and Remote Sensing, ETH Zurich"
+2e927d0a2dc4b69fc03124ad876329b22a61f1b0,Temporal Reasoning in Videos using Convolutional Gated Recurrent Units,"Temporal Reasoning in Videos using Convolutional Gated Recurrent Units +Debidatta Dwibedi∗ +Pierre Sermanet +Jonathan Tompson +Google Brain +{debidatta, sermanet,"
+2ec393b4fa5739c54ac9f61e583f5e41cfb2687c,Face Recognition using Spherical Wavelets,"Face Recognition using Spherical Wavelets +Christian Lessig∗"
+2e55fd3f5138e55250aed84a7dc17adfc34970d3,The implications of social neuroscience for social disability.,"J Autism Dev Disord (2012) 42:1256–1262 +DOI 10.1007/s10803-012-1514-z +O R I G I N A L P A P E R +The Implications of Social Neuroscience for Social Disability +James C. McPartland • Kevin A. Pelphrey +Published online: 29 March 2012 +Ó Springer Science+Business Media, LLC 2012"
2ea78e128bec30fb1a623c55ad5d55bb99190bd2,Residual vs. Inception vs. Classical Networks for Low-Resolution Face Recognition,"Residual vs. Inception vs. Classical Networks for Low-Resolution Face Recognition Christian Herrmann1,2, Dieter Willersinn2, and J¨urgen Beyerer1,2 @@ -16708,6 +58227,8 @@ Lukas Bossard1, Matthias Dantone1, Christian Leistner1,2, Christian Wengert1,3, Till Quack3, Luc Van Gool1,4 ETH Z¨urich, Switzerland 2Microsoft, Austria 3Kooaba AG, Switzerland KU Leuven, Belgium"
+2e491c8e3d1d3314ea5e50943c0bdf2aa57b99b7,Weighted joint sparse representation-based classification method for robust alignment-free face recognition,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 12/17/2017 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +Weightedjointsparserepresentation-basedclassificationmethodforrobustalignment-freefacerecognitionBoSunFengXuGuoyanZhouJunHeFengxiangGe"
2ec7d6a04c8c72cc194d7eab7456f73dfa501c8c,A R Eview on T Exture B Ased E Motion R Ecognition from F Acial E Xpression,"International Journal of Scientific Research and Management Studies (IJSRMS) ISSN: 2349-3771 Volume 3 Issue 4, pg: 164-169 @@ -16721,6 +58242,48 @@ Dept. of E & C Engg., MIT Moradabad, Ram Ganga Vihar, Phase II, Moradabad, India Maja Pantic Imperial College, Computing Department, 180 Queens Gate, London SW7 2AZ, U.K."
+2e6c3557cb90f472e6798fcaa8ecc9dff3557f11,Towards Perspective-Free Object Counting with Deep Learning,"Towards perspective-free object counting with +deep learning +Daniel O˜noro-Rubio and Roberto J. L´opez-Sastre +GRAM, University of Alcal´a, Alcal´a de Henares, Spain"
+2e56209ed179be641e6df5efd11be8b3d54a62e9,Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors,"Article +Combining Deep and Handcrafted Image Features for +Presentation Attack Detection in Face Recognition +Systems Using Visible-Light Camera Sensors +Dat Tien Nguyen, Tuyen Danh Pham, Na Rae Baek and Kang Ryoung Park * +Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, +Seoul 100-715, Korea; (D.T.N.); (T.D.P.); +(N.R.B.) +* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +Received: 30 January 2018; Accepted: 24 February 2018; Published: 26 February 2018"
+2efc6f98720b804345c030e22aef6c9f4a53023e,Soft-biometrics evaluation for people re-identification in uncontrolled multi-camera environments,"Moctezuma et al. EURASIP Journal on Image and Video Processing (2015) 2015:28 +DOI 10.1186/s13640-015-0078-1 +RESEARCH +Open Access +Soft-biometrics evaluation for people +re-identification in uncontrolled multi-camera +environments +Daniela Moctezuma1*, Cristina Conde2, Isaac Martín De Diego2 and Enrique Cabello2"
+2e708431df3e7a9585a338e1571f078ddbe93a71,Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification.,"Aalborg Universitet +Deep Pain +Rodriguez, Pau; Cucurull, Guillem; Gonzàlez, Jordi; M. Gonfaus, Josep ; Nasrollahi, Kamal; +Moeslund, Thomas B.; Xavier Roca, F. +Published in: +I E E E Transactions on Cybernetics +DOI (link to publication from Publisher): +0.1109/TCYB.2017.2662199 +Publication date: +Document Version +Accepted author manuscript, peer reviewed version +Link to publication from Aalborg University +Citation for published version (APA): +Rodriguez, P., Cucurull, G., Gonzàlez, J., M. Gonfaus, J., Nasrollahi, K., Moeslund, T. B., & Xavier Roca, F. +(2017). Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification. I E E E +Transactions on Cybernetics, 1-11. DOI: 10.1109/TCYB.2017.2662199 +General rights +Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +? Users may download and print one copy of any publication from the public portal for the purpose of private study or research."
2e832d5657bf9e5678fd45b118fc74db07dac9da,"Recognition of Facial Expressions of Emotion: The Effects of Anxiety, Depression, and Fear of Negative Evaluation","Running head: RECOGNITION OF FACIAL EXPRESSIONS OF EMOTION Recognition of Facial Expressions of Emotion: The Effects of Anxiety, Depression, and Fear of Negative Evaluation @@ -16733,6 +58296,57 @@ Wittenberg University, and Dr. Michael Anes, Psychology Department, Witt Correspondence concerning this article should be addressed to Rachel Merchak, 10063 Fox Chase Drive, Loveland, OH 45140. E‐mail:"
+2bb968e8f9df0fa72dd72e5d705ea7b75af8dcd7,Fast Support Vector Classifier for automated content-based search in video surveillance,"Fast Support Vector Classifier for Automated +Content-based Search in Video Surveillance +Cătălin A. Mitrea1, Ionuț Mironică1, Bogdan Ionescu1,2, Radu Dogaru1 +LAPI & Natural Computing Labs, University “Politehnica” of Bucharest, 061971, Romania +LISTIC, University Savoie Mont Blanc, 74940 Annecy-le-Vieux, France +Email: +for multiple-instance human retrieval"
+2ba5e4c421b1413139e4bc5d935d6d48cc753757,Vantage Feature Frames for Fine-Grained Categorization,"Vantage Feature Frames For Fine-Grained Categorization +Asma Rejeb Sfar +INRIA Saclay +Palaiseau, France +Nozha Boujemaa +INRIA Saclay +Palaiseau, France +Donald Geman +Johns Hopkins University +Baltimore, MD, USA +sma.rejeb"
+2baea24cc71793ba40cf738b7ad1914f0e549863,Attribute Augmented Convolutional Neural Network for Face Hallucination,"Attribute Augmented Convolutional Neural Network for Face Hallucination +Cheng-Han Lee1 Kaipeng Zhang1 Hu-Cheng Lee1 Chia-Wen Cheng2 Winston Hsu1 +National Taiwan University 2The University of Texas at Austin +{r05922077, r05944047, r05922174,"
+2ba64deeb3e170e4776e2d2704771019cf9c8639,Differences between Old and Young Adults’ Ability to Recognize Human Faces Underlie Processing of Horizontal Information,"AGING NEUROSCIENCE +ORIGINAL RESEARCH ARTICLE +published: 23 April 2012 +doi: 10.3389/fnagi.2012.00003 +Differences between old and young adults’ ability to +recognize human faces underlie processing of +horizontal information +Sven Obermeyer *,Thorsten Kolling, Andreas Schaich and Monika Knopf +Department of Psychology, Institute for Psychology, Goethe-University Frankfurt am Main, Frankfurt am Main, Germany +Edited by: +Hari S. Sharma, Uppsala University, +Sweden +Reviewed by: +Luis Francisco Gonzalez-Cuyar, +University of Washington School of +Medicine, USA +Gregory F. Oxenkrug, Tufts University, +*Correspondence: +Sven Obermeyer , Department of +Psychology, Goethe-University"
+2b50f8e4568ecd84e2f9d6357254272d8db4bbd4,Hierarchical Gaussian Descriptor for Person Re-identification,"Hierarchical Gaussian Descriptor for Person Re-Identification +Tetsu Matsukawa1, Takahiro Okabe2, Einoshin Suzuki1, Yoichi Sato3 +Kyushu University 2 Kyushu Institute of Technology 3 The University of Tokyo +{matsukawa,"
+2bf41bf420c8d86dd1bffbacd28c70fa8b12b6dd,Counting the uncountable: deep semantic density estimation from Space,"Counting the uncountable: Deep semantic +density estimation from space +Andres C. Rodriguez and Jan D. Wegner +ETH Zurich, Stefano-franscini-platz 5 8093 Zurich, Switzerland +Accepted at GCPR 2018"
2b4d092d70efc13790d0c737c916b89952d4d8c7,Robust Facial Expression Recognition using Local Haar Mean Binary Pattern,"JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 32, XXXX-XXXX (2016) Robust Facial Expression Recognition using Local Haar Mean Binary Pattern @@ -16753,18 +58367,100 @@ ased feature comparison. Experiments prove the superiority of HNAD over template matching techniques such as L2 norm and Chi-Square. We also investigated LHMBP for expression recognition in low resolution. The performance of the proposed ap- proach is tested on well-known CK, JAFFE, and SFEW facial expression datasets in diverse"
+2b1358efbceda12de2f36398cdbdb3c7bccc70d4,Unified Detection and Tracking of Instruments during Retinal Microsurgery,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007 +Unified detection and tracking of instruments +during retinal microsurgery +Raphael Sznitman, Rogerio Richa, Russell H. Taylor Fellow, IEEE, Bruno Jedynak +nd Gregory D. Hager, Fellow, IEEE"
+2befea9b289f22547f8911aa56672d6373c1ac64,GAIDON et al.: RECOGNIZING ACTIVITIES WITH CLUSTER-TREES OF TRACKLETS 1 Recognizing activities with cluster-trees of tracklets,"GAIDON et al.: RECOGNIZING ACTIVITIES WITH CLUSTER-TREES OF TRACKLETS +Recognizing activities with cluster-trees of +tracklets +Adrien Gaidon +http://lear.inrialpes.fr/people/gaidon +Zaid Harchaoui +http://lear.inrialpes.fr/people/harchaoui +Cordelia Schmid +http://lear.inrialpes.fr/people/schmid +LEAR - INRIA Grenoble, LJK +655, avenue de l’Europe +8330 Montbonnot, France"
+2b4d40ef1610500c207f166e9a5b55dbfe234045,A New Biased Discriminant Analysis Using Composite Vectors for Eye Detection,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 4, AUGUST 2012 +A New Biased Discriminant Analysis Using +Composite Vectors for Eye Detection +Chunghoon Kim, Member, IEEE, Sang-Il Choi, Member, IEEE, +Matthew Turk, Senior Member, IEEE, and Chong-Ho Choi, Member, IEEE"
2b0ff4b82bac85c4f980c40b3dc4fde05d3cc23f,An Effective Approach for Facial Expression Recognition with Local Binary Pattern and Support Vector Machine,"An Effective Approach for Facial Expression Recognition with Local Binary Pattern and Support Vector Machine Cao Thi Nhan, 2Ton That Hoa An, 3Hyung Il Choi *1School of Media, Soongsil University, School of Media, Soongsil University, School of Media, Soongsil University,"
+2bac4161a928eb33e6be700ed8ea4d823494b22c,MergeNet: A Deep Net Architecture for Small Obstacle Discovery,"MergeNet: A Deep Net Architecture for Small Obstacle Discovery +Krishnam Gupta1, Syed Ashar Javed2, Vineet Gandhi2 and K. Madhava Krishna2 +evidences is more likely to perform the task better. Recent +efforts [3] on multi modal fusion also suggests likewise."
+2baf54199b4b0047f3610ba691fb0a718dbce97e,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"International Journal of Computer Applications (0975 – 8887) +Volume 134 – No.7, January 2016 +Development of an Efficient Face Recognition System +ased on Linear and Nonlinear Algorithms +Filani Araoluwa S. +Department of Computer Science, +The Federal University of Technology, +P.M.B.704, Akure, Ondo State, Nigeria."
+2b4b0795358d0264f846e8b3c19ec3180da301cc,Active MAP Inference in CRFs for Efficient Semantic Segmentation,"Active MAP Inference in CRFs for Efficient Semantic Segmentation +Roderick de Nijs2 +Gemma Roig1 ∗ +Sebastian Ramos3 +Xavier Boix1 ∗ +Kolja K¨uhnlenz2 +Luc Van Gool1,4 +ETH Z¨urich, Switzerland 2TU Munchen, Germany 3CVC Barcelona, Spain 4KU Leuven, Belgium +Both first authors contributed equally."
+2ba7c88a7e96d412c116d6bea4ba27be2ed4dd48,CocoNet: A deep neural network for mapping pixel coordinates to color values,"CocoNet: A Deep Neural Network for Mapping +Pixel Coordinates to Color Values +Paul Andrei Bricman1 and Radu Tudor Ionescu2 +George Co¸sbuc National College, 29-31 Olari, Bucharest, Romania, +University of Bucharest, 14 Academiei, Bucharest, Romania"
+2b285e5eaeb7a2aa7e37c5ae6762b838d3742b4e,Video event recognition using concept attributes,"Video Event Recognition Using Concept Attributes +Jingen Liu, Qian Yu, Omar Javed, Saad Ali, Amir Tamrakar, Ajay Divakaran, Hui Cheng, Harpreet Sawhney +SRI International Sarnoff +Princeton, NJ, USA 08540"
+2bd49bdfc61788c8ac5621fe7f08a06dd2152fb9,Pose Invariant Face Recognition Using Neuro - Biologically Inspired Features Pramod,"International Journal of Future Computer and Communication, Vol. 1, No. 3, October 2012 +Pose Invariant Face Recognition Using +Neuro-Biologically Inspired Features +Pramod Kumar Pisharady and Martin Saerbeck"
2b1327a51412646fcf96aa16329f6f74b42aba89,Improving performance of recurrent neural network with relu nonlinearity,"Under review as a conference paper at ICLR 2016 IMPROVING PERFORMANCE OF RECURRENT NEURAL NETWORK WITH RELU NONLINEARITY Sachin S. Talathi & Aniket Vartak Qualcomm Research San Diego, CA 92121, USA"
+2bdc0c79b26fed51bc2af1af16117879ee3f571e,Augmented Multitouch Interaction upon a 2-DOF Rotating Disk,"Augmented Multitouch Interaction +upon a 2-DOF Rotating Disk +Xenophon Zabulis, Panagiotis Koutlemanis, and Dimitris Grammenos +Institute of Computer Science, Foundation for Research and Technology - Hellas, +Herakleion, Crete, Greece"
+2b8a61184b6423e3d5285803eb1908ff955db1a8,Processing and analysis of 2 . 5 D face models for non-rigid mapping based face recognition using differential geometry tools,"Processing and analysis of 2.5D face models for +non-rigid mapping based face recognition using +differential geometry tools +Przemyslaw Szeptycki +To cite this version: +Przemyslaw Szeptycki. Processing and analysis of 2.5D face models for non-rigid mapping +ased face recognition using differential geometry tools. Other. Ecole Centrale de Lyon, 2011. +English. <NNT : 2011ECDL0020>. <tel-00675988> +HAL Id: tel-00675988 +https://tel.archives-ouvertes.fr/tel-00675988 +Submitted on 2 Mar 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destin´ee au d´epˆot et `a la diffusion de documents +scientifiques de niveau recherche, publi´es ou non,"
2b632f090c09435d089ff76220fd31fd314838ae,Early Adaptation of Deep Priors in Age Prediction from Face Images,"Early Adaptation of Deep Priors in Age Prediction from Face Images Mahdi Hajibabaei Computer Vision Lab @@ -16775,9 +58471,25 @@ D-ITET, ETH Zurich Radu Timofte CVL, D-ITET, ETH Zurich Merantix GmbH"
+2beb9777bf452d02f9bec5275c100f4a736def10,Near Duplicate Image Discovery on One Billion Images,"Near Duplicate Image Discovery on One Billion Images +Saehoon Kim ∗ +Department of Computer Science, +POSTECH, Korea +Xin-Jing Wang +Web Search and Mining Group +Microsoft Research Asia, Beijing +Lei Zhang +Web Search and Mining Group +Microsoft Research Asia, Beijing +Seungjin Choi +Department of Computer Science, +POSTECH, Korea"
2b507f659b341ed0f23106446de8e4322f4a3f7e,Deep Identity-aware Transfer of Facial Attributes,"Deep Identity-aware Transfer of Facial Attributes Mu Li1, Wangmeng Zuo2, David Zhang1 The Hong Kong Polytechnic University 2Harbin Institute of Technology"
+2bbb772332a90b2aba893f7467daa76b373be240,Extracting 3D Layout From a Single Image Using Global Image Structures,"Extracting 3D Layout From a Single Image +Using Global Image Structures +Zhongyu Lou, Theo Gevers, Member, IEEE, and Ninghang Hu"
2b8dfbd7cae8f412c6c943ab48c795514d53c4a7,Polynomial based texture representation for facial expression recognition,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) 978-1-4799-2893-4/14/$31.00 ©2014 IEEE e-mail: @@ -16786,6 +58498,12 @@ RECOGNITION . INTRODUCTION (d1,d2)∈[0;d]2 d1+d2≤d"
+2b3fe9a0356eaf50f1340dda3f3d14f6904905ec,Taking advantage of sensor modality specific properties in Automated Driving Extended Abstract,"Taking advantage of sensor modality specific properties in +Automated Driving"
+2b9082b6b5266f6f7d7a95892f30cc84138697e5,Video Person Re-identification by Temporal Residual Learning,"SUBMITTED TO IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. XX, NO. XX, FEB 2018 +Video Person Re-identification by Temporal +Residual Learning +Ju Dai∗, Pingping Zhang∗, Huchuan Lu, Senior Member, IEEE, and Hongyu Wang, Member, IEEE"
2bae810500388dd595f4ebe992c36e1443b048d2,Analysis of Facial Expression Recognition by Event-related Potentials,"International Journal of Bioelectromagnetism Vol. 18, No. 1, pp. 13 - 18, 2016 www.ijbem.org @@ -16811,6 +58529,66 @@ B.Mahalakshmi1, K.Duraiswamy2, P.Gnanasuganya3, P.Aruldhevi4, R.Sundarapandiyan5 Associate Professor, Department of CSE, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India1 Dean, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India2 B.E, Department of CSE, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India3, 4, 5"
+2b8667df1a0332386d8d799fbac0327496ce02c9,Stranger danger: Parenthood increases the envisioned bodily formidability of menacing men,"Evolution and Human Behavior 35 (2014) 109–117 +Contents lists available at ScienceDirect +Evolution and Human Behavior +j o u r n a l h o m e p a g e : w w w . e h b o n l i n e . o r g +Original Article +Stranger danger: Parenthood increases the envisioned bodily formidability +of menacing men☆ +Daniel M.T. Fessler a,b,⁎, Colin Holbrook a,b, Jeremy S. Pollack b, Jennifer Hahn-Holbrook b,c +Department of Anthropology, University of California, Los Angeles, Los Angeles, CA 90095, USA +Center for Behavior, Evolution, and Culture, University of California, Los Angeles, Los Angeles, CA 90095, USA +Department of Psychology, University of California, Los Angeles, Los Angeles, CA 90095, USA +r t i c l e +i n f o +b s t r a c t +Article history: +Initial receipt 6 April 2013 +Final revision received 1 November 2013 +Keywords: +Parenthood +Relative formidability"
+47fc921add1421ff8adb730df7aa9e7f865bfdeb,Toward Practical Smile Detection,"Towards Practical Smile Detection +Jacob Whitehill, Gwen Littlewort, Ian Fasel, Marian Bartlett, and Javier Movellan"
+4701112bfe9946a97a60c2bbb2d47dc784942c3f,Understanding classifier errors by examining influential neighbors,"Understanding Classifier Errors by Examining Influential Neighbors +Mayank Kabra, Alice Robie, Kristin Branson +Janelia Research Campus of the Howard Hughes Medical Institute +Ashburn, VA, 20147, USA"
+47be79c0ecb598e1af44e57f386f79adf491f82b,Scenes categorization based on appears objects probability,"016 IEEE 6th International Conference on System Engineering and Technology (ICSET) +Oktober 3-4, 2016 Bandung – Indonesia +Scenes Categorization based on Appears Objects +Probability +Marzuki1, Egi Muhamad Hidayat2, Rinaldi Munir3, Ary Setijadi P4 ,Carmadi Machbub5 +School of Electrical Engineering and Informatics, Institut Teknologi Bandung +Bandung, Indonesia +lskk.ee.itb.ac.id"
+47ce78c9f49248a7d1bd395befb43e45d89555ee,Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments,"Vision-and-Language Navigation: Interpreting visually-grounded +navigation instructions in real environments +Peter Anderson1 +Niko S¨underhauf3 +Qi Wu2 +Damien Teney2 +Jake Bruce3 +Mark Johnson4 +Ian Reid2 +Stephen Gould1 +Anton van den Hengel2 +Australian National University 2University of Adelaide 3Queensland University of Technology 4Macquarie University"
+47096e7103a2fbb6f6ede05e996209497d41db6a,Implementation of Artificial Intelligence Methods for Virtual Reality Solutions: a Review of the Literature,"Implementation of Artificial Intelligence Methods for +Virtual Reality Solutions: a Review of the Literature +Rytis Augustauskas +Department of Automation +Aurimas Kudarauskas +Department of Automation +Kaunas University of Technology, +Kaunas University of Technology, +Kaunas, Lithuania +Kaunas, Lithuania +Cenker Canbulut +Department of Multimedia Engineering +Kaunas University of Technology, +Kaunas, Lithuania"
477236563c6a6c6db922045453b74d3f9535bfa1,Attribute Based Image Search Re-Ranking Snehal,"International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 @@ -16820,6 +58598,13 @@ Master of Computer Engg, Savitribai Phule Pune University, G. H. Raisoni Collage 2Professor, Computer and Science Dept, Savitribai Phule Pune University, G. H .Raisoni Collage of Engg and Technology, Wagholi, Pune integrating images by"
+47fdd1579f732dd6389f9342027560e385853180,Deep Sparse Subspace Clustering,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +Deep Sparse Subspace Clustering +Xi Peng, Jiashi Feng, Shijie Xiao, Jiwen Lu Senior Member, IEEE, Zhang Yi Fellow, IEEE, +Shuicheng Yan Fellow, IEEE,"
+47f2088afb616bde5468818e23d79e1ae5a562cd,Multi-view gender classification based on local Gabor binary mapping pattern and support vector machines,"Multi-view Gender Classification based on Local Gabor Binary +Mapping Pattern and Support Vector Machines +Bin Xia, He Sun and Bao-Liang Lu∗ Senior Member, IEEE"
470dbd3238b857f349ebf0efab0d2d6e9779073a,Unsupervised Simultaneous Orthogonal basis Clustering Feature Selection,"Unsupervised Simultaneous Orthogonal Basis Clustering Feature Selection Dongyoon Han and Junmo Kim School of Electrical Engineering, KAIST, South Korea @@ -16841,6 +58626,15 @@ taneously performed. In this way, the projection matrix for feature selection is more properly computed by the estimated latent cluster centers of the projected data points. To the best of our knowledge, this is the first valid"
47541d04ec24662c0be438531527323d983e958e,British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Control Number: 2008xxxxxx,Affective Information Processing
+479f44f9b4c401327a721550334b8d491f6b3f16,OR-PCA with MRF for Robust Foreground Detection in Highly Dynamic Backgrounds,"OR-PCA with MRF for Robust Foreground +Detection in Highly Dynamic Backgrounds +Sajid Javed1, Seon Ho Oh1, Andrews Sobral2, +Thierry Bouwmans2 and Soon Ki Jung1 +School of Computer Science and Engineering, Kyungpook National University, +80 Daehak-ro, Buk-gu,Daegu, 702-701, Republic of Korea +{sajid, +Laboratoire MIA (Mathematiques, Image et Applications)- Universit´e de La +Rochelle, 17000, France, {andrews.sobral,"
474b461cd12c6d1a2fbd67184362631681defa9e,Multi-resolution fusion of DTCWT and DCT for shift invariant face recognition,"014 IEEE International Conference on Systems, Man nd Cybernetics @@ -16871,9 +58665,33 @@ Unfelt Emotions Kaustubh Kulkarni*, Ciprian Adrian Corneanu*, Ikechukwu Ofodile*, Student Member, IEEE, Sergio Escalera, Xavier Bar´o, Sylwia Hyniewska, Member, IEEE, J¨uri Allik, nd Gholamreza Anbarjafari, Senior Member, IEEE"
+47f8ba44fde1f8a3a621b20cabb7e84515fb8313,Superpixel-based Road Segmentation for Real-time Systems using CNN,
+4753a125469da7649e9f58fb0db781622dff41f8,Multi-view Stereo with Single-View Semantic Mesh Refinement,"Multi-View Stereo with Single-View Semantic Mesh Refinement +Andrea Romanoni Marco Ciccone +Francesco Visin Matteo Matteucci +{andrea.romanoni, marco.ciccone, francesco.visin, +Politecnico di Milano, Italy"
47a2727bd60e43f3253247b6d6f63faf2b67c54b,Semi-supervised Vocabulary-Informed Learning,"Semi-supervised Vocabulary-informed Learning Yanwei Fu and Leonid Sigal Disney Research"
+475de283dad61a8a9ed231dce0d8d62a54f4d062,Person Following by Autonomous Robots: A Categorical Overview,"Islam et al. +Person Following by Autonomous +Robots: A Categorical Overview +Md Jahidul Islam, Jungseok Hong and Junaed Sattar +Preprint Version I +XX(X):1–25 +(cid:13)The Author(s) 2018 +Reprints and permission: +sagepub.co.uk/journalsPermissions.nav +DOI: 10.1177/ToBeAssigned +www.sagepub.com/"
+478261574ddc6cf297611000735aa9808f8f0030,ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes,
+47022785c35735a242dbacd4f1f1bb73628493ea,Person Retrieval Based on Viewpoint Saliency Prior,"Journal of Computational Information Systems 9: 20 (2013) 8235–8242 +Available at http://www.Jofcis.com +Person Retrieval Based on Viewpoint Saliency Prior +Qingming LENG, Ruimin HU∗, Cuina JIAO, Chao LIANG, Zheng WANG +National Engineering Research Center for Multimedia Software, School of Computer, Wuhan +University, Wuhan 430079, China"
47d3b923730746bfaabaab29a35634c5f72c3f04,Real-Time Facial Expression Recognition App Development on Smart Phones,"Humaid Alshamsi.et.al. Int. Journal of Engineering Research and Application www.ijera.com ISSN : 2248-9622, Vol. 7, Issue 7, ( Part -3) July 2017, pp.30-38 RESEARCH ARTICLE @@ -16887,6 +58705,26 @@ Facial Expression Recognition in still pictures and videos using Active Appearance Models. A comparison approach. Drago(cid:1) Datcu Léon Rothkrantz"
+470b89e2c5248eb58e09129aa9b4d8bc77497e7e,Neurobiology of Disease Cortical Folding Abnormalities in Autism Revealed by Surface-Based Morphometry,"The Journal of Neuroscience, October 24, 2007 • 27(43):11725–11735 • 11725 +Neurobiology of Disease +Cortical Folding Abnormalities in Autism Revealed by +Surface-Based Morphometry +Christine Wu Nordahl,1 Donna Dierker,2 Iman Mostafavi,1 Cynthia M. Schumann,1,3 Susan M. Rivera,4 +David G. Amaral,1 and David C. Van Essen2 +The Medical Investigation of Neurodevelopmental Disorders (M.I.N.D.) Institute and the Department of Psychiatry and Behavioral Sciences, University of +California, Davis, Sacramento, California 95817, 2Department of Anatomy and Neurobiology, Washington University in St. Louis, St. Louis, Missouri 63110, +Department of Neurosciences, University of California, San Diego, La Jolla, California 92093, and 4The M.I.N.D. Institute and the Department of +Psychology, University of California, Davis, Davis, California 95616 +We tested for cortical shape abnormalities using surface-based morphometry across a range of autism spectrum disorders (7.5–18 years +of age). We generated sulcal depth maps from structural magnetic resonance imaging data and compared typically developing controls +to three autism spectrum disorder subgroups: low-functioning autism, high-functioning autism, and Asperger’s syndrome. The low- +functioning autism group had a prominent shape abnormality centered on the pars opercularis of the inferior frontal gyrus that was +ssociated with a sulcal depth difference in the anterior insula and frontal operculum. The high-functioning autism group had bilateral +shape abnormalities similar to the low-functioning group, but smaller in size and centered more posteriorly, in and near the parietal +operculum and ventral postcentral gyrus. Individuals with Asperger’s syndrome had bilateral abnormalities in the intraparietal sulcus +that correlated with age, intelligence quotient, and Autism Diagnostic Interview-Revised social and repetitive behavior scores. Because of +evidence suggesting age-related differences in the developmental time course of neural alterations in autism, separate analyses on +hildren (7.5–12.5 years of age) and adolescents (12.75–18 years of age) were also carried out. All of the cortical shape abnormalities"
475e16577be1bfc0dd1f74f67bb651abd6d63524,DAiSEE: Towards User Engagement Recognition in the Wild,"DAiSEE: Towards User Engagement Recognition in the Wild Abhay Gupta Microsoft @@ -16896,12 +58734,24 @@ Indian Institution of Technology Hyderabad" Analysis for Face Verification Georgios Goudelis, Stefanos Zafeiriou, Anastasios Tefas, Member, IEEE, and Ioannis Pitas, Fellow, IEEE lass problems ("
+47bd6c1d7da596d3cf79f06ec0de816d10f11beb,Coupled Discriminant Analysis for Heterogeneous Face Recognition,"Coupled Discriminant Analysis for Heterogeneous +Face Recognition +Zhen Leiy, Member, IEEE, Shengcai Liaoz, Anil K. Jainz, Fellow, IEEE, and Stan Z. Liy, Fellow, IEEE"
47e8db3d9adb79a87c8c02b88f432f911eb45dc5,MAGMA: Multilevel Accelerated Gradient Mirror Descent Algorithm for Large-Scale Convex Composite Minimization,"MAGMA: Multi-level accelerated gradient mirror descent algorithm for large-scale convex composite minimization Vahan Hovhannisyan Panos Parpas Stefanos Zafeiriou July 15, 2016"
+47c0c7f1a27d467e00a6fa7ea2ca0af2e3328b9e,Predicting Scene Parsing and Motion Dynamics in the Future,"Predicting Scene Parsing and Motion Dynamics +in the Future +Xiaojie Jin1, Huaxin Xiao2, Xiaohui Shen3, Jimei Yang3, Zhe Lin3 +Yunpeng Chen2, Zequn Jie4, Jiashi Feng2, Shuicheng Yan5,2 +NUS Graduate School for Integrative Science and Engineering (NGS), NUS +Department of ECE, NUS +Adobe Research +Tencent AI Lab +5Qihoo 360 AI Institute"
47f5f740e225281c02c8a2ae809be201458a854f,Simultaneous Unsupervised Learning of Disparate Clusterings,"Simultaneous Unsupervised Learning of Disparate Clusterings Prateek Jain*, Raghu Meka and Inderjit S. Dhillon Department of Computer Sciences, University of Texas, Austin, TX 78712-1188, USA @@ -16926,7 +58776,96 @@ Tara Prasad Singh (M.Tech. Student) Computer Science & Engineering Iftm University,Moradabad-244001 U.P."
+47b34a8ad5100582aa7cbfd85df3ca7659adc392,Is this a wampimuk? Cross-modal mapping between distributional semantics and the visual world,"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, pages 1403–1414, +Baltimore, Maryland, USA, June 23-25 2014. c(cid:13)2014 Association for Computational Linguistics"
+47440f514318b438ebf04d9932f5dafdb488a536,Emotion Recognition from Facial Images Using Binary Face Relevance Maps,"STUDIA INFORMATICA +Volume 36 +Number 4 (122) +Tomasz HERUD, Michal KAWULOK +Silesian University of Technology, Institute of Informatics +Future Processing, Gliwice, Poland +Bogdan SMOLKA +Silesian University of Technology, Institute of Automatic Control +EMOTION RECOGNITION FROM FACIAL IMAGES USING +BINARY FACE RELEVANCE MAPS1 +Summary. This paper is focused on automatic emotion recognition from static +grayscale images. Here, we propose a new approach to this problem, which combines +few other methods. The facial region is divided into small subregions, which are +selected for processing based on a face relevance map. From these regions, local +directional pattern histograms are extracted and concatenated into a single feature +histogram, which is classified into one of seven defined emotional states using support +vector machines. In our case, we distinguish: anger, disgust, fear, happiness, +neutrality, sadness and surprise. In our experimental study we demonstrate that the +expression recognition accuracy for Japanese Female Facial Expression database is +one of the best compared with the results reported in the literature."
782188821963304fb78791e01665590f0cd869e8,Automatic Spatially-Aware Fashion Concept Discovery,"sleevelengthincreasing dress length+ mini =(b) Structured product browsing(c) Attribute-feedback product retrieval(a) Concept discoveryminimidimaxisleevelessshort-sleevelong-sleeveblueblackredyellowFigure1.(a)Weproposeaconceptdiscoveryapproachtoauto-maticallyclusterspatially-awareattributesintomeaningfulcon-cepts.Thediscoveredspatially-awareconceptsarefurtherutilizedfor(b)structuredproductbrowsing(visualizingimagesaccordingtoselectedconcepts)and(c)attribute-feedbackproductretrieval(refiningsearchresultsbyprovidingadesiredattribute).variousfeedback,includingtherelevanceofdisplayedim-ages[20,4],ortuningparameterslikecolorandtexture,andthenresultsareupdatedcorrespondingly.However,rel-evancefeedbackislimitedduetoitsslowconvergencetomeetthecustomerrequirements.Inadditiontocolorandtexture,customersoftenwishtoexploithigher-levelfea-tures,suchasneckline,sleevelength,dresslength,etc.Semanticattributes[13],whichhavebeenappliedef-fectivelytoobjectcategorization[15,27]andfine-grainedrecognition[12]couldpotentiallyaddresssuchchallenges.Theyaremid-levelrepresentationsthatdescribesemanticproperties.Recently,researchershaveannotatedclotheswithsemanticattributes[9,2,8,16,11](e.g.,material,pat-tern)asintermediaterepresentationsorsupervisorysignalstobridgethesemanticgap.However,annotatingsemanticattributesiscostly.Further,attributesconditionedonob-jectpartshaveachievedgoodperformanceinfine-grainedrecognition[3,33],confirmingthatspatialinformationiscriticalforattributes.Thisalsoholdsforclothingimages.Forexample,thenecklineattributeusuallycorrespondstothetoppartinimageswhilethesleeveattributeordinarily1"
+786e57ed6877dc8491b1bb9253f8b82c02732977,Efficient approach to de-identifying faces in videos,"Page 1 of 8 +An Efficient Approach to De-Identifying Faces in Videos +Li Meng *, Zongji Sun, Odette Tejada Collado +School of Engineering and Technology, University of Hertfordshire, College Lane, Hatfield, UK"
+788eceb4d1b7556d1c9033224da2348b4402d6ca,An Empirical Evaluation of Visual Question Answering for Novel Objects,"An Empirical Evaluation of Visual Question Answering for Novel Objects +Santhosh K. Ramakrishnan1,2 Ambar Pal1 Gaurav Sharma1 Anurag Mittal2 +IIT Kanpur∗ +IIT Madras†"
+7854876ab5d87248ace94615731ed3e3e56af769,MixedPeds: Pedestrian Detection in Unannotated Videos Using Synthetically Generated Human-Agents for Training,
+789c76749a15614d97ac8f4ec18b3ce7d80a2d28,Explorer Multiplicative LSTM for sequence modelling,"Multiplicative LSTM for sequence modelling +Citation for published version: +Krause, B, Murray, I, Renals, S & LU, L 2017, Multiplicative LSTM for sequence modelling. in International +Conference on Learning Representations - ICLR 2017 - Workshop Track. pp. 2872-2880. +Link: +Link to publication record in Edinburgh Research Explorer +Document Version: +Publisher's PDF, also known as Version of record +Published In: +International Conference on Learning Representations - ICLR 2017 - Workshop Track +General rights +Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +nd / or other copyright owners and it is a condition of accessing these publications that users recognise and +bide by the legal requirements associated with these rights. +Take down policy +The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer +ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please +ontact providing details, and we will remove access to the work immediately and +investigate your claim. +Download date: 02. Sep. 2017"
+78749b58299ecebf100e2512872029f89878449b,One-class Selective Transfer Machine for Personalized Anomalous Facial Expression Detection,
+78c91d969c55a4a61184f81001c376810cdbd541,A Spike and Slab Restricted Boltzmann Machine,"A Spike and Slab Restricted Boltzmann Machine +Aaron Courville +James Bergstra +Yoshua Bengio +DIRO, Universit´e de Montr´eal, Montr´eal, Qu´ebec, Canada"
+787303db8e707feee2fa2b93dfc46e3d3cc244cd,Defocus Blur Parameter Estimation Technique,"International Journal of Electronics and Communication Engineering and Technology (IJECET) +Volume 7, Issue 4, July-August 2016, pp. 85–90, Article ID: IJECET_07_04_010 +Available online at +http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=7&IType=4 +Journal Impact Factor (2016): 8.2691 (Calculated by GISI) www.jifactor.com +ISSN Print: 0976-6464 and ISSN Online: 0976-6472 +© IAEME Publication +DEFOCUS BLUR PARAMETER ESTIMATION +TECHNIQUE +Ruchi Gajjar, Aditi Pathak and Tanish Zaveri +Electronics and Communication Engineering Department +Institute of Technology, Nirma University, Ahmedabad, Gujarat, India"
+784cc0363d44bf09f3f636abd1a532ddac95ca13,Group-level emotion recognition using transfer learning from face identification,"Group-level Emotion Recognition using Transfer Learning from +Face Identification +Alexandr Rassadin +Alexey Gruzdev +Andrey Savchenko +National Research University Higher +National Research University Higher +National Research University Higher +School of Economics +Laboratory of Algorithms and +Technologies for Network Analysis, +School of Economics +Nizhny Novgorod +Russia +School of Economics +Laboratory of Algorithms and +Technologies for Network Analysis, +Nizhny Novgorod +Russia +Nizhny Novgorod"
783f3fccde99931bb900dce91357a6268afecc52,Adapted Active Appearance Models,"Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2009, Article ID 945717, 14 pages @@ -16947,7 +58886,61 @@ dapted AAM for an unknown face. Tests on public and private databases show the i to align unknown faces in real-time situations, in which light and pose are not controlled. Copyright © 2009 Renaud S´eguier et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly"
+789389dce27ad72adad251c81734bdb6c274c30f,3D Facial Feature Localization for Registration,"D Facial Feature Localization for Registration +Albert Ali Salah and Lale Akarun +Bo˘gazi¸ci University +Computer Engineering Department, Turkey +Perceptual Intelligence Laboratory +{salah,"
+78a2a964b61308f683fae6f3a62e3a8aece51bae,Functional Neuroimaging of the Interaction between Social and Executive Neural Circuitry in Individuals with High- Functioning Autism,"FUNCTIONAL NEUROIMAGING OF THE INTERACTION BETWEEN SOCIAL +AND EXECUTIVE NEURAL CIRCUITRY IN INDIVIDUALS WITH HIGH- +FUNCTIONING AUTISM +Kimberly Lynn Hills Carpenter +A dissertation submitted to the faculty of the University of North Carolina at Chapel +Hill in partial fulfillment of the requirements for the degree of Doctor of Philosophy in +the Curriculum in Neurobiology +Chapel Hill +Approved By: +Dr. Aysenil Belger +Dr. Jim Bodfish +Dr. Gabriel Dichter +Dr. Kevin LaBar +Dr. Joseph Piven +Dr. Aldo Rustioni"
+781d3550f54f3b4bfbd99ca9957aba6d6dec990e,Regularized Kernel Discriminant Analysis With a Robust Kernel for Face Recognition and Verification,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +Brief Papers +Regularized Kernel Discriminant Analysis With a Robust +Kernel for Face Recognition and Verification +Stefanos Zafeiriou, Georgios Tzimiropoulos, Maria Petrou, +nd Tania Stathaki"
+78045e2b93745b16a174137074e430ccd5ff53ff,Hedging Deep Features for Visual Tracking.,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI +Hedging Deep Features for Visual Tracking +Yuankai Qi, Shengping Zhang, Lei Qin, Qingming Huang, Hongxun Yao, Jongwoo Lim, and Ming-Hsuan Yang"
+78342d17c6c6fff00cf1b20602f3213a3f61ba56,Collaborative Discriminant Locality Preserving Projections With its Application to Face Recognition,"Collaborative Discriminant Locality Preserving Projections With its Application +to Face Recognition +Sheng Huanga,c, Dan Yanga,b,∗, Dong Yangc, Ahmed Elgammalc +College of Computer Science at Chongqing University, Chonqing, 400044, China +School of Software Engineering at Chongqing University Chonqing, 400044, China +Department of Computer Science at Rutgers University, Piscataway, NJ, 08854, USA"
78f438ed17f08bfe71dfb205ac447ce0561250c6,Bridging the Semantic Gap : Image and video Understanding by Exploiting Attributes,
+78f7304ba4c853c568dc4e38fef35aa2c003e3f3,Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines,"visual cortex with centered Gaussian-binary deep +Boltzmann machines +Nan Wang +Institut f¨ur Neuroinformatik +Ruhr-Universit¨at Bochum +Bochum, 44780, Germany +Dirk Jancke +Institut f¨ur Neuroinformatik +Ruhr-Universit¨at Bochum +Bochum, 44780, Germany +Laurenz Wiskott +Institut f¨ur Neuroinformatik +Ruhr-Universit¨at Bochum +Bochum, 44780, Germany"
+78c9a63be8e07dc6acb90f4fe3f06821719eaa34,Hierarchical online domain adaptation of deformable part-based models,"Hierarchical online domain adaptation of deformable part-based models +Jiaolong Xu1, David V´azquez2, Krystian Mikolajczyk3 and Antonio M. L´opez1"
+7882c67f555b761e10ecc70216db25382890d9d7,Automated Characterization of Stenosis in Invasive Coronary Angiography Images with Convolutional Neural Networks,"Automated Characterization of Stenosis in Invasive Coronary Angiography Images with Convolutional +Neural Networks"
781c2553c4ed2a3147bbf78ad57ef9d0aeb6c7ed,Tubelets: Unsupervised Action Proposals from Spatiotemporal Super-Voxels,"Int J Comput Vis DOI 10.1007/s11263-017-1023-9 Tubelets: Unsupervised Action Proposals from Spatiotemporal @@ -16957,11 +58950,33 @@ Cees G. M. Snoek1 · Jan van Gemert2 · Hervé Jégou3 · Patrick Bouthemy3 · Received: 25 June 2016 / Accepted: 18 May 2017 © The Author(s) 2017. This article is an open access publication"
+7803206f024ba6887d93e8aec91dd0097ffc5165,Automatic detection of facial actions from 3D data,"Automatic Detection of Facial Actions from 3D Data +Arman Savran +Electrical and Electronics Engineering Department +Bo˘gazic¸i University, Istanbul, Turkey +B¨ulent Sankur"
+78598c69201cccfc060d47fc0415f2f9365035fc,A Taught-Obesrve-Ask (TOA) Method for Object Detection with Critical Supervision,"A Taught-Obesrve-Ask (TOA) Method for Object +Detection with Critical Supervision +Chi-Hao Wu, Qin Huang, Siyang Li, and C.-C. Jay Kuo, Fellow, IEEE"
+78a144d5dce1a61c92420e77c11116f541a7617f,Box Aggregation for Proposal Decimation: Last Mile of Object Detection,"Box Aggregation for Proposal Decimation: Last Mile of Object Detection +The Chinese University of Hong Kong ♯Stanford University ‡Shanghai Jiao Tong University +Shu Liu† Cewu Lu♯,‡ +Jiaya Jia†"
78df7d3fdd5c32f037fb5cc2a7c104ac1743d74e,Temporal Pyramid Pooling-Based Convolutional Neural Network for Action Recognition,"TEMPORAL PYRAMID POOLING CNN FOR ACTION RECOGNITION Temporal Pyramid Pooling Based Convolutional Neural Network for Action Recognition Peng Wang, Yuanzhouhan Cao, Chunhua Shen, Lingqiao Liu, and Heng Tao Shen"
78fdf2b98cf6380623b0e20b0005a452e736181e,Dense Wide-Baseline Stereo with Varying Illumination and its Application to Face Recognition,
+7858410077f9ba94ca60d0f6b4d29509e46a4ef9,Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning,"Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning +Soravit Changpinyo +U. of Southern California +Los Angeles, CA +Wei-Lun Chao +Los Angeles, CA +U. of Southern California +U. of Southern California +Fei Sha +Los Angeles, CA"
787c1bb6d1f2341c5909a0d6d7314bced96f4681,"Face Detection and Verification in Unconstrained Videos: Challenges, Detection, and Benchmark Evaluation","Face Detection and Verification in Unconstrained Videos: Challenges, Detection, and Benchmark Evaluation @@ -16980,6 +58995,25 @@ Keywords: face recognition, face detection, face verification" Lubomir Bourdev1,2, Subhransu Maji1 and Jitendra Malik1 EECS, U.C. Berkeley, Berkeley, CA 94720 Adobe Systems, Inc., 345 Park Ave, San Jose, CA 95110"
+7809a42a833b49725f3a4bb8f70f63f4d2cee11c,Detection of Person in A Group of People Using 3-D Based Model,"Detection of Person in A Group of People Using 3-D Based Model +Dr. P. Srirama Chandra Murty1, Ch. Anuradha2, Dr. Syed Muneer3 +Assistant Professor, Dept. of Computer Science and Engineering, ANUCET, Acharya Nagarjuna +University, Guntur, India +Asst. Professor, Dept. of Computer Science and Engineering, PNC & Vijay Institute of Engineering +Computer Professional, Dept. of Computer Science and Engineering, ANUCET, Acharya Nagarjuna +nd Technology, Guntur, Andhra Pradesh, India. +University, Guntur, Andhra Pradesh, India"
+788a3faa14ca191d7f187b812047190a70798428,Interpretable Set Functions,"Interpretable Set Functions +Andrew Cotter, Maya Gupta, Heinrich Jiang, +James Muller, Taman Narayan, Serena Wang, Tao Zhu +600 Amphitheatre Parkway, Mountain View, CA 94043 +Google Research"
+780772a69b1556d5f725630dff8e79ec3ccb46bb,FieldSAFE: Dataset for Obstacle Detection in Agriculture,"FieldSAFE: Dataset for Obstacle Detection in Agriculture +Mikkel Kragh∗1, Peter Christiansen∗1, Morten S. Laursen1, Morten Larsen2, Kim +A. Steen3, Ole Green3, Henrik Karstoft1 and Rasmus N. Jørgensen1 +Department of Engineering, Aarhus University, Denmark +Conpleks Innovation ApS, Struer, Denmark +AgroIntelli, Aarhus, Denmark"
8b2c090d9007e147b8c660f9282f357336358061,Emotion Classification based on Expressions and Body Language using Convolutional Neural Networks,"Lake Forest College Lake Forest College Publications Senior Theses @@ -16997,6 +59031,23 @@ Tanveer, Aasimah S., ""Emotion Classification based on Expressions and Body Lang (2018). Senior Theses. This Thesis is brought to you for free and open access by the Student Publications at Lake Forest College Publications. It has been accepted for inclusion in Senior Theses by an authorized administrator of Lake Forest College Publications. For more information, please contact"
+8b607928c7af70259a9f8af9e08e28e6037411c8,Bayesian teaching of image categories,"Bayesian teaching of image categories +Wai Keen Vong∗ +Ravi B. Sojitra* +Newark, NJ, 07102 +Anderson Reyes +Scott Cheng-Hsin Yang +Patrick Shafto +Department of Mathematics and Computer Science, 110 Warren Street,"
+8b9c53e7d65ba7a7be3d588d00481f2ff49b5ef4,Orienting in response to gaze and the social use of gaze among children with autism spectrum disorder.,23Journal of Autism andDevelopmental Disorders ISSN 0162-3257Volume 43Number 7 J Autism Dev Disord (2013)43:1584-1596DOI 10.1007/s10803-012-1704-8Orienting in Response to Gaze and theSocial Use of Gaze among Children withAutism Spectrum DisorderAdrienne Rombough & Grace Iarocci
+8bddd0afd064e2d45ab6cf9510f2631f7438c17b,Outlier Detection using Generative Models with Theoretical Performance Guarantees,"Outlier Detection using Generative Models with +Theoretical Performance Guarantees∗ +Jirong Yi† +Anh Duc Le‡ +Tianming Wang§ +Xiaodong Wu¶ +Weiyu Xu(cid:107) +October 29, 2018"
8b547b87fd95c8ff6a74f89a2b072b60ec0a3351,Initial perceptions of a casual game to crowdsource facial expressions in the wild,"Initial Perceptions of a Casual Game to Crowdsource Facial Expressions in the Wild Chek Tien Tan @@ -17004,6 +59055,19 @@ Hemanta Sapkota Daniel Rosser Yusuf Pisan Games Studio, Faculty of Engineering and IT, University of Technology, Sydney"
+8b26744e11e5f226f187bf903b88933c5b0fcdc0,Cost-Effective Class-Imbalance Aware CNN for Vehicle Localization and Categorization in High Resolution Aerial Images,"Article +Cost-Effective Class-Imbalance Aware CNN for +Vehicle Localization and Categorization in High +Resolution Aerial Images +Feimo Li 1,2,*, Shuxiao Li 1,2,*, Chengfei Zhu 1,2, Xiaosong Lan 1,2 and Hongxing Chang 1,2 +Institute of Automation Chinese Academy of Sciences, Beijing 100190, China; +(C.Z.); (X.L.); (H.C.) +University of Chinese Academy of Science, Beijing 100049, China +* Correspondence: (F.L.); (S.L.); +Tel.: +86-188-0012-4228 (F.L.); +86-138-1077-1030 (S.L.) +Academic Editors: Qi Wang, Nicolas H. Younan, Carlos López-Martínez, Gonzalo Pajares Martinsanz, +Xiaofeng Li and Prasad S. Thenkabail +Received: 26 February 2017; Accepted: 15 May 2017; Published: 18 May 2017"
8bf57dc0dd45ed969ad9690033d44af24fd18e05,Subject-Independent Emotion Recognition from Facial Expressions using a Gabor Feature RBF Neural Classifier Trained with Virtual Samples Generated by Concurrent Self-Organizing Maps,"Subject-Independent Emotion Recognition from Facial Expressions using a Gabor Feature RBF Neural Classifier Trained with Virtual Samples Generated by Concurrent Self-Organizing Maps @@ -17012,8 +59076,99 @@ Depart. Electronics, Telecommunications & Information Technology Polytechnic University of Bucharest Splaiul Independentei No. 313, Sector 6, Bucharest, ROMANIA"
+8bdbb685174d6023e63c55fdf9ad9b2ac78e79bd,Learning Human Poses from Actions-Supplementary Material,"ADITYA, JAWAHAR, PAWAN: LEARNING HUMAN POSES FROM ACTIONS +Learning Human Poses from Actions - +Supplementary Material +Aditya Arun1 +C.V. Jawahar1 +M. Pawan Kumar2 +IIIT Hyderabad +University of Oxford & +The Alan Turing Institute +In this supplementary material, we provide additional details on optimization of our +learning objective, implementation details, and visualization of the learning process. We +lso provide additional results of training a different architecture for human pose estimation +on two data sets. +Optimization +In this section, we provide details of optimization presented in section 3.5 of the paper. +.1 Learning Objective +We represent the prediction distribution using a DISCO Net, which we denote by Prw, w +eing the parameter of the network. Similarly, we represent the conditional distribution using +set of DISCO Nets, which we denote by Prθθθ . The set of parameters for the conditional +networks is denoted by θθθ. We compute samples from the prediction network as {hw"
+8b9f529700a93a2ff6e227c76a1333883a1f6213,PREMOC: Plataforma de reconocimiento multimodal de emociones,"PREMOC: Plataforma de reconocimiento multimodal +de emociones +Ramón Zatarain-Cabada, María Lucia Barrón-Estrada, Gilberto Muñoz-Sandoval +Instituto Tecnológico de Culiacán, Culiacán, Sinaloa, +México +{rzaratain, lbarron, +Resumen. En años recientes la computación afectiva ha venido a mejorar la +interacción humano-computadora, pues ayuda a la computadora a conocer el +estado afectivo del usuario para mejorar la toma de decisiones. Este artículo +presenta los avances en el proyecto PREMOC, una plataforma que brinda un +servicio web para el reconocimiento de emociones en texto, imágenes de rostros, +sonidos de voz y señales EEG de manera mono-modal y multimodal. PREMOC +yuda a los desarrolladores a integrar el reconocimiento de afecto a sus +plicaciones o sistemas de software. Cada uno de los reconocedores se +implementó aplicando diferentes técnicas tanto para extraer características como +para clasificar emociones; además para el reconocimiento multimodal se +integraron las emociones mediante un sistema difuso. Esta plataforma ya está +siendo utilizada por diferentes proyectos en el laboratorio de la Maestría en +Ciencias de la Computación del Instituto Tecnológico de Culiacán. +Palabras claves: Computación afectiva, inteligencia artificial, reconocimiento"
+8b8b3375bc51ae357528a1f015c4d094418c9f71,"An Efficient Feature Extraction Method, Global Between Maximum and Local Within Minimum, and Its Applications","Hindawi Publishing Corporation +Mathematical Problems in Engineering +Volume 2011, Article ID 176058, 15 pages +doi:10.1155/2011/176058 +Research Article +An Efficient Feature Extraction Method, +Global Between Maximum and Local Within +Minimum, and Its Applications +Lei Wang,1, 2 Jiangshe Zhang,1, 2 and Fei Zang1, 2 +School of Science, Xi’an Jiaotong University, Xi’an 710049, China +State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, +Xi’an 710049, China +Correspondence should be addressed to Lei Wang, +Received 28 March 2011; Revised 16 April 2011; Accepted 18 April 2011 +Academic Editor: Jyh Horng Chou +Copyright q 2011 Lei Wang et al. This is an open access article distributed under the Creative +Commons Attribution License, which permits unrestricted use, distribution, and reproduction in +ny medium, provided the original work is properly cited. +Feature extraction plays an important role in preprocessing procedure in dealing with small +sample size problems. Considering the fact that LDA, LPP, and many other existing methods are"
8b744786137cf6be766778344d9f13abf4ec0683,And Summarization by Sub-modular Inference,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE ICASSP 2016"
+8b879863237d315997857a5585afb2bbbf78c622,Social Network Analysis as a Tool for Improving Enterprise Architecture,"Proceedings of the 5th International KES Symposium on Agents and Multi-agent +Systems, KES-AMSTA 2011. Manchester, UK, June 29 - July 1, 2011 +Lecture Notes in Artificial Intelligence LNAI, Volume 6682, 2011, pp. 651-660 +DOI: 10.1007/978-3-642-22000-5_67 +Social Network Analysis as a Tool +for Improving Enterprise Architecture +Przemysław Kazienko, Radosław Michalski, Sebastian Palus +Institute of Informatics, Wrocław University of Technology +Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland +{kazienko, radoslaw.michalski,"
+8bb4d90d5b97e8d08d2aaa99e9c075a506b3108a,Generating Diverse Clusterings,"Generating Diverse Clusterings +Anonymous Author(s)"
+8b64dbeac77fe8d6bf440311337451f9f61b9ea0,Image-based approaches to hair modeling,"Image-Based Approaches to Hair Modeling +Dissertation +Erlangung des Doktorgrades (Dr. rer. nat) +Mathematisch-Naturwissenschaftlichen Fakult¨at +Rheinischen Friedrich-Wilhelms-Universit¨at Bonn +vorgelegt von +Tom´as Lay Herrera +Havanna +Bonn, November 2012"
+8bbafa3efb7b96adb95128ea2a30a363bfe06812,Towards usable authentication on mobile phones: An evaluation of speaker and face recognition on off-the-shelf handsets,"Towards usable authentication on mobile phones: An +evaluation of speaker and face recognition on off-the-shelf +handsets +Rene Mayrhofer +University of Applied Sciences Upper Austria +Softwarepark 11, A-4232 Hagenberg, Austria +University of Applied Sciences Upper Austria +Softwarepark 11, A-4232 Hagenberg, Austria +Thomas Kaiser +hagenberg.at"
8bf647fed40bdc9e35560021636dfb892a46720e,Learning to hash-tag videos with Tag2Vec,"Learning to Hash-tag Videos with Tag2Vec Aditya Singh Saurabh Saini @@ -17023,6 +59178,32 @@ P J Narayanan http://cvit.iiit.ac.in/research/projects/tag2vec Figure 1. Learning a direct mapping from videos to hash-tags : sample frames from short video clips with user-given hash-tags (left); a sample frame from a query video and hash-tags suggested by our system for this query (right)."
+8b2f99b0106143fd0193fcbf2b07eba80dc7f8dd,Enhancing Recommender Systems for TV by Face Recognition,
+8b29ee0a47efc11071ab8baec8369fd54970bfbb,Features Extraction for Low-Power Face Verification,"Thèse présentée à la faculté des sciences pour +l’obtention du grade de docteur ès sciences +Features Extraction for +Low-Power Face Verification +Patrick Stadelmann +Acceptée sur proposition du jury : +Prof. Fausto Pellandini, directeur de thèse +PD Dr. Michael Ansorge, co-directeur de thèse +Prof. Pierre-André Farine, rapporteur +Dr. Nicolas Blanc, rapporteur +Soutenue le 23 mai 2008 +Institut de Microtechnique +Université de Neuchâtel"
+8b20737b454fa8c2848979b5c76be9915a65a75f,Automated Object Recognition Using Multiple X-ray Views,"Automated Object Recognition +Using Multiple X-ray Views +Domingo Mery1 – Vladimir Riffo1, 2 +Department of Computer Science, Pontificia +Universidad Católica de Chile. +Department of Computer Engineering and +Computer Science, Universidad de Atacama. +Av. Vicuña Mackenna 4860(143) – Santiago de +Chile. +Av. Copayapu 485 – Copiapó, Chile. +http://dmery.ing.puc.cl +http://www.ing.puc.cl/~vriffo1"
8bb21b1f8d6952d77cae95b4e0b8964c9e0201b0,Multimodal Interaction on a Social Robotic Platform,"Methoden t 11/2013 (cid:2)(cid:2)(cid:2) @@ -17048,6 +59229,88 @@ Walter J. Scheirer, Laurence G. Hassebrook, Proc. of SPIE Vol. 8712, 87120Q · CCC code: 0277-786X/13/$18 · doi: 10.1117/12.2018974 Proc. of SPIE Vol. 8712 87120Q-1 From: http://proceedings.spiedigitallibrary.org/ on 06/07/2013 Terms of Use: http://spiedl.org/terms"
+8bff7353fa4f75629ea418ca8db60477a751db93,Invariance of Weight Distributions in Rectified MLPs,"Invariance of Weight Distributions in Rectified MLPs +Russell Tsuchida 1 Farbod Roosta-Khorasani 2 3 Marcus Gallagher 1"
+8b9db19d0d3e2a7d740be811810a043a04d6226a,An Attention-based Regression Model for Grounding Textual Phrases in Images,Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
+8bda09b2fb85c317c6361aee1935bcbcf87c1c70,Score Normalization in Multimodal Systems using Generalized Extreme Value Distribution,"Score Normalization in Multimodal +Systems using Generalized Extreme Value +Distribution +Renu Sharma1, 2 1Centre for Development of Advanced Computing, +Mumbai, India +Sukhendu Das2 2Indian Institute of Technology, Madras, India +Padmaja Joshi1"
+8b632db02220806cd62e35fdebb3ede58243dee0,Recognizing Partially Occluded Faces from a Single Sample Per Class Using String-Based Matching,"Recognizing Partially Occluded Faces from a +Single Sample Per Class Using String-Based +Matching +Weiping Chen1 and Yongsheng Gao1,2 +School of Engineering, Griffith University, Australia +National ICT Australia, Queensland Research Lab"
+8b9e94fb3bb64389e9765ffde365862231b5972c,Fast Eye Tracking and Feature Measurement using a Multi-stage Particle Filter,
+8bba26895022749e2273729f96051571eabc7b99,Natural language acquisition in recurrent neural architectures,"Natural Language Acquisition in +Recurrent Neural Architectures +Dissertation +submitted to the Universität Hamburg, +Faculty of Mathematics, +Informatics +nd Natural Sciences, Department +fulfilment +of the requirements for the degree of +Doctor rerum naturalium (Dr. rer. nat.) +Informatics, +in partial +Dipl.-Inform. Stefan Heinrich +Hamburg, 2016"
+135fcdab631ab30ae837a743040f1c8751268e41,DeepStyle: Multimodal Search Engine for Fashion and Interior Design,"SUBMITTED TO IEEE TRANSACTIONS ON MULTIMEDIA +DeepStyle: Multimodal Search Engine +for Fashion and Interior Design +Ivona Tautkute1, 3, Tomasz Trzci´nski2, 3, Aleksander Skorupa3, Lukasz Brocki1 and Krzysztof Marasek1"
+139bb2a4034a0498934185e8c6d515d8f9330e2a,One-Shot Segmentation in Clutter,"One-Shot Segmentation in Clutter +Claudio Michaelis 1 2 Matthias Bethge 1 2 3 4 Alexander S. Ecker 1 2 4"
+13f9922632ff5311046229b849615fcd2f5d0c06,On Multi-scale differential features for face recognition,"On Multi-scale differential features for face recognition +Center for Intelligent Information Retrieval +S. Ravela +Allen R. Hanson +Vision Laboratory +Dept. of Computer Science, University of Massachusetts at Amherst, MA, 01002"
+135fe2a0a0e6b726e5d81299edad4b3ce39d6614,Multichannel-Kernel Canonical Correlation Analysis for Cross-View Person Reidentification,"This is a pre-print version, the final version of the manuscript with more experiments can be found at: +https://doi.org/10.1145/3038916 +Multi Channel-Kernel Canonical Correlation +Analysis for Cross-View Person Re-Identification +Giuseppe Lisanti, Svebor Karaman, Iacopo Masi"
+13a82da2bfa24583caf78ab1d14b5cfa4798b3b3,Robust face hallucination using quantization-adaptive dictionaries,"Robust Face Hallucination using +Quantization-Adaptive Dictionaries +Reuben Farrugia +Christine Guillemot +IEEE Int. Conf. on Image Processing, Arizona, USA +6th September 2016"
+137457bbf46009b25d7f6d853083b6da02bfd6b9,Following Eye Gaze Activates a Patch in the Posterior Temporal Cortex That Is not Part of the Human “Face Patch” System,"New Research +Cognition and Behavior +Following Eye Gaze Activates a Patch in the +Posterior Temporal Cortex That Is not Part of the +Human “Face Patch” System +Kira Marquardt,1,ⴱ Hamidreza Ramezanpour,1,2,3,ⴱ Peter W. Dicke,1 and Peter Thier1,4 +DOI:http://dx.doi.org/10.1523/ENEURO.0317-16.2017 +Department of Cognitive Neurology, Hertie Institute for Clinical Brain Research, 72076 Tübingen, Germany, +Graduate School of Neural and Behavioural Sciences, University of Tübingen, 72074 Tübingen, Germany, +International Max Planck Research School for Cognitive and Systems Neuroscience, University of Tübingen, 72074 +Tübingen, Germany, 4Werner Reichardt Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076 +Tübingen, Germany"
+13ab059e6b592ca7bcb14337316ec1ac14aa5c5a,Constrained planar cuts - Object partitioning for point clouds,"Constrained Planar Cuts - Object Partitioning for Point Clouds +Markus Schoeler, Jeremie Papon and Florentin W¨org¨otter +Bernstein Center for Computational Neuroscience (BCCN) +III Physikalisches Institut - Biophysik, Georg-August University of G¨ottingen"
+13b2e01030ae41983003e3ae53b5bb3ed3e764f0,Detection-Tracking for Efficient Person Analysis: The DetTA Pipeline,"Detection-Tracking for Efficient Person Analysis: The DetTA Pipeline +Stefan Breuers1, Lucas Beyer1, Umer Rafi1, Bastian Leibe1"
+130bf256f4cc3dded4fb701f74f6a34992be639b,A Robust Multiwavelet-Based Watermarking Scheme for Copyright Protection of Digital Images Using Human Visual System,"The International Arab Journal of Information Technology, Vol. 10, No. 6, November 2013 527 +A Robust Multiwavelet-Based Watermarking +Scheme for Copyright Protection of Digital +Images using Human Visual System +Padmanabhareddy Vundela1 and Varadarajan Sourirajan2 +Department of Information Technology, Vardhaman College of Engineering, India +Department of Electrical and Electronic Engineering, S.V. University College of Engineering, India"
+13f8c13cfbf2a504f02745bd44da4ac40fd8f8df,Feature Sets and Dimensionality Reduction for Visual Object Detection,"Author manuscript, published in ""British Machine Vision Conference, Aberystwyth : +Royaume-Uni (2010)"" +DOI : 10.5244/C.24.112"
134db6ca13f808a848321d3998e4fe4cdc52fbc2,Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 2, APRIL 2006 Dynamics of Facial Expression: Recognition of Facial Actions and Their Temporal Segments @@ -17057,12 +59320,50 @@ Maja Pantic, Member, IEEE, and Ioannis Patras, Member, IEEE" Active Clustering with Model-Based Uncertainty Reduction Caiming Xiong, David M. Johnson, and Jason J. Corso Senior Member, IEEE"
+13f03aab62fc29748114a0219426613cf3ba76ae,MORPH-II: Feature Vector Documentation,"MORPH-II: Feature Vector Documentation +Troy P. Kling +NSF-REU Site at UNC Wilmington, Summer 2017 +MORPH-II Subsets +Four different subsets of the MORPH-II database were selected for a wide range of purposes, including age +estimate, gender and race classification, and facial recognition. +• The “Full” data set contains all 55,134 mugshots [1]. +• The “Partial” data set contains 1,000 mugshots randomly selected from the full data set. +• The “Partial (Even)” data set contains 1,000 mugshots selected from the full data set according to very +strict rules and is intended mainly for age estimation tasks. The subjects range in age from 21 to 45, +with exactly 40 subjects in each age category (thus the term “even” in the name of the data set). Of +these 40 subjects in each age group, exactly 30 are male and 10 are female, giving rise to a 3:1 gender +ratio. Additionally, half of the males in each age group are black, and the same goes for the females, +so there is a precise 1:1 ratio of black to white individuals. No subject is represented more than once +in this data set, so it should not be used for face recognition tasks. +• The “Recognition” data set contains 1,660 mugshots selected from the full data set according to certain +rules and is intended to be used for facial recognition tasks. There are 166 subjects present in the data +set – 83 males and 83 females – each of whom has exactly 10 images, usually taken over the span of +multiple years. No restrictions on age or race were placed on this data set. +Image Preprocessing"
+134fe1c4f45cea3339c094fee817e7a024d73d88,Inferring door locations from a teammate's trajectory in stealth human-robot team operations,"Inferring door locations from a teammate’s trajectory in stealth +human-robot team operations +Jean Oh, Luis Navarro-Serment, Arne Supp´e, Anthony Stentz and Martial Hebert1"
1369e9f174760ea592a94177dbcab9ed29be1649,Geometrical facial modeling for emotion recognition,"Geometrical Facial Modeling for Emotion Recognition Giampaolo L. Libralon and Roseli A. F. Romero"
133900a0e7450979c9491951a5f1c2a403a180f0,Social Grouping for Multi-Target Tracking and Head Pose Estimation in Video,"JOURNAL OF LATEX CLASS FILES Social Grouping for Multi-target Tracking and Head Pose Estimation in Video Zhen Qin and Christian R. Shelton"
+131059ea24073d08de0bd153f9caddc123911e51,Facial emotional recognition in schizophrenia: preliminary results of the Virtual Reality Program for Facial Emotional Recognition Reconhecimento emocional de faces na esquizofrenia: resultados preliminares do Programa de Realidade Virtual para o Reconhecimento Emocional de Faces,"Facial emotional recognition in schizophrenia: preliminary results of the Virtual +Reality Program for Facial Emotional Recognition +Reconhecimento emocional de faces na esquizofrenia: resultados preliminares do Programa de Realidade Virtual +para o Reconhecimento Emocional de Faces +Teresa souTo1,2, alexandre BapTisTa1, diana Tavares1,3, CrisTina Queirós1,2, anTónio MarQues1,3 +Psychosocial Rehabilitation Laboratory of Faculty of Psychology and Educational Sciences, Porto University/School of Allied Health Sciences, Porto Polytechnic Institute (FPCEUP/ESTSPIPP), Porto, +Portugal. +FPCEUP, Porto, Portugal. +ESTSPIPP, Porto, Portugal. +Institution where the study was elaborated: Faculty of Psychology and Educational Sciences, Porto University, Portugal. +Received: 11/6/2012 – Accepted: 2/14/2013"
+13b8d657f0f9a0178339570bdc153bfd10a81300,Harvesting large-scale weakly-tagged image databases from the web,"Harvesting Large-Scale Weakly-Tagged Image Databases from the Web +Jianping Fan1, Yi Shen1, Ning Zhou1, Yuli Gao2 +Department of Computer Science, UNC-Charlotte, NC28223, USA +Multimedia Interaction and Understanding, HP Labs, Palo Alto, CA94304, USA"
13db9466d2ddf3c30b0fd66db8bfe6289e880802,Transfer Subspace Learning Model for Face Recognition at a Distance,"I.J. Image, Graphics and Signal Processing, 2017, 1, 27-32 Published Online January 2017 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijigsp.2017.01.04 @@ -17078,6 +59379,36 @@ Vibha Vyas College of Engineering Pune,India Email: learning algorithms work"
+13ec6666b8b722ad9eb68a21a302e3f2f1ab4df7,Biometric Human Identification of Hand Geometry Features Using Discrete Wavelet Transform,"Biometric Human Identification of Hand +Geometry Features Using Discrete +Wavelet Transform +Osslan Osiris Vergara Villegas, Humberto de Jesús Ochoa Domínguez, +Vianey Guadalupe Cruz Sánchez, Leticia Ortega Maynez +nd Hiram Madero Orozco +Universidad Autónoma de Ciudad Juárez +Instituto de Ingeniería y Tecnología +Mexico +. Introduction +Since the security factor became a basic need for civilization, a lot of systems have been +developed. Those systems, try to ensure the safety in all the things that driving a certain +degree of exclusivity. Historically, keys, cards and passwords were used as security systems; +however, these methods are vulnerable to loss and theft. As a result biometric identification +methods emerge in order to tackle the disadvantages of the non biometric classical methods. +Biometrics, +is an emerging technology that addresses the automated identification of +individuals, based on their physiological and behavioral traits. The main advantage of +iometric methods is the ability to recognize, which is made by means of a physical feature or +unique pattern (Jain et al. (2008)). With these methods and individual can hardly be victim"
+13ae3c8afef5a0d6f4c9e684da9fc1fa96caaeb6,Online Anomaly Detection in Crowd Scenes via Structure Analysis,"Online Anomaly Detection in Crowd Scenes +via Structure Analysis +Yuan Yuan, Senior Member, IEEE, Jianwu Fang, and Qi Wang"
+13caf4d2e0a4b6fcfcd4b9e8e2341b8ebd38258d,Joint Learning of Siamese CNNs and Temporally Constrained Metrics for Tracklet Association,"Joint Learning of Siamese CNNs and Temporally +Constrained Metrics for Tracklet Association +Bing Wang, Student Member, IEEE, Li Wang, Member, IEEE, Bing Shuai, Student Member, IEEE, +Zhen Zuo, Student Member, IEEE, Ting Liu, Student Member, IEEE, Kap Luk Chan, Member, IEEE, and +Gang Wang, Member, IEEE"
+13aac86217231a7d118ecdff444ee07234fcff50,Classification via Incoherent Subspaces,"Classification via Incoherent Subspaces +Karin Schnass, Pierre Vandergheynst, Senior Member, IEEE"
13141284f1a7e1fe255f5c2b22c09e32f0a4d465,Object Tracking by Oversampling Local Features,"Object Tracking by Oversampling Local Features Federico Pernici and Alberto Del Bimbo"
@@ -17101,6 +59432,18 @@ Charles E. Hughes University of Central Florida 85 PUBLICATIONS 1,248 CITATIONS SEE PROFILE"
+135fc59c8adb8d97a0a8dacf615f1b18a2102372,Language-Based Image Editing with Recurrent Attentive Models,"Language-Based Image Editing with Recurrent Attentive Models +Jianbo Chen∗, Yelong Shen†, Jianfeng Gao†, Jingjing Liu†, Xiaodong Liu† +University of California, Berkeley∗ and Microsoft Research† +yeshen, jfgao, jingjl,"
+1373195c26eab581138579f7389cdf8b7a94a4bb,Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing,"Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing +Magnus Wrenninge1,∗ Jonas Unger1,2,† +7D Labs +Link¨oping University, Sweden +Figure 1: Example image from Synscapes."
+13631379de6487fd0571e5919f4efb65d16c1633,Accelerated Inference in Markov Random Fields via Smooth Riemannian Optimization,"Accelerated Inference in Markov Random Fields +via Smooth Riemannian Optimization +Siyi Hu and Luca Carlone"
133da0d8c7719a219537f4a11c915bf74c320da7,A Novel Method for 3D Image Segmentation with Fusion of Two Images using Color K-means Algorithm,"International Journal of Computer Applications (0975 – 8887) Volume 123 – No.4, August 2015 A Novel Method for 3D Image Segmentation with Fusion @@ -17113,6 +59456,14 @@ Priusha Narwariya Dept. of CSE ITM Universe Gwalior"
+134dd3bb637b51c61fa9d2332f11e39efc0b359a,High-level activity learning and recognition in structured environments,"High-level activity learning and recognition in +structured environments +John Patrick Greenall +Submitted in accordance with the requirements +for the degree of Doctor of Philosophy. +The University of Leeds +School of Computing +June 2012"
133f01aec1534604d184d56de866a4bd531dac87,Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics,"Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics @@ -17134,6 +59485,28 @@ Downloaded from http://hdl.handle.net/10072/30001 Griffith Research Online https://research-repository.griffith.edu.au"
+13451899558d7217206b275ca0bb1f48fa4afdd9,Hidden Markov Models Training by a Particle Swarm Optimization Algorithm,"Journal of Mathematical Modelling and Algorithms (2007) 6: 175–193 +DOI: 10.1007/s10852-005-9037-7 +# Springer 2006 +Hidden Markov Models Training by a Particle +Swarm Optimization Algorithm +, NICOLAS MONMARCHE´ +SE´ BASTIEN AUPETIT +nd MOHAMED SLIMANE +Laboratoire d’Informatique, Polytech’Tours, Universite´ Franc¸ois-Rabelais de Tours, +64 avenue Jean Portalis, 37200 Tours, France. +e-mail: {sebastien.aupetit, nicolas.monmarche, +(Received 16 July 2005; in final form 22 December 2005; published online 28 February 2006) +In this work we consider the problem of Hidden Markov Models (HMM) training. This"
+132781c1b2495ff0e792b46b94fdf33867394e4a,Autistic Traits and Symptoms of Social Anxiety are Differentially Related to Attention to Others’ Eyes in Social Anxiety Disorder,"J Autism Dev Disord (2017) 47:3814–3821 +DOI 10.1007/s10803-016-2978-z +S.I. : ANXIETY IN AUTISM SPECTRUM DISORDERS +Autistic Traits and Symptoms of Social Anxiety are Differentially +Related to Attention to Others’ Eyes in Social Anxiety Disorder +Johan Lundin Kleberg1 · Jens Högström2,3 · Martina Nord2,3 · Sven Bölte4,5 · +Eva Serlachius2,3 · Terje Falck‑Ytter1,4,5 +Published online: 20 December 2016 +© The Author(s) 2016. This article is published with open access at Springerlink.com"
132f88626f6760d769c95984212ed0915790b625,Exploring Entity Resolution for Multimedia Person Identification,"UC Irvine UC Irvine Electronic Theses and Dissertations Title @@ -17156,14 +59529,72 @@ Juan Rodrı´guez-Gonza´ lez, Nuo Li, John J Macklin, James W Phillips, Brett D Mensh, Kristin Branson, Adam W Hantman* Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States"
+138778d75fc4e2fd490897ac064b9ac84b6b9f04,Generation and visualization of emotional states in virtual characters,"COMPUTER ANIMATION AND VIRTUAL WORLDS +Comp. Anim. Virtual Worlds 2008; 19: 259–270 +Published online 25 July 2008 in Wiley InterScience +(www.interscience.wiley.com) DOI: 10.1002/cav.234 +........................................................................................... +Generation and visualization of +emotional states in virtual characters +By Diana Arellano*, Javier Varona and Francisco J. Perales +.......................................................................... +This paper presents an affective model that determines the emotional state of a character +ccording to the personality traits and the experienced emotions. We consider an emotional +state as the layer between personality and emotion. The proposed affective model offers a +mapping between emotions and emotional states. To evidence emotional states of a virtual +haracter, we can attribute them facial expressions based on their associated emotions. +Facial expressions for intermediate emotions are generated automatically from expressions +for universal emotions. The experiments show coherent emotional states produced by a +simulated story. They also present how the corresponding emotions were represented +through dynamic and static facial expressions. Finally, the obtained results demonstrate the +satisfactory recognition by a group of people unfamiliar with the work described. Copyright +© 2008 John Wiley & Sons, Ltd."
13afc4f8d08f766479577db2083f9632544c7ea6,Multiple kernel learning for emotion recognition in the wild,"Multiple Kernel Learning for Emotion Recognition in the Wild Karan Sikka, Karmen Dykstra, Suchitra Sathyanarayana, Gwen Littlewort and Marian S. Bartlett Machine Perception Laboratory EmotiW Challenge, ICMI, 2013"
+13c4a4359e9d7f5b2abe1b9542c0950946b0565a,Learning sparse tag patterns for social image classification,"This document is downloaded from DR-NTU, Nanyang Technological +University Library, Singapore. +Title +Learning sparse tag patterns for social image +lassification +Author(s) +Lin, Jie; Duan, Ling-Yu; Yuan, Junsong; Li, Qingyong; +Luo, Siwei +Citation +http://hdl.handle.net/10220/12960 +Rights"
+13f07d51c073964d11f9af6463fe3ffe5475c393,"Part-Based Pedestrian Detection and Feature-Based Tracking for Driver Assistance: Real-Time, Robust Algorithms, and Evaluation","This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +Part-Based Pedestrian Detection and Feature-Based +Tracking for Driver Assistance: Real-Time, +Robust Algorithms, and Evaluation +Antonio Prioletti, Student Member, IEEE, Andreas Møgelmose, Student Member, IEEE, Paolo Grisleri, +Mohan Manubhai Trivedi, Fellow, IEEE, Alberto Broggi, Senior Member, IEEE, and +Thomas B. Moeslund, Member, IEEE"
13188a88bbf83a18dd4964e3f89d0bc0a4d3a0bd,Image Normalization Robust using Histogram Equalization and Logarithm Transform Frequency DCT Coefficients for Illumination in Facial Images,"Dr. V. S. Manjula HOD, Department of Computer Science, St. Joseph College of Information Technology, Songea, Tanzania"
+13e348264fe1077caa44e1b59c71e67a8e4b5ad9,Effect of Eyes Detection and Position Estimation Methods on the Accuracy of Comparative Testing of Face Detection Algorithms,"EFFECT OF EYES DETECTION AND POSITION ESTIMATION METHODS +ON THE ACCURACY OF COMPARATIVE TESTING OF FACE +DETECTION ALGORITHMS1 +N. Degtyarev, O. Seredin +Tula State University, 92 Lenin Ave., Tula 300600, Russian Federation; +Phone: +7(4872)353637; E-mail: +Many published comparisons of face detection algorithms used different evaluation +procedures for each algorithm or even contain only a summary of the originally reported +performance among several face detection algorithms on the pair of small datasets. Deg- +tyarev et al. have proposed the FD algorithm evaluation procedure containing model of +face representation conversion unifying the FD algorithms comparison procedures, +which makes such evaluation more reliable. However, there is no evidence that such +""conversion"" does not diminish the localization accuracy. The aim of this work is to ex- +mined the effects of two different face representation conversion techniques - eyes es- +timation model proposed by Degtyarev et al. and highly scored eyes detection method +proposed by Bolme et al. and based on ASE filters - via routine testing. +Introduction +Face detection (FD) algorithms are getting +widely used in the modern world: security sys- +tems, interactive user interfaces, advertisement"
13d9da779138af990d761ef84556e3e5c1e0eb94,Learning to Locate Informative Features for Visual Identification,"Int J Comput Vis (2008) 77: 3–24 DOI 10.1007/s11263-007-0093-5 Learning to Locate Informative Features for Visual Identification @@ -17176,6 +59607,20 @@ CONVOLUTIONAL NEURAL NETWORK Yunfeng Wang(cid:63), Wengang Zhou(cid:63), Qilin Zhang†, Xiaotian Zhu(cid:63), Houqiang Li(cid:63) (cid:63)University of Science and Technology of China, Hefei, Anhui, China HERE Technologies, Chicago, Illinois, USA"
+7ff83f10e49e81ce6f66270e8f3f42dd2c6eb3ed,PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report,"PIRM Challenge on Perceptual Image Enhancement +on Smartphones: Report +Andrey Ignatov, Radu Timofte, Thang Van Vu, Tung Minh Luu, Trung X Pham, Cao Van Nguyen, +Yongwoo Kim, Jae-Seok Choi, Munchurl Kim, Jie Huang, Jiewen Ran, Chen Xing, Xingguang Zhou, +Pengfei Zhu, Mingrui Geng, Yawei Li, Eirikur Agustsson, Shuhang Gu, Luc Van Gool, Etienne de Stoutz, +Nikolay Kobyshev, Kehui Nie, Yan Zhao, Gen Li, Tong Tong, Qinquan Gao, Liu Hanwen, Pablo Navarrete +Michelini, Zhu Dan, Hu Fengshuo, Zheng Hui, Xiumei Wang, Lirui Deng, Rang Meng, Jinghui Qin, Yukai +Shi, Wushao Wen, Liang Lin, Ruicheng Feng, Shixiang Wu, Chao Dong, Yu Qiao, Subeesh Vasu, Nimisha +Thekke Madam, Praveen Kandula, A. N. Rajagopalan, Jie Liu, Cheolkon Jung ∗"
+7fa62c091a14830ae256dc00b512f7d4b4cf5b94,Stabilizing GAN Training with Multiple Random Projections,"Under review as a conference paper at ICLR 2018 +Stabilizing GAN Training with +Multiple Random Projections +Anonymous authors +Paper under double-blind review"
7ff42ee09c9b1a508080837a3dc2ea780a1a839b,Data Fusion for Real-time Multimodal Emotion Recognition through Webcams and Microphones in E-Learning,"Data Fusion for Real-time Multimodal Emotion Recognition through Webcams nd Microphones in E-Learning Kiavash Bahreini*, Rob Nadolski*, Wim Westera* @@ -17183,6 +59628,14 @@ Kiavash Bahreini*, Rob Nadolski*, Wim Westera* Psychology and Educational Sciences, Open University of the Netherlands, Valkenburgerweg 77, 6419 AT Heerlen, The Netherlands {kiavash.bahreini, rob.nadolski,"
+7fbff9fa2ba7a7ff57a433e8bb19cfd99d52132d,A probabilistic framework for car detection in images using context and scale,"RiverCentre, Saint Paul, Minnesota, USA +May 14-18, 2012 +978-1-4673-1405-3/12/$31.00 ©2012 IEEE"
+7fdcb6638a9e01986cd8fb4133b4448700087faf,Expression-Invariant Multispectral Face Recognition: You Can Smile Now!,"Expression-Invariant Multispectral Face Recognition: +You Can Smile Now! +Ioannis A. Kakadiarisa, George Passalisa, George Todericia, Yunliang Lua, +Nikos Karampatziakisa, Najam Murtuzaa, Theoharis Theoharisa +Computational Biomedicine Lab, Dept. of Computer Science, Univ. of Houston, TX, USA"
7f533bd8f32525e2934a66a5b57d9143d7a89ee1,Audio-Visual Identity Grounding for Enabling Cross Media Search,"Audio-Visual Identity Grounding for Enabling Cross Media Search Kevin Brady, MIT Lincoln Laboratory Paper ID 22"
@@ -17213,23 +59666,136 @@ Paul Natsev Balakrishnan Varadarajan Sudheendra Vijayanarasimhan Google Research"
+7f65bbc93cf414d4889773b697b1833e85f0a15f,Neural Perspective to Jigsaw Puzzle Solving,"Neural Perspective to Jigsaw Puzzle Solving +Viveka Kulharia⇤, Arnab Ghosh⇤, Nikhil Patil?, Piyush Rai +Department of Computer Science, IIT Kanpur +Kanpur, India"
+7ff0ad5c34f02b9c394ed0d8a3db9c270dc70e44,Learning a temporally invariant representation for visual tracking,"LEARNING A TEMPORALLY INVARIANT REPRESENTATION FOR VISUAL TRACKING +Chao Ma(cid:63)†, Xiaokang Yang(cid:63), Chongyang Zhang(cid:63), and Ming-Hsuan Yang† +(cid:63)Shanghai Jiao Tong University, China +University of California at Merced, USA"
+7f0fadae16cc74b6176ba940aa2f8b5a0a67e09e,An Expert Local Mesh Correlation Histograms for Biomedical Image Indexing and Retrieval,"CHAPTER 1 +An Expert Local Mesh Correlation Histograms for +Biomedical Image Indexing and Retrieval +Santosh Kumar Vipparthi, Subrahmanyam Murala, S.K. Nagar and Anil +Balaji Gonde +Santosh Kumar Vipparthi +Department of Computer Science and Engineering +Malaviya National Institute of Technology +Jaipur, India +e-mail: +Subrahmanyam Murala +Department of Electrical Engineering +Indian Institute of Technology Ropar +India +e-mail: +S.K. Nagar +Department of Electrical Engineering +Indian Institute of Technology Banaras Hindu University +India +e-mail:"
+7f7c3a99923549601c81cd5e9659ca01e8a42f47,Zero-Shot Learning of Language Models for Describing Human Actions Based on Semantic Compositionality of Actions,"PACLIC 28 +Zero-Shot Learning of Language Models for Describing Human Actions +Based on Semantic Compositionality of Actions +Hideki ASOH +National Institute of +Graduate School of Humanities and Sciences, +Ichiro KOBAYASHI +Ochanomizu University +Bunkyo-ku, Tokyo 112-8610 Japan +Advanced Industrial Science and Technology +Tsukuba, Ibaraki 305-8568 Japan"
7f36dd9ead29649ed389306790faf3b390dc0aa2,Movement Differences between Deliberate and Spontaneous Facial Expressions: Zygomaticus Major Action in Smiling.,"MOVEMENT DIFFERENCES BETWEEN DELIBERATE AND SPONTANEOUS FACIAL EXPRESSIONS: ZYGOMATICUS MAJOR ACTION IN SMILING Karen L. Schmidt, Zara Ambadar, Jeffrey F. Cohn, and L. Ian Reed"
+7f217ff1f3c21c84ed116d32e3b8d1509a306fbd,Direct Optimization through arg max for Discrete Variational Auto-Encoder,"Direct Optimization through arg max for Discrete +Variational Auto-Encoder +Guy Lorberbom (Technion), Andreea Gane (MIT), +Tommi Jaakkola (MIT), Tamir Hazan (Technion)."
7f6cd03e3b7b63fca7170e317b3bb072ec9889e0,A Face Recognition Signature Combining Patch-based Features with Soft Facial Attributes,"A Face Recognition Signature Combining Patch-based Features with Soft Facial Attributes L. Zhang, P. Dou, I.A. Kakadiaris Computational Biomedicine Lab, 4849 Calhoun Rd, Rm 373, Houston, TX 77204"
+7fa41631cdef8f7fba7e1289dd4c5f3723b172ab,A robust and isotropic curved surface representation for 3D faces description,"A robust and isotropic curved surface representation for 3D faces +description +Majdi Jribi and Faouzi Ghorbel"
+7f6a527a3dc2e526aa59a57cadb20ff727124973,A comparison of adaptive matchers for screening of faces in video surveillance,"012 IEEE Symposium on +Computational Intelligence for +Security and Defence Applications +(CISDA 2012) +Ottawa, Ontario, Canada +1 – 13 July 2012 +IEEE Catalog Number: +ISBN: +CFP12SDA-PRT +978-1-4673-1416-9"
+7f9cacb5fc126f87dbf53dd547a9fb9f58ded557,RoadNet-v2: A 10 ms Road Segmentation Using Spatial Sequence Layer,"RoadNet-v2: A 10 ms Road Segmentation Using +Spatial Sequence Layer +Yecheng Lyu and Xinming Huang +Department of Electrical and Computer Engineering +Worcester Polytechnic Institute +Worcester, MA 01609, USA"
+7f3c6bf191a8633d10fad32e23fa06a3c925ffee,The benefits of simply observing: mindful attention modulates the link between motivation and behavior.,"015, Vol. 108, No. 1, 148 –170 +0022-3514/15/$12.00 +© 2014 American Psychological Association +http://dx.doi.org/10.1037/a0038032 +The Benefits of Simply Observing: Mindful Attention Modulates the Link +Between Motivation and Behavior +Esther K. Papies +Utrecht University +Mike Keesman +Utrecht University +Tila M. Pronk +Tilburg University +Lawrence W. Barsalou +Emory University +Mindful attention, a central component of mindfulness meditation, can be conceived as becoming aware +of one’s thoughts and experiences and being able to observe them as transient mental events. Here, we +present a series of studies demonstrating the effects of applying this metacognitive perspective to one’s +spontaneous reward responses when encountering attractive stimuli. Taking a grounded cognition +perspective, we argue that reward simulations in response to attractive stimuli contribute to appetitive +ehavior and that motivational states and traits enhance these simulations. Directing mindful attention at"
7f97a36a5a634c30de5a8e8b2d1c812ca9f971ae,Incremental Classifier Learning with Generative Adversarial Networks,"Incremental Classifier Learning with Generative Adversarial Networks Yue Wu1 Yinpeng Chen2 Lijuan Wang2 Yuancheng Ye3 Zicheng Liu2 Yandong Guo2 Zhengyou Zhang2 Yun Fu1 Northeastern University 2Microsoft Research 3City University of New York"
+7ff636c82898a35d3239573f8e3a29da89c73ed4,Automatic Detection of the Uterus and Fallopian Tube Junctions in Laparoscopic Images,"Automatic Detection of the Uterus and +Fallopian Tube Junctions in Laparoscopic Images +Kristina Prokopetc, Toby Collins, and Adrien Bartoli +Image Science for Interventional Techniques (ISIT), +UMR 6284 CNRS, Universit´e d(cid:48)Auvergne, France"
+7fc5ab3743e6e9a2f4fe70152440e13a673e239b,Improved Face Recognition Rate Using HOG Features and SVM Classifier,"IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) +e-ISSN: 2278-2834,p- ISSN: 2278-8735.Volume 11, Issue 4, Ver. I (Jul.-Aug .2016), PP 34-44 +www.iosrjournals.org +Improved Face Recognition Rate Using HOG Features and SVM +Classifier +Harihara Santosh Dadi, Gopala Krishna Mohan Pillutla"
+7f04b65f2c6f96c7ce000f537fb691a93f61db52,Geometrical and Visual Feature Quantization for 3D Face Recognition,
7f268f29d2c8f58cea4946536f5e2325777fa8fa,Facial Emotion Recognition in Curvelet Domain,"Facial Emotion Recognition in Curvelet Domain Gyanendra K Verma and Bhupesh Kumar Singh Indian Institute of Informaiton Technology, Allahabad, India Allahabad, India - 211012"
+7ff1c4e0ad0dae92d4f25b93783fadde8f07276d,An efficient example-based approach for image super-resolution,"IEEE Int. Conference Neural Networks & Signal Processing +Zhenjiang, China, June 8~10, 2008 +AN EFFICIENT EXAMPLE-BASED APPROACH FOR IMAGE +SUPER-RESOLUTION +Xiaoguang Li1,2, Kin Man Lam2, Guoping Qiu3, Lansun Shen1 and Suyu Wang1 +. Signal & Information Processing Lab. Beijing University of Technology, Beijing, China, 100124 +. Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong +Polytechnic University, Hong Kong +. Department of Computer Science, Nottingham University, UK"
7f3a73babe733520112c0199ff8d26ddfc7038a0,Robust Face Identification with Small Sample Sizes using Bag of Words and Histogram of Oriented Gradients,
+7fd97bc23c85213b8b2e4d28264f04ce6dc84e74,Optimal Transformation Estimation with Semantic Cues,"Optimal Transformation Estimation with Semantic Cues +Danda Pani Paudel +Computer Vision Laboratory +D-ITET, ETH Zurich +Adlane Habed +ICube Laboratory +CNRS, University of Strasbourg +Luc Van Gool +Computer Vision Laboratory +D-ITET, ETH Zurich"
7af38f6dcfbe1cd89f2307776bcaa09c54c30a8b,Learning in Computer Vision and Beyond: Development,"eaig i C e Vii ad Beyd: Deve h . Weg @@ -17248,8 +59814,54 @@ deve way aia ea whi de deve +7a1828e181e3c8bd014c7e5fc1bcc417f122c18c,Face Perception and Test Reliabilities in Congenital Prosopagnosia in Seven Tests,"i-Perception +January-February 2016: 1–37 +! The Author(s) 2016 +DOI: 10.1177/2041669515625797 +ipe.sagepub.com +Article +Face Perception and Test +Reliabilities in Congenital +Prosopagnosia in Seven Tests +Janina Esins +Department of Human Perception, Cognition and Action, Max Planck +Institute for Biological Cybernetics, Tu¨bingen, Germany +Johannes Schultz +Department of Psychology, Durham University, Durham, UK +Claudia Stemper +Institute of Human Genetics, Westfa¨lische Wilhelms-Universita¨t +Mu¨nster, Mu¨nster, Germany +Ingo Kennerknecht +Institute of Human Genetics, Westfa¨lische Wilhelms-Universita¨t +Mu¨nster, Mu¨nster, Germany"
+7ab41d2fb37079d20db5e25fd6e71755673f82f0,Building Emotional Machines: Recognizing Image Emotions Through Deep Neural Networks,"Building Emotional Machines: Recognizing Image +Emotions through Deep Neural Networks +Hye-Rin Kim, Yeong-Seok Kim, Seon Joo Kim, In-Kwon Lee"
+7af6d86139aa86cb5897904563a9f67c016a176d,Performance of Correlation Filters in Facial Recognition,"Performance of Correlation Filters in Facial +Recognition +Everardo Santiago-Ramirez, J.A. Gonzalez-Fraga, and J.I. Ascencio-Lopez +Facultad de Ciencias, Universidad Autónoma de Baja California, Km. 103, Carretera Tijuana- +Ensenada, Ensenada, Baja California C. P. 22860"
7a81967598c2c0b3b3771c1af943efb1defd4482,Do We Need More Training Data?,"Do We Need More Training Data? Xiangxin Zhu · Carl Vondrick · Charless C. Fowlkes · Deva Ramanan"
+7a7a53b05e22305b2963c05ac89830e099146767,Assessing fish abundance from underwater video using deep neural networks,"Assessing fish abundance from underwater video +using deep neural networks +Ranju Mandal∗, Rod M. Connolly†, Thomas A. Schlacher‡ and Bela Stantic∗ +School of ICT, Griffith Sciences, Griffith University, QLD 4222, Australia +Australian Rivers Institute - Coast & Estuaries and +School of Environment and Science, Griffith University, QLD 4222, Australia +School of Science and Engineering, University of the Sunshine Coast, QLD 4558, Australia +{r.mandal, r.connolly,"
+7ace44190729927e5cb0dd5d363fcae966fe13f7,A bag-of-features approach based on Hue-SIFT descriptor for nude detection,"7th European Signal Processing Conference (EUSIPCO 2009) +Glasgow, Scotland, August 24-28, 2009 +A BAG-OF-FEATURES APPROACH BASED ON +HUE-SIFT DESCRIPTOR FOR NUDE DETECTION +Ana P. B. Lopes1,2, Sandra E. F. de Avila1, Anderson N. A. Peixoto1 +Rodrigo S. Oliveira1 and Arnaldo de A. Ara´ujo1 +Computer Science Department – Federal University of Minas Gerais +Av. Antˆonio Carlos, 6627, Pampulha, CEP 31270–901, Belo Horizonte, MG, Brazil +Exact and Technological Sciences Department – State University of Santa Cruz +Rodovia Ilh´eus-Itabuna, km 16 – Pavilh˜ao Jorge Amado, CEP 45600-000, Ilh´eus, BA, Brazil"
7ae0212d6bf8a067b468f2a78054c64ea6a577ce,Human Face Processing Techniques With Application To Large Scale Video Indexing,"Human Face Processing Techniques With Application To Large Scale Video Indexing @@ -17261,6 +59873,26 @@ School of Multidisciplinary Sciences, The Graduate University for Advanced Studies (SOKENDAI) 006 (School Ｙear) September 2006"
+7ab9035ec3871bbeadf1095afbe1ff9d9cb25480,DLBP and SVD Fusion for 3 D Face Recognition Using Range Image,"Computer Science and Information Technology 5(2): 61-65, 2017 +DOI: 10.13189/csit.2017.050203 +http://www.hrpub.org +DLBP and SVD Fusion for 3D Face Recognition Using +Range Image +El Mahdi Barrah, Rachid Ahdid, Said Safi, Abdessamad Malaoui∗ +Interdisciplinary Laboratory of Research in Sciences and Technologies (LIRST), Sultan Moulay Slimane University, Bni Mellal, Morocco +Copyright c(cid:13)2017 by authors, all rights reserved. Authors agree that this article remains permanently +open access under the terms of the Creative Commons Attribution License 4.0 International License"
+7a540e0e2049a8f0118be2eab9a2ec5f57e022c9,Deep Learning Methods for Classification with Limited Training Data,"Deep Learning Methods for Classification with +Limited Training Data +Seminar Report : Spring 2017 +submitted by +Aviral Kumar +(140070031) +under the guidance of +Prof. Sunita Sarawagi +Department of Computer Science and Engineering +Indian Institute of Technology Bombay +April, 2017"
7a0fb972e524cb9115cae655e24f2ae0cfe448e0,Facial Expression Classification Using RBF AND Back-Propagation Neural Networks,"Facial Expression Classification Using RBF AND Back-Propagation Neural Networks R.Q.Feitosa1,2, M.M.B.Vellasco1,2, @@ -17275,11 +59907,54 @@ e-mail: [raul, -rio.br, [diogo," 7ad77b6e727795a12fdacd1f328f4f904471233f,Supervised Local Descriptor Learning for Human Action Recognition,"Supervised Local Descriptor Learning for Human Action Recognition Xiantong Zhen, Feng Zheng, Ling Shao, Senior Member, IEEE, Xianbin Cao, Senior Member, IEEE, and Dan Xu"
+7a88d33b3e23a2cdf1e8a2b848c73a12a34ba88c,TUB-IRML at MediaEval 2014 Violent Scenes Detection Task: Violence Modeling through Feature Space Partitioning,"TUB-IRML at MediaEval 2014 Violent Scenes Detection +Task: Violence Modeling through Feature Space +Partitioning +Esra Acar, Sahin Albayrak +DAI Laboratory, Technische Universität Berlin +Ernst-Reuter-Platz 7, TEL 14, 10587 Berlin, Germany"
+7a4f3d17672ecd89e4ad0d4f3a9257352a055d9b,A Novel Data-driven Image Annotation Method,"A Novel Data-driven Image Annotation Method +Guiguang Ding, Jianmin Wang, Na Xu"
7a97de9460d679efa5a5b4c6f0b0a5ef68b56b3b,Constrained Joint Cascade Regression Framework for Simultaneous Facial Action Unit Recognition and Facial Landmark Detection,"nd Face shape relationship2)AU relationship3)Face shape patternUpdate facial landmark locationsUpdate AU activation probabilitiesAU activation probabilitiesCurrent landmark locationsFigure1.Constrainedjointcascaderegressionframeworkforsi-multaneousfacialactionunitrecognitionandlandmarkdetection.wouldenablethemachineunderstandingofhumanfacialbehavior,intent,emotionetc.Facialactionunitrecognitionandfaciallandmarkdetec-tionarerelatedtasks,buttheyareseldomlyexploitedjointlyintheliteratures.Forexample,thefaceshapedefinedbythelandmarklocationsareconsideredaseffectivefeaturesforAUrecognition.But,thelandmarklocationinforma-tionisusuallyextractedbeforehandwithfaciallandmarkdetectionalgorithms.Ontheotherhand,theActionUnitinformationisrarelyutilizedintheliteraturetohelpfaciallandmarkdetection,eventhoughthefacialmusclemove-mentsandtheactivationofspecificfacialactionunitcancausetheappearanceandshapechangesofthefacewhichsignificantlyaffectfaciallandmarkdetection.Themutualinformationandintertwinedrelationshipamongfacialac-tionunitrecognitionandfaciallandmarkdetectionshouldbeutilizedtoboosttheperformancesofbothtasks.Cascaderegressionframeworkhasbeenshowntobeaneffectivemethodforfacealignmentrecently[19][13].Itstartsfromaninitialfaceshape(e.g.meanface)anditit-erativelyupdatesthefaciallandmarklocationsbasedonthelocalappearancefeaturesuntilconvergence.Severalregres-sionmodelshavebeenappliedtolearnthemappingfromthelocalappearancefeaturestothefaceshapeupdate.Toleveragethesuccessofthecascaderegressionframe-workandtoachievethegoalofjointfacialactionunit13400"
+7a7db5a1325844b62d2ecf8489872c8f515f1c37,Nuclear Norm-Based 2-DPCA for Extracting Features From Images,"Nuclear Norm-Based 2-DPCA for Extracting +Features From Images +Fanlong Zhang, Jian Yang, Member, IEEE, Jianjun Qian, and Yong Xu, Member, IEEE"
+7a776f080b270c8759b2b4fe601682276d1b2eb4,Multi-target Tracking with Sparse Group Features and Position Using Discrete-Continuous Optimization,"Multi-Target Tracking with Sparse Group +Features and Position using Discrete-Continuous +Optimization +Billy Peralta (1) and Alvaro Soto (2) +(1)Universidad Cat´olica de Temuco, (2)Pontificia Universidad Cat´olica de Chile"
+7a3676dcf55e22c7249eac7615174309617c8246,Joint Feature Learning With Robust Local Ternary Pattern for Face Recognition,"International Journal of Application or Innovation in Engineering & Management (IJAIEM) +Web Site: www.ijaiem.org Email: +ISSN 2319 - 4847 +Volume 5, Issue 6, June 2016 +Joint Feature Learning With Robust Local +Ternary Pattern for Face Recognition +Yuvaraju.M1, Shalini.S2 +Nadu, India +Assistant Professor, Department of Electrical and Electronics Engineering, Anna University Regional Campus, Coimbatore, Tamil +Pg Scholar, Department of Electrical and Electronics Engineering, Anna University Regional Campus, Coimbatore, Tamil Nadu, +India"
+7ac25c5391251611696d16e677bd71040d80d583,Person Re-Identification by Saliency Learning,"MANUSCRIPT DRAFT +Person Re-identification by saliency Learning +Rui Zhao, Student Member, IEEE, Wanli Oyang, Member, IEEE, and +Xiaogang Wang, Member, IEEE"
7aa4c16a8e1481629f16167dea313fe9256abb42,Multi-task learning for face identification and attribute estimation,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE ICASSP 2017"
+7ad204758df6c921010d9967a5b7449dd406ea56,Deep Face Quality Assessment,"Deep Face Quality Assessment +Vishal Agarwal +Department of Electronics and Electrical Engineering +Indian Institute of Technology Guwahati +India"
7ad7897740e701eae455457ea74ac10f8b307bed,Random Subspace Two-dimensional LDA for Face Recognition,"Random Subspace Two-dimensional LDA for Face Recognition* Garrett Bingham1"
+7acc05ae92823c12b28d6ad73cb2a7707ccb6c7b,Single view-based 3D face reconstruction robust to self-occlusion,"Lee et al. EURASIP Journal on Advances in Signal Processing 2012, 2012:176 +http://asp.eurasipjournals.com/content/2012/1/176 +R ES EAR CH +Open Access +Single view-based 3D face reconstruction robust +to self-occlusion +Youn Joo Lee1, Sung Joo Lee2, Kang Ryoung Park3, Jaeik Jo1 and Jaihie Kim1*"
7a7b1352d97913ba7b5d9318d4c3d0d53d6fb697,Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery,"Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery Pau Rodr´ıguez†, Josep M. Gonfaus‡, Guillem Cucurull†, @@ -17296,6 +59971,18 @@ Recognition Chollette C. Olisah Department of Computer Science and IT, Baze University, Abuja, Nigeria E-mail:"
+7a8ba1a6c90b56ae0a98fe43d015ab0f2a73912e,A Vision-Based Hybrid Method for Eye Detection and Tracking,"A Vision-Based Hybrid Method for Eye Detection and Tracking +International Journal of Security and Its Applications +Vol. 7, No. 4, July, 2013 +Kun Mu +Department of Computer Science and Engineering, Henan Institute of Engineering, +Zhengzhou 451191, China"
+146879bd04a1ab25dce3484bc587e5f2ff1b1d91,Securing Certificate Revocation through Speaker Verification: the CertiVeR Project,"Securing Certificate Revocation through Speaker Verification: +the CertiVeR Project +Javier R. Saeta1, Javier Hernando2, Oscar Manso3, Manel Medina3 +Biometric Technologies, S.L. Barcelona, Spain +TALP Research Center. Universitat Politècnica de Catalunya, Spain +SeMarket, S.A. Barcelona, Spain"
1451e7b11e66c86104f9391b80d9fb422fb11c01,Image privacy protection with secure JPEG transmorphing,"IET Signal Processing Research Article Image privacy protection with secure JPEG @@ -17309,18 +59996,143 @@ www.ietdl.org Lin Yuan1 , Touradj Ebrahimi1 Multimedia Signal Processing Group, Electrical Engineering Department, EPFL, Station 11, Lausanne, Switzerland E-mail:"
+1456f147381bf7c385225d854c2fb48c19eca285,LCAV-31: a dataset for light field object recognition,"Computational Imaging XII, edited by Charles A. Bouman, Ken D. Sauer, Proc. of SPIE-IS&T Electronic Imaging, +SPIE Vol. 9020, 902014 · © 2014 SPIE-IS&T · CCC code: 0277-786X/14/$18 · doi: 10.1117/12.2041097 +Proc. of SPIE-IS&T/ Vol. 9020 902014-1"
+143e3ec5a5a11547da2d77a17d0ca7b1940280b5,"People detection, tracking and re-identification through a video camera network. (Détection, suivi et ré-identification de personnes à travers un réseau de caméra vidéo)","People detection, tracking and re-identification through +video camera network +Malik Souded +To cite this version: +Malik Souded. People detection, tracking and re-identification through a video camera network. +Other [cs.OH]. Université Nice Sophia Antipolis, 2013. English. <NNT : 2013NICE4152>. <tel- +00913072v2> +HAL Id: tel-00913072 +https://tel.archives-ouvertes.fr/tel-00913072v2 +Submitted on 29 Jan 2014 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents +scientifiques de niveau recherche, publiés ou non, +émanant des établissements d’enseignement et de"
+14aad0d391a9491eb122d5b6af6c325a0e090dc7,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms +{tag} {/tag} +International Journal of Computer Applications +Foundation of Computer Science (FCS), NY, USA +Volume 134 +Number 7 +Year of Publication: 2016 +Authors: +Filani Araoluwa S., Adetunmbi Adebayo O. +10.5120/ijca2016907932 +{bibtex}2016907932.bib{/bibtex}"
14761b89152aa1fc280a33ea4d77b723df4e3864,Zero-Shot Learning via Visual Abstraction,
14fdec563788af3202ce71c021dd8b300ae33051,Social Influence Analysis based on Facial Emotions,"Social Influence Analysis based on Facial Emotions Pankaj Mishra, Rafik Hadfi, and Takayuki Ito Department of Computer Science and Engineering Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, 466-8555 Japan {pankaj.mishra,"
+14fed18d838bf6b89d98837837ff314e61ab7c60,Deep Learning with Differential Privacy,"A preliminary version of this paper appears in the proceedings of the 23rd ACM Conference on Computer and Communications Security +(CCS 2016). This is a full version. +Deep Learning with Differential Privacy +Martín Abadi∗ +H. Brendan McMahan∗ +October 25, 2016 +Andy Chu∗ +Ilya Mironov∗ +Li Zhang∗ +Ian Goodfellow† +Kunal Talwar∗"
+1419956b08f9ab398cd2100ddec74271ef5fa72c,Joint detection and online multi-object tracking,"Joint detection and online multi-object tracking +Hilke Kieritz, Wolfgang H¨ubner, and Michael Arens +Fraunhofer IOSB, Germany"
+149e5e5eeea5a9015ab5ae755f62c45ef70fa79b,Hierarchical Convolutional Features for Visual Tracking,"Hierarchical Convolutional Features for Visual Tracking +Chao Ma +Jia-Bin Huang +Xiaokang Yang +Ming-Hsuan Yang +UC Merced"
+1414d4880e368414cbbbbd215e8b0471f185aa03,Face Detection in Low-Resolution Color Images,"Face Detection in Low-resolution Color Images +Jun Zheng, Geovany A. Ramirez, and Olac Fuentes, +Computer Science Department, +University of Texas at El Paso, +El Paso, Texas, 79968, U.S.A. +No Institute Given"
+140dbcb0be3ce7961ed551f129698e9ad4c9aa8c,Interactive Learning and its Role in Pervasive Robotics,"Interactive Learning and its Role in Pervasive Robotics +Cynthia Matuszek +Dieter Fox +Nicholas FitzGerald +Evan Herbst"
1459d4d16088379c3748322ab0835f50300d9a38,Cross-Domain Visual Matching via Generalized Similarity Measure and Feature Learning,"Cross-Domain Visual Matching via Generalized Similarity Measure and Feature Learning Liang Lin, Guangrun Wang, Wangmeng Zuo, Xiangchu Feng, and Lei Zhang"
+14f964d152337e963e4a4fd3619f6030aa75deb1,Person Re-identification by Discriminatively Selecting Parts and Features,"Person re-identification by discriminatively +selecting parts and features +Amran Bhuiyan, Alessandro Perina and Vittorio Murino +Pattern Analysis and Computer Vision (PAVIS) +Istituto Italiano di Tecnologia +Genova, Italy"
1450296fb936d666f2f11454cc8f0108e2306741,Learning to Discover Cross-Domain Relations with Generative Adversarial Networks,"Learning to Discover Cross-Domain Relations with Generative Adversarial Networks Taeksoo Kim 1 Moonsu Cha 1 Hyunsoo Kim 1 Jung Kwon Lee 1 Jiwon Kim 1"
+14373c9fd08dee8f7195a88430121c69bbebbe1b,Head Pose Estimation Using Covariance of Oriented Gradients,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE +ICASSP 2010"
+14a01628169a3a060b6af5d5dcdeeb584b648abf,Semi-Supervised Multiresolution Classification Using Adaptive Graph Filtering With Application to Indirect Bridge Structural Health Monitoring,"Semi-Supervised Multiresolution Classification +Using Adaptive Graph Filtering with Application to +Indirect Bridge Structural Health Monitoring +Siheng Chen, Student Member, IEEE, Fernando Cerda, Piervincenzo Rizzo, Jacobo Bielak, James H. Garrett and +Jelena Kovaˇcevi´c, Fellow, IEEE"
+147b7998526ebbdf64b1662503b378d9f6456ccd,Generative Adversarial Networks for Image Steganography,"Under review as a conference paper at ICLR 2017 +GENERATIVE ADVERSARIAL NETWORKS FOR IMAGE +STEGANOGRAPHY +Denis Volkhonskiy2,3, Boris Borisenko3 and Evgeny Burnaev1,2,3 +Skolkovo Institute of Science and Technology +The Institute for Information Transmission Problems RAS (Kharkevich Institute) +National Research University Higher School of Economics (HSE)"
+143b54525bdda1f83965002616a4e7b5b9f523a3,A probabilistic patch based image representation using Conditional Random Field model for image classification,"A probabilistic patch based image representation using Conditional Random Field model +for image classification +Fariborz Taherkhani +Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, USA"
+14a022a3eb8cc9681b1ab075650d462788de1fa0,GANs for Biological Image Synthesis,"GANs for Biological Image Synthesis +INRIA/ENS∗, France +Anton Osokin +HSE†, Russia +Anatole Chessel +´Ecole Polytechnique‡, +France"
+14860877a790d99296a990281b22e6b6a430b64f,Deep Over-sampling Framework for Classifying Imbalanced Data,"Deep Over-sampling Framework for Classifying +Imbalanced Data +Shin Ando1 and Chun Yuan Huang2 +School of Management, +Tokyo University of Science, +-11-2 Fujimi, Chiyoda-ku, Tokyo, Japan +School of Management, +Tokyo University of Science, +-11-2 Fujimi, Chiyoda-ku, Tokyo, Japan"
+14f0283c703e450e5f17cbe94878896de865ce30,International Journal of Advance Research and Innovation,"Volume 3, Issue 2 (2015) 383-385 +ISSN 2347 - 3258 +International Journal of Advance Research and Innovation +Robust Visual Tracking for Multiple Targets with Data Association and +Track Management +N. Mahalakshmi, S. R. Saranya +Department of Computer Science Engineering, Dhanalakshmi Srinivasan Engineering College, Perambalur, Tamil +Nadu, India +Article Info +Article history: +Received 5 April 2015 +Received in revised form +0 April 2015 +Accepted 20 May 2015 +Available online 15 June 2015 +Keywords +Online Multi-Object Tracking, +Tracking-By Detection, +Data Association, +Track Management,"
1442319de86d171ce9595b20866ec865003e66fc,Vision-Based Fall Detection with Convolutional Neural Networks,"Vision-Based Fall Detection with Convolutional Neural Networks Adri´an Nu˜nez-Marcos1, Gorka Azkune1, Ignacio Arganda-Carreras234 @@ -17333,6 +60145,15 @@ Ikerbasque, Basque Foundation for Science, Bilbao, Spain Maria Diaz de Haro, 3 - 48013 Bilbao, Spain Donostia International Physics Center (DIPC), San Sebastian, Spain P. Manuel Lardizabal, 4 - 20018, San Sebastian, Spain"
+147c33df99dd52502d65fe390ee45c585349b3b3,Pixel and Feature Level Based Domain Adaption for Object Detection in Autonomous Driving,"Pixel and Feature Level Based Domain Adaption +for Object Detection in Autonomous Driving +Yuhu Shan, Wen Feng Lu, Chee Meng Chew"
+146e6504d473b92e56108b7276d96aebaa58ccfc,3 D Model and Part Fusion for Vehicle Retrieval,"International Journal of Research in Advent Technology, Vol.2, No.5, May 2014 +E-ISSN: 2321-9637 +D Model and Part Fusion for Vehicle Retrieval +M.Nagarasan1, T.N.Chitradevi2, S.Senthilnathan3 +Department of computer science and engineering1,2, 3 +Aditya institute of technology, Coimbatore.1, 3,Sri Ramakrishna Engineering College, Coimbatore2"
1462bc73834e070201acd6e3eaddd23ce3c1a114,Face Authentication /recognition System for Forensic Application Using Sketch Based on the Sift Features Approach,"International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 4, April 2014 FACE AUTHENTICATION /RECOGNITION SYSTEM FOR FORENSIC APPLICATION @@ -17341,6 +60162,18 @@ FEATURES APPROACH Poonam A. Katre Department of Electronics Engineering KITS, RTMNU Nagpur University, India"
+143ac3b7338e240b106863d35177c4567ef9c1aa,Euclidean & Geodesic Distance between a Facial Feature Points in Two-Dimensional Face Recognition System,"Euclidean & Geodesic Distance between a Facial +Feature Points in Two-Dimensional Face +Recognition System +Rachid AHDID1, Khaddouj TAIFI1, Said SAFI1 and Bouzid MANAUT2"
+1471c0b72e4a88b39e59362bf169bb35915966a9,Extended Coding and Pooling in the HMAX Model,"Extended coding and pooling in the HMAX model +Christian Th´eriault, Nicolas Thome, Member, IEEE, and Matthieu Cord, Member, IEEE +Universit´e Pierre et Marie Curie, UPMC-Sorbonne Universities, LIP6, 4 place Jussieu, 75005, Paris, France"
+1436d72a51feefda3278068a164d263f6d845236,Interactive Learning a Person Detector: Fewer Clicks – Less Frustration1,"INTERACTIVE LEARNING A PERSON +DETECTOR: +FEWER CLICKS – LESS FRUSTRATION1 +Peter M. Roth2, Helmut Grabner2, Christian Leistner2, +Martin Winter2, and Horst Bischof2"
140c95e53c619eac594d70f6369f518adfea12ef,Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A,"Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A Brendan F. Klare, Emma Taborsky , Austin Blanton , Jordan Cheney , Kristen Allen , Patrick Grother , Alan Mah , Anil K. Jain The development of accurate and scalable unconstrained face recogni- @@ -17374,12 +60207,44 @@ Onur C. Hamsici Qualcomm Research, San Diego Ming-Hsuan Yang UC Merced"
+14e9eaa6ac23996e9a62060c8da90bdb7116ee37,Localization Recall Precision (LRP): A New Performance Metric for Object Detection,[cs.CV] 5 Jul 2018
+14f457bcb5c3e294919512b132bb171bdcaf5ec2,Understanding Human Actions in Still Images a Dissertation Submitted to the Department of Computer Science and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"UNDERSTANDING HUMAN ACTIONS +IN STILL IMAGES +A DISSERTATION +SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE +AND THE COMMITTEE ON GRADUATE STUDIES +OF STANFORD UNIVERSITY +IN PARTIAL FULFILLMENT OF THE REQUIREMENTS +FOR THE DEGREE OF +DOCTOR OF PHILOSOPHY +Bangpeng Yao +August 2013"
+14c988aa9086207b337dcc5611aad08422129b42,Human Relative Position Detection Based on Mutual Occlusion,"Human Relative Position Detection +Based on Mutual Occlusion +V´ıctor Borjas, Michal Drozdzal, Petia Radeva, and Jordi Vitri`a +Facultat de Matem`atiques & Centre de Visi`o per Computador, +Universitat de Barcelona, +Campus UAB"
14e428f2ff3dc5cf96e5742eedb156c1ea12ece1,Facial Expression Recognition Using Neural Network Trained with Zernike Moments,"Facial Expression Recognition Using Neural Network Trained with Zernike Moments Mohammed Saaidia Dept. Génie-Electrique Université M.C.M Souk-Ahras Souk-Ahras, Algeria"
+148721b162dd355812fae94c8aaf365e5e2c3a79,"Vista: A Visually, Socially, and Temporally-aware Model for Artistic Recommendation","Vista: A Visually, Socially, and Temporally-aware Model +for Artistic Recommendation +Ruining He +UC San Diego +Chen Fang +Adobe Research +Zhaowen Wang +Adobe Research +Julian McAuley +UC San Diego"
+147fe6bfc76f30ccacc3620662511e452bc395f6,A Survey of Face Recognition Techniques,"Invited Paper +Journal of Information Processing Systems, Vol.5, No.2, June 2009 41 +A Survey of Face Recognition Techniques +Rabia Jafri* and Hamid R. Arabnia*"
14a5feadd4209d21fa308e7a942967ea7c13b7b6,Content-based vehicle retrieval using 3D model and part information,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE ICASSP 2012"
14fee990a372bcc4cb6dc024ab7fc4ecf09dba2b,Modeling Spatio-Temporal Human Track Structure for Action Localization,"Modeling Spatio-Temporal Human Track Structure for Action @@ -17393,6 +60258,28 @@ http://qmro.qmul.ac.uk/xmlui/handle/123456789/36405 Information about this research object was correct at the time of download; we occasionally make corrections to records, please therefore check the published record when citing. For more information contact"
+8ea56e4697430d1dbc728bad5a6e8ebafcced835,Adaptive Stochastic Gradient Descent on the Grassmannian for Robust Low-Rank Subspace Recovery,"Adaptive Stochastic Gradient Descent on the +Grassmannian for Robust Low-Rank Subspace +Recovery +Jun He, Member, IEEE, Yue Zhang, Student Member, IEEE"
+8ec76d7d4a9abd09f088fb3f7a3351a7fda1fde0,Generative Adversarial Networks to Synthetically Augment Data for Deep Learning based Image Segmentation *,"Proceedings of the OAGM Workshop 2018 +DOI: 10.3217/978-3-85125-603-1-07"
+8e9f973e9d01fdd275af6c1460e5307d2ff3d2bc,OF KITH AND KIN 1 Of kith and kin :,"OF KITH AND KIN +Of kith and kin: +Perceptual enrichment, expectancy and reciprocal processing in face perception +Joshua Correll Sean M. Hudson Steffanie Guillermo Holly A. Earls +University of Colorado Boulder +Author Note +Joshua Correll, Sean M. Hudson, Steffanie Guillermo, Holly A. Earls, Department of +Psychology & Neuroscience, University of Colorado Boulder. +We dedicate this paper to the memory of Sean Hudson, a wonderful scientist and a true +friend. We thank Jasmin Cloutier, Tim Correll, Tim Curran, Tiffany Ito, Sarah Lamer, +Debbie Ma, Max Weisbuch, and Bernd Wittenbrink for their thoughtful comments on +previous drafts. +Correspondence should be addressed to Joshua Correll, Department of Psychology & +Neuroscience, UCB 345, Boulder, Colorado, 80309-0345;"
+8ea9093542075bd8cc4928a4c671a95f363c61ef,Sliced-Wasserstein Autoencoder : An Embarrassingly Simple Generative Model,"Sliced-Wasserstein Autoencoder: An +Embarrassingly Simple Generative Model"
8ee62f7d59aa949b4a943453824e03f4ce19e500,Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions,"Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regression Vincent Drouard∗, Radu Horaud∗, Antoine Deleforge†, Sil`eye Ba∗ and Georgios Evangelidis∗ @@ -17420,12 +60307,74 @@ mirrors related insights from neuroscience about humans’ face recognition abil In this project, we implement both face recognition algorithms and image manipulations. We then"
8e3d0b401dec8818cd0245c540c6bc032f169a1d,McGan: Mean and Covariance Feature Matching GAN,"McGan: Mean and Covariance Feature Matching GAN Youssef Mroueh * 1 2 Tom Sercu * 1 2 Vaibhava Goel 2"
+8e7749f635b161558efa3e98a324e88c73e2b18f,[Neuroimaging findings in autism: a brief review].,"Türk Psikiyatri Dergisi 2009; +Turkish Journal of Psychiatry +Neuroimaging Findings in Auti sm: A Brief Review +Halime Tuna ULAY1, Aygün ERTUĞRUL2"
+8edb2219370a86c4277549813d36a6c139503fb4,Facial feature units’ localization using horizontal information of most significant bit planes,"Journal of Engineering and Technology Research Vol. 3(14), pp. 381-387, 22 December, 2011 +Available online at http:// www.academicjournals.org/JETR +DOI: 10.5897/JETR11.068 +ISSN 2006-9790 ©2011 Academic Journals +Full Length Research Paper +Facial feature units’ localization using horizontal +information of most significant bit planes +Asif Khan1*, Khalilullah1, Ihtesham-Ul-Islam1 and Mohammad A. U. Khan2 +FAST National University of Computer and Emerging Sciences, Peshawar, Pakistan. +Effat University, Jeddah, Saudi Arabia. +Accepted 8 November, 2011 +We present here an approach to find the exact position of some feature units related to human face +images. We use the horizontal information in most significant bit planes of images to accomplish the +task. Finding location of facial feature units is of importance as most human face recognition +pproaches take it as initial point. The prominent feature units in a face are eyes, nostrils and lips which +re usually oriented in horizontal direction and visually significant in face image. The majority of the +visually significant data in image can be extracted using higher order bits of that image. Our four step +method consists of bit planes processing, separating horizontal information using wavelet transform +(WT), binary thresholding and appropriate combination of Dilation and Erosion. The proposed method +shows high accuracy in the presence of all real world situations like various gestures, illumination"
+8eeab0aeb3170b1ef6497745d2a9bf78c001331d,Machine Vision Techniques for the Evaluation of Animal Behaviour,"Machine Vision Techniques for the +Evaluation of Animal Behaviour +Dr Derek Robert Magee +Submitted in accordance with the requirements +for the degree of Doctor of Philosophy +SI T Y O +The University of Leeds +School of Computing +October 2000 +The candidate confirms that the work submitted is his own and that appropriate credit has been +given where reference has been made to the work of others."
8e94ed0d7606408a0833e69c3185d6dcbe22bbbe,For your eyes only,"© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, reating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Pre-print of article that will appear at WACV 2012."
+8e6957334ab60111fd7e2ae59b008a745223aabe,An incremental learning face recognition system for single sample per person,"An Incremental Learning Face Recognition System +for Single Sample Per Person +Tao Zhu, Furao Shen and Jinxi Zhao +recognition system. In nowadays, most of the existed in- +remental +learning systems are designed to update the +eigenspace of face data as new images arrive [8]. To our +knowledge, few of them can automatically decide when to +learn new information from an input image. In other words, +they need an external observer to tell them how to prevent +learning distorted information from a misclassified or non- +ideal image. Moreover, few of these methods can be applied +in the scenario of single sample per person. +In this paper, we mainly focus on the issue of robust incre- +mental face recognition under the condition of one training +sample per person. Inspired by the Single Image subspace +(SIS) approach [9], we propose an incremental learning face +recognition system. The goals of the proposed system are: +(1) self-adaptively updating and adjusting training samples +during learning process; (2) keeping learning new knowledge"
+8e64f7f38db57ddc197cc7a9c51b914920ee99cc,An Optimized Framework for Detection and Tracking of Video Objects in Challenging Backgrounds,"The International Journal of Multimedia & Its Applications (IJMA) Vol.6, No.4, August 2014 +AN OPTIMIZED FRAMEWORK FOR DETECTION +AND TRACKING OF VIDEO OBJECTS IN +CHALLENGING BACKGROUNDS +Sukanyathara J1 and Alphonsa Kuriakose2 +Department of Computer Science & Engineering, +Viswajyothi College of Engineering & Technology, MG University, Kerala, India"
8e461978359b056d1b4770508e7a567dbed49776,LOMo: Latent Ordinal Model for Facial Analysis in Videos,"LOMo: Latent Ordinal Model for Facial Analysis in Videos Karan Sikka1,∗ Gaurav Sharma2,3,† @@ -17439,6 +60388,11 @@ Institut Eur´ecom Multimedia Communications Department BP 193, 06904 Sophia Antipolis Cedex, France fflorent.perronnin,"
+8e723e8a3a5a9ea258591d384232e0251f842a1c,Twin-GAN - Unpaired Cross-Domain Image Translation with Weight-Sharing GANs,"Twin-GAN – Unpaired Cross-Domain Image +Translation with Weight-Sharing GANs +Jerry Li +Google +600 Amphitheatre Parkway, Mountain View, CA 94040"
8e8e3f2e66494b9b6782fb9e3f52aeb8e1b0d125,"Detecting and classifying scars, marks, and tattoos found in the wild","in any current or future media, for all other uses, @@ -17449,6 +60403,10 @@ reprinting/republishing this material for advertising or promotional purp new collective works, for resale or redistribution to servers or lists, or reuse of any opyrighted component of this work in other works. Pre-print of article that will appear at BTAS 2012.!!"
+8e92168860d8c6591a0c088573629e4d167f5947,"Look at the Driver, Look at the Road: No Distraction! No Accident!","Look at the Driver, Look at the Road: No Distraction! No Accident! +Mahdi Rezaei and Reinhard Klette +The University of Auckland +Private Bag 92019, Auckland, New Zealand"
8e378ef01171b33c59c17ff5798f30293fe30686,A system for automatic face analysis based on statistical shape and texture models,"Lehrstuhl f¨ur Mensch-Maschine-Kommunikation der Technischen Universit¨at M¨unchen A System for Automatic Face Analysis @@ -17468,6 +60426,71 @@ Pr¨ufer der Dissertation: Die Dissertation wurde am 28.02.2008 bei der Technischen Universit¨at M¨unchen eingereicht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik m 18.09.2008 angenommen."
+8e579a8a43f6af1d66e927a48b89e8296eba63f7,Learning to hash faces using large feature vectors,"Learning to Hash Faces Using Large Feature Vectors +Cassio E. dos Santos Jr.∗, Ewa Kijak†, Guillaume Gravier†, William Robson Schwartz∗ +Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil +IRISA & Inria Rennes (CNRS, Univ. Rennes 1), Campus de Beaulieu, Rennes, France"
+8eb2e7c9017b4a110978a1bb504accbc7b9ba211,Marching into battle: synchronized walking diminishes the conceptualized formidability of an antagonist in men.,"Downloaded from +http://rsbl.royalsocietypublishing.org/ +on June 9, 2015 +rsbl.royalsocietypublishing.org +Research +Cite this article: Fessler DMT, Holbrook C. +014 Marching into battle: synchronized +walking diminishes the conceptualized +formidability of an antagonist in men. Biol. +Lett. 10: 20140592. +http://dx.doi.org/10.1098/rsbl.2014.0592 +Received: 25 July 2014 +Accepted: 6 August 2014 +Subject Areas: +ehaviour +Keywords: +synchrony, alliance, fighting capacity +Author for correspondence: +Daniel M. T. Fessler +e-mail:"
+8ec7194952ee9e7cf383b1a1b0aeccaed5b7daaa,Constrained multi-target tracking for team sports activities,"Gade and Moeslund IPSJ Transactions on Computer Vision and +Applications (2018) 10:2 +DOI 10.1186/s41074-017-0038-z +IPSJ Transactions on Computer +Vision and Applications +SYSTEMS PAPER +Open Access +Constrained multi-target tracking for +team sports activities +Rikke Gade* +nd Thomas B. Moeslund"
+8e7493bdabddc2ec99cfa2b9b862343f70c1701a,Pseudo-positive regularization for deep person re-identification,"Noname manuscript No. +(will be inserted by the editor) +Pseudo-positive regularization for deep person re-identification +Fuqing Zhu · Xiangwei Kong · Haiyan Fu · Qi Tian +Received: date / Accepted: date"
+8e8c511ebc12a093d3f73a4717ec71c32e4dbd49,The use of visual information in the recognition of posed and spontaneous facial expressions.,"The use of visual information in the recognition of posed and +spontaneous facial expressions +Camille Saumure +Marie-Pier Plouffe-Demers +Amanda Est ´ephan +Daniel Fiset +Caroline Blais +Department of Psychoeducation and Psychology, +Universit ´e du Qu ´ebec en Outaouais, +Gatineau, Qu ´ebec, Canada +Department of Psychoeducation and Psychology, +Universit ´e du Qu ´ebec en Outaouais, +Gatineau, Qu ´ebec, Canada +Department of Psychoeducation and Psychology, +Universit ´e du Qu ´ebec en Outaouais, +Gatineau, Qu ´ebec, Canada +Department of Psychoeducation and Psychology, +Universit ´e du Qu ´ebec en Outaouais, +Gatineau, Qu ´ebec, Canada +Department of Psychoeducation and Psychology,"
+8e6526b46a52a18028336a8d026e9d466aa12edf,Moving Poselets: A Discriminative and Interpretable Skeletal Motion Representation for Action Recognition,"Moving Poselets: A Discriminative and Interpretable Skeletal Motion +Representation for Action Recognition +Lingling Tao and Ren´e Vidal +Center for Imaging Science, Johns Hopkins University +ltao4,"
8ed051be31309a71b75e584bc812b71a0344a019,Class-Based Feature Matching Across Unrestricted Transformations,"Class-based feature matching across unrestricted transformations Evgeniy Bart and Shimon Ullman"
@@ -17475,6 +60498,18 @@ Evgeniy Bart and Shimon Ullman" Timur Bagautdinov∗1, Chenglei Wu2, Jason Saragih2, Pascal Fua1, Yaser Sheikh2 ´Ecole Polytechnique F´ed´erale de Lausanne Facebook Reality Labs, Pittsburgh"
+8e112ad656ff90720ae609841bd0fcb2caa90d65,"""Show me the cup"": Reference with Continuous Representations",[cs.CL] 28 Jun 2016
+8edcd935362c899e630349784e4ff8adb3a69cdc,Person re-identification using deformable patch metric learning,"Person Re-identification using Deformable Patch Metric Learning +Sławomir B ˛ak +Peter Carr +Disney Research +Pittsburgh, PA, USA, 15213"
+8ee50fd3e19729a487f7196b682ccaa2d17aa0df,Improving head and body pose estimation through semi-supervised manifold alignment,"IMPROVING HEAD AND BODY POSE ESTIMATION +THROUGH SEMI-SUPERVISED MANIFOLD ALIGNMENT +Alexandre Heili(cid:63), Jagannadan Varadarajan†, Bernard Ghanem‡, Narendra Ahuja(cid:63)†, Jean-Marc Odobez(cid:63) +(cid:63) Idiap Research Institute, ´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland +Advanced Digital Sciences Center, Singapore, (cid:63)† University of Illinois at Urbana-Champaign +King Abdullah University of Science and Technology, Saudi Arabia"
8e0becfc5fe3ecdd2ac93fabe34634827b21ef2b,Learning from Longitudinal Face Demonstration - Where Tractable Deep Modeling Meets Inverse Reinforcement Learning,"International Journal of Computer Vision manuscript No. (will be inserted by the editor) Learning from Longitudinal Face Demonstration - @@ -17482,10 +60517,78 @@ Where Tractable Deep Modeling Meets Inverse Reinforcement Learning Chi Nhan Duong · Kha Gia Quach · Khoa Luu · T. Hoang Ngan Le · Marios Savvides · Tien D. Bui Received: date / Accepted: date"
+8e0cc47c194ef7daf15aaef14d61e493879ae137,Deep Network Flow for Multi-object Tracking,"Deep Network Flow for Multi-Object Tracking +Samuel Schulter +Paul Vernaza Wongun Choi Manmohan Chandraker +NEC Laboratories America, Media Analytics Department +Cupertino, CA, USA"
+22cf367d14e646914cc959bbcd402df0c20cd0dc,Towards Automated Melanoma Screening: Proper Computer Vision & Reliable Results,"Towards Automated Melanoma Screening: +Proper Computer Vision & Reliable Results +Michel Fornaciali, Micael Carvalho, Fl´avia Vasques Bittencourt, Sandra Avila, Eduardo Valle"
+2258e01865367018ed6f4262c880df85b94959f8,Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics,"Hindawi Publishing Corporation +EURASIP Journal on Image and Video Processing +Volume 2008, Article ID 246309, 10 pages +doi:10.1155/2008/246309 +Research Article +Evaluating Multiple Object Tracking Performance: +The CLEAR MOT Metrics +Keni Bernardin and Rainer Stiefelhagen +Interactive Systems Lab, Institut f¨ur Theoretische Informatik, Universit¨at Karlsruhe, 76131 Karlsruhe, Germany +Correspondence should be addressed to Keni Bernardin, +Received 2 November 2007; Accepted 23 April 2008 +Recommended by Carlo Regazzoni +Simultaneous tracking of multiple persons in real-world environments is an active research field and several approaches have +een proposed, based on a variety of features and algorithms. Recently, there has been a growing interest in organizing systematic +evaluations to compare the various techniques. Unfortunately, the lack of common metrics for measuring the performance of +multiple object trackers still makes it hard to compare their results. In this work, we introduce two intuitive and general metrics to +llow for objective comparison of tracker characteristics, focusing on their precision in estimating object locations, their accuracy +in recognizing object configurations and their ability to consistently label objects over time. These metrics have been extensively +used in two large-scale international evaluations, the 2006 and 2007 CLEAR evaluations, to measure and compare the performance +of multiple object trackers for a wide variety of tracking tasks. Selected performance results are presented and the advantages and"
+229e105fd4d34815e476702dd5ca4362943c475d,WildDash - Creating Hazard-Aware Benchmarks,"WildDash - Creating Hazard-Aware Benchmarks +Oliver Zendel, Katrin Honauer, Markus Murschitz, Daniel Steininger, and +Gustavo Fern´andez Dom´ınguez +AIT, Austrian Institute of Technology, Giefinggasse 4, 1210, Vienna, Austria +{oliver.zendel, katrin.honauer.fl, markus.murschitz, daniel.steininger,"
22043cbd2b70cb8195d8d0500460ddc00ddb1a62,Separability-Oriented Subclass Discriminant Analysis,"Separability-Oriented Subclass Discriminant Analysis Huan Wan, Hui Wang, Gongde Guo, Xin Wei"
22137ce9c01a8fdebf92ef35407a5a5d18730dde,Recognition of Faces from single and Multi-View Videos,
+2270c94d3f9d9451b3d337aa5ba2d5681cb98497,Evaluation of GIST descriptors for web-scale image search,"Evaluation of GIST descriptors for web-scale image +search +Matthijs Douze, Hervé Jégou, Sandhawalia Harsimrat, Laurent Amsaleg, +Cordelia Schmid +To cite this version: +Matthijs Douze, Hervé Jégou, Sandhawalia Harsimrat, Laurent Amsaleg, Cordelia Schmid. Evaluation +of GIST descriptors for web-scale image search. CIVR 2009 - International Conference on Image and +Video Retrieval, Jul 2009, Santorini, Greece. ACM, pp.19:1-8, 2009, <10.1145/1646396.1646421>. +<inria-00394212> +HAL Id: inria-00394212 +https://hal.inria.fr/inria-00394212 +Submitted on 23 Mar 2012 +HAL is a multi-disciplinary open access +rchive for the deposit and dissemination of sci- +entific research documents, whether they are pub- +lished or not. The documents may come from +teaching and research institutions in France or +broad, or from public or private research centers. +L’archive ouverte pluridisciplinaire HAL, est +destinée au dépôt et à la diffusion de documents"
+22fb836a593267d9ff09a4d12aa5b4a6fd52c81e,Brief report: Visual processing of faces in individuals with fragile X syndrome: an eye tracking study.,"J Autism Dev Disord (2009) 39:946–952 +DOI 10.1007/s10803-009-0744-1 +B R I E F R E P O R T +Brief Report: Visual Processing of Faces in Individuals +with Fragile X Syndrome: An Eye Tracking Study +Faraz Farzin Æ Susan M. Rivera Æ David Hessl +Published online: 28 April 2009 +Ó The Author(s) 2009. This article is published with open access at Springerlink.com"
+221debbd7878ed303eaa4666f8df04a48e4c5070,Making Computer Vision Computationally Efficient,"Making computer vision computationally efficient +Narayanan Sundaram +Electrical Engineering and Computer Sciences +University of California at Berkeley +Technical Report No. UCB/EECS-2012-106 +http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-106.html +May 11, 2012"
22264e60f1dfbc7d0b52549d1de560993dd96e46,UnitBox: An Advanced Object Detection Network,"UnitBox: An Advanced Object Detection Network Jiahui Yu1,2 Yuning Jiang2 @@ -17495,6 +60598,28 @@ Thomas Huang1 University of Illinois at Urbana−Champaign Megvii Inc {jyu79, zwang119, {jyn,"
+220f8088f2fc1ddd9df1a0b583d3d01cb929ee8d,ROML: A Robust Feature Correspondence Approach for Matching Objects in A Set of Images,"Noname manuscript No. +(will be inserted by the editor) +ROML: A Robust Feature Correspondence Approach for +Matching Objects in A Set of Images +Kui Jia · Tsung-Han Chan · Zinan Zeng · Shenghua Gao +Gang Wang · Tianzhu Zhang · Yi Ma"
+22029de24dbf6867658145264f36b161c40a09d8,A Discriminative Representation of Convolutional Features for Indoor Scene Recognition,"A Discriminative Representation of Convolutional +Features for Indoor Scene Recognition +S. H. Khan, M. Hayat, M. Bennamoun, Member, IEEE, R. Togneri, and F. Sohel, Senior Member, IEEE"
+22c01d758a4941c01239fa8facdb3407559132ed,Segmentation and Restoration of Images on Surfaces by Parametric Active Contours with Topology Changes,"Segmentation and Restoration of Images on Surfaces by Parametric +Active Contours with Topology Changes +Heike Benninghoff∗ and Harald Garcke†"
+22f8148e43c50341bad686d7fccb425b0682e667,Facial ethnicity classification based on boosted local texture and shape descriptions,"Facial Ethnicity Classification based on Boosted Local Texture and +Shape Descriptions +Huaxiong Ding, Di Huang, IEEE Member, Yunhong Wang, IEEE Member, Liming Chen, IEEE Member,"
+224547337e1ace6411a69c2e06ce538bc67923f7,Convolutional Neural Network for Camera Pose Estimation from Object Detections,"CONVOLUTIONAL NEURAL NETWORK FOR CAMERA POSE ESTIMATION FROM +OBJECT DETECTIONS +E. V. Shalnova, A. S. Konushina,b +MSU, Faculty of Computational Mathematics and Cybernetics, Russia, 119991, Moscow, GSP-1, 1-52, Leninskiye Gory, - +HSE, Faculty of Computer Science, Russia, 125319, Moscow, 3, Kochnovsky Proezd +KEY WORDS: Camera Pose, CNN, Head Detection, Computer Graphics +Commission II, WG II/5"
223ec77652c268b98c298327d42aacea8f3ce23f,Acted Facial Expressions In The Wild Database,"TR-CS-11-02 Acted Facial Expressions In The Wild Database @@ -17511,6 +60636,16 @@ Zhe Lin2 Adobe Research Li Zhang1 http://www.cs.wisc.edu/~lizhang/projects/face-landmark-localization/"
+2230848e506553159e0edfc20472b8cd6084be17,Vision Based Hand Puppet,"ENTERFACE’10, JULY 12TH - AUGUST 6TH, AMSTERDAM, THE NETHERLANDS. +Vision Based Hand Puppet +Cem Keskin, ˙Ismail Arı, Tolga Eren, Furkan Kırac¸, Lukas Rybok, Hazım Ekenel, Rainer Stiefelhagen, Lale Akarun"
+22ee43dbd2bdefbc8945d453c6cd453f49ab5eb7,Urban Traffic Surveillance in Smart Cities Using Radar Images,"Urban Traffic Surveillance in Smart Cities +Using Radar Images +J. S´anchez-Oro, David Fern´andez-L´opez, R. Cabido, +Antonio S. Montemayor, and Juan Jos´e Pantrigo +Dept. Ciencias de la Computaci´on +Universidad Rey Juan Carlos +Spain"
22fdd8d65463f520f054bf4f6d2d216b54fc5677,Efficient Small and Capital Handwritten Character Recognition with Noise Reduction,"International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 3, Issue 8, August 2013) Efficient Small and Capital Handwritten Character @@ -17523,6 +60658,58 @@ Integrated Data Systems Department Siemens Corporate Research 755 College Road East, Princeton, NJ 08540 Email:"
+225fbfd99465033e993460a1bc838a87fbf42346,Gaussian-Bernoulli deep Boltzmann machine,"Gaussian-Bernoulli Deep Boltzmann Machine +KyungHyun Cho, Tapani Raiko and Alexander Ilin +Department of Information and Computer Science, +Aalto University School of Science +Email:"
+222d86787abed673600f1054796367f439c2eec1,Etworks via a Ttention T Ransfer,"Published as a conference paper at ICLR 2017 +PAYING MORE ATTENTION TO ATTENTION: +IMPROVING THE PERFORMANCE OF CONVOLUTIONAL +NEURAL NETWORKS VIA ATTENTION TRANSFER +Sergey Zagoruyko, Nikos Komodakis +Universit´e Paris-Est, ´Ecole des Ponts ParisTech +Paris, France"
+22532c6e38ded690dc1420f05c18e23f6f24804d,Chapter 5 Genetic & Evolutionary Biometrics,"We are IntechOpen, +the world’s leading publisher of +Open Access books +Built by scientists, for scientists +,700 +08,500 +.7 M +Open access books available +International authors and editors +Downloads +Our authors are among the +Countries delivered to +TOP 1% +2.2% +most cited scientists +Contributors from top 500 universities +Selection of our books indexed in the Book Citation Index +in Web of Science™ Core Collection (BKCI) +Interested in publishing with us? +Contact"
+2251a1efad0cef802fd64fc79cc1b7007b64f425,Estimating 3D Pose via Stochastic Search and Expectation Maximization,"-IJE=JEC !, 2IA LE= 5J?D=IJE? 5A=H?D +-NFA?J=JE =NEE=JE +*A ,=K>AO :E=CDK= :EA +,AF=HJAJ B +FKJAH 5?EA?A 5M=IA= 7ELAHIEJO +5) &22 +*,=K>AO::EA(IM=IA==?K +)>IJH=?J 1 JDEI F=FAH = =FFH=?D EI J AIJE=JA !, FIA +KIEC = F=HJ IJ?D=IJE? ) HAFHAIAJ=JE B JDA +DK= EI LAH EJI JD=J AFOI BK +A=HJ >AJMAA EJI 6DEI HAFHAIAJ=JE EI +=C=EIJ = FFK=H =JAH=JELA LAH F=HJI KIEC E> +J EI IDM JD=J KIEC BK E> HAIKJI E = +JD=J EI B=H HA HAFHAIAJ=JELA B JDA HECE= JH=EEC .KH +JDAHHA EJ EI JD=J -NFA?J=JE =NEE=JE EI IKEJ=>A +BH AIJE=JEC !, FIA >AJJAH ?LAHCA?A EI MDA KIEC BK +E> 6 JDA A?=?O B JDA EJ +EI J JDA B !, FIA AIJE=JE KIEC = IECA ?K=H +E=CA 3K=JEJ=JELA HAIKJI =HA KIEC JDA 0K=-L= +MDE?D ?H JD=J JDA KJFAHBHI JD=J B JDA ? +FAJEC F=HJ 1 JDEI MH KIJ = IECA EI A=HJ J"
227b18fab568472bf14f9665cedfb95ed33e5fce,Compositional Dictionaries for Domain Adaptive Face Recognition,"Compositional Dictionaries for Domain Adaptive Face Recognition Qiang Qiu, and Rama Chellappa, Fellow, IEEE."
@@ -17535,6 +60722,66 @@ Multi-feature shape regression for face lignment Wei-Jong Yang, Yi-Chen Chen, Pau-Choo Chung and Jar-Ferr Yang* Open Access"
+22029beb936c9871757813758c5ae3e5820260c9,Proximity Distribution Kernels for Geometric Context in Category Recognition,"Proximity Distribution Kernels for Geometric Context in Category Recognition +Haibin Ling∗ +Stefano Soatto +Integrated Data Systems Department +Computer Science Department +Siemens Corporate Research, Princeton, NJ +University of California, Los Angeles, CA +haibin.ling siemens.com +soatto cs.ucla.edu"
+2279cae83716e2a00181593a7b10966020dd11d1,Real-time head pose estimation and facial feature localization using a depth sensor and triangular surface patch features,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES +http://www.merl.com +Real-time head pose estimation and facial feature localization +using a depth sensor and triangular surface patch features +Papazov, C.; Marks, T.K.; Jones, M.J. +TR2015-069 +June 2015"
+22086b3c772ba638e7d50b10bcf544abd93c9305,Face Localization based on Skin Color,"International Journal of Computer Applications (0975 – 8887) +Volume 109 – No. 12, January 2015 +Face Localization based on Skin Color +M. Mahadevi +Research Scholar, M.S. University +S.D.N.B. Vaishnav College for Women +Chrompet,Chennai-44"
+224ffad672f7e6c7995780eb9bd3c8a141cb25cd,Understanding pedestrian behaviors from stationary crowd groups,"Understanding Pedestrian Behaviors from Stationary Crowd Groups +Shuai Yi1, Hongsheng Li1,2, Xiaogang Wang1 +Department of Electronic Engineering, The Chinese University of Hong Kong. +School of Electronic Engineering, University of Electronic Science and Technology of China. +Pedestrian behavior modeling and analysis is important for crowd scene un- +derstanding and has various applications in video surveillance. Stationary +rowd groups are a key factor influencing pedestrian walking patterns but +was largely ignored in literature. As shown in Figure 1 (d), the walking +path of a pedestrian (black curve) is affected by a stationary crowd group. +Without modeling the stationary crowd group, it is difficult to explain why +the pedestrian detours when approaching the destination (Figure 1 (f)). Sta- +tionary crowd groups can serve as multiple roles (Figure 1 (e)) for different +pedestrians, such as source, destination, or obstacle. Moreover, the spatial +distribution of stationary crowd groups might change over time (Figure 1 +(a)-(d)), which leads to the dynamic variations of traffic patterns. In our +work, the factor of stationary crowd groups is introduced for the first time +to model pedestrian behaviors. +The Proposed Pedestrian Behavior Model +A general energy map M is proposed to model the traveling difficulty of +every location of the scene. It can be modeled with three channels calculated"
+227094e85ae30794d03f3cee426f40877ac2b11b,Performance Improvements in Face Classification using Random Forest,"Vatsal Vishwakarma, Abhishek Kumar Srivastava / International Journal of Engineering Research and +Applications (IJERA) ISSN: 2248-9622 www.ijera.com +Vol. 2, Issue 3, May-Jun 2012, pp.2384-2388 +Performance Improvements in Face Classification using Random Forest +Vatsal Vishwakarma*, Abhishek Kumar Srivastava ** +*(Department of Electronics and Communication, Lovely Professional University, Jalandhar , India.) +** (Department of Electronics and Communication, Lovely Professional University, Jalandhar , India.)"
+2236294e803316c5934fa387f27d128fa7819a03,Iterative Human Pose Estimation based on A New Part Appearance Model,"Appl. Math. Inf. Sci. 8, No. 1L, 311-317 (2014) +Applied Mathematics & Information Sciences +An International Journal +http://dx.doi.org/10.12785/amis/081L39 +Iterative Human Pose Estimation based on A New Part +Appearance Model +Wang Hao, Meng Fanhui and Fang Baofu∗ +School of Computer and Information, Hefei Universty of Technology, Hefei, China +Received: 15 May. 2013, Revised: 9 Sep. 2013, Accepted: 10 Sep. 2013 +Published online: 1 Apr. 2014"
22dabd4f092e7f3bdaf352edd925ecc59821e168,Exploiting side information in locality preserving projection,"Deakin Research Online This is the published version: An, Senjian, Liu, Wanquan and Venkatesh, Svetha 2008, Exploiting side information in @@ -17548,6 +60795,30 @@ material for advertising or promotional purposes or for creating new collective resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Copyright : 2008, IEEE"
+224868cc607dc38b7eca8536018580c577f9fedf,Exploring Temporal Patterns in Classifying Frustrated and Delighted Smiles,"IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, MANUSCRIPT ID +Exploring Temporal Patterns in Classifying +Frustrated and Delighted Smiles +Mohammed E. Hoque, Daniel J. McDuff, and Rosalind W. Picard, Member, IEEE"
+224d4cf75e8baf32a795f38ee8ccfdf82e4c5a70,Identifying Exceptional Descriptions of People Using Topic Modeling and Subgroup Discovery,"Identifying Exceptional Descriptions of People +using Topic Modeling and Subgroup Discovery +Andrew T. Hendrickson, Jason Wang, and Martin Atzmueller +Tilburg University, 5037AB, the Netherlands +{a.hendrickson, y.w.wang,"
+220d62414053519f7b9a6aecb4aa9f775014c98c,Incremental Feature Transformation for Temporal Space,"Incremental Feature Transformation for Temporal Space +International Journal of Computer Applications (0975 – 8887) +Volume 145 – No.8, July 2016 +Preeti Mahadev +University of Mysore, +Mysuru, Karnataka, +India +P. Nagabhushan +University of Mysore, +Mysuru, Karnataka, +India"
+229bce6384ae16a388881e766bfa5a672b61dc9b,Application of Video Scene Semantic Recognition Technology in Smart Video,"ISSN 1330-3651 (Print), ISSN 1848-6339 (Online) https://doi.org/10.17559/TV-20180620082101 +Original scientific paper +Application of Video Scene Semantic Recognition Technology in Smart Video +Lele QIN, Lihua KANG"
22e189a813529a8f43ad76b318207d9a4b6de71a,What will Happen Next? Forecasting Player Moves in Sports Videos,"What will Happen Next? Forecasting Player Moves in Sports Videos Panna Felsen @@ -17556,6 +60827,40 @@ Pulkit Agrawal UC Berkeley Jitendra Malik UC Berkeley"
+22e4e64c1172c90ba23f634d850931ee5f9a972f,Robust Bayesian fitting of 3D morphable model,"Robust Bayesian Fitting of 3D Morphable +Model +Claudia Arellano and Rozenn Dahyot +School of Computer Science and Statistics +Trinity College Dublin, Ireland +7th November 2013"
+227a312324edd41892eb2c1dbc4bf8d94984a326,Deep Learning Based Vehicle Make-Model Classification,"Deep Learning Based Vehicle Make-Model +Classification +Burak Satar1 and Ahmet Emir Dirik2(cid:63) +Uludag University, Bursa, Turkey +Department of Electrical-Electronics Engineering +Uludag University, Bursa, Turkey +Department of Computer Engineering"
+22c89775cb5309eae5ac1f9ce9d1c2d569439492,Face recognition based on extended separable lattice 2-D HMMS,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE +ICASSP 2012"
+25ae83767c926898047bbc50971b5b11de34e12a,Detection and Tracking of Occluded People,"Noname manuscript No. +(will be inserted by the editor) +Detection and Tracking of Occluded People +Siyu Tang · Mykhaylo Andriluka · Bernt Schiele +Received: date / Accepted: date"
+25b9ef5c78dbf17c71e6fd94054dd55d66c39264,Multimedia Semantic Integrity Assessment Using Joint Embedding Of Images And Text,"Multimedia Semantic Integrity Assessment Using Joint +Embedding Of Images And Text +Ayush Jaiswal∗ +USC Information Sciences Institute +Marina del Rey, CA, USA +Ekraam Sabir∗ +USC Information Sciences Institute +Marina del Rey, CA, USA +Wael AbdAlmageed +USC Information Sciences Institute +Marina del Rey, CA, USA +Premkumar Natarajan +USC Information Sciences Institute +Marina del Rey, CA, USA"
25c19d8c85462b3b0926820ee5a92fc55b81c35a,Pose-Invariant Facial Expression Recognition Using Variable-Intensity Templates,"Noname manuscript No. (will be inserted by the editor) Pose-Invariant Facial Expression Recognition @@ -17563,6 +60868,35 @@ Using Variable-Intensity Templates Shiro Kumano · Kazuhiro Otsuka · Junji Yamato · Eisaku Maeda · Yoichi Sato Received: date / Accepted: date"
+2528022c14428ad5912c323f6a356009457c985b,Automatic 3D facial expression recognition using geometric and textured feature fusion,"Automatic 3D Facial Expression Recognition using Geometric and +Textured Feature Fusion +Department of Electronic and Computer Engineering, Brunel University London, UK +Asim Jan and Hongying Meng"
+25474c21613607f6bb7687a281d5f9d4ffa1f9f3,Recognizing disguised faces,"This article was downloaded by: [Carnegie Mellon University] +On: 03 May 2012, At: 06:22 +Publisher: Psychology Press +Informa Ltd Registered in England and Wales Registered Number: 1072954 +Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, +Visual Cognition +Publication details, including instructions for authors +nd subscription information: +http://www.tandfonline.com/loi/pvis20 +Recognizing disguised faces +Giulia Righi a , Jessie J. Peissig b & Michael J. Tarr c +Children's Hospital Boston, Harvard Medical School, +Boston, MA, USA +Department of Psychology, California State University +Fullerton, Fullerton, CA, USA +Department of Psychology, Carnegie Mellon +University, Pittsburgh, PA, USA +Available online: 13 Feb 2012 +To cite this article: Giulia Righi, Jessie J. Peissig & Michael J. Tarr (2012): Recognizing +disguised faces, Visual Cognition, 20:2, 143-169"
+25ed9bd6c5febac832f3d68b96123e6ba013df83,Object segmentation by alignment of poselet activations to image contours,"Object Segmentation by Alignment of Poselet Activations to Image Contours +Thomas Brox1, Lubomir Bourdev2,3, Subhransu Maji2, and Jitendra Malik2∗ +University of California at Berkeley +University of Freiburg, Germany +Adobe Systems Inc., San Jose, CA"
258a8c6710a9b0c2dc3818333ec035730062b1a5,Benelearn 2005 Annual Machine Learning Conference of Belgium and the Netherlands CTIT P ROCEEDINGS OF THE FOURTEENTH,"Benelearn 2005 Annual Machine Learning Conference of Belgium and the Netherlands @@ -17577,6 +60911,26 @@ UNIFIED PROCEDURE USING GPU COMPUTING J M McDonagh MSc by Research"
+25b83cffddff334d78c55db4d67c65b1d8999b2f,Optimization of Person Re-Identification through Visual Descriptors,
+257e61e6b38ae23b7ddce9907c05b0e78be4d79d,The LORACs prior for VAEs: Letting the Trees Speak for the Data,"The LORACs prior for VAEs: Letting the Trees Speak for the Data +Sharad Vikram +U.C. San Diego1 +Matthew D. Hoffman +Matthew J. Johnson +Google AI +Google Brain"
+253325f09f07c2f7a05191f76e4977f473f4bac5,Filtering and Optimization Strategies for Markerless Human Motion Capture,"FILTERING AND OPTIMIZATION +STRATEGIES FOR MARKERLESS +HUMAN MOTION CAPTURE WITH +SKELETON-BASED SHAPE MODELS. +DISSERTATION +ZUR ERLANGUNG DES GRADES DES +DOKTORS DER INGENIEURWISSENSCHAFTEN (DR.-ING.) +DER NATURWISSENSCHAFTLICH-TECHNISCHEN FAKULT ¨ATEN +DER UNIVERSIT ¨AT DES SAARLANDES +VORGELEGT VON +JUERGEN GALL +SAARBR ¨UCKEN"
250ebcd1a8da31f0071d07954eea4426bb80644c,DenseBox: Unifying Landmark Localization with End to End Object Detection,"DenseBox: Unifying Landmark Localization with End to End Object Detection Lichao Huang1 @@ -17585,6 +60939,22 @@ Yafeng Deng2 Institute of Deep Learning Baidu Research Yinan Yu3"
+25a5f7179b794ab2bb7283c8337480fccee51944,Two novel motion-based algorithms for surveillance video analysis on embedded platforms,"Julien A. Vijverberg, Marijn J.H. Loomans, Cornelis J. Koeleman and Peter H.N. de With, ”Two novel +motion-based algorithms for surveillance video analysis on embedded platforms,” Real-Time Image and Video +Processing, Nasser Kehtarnavaz and Matthias F. Carlsohn, Editors, Proc. SPIE 7724, 77240I(2010). +Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be +made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any +material in this paper for a fee or for commercial purposes, or modification of the content of the paper are +prohibited. +http://dx.doi.org/10.1117/12.851371"
+2504b7bddd1892bc905fc5df6b5afc0b109ef40e,Function Norms and Regularization in Deep Networks,"Function Norms and Regularization in Deep +Networks +Amal Rannen Triki∗ +KU Leuven, ESAT-PSI, imec, Belgium +Maxim Berman +KU Leuven, ESAT-PSI, imec, Belgium +Matthew B. Blaschko +KU Leuven, ESAT-PSI, imec, Belgium"
25337690fed69033ef1ce6944e5b78c4f06ffb81,Strategic Engagement Regulation: an Integration of Self-enhancement and Engagement,"STRATEGIC ENGAGEMENT REGULATION: AN INTEGRATION OF SELF-ENHANCEMENT AND ENGAGEMENT Jordan B. Leitner @@ -17593,17 +60963,125 @@ fulfillment of the requirements for the degree of Doctor of Philosophy in Psycho Spring 2014 © 2014 Jordan B. Leitner All Rights Reserved"
+25bb4212af72d64ec20cac533f58f7af1472e057,Person Re-Identification by Camera Correlation Aware Feature Augmentation,"Person Re-Identification by Camera +Correlation Aware Feature Augmentation +Ying-Cong Chen, Xiatian Zhu, Wei-Shi Zheng, Jian-Huang Lai +Code is available at the project page: +http://isee.sysu.edu.cn/%7ezhwshi/project/CRAFT.html +For reference of this work, please cite: +Ying-Cong Chen, Xiatian Zhu,Wei-Shi Zheng, and Jian-Huang Lai. Per- +son Re-Identification by Camera Correlation Aware Feature Augmenta- +0.1109/TPAMI.2017.2666805) +title={Person Re-Identification by Camera Correlation Aware Feature Aug- +mentation}, +uthor={Chen, Ying-Cong and Zhu, Xiatian and Zheng, Wei-Shi and Lai, +Jian-Huang}, +(DOI: 10.1109/TPAMI.2017.2666805)}"
+2547607a98eff30654994902f518e30caf2f8271,Synthesizing manipulation sequences for under-specified tasks using unrolled Markov Random Fields,"Synthesizing Manipulation Sequences for Under-Specified Tasks +using Unrolled Markov Random Fields +Jaeyong Sung, Bart Selman and Ashutosh Saxena"
+250449a9827e125d6354f019fc7bc6205c5fd549,Adversarial Reconstruction Loss,"PAIRWISE AUGMENTED GANS WITH +ADVERSARIAL RECONSTRUCTION LOSS +Aibek Alanov1,2,3∗, Max Kochurov1,2∗, Daniil Yashkov5, Dmitry Vetrov1,3,4 +Samsung AI Center in Moscow +Skolkovo Institute of Science and Technology +National Research University Higher School of Economics +Joint Samsung-HSE lab +5Federal Research Center ""Informatics and Management"" of the Russian Academy of Sciences"
+253d2fd2891a97d4caa49d87094dac1ec18c7752,Bio-authentication for Layered Remote Health Monitor Framework,"JOURNAL OF MEDICAL INFORMATICS & TECHNOLOGIES Vol. 23/2014, ISSN 1642-6037 +Remote Health Monitor, Security Issues, +Multi-Factor Biometric Authentication, +Keystroke Analysis, Face Recognition +Tapalina BHATTASALI1, Khalid SAEED2, Nabendu CHAKI1, Rituparna CHAKI3 +BIO-AUTHENTICATION FOR LAYERED REMOTE +HEALTH MONITOR FRAMEWORK +Aged people, patients with chronic disease, patients at remote location need continuous monitoring under +healthcare professionals. Remote health monitor is likely to be an effective approach to provide healthcare service +in a simple and cost effective way. However, effective implementation of this type of framework needs consid- +eration of variety of security threats. In this paper, a layer based remote health monitor framework is proposed +to analyze health condition of patients from remote places. Beside this, a multi-modal biometric authentication +mechanism is proposed here to reduce misuse of health data and biometrics templates in heterogeneous cloud +environment. Main focus of the paper is to design semi-continuous authentication mechanism after establishing +mutual 1:1 trust relationship among the participants in cloud environment. Behavioral biometrics keystroke +nalysis is fused with physiological biometrics face recognition to enhance accuracy of authentication. Instead of +onsidering traditional performance evaluation parameters for biometrics, this paper considers a few performance +metrics for determining efficiency of semi-continuous verification of the proposed framework. +. INTRODUCTION +Remote health monitor provides healthcare service for patients from remote locations to support"
+2562d6ec0044eee9d604fe3a351f80d4d10d4a3d,Conditional Image-Text Embedding Networks,"Conditional Image-Text Embedding Networks +Bryan A. Plummer†, Paige Kordas†, M. Hadi Kiapour‡, Shuai Zheng‡, +Robinson Piramuthu‡, and Svetlana Lazebnik† +University of Illinois at Urbana-Champaign† +Ebay Inc.‡"
25d3e122fec578a14226dc7c007fb1f05ddf97f7,The first facial expression recognition and analysis challenge,"The First Facial Expression Recognition and Analysis Challenge Michel F. Valstar, Bihan Jiang, Marc Mehu, Maja Pantic, and Klaus Scherer"
2597b0dccdf3d89eaffd32e202570b1fbbedd1d6,Towards Predicting the Likeability of Fashion Images,"Towards predicting the likeability of fashion images Jinghua Wang, Abrar Abdul Nabi, Gang Wang, Member, IEEE, Chengde Wan, Tian-Tsong Ng, Member, IEEE,"
+2594bf77a1fef68d86be74a2cb79c55499cb2bec,Learning Invariant Color Features for Person Reidentification,"Learning Invariant Color Features for +Person Re-Identification +Rahul Rama Varior, Student Member, IEEE, +Gang Wang, Member, IEEE Jiwen Lu, Member, IEEE"
+25aa935217a52d83bc1637687a78017984fcb731,The Continuous N-tuple Classiier and Its Application to Face Recognition,"Thecontinuousn-tupleclassi(cid:12)eranditsapplicationto +facerecognition +S.M.Lucas +DepartmentofElectronicSystemsEngineering +UniversityofEssex +ColchesterCOSQ,UK"
+25e62096a44e3fe2f641b492379e7c4babce7ee6,Investigating Gaze of Children with ASD in Naturalistic Settings,"Investigating Gaze of Children with ASD in Naturalistic +Settings +Basilio Noris1*, Jacqueline Nadel2, Mandy Barker3, Nouchine Hadjikhani4, Aude Billard1 +Learning Algorithms and Systems Laboratory, Ecole Polyte´chnique Fe´de´rale de Lausanne, Lausanne, Switzerland, 2 Emotion Centre, Hoˆ pital de La Salpe´trie`re, Paris, +France, 3 Lausanne University Department of Child and Adolescent Psychiatry, University Hospital of Canton de Vaud, Lausanne, Switzerland, 4 Brain and Mind Institute, +Ecole Polyte´chnique Fe´de´rale de Lausanne, Lausanne, Switzerland & Martinos Center for Biomedical Imaging Massachusetts General Hospital/Healthcare Management +Systems/HST, Boston, Massachusetts, United States of America"
25982e2bef817ebde7be5bb80b22a9864b979fb0,Facial Feature Tracking Under Varying Facial Expressions and Face Poses Based on Restricted Boltzmann Machines,"(a)26facialfeaturepointsthatwetrack(b)oneexamplesequenceFigure1.Facialfeaturepointtrackingunderexpressionvariationandocclusion.Inrecentyears,thesemodelshavebeenusedexplicitlytohandletheshapevariations[17][5].Thenonlinearityem-beddedinRBManditsvariantsmakesthemmoreeffectiveandefficienttorepresentthenonrigiddeformationsofob-jectscomparedtothelinearmethods.Theirlargenumberofhiddennodesanddeeparchitecturesalsocanimposesuffi-cientconstraintsaswellasenoughdegreesoffreedomsintotherepresentationsofthetargetobjects.Inthispaper,wepresentaworkthatcaneffectivelytrackfacialfeaturepointsusingfaceshapepriormodelsthatareconstructedbasedonRBM.Thefacialfeaturetrackercantrack26facialfeaturepoints(Fig.1(a))eveniffaceshavedifferentfacialexpressions,varyingposes,orocclu-sion(Fig.1(b)).Unlikethepreviousworksthattrackfacialfeaturepointsindependentlyorbuildashapemodeltocap-turethevariationsoffaceshapeorappearanceregardlessofthefacialexpressionsandfaceposes,theproposedmodelcouldcapturethedistinctionsaswellasthevariationsoffaceshapesduetofacialexpressionandposechangeinaunifiedframework.Specifically,wefirstconstructamodel1"
+251da2569036cebc2ea109972f412c5b1a9db20f,Appearance modeling for person re-identification using Weighted Brightness Transfer Functions,"1st International Conference on Pattern Recognition (ICPR 2012) +November 11-15, 2012. Tsukuba, Japan +978-4-9906441-1-6 ©2012 IAPR"
+25403c52a7c3092866773b0e765ab55841d3cb67,Joint Prediction of Activity Labels and Starting Times in Untrimmed Videos,"Joint Prediction of Activity Labels and Starting Times in Untrimmed Videos +Tahmida Mahmud1, Mahmudul Hasan2, Amit K. Roy-Chowdhury1 +University of California, Riverside, CA-92521, USA +Comcast Labs, Washington, DC-20005, USA"
+25d48ab3b05bf299fe61ed6580674e893f08380b,"Pedestrian Detection: A Survey of Methodologies, Techniques and Current Advancements","International Journal of Scientific Research Engineering & Technology (IJSRET), ISSN 2278 – 0882 +Volume 4, Issue 1, January 2015 +Pedestrian Detection: A Survey of Methodologies, Techniques and Current +Advancements +Tanmay Bhadra1, Joydeep Sonar2 , Arup Sarmah3 ,Chandan Jyoti Kumar4 +Dept. of CSE & IT, School of Technology +Assam Don Bosco University"
25e05a1ea19d5baf5e642c2a43cca19c5cbb60f8,Label Distribution Learning,"Label Distribution Learning Xin Geng*, Member, IEEE"
2559b15f8d4a57694a0a33bdc4ac95c479a3c79a,Contextual Object Localization With Multiple Kernel Nearest Neighbor,"Contextual Object Localization With Multiple Kernel Nearest Neighbor Brian McFee, Student Member, IEEE, Carolina Galleguillos, Student Member, IEEE, and Gert Lanckriet, Member, IEEE"
+259bd09bc382763f864986498e46ab0178714f58,Lifelong Machine Learning,"Lifelong Machine Learning +November, 2016 +Zhiyuan Chen and Bing Liu +Draft : This is mainly an early draft of the book. +We also updated a few places after the publication, highlighted in yellow. +Zhiyuan Chen and Bing Liu. Lifelong Machine Learning. +Morgan & Claypool Publishers, Nov 2016. +LifelongMachineLearningZhiyuan ChenBing Liu"
+257eb6d5ca49eb4ea90658a8668d1853d9c38af7,A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in,"UNIVERSITY OF CALIFORNIA +RIVERSIDE +Wide-Area Video Understanding: Tracking, Video Summarization and +Algorithm-Platform Co-Design +A Dissertation submitted in partial satisfaction +of the requirements for the degree of +Doctor of Philosophy +Electrical Engineering +Shu Zhang +December 2015 +Dissertation Committee: +Dr. Amit K. Roy-Chowdhury, Chairperson +Dr. Qi Zhu +Dr. Ertem Tuncel"
+253cedd3022e25a79bcaffe74e3405db65c6d2ce,Deep Hashing for Scalable Image Search,"Deep Hashing for Scalable Image Search +Jiwen Lu, Senior Member, IEEE, Venice Erin Liong, and Jie Zhou, Senior Member, IEEE"
+25f1a5121cb7fb67749a6f6dbc27fd48f177d5fb,Context-Aware Hypergraph Modeling for Re-identification and Summarization,"Context-Aware Hypergraph Modeling for +Re-identification and Summarization +Santhoshkumar Sunderrajan, Member, IEEE, and B. S. Manjunath, Fellow, IEEE"
25f1f195c0efd84c221b62d1256a8625cb4b450c,Experiments with Facial Expression Recognition using Spatiotemporal Local Binary Patterns,"-4244-1017-7/07/$25.00 ©2007 IEEE ICME 2007"
25885e9292957feb89dcb4a30e77218ffe7b9868,Analyzing the Affect of a Group of People Using Multi-modal Framework,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2016 |